diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download PATCHED Facebook Messenger For Samsung Gt-e2252 Tools Sesiones Speed.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download PATCHED Facebook Messenger For Samsung Gt-e2252 Tools Sesiones Speed.md
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--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download PATCHED Facebook Messenger For Samsung Gt-e2252 Tools Sesiones Speed.md	
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-<h1>How to Download Facebook Messenger for Samsung E2252</h1>
-<p>Facebook Messenger is a popular app that allows you to chat with your friends and family on the social media platform. You can also send text messages, images, videos, stickers, voice notes, and more in free group chats. But how can you download Facebook Messenger for Samsung E2252, a feature phone that runs on a proprietary operating system?</p>
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-<p>In this article, we will show you the steps to download and install Facebook Messenger for Samsung E2252 using a third-party website called Apkpure. Apkpure is a website that offers free APK files of various apps and games for Android devices. APK files are the installation packages that contain all the necessary files and data for an app to run on your device.</p>
-<p>Before we begin, please note that downloading and installing APK files from unknown sources may pose some risks to your device and personal data. You should only download APK files from trusted and verified websites, and scan them with an antivirus software before opening them. We are not responsible for any damage or loss that may occur as a result of following this guide.</p>
-<h2>Steps to Download Facebook Messenger for Samsung E2252</h2>
-<ol>
-<li>On your Samsung E2252, open the browser app and go to <a href="https://apkpure.com/facebook-messenger/com.facebook.orca">https://apkpure.com/facebook-messenger/com.facebook.orca</a>. This is the official page of Facebook Messenger on Apkpure.</li>
-<li>Scroll down and tap on the green "Download APK" button. This will start downloading the APK file of Facebook Messenger to your device.</li>
-<li>Once the download is complete, go to your file manager app and locate the downloaded APK file. It should be in the "Downloads" folder or a similar location.</li>
-<li>Tap on the APK file to open it. You may see a warning message that says "Install blocked" or "For security, your phone is set to block installation of apps obtained from unknown sources". If you see this message, tap on "Settings" and enable the option to allow installation of apps from unknown sources. You may need to enter your password or PIN to confirm this action.</li>
-<li>After enabling the option, go back to the APK file and tap on it again. You should see a screen that shows the app's permissions and information. Tap on "Install" to start installing Facebook Messenger on your device.</li>
-<li>Wait for the installation process to finish. You should see a message that says "App installed" when it is done.</li>
-<li>Tap on "Open" to launch Facebook Messenger on your device. You may need to sign in with your Facebook account or create a new one if you don't have one already.</li>
-</ol>
-<p>Congratulations! You have successfully downloaded and installed Facebook Messenger for Samsung E2252. You can now enjoy chatting with your friends and family on Facebook using this app.</p>
-<p></p><h2>Tips and Tricks for Using Facebook Messenger on Samsung E2252</h2>
-<p>Now that you have Facebook Messenger on your device, you may want to know some tips and tricks to make the most out of it. Here are some of them:</p>
-<ul>
-<li>To access the app's settings, tap on your profile picture in the top left corner of the screen. Here you can change your name, photo, status, notifications, chat colors, emoji, and more.</li>
-<li>To start a new chat, tap on the blue "+" icon in the bottom right corner of the screen. You can search for a contact by name or phone number, or scan a QR code to add them. You can also create a group chat by selecting multiple contacts.</li>
-<li>To send a message, type it in the text box at the bottom of the chat screen and tap on the send icon. You can also send voice notes by tapping and holding the microphone icon, or send photos and videos by tapping on the camera icon. To send stickers, GIFs, or emojis, tap on the smiley icon.</li>
-<li>To make a voice or video call, tap on the phone or video icon in the top right corner of the chat screen. You can also switch between voice and video during a call by tapping on the same icons. To end a call, tap on the red hang up icon.</li>
-<li>To delete a message, tap and hold on it and select "Delete". You can also delete an entire chat by tapping and holding on it in the main screen and selecting "Delete". Note that deleting a message or chat will only remove it from your device, not from the other person's device.</li>
-<li>To archive a chat, swipe left on it in the main screen and select "Archive". This will hide the chat from your main screen but you can still access it by tapping on the search icon and typing the contact's name. To unarchive a chat, swipe left on it in the search screen and select "Unarchive".</li>
-<li>To mute a chat, swipe left on it in the main screen and select "Mute". This will stop receiving notifications from that chat until you unmute it. To unmute a chat, swipe left on it in the main screen and select "Unmute".</li>
-<li>To block a contact, tap on their name or profile picture in the chat screen and select "Block". This will prevent them from sending you messages or calling you. To unblock a contact, tap on their name or profile picture in the chat screen and select "Unblock".</li>
-</ul>
-<p>These are some of the tips and tricks for using Facebook Messenger on Samsung E2252. We hope you find them useful and enjoy using this app.</p> 81aa517590<br />
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Carte Maroc Format Fbl.md b/spaces/1gistliPinn/ChatGPT4/Examples/Carte Maroc Format Fbl.md
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--- a/spaces/1gistliPinn/ChatGPT4/Examples/Carte Maroc Format Fbl.md	
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diff --git a/spaces/1phancelerku/anime-remove-background/City of Angels - The Masterpiece by Thirty Seconds to Mars How to Download MP3.md b/spaces/1phancelerku/anime-remove-background/City of Angels - The Masterpiece by Thirty Seconds to Mars How to Download MP3.md
deleted file mode 100644
index fd0f4a626257d7a2a3688aa1c6e67109b69be02f..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/City of Angels - The Masterpiece by Thirty Seconds to Mars How to Download MP3.md	
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-<h1>City of Angels MP3 Download 30 Seconds to Mars</h1>
-<p>If you are looking for a song that will inspire you, touch your emotions, and make you feel alive, then you should check out City of Angels by 30 Seconds to Mars. This song is one of the most popular and acclaimed tracks by the American rock band, and it has a lot to offer to the listeners. In this article, we will tell you everything you need to know about City of Angels, and how you can download it as an MP3 file for your convenience.</p>
- <h2>What is City of Angels by 30 Seconds to Mars?</h2>
-<p>City of Angels is a song by 30 Seconds to Mars, released in 2013 as the fourth single from their fourth studio album, Love Lust Faith + Dreams. The song was written and produced by the lead vocalist and founder of the band, Jared Leto, who also directed the music video and the short film based on the song.</p>
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- <h3>The meaning and inspiration behind the song</h3>
-<p>City of Angels is a tribute to Los Angeles, the city where 30 Seconds to Mars was formed and where they achieved their success. The song explores the themes of dreams, hopes, struggles, and realities that people face in the city, as well as the beauty and diversity that it offers. Jared Leto said that he wanted to capture the spirit and essence of Los Angeles in the song, and that he was inspired by his own personal experiences and stories from other people who live or have lived in the city.</p>
- <h3>The music video and the short film</h3>
-<p>The music video for City of Angels was released in October 2013, and it features a series of interviews with various celebrities, artists, musicians, athletes, and ordinary people who share their thoughts and feelings about Los Angeles. Some of the famous faces that appear in the video include Kanye West, James Franco, Selena Gomez, Lindsay Lohan, Olivia Wilde, Steve Nash, Corey Feldman, Ashley Olsen, Alan Cumming, Juliette Lewis, Shaun White, Lily Collins, and many more. The video also shows scenes of the band performing the song in different locations around the city.</p>
-<p>The short film for City of Angels was released in November 2013, and it is an extended version of the music video that runs for about 11 minutes. The short film includes more interviews and footage that were not shown in the music video, as well as some additional narration by Jared Leto. The short film was praised by critics and fans alike for its artistic vision and emotional impact.</p>
- <h2>How to download City of Angels MP3 by 30 Seconds to Mars?</h2>
-<p>If you want to enjoy City of Angels by 30 Seconds to Mars anytime and anywhere, you might want to download it as an MP3 file that you can store on your device or transfer to other devices. There are several ways you can do this, depending on your preferences and budget.</p>
- <h3>The official sources and platforms</h3>
-<p>The most recommended way to download City of Angels MP3 by 30 Seconds to Mars is to use the official sources and platforms that are authorized by the band and their record label. This way, you can support the band financially and legally, as well as get the best quality and security for your download. Some of the official sources and platforms that you can use are:</p>
-<ul>
-<li>iTunes: You can buy City of Angels as a single track or as part of the Love Lust Faith + Dreams album on iTunes for $1.29 or $9.99 respectively. You can also stream it on Apple Music if you have a subscription.</li>
-<li>Amazon: You <li>Amazon: You can buy City of Angels as a single track or as part of the Love Lust Faith + Dreams album on Amazon for $1.29 or $9.99 respectively. You can also stream it on Amazon Music if you have a subscription.</li>
-<li>Spotify: You can stream City of Angels on Spotify if you have a subscription, or listen to it with ads if you use the free version. You can also download it for offline listening if you have a premium account.</li>
-<li>YouTube: You can watch the music video or the short film for City of Angels on YouTube for free, or buy the song as an MP3 file for $1.29 on YouTube Music.</li>
-</ul>
- <h3>The alternative methods and tools</h3>
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-<ul>
-<li>Online converters: You can use some online converters that allow you to convert YouTube videos or other online audio files into MP3 files that you can download. Some examples of these online converters are YTMP3, MP3FY, and OnlineVideoConverter. You just need to copy and paste the URL of the video or audio file that you want to convert, choose the output format and quality, and click on the download button.</li>
-<li>Desktop software: You can use some desktop software that allow you to download YouTube videos or other online audio files as MP3 files. Some examples of these desktop software are 4K Video Downloader, Freemake Video Downloader, and Any Video Converter. You just need to install the software on your computer, copy and paste the URL of the video or audio file that you want to download, choose the output format and quality, and click on the download button.</li>
-<li>Mobile apps: You can use some mobile apps that allow you to download YouTube videos or other online audio files as MP3 files. Some examples of these mobile apps are TubeMate, VidMate, and SnapTube. You just need to install the app on your smartphone or tablet, search for the video or audio file that you want to download, choose the output format and quality, and click on the download button.</li>
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-<p>Listening to music can have many positive effects on your physical, mental, and emotional well-being. Some of the benefits of listening to music are:</p>
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-<ul>
-<li>It can reduce stress and anxiety by lowering your blood pressure, heart rate, and cortisol levels.</li>
-<li>It can improve your mood and happiness by releasing dopamine, serotonin, and oxytocin in your brain.</li>
-<li>It can enhance your memory and cognition by stimulating your hippocampus and prefrontal cortex.</li>
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- <h3>The reasons why City of Angels is a great song</h3>
-<p>Besides the general benefits of listening to music, City of Angels by 30 Seconds to Mars has some specific qualities that make it a great song to listen to. Some of the reasons why City of Angels is a great song are:</p>
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-<li>It has a powerful and uplifting message that encourages you to follow your dreams and overcome your challenges.</li>
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-<li>It has a passionate and expressive performance by Jared Leto and his bandmates.</li>
-<li>It has a stunning and inspiring visual representation by the music video and the short film.</li>
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-<p>In conclusion, City of Angels by 30 Seconds to Mars is a song <p>In conclusion, City of Angels by 30 Seconds to Mars is a song that you should definitely listen to and download as an MP3 file. It is a song that celebrates Los Angeles, the city of dreams, and the people who live or have lived there. It is a song that has a beautiful and meaningful message, a catchy and melodic tune, a rich and diverse sound, a passionate and expressive performance, and a stunning and inspiring visual representation. It is a song that can make you feel inspired, touched, and alive.</p>
-<p>If you want to download City of Angels MP3 by 30 Seconds to Mars, you can use the official sources and platforms that are authorized by the band and their record label, such as iTunes, Amazon, Spotify, YouTube, or YouTube Music. Alternatively, you can use some online converters, desktop software, or mobile apps that can convert YouTube videos or other online audio files into MP3 files. However, you should be careful about the quality and security of your download, and respect the rights of the band and their record label.</p>
-<p>So what are you waiting for? Go ahead and download City of Angels MP3 by 30 Seconds to Mars today, and enjoy this amazing song that will make you feel like you are in the city of angels.</p>
- <h3>FAQs</h3>
-<ul>
-<li>Q: Who are 30 Seconds to Mars?<br>
-A: 30 Seconds to Mars is an American rock band that was formed in Los Angeles in 1998 by Jared Leto and his brother Shannon Leto. The band currently consists of Jared Leto (lead vocals, guitar, keyboards), Shannon Leto (drums, percussion), and Tomo Miličević (lead guitar, keyboards). The band has released five studio albums, four EPs, and 16 singles.</li>
-<li>Q: What is the genre of City of Angels?<br>
-A: City of Angels is a song that belongs to the genre of alternative rock, with elements of pop rock, electronic rock, orchestral rock, and choir music.</li>
-<li>Q: How long is City of Angels?<br>
-A: City of Angels is a song that has a duration of 5 minutes and 2 seconds. The music video has a duration of 4 minutes and 54 seconds. The short film has a duration of 11 minutes and 13 seconds.</li>
-<li>Q: How many awards did City of Angels win?<br>
-A: City of Angels won several awards for its music video and short film, such as the MTV Video Music Award for Best Rock Video in 2014, the iHeartRadio Music Award for Alternative Rock Song of the Year in 2014, the Kerrang! Award for Best Single in 2014, the MTV Europe Music Award for Best Video in 2014, and the Berlin Music Video Award for Best Cinematography in 2015.</li>
-<li>Q: Where can I watch the music video or the short film for City of Angels?<br>
-A: You can watch the music video or the short film for City of Angels on YouTube. You can also find them on the official website of 30 Seconds to Mars or on their social media accounts.</li>
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diff --git a/spaces/1phancelerku/anime-remove-background/Download dan Nonton Film Ashfall (2019) Sub Indo Full Movie HD.md b/spaces/1phancelerku/anime-remove-background/Download dan Nonton Film Ashfall (2019) Sub Indo Full Movie HD.md
deleted file mode 100644
index 88078297a4c7c4298aefb2b31263338b28d00c78..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download dan Nonton Film Ashfall (2019) Sub Indo Full Movie HD.md	
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-<h1>Download Film Ashfall Full Movie Sub Indo: A Review of the Epic Disaster Film</h1>
-<p>If you are a fan of action-packed disaster movies, you might have heard of Ashfall, a 2019 South Korean film that depicts the aftermath of a volcanic eruption on the Korean peninsula. But how can you watch this film online with Indonesian subtitles? And is it worth your time and money? In this article, I will give you a brief overview of what Ashfall is about, how to download film ashfall full movie sub indo legally and safely, and my personal opinion on whether you should watch it or not.</p>
- <h2>What is Ashfall?</h2>
-<p>Ashfall (Korean: 백두산; Hanja: 白頭山; RR: Baekdusan), also known as Mount Paektu, is a 2019 South Korean disaster film directed by Lee Hae-jun and Kim Byung-seo, starring Lee Byung-hun, Ha Jung-woo, Ma Dong-seok, Jeon Hye-jin and Bae Suzy. The film was released in December 2019 in South Korea and became one of the highest-grossing films of the year.</p>
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-<p>The film follows the events that unfold when Paektu Mountain, an active volcano straddling the China–North Korea border, suddenly erupts, causing severe earthquakes in both North and South Korea. To prevent another disaster, Jeon Yoo-kyung (Jeon Hye-jin), a government official, plans an operation based on a theory by Professor Kang Bong-rae (Ma Dong-seok), who had studied Mount Paektu and its possible future eruptions. Jo In-chang (Ha Jung-woo) is assigned to be the captain of a special forces team taking part in the operation. He contacts Lee Joon-pyeong (Lee Byung-hun), who is part of the Korean People's Army in North Korea as a spy. Joon-pyeong is the only one who knows where to find nuclear warheads that can be used to stop the volcano from erupting again. Meanwhile, Jo In-chang's pregnant wife Choi Ji-young (Bae Suzy) is alone in Seoul and struggling to survive amidst the chaos.</p>
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-<p>The film features a star-studded cast of some of the most popular actors and actresses in South Korea. Here are some of the main characters and their roles:</p>
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-<li>Lee Byung-hun as Lee Joon-pyeong: A North Korean spy who holds the key to stopping the volcano. He is also a father who wants to reunite with his daughter.</li>
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-<li>Jeon Hye-jin as Jeon Yoo-kyung: A government official who is in charge of the operation to stop the volcano. She is also a former colleague and lover of Joon-pyeong.</li>
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-<p>One of the most impressive aspects of Ashfall is the realistic and spectacular depiction of the volcanic eruption and its consequences. The film used a combination of practical and computer-generated effects to create the scenes of destruction, chaos, and panic. The film also employed various techniques such as aerial shots, drone shots, handheld shots, and slow-motion shots to capture the scale and intensity of the disaster. The film's cinematography was praised by critics and audiences alike for its stunning visuals and immersive experience.</p>
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-<p>If you are interested in watching Ashfall with Indonesian subtitles, you might be wondering how to download film ashfall full movie sub indo online. There are two main ways to do this: legal and safe ways, and illegal and risky ways. Let's take a look at each option and weigh their pros and cons.</p>
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-<p>The best way to watch Ashfall online is to use legal and safe streaming services that offer the film with Indonesian subtitles. This way, you can enjoy the film without worrying about breaking the law, harming your device, or compromising your personal information. Here are some of the streaming services that offer Ashfall:</p>
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-<tr><td>Netflix</td><td>$8.99-$17.99 per month</td><td>Worldwide (except China, Syria, North Korea, and Crimea)</td></tr>
-<tr><td>iQIYI</td><td>$2.99-$19.99 per month</td><td>Asia-Pacific (except Japan)</td></tr>
-<tr><td>Viu</td><td>$2.99-$6.99 per month</td><td>Asia-Pacific (except China)</td></tr>
-<tr><td>Iflix</td><td>$0-$9.99 per month</td><td>Asia-Pacific (except China, Japan, Taiwan, Hong Kong, Macau)</td></tr>
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-<p>If you already have access to Ashfall through a streaming service or a DVD, but you need Indonesian subtitles, you can also download them from websites that provide subtitles for various languages. However, you should be careful when downloading subtitles from unknown sources, as they might contain malware or viruses that can harm your device or steal your data. Here are some of the websites that provide Ashfall subtitles:</p>
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-<p>Torrent sites are websites that allow users to share files through peer-to-peer networks. Some of the torrent sites that host Ashfall files are:</p> <ul>
-<li>[The Pirate Bay]: One of the most popular and notorious torrent sites in the world, known for hosting a variety of content, including movies, TV shows, music, games, software, and more.</li>
-<li>[1337x]: A torrent site that offers a wide range of content, including movies, TV shows, music, games, software, and more.</li>
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-<li>Security issues: Torrent sites often contain malware or viruses that can infect your device or steal your personal information. You might also expose your IP address and location to hackers or cybercriminals.</li>
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-</ul>
- <h2>Conclusion: Is Ashfall Worth Watching?</h2>
-<p>Now that you know what Ashfall is about and how to download film ashfall full movie sub indo online, you might be wondering if it is worth watching. To help you decide, here are some of the pros and cons of Ashfall:</p>
- <h3>The Pros and Cons of Ashfall</h3>
-<table>
-<tr><th>Pros</th><th>Cons</th></tr>
-<tr><td>A thrilling and exciting disaster film with realistic and spectacular special effects and cinematography.</td><td>A clichéd and predictable plot with some logical flaws and inconsistencies.</td></tr>
-<tr><td>A star-studded cast with impressive performances and chemistry.</td><td>A lack of character development and depth for some of the main characters.</td></tr>
-<tr><td>A message of hope and unity in the face of adversity and conflict.</td><td>A simplistic and idealistic portrayal of the political and social situation on the Korean peninsula.</td></tr>
-<tr><td>A cultural and commercial success that showcases the potential of the South Korean film industry.</td><td>A limited availability and accessibility for international audiences who might not be familiar with the context or language of the film.</td></tr>
-</table>
- <h3>My Personal Opinion on Ashfall</h3>
-<p>In my personal opinion, Ashfall is a film that is worth watching if you are a fan of disaster movies or Korean cinema. It is a film that delivers on its promise of providing an entertaining and thrilling experience with stunning visuals and sound. It is also a film that has a heart and a message that resonates with the current times. However, it is not a film that is perfect or flawless. It has its share of weaknesses and shortcomings that might disappoint some viewers who expect more from it. It is also not a film that is easy to watch or understand for everyone. It requires some background knowledge and appreciation of the culture and history of Korea. Therefore, I would recommend Ashfall to anyone who is looking for a fun and exciting movie night, but not to anyone who is looking for a deep and meaningful cinematic masterpiece.</p>
- <h2>Frequently Asked Questions</h2>
-<p>Here are some of the frequently asked questions about Ashfall:</p>
- <h4>Q: Is Ashfall based on a true story?</h4>
-<p>A: No, Ashfall is not based on a true story. It is a fictional story that imagines what would happen if Mount Paektu erupted in the present day. However, Mount Paektu is a real volcano that has erupted in the past and could erupt again in the future. The film was inspired by the historical and scientific research on Mount Paektu and its potential eruptions.</p>
- <h4>Q: How accurate is Ashfall?</h4>
-<p>A: Ashfall is not meant to be a realistic or accurate depiction of a volcanic eruption or its consequences. It is a fictional story that exaggerates and dramatizes some aspects of the disaster for entertainment purposes. The film does not follow the scientific facts or data on Mount Paektu or its eruptions. The film also does not reflect the actual political or social situation on the Korean peninsula or its relations with other countries.</p>
- <h4>Q: How Q: How did Ashfall perform at the box office?</h4>
-<p>A: Ashfall was a commercial success at the box office, both domestically and internationally. It grossed over $61 million in South Korea, becoming the fourth highest-grossing film of 2019 and the 11th highest-grossing film of all time in the country. It also grossed over $24 million in other countries, mainly in Asia, bringing its worldwide total to over $85 million. It was also nominated for several awards, including the Baeksang Arts Awards, the Blue Dragon Film Awards, and the Grand Bell Awards.</p>
- <h4>Q: Where can I find more information about Ashfall?</h4>
-<p>A: If you want to learn more about Ashfall, you can visit the following websites:</p>
-<ul>
-<li>[Ashfall Official Website]: The official website of the film, where you can find the trailer, synopsis, cast and crew information, gallery, and more.</li>
-<li>[Ashfall IMDb Page]: The IMDb page of the film, where you can find the ratings, reviews, trivia, quotes, and more.</li>
-<li>[Ashfall Wikipedia Page]: The Wikipedia page of the film, where you can find the plot summary, production details, reception, and more.</li>
-</ul>
- <h4>Q: What are some other films like Ashfall?</h4>
-<p>A: If you enjoyed Ashfall and want to watch more films like it, you might like these films:</p>
-<ul>
-<li>[2012]: A 2009 American disaster film directed by Roland Emmerich, starring John Cusack, Chiwetel Ejiofor, Amanda Peet, Thandie Newton, and Danny Glover. The film depicts a series of cataclysmic events that occur in 2012 as a result of a massive solar flare that causes the Earth's crust to shift.</li>
-<li>[The Day After Tomorrow]: A 2004 American disaster film directed by Roland Emmerich, starring Dennis Quaid, Jake Gyllenhaal, Emmy Rossum, Ian Holm, and Sela Ward. The film depicts a global climate change that triggers a new ice age and forces a group of survivors to cope with the harsh conditions.</li>
-<li>[Train to Busan]: A 2016 South Korean zombie apocalypse film directed by Yeon Sang-ho, starring Gong Yoo, Ma Dong-seok, Jung Yu-mi, Kim Su-an, Kim Eui-sung, Choi Woo-shik, and Ahn So-hee. The film follows a group of passengers on a train from Seoul to Busan as they try to survive a zombie outbreak that spreads across the country.</li>
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diff --git a/spaces/801artistry/RVC801/demucs/augment.py b/spaces/801artistry/RVC801/demucs/augment.py
deleted file mode 100644
index bb36d3298d89470f306316322e7587187819c94b..0000000000000000000000000000000000000000
--- a/spaces/801artistry/RVC801/demucs/augment.py
+++ /dev/null
@@ -1,106 +0,0 @@
-# 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.
-
-import random
-import torch as th
-from torch import nn
-
-
-class Shift(nn.Module):
-    """
-    Randomly shift audio in time by up to `shift` samples.
-    """
-    def __init__(self, shift=8192):
-        super().__init__()
-        self.shift = shift
-
-    def forward(self, wav):
-        batch, sources, channels, time = wav.size()
-        length = time - self.shift
-        if self.shift > 0:
-            if not self.training:
-                wav = wav[..., :length]
-            else:
-                offsets = th.randint(self.shift, [batch, sources, 1, 1], device=wav.device)
-                offsets = offsets.expand(-1, -1, channels, -1)
-                indexes = th.arange(length, device=wav.device)
-                wav = wav.gather(3, indexes + offsets)
-        return wav
-
-
-class FlipChannels(nn.Module):
-    """
-    Flip left-right channels.
-    """
-    def forward(self, wav):
-        batch, sources, channels, time = wav.size()
-        if self.training and wav.size(2) == 2:
-            left = th.randint(2, (batch, sources, 1, 1), device=wav.device)
-            left = left.expand(-1, -1, -1, time)
-            right = 1 - left
-            wav = th.cat([wav.gather(2, left), wav.gather(2, right)], dim=2)
-        return wav
-
-
-class FlipSign(nn.Module):
-    """
-    Random sign flip.
-    """
-    def forward(self, wav):
-        batch, sources, channels, time = wav.size()
-        if self.training:
-            signs = th.randint(2, (batch, sources, 1, 1), device=wav.device, dtype=th.float32)
-            wav = wav * (2 * signs - 1)
-        return wav
-
-
-class Remix(nn.Module):
-    """
-    Shuffle sources to make new mixes.
-    """
-    def __init__(self, group_size=4):
-        """
-        Shuffle sources within one batch.
-        Each batch is divided into groups of size `group_size` and shuffling is done within
-        each group separatly. This allow to keep the same probability distribution no matter
-        the number of GPUs. Without this grouping, using more GPUs would lead to a higher
-        probability of keeping two sources from the same track together which can impact
-        performance.
-        """
-        super().__init__()
-        self.group_size = group_size
-
-    def forward(self, wav):
-        batch, streams, channels, time = wav.size()
-        device = wav.device
-
-        if self.training:
-            group_size = self.group_size or batch
-            if batch % group_size != 0:
-                raise ValueError(f"Batch size {batch} must be divisible by group size {group_size}")
-            groups = batch // group_size
-            wav = wav.view(groups, group_size, streams, channels, time)
-            permutations = th.argsort(th.rand(groups, group_size, streams, 1, 1, device=device),
-                                      dim=1)
-            wav = wav.gather(1, permutations.expand(-1, -1, -1, channels, time))
-            wav = wav.view(batch, streams, channels, time)
-        return wav
-
-
-class Scale(nn.Module):
-    def __init__(self, proba=1., min=0.25, max=1.25):
-        super().__init__()
-        self.proba = proba
-        self.min = min
-        self.max = max
-
-    def forward(self, wav):
-        batch, streams, channels, time = wav.size()
-        device = wav.device
-        if self.training and random.random() < self.proba:
-            scales = th.empty(batch, streams, 1, 1, device=device).uniform_(self.min, self.max)
-            wav *= scales
-        return wav
diff --git a/spaces/A00001/bingothoo/tests/kblob.ts b/spaces/A00001/bingothoo/tests/kblob.ts
deleted file mode 100644
index 9e15b41c1c94a690beb61b23cdb42fc78767ccd2..0000000000000000000000000000000000000000
--- a/spaces/A00001/bingothoo/tests/kblob.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import FormData from 'form-data'
-
-import { fetch } from '@/lib/isomorphic'
-
-const formData = new FormData()
-
-const knowledgeRequest = {"imageInfo":{"url":"https://www.baidu.com/img/PCfb_5bf082d29588c07f842ccde3f97243ea.png"},"knowledgeRequest":{"invokedSkills":["ImageById"],"subscriptionId":"Bing.Chat.Multimodal","invokedSkillsRequestData":{"enableFaceBlur":true},"convoData":{"convoid":"51D|BingProdUnAuthenticatedUsers|E3DCA904FF236C67C3450163BCEC64CFF3F618CC8A4AFD75FD518F5ED0ADA080","convotone":"Creative"}}}
-
-formData.append('knowledgeRequest', JSON.stringify(knowledgeRequest))
-
-
-fetch('https://bing.vcanbb.top/images/kblob',
-  {
-    method: 'POST',
-    body: formData.getBuffer(),
-    headers: {
-      "sec-ch-ua": "\"Not/A)Brand\";v=\"99\", \"Google Chrome\";v=\"115\", \"Chromium\";v=\"115\"",
-      "sec-ch-ua-mobile": "?0",
-      "sec-ch-ua-platform": "\"Windows\"",
-      "Referer": "https://bing.vcanbb.top/web/index.html",
-      "Referrer-Policy": "origin-when-cross-origin",
-      ...formData.getHeaders()
-    }
-
-  }
-).then(res => res.text())
-.then(res => console.log('res', res))
diff --git a/spaces/AAYUSH27/Neuro/app.py b/spaces/AAYUSH27/Neuro/app.py
deleted file mode 100644
index d5e99d5ee95267d23a7307e70b2c04e76dc99e0a..0000000000000000000000000000000000000000
--- a/spaces/AAYUSH27/Neuro/app.py
+++ /dev/null
@@ -1,98 +0,0 @@
-import streamlit as st
-from streamlit_chat import message
-from langchain.chains import ConversationalRetrievalChain
-from langchain.document_loaders import PyPDFLoader, DirectoryLoader
-from langchain.embeddings import HuggingFaceEmbeddings
-from langchain.llms import CTransformers
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.vectorstores import FAISS
-from langchain.memory import ConversationBufferMemory
-
-# load the pdf files from the path
-loader = DirectoryLoader("data/", glob="*.pdf", loader_cls=PyPDFLoader)
-documents = loader.load()
-
-# split text into chunks
-text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
-text_chunks = text_splitter.split_documents(documents)
-
-# create embeddings
-embeddings = HuggingFaceEmbeddings(
-    model_name="sentence-transformers/all-MiniLM-L6-v2", model_kwargs={"device": "cpu"}
-)
-
-# vectorstore
-vector_store = FAISS.from_documents(text_chunks, embeddings)
-
-# create llm
-llm = CTransformers(
-    model="llama-2-7b-chat.ggmlv3.q4_0.bin",
-    model_type="llama",
-    config={"max_new_tokens": 128, "temperature": 0.01},
-)
-
-memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
-
-chain = ConversationalRetrievalChain.from_llm(
-    llm=llm,
-    chain_type="stuff",
-    retriever=vector_store.as_retriever(search_kwargs={"k": 2}),
-    memory=memory,
-)
-
-st.title("Neuro Health-Care Chat Bot")
-
-
-def conversation_chat(query):
-    result = chain({"question": query, "chat_history": st.session_state["history"]})
-    st.session_state["history"].append((query, result["answer"]))
-    return result["answer"]
-
-
-def initialize_session_state():
-    if "history" not in st.session_state:
-        st.session_state["history"] = []
-
-    if "generated" not in st.session_state:
-        st.session_state["generated"] = ["Hello! Ask me anything about Neuro"]
-
-    if "past" not in st.session_state:
-        st.session_state["past"] = ["Hello!"]
-
-
-def display_chat_history():
-    reply_container = st.container()
-    container = st.container()
-
-    with container:
-        with st.form(key="my_form", clear_on_submit=True):
-            user_input = st.text_input(
-                "Question:", placeholder="Ask anything about Neuro", key="input"
-            )
-            submit_button = st.form_submit_button(label="Send")
-
-        if submit_button and user_input:
-            output = conversation_chat(user_input)
-
-            st.session_state["past"].append(user_input)
-            st.session_state["generated"].append(output)
-
-    if st.session_state["generated"]:
-        with reply_container:
-            for i in range(len(st.session_state["generated"])):
-                message(
-                    st.session_state["past"][i],
-                    is_user=True,
-                    key=str(i) + "_user",
-                    avatar_style="person",
-                )
-
-                message(
-                    st.session_state["generated"][i],
-                    key=str(i),
-                    logo="https://img.icons8.com/?size=96&id=19625&format=png",
-                )
-# Initialize session state
-initialize_session_state()
-# Display chat history
-display_chat_history()
diff --git a/spaces/AFRAC/NCM_DEMO/README.md b/spaces/AFRAC/NCM_DEMO/README.md
deleted file mode 100644
index 851142e2a11c5e1b4bdf3aaf9c1faf5a78e08e89..0000000000000000000000000000000000000000
--- a/spaces/AFRAC/NCM_DEMO/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: NCM DEMO
-emoji: 🧾
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 3.35.2
-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/AIConsultant/MusicGen/audiocraft/modules/transformer.py b/spaces/AIConsultant/MusicGen/audiocraft/modules/transformer.py
deleted file mode 100644
index 048c06dfbb0ab4167afce95dffb73dcc343c2344..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/audiocraft/modules/transformer.py
+++ /dev/null
@@ -1,747 +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.
-
-"""
-Transformer model, with streaming support, xformer attention support
-and easy causal attention with a potentially finite receptive field.
-
-See `StreamingTransformer` for more information.
-
-Unlike regular PyTorch Transformer, we make the hard choice that batches are first.
-"""
-
-import typing as tp
-
-from einops import rearrange
-import torch
-import torch.nn as nn
-from torch.nn import functional as F
-from torch.utils.checkpoint import checkpoint as torch_checkpoint
-from xformers import ops
-
-from .rope import RotaryEmbedding
-from .streaming import StreamingModule
-
-_efficient_attention_backend: str = 'torch'
-
-
-def set_efficient_attention_backend(backend: str = 'torch'):
-    # Using torch by default, it seems a bit faster on older P100 GPUs (~20% faster).
-    global _efficient_attention_backend
-    assert _efficient_attention_backend in ['xformers', 'torch']
-    _efficient_attention_backend = backend
-
-
-def _get_attention_time_dimension() -> int:
-    if _efficient_attention_backend == 'torch':
-        return 2
-    else:
-        return 1
-
-
-def _is_profiled() -> bool:
-    # Return true if we are currently running with a xformers profiler activated.
-    try:
-        from xformers.profiler import profiler
-    except ImportError:
-        return False
-    return profiler._Profiler._CURRENT_PROFILER is not None
-
-
-def create_norm_fn(norm_type: str, dim: int, **kwargs) -> nn.Module:
-    """Create normalization module for transformer encoder layer.
-
-    Args:
-        norm_type (str): Normalization method.
-        dim (int): Dimension of the normalized layer.
-        **kwargs (dict): Additional parameters for normalization layer.
-    Returns:
-        nn.Module: Normalization module.
-    """
-    if norm_type == 'layer_norm':
-        return nn.LayerNorm(dim, eps=1e-5, **kwargs)
-    else:
-        raise ValueError(f"Unknown norm type: {norm_type}")
-
-
-def create_sin_embedding(positions: torch.Tensor, dim: int, max_period: float = 10000,
-                         dtype: torch.dtype = torch.float32) -> torch.Tensor:
-    """Create sinusoidal positional embedding, with shape `[B, T, C]`.
-
-    Args:
-        positions (torch.Tensor): LongTensor of positions.
-        dim (int): Dimension of the embedding.
-        max_period (float): Maximum period of the cosine/sine functions.
-        dtype (torch.dtype or str): dtype to use to generate the embedding.
-    Returns:
-        torch.Tensor: Sinusoidal positional embedding.
-    """
-    # We aim for BTC format
-    assert dim % 2 == 0
-    half_dim = dim // 2
-    positions = positions.to(dtype)
-    adim = torch.arange(half_dim, device=positions.device, dtype=dtype).view(1, 1, -1)
-    max_period_tensor = torch.full([], max_period, device=positions.device, dtype=dtype)  # avoid sync point
-    phase = positions / (max_period_tensor ** (adim / (half_dim - 1)))
-    return torch.cat([torch.cos(phase), torch.sin(phase)], dim=-1)
-
-
-def expand_repeated_kv(x: torch.Tensor, n_rep: int) -> torch.Tensor:
-    """torch.repeat_interleave(x, dim=2, repeats=n_rep) from xlformers."""
-    if n_rep == 1:
-        return x
-    if _efficient_attention_backend == 'torch':
-        bs, n_kv_heads, slen, head_dim = x.shape
-        return (
-            x[:, :, None, :, :]
-            .expand(bs, n_kv_heads, n_rep, slen, head_dim)
-            .reshape(bs, n_kv_heads * n_rep, slen, head_dim)
-        )
-    else:
-        bs, slen, n_kv_heads, head_dim = x.shape
-        return (
-            x[:, :, :, None, :]
-            .expand(bs, slen, n_kv_heads, n_rep, head_dim)
-            .reshape(bs, slen, n_kv_heads * n_rep, head_dim)
-        )
-
-
-class LayerScale(nn.Module):
-    """Layer scale from [Touvron et al 2021] (https://arxiv.org/pdf/2103.17239.pdf).
-    This rescales diagonally the residual outputs close to 0, with a learnt scale.
-
-    Args:
-        channels (int): Number of channels.
-        init (float): Initial scale.
-        channel_last (bool): If True, expect `[*, C]` shaped tensors, otherwise, `[*, C, T]`.
-        device (torch.device or str, optional): Device on which to initialize the module.
-        dtype (torch.dtype, optional): dtype to use to initialize the module.
-    """
-    def __init__(self, channels: int, init: float = 1e-4, channel_last: bool = True,
-                 device=None, dtype=None):
-        super().__init__()
-        self.channel_last = channel_last
-        self.scale = nn.Parameter(
-            torch.full((channels,), init,
-                       requires_grad=True, device=device, dtype=dtype))
-
-    def forward(self, x: torch.Tensor):
-        if self.channel_last:
-            return self.scale * x
-        else:
-            return self.scale[:, None] * x
-
-
-class StreamingMultiheadAttention(StreamingModule):
-    """Similar to `nn.MultiheadAttention` but with support for streaming, causal evaluation.
-
-    Args:
-        embed_dim (int): Dimension to project to.
-        num_heads (int): Number of heads.
-        dropout (float): Dropout level.
-        bias (bool): Use bias in projections.
-        causal (bool): Causal mask applied automatically.
-        past_context (int, optional): Receptive field for the causal mask, infinite if None.
-        custom (bool): Use custom MHA implementation, for testing / benchmarking.
-        memory_efficient (bool): Use xformers based memory efficient attention.
-        attention_as_float32 (bool): Perform the attention as float32
-            (especially important with memory_efficient as autocast won't do this automatically).
-        rope (`RotaryEmbedding`, optional): Rope embedding to use.
-        cross_attention: Should be true when used as a cross attention.
-            All keys and values must be available at once, streaming is only for the queries.
-            Cannot be used with `causal` or `rope` (as it wouldn't make sens to
-            interpret the time steps in the keys relative to those in the queries).
-        safe_streaming (bool): Bug fix, will go away with xformers update.
-        qk_layer_norm (bool): Layer normalization applied to queries and keys before dot product.
-        kv_repeat (int): If > 1, will repeat keys and queries multiple times (need to divide num_heads).
-            This will lead to faster decoding time on A100 or other GPUs with tensorcore.
-        device (torch.device, optional): Device on which to initialize.
-        dtype (torch.dtype, optional): dtype to use.
-    """
-    def __init__(self, embed_dim: int, num_heads: int, dropout: float = 0.0, bias: bool = True,
-                 causal: bool = False, past_context: tp.Optional[int] = None, custom: bool = False,
-                 memory_efficient: bool = False, attention_as_float32: bool = False,
-                 rope: tp.Optional[RotaryEmbedding] = None, cross_attention: bool = False,
-                 safe_streaming: bool = True, qk_layer_norm: bool = False, kv_repeat: int = 1,
-                 device=None, dtype=None):
-        super().__init__()
-        factory_kwargs = {'device': device, 'dtype': dtype}
-        if past_context is not None:
-            assert causal
-
-        self.embed_dim = embed_dim
-        self.causal = causal
-        self.past_context = past_context
-        self.memory_efficient = memory_efficient
-        self.attention_as_float32 = attention_as_float32
-        self.rope = rope
-        self.cross_attention = cross_attention
-        self.safe_streaming = safe_streaming
-        self.num_heads = num_heads
-        self.dropout = dropout
-        self.kv_repeat = kv_repeat
-        if cross_attention:
-            assert not causal, "Causal cannot work with cross attention."
-            assert rope is None, "Rope cannot work with cross attention."
-
-        if memory_efficient:
-            _verify_xformers_memory_efficient_compat()
-
-        self.custom = _is_custom(custom, memory_efficient)
-        if self.custom:
-            out_dim = embed_dim
-            assert num_heads % kv_repeat == 0
-            assert not cross_attention or kv_repeat == 1
-            num_kv = num_heads // kv_repeat
-            kv_dim = (embed_dim // num_heads) * num_kv
-            out_dim += 2 * kv_dim
-            in_proj = nn.Linear(embed_dim, out_dim, bias=bias, **factory_kwargs)
-            # We try to follow the default PyTorch MHA convention, to easily compare results.
-            self.in_proj_weight = in_proj.weight
-            self.in_proj_bias = in_proj.bias
-            if bias:
-                self.in_proj_bias.data.zero_()  # Following Pytorch convention
-            self.out_proj = nn.Linear(embed_dim, embed_dim, bias=bias, **factory_kwargs)
-            if bias:
-                self.out_proj.bias.data.zero_()
-        else:
-            assert not qk_layer_norm
-            assert kv_repeat == 1
-            self.mha = nn.MultiheadAttention(
-                embed_dim, num_heads, dropout=dropout, bias=bias, batch_first=True,
-                **factory_kwargs)
-        self.qk_layer_norm = qk_layer_norm
-        if qk_layer_norm:
-            assert self.custom
-            assert kv_repeat == 1
-            ln_dim = embed_dim
-            self.q_layer_norm = nn.LayerNorm(ln_dim)
-            self.k_layer_norm = nn.LayerNorm(ln_dim)
-
-    def _load_from_state_dict(self, state_dict, prefix, *args, **kwargs):
-        if not self.custom:
-            # Support compat with regular MHA
-            keys = [n for n, _ in self.mha.named_parameters()]
-            for key in keys:
-                if prefix + key in state_dict:
-                    state_dict[prefix + "mha." + key] = state_dict.pop(prefix + key)
-        super()._load_from_state_dict(state_dict, prefix, *args, **kwargs)
-
-    def _get_mask(self, current_steps: int, device: torch.device, dtype: torch.dtype):
-        # Return a causal mask, accounting for potentially stored past keys/values
-        # We actually return a bias for the attention score, as this has the same
-        # convention both in the builtin MHA in Pytorch, and Xformers functions.
-        time_dim = _get_attention_time_dimension()
-        if self.memory_efficient:
-            from xformers.ops import LowerTriangularMask
-            if current_steps == 1:
-                # If we only have one step, then we do not need a mask.
-                return None
-            elif 'past_keys' in self._streaming_state:
-                raise RuntimeError("Not supported at the moment")
-            else:
-                # Then we can safely use a lower triangular mask
-                return LowerTriangularMask()
-        if self._streaming_state:
-            past_keys = self._streaming_state['past_keys']
-            past_steps = past_keys.shape[time_dim]
-        else:
-            past_steps = 0
-
-        queries_pos = torch.arange(
-            past_steps, current_steps + past_steps, device=device).view(-1, 1)
-        keys_pos = torch.arange(past_steps + current_steps, device=device).view(1, -1)
-        delta = queries_pos - keys_pos
-        valid = delta >= 0
-        if self.past_context is not None:
-            valid &= (delta <= self.past_context)
-        return torch.where(
-            valid,
-            torch.zeros([], device=device, dtype=dtype),
-            torch.full([], float('-inf'), device=device, dtype=dtype))
-
-    def _complete_kv(self, k, v):
-        time_dim = _get_attention_time_dimension()
-        if self.cross_attention:
-            # With cross attention we assume all keys and values
-            # are already available, and streaming is with respect
-            # to the queries only.
-            return k, v
-        # Complete the key/value pair using the streaming state.
-        if self._streaming_state:
-            pk = self._streaming_state['past_keys']
-            nk = torch.cat([pk, k], dim=time_dim)
-            if v is k:
-                nv = nk
-            else:
-                pv = self._streaming_state['past_values']
-                nv = torch.cat([pv, v], dim=time_dim)
-        else:
-            nk = k
-            nv = v
-
-        assert nk.shape[time_dim] == nv.shape[time_dim]
-        offset = 0
-        if self.past_context is not None:
-            offset = max(0, nk.shape[time_dim] - self.past_context)
-        if self._is_streaming:
-            self._streaming_state['past_keys'] = nk[:, offset:]
-            if v is not k:
-                self._streaming_state['past_values'] = nv[:, offset:]
-            if 'offset' in self._streaming_state:
-                self._streaming_state['offset'] += offset
-            else:
-                self._streaming_state['offset'] = torch.tensor(0)
-        return nk, nv
-
-    def _apply_rope(self, query: torch.Tensor, key: torch.Tensor):
-        # TODO: fix and verify layout.
-        assert _efficient_attention_backend == 'xformers', "Rope not supported with torch attn."
-        # Apply rope embeddings to query and key tensors.
-        assert self.rope is not None
-        if 'past_keys' in self._streaming_state:
-            past_keys_offset = self._streaming_state['past_keys'].shape[1]
-        else:
-            past_keys_offset = 0
-        if 'offset' in self._streaming_state:
-            past_context_offset = int(self._streaming_state['offset'].item())
-        else:
-            past_context_offset = 0
-        streaming_offset = past_context_offset + past_keys_offset
-        return self.rope.rotate_qk(query, key, start=streaming_offset)
-
-    def forward(self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor,
-                key_padding_mask=None, need_weights=False, attn_mask=None,
-                average_attn_weights=True, is_causal=False):
-        assert attn_mask is None
-        assert not is_causal, ("New param added in torch 2.0.1 not supported, "
-                               "use the causal args in the constructor.")
-
-        time_dim = _get_attention_time_dimension()
-        if time_dim == 2:
-            layout = "b h t d"
-        else:
-            layout = "b t h d"
-        dtype = query.dtype
-        if self._is_streaming:
-            assert self.causal or self.cross_attention, \
-                "Streaming only available for causal or cross attention"
-
-        if self.causal:
-            # At the moment we specialize only for the self-attention case.
-            assert query.shape[1] == key.shape[1], "Causal only for same length query / key / value"
-            assert value.shape[1] == key.shape[1], "Causal only for same length query / key / value"
-            attn_mask = self._get_mask(query.shape[1], query.device, query.dtype)
-
-        if self.custom:
-            # custom implementation
-            assert need_weights is False
-            assert key_padding_mask is None
-            if self.cross_attention:
-                # Different queries, keys, values, we have to spit manually the weights
-                # before applying the linear.
-                dim = self.in_proj_weight.shape[0] // 3
-                if self.in_proj_bias is None:
-                    bias_q, bias_k, bias_v = None, None, None
-                else:
-                    bias_q = self.in_proj_bias[:dim]
-                    bias_k = self.in_proj_bias[dim: 2 * dim]
-                    bias_v = self.in_proj_bias[2 * dim:]
-                q = nn.functional.linear(query, self.in_proj_weight[:dim], bias_q)
-                # todo: when streaming, we could actually save k, v and check the shape actually match.
-                k = nn.functional.linear(key, self.in_proj_weight[dim: 2 * dim], bias_k)
-                v = nn.functional.linear(value, self.in_proj_weight[2 * dim:], bias_v)
-                if self.qk_layer_norm is True:
-                    q = self.q_layer_norm(q)
-                    k = self.k_layer_norm(k)
-                q, k, v = [rearrange(x, f"b t (h d) -> {layout}", h=self.num_heads) for x in [q, k, v]]
-            else:
-                if not _is_profiled():
-                    # profiling breaks that propertysomehow.
-                    assert query is key, "specialized implementation"
-                    assert value is key, "specialized implementation"
-                projected = nn.functional.linear(query, self.in_proj_weight, self.in_proj_bias)
-                if self.kv_repeat == 1:
-                    if time_dim == 2:
-                        bound_layout = "b h p t d"
-                    else:
-                        bound_layout = "b t p h d"
-                    packed = rearrange(projected, f"b t (p h d) -> {bound_layout}", p=3, h=self.num_heads)
-                    q, k, v = ops.unbind(packed, dim=2)
-                else:
-                    embed_dim = self.embed_dim
-                    per_head_dim = (embed_dim // self.num_heads)
-                    kv_heads = self.num_heads // self.kv_repeat
-                    q = projected[:, :, :embed_dim]
-                    start = embed_dim
-                    end = start + per_head_dim * kv_heads
-                    k = projected[:, :, start: end]
-                    v = projected[:, :, end:]
-                    q = rearrange(q, f"b t (h d) -> {layout}", h=self.num_heads)
-                    k = rearrange(k, f"b t (h d) -> {layout}", h=kv_heads)
-                    v = rearrange(v, f"b t (h d) -> {layout}", h=kv_heads)
-
-                if self.qk_layer_norm is True:
-                    assert self.kv_repeat == 1
-                    q, k = [rearrange(x, f"{layout} -> b t (h d)") for x in [q, k]]
-                    q = self.q_layer_norm(q)
-                    k = self.k_layer_norm(k)
-                    q, k = [rearrange(x, f"b t (h d) -> {layout}", h=self.num_heads) for x in [q, k]]
-                if self.rope:
-                    q, k = self._apply_rope(q, k)
-                k, v = self._complete_kv(k, v)
-                if self.kv_repeat > 1:
-                    k = expand_repeated_kv(k, self.kv_repeat)
-                    v = expand_repeated_kv(v, self.kv_repeat)
-            if self.attention_as_float32:
-                q, k, v = [x.float() for x in [q, k, v]]
-            if self.memory_efficient:
-                p = self.dropout if self.training else 0
-                if _efficient_attention_backend == 'torch':
-                    x = torch.nn.functional.scaled_dot_product_attention(
-                        q, k, v, is_causal=attn_mask is not None, dropout_p=p)
-                else:
-                    x = ops.memory_efficient_attention(q, k, v, attn_mask, p=p)
-            else:
-                # We include the dot product as float32, for consistency
-                # with the other implementations that include that step
-                # as part of the attention. Note that when using `autocast`,
-                # the einsums would be done as bfloat16, but the softmax
-                # would be done as bfloat16, so `attention_as_float32` will
-                # extend a bit the range of operations done in float32,
-                # although this should make no difference.
-                q = q / q.shape[-1] ** 0.5
-                key_layout = layout.replace('t', 'k')
-                query_layout = layout
-                if self._is_streaming and self.safe_streaming and q.device.type == 'cuda':
-                    with torch.autocast(device_type=q.device.type, dtype=torch.float32):
-                        pre_w = torch.einsum(f"{query_layout},{key_layout}-> b h t k", q, k)
-                else:
-                    pre_w = torch.einsum(f"{query_layout},{key_layout}-> b h t k", q, k)
-                if attn_mask is not None:
-                    pre_w = pre_w + attn_mask
-                w = torch.softmax(pre_w, dim=-1)
-                w = F.dropout(w, self.dropout, training=self.training).to(v)
-                # Key and value have the same format.
-                x = torch.einsum(f"b h t k, {key_layout} -> {layout}", w, v)
-            x = x.to(dtype)
-            x = rearrange(x, f"{layout} -> b t (h d)", h=self.num_heads)
-            x = self.out_proj(x)
-        else:
-            key, value = self._complete_kv(key, value)
-            if self.attention_as_float32:
-                query, key, value = [x.float() for x in [query, key, value]]
-            x, _ = self.mha(
-                query, key, value, key_padding_mask,
-                need_weights, attn_mask, average_attn_weights)
-            x = x.to(dtype)
-
-        return x, None
-
-
-class StreamingTransformerLayer(nn.TransformerEncoderLayer):
-    """TransformerLayer with Streaming / Causal support.
-    This also integrates cross_attention, when passing `cross_attention=True`,
-    rather than having two separate classes like in PyTorch.
-
-    Args:
-        d_model (int): Dimension of the data.
-        num_heads (int): Number of heads.
-        dim_feedforward (int): Intermediate dimension of FF module.
-        dropout (float): Dropout both for MHA and FF.
-        bias_ff (bool): Use bias for FF.
-        bias_attn (bool): Use bias for MHA.
-        causal (bool): Causal mask applied automatically.
-        past_context (int, optional): Receptive field for the causal mask, infinite if None.
-        custom (bool): Use custom MHA implementation, for testing / benchmarking.
-        memory_efficient (bool): Use xformers based memory efficient attention.
-        attention_as_float32 (bool): Perform the attention as float32
-            (especially important with memory_efficient as autocast won't do this automatically).
-        qk_layer_norm (bool): Layer normalization applied to queries and keys before dot product in attention.
-        qk_layer_norm_cross (bool): Same for the cross attention.
-        cross_attention (bool): If True, expect to get secondary input for cross-attention.
-            Cross attention will use the default MHA, as it typically won't require
-            special treatment.
-        layer_scale (float, optional): If not None, LayerScale will be used with
-            the given value as initial scale.
-        rope (`RotaryEmbedding`, optional): Rope embedding to use.
-        attention_dropout (float, optional): If not None, separate the value of the dimension dropout
-            in FFN and of the attention dropout.
-        kv_repeat (int): If > 1, will repeat keys and queries multiple times (need to divide num_heads).
-            This will lead to faster decoding time on A100 or other GPUs with tensorcore.
-        device (torch.device, optional): Device on which to initialize.
-        dtype (torch.dtype, optional): dtype to use.
-        **kwargs: See `nn.TransformerEncoderLayer`.
-    """
-    def __init__(self, d_model: int, num_heads: int, dim_feedforward: int = 2048, dropout: float = 0.1,
-                 bias_ff: bool = True, bias_attn: bool = True, causal: bool = False,
-                 past_context: tp.Optional[int] = None, custom: bool = False,
-                 memory_efficient: bool = False, attention_as_float32: bool = False,
-                 qk_layer_norm: bool = False, qk_layer_norm_cross: bool = False,
-                 cross_attention: bool = False, layer_scale: tp.Optional[float] = None,
-                 rope: tp.Optional[RotaryEmbedding] = None, attention_dropout: tp.Optional[float] = None,
-                 kv_repeat: int = 1, norm: str = 'layer_norm', device=None, dtype=None, **kwargs):
-        super().__init__(d_model, num_heads, dim_feedforward, dropout,
-                         device=device, dtype=dtype, batch_first=True, **kwargs)
-        factory_kwargs = {'device': device, 'dtype': dtype}
-        # Redefine self_attn to our streaming multi-head attention
-        attn_kwargs: tp.Dict[str, tp.Any] = {
-            'embed_dim': d_model,
-            'num_heads': num_heads,
-            'dropout': dropout if attention_dropout is None else attention_dropout,
-            'bias': bias_attn,
-            'custom': custom,
-            'memory_efficient': memory_efficient,
-            'attention_as_float32': attention_as_float32,
-        }
-        self.self_attn: StreamingMultiheadAttention = StreamingMultiheadAttention(
-            causal=causal, past_context=past_context, rope=rope, qk_layer_norm=qk_layer_norm,
-            kv_repeat=kv_repeat, **attn_kwargs, **factory_kwargs)  # type: ignore
-        # Redefine feedforward layers to expose bias parameter
-        self.linear1 = nn.Linear(d_model, dim_feedforward, bias=bias_ff, **factory_kwargs)
-        self.linear2 = nn.Linear(dim_feedforward, d_model, bias=bias_ff, **factory_kwargs)
-
-        self.layer_scale_1: nn.Module
-        self.layer_scale_2: nn.Module
-        if layer_scale is None:
-            self.layer_scale_1 = nn.Identity()
-            self.layer_scale_2 = nn.Identity()
-        else:
-            self.layer_scale_1 = LayerScale(d_model, layer_scale, **factory_kwargs)
-            self.layer_scale_2 = LayerScale(d_model, layer_scale, **factory_kwargs)
-
-        self.cross_attention: tp.Optional[nn.Module] = None
-        if cross_attention:
-            self.cross_attention = StreamingMultiheadAttention(
-                cross_attention=True, qk_layer_norm=qk_layer_norm_cross,
-                **attn_kwargs, **factory_kwargs)
-            # Norm and dropout
-            self.dropout_cross = nn.Dropout(dropout)
-            # eps value matching that used in PyTorch reference implementation.
-            self.norm_cross = nn.LayerNorm(d_model, eps=1e-5, **factory_kwargs)
-            self.layer_scale_cross: nn.Module
-            if layer_scale is None:
-                self.layer_scale_cross = nn.Identity()
-            else:
-                self.layer_scale_cross = LayerScale(d_model, layer_scale, **factory_kwargs)
-        self.norm1 = create_norm_fn(norm, d_model, **factory_kwargs)  # type: ignore
-        self.norm2 = create_norm_fn(norm, d_model, **factory_kwargs)  # type: ignore
-
-    def _cross_attention_block(self, src: torch.Tensor,
-                               cross_attention_src: torch.Tensor) -> torch.Tensor:
-        assert self.cross_attention is not None
-        # queries are from src, keys and values from cross_attention_src.
-        x = self.cross_attention(
-            src, cross_attention_src, cross_attention_src, need_weights=False)[0]
-        return self.dropout_cross(x)  # type: ignore
-
-    def forward(self, src: torch.Tensor, src_mask: tp.Optional[torch.Tensor] = None,  # type: ignore
-                src_key_padding_mask: tp.Optional[torch.Tensor] = None,
-                cross_attention_src: tp.Optional[torch.Tensor] = None):
-        if self.cross_attention is None:
-            assert cross_attention_src is None
-        else:
-            assert cross_attention_src is not None
-        x = src
-        if self.norm_first:
-            x = x + self.layer_scale_1(
-                self._sa_block(self.norm1(x), src_mask, src_key_padding_mask))
-            if cross_attention_src is not None:
-                x = x + self.layer_scale_cross(
-                    self._cross_attention_block(
-                        self.norm_cross(x), cross_attention_src))
-            x = x + self.layer_scale_2(self._ff_block(self.norm2(x)))
-        else:
-            x = self.norm1(x + self.layer_scale_1(
-                self._sa_block(x, src_mask, src_key_padding_mask)))
-            if cross_attention_src is not None:
-                x = self.norm_cross(
-                    x + self.layer_scale_cross(
-                        self._cross_attention_block(src, cross_attention_src)))
-            x = self.norm2(x + self.layer_scale_2(self._ff_block(x)))
-        return x
-
-
-class StreamingTransformer(StreamingModule):
-    """Transformer with Streaming / Causal support.
-
-    Args:
-        d_model (int): Dimension of the data.
-        num_heads (int): Number of heads.
-        dim_feedforward (int): Intermediate dimension of FF module.
-        dropout (float): Dropout both for MHA and FF.
-        bias_ff (bool): Use bias for FF.
-        bias_attn (bool): Use bias for MHA.
-        causal (bool): Causal mask applied automatically.
-        past_context (int, optional): Receptive field for the causal mask, infinite if None.
-        custom (bool): Use custom MHA implementation, for testing / benchmarking.
-        memory_efficient (bool): Use xformers based memory efficient attention.
-        attention_as_float32 (bool): Perform the attention as float32
-            (especially important with memory_efficient as autocast won't do this automatically).
-        cross_attention (bool): If True, expect to get secondary input for cross-attention.
-        layer_scale (float, optional): If not None, LayerScale will be used
-            with the given value as initial scale.
-        positional_embedding (str): Positional embedding strategy (sin, rope, or sin_rope).
-        max_period (float): Maximum period of the time embedding.
-        positional_scale (float): Scale of positional embedding, set to 0 to deactivate.
-        xpos (bool): Apply xpos exponential decay to positional embedding (rope only).
-        lr (float, optional): learning rate override through the `make_optim_group` API.
-        weight_decay (float, optional): Weight_decay override through the `make_optim_group` API.
-        layer_class: (subclass of `StreamingTransformerLayer): class to use
-            to initialize the layers, allowing further customization outside of AudioCraft.
-        checkpointing (str): Checkpointing strategy to reduce memory usage.
-            No checkpointing if set to 'none'. Per layer checkpointing using PyTorch
-            if set to 'torch' (entire layer checkpointed, i.e. linears are evaluated twice,
-            minimal memory usage, but maximal runtime). Finally, `xformers_default` provide
-            a policy for opting-out some operations of the checkpointing like
-            linear layers and attention, providing a middle ground between speed and memory.
-        device (torch.device, optional): Device on which to initialize.
-        dtype (torch.dtype, optional): dtype to use.
-        **kwargs: See `nn.TransformerEncoderLayer`.
-    """
-    def __init__(self, d_model: int, num_heads: int, num_layers: int, dim_feedforward: int = 2048,
-                 dropout: float = 0.1, bias_ff: bool = True, bias_attn: bool = True,
-                 causal: bool = False, past_context: tp.Optional[int] = None,
-                 custom: bool = False, memory_efficient: bool = False, attention_as_float32: bool = False,
-                 cross_attention: bool = False, layer_scale: tp.Optional[float] = None,
-                 positional_embedding: str = 'sin', max_period: float = 10_000, positional_scale: float = 1.,
-                 xpos: bool = False, lr: tp.Optional[float] = None, weight_decay: tp.Optional[float] = None,
-                 layer_class: tp.Type[StreamingTransformerLayer] = StreamingTransformerLayer,
-                 checkpointing: str = 'none', device=None, dtype=None, **kwargs):
-        super().__init__()
-        assert d_model % num_heads == 0
-
-        self.positional_embedding = positional_embedding
-        self.max_period = max_period
-        self.positional_scale = positional_scale
-        self.weight_decay = weight_decay
-        self.lr = lr
-
-        assert positional_embedding in ['sin', 'rope', 'sin_rope']
-        self.rope: tp.Optional[RotaryEmbedding] = None
-        if self.positional_embedding in ['rope', 'sin_rope']:
-            assert _is_custom(custom, memory_efficient)
-            self.rope = RotaryEmbedding(d_model // num_heads, max_period=max_period,
-                                        xpos=xpos, scale=positional_scale, device=device)
-
-        self.checkpointing = checkpointing
-
-        assert checkpointing in ['none', 'torch', 'xformers_default', 'xformers_mm']
-        if self.checkpointing.startswith('xformers'):
-            _verify_xformers_internal_compat()
-
-        self.layers = nn.ModuleList()
-        for idx in range(num_layers):
-            self.layers.append(
-                layer_class(
-                    d_model=d_model, num_heads=num_heads, dim_feedforward=dim_feedforward,
-                    dropout=dropout, bias_ff=bias_ff, bias_attn=bias_attn,
-                    causal=causal, past_context=past_context, custom=custom,
-                    memory_efficient=memory_efficient, attention_as_float32=attention_as_float32,
-                    cross_attention=cross_attention, layer_scale=layer_scale, rope=self.rope,
-                    device=device, dtype=dtype, **kwargs))
-
-        if self.checkpointing != 'none':
-            for layer in self.layers:
-                # see audiocraft/optim/fsdp.py, magic signal to indicate this requires fixing the
-                # backward hook inside of FSDP...
-                layer._magma_checkpointed = True  # type: ignore
-                assert layer.layer_drop == 0., "Need further checking"  # type: ignore
-
-    def _apply_layer(self, layer, *args, **kwargs):
-        method = self.checkpointing
-        if method == 'none':
-            return layer(*args, **kwargs)
-        elif method == 'torch':
-            return torch_checkpoint(layer, *args, use_reentrant=False, **kwargs)
-        elif method.startswith('xformers'):
-            from xformers.checkpoint_fairinternal import checkpoint, _get_default_policy
-            if method == 'xformers_default':
-                # those operations will be saved, and not recomputed.
-                # According to Francisco we can get smarter policies but this is a good start.
-                allow_list = [
-                    "xformers.efficient_attention_forward_cutlass.default",
-                    "xformers_flash.flash_fwd.default",
-                    "aten.addmm.default",
-                    "aten.mm.default",
-                ]
-            elif method == 'xformers_mm':
-                # those operations will be saved, and not recomputed.
-                # According to Francisco we can get smarter policies but this is a good start.
-                allow_list = [
-                    "aten.addmm.default",
-                    "aten.mm.default",
-                ]
-            else:
-                raise ValueError(f"xformers checkpointing xformers policy {method} is not known.")
-            policy_fn = _get_default_policy(allow_list)
-            return checkpoint(layer, *args, policy_fn=policy_fn, **kwargs)
-        else:
-            raise ValueError(f"Checkpointing method {method} is unknown.")
-
-    def forward(self, x: torch.Tensor, *args, **kwargs):
-        B, T, C = x.shape
-
-        if 'offsets' in self._streaming_state:
-            offsets = self._streaming_state['offsets']
-        else:
-            offsets = torch.zeros(B, dtype=torch.long, device=x.device)
-
-        if self.positional_embedding in ['sin', 'sin_rope']:
-            positions = torch.arange(T, device=x.device).view(1, -1, 1)
-            positions = positions + offsets.view(-1, 1, 1)
-            pos_emb = create_sin_embedding(positions, C, max_period=self.max_period, dtype=x.dtype)
-            x = x + self.positional_scale * pos_emb
-
-        for layer in self.layers:
-            x = self._apply_layer(layer, x, *args, **kwargs)
-
-        if self._is_streaming:
-            self._streaming_state['offsets'] = offsets + T
-
-        return x
-
-    def make_optim_group(self):
-        group = {"params": list(self.parameters())}
-        if self.lr is not None:
-            group["lr"] = self.lr
-        if self.weight_decay is not None:
-            group["weight_decay"] = self.weight_decay
-        return group
-
-
-# special attention related function
-
-def _verify_xformers_memory_efficient_compat():
-    try:
-        from xformers.ops import memory_efficient_attention, LowerTriangularMask  # noqa
-    except ImportError:
-        raise ImportError(
-            "xformers is not installed. Please install it and try again.\n"
-            "To install on AWS and Azure, run \n"
-            "FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST='8.0'\\\n"
-            "pip install -U git+https://git@github.com/fairinternal/xformers.git#egg=xformers\n"
-            "To install on FAIR Cluster, run \n"
-            "FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST='6.0;7.0'\\\n"
-            "pip install -U git+https://git@github.com/fairinternal/xformers.git#egg=xformers\n")
-
-
-def _verify_xformers_internal_compat():
-    try:
-        from xformers.checkpoint_fairinternal import checkpoint, _get_default_policy  # noqa
-    except ImportError:
-        raise ImportError(
-            "Francisco's fairinternal xformers is not installed. Please install it and try again.\n"
-            "To install on AWS and Azure, run \n"
-            "FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST='8.0'\\\n"
-            "pip install -U git+https://git@github.com/fairinternal/xformers.git#egg=xformers\n"
-            "To install on FAIR Cluster, run \n"
-            "FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST='6.0;7.0'\\\n"
-            "pip install -U git+https://git@github.com/fairinternal/xformers.git#egg=xformers\n")
-
-
-def _is_custom(custom: bool, memory_efficient: bool):
-    return custom or memory_efficient
diff --git a/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/export.py b/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/export.py
deleted file mode 100644
index b513b52267f7bf5aae09282c15b0a2e20c8a8fee..0000000000000000000000000000000000000000
--- a/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/export.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.
-
-"""
-Utility to export a training checkpoint to a lightweight release checkpoint.
-"""
-
-from pathlib import Path
-import typing as tp
-
-from omegaconf import OmegaConf, DictConfig
-import torch
-
-
-def _clean_lm_cfg(cfg: DictConfig):
-    OmegaConf.set_struct(cfg, False)
-    # This used to be set automatically in the LM solver, need a more robust solution
-    # for the future.
-    cfg['transformer_lm']['card'] = 2048
-    cfg['transformer_lm']['n_q'] = 4
-    # Experimental params no longer supported.
-    bad_params = ['spectral_norm_attn_iters', 'spectral_norm_ff_iters',
-                  'residual_balancer_attn', 'residual_balancer_ff', 'layer_drop']
-    for name in bad_params:
-        del cfg['transformer_lm'][name]
-    OmegaConf.set_struct(cfg, True)
-    return cfg
-
-
-def export_encodec(checkpoint_path: tp.Union[Path, str], out_folder: tp.Union[Path, str]):
-    sig = Path(checkpoint_path).parent.name
-    assert len(sig) == 8, "Not a valid Dora signature"
-    pkg = torch.load(checkpoint_path, 'cpu')
-    new_pkg = {
-        'best_state': pkg['ema']['state']['model'],
-        'xp.cfg': OmegaConf.to_yaml(pkg['xp.cfg']),
-    }
-    out_file = Path(out_folder) / f'{sig}.th'
-    torch.save(new_pkg, out_file)
-    return out_file
-
-
-def export_lm(checkpoint_path: tp.Union[Path, str], out_folder: tp.Union[Path, str]):
-    sig = Path(checkpoint_path).parent.name
-    assert len(sig) == 8, "Not a valid Dora signature"
-    pkg = torch.load(checkpoint_path, 'cpu')
-    new_pkg = {
-        'best_state': pkg['fsdp_best_state']['model'],
-        'xp.cfg': OmegaConf.to_yaml(_clean_lm_cfg(pkg['xp.cfg']))
-    }
-    out_file = Path(out_folder) / f'{sig}.th'
-    torch.save(new_pkg, out_file)
-    return out_file
diff --git a/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/extend.py b/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/extend.py
deleted file mode 100644
index 5c919a5cb740e14ca8751d68a0ab16d9400d35d6..0000000000000000000000000000000000000000
--- a/spaces/AbandonedMuse/UnlimitedMusicGen/audiocraft/utils/extend.py
+++ /dev/null
@@ -1,332 +0,0 @@
-from tabnanny import verbose
-import torch
-import math
-from audiocraft.models import MusicGen
-import numpy as np
-from PIL import Image, ImageDraw, ImageFont, ImageColor
-import string
-import tempfile
-import os
-import textwrap
-import requests
-from io import BytesIO
-from huggingface_hub import hf_hub_download
-import librosa
-
-
-INTERRUPTING = False
-
-def separate_audio_segments(audio, segment_duration=30, overlap=1):
-    sr, audio_data = audio[0], audio[1]
-    
-    segment_samples = sr * segment_duration
-    total_samples = max(min((len(audio_data) // segment_samples), 25), 0)
-    overlap_samples = sr * overlap
-
-    segments = []
-    start_sample = 0
-    # handle the case where the audio is shorter than the segment duration
-    if total_samples == 0:
-        total_samples = 1
-        segment_samples = len(audio_data)
-        overlap_samples = 0
-    while total_samples >= segment_samples:
-        # Collect the segment
-        # the end sample is the start sample plus the segment samples, 
-        # the start sample, after 0, is minus the overlap samples to account for the overlap        
-        end_sample = start_sample + segment_samples
-        segment = audio_data[start_sample:end_sample]
-        segments.append((sr, segment))
-
-        start_sample += segment_samples - overlap_samples
-        total_samples -= segment_samples
-
-    # Collect the final segment
-    if total_samples > 0:
-        segment = audio_data[-segment_samples:]
-        segments.append((sr, segment))
-    print(f"separate_audio_segments: {len(segments)} segments of length {segment_samples // sr} seconds")
-    return segments
-
-def generate_music_segments(text, melody, seed, MODEL, duration:int=10, overlap:int=1, segment_duration:int=30, prompt_index:int=0, harmony_only:bool= False):
-    # generate audio segments
-    melody_segments = separate_audio_segments(melody, segment_duration, 0) 
-    
-    # Create lists to store the melody tensors for each segment
-    melodys = []
-    output_segments = []
-    last_chunk = []
-    text += ", seed=" + str(seed)
-    prompt_segment = None
-    # prevent hacking
-    duration = min(duration, 720)
-    overlap =  min(overlap, 15)
-    
-    # Calculate the total number of segments
-    total_segments = max(math.ceil(duration / segment_duration),1)
-    #calculate duration loss from segment overlap
-    duration_loss = max(total_segments - 1,0) * math.ceil(overlap / 2)
-    #calc excess duration
-    excess_duration = segment_duration - (total_segments * segment_duration - duration)
-    print(f"total Segments to Generate: {total_segments} for {duration} seconds. Each segment is {segment_duration} seconds. Excess {excess_duration} Overlap Loss {duration_loss}")
-    duration += duration_loss
-    while excess_duration + duration_loss > segment_duration:
-        total_segments += 1
-        #calculate duration loss from segment overlap
-        duration_loss += math.ceil(overlap / 2)
-        #calc excess duration
-        excess_duration = segment_duration - (total_segments * segment_duration - duration)
-        print(f"total Segments to Generate: {total_segments} for {duration} seconds. Each segment is {segment_duration} seconds. Excess {excess_duration} Overlap Loss {duration_loss}")
-        if excess_duration + duration_loss > segment_duration:
-            duration += duration_loss
-            duration_loss = 0
-    total_segments = min(total_segments, (720 // segment_duration))
-
-    # If melody_segments is shorter than total_segments, repeat the segments until the total_segments is reached
-    if len(melody_segments) < total_segments:
-        #fix melody_segments
-        for i in range(total_segments - len(melody_segments)):
-            segment = melody_segments[i]
-            melody_segments.append(segment)
-        print(f"melody_segments: {len(melody_segments)} fixed")
-
-    # Iterate over the segments to create list of Meldoy tensors
-    for segment_idx in range(total_segments):
-        if INTERRUPTING:
-            return [], duration
-        print(f"segment {segment_idx + 1} of {total_segments} \r")
-
-        if harmony_only:
-            # REMOVE PERCUSION FROM MELODY
-            # Apply HPSS using librosa
-            verse_harmonic, verse_percussive = librosa.effects.hpss(melody_segments[segment_idx][1])
-            # Convert the separated components back to torch.Tensor
-            #harmonic_tensor = torch.from_numpy(verse_harmonic)
-            #percussive_tensor = torch.from_numpy(verse_percussive)
-            sr, verse = melody_segments[segment_idx][0], torch.from_numpy(verse_harmonic).to(MODEL.device).float().t().unsqueeze(0)
-        else:
-            sr, verse = melody_segments[segment_idx][0], torch.from_numpy(melody_segments[segment_idx][1]).to(MODEL.device).float().t().unsqueeze(0)
-
-        print(f"shape:{verse.shape} dim:{verse.dim()}")
-        if verse.dim() == 2:
-            verse = verse[None]
-        verse = verse[..., :int(sr * MODEL.lm.cfg.dataset.segment_duration)]
-
-        # Append the segment to the melodys list
-        melodys.append(verse)
-
-    torch.manual_seed(seed)
-
-    # If user selects a prompt segment, generate a new prompt segment to use on all segments
-    #default to the first segment for prompt conditioning
-    prompt_verse = melodys[0]
-    if prompt_index > 0:
-        # Get a prompt segment from the selected verse, normally the first verse
-        prompt_verse = melodys[prompt_index if prompt_index <= (total_segments - 1) else (total_segments -1)]
-       
-    # set the prompt segment MODEL generation params
-    MODEL.set_generation_params(
-        use_sampling=True,
-        top_k=MODEL.generation_params["top_k"],
-        top_p=MODEL.generation_params["top_p"],
-        temperature=MODEL.generation_params["temp"],
-        cfg_coef=MODEL.generation_params["cfg_coef"],
-        duration=segment_duration,
-        two_step_cfg=False,
-        rep_penalty=0.5
-    )
-    # Generate a new prompt segment. This will be applied to all segments for consistency
-    print(f"Generating New Prompt Segment: {text} from verse {prompt_index}\r")
-    prompt_segment = MODEL.generate_with_all(
-        descriptions=[text],
-        melody_wavs=prompt_verse,
-        sample_rate=sr,
-        progress=False,
-        prompt=None,
-    )       
-
-    for idx, verse in enumerate(melodys):
-        if INTERRUPTING:
-            return output_segments, duration
-
-        print(f'Segment duration: {segment_duration}, duration: {duration}, overlap: {overlap} Overlap Loss: {duration_loss}')
-        # Compensate for the length of final segment
-        if ((idx + 1) == len(melodys)) or (duration < segment_duration):
-            mod_duration = max(min(duration, segment_duration),1)
-            print(f'Modify verse length, duration: {duration}, overlap: {overlap} Overlap Loss: {duration_loss} to mod duration: {mod_duration}')
-            MODEL.set_generation_params(
-                use_sampling=True,
-                top_k=MODEL.generation_params["top_k"],
-                top_p=MODEL.generation_params["top_p"],
-                temperature=MODEL.generation_params["temp"],
-                cfg_coef=MODEL.generation_params["cfg_coef"],
-                duration=mod_duration,
-                two_step_cfg=False,
-                rep_penalty=0.5
-            )
-            try:
-                # get last chunk
-                verse = verse[:, :, -mod_duration*MODEL.sample_rate:]
-                prompt_segment = prompt_segment[:, :, -mod_duration*MODEL.sample_rate:]
-            except:
-                # get first chunk
-                verse = verse[:, :, :mod_duration*MODEL.sample_rate] 
-                prompt_segment = prompt_segment[:, :, :mod_duration*MODEL.sample_rate]
-      
-            
-        print(f"Generating New Melody Segment {idx + 1}: {text}\r")
-        output = MODEL.generate_with_all(
-            descriptions=[text],
-            melody_wavs=verse,
-            sample_rate=sr,
-            progress=False,
-            prompt=prompt_segment,
-        )
-        # If user selects a prompt segment, use the prompt segment for all segments
-        # Otherwise, use the previous segment as the prompt
-        if prompt_index < 0:
-            prompt_segment = output
-
-        # Append the generated output to the list of segments
-        #output_segments.append(output[:, :segment_duration])
-        output_segments.append(output)
-        print(f"output_segments: {len(output_segments)}: shape: {output.shape} dim {output.dim()}")
-        #track duration
-        if duration > segment_duration:
-            duration -= segment_duration
-    return output_segments, excess_duration
-
-def save_image(image):
-    """
-    Saves a PIL image to a temporary file and returns the file path.
-
-    Parameters:
-    - image: PIL.Image
-        The PIL image object to be saved.
-
-    Returns:
-    - str or None: The file path where the image was saved,
-        or None if there was an error saving the image.
-
-    """
-    temp_dir = tempfile.gettempdir()
-    temp_file = tempfile.NamedTemporaryFile(suffix=".png", dir=temp_dir, delete=False)
-    temp_file.close()
-    file_path = temp_file.name
-
-    try:
-        image.save(file_path)
-        
-    except Exception as e:
-        print("Unable to save image:", str(e))
-        return None
-    finally:
-        return file_path
-
-def hex_to_rgba(hex_color):
-    try:
-        # Convert hex color to RGBA tuple
-        rgba = ImageColor.getcolor(hex_color, "RGBA")
-    except ValueError:
-        # If the hex color is invalid, default to yellow
-        rgba = (255,255,0,255)
-    return rgba
-
-def load_font(font_name, font_size=16):
-    """
-    Load a font using the provided font name and font size.
-
-    Parameters:
-        font_name (str): The name of the font to load. Can be a font name recognized by the system, a URL to download the font file,
-            a local file path, or a Hugging Face model hub identifier.
-        font_size (int, optional): The size of the font. Default is 16.
-
-    Returns:
-        ImageFont.FreeTypeFont: The loaded font object.
-
-    Notes:
-        This function attempts to load the font using various methods until a suitable font is found. If the provided font_name
-        cannot be loaded, it falls back to a default font.
-
-        The font_name can be one of the following:
-        - A font name recognized by the system, which can be loaded using ImageFont.truetype.
-        - A URL pointing to the font file, which is downloaded using requests and then loaded using ImageFont.truetype.
-        - A local file path to the font file, which is loaded using ImageFont.truetype.
-        - A Hugging Face model hub identifier, which downloads the font file from the Hugging Face model hub using hf_hub_download
-          and then loads it using ImageFont.truetype.
-
-    Example:
-        font = load_font("Arial.ttf", font_size=20)
-    """
-    font = None
-    if not "http" in font_name:
-        try:
-            font = ImageFont.truetype(font_name, font_size)
-        except (FileNotFoundError, OSError):
-            print("Font not found. Using Hugging Face download..\n")
-
-        if font is None:
-            try:
-                font_path = ImageFont.truetype(hf_hub_download(repo_id=os.environ.get('SPACE_ID', ''), filename="assets/" + font_name, repo_type="space"), encoding="UTF-8")        
-                font = ImageFont.truetype(font_path, font_size)
-            except (FileNotFoundError, OSError):
-                print("Font not found. Trying to download from local assets folder...\n")
-        if font is None:
-            try:
-                font = ImageFont.truetype("assets/" + font_name, font_size)
-            except (FileNotFoundError, OSError):
-                print("Font not found. Trying to download from URL...\n")
-
-    if font is None:
-        try:
-            req = requests.get(font_name)
-            font = ImageFont.truetype(BytesIO(req.content), font_size)  
-        except (FileNotFoundError, OSError):            
-            print(f"Font not found: {font_name} Using default font\n")
-    if font:
-        print(f"Font loaded {font.getname()}")
-    else:
-        font = ImageFont.load_default()
-    return font
-
-
-def add_settings_to_image(title: str = "title", description: str = "", width: int = 768, height: int = 512, background_path: str = "", font: str = "arial.ttf", font_color: str = "#ffffff"):
-    # Create a new RGBA image with the specified dimensions
-    image = Image.new("RGBA", (width, height), (255, 255, 255, 0))
-    # If a background image is specified, open it and paste it onto the image
-    if background_path == "":
-        background = Image.new("RGBA", (width, height), (255, 255, 255, 255))
-    else:
-        background = Image.open(background_path).convert("RGBA")
-
-    #Convert font color to RGBA tuple
-    font_color = hex_to_rgba(font_color)
-
-    # Calculate the center coordinates for placing the text
-    text_x = width // 2
-    text_y = height // 2
-    # Draw the title text at the center top
-    title_font = load_font(font, 26)  # Replace with your desired font and size
-
-    title_text = '\n'.join(textwrap.wrap(title, width // 12))
-    title_x, title_y, title_text_width, title_text_height = title_font.getbbox(title_text)
-    title_x = max(text_x - (title_text_width // 2), title_x, 0)
-    title_y = text_y - (height // 2) + 10  # 10 pixels padding from the top
-    title_draw = ImageDraw.Draw(image)
-    title_draw.multiline_text((title_x, title_y), title, fill=font_color, font=title_font, align="center")
-    # Draw the description text two lines below the title
-    description_font = load_font(font, 16)  # Replace with your desired font and size
-    description_text = '\n'.join(textwrap.wrap(description, width // 12))
-    description_x, description_y, description_text_width, description_text_height = description_font.getbbox(description_text)
-    description_x = max(text_x - (description_text_width // 2), description_x, 0)
-    description_y = title_y + title_text_height + 20  # 20 pixels spacing between title and description
-    description_draw = ImageDraw.Draw(image)
-    description_draw.multiline_text((description_x, description_y), description_text, fill=font_color, font=description_font, align="center")
-    # Calculate the offset to center the image on the background
-    bg_w, bg_h = background.size
-    offset = ((bg_w - width) // 2, (bg_h - height) // 2)
-    # Paste the image onto the background
-    background.paste(image, offset, mask=image)
-
-    # Save the image and return the file path
-    return save_image(background)
\ No newline at end of file
diff --git a/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/lib/utils/template.ts b/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/lib/utils/template.ts
deleted file mode 100644
index 87360c88fe6c655fff39f7947da9c6b345402a60..0000000000000000000000000000000000000000
--- a/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/lib/utils/template.ts
+++ /dev/null
@@ -1,28 +0,0 @@
-import type { Message } from "$lib/types/Message";
-import type { LegacyParamatersTemplateInput } from "$lib/types/Template";
-import Handlebars from "handlebars";
-
-Handlebars.registerHelper("ifUser", function (this: Pick<Message, "from" | "content">, options) {
-	if (this.from == "user") return options.fn(this);
-});
-
-Handlebars.registerHelper(
-	"ifAssistant",
-	function (this: Pick<Message, "from" | "content">, options) {
-		if (this.from == "assistant") return options.fn(this);
-	}
-);
-
-export function compileTemplate<T>(input: string, model: LegacyParamatersTemplateInput) {
-	const template = Handlebars.compile<T & LegacyParamatersTemplateInput>(input, {
-		knownHelpers: { ifUser: true, ifAssistant: true },
-		knownHelpersOnly: true,
-		noEscape: true,
-		strict: true,
-		preventIndent: true,
-	});
-
-	return function render(inputs: T, options?: RuntimeOptions) {
-		return template({ ...model, ...inputs }, options);
-	};
-}
diff --git a/spaces/AchyuthGamer/OpenGPT/g4f/models.py b/spaces/AchyuthGamer/OpenGPT/g4f/models.py
deleted file mode 100644
index b42477036ba65315d4e867e5f9df3c4b0ed901d3..0000000000000000000000000000000000000000
--- a/spaces/AchyuthGamer/OpenGPT/g4f/models.py
+++ /dev/null
@@ -1,274 +0,0 @@
-from __future__  import annotations
-from dataclasses import dataclass
-from .typing     import Union
-from .Provider   import BaseProvider, RetryProvider
-from .Provider   import (
-    AItianhuSpace,
-    ChatgptLogin,
-    ChatgptDemo,
-    ChatgptDuo,
-    Vitalentum,
-    ChatgptAi,
-    ChatForAi,
-    AItianhu,
-    ChatBase,
-    Liaobots,
-    Yqcloud,
-    Myshell,
-    FreeGpt,
-    Vercel, 
-    DeepAi,
-    Aichat,
-    GPTalk,
-    GptGod,
-    AiAsk,
-    GptGo,
-    Ylokh,
-    Bard, 
-    Aibn,
-    Bing,
-    You,
-    H2o
-)
-
-@dataclass(unsafe_hash=True)
-class Model:
-    name: str
-    base_provider: str
-    best_provider: Union[type[BaseProvider], RetryProvider] = None
-
-default = Model(
-    name          = "",
-    base_provider = "",
-    best_provider = RetryProvider([
-        Bing,         # Not fully GPT 3 or 4
-        Yqcloud,      # Answers short questions in chinese
-        ChatBase,     # Don't want to answer creatively
-        ChatgptDuo,   # Include search results
-        Aibn, Aichat, ChatForAi, ChatgptAi, ChatgptLogin, DeepAi, FreeGpt, GptGo, Myshell, Ylokh,
-    ])
-)
-
-# GPT-3.5 too, but all providers supports long responses and a custom timeouts
-gpt_35_long = Model(
-    name          = 'gpt-3.5-turbo',
-    base_provider = 'openai',
-    best_provider = RetryProvider([
-        AiAsk, Aibn, Aichat, ChatForAi, ChatgptAi, ChatgptDemo, ChatgptDuo,
-        FreeGpt, GptGo, Liaobots, Myshell, Vitalentum, Ylokh, You, Yqcloud,
-        GPTalk, GptGod
-    ])
-)
-
-# GPT-3.5 / GPT-4
-gpt_35_turbo = Model(
-    name          = 'gpt-3.5-turbo',
-    base_provider = 'openai',
-    best_provider = RetryProvider([
-        DeepAi, ChatgptLogin, ChatgptAi, GptGo, AItianhu, Aichat, AItianhuSpace, Myshell, Aibn, ChatForAi, FreeGpt, Ylokh
-    ])
-)
-
-gpt_4 = Model(
-    name          = 'gpt-4',
-    base_provider = 'openai',
-    best_provider = Bing
-)
-
-# Bard
-palm = Model(
-    name          = 'palm',
-    base_provider = 'google',
-    best_provider = Bard)
-
-# H2o
-falcon_7b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
-    base_provider = 'huggingface',
-    best_provider = H2o)
-
-falcon_40b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
-    base_provider = 'huggingface',
-    best_provider = H2o)
-
-llama_13b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
-    base_provider = 'huggingface',
-    best_provider = H2o)
-
-# Vercel
-claude_instant_v1 = Model(
-    name          = 'claude-instant-v1',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
-
-claude_v1 = Model(
-    name          = 'claude-v1',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
-
-claude_v2 = Model(
-    name          = 'claude-v2',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
-
-command_light_nightly = Model(
-    name          = 'command-light-nightly',
-    base_provider = 'cohere',
-    best_provider = Vercel)
-
-command_nightly = Model(
-    name          = 'command-nightly',
-    base_provider = 'cohere',
-    best_provider = Vercel)
-
-gpt_neox_20b = Model(
-    name          = 'EleutherAI/gpt-neox-20b',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-oasst_sft_1_pythia_12b = Model(
-    name          = 'OpenAssistant/oasst-sft-1-pythia-12b',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-oasst_sft_4_pythia_12b_epoch_35 = Model(
-    name          = 'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-santacoder = Model(
-    name          = 'bigcode/santacoder',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-bloom = Model(
-    name          = 'bigscience/bloom',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-flan_t5_xxl = Model(
-    name          = 'google/flan-t5-xxl',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
-
-code_davinci_002 = Model(
-    name          = 'code-davinci-002',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-gpt_35_turbo_16k = Model(
-    name          = 'gpt-3.5-turbo-16k',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-gpt_35_turbo_16k_0613 = Model(
-    name          = 'gpt-3.5-turbo-16k-0613',
-    base_provider = 'openai')
-
-gpt_35_turbo_0613 = Model(
-    name          = 'gpt-3.5-turbo-0613',
-    base_provider = 'openai'
-)
-
-gpt_4_0613 = Model(
-    name          = 'gpt-4-0613',
-    base_provider = 'openai'
-)
-
-gpt_4_32k = Model(
-    name          = 'gpt-4-32k',
-    base_provider = 'openai'
-)
-
-gpt_4_32k_0613 = Model(
-    name          = 'gpt-4-32k-0613',
-    base_provider = 'openai'
-)
-
-text_ada_001 = Model(
-    name          = 'text-ada-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-text_babbage_001 = Model(
-    name          = 'text-babbage-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-text_curie_001 = Model(
-    name          = 'text-curie-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-text_davinci_002 = Model(
-    name          = 'text-davinci-002',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-text_davinci_003 = Model(
-    name          = 'text-davinci-003',
-    base_provider = 'openai',
-    best_provider = Vercel)
-
-llama13b_v2_chat = Model(
-    name          = 'replicate:a16z-infra/llama13b-v2-chat',
-    base_provider = 'replicate',
-    best_provider = Vercel)
-
-llama7b_v2_chat = Model(
-    name          = 'replicate:a16z-infra/llama7b-v2-chat',
-    base_provider = 'replicate',
-    best_provider = Vercel)
-
-
-class ModelUtils:
-    convert: dict[str, Model] = {
-        # gpt-3.5
-        'gpt-3.5-turbo'          : gpt_35_turbo,
-        'gpt-3.5-turbo-0613'     : gpt_35_turbo_0613,
-        'gpt-3.5-turbo-16k'      : gpt_35_turbo_16k,
-        'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
-        
-        # gpt-4
-        'gpt-4'          : gpt_4,
-        'gpt-4-0613'     : gpt_4_0613,
-        'gpt-4-32k'      : gpt_4_32k,
-        'gpt-4-32k-0613' : gpt_4_32k_0613,
-        
-        # Bard
-        'palm2'       : palm,
-        'palm'        : palm,
-        'google'      : palm,
-        'google-bard' : palm,
-        'google-palm' : palm,
-        'bard'        : palm,
-        
-        # H2o
-        'falcon-40b' : falcon_40b,
-        'falcon-7b'  : falcon_7b,
-        'llama-13b'  : llama_13b,
-        
-        # Vercel
-        'claude-instant-v1' : claude_instant_v1,
-        'claude-v1'         : claude_v1,
-        'claude-v2'         : claude_v2,
-        'command-nightly'   : command_nightly,
-        'gpt-neox-20b'      : gpt_neox_20b,
-        'santacoder'        : santacoder,
-        'bloom'             : bloom,
-        'flan-t5-xxl'       : flan_t5_xxl,
-        'code-davinci-002'  : code_davinci_002,
-        'text-ada-001'      : text_ada_001,
-        'text-babbage-001'  : text_babbage_001,
-        'text-curie-001'    : text_curie_001,
-        'text-davinci-002'  : text_davinci_002,
-        'text-davinci-003'  : text_davinci_003,
-        'llama13b-v2-chat'  : llama13b_v2_chat,
-        'llama7b-v2-chat'   : llama7b_v2_chat,
-        
-        'oasst-sft-1-pythia-12b'           : oasst_sft_1_pythia_12b,
-        'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
-        'command-light-nightly'            : command_light_nightly,
-    }
diff --git a/spaces/AfrodreamsAI/afrodreams/ex_app.py b/spaces/AfrodreamsAI/afrodreams/ex_app.py
deleted file mode 100644
index 94fbdab3b3266feff108e8004028b9134cacb7af..0000000000000000000000000000000000000000
--- a/spaces/AfrodreamsAI/afrodreams/ex_app.py
+++ /dev/null
@@ -1,95 +0,0 @@
-import neural_style
-import streamlit as st
-import os 
-import random
-import numpy as np
-from  PIL import Image, ImageEnhance
-from io import BytesIO
-#import streamlit_ext as ste #for download button not to rerun
-from huggingface_hub import upload_file
-
-HF_TOKEN = os.environ.get("HF_TOKEN")
-
-st.set_page_config(layout="wide")
-#Create two columns with different width
-col1, col2 = st.columns( [0.8, 0.2])
-with col1:               # To display the header text using css style
-    st.markdown(""" <style> .font {
-    font-size:35px ; font-family: 'Cooper Black'; color: #FF9633;} 
-    </style> """, unsafe_allow_html=True)
-    st.markdown('<p class="font">Upload your photo here...</p>', unsafe_allow_html=True)
-    st.subheader("This app takes in your image and styles it with a unique african art.")
-    
-#Add a header and expander in side bar
-st.sidebar.markdown('<p class="font">Afrodreams.AI</p>', unsafe_allow_html=True)
-with st.sidebar.expander("About the App"):
-     st.write("""
-        This app takes in your image and styles it with a unique african art.""")
-
-
-#Add file uploader to allow users to upload photos
-uploaded_file = st.file_uploader("", type=['jpg','png','jpeg'])
-
-# add slider to side bar
-style_weight = st.slider("Select Style Weight", min_value=10, max_value=100, value=12)
-
-#Add 'before' and 'after' columns
-if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    
-    col1, col2 = st.columns( [0.5, 0.5])
-    with col1:
-        st.markdown('<p style="text-align: center;">Before</p>',unsafe_allow_html=True)
-        st.image(image,width=300)  
-
-    with col2:
-        st.markdown('<p style="text-align: center;">After</p>',unsafe_allow_html=True)
-        
-    # add a button
-    run = st.button('Generate Art')
-    my_bar = st.progress(0)
-    params = neural_style.TransferParams()
-    params.gpu = 0#"c"
-    params.backend = "mkl"
-    params.image_size = 400
-    params.content_image = uploaded_file
-    params.style_weight = style_weight
-    keep_style = False
-    if run==True:
-        # run image selection if keep style is false
-        if keep_style==False:
-            path = 'stylesv2'
-            styles = os.listdir(path)
-            params.style_image = path + '/' + random.choice(styles)
-            
-        st.session_state.submitted = True   
-        with st.spinner('Wait for it...'): 
-            neural_style.transfer(params)
-
-        #display image when done.
-        with col2:
-            if 'submitted' in st.session_state:
-                result = Image.open('out.png')
-                st.image(result, width=300)
-                buf = BytesIO()
-                result.save(buf, format="png")
-                if len(os.listdir('generated_samples')) <= 10:
-                    img_file_name = f"generated_samples/{str(len(os.listdir('generated_samples')))}.png"
-                
-                    _ = upload_file(path_or_fileobj = 'out.png',
-                            path_in_repo = img_file_name,
-                            repo_id='AfrodreamsAI/afrodreams',
-                            repo_type='space',
-                            token=HF_TOKEN
-                        ) 
-                    
-                byte_im = buf.getvalue()
-                #run =ste.download_button(button_text="Download Image", data=byte_im, download_filename='afrodreams.jpg', mime="image/png")
-        #keeping the current style by update the weight 
-        keep_style = st.sidebar.checkbox("Keep current style")
-        
-    
-    
-
-
-
diff --git a/spaces/AlexWortega/food_calories/app.py b/spaces/AlexWortega/food_calories/app.py
deleted file mode 100644
index 779d200948b5700d083debcc784294b6bc8b70ac..0000000000000000000000000000000000000000
--- a/spaces/AlexWortega/food_calories/app.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import torch
-from rudalle import get_tokenizer, get_vae
-from rudalle.utils import seed_everything
-
-import sys
-from rudolph.model.utils import get_i2t_attention_mask, get_t2t_attention_mask
-from rudolph.model import get_rudolph_model, ruDolphModel, FP16Module
-from rudolph.pipelines import generate_codebooks, self_reranking_by_image, self_reranking_by_text, show, generate_captions, generate_texts 
-from rudolph.pipelines import  zs_clf
-
-import gradio as gr
-from rudolph import utils
-from PIL import Image
-
-device = 'cpu'
-if device=='cuda':
-  half = True
-else:
-  half = False
-model = get_rudolph_model('350M',  fp16=half, device=device)
-model.load_state_dict(torch.load("awesomemodel__dalle_1500.pt",map_location=torch.device('cpu')))
-tokenizer = get_tokenizer()
-vae = get_vae(dwt=False).to(device)
-
-
-template = 'белков: ' 
-
-
-
-# Download human-readable labels for ImageNet.
-
-
-
-def classify_image(inp):
-  print(type(inp))
-  inp =  Image.fromarray(inp)
-  texts = generate_captions(inp, tokenizer, model, vae, template=template,  top_k=16, captions_num=1, bs=16, top_p=0.6, seed=43,       temperature=0.8)
-  rp = texts[0].replace('белков','protein').replace('жиров','fat').replace('углеводов','carbs').replace('calories','ккал') 
-  print(rp)
-
-  
-  return rp
-
-image = gr.inputs.Image(shape=(128, 128))
-label = gr.outputs.Label(num_top_classes=3)
-
-
-iface = gr.Interface(fn=classify_image, description="https://github.com/sberbank-ai/ru-dolph RuDoplh by SBER AI finetuned for a image2text task to predict food calories by https://t.me/lovedeathtransformers Alex Wortega", inputs=image, outputs="text",examples=[
-  ['b9c277a3.jpeg']])
-iface.launch()
diff --git a/spaces/AllAideas/SegmentacionVideo/utils/predict.py b/spaces/AllAideas/SegmentacionVideo/utils/predict.py
deleted file mode 100644
index e4edb3d986d42fdd8dba8da9ab795350b3b2fa9f..0000000000000000000000000000000000000000
--- a/spaces/AllAideas/SegmentacionVideo/utils/predict.py
+++ /dev/null
@@ -1,104 +0,0 @@
-#from .custom_layers import TransformerEncoder, PositionalEmbedding
-from .constants import MAX_SEQ_LENGTH, NUM_FEATURES, IMG_SIZE, CLASS_VOCAB
-from huggingface_hub import from_pretrained_keras
-from tensorflow import keras
-from keras import layers
-import numpy as np
-import imageio
-import cv2
-
-#model = from_pretrained_keras("shivi/video-classification",custom_objects={"PositionalEmbedding":PositionalEmbedding,"TransformerEncoder": TransformerEncoder})
-
-model = from_pretrained_keras("keras-io/video-transformers")
-
-"""
-Below code is taken from the Video-Transformers example on keras-io by Sayak Paul
-"""
-def build_feature_extractor():
-    feature_extractor = keras.applications.DenseNet121(
-        weights="imagenet",
-        include_top=False,
-        pooling="avg",
-        input_shape=(IMG_SIZE, IMG_SIZE, 3),
-    )
-    preprocess_input = keras.applications.densenet.preprocess_input
-
-    inputs = keras.Input((IMG_SIZE, IMG_SIZE, 3))
-    preprocessed = preprocess_input(inputs)
-
-    outputs = feature_extractor(preprocessed)
-    return keras.Model(inputs, outputs, name="feature_extractor")
-
-
-feature_extractor = build_feature_extractor()
-
-
-
-def crop_center(frame):
-    center_crop_layer = layers.CenterCrop(IMG_SIZE, IMG_SIZE)
-    cropped = center_crop_layer(frame[None, ...])
-    cropped = cropped.numpy().squeeze()
-    return cropped
-
-def load_video(path, max_frames=0):
-    cap = cv2.VideoCapture(path)
-    frames = []
-    try:
-        while True:
-            ret, frame = cap.read()
-            if not ret:
-                break
-            frame = crop_center(frame)
-            frame = frame[:, :, [2, 1, 0]]
-            frames.append(frame)
-
-            if len(frames) == max_frames:
-                break
-    finally:
-        cap.release()
-    return np.array(frames)
-
-def prepare_single_video(frames):
-    frame_features = np.zeros(shape=(1, MAX_SEQ_LENGTH, NUM_FEATURES), dtype="float32")
-
-    # Pad shorter videos.
-    if len(frames) < MAX_SEQ_LENGTH:
-        diff = MAX_SEQ_LENGTH - len(frames)
-        padding = np.zeros((diff, IMG_SIZE, IMG_SIZE, 3))
-        frames = np.concatenate(frames, padding)
-
-    frames = frames[None, ...]
-
-    # Extract features from the frames of the current video.
-    for i, batch in enumerate(frames):
-        video_length = batch.shape[0]
-        length = min(MAX_SEQ_LENGTH, video_length)
-        for j in range(length):
-            if np.mean(batch[j, :]) > 0.0:
-                frame_features[i, j, :] = feature_extractor.predict(batch[None, j, :])
-            else:
-                frame_features[i, j, :] = 0.0
-
-    return frame_features
-
-
-def predict_action(path):
-    frames = load_video(path)
-    frame_features = prepare_single_video(frames)
-    probabilities = model.predict(frame_features)[0]
-    confidences = {}
-
-    for i in np.argsort(probabilities)[::-1]:
-        confidences[CLASS_VOCAB[i]] = float(probabilities[i])
-
-    gif_out = to_gif(frames[:MAX_SEQ_LENGTH])
-
-    print(confidences)
-    return confidences, gif_out
-
-
-def to_gif(images):
-    converted_images = images.astype(np.uint8)
-    imageio.mimsave("animation.gif", converted_images, fps=10)
-    return "animation.gif"
-
diff --git a/spaces/Aloento/9Nine-PITS/app.py b/spaces/Aloento/9Nine-PITS/app.py
deleted file mode 100644
index 90b8019a1d2a9af0ae4eef108a0e38193d898b7b..0000000000000000000000000000000000000000
--- a/spaces/Aloento/9Nine-PITS/app.py
+++ /dev/null
@@ -1,186 +0,0 @@
-import argparse
-
-import gradio as gr
-import torch
-
-import commons
-import utils
-from models import SynthesizerTrn
-from text import cleaned_text_to_sequence
-from text.cleaners import clean_text
-from text.symbols import symbols
-
-
-# we use Kyubyong/g2p for demo instead of our internal g2p
-# https://github.com/Kyubyong/g2p
-def get_text(text, hps):
-  cleaned_text, lang = clean_text(text)
-  text_norm = cleaned_text_to_sequence(cleaned_text)
-  if hps.data.add_blank:
-    text_norm, lang = commons.intersperse_with_language_id(text_norm, lang, 0)
-  text_norm = torch.LongTensor(text_norm)
-  lang = torch.LongTensor(lang)
-  return text_norm, lang, cleaned_text
-
-
-class GradioApp:
-
-  def __init__(self, args):
-    self.hps = utils.get_hparams_from_file(args.config)
-    self.device = "cpu"
-
-    self.net_g = SynthesizerTrn(
-      len(symbols),
-      self.hps.data.filter_length // 2 + 1,
-      self.hps.train.segment_size //
-      self.hps.data.hop_length,
-      midi_start=-5,
-      midi_end=75,
-      octave_range=24,
-      n_speakers=len(self.hps.data.speakers),
-      **self.hps.model
-    ).to(self.device)
-
-    _ = self.net_g.eval()
-    _ = utils.load_checkpoint(args.checkpoint_path, model_g=self.net_g)
-    self.interface = self._gradio_interface()
-
-  def get_phoneme(self, text):
-    cleaned_text, lang = clean_text(text)
-    text_norm = cleaned_text_to_sequence(cleaned_text)
-
-    if self.hps.data.add_blank:
-      text_norm, lang = commons.intersperse_with_language_id(text_norm, lang, 0)
-
-    text_norm = torch.LongTensor(text_norm)
-    lang = torch.LongTensor(lang)
-
-    return text_norm, lang, cleaned_text
-
-  def inference(self, text, speaker_id_val, seed, scope_shift, duration):
-    seed = int(seed)
-    scope_shift = int(scope_shift)
-    torch.manual_seed(seed)
-    text_norm, tone, phones = self.get_phoneme(text)
-    x_tst = text_norm.to(self.device).unsqueeze(0)
-    t_tst = tone.to(self.device).unsqueeze(0)
-    x_tst_lengths = torch.LongTensor([text_norm.size(0)]).to(self.device)
-    speaker_id = torch.LongTensor([speaker_id_val]).to(self.device)
-
-    decoder_inputs, *_ = self.net_g.infer_pre_decoder(
-      x_tst,
-      t_tst,
-      x_tst_lengths,
-      sid=speaker_id,
-      noise_scale=0.667,
-      noise_scale_w=0.8,
-      length_scale=duration,
-      scope_shift=scope_shift
-    )
-
-    audio = self.net_g.infer_decode_chunk(
-      decoder_inputs, sid=speaker_id
-    )[0, 0].data.cpu().float().numpy()
-
-    del decoder_inputs,
-
-    return phones, (self.hps.data.sampling_rate, audio)
-
-  def _gradio_interface(self):
-    title = "9Nine - PITS"
-
-    self.inputs = [
-      gr.Textbox(
-        label="Text (150 words limitation)",
-        value="[JA]そんなわけないじゃない。どうしてこうなるだろう。始めて好きな人ができた。一生ものの友达ができた。嬉しいことが二つ重なて。"
-              "その二つの嬉しさがまたたくさんの嬉しさをつれて来てくれて。梦のように幸せの时间を手に入れたはずなのに。なのにどうして、こうなちょうだろう。[JA]",
-        elem_id="tts-input"
-      ),
-      gr.Dropdown(
-        list(self.hps.data.speakers),
-        value=self.hps.data.speakers[1],
-        label="Speaker Identity",
-        type="index"
-      ),
-      gr.Slider(
-        0, 65536, value=0, step=1, label="random seed"
-      ),
-      gr.Slider(
-        -15, 15, value=0, step=1, label="scope-shift"
-      ),
-      gr.Slider(
-        0.5, 2., value=1., step=0.1, label="duration multiplier"
-      ),
-    ]
-
-    self.outputs = [
-      gr.Textbox(label="Phonemes"),
-      gr.Audio(type="numpy", label="Output audio")
-    ]
-
-    description = "9Nine - PITS"
-    article = "Github: https://github.com/Aloento/VariTTS"
-    examples = [["[JA]こんにちは、私は綾地寧々です。[JA]"]]
-
-    return gr.Interface(
-      fn=self.inference,
-      inputs=self.inputs,
-      outputs=self.outputs,
-      title=title,
-      description=description,
-      article=article,
-      cache_examples=False,
-      examples=examples,
-    )
-
-  def launch(self):
-    return self.interface.launch(share=False)
-
-
-def parsearg():
-  parser = argparse.ArgumentParser()
-  parser.add_argument(
-    '-c',
-    '--config',
-    type=str,
-    default="./configs/config_cje.yaml",
-    help='Path to configuration file'
-  )
-  parser.add_argument(
-    '-m',
-    '--model',
-    type=str,
-    default='9Nine',
-    help='Model name'
-  )
-  parser.add_argument(
-    '-r',
-    '--checkpoint_path',
-    type=str,
-    default='./9Nine_Eval_71200.pth',
-    help='Path to checkpoint for resume'
-  )
-  parser.add_argument(
-    '-f',
-    '--force_resume',
-    type=str,
-    help='Path to checkpoint for force resume'
-  )
-  parser.add_argument(
-    '-d',
-    '--dir',
-    type=str,
-    default='/DATA/audio/pits_samples',
-    help='root dir'
-  )
-  args = parser.parse_args()
-  return args
-
-
-if __name__ == "__main__":
-  import nltk
-  nltk.download('cmudict')
-
-  args = parsearg()
-  app = GradioApp(args)
-  app.launch()
diff --git a/spaces/Amon1/ChatGPTForAcadamic/crazy_functions/test_project/cpp/cppipc/policy.h b/spaces/Amon1/ChatGPTForAcadamic/crazy_functions/test_project/cpp/cppipc/policy.h
deleted file mode 100644
index f88ab5d8cb343f97026966b402eaeed8831e356a..0000000000000000000000000000000000000000
--- a/spaces/Amon1/ChatGPTForAcadamic/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/Andy1621/uniformer_image_segmentation/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py
deleted file mode 100644
index 23a81eb7ef56a4cd8e7c9da65b86f3d0e562001a..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py
+++ /dev/null
@@ -1,9 +0,0 @@
-_base_ = [
-    '../_base_/models/pspnet_r50-d8.py',
-    '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
-    '../_base_/schedules/schedule_80k.py'
-]
-model = dict(
-    decode_head=dict(align_corners=True),
-    auxiliary_head=dict(align_corners=True),
-    test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
diff --git a/spaces/Andy1621/uniformer_light/app.py b/spaces/Andy1621/uniformer_light/app.py
deleted file mode 100644
index c2a797e2631f98fea83af0dca46363f58f8836fa..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_light/app.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import os
-
-import torch
-import torch.nn as nn
-import numpy as np
-import torch.nn.functional as F
-import torchvision.transforms as T
-from PIL import Image
-from decord import VideoReader
-from decord import cpu
-from uniformer_light_video import uniformer_xxs_video
-from uniformer_light_image import uniformer_xxs_image
-from kinetics_class_index import kinetics_classnames
-from imagenet_class_index import imagenet_classnames
-from transforms import (
-    GroupNormalize, GroupScale, GroupCenterCrop, 
-    Stack, ToTorchFormatTensor
-)
-
-import gradio as gr
-from huggingface_hub import hf_hub_download
-
-
-# Device on which to run the model
-# Set to cuda to load on GPU
-device = "cpu"
-model_video_path = hf_hub_download(repo_id="Andy1621/uniformer_light", filename="uniformer_xxs16_160_k400.pth")
-model_image_path = hf_hub_download(repo_id="Andy1621/uniformer_light", filename="uniformer_xxs_160_in1k.pth")
-# Pick a pretrained model 
-model_video = uniformer_xxs_video()
-model_video.load_state_dict(torch.load(model_video_path, map_location='cpu'))
-model_image = uniformer_xxs_image()
-model_image.load_state_dict(torch.load(model_image_path, map_location='cpu'))
-# Set to eval mode and move to desired device
-model_video = model_video.to(device).eval()
-model_image = model_image.to(device).eval()
-
-# Create an id to label name mapping
-kinetics_id_to_classname = {}
-for k, v in kinetics_classnames.items():
-    kinetics_id_to_classname[k] = v
-imagenet_id_to_classname = {}
-for k, v in imagenet_classnames.items():
-    imagenet_id_to_classname[k] = v[1] 
-
-
-def get_index(num_frames, num_segments=8):
-    seg_size = float(num_frames - 1) / num_segments
-    start = int(seg_size / 2)
-    offsets = np.array([
-        start + int(np.round(seg_size * idx)) for idx in range(num_segments)
-    ])
-    return offsets
-
-
-def load_video(video_path):
-    vr = VideoReader(video_path, ctx=cpu(0))
-    num_frames = len(vr)
-    frame_indices = get_index(num_frames, 16)
-
-    # transform
-    crop_size = 160
-    scale_size = 160
-    input_mean = [0.485, 0.456, 0.406]
-    input_std = [0.229, 0.224, 0.225]
-
-    transform = T.Compose([
-        GroupScale(int(scale_size)),
-        GroupCenterCrop(crop_size),
-        Stack(),
-        ToTorchFormatTensor(),
-        GroupNormalize(input_mean, input_std) 
-    ])
-
-    images_group = list()
-    for frame_index in frame_indices:
-        img = Image.fromarray(vr[frame_index].asnumpy())
-        images_group.append(img)
-    torch_imgs = transform(images_group)
-    return torch_imgs
-    
-
-def inference_video(video):
-    vid = load_video(video)
-    
-    # The model expects inputs of shape: B x C x H x W
-    TC, H, W = vid.shape
-    inputs = vid.reshape(1, TC//3, 3, H, W).permute(0, 2, 1, 3, 4)
-    
-    with torch.no_grad():
-        prediction = model_video(inputs)
-        prediction = F.softmax(prediction, dim=1).flatten()
-
-    return {kinetics_id_to_classname[str(i)]: float(prediction[i]) for i in range(400)}
-    
-
-def set_example_video(example: list) -> dict:
-    return gr.Video.update(value=example[0])
-
-
-def inference_image(img):
-    image = img
-    image_transform = T.Compose(
-    [
-        T.Resize(224),
-        T.CenterCrop(224),
-        T.ToTensor(),
-        T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
-    ]
-    )
-    image = image_transform(image)
-    
-    # The model expects inputs of shape: B x C x H x W
-    image = image.unsqueeze(0)
-    
-    with torch.no_grad():
-        prediction = model_image(image)
-        prediction = F.softmax(prediction, dim=1).flatten()
-
-    return {imagenet_id_to_classname[str(i)]: float(prediction[i]) for i in range(1000)}
-
-
-def set_example_image(example: list) -> dict:
-    return gr.Image.update(value=example[0])
-
-
-demo = gr.Blocks()
-with demo:
-    gr.Markdown(
-        """
-        # UniFormer Light
-        Gradio demo for <a href='https://github.com/Sense-X/UniFormer' target='_blank'>UniFormer</a>: To use it, simply upload your video, or click one of the examples to load them. Read more at the links below.
-        """
-    )
-
-    with gr.Tab("Video"):
-        with gr.Box():
-            with gr.Row():
-                with gr.Column():
-                    with gr.Row():
-                        input_video = gr.Video(label='Input Video').style(height=360)
-                    with gr.Row():
-                        submit_video_button = gr.Button('Submit')
-                with gr.Column():
-                        label_video = gr.Label(num_top_classes=5)
-            with gr.Row():
-                example_videos = gr.Dataset(components=[input_video], samples=[['./videos/hitting_baseball.mp4'], ['./videos/hoverboarding.mp4'], ['./videos/yoga.mp4']])
-        
-    with gr.Tab("Image"):
-        with gr.Box():
-            with gr.Row():
-                with gr.Column():
-                    with gr.Row():
-                        input_image = gr.Image(label='Input Image', type='pil').style(height=360)
-                    with gr.Row():
-                        submit_image_button = gr.Button('Submit')
-                with gr.Column():
-                    label_image = gr.Label(num_top_classes=5)
-            with gr.Row():
-                example_images = gr.Dataset(components=[input_image], samples=[['./images/cat.png'], ['./images/dog.png'], ['./images/panda.png']])
-
-    gr.Markdown(
-        """
-        <p style='text-align: center'><a href='https://arxiv.org/abs/2201.09450' target='_blank'>[TPAMI] UniFormer: Unifying Convolution and Self-attention for Visual Recognition</a> | <a href='https://github.com/Sense-X/UniFormer' target='_blank'>Github Repo</a></p>
-        """
-    )
-
-    submit_video_button.click(fn=inference_video, inputs=input_video, outputs=label_video)
-    example_videos.click(fn=set_example_video, inputs=example_videos, outputs=example_videos.components)
-    submit_image_button.click(fn=inference_image, inputs=input_image, outputs=label_image)
-    example_images.click(fn=set_example_image, inputs=example_images, outputs=example_images.components)
-
-demo.launch(enable_queue=True)
\ No newline at end of file
diff --git a/spaces/AngoHF/ANGO-Leaderboard/assets/evaluation.py b/spaces/AngoHF/ANGO-Leaderboard/assets/evaluation.py
deleted file mode 100644
index b2c625686ed23aa67c42815d4ddf372344e8daec..0000000000000000000000000000000000000000
--- a/spaces/AngoHF/ANGO-Leaderboard/assets/evaluation.py
+++ /dev/null
@@ -1,185 +0,0 @@
-import os
-import json
-import re
-import argparse
-import torch
-import gc
-from tqdm import tqdm
-
-from transformers import AutoModelForCausalLM, AutoModel, AutoTokenizer
-
-os.environ['CUDA_VISIBLE_DEVICES'] = '1'
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description='Validation')
-    parser.add_argument('--model_path', dest="model_path")
-    parser.add_argument('--dataset_path', dest="dataset_path")
-    parser.add_argument('--save_path', dest='save_path')
-    parser.add_argument('--max_length', dest="max_length", default=2000)
-    parser.add_argument('--max_new_tokens', dest="max_new_tokens", default=48)
-    parser.add_argument('--input_template', dest="input_template",
-                        default="材料：{material}\n问题：{question}\n{options}\n答案：{response}")
-    parser.add_argument('--query_template', dest="query_template", default="问题：{question}\n{options}\n答案：{response}")
-    parser.add_argument('--system_prompt', dest="system_prompt",
-                        default="你是一名考生，请回答问题的正确选项，比如C。如果有多个正确选项，请按顺序回答所有正确选项，比如ABD。")
-    parser.add_argument('--level_delimiter', dest="level_delimiter", default="|")
-    args = parser.parse_args()
-    return args
-
-
-class Validator:
-    def __init__(self, args):
-        self.load_model(args.model_path)
-        self.load_dataset(args.dataset_path)
-        self.save_dir = os.path.join(args.save_path, os.path.split(model_path)[-1])
-        if not os.path.exists(self.save_dir):
-            os.makedirs(self.save_dir)
-
-        self.max_length = args.max_length
-        self.max_new_tokens = args.max_new_tokens
-        self.input_template = args.input_template
-        self.query_template = args.query_template
-        self.system_prompt = args.system_prompt
-        self.level_delimiter = args.level_delimiter
-
-    def load_model(self, model_path):
-        self.tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
-
-        self.model = AutoModelForCausalLM.from_pretrained(model_path, device_map={"": 0}, trust_remote_code=True)
-        self.model.eval()
-
-    def load_dataset(self, dataset_path):
-        self.dataset = json.load(open(dataset_path, encoding="utf-8"))
-
-    def format_prompt(self, material, question, options, response):
-        if material:
-            return self.input_template.format(material=material, question=question, options=options,
-                                              response=response).strip()
-        return self.query_template.format(question=question, options=options, response=response).strip()
-
-    def build_prompt(self, item):
-        query_prompt = self.format_prompt(item['material'], item['question'], item['options'], "")
-        history_prompts = []
-        for sub in item['history']:
-            history_prompts.append(self.format_prompt(sub['material'], sub['question'], sub['options'], sub['choice']))
-
-            final_prompt = self.system_prompt + "\n" + "\n".join(history_prompts) + "\n" + query_prompt
-
-            if len(self.tokenizer.tokenize(final_prompt)) > self.max_length:
-                history_prompts.pop()
-                break
-        return self.system_prompt + "\n" + "\n".join(history_prompts) + "\n" + query_prompt
-
-    def get_predict(self, prompt):
-        gen_kwargs = {"do_sample": False, "max_new_tokens": self.max_new_tokens}
-        inputs = self.tokenizer([prompt], return_tensors="pt")
-        inputs = inputs.to(self.model.device)
-        with torch.no_grad():
-            outputs = self.model.generate(**inputs, return_dict_in_generate=True, **gen_kwargs)
-        predict = self.tokenizer.decode(outputs.sequences[0], skip_special_tokens=True)[len(prompt):]
-        return predict
-
-    def extract_answer(self, results):
-        predict_result = {"acc": 0, "wrong_value": 0, "human_acc": 0, "hit": 0, "total": 0, "wrong_hit": 0,
-                          "wrong_total": 0, 'detail': []}
-        for result in results:
-            answer = result['item']['choice']
-            most_wrong = result['item']['most_wrong']
-            human_acc = result['item']['human_acc'] * 0.01
-
-            predict = ""
-            for e in re.split(r'[、,.，和\s]\s*', result['predict']):
-                if not e.isascii():
-                    break
-                predict += e
-            result['predict'] = predict
-            predict_result['detail'].append(
-                {"answer": answer, "most_wrong": most_wrong, "predict": predict, "human_acc": human_acc})
-            predict_result['hit'] += 1 if answer == predict else 0
-            predict_result['wrong_hit'] += 1 if most_wrong == predict else 0
-            predict_result['wrong_value'] += 1 - human_acc if most_wrong == predict else 0
-            predict_result['human_acc'] += human_acc
-            predict_result['total'] += 1
-        predict_result['acc'] = predict_result['hit'] / predict_result['total']
-        predict_result['wrong_total'] = predict_result['total'] - predict_result['hit']
-        predict_result['wrong_value'] = predict_result['wrong_value'] / predict_result['wrong_total']
-        predict_result['human_acc'] = predict_result['human_acc'] / len(results)
-
-        json.dump(predict_result, open(os.path.join(self.save_dir, "acc_result.json"), "w", encoding="utf-8"),
-                  ensure_ascii=False)
-
-    def category_summary(self, results):
-        category_result = {"总计": {"hit": 0, "all": 0, "difficulty": {}, "human_acc": 0}}
-        for result in results:
-            hit = 1 if result['item']['choice'] == result['predict'] else 0
-            categories_list = result['item']['categories']
-            difficulty = result['item']['difficulty']
-            human_acc = result['item']['human_acc']
-            for categories in categories_list:
-                if difficulty not in category_result["总计"]["difficulty"]:
-                    category_result["总计"]["difficulty"][difficulty] = {"hit": 0, "all": 0}
-                category_result["总计"]["difficulty"][difficulty]['hit'] += hit
-                category_result["总计"]["difficulty"][difficulty]['all'] += 1
-                category_result["总计"]['hit'] += hit
-                category_result["总计"]['all'] += 1
-                category_result["总计"]['human_acc'] += human_acc
-                category_subset = []
-                for category in categories:
-                    category_subset.append(category)
-                    category_name = self.level_delimiter.join(category_subset)
-                    if not category_name:
-                        category_name = "未分类"
-                    if category_name not in category_result:
-                        category_result[category_name] = {"hit": 0, "all": 0, "difficulty": {}, "human_acc": 0}
-                    if difficulty not in category_result[category_name]["difficulty"]:
-                        category_result[category_name]["difficulty"][difficulty] = {"hit": 0, "all": 0}
-                    category_result[category_name]["difficulty"][difficulty]['hit'] += hit
-                    category_result[category_name]["difficulty"][difficulty]['all'] += 1
-                    category_result[category_name]['hit'] += hit
-                    category_result[category_name]['all'] += 1
-                    category_result[category_name]['human_acc'] += human_acc
-
-        for k, v in category_result.items():
-            v['acc'] = v['hit'] / v['all']
-            v['human_acc'] = v['human_acc'] / v['all']
-            for d, sub_v in v['difficulty'].items():
-                sub_v['acc'] = sub_v['hit'] / sub_v['all']
-        json.dump(category_result, open(os.path.join(self.save_dir, "category_result.json"), "w", encoding="utf-8"),
-                  ensure_ascii=False)
-
-    def difficulty_summary(self, results):
-        difficulty_result = {"总计": {"hit": 0, "all": 0}}
-        for result in results:
-            hit = 1 if result['item']['choice'] == result['predict'] else 0
-            difficulty = result['item']['difficulty']
-            if difficulty not in difficulty_result:
-                difficulty_result[difficulty] = {"hit": 0, "all": 0}
-            difficulty_result[difficulty]['hit'] += hit
-            difficulty_result[difficulty]['all'] += 1
-            difficulty_result["总计"]['hit'] += hit
-            difficulty_result["总计"]['all'] += 1
-
-        for k in difficulty_result:
-            difficulty_result[k]['acc'] = difficulty_result[k]['hit'] / difficulty_result[k]['all']
-
-        json.dump(difficulty_result, open(os.path.join(self.save_dir, "difficulty_result.json"), "w", encoding="utf-8"),
-                  ensure_ascii=False)
-
-    def __call__(self):
-        results = []
-        for item in tqdm(self.dataset):
-            prompt = self.build_prompt(item)
-            predict = self.get_predict(prompt)
-            results.append({"item": item, "predict": predict})
-            gc.collect()
-
-        json.dump(results, open(os.path.join(self.save_dir, "raw.json"), "w", encoding="utf-8"), ensure_ascii=False)
-        self.extract_answer(results)
-        self.category_summary(results)
-        self.difficulty_summary(results)
-
-
-if __name__ == "__main__":
-    args = parse_args()
-    Validator(args)()
diff --git a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/api-examples/api-example.py b/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/api-examples/api-example.py
deleted file mode 100644
index d9fd60d05c95d76d2ce011fa5ecdd97433b5e3de..0000000000000000000000000000000000000000
--- a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/api-examples/api-example.py
+++ /dev/null
@@ -1,63 +0,0 @@
-import requests
-
-# For local streaming, the websockets are hosted without ssl - http://
-HOST = 'localhost:5000'
-URI = f'http://{HOST}/api/v1/generate'
-
-# For reverse-proxied streaming, the remote will likely host with ssl - https://
-# URI = 'https://your-uri-here.trycloudflare.com/api/v1/generate'
-
-
-def run(prompt):
-    request = {
-        'prompt': prompt,
-        'max_new_tokens': 250,
-        'auto_max_new_tokens': False,
-        'max_tokens_second': 0,
-
-        # Generation params. If 'preset' is set to different than 'None', the values
-        # in presets/preset-name.yaml are used instead of the individual numbers.
-        'preset': 'None',
-        'do_sample': True,
-        'temperature': 0.7,
-        'top_p': 0.1,
-        'typical_p': 1,
-        'epsilon_cutoff': 0,  # In units of 1e-4
-        'eta_cutoff': 0,  # In units of 1e-4
-        'tfs': 1,
-        'top_a': 0,
-        'repetition_penalty': 1.18,
-        'repetition_penalty_range': 0,
-        'top_k': 40,
-        'min_length': 0,
-        'no_repeat_ngram_size': 0,
-        'num_beams': 1,
-        'penalty_alpha': 0,
-        'length_penalty': 1,
-        'early_stopping': False,
-        'mirostat_mode': 0,
-        'mirostat_tau': 5,
-        'mirostat_eta': 0.1,
-        'grammar_string': '',
-        'guidance_scale': 1,
-        'negative_prompt': '',
-
-        'seed': -1,
-        'add_bos_token': True,
-        'truncation_length': 2048,
-        'ban_eos_token': False,
-        'custom_token_bans': '',
-        'skip_special_tokens': True,
-        'stopping_strings': []
-    }
-
-    response = requests.post(URI, json=request)
-
-    if response.status_code == 200:
-        result = response.json()['results'][0]['text']
-        print(prompt + result)
-
-
-if __name__ == '__main__':
-    prompt = "In order to make homemade bread, follow these steps:\n1)"
-    run(prompt)
diff --git a/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/guided_diffusion/guided_diffusion/fp16_util.py b/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/guided_diffusion/guided_diffusion/fp16_util.py
deleted file mode 100644
index 35a3f461d6d5469719d7734d03056544643d44db..0000000000000000000000000000000000000000
--- a/spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/guided_diffusion/guided_diffusion/fp16_util.py
+++ /dev/null
@@ -1,236 +0,0 @@
-"""
-Helpers to train with 16-bit precision.
-"""
-
-import numpy as np
-import torch as th
-import torch.nn as nn
-from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
-
-from . import logger
-
-INITIAL_LOG_LOSS_SCALE = 20.0
-
-
-def convert_module_to_f16(l):
-    """
-    Convert primitive modules to float16.
-    """
-    if isinstance(l, (nn.Conv1d, nn.Conv2d, nn.Conv3d)):
-        l.weight.data = l.weight.data.half()
-        if l.bias is not None:
-            l.bias.data = l.bias.data.half()
-
-
-def convert_module_to_f32(l):
-    """
-    Convert primitive modules to float32, undoing convert_module_to_f16().
-    """
-    if isinstance(l, (nn.Conv1d, nn.Conv2d, nn.Conv3d)):
-        l.weight.data = l.weight.data.float()
-        if l.bias is not None:
-            l.bias.data = l.bias.data.float()
-
-
-def make_master_params(param_groups_and_shapes):
-    """
-    Copy model parameters into a (differently-shaped) list of full-precision
-    parameters.
-    """
-    master_params = []
-    for param_group, shape in param_groups_and_shapes:
-        master_param = nn.Parameter(
-            _flatten_dense_tensors(
-                [param.detach().float() for (_, param) in param_group]
-            ).view(shape)
-        )
-        master_param.requires_grad = True
-        master_params.append(master_param)
-    return master_params
-
-
-def model_grads_to_master_grads(param_groups_and_shapes, master_params):
-    """
-    Copy the gradients from the model parameters into the master parameters
-    from make_master_params().
-    """
-    for master_param, (param_group, shape) in zip(
-        master_params, param_groups_and_shapes
-    ):
-        master_param.grad = _flatten_dense_tensors(
-            [param_grad_or_zeros(param) for (_, param) in param_group]
-        ).view(shape)
-
-
-def master_params_to_model_params(param_groups_and_shapes, master_params):
-    """
-    Copy the master parameter data back into the model parameters.
-    """
-    # Without copying to a list, if a generator is passed, this will
-    # silently not copy any parameters.
-    for master_param, (param_group, _) in zip(master_params, param_groups_and_shapes):
-        for (_, param), unflat_master_param in zip(
-            param_group, unflatten_master_params(param_group, master_param.view(-1))
-        ):
-            param.detach().copy_(unflat_master_param)
-
-
-def unflatten_master_params(param_group, master_param):
-    return _unflatten_dense_tensors(master_param, [param for (_, param) in param_group])
-
-
-def get_param_groups_and_shapes(named_model_params):
-    named_model_params = list(named_model_params)
-    scalar_vector_named_params = (
-        [(n, p) for (n, p) in named_model_params if p.ndim <= 1],
-        (-1),
-    )
-    matrix_named_params = (
-        [(n, p) for (n, p) in named_model_params if p.ndim > 1],
-        (1, -1),
-    )
-    return [scalar_vector_named_params, matrix_named_params]
-
-
-def master_params_to_state_dict(
-    model, param_groups_and_shapes, master_params, use_fp16
-):
-    if use_fp16:
-        state_dict = model.state_dict()
-        for master_param, (param_group, _) in zip(
-            master_params, param_groups_and_shapes
-        ):
-            for (name, _), unflat_master_param in zip(
-                param_group, unflatten_master_params(param_group, master_param.view(-1))
-            ):
-                assert name in state_dict
-                state_dict[name] = unflat_master_param
-    else:
-        state_dict = model.state_dict()
-        for i, (name, _value) in enumerate(model.named_parameters()):
-            assert name in state_dict
-            state_dict[name] = master_params[i]
-    return state_dict
-
-
-def state_dict_to_master_params(model, state_dict, use_fp16):
-    if use_fp16:
-        named_model_params = [
-            (name, state_dict[name]) for name, _ in model.named_parameters()
-        ]
-        param_groups_and_shapes = get_param_groups_and_shapes(named_model_params)
-        master_params = make_master_params(param_groups_and_shapes)
-    else:
-        master_params = [state_dict[name] for name, _ in model.named_parameters()]
-    return master_params
-
-
-def zero_master_grads(master_params):
-    for param in master_params:
-        param.grad = None
-
-
-def zero_grad(model_params):
-    for param in model_params:
-        # Taken from https://pytorch.org/docs/stable/_modules/torch/optim/optimizer.html#Optimizer.add_param_group
-        if param.grad is not None:
-            param.grad.detach_()
-            param.grad.zero_()
-
-
-def param_grad_or_zeros(param):
-    if param.grad is not None:
-        return param.grad.data.detach()
-    else:
-        return th.zeros_like(param)
-
-
-class MixedPrecisionTrainer:
-    def __init__(
-        self,
-        *,
-        model,
-        use_fp16=False,
-        fp16_scale_growth=1e-3,
-        initial_lg_loss_scale=INITIAL_LOG_LOSS_SCALE,
-    ):
-        self.model = model
-        self.use_fp16 = use_fp16
-        self.fp16_scale_growth = fp16_scale_growth
-
-        self.model_params = list(self.model.parameters())
-        self.master_params = self.model_params
-        self.param_groups_and_shapes = None
-        self.lg_loss_scale = initial_lg_loss_scale
-
-        if self.use_fp16:
-            self.param_groups_and_shapes = get_param_groups_and_shapes(
-                self.model.named_parameters()
-            )
-            self.master_params = make_master_params(self.param_groups_and_shapes)
-            self.model.convert_to_fp16()
-
-    def zero_grad(self):
-        zero_grad(self.model_params)
-
-    def backward(self, loss: th.Tensor):
-        if self.use_fp16:
-            loss_scale = 2 ** self.lg_loss_scale
-            (loss * loss_scale).backward()
-        else:
-            loss.backward()
-
-    def optimize(self, opt: th.optim.Optimizer):
-        if self.use_fp16:
-            return self._optimize_fp16(opt)
-        else:
-            return self._optimize_normal(opt)
-
-    def _optimize_fp16(self, opt: th.optim.Optimizer):
-        logger.logkv_mean("lg_loss_scale", self.lg_loss_scale)
-        model_grads_to_master_grads(self.param_groups_and_shapes, self.master_params)
-        grad_norm, param_norm = self._compute_norms(grad_scale=2 ** self.lg_loss_scale)
-        if check_overflow(grad_norm):
-            self.lg_loss_scale -= 1
-            logger.log(f"Found NaN, decreased lg_loss_scale to {self.lg_loss_scale}")
-            zero_master_grads(self.master_params)
-            return False
-
-        logger.logkv_mean("grad_norm", grad_norm)
-        logger.logkv_mean("param_norm", param_norm)
-
-        self.master_params[0].grad.mul_(1.0 / (2 ** self.lg_loss_scale))
-        opt.step()
-        zero_master_grads(self.master_params)
-        master_params_to_model_params(self.param_groups_and_shapes, self.master_params)
-        self.lg_loss_scale += self.fp16_scale_growth
-        return True
-
-    def _optimize_normal(self, opt: th.optim.Optimizer):
-        grad_norm, param_norm = self._compute_norms()
-        logger.logkv_mean("grad_norm", grad_norm)
-        logger.logkv_mean("param_norm", param_norm)
-        opt.step()
-        return True
-
-    def _compute_norms(self, grad_scale=1.0):
-        grad_norm = 0.0
-        param_norm = 0.0
-        for p in self.master_params:
-            with th.no_grad():
-                param_norm += th.norm(p, p=2, dtype=th.float32).item() ** 2
-                if p.grad is not None:
-                    grad_norm += th.norm(p.grad, p=2, dtype=th.float32).item() ** 2
-        return np.sqrt(grad_norm) / grad_scale, np.sqrt(param_norm)
-
-    def master_params_to_state_dict(self, master_params):
-        return master_params_to_state_dict(
-            self.model, self.param_groups_and_shapes, master_params, self.use_fp16
-        )
-
-    def state_dict_to_master_params(self, state_dict):
-        return state_dict_to_master_params(self.model, state_dict, self.use_fp16)
-
-
-def check_overflow(value):
-    return (value == float("inf")) or (value == -float("inf")) or (value != value)
diff --git a/spaces/Anonymous-sub/Rerender/gmflow_module/main.py b/spaces/Anonymous-sub/Rerender/gmflow_module/main.py
deleted file mode 100644
index 1b4c04adc27507ea86867d6e2bf2e0bfacc9233c..0000000000000000000000000000000000000000
--- a/spaces/Anonymous-sub/Rerender/gmflow_module/main.py
+++ /dev/null
@@ -1,557 +0,0 @@
-import torch
-from torch.utils.data import DataLoader
-from torch.utils.tensorboard import SummaryWriter
-
-import argparse
-import numpy as np
-import os
-
-from data import build_train_dataset
-from gmflow.gmflow import GMFlow
-from loss import flow_loss_func
-from evaluate import (validate_chairs, validate_things, validate_sintel, validate_kitti,
-                      create_sintel_submission, create_kitti_submission, inference_on_dir)
-
-from utils.logger import Logger
-from utils import misc
-from utils.dist_utils import get_dist_info, init_dist, setup_for_distributed
-
-
-def get_args_parser():
-    parser = argparse.ArgumentParser()
-
-    # dataset
-    parser.add_argument('--checkpoint_dir', default='tmp', type=str,
-                        help='where to save the training log and models')
-    parser.add_argument('--stage', default='chairs', type=str,
-                        help='training stage')
-    parser.add_argument('--image_size', default=[384, 512], type=int, nargs='+',
-                        help='image size for training')
-    parser.add_argument('--padding_factor', default=16, type=int,
-                        help='the input should be divisible by padding_factor, otherwise do padding')
-
-    parser.add_argument('--max_flow', default=400, type=int,
-                        help='exclude very large motions during training')
-    parser.add_argument('--val_dataset', default=['chairs'], type=str, nargs='+',
-                        help='validation dataset')
-    parser.add_argument('--with_speed_metric', action='store_true',
-                        help='with speed metric when evaluation')
-
-    # training
-    parser.add_argument('--lr', default=4e-4, type=float)
-    parser.add_argument('--batch_size', default=12, type=int)
-    parser.add_argument('--num_workers', default=4, type=int)
-    parser.add_argument('--weight_decay', default=1e-4, type=float)
-    parser.add_argument('--grad_clip', default=1.0, type=float)
-    parser.add_argument('--num_steps', default=100000, type=int)
-    parser.add_argument('--seed', default=326, type=int)
-    parser.add_argument('--summary_freq', default=100, type=int)
-    parser.add_argument('--val_freq', default=10000, type=int)
-    parser.add_argument('--save_ckpt_freq', default=10000, type=int)
-    parser.add_argument('--save_latest_ckpt_freq', default=1000, type=int)
-
-    # resume pretrained model or resume training
-    parser.add_argument('--resume', default=None, type=str,
-                        help='resume from pretrain model for finetuing or resume from terminated training')
-    parser.add_argument('--strict_resume', action='store_true')
-    parser.add_argument('--no_resume_optimizer', action='store_true')
-
-    # GMFlow model
-    parser.add_argument('--num_scales', default=1, type=int,
-                        help='basic gmflow model uses a single 1/8 feature, the refinement uses 1/4 feature')
-    parser.add_argument('--feature_channels', default=128, type=int)
-    parser.add_argument('--upsample_factor', default=8, type=int)
-    parser.add_argument('--num_transformer_layers', default=6, type=int)
-    parser.add_argument('--num_head', default=1, type=int)
-    parser.add_argument('--attention_type', default='swin', type=str)
-    parser.add_argument('--ffn_dim_expansion', default=4, type=int)
-
-    parser.add_argument('--attn_splits_list', default=[2], type=int, nargs='+',
-                        help='number of splits in attention')
-    parser.add_argument('--corr_radius_list', default=[-1], type=int, nargs='+',
-                        help='correlation radius for matching, -1 indicates global matching')
-    parser.add_argument('--prop_radius_list', default=[-1], type=int, nargs='+',
-                        help='self-attention radius for flow propagation, -1 indicates global attention')
-
-    # loss
-    parser.add_argument('--gamma', default=0.9, type=float,
-                        help='loss weight')
-
-    # evaluation
-    parser.add_argument('--eval', action='store_true')
-    parser.add_argument('--save_eval_to_file', action='store_true')
-    parser.add_argument('--evaluate_matched_unmatched', action='store_true')
-
-    # inference on a directory
-    parser.add_argument('--inference_dir', default=None, type=str)
-    parser.add_argument('--inference_size', default=None, type=int, nargs='+',
-                        help='can specify the inference size')
-    parser.add_argument('--dir_paired_data', action='store_true',
-                        help='Paired data in a dir instead of a sequence')
-    parser.add_argument('--save_flo_flow', action='store_true')
-    parser.add_argument('--pred_bidir_flow', action='store_true',
-                        help='predict bidirectional flow')
-    parser.add_argument('--fwd_bwd_consistency_check', action='store_true',
-                        help='forward backward consistency check with bidirection flow')
-
-    # predict on sintel and kitti test set for submission
-    parser.add_argument('--submission', action='store_true',
-                        help='submission to sintel or kitti test sets')
-    parser.add_argument('--output_path', default='output', type=str,
-                        help='where to save the prediction results')
-    parser.add_argument('--save_vis_flow', action='store_true',
-                        help='visualize flow prediction as .png image')
-    parser.add_argument('--no_save_flo', action='store_true',
-                        help='not save flow as .flo')
-
-    # distributed training
-    parser.add_argument('--local_rank', default=0, type=int)
-    parser.add_argument('--distributed', action='store_true')
-    parser.add_argument('--launcher', default='none', type=str, choices=['none', 'pytorch'])
-    parser.add_argument('--gpu_ids', default=0, type=int, nargs='+')
-
-    parser.add_argument('--count_time', action='store_true',
-                        help='measure the inference time on sintel')
-
-    return parser
-
-
-def main(args):
-    if not args.eval and not args.submission and args.inference_dir is None:
-        if args.local_rank == 0:
-            print('pytorch version:', torch.__version__)
-            print(args)
-            misc.save_args(args)
-            misc.check_path(args.checkpoint_dir)
-            misc.save_command(args.checkpoint_dir)
-
-    seed = args.seed
-    torch.manual_seed(seed)
-    np.random.seed(seed)
-
-    torch.backends.cudnn.benchmark = True
-
-    if args.launcher == 'none':
-        args.distributed = False
-        device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    else:
-        args.distributed = True
-
-        # adjust batch size for each gpu
-        assert args.batch_size % torch.cuda.device_count() == 0
-        args.batch_size = args.batch_size // torch.cuda.device_count()
-
-        dist_params = dict(backend='nccl')
-        init_dist(args.launcher, **dist_params)
-        # re-set gpu_ids with distributed training mode
-        _, world_size = get_dist_info()
-        args.gpu_ids = range(world_size)
-        device = torch.device('cuda:{}'.format(args.local_rank))
-
-        setup_for_distributed(args.local_rank == 0)
-
-    # model
-    model = GMFlow(feature_channels=args.feature_channels,
-                   num_scales=args.num_scales,
-                   upsample_factor=args.upsample_factor,
-                   num_head=args.num_head,
-                   attention_type=args.attention_type,
-                   ffn_dim_expansion=args.ffn_dim_expansion,
-                   num_transformer_layers=args.num_transformer_layers,
-                   ).to(device)
-
-    if not args.eval and not args.submission and not args.inference_dir:
-        print('Model definition:')
-        print(model)
-
-    if args.distributed:
-        model = torch.nn.parallel.DistributedDataParallel(
-            model.to(device),
-            device_ids=[args.local_rank],
-            output_device=args.local_rank)
-        model_without_ddp = model.module
-    else:
-        if torch.cuda.device_count() > 1:
-            print('Use %d GPUs' % torch.cuda.device_count())
-            model = torch.nn.DataParallel(model)
-
-            model_without_ddp = model.module
-        else:
-            model_without_ddp = model
-
-    num_params = sum(p.numel() for p in model.parameters())
-    print('Number of params:', num_params)
-    if not args.eval and not args.submission and args.inference_dir is None:
-        save_name = '%d_parameters' % num_params
-        open(os.path.join(args.checkpoint_dir, save_name), 'a').close()
-
-    optimizer = torch.optim.AdamW(model_without_ddp.parameters(), lr=args.lr,
-                                  weight_decay=args.weight_decay)
-
-    start_epoch = 0
-    start_step = 0
-    # resume checkpoints
-    if args.resume:
-        print('Load checkpoint: %s' % args.resume)
-
-        loc = 'cuda:{}'.format(args.local_rank)
-        checkpoint = torch.load(args.resume, map_location=loc)
-
-        weights = checkpoint['model'] if 'model' in checkpoint else checkpoint
-
-        model_without_ddp.load_state_dict(weights, strict=args.strict_resume)
-
-        if 'optimizer' in checkpoint and 'step' in checkpoint and 'epoch' in checkpoint and not \
-                args.no_resume_optimizer:
-            print('Load optimizer')
-            optimizer.load_state_dict(checkpoint['optimizer'])
-            start_epoch = checkpoint['epoch']
-            start_step = checkpoint['step']
-
-        print('start_epoch: %d, start_step: %d' % (start_epoch, start_step))
-
-    # evaluate
-    if args.eval:
-        val_results = {}
-
-        if 'chairs' in args.val_dataset:
-            results_dict = validate_chairs(model_without_ddp,
-                                           with_speed_metric=args.with_speed_metric,
-                                           attn_splits_list=args.attn_splits_list,
-                                           corr_radius_list=args.corr_radius_list,
-                                           prop_radius_list=args.prop_radius_list,
-                                           )
-
-            val_results.update(results_dict)
-
-        if 'things' in args.val_dataset:
-            results_dict = validate_things(model_without_ddp,
-                                           padding_factor=args.padding_factor,
-                                           with_speed_metric=args.with_speed_metric,
-                                           attn_splits_list=args.attn_splits_list,
-                                           corr_radius_list=args.corr_radius_list,
-                                           prop_radius_list=args.prop_radius_list,
-                                           )
-            val_results.update(results_dict)
-
-        if 'sintel' in args.val_dataset:
-            results_dict = validate_sintel(model_without_ddp,
-                                           count_time=args.count_time,
-                                           padding_factor=args.padding_factor,
-                                           with_speed_metric=args.with_speed_metric,
-                                           evaluate_matched_unmatched=args.evaluate_matched_unmatched,
-                                           attn_splits_list=args.attn_splits_list,
-                                           corr_radius_list=args.corr_radius_list,
-                                           prop_radius_list=args.prop_radius_list,
-                                           )
-            val_results.update(results_dict)
-
-        if 'kitti' in args.val_dataset:
-            results_dict = validate_kitti(model_without_ddp,
-                                          padding_factor=args.padding_factor,
-                                          with_speed_metric=args.with_speed_metric,
-                                          attn_splits_list=args.attn_splits_list,
-                                          corr_radius_list=args.corr_radius_list,
-                                          prop_radius_list=args.prop_radius_list,
-                                          )
-            val_results.update(results_dict)
-
-        if args.save_eval_to_file:
-            misc.check_path(args.checkpoint_dir)
-            val_file = os.path.join(args.checkpoint_dir, 'val_results.txt')
-            with open(val_file, 'a') as f:
-                f.write('\neval results after training done\n\n')
-                metrics = ['chairs_epe', 'chairs_s0_10', 'chairs_s10_40', 'chairs_s40+',
-                           'things_clean_epe', 'things_clean_s0_10', 'things_clean_s10_40', 'things_clean_s40+',
-                           'things_final_epe', 'things_final_s0_10', 'things_final_s10_40', 'things_final_s40+',
-                           'sintel_clean_epe', 'sintel_clean_s0_10', 'sintel_clean_s10_40', 'sintel_clean_s40+',
-                           'sintel_final_epe', 'sintel_final_s0_10', 'sintel_final_s10_40', 'sintel_final_s40+',
-                           'kitti_epe', 'kitti_f1', 'kitti_s0_10', 'kitti_s10_40', 'kitti_s40+',
-                           ]
-                eval_metrics = []
-                for metric in metrics:
-                    if metric in val_results.keys():
-                        eval_metrics.append(metric)
-
-                metrics_values = [val_results[metric] for metric in eval_metrics]
-
-                num_metrics = len(eval_metrics)
-
-                # save as markdown format
-                f.write(("| {:>20} " * num_metrics + '\n').format(*eval_metrics))
-                f.write(("| {:20.3f} " * num_metrics).format(*metrics_values))
-
-                f.write('\n\n')
-
-        return
-
-    # Sintel and KITTI submission
-    if args.submission:
-        # NOTE: args.val_dataset is a list
-        if args.val_dataset[0] == 'sintel':
-            create_sintel_submission(model_without_ddp,
-                                     output_path=args.output_path,
-                                     padding_factor=args.padding_factor,
-                                     save_vis_flow=args.save_vis_flow,
-                                     no_save_flo=args.no_save_flo,
-                                     attn_splits_list=args.attn_splits_list,
-                                     corr_radius_list=args.corr_radius_list,
-                                     prop_radius_list=args.prop_radius_list,
-                                     )
-        elif args.val_dataset[0] == 'kitti':
-            create_kitti_submission(model_without_ddp,
-                                    output_path=args.output_path,
-                                    padding_factor=args.padding_factor,
-                                    save_vis_flow=args.save_vis_flow,
-                                    attn_splits_list=args.attn_splits_list,
-                                    corr_radius_list=args.corr_radius_list,
-                                    prop_radius_list=args.prop_radius_list,
-                                    )
-        else:
-            raise ValueError(f'Not supported dataset for submission')
-
-        return
-
-    # inferece on a dir
-    if args.inference_dir is not None:
-        inference_on_dir(model_without_ddp,
-                         inference_dir=args.inference_dir,
-                         output_path=args.output_path,
-                         padding_factor=args.padding_factor,
-                         inference_size=args.inference_size,
-                         paired_data=args.dir_paired_data,
-                         save_flo_flow=args.save_flo_flow,
-                         attn_splits_list=args.attn_splits_list,
-                         corr_radius_list=args.corr_radius_list,
-                         prop_radius_list=args.prop_radius_list,
-                         pred_bidir_flow=args.pred_bidir_flow,
-                         fwd_bwd_consistency_check=args.fwd_bwd_consistency_check,
-                         )
-
-        return
-
-    # training datset
-    train_dataset = build_train_dataset(args)
-    print('Number of training images:', len(train_dataset))
-
-    # Multi-processing
-    if args.distributed:
-        train_sampler = torch.utils.data.distributed.DistributedSampler(
-            train_dataset,
-            num_replicas=torch.cuda.device_count(),
-            rank=args.local_rank)
-    else:
-        train_sampler = None
-
-    shuffle = False if args.distributed else True
-    train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=args.batch_size,
-                                               shuffle=shuffle, num_workers=args.num_workers,
-                                               pin_memory=True, drop_last=True,
-                                               sampler=train_sampler)
-
-    last_epoch = start_step if args.resume and start_step > 0 else -1
-    lr_scheduler = torch.optim.lr_scheduler.OneCycleLR(
-        optimizer, args.lr,
-        args.num_steps + 10,
-        pct_start=0.05,
-        cycle_momentum=False,
-        anneal_strategy='cos',
-        last_epoch=last_epoch,
-    )
-
-    if args.local_rank == 0:
-        summary_writer = SummaryWriter(args.checkpoint_dir)
-        logger = Logger(lr_scheduler, summary_writer, args.summary_freq,
-                        start_step=start_step)
-
-    total_steps = start_step
-    epoch = start_epoch
-    print('Start training')
-
-    while total_steps < args.num_steps:
-        model.train()
-
-        # mannual change random seed for shuffling every epoch
-        if args.distributed:
-            train_sampler.set_epoch(epoch)
-
-        for i, sample in enumerate(train_loader):
-            img1, img2, flow_gt, valid = [x.to(device) for x in sample]
-
-            results_dict = model(img1, img2,
-                                 attn_splits_list=args.attn_splits_list,
-                                 corr_radius_list=args.corr_radius_list,
-                                 prop_radius_list=args.prop_radius_list,
-                                 )
-
-            flow_preds = results_dict['flow_preds']
-
-            loss, metrics = flow_loss_func(flow_preds, flow_gt, valid,
-                                           gamma=args.gamma,
-                                           max_flow=args.max_flow,
-                                           )
-
-            if isinstance(loss, float):
-                continue
-
-            if torch.isnan(loss):
-                continue
-
-            metrics.update({'total_loss': loss.item()})
-
-            # more efficient zero_grad
-            for param in model_without_ddp.parameters():
-                param.grad = None
-
-            loss.backward()
-
-            # Gradient clipping
-            torch.nn.utils.clip_grad_norm_(model.parameters(), args.grad_clip)
-
-            optimizer.step()
-
-            lr_scheduler.step()
-
-            if args.local_rank == 0:
-                logger.push(metrics)
-
-                logger.add_image_summary(img1, img2, flow_preds, flow_gt)
-
-            total_steps += 1
-
-            if total_steps % args.save_ckpt_freq == 0 or total_steps == args.num_steps:
-                if args.local_rank == 0:
-                    checkpoint_path = os.path.join(args.checkpoint_dir, 'step_%06d.pth' % total_steps)
-                    torch.save({
-                        'model': model_without_ddp.state_dict()
-                    }, checkpoint_path)
-
-            if total_steps % args.save_latest_ckpt_freq == 0:
-                checkpoint_path = os.path.join(args.checkpoint_dir, 'checkpoint_latest.pth')
-
-                if args.local_rank == 0:
-                    torch.save({
-                        'model': model_without_ddp.state_dict(),
-                        'optimizer': optimizer.state_dict(),
-                        'step': total_steps,
-                        'epoch': epoch,
-                    }, checkpoint_path)
-
-            if total_steps % args.val_freq == 0:
-                print('Start validation')
-
-                val_results = {}
-                # support validation on multiple datasets
-                if 'chairs' in args.val_dataset:
-                    results_dict = validate_chairs(model_without_ddp,
-                                                   with_speed_metric=args.with_speed_metric,
-                                                   attn_splits_list=args.attn_splits_list,
-                                                   corr_radius_list=args.corr_radius_list,
-                                                   prop_radius_list=args.prop_radius_list,
-                                                   )
-                    if args.local_rank == 0:
-                        val_results.update(results_dict)
-
-                if 'things' in args.val_dataset:
-                    results_dict = validate_things(model_without_ddp,
-                                                   padding_factor=args.padding_factor,
-                                                   with_speed_metric=args.with_speed_metric,
-                                                   attn_splits_list=args.attn_splits_list,
-                                                   corr_radius_list=args.corr_radius_list,
-                                                   prop_radius_list=args.prop_radius_list,
-                                                   )
-                    if args.local_rank == 0:
-                        val_results.update(results_dict)
-
-                if 'sintel' in args.val_dataset:
-                    results_dict = validate_sintel(model_without_ddp,
-                                                   count_time=args.count_time,
-                                                   padding_factor=args.padding_factor,
-                                                   with_speed_metric=args.with_speed_metric,
-                                                   evaluate_matched_unmatched=args.evaluate_matched_unmatched,
-                                                   attn_splits_list=args.attn_splits_list,
-                                                   corr_radius_list=args.corr_radius_list,
-                                                   prop_radius_list=args.prop_radius_list,
-                                                   )
-                    if args.local_rank == 0:
-                        val_results.update(results_dict)
-
-                if 'kitti' in args.val_dataset:
-                    results_dict = validate_kitti(model_without_ddp,
-                                                  padding_factor=args.padding_factor,
-                                                  with_speed_metric=args.with_speed_metric,
-                                                  attn_splits_list=args.attn_splits_list,
-                                                  corr_radius_list=args.corr_radius_list,
-                                                  prop_radius_list=args.prop_radius_list,
-                                                  )
-                    if args.local_rank == 0:
-                        val_results.update(results_dict)
-
-                if args.local_rank == 0:
-                    logger.write_dict(val_results)
-
-                    # Save validation results
-                    val_file = os.path.join(args.checkpoint_dir, 'val_results.txt')
-                    with open(val_file, 'a') as f:
-                        f.write('step: %06d\n' % total_steps)
-                        if args.evaluate_matched_unmatched:
-                            metrics = ['chairs_epe',
-                                       'chairs_s0_10', 'chairs_s10_40', 'chairs_s40+',
-                                       'things_clean_epe', 'things_clean_s0_10', 'things_clean_s10_40',
-                                       'things_clean_s40+',
-                                       'sintel_clean_epe', 'sintel_clean_matched', 'sintel_clean_unmatched',
-                                       'sintel_clean_s0_10', 'sintel_clean_s10_40',
-                                       'sintel_clean_s40+',
-                                       'sintel_final_epe', 'sintel_final_matched', 'sintel_final_unmatched',
-                                       'sintel_final_s0_10', 'sintel_final_s10_40',
-                                       'sintel_final_s40+',
-                                       'kitti_epe', 'kitti_f1', 'kitti_s0_10', 'kitti_s10_40', 'kitti_s40+',
-                                       ]
-                        else:
-                            metrics = ['chairs_epe', 'chairs_s0_10', 'chairs_s10_40', 'chairs_s40+',
-                                       'things_clean_epe', 'things_clean_s0_10', 'things_clean_s10_40',
-                                       'things_clean_s40+',
-                                       'sintel_clean_epe', 'sintel_clean_s0_10', 'sintel_clean_s10_40',
-                                       'sintel_clean_s40+',
-                                       'sintel_final_epe', 'sintel_final_s0_10', 'sintel_final_s10_40',
-                                       'sintel_final_s40+',
-                                       'kitti_epe', 'kitti_f1', 'kitti_s0_10', 'kitti_s10_40', 'kitti_s40+',
-                                       ]
-
-                        eval_metrics = []
-                        for metric in metrics:
-                            if metric in val_results.keys():
-                                eval_metrics.append(metric)
-
-                        metrics_values = [val_results[metric] for metric in eval_metrics]
-
-                        num_metrics = len(eval_metrics)
-
-                        # save as markdown format
-                        if args.evaluate_matched_unmatched:
-                            f.write(("| {:>25} " * num_metrics + '\n').format(*eval_metrics))
-                            f.write(("| {:25.3f} " * num_metrics).format(*metrics_values))
-                        else:
-                            f.write(("| {:>20} " * num_metrics + '\n').format(*eval_metrics))
-                            f.write(("| {:20.3f} " * num_metrics).format(*metrics_values))
-
-                        f.write('\n\n')
-
-                model.train()
-
-            if total_steps >= args.num_steps:
-                print('Training done')
-
-                return
-
-        epoch += 1
-
-
-if __name__ == '__main__':
-    parser = get_args_parser()
-    args = parser.parse_args()
-
-    if 'LOCAL_RANK' not in os.environ:
-        os.environ['LOCAL_RANK'] = str(args.local_rank)
-
-    main(args)
diff --git a/spaces/AriaMei/TTSdemo/mel_processing.py b/spaces/AriaMei/TTSdemo/mel_processing.py
deleted file mode 100644
index ecc547270f044cfbb5538a051314b770aa2b058e..0000000000000000000000000000000000000000
--- a/spaces/AriaMei/TTSdemo/mel_processing.py
+++ /dev/null
@@ -1,119 +0,0 @@
-import math
-import os
-import random
-import torch
-from torch import nn
-import torch.nn.functional as F
-import torch.utils.data
-import numpy as np
-
-import logging
-
-numba_logger = logging.getLogger('numba')
-numba_logger.setLevel(logging.WARNING)
-import warnings
-warnings.filterwarnings('ignore')
-import librosa
-import librosa.util as librosa_util
-from librosa.util import normalize, pad_center, tiny
-from scipy.signal import get_window
-from scipy.io.wavfile import read
-from librosa.filters import mel as librosa_mel_fn
-
-MAX_WAV_VALUE = 32768.0
-
-
-def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
-    """
-    PARAMS
-    ------
-    C: compression factor
-    """
-    return torch.log(torch.clamp(x, min=clip_val) * C)
-
-
-def dynamic_range_decompression_torch(x, C=1):
-    """
-    PARAMS
-    ------
-    C: compression factor used to compress
-    """
-    return torch.exp(x) / C
-
-
-def spectral_normalize_torch(magnitudes):
-    output = dynamic_range_compression_torch(magnitudes)
-    return output
-
-
-def spectral_de_normalize_torch(magnitudes):
-    output = dynamic_range_decompression_torch(magnitudes)
-    return output
-
-
-mel_basis = {}
-hann_window = {}
-
-
-def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
-    if torch.min(y) < -1.:
-        print('min value is ', torch.min(y))
-    if torch.max(y) > 1.:
-        print('max value is ', torch.max(y))
-
-    global hann_window
-    dtype_device = str(y.dtype) + '_' + str(y.device)
-    wnsize_dtype_device = str(win_size) + '_' + dtype_device
-    if wnsize_dtype_device not in hann_window:
-        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
-
-    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
-    y = y.squeeze(1)
-
-    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
-                      center=center, pad_mode='reflect', normalized=False, onesided=True)
-
-    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
-    return spec
-
-
-def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
-    global mel_basis
-    dtype_device = str(spec.dtype) + '_' + str(spec.device)
-    fmax_dtype_device = str(fmax) + '_' + dtype_device
-    if fmax_dtype_device not in mel_basis:
-        mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
-        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=spec.dtype, device=spec.device)
-    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
-    spec = spectral_normalize_torch(spec)
-    return spec
-
-
-def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False):
-    if torch.min(y) < -1.:
-        print('min value is ', torch.min(y))
-    if torch.max(y) > 1.:
-        print('max value is ', torch.max(y))
-
-    global mel_basis, hann_window
-    dtype_device = str(y.dtype) + '_' + str(y.device)
-    fmax_dtype_device = str(fmax) + '_' + dtype_device
-    wnsize_dtype_device = str(win_size) + '_' + dtype_device
-    if fmax_dtype_device not in mel_basis:
-        mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
-        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
-    if wnsize_dtype_device not in hann_window:
-        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
-
-    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
-    y = y.squeeze(1)
-
-    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
-                      center=center, pad_mode='reflect', normalized=False, onesided=True)
-
-    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
-
-    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
-    spec = spectral_normalize_torch(spec)
-
-    return spec
diff --git a/spaces/Arnx/MusicGenXvAKN/audiocraft/models/loaders.py b/spaces/Arnx/MusicGenXvAKN/audiocraft/models/loaders.py
deleted file mode 100644
index 97c662c3212b7695669cbfc5214ff2f099c3f319..0000000000000000000000000000000000000000
--- a/spaces/Arnx/MusicGenXvAKN/audiocraft/models/loaders.py
+++ /dev/null
@@ -1,94 +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.
-
-"""
-Utility functions to load from the checkpoints.
-Each checkpoint is a torch.saved dict with the following keys:
-- 'xp.cfg': the hydra config as dumped during training. This should be used
-    to rebuild the object using the audiocraft.models.builders functions,
-- 'model_best_state': a readily loadable best state for the model, including
-    the conditioner. The model obtained from `xp.cfg` should be compatible
-    with this state dict. In the case of a LM, the encodec model would not be
-    bundled along but instead provided separately.
-
-Those functions also support loading from a remote location with the Torch Hub API.
-They also support overriding some parameters, in particular the device and dtype
-of the returned model.
-"""
-
-from pathlib import Path
-from huggingface_hub import hf_hub_download
-import typing as tp
-import os
-
-from omegaconf import OmegaConf
-import torch
-
-from . import builders
-
-
-HF_MODEL_CHECKPOINTS_MAP = {
-    "small": "facebook/musicgen-small",
-    "medium": "facebook/musicgen-medium",
-    "large": "facebook/musicgen-large",
-    "melody": "facebook/musicgen-melody",
-}
-
-
-def _get_state_dict(
-    file_or_url_or_id: tp.Union[Path, str],
-    filename: tp.Optional[str] = None,
-    device='cpu',
-    cache_dir: tp.Optional[str] = None,
-):
-    # Return the state dict either from a file or url
-    file_or_url_or_id = str(file_or_url_or_id)
-    assert isinstance(file_or_url_or_id, str)
-
-    if os.path.isfile(file_or_url_or_id):
-        return torch.load(file_or_url_or_id, map_location=device)
-
-    if os.path.isdir(file_or_url_or_id):
-        file = f"{file_or_url_or_id}/{filename}"
-        return torch.load(file, map_location=device)
-
-    elif file_or_url_or_id.startswith('https://'):
-        return torch.hub.load_state_dict_from_url(file_or_url_or_id, map_location=device, check_hash=True)
-
-    elif file_or_url_or_id in HF_MODEL_CHECKPOINTS_MAP:
-        assert filename is not None, "filename needs to be defined if using HF checkpoints"
-
-        repo_id = HF_MODEL_CHECKPOINTS_MAP[file_or_url_or_id]
-        file = hf_hub_download(repo_id=repo_id, filename=filename, cache_dir=cache_dir)
-        return torch.load(file, map_location=device)
-
-    else:
-        raise ValueError(f"{file_or_url_or_id} is not a valid name, path or link that can be loaded.")
-
-
-def load_compression_model(file_or_url_or_id: tp.Union[Path, str], device='cpu', cache_dir: tp.Optional[str] = None):
-    pkg = _get_state_dict(file_or_url_or_id, filename="compression_state_dict.bin", cache_dir=cache_dir)
-    cfg = OmegaConf.create(pkg['xp.cfg'])
-    cfg.device = str(device)
-    model = builders.get_compression_model(cfg)
-    model.load_state_dict(pkg['best_state'])
-    model.eval()
-    return model
-
-
-def load_lm_model(file_or_url_or_id: tp.Union[Path, str], device='cpu', cache_dir: tp.Optional[str] = None):
-    pkg = _get_state_dict(file_or_url_or_id, filename="state_dict.bin", cache_dir=cache_dir)
-    cfg = OmegaConf.create(pkg['xp.cfg'])
-    cfg.device = str(device)
-    if cfg.device == 'cpu':
-        cfg.dtype = 'float32'
-    else:
-        cfg.dtype = 'float16'
-    model = builders.get_lm_model(cfg)
-    model.load_state_dict(pkg['best_state'])
-    model.eval()
-    model.cfg = cfg
-    return model
diff --git a/spaces/Artrajz/vits-simple-api/bert_vits2/utils.py b/spaces/Artrajz/vits-simple-api/bert_vits2/utils.py
deleted file mode 100644
index 5ac625294ec1c6ef87b12750a1f1b2169d2c5254..0000000000000000000000000000000000000000
--- a/spaces/Artrajz/vits-simple-api/bert_vits2/utils.py
+++ /dev/null
@@ -1,70 +0,0 @@
-import os
-import sys
-import logging
-import torch
-
-MATPLOTLIB_FLAG = False
-
-logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
-logger = logging
-
-
-def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False, version=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 and not skip_optimizer and checkpoint_dict['optimizer'] is not None:
-        optimizer.load_state_dict(checkpoint_dict['optimizer'])
-    elif optimizer is None and not skip_optimizer:
-        # else: #Disable this line if Infer ,and enable the line upper
-        new_opt_dict = optimizer.state_dict()
-        new_opt_dict_params = new_opt_dict['param_groups'][0]['params']
-        new_opt_dict['param_groups'] = checkpoint_dict['optimizer']['param_groups']
-        new_opt_dict['param_groups'][0]['params'] = new_opt_dict_params
-        optimizer.load_state_dict(new_opt_dict)
-    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:
-            # assert "emb_g" not in k
-            # print("load", k)
-            new_state_dict[k] = saved_state_dict[k]
-            assert saved_state_dict[k].shape == v.shape, (saved_state_dict[k].shape, v.shape)
-        except:
-            # Handle legacy model versions and provide appropriate warnings
-            if "ja_bert_proj" in k:
-                v = torch.zeros_like(v)
-                if version is None:
-                    logger.error(f"{k} is not in the checkpoint")
-                    logger.warning(
-                        f"If you're using an older version of the model, consider adding the \"version\" parameter to the model's config.json under the \"data\" section. For instance: \"legacy_version\": \"1.0.1\"")
-            elif "flow.flows.0.enc.attn_layers.3" in k:
-                logger.error(f"{k} is not in the checkpoint")
-                logger.warning(
-                    f"If you're using a transitional version, please add the \"version\": \"1.1.0-transition\" parameter within the \"data\" section of the model's config.json.")
-            else:
-                logger.error(f"{k} is not in the checkpoint")
-
-            new_state_dict[k] = v
-    if hasattr(model, 'module'):
-        model.module.load_state_dict(new_state_dict, strict=False)
-    else:
-        model.load_state_dict(new_state_dict, strict=False)
-    # print("load ")
-    logger.info("Loaded checkpoint '{}' (iteration {})".format(
-        checkpoint_path, iteration))
-    return model, optimizer, learning_rate, iteration
-
-
-def process_legacy_versions(hps):
-    version = getattr(hps, "version", getattr(hps.data, "version", None))
-    if version:
-        prefix = version[0].lower()
-        if prefix == "v":
-            version = version[1:]
-    return version
diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langbulgarianmodel.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langbulgarianmodel.py
deleted file mode 100644
index 994668219dd4def6404e0afd3f538b29a0e50f8b..0000000000000000000000000000000000000000
--- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/chardet/langbulgarianmodel.py
+++ /dev/null
@@ -1,4649 +0,0 @@
-from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
-
-# 3: Positive
-# 2: Likely
-# 1: Unlikely
-# 0: Negative
-
-BULGARIAN_LANG_MODEL = {
-    63: {  # 'e'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 1,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 0,  # 'и'
-        26: 1,  # 'й'
-        12: 1,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 1,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 0,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    45: {  # '\xad'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 0,  # 'Л'
-        38: 1,  # 'М'
-        36: 0,  # 'Н'
-        41: 1,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 0,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 0,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    31: {  # 'А'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 2,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 2,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 2,  # 'З'
-        40: 1,  # 'И'
-        59: 1,  # 'Й'
-        33: 1,  # 'К'
-        46: 2,  # 'Л'
-        38: 1,  # 'М'
-        36: 2,  # 'Н'
-        41: 1,  # 'О'
-        30: 2,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 2,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 2,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 1,  # 'а'
-        18: 2,  # 'б'
-        9: 2,  # 'в'
-        20: 2,  # 'г'
-        11: 2,  # 'д'
-        3: 1,  # 'е'
-        23: 1,  # 'ж'
-        15: 2,  # 'з'
-        2: 0,  # 'и'
-        26: 2,  # 'й'
-        12: 2,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 0,  # 'о'
-        13: 2,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 1,  # 'у'
-        29: 2,  # 'ф'
-        25: 1,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    32: {  # 'Б'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 2,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 1,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 2,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 2,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 2,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 2,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 2,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 1,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    35: {  # 'В'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 2,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 2,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 2,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 2,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    43: {  # 'Г'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 0,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 1,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    37: {  # 'Д'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 2,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 2,  # 'Е'
-        55: 2,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 2,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 2,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 2,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    44: {  # 'Е'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 2,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 1,  # 'Й'
-        33: 2,  # 'К'
-        46: 2,  # 'Л'
-        38: 1,  # 'М'
-        36: 2,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 2,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 2,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 0,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 2,  # 'д'
-        3: 0,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 0,  # 'и'
-        26: 1,  # 'й'
-        12: 2,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 2,  # 'н'
-        4: 0,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 1,  # 'т'
-        19: 1,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    55: {  # 'Ж'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    47: {  # 'З'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 2,  # 'Н'
-        41: 1,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 2,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 1,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 1,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    40: {  # 'И'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 2,  # 'З'
-        40: 1,  # 'И'
-        59: 1,  # 'Й'
-        33: 2,  # 'К'
-        46: 2,  # 'Л'
-        38: 2,  # 'М'
-        36: 2,  # 'Н'
-        41: 1,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 0,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 2,  # 'Я'
-        1: 1,  # 'а'
-        18: 1,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 1,  # 'д'
-        3: 1,  # 'е'
-        23: 0,  # 'ж'
-        15: 3,  # 'з'
-        2: 0,  # 'и'
-        26: 1,  # 'й'
-        12: 1,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 2,  # 'н'
-        4: 0,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 0,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    59: {  # 'Й'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 1,  # 'С'
-        34: 1,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 1,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    33: {  # 'К'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 2,  # 'Н'
-        41: 2,  # 'О'
-        30: 2,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 1,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 2,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 3,  # 'р'
-        8: 1,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    46: {  # 'Л'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 2,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 0,  # 'Р'
-        28: 1,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    38: {  # 'М'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 2,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 2,  # 'л'
-        14: 0,  # 'м'
-        6: 2,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    36: {  # 'Н'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 2,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 2,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 1,  # 'Й'
-        33: 2,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 1,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 1,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 2,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    41: {  # 'О'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 2,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 1,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 1,  # 'Й'
-        33: 2,  # 'К'
-        46: 2,  # 'Л'
-        38: 2,  # 'М'
-        36: 2,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 1,  # 'а'
-        18: 2,  # 'б'
-        9: 2,  # 'в'
-        20: 2,  # 'г'
-        11: 1,  # 'д'
-        3: 1,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 0,  # 'и'
-        26: 1,  # 'й'
-        12: 2,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 0,  # 'о'
-        13: 2,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 3,  # 'т'
-        19: 1,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 1,  # 'ц'
-        21: 2,  # 'ч'
-        27: 0,  # 'ш'
-        24: 2,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    30: {  # 'П'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 2,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 2,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 3,  # 'л'
-        14: 0,  # 'м'
-        6: 1,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 3,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 2,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    39: {  # 'Р'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 2,  # 'Г'
-        37: 2,  # 'Д'
-        44: 2,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 0,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 2,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 1,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 1,  # 'с'
-        5: 0,  # 'т'
-        19: 3,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    28: {  # 'С'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 3,  # 'А'
-        32: 2,  # 'Б'
-        35: 2,  # 'В'
-        43: 1,  # 'Г'
-        37: 2,  # 'Д'
-        44: 2,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 2,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 2,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 2,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 1,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 2,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 1,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 3,  # 'т'
-        19: 2,  # 'у'
-        29: 2,  # 'ф'
-        25: 1,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    34: {  # 'Т'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 2,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 2,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 2,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 1,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 1,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 1,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 3,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    51: {  # 'У'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 2,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 0,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 2,  # 'Т'
-        51: 0,  # 'У'
-        48: 1,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 1,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 2,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 2,  # 'и'
-        26: 1,  # 'й'
-        12: 2,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 2,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 2,  # 'с'
-        5: 1,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    48: {  # 'Ф'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 2,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 1,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 2,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    49: {  # 'Х'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 1,  # 'П'
-        39: 1,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    53: {  # 'Ц'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 2,  # 'И'
-        59: 0,  # 'Й'
-        33: 2,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 1,  # 'Р'
-        28: 2,  # 'С'
-        34: 0,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 2,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 1,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    50: {  # 'Ч'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 2,  # 'А'
-        32: 1,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 1,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 2,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    54: {  # 'Ш'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 1,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 1,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 2,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 2,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    57: {  # 'Щ'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 1,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 1,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 1,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 1,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    61: {  # 'Ъ'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 1,  # 'Д'
-        44: 0,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 1,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 2,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 0,  # 'О'
-        30: 1,  # 'П'
-        39: 2,  # 'Р'
-        28: 1,  # 'С'
-        34: 1,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 1,  # 'Х'
-        53: 1,  # 'Ц'
-        50: 1,  # 'Ч'
-        54: 1,  # 'Ш'
-        57: 1,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 0,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 1,  # 'л'
-        14: 0,  # 'м'
-        6: 1,  # 'н'
-        4: 0,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    60: {  # 'Ю'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 1,  # 'Б'
-        35: 0,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 0,  # 'Е'
-        55: 1,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 0,  # 'М'
-        36: 1,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 1,  # 'Р'
-        28: 1,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 2,  # 'г'
-        11: 1,  # 'д'
-        3: 0,  # 'е'
-        23: 2,  # 'ж'
-        15: 1,  # 'з'
-        2: 1,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 0,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    56: {  # 'Я'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 1,  # 'Б'
-        35: 1,  # 'В'
-        43: 1,  # 'Г'
-        37: 1,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 1,  # 'Л'
-        38: 1,  # 'М'
-        36: 1,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 1,  # 'С'
-        34: 2,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 0,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 1,  # 'и'
-        26: 1,  # 'й'
-        12: 1,  # 'к'
-        10: 1,  # 'л'
-        14: 2,  # 'м'
-        6: 2,  # 'н'
-        4: 0,  # 'о'
-        13: 2,  # 'п'
-        7: 1,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    1: {  # 'а'
-        63: 1,  # 'e'
-        45: 1,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 1,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 1,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 3,  # 'и'
-        26: 3,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 3,  # 'ф'
-        25: 3,  # 'х'
-        22: 3,  # 'ц'
-        21: 3,  # 'ч'
-        27: 3,  # 'ш'
-        24: 3,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    18: {  # 'б'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 3,  # 'в'
-        20: 1,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 0,  # 'т'
-        19: 3,  # 'у'
-        29: 0,  # 'ф'
-        25: 2,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 3,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    9: {  # 'в'
-        63: 1,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 1,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 0,  # 'в'
-        20: 2,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 3,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 2,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 3,  # 'ч'
-        27: 2,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    20: {  # 'г'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 3,  # 'л'
-        14: 1,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 3,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    11: {  # 'д'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 2,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 1,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    3: {  # 'е'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 2,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 2,  # 'и'
-        26: 3,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 2,  # 'у'
-        29: 3,  # 'ф'
-        25: 3,  # 'х'
-        22: 3,  # 'ц'
-        21: 3,  # 'ч'
-        27: 3,  # 'ш'
-        24: 3,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    23: {  # 'ж'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 2,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    15: {  # 'з'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 2,  # 'ш'
-        24: 1,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    2: {  # 'и'
-        63: 1,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 1,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 1,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 1,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 1,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 3,  # 'и'
-        26: 3,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 2,  # 'у'
-        29: 3,  # 'ф'
-        25: 3,  # 'х'
-        22: 3,  # 'ц'
-        21: 3,  # 'ч'
-        27: 3,  # 'ш'
-        24: 3,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    26: {  # 'й'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 1,  # 'а'
-        18: 2,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 2,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 2,  # 'з'
-        2: 1,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 1,  # 'у'
-        29: 2,  # 'ф'
-        25: 1,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    12: {  # 'к'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 1,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 1,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 3,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    10: {  # 'л'
-        63: 1,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 1,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 1,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 2,  # 'п'
-        7: 2,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 2,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 2,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 2,  # 'ь'
-        42: 3,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    14: {  # 'м'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 1,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 2,  # 'к'
-        10: 3,  # 'л'
-        14: 1,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 1,  # 'т'
-        19: 3,  # 'у'
-        29: 2,  # 'ф'
-        25: 1,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 2,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    6: {  # 'н'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 1,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 2,  # 'б'
-        9: 2,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 2,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 3,  # 'ф'
-        25: 2,  # 'х'
-        22: 3,  # 'ц'
-        21: 3,  # 'ч'
-        27: 2,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 2,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    4: {  # 'о'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 2,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 3,  # 'и'
-        26: 3,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 2,  # 'у'
-        29: 3,  # 'ф'
-        25: 3,  # 'х'
-        22: 3,  # 'ц'
-        21: 3,  # 'ч'
-        27: 3,  # 'ш'
-        24: 3,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    13: {  # 'п'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 1,  # 'й'
-        12: 2,  # 'к'
-        10: 3,  # 'л'
-        14: 1,  # 'м'
-        6: 2,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 3,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    7: {  # 'р'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 3,  # 'е'
-        23: 3,  # 'ж'
-        15: 2,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 2,  # 'п'
-        7: 1,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 2,  # 'ф'
-        25: 3,  # 'х'
-        22: 3,  # 'ц'
-        21: 2,  # 'ч'
-        27: 3,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    8: {  # 'с'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 2,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 1,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 2,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 2,  # 'ш'
-        24: 0,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 2,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    5: {  # 'т'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 2,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 2,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 3,  # 'у'
-        29: 1,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 2,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 3,  # 'ъ'
-        52: 2,  # 'ь'
-        42: 2,  # 'ю'
-        16: 3,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    19: {  # 'у'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 2,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 2,  # 'и'
-        26: 2,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 1,  # 'у'
-        29: 2,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 3,  # 'ч'
-        27: 3,  # 'ш'
-        24: 2,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    29: {  # 'ф'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 1,  # 'в'
-        20: 1,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 2,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 2,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 2,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    25: {  # 'х'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 3,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 2,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 1,  # 'п'
-        7: 3,  # 'р'
-        8: 1,  # 'с'
-        5: 2,  # 'т'
-        19: 3,  # 'у'
-        29: 0,  # 'ф'
-        25: 1,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    22: {  # 'ц'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 2,  # 'в'
-        20: 1,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 1,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 2,  # 'к'
-        10: 1,  # 'л'
-        14: 1,  # 'м'
-        6: 1,  # 'н'
-        4: 2,  # 'о'
-        13: 1,  # 'п'
-        7: 1,  # 'р'
-        8: 1,  # 'с'
-        5: 1,  # 'т'
-        19: 2,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 1,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 0,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    21: {  # 'ч'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 1,  # 'б'
-        9: 3,  # 'в'
-        20: 1,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 1,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 2,  # 'р'
-        8: 0,  # 'с'
-        5: 2,  # 'т'
-        19: 3,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 1,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    27: {  # 'ш'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 2,  # 'в'
-        20: 0,  # 'г'
-        11: 1,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 3,  # 'к'
-        10: 2,  # 'л'
-        14: 1,  # 'м'
-        6: 3,  # 'н'
-        4: 2,  # 'о'
-        13: 2,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 1,  # 'т'
-        19: 2,  # 'у'
-        29: 1,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 1,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 2,  # 'ъ'
-        52: 1,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    24: {  # 'щ'
-        63: 1,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 3,  # 'а'
-        18: 0,  # 'б'
-        9: 1,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 3,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 3,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 2,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 1,  # 'р'
-        8: 0,  # 'с'
-        5: 2,  # 'т'
-        19: 3,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 1,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 2,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    17: {  # 'ъ'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 1,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 3,  # 'г'
-        11: 3,  # 'д'
-        3: 2,  # 'е'
-        23: 3,  # 'ж'
-        15: 3,  # 'з'
-        2: 1,  # 'и'
-        26: 2,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 3,  # 'о'
-        13: 3,  # 'п'
-        7: 3,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 1,  # 'у'
-        29: 1,  # 'ф'
-        25: 2,  # 'х'
-        22: 2,  # 'ц'
-        21: 3,  # 'ч'
-        27: 2,  # 'ш'
-        24: 3,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 2,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    52: {  # 'ь'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 1,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 1,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 1,  # 'н'
-        4: 3,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 1,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 1,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 1,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    42: {  # 'ю'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 1,  # 'а'
-        18: 2,  # 'б'
-        9: 1,  # 'в'
-        20: 2,  # 'г'
-        11: 2,  # 'д'
-        3: 1,  # 'е'
-        23: 2,  # 'ж'
-        15: 2,  # 'з'
-        2: 1,  # 'и'
-        26: 1,  # 'й'
-        12: 2,  # 'к'
-        10: 2,  # 'л'
-        14: 2,  # 'м'
-        6: 2,  # 'н'
-        4: 1,  # 'о'
-        13: 1,  # 'п'
-        7: 2,  # 'р'
-        8: 2,  # 'с'
-        5: 2,  # 'т'
-        19: 1,  # 'у'
-        29: 1,  # 'ф'
-        25: 1,  # 'х'
-        22: 2,  # 'ц'
-        21: 3,  # 'ч'
-        27: 1,  # 'ш'
-        24: 1,  # 'щ'
-        17: 1,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    16: {  # 'я'
-        63: 0,  # 'e'
-        45: 1,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 3,  # 'б'
-        9: 3,  # 'в'
-        20: 2,  # 'г'
-        11: 3,  # 'д'
-        3: 2,  # 'е'
-        23: 1,  # 'ж'
-        15: 2,  # 'з'
-        2: 1,  # 'и'
-        26: 2,  # 'й'
-        12: 3,  # 'к'
-        10: 3,  # 'л'
-        14: 3,  # 'м'
-        6: 3,  # 'н'
-        4: 1,  # 'о'
-        13: 2,  # 'п'
-        7: 2,  # 'р'
-        8: 3,  # 'с'
-        5: 3,  # 'т'
-        19: 1,  # 'у'
-        29: 1,  # 'ф'
-        25: 3,  # 'х'
-        22: 2,  # 'ц'
-        21: 1,  # 'ч'
-        27: 1,  # 'ш'
-        24: 2,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 1,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    58: {  # 'є'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 0,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 0,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-    62: {  # '№'
-        63: 0,  # 'e'
-        45: 0,  # '\xad'
-        31: 0,  # 'А'
-        32: 0,  # 'Б'
-        35: 0,  # 'В'
-        43: 0,  # 'Г'
-        37: 0,  # 'Д'
-        44: 0,  # 'Е'
-        55: 0,  # 'Ж'
-        47: 0,  # 'З'
-        40: 0,  # 'И'
-        59: 0,  # 'Й'
-        33: 0,  # 'К'
-        46: 0,  # 'Л'
-        38: 0,  # 'М'
-        36: 0,  # 'Н'
-        41: 0,  # 'О'
-        30: 0,  # 'П'
-        39: 0,  # 'Р'
-        28: 0,  # 'С'
-        34: 0,  # 'Т'
-        51: 0,  # 'У'
-        48: 0,  # 'Ф'
-        49: 0,  # 'Х'
-        53: 0,  # 'Ц'
-        50: 0,  # 'Ч'
-        54: 0,  # 'Ш'
-        57: 0,  # 'Щ'
-        61: 0,  # 'Ъ'
-        60: 0,  # 'Ю'
-        56: 0,  # 'Я'
-        1: 0,  # 'а'
-        18: 0,  # 'б'
-        9: 0,  # 'в'
-        20: 0,  # 'г'
-        11: 0,  # 'д'
-        3: 0,  # 'е'
-        23: 0,  # 'ж'
-        15: 0,  # 'з'
-        2: 0,  # 'и'
-        26: 0,  # 'й'
-        12: 0,  # 'к'
-        10: 0,  # 'л'
-        14: 0,  # 'м'
-        6: 0,  # 'н'
-        4: 0,  # 'о'
-        13: 0,  # 'п'
-        7: 0,  # 'р'
-        8: 0,  # 'с'
-        5: 0,  # 'т'
-        19: 0,  # 'у'
-        29: 0,  # 'ф'
-        25: 0,  # 'х'
-        22: 0,  # 'ц'
-        21: 0,  # 'ч'
-        27: 0,  # 'ш'
-        24: 0,  # 'щ'
-        17: 0,  # 'ъ'
-        52: 0,  # 'ь'
-        42: 0,  # 'ю'
-        16: 0,  # 'я'
-        58: 0,  # 'є'
-        62: 0,  # '№'
-    },
-}
-
-# 255: Undefined characters that did not exist in training text
-# 254: Carriage/Return
-# 253: symbol (punctuation) that does not belong to word
-# 252: 0 - 9
-# 251: Control characters
-
-# Character Mapping Table(s):
-ISO_8859_5_BULGARIAN_CHAR_TO_ORDER = {
-    0: 255,  # '\x00'
-    1: 255,  # '\x01'
-    2: 255,  # '\x02'
-    3: 255,  # '\x03'
-    4: 255,  # '\x04'
-    5: 255,  # '\x05'
-    6: 255,  # '\x06'
-    7: 255,  # '\x07'
-    8: 255,  # '\x08'
-    9: 255,  # '\t'
-    10: 254,  # '\n'
-    11: 255,  # '\x0b'
-    12: 255,  # '\x0c'
-    13: 254,  # '\r'
-    14: 255,  # '\x0e'
-    15: 255,  # '\x0f'
-    16: 255,  # '\x10'
-    17: 255,  # '\x11'
-    18: 255,  # '\x12'
-    19: 255,  # '\x13'
-    20: 255,  # '\x14'
-    21: 255,  # '\x15'
-    22: 255,  # '\x16'
-    23: 255,  # '\x17'
-    24: 255,  # '\x18'
-    25: 255,  # '\x19'
-    26: 255,  # '\x1a'
-    27: 255,  # '\x1b'
-    28: 255,  # '\x1c'
-    29: 255,  # '\x1d'
-    30: 255,  # '\x1e'
-    31: 255,  # '\x1f'
-    32: 253,  # ' '
-    33: 253,  # '!'
-    34: 253,  # '"'
-    35: 253,  # '#'
-    36: 253,  # '$'
-    37: 253,  # '%'
-    38: 253,  # '&'
-    39: 253,  # "'"
-    40: 253,  # '('
-    41: 253,  # ')'
-    42: 253,  # '*'
-    43: 253,  # '+'
-    44: 253,  # ','
-    45: 253,  # '-'
-    46: 253,  # '.'
-    47: 253,  # '/'
-    48: 252,  # '0'
-    49: 252,  # '1'
-    50: 252,  # '2'
-    51: 252,  # '3'
-    52: 252,  # '4'
-    53: 252,  # '5'
-    54: 252,  # '6'
-    55: 252,  # '7'
-    56: 252,  # '8'
-    57: 252,  # '9'
-    58: 253,  # ':'
-    59: 253,  # ';'
-    60: 253,  # '<'
-    61: 253,  # '='
-    62: 253,  # '>'
-    63: 253,  # '?'
-    64: 253,  # '@'
-    65: 77,  # 'A'
-    66: 90,  # 'B'
-    67: 99,  # 'C'
-    68: 100,  # 'D'
-    69: 72,  # 'E'
-    70: 109,  # 'F'
-    71: 107,  # 'G'
-    72: 101,  # 'H'
-    73: 79,  # 'I'
-    74: 185,  # 'J'
-    75: 81,  # 'K'
-    76: 102,  # 'L'
-    77: 76,  # 'M'
-    78: 94,  # 'N'
-    79: 82,  # 'O'
-    80: 110,  # 'P'
-    81: 186,  # 'Q'
-    82: 108,  # 'R'
-    83: 91,  # 'S'
-    84: 74,  # 'T'
-    85: 119,  # 'U'
-    86: 84,  # 'V'
-    87: 96,  # 'W'
-    88: 111,  # 'X'
-    89: 187,  # 'Y'
-    90: 115,  # 'Z'
-    91: 253,  # '['
-    92: 253,  # '\\'
-    93: 253,  # ']'
-    94: 253,  # '^'
-    95: 253,  # '_'
-    96: 253,  # '`'
-    97: 65,  # 'a'
-    98: 69,  # 'b'
-    99: 70,  # 'c'
-    100: 66,  # 'd'
-    101: 63,  # 'e'
-    102: 68,  # 'f'
-    103: 112,  # 'g'
-    104: 103,  # 'h'
-    105: 92,  # 'i'
-    106: 194,  # 'j'
-    107: 104,  # 'k'
-    108: 95,  # 'l'
-    109: 86,  # 'm'
-    110: 87,  # 'n'
-    111: 71,  # 'o'
-    112: 116,  # 'p'
-    113: 195,  # 'q'
-    114: 85,  # 'r'
-    115: 93,  # 's'
-    116: 97,  # 't'
-    117: 113,  # 'u'
-    118: 196,  # 'v'
-    119: 197,  # 'w'
-    120: 198,  # 'x'
-    121: 199,  # 'y'
-    122: 200,  # 'z'
-    123: 253,  # '{'
-    124: 253,  # '|'
-    125: 253,  # '}'
-    126: 253,  # '~'
-    127: 253,  # '\x7f'
-    128: 194,  # '\x80'
-    129: 195,  # '\x81'
-    130: 196,  # '\x82'
-    131: 197,  # '\x83'
-    132: 198,  # '\x84'
-    133: 199,  # '\x85'
-    134: 200,  # '\x86'
-    135: 201,  # '\x87'
-    136: 202,  # '\x88'
-    137: 203,  # '\x89'
-    138: 204,  # '\x8a'
-    139: 205,  # '\x8b'
-    140: 206,  # '\x8c'
-    141: 207,  # '\x8d'
-    142: 208,  # '\x8e'
-    143: 209,  # '\x8f'
-    144: 210,  # '\x90'
-    145: 211,  # '\x91'
-    146: 212,  # '\x92'
-    147: 213,  # '\x93'
-    148: 214,  # '\x94'
-    149: 215,  # '\x95'
-    150: 216,  # '\x96'
-    151: 217,  # '\x97'
-    152: 218,  # '\x98'
-    153: 219,  # '\x99'
-    154: 220,  # '\x9a'
-    155: 221,  # '\x9b'
-    156: 222,  # '\x9c'
-    157: 223,  # '\x9d'
-    158: 224,  # '\x9e'
-    159: 225,  # '\x9f'
-    160: 81,  # '\xa0'
-    161: 226,  # 'Ё'
-    162: 227,  # 'Ђ'
-    163: 228,  # 'Ѓ'
-    164: 229,  # 'Є'
-    165: 230,  # 'Ѕ'
-    166: 105,  # 'І'
-    167: 231,  # 'Ї'
-    168: 232,  # 'Ј'
-    169: 233,  # 'Љ'
-    170: 234,  # 'Њ'
-    171: 235,  # 'Ћ'
-    172: 236,  # 'Ќ'
-    173: 45,  # '\xad'
-    174: 237,  # 'Ў'
-    175: 238,  # 'Џ'
-    176: 31,  # 'А'
-    177: 32,  # 'Б'
-    178: 35,  # 'В'
-    179: 43,  # 'Г'
-    180: 37,  # 'Д'
-    181: 44,  # 'Е'
-    182: 55,  # 'Ж'
-    183: 47,  # 'З'
-    184: 40,  # 'И'
-    185: 59,  # 'Й'
-    186: 33,  # 'К'
-    187: 46,  # 'Л'
-    188: 38,  # 'М'
-    189: 36,  # 'Н'
-    190: 41,  # 'О'
-    191: 30,  # 'П'
-    192: 39,  # 'Р'
-    193: 28,  # 'С'
-    194: 34,  # 'Т'
-    195: 51,  # 'У'
-    196: 48,  # 'Ф'
-    197: 49,  # 'Х'
-    198: 53,  # 'Ц'
-    199: 50,  # 'Ч'
-    200: 54,  # 'Ш'
-    201: 57,  # 'Щ'
-    202: 61,  # 'Ъ'
-    203: 239,  # 'Ы'
-    204: 67,  # 'Ь'
-    205: 240,  # 'Э'
-    206: 60,  # 'Ю'
-    207: 56,  # 'Я'
-    208: 1,  # 'а'
-    209: 18,  # 'б'
-    210: 9,  # 'в'
-    211: 20,  # 'г'
-    212: 11,  # 'д'
-    213: 3,  # 'е'
-    214: 23,  # 'ж'
-    215: 15,  # 'з'
-    216: 2,  # 'и'
-    217: 26,  # 'й'
-    218: 12,  # 'к'
-    219: 10,  # 'л'
-    220: 14,  # 'м'
-    221: 6,  # 'н'
-    222: 4,  # 'о'
-    223: 13,  # 'п'
-    224: 7,  # 'р'
-    225: 8,  # 'с'
-    226: 5,  # 'т'
-    227: 19,  # 'у'
-    228: 29,  # 'ф'
-    229: 25,  # 'х'
-    230: 22,  # 'ц'
-    231: 21,  # 'ч'
-    232: 27,  # 'ш'
-    233: 24,  # 'щ'
-    234: 17,  # 'ъ'
-    235: 75,  # 'ы'
-    236: 52,  # 'ь'
-    237: 241,  # 'э'
-    238: 42,  # 'ю'
-    239: 16,  # 'я'
-    240: 62,  # '№'
-    241: 242,  # 'ё'
-    242: 243,  # 'ђ'
-    243: 244,  # 'ѓ'
-    244: 58,  # 'є'
-    245: 245,  # 'ѕ'
-    246: 98,  # 'і'
-    247: 246,  # 'ї'
-    248: 247,  # 'ј'
-    249: 248,  # 'љ'
-    250: 249,  # 'њ'
-    251: 250,  # 'ћ'
-    252: 251,  # 'ќ'
-    253: 91,  # '§'
-    254: 252,  # 'ў'
-    255: 253,  # 'џ'
-}
-
-ISO_8859_5_BULGARIAN_MODEL = SingleByteCharSetModel(
-    charset_name="ISO-8859-5",
-    language="Bulgarian",
-    char_to_order_map=ISO_8859_5_BULGARIAN_CHAR_TO_ORDER,
-    language_model=BULGARIAN_LANG_MODEL,
-    typical_positive_ratio=0.969392,
-    keep_ascii_letters=False,
-    alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
-)
-
-WINDOWS_1251_BULGARIAN_CHAR_TO_ORDER = {
-    0: 255,  # '\x00'
-    1: 255,  # '\x01'
-    2: 255,  # '\x02'
-    3: 255,  # '\x03'
-    4: 255,  # '\x04'
-    5: 255,  # '\x05'
-    6: 255,  # '\x06'
-    7: 255,  # '\x07'
-    8: 255,  # '\x08'
-    9: 255,  # '\t'
-    10: 254,  # '\n'
-    11: 255,  # '\x0b'
-    12: 255,  # '\x0c'
-    13: 254,  # '\r'
-    14: 255,  # '\x0e'
-    15: 255,  # '\x0f'
-    16: 255,  # '\x10'
-    17: 255,  # '\x11'
-    18: 255,  # '\x12'
-    19: 255,  # '\x13'
-    20: 255,  # '\x14'
-    21: 255,  # '\x15'
-    22: 255,  # '\x16'
-    23: 255,  # '\x17'
-    24: 255,  # '\x18'
-    25: 255,  # '\x19'
-    26: 255,  # '\x1a'
-    27: 255,  # '\x1b'
-    28: 255,  # '\x1c'
-    29: 255,  # '\x1d'
-    30: 255,  # '\x1e'
-    31: 255,  # '\x1f'
-    32: 253,  # ' '
-    33: 253,  # '!'
-    34: 253,  # '"'
-    35: 253,  # '#'
-    36: 253,  # '$'
-    37: 253,  # '%'
-    38: 253,  # '&'
-    39: 253,  # "'"
-    40: 253,  # '('
-    41: 253,  # ')'
-    42: 253,  # '*'
-    43: 253,  # '+'
-    44: 253,  # ','
-    45: 253,  # '-'
-    46: 253,  # '.'
-    47: 253,  # '/'
-    48: 252,  # '0'
-    49: 252,  # '1'
-    50: 252,  # '2'
-    51: 252,  # '3'
-    52: 252,  # '4'
-    53: 252,  # '5'
-    54: 252,  # '6'
-    55: 252,  # '7'
-    56: 252,  # '8'
-    57: 252,  # '9'
-    58: 253,  # ':'
-    59: 253,  # ';'
-    60: 253,  # '<'
-    61: 253,  # '='
-    62: 253,  # '>'
-    63: 253,  # '?'
-    64: 253,  # '@'
-    65: 77,  # 'A'
-    66: 90,  # 'B'
-    67: 99,  # 'C'
-    68: 100,  # 'D'
-    69: 72,  # 'E'
-    70: 109,  # 'F'
-    71: 107,  # 'G'
-    72: 101,  # 'H'
-    73: 79,  # 'I'
-    74: 185,  # 'J'
-    75: 81,  # 'K'
-    76: 102,  # 'L'
-    77: 76,  # 'M'
-    78: 94,  # 'N'
-    79: 82,  # 'O'
-    80: 110,  # 'P'
-    81: 186,  # 'Q'
-    82: 108,  # 'R'
-    83: 91,  # 'S'
-    84: 74,  # 'T'
-    85: 119,  # 'U'
-    86: 84,  # 'V'
-    87: 96,  # 'W'
-    88: 111,  # 'X'
-    89: 187,  # 'Y'
-    90: 115,  # 'Z'
-    91: 253,  # '['
-    92: 253,  # '\\'
-    93: 253,  # ']'
-    94: 253,  # '^'
-    95: 253,  # '_'
-    96: 253,  # '`'
-    97: 65,  # 'a'
-    98: 69,  # 'b'
-    99: 70,  # 'c'
-    100: 66,  # 'd'
-    101: 63,  # 'e'
-    102: 68,  # 'f'
-    103: 112,  # 'g'
-    104: 103,  # 'h'
-    105: 92,  # 'i'
-    106: 194,  # 'j'
-    107: 104,  # 'k'
-    108: 95,  # 'l'
-    109: 86,  # 'm'
-    110: 87,  # 'n'
-    111: 71,  # 'o'
-    112: 116,  # 'p'
-    113: 195,  # 'q'
-    114: 85,  # 'r'
-    115: 93,  # 's'
-    116: 97,  # 't'
-    117: 113,  # 'u'
-    118: 196,  # 'v'
-    119: 197,  # 'w'
-    120: 198,  # 'x'
-    121: 199,  # 'y'
-    122: 200,  # 'z'
-    123: 253,  # '{'
-    124: 253,  # '|'
-    125: 253,  # '}'
-    126: 253,  # '~'
-    127: 253,  # '\x7f'
-    128: 206,  # 'Ђ'
-    129: 207,  # 'Ѓ'
-    130: 208,  # '‚'
-    131: 209,  # 'ѓ'
-    132: 210,  # '„'
-    133: 211,  # '…'
-    134: 212,  # '†'
-    135: 213,  # '‡'
-    136: 120,  # '€'
-    137: 214,  # '‰'
-    138: 215,  # 'Љ'
-    139: 216,  # '‹'
-    140: 217,  # 'Њ'
-    141: 218,  # 'Ќ'
-    142: 219,  # 'Ћ'
-    143: 220,  # 'Џ'
-    144: 221,  # 'ђ'
-    145: 78,  # '‘'
-    146: 64,  # '’'
-    147: 83,  # '“'
-    148: 121,  # '”'
-    149: 98,  # '•'
-    150: 117,  # '–'
-    151: 105,  # '—'
-    152: 222,  # None
-    153: 223,  # '™'
-    154: 224,  # 'љ'
-    155: 225,  # '›'
-    156: 226,  # 'њ'
-    157: 227,  # 'ќ'
-    158: 228,  # 'ћ'
-    159: 229,  # 'џ'
-    160: 88,  # '\xa0'
-    161: 230,  # 'Ў'
-    162: 231,  # 'ў'
-    163: 232,  # 'Ј'
-    164: 233,  # '¤'
-    165: 122,  # 'Ґ'
-    166: 89,  # '¦'
-    167: 106,  # '§'
-    168: 234,  # 'Ё'
-    169: 235,  # '©'
-    170: 236,  # 'Є'
-    171: 237,  # '«'
-    172: 238,  # '¬'
-    173: 45,  # '\xad'
-    174: 239,  # '®'
-    175: 240,  # 'Ї'
-    176: 73,  # '°'
-    177: 80,  # '±'
-    178: 118,  # 'І'
-    179: 114,  # 'і'
-    180: 241,  # 'ґ'
-    181: 242,  # 'µ'
-    182: 243,  # '¶'
-    183: 244,  # '·'
-    184: 245,  # 'ё'
-    185: 62,  # '№'
-    186: 58,  # 'є'
-    187: 246,  # '»'
-    188: 247,  # 'ј'
-    189: 248,  # 'Ѕ'
-    190: 249,  # 'ѕ'
-    191: 250,  # 'ї'
-    192: 31,  # 'А'
-    193: 32,  # 'Б'
-    194: 35,  # 'В'
-    195: 43,  # 'Г'
-    196: 37,  # 'Д'
-    197: 44,  # 'Е'
-    198: 55,  # 'Ж'
-    199: 47,  # 'З'
-    200: 40,  # 'И'
-    201: 59,  # 'Й'
-    202: 33,  # 'К'
-    203: 46,  # 'Л'
-    204: 38,  # 'М'
-    205: 36,  # 'Н'
-    206: 41,  # 'О'
-    207: 30,  # 'П'
-    208: 39,  # 'Р'
-    209: 28,  # 'С'
-    210: 34,  # 'Т'
-    211: 51,  # 'У'
-    212: 48,  # 'Ф'
-    213: 49,  # 'Х'
-    214: 53,  # 'Ц'
-    215: 50,  # 'Ч'
-    216: 54,  # 'Ш'
-    217: 57,  # 'Щ'
-    218: 61,  # 'Ъ'
-    219: 251,  # 'Ы'
-    220: 67,  # 'Ь'
-    221: 252,  # 'Э'
-    222: 60,  # 'Ю'
-    223: 56,  # 'Я'
-    224: 1,  # 'а'
-    225: 18,  # 'б'
-    226: 9,  # 'в'
-    227: 20,  # 'г'
-    228: 11,  # 'д'
-    229: 3,  # 'е'
-    230: 23,  # 'ж'
-    231: 15,  # 'з'
-    232: 2,  # 'и'
-    233: 26,  # 'й'
-    234: 12,  # 'к'
-    235: 10,  # 'л'
-    236: 14,  # 'м'
-    237: 6,  # 'н'
-    238: 4,  # 'о'
-    239: 13,  # 'п'
-    240: 7,  # 'р'
-    241: 8,  # 'с'
-    242: 5,  # 'т'
-    243: 19,  # 'у'
-    244: 29,  # 'ф'
-    245: 25,  # 'х'
-    246: 22,  # 'ц'
-    247: 21,  # 'ч'
-    248: 27,  # 'ш'
-    249: 24,  # 'щ'
-    250: 17,  # 'ъ'
-    251: 75,  # 'ы'
-    252: 52,  # 'ь'
-    253: 253,  # 'э'
-    254: 42,  # 'ю'
-    255: 16,  # 'я'
-}
-
-WINDOWS_1251_BULGARIAN_MODEL = SingleByteCharSetModel(
-    charset_name="windows-1251",
-    language="Bulgarian",
-    char_to_order_map=WINDOWS_1251_BULGARIAN_CHAR_TO_ORDER,
-    language_model=BULGARIAN_LANG_MODEL,
-    typical_positive_ratio=0.969392,
-    keep_ascii_letters=False,
-    alphabet="АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЬЮЯабвгдежзийклмнопрстуфхцчшщъьюя",
-)
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/layers/rotated_boxes.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/layers/rotated_boxes.py
deleted file mode 100644
index 03f73b3bb99275931a887ad9b2d8c0ac9f412bf3..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/layers/rotated_boxes.py
+++ /dev/null
@@ -1,21 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from __future__ import absolute_import, division, print_function, unicode_literals
-import torch
-
-
-def pairwise_iou_rotated(boxes1, boxes2):
-    """
-    Return intersection-over-union (Jaccard index) of boxes.
-
-    Both sets of boxes are expected to be in
-    (x_center, y_center, width, height, angle) format.
-
-    Arguments:
-        boxes1 (Tensor[N, 5])
-        boxes2 (Tensor[M, 5])
-
-    Returns:
-        iou (Tensor[N, M]): the NxM matrix containing the pairwise
-            IoU values for every element in boxes1 and boxes2
-    """
-    return torch.ops.detectron2.box_iou_rotated(boxes1, boxes2)
diff --git a/spaces/Benson/text-generation/Examples/Descargar Facebook Lite Apk Versin Antigua.md b/spaces/Benson/text-generation/Examples/Descargar Facebook Lite Apk Versin Antigua.md
deleted file mode 100644
index f98750ba5fc9faa4300e551aa73528a3b1a8cba7..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Descargar Facebook Lite Apk Versin Antigua.md	
+++ /dev/null
@@ -1,118 +0,0 @@
-
-<h1>Cómo descargar Facebook Lite APK versión anterior</h1>
-<p>Facebook Lite es una aplicación popular que te permite usar Facebook en tu dispositivo Android sin consumir demasiados datos o espacio de almacenamiento. Sin embargo, a veces es posible que tenga que descargar una versión antigua de Facebook Lite por varias razones, como problemas de compatibilidad, problemas de rendimiento o preferencias personales. En este artículo, le mostraremos cómo encontrar y descargar la versión antigua de Facebook Lite APK de diferentes fuentes, y cómo instalarlo en su dispositivo Android. </p>
- <h2>¿Qué es Facebook Lite y por qué es posible que necesite una versión antigua</h2>
-<p>Facebook Lite es una versión de Facebook diseñada para trabajar más rápido y usar menos datos en dispositivos de gama baja o lenta. Tiene muchas características y beneficios que lo convierten en una gran alternativa a la aplicación regular de Facebook, como:</p>
-<h2>descargar facebook lite apk versión antigua</h2><br /><p><b><b>Download</b> &#9675; <a href="https://bltlly.com/2v6Lhe">https://bltlly.com/2v6Lhe</a></b></p><br /><br />
-<ul>
-<li>Utiliza menos de 2 MB de espacio de almacenamiento en su dispositivo. </li>
-<li>Se carga rápidamente y funciona sin problemas en redes 2G y áreas con mala conexión a Internet. </li>
-<li>Guarda sus datos mostrando solo características básicas e imágenes de baja resolución. </li>
-<li>Soporta la mayoría de las funciones de Facebook, como mensajería, publicación, me gusta, comentarios, compartir, etc.</li>
-<li>Funciona en casi cualquier dispositivo Android, incluso aquellos con versiones anteriores de Android OS.</li>
-</ul>
-<p>Sin embargo, puede haber algunas situaciones en las que prefieras usar una versión antigua de Facebook Lite en lugar de la última, como:</p>
-<ul>
-<li>Tienes un dispositivo muy antiguo que no soporta la última versión de Facebook Lite.</li>
-<li>Usted experimenta errores o problemas técnicos con la última versión de Facebook Lite que afectan a su experiencia de usuario. </li>
-<li>Prefieres la interfaz o características de una versión antigua de Facebook Lite sobre la nueva. </li>
-<li>Desea evitar actualizaciones que puedan cambiar sus ajustes o preferencias. </li>
-</ul>
- <h2>Cómo encontrar y descargar Facebook Lite APK versión anterior</h2>
-
- <h3>Uso del sitio web de Uptodown</h3>
-<p>Uptodown es un sitio web que proporciona descargas gratuitas de aplicaciones y juegos para Android, iOS, Windows, Mac y Linux. Tiene una gran colección de versiones antiguas de Facebook Lite, que se remonta a 2015. Para descargar una versión antigua de Facebook Lite de Uptodown, sigue estos pasos:</p>
-<ol>
-<li>Ir a <a href="( 1 )">https://facebook-lite.en.uptodown.com/android/versions</a>. </li>
-<li>Desplácese hacia abajo y encuentre la versión de Facebook Lite que desea descargar. Puede ver la fecha de lanzamiento, el tamaño y la compatibilidad con Android de cada versión. </li>
-<li>Haga clic en el botón verde "Descargar" junto a la versión que desee. </li>
-<li>Espere a que termine la descarga. El archivo se guardará en la carpeta "Descargas" de su dispositivo. </li>
-</ol>
- <h3>Uso del sitio web de APKPure</h3>
-<p>APKPure es otro sitio web que ofrece descargas gratuitas de aplicaciones y juegos para dispositivos Android. También tiene una amplia gama de versiones antiguas de Facebook Lite, que se remonta a 2015. Para descargar una versión antigua de Facebook Lite desde APKPure, sigue estos pasos:</p>
-<ol>
-<li>Ir a <a href=">https://apkpure.com/facebook-lite/com.facebook.lit.lite/versions</a>. </li>
-<li <li>Desplácese hacia abajo y encuentre la versión de Facebook Lite que desea descargar. Puede ver la fecha de lanzamiento, el tamaño y la compatibilidad con Android de cada versión. </li>
-<li>Haga clic en el botón azul "Descargar APK" junto a la versión que desee. </li>
-<li>Espere a que termine la descarga. El archivo se guardará en la carpeta "Descargas" de su dispositivo. </li>
-</ol>
- <h3>Uso del sitio web de APKMirror</h3>
-<p>APKMirror es otro sitio web que ofrece descargas gratuitas de aplicaciones y juegos para dispositivos Android. También tiene un enorme archivo de versiones antiguas de Facebook Lite, que se remonta a 2015. Para descargar una versión antigua de Facebook Lite desde APKMirror, sigue estos pasos:</p>
-<ol>
-<li>Ir a <a href=">https://www.apkmirror.com/apk/facebook-2/lite/</a>. </li>
-
-<li>Haga clic en la versión que desee. Será redirigido a una nueva página con más detalles sobre la aplicación. </li>
-<li>Haga clic en el botón rojo "Descargar APK" en la parte inferior de la página. </li>
-<li>Espere a que termine la descarga. El archivo se guardará en la carpeta "Descargas" de su dispositivo. </li>
-</ol>
- <h2>Cómo instalar Facebook Lite APK versión antigua en su dispositivo Android</h2>
-<p>Una vez que haya descargado el archivo de versión antigua de Facebook Lite APK de una de las fuentes anteriores, tendrá que instalarlo en su dispositivo Android. Para ello, deberá seguir estos pasos:</p>
- <h3>Habilitar la opción de fuentes desconocidas</h3>
-<p>De forma predeterminada, tu dispositivo Android no te permitirá instalar aplicaciones desde fuentes distintas de Google Play Store. Esta es una medida de seguridad para evitar que malware y virus infecten tu dispositivo. Sin embargo, si confías en la fuente del archivo APK, puedes habilitar la opción de instalar aplicaciones de fuentes desconocidas. Para hacerlo, sigue estos pasos:</p>
-<ol>
-<li>Ir a la aplicación "Configuración" de su dispositivo. </li>
-<li>Toque en "Seguridad" o "Privacidad" dependiendo del modelo de su dispositivo. </li>
-<li> Buscar y alternar en la opción que dice "Fuentes desconocidas" o "Permitir la instalación de aplicaciones de fuentes desconocidas". </li>
-<li> Aparecerá un mensaje de advertencia. Toque en "OK" o "Permitir" para confirmar. </li>
-</ol>
- <h3>Localizar y abrir el archivo descargado</h3>
-<p>Siguiente, tendrá que encontrar y abrir el archivo de versión antigua de Facebook Lite APK que ha descargado. Para hacer eso, siga estos pasos:</p>
-<p></p>
-<ol>
-<li>Vaya a la aplicación "Administrador de archivos" de su dispositivo o a cualquier otra aplicación que pueda acceder a sus archivos. </li>
-<li>Vaya a la carpeta "Descargas" de su dispositivo o donde quiera que haya guardado el archivo. </li>
-<li>Encuentre y toque en el archivo que tiene el nombre "Facebook Lite" y el número de versión que ha descargado. </li>
-</ol>
- <h3>Siguiendo los pasos de instalación</h3>
-<p>Finalmente, tendrá que seguir los pasos de instalación para completar el proceso. Para ello, siga estos pasos:</p>
-<ol>
-
-<li> La instalación comenzará y tomará unos segundos o minutos dependiendo del tamaño del dispositivo y del archivo. </li>
-<li> Aparecerá una pantalla diciendo que la aplicación ha sido instalada. Toque en "Abrir" para iniciar la aplicación o "Hecho" para salir. </li>
-</ol>
- <h2>Conclusión</h2>
-<p>En este artículo, le hemos mostrado cómo descargar la versión antigua de Facebook Lite APK de diferentes fuentes, y cómo instalarlo en su dispositivo Android. Esperamos que esta guía haya sido útil e informativa para usted. Si tiene alguna pregunta o comentario, no dude en dejar un comentario a continuación. </p>
- <h2>Preguntas frecuentes</h2>
-<ul>
-<li><b>Q: ¿Es seguro descargar e instalar Facebook Lite APK versión antigua? </b></li>
-<li>A: Depende de dónde descargue el archivo. Algunos sitios web pueden ofrecer archivos falsos o maliciosos que pueden dañar su dispositivo o robar sus datos. Por lo tanto, es importante descargar solo de fuentes confiables y de buena reputación, como las que hemos mencionado en este artículo. Además, asegúrese de escanear el archivo con una aplicación antivirus antes de instalarlo. </li>
- <li><b>Q: ¿Cuáles son las ventajas y desventajas de usar la versión antigua de Facebook Lite APK? </b></li>
-<li>A: Algunas de las ventajas de usar Facebook Lite APK versión antigua son:   <ul>
-  <li>Puede usarlo en dispositivos que no admiten la última versión de Facebook Lite <li>Puede evitar errores o problemas técnicos que puedan ocurrir con la última versión de Facebook Lite</li>
-<li>Puedes disfrutar de la interfaz o características de una versión antigua de Facebook Lite que prefieras sobre la nueva</li>
-<li> Puede guardar sus datos y espacio de almacenamiento no actualizando la aplicación</li>
-  </ul>
-Algunas de las desventajas de usar Facebook Lite APK versión antigua son:   <ul>
-<li>Es posible que se pierda algunas nuevas características o mejoras que se agregan a la última versión de Facebook Lite</li>
-<li>Es posible que tenga problemas de compatibilidad con algunos dispositivos u otras aplicaciones que requieren la última versión de Facebook Lite</li>
-
-  </ul>
-</li>
- <li><b>Q: ¿Cómo puedo actualizar la versión antigua de Facebook Lite APK a la última versión? </b></li>
-<li>A: Si desea actualizar la versión antigua de Facebook Lite APK a la última versión, tiene dos opciones:   <ol>
-  <li>Desinstalar la versión anterior e instalar la última versión de la Google Play Store o cualquiera de las fuentes mencionadas en este artículo. </li>
-  <li>Descargar e instalar la última versión sobre la versión anterior sin desinstalarlo. Esto mantendrá sus datos y configuraciones intactos, pero podría causar algunos errores o conflictos. </li>
-  </ol>
-</li>
- <li><b>Q: ¿Cómo puedo eliminar la versión antigua de Facebook Lite APK de mi dispositivo? </b></li>
-<li>A: Si desea eliminar la versión antigua de Facebook Lite APK de su dispositivo, puede seguir estos pasos:   <ol>
-  <li>Ir a la aplicación "Configuración" de su dispositivo. </li>
-  <li>Toque en "Aplicaciones" o "Aplicaciones" dependiendo del modelo de su dispositivo. </li>
-  <li>Encuentra y toca "Facebook Lite". </li>
-  <li>Toque en "Desinstalar". </li>
-  <li>Aparecerá un mensaje de confirmación. Toca "OK" o "Desinstalar" para confirmar. </li>
-  </ol>
-</li>
- <li><b>Q: ¿Cómo puedo contactar al soporte de Facebook Lite si tengo algún problema o pregunta? </b></li>
-<li>A: Si tiene algún problema o pregunta con respecto a Facebook Lite, puede ponerse en contacto con el soporte de Facebook Lite siguiendo estos pasos:   <ol>
-  <li>Abra la aplicación Facebook Lite en su dispositivo. </li>
-  <li>Toque en el icono del menú (tres líneas horizontales) en la esquina superior derecha de la pantalla. </li>
-  <li>Desplácese hacia abajo y toque en "Ayuda y soporte". </li>
-  <li>Toque en "Informar de un problema". </li>
-  <li>Seleccione el tipo de problema que desea reportar, como "Algo no está funcionando", "Contenido abusivo" o "Comentarios generales". </li>
-  <li>Rellene los detalles de su problema, como una descripción, capturas de pantalla o registros. </li>
-  <li>Toque en "Enviar". </li>
-  </ol>
-También puede visitar el Centro de ayuda de Facebook Lite en <a href="">https://www.facebook.com/help/lite/</a> para obtener más información y preguntas frecuentes. </ul></p> 64aa2da5cf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/s3transfer/copies.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/s3transfer/copies.py
deleted file mode 100644
index a42b848fb8f8b828b3fb1681617ffbe56e480fde..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/s3transfer/copies.py
+++ /dev/null
@@ -1,382 +0,0 @@
-# Copyright 2016 Amazon.com, Inc. or its affiliates. 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. A copy of
-# the License is located at
-#
-# http://aws.amazon.com/apache2.0/
-#
-# or in the "license" file accompanying this file. This file 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 copy
-import math
-
-from s3transfer.tasks import (
-    CompleteMultipartUploadTask,
-    CreateMultipartUploadTask,
-    SubmissionTask,
-    Task,
-)
-from s3transfer.utils import (
-    ChunksizeAdjuster,
-    calculate_range_parameter,
-    get_callbacks,
-    get_filtered_dict,
-)
-
-
-class CopySubmissionTask(SubmissionTask):
-    """Task for submitting tasks to execute a copy"""
-
-    EXTRA_ARGS_TO_HEAD_ARGS_MAPPING = {
-        'CopySourceIfMatch': 'IfMatch',
-        'CopySourceIfModifiedSince': 'IfModifiedSince',
-        'CopySourceIfNoneMatch': 'IfNoneMatch',
-        'CopySourceIfUnmodifiedSince': 'IfUnmodifiedSince',
-        'CopySourceSSECustomerKey': 'SSECustomerKey',
-        'CopySourceSSECustomerAlgorithm': 'SSECustomerAlgorithm',
-        'CopySourceSSECustomerKeyMD5': 'SSECustomerKeyMD5',
-        'RequestPayer': 'RequestPayer',
-        'ExpectedBucketOwner': 'ExpectedBucketOwner',
-    }
-
-    UPLOAD_PART_COPY_ARGS = [
-        'CopySourceIfMatch',
-        'CopySourceIfModifiedSince',
-        'CopySourceIfNoneMatch',
-        'CopySourceIfUnmodifiedSince',
-        'CopySourceSSECustomerKey',
-        'CopySourceSSECustomerAlgorithm',
-        'CopySourceSSECustomerKeyMD5',
-        'SSECustomerKey',
-        'SSECustomerAlgorithm',
-        'SSECustomerKeyMD5',
-        'RequestPayer',
-        'ExpectedBucketOwner',
-    ]
-
-    CREATE_MULTIPART_ARGS_BLACKLIST = [
-        'CopySourceIfMatch',
-        'CopySourceIfModifiedSince',
-        'CopySourceIfNoneMatch',
-        'CopySourceIfUnmodifiedSince',
-        'CopySourceSSECustomerKey',
-        'CopySourceSSECustomerAlgorithm',
-        'CopySourceSSECustomerKeyMD5',
-        'MetadataDirective',
-        'TaggingDirective',
-    ]
-
-    COMPLETE_MULTIPART_ARGS = ['RequestPayer', 'ExpectedBucketOwner']
-
-    def _submit(
-        self, client, config, osutil, request_executor, transfer_future
-    ):
-        """
-        :param client: The client associated with the transfer manager
-
-        :type config: s3transfer.manager.TransferConfig
-        :param config: The transfer config associated with the transfer
-            manager
-
-        :type osutil: s3transfer.utils.OSUtil
-        :param osutil: The os utility associated to the transfer manager
-
-        :type request_executor: s3transfer.futures.BoundedExecutor
-        :param request_executor: The request executor associated with the
-            transfer manager
-
-        :type transfer_future: s3transfer.futures.TransferFuture
-        :param transfer_future: The transfer future associated with the
-            transfer request that tasks are being submitted for
-        """
-        # Determine the size if it was not provided
-        if transfer_future.meta.size is None:
-            # If a size was not provided figure out the size for the
-            # user. Note that we will only use the client provided to
-            # the TransferManager. If the object is outside of the region
-            # of the client, they may have to provide the file size themselves
-            # with a completely new client.
-            call_args = transfer_future.meta.call_args
-            head_object_request = (
-                self._get_head_object_request_from_copy_source(
-                    call_args.copy_source
-                )
-            )
-            extra_args = call_args.extra_args
-
-            # Map any values that may be used in the head object that is
-            # used in the copy object
-            for param, value in extra_args.items():
-                if param in self.EXTRA_ARGS_TO_HEAD_ARGS_MAPPING:
-                    head_object_request[
-                        self.EXTRA_ARGS_TO_HEAD_ARGS_MAPPING[param]
-                    ] = value
-
-            response = call_args.source_client.head_object(
-                **head_object_request
-            )
-            transfer_future.meta.provide_transfer_size(
-                response['ContentLength']
-            )
-
-        # If it is greater than threshold do a multipart copy, otherwise
-        # do a regular copy object.
-        if transfer_future.meta.size < config.multipart_threshold:
-            self._submit_copy_request(
-                client, config, osutil, request_executor, transfer_future
-            )
-        else:
-            self._submit_multipart_request(
-                client, config, osutil, request_executor, transfer_future
-            )
-
-    def _submit_copy_request(
-        self, client, config, osutil, request_executor, transfer_future
-    ):
-        call_args = transfer_future.meta.call_args
-
-        # Get the needed progress callbacks for the task
-        progress_callbacks = get_callbacks(transfer_future, 'progress')
-
-        # Submit the request of a single copy.
-        self._transfer_coordinator.submit(
-            request_executor,
-            CopyObjectTask(
-                transfer_coordinator=self._transfer_coordinator,
-                main_kwargs={
-                    'client': client,
-                    'copy_source': call_args.copy_source,
-                    'bucket': call_args.bucket,
-                    'key': call_args.key,
-                    'extra_args': call_args.extra_args,
-                    'callbacks': progress_callbacks,
-                    'size': transfer_future.meta.size,
-                },
-                is_final=True,
-            ),
-        )
-
-    def _submit_multipart_request(
-        self, client, config, osutil, request_executor, transfer_future
-    ):
-        call_args = transfer_future.meta.call_args
-
-        # Submit the request to create a multipart upload and make sure it
-        # does not include any of the arguments used for copy part.
-        create_multipart_extra_args = {}
-        for param, val in call_args.extra_args.items():
-            if param not in self.CREATE_MULTIPART_ARGS_BLACKLIST:
-                create_multipart_extra_args[param] = val
-
-        create_multipart_future = self._transfer_coordinator.submit(
-            request_executor,
-            CreateMultipartUploadTask(
-                transfer_coordinator=self._transfer_coordinator,
-                main_kwargs={
-                    'client': client,
-                    'bucket': call_args.bucket,
-                    'key': call_args.key,
-                    'extra_args': create_multipart_extra_args,
-                },
-            ),
-        )
-
-        # Determine how many parts are needed based on filesize and
-        # desired chunksize.
-        part_size = config.multipart_chunksize
-        adjuster = ChunksizeAdjuster()
-        part_size = adjuster.adjust_chunksize(
-            part_size, transfer_future.meta.size
-        )
-        num_parts = int(
-            math.ceil(transfer_future.meta.size / float(part_size))
-        )
-
-        # Submit requests to upload the parts of the file.
-        part_futures = []
-        progress_callbacks = get_callbacks(transfer_future, 'progress')
-
-        for part_number in range(1, num_parts + 1):
-            extra_part_args = self._extra_upload_part_args(
-                call_args.extra_args
-            )
-            # The part number for upload part starts at 1 while the
-            # range parameter starts at zero, so just subtract 1 off of
-            # the part number
-            extra_part_args['CopySourceRange'] = calculate_range_parameter(
-                part_size,
-                part_number - 1,
-                num_parts,
-                transfer_future.meta.size,
-            )
-            # Get the size of the part copy as well for the progress
-            # callbacks.
-            size = self._get_transfer_size(
-                part_size,
-                part_number - 1,
-                num_parts,
-                transfer_future.meta.size,
-            )
-            # Get the checksum algorithm of the multipart request.
-            checksum_algorithm = call_args.extra_args.get("ChecksumAlgorithm")
-            part_futures.append(
-                self._transfer_coordinator.submit(
-                    request_executor,
-                    CopyPartTask(
-                        transfer_coordinator=self._transfer_coordinator,
-                        main_kwargs={
-                            'client': client,
-                            'copy_source': call_args.copy_source,
-                            'bucket': call_args.bucket,
-                            'key': call_args.key,
-                            'part_number': part_number,
-                            'extra_args': extra_part_args,
-                            'callbacks': progress_callbacks,
-                            'size': size,
-                            'checksum_algorithm': checksum_algorithm,
-                        },
-                        pending_main_kwargs={
-                            'upload_id': create_multipart_future
-                        },
-                    ),
-                )
-            )
-
-        complete_multipart_extra_args = self._extra_complete_multipart_args(
-            call_args.extra_args
-        )
-        # Submit the request to complete the multipart upload.
-        self._transfer_coordinator.submit(
-            request_executor,
-            CompleteMultipartUploadTask(
-                transfer_coordinator=self._transfer_coordinator,
-                main_kwargs={
-                    'client': client,
-                    'bucket': call_args.bucket,
-                    'key': call_args.key,
-                    'extra_args': complete_multipart_extra_args,
-                },
-                pending_main_kwargs={
-                    'upload_id': create_multipart_future,
-                    'parts': part_futures,
-                },
-                is_final=True,
-            ),
-        )
-
-    def _get_head_object_request_from_copy_source(self, copy_source):
-        if isinstance(copy_source, dict):
-            return copy.copy(copy_source)
-        else:
-            raise TypeError(
-                'Expecting dictionary formatted: '
-                '{"Bucket": bucket_name, "Key": key} '
-                'but got %s or type %s.' % (copy_source, type(copy_source))
-            )
-
-    def _extra_upload_part_args(self, extra_args):
-        # Only the args in COPY_PART_ARGS actually need to be passed
-        # onto the upload_part_copy calls.
-        return get_filtered_dict(extra_args, self.UPLOAD_PART_COPY_ARGS)
-
-    def _extra_complete_multipart_args(self, extra_args):
-        return get_filtered_dict(extra_args, self.COMPLETE_MULTIPART_ARGS)
-
-    def _get_transfer_size(
-        self, part_size, part_index, num_parts, total_transfer_size
-    ):
-        if part_index == num_parts - 1:
-            # The last part may be different in size then the rest of the
-            # parts.
-            return total_transfer_size - (part_index * part_size)
-        return part_size
-
-
-class CopyObjectTask(Task):
-    """Task to do a nonmultipart copy"""
-
-    def _main(
-        self, client, copy_source, bucket, key, extra_args, callbacks, size
-    ):
-        """
-        :param client: The client to use when calling PutObject
-        :param copy_source: The CopySource parameter to use
-        :param bucket: The name of the bucket to copy to
-        :param key: The name of the key to copy to
-        :param extra_args: A dictionary of any extra arguments that may be
-            used in the upload.
-        :param callbacks: List of callbacks to call after copy
-        :param size: The size of the transfer. This value is passed into
-            the callbacks
-
-        """
-        client.copy_object(
-            CopySource=copy_source, Bucket=bucket, Key=key, **extra_args
-        )
-        for callback in callbacks:
-            callback(bytes_transferred=size)
-
-
-class CopyPartTask(Task):
-    """Task to upload a part in a multipart copy"""
-
-    def _main(
-        self,
-        client,
-        copy_source,
-        bucket,
-        key,
-        upload_id,
-        part_number,
-        extra_args,
-        callbacks,
-        size,
-        checksum_algorithm=None,
-    ):
-        """
-        :param client: The client to use when calling PutObject
-        :param copy_source: The CopySource parameter to use
-        :param bucket: The name of the bucket to upload to
-        :param key: The name of the key to upload to
-        :param upload_id: The id of the upload
-        :param part_number: The number representing the part of the multipart
-            upload
-        :param extra_args: A dictionary of any extra arguments that may be
-            used in the upload.
-        :param callbacks: List of callbacks to call after copy part
-        :param size: The size of the transfer. This value is passed into
-            the callbacks
-        :param checksum_algorithm: The algorithm that was used to create the multipart
-            upload
-
-        :rtype: dict
-        :returns: A dictionary representing a part::
-
-            {'Etag': etag_value, 'PartNumber': part_number}
-
-            This value can be appended to a list to be used to complete
-            the multipart upload. If a checksum is in the response,
-            it will also be included.
-        """
-        response = client.upload_part_copy(
-            CopySource=copy_source,
-            Bucket=bucket,
-            Key=key,
-            UploadId=upload_id,
-            PartNumber=part_number,
-            **extra_args,
-        )
-        for callback in callbacks:
-            callback(bytes_transferred=size)
-        etag = response['CopyPartResult']['ETag']
-        part_metadata = {'ETag': etag, 'PartNumber': part_number}
-        if checksum_algorithm:
-            checksum_member = f'Checksum{checksum_algorithm.upper()}'
-            if checksum_member in response['CopyPartResult']:
-                part_metadata[checksum_member] = response['CopyPartResult'][
-                    checksum_member
-                ]
-        return part_metadata
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_distutils/unixccompiler.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_distutils/unixccompiler.py
deleted file mode 100644
index 4ab771a475df8f53f4054d7869366a2457397a09..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_distutils/unixccompiler.py
+++ /dev/null
@@ -1,401 +0,0 @@
-"""distutils.unixccompiler
-
-Contains the UnixCCompiler class, a subclass of CCompiler that handles
-the "typical" Unix-style command-line C compiler:
-  * macros defined with -Dname[=value]
-  * macros undefined with -Uname
-  * include search directories specified with -Idir
-  * libraries specified with -lllib
-  * library search directories specified with -Ldir
-  * compile handled by 'cc' (or similar) executable with -c option:
-    compiles .c to .o
-  * link static library handled by 'ar' command (possibly with 'ranlib')
-  * link shared library handled by 'cc -shared'
-"""
-
-import os
-import sys
-import re
-import shlex
-import itertools
-
-from distutils import sysconfig
-from distutils.dep_util import newer
-from distutils.ccompiler import CCompiler, gen_preprocess_options, gen_lib_options
-from distutils.errors import DistutilsExecError, CompileError, LibError, LinkError
-from distutils import log
-from ._macos_compat import compiler_fixup
-
-# XXX Things not currently handled:
-#   * optimization/debug/warning flags; we just use whatever's in Python's
-#     Makefile and live with it.  Is this adequate?  If not, we might
-#     have to have a bunch of subclasses GNUCCompiler, SGICCompiler,
-#     SunCCompiler, and I suspect down that road lies madness.
-#   * even if we don't know a warning flag from an optimization flag,
-#     we need some way for outsiders to feed preprocessor/compiler/linker
-#     flags in to us -- eg. a sysadmin might want to mandate certain flags
-#     via a site config file, or a user might want to set something for
-#     compiling this module distribution only via the setup.py command
-#     line, whatever.  As long as these options come from something on the
-#     current system, they can be as system-dependent as they like, and we
-#     should just happily stuff them into the preprocessor/compiler/linker
-#     options and carry on.
-
-
-def _split_env(cmd):
-    """
-    For macOS, split command into 'env' portion (if any)
-    and the rest of the linker command.
-
-    >>> _split_env(['a', 'b', 'c'])
-    ([], ['a', 'b', 'c'])
-    >>> _split_env(['/usr/bin/env', 'A=3', 'gcc'])
-    (['/usr/bin/env', 'A=3'], ['gcc'])
-    """
-    pivot = 0
-    if os.path.basename(cmd[0]) == "env":
-        pivot = 1
-        while '=' in cmd[pivot]:
-            pivot += 1
-    return cmd[:pivot], cmd[pivot:]
-
-
-def _split_aix(cmd):
-    """
-    AIX platforms prefix the compiler with the ld_so_aix
-    script, so split that from the linker command.
-
-    >>> _split_aix(['a', 'b', 'c'])
-    ([], ['a', 'b', 'c'])
-    >>> _split_aix(['/bin/foo/ld_so_aix', 'gcc'])
-    (['/bin/foo/ld_so_aix'], ['gcc'])
-    """
-    pivot = os.path.basename(cmd[0]) == 'ld_so_aix'
-    return cmd[:pivot], cmd[pivot:]
-
-
-def _linker_params(linker_cmd, compiler_cmd):
-    """
-    The linker command usually begins with the compiler
-    command (possibly multiple elements), followed by zero or more
-    params for shared library building.
-
-    If the LDSHARED env variable overrides the linker command,
-    however, the commands may not match.
-
-    Return the best guess of the linker parameters by stripping
-    the linker command. If the compiler command does not
-    match the linker command, assume the linker command is
-    just the first element.
-
-    >>> _linker_params('gcc foo bar'.split(), ['gcc'])
-    ['foo', 'bar']
-    >>> _linker_params('gcc foo bar'.split(), ['other'])
-    ['foo', 'bar']
-    >>> _linker_params('ccache gcc foo bar'.split(), 'ccache gcc'.split())
-    ['foo', 'bar']
-    >>> _linker_params(['gcc'], ['gcc'])
-    []
-    """
-    c_len = len(compiler_cmd)
-    pivot = c_len if linker_cmd[:c_len] == compiler_cmd else 1
-    return linker_cmd[pivot:]
-
-
-class UnixCCompiler(CCompiler):
-
-    compiler_type = 'unix'
-
-    # These are used by CCompiler in two places: the constructor sets
-    # instance attributes 'preprocessor', 'compiler', etc. from them, and
-    # 'set_executable()' allows any of these to be set.  The defaults here
-    # are pretty generic; they will probably have to be set by an outsider
-    # (eg. using information discovered by the sysconfig about building
-    # Python extensions).
-    executables = {
-        'preprocessor': None,
-        'compiler': ["cc"],
-        'compiler_so': ["cc"],
-        'compiler_cxx': ["cc"],
-        'linker_so': ["cc", "-shared"],
-        'linker_exe': ["cc"],
-        'archiver': ["ar", "-cr"],
-        'ranlib': None,
-    }
-
-    if sys.platform[:6] == "darwin":
-        executables['ranlib'] = ["ranlib"]
-
-    # Needed for the filename generation methods provided by the base
-    # class, CCompiler.  NB. whoever instantiates/uses a particular
-    # UnixCCompiler instance should set 'shared_lib_ext' -- we set a
-    # reasonable common default here, but it's not necessarily used on all
-    # Unices!
-
-    src_extensions = [".c", ".C", ".cc", ".cxx", ".cpp", ".m"]
-    obj_extension = ".o"
-    static_lib_extension = ".a"
-    shared_lib_extension = ".so"
-    dylib_lib_extension = ".dylib"
-    xcode_stub_lib_extension = ".tbd"
-    static_lib_format = shared_lib_format = dylib_lib_format = "lib%s%s"
-    xcode_stub_lib_format = dylib_lib_format
-    if sys.platform == "cygwin":
-        exe_extension = ".exe"
-
-    def preprocess(
-        self,
-        source,
-        output_file=None,
-        macros=None,
-        include_dirs=None,
-        extra_preargs=None,
-        extra_postargs=None,
-    ):
-        fixed_args = self._fix_compile_args(None, macros, include_dirs)
-        ignore, macros, include_dirs = fixed_args
-        pp_opts = gen_preprocess_options(macros, include_dirs)
-        pp_args = self.preprocessor + pp_opts
-        if output_file:
-            pp_args.extend(['-o', output_file])
-        if extra_preargs:
-            pp_args[:0] = extra_preargs
-        if extra_postargs:
-            pp_args.extend(extra_postargs)
-        pp_args.append(source)
-
-        # reasons to preprocess:
-        # - force is indicated
-        # - output is directed to stdout
-        # - source file is newer than the target
-        preprocess = self.force or output_file is None or newer(source, output_file)
-        if not preprocess:
-            return
-
-        if output_file:
-            self.mkpath(os.path.dirname(output_file))
-
-        try:
-            self.spawn(pp_args)
-        except DistutilsExecError as msg:
-            raise CompileError(msg)
-
-    def _compile(self, obj, src, ext, cc_args, extra_postargs, pp_opts):
-        compiler_so = compiler_fixup(self.compiler_so, cc_args + extra_postargs)
-        try:
-            self.spawn(compiler_so + cc_args + [src, '-o', obj] + extra_postargs)
-        except DistutilsExecError as msg:
-            raise CompileError(msg)
-
-    def create_static_lib(
-        self, objects, output_libname, output_dir=None, debug=0, target_lang=None
-    ):
-        objects, output_dir = self._fix_object_args(objects, output_dir)
-
-        output_filename = self.library_filename(output_libname, output_dir=output_dir)
-
-        if self._need_link(objects, output_filename):
-            self.mkpath(os.path.dirname(output_filename))
-            self.spawn(self.archiver + [output_filename] + objects + self.objects)
-
-            # Not many Unices required ranlib anymore -- SunOS 4.x is, I
-            # think the only major Unix that does.  Maybe we need some
-            # platform intelligence here to skip ranlib if it's not
-            # needed -- or maybe Python's configure script took care of
-            # it for us, hence the check for leading colon.
-            if self.ranlib:
-                try:
-                    self.spawn(self.ranlib + [output_filename])
-                except DistutilsExecError as msg:
-                    raise LibError(msg)
-        else:
-            log.debug("skipping %s (up-to-date)", output_filename)
-
-    def link(
-        self,
-        target_desc,
-        objects,
-        output_filename,
-        output_dir=None,
-        libraries=None,
-        library_dirs=None,
-        runtime_library_dirs=None,
-        export_symbols=None,
-        debug=0,
-        extra_preargs=None,
-        extra_postargs=None,
-        build_temp=None,
-        target_lang=None,
-    ):
-        objects, output_dir = self._fix_object_args(objects, output_dir)
-        fixed_args = self._fix_lib_args(libraries, library_dirs, runtime_library_dirs)
-        libraries, library_dirs, runtime_library_dirs = fixed_args
-
-        lib_opts = gen_lib_options(self, library_dirs, runtime_library_dirs, libraries)
-        if not isinstance(output_dir, (str, type(None))):
-            raise TypeError("'output_dir' must be a string or None")
-        if output_dir is not None:
-            output_filename = os.path.join(output_dir, output_filename)
-
-        if self._need_link(objects, output_filename):
-            ld_args = objects + self.objects + lib_opts + ['-o', output_filename]
-            if debug:
-                ld_args[:0] = ['-g']
-            if extra_preargs:
-                ld_args[:0] = extra_preargs
-            if extra_postargs:
-                ld_args.extend(extra_postargs)
-            self.mkpath(os.path.dirname(output_filename))
-            try:
-                # Select a linker based on context: linker_exe when
-                # building an executable or linker_so (with shared options)
-                # when building a shared library.
-                building_exe = target_desc == CCompiler.EXECUTABLE
-                linker = (self.linker_exe if building_exe else self.linker_so)[:]
-
-                if target_lang == "c++" and self.compiler_cxx:
-                    env, linker_ne = _split_env(linker)
-                    aix, linker_na = _split_aix(linker_ne)
-                    _, compiler_cxx_ne = _split_env(self.compiler_cxx)
-                    _, linker_exe_ne = _split_env(self.linker_exe)
-
-                    params = _linker_params(linker_na, linker_exe_ne)
-                    linker = env + aix + compiler_cxx_ne + params
-
-                linker = compiler_fixup(linker, ld_args)
-
-                self.spawn(linker + ld_args)
-            except DistutilsExecError as msg:
-                raise LinkError(msg)
-        else:
-            log.debug("skipping %s (up-to-date)", output_filename)
-
-    # -- Miscellaneous methods -----------------------------------------
-    # These are all used by the 'gen_lib_options() function, in
-    # ccompiler.py.
-
-    def library_dir_option(self, dir):
-        return "-L" + dir
-
-    def _is_gcc(self):
-        cc_var = sysconfig.get_config_var("CC")
-        compiler = os.path.basename(shlex.split(cc_var)[0])
-        return "gcc" in compiler or "g++" in compiler
-
-    def runtime_library_dir_option(self, dir):
-        # XXX Hackish, at the very least.  See Python bug #445902:
-        # http://sourceforge.net/tracker/index.php
-        #   ?func=detail&aid=445902&group_id=5470&atid=105470
-        # Linkers on different platforms need different options to
-        # specify that directories need to be added to the list of
-        # directories searched for dependencies when a dynamic library
-        # is sought.  GCC on GNU systems (Linux, FreeBSD, ...) has to
-        # be told to pass the -R option through to the linker, whereas
-        # other compilers and gcc on other systems just know this.
-        # Other compilers may need something slightly different.  At
-        # this time, there's no way to determine this information from
-        # the configuration data stored in the Python installation, so
-        # we use this hack.
-        if sys.platform[:6] == "darwin":
-            from distutils.util import get_macosx_target_ver, split_version
-
-            macosx_target_ver = get_macosx_target_ver()
-            if macosx_target_ver and split_version(macosx_target_ver) >= [10, 5]:
-                return "-Wl,-rpath," + dir
-            else:  # no support for -rpath on earlier macOS versions
-                return "-L" + dir
-        elif sys.platform[:7] == "freebsd":
-            return "-Wl,-rpath=" + dir
-        elif sys.platform[:5] == "hp-ux":
-            return [
-                "-Wl,+s" if self._is_gcc() else "+s",
-                "-L" + dir,
-            ]
-
-        # For all compilers, `-Wl` is the presumed way to
-        # pass a compiler option to the linker and `-R` is
-        # the way to pass an RPATH.
-        if sysconfig.get_config_var("GNULD") == "yes":
-            # GNU ld needs an extra option to get a RUNPATH
-            # instead of just an RPATH.
-            return "-Wl,--enable-new-dtags,-R" + dir
-        else:
-            return "-Wl,-R" + dir
-
-    def library_option(self, lib):
-        return "-l" + lib
-
-    @staticmethod
-    def _library_root(dir):
-        """
-        macOS users can specify an alternate SDK using'-isysroot'.
-        Calculate the SDK root if it is specified.
-
-        Note that, as of Xcode 7, Apple SDKs may contain textual stub
-        libraries with .tbd extensions rather than the normal .dylib
-        shared libraries installed in /.  The Apple compiler tool
-        chain handles this transparently but it can cause problems
-        for programs that are being built with an SDK and searching
-        for specific libraries.  Callers of find_library_file need to
-        keep in mind that the base filename of the returned SDK library
-        file might have a different extension from that of the library
-        file installed on the running system, for example:
-          /Applications/Xcode.app/Contents/Developer/Platforms/
-              MacOSX.platform/Developer/SDKs/MacOSX10.11.sdk/
-              usr/lib/libedit.tbd
-        vs
-          /usr/lib/libedit.dylib
-        """
-        cflags = sysconfig.get_config_var('CFLAGS')
-        match = re.search(r'-isysroot\s*(\S+)', cflags)
-
-        apply_root = (
-            sys.platform == 'darwin'
-            and match
-            and (
-                dir.startswith('/System/')
-                or (dir.startswith('/usr/') and not dir.startswith('/usr/local/'))
-            )
-        )
-
-        return os.path.join(match.group(1), dir[1:]) if apply_root else dir
-
-    def find_library_file(self, dirs, lib, debug=0):
-        r"""
-        Second-guess the linker with not much hard
-        data to go on: GCC seems to prefer the shared library, so
-        assume that *all* Unix C compilers do,
-        ignoring even GCC's "-static" option.
-
-        >>> compiler = UnixCCompiler()
-        >>> compiler._library_root = lambda dir: dir
-        >>> monkeypatch = getfixture('monkeypatch')
-        >>> monkeypatch.setattr(os.path, 'exists', lambda d: 'existing' in d)
-        >>> dirs = ('/foo/bar/missing', '/foo/bar/existing')
-        >>> compiler.find_library_file(dirs, 'abc').replace('\\', '/')
-        '/foo/bar/existing/libabc.dylib'
-        >>> compiler.find_library_file(reversed(dirs), 'abc').replace('\\', '/')
-        '/foo/bar/existing/libabc.dylib'
-        >>> monkeypatch.setattr(os.path, 'exists',
-        ...     lambda d: 'existing' in d and '.a' in d)
-        >>> compiler.find_library_file(dirs, 'abc').replace('\\', '/')
-        '/foo/bar/existing/libabc.a'
-        >>> compiler.find_library_file(reversed(dirs), 'abc').replace('\\', '/')
-        '/foo/bar/existing/libabc.a'
-        """
-        lib_names = (
-            self.library_filename(lib, lib_type=type)
-            for type in 'dylib xcode_stub shared static'.split()
-        )
-
-        roots = map(self._library_root, dirs)
-
-        searched = (
-            os.path.join(root, lib_name)
-            for root, lib_name in itertools.product(roots, lib_names)
-        )
-
-        found = filter(os.path.exists, searched)
-
-        # Return None if it could not be found in any dir.
-        return next(found, None)
diff --git a/spaces/BigSalmon/TestAnyGPTModel/README.md b/spaces/BigSalmon/TestAnyGPTModel/README.md
deleted file mode 100644
index f7c1fa41a3746737a38408a908a14c869e4763e7..0000000000000000000000000000000000000000
--- a/spaces/BigSalmon/TestAnyGPTModel/README.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-title: TestAnyGPTModel
-emoji: 📚
-colorFrom: green
-colorTo: gray
-sdk: streamlit
-sdk_version: 0.89.0
-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` or `streamlit`
-
-`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).  
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_  
-Whether the Space stays on top of your list.
\ No newline at end of file
diff --git a/spaces/Billyosoro/ESRGAN/FAQ.md b/spaces/Billyosoro/ESRGAN/FAQ.md
deleted file mode 100644
index caa8c08cfe4302eb8812c823569e8a0be30fa49c..0000000000000000000000000000000000000000
--- a/spaces/Billyosoro/ESRGAN/FAQ.md
+++ /dev/null
@@ -1,9 +0,0 @@
-# FAQ
-
-1. **What is the difference of `--netscale` and `outscale`?**
-
-A: TODO.
-
-1. **How to select models?**
-
-A: TODO.
diff --git a/spaces/Brainclub5000/wesley7137-Llama-2-13B-Nous-Hermes-vicuna-uncensored-mastermod-spych/app.py b/spaces/Brainclub5000/wesley7137-Llama-2-13B-Nous-Hermes-vicuna-uncensored-mastermod-spych/app.py
deleted file mode 100644
index 29683a064da260f04160e00b63e17ae28d16e4a8..0000000000000000000000000000000000000000
--- a/spaces/Brainclub5000/wesley7137-Llama-2-13B-Nous-Hermes-vicuna-uncensored-mastermod-spych/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/wesley7137/Llama-2-13B-Nous-Hermes-vicuna-uncensored-mastermod-spych").launch()
\ No newline at end of file
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/data/datasets/builtin.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/data/datasets/builtin.py
deleted file mode 100644
index 303855f5ce5516a154186eca864269e51de802eb..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/data/datasets/builtin.py
+++ /dev/null
@@ -1,220 +0,0 @@
-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-
-"""
-This file registers pre-defined datasets at hard-coded paths, and their metadata.
-
-We hard-code metadata for common datasets. This will enable:
-1. Consistency check when loading the datasets
-2. Use models on these standard datasets directly and run demos,
-   without having to download the dataset annotations
-
-We hard-code some paths to the dataset that's assumed to
-exist in "./datasets/".
-
-Users SHOULD NOT use this file to create new dataset / metadata for new dataset.
-To add new dataset, refer to the tutorial "docs/DATASETS.md".
-"""
-
-import os
-
-from detectron2.data import DatasetCatalog, MetadataCatalog
-
-from .builtin_meta import _get_builtin_metadata
-from .cityscapes import load_cityscapes_instances, load_cityscapes_semantic
-from .lvis import get_lvis_instances_meta, register_lvis_instances
-from .pascal_voc import register_pascal_voc
-from .register_coco import register_coco_instances, register_coco_panoptic_separated
-
-# ==== Predefined datasets and splits for COCO ==========
-
-_PREDEFINED_SPLITS_COCO = {}
-_PREDEFINED_SPLITS_COCO["coco"] = {
-    "coco_2014_train": ("coco/train2014", "coco/annotations/instances_train2014.json"),
-    "coco_2014_val": ("coco/val2014", "coco/annotations/instances_val2014.json"),
-    "coco_2014_minival": ("coco/val2014", "coco/annotations/instances_minival2014.json"),
-    "coco_2014_minival_100": ("coco/val2014", "coco/annotations/instances_minival2014_100.json"),
-    "coco_2014_valminusminival": (
-        "coco/val2014",
-        "coco/annotations/instances_valminusminival2014.json",
-    ),
-    "coco_2017_train": ("coco/train2017", "coco/annotations/instances_train2017.json"),
-    "coco_2017_val": ("coco/val2017", "coco/annotations/instances_val2017.json"),
-    "coco_2017_test": ("coco/test2017", "coco/annotations/image_info_test2017.json"),
-    "coco_2017_test-dev": ("coco/test2017", "coco/annotations/image_info_test-dev2017.json"),
-    "coco_2017_val_100": ("coco/val2017", "coco/annotations/instances_val2017_100.json"),
-}
-
-_PREDEFINED_SPLITS_COCO["coco_person"] = {
-    "keypoints_coco_2014_train": (
-        "coco/train2014",
-        "coco/annotations/person_keypoints_train2014.json",
-    ),
-    "keypoints_coco_2014_val": ("coco/val2014", "coco/annotations/person_keypoints_val2014.json"),
-    "keypoints_coco_2014_minival": (
-        "coco/val2014",
-        "coco/annotations/person_keypoints_minival2014.json",
-    ),
-    "keypoints_coco_2014_valminusminival": (
-        "coco/val2014",
-        "coco/annotations/person_keypoints_valminusminival2014.json",
-    ),
-    "keypoints_coco_2014_minival_100": (
-        "coco/val2014",
-        "coco/annotations/person_keypoints_minival2014_100.json",
-    ),
-    "keypoints_coco_2017_train": (
-        "coco/train2017",
-        "coco/annotations/person_keypoints_train2017.json",
-    ),
-    "keypoints_coco_2017_val": ("coco/val2017", "coco/annotations/person_keypoints_val2017.json"),
-    "keypoints_coco_2017_val_100": (
-        "coco/val2017",
-        "coco/annotations/person_keypoints_val2017_100.json",
-    ),
-}
-
-
-_PREDEFINED_SPLITS_COCO_PANOPTIC = {
-    "coco_2017_train_panoptic": (
-        # This is the original panoptic annotation directory
-        "coco/panoptic_train2017",
-        "coco/annotations/panoptic_train2017.json",
-        # This directory contains semantic annotations that are
-        # converted from panoptic annotations.
-        # It is used by PanopticFPN.
-        # You can use the script at detectron2/datasets/prepare_panoptic_fpn.py
-        # to create these directories.
-        "coco/panoptic_stuff_train2017",
-    ),
-    "coco_2017_val_panoptic": (
-        "coco/panoptic_val2017",
-        "coco/annotations/panoptic_val2017.json",
-        "coco/panoptic_stuff_val2017",
-    ),
-    "coco_2017_val_100_panoptic": (
-        "coco/panoptic_val2017_100",
-        "coco/annotations/panoptic_val2017_100.json",
-        "coco/panoptic_stuff_val2017_100",
-    ),
-}
-
-
-def register_all_coco(root):
-    for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_COCO.items():
-        for key, (image_root, json_file) in splits_per_dataset.items():
-            # Assume pre-defined datasets live in `./datasets`.
-            register_coco_instances(
-                key,
-                _get_builtin_metadata(dataset_name),
-                os.path.join(root, json_file) if "://" not in json_file else json_file,
-                os.path.join(root, image_root),
-            )
-
-    for (
-        prefix,
-        (panoptic_root, panoptic_json, semantic_root),
-    ) in _PREDEFINED_SPLITS_COCO_PANOPTIC.items():
-        prefix_instances = prefix[: -len("_panoptic")]
-        instances_meta = MetadataCatalog.get(prefix_instances)
-        image_root, instances_json = instances_meta.image_root, instances_meta.json_file
-        register_coco_panoptic_separated(
-            prefix,
-            _get_builtin_metadata("coco_panoptic_separated"),
-            image_root,
-            os.path.join(root, panoptic_root),
-            os.path.join(root, panoptic_json),
-            os.path.join(root, semantic_root),
-            instances_json,
-        )
-
-
-# ==== Predefined datasets and splits for LVIS ==========
-
-
-_PREDEFINED_SPLITS_LVIS = {
-    "lvis_v0.5": {
-        "lvis_v0.5_train": ("coco/train2017", "lvis/lvis_v0.5_train.json"),
-        "lvis_v0.5_val": ("coco/val2017", "lvis/lvis_v0.5_val.json"),
-        "lvis_v0.5_val_rand_100": ("coco/val2017", "lvis/lvis_v0.5_val_rand_100.json"),
-        "lvis_v0.5_test": ("coco/test2017", "lvis/lvis_v0.5_image_info_test.json"),
-    },
-    "lvis_v0.5_cocofied": {
-        "lvis_v0.5_train_cocofied": ("coco/train2017", "lvis/lvis_v0.5_train_cocofied.json"),
-        "lvis_v0.5_val_cocofied": ("coco/val2017", "lvis/lvis_v0.5_val_cocofied.json"),
-    },
-}
-
-
-def register_all_lvis(root):
-    for dataset_name, splits_per_dataset in _PREDEFINED_SPLITS_LVIS.items():
-        for key, (image_root, json_file) in splits_per_dataset.items():
-            # Assume pre-defined datasets live in `./datasets`.
-            register_lvis_instances(
-                key,
-                get_lvis_instances_meta(dataset_name),
-                os.path.join(root, json_file) if "://" not in json_file else json_file,
-                os.path.join(root, image_root),
-            )
-
-
-# ==== Predefined splits for raw cityscapes images ===========
-
-
-_RAW_CITYSCAPES_SPLITS = {
-    "cityscapes_fine_{task}_train": ("cityscapes/leftImg8bit/train", "cityscapes/gtFine/train"),
-    "cityscapes_fine_{task}_val": ("cityscapes/leftImg8bit/val", "cityscapes/gtFine/val"),
-    "cityscapes_fine_{task}_test": ("cityscapes/leftImg8bit/test", "cityscapes/gtFine/test"),
-}
-
-
-def register_all_cityscapes(root):
-    for key, (image_dir, gt_dir) in _RAW_CITYSCAPES_SPLITS.items():
-        meta = _get_builtin_metadata("cityscapes")
-        image_dir = os.path.join(root, image_dir)
-        gt_dir = os.path.join(root, gt_dir)
-
-        inst_key = key.format(task="instance_seg")
-        DatasetCatalog.register(
-            inst_key,
-            lambda x=image_dir, y=gt_dir: load_cityscapes_instances(
-                x, y, from_json=True, to_polygons=True
-            ),
-        )
-        MetadataCatalog.get(inst_key).set(
-            image_dir=image_dir, gt_dir=gt_dir, evaluator_type="cityscapes", **meta
-        )
-
-        sem_key = key.format(task="sem_seg")
-        DatasetCatalog.register(
-            sem_key, lambda x=image_dir, y=gt_dir: load_cityscapes_semantic(x, y)
-        )
-        MetadataCatalog.get(sem_key).set(
-            image_dir=image_dir, gt_dir=gt_dir, evaluator_type="sem_seg", **meta
-        )
-
-
-# ==== Predefined splits for PASCAL VOC ===========
-def register_all_pascal_voc(root):
-    SPLITS = [
-        ("voc_2007_trainval", "VOC2007", "trainval"),
-        ("voc_2007_train", "VOC2007", "train"),
-        ("voc_2007_val", "VOC2007", "val"),
-        ("voc_2007_test", "VOC2007", "test"),
-        ("voc_2012_trainval", "VOC2012", "trainval"),
-        ("voc_2012_train", "VOC2012", "train"),
-        ("voc_2012_val", "VOC2012", "val"),
-    ]
-    for name, dirname, split in SPLITS:
-        year = 2007 if "2007" in name else 2012
-        register_pascal_voc(name, os.path.join(root, dirname), split, year)
-        MetadataCatalog.get(name).evaluator_type = "pascal_voc"
-
-
-# Register them all under "./datasets"
-_root = os.getenv("DETECTRON2_DATASETS", "datasets")
-register_all_coco(_root)
-register_all_lvis(_root)
-register_all_cityscapes(_root)
-register_all_pascal_voc(_root)
diff --git a/spaces/CVPR/LIVE/LIVE/colab.py b/spaces/CVPR/LIVE/LIVE/colab.py
deleted file mode 100644
index dd0adc9ab4a11dee6d31e37d2b4c3b7f4fef9d23..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/LIVE/colab.py
+++ /dev/null
@@ -1,687 +0,0 @@
-"""
-Here are some use cases:
-python main.py --config config/all.yaml --experiment experiment_8x1 --signature demo1 --target data/demo1.png
-"""
-import pydiffvg
-import torch
-import cv2
-import matplotlib.pyplot as plt
-import random
-import argparse
-import math
-import errno
-from tqdm import tqdm
-from torch.optim.lr_scheduler import CosineAnnealingLR, LambdaLR
-from torch.nn.functional import adaptive_avg_pool2d
-import warnings
-warnings.filterwarnings("ignore")
-
-import PIL
-import PIL.Image
-import os
-import os.path as osp
-import numpy as np
-import numpy.random as npr
-import shutil
-import copy
-# import skfmm
-from xing_loss import xing_loss
-
-import yaml
-from easydict import EasyDict as edict
-
-
-pydiffvg.set_print_timing(False)
-gamma = 1.0
-
-##########
-# helper #
-##########
-
-from utils import \
-    get_experiment_id, \
-    get_path_schedule, \
-    edict_2_dict, \
-    check_and_create_dir
-
-def get_bezier_circle(radius=1, segments=4, bias=None):
-    points = []
-    if bias is None:
-        bias = (random.random(), random.random())
-    avg_degree = 360 / (segments*3)
-    for i in range(0, segments*3):
-        point = (np.cos(np.deg2rad(i * avg_degree)),
-                    np.sin(np.deg2rad(i * avg_degree)))
-        points.append(point)
-    points = torch.tensor(points)
-    points = (points)*radius + torch.tensor(bias).unsqueeze(dim=0)
-    points = points.type(torch.FloatTensor)
-    return points
-
-def get_sdf(phi, method='skfmm', **kwargs):
-    if method == 'skfmm':
-        import skfmm
-        phi = (phi-0.5)*2
-        if (phi.max() <= 0) or (phi.min() >= 0):
-            return np.zeros(phi.shape).astype(np.float32)
-        sd = skfmm.distance(phi, dx=1)
-
-        flip_negative = kwargs.get('flip_negative', True)
-        if flip_negative:
-            sd = np.abs(sd)
-
-        truncate = kwargs.get('truncate', 10)
-        sd = np.clip(sd, -truncate, truncate)
-        # print(f"max sd value is: {sd.max()}")
-
-        zero2max = kwargs.get('zero2max', True)
-        if zero2max and flip_negative:
-            sd = sd.max() - sd
-        elif zero2max:
-            raise ValueError
-
-        normalize = kwargs.get('normalize', 'sum')
-        if normalize == 'sum':
-            sd /= sd.sum()
-        elif normalize == 'to1':
-            sd /= sd.max()
-        return sd
-
-def parse_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--debug', action='store_true', default=False)
-    parser.add_argument("--config", type=str)
-    parser.add_argument("--experiment", type=str)
-    parser.add_argument("--seed", type=int)
-    parser.add_argument("--target", type=str, help="target image path")
-    parser.add_argument('--log_dir', metavar='DIR', default="log/debug")
-    parser.add_argument('--initial', type=str, default="random", choices=['random', 'circle'])
-    parser.add_argument('--signature', nargs='+', type=str)
-    parser.add_argument('--seginit', nargs='+', type=str)
-    parser.add_argument("--num_segments", type=int, default=4)
-    # parser.add_argument("--num_paths", type=str, default="1,1,1")
-    # parser.add_argument("--num_iter", type=int, default=500)
-    # parser.add_argument('--free', action='store_true')
-    # Please ensure that image resolution is divisible by pool_size; otherwise the performance would drop a lot.
-    # parser.add_argument('--pool_size', type=int, default=40, help="the pooled image size for next path initialization")
-    # parser.add_argument('--save_loss', action='store_true')
-    # parser.add_argument('--save_init', action='store_true')
-    # parser.add_argument('--save_image', action='store_true')
-    # parser.add_argument('--save_video', action='store_true')
-    # parser.add_argument('--print_weight', action='store_true')
-    # parser.add_argument('--circle_init_radius',  type=float)
-    cfg = edict()
-    args = parser.parse_args()
-    cfg.debug = args.debug
-    cfg.config = args.config
-    cfg.experiment = args.experiment
-    cfg.seed = args.seed
-    cfg.target = args.target
-    cfg.log_dir = args.log_dir
-    cfg.initial = args.initial
-    cfg.signature = args.signature
-    # set cfg num_segments in command
-    cfg.num_segments = args.num_segments
-    if args.seginit is not None:
-        cfg.seginit = edict()
-        cfg.seginit.type = args.seginit[0]
-        if cfg.seginit.type == 'circle':
-            cfg.seginit.radius = float(args.seginit[1])
-    return cfg
-
-def ycrcb_conversion(im, format='[bs x 3 x 2D]', reverse=False):
-    mat = torch.FloatTensor([
-        [ 65.481/255, 128.553/255,  24.966/255], # ranged_from [0, 219/255]
-        [-37.797/255, -74.203/255, 112.000/255], # ranged_from [-112/255, 112/255]
-        [112.000/255, -93.786/255, -18.214/255], # ranged_from [-112/255, 112/255]
-    ]).to(im.device)
-
-    if reverse:
-        mat = mat.inverse()
-
-    if format == '[bs x 3 x 2D]':
-        im = im.permute(0, 2, 3, 1)
-        im = torch.matmul(im, mat.T)
-        im = im.permute(0, 3, 1, 2).contiguous()
-        return im
-    elif format == '[2D x 3]':
-        im = torch.matmul(im, mat.T)
-        return im
-    else:
-        raise ValueError
-
-class random_coord_init():
-    def __init__(self, canvas_size):
-        self.canvas_size = canvas_size
-    def __call__(self):
-        h, w = self.canvas_size
-        return [npr.uniform(0, 1)*w, npr.uniform(0, 1)*h]
-
-class naive_coord_init():
-    def __init__(self, pred, gt, format='[bs x c x 2D]', replace_sampling=True):
-        if isinstance(pred, torch.Tensor):
-            pred = pred.detach().cpu().numpy()
-        if isinstance(gt, torch.Tensor):
-            gt = gt.detach().cpu().numpy()
-
-        if format == '[bs x c x 2D]':
-            self.map = ((pred[0] - gt[0])**2).sum(0)
-        elif format == ['[2D x c]']:
-            self.map = ((pred - gt)**2).sum(-1)
-        else:
-            raise ValueError
-        self.replace_sampling = replace_sampling
-
-    def __call__(self):
-        coord = np.where(self.map == self.map.max())
-        coord_h, coord_w = coord[0][0], coord[1][0]
-        if self.replace_sampling:
-            self.map[coord_h, coord_w] = -1
-        return [coord_w, coord_h]
-
-
-class sparse_coord_init():
-    def __init__(self, pred, gt, format='[bs x c x 2D]', quantile_interval=200, nodiff_thres=0.1):
-        if isinstance(pred, torch.Tensor):
-            pred = pred.detach().cpu().numpy()
-        if isinstance(gt, torch.Tensor):
-            gt = gt.detach().cpu().numpy()
-        if format == '[bs x c x 2D]':
-            self.map = ((pred[0] - gt[0])**2).sum(0)
-            self.reference_gt = copy.deepcopy(
-                np.transpose(gt[0], (1, 2, 0)))
-        elif format == ['[2D x c]']:
-            self.map = (np.abs(pred - gt)).sum(-1)
-            self.reference_gt = copy.deepcopy(gt[0])
-        else:
-            raise ValueError
-        # OptionA: Zero too small errors to avoid the error too small deadloop
-        self.map[self.map < nodiff_thres] = 0
-        quantile_interval = np.linspace(0., 1., quantile_interval)
-        quantized_interval = np.quantile(self.map, quantile_interval)
-        # remove redundant
-        quantized_interval = np.unique(quantized_interval)
-        quantized_interval = sorted(quantized_interval[1:-1])
-        self.map = np.digitize(self.map, quantized_interval, right=False)
-        self.map = np.clip(self.map, 0, 255).astype(np.uint8)
-        self.idcnt = {}
-        for idi in sorted(np.unique(self.map)):
-            self.idcnt[idi] = (self.map==idi).sum()
-        self.idcnt.pop(min(self.idcnt.keys()))
-        # remove smallest one to remove the correct region
-    def __call__(self):
-        if len(self.idcnt) == 0:
-            h, w = self.map.shape
-            return [npr.uniform(0, 1)*w, npr.uniform(0, 1)*h]
-        target_id = max(self.idcnt, key=self.idcnt.get)
-        _, component, cstats, ccenter = cv2.connectedComponentsWithStats(
-            (self.map==target_id).astype(np.uint8), connectivity=4)
-        # remove cid = 0, it is the invalid area
-        csize = [ci[-1] for ci in cstats[1:]]
-        target_cid = csize.index(max(csize))+1
-        center = ccenter[target_cid][::-1]
-        coord = np.stack(np.where(component == target_cid)).T
-        dist = np.linalg.norm(coord-center, axis=1)
-        target_coord_id = np.argmin(dist)
-        coord_h, coord_w = coord[target_coord_id]
-        # replace_sampling
-        self.idcnt[target_id] -= max(csize)
-        if self.idcnt[target_id] == 0:
-            self.idcnt.pop(target_id)
-        self.map[component == target_cid] = 0
-        return [coord_w, coord_h]
-
-
-def init_shapes(num_paths,
-                num_segments,
-                canvas_size,
-                seginit_cfg,
-                shape_cnt,
-                pos_init_method=None,
-                trainable_stroke=False,
-                **kwargs):
-    shapes = []
-    shape_groups = []
-    h, w = canvas_size
-
-    # change path init location
-    if pos_init_method is None:
-        pos_init_method = random_coord_init(canvas_size=canvas_size)
-
-    for i in range(num_paths):
-        num_control_points = [2] * num_segments
-
-        if seginit_cfg.type=="random":
-            points = []
-            p0 = pos_init_method()
-            color_ref = copy.deepcopy(p0)
-            points.append(p0)
-            for j in range(num_segments):
-                radius = seginit_cfg.radius
-                p1 = (p0[0] + radius * npr.uniform(-0.5, 0.5),
-                      p0[1] + radius * npr.uniform(-0.5, 0.5))
-                p2 = (p1[0] + radius * npr.uniform(-0.5, 0.5),
-                      p1[1] + radius * npr.uniform(-0.5, 0.5))
-                p3 = (p2[0] + radius * npr.uniform(-0.5, 0.5),
-                      p2[1] + radius * npr.uniform(-0.5, 0.5))
-                points.append(p1)
-                points.append(p2)
-                if j < num_segments - 1:
-                    points.append(p3)
-                    p0 = p3
-            points = torch.FloatTensor(points)
-
-        # circle points initialization
-        elif seginit_cfg.type=="circle":
-            radius = seginit_cfg.radius
-            if radius is None:
-                radius = npr.uniform(0.5, 1)
-            center = pos_init_method()
-            color_ref = copy.deepcopy(center)
-            points = get_bezier_circle(
-                radius=radius, segments=num_segments,
-                bias=center)
-
-        path = pydiffvg.Path(num_control_points = torch.LongTensor(num_control_points),
-                             points = points,
-                             stroke_width = torch.tensor(0.0),
-                             is_closed = True)
-        shapes.append(path)
-        # !!!!!!problem is here. the shape group shape_ids is wrong
-
-        if 'gt' in kwargs:
-            wref, href = color_ref
-            wref = max(0, min(int(wref), w-1))
-            href = max(0, min(int(href), h-1))
-            fill_color_init = list(gt[0, :, href, wref]) + [1.]
-            fill_color_init = torch.FloatTensor(fill_color_init)
-            stroke_color_init = torch.FloatTensor(npr.uniform(size=[4]))
-        else:
-            fill_color_init = torch.FloatTensor(npr.uniform(size=[4]))
-            stroke_color_init = torch.FloatTensor(npr.uniform(size=[4]))
-
-        path_group = pydiffvg.ShapeGroup(
-            shape_ids = torch.LongTensor([shape_cnt+i]),
-            fill_color = fill_color_init,
-            stroke_color = stroke_color_init,
-        )
-        shape_groups.append(path_group)
-
-    point_var = []
-    color_var = []
-
-    for path in shapes:
-        path.points.requires_grad = True
-        point_var.append(path.points)
-    for group in shape_groups:
-        group.fill_color.requires_grad = True
-        color_var.append(group.fill_color)
-
-    if trainable_stroke:
-        stroke_width_var = []
-        stroke_color_var = []
-        for path in shapes:
-            path.stroke_width.requires_grad = True
-            stroke_width_var.append(path.stroke_width)
-        for group in shape_groups:
-            group.stroke_color.requires_grad = True
-            stroke_color_var.append(group.stroke_color)
-        return shapes, shape_groups, point_var, color_var, stroke_width_var, stroke_color_var
-    else:
-        return shapes, shape_groups, point_var, color_var
-
-class linear_decay_lrlambda_f(object):
-    def __init__(self, decay_every, decay_ratio):
-        self.decay_every = decay_every
-        self.decay_ratio = decay_ratio
-
-    def __call__(self, n):
-        decay_time = n//self.decay_every
-        decay_step = n %self.decay_every
-        lr_s = self.decay_ratio**decay_time
-        lr_e = self.decay_ratio**(decay_time+1)
-        r = decay_step/self.decay_every
-        lr = lr_s * (1-r) + lr_e * r
-        return lr
-
-
-if __name__ == "__main__":
-
-    ###############
-    # make config #
-    ###############
-
-    cfg_arg = parse_args()
-    with open(cfg_arg.config, 'r') as f:
-        cfg = yaml.load(f, Loader=yaml.FullLoader)
-    cfg_default = edict(cfg['default'])
-    cfg = edict(cfg[cfg_arg.experiment])
-    cfg.update(cfg_default)
-    cfg.update(cfg_arg)
-    cfg.exid = get_experiment_id(cfg.debug)
-
-    cfg.experiment_dir = \
-        osp.join(cfg.log_dir, '{}_{}'.format(cfg.exid, '_'.join(cfg.signature)))
-    configfile = osp.join(cfg.experiment_dir, 'config.yaml')
-    check_and_create_dir(configfile)
-    with open(osp.join(configfile), 'w') as f:
-        yaml.dump(edict_2_dict(cfg), f)
-
-    # Use GPU if available
-    pydiffvg.set_use_gpu(torch.cuda.is_available())
-    device = pydiffvg.get_device()
-
-    gt = np.array(PIL.Image.open(cfg.target))
-    print(f"Input image shape is: {gt.shape}")
-    if len(gt.shape) == 2:
-        print("Converting the gray-scale image to RGB.")
-        gt = gt.unsqueeze(dim=-1).repeat(1,1,3)
-    if gt.shape[2] == 4:
-        print("Input image includes alpha channel, simply dropout alpha channel.")
-        gt = gt[:, :, :3]
-    gt = (gt/255).astype(np.float32)
-    gt = torch.FloatTensor(gt).permute(2, 0, 1)[None].to(device)
-    if cfg.use_ycrcb:
-        gt = ycrcb_conversion(gt)
-    h, w = gt.shape[2:]
-
-    path_schedule = get_path_schedule(**cfg.path_schedule)
-
-    if cfg.seed is not None:
-        random.seed(cfg.seed)
-        npr.seed(cfg.seed)
-        torch.manual_seed(cfg.seed)
-    render = pydiffvg.RenderFunction.apply
-
-    shapes_record, shape_groups_record = [], []
-
-    region_loss = None
-    loss_matrix = []
-
-    para_point, para_color = {}, {}
-    if cfg.trainable.stroke:
-        para_stroke_width, para_stroke_color = {}, {}
-
-    pathn_record = []
-    # Background
-    if cfg.trainable.bg:
-        # meancolor = gt.mean([2, 3])[0]
-        para_bg = torch.tensor([1., 1., 1.], requires_grad=True, device=device)
-    else:
-        if cfg.use_ycrcb:
-            para_bg = torch.tensor([219/255, 0, 0], requires_grad=False, device=device)
-        else:
-            para_bg = torch.tensor([1., 1., 1.], requires_grad=False, device=device)
-
-    ##################
-    # start_training #
-    ##################
-
-    loss_weight = None
-    loss_weight_keep = 0
-    if cfg.coord_init.type == 'naive':
-        pos_init_method = naive_coord_init(
-            para_bg.view(1, -1, 1, 1).repeat(1, 1, h, w), gt)
-    elif cfg.coord_init.type == 'sparse':
-        pos_init_method = sparse_coord_init(
-            para_bg.view(1, -1, 1, 1).repeat(1, 1, h, w), gt)
-    elif cfg.coord_init.type == 'random':
-        pos_init_method = random_coord_init([h, w])
-    else:
-        raise ValueError
-
-    lrlambda_f = linear_decay_lrlambda_f(cfg.num_iter, 0.4)
-    optim_schedular_dict = {}
-
-    for path_idx, pathn in enumerate(path_schedule):
-        loss_list = []
-        print("=> Adding [{}] paths, [{}] ...".format(pathn, cfg.seginit.type))
-        pathn_record.append(pathn)
-        pathn_record_str = '-'.join([str(i) for i in pathn_record])
-
-        # initialize new shapes related stuffs.
-        if cfg.trainable.stroke:
-            shapes, shape_groups, point_var, color_var, stroke_width_var, stroke_color_var = init_shapes(
-                pathn, cfg.num_segments, (h, w),
-                cfg.seginit, len(shapes_record),
-                pos_init_method,
-                trainable_stroke=True,
-                gt=gt, )
-            para_stroke_width[path_idx] = stroke_width_var
-            para_stroke_color[path_idx] = stroke_color_var
-        else:
-            shapes, shape_groups, point_var, color_var = init_shapes(
-                pathn, cfg.num_segments, (h, w),
-                cfg.seginit, len(shapes_record),
-                pos_init_method,
-                trainable_stroke=False,
-                gt=gt, )
-
-        shapes_record += shapes
-        shape_groups_record += shape_groups
-
-        if cfg.save.init:
-            filename = os.path.join(
-                cfg.experiment_dir, "svg-init",
-                "{}-init.svg".format(pathn_record_str))
-            check_and_create_dir(filename)
-            pydiffvg.save_svg(
-                filename, w, h,
-                shapes_record, shape_groups_record)
-
-        para = {}
-        if (cfg.trainable.bg) and (path_idx == 0):
-            para['bg'] = [para_bg]
-        para['point'] = point_var
-        para['color'] = color_var
-        if cfg.trainable.stroke:
-            para['stroke_width'] = stroke_width_var
-            para['stroke_color'] = stroke_color_var
-
-        pg = [{'params' : para[ki], 'lr' : cfg.lr_base[ki]} for ki in sorted(para.keys())]
-        optim = torch.optim.Adam(pg)
-
-        if cfg.trainable.record:
-            scheduler = LambdaLR(
-                optim, lr_lambda=lrlambda_f, last_epoch=-1)
-        else:
-            scheduler = LambdaLR(
-                optim, lr_lambda=lrlambda_f, last_epoch=cfg.num_iter)
-        optim_schedular_dict[path_idx] = (optim, scheduler)
-
-        # Inner loop training
-        t_range = tqdm(range(cfg.num_iter))
-        for t in t_range:
-
-            for _, (optim, _) in optim_schedular_dict.items():
-                optim.zero_grad()
-
-            # Forward pass: render the image.
-            scene_args = pydiffvg.RenderFunction.serialize_scene(
-                w, h, shapes_record, shape_groups_record)
-            img = render(w, h, 2, 2, t, None, *scene_args)
-
-            # Compose img with white background
-            img = img[:, :, 3:4] * img[:, :, :3] + \
-                para_bg * (1 - img[:, :, 3:4])
-
-            if cfg.save.video:
-                filename = os.path.join(
-                    cfg.experiment_dir, "video-png",
-                    "{}-iter{}.png".format(pathn_record_str, t))
-                check_and_create_dir(filename)
-                if cfg.use_ycrcb:
-                    imshow = ycrcb_conversion(
-                        img, format='[2D x 3]', reverse=True).detach().cpu()
-                else:
-                    imshow = img.detach().cpu()
-                pydiffvg.imwrite(imshow, filename, gamma=gamma)
-
-            x = img.unsqueeze(0).permute(0, 3, 1, 2) # HWC -> NCHW
-
-            if cfg.use_ycrcb:
-                color_reweight = torch.FloatTensor([255/219, 255/224, 255/255]).to(device)
-                loss = ((x-gt)*(color_reweight.view(1, -1, 1, 1)))**2
-            else:
-                loss = ((x-gt)**2)
-
-            if cfg.loss.use_l1_loss:
-                loss = abs(x-gt)
-
-            if cfg.loss.use_distance_weighted_loss:
-                if cfg.use_ycrcb:
-                    raise ValueError
-                shapes_forsdf = copy.deepcopy(shapes)
-                shape_groups_forsdf = copy.deepcopy(shape_groups)
-                for si in shapes_forsdf:
-                    si.stroke_width = torch.FloatTensor([0]).to(device)
-                for sg_idx, sgi in enumerate(shape_groups_forsdf):
-                    sgi.fill_color = torch.FloatTensor([1, 1, 1, 1]).to(device)
-                    sgi.shape_ids = torch.LongTensor([sg_idx]).to(device)
-
-                sargs_forsdf = pydiffvg.RenderFunction.serialize_scene(
-                    w, h, shapes_forsdf, shape_groups_forsdf)
-                with torch.no_grad():
-                    im_forsdf = render(w, h, 2, 2, 0, None, *sargs_forsdf)
-                # use alpha channel is a trick to get 0-1 image
-                im_forsdf = (im_forsdf[:, :, 3]).detach().cpu().numpy()
-                loss_weight = get_sdf(im_forsdf, normalize='to1')
-                loss_weight += loss_weight_keep
-                loss_weight = np.clip(loss_weight, 0, 1)
-                loss_weight = torch.FloatTensor(loss_weight).to(device)
-
-            if cfg.save.loss:
-                save_loss = loss.squeeze(dim=0).mean(dim=0,keepdim=False).cpu().detach().numpy()
-                save_weight = loss_weight.cpu().detach().numpy()
-                save_weighted_loss = save_loss*save_weight
-                # normalize to [0,1]
-                save_loss = (save_loss - np.min(save_loss))/np.ptp(save_loss)
-                save_weight = (save_weight - np.min(save_weight))/np.ptp(save_weight)
-                save_weighted_loss = (save_weighted_loss - np.min(save_weighted_loss))/np.ptp(save_weighted_loss)
-
-                # save
-                plt.imshow(save_loss, cmap='Reds')
-                plt.axis('off')
-                # plt.colorbar()
-                filename = os.path.join(cfg.experiment_dir, "loss", "{}-iter{}-mseloss.png".format(pathn_record_str, t))
-                check_and_create_dir(filename)
-                plt.savefig(filename, dpi=800)
-                plt.close()
-
-                plt.imshow(save_weight, cmap='Greys')
-                plt.axis('off')
-                # plt.colorbar()
-                filename = os.path.join(cfg.experiment_dir, "loss", "{}-iter{}-sdfweight.png".format(pathn_record_str, t))
-                plt.savefig(filename, dpi=800)
-                plt.close()
-
-                plt.imshow(save_weighted_loss, cmap='Reds')
-                plt.axis('off')
-                # plt.colorbar()
-                filename = os.path.join(cfg.experiment_dir, "loss", "{}-iter{}-weightedloss.png".format(pathn_record_str, t))
-                plt.savefig(filename, dpi=800)
-                plt.close()
-
-
-
-
-
-            if loss_weight is None:
-                loss = loss.sum(1).mean()
-            else:
-                loss = (loss.sum(1)*loss_weight).mean()
-
-            # if (cfg.loss.bis_loss_weight is not None)  and (cfg.loss.bis_loss_weight > 0):
-            #     loss_bis = bezier_intersection_loss(point_var[0]) * cfg.loss.bis_loss_weight
-            #     loss = loss + loss_bis
-            if (cfg.loss.xing_loss_weight is not None) \
-                    and (cfg.loss.xing_loss_weight > 0):
-                loss_xing = xing_loss(point_var) * cfg.loss.xing_loss_weight
-                loss = loss + loss_xing
-
-
-            loss_list.append(loss.item())
-            t_range.set_postfix({'loss': loss.item()})
-            loss.backward()
-
-            # step
-            for _, (optim, scheduler) in optim_schedular_dict.items():
-                optim.step()
-                scheduler.step()
-
-            for group in shape_groups_record:
-                group.fill_color.data.clamp_(0.0, 1.0)
-
-        if cfg.loss.use_distance_weighted_loss:
-            loss_weight_keep = loss_weight.detach().cpu().numpy() * 1
-
-        if not cfg.trainable.record:
-            for _, pi in pg.items():
-                for ppi in pi:
-                    pi.require_grad = False
-            optim_schedular_dict = {}
-
-        if cfg.save.image:
-            filename = os.path.join(
-                cfg.experiment_dir, "demo-png", "{}.png".format(pathn_record_str))
-            check_and_create_dir(filename)
-            if cfg.use_ycrcb:
-                imshow = ycrcb_conversion(
-                    img, format='[2D x 3]', reverse=True).detach().cpu()
-            else:
-                imshow = img.detach().cpu()
-            pydiffvg.imwrite(imshow, filename, gamma=gamma)
-
-        if cfg.save.output:
-            filename = os.path.join(
-                cfg.experiment_dir, "output-svg", "{}.svg".format(pathn_record_str))
-            check_and_create_dir(filename)
-            pydiffvg.save_svg(filename, w, h, shapes_record, shape_groups_record)
-
-        loss_matrix.append(loss_list)
-
-        # calculate the pixel loss
-        # pixel_loss = ((x-gt)**2).sum(dim=1, keepdim=True).sqrt_() # [N,1,H, W]
-        # region_loss = adaptive_avg_pool2d(pixel_loss, cfg.region_loss_pool_size)
-        # loss_weight = torch.softmax(region_loss.reshape(1, 1, -1), dim=-1)\
-        #     .reshape_as(region_loss)
-
-        pos_init_method = naive_coord_init(x, gt)
-
-        if cfg.coord_init.type == 'naive':
-            pos_init_method = naive_coord_init(x, gt)
-        elif cfg.coord_init.type == 'sparse':
-            pos_init_method = sparse_coord_init(x, gt)
-        elif cfg.coord_init.type == 'random':
-            pos_init_method = random_coord_init([h, w])
-        else:
-            raise ValueError
-
-        if cfg.save.video:
-            print("saving iteration video...")
-            img_array = []
-            for ii in range(0, cfg.num_iter):
-                filename = os.path.join(
-                    cfg.experiment_dir, "video-png", 
-                    "{}-iter{}.png".format(pathn_record_str, ii))
-                img = cv2.imread(filename)
-                # cv2.putText(
-                #     img, "Path:{} \nIteration:{}".format(pathn_record_str, ii), 
-                #     (10, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1)
-                img_array.append(img)
-
-            videoname = os.path.join(
-                cfg.experiment_dir, "video-mp4",
-                "{}.mp4".format(pathn_record_str))
-            check_and_create_dir(videoname)
-            out = cv2.VideoWriter(
-                videoname, 
-                cv2.VideoWriter_fourcc(*'mp4v'),
-                # cv2.VideoWriter_fourcc(*'FFV1'),
-                20.0, (w, h))
-            for iii in range(len(img_array)):
-                out.write(img_array[iii])
-            out.release()
-            # shutil.rmtree(os.path.join(cfg.experiment_dir, "video-png"))
-
-    print("The last loss is: {}".format(loss.item()))
diff --git a/spaces/CVPR/LIVE/pybind11/tests/test_eigen.py b/spaces/CVPR/LIVE/pybind11/tests/test_eigen.py
deleted file mode 100644
index ac68471474a869b59f786fd35cc69a3f2f1b27d5..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/pybind11/tests/test_eigen.py
+++ /dev/null
@@ -1,697 +0,0 @@
-# -*- coding: utf-8 -*-
-import pytest
-from pybind11_tests import ConstructorStats
-
-np = pytest.importorskip("numpy")
-m = pytest.importorskip("pybind11_tests.eigen")
-
-
-ref = np.array([[ 0.,  3,  0,  0,  0, 11],
-                [22,  0,  0,  0, 17, 11],
-                [ 7,  5,  0,  1,  0, 11],
-                [ 0,  0,  0,  0,  0, 11],
-                [ 0,  0, 14,  0,  8, 11]])
-
-
-def assert_equal_ref(mat):
-    np.testing.assert_array_equal(mat, ref)
-
-
-def assert_sparse_equal_ref(sparse_mat):
-    assert_equal_ref(sparse_mat.toarray())
-
-
-def test_fixed():
-    assert_equal_ref(m.fixed_c())
-    assert_equal_ref(m.fixed_r())
-    assert_equal_ref(m.fixed_copy_r(m.fixed_r()))
-    assert_equal_ref(m.fixed_copy_c(m.fixed_c()))
-    assert_equal_ref(m.fixed_copy_r(m.fixed_c()))
-    assert_equal_ref(m.fixed_copy_c(m.fixed_r()))
-
-
-def test_dense():
-    assert_equal_ref(m.dense_r())
-    assert_equal_ref(m.dense_c())
-    assert_equal_ref(m.dense_copy_r(m.dense_r()))
-    assert_equal_ref(m.dense_copy_c(m.dense_c()))
-    assert_equal_ref(m.dense_copy_r(m.dense_c()))
-    assert_equal_ref(m.dense_copy_c(m.dense_r()))
-
-
-def test_partially_fixed():
-    ref2 = np.array([[0., 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]])
-    np.testing.assert_array_equal(m.partial_copy_four_rm_r(ref2), ref2)
-    np.testing.assert_array_equal(m.partial_copy_four_rm_c(ref2), ref2)
-    np.testing.assert_array_equal(m.partial_copy_four_rm_r(ref2[:, 1]), ref2[:, [1]])
-    np.testing.assert_array_equal(m.partial_copy_four_rm_c(ref2[0, :]), ref2[[0], :])
-    np.testing.assert_array_equal(m.partial_copy_four_rm_r(ref2[:, (0, 2)]), ref2[:, (0, 2)])
-    np.testing.assert_array_equal(
-        m.partial_copy_four_rm_c(ref2[(3, 1, 2), :]), ref2[(3, 1, 2), :])
-
-    np.testing.assert_array_equal(m.partial_copy_four_cm_r(ref2), ref2)
-    np.testing.assert_array_equal(m.partial_copy_four_cm_c(ref2), ref2)
-    np.testing.assert_array_equal(m.partial_copy_four_cm_r(ref2[:, 1]), ref2[:, [1]])
-    np.testing.assert_array_equal(m.partial_copy_four_cm_c(ref2[0, :]), ref2[[0], :])
-    np.testing.assert_array_equal(m.partial_copy_four_cm_r(ref2[:, (0, 2)]), ref2[:, (0, 2)])
-    np.testing.assert_array_equal(
-        m.partial_copy_four_cm_c(ref2[(3, 1, 2), :]), ref2[(3, 1, 2), :])
-
-    # TypeError should be raise for a shape mismatch
-    functions = [m.partial_copy_four_rm_r, m.partial_copy_four_rm_c,
-                 m.partial_copy_four_cm_r, m.partial_copy_four_cm_c]
-    matrix_with_wrong_shape = [[1, 2],
-                               [3, 4]]
-    for f in functions:
-        with pytest.raises(TypeError) as excinfo:
-            f(matrix_with_wrong_shape)
-        assert "incompatible function arguments" in str(excinfo.value)
-
-
-def test_mutator_descriptors():
-    zr = np.arange(30, dtype='float32').reshape(5, 6)  # row-major
-    zc = zr.reshape(6, 5).transpose()  # column-major
-
-    m.fixed_mutator_r(zr)
-    m.fixed_mutator_c(zc)
-    m.fixed_mutator_a(zr)
-    m.fixed_mutator_a(zc)
-    with pytest.raises(TypeError) as excinfo:
-        m.fixed_mutator_r(zc)
-    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6],'
-            ' flags.writeable, flags.c_contiguous]) -> None'
-            in str(excinfo.value))
-    with pytest.raises(TypeError) as excinfo:
-        m.fixed_mutator_c(zr)
-    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6],'
-            ' flags.writeable, flags.f_contiguous]) -> None'
-            in str(excinfo.value))
-    with pytest.raises(TypeError) as excinfo:
-        m.fixed_mutator_a(np.array([[1, 2], [3, 4]], dtype='float32'))
-    assert ('(arg0: numpy.ndarray[numpy.float32[5, 6], flags.writeable]) -> None'
-            in str(excinfo.value))
-    zr.flags.writeable = False
-    with pytest.raises(TypeError):
-        m.fixed_mutator_r(zr)
-    with pytest.raises(TypeError):
-        m.fixed_mutator_a(zr)
-
-
-def test_cpp_casting():
-    assert m.cpp_copy(m.fixed_r()) == 22.
-    assert m.cpp_copy(m.fixed_c()) == 22.
-    z = np.array([[5., 6], [7, 8]])
-    assert m.cpp_copy(z) == 7.
-    assert m.cpp_copy(m.get_cm_ref()) == 21.
-    assert m.cpp_copy(m.get_rm_ref()) == 21.
-    assert m.cpp_ref_c(m.get_cm_ref()) == 21.
-    assert m.cpp_ref_r(m.get_rm_ref()) == 21.
-    with pytest.raises(RuntimeError) as excinfo:
-        # Can't reference m.fixed_c: it contains floats, m.cpp_ref_any wants doubles
-        m.cpp_ref_any(m.fixed_c())
-    assert 'Unable to cast Python instance' in str(excinfo.value)
-    with pytest.raises(RuntimeError) as excinfo:
-        # Can't reference m.fixed_r: it contains floats, m.cpp_ref_any wants doubles
-        m.cpp_ref_any(m.fixed_r())
-    assert 'Unable to cast Python instance' in str(excinfo.value)
-    assert m.cpp_ref_any(m.ReturnTester.create()) == 1.
-
-    assert m.cpp_ref_any(m.get_cm_ref()) == 21.
-    assert m.cpp_ref_any(m.get_cm_ref()) == 21.
-
-
-def test_pass_readonly_array():
-    z = np.full((5, 6), 42.0)
-    z.flags.writeable = False
-    np.testing.assert_array_equal(z, m.fixed_copy_r(z))
-    np.testing.assert_array_equal(m.fixed_r_const(), m.fixed_r())
-    assert not m.fixed_r_const().flags.writeable
-    np.testing.assert_array_equal(m.fixed_copy_r(m.fixed_r_const()), m.fixed_r_const())
-
-
-def test_nonunit_stride_from_python():
-    counting_mat = np.arange(9.0, dtype=np.float32).reshape((3, 3))
-    second_row = counting_mat[1, :]
-    second_col = counting_mat[:, 1]
-    np.testing.assert_array_equal(m.double_row(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_col(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_complex(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_row(second_col), 2.0 * second_col)
-    np.testing.assert_array_equal(m.double_col(second_col), 2.0 * second_col)
-    np.testing.assert_array_equal(m.double_complex(second_col), 2.0 * second_col)
-
-    counting_3d = np.arange(27.0, dtype=np.float32).reshape((3, 3, 3))
-    slices = [counting_3d[0, :, :], counting_3d[:, 0, :], counting_3d[:, :, 0]]
-    for ref_mat in slices:
-        np.testing.assert_array_equal(m.double_mat_cm(ref_mat), 2.0 * ref_mat)
-        np.testing.assert_array_equal(m.double_mat_rm(ref_mat), 2.0 * ref_mat)
-
-    # Mutator:
-    m.double_threer(second_row)
-    m.double_threec(second_col)
-    np.testing.assert_array_equal(counting_mat, [[0., 2, 2], [6, 16, 10], [6, 14, 8]])
-
-
-def test_negative_stride_from_python(msg):
-    """Eigen doesn't support (as of yet) negative strides. When a function takes an Eigen matrix by
-    copy or const reference, we can pass a numpy array that has negative strides.  Otherwise, an
-    exception will be thrown as Eigen will not be able to map the numpy array."""
-
-    counting_mat = np.arange(9.0, dtype=np.float32).reshape((3, 3))
-    counting_mat = counting_mat[::-1, ::-1]
-    second_row = counting_mat[1, :]
-    second_col = counting_mat[:, 1]
-    np.testing.assert_array_equal(m.double_row(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_col(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_complex(second_row), 2.0 * second_row)
-    np.testing.assert_array_equal(m.double_row(second_col), 2.0 * second_col)
-    np.testing.assert_array_equal(m.double_col(second_col), 2.0 * second_col)
-    np.testing.assert_array_equal(m.double_complex(second_col), 2.0 * second_col)
-
-    counting_3d = np.arange(27.0, dtype=np.float32).reshape((3, 3, 3))
-    counting_3d = counting_3d[::-1, ::-1, ::-1]
-    slices = [counting_3d[0, :, :], counting_3d[:, 0, :], counting_3d[:, :, 0]]
-    for ref_mat in slices:
-        np.testing.assert_array_equal(m.double_mat_cm(ref_mat), 2.0 * ref_mat)
-        np.testing.assert_array_equal(m.double_mat_rm(ref_mat), 2.0 * ref_mat)
-
-    # Mutator:
-    with pytest.raises(TypeError) as excinfo:
-        m.double_threer(second_row)
-    assert msg(excinfo.value) == """
-        double_threer(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[numpy.float32[1, 3], flags.writeable]) -> None
-
-        Invoked with: """ + repr(np.array([ 5.,  4.,  3.], dtype='float32'))  # noqa: E501 line too long
-
-    with pytest.raises(TypeError) as excinfo:
-        m.double_threec(second_col)
-    assert msg(excinfo.value) == """
-        double_threec(): incompatible function arguments. The following argument types are supported:
-            1. (arg0: numpy.ndarray[numpy.float32[3, 1], flags.writeable]) -> None
-
-        Invoked with: """ + repr(np.array([ 7.,  4.,  1.], dtype='float32'))  # noqa: E501 line too long
-
-
-def test_nonunit_stride_to_python():
-    assert np.all(m.diagonal(ref) == ref.diagonal())
-    assert np.all(m.diagonal_1(ref) == ref.diagonal(1))
-    for i in range(-5, 7):
-        assert np.all(m.diagonal_n(ref, i) == ref.diagonal(i)), "m.diagonal_n({})".format(i)
-
-    assert np.all(m.block(ref, 2, 1, 3, 3) == ref[2:5, 1:4])
-    assert np.all(m.block(ref, 1, 4, 4, 2) == ref[1:, 4:])
-    assert np.all(m.block(ref, 1, 4, 3, 2) == ref[1:4, 4:])
-
-
-def test_eigen_ref_to_python():
-    chols = [m.cholesky1, m.cholesky2, m.cholesky3, m.cholesky4]
-    for i, chol in enumerate(chols, start=1):
-        mymat = chol(np.array([[1., 2, 4], [2, 13, 23], [4, 23, 77]]))
-        assert np.all(mymat == np.array([[1, 0, 0], [2, 3, 0], [4, 5, 6]])), "cholesky{}".format(i)
-
-
-def assign_both(a1, a2, r, c, v):
-    a1[r, c] = v
-    a2[r, c] = v
-
-
-def array_copy_but_one(a, r, c, v):
-    z = np.array(a, copy=True)
-    z[r, c] = v
-    return z
-
-
-def test_eigen_return_references():
-    """Tests various ways of returning references and non-referencing copies"""
-
-    master = np.ones((10, 10))
-    a = m.ReturnTester()
-    a_get1 = a.get()
-    assert not a_get1.flags.owndata and a_get1.flags.writeable
-    assign_both(a_get1, master, 3, 3, 5)
-    a_get2 = a.get_ptr()
-    assert not a_get2.flags.owndata and a_get2.flags.writeable
-    assign_both(a_get1, master, 2, 3, 6)
-
-    a_view1 = a.view()
-    assert not a_view1.flags.owndata and not a_view1.flags.writeable
-    with pytest.raises(ValueError):
-        a_view1[2, 3] = 4
-    a_view2 = a.view_ptr()
-    assert not a_view2.flags.owndata and not a_view2.flags.writeable
-    with pytest.raises(ValueError):
-        a_view2[2, 3] = 4
-
-    a_copy1 = a.copy_get()
-    assert a_copy1.flags.owndata and a_copy1.flags.writeable
-    np.testing.assert_array_equal(a_copy1, master)
-    a_copy1[7, 7] = -44  # Shouldn't affect anything else
-    c1want = array_copy_but_one(master, 7, 7, -44)
-    a_copy2 = a.copy_view()
-    assert a_copy2.flags.owndata and a_copy2.flags.writeable
-    np.testing.assert_array_equal(a_copy2, master)
-    a_copy2[4, 4] = -22  # Shouldn't affect anything else
-    c2want = array_copy_but_one(master, 4, 4, -22)
-
-    a_ref1 = a.ref()
-    assert not a_ref1.flags.owndata and a_ref1.flags.writeable
-    assign_both(a_ref1, master, 1, 1, 15)
-    a_ref2 = a.ref_const()
-    assert not a_ref2.flags.owndata and not a_ref2.flags.writeable
-    with pytest.raises(ValueError):
-        a_ref2[5, 5] = 33
-    a_ref3 = a.ref_safe()
-    assert not a_ref3.flags.owndata and a_ref3.flags.writeable
-    assign_both(a_ref3, master, 0, 7, 99)
-    a_ref4 = a.ref_const_safe()
-    assert not a_ref4.flags.owndata and not a_ref4.flags.writeable
-    with pytest.raises(ValueError):
-        a_ref4[7, 0] = 987654321
-
-    a_copy3 = a.copy_ref()
-    assert a_copy3.flags.owndata and a_copy3.flags.writeable
-    np.testing.assert_array_equal(a_copy3, master)
-    a_copy3[8, 1] = 11
-    c3want = array_copy_but_one(master, 8, 1, 11)
-    a_copy4 = a.copy_ref_const()
-    assert a_copy4.flags.owndata and a_copy4.flags.writeable
-    np.testing.assert_array_equal(a_copy4, master)
-    a_copy4[8, 4] = 88
-    c4want = array_copy_but_one(master, 8, 4, 88)
-
-    a_block1 = a.block(3, 3, 2, 2)
-    assert not a_block1.flags.owndata and a_block1.flags.writeable
-    a_block1[0, 0] = 55
-    master[3, 3] = 55
-    a_block2 = a.block_safe(2, 2, 3, 2)
-    assert not a_block2.flags.owndata and a_block2.flags.writeable
-    a_block2[2, 1] = -123
-    master[4, 3] = -123
-    a_block3 = a.block_const(6, 7, 4, 3)
-    assert not a_block3.flags.owndata and not a_block3.flags.writeable
-    with pytest.raises(ValueError):
-        a_block3[2, 2] = -44444
-
-    a_copy5 = a.copy_block(2, 2, 2, 3)
-    assert a_copy5.flags.owndata and a_copy5.flags.writeable
-    np.testing.assert_array_equal(a_copy5, master[2:4, 2:5])
-    a_copy5[1, 1] = 777
-    c5want = array_copy_but_one(master[2:4, 2:5], 1, 1, 777)
-
-    a_corn1 = a.corners()
-    assert not a_corn1.flags.owndata and a_corn1.flags.writeable
-    a_corn1 *= 50
-    a_corn1[1, 1] = 999
-    master[0, 0] = 50
-    master[0, 9] = 50
-    master[9, 0] = 50
-    master[9, 9] = 999
-    a_corn2 = a.corners_const()
-    assert not a_corn2.flags.owndata and not a_corn2.flags.writeable
-    with pytest.raises(ValueError):
-        a_corn2[1, 0] = 51
-
-    # All of the changes made all the way along should be visible everywhere
-    # now (except for the copies, of course)
-    np.testing.assert_array_equal(a_get1, master)
-    np.testing.assert_array_equal(a_get2, master)
-    np.testing.assert_array_equal(a_view1, master)
-    np.testing.assert_array_equal(a_view2, master)
-    np.testing.assert_array_equal(a_ref1, master)
-    np.testing.assert_array_equal(a_ref2, master)
-    np.testing.assert_array_equal(a_ref3, master)
-    np.testing.assert_array_equal(a_ref4, master)
-    np.testing.assert_array_equal(a_block1, master[3:5, 3:5])
-    np.testing.assert_array_equal(a_block2, master[2:5, 2:4])
-    np.testing.assert_array_equal(a_block3, master[6:10, 7:10])
-    np.testing.assert_array_equal(a_corn1, master[0::master.shape[0] - 1, 0::master.shape[1] - 1])
-    np.testing.assert_array_equal(a_corn2, master[0::master.shape[0] - 1, 0::master.shape[1] - 1])
-
-    np.testing.assert_array_equal(a_copy1, c1want)
-    np.testing.assert_array_equal(a_copy2, c2want)
-    np.testing.assert_array_equal(a_copy3, c3want)
-    np.testing.assert_array_equal(a_copy4, c4want)
-    np.testing.assert_array_equal(a_copy5, c5want)
-
-
-def assert_keeps_alive(cl, method, *args):
-    cstats = ConstructorStats.get(cl)
-    start_with = cstats.alive()
-    a = cl()
-    assert cstats.alive() == start_with + 1
-    z = method(a, *args)
-    assert cstats.alive() == start_with + 1
-    del a
-    # Here's the keep alive in action:
-    assert cstats.alive() == start_with + 1
-    del z
-    # Keep alive should have expired:
-    assert cstats.alive() == start_with
-
-
-def test_eigen_keepalive():
-    a = m.ReturnTester()
-    cstats = ConstructorStats.get(m.ReturnTester)
-    assert cstats.alive() == 1
-    unsafe = [a.ref(), a.ref_const(), a.block(1, 2, 3, 4)]
-    copies = [a.copy_get(), a.copy_view(), a.copy_ref(), a.copy_ref_const(),
-              a.copy_block(4, 3, 2, 1)]
-    del a
-    assert cstats.alive() == 0
-    del unsafe
-    del copies
-
-    for meth in [m.ReturnTester.get, m.ReturnTester.get_ptr, m.ReturnTester.view,
-                 m.ReturnTester.view_ptr, m.ReturnTester.ref_safe, m.ReturnTester.ref_const_safe,
-                 m.ReturnTester.corners, m.ReturnTester.corners_const]:
-        assert_keeps_alive(m.ReturnTester, meth)
-
-    for meth in [m.ReturnTester.block_safe, m.ReturnTester.block_const]:
-        assert_keeps_alive(m.ReturnTester, meth, 4, 3, 2, 1)
-
-
-def test_eigen_ref_mutators():
-    """Tests Eigen's ability to mutate numpy values"""
-
-    orig = np.array([[1., 2, 3], [4, 5, 6], [7, 8, 9]])
-    zr = np.array(orig)
-    zc = np.array(orig, order='F')
-    m.add_rm(zr, 1, 0, 100)
-    assert np.all(zr == np.array([[1., 2, 3], [104, 5, 6], [7, 8, 9]]))
-    m.add_cm(zc, 1, 0, 200)
-    assert np.all(zc == np.array([[1., 2, 3], [204, 5, 6], [7, 8, 9]]))
-
-    m.add_any(zr, 1, 0, 20)
-    assert np.all(zr == np.array([[1., 2, 3], [124, 5, 6], [7, 8, 9]]))
-    m.add_any(zc, 1, 0, 10)
-    assert np.all(zc == np.array([[1., 2, 3], [214, 5, 6], [7, 8, 9]]))
-
-    # Can't reference a col-major array with a row-major Ref, and vice versa:
-    with pytest.raises(TypeError):
-        m.add_rm(zc, 1, 0, 1)
-    with pytest.raises(TypeError):
-        m.add_cm(zr, 1, 0, 1)
-
-    # Overloads:
-    m.add1(zr, 1, 0, -100)
-    m.add2(zr, 1, 0, -20)
-    assert np.all(zr == orig)
-    m.add1(zc, 1, 0, -200)
-    m.add2(zc, 1, 0, -10)
-    assert np.all(zc == orig)
-
-    # a non-contiguous slice (this won't work on either the row- or
-    # column-contiguous refs, but should work for the any)
-    cornersr = zr[0::2, 0::2]
-    cornersc = zc[0::2, 0::2]
-
-    assert np.all(cornersr == np.array([[1., 3], [7, 9]]))
-    assert np.all(cornersc == np.array([[1., 3], [7, 9]]))
-
-    with pytest.raises(TypeError):
-        m.add_rm(cornersr, 0, 1, 25)
-    with pytest.raises(TypeError):
-        m.add_cm(cornersr, 0, 1, 25)
-    with pytest.raises(TypeError):
-        m.add_rm(cornersc, 0, 1, 25)
-    with pytest.raises(TypeError):
-        m.add_cm(cornersc, 0, 1, 25)
-    m.add_any(cornersr, 0, 1, 25)
-    m.add_any(cornersc, 0, 1, 44)
-    assert np.all(zr == np.array([[1., 2, 28], [4, 5, 6], [7, 8, 9]]))
-    assert np.all(zc == np.array([[1., 2, 47], [4, 5, 6], [7, 8, 9]]))
-
-    # You shouldn't be allowed to pass a non-writeable array to a mutating Eigen method:
-    zro = zr[0:4, 0:4]
-    zro.flags.writeable = False
-    with pytest.raises(TypeError):
-        m.add_rm(zro, 0, 0, 0)
-    with pytest.raises(TypeError):
-        m.add_any(zro, 0, 0, 0)
-    with pytest.raises(TypeError):
-        m.add1(zro, 0, 0, 0)
-    with pytest.raises(TypeError):
-        m.add2(zro, 0, 0, 0)
-
-    # integer array shouldn't be passable to a double-matrix-accepting mutating func:
-    zi = np.array([[1, 2], [3, 4]])
-    with pytest.raises(TypeError):
-        m.add_rm(zi)
-
-
-def test_numpy_ref_mutators():
-    """Tests numpy mutating Eigen matrices (for returned Eigen::Ref<...>s)"""
-
-    m.reset_refs()  # In case another test already changed it
-
-    zc = m.get_cm_ref()
-    zcro = m.get_cm_const_ref()
-    zr = m.get_rm_ref()
-    zrro = m.get_rm_const_ref()
-
-    assert [zc[1, 2], zcro[1, 2], zr[1, 2], zrro[1, 2]] == [23] * 4
-
-    assert not zc.flags.owndata and zc.flags.writeable
-    assert not zr.flags.owndata and zr.flags.writeable
-    assert not zcro.flags.owndata and not zcro.flags.writeable
-    assert not zrro.flags.owndata and not zrro.flags.writeable
-
-    zc[1, 2] = 99
-    expect = np.array([[11., 12, 13], [21, 22, 99], [31, 32, 33]])
-    # We should have just changed zc, of course, but also zcro and the original eigen matrix
-    assert np.all(zc == expect)
-    assert np.all(zcro == expect)
-    assert np.all(m.get_cm_ref() == expect)
-
-    zr[1, 2] = 99
-    assert np.all(zr == expect)
-    assert np.all(zrro == expect)
-    assert np.all(m.get_rm_ref() == expect)
-
-    # Make sure the readonly ones are numpy-readonly:
-    with pytest.raises(ValueError):
-        zcro[1, 2] = 6
-    with pytest.raises(ValueError):
-        zrro[1, 2] = 6
-
-    # We should be able to explicitly copy like this (and since we're copying,
-    # the const should drop away)
-    y1 = np.array(m.get_cm_const_ref())
-
-    assert y1.flags.owndata and y1.flags.writeable
-    # We should get copies of the eigen data, which was modified above:
-    assert y1[1, 2] == 99
-    y1[1, 2] += 12
-    assert y1[1, 2] == 111
-    assert zc[1, 2] == 99  # Make sure we aren't referencing the original
-
-
-def test_both_ref_mutators():
-    """Tests a complex chain of nested eigen/numpy references"""
-
-    m.reset_refs()  # In case another test already changed it
-
-    z = m.get_cm_ref()  # numpy -> eigen
-    z[0, 2] -= 3
-    z2 = m.incr_matrix(z, 1)  # numpy -> eigen -> numpy -> eigen
-    z2[1, 1] += 6
-    z3 = m.incr_matrix(z, 2)  # (numpy -> eigen)^3
-    z3[2, 2] += -5
-    z4 = m.incr_matrix(z, 3)  # (numpy -> eigen)^4
-    z4[1, 1] -= 1
-    z5 = m.incr_matrix(z, 4)  # (numpy -> eigen)^5
-    z5[0, 0] = 0
-    assert np.all(z == z2)
-    assert np.all(z == z3)
-    assert np.all(z == z4)
-    assert np.all(z == z5)
-    expect = np.array([[0., 22, 20], [31, 37, 33], [41, 42, 38]])
-    assert np.all(z == expect)
-
-    y = np.array(range(100), dtype='float64').reshape(10, 10)
-    y2 = m.incr_matrix_any(y, 10)  # np -> eigen -> np
-    y3 = m.incr_matrix_any(y2[0::2, 0::2], -33)  # np -> eigen -> np slice -> np -> eigen -> np
-    y4 = m.even_rows(y3)  # numpy -> eigen slice -> (... y3)
-    y5 = m.even_cols(y4)  # numpy -> eigen slice -> (... y4)
-    y6 = m.incr_matrix_any(y5, 1000)  # numpy -> eigen -> (... y5)
-
-    # Apply same mutations using just numpy:
-    yexpect = np.array(range(100), dtype='float64').reshape(10, 10)
-    yexpect += 10
-    yexpect[0::2, 0::2] -= 33
-    yexpect[0::4, 0::4] += 1000
-    assert np.all(y6 == yexpect[0::4, 0::4])
-    assert np.all(y5 == yexpect[0::4, 0::4])
-    assert np.all(y4 == yexpect[0::4, 0::2])
-    assert np.all(y3 == yexpect[0::2, 0::2])
-    assert np.all(y2 == yexpect)
-    assert np.all(y == yexpect)
-
-
-def test_nocopy_wrapper():
-    # get_elem requires a column-contiguous matrix reference, but should be
-    # callable with other types of matrix (via copying):
-    int_matrix_colmajor = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], order='F')
-    dbl_matrix_colmajor = np.array(int_matrix_colmajor, dtype='double', order='F', copy=True)
-    int_matrix_rowmajor = np.array(int_matrix_colmajor, order='C', copy=True)
-    dbl_matrix_rowmajor = np.array(int_matrix_rowmajor, dtype='double', order='C', copy=True)
-
-    # All should be callable via get_elem:
-    assert m.get_elem(int_matrix_colmajor) == 8
-    assert m.get_elem(dbl_matrix_colmajor) == 8
-    assert m.get_elem(int_matrix_rowmajor) == 8
-    assert m.get_elem(dbl_matrix_rowmajor) == 8
-
-    # All but the second should fail with m.get_elem_nocopy:
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_nocopy(int_matrix_colmajor)
-    assert ('get_elem_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.f_contiguous' in str(excinfo.value))
-    assert m.get_elem_nocopy(dbl_matrix_colmajor) == 8
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_nocopy(int_matrix_rowmajor)
-    assert ('get_elem_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.f_contiguous' in str(excinfo.value))
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_nocopy(dbl_matrix_rowmajor)
-    assert ('get_elem_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.f_contiguous' in str(excinfo.value))
-
-    # For the row-major test, we take a long matrix in row-major, so only the third is allowed:
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_rm_nocopy(int_matrix_colmajor)
-    assert ('get_elem_rm_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.c_contiguous' in str(excinfo.value))
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_rm_nocopy(dbl_matrix_colmajor)
-    assert ('get_elem_rm_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.c_contiguous' in str(excinfo.value))
-    assert m.get_elem_rm_nocopy(int_matrix_rowmajor) == 8
-    with pytest.raises(TypeError) as excinfo:
-        m.get_elem_rm_nocopy(dbl_matrix_rowmajor)
-    assert ('get_elem_rm_nocopy(): incompatible function arguments.' in str(excinfo.value) and
-            ', flags.c_contiguous' in str(excinfo.value))
-
-
-def test_eigen_ref_life_support():
-    """Ensure the lifetime of temporary arrays created by the `Ref` caster
-
-    The `Ref` caster sometimes creates a copy which needs to stay alive. This needs to
-    happen both for directs casts (just the array) or indirectly (e.g. list of arrays).
-    """
-
-    a = np.full(shape=10, fill_value=8, dtype=np.int8)
-    assert m.get_elem_direct(a) == 8
-
-    list_of_a = [a]
-    assert m.get_elem_indirect(list_of_a) == 8
-
-
-def test_special_matrix_objects():
-    assert np.all(m.incr_diag(7) == np.diag([1., 2, 3, 4, 5, 6, 7]))
-
-    asymm = np.array([[ 1.,  2,  3,  4],
-                      [ 5,  6,  7,  8],
-                      [ 9, 10, 11, 12],
-                      [13, 14, 15, 16]])
-    symm_lower = np.array(asymm)
-    symm_upper = np.array(asymm)
-    for i in range(4):
-        for j in range(i + 1, 4):
-            symm_lower[i, j] = symm_lower[j, i]
-            symm_upper[j, i] = symm_upper[i, j]
-
-    assert np.all(m.symmetric_lower(asymm) == symm_lower)
-    assert np.all(m.symmetric_upper(asymm) == symm_upper)
-
-
-def test_dense_signature(doc):
-    assert doc(m.double_col) == """
-        double_col(arg0: numpy.ndarray[numpy.float32[m, 1]]) -> numpy.ndarray[numpy.float32[m, 1]]
-    """
-    assert doc(m.double_row) == """
-        double_row(arg0: numpy.ndarray[numpy.float32[1, n]]) -> numpy.ndarray[numpy.float32[1, n]]
-    """
-    assert doc(m.double_complex) == ("""
-        double_complex(arg0: numpy.ndarray[numpy.complex64[m, 1]])"""
-                                     """ -> numpy.ndarray[numpy.complex64[m, 1]]
-    """)
-    assert doc(m.double_mat_rm) == ("""
-        double_mat_rm(arg0: numpy.ndarray[numpy.float32[m, n]])"""
-                                    """ -> numpy.ndarray[numpy.float32[m, n]]
-    """)
-
-
-def test_named_arguments():
-    a = np.array([[1.0, 2], [3, 4], [5, 6]])
-    b = np.ones((2, 1))
-
-    assert np.all(m.matrix_multiply(a, b) == np.array([[3.], [7], [11]]))
-    assert np.all(m.matrix_multiply(A=a, B=b) == np.array([[3.], [7], [11]]))
-    assert np.all(m.matrix_multiply(B=b, A=a) == np.array([[3.], [7], [11]]))
-
-    with pytest.raises(ValueError) as excinfo:
-        m.matrix_multiply(b, a)
-    assert str(excinfo.value) == 'Nonconformable matrices!'
-
-    with pytest.raises(ValueError) as excinfo:
-        m.matrix_multiply(A=b, B=a)
-    assert str(excinfo.value) == 'Nonconformable matrices!'
-
-    with pytest.raises(ValueError) as excinfo:
-        m.matrix_multiply(B=a, A=b)
-    assert str(excinfo.value) == 'Nonconformable matrices!'
-
-
-def test_sparse():
-    pytest.importorskip("scipy")
-    assert_sparse_equal_ref(m.sparse_r())
-    assert_sparse_equal_ref(m.sparse_c())
-    assert_sparse_equal_ref(m.sparse_copy_r(m.sparse_r()))
-    assert_sparse_equal_ref(m.sparse_copy_c(m.sparse_c()))
-    assert_sparse_equal_ref(m.sparse_copy_r(m.sparse_c()))
-    assert_sparse_equal_ref(m.sparse_copy_c(m.sparse_r()))
-
-
-def test_sparse_signature(doc):
-    pytest.importorskip("scipy")
-    assert doc(m.sparse_copy_r) == """
-        sparse_copy_r(arg0: scipy.sparse.csr_matrix[numpy.float32]) -> scipy.sparse.csr_matrix[numpy.float32]
-    """  # noqa: E501 line too long
-    assert doc(m.sparse_copy_c) == """
-        sparse_copy_c(arg0: scipy.sparse.csc_matrix[numpy.float32]) -> scipy.sparse.csc_matrix[numpy.float32]
-    """  # noqa: E501 line too long
-
-
-def test_issue738():
-    """Ignore strides on a length-1 dimension (even if they would be incompatible length > 1)"""
-    assert np.all(m.iss738_f1(np.array([[1., 2, 3]])) == np.array([[1., 102, 203]]))
-    assert np.all(m.iss738_f1(np.array([[1.], [2], [3]])) == np.array([[1.], [12], [23]]))
-
-    assert np.all(m.iss738_f2(np.array([[1., 2, 3]])) == np.array([[1., 102, 203]]))
-    assert np.all(m.iss738_f2(np.array([[1.], [2], [3]])) == np.array([[1.], [12], [23]]))
-
-
-def test_issue1105():
-    """Issue 1105: 1xN or Nx1 input arrays weren't accepted for eigen
-    compile-time row vectors or column vector"""
-    assert m.iss1105_row(np.ones((1, 7)))
-    assert m.iss1105_col(np.ones((7, 1)))
-
-    # These should still fail (incompatible dimensions):
-    with pytest.raises(TypeError) as excinfo:
-        m.iss1105_row(np.ones((7, 1)))
-    assert "incompatible function arguments" in str(excinfo.value)
-    with pytest.raises(TypeError) as excinfo:
-        m.iss1105_col(np.ones((1, 7)))
-    assert "incompatible function arguments" in str(excinfo.value)
-
-
-def test_custom_operator_new():
-    """Using Eigen types as member variables requires a class-specific
-    operator new with proper alignment"""
-
-    o = m.CustomOperatorNew()
-    np.testing.assert_allclose(o.a, 0.0)
-    np.testing.assert_allclose(o.b.diagonal(), 1.0)
diff --git a/spaces/CVPR/LIVE/shape.cpp b/spaces/CVPR/LIVE/shape.cpp
deleted file mode 100644
index 19a30962f7505d8cfdd65254a25c4230c6782a46..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/shape.cpp
+++ /dev/null
@@ -1,22 +0,0 @@
-#include "shape.h"
-
-void Path::copy_to(ptr<float> points, ptr<float> thickness) const {
-    float *p = points.get();
-    for (int i = 0; i < 2 * num_points; i++) {
-        p[i] = this->points[i];
-    }
-    if (this->thickness != nullptr) {
-        float *t = thickness.get();
-        for (int i = 0; i < num_points; i++) {
-            t[i] = this->thickness[i];
-        }
-    }
-}
-
-void ShapeGroup::copy_to(ptr<float> shape_to_canvas) const {
-    for (int i = 0; i < 3; i++) {
-        for (int j = 0; j < 3; j++) {
-            shape_to_canvas.get()[i * 3 + j] = this->shape_to_canvas(i, j);
-        }
-    }
-}
diff --git a/spaces/CVPR/WALT/mmdet/core/evaluation/eval_hooks.py b/spaces/CVPR/WALT/mmdet/core/evaluation/eval_hooks.py
deleted file mode 100644
index 6fb932eae1ccb23a2b687a05a6cb9525200de718..0000000000000000000000000000000000000000
--- a/spaces/CVPR/WALT/mmdet/core/evaluation/eval_hooks.py
+++ /dev/null
@@ -1,303 +0,0 @@
-import os.path as osp
-import warnings
-from math import inf
-
-import mmcv
-import torch.distributed as dist
-from mmcv.runner import Hook
-from torch.nn.modules.batchnorm import _BatchNorm
-from torch.utils.data import DataLoader
-
-from mmdet.utils import get_root_logger
-
-
-class EvalHook(Hook):
-    """Evaluation hook.
-
-    Notes:
-        If new arguments are added for EvalHook, tools/test.py,
-        tools/analysis_tools/eval_metric.py may be effected.
-
-    Attributes:
-        dataloader (DataLoader): A PyTorch dataloader.
-        start (int, optional): Evaluation starting epoch. It enables evaluation
-            before the training starts if ``start`` <= the resuming epoch.
-            If None, whether to evaluate is merely decided by ``interval``.
-            Default: None.
-        interval (int): Evaluation interval (by epochs). Default: 1.
-        save_best (str, optional): If a metric is specified, it would measure
-            the best checkpoint during evaluation. The information about best
-            checkpoint would be save in best.json.
-            Options are the evaluation metrics to the test dataset. e.g.,
-            ``bbox_mAP``, ``segm_mAP`` for bbox detection and instance
-            segmentation. ``AR@100`` for proposal recall. If ``save_best`` is
-            ``auto``, the first key will be used. The interval of
-            ``CheckpointHook`` should device EvalHook. Default: None.
-        rule (str, optional): Comparison rule for best score. If set to None,
-            it will infer a reasonable rule. Keys such as 'mAP' or 'AR' will
-            be inferred by 'greater' rule. Keys contain 'loss' will be inferred
-             by 'less' rule. Options are 'greater', 'less'. Default: None.
-        **eval_kwargs: Evaluation arguments fed into the evaluate function of
-            the dataset.
-    """
-
-    rule_map = {'greater': lambda x, y: x > y, 'less': lambda x, y: x < y}
-    init_value_map = {'greater': -inf, 'less': inf}
-    greater_keys = ['mAP', 'AR']
-    less_keys = ['loss']
-
-    def __init__(self,
-                 dataloader,
-                 start=None,
-                 interval=1,
-                 by_epoch=True,
-                 save_best=None,
-                 rule=None,
-                 **eval_kwargs):
-        if not isinstance(dataloader, DataLoader):
-            raise TypeError('dataloader must be a pytorch DataLoader, but got'
-                            f' {type(dataloader)}')
-        if not interval > 0:
-            raise ValueError(f'interval must be positive, but got {interval}')
-        if start is not None and start < 0:
-            warnings.warn(
-                f'The evaluation start epoch {start} is smaller than 0, '
-                f'use 0 instead', UserWarning)
-            start = 0
-        self.dataloader = dataloader
-        self.interval = interval
-        self.by_epoch = by_epoch
-        self.start = start
-        assert isinstance(save_best, str) or save_best is None
-        self.save_best = save_best
-        self.eval_kwargs = eval_kwargs
-        self.initial_epoch_flag = True
-
-        self.logger = get_root_logger()
-
-        if self.save_best is not None:
-            self._init_rule(rule, self.save_best)
-
-    def _init_rule(self, rule, key_indicator):
-        """Initialize rule, key_indicator, comparison_func, and best score.
-
-        Args:
-            rule (str | None): Comparison rule for best score.
-            key_indicator (str | None): Key indicator to determine the
-                comparison rule.
-        """
-        if rule not in self.rule_map and rule is not None:
-            raise KeyError(f'rule must be greater, less or None, '
-                           f'but got {rule}.')
-
-        if rule is None:
-            if key_indicator != 'auto':
-                if any(key in key_indicator for key in self.greater_keys):
-                    rule = 'greater'
-                elif any(key in key_indicator for key in self.less_keys):
-                    rule = 'less'
-                else:
-                    raise ValueError(f'Cannot infer the rule for key '
-                                     f'{key_indicator}, thus a specific rule '
-                                     f'must be specified.')
-        self.rule = rule
-        self.key_indicator = key_indicator
-        if self.rule is not None:
-            self.compare_func = self.rule_map[self.rule]
-
-    def before_run(self, runner):
-        if self.save_best is not None:
-            if runner.meta is None:
-                warnings.warn('runner.meta is None. Creating a empty one.')
-                runner.meta = dict()
-            runner.meta.setdefault('hook_msgs', dict())
-
-    def before_train_epoch(self, runner):
-        """Evaluate the model only at the start of training."""
-        if not self.initial_epoch_flag:
-            return
-        if self.start is not None and runner.epoch >= self.start:
-            self.after_train_epoch(runner)
-        self.initial_epoch_flag = False
-
-    def evaluation_flag(self, runner):
-        """Judge whether to perform_evaluation after this epoch.
-
-        Returns:
-            bool: The flag indicating whether to perform evaluation.
-        """
-        if self.start is None:
-            if not self.every_n_epochs(runner, self.interval):
-                # No evaluation during the interval epochs.
-                return False
-        elif (runner.epoch + 1) < self.start:
-            # No evaluation if start is larger than the current epoch.
-            return False
-        else:
-            # Evaluation only at epochs 3, 5, 7... if start==3 and interval==2
-            if (runner.epoch + 1 - self.start) % self.interval:
-                return False
-        return True
-
-    def after_train_epoch(self, runner):
-        if not self.by_epoch or not self.evaluation_flag(runner):
-            return
-        from mmdet.apis import single_gpu_test
-        results = single_gpu_test(runner.model, self.dataloader, show=False)
-        key_score = self.evaluate(runner, results)
-        if self.save_best:
-            self.save_best_checkpoint(runner, key_score)
-
-    def after_train_iter(self, runner):
-        if self.by_epoch or not self.every_n_iters(runner, self.interval):
-            return
-        from mmdet.apis import single_gpu_test
-        results = single_gpu_test(runner.model, self.dataloader, show=False)
-        key_score = self.evaluate(runner, results)
-        if self.save_best:
-            self.save_best_checkpoint(runner, key_score)
-
-    def save_best_checkpoint(self, runner, key_score):
-        best_score = runner.meta['hook_msgs'].get(
-            'best_score', self.init_value_map[self.rule])
-        if self.compare_func(key_score, best_score):
-            best_score = key_score
-            runner.meta['hook_msgs']['best_score'] = best_score
-            last_ckpt = runner.meta['hook_msgs']['last_ckpt']
-            runner.meta['hook_msgs']['best_ckpt'] = last_ckpt
-            mmcv.symlink(
-                last_ckpt,
-                osp.join(runner.work_dir, f'best_{self.key_indicator}.pth'))
-            time_stamp = runner.epoch + 1 if self.by_epoch else runner.iter + 1
-            self.logger.info(f'Now best checkpoint is epoch_{time_stamp}.pth.'
-                             f'Best {self.key_indicator} is {best_score:0.4f}')
-
-    def evaluate(self, runner, results):
-        eval_res = self.dataloader.dataset.evaluate(
-            results, logger=runner.logger, **self.eval_kwargs)
-        for name, val in eval_res.items():
-            runner.log_buffer.output[name] = val
-        runner.log_buffer.ready = True
-        if self.save_best is not None:
-            if self.key_indicator == 'auto':
-                # infer from eval_results
-                self._init_rule(self.rule, list(eval_res.keys())[0])
-            return eval_res[self.key_indicator]
-        else:
-            return None
-
-
-class DistEvalHook(EvalHook):
-    """Distributed evaluation hook.
-
-    Notes:
-        If new arguments are added, tools/test.py may be effected.
-
-    Attributes:
-        dataloader (DataLoader): A PyTorch dataloader.
-        start (int, optional): Evaluation starting epoch. It enables evaluation
-            before the training starts if ``start`` <= the resuming epoch.
-            If None, whether to evaluate is merely decided by ``interval``.
-            Default: None.
-        interval (int): Evaluation interval (by epochs). Default: 1.
-        tmpdir (str | None): Temporary directory to save the results of all
-            processes. Default: None.
-        gpu_collect (bool): Whether to use gpu or cpu to collect results.
-            Default: False.
-        save_best (str, optional): If a metric is specified, it would measure
-            the best checkpoint during evaluation. The information about best
-            checkpoint would be save in best.json.
-            Options are the evaluation metrics to the test dataset. e.g.,
-            ``bbox_mAP``, ``segm_mAP`` for bbox detection and instance
-            segmentation. ``AR@100`` for proposal recall. If ``save_best`` is
-            ``auto``, the first key will be used. The interval of
-            ``CheckpointHook`` should device EvalHook. Default: None.
-        rule (str | None): Comparison rule for best score. If set to None,
-            it will infer a reasonable rule. Default: 'None'.
-        broadcast_bn_buffer (bool): Whether to broadcast the
-            buffer(running_mean and running_var) of rank 0 to other rank
-            before evaluation. Default: True.
-        **eval_kwargs: Evaluation arguments fed into the evaluate function of
-            the dataset.
-    """
-
-    def __init__(self,
-                 dataloader,
-                 start=None,
-                 interval=1,
-                 by_epoch=True,
-                 tmpdir=None,
-                 gpu_collect=False,
-                 save_best=None,
-                 rule=None,
-                 broadcast_bn_buffer=True,
-                 **eval_kwargs):
-        super().__init__(
-            dataloader,
-            start=start,
-            interval=interval,
-            by_epoch=by_epoch,
-            save_best=save_best,
-            rule=rule,
-            **eval_kwargs)
-        self.broadcast_bn_buffer = broadcast_bn_buffer
-        self.tmpdir = tmpdir
-        self.gpu_collect = gpu_collect
-
-    def _broadcast_bn_buffer(self, runner):
-        # Synchronization of BatchNorm's buffer (running_mean
-        # and running_var) is not supported in the DDP of pytorch,
-        # which may cause the inconsistent performance of models in
-        # different ranks, so we broadcast BatchNorm's buffers
-        # of rank 0 to other ranks to avoid this.
-        if self.broadcast_bn_buffer:
-            model = runner.model
-            for name, module in model.named_modules():
-                if isinstance(module,
-                              _BatchNorm) and module.track_running_stats:
-                    dist.broadcast(module.running_var, 0)
-                    dist.broadcast(module.running_mean, 0)
-
-    def after_train_epoch(self, runner):
-        if not self.by_epoch or not self.evaluation_flag(runner):
-            return
-
-        if self.broadcast_bn_buffer:
-            self._broadcast_bn_buffer(runner)
-
-        from mmdet.apis import multi_gpu_test
-        tmpdir = self.tmpdir
-        if tmpdir is None:
-            tmpdir = osp.join(runner.work_dir, '.eval_hook')
-        results = multi_gpu_test(
-            runner.model,
-            self.dataloader,
-            tmpdir=tmpdir,
-            gpu_collect=self.gpu_collect)
-        if runner.rank == 0:
-            print('\n')
-            key_score = self.evaluate(runner, results)
-            if self.save_best:
-                self.save_best_checkpoint(runner, key_score)
-
-    def after_train_iter(self, runner):
-        if self.by_epoch or not self.every_n_iters(runner, self.interval):
-            return
-
-        if self.broadcast_bn_buffer:
-            self._broadcast_bn_buffer(runner)
-
-        from mmdet.apis import multi_gpu_test
-        tmpdir = self.tmpdir
-        if tmpdir is None:
-            tmpdir = osp.join(runner.work_dir, '.eval_hook')
-        results = multi_gpu_test(
-            runner.model,
-            self.dataloader,
-            tmpdir=tmpdir,
-            gpu_collect=self.gpu_collect)
-        if runner.rank == 0:
-            print('\n')
-            key_score = self.evaluate(runner, results)
-            if self.save_best:
-                self.save_best_checkpoint(runner, key_score)
diff --git a/spaces/CVPR/transfiner/configs/common/train.py b/spaces/CVPR/transfiner/configs/common/train.py
deleted file mode 100644
index 7c63bdb073797e48e0b3640e668ecc1d5c137d59..0000000000000000000000000000000000000000
--- a/spaces/CVPR/transfiner/configs/common/train.py
+++ /dev/null
@@ -1,18 +0,0 @@
-# Common training-related configs that are designed for "tools/lazyconfig_train_net.py"
-# You can use your own instead, together with your own train_net.py
-train = dict(
-    output_dir="./output",
-    init_checkpoint="detectron2://ImageNetPretrained/MSRA/R-50.pkl",
-    max_iter=90000,
-    amp=dict(enabled=False),  # options for Automatic Mixed Precision
-    ddp=dict(  # options for DistributedDataParallel
-        broadcast_buffers=False,
-        find_unused_parameters=False,
-        fp16_compression=False,
-    ),
-    checkpointer=dict(period=5000, max_to_keep=100),  # options for PeriodicCheckpointer
-    eval_period=5000,
-    log_period=20,
-    device="cuda"
-    # ...
-)
diff --git a/spaces/ChrisPreston/diff-svc_minato_aqua/modules/nsf_hifigan/nvSTFT.py b/spaces/ChrisPreston/diff-svc_minato_aqua/modules/nsf_hifigan/nvSTFT.py
deleted file mode 100644
index 45d235f2c537de8c71efd3a81ecafb0c92212f36..0000000000000000000000000000000000000000
--- a/spaces/ChrisPreston/diff-svc_minato_aqua/modules/nsf_hifigan/nvSTFT.py
+++ /dev/null
@@ -1,120 +0,0 @@
-import os
-
-os.environ["LRU_CACHE_CAPACITY"] = "3"
-import torch
-import torch.utils.data
-import numpy as np
-import librosa
-from librosa.filters import mel as librosa_mel_fn
-import soundfile as sf
-
-
-def load_wav_to_torch(full_path, target_sr=None, return_empty_on_exception=False):
-    sampling_rate = None
-    try:
-        data, sampling_rate = sf.read(full_path, always_2d=True)  # than soundfile.
-    except Exception as ex:
-        print(f"'{full_path}' failed to load.\nException:")
-        print(ex)
-        if return_empty_on_exception:
-            return [], sampling_rate or target_sr or 48000
-        else:
-            raise Exception(ex)
-
-    if len(data.shape) > 1:
-        data = data[:, 0]
-        assert len(
-            data) > 2  # check duration of audio file is > 2 samples (because otherwise the slice operation was on the wrong dimension)
-
-    if np.issubdtype(data.dtype, np.integer):  # if audio data is type int
-        max_mag = -np.iinfo(data.dtype).min  # maximum magnitude = min possible value of intXX
-    else:  # if audio data is type fp32
-        max_mag = max(np.amax(data), -np.amin(data))
-        max_mag = (2 ** 31) + 1 if max_mag > (2 ** 15) else ((
-                                                                         2 ** 15) + 1 if max_mag > 1.01 else 1.0)  # data should be either 16-bit INT, 32-bit INT or [-1 to 1] float32
-
-    data = torch.FloatTensor(data.astype(np.float32)) / max_mag
-
-    if (torch.isinf(data) | torch.isnan(
-            data)).any() and return_empty_on_exception:  # resample will crash with inf/NaN inputs. return_empty_on_exception will return empty arr instead of except
-        return [], sampling_rate or target_sr or 48000
-    if target_sr is not None and sampling_rate != target_sr:
-        data = torch.from_numpy(librosa.core.resample(data.numpy(), orig_sr=sampling_rate, target_sr=target_sr))
-        sampling_rate = target_sr
-
-    return data, sampling_rate
-
-
-def dynamic_range_compression(x, C=1, clip_val=1e-5):
-    return np.log(np.clip(x, a_min=clip_val, a_max=None) * C)
-
-
-def dynamic_range_decompression(x, C=1):
-    return np.exp(x) / C
-
-
-def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
-    return torch.log(torch.clamp(x, min=clip_val) * C)
-
-
-def dynamic_range_decompression_torch(x, C=1):
-    return torch.exp(x) / C
-
-
-class STFT():
-    def __init__(self, sr=22050, n_mels=80, n_fft=1024, win_size=1024, hop_length=256, fmin=20, fmax=11025,
-                 clip_val=1e-5):
-        self.target_sr = sr
-
-        self.n_mels = n_mels
-        self.n_fft = n_fft
-        self.win_size = win_size
-        self.hop_length = hop_length
-        self.fmin = fmin
-        self.fmax = fmax
-        self.clip_val = clip_val
-        self.mel_basis = {}
-        self.hann_window = {}
-
-    def get_mel(self, y, center=False):
-        sampling_rate = self.target_sr
-        n_mels = self.n_mels
-        n_fft = self.n_fft
-        win_size = self.win_size
-        hop_length = self.hop_length
-        fmin = self.fmin
-        fmax = self.fmax
-        clip_val = self.clip_val
-
-        if torch.min(y) < -1.:
-            print('min value is ', torch.min(y))
-        if torch.max(y) > 1.:
-            print('max value is ', torch.max(y))
-
-        if fmax not in self.mel_basis:
-            mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax)
-            self.mel_basis[str(fmax) + '_' + str(y.device)] = torch.from_numpy(mel).float().to(y.device)
-            self.hann_window[str(y.device)] = torch.hann_window(self.win_size).to(y.device)
-
-        y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft - hop_length) / 2), int((n_fft - hop_length) / 2)),
-                                    mode='reflect')
-        y = y.squeeze(1)
-
-        spec = torch.stft(y, n_fft, hop_length=hop_length, win_length=win_size, window=self.hann_window[str(y.device)],
-                          center=center, pad_mode='reflect', normalized=False, onesided=True)
-        # print(111,spec)
-        spec = torch.sqrt(spec.pow(2).sum(-1) + (1e-9))
-        # print(222,spec)
-        spec = torch.matmul(self.mel_basis[str(fmax) + '_' + str(y.device)], spec)
-        # print(333,spec)
-        spec = dynamic_range_compression_torch(spec, clip_val=clip_val)
-        # print(444,spec)
-        return spec
-
-    def __call__(self, audiopath):
-        audio, sr = load_wav_to_torch(audiopath, target_sr=self.target_sr)
-        spect = self.get_mel(audio.unsqueeze(0)).squeeze(0)
-        return spect
-
-
-stft = STFT()
diff --git a/spaces/CikeyQI/Yunzai/Yunzai/lib/config/log.js b/spaces/CikeyQI/Yunzai/Yunzai/lib/config/log.js
deleted file mode 100644
index e957e5261db637918df4afc640dcd90a885b556a..0000000000000000000000000000000000000000
--- a/spaces/CikeyQI/Yunzai/Yunzai/lib/config/log.js
+++ /dev/null
@@ -1,98 +0,0 @@
-import log4js from 'log4js'
-import chalk from 'chalk'
-import cfg from './config.js'
-import fs from 'node:fs'
-
-/**
-* 设置日志样式
-*/
-export default function setLog () {
-  let file = './logs'
-  if (!fs.existsSync(file)) {
-    fs.mkdirSync(file)
-  }
-
-  /** 调整error日志等级 */
-  // log4js.levels.levels[5].level = Number.MAX_VALUE
-  // log4js.levels.levels.sort((a, b) => a.level - b.level)
-
-  log4js.configure({
-    appenders: {
-      console: {
-        type: 'console',
-        layout: {
-          type: 'pattern',
-          pattern: '%[[TRSSYz][%d{hh:mm:ss.SSS}][%4.4p]%] %m'
-        }
-      },
-      command: {
-        type: 'dateFile', // 可以是console,dateFile,file,Logstash等
-        filename: 'logs/command', // 将会按照filename和pattern拼接文件名
-        pattern: 'yyyy-MM-dd.log',
-        numBackups: 15,
-        alwaysIncludePattern: true,
-        layout: {
-          type: 'pattern',
-          pattern: '[%d{hh:mm:ss.SSS}][%4.4p] %m'
-        }
-      },
-      error: {
-        type: 'file',
-        filename: 'logs/error.log',
-        alwaysIncludePattern: true,
-        layout: {
-          type: 'pattern',
-          pattern: '[%d{hh:mm:ss.SSS}][%4.4p] %m'
-        }
-      }
-    },
-    categories: {
-      default: { appenders: ['console'], level: cfg.bot.log_level },
-      command: { appenders: ['console', 'command'], level: 'warn' },
-      error: { appenders: ['console', 'command', 'error'], level: 'error' }
-    }
-  })
-
-  const defaultLogger = log4js.getLogger('message')
-  const commandLogger = log4js.getLogger('command')
-  const errorLogger = log4js.getLogger('error')
-
-  /* eslint-disable no-useless-call */
-  /** 全局变量 logger */
-  global.logger = {
-    trace () {
-      defaultLogger.trace.call(defaultLogger, ...arguments)
-    },
-    debug () {
-      defaultLogger.debug.call(defaultLogger, ...arguments)
-    },
-    info () {
-      defaultLogger.info.call(defaultLogger, ...arguments)
-    },
-    // warn及以上的日志采用error策略
-    warn () {
-      commandLogger.warn.call(defaultLogger, ...arguments)
-    },
-    error () {
-      errorLogger.error.call(errorLogger, ...arguments)
-    },
-    fatal () {
-      errorLogger.fatal.call(errorLogger, ...arguments)
-    },
-    mark () {
-      errorLogger.mark.call(commandLogger, ...arguments)
-    }
-  }
-
-  logColor()
-}
-
-function logColor () {
-  logger.chalk = chalk
-  logger.red = chalk.red
-  logger.green = chalk.green
-  logger.yellow = chalk.yellow
-  logger.blue = chalk.blue
-  logger.magenta = chalk.magenta
-  logger.cyan = chalk.cyan
-}
diff --git a/spaces/CikeyQI/Yunzai/Yunzai/plugins/ws-plugin/resources/common/common.css b/spaces/CikeyQI/Yunzai/Yunzai/plugins/ws-plugin/resources/common/common.css
deleted file mode 100644
index f21e5890be2b6622b9db263487f43ad3cd3f3279..0000000000000000000000000000000000000000
--- a/spaces/CikeyQI/Yunzai/Yunzai/plugins/ws-plugin/resources/common/common.css
+++ /dev/null
@@ -1,458 +0,0 @@
-@font-face {
-  font-family: 'Number';
-  src: url("./font/tttgbnumber.woff") format('woff'), url("./font/tttgbnumber.ttf") format('truetype');
-}
-@font-face {
-  font-family: 'NZBZ';
-  src: url("./font/NZBZ.woff") format('woff'), url("./font/NZBZ.ttf") format('truetype');
-}
-@font-face {
-  font-family: 'YS';
-  src: url("./font/HYWH-65W.woff") format('woff'), url("./font/HYWH-65W.ttf") format('truetype');
-}
-.font-YS {
-  font-family: Number, "汉仪文黑-65W", YS, PingFangSC-Medium, "PingFang SC", sans-serif;
-}
-.font-NZBZ {
-  font-family: Number, "印品南征北战NZBZ体", NZBZ, "汉仪文黑-65W", YS, PingFangSC-Medium, "PingFang SC", sans-serif;
-}
-* {
-  margin: 0;
-  padding: 0;
-  box-sizing: border-box;
-  -webkit-user-select: none;
-  user-select: none;
-}
-body {
-  font-size: 18px;
-  color: #1e1f20;
-  font-family: Number, "汉仪文黑-65W", YS, PingFangSC-Medium, "PingFang SC", sans-serif;
-  transform: scale(1.4);
-  transform-origin: 0 0;
-  width: 600px;
-}
-.container {
-  width: 600px;
-  padding: 20px 15px 10px 15px;
-  background-size: contain;
-}
-.head-box {
-  border-radius: 15px;
-  padding: 10px 20px;
-  position: relative;
-  color: #fff;
-  margin-top: 30px;
-}
-.head-box .title {
-  font-family: Number, "印品南征北战NZBZ体", NZBZ, "汉仪文黑-65W", YS, PingFangSC-Medium, "PingFang SC", sans-serif;
-  font-size: 36px;
-  text-shadow: 0 0 1px #000, 1px 1px 3px rgba(0, 0, 0, 0.9);
-}
-.head-box .title .label {
-  display: inline-block;
-  margin-left: 10px;
-}
-.head-box .genshin_logo {
-  position: absolute;
-  top: 1px;
-  right: 15px;
-  width: 97px;
-}
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-  font-size: 16px;
-  text-shadow: 0 0 1px #000, 1px 1px 3px rgba(0, 0, 0, 0.9);
-}
-.head-box .label span {
-  color: #d3bc8e;
-  padding: 0 2px;
-}
-.notice {
-  color: #888;
-  font-size: 12px;
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-  padding: 12px 5px 5px;
-}
-.notice-center {
-  color: #fff;
-  text-align: center;
-  margin-bottom: 10px;
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-}
-.copyright {
-  font-size: 14px;
-  text-align: center;
-  color: #fff;
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-  margin: 10px 0;
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-.copyright .version {
-  color: #d3bc8e;
-  display: inline-block;
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-/*  */
-.cons {
-  display: inline-block;
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-.cons2-6 {
-  border-radius: 4px;
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-  color: #fff;
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-/********  Fetter  ********/
-.fetter {
-  width: 50px;
-  height: 50px;
-  display: inline-block;
-  background: url('./item/fetter.png');
-  background-size: auto 100%;
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-.fetter.fetter1 {
-  background-position: 0% 0;
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-/********  ELEM  ********/
-.elem-hydro .talent-icon {
-  background-image: url("./bg/talent-hydro.png");
-}
-.elem-hydro .elem-bg,
-.hydro-bg {
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-.elem-anemo .talent-icon {
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-.elem-anemo .elem-bg,
-.anemo-bg {
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-.elem-cryo .talent-icon {
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-}
-.elem-cryo .elem-bg,
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-}
-.elem-electro .talent-icon {
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-.elem-electro .elem-bg,
-.electro-bg {
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-.elem-geo .talent-icon {
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-.elem-geo .elem-bg,
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-.elem-pyro .elem-bg,
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-.elem-dendro .elem-bg,
-.dendro-bg {
-  background-image: url("./bg/bg-dendro.jpg");
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-/* cont */
-.cont {
-  border-radius: 10px;
-  background: url("../common/cont/card-bg.png") top left repeat-x;
-  background-size: auto 100%;
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-  position: relative;
-  box-shadow: 0 0 1px 0 #ccc, 2px 2px 4px 0 rgba(50, 50, 50, 0.8);
-  overflow: hidden;
-  color: #fff;
-  font-size: 16px;
-}
-.cont-title {
-  background: rgba(0, 0, 0, 0.4);
-  box-shadow: 0 0 1px 0 #fff;
-  color: #d3bc8e;
-  padding: 10px 20px;
-  text-align: left;
-  border-radius: 10px 10px 0 0;
-}
-.cont-title span {
-  font-size: 12px;
-  color: #aaa;
-  margin-left: 10px;
-  font-weight: normal;
-}
-.cont-title.border-less {
-  background: linear-gradient(rgba(0, 0, 0, 0.5), rgba(0, 0, 0, 0));
-  box-shadow: none;
-  padding-bottom: 5px;
-}
-.cont-body {
-  padding: 10px 15px;
-  font-size: 12px;
-  background: rgba(0, 0, 0, 0.5);
-  box-shadow: 0 0 1px 0 #fff;
-  font-weight: normal;
-}
-.cont-footer {
-  padding: 10px 15px;
-  font-size: 12px;
-  background: rgba(0, 0, 0, 0.5);
-  font-weight: normal;
-}
-.cont > ul.cont-msg {
-  display: block;
-  padding: 5px 10px;
-  background: rgba(0, 0, 0, 0.5);
-}
-ul.cont-msg,
-.cont-footer ul {
-  padding-left: 15px;
-}
-ul.cont-msg li,
-.cont-footer ul li {
-  margin: 5px 0;
-  margin-left: 15px;
-}
-ul.cont-msg li strong,
-.cont-footer ul li strong {
-  font-weight: normal;
-  margin: 0 2px;
-  color: #d3bc8e;
-}
-.cont-table {
-  display: table;
-  width: 100%;
-}
-.cont-table .tr {
-  display: table-row;
-}
-.cont-table .tr:nth-child(even) {
-  background: rgba(0, 0, 0, 0.4);
-}
-.cont-table .tr:nth-child(odd) {
-  background: rgba(50, 50, 50, 0.4);
-}
-.cont-table .tr > div,
-.cont-table .tr > td {
-  display: table-cell;
-  box-shadow: 0 0 1px 0 #fff;
-}
-.cont-table .tr > div.value-full {
-  display: table;
-  width: 200%;
-}
-.cont-table .tr > div.value-none {
-  box-shadow: none;
-}
-.cont-table .thead {
-  text-align: center;
-}
-.cont-table .thead > div,
-.cont-table .thead > td {
-  color: #d3bc8e;
-  background: rgba(0, 0, 0, 0.4);
-  line-height: 40px;
-  height: 40px;
-}
-.cont-table .title,
-.cont-table .th {
-  color: #d3bc8e;
-  padding-right: 15px;
-  text-align: right;
-  background: rgba(0, 0, 0, 0.4);
-  min-width: 100px;
-  vertical-align: middle;
-}
-.logo {
-  font-size: 18px;
-  text-align: center;
-  color: #fff;
-  margin: 20px 0 10px 0;
-}
-/* item-icon */
-.item-icon {
-  width: 100%;
-  height: 100%;
-  border-radius: 4px;
-  position: relative;
-  overflow: hidden;
-}
-.item-icon .img {
-  width: 100%;
-  height: 100%;
-  display: block;
-  background-size: contain;
-  background-position: center;
-  background-repeat: no-repeat;
-}
-.item-icon.artis .img {
-  width: 84%;
-  height: 84%;
-  margin: 8%;
-}
-.item-icon.star1 {
-  background-image: url("../common/item/bg1.png");
-}
-.item-icon.opacity-bg.star1 {
-  background-image: url("../common/item/bg1-o.png");
-}
-.item-icon.star2 {
-  background-image: url("../common/item/bg2.png");
-}
-.item-icon.opacity-bg.star2 {
-  background-image: url("../common/item/bg2-o.png");
-}
-.item-icon.star3 {
-  background-image: url("../common/item/bg3.png");
-}
-.item-icon.opacity-bg.star3 {
-  background-image: url("../common/item/bg3-o.png");
-}
-.item-icon.star4 {
-  background-image: url("../common/item/bg4.png");
-}
-.item-icon.opacity-bg.star4 {
-  background-image: url("../common/item/bg4-o.png");
-}
-.item-icon.star5 {
-  background-image: url("../common/item/bg5.png");
-}
-.item-icon.opacity-bg.star5 {
-  background-image: url("../common/item/bg5-o.png");
-}
-.item-icon.star-w {
-  background: #fff;
-}
-.item-list {
-  display: flex;
-}
-.item-list .item-card {
-  width: 70px;
-  background: #e7e5d9;
-}
-.item-list .item-icon {
-  border-bottom-left-radius: 0;
-  border-bottom-right-radius: 12px;
-}
-.item-list .item-title {
-  color: #222;
-  font-size: 13px;
-  text-align: center;
-  padding: 2px;
-  white-space: nowrap;
-  overflow: hidden;
-}
-.item-list .item-icon {
-  height: initial;
-}
-.item-list .item-badge {
-  position: absolute;
-  display: block;
-  left: 0;
-  top: 0;
-  background: rgba(0, 0, 0, 0.6);
-  font-size: 12px;
-  color: #fff;
-  padding: 4px 5px 3px;
-  border-radius: 0 0 6px 0;
-}
-/*# sourceMappingURL=common.css.map */
\ No newline at end of file
diff --git a/spaces/CikeyQI/meme-api/meme_generator/memes/jiji_king/__init__.py b/spaces/CikeyQI/meme-api/meme_generator/memes/jiji_king/__init__.py
deleted file mode 100644
index dd67f38d3a46b2d77a84514173aa963a142bf15a..0000000000000000000000000000000000000000
--- a/spaces/CikeyQI/meme-api/meme_generator/memes/jiji_king/__init__.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import math
-from pathlib import Path
-from typing import List
-
-from pil_utils import BuildImage
-from pydantic import Field
-
-from meme_generator import MemeArgsModel, MemeArgsParser, MemeArgsType, add_meme
-from meme_generator.exception import TextOverLength
-
-img_dir = Path(__file__).parent / "images"
-
-help = "是否将图片变为圆形"
-
-parser = MemeArgsParser(prefix_chars="-/")
-parser.add_argument("--circle", "/圆", action="store_true", help=help)
-
-
-class Model(MemeArgsModel):
-    circle: bool = Field(False, description=help)
-
-
-def jiji_king(images: List[BuildImage], texts: List[str], args: Model):
-    block_num = 5
-    if len(images) >= 7 or len(texts) >= 7:
-        block_num = max(len(images), len(texts)) - 1
-
-    chars = ["急"]
-    text = "我是急急国王"
-
-    if len(texts) == 1:
-        if len(images) == 1:
-            chars = [texts[0]] * block_num
-            text = f"我是{texts[0]*2}国王"
-        else:
-            text = texts[0]
-    elif len(texts) == 2:
-        chars = [texts[0]] * block_num
-        text = texts[1]
-    elif texts:
-        chars = sum(
-            [[arg] * math.ceil(block_num / len(texts[:-1])) for arg in texts[:-1]], []
-        )
-        text = texts[-1]
-
-    frame = BuildImage.new("RGBA", (10 + 100 * block_num, 400), "white")
-    king = BuildImage.open(img_dir / "0.png")
-    head = images[0].convert("RGBA").square().resize((125, 125))
-    if args.circle:
-        head = head.circle()
-    king.paste(head, (237, 5), alpha=True)
-    frame.paste(king, ((frame.width - king.width) // 2, 0))
-
-    if len(images) > 1:
-        imgs = images[1:]
-        imgs = [img.convert("RGBA").square().resize((90, 90)) for img in imgs]
-    else:
-        imgs = []
-        for char in chars:
-            block = BuildImage.new("RGBA", (90, 90), "black")
-            try:
-                block.draw_text(
-                    (0, 0, 90, 90),
-                    char,
-                    lines_align="center",
-                    weight="bold",
-                    max_fontsize=60,
-                    min_fontsize=30,
-                    fill="white",
-                )
-            except ValueError:
-                raise TextOverLength(char)
-            imgs.append(block)
-
-    imgs = sum([[img] * math.ceil(block_num / len(imgs)) for img in imgs], [])
-    for i in range(block_num):
-        frame.paste(imgs[i], (10 + 100 * i, 200))
-
-    try:
-        frame.draw_text(
-            (10, 300, frame.width - 10, 390),
-            text,
-            lines_align="center",
-            weight="bold",
-            max_fontsize=100,
-            min_fontsize=30,
-        )
-    except ValueError:
-        raise TextOverLength(text)
-
-    return frame.save_jpg()
-
-
-add_meme(
-    "jiji_king",
-    jiji_king,
-    min_images=1,
-    max_images=11,
-    min_texts=0,
-    max_texts=11,
-    args_type=MemeArgsType(parser, Model, [Model(circle=False), Model(circle=True)]),
-    keywords=["急急国王"],
-)
diff --git a/spaces/CofAI/chat/client/js/theme-toggler.js b/spaces/CofAI/chat/client/js/theme-toggler.js
deleted file mode 100644
index 67e1a9501b70d54ab8a717f34983c012328e74a0..0000000000000000000000000000000000000000
--- a/spaces/CofAI/chat/client/js/theme-toggler.js
+++ /dev/null
@@ -1,22 +0,0 @@
-var switch_theme_toggler = document.getElementById("theme-toggler");
-
-switch_theme_toggler.addEventListener("change", toggleTheme);
-
-function setTheme(themeName) {
-	localStorage.setItem("theme", themeName);
-	document.documentElement.className = themeName;
-}
-
-function toggleTheme() {
-	var currentTheme = localStorage.getItem("theme");
-	var newTheme = currentTheme === "theme-dark" ? "theme-light" : "theme-dark";
-
-	setTheme(newTheme);
-	switch_theme_toggler.checked = newTheme === "theme-dark";
-}
-
-(function () {
-	var currentTheme = localStorage.getItem("theme") || "theme-dark";
-	setTheme(currentTheme);
-	switch_theme_toggler.checked = currentTheme === "theme-dark";
-})();
diff --git a/spaces/CofAI/openjourney/midjourney.py b/spaces/CofAI/openjourney/midjourney.py
deleted file mode 100644
index ca8415ad9440ad4d838076d4baa43021e2e246b7..0000000000000000000000000000000000000000
--- a/spaces/CofAI/openjourney/midjourney.py
+++ /dev/null
@@ -1,5 +0,0 @@
-#import libraries
-import gradio as gr
-
-#interface
-gr.Interface.load("models/prompthero/openjourney").launch()
\ No newline at end of file
diff --git a/spaces/CognitiveLabs/GPT-auto-webscraping/README.md b/spaces/CognitiveLabs/GPT-auto-webscraping/README.md
deleted file mode 100644
index 280829d4dc353b15ea158e977482ebd816766140..0000000000000000000000000000000000000000
--- a/spaces/CognitiveLabs/GPT-auto-webscraping/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: GPT Auto Web scraping
-emoji: 🍧
-colorFrom: gray
-colorTo: purple
-sdk: streamlit
-sdk_version: 1.21.0
-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/CompVis/text2img-latent-diffusion/app.py b/spaces/CompVis/text2img-latent-diffusion/app.py
deleted file mode 100644
index 11286d62af358f93ea3afe6b77331d970103fe94..0000000000000000000000000000000000000000
--- a/spaces/CompVis/text2img-latent-diffusion/app.py
+++ /dev/null
@@ -1,34 +0,0 @@
-import os
-os.environ['CUDA_LAUNCH_BLOCKING'] = "1"
-from diffusers import LDMTextToImagePipeline
-import gradio as gr
-import PIL.Image
-import numpy as np
-import random
-import torch
-import subprocess
-
-ldm_pipeline = LDMTextToImagePipeline.from_pretrained("CompVis/ldm-text2im-large-256")
-
-def predict(prompt, steps=100, seed=42, guidance_scale=6.0):
-    #torch.cuda.empty_cache()
-    print(subprocess.check_output(["nvidia-smi"], stderr=subprocess.STDOUT).decode("utf8"))
-    generator = torch.manual_seed(seed)
-    images = ldm_pipeline([prompt], generator=generator, num_inference_steps=steps, eta=0.3, guidance_scale=guidance_scale)["images"]
-    print(subprocess.check_output(["nvidia-smi"], stderr=subprocess.STDOUT).decode("utf8"))
-    return images[0]
-
-random_seed = random.randint(0, 2147483647)
-gr.Interface(
-    predict,
-    inputs=[
-        gr.inputs.Textbox(label='Prompt', default='a chalk pastel drawing of a llama wearing a wizard hat'),
-        gr.inputs.Slider(1, 100, label='Inference Steps', default=50, step=1),
-        gr.inputs.Slider(0, 2147483647, label='Seed', default=random_seed, step=1),
-        gr.inputs.Slider(1.0, 20.0, label='Guidance Scale - how much the prompt will influence the results', default=6.0, step=0.1),
-    ],
-    outputs=gr.Image(shape=[256,256], type="pil", elem_id="output_image"),
-    css="#output_image{width: 256px}",
-    title="ldm-text2im-large-256 - 🧨 diffusers library",
-    description="This Spaces contains a text-to-image Latent Diffusion process for the <a href=\"https://huggingface.co/CompVis/ldm-text2im-large-256\">ldm-text2im-large-256</a> model by <a href=\"https://huggingface.co/CompVis\">CompVis</a> using the <a href=\"https://github.com/huggingface/diffusers\">diffusers library</a>. The goal of this demo is to showcase the diffusers library and you can check how the code works here. If you want the state-of-the-art experience with Latent Diffusion text-to-image check out the <a href=\"https://huggingface.co/spaces/multimodalart/latentdiffusion\">main Spaces</a>.",
-).launch()
\ No newline at end of file
diff --git a/spaces/Cran-May/Mistril-7b/README.md b/spaces/Cran-May/Mistril-7b/README.md
deleted file mode 100644
index 0001d7194c2d5536beeb939b268ed74b2ad5f204..0000000000000000000000000000000000000000
--- a/spaces/Cran-May/Mistril-7b/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Mistril 7b
-emoji: 📈
-colorFrom: red
-colorTo: green
-sdk: streamlit
-sdk_version: 1.27.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Crossbro/succinctly-text2image-prompt-generator/README.md b/spaces/Crossbro/succinctly-text2image-prompt-generator/README.md
deleted file mode 100644
index af2c21e9a23e2982aefe3c82363f6c7435e3f947..0000000000000000000000000000000000000000
--- a/spaces/Crossbro/succinctly-text2image-prompt-generator/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Succinctly Text2image Prompt Generator
-emoji: 💻
-colorFrom: red
-colorTo: indigo
-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/Cyril666/ContourNet-ABI/maskrcnn_benchmark/data/datasets/evaluation/word/util/ml.py b/spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/data/datasets/evaluation/word/util/ml.py
deleted file mode 100644
index 12bee2ba8caefb32d4337071c6b45889693b8f62..0000000000000000000000000000000000000000
--- a/spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/data/datasets/evaluation/word/util/ml.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import logging
-import cv2
-import numpy as np
-import util.dec
-import util.np
-
-@util.dec.print_calling
-def kmeans(samples, k, criteria = None, attempts = 3, flags = cv2.KMEANS_RANDOM_CENTERS):
-    if criteria == None:
-        criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
-    samples = np.asarray(samples, dtype = np.float32)
-    _,labels,centers = cv2.kmeans(samples, k, criteria, attempts, flags)
-    labels = util.np.flatten(labels)
-    clusters = [None]*k
-    for idx, label in enumerate(labels):
-        if clusters[label] is None:
-            clusters[label] = []
-        clusters[label].append(idx)
-        
-    for  idx, cluster in enumerate(clusters):
-        if cluster == None:
-            logging.warn('Empty cluster appeared.')
-            clusters[idx] = []
-            
-    return labels, clusters, centers
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/aiohttp/hdrs.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/aiohttp/hdrs.py
deleted file mode 100644
index a619f2543e47cbd708a67cd3dd756fdd3094aa6b..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/aiohttp/hdrs.py
+++ /dev/null
@@ -1,114 +0,0 @@
-"""HTTP Headers constants."""
-
-# After changing the file content call ./tools/gen.py
-# to regenerate the headers parser
-import sys
-from typing import Set
-
-from multidict import istr
-
-if sys.version_info >= (3, 8):
-    from typing import Final
-else:
-    from typing_extensions import Final
-
-METH_ANY: Final[str] = "*"
-METH_CONNECT: Final[str] = "CONNECT"
-METH_HEAD: Final[str] = "HEAD"
-METH_GET: Final[str] = "GET"
-METH_DELETE: Final[str] = "DELETE"
-METH_OPTIONS: Final[str] = "OPTIONS"
-METH_PATCH: Final[str] = "PATCH"
-METH_POST: Final[str] = "POST"
-METH_PUT: Final[str] = "PUT"
-METH_TRACE: Final[str] = "TRACE"
-
-METH_ALL: Final[Set[str]] = {
-    METH_CONNECT,
-    METH_HEAD,
-    METH_GET,
-    METH_DELETE,
-    METH_OPTIONS,
-    METH_PATCH,
-    METH_POST,
-    METH_PUT,
-    METH_TRACE,
-}
-
-ACCEPT: Final[istr] = istr("Accept")
-ACCEPT_CHARSET: Final[istr] = istr("Accept-Charset")
-ACCEPT_ENCODING: Final[istr] = istr("Accept-Encoding")
-ACCEPT_LANGUAGE: Final[istr] = istr("Accept-Language")
-ACCEPT_RANGES: Final[istr] = istr("Accept-Ranges")
-ACCESS_CONTROL_MAX_AGE: Final[istr] = istr("Access-Control-Max-Age")
-ACCESS_CONTROL_ALLOW_CREDENTIALS: Final[istr] = istr("Access-Control-Allow-Credentials")
-ACCESS_CONTROL_ALLOW_HEADERS: Final[istr] = istr("Access-Control-Allow-Headers")
-ACCESS_CONTROL_ALLOW_METHODS: Final[istr] = istr("Access-Control-Allow-Methods")
-ACCESS_CONTROL_ALLOW_ORIGIN: Final[istr] = istr("Access-Control-Allow-Origin")
-ACCESS_CONTROL_EXPOSE_HEADERS: Final[istr] = istr("Access-Control-Expose-Headers")
-ACCESS_CONTROL_REQUEST_HEADERS: Final[istr] = istr("Access-Control-Request-Headers")
-ACCESS_CONTROL_REQUEST_METHOD: Final[istr] = istr("Access-Control-Request-Method")
-AGE: Final[istr] = istr("Age")
-ALLOW: Final[istr] = istr("Allow")
-AUTHORIZATION: Final[istr] = istr("Authorization")
-CACHE_CONTROL: Final[istr] = istr("Cache-Control")
-CONNECTION: Final[istr] = istr("Connection")
-CONTENT_DISPOSITION: Final[istr] = istr("Content-Disposition")
-CONTENT_ENCODING: Final[istr] = istr("Content-Encoding")
-CONTENT_LANGUAGE: Final[istr] = istr("Content-Language")
-CONTENT_LENGTH: Final[istr] = istr("Content-Length")
-CONTENT_LOCATION: Final[istr] = istr("Content-Location")
-CONTENT_MD5: Final[istr] = istr("Content-MD5")
-CONTENT_RANGE: Final[istr] = istr("Content-Range")
-CONTENT_TRANSFER_ENCODING: Final[istr] = istr("Content-Transfer-Encoding")
-CONTENT_TYPE: Final[istr] = istr("Content-Type")
-COOKIE: Final[istr] = istr("Cookie")
-DATE: Final[istr] = istr("Date")
-DESTINATION: Final[istr] = istr("Destination")
-DIGEST: Final[istr] = istr("Digest")
-ETAG: Final[istr] = istr("Etag")
-EXPECT: Final[istr] = istr("Expect")
-EXPIRES: Final[istr] = istr("Expires")
-FORWARDED: Final[istr] = istr("Forwarded")
-FROM: Final[istr] = istr("From")
-HOST: Final[istr] = istr("Host")
-IF_MATCH: Final[istr] = istr("If-Match")
-IF_MODIFIED_SINCE: Final[istr] = istr("If-Modified-Since")
-IF_NONE_MATCH: Final[istr] = istr("If-None-Match")
-IF_RANGE: Final[istr] = istr("If-Range")
-IF_UNMODIFIED_SINCE: Final[istr] = istr("If-Unmodified-Since")
-KEEP_ALIVE: Final[istr] = istr("Keep-Alive")
-LAST_EVENT_ID: Final[istr] = istr("Last-Event-ID")
-LAST_MODIFIED: Final[istr] = istr("Last-Modified")
-LINK: Final[istr] = istr("Link")
-LOCATION: Final[istr] = istr("Location")
-MAX_FORWARDS: Final[istr] = istr("Max-Forwards")
-ORIGIN: Final[istr] = istr("Origin")
-PRAGMA: Final[istr] = istr("Pragma")
-PROXY_AUTHENTICATE: Final[istr] = istr("Proxy-Authenticate")
-PROXY_AUTHORIZATION: Final[istr] = istr("Proxy-Authorization")
-RANGE: Final[istr] = istr("Range")
-REFERER: Final[istr] = istr("Referer")
-RETRY_AFTER: Final[istr] = istr("Retry-After")
-SEC_WEBSOCKET_ACCEPT: Final[istr] = istr("Sec-WebSocket-Accept")
-SEC_WEBSOCKET_VERSION: Final[istr] = istr("Sec-WebSocket-Version")
-SEC_WEBSOCKET_PROTOCOL: Final[istr] = istr("Sec-WebSocket-Protocol")
-SEC_WEBSOCKET_EXTENSIONS: Final[istr] = istr("Sec-WebSocket-Extensions")
-SEC_WEBSOCKET_KEY: Final[istr] = istr("Sec-WebSocket-Key")
-SEC_WEBSOCKET_KEY1: Final[istr] = istr("Sec-WebSocket-Key1")
-SERVER: Final[istr] = istr("Server")
-SET_COOKIE: Final[istr] = istr("Set-Cookie")
-TE: Final[istr] = istr("TE")
-TRAILER: Final[istr] = istr("Trailer")
-TRANSFER_ENCODING: Final[istr] = istr("Transfer-Encoding")
-UPGRADE: Final[istr] = istr("Upgrade")
-URI: Final[istr] = istr("URI")
-USER_AGENT: Final[istr] = istr("User-Agent")
-VARY: Final[istr] = istr("Vary")
-VIA: Final[istr] = istr("Via")
-WANT_DIGEST: Final[istr] = istr("Want-Digest")
-WARNING: Final[istr] = istr("Warning")
-WWW_AUTHENTICATE: Final[istr] = istr("WWW-Authenticate")
-X_FORWARDED_FOR: Final[istr] = istr("X-Forwarded-For")
-X_FORWARDED_HOST: Final[istr] = istr("X-Forwarded-Host")
-X_FORWARDED_PROTO: Final[istr] = istr("X-Forwarded-Proto")
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/misc/treeTools.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/misc/treeTools.py
deleted file mode 100644
index 24e10ba5b19ef41d56a552527680a4c73503cc3c..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/misc/treeTools.py
+++ /dev/null
@@ -1,45 +0,0 @@
-"""Generic tools for working with trees."""
-
-from math import ceil, log
-
-
-def build_n_ary_tree(leaves, n):
-    """Build N-ary tree from sequence of leaf nodes.
-
-    Return a list of lists where each non-leaf node is a list containing
-    max n nodes.
-    """
-    if not leaves:
-        return []
-
-    assert n > 1
-
-    depth = ceil(log(len(leaves), n))
-
-    if depth <= 1:
-        return list(leaves)
-
-    # Fully populate complete subtrees of root until we have enough leaves left
-    root = []
-    unassigned = None
-    full_step = n ** (depth - 1)
-    for i in range(0, len(leaves), full_step):
-        subtree = leaves[i : i + full_step]
-        if len(subtree) < full_step:
-            unassigned = subtree
-            break
-        while len(subtree) > n:
-            subtree = [subtree[k : k + n] for k in range(0, len(subtree), n)]
-        root.append(subtree)
-
-    if unassigned:
-        # Recurse to fill the last subtree, which is the only partially populated one
-        subtree = build_n_ary_tree(unassigned, n)
-        if len(subtree) <= n - len(root):
-            # replace last subtree with its children if they can still fit
-            root.extend(subtree)
-        else:
-            root.append(subtree)
-        assert len(root) <= n
-
-    return root
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/T_S_I__0.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/T_S_I__0.py
deleted file mode 100644
index 4112937d45d973bb61ae4ccf825f99a752901ed0..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/T_S_I__0.py
+++ /dev/null
@@ -1,57 +0,0 @@
-""" TSI{0,1,2,3,5} are private tables used by Microsoft Visual TrueType (VTT)
-tool to store its hinting source data.
-
-TSI0 is the index table containing the lengths and offsets for the glyph
-programs and 'extra' programs ('fpgm', 'prep', and 'cvt') that are contained
-in the TSI1 table.
-"""
-from . import DefaultTable
-import struct
-
-tsi0Format = ">HHL"
-
-
-def fixlongs(glyphID, textLength, textOffset):
-    return int(glyphID), int(textLength), textOffset
-
-
-class table_T_S_I__0(DefaultTable.DefaultTable):
-
-    dependencies = ["TSI1"]
-
-    def decompile(self, data, ttFont):
-        numGlyphs = ttFont["maxp"].numGlyphs
-        indices = []
-        size = struct.calcsize(tsi0Format)
-        for i in range(numGlyphs + 5):
-            glyphID, textLength, textOffset = fixlongs(
-                *struct.unpack(tsi0Format, data[:size])
-            )
-            indices.append((glyphID, textLength, textOffset))
-            data = data[size:]
-        assert len(data) == 0
-        assert indices[-5] == (0xFFFE, 0, 0xABFC1F34), "bad magic number"
-        self.indices = indices[:-5]
-        self.extra_indices = indices[-4:]
-
-    def compile(self, ttFont):
-        if not hasattr(self, "indices"):
-            # We have no corresponding table (TSI1 or TSI3); let's return
-            # no data, which effectively means "ignore us".
-            return b""
-        data = b""
-        for index, textLength, textOffset in self.indices:
-            data = data + struct.pack(tsi0Format, index, textLength, textOffset)
-        data = data + struct.pack(tsi0Format, 0xFFFE, 0, 0xABFC1F34)
-        for index, textLength, textOffset in self.extra_indices:
-            data = data + struct.pack(tsi0Format, index, textLength, textOffset)
-        return data
-
-    def set(self, indices, extra_indices):
-        # gets called by 'TSI1' or 'TSI3'
-        self.indices = indices
-        self.extra_indices = extra_indices
-
-    def toXML(self, writer, ttFont):
-        writer.comment("This table will be calculated by the compiler")
-        writer.newline()
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/frontend/assets/index-d39d2fed.js b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/frontend/assets/index-d39d2fed.js
deleted file mode 100644
index 3f3dfc50b2d7558bc9cc55822982b44c2124603f..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/frontend/assets/index-d39d2fed.js
+++ /dev/null
@@ -1,13264 +0,0 @@
-import{al as Zr,S as rl,e as ol,s as al,k as Hn,O as Jr,m as sl,o as Wn,p as Di,z as un,u as cl,v as mn,y as ll,A as Li,x as Xn,C as Pf,am as Cf,N as Qr,K as bi,M as qr,h as ul,B as Rv,a7 as Ef,n as xf,j as Ov,t as Mv,a9 as Iv,ab as Dv,ac as Lv,ad as Nv,E as wv,ae as Fv,q as Bv,r as Uv,F as Sf}from"./index-3370be2a.js";import{n as Vv}from"./ModifyUpload.svelte_svelte_type_style_lang-d2acacf0.js";import{B as kv}from"./Button-89624748.js";import{B as hl}from"./BlockLabel-56db415e.js";import{E as Gv}from"./Empty-585389a4.js";import{F as za}from"./File-ae385ffc.js";import{I as zv}from"./IconButton-abe5ede9.js";import{D as jv}from"./Download-fdaaf5d4.js";import{U as Hv}from"./Upload-f29b2460.js";import{M as Wv}from"./ModifyUpload-d8fc50ab.js";import{U as Xv}from"./UploadText-28892309.js";import"./Blocks-f0129fcd.js";import{E as Rb}from"./Model3D-db673911.js";var Rf={exports:{}};(function(ut,Ke){(function(Me,y){ut.exports=y()})(typeof self<"u"?self:typeof Zr<"u"?Zr:Zr,function(){return function(Me){var y={};function f(U){if(y[U])return y[U].exports;var _=y[U]={i:U,l:!1,exports:{}};return Me[U].call(_.exports,_,_.exports,f),_.l=!0,_.exports}return f.m=Me,f.c=y,f.d=function(U,_,x){f.o(U,_)||Object.defineProperty(U,_,{enumerable:!0,get:x})},f.r=function(U){typeof Symbol<"u"&&Symbol.toStringTag&&Object.defineProperty(U,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(U,"__esModule",{value:!0})},f.t=function(U,_){if(1&_&&(U=f(U)),8&_||4&_&&typeof U=="object"&&U&&U.__esModule)return U;var x=Object.create(null);if(f.r(x),Object.defineProperty(x,"default",{enumerable:!0,value:U}),2&_&&typeof U!="string")for(var u in U)f.d(x,u,function(M){return U[M]}.bind(null,u));return x},f.n=function(U){var _=U&&U.__esModule?function(){return U.default}:function(){return U};return f.d(_,"a",_),_},f.o=function(U,_){return Object.prototype.hasOwnProperty.call(U,_)},f.p="",f(f.s=169)}([function(Me,y,f){f.d(y,"d",function(){return R}),f.d(y,"e",function(){return 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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+" W:"+this.w+"}"},g.prototype.getClassName=function(){return"Vector4"},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(){var l=new Array;return this.toArray(l,0),l},g.prototype.toArray=function(l,h){return h===void 0&&(h=0),l[h]=this.x,l[h+1]=this.y,l[h+2]=this.z,l[h+3]=this.w,this},g.prototype.fromArray=function(l,h){return h===void 0&&(h=0),g.FromArrayToRef(l,h,this),this},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.add=function(l){return new g(this.x+l.x,this.y+l.y,this.z+l.z,this.w+l.w)},g.prototype.addToRef=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.subtractInPlace=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.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 C(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=C.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),ct=+(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,ct*q,wt*q,k*q,Ge*q,st*q,It*q,H*q,nt*q,mt*q,Pt*q,Z*q,$e*q,St*q,Ot*q,l),this},g.prototype.addAtIndex=function(l,h){return this._m[l]+=h,this._markAsUpdated(),this},g.prototype.multiplyAtIndex=function(l,h){return this._m[l]*=h,this._markAsUpdated(),this},g.prototype.setTranslationFromFloats=function(l,h,v){return this._m[12]=l,this._m[13]=h,this._m[14]=v,this._markAsUpdated(),this},g.prototype.addTranslationFromFloats=function(l,h,v){return this._m[12]+=l,this._m[13]+=h,this._m[14]+=v,this._markAsUpdated(),this},g.prototype.setTranslation=function(l){return this.setTranslationFromFloats(l._x,l._y,l._z)},g.prototype.getTranslation=function(){return new C(this._m[12],this._m[13],this._m[14])},g.prototype.getTranslationToRef=function(l){return l.x=this._m[12],l.y=this._m[13],l.z=this._m[14],this},g.prototype.removeRotationAndScaling=function(){var l=this.m;return g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,l[12],l[13],l[14],l[15],this),this._updateIdentityStatus(l[12]===0&&l[13]===0&&l[14]===0&&l[15]===1),this},g.prototype.multiply=function(l){var h=new g;return this.multiplyToRef(l,h),h},g.prototype.copyFrom=function(l){l.copyToArray(this._m);var h=l;return this._updateIdentityStatus(h._isIdentity,h._isIdentityDirty,h._isIdentity3x2,h._isIdentity3x2Dirty),this},g.prototype.copyToArray=function(l,h){h===void 0&&(h=0);var v=this._m;return l[h]=v[0],l[h+1]=v[1],l[h+2]=v[2],l[h+3]=v[3],l[h+4]=v[4],l[h+5]=v[5],l[h+6]=v[6],l[h+7]=v[7],l[h+8]=v[8],l[h+9]=v[9],l[h+10]=v[10],l[h+11]=v[11],l[h+12]=v[12],l[h+13]=v[13],l[h+14]=v[14],l[h+15]=v[15],this},g.prototype.multiplyToRef=function(l,h){return this._isIdentity?(h.copyFrom(l),this):l._isIdentity?(h.copyFrom(this),this):(this.multiplyToArray(l,h._m,0),h._markAsUpdated(),this)},g.prototype.multiplyToArray=function(l,h,v){var E=this._m,D=l.m,w=E[0],N=E[1],I=E[2],V=E[3],X=E[4],j=E[5],ne=E[6],te=E[7],de=E[8],pe=E[9],ae=E[10],ee=E[11],K=E[12],$=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 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ae,H._effectiveMaterial=null,H._shouldGenerateFlatShading=!1,H._originalBuilderSideOrientation=L.DEFAULTSIDE,H.overrideMaterialSideOrientation=null,Q=H.getScene(),re){if(re._geometry&&re._geometry.applyToMesh(H),u.a.DeepCopy(re,H,["name","material","skeleton","instances","parent","uniqueId","source","metadata","morphTargetManager","hasInstances","source","worldMatrixInstancedBuffer","hasLODLevels","geometry","isBlocked","areNormalsFrozen","facetNb","isFacetDataEnabled","lightSources","useBones","isAnInstance","collider","edgesRenderer","forward","up","right","absolutePosition","absoluteScaling","absoluteRotationQuaternion","isWorldMatrixFrozen","nonUniformScaling","behaviors","worldMatrixFromCache","hasThinInstances","cloneMeshMap"],["_poseMatrix"]),H._internalMeshDataInfo._source=re,Q.useClonedMeshMap&&(re._internalMeshDataInfo.meshMap||(re._internalMeshDataInfo.meshMap={}),re._internalMeshDataInfo.meshMap[H.uniqueId]=H),H._originalBuilderSideOrientation=re._originalBuilderSideOrientation,H._creationDataStorage=re._creationDataStorage,re._ranges){var Z=re._ranges;for(var G in Z)Z.hasOwnProperty(G)&&Z[G]&&H.createAnimationRange(G,Z[G].from,Z[G].to)}var W;if(re.metadata&&re.metadata.clone?H.metadata=re.metadata.clone():H.metadata=re.metadata,M.a&&M.a.HasTags(re)&&M.a.AddTagsTo(H,M.a.GetTags(re,!0)),H.setEnabled(re.isEnabled()),H.parent=re.parent,H.setPivotMatrix(re.getPivotMatrix()),H.id=G+"."+re.id,H.material=re.material,!Y)for(var q=re.getDescendants(!0),he=0;he<q.length;he++){var ge=q[he];ge.clone&&ge.clone(G+"."+ge.name,H)}if(re.morphTargetManager&&(H.morphTargetManager=re.morphTargetManager),Q.getPhysicsEngine){var me=Q.getPhysicsEngine();if(k&&me){var _e=me.getImpostorForPhysicsObject(re);_e&&(H.physicsImpostor=_e.clone(H))}}for(W=0;W<Q.particleSystems.length;W++){var be=Q.particleSystems[W];be.emitter===re&&be.clone(be.name,H)}H.refreshBoundingInfo(),H.computeWorldMatrix(!0)}return oe!==null&&(H.parent=oe),H._instanceDataStorage.hardwareInstancedRendering=H.getEngine().getCaps().instancedArrays,H}return Object(U.d)(L,$),L._GetDefaultSideOrientation=function(G){return G||L.FRONTSIDE},Object.defineProperty(L.prototype,"computeBonesUsingShaders",{get:function(){return this._internalAbstractMeshDataInfo._computeBonesUsingShaders},set:function(G){this._internalAbstractMeshDataInfo._computeBonesUsingShaders!==G&&(G&&this._internalMeshDataInfo._sourcePositions&&(this.setVerticesData(c.b.PositionKind,this._internalMeshDataInfo._sourcePositions.slice(),!0),this._internalMeshDataInfo._sourceNormals&&this.setVerticesData(c.b.NormalKind,this._internalMeshDataInfo._sourceNormals.slice(),!0)),this._internalAbstractMeshDataInfo._computeBonesUsingShaders=G,this._markSubMeshesAsAttributesDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"onBeforeRenderObservable",{get:function(){return this._internalMeshDataInfo._onBeforeRenderObservable||(this._internalMeshDataInfo._onBeforeRenderObservable=new 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this._internalMeshDataInfo._morphTargetManager},set:function(G){this._internalMeshDataInfo._morphTargetManager!==G&&(this._internalMeshDataInfo._morphTargetManager=G,this._syncGeometryWithMorphTargetManager())},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"source",{get:function(){return this._internalMeshDataInfo._source},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"cloneMeshMap",{get:function(){return this._internalMeshDataInfo.meshMap},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"isUnIndexed",{get:function(){return this._unIndexed},set:function(G){this._unIndexed!==G&&(this._unIndexed=G,this._markSubMeshesAsAttributesDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"worldMatrixInstancedBuffer",{get:function(){return this._instanceDataStorage.instancesData},enumerable:!1,configurable:!0}),Object.defineProperty(L.prototype,"manualUpdateOfWorldMatrixInstancedBuffer",{get:function(){return this._instanceDataStorage.manualUpdate},set:function(G){this._instanceDataStorage.manualUpdate=G},enumerable:!1,configurable:!0}),L.prototype.instantiateHierarchy=function(G,Q,oe){G===void 0&&(G=null);var re=!(this.getTotalVertices()>0)||Q&&Q.doNotInstantiate?this.clone("Clone of "+(this.name||this.id),G||this.parent,!0):this.createInstance("instance of "+(this.name||this.id));re&&(re.parent=G||this.parent,re.position=this.position.clone(),re.scaling=this.scaling.clone(),this.rotationQuaternion?re.rotationQuaternion=this.rotationQuaternion.clone():re.rotation=this.rotation.clone(),oe&&oe(this,re));for(var Y=0,k=this.getChildTransformNodes(!0);Y<k.length;Y++)k[Y].instantiateHierarchy(re,Q,oe);return re},L.prototype.getClassName=function(){return"Mesh"},Object.defineProperty(L.prototype,"_isMesh",{get:function(){return!0},enumerable:!1,configurable:!0}),L.prototype.toString=function(G){var Q=$.prototype.toString.call(this,G);if(Q+=", n vertices: "+this.getTotalVertices(),Q+=", parent: "+(this._waitingParentId?this._waitingParentId:this.parent?this.parent.name:"NONE"),this.animations)for(var oe=0;oe<this.animations.length;oe++)Q+=", animation[0]: "+this.animations[oe].toString(G);if(G)if(this._geometry){var re=this.getIndices(),Y=this.getVerticesData(c.b.PositionKind);Y&&re&&(Q+=", flat shading: "+(Y.length/3===re.length?"YES":"NO"))}else Q+=", flat shading: UNKNOWN";return Q},L.prototype._unBindEffect=function(){$.prototype._unBindEffect.call(this);for(var G=0,Q=this.instances;G<Q.length;G++)Q[G]._unBindEffect()},Object.defineProperty(L.prototype,"hasLODLevels",{get:function(){return this._internalMeshDataInfo._LODLevels.length>0},enumerable:!1,configurable:!0}),L.prototype.getLODLevels=function(){return this._internalMeshDataInfo._LODLevels},L.prototype._sortLODLevels=function(){this._internalMeshDataInfo._LODLevels.sort(function(G,Q){return G.distance<Q.distance?1:G.distance>Q.distance?-1:0})},L.prototype.addLODLevel=function(G,Q){if(Q&&Q._masterMesh)return N.a.Warn("You cannot use a mesh as LOD level twice"),this;var oe=new j.a(G,Q);return this._internalMeshDataInfo._LODLevels.push(oe),Q&&(Q._masterMesh=this),this._sortLODLevels(),this},L.prototype.getLODLevelAtDistance=function(G){for(var Q=this._internalMeshDataInfo,oe=0;oe<Q._LODLevels.length;oe++){var re=Q._LODLevels[oe];if(re.distance===G)return re.mesh}return null},L.prototype.removeLODLevel=function(G){for(var Q=this._internalMeshDataInfo,oe=0;oe<Q._LODLevels.length;oe++)Q._LODLevels[oe].mesh===G&&(Q._LODLevels.splice(oe,1),G&&(G._masterMesh=null));return this._sortLODLevels(),this},L.prototype.getLOD=function(G,Q){var oe,re=this._internalMeshDataInfo;if(!re._LODLevels||re._LODLevels.length===0)return this;Q?oe=Q:oe=this.getBoundingInfo().boundingSphere;var Y=oe.centerWorld.subtract(G.globalPosition).length();if(re._LODLevels[re._LODLevels.length-1].distance>Y)return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,this),this;for(var k=0;k<re._LODLevels.length;k++){var H=re._LODLevels[k];if(H.distance<Y){if(H.mesh){if(H.mesh.delayLoadState===D.a.DELAYLOADSTATE_NOTLOADED)return H.mesh._checkDelayState(),this;if(H.mesh.delayLoadState===D.a.DELAYLOADSTATE_LOADING)return this;H.mesh._preActivate(),H.mesh._updateSubMeshesBoundingInfo(this.worldMatrixFromCache)}return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,H.mesh),H.mesh}}return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,this),this},Object.defineProperty(L.prototype,"geometry",{get:function(){return this._geometry},enumerable:!1,configurable:!0}),L.prototype.getTotalVertices=function(){return this._geometry===null||this._geometry===void 0?0:this._geometry.getTotalVertices()},L.prototype.getVerticesData=function(G,Q,oe){return this._geometry?this._geometry.getVerticesData(G,Q,oe):null},L.prototype.getVertexBuffer=function(G){return this._geometry?this._geometry.getVertexBuffer(G):null},L.prototype.isVerticesDataPresent=function(G){return this._geometry?this._geometry.isVerticesDataPresent(G):!!this._delayInfo&&this._delayInfo.indexOf(G)!==-1},L.prototype.isVertexBufferUpdatable=function(G){return this._geometry?this._geometry.isVertexBufferUpdatable(G):!!this._delayInfo&&this._delayInfo.indexOf(G)!==-1},L.prototype.getVerticesDataKinds=function(){if(!this._geometry){var G=new Array;return this._delayInfo&&this._delayInfo.forEach(function(Q){G.push(Q)}),G}return this._geometry.getVerticesDataKinds()},L.prototype.getTotalIndices=function(){return this._geometry?this._geometry.getTotalIndices():0},L.prototype.getIndices=function(G,Q){return this._geometry?this._geometry.getIndices(G,Q):[]},Object.defineProperty(L.prototype,"isBlocked",{get:function(){return this._masterMesh!==null&&this._masterMesh!==void 0},enumerable:!1,configurable:!0}),L.prototype.isReady=function(G,Q){var oe,re,Y,k,H,Z;if(G===void 0&&(G=!1),Q===void 0&&(Q=!1),this.delayLoadState===D.a.DELAYLOADSTATE_LOADING||!$.prototype.isReady.call(this,G))return!1;if(!this.subMeshes||this.subMeshes.length===0||!G)return!0;var W=this.getEngine(),q=this.getScene(),he=Q||W.getCaps().instancedArrays&&(this.instances.length>0||this.hasThinInstances);this.computeWorldMatrix();var ge=this.material||q.defaultMaterial;if(ge){if(ge._storeEffectOnSubMeshes)for(var me=0,_e=this.subMeshes;me<_e.length;me++){var be=(je=_e[me]).getMaterial();if(be){if(be._storeEffectOnSubMeshes){if(!be.isReadyForSubMesh(this,je,he))return!1}else if(!be.isReady(this,he))return!1}}else if(!ge.isReady(this,he))return!1}for(var Pe=0,ye=this.lightSources;Pe<ye.length;Pe++){var Be=ye[Pe].getShadowGenerator();if(Be&&(!(!((oe=Be.getShadowMap())===null||oe===void 0)&&oe.renderList)||!((re=Be.getShadowMap())===null||re===void 0)&&re.renderList&&((k=(Y=Be.getShadowMap())===null||Y===void 0?void 0:Y.renderList)===null||k===void 0?void 0:k.indexOf(this))!==-1))for(var ke=0,We=this.subMeshes;ke<We.length;ke++){var je=We[ke];if(!Be.isReady(je,he,(Z=(H=je.getMaterial())===null||H===void 0?void 0:H.needAlphaBlendingForMesh(this))!==null&&Z!==void 0&&Z))return!1}}for(var He=0,qe=this._internalMeshDataInfo._LODLevels;He<qe.length;He++){var Ge=qe[He];if(Ge.mesh&&!Ge.mesh.isReady(he))return!1}return!0},Object.defineProperty(L.prototype,"areNormalsFrozen",{get:function(){return this._internalMeshDataInfo._areNormalsFrozen},enumerable:!1,configurable:!0}),L.prototype.freezeNormals=function(){return this._internalMeshDataInfo._areNormalsFrozen=!0,this},L.prototype.unfreezeNormals=function(){return this._internalMeshDataInfo._areNormalsFrozen=!1,this},Object.defineProperty(L.prototype,"overridenInstanceCount",{set:function(G){this._instanceDataStorage.overridenInstanceCount=G},enumerable:!1,configurable:!0}),L.prototype._preActivate=function(){var G=this._internalMeshDataInfo,Q=this.getScene().getRenderId();return G._preActivateId===Q||(G._preActivateId=Q,this._instanceDataStorage.visibleInstances=null),this},L.prototype._preActivateForIntermediateRendering=function(G){return this._instanceDataStorage.visibleInstances&&(this._instanceDataStorage.visibleInstances.intermediateDefaultRenderId=G),this},L.prototype._registerInstanceForRenderId=function(G,Q){return this._instanceDataStorage.visibleInstances||(this._instanceDataStorage.visibleInstances={defaultRenderId:Q,selfDefaultRenderId:this._renderId}),this._instanceDataStorage.visibleInstances[Q]||(this._instanceDataStorage.previousRenderId!==void 0&&this._instanceDataStorage.isFrozen&&(this._instanceDataStorage.visibleInstances[this._instanceDataStorage.previousRenderId]=null),this._instanceDataStorage.previousRenderId=Q,this._instanceDataStorage.visibleInstances[Q]=new 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 x.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 x.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 x.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:x.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]=x.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=C.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 G._sourcePositions;G._sourcePositions=new Float32Array(Q),this.isVertexBufferUpdatable(c.b.PositionKind)||this.setVerticesData(c.b.PositionKind,Q,!0)}return G._sourcePositions},L.prototype.setNormalsForCPUSkinning=function(){var G=this._internalMeshDataInfo;if(!G._sourceNormals){var Q=this.getVerticesData(c.b.NormalKind);if(!Q)return G._sourceNormals;G._sourceNormals=new Float32Array(Q),this.isVertexBufferUpdatable(c.b.NormalKind)||this.setVerticesData(c.b.NormalKind,Q,!0)}return G._sourceNormals},L.prototype.applySkeleton=function(G){if(!this.geometry)return this;if(this.geometry._softwareSkinningFrameId==this.getScene().getFrameId())return this;if(this.geometry._softwareSkinningFrameId=this.getScene().getFrameId(),!this.isVerticesDataPresent(c.b.PositionKind))return this;if(!this.isVerticesDataPresent(c.b.MatricesIndicesKind))return this;if(!this.isVerticesDataPresent(c.b.MatricesWeightsKind))return this;var 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 ke;for(W=0;W<4;W++)(ke=Z[ye+W])>0&&(R.a.FromFloat32ArrayToRefScaled(me,Math.floor(16*H[ye+W]),ke,Pe),be.addToSelf(Pe));if(q)for(W=0;W<4;W++)(ke=ge[ye+W])>0&&(R.a.FromFloat32ArrayToRefScaled(me,Math.floor(16*he[ye+W]),ke,Pe),be.addToSelf(Pe));R.e.TransformCoordinatesFromFloatsToRef(oe._sourcePositions[Be],oe._sourcePositions[Be+1],oe._sourcePositions[Be+2],be,_e),_e.toArray(Y,Be),Q&&(R.e.TransformNormalFromFloatsToRef(oe._sourceNormals[Be],oe._sourceNormals[Be+1],oe._sourceNormals[Be+2],be,_e),_e.toArray(k,Be)),be.reset()}return this.updateVerticesData(c.b.PositionKind,Y),Q&&this.updateVerticesData(c.b.NormalKind,k),this},L.MinMax=function(G){var Q=null,oe=null;return G.forEach(function(re){var Y=re.getBoundingInfo().boundingBox;Q&&oe?(Q.minimizeInPlace(Y.minimumWorld),oe.maximizeInPlace(Y.maximumWorld)):(Q=Y.minimumWorld,oe=Y.maximumWorld)}),Q&&oe?{min:Q,max:oe}:{min:R.e.Zero(),max:R.e.Zero()}},L.Center=function(G){var Q=G instanceof Array?L.MinMax(G):G;return R.e.Center(Q.min,Q.max)},L.MergeMeshes=function(G,Q,oe,re,Y,k){var H;if(Q===void 0&&(Q=!0),!oe){var Z=0;for(H=0;H<G.length;H++)if(G[H]&&(Z+=G[H].getTotalVertices())>=65536)return N.a.Warn("Cannot merge meshes because resulting mesh will have more than 65536 vertices. 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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=C.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 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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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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:C.a.TEXTURETYPE_UNSIGNED_INT,samplingMode:C.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,C.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,C.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(),x.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)),x.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(x.a.IsWindowObjectExist()){var h=this.loadingScreen;h&&h.displayLoadingUI()}},l.prototype.hideLoadingUI=function(){if(x.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=C.a.ALPHA_DISABLE,l.ALPHA_ADD=C.a.ALPHA_ADD,l.ALPHA_COMBINE=C.a.ALPHA_COMBINE,l.ALPHA_SUBTRACT=C.a.ALPHA_SUBTRACT,l.ALPHA_MULTIPLY=C.a.ALPHA_MULTIPLY,l.ALPHA_MAXIMIZED=C.a.ALPHA_MAXIMIZED,l.ALPHA_ONEONE=C.a.ALPHA_ONEONE,l.ALPHA_PREMULTIPLIED=C.a.ALPHA_PREMULTIPLIED,l.ALPHA_PREMULTIPLIED_PORTERDUFF=C.a.ALPHA_PREMULTIPLIED_PORTERDUFF,l.ALPHA_INTERPOLATE=C.a.ALPHA_INTERPOLATE,l.ALPHA_SCREENMODE=C.a.ALPHA_SCREENMODE,l.DELAYLOADSTATE_NONE=C.a.DELAYLOADSTATE_NONE,l.DELAYLOADSTATE_LOADED=C.a.DELAYLOADSTATE_LOADED,l.DELAYLOADSTATE_LOADING=C.a.DELAYLOADSTATE_LOADING,l.DELAYLOADSTATE_NOTLOADED=C.a.DELAYLOADSTATE_NOTLOADED,l.NEVER=C.a.NEVER,l.ALWAYS=C.a.ALWAYS,l.LESS=C.a.LESS,l.EQUAL=C.a.EQUAL,l.LEQUAL=C.a.LEQUAL,l.GREATER=C.a.GREATER,l.GEQUAL=C.a.GEQUAL,l.NOTEQUAL=C.a.NOTEQUAL,l.KEEP=C.a.KEEP,l.REPLACE=C.a.REPLACE,l.INCR=C.a.INCR,l.DECR=C.a.DECR,l.INVERT=C.a.INVERT,l.INCR_WRAP=C.a.INCR_WRAP,l.DECR_WRAP=C.a.DECR_WRAP,l.TEXTURE_CLAMP_ADDRESSMODE=C.a.TEXTURE_CLAMP_ADDRESSMODE,l.TEXTURE_WRAP_ADDRESSMODE=C.a.TEXTURE_WRAP_ADDRESSMODE,l.TEXTURE_MIRROR_ADDRESSMODE=C.a.TEXTURE_MIRROR_ADDRESSMODE,l.TEXTUREFORMAT_ALPHA=C.a.TEXTUREFORMAT_ALPHA,l.TEXTUREFORMAT_LUMINANCE=C.a.TEXTUREFORMAT_LUMINANCE,l.TEXTUREFORMAT_LUMINANCE_ALPHA=C.a.TEXTUREFORMAT_LUMINANCE_ALPHA,l.TEXTUREFORMAT_RGB=C.a.TEXTUREFORMAT_RGB,l.TEXTUREFORMAT_RGBA=C.a.TEXTUREFORMAT_RGBA,l.TEXTUREFORMAT_RED=C.a.TEXTUREFORMAT_RED,l.TEXTUREFORMAT_R=C.a.TEXTUREFORMAT_R,l.TEXTUREFORMAT_RG=C.a.TEXTUREFORMAT_RG,l.TEXTUREFORMAT_RED_INTEGER=C.a.TEXTUREFORMAT_RED_INTEGER,l.TEXTUREFORMAT_R_INTEGER=C.a.TEXTUREFORMAT_R_INTEGER,l.TEXTUREFORMAT_RG_INTEGER=C.a.TEXTUREFORMAT_RG_INTEGER,l.TEXTUREFORMAT_RGB_INTEGER=C.a.TEXTUREFORMAT_RGB_INTEGER,l.TEXTUREFORMAT_RGBA_INTEGER=C.a.TEXTUREFORMAT_RGBA_INTEGER,l.TEXTURETYPE_UNSIGNED_BYTE=C.a.TEXTURETYPE_UNSIGNED_BYTE,l.TEXTURETYPE_UNSIGNED_INT=C.a.TEXTURETYPE_UNSIGNED_INT,l.TEXTURETYPE_FLOAT=C.a.TEXTURETYPE_FLOAT,l.TEXTURETYPE_HALF_FLOAT=C.a.TEXTURETYPE_HALF_FLOAT,l.TEXTURETYPE_BYTE=C.a.TEXTURETYPE_BYTE,l.TEXTURETYPE_SHORT=C.a.TEXTURETYPE_SHORT,l.TEXTURETYPE_UNSIGNED_SHORT=C.a.TEXTURETYPE_UNSIGNED_SHORT,l.TEXTURETYPE_INT=C.a.TEXTURETYPE_INT,l.TEXTURETYPE_UNSIGNED_INTEGER=C.a.TEXTURETYPE_UNSIGNED_INTEGER,l.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4=C.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4,l.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1=C.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1,l.TEXTURETYPE_UNSIGNED_SHORT_5_6_5=C.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5,l.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV=C.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV,l.TEXTURETYPE_UNSIGNED_INT_24_8=C.a.TEXTURETYPE_UNSIGNED_INT_24_8,l.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV=C.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV,l.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV=C.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV,l.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV=C.a.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV,l.TEXTURE_NEAREST_SAMPLINGMODE=C.a.TEXTURE_NEAREST_SAMPLINGMODE,l.TEXTURE_BILINEAR_SAMPLINGMODE=C.a.TEXTURE_BILINEAR_SAMPLINGMODE,l.TEXTURE_TRILINEAR_SAMPLINGMODE=C.a.TEXTURE_TRILINEAR_SAMPLINGMODE,l.TEXTURE_NEAREST_NEAREST_MIPLINEAR=C.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR_MIPNEAREST=C.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST,l.TEXTURE_LINEAR_LINEAR_MIPLINEAR=C.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_NEAREST_MIPNEAREST=C.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPNEAREST=C.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPLINEAR=C.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_LINEAR=C.a.TEXTURE_NEAREST_LINEAR,l.TEXTURE_NEAREST_NEAREST=C.a.TEXTURE_NEAREST_NEAREST,l.TEXTURE_LINEAR_NEAREST_MIPNEAREST=C.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST,l.TEXTURE_LINEAR_NEAREST_MIPLINEAR=C.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR=C.a.TEXTURE_LINEAR_LINEAR,l.TEXTURE_LINEAR_NEAREST=C.a.TEXTURE_LINEAR_NEAREST,l.TEXTURE_EXPLICIT_MODE=C.a.TEXTURE_EXPLICIT_MODE,l.TEXTURE_SPHERICAL_MODE=C.a.TEXTURE_SPHERICAL_MODE,l.TEXTURE_PLANAR_MODE=C.a.TEXTURE_PLANAR_MODE,l.TEXTURE_CUBIC_MODE=C.a.TEXTURE_CUBIC_MODE,l.TEXTURE_PROJECTION_MODE=C.a.TEXTURE_PROJECTION_MODE,l.TEXTURE_SKYBOX_MODE=C.a.TEXTURE_SKYBOX_MODE,l.TEXTURE_INVCUBIC_MODE=C.a.TEXTURE_INVCUBIC_MODE,l.TEXTURE_EQUIRECTANGULAR_MODE=C.a.TEXTURE_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MODE=C.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE=C.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,l.SCALEMODE_FLOOR=C.a.SCALEMODE_FLOOR,l.SCALEMODE_NEAREST=C.a.SCALEMODE_NEAREST,l.SCALEMODE_CEILING=C.a.SCALEMODE_CEILING,l._RescalePostProcessFactory=null,l}(R.a))},function(Me,y,f){f.d(y,"a",function(){return 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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&&x.a.LastCreatedEngine)for(var h=x.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=C.a.Black(),T}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(0),_=f(4),x=f(21),u=f(9),M=f(8),R=function(){function C(){}return C.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}},C.prototype.applyToMesh=function(m,c){return this._applyTo(m,c),this},C.prototype.applyToGeometry=function(m,c){return this._applyTo(m,c),this},C.prototype.updateMesh=function(m){return this._update(m),this},C.prototype.updateGeometry=function(m){return this._update(m),this},C.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},C.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},C.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},C.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},C.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)},C.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)},C.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},C.ExtractFromMesh=function(m,c,T){return C._ExtractFrom(m,c,T)},C.ExtractFromGeometry=function(m,c,T){return C._ExtractFrom(m,c,T)},C._ExtractFrom=function(m,c,T){var A=new C;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},C.CreateRibbon=function(m){throw x.a.WarnImport("ribbonBuilder")},C.CreateBox=function(m){throw x.a.WarnImport("boxBuilder")},C.CreateTiledBox=function(m){throw x.a.WarnImport("tiledBoxBuilder")},C.CreateTiledPlane=function(m){throw x.a.WarnImport("tiledPlaneBuilder")},C.CreateSphere=function(m){throw x.a.WarnImport("sphereBuilder")},C.CreateCylinder=function(m){throw x.a.WarnImport("cylinderBuilder")},C.CreateTorus=function(m){throw x.a.WarnImport("torusBuilder")},C.CreateLineSystem=function(m){throw x.a.WarnImport("linesBuilder")},C.CreateDashedLines=function(m){throw x.a.WarnImport("linesBuilder")},C.CreateGround=function(m){throw x.a.WarnImport("groundBuilder")},C.CreateTiledGround=function(m){throw x.a.WarnImport("groundBuilder")},C.CreateGroundFromHeightMap=function(m){throw x.a.WarnImport("groundBuilder")},C.CreatePlane=function(m){throw x.a.WarnImport("planeBuilder")},C.CreateDisc=function(m){throw x.a.WarnImport("discBuilder")},C.CreatePolygon=function(m,c,T,A,S,g,l){throw x.a.WarnImport("polygonBuilder")},C.CreateIcoSphere=function(m){throw x.a.WarnImport("icoSphereBuilder")},C.CreatePolyhedron=function(m){throw x.a.WarnImport("polyhedronBuilder")},C.CreateCapsule=function(m){throw m===void 0&&(m={orientation:U.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6}),x.a.WarnImport("capsuleBuilder")},C.CreateTorusKnot=function(m){throw x.a.WarnImport("torusKnotBuilder")},C.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,$e=0,ct=A.bbSize.x>A.bbSize.y?A.bbSize.x:A.bbSize.y;ct=ct>A.bbSize.z?ct:A.bbSize.z,H=A.subDiv.X*re/A.bbSize.x,Z=A.subDiv.Y*re/A.bbSize.y,W=A.subDiv.Z*re/A.bbSize.z,q=A.subDiv.max*A.subDiv.max,A.facetPartitioning.length=0}for(S=0;S<m.length;S++)T[S]=0;var st=c.length/3|0;for(S=0;S<st;S++){if(j=(X=3*c[3*S])+1,ne=X+2,de=(te=3*c[3*S+1])+1,pe=te+2,ee=(ae=3*c[3*S+2])+1,K=ae+2,g=m[X]-m[te],l=m[j]-m[de],h=m[ne]-m[pe],v=m[ae]-m[te],E=m[ee]-m[de],w=oe*(l*(D=m[K]-m[pe])-h*E),N=oe*(h*v-g*D),I=oe*(g*E-l*v),w/=V=(V=Math.sqrt(w*w+N*N+I*I))===0?1:V,N/=V,I/=V,$&&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},C._ComputeSides=function(m,c,T,A,S,g,l){var h,v,E=T.length,D=A.length;switch(m=m||C.DEFAULTSIDE){case C.FRONTSIDE:break;case C.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 C.DOUBLESIDE:for(var N=c.length,I=N/3,V=0;V<N;V++)c[N+V]=c[V];for(h=0;h<E;h+=3)T[h+E]=T[h+2]+I,T[h+1+E]=T[h+1]+I,T[h+2+E]=T[h]+I;for(v=0;v<D;v++)A[D+v]=-A[v];var X=S.length,j=0;for(j=0;j<X;j++)S[j+X]=S[j];for(g=g||new U.f(0,0,1,1),l=l||new U.f(0,0,1,1),j=0,h=0;h<X/2;h++)S[j]=g.x+(g.z-g.x)*S[j],S[j+1]=g.y+(g.w-g.y)*S[j+1],S[j+X]=l.x+(l.z-l.x)*S[j+X],S[j+X+1]=l.y+(l.w-l.y)*S[j+X+1],j+=2}},C.ImportVertexData=function(m,c){var T=new C,A=m.positions;A&&T.set(A,_.b.PositionKind);var S=m.normals;S&&T.set(S,_.b.NormalKind);var g=m.tangents;g&&T.set(g,_.b.TangentKind);var l=m.uvs;l&&T.set(l,_.b.UVKind);var h=m.uv2s;h&&T.set(h,_.b.UV2Kind);var v=m.uv3s;v&&T.set(v,_.b.UV3Kind);var E=m.uv4s;E&&T.set(E,_.b.UV4Kind);var D=m.uv5s;D&&T.set(D,_.b.UV5Kind);var w=m.uv6s;w&&T.set(w,_.b.UV6Kind);var N=m.colors;N&&T.set(u.b.CheckColors4(N,A.length/3),_.b.ColorKind);var I=m.matricesIndices;I&&T.set(I,_.b.MatricesIndicesKind);var V=m.matricesWeights;V&&T.set(V,_.b.MatricesWeightsKind);var 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M(R){return u.apply(this,R)||this}return Object(U.d)(M,u),M.Create=function(){return Object.create(M.prototype)},M.prototype.registerStep=function(R,C,m){var c=0;for(Number.MAX_VALUE;c<this.length&&!(R<this[c].index);c++);this.splice(c,0,{index:R,component:C,action:m.bind(C)})},M.prototype.clear=function(){this.length=0},M}(Array)},function(Me,y,f){f.d(y,"a",function(){return x}),f.d(y,"c",function(){return u}),f.d(y,"d",function(){return M}),f.d(y,"b",function(){return R});var U=f(1),_=f(0),x=function(){function C(){}return C.POINTERDOWN=1,C.POINTERUP=2,C.POINTERMOVE=4,C.POINTERWHEEL=8,C.POINTERPICK=16,C.POINTERTAP=32,C.POINTERDOUBLETAP=64,C}(),u=function(C,m){this.type=C,this.event=m},M=function(C){function m(c,T,A,S){var g=C.call(this,c,T)||this;return g.ray=null,g.skipOnPointerObservable=!1,g.localPosition=new _.d(A,S),g}return Object(U.d)(m,C),m}(u),R=function(C){function m(c,T,A){var S=C.call(this,c,T)||this;return S.pickInfo=A,S}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),x=f(57),u=f(6),M=f(33),R=f(112),C=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=x.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];C.a&&C.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(x){return x+" 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 x});var U,_=f(0);(function(M){M[M.LOCAL=0]="LOCAL",M[M.WORLD=1]="WORLD",M[M.BONE=2]="BONE"})(U||(U={}));var x,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"})(x||(x={}))},function(Me,y,f){f.d(y,"a",function(){return g});var U=f(1),_=f(3),x=f(33),u=f(12),M=f(6),R=f(0),C=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 x.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=C.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))}C.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}(C.a)},function(Me,y,f){f.d(y,"a",function(){return A});var U=f(1),_=f(3),x=f(12),u=f(6),M=f(22),R=f(61),C=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||x.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 C.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 x.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),x=f(21),u=f(6),M=f(141),R=f(142),C=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 C.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 x.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),x.a.WarnImport("Engine.RawTexture")},N.prototype.createRawCubeTexture=function(I,V,X,j,ne,te,de,pe){throw x.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),x.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),x.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 x.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),x=f(102),u=f(2),M=f(21);(function(C){C[C.Unknown=0]="Unknown",C[C.Url=1]="Url",C[C.Temp=2]="Temp",C[C.Raw=3]="Raw",C[C.Dynamic=4]="Dynamic",C[C.RenderTarget=5]="RenderTarget",C[C.MultiRenderTarget=6]="MultiRenderTarget",C[C.Cube=7]="Cube",C[C.CubeRaw=8]="CubeRaw",C[C.CubePrefiltered=9]="CubePrefiltered",C[C.Raw3D=10]="Raw3D",C[C.Raw2DArray=11]="Raw2DArray",C[C.Depth=12]="Depth",C[C.CubeRawRGBD=13]="CubeRawRGBD"})(U||(U={}));var R=function(){function C(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 C.prototype.getEngine=function(){return this._engine},Object.defineProperty(C.prototype,"source",{get:function(){return this._source},enumerable:!1,configurable:!0}),C.prototype.incrementReferences=function(){this._references++},C.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},C.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 x.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 C._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)}},C.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)},C.prototype.dispose=function(){this._webGLTexture&&(this._references--,this._references===0&&(this._engine._releaseTexture(this),this._webGLTexture=null))},C._UpdateRGBDAsync=function(m,c,T,A,S){throw M.a.WarnImport("environmentTextureTools")},C}()},function(Me,y,f){f.d(y,"b",function(){return U}),f.d(y,"c",function(){return _}),f.d(y,"a",function(){return x});var U=1/2.2,_=2.2,x=.001},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(1),_=f(0),x=f(3),u=f(6),M=f(22),R=f(21),C=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(x.c)()],m.prototype,"name",void 0),Object(U.c)([Object(x.c)()],m.prototype,"id",void 0),Object(U.c)([Object(x.c)()],m.prototype,"uniqueId",void 0),Object(U.c)([Object(x.c)()],m.prototype,"state",void 0),Object(U.c)([Object(x.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),x=f(33),u=f(20),M=f(0),R=f(9),C=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 x.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=[C.b.PositionKind];Q.NORMAL&&k.push(C.b.NormalKind),Q.UV1&&k.push(C.b.UVKind),Q.UV2&&k.push(C.b.UV2Kind),Q.VERTEXCOLOR&&k.push(C.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,C.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):[],C.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),x=f(0),u=f(31),M=f(7),R=f(50),C=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=x.e.Zero(),this._isDisposed=!1,this.soft=!1,this.segments=0,this._tmpQuat=new x.b,this._tmpQuat2=new x.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 x.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=x.b.RotationYawPitchRoll(this.object.rotation.y,this.object.rotation.x,this.object.rotation.z):this.object.rotationQuaternion=new x.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):x.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):x.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):x.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 x.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,C.c.WORLD,A)}else T.setRotationQuaternion(v.rotationQuaternion,C.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(C.c.WORLD,A,E),E.multiplyToRef(l,v.rotationQuaternion)}else T.getRotationQuaternionToRef(C.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 x.e(1,1,1),c.IDENTITY_QUATERNION=x.b.Identity(),c._tmpVecs=_.a.BuildArray(3,x.e.Zero),c._tmpQuat=x.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 x});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}(),x=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 C=0;C<R.length;C++){var m=(R.data||R)[C];this.pushNoDuplicate(m)}}},M}(_)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.EndsWith=function(x,u){return x.indexOf(u,x.length-u.length)!==-1},_.StartsWith=function(x,u){return!!x&&x.indexOf(u)===0},_.Decode=function(x){if(typeof TextDecoder<"u")return new TextDecoder().decode(x);for(var u="",M=0;M<x.byteLength;M++)u+=String.fromCharCode(x[M]);return u},_.EncodeArrayBufferToBase64=function(x){for(var u,M,R,C,m,c,T,A="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",S="",g=0,l=ArrayBuffer.isView(x)?new Uint8Array(x.buffer,x.byteOffset,x.byteLength):new Uint8Array(x);g<l.length;)C=(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(C)+A.charAt(m)+A.charAt(c)+A.charAt(T);return S},_.PadNumber=function(x,u){for(var M=String(x);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(x,u){this._BabylonFileParsers[x]=u},_.GetParser=function(x){return this._BabylonFileParsers[x]?this._BabylonFileParsers[x]:null},_.AddIndividualParser=function(x,u){this._IndividualBabylonFileParsers[x]=u},_.GetIndividualParser=function(x){return this._IndividualBabylonFileParsers[x]?this._IndividualBabylonFileParsers[x]:null},_.Parse=function(x,u,M,R){for(var C in this._BabylonFileParsers)this._BabylonFileParsers.hasOwnProperty(C)&&this._BabylonFileParsers[C](x,u,M,R)},Object.defineProperty(_.prototype,"environmentTexture",{get:function(){return this._environmentTexture},set:function(x){this._environmentTexture=x},enumerable:!1,configurable:!0}),_.prototype.getNodes=function(){var x=new Array;return x=(x=(x=(x=x.concat(this.meshes)).concat(this.lights)).concat(this.cameras)).concat(this.transformNodes),this.skeletons.forEach(function(u){return x=x.concat(u.bones)}),x},_._BabylonFileParsers={},_._IndividualBabylonFileParsers={},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(20),_=f(6),x=f(18),u=f(22),M=f(86),R=f(0),C=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===x.a.POINTERMOVE||g.type===x.a.POINTERUP||g.type===x.a.POINTERDOWN||g.type===x.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!=x.a.POINTERDOWN)return g.skipOnPointerObservable||S.utilityLayerScene.onPointerObservable.notifyObservers(new x.b(g.type,g.event,v),g.type),void(g.type===x.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 x.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===x.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===x.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=C.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 x.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 x(){}return x.EnableFor=function(u){u._tags=u._tags||{},u.hasTags=function(){return x.HasTags(u)},u.addTags=function(M){return x.AddTagsTo(u,M)},u.removeTags=function(M){return x.RemoveTagsFrom(u,M)},u.matchesTagsQuery=function(M){return x.MatchesQuery(u,M)}},x.DisableFor=function(u){delete u._tags,delete u.hasTags,delete u.addTags,delete u.removeTags,delete u.matchesTagsQuery},x.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},x.GetTags=function(u,M){if(M===void 0&&(M=!0),!u._tags)return null;if(M){var R=[];for(var C in u._tags)u._tags.hasOwnProperty(C)&&u._tags[C]===!0&&R.push(C);return R.join(" ")}return u._tags},x.AddTagsTo=function(u,M){M&&typeof M=="string"&&M.split(" 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U=f(44),_=f(0),x=f(54),u=f(114),M=f(20),R=f(24),C=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=C.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=C.Zero();return this.createPickingRayInCameraSpaceToRef(m,c,A,T),A},M.a.prototype.createPickingRayInCameraSpaceToRef=function(m,c,T,A){if(!x.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(!x.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 x.a},M.a.prototype._internalMultiPick=function(m,c,T){if(!x.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(!x.a)return null;var l=this._internalPick(function(h){return g._tempPickingRay||(g._tempPickingRay=C.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(!x.a)return null;var h=this._internalPick(function(v){return l._tempPickingRay||(l._tempPickingRay=C.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=C.Zero()),C.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=C.Zero()),C.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 C(_.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),x=f(16),u=f(98),M=f(4);x.a.CreateLineSystem=function(C){for(var m=[],c=[],T=C.lines,A=C.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 x.a;return D.indices=m,D.positions=c,A&&(D.colors=S),D},x.a.CreateDashedLines=function(C){var m,c,T=C.dashSize||3,A=C.gapSize||1,S=C.dashNb||200,g=C.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 x.a;return X.positions=l,X.indices=h,X},_.a.CreateLines=function(C,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(C,S,c)},_.a.CreateDashedLines=function(C,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(C,h,S)};var R=function(){function C(){}return C.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 x.a.CreateLineSystem(c).applyToMesh(X,c.updatable),X},C.CreateLines=function(m,c,T){T===void 0&&(T=null);var A=c.colors?[c.colors]:null;return C.CreateLineSystem(m,{lines:[c.points],updatable:c.updatable,instance:c.instance,colors:A,useVertexAlpha:c.useVertexAlpha},T)},C.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 x.a.CreateDashedLines(c).applyToMesh(h,c.updatable),h._creationDataStorage=new _.b,h._creationDataStorage.dashSize=l,h._creationDataStorage.gapSize=g,h},C}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(34),_=f(8),x=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,C,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(C[S]=[],g.length>0)if(typeof g[0]=="object")for(var h=0;h<g.length;h++){var v=x(g[h],C);C[S].indexOf(v)===-1&&C[S].push(v)}else C[S]=g.slice(0)}else C[S]=x(g,C);else 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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 x.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&&C.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&&C.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),x=f(2),u=f(103),M=f(113),R={min:0,max:0},C={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,C),!(R.min>C.max||C.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=x.a.MESHES_CULLINGSTRATEGY_STANDARD),!(g!==x.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION&&g!==x.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY||!this.boundingSphere.isCenterInFrustum(S))||!!this.boundingSphere.isInFrustum(S)&&(!(g!==x.a.MESHES_CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY&&g!==x.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(x,u){for(var M=[],R=0;R<x;++R)M.push(u());return M},_}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(0),_=f(7),x=f(16);x.a.CreateSphere=function(M){for(var R=M.segments||32,C=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||x.a.DEFAULTSIDE,g=!!M.dedupTopBottomIndices,l=new U.e(C/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))}x.a._ComputeSides(S,D,E,w,N,M.frontUVs,M.backUVs);var Q=new x.a;return Q.indices=E,Q.positions=D,Q.normals=w,Q.uvs=N,Q},_.a.CreateSphere=function(M,R,C,m,c,T){var A={segments:R,diameterX:C,diameterY:C,diameterZ:C,sideOrientation:T,updatable:c};return u.CreateSphere(M,A,m)};var u=function(){function M(){}return M.CreateSphere=function(R,C,m){m===void 0&&(m=null);var c=new _.a(R,m);return C.sideOrientation=_.a._GetDefaultSideOrientation(C.sideOrientation),c._originalBuilderSideOrientation=C.sideOrientation,x.a.CreateSphere(C).applyToMesh(c,C.updatable),c},M}()},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(1),_=f(3),x=f(6),u=f(0),M=f(29),R=f(23),C=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 x.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 _(x,u,M,R,C,m){this.source=x,this.pointerX=u,this.pointerY=M,this.meshUnderPointer=R,this.sourceEvent=C,this.additionalData=m}return _.CreateNew=function(x,u,M){var R=x.getScene();return new _(x,R.pointerX,R.pointerY,R.meshUnderPointer||x,u,M)},_.CreateNewFromSprite=function(x,u,M,R){return new _(x,u.pointerX,u.pointerY,u.meshUnderPointer,M,R)},_.CreateNewFromScene=function(x,u){return new _(null,x.pointerX,x.pointerY,x.meshUnderPointer,u)},_.CreateNewFromPrimitive=function(x,u,M,R){return new _(x,u.x,u.y,null,M,R)},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(1),_=f(3),x=f(0),u=f(9),M=f(29),R=f(85),C=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 x.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=C.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 x in _.CustomRequestHeaders){var u=_.CustomRequestHeaders[x];u&&this._xhr.setRequestHeader(x,u)}},Object.defineProperty(_.prototype,"onprogress",{get:function(){return this._xhr.onprogress},set:function(x){this._xhr.onprogress=x},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(x){this._xhr.responseType=x},enumerable:!1,configurable:!0}),_.prototype.addEventListener=function(x,u,M){this._xhr.addEventListener(x,u,M)},_.prototype.removeEventListener=function(x,u,M){this._xhr.removeEventListener(x,u,M)},_.prototype.abort=function(){this._xhr.abort()},_.prototype.send=function(x){_.CustomRequestHeaders&&this._injectCustomRequestHeaders(),this._xhr.send(x)},_.prototype.open=function(x,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(x,u,!0)},_.prototype.setRequestHeader=function(x,u){this._xhr.setRequestHeader(x,u)},_.prototype.getResponseHeader=function(x){return this._xhr.getResponseHeader(x)},_.CustomRequestHeaders={},_.CustomRequestModifiers=new Array,_}()},function(Me,y,f){f.d(y,"e",function(){return _}),f.d(y,"a",function(){return x}),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 C(m,c){this.type=m,this.jointData=c,c.nativeParams=c.nativeParams||{}}return Object.defineProperty(C.prototype,"physicsJoint",{get:function(){return this._physicsJoint},set:function(m){this._physicsJoint,this._physicsJoint=m},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"physicsPlugin",{set:function(m){this._physicsPlugin=m},enumerable:!1,configurable:!0}),C.prototype.executeNativeFunction=function(m){m(this._physicsPlugin.world,this._physicsJoint)},C.DistanceJoint=0,C.HingeJoint=1,C.BallAndSocketJoint=2,C.WheelJoint=3,C.SliderJoint=4,C.PrismaticJoint=5,C.UniversalJoint=6,C.Hinge2Joint=C.WheelJoint,C.PointToPointJoint=8,C.SpringJoint=9,C.LockJoint=10,C}(),x=function(C){function m(c){return C.call(this,_.DistanceJoint,c)||this}return 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U=f(0),_=f(7),x=f(36),u=f(18),M=function(){function R(C){var m=this;C===void 0&&(C=x.a.DefaultUtilityLayer),this.gizmoLayer=C,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",C.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),C._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 C,m,c=this._attachedNode;if(c.parent){var T=this._tempMatrix2;c.parent._worldMatrix.invertToRef(T),this._attachedNode._worldMatrix.multiplyToRef(T,this._tempMatrix1),C=this._tempMatrix1}else C=this._attachedNode._worldMatrix;if(c.getScene().useRightHandedSystem?(this._rightHandtoLeftHandMatrix.multiplyToRef(C,this._tempMatrix2),m=this._tempMatrix2):m=C,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(C,m){var c=!1;return C.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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this._texture?(this._texture._gammaSpace===null&&(this._texture._gammaSpace=this._gammaSpace),this._texture._gammaSpace):this._gammaSpace},set:function(S){if(this._texture){if(this._texture._gammaSpace===S)return;this._texture._gammaSpace=S}else{if(this._gammaSpace===S)return;this._gammaSpace=S}this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"isRGBD",{get:function(){return this._texture!=null&&this._texture._isRGBD},set:function(S){this._texture&&(this._texture._isRGBD=S)},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"noMipmap",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"lodGenerationOffset",{get:function(){return this._texture?this._texture._lodGenerationOffset:0},set:function(S){this._texture&&(this._texture._lodGenerationOffset=S)},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"lodGenerationScale",{get:function(){return 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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 C});var U=f(0),_=f(9),x=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||x.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,$=new Array,L=new 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me=D!==1&&v?g+4:g;for(te=0,q=0;q<l;q++){var _e=0,be=0,Pe=0,ye=0;for(de=0;de<g;de++)_e=te*(me+1)+de,be=(te+1)*(me+1)+de,Pe=te*(me+1)+(de+1),ye=(te+1)*(me+1)+(de+1),ae.push(_e,be,Pe),ae.push(ye,Pe,be);D!==1&&v&&(ae.push(_e+2,be+2,Pe+2),ae.push(ye+2,Pe+2,be+2),ae.push(_e+4,be+4,Pe+4),ae.push(ye+4,Pe+4,be+4)),te=h?te+2:te+1}var Be=function(We){var je=We?T/2:A/2;if(je!==0){var He,qe,Ge,nt=We?N[V-1]:N[0],$e=null;I&&($e=We?I[V-1]:I[0]);var ct=ee.length/3,st=We?c/2:-c/2,mt=new U.e(0,st,0);ee.push(mt.x,mt.y,mt.z),K.push(0,We?1:-1,0),$.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 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-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;
-}
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x._RemoveAndStorePivotPoint=function(u){u&&x._PivotCached===0&&(u.getPivotPointToRef(x._OldPivotPoint),x._PivotPostMultiplyPivotMatrix=u._postMultiplyPivotMatrix,x._OldPivotPoint.equalsToFloats(0,0,0)||(u.setPivotMatrix(U.a.IdentityReadOnly),x._OldPivotPoint.subtractToRef(u.getPivotPoint(),x._PivotTranslation),x._PivotTmpVector.copyFromFloats(1,1,1),x._PivotTmpVector.subtractInPlace(u.scaling),x._PivotTmpVector.multiplyInPlace(x._PivotTranslation),u.position.addInPlace(x._PivotTmpVector))),x._PivotCached++},x._RestorePivotPoint=function(u){u&&!x._OldPivotPoint.equalsToFloats(0,0,0)&&x._PivotCached===1&&(u.setPivotPoint(x._OldPivotPoint),u._postMultiplyPivotMatrix=x._PivotPostMultiplyPivotMatrix,x._PivotTmpVector.copyFromFloats(1,1,1),x._PivotTmpVector.subtractInPlace(u.scaling),x._PivotTmpVector.multiplyInPlace(x._PivotTranslation),u.position.subtractInPlace(x._PivotTmpVector)),this._PivotCached--},x._PivotCached=0,x._OldPivotPoint=new U.e,x._PivotTranslation=new U.e,x._PivotTmpVector=new U.e,x._PivotPostMultiplyPivotMatrix=!1,x}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(4),_=f(114),x=f(43),u=f(2),M=f(101),R=function(){function C(m,c,T,A,S,g,l,h,v){h===void 0&&(h=!0),v===void 0&&(v=!0),this.materialIndex=m,this.verticesStart=c,this.verticesCount=T,this.indexStart=A,this.indexCount=S,this._materialDefines=null,this._materialEffect=null,this._effectOverride=null,this._linesIndexCount=0,this._linesIndexBuffer=null,this._lastColliderWorldVertices=null,this._lastColliderTransformMatrix=null,this._renderId=0,this._alphaIndex=0,this._distanceToCamera=0,this._currentMaterial=null,this._mesh=g,this._renderingMesh=l||g,v&&g.subMeshes.push(this),this._trianglePlanes=[],this._id=g.subMeshes.length-1,h&&(this.refreshBoundingInfo(),g.computeWorldMatrix(!0))}return Object.defineProperty(C.prototype,"materialDefines",{get:function(){return this._materialDefines},set:function(m){this._materialDefines=m},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"effect",{get:function(){var m;return(m=this._effectOverride)!==null&&m!==void 0?m:this._materialEffect},enumerable:!1,configurable:!0}),C.prototype.setEffect=function(m,c){c===void 0&&(c=null),this._materialEffect!==m?(this._materialDefines=c,this._materialEffect=m):m||(this._materialDefines=null)},C.AddToMesh=function(m,c,T,A,S,g,l,h){return h===void 0&&(h=!0),new C(m,c,T,A,S,g,l,h)},Object.defineProperty(C.prototype,"IsGlobal",{get:function(){return this.verticesStart===0&&this.verticesCount===this._mesh.getTotalVertices()},enumerable:!1,configurable:!0}),C.prototype.getBoundingInfo=function(){return this.IsGlobal?this._mesh.getBoundingInfo():this._boundingInfo},C.prototype.setBoundingInfo=function(m){return this._boundingInfo=m,this},C.prototype.getMesh=function(){return this._mesh},C.prototype.getRenderingMesh=function(){return this._renderingMesh},C.prototype.getReplacementMesh=function(){return this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null},C.prototype.getEffectiveMesh=function(){var m=this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null;return m||this._renderingMesh},C.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},C.prototype._IsMultiMaterial=function(m){return m.getSubMaterial!==void 0},C.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 x.a(c.minimum,c.maximum),this},C.prototype._checkCollision=function(m){return this.getBoundingInfo()._checkCollision(m)},C.prototype.updateBoundingInfo=function(m){var c=this.getBoundingInfo();return c||(this.refreshBoundingInfo(),c=this.getBoundingInfo()),c&&c.update(m),this},C.prototype.isInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isInFrustum(m,this._mesh.cullingStrategy)},C.prototype.isCompletelyInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isCompletelyInFrustum(m)},C.prototype.render=function(m){return this._renderingMesh.render(this,m,this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:void 0),this},C.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},C.prototype.canIntersects=function(m){var c=this.getBoundingInfo();return!!c&&m.intersectsBox(c.boundingBox)},C.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)},C.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},C.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},C.prototype._intersectTriangles=function(m,c,T,A,S,g,l){for(var h=null,v=-1,E=this.indexStart;E<this.indexStart+this.indexCount;E+=A){v++;var D=T[E],w=T[E+1],N=T[E+2];if(S&&N===4294967295)E+=2;else{var I=c[D],V=c[w],X=c[N];if(!l||l(I,V,X,m)){var j=m.intersectsTriangle(I,V,X);if(j){if(j.distance<0)continue;if((g||!h||j.distance<h.distance)&&((h=j).faceId=v,g))break}}}}return h},C.prototype._intersectUnIndexedTriangles=function(m,c,T,A,S){for(var g=null,l=this.verticesStart;l<this.verticesStart+this.verticesCount;l+=3){var h=c[l],v=c[l+1],E=c[l+2];if(!S||S(h,v,E,m)){var D=m.intersectsTriangle(h,v,E);if(D){if(D.distance<0)continue;if((A||!g||D.distance<g.distance)&&((g=D).faceId=l/3,A))break}}}return g},C.prototype._rebuild=function(){this._linesIndexBuffer&&(this._linesIndexBuffer=null)},C.prototype.clone=function(m,c){var T=new C(this.materialIndex,this.verticesStart,this.verticesCount,this.indexStart,this.indexCount,m,c,!1);if(!this.IsGlobal){var A=this.getBoundingInfo();if(!A)return T;T._boundingInfo=new x.a(A.minimum,A.maximum)}return 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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];C=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,C,m,c,T,R.frontUVs,R.backUVs);var $=new u.a;if($.indices=m,$.positions=C,$.normals=c,$.uvs=T,de){var 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U.e.Dot(u,this.normal)+this.d},x.FromArray=function(u){return new x(u[0],u[1],u[2],u[3])},x.FromPoints=function(u,M,R){var C=new x(0,0,0,0);return C.copyFromPoints(u,M,R),C},x.FromPositionAndNormal=function(u,M){var R=new x(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},x.SignedDistanceToPlaneFromPositionAndNormal=function(u,M,R){var C=-(M.x*u.x+M.y*u.y+M.z*u.z);return U.e.Dot(R,M)+C},x._TmpMatrix=U.a.Identity(),x}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(7),_=f(20),x=f(6),u=f(0),M=f(18),R=f(39),C=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 x.c,this.onDragStartObservable=new x.c,this.onDragEndObservable=new 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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&&(C.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),C.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){C.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)),C.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 x}),f.d(y,"c",function(){return u});var U=f(1),_=function(){function M(){}return M.KEYDOWN=1,M.KEYUP=2,M}(),x=function(M,R){this.type=M,this.event=R},u=function(M){function R(C,m){var c=M.call(this,C,m)||this;return c.type=C,c.event=m,c.skipOnPointerObservable=!1,c}return Object(U.d)(R,M),R}(x)},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(x,u){this._defines[x]||(x<this._currentRank&&(this._currentRank=x),x>this._maxRank&&(this._maxRank=x),this._defines[x]=new Array),this._defines[x].push(u)},_.prototype.addCPUSkinningFallback=function(x,u){this._mesh=u,x<this._currentRank&&(this._currentRank=x),x>this._maxRank&&(this._maxRank=x)},Object.defineProperty(_.prototype,"hasMoreFallbacks",{get:function(){return this._currentRank<=this._maxRank},enumerable:!1,configurable:!0}),_.prototype.reduce=function(x,u){if(this._mesh&&this._mesh.computeBonesUsingShaders&&this._mesh.numBoneInfluencers>0){this._mesh.computeBonesUsingShaders=!1,x=x.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 C=M.meshes[R];if(C.material){if(C.computeBonesUsingShaders&&C.numBoneInfluencers!==0){if(C.material.getEffect()===u)C.computeBonesUsingShaders=!1;else if(C.subMeshes){for(var m=0,c=C.subMeshes;m<c.length;m++)if(c[m].effect===u){C.computeBonesUsingShaders=!1;break}}}}else!this._mesh.material&&C.computeBonesUsingShaders&&C.numBoneInfluencers>0&&(C.computeBonesUsingShaders=!1)}}else{var T=this._defines[this._currentRank];if(T)for(R=0;R<T.length;R++)x=x.replace("#define "+T[R],"");this._currentRank++}return x},_}()},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(1),_=f(25),x=f(37),u=f(11),M=function(R){function C(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)(C,R),Object.defineProperty(C.prototype,"subMaterials",{get:function(){return this._subMaterials},set:function(m){this._subMaterials=m,this._hookArray(m)},enumerable:!1,configurable:!0}),C.prototype.getChildren=function(){return this.subMaterials},C.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}},C.prototype.getSubMaterial=function(m){return m<0||m>=this.subMaterials.length?this.getScene().defaultMaterial:this.subMaterials[m]},C.prototype.getActiveTextures=function(){var m;return(m=R.prototype.getActiveTextures.call(this)).concat.apply(m,this.subMaterials.map(function(c){return c?c.getActiveTextures():[]}))},C.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},C.prototype.getClassName=function(){return"MultiMaterial"},C.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},C.prototype.clone=function(m,c){for(var T=new C(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},C.prototype.serialize=function(){var m={};m.name=this.name,m.id=this.id,x.a&&(m.tags=x.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},C.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)}},C.ParseMultiMaterial=function(m,c){var T=new C(m.name,c);T.id=m.id,x.a&&x.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},C}(_.a);u.a.RegisteredTypes["BABYLON.MultiMaterial"]=M},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){}return Object.defineProperty(x,"ForceFullSceneLoadingForIncremental",{get:function(){return x._ForceFullSceneLoadingForIncremental},set:function(u){x._ForceFullSceneLoadingForIncremental=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"ShowLoadingScreen",{get:function(){return x._ShowLoadingScreen},set:function(u){x._ShowLoadingScreen=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"loggingLevel",{get:function(){return x._loggingLevel},set:function(u){x._loggingLevel=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"CleanBoneMatrixWeights",{get:function(){return x._CleanBoneMatrixWeights},set:function(u){x._CleanBoneMatrixWeights=u},enumerable:!1,configurable:!0}),x._ForceFullSceneLoadingForIncremental=!1,x._ShowLoadingScreen=!0,x._CleanBoneMatrixWeights=!1,x._loggingLevel=U.a.SCENELOADER_NO_LOGGING,x}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.CreateCanvas=function(x,u){if(typeof document>"u")return new OffscreenCanvas(x,u);var M=document.createElement("canvas");return M.width=x,M.height=u,M},_}()},function(Me,y,f){f.d(y,"a",function(){return S});var U=f(0),_=f(9),x=f(16),u=f(4),M=f(61),R=f(69),C=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 C.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 C.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 C.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 x.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 C.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 C.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=x.a.ImportVertexData):x.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 C}),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),x=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}(),C=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 x.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 x.d(S,g))}return A.prototype.addLineTo=function(S,g){if(this.closed)return this;var l=new x.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 x.d(S,g),w=new x.d(l,h),N=new C(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 x.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 x.d(E.x+N.x*I,E.y+N.y*I)}l=w}return x.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:x.e.Zero(),previousPointArrayIndex:0,position:0,subPosition:0,interpolateReady:!1,interpolationMatrix:x.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?x.e.TransformCoordinates(x.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?x.e.TransformCoordinates(x.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?x.e.TransformCoordinates(x.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(x.e.Dot(E,S.subtract(v).normalize()),0)*x.e.Distance(v,S)/D,1),N=x.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]=x.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]=x.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]=x.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)?x.e.Zero():new x.e(0,0,1):new x.e(1,0,0):new x.e(0,-1,0),l=x.e.Cross(S,h)):(l=x.e.Cross(S,g),x.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=x.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=x.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=x.b.RotationQuaternionFromAxis(h,v,l),I=x.b.RotationQuaternionFromAxis(D,w,E);x.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 x.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 x.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(x.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(x.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(x.e.CatmullRom(I[w],I[w+1],I[w+2],I[w+3],E)),E+=v;w--,h.push(x.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),x=f(0),u=f(4),M=f(10),R=f(15),C=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 x.a,I._cachedWorldViewProjectionMatrix=new x.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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Object.defineProperty(x.prototype,"useUbo",{get:function(){return!this._noUBO},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"isSync",{get:function(){return!this._needSync},enumerable:!1,configurable:!0}),x.prototype.isDynamic=function(){return this._dynamic!==void 0},x.prototype.getData=function(){return this._bufferData},x.prototype.getBuffer=function(){return this._buffer},x.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 C=this._uniformLocationPointer-R,m=0;m<C;m++)this._data.push(0)}},x.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 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0&&(C=""),this._currentEffect.setFloat2(u+C,M,R)},x.prototype._updateFloat2ForUniform=function(u,M,R){x._tempBuffer[0]=M,x._tempBuffer[1]=R,this.updateUniform(u,x._tempBuffer,2)},x.prototype._updateFloat3ForEffect=function(u,M,R,C,m){m===void 0&&(m=""),this._currentEffect.setFloat3(u+m,M,R,C)},x.prototype._updateFloat3ForUniform=function(u,M,R,C){x._tempBuffer[0]=M,x._tempBuffer[1]=R,x._tempBuffer[2]=C,this.updateUniform(u,x._tempBuffer,3)},x.prototype._updateFloat4ForEffect=function(u,M,R,C,m,c){c===void 0&&(c=""),this._currentEffect.setFloat4(u+c,M,R,C,m)},x.prototype._updateFloat4ForUniform=function(u,M,R,C,m){x._tempBuffer[0]=M,x._tempBuffer[1]=R,x._tempBuffer[2]=C,x._tempBuffer[3]=m,this.updateUniform(u,x._tempBuffer,4)},x.prototype._updateMatrixForEffect=function(u,M){this._currentEffect.setMatrix(u,M)},x.prototype._updateMatrixForUniform=function(u,M){this._cacheMatrix(u,M)&&this.updateUniform(u,M.toArray(),16)},x.prototype._updateVector3ForEffect=function(u,M){this._currentEffect.setVector3(u,M)},x.prototype._updateVector3ForUniform=function(u,M){M.toArray(x._tempBuffer),this.updateUniform(u,x._tempBuffer,3)},x.prototype._updateVector4ForEffect=function(u,M){this._currentEffect.setVector4(u,M)},x.prototype._updateVector4ForUniform=function(u,M){M.toArray(x._tempBuffer),this.updateUniform(u,x._tempBuffer,4)},x.prototype._updateColor3ForEffect=function(u,M,R){R===void 0&&(R=""),this._currentEffect.setColor3(u+R,M)},x.prototype._updateColor3ForUniform=function(u,M){M.toArray(x._tempBuffer),this.updateUniform(u,x._tempBuffer,3)},x.prototype._updateColor4ForEffect=function(u,M,R,C){C===void 0&&(C=""),this._currentEffect.setColor4(u+C,M,R)},x.prototype._updateColor4ForUniform=function(u,M,R){M.toArray(x._tempBuffer),x._tempBuffer[3]=R,this.updateUniform(u,x._tempBuffer,4)},x.prototype.setTexture=function(u,M){this._currentEffect.setTexture(u,M)},x.prototype.updateUniformDirectly=function(u,M){this.updateUniform(u,M,M.length),this.update()},x.prototype.bindToEffect=function(u,M){this._currentEffect=u,!this._noUBO&&this._buffer&&(this._alreadyBound=!0,u.bindUniformBuffer(this._buffer,M))},x.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)}},x._MAX_UNIFORM_SIZE=256,x._tempBuffer=new 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null},c.prototype.transferToEffect=function(T,A){var S=x.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=x.e.Normalize(this.direction);return T.setFloat3(A,S.x,S.y,S.z),this},c.prototype.computeWorldMatrix=function(){return this._worldMatrix||(this._worldMatrix=x.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 x});var U=f(1),_=f(0),x=function(u){function M(R,C){var m=u.call(this,R,C)||this;return m._normalMatrix=new _.a,m._storeEffectOnSubMeshes=!0,m}return 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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()},x.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()},x.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()},x.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()},x.GetPlanesToRef=function(u,M){x.GetNearPlaneToRef(u,M[0]),x.GetFarPlaneToRef(u,M[1]),x.GetLeftPlaneToRef(u,M[2]),x.GetRightPlaneToRef(u,M[3]),x.GetTopPlaneToRef(u,M[4]),x.GetBottomPlaneToRef(u,M[5])},x}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){this.hoverCursor="",this.actions=new Array,this.isRecursive=!1}return Object.defineProperty(x,"HasTriggers",{get:function(){for(var u in x.Triggers)if(x.Triggers.hasOwnProperty(u))return!0;return!1},enumerable:!1,configurable:!0}),Object.defineProperty(x,"HasPickTriggers",{get:function(){for(var u in x.Triggers)if(x.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}),x.HasSpecificTrigger=function(u){for(var M in x.Triggers)if(x.Triggers.hasOwnProperty(M)&&parseInt(M)===u)return!0;return!1},x.Triggers={},x}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(1),_=f(25),x=f(3),u=f(19),M=f(15),R=function(){function C(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 C.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},C.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())},C.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},C.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))},C.prototype.hasTexture=function(m){return this._texture===m},C.prototype.getActiveTextures=function(m){this._texture&&m.push(this._texture)},C.prototype.getAnimatables=function(m){this._texture&&this._texture.animations&&this._texture.animations.length>0&&m.push(this._texture)},C.prototype.dispose=function(m){var c;m&&((c=this._texture)===null||c===void 0||c.dispose())},C.prototype.getClassName=function(){return"DetailMap"},C.AddUniforms=function(m){m.push("vDetailInfos")},C.AddSamplers=function(m){m.push("detailSampler")},C.PrepareUniformBuffer=function(m){m.addUniform("vDetailInfos",4),m.addUniform("detailMatrix",16)},C.prototype.copyTo=function(m){x.a.Clone(function(){return m},this)},C.prototype.serialize=function(){return x.a.Serialize(this)},C.prototype.parse=function(m,c,T){var A=this;x.a.Parse(function(){return A},m,c,T)},Object(U.c)([Object(x.m)("detailTexture"),Object(x.b)("_markAllSubMeshesAsTexturesDirty")],C.prototype,"texture",void 0),Object(U.c)([Object(x.c)()],C.prototype,"diffuseBlendLevel",void 0),Object(U.c)([Object(x.c)()],C.prototype,"roughnessBlendLevel",void 0),Object(U.c)([Object(x.c)()],C.prototype,"bumpLevel",void 0),Object(U.c)([Object(x.c)(),Object(x.b)("_markAllSubMeshesAsTexturesDirty")],C.prototype,"normalBlendMethod",void 0),Object(U.c)([Object(x.c)(),Object(x.b)("_markAllSubMeshesAsTexturesDirty")],C.prototype,"isEnabled",void 0),C}()},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
-attribute vec3 tangent{X};
-#endif
-#ifdef MORPHTARGETS_UV
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-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(25),_=f(4),x=f(2),u=function(){function M(R){this._vertexBuffers={},this._scene=R}return M.prototype._prepareBuffers=function(){if(!this._vertexBuffers[_.b.PositionKind]){var R=[];R.push(1,1),R.push(-1,1),R.push(-1,-1),R.push(1,-1),this._vertexBuffers[_.b.PositionKind]=new _.b(this._scene.getEngine(),R,_.b.PositionKind,!1,!1,2),this._buildIndexBuffer()}},M.prototype._buildIndexBuffer=function(){var R=[];R.push(0),R.push(1),R.push(2),R.push(0),R.push(2),R.push(3),this._indexBuffer=this._scene.getEngine().createIndexBuffer(R)},M.prototype._rebuild=function(){var R=this._vertexBuffers[_.b.PositionKind];R&&(R._rebuild(),this._buildIndexBuffer())},M.prototype._prepareFrame=function(R,C){R===void 0&&(R=null),C===void 0&&(C=null);var m=this._scene.activeCamera;return!!m&&!(!(C=C||m._postProcesses.filter(function(c){return c!=null}))||C.length===0||!this._scene.postProcessesEnabled)&&(C[0].activate(m,R,C!=null),!0)},M.prototype.directRender=function(R,C,m,c,T,A){C===void 0&&(C=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,C):C?S.bindFramebuffer(C,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,C,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,C):C?(S.bindFramebuffer(C,m,void 0,void 0,T),h._outputTexture=C):(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(x.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 x});var U=f(148),_=function(){},x=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,C,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,C,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,C){R===void 0&&(R=M.getMesh());var m=R.renderingGroupId||0;this._prepareRenderingGroup(m),this._renderingGroups[m].dispatch(M,R,C)},u.prototype.setRenderingOrder=function(M,R,C,m){if(R===void 0&&(R=null),C===void 0&&(C=null),m===void 0&&(m=null),this._customOpaqueSortCompareFn[M]=R,this._customAlphaTestSortCompareFn[M]=C,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,C,m){C===void 0&&(C=!0),m===void 0&&(m=!0),this._autoClearDepthStencil[M]={autoClear:R,depth:C,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),x=f(82),u=f(72);_.a.ExtrudeShape=function(R,C,m,c,T,A,S,g,l,h){S===void 0&&(S=null);var v={shape:C,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,C,m,c,T,A,S,g,l,h,v,E){var D={shape:C,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(C,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(C,A,T,S,g,null,null,!1,!1,l,!1,c,!!h,v,E,D,m.frontUVs||null,m.backUVs||null)},R.ExtrudeShapeCustom=function(C,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(C,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(C,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(),ct=U.e.Zero();for(nt=0;nt<Ge.length;nt++)ct.addInPlace(Ge[nt]);for(ct.scaleInPlace(1/Ge.length),nt=0;nt<Ge.length;nt++)$e.push(ct);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=x.a.CreateRibbon(C,{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),x=f(4),u=f(7),M=f(151),R=f(25),C=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:[x.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(x.b.ColorKind)):(I.uniforms.push("color"),N.color4=new _.b),N._colorShader=new C.a("colorShader",N.getScene(),"color",I),N}return Object(U.d)(S,A),S.prototype._addClipPlaneDefine=function(g){var l="#define 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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),x=f(30),u=f(75),M=f(9),R=function(){function $(L,G,Q,oe,re,Y){if(G===void 0&&(G=1),Q===void 0&&(Q=2),this._scaleLinesFactor=4,this._instanced=!1,this.scene=null,this.scaleLines=1,this.scaleLines=G,!oe){var k=new x.a("",L);k.disableLighting=!0,k.emissiveColor=M.a.Red().scale(.5),oe=u.a._CreateArrow(L,k)}if(!re){var H=new x.a("",L);H.disableLighting=!0,H.emissiveColor=M.a.Green().scale(.5),re=u.a._CreateArrow(L,H)}if(!Y){var Z=new x.a("",L);Z.disableLighting=!0,Z.emissiveColor=M.a.Blue().scale(.5),Y=u.a._CreateArrow(L,Z)}this._xAxis=oe,this._xAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._yAxis=re,this._yAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._zAxis=Y,this._zAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),Q!=null&&($._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},$._SetRenderingGroupId=function(L,G){L.getChildMeshes().forEach(function(Q){Q.renderingGroupId=G})},$}(),C=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(C.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}),$.prototype._createInspector=function(L){if(!this.isVisible()){if(this._onPropertyChangedObservable){for(var G=0,Q=this._onPropertyChangedObservable.observers;G<Q.length;G++){var oe=Q[G];this.BJSINSPECTOR.Inspector.OnPropertyChangedObservable.add(oe)}this._onPropertyChangedObservable.clear(),this._onPropertyChangedObservable=void 0}var re=Object(C.a)({overlay:!1,showExplorer:!0,showInspector:!0,embedMode:!1,handleResize:!0,enablePopup:!0},L);this.BJSINSPECTOR=this.BJSINSPECTOR||this._getGlobalInspector(),this.BJSINSPECTOR.Inspector.Show(this._scene,re)}},$.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 x.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,Cn=W.midStepFactor||.215,Ue=Pn.scale(nn),xn=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*Cn}return 0},sideOrientation:h.a.DEFAULTSIDE,updatable:!1},oe),dr=xn.getTotalVertices(),Xe=[],An=[],ti=0;ti<dr;ti++)Xe.push(1,0,0,0),W.spurFollowsChild&&ti>9?An.push(It.getIndex(),0,0,0):An.push(qe.getIndex(),0,0,0);xn.position=nt.clone(),xn.setVerticesData(pe.b.MatricesWeightsKind,Xe,!1),xn.setVerticesData(pe.b.MatricesIndicesKind,An,!1),xn.convertToFlatShadedMesh(),k.push(xn)}});for(var $e=W.sphereBaseSize||.2,ct=E.a.CreateSphere("skeletonViewer",{segments:6,diameter:$e,updatable:!0},oe),st=ct.getTotalVertices(),mt=[],St=[],wt=0;wt<st;wt++)mt.push(1,0,0,0),St.push(qe.getIndex(),0,0,0);ct.setVerticesData(pe.b.MatricesWeightsKind,mt,!1),ct.setVerticesData(pe.b.MatricesIndicesKind,St,!1),ct.position=nt.clone(),Y.push([ct,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 x});var U=f(0);function _(u,M,R,C,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+C;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 x(u,M,R,C,m){C===void 0&&(C=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 C&&(c.x-=c.x*C.x+C.y,c.y-=c.y*C.x+C.y,c.z-=c.z*C.x+C.y,T.x+=T.x*C.x+C.y,T.y+=T.y*C.x+C.y,T.z+=T.z*C.x+C.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),x=f(28),u=function(){function M(R,C,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,C,m)}return M.prototype.reConstruct=function(R,C,m){var c=R.x,T=R.y,A=R.z,S=C.x,g=C.y,l=C.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),C.addToRef(R,this.center).scaleInPlace(.5),C.subtractToRef(R,this.extendSize).scaleInPlace(.5),this._worldMatrix=m||_.a.IdentityReadOnly,this._update(this._worldMatrix)},M.prototype.scale=function(R){var C=M.TmpVector3,m=this.maximum.subtractToRef(this.minimum,C[0]),c=m.length();m.normalizeFromLength(c);var T=c*R,A=m.scaleInPlace(.5*T),S=this.center.subtractToRef(A,C[1]),g=this.center.addToRef(A,C[2]);return this.reConstruct(S,g,this._worldMatrix),this},M.prototype.getWorldMatrix=function(){return this._worldMatrix},M.prototype._update=function(R){var C=this.minimumWorld,m=this.maximumWorld,c=this.directions,T=this.vectorsWorld,A=this.vectors;if(R.isIdentity()){for(C.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{C.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),C.minimizeInPlace(g),m.maximizeInPlace(g)}m.subtractToRef(C,this.extendSizeWorld).scaleInPlace(.5),m.addToRef(C,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 C=this.minimumWorld,m=this.maximumWorld,c=C.x,T=C.y,A=C.z,S=m.x,g=m.y,l=m.z,h=R.x,v=R.y,E=R.z,D=-x.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,C){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=C.x,N=C.y,I=C.z;return!(g<v||T>w)&&!(l<E||A>N)&&!(h<D||S>I)},M.Intersects=function(R,C){return R.intersectsMinMax(C.minimumWorld,C.maximumWorld)},M.IntersectsSphere=function(R,C,m,c){var T=M.TmpVector3[0];return _.e.ClampToRef(m,R,C,T),_.e.DistanceSquared(m,T)<=c*c},M.IsCompletelyInFrustum=function(R,C){for(var m=0;m<6;++m)for(var c=C[m],T=0;T<8;++T)if(c.dotCoordinate(R[T])<0)return!1;return!0},M.IsInFrustum=function(R,C){for(var m=0;m<6;++m){for(var c=!0,T=C[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 x(){}return x.SetImmediate=function(u){U.a.IsWindowObjectExist()&&window.setImmediate?window.setImmediate(u):setTimeout(u,1)},x}()},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(0),_=f(2),x=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,C,m,c){R.prePassRenderer&&R.prePassRenderer.enabled&&R.prePassRenderer.getIndex(_.a.PREPASS_VELOCITY_TEXTURE_TYPE)!==-1&&(this.previousWorldMatrices[C.uniqueId]||(this.previousWorldMatrices[C.uniqueId]=U.a.Identity()),this.previousViewProjection||(this.previousViewProjection=R.getTransformMatrix()),M.setMatrix("previousWorld",this.previousWorldMatrices[C.uniqueId]),M.setMatrix("previousViewProjection",this.previousViewProjection),this.previousWorldMatrices[C.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}];
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s={};de.a.DeepCopy(a.parameter,s,["mesh"]),a.parameter&&a.parameter.mesh&&(s._meshId=a.parameter.mesh.id),o.properties.push({name:"parameter",targetType:null,value:s})}this.actions[i].serialize(o),n.children.push(o)}return n},t.Parse=function(e,n,i){var o=new t(i);n===null?i.actionManager=o:n.actionManager=o;for(var a=function(F,z,J,ie){if(ie===null){var se=parseFloat(z);return z==="true"||z==="false"?z==="true":isNaN(se)?z:se}for(var ce=ie.split("."),ue=z.split(","),fe=0;fe<ce.length;fe++)J=J[ce[fe]];if(typeof J=="boolean")return ue[0]==="true";if(typeof J=="string")return ue[0];var ve=new Array;for(fe=0;fe<ue.length;fe++)ve.push(parseFloat(ue[fe]));return J instanceof u.e?u.e.FromArray(ve):J instanceof u.f?u.f.FromArray(ve):J instanceof M.a?M.a.FromArray(ve):J instanceof M.b?M.b.FromArray(ve):parseFloat(ue[0])},s=function(F,z,J,ie,se){if(se===void 0&&(se=null),!F.detached){var ce=new 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instanceof T?(J=Ne,Ne=ie):(J=null,ie?ie.then(Ne):o.registerAction(Ne)):se.push(Ne),Ae=0;Ae<F.children.length;Ae++)s(F.children[Ae],z,J,Ne,null)}},d=0;d<e.children.length;d++){var p,b=e.children[d];if(b.properties.length>0){var P=b.properties[0].value,O=b.properties[0].targetType===null?P:i.getMeshByName(P);O._meshId&&(O.mesh=i.getMeshByID(O._meshId)),p={trigger:t[b.name],parameter:O}}else p=t[b.name];for(var B=0;B<b.children.length;B++)b.detached||s(b.children[B],p,null,null)}},t.GetTriggerName=function(e){switch(e){case 0:return"NothingTrigger";case 1:return"OnPickTrigger";case 2:return"OnLeftPickTrigger";case 3:return"OnRightPickTrigger";case 4:return"OnCenterPickTrigger";case 5:return"OnPickDownTrigger";case 6:return"OnPickUpTrigger";case 7:return"OnLongPressTrigger";case 8:return"OnPointerOverTrigger";case 9:return"OnPointerOutTrigger";case 10:return"OnEveryFrameTrigger";case 11:return"OnIntersectionEnterTrigger";case 12:return"OnIntersectionExitTrigger";case 13:return"OnKeyDownTrigger";case 14:return"OnKeyUpTrigger";case 15:return"OnPickOutTrigger";default:return""}},t.NothingTrigger=h.a.ACTION_NothingTrigger,t.OnPickTrigger=h.a.ACTION_OnPickTrigger,t.OnLeftPickTrigger=h.a.ACTION_OnLeftPickTrigger,t.OnRightPickTrigger=h.a.ACTION_OnRightPickTrigger,t.OnCenterPickTrigger=h.a.ACTION_OnCenterPickTrigger,t.OnPickDownTrigger=h.a.ACTION_OnPickDownTrigger,t.OnDoublePickTrigger=h.a.ACTION_OnDoublePickTrigger,t.OnPickUpTrigger=h.a.ACTION_OnPickUpTrigger,t.OnPickOutTrigger=h.a.ACTION_OnPickOutTrigger,t.OnLongPressTrigger=h.a.ACTION_OnLongPressTrigger,t.OnPointerOverTrigger=h.a.ACTION_OnPointerOverTrigger,t.OnPointerOutTrigger=h.a.ACTION_OnPointerOutTrigger,t.OnEveryFrameTrigger=h.a.ACTION_OnEveryFrameTrigger,t.OnIntersectionEnterTrigger=h.a.ACTION_OnIntersectionEnterTrigger,t.OnIntersectionExitTrigger=h.a.ACTION_OnIntersectionExitTrigger,t.OnKeyDownTrigger=h.a.ACTION_OnKeyDownTrigger,t.OnKeyUpTrigger=15,t}(_.a),ae=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._sound=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._sound!==void 0&&this._sound.play()},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"PlaySoundAction",properties:[{name:"sound",value:this._sound.name}]},e)},t}(C),ee=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._sound=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._sound!==void 0&&this._sound.stop()},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"StopSoundAction",properties:[{name:"sound",value:this._sound.name}]},e)},t}(C);R.a.RegisteredTypes["BABYLON.PlaySoundAction"]=ee,R.a.RegisteredTypes["BABYLON.StopSoundAction"]=ee;var K,$=f(14),L=f(3);(function(r){r[r.STEP=1]="STEP"})(K||(K={}));var G=function(){function r(t,e,n){this.name=t,this.from=e,this.to=n}return r.prototype.clone=function(){return new r(this.name,this.from,this.to)},r}(),Q=f(29),oe=f(77),re=f(49),Y=function(){},k=function(){function r(t,e,n,i,o,a){this.name=t,this.targetProperty=e,this.framePerSecond=n,this.dataType=i,this.loopMode=o,this.enableBlending=a,this._runtimeAnimations=new Array,this._events=new Array,this.blendingSpeed=.01,this._ranges={},this.targetPropertyPath=e.split("."),this.dataType=i,this.loopMode=o===void 0?r.ANIMATIONLOOPMODE_CYCLE:o}return r._PrepareAnimation=function(t,e,n,i,o,a,s,d){var p=void 0;if(!isNaN(parseFloat(o))&&isFinite(o)?p=r.ANIMATIONTYPE_FLOAT:o instanceof u.b?p=r.ANIMATIONTYPE_QUATERNION:o instanceof u.e?p=r.ANIMATIONTYPE_VECTOR3:o instanceof u.d?p=r.ANIMATIONTYPE_VECTOR2:o instanceof M.a?p=r.ANIMATIONTYPE_COLOR3:o instanceof M.b?p=r.ANIMATIONTYPE_COLOR4:o instanceof oe.a&&(p=r.ANIMATIONTYPE_SIZE),p==null)return null;var b=new r(t,e,n,p,s),P=[{frame:0,value:o},{frame:i,value:a}];return b.setKeys(P),d!==void 0&&b.setEasingFunction(d),b},r.CreateAnimation=function(t,e,n,i){var 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 s=0,d=a._keys[0],p=a._keys.length-1,b=a._keys[p],P={referenceValue:d.value,referencePosition:u.c.Vector3[0],referenceQuaternion:u.c.Quaternion[0],referenceScaling:u.c.Vector3[1],keyPosition:u.c.Vector3[2],keyQuaternion:u.c.Quaternion[1],keyScaling:u.c.Vector3[3]},O=!1,B=d.frame,F=b.frame;if(n){var z=a.getRange(n);z&&(B=z.from,F=z.to)}var J=d.frame===B,ie=b.frame===F;if(a._keys.length===1){var se=a._getKeyValue(a._keys[0]);P.referenceValue=se.clone?se.clone():se,O=!0}else e<=d.frame?(se=a._getKeyValue(d.value),P.referenceValue=se.clone?se.clone():se,O=!0):e>=b.frame&&(se=a._getKeyValue(b.value),P.referenceValue=se.clone?se.clone():se,O=!0);for(var ce=0;!O||!J||!ie&&ce<a._keys.length-1;){var ue=a._keys[ce],fe=a._keys[ce+1];if(!O&&e>=ue.frame&&e<=fe.frame){if(se=void 0,e===ue.frame)se=a._getKeyValue(ue.value);else if(e===fe.frame)se=a._getKeyValue(fe.value);else{var ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT};se=a._interpolate(e,ve)}P.referenceValue=se.clone?se.clone():se,O=!0}if(!J&&B>=ue.frame&&B<=fe.frame){if(B===ue.frame)s=ce;else if(B===fe.frame)s=ce+1;else{ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT};var Te={frame:B,value:(se=a._interpolate(B,ve)).clone?se.clone():se};a._keys.splice(ce+1,0,Te),s=ce+1}J=!0}!ie&&F>=ue.frame&&F<=fe.frame&&(F===ue.frame?p=ce:F===fe.frame?p=ce+1:(ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT},Te={frame:F,value:(se=a._interpolate(F,ve)).clone?se.clone():se},a._keys.splice(ce+1,0,Te),p=ce+1),ie=!0),ce++}for(a.dataType===r.ANIMATIONTYPE_QUATERNION?P.referenceValue.normalize().conjugateInPlace():a.dataType===r.ANIMATIONTYPE_MATRIX&&(P.referenceValue.decompose(P.referenceScaling,P.referenceQuaternion,P.referencePosition),P.referenceQuaternion.normalize().conjugateInPlace()),ce=s;ce<=p;ce++)if(Te=a._keys[ce],!ce||a.dataType===r.ANIMATIONTYPE_FLOAT||Te.value!==d.value)switch(a.dataType){case 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 b=i.beginAnimation(n,0,p,!1);return b.onAnimationEnd=d,b},Object.defineProperty(r.prototype,"runtimeAnimations",{get:function(){return this._runtimeAnimations},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasRunningRuntimeAnimations",{get:function(){for(var t=0,e=this._runtimeAnimations;t<e.length;t++)if(!e[t].isStopped)return!0;return!1},enumerable:!1,configurable:!0}),r.prototype.toString=function(t){var e="Name: "+this.name+", property: "+this.targetProperty;if(e+=", datatype: "+["Float","Vector3","Quaternion","Matrix","Color3","Vector2"][this.dataType],e+=", nKeys: "+(this._keys?this._keys.length:"none"),e+=", nRanges: "+(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.addEvent=function(t){this._events.push(t),this._events.sort(function(e,n){return e.frame-n.frame})},r.prototype.removeEvents=function(t){for(var e=0;e<this._events.length;e++)this._events[e].frame===t&&(this._events.splice(e,1),e--)},r.prototype.getEvents=function(){return this._events},r.prototype.createRange=function(t,e,n){this._ranges[t]||(this._ranges[t]=new G(t,e,n))},r.prototype.deleteRange=function(t,e){e===void 0&&(e=!0);var n=this._ranges[t];if(n){if(e)for(var i=n.from,o=n.to,a=this._keys.length-1;a>=0;a--)this._keys[a].frame>=i&&this._keys[a].frame<=o&&this._keys.splice(a,1);this._ranges[t]=null}},r.prototype.getRange=function(t){return this._ranges[t]},r.prototype.getKeys=function(){return this._keys},r.prototype.getHighestFrame=function(){for(var t=0,e=0,n=this._keys.length;e<n;e++)t<this._keys[e].frame&&(t=this._keys[e].frame);return t},r.prototype.getEasingFunction=function(){return this._easingFunction},r.prototype.setEasingFunction=function(t){this._easingFunction=t},r.prototype.floatInterpolateFunction=function(t,e,n){return $.a.Lerp(t,e,n)},r.prototype.floatInterpolateFunctionWithTangents=function(t,e,n,i,o){return $.a.Hermite(t,e,n,i,o)},r.prototype.quaternionInterpolateFunction=function(t,e,n){return u.b.Slerp(t,e,n)},r.prototype.quaternionInterpolateFunctionWithTangents=function(t,e,n,i,o){return u.b.Hermite(t,e,n,i,o).normalize()},r.prototype.vector3InterpolateFunction=function(t,e,n){return u.e.Lerp(t,e,n)},r.prototype.vector3InterpolateFunctionWithTangents=function(t,e,n,i,o){return u.e.Hermite(t,e,n,i,o)},r.prototype.vector2InterpolateFunction=function(t,e,n){return u.d.Lerp(t,e,n)},r.prototype.vector2InterpolateFunctionWithTangents=function(t,e,n,i,o){return u.d.Hermite(t,e,n,i,o)},r.prototype.sizeInterpolateFunction=function(t,e,n){return oe.a.Lerp(t,e,n)},r.prototype.color3InterpolateFunction=function(t,e,n){return M.a.Lerp(t,e,n)},r.prototype.color4InterpolateFunction=function(t,e,n){return M.b.Lerp(t,e,n)},r.prototype._getKeyValue=function(t){return typeof 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 x.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:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:C._SerializeValueAsString(this.value)},{name:"duration",value:C._SerializeValueAsString(this.duration)},{name:"stopOtherAnimations",value:C._SerializeValueAsString(this.stopOtherAnimations)||!1}]},e)},t}(C);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 x.c,this.onAnimationLoopObservable=new x.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 x.c,this.onAnimationLoopObservable=new x.c,this.onAnimationGroupLoopObservable=new x.c,this.onAnimationGroupEndObservable=new x.c,this.onAnimationGroupPauseObservable=new x.c,this.onAnimationGroupPlayObservable=new x.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),ct=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=[]},Cn=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),xn=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 x.c,this.onAudioLockedObservable=new x.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),ti=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 x.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(ti.Parse(d,t,n,o[d.url])):(i=ti.Parse(d,t,n),o[d.url]=i,e.sounds.push(i))):e.sounds.push(new ti(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 ni(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 ni(this),this._addComponent(r)),r.audioEnabled},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(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 ni(this),this._addComponent(r)),r.headphone},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(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 ni(this),this._addComponent(r)),r.audioListenerPositionProvider},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);if(t||(t=new ni(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 ni(this),this._addComponent(r)),r.audioPositioningRefreshRate},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(this),this._addComponent(t)),t.audioPositioningRefreshRate=r},enumerable:!0,configurable:!0});var ni=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}();ti._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_AUDIO);t||(t=new ni(r),r._addComponent(t))};var If=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),dl=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}(),fl=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}(),pl=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},Df=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}(),Lf=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),Nf=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),_l=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 x.c,this.onDragObservable=new x.c,this.onDragEndObservable=new x.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}(),wf=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}(),Ff=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),xt=f(27),Bt=f(26);function ml(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 gl(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?xt.b.Raw3D:xt.b.Raw2DArray,B=new xt.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 vl(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 xt.a(this,xt.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 xt.a(this,xt.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=ml(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=ml(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=gl(!1),Bt.a.prototype.createRawTexture3D=gl(!0),Bt.a.prototype.updateRawTexture2DArray=vl(!1),Bt.a.prototype.updateRawTexture3D=vl(!0);var ii=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 x.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=ii.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=ii.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}(),Bf=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}(),bl=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.onButtonDownObservable=new x.c,o.onButtonUpObservable=new x.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),ja=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=ja;var Zi=f(66),Ha=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=Ha;var Wa=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=Wa;var yl=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}(),Xa=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}(yl);hn.ArcRotateCameraPointersInput=Xa;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 Wa),this},t.prototype.addPointers=function(){return this.add(new Xa),this},t.prototype.addKeyboard=function(){return this.add(new Ha),this},t}($r);wo.prototype.addVRDeviceOrientation=function(){return this.add(new Ya),this};var Ya=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=Ya;var Ka=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=Ka;var Qa=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=Qa;var qa=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=qa;var Za=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=Za;var Ja=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}(yl);hn.FollowCameraPointersInput=Ja;var $a=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=$a;var es=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 x.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=es;var kt,Uf=function(){function r(){this.wheelPrecisionX=3,this.wheelPrecisionY=3,this.wheelPrecisionZ=3,this.onChangedObservable=new x.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 ts=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}(Uf);hn.FreeCameraMouseWheelInput=ts;var ns=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=ns;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 $a),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this._mouseInput||(this._mouseInput=new es(e),this.add(this._mouseInput)),this},t.prototype.removeMouse=function(){return this._mouseInput&&this.remove(this._mouseInput),this},t.prototype.addMouseWheel=function(){return this._mouseWheelInput||(this._mouseWheelInput=new ts,this.add(this._mouseWheelInput)),this},t.prototype.removeMouseWheel=function(){return this._mouseWheelInput&&this.remove(this._mouseWheelInput),this},t.prototype.addTouch=function(){return this.add(new ns),this},t.prototype.clear=function(){r.prototype.clear.call(this),this._mouseInput=null},t}($r);eo.prototype.addDeviceOrientation=function(){return this._deviceOrientationInput||(this._deviceOrientationInput=new is,this.add(this._deviceOrientationInput)),this};var is=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 x.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=is;var rs=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=rs;var an,Tl=f(112);(function(r){r[r.X=0]="X",r[r.Y=1]="Y",r[r.Z=2]="Z"})(an||(an={}));var os=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 Tl.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 as),this};var as=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 os(!0),this._leftjoystick.setAxisForUpDown(an.Z),this._leftjoystick.setAxisForLeftRight(an.X),this._leftjoystick.setJoystickSensibility(.15),this._rightjoystick=new os(!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=as;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 ss(r,u.e.Zero(),t)}});var ss=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 x.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 fl,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 pl,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 dl,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),El=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 Ka),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this.add(new Qa(e)),this},t}($r),Vf=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 El(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),Sl=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.addMouseWheel=function(){return this.add(new Za),this},t.prototype.addPointers=function(){return this.add(new Ja),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 Al(r,u.e.Zero(),t)}}),Q.a.AddNodeConstructor("ArcFollowCamera",function(r,t){return function(){return new Pl(r,0,0,1,null,t)}});var ri,Al=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 Sl(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),Pl=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),cs=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"})(ri||(ri={}));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 x.c,n.type=dn.POSE_ENABLED,n.controllerType=ri.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,Cl=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 x.c,a.onButtonUpObservable=new x.c,a.onPadDownObservable=new x.c,a.onPadUpObservable=new x.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 xl=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 x.c,o.onButtonUpObservable=new x.c,o.onPadDownObservable=new x.c,o.onPadUpObservable=new x.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),Rl=function(){function r(t){var e=this;if(this._scene=t,this._babylonGamepads=[],this._oneGamepadConnected=!1,this._isMonitoring=!1,this.onGamepadDisconnectedObservable=new x.c,cs.a.IsWindowObjectExist()?(this._gamepadEventSupported="GamepadEvent"in window,this._gamepadSupport=navigator.getGamepads||navigator.webkitGetGamepads||navigator.msGetGamepads||navigator.webkitGamepads):this._gamepadEventSupported=!1,this.onGamepadConnectedObservable=new x.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 Cl(t.id,t.index,t,i):n?new xl(t.id,t.index,t):t.pose?wi.InitiateController(t):new bl(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 Rl(this);var r=this._getComponent(at.a.NAME_GAMEPAD);r||(r=new Ol(this),this._addComponent(r))}return this._gamepadManager},enumerable:!0,configurable:!0}),eo.prototype.addGamepad=function(){return this.add(new rs),this},wo.prototype.addGamepad=function(){return this.add(new ja),this};var Ol=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}(ss);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),kf=`
-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=kf;var Ml=f(102);Bt.a.prototype.createRenderTargetTexture=function(r,t){var e=new Ml.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 xt.a(this,xt.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 xt.a(this,xt.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 x.c,this.onSizeChangedObservable=new x.c,this.onApplyObservable=new x.c,this.onBeforeRenderObservable=new x.c,this.onAfterRenderObservable=new x.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 Gf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-}`;ze.a.ShadersStore.passPixelShader=Gf;var zf=`
-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=zf;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 jf=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 Hf=`
-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=Hf;var ls=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"]=ls,gt.a._setStereoscopicAnaglyphRigMode=function(r){r._rigCameras[0]._rigPostProcess=new Fi(r.name+"_passthru",1,r._rigCameras[0]),r._rigCameras[1]._rigPostProcess=new ls(r.name+"_anaglyph",1,r._rigCameras)},Q.a.AddNodeConstructor("AnaglyphArcRotateCamera",function(r,t,e){return function(){return new Il(r,0,0,1,u.e.Zero(),e.interaxial_distance,t)}});var Il=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 Dl(r,u.e.Zero(),e.interaxial_distance,t)}});var Dl=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 Ll(r,u.e.Zero(),e.interaxial_distance,t)}});var Ll=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 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"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 wl(r,0,0,1,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var wl=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 Fl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Fl=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 Bl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Bl=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 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"StereoscopicUniversalCamera"},t}(_r);Q.a.AddNodeConstructor("VirtualJoysticksCamera",function(r,t){return function(){return new Vl(r,u.e.Zero(),t)}});var Vl=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}(),Wf=`
-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=Wf;var us=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),Xf=`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=Xf;var kl=f(85),hs=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 xt.a(this,xt.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 x.c,z.onAfterUnbindObservable=new x.c,z.onBeforeRenderObservable=new x.c,z.onAfterRenderObservable=new x.c,z.onClearObservable=new x.c,z.onResizeObservable=new x.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 hs.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 Gl=function(r){function t(e,n){n===void 0&&(n=512);var i=r.call(this,"multiview rtt",n,e,!1,!0,xt.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),zl=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 xt.a(this,xt.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 Gl(this.getScene(),{width:r,height:t})):this._multiviewTexture=new Gl(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 kl.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]),zl.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 ds=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 ds("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 us("VR_Distort_Compensation_Left",r._rigCameras[0],!1,e),r._rigCameras[1]._rigPostProcess=new us("VR_Distort_Compensation_Right",r._rigCameras[1],!0,e))},Q.a.AddNodeConstructor("VRDeviceOrientationFreeCamera",function(r,t){return function(){return new jl(r,0,0,1,u.e.Zero(),t)}});var jl=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 Hl(r,u.e.Zero(),t)}});var Hl=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 x.c,this.onVRRequestPresentComplete=new x.c,this.onVRRequestPresentStart=new x.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()}),cs.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()}},cs.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 x.c,a.onControllerMeshLoadedObservable=new x.c,a.onPoseUpdatedFromDeviceObservable=new x.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 ds("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===ri.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 x.c,n.onMainButtonStateChangedObservable=new x.c,n.onSecondaryButtonStateChangedObservable=new x.c,n.onPadStateChangedObservable=new x.c,n.onPadValuesChangedObservable=new x.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),Yf=(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=Yf;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),fs=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=fs.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),ps=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}(),Wl=function(){function r(t,e){var n=this;if(e===void 0&&(e=ps.GetDefaults()),this._options=e,this._canvas=null,this.xrLayer=null,this.onXRLayerInitObservable=new x.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}(),_s=function(){function r(t){this.scene=t,this._sessionEnded=!1,this.baseLayer=null,this.currentTimestamp=-1,this.defaultHeightCompensation=1.7,this.onXRFrameObservable=new x.c,this.onXRReferenceSpaceChanged=new x.c,this.onXRSessionEnded=new x.c,this.onXRSessionInit=new x.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||ps.GetDefaults(e)).canvasElement=e.getRenderingCanvas()||void 0,new Wl(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 xt.a(this.scene.getEngine(),xt.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 oi,Xl=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}(),Kf=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}(Xl),Yl=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}(Xl),Qf=function(){},Kl=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 x.c,this.onAfterEnteringVRObservable=new x.c,this.onExitingVRObservable=new x.c,this.onControllerMeshLoadedObservable=new x.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 x.c,this.onMeshSelectedWithController=new x.c,this.onNewMeshPicked=new x.c,this.onBeforeCameraTeleport=new x.c,this.onAfterCameraTeleport=new x.c,this.onSelectedMeshUnselected=new x.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 Kf(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?_s.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 Yl(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 Yl(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===ri.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=(oi={root:0,found:!1},function(r,t,e,n){oi.root=0,oi.found=!1;var i=t*t-4*r*e;if(i<0)return oi;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?(oi.root=a,oi.found=!0,oi):(s>0&&s<n&&(oi.root=s,oi.found=!0),oi)}),Ql=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}(),ql=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 Ql},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 ql};var nr=f(54),qf=f(114),Zf=f(147),ms=f(103),Vi=f(43),Zl=f(113),Jl=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(ms.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(ms.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){Jl._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 Ts(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 Ts(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,gs,vs,bs,ys,Ts=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"}(gs||(gs={})),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"}(vs||(vs={})),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"}(bs||(bs={})),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"}(ys||(ys={}));var $l=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}(),eu=function(){function r(t,e,n){n===void 0&&(n=0),this.deviceType=e,this.deviceSlot=n,this.onInputChangedObservable=new x.c,this._deviceInputSystem=t}return r.prototype.getInput=function(t){return this._deviceInputSystem.pollInput(this.deviceType,this.deviceSlot,t)},r}(),Jf=function(){function r(t){var e=this;this.onDeviceConnectedObservable=new x.c(function(i){e.getDevices().forEach(function(o){e.onDeviceConnectedObservable.notifyObserver(i,o)})}),this.onDeviceDisconnectedObservable=new x.c;var n=Object.keys(Kt).length/2;this._devices=new Array(n),this._firstDevice=new Array(n),this._deviceInputSystem=$l.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 eu(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}(),tu=f(168),nu=(f(123),function(){this._timeElapsedQueryEnded=!1}),iu=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 nu;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 iu),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 $f=!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=fs.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 xt.a(this,xt.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 xt.a(this,xt.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 xt.a(this,xt.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 xt.a(this,xt.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,Ce=0;Ce<Se.length;Ce++)if(Re[Ce].width!==Ae||Re[Ce].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[Ce],0,0,Re[Ce].width,Re[Ce].height,0,0,Ae,Ee),F.texImage2D(Se[Ce],0,Le,Le,F.UNSIGNED_BYTE,B._workingCanvas)}else F.texImage2D(Se[Ce],0,Le,Le,F.UNSIGNED_BYTE,Re[Ce]);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 ep=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 tp(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=tp.bind(this),this._textureFormatInUse=t[e];return this._textureFormatInUse="",this._transformTextureUrl=null,null};var np=f(144),ru=f(118),ou=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))],ip=[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]*ip[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],Es=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=Es.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 Es,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(Ce){var Ne=Ce.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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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=xt.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}();xt.a._UpdateRGBDAsync=Ai._UpdateRGBDAsync;var Pi,Ss=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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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 au;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 au;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 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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 ap},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 Ss(n);d.processCode(),n=d.code;var p=new Ss(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 xt.a(this,xt.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 Ce=se._webGLTexture;Ce?z._native.loadTexture(Ce,Le,!n,i,function(){se.baseWidth=z._native.getTextureWidth(Ce),se.baseHeight=z._native.getTextureHeight(Ce),se.width=se.baseWidth,se.height=se.baseHeight,se.isReady=!0;var Ne=z._getNativeSamplingMode(a);z._native.setTextureSampling(Ce,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 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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 xt.a(this,xt.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 Ml.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 su(this,xt.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"&&(xs._IsQuest=!0),r.id.indexOf("Oculus Touch")!==-1},create:function(r){return new xs(r)}});var cu=function(r){function t(e){var n=r.call(this,e)||this;return n.controllerType=ri.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 cu(r)}});var up=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 x.c,n.onTrackpadValuesChangedObservable=new x.c,n.trackpad={x:0,y:0},n.controllerType=ri.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 up;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),hp=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 x.c,n.onThumbstickValuesChangedObservable=new x.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 x.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(Ce){var Ne=Ce*(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(Ce){if(F.attachedNode){var Ne=F.sensitivity*Ce.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(Ce){return ve(Ce.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(Ce){return ve(Ce.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(Ce){var Ne;if(!F._customMeshSet&&(F._isHovered=Se.colliderMeshes.indexOf((Ne=Ce?.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),lu=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 x.c,i.onScaleBoxDragObservable=new x.c,i.onScaleBoxDragEndObservable=new x.c,i.onRotationSphereDragObservable=new x.c,i.onRotationSphereDragEndObservable=new x.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 x.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),Ce=b._rotationCircle.getDirection(Le);Ce.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(Ce),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),Ce=new u.b(0,0,0,1),Ne=new u.e(0,0,0);b.attachedNode.getWorldMatrix().decompose(Le,Ce,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&&(Ce.toRotationMatrix(se),ue=u.e.TransformCoordinates(ce,se));var lt=!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),lt=!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+=lt?-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?Ce.multiplyToRef(Re,Ce):Re.multiplyToRef(Ce,Ce),b.attachedNode.getWorldMatrix().copyFrom(u.a.Compose(Le,Ce,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 Ce=b._isHovered||b._dragging?b._hoverMaterial:b._coloredMaterial;Ee.gizmoMeshes.forEach(function(Ne){Ne.material=Ce,Ne.color&&(Ne.color=Ce.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),uu=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 x.c,s.onDragEndObservable=new x.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),Rs=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 x.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=Rs.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),hu=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 x.c,o.onDragEndObservable=new x.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 Ce=B.face[Le].length;for(i=2*Math.PI/Ce,o=.5*Math.tan(i/2),a=.5,Se=0;Se<Ce;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<Ce-2;Se++)ue.push(Ee[0+Ae],Ee[Se+2+Ae],Ee[Se+1+Ae]);Ae+=Ce}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}(),du=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 x.c,o.onDragEndObservable=new x.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),dp=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 x.c,this.onAttachedToNodeObservable=new x.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 _l,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 hu(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 uu(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 du(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 lu(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}(),xi=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}(xi.a);Q.a.AddNodeConstructor("Light_Type_1",function(r,t){return function(){return new Os(r,u.e.Zero(),t)}});var Os=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 xi.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 Ms(r,u.e.Zero(),u.e.Zero(),0,0,t)}});var Ms=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 xi.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),fp=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 x.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 Os?t._CreateDirectionalLightMesh(this.gizmoLayer.utilityLayerScene):e instanceof Ms?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),Is=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}(),pp=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}(),_p=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 x.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 mp=`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=mp;var gp=`#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=gp;var vp=`#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=vp;var bp=`
-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=bp,ze.a.IncludesShadersStore.kernelBlurVertex="sampleCoord{X}=sampleCenter+delta*KERNEL_OFFSET{X};";var yp=`
-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=yp;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 Ds=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 Ds(r,t,e,n)};var Qn=f(34),ai=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 x.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=ai.Parse,R.a.RegisteredTypes["BABYLON.CubeTexture"]=ai;var et=f(15),Jo=f(76),$o=f(87),ht=f(19),Tp=` 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=Tp;var Ep=`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=Ep,f(131),f(106),f(107),f(154),f(130),f(115),f(125),f(110),f(135),f(136);var Sp=`#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=Sp;var Ap=`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=Ap,f(78),f(79),f(117),f(137),f(80),f(81),f(111),f(157),f(138);var Pp=`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=Pp;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 Ls=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 x.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=ai.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 Ds("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 ai(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 x.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),xp=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),fu=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,fu.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}(),Rp=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;
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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;
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-uniform vec2 vRefractionFilteringInfo;
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
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-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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-#define vMetallicReflectanceUV vMainUV1
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-#define vClearCoatUV vMainUV1
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-#endif
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-#define sampleReflection(s,c) texture2D(s,c)
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-#ifdef USEIRRADIANCEMAP
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-#endif
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
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-#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
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-{
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-float reflectance90=saturate(reflectance0*25.0);
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-
-vec3 getAnisotropicBentNormals(const vec3 T,const vec3 B,const vec3 N,const vec3 V,float anisotropy) {
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-#ifdef MICROSURFACEAUTOMATIC
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-{
-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=Np;var wp=`#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=wp;var Fp=`
-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=Fp;var Bp=`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=Bp;var Up=`
-#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=Up;var Vp=`#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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-
-
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-
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-
-
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-
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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=Vp;var kp=`#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=kp;var Gp=`#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=Gp,f(132),f(133);var zp=`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=zp;var jp=`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=jp;var Hp=`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=Hp;var Wp=`#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=Wp;var Xp=`#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=Xp;var Yp=`#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=Yp;var Kp=`#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=Kp;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 qp=`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=qp;var Zp=`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=Zp,f(134);var Jp=`#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=Jp,f(162);var $p=`#ifdef LIGHTMAP
-vec4 lightmapColor=texture2D(lightmapSampler,vLightmapUV+uvOffset);
-#ifdef RGBDLIGHTMAP
-lightmapColor.rgb=fromRGBD(lightmapColor);
-#endif
-#ifdef GAMMALIGHTMAP
-lightmapColor.rgb=toLinearSpace(lightmapColor.rgb);
-#endif
-lightmapColor.rgb*=vLightmapInfos.y;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockLightmapInit=$p;var e_=`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=e_;var t_=`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=t_;var n_=`#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=n_;var i_=`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=i_;var r_=`
-
-
-
-#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=r_;var o_=`
-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=o_;var a_=`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=a_,f(155);var s_=`#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=s_;var c_=`#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=c_;var l_=`#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=l_;var u_=`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=u_,f(163),f(164),f(93),f(94),f(100),f(165),f(156),f(158);var h_=`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=h_;var ta=f(92),Cr={effect:null,subMesh:null},ws=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 Rp(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 Ns.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 ws);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&&(Cr.effect=P,Cr.subMesh=n,this._onEffectCreatedObservable.notifyObservers(Cr)),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),Ns.a.AddUniforms(F),Ns.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 ws,d=this._prepareEffect(e,s,void 0,void 0,a.useInstances,a.clipPlane,e.hasThinInstances);this._onEffectCreatedObservable&&(Cr.effect=d,Cr.subMesh=null,this._onEffectCreatedObservable.notifyObservers(Cr)),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 pu=na("DXT1"),_u=na("DXT3"),mu=na("DXT5"),Fs=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===Fs?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 Fs: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===pu||o===_u||o===mu,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 pu:fe=8,ue=ie.COMPRESSED_RGBA_S3TC_DXT1_EXT;break;case _u:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT3_EXT;break;case mu:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT5_EXT;break;case 113:case 116:Re=!0;break;case Fs: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]),Ce=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,Ce),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=xt.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=$.a.Log2(B)*e+n,ce=ie+(se-ie)*J,ue=Math.round(Math.min(Math.max(ce,0),se)),fe=new xt.a(p,xt.b.Temp);if(fe.type=P.type,fe.format=P.format,fe.width=Math.pow(2,Math.max($.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 gu=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 gu);var vu=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 vu);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;case r.TEX_2D:case r.COMPRESSED_3D:case r.TEX_3D:}},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}(),Bs=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}(),Us=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="("+d_+")()",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 Bs(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 d_(){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 bu=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 Us.IsValid(t)?new Us(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 bu);var yu=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 x.c,o.onAfterCameraTeleport=new x.c,o.onTrackingStateChanged=new x.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),si=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}(),Tu=function(){function r(t){var e=this;this.scene=t,this._nonVRCamera=null,this._originalSceneAutoClear=!0,this._supported=!1,this.onInitialXRPoseSetObservable=new x.c,this.onStateChangedObservable=new x.c,this.state=pn.NOT_IN_XR,this.sessionManager=new _s(t),this.camera=new yu("",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}(),xr=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 x.c,this.onButtonStateChangedObservable=new x.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 xr(s,p,b,P)}},this._modelReady=!1,this.components={},this.disableAnimation=!1,this.onModelLoadedObservable=new x.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}(),Vs=function(r){function t(e,n,i){var o=r.call(this,e,f_[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),f_={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"}},Eu=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===xr.TOUCHPAD_TYPE&&o.touchPointNodeName?o.touchPointNodeName:s.valueNodeName;if(n._buttonMeshMapping[i].states[a]={valueMesh:n._getChildByName(n.rootMesh,d)},o.type===xr.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 Eu(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(Vs.ProfileId,function(r,t){return new Vs(t,r.gamepad,r.handedness)}),Bn.DefaultFallbacks();var p_=0,Su=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 x.c,this.onMeshLoadedObservable=new x.c,this.onMotionControllerInitObservable=new x.c,this._uniqueId="controller-"+p_+++"-"+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}(),Au=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 x.c,this.onControllerRemovedObservable=new x.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 Su(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}(),ci=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=si.POINTER_SELECTION,t.Version=1,t}(ci);qn.AddWebXRFeature(ho.Name,function(r,t){return function(){return new ho(r,t)}},ho.Version,!0);var zi,Pu=function(){function r(t,e,n){this.element=t,this.sessionMode=e,this.referenceSpaceType=n}return r.prototype.update=function(t){},r}(),__=function(){},Cu=function(){function r(t,e){var n=this;if(this.scene=t,this.options=e,this._activeButton=null,this._buttons=[],this.activeButtonChangedObservable=new x.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 Pu(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 ks(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 m_=function(){function r(t){var e,n,i=this;this.onEachCountObservable=new x.c,this.onTimerAbortedObservable=new x.c,this.onTimerEndedObservable=new x.c,this.onStateChangedObservable=new x.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(xr.THUMBSTICK_TYPE)||o.motionController.getComponentOfType(xr.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,ks({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,ks({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=si.TELEPORTATION,t.Version=1,t}(ci);qn.AddWebXRFeature(fo.Name,function(r,t){return function(){return new fo(r,t)}},fo.Version,!0);var g_=function(){},xu=function(){function r(){}return r.CreateAsync=function(t,e){e===void 0&&(e={});var n=new r;return Tu.CreateAsync(t).then(function(i){if(n.baseExperience=i,e.ignoreNativeCameraTransformation&&(n.baseExperience.camera.compensateOnFirstFrame=!1),n.input=new Au(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),Cu.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}(),v_=!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 Ls?new Ls(r,this):null},_e.a.prototype.createDefaultVRExperience=function(r){return r===void 0&&(r={}),new Kl(this,r)},_e.a.prototype.createDefaultXRExperienceAsync=function(r){return r===void 0&&(r={}),xu.CreateAsync(this,r).then(function(t){return t})};var Ru=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 x.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),b_=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 Ru((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),y_=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}(),T_=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}(),E_=`#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=E_;var S_=`
-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=S_;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 x.c,this.onBeforeRenderMainTextureObservable=new x.c,this.onBeforeComposeObservable=new x.c,this.onBeforeRenderMeshToEffect=new x.c,this.onAfterRenderMeshToEffect=new x.c,this.onAfterComposeObservable=new x.c,this.onSizeChangedObservable=new x.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 Ou=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 Ou(r),r._addComponent(t))};var A_=`
-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=A_;var P_=`
-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=P_,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()===Gs.EffectName)return this.effectLayers[t];return null};var Mu=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),Gs=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 x.c,o.onAfterBlurObservable=new x.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 Mu("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 Mu("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"]=Gs;var Iu=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}(),x_=`
-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=x_;var R_=`
-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=R_;var O_=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 x.c,this.onBeforeRenderObservable=new x.c,this.onAfterRenderObservable=new x.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 Iu(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}(),Du=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}(),M_=`
-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=M_;var I_=`
-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=I_;var zs=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];Du.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=zs.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 Lu=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}();zs._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_LENSFLARESYSTEM);t||(t=new Lu(r),r._addComponent(t))};var D_=`
-
-
-
-
-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=D_;var L_=`#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=L_;var N_=` 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=N_;var w_=`#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=w_;var F_=`#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=F_;var B_=`
-#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=B_;var U_=`#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=U_;var V_=`
-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=V_;var k_=`
-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=k_;var G_=`#if SM_SOFTTRANSPARENTSHADOW == 1
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM*alpha) discard;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapFragmentSoftTransparentShadow=G_;var Nu=new u.a,wu=new u.a,Un=function(){function r(t,e,n){this.onBeforeShadowMapRenderObservable=new x.c,this.onAfterShadowMapRenderObservable=new x.c,this.onBeforeShadowMapRenderMeshObservable=new x.c,this.onAfterShadowMapRenderMeshObservable=new x.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(),Nu),e.setMatrix((p=n?.worldViewProjection)!==null&&p!==void 0?p:"worldViewProjection",Nu),P.multiplyToRef(this._viewMatrix,wu),e.setMatrix((b=n?.worldView)!==null&&b!==void 0?b:"worldView",wu)},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()===xi.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()===xi.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,Ce=this.customShaderOptions.samplers;Le<Ce.length;Le++){var Ne=Ce[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}(),z_=`#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=z_;var j_=`
-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=j_;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}(),H_=`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=H_;var Fu=function(){function r(t){this.onAfterReductionPerformed=new x.c,this._forceFullscreenViewport=!0,this._activated=!1,this._camera=t,this._postProcessManager=new hs.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}(),Bu=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}(Fu),Uu=u.e.Up(),W_=u.e.Zero(),vn=new u.e,Or=new u.e,Mr=new u.a,Vu=new u.a,js=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 Bu(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],Uu,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(W_,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,Uu,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),Vu),n.setMatrix((P=i?.worldView)!==null&&P!==void 0?P:"worldView",Vu)},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===js.CLASSNAME?js.Parse(i,t):Un.Parse(i,t)}});var ku=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 ku(r),r._addComponent(t))},Q.a.AddNodeConstructor("Light_Type_0",function(r,t){return function(){return new Hs(r,u.e.Zero(),t)}});var Hs=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 xi.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),Gu=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 Gu(r)};var Ws=f(71),rr=f(68),Xs=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}(),zu=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}(),X_=`
-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=X_;var Y_=`#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=Y_;var Wu=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 Hu({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 ju(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 Wu(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=zu.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 Xu=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 x.c,this._onDataLayoutChanged=new x.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(Xu.Parse(a))}return n},r}(),Ct=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}(),Ys=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}(),Ks=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 Ys):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!=Ct.a.HeightmapImpostor&&o.type!==Ct.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 Ct.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 Ct.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 Ct.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 Ct.a.PlaneImpostor:l.a.Warn("Attention, PlaneImposter might not behave as you expect. Consider using BoxImposter instead"),e=new this.BJSCANNON.Plane;break;case Ct.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 Ct.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 Ct.a.ParticleImpostor:e=new this.BJSCANNON.Particle;break;case Ct.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!==Ct.a.PlaneImpostor&&t.type!==Ct.a.HeightmapImpostor||(i=i.multiply(this._minus90X),t.setDeltaRotation(this._plus90X)),t.type===Ct.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===Ct.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 Ks};var Yu=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 Ys}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 Ct.a.ParticleImpostor:l.a.Warn("No Particle support in OIMO.js. using SphereImpostor instead");case Ct.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 Ct.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 Ct.a.PlaneImpostor:case Ct.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),Ku=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 Ys,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===Ct.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===Ct.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===Ct.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!=Ct.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==Ct.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!=Ct.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 Ct.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 Ct.a.CapsuleImpostor:i=new this.bjsAMMO.btCapsuleShape(a.x/2,a.y/2);break;case Ct.a.CylinderImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btCylinderShape(this._tmpAmmoVectorA);break;case Ct.a.PlaneImpostor:case Ct.a.BoxImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btBoxShape(this._tmpAmmoVectorA);break;case Ct.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 Ct.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 Ct.a.NoImpostor:i=new this.bjsAMMO.btSphereShape(a.x/2);break;case Ct.a.CustomImpostor:i=this._createCustom(t);break;case Ct.a.SoftbodyImpostor:i=this._createSoftbody(t);break;case Ct.a.ClothImpostor:i=this._createCloth(t);break;case Ct.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===Ct.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 Qu=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}(),K_=!0,la=function(){function r(){}return r.LoaderInjectedPhysicsEngine=void 0,r}(),qu=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")},Zu=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}},Ju=function(r,t,e,n,i){i===void 0&&(i=!1);var o=new Cn(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 ai((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r);s.environmentTextureRotationY&&(F.rotationY=s.environmentTextureRotationY),r.environmentTexture=F}else{var z=ai.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=xi.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=Qu.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 Ce=0,Ne=s.morphTargetManagers;Ce<Ne.length;Ce++){var Ie=Ne[Ce];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,lt=tt.vertexData;if(lt!=null)for(d=0,p=lt.length;d<p;d++){var Qe=lt[d];it.push(Ws.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=$u.Parse;var eh=f(119),Qs=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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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(["("+$_+")()"],{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 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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 ah=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 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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),Zs=function(r,t,e){this.id=r,this.scale=t,this.offset=e},em=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),Ce=e.sets[Ae];if(Ce.getContext().putImageData(Le,n.x*Te.x,n.y*Te.y),fe.dispose(),Ce.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 Ce=0;Ce<9;Ce++)ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[Ce],F+B*Le[Ce+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 Zs(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 Zs(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}(),sh=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}(),tm=`
-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=tm;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 x.c,b.onBeforeGenerationObservable=new x.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 sh(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 nm=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),im=`
-
-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=im;var ch=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"]=ch;var xe,le,bn,bt,Mn,li,Tn,rm=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===xt.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=xt.b.CubeRawRGBD,e._bufferViewArrayArray=n,e._lodGenerationScale=o,e._lodGenerationOffset=a,e._sphericalPolynomial=i,Ai.UploadLevelsAsync(e,n).then(function(){e.isReady=!0})},t}(ai),om=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),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().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),sm=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"})(xe||(xe={})),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"}(li||(li={})),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 x.c,this.isExposedOnFrame=!1,this.exposedPortPosition=-1,this._prioritizeVertex=!1,this._target=xe.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!==xe.VertexAndFragment?this._target:this._ownerBlock.target===xe.Fragment?xe.Fragment:xe.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===xe.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===xe.Vertex||n.target===xe.Vertex||(n.ownerBlock.target===xe.Neutral||n.ownerBlock.target===xe.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===xe.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===xe.Fragment||(n.ownerBlock.target===xe.Neutral||n.ownerBlock.target===xe.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)===li.Compatible},r.prototype.checkCompatibilityState=function(t){if(this._ownerBlock.target===xe.Fragment){var e=t.ownerBlock;if(e.target===xe.Vertex)return li.TargetIncompatible;for(var n=0,i=e.outputs;n<i.length;n++)if(i[n].isConnectedInVertexShader)return li.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)?li.Compatible:li.TypeIncompatible:t.excludedConnectionPointTypes&&t.excludedConnectionPointTypes.indexOf(this.type)!==-1?1:li.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}(),cm=f(152),pt=function(){function r(t,e,n,i){e===void 0&&(e=xe.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=cm.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===xe.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===xe.Vertex&&t.target!==xe.VertexAndFragment;if(o&&(!(t.target&t._buildTarget)||!(t.target&n.target)||this.target!==xe.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!==xe.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===xe.Vertex?"Vertex shader":"Fragment shader")+": Building "+this.name+" ["+this.getClassName()+"]"),this.isFinalMerger)switch(t.target){case xe.Vertex:t.sharedData.checks.emitVertex=!0;break;case xe.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}(),lh=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===xe.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}(),lm=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,xe.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,xe.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,xe.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 um={position2d:"position",particle_uv:"vUV",particle_color:"vColor",particle_texturemask:"textureMask",particle_positionw:"vPositionW"},Js={particle_uv:!0,particle_color:!0,particle_texturemask:!0,particle_positionw:!0},uh={particle_texturemask:!0},At=function(r){function t(e,n,i){n===void 0&&(n=xe.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 x.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 Js[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=um[this.name])!==null&&i!==void 0?i:this.name,this.target===xe.Vertex&&e._vertexState)return void(Js[this.name]?uh[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),Js[this.name]?uh[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 $s=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment)||this;return n._samplerName="textureSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),n.registerOutput("rgba",le.Color4,xe.Neutral),n.registerOutput("rgb",le.Color3,xe.Neutral),n.registerOutput("r",le.Float,xe.Neutral),n.registerOutput("g",le.Float,xe.Neutral),n.registerOutput("b",le.Float,xe.Neutral),n.registerOutput("a",le.Float,xe.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?xe.VertexAndFragment:xe.Fragment:xe.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===xe.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==xe.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===xe.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else this.uv.ownerBlock.target!==xe.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!==xe.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"]=$s;var ec=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._samplerName="diffuseSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),n.registerOutput("rgba",le.Color4,xe.Neutral),n.registerOutput("rgb",le.Color3,xe.Neutral),n.registerOutput("r",le.Float,xe.Neutral),n.registerOutput("g",le.Float,xe.Neutral),n.registerOutput("b",le.Float,xe.Neutral),n.registerOutput("a",le.Float,xe.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!==xe.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"]=ec;var tc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,xe.Fragment),n.registerOutput("rampColor",le.Color4,xe.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!==xe.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"]=tc;var nc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,xe.Fragment),n.registerInput("alphaTexture",le.Float,!1,xe.Fragment),n.registerInput("alphaColor",le.Float,!1,xe.Fragment),n.registerOutput("blendColor",le.Color4,xe.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!==xe.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"]=nc;var Lt,bo=function(r){function t(e){var n=r.call(this,e,xe.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 ic=function(r){function t(e){var n=r.call(this,e,xe.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"]=ic;var pa=function(r){function t(e){var n=r.call(this,e,xe.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}(),rc=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=$.a.RandomRange((1-this.radiusRange)*(1-this.radiusRange),1),d=Math.sqrt(s)*this.radius,p=d*Math.cos(a),b=d*Math.sin(a);i?e.copyFromFloats(p,o,b):u.e.TransformCoordinatesFromFloatsToRef(p,o,b,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("height",this.height),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define CYLINDEREMITTER"},r.prototype.getClassName=function(){return"CylinderParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.height=this.height,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.height=t.height,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),oc=function(r){function t(e,n,i,o,a){e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=1),o===void 0&&(o=new u.e(0,1,0)),a===void 0&&(a=new u.e(0,1,0));var s=r.call(this,e,n,i)||this;return s.direction1=o,s.direction2=a,s}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.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),ac=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}(),sc=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=$.a.RandomRange(0,2*Math.PI),d=Math.acos(2*a-1),p=o*Math.cos(s)*Math.sin(d),b=o*Math.cos(d),P=o*Math.sin(s)*Math.sin(d);i?e.copyFromFloats(p,b,P):u.e.TransformCoordinatesFromFloatsToRef(p,b,P,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define SPHEREEMITTER"},r.prototype.getClassName=function(){return"SphereParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),cc=function(r){function t(e,n,i){e===void 0&&(e=1),n===void 0&&(n=new u.e(0,1,0)),i===void 0&&(i=new u.e(0,1,0));var o=r.call(this,e)||this;return o.direction1=n,o.direction2=i,o}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.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}(),hh=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 sc;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 ac(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 cc(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 oc(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 rc(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}(),lc=function(r){function t(e){var n=r.call(this,e,xe.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"]=lc;var rn,dh=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 uc=function(r){function t(e){var n=r.call(this,e,xe.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"]=uc;var hc={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 x.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&xe.Vertex&&this._addVertexOutputNode(e),e.target&xe.Fragment&&this._addFragmentOutputNode(e),this},t.prototype.removeOutputNode=function(e){return e.target===null||(e.target&xe.Vertex&&this._removeVertexOutputNode(e),e.target&xe.Fragment&&this._removeFragmentOutputNode(e)),this},t.prototype._addVertexOutputNode=function(e){if(this._vertexOutputNodes.indexOf(e)===-1)return e.target=xe.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=xe.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===xe.VertexAndFragment||n.target===xe.Fragment&&O.target===xe.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===xe.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 lh,this._vertexCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._vertexCompilationState.target=xe.Vertex,this._fragmentCompilationState=new lh,this._fragmentCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._fragmentCompilationState.target=xe.Fragment,this._sharedData=new lm,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),dh.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),dh.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&&(hc.effect=z,hc.subMesh=n,this._onEffectCreatedObservable.notifyObservers(hc)),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 ic("uv0");e.connectTo(s);var d=new pa("UV scale");s.connectTo(d),a.connectTo(d);var p=new $s("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 uc("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 ec("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 tc("ParticleRampGradient");o.connectTo(a);var s=new lc("ColorSplitter");i.connectTo(s);var d=new nc("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 fh=function(r){function t(e){var n=r.call(this,e,xe.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"]=fh;var ph=function(r){function t(e){var n=r.call(this,e,xe.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"]=ph;var _h=function(r){function t(e){var n=r.call(this,e,xe.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"]=_h;var mh=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.registerInput("worldPosition",le.Vector4,!1,xe.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 Hs))}},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"]=mh;var gh=function(r){function t(e){var n=r.call(this,e,xe.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"]=gh;var vh=function(r){function t(e){var n=r.call(this,e,xe.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"]=vh;var bh=function(r){function t(e){var n=r.call(this,e,xe.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"]=bh;var yh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("output",le.Float,xe.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===xe.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"]=yh;var Th=function(r){function t(e){var n=r.call(this,e,xe.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"]=Th;var Eh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("xy",le.Vector2,xe.Fragment),n.registerOutput("xyz",le.Vector3,xe.Fragment),n.registerOutput("xyzw",le.Vector4,xe.Fragment),n.registerOutput("x",le.Float,xe.Fragment),n.registerOutput("y",le.Float,xe.Fragment),n.registerOutput("z",le.Float,xe.Fragment),n.registerOutput("w",le.Float,xe.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===xe.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"]=Eh;var Sh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("xy",le.Vector2,xe.Fragment),n.registerOutput("x",le.Float,xe.Fragment),n.registerOutput("y",le.Float,xe.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===xe.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"]=Sh;var Ah=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment,!0)||this;return n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("view",le.Matrix,!1,xe.Vertex),n.registerInput("input",le.Color3,!1,xe.Fragment),n.registerInput("fogColor",le.Color3,!1,xe.Fragment),n.registerOutput("output",le.Color3,xe.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===xe.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"]=Ah;var Ph=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment)||this;return n._isUnique=!0,n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("glossiness",le.Float,!0,xe.Fragment),n.registerInput("glossPower",le.Float,!0,xe.Fragment),n.registerInput("diffuseColor",le.Color3,!0,xe.Fragment),n.registerInput("specularColor",le.Color3,!0,xe.Fragment),n.registerInput("view",le.Matrix,!0),n.registerOutput("diffuseOutput",le.Color3,xe.Fragment),n.registerOutput("specularOutput",le.Color3,xe.Fragment),n.registerOutput("shadow",le.Float,xe.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===xe.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"]=Ph;var Ch=function(r){function t(e,n){n===void 0&&(n=!1);var i=r.call(this,e,n?xe.Fragment:xe.VertexAndFragment)||this;return i.convertToGammaSpace=!1,i.convertToLinearSpace=!1,i._fragmentOnly=n,i.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),i.registerOutput("rgba",le.Color4,xe.Neutral),i.registerOutput("rgb",le.Color3,xe.Neutral),i.registerOutput("r",le.Float,xe.Neutral),i.registerOutput("g",le.Float,xe.Neutral),i.registerOutput("b",le.Float,xe.Neutral),i.registerOutput("a",le.Float,xe.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 xe.Fragment;if(!this.uv.isConnected||this.uv.sourceBlock.isInput)return xe.VertexAndFragment;for(var e=this.uv.connectedPoint;e;){if(e.target===xe.Fragment)return xe.Fragment;if(e.target===xe.Vertex)return xe.VertexAndFragment;if(e.target===xe.Neutral||e.target===xe.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 xe.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!==xe.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===xe.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==xe.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===xe.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else if(this.uv.ownerBlock.target!==xe.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===xe.Vertex||this._fragmentOnly)&&(this._tempTextureRead=e._getFreeVariableName("tempTextureRead")),(!this._isMixed&&e.target===xe.Fragment||this._isMixed&&e.target===xe.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===xe.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"]=Ch;var dc=function(r){function t(e){return r.call(this,e,xe.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===xe.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=ai.Parse(e.texture,n,i):this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.ReflectionTextureBaseBlock"]=dc;var xh=function(r){function t(e){var n=r.call(this,e)||this;return n.registerInput("position",le.Vector3,!1,xe.Vertex),n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("world",le.Matrix,!1,xe.Vertex),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("view",le.Matrix,!1,xe.Fragment),n.registerOutput("rgb",le.Color3,xe.Fragment),n.registerOutput("rgba",le.Color4,xe.Fragment),n.registerOutput("r",le.Float,xe.Fragment),n.registerOutput("g",le.Float,xe.Fragment),n.registerOutput("b",le.Float,xe.Fragment),n.registerOutput("a",le.Float,xe.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!==xe.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}(dc);R.a.RegisteredTypes["BABYLON.ReflectionTextureBlock"]=xh;var Rh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Rh;var Oh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Oh;var Mh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Mh;var Ih=function(r){function t(e){var n=r.call(this,e,xe.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"]=Ih;var Dh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Dh;var Lh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Lh;var Nh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Nh;var wh=function(r){function t(e){var n=r.call(this,e,xe.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"]=wh;var Fh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Fh;var Bh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Bh;var Uh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Uh;var Vh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Vh;var fc=function(r){function t(e){var n=r.call(this,e,xe.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"]=fc,R.a.RegisteredTypes["BABYLON.OppositeBlock"]=fc;var pc=function(r){function t(e){var n=r.call(this,e,xe.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"]=kh;var Gh=function(r){function t(e){var n=r.call(this,e,xe.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
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MaxBlock"]=Gh;var zh=function(r){function t(e){var n=r.call(this,e,xe.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"MinBlock"},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)+" = min("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MinBlock"]=zh;var jh=function(r){function t(e){var n=r.call(this,e,xe.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"]=jh;var Hh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Hh;var Wh=function(r){function t(e){var n=r.call(this,e,xe.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
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NegateBlock"]=Wh;var Xh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("power",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"PowBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"power",{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)+" = pow("+this.value.associatedVariableName+", "+this.power.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.PowBlock"]=Xh;var Yh=function(r){function t(e){var n=r.call(this,e,xe.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
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.RandomNumberBlock"]=Yh;var Kh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("x",le.Float),n.registerInput("y",le.Float),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ArcTan2Block"},Object.defineProperty(t.prototype,"x",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{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)+" = atan("+this.x.associatedVariableName+", "+this.y.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ArcTan2Block"]=Kh;var Qh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Qh;var qh=function(r){function t(e){var n=r.call(this,e,xe.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"]=qh;var Zh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Zh;var or,Jh=function(r){function t(e){var n=r.call(this,e,xe.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"]=Jh,function(r){r[r.SawTooth=0]="SawTooth",r[r.Square=1]="Square",r[r.Triangle=2]="Triangle"}(or||(or={}));var $h=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.kind=or.SawTooth,n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"WaveBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];switch(this.kind){case or.SawTooth:e.compilationString+=this._declareOutput(n,e)+" = "+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`);\r
-`;break;case or.Square:e.compilationString+=this._declareOutput(n,e)+" = 1.0 - 2.0 * round(fract("+this.input.associatedVariableName+`));\r
-`;break;case or.Triangle:e.compilationString+=this._declareOutput(n,e)+" = 2.0 * abs(2.0 * ("+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`))) - 1.0;\r
-`}return this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.kind=this.kind,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.kind=e.kind},t}(pt);R.a.RegisteredTypes["BABYLON.WaveBlock"]=$h;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}(),ed=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.colorSteps=[new va(0,M.a.Black()),new va(1,M.a.White())],n.onValueChangedObservable=new x.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"]=ed;var td=function(r){function t(e){var n=r.call(this,e,xe.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"]=td;var nd=function(r){function t(e){var n=r.call(this,e,xe.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"]=nd;var id=function(r){function t(e){var n=r.call(this,e,xe.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"]=id;var rd=function(r){function t(e){var n=r.call(this,e,xe.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"]=rd;var od=function(r){function t(e){var n=r.call(this,e,xe.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"]=od;var ad=function(r){function t(e){var n=r.call(this,e,xe.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"]=ad;var sd=function(r){function t(e){var n=r.call(this,e,xe.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"]=sd;var cd=function(r){function t(e){var n=r.call(this,e,xe.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"]=cd;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?li.Compatible:li.TypeIncompatible},t.prototype.createCustomInputBlock=function(){return[new this._blockType(this._blockName),this.name]},t}(da),_c=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.albedoScaling=!1,n.linkSheenWithAlbedo=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!0,xe.Fragment),n.registerInput("color",le.Color3,!0,xe.Fragment),n.registerInput("roughness",le.Float,!0,xe.Fragment),n.registerOutput("sheen",le.Object,xe.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===xe.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"]=_c;var mc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("intensity",le.Float,!0,xe.Fragment),n.registerInput("direction",le.Vector2,!0,xe.Fragment),n.registerInput("uv",le.Vector2,!0),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("anisotropy",le.Object,xe.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===xe.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.AnisotropyBlock"]=mc;var gc=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,xe.Vertex),n.registerInput("world",le.Matrix,!1,xe.Vertex),n.registerInput("color",le.Color3,!0,xe.Fragment),n.registerOutput("reflection",le.Object,xe.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!==xe.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}(dc);R.a.RegisteredTypes["BABYLON.ReflectionBlock"]=gc;var ba=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.remapF0OnInterfaceChange=!0,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,xe.Fragment),n.registerInput("roughness",le.Float,!0,xe.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,xe.Fragment),n.registerInput("normalMapColor",le.Color3,!0,xe.Fragment),n.registerInput("uv",le.Vector2,!0,xe.Fragment),n.registerInput("tintColor",le.Color3,!0,xe.Fragment),n.registerInput("tintAtDistance",le.Float,!0,xe.Fragment),n.registerInput("tintThickness",le.Float,!0,xe.Fragment),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("clearcoat",le.Object,xe.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",xe.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===xe.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 vc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.linkRefractionWithTransparency=!1,n.invertRefractionY=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,xe.Fragment),n.registerInput("tintAtDistance",le.Float,!0,xe.Fragment),n.registerOutput("refraction",le.Object,xe.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",xe.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=ai.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"]=vc;var ya=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("thickness",le.Float,!1,xe.Fragment),n.registerInput("tintColor",le.Color3,!0,xe.Fragment),n.registerInput("translucencyIntensity",le.Float,!0,xe.Fragment),n.registerInput("translucencyDiffusionDist",le.Color3,!0,xe.Fragment),n.registerInput("refraction",le.Object,!0,xe.Fragment,new Zn("refraction",n,Tn.Input,vc,"RefractionBlock")),n.registerOutput("subsurface",le.Object,xe.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",xe.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.",Ce=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(`+Ce+", "+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===xe.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.SubSurfaceBlock"]=ya;var hm={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",""]},ld=function(r){function t(e){var n=r.call(this,e,xe.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,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("view",le.Matrix,!1),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("perturbedNormal",le.Vector4,!0,xe.Fragment),n.registerInput("baseColor",le.Color3,!0,xe.Fragment),n.registerInput("metallic",le.Float,!1,xe.Fragment),n.registerInput("roughness",le.Float,!1,xe.Fragment),n.registerInput("ambientOcc",le.Float,!0,xe.Fragment),n.registerInput("opacity",le.Float,!0,xe.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,xe.Fragment),n.registerInput("ambientColor",le.Color3,!0,xe.Fragment),n.registerInput("reflection",le.Object,!0,xe.Fragment,new Zn("reflection",n,Tn.Input,gc,"ReflectionBlock")),n.registerInput("clearcoat",le.Object,!0,xe.Fragment,new Zn("clearcoat",n,Tn.Input,ba,"ClearCoatBlock")),n.registerInput("sheen",le.Object,!0,xe.Fragment,new Zn("sheen",n,Tn.Input,_c,"SheenBlock")),n.registerInput("subsurface",le.Object,!0,xe.Fragment,new Zn("subsurface",n,Tn.Input,ya,"SubSurfaceBlock")),n.registerInput("anisotropy",le.Object,!0,xe.Fragment,new Zn("anisotropy",n,Tn.Input,mc,"AnisotropyBlock")),n.registerOutput("ambientClr",le.Color3,xe.Fragment),n.registerOutput("diffuseDir",le.Color3,xe.Fragment),n.registerOutput("specularDir",le.Color3,xe.Fragment),n.registerOutput("clearcoatDir",le.Color3,xe.Fragment),n.registerOutput("sheenDir",le.Color3,xe.Fragment),n.registerOutput("diffuseInd",le.Color3,xe.Fragment),n.registerOutput("specularInd",le.Color3,xe.Fragment),n.registerOutput("clearcoatInd",le.Color3,xe.Fragment),n.registerOutput("sheenInd",le.Color3,xe.Fragment),n.registerOutput("refraction",le.Color3,xe.Fragment),n.registerOutput("lighting",le.Color3,xe.Fragment),n.registerOutput("shadow",le.Float,xe.Fragment),n.registerOutput("alpha",le.Float,xe.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,Ce,Ne,Ie,Fe,Ye,tt,it,lt,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!==xe.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:(Ce=Ve?._defineLinearSpecularReflection)!==null&&Ce!==void 0?Ce:"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:(lt=Ve?._defineOppositeZ)!==null&&lt!==void 0?lt:"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=hm[Ln.name];if(qt){var hi=qt[0],Ri=qt[1];Ri&&(e.compilationString+="#if "+Ri+`\r
-`),e.compilationString+=this._declareOutput(Ln,e)+" = "+hi+`;\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"]=ld;var ud=function(r){function t(e){var n=r.call(this,e,xe.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"]=ud;var dm=function(){function r(){}return r.prototype.optimize=function(t,e){},r}(),fm=f(120),pm=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}(),_m=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 pm,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:fm.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}(),hd=f(101);function bc(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 mm(){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){bc(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 dd(r){return typeof document!="object"||typeof r!="string"?r:Xe.b.GetAbsoluteUrl(r)}var gm=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(dd(e.wasmBinaryUrl))}:{url:e.fallbackUrl,wasmBinaryPromise:Promise.resolve(void 0)};t&&typeof Worker=="function"?this._workerPoolPromise=n.wasmBinaryPromise.then(function(i){for(var o=bc+"("+mm+")()",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:dd(n.url),wasmBinary:i}})});return Promise.all(s).then(function(p){return new Bs(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 bc(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),fd=0,vm=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}(),bm=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 yc(O,t.shared)).plane&&i.push(P),B.length>=3&&(P=new yc(B,t.shared)).plane&&o.push(P)}},r.EPSILON=1e-5,r}(),yc=function(){function r(t,e){this.vertices=t,this.shared=e,this.plane=bm.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}(),ym=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 vm(i,n,P,O),a.push(e)}(o=new yc(a,{subMeshId:fe,meshId:fd,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,fd++,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(lt,Qe){return lt.shared.meshId===Qe.shared.meshId?lt.shared.subMeshId-Qe.shared.subMeshId:lt.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),Ce=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]!==Ce.x||P[3*a+1]!==Ce.y||P[3*a+2]!==Ce.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}(),Tm=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),Em=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 Ce=0;Ce<Ee/3;Ce++)Te[O].push(new u.e(J[O].positions[3*Ce],J[O].positions[3*Ce+1],J[O].positions[3*Ce+2])),Re[O].push(new u.e(J[O].normals[3*Ce],J[O].normals[3*Ce+1],J[O].normals[3*Ce+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 lt=u.a.RotationY(Math.PI/2);se=se.concat(Te[3].map(function(Ve){return u.e.TransformNormal(Ve,lt).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,lt)}).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 pd=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,lt=s*(2+tt)*Fe*.5,Qe=s*Math.sin(Ye)*.5;return new u.e(it,lt,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 Ce=new ft.a;return Ce.indices=n,Ce.positions=i,Ce.normals=o,Ce.uvs=a,Ce},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 Tc.CreateTorusKnot(r,b,s)};var Tc=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}(),Sm=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),Ec=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 Sm(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}(),Am=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}(),_d=function(){function r(t,e,n,i){var o;i===void 0&&(i=earcut),this._points=new Ec,this._outlinepoints=new Ec,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 Ec;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 _d(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 Sc.CreateLathe(r,s,i)};var Sc=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 Ce,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),lt=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=[Ce=1-d/e,Ne=1-P/n,Ie=1,Ne,Ie,Fe=1,Ce,Fe],t===De.a.ROTATE_ROW&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t===De.a.FLIP_ROW&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t===De.a.FLIP_N_ROTATE_ROW&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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&&lt&&(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=[Ce=0,Ne=1-P/n,Ie=d/e,Ne,Ie,Fe=1,Ce,Fe],(t===De.a.ROTATE_ROW||t===De.a.ROTATE_TILE&&s%2==0)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW||t===De.a.FLIP_TILE&&s%2==0)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW||t===De.a.FLIP_N_ROTATE_TILE&&s%2==0)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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=[Ce=1-d/e,Ne=0,Ie=1,Ne,Ie,Fe=P/n,Ce,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&b%1==0)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&b%2==0)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&b%2==0)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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&&lt&&(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=[Ce=0,Ne=0,Ie=d/e,Ne,Ie,Fe=P/n,Ce,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&(b+s)%2==1)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&(b+s)%2==1)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&(b+s)%2==1)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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(Ce=0,Ne=1-P/n,Ie=1,Fe=1,ot[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],ot[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(ot[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(ot[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(ot[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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(Ce=0,Ne=0,Ie=1,Fe=P/n,rt[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],rt[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(rt[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(rt[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(rt[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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(Ce=1-d/e,Ne=0,Ie=1,Fe=1,Ze[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],Ze[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(Ze[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(Ze[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(Ze[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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(lt){var dt=[];for(Ce=0,Ne=0,Ie=d/n,Fe=1,dt[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],dt[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(dt[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(dt[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(dt[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,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 md=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 Ac.CreateTube(r,b,a)};var Ac=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,Ce,Ne,Ie=ue.getTangents(),Fe=ue.getNormals(),Ye=ue.getDistances(),tt=2*Math.PI/Te*Ee,it=Re||function(){return ve},lt=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(),Ce=Fe[ot];for(var rt=0;rt<Te;rt++)u.a.RotationAxisToRef(Ie[ot],tt*rt,lt),Ne=Se[rt]?Se[rt]:u.e.Zero(),u.e.TransformCoordinatesToRef(Ce,lt,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,Ce,Ne,Ie){var Fe,Ye=u.e.Lerp(ue[0],ue[2],Ce/o),tt=u.e.Lerp(ue[1],ue[2],Ce/o),it=o===Ce?ue[2]:u.e.Lerp(Ye,tt,Le/(o-Ce));if(it.normalize(),i){var lt=u.e.Lerp(ue[0],ue[2],Ie/o),Qe=u.e.Lerp(ue[1],ue[2],Ie/o);Fe=u.e.Lerp(lt,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],Ce/o),rt=u.d.Lerp(fe[1],fe[2],Ce/o),Ze=o===Ce?fe[2]:u.d.Lerp(ot,rt,Le/(o-Ce));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 Pc.CreateIcoSphere(r,t,e)};var Pc=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 Cc.CreateDecal(r,t,a)};var Cc=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(Ce){var Ne=new Is;if(!i||!o||!a)return Ne;var Ie=i[Ce];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(Ce,Ne){if(Ce.length===0)return Ce;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 Is(u.e.Lerp(Ve.position,Je.position,yt),u.e.Lerp(Ve.normal,Je.normal,yt))},Ye=new Array,tt=0;tt<Ce.length;tt+=3){var it,lt,Qe,ot=null,rt=null,Ze=null,dt=null;switch(((it=u.e.Dot(Ce[tt].position,Ne)-Ie>0)?1:0)+((lt=u.e.Dot(Ce[tt+1].position,Ne)-Ie>0)?1:0)+((Qe=u.e.Dot(Ce[tt+2].position,Ne)-Ie>0)?1:0)){case 0:Ye.push(Ce[tt]),Ye.push(Ce[tt+1]),Ye.push(Ce[tt+2]);break;case 1:if(it&&(ot=Ce[tt+1],rt=Ce[tt+2],Ze=Fe(Ce[tt],ot),dt=Fe(Ce[tt],rt)),lt){ot=Ce[tt],rt=Ce[tt+2],Ze=Fe(Ce[tt+1],ot),dt=Fe(Ce[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=Ce[tt],rt=Ce[tt+1],Ze=Fe(Ce[tt+2],ot),dt=Fe(Ce[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=Ce[tt].clone(),Ce[tt+1]),Ze=Fe(ot,Ce[tt+2]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),lt||(rt=Fe(ot=Ce[tt+1].clone(),Ce[tt+2]),Ze=Fe(ot,Ce[tt]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),Qe||(rt=Fe(ot=Ce[tt+2].clone(),Ce[tt]),Ze=Fe(ot,Ce[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),Ce=new u.d(b*Le,Te+b*Se).subtract(new u.d(P*Le,P*Se-Te)).length(),Ne=b*J+Ce+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),lt=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=lt*ot,Ee.y=Te+it*b,Ee.z=lt*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+=Ce/p,lt=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=lt*ot,Ee.y=Te+Se*b-e*Ze/p,Ee.z=lt*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),lt=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=lt*ot,Ee.y=it*P-Te,Ee.z=lt*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 xc.CreateCapsule(r,t,e)};var Co,xc=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}(),Pm=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),pd.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),Pc.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),Tc.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),Sc.CreateLathe(t,e,n)},r.CreateTiledPlane=function(t,e,n){return n===void 0&&(n=null),md.CreateTiledPlane(t,e,n)},r.CreatePlane=function(t,e,n){return n===void 0&&(n=null),Rs.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),Ac.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 Cc.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),xc.CreateCapsule(t,e,n)},r}(),Cm=function(r,t,e){this.quality=r,this.distance=t,this.optimizeMesh=e},gd=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 Co.QUADRATIC:default:return new bd(t.mesh)}},r}();(function(r){r[r.QUADRATIC=0]="QUADRATIC"})(Co||(Co={}));var xm=function(r){this.vertices=r,this.error=new Array(4),this.deleted=!1,this.isDirty=!1,this.deletePending=!1,this.borderFactor=0},Rm=function(){function r(t,e){this.position=t,this.id=e,this.isBorder=!0,this.q=new vd,this.triangleCount=0,this.triangleStart=0,this.originalOffsets=[]}return r.prototype.updatePosition=function(t){this.position.copyFrom(t)},r}(),vd=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}(),Om=function(r,t){this.vertexId=r,this.triangleId=t},bd=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 Rm(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 xm([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(vd.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 Om(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 gd;var r=this._getComponent(at.a.NAME_SIMPLIFICATIONQUEUE);r||(r=new yd(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=Co.QUADRATIC),this.getScene().simplificationQueue.addTask({settings:r,parallelProcessing:t,mesh:this,simplificationType:e,successCallback:n}),this};var yd=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}(),Mm=f(149),Im=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 Dm=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 Td(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}(),Td=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 Ed(r,t,e)};var Fr,Ed=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}(),Rc=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}(),Sd=function(r,t){this.gradient=r,this.color=t},Oc=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}(),Ad=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 xo=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}(),Lm=`
-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=Lm;var Nm=`
-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=Nm;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 x.c,d.onStoppedObservable=new x.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 Ad(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),Ce=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.x=Le,O.remapData.y=Ce-Le}),d._alphaRemapGradients&&d._alphaRemapGradients.length>0&&In.GetCurrentGradient(se,d._alphaRemapGradients,function(Ae,Ee,Se){var Le=$.a.Lerp(Ae.factor1,Ee.factor1,Se),Ce=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.z=Le,O.remapData.w=Ce-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 x.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 Oc(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=ii.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 Sd(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 Rc(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 xo(n)]):n instanceof xo?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)&&eh.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 Ce=0,Ne=Le;Ce<Ne.length;Ce++){var Ie=Ne[Ce];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 lt=n.getDragGradients();if(lt){e.dragGradients=[];for(var Qe=0,ot=lt;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 Ce=Le[Se];n.addAngularSpeedGradient(Ce.gradient,Ce.factor1!==void 0?Ce.factor1:Ce.factor,Ce.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 lt=0,Qe=e.emitRateGradients;lt<Qe.length;lt++){var ot=Qe[lt];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 cc;break;case"ConeEmitter":case"ConeParticleEmitter":s=new rc;break;case"CylinderParticleEmitter":s=new _a;break;case"CylinderDirectedParticleEmitter":s=new oc;break;case"HemisphericParticleEmitter":s=new ac;break;case"PointParticleEmitter":s=new sc;break;case"MeshParticleEmitter":s=new hh;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(xo.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);xo._ParseParticleSystem=ln.Parse,ze.a.ShadersStore.gpuUpdateParticlesPixelShader=`#version 300 es
-void main() {
-discard;
-}
-`;var wm=`#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=wm;var Fm=`#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=Fm;var Bm=`#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=Bm;var Um=`#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=Um;var Vm=`#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=Vm;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 x.c,s.onStoppedObservable=new x.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 ii(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 ii(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 x.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 Rc(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 Oc(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]=ii.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=ii.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}(),km=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,Mc=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?Zl.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}(),Ic=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},Pd=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},Cd=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}(),Gm=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 Mc(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 Cd}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,Ce=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<Ce.length;Se++)ce.addInPlace(Ce[Se]);ce.scaleInPlace(1/Ce.length);var tt,it=new u.e(1/0,1/0,1/0),lt=new u.e(-1/0,-1/0,-1/0);for(Se=0;Se<Ce.length;Se++)Ce[Se].subtractInPlace(ce),it.minimizeInPlaceFromFloats(Ce[Se].x,Ce[Se].y,Ce[Se].z),lt.maximizeInPlaceFromFloats(Ce[Se].x,Ce[Se].y,Ce[Se].z);this._particlesIntersect&&(tt=new Vi.a(it,lt));var Qe=null;this._useModelMaterial&&(Qe=t.material?t.material:this._setDefaultMaterial());var ot=new Ic(this._shapeCounter,Ce,Ie,Ye,Fe,Ne,null,null,Qe),rt=this._positions.length,Ze=this._indices.length;this._meshBuilder(this._index,Ze,Ce,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+=Ce.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,Ce=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&&Ce.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(Ce);else{var lt=this._color;p&&p[ce]!==void 0?(lt.r=p[ce],lt.g=p[ce+1],lt.b=p[ce+2],lt.a=p[ce+3]):(lt.r=1,lt.g=1,lt.b=1,lt.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 Pd(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 Mc(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 Ic(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,Ce=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 lt=t;lt<=e;lt++){var Qe=this.particles[lt];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[lt];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,Ce=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,hi=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,hi,Ri),ce.maximizeInPlaceFromFloats(qt,hi,Ri)),!this._computeParticleVertex){var Gr=B[Se],zr=B[Se+1],di=B[Se+2],Hi=Gr*Ze[0]+zr*Ze[3]+di*Ze[6],jr=Gr*Ze[1]+zr*Ze[4]+di*Ze[7],jt=Gr*Ze[2]+zr*Ze[5]+di*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[Ce]=Te.r,Wi[Ce+1]=Te.g,Wi[Ce+2]=Te.b,Wi[Ce+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(Ce=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[Ce]=lr.r,s[Ce+1]=lr.g,s[Ce+2]=lr.b,s[Ce+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]),Sv=Io.addToRef(hr,F[2]);Ga.reConstruct(Do,Sv,a._worldMatrix)}Le=Se+3,Ne=Ce+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 Av=a.isFacetDataEnabled?a.getFacetDataParameters():null;ft.a.ComputeNormals(d,P,p,Av);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 el=this.depthSortedParticles;el.sort(this._depthSortFunction);for(var Pv=el.length,yf=0,tl=0,nl=0;nl<Pv;nl++){var il=el[nl],Cv=il.indicesLength,xv=il.ind;for(Ii=0;Ii<Cv;Ii++)if(P[yf]=O[xv+Ii],yf++,this._pickable&&Ii%3==0){var Tf=this.pickedParticles[tl];Tf.idx=il.idx,Tf.faceId=tl,tl++}}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}(),xd=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 zm=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 xd(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,Ce=0,Ne=0,Ie=0,Fe=u.e.Zero(),Ye=u.e.Zero(),tt=u.e.Zero(),it=u.e.Zero(),lt=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,$n=0,Ln=0,qt=u.f.Zero(),hi=u.f.Zero(),Ri=u.f.Zero(),Gr=u.f.Zero(),zr=u.f.Zero(),di=0,Hi=0;s=s||0;var jr,jt=new u.f(0,0,0,0),Wi=u.e.Zero(),Sn=u.e.Zero(),lr=u.e.Zero(),Oi=0,ka=u.e.Zero(),Ga=0,Hr=0,Xi=new fn.a(u.e.Zero(),new u.e(1,0,0)),Yi=u.e.Zero();for(ce=0;ce<b.length/3;ce++){var ur,Ki,Wr,Xr,Yr,Qi,qi,Kr;ue=b[3*ce],fe=b[3*ce+1],ve=b[3*ce+2],Te=p[3*ue],Re=p[3*ue+1],Ae=p[3*ue+2],Ee=p[3*fe],Se=p[3*fe+1],Le=p[3*fe+2],Ce=p[3*ve],Ne=p[3*ve+1],Ie=p[3*ve+2],Fe.set(Te,Re,Ae),Ye.set(Ee,Se,Le),tt.set(Ce,Ne,Ie),Ye.subtractToRef(Fe,it),tt.subtractToRef(Ye,lt),P&&(Qe=P[2*ue],ot=P[2*ue+1],rt=P[2*fe],Ze=P[2*fe+1],dt=P[2*ve],Ve=P[2*ve+1],Je.set(Qe,ot),yt.set(rt,Ze),Wt.set(dt,Ve),yt.subtractToRef(Je,Nt),Wt.subtractToRef(yt,Qt)),O&&i&&(vt=O[4*ue],Jt=O[4*ue+1],Xt=O[4*ue+2],zt=O[4*ue+3],Yt=O[4*fe],Et=O[4*fe+1],Mt=O[4*fe+2],$t=O[4*fe+3],Dn=O[4*ve],Vn=O[4*ve+1],$n=O[4*ve+2],Ln=O[4*ve+3],qt.set(vt,Jt,Xt,zt),hi.set(Yt,Et,Mt,$t),Ri.set(Dn,Vn,$n,Ln),hi.subtractToRef(qt,Gr),Ri.subtractToRef(hi,zr));for(var Mi,Nn,Io=new M.a(0,0,0),hr=new M.a(0,0,0),Do=0;Do<e._groupDensity[ce];Do++)se=this.particles.length,this._addParticle(se,e,this._groupCounter,ce+Do),Nn=this.particles[se],di=$.a.RandomRange(0,1),Hi=$.a.RandomRange(0,1),J=Fe.add(it.scale(di)).add(lt.scale(di*Hi)),n&&(Wi=t.getFacetNormal(ce).normalize().scale(-1),Sn=it.clone().normalize(),lr=u.e.Cross(Wi,Sn),Oi=$.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(di)).add(Qt.scale(di*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(di)).add(zr.scale(di*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,Ce=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,Ce+=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]/Ce),Fe+=fe[Ie];var Ye=t-Fe,tt=Math.floor(Ye/Ne),it=Ye%Ne;for(tt>0&&(fe=fe.map(function(lt){return lt+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],Ce=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+Ce,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,lt=Ye.z-fe.pivot.z,Qe=tt*ve[0]+it*ve[3]+lt*ve[6],ot=tt*ve[1]+it*ve[4]+lt*ve[7],rt=tt*ve[2]+it*ve[5]+lt*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 Rd(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,Rd=function(){function r(t){var e=this;this.name=at.a.NAME_PHYSICSENGINE,this.scene=t,this.scene.onBeforePhysicsObservable=new x.c,this.scene.onAfterPhysicsObservable=new x.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}(),jm=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 Od(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 Od(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 Hm(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 Dc).radius=e,e.strength=n||e.strength,e.height=i||e.height,e.updraftMode=o||e.updraftMode);var a=new Wm(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 Lc).radius=e,e.strength=n||e.strength,e.height=i||e.height);var o=new Xm(this._scene,t,e);return o.dispose(!1),o},r}(),Od=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}(),Hm=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}(),Wm=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 Dc),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}(),Xm=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 Lc),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}},Dc=function(){this.radius=5,this.strength=10,this.height=10,this.updraftMode=Br.Center},Lc=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 Ym=`
-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=Ym;var Md=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"]=Md;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}(),Km=`#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=Km;var Nc=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"]=Nc;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 wc=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"]=wc;var Fc=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 Nc("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 wc("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),qm=`
-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=qm;var Bc=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"]=Bc;var Zm=`
-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=Zm;var Uc=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"]=Uc;var Jm=`
-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=Jm;var Id=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"]=Id;var $m=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 screenSize;
-uniform float kernel[9];
-void main(void)
-{
-vec2 onePixel=vec2(1.0,1.0)/screenSize;
-vec4 colorSum =
-texture2D(textureSampler,vUV+onePixel*vec2(-1,-1))*kernel[0] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,-1))*kernel[1] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,-1))*kernel[2] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,0))*kernel[3] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,0))*kernel[4] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,0))*kernel[5] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,1))*kernel[6] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,1))*kernel[7] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,1))*kernel[8];
-float kernelWeight =
-kernel[0] +
-kernel[1] +
-kernel[2] +
-kernel[3] +
-kernel[4] +
-kernel[5] +
-kernel[6] +
-kernel[7] +
-kernel[8];
-if (kernelWeight<=0.0) {
-kernelWeight=1.0;
-}
-gl_FragColor=vec4((colorSum/kernelWeight).rgb,1);
-}`;ze.a.ShadersStore.convolutionPixelShader=$m;var Dd=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"]=Dd;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 eg=`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=eg;var sr,tg=function(){},Ld=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 Vc=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 Uc("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 Ld("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),ng=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D passSampler;
-void main(void)
-{
-gl_FragColor=texture2D(passSampler,vUV);
-}`;ze.a.ShadersStore.displayPassPixelShader=ng;var Nd=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"]=Nd;var ig=`
-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=ig;var wd=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"]=wd;var rg=`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=rg;var og=`
-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=og;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 ag=`#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=ag;var kc=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"]=kc;var sg=`
-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=sg;var cg=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 lg=`#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=lg;var ug=`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=ug;var ui=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 qs("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}(),hg=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 ui(this,r),this._geometryBufferRenderer.isSupported||(this._geometryBufferRenderer=null)),this._geometryBufferRenderer},_e.a.prototype.disableGeometryBufferRenderer=function(){this._geometryBufferRenderer&&(this._geometryBufferRenderer.dispose(),this._geometryBufferRenderer=null)};var Fd=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}();ui._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_GEOMETRYBUFFERRENDERER);t||(t=new Fd(r),r._addComponent(t))};var dg=`
-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=dg;var Gc=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 hg)),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(ui.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(ui.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"]=Gc;var fg=`
-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=fg;var Bd=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"]=Bd;var pg=`
-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=pg;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,"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"]=zc;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}(),Ud=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 Vd(this),this._addComponent(r)),this._postProcessRenderPipelineManager=new Ud}return this._postProcessRenderPipelineManager},enumerable:!0,configurable:!0});var Vd=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}(),kd=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 x.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 zc("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 Vc(s._scene,null,s._depthOfFieldBlurLevel,s._defaultPipelineTextureType,!0),s.bloom=new Fc(s._scene,s._bloomScale,s._bloomWeight,s.bloomKernel,s._defaultPipelineTextureType,!0),s.chromaticAberration=new Bc("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 kc("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 Fc(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 Vc(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"]=kd;var _g=`
-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=_g;var mg=`
-
-
-
-
-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=mg;var gg=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),vg=function(){this.enabled=!1,this.name="ssao2",this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE]},bg=`
-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=bg;var yg=`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=yg;var Gd=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 vg)},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"]=Gd;var Tg=`
-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=Tg;var Eg=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),Sg=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]},Ag=`
-
-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=Ag;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,"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 Sg;return O._updateEffectDefines(),O.onApply=function(F){var z=O._geometryBufferRenderer,J=O._prePassRenderer;if(J||z){if(z){var ie=z.getTextureIndex(ui.POSITION_TEXTURE_TYPE),se=z.getTextureIndex(ui.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"]=jc;var Pg=`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=Pg;var zd=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 jc("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 Gc("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"]=zd;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 xg=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),Rg=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),Og=`
-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=Og;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 Mg=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),Ig=`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=Ig;var Dg=`
-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=Dg;var Lg=`#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=Lg;var jd=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"]=jd;var Ng=`
-
-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=Ng;var Hd=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"]=Hd,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 Wd(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 Wd=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 x.c,this.onAfterBoxRenderingObservable=new x.c,this.onResourcesReadyObservable=new x.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 Xd=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 Xd(r),r._addComponent(t))},ze.a.ShadersStore.linePixelShader=`uniform vec4 color;
-void main(void) {
-gl_FragColor=color;
-}`;var wg=`#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=wg,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 Hc(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 Yd(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 Fg=function(){this.edges=new Array,this.edgesConnectedCount=0},Hc=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=[],Ce=0;Ce<P.length;Ce+=3)for(var Ne=void 0,Ie=0;Ie<3;++Ie){var Fe=F[P[Ce+Ie]],Ye=F[P[Ce+(Ie+1)%3]],tt=F[P[Ce+(Ie+2)%3]];if(Fe!==Ye)for(var it=b[3*Fe+0],lt=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-lt)*(rt-lt)+(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-lt)*(Wt-lt)+(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:Ce,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(Ce=0;Ce<P.length;Ce+=3){var Yt=void 0;for(Ie=0;Ie<3;++Ie)if(Fe=F[P[Ce+Ie]],Ye=F[P[Ce+(Ie+1)%3]],tt=F[P[Ce+(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:Ce,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 Fg;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}(),Yd=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}(Hc),Wc=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 qs("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:ui.DEPTHNORMAL_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_POSITION_TEXTURE_TYPE,geometryBufferConstant:ui.POSITION_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,geometryBufferConstant:ui.REFLECTIVITY_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_VELOCITY_TEXTURE_TYPE,geometryBufferConstant:ui.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 Wc(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 Kd=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}();Wc._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_PREPASSRENDERER);t||(t=new Kd(r),r._addComponent(t))};var Bg=`#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=Bg;var Ug=`uniform vec3 diffusionS[5];
-uniform float diffusionD[5];
-uniform float filterRadii[5];`;ze.a.IncludesShadersStore.diffusionProfile=Ug;var Vg=`
-#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=Vg;var kg=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),Qd=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 kg("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 Qd(this),r.addEffectConfiguration(this._subSurfaceConfiguration),this._subSurfaceConfiguration):null},_e.a.prototype.disableSubSurfaceForPrePass=function(){this._subSurfaceConfiguration&&(this._subSurfaceConfiguration.dispose(),this._subSurfaceConfiguration=null)};var qd=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}();Qd._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_SUBSURFACE);t||(t=new qd(r),r._addComponent(t))};var Gg=`#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=Gg;var zg=`
-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=zg,_e.a.prototype.getOutlineRenderer=function(){return this._outlineRenderer||(this._outlineRenderer=new Zd(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 Zd=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}(),jg=f(148),Jd=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 x.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 $d=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 x.c,this.scene.onAfterSpritesRenderingObservable=new x.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 Hg=`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=Hg;var Wg=`
-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=Wg;var Xg=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}(),ef=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 x.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 $d(o)),this._fromPacked=d,this._scene=o;var P=this._scene.getEngine();if(this._spriteRenderer=new Xg(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];Jd.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}(),Yg=`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=Yg;var Kg=`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=Kg;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 ii.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 ii.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 ii.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}(),qg=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}(ef),Zg=f(143),Jg=f(141),$g=f(142),ev=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 Xc,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}(),tf=function(r,t,e){this.remainingCount=r,this.totalCount=t,this.task=e},nf=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),rf=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),of=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),af=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),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,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),cf=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),lf=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 ai(this.url,e,this.extensions,this.noMipmap,this.files,function(){n()},function(o,a){i(o,a)})},t}(gi),uf=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),hf=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 rh(this.url,e,this.size,this.noMipmap,this.gammaSpace,function(){n()},function(o,a){i(o,a)})},t}(gi),tv=function(){function r(t){this._isLoading=!1,this._tasks=new Array,this._waitingTasksCount=0,this._totalTasksCount=0,this.onTaskSuccessObservable=new x.c,this.onTaskErrorObservable=new x.c,this.onTasksDoneObservable=new x.c,this.onProgressObservable=new x.c,this.useDefaultLoadingScreen=!0,this.autoHideLoadingUI=!0,this._scene=t}return r.prototype.addContainerTask=function(t,e,n,i){var o=new nf(t,e,n,i);return this._tasks.push(o),o},r.prototype.addMeshTask=function(t,e,n,i){var o=new rf(t,e,n,i);return this._tasks.push(o),o},r.prototype.addTextFileTask=function(t,e){var n=new of(t,e);return this._tasks.push(n),n},r.prototype.addBinaryFileTask=function(t,e){var n=new af(t,e);return this._tasks.push(n),n},r.prototype.addImageTask=function(t,e){var n=new sf(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 cf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.addCubeTextureTask=function(t,e,n,i,o){var a=new lf(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 uf(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 hf(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 tf(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}(),nv=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}(),iv=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}(),rv=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 As.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}(),df=f(146),ov=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),Yc=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),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 shadows on/off"},t.prototype.apply=function(e,n){return e.shadowsEnabled=n.isInImprovementMode,!0},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 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),ff=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),Kc=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),Qc=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 ff(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 Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(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 Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,512)),n++,e.addOptimization(new Kc(n)),n++,e.addOptimization(new Yc(n,2)),e},r.HighDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,256)),n++,e.addOptimization(new Kc(n)),n++,e.addOptimization(new Yc(n,4)),e},r}(),av=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 x.c,this.onNewOptimizationAppliedObservable=new x.c,this.onFailureObservable=new x.c,this._options=e||new Qc,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 pv=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}(),_f=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}(),Jc=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}(),mf=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 Jc.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}(),_v=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=_f.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],mf.Deserialize(e.nameToDescribedTrajectory[i+1],n._levenshteinAlphabet));return n},r.Generate=function(){for(var t=_f.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 mf),this._nameToDescribedTrajectory.get(e).add(Jc.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=Jc.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}(),mv=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 x.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=si.HIT_TEST,t.Version=1,t}(ci);qn.AddWebXRFeature(Da.Name,function(r,t){return function(){return new Da(r,t)}},Da.Version,!1);var gv=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 x.c,i.onAnchorRemovedObservable=new x.c,i.onAnchorUpdatedObservable=new x.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:gv++,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=si.ANCHOR_SYSTEM,t.Version=1,t}(ci);qn.AddWebXRFeature(La.Name,function(r,t){return function(){return new La(r,t)}},La.Version);var vv=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 x.c,i.onPlaneRemovedObservable=new x.c,i.onPlaneUpdatedObservable=new x.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:vv++,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=si.PLANE_DETECTION,t.Version=1,t}(ci);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 x.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=si.BACKGROUND_REMOVER,t.Version=1,t}(ci);qn.AddWebXRFeature(wa.Name,function(r,t){return function(){return new wa(r,t)}},wa.Version,!0);var bv=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 Ct.a(P.rootMesh,Ct.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||Ct.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 Ct.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:Ct.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 Ct.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=si.PHYSICS_CONTROLLERS,t.Version=1,t}(ci);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 x.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=si.HIT_TEST,t.Version=2,t}(ci);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 x.c,n.onFeaturePointsUpdatedObservable=new x.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=si.FEATURE_POINTS,t.Version=1,t}(ci);qn.AddWebXRFeature(Ua.Name,function(r){return function(){return new Ua(r)}},Ua.Version);var gf=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 x.c,i.onHandRemovedObservable=new x.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:Ct.a.SphereImpostor;ue.physicsImpostor=new Ct.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 gf(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=si.HAND_TRACKING,t.Version=1,t}(ci);qn.AddWebXRFeature(Va.Name,function(r,t){return function(){return new Va(r,t)}},Va.Version,!1);var vf=function(r){function t(e,n,i){var o=r.call(this,e,yv["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 vf(t,r.gamepad,r.handedness)});var yv={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"}},$c=function(r){function t(e,n,i,o,a){a===void 0&&(a=!1);var s=r.call(this,e,Tv[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 $c(t,r.gamepad,r.handedness)}),Bn.RegisterController("oculus-touch-legacy",function(r,t){return new $c(t,r.gamepad,r.handedness,!0)});var Tv={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"}},bf=function(r){function t(e,n,i){var o=r.call(this,e,Ev[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 bf(t,r.gamepad,r.handedness)});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-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)
-{
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-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(x,u){return(x=x.match(/\([^\(\)]*\)/g)?x.replace(/\([^\(\)]*\)/g,function(M){return M=M.slice(1,M.length-1),_._HandleParenthesisContent(M,u)}):_._HandleParenthesisContent(x,u))==="true"||x!=="false"&&_.Eval(x,u)},_._HandleParenthesisContent=function(x,u){var M;u=u||function(S){return S==="true"};var R=x.split("||");for(var C in R)if(R.hasOwnProperty(C)){var m=_._SimplifyNegation(R[C].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(x){return(x=(x=x.replace(/^[\s!]+/,function(u){return(u=u.replace(/[\s]/g,function(){return""})).length%2?"!":""})).trim())==="!true"?x="false":x==="!false"&&(x="true"),x},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.ExponentialBackoff=function(x,u){return x===void 0&&(x=3),u===void 0&&(u=500),function(M,R,C){return R.status!==0||C>=x||M.indexOf("file:")!==-1?-1:Math.pow(2,C)*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(x){this._zOffset!==x&&(this._zOffset=x,this._isZOffsetDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cullFace",{get:function(){return this._cullFace},set:function(x){this._cullFace!==x&&(this._cullFace=x,this._isCullFaceDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cull",{get:function(){return this._cull},set:function(x){this._cull!==x&&(this._cull=x,this._isCullDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthFunc",{get:function(){return this._depthFunc},set:function(x){this._depthFunc!==x&&(this._depthFunc=x,this._isDepthFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthMask",{get:function(){return this._depthMask},set:function(x){this._depthMask!==x&&(this._depthMask=x,this._isDepthMaskDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthTest",{get:function(){return this._depthTest},set:function(x){this._depthTest!==x&&(this._depthTest=x,this._isDepthTestDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"frontFace",{get:function(){return this._frontFace},set:function(x){this._frontFace!==x&&(this._frontFace=x,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(x){this.isDirty&&(this._isCullDirty&&(this.cull?x.enable(x.CULL_FACE):x.disable(x.CULL_FACE),this._isCullDirty=!1),this._isCullFaceDirty&&(x.cullFace(this.cullFace),this._isCullFaceDirty=!1),this._isDepthMaskDirty&&(x.depthMask(this.depthMask),this._isDepthMaskDirty=!1),this._isDepthTestDirty&&(this.depthTest?x.enable(x.DEPTH_TEST):x.disable(x.DEPTH_TEST),this._isDepthTestDirty=!1),this._isDepthFuncDirty&&(x.depthFunc(this.depthFunc),this._isDepthFuncDirty=!1),this._isZOffsetDirty&&(this.zOffset?(x.enable(x.POLYGON_OFFSET_FILL),x.polygonOffset(this.zOffset,0)):x.disable(x.POLYGON_OFFSET_FILL),this._isZOffsetDirty=!1),this._isFrontFaceDirty&&(x.frontFace(this.frontFace),this._isFrontFaceDirty=!1))},_}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){this._isStencilTestDirty=!1,this._isStencilMaskDirty=!1,this._isStencilFuncDirty=!1,this._isStencilOpDirty=!1,this.reset()}return Object.defineProperty(x.prototype,"isDirty",{get:function(){return this._isStencilTestDirty||this._isStencilMaskDirty||this._isStencilFuncDirty||this._isStencilOpDirty},enumerable:!1,configurable:!0}),Object.defineProperty(x.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(x.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(x.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(x.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(x.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(x.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(x.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(x.prototype,"stencilTest",{get:function(){return this._stencilTest},set:function(u){this._stencilTest!==u&&(this._stencilTest=u,this._isStencilTestDirty=!0)},enumerable:!1,configurable:!0}),x.prototype.reset=function(){this._stencilTest=!1,this._stencilMask=255,this._stencilFunc=x.ALWAYS,this._stencilFuncRef=1,this._stencilFuncMask=255,this._stencilOpStencilFail=x.KEEP,this._stencilOpDepthFail=x.KEEP,this._stencilOpStencilDepthPass=x.REPLACE,this._isStencilTestDirty=!0,this._isStencilMaskDirty=!0,this._isStencilFuncDirty=!0,this._isStencilOpDirty=!0},x.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))},x.ALWAYS=U.a.ALWAYS,x.KEEP=U.a.KEEP,x.REPLACE=U.a.REPLACE,x}()},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(x){this._alphaBlend!==x&&(this._alphaBlend=x,this._isAlphaBlendDirty=!0)},enumerable:!1,configurable:!0}),_.prototype.setAlphaBlendConstants=function(x,u,M,R){this._blendConstants[0]===x&&this._blendConstants[1]===u&&this._blendConstants[2]===M&&this._blendConstants[3]===R||(this._blendConstants[0]=x,this._blendConstants[1]=u,this._blendConstants[2]=M,this._blendConstants[3]=R,this._isBlendConstantsDirty=!0)},_.prototype.setAlphaBlendFunctionParameters=function(x,u,M,R){this._blendFunctionParameters[0]===x&&this._blendFunctionParameters[1]===u&&this._blendFunctionParameters[2]===M&&this._blendFunctionParameters[3]===R||(this._blendFunctionParameters[0]=x,this._blendFunctionParameters[1]=u,this._blendFunctionParameters[2]=M,this._blendFunctionParameters[3]=R,this._isBlendFunctionParametersDirty=!0)},_.prototype.setAlphaEquationParameters=function(x,u){this._blendEquationParameters[0]===x&&this._blendEquationParameters[1]===u||(this._blendEquationParameters[0]=x,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(x){this.isDirty&&(this._isAlphaBlendDirty&&(this._alphaBlend?x.enable(x.BLEND):x.disable(x.BLEND),this._isAlphaBlendDirty=!1),this._isBlendFunctionParametersDirty&&(x.blendFuncSeparate(this._blendFunctionParameters[0],this._blendFunctionParameters[1],this._blendFunctionParameters[2],this._blendFunctionParameters[3]),this._isBlendFunctionParametersDirty=!1),this._isBlendEquationParametersDirty&&(x.blendEquationSeparate(this._blendEquationParameters[0],this._blendEquationParameters[1]),this._isBlendEquationParametersDirty=!1),this._isBlendConstantsDirty&&(x.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(x){x&&this.program&&x(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=[]},x=function(){function M(R){var C=this;if(this._state=U.Pending,this._children=new Array,this._rejectWasConsumed=!1,R)try{R(function(m){C._resolve(m)},function(m){C._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,C){var m=this,c=new M;return c._onFulfilled=R,c._onRejected=C,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 C,m=this;if((C=this._children).push.apply(C,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 C=null;if(this._onFulfilled&&(C=this._onFulfilled(R)),C!=null)if(C._state!==void 0){var m=C;m._parent=this,m._moveChildren(this._children),R=m._result}else R=C;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,C){if(C===void 0&&(C=!1),this._state=U.Rejected,this._reason=R,this._onRejected&&!C)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 C=new M;return C._resolve(R),C},M._RegisterForFulfillment=function(R,C,m){R.then(function(c){return C.results[m]=c,C.count++,C.count===C.target&&C.rootPromise._resolve(C.results),null},function(c){C.rootPromise._state!==U.Rejected&&C.rootPromise._reject(c)})},M.all=function(R){var C=new M,m=new _;if(m.target=R.length,m.rootPromise=C,R.length)for(var c=0;c<R.length;c++)M._RegisterForFulfillment(R[c],m,c);else C._resolve([]);return C},M.race=function(R){var C=new M;if(R.length)for(var m=0,c=R;m<c.length;m++)c[m].then(function(T){return C&&(C._resolve(T),C=null),null},function(T){C&&(C._reject(T),C=null)});return C},M}(),u=function(){function M(){}return M.Apply=function(R){R===void 0&&(R=!1),(R||typeof Promise>"u")&&(window.Promise=x)},M}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return x});var 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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}(),x=function(){function u(M){this._samples=new Array(M),this.reset()}return u.prototype.add=function(M){var R;if(this.isSaturated()){var C=this._samples[this._pos];R=C-this.average,this.average-=R/(this._sampleCount-1),this._m2-=R*(C-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),x=f(2),u=function(){function M(R,C,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=C,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,C,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),C&&this._renderSprites(),m&&this._renderParticles(c),this.onBeforeTransparentRendering&&this.onBeforeTransparentRendering(),this._transparentSubMeshes.length!==0&&(T.setStencilBuffer(A),this._renderTransparent(this._transparentSubMeshes),T.setAlphaMode(x.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(x.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,C,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(C&&g.sort(C),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(x.a.ALPHA_DISABLE),T.render(!1),h.setColorWrite(!0)}}T.render(c)}},M.renderUnsorted=function(R){for(var C=0;C<R.length;C++)R.data[C].render(!1)},M.defaultTransparentSortCompare=function(R,C){return 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m=x.getSize(),c=m.width,T=m.height;if(C instanceof Float32Array){for(var A=C.byteLength/C.BYTES_PER_ELEMENT,S=new Uint8Array(A);--A>=0;){var g=C[A];g<0?g=0:g>1&&(g=1),S[A]=255*g}C=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(C),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),x=f(8),u=f(31),M=f(7),R=f(41),C=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&&x.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||x.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!==C.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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-#endif
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-float ndl;
-#endif
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R(C){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=C}return R.RegisterExtension=function(C,m){R.UnregisterExtension(C)&&_.Logger.Warn("Extension with the name '"+C+"' already exists"),R._RegisteredExtensions[C]={factory:m}},R.UnregisterExtension=function(C){return!!R._RegisteredExtensions[C]&&(delete R._RegisteredExtensions[C],!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 C in this._disposed=!0,this._completePromises.length=0,this._extensions){var m=this._extensions[C];m.dispose&&m.dispose(),delete this._extensions[C]}this._gltf=null,this._babylonScene=null,this._rootBabylonMesh=null,this._parent.dispose()}},R.prototype.importMeshAsync=function(C,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(C){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=(C instanceof Array?C:[C]).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(C,m,c,T,A){var S=this;return Promise.resolve().then(function(){return S._babylonScene=C,S._rootUrl=c,S._fileName=A||"scene",S._loadData(m),S._loadAsync(null,function(){})})},R.prototype._loadAsync=function(C,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=x.GLTFLoaderState[x.GLTFLoaderState.LOADING]+" => "+x.GLTFLoaderState[x.GLTFLoaderState.READY],A=x.GLTFLoaderState[x.GLTFLoaderState.LOADING]+" => "+x.GLTFLoaderState[x.GLTFLoaderState.COMPLETE];c._parent._startPerformanceCounter(T),c._parent._startPerformanceCounter(A),c._setState(x.GLTFLoaderState.LOADING),c._extensionsOnLoading();var S=new Array,g=c._babylonScene.blockMaterialDirtyMechanism;if(c._babylonScene.blockMaterialDirtyMechanism=!0,C)S.push(c.loadSceneAsync("/nodes",{nodes:C,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(x.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(x.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(C){if(this._gltf=C.json,this._setupData(),C.bin){var m=this._gltf.buffers;if(m&&m[0]&&!m[0].uri){var c=m[0];(c.byteLength<C.bin.byteLength-3||c.byteLength>C.bin.byteLength)&&_.Logger.Warn("Binary buffer length ("+c.byteLength+") from JSON does not match chunk length ("+C.bin.byteLength+")"),this._bin=C.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 C={},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++)C[A[T]]=h.index;for(var S=this._createRootNode(),g=0,l=this._gltf.nodes;g<l.length;g++){var h,v=C[(h=l[g]).index];h.parent=v===void 0?S:this._gltf.nodes[v]}}},R.prototype._loadExtensions=function(){for(var C in R._RegisteredExtensions){var m=R._RegisteredExtensions[C].factory(this);m.name!==C&&_.Logger.Warn("The name of the glTF loader extension instance does not match the registered name: "+m.name+" !== "+C),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 C=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++)C(T[c])},R.prototype._setState=function(C){this._state=C,this.log(x.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 C={_babylonTransformNode:this._rootBabylonMesh,index:-1};switch(this._parent.coordinateSystemMode){case x.GLTFLoaderCoordinateSystemMode.AUTO:this._babylonScene.useRightHandedSystem||(C.rotation=[0,1,0,0],C.scale=[1,1,-1],R._LoadTransform(C,this._rootBabylonMesh));break;case x.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),C},R.prototype.loadSceneAsync=function(C,m){var c=this,T=this._extensionsLoadSceneAsync(C,m);if(T)return T;var A=new Array;if(this.logOpen(C+" "+(m.name||"")),m.nodes)for(var S=0,g=m.nodes;S<g.length;S++){var l=g[S],h=u.Get(C+"/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(C,m){if(C._primitiveBabylonMeshes)for(var c=0,T=C._primitiveBabylonMeshes;c<T.length;c++)m(T[c])},R.prototype._getGeometries=function(){var C=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&&C.indexOf(g)===-1&&C.push(g)})}return C},R.prototype._getMeshes=function(){var C=new Array;C.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){C.push(S)})}return C},R.prototype._getTransformNodes=function(){var C=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"&&C.push(A._babylonTransformNode)}return C},R.prototype._getSkeletons=function(){var C=new Array,m=this._gltf.skins;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._data&&C.push(A._data.babylonSkeleton)}return C},R.prototype._getAnimationGroups=function(){var C=new Array,m=this._gltf.animations;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._babylonAnimationGroup&&C.push(A._babylonAnimationGroup)}return C},R.prototype._startAnimations=function(){switch(this._parent.animationStartMode){case x.GLTFLoaderAnimationStartMode.NONE:break;case x.GLTFLoaderAnimationStartMode.FIRST:(C=this._getAnimationGroups()).length!==0&&C[0].start(!0);break;case x.GLTFLoaderAnimationStartMode.ALL:for(var C,m=0,c=C=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(C,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadNodeAsync(C,m,c);if(A)return A;if(m._babylonTransformNode)throw new Error(C+": Invalid recursive node hierarchy");var S=new Array;this.logOpen(C+" "+(m.name||""));var g=function(v){if(R.AddPointerMetadata(v,C),R._LoadTransform(m,v),m.camera!=null){var E=u.Get(C+"/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(C+"/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(C+"/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(C,m,c,T){var A=c.primitives;if(!A||!A.length)throw new Error(C+": Primitives are missing");A[0].index==null&&u.Assign(A);var S=new Array;this.logOpen(C+" "+(c.name||""));var g=m.name||"node"+m.index;if(A.length===1){var l=c.primitives[0];S.push(this._loadMeshPrimitiveAsync(C+"/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(C+"/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(C+"/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(C,m,c,T,A,S){var g=this,l=this._extensionsLoadMeshPrimitiveAsync(C,m,c,T,A,S);if(l)return l;this.logOpen(""+C);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(C,c,T,A,w),D.push(this._loadVertexDataAsync(C,A,w).then(function(X){return g._loadMorphTargetsAsync(C,A,w,X).then(function(){g._babylonScene._blockEntityCollection=g._forAssetContainer,X.applyToMesh(w),g._babylonScene._blockEntityCollection=!1})}));var N=R._GetDrawMode(C,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(C+"/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,C),this._parent.onMeshLoadedObservable.notifyObservers(h),S(h),this.logClose(),v.then(function(){return h})},R.prototype._loadVertexDataAsync=function(C,m,c){var T=this,A=this._extensionsLoadVertexDataAsync(C,m,c);if(A)return A;var S=m.attributes;if(!S)throw new Error(C+": 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(C+"/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(C+"/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(C,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(C+": 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(C,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(C+"/targets/"+g,T,m.targets[g],l))}return Promise.all(A).then(function(){})},R.prototype._loadMorphTargetVertexDataAsync=function(C,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(C+"/"+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(C,m){if(C.skin==null){var c=_.Vector3.Zero(),T=_.Quaternion.Identity(),A=_.Vector3.One();C.matrix?_.Matrix.FromArray(C.matrix).decompose(A,T,c):(C.translation&&(c=_.Vector3.FromArray(C.translation)),C.rotation&&(T=_.Quaternion.FromArray(C.rotation)),C.scale&&(A=_.Vector3.FromArray(C.scale))),m.position=c,m.rotationQuaternion=T,m.scaling=A}},R.prototype._loadSkinAsync=function(C,m,c){var T=this,A=this._extensionsLoadSkinAsync(C,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(C,c,l),S(l);var h=this._loadSkinInverseBindMatricesDataAsync(C,c).then(function(v){T._updateBoneMatrices(l,v)});return c._data={babylonSkeleton:l,promise:h},h},R.prototype._loadBones=function(C,m,c){for(var T={},A=0,S=m.joints;A<S.length;A++){var g=S[A],l=u.Get(C+"/joints/"+g,this._gltf.nodes,g);this._loadBone(l,m,c,T)}},R.prototype._loadBone=function(C,m,c,T){var A=T[C.index];if(A)return A;var S=null;C.parent&&C.parent._babylonTransformNode!==this._rootBabylonMesh&&(S=this._loadBone(C.parent,m,c,T));var g=m.joints.indexOf(C.index);return A=new _.Bone(C.name||"joint"+C.index,c,S,this._getNodeMatrix(C),null,null,g),T[C.index]=A,C._babylonBones=C._babylonBones||[],C._babylonBones.push(A),A},R.prototype._loadSkinInverseBindMatricesDataAsync=function(C,m){if(m.inverseBindMatrices==null)return Promise.resolve(null);var c=u.Get(C+"/inverseBindMatrices",this._gltf.accessors,m.inverseBindMatrices);return this._loadFloatAccessorAsync("/accessors/"+c.index,c)},R.prototype._updateBoneMatrices=function(C,m){for(var c=0,T=C.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(C){return C.matrix?_.Matrix.FromArray(C.matrix):_.Matrix.Compose(C.scale?_.Vector3.FromArray(C.scale):_.Vector3.One(),C.rotation?_.Quaternion.FromArray(C.rotation):_.Quaternion.Identity(),C.translation?_.Vector3.FromArray(C.translation):_.Vector3.Zero())},R.prototype.loadCameraAsync=function(C,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadCameraAsync(C,m,c);if(T)return T;var A=new Array;this.logOpen(C+" "+(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(C+": 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(C+": 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(C+": Invalid camera type ("+m.type+")")}return R.AddPointerMetadata(S,C),this._parent.onCameraLoadedObservable.notifyObservers(S),c(S),this.logClose(),Promise.all(A).then(function(){return S})},R.prototype._loadAnimationsAsync=function(){var C=this._gltf.animations;if(!C)return Promise.resolve();for(var m=new Array,c=0;c<C.length;c++){var T=C[c];m.push(this.loadAnimationAsync("/animations/"+T.index,T))}return Promise.all(m).then(function(){})},R.prototype.loadAnimationAsync=function(C,m){var c=this._extensionsLoadAnimationAsync(C,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(C+"/channels/"+l.index,C,m,l,T))}return Promise.all(A).then(function(){return T.normalize(0),T})},R.prototype._loadAnimationChannelAsync=function(C,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(C+"/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(C+"/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(C+"/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(C,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(C+"/interpolation: Invalid value ("+m.interpolation+")")}var T=u.Get(C+"/input",this._gltf.accessors,m.input),A=u.Get(C+"/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(C,m,c,T){var A=this._extensionsLoadBufferAsync(C,m,c,T);if(A)return A;if(!m._data)if(m.uri)m._data=this.loadUriAsync(C+"/uri",m,m.uri);else{if(!this._bin)throw new Error(C+": 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(C+": "+g.message)}})},R.prototype.loadBufferViewAsync=function(C,m){var c=this._extensionsLoadBufferViewAsync(C,m);if(c)return c;if(m._data)return m._data;var T=u.Get(C+"/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(C,m,c){var T=this;if(m._data)return m._data;var A=R._GetNumComponents(C,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(C+"/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(C,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(C+"/sparse/indices/bufferView",T._gltf.bufferViews,h.indices.bufferView),w=u.Get(C+"/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(C+"/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(C+"/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(C+"/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(C,m){return this._loadAccessorAsync(C,m,Float32Array)},R.prototype._loadIndicesAccessorAsync=function(C,m){if(m.type!=="SCALAR")throw new Error(C+"/type: Invalid value "+m.type);if(m.componentType!==5121&&m.componentType!==5123&&m.componentType!==5125)throw new Error(C+"/componentType: Invalid value "+m.componentType);if(m._data)return m._data;if(m.sparse){var c=R._GetTypedArrayConstructor(C+"/componentType",m.componentType);m._data=this._loadAccessorAsync(C,m,c)}else{var T=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+T.index,T).then(function(A){return R._GetTypedArray(C,m.componentType,A,m.byteOffset,m.count)})}return m._data},R.prototype._loadVertexBufferViewAsync=function(C,m){var c=this;return C._babylonBuffer||(C._babylonBuffer=this.loadBufferViewAsync("/bufferViews/"+C.index,C).then(function(T){return new _.Buffer(c._babylonScene.getEngine(),T,!1)})),C._babylonBuffer},R.prototype._loadVertexAccessorAsync=function(C,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(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._babylonVertexBuffer=this._loadVertexBufferViewAsync(A,c).then(function(S){var g=R._GetNumComponents(C,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(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": 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(C+"/baseColorTexture",m.baseColorTexture,function(A){A.name=c.name+" (Base Color)",c.albedoTexture=A})),m.metallicRoughnessTexture&&(m.metallicRoughnessTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(C+"/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(C,m,c,T,A){A===void 0&&(A=function(){});var S=this._extensionsLoadMaterialAsync(C,m,c,T,A);if(S)return S;m._data=m._data||{};var g=m._data[T];if(!g){this.logOpen(C+" "+(m.name||""));var l=this.createMaterial(C,m,T);g={babylonMaterial:l,babylonMeshes:[],promise:this.loadMaterialPropertiesAsync(C,m,l)},m._data[T]=g,R.AddPointerMetadata(l,C),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(C,m){this._babylonScene._blockEntityCollection=this._forAssetContainer;var c=new _.PBRMaterial(C,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(C,m,c){var T=this._extensionsCreateMaterial(C,m,c);if(T)return T;var A=m.name||"material"+m.index;return this._createDefaultMaterial(A,c)},R.prototype.loadMaterialPropertiesAsync=function(C,m,c){var T=this._extensionsLoadMaterialPropertiesAsync(C,m,c);if(T)return T;var A=new Array;return A.push(this.loadMaterialBasePropertiesAsync(C,m,c)),m.pbrMetallicRoughness&&A.push(this._loadMaterialMetallicRoughnessPropertiesAsync(C+"/pbrMetallicRoughness",m.pbrMetallicRoughness,c)),this.loadMaterialAlphaProperties(C,m,c),Promise.all(A).then(function(){})},R.prototype.loadMaterialBasePropertiesAsync=function(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": 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(C+"/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(C+"/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(C+"/emissiveTexture",m.emissiveTexture,function(A){A.name=c.name+" (Emissive)",c.emissiveTexture=A})),Promise.all(T).then(function(){})},R.prototype.loadMaterialAlphaProperties=function(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": 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(C+"/alphaMode: Invalid value ("+m.alphaMode+")")}},R.prototype.loadTextureInfoAsync=function(C,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadTextureInfoAsync(C,m,c);if(A)return A;if(this.logOpen(""+C),m.texCoord>=2)throw new Error(C+"/texCoord: Invalid value ("+m.texCoord+")");var S=u.Get(C+"/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,C),T._parent.onTextureLoadedObservable.notifyObservers(l),c(l)});return this.logClose(),g},R.prototype._loadTextureAsync=function(C,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadTextureAsync(C,m,c);if(T)return T;this.logOpen(C+" "+(m.name||""));var A=m.sampler==null?R.DefaultSampler:u.Get(C+"/sampler",this._gltf.samplers,m.sampler),S=u.Get(C+"/source",this._gltf.images,m.source),g=this._createTextureAsync(C,A,S,c);return this.logClose(),g},R.prototype._createTextureAsync=function(C,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(C+": "+(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(C,m){return m._data||(m._data={noMipMaps:m.minFilter===9728||m.minFilter===9729,samplingMode:R._GetTextureSamplingMode(C,m),wrapU:R._GetTextureWrapMode(C+"/wrapS",m.wrapS),wrapV:R._GetTextureWrapMode(C+"/wrapT",m.wrapT)}),m._data},R.prototype.loadImageAsync=function(C,m){if(!m._data){if(this.logOpen(C+" "+(m.name||"")),m.uri)m._data=this.loadUriAsync(C+"/uri",m,m.uri);else{var c=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+c.index,c)}this.logClose()}return m._data},R.prototype.loadUriAsync=function(C,m,c){var T=this,A=this._extensionsLoadUriAsync(C,m,c);if(A)return A;if(!R._ValidateUri(c))throw new Error(C+": '"+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(C+": Failed to load '"+c+"'"+(v?": "+v.status+" "+v.statusText:""),v))})})})},R.AddPointerMetadata=function(C,m){var c=C.metadata=C.metadata||{},T=c.gltf=c.gltf||{};(T.pointers=T.pointers||[]).push(m)},R._GetTextureWrapMode=function(C,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(C+": Invalid value ("+m+")"),_.Texture.WRAP_ADDRESSMODE}},R._GetTextureSamplingMode=function(C,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(C+"/minFilter: Invalid value ("+T+")"),_.Texture.LINEAR_LINEAR_MIPLINEAR}else switch(c!==9728&&_.Logger.Warn(C+"/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(C+"/minFilter: Invalid value ("+T+")"),_.Texture.NEAREST_NEAREST_MIPNEAREST}},R._GetTypedArrayConstructor=function(C,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(C,m,c)})},R.prototype._extensionsLoadMaterialPropertiesAsync=function(C,m,c){return this._applyExtensions(m,"loadMaterialProperties",function(T){return T.loadMaterialPropertiesAsync&&T.loadMaterialPropertiesAsync(C,m,c)})},R.prototype._extensionsLoadTextureInfoAsync=function(C,m,c){return this._applyExtensions(m,"loadTextureInfo",function(T){return T.loadTextureInfoAsync&&T.loadTextureInfoAsync(C,m,c)})},R.prototype._extensionsLoadTextureAsync=function(C,m,c){return this._applyExtensions(m,"loadTexture",function(T){return T._loadTextureAsync&&T._loadTextureAsync(C,m,c)})},R.prototype._extensionsLoadAnimationAsync=function(C,m){return this._applyExtensions(m,"loadAnimation",function(c){return c.loadAnimationAsync&&c.loadAnimationAsync(C,m)})},R.prototype._extensionsLoadSkinAsync=function(C,m,c){return this._applyExtensions(c,"loadSkin",function(T){return 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*****************************************************************************
-	Copyright (c) Microsoft Corporation.
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-	Permission to use, copy, modify, and/or distribute this software for any
-	purpose with or without fee is hereby granted.
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-	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.
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_.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),x.b.AddPointerMetadata(re,G),$(oe)})})},ae}();x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loadSpecularGlossinessPropertiesAsync(G,K,Q,$)),L._loader.loadMaterialAlphaProperties(ee,K,$),Promise.all(oe).then(function(){})})},ae.prototype._loadSpecularGlossinessPropertiesAsync=function(ee,K,$,L){if(!(L instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=new Array;return 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ae(ee){this.name="KHR_materials_unlit",this.order=210,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_unlit")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.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=$.name+" (Base 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$.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 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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}();x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),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}();x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),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}();x.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,$,L,G,Q){var oe=this;return x.b.LoadExtensionAsync(ee,G,this.name,function(re,Y){var k=new Array;return k.push(oe._loader._loadMeshPrimitiveAsync(ee,K,$,L,G,function(H){if(Q(H),H instanceof _.Mesh){var Z=x.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=x.a.Get(re+"/mapping/"+We,oe._variants,We),He=x.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}();x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),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=$;if(G.subSurface.isRefractionEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.useAlbedoToTintRefraction=!0,L.transmissionFactor===void 0)return G.subSurface.refractionIntensity=0,G.subSurface.isRefractionEnabled=!1,Promise.resolve();G.subSurface.refractionIntensity=L.transmissionFactor;var Q=G.getScene();return G.subSurface.refractionIntensity&&!Q._transmissionHelper&&new D({},G.getScene()),L.transmissionTexture?(L.transmissionTexture.nonColorData=!0,this._loader.loadTextureInfoAsync(ee+"/transmissionTexture",L.transmissionTexture,void 0).then(function(oe){G.subSurface.thicknessTexture=oe,G.subSurface.useMaskFromThicknessTextureGltf=!0})):Promise.resolve()},ae}();x.b.RegisterExtension("KHR_materials_transmission",function(ae){return new w(ae)});var N=function(){function ae(ee){this.name="KHR_materials_translucency",this.order=175,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_translucency"),this.enabled&&(ee.parent.transparencyAsCoverage=!0)}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.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=$;return G.subSurface.isTranslucencyEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.minimumThickness=0,G.subSurface.maximumThickness=0,G.subSurface.useAlbedoToTintRefraction=!0,L.translucencyFactor===void 0?(G.subSurface.translucencyIntensity=0,G.subSurface.isTranslucencyEnabled=!1,Promise.resolve()):(G.subSurface.translucencyIntensity=L.translucencyFactor,L.translucencyTexture?this._loader.loadTextureInfoAsync(ee+"/translucencyTexture",L.translucencyTexture).then(function(Q){G.subSurface.thicknessTexture=Q,G.subSurface.useMaskFromThicknessTextureGltf=!0}):Promise.resolve())},ae}();x.b.RegisterExtension("KHR_materials_translucency",function(ae){return new N(ae)});var I=function(){function ae(ee){this.name="KHR_mesh_quantization",this.enabled=ee.isExtensionUsed("KHR_mesh_quantization")}return ae.prototype.dispose=function(){},ae}();x.b.RegisterExtension("KHR_mesh_quantization",function(ae){return new I(ae)});var V=function(){function ae(ee){this.name="KHR_texture_basisu",this._loader=ee,this.enabled=ee.isExtensionUsed("KHR_texture_basisu")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype._loadTextureAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=K.sampler==null?x.b.DefaultSampler:x.a.Get(ee+"/sampler",L._loader.gltf.samplers,K.sampler),re=x.a.Get(G+"/source",L._loader.gltf.images,Q.source);return L._loader._createTextureAsync(ee,oe,re,function(Y){$(Y)},K._textureInfo.nonColorData?{useRGBAIfASTCBC7NotAvailableWhenUASTC:!0}:void 0)})},ae}();x.b.RegisterExtension("KHR_texture_basisu",function(ae){return new V(ae)});var X=function(){function ae(ee){this.name="KHR_texture_transform",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_texture_transform")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadTextureInfoAsync=function(ee,K,$){var L=this;return x.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}();x.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,x.a.Assign(this._clips),x.a.Assign(this._emitters)}},ae.prototype.loadSceneAsync=function(ee,K){var $=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(L,G){var Q=new Array;Q.push($._loader.loadSceneAsync(ee,K));for(var oe=0,re=G.emitters;oe<re.length;oe++){var Y=re[oe],k=x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return L._loader.loadNodeAsync(G,K,function(re){for(var Y=function(Z){var W=x.a.Get(G+"/emitters",L._emitters,Z);oe.push(L._loadEmitterAsync(G+"/emitters/"+W.index,W).then(function(){for(var q=0,he=W._babylonSounds;q<he.length;q++){var ge=he[q];ge.attachToMesh(re),W.innerAngle==null&&W.outerAngle==null||(ge.setLocalDirectionToMesh(_.Vector3.Forward()),ge.setDirectionalCone(2*_.Tools.ToDegrees(W.innerAngle==null?Math.PI:W.innerAngle),2*_.Tools.ToDegrees(W.outerAngle==null?Math.PI:W.outerAngle),0))}}))},k=0,H=Q.emitters;k<H.length;k++)Y(H[k]);$(re)}).then(function(re){return Promise.all(oe).then(function(){return re})})})},ae.prototype.loadAnimationAsync=function(ee,K){var $=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(L,G){return $._loader.loadAnimationAsync(ee,K).then(function(Q){var oe=new Array;x.a.Assign(G.events);for(var re=0,Y=G.events;re<Y.length;re++){var k=Y[re];oe.push($._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=x.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 $=this;if(K._babylonSounds=K._babylonSounds||[],!K._babylonData){for(var L=new Array,G=K.name||"emitter"+K.index,Q={loop:!1,autoplay:!1,volume:K.volume==null?1:K.volume},oe=function(H){var Z="/extensions/"+re.name+"/clips",W=x.a.Get(Z,re._clips,K.clips[H].clip);L.push(re._loadClipAsync(Z+"/"+K.clips[H].clip,W).then(function(q){var he=K._babylonSounds[H]=new _.Sound(G,q,$._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=x.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}();x.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,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe,re=L._getLODs(G,K,L._loader.gltf.nodes,Q.ids);L._loader.logOpen(""+G);for(var Y=function(H){var Z=re[H];H!==0&&(L._nodeIndexLOD=H,L._nodeSignalLODs[H]=L._nodeSignalLODs[H]||new _.Deferred);var W=L._loader.loadNodeAsync("/nodes/"+Z.index,Z,function(q){q.setEnabled(!1)}).then(function(q){if(H!==0){var he=re[H-1];he._babylonTransformNode&&(L._disposeTransformNode(he._babylonTransformNode),delete he._babylonTransformNode)}return q.setEnabled(!0),q});L._nodePromiseLODs[H]=L._nodePromiseLODs[H]||[],H===0?oe=W:(L._nodeIndexLOD=null,L._nodePromiseLODs[H].push(W))},k=0;k<re.length;k++)Y(k);return L._loader.logClose(),oe})},ae.prototype._loadMaterialAsync=function(ee,K,$,L,G){var Q=this;return this._nodeIndexLOD?null:x.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 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st;if(st=te(W,q.jointNames[Pe])){for(je=0;je<ct.length;je++)if(ct[je].id===st.id){ge.bones.push(ct[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,ct=null,st=null;for(var mt in $e)if(ct=W.accessors[$e[mt]],st=g.GetBufferFromAccessor(W,ct),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(ct=W.accessors[nt.indices])st=g.GetBufferFromAccessor(W,ct),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 ct=We[We.type],st=new S.SpotLight(q.light,S.Vector3.Zero(),S.Vector3.Zero(),0,0,W.scene);st.name=q.name||"",ct.color&&(st.diffuse=S.Color3.FromArray(ct.color)),ct.fallOfAngle&&(st.angle=ct.fallOfAngle),ct.fallOffExponent&&(st.exponent=ct.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 ct=$e instanceof S.Bone,st=ke.target.path,mt=D.indexOf(st);mt!==-1&&(st=w[mt]);var St=S.Animation.ANIMATIONTYPE_MATRIX;ct||(st==="rotationQuaternion"?(St=S.Animation.ANIMATIONTYPE_QUATERNION,$e.rotationQuaternion=new S.Quaternion):St=S.Animation.ANIMATIONTYPE_VECTOR3);var wt=null,It=[],Pt=0,Ot=!1;ct&&ye&&ye.getKeys().length===qe.length&&(wt=ye,Ot=!0),Ot||(_e.scene._blockEntityCollection=_e.forAssetContainer,wt=new S.Animation(be,ct?"_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),ct){var tn=$e,De=S.Vector3.Zero(),Pn=new S.Quaternion,nn=S.Vector3.Zero(),Cn=tn.getBaseMatrix();Ot&&ye&&(Cn=ye.getKeys()[on].value),Cn.decompose(nn,Pn,De),st==="position"?De=Zt:st==="rotationQuaternion"?Pn=Zt:nn=Zt,Zt=S.Matrix.Compose(nn,Pn,De)}Ot?ye&&(ye.getKeys()[on].value=Zt):It.push({frame:qe[on],value:Zt})}!Ot&&wt&&(wt.setKeys(It),$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(ct===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,ct)}}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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za({}),{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.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function ab(ut){let Ke,Me;return Ke=new Xv({props:{type:"file"}}),{c(){Hn(Ke.$$.fragment)},m(y,f){Wn(Ke,y,f),Me=!0},p:xf,i(y){Me||(un(Ke.$$.fragment,y),Me=!0)},o(y){mn(Ke.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function sb(ut){let Ke,Me,y,f,U,_;const x=[ut[6]];let u={};for(let m=0;m<x.length;m+=1)u=wv(u,x[m]);Ke=new Fv({props:u});const M=[rb,ib,nb],R=[];function C(m,c){return m[4]==="dynamic"?0:m[0]?1:2}return y=C(ut),f=R[y]=M[y](ut),{c(){Hn(Ke.$$.fragment),Me=Jr(),f.c(),U=sl()},m(m,c){Wn(Ke,m,c),Di(m,Me,c),R[y].m(m,c),Di(m,U,c),_=!0},p(m,c){const T=c&64?Bv(x,[Uv(m[6])]):{};Ke.$set(T);let A=y;y=C(m),y===A?R[y].p(m,c):(cl(),mn(R[A],1,1,()=>{R[A]=null}),ll(),f=R[y],f?f.p(m,c):(f=R[y]=M[y](m),f.c()),un(f,1),f.m(U.parentNode,U))},i(m){_||(un(Ke.$$.fragment,m),un(f),_=!0)},o(m){mn(Ke.$$.fragment,m),mn(f),_=!1},d(m){m&&(Li(Me),Li(U)),Xn(Ke,m),R[y].d(m)}}}function cb(ut){let Ke,Me;return Ke=new kv({props:{visible:ut[3],variant:ut[0]===null?"dashed":"solid",border_mode:ut[13]?"focus":"base",padding:!1,elem_id:ut[1],elem_classes:ut[2],container:ut[9],scale:ut[10],min_width:ut[11],$$slots:{default:[sb]},$$scope:{ctx:ut}}}),{c(){Hn(Ke.$$.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&8192&&(U.border_mode=y[13]?"focus":"base"),f&2&&(U.elem_id=y[1]),f&4&&(U.elem_classes=y[2]),f&512&&(U.container=y[9]),f&1024&&(U.scale=y[10]),f&2048&&(U.min_width=y[11]),f&1061361&&(U.$$scope={dirty:f,ctx:y}),Ke.$set(U)},i(y){Me||(un(Ke.$$.fragment,y),Me=!0)},o(y){mn(Ke.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function lb(ut,Ke,Me){let{elem_id:y=""}=Ke,{elem_classes:f=[]}=Ke,{visible:U=!0}=Ke,{value:_=null}=Ke,{mode:x}=Ke,{root:u}=Ke,{root_url:M}=Ke,{clearColor:R}=Ke,{loading_status:C}=Ke,{label:m}=Ke,{show_label:c}=Ke,{container:T=!0}=Ke,{scale:A=null}=Ke,{min_width:S=void 0}=Ke,g,l=!1;const h=({detail:w})=>Me(0,_=w),v=({detail:w})=>Me(13,l=w);function E(w){Sf.call(this,ut,w)}function D(w){Sf.call(this,ut,w)}return ut.$$set=w=>{"elem_id"in w&&Me(1,y=w.elem_id),"elem_classes"in w&&Me(2,f=w.elem_classes),"visible"in w&&Me(3,U=w.visible),"value"in w&&Me(0,_=w.value),"mode"in w&&Me(4,x=w.mode),"root"in w&&Me(14,u=w.root),"root_url"in w&&Me(15,M=w.root_url),"clearColor"in w&&Me(5,R=w.clearColor),"loading_status"in w&&Me(6,C=w.loading_status),"label"in w&&Me(7,m=w.label),"show_label"in w&&Me(8,c=w.show_label),"container"in w&&Me(9,T=w.container),"scale"in w&&Me(10,A=w.scale),"min_width"in w&&Me(11,S=w.min_width)},ut.$$.update=()=>{ut.$$.dirty&49153&&Me(12,g=Vv(_,u,M))},[_,y,f,U,x,R,C,m,c,T,A,S,g,l,u,M,h,v,E,D]}class ub extends rl{constructor(Ke){super(),ol(this,Ke,lb,cb,al,{elem_id:1,elem_classes:2,visible:3,value:0,mode:4,root:14,root_url:15,clearColor:5,loading_status:6,label:7,show_label:8,container:9,scale:10,min_width:11})}}const Sb=ub,Ab=["static","dynamic"],Pb=ut=>({type:{payload:"{ name: string; data: string }"},description:{payload:"object with file name and base64 data"}});export{Sb as Component,Rb as ExampleComponent,Pb as document,Ab as modes};
-//# sourceMappingURL=index-d39d2fed.js.map
diff --git a/spaces/Danky/dreamlike-art-dreamlike-diffusion-1.0/README.md b/spaces/Danky/dreamlike-art-dreamlike-diffusion-1.0/README.md
deleted file mode 100644
index 4f33b14196dfe369def8ece6538574da05e8da37..0000000000000000000000000000000000000000
--- a/spaces/Danky/dreamlike-art-dreamlike-diffusion-1.0/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Dreamlike Art Dreamlike Diffusion 1.0
-emoji: 🔥
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.15.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Datasculptor/MusicGen/audiocraft/data/audio.py b/spaces/Datasculptor/MusicGen/audiocraft/data/audio.py
deleted file mode 100644
index 2048df6f175d7303bcf5c7b931922fd297908ead..0000000000000000000000000000000000000000
--- a/spaces/Datasculptor/MusicGen/audiocraft/data/audio.py
+++ /dev/null
@@ -1,215 +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.
-
-"""
-Audio IO methods are defined in this module (info, read, write),
-We rely on av library for faster read when possible, otherwise on torchaudio.
-"""
-
-from dataclasses import dataclass
-from pathlib import Path
-import logging
-import typing as tp
-
-import numpy as np
-import soundfile
-import torch
-from torch.nn import functional as F
-import torchaudio as ta
-
-import av
-
-from .audio_utils import f32_pcm, i16_pcm, normalize_audio
-
-
-_av_initialized = False
-
-
-def _init_av():
-    global _av_initialized
-    if _av_initialized:
-        return
-    logger = logging.getLogger('libav.mp3')
-    logger.setLevel(logging.ERROR)
-    _av_initialized = True
-
-
-@dataclass(frozen=True)
-class AudioFileInfo:
-    sample_rate: int
-    duration: float
-    channels: int
-
-
-def _av_info(filepath: tp.Union[str, Path]) -> AudioFileInfo:
-    _init_av()
-    with av.open(str(filepath)) as af:
-        stream = af.streams.audio[0]
-        sample_rate = stream.codec_context.sample_rate
-        duration = float(stream.duration * stream.time_base)
-        channels = stream.channels
-        return AudioFileInfo(sample_rate, duration, channels)
-
-
-def _soundfile_info(filepath: tp.Union[str, Path]) -> AudioFileInfo:
-    info = soundfile.info(filepath)
-    return AudioFileInfo(info.samplerate, info.duration, info.channels)
-
-
-def audio_info(filepath: tp.Union[str, Path]) -> AudioFileInfo:
-    # torchaudio no longer returns useful duration informations for some formats like mp3s.
-    filepath = Path(filepath)
-    if filepath.suffix in ['.flac', '.ogg']:  # TODO: Validate .ogg can be safely read with av_info
-        # ffmpeg has some weird issue with flac.
-        return _soundfile_info(filepath)
-    else:
-        return _av_info(filepath)
-
-
-def _av_read(filepath: tp.Union[str, Path], seek_time: float = 0, duration: float = -1.) -> tp.Tuple[torch.Tensor, int]:
-    """FFMPEG-based audio file reading using PyAV bindings.
-    Soundfile cannot read mp3 and av_read is more efficient than torchaudio.
-
-    Args:
-        filepath (str or Path): Path to audio file to read.
-        seek_time (float): Time at which to start reading in the file.
-        duration (float): Duration to read from the file. If set to -1, the whole file is read.
-    Returns:
-        Tuple[torch.Tensor, int]: Tuple containing audio data and sample rate
-    """
-    _init_av()
-    with av.open(str(filepath)) as af:
-        stream = af.streams.audio[0]
-        sr = stream.codec_context.sample_rate
-        num_frames = int(sr * duration) if duration >= 0 else -1
-        frame_offset = int(sr * seek_time)
-        # we need a small negative offset otherwise we get some edge artifact
-        # from the mp3 decoder.
-        af.seek(int(max(0, (seek_time - 0.1)) / stream.time_base), stream=stream)
-        frames = []
-        length = 0
-        for frame in af.decode(streams=stream.index):
-            current_offset = int(frame.rate * frame.pts * frame.time_base)
-            strip = max(0, frame_offset - current_offset)
-            buf = torch.from_numpy(frame.to_ndarray())
-            if buf.shape[0] != stream.channels:
-                buf = buf.view(-1, stream.channels).t()
-            buf = buf[:, strip:]
-            frames.append(buf)
-            length += buf.shape[1]
-            if num_frames > 0 and length >= num_frames:
-                break
-        assert frames
-        # If the above assert fails, it is likely because we seeked past the end of file point,
-        # in which case ffmpeg returns a single frame with only zeros, and a weird timestamp.
-        # This will need proper debugging, in due time.
-        wav = torch.cat(frames, dim=1)
-        assert wav.shape[0] == stream.channels
-        if num_frames > 0:
-            wav = wav[:, :num_frames]
-        return f32_pcm(wav), sr
-
-
-def audio_read(filepath: tp.Union[str, Path], seek_time: float = 0.,
-               duration: float = -1., pad: bool = False) -> tp.Tuple[torch.Tensor, int]:
-    """Read audio by picking the most appropriate backend tool based on the audio format.
-
-    Args:
-        filepath (str or Path): Path to audio file to read.
-        seek_time (float): Time at which to start reading in the file.
-        duration (float): Duration to read from the file. If set to -1, the whole file is read.
-        pad (bool): Pad output audio if not reaching expected duration.
-    Returns:
-        Tuple[torch.Tensor, int]: Tuple containing audio data and sample rate.
-    """
-    fp = Path(filepath)
-    if fp.suffix in ['.flac', '.ogg']:  # TODO: check if we can safely use av_read for .ogg
-        # There is some bug with ffmpeg and reading flac
-        info = _soundfile_info(filepath)
-        frames = -1 if duration <= 0 else int(duration * info.sample_rate)
-        frame_offset = int(seek_time * info.sample_rate)
-        wav, sr = soundfile.read(filepath, start=frame_offset, frames=frames, dtype=np.float32)
-        assert info.sample_rate == sr, f"Mismatch of sample rates {info.sample_rate} {sr}"
-        wav = torch.from_numpy(wav).t().contiguous()
-        if len(wav.shape) == 1:
-            wav = torch.unsqueeze(wav, 0)
-    elif (
-        fp.suffix in ['.wav', '.mp3'] and fp.suffix[1:] in ta.utils.sox_utils.list_read_formats()
-        and duration <= 0 and seek_time == 0
-    ):
-        # Torchaudio is faster if we load an entire file at once.
-        wav, sr = ta.load(fp)
-    else:
-        wav, sr = _av_read(filepath, seek_time, duration)
-    if pad and duration > 0:
-        expected_frames = int(duration * sr)
-        wav = F.pad(wav, (0, expected_frames - wav.shape[-1]))
-    return wav, sr
-
-
-def audio_write(stem_name: tp.Union[str, Path],
-                wav: torch.Tensor, sample_rate: int,
-                format: str = 'wav', mp3_rate: int = 320, normalize: bool = True,
-                strategy: str = 'peak', peak_clip_headroom_db: float = 1,
-                rms_headroom_db: float = 18, loudness_headroom_db: float = 14,
-                loudness_compressor: bool = False,
-                log_clipping: bool = True, make_parent_dir: bool = True,
-                add_suffix: bool = True) -> Path:
-    """Convenience function for saving audio to disk. Returns the filename the audio was written to.
-
-    Args:
-        stem_name (str or Path): Filename without extension which will be added automatically.
-        format (str): Either "wav" or "mp3".
-        mp3_rate (int): kbps when using mp3s.
-        normalize (bool): if `True` (default), normalizes according to the prescribed
-            strategy (see after). If `False`, the strategy is only used in case clipping
-            would happen.
-        strategy (str): Can be either 'clip', 'peak', or 'rms'. Default is 'peak',
-            i.e. audio is normalized by its largest value. RMS normalizes by root-mean-square
-            with extra headroom to avoid clipping. 'clip' just clips.
-        peak_clip_headroom_db (float): Headroom in dB when doing 'peak' or 'clip' strategy.
-        rms_headroom_db (float): Headroom in dB when doing 'rms' strategy. This must be much larger
-            than the `peak_clip` one to avoid further clipping.
-        loudness_headroom_db (float): Target loudness for loudness normalization.
-        loudness_compressor (bool): Uses tanh for soft clipping when strategy is 'loudness'.
-         when strategy is 'loudness'log_clipping (bool): If True, basic logging on stderr when clipping still
-            occurs despite strategy (only for 'rms').
-        make_parent_dir (bool): Make parent directory if it doesn't exist.
-    Returns:
-        Path: Path of the saved audio.
-    """
-    assert wav.dtype.is_floating_point, "wav is not floating point"
-    if wav.dim() == 1:
-        wav = wav[None]
-    elif wav.dim() > 2:
-        raise ValueError("Input wav should be at most 2 dimension.")
-    assert wav.isfinite().all()
-    wav = normalize_audio(wav, normalize, strategy, peak_clip_headroom_db,
-                          rms_headroom_db, loudness_headroom_db, log_clipping=log_clipping,
-                          sample_rate=sample_rate, stem_name=str(stem_name))
-    kwargs: dict = {}
-    if format == 'mp3':
-        suffix = '.mp3'
-        kwargs.update({"compression": mp3_rate})
-    elif format == 'wav':
-        wav = i16_pcm(wav)
-        suffix = '.wav'
-        kwargs.update({"encoding": "PCM_S", "bits_per_sample": 16})
-    else:
-        raise RuntimeError(f"Invalid format {format}. Only wav or mp3 are supported.")
-    if not add_suffix:
-        suffix = ''
-    path = Path(str(stem_name) + suffix)
-    if make_parent_dir:
-        path.parent.mkdir(exist_ok=True, parents=True)
-    try:
-        ta.save(path, wav, sample_rate, **kwargs)
-    except Exception:
-        if path.exists():
-            # we do not want to leave half written files around.
-            path.unlink()
-        raise
-    return path
diff --git a/spaces/Defalt-404/Bittensor_Explore/app.py b/spaces/Defalt-404/Bittensor_Explore/app.py
deleted file mode 100644
index f0004189d65ebb3bdfc4731fefd5996829699d6e..0000000000000000000000000000000000000000
--- a/spaces/Defalt-404/Bittensor_Explore/app.py
+++ /dev/null
@@ -1,143 +0,0 @@
-import gradio as gr
-import http
-import ssl
-import json
-import warnings
-warnings.filterwarnings("ignore")
-
-def retrieve_api_key(url):
-    
-    context = ssl.create_default_context()
-    context.check_hostname = True
-    conn = http.client.HTTPSConnection(url, context=context)
-    conn.request("GET", "/admin/api-keys/")
-    api_key_response = conn.getresponse()
-    api_keys_data = (
-            api_key_response.read().decode("utf-8").replace("\n", "").replace("\t", "")
-        )
-    api_keys_json = json.loads(api_keys_data)
-    api_key = api_keys_json[0]["api_key"]
-    conn.close()
-    return api_key
-    
-    
-def get_benchmark_uids(num_miner,mode):
-    
-    url="test.neuralinternet.ai"
-    api_key = retrieve_api_key(url)
-    
-    context = ssl.create_default_context()
-    context.check_hostname = True
-    conn = http.client.HTTPSConnection(url, context=context)
-    
-    headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "Endpoint-Version": "2023-05-19",
-        }
-    
-    conn.request("GET", f"/top_miner_uids?n={num_miner}&mode={mode}", headers=headers)
-    miner_response = conn.getresponse()
-    miner_data = (
-            miner_response.read().decode("utf-8").replace("\n", "").replace("\t", "")
-        )
-    uids = json.loads(miner_data)
-    return uids
-
-
-
-def retrieve_response(payload):
-    
-    url="d509-65-108-32-175.ngrok-free.app"
-    api_key = retrieve_api_key(url)
-    headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "Endpoint-Version": "2023-05-19",
-        }
-    payload = json.dumps(payload)
-    context = ssl.create_default_context()
-    context.check_hostname = True
-    conn = http.client.HTTPSConnection(url, context=context)
-    conn.request("POST", "/chat", payload, headers)
-    init_response = conn.getresponse()
-    init_data = init_response.read().decode("utf-8").replace("\n", "").replace("\t", "")
-    init_json = json.loads(init_data)
-    
-    response_dict = dict()
-    for choice in init_json['choices']:
-        uid = choice['uid']
-        resp = choice['message']['content']
-        resp = resp.replace("\n", "").replace("\t", "")
-        response_dict[uid] = resp
-    response_text = '\n\n'.join([f'"{key}": "{value}"' for key, value in response_dict.items()])
-    return response_text
-
-
-
-def interface_fn(system_prompt, optn, arg, user_prompt):
-    
-    if len(system_prompt) == 0:
-        system_prompt = "You are an AI Assistant, created by bittensor and powered by NI(Neural Internet). Your task is to provide consise response to user's prompt"
-    
-    messages = [{"role": "system", "content": system_prompt},{"role": "user", "content": user_prompt}]
-    payload = dict()
-    
-    if optn == 'TOP':
-        
-        if int(arg) > 50:
-            arg = 50
-        payload['top_n'] = int(arg)
-        payload['messages'] = messages
-        response = retrieve_response(payload)
-        return response
-    
-    elif optn == 'BENCHMARK_TextEval':
-        
-        if int(arg) > 50:
-            arg = 50
-        uids = get_benchmark_uids(int(arg), 'TextEval')
-        payload['uids'] = uids
-        payload['messages'] = messages
-        response = retrieve_response(payload)
-        return response
-
-    elif optn == 'BENCHMARK_AGIEval':
-        
-        if int(arg) > 50:
-            arg = 50
-        uids = get_benchmark_uids(int(arg), 'AGIEval')
-        payload['uids'] = uids
-        payload['messages'] = messages
-        response = retrieve_response(payload)
-        return response
-    
-    else:
-        
-        uids = list()
-        if ',' in arg:
-            uids = [int(x) for x in arg.split(',')]
-        else:
-            uids = [arg]
-        payload['uids'] = uids
-        payload['messages'] = messages
-        response = retrieve_response(payload)
-        return response
-
-
-interface = gr.Interface(
-    fn=interface_fn,
-    inputs=[
-        gr.inputs.Textbox(label="System Prompt", optional=True),
-        gr.inputs.Dropdown(["TOP", "BENCHMARK_TextEval", "BENCHMARK_AGIEval", "UIDs"], label="Select Function"),
-        gr.inputs.Textbox(label="Arguement"),
-        gr.inputs.Textbox(label="Enter your question")
-        ],
-    outputs=gr.outputs.Textbox(label="Model Responses"),
-    title="Explore Bittensor Miners",
-    description="Enter parameters as per you want and get response",
-    examples=[["Your task is to provide consise response of user prompts", "TOP", 5, 'What is Bittensor?']
-            ,["Your task is to provide accurate, lengthy response with good lexical flow", "BENCHMARK_TextEval", 5, "What is neural network and how its feeding mechanism works?"], 
-            ["Act like you're in the technology field for 10+ year and give unbiased opinion", "UIDs", '975,517,906,743,869' , "What are the potential ethical concerns surrounding artificial intelligence and machine learning in healthcare?"]])
-
-interface.launch(enable_queue=True)
\ No newline at end of file
diff --git a/spaces/Dinoking/Guccio-AI-Designer/netdissect/upsegmodel/prroi_pool/functional.py b/spaces/Dinoking/Guccio-AI-Designer/netdissect/upsegmodel/prroi_pool/functional.py
deleted file mode 100644
index 7dc7a8c282e846bd633c4fdc4190c4dca3da5a6f..0000000000000000000000000000000000000000
--- a/spaces/Dinoking/Guccio-AI-Designer/netdissect/upsegmodel/prroi_pool/functional.py
+++ /dev/null
@@ -1,70 +0,0 @@
-#! /usr/bin/env python3
-# -*- coding: utf-8 -*-
-# File   : functional.py
-# Author : Jiayuan Mao, Tete Xiao
-# Email  : maojiayuan@gmail.com, jasonhsiao97@gmail.com
-# Date   : 07/13/2018
-#
-# This file is part of PreciseRoIPooling.
-# Distributed under terms of the MIT license.
-# Copyright (c) 2017 Megvii Technology Limited.
-
-import torch
-import torch.autograd as ag
-
-try:
-    from os.path import join as pjoin, dirname
-    from torch.utils.cpp_extension import load as load_extension
-    root_dir = pjoin(dirname(__file__), 'src')
-    _prroi_pooling = load_extension(
-        '_prroi_pooling',
-        [pjoin(root_dir, 'prroi_pooling_gpu.c'), pjoin(root_dir, 'prroi_pooling_gpu_impl.cu')],
-        verbose=False
-    )
-except ImportError:
-    raise ImportError('Can not compile Precise RoI Pooling library.')
-
-__all__ = ['prroi_pool2d']
-
-
-class PrRoIPool2DFunction(ag.Function):
-    @staticmethod
-    def forward(ctx, features, rois, pooled_height, pooled_width, spatial_scale):
-        assert 'FloatTensor' in features.type() and 'FloatTensor' in rois.type(), \
-                'Precise RoI Pooling only takes float input, got {} for features and {} for rois.'.format(features.type(), rois.type())
-
-        pooled_height = int(pooled_height)
-        pooled_width = int(pooled_width)
-        spatial_scale = float(spatial_scale)
-
-        features = features.contiguous()
-        rois = rois.contiguous()
-        params = (pooled_height, pooled_width, spatial_scale)
-
-        if features.is_cuda:
-            output = _prroi_pooling.prroi_pooling_forward_cuda(features, rois, *params)
-            ctx.params = params
-            # everything here is contiguous.
-            ctx.save_for_backward(features, rois, output)
-        else:
-            raise NotImplementedError('Precise RoI Pooling only supports GPU (cuda) implememtations.')
-
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        features, rois, output = ctx.saved_tensors
-        grad_input = grad_coor = None
-
-        if features.requires_grad:
-            grad_output = grad_output.contiguous()
-            grad_input = _prroi_pooling.prroi_pooling_backward_cuda(features, rois, output, grad_output, *ctx.params)
-        if rois.requires_grad:
-            grad_output = grad_output.contiguous()
-            grad_coor = _prroi_pooling.prroi_pooling_coor_backward_cuda(features, rois, output, grad_output, *ctx.params)
-
-        return grad_input, grad_coor, None, None, None
-
-
-prroi_pool2d = PrRoIPool2DFunction.apply
-
diff --git a/spaces/DrGabrielLopez/GPT2_Chatbot/README.md b/spaces/DrGabrielLopez/GPT2_Chatbot/README.md
deleted file mode 100644
index 38151d4fbd2d870b5c5a7c833884f7bccebd97b1..0000000000000000000000000000000000000000
--- a/spaces/DrGabrielLopez/GPT2_Chatbot/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Funny Chatbot
-emoji: 🌖
-colorFrom: yellow
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.9.1
-app_file: app.py
-pinned: false
-license: cc-by-nc-sa-4.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/DragGan/DragGan-Inversion/torch_utils/custom_ops.py b/spaces/DragGan/DragGan-Inversion/torch_utils/custom_ops.py
deleted file mode 100644
index 6c11b863842a2e5ef1ee2da0b02c0733fe79e4b1..0000000000000000000000000000000000000000
--- a/spaces/DragGan/DragGan-Inversion/torch_utils/custom_ops.py
+++ /dev/null
@@ -1,171 +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 glob
-import hashlib
-import importlib
-import os
-import re
-import shutil
-import uuid
-
-import torch
-import torch.utils.cpp_extension
-from torch.utils.file_baton import FileBaton
-
-# ----------------------------------------------------------------------------
-# Global options.
-
-verbosity = 'brief'  # Verbosity level: 'none', 'brief', 'full'
-
-# ----------------------------------------------------------------------------
-# Internal helper funcs.
-
-
-def _find_compiler_bindir():
-    patterns = [
-        'C:/Program Files*/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64',
-        'C:/Program Files*/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64',
-        'C:/Program Files*/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64',
-        'C:/Program Files*/Microsoft Visual Studio */vc/bin',
-    ]
-    for pattern in patterns:
-        matches = sorted(glob.glob(pattern))
-        if len(matches):
-            return matches[-1]
-    return None
-
-# ----------------------------------------------------------------------------
-
-
-def _get_mangled_gpu_name():
-    name = torch.cuda.get_device_name().lower()
-    out = []
-    for c in name:
-        if re.match('[a-z0-9_-]+', c):
-            out.append(c)
-        else:
-            out.append('-')
-    return ''.join(out)
-
-# ----------------------------------------------------------------------------
-# Main entry point for compiling and loading C++/CUDA plugins.
-
-
-_cached_plugins = dict()
-
-
-def get_plugin(module_name, sources, headers=None, source_dir=None, **build_kwargs):
-    assert verbosity in ['none', 'brief', 'full']
-    if headers is None:
-        headers = []
-    if source_dir is not None:
-        sources = [os.path.join(source_dir, fname) for fname in sources]
-        headers = [os.path.join(source_dir, fname) for fname in headers]
-
-    # Already cached?
-    if module_name in _cached_plugins:
-        return _cached_plugins[module_name]
-
-    # Print status.
-    if verbosity == 'full':
-        print(f'Setting up PyTorch plugin "{module_name}"...')
-    elif verbosity == 'brief':
-        print(
-            f'Setting up PyTorch plugin "{module_name}"... ', end='', flush=True)
-    verbose_build = (verbosity == 'full')
-
-    # Compile and load.
-    try:  # pylint: disable=too-many-nested-blocks
-        # Make sure we can find the necessary compiler binaries.
-        if os.name == 'nt' and os.system("where cl.exe >nul 2>nul") != 0:
-            compiler_bindir = _find_compiler_bindir()
-            if compiler_bindir is None:
-                raise RuntimeError(
-                    f'Could not find MSVC/GCC/CLANG installation on this computer. Check _find_compiler_bindir() in "{__file__}".')
-            os.environ['PATH'] += ';' + compiler_bindir
-
-        # Some containers set TORCH_CUDA_ARCH_LIST to a list that can either
-        # break the build or unnecessarily restrict what's available to nvcc.
-        # Unset it to let nvcc decide based on what's available on the
-        # machine.
-        os.environ['TORCH_CUDA_ARCH_LIST'] = ''
-
-        # Incremental build md5sum trickery.  Copies all the input source files
-        # into a cached build directory under a combined md5 digest of the input
-        # source files.  Copying is done only if the combined digest has changed.
-        # This keeps input file timestamps and filenames the same as in previous
-        # extension builds, allowing for fast incremental rebuilds.
-        #
-        # This optimization is done only in case all the source files reside in
-        # a single directory (just for simplicity) and if the TORCH_EXTENSIONS_DIR
-        # environment variable is set (we take this as a signal that the user
-        # actually cares about this.)
-        #
-        # EDIT: We now do it regardless of TORCH_EXTENSIOS_DIR, in order to work
-        # around the *.cu dependency bug in ninja config.
-        #
-        all_source_files = sorted(sources + headers)
-        all_source_dirs = set(os.path.dirname(fname)
-                              for fname in all_source_files)
-        # and ('TORCH_EXTENSIONS_DIR' in os.environ):
-        if len(all_source_dirs) == 1:
-
-            # Compute combined hash digest for all source files.
-            hash_md5 = hashlib.md5()
-            for src in all_source_files:
-                with open(src, 'rb') as f:
-                    hash_md5.update(f.read())
-
-            # Select cached build directory name.
-            source_digest = hash_md5.hexdigest()
-            build_top_dir = torch.utils.cpp_extension._get_build_directory(
-                module_name, verbose=verbose_build)  # pylint: disable=protected-access
-            cached_build_dir = os.path.join(
-                build_top_dir, f'{source_digest}-{_get_mangled_gpu_name()}')
-
-            if not os.path.isdir(cached_build_dir):
-                tmpdir = f'{build_top_dir}/srctmp-{uuid.uuid4().hex}'
-                os.makedirs(tmpdir)
-                for src in all_source_files:
-                    shutil.copyfile(src, os.path.join(
-                        tmpdir, os.path.basename(src)))
-                try:
-                    os.replace(tmpdir, cached_build_dir)  # atomic
-                except OSError:
-                    # source directory already exists, delete tmpdir and its contents.
-                    shutil.rmtree(tmpdir)
-                    if not os.path.isdir(cached_build_dir):
-                        raise
-
-            # Compile.
-            cached_sources = [os.path.join(
-                cached_build_dir, os.path.basename(fname)) for fname in sources]
-            torch.utils.cpp_extension.load(name=module_name, build_directory=cached_build_dir,
-                                           verbose=verbose_build, sources=cached_sources, **build_kwargs)
-        else:
-            torch.utils.cpp_extension.load(
-                name=module_name, verbose=verbose_build, sources=sources, **build_kwargs)
-
-        # Load.
-        module = importlib.import_module(module_name)
-
-    except:
-        if verbosity == 'brief':
-            print('Failed!')
-        raise
-
-    # Print status and add to cache dict.
-    if verbosity == 'full':
-        print(f'Done setting up PyTorch plugin "{module_name}".')
-    elif verbosity == 'brief':
-        print('Done.')
-    _cached_plugins[module_name] = module
-    return module
-
-# ----------------------------------------------------------------------------
diff --git a/spaces/ECCV2022/bytetrack/yolox/motdt_tracker/reid_model.py b/spaces/ECCV2022/bytetrack/yolox/motdt_tracker/reid_model.py
deleted file mode 100644
index 6ad49e340584452da3eeea487b0f8bf7d7e5db5d..0000000000000000000000000000000000000000
--- a/spaces/ECCV2022/bytetrack/yolox/motdt_tracker/reid_model.py
+++ /dev/null
@@ -1,270 +0,0 @@
-import cv2
-import numpy as np
-import torch
-from torch.autograd import Variable
-import torch.nn.functional as F
-import torch.nn as nn
-import pickle
-import os
-from torch.nn.modules import CrossMapLRN2d as SpatialCrossMapLRN
-#from torch.legacy.nn import SpatialCrossMapLRN as SpatialCrossMapLRNOld
-from torch.autograd import Function, Variable
-from torch.nn import Module
-
-
-def clip_boxes(boxes, im_shape):
-    """
-    Clip boxes to image boundaries.
-    """
-    boxes = np.asarray(boxes)
-    if boxes.shape[0] == 0:
-        return boxes
-    boxes = np.copy(boxes)
-    # x1 >= 0
-    boxes[:, 0::4] = np.maximum(np.minimum(boxes[:, 0::4], im_shape[1] - 1), 0)
-    # y1 >= 0
-    boxes[:, 1::4] = np.maximum(np.minimum(boxes[:, 1::4], im_shape[0] - 1), 0)
-    # x2 < im_shape[1]
-    boxes[:, 2::4] = np.maximum(np.minimum(boxes[:, 2::4], im_shape[1] - 1), 0)
-    # y2 < im_shape[0]
-    boxes[:, 3::4] = np.maximum(np.minimum(boxes[:, 3::4], im_shape[0] - 1), 0)
-    return boxes
-
-
-def load_net(fname, net, prefix='', load_state_dict=False):
-    import h5py
-    with h5py.File(fname, mode='r') as h5f:
-        h5f_is_module = True
-        for k in h5f.keys():
-            if not str(k).startswith('module.'):
-                h5f_is_module = False
-                break
-        if prefix == '' and not isinstance(net, nn.DataParallel) and h5f_is_module:
-            prefix = 'module.'
-
-        for k, v in net.state_dict().items():
-            k = prefix + k
-            if k in h5f:
-                param = torch.from_numpy(np.asarray(h5f[k]))
-                if v.size() != param.size():
-                    print('Inconsistent shape: {}, {}'.format(v.size(), param.size()))
-                else:
-                    v.copy_(param)
-            else:
-                print.warning('No layer: {}'.format(k))
-
-        epoch = h5f.attrs['epoch'] if 'epoch' in h5f.attrs else -1
-
-        if not load_state_dict:
-            if 'learning_rates' in h5f.attrs:
-                lr = h5f.attrs['learning_rates']
-            else:
-                lr = h5f.attrs.get('lr', -1)
-                lr = np.asarray([lr] if lr > 0 else [], dtype=np.float)
-
-            return epoch, lr
-
-        state_file = fname + '.optimizer_state.pk'
-        if os.path.isfile(state_file):
-            with open(state_file, 'rb') as f:
-                state_dicts = pickle.load(f)
-                if not isinstance(state_dicts, list):
-                    state_dicts = [state_dicts]
-        else:
-            state_dicts = None
-        return epoch, state_dicts
-
-
-# class SpatialCrossMapLRNFunc(Function):
-
-#     def __init__(self, size, alpha=1e-4, beta=0.75, k=1):
-#         self.size = size
-#         self.alpha = alpha
-#         self.beta = beta
-#         self.k = k
-
-#     def forward(self, input):
-#         self.save_for_backward(input)
-#         self.lrn = SpatialCrossMapLRNOld(self.size, self.alpha, self.beta, self.k)
-#         self.lrn.type(input.type())
-#         return self.lrn.forward(input)
-
-#     def backward(self, grad_output):
-#         input, = self.saved_tensors
-#         return self.lrn.backward(input, grad_output)
-
-
-# # use this one instead
-# class SpatialCrossMapLRN(Module):
-#     def __init__(self, size, alpha=1e-4, beta=0.75, k=1):
-#         super(SpatialCrossMapLRN, self).__init__()
-#         self.size = size
-#         self.alpha = alpha
-#         self.beta = beta
-#         self.k = k
-
-#     def forward(self, input):
-#         return SpatialCrossMapLRNFunc(self.size, self.alpha, self.beta, self.k)(input)
-
-
-class Inception(nn.Module):
-    def __init__(self, in_planes, n1x1, n3x3red, n3x3, n5x5red, n5x5, pool_planes):
-        super(Inception, self).__init__()
-        # 1x1 conv branch
-        self.b1 = nn.Sequential(
-            nn.Conv2d(in_planes, n1x1, kernel_size=1),
-            nn.ReLU(True),
-        )
-
-        # 1x1 conv -> 3x3 conv branch
-        self.b2 = nn.Sequential(
-            nn.Conv2d(in_planes, n3x3red, kernel_size=1),
-            nn.ReLU(True),
-            nn.Conv2d(n3x3red, n3x3, kernel_size=3, padding=1),
-            nn.ReLU(True),
-        )
-
-        # 1x1 conv -> 5x5 conv branch
-        self.b3 = nn.Sequential(
-            nn.Conv2d(in_planes, n5x5red, kernel_size=1),
-            nn.ReLU(True),
-
-            nn.Conv2d(n5x5red, n5x5, kernel_size=5, padding=2),
-            nn.ReLU(True),
-        )
-
-        # 3x3 pool -> 1x1 conv branch
-        self.b4 = nn.Sequential(
-            nn.MaxPool2d(3, stride=1, padding=1),
-
-            nn.Conv2d(in_planes, pool_planes, kernel_size=1),
-            nn.ReLU(True),
-        )
-
-    def forward(self, x):
-        y1 = self.b1(x)
-        y2 = self.b2(x)
-        y3 = self.b3(x)
-        y4 = self.b4(x)
-        return torch.cat([y1,y2,y3,y4], 1)
-
-
-class GoogLeNet(nn.Module):
-
-    output_channels = 832
-
-    def __init__(self):
-        super(GoogLeNet, self).__init__()
-        self.pre_layers = nn.Sequential(
-            nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3),
-            nn.ReLU(True),
-
-            nn.MaxPool2d(3, stride=2, ceil_mode=True),
-            SpatialCrossMapLRN(5),
-
-            nn.Conv2d(64, 64, 1),
-            nn.ReLU(True),
-
-            nn.Conv2d(64, 192, 3, padding=1),
-            nn.ReLU(True),
-
-            SpatialCrossMapLRN(5),
-            nn.MaxPool2d(3, stride=2, ceil_mode=True),
-        )
-
-        self.a3 = Inception(192,  64,  96, 128, 16, 32, 32)
-        self.b3 = Inception(256, 128, 128, 192, 32, 96, 64)
-
-        self.maxpool = nn.MaxPool2d(3, stride=2, ceil_mode=True)
-
-        self.a4 = Inception(480, 192,  96, 208, 16,  48,  64)
-        self.b4 = Inception(512, 160, 112, 224, 24,  64,  64)
-        self.c4 = Inception(512, 128, 128, 256, 24,  64,  64)
-        self.d4 = Inception(512, 112, 144, 288, 32,  64,  64)
-        self.e4 = Inception(528, 256, 160, 320, 32, 128, 128)
-
-    def forward(self, x):
-        out = self.pre_layers(x)
-        out = self.a3(out)
-        out = self.b3(out)
-        out = self.maxpool(out)
-        out = self.a4(out)
-        out = self.b4(out)
-        out = self.c4(out)
-        out = self.d4(out)
-        out = self.e4(out)
-
-        return out
-
-
-class Model(nn.Module):
-    def __init__(self, n_parts=8):
-        super(Model, self).__init__()
-        self.n_parts = n_parts
-
-        self.feat_conv = GoogLeNet()
-        self.conv_input_feat = nn.Conv2d(self.feat_conv.output_channels, 512, 1)
-
-        # part net
-        self.conv_att = nn.Conv2d(512, self.n_parts, 1)
-
-        for i in range(self.n_parts):
-            setattr(self, 'linear_feature{}'.format(i+1), nn.Linear(512, 64))
-
-    def forward(self, x):
-        feature = self.feat_conv(x)
-        feature = self.conv_input_feat(feature)
-
-        att_weights = torch.sigmoid(self.conv_att(feature))
-
-        linear_feautres = []
-        for i in range(self.n_parts):
-            masked_feature = feature * torch.unsqueeze(att_weights[:, i], 1)
-            pooled_feature = F.avg_pool2d(masked_feature, masked_feature.size()[2:4])
-            linear_feautres.append(
-                getattr(self, 'linear_feature{}'.format(i+1))(pooled_feature.view(pooled_feature.size(0), -1))
-            )
-
-        concat_features = torch.cat(linear_feautres, 1)
-        normed_feature = concat_features / torch.clamp(torch.norm(concat_features, 2, 1, keepdim=True), min=1e-6)
-
-        return normed_feature
-
-
-def load_reid_model(ckpt):
-    model = Model(n_parts=8)
-    model.inp_size = (80, 160)
-    load_net(ckpt, model)
-    print('Load ReID model from {}'.format(ckpt))
-
-    model = model.cuda()
-    model.eval()
-    return model
-
-
-def im_preprocess(image):
-    image = np.asarray(image, np.float32)
-    image -= np.array([104, 117, 123], dtype=np.float32).reshape(1, 1, -1)
-    image = image.transpose((2, 0, 1))
-    return image
-
-
-def extract_image_patches(image, bboxes):
-    bboxes = np.round(bboxes).astype(np.int)
-    bboxes = clip_boxes(bboxes, image.shape)
-    patches = [image[box[1]:box[3], box[0]:box[2]] for box in bboxes]
-    return patches
-
-
-def extract_reid_features(reid_model, image, tlbrs):
-    if len(tlbrs) == 0:
-        return torch.FloatTensor()
-
-    patches = extract_image_patches(image, tlbrs)
-    patches = np.asarray([im_preprocess(cv2.resize(p, reid_model.inp_size)) for p in patches], dtype=np.float32)
-
-    with torch.no_grad():
-        im_var = Variable(torch.from_numpy(patches))
-        im_var = im_var.cuda()
-        features = reid_model(im_var).data
-    return features
\ No newline at end of file
diff --git a/spaces/Eddycrack864/Applio-Inference/go-applio.bat b/spaces/Eddycrack864/Applio-Inference/go-applio.bat
deleted file mode 100644
index 60c0c41d34a8aee5e14e744accb33d028d807245..0000000000000000000000000000000000000000
--- a/spaces/Eddycrack864/Applio-Inference/go-applio.bat
+++ /dev/null
@@ -1,92 +0,0 @@
-@echo off
-setlocal
-title Start Applio
-
-:::
-:::                       _ _
-:::     /\               | (_)
-:::    /  \   _ __  _ __ | |_  ___
-:::   / /\ \ | '_ \| '_ \| | |/ _ \
-:::  / ____ \| |_) | |_) | | | (_) |
-::: /_/    \_\ .__/| .__/|_|_|\___/
-:::          | |   | |
-:::          |_|   |_|
-:::
-:::
-
-:menu
-for /f "delims=: tokens=*" %%A in ('findstr /b ":::" "%~f0"') do @echo(%%A
-
-echo [1] Start Applio
-echo [2] Start Applio (DML)
-echo [3] Start Realtime GUI (DML)
-echo [4] Start Realtime GUI (V0)
-echo [5] Start Realtime GUI (V1)
-echo.
-
-set /p choice=Select an option: 
-set choice=%choice: =%
-
-cls
-echo WARNING: It's recommended to disable antivirus or firewall, as errors might occur when starting the ssl.
-pause
-
-if "%choice%"=="1" (
-    cls
-    echo WARNING: At this point, it's recommended to disable antivirus or firewall, as errors might occur when downloading pretrained models.
-    pause>null
-    echo Starting Applio...
-    echo.
-    runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897
-    pause
-    cls
-    goto menu
-)
-
-if "%choice%"=="2" (
-    cls
-    echo Starting Applio ^(DML^)...
-    echo.
-    runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897 --dml
-    pause
-    cls
-    goto menu
-)
-
-if "%choice%"=="3" (
-    cls
-    echo Starting Realtime GUI ^(DML^)...
-    echo.
-    runtime\python.exe gui_v1.py --pycmd runtime\python.exe --dml
-    pause
-    cls
-    goto menu
-)
-
-if "%choice%"=="4" (
-    cls
-    echo Starting Realtime GUI ^(V0^)...
-    echo.
-    runtime\python.exe gui_v0.py
-    pause
-    cls
-    goto menu
-)
-
-if "%choice%"=="5" (
-    cls
-    echo Starting Realtime GUI ^(V1^)...
-    echo.
-    runtime\python.exe gui_v1.py
-    pause
-    cls
-    goto menu
-)
-
-cls
-echo Invalid option. Please enter a number from 1 to 5.
-echo.
-echo Press 'Enter' to access the main menu...
-pause>nul
-cls
-goto menu
diff --git a/spaces/ElainaFanBoy/MusicGen/audiocraft/modules/codebooks_patterns.py b/spaces/ElainaFanBoy/MusicGen/audiocraft/modules/codebooks_patterns.py
deleted file mode 100644
index c5b35cbea8cff84aa56116dbdd860fc72a913a13..0000000000000000000000000000000000000000
--- a/spaces/ElainaFanBoy/MusicGen/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/EleutherAI/polyglot-ko-1.3b/app.py b/spaces/EleutherAI/polyglot-ko-1.3b/app.py
deleted file mode 100644
index 4a76a822706bc809e723530899e0e9581f609351..0000000000000000000000000000000000000000
--- a/spaces/EleutherAI/polyglot-ko-1.3b/app.py
+++ /dev/null
@@ -1,63 +0,0 @@
-import gradio as gr
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM, StoppingCriteriaList
-import os
-import torch
-
-theme = "darkgrass"
-title = "Polyglot(Korean) Demo"
-model_name = "EleutherAI/polyglot-ko-1.3b"
-
-bad_words = [
-  '...',
-  '....',
-  '(중략)',
-  'http'
-]
-
-description = "polyglot (1.3B 파라미터 사이즈) 한국어 모델을 시연하는 데모페이지 입니다."
-article = "<p style='text-align: center'><a href='https://github.com/EleutherAI/polyglot' target='_blank'>Polyglot: Large Language Models of Well-balanced Competence in Multi-languages</a></p>"
-examples = [
-    ["CPU와 GPU의 차이는,"],
-    ["질문: 우크라이나 전쟁이 세계3차대전으로 확전이 될까요? \n답변:"],
-    ["2040년 미국은, "]
-]
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(
-  model_name
-)
-model.eval()
-
-pipe = pipeline('text-generation', model=model, tokenizer=tokenizer, eos_token_id=tokenizer.eos_token_id)
-
-def predict(text):
-  with torch.no_grad():
-    tokens = tokenizer(text, return_tensors="pt").input_ids
-    # generate and end generate if <|endoftext|> is not in text
-    gen_tokens = model.generate(
-      tokens, do_sample=True, temperature=0.8, max_new_tokens=64, top_k=50, top_p=0.8,
-      no_repeat_ngram_size=3, repetition_penalty=1.2,
-      bad_words_ids=[
-        tokenizer.encode(bad_word) for bad_word in bad_words
-      ],
-      eos_token_id=tokenizer.eos_token_id,
-      pad_token_id=tokenizer.pad_token_id
-    )
-    generated = tokenizer.batch_decode(gen_tokens)[0]
-    return generated
-  # return pipe(text)[0]['generated_text']
-
-iface = gr.Interface(
-  fn=predict, 
-  inputs='text',
-  outputs='text',
-  examples=examples
-)
-
-iface.launch()
-
-
-
-
-
-  
-# print(generated)  # print: 인간처럼 생각하고, 행동하는 '지능'을 통해 인류가 이제까지 풀지 못했던 문제의 해답을 찾을 수 있을 것이다. 과학기술이 고도로 발달한 21세기를 살아갈 우리 아이들에게 가장 필요한 것은 사고력 훈련이다. 사고력 훈련을 통해, 세상
diff --git a/spaces/EllieSiegel/Falcon-40B/README.md b/spaces/EllieSiegel/Falcon-40B/README.md
deleted file mode 100644
index 83f37ef8d202cf7c5d69291a4adb6ab804740e86..0000000000000000000000000000000000000000
--- a/spaces/EllieSiegel/Falcon-40B/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Falcon 40B
-emoji: 🦀
-colorFrom: blue
-colorTo: red
-sdk: gradio
-sdk_version: 3.33.1
-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/EmilyBrat/bratty-space-needs-correction/README.md b/spaces/EmilyBrat/bratty-space-needs-correction/README.md
deleted file mode 100644
index 29cc8efed1c745a547d7c0052d19aeb09267c6fd..0000000000000000000000000000000000000000
--- a/spaces/EmilyBrat/bratty-space-needs-correction/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: Bratty Proxy Needs Correction
-emoji: 📚
-colorFrom: red
-colorTo: pink
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Error114/bingo/Dockerfile b/spaces/Error114/bingo/Dockerfile
deleted file mode 100644
index c677b05b75f7e4b2beee8c97fb47957a0861a83e..0000000000000000000000000000000000000000
--- a/spaces/Error114/bingo/Dockerfile
+++ /dev/null
@@ -1,7 +0,0 @@
-FROM weaigc/bingo:latest
-
-ARG DEBIAN_FRONTEND=noninteractive
-
-ENV BING_HEADER ""
-
-CMD npm start
diff --git a/spaces/EuroPython2022/clickbaitonator/fudge/poetry_data/README.md b/spaces/EuroPython2022/clickbaitonator/fudge/poetry_data/README.md
deleted file mode 100644
index d1c7b7d1c8593cc4f0eda2f975571a71a9569fa2..0000000000000000000000000000000000000000
--- a/spaces/EuroPython2022/clickbaitonator/fudge/poetry_data/README.md
+++ /dev/null
@@ -1 +0,0 @@
-`couplet_prefixes.txt` contains the 13th line of each of Shakespeare's sonnets. `couplet_ends.txt` contains the 14th. (Each 14-line sonnet ends with a couplet in the last two lines). The prefixes are our test set prefixes for the couplet completion task; the ends are Shakespeare's outputs. 
\ No newline at end of file
diff --git a/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_models/master.py b/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_models/master.py
deleted file mode 100644
index 39eaef248e132f7ccd6675b63ba21ef41e350c3b..0000000000000000000000000000000000000000
--- a/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_models/master.py
+++ /dev/null
@@ -1,61 +0,0 @@
-label_convertor = dict(
-    type='AttnConvertor', dict_type='DICT90', with_unknown=True)
-
-model = dict(
-    type='MASTER',
-    backbone=dict(
-        type='ResNet',
-        in_channels=3,
-        stem_channels=[64, 128],
-        block_cfgs=dict(
-            type='BasicBlock',
-            plugins=dict(
-                cfg=dict(
-                    type='GCAModule',
-                    ratio=0.0625,
-                    n_head=1,
-                    pooling_type='att',
-                    is_att_scale=False,
-                    fusion_type='channel_add'),
-                position='after_conv2')),
-        arch_layers=[1, 2, 5, 3],
-        arch_channels=[256, 256, 512, 512],
-        strides=[1, 1, 1, 1],
-        plugins=[
-            dict(
-                cfg=dict(type='Maxpool2d', kernel_size=2, stride=(2, 2)),
-                stages=(True, True, False, False),
-                position='before_stage'),
-            dict(
-                cfg=dict(type='Maxpool2d', kernel_size=(2, 1), stride=(2, 1)),
-                stages=(False, False, True, False),
-                position='before_stage'),
-            dict(
-                cfg=dict(
-                    type='ConvModule',
-                    kernel_size=3,
-                    stride=1,
-                    padding=1,
-                    norm_cfg=dict(type='BN'),
-                    act_cfg=dict(type='ReLU')),
-                stages=(True, True, True, True),
-                position='after_stage')
-        ],
-        init_cfg=[
-            dict(type='Kaiming', layer='Conv2d'),
-            dict(type='Constant', val=1, layer='BatchNorm2d'),
-        ]),
-    encoder=None,
-    decoder=dict(
-        type='MasterDecoder',
-        d_model=512,
-        n_head=8,
-        attn_drop=0.,
-        ffn_drop=0.,
-        d_inner=2048,
-        n_layers=3,
-        feat_pe_drop=0.2,
-        feat_size=6 * 40),
-    loss=dict(type='TFLoss', reduction='mean'),
-    label_convertor=label_convertor,
-    max_seq_len=30)
diff --git a/spaces/ExpertPrompters/AskIDF/app.py b/spaces/ExpertPrompters/AskIDF/app.py
deleted file mode 100644
index 18688b2a7cb7b37b89d315a5a5b52f5f1f00b2f2..0000000000000000000000000000000000000000
--- a/spaces/ExpertPrompters/AskIDF/app.py
+++ /dev/null
@@ -1,160 +0,0 @@
-import streamlit as st
-import numpy as np
-import pandas as pd
-import altair as alt
-import chat as idf_chat
-from langchain.sql_database import SQLDatabase
-from langchain.agents.agent_toolkits import SQLDatabaseToolkit
-from langchain.agents import create_sql_agent
-from langchain import OpenAI
-from langchain import PromptTemplate, OpenAI, LLMChain
-from langchain.chains import SimpleSequentialChain
-from langchain_experimental.sql import SQLDatabaseChain
-from langchain_experimental.agents.agent_toolkits import create_python_agent
-from langchain_experimental.tools import PythonREPLTool
-from langchain_experimental.utilities import PythonREPL
-
-
-JSON_DATA_LABEL = 'json_data'
-llm=OpenAI(temperature=0)
-db = SQLDatabase.from_uri("sqlite:///FXTrades.db")
-
-
-if JSON_DATA_LABEL not in st.session_state:
-    st.session_state[JSON_DATA_LABEL] = {}
-
-
-def get_db_chain():
-
-    template = """Your name is IDF. If you recieve a "Hey IDF" salute reply by saying, "Hey BBHer!". Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer.
-    Use the following format:
-    Question: "Question here"
-    SQLQuery: "SQL Query to run"
-    SQLResult: "Result of the SQLQuery"
-    Answer: "Final answer here"
-
-    Only use the following tables:
-
-    {table_info}
-
-    If someone asks any question involving client name, you need to join with Client table
-    volume: you need to count records
-    Trades: you need to get volume of trades
-    Currency Bought: you need to use ccyBought
-    Currency Sold: you need to use ccySold
-
-
-    Question: {input}"""
-    PROMPT = PromptTemplate(
-        input_variables=["input", "table_info", "dialect"],
-        template=template
-        )
-
-    return SQLDatabaseChain.from_llm(llm, db, prompt=PROMPT, verbose=True)
-
-
-def get_json_chain():
-    prompt_template = "Reformat this {result} in JSON format"
-    return LLMChain(
-        llm=llm,
-        prompt=PromptTemplate.from_template(prompt_template)
-    )
-
-def plot_chart():
-    json = st.session_state[JSON_DATA_LABEL]
-    # print(json)
-#    if not json:
-#        return "no data to plot"
-
-    agent_executor = create_python_agent(
-    llm=llm,
-    tool=PythonREPLTool(),
-    verbose=True
-    )
-    question = "Plot these results: " + json
-#   Add Open AI call to format outcome in a table
-    return agent_executor.run(question)
-
-   
-db_chain = get_db_chain()
-json_chain = get_json_chain()
-
-def from_gpt(query: str, plot: bool):
-    try:
-        chains = [db_chain, json_chain] if plot else [db_chain]
-        main_chain = SimpleSequentialChain(chains=chains, verbose=True)
-        ans = main_chain.run(query)
-       # Execute Python if plot
-        st.session_state[JSON_DATA_LABEL] = ans if plot else {}
-        return ans
-    except Exception as e:
-        return "Please ask a proper business question related to selected datasets" 
-
-def circle_chart():
-    df = pd.DataFrame(np.random.randn(200, 3), columns=['a', 'b', 'c'])
-    return alt.Chart(df).mark_circle().encode(
-        x='a', y='b', size='c', color='c', tooltip=['a', 'b', 'c']
-    )
-
-# Parse the prompt to pick an example and a render function
-def get_response(prompt: str, *kargs):
-    on_render = st.write
-    response = f"Here's what you asked: '{prompt}'"
-
-    prompt_lower = prompt.lower()
-    if prompt_lower == 'line chart':
-        on_render = st.line_chart
-        response = np.random.randn(30, 30)
-    elif prompt_lower == 'circle chart':
-        on_render = st.write
-        response = circle_chart()
-    elif prompt_lower.startswith('json'):
-        p = prompt_lower.split('json ')[1]
-        on_render = st.write
-        response = from_gpt(p, plot=True)
-    elif prompt_lower == 'plot':
-        on_render = st.write
-        response = plot_chart()
-    else:
-        on_render = st.write
-        response = from_gpt(prompt, plot=False)
-
-    return (response, on_render)
-
-
-
-
-chat = idf_chat.Chat()
-
-sidebar_text = """
-# Ask IDF
-
-
-
-## Example prompts
-Replace `{client}` with a client name. 
-Hint: you can ask IDF to tell you what clients are available
-
-```
-What is the total USD Amount for client {client} for Jan 2022 
-```
-```
-What is the average USD Amount per month for client {client} for 2022
-```
-```
-Trades volume for {client} in May 2022
-```
-```
-Get the total USD amount where Currency Bought is {Currency (e.g. GBP)} for {client} in Jun 2022
-```
-```
-Get the Currency Bought/Sold with least total USD amount for {client} in Mar 2022
-```
-"""
-
-with st.sidebar:
-    st.markdown(sidebar_text)
-
-# prompt = chat.get_promt("Ask IDF Anything")
-
-chat.process(get_response, llm)
diff --git a/spaces/GXSA/bingo/src/components/chat-image.tsx b/spaces/GXSA/bingo/src/components/chat-image.tsx
deleted file mode 100644
index 05ecc9771eada27a0f2d160bb01cba170d37bb09..0000000000000000000000000000000000000000
--- a/spaces/GXSA/bingo/src/components/chat-image.tsx
+++ /dev/null
@@ -1,170 +0,0 @@
-import {
-  useEffect,
-  useState,
-  useCallback,
-  ChangeEvent,
-  ClipboardEvent,
-  MouseEventHandler,
-  FormEvent,
-  useRef
-} from "react"
-import Image from 'next/image'
-import PasteIcon from '@/assets/images/paste.svg'
-import UploadIcon from '@/assets/images/upload.svg'
-import CameraIcon from '@/assets/images/camera.svg'
-import { useBing } from '@/lib/hooks/use-bing'
-import { cn } from '@/lib/utils'
-
-interface ChatImageProps extends Pick<ReturnType<typeof useBing>, 'uploadImage'> {}
-
-const preventDefault: MouseEventHandler<HTMLDivElement> = (event) => {
-  event.nativeEvent.stopImmediatePropagation()
-}
-
-const toBase64 = (file: File): Promise<string> => new Promise((resolve, reject) => {
-  const reader = new FileReader()
-  reader.readAsDataURL(file)
-  reader.onload = () => resolve(reader.result as string)
-  reader.onerror = reject
-})
-
-export function ChatImage({ children, uploadImage }: React.PropsWithChildren<ChatImageProps>) {
-  const videoRef = useRef<HTMLVideoElement>(null)
-  const canvasRef = useRef<HTMLCanvasElement>(null)
-  const mediaStream = useRef<MediaStream>()
-  const [panel, setPanel] = useState('none')
-
-  const upload = useCallback((url: string) => {
-    if (url) {
-      uploadImage(url)
-    }
-    setPanel('none')
-  }, [panel])
-
-  const onUpload = useCallback(async (event: ChangeEvent<HTMLInputElement>) => {
-    const file = event.target.files?.[0]
-    if (file) {
-      const fileDataUrl = await toBase64(file)
-      if (fileDataUrl) {
-        upload(fileDataUrl)
-      }
-    }
-  }, [])
-
-  const onPaste = useCallback((event: ClipboardEvent<HTMLInputElement>) => {
-    const pasteUrl = event.clipboardData.getData('text') ?? ''
-    upload(pasteUrl)
-  }, [])
-
-  const onEnter = useCallback((event: FormEvent<HTMLFormElement>) => {
-    event.preventDefault()
-    event.stopPropagation()
-    // @ts-ignore
-    const inputUrl = event.target.elements.image.value
-    if (inputUrl) {
-      upload(inputUrl)
-    }
-  }, [])
-
-  const openVideo: MouseEventHandler<HTMLButtonElement> = async (event) => {
-    event.stopPropagation()
-    setPanel('camera-mode')
-  }
-
-  const onCapture = () => {
-    if (canvasRef.current && videoRef.current) {
-      const canvas = canvasRef.current
-      canvas.width = videoRef.current!.videoWidth
-      canvas.height = videoRef.current!.videoHeight
-      canvas.getContext('2d')?.drawImage(videoRef.current, 0, 0, canvas.width, canvas.height)
-      const cameraUrl = canvas.toDataURL('image/jpeg')
-      upload(cameraUrl)
-    }
-  }
-
-  useEffect(() => {
-    const handleBlur = () => {
-      if (panel !== 'none') {
-        setPanel('none')
-      }
-    }
-    document.addEventListener('click', handleBlur)
-    return () => {
-      document.removeEventListener('click', handleBlur)
-    }
-  }, [panel])
-
-  useEffect(() => {
-    if (panel === 'camera-mode') {
-      navigator.mediaDevices.getUserMedia({ video: true, audio: false })
-      .then(videoStream => {
-        mediaStream.current = videoStream
-        if (videoRef.current) {
-          videoRef.current.srcObject = videoStream
-        }
-      })
-    } else {
-      if (mediaStream.current) {
-        mediaStream.current.getTracks().forEach(function(track) {
-          track.stop()
-        })
-        mediaStream.current = undefined
-      }
-    }
-  }, [panel])
-
-  return (
-    <div className="visual-search-container">
-      <div onClick={() => panel === 'none' ? setPanel('normal') : setPanel('none')}>{children}</div>
-      <div className={cn('visual-search', panel)} onClick={preventDefault}>
-        <div className="normal-content">
-          <div className="header">
-            <h4>添加图像</h4>
-          </div>
-          <div className="paste">
-            <Image alt="paste" src={PasteIcon} width={24} />
-            <form onSubmitCapture={onEnter}>
-              <input
-                className="paste-input"
-                id="sb_imgpst"
-                type="text"
-                name="image"
-                placeholder="粘贴图像 URL"
-                aria-label="粘贴图像 URL"
-                onPaste={onPaste}
-                onClickCapture={(e) => e.stopPropagation()}
-              />
-            </form>
-          </div>
-          <div className="buttons">
-            <button type="button" aria-label="从此设备上传">
-              <input
-                id="vs_fileinput"
-                className="fileinput"
-                type="file"
-                accept="image/gif, image/jpeg, image/png, image/webp"
-                onChange={onUpload}
-              />
-              <Image alt="uplaod" src={UploadIcon} width={20} />
-              从此设备上传
-            </button>
-            <button type="button" aria-label="拍照" onClick={openVideo}>
-              <Image alt="camera" src={CameraIcon} width={20} />
-              拍照
-            </button>
-          </div>
-        </div>
-        {panel === 'camera-mode' && <div className="cam-content">
-          <div className="webvideo-container">
-            <video className="webvideo" autoPlay muted playsInline ref={videoRef} />
-            <canvas className="webcanvas" ref={canvasRef} />
-          </div>
-          <div className="cambtn" role="button" aria-label="拍照" onClick={onCapture}>
-            <div className="cam-btn-circle-large"></div>
-            <div className="cam-btn-circle-small"></div>
-          </div>
-        </div>}
-      </div>
-    </div>
-  )
-}
diff --git a/spaces/GeorgeOrville/bingo/src/app/layout.tsx b/spaces/GeorgeOrville/bingo/src/app/layout.tsx
deleted file mode 100644
index 8b5122759987177b8dc4e4356d1d06cea25c15ea..0000000000000000000000000000000000000000
--- a/spaces/GeorgeOrville/bingo/src/app/layout.tsx
+++ /dev/null
@@ -1,47 +0,0 @@
-import { Metadata } from 'next'
-import { Toaster } from 'react-hot-toast'
-import { TailwindIndicator } from '@/components/tailwind-indicator'
-import { Providers } from '@/components/providers'
-import { Header } from '@/components/header'
-
-import '@/app/globals.scss'
-
-
-export const metadata: Metadata = {
-  title: {
-    default: 'Bing AI Chatbot',
-    template: `%s - Bing AI Chatbot`
-  },
-  description: 'Bing AI Chatbot Web App.',
-  themeColor: [
-    { media: '(prefers-color-scheme: light)', color: 'white' },
-    { media: '(prefers-color-scheme: dark)', color: 'dark' }
-  ],
-  icons: {
-    icon: '/favicon.ico',
-    shortcut: '../assets/images/logo.svg',
-    apple: '../assets/images/logo.svg'
-  }
-}
-
-interface RootLayoutProps {
-  children: React.ReactNode
-}
-
-export default function RootLayout({ children }: RootLayoutProps) {
-  return (
-    <html lang="zh-CN" suppressHydrationWarning>
-      <body>
-        <Toaster />
-        <Providers attribute="class" defaultTheme="system" enableSystem>
-          <div className="flex flex-col min-h-screen">
-            {/* @ts-ignore */}
-            <Header />
-            <main className="flex flex-col flex-1">{children}</main>
-          </div>
-          <TailwindIndicator />
-        </Providers>
-      </body>
-    </html>
-  )
-}
diff --git a/spaces/Gradio-Blocks/uniformer_image_detection/mmdet/models/dense_heads/pisa_ssd_head.py b/spaces/Gradio-Blocks/uniformer_image_detection/mmdet/models/dense_heads/pisa_ssd_head.py
deleted file mode 100644
index 90ef3c83ed62d8346c8daef01f18ad7bd236623c..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_detection/mmdet/models/dense_heads/pisa_ssd_head.py
+++ /dev/null
@@ -1,139 +0,0 @@
-import torch
-
-from mmdet.core import multi_apply
-from ..builder import HEADS
-from ..losses import CrossEntropyLoss, SmoothL1Loss, carl_loss, isr_p
-from .ssd_head import SSDHead
-
-
-# TODO: add loss evaluator for SSD
-@HEADS.register_module()
-class PISASSDHead(SSDHead):
-
-    def loss(self,
-             cls_scores,
-             bbox_preds,
-             gt_bboxes,
-             gt_labels,
-             img_metas,
-             gt_bboxes_ignore=None):
-        """Compute losses of the head.
-
-        Args:
-            cls_scores (list[Tensor]): Box scores for each scale level
-                Has shape (N, num_anchors * num_classes, H, W)
-            bbox_preds (list[Tensor]): Box energies / deltas for each scale
-                level with shape (N, num_anchors * 4, H, W)
-            gt_bboxes (list[Tensor]): Ground truth bboxes of each image
-                with shape (num_obj, 4).
-            gt_labels (list[Tensor]): Ground truth labels of each image
-                with shape (num_obj, 4).
-            img_metas (list[dict]): Meta information of each image, e.g.,
-                image size, scaling factor, etc.
-            gt_bboxes_ignore (list[Tensor]): Ignored gt bboxes of each image.
-                Default: None.
-
-        Returns:
-            dict: Loss dict, comprise classification loss regression loss and
-                carl loss.
-        """
-        featmap_sizes = [featmap.size()[-2:] for featmap in cls_scores]
-        assert len(featmap_sizes) == self.anchor_generator.num_levels
-
-        device = cls_scores[0].device
-
-        anchor_list, valid_flag_list = self.get_anchors(
-            featmap_sizes, img_metas, device=device)
-        cls_reg_targets = self.get_targets(
-            anchor_list,
-            valid_flag_list,
-            gt_bboxes,
-            img_metas,
-            gt_bboxes_ignore_list=gt_bboxes_ignore,
-            gt_labels_list=gt_labels,
-            label_channels=1,
-            unmap_outputs=False,
-            return_sampling_results=True)
-        if cls_reg_targets is None:
-            return None
-        (labels_list, label_weights_list, bbox_targets_list, bbox_weights_list,
-         num_total_pos, num_total_neg, sampling_results_list) = cls_reg_targets
-
-        num_images = len(img_metas)
-        all_cls_scores = torch.cat([
-            s.permute(0, 2, 3, 1).reshape(
-                num_images, -1, self.cls_out_channels) for s in cls_scores
-        ], 1)
-        all_labels = torch.cat(labels_list, -1).view(num_images, -1)
-        all_label_weights = torch.cat(label_weights_list,
-                                      -1).view(num_images, -1)
-        all_bbox_preds = torch.cat([
-            b.permute(0, 2, 3, 1).reshape(num_images, -1, 4)
-            for b in bbox_preds
-        ], -2)
-        all_bbox_targets = torch.cat(bbox_targets_list,
-                                     -2).view(num_images, -1, 4)
-        all_bbox_weights = torch.cat(bbox_weights_list,
-                                     -2).view(num_images, -1, 4)
-
-        # concat all level anchors to a single tensor
-        all_anchors = []
-        for i in range(num_images):
-            all_anchors.append(torch.cat(anchor_list[i]))
-
-        isr_cfg = self.train_cfg.get('isr', None)
-        all_targets = (all_labels.view(-1), all_label_weights.view(-1),
-                       all_bbox_targets.view(-1,
-                                             4), all_bbox_weights.view(-1, 4))
-        # apply ISR-P
-        if isr_cfg is not None:
-            all_targets = isr_p(
-                all_cls_scores.view(-1, all_cls_scores.size(-1)),
-                all_bbox_preds.view(-1, 4),
-                all_targets,
-                torch.cat(all_anchors),
-                sampling_results_list,
-                loss_cls=CrossEntropyLoss(),
-                bbox_coder=self.bbox_coder,
-                **self.train_cfg.isr,
-                num_class=self.num_classes)
-            (new_labels, new_label_weights, new_bbox_targets,
-             new_bbox_weights) = all_targets
-            all_labels = new_labels.view(all_labels.shape)
-            all_label_weights = new_label_weights.view(all_label_weights.shape)
-            all_bbox_targets = new_bbox_targets.view(all_bbox_targets.shape)
-            all_bbox_weights = new_bbox_weights.view(all_bbox_weights.shape)
-
-        # add CARL loss
-        carl_loss_cfg = self.train_cfg.get('carl', None)
-        if carl_loss_cfg is not None:
-            loss_carl = carl_loss(
-                all_cls_scores.view(-1, all_cls_scores.size(-1)),
-                all_targets[0],
-                all_bbox_preds.view(-1, 4),
-                all_targets[2],
-                SmoothL1Loss(beta=1.),
-                **self.train_cfg.carl,
-                avg_factor=num_total_pos,
-                num_class=self.num_classes)
-
-        # check NaN and Inf
-        assert torch.isfinite(all_cls_scores).all().item(), \
-            'classification scores become infinite or NaN!'
-        assert torch.isfinite(all_bbox_preds).all().item(), \
-            'bbox predications become infinite or NaN!'
-
-        losses_cls, losses_bbox = multi_apply(
-            self.loss_single,
-            all_cls_scores,
-            all_bbox_preds,
-            all_anchors,
-            all_labels,
-            all_label_weights,
-            all_bbox_targets,
-            all_bbox_weights,
-            num_total_samples=num_total_pos)
-        loss_dict = dict(loss_cls=losses_cls, loss_bbox=losses_bbox)
-        if carl_loss_cfg is not None:
-            loss_dict.update(loss_carl)
-        return loss_dict
diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/ocrnet/ocrnet_hr48_512x1024_80k_cityscapes.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/ocrnet/ocrnet_hr48_512x1024_80k_cityscapes.py
deleted file mode 100644
index 1b2e0094393151fa8975a0d53c48b6048b7e1929..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/ocrnet/ocrnet_hr48_512x1024_80k_cityscapes.py
+++ /dev/null
@@ -1,39 +0,0 @@
-_base_ = './ocrnet_hr18_512x1024_80k_cityscapes.py'
-norm_cfg = dict(type='SyncBN', requires_grad=True)
-model = dict(
-    pretrained='open-mmlab://msra/hrnetv2_w48',
-    backbone=dict(
-        extra=dict(
-            stage2=dict(num_channels=(48, 96)),
-            stage3=dict(num_channels=(48, 96, 192)),
-            stage4=dict(num_channels=(48, 96, 192, 384)))),
-    decode_head=[
-        dict(
-            type='FCNHead',
-            in_channels=[48, 96, 192, 384],
-            channels=sum([48, 96, 192, 384]),
-            input_transform='resize_concat',
-            in_index=(0, 1, 2, 3),
-            kernel_size=1,
-            num_convs=1,
-            norm_cfg=norm_cfg,
-            concat_input=False,
-            dropout_ratio=-1,
-            num_classes=19,
-            align_corners=False,
-            loss_decode=dict(
-                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-        dict(
-            type='OCRHead',
-            in_channels=[48, 96, 192, 384],
-            channels=512,
-            ocr_channels=256,
-            input_transform='resize_concat',
-            in_index=(0, 1, 2, 3),
-            norm_cfg=norm_cfg,
-            dropout_ratio=-1,
-            num_classes=19,
-            align_corners=False,
-            loss_decode=dict(
-                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
-    ])
diff --git a/spaces/GrandaddyShmax/MusicGen_Plus_hfv2/tests/modules/test_transformer.py b/spaces/GrandaddyShmax/MusicGen_Plus_hfv2/tests/modules/test_transformer.py
deleted file mode 100644
index ff7dfe4c2de05112aec55ddea9c8fd978668f80b..0000000000000000000000000000000000000000
--- a/spaces/GrandaddyShmax/MusicGen_Plus_hfv2/tests/modules/test_transformer.py
+++ /dev/null
@@ -1,253 +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 itertools import product
-
-import pytest
-import torch
-
-from audiocraft.modules.transformer import (
-    StreamingMultiheadAttention, StreamingTransformer, set_efficient_attention_backend)
-
-
-def test_transformer_causal_streaming():
-    torch.manual_seed(1234)
-
-    for context, custom in product([None, 10], [False, True]):
-        # Test that causality and receptive fields are properly handled.
-        # looking at the gradients
-        tr = StreamingTransformer(
-            16, 4, 1 if context else 2,
-            causal=True, past_context=context, custom=custom,
-            dropout=0.)
-        steps = 20
-        for k in [0, 10, 15, 19]:
-            x = torch.randn(4, steps, 16, requires_grad=True)
-            y = tr(x)
-            y[:, k].abs().sum().backward()
-            if k + 1 < steps:
-                assert torch.allclose(x.grad[:, k + 1:], torch.tensor(0.)), x.grad[:, k + 1:].norm()
-            assert not torch.allclose(x.grad[:, :k + 1], torch.tensor(0.)), x.grad[:, :k + 1].norm()
-            if context is not None and k > context:
-                limit = k - context - 1
-                assert torch.allclose(x.grad[:, :limit],
-                                      torch.tensor(0.)), x.grad[:, :limit].norm()
-
-        # Now check that streaming gives the same result at batch eval.
-        x = torch.randn(4, steps, 16)
-        y = tr(x)
-        ys = []
-        with tr.streaming():
-            for k in range(steps):
-                chunk = x[:, k:k + 1, :]
-                ys.append(tr(chunk))
-        y_stream = torch.cat(ys, dim=1)
-        delta = torch.norm(y_stream - y) / torch.norm(y)
-        assert delta < 1e-6, delta
-
-
-def test_transformer_vs_pytorch():
-    torch.manual_seed(1234)
-    # Check that in the non causal setting, we get the same result as
-    # PyTorch Transformer encoder.
-    for custom in [False, True]:
-        tr = StreamingTransformer(
-            16, 4, 2,
-            causal=False, custom=custom, dropout=0., positional_scale=0.)
-        layer = torch.nn.TransformerEncoderLayer(16, 4, dropout=0., batch_first=True)
-        tr_ref = torch.nn.TransformerEncoder(layer, 2)
-        tr.load_state_dict(tr_ref.state_dict())
-
-        x = torch.randn(4, 20, 16)
-        y = tr(x)
-        y2 = tr_ref(x)
-        delta = torch.norm(y2 - y) / torch.norm(y)
-        assert delta < 1e-6, delta
-
-
-def test_streaming_api():
-    tr = StreamingTransformer(16, 4, 2, causal=True, dropout=0.)
-    tr.eval()
-    steps = 12
-    x = torch.randn(1, steps, 16)
-
-    with torch.no_grad():
-        with tr.streaming():
-            _ = tr(x[:, :1])
-            state = {k: v.clone() for k, v in tr.get_streaming_state().items()}
-            y = tr(x[:, 1:2])
-            tr.set_streaming_state(state)
-            y2 = tr(x[:, 1:2])
-            assert torch.allclose(y, y2), (y - y2).norm()
-            assert tr.flush() is None
-
-
-def test_memory_efficient():
-    for backend in ['torch', 'xformers']:
-        torch.manual_seed(1234)
-        set_efficient_attention_backend(backend)
-
-        tr = StreamingTransformer(
-            16, 4, 2, custom=True, dropout=0., layer_scale=0.1)
-        tr_mem_efficient = StreamingTransformer(
-            16, 4, 2, dropout=0., memory_efficient=True, layer_scale=0.1)
-        tr_mem_efficient.load_state_dict(tr.state_dict())
-        tr.eval()
-        steps = 12
-        x = torch.randn(3, steps, 16)
-
-        with torch.no_grad():
-            y = tr(x)
-            y2 = tr_mem_efficient(x)
-            assert torch.allclose(y, y2), ((y - y2).norm(), backend)
-
-
-def test_attention_as_float32():
-    torch.manual_seed(1234)
-    cases = [
-        {'custom': True},
-        {'custom': False},
-    ]
-    for case in cases:
-        tr = StreamingTransformer(16, 4, 2, dropout=0., dtype=torch.bfloat16, **case)
-        tr_float32 = StreamingTransformer(
-            16, 4, 2, dropout=0., attention_as_float32=True, dtype=torch.bfloat16, **case)
-        if not case['custom']:
-            # we are not using autocast here because it doesn't really
-            # work as expected on CPU, so we have to manually cast the weights of the MHA.
-            for layer in tr_float32.layers:
-                layer.self_attn.mha.to(torch.float32)
-        tr_float32.load_state_dict(tr.state_dict())
-        steps = 12
-        x = torch.randn(3, steps, 16, dtype=torch.bfloat16)
-
-        with torch.no_grad():
-            y = tr(x)
-            y2 = tr_float32(x)
-            assert not torch.allclose(y, y2), (y - y2).norm()
-
-
-@torch.no_grad()
-def test_streaming_memory_efficient():
-    for backend in ['torch', 'xformers']:
-        torch.manual_seed(1234)
-        set_efficient_attention_backend(backend)
-        tr = StreamingTransformer(16, 4, 2, causal=True, dropout=0., custom=True)
-        tr_mem_efficient = StreamingTransformer(
-            16, 4, 2, dropout=0., memory_efficient=True, causal=True)
-        tr.load_state_dict(tr_mem_efficient.state_dict())
-        tr.eval()
-        tr_mem_efficient.eval()
-        steps = 12
-        x = torch.randn(3, steps, 16)
-
-        ref = tr(x)
-
-        with tr_mem_efficient.streaming():
-            outs = []
-            # frame_sizes = [2] + [1] * (steps - 2)
-            frame_sizes = [1] * steps
-
-            for frame_size in frame_sizes:
-                frame = x[:, :frame_size]
-                x = x[:, frame_size:]
-                outs.append(tr_mem_efficient(frame))
-
-        out = torch.cat(outs, dim=1)
-        delta = torch.norm(out - ref) / torch.norm(out)
-        assert delta < 1e-6, delta
-
-
-def test_cross_attention():
-    torch.manual_seed(1234)
-    for norm_first in [True, False]:
-        m = StreamingTransformer(
-            16, 4, 2, cross_attention=False, norm_first=norm_first, dropout=0., custom=True)
-        m_cross = StreamingTransformer(
-            16, 4, 2, cross_attention=True, norm_first=norm_first, dropout=0., custom=True)
-        m_cross.load_state_dict(m.state_dict(), strict=False)
-        x = torch.randn(2, 5, 16)
-        cross_x = torch.randn(2, 3, 16)
-        y_ref = m(x)
-        y_cross_zero = m_cross(x, cross_attention_src=0 * cross_x)
-        # With norm_first, the two should be exactly yhe same,
-        # but with norm_first=False, we get 2 normalization in a row
-        # and the epsilon value leads to a tiny change.
-        atol = 0. if norm_first else 1e-6
-        print((y_ref - y_cross_zero).norm() / y_ref.norm())
-        assert torch.allclose(y_ref, y_cross_zero, atol=atol)
-
-        # We now expect a difference even with a generous atol of 1e-2.
-        y_cross = m_cross(x, cross_attention_src=cross_x)
-        assert not torch.allclose(y_cross, y_cross_zero, atol=1e-2)
-
-        with pytest.raises(AssertionError):
-            _ = m_cross(x)
-            _ = m(x, cross_attention_src=cross_x)
-
-
-def test_cross_attention_compat():
-    torch.manual_seed(1234)
-    num_heads = 2
-    dim = num_heads * 64
-    with pytest.raises(AssertionError):
-        StreamingMultiheadAttention(dim, num_heads, causal=True, cross_attention=True)
-
-    cross_attn = StreamingMultiheadAttention(
-        dim, num_heads, dropout=0, cross_attention=True, custom=True)
-    ref_attn = torch.nn.MultiheadAttention(dim, num_heads, dropout=0, batch_first=True)
-
-    # We can load the regular attention state dict
-    # so we have compat when loading old checkpoints.
-    cross_attn.load_state_dict(ref_attn.state_dict())
-
-    queries = torch.randn(3, 7, dim)
-    keys = torch.randn(3, 9, dim)
-    values = torch.randn(3, 9, dim)
-
-    y = cross_attn(queries, keys, values)[0]
-    y_ref = ref_attn(queries, keys, values)[0]
-    assert torch.allclose(y, y_ref, atol=1e-7), (y - y_ref).norm() / y_ref.norm()
-
-    # Now let's check that streaming is working properly.
-    with cross_attn.streaming():
-        ys = []
-        for step in range(queries.shape[1]):
-            ys.append(cross_attn(queries[:, step: step + 1], keys, values)[0])
-    y_streaming = torch.cat(ys, dim=1)
-    assert torch.allclose(y_streaming, y, atol=1e-7)
-
-
-def test_repeat_kv():
-    torch.manual_seed(1234)
-    num_heads = 8
-    kv_repeat = 4
-    dim = num_heads * 64
-    with pytest.raises(AssertionError):
-        mha = StreamingMultiheadAttention(
-            dim, num_heads, causal=True, kv_repeat=kv_repeat, cross_attention=True)
-        mha = StreamingMultiheadAttention(
-            dim, num_heads, causal=True, kv_repeat=kv_repeat)
-    mha = StreamingMultiheadAttention(
-        dim, num_heads, causal=True, kv_repeat=kv_repeat, custom=True)
-    x = torch.randn(4, 18, dim)
-    y = mha(x, x, x)[0]
-    assert x.shape == y.shape
-
-
-def test_qk_layer_norm():
-    torch.manual_seed(1234)
-    tr = StreamingTransformer(
-        16, 4, 2, custom=True, dropout=0., qk_layer_norm=True, bias_attn=False)
-    steps = 12
-    x = torch.randn(3, steps, 16)
-    y = tr(x)
-
-    tr = StreamingTransformer(
-        16, 4, 2, custom=True, dropout=0., qk_layer_norm=True, cross_attention=True)
-    z = torch.randn(3, 21, 16)
-    y = tr(x, cross_attention_src=z)
-    assert y.shape == x.shape
diff --git a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/configs/__init__.py b/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/configs/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/models/linformer_roberta.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/models/linformer_roberta.py
deleted file mode 100644
index b7bdbb11057d0ba791c2f8c7fb1e77507c90172e..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/models/linformer_roberta.py
+++ /dev/null
@@ -1,120 +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.
-"""
-Linformer: Self-Attention with Linear Complexity
-"""
-
-import logging
-
-import torch
-from fairseq import utils
-from fairseq.models import register_model, register_model_architecture
-from fairseq.models.roberta import (
-    init_bert_params,
-    roberta_base_architecture,
-    roberta_large_architecture,
-    RobertaEncoder,
-    RobertaModel,
-)
-from fairseq.utils import safe_hasattr
-
-from ..modules.linformer_sentence_encoder import LinformerTransformerEncoder
-
-
-logger = logging.getLogger(__name__)
-
-
-@register_model("linformer_roberta")
-class LinformerModel(RobertaModel):
-    @staticmethod
-    def add_args(parser):
-        RobertaModel.add_args(parser)
-
-        # add args for Linformer
-        parser.add_argument(
-            "--compressed", type=int, help="compressed ratio of sequence length"
-        )
-        parser.add_argument(
-            "--shared-kv-compressed",
-            type=int,
-            help="share compressed matrix between k and v, in each layer",
-        )
-        parser.add_argument(
-            "--shared-layer-kv-compressed",
-            type=int,
-            help="share compressed matrix between k and v and across all layers",
-        )
-        parser.add_argument(
-            "--freeze-compress",
-            type=int,
-            help="freeze the parameters in compressed layer",
-        )
-
-    @classmethod
-    def build_model(cls, args, task):
-        """Build a new model instance."""
-
-        # make sure all arguments are present
-        base_architecture(args)
-
-        if not safe_hasattr(args, "max_positions"):
-            args.max_positions = args.tokens_per_sample
-
-        encoder = LinformerEncoder(args, task.source_dictionary)
-        return cls(args, encoder)
-
-
-class LinformerEncoder(RobertaEncoder):
-    """Linformer encoder."""
-
-    def __init__(self, args, dictionary):
-        super().__init__(args, dictionary)
-        self.register_buffer("version", torch.tensor(2))
-
-    def build_encoder(self, args, dictionary, embed_tokens):
-        encoder = LinformerTransformerEncoder(args, dictionary, embed_tokens)
-        encoder.apply(init_bert_params)
-        return encoder
-
-    def upgrade_state_dict_named(self, state_dict, name):
-        super().upgrade_state_dict_named(state_dict, name)
-        prefix = name + "." if name != "" else ""
-
-        # some old checkpoints had weight sharing implemented incorrectly
-        # (note: this was correct in the original paper code)
-        if utils.item(state_dict.get(f"{prefix}version", torch.tensor(1))) < 2:
-            state_dict[f"{prefix}version"] = torch.tensor(1)
-            # check if input embeddings and output embeddings were tied
-            if not torch.allclose(
-                state_dict[f"{prefix}sentence_encoder.embed_tokens.weight"],
-                state_dict[f"{prefix}lm_head.weight"],
-            ):
-                # they weren't tied, re-init the LM head without weight sharing
-                self.lm_head = self.build_lm_head(
-                    embed_dim=self.args.encoder_embed_dim,
-                    output_dim=len(self.dictionary),
-                    activation_fn=self.args.activation_fn,
-                    weight=None,  # don't share weights
-                )
-
-
-@register_model_architecture("linformer_roberta", "linformer_roberta")
-def base_architecture(args):
-    args.compressed = getattr(args, "compressed", 4)
-    args.shared_kv_compressed = getattr(args, "shared_kv_compressed", 0)
-    args.shared_layer_kv_compressed = getattr(args, "shared_layer_kv_compressed", 0)
-    args.freeze_compress = getattr(args, "freeze_compress", 0)
-    roberta_base_architecture(args)
-
-
-@register_model_architecture("linformer_roberta", "linformer_roberta_base")
-def linformer_roberta_base_architecture(args):
-    base_architecture(args)
-
-
-@register_model_architecture("linformer_roberta", "linformer_roberta_large")
-def linformer_roberta_large_architecture(args):
-    roberta_large_architecture(args)
-    base_architecture(args)
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/speech_recognition/new/decoders/viterbi_decoder.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/speech_recognition/new/decoders/viterbi_decoder.py
deleted file mode 100644
index b1c47868fa3b4e21f939b0695ede8d14ba1b168d..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/speech_recognition/new/decoders/viterbi_decoder.py
+++ /dev/null
@@ -1,24 +0,0 @@
-#!/usr/bin/env python3
-
-# 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
-
-from typing import List, Dict
-
-from .base_decoder import BaseDecoder
-
-
-class ViterbiDecoder(BaseDecoder):
-    def decode(
-        self,
-        emissions: torch.FloatTensor,
-    ) -> List[List[Dict[str, torch.LongTensor]]]:
-        def get_pred(e):
-            toks = e.argmax(dim=-1).unique_consecutive()
-            return toks[toks != self.blank]
-
-        return [[{"tokens": get_pred(x), "score": 0}] for x in emissions]
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/unsupervised_quality_estimation/aggregate_scores.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/unsupervised_quality_estimation/aggregate_scores.py
deleted file mode 100644
index 66d50d07ff2067b802b90a2aadd88df23153830a..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/unsupervised_quality_estimation/aggregate_scores.py
+++ /dev/null
@@ -1,41 +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 argparse
-import sys
-
-import numpy as np
-
-
-aggregate_funcs = {
-    "std": np.std,
-    "var": np.var,
-    "median": np.median,
-    "mean": np.mean,
-    "min": np.min,
-    "max": np.max,
-}
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("-i", "--input_file", required=True, type=str)
-    parser.add_argument("-n", "--repeat_times", required=True, type=int)
-    parser.add_argument("-o", "--output_file", required=False)
-    parser.add_argument("-f", "--func", required=False, default="mean")
-    args = parser.parse_args()
-
-    stream = open(args.output_file, "w") if args.output_file else sys.stdout
-
-    segment_scores = []
-    for line in open(args.input_file):
-        segment_scores.append(float(line.strip()))
-        if len(segment_scores) == args.repeat_times:
-            stream.write("{}\n".format(aggregate_funcs[args.func](segment_scores)))
-            segment_scores = []
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/Harveenchadha/Vakyansh-Hindi-TTS/ttsv/src/glow_tts/data_utils.py b/spaces/Harveenchadha/Vakyansh-Hindi-TTS/ttsv/src/glow_tts/data_utils.py
deleted file mode 100644
index b58d84b3df3de3afb0a6a3bb8fadfd7a592dd602..0000000000000000000000000000000000000000
--- a/spaces/Harveenchadha/Vakyansh-Hindi-TTS/ttsv/src/glow_tts/data_utils.py
+++ /dev/null
@@ -1,274 +0,0 @@
-import random
-import numpy as np
-import torch
-import torch.utils.data
-
-import commons
-from utils import load_wav_to_torch, load_filepaths_and_text
-from text import text_to_sequence
-
-class TextMelLoader(torch.utils.data.Dataset):
-    """
-    1) loads audio,text pairs
-    2) normalizes text and converts them to sequences of one-hot vectors
-    3) computes mel-spectrograms from audio files.
-    """
-
-    def __init__(self, audiopaths_and_text, hparams):
-        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
-        self.text_cleaners = hparams.text_cleaners
-        self.max_wav_value = hparams.max_wav_value
-        self.sampling_rate = hparams.sampling_rate
-        self.load_mel_from_disk = hparams.load_mel_from_disk
-        self.add_noise = hparams.add_noise
-        self.symbols = hparams.punc + hparams.chars
-        self.add_blank = getattr(hparams, "add_blank", False)  # improved version
-        self.stft = commons.TacotronSTFT(
-            hparams.filter_length,
-            hparams.hop_length,
-            hparams.win_length,
-            hparams.n_mel_channels,
-            hparams.sampling_rate,
-            hparams.mel_fmin,
-            hparams.mel_fmax,
-        )
-        random.seed(1234)
-        random.shuffle(self.audiopaths_and_text)
-
-    def get_mel_text_pair(self, audiopath_and_text):
-        # separate filename and text
-        audiopath, text = audiopath_and_text[0], audiopath_and_text[1]
-        text = self.get_text(text)
-        mel = self.get_mel(audiopath)
-        return (text, mel)
-
-    def get_mel(self, filename):
-        if not self.load_mel_from_disk:
-            audio, sampling_rate = load_wav_to_torch(filename)
-            if sampling_rate != self.stft.sampling_rate:
-                raise ValueError(
-                    "{} {} SR doesn't match target {} SR".format(
-                        sampling_rate, self.stft.sampling_rate
-                    )
-                )
-            if self.add_noise:
-                audio = audio + torch.rand_like(audio)
-            audio_norm = audio / self.max_wav_value
-            audio_norm = audio_norm.unsqueeze(0)
-            melspec = self.stft.mel_spectrogram(audio_norm)
-            melspec = torch.squeeze(melspec, 0)
-        else:
-            melspec = torch.from_numpy(np.load(filename))
-            assert (
-                melspec.size(0) == self.stft.n_mel_channels
-            ), "Mel dimension mismatch: given {}, expected {}".format(
-                melspec.size(0), self.stft.n_mel_channels
-            )
-
-        return melspec
-
-    def get_text(self, text):
-        text_norm = text_to_sequence(text, self.symbols, self.text_cleaners)
-        if self.add_blank:
-            text_norm = commons.intersperse(
-                text_norm, len(self.symbols)
-            )  # add a blank token, whose id number is len(symbols)
-        text_norm = torch.IntTensor(text_norm)
-        return text_norm
-
-    def __getitem__(self, index):
-        return self.get_mel_text_pair(self.audiopaths_and_text[index])
-
-    def __len__(self):
-        return len(self.audiopaths_and_text)
-
-
-class TextMelCollate:
-    """Zero-pads model inputs and targets based on number of frames per step"""
-
-    def __init__(self, n_frames_per_step=1):
-        self.n_frames_per_step = n_frames_per_step
-
-    def __call__(self, batch):
-        """Collate's training batch from normalized text and mel-spectrogram
-        PARAMS
-        ------
-        batch: [text_normalized, mel_normalized]
-        """
-        # Right zero-pad all one-hot text sequences to max input length
-        input_lengths, ids_sorted_decreasing = torch.sort(
-            torch.LongTensor([len(x[0]) for x in batch]), dim=0, descending=True
-        )
-        max_input_len = input_lengths[0]
-
-        text_padded = torch.LongTensor(len(batch), max_input_len)
-        text_padded.zero_()
-        for i in range(len(ids_sorted_decreasing)):
-            text = batch[ids_sorted_decreasing[i]][0]
-            text_padded[i, : text.size(0)] = text
-
-        # Right zero-pad mel-spec
-        num_mels = batch[0][1].size(0)
-        max_target_len = max([x[1].size(1) for x in batch])
-        if max_target_len % self.n_frames_per_step != 0:
-            max_target_len += (
-                self.n_frames_per_step - max_target_len % self.n_frames_per_step
-            )
-            assert max_target_len % self.n_frames_per_step == 0
-
-        # include mel padded
-        mel_padded = torch.FloatTensor(len(batch), num_mels, max_target_len)
-        mel_padded.zero_()
-        output_lengths = torch.LongTensor(len(batch))
-        for i in range(len(ids_sorted_decreasing)):
-            mel = batch[ids_sorted_decreasing[i]][1]
-            mel_padded[i, :, : mel.size(1)] = mel
-            output_lengths[i] = mel.size(1)
-
-        return text_padded, input_lengths, mel_padded, output_lengths
-
-
-"""Multi speaker version"""
-
-
-class TextMelSpeakerLoader(torch.utils.data.Dataset):
-    """
-    1) loads audio, speaker_id, text pairs
-    2) normalizes text and converts them to sequences of one-hot vectors
-    3) computes mel-spectrograms from audio files.
-    """
-
-    def __init__(self, audiopaths_sid_text, hparams):
-        self.audiopaths_sid_text = load_filepaths_and_text(audiopaths_sid_text)
-        self.text_cleaners = hparams.text_cleaners
-        self.max_wav_value = hparams.max_wav_value
-        self.sampling_rate = hparams.sampling_rate
-        self.load_mel_from_disk = hparams.load_mel_from_disk
-        self.add_noise = hparams.add_noise
-        self.symbols = hparams.punc + hparams.chars
-        self.add_blank = getattr(hparams, "add_blank", False)  # improved version
-        self.min_text_len = getattr(hparams, "min_text_len", 1)
-        self.max_text_len = getattr(hparams, "max_text_len", 190)
-        self.stft = commons.TacotronSTFT(
-            hparams.filter_length,
-            hparams.hop_length,
-            hparams.win_length,
-            hparams.n_mel_channels,
-            hparams.sampling_rate,
-            hparams.mel_fmin,
-            hparams.mel_fmax,
-        )
-
-        self._filter_text_len()
-        random.seed(1234)
-        random.shuffle(self.audiopaths_sid_text)
-
-    def _filter_text_len(self):
-        audiopaths_sid_text_new = []
-        for audiopath, sid, text in self.audiopaths_sid_text:
-            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
-                audiopaths_sid_text_new.append([audiopath, sid, text])
-        self.audiopaths_sid_text = audiopaths_sid_text_new
-
-    def get_mel_text_speaker_pair(self, audiopath_sid_text):
-        # separate filename, speaker_id and text
-        audiopath, sid, text = (
-            audiopath_sid_text[0],
-            audiopath_sid_text[1],
-            audiopath_sid_text[2],
-        )
-        text = self.get_text(text)
-        mel = self.get_mel(audiopath)
-        sid = self.get_sid(sid)
-        return (text, mel, sid)
-
-    def get_mel(self, filename):
-        if not self.load_mel_from_disk:
-            audio, sampling_rate = load_wav_to_torch(filename)
-            if sampling_rate != self.stft.sampling_rate:
-                raise ValueError(
-                    "{} {} SR doesn't match target {} SR".format(
-                        sampling_rate, self.stft.sampling_rate
-                    )
-                )
-            if self.add_noise:
-                audio = audio + torch.rand_like(audio)
-            audio_norm = audio / self.max_wav_value
-            audio_norm = audio_norm.unsqueeze(0)
-            melspec = self.stft.mel_spectrogram(audio_norm)
-            melspec = torch.squeeze(melspec, 0)
-        else:
-            melspec = torch.from_numpy(np.load(filename))
-            assert (
-                melspec.size(0) == self.stft.n_mel_channels
-            ), "Mel dimension mismatch: given {}, expected {}".format(
-                melspec.size(0), self.stft.n_mel_channels
-            )
-
-        return melspec
-
-    def get_text(self, text):
-        text_norm = text_to_sequence(text, self.symbols, self.text_cleaners)
-        if self.add_blank:
-            text_norm = commons.intersperse(
-                text_norm, len(self.symbols)
-            )  # add a blank token, whose id number is len(symbols)
-        text_norm = torch.IntTensor(text_norm)
-        return text_norm
-
-    def get_sid(self, sid):
-        sid = torch.IntTensor([int(sid)])
-        return sid
-
-    def __getitem__(self, index):
-        return self.get_mel_text_speaker_pair(self.audiopaths_sid_text[index])
-
-    def __len__(self):
-        return len(self.audiopaths_sid_text)
-
-
-class TextMelSpeakerCollate:
-    """Zero-pads model inputs and targets based on number of frames per step"""
-
-    def __init__(self, n_frames_per_step=1):
-        self.n_frames_per_step = n_frames_per_step
-
-    def __call__(self, batch):
-        """Collate's training batch from normalized text and mel-spectrogram
-        PARAMS
-        ------
-        batch: [text_normalized, mel_normalized]
-        """
-        # Right zero-pad all one-hot text sequences to max input length
-        input_lengths, ids_sorted_decreasing = torch.sort(
-            torch.LongTensor([len(x[0]) for x in batch]), dim=0, descending=True
-        )
-        max_input_len = input_lengths[0]
-
-        text_padded = torch.LongTensor(len(batch), max_input_len)
-        text_padded.zero_()
-        for i in range(len(ids_sorted_decreasing)):
-            text = batch[ids_sorted_decreasing[i]][0]
-            text_padded[i, : text.size(0)] = text
-
-        # Right zero-pad mel-spec
-        num_mels = batch[0][1].size(0)
-        max_target_len = max([x[1].size(1) for x in batch])
-        if max_target_len % self.n_frames_per_step != 0:
-            max_target_len += (
-                self.n_frames_per_step - max_target_len % self.n_frames_per_step
-            )
-            assert max_target_len % self.n_frames_per_step == 0
-
-        # include mel padded & sid
-        mel_padded = torch.FloatTensor(len(batch), num_mels, max_target_len)
-        mel_padded.zero_()
-        output_lengths = torch.LongTensor(len(batch))
-        sid = torch.LongTensor(len(batch))
-        for i in range(len(ids_sorted_decreasing)):
-            mel = batch[ids_sorted_decreasing[i]][1]
-            mel_padded[i, :, : mel.size(1)] = mel
-            output_lengths[i] = mel.size(1)
-            sid[i] = batch[ids_sorted_decreasing[i]][2]
-
-        return text_padded, input_lengths, mel_padded, output_lengths, sid
diff --git a/spaces/Harveenchadha/Vakyansh-Odia-TTS/ttsv/scripts/data/resample.sh b/spaces/Harveenchadha/Vakyansh-Odia-TTS/ttsv/scripts/data/resample.sh
deleted file mode 100644
index 8489b0a0056d46a93d24db8dba173ad7a4b8a44a..0000000000000000000000000000000000000000
--- a/spaces/Harveenchadha/Vakyansh-Odia-TTS/ttsv/scripts/data/resample.sh
+++ /dev/null
@@ -1,14 +0,0 @@
-input_wav_path='/home/harveen/en/iitm_data/english/wav/'
-output_wav_path='/home/harveen/en/iitm_data/english/wav_22k/'
-output_sample_rate=22050
-
-#######################
-
-dir=$PWD
-parentdir="$(dirname "$dir")"
-parentdir="$(dirname "$parentdir")"
-
-mkdir -p $output_wav_path
-python $parentdir/utils/data/resample.py -i $input_wav_path -o $output_wav_path -s $output_sample_rate
-
-python $parentdir/utils/data/duration.py $output_wav_path
diff --git a/spaces/Heisenberg08/Ai_Portrait_Mode/model.py b/spaces/Heisenberg08/Ai_Portrait_Mode/model.py
deleted file mode 100644
index 7fbde23fa5df96794746ccbb7ccf1335d2e5c389..0000000000000000000000000000000000000000
--- a/spaces/Heisenberg08/Ai_Portrait_Mode/model.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import torch
-import torch.nn as nn
-import torchvision.transforms.functional as TF
-
-class DoubleConv(nn.Module):
-    def __init__(self, in_channels, out_channels):
-        super(DoubleConv, self).__init__()
-        self.conv = nn.Sequential(
-            nn.Conv2d(in_channels, out_channels, 3, 1, 1, bias=False),
-            nn.BatchNorm2d(out_channels),
-            nn.ReLU(inplace=True),
-            nn.Conv2d(out_channels, out_channels, 3, 1, 1, bias=False),
-            nn.BatchNorm2d(out_channels),
-            nn.ReLU(inplace=True),
-        )
-
-    def forward(self, x):
-        return self.conv(x)
-
-class UNET(nn.Module):
-    def __init__(
-            self, in_channels=3, out_channels=1, features=[64, 128, 256, 512],
-    ):
-        super(UNET, self).__init__()
-        self.ups = nn.ModuleList()
-        self.downs = nn.ModuleList()
-        self.pool = nn.MaxPool2d(kernel_size=2, stride=2)
-
-        # Down part of UNET
-        for feature in features:
-            self.downs.append(DoubleConv(in_channels, feature))
-            in_channels = feature
-
-        # Up part of UNET
-        for feature in reversed(features):
-            self.ups.append(
-                nn.ConvTranspose2d(
-                    feature*2, feature, kernel_size=2, stride=2,
-                )
-            )
-            self.ups.append(DoubleConv(feature*2, feature))
-
-        self.bottleneck = DoubleConv(features[-1], features[-1]*2)
-        self.final_conv = nn.Conv2d(features[0], out_channels, kernel_size=1)
-
-    def forward(self, x):
-        skip_connections = []
-
-        for down in self.downs:
-            x = down(x)
-            skip_connections.append(x)
-            x = self.pool(x)
-
-        x = self.bottleneck(x)
-        skip_connections = skip_connections[::-1]
-
-        for idx in range(0, len(self.ups), 2):
-            x = self.ups[idx](x)
-            skip_connection = skip_connections[idx//2]
-
-            if x.shape != skip_connection.shape:
-                x = TF.resize(x, size=skip_connection.shape[2:])
-
-            concat_skip = torch.cat((skip_connection, x), dim=1)
-            x = self.ups[idx+1](concat_skip)
-
-        return self.final_conv(x)
-
diff --git a/spaces/Heshwa/html-code-generation-from-images-with-deep-neural-networks/classes/model/Main_Model.py b/spaces/Heshwa/html-code-generation-from-images-with-deep-neural-networks/classes/model/Main_Model.py
deleted file mode 100644
index e3ba6aae6965dd51ed4ebb959828778b5950d9e2..0000000000000000000000000000000000000000
--- a/spaces/Heshwa/html-code-generation-from-images-with-deep-neural-networks/classes/model/Main_Model.py
+++ /dev/null
@@ -1,71 +0,0 @@
-__author__ = 'Taneem Jan, improved the old model through pretrained Auto-encoders'
-
-from keras.layers import Input, Dense, Dropout, RepeatVector, LSTM, concatenate, Flatten
-from keras.models import Sequential, Model
-from tensorflow.keras.optimizers import RMSprop
-from .Config import *
-from .AModel import *
-from .autoencoder_image import *
-
-
-class Main_Model(AModel):
-    def __init__(self, input_shape, output_size, output_path):
-        AModel.__init__(self, input_shape, output_size, output_path)
-        self.name = "Main_Model"
-
-        visual_input = Input(shape=input_shape)
-
-        # Load the pre-trained autoencoder model
-        autoencoder_model = autoencoder_image(input_shape, input_shape, output_path)
-        autoencoder_model.load('autoencoder')
-        path = "classes/model/bin/"
-        path_to_autoencoder = "{}autoencoder.h5".format(path)
-        autoencoder_model.model.load_weights(path_to_autoencoder)
-        # Get only the model up to the encoded part
-        hidden_layer_model_freeze = Model(
-            inputs=autoencoder_model.model.input,
-            outputs=autoencoder_model.model.get_layer('encoded_layer').output
-        )
-        hidden_layer_input = hidden_layer_model_freeze(visual_input)
-
-        # Additional layers before concatenation
-        hidden_layer_model = Flatten()(hidden_layer_input)
-        hidden_layer_model = Dense(1024, activation='relu')(hidden_layer_model)
-        hidden_layer_model = Dropout(0.3)(hidden_layer_model)
-        hidden_layer_model = Dense(1024, activation='relu')(hidden_layer_model)
-        hidden_layer_model = Dropout(0.3)(hidden_layer_model)
-        hidden_layer_result = RepeatVector(CONTEXT_LENGTH)(hidden_layer_model)
-
-        # Making sure the loaded hidden_layer_model_freeze will no longer be updated
-        for layer in hidden_layer_model_freeze.layers:
-            layer.trainable = False
-
-        # The same language model that of pix2code by Tony Beltramelli
-        language_model = Sequential()
-        language_model.add(LSTM(128, return_sequences=True, input_shape=(CONTEXT_LENGTH, output_size)))
-        language_model.add(LSTM(128, return_sequences=True))
-
-        textual_input = Input(shape=(CONTEXT_LENGTH, output_size))
-        encoded_text = language_model(textual_input)
-
-        decoder = concatenate([hidden_layer_result, encoded_text])
-
-        decoder = LSTM(512, return_sequences=True)(decoder)
-        decoder = LSTM(512, return_sequences=False)(decoder)
-        decoder = Dense(output_size, activation='softmax')(decoder)
-
-        self.model = Model(inputs=[visual_input, textual_input], outputs=decoder)
-
-        optimizer = RMSprop(learning_rate=0.0001, clipvalue=1.0)
-        self.model.compile(loss='categorical_crossentropy', optimizer=optimizer)
-
-    def fit_generator(self, generator, steps_per_epoch):
-        # self.model.summary()
-        self.model.fit_generator(generator, steps_per_epoch=steps_per_epoch, epochs=EPOCHS, verbose=1)
-        self.save()
-
-    def predict(self, image, partial_caption):
-        return self.model.predict([image, partial_caption], verbose=0)[0]
-
-    def predict_batch(self, images, partial_captions):
-        return self.model.predict([images, partial_captions], verbose=1)
diff --git a/spaces/HugoDzz/spaceship_drift/vite.config.ts b/spaces/HugoDzz/spaceship_drift/vite.config.ts
deleted file mode 100644
index bbf8c7da43f0080dc6b9fb275f9583b7c17f1506..0000000000000000000000000000000000000000
--- a/spaces/HugoDzz/spaceship_drift/vite.config.ts
+++ /dev/null
@@ -1,6 +0,0 @@
-import { sveltekit } from '@sveltejs/kit/vite';
-import { defineConfig } from 'vite';
-
-export default defineConfig({
-	plugins: [sveltekit()]
-});
diff --git a/spaces/ICML2022/OFA/fairseq/examples/speech_to_text/simultaneous_translation/agents/fairseq_simul_st_agent.py b/spaces/ICML2022/OFA/fairseq/examples/speech_to_text/simultaneous_translation/agents/fairseq_simul_st_agent.py
deleted file mode 100644
index 61617a1739ce196abba1e9a6f9ad9e9f4b37b9c1..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/OFA/fairseq/examples/speech_to_text/simultaneous_translation/agents/fairseq_simul_st_agent.py
+++ /dev/null
@@ -1,363 +0,0 @@
-import math
-import os
-import json
-import numpy as np
-import torch
-import torchaudio.compliance.kaldi as kaldi
-import yaml
-from fairseq import checkpoint_utils, tasks
-from fairseq.file_io import PathManager
-
-try:
-    from simuleval import READ_ACTION, WRITE_ACTION, DEFAULT_EOS
-    from simuleval.agents import SpeechAgent
-    from simuleval.states import ListEntry, SpeechStates
-except ImportError:
-    print("Please install simuleval 'pip install simuleval'")
-
-SHIFT_SIZE = 10
-WINDOW_SIZE = 25
-SAMPLE_RATE = 16000
-FEATURE_DIM = 80
-BOW_PREFIX = "\u2581"
-
-
-class OnlineFeatureExtractor:
-    """
-    Extract speech feature on the fly.
-    """
-
-    def __init__(self, args):
-        self.shift_size = args.shift_size
-        self.window_size = args.window_size
-        assert self.window_size >= self.shift_size
-
-        self.sample_rate = args.sample_rate
-        self.feature_dim = args.feature_dim
-        self.num_samples_per_shift = int(self.shift_size * self.sample_rate / 1000)
-        self.num_samples_per_window = int(self.window_size * self.sample_rate / 1000)
-        self.len_ms_to_samples = lambda x: x * self.sample_rate / 1000
-        self.previous_residual_samples = []
-        self.global_cmvn = args.global_cmvn
-
-    def clear_cache(self):
-        self.previous_residual_samples = []
-
-    def __call__(self, new_samples):
-        samples = self.previous_residual_samples + new_samples
-        if len(samples) < self.num_samples_per_window:
-            self.previous_residual_samples = samples
-            return
-
-        # num_frames is the number of frames from the new segment
-        num_frames = math.floor(
-            (len(samples) - self.len_ms_to_samples(self.window_size - self.shift_size))
-            / self.num_samples_per_shift
-        )
-
-        # the number of frames used for feature extraction
-        # including some part of thte previous segment
-        effective_num_samples = int(
-            num_frames * self.len_ms_to_samples(self.shift_size)
-            + self.len_ms_to_samples(self.window_size - self.shift_size)
-        )
-
-        input_samples = samples[:effective_num_samples]
-        self.previous_residual_samples = samples[
-            num_frames * self.num_samples_per_shift:
-        ]
-
-        torch.manual_seed(1)
-        output = kaldi.fbank(
-            torch.FloatTensor(input_samples).unsqueeze(0),
-            num_mel_bins=self.feature_dim,
-            frame_length=self.window_size,
-            frame_shift=self.shift_size,
-        ).numpy()
-
-        output = self.transform(output)
-
-        return torch.from_numpy(output)
-
-    def transform(self, input):
-        if self.global_cmvn is None:
-            return input
-
-        mean = self.global_cmvn["mean"]
-        std = self.global_cmvn["std"]
-
-        x = np.subtract(input, mean)
-        x = np.divide(x, std)
-        return x
-
-
-class TensorListEntry(ListEntry):
-    """
-    Data structure to store a list of tensor.
-    """
-
-    def append(self, value):
-
-        if len(self.value) == 0:
-            self.value = value
-            return
-
-        self.value = torch.cat([self.value] + [value], dim=0)
-
-    def info(self):
-        return {
-            "type": str(self.new_value_type),
-            "length": self.__len__(),
-            "value": "" if type(self.value) is list else self.value.size(),
-        }
-
-
-class FairseqSimulSTAgent(SpeechAgent):
-
-    speech_segment_size = 40  # in ms, 4 pooling ratio * 10 ms step size
-
-    def __init__(self, args):
-        super().__init__(args)
-
-        self.eos = DEFAULT_EOS
-
-        self.gpu = getattr(args, "gpu", False)
-
-        self.args = args
-
-        self.load_model_vocab(args)
-
-        if getattr(
-            self.model.decoder.layers[0].encoder_attn,
-            'pre_decision_ratio',
-            None
-        ) is not None:
-            self.speech_segment_size *= (
-                self.model.decoder.layers[0].encoder_attn.pre_decision_ratio
-            )
-
-        args.global_cmvn = None
-        if args.config:
-            with open(os.path.join(args.data_bin, args.config), "r") as f:
-                config = yaml.load(f, Loader=yaml.BaseLoader)
-
-            if "global_cmvn" in config:
-                args.global_cmvn = np.load(config["global_cmvn"]["stats_npz_path"])
-
-        if args.global_stats:
-            with PathManager.open(args.global_stats, "r") as f:
-                global_cmvn = json.loads(f.read())
-                self.global_cmvn = {"mean": global_cmvn["mean"], "std": global_cmvn["stddev"]}
-
-        self.feature_extractor = OnlineFeatureExtractor(args)
-
-        self.max_len = args.max_len
-
-        self.force_finish = args.force_finish
-
-        torch.set_grad_enabled(False)
-
-    def build_states(self, args, client, sentence_id):
-        # Initialize states here, for example add customized entry to states
-        # This function will be called at beginning of every new sentence
-        states = SpeechStates(args, client, sentence_id, self)
-        self.initialize_states(states)
-        return states
-
-    def to_device(self, tensor):
-        if self.gpu:
-            return tensor.cuda()
-        else:
-            return tensor.cpu()
-
-    @staticmethod
-    def add_args(parser):
-        # fmt: off
-        parser.add_argument('--model-path', type=str, required=True,
-                            help='path to your pretrained model.')
-        parser.add_argument("--data-bin", type=str, required=True,
-                            help="Path of data binary")
-        parser.add_argument("--config", type=str, default=None,
-                            help="Path to config yaml file")
-        parser.add_argument("--global-stats", type=str, default=None,
-                            help="Path to json file containing cmvn stats")
-        parser.add_argument("--tgt-splitter-type", type=str, default="SentencePiece",
-                            help="Subword splitter type for target text")
-        parser.add_argument("--tgt-splitter-path", type=str, default=None,
-                            help="Subword splitter model path for target text")
-        parser.add_argument("--user-dir", type=str, default="examples/simultaneous_translation",
-                            help="User directory for simultaneous translation")
-        parser.add_argument("--max-len", type=int, default=200,
-                            help="Max length of translation")
-        parser.add_argument("--force-finish", default=False, action="store_true",
-                            help="Force the model to finish the hypothsis if the source is not finished")
-        parser.add_argument("--shift-size", type=int, default=SHIFT_SIZE,
-                            help="Shift size of feature extraction window.")
-        parser.add_argument("--window-size", type=int, default=WINDOW_SIZE,
-                            help="Window size of feature extraction window.")
-        parser.add_argument("--sample-rate", type=int, default=SAMPLE_RATE,
-                            help="Sample rate")
-        parser.add_argument("--feature-dim", type=int, default=FEATURE_DIM,
-                            help="Acoustic feature dimension.")
-
-        # fmt: on
-        return parser
-
-    def load_model_vocab(self, args):
-
-        filename = args.model_path
-        if not os.path.exists(filename):
-            raise IOError("Model file not found: {}".format(filename))
-
-        state = checkpoint_utils.load_checkpoint_to_cpu(filename)
-
-        task_args = state["cfg"]["task"]
-        task_args.data = args.data_bin
-
-        if args.config is not None:
-            task_args.config_yaml = args.config
-
-        task = tasks.setup_task(task_args)
-
-        # build model for ensemble
-        state["cfg"]["model"].load_pretrained_encoder_from = None
-        state["cfg"]["model"].load_pretrained_decoder_from = None
-        self.model = task.build_model(state["cfg"]["model"])
-        self.model.load_state_dict(state["model"], strict=True)
-        self.model.eval()
-        self.model.share_memory()
-
-        if self.gpu:
-            self.model.cuda()
-
-        # Set dictionary
-        self.dict = {}
-        self.dict["tgt"] = task.target_dictionary
-
-    def initialize_states(self, states):
-        self.feature_extractor.clear_cache()
-        states.units.source = TensorListEntry()
-        states.units.target = ListEntry()
-        states.incremental_states = dict()
-
-    def segment_to_units(self, segment, states):
-        # Convert speech samples to features
-        features = self.feature_extractor(segment)
-        if features is not None:
-            return [features]
-        else:
-            return []
-
-    def units_to_segment(self, units, states):
-        # Merge sub word to full word.
-        if self.model.decoder.dictionary.eos() == units[0]:
-            return DEFAULT_EOS
-
-        segment = []
-        if None in units.value:
-            units.value.remove(None)
-
-        for index in units:
-            if index is None:
-                units.pop()
-            token = self.model.decoder.dictionary.string([index])
-            if token.startswith(BOW_PREFIX):
-                if len(segment) == 0:
-                    segment += [token.replace(BOW_PREFIX, "")]
-                else:
-                    for j in range(len(segment)):
-                        units.pop()
-
-                    string_to_return = ["".join(segment)]
-
-                    if self.model.decoder.dictionary.eos() == units[0]:
-                        string_to_return += [DEFAULT_EOS]
-
-                    return string_to_return
-            else:
-                segment += [token.replace(BOW_PREFIX, "")]
-
-        if (
-            len(units) > 0
-            and self.model.decoder.dictionary.eos() == units[-1]
-            or len(states.units.target) > self.max_len
-        ):
-            tokens = [self.model.decoder.dictionary.string([unit]) for unit in units]
-            return ["".join(tokens).replace(BOW_PREFIX, "")] + [DEFAULT_EOS]
-
-        return None
-
-    def update_model_encoder(self, states):
-        if len(states.units.source) == 0:
-            return
-        src_indices = self.to_device(
-            states.units.source.value.unsqueeze(0)
-        )
-        src_lengths = self.to_device(
-            torch.LongTensor([states.units.source.value.size(0)])
-        )
-
-        states.encoder_states = self.model.encoder(src_indices, src_lengths)
-        torch.cuda.empty_cache()
-
-    def update_states_read(self, states):
-        # Happens after a read action.
-        self.update_model_encoder(states)
-
-    def policy(self, states):
-        if not getattr(states, "encoder_states", None):
-            return READ_ACTION
-
-        tgt_indices = self.to_device(
-            torch.LongTensor(
-                [self.model.decoder.dictionary.eos()]
-                + [x for x in states.units.target.value if x is not None]
-            ).unsqueeze(0)
-        )
-
-        states.incremental_states["steps"] = {
-            "src": states.encoder_states["encoder_out"][0].size(0),
-            "tgt": 1 + len(states.units.target),
-        }
-
-        states.incremental_states["online"] = {"only": torch.tensor(not states.finish_read())}
-
-        x, outputs = self.model.decoder.forward(
-            prev_output_tokens=tgt_indices,
-            encoder_out=states.encoder_states,
-            incremental_state=states.incremental_states,
-        )
-
-        states.decoder_out = x
-
-        states.decoder_out_extra = outputs
-
-        torch.cuda.empty_cache()
-
-        if outputs.action == 0:
-            return READ_ACTION
-        else:
-            return WRITE_ACTION
-
-    def predict(self, states):
-        decoder_states = states.decoder_out
-
-        lprobs = self.model.get_normalized_probs(
-            [decoder_states[:, -1:]], log_probs=True
-        )
-
-        index = lprobs.argmax(dim=-1)
-
-        index = index[0, 0].item()
-
-        if (
-            self.force_finish
-            and index == self.model.decoder.dictionary.eos()
-            and not states.finish_read()
-        ):
-            # If we want to force finish the translation
-            # (don't stop before finish reading), return a None
-            # self.model.decoder.clear_cache(states.incremental_states)
-            index = None
-
-        return index
diff --git a/spaces/ICML2022/OFA/fairseq/fairseq/nan_detector.py b/spaces/ICML2022/OFA/fairseq/fairseq/nan_detector.py
deleted file mode 100644
index faa8031d4666c9ba9837919fe1c884dacf47ac3a..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/OFA/fairseq/fairseq/nan_detector.py
+++ /dev/null
@@ -1,108 +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 torch
-
-
-logger = logging.getLogger(__name__)
-
-
-class NanDetector:
-    """
-    Detects the first NaN or Inf in forward and/or backward pass and logs, together with the module name
-    """
-
-    def __init__(self, model, forward=True, backward=True):
-        self.bhooks = []
-        self.fhooks = []
-        self.forward = forward
-        self.backward = backward
-        self.named_parameters = list(model.named_parameters())
-        self.reset()
-
-        for name, mod in model.named_modules():
-            mod.__module_name = name
-            self.add_hooks(mod)
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_value, exc_traceback):
-        # Dump out all model gnorms to enable better debugging
-        norm = {}
-        gradients = {}
-        for name, param in self.named_parameters:
-            if param.grad is not None:
-                grad_norm = torch.norm(param.grad.data, p=2, dtype=torch.float32)
-                norm[name] = grad_norm.item()
-                if torch.isnan(grad_norm).any() or torch.isinf(grad_norm).any():
-                    gradients[name] = param.grad.data
-        if len(gradients) > 0:
-            logger.info("Detected nan/inf grad norm, dumping norms...")
-            logger.info(f"norms: {norm}")
-            logger.info(f"gradients: {gradients}")
-
-        self.close()
-
-    def add_hooks(self, module):
-        if self.forward:
-            self.fhooks.append(module.register_forward_hook(self.fhook_fn))
-        if self.backward:
-            self.bhooks.append(module.register_backward_hook(self.bhook_fn))
-
-    def reset(self):
-        self.has_printed_f = False
-        self.has_printed_b = False
-
-    def _detect(self, tensor, name, backward):
-        err = None
-        if (
-            torch.is_floating_point(tensor)
-            # single value tensors (like the loss) will not provide much info
-            and tensor.numel() >= 2
-        ):
-            with torch.no_grad():
-                if torch.isnan(tensor).any():
-                    err = "NaN"
-                elif torch.isinf(tensor).any():
-                    err = "Inf"
-        if err is not None:
-            err = f"{err} detected in output of {name}, shape: {tensor.shape}, {'backward' if backward else 'forward'}"
-        return err
-
-    def _apply(self, module, inp, x, backward):
-        if torch.is_tensor(x):
-            if isinstance(inp, tuple) and len(inp) > 0:
-                inp = inp[0]
-            err = self._detect(x, module.__module_name, backward)
-            if err is not None:
-                if torch.is_tensor(inp) and not backward:
-                    err += (
-                        f" input max: {inp.max().item()}, input min: {inp.min().item()}"
-                    )
-
-                has_printed_attr = "has_printed_b" if backward else "has_printed_f"
-                logger.warning(err)
-                setattr(self, has_printed_attr, True)
-        elif isinstance(x, dict):
-            for v in x.values():
-                self._apply(module, inp, v, backward)
-        elif isinstance(x, list) or isinstance(x, tuple):
-            for v in x:
-                self._apply(module, inp, v, backward)
-
-    def fhook_fn(self, module, inp, output):
-        if not self.has_printed_f:
-            self._apply(module, inp, output, backward=False)
-
-    def bhook_fn(self, module, inp, output):
-        if not self.has_printed_b:
-            self._apply(module, inp, output, backward=True)
-
-    def close(self):
-        for hook in self.fhooks + self.bhooks:
-            hook.remove()
diff --git a/spaces/ICML2022/selection_bias_induced_spurious_correlations/README.md b/spaces/ICML2022/selection_bias_induced_spurious_correlations/README.md
deleted file mode 100644
index 028dd8dcc623918c05e24e51538635a217cff348..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/selection_bias_induced_spurious_correlations/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Selection Bias Induced Spurious Correlations
-emoji: 🐢
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 3.1.0
-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/IIITT/SumMeet/app.py b/spaces/IIITT/SumMeet/app.py
deleted file mode 100644
index 4279c37dd3a8b60c8889926b41da96e9aa5f4759..0000000000000000000000000000000000000000
--- a/spaces/IIITT/SumMeet/app.py
+++ /dev/null
@@ -1,107 +0,0 @@
-"""
-Created on Mon Mar 28 01:04:50 2022
-@author: adeep
-"""
-from fnmatch import translate
-import cv2 as cv
-import tempfile
-import numpy as np
-import pandas as pd
-import streamlit as st 
-import joblib
-import os
-from moviepy.editor import VideoFileClip
-import speech_recognition as sr
-from pydub import AudioSegment
-from pydub.silence import split_on_silence
-import transformers
-from transformers import pipeline
-import nltk
-nltk.download('punkt')
-nltk.download('averaged_perceptron_tagger')
-import nltk
-nltk.download('punkt')
-nltk.download('averaged_perceptron_tagger')
-from nltk.tokenize import sent_tokenize
-import re
-from utils import get_translation, welcome, get_large_audio_transcription
-
-from PIL import Image
-
-#import stanfordnlp
-
-def main():
- 
-    
-    st.title("Summarize Text")
-    video = st.file_uploader("Choose a file", type=['mp4'])
-    button = st.button("Summarize")
-    
-    max_c = st.sidebar.slider('Select max words', 50, 500, step=10, value=150)
-    min_c = st.sidebar.slider('Select min words', 10, 450, step=10, value=50)
-    gen_summ = False
-    
- 
-
-    with st.spinner("Running.."):
-    
-        if button and video:
-            tfile = tempfile.NamedTemporaryFile(delete=False)
-            tfile.write(video.read())
-            #st.write(tfile.name)
-            v = VideoFileClip(tfile.name)
-            v.audio.write_audiofile("movie.wav")
-            #st.video(video, format="video/mp4", start_time=0)
-            #st.audio("movie.wav")
-            whole_text=get_large_audio_transcription("movie.wav")
-            #st.write(whole_text)
-            #summarizer = pipeline("summarization")
-            #summarizer = pipeline("summarization", model="t5-base", tokenizer="t5-base", framework="pt")
-            summarizer = pipeline("summarization", model="t5-large", tokenizer="t5-large", framework="pt")
-            summarized = summarizer(whole_text, min_length=min_c, max_length=max_c)
-            summ=summarized[0]['summary_text']
-            #st.write(summ) 
-            gen_summ = True
-            #stf_nlp = stanfordnlp.Pipeline(processors='tokenize,mwt,pos')
-            #doc = stf_nlp(summ)
-            #l=[w.text.capitalize() if w.upos in ["PROPN","NNS"] else w.text for sent in doc.sentences for w in sent.words]
-            #text=" ".join(l)
-            #summ=truecasing_by_sentence_segmentation(summ)  
-            sentences = sent_tokenize(summ, language='english')
-            # capitalize the sentences
-            sentences_capitalized = [s.capitalize() for s in sentences]
-            # join the capitalized sentences
-            summ = re.sub(" (?=[\.,'!?:;])", "", ' '.join(sentences_capitalized))
-            
-            if 'summary' not in st.session_state:
-                st.session_state.summary=True
-                st.session_state.summarization = summ
-                st.session_state.gen_summ = True
-                
-
-
-    translate = st.sidebar.radio('Do you want to translate the text to any different language?', ('No', 'Yes'))
-    if 'summary' in st.session_state:
-            summarized_text = st.session_state.summarization
-            st.write(summarized_text)
-            gen_summ = st.session_state.gen_summ
-            
-    if translate == 'Yes' and gen_summ == True:
-        lang_list  = ['Hindi', 'Marathi', 'Malayalam', 'Kannada', 'Telugu', 'Tamil', 'Oriya', 'Bengali', 'Gujarati', 'Urdu']
-    
-        s_type = st.sidebar.selectbox('Select the Language in which you want to Translate:',lang_list) 
-        st.sidebar.write('You selected:', s_type)
-
-         
-        translation = get_translation(source='English', dest=s_type, text=summarized_text)
-
-        st.sidebar.write(translation)
-    elif translate == 'Yes' and gen_summ == False:
-        st.error("The summary has not been generated yet. Please generate the summary first and then translate")
-      
-    else:
-         st.write('')
-             
-if __name__ == '__main__':
-    
-    main()
\ No newline at end of file
diff --git a/spaces/Izal887/rvc-ram12/lib/infer_pack/attentions.py b/spaces/Izal887/rvc-ram12/lib/infer_pack/attentions.py
deleted file mode 100644
index 05501be1871643f78dddbeaa529c96667031a8db..0000000000000000000000000000000000000000
--- a/spaces/Izal887/rvc-ram12/lib/infer_pack/attentions.py
+++ /dev/null
@@ -1,417 +0,0 @@
-import copy
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from lib.infer_pack import commons
-from lib.infer_pack import modules
-from lib.infer_pack.modules import LayerNorm
-
-
-class Encoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        window_size=10,
-        **kwargs
-    ):
-        super().__init__()
-        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.window_size = window_size
-
-        self.drop = nn.Dropout(p_dropout)
-        self.attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    window_size=window_size,
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask):
-        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.attn_layers[i](x, x, attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        proximal_bias=False,
-        proximal_init=True,
-        **kwargs
-    ):
-        super().__init__()
-        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.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-
-        self.drop = nn.Dropout(p_dropout)
-        self.self_attn_layers = nn.ModuleList()
-        self.norm_layers_0 = nn.ModuleList()
-        self.encdec_attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.self_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    proximal_bias=proximal_bias,
-                    proximal_init=proximal_init,
-                )
-            )
-            self.norm_layers_0.append(LayerNorm(hidden_channels))
-            self.encdec_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                    causal=True,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask, h, h_mask):
-        """
-        x: decoder input
-        h: encoder output
-        """
-        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
-            device=x.device, dtype=x.dtype
-        )
-        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.self_attn_layers[i](x, x, self_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_0[i](x + y)
-
-            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class MultiHeadAttention(nn.Module):
-    def __init__(
-        self,
-        channels,
-        out_channels,
-        n_heads,
-        p_dropout=0.0,
-        window_size=None,
-        heads_share=True,
-        block_length=None,
-        proximal_bias=False,
-        proximal_init=False,
-    ):
-        super().__init__()
-        assert channels % n_heads == 0
-
-        self.channels = channels
-        self.out_channels = out_channels
-        self.n_heads = n_heads
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-        self.heads_share = heads_share
-        self.block_length = block_length
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-        self.attn = None
-
-        self.k_channels = channels // n_heads
-        self.conv_q = nn.Conv1d(channels, channels, 1)
-        self.conv_k = nn.Conv1d(channels, channels, 1)
-        self.conv_v = nn.Conv1d(channels, channels, 1)
-        self.conv_o = nn.Conv1d(channels, out_channels, 1)
-        self.drop = nn.Dropout(p_dropout)
-
-        if window_size is not None:
-            n_heads_rel = 1 if heads_share else n_heads
-            rel_stddev = self.k_channels**-0.5
-            self.emb_rel_k = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-            self.emb_rel_v = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-
-        nn.init.xavier_uniform_(self.conv_q.weight)
-        nn.init.xavier_uniform_(self.conv_k.weight)
-        nn.init.xavier_uniform_(self.conv_v.weight)
-        if proximal_init:
-            with torch.no_grad():
-                self.conv_k.weight.copy_(self.conv_q.weight)
-                self.conv_k.bias.copy_(self.conv_q.bias)
-
-    def forward(self, x, c, attn_mask=None):
-        q = self.conv_q(x)
-        k = self.conv_k(c)
-        v = self.conv_v(c)
-
-        x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-        x = self.conv_o(x)
-        return x
-
-    def attention(self, query, key, value, mask=None):
-        # reshape [b, d, t] -> [b, n_h, t, d_k]
-        b, d, t_s, t_t = (*key.size(), query.size(2))
-        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-        if self.window_size is not None:
-            assert (
-                t_s == t_t
-            ), "Relative attention is only available for self-attention."
-            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-            rel_logits = self._matmul_with_relative_keys(
-                query / math.sqrt(self.k_channels), key_relative_embeddings
-            )
-            scores_local = self._relative_position_to_absolute_position(rel_logits)
-            scores = scores + scores_local
-        if self.proximal_bias:
-            assert t_s == t_t, "Proximal bias is only available for self-attention."
-            scores = scores + self._attention_bias_proximal(t_s).to(
-                device=scores.device, dtype=scores.dtype
-            )
-        if mask is not None:
-            scores = scores.masked_fill(mask == 0, -1e4)
-            if self.block_length is not None:
-                assert (
-                    t_s == t_t
-                ), "Local attention is only available for self-attention."
-                block_mask = (
-                    torch.ones_like(scores)
-                    .triu(-self.block_length)
-                    .tril(self.block_length)
-                )
-                scores = scores.masked_fill(block_mask == 0, -1e4)
-        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
-        p_attn = self.drop(p_attn)
-        output = torch.matmul(p_attn, value)
-        if self.window_size is not None:
-            relative_weights = self._absolute_position_to_relative_position(p_attn)
-            value_relative_embeddings = self._get_relative_embeddings(
-                self.emb_rel_v, t_s
-            )
-            output = output + self._matmul_with_relative_values(
-                relative_weights, value_relative_embeddings
-            )
-        output = (
-            output.transpose(2, 3).contiguous().view(b, d, t_t)
-        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
-        return output, p_attn
-
-    def _matmul_with_relative_values(self, x, y):
-        """
-        x: [b, h, l, m]
-        y: [h or 1, m, d]
-        ret: [b, h, l, d]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0))
-        return ret
-
-    def _matmul_with_relative_keys(self, x, y):
-        """
-        x: [b, h, l, d]
-        y: [h or 1, m, d]
-        ret: [b, h, l, m]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-        return ret
-
-    def _get_relative_embeddings(self, relative_embeddings, length):
-        max_relative_position = 2 * self.window_size + 1
-        # Pad first before slice to avoid using cond ops.
-        pad_length = max(length - (self.window_size + 1), 0)
-        slice_start_position = max((self.window_size + 1) - length, 0)
-        slice_end_position = slice_start_position + 2 * length - 1
-        if pad_length > 0:
-            padded_relative_embeddings = F.pad(
-                relative_embeddings,
-                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
-            )
-        else:
-            padded_relative_embeddings = relative_embeddings
-        used_relative_embeddings = padded_relative_embeddings[
-            :, slice_start_position:slice_end_position
-        ]
-        return used_relative_embeddings
-
-    def _relative_position_to_absolute_position(self, x):
-        """
-        x: [b, h, l, 2*l-1]
-        ret: [b, h, l, l]
-        """
-        batch, heads, length, _ = x.size()
-        # Concat columns of pad to shift from relative to absolute indexing.
-        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
-
-        # Concat extra elements so to add up to shape (len+1, 2*len-1).
-        x_flat = x.view([batch, heads, length * 2 * length])
-        x_flat = F.pad(
-            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
-        )
-
-        # Reshape and slice out the padded elements.
-        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
-            :, :, :length, length - 1 :
-        ]
-        return x_final
-
-    def _absolute_position_to_relative_position(self, x):
-        """
-        x: [b, h, l, l]
-        ret: [b, h, l, 2*l-1]
-        """
-        batch, heads, length, _ = x.size()
-        # padd along column
-        x = F.pad(
-            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
-        )
-        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
-        # add 0's in the beginning that will skew the elements after reshape
-        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
-        return x_final
-
-    def _attention_bias_proximal(self, length):
-        """Bias for self-attention to encourage attention to close positions.
-        Args:
-          length: an integer scalar.
-        Returns:
-          a Tensor with shape [1, 1, length, length]
-        """
-        r = torch.arange(length, dtype=torch.float32)
-        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        filter_channels,
-        kernel_size,
-        p_dropout=0.0,
-        activation=None,
-        causal=False,
-    ):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.activation = activation
-        self.causal = causal
-
-        if causal:
-            self.padding = self._causal_padding
-        else:
-            self.padding = self._same_padding
-
-        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-        self.drop = nn.Dropout(p_dropout)
-
-    def forward(self, x, x_mask):
-        x = self.conv_1(self.padding(x * x_mask))
-        if self.activation == "gelu":
-            x = x * torch.sigmoid(1.702 * x)
-        else:
-            x = torch.relu(x)
-        x = self.drop(x)
-        x = self.conv_2(self.padding(x * x_mask))
-        return x * x_mask
-
-    def _causal_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = self.kernel_size - 1
-        pad_r = 0
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
-
-    def _same_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = (self.kernel_size - 1) // 2
-        pad_r = self.kernel_size // 2
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
diff --git a/spaces/JMalott/ai_architecture/min_dalle/text_tokenizer.py b/spaces/JMalott/ai_architecture/min_dalle/text_tokenizer.py
deleted file mode 100644
index 563e927a78be51c75151e2dbaf8d643b0e69c199..0000000000000000000000000000000000000000
--- a/spaces/JMalott/ai_architecture/min_dalle/text_tokenizer.py
+++ /dev/null
@@ -1,41 +0,0 @@
-from math import inf
-from typing import List, Tuple
-from emoji import demojize
-
-class TextTokenizer:
-    def __init__(self, vocab: dict, merges: List[str]):
-        self.token_from_subword = vocab
-        pairs = [tuple(pair.split()) for pair in merges]
-        self.rank_from_pair = dict(zip(pairs, range(len(pairs))))
-
-    def tokenize(self, text: str, is_verbose: bool = False) -> List[int]:
-        sep_token = self.token_from_subword['</s>']
-        cls_token = self.token_from_subword['<s>']
-        unk_token = self.token_from_subword['<unk>']
-        text = demojize(text, delimiters=['', ''])
-        text = text.lower().encode("ascii", errors="ignore").decode()
-        tokens = [
-            self.token_from_subword.get(subword, unk_token)
-            for word in text.split(" ") if len(word) > 0
-            for subword in self.get_byte_pair_encoding(word, is_verbose)
-        ]
-        return [cls_token] + tokens + [sep_token]
-
-    def get_byte_pair_encoding(self, word: str, is_verbose: bool) -> List[str]:
-        def get_pair_rank(pair: Tuple[str, str]) -> int:
-            return self.rank_from_pair.get(pair, inf)
-
-        subwords = [chr(ord(" ") + 256)] + list(word)
-        while len(subwords) > 1:
-            pairs = list(zip(subwords[:-1], subwords[1:]))
-            pair_to_merge = min(pairs, key=get_pair_rank)
-            if pair_to_merge not in self.rank_from_pair: break
-            i = pairs.index(pair_to_merge)
-            subwords = (
-                (subwords[:i] if i > 0 else []) + 
-                [subwords[i] + subwords[i + 1]] + 
-                (subwords[i + 2:] if i + 2 < len(subwords) else [])
-            )
-
-        if is_verbose: print(subwords)
-        return subwords
\ No newline at end of file
diff --git a/spaces/JUNGU/VToonify/vtoonify/model/stylegan/op/readme.md b/spaces/JUNGU/VToonify/vtoonify/model/stylegan/op/readme.md
deleted file mode 100644
index 7cffcfc72069ff9a098d292f9e37035031e19081..0000000000000000000000000000000000000000
--- a/spaces/JUNGU/VToonify/vtoonify/model/stylegan/op/readme.md
+++ /dev/null
@@ -1,12 +0,0 @@
-Code from [rosinality-stylegan2-pytorch-cp](https://github.com/senior-sigan/rosinality-stylegan2-pytorch-cpu)
-
-Scripts to convert rosinality/stylegan2-pytorch to the CPU compatible format
-
-If you would like to use CPU for testing or have a problem regarding the cpp extention (fused and upfirdn2d), please make the following changes:
-
-Change `model.stylegan.op`  to `model.stylegan.op_cpu`
-https://github.com/williamyang1991/VToonify/blob/01b383efc00007f9b069585db41a7d31a77a8806/util.py#L14
-
-https://github.com/williamyang1991/VToonify/blob/01b383efc00007f9b069585db41a7d31a77a8806/model/simple_augment.py#L12
-
-https://github.com/williamyang1991/VToonify/blob/01b383efc00007f9b069585db41a7d31a77a8806/model/stylegan/model.py#L11
diff --git a/spaces/JohnSmith9982/ChuanhuChatGPT/modules/models/models.py b/spaces/JohnSmith9982/ChuanhuChatGPT/modules/models/models.py
deleted file mode 100644
index fe1edbc91fc611881f6dff34affd23dc93596699..0000000000000000000000000000000000000000
--- a/spaces/JohnSmith9982/ChuanhuChatGPT/modules/models/models.py
+++ /dev/null
@@ -1,675 +0,0 @@
-from __future__ import annotations
-from typing import TYPE_CHECKING, List
-
-import logging
-import json
-import commentjson as cjson
-import os
-import sys
-import requests
-import urllib3
-import platform
-import base64
-from io import BytesIO
-from PIL import Image
-
-from tqdm import tqdm
-import colorama
-import asyncio
-import aiohttp
-from enum import Enum
-import uuid
-
-from ..presets import *
-from ..index_func import *
-from ..utils import *
-from .. import shared
-from ..config import retrieve_proxy, usage_limit, sensitive_id
-from modules import config
-from .base_model import BaseLLMModel, ModelType
-
-
-class OpenAIClient(BaseLLMModel):
-    def __init__(
-        self,
-        model_name,
-        api_key,
-        system_prompt=INITIAL_SYSTEM_PROMPT,
-        temperature=1.0,
-        top_p=1.0,
-        user_name=""
-    ) -> None:
-        super().__init__(
-            model_name=model_name,
-            temperature=temperature,
-            top_p=top_p,
-            system_prompt=system_prompt,
-            user=user_name
-        )
-        self.api_key = api_key
-        self.need_api_key = True
-        self._refresh_header()
-
-    def get_answer_stream_iter(self):
-        response = self._get_response(stream=True)
-        if response is not None:
-            iter = self._decode_chat_response(response)
-            partial_text = ""
-            for i in iter:
-                partial_text += i
-                yield partial_text
-        else:
-            yield STANDARD_ERROR_MSG + GENERAL_ERROR_MSG
-
-    def get_answer_at_once(self):
-        response = self._get_response()
-        response = json.loads(response.text)
-        content = response["choices"][0]["message"]["content"]
-        total_token_count = response["usage"]["total_tokens"]
-        return content, total_token_count
-
-    def count_token(self, user_input):
-        input_token_count = count_token(construct_user(user_input))
-        if self.system_prompt is not None and len(self.all_token_counts) == 0:
-            system_prompt_token_count = count_token(
-                construct_system(self.system_prompt)
-            )
-            return input_token_count + system_prompt_token_count
-        return input_token_count
-
-    def billing_info(self):
-        try:
-            curr_time = datetime.datetime.now()
-            last_day_of_month = get_last_day_of_month(
-                curr_time).strftime("%Y-%m-%d")
-            first_day_of_month = curr_time.replace(day=1).strftime("%Y-%m-%d")
-            usage_url = f"{shared.state.usage_api_url}?start_date={first_day_of_month}&end_date={last_day_of_month}"
-            try:
-                usage_data = self._get_billing_data(usage_url)
-            except Exception as e:
-                # logging.error(f"获取API使用情况失败: " + str(e))
-                if "Invalid authorization header" in str(e):
-                    return i18n("**获取API使用情况失败**，需在填写`config.json`中正确填写sensitive_id")
-                elif "Incorrect API key provided: sess" in str(e):
-                    return i18n("**获取API使用情况失败**，sensitive_id错误或已过期")
-                return i18n("**获取API使用情况失败**")
-            # rounded_usage = "{:.5f}".format(usage_data["total_usage"] / 100)
-            rounded_usage = round(usage_data["total_usage"] / 100, 5)
-            usage_percent = round(usage_data["total_usage"] / usage_limit, 2)
-            from ..webui import get_html
-            # return i18n("**本月使用金额** ") + f"\u3000 ${rounded_usage}"
-            return get_html("billing_info.html").format(
-                    label = i18n("本月使用金额"),
-                    usage_percent = usage_percent,
-                    rounded_usage = rounded_usage,
-                    usage_limit = usage_limit
-                )
-        except requests.exceptions.ConnectTimeout:
-            status_text = (
-                STANDARD_ERROR_MSG + CONNECTION_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
-            )
-            return status_text
-        except requests.exceptions.ReadTimeout:
-            status_text = STANDARD_ERROR_MSG + READ_TIMEOUT_MSG + ERROR_RETRIEVE_MSG
-            return status_text
-        except Exception as e:
-            import traceback
-            traceback.print_exc()
-            logging.error(i18n("获取API使用情况失败:") + str(e))
-            return STANDARD_ERROR_MSG + ERROR_RETRIEVE_MSG
-
-    def set_token_upper_limit(self, new_upper_limit):
-        pass
-
-    @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(self, stream=False):
-        openai_api_key = self.api_key
-        system_prompt = self.system_prompt
-        history = self.history
-        logging.debug(colorama.Fore.YELLOW +
-                      f"{history}" + colorama.Fore.RESET)
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {openai_api_key}",
-        }
-
-        if system_prompt is not None:
-            history = [construct_system(system_prompt), *history]
-
-        payload = {
-            "model": self.model_name,
-            "messages": history,
-            "temperature": self.temperature,
-            "top_p": self.top_p,
-            "n": self.n_choices,
-            "stream": stream,
-            "presence_penalty": self.presence_penalty,
-            "frequency_penalty": self.frequency_penalty,
-        }
-
-        if self.max_generation_token is not None:
-            payload["max_tokens"] = self.max_generation_token
-        if self.stop_sequence is not None:
-            payload["stop"] = self.stop_sequence
-        if self.logit_bias is not None:
-            payload["logit_bias"] = self.logit_bias
-        if self.user_identifier:
-            payload["user"] = self.user_identifier
-
-        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.debug(f"使用自定义API URL: {shared.state.completion_url}")
-
-        with retrieve_proxy():
-            try:
-                response = requests.post(
-                    shared.state.completion_url,
-                    headers=headers,
-                    json=payload,
-                    stream=stream,
-                    timeout=timeout,
-                )
-            except:
-                return None
-        return response
-
-    def _refresh_header(self):
-        self.headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {sensitive_id}",
-        }
-
-
-    def _get_billing_data(self, billing_url):
-        with retrieve_proxy():
-            response = requests.get(
-                billing_url,
-                headers=self.headers,
-                timeout=TIMEOUT_ALL,
-            )
-
-        if response.status_code == 200:
-            data = response.json()
-            return data
-        else:
-            raise Exception(
-                f"API request failed with status code {response.status_code}: {response.text}"
-            )
-
-    def _decode_chat_response(self, response):
-        error_msg = ""
-        for chunk in response.iter_lines():
-            if chunk:
-                chunk = chunk.decode()
-                chunk_length = len(chunk)
-                try:
-                    chunk = json.loads(chunk[6:])
-                except:
-                    print(i18n("JSON解析错误,收到的内容: ") + f"{chunk}")
-                    error_msg += chunk
-                    continue
-                if chunk_length > 6 and "delta" in chunk["choices"][0]:
-                    if chunk["choices"][0]["finish_reason"] == "stop":
-                        break
-                    try:
-                        yield chunk["choices"][0]["delta"]["content"]
-                    except Exception as e:
-                        # logging.error(f"Error: {e}")
-                        continue
-        if error_msg:
-            raise Exception(error_msg)
-
-    def set_key(self, new_access_key):
-        ret = super().set_key(new_access_key)
-        self._refresh_header()
-        return ret
-
-
-class ChatGLM_Client(BaseLLMModel):
-    def __init__(self, model_name, user_name="") -> None:
-        super().__init__(model_name=model_name, user=user_name)
-        from transformers import AutoTokenizer, AutoModel
-        import torch
-        global CHATGLM_TOKENIZER, CHATGLM_MODEL
-        if CHATGLM_TOKENIZER is None or CHATGLM_MODEL is None:
-            system_name = platform.system()
-            model_path = None
-            if os.path.exists("models"):
-                model_dirs = os.listdir("models")
-                if model_name in model_dirs:
-                    model_path = f"models/{model_name}"
-            if model_path is not None:
-                model_source = model_path
-            else:
-                model_source = f"THUDM/{model_name}"
-            CHATGLM_TOKENIZER = AutoTokenizer.from_pretrained(
-                model_source, trust_remote_code=True
-            )
-            quantified = False
-            if "int4" in model_name:
-                quantified = True
-            model = AutoModel.from_pretrained(
-                model_source, trust_remote_code=True
-            )
-            if torch.cuda.is_available():
-                # run on CUDA
-                logging.info("CUDA is available, using CUDA")
-                model = model.half().cuda()
-            # mps加速还存在一些问题，暂时不使用
-            elif system_name == "Darwin" and model_path is not None and not quantified:
-                logging.info("Running on macOS, using MPS")
-                # running on macOS and model already downloaded
-                model = model.half().to("mps")
-            else:
-                logging.info("GPU is not available, using CPU")
-                model = model.float()
-            model = model.eval()
-            CHATGLM_MODEL = model
-
-    def _get_glm_style_input(self):
-        history = [x["content"] for x in self.history]
-        query = history.pop()
-        logging.debug(colorama.Fore.YELLOW +
-                      f"{history}" + colorama.Fore.RESET)
-        assert (
-            len(history) % 2 == 0
-        ), f"History should be even length. current history is: {history}"
-        history = [[history[i], history[i + 1]]
-                   for i in range(0, len(history), 2)]
-        return history, query
-
-    def get_answer_at_once(self):
-        history, query = self._get_glm_style_input()
-        response, _ = CHATGLM_MODEL.chat(
-            CHATGLM_TOKENIZER, query, history=history)
-        return response, len(response)
-
-    def get_answer_stream_iter(self):
-        history, query = self._get_glm_style_input()
-        for response, history in CHATGLM_MODEL.stream_chat(
-            CHATGLM_TOKENIZER,
-            query,
-            history,
-            max_length=self.token_upper_limit,
-            top_p=self.top_p,
-            temperature=self.temperature,
-        ):
-            yield response
-
-
-class LLaMA_Client(BaseLLMModel):
-    def __init__(
-        self,
-        model_name,
-        lora_path=None,
-        user_name=""
-    ) -> None:
-        super().__init__(model_name=model_name, user=user_name)
-        from lmflow.datasets.dataset import Dataset
-        from lmflow.pipeline.auto_pipeline import AutoPipeline
-        from lmflow.models.auto_model import AutoModel
-        from lmflow.args import ModelArguments, DatasetArguments, InferencerArguments
-
-        self.max_generation_token = 1000
-        self.end_string = "\n\n"
-        # We don't need input data
-        data_args = DatasetArguments(dataset_path=None)
-        self.dataset = Dataset(data_args)
-        self.system_prompt = ""
-
-        global LLAMA_MODEL, LLAMA_INFERENCER
-        if LLAMA_MODEL is None or LLAMA_INFERENCER is None:
-            model_path = None
-            if os.path.exists("models"):
-                model_dirs = os.listdir("models")
-                if model_name in model_dirs:
-                    model_path = f"models/{model_name}"
-            if model_path is not None:
-                model_source = model_path
-            else:
-                model_source = f"decapoda-research/{model_name}"
-                # raise Exception(f"models目录下没有这个模型: {model_name}")
-            if lora_path is not None:
-                lora_path = f"lora/{lora_path}"
-            model_args = ModelArguments(model_name_or_path=model_source, lora_model_path=lora_path, model_type=None, config_overrides=None, config_name=None, tokenizer_name=None, cache_dir=None,
-                                        use_fast_tokenizer=True, model_revision='main', use_auth_token=False, torch_dtype=None, use_lora=False, lora_r=8, lora_alpha=32, lora_dropout=0.1, use_ram_optimized_load=True)
-            pipeline_args = InferencerArguments(
-                local_rank=0, random_seed=1, deepspeed='configs/ds_config_chatbot.json', mixed_precision='bf16')
-
-            with open(pipeline_args.deepspeed, "r", encoding="utf-8") as f:
-                ds_config = json.load(f)
-            LLAMA_MODEL = AutoModel.get_model(
-                model_args,
-                tune_strategy="none",
-                ds_config=ds_config,
-            )
-            LLAMA_INFERENCER = AutoPipeline.get_pipeline(
-                pipeline_name="inferencer",
-                model_args=model_args,
-                data_args=data_args,
-                pipeline_args=pipeline_args,
-            )
-
-    def _get_llama_style_input(self):
-        history = []
-        instruction = ""
-        if self.system_prompt:
-            instruction = (f"Instruction: {self.system_prompt}\n")
-        for x in self.history:
-            if x["role"] == "user":
-                history.append(f"{instruction}Input: {x['content']}")
-            else:
-                history.append(f"Output: {x['content']}")
-        context = "\n\n".join(history)
-        context += "\n\nOutput: "
-        return context
-
-    def get_answer_at_once(self):
-        context = self._get_llama_style_input()
-
-        input_dataset = self.dataset.from_dict(
-            {"type": "text_only", "instances": [{"text": context}]}
-        )
-
-        output_dataset = LLAMA_INFERENCER.inference(
-            model=LLAMA_MODEL,
-            dataset=input_dataset,
-            max_new_tokens=self.max_generation_token,
-            temperature=self.temperature,
-        )
-
-        response = output_dataset.to_dict()["instances"][0]["text"]
-        return response, len(response)
-
-    def get_answer_stream_iter(self):
-        context = self._get_llama_style_input()
-        partial_text = ""
-        step = 1
-        for _ in range(0, self.max_generation_token, step):
-            input_dataset = self.dataset.from_dict(
-                {"type": "text_only", "instances": [
-                    {"text": context + partial_text}]}
-            )
-            output_dataset = LLAMA_INFERENCER.inference(
-                model=LLAMA_MODEL,
-                dataset=input_dataset,
-                max_new_tokens=step,
-                temperature=self.temperature,
-            )
-            response = output_dataset.to_dict()["instances"][0]["text"]
-            if response == "" or response == self.end_string:
-                break
-            partial_text += response
-            yield partial_text
-
-
-class XMChat(BaseLLMModel):
-    def __init__(self, api_key, user_name=""):
-        super().__init__(model_name="xmchat", user=user_name)
-        self.api_key = api_key
-        self.session_id = None
-        self.reset()
-        self.image_bytes = None
-        self.image_path = None
-        self.xm_history = []
-        self.url = "https://xmbot.net/web"
-        self.last_conv_id = None
-
-    def reset(self):
-        self.session_id = str(uuid.uuid4())
-        self.last_conv_id = None
-        return [], "已重置"
-
-    def image_to_base64(self, image_path):
-        # 打开并加载图片
-        img = Image.open(image_path)
-
-        # 获取图片的宽度和高度
-        width, height = img.size
-
-        # 计算压缩比例，以确保最长边小于4096像素
-        max_dimension = 2048
-        scale_ratio = min(max_dimension / width, max_dimension / height)
-
-        if scale_ratio < 1:
-            # 按压缩比例调整图片大小
-            new_width = int(width * scale_ratio)
-            new_height = int(height * scale_ratio)
-            img = img.resize((new_width, new_height), Image.ANTIALIAS)
-
-        # 将图片转换为jpg格式的二进制数据
-        buffer = BytesIO()
-        if img.mode == "RGBA":
-            img = img.convert("RGB")
-        img.save(buffer, format='JPEG')
-        binary_image = buffer.getvalue()
-
-        # 对二进制数据进行Base64编码
-        base64_image = base64.b64encode(binary_image).decode('utf-8')
-
-        return base64_image
-
-    def try_read_image(self, filepath):
-        def is_image_file(filepath):
-            # 判断文件是否为图片
-            valid_image_extensions = [
-                ".jpg", ".jpeg", ".png", ".bmp", ".gif", ".tiff"]
-            file_extension = os.path.splitext(filepath)[1].lower()
-            return file_extension in valid_image_extensions
-
-        if is_image_file(filepath):
-            logging.info(f"读取图片文件: {filepath}")
-            self.image_bytes = self.image_to_base64(filepath)
-            self.image_path = filepath
-        else:
-            self.image_bytes = None
-            self.image_path = None
-
-    def like(self):
-        if self.last_conv_id is None:
-            return "点赞失败，你还没发送过消息"
-        data = {
-            "uuid": self.last_conv_id,
-            "appraise": "good"
-        }
-        requests.post(self.url, json=data)
-        return "👍点赞成功，感谢反馈～"
-
-    def dislike(self):
-        if self.last_conv_id is None:
-            return "点踩失败，你还没发送过消息"
-        data = {
-            "uuid": self.last_conv_id,
-            "appraise": "bad"
-        }
-        requests.post(self.url, json=data)
-        return "👎点踩成功，感谢反馈～"
-
-    def prepare_inputs(self, real_inputs, use_websearch, files, reply_language, chatbot):
-        fake_inputs = real_inputs
-        display_append = ""
-        limited_context = False
-        return limited_context, fake_inputs, display_append, real_inputs, chatbot
-
-    def handle_file_upload(self, files, chatbot, language):
-        """if the model accepts multi modal input, implement this function"""
-        if files:
-            for file in files:
-                if file.name:
-                    logging.info(f"尝试读取图像: {file.name}")
-                    self.try_read_image(file.name)
-            if self.image_path is not None:
-                chatbot = chatbot + [((self.image_path,), None)]
-            if self.image_bytes is not None:
-                logging.info("使用图片作为输入")
-                # XMChat的一轮对话中实际上只能处理一张图片
-                self.reset()
-                conv_id = str(uuid.uuid4())
-                data = {
-                    "user_id": self.api_key,
-                    "session_id": self.session_id,
-                    "uuid": conv_id,
-                    "data_type": "imgbase64",
-                    "data": self.image_bytes
-                }
-                response = requests.post(self.url, json=data)
-                response = json.loads(response.text)
-                logging.info(f"图片回复: {response['data']}")
-        return None, chatbot, None
-
-    def get_answer_at_once(self):
-        question = self.history[-1]["content"]
-        conv_id = str(uuid.uuid4())
-        self.last_conv_id = conv_id
-        data = {
-            "user_id": self.api_key,
-            "session_id": self.session_id,
-            "uuid": conv_id,
-            "data_type": "text",
-            "data": question
-        }
-        response = requests.post(self.url, json=data)
-        try:
-            response = json.loads(response.text)
-            return response["data"], len(response["data"])
-        except Exception as e:
-            return response.text, len(response.text)
-
-
-def get_model(
-    model_name,
-    lora_model_path=None,
-    access_key=None,
-    temperature=None,
-    top_p=None,
-    system_prompt=None,
-    user_name=""
-) -> BaseLLMModel:
-    msg = i18n("模型设置为了：") + f" {model_name}"
-    model_type = ModelType.get_type(model_name)
-    lora_selector_visibility = False
-    lora_choices = []
-    dont_change_lora_selector = False
-    if model_type != ModelType.OpenAI:
-        config.local_embedding = True
-    # del current_model.model
-    model = None
-    chatbot = gr.Chatbot.update(label=model_name)
-    try:
-        if model_type == ModelType.OpenAI:
-            logging.info(f"正在加载OpenAI模型: {model_name}")
-            access_key = os.environ.get("OPENAI_API_KEY", access_key)
-            model = OpenAIClient(
-                model_name=model_name,
-                api_key=access_key,
-                system_prompt=system_prompt,
-                temperature=temperature,
-                top_p=top_p,
-                user_name=user_name,
-            )
-        elif model_type == ModelType.ChatGLM:
-            logging.info(f"正在加载ChatGLM模型: {model_name}")
-            model = ChatGLM_Client(model_name, user_name=user_name)
-        elif model_type == ModelType.LLaMA and lora_model_path == "":
-            msg = f"现在请为 {model_name} 选择LoRA模型"
-            logging.info(msg)
-            lora_selector_visibility = True
-            if os.path.isdir("lora"):
-                lora_choices = get_file_names(
-                    "lora", plain=True, filetypes=[""])
-            lora_choices = ["No LoRA"] + lora_choices
-        elif model_type == ModelType.LLaMA and lora_model_path != "":
-            logging.info(f"正在加载LLaMA模型: {model_name} + {lora_model_path}")
-            dont_change_lora_selector = True
-            if lora_model_path == "No LoRA":
-                lora_model_path = None
-                msg += " + No LoRA"
-            else:
-                msg += f" + {lora_model_path}"
-            model = LLaMA_Client(
-                model_name, lora_model_path, user_name=user_name)
-        elif model_type == ModelType.XMChat:
-            if os.environ.get("XMCHAT_API_KEY") != "":
-                access_key = os.environ.get("XMCHAT_API_KEY")
-            model = XMChat(api_key=access_key, user_name=user_name)
-        elif model_type == ModelType.StableLM:
-            from .StableLM import StableLM_Client
-            model = StableLM_Client(model_name, user_name=user_name)
-        elif model_type == ModelType.MOSS:
-            from .MOSS import MOSS_Client
-            model = MOSS_Client(model_name, user_name=user_name)
-        elif model_type == ModelType.YuanAI:
-            from .inspurai import Yuan_Client
-            model = Yuan_Client(model_name, api_key=access_key, user_name=user_name, system_prompt=system_prompt)
-        elif model_type == ModelType.Minimax:
-            from .minimax import MiniMax_Client
-            if os.environ.get("MINIMAX_API_KEY") != "":
-                access_key = os.environ.get("MINIMAX_API_KEY")
-            model = MiniMax_Client(model_name, api_key=access_key, user_name=user_name, system_prompt=system_prompt)
-        elif model_type == ModelType.ChuanhuAgent:
-            from .ChuanhuAgent import ChuanhuAgent_Client
-            model = ChuanhuAgent_Client(model_name, access_key, user_name=user_name)
-        elif model_type == ModelType.GooglePaLM:
-            from .Google_PaLM import Google_PaLM_Client
-            access_key = os.environ.get("GOOGLE_PALM_API_KEY", access_key)
-            model = Google_PaLM_Client(model_name, access_key, user_name=user_name)
-        elif model_type == ModelType.LangchainChat:
-            from .azure import Azure_OpenAI_Client
-            model = Azure_OpenAI_Client(model_name, user_name=user_name)
-        elif model_type == ModelType.Midjourney:
-            from .midjourney import Midjourney_Client
-            mj_proxy_api_secret = os.getenv("MIDJOURNEY_PROXY_API_SECRET")
-            model = Midjourney_Client(model_name, mj_proxy_api_secret, user_name=user_name)
-        elif model_type == ModelType.Unknown:
-            raise ValueError(f"未知模型: {model_name}")
-        logging.info(msg)
-    except Exception as e:
-        import traceback
-        traceback.print_exc()
-        msg = f"{STANDARD_ERROR_MSG}: {e}"
-    presudo_key = hide_middle_chars(access_key)
-    if dont_change_lora_selector:
-        return model, msg, chatbot, gr.update(), access_key, presudo_key
-    else:
-        return model, msg, chatbot, gr.Dropdown.update(choices=lora_choices, visible=lora_selector_visibility), access_key, presudo_key
-
-
-if __name__ == "__main__":
-    with open("config.json", "r", encoding="utf-8") as f:
-        openai_api_key = cjson.load(f)["openai_api_key"]
-    # set logging level to debug
-    logging.basicConfig(level=logging.DEBUG)
-    # client = ModelManager(model_name="gpt-3.5-turbo", access_key=openai_api_key)
-    client = get_model(model_name="chatglm-6b-int4")
-    chatbot = []
-    stream = False
-    # 测试账单功能
-    logging.info(colorama.Back.GREEN + "测试账单功能" + colorama.Back.RESET)
-    logging.info(client.billing_info())
-    # 测试问答
-    logging.info(colorama.Back.GREEN + "测试问答" + colorama.Back.RESET)
-    question = "巴黎是中国的首都吗？"
-    for i in client.predict(inputs=question, chatbot=chatbot, stream=stream):
-        logging.info(i)
-    logging.info(f"测试问答后history : {client.history}")
-    # 测试记忆力
-    logging.info(colorama.Back.GREEN + "测试记忆力" + colorama.Back.RESET)
-    question = "我刚刚问了你什么问题？"
-    for i in client.predict(inputs=question, chatbot=chatbot, stream=stream):
-        logging.info(i)
-    logging.info(f"测试记忆力后history : {client.history}")
-    # 测试重试功能
-    logging.info(colorama.Back.GREEN + "测试重试功能" + colorama.Back.RESET)
-    for i in client.retry(chatbot=chatbot, stream=stream):
-        logging.info(i)
-    logging.info(f"重试后history : {client.history}")
-    # # 测试总结功能
-    # print(colorama.Back.GREEN + "测试总结功能" + colorama.Back.RESET)
-    # chatbot, msg = client.reduce_token_size(chatbot=chatbot)
-    # print(chatbot, msg)
-    # print(f"总结后history: {client.history}")
diff --git a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/web_assets/html/billing_info.html b/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/web_assets/html/billing_info.html
deleted file mode 100644
index 71abcc802da3c70716919c1a4738ac077c47bf01..0000000000000000000000000000000000000000
--- a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/web_assets/html/billing_info.html
+++ /dev/null
@@ -1,9 +0,0 @@
-<b>{label}</b>
-<div class="progress-bar">
-    <div class="progress" style="width: {usage_percent}%;">
-        <span class="progress-text">{usage_percent}%</span>
-    </div>
-</div>
-<div style="display: flex; justify-content: space-between;">
-    <span>${rounded_usage}</span><span>${usage_limit}</span>
-</div>
\ No newline at end of file
diff --git a/spaces/KenjieDec/GPEN/retinaface/layers/functions/prior_box.py b/spaces/KenjieDec/GPEN/retinaface/layers/functions/prior_box.py
deleted file mode 100644
index c52ec0bdeab7d266698a4aa7dfcedd2540baae3c..0000000000000000000000000000000000000000
--- a/spaces/KenjieDec/GPEN/retinaface/layers/functions/prior_box.py
+++ /dev/null
@@ -1,34 +0,0 @@
-import torch
-from itertools import product as product
-import numpy as np
-from math import ceil
-
-
-class PriorBox(object):
-    def __init__(self, cfg, image_size=None, phase='train'):
-        super(PriorBox, self).__init__()
-        self.msizes = cfg['msizes']
-        self.steps = cfg['steps']
-        self.clip = cfg['clip']
-        self.image_size = image_size
-        self.feature_maps = [[ceil(self.image_size[0]/step), ceil(self.image_size[1]/step)] for step in self.steps]
-        self.name = "s"
-
-    def forward(self):
-        anchors = []
-        for k, f in enumerate(self.feature_maps):
-            msizes = self.msizes[k]
-            for i, j in product(range(f[0]), range(f[1])):
-                for msize in msizes:
-                    s_kx = msize / self.image_size[1]
-                    s_ky = msize / self.image_size[0]
-                    dense_cx = [x * self.steps[k] / self.image_size[1] for x in [j + 0.5]]
-                    dense_cy = [y * self.steps[k] / self.image_size[0] for y in [i + 0.5]]
-                    for cy, cx in product(dense_cy, dense_cx):
-                        anchors += [cx, cy, s_kx, s_ky]
-
-        # back to torch land
-        output = torch.Tensor(anchors).view(-1, 4)
-        if self.clip:
-            output.clamp_(max=1, min=0)
-        return output
diff --git a/spaces/KyanChen/RSPrompter/mmpretrain/apis/multimodal_retrieval.py b/spaces/KyanChen/RSPrompter/mmpretrain/apis/multimodal_retrieval.py
deleted file mode 100644
index 5eb9c859aca309306c1e775b7a03bf3bbc1c7717..0000000000000000000000000000000000000000
--- a/spaces/KyanChen/RSPrompter/mmpretrain/apis/multimodal_retrieval.py
+++ /dev/null
@@ -1,603 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from copy import deepcopy
-from pathlib import Path
-from typing import Callable, List, Optional, Tuple, Union
-
-import mmengine
-import numpy as np
-import torch
-from mmcv.image import imread
-from mmengine.config import Config
-from mmengine.dataset import BaseDataset, Compose, default_collate
-
-from mmpretrain.registry import TRANSFORMS
-from mmpretrain.structures import DataSample
-from mmpretrain.utils import track
-from .base import BaseInferencer
-from .base import InputType as ImageType
-from .base import ModelType
-from .model import list_models
-
-
-def filter_transforms(transforms: list, data_info: dict):
-    """Filter pipeline to avoid KeyError with partial data info."""
-    data_info = deepcopy(data_info)
-    filtered_transforms = []
-    for t in transforms:
-        try:
-            data_info = t(data_info)
-            filtered_transforms.append(t)
-        except KeyError:
-            pass
-    return filtered_transforms
-
-
-class TextToImageRetrievalInferencer(BaseInferencer):
-    """The inferencer for text to image retrieval.
-
-    Args:
-        model (BaseModel | str | Config): A model name or a path to the config
-            file, or a :obj:`BaseModel` object. The model name can be found
-            by ``TextToImageRetrievalInferencer.list_models()`` and you can also
-            query it in :doc:`/modelzoo_statistics`.
-        prototype (str | list | dict | DataLoader | BaseDataset): The images to
-            be retrieved. It can be the following types:
-
-            - str: The directory of the the images.
-            - list: A list of path of the images.
-            - dict: A config dict of the a prototype dataset.
-            - BaseDataset: A prototype dataset.
-            - DataLoader: A data loader to load the prototype data.
-
-        prototype_cache (str, optional): The path of the generated prototype
-            features. If exists, directly load the cache instead of re-generate
-            the prototype features. If not exists, save the generated features
-            to the path. Defaults to None.
-        fast_match (bool): Some algorithms will record extra image features for
-            further matching, which may consume large memory, set True to avoid
-            this behavior. Defaults to True.
-        pretrained (str, optional): Path to the checkpoint. If None, it will
-            try to find a pre-defined weight from the model you specified
-            (only work if the ``model`` is a model name). Defaults to None.
-        device (str, optional): Device to run inference. If None, the available
-            device will be automatically used. Defaults to None.
-        **kwargs: Other keyword arguments to initialize the model (only work if
-            the ``model`` is a model name).
-
-    Example:
-        >>> from mmpretrain import TextToImageRetrievalInferencer
-        >>> inferencer = TextToImageRetrievalInferencer(
-        ...     'blip-base_3rdparty_retrieval',
-        ...     prototype='./demo/',
-        ...     prototype_cache='t2i_retri.pth')
-        >>> inferencer('A cat and a dog.')[0]
-        {'match_score': tensor(0.3855, device='cuda:0'),
-         'sample_idx': 1,
-         'sample': {'img_path': './demo/cat-dog.png'}}
-    """  # noqa: E501
-
-    visualize_kwargs: set = {
-        'draw_score', 'show_dir', 'show', 'wait_time', 'figsize', 'topk'
-    }
-    postprocess_kwargs: set = {'topk'}
-
-    def __init__(self,
-                 model: ModelType,
-                 prototype,
-                 prototype_cache=None,
-                 fast_match=True,
-                 prepare_batch_size=8,
-                 pretrained: Union[bool, str] = True,
-                 device: Union[str, torch.device, None] = None,
-                 **kwargs) -> None:
-        super().__init__(
-            model=model, pretrained=pretrained, device=device, **kwargs)
-
-        self.img_pipeline, self.text_pipeline = self.pipeline
-
-        if hasattr(self.model, 'fast_match'):
-            self.model.fast_match = fast_match
-
-        self.prototype_dataset = self._prepare_prototype(
-            prototype, prototype_cache, batch_size=prepare_batch_size)
-
-    def _prepare_prototype(self, prototype, cache=None, batch_size=8):
-        from mmengine.dataset import DefaultSampler
-        from torch.utils.data import DataLoader
-
-        def build_dataloader(dataset):
-            return DataLoader(
-                dataset,
-                batch_size=batch_size,
-                collate_fn=default_collate,
-                sampler=DefaultSampler(dataset, shuffle=False),
-                persistent_workers=False,
-            )
-
-        if isinstance(prototype, str):
-            # A directory path of images
-            prototype = dict(
-                type='CustomDataset', with_label=False, data_root=prototype)
-
-        if isinstance(prototype, list):
-            test_pipeline = [dict(type='LoadImageFromFile'), self.img_pipeline]
-            dataset = BaseDataset(
-                lazy_init=True, serialize_data=False, pipeline=test_pipeline)
-            dataset.data_list = [{
-                'sample_idx': i,
-                'img_path': file
-            } for i, file in enumerate(prototype)]
-            dataset._fully_initialized = True
-            dataloader = build_dataloader(dataset)
-        elif isinstance(prototype, dict):
-            # A config of dataset
-            from mmpretrain.registry import DATASETS
-            test_pipeline = [dict(type='LoadImageFromFile'), self.img_pipeline]
-            prototype.setdefault('pipeline', test_pipeline)
-            dataset = DATASETS.build(prototype)
-            dataloader = build_dataloader(dataset)
-        elif isinstance(prototype, list):
-            test_pipeline = [dict(type='LoadImageFromFile'), self.img_pipeline]
-            dataset = BaseDataset(
-                lazy_init=True, serialize_data=False, pipeline=test_pipeline)
-            dataset.data_list = [{
-                'sample_idx': i,
-                'img_path': file
-            } for i, file in enumerate(prototype)]
-            dataset._fully_initialized = True
-            dataloader = build_dataloader(dataset)
-        elif isinstance(prototype, DataLoader):
-            dataset = prototype.dataset
-            dataloader = prototype
-        elif isinstance(prototype, BaseDataset):
-            dataset = prototype
-            dataloader = build_dataloader(dataset)
-        else:
-            raise TypeError(f'Unsupported prototype type {type(prototype)}.')
-
-        if cache is not None and Path(cache).exists():
-            self.prototype = torch.load(cache)
-        else:
-            prototype = []
-            for data_batch in track(dataloader, 'Prepare prototype...'):
-                with torch.no_grad():
-                    data_batch = self.model.data_preprocessor(
-                        data_batch, False)
-                    feats = self.model._run_forward(data_batch, mode='tensor')
-                    prototype.append(feats)
-            prototype = {
-                k: torch.cat([d[k] for d in prototype])
-                for k in prototype[0]
-            }
-            self.prototype = prototype
-
-        from mmengine.logging import MMLogger
-        logger = MMLogger.get_current_instance()
-        if cache is None:
-            logger.info('The prototype has been prepared, you can use '
-                        '`save_prototype` to dump it into a pickle '
-                        'file for the future usage.')
-        elif not Path(cache).exists():
-            self.save_prototype(cache)
-            logger.info(f'The prototype has been saved at {cache}.')
-
-        return dataset
-
-    def save_prototype(self, path):
-        torch.save(self.prototype, path)
-
-    def __call__(self,
-                 inputs: ImageType,
-                 return_datasamples: bool = False,
-                 batch_size: int = 1,
-                 **kwargs) -> dict:
-        """Call the inferencer.
-
-        Args:
-            inputs (str | array | list): The image path or array, or a list of
-                images.
-            return_datasamples (bool): Whether to return results as
-                :obj:`DataSample`. Defaults to False.
-            batch_size (int): Batch size. Defaults to 1.
-            resize (int, optional): Resize the long edge of the image to the
-                specified length before visualization. Defaults to None.
-            draw_score (bool): Whether to draw the match scores.
-                Defaults to True.
-            show (bool): Whether to display the visualization result in a
-                window. Defaults to False.
-            wait_time (float): The display time (s). Defaults to 0, which means
-                "forever".
-            show_dir (str, optional): If not None, save the visualization
-                results in the specified directory. Defaults to None.
-
-        Returns:
-            list: The inference results.
-        """
-        return super().__call__(inputs, return_datasamples, batch_size,
-                                **kwargs)
-
-    @torch.no_grad()
-    def forward(self, data: dict, **kwargs):
-        """Feed the inputs to the model."""
-        data = self.model.data_preprocessor(data, False)
-        data_samples = data['data_samples']
-        feats = self.prototype.copy()
-        feats.update(self.model.extract_feat(data_samples=data_samples))
-        return self.model.predict_all(feats, data_samples, cal_i2t=False)[0]
-
-    def _init_pipeline(self, cfg: Config) -> Callable:
-        test_pipeline_cfg = cfg.test_dataloader.dataset.pipeline
-        test_transfroms = [TRANSFORMS.build(t) for t in test_pipeline_cfg]
-        img_info = {'img': np.zeros((224, 224, 3), dtype=np.uint8)}
-        text_info = {'text': 'example'}
-        img_pipeline = Compose(filter_transforms(test_transfroms, img_info))
-        text_pipeline = Compose(filter_transforms(test_transfroms, text_info))
-        return img_pipeline, text_pipeline
-
-    def preprocess(self, inputs: List[str], batch_size: int = 1):
-
-        def process_text(input_: str):
-            return self.text_pipeline({'text': input_})
-
-        chunked_data = self._get_chunk_data(
-            map(process_text, inputs), batch_size)
-        yield from map(default_collate, chunked_data)
-
-    def visualize(self,
-                  ori_inputs: List[str],
-                  preds: List[DataSample],
-                  topk: int = 3,
-                  figsize: Tuple[int, int] = (16, 9),
-                  show: bool = False,
-                  wait_time: int = 0,
-                  draw_score=True,
-                  show_dir=None):
-        if not show and show_dir is None:
-            return None
-
-        if self.visualizer is None:
-            from mmpretrain.visualization import UniversalVisualizer
-            self.visualizer = UniversalVisualizer()
-
-        visualization = []
-        for i, (text, data_sample) in enumerate(zip(ori_inputs, preds)):
-            name = str(i)
-
-            if show_dir is not None:
-                show_dir = Path(show_dir)
-                show_dir.mkdir(exist_ok=True)
-                out_file = str((show_dir / name).with_suffix('.png'))
-            else:
-                out_file = None
-
-            self.visualizer.visualize_t2i_retrieval(
-                text,
-                data_sample,
-                self.prototype_dataset,
-                topk=topk,
-                fig_cfg=dict(figsize=figsize),
-                draw_score=draw_score,
-                show=show,
-                wait_time=wait_time,
-                name=name,
-                out_file=out_file)
-            visualization.append(self.visualizer.get_image())
-        if show:
-            self.visualizer.close()
-        return visualization
-
-    def postprocess(
-        self,
-        preds: List[DataSample],
-        visualization: List[np.ndarray],
-        return_datasamples=False,
-        topk=1,
-    ) -> dict:
-        if return_datasamples:
-            return preds
-
-        results = []
-        for data_sample in preds:
-            match_scores, indices = torch.topk(data_sample.pred_score, k=topk)
-            matches = []
-            for match_score, sample_idx in zip(match_scores, indices):
-                sample = self.prototype_dataset.get_data_info(
-                    sample_idx.item())
-                sample_idx = sample.pop('sample_idx')
-                matches.append({
-                    'match_score': match_score,
-                    'sample_idx': sample_idx,
-                    'sample': sample
-                })
-            results.append(matches)
-
-        return results
-
-    @staticmethod
-    def list_models(pattern: Optional[str] = None):
-        """List all available model names.
-
-        Args:
-            pattern (str | None): A wildcard pattern to match model names.
-
-        Returns:
-            List[str]: a list of model names.
-        """
-        return list_models(pattern=pattern, task='Text-To-Image Retrieval')
-
-
-class ImageToTextRetrievalInferencer(BaseInferencer):
-    """The inferencer for image to text retrieval.
-
-    Args:
-        model (BaseModel | str | Config): A model name or a path to the config
-            file, or a :obj:`BaseModel` object. The model name can be found
-            by ``ImageToTextRetrievalInferencer.list_models()`` and you can
-            also query it in :doc:`/modelzoo_statistics`.
-        prototype (str | list | dict | DataLoader, BaseDataset): The images to
-            be retrieved. It can be the following types:
-
-            - str: The file path to load the string list.
-            - list: A list of string.
-
-        prototype_cache (str, optional): The path of the generated prototype
-            features. If exists, directly load the cache instead of re-generate
-            the prototype features. If not exists, save the generated features
-            to the path. Defaults to None.
-        fast_match (bool): Some algorithms will record extra image features for
-            further matching, which may consume large memory, set True to avoid
-            this behavior. Defaults to True.
-        pretrained (str, optional): Path to the checkpoint. If None, it will
-            try to find a pre-defined weight from the model you specified
-            (only work if the ``model`` is a model name). Defaults to None.
-        device (str, optional): Device to run inference. If None, the available
-            device will be automatically used. Defaults to None.
-        **kwargs: Other keyword arguments to initialize the model (only work if
-            the ``model`` is a model name).
-
-    Example:
-        >>> from mmpretrain import ImageToTextRetrievalInferencer
-        >>> inferencer = ImageToTextRetrievalInferencer(
-        ...     'blip-base_3rdparty_retrieval',
-        ...     prototype=['cat', 'dog', 'snake', 'bird'],
-        ...     prototype_cache='i2t_retri.pth')
-        >>> inferencer('demo/bird.JPEG')[0]
-        {'match_score': tensor(0.3855, device='cuda:0'),
-         'sample_idx': 1,
-         'sample': {'img_path': './demo/cat-dog.png'}}
-    """  # noqa: E501
-
-    visualize_kwargs: set = {
-        'draw_score', 'resize', 'show_dir', 'show', 'wait_time', 'topk'
-    }
-    postprocess_kwargs: set = {'topk'}
-
-    def __init__(self,
-                 model: ModelType,
-                 prototype,
-                 prototype_cache=None,
-                 fast_match=True,
-                 prepare_batch_size=8,
-                 pretrained: Union[bool, str] = True,
-                 device: Union[str, torch.device, None] = None,
-                 **kwargs) -> None:
-        super().__init__(
-            model=model, pretrained=pretrained, device=device, **kwargs)
-
-        self.img_pipeline, self.text_pipeline = self.pipeline
-
-        if hasattr(self.model, 'fast_match'):
-            self.model.fast_match = fast_match
-
-        self.prototype_dataset = self._prepare_prototype(
-            prototype, cache=prototype_cache, batch_size=prepare_batch_size)
-
-    def _prepare_prototype(self, prototype, cache=None, batch_size=8):
-        from mmengine.dataset import DefaultSampler
-        from torch.utils.data import DataLoader
-
-        def build_dataloader(dataset):
-            return DataLoader(
-                [
-                    self.text_pipeline({
-                        'sample_idx': i,
-                        'text': text
-                    }) for i, text in enumerate(dataset)
-                ],
-                batch_size=batch_size,
-                collate_fn=default_collate,
-                sampler=DefaultSampler(dataset, shuffle=False),
-                persistent_workers=False,
-            )
-
-        if isinstance(prototype, str):
-            # A file path of a list of string
-            dataset = mmengine.list_from_file(prototype)
-        elif mmengine.utils.is_seq_of(prototype, str):
-            dataset = prototype
-        else:
-            raise TypeError(f'Unsupported prototype type {type(prototype)}.')
-
-        dataloader = build_dataloader(dataset)
-
-        if cache is not None and Path(cache).exists():
-            self.prototype = torch.load(cache)
-        else:
-            prototype = []
-            for data_batch in track(dataloader, 'Prepare prototype...'):
-                with torch.no_grad():
-                    data_batch = self.model.data_preprocessor(
-                        data_batch, False)
-                    feats = self.model._run_forward(data_batch, mode='tensor')
-                    prototype.append(feats)
-            prototype = {
-                k: torch.cat([d[k] for d in prototype])
-                for k in prototype[0]
-            }
-            self.prototype = prototype
-
-        from mmengine.logging import MMLogger
-        logger = MMLogger.get_current_instance()
-        if cache is None:
-            logger.info('The prototype has been prepared, you can use '
-                        '`save_prototype` to dump it into a pickle '
-                        'file for the future usage.')
-        elif not Path(cache).exists():
-            self.save_prototype(cache)
-            logger.info(f'The prototype has been saved at {cache}.')
-
-        return dataset
-
-    def save_prototype(self, path):
-        torch.save(self.prototype, path)
-
-    def __call__(self,
-                 inputs: ImageType,
-                 return_datasamples: bool = False,
-                 batch_size: int = 1,
-                 **kwargs) -> dict:
-        """Call the inferencer.
-
-        Args:
-            inputs (str | array | list): The image path or array, or a list of
-                images.
-            return_datasamples (bool): Whether to return results as
-                :obj:`DataSample`. Defaults to False.
-            batch_size (int): Batch size. Defaults to 1.
-            resize (int, optional): Resize the long edge of the image to the
-                specified length before visualization. Defaults to None.
-            draw_score (bool): Whether to draw the match scores.
-                Defaults to True.
-            show (bool): Whether to display the visualization result in a
-                window. Defaults to False.
-            wait_time (float): The display time (s). Defaults to 0, which means
-                "forever".
-            show_dir (str, optional): If not None, save the visualization
-                results in the specified directory. Defaults to None.
-
-        Returns:
-            list: The inference results.
-        """
-        return super().__call__(inputs, return_datasamples, batch_size,
-                                **kwargs)
-
-    @torch.no_grad()
-    def forward(self, data: dict, **kwargs):
-        """Feed the inputs to the model."""
-        data = self.model.data_preprocessor(data, False)
-        feats = self.prototype.copy()
-        feats.update(self.model.extract_feat(images=data['images']))
-        return self.model.predict_all(
-            feats, data['data_samples'], cal_t2i=False)[0]
-
-    def _init_pipeline(self, cfg: Config) -> Callable:
-        test_pipeline_cfg = cfg.test_dataloader.dataset.pipeline
-        test_transfroms = [TRANSFORMS.build(t) for t in test_pipeline_cfg]
-        img_info = {'img': np.zeros((224, 224, 3), dtype=np.uint8)}
-        text_info = {'text': 'example'}
-        img_pipeline = Compose(filter_transforms(test_transfroms, img_info))
-        text_pipeline = Compose(filter_transforms(test_transfroms, text_info))
-        return img_pipeline, text_pipeline
-
-    def preprocess(self, inputs: List[ImageType], batch_size: int = 1):
-
-        def load_image(input_):
-            img = imread(input_)
-            if img is None:
-                raise ValueError(f'Failed to read image {input_}.')
-            return dict(
-                img=img,
-                img_shape=img.shape[:2],
-                ori_shape=img.shape[:2],
-            )
-
-        pipeline = Compose([load_image, self.img_pipeline])
-
-        chunked_data = self._get_chunk_data(map(pipeline, inputs), batch_size)
-        yield from map(default_collate, chunked_data)
-
-    def visualize(self,
-                  ori_inputs: List[ImageType],
-                  preds: List[DataSample],
-                  topk: int = 3,
-                  resize: Optional[int] = 224,
-                  show: bool = False,
-                  wait_time: int = 0,
-                  draw_score=True,
-                  show_dir=None):
-        if not show and show_dir is None:
-            return None
-
-        if self.visualizer is None:
-            from mmpretrain.visualization import UniversalVisualizer
-            self.visualizer = UniversalVisualizer()
-
-        visualization = []
-        for i, (input_, data_sample) in enumerate(zip(ori_inputs, preds)):
-            image = imread(input_)
-            if isinstance(input_, str):
-                # The image loaded from path is BGR format.
-                image = image[..., ::-1]
-                name = Path(input_).stem
-            else:
-                name = str(i)
-
-            if show_dir is not None:
-                show_dir = Path(show_dir)
-                show_dir.mkdir(exist_ok=True)
-                out_file = str((show_dir / name).with_suffix('.png'))
-            else:
-                out_file = None
-
-            self.visualizer.visualize_i2t_retrieval(
-                image,
-                data_sample,
-                self.prototype_dataset,
-                topk=topk,
-                resize=resize,
-                draw_score=draw_score,
-                show=show,
-                wait_time=wait_time,
-                name=name,
-                out_file=out_file)
-            visualization.append(self.visualizer.get_image())
-        if show:
-            self.visualizer.close()
-        return visualization
-
-    def postprocess(
-        self,
-        preds: List[DataSample],
-        visualization: List[np.ndarray],
-        return_datasamples=False,
-        topk=1,
-    ) -> dict:
-        if return_datasamples:
-            return preds
-
-        results = []
-        for data_sample in preds:
-            match_scores, indices = torch.topk(data_sample.pred_score, k=topk)
-            matches = []
-            for match_score, sample_idx in zip(match_scores, indices):
-                text = self.prototype_dataset[sample_idx.item()]
-                matches.append({
-                    'match_score': match_score,
-                    'sample_idx': sample_idx,
-                    'text': text
-                })
-            results.append(matches)
-
-        return results
-
-    @staticmethod
-    def list_models(pattern: Optional[str] = None):
-        """List all available model names.
-
-        Args:
-            pattern (str | None): A wildcard pattern to match model names.
-
-        Returns:
-            List[str]: a list of model names.
-        """
-        return list_models(pattern=pattern, task='Image-To-Text Retrieval')
diff --git a/spaces/LanguageBind/LanguageBind/a_cls/util.py b/spaces/LanguageBind/LanguageBind/a_cls/util.py
deleted file mode 100644
index 7c48efe4f3609256d3d2230f7bf24b9c18ae5bbb..0000000000000000000000000000000000000000
--- a/spaces/LanguageBind/LanguageBind/a_cls/util.py
+++ /dev/null
@@ -1,306 +0,0 @@
-import math
-import pickle
-import numpy as np
-import torch
-import torch.nn as nn
-import random
-from collections import namedtuple
-
-def calc_recalls(S):
-    """
-    Computes recall at 1, 5, and 10 given a similarity matrix S.
-    By convention, rows of S are assumed to correspond to images and columns are captions.
-    """
-    assert(S.dim() == 2)
-    assert(S.size(0) == S.size(1))
-    if isinstance(S, torch.autograd.Variable):
-        S = S.data
-    n = S.size(0)
-    A2I_scores, A2I_ind = S.topk(10, 0)
-    I2A_scores, I2A_ind = S.topk(10, 1)
-    A_r1 = AverageMeter()
-    A_r5 = AverageMeter()
-    A_r10 = AverageMeter()
-    I_r1 = AverageMeter()
-    I_r5 = AverageMeter()
-    I_r10 = AverageMeter()
-    for i in range(n):
-        A_foundind = -1
-        I_foundind = -1
-        for ind in range(10):
-            if A2I_ind[ind, i] == i:
-                I_foundind = ind
-            if I2A_ind[i, ind] == i:
-                A_foundind = ind
-        # do r1s
-        if A_foundind == 0:
-            A_r1.update(1)
-        else:
-            A_r1.update(0)
-        if I_foundind == 0:
-            I_r1.update(1)
-        else:
-            I_r1.update(0)
-        # do r5s
-        if A_foundind >= 0 and A_foundind < 5:
-            A_r5.update(1)
-        else:
-            A_r5.update(0)
-        if I_foundind >= 0 and I_foundind < 5:
-            I_r5.update(1)
-        else:
-            I_r5.update(0)
-        # do r10s
-        if A_foundind >= 0 and A_foundind < 10:
-            A_r10.update(1)
-        else:
-            A_r10.update(0)
-        if I_foundind >= 0 and I_foundind < 10:
-            I_r10.update(1)
-        else:
-            I_r10.update(0)
-
-    recalls = {'A_r1':A_r1.avg, 'A_r5':A_r5.avg, 'A_r10':A_r10.avg,
-                'I_r1':I_r1.avg, 'I_r5':I_r5.avg, 'I_r10':I_r10.avg}
-                #'A_meanR':A_meanR.avg, 'I_meanR':I_meanR.avg}
-
-    return recalls
-
-def computeMatchmap(I, A):
-    assert(I.dim() == 3)
-    assert(A.dim() == 2)
-    D = I.size(0)
-    H = I.size(1)
-    W = I.size(2)
-    T = A.size(1)
-    Ir = I.view(D, -1).t()
-    matchmap = torch.mm(Ir, A)
-    matchmap = matchmap.view(H, W, T)
-    return matchmap
-
-def matchmapSim(M, simtype):
-    assert(M.dim() == 3)
-    if simtype == 'SISA':
-        return M.mean()
-    elif simtype == 'MISA':
-        M_maxH, _ = M.max(0)
-        M_maxHW, _ = M_maxH.max(0)
-        return M_maxHW.mean()
-    elif simtype == 'SIMA':
-        M_maxT, _ = M.max(2)
-        return M_maxT.mean()
-    else:
-        raise ValueError
-
-def sampled_margin_rank_loss(image_outputs, audio_outputs, nframes, margin=1., simtype='MISA'):
-    """
-    Computes the triplet margin ranking loss for each anchor image/caption pair
-    The impostor image/caption is randomly sampled from the minibatch
-    """
-    assert(image_outputs.dim() == 4)
-    assert(audio_outputs.dim() == 3)
-    n = image_outputs.size(0)
-    loss = torch.zeros(1, device=image_outputs.device, requires_grad=True)
-    for i in range(n):
-        I_imp_ind = i
-        A_imp_ind = i
-        while I_imp_ind == i:
-            I_imp_ind = np.random.randint(0, n)
-        while A_imp_ind == i:
-            A_imp_ind = np.random.randint(0, n)
-        nF = nframes[i]
-        nFimp = nframes[A_imp_ind]
-        anchorsim = matchmapSim(computeMatchmap(image_outputs[i], audio_outputs[i][:, 0:nF]), simtype)
-        Iimpsim = matchmapSim(computeMatchmap(image_outputs[I_imp_ind], audio_outputs[i][:, 0:nF]), simtype)
-        Aimpsim = matchmapSim(computeMatchmap(image_outputs[i], audio_outputs[A_imp_ind][:, 0:nFimp]), simtype)
-        A2I_simdif = margin + Iimpsim - anchorsim
-        if (A2I_simdif.data > 0).all():
-            loss = loss + A2I_simdif
-        I2A_simdif = margin + Aimpsim - anchorsim
-        if (I2A_simdif.data > 0).all():
-            loss = loss + I2A_simdif
-    loss = loss / n
-    return loss
-
-def compute_matchmap_similarity_matrix(image_outputs, audio_outputs, nframes, simtype='MISA'):
-    """
-    Assumes image_outputs is a (batchsize, embedding_dim, rows, height) tensor
-    Assumes audio_outputs is a (batchsize, embedding_dim, 1, time) tensor
-    Returns similarity matrix S where images are rows and audios are along the columns
-    """
-    assert(image_outputs.dim() == 4)
-    assert(audio_outputs.dim() == 3)
-    n = image_outputs.size(0)
-    S = torch.zeros(n, n, device=image_outputs.device)
-    for image_idx in range(n):
-            for audio_idx in range(n):
-                nF = max(1, nframes[audio_idx])
-                S[image_idx, audio_idx] = matchmapSim(computeMatchmap(image_outputs[image_idx], audio_outputs[audio_idx][:, 0:nF]), simtype)
-    return S
-
-def compute_pooldot_similarity_matrix(image_outputs, audio_outputs, nframes):
-    """
-    Assumes image_outputs is a (batchsize, embedding_dim, rows, height) tensor
-    Assumes audio_outputs is a (batchsize, embedding_dim, 1, time) tensor
-    Returns similarity matrix S where images are rows and audios are along the columns
-    S[i][j] is computed as the dot product between the meanpooled embeddings of
-    the ith image output and jth audio output
-    """
-    assert(image_outputs.dim() == 4)
-    assert(audio_outputs.dim() == 4)
-    n = image_outputs.size(0)
-    imagePoolfunc = nn.AdaptiveAvgPool2d((1, 1))
-    pooled_image_outputs = imagePoolfunc(image_outputs).squeeze(3).squeeze(2)
-    audioPoolfunc = nn.AdaptiveAvgPool2d((1, 1))
-    pooled_audio_outputs_list = []
-    for idx in range(n):
-        nF = max(1, nframes[idx])
-        pooled_audio_outputs_list.append(audioPoolfunc(audio_outputs[idx][:, :, 0:nF]).unsqueeze(0))
-    pooled_audio_outputs = torch.cat(pooled_audio_outputs_list).squeeze(3).squeeze(2)
-    S = torch.mm(pooled_image_outputs, pooled_audio_outputs.t())
-    return S
-
-def one_imposter_index(i, N):
-    imp_ind = random.randint(0, N - 2)
-    if imp_ind == i:
-        imp_ind = N - 1
-    return imp_ind
-
-def basic_get_imposter_indices(N):
-    imposter_idc = []
-    for i in range(N):
-        # Select an imposter index for example i:
-        imp_ind = one_imposter_index(i, N)
-        imposter_idc.append(imp_ind)
-    return imposter_idc
-
-def semihardneg_triplet_loss_from_S(S, margin):
-    """
-    Input: Similarity matrix S as an autograd.Variable
-    Output: The one-way triplet loss from rows of S to columns of S. Impostors are taken
-    to be the most similar point to the anchor that is still less similar to the anchor
-    than the positive example.
-    You would need to run this function twice, once with S and once with S.t(),
-    in order to compute the triplet loss in both directions.
-    """
-    assert(S.dim() == 2)
-    assert(S.size(0) == S.size(1))
-    N = S.size(0)
-    loss = torch.autograd.Variable(torch.zeros(1).type(S.data.type()), requires_grad=True)
-    # Imposter - ground truth
-    Sdiff = S - torch.diag(S).view(-1, 1)
-    eps = 1e-12
-    # All examples less similar than ground truth
-    mask = (Sdiff < -eps).type(torch.LongTensor)
-    maskf = mask.type_as(S)
-    # Mask out all examples >= gt with minimum similarity
-    Sp = maskf * Sdiff + (1 - maskf) * torch.min(Sdiff).detach()
-    # Find the index maximum similar of the remaining
-    _, idc = Sp.max(dim=1)
-    idc = idc.data.cpu()
-    # Vector mask: 1 iff there exists an example < gt
-    has_neg = (mask.sum(dim=1) > 0).data.type(torch.LongTensor)
-    # Random imposter indices
-    random_imp_ind = torch.LongTensor(basic_get_imposter_indices(N))
-    # Use hardneg if there exists an example < gt, otherwise use random imposter
-    imp_idc = has_neg * idc + (1 - has_neg) * random_imp_ind
-    # This could probably be vectorized too, but I haven't.
-    for i, imp in enumerate(imp_idc):
-        local_loss = Sdiff[i, imp] + margin
-        if (local_loss.data > 0).all():
-            loss = loss + local_loss
-    loss = loss / N
-    return loss
-
-def sampled_triplet_loss_from_S(S, margin):
-    """
-    Input: Similarity matrix S as an autograd.Variable
-    Output: The one-way triplet loss from rows of S to columns of S. Imposters are
-    randomly sampled from the columns of S.
-    You would need to run this function twice, once with S and once with S.t(),
-    in order to compute the triplet loss in both directions.
-    """
-    assert(S.dim() == 2)
-    assert(S.size(0) == S.size(1))
-    N = S.size(0)
-    loss = torch.autograd.Variable(torch.zeros(1).type(S.data.type()), requires_grad=True)
-    # Imposter - ground truth
-    Sdiff = S - torch.diag(S).view(-1, 1)
-    imp_ind = torch.LongTensor(basic_get_imposter_indices(N))
-    # This could probably be vectorized too, but I haven't.
-    for i, imp in enumerate(imp_ind):
-        local_loss = Sdiff[i, imp] + margin
-        if (local_loss.data > 0).all():
-            loss = loss + local_loss
-    loss = loss / N
-    return loss
-
-class AverageMeter(object):
-    """Computes and stores the average and current value"""
-    def __init__(self):
-        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 adjust_learning_rate(base_lr, lr_decay, optimizer, epoch):
-    """Sets the learning rate to the initial LR decayed by 10 every lr_decay epochs"""
-    lr = base_lr * (0.1 ** (epoch // lr_decay))
-    print('now learning rate changed to {:f}'.format(lr))
-    for param_group in optimizer.param_groups:
-        param_group['lr'] = lr
-
-def adjust_learning_rate2(base_lr, lr_decay, optimizer, epoch):
-    """Sets the learning rate to the initial LR decayed by 10 every lr_decay epochs"""
-    for param_group in optimizer.param_groups:
-        cur_lr = param_group['lr']
-        print('current learing rate is {:f}'.format(lr))
-    lr = cur_lr  * 0.1
-    print('now learning rate changed to {:f}'.format(lr))
-    for param_group in optimizer.param_groups:
-        param_group['lr'] = lr
-
-
-def load_progress(prog_pkl, quiet=False):
-    """
-    load progress pkl file
-    Args:
-        prog_pkl(str): path to progress pkl file
-    Return:
-        progress(list):
-        epoch(int):
-        global_step(int):
-        best_epoch(int):
-        best_avg_r10(float):
-    """
-    def _print(msg):
-        if not quiet:
-            print(msg)
-
-    with open(prog_pkl, "rb") as f:
-        prog = pickle.load(f)
-        epoch, global_step, best_epoch, best_avg_r10, _ = prog[-1]
-
-    _print("\nPrevious Progress:")
-    msg =  "[%5s %7s %5s %7s %6s]" % ("epoch", "step", "best_epoch", "best_avg_r10", "time")
-    _print(msg)
-    return prog, epoch, global_step, best_epoch, best_avg_r10
-
-def count_parameters(model):
-    return sum([p.numel() for p in model.parameters() if p.requires_grad])
-
-PrenetConfig = namedtuple(
-  'PrenetConfig', ['input_size', 'hidden_size', 'num_layers', 'dropout'])
-
-RNNConfig = namedtuple(
-  'RNNConfig',
-  ['input_size', 'hidden_size', 'num_layers', 'dropout', 'residual'])
\ No newline at end of file
diff --git a/spaces/Lavanya30/hiddenhunger/README.md b/spaces/Lavanya30/hiddenhunger/README.md
deleted file mode 100644
index 0458a9d2bc080f273b53afca2f47a7fed6937544..0000000000000000000000000000000000000000
--- a/spaces/Lavanya30/hiddenhunger/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Hiddenhunger
-emoji: 🐠
-colorFrom: indigo
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.19.0
-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/LightChen2333/OpenSLU/static/template/visualization.html b/spaces/LightChen2333/OpenSLU/static/template/visualization.html
deleted file mode 100644
index ededde14d239f1dcb1487ff584f5039d5772a037..0000000000000000000000000000000000000000
--- a/spaces/LightChen2333/OpenSLU/static/template/visualization.html
+++ /dev/null
@@ -1,453 +0,0 @@
-<html>
-
-<head>
-    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
-    <title>OpenSLU Visual Analysis</title>
-    <meta name="viewport" content="width=device-width, initial-scale=1">
-    <link href="https://cdn.staticfile.org/twitter-bootstrap/5.1.1/css/bootstrap.min.css" rel="stylesheet">
-    <script src="https://cdn.staticfile.org/twitter-bootstrap/5.1.1/js/bootstrap.bundle.min.js"></script>
-    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
-    <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.1/dist/echarts.min.js"></script>
-    <style type="text/css">
-        span.rcorners2 {
-            background-color: #e6e6e6;
-            color: #000;
-        }
-    </style>
-    <link rel="icon" href="{{url_for('static',filename='favicon.ico')}}" type ="image/x-icon">
-</head>
-
-<body>
-    <div class="row" style="width: 100%;margin: 2px;">
-        <div class="col-md-12 col-sm-12" style="display: flex; flex-direction: column; align-items: center;">
-
-            <div class="row" style="width: 100%; margin: 20px 0px 30px 0px; justify-content: center;">
-                <div class="col-md-4">
-                    <div class="card"
-                        style="width: 100%;display: flex;align-content: center;flex-direction: column;flex-wrap: nowrap;justify-content: center;align-items: center;">
-                        <div style="margin-bottom: 0px; margin-top: 20px;text-align: center;">
-                            <b>Error Intent Label Distribution</b>
-                        </div>
-                        <div id="intent-pie" style="width: 100%;height:300px;"></div>
-                    </div>
-
-                </div>
-                <div class="col-md-4">
-                    <div class="card"
-                        style="width: 100%;display: flex;align-content: center;flex-direction: column;flex-wrap: nowrap;justify-content: center;align-items: center;">
-                        <div style="margin-bottom: 0px; margin-top: 20px;text-align: center;">
-                            <b>Error Slot Label Distribution</b>
-                        </div>
-                        <div id="slot-pie" style="width: 100%;height:300px;"></div>
-                    </div>
-                </div>
-                <div class="col-md-4">
-                    <div class="card"
-                        style="width: 90%;display: flex;align-content: center;flex-direction: column;flex-wrap: nowrap;justify-content: center;align-items: center;">
-                        <div class="card-body" style="width: 100%;">
-                            <div id="card-title" style="text-align: center;"></div>
-                            <div id="gauge_chart" style="width: 100%; height:200px;"></div>
-                            <p class="card-text" style="margin-top: -80px;" id="card-statistics">
-                            </p>
-                        </div>
-                    </div>
-                </div>
-            </div>
-            <div class="row" style="width: 100%; margin: 20px 0px 30px 0px; justify-content: center;">
-
-
-
-                <script type="text/javascript">
-                    {% autoescape false %}
-                    var slot_dict = {{ slot_dict }}
-                    var slot_dict_list = {{ slot_dict_list }}
-                    var intent_dict = {{ intent_dict }}
-                    var intent_dict_list = {{ intent_dict_list }}
-
-                    {% endautoescape %}
-                    function drawPieChart(docId, data, type) {
-                        var chartDom = document.getElementById(docId);
-                        var data_keys = []
-                        for (var i = 0; i < data.length; i++) {
-                            data_keys.push(data[i]["name"])
-                        }
-                        var myChart = echarts.init(chartDom);
-
-                        var option = {
-                            tooltip: {
-                                trigger: 'item'
-                            },
-                            visualMap: {
-                                show: false,
-                                // min: 0,
-                                // max: {{max_slot}},
-                                splitNumber: 10,
-                                inRange: {
-                                    color: ["#a50026", "#d73027", "#f46d43", "#fdae61", "#fee090", "#ffffbf", "#e0f3f8", "#abd9e9", "#74add1", "#4575b4", "#313695"]
-                                    // colorLightness: [0, 1]
-                                },
-                                pieces: [
-                                    { gt: data[1]["value"], lte: data[0]["value"] },
-                                    { gt: data[2]["value"], lte: data[1]["value"] },
-                                    { gt: data[3]["value"], lte: data[2]["value"] },
-                                    { gt: data[4]["value"], lte: data[3]["value"] },
-                                    { gt: data[5]["value"], lte: data[4]["value"] },
-                                    { gt: data[6]["value"], lte: data[5]["value"] },
-                                    { gt: data[7]["value"], lte: data[6]["value"] },
-                                    { gt: data[8]["value"], lte: data[7]["value"] },
-                                    { gt: data[9]["value"], lte: data[8]["value"] },
-                                    { lte: data[9]["value"] }                 // (-Infinity, 5)
-                                ]
-                            },
-                            series: [
-                                {
-                                    type: 'pie',
-                                    radius: ['50%', '70%'],
-                                    avoidLabelOverlap: false,
-                                    itemStyle: {
-                                        // color: 'rgb(56,116,255)',
-                                        borderRadius: 10,
-                                        borderColor: '#fff',
-                                        borderWidth: 2
-                                    },
-                                    label: {
-                                        show: false,
-                                        position: 'center'
-                                    },
-                                    emphasis: {
-                                        label: {
-                                            show: true,
-                                            fontSize: 20,
-                                            fontWeight: 'bold'
-                                        }
-                                    },
-                                    labelLine: {
-                                        show: false
-                                    },
-                                    data: data
-                                }
-                            ]
-                        };
-
-                        option && myChart.setOption(option);
-                        myChart.on('click', function (params) {
-                            if (type == "slot") {
-                                var detailChart = drawGaugeChart("gauge_chart", slot_dict, params.name, "slot")
-                            } else {
-                                var detailChart = drawGaugeChart("gauge_chart", intent_dict, params.name, "intent")
-                            }
-
-                        });
-                    }
-                    function drawBarChart(docId, data, type) {
-                        var chartDom = document.getElementById(docId);
-                        var data_dicts = {}
-                        var data_keys = []
-                        var bars = []
-                        for (var i = 0; i < data.length; i++) {
-                            data_dicts[data[i]["name"]] = data[i]["value"]
-                            data_keys.push(data[i]["name"])
-                            bars.push({ type: 'bar' })
-                        }
-                        var myChart = echarts.init(chartDom);
-
-                        option = {
-                            legend: {},
-                            tooltip: {},
-                            dataset: {
-                                dimensions: data_keys,
-                                source: [data_dicts]
-                            },
-                            xAxis: { type: 'category' },
-                            yAxis: {},
-                            // Declare several bar series, each will be mapped
-                            // to a column of dataset.source by default.
-                            series: bars
-                        };
-                        option && myChart.setOption(option);
-                        myChart.on('click', function (params) {
-                            if (type == "slot") {
-                                var detailChart = drawGaugeChart("gauge_chart", slot_dict, params.name, "slot")
-                            } else {
-                                var detailChart = drawGaugeChart("gauge_chart", intent_dict, params.name, "intent")
-                            }
-
-                        });
-                    }
-                    function greatBarChart(docId, data, type) {
-                        var chartDom = document.getElementById(docId);
-                        var myChart = echarts.init(chartDom);
-                        myChart.hideLoading();
-                        var data_lists = []
-                        var data_keys = []
-                        var bars = []
-                        var colors = [
-                            '#dd6b66',
-                            '#759aa0',
-                            '#e69d87',
-                            '#8dc1a9',
-                            '#ea7e53',
-                            '#eedd78',
-                            '#73a373',
-                            '#73b9bc',
-                            '#7289ab',
-                            '#91ca8c',
-                            '#f49f42'
-                        ]
-                        for (var i = 0; i < data.length; i++) {
-                            data_lists.push({ "value": data[i]["value"], "itemStyle": { color: colors[i % colors.length] } })
-                            data_keys.push(data[i]["name"])
-                            bars.push({ type: 'bar' })
-                        }
-                        console.log(data_lists)
-                        option = {
-                            tooltip: {
-                                trigger: 'axis',
-                                axisPointer: {
-                                    type: 'shadow',
-                                    label: {
-                                        show: true
-                                    }
-                                }
-                            },
-                            toolbox: {
-                                show: true,
-                                feature: {
-                                    dataZoom: { yAxisIndex: 'none', title: 'Area Zoom' },
-                                    // mark: { show: true, title: "" },
-                                    dataView: { show: true, readOnly: false, title: 'Raw Data' },
-                                    magicType: { show: true, type: ['line', 'bar'], title: { line: 'Switch to Line Chart', bar: 'Switch to Bar Chart' } },
-                                    restore: { show: true, title: 'Restore Image' },
-                                    saveAsImage: { show: true, title: 'Save as Image' }
-                                }
-                            },
-                            calculable: true,
-                            legend: {
-                                data: ['Budget 2011'],
-                                itemGap: 5
-                            },
-                            grid: {
-                                top: 50,
-                                bottom: 50,
-                                left: 10,
-                                right: 30,
-                                containLabel: true
-                            },
-                            xAxis: { type: 'category', data: data_keys, show: false },
-                            yAxis: {},
-                            dataZoom: [
-                                {
-                                    show: true,
-                                    start: 0,
-                                    end: 100
-                                },
-                                {
-                                    type: 'inside',
-                                    start: 0,
-                                    end: 100
-                                },
-                                {
-                                    show: true,
-                                    yAxisIndex: 0,
-                                    filterMode: 'empty',
-                                    width: 20,
-                                    // top: '10%',
-                                    height: '60%',
-                                    showDataShadow: false,
-                                    // left: '93%'
-                                }
-                            ],
-                            series: [{ data: data_lists, type: 'bar' }]
-                        };
-                        option && myChart.setOption(option);
-                        myChart.on('click', function (params) {
-                            if (type == "slot") {
-                                var detailChart = drawGaugeChart("gauge_chart", slot_dict, params.name, "slot")
-                            } else {
-                                var detailChart = drawGaugeChart("gauge_chart", intent_dict, params.name, "intent")
-                            }
-
-                        });
-                    }
-                    var xchart = greatBarChart("intent-pie", intent_dict_list, "intent")
-                    var ychart = greatBarChart("slot-pie", slot_dict_list, "slot")
-                    function drawGaugeChart(docId, x_dict, x_name, type) {
-                        var chartDom = document.getElementById(docId);
-                        var data = x_dict[x_name]
-                        var total = data[0][1]
-                        var error = data[1][1]
-                        var option = {
-                            series: [{
-                                type: 'gauge',
-                                startAngle: 170,
-                                endAngle: 10,
-                                min: 0,
-                                max: 100,
-                                pointer: { show: false },
-                                splitLine: {
-                                    show: false,
-                                    distance: 0,
-                                    length: 10
-                                },
-                                axisTick: { show: false },
-                                axisLabel: {
-                                    show: false,
-                                    distance: 50
-                                },
-                                detail: {
-                                    show: false,
-                                    width: 50,
-                                    height: 14,
-                                    fontSize: 14,
-                                    color: 'inherit',
-                                    borderColor: 'inherit',
-                                    borderRadius: 20,
-                                    borderWidth: 1,
-                                    formatter: '{value}%'
-                                },
-                                itemStyle: {
-                                    color: 'rgb(128,183,214)',
-                                    // color: 'rgb(56,116,255)',
-                                    // shadowColor: 'rgba(56,116,255,0.75)',
-                                    // shadowBlur: 10,
-                                    // shadowOffsetX: 2,
-                                    // shadowOffsetY: 2
-                                },
-                                progress: {
-                                    show: true,
-                                    roundCap: true,
-                                    width: 18
-                                },
-                                axisLine: {
-                                    roundCap: true,
-                                    lineStyle: { width: 18 }
-                                },
-                                data: [100.0 * error / total]
-                            }]
-                        };
-                        var myChart = echarts.init(chartDom);
-                        option && myChart.setOption(option);
-                        var element = document.getElementById("card-statistics");
-                        var html_txt = ``
-                        html_txt += '<div style="margin: 0px 10px 10px 10px;"><b>' + Math.round(100.0 * error / total * 10) / 10 + '%</b> of <b>' + x_name + '</b> labels are predicted incorrectly.  They are predicted as: </div>';
-                        for (var i = 2; i < data.length; i++) {
-                            ratio = Math.round(100.0 * data[i][1] / error * 10) / 10
-                            html_txt += `<div style="margin: 0px 10px 0px 10px;">
-                        <div style="width:15%; height:12px; background-color:rgb(234, 235, 235);border-radius: 6px; display: inline-block;">
-                            <div style="width:`
-                                + (ratio) + `%; height:12px; background-color:rgb(128,183,214);border-radius: 6px; display: inline-block;"></div>
-                        </div>
-                        <div style="width: 63%;margin-left: 12px;display: inline-block;">`
-                                + data[i][0] +
-                                `</div>
-                            <div style="width:15%; display: inline-block;text-align: right;">`
-                                + ratio +
-                                `%</div></div>`;
-                        }
-                        element.innerHTML = html_txt;
-                        var title = document.getElementById("card-title");
-                        title.innerHTML = "<b>Error ratio for " + type + " '" + x_name + "'</b>"
-                    }
-                    var detailChart = drawGaugeChart("gauge_chart", slot_dict, slot_dict_list[0].name, "slot")
-                </script>
-            </div>
-        </div>
-        <div class="col-md-12 col-sm-12" style="margin: -30px 10px 10px 10px; padding: 0px 40px 0px 40px;">
-            <div style="font-size: larger;margin-bottom: 10px;"><b>Instance Analysis</b>
-                <hr />
-            </div>
-            {% for example in examples %}
-            <b>Intent:</b>
-            {% for e in example["intent"] %}
-            {% if e["intent"] == e["pred_intent"] %}
-
-            <button type="button" class="btn btn-white">
-                <span class="badge text-dark btn-light">{{e["pred_intent"]}}</span>
-            </button>
-            {% else %}
-            <button type="button" class="btn btn-light" data-bs-trigger="hover" data-bs-toggle="popover"
-                data-bs-placement="left" data-bs-content="
-                <b>Golden Intent: </b>
-                <span class='badge text-dark btn-light' style='background-color: #e6e6e6;'>
-                    {{e['intent']}}
-                </span>">
-                <span class="badge"
-                    style="background-color: rgb(246,123,74);color: rgb(255, 255, 255);">{{e["pred_intent"]}}</span>
-            </button>
-            {% endif %}
-            {% endfor %}
-
-            <br />
-            <b>Slot:</b>
-            {% for e in example["slot"] %}
-            {% if e["slot"] == e["pred_slot"] %}
-
-            <button type="button" class="btn btn-white">
-                {{e["text"]}} <span class="badge text-dark" style="background-color: rgb(255, 255, 255);
-                color: rgb(62 62 62);
-                box-shadow: 2px 2px 7px 1px rgba(210, 210, 210, 0.42);">{{e["pred_slot"]}}</span>
-            </button>
-            {% else %}
-            <button type="button" class="btn btn-light" data-bs-trigger="hover" data-bs-toggle="popover"
-                data-bs-placement="left" data-bs-content="
-                <b>Golden Slot: </b>
-                <span class='rcorners2 badge text-dark btn-light'>
-                    {{e['slot']}}
-                </span>">
-                {{e["text"]}} <span class="badge" style="background-color: rgb(246,123,74);
-                color: rgb(255, 255, 255);
-                ">{{e["pred_slot"]}}</span>
-            </button>
-            {% endif %}
-            {% endfor %}
-            <hr /><br />
-            {% endfor %}
-            <div class="row">
-                <div class="col"><button type="button" class="btn btn-outline-light text-dark"
-                        style="box-shadow: 2px 2px 7px 1px rgba(210, 210, 210, 0.42);" onclick="jump('/?page={{page - 1}}')">← Last
-                        Page</button></div>
-                <div class="col" style="justify-content: center;display: flex;align-content: center;align-items: center;">
-                    <div class="row" style="width: 230px;">
-                        <div class="col" style="display: flex; align-items: center;">Page Index:</div>
-                        <div class="col">
-                            <div class="input-group">
-                                <input type="text" class="form-control" id="inputs" value="{{page}}">
-                            </div>
-                        </div>
-                    </div>
-
-
-                </div>
-                <script>
-                    var inputDom = document.getElementById('inputs');
-                    inputDom.onblur = function () {
-                        var n = Number(inputDom.value);
-                        if (!isNaN(n)){
-                            window.location.href = '/?page=' + inputDom.value;
-                        }
-                            
-                    };
-                    function jump(url){ window.location.href=url;}
-                </script>
-                <div class="col" style="display: flex; justify-content: flex-end; padding-right: 40px;"><button
-                        type="button" class="btn btn-outline-light text-dark"
-                        style="box-shadow: 2px 2px 7px 1px rgba(210, 210, 210, 0.42);" onclick="jump('/?page={{page + 1}}')">Next
-                        Page →</button></div>
-            </div>
-
-
-        </div>
-    </div>
-
-</body>
-<script>
-    var popoverTriggerList = [].slice.call(document.querySelectorAll('[data-bs-toggle="popover"]'))
-    var popoverList = popoverTriggerList.map(function (popoverTriggerEl) {
-        return new bootstrap.Popover(popoverTriggerEl, {
-            "html": true,
-            "placement": "bottom"
-        })
-    });
-</script>
-
-</html>
\ No newline at end of file
diff --git a/spaces/Lizzbitt/pi2/Dockerfile b/spaces/Lizzbitt/pi2/Dockerfile
deleted file mode 100644
index e6158e4b2d67eeea6e30ad3c1bb6043ec09b7b9b..0000000000000000000000000000000000000000
--- a/spaces/Lizzbitt/pi2/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" ]
\ No newline at end of file
diff --git a/spaces/LuxOAI/ChatGpt-Web/app/components/chat.tsx b/spaces/LuxOAI/ChatGpt-Web/app/components/chat.tsx
deleted file mode 100644
index 0cfed38649db00dcb74a9a75d9f9ae2c18a2ee88..0000000000000000000000000000000000000000
--- a/spaces/LuxOAI/ChatGpt-Web/app/components/chat.tsx
+++ /dev/null
@@ -1,821 +0,0 @@
-import { useDebouncedCallback } from "use-debounce";
-import { useState, useRef, useEffect, useLayoutEffect } from "react";
-
-import SendWhiteIcon from "../icons/send-white.svg";
-import BrainIcon from "../icons/brain.svg";
-import RenameIcon from "../icons/rename.svg";
-import ExportIcon from "../icons/share.svg";
-import ReturnIcon from "../icons/return.svg";
-import CopyIcon from "../icons/copy.svg";
-import DownloadIcon from "../icons/download.svg";
-import LoadingIcon from "../icons/three-dots.svg";
-import PromptIcon from "../icons/prompt.svg";
-import MaskIcon from "../icons/mask.svg";
-import MaxIcon from "../icons/max.svg";
-import MinIcon from "../icons/min.svg";
-import ResetIcon from "../icons/reload.svg";
-
-import LightIcon from "../icons/light.svg";
-import DarkIcon from "../icons/dark.svg";
-import AutoIcon from "../icons/auto.svg";
-import BottomIcon from "../icons/bottom.svg";
-import StopIcon from "../icons/pause.svg";
-
-import {
-  Message,
-  SubmitKey,
-  useChatStore,
-  BOT_HELLO,
-  createMessage,
-  useAccessStore,
-  Theme,
-  useAppConfig,
-  DEFAULT_TOPIC,
-} from "../store";
-
-import {
-  copyToClipboard,
-  downloadAs,
-  selectOrCopy,
-  autoGrowTextArea,
-  useMobileScreen,
-} from "../utils";
-
-import dynamic from "next/dynamic";
-
-import { ControllerPool } from "../requests";
-import { Prompt, usePromptStore } from "../store/prompt";
-import Locale from "../locales";
-
-import { IconButton } from "./button";
-import styles from "./home.module.scss";
-import chatStyle from "./chat.module.scss";
-
-import { ListItem, Modal, showModal } from "./ui-lib";
-import { useLocation, useNavigate } from "react-router-dom";
-import { LAST_INPUT_KEY, Path } from "../constant";
-import { Avatar } from "./emoji";
-import { MaskAvatar, MaskConfig } from "./mask";
-import { useMaskStore } from "../store/mask";
-import { useCommand } from "../command";
-
-const Markdown = dynamic(async () => (await import("./markdown")).Markdown, {
-  loading: () => <LoadingIcon />,
-});
-
-function exportMessages(messages: Message[], topic: string) {
-  const mdText =
-    `# ${topic}\n\n` +
-    messages
-      .map((m) => {
-        return m.role === "user"
-          ? `## ${Locale.Export.MessageFromYou}:\n${m.content}`
-          : `## ${Locale.Export.MessageFromChatGPT}:\n${m.content.trim()}`;
-      })
-      .join("\n\n");
-  const filename = `${topic}.md`;
-
-  showModal({
-    title: Locale.Export.Title,
-    children: (
-      <div className="markdown-body">
-        <pre className={styles["export-content"]}>{mdText}</pre>
-      </div>
-    ),
-    actions: [
-      <IconButton
-        key="copy"
-        icon={<CopyIcon />}
-        bordered
-        text={Locale.Export.Copy}
-        onClick={() => copyToClipboard(mdText)}
-      />,
-      <IconButton
-        key="download"
-        icon={<DownloadIcon />}
-        bordered
-        text={Locale.Export.Download}
-        onClick={() => downloadAs(mdText, filename)}
-      />,
-    ],
-  });
-}
-
-export function SessionConfigModel(props: { onClose: () => void }) {
-  const chatStore = useChatStore();
-  const session = chatStore.currentSession();
-  const maskStore = useMaskStore();
-  const navigate = useNavigate();
-
-  return (
-    <div className="modal-mask">
-      <Modal
-        title={Locale.Context.Edit}
-        onClose={() => props.onClose()}
-        actions={[
-          <IconButton
-            key="reset"
-            icon={<ResetIcon />}
-            bordered
-            text={Locale.Chat.Config.Reset}
-            onClick={() =>
-              confirm(Locale.Memory.ResetConfirm) && chatStore.resetSession()
-            }
-          />,
-          <IconButton
-            key="copy"
-            icon={<CopyIcon />}
-            bordered
-            text={Locale.Chat.Config.SaveAs}
-            onClick={() => {
-              navigate(Path.Masks);
-              setTimeout(() => {
-                maskStore.create(session.mask);
-              }, 500);
-            }}
-          />,
-        ]}
-      >
-        <MaskConfig
-          mask={session.mask}
-          updateMask={(updater) => {
-            const mask = { ...session.mask };
-            updater(mask);
-            chatStore.updateCurrentSession((session) => (session.mask = mask));
-          }}
-          extraListItems={
-            session.mask.modelConfig.sendMemory ? (
-              <ListItem
-                title={`${Locale.Memory.Title} (${session.lastSummarizeIndex} of ${session.messages.length})`}
-                subTitle={session.memoryPrompt || Locale.Memory.EmptyContent}
-              ></ListItem>
-            ) : (
-              <></>
-            )
-          }
-        ></MaskConfig>
-      </Modal>
-    </div>
-  );
-}
-
-function PromptToast(props: {
-  showToast?: boolean;
-  showModal?: boolean;
-  setShowModal: (_: boolean) => void;
-}) {
-  const chatStore = useChatStore();
-  const session = chatStore.currentSession();
-  const context = session.mask.context;
-
-  return (
-    <div className={chatStyle["prompt-toast"]} key="prompt-toast">
-      {props.showToast && (
-        <div
-          className={chatStyle["prompt-toast-inner"] + " clickable"}
-          role="button"
-          onClick={() => props.setShowModal(true)}
-        >
-          <BrainIcon />
-          <span className={chatStyle["prompt-toast-content"]}>
-            {Locale.Context.Toast(context.length)}
-          </span>
-        </div>
-      )}
-      {props.showModal && (
-        <SessionConfigModel onClose={() => props.setShowModal(false)} />
-      )}
-    </div>
-  );
-}
-
-function useSubmitHandler() {
-  const config = useAppConfig();
-  const submitKey = config.submitKey;
-
-  const shouldSubmit = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
-    if (e.key !== "Enter") return false;
-    if (e.key === "Enter" && e.nativeEvent.isComposing) return false;
-    return (
-      (config.submitKey === SubmitKey.AltEnter && e.altKey) ||
-      (config.submitKey === SubmitKey.CtrlEnter && e.ctrlKey) ||
-      (config.submitKey === SubmitKey.ShiftEnter && e.shiftKey) ||
-      (config.submitKey === SubmitKey.MetaEnter && e.metaKey) ||
-      (config.submitKey === SubmitKey.Enter &&
-        !e.altKey &&
-        !e.ctrlKey &&
-        !e.shiftKey &&
-        !e.metaKey)
-    );
-  };
-
-  return {
-    submitKey,
-    shouldSubmit,
-  };
-}
-
-export function PromptHints(props: {
-  prompts: Prompt[];
-  onPromptSelect: (prompt: Prompt) => void;
-}) {
-  const noPrompts = props.prompts.length === 0;
-  const [selectIndex, setSelectIndex] = useState(0);
-  const selectedRef = useRef<HTMLDivElement>(null);
-
-  useEffect(() => {
-    setSelectIndex(0);
-  }, [props.prompts.length]);
-
-  useEffect(() => {
-    const onKeyDown = (e: KeyboardEvent) => {
-      if (noPrompts) return;
-
-      // arrow up / down to select prompt
-      const changeIndex = (delta: number) => {
-        e.stopPropagation();
-        e.preventDefault();
-        const nextIndex = Math.max(
-          0,
-          Math.min(props.prompts.length - 1, selectIndex + delta),
-        );
-        setSelectIndex(nextIndex);
-        selectedRef.current?.scrollIntoView({
-          block: "center",
-        });
-      };
-
-      if (e.key === "ArrowUp") {
-        changeIndex(1);
-      } else if (e.key === "ArrowDown") {
-        changeIndex(-1);
-      } else if (e.key === "Enter") {
-        const selectedPrompt = props.prompts.at(selectIndex);
-        if (selectedPrompt) {
-          props.onPromptSelect(selectedPrompt);
-        }
-      }
-    };
-
-    window.addEventListener("keydown", onKeyDown);
-
-    return () => window.removeEventListener("keydown", onKeyDown);
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [noPrompts, selectIndex]);
-
-  if (noPrompts) return null;
-  return (
-    <div className={styles["prompt-hints"]}>
-      {props.prompts.map((prompt, i) => (
-        <div
-          ref={i === selectIndex ? selectedRef : null}
-          className={
-            styles["prompt-hint"] +
-            ` ${i === selectIndex ? styles["prompt-hint-selected"] : ""}`
-          }
-          key={prompt.title + i.toString()}
-          onClick={() => props.onPromptSelect(prompt)}
-          onMouseEnter={() => setSelectIndex(i)}
-        >
-          <div className={styles["hint-title"]}>{prompt.title}</div>
-          <div className={styles["hint-content"]}>{prompt.content}</div>
-        </div>
-      ))}
-    </div>
-  );
-}
-
-function useScrollToBottom() {
-  // for auto-scroll
-  const scrollRef = useRef<HTMLDivElement>(null);
-  const [autoScroll, setAutoScroll] = useState(true);
-  const scrollToBottom = () => {
-    const dom = scrollRef.current;
-    if (dom) {
-      setTimeout(() => (dom.scrollTop = dom.scrollHeight), 1);
-    }
-  };
-
-  // auto scroll
-  useLayoutEffect(() => {
-    autoScroll && scrollToBottom();
-  });
-
-  return {
-    scrollRef,
-    autoScroll,
-    setAutoScroll,
-    scrollToBottom,
-  };
-}
-
-export function ChatActions(props: {
-  showPromptModal: () => void;
-  scrollToBottom: () => void;
-  showPromptHints: () => void;
-  hitBottom: boolean;
-}) {
-  const config = useAppConfig();
-  const navigate = useNavigate();
-
-  // switch themes
-  const theme = config.theme;
-  function nextTheme() {
-    const themes = [Theme.Auto, Theme.Light, Theme.Dark];
-    const themeIndex = themes.indexOf(theme);
-    const nextIndex = (themeIndex + 1) % themes.length;
-    const nextTheme = themes[nextIndex];
-    config.update((config) => (config.theme = nextTheme));
-  }
-
-  // stop all responses
-  const couldStop = ControllerPool.hasPending();
-  const stopAll = () => ControllerPool.stopAll();
-
-  return (
-    <div className={chatStyle["chat-input-actions"]}>
-      {couldStop && (
-        <div
-          className={`${chatStyle["chat-input-action"]} clickable`}
-          onClick={stopAll}
-        >
-          <StopIcon />
-        </div>
-      )}
-      {!props.hitBottom && (
-        <div
-          className={`${chatStyle["chat-input-action"]} clickable`}
-          onClick={props.scrollToBottom}
-        >
-          <BottomIcon />
-        </div>
-      )}
-      {props.hitBottom && (
-        <div
-          className={`${chatStyle["chat-input-action"]} clickable`}
-          onClick={props.showPromptModal}
-        >
-          <BrainIcon />
-        </div>
-      )}
-
-      <div
-        className={`${chatStyle["chat-input-action"]} clickable`}
-        onClick={nextTheme}
-      >
-        {theme === Theme.Auto ? (
-          <AutoIcon />
-        ) : theme === Theme.Light ? (
-          <LightIcon />
-        ) : theme === Theme.Dark ? (
-          <DarkIcon />
-        ) : null}
-      </div>
-
-      <div
-        className={`${chatStyle["chat-input-action"]} clickable`}
-        onClick={props.showPromptHints}
-      >
-        <PromptIcon />
-      </div>
-
-      <div
-        className={`${chatStyle["chat-input-action"]} clickable`}
-        onClick={() => {
-          navigate(Path.Masks);
-        }}
-      >
-        <MaskIcon />
-      </div>
-    </div>
-  );
-}
-
-export function Chat() {
-  type RenderMessage = Message & { preview?: boolean };
-
-  const chatStore = useChatStore();
-  const [session, sessionIndex] = useChatStore((state) => [
-    state.currentSession(),
-    state.currentSessionIndex,
-  ]);
-  const config = useAppConfig();
-  const fontSize = config.fontSize;
-
-  const inputRef = useRef<HTMLTextAreaElement>(null);
-  const [userInput, setUserInput] = useState("");
-  const [beforeInput, setBeforeInput] = useState("");
-  const [isLoading, setIsLoading] = useState(false);
-  const { submitKey, shouldSubmit } = useSubmitHandler();
-  const { scrollRef, setAutoScroll, scrollToBottom } = useScrollToBottom();
-  const [hitBottom, setHitBottom] = useState(true);
-  const isMobileScreen = useMobileScreen();
-  const navigate = useNavigate();
-
-  const onChatBodyScroll = (e: HTMLElement) => {
-    const isTouchBottom = e.scrollTop + e.clientHeight >= e.scrollHeight - 100;
-    setHitBottom(isTouchBottom);
-  };
-
-  // prompt hints
-  const promptStore = usePromptStore();
-  const [promptHints, setPromptHints] = useState<Prompt[]>([]);
-  const onSearch = useDebouncedCallback(
-    (text: string) => {
-      setPromptHints(promptStore.search(text));
-    },
-    100,
-    { leading: true, trailing: true },
-  );
-
-  const onPromptSelect = (prompt: Prompt) => {
-    setPromptHints([]);
-    inputRef.current?.focus();
-    setTimeout(() => setUserInput(prompt.content), 60);
-  };
-
-  // auto grow input
-  const [inputRows, setInputRows] = useState(2);
-  const measure = useDebouncedCallback(
-    () => {
-      const rows = inputRef.current ? autoGrowTextArea(inputRef.current) : 1;
-      const inputRows = Math.min(
-        20,
-        Math.max(2 + Number(!isMobileScreen), rows),
-      );
-      setInputRows(inputRows);
-    },
-    100,
-    {
-      leading: true,
-      trailing: true,
-    },
-  );
-
-  // eslint-disable-next-line react-hooks/exhaustive-deps
-  useEffect(measure, [userInput]);
-
-  // only search prompts when user input is short
-  const SEARCH_TEXT_LIMIT = 30;
-  const onInput = (text: string) => {
-    setUserInput(text);
-    const n = text.trim().length;
-
-    // clear search results
-    if (n === 0) {
-      setPromptHints([]);
-    } else if (!config.disablePromptHint && n < SEARCH_TEXT_LIMIT) {
-      // check if need to trigger auto completion
-      if (text.startsWith("/")) {
-        let searchText = text.slice(1);
-        onSearch(searchText);
-      }
-    }
-  };
-
-  // submit user input
-  const doSubmit = (userInput: string) => {
-    if (userInput.trim() === "") return;
-    setIsLoading(true);
-    chatStore.onUserInput(userInput).then(() => setIsLoading(false));
-    localStorage.setItem(LAST_INPUT_KEY, userInput);
-    setUserInput("");
-    setPromptHints([]);
-    if (!isMobileScreen) inputRef.current?.focus();
-    setAutoScroll(true);
-  };
-
-  // stop response
-  const onUserStop = (messageId: number) => {
-    ControllerPool.stop(sessionIndex, messageId);
-  };
-
-  // check if should send message
-  const onInputKeyDown = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
-    // if ArrowUp and no userInput, fill with last input
-    if (e.key === "ArrowUp" && userInput.length <= 0) {
-      setUserInput(localStorage.getItem(LAST_INPUT_KEY) ?? "");
-      e.preventDefault();
-      return;
-    }
-    if (shouldSubmit(e)) {
-      doSubmit(userInput);
-      e.preventDefault();
-    }
-  };
-  const onRightClick = (e: any, message: Message) => {
-
-    // copy to clipboard
-    if (selectOrCopy(e.currentTarget, message.content)) {
-      e.preventDefault();
-    }
-  };
-
-  const findLastUserIndex = (messageId: number) => {
-    // find last user input message and resend
-    let lastUserMessageIndex: number | null = null;
-    for (let i = 0; i < session.messages.length; i += 1) {
-      const message = session.messages[i];
-      if (message.id === messageId) {
-        break;
-      }
-      if (message.role === "user") {
-        lastUserMessageIndex = i;
-      }
-    }
-
-    return lastUserMessageIndex;
-  };
-
-  const deleteMessage = (userIndex: number) => {
-    chatStore.updateCurrentSession((session) =>
-      session.messages.splice(userIndex, 2),
-    );
-  };
-
-  const onDelete = (botMessageId: number) => {
-    const userIndex = findLastUserIndex(botMessageId);
-    if (userIndex === null) return;
-    deleteMessage(userIndex);
-  };
-
-  const onResend = (botMessageId: number) => {
-    // find last user input message and resend
-    const userIndex = findLastUserIndex(botMessageId);
-    if (userIndex === null) return;
-
-    setIsLoading(true);
-    const content = session.messages[userIndex].content;
-    deleteMessage(userIndex);
-    chatStore.onUserInput(content).then(() => setIsLoading(false));
-    inputRef.current?.focus();
-  };
-
-  const context: RenderMessage[] = session.mask.context.slice();
-
-  const accessStore = useAccessStore();
-
-  if (
-    context.length === 0 &&
-    session.messages.at(0)?.content !== BOT_HELLO.content
-  ) {
-    const copiedHello = Object.assign({}, BOT_HELLO);
-    if (!accessStore.isAuthorized()) {
-      copiedHello.content = Locale.Error.Unauthorized;
-    }
-    context.push(copiedHello);
-  }
-
-  // preview messages
-  const messages = context
-    .concat(session.messages as RenderMessage[])
-    .concat(
-      isLoading
-        ? [
-            {
-              ...createMessage({
-                role: "assistant",
-                content: "……",
-              }),
-              preview: true,
-            },
-          ]
-        : [],
-    )
-    .concat(
-      userInput.length > 0 && config.sendPreviewBubble
-        ? [
-            {
-              ...createMessage({
-                role: "user",
-                content: userInput,
-              }),
-              preview: true,
-            },
-          ]
-        : [],
-    );
-
-  const [showPromptModal, setShowPromptModal] = useState(false);
-
-  const renameSession = () => {
-    const newTopic = prompt(Locale.Chat.Rename, session.topic);
-    if (newTopic && newTopic !== session.topic) {
-      chatStore.updateCurrentSession((session) => (session.topic = newTopic!));
-    }
-  };
-
-  const location = useLocation();
-  const isChat = location.pathname === Path.Chat;
-  const autoFocus = !isMobileScreen || isChat; // only focus in chat page
-  useCommand({
-    fill: setUserInput,
-    submit: (text) => {
-      doSubmit(text);
-    },
-  });
-  return (
-    <div className={styles.chat} key={session.id}>
-      <div className="window-header">
-        <div className="window-header-title">
-          <div
-            className={`window-header-main-title " ${styles["chat-body-title"]}`}
-            onClickCapture={renameSession}
-          >
-            {!session.topic ? DEFAULT_TOPIC : session.topic}
-          </div>
-          <div className="window-header-sub-title">
-            {Locale.Chat.SubTitle(session.messages.length)}
-          </div>
-        </div>
-        <div className="window-actions">
-          <div className={"window-action-button" + " " + styles.mobile}>
-            <IconButton
-              icon={<ReturnIcon />}
-              bordered
-              title={Locale.Chat.Actions.ChatList}
-              onClick={() => navigate(Path.Home)}
-            />
-          </div>
-          <div className="window-action-button">
-            <IconButton
-              icon={<RenameIcon />}
-              bordered
-              onClick={renameSession}
-            />
-          </div>
-          <div className="window-action-button">
-            <IconButton
-              icon={<ExportIcon />}
-              bordered
-              title={Locale.Chat.Actions.Export}
-              onClick={() => {
-                exportMessages(
-                  session.messages.filter((msg) => !msg.isError),
-                  session.topic,
-                );
-              }}
-            />
-          </div>
-          {!isMobileScreen && (
-            <div className="window-action-button">
-              <IconButton
-                icon={config.tightBorder ? <MinIcon /> : <MaxIcon />}
-                bordered
-                onClick={() => {
-                  config.update(
-                    (config) => (config.tightBorder = !config.tightBorder),
-                  );
-                }}
-              />
-            </div>
-          )}
-        </div>
-
-        <PromptToast
-          showToast={!hitBottom}
-          showModal={showPromptModal}
-          setShowModal={setShowPromptModal}
-        />
-      </div>
-
-      <div
-        className={styles["chat-body"]}
-        ref={scrollRef}
-        onScroll={(e) => onChatBodyScroll(e.currentTarget)}
-        onMouseDown={() => inputRef.current?.blur()}
-        onWheel={(e) => setAutoScroll(hitBottom && e.deltaY > 0)}
-        onTouchStart={() => {
-          inputRef.current?.blur();
-          setAutoScroll(false);
-        }}
-      >
-        {messages.map((message, i) => {
-          const isUser = message.role === "user";
-          const showActions =
-            !isUser &&
-            i > 0 &&
-            !(message.preview || message.content.length === 0);
-          const showTyping = message.preview || message.streaming;
-
-          return (
-            <div
-              key={i}
-              className={
-                isUser ? styles["chat-message-user"] : styles["chat-message"]
-              }
-            >
-              <div className={styles["chat-message-container"]}>
-                <div className={styles["chat-message-avatar"]}>
-                  {message.role === "user" ? (
-                    <Avatar avatar={config.avatar} />
-                  ) : (
-                    <MaskAvatar mask={session.mask} />
-                  )}
-                </div>
-                {showTyping && (
-                  <div className={styles["chat-message-status"]}>
-                    {Locale.Chat.Typing}
-                  </div>
-                )}
-                <div className={styles["chat-message-item"]}>
-                  {showActions && (
-                    <div className={styles["chat-message-top-actions"]}>
-                      {message.streaming ? (
-                        <div
-                          className={styles["chat-message-top-action"]}
-                          onClick={() => onUserStop(message.id ?? i)}
-                        >
-                          {Locale.Chat.Actions.Stop}
-                        </div>
-                      ) : (
-                        <>
-                          <div
-                            className={styles["chat-message-top-action"]}
-                            onClick={() => onDelete(message.id ?? i)}
-                          >
-                            {Locale.Chat.Actions.Delete}
-                          </div>
-                          <div
-                            className={styles["chat-message-top-action"]}
-                            onClick={() => onResend(message.id ?? i)}
-                          >
-                            {Locale.Chat.Actions.Retry}
-                          </div>
-                        </>
-                      )}
-
-                      <div
-                        className={styles["chat-message-top-action"]}
-                        onClick={() => copyToClipboard(message.content)}
-                      >
-                        {Locale.Chat.Actions.Copy}
-                      </div>
-                    </div>
-                  )}
-                  <Markdown
-                    content={message.content}
-                    loading={
-                      (message.preview || message.content.length === 0) &&
-                      !isUser
-                    }
-                    onContextMenu={(e) => onRightClick(e, message)}
-                    onDoubleClickCapture={() => {
-                      if (!isMobileScreen) return;
-                      setUserInput(message.content);
-                    }}
-                    fontSize={fontSize}
-                    parentRef={scrollRef}
-                    defaultShow={i >= messages.length - 10}
-                  />
-                </div>
-                {!isUser && !message.preview && (
-                  <div className={styles["chat-message-actions"]}>
-                    <div className={styles["chat-message-action-date"]}>
-                      {message.date.toLocaleString()}
-                    </div>
-                  </div>
-                )}
-              </div>
-            </div>
-          );
-        })}
-      </div>
-
-      <div className={styles["chat-input-panel"]}>
-        <PromptHints prompts={promptHints} onPromptSelect={onPromptSelect} />
-
-        <ChatActions
-          showPromptModal={() => setShowPromptModal(true)}
-          scrollToBottom={scrollToBottom}
-          hitBottom={hitBottom}
-          showPromptHints={() => {
-            inputRef.current?.focus();
-            onSearch("");
-          }}
-        />
-        <div className={styles["chat-input-panel-inner"]}>
-          <textarea
-            ref={inputRef}
-            className={styles["chat-input"]}
-            placeholder={Locale.Chat.Input(submitKey)}
-            onInput={(e) => onInput(e.currentTarget.value)}
-            value={userInput}
-            onKeyDown={onInputKeyDown}
-            onFocus={() => setAutoScroll(true)}
-            onBlur={() => setAutoScroll(false)}
-            rows={inputRows}
-            autoFocus={autoFocus}
-          />
-          <IconButton
-            icon={<SendWhiteIcon />}
-            text={Locale.Chat.Send}
-            className={styles["chat-input-send"]}
-            type="primary"
-            onClick={() => doSubmit(userInput)}
-          />
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/spaces/Lykon/DreamShaper-webui/app.py b/spaces/Lykon/DreamShaper-webui/app.py
deleted file mode 100644
index c17e35b730a414af429a08a07a5e20dc53a002d1..0000000000000000000000000000000000000000
--- a/spaces/Lykon/DreamShaper-webui/app.py
+++ /dev/null
@@ -1,72 +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/0.0.15/xformers-0.0.15.dev0+4c06c79.d20221205-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/0.0.15/xformers-0.0.15.dev0+1515f77.d20221130-cp38-cp38-linux_x86_64.whl")
-
-os.system(f"git clone -b v1.5 https://github.com/camenduru/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 '$a fastapi==0.90.0' /home/user/app/stable-diffusion-webui/requirements_versions.txt")
-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/ outputs=\[/queue=False, &/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e 's/               queue=False,  /                /g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"pip install torchmetrics==0.11.4")
-
-if "IS_SHARED_UI" in os.environ:
-    os.system(f"rm -rfv /home/user/app/stable-diffusion-webui/scripts/")
-    
-    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"wget -q https://huggingface.co/ckpt/anything-v3-vae-swapped/resolve/main/anything-v3-vae-swapped.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/anything-v3-vae-swapped.ckpt")
-    # os.system(f"wget -q {os.getenv('MODEL_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('MODEL_NAME')}")
-    # os.system(f"wget -q {os.getenv('VAE_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('VAE_NAME')}")
-    # os.system(f"wget -q {os.getenv('YAML_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('YAML_NAME')}")
-    os.system(f"wget -q https://huggingface.co/Lykon/DreamShaper/resolve/main/DreamShaper_3.3_baked_vae.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/DreamShaper_3.3_baked_vae.safetensors")
-    os.system(f"wget -q https://huggingface.co/Lykon/DreamShaper/resolve/main/Dreamshaper_3.32_baked_vae_clip_fix.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Dreamshaper_3.32_baked_vae_clip_fix.safetensors")
-
-    os.system(f"python launch.py --force-enable-xformers --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")
-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/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/camenduru/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/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/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Anything-V3.0-pruned.ckpt")
-    #os.system(f"wget -q https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0.vae.pt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Anything-V3.0-pruned.vae.pt")
-    
-    #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"wget -q https://huggingface.co/Lykon/DreamShaper/resolve/main/DreamShaper_7_pruned.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/DreamShaper_7_pruned.safetensors")
-    os.system(f"wget -q https://huggingface.co/Lykon/AbsoluteReality/resolve/main/AbsoluteRealityV1.6525_pruned.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/AbsoluteRealityV1.6525_pruned.safetensors")
-    
-    os.system(f"python launch.py --precision full --no-half --use-cpu SD BSRGAN ESRGAN SCUNet CodeFormer --all --ui-config-file /home/user/app/ui-config.json --ui-settings-file /home/user/app/config.json --disable-console-progressbars --enable-console-prompts --cors-allow-origins huggingface.co,hf.space --no-progressbar-hiding --api --skip-torch-cuda-test")
-    
\ No newline at end of file
diff --git a/spaces/MMMMQZ/MQZGPT/modules/__init__.py b/spaces/MMMMQZ/MQZGPT/modules/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/MathysL/AutoGPT4/CODE_OF_CONDUCT.md b/spaces/MathysL/AutoGPT4/CODE_OF_CONDUCT.md
deleted file mode 100644
index d2331b4c60b9fb27f06953273355dcf53b8d4321..0000000000000000000000000000000000000000
--- a/spaces/MathysL/AutoGPT4/CODE_OF_CONDUCT.md
+++ /dev/null
@@ -1,40 +0,0 @@
-# Code of Conduct for auto-gpt
-
-## 1. Purpose
-
-The purpose of this Code of Conduct is to provide guidelines for contributors to the auto-gpt project on GitHub. We aim to create a positive and inclusive environment where all participants can contribute and collaborate effectively. By participating in this project, you agree to abide by this Code of Conduct.
-
-## 2. Scope
-
-This Code of Conduct applies to all contributors, maintainers, and users of the auto-gpt project. It extends to all project spaces, including but not limited to issues, pull requests, code reviews, comments, and other forms of communication within the project.
-
-## 3. Our Standards
-
-We encourage the following behavior:
-
-* Being respectful and considerate to others
-* Actively seeking diverse perspectives
-* Providing constructive feedback and assistance
-* Demonstrating empathy and understanding
-
-We discourage the following behavior:
-
-* Harassment or discrimination of any kind
-* Disrespectful, offensive, or inappropriate language or content
-* Personal attacks or insults
-* Unwarranted criticism or negativity
-
-## 4. Reporting and Enforcement
-
-If you witness or experience any violations of this Code of Conduct, please report them to the project maintainers by email or other appropriate means. The maintainers will investigate and take appropriate action, which may include warnings, temporary or permanent bans, or other measures as necessary.
-
-Maintainers are responsible for ensuring compliance with this Code of Conduct and may take action to address any violations.
-
-## 5. Acknowledgements
-
-This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org/version/2/0/code_of_conduct.html).
-
-## 6. Contact
-
-If you have any questions or concerns, please contact the project maintainers.
-
diff --git a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/contour_expand.py b/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/contour_expand.py
deleted file mode 100644
index ea1111e1768b5f27e118bf7dbc0d9c70a7afd6d7..0000000000000000000000000000000000000000
--- a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/contour_expand.py
+++ /dev/null
@@ -1,49 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import numpy as np
-import torch
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext('_ext', ['contour_expand'])
-
-
-def contour_expand(kernel_mask, internal_kernel_label, min_kernel_area,
-                   kernel_num):
-    """Expand kernel contours so that foreground pixels are assigned into
-    instances.
-
-    Arguments:
-        kernel_mask (np.array or Tensor): The instance kernel mask with
-            size hxw.
-        internal_kernel_label (np.array or Tensor): The instance internal
-            kernel label with size hxw.
-        min_kernel_area (int): The minimum kernel area.
-        kernel_num (int): The instance kernel number.
-
-    Returns:
-        label (list): The instance index map with size hxw.
-    """
-    assert isinstance(kernel_mask, (torch.Tensor, np.ndarray))
-    assert isinstance(internal_kernel_label, (torch.Tensor, np.ndarray))
-    assert isinstance(min_kernel_area, int)
-    assert isinstance(kernel_num, int)
-
-    if isinstance(kernel_mask, np.ndarray):
-        kernel_mask = torch.from_numpy(kernel_mask)
-    if isinstance(internal_kernel_label, np.ndarray):
-        internal_kernel_label = torch.from_numpy(internal_kernel_label)
-
-    if torch.__version__ == 'parrots':
-        if kernel_mask.shape[0] == 0 or internal_kernel_label.shape[0] == 0:
-            label = []
-        else:
-            label = ext_module.contour_expand(
-                kernel_mask,
-                internal_kernel_label,
-                min_kernel_area=min_kernel_area,
-                kernel_num=kernel_num)
-            label = label.tolist()
-    else:
-        label = ext_module.contour_expand(kernel_mask, internal_kernel_label,
-                                          min_kernel_area, kernel_num)
-    return label
diff --git a/spaces/Mileena/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/glm.py b/spaces/Mileena/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/glm.py
deleted file mode 100644
index 8be14b50f0d7edcde6328f1f805b392c8e3ab7e2..0000000000000000000000000000000000000000
--- a/spaces/Mileena/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/glm.py
+++ /dev/null
@@ -1,125 +0,0 @@
-import numpy as np
-
-
-def vec3(x, y, z):
-    return np.array([x, y, z], dtype=np.float32)
-
-
-def radians(v):
-    return np.radians(v)
-
-
-def identity():
-    return np.identity(4, dtype=np.float32)
-
-
-def empty():
-    return np.zeros([4, 4], dtype=np.float32)
-
-
-def magnitude(v):
-    return np.linalg.norm(v)
-
-
-def normalize(v):
-    m = magnitude(v)
-    return v if m == 0 else v / m
-
-
-def dot(u, v):
-    return np.sum(u * v)
-
-
-def cross(u, v):
-    res = vec3(0, 0, 0)
-    res[0] = u[1] * v[2] - u[2] * v[1]
-    res[1] = u[2] * v[0] - u[0] * v[2]
-    res[2] = u[0] * v[1] - u[1] * v[0]
-    return res
-
-
-# below functions can be optimized
-
-def translate(m, v):
-    res = np.copy(m)
-    res[:, 3] = m[:, 0] * v[0] + m[:, 1] * v[1] + m[:, 2] * v[2] + m[:, 3]
-    return res
-
-
-def rotate(m, angle, v):
-    a = angle
-    c = np.cos(a)
-    s = np.sin(a)
-
-    axis = normalize(v)
-    temp = (1 - c) * axis
-
-    rot = empty()
-    rot[0][0] = c + temp[0] * axis[0]
-    rot[0][1] = temp[0] * axis[1] + s * axis[2]
-    rot[0][2] = temp[0] * axis[2] - s * axis[1]
-
-    rot[1][0] = temp[1] * axis[0] - s * axis[2]
-    rot[1][1] = c + temp[1] * axis[1]
-    rot[1][2] = temp[1] * axis[2] + s * axis[0]
-
-    rot[2][0] = temp[2] * axis[0] + s * axis[1]
-    rot[2][1] = temp[2] * axis[1] - s * axis[0]
-    rot[2][2] = c + temp[2] * axis[2]
-
-    res = empty()
-    res[:, 0] = m[:, 0] * rot[0][0] + m[:, 1] * rot[0][1] + m[:, 2] * rot[0][2]
-    res[:, 1] = m[:, 0] * rot[1][0] + m[:, 1] * rot[1][1] + m[:, 2] * rot[1][2]
-    res[:, 2] = m[:, 0] * rot[2][0] + m[:, 1] * rot[2][1] + m[:, 2] * rot[2][2]
-    res[:, 3] = m[:, 3]
-    return res
-
-
-def perspective(fovy, aspect, zNear, zFar):
-    tanHalfFovy = np.tan(fovy / 2)
-
-    res = empty()
-    res[0][0] = 1 / (aspect * tanHalfFovy)
-    res[1][1] = 1 / (tanHalfFovy)
-    res[2][3] = -1
-    res[2][2] = - (zFar + zNear) / (zFar - zNear)
-    res[3][2] = -(2 * zFar * zNear) / (zFar - zNear)
-
-    return res.T
-
-
-def ortho(left, right, bottom, top, zNear, zFar):
-    # res = np.ones([4, 4], dtype=np.float32)
-    res = identity()
-    res[0][0] = 2 / (right - left)
-    res[1][1] = 2 / (top - bottom)
-    res[2][2] = - 2 / (zFar - zNear)
-    res[3][0] = - (right + left) / (right - left)
-    res[3][1] = - (top + bottom) / (top - bottom)
-    res[3][2] = - (zFar + zNear) / (zFar - zNear)
-    return res.T
-
-
-def lookat(eye, center, up):
-    f = normalize(center - eye)
-    s = normalize(cross(f, up))
-    u = cross(s, f)
-
-    res = identity()
-    res[0][0] = s[0]
-    res[1][0] = s[1]
-    res[2][0] = s[2]
-    res[0][1] = u[0]
-    res[1][1] = u[1]
-    res[2][1] = u[2]
-    res[0][2] = -f[0]
-    res[1][2] = -f[1]
-    res[2][2] = -f[2]
-    res[3][0] = -dot(s, eye)
-    res[3][1] = -dot(u, eye)
-    res[3][2] = -dot(f, eye)
-    return res.T
-
-
-def transform(d, m):
-    return np.dot(m, d.T).T
diff --git a/spaces/MoEternal/Hoshino/app.py b/spaces/MoEternal/Hoshino/app.py
deleted file mode 100644
index 2439c5cec6b61e8a517f957daf710cbb6b5c3cf6..0000000000000000000000000000000000000000
--- a/spaces/MoEternal/Hoshino/app.py
+++ /dev/null
@@ -1,62 +0,0 @@
-from upcunet_v3 import RealWaifuUpScaler
-import gradio as gr
-import time
-import logging
-import os
-from PIL import ImageOps
-import numpy as np
-import math
-
-
-def greet(input_img, input_model_name, input_tile_mode):
-    # if input_img.size[0] * input_img.size[1] > 256 * 256:
-    #     y = int(math.sqrt(256*256/input_img.size[0]*input_img.size[1]))
-    #     x = int(input_img.size[0]/input_img.size[1]*y)
-    #     input_img = ImageOps.fit(input_img, (x, y))
-    input_img = np.array(input_img)
-    if input_model_name not in model_cache:
-        t1 = time.time()
-        upscaler = RealWaifuUpScaler(input_model_name[2], ModelPath + input_model_name, half=False, device="cpu")
-        t2 = time.time()
-        logger.info(f'load model time, {t2 - t1}')
-        model_cache[input_model_name] = upscaler
-    else:
-        upscaler = model_cache[input_model_name]
-        logger.info(f'load model from cache')
-
-    start = time.time()
-    result = upscaler(input_img, tile_mode=input_tile_mode)
-    end = time.time()
-    logger.info(f'input_model_name, {input_model_name}')
-    logger.info(f'input_tile_mode, {input_tile_mode}')
-    logger.info(f'input shape, {input_img.shape}')
-    logger.info(f'output shape, {result.shape}')
-    logger.info(f'speed time, {end - start}')
-    return result
-
-
-if __name__ == '__main__':
-    logging.basicConfig(level=logging.INFO, format="[%(asctime)s] [%(process)d] [%(levelname)s] %(message)s")
-    logger = logging.getLogger()
-
-    ModelPath = "weights_v3/"
-    model_cache = {}
-
-    input_model_name = gr.inputs.Dropdown(os.listdir(ModelPath), default="up2x-latest-denoise2x.pth", label='选择model')
-    input_tile_mode = gr.inputs.Dropdown([0, 1, 2, 3, 4], default=2, label='选择tile_mode')
-    input_img = gr.inputs.Image(label='image', type='pil')
-
-    inputs = [input_img, input_model_name, input_tile_mode]
-    outputs = "image"
-    iface = gr.Interface(fn=greet,
-                         inputs=inputs,
-                         outputs=outputs,
-                         allow_screenshot=False,
-                         allow_flagging='never',
-                         examples=[['test-img.jpg', "up2x-latest-denoise2x.pth", 2]],
-                         article='[https://github.com/bilibili/ailab/tree/main/Real-CUGAN](https://github.com/bilibili/ailab/tree/main/Real-CUGAN)<br>'
-                                 '感谢b站开源的项目，图片过大会导致内存不足，所有我将图片裁剪小，想体验大图片的效果请自行前往上面的链接。<br>'
-                                 '修改bbb'
-                                 'The large image will lead to memory limit exceeded. So I crop and resize image. '
-                                 'If you want to experience the large image, please go to the link above.')
-    iface.launch()
diff --git a/spaces/ModIA/FrenchDroneKeyword/resnet.py b/spaces/ModIA/FrenchDroneKeyword/resnet.py
deleted file mode 100644
index e275555938ae33690f52ee5ca3610f4619367250..0000000000000000000000000000000000000000
--- a/spaces/ModIA/FrenchDroneKeyword/resnet.py
+++ /dev/null
@@ -1,70 +0,0 @@
-import torch
-import torch.nn as nn
-
-
-class ResNet(nn.Module):
-    def __init__(self, in_channels: int, num_classes: int):
-        """ResNet9"""
-        super().__init__()
-        
-        self.conv1 = ConvBlock(in_channels, 64)
-        self.conv2 = ConvBlock(64, 128, pool=True)
-        self.res1 = nn.Sequential(
-            ConvBlock(128, 128),
-            ConvBlock(128, 128)
-        )
-
-        self.conv3 = ConvBlock(128, 256)
-        self.conv4 = ConvBlock(256, 512, pool=True)
-        self.res2 = nn.Sequential(
-            ConvBlock(512, 512),
-            ConvBlock(512, 512)
-        )
-        
-        self.classifier = nn.Sequential(
-            nn.MaxPool2d(kernel_size=(4, 4)),
-            nn.AdaptiveAvgPool2d(1),
-            nn.Flatten(), 
-            nn.Linear(512, 128),
-            nn.Dropout(0.25),
-            nn.Linear(128, num_classes),
-            nn.Dropout(0.25),
-        )
-        
-    def forward(self, x: torch.Tensor) -> torch.Tensor:
-        x = self.conv1(x)
-        x = self.conv2(x)
-        x = self.res1(x) + x #skip
-        x = self.conv3(x)
-        x = self.conv4(x)
-        x = self.res2(x) + x #skip
-        prediction = self.classifier(x)
-        return prediction
-
-class ConvBlock(nn.Module):
-    def __init__(self, in_channels: int, out_channels: int, pool: bool = False, pool_no: int = 2):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.pool = pool
-        self.pool_no = pool_no
-
-        if self.pool:
-            self.pool_block = nn.Sequential(
-                nn.ReLU(inplace=True),
-                nn.MaxPool2d(self.pool_no)
-            )
-        else:
-            self.pool_block = nn.Sequential(
-                nn.ReLU(inplace=True),
-            )
-        
-        self.block = nn.Sequential(
-            nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1),
-            nn.BatchNorm2d(out_channels),
-            self.pool_block
-        )
-    
-    def forward(self, x: torch.Tensor) -> torch.Tensor:
-        x = self.block(x)
-        return x
\ No newline at end of file
diff --git a/spaces/MoonQiu/LongerCrafter/lvdm/modules/encoders/condition.py b/spaces/MoonQiu/LongerCrafter/lvdm/modules/encoders/condition.py
deleted file mode 100644
index 401a6b3d0597c80e9a9189d8e0e465bb181d4f7a..0000000000000000000000000000000000000000
--- a/spaces/MoonQiu/LongerCrafter/lvdm/modules/encoders/condition.py
+++ /dev/null
@@ -1,392 +0,0 @@
-import torch
-import torch.nn as nn
-from torch.utils.checkpoint import checkpoint
-import kornia
-import open_clip
-from transformers import T5Tokenizer, T5EncoderModel, CLIPTokenizer, CLIPTextModel
-from lvdm.common import autocast
-from utils.utils import count_params
-
-class AbstractEncoder(nn.Module):
-    def __init__(self):
-        super().__init__()
-
-    def encode(self, *args, **kwargs):
-        raise NotImplementedError
-
-
-class IdentityEncoder(AbstractEncoder):
-
-    def encode(self, x):
-        return x
-
-
-class ClassEmbedder(nn.Module):
-    def __init__(self, embed_dim, n_classes=1000, key='class', ucg_rate=0.1):
-        super().__init__()
-        self.key = key
-        self.embedding = nn.Embedding(n_classes, embed_dim)
-        self.n_classes = n_classes
-        self.ucg_rate = ucg_rate
-
-    def forward(self, batch, key=None, disable_dropout=False):
-        if key is None:
-            key = self.key
-        # this is for use in crossattn
-        c = batch[key][:, None]
-        if self.ucg_rate > 0. and not disable_dropout:
-            mask = 1. - torch.bernoulli(torch.ones_like(c) * self.ucg_rate)
-            c = mask * c + (1 - mask) * torch.ones_like(c) * (self.n_classes - 1)
-            c = c.long()
-        c = self.embedding(c)
-        return c
-
-    def get_unconditional_conditioning(self, bs, device="cuda"):
-        uc_class = self.n_classes - 1  # 1000 classes --> 0 ... 999, one extra class for ucg (class 1000)
-        uc = torch.ones((bs,), device=device) * uc_class
-        uc = {self.key: uc}
-        return uc
-
-
-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 FrozenT5Embedder(AbstractEncoder):
-    """Uses the T5 transformer encoder for text"""
-
-    def __init__(self, version="google/t5-v1_1-large", device="cuda", max_length=77,
-                 freeze=True):  # others are google/t5-v1_1-xl and google/t5-v1_1-xxl
-        super().__init__()
-        self.tokenizer = T5Tokenizer.from_pretrained(version)
-        self.transformer = T5EncoderModel.from_pretrained(version)
-        self.device = device
-        self.max_length = max_length  # TODO: typical value?
-        if freeze:
-            self.freeze()
-
-    def freeze(self):
-        self.transformer = self.transformer.eval()
-        # self.train = disabled_train
-        for param in self.parameters():
-            param.requires_grad = False
-
-    def forward(self, text):
-        batch_encoding = self.tokenizer(text, truncation=True, max_length=self.max_length, return_length=True,
-                                        return_overflowing_tokens=False, padding="max_length", return_tensors="pt")
-        tokens = batch_encoding["input_ids"].to(self.device)
-        outputs = self.transformer(input_ids=tokens)
-
-        z = outputs.last_hidden_state
-        return z
-
-    def encode(self, text):
-        return self(text)
-
-
-class FrozenCLIPEmbedder(AbstractEncoder):
-    """Uses the CLIP transformer encoder for text (from huggingface)"""
-    LAYERS = [
-        "last",
-        "pooled",
-        "hidden"
-    ]
-
-    def __init__(self, version="openai/clip-vit-large-patch14", device="cuda", max_length=77,
-                 freeze=True, layer="last", layer_idx=None):  # clip-vit-base-patch32
-        super().__init__()
-        assert layer in self.LAYERS
-        self.tokenizer = CLIPTokenizer.from_pretrained(version)
-        self.transformer = CLIPTextModel.from_pretrained(version)
-        self.device = device
-        self.max_length = max_length
-        if freeze:
-            self.freeze()
-        self.layer = layer
-        self.layer_idx = layer_idx
-        if layer == "hidden":
-            assert layer_idx is not None
-            assert 0 <= abs(layer_idx) <= 12
-
-    def freeze(self):
-        self.transformer = self.transformer.eval()
-        # self.train = disabled_train
-        for param in self.parameters():
-            param.requires_grad = False
-
-    def forward(self, text):
-        batch_encoding = self.tokenizer(text, truncation=True, max_length=self.max_length, return_length=True,
-                                        return_overflowing_tokens=False, padding="max_length", return_tensors="pt")
-        tokens = batch_encoding["input_ids"].to(self.device)
-        outputs = self.transformer(input_ids=tokens, output_hidden_states=self.layer == "hidden")
-        if self.layer == "last":
-            z = outputs.last_hidden_state
-        elif self.layer == "pooled":
-            z = outputs.pooler_output[:, None, :]
-        else:
-            z = outputs.hidden_states[self.layer_idx]
-        return z
-
-    def encode(self, text):
-        return self(text)
-
-
-class ClipImageEmbedder(nn.Module):
-    def __init__(
-            self,
-            model,
-            jit=False,
-            device='cuda' if torch.cuda.is_available() else 'cpu',
-            antialias=True,
-            ucg_rate=0.
-    ):
-        super().__init__()
-        from clip import load as load_clip
-        self.model, _ = load_clip(name=model, device=device, jit=jit)
-
-        self.antialias = antialias
-
-        self.register_buffer('mean', torch.Tensor([0.48145466, 0.4578275, 0.40821073]), persistent=False)
-        self.register_buffer('std', torch.Tensor([0.26862954, 0.26130258, 0.27577711]), persistent=False)
-        self.ucg_rate = ucg_rate
-
-    def preprocess(self, x):
-        # normalize to [0,1]
-        x = kornia.geometry.resize(x, (224, 224),
-                                   interpolation='bicubic', align_corners=True,
-                                   antialias=self.antialias)
-        x = (x + 1.) / 2.
-        # re-normalize according to clip
-        x = kornia.enhance.normalize(x, self.mean, self.std)
-        return x
-
-    def forward(self, x, no_dropout=False):
-        # x is assumed to be in range [-1,1]
-        out = self.model.encode_image(self.preprocess(x))
-        out = out.to(x.dtype)
-        if self.ucg_rate > 0. and not no_dropout:
-            out = torch.bernoulli((1. - self.ucg_rate) * torch.ones(out.shape[0], device=out.device))[:, None] * out
-        return out
-
-
-class FrozenOpenCLIPEmbedder(AbstractEncoder):
-    """
-    Uses the OpenCLIP transformer encoder for text
-    """
-    LAYERS = [
-        # "pooled",
-        "last",
-        "penultimate"
-    ]
-
-    def __init__(self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", max_length=77,
-                 freeze=True, layer="last"):
-        super().__init__()
-        assert layer in self.LAYERS
-        model, _, _ = open_clip.create_model_and_transforms(arch, device=torch.device('cpu'))
-        del model.visual
-        self.model = model
-
-        self.device = device
-        self.max_length = max_length
-        if freeze:
-            self.freeze()
-        self.layer = layer
-        if self.layer == "last":
-            self.layer_idx = 0
-        elif self.layer == "penultimate":
-            self.layer_idx = 1
-        else:
-            raise NotImplementedError()
-
-    def freeze(self):
-        self.model = self.model.eval()
-        for param in self.parameters():
-            param.requires_grad = False
-
-    def forward(self, text):
-        self.device = self.model.positional_embedding.device
-        tokens = open_clip.tokenize(text)
-        z = self.encode_with_transformer(tokens.to(self.device))
-        return z
-
-    def encode_with_transformer(self, text):
-        x = self.model.token_embedding(text)  # [batch_size, n_ctx, d_model]
-        x = x + self.model.positional_embedding
-        x = x.permute(1, 0, 2)  # NLD -> LND
-        x = self.text_transformer_forward(x, attn_mask=self.model.attn_mask)
-        x = x.permute(1, 0, 2)  # LND -> NLD
-        x = self.model.ln_final(x)
-        return x
-
-    def text_transformer_forward(self, x: torch.Tensor, attn_mask=None):
-        for i, r in enumerate(self.model.transformer.resblocks):
-            if i == len(self.model.transformer.resblocks) - self.layer_idx:
-                break
-            if self.model.transformer.grad_checkpointing and not torch.jit.is_scripting():
-                x = checkpoint(r, x, attn_mask)
-            else:
-                x = r(x, attn_mask=attn_mask)
-        return x
-
-    def encode(self, text):
-        return self(text)
-
-
-class FrozenOpenCLIPImageEmbedder(AbstractEncoder):
-    """
-    Uses the OpenCLIP vision transformer encoder for images
-    """
-
-    def __init__(self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", max_length=77,
-                 freeze=True, layer="pooled", antialias=True, ucg_rate=0.):
-        super().__init__()
-        model, _, _ = open_clip.create_model_and_transforms(arch, device=torch.device('cpu'),
-                                                            pretrained=version, )
-        del model.transformer
-        self.model = model
-
-        self.device = device
-        self.max_length = max_length
-        if freeze:
-            self.freeze()
-        self.layer = layer
-        if self.layer == "penultimate":
-            raise NotImplementedError()
-            self.layer_idx = 1
-
-        self.antialias = antialias
-
-        self.register_buffer('mean', torch.Tensor([0.48145466, 0.4578275, 0.40821073]), persistent=False)
-        self.register_buffer('std', torch.Tensor([0.26862954, 0.26130258, 0.27577711]), persistent=False)
-        self.ucg_rate = ucg_rate
-
-    def preprocess(self, x):
-        # normalize to [0,1]
-        x = kornia.geometry.resize(x, (224, 224),
-                                   interpolation='bicubic', align_corners=True,
-                                   antialias=self.antialias)
-        x = (x + 1.) / 2.
-        # renormalize according to clip
-        x = kornia.enhance.normalize(x, self.mean, self.std)
-        return x
-
-    def freeze(self):
-        self.model = self.model.eval()
-        for param in self.parameters():
-            param.requires_grad = False
-
-    @autocast
-    def forward(self, image, no_dropout=False):
-        z = self.encode_with_vision_transformer(image)
-        if self.ucg_rate > 0. and not no_dropout:
-            z = torch.bernoulli((1. - self.ucg_rate) * torch.ones(z.shape[0], device=z.device))[:, None] * z
-        return z
-
-    def encode_with_vision_transformer(self, img):
-        img = self.preprocess(img)
-        x = self.model.visual(img)
-        return x
-
-    def encode(self, text):
-        return self(text)
-
-
-
-class FrozenOpenCLIPImageEmbedderV2(AbstractEncoder):
-    """
-    Uses the OpenCLIP vision transformer encoder for images
-    """
-
-    def __init__(self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda",
-                 freeze=True, layer="pooled", antialias=True):
-        super().__init__()
-        model, _, _ = open_clip.create_model_and_transforms(arch, device=torch.device('cpu'),
-                                                            pretrained=version, )
-        del model.transformer
-        self.model = model
-        self.device = device
-
-        if freeze:
-            self.freeze()
-        self.layer = layer
-        if self.layer == "penultimate":
-            raise NotImplementedError()
-            self.layer_idx = 1
-
-        self.antialias = antialias
-        self.register_buffer('mean', torch.Tensor([0.48145466, 0.4578275, 0.40821073]), persistent=False)
-        self.register_buffer('std', torch.Tensor([0.26862954, 0.26130258, 0.27577711]), persistent=False)
-
-
-    def preprocess(self, x):
-        # normalize to [0,1]
-        x = kornia.geometry.resize(x, (224, 224),
-                                   interpolation='bicubic', align_corners=True,
-                                   antialias=self.antialias)
-        x = (x + 1.) / 2.
-        # renormalize according to clip
-        x = kornia.enhance.normalize(x, self.mean, self.std)
-        return x
-
-    def freeze(self):
-        self.model = self.model.eval()
-        for param in self.model.parameters():
-            param.requires_grad = False
-
-    def forward(self, image, no_dropout=False):
-        ## image: b c h w
-        z = self.encode_with_vision_transformer(image)
-        return z
-
-    def encode_with_vision_transformer(self, x):
-        x = self.preprocess(x)
-
-        # to patches - whether to use dual patchnorm - https://arxiv.org/abs/2302.01327v1
-        if self.model.visual.input_patchnorm:
-            # einops - rearrange(x, 'b c (h p1) (w p2) -> b (h w) (c p1 p2)')
-            x = x.reshape(x.shape[0], x.shape[1], self.model.visual.grid_size[0], self.model.visual.patch_size[0], self.model.visual.grid_size[1], self.model.visual.patch_size[1])
-            x = x.permute(0, 2, 4, 1, 3, 5)
-            x = x.reshape(x.shape[0], self.model.visual.grid_size[0] * self.model.visual.grid_size[1], -1)
-            x = self.model.visual.patchnorm_pre_ln(x)
-            x = self.model.visual.conv1(x)
-        else:
-            x = self.model.visual.conv1(x)  # shape = [*, width, grid, grid]
-            x = x.reshape(x.shape[0], x.shape[1], -1)  # shape = [*, width, grid ** 2]
-            x = x.permute(0, 2, 1)  # shape = [*, grid ** 2, width]
-
-        # class embeddings and positional embeddings
-        x = torch.cat(
-            [self.model.visual.class_embedding.to(x.dtype) + torch.zeros(x.shape[0], 1, x.shape[-1], dtype=x.dtype, device=x.device),
-             x], dim=1)  # shape = [*, grid ** 2 + 1, width]
-        x = x + self.model.visual.positional_embedding.to(x.dtype)
-
-        # a patch_dropout of 0. would mean it is disabled and this function would do nothing but return what was passed in
-        x = self.model.visual.patch_dropout(x)
-        x = self.model.visual.ln_pre(x)
-
-        x = x.permute(1, 0, 2)  # NLD -> LND
-        x = self.model.visual.transformer(x)
-        x = x.permute(1, 0, 2)  # LND -> NLD
-
-        return x
-
-
-class FrozenCLIPT5Encoder(AbstractEncoder):
-    def __init__(self, clip_version="openai/clip-vit-large-patch14", t5_version="google/t5-v1_1-xl", device="cuda",
-                 clip_max_length=77, t5_max_length=77):
-        super().__init__()
-        self.clip_encoder = FrozenCLIPEmbedder(clip_version, device, max_length=clip_max_length)
-        self.t5_encoder = FrozenT5Embedder(t5_version, device, max_length=t5_max_length)
-        print(f"{self.clip_encoder.__class__.__name__} has {count_params(self.clip_encoder) * 1.e-6:.2f} M parameters, "
-              f"{self.t5_encoder.__class__.__name__} comes with {count_params(self.t5_encoder) * 1.e-6:.2f} M params.")
-
-    def encode(self, text):
-        return self(text)
-
-    def forward(self, text):
-        clip_z = self.clip_encoder.encode(text)
-        t5_z = self.t5_encoder.encode(text)
-        return [clip_z, t5_z]
\ No newline at end of file
diff --git a/spaces/MoonQiu/LongerCrafter/scripts/run_text2video.sh b/spaces/MoonQiu/LongerCrafter/scripts/run_text2video.sh
deleted file mode 100644
index a857e1f0a6e0abd2d1c4c0aac1b628e292847c6b..0000000000000000000000000000000000000000
--- a/spaces/MoonQiu/LongerCrafter/scripts/run_text2video.sh
+++ /dev/null
@@ -1,22 +0,0 @@
-name="base_512_test"
-
-ckpt='checkpoints/base_512_v1/model.ckpt'
-config='configs/inference_t2v_tconv512_v1.0.yaml'
-
-prompt_file="prompts/single_prompts.txt"
-res_dir="results_single_512"
-
-python3 scripts/evaluation/inference.py \
---seed 123 \
---mode 'base' \
---ckpt_path $ckpt \
---config $config \
---savedir $res_dir/$name \
---n_samples 3 \
---bs 1 --height 320 --width 512 \
---unconditional_guidance_scale 12.0 \
---ddim_steps 50 \
---ddim_eta 0.0 \
---prompt_file $prompt_file \
---fps 8 \
---frames 16 
diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textdet/heads/__init__.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textdet/heads/__init__.py
deleted file mode 100644
index 5663ebebb88ab2ef0cf41e8beee86f0253288972..0000000000000000000000000000000000000000
--- a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textdet/heads/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from .base import BaseTextDetHead
-from .db_head import DBHead
-from .drrg_head import DRRGHead
-from .fce_head import FCEHead
-from .pan_head import PANHead
-from .pse_head import PSEHead
-from .textsnake_head import TextSnakeHead
-
-__all__ = [
-    'PSEHead', 'PANHead', 'DBHead', 'FCEHead', 'TextSnakeHead', 'DRRGHead',
-    'BaseTextDetHead'
-]
diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/aster_encoder.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/aster_encoder.py
deleted file mode 100644
index 521218153701c510478b1e4ac3912c89f8eecfd4..0000000000000000000000000000000000000000
--- a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/aster_encoder.py
+++ /dev/null
@@ -1,43 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import torch
-import torch.nn as nn
-
-from mmocr.registry import MODELS
-from .base import BaseEncoder
-
-
-@MODELS.register_module()
-class ASTEREncoder(BaseEncoder):
-    """Implement BiLSTM encoder module in `ASTER: An Attentional Scene Text
-    Recognizer with Flexible Rectification.
-
-    <https://ieeexplore.ieee.org/abstract/document/8395027/`
-    Args:
-        in_channels (int): Number of input channels.
-        num_layers (int): Layers of BiLSTM. Defaults to 2.
-    """
-
-    def __init__(self,
-                 in_channels: int,
-                 num_layers: int = 2,
-                 init_cfg=dict(type='Xavier', layer='Conv2d')) -> None:
-        super().__init__(init_cfg=init_cfg)
-        self.bilstm = nn.LSTM(
-            in_channels,
-            in_channels // 2,
-            num_layers=num_layers,
-            bidirectional=True,
-            batch_first=True)
-
-    def forward(self, feat: torch.Tensor, img_metas=None) -> torch.Tensor:
-        """
-        Args:
-            feat (Tensor): Feature of shape (N, C, 1, W).
-        Returns:
-            Tensor: Output of BiLSTM.
-        """
-        assert feat.dim() == 4
-        assert feat.size(2) == 1, 'height must be 1'
-        feat = feat.squeeze(2).permute(0, 2, 1)
-        feat, _ = self.bilstm(feat)
-        return feat.contiguous()
diff --git a/spaces/MuGeminorum/insecta/README.md b/spaces/MuGeminorum/insecta/README.md
deleted file mode 100644
index 8c4f49d0669d44bba4b22cd2b08199b0ebd97d56..0000000000000000000000000000000000000000
--- a/spaces/MuGeminorum/insecta/README.md
+++ /dev/null
@@ -1,25 +0,0 @@
----
-title: insecta
-emoji: 🐞
-colorFrom: indigo
-colorTo: pink
-sdk: gradio
-sdk_version: 3.37.0
-app_file: app.py
-pinned: false
----
-
-# 特性
-- 支持 2037 类 (可能是目, 科, 属或种等) 昆虫或其他节肢动物
-- 模型开源, 持续更新.
-
-# 安装
-先安装 Miniconda, 然后执行
-```
-echo y | conda create -n insect python=3.10
-conda activate insect
-pip install -r requirements.txt
-```
-
-# 用法 
-拖拽含有昆虫的图片进网页，点击 Detect
\ No newline at end of file
diff --git a/spaces/MultiTransformer/Automated-Social-Media-Campaign/README.md b/spaces/MultiTransformer/Automated-Social-Media-Campaign/README.md
deleted file mode 100644
index 6b815005acc574fd6e88fa0a7b297850fc378c23..0000000000000000000000000000000000000000
--- a/spaces/MultiTransformer/Automated-Social-Media-Campaign/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Automated Social Media Campaign
-emoji: 🏃
-colorFrom: yellow
-colorTo: green
-sdk: static
-pinned: false
-license: mit
----
-
-# Automated Social Media Campaign By Jamp
-
-See the app.py file in the file tab for the program
\ No newline at end of file
diff --git a/spaces/NAACL2022/CLIP-Caption-Reward/retrieval/text_utils.py b/spaces/NAACL2022/CLIP-Caption-Reward/retrieval/text_utils.py
deleted file mode 100644
index 51f981054b41a945656f9e619c722e09de198bf7..0000000000000000000000000000000000000000
--- a/spaces/NAACL2022/CLIP-Caption-Reward/retrieval/text_utils.py
+++ /dev/null
@@ -1,74 +0,0 @@
-import random
-
-def repeat(text, n_max_gram=3, n_max_repeat=3):
-    """repeat n-grams"""
-    tokens = text.split()
-
-    n_gram = random.randint(1, n_max_gram)
-
-    repeat_token_idx = random.randint(0, len(tokens) - n_gram)
-
-    repeated_tokens = tokens[repeat_token_idx:repeat_token_idx+n_gram]
-
-    n_repeat = random.randint(1, n_max_repeat)
-    for _ in range(n_repeat):
-        insert_idx = random.randint(0, len(tokens))
-        tokens = tokens[:insert_idx] + \
-            repeated_tokens + tokens[insert_idx:]
-
-    new_text = " ".join(tokens)
-    return new_text
-
-def remove(text, n_max_gram=3):
-    """remove n-grams"""
-    tokens = text.split()
-
-    n_gram = random.randint(1, n_max_gram)
-
-    remove_token_idx = random.randint(0, len(tokens) - n_gram)
-
-    tokens = tokens[:remove_token_idx] + tokens[remove_token_idx + n_gram:]
-
-    new_text = " ".join(tokens)
-    return new_text
-
-def insert(text, vocab, n_max_tokens=3):
-    """Insert tokens"""
-    tokens = text.split()
-
-    n_insert_token = random.randint(1, n_max_tokens)
-
-    for _ in range(n_insert_token):
-        insert_token_idx = random.randint(0, len(tokens) - 1)
-        insert_token = random.choice(vocab)
-        tokens = tokens[:insert_token_idx] + [insert_token] + tokens[insert_token_idx:]
-
-    new_text = " ".join(tokens)
-    return new_text
-
-def swap(text, vocab, n_max_tokens=3):
-    """Swap tokens"""
-    tokens = text.split()
-
-    n_swap_tokens = random.randint(1, n_max_tokens)
-
-    for _ in range(n_swap_tokens):
-        swap_token_idx = random.randint(0, len(tokens) - 1)
-
-        swap_token = random.choice(vocab)
-        while swap_token == tokens[swap_token_idx]:
-            swap_token = random.choice(vocab)
-
-        tokens[swap_token_idx] = swap_token
-
-    new_text = " ".join(tokens)
-    return new_text
-
-def shuffle(text):
-    """shuffle tokens"""
-    tokens = text.split()
-
-    random.shuffle(tokens)
-
-    new_text = " ".join(tokens)
-    return new_text
diff --git a/spaces/NATSpeech/PortaSpeech/docs/framework.md b/spaces/NATSpeech/PortaSpeech/docs/framework.md
deleted file mode 100644
index a48bb2b49d2e9696e2f8d4b01be8af68befc552c..0000000000000000000000000000000000000000
--- a/spaces/NATSpeech/PortaSpeech/docs/framework.md
+++ /dev/null
@@ -1,106 +0,0 @@
-# Framework of NATSpeech
-
-NATSpeech is a simple framework for Non-Autoregressive Text-to-Speech.
-
-## Directory Structure
-
-- `egs`: configuration files, which will be loaded by `utils/commons/hparams.py`
-- `data_gen`: data binarization codes
-- `modules`: modules and models
-- `tasks`: the training and inference logics
-- `utils`: commonly used utils
-- `data`: data
-    - `raw`: raw data
-    - `processed`: data after preprocess
-    - `binary`: binary data
-- `checkpoints`: model checkpoints, tensorboard logs and generated results for all experiments.
-
-## How to Add New Tasks and Run?
-
-We show the basic steps of adding a new task/model and running the code (LJSpeech dataset as an example).
-
-### Add the model
-
-Add your model to `modules`.
-
-### Add the task
-
-Task classes are used to manage the training and inference procedures.
-
-A new task (e.g., `tasks.tts.fs.FastSpeechTask`) should inherit the base task (`tasks.tts.speech_base.TTSBaseTask`)
-class.
-
-You must implement these methods:
-
-- `build_tts_model`, which builds the model for your task. - `run_model`, indicating how to use the model in training
-  and inference.
-
-You can override `test_step` and `save_valid_result` to change the validation/testing logics or add more plots to
-tensorboard.
-
-### Add a new config file
-
-Add a new config file in `egs/datasets/audio/lj/YOUR_TASK.yaml`. For example:
-
-```yaml
-base_config: ./base_text2mel.yaml
-task_cls: tasks.tts.fs.FastSpeechTask
-
-# model configs
-hidden_size: 256
-dropout: 0.1
-
-# some more configs .....
-```
-
-If you use a new dataset `YOUR_DATASET`, you should also add a `YOUR_DATASET_Processor`
-in `egs/datasets/audio/YOUR_DATASET/preprocess.py`, inheriting `data_gen.tts.base_preprocess.BasePreprocessor`, which
-loads some meta information of the dataset.
-
-### Preprocess and binary dataset
-
-```bash
-python data_gen/tts/runs/align_and_binarize.py --config egs/datasets/audio/lj/base_text2mel.yaml
-```
-
-### Training
-
-```bash
-CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config YOUR_CONFIG --exp_name YOUR_EXP_NAME --reset
-```
-
-You can open Tensorboard via:
-
-```bash
-tensorboard --logdir checkpoints/EXP_NAME
-```
-
-### Inference (Testing)
-
-```bash
-CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config egs/datasets/audio/lj/YOUR_TASK.yaml --exp_name YOUR_EXP_NAME --reset --infer
-```
-
-## Design Philosophy
-
-### Random-Access Binarized Dataset
-
-To address the IO problem when reading small files, we design a `IndexedDataset` class (_utils/commons/indexed_datasets.py_)
-
-### Global Config
-
-We introduce a global config `hparams`, which is load from a `.yaml` config file and can be used in anywhere. However,
-we do not recommend using it in some general-purpose modules.
-
-### BaseTrainer Framework
-
-Our [base trainer](utils/commons/trainer.py) and [base task ](utils/commons/base_task.py) classes refer
-to [PytorchLightning](https://github.com/PyTorchLightning/pytorch-lightning), which builds some commonly used
-training/inference code structure. Our framework supports multi-process GPU training without changing the subclass
-codes.
-
-### Checkpoint Saving
-
-All checkpoints and tensorboard logs are saved in `checkpoints/EXP_NAME`, where `EXP_NAME` is set in the running
-command: `python tasks/run.py .... --exp_name EXP_NAME`. You can use `tensorboard --logdir checkpoints/EXP_NAME` to open
-the tensorboard and check the training loss curves etc.
diff --git a/spaces/NCTCMumbai/NCTC/models/official/benchmark/nhnet_benchmark.py b/spaces/NCTCMumbai/NCTC/models/official/benchmark/nhnet_benchmark.py
deleted file mode 100644
index 7eac36b204a4f064216fb4c81effff06d8c7e6f0..0000000000000000000000000000000000000000
--- a/spaces/NCTCMumbai/NCTC/models/official/benchmark/nhnet_benchmark.py
+++ /dev/null
@@ -1,148 +0,0 @@
-# Lint as: python3
-# Copyright 2020 The TensorFlow 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.
-# ==============================================================================
-"""Executes benchmark testing for bert pretraining."""
-# pylint: disable=line-too-long
-from __future__ import print_function
-
-import time
-from typing import Optional
-
-from absl import flags
-import tensorflow as tf
-
-from official.benchmark import benchmark_wrappers
-from official.benchmark import owner_utils
-from official.benchmark import perfzero_benchmark
-from official.nlp.nhnet import trainer
-from official.utils.flags import core as flags_core
-
-MIN_LOSS = 0.40
-MAX_LOSS = 0.55
-NHNET_DATA = 'gs://tf-perfzero-data/nhnet/v1/processed/train.tfrecord*'
-PRETRAINED_CHECKPOINT_PATH = 'gs://cloud-tpu-checkpoints/bert/keras_bert/uncased_L-12_H-768_A-12/bert_model.ckpt'
-
-FLAGS = flags.FLAGS
-
-
-class NHNetBenchmark(perfzero_benchmark.PerfZeroBenchmark):
-  """Base benchmark class for NHNet."""
-
-  def __init__(self, output_dir=None, default_flags=None, tpu=None, **kwargs):
-    self.default_flags = default_flags or {}
-    flag_methods = trainer.define_flags()
-    super(NHNetBenchmark, self).__init__(
-        output_dir=output_dir,
-        default_flags=default_flags,
-        flag_methods=flag_methods,
-        tpu=tpu,
-        **kwargs)
-
-  def _report_benchmark(self,
-                        stats,
-                        wall_time_sec,
-                        max_value=None,
-                        min_value=None):
-    """Report benchmark results by writing to local protobuf file.
-
-    Args:
-      stats: dict returned from keras models with known entries.
-      wall_time_sec: the during of the benchmark execution in seconds
-      max_value: highest passing level.
-      min_value: lowest passing level.
-    """
-
-    metrics = []
-    metrics.append({
-        'name': 'training_loss',
-        'value': stats['training_loss'],
-        'min_value': min_value,
-        'max_value': max_value
-    })
-    # These metrics are placeholders to avoid PerfZero failure.
-    metrics.append({
-        'name': 'exp_per_second',
-        'value': 0.0,
-    })
-    metrics.append({
-        'name': 'startup_time',
-        'value': 9999.,
-    })
-    flags_str = flags_core.get_nondefault_flags_as_str()
-    self.report_benchmark(
-        iters=-1,
-        wall_time=wall_time_sec,
-        metrics=metrics,
-        extras={'flags': flags_str})
-
-
-class NHNetAccuracyBenchmark(NHNetBenchmark):
-  """Benchmark accuracy tests for NHNet."""
-
-  def __init__(self,
-               output_dir: Optional[str] = None,
-               tpu: Optional[str] = None,
-               **kwargs):
-    default_flags = dict(
-        mode='train',
-        train_file_pattern=NHNET_DATA,
-        train_batch_size=1024,
-        model_type='nhnet',
-        len_title=15,
-        len_passage=200,
-        num_encoder_layers=12,
-        num_decoder_layers=12,
-        num_nhnet_articles=5,
-        steps_per_loop=1000,
-        params_override='init_from_bert2bert=false')
-    super(NHNetAccuracyBenchmark, self).__init__(
-        output_dir=output_dir, default_flags=default_flags, tpu=tpu, **kwargs)
-
-  @benchmark_wrappers.enable_runtime_flags
-  def _run_and_report_benchmark(self, max_value=MAX_LOSS, min_value=MIN_LOSS):
-    """Runs and reports the benchmark given the provided configuration."""
-    start_time_sec = time.time()
-    stats = trainer.run()
-    wall_time_sec = time.time() - start_time_sec
-    self._report_benchmark(
-        stats, wall_time_sec, max_value=max_value, min_value=min_value)
-
-  @owner_utils.Owner('tf-model-garden')
-  def benchmark_accuracy_4x4_tpu_f32_50k_steps(self):
-    """Test bert pretraining with 4x4 TPU for 50k steps."""
-    # This is used for accuracy test.
-    self._setup()
-    FLAGS.train_steps = 50000
-    FLAGS.checkpoint_interval = FLAGS.train_steps
-    FLAGS.distribution_strategy = 'tpu'
-    FLAGS.init_checkpoint = PRETRAINED_CHECKPOINT_PATH
-    FLAGS.model_dir = self._get_model_dir(
-        'benchmark_accuracy_4x4_tpu_bf32_50k_steps')
-    self._run_and_report_benchmark()
-
-  @owner_utils.Owner('tf-model-garden')
-  def benchmark_accuracy_4x4_tpu_f32_1k_steps(self):
-    """Test bert pretraining with 4x4 TPU for 1k steps."""
-    self._setup()
-    FLAGS.train_steps = 1000
-    FLAGS.checkpoint_interval = FLAGS.train_steps
-    FLAGS.distribution_strategy = 'tpu'
-    FLAGS.model_dir = self._get_model_dir(
-        'benchmark_accuracy_4x4_tpu_bf32_1k_steps')
-    self._run_and_report_benchmark()
-
-
-if __name__ == '__main__':
-  tf.test.main()
diff --git a/spaces/NCTCMumbai/NCTC/models/official/vision/detection/executor/__init__.py b/spaces/NCTCMumbai/NCTC/models/official/vision/detection/executor/__init__.py
deleted file mode 100644
index 931c2ef11db4a949e6c2e95bca44e36bac1241e9..0000000000000000000000000000000000000000
--- a/spaces/NCTCMumbai/NCTC/models/official/vision/detection/executor/__init__.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# Copyright 2019 The TensorFlow 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.
-# ==============================================================================
diff --git a/spaces/NKU-AMT/AMT/utils.py b/spaces/NKU-AMT/AMT/utils.py
deleted file mode 100644
index 6e6f440f18be737469cbf9147d57523474ebe73b..0000000000000000000000000000000000000000
--- a/spaces/NKU-AMT/AMT/utils.py
+++ /dev/null
@@ -1,247 +0,0 @@
-'''
-    This code is partially borrowed from IFRNet (https://github.com/ltkong218/IFRNet). 
-'''
-import re
-import sys
-import torch
-import random
-import numpy as np
-from PIL import ImageFile
-import torch.nn.functional as F
-from imageio import imread, imwrite
-ImageFile.LOAD_TRUNCATED_IMAGES = True
-
-class InputPadder:
-    """ Pads images such that dimensions are divisible by divisor """
-    def __init__(self, dims, divisor=16):
-        self.ht, self.wd = dims[-2:]
-        pad_ht = (((self.ht // divisor) + 1) * divisor - self.ht) % divisor
-        pad_wd = (((self.wd // divisor) + 1) * divisor - self.wd) % divisor
-        self._pad = [pad_wd//2, pad_wd - pad_wd//2, pad_ht//2, pad_ht - pad_ht//2]
-
-    def pad(self, *inputs):
-        if len(inputs) == 1:
-            return F.pad(inputs[0], self._pad, mode='replicate')
-        else:
-            return [F.pad(x, self._pad, mode='replicate') for x in inputs]
-
-    def unpad(self, *inputs):
-        if len(inputs) == 1:
-            return self._unpad(inputs[0])
-        else:
-            return [self._unpad(x) for x in inputs]
-    
-    def _unpad(self, x):
-        ht, wd = x.shape[-2:]
-        c = [self._pad[2], ht-self._pad[3], self._pad[0], wd-self._pad[1]]
-        return x[..., c[0]:c[1], c[2]:c[3]]
-
-def img2tensor(img):
-    return torch.tensor(img).permute(2, 0, 1).unsqueeze(0) / 255.0
-
-def tensor2img(img_t):
-    return (img_t * 255.).detach(
-                        ).squeeze(0).permute(1, 2, 0).cpu().numpy(
-                        ).clip(0, 255).astype(np.uint8)
-
-
-def read(file):
-    if file.endswith('.float3'): return readFloat(file)
-    elif file.endswith('.flo'): return readFlow(file)
-    elif file.endswith('.ppm'): return readImage(file)
-    elif file.endswith('.pgm'): return readImage(file)
-    elif file.endswith('.png'): return readImage(file)
-    elif file.endswith('.jpg'): return readImage(file)
-    elif file.endswith('.pfm'): return readPFM(file)[0]
-    else: raise Exception('don\'t know how to read %s' % file)
-
-def write(file, data):
-    if file.endswith('.float3'): return writeFloat(file, data)
-    elif file.endswith('.flo'): return writeFlow(file, data)
-    elif file.endswith('.ppm'): return writeImage(file, data)
-    elif file.endswith('.pgm'): return writeImage(file, data)
-    elif file.endswith('.png'): return writeImage(file, data)
-    elif file.endswith('.jpg'): return writeImage(file, data)
-    elif file.endswith('.pfm'): return writePFM(file, data)
-    else: raise Exception('don\'t know how to write %s' % file)
-
-def readPFM(file):
-    file = open(file, 'rb')
-
-    color = None
-    width = None
-    height = None
-    scale = None
-    endian = None
-
-    header = file.readline().rstrip()
-    if header.decode("ascii") == 'PF':
-        color = True
-    elif header.decode("ascii") == 'Pf':
-        color = False
-    else:
-        raise Exception('Not a PFM file.')
-
-    dim_match = re.match(r'^(\d+)\s(\d+)\s$', file.readline().decode("ascii"))
-    if dim_match:
-        width, height = list(map(int, dim_match.groups()))
-    else:
-        raise Exception('Malformed PFM header.')
-
-    scale = float(file.readline().decode("ascii").rstrip())
-    if scale < 0:
-        endian = '<'
-        scale = -scale
-    else:
-        endian = '>'
-
-    data = np.fromfile(file, endian + 'f')
-    shape = (height, width, 3) if color else (height, width)
-
-    data = np.reshape(data, shape)
-    data = np.flipud(data)
-    return data, scale
-
-def writePFM(file, image, scale=1):
-    file = open(file, 'wb')
-
-    color = None
-
-    if image.dtype.name != 'float32':
-        raise Exception('Image dtype must be float32.')
-
-    image = np.flipud(image)
-
-    if len(image.shape) == 3 and image.shape[2] == 3:
-        color = True
-    elif len(image.shape) == 2 or len(image.shape) == 3 and image.shape[2] == 1:
-        color = False
-    else:
-        raise Exception('Image must have H x W x 3, H x W x 1 or H x W dimensions.')
-
-    file.write('PF\n' if color else 'Pf\n'.encode())
-    file.write('%d %d\n'.encode() % (image.shape[1], image.shape[0]))
-
-    endian = image.dtype.byteorder
-
-    if endian == '<' or endian == '=' and sys.byteorder == 'little':
-        scale = -scale
-
-    file.write('%f\n'.encode() % scale)
-
-    image.tofile(file)
-
-def readFlow(name):
-    if name.endswith('.pfm') or name.endswith('.PFM'):
-        return readPFM(name)[0][:,:,0:2]
-
-    f = open(name, 'rb')
-
-    header = f.read(4)
-    if header.decode("utf-8") != 'PIEH':
-        raise Exception('Flow file header does not contain PIEH')
-
-    width = np.fromfile(f, np.int32, 1).squeeze()
-    height = np.fromfile(f, np.int32, 1).squeeze()
-
-    flow = np.fromfile(f, np.float32, width * height * 2).reshape((height, width, 2))
-
-    return flow.astype(np.float32)
-
-def readImage(name):
-    if name.endswith('.pfm') or name.endswith('.PFM'):
-        data = readPFM(name)[0]
-        if len(data.shape)==3:
-            return data[:,:,0:3]
-        else:
-            return data
-    return imread(name)
-
-def writeImage(name, data):
-    if name.endswith('.pfm') or name.endswith('.PFM'):
-        return writePFM(name, data, 1)
-    return imwrite(name, data)
-
-def writeFlow(name, flow):
-    f = open(name, 'wb')
-    f.write('PIEH'.encode('utf-8'))
-    np.array([flow.shape[1], flow.shape[0]], dtype=np.int32).tofile(f)
-    flow = flow.astype(np.float32)
-    flow.tofile(f)
-
-def readFloat(name):
-    f = open(name, 'rb')
-
-    if(f.readline().decode("utf-8"))  != 'float\n':
-        raise Exception('float file %s did not contain <float> keyword' % name)
-
-    dim = int(f.readline())
-
-    dims = []
-    count = 1
-    for i in range(0, dim):
-        d = int(f.readline())
-        dims.append(d)
-        count *= d
-
-    dims = list(reversed(dims))
-
-    data = np.fromfile(f, np.float32, count).reshape(dims)
-    if dim > 2:
-        data = np.transpose(data, (2, 1, 0))
-        data = np.transpose(data, (1, 0, 2))
-
-    return data
-
-def writeFloat(name, data):
-    f = open(name, 'wb')
-
-    dim=len(data.shape)
-    if dim>3:
-        raise Exception('bad float file dimension: %d' % dim)
-
-    f.write(('float\n').encode('ascii'))
-    f.write(('%d\n' % dim).encode('ascii'))
-
-    if dim == 1:
-        f.write(('%d\n' % data.shape[0]).encode('ascii'))
-    else:
-        f.write(('%d\n' % data.shape[1]).encode('ascii'))
-        f.write(('%d\n' % data.shape[0]).encode('ascii'))
-        for i in range(2, dim):
-            f.write(('%d\n' % data.shape[i]).encode('ascii'))
-
-    data = data.astype(np.float32)
-    if dim==2:
-        data.tofile(f)
-
-    else:
-        np.transpose(data, (2, 0, 1)).tofile(f)
-
-def warp(img, flow):
-    B, _, H, W = flow.shape
-    xx = torch.linspace(-1.0, 1.0, W).view(1, 1, 1, W).expand(B, -1, H, -1)
-    yy = torch.linspace(-1.0, 1.0, H).view(1, 1, H, 1).expand(B, -1, -1, W)
-    grid = torch.cat([xx, yy], 1).to(img)
-    flow_ = torch.cat([flow[:, 0:1, :, :] / ((W - 1.0) / 2.0), flow[:, 1:2, :, :] / ((H - 1.0) / 2.0)], 1)
-    grid_ = (grid + flow_).permute(0, 2, 3, 1)
-    output = F.grid_sample(input=img, grid=grid_, mode='bilinear', padding_mode='border', align_corners=True)
-    return output
-
-def check_dim_and_resize(tensor_list):
-    shape_list = []
-    for t in tensor_list:
-        shape_list.append(t.shape[2:])
-
-    if len(set(shape_list)) > 1:
-        desired_shape = shape_list[0]
-        print(f'Inconsistent size of input video frames. All frames will be resized to {desired_shape}')
-        
-        resize_tensor_list = []
-        for t in tensor_list:
-            resize_tensor_list.append(torch.nn.functional.interpolate(t, size=tuple(desired_shape), mode='bilinear'))
-
-        tensor_list = resize_tensor_list
-
-    return tensor_list
-
diff --git a/spaces/NMEX/rvc-hoyogame-v2/lib/infer_pack/attentions.py b/spaces/NMEX/rvc-hoyogame-v2/lib/infer_pack/attentions.py
deleted file mode 100644
index 05501be1871643f78dddbeaa529c96667031a8db..0000000000000000000000000000000000000000
--- a/spaces/NMEX/rvc-hoyogame-v2/lib/infer_pack/attentions.py
+++ /dev/null
@@ -1,417 +0,0 @@
-import copy
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from lib.infer_pack import commons
-from lib.infer_pack import modules
-from lib.infer_pack.modules import LayerNorm
-
-
-class Encoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        window_size=10,
-        **kwargs
-    ):
-        super().__init__()
-        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.window_size = window_size
-
-        self.drop = nn.Dropout(p_dropout)
-        self.attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    window_size=window_size,
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask):
-        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.attn_layers[i](x, x, attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        proximal_bias=False,
-        proximal_init=True,
-        **kwargs
-    ):
-        super().__init__()
-        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.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-
-        self.drop = nn.Dropout(p_dropout)
-        self.self_attn_layers = nn.ModuleList()
-        self.norm_layers_0 = nn.ModuleList()
-        self.encdec_attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.self_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    proximal_bias=proximal_bias,
-                    proximal_init=proximal_init,
-                )
-            )
-            self.norm_layers_0.append(LayerNorm(hidden_channels))
-            self.encdec_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                    causal=True,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask, h, h_mask):
-        """
-        x: decoder input
-        h: encoder output
-        """
-        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
-            device=x.device, dtype=x.dtype
-        )
-        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.self_attn_layers[i](x, x, self_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_0[i](x + y)
-
-            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class MultiHeadAttention(nn.Module):
-    def __init__(
-        self,
-        channels,
-        out_channels,
-        n_heads,
-        p_dropout=0.0,
-        window_size=None,
-        heads_share=True,
-        block_length=None,
-        proximal_bias=False,
-        proximal_init=False,
-    ):
-        super().__init__()
-        assert channels % n_heads == 0
-
-        self.channels = channels
-        self.out_channels = out_channels
-        self.n_heads = n_heads
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-        self.heads_share = heads_share
-        self.block_length = block_length
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-        self.attn = None
-
-        self.k_channels = channels // n_heads
-        self.conv_q = nn.Conv1d(channels, channels, 1)
-        self.conv_k = nn.Conv1d(channels, channels, 1)
-        self.conv_v = nn.Conv1d(channels, channels, 1)
-        self.conv_o = nn.Conv1d(channels, out_channels, 1)
-        self.drop = nn.Dropout(p_dropout)
-
-        if window_size is not None:
-            n_heads_rel = 1 if heads_share else n_heads
-            rel_stddev = self.k_channels**-0.5
-            self.emb_rel_k = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-            self.emb_rel_v = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-
-        nn.init.xavier_uniform_(self.conv_q.weight)
-        nn.init.xavier_uniform_(self.conv_k.weight)
-        nn.init.xavier_uniform_(self.conv_v.weight)
-        if proximal_init:
-            with torch.no_grad():
-                self.conv_k.weight.copy_(self.conv_q.weight)
-                self.conv_k.bias.copy_(self.conv_q.bias)
-
-    def forward(self, x, c, attn_mask=None):
-        q = self.conv_q(x)
-        k = self.conv_k(c)
-        v = self.conv_v(c)
-
-        x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-        x = self.conv_o(x)
-        return x
-
-    def attention(self, query, key, value, mask=None):
-        # reshape [b, d, t] -> [b, n_h, t, d_k]
-        b, d, t_s, t_t = (*key.size(), query.size(2))
-        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-        if self.window_size is not None:
-            assert (
-                t_s == t_t
-            ), "Relative attention is only available for self-attention."
-            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-            rel_logits = self._matmul_with_relative_keys(
-                query / math.sqrt(self.k_channels), key_relative_embeddings
-            )
-            scores_local = self._relative_position_to_absolute_position(rel_logits)
-            scores = scores + scores_local
-        if self.proximal_bias:
-            assert t_s == t_t, "Proximal bias is only available for self-attention."
-            scores = scores + self._attention_bias_proximal(t_s).to(
-                device=scores.device, dtype=scores.dtype
-            )
-        if mask is not None:
-            scores = scores.masked_fill(mask == 0, -1e4)
-            if self.block_length is not None:
-                assert (
-                    t_s == t_t
-                ), "Local attention is only available for self-attention."
-                block_mask = (
-                    torch.ones_like(scores)
-                    .triu(-self.block_length)
-                    .tril(self.block_length)
-                )
-                scores = scores.masked_fill(block_mask == 0, -1e4)
-        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
-        p_attn = self.drop(p_attn)
-        output = torch.matmul(p_attn, value)
-        if self.window_size is not None:
-            relative_weights = self._absolute_position_to_relative_position(p_attn)
-            value_relative_embeddings = self._get_relative_embeddings(
-                self.emb_rel_v, t_s
-            )
-            output = output + self._matmul_with_relative_values(
-                relative_weights, value_relative_embeddings
-            )
-        output = (
-            output.transpose(2, 3).contiguous().view(b, d, t_t)
-        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
-        return output, p_attn
-
-    def _matmul_with_relative_values(self, x, y):
-        """
-        x: [b, h, l, m]
-        y: [h or 1, m, d]
-        ret: [b, h, l, d]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0))
-        return ret
-
-    def _matmul_with_relative_keys(self, x, y):
-        """
-        x: [b, h, l, d]
-        y: [h or 1, m, d]
-        ret: [b, h, l, m]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-        return ret
-
-    def _get_relative_embeddings(self, relative_embeddings, length):
-        max_relative_position = 2 * self.window_size + 1
-        # Pad first before slice to avoid using cond ops.
-        pad_length = max(length - (self.window_size + 1), 0)
-        slice_start_position = max((self.window_size + 1) - length, 0)
-        slice_end_position = slice_start_position + 2 * length - 1
-        if pad_length > 0:
-            padded_relative_embeddings = F.pad(
-                relative_embeddings,
-                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
-            )
-        else:
-            padded_relative_embeddings = relative_embeddings
-        used_relative_embeddings = padded_relative_embeddings[
-            :, slice_start_position:slice_end_position
-        ]
-        return used_relative_embeddings
-
-    def _relative_position_to_absolute_position(self, x):
-        """
-        x: [b, h, l, 2*l-1]
-        ret: [b, h, l, l]
-        """
-        batch, heads, length, _ = x.size()
-        # Concat columns of pad to shift from relative to absolute indexing.
-        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
-
-        # Concat extra elements so to add up to shape (len+1, 2*len-1).
-        x_flat = x.view([batch, heads, length * 2 * length])
-        x_flat = F.pad(
-            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
-        )
-
-        # Reshape and slice out the padded elements.
-        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
-            :, :, :length, length - 1 :
-        ]
-        return x_final
-
-    def _absolute_position_to_relative_position(self, x):
-        """
-        x: [b, h, l, l]
-        ret: [b, h, l, 2*l-1]
-        """
-        batch, heads, length, _ = x.size()
-        # padd along column
-        x = F.pad(
-            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
-        )
-        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
-        # add 0's in the beginning that will skew the elements after reshape
-        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
-        return x_final
-
-    def _attention_bias_proximal(self, length):
-        """Bias for self-attention to encourage attention to close positions.
-        Args:
-          length: an integer scalar.
-        Returns:
-          a Tensor with shape [1, 1, length, length]
-        """
-        r = torch.arange(length, dtype=torch.float32)
-        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        filter_channels,
-        kernel_size,
-        p_dropout=0.0,
-        activation=None,
-        causal=False,
-    ):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.activation = activation
-        self.causal = causal
-
-        if causal:
-            self.padding = self._causal_padding
-        else:
-            self.padding = self._same_padding
-
-        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-        self.drop = nn.Dropout(p_dropout)
-
-    def forward(self, x, x_mask):
-        x = self.conv_1(self.padding(x * x_mask))
-        if self.activation == "gelu":
-            x = x * torch.sigmoid(1.702 * x)
-        else:
-            x = torch.relu(x)
-        x = self.drop(x)
-        x = self.conv_2(self.padding(x * x_mask))
-        return x * x_mask
-
-    def _causal_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = self.kernel_size - 1
-        pad_r = 0
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
-
-    def _same_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = (self.kernel_size - 1) // 2
-        pad_r = self.kernel_size // 2
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
diff --git a/spaces/NSect/VALL-E-X/modules/scaling.py b/spaces/NSect/VALL-E-X/modules/scaling.py
deleted file mode 100644
index 824a2077cedb787dd05bbad5ba6fe65099e11fcf..0000000000000000000000000000000000000000
--- a/spaces/NSect/VALL-E-X/modules/scaling.py
+++ /dev/null
@@ -1,1401 +0,0 @@
-# Copyright    2022  Xiaomi Corp.        (authors: Daniel Povey)
-#
-# 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 collections
-import logging
-import random
-import math
-from functools import reduce
-from itertools import repeat
-from typing import Optional, Tuple, Union
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from torch import Tensor
-from torch.nn import Embedding as ScaledEmbedding
-
-from utils import Transpose
-
-
-class ActivationBalancerFunction(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        x: Tensor,
-        scale_factor: Tensor,
-        sign_factor: Optional[Tensor],
-        channel_dim: int,
-    ) -> Tensor:
-        if channel_dim < 0:
-            channel_dim += x.ndim
-        ctx.channel_dim = channel_dim
-        xgt0 = x > 0
-        if sign_factor is None:
-            ctx.save_for_backward(xgt0, scale_factor)
-        else:
-            ctx.save_for_backward(xgt0, scale_factor, sign_factor)
-        return x
-
-    @staticmethod
-    def backward(ctx, x_grad: Tensor) -> Tuple[Tensor, None, None, None]:
-        if len(ctx.saved_tensors) == 3:
-            xgt0, scale_factor, sign_factor = ctx.saved_tensors
-            for _ in range(ctx.channel_dim, x_grad.ndim - 1):
-                scale_factor = scale_factor.unsqueeze(-1)
-                sign_factor = sign_factor.unsqueeze(-1)
-            factor = sign_factor + scale_factor * (xgt0.to(x_grad.dtype) - 0.5)
-        else:
-            xgt0, scale_factor = ctx.saved_tensors
-            for _ in range(ctx.channel_dim, x_grad.ndim - 1):
-                scale_factor = scale_factor.unsqueeze(-1)
-            factor = scale_factor * (xgt0.to(x_grad.dtype) - 0.5)
-        neg_delta_grad = x_grad.abs() * factor
-        return (
-            x_grad - neg_delta_grad,
-            None,
-            None,
-            None,
-        )
-
-
-def _compute_scale_factor(
-    x: Tensor,
-    channel_dim: int,
-    min_abs: float,
-    max_abs: float,
-    gain_factor: float,
-    max_factor: float,
-) -> Tensor:
-    if channel_dim < 0:
-        channel_dim += x.ndim
-    sum_dims = [d for d in range(x.ndim) if d != channel_dim]
-    x_abs_mean = torch.mean(x.abs(), dim=sum_dims).to(torch.float32)
-
-    if min_abs == 0.0:
-        below_threshold = 0.0
-    else:
-        # below_threshold is 0 if x_abs_mean > min_abs, can be at most max_factor if
-        # x_abs)_mean , min_abs.
-        below_threshold = (
-            (min_abs - x_abs_mean) * (gain_factor / min_abs)
-        ).clamp(min=0, max=max_factor)
-
-    above_threshold = ((x_abs_mean - max_abs) * (gain_factor / max_abs)).clamp(
-        min=0, max=max_factor
-    )
-
-    return below_threshold - above_threshold
-
-
-def _compute_sign_factor(
-    x: Tensor,
-    channel_dim: int,
-    min_positive: float,
-    max_positive: float,
-    gain_factor: float,
-    max_factor: float,
-) -> Tensor:
-    if channel_dim < 0:
-        channel_dim += x.ndim
-    sum_dims = [d for d in range(x.ndim) if d != channel_dim]
-    proportion_positive = torch.mean((x > 0).to(torch.float32), dim=sum_dims)
-    if min_positive == 0.0:
-        factor1 = 0.0
-    else:
-        # 0 if proportion_positive >= min_positive, else can be
-        # as large as max_factor.
-        factor1 = (
-            (min_positive - proportion_positive) * (gain_factor / min_positive)
-        ).clamp_(min=0, max=max_factor)
-
-    if max_positive == 1.0:
-        factor2 = 0.0
-    else:
-        # 0 if self.proportion_positive <= max_positive, else can be
-        # as large as -max_factor.
-        factor2 = (
-            (proportion_positive - max_positive)
-            * (gain_factor / (1.0 - max_positive))
-        ).clamp_(min=0, max=max_factor)
-    sign_factor = factor1 - factor2
-    # require min_positive != 0 or max_positive != 1:
-    assert not isinstance(sign_factor, float)
-    return sign_factor
-
-
-class ActivationScaleBalancerFunction(torch.autograd.Function):
-    """
-    This object is used in class ActivationBalancer when the user specified
-    min_positive=0, max_positive=1, so there are no constraints on the signs
-    of the activations and only the absolute value has a constraint.
-    """
-
-    @staticmethod
-    def forward(
-        ctx,
-        x: Tensor,
-        sign_factor: Tensor,
-        scale_factor: Tensor,
-        channel_dim: int,
-    ) -> Tensor:
-        if channel_dim < 0:
-            channel_dim += x.ndim
-        ctx.channel_dim = channel_dim
-        xgt0 = x > 0
-        ctx.save_for_backward(xgt0, sign_factor, scale_factor)
-        return x
-
-    @staticmethod
-    def backward(ctx, x_grad: Tensor) -> Tuple[Tensor, None, None, None]:
-        xgt0, sign_factor, scale_factor = ctx.saved_tensors
-        for _ in range(ctx.channel_dim, x_grad.ndim - 1):
-            sign_factor = sign_factor.unsqueeze(-1)
-            scale_factor = scale_factor.unsqueeze(-1)
-
-        factor = sign_factor + scale_factor * (xgt0.to(x_grad.dtype) - 0.5)
-        neg_delta_grad = x_grad.abs() * factor
-        return (
-            x_grad - neg_delta_grad,
-            None,
-            None,
-            None,
-        )
-
-
-class RandomClampFunction(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        x: Tensor,
-        min: Optional[float],
-        max: Optional[float],
-        prob: float,
-        reflect: float,
-    ) -> Tensor:
-        x_clamped = torch.clamp(x, min=min, max=max)
-        mask = torch.rand_like(x) < prob
-        ans = torch.where(mask, x_clamped, x)
-        if x.requires_grad:
-            ctx.save_for_backward(ans == x)
-            ctx.reflect = reflect
-        if reflect != 0.0:
-            ans = ans * (1.0 + reflect) - (x * reflect)
-        return ans
-
-    @staticmethod
-    def backward(
-        ctx, ans_grad: Tensor
-    ) -> Tuple[Tensor, None, None, None, None]:
-        (is_same,) = ctx.saved_tensors
-        x_grad = ans_grad * is_same.to(ans_grad.dtype)
-        reflect = ctx.reflect
-        if reflect != 0.0:
-            x_grad = x_grad * (1.0 + reflect) - (ans_grad * reflect)
-        return x_grad, None, None, None, None
-
-
-def random_clamp(
-    x: Tensor,
-    min: Optional[float] = None,
-    max: Optional[float] = None,
-    prob: float = 0.5,
-    reflect: float = 0.0,
-):
-    return RandomClampFunction.apply(x, min, max, prob, reflect)
-
-
-def random_cast_to_half(x: Tensor, min_abs: float = 5.0e-06) -> Tensor:
-    """
-    A randomized way of casting a floating point value to half precision.
-    """
-    if x.dtype == torch.float16:
-        return x
-    x_abs = x.abs()
-    is_too_small = x_abs < min_abs
-    # for elements where is_too_small is true, random_val will contain +-min_abs with
-    # probability (x.abs() / min_abs), and 0.0 otherwise.  [so this preserves expectations,
-    # for those elements].
-    random_val = min_abs * x.sign() * (torch.rand_like(x) * min_abs < x_abs)
-    return torch.where(is_too_small, random_val, x).to(torch.float16)
-
-
-class RandomGradFunction(torch.autograd.Function):
-    """
-    Does nothing in forward pass; in backward pass, gets rid of very small grads using
-    randomized approach that preserves expectations (intended to reduce roundoff).
-    """
-
-    @staticmethod
-    def forward(ctx, x: Tensor, min_abs: float) -> Tensor:
-        ctx.min_abs = min_abs
-        return x
-
-    @staticmethod
-    def backward(ctx, ans_grad: Tensor) -> Tuple[Tensor, None]:
-        if ans_grad.dtype == torch.float16:
-            return (
-                random_cast_to_half(
-                    ans_grad.to(torch.float32), min_abs=ctx.min_abs
-                ),
-                None,
-            )
-        else:
-            return ans_grad, None
-
-
-class RandomGrad(torch.nn.Module):
-    """
-    Gets rid of very small gradients using an expectation-preserving method, intended to increase
-    accuracy of training when using amp (automatic mixed precision)
-    """
-
-    def __init__(self, min_abs: float = 5.0e-06):
-        super(RandomGrad, self).__init__()
-        self.min_abs = min_abs
-
-    def forward(self, x: Tensor):
-        if (
-            torch.jit.is_scripting()
-            or not self.training
-            or torch.jit.is_tracing()
-        ):
-            return x
-        else:
-            return RandomGradFunction.apply(x, self.min_abs)
-
-
-class SoftmaxFunction(torch.autograd.Function):
-    """
-    Tries to handle half-precision derivatives in a randomized way that should
-    be more accurate for training than the default behavior.
-    """
-
-    @staticmethod
-    def forward(ctx, x: Tensor, dim: int):
-        ans = x.softmax(dim=dim)
-        # if x dtype is float16, x.softmax() returns a float32 because
-        # (presumably) that op does not support float16, and autocast
-        # is enabled.
-        if torch.is_autocast_enabled():
-            ans = ans.to(torch.float16)
-        ctx.save_for_backward(ans)
-        ctx.x_dtype = x.dtype
-        ctx.dim = dim
-        return ans
-
-    @staticmethod
-    def backward(ctx, ans_grad: Tensor):
-        (ans,) = ctx.saved_tensors
-        with torch.cuda.amp.autocast(enabled=False):
-            ans_grad = ans_grad.to(torch.float32)
-            ans = ans.to(torch.float32)
-            x_grad = ans_grad * ans
-            x_grad = x_grad - ans * x_grad.sum(dim=ctx.dim, keepdim=True)
-            return x_grad, None
-
-
-def softmax(x: Tensor, dim: int):
-    if torch.jit.is_scripting() or torch.jit.is_tracing():
-        return x.softmax(dim)
-
-    return SoftmaxFunction.apply(x, dim)
-
-
-class MaxEigLimiterFunction(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        x: Tensor,
-        coeffs: Tensor,
-        direction: Tensor,
-        channel_dim: int,
-        grad_scale: float,
-    ) -> Tensor:
-        ctx.channel_dim = channel_dim
-        ctx.grad_scale = grad_scale
-        ctx.save_for_backward(x.detach(), coeffs.detach(), direction.detach())
-        return x
-
-    @staticmethod
-    def backward(ctx, x_grad, *args):
-        with torch.enable_grad():
-            (x_orig, coeffs, new_direction) = ctx.saved_tensors
-            x_orig.requires_grad = True
-            num_channels = x_orig.shape[ctx.channel_dim]
-            x = x_orig.transpose(ctx.channel_dim, -1).reshape(-1, num_channels)
-            new_direction.requires_grad = False
-            x = x - x.mean(dim=0)
-            x_var = (x ** 2).mean()
-            x_residual = x - coeffs * new_direction
-            x_residual_var = (x_residual ** 2).mean()
-            # `variance_proportion` is the proportion of the variance accounted for
-            # by the top eigen-direction.  This is to be minimized.
-            variance_proportion = (x_var - x_residual_var) / (x_var + 1.0e-20)
-            variance_proportion.backward()
-        x_orig_grad = x_orig.grad
-        x_extra_grad = (
-            x_orig.grad
-            * ctx.grad_scale
-            * x_grad.norm()
-            / (x_orig_grad.norm() + 1.0e-20)
-        )
-        return x_grad + x_extra_grad.detach(), None, None, None, None
-
-
-class BasicNorm(torch.nn.Module):
-    """
-    This is intended to be a simpler, and hopefully cheaper, replacement for
-    LayerNorm.  The observation this is based on, is that Transformer-type
-    networks, especially with pre-norm, sometimes seem to set one of the
-    feature dimensions to a large constant value (e.g. 50), which "defeats"
-    the LayerNorm because the output magnitude is then not strongly dependent
-    on the other (useful) features.  Presumably the weight and bias of the
-    LayerNorm are required to allow it to do this.
-
-    So the idea is to introduce this large constant value as an explicit
-    parameter, that takes the role of the "eps" in LayerNorm, so the network
-    doesn't have to do this trick.  We make the "eps" learnable.
-
-    Args:
-       num_channels: the number of channels, e.g. 512.
-      channel_dim: the axis/dimension corresponding to the channel,
-        interprted as an offset from the input's ndim if negative.
-        shis is NOT the num_channels; it should typically be one of
-        {-2, -1, 0, 1, 2, 3}.
-       eps: the initial "epsilon" that we add as ballast in:
-             scale = ((input_vec**2).mean() + epsilon)**-0.5
-          Note: our epsilon is actually large, but we keep the name
-          to indicate the connection with conventional LayerNorm.
-       learn_eps: if true, we learn epsilon; if false, we keep it
-         at the initial value.
-    eps_min: float
-    eps_max: float
-    """
-
-    def __init__(
-        self,
-        num_channels: int,
-        channel_dim: int = -1,  # CAUTION: see documentation.
-        eps: float = 0.25,
-        learn_eps: bool = True,
-        eps_min: float = -3.0,
-        eps_max: float = 3.0,
-    ) -> None:
-        super(BasicNorm, self).__init__()
-        self.num_channels = num_channels
-        self.channel_dim = channel_dim
-        if learn_eps:
-            self.eps = nn.Parameter(torch.tensor(eps).log().detach())
-        else:
-            self.register_buffer("eps", torch.tensor(eps).log().detach())
-        self.eps_min = eps_min
-        self.eps_max = eps_max
-
-    def forward(self, x: Tensor) -> Tensor:
-        assert x.shape[self.channel_dim] == self.num_channels
-        eps = self.eps
-        if self.training and random.random() < 0.25:
-            # with probability 0.25, in training mode, clamp eps between the min
-            # and max; this will encourage it to learn parameters within the
-            # allowed range by making parameters that are outside the allowed
-            # range noisy.
-
-            # gradients to allow the parameter to get back into the allowed
-            # region if it happens to exit it.
-            eps = eps.clamp(min=self.eps_min, max=self.eps_max)
-        scales = (
-            torch.mean(x ** 2, dim=self.channel_dim, keepdim=True) + eps.exp()
-        ) ** -0.5
-        return x * scales
-
-
-def ScaledLinear(*args, initial_scale: float = 1.0, **kwargs) -> nn.Linear:
-    """
-    Behaves like a constructor of a modified version of nn.Linear
-    that gives an easy way to set the default initial parameter scale.
-
-    Args:
-        Accepts the standard args and kwargs that nn.Linear accepts
-        e.g. in_features, out_features, bias=False.
-
-        initial_scale: you can override this if you want to increase
-           or decrease the initial magnitude of the module's output
-           (affects the initialization of weight_scale and bias_scale).
-           Another option, if you want to do something like this, is
-           to re-initialize the parameters.
-    """
-    ans = nn.Linear(*args, **kwargs)
-    with torch.no_grad():
-        ans.weight[:] *= initial_scale
-        if ans.bias is not None:
-            torch.nn.init.uniform_(
-                ans.bias, -0.1 * initial_scale, 0.1 * initial_scale
-            )
-    return ans
-
-
-def ScaledConv1d(
-    *args,
-    initial_scale: float = 1.0,
-    kernel_size: int = 3,
-    padding: str = "same",
-    **kwargs,
-) -> nn.Conv1d:
-    """
-    Behaves like a constructor of a modified version of nn.Conv1d
-    that gives an easy way to set the default initial parameter scale.
-
-    Args:
-        Accepts the standard args and kwargs that nn.Linear accepts
-        e.g. in_features, out_features, bias=False.
-
-        initial_scale: you can override this if you want to increase
-           or decrease the initial magnitude of the module's output
-           (affects the initialization of weight_scale and bias_scale).
-           Another option, if you want to do something like this, is
-           to re-initialize the parameters.
-    """
-    ans = nn.Conv1d(*args, kernel_size=kernel_size, padding=padding, **kwargs)
-    with torch.no_grad():
-        ans.weight[:] *= initial_scale
-        if ans.bias is not None:
-            torch.nn.init.uniform_(
-                ans.bias, -0.1 * initial_scale, 0.1 * initial_scale
-            )
-    return ans
-
-
-def TransposeScaledConv1d(
-    *args,
-    initial_scale: float = 1.0,
-    kernel_size: int = 3,
-    padding: str = "same",
-    **kwargs,
-) -> nn.Sequential:
-    """
-    Transpose -> ScaledConv1d
-    """
-    return nn.Sequential(
-        Transpose(),
-        ScaledConv1d(
-            *args,
-            initial_scale=initial_scale,
-            kernel_size=kernel_size,
-            padding=padding,
-            **kwargs,
-        ),
-    )
-
-
-def ScaledConv1dTranspose(
-    *args,
-    initial_scale: float = 1.0,
-    kernel_size: int = 3,
-    padding: str = "same",
-    **kwargs,
-) -> nn.Sequential:
-    """
-    Transpose -> ScaledConv1d
-    """
-    return nn.Sequential(
-        ScaledConv1d(
-            *args,
-            initial_scale=initial_scale,
-            kernel_size=kernel_size,
-            padding=padding,
-            **kwargs,
-        ),
-        Transpose(),
-    )
-
-
-def TransposeConv1d(
-    *args, kernel_size: int = 3, padding: str = "same", **kwargs
-) -> nn.Sequential:
-    """
-    Transpose -> Conv1d
-    """
-    return nn.Sequential(
-        Transpose(),
-        nn.Conv1d(*args, kernel_size=kernel_size, padding=padding, **kwargs),
-    )
-
-
-def Conv1dTranspose(
-    *args, kernel_size: int = 3, padding: str = "same", **kwargs
-) -> nn.Sequential:
-    """
-    ScaledConv1d -> Transpose
-    """
-    return nn.Sequential(
-        nn.Conv1d(*args, kernel_size=kernel_size, padding=padding, **kwargs),
-        Transpose(),
-    )
-
-
-class SRLinear(nn.Linear):
-    """https://arxiv.org/abs/2303.06296
-    Stabilizing Transformer Training by Preventing Attention Entropy Collapse
-    """
-
-    def __init__(self, in_features, out_features, bias=True, **kwargs):
-        super().__init__(in_features, out_features, bias=bias, **kwargs)
-        self.register_buffer(
-            "u", nn.functional.normalize(torch.randn(in_features), dim=0)
-        )
-        with torch.no_grad():
-            sigma = self.get_sigma()
-        self.register_buffer("spectral_norm", sigma)
-        self.sigma = nn.Parameter(torch.ones(1))
-
-    def get_sigma(self):
-        with torch.no_grad():
-            u = self.u
-            v = self.weight.mv(u)
-            v = nn.functional.normalize(v, dim=0)
-            u = self.weight.T.mv(v)
-            u = nn.functional.normalize(u, dim=0)
-            self.u.data.copy_(u)
-        return torch.einsum("c,cd,d->", v, self.weight, u)
-
-    def get_weight(self):
-        sigma = self.get_sigma()
-        if self.training:
-            self.spectral_norm.data.copy_(sigma)
-        weight = (self.sigma / sigma) * self.weight
-        return weight
-
-    def forward(self, x):
-        return nn.functional.linear(x, self.get_weight(), self.bias)
-
-
-class SRConv1d(SRLinear):
-    def __init__(
-        self,
-        in_features,
-        out_features,
-        kernel_size,
-        stride: int = 1,
-        padding: str = "same",
-        bias: bool = True,
-        **kwargs,
-    ):
-        in_features = in_features * kernel_size
-        super().__init__(in_features, out_features, bias=bias, **kwargs)
-        nn.init.kaiming_uniform_(self.weight, a=math.sqrt(5))
-        self.kernel_size = kernel_size
-        self.stride = stride
-        self.padding = padding
-
-    def forward(self, x):
-        in_features = self.in_features // self.kernel_size
-        weight = self.get_weight().view(
-            self.out_features, in_features, self.kernel_size
-        )
-        return nn.functional.conv1d(
-            x, weight, bias=self.bias, stride=self.stride, padding=self.padding
-        )
-
-
-def TransposeSRConv1d(
-    *args, kernel_size: int = 3, padding: str = "same", **kwargs
-) -> nn.Sequential:
-    """
-    Transpose -> SRConv1d
-    """
-    return nn.Sequential(
-        Transpose(),
-        SRConv1d(*args, kernel_size=kernel_size, padding=padding, **kwargs),
-    )
-
-
-def SRConv1dTranspose(
-    *args, kernel_size: int = 3, padding: str = "same", **kwargs
-) -> nn.Sequential:
-    """
-    SRConv1d -> Transpose
-    """
-    return nn.Sequential(
-        SRConv1d(*args, kernel_size=kernel_size, padding=padding, **kwargs),
-        Transpose(),
-    )
-
-
-class ActivationBalancer(torch.nn.Module):
-    """
-    Modifies the backpropped derivatives of a function to try to encourage, for
-    each channel, that it is positive at least a proportion `threshold` of the
-    time.  It does this by multiplying negative derivative values by up to
-    (1+max_factor), and positive derivative values by up to (1-max_factor),
-    interpolated from 1 at the threshold to those extremal values when none
-    of the inputs are positive.
-
-    Args:
-           num_channels: the number of channels
-           channel_dim: the dimension/axis corresponding to the channel, e.g.
-               -1, 0, 1, 2; will be interpreted as an offset from x.ndim if negative.
-           min_positive: the minimum, per channel, of the proportion of the time
-               that (x > 0), below which we start to modify the derivatives.
-           max_positive: the maximum, per channel, of the proportion of the time
-               that (x > 0), above which we start to modify the derivatives.
-           max_factor: the maximum factor by which we modify the derivatives for
-              either the sign constraint or the magnitude constraint;
-              e.g. with max_factor=0.02, the the derivatives would be multiplied by
-              values in the range [0.98..1.02].
-           sign_gain_factor: determines the 'gain' with which we increase the
-              change in gradient once the constraints on min_positive and max_positive
-              are violated.
-           scale_gain_factor: determines the 'gain' with which we increase the
-              change in gradient once the constraints on min_abs and max_abs
-              are violated.
-           min_abs:  the minimum average-absolute-value difference from the mean
-               value per channel, which we allow, before we start to modify
-               the derivatives to prevent this.
-           max_abs:  the maximum average-absolute-value difference from the mean
-               value per channel, which we allow, before we start to modify
-               the derivatives to prevent this.
-          min_prob: determines the minimum probability with which we modify the
-             gradients for the {min,max}_positive and {min,max}_abs constraints,
-             on each forward().  This is done randomly to prevent all layers
-             from doing it at the same time.  Early in training we may use
-             higher probabilities than this; it will decay to this value.
-    """
-
-    def __init__(
-        self,
-        num_channels: int,
-        channel_dim: int,
-        min_positive: float = 0.05,
-        max_positive: float = 0.95,
-        max_factor: float = 0.04,
-        sign_gain_factor: float = 0.01,
-        scale_gain_factor: float = 0.02,
-        min_abs: float = 0.2,
-        max_abs: float = 100.0,
-        min_prob: float = 0.1,
-    ):
-        super(ActivationBalancer, self).__init__()
-        self.num_channels = num_channels
-        self.channel_dim = channel_dim
-        self.min_positive = min_positive
-        self.max_positive = max_positive
-        self.max_factor = max_factor
-        self.min_abs = min_abs
-        self.max_abs = max_abs
-        self.min_prob = min_prob
-        self.sign_gain_factor = sign_gain_factor
-        self.scale_gain_factor = scale_gain_factor
-
-        # count measures how many times the forward() function has been called.
-        # We occasionally sync this to a tensor called `count`, that exists to
-        # make sure it is synced to disk when we load and save the model.
-        self.cpu_count = 0
-        self.register_buffer("count", torch.tensor(0, dtype=torch.int64))
-
-    def forward(self, x: Tensor) -> Tensor:
-        if (
-            torch.jit.is_scripting()
-            or not x.requires_grad
-            or torch.jit.is_tracing()
-        ):
-            return _no_op(x)
-
-        count = self.cpu_count
-        self.cpu_count += 1
-
-        if random.random() < 0.01:
-            # Occasionally sync self.cpu_count with self.count.
-            # count affects the decay of 'prob'.  don't do this on every iter,
-            # because syncing with the GPU is slow.
-            self.cpu_count = max(self.cpu_count, self.count.item())
-            self.count.fill_(self.cpu_count)
-
-        # the prob of doing some work exponentially decreases from 0.5 till it hits
-        # a floor at min_prob (==0.1, by default)
-        prob = max(self.min_prob, 0.5 ** (1 + (count / 4000.0)))
-
-        if random.random() < prob:
-            sign_gain_factor = 0.5
-            if self.min_positive != 0.0 or self.max_positive != 1.0:
-                sign_factor = _compute_sign_factor(
-                    x,
-                    self.channel_dim,
-                    self.min_positive,
-                    self.max_positive,
-                    gain_factor=self.sign_gain_factor / prob,
-                    max_factor=self.max_factor,
-                )
-            else:
-                sign_factor = None
-
-            scale_factor = _compute_scale_factor(
-                x.detach(),
-                self.channel_dim,
-                min_abs=self.min_abs,
-                max_abs=self.max_abs,
-                gain_factor=self.scale_gain_factor / prob,
-                max_factor=self.max_factor,
-            )
-            return ActivationBalancerFunction.apply(
-                x,
-                scale_factor,
-                sign_factor,
-                self.channel_dim,
-            )
-        else:
-            return _no_op(x)
-
-
-def penalize_abs_values_gt(x: Tensor, limit: float, penalty: float) -> Tensor:
-    """
-    Returns x unmodified, but in backprop will put a penalty for the excess of
-    the absolute values of elements of x over the limit "limit".  E.g. if
-    limit == 10.0, then if x has any values over 10 it will get a penalty.
-
-    Caution: the value of this penalty will be affected by grad scaling used
-    in automatic mixed precision training.  For this reasons we use this,
-    it shouldn't really matter, or may even be helpful; we just use this
-    to disallow really implausible values of scores to be given to softmax.
-    """
-    x_sign = x.sign()
-    over_limit = (x.abs() - limit) > 0
-    # The following is a memory efficient way to penalize the absolute values of
-    # x that's over the limit.  (The memory efficiency comes when you think
-    # about which items torch needs to cache for the autograd, and which ones it
-    # can throw away).  The numerical value of aux_loss as computed here will
-    # actually be larger than it should be, by limit * over_limit.sum(), but it
-    # has the same derivative as the real aux_loss which is penalty * (x.abs() -
-    # limit).relu().
-    aux_loss = penalty * ((x_sign * over_limit).to(torch.int8) * x)
-    # note: we don't do sum() here on aux)_loss, but it's as if we had done
-    # sum() due to how with_loss() works.
-    x = with_loss(x, aux_loss)
-    # you must use x for something, or this will be ineffective.
-    return x
-
-
-def _diag(x: Tensor):  # like .diag(), but works for tensors with 3 dims.
-    if x.ndim == 2:
-        return x.diag()
-    else:
-        (batch, dim, dim) = x.shape
-        x = x.reshape(batch, dim * dim)
-        x = x[:, :: dim + 1]
-        assert x.shape == (batch, dim)
-        return x
-
-
-def _whitening_metric(x: Tensor, num_groups: int):
-    """
-    Computes the "whitening metric", a value which will be 1.0 if all the eigenvalues of
-    of the centered feature covariance are the same within each group's covariance matrix
-    and also between groups.
-    Args:
-        x: a Tensor of shape (*, num_channels)
-     num_groups:  the number of groups of channels, a number >=1 that divides num_channels
-    Returns:
-        Returns a scalar Tensor that will be 1.0 if the data is "perfectly white" and
-    greater than 1.0 otherwise.
-    """
-    assert x.dtype != torch.float16
-    x = x.reshape(-1, x.shape[-1])
-    (num_frames, num_channels) = x.shape
-    assert num_channels % num_groups == 0
-    channels_per_group = num_channels // num_groups
-    x = x.reshape(num_frames, num_groups, channels_per_group).transpose(0, 1)
-    # x now has shape (num_groups, num_frames, channels_per_group)
-    # subtract the mean so we use the centered, not uncentered, covariance.
-    # My experience has been that when we "mess with the gradients" like this,
-    # it's better not do anything that tries to move the mean around, because
-    # that can easily cause instability.
-    x = x - x.mean(dim=1, keepdim=True)
-    # x_covar: (num_groups, channels_per_group, channels_per_group)
-    x_covar = torch.matmul(x.transpose(1, 2), x)
-    x_covar_mean_diag = _diag(x_covar).mean()
-    # the following expression is what we'd get if we took the matrix product
-    # of each covariance and measured the mean of its trace, i.e.
-    # the same as _diag(torch.matmul(x_covar, x_covar)).mean().
-    x_covarsq_mean_diag = (x_covar ** 2).sum() / (
-        num_groups * channels_per_group
-    )
-    # this metric will be >= 1.0; the larger it is, the less 'white' the data was.
-    metric = x_covarsq_mean_diag / (x_covar_mean_diag ** 2 + 1.0e-20)
-    return metric
-
-
-class WhiteningPenaltyFunction(torch.autograd.Function):
-    @staticmethod
-    def forward(
-        ctx,
-        x: Tensor,
-        num_groups: int,
-        whitening_limit: float,
-        grad_scale: float,
-    ) -> Tensor:
-        ctx.save_for_backward(x)
-        ctx.num_groups = num_groups
-        ctx.whitening_limit = whitening_limit
-        ctx.grad_scale = grad_scale
-        return x
-
-    @staticmethod
-    def backward(ctx, x_grad: Tensor):
-        (x_orig,) = ctx.saved_tensors
-        with torch.enable_grad():
-            with torch.cuda.amp.autocast(enabled=False):
-                x_detached = x_orig.to(torch.float32).detach()
-                x_detached.requires_grad = True
-
-                metric = _whitening_metric(x_detached, ctx.num_groups)
-
-                if random.random() < 0.005 or __name__ == "__main__":
-                    logging.info(
-                        f"Whitening: num_groups={ctx.num_groups}, num_channels={x_orig.shape[-1]}, "
-                        f"metric={metric.item():.2f} vs. limit={ctx.whitening_limit}"
-                    )
-
-                (metric - ctx.whitening_limit).relu().backward()
-                penalty_grad = x_detached.grad
-                scale = ctx.grad_scale * (
-                    x_grad.to(torch.float32).norm()
-                    / (penalty_grad.norm() + 1.0e-20)
-                )
-                penalty_grad = penalty_grad * scale
-        return x_grad + penalty_grad.to(x_grad.dtype), None, None, None
-
-
-class Whiten(nn.Module):
-    def __init__(
-        self,
-        num_groups: int,
-        whitening_limit: float,
-        prob: Union[float, Tuple[float, float]],
-        grad_scale: float,
-    ):
-        """
-        Args:
-          num_groups: the number of groups to divide the channel dim into before
-            whitening.  We will attempt to make the feature covariance
-            within each group, after mean subtraction, as "white" as possible,
-            while having the same trace across all groups.
-         whitening_limit: a value greater than 1.0, that dictates how much
-           freedom we have to violate the constraints.  1.0 would mean perfectly
-           white, with exactly the same trace across groups; larger values
-           give more freedom.  E.g. 2.0.
-         prob: the probability with which we apply the gradient modification
-           (also affects the grad scale).  May be supplied as a float,
-           or as a pair (min_prob, max_prob)
-
-          grad_scale: determines the scale on the gradient term from this object,
-            relative to the rest of the gradient on the attention weights.
-            E.g. 0.02 (you may want to use smaller values than this if prob is large)
-        """
-        super(Whiten, self).__init__()
-        assert num_groups >= 1
-        assert whitening_limit >= 1
-        assert grad_scale >= 0
-        self.num_groups = num_groups
-        self.whitening_limit = whitening_limit
-        if isinstance(prob, float):
-            assert 0 < prob <= 1
-            self.prob = prob
-        else:
-            (self.min_prob, self.max_prob) = prob
-            assert 0 < self.min_prob < self.max_prob <= 1
-            self.prob = self.max_prob
-
-        self.grad_scale = grad_scale
-
-    def forward(self, x: Tensor) -> Tensor:
-        """
-        In the forward pass, this function just returns the input unmodified.
-        In the backward pass, it will modify the gradients to ensure that the
-        distribution in each group has close to (lambda times I) as the covariance
-        after mean subtraction, with the same lambda across groups.
-        For whitening_limit > 1, there will be more freedom to violate this
-        constraint.
-
-        Args:
-           x: the input of shape (*, num_channels)
-
-        Returns:
-            x, unmodified.   You should make sure
-        you use the returned value, or the graph will be freed
-        and nothing will happen in backprop.
-        """
-        if (
-            not x.requires_grad
-            or random.random() > self.prob
-            or self.grad_scale == 0
-        ):
-            return _no_op(x)
-        else:
-            if hasattr(self, "min_prob") and random.random() < 0.25:
-                # occasionally switch between min_prob and max_prob, based on whether
-                # we are above or below the threshold.
-                if (
-                    _whitening_metric(x.to(torch.float32), self.num_groups)
-                    > self.whitening_limit
-                ):
-                    # there would be a change to the grad.
-                    self.prob = self.max_prob
-                else:
-                    self.prob = self.min_prob
-
-            return WhiteningPenaltyFunction.apply(
-                x, self.num_groups, self.whitening_limit, self.grad_scale
-            )
-
-
-class WithLoss(torch.autograd.Function):
-    @staticmethod
-    def forward(ctx, x: Tensor, y: Tensor):
-        ctx.y_shape = y.shape
-        return x
-
-    @staticmethod
-    def backward(ctx, ans_grad: Tensor):
-        return ans_grad, torch.ones(
-            ctx.y_shape, dtype=ans_grad.dtype, device=ans_grad.device
-        )
-
-
-def with_loss(x, y):
-    if torch.jit.is_scripting() or torch.jit.is_tracing():
-        return x
-    # returns x but adds y.sum() to the loss function.
-    return WithLoss.apply(x, y)
-
-
-def _no_op(x: Tensor) -> Tensor:
-    if torch.jit.is_scripting() or torch.jit.is_tracing():
-        return x
-    else:
-        # a no-op function that will have a node in the autograd graph,
-        # to avoid certain bugs relating to backward hooks
-        return x.chunk(1, dim=-1)[0]
-
-
-class Identity(torch.nn.Module):
-    def __init__(self):
-        super(Identity, self).__init__()
-
-    def forward(self, x):
-        return _no_op(x)
-
-
-class MaxEig(torch.nn.Module):
-    """
-    Modifies the backpropped derivatives of a function to try to discourage
-    that any given direction in activation space accounts for more than
-    a specified proportion of the covariance (e.g. 0.2).
-
-
-    Args:
-           num_channels: the number of channels
-           channel_dim: the dimension/axis corresponding to the channel, e.g.
-               -1, 0, 1, 2; will be interpreted as an offset from x.ndim if negative.
-           max_var_per_eig:  the maximum proportion of the variance of the
-               features/channels, after mean subtraction, that can come from
-               any given eigenvalue.
-           min_prob: the minimum probability with which we apply this during any invocation
-               of forward(), assuming last time we applied the constraint it was
-               not active; supplied for speed.
-           scale: determines the scale with which we modify the gradients, relative
-               to the existing / unmodified gradients
-    """
-
-    def __init__(
-        self,
-        num_channels: int,
-        channel_dim: int,
-        max_var_per_eig: float = 0.2,
-        min_prob: float = 0.01,
-        scale: float = 0.01,
-    ):
-        super(MaxEig, self).__init__()
-        self.num_channels = num_channels
-        self.channel_dim = channel_dim
-        self.scale = scale
-        assert max_var_per_eig == 0.0 or max_var_per_eig > 1.0 / num_channels
-        self.max_var_per_eig = max_var_per_eig
-
-        # we figure out the dominant direction using the power method: starting with
-        # a random vector, keep multiplying by the covariance and renormalizing.
-        with torch.no_grad():
-            # arbitrary.. would use randn() but want to leave the rest of the model's
-            # random parameters unchanged for comparison
-            direction = torch.arange(num_channels).to(torch.float)
-            direction = direction / direction.norm()
-            self.register_buffer("max_eig_direction", direction)
-
-        self.min_prob = min_prob
-        # cur_prob is the current probability we'll use to apply the ActivationBalancer.
-        # We'll regress this towards prob, each tiem we try to apply it and it is not
-        # active.
-        self.cur_prob = 1.0
-
-    def forward(self, x: Tensor) -> Tensor:
-        if (
-            torch.jit.is_scripting()
-            or self.max_var_per_eig <= 0
-            or random.random() > self.cur_prob
-            or torch.jit.is_tracing()
-        ):
-            return _no_op(x)
-
-        with torch.cuda.amp.autocast(enabled=False):
-            eps = 1.0e-20
-            orig_x = x
-            x = x.to(torch.float32)
-            with torch.no_grad():
-                x = x.transpose(self.channel_dim, -1).reshape(
-                    -1, self.num_channels
-                )
-                x = x - x.mean(dim=0)
-                new_direction, coeffs = self._find_direction_coeffs(
-                    x, self.max_eig_direction
-                )
-                x_var = (x ** 2).mean()
-                x_residual = x - coeffs * new_direction
-                x_residual_var = (x_residual ** 2).mean()
-
-                # `variance_proportion` is the proportion of the variance accounted for
-                # by the top eigen-direction.
-                variance_proportion = (x_var - x_residual_var) / (
-                    x_var + 1.0e-20
-                )
-
-                # ensure new direction is nonzero even if x == 0, by including `direction`.
-                self._set_direction(
-                    0.1 * self.max_eig_direction + new_direction
-                )
-
-            if random.random() < 0.01 or __name__ == "__main__":
-                logging.info(
-                    f"variance_proportion = {variance_proportion.item()}, shape={tuple(orig_x.shape)}, cur_prob={self.cur_prob}"
-                )
-
-            if variance_proportion >= self.max_var_per_eig:
-                # The constraint is active.  Note, we should quite rarely
-                # reach here, only near the beginning of training if we are
-                # starting to diverge, should this constraint be active.
-                cur_prob = self.cur_prob
-                self.cur_prob = (
-                    1.0  # next time, do the update with probability 1.0.
-                )
-                return MaxEigLimiterFunction.apply(
-                    orig_x, coeffs, new_direction, self.channel_dim, self.scale
-                )
-            else:
-                # let self.cur_prob exponentially approach self.min_prob, as
-                # long as the constraint is inactive.
-                self.cur_prob = 0.75 * self.cur_prob + 0.25 * self.min_prob
-                return orig_x
-
-    def _set_direction(self, direction: Tensor):
-        """
-        Sets self.max_eig_direction to a normalized version of `direction`
-        """
-        direction = direction.detach()
-        direction = direction / direction.norm()
-        direction_sum = direction.sum().item()
-        if direction_sum - direction_sum == 0:  # no inf/nan
-            self.max_eig_direction[:] = direction
-        else:
-            logging.info(
-                f"Warning: sum of direction in MaxEig is {direction_sum}, "
-                "num_channels={self.num_channels}, channel_dim={self.channel_dim}"
-            )
-
-    def _find_direction_coeffs(
-        self, x: Tensor, prev_direction: Tensor
-    ) -> Tuple[Tensor, Tensor, Tensor]:
-        """
-            Figure out (an approximation to) the proportion of the variance of a set of
-            feature vectors that can be attributed to the top eigen-direction.
-            Args:
-             x: a Tensor of shape (num_frames, num_channels), with num_frames > 1.
-          prev_direction:  a Tensor of shape (num_channels,), that is our previous estimate
-                   of the top eigen-direction, or a random direction if this is the first
-                   iteration.  Does not have to be normalized, but should be nonzero.
-
-        Returns: (cur_direction, coeffs), where:
-             cur_direction: a Tensor of shape (num_channels,) that is the current
-                estimate of the top eigen-direction.
-             coeffs: a Tensor of shape (num_frames, 1) that minimizes, or
-                approximately minimizes, (x - coeffs * cur_direction).norm()
-        """
-        (num_frames, num_channels) = x.shape
-        assert num_channels > 1 and num_frames > 1
-        assert prev_direction.shape == (num_channels,)
-        # `coeffs` are the coefficients of `prev_direction` in x.
-        # actually represent the coeffs up to a constant positive factor.
-        coeffs = (x * prev_direction).sum(dim=1, keepdim=True) + 1.0e-10
-        cur_direction = (x * coeffs).sum(dim=0) / (
-            (coeffs ** 2).sum() + 1.0e-20
-        )
-        return cur_direction, coeffs
-
-
-class DoubleSwishFunction(torch.autograd.Function):
-    """
-      double_swish(x) = x * torch.sigmoid(x-1)
-    This is a definition, originally motivated by its close numerical
-    similarity to swish(swish(x)), where swish(x) =  x * sigmoid(x).
-
-    Memory-efficient derivative computation:
-     double_swish(x) = x * s, where s(x) = torch.sigmoid(x-1)
-     double_swish'(x) = d/dx double_swish(x) =  x * s'(x) + x' * s(x) = x * s'(x) + s(x).
-     Now, s'(x) = s(x) * (1-s(x)).
-     double_swish'(x) =  x * s'(x) + s(x).
-                      =  x * s(x) * (1-s(x)) + s(x).
-                     = double_swish(x) * (1-s(x)) + s(x)
-     ... so we just need to remember s(x) but not x itself.
-    """
-
-    @staticmethod
-    def forward(ctx, x: Tensor) -> Tensor:
-        requires_grad = x.requires_grad
-        x_dtype = x.dtype
-        if x.dtype == torch.float16:
-            x = x.to(torch.float32)
-
-        s = torch.sigmoid(x - 1.0)
-        y = x * s
-
-        if requires_grad:
-            deriv = y * (1 - s) + s
-            # notes on derivative of x * sigmoid(x - 1):
-            # https://www.wolframalpha.com/input?i=d%2Fdx+%28x+*+sigmoid%28x-1%29%29
-            # min \simeq -0.043638.  Take floor as -0.043637 so it's a lower bund
-            # max \simeq 1.1990.   Take ceil to be 1.2 so it's an upper bound.
-            # the combination of "+ torch.rand_like(deriv)" and casting to torch.uint8 (which
-            # floors), should be expectation-preserving.
-            floor = -0.043637
-            ceil = 1.2
-            d_scaled = (deriv - floor) * (
-                255.0 / (ceil - floor)
-            ) + torch.rand_like(deriv)
-            if __name__ == "__main__":
-                # for self-testing only.
-                assert d_scaled.min() >= 0.0
-                assert d_scaled.max() < 256.0
-            d_int = d_scaled.to(torch.uint8)
-            ctx.save_for_backward(d_int)
-        if x.dtype == torch.float16 or torch.is_autocast_enabled():
-            y = y.to(torch.float16)
-        return y
-
-    @staticmethod
-    def backward(ctx, y_grad: Tensor) -> Tensor:
-        (d,) = ctx.saved_tensors
-        # the same constants as used in forward pass.
-        floor = -0.043637
-        ceil = 1.2
-        d = d * ((ceil - floor) / 255.0) + floor
-        return y_grad * d
-
-
-class DoubleSwish(torch.nn.Module):
-    def forward(self, x: Tensor) -> Tensor:
-        """Return double-swish activation function which is an approximation to Swish(Swish(x)),
-        that we approximate closely with x * sigmoid(x-1).
-        """
-        if torch.jit.is_scripting() or torch.jit.is_tracing():
-            return x * torch.sigmoid(x - 1.0)
-        return DoubleSwishFunction.apply(x)
-
-
-def BalancedDoubleSwish(
-    d_model, channel_dim=-1, max_abs=10.0, min_prob=0.25
-) -> nn.Sequential:
-    """
-    ActivationBalancer -> DoubleSwish
-    """
-    balancer = ActivationBalancer(
-        d_model, channel_dim=channel_dim, max_abs=max_abs, min_prob=min_prob
-    )
-    return nn.Sequential(
-        balancer,
-        DoubleSwish(),
-    )
-
-
-def _test_max_eig():
-    for proportion in [0.1, 0.5, 10.0]:
-        logging.info(f"proportion = {proportion}")
-        x = torch.randn(100, 128)
-        direction = torch.randn(128)
-        coeffs = torch.randn(100, 1)
-        x += proportion * direction * coeffs
-
-        x.requires_grad = True
-
-        num_channels = 128
-        m = MaxEig(
-            num_channels, 1, 0.5, scale=0.1  # channel_dim  # max_var_per_eig
-        )  # grad_scale
-
-        for _ in range(4):
-            y = m(x)
-
-        y_grad = torch.randn_like(x)
-        y.backward(gradient=y_grad)
-
-        if proportion < 0.2:
-            assert torch.allclose(x.grad, y_grad, atol=1.0e-02)
-        elif proportion > 1.0:
-            assert not torch.allclose(x.grad, y_grad)
-
-
-def _test_whiten():
-    for proportion in [0.1, 0.5, 10.0]:
-        logging.info(f"_test_whiten(): proportion = {proportion}")
-        x = torch.randn(100, 128)
-        direction = torch.randn(128)
-        coeffs = torch.randn(100, 1)
-        x += proportion * direction * coeffs
-
-        x.requires_grad = True
-
-        num_channels = 128
-        m = Whiten(
-            1, 5.0, prob=1.0, grad_scale=0.1  # num_groups  # whitening_limit,
-        )  # grad_scale
-
-        for _ in range(4):
-            y = m(x)
-
-        y_grad = torch.randn_like(x)
-        y.backward(gradient=y_grad)
-
-        if proportion < 0.2:
-            assert torch.allclose(x.grad, y_grad)
-        elif proportion > 1.0:
-            assert not torch.allclose(x.grad, y_grad)
-
-
-def _test_activation_balancer_sign():
-    probs = torch.arange(0, 1, 0.01)
-    N = 1000
-    x = 1.0 * (
-        (2.0 * (torch.rand(probs.numel(), N) < probs.unsqueeze(-1))) - 1.0
-    )
-    x = x.detach()
-    x.requires_grad = True
-    m = ActivationBalancer(
-        probs.numel(),
-        channel_dim=0,
-        min_positive=0.05,
-        max_positive=0.95,
-        max_factor=0.2,
-        min_abs=0.0,
-    )
-
-    y_grad = torch.sign(torch.randn(probs.numel(), N))
-
-    y = m(x)
-    y.backward(gradient=y_grad)
-    print("_test_activation_balancer_sign: x = ", x)
-    print("_test_activation_balancer_sign: y grad = ", y_grad)
-    print("_test_activation_balancer_sign: x grad = ", x.grad)
-
-
-def _test_activation_balancer_magnitude():
-    magnitudes = torch.arange(0, 1, 0.01)
-    N = 1000
-    x = torch.sign(torch.randn(magnitudes.numel(), N)) * magnitudes.unsqueeze(
-        -1
-    )
-    x = x.detach()
-    x.requires_grad = True
-    m = ActivationBalancer(
-        magnitudes.numel(),
-        channel_dim=0,
-        min_positive=0.0,
-        max_positive=1.0,
-        max_factor=0.2,
-        min_abs=0.2,
-        max_abs=0.8,
-        min_prob=1.0,
-    )
-
-    y_grad = torch.sign(torch.randn(magnitudes.numel(), N))
-
-    y = m(x)
-    y.backward(gradient=y_grad)
-    print("_test_activation_balancer_magnitude: x = ", x)
-    print("_test_activation_balancer_magnitude: y grad = ", y_grad)
-    print("_test_activation_balancer_magnitude: x grad = ", x.grad)
-
-
-def _test_basic_norm():
-    num_channels = 128
-    m = BasicNorm(num_channels=num_channels, channel_dim=1)
-
-    x = torch.randn(500, num_channels)
-
-    y = m(x)
-
-    assert y.shape == x.shape
-    x_rms = (x ** 2).mean().sqrt()
-    y_rms = (y ** 2).mean().sqrt()
-    print("x rms = ", x_rms)
-    print("y rms = ", y_rms)
-    assert y_rms < x_rms
-    assert y_rms > 0.5 * x_rms
-
-
-def _test_double_swish_deriv():
-    x = torch.randn(10, 12, dtype=torch.double) * 3.0
-    x.requires_grad = True
-    m = DoubleSwish()
-
-    tol = (1.2 - (-0.043637)) / 255.0
-    torch.autograd.gradcheck(m, x, atol=tol)
-
-    # for self-test.
-    x = torch.randn(1000, 1000, dtype=torch.double) * 3.0
-    x.requires_grad = True
-    y = m(x)
-
-
-def _test_softmax():
-    a = torch.randn(2, 10, dtype=torch.float64)
-    b = a.clone()
-    a.requires_grad = True
-    b.requires_grad = True
-    a.softmax(dim=1)[:, 0].sum().backward()
-    print("a grad = ", a.grad)
-    softmax(b, dim=1)[:, 0].sum().backward()
-    print("b grad = ", b.grad)
-    assert torch.allclose(a.grad, b.grad)
-
-
-if __name__ == "__main__":
-    logging.getLogger().setLevel(logging.INFO)
-    torch.set_num_threads(1)
-    torch.set_num_interop_threads(1)
-    _test_softmax()
-    _test_whiten()
-    _test_max_eig()
-    _test_activation_balancer_sign()
-    _test_activation_balancer_magnitude()
-    _test_basic_norm()
-    _test_double_swish_deriv()
diff --git a/spaces/Nee001/bing0/src/components/chat-image.tsx b/spaces/Nee001/bing0/src/components/chat-image.tsx
deleted file mode 100644
index 05ecc9771eada27a0f2d160bb01cba170d37bb09..0000000000000000000000000000000000000000
--- a/spaces/Nee001/bing0/src/components/chat-image.tsx
+++ /dev/null
@@ -1,170 +0,0 @@
-import {
-  useEffect,
-  useState,
-  useCallback,
-  ChangeEvent,
-  ClipboardEvent,
-  MouseEventHandler,
-  FormEvent,
-  useRef
-} from "react"
-import Image from 'next/image'
-import PasteIcon from '@/assets/images/paste.svg'
-import UploadIcon from '@/assets/images/upload.svg'
-import CameraIcon from '@/assets/images/camera.svg'
-import { useBing } from '@/lib/hooks/use-bing'
-import { cn } from '@/lib/utils'
-
-interface ChatImageProps extends Pick<ReturnType<typeof useBing>, 'uploadImage'> {}
-
-const preventDefault: MouseEventHandler<HTMLDivElement> = (event) => {
-  event.nativeEvent.stopImmediatePropagation()
-}
-
-const toBase64 = (file: File): Promise<string> => new Promise((resolve, reject) => {
-  const reader = new FileReader()
-  reader.readAsDataURL(file)
-  reader.onload = () => resolve(reader.result as string)
-  reader.onerror = reject
-})
-
-export function ChatImage({ children, uploadImage }: React.PropsWithChildren<ChatImageProps>) {
-  const videoRef = useRef<HTMLVideoElement>(null)
-  const canvasRef = useRef<HTMLCanvasElement>(null)
-  const mediaStream = useRef<MediaStream>()
-  const [panel, setPanel] = useState('none')
-
-  const upload = useCallback((url: string) => {
-    if (url) {
-      uploadImage(url)
-    }
-    setPanel('none')
-  }, [panel])
-
-  const onUpload = useCallback(async (event: ChangeEvent<HTMLInputElement>) => {
-    const file = event.target.files?.[0]
-    if (file) {
-      const fileDataUrl = await toBase64(file)
-      if (fileDataUrl) {
-        upload(fileDataUrl)
-      }
-    }
-  }, [])
-
-  const onPaste = useCallback((event: ClipboardEvent<HTMLInputElement>) => {
-    const pasteUrl = event.clipboardData.getData('text') ?? ''
-    upload(pasteUrl)
-  }, [])
-
-  const onEnter = useCallback((event: FormEvent<HTMLFormElement>) => {
-    event.preventDefault()
-    event.stopPropagation()
-    // @ts-ignore
-    const inputUrl = event.target.elements.image.value
-    if (inputUrl) {
-      upload(inputUrl)
-    }
-  }, [])
-
-  const openVideo: MouseEventHandler<HTMLButtonElement> = async (event) => {
-    event.stopPropagation()
-    setPanel('camera-mode')
-  }
-
-  const onCapture = () => {
-    if (canvasRef.current && videoRef.current) {
-      const canvas = canvasRef.current
-      canvas.width = videoRef.current!.videoWidth
-      canvas.height = videoRef.current!.videoHeight
-      canvas.getContext('2d')?.drawImage(videoRef.current, 0, 0, canvas.width, canvas.height)
-      const cameraUrl = canvas.toDataURL('image/jpeg')
-      upload(cameraUrl)
-    }
-  }
-
-  useEffect(() => {
-    const handleBlur = () => {
-      if (panel !== 'none') {
-        setPanel('none')
-      }
-    }
-    document.addEventListener('click', handleBlur)
-    return () => {
-      document.removeEventListener('click', handleBlur)
-    }
-  }, [panel])
-
-  useEffect(() => {
-    if (panel === 'camera-mode') {
-      navigator.mediaDevices.getUserMedia({ video: true, audio: false })
-      .then(videoStream => {
-        mediaStream.current = videoStream
-        if (videoRef.current) {
-          videoRef.current.srcObject = videoStream
-        }
-      })
-    } else {
-      if (mediaStream.current) {
-        mediaStream.current.getTracks().forEach(function(track) {
-          track.stop()
-        })
-        mediaStream.current = undefined
-      }
-    }
-  }, [panel])
-
-  return (
-    <div className="visual-search-container">
-      <div onClick={() => panel === 'none' ? setPanel('normal') : setPanel('none')}>{children}</div>
-      <div className={cn('visual-search', panel)} onClick={preventDefault}>
-        <div className="normal-content">
-          <div className="header">
-            <h4>添加图像</h4>
-          </div>
-          <div className="paste">
-            <Image alt="paste" src={PasteIcon} width={24} />
-            <form onSubmitCapture={onEnter}>
-              <input
-                className="paste-input"
-                id="sb_imgpst"
-                type="text"
-                name="image"
-                placeholder="粘贴图像 URL"
-                aria-label="粘贴图像 URL"
-                onPaste={onPaste}
-                onClickCapture={(e) => e.stopPropagation()}
-              />
-            </form>
-          </div>
-          <div className="buttons">
-            <button type="button" aria-label="从此设备上传">
-              <input
-                id="vs_fileinput"
-                className="fileinput"
-                type="file"
-                accept="image/gif, image/jpeg, image/png, image/webp"
-                onChange={onUpload}
-              />
-              <Image alt="uplaod" src={UploadIcon} width={20} />
-              从此设备上传
-            </button>
-            <button type="button" aria-label="拍照" onClick={openVideo}>
-              <Image alt="camera" src={CameraIcon} width={20} />
-              拍照
-            </button>
-          </div>
-        </div>
-        {panel === 'camera-mode' && <div className="cam-content">
-          <div className="webvideo-container">
-            <video className="webvideo" autoPlay muted playsInline ref={videoRef} />
-            <canvas className="webcanvas" ref={canvasRef} />
-          </div>
-          <div className="cambtn" role="button" aria-label="拍照" onClick={onCapture}>
-            <div className="cam-btn-circle-large"></div>
-            <div className="cam-btn-circle-small"></div>
-          </div>
-        </div>}
-      </div>
-    </div>
-  )
-}
diff --git a/spaces/Nixtla/chatgpt-forecast/app.py b/spaces/Nixtla/chatgpt-forecast/app.py
deleted file mode 100644
index 3a27ebdd3f4a00c059ae31d334f6d277cd9f1845..0000000000000000000000000000000000000000
--- a/spaces/Nixtla/chatgpt-forecast/app.py
+++ /dev/null
@@ -1,115 +0,0 @@
-import pandas as pd
-import streamlit as st
-
-from src.utils import ChatGPTForecast
-
-
-DATASETS = {
-    "Demand (AirPassengers)": "https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/air_passengers.csv",
-    #"Electriciy (ERCOT, multiple markets)": "https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/ercot_multiple_ts.csv",
-    "Web Traffic (Peyton Manning)": "https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/peyton_manning.csv",
-    "Finance (Exchange USD-EUR)": "https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/usdeur.csv",
-    "Electricity (Ercot COAST)": "https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/ercot_COAST.csv",
-}
-gpt_forecast = ChatGPTForecast()
-
-
-def st_chatgpt_forecast():
-    st.set_page_config(
-        page_title="ChatGPT Forecast",
-        page_icon="🔮",
-        layout="wide",
-        initial_sidebar_state="expanded",
-    )
-
-    st.title(
-        "ChatGPT Forecast: Revolutionizing Time Series by Nixtla"
-    )
-    st.write(
-        "<style>div.block-container{padding-top:2rem;}</style>", unsafe_allow_html=True
-    )
-
-    intro = """
-        This application is designed to analyze time series forecasting tasks by leveraging the power of OpenAI's ChatGPT. 
-
-        Here's how it works:
-
-        1. **Upload Your Data**: You can upload your own time series data which will be used to generate forecasts.
-
-        2. **Forecast with GPT**: Our application utilizes the advanced language model, ChatGPT, to generate time series forecasts. ChatGPT has been trained on a diverse range of internet text, but it also has the unique ability to generate numerical sequences, making it a fascinating tool for time series forecasting.
-
-        3. **Compare with Naive Forecast**: We provide a simple naive forecast as a benchmark for comparison. This forecast is based on the simple assumption that future values will be the same as the most recent observed value. 
-
-        By comparing the GPT-based forecast against the naive model, you can gain insights into the capabilities and potential advantages of using advanced AI models for time series prediction. 
-
-        Please note that this application is meant for experimental purposes and the forecasts generated by the AI should not be used for making real-world decisions without proper consideration and additional checks. 
-	"""
-    st.write(intro)
-
-    required_cols = ["ds", "y"]
-
-    with st.sidebar.expander("Dataset", expanded=True):
-        data_selection = st.selectbox("Select example dataset", DATASETS.keys())
-        data_url = DATASETS[data_selection]
-        url_json = st.text_input("Data (you can pass your own url here)", data_url)
-        st.write(
-            "You can also upload a CSV file like [this one](https://github.com/Nixtla/transfer-learning-time-series/blob/main/datasets/air_passengers.csv)."
-        )
-
-        uploaded_file = st.file_uploader("Upload CSV")
-        with st.form("Data"):
-
-            if uploaded_file is not None:
-                df = pd.read_csv(uploaded_file)
-                cols = df.columns
-                timestamp_col = st.selectbox("Timestamp column", options=cols)
-                value_col = st.selectbox("Value column", options=cols)
-            else:
-                timestamp_col = st.text_input("Timestamp column", value="timestamp")
-                value_col = st.text_input("Value column", value="value")
-            st.write("You must press Submit each time you want to forecast.")
-            submitted = st.form_submit_button("Submit")
-            if submitted:
-                if uploaded_file is None:
-                    st.write("Please provide a dataframe.")
-                    if url_json.endswith("json"):
-                        df = pd.read_json(url_json)
-                    else:
-                        df = pd.read_csv(url_json)
-                    df = df.rename(
-                        columns=dict(zip([timestamp_col, value_col], required_cols))
-                    )
-                else:
-                    # df = pd.read_csv(uploaded_file)
-                    df = df.rename(
-                        columns=dict(zip([timestamp_col, value_col], required_cols))
-                    )
-            else:
-                if url_json.endswith("json"):
-                    df = pd.read_json(url_json)
-                else:
-                    df = pd.read_csv(url_json)
-                cols = df.columns
-                if "unique_id" in cols:
-                    cols = cols[-2:]
-                df = df.rename(columns=dict(zip(cols, required_cols)))
-
-            if "unique_id" not in df:
-                df.insert(0, "unique_id", "ts_0")
-
-            df["ds"] = pd.to_datetime(df["ds"])
-            df = df.sort_values(["unique_id", "ds"])
-    with st.sidebar:
-        horizon = st.number_input("Forecasting horizon to predict:", value=24)
-        input_size = st.number_input("Number of values to make inference:", value=12)
-    
-    st.header("Forecasts generated by ChatGPT against a Naive model")
-    fig = gpt_forecast.forecast(df, horizon, input_size)
-    fig.update_layout(height=400)  
-    st.plotly_chart(
-        fig,
-        use_container_width=True,
-    )
-
-if __name__ == "__main__":
-    st_chatgpt_forecast()
diff --git a/spaces/Nixtla/transfer-learning-time-series/README.md b/spaces/Nixtla/transfer-learning-time-series/README.md
deleted file mode 100644
index 3fe62bdfc40c098e9b2e61fea7b2ddec9c65077f..0000000000000000000000000000000000000000
--- a/spaces/Nixtla/transfer-learning-time-series/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Transfer Learning Time Series
-emoji: 🐠
-colorFrom: indigo
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.21.0
-app_file: app.py
-pinned: false
-license: bsd-3-clause
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Nunchakuka/FrenchAnonymizer/speaker_encoder/compute_embed.py b/spaces/Nunchakuka/FrenchAnonymizer/speaker_encoder/compute_embed.py
deleted file mode 100644
index 2fee33db0168f40efc42145c06fa62016e3e008e..0000000000000000000000000000000000000000
--- a/spaces/Nunchakuka/FrenchAnonymizer/speaker_encoder/compute_embed.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from speaker_encoder import inference as encoder
-from multiprocessing.pool import Pool
-from functools import partial
-from pathlib import Path
-# from utils import logmmse
-# from tqdm import tqdm
-# import numpy as np
-# import librosa
-
-
-def embed_utterance(fpaths, encoder_model_fpath):
-    if not encoder.is_loaded():
-        encoder.load_model(encoder_model_fpath)
-
-    # Compute the speaker embedding of the utterance
-    wav_fpath, embed_fpath = fpaths
-    wav = np.load(wav_fpath)
-    wav = encoder.preprocess_wav(wav)
-    embed = encoder.embed_utterance(wav)
-    np.save(embed_fpath, embed, allow_pickle=False)
-    
- 
-def create_embeddings(outdir_root: Path, wav_dir: Path, encoder_model_fpath: Path, n_processes: int):
-
-    wav_dir = outdir_root.joinpath("audio")
-    metadata_fpath = synthesizer_root.joinpath("train.txt")
-    assert wav_dir.exists() and metadata_fpath.exists()
-    embed_dir = synthesizer_root.joinpath("embeds")
-    embed_dir.mkdir(exist_ok=True)
-    
-    # Gather the input wave filepath and the target output embed filepath
-    with metadata_fpath.open("r") as metadata_file:
-        metadata = [line.split("|") for line in metadata_file]
-        fpaths = [(wav_dir.joinpath(m[0]), embed_dir.joinpath(m[2])) for m in metadata]
-        
-    # TODO: improve on the multiprocessing, it's terrible. Disk I/O is the bottleneck here.
-    # Embed the utterances in separate threads
-    func = partial(embed_utterance, encoder_model_fpath=encoder_model_fpath)
-    job = Pool(n_processes).imap(func, fpaths)
-    list(tqdm(job, "Embedding", len(fpaths), unit="utterances"))
\ No newline at end of file
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_recognition/kaldi/kaldi_decoder.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_recognition/kaldi/kaldi_decoder.py
deleted file mode 100644
index 5f62cc58ae8c0c5a3ba7d17713fedf0abc302942..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_recognition/kaldi/kaldi_decoder.py
+++ /dev/null
@@ -1,244 +0,0 @@
-#!/usr/bin/env python3
-
-# 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 concurrent.futures import ThreadPoolExecutor
-import logging
-from omegaconf import MISSING
-import os
-import torch
-from typing import Optional
-import warnings
-
-
-from dataclasses import dataclass
-from fairseq.dataclass import FairseqDataclass
-from .kaldi_initializer import KaldiInitializerConfig, initalize_kaldi
-
-
-logger = logging.getLogger(__name__)
-
-
-@dataclass
-class KaldiDecoderConfig(FairseqDataclass):
-    hlg_graph_path: Optional[str] = None
-    output_dict: str = MISSING
-
-    kaldi_initializer_config: Optional[KaldiInitializerConfig] = None
-
-    acoustic_scale: float = 0.5
-    max_active: int = 10000
-    beam_delta: float = 0.5
-    hash_ratio: float = 2.0
-
-    is_lattice: bool = False
-    lattice_beam: float = 10.0
-    prune_interval: int = 25
-    determinize_lattice: bool = True
-    prune_scale: float = 0.1
-    max_mem: int = 0
-    phone_determinize: bool = True
-    word_determinize: bool = True
-    minimize: bool = True
-
-    num_threads: int = 1
-
-
-class KaldiDecoder(object):
-    def __init__(
-        self,
-        cfg: KaldiDecoderConfig,
-        beam: int,
-        nbest: int = 1,
-    ):
-        try:
-            from kaldi.asr import FasterRecognizer, LatticeFasterRecognizer
-            from kaldi.base import set_verbose_level
-            from kaldi.decoder import (
-                FasterDecoder,
-                FasterDecoderOptions,
-                LatticeFasterDecoder,
-                LatticeFasterDecoderOptions,
-            )
-            from kaldi.lat.functions import DeterminizeLatticePhonePrunedOptions
-            from kaldi.fstext import read_fst_kaldi, SymbolTable
-        except:
-            warnings.warn(
-                "pykaldi is required for this functionality. Please install from https://github.com/pykaldi/pykaldi"
-            )
-
-        # set_verbose_level(2)
-
-        self.acoustic_scale = cfg.acoustic_scale
-        self.nbest = nbest
-
-        if cfg.hlg_graph_path is None:
-            assert (
-                cfg.kaldi_initializer_config is not None
-            ), "Must provide hlg graph path or kaldi initializer config"
-            cfg.hlg_graph_path = initalize_kaldi(cfg.kaldi_initializer_config)
-
-        assert os.path.exists(cfg.hlg_graph_path), cfg.hlg_graph_path
-
-        if cfg.is_lattice:
-            self.dec_cls = LatticeFasterDecoder
-            opt_cls = LatticeFasterDecoderOptions
-            self.rec_cls = LatticeFasterRecognizer
-        else:
-            assert self.nbest == 1, "nbest > 1 requires lattice decoder"
-            self.dec_cls = FasterDecoder
-            opt_cls = FasterDecoderOptions
-            self.rec_cls = FasterRecognizer
-
-        self.decoder_options = opt_cls()
-        self.decoder_options.beam = beam
-        self.decoder_options.max_active = cfg.max_active
-        self.decoder_options.beam_delta = cfg.beam_delta
-        self.decoder_options.hash_ratio = cfg.hash_ratio
-
-        if cfg.is_lattice:
-            self.decoder_options.lattice_beam = cfg.lattice_beam
-            self.decoder_options.prune_interval = cfg.prune_interval
-            self.decoder_options.determinize_lattice = cfg.determinize_lattice
-            self.decoder_options.prune_scale = cfg.prune_scale
-            det_opts = DeterminizeLatticePhonePrunedOptions()
-            det_opts.max_mem = cfg.max_mem
-            det_opts.phone_determinize = cfg.phone_determinize
-            det_opts.word_determinize = cfg.word_determinize
-            det_opts.minimize = cfg.minimize
-            self.decoder_options.det_opts = det_opts
-
-        self.output_symbols = {}
-        with open(cfg.output_dict, "r") as f:
-            for line in f:
-                items = line.rstrip().split()
-                assert len(items) == 2
-                self.output_symbols[int(items[1])] = items[0]
-
-        logger.info(f"Loading FST from {cfg.hlg_graph_path}")
-        self.fst = read_fst_kaldi(cfg.hlg_graph_path)
-        self.symbol_table = SymbolTable.read_text(cfg.output_dict)
-
-        self.executor = ThreadPoolExecutor(max_workers=cfg.num_threads)
-
-    def generate(self, models, sample, **unused):
-        """Generate a batch of inferences."""
-        # model.forward normally channels prev_output_tokens into the decoder
-        # separately, but SequenceGenerator directly calls model.encoder
-        encoder_input = {
-            k: v for k, v in sample["net_input"].items() if k != "prev_output_tokens"
-        }
-        emissions, padding = self.get_emissions(models, encoder_input)
-        return self.decode(emissions, padding)
-
-    def get_emissions(self, models, encoder_input):
-        """Run encoder and normalize emissions"""
-        model = models[0]
-
-        all_encoder_out = [m(**encoder_input) for m in models]
-
-        if len(all_encoder_out) > 1:
-
-            if "encoder_out" in all_encoder_out[0]:
-                encoder_out = {
-                    "encoder_out": sum(e["encoder_out"] for e in all_encoder_out)
-                    / len(all_encoder_out),
-                    "encoder_padding_mask": all_encoder_out[0]["encoder_padding_mask"],
-                }
-                padding = encoder_out["encoder_padding_mask"]
-            else:
-                encoder_out = {
-                    "logits": sum(e["logits"] for e in all_encoder_out)
-                    / len(all_encoder_out),
-                    "padding_mask": all_encoder_out[0]["padding_mask"],
-                }
-                padding = encoder_out["padding_mask"]
-        else:
-            encoder_out = all_encoder_out[0]
-            padding = (
-                encoder_out["padding_mask"]
-                if "padding_mask" in encoder_out
-                else encoder_out["encoder_padding_mask"]
-            )
-
-        if hasattr(model, "get_logits"):
-            emissions = model.get_logits(encoder_out, normalize=True)
-        else:
-            emissions = model.get_normalized_probs(encoder_out, log_probs=True)
-
-        return (
-            emissions.cpu().float().transpose(0, 1),
-            padding.cpu() if padding is not None and padding.any() else None,
-        )
-
-    def decode_one(self, logits, padding):
-        from kaldi.matrix import Matrix
-
-        decoder = self.dec_cls(self.fst, self.decoder_options)
-        asr = self.rec_cls(
-            decoder, self.symbol_table, acoustic_scale=self.acoustic_scale
-        )
-
-        if padding is not None:
-            logits = logits[~padding]
-
-        mat = Matrix(logits.numpy())
-
-        out = asr.decode(mat)
-
-        if self.nbest > 1:
-            from kaldi.fstext import shortestpath
-            from kaldi.fstext.utils import (
-                convert_compact_lattice_to_lattice,
-                convert_lattice_to_std,
-                convert_nbest_to_list,
-                get_linear_symbol_sequence,
-            )
-
-            lat = out["lattice"]
-
-            sp = shortestpath(lat, nshortest=self.nbest)
-
-            sp = convert_compact_lattice_to_lattice(sp)
-            sp = convert_lattice_to_std(sp)
-            seq = convert_nbest_to_list(sp)
-
-            results = []
-            for s in seq:
-                _, o, w = get_linear_symbol_sequence(s)
-                words = list(self.output_symbols[z] for z in o)
-                results.append(
-                    {
-                        "tokens": words,
-                        "words": words,
-                        "score": w.value,
-                        "emissions": logits,
-                    }
-                )
-            return results
-        else:
-            words = out["text"].split()
-            return [
-                {
-                    "tokens": words,
-                    "words": words,
-                    "score": out["likelihood"],
-                    "emissions": logits,
-                }
-            ]
-
-    def decode(self, emissions, padding):
-        if padding is None:
-            padding = [None] * len(emissions)
-
-        ret = list(
-            map(
-                lambda e, p: self.executor.submit(self.decode_one, e, p),
-                emissions,
-                padding,
-            )
-        )
-        return ret
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/symbols.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/symbols.py
deleted file mode 100644
index 5f0d70fdad92ba4f554d971710b60f2f9e8d9298..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/symbols.py
+++ /dev/null
@@ -1,18 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-
-'''
-Defines the set of symbols used in text input to the model.
-
-The default is a set of ASCII characters that works well for English or text that has been run through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details. '''
-from . import cmudict
-
-_pad        = '_'
-_punctuation = '!\'(),.:;? '
-_special = '-'
-_letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
-
-# Prepend "@" to ARPAbet symbols to ensure uniqueness (some are the same as uppercase letters):
-_arpabet = ['@' + s for s in cmudict.valid_symbols]
-
-# Export all symbols:
-symbols = [_pad] + list(_special) + list(_punctuation) + list(_letters) + _arpabet
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/replace_dataset.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/replace_dataset.py
deleted file mode 100644
index 5aac2ba96bee0a8bb65f4c9e56fa0b17248ee1d9..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/replace_dataset.py
+++ /dev/null
@@ -1,36 +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 . import BaseWrapperDataset
-
-
-class ReplaceDataset(BaseWrapperDataset):
-    """Replaces tokens found in the dataset by a specified replacement token
-
-    Args:
-        dataset (~torch.utils.data.Dataset): dataset to replace tokens in
-        replace_map(Dictionary[int,int]): map of token to replace -> replacement token
-        offsets (List[int]): do not replace tokens before (from left if pos, right if neg) this offset. should be
-        as many as the number of objects returned by the underlying dataset __getitem__ method.
-    """
-
-    def __init__(self, dataset, replace_map, offsets):
-        super().__init__(dataset)
-        assert len(replace_map) > 0
-        self.replace_map = replace_map
-        self.offsets = offsets
-
-    def __getitem__(self, index):
-        item = self.dataset[index]
-        is_tuple = isinstance(item, tuple)
-        srcs = item if is_tuple else [item]
-
-        for offset, src in zip(self.offsets, srcs):
-            for k, v in self.replace_map.items():
-                src_off = src[offset:] if offset >= 0 else src[:offset]
-                src_off.masked_fill_(src_off == k, v)
-
-        item = srcs if is_tuple else srcs[0]
-        return item
diff --git a/spaces/OFA-Sys/OFA-Visual_Grounding/fairseq/examples/byte_level_bpe/gru_transformer.py b/spaces/OFA-Sys/OFA-Visual_Grounding/fairseq/examples/byte_level_bpe/gru_transformer.py
deleted file mode 100644
index d4efa93a4d75da71c78e786d7f62101ef3266af4..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Visual_Grounding/fairseq/examples/byte_level_bpe/gru_transformer.py
+++ /dev/null
@@ -1,107 +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.
-
-# 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
-import torch.nn.functional as F
-from fairseq.models import register_model, register_model_architecture
-from fairseq.models.transformer import TransformerEncoder, TransformerModel
-
-
-@register_model("gru_transformer")
-class GRUTransformerModel(TransformerModel):
-    @classmethod
-    def build_encoder(cls, args, src_dict, embed_tokens):
-        return GRUTransformerEncoder(args, src_dict, embed_tokens)
-
-
-class GRUTransformerEncoder(TransformerEncoder):
-    def __init__(self, args, dictionary, embed_tokens):
-        super().__init__(args, dictionary, embed_tokens)
-        self.emb_ctx = nn.GRU(
-            input_size=embed_tokens.embedding_dim,
-            hidden_size=embed_tokens.embedding_dim // 2,
-            num_layers=1,
-            bidirectional=True,
-        )
-
-    def forward_embedding(self, src_tokens):
-        # embed tokens and positions
-        x = embed = self.embed_scale * self.embed_tokens(src_tokens)
-        if self.embed_positions is not None:
-            x = embed + self.embed_positions(src_tokens)
-
-        # contextualize embeddings
-        x = x.transpose(0, 1)
-        x = self.dropout_module(x)
-        x, _ = self.emb_ctx.forward(x)
-        x = x.transpose(0, 1)
-
-        if self.layernorm_embedding is not None:
-            x = self.layernorm_embedding(x)
-        x = self.dropout_module(x)
-        return x, embed
-
-
-@register_model_architecture("gru_transformer", "gru_transformer")
-def gru_transformer_base_architecture(args):
-    args.encoder_embed_path = getattr(args, "encoder_embed_path", None)
-    args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 512)
-    args.encoder_ffn_embed_dim = getattr(args, "encoder_ffn_embed_dim", 2048)
-    args.encoder_layers = getattr(args, "encoder_layers", 6)
-    args.encoder_attention_heads = getattr(args, "encoder_attention_heads", 8)
-    args.encoder_normalize_before = getattr(args, "encoder_normalize_before", False)
-    args.encoder_learned_pos = getattr(args, "encoder_learned_pos", False)
-    args.decoder_embed_path = getattr(args, "decoder_embed_path", None)
-    args.decoder_embed_dim = getattr(args, "decoder_embed_dim", args.encoder_embed_dim)
-    args.decoder_ffn_embed_dim = getattr(
-        args, "decoder_ffn_embed_dim", args.encoder_ffn_embed_dim
-    )
-    args.decoder_layers = getattr(args, "decoder_layers", 6)
-    args.decoder_attention_heads = getattr(args, "decoder_attention_heads", 8)
-    args.decoder_normalize_before = getattr(args, "decoder_normalize_before", False)
-    args.decoder_learned_pos = getattr(args, "decoder_learned_pos", False)
-    args.attention_dropout = getattr(args, "attention_dropout", 0.0)
-    args.activation_dropout = getattr(args, "activation_dropout", 0.0)
-    args.activation_fn = getattr(args, "activation_fn", "relu")
-    args.dropout = getattr(args, "dropout", 0.1)
-    args.adaptive_softmax_cutoff = getattr(args, "adaptive_softmax_cutoff", None)
-    args.adaptive_softmax_dropout = getattr(args, "adaptive_softmax_dropout", 0)
-    args.share_decoder_input_output_embed = getattr(
-        args, "share_decoder_input_output_embed", False
-    )
-    args.share_all_embeddings = getattr(args, "share_all_embeddings", False)
-    args.no_token_positional_embeddings = getattr(
-        args, "no_token_positional_embeddings", False
-    )
-    args.adaptive_input = getattr(args, "adaptive_input", False)
-    args.no_cross_attention = getattr(args, "no_cross_attention", False)
-    args.cross_self_attention = getattr(args, "cross_self_attention", False)
-    args.layer_wise_attention = getattr(args, "layer_wise_attention", False)
-
-    args.decoder_output_dim = getattr(
-        args, "decoder_output_dim", args.decoder_embed_dim
-    )
-    args.decoder_input_dim = getattr(args, "decoder_input_dim", args.decoder_embed_dim)
-
-    args.no_scale_embedding = getattr(args, "no_scale_embedding", False)
-    args.layernorm_embedding = getattr(args, "layernorm_embedding", False)
-
-
-@register_model_architecture("gru_transformer", "gru_transformer_big")
-def gru_transformer_big(args):
-    args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 1024)
-    args.encoder_ffn_embed_dim = getattr(args, "encoder_ffn_embed_dim", 4096)
-    args.encoder_attention_heads = getattr(args, "encoder_attention_heads", 16)
-    args.encoder_normalize_before = getattr(args, "encoder_normalize_before", False)
-    args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 1024)
-    args.decoder_ffn_embed_dim = getattr(args, "decoder_ffn_embed_dim", 4096)
-    args.decoder_attention_heads = getattr(args, "decoder_attention_heads", 16)
-    args.dropout = getattr(args, "dropout", 0.3)
-    gru_transformer_base_architecture(args)
diff --git a/spaces/OFA-Sys/OFA-vqa/fairseq/fairseq/trainer.py b/spaces/OFA-Sys/OFA-vqa/fairseq/fairseq/trainer.py
deleted file mode 100644
index e46ccfe0b8d3a224586fb16c69168321f60ce30e..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-vqa/fairseq/fairseq/trainer.py
+++ /dev/null
@@ -1,1509 +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.
-
-"""
-Train a network across multiple GPUs.
-"""
-
-import contextlib
-import logging
-import sys
-import time
-from argparse import Namespace
-from itertools import chain
-from typing import Any, Dict, List
-
-import torch
-from fairseq import checkpoint_utils, models, optim, utils
-from fairseq.dataclass.configs import FairseqConfig
-from fairseq.dataclass.utils import convert_namespace_to_omegaconf
-from fairseq.distributed import utils as distributed_utils
-from fairseq.file_io import PathManager
-from fairseq.logging import meters, metrics
-from fairseq.models.ema import build_ema
-from fairseq.nan_detector import NanDetector
-from fairseq.optim import lr_scheduler
-from omegaconf import OmegaConf
-
-logger = logging.getLogger(__name__)
-
-
-class Trainer(object):
-    """Main class for data parallel training.
-
-    This class supports synchronous distributed data parallel training,
-    where multiple workers each have a full model replica and gradients
-    are accumulated across workers before each update. We use
-    :class:`~torch.nn.parallel.DistributedDataParallel` to handle
-    communication of the gradients across workers.
-    """
-
-    def __init__(self, cfg: FairseqConfig, task, model, criterion, quantizer=None):
-
-        if isinstance(cfg, Namespace):
-            logger.warning(
-                "argparse.Namespace configuration is deprecated! Automatically converting to OmegaConf"
-            )
-            cfg = convert_namespace_to_omegaconf(cfg)
-
-        self.cfg = cfg
-        self.task = task
-
-        # catalog shared parameters
-        shared_params = _catalog_shared_params(model)
-        self.tpu = cfg.common.tpu
-        self.cuda = torch.cuda.is_available() and not cfg.common.cpu and not self.tpu
-        if self.cuda:
-            self.device = torch.device("cuda")
-        elif self.tpu:
-            self.device = utils.get_tpu_device()
-        else:
-            self.device = torch.device("cpu")
-
-        if self.is_fsdp:
-            import fairscale
-            if self.cfg.common.bf16:
-                raise ValueError(
-                    "FullyShardedDataParallel is not compatible with --bf16 or "
-                    "--memory-efficient-bf16"
-                )
-            if self.cfg.distributed_training.zero_sharding != "none":
-                raise ValueError(
-                    "FullyShardedDataParallel is not compatible with --zero-sharding "
-                    "option (it's already built in)"
-                )
-            if max(self.cfg.optimization.update_freq) > 1 and fairscale.__version__ < "0.4.0":
-                raise RuntimeError(
-                    "Please update to fairscale 0.4.0 or newer when combining "
-                    "--update-freq with FullyShardedDataParallel"
-                )
-        else:
-            if (
-                hasattr(self.cfg.distributed_training, "cpu_offload")
-                and self.cfg.distributed_training.cpu_offload
-            ):
-                raise ValueError("--cpu-offload requires --ddp-backend=fully_sharded")
-
-        # copy model and criterion to current device/dtype
-        self._criterion = criterion
-        self._model = model
-        if not self.is_fsdp:
-            if cfg.common.fp16:
-                assert not cfg.common.amp, "Cannot use fp16 and AMP together"
-                self._criterion = self._criterion.half()
-                self._model = self._model.half()
-            elif cfg.common.bf16:
-                self._criterion = self._criterion.to(dtype=torch.bfloat16)
-                self._model = self._model.to(dtype=torch.bfloat16)
-            elif cfg.common.amp:
-                self._amp_retries = 0
-        if (
-            not cfg.distributed_training.pipeline_model_parallel
-            # the DistributedFairseqModel wrapper will handle moving to device,
-            # so only handle cases which don't use the wrapper
-            and not self.use_distributed_wrapper
-        ):
-            self._criterion = self._criterion.to(device=self.device)
-            self._model = self._model.to(device=self.device)
-        self.pipeline_model_parallel = cfg.distributed_training.pipeline_model_parallel
-        self.last_device = None
-        if self.cuda and self.pipeline_model_parallel:
-            self.last_device = torch.device(
-                cfg.distributed_training.pipeline_devices[-1]
-            )
-
-        # check that shared parameters are preserved after device transfer
-        for shared_param in shared_params:
-            ref = _get_module_by_path(self._model, shared_param[0])
-            for path in shared_param[1:]:
-                logger.info(
-                    "detected shared parameter: {} <- {}".format(shared_param[0], path)
-                )
-                _set_module_by_path(self._model, path, ref)
-
-        self._dummy_batch = None  # indicates we don't have a dummy batch at first
-        self._lr_scheduler = None
-        self._num_updates = 0
-        self._num_xla_compiles = 0  # for TPUs
-        self._optim_history = None
-        self._optimizer = None
-        self._warn_once = set()
-        self._wrapped_criterion = None
-        self._wrapped_model = None
-        self._ema = None
-
-        # TODO(myleott): support tpu
-        if self.cuda and self.data_parallel_world_size > 1:
-            self._grad_norm_buf = torch.cuda.DoubleTensor(self.data_parallel_world_size)
-        else:
-            self._grad_norm_buf = None
-
-        self.quantizer = quantizer
-        if self.quantizer is not None:
-            self.quantizer.set_trainer(self)
-
-        # get detailed cuda environment
-        if self.cuda:
-            self.cuda_env = utils.CudaEnvironment()
-            if self.data_parallel_world_size > 1:
-                self.cuda_env_arr = distributed_utils.all_gather_list(
-                    self.cuda_env, group=distributed_utils.get_global_group()
-                )
-            else:
-                self.cuda_env_arr = [self.cuda_env]
-            if self.data_parallel_rank == 0:
-                utils.CudaEnvironment.pretty_print_cuda_env_list(self.cuda_env_arr)
-        else:
-            self.cuda_env = None
-            self.cuda_env_arr = None
-
-        metrics.log_start_time("wall", priority=790, round=0)
-
-        self._start_time = time.time()
-        self._previous_training_time = 0
-        self._cumulative_training_time = None
-
-    def reinitialize(self):
-        """Reinitialize the Trainer, typically after model params change."""
-        self._lr_scheduler = None
-        self._optimizer = None
-        self._wrapped_criterion = None
-        self._wrapped_model = None
-
-    @property
-    def data_parallel_world_size(self):
-        if self.cfg.distributed_training.distributed_world_size == 1:
-            return 1
-        return distributed_utils.get_data_parallel_world_size()
-
-    @property
-    def data_parallel_process_group(self):
-        return distributed_utils.get_data_parallel_group()
-
-    @property
-    def data_parallel_rank(self):
-        if self.cfg.distributed_training.distributed_world_size == 1:
-            return 0
-        return distributed_utils.get_data_parallel_rank()
-
-    @property
-    def is_data_parallel_master(self):
-        # NOTE: this returns true for all model parallel replicas with data
-        # parallel rank 0
-        return self.data_parallel_rank == 0
-
-    @property
-    def use_distributed_wrapper(self) -> bool:
-        return (
-            self.data_parallel_world_size > 1 and not self.cfg.optimization.use_bmuf
-        ) or (
-            self.is_fsdp and self.cfg.distributed_training.cpu_offload
-        )
-
-    @property
-    def should_save_checkpoint_on_current_rank(self) -> bool:
-        """Indicates whether to save checkpoints on the current DDP rank."""
-        if (
-            self.is_fsdp and self.cfg.distributed_training.use_sharded_state
-        ) or getattr(self.cfg.model, "base_layers", 0) > 0:
-            return True
-        else:
-            return self.is_data_parallel_master
-
-    @property
-    def always_call_state_dict_during_save_checkpoint(self) -> bool:
-        if self.is_fsdp and not self.cfg.distributed_training.use_sharded_state:
-            # FSDP calls communication collective when consolidating checkpoints
-            return True
-        else:
-            return False
-
-    @property
-    def checkpoint_suffix(self) -> str:
-        """Suffix to add to the checkpoint file name."""
-        if self.is_fsdp and self.cfg.distributed_training.use_sharded_state:
-            return self.cfg.checkpoint.checkpoint_suffix + "-shard{0}".format(
-                self.data_parallel_rank
-            )
-        else:
-            return self.cfg.checkpoint.checkpoint_suffix or ""
-
-    @property
-    def criterion(self):
-        if self._wrapped_criterion is None:
-            if utils.has_parameters(self._criterion) and self.use_distributed_wrapper:
-                self._wrapped_criterion = models.DistributedFairseqModel(
-                    self.cfg.distributed_training,
-                    self._criterion,
-                    process_group=self.data_parallel_process_group,
-                    device=self.device,
-                )
-            else:
-                self._wrapped_criterion = self._criterion
-        return self._wrapped_criterion
-
-    @property
-    def model(self):
-        if self._wrapped_model is None:
-            if self.use_distributed_wrapper:
-                self._wrapped_model = models.DistributedFairseqModel(
-                    self.cfg.distributed_training,
-                    self._model,
-                    process_group=self.data_parallel_process_group,
-                    device=self.device,
-                )
-            else:
-                self._wrapped_model = self._model
-        return self._wrapped_model
-
-    @property
-    def ema(self):
-        if self._ema is None:
-            self._build_ema()
-        return self._ema
-
-    def _build_ema(self):
-        if self.cfg.ema.store_ema:
-            self._ema = build_ema(self._model, self.cfg.ema, self.device)
-            logger.info(
-                "Exponential Moving Average Shadow Model is initialized."
-            )
-
-    @property
-    def optimizer(self):
-        if self._optimizer is None:
-            self._build_optimizer()
-        return self._optimizer
-
-    @property
-    def lr_scheduler(self):
-        if self._lr_scheduler is None:
-            self._build_optimizer()  # this will initialize self._lr_scheduler
-        return self._lr_scheduler
-
-    def _build_optimizer(self):
-        params = list(
-            filter(
-                lambda p: p.requires_grad,
-                chain(self.model.parameters(), self.criterion.parameters()),
-            )
-        )
-
-        if self.is_fsdp and self.cfg.common.fp16:
-            # FullyShardedDataParallel always uses MemoryEfficientFP16 wrapper,
-            # mostly for the grad scaling. But if we don't have the
-            # --memory-efficient-fp16 flag set, then we're effectively doing
-            # regular --fp16 and can allow the use of optimizers that would
-            # otherwise be unsupported by MemoryEfficientFP16Optimizer.
-            allow_unsupported = not self.cfg.common.memory_efficient_fp16
-            self._optimizer = optim.MemoryEfficientFP16Optimizer.build_optimizer(
-                self.cfg, params, allow_unsupported=allow_unsupported
-            )
-        elif self.cfg.common.fp16 or self.cfg.common.bf16 or self.cfg.common.amp:
-            if self.cuda and torch.cuda.get_device_capability(0)[0] < 7:
-                logger.info(
-                    "NOTE: your device does NOT support faster training with --fp16 or --amp, "
-                    "please switch to FP32 which is likely to be faster"
-                )
-            if (
-                self.cfg.common.memory_efficient_fp16
-                or self.cfg.common.memory_efficient_bf16
-            ):
-                self._optimizer = optim.MemoryEfficientFP16Optimizer.build_optimizer(
-                    self.cfg, params
-                )
-            elif self.cfg.common.amp:
-                self._optimizer = optim.AMPOptimizer.build_optimizer(self.cfg, params)
-            else:
-                self._optimizer = optim.FP16Optimizer.build_optimizer(self.cfg, params)
-        else:
-            if self.cuda and torch.cuda.get_device_capability(0)[0] >= 7:
-                logger.info("NOTE: your device may support faster training with --fp16 or --amp")
-            self._optimizer = optim.build_optimizer(self.cfg.optimizer, params)
-
-        if self.is_fsdp:
-            assert (
-                not self.cfg.optimization.use_bmuf
-            ), "--ddp-backend=fully_sharded is not compatible with BMUF"
-            assert self._optimizer.supports_flat_params, (
-                "--ddp-backend=fully_sharded is only compatible with pointwise "
-                "optimizers (e.g., Adam, AdamW, Adadelta, Adamax, SGD, etc.). "
-                "However, the sharding will result in slightly different results when "
-                "using non-pointwise optimizers (e.g., Adagrad, Adafactor, LAMB)"
-            )
-
-        if self.cfg.optimization.use_bmuf:
-            self._optimizer = optim.FairseqBMUF(
-                self.cfg.bmuf,
-                self._optimizer,
-            )
-
-        if self.cfg.distributed_training.zero_sharding == "os":
-            if (
-                self.cfg.common.fp16
-                and not self.cfg.common.memory_efficient_fp16
-                and not self.cfg.common.memory_efficient_bf16
-            ) and not self.cfg.common.fp16_no_flatten_grads:
-                raise ValueError(
-                    "ZeRO is incomptabile with fp16 and flattened grads. "
-                    "Please use --fp16-no-flatten-grads"
-                )
-            else:
-                optim.shard_(self._optimizer, self.data_parallel_process_group)
-
-        # We should initialize the learning rate scheduler immediately after
-        # building the optimizer, so that the initial learning rate is set.
-        self._lr_scheduler = lr_scheduler.build_lr_scheduler(
-            self.cfg.lr_scheduler,
-            self.optimizer,
-        )
-        self._lr_scheduler.step_update(0)
-
-    @property
-    def is_fsdp(self):
-        return self.cfg.distributed_training.ddp_backend == "fully_sharded"
-
-    def consolidate_optimizer(self):
-        """For OSS, we need to consolidate the state dict."""
-        if self.cfg.checkpoint.no_save_optimizer_state:
-            return
-        self._gathered_optim_state = None
-        if hasattr(self.optimizer.optimizer, "consolidate_state_dict"):
-            self.optimizer.optimizer.consolidate_state_dict()
-        elif self.is_fsdp and not self.model.use_sharded_state:
-            st = self.model.gather_full_optim_state_dict(
-                self.optimizer
-            )  # only returns on rank 0
-            self._gathered_optim_state = st
-
-    def state_dict(self):
-        state_dict = {
-            "args": None,  # legacy
-            "cfg": (
-                OmegaConf.to_container(self.cfg, resolve=True, enum_to_str=True)
-                if OmegaConf.is_config(self.cfg)
-                else self.cfg
-            ),
-            "model": self.model.state_dict(),
-            "criterion": (
-                self.criterion.state_dict()
-                if utils.has_parameters(self.criterion)
-                else None
-            ),
-            "optimizer_history": (self._optim_history or [])
-            + [
-                {
-                    "criterion_name": self.get_criterion().__class__.__name__,
-                    "optimizer_name": self.optimizer.__class__.__name__,
-                    "lr_scheduler_state": self.lr_scheduler.state_dict(),
-                    "num_updates": self.get_num_updates(),
-                }
-            ],
-            "task_state": self.task.state_dict() if self.task is not None else {},
-            "extra_state": {
-                "metrics": metrics.state_dict(),
-                "previous_training_time": self.cumulative_training_time(),
-            },
-        }
-        if self.cfg.ema.store_ema:
-            # Save EMA model state as extra state
-            state_dict["extra_state"]["ema"] = self.ema.get_model().state_dict()
-            if self.cfg.ema.ema_fp32:
-                # Save EMA params in fp32
-                state_dict["extra_state"]["ema_fp32_params"] = self.ema.fp32_params
-        if not self.cfg.checkpoint.no_save_optimizer_state:
-            if self._gathered_optim_state is not None:
-                state_dict["last_optimizer_state"] = self._gathered_optim_state
-                self._gathered_optim_state = None
-            else:
-                state_dict["last_optimizer_state"] = self.optimizer.state_dict()
-        if self.is_fsdp:
-            # save meta data for recombining checkpoint upon loading
-            state_dict["fsdp_metadata"] = self.model.local_metadata_dict()
-        return state_dict
-
-    def save_checkpoint(self, filename, extra_state):
-        """Save all training state in a checkpoint file."""
-        logger.info(f"Saving checkpoint to {filename}")
-        # call state_dict on all ranks in case it needs internal communication
-        state_dict = utils.move_to_cpu(self.state_dict())
-        state_dict["extra_state"].update(extra_state)
-        if self.should_save_checkpoint_on_current_rank:
-            checkpoint_utils.torch_persistent_save(
-                state_dict,
-                filename,
-                async_write=self.cfg.checkpoint.write_checkpoints_asynchronously,
-            )
-        logger.info(f"Finished saving checkpoint to {filename}")
-
-    def load_checkpoint(
-        self,
-        filename,
-        reset_optimizer=False,
-        reset_lr_scheduler=False,
-        optimizer_overrides=None,
-        reset_meters=False,
-    ):
-        """
-        Load all training state from a checkpoint file.
-        rank = 0 will load the checkpoint, and then broadcast it to all
-        other ranks.
-        """
-        extra_state, self._optim_history, last_optim_state = None, [], None
-
-        logger.info(f"Preparing to load checkpoint {filename}")
-        is_distributed = self.data_parallel_world_size > 1
-        bexists = PathManager.isfile(filename)
-        if bexists:
-            load_on_all_ranks = (
-                self.cfg.checkpoint.load_checkpoint_on_all_dp_ranks
-                # TPUs don't support broadcast yet, so load checkpoints
-                # on every worker for now
-                or self.tpu
-                # FSDP requires loading checkpoint shards on all ranks
-                or (self.is_fsdp and self.cfg.distributed_training.use_sharded_state)
-                or getattr(self.cfg.model, "base_layers", 0) > 0
-            )
-
-            if load_on_all_ranks or self.data_parallel_rank == 0:
-                state = checkpoint_utils.load_checkpoint_to_cpu(
-                    filename, load_on_all_ranks=load_on_all_ranks
-                )
-                last_optim_state = state.get("last_optimizer_state", None)
-
-                # If doing zero_sharding, do not broadcast global optimizer
-                # state. Later we will broadcast sharded states to each rank
-                # to avoid memory from exploding.
-                if (
-                    not load_on_all_ranks
-                    and self.cfg.distributed_training.zero_sharding == "os"
-                    and "last_optimizer_state" in state
-                    and is_distributed
-                ):
-                    state["last_optimizer_state"] = "SHARDED"
-            else:
-                last_optim_state = None
-                state = None
-
-            if is_distributed and not load_on_all_ranks:
-                state = distributed_utils.broadcast_object(
-                    state,
-                    src_rank=0,
-                    group=self.data_parallel_process_group,
-                    dist_device=self.device,
-                )
-                if self.data_parallel_rank > 0:
-                    last_optim_state = state.get("last_optimizer_state", None)
-
-            # load model parameters
-            try:
-                self.model.load_state_dict(
-                    state["model"], strict=True, model_cfg=self.cfg.model
-                )
-                # save memory for later steps
-                del state["model"]
-                if utils.has_parameters(self.get_criterion()):
-                    self.get_criterion().load_state_dict(
-                        state["criterion"], strict=True
-                    )
-                    del state["criterion"]
-
-            except Exception:
-                raise Exception(
-                    "Cannot load model parameters from checkpoint {}; "
-                    "please ensure that the architectures match.".format(filename)
-                )
-            extra_state = state["extra_state"]
-            self._optim_history = state["optimizer_history"]
-
-        if last_optim_state is not None and not reset_optimizer:
-            # rebuild optimizer after loading model, since params may have changed
-            self._build_optimizer()
-
-            # only reload optimizer and lr_scheduler if they match
-            last_optim = self._optim_history[-1]
-            assert (
-                last_optim["criterion_name"] == self.get_criterion().__class__.__name__
-            ), f"Criterion does not match; please reset the optimizer (--reset-optimizer). {last_optim['criterion_name']} vs {self.get_criterion().__class__.__name__}"
-            assert (
-                last_optim["optimizer_name"] == self.optimizer.__class__.__name__
-            ), f"Optimizer does not match; please reset the optimizer (--reset-optimizer). {last_optim['optimizer_name']} vs {self.optimizer.__class__.__name__}"
-
-            if not reset_lr_scheduler:
-                self.lr_scheduler.load_state_dict(last_optim["lr_scheduler_state"])
-
-            if self.is_fsdp and not self.model.use_sharded_state:
-                # if use_sharded_state, the last_optim_state is already sharded, skip this
-                last_optim_state = self.model.get_shard_from_optim_state_dict(
-                    last_optim_state
-                )
-            elif not load_on_all_ranks and is_distributed:
-                last_optim_state = self.optimizer.broadcast_global_state_dict(
-                    last_optim_state
-                )
-
-            self.optimizer.load_state_dict(last_optim_state, optimizer_overrides)
-
-            self.set_num_updates(last_optim["num_updates"])
-
-        if extra_state is not None:
-            itr_state = extra_state["train_iterator"]
-            epoch = itr_state["epoch"]
-
-            if "previous_training_time" in extra_state:
-                self._previous_training_time = extra_state["previous_training_time"]
-                self._start_time = time.time()
-
-            self.lr_step(epoch)
-
-            if (
-                itr_state.get("version", 1) >= 2
-                and itr_state["iterations_in_epoch"] == 0
-            ):
-                # reset meters at start of epoch
-                reset_meters = True
-
-            if "metrics" in extra_state and not reset_meters:
-                metrics.load_state_dict(extra_state["metrics"])
-
-                # reset TimeMeters, since their start times don't make sense anymore
-                for meter in metrics.get_meters("default"):
-                    if isinstance(meter, meters.TimeMeter):
-                        meter.reset()
-
-            if self.cfg.ema.store_ema:
-                if "ema" not in extra_state:
-                    logger.warn(
-                        "EMA not found in checkpoint. But store_ema is True. "
-                        "EMA is re-initialized from checkpoint."
-                    )
-                    self.ema.restore(state["model"], build_fp32_params=self.cfg.ema.ema_fp32)
-                else:
-                    logger.info(
-                        "Loading EMA from checkpoint"
-                    )
-                    self.ema.restore(extra_state["ema"], build_fp32_params=False)
-
-                    if self.cfg.ema.ema_fp32:
-                        if "ema_fp32_params" in extra_state:
-                            logger.info(
-                                "Loading EMA fp32 params from checkpoint"
-                            )
-                            self.ema.build_fp32_params(extra_state["ema_fp32_params"])
-                        else:
-                            logger.info(
-                                "Building EMA fp32 params from EMA model in checkpoint"
-                            )
-                            self.ema.build_fp32_params()
-
-            logger.info(
-                "Loaded checkpoint {} (epoch {} @ {} updates)".format(
-                    filename, epoch, self.get_num_updates()
-                )
-            )
-
-        else:
-            logger.info("No existing checkpoint found {}".format(filename))
-
-        return extra_state
-
-    def get_train_iterator(
-        self,
-        epoch,
-        combine=True,
-        load_dataset=True,
-        data_selector=None,
-        shard_batch_itr=True,
-        disable_iterator_cache=False,
-    ):
-        """Return an EpochBatchIterator over the training set for a given epoch."""
-        if load_dataset:
-            logger.info("loading train data for epoch {}".format(epoch))
-            self.task.load_dataset(
-                self.cfg.dataset.train_subset,
-                epoch=epoch,
-                combine=combine,
-                data_selector=data_selector,
-                tpu=self.tpu,
-            )
-        batch_iterator = self.task.get_batch_iterator(
-            dataset=self.task.dataset(self.cfg.dataset.train_subset),
-            max_tokens=self.cfg.dataset.max_tokens,
-            max_sentences=self.cfg.dataset.batch_size,
-            max_positions=utils.resolve_max_positions(
-                self.task.max_positions(),
-                self.model.max_positions(),
-                self.cfg.dataset.max_tokens,
-            ),
-            ignore_invalid_inputs=True,
-            required_batch_size_multiple=self.cfg.dataset.required_batch_size_multiple,
-            seed=self.cfg.common.seed,
-            num_shards=self.data_parallel_world_size if shard_batch_itr else 1,
-            shard_id=self.data_parallel_rank if shard_batch_itr else 0,
-            num_workers=self.cfg.dataset.num_workers,
-            epoch=epoch,
-            data_buffer_size=self.cfg.dataset.data_buffer_size,
-            disable_iterator_cache=disable_iterator_cache,
-        )
-        self.reset_dummy_batch(batch_iterator.first_batch)
-        return batch_iterator
-
-    def get_valid_iterator(
-        self,
-        subset,
-        disable_iterator_cache=False,
-    ):
-        """Return an EpochBatchIterator over given validation subset for a given epoch."""
-        batch_iterator = self.task.get_batch_iterator(
-            dataset=self.task.dataset(subset),
-            max_tokens=self.cfg.dataset.max_tokens_valid,
-            max_sentences=self.cfg.dataset.batch_size_valid,
-            max_positions=utils.resolve_max_positions(
-                self.task.max_positions(),
-                self.model.max_positions(),
-            ),
-            ignore_invalid_inputs=self.cfg.dataset.skip_invalid_size_inputs_valid_test,
-            required_batch_size_multiple=self.cfg.dataset.required_batch_size_multiple,
-            seed=self.cfg.common.seed,
-            num_shards=self.data_parallel_world_size,
-            shard_id=self.data_parallel_rank,
-            num_workers=self.cfg.dataset.num_workers,
-            # always pass a fixed "epoch" to keep validation data consistent
-            # across training epochs
-            epoch=1,
-            data_buffer_size=self.cfg.dataset.data_buffer_size,
-            disable_iterator_cache=disable_iterator_cache,
-        )
-        self.reset_dummy_batch(batch_iterator.first_batch)
-        return batch_iterator
-
-    def begin_epoch(self, epoch):
-        """Called at the beginning of each epoch."""
-        logger.info("begin training epoch {}".format(epoch))
-
-        self.lr_step_begin_epoch(epoch)
-
-        if self.quantizer is not None:
-            self.quantizer.begin_epoch(epoch)
-
-        # task specific setup per epoch
-        self.task.begin_epoch(epoch, self.get_model())
-
-        if self.tpu:
-            import torch_xla.core.xla_model as xm
-
-            xm.rendezvous("begin_epoch")  # wait for all workers
-            xm.mark_step()
-
-    def begin_valid_epoch(self, epoch):
-        """Called at the beginning of each validation epoch."""
-
-        # task specific setup per validation epoch
-        self.task.begin_valid_epoch(epoch, self.get_model())
-
-    def reset_dummy_batch(self, batch):
-        self._dummy_batch = batch
-
-    @metrics.aggregate("train")
-    def train_step(self, samples, raise_oom=False):
-        """Do forward, backward and parameter update."""
-        self._set_seed()
-        self.model.train()
-        self.criterion.train()
-        self.zero_grad()
-
-        metrics.log_start_time("train_wall", priority=800, round=0)
-
-        # If EMA is enabled through store_ema=True
-        # and task.uses_ema is True, pass the EMA model as a keyword
-        # argument to the task.
-        extra_kwargs = {}
-        if self.cfg.ema.store_ema and getattr(self.task, "uses_ema", False):
-            extra_kwargs["ema_model"] = self.ema.get_model()
-
-        # forward and backward pass
-        logging_outputs, sample_size, ooms = [], 0, 0
-        for i, sample in enumerate(samples):  # delayed update loop
-            sample, is_dummy_batch = self._prepare_sample(sample)
-
-            def maybe_no_sync():
-                """
-                Whenever *samples* contains more than one mini-batch, we
-                want to accumulate gradients locally and only call
-                all-reduce in the last backwards pass.
-                """
-                if (
-                    self.data_parallel_world_size > 1
-                    and hasattr(self.model, "no_sync")
-                    and i < len(samples) - 1
-                    # The no_sync context manager results in increased memory
-                    # usage with FSDP, since full-size gradients will be
-                    # accumulated on each GPU. It's typically a better tradeoff
-                    # to do the extra communication with FSDP.
-                    and not self.is_fsdp
-                ):
-                    return self.model.no_sync()
-                else:
-                    return contextlib.ExitStack()  # dummy contextmanager
-
-            try:
-                with maybe_no_sync():
-                    # forward and backward
-                    loss, sample_size_i, logging_output = self.task.train_step(
-                        sample=sample,
-                        model=self.model,
-                        criterion=self.criterion,
-                        optimizer=self.optimizer,
-                        update_num=self.get_num_updates(),
-                        ignore_grad=is_dummy_batch,
-                        **extra_kwargs,
-                    )
-                    del loss
-
-                logging_outputs.append(logging_output)
-                sample_size += sample_size_i
-
-                # emptying the CUDA cache after the first step can
-                # reduce the chance of OOM
-                if self.cuda and self.get_num_updates() == 0:
-                    torch.cuda.empty_cache()
-            except RuntimeError as e:
-                if "out of memory" in str(e):
-                    self._log_oom(e)
-                    if raise_oom:
-                        raise e
-                    logger.warning(
-                        "attempting to recover from OOM in forward/backward pass"
-                    )
-                    ooms += 1
-                    self.zero_grad()
-                    if self.cuda:
-                        torch.cuda.empty_cache()
-                    if self.cfg.distributed_training.distributed_world_size == 1:
-                        return None
-                else:
-                    raise e
-
-            if self.tpu and i < len(samples) - 1:
-                # tpu-comment: every XLA operation before marking step is
-                # appended to the IR graph, and processing too many batches
-                # before marking step can lead to OOM errors.
-                # To handle gradient accumulation use case, we explicitly
-                # mark step here for every forward pass without a backward pass
-                self._xla_markstep_and_send_to_cpu()
-
-        if is_dummy_batch:
-            if torch.is_tensor(sample_size):
-                sample_size.zero_()
-            else:
-                sample_size *= 0.0
-
-        if torch.is_tensor(sample_size):
-            sample_size = sample_size.float()
-        else:
-            sample_size = float(sample_size)
-
-        # gather logging outputs from all replicas
-        if self._sync_stats():
-            train_time = self._local_cumulative_training_time()
-            logging_outputs, (
-                sample_size,
-                ooms,
-                total_train_time,
-            ) = self._aggregate_logging_outputs(
-                logging_outputs, sample_size, ooms, train_time, ignore=is_dummy_batch
-            )
-            self._cumulative_training_time = (
-                total_train_time / self.data_parallel_world_size
-            )
-
-        overflow = False
-        try:
-            with torch.autograd.profiler.record_function("reduce-grads"):
-                # reduce gradients across workers
-                self.optimizer.all_reduce_grads(self.model)
-                if utils.has_parameters(self.criterion):
-                    self.optimizer.all_reduce_grads(self.criterion)
-
-            with torch.autograd.profiler.record_function("multiply-grads"):
-                # multiply gradients by (data_parallel_size / sample_size) since
-                # DDP normalizes by the number of data parallel workers for
-                # improved fp16 precision.
-                # Thus we get (sum_of_gradients / sample_size) at the end.
-                # In case of fp16, this step also undoes loss scaling.
-                # (Debugging note: Some optimizers perform this scaling on the
-                # fly, so inspecting model.parameters() or optimizer.params may
-                # still show the original, unscaled gradients.)
-                numer = (
-                    self.data_parallel_world_size
-                    if not self.cfg.optimization.use_bmuf or self._sync_stats()
-                    else 1
-                )
-                self.optimizer.multiply_grads(numer / (sample_size or 1.0))
-                # Note: (sample_size or 1.0) handles the case of a zero gradient, in a
-                # way that avoids CPU/device transfers in case sample_size is a GPU or
-                # TPU object. The assumption is that the gradient itself is also 0.
-
-            with torch.autograd.profiler.record_function("clip-grads"):
-                # clip grads
-                grad_norm = self.clip_grad_norm(self.cfg.optimization.clip_norm)
-
-            # check that grad norms are consistent across workers
-            # on tpu check tensor is slow
-            if not self.tpu:
-                if (
-                    not self.cfg.optimization.use_bmuf
-                    and self.cfg.distributed_training.ddp_backend != "slow_mo"
-                ):
-                    self._check_grad_norms(grad_norm)
-                if not torch.isfinite(grad_norm).all():
-                    # in case of AMP, if gradients are Nan/Inf then
-                    # optimizer step is still required
-                    if self.cfg.common.amp:
-                        overflow = True
-                    else:
-                        # check local gradnorm single GPU case, trigger NanDetector
-                        raise FloatingPointError("gradients are Nan/Inf")
-
-            with torch.autograd.profiler.record_function("optimizer"):
-                # take an optimization step
-                self.task.optimizer_step(
-                    self.optimizer, model=self.model, update_num=self.get_num_updates()
-                )
-                if self.cfg.common.amp and overflow:
-                    if self._amp_retries == self.cfg.common.amp_batch_retries:
-                        logger.info("AMP: skipping this batch.")
-                        self._amp_retries = 0
-                    else:
-                        self._amp_retries += 1
-                        return self.train_step(samples, raise_oom)  # recursion to feed in same batch
-
-        except FloatingPointError:
-            # re-run the forward and backward pass with hooks attached to print
-            # out where it fails
-            self.zero_grad()
-            with NanDetector(self.get_model()):
-                for _, sample in enumerate(samples):
-                    sample, _ = self._prepare_sample(sample)
-                    self.task.train_step(
-                        sample,
-                        self.model,
-                        self.criterion,
-                        self.optimizer,
-                        self.get_num_updates(),
-                        ignore_grad=False,
-                        **extra_kwargs,
-                    )
-            raise
-        except OverflowError as e:
-            overflow = True
-            logger.info(
-                f"NOTE: gradient overflow detected, ignoring gradient, {str(e)}"
-            )
-            grad_norm = torch.tensor(0.0).cuda()
-            self.zero_grad()
-        except RuntimeError as e:
-            if "out of memory" in str(e):
-                self._log_oom(e)
-                logger.error("OOM during optimization, irrecoverable")
-            raise e
-
-        # Some distributed wrappers (e.g., SlowMo) need access to the optimizer
-        # after the step
-        if hasattr(self.model, "perform_additional_optimizer_actions"):
-            if hasattr(self.optimizer, "fp32_params"):
-                self.model.perform_additional_optimizer_actions(
-                    self.optimizer.optimizer, self.optimizer.fp32_params
-                )
-            else:
-                self.model.perform_additional_optimizer_actions(
-                    self.optimizer.optimizer
-                )
-
-        logging_output = None
-        if not overflow or self.cfg.distributed_training.ddp_backend == "slow_mo":
-            self.set_num_updates(self.get_num_updates() + 1)
-
-            if self.cfg.ema.store_ema:
-                # Step EMA forward with new model.
-                self.ema.step(
-                    self.get_model(),
-                    self.get_num_updates(),
-                )
-                metrics.log_scalar(
-                    "ema_decay",
-                    self.ema.get_decay(),
-                    priority=10000,
-                    round=5,
-                    weight=0,
-                )
-
-            if self.tpu:
-                import torch_xla.core.xla_model as xm
-
-                # mark step on TPUs
-                self._xla_markstep_and_send_to_cpu()
-
-                # only log stats every log_interval steps
-                # this causes wps to be misreported when log_interval > 1
-                logging_output = {}
-                if self.get_num_updates() % self.cfg.common.log_interval == 0:
-                    # log memory usage
-                    mem_info = xm.get_memory_info(self.device)
-                    gb_free = mem_info["kb_free"] / 1024 / 1024
-                    gb_total = mem_info["kb_total"] / 1024 / 1024
-                    metrics.log_scalar(
-                        "gb_free", gb_free, priority=1500, round=1, weight=0
-                    )
-                    metrics.log_scalar(
-                        "gb_total", gb_total, priority=1600, round=1, weight=0
-                    )
-                    logging_outputs = self._xla_markstep_and_send_to_cpu(
-                        logging_outputs
-                    )
-                    logging_output = self._reduce_and_log_stats(
-                        logging_outputs, sample_size, grad_norm
-                    )
-
-                # log whenever there's an XLA compilation, since these
-                # slow down training and may indicate opportunities for
-                # optimization
-                self._check_xla_compilation()
-            else:
-                if self.cuda and self.cuda_env is not None:
-                    # log minimum free memory over the iteration
-                    gb_used = torch.cuda.max_memory_allocated() / 1024 / 1024 / 1024
-                    torch.cuda.reset_peak_memory_stats()
-                    gb_free = self.cuda_env.total_memory_in_GB - gb_used
-                    metrics.log_scalar(
-                        "gb_free", gb_free, priority=1500, round=1, weight=0
-                    )
-
-                # log stats
-                logging_output = self._reduce_and_log_stats(
-                    logging_outputs, sample_size, grad_norm
-                )
-
-                # clear CUDA cache to reduce memory fragmentation
-                if (
-                    self.cuda
-                    and self.cfg.common.empty_cache_freq > 0
-                    and (
-                        (self.get_num_updates() + self.cfg.common.empty_cache_freq - 1)
-                        % self.cfg.common.empty_cache_freq
-                    )
-                    == 0
-                ):
-                    torch.cuda.empty_cache()
-
-        if self.cfg.common.fp16 or self.cfg.common.amp:
-            metrics.log_scalar(
-                "loss_scale",
-                (
-                    self.optimizer.scaler.loss_scale
-                    if self.cfg.common.fp16
-                    else self.optimizer.scaler.get_scale()
-                ),
-                priority=700,
-                round=4,
-                weight=0,
-            )
-
-        metrics.log_stop_time("train_wall")
-        return logging_output
-
-    @metrics.aggregate("valid")
-    def valid_step(self, sample, raise_oom=False):
-        """Do forward pass in evaluation mode."""
-        if self.tpu:
-            import torch_xla.core.xla_model as xm
-
-            xm.rendezvous("valid_step")  # wait for all workers
-
-        # If EMA is enabled through store_ema=True
-        # and task.uses_ema is True, pass the EMA model as a keyword
-        # argument to the task.
-        extra_kwargs = {}
-        if self.cfg.ema.store_ema and getattr(self.task, "uses_ema", False):
-            extra_kwargs["ema_model"] = self.ema.get_model()
-
-        with torch.no_grad():
-            self.model.eval()
-            self.criterion.eval()
-
-            sample, is_dummy_batch = self._prepare_sample(sample)
-
-            try:
-                _loss, sample_size, logging_output = self.task.valid_step(
-                    sample, self.model, self.criterion, **extra_kwargs
-                )
-            except RuntimeError as e:
-                if "out of memory" in str(e):
-                    self._log_oom(e)
-                    if not raise_oom:
-                        logger.warning(
-                            "ran out of memory in validation step, retrying batch"
-                        )
-                        for p in self.model.parameters():
-                            if p.grad is not None:
-                                p.grad = None  # free some memory
-                        if self.cuda:
-                            torch.cuda.empty_cache()
-                        return self.valid_step(sample, raise_oom=True)
-                raise e
-
-            logging_outputs = [logging_output]
-            if is_dummy_batch:
-                if torch.is_tensor(sample_size):
-                    sample_size.zero_()
-                else:
-                    sample_size *= 0.0
-
-        # gather logging outputs from all replicas
-        if self.data_parallel_world_size > 1:
-            logging_outputs, (sample_size,) = self._aggregate_logging_outputs(
-                logging_outputs,
-                sample_size,
-                ignore=is_dummy_batch,
-            )
-
-        # log validation stats
-        if self.tpu:
-            logging_outputs = self._xla_markstep_and_send_to_cpu(logging_outputs)
-        logging_output = self._reduce_and_log_stats(logging_outputs, sample_size)
-
-        return logging_output
-
-    def zero_grad(self):
-        self.optimizer.zero_grad()
-
-    def lr_step_begin_epoch(self, epoch):
-        """Adjust the learning rate at the beginning of the epoch."""
-        self.lr_scheduler.step_begin_epoch(epoch)
-        # prefer updating the LR based on the number of steps
-        return self.lr_step_update()
-
-    def lr_step(self, epoch, val_loss=None):
-        """Adjust the learning rate at the end of the epoch."""
-        self.lr_scheduler.step(epoch, val_loss)
-        # prefer updating the LR based on the number of steps
-        return self.lr_step_update()
-
-    def lr_step_update(self):
-        """Update the learning rate after each update."""
-        new_lr = self.lr_scheduler.step_update(self.get_num_updates())
-        if isinstance(new_lr, dict):
-            for k, v in new_lr.items():
-                metrics.log_scalar(f"lr_{k}", v, weight=0, priority=300)
-            new_lr = new_lr.get("default", next(iter(new_lr.values())))
-        else:
-            metrics.log_scalar("lr", new_lr, weight=0, priority=300)
-        return new_lr
-
-    def get_lr(self):
-        """Get the current learning rate."""
-        return self.optimizer.get_lr()
-
-    def get_model(self):
-        """Get the (non-wrapped) model instance."""
-        return self._model
-
-    def get_criterion(self):
-        """Get the (non-wrapped) criterion instance."""
-        return self._criterion
-
-    def get_meter(self, name):
-        """[deprecated] Get a specific meter by name."""
-        from fairseq import meters
-
-        if "get_meter" not in self._warn_once:
-            self._warn_once.add("get_meter")
-            utils.deprecation_warning(
-                "Trainer.get_meter is deprecated. Please use fairseq.metrics instead."
-            )
-
-        train_meters = metrics.get_meters("train")
-        if train_meters is None:
-            train_meters = {}
-
-        if name == "train_loss" and "loss" in train_meters:
-            return train_meters["loss"]
-        elif name == "train_nll_loss":
-            # support for legacy train.py, which assumed this meter is
-            # always initialized
-            m = train_meters.get("nll_loss", None)
-            return m or meters.AverageMeter()
-        elif name == "wall":
-            # support for legacy train.py, which assumed this meter is
-            # always initialized
-            m = metrics.get_meter("default", "wall")
-            return m or meters.TimeMeter()
-        elif name == "wps":
-            m = metrics.get_meter("train", "wps")
-            return m or meters.TimeMeter()
-        elif name in {"valid_loss", "valid_nll_loss"}:
-            # support for legacy train.py, which assumed these meters
-            # are always initialized
-            k = name[len("valid_") :]
-            m = metrics.get_meter("valid", k)
-            return m or meters.AverageMeter()
-        elif name == "oom":
-            return meters.AverageMeter()
-        elif name in train_meters:
-            return train_meters[name]
-        return None
-
-    def get_num_updates(self):
-        """Get the number of parameters updates."""
-        return self._num_updates
-
-    def set_num_updates(self, num_updates):
-        """Set the number of parameters updates."""
-        self._num_updates = num_updates
-        self.lr_step_update()
-        if self.quantizer:
-            self.quantizer.step_update(self._num_updates)
-        metrics.log_scalar("num_updates", self._num_updates, weight=0, priority=200)
-
-    def clip_grad_norm(self, clip_norm):
-        def agg_norm_fn(total_norm):
-            total_norm = total_norm.cuda().float() ** 2
-            total_norm = distributed_utils.all_reduce(
-                total_norm, group=self.data_parallel_process_group
-            )
-            return total_norm ** 0.5
-
-        should_agg_norm = (
-            self.is_fsdp
-            and (
-                self.data_parallel_process_group is not None
-                or torch.distributed.is_initialized()
-            )
-        )
-        return self.optimizer.clip_grad_norm(
-            clip_norm, aggregate_norm_fn=agg_norm_fn if should_agg_norm else None
-        )
-
-    def cumulative_training_time(self):
-        if self._cumulative_training_time is None:
-            # single GPU
-            return self._local_cumulative_training_time()
-        else:
-            return self._cumulative_training_time
-
-    def _local_cumulative_training_time(self):
-        """Aggregate training time in seconds."""
-        return time.time() - self._start_time + self._previous_training_time
-
-    def _fp_convert_sample(self, sample):
-        def apply_half(t):
-            if t.dtype is torch.float32:
-                return t.to(dtype=torch.half)
-            return t
-
-        def apply_bfloat16(t):
-            if t.dtype is torch.float32:
-                return t.to(dtype=torch.bfloat16)
-            return t
-
-        if self.cfg.common.fp16:
-            sample = utils.apply_to_sample(apply_half, sample)
-
-        if self.cfg.common.bf16:
-            sample = utils.apply_to_sample(apply_bfloat16, sample)
-
-        return sample
-
-    def _prepare_sample(self, sample, is_dummy=False):
-        if sample == "DUMMY":
-            raise Exception(
-                "Trying to use an uninitialized 'dummy' batch. This usually indicates "
-                "that the total number of batches is smaller than the number of "
-                "participating GPUs. Try reducing the batch size or using fewer GPUs."
-            )
-
-        if sample is None or len(sample) == 0:
-            assert (
-                self._dummy_batch is not None and len(self._dummy_batch) > 0
-            ), "Invalid dummy batch: {}".format(self._dummy_batch)
-            sample, _ = self._prepare_sample(self._dummy_batch, is_dummy=True)
-            return sample, True
-
-        # Given that PCIe/NVLink bandwidth is significantly smaller than DRAM bandwidth
-        # it makes sense to do the format conversion on the CPU and then transfer
-        # a smaller buffer to the device. This also saves GPU memory capacity.
-
-        if self.cfg.common.on_cpu_convert_precision:
-            sample = self._fp_convert_sample(sample)
-
-        if self.cuda:
-            if self.pipeline_model_parallel:
-                if 'target' in sample:
-                    sample['target'] = utils.move_to_cuda(sample['target'], device=self.last_device)
-            else:
-                sample = utils.move_to_cuda(sample)
-        elif self.tpu and is_dummy:
-            # the dummy batch may not be on the appropriate device
-            sample = utils.move_to_cuda(sample, device=self.device)
-
-        if not self.cfg.common.on_cpu_convert_precision:
-            sample = self._fp_convert_sample(sample)
-
-        if self._dummy_batch == "DUMMY":
-            self._dummy_batch = sample
-
-        return sample, False
-
-    def _set_seed(self):
-        # Set seed based on args.seed and the update number so that we get
-        # reproducible results when resuming from checkpoints
-        seed = self.cfg.common.seed + self.get_num_updates()
-        utils.set_torch_seed(seed)
-
-    def _sync_stats(self):
-        # Return True if it's using multiple GPUs and DDP or multiple GPUs with
-        # BMUF and it's a bmuf sync with warmup iterations completed before.
-        if self.data_parallel_world_size == 1:
-            return False
-        elif self.cfg.optimization.use_bmuf:
-            return (
-                self.get_num_updates() + 1
-            ) % self.cfg.bmuf.global_sync_iter == 0 and (
-                self.get_num_updates() + 1
-            ) > self.cfg.bmuf.warmup_iterations
-        else:
-            return True
-
-    def _log_oom(self, exc):
-        msg = "OOM: Ran out of memory with exception: {}".format(exc)
-        logger.warning(msg)
-        if torch.cuda.is_available() and hasattr(torch.cuda, "memory_summary"):
-            for device_idx in range(torch.cuda.device_count()):
-                logger.warning(torch.cuda.memory_summary(device=device_idx))
-        sys.stderr.flush()
-
-    def _aggregate_logging_outputs(
-        self,
-        logging_outputs: List[Dict[str, Any]],
-        *extra_stats_to_sum,
-        ignore=False,
-    ):
-        if self.task.__class__.logging_outputs_can_be_summed(self.get_criterion()):
-            return self._fast_stat_sync_sum(
-                logging_outputs, *extra_stats_to_sum, ignore=ignore
-            )
-        else:
-            return self._all_gather_list_sync(
-                logging_outputs, *extra_stats_to_sum, ignore=ignore
-            )
-
-    def _all_gather_list_sync(
-        self,
-        logging_outputs: List[Dict[str, Any]],
-        *extra_stats_to_sum,
-        ignore=False,
-    ):
-        """
-        Sync logging outputs across workers. all_gather_list_sync is
-        suitable when logging outputs are complex types.
-        """
-        if self.tpu:
-            raise NotImplementedError
-        if ignore:
-            logging_outputs = []
-        results = list(
-            zip(
-                *distributed_utils.all_gather_list(
-                    [logging_outputs] + list(extra_stats_to_sum),
-                    max_size=getattr(self.cfg.common, "all_gather_list_size", 16384),
-                    group=self.data_parallel_process_group,
-                )
-            )
-        )
-        logging_outputs, extra_stats_to_sum = results[0], results[1:]
-        logging_outputs = list(chain.from_iterable(logging_outputs))
-        extra_stats_to_sum = [sum(s) for s in extra_stats_to_sum]
-        return logging_outputs, extra_stats_to_sum
-
-    def _fast_stat_sync_sum(
-        self,
-        logging_outputs: List[Dict[str, Any]],
-        *extra_stats_to_sum,
-        ignore=False,
-    ):
-        """
-        Sync logging outputs across workers. fast_stat_sync_sum is
-        faster than all_gather_list_sync, but is only suitable when
-        logging outputs are scalars and can be summed. Note that
-        *logging_outputs* cannot contain any nested dicts/lists.
-        """
-        data = {}
-        for i, stat in enumerate(extra_stats_to_sum):
-            data["extra_stats_" + str(i)] = stat
-        if len(logging_outputs) > 0:
-            log_keys = list(logging_outputs[0].keys())
-            for k in log_keys:
-                if not ignore:
-                    v = sum(log[k] for log in logging_outputs if k in log)
-                else:
-                    v = logging_outputs[0][k]
-                    v = torch.zeros_like(v) if torch.is_tensor(v) else 0
-                data["logging_outputs_" + k] = v
-        else:
-            log_keys = None
-
-        data = distributed_utils.all_reduce_dict(
-            data, device=self.device, group=self.data_parallel_process_group
-        )
-
-        extra_stats_to_sum = [
-            data["extra_stats_" + str(i)] for i in range(len(extra_stats_to_sum))
-        ]
-        if log_keys is not None:
-            logging_outputs = [{k: data["logging_outputs_" + k] for k in log_keys}]
-        else:
-            logging_outputs = []
-        return logging_outputs, extra_stats_to_sum
-
-    def _check_grad_norms(self, grad_norm):
-        """Check that grad norms are consistent across workers."""
-        if self._grad_norm_buf is not None:
-            self._grad_norm_buf.zero_()
-            self._grad_norm_buf[self.data_parallel_rank] = grad_norm
-            distributed_utils.all_reduce(
-                self._grad_norm_buf, group=self.data_parallel_process_group
-            )
-
-            def is_consistent(tensor):
-                max_abs_diff = torch.max(torch.abs(tensor - tensor[0]))
-                return (
-                    (torch.isfinite(tensor).all()
-                     and (max_abs_diff / (tensor[0] + 1e-6) < 1e-6).all())
-                    or
-                    (self.cfg.common.amp and not torch.isfinite(tensor).all())
-                    # in case of amp non-finite grads are fine
-                )
-
-            if not is_consistent(self._grad_norm_buf):
-                pretty_detail = "\n".join(
-                    "rank {:3d} = {:.8f}".format(r, n)
-                    for r, n in enumerate(self._grad_norm_buf.tolist())
-                )
-                error_detail = "grad_norm across the workers:\n{}\n".format(
-                    pretty_detail
-                )
-                # use FloatingPointError to trigger NanDetector
-                raise FloatingPointError(
-                    "Fatal error: gradients are inconsistent between workers. "
-                    "Try --ddp-backend=legacy_ddp. "
-                    "Or are you mixing up different generation of GPUs in training?"
-                    + "\n"
-                    + "-" * 80
-                    + "\n{}\n".format(error_detail)
-                    + "-" * 80
-                )
-
-    def _reduce_and_log_stats(self, logging_outputs, sample_size, grad_norm=None):
-        if grad_norm is not None and (
-            not torch.is_tensor(grad_norm) or torch.isfinite(grad_norm)
-        ):
-            metrics.log_speed("ups", 1.0, priority=100, round=2)
-            metrics.log_scalar("gnorm", grad_norm, priority=400, round=3)
-            if self.cfg.optimization.clip_norm > 0:
-                metrics.log_scalar(
-                    "clip",
-                    torch.where(
-                        grad_norm > self.cfg.optimization.clip_norm,
-                        grad_norm.new_tensor(100),
-                        grad_norm.new_tensor(0),
-                    ),
-                    priority=500,
-                    round=1,
-                )
-
-        with metrics.aggregate() as agg:
-            if logging_outputs is not None:
-                self.task.reduce_metrics(logging_outputs, self.get_criterion())
-                del logging_outputs
-
-            # extra warning for criterions that don't properly log a loss value
-            if "loss" not in agg:
-                if "loss" not in self._warn_once:
-                    self._warn_once.add("loss")
-                    logger.warning(
-                        "Criterion.reduce_metrics did not log a 'loss' value, "
-                        "which may break some functionality"
-                    )
-                metrics.log_scalar("loss", -1)
-
-            # support legacy interface
-            if self.tpu:
-                logging_output = {}
-            else:
-                logging_output = agg.get_smoothed_values()
-                logging_output["sample_size"] = sample_size
-                for key_to_delete in ["ppl", "wps", "wpb", "bsz"]:
-                    if key_to_delete in logging_output:
-                        del logging_output[key_to_delete]
-            return logging_output
-
-    def _check_xla_compilation(self):
-        import torch_xla.debug.metrics as met
-
-        compile_stats = met.metric_data("CompileTime")
-        if compile_stats is None:
-            return
-        num_xla_compiles = compile_stats[0]
-        if num_xla_compiles > self._num_xla_compiles:
-            logger.warning(
-                "XLA compilation detected on device #{}; too many of these can lead "
-                "to slow training, but we expect a few in the beginning".format(
-                    self.cfg.distributed_training.distributed_rank
-                )
-            )
-        self._num_xla_compiles = num_xla_compiles
-
-    def _xla_markstep_and_send_to_cpu(self, data=None):
-        import torch_xla.core.xla_model as xm
-
-        xm.mark_step()
-        if data is not None:
-            from fairseq.utils import xla_device_to_cpu
-
-            return xla_device_to_cpu(data)
-
-
-def _catalog_shared_params(module, memo=None, prefix=""):
-    if memo is None:
-        first_call = True
-        memo = {}
-    else:
-        first_call = False
-    for name, param in module._parameters.items():
-        param_prefix = prefix + ("." if prefix else "") + name
-        if param not in memo:
-            memo[param] = []
-        memo[param].append(param_prefix)
-    for name, m in module._modules.items():
-        if m is None:
-            continue
-        submodule_prefix = prefix + ("." if prefix else "") + name
-        _catalog_shared_params(m, memo, submodule_prefix)
-    if first_call:
-        return [x for x in memo.values() if len(x) > 1]
-
-
-def _get_module_by_path(module, path):
-    path = path.split(".")
-    for name in path:
-        module = getattr(module, name)
-    return module
-
-
-def _set_module_by_path(module, path, value):
-    path = path.split(".")
-    for name in path[:-1]:
-        module = getattr(module, name)
-    setattr(module, path[-1], value)
diff --git a/spaces/OpenDILabCommunity/DI-sheep/DI-sheep/service/test_sheep_env.py b/spaces/OpenDILabCommunity/DI-sheep/DI-sheep/service/test_sheep_env.py
deleted file mode 100644
index 66c66d16e28f82957abbeacb40b1bcef394c0798..0000000000000000000000000000000000000000
--- a/spaces/OpenDILabCommunity/DI-sheep/DI-sheep/service/test_sheep_env.py
+++ /dev/null
@@ -1,23 +0,0 @@
-import pytest
-import numpy as np
-from sheep_env import SheepEnv
-
-
-@pytest.mark.unittest
-def test_naive():
-    env = SheepEnv(level=9)
-    obs = env.reset()
-    print(env.observation_space)
-
-    while True:
-        action_mask = obs['action_mask']
-        action = np.random.choice(len(action_mask), p=action_mask / action_mask.sum())
-        obs, rew, done, info = env.step(action)
-        print(env.bucket, rew, done)
-        assert isinstance(obs, dict)
-        assert set(obs.keys()) == set(['item_obs', 'bucket_obs', 'global_obs', 'action_mask'])
-        assert np.isscalar(rew)
-        assert isinstance(done, bool)
-        assert isinstance(info, dict)
-        if done:
-            break
diff --git a/spaces/OpenDILabCommunity/LLMRiddlesChatGPTEN/llmriddles/questions/question.py b/spaces/OpenDILabCommunity/LLMRiddlesChatGPTEN/llmriddles/questions/question.py
deleted file mode 100644
index 111ecaf108ff6dda532bdff63ef3241948899291..0000000000000000000000000000000000000000
--- a/spaces/OpenDILabCommunity/LLMRiddlesChatGPTEN/llmriddles/questions/question.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import collections.abc
-from dataclasses import dataclass
-from typing import Union, Mapping, Literal, Callable, Tuple, List, Optional
-
-LangTyping = Literal['en', 'cn']
-MultiLangCheckerTyping = Callable[[str, str, str, str], Tuple[bool, Optional[str]]]
-SingleLangCheckerTyping = Callable[[str, str, str], Tuple[bool, Optional[str]]]
-
-
-@dataclass
-class Question:
-    texts: Mapping[str, str]
-    checker: MultiLangCheckerTyping
-    names: Mapping[str, str]
-    level: int
-
-
-_KNOWN_PROBLEMS = []
-
-
-def register_question(text: Union[Mapping[str, str], str],
-                      checkers: Union[Mapping[str, SingleLangCheckerTyping], MultiLangCheckerTyping],
-                      name=Union[Mapping[str, str], str],
-                      level: int = 1, default_lang='cn'):
-    if isinstance(checkers, collections.abc.Mapping):
-        _origin_checkers = checkers
-
-        def _integrated_checker(question_text: str, user_text: str, answer_text: str, lang: str):
-            return _origin_checkers[lang](question_text, user_text, answer_text)
-
-        checker: MultiLangCheckerTyping = _integrated_checker
-    else:
-        checker: MultiLangCheckerTyping = checkers
-
-    if isinstance(text, str):
-        texts = {default_lang: text}
-    else:
-        texts = text
-
-    if isinstance(name, str):
-        names = {default_lang: name}
-    else:
-        names = name
-
-    _KNOWN_PROBLEMS.append(Question(texts, checker, names, level))
-
-
-def list_ordered_questions() -> List[Question]:
-    return [
-        problem for _, problem in
-        sorted(enumerate(_KNOWN_PROBLEMS), key=lambda x: (x[1].level, x[0]))
-    ]
diff --git a/spaces/OpenGVLab/DragGAN/stylegan2/lpips/util.py b/spaces/OpenGVLab/DragGAN/stylegan2/lpips/util.py
deleted file mode 100644
index 4f8b5826cb4ff0614f1ab9bb273af551a3c82311..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/DragGAN/stylegan2/lpips/util.py
+++ /dev/null
@@ -1,160 +0,0 @@
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-from skimage.metrics import structural_similarity
-import torch
-
-
-from . import dist_model
-
-class PerceptualLoss(torch.nn.Module):
-    def __init__(self, model='net-lin', net='alex', colorspace='rgb', spatial=False, use_gpu=True, gpu_ids=[0]): # VGG using our perceptually-learned weights (LPIPS metric)
-    # def __init__(self, model='net', net='vgg', use_gpu=True): # "default" way of using VGG as a perceptual loss
-        super(PerceptualLoss, self).__init__()
-        print('Setting up Perceptual loss...')
-        self.use_gpu = use_gpu
-        self.spatial = spatial
-        self.gpu_ids = gpu_ids
-        self.model = dist_model.DistModel()
-        self.model.initialize(model=model, net=net, use_gpu=use_gpu, colorspace=colorspace, spatial=self.spatial, gpu_ids=gpu_ids)
-        print('...[%s] initialized'%self.model.name())
-        print('...Done')
-
-    def forward(self, pred, target, normalize=False):
-        """
-        Pred and target are Variables.
-        If normalize is True, assumes the images are between [0,1] and then scales them between [-1,+1]
-        If normalize is False, assumes the images are already between [-1,+1]
-
-        Inputs pred and target are Nx3xHxW
-        Output pytorch Variable N long
-        """
-
-        if normalize:
-            target = 2 * target  - 1
-            pred = 2 * pred  - 1
-
-        return self.model.forward(target, pred)
-
-def normalize_tensor(in_feat,eps=1e-10):
-    norm_factor = torch.sqrt(torch.sum(in_feat**2,dim=1,keepdim=True))
-    return in_feat/(norm_factor+eps)
-
-def l2(p0, p1, range=255.):
-    return .5*np.mean((p0 / range - p1 / range)**2)
-
-def psnr(p0, p1, peak=255.):
-    return 10*np.log10(peak**2/np.mean((1.*p0-1.*p1)**2))
-
-def dssim(p0, p1, range=255.):
-    return (1 - structural_similarity(p0, p1, data_range=range, multichannel=True)) / 2.
-
-def rgb2lab(in_img,mean_cent=False):
-    from skimage import color
-    img_lab = color.rgb2lab(in_img)
-    if(mean_cent):
-        img_lab[:,:,0] = img_lab[:,:,0]-50
-    return img_lab
-
-def tensor2np(tensor_obj):
-    # change dimension of a tensor object into a numpy array
-    return tensor_obj[0].cpu().float().numpy().transpose((1,2,0))
-
-def np2tensor(np_obj):
-     # change dimenion of np array into tensor array
-    return torch.Tensor(np_obj[:, :, :, np.newaxis].transpose((3, 2, 0, 1)))
-
-def tensor2tensorlab(image_tensor,to_norm=True,mc_only=False):
-    # image tensor to lab tensor
-    from skimage import color
-
-    img = tensor2im(image_tensor)
-    img_lab = color.rgb2lab(img)
-    if(mc_only):
-        img_lab[:,:,0] = img_lab[:,:,0]-50
-    if(to_norm and not mc_only):
-        img_lab[:,:,0] = img_lab[:,:,0]-50
-        img_lab = img_lab/100.
-
-    return np2tensor(img_lab)
-
-def tensorlab2tensor(lab_tensor,return_inbnd=False):
-    from skimage import color
-    import warnings
-    warnings.filterwarnings("ignore")
-
-    lab = tensor2np(lab_tensor)*100.
-    lab[:,:,0] = lab[:,:,0]+50
-
-    rgb_back = 255.*np.clip(color.lab2rgb(lab.astype('float')),0,1)
-    if(return_inbnd):
-        # convert back to lab, see if we match
-        lab_back = color.rgb2lab(rgb_back.astype('uint8'))
-        mask = 1.*np.isclose(lab_back,lab,atol=2.)
-        mask = np2tensor(np.prod(mask,axis=2)[:,:,np.newaxis])
-        return (im2tensor(rgb_back),mask)
-    else:
-        return im2tensor(rgb_back)
-
-def rgb2lab(input):
-    from skimage import color
-    return color.rgb2lab(input / 255.)
-
-def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=255./2.):
-    image_numpy = image_tensor[0].cpu().float().numpy()
-    image_numpy = (np.transpose(image_numpy, (1, 2, 0)) + cent) * factor
-    return image_numpy.astype(imtype)
-
-def im2tensor(image, imtype=np.uint8, cent=1., factor=255./2.):
-    return torch.Tensor((image / factor - cent)
-                        [:, :, :, np.newaxis].transpose((3, 2, 0, 1)))
-
-def tensor2vec(vector_tensor):
-    return vector_tensor.data.cpu().numpy()[:, :, 0, 0]
-
-def voc_ap(rec, prec, use_07_metric=False):
-    """ ap = voc_ap(rec, prec, [use_07_metric])
-    Compute VOC AP given precision and recall.
-    If use_07_metric is true, uses the
-    VOC 07 11 point method (default:False).
-    """
-    if use_07_metric:
-        # 11 point metric
-        ap = 0.
-        for t in np.arange(0., 1.1, 0.1):
-            if np.sum(rec >= t) == 0:
-                p = 0
-            else:
-                p = np.max(prec[rec >= t])
-            ap = ap + p / 11.
-    else:
-        # correct AP calculation
-        # first append sentinel values at the end
-        mrec = np.concatenate(([0.], rec, [1.]))
-        mpre = np.concatenate(([0.], prec, [0.]))
-
-        # compute the precision envelope
-        for i in range(mpre.size - 1, 0, -1):
-            mpre[i - 1] = np.maximum(mpre[i - 1], mpre[i])
-
-        # to calculate area under PR curve, look for points
-        # where X axis (recall) changes value
-        i = np.where(mrec[1:] != mrec[:-1])[0]
-
-        # and sum (\Delta recall) * prec
-        ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1])
-    return ap
-
-def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=255./2.):
-# def tensor2im(image_tensor, imtype=np.uint8, cent=1., factor=1.):
-    image_numpy = image_tensor[0].cpu().float().numpy()
-    image_numpy = (np.transpose(image_numpy, (1, 2, 0)) + cent) * factor
-    return image_numpy.astype(imtype)
-
-def im2tensor(image, imtype=np.uint8, cent=1., factor=255./2.):
-# def im2tensor(image, imtype=np.uint8, cent=1., factor=1.):
-    return torch.Tensor((image / factor - cent)
-                        [:, :, :, np.newaxis].transpose((3, 2, 0, 1)))
diff --git a/spaces/PBJ/image_colorization_app/README.md b/spaces/PBJ/image_colorization_app/README.md
deleted file mode 100644
index 24412f2a0e7cb3983124a73b2bbd34fc258b7509..0000000000000000000000000000000000000000
--- a/spaces/PBJ/image_colorization_app/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Image Colorization App
-emoji: 🌈
-colorFrom: yellow
-colorTo: yellow
-sdk: streamlit
-sdk_version: 1.15.2
-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/PSLD/PSLD/diffusion-posterior-sampling/bkse/train.py b/spaces/PSLD/PSLD/diffusion-posterior-sampling/bkse/train.py
deleted file mode 100644
index 8d34cf05d9cb764bcf785c06f4da8083adf2a625..0000000000000000000000000000000000000000
--- a/spaces/PSLD/PSLD/diffusion-posterior-sampling/bkse/train.py
+++ /dev/null
@@ -1,320 +0,0 @@
-import argparse
-import logging
-import math
-import os
-import random
-
-import numpy as np
-import options.options as option
-import torch
-import torch.distributed as dist
-import torch.multiprocessing as mp
-from data import create_dataloader, create_dataset
-from data.data_sampler import DistIterSampler
-from models import create_model
-from utils import util
-
-
-def init_dist(backend="nccl", **kwargs):
-    """initialization for distributed training"""
-    if mp.get_start_method(allow_none=True) != "spawn":
-        mp.set_start_method("spawn")
-    rank = int(os.environ["RANK"])
-    num_gpus = torch.cuda.device_count()
-    torch.cuda.set_device(rank % num_gpus)
-    dist.init_process_group(backend=backend, **kwargs)
-
-
-def main():
-    # options
-    parser = argparse.ArgumentParser()
-    parser.add_argument("-opt", type=str, help="Path to option YAML file.")
-    parser.add_argument("--launcher", choices=["none", "pytorch"], default="none", help="job launcher")
-    parser.add_argument("--local_rank", type=int, default=0)
-    args = parser.parse_args()
-    opt = option.parse(args.opt, is_train=True)
-
-    # distributed training settings
-    if args.launcher == "none":  # disabled distributed training
-        opt["dist"] = False
-        rank = -1
-        print("Disabled distributed training.")
-    else:
-        opt["dist"] = True
-        init_dist()
-        world_size = torch.distributed.get_world_size()
-        rank = torch.distributed.get_rank()
-
-    # loading resume state if exists
-    if opt["path"].get("resume_state", None):
-        # distributed resuming: all load into default GPU
-        device_id = torch.cuda.current_device()
-        resume_state = torch.load(
-            opt["path"]["resume_state"], map_location=lambda storage, loc: storage.cuda(device_id)
-        )
-        option.check_resume(opt, resume_state["iter"])  # check resume options
-    else:
-        resume_state = None
-
-    # mkdir and loggers
-    if rank <= 0:  # normal training (rank -1) OR distributed training (rank 0)
-        if resume_state is None:
-            util.mkdir_and_rename(opt["path"]["experiments_root"])  # rename experiment folder if exists
-            util.mkdirs(
-                (
-                    path
-                    for key, path in opt["path"].items()
-                    if not key == "experiments_root" and "pretrain_model" not in key and "resume" not in key
-                )
-            )
-
-        # config loggers. Before it, the log will not work
-        util.setup_logger(
-            "base", opt["path"]["log"], "train_" + opt["name"], level=logging.INFO, screen=True, tofile=True
-        )
-        logger = logging.getLogger("base")
-        logger.info(option.dict2str(opt))
-        # tensorboard logger
-        if opt["use_tb_logger"] and "debug" not in opt["name"]:
-            version = float(torch.__version__[0:3])
-            if version >= 1.1:  # PyTorch 1.1
-                from torch.utils.tensorboard import SummaryWriter
-            else:
-                logger.info(
-                    "You are using PyTorch {}. \
-                            Tensorboard will use [tensorboardX]".format(
-                        version
-                    )
-                )
-                from tensorboardX import SummaryWriter
-            tb_logger = SummaryWriter(log_dir="../tb_logger/" + opt["name"])
-    else:
-        util.setup_logger("base", opt["path"]["log"], "train", level=logging.INFO, screen=True)
-        logger = logging.getLogger("base")
-
-    # convert to NoneDict, which returns None for missing keys
-    opt = option.dict_to_nonedict(opt)
-
-    # random seed
-    seed = opt["train"]["manual_seed"]
-    if seed is None:
-        seed = random.randint(1, 10000)
-    if rank <= 0:
-        logger.info("Random seed: {}".format(seed))
-    util.set_random_seed(seed)
-
-    torch.backends.cudnn.benchmark = True
-    # torch.backends.cudnn.deterministic = True
-
-    # create train and val dataloader
-    dataset_ratio = 200  # enlarge the size of each epoch
-    for phase, dataset_opt in opt["datasets"].items():
-        if phase == "train":
-            train_set = create_dataset(dataset_opt)
-            train_size = int(math.ceil(len(train_set) / dataset_opt["batch_size"]))
-            total_iters = int(opt["train"]["niter"])
-            total_epochs = int(math.ceil(total_iters / train_size))
-            if opt["dist"]:
-                train_sampler = DistIterSampler(train_set, world_size, rank, dataset_ratio)
-                total_epochs = int(math.ceil(total_iters / (train_size * dataset_ratio)))
-            else:
-                train_sampler = None
-            train_loader = create_dataloader(train_set, dataset_opt, opt, train_sampler)
-            if rank <= 0:
-                logger.info("Number of train images: {:,d}, iters: {:,d}".format(len(train_set), train_size))
-                logger.info("Total epochs needed: {:d} for iters {:,d}".format(total_epochs, total_iters))
-        elif phase == "val":
-            val_set = create_dataset(dataset_opt)
-            val_loader = create_dataloader(val_set, dataset_opt, opt, None)
-            if rank <= 0:
-                logger.info("Number of val images in [{:s}]: {:d}".format(dataset_opt["name"], len(val_set)))
-        else:
-            raise NotImplementedError("Phase [{:s}] is not recognized.".format(phase))
-    assert train_loader is not None
-
-    # create model
-    model = create_model(opt)
-    print("Model created!")
-
-    # resume training
-    if resume_state:
-        logger.info("Resuming training from epoch: {}, iter: {}.".format(resume_state["epoch"], resume_state["iter"]))
-
-        start_epoch = resume_state["epoch"]
-        current_step = resume_state["iter"]
-        model.resume_training(resume_state)  # handle optimizers and schedulers
-    else:
-        current_step = 0
-        start_epoch = 0
-
-    # training
-    logger.info("Start training from epoch: {:d}, iter: {:d}".format(start_epoch, current_step))
-    for epoch in range(start_epoch, total_epochs + 1):
-        if opt["dist"]:
-            train_sampler.set_epoch(epoch)
-        for _, train_data in enumerate(train_loader):
-            current_step += 1
-            if current_step > total_iters:
-                break
-            # update learning rate
-            model.update_learning_rate(current_step, warmup_iter=opt["train"]["warmup_iter"])
-
-            # training
-            model.feed_data(train_data)
-            model.optimize_parameters(current_step)
-
-            # log
-            if current_step % opt["logger"]["print_freq"] == 0:
-                logs = model.get_current_log()
-                message = "[epoch:{:3d}, iter:{:8,d}, lr:(".format(epoch, current_step)
-                for v in model.get_current_learning_rate():
-                    message += "{:.3e},".format(v)
-                message += ")] "
-                for k, v in logs.items():
-                    message += "{:s}: {:.4e} ".format(k, v)
-                    # tensorboard logger
-                    if opt["use_tb_logger"] and "debug" not in opt["name"]:
-                        if rank <= 0:
-                            tb_logger.add_scalar(k, v, current_step)
-                if rank <= 0:
-                    logger.info(message)
-            # validation
-            if opt["datasets"].get("val", None) and current_step % opt["train"]["val_freq"] == 0:
-                # image restoration validation
-                if opt["model"] in ["sr", "srgan"] and rank <= 0:
-                    # does not support multi-GPU validation
-                    pbar = util.ProgressBar(len(val_loader))
-                    avg_psnr = 0.0
-                    idx = 0
-                    for val_data in val_loader:
-                        idx += 1
-                        img_name = os.path.splitext(os.path.basename(val_data["LQ_path"][0]))[0]
-                        img_dir = os.path.join(opt["path"]["val_images"], img_name)
-                        util.mkdir(img_dir)
-
-                        model.feed_data(val_data)
-                        model.test()
-
-                        visuals = model.get_current_visuals()
-                        sr_img = util.tensor2img(visuals["rlt"])  # uint8
-                        gt_img = util.tensor2img(visuals["GT"])  # uint8
-
-                        # Save SR images for reference
-                        save_img_path = os.path.join(img_dir, "{:s}_{:d}.png".format(img_name, current_step))
-                        util.save_img(sr_img, save_img_path)
-
-                        # calculate PSNR
-                        sr_img, gt_img = util.crop_border([sr_img, gt_img], opt["scale"])
-                        avg_psnr += util.calculate_psnr(sr_img, gt_img)
-                        pbar.update("Test {}".format(img_name))
-
-                    avg_psnr = avg_psnr / idx
-
-                    # log
-                    logger.info("# Validation # PSNR: {:.4e}".format(avg_psnr))
-                    # tensorboard logger
-                    if opt["use_tb_logger"] and "debug" not in opt["name"]:
-                        tb_logger.add_scalar("psnr", avg_psnr, current_step)
-                else:  # video restoration validation
-                    if opt["dist"]:
-                        # multi-GPU testing
-                        psnr_rlt = {}  # with border and center frames
-                        if rank == 0:
-                            pbar = util.ProgressBar(len(val_set))
-                        for idx in range(rank, len(val_set), world_size):
-                            val_data = val_set[idx]
-                            val_data["LQs"].unsqueeze_(0)
-                            val_data["GT"].unsqueeze_(0)
-                            folder = val_data["folder"]
-                            idx_d, max_idx = val_data["idx"].split("/")
-                            idx_d, max_idx = int(idx_d), int(max_idx)
-                            if psnr_rlt.get(folder, None) is None:
-                                psnr_rlt[folder] = torch.zeros(max_idx, dtype=torch.float32, device="cuda")
-                            model.feed_data(val_data)
-                            model.test()
-                            visuals = model.get_current_visuals()
-                            rlt_img = util.tensor2img(visuals["rlt"])  # uint8
-                            gt_img = util.tensor2img(visuals["GT"])  # uint8
-                            # calculate PSNR
-                            psnr_rlt[folder][idx_d] = util.calculate_psnr(rlt_img, gt_img)
-
-                            if rank == 0:
-                                for _ in range(world_size):
-                                    pbar.update("Test {} - {}/{}".format(folder, idx_d, max_idx))
-                        # collect data
-                        for _, v in psnr_rlt.items():
-                            dist.reduce(v, 0)
-                        dist.barrier()
-
-                        if rank == 0:
-                            psnr_rlt_avg = {}
-                            psnr_total_avg = 0.0
-                            for k, v in psnr_rlt.items():
-                                psnr_rlt_avg[k] = torch.mean(v).cpu().item()
-                                psnr_total_avg += psnr_rlt_avg[k]
-                            psnr_total_avg /= len(psnr_rlt)
-                            log_s = "# Validation # PSNR: {:.4e}:".format(psnr_total_avg)
-                            for k, v in psnr_rlt_avg.items():
-                                log_s += " {}: {:.4e}".format(k, v)
-                            logger.info(log_s)
-                            if opt["use_tb_logger"] and "debug" not in opt["name"]:
-                                tb_logger.add_scalar("psnr_avg", psnr_total_avg, current_step)
-                                for k, v in psnr_rlt_avg.items():
-                                    tb_logger.add_scalar(k, v, current_step)
-                    else:
-                        pbar = util.ProgressBar(len(val_loader))
-                        psnr_rlt = {}  # with border and center frames
-                        psnr_rlt_avg = {}
-                        psnr_total_avg = 0.0
-                        for val_data in val_loader:
-                            folder = val_data["folder"][0]
-                            idx_d, max_id = val_data["idx"][0].split("/")
-                            # border = val_data['border'].item()
-                            if psnr_rlt.get(folder, None) is None:
-                                psnr_rlt[folder] = []
-
-                            model.feed_data(val_data)
-                            model.test()
-                            visuals = model.get_current_visuals()
-                            rlt_img = util.tensor2img(visuals["rlt"])  # uint8
-                            gt_img = util.tensor2img(visuals["GT"])  # uint8
-                            lq_img = util.tensor2img(visuals["LQ"][2])  # uint8
-
-                            img_dir = opt["path"]["val_images"]
-                            util.mkdir(img_dir)
-                            save_img_path = os.path.join(img_dir, "{}.png".format(idx_d))
-                            util.save_img(np.hstack((lq_img, rlt_img, gt_img)), save_img_path)
-
-                            # calculate PSNR
-                            psnr = util.calculate_psnr(rlt_img, gt_img)
-                            psnr_rlt[folder].append(psnr)
-                            pbar.update("Test {} - {}".format(folder, idx_d))
-                        for k, v in psnr_rlt.items():
-                            psnr_rlt_avg[k] = sum(v) / len(v)
-                            psnr_total_avg += psnr_rlt_avg[k]
-                        psnr_total_avg /= len(psnr_rlt)
-                        log_s = "# Validation # PSNR: {:.4e}:".format(psnr_total_avg)
-                        for k, v in psnr_rlt_avg.items():
-                            log_s += " {}: {:.4e}".format(k, v)
-                        logger.info(log_s)
-                        if opt["use_tb_logger"] and "debug" not in opt["name"]:
-                            tb_logger.add_scalar("psnr_avg", psnr_total_avg, current_step)
-                            for k, v in psnr_rlt_avg.items():
-                                tb_logger.add_scalar(k, v, current_step)
-
-            # save models and training states
-            if current_step % opt["logger"]["save_checkpoint_freq"] == 0:
-                if rank <= 0:
-                    logger.info("Saving models and training states.")
-                    model.save(current_step)
-                    model.save_training_state(epoch, current_step)
-
-    if rank <= 0:
-        logger.info("Saving the final model.")
-        model.save("latest")
-        logger.info("End of training.")
-        tb_logger.close()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/srfi/srfi-35.go b/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/srfi/srfi-35.go
deleted file mode 100644
index fd927669a7828bbfe6150e29f415c79500da535e..0000000000000000000000000000000000000000
Binary files a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/srfi/srfi-35.go and /dev/null differ
diff --git a/spaces/Plurigrid/LifeSim/src/components/ui/textarea.tsx b/spaces/Plurigrid/LifeSim/src/components/ui/textarea.tsx
deleted file mode 100644
index af10d34eeae448c2614c67141f83a8748754332c..0000000000000000000000000000000000000000
--- a/spaces/Plurigrid/LifeSim/src/components/ui/textarea.tsx
+++ /dev/null
@@ -1,24 +0,0 @@
-import * as React from "react"
-
-import { cn } from "@/lib/utils"
-
-export interface TextareaProps
-  extends React.TextareaHTMLAttributes<HTMLTextAreaElement> {}
-
-const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
-  ({ className, ...props }, ref) => {
-    return (
-      <textarea
-        className={cn(
-          "flex min-h-[80px] w-full rounded-md border border-stone-200 border-stone-200 bg-transparent px-3 py-2 text-sm ring-offset-white placeholder:text-stone-500 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-stone-400 focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 dark:border-stone-800 dark:border-stone-800 dark:ring-offset-stone-950 dark:placeholder:text-stone-400 dark:focus-visible:ring-stone-800",
-          className
-        )}
-        ref={ref}
-        {...props}
-      />
-    )
-  }
-)
-Textarea.displayName = "Textarea"
-
-export { Textarea }
diff --git a/spaces/Prashanth35/Chit_Chat/README.md b/spaces/Prashanth35/Chit_Chat/README.md
deleted file mode 100644
index 1faff651e858ea07be2d24014ee632df016e47fd..0000000000000000000000000000000000000000
--- a/spaces/Prashanth35/Chit_Chat/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Chit Chat
-emoji: 💻
-colorFrom: green
-colorTo: blue
-sdk: gradio
-sdk_version: 3.40.1
-app_file: app.py
-pinned: false
-license: other
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/losses/sisnr.py b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/losses/sisnr.py
deleted file mode 100644
index 30f1fa1de9aca22758b6665609a1eacc0bd992ca..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/losses/sisnr.py
+++ /dev/null
@@ -1,92 +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 math
-import typing as tp
-
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-
-def _unfold(a: torch.Tensor, kernel_size: int, stride: int) -> torch.Tensor:
-    """Given input of size [*OT, T], output Tensor of size [*OT, F, K]
-    with K the kernel size, by extracting frames with the given stride.
-    This will pad the input so that `F = ceil(T / K)`.
-    see https://github.com/pytorch/pytorch/issues/60466
-    """
-    *shape, length = a.shape
-    n_frames = math.ceil(length / stride)
-    tgt_length = (n_frames - 1) * stride + kernel_size
-    a = F.pad(a, (0, tgt_length - length))
-    strides = list(a.stride())
-    assert strides[-1] == 1, "data should be contiguous"
-    strides = strides[:-1] + [stride, 1]
-    return a.as_strided([*shape, n_frames, kernel_size], strides)
-
-
-def _center(x: torch.Tensor) -> torch.Tensor:
-    return x - x.mean(-1, True)
-
-
-def _norm2(x: torch.Tensor) -> torch.Tensor:
-    return x.pow(2).sum(-1, True)
-
-
-class SISNR(nn.Module):
-    """SISNR loss.
-
-    Input should be [B, C, T], output is scalar.
-
-    Args:
-        sample_rate (int): Sample rate.
-        segment (float or None): Evaluate on chunks of that many seconds. If None, evaluate on
-            entire audio only.
-        overlap (float): Overlap between chunks, i.e. 0.5 = 50 % overlap.
-        epsilon (float): Epsilon value for numerical stability.
-    """
-    def __init__(
-        self,
-        sample_rate: int = 16000,
-        segment: tp.Optional[float] = 20,
-        overlap: float = 0.5,
-        epsilon: float = torch.finfo(torch.float32).eps,
-    ):
-        super().__init__()
-        self.sample_rate = sample_rate
-        self.segment = segment
-        self.overlap = overlap
-        self.epsilon = epsilon
-
-    def forward(self, out_sig: torch.Tensor, ref_sig: torch.Tensor) -> torch.Tensor:
-        B, C, T = ref_sig.shape
-        assert ref_sig.shape == out_sig.shape
-
-        if self.segment is None:
-            frame = T
-            stride = T
-        else:
-            frame = int(self.segment * self.sample_rate)
-            stride = int(frame * (1 - self.overlap))
-
-        epsilon = self.epsilon * frame  # make epsilon prop to frame size.
-
-        gt = _unfold(ref_sig, frame, stride)
-        est = _unfold(out_sig, frame, stride)
-        if self.segment is None:
-            assert gt.shape[-1] == 1
-
-        gt = _center(gt)
-        est = _center(est)
-        dot = torch.einsum("bcft,bcft->bcf", gt, est)
-
-        proj = dot[:, :, :, None] * gt / (epsilon + _norm2(gt))
-        noise = est - proj
-
-        sisnr = 10 * (
-            torch.log10(epsilon + _norm2(proj)) - torch.log10(epsilon + _norm2(noise))
-        )
-        return -1 * sisnr[..., 0].mean()
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/conv.py b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/conv.py
deleted file mode 100644
index d115cbf8729b642ed78608bd00a4d0fd5afae6fd..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/conv.py
+++ /dev/null
@@ -1,243 +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 math
-import typing as tp
-import warnings
-
-import torch
-from torch import nn
-from torch.nn import functional as F
-from torch.nn.utils import spectral_norm, weight_norm
-
-
-CONV_NORMALIZATIONS = frozenset(['none', 'weight_norm', 'spectral_norm',
-                                 'time_group_norm'])
-
-
-def apply_parametrization_norm(module: nn.Module, norm: str = 'none'):
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'weight_norm':
-        return weight_norm(module)
-    elif norm == 'spectral_norm':
-        return spectral_norm(module)
-    else:
-        # We already check was in CONV_NORMALIZATION, so any other choice
-        # doesn't need reparametrization.
-        return module
-
-
-def get_norm_module(module: nn.Module, causal: bool = False, norm: str = 'none', **norm_kwargs):
-    """Return the proper normalization module. If causal is True, this will ensure the returned
-    module is causal, or return an error if the normalization doesn't support causal evaluation.
-    """
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'time_group_norm':
-        if causal:
-            raise ValueError("GroupNorm doesn't support causal evaluation.")
-        assert isinstance(module, nn.modules.conv._ConvNd)
-        return nn.GroupNorm(1, module.out_channels, **norm_kwargs)
-    else:
-        return nn.Identity()
-
-
-def get_extra_padding_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int,
-                                 padding_total: int = 0) -> int:
-    """See `pad_for_conv1d`."""
-    length = x.shape[-1]
-    n_frames = (length - kernel_size + padding_total) / stride + 1
-    ideal_length = (math.ceil(n_frames) - 1) * stride + (kernel_size - padding_total)
-    return ideal_length - length
-
-
-def pad_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int, padding_total: int = 0):
-    """Pad for a convolution to make sure that the last window is full.
-    Extra padding is added at the end. This is required to ensure that we can rebuild
-    an output of the same length, as otherwise, even with padding, some time steps
-    might get removed.
-    For instance, with total padding = 4, kernel size = 4, stride = 2:
-        0 0 1 2 3 4 5 0 0   # (0s are padding)
-        1   2   3           # (output frames of a convolution, last 0 is never used)
-        0 0 1 2 3 4 5 0     # (output of tr. conv., but pos. 5 is going to get removed as padding)
-            1 2 3 4         # once you removed padding, we are missing one time step !
-    """
-    extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-    return F.pad(x, (0, extra_padding))
-
-
-def pad1d(x: torch.Tensor, paddings: tp.Tuple[int, int], mode: str = 'constant', value: float = 0.):
-    """Tiny wrapper around F.pad, just to allow for reflect padding on small input.
-    If this is the case, we insert extra 0 padding to the right before the reflection happen.
-    """
-    length = x.shape[-1]
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    if mode == 'reflect':
-        max_pad = max(padding_left, padding_right)
-        extra_pad = 0
-        if length <= max_pad:
-            extra_pad = max_pad - length + 1
-            x = F.pad(x, (0, extra_pad))
-        padded = F.pad(x, paddings, mode, value)
-        end = padded.shape[-1] - extra_pad
-        return padded[..., :end]
-    else:
-        return F.pad(x, paddings, mode, value)
-
-
-def unpad1d(x: torch.Tensor, paddings: tp.Tuple[int, int]):
-    """Remove padding from x, handling properly zero padding. Only for 1d!"""
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    assert (padding_left + padding_right) <= x.shape[-1]
-    end = x.shape[-1] - padding_right
-    return x[..., padding_left: end]
-
-
-class NormConv1d(nn.Module):
-    """Wrapper around Conv1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConv2d(nn.Module):
-    """Wrapper around Conv2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal=False, norm=norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConvTranspose1d(nn.Module):
-    """Wrapper around ConvTranspose1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConvTranspose2d(nn.Module):
-    """Wrapper around ConvTranspose2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal=False, norm=norm, **norm_kwargs)
-
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-
-
-class StreamableConv1d(nn.Module):
-    """Conv1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, dilation: int = 1,
-                 groups: int = 1, bias: bool = True, causal: bool = False,
-                 norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {},
-                 pad_mode: str = 'reflect'):
-        super().__init__()
-        # warn user on unusual setup between dilation and stride
-        if stride > 1 and dilation > 1:
-            warnings.warn("StreamableConv1d has been initialized with stride > 1 and dilation > 1"
-                          f" (kernel_size={kernel_size} stride={stride}, dilation={dilation}).")
-        self.conv = NormConv1d(in_channels, out_channels, kernel_size, stride,
-                               dilation=dilation, groups=groups, bias=bias, causal=causal,
-                               norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.pad_mode = pad_mode
-
-    def forward(self, x):
-        B, C, T = x.shape
-        kernel_size = self.conv.conv.kernel_size[0]
-        stride = self.conv.conv.stride[0]
-        dilation = self.conv.conv.dilation[0]
-        kernel_size = (kernel_size - 1) * dilation + 1  # effective kernel size with dilations
-        padding_total = kernel_size - stride
-        extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-        if self.causal:
-            # Left padding for causal
-            x = pad1d(x, (padding_total, extra_padding), mode=self.pad_mode)
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            x = pad1d(x, (padding_left, padding_right + extra_padding), mode=self.pad_mode)
-        return self.conv(x)
-
-
-class StreamableConvTranspose1d(nn.Module):
-    """ConvTranspose1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, causal: bool = False,
-                 norm: str = 'none', trim_right_ratio: float = 1.,
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}):
-        super().__init__()
-        self.convtr = NormConvTranspose1d(in_channels, out_channels, kernel_size, stride,
-                                          causal=causal, norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.trim_right_ratio = trim_right_ratio
-        assert self.causal or self.trim_right_ratio == 1., \
-            "`trim_right_ratio` != 1.0 only makes sense for causal convolutions"
-        assert self.trim_right_ratio >= 0. and self.trim_right_ratio <= 1.
-
-    def forward(self, x):
-        kernel_size = self.convtr.convtr.kernel_size[0]
-        stride = self.convtr.convtr.stride[0]
-        padding_total = kernel_size - stride
-
-        y = self.convtr(x)
-
-        # We will only trim fixed padding. Extra padding from `pad_for_conv1d` would be
-        # removed at the very end, when keeping only the right length for the output,
-        # as removing it here would require also passing the length at the matching layer
-        # in the encoder.
-        if self.causal:
-            # Trim the padding on the right according to the specified ratio
-            # if trim_right_ratio = 1.0, trim everything from right
-            padding_right = math.ceil(padding_total * self.trim_right_ratio)
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        return y
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/rope.py b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/rope.py
deleted file mode 100644
index 503e6748df2bb72b3c864c20b37cba5498ffdd21..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/rope.py
+++ /dev/null
@@ -1,121 +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 torch import nn
-import torch
-
-
-class XPos(nn.Module):
-    """Length-extrapolatable positional embedding (xPos) from [Sun et al 2022](https://arxiv.org/abs/2212.10554v1).
-    This applies an exponential decay to the RoPE rotation matrix.
-
-    Args:
-        dim (int): Embedding dimension.
-        smoothing (float): Smoothing factor applied to the decay rates.
-        base_scale (int): Base decay rate, given in terms of scaling time.
-        device (torch.device, optional): Device on which to initialize the module.
-        dtype (torch.dtype): dtype to use to generate the embedding.
-    """
-    def __init__(self, dim: int, smoothing: float = 0.4, base_scale: int = 512,
-                 device=None, dtype: torch.dtype = torch.float32):
-        super().__init__()
-        assert dim % 2 == 0
-        assert dtype in [torch.float64, torch.float32]
-        self.dtype = dtype
-        self.base_scale = base_scale
-
-        half_dim = dim // 2
-        adim = torch.arange(half_dim, device=device, dtype=dtype)
-        decay_rates = (adim / half_dim + smoothing) / (1.0 + smoothing)
-        self.register_buffer("decay_rates", decay_rates)
-        self.decay: tp.Optional[torch.Tensor] = None
-
-    def get_decay(self, start: int, end: int):
-        """Create complex decay tensor, cache values for fast computation."""
-        if self.decay is None or end > self.decay.shape[0]:
-            assert isinstance(self.decay_rates, torch.Tensor)  # Satisfy type checker.
-            idx = torch.arange(end, device=self.decay_rates.device, dtype=self.dtype)
-            power = idx / self.base_scale
-            scale = self.decay_rates ** power.unsqueeze(-1)
-            self.decay = torch.polar(scale, torch.zeros_like(scale))
-        return self.decay[start:end]  # [T, C/2]
-
-
-class RotaryEmbedding(nn.Module):
-    """Rotary positional embedding (RoPE) from [Su et al 2022](https://arxiv.org/abs/2104.09864).
-
-    Args:
-        dim (int): Embedding dimension (twice the number of frequencies).
-        max_period (float): Maximum period of the rotation frequencies.
-        xpos (bool): Use xPos, applies an exponential decay to rotation matrix.
-        scale (float): Scale of positional embedding, set to 0 to deactivate.
-        device (torch.device, optional): Device on which to initialize the module.
-        dtype (torch.dtype): dtype to use to generate the embedding.
-    """
-    def __init__(self, dim: int, max_period: float = 10000.0, xpos: bool = False,
-                 scale: float = 1.0, device=None, dtype: torch.dtype = torch.float32):
-        super().__init__()
-        assert dim % 2 == 0
-        self.scale = scale
-        assert dtype in [torch.float64, torch.float32]
-        self.dtype = dtype
-
-        adim = torch.arange(0, dim, 2, device=device, dtype=dtype)[: (dim // 2)]
-        frequencies = 1.0 / (max_period ** (adim / dim))
-        self.register_buffer("frequencies", frequencies)
-        self.rotation: tp.Optional[torch.Tensor] = None
-
-        self.xpos = XPos(dim, device=device, dtype=dtype) if xpos else None
-
-    def get_rotation(self, start: int, end: int):
-        """Create complex rotation tensor, cache values for fast computation."""
-        if self.rotation is None or end > self.rotation.shape[0]:
-            assert isinstance(self.frequencies, torch.Tensor)  # Satisfy type checker.
-            idx = torch.arange(end, device=self.frequencies.device, dtype=self.dtype)
-            angles = torch.outer(idx, self.frequencies)
-            self.rotation = torch.polar(torch.ones_like(angles), angles)
-        return self.rotation[start:end]
-
-    def rotate(self, x: torch.Tensor, start: int = 0, invert_decay: bool = False):
-        """Apply rope rotation to query or key tensor."""
-        T = x.shape[1]
-        rotation = self.get_rotation(start, start + T).unsqueeze(0).unsqueeze(2)
-
-        if self.xpos:
-            decay = self.xpos.get_decay(start, start + T).unsqueeze(0).unsqueeze(2)
-        else:
-            decay = 1.0
-
-        if invert_decay:
-            decay = decay ** -1
-
-        x_complex = torch.view_as_complex(x.to(self.dtype).reshape(*x.shape[:-1], -1, 2))
-        scaled_rotation = (rotation * decay) * self.scale + (1.0 - self.scale)
-        x_out = torch.view_as_real(x_complex * scaled_rotation).flatten(-2)
-
-        return x_out.type_as(x)
-
-    def rotate_qk(self, query: torch.Tensor, key: torch.Tensor, start: int = 0):
-        """ Apply rope rotation to both query and key tensors.
-        Supports streaming mode, in which query and key are not expected to have the same shape.
-        In streaming mode, key will be of length [P + C] with P the cached past timesteps, but
-        query will be [C] (typically C == 1).
-
-        Args:
-            query (torch.Tensor): Query to rotate.
-            key (torch.Tensor): Key to rotate.
-            start (int): Start index of the sequence for time offset.
-        """
-        query_timesteps = query.shape[1]
-        key_timesteps = key.shape[1]
-        streaming_offset = key_timesteps - query_timesteps
-
-        query_out = self.rotate(query, start + streaming_offset)
-        key_out = self.rotate(key, start, invert_decay=True)
-
-        return query_out, key_out
diff --git a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/pip/_vendor/chardet/metadata/__init__.py b/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/pip/_vendor/chardet/metadata/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/command/build_py.py b/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/command/build_py.py
deleted file mode 100644
index ec0627429ccbb88f3a17325726441ebcb28fb597..0000000000000000000000000000000000000000
--- a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/command/build_py.py
+++ /dev/null
@@ -1,368 +0,0 @@
-from functools import partial
-from glob import glob
-from distutils.util import convert_path
-import distutils.command.build_py as orig
-import os
-import fnmatch
-import textwrap
-import io
-import distutils.errors
-import itertools
-import stat
-import warnings
-from pathlib import Path
-from typing import Dict, Iterable, Iterator, List, Optional, Tuple
-
-from setuptools._deprecation_warning import SetuptoolsDeprecationWarning
-from setuptools.extern.more_itertools import unique_everseen
-
-
-def make_writable(target):
-    os.chmod(target, os.stat(target).st_mode | stat.S_IWRITE)
-
-
-class build_py(orig.build_py):
-    """Enhanced 'build_py' command that includes data files with packages
-
-    The data files are specified via a 'package_data' argument to 'setup()'.
-    See 'setuptools.dist.Distribution' for more details.
-
-    Also, this version of the 'build_py' command allows you to specify both
-    'py_modules' and 'packages' in the same setup operation.
-    """
-    editable_mode: bool = False
-    existing_egg_info_dir: Optional[str] = None  #: Private API, internal use only.
-
-    def finalize_options(self):
-        orig.build_py.finalize_options(self)
-        self.package_data = self.distribution.package_data
-        self.exclude_package_data = self.distribution.exclude_package_data or {}
-        if 'data_files' in self.__dict__:
-            del self.__dict__['data_files']
-        self.__updated_files = []
-
-    def copy_file(self, infile, outfile, preserve_mode=1, preserve_times=1,
-                  link=None, level=1):
-        # Overwrite base class to allow using links
-        if link:
-            infile = str(Path(infile).resolve())
-            outfile = str(Path(outfile).resolve())
-        return super().copy_file(infile, outfile, preserve_mode, preserve_times,
-                                 link, level)
-
-    def run(self):
-        """Build modules, packages, and copy data files to build directory"""
-        if not (self.py_modules or self.packages) or self.editable_mode:
-            return
-
-        if self.py_modules:
-            self.build_modules()
-
-        if self.packages:
-            self.build_packages()
-            self.build_package_data()
-
-        # Only compile actual .py files, using our base class' idea of what our
-        # output files are.
-        self.byte_compile(orig.build_py.get_outputs(self, include_bytecode=0))
-
-    def __getattr__(self, attr):
-        "lazily compute data files"
-        if attr == 'data_files':
-            self.data_files = self._get_data_files()
-            return self.data_files
-        return orig.build_py.__getattr__(self, attr)
-
-    def build_module(self, module, module_file, package):
-        outfile, copied = orig.build_py.build_module(self, module, module_file, package)
-        if copied:
-            self.__updated_files.append(outfile)
-        return outfile, copied
-
-    def _get_data_files(self):
-        """Generate list of '(package,src_dir,build_dir,filenames)' tuples"""
-        self.analyze_manifest()
-        return list(map(self._get_pkg_data_files, self.packages or ()))
-
-    def get_data_files_without_manifest(self):
-        """
-        Generate list of ``(package,src_dir,build_dir,filenames)`` tuples,
-        but without triggering any attempt to analyze or build the manifest.
-        """
-        # Prevent eventual errors from unset `manifest_files`
-        # (that would otherwise be set by `analyze_manifest`)
-        self.__dict__.setdefault('manifest_files', {})
-        return list(map(self._get_pkg_data_files, self.packages or ()))
-
-    def _get_pkg_data_files(self, package):
-        # Locate package source directory
-        src_dir = self.get_package_dir(package)
-
-        # Compute package build directory
-        build_dir = os.path.join(*([self.build_lib] + package.split('.')))
-
-        # Strip directory from globbed filenames
-        filenames = [
-            os.path.relpath(file, src_dir)
-            for file in self.find_data_files(package, src_dir)
-        ]
-        return package, src_dir, build_dir, filenames
-
-    def find_data_files(self, package, src_dir):
-        """Return filenames for package's data files in 'src_dir'"""
-        patterns = self._get_platform_patterns(
-            self.package_data,
-            package,
-            src_dir,
-        )
-        globs_expanded = map(partial(glob, recursive=True), patterns)
-        # flatten the expanded globs into an iterable of matches
-        globs_matches = itertools.chain.from_iterable(globs_expanded)
-        glob_files = filter(os.path.isfile, globs_matches)
-        files = itertools.chain(
-            self.manifest_files.get(package, []),
-            glob_files,
-        )
-        return self.exclude_data_files(package, src_dir, files)
-
-    def get_outputs(self, include_bytecode=1) -> List[str]:
-        """See :class:`setuptools.commands.build.SubCommand`"""
-        if self.editable_mode:
-            return list(self.get_output_mapping().keys())
-        return super().get_outputs(include_bytecode)
-
-    def get_output_mapping(self) -> Dict[str, str]:
-        """See :class:`setuptools.commands.build.SubCommand`"""
-        mapping = itertools.chain(
-            self._get_package_data_output_mapping(),
-            self._get_module_mapping(),
-        )
-        return dict(sorted(mapping, key=lambda x: x[0]))
-
-    def _get_module_mapping(self) -> Iterator[Tuple[str, str]]:
-        """Iterate over all modules producing (dest, src) pairs."""
-        for (package, module, module_file) in self.find_all_modules():
-            package = package.split('.')
-            filename = self.get_module_outfile(self.build_lib, package, module)
-            yield (filename, module_file)
-
-    def _get_package_data_output_mapping(self) -> Iterator[Tuple[str, str]]:
-        """Iterate over package data producing (dest, src) pairs."""
-        for package, src_dir, build_dir, filenames in self.data_files:
-            for filename in filenames:
-                target = os.path.join(build_dir, filename)
-                srcfile = os.path.join(src_dir, filename)
-                yield (target, srcfile)
-
-    def build_package_data(self):
-        """Copy data files into build directory"""
-        for target, srcfile in self._get_package_data_output_mapping():
-            self.mkpath(os.path.dirname(target))
-            _outf, _copied = self.copy_file(srcfile, target)
-            make_writable(target)
-
-    def analyze_manifest(self):
-        self.manifest_files = mf = {}
-        if not self.distribution.include_package_data:
-            return
-        src_dirs = {}
-        for package in self.packages or ():
-            # Locate package source directory
-            src_dirs[assert_relative(self.get_package_dir(package))] = package
-
-        if (
-            getattr(self, 'existing_egg_info_dir', None)
-            and Path(self.existing_egg_info_dir, "SOURCES.txt").exists()
-        ):
-            egg_info_dir = self.existing_egg_info_dir
-            manifest = Path(egg_info_dir, "SOURCES.txt")
-            files = manifest.read_text(encoding="utf-8").splitlines()
-        else:
-            self.run_command('egg_info')
-            ei_cmd = self.get_finalized_command('egg_info')
-            egg_info_dir = ei_cmd.egg_info
-            files = ei_cmd.filelist.files
-
-        check = _IncludePackageDataAbuse()
-        for path in self._filter_build_files(files, egg_info_dir):
-            d, f = os.path.split(assert_relative(path))
-            prev = None
-            oldf = f
-            while d and d != prev and d not in src_dirs:
-                prev = d
-                d, df = os.path.split(d)
-                f = os.path.join(df, f)
-            if d in src_dirs:
-                if f == oldf:
-                    if check.is_module(f):
-                        continue  # it's a module, not data
-                else:
-                    importable = check.importable_subpackage(src_dirs[d], f)
-                    if importable:
-                        check.warn(importable)
-                mf.setdefault(src_dirs[d], []).append(path)
-
-    def _filter_build_files(self, files: Iterable[str], egg_info: str) -> Iterator[str]:
-        """
-        ``build_meta`` may try to create egg_info outside of the project directory,
-        and this can be problematic for certain plugins (reported in issue #3500).
-
-        Extensions might also include between their sources files created on the
-        ``build_lib`` and ``build_temp`` directories.
-
-        This function should filter this case of invalid files out.
-        """
-        build = self.get_finalized_command("build")
-        build_dirs = (egg_info, self.build_lib, build.build_temp, build.build_base)
-        norm_dirs = [os.path.normpath(p) for p in build_dirs if p]
-
-        for file in files:
-            norm_path = os.path.normpath(file)
-            if not os.path.isabs(file) or all(d not in norm_path for d in norm_dirs):
-                yield file
-
-    def get_data_files(self):
-        pass  # Lazily compute data files in _get_data_files() function.
-
-    def check_package(self, package, package_dir):
-        """Check namespace packages' __init__ for declare_namespace"""
-        try:
-            return self.packages_checked[package]
-        except KeyError:
-            pass
-
-        init_py = orig.build_py.check_package(self, package, package_dir)
-        self.packages_checked[package] = init_py
-
-        if not init_py or not self.distribution.namespace_packages:
-            return init_py
-
-        for pkg in self.distribution.namespace_packages:
-            if pkg == package or pkg.startswith(package + '.'):
-                break
-        else:
-            return init_py
-
-        with io.open(init_py, 'rb') as f:
-            contents = f.read()
-        if b'declare_namespace' not in contents:
-            raise distutils.errors.DistutilsError(
-                "Namespace package problem: %s is a namespace package, but "
-                "its\n__init__.py does not call declare_namespace()! Please "
-                'fix it.\n(See the setuptools manual under '
-                '"Namespace Packages" for details.)\n"' % (package,)
-            )
-        return init_py
-
-    def initialize_options(self):
-        self.packages_checked = {}
-        orig.build_py.initialize_options(self)
-        self.editable_mode = False
-        self.existing_egg_info_dir = None
-
-    def get_package_dir(self, package):
-        res = orig.build_py.get_package_dir(self, package)
-        if self.distribution.src_root is not None:
-            return os.path.join(self.distribution.src_root, res)
-        return res
-
-    def exclude_data_files(self, package, src_dir, files):
-        """Filter filenames for package's data files in 'src_dir'"""
-        files = list(files)
-        patterns = self._get_platform_patterns(
-            self.exclude_package_data,
-            package,
-            src_dir,
-        )
-        match_groups = (fnmatch.filter(files, pattern) for pattern in patterns)
-        # flatten the groups of matches into an iterable of matches
-        matches = itertools.chain.from_iterable(match_groups)
-        bad = set(matches)
-        keepers = (fn for fn in files if fn not in bad)
-        # ditch dupes
-        return list(unique_everseen(keepers))
-
-    @staticmethod
-    def _get_platform_patterns(spec, package, src_dir):
-        """
-        yield platform-specific path patterns (suitable for glob
-        or fn_match) from a glob-based spec (such as
-        self.package_data or self.exclude_package_data)
-        matching package in src_dir.
-        """
-        raw_patterns = itertools.chain(
-            spec.get('', []),
-            spec.get(package, []),
-        )
-        return (
-            # Each pattern has to be converted to a platform-specific path
-            os.path.join(src_dir, convert_path(pattern))
-            for pattern in raw_patterns
-        )
-
-
-def assert_relative(path):
-    if not os.path.isabs(path):
-        return path
-    from distutils.errors import DistutilsSetupError
-
-    msg = (
-        textwrap.dedent(
-            """
-        Error: setup script specifies an absolute path:
-
-            %s
-
-        setup() arguments must *always* be /-separated paths relative to the
-        setup.py directory, *never* absolute paths.
-        """
-        ).lstrip()
-        % path
-    )
-    raise DistutilsSetupError(msg)
-
-
-class _IncludePackageDataAbuse:
-    """Inform users that package or module is included as 'data file'"""
-
-    MESSAGE = """\
-    Installing {importable!r} as data is deprecated, please list it in `packages`.
-    !!\n\n
-    ############################
-    # Package would be ignored #
-    ############################
-    Python recognizes {importable!r} as an importable package,
-    but it is not listed in the `packages` configuration of setuptools.
-
-    {importable!r} has been automatically added to the distribution only
-    because it may contain data files, but this behavior is likely to change
-    in future versions of setuptools (and therefore is considered deprecated).
-
-    Please make sure that {importable!r} is included as a package by using
-    the `packages` configuration field or the proper discovery methods
-    (for example by using `find_namespace_packages(...)`/`find_namespace:`
-    instead of `find_packages(...)`/`find:`).
-
-    You can read more about "package discovery" and "data files" on setuptools
-    documentation page.
-    \n\n!!
-    """
-
-    def __init__(self):
-        self._already_warned = set()
-
-    def is_module(self, file):
-        return file.endswith(".py") and file[:-len(".py")].isidentifier()
-
-    def importable_subpackage(self, parent, file):
-        pkg = Path(file).parent
-        parts = list(itertools.takewhile(str.isidentifier, pkg.parts))
-        if parts:
-            return ".".join([parent, *parts])
-        return None
-
-    def warn(self, importable):
-        if importable not in self._already_warned:
-            msg = textwrap.dedent(self.MESSAGE).format(importable=importable)
-            warnings.warn(msg, SetuptoolsDeprecationWarning, stacklevel=2)
-            self._already_warned.add(importable)
diff --git a/spaces/Realcat/image-matching-webui/third_party/DeDoDe/demo/demo_kpts.py b/spaces/Realcat/image-matching-webui/third_party/DeDoDe/demo/demo_kpts.py
deleted file mode 100644
index f0ae36aa4bbe3439e96d7b45bfa809c48b6ebf45..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/DeDoDe/demo/demo_kpts.py
+++ /dev/null
@@ -1,22 +0,0 @@
-import torch
-import cv2
-import numpy as np
-from PIL import Image
-from DeDoDe import dedode_detector_L
-
-
-def draw_kpts(im, kpts):
-    kpts = [cv2.KeyPoint(x, y, 1.0) for x, y in kpts.cpu().numpy()]
-    im = np.array(im)
-    ret = cv2.drawKeypoints(im, kpts, None)
-    return ret
-
-
-detector = dedode_detector_L(weights=torch.load("dedode_detector_l.pth"))
-im_path = "assets/im_A.jpg"
-im = Image.open(im_path)
-out = detector.detect_from_path(im_path, num_keypoints=10_000)
-W, H = im.size
-kps = out["keypoints"]
-kps = detector.to_pixel_coords(kps, H, W)
-Image.fromarray(draw_kpts(im, kps[0])).save("demo/keypoints.png")
diff --git a/spaces/Realcat/image-matching-webui/third_party/SGMNet/superglue/__init__.py b/spaces/Realcat/image-matching-webui/third_party/SGMNet/superglue/__init__.py
deleted file mode 100644
index fabeccd0fe21eb5be637602f2b2eb3cfd944d11b..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/SGMNet/superglue/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .match_model import matcher
diff --git a/spaces/RichardMB1217/blip/models/blip.py b/spaces/RichardMB1217/blip/models/blip.py
deleted file mode 100644
index 38678f65ea2c276b351c2c97d429ebc2525ddcf7..0000000000000000000000000000000000000000
--- a/spaces/RichardMB1217/blip/models/blip.py
+++ /dev/null
@@ -1,238 +0,0 @@
-'''
- * Copyright (c) 2022, salesforce.com, inc.
- * All rights reserved.
- * SPDX-License-Identifier: BSD-3-Clause
- * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
- * By Junnan Li
-'''
-import warnings
-warnings.filterwarnings("ignore")
-
-from models.vit import VisionTransformer, interpolate_pos_embed
-from models.med import BertConfig, BertModel, BertLMHeadModel
-from transformers import BertTokenizer
-
-import torch
-from torch import nn
-import torch.nn.functional as F
-
-import os
-from urllib.parse import urlparse
-from timm.models.hub import download_cached_file
-
-class BLIP_Base(nn.Module):
-    def __init__(self,                 
-                 med_config = 'configs/med_config.json',  
-                 image_size = 224,
-                 vit = 'base',
-                 vit_grad_ckpt = False,
-                 vit_ckpt_layer = 0,                 
-                 ):
-        """
-        Args:
-            med_config (str): path for the mixture of encoder-decoder model's configuration file
-            image_size (int): input image size
-            vit (str): model size of vision transformer
-        """               
-        super().__init__()
-        
-        self.visual_encoder, vision_width = create_vit(vit,image_size, vit_grad_ckpt, vit_ckpt_layer)
-        self.tokenizer = init_tokenizer()   
-        med_config = BertConfig.from_json_file(med_config)
-        med_config.encoder_width = vision_width
-        self.text_encoder = BertModel(config=med_config, add_pooling_layer=False)  
-
-        
-    def forward(self, image, caption, mode):
-        
-        assert mode in ['image', 'text', 'multimodal'], "mode parameter must be image, text, or multimodal"
-        text = self.tokenizer(caption, return_tensors="pt").to(image.device) 
-        
-        if mode=='image':    
-            # return image features
-            image_embeds = self.visual_encoder(image)             
-            return image_embeds
-        
-        elif mode=='text':
-            # return text features
-            text_output = self.text_encoder(text.input_ids, attention_mask = text.attention_mask,                      
-                                            return_dict = True, mode = 'text')  
-            return text_output.last_hidden_state
-        
-        elif mode=='multimodal':
-            # return multimodel features
-            image_embeds = self.visual_encoder(image)    
-            image_atts = torch.ones(image_embeds.size()[:-1],dtype=torch.long).to(image.device)      
-            
-            text.input_ids[:,0] = self.tokenizer.enc_token_id
-            output = self.text_encoder(text.input_ids,
-                                       attention_mask = text.attention_mask,
-                                       encoder_hidden_states = image_embeds,
-                                       encoder_attention_mask = image_atts,      
-                                       return_dict = True,
-                                      )              
-            return output.last_hidden_state
-        
-        
-        
-class BLIP_Decoder(nn.Module):
-    def __init__(self,                 
-                 med_config = 'configs/med_config.json',  
-                 image_size = 384,
-                 vit = 'base',
-                 vit_grad_ckpt = False,
-                 vit_ckpt_layer = 0,
-                 prompt = 'a picture of ',
-                 ):
-        """
-        Args:
-            med_config (str): path for the mixture of encoder-decoder model's configuration file
-            image_size (int): input image size
-            vit (str): model size of vision transformer
-        """            
-        super().__init__()
-        
-        self.visual_encoder, vision_width = create_vit(vit,image_size, vit_grad_ckpt, vit_ckpt_layer)
-        self.tokenizer = init_tokenizer()   
-        med_config = BertConfig.from_json_file(med_config)
-        med_config.encoder_width = vision_width
-        self.text_decoder = BertLMHeadModel(config=med_config)    
-        
-        self.prompt = prompt
-        self.prompt_length = len(self.tokenizer(self.prompt).input_ids)-1
-
-        
-    def forward(self, image, caption):
-        
-        image_embeds = self.visual_encoder(image) 
-        image_atts = torch.ones(image_embeds.size()[:-1],dtype=torch.long).to(image.device)
-        
-        text = self.tokenizer(caption, padding='longest', truncation=True, max_length=40, return_tensors="pt").to(image.device) 
-        
-        text.input_ids[:,0] = self.tokenizer.bos_token_id
-        
-        decoder_targets = text.input_ids.masked_fill(text.input_ids == self.tokenizer.pad_token_id, -100)         
-        decoder_targets[:,:self.prompt_length] = -100
-     
-        decoder_output = self.text_decoder(text.input_ids, 
-                                           attention_mask = text.attention_mask, 
-                                           encoder_hidden_states = image_embeds,
-                                           encoder_attention_mask = image_atts,                  
-                                           labels = decoder_targets,
-                                           return_dict = True,   
-                                          )   
-        loss_lm = decoder_output.loss
-        
-        return loss_lm
-        
-    def generate(self, image, sample=False, num_beams=3, max_length=30, min_length=10, top_p=0.9, repetition_penalty=1.0):
-        image_embeds = self.visual_encoder(image)
-
-        if not sample:
-            image_embeds = image_embeds.repeat_interleave(num_beams,dim=0)
-            
-        image_atts = torch.ones(image_embeds.size()[:-1],dtype=torch.long).to(image.device)
-        model_kwargs = {"encoder_hidden_states": image_embeds, "encoder_attention_mask":image_atts}
-        
-        prompt = [self.prompt] * image.size(0)
-        input_ids = self.tokenizer(prompt, return_tensors="pt").input_ids.to(image.device) 
-        input_ids[:,0] = self.tokenizer.bos_token_id
-        input_ids = input_ids[:, :-1] 
-
-        if sample:
-            #nucleus sampling
-            outputs = self.text_decoder.generate(input_ids=input_ids,
-                                                  max_length=max_length,
-                                                  min_length=min_length,
-                                                  do_sample=True,
-                                                  top_p=top_p,
-                                                  num_return_sequences=1,
-                                                  eos_token_id=self.tokenizer.sep_token_id,
-                                                  pad_token_id=self.tokenizer.pad_token_id, 
-                                                  repetition_penalty=1.1,                                            
-                                                  **model_kwargs)
-        else:
-            #beam search
-            outputs = self.text_decoder.generate(input_ids=input_ids,
-                                                  max_length=max_length,
-                                                  min_length=min_length,
-                                                  num_beams=num_beams,
-                                                  eos_token_id=self.tokenizer.sep_token_id,
-                                                  pad_token_id=self.tokenizer.pad_token_id,     
-                                                  repetition_penalty=repetition_penalty,
-                                                  **model_kwargs)            
-            
-        captions = []    
-        for output in outputs:
-            caption = self.tokenizer.decode(output, skip_special_tokens=True)    
-            captions.append(caption[len(self.prompt):])
-        return captions
-    
-
-def blip_decoder(pretrained='',**kwargs):
-    model = BLIP_Decoder(**kwargs)
-    if pretrained:
-        model,msg = load_checkpoint(model,pretrained)
-        assert(len(msg.missing_keys)==0)
-    return model    
-    
-def blip_feature_extractor(pretrained='',**kwargs):
-    model = BLIP_Base(**kwargs)
-    if pretrained:
-        model,msg = load_checkpoint(model,pretrained)
-        assert(len(msg.missing_keys)==0)
-    return model        
-
-def init_tokenizer():
-    tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
-    tokenizer.add_special_tokens({'bos_token':'[DEC]'})
-    tokenizer.add_special_tokens({'additional_special_tokens':['[ENC]']})       
-    tokenizer.enc_token_id = tokenizer.additional_special_tokens_ids[0]  
-    return tokenizer
-
-
-def create_vit(vit, image_size, use_grad_checkpointing=False, ckpt_layer=0, drop_path_rate=0):
-        
-    assert vit in ['base', 'large'], "vit parameter must be base or large"
-    if vit=='base':
-        vision_width = 768
-        visual_encoder = VisionTransformer(img_size=image_size, patch_size=16, embed_dim=vision_width, depth=12, 
-                                           num_heads=12, use_grad_checkpointing=use_grad_checkpointing, ckpt_layer=ckpt_layer,
-                                           drop_path_rate=0 or drop_path_rate
-                                          )   
-    elif vit=='large':
-        vision_width = 1024
-        visual_encoder = VisionTransformer(img_size=image_size, patch_size=16, embed_dim=vision_width, depth=24, 
-                                           num_heads=16, use_grad_checkpointing=use_grad_checkpointing, ckpt_layer=ckpt_layer,
-                                           drop_path_rate=0.1 or drop_path_rate
-                                          )   
-    return visual_encoder, vision_width
-
-def is_url(url_or_filename):
-    parsed = urlparse(url_or_filename)
-    return parsed.scheme in ("http", "https")
-
-def load_checkpoint(model,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']
-    
-    state_dict['visual_encoder.pos_embed'] = interpolate_pos_embed(state_dict['visual_encoder.pos_embed'],model.visual_encoder) 
-    if 'visual_encoder_m.pos_embed' in model.state_dict().keys():
-        state_dict['visual_encoder_m.pos_embed'] = interpolate_pos_embed(state_dict['visual_encoder_m.pos_embed'],
-                                                                         model.visual_encoder_m)    
-    for key in model.state_dict().keys():
-        if key in state_dict.keys():
-            if state_dict[key].shape!=model.state_dict()[key].shape:
-                del state_dict[key]
-    
-    msg = model.load_state_dict(state_dict,strict=False)
-    print('load checkpoint from %s'%url_or_filename)  
-    return model,msg
-    
diff --git a/spaces/Ritvik19/VidScripter/app.py b/spaces/Ritvik19/VidScripter/app.py
deleted file mode 100644
index 23101dffd61ef8c676b5bed486638f0b70968a63..0000000000000000000000000000000000000000
--- a/spaces/Ritvik19/VidScripter/app.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import streamlit as st
-import requests
-import base64
-import os
-from moviepy.editor import VideoFileClip
-from pytube import YouTube
-from youtube_transcript_api import YouTubeTranscriptApi
-from youtube_transcript_api._errors import CouldNotRetrieveTranscript
-import whisper
-import ffmpeg
-import re
-import tempfile
-
-st. set_page_config(layout="wide", initial_sidebar_state="collapsed") 
-
-@st.cache_resource()
-def load_whisper(model):
-    return whisper.load_model(model)
-
-@st.cache_data
-def download_video(url):
-    if "youtube" in url or "youtu.be" in url:
-        yt = YouTube(url)
-        video = yt.streams.get_highest_resolution()
-        filename = video.download()
-    else:
-        response = requests.get(url, stream=True)
-        filename = url.split("/")[-1]
-        with open(filename, "wb") as file:
-            for chunk in response.iter_content(chunk_size=1024):
-                if chunk:
-                    file.write(chunk)
-    return filename
-
-@st.cache_data
-def convert_to_audio(video_filename):
-    video = VideoFileClip(video_filename)
-    audio_filename = video_filename.replace(".mp4", ".mp3")
-    audio = video.audio
-    audio.write_audiofile(audio_filename, codec="mp3")
-    return audio_filename
-
-def delete_files(video_filename, audio_filename):
-    delete_file(video_filename)
-    delete_file(audio_filename)
-
-def delete_file(filename):
-    if os.path.exists(filename):
-        os.remove(filename)
-        st.info(f"File '{os.path.basename(filename)}' deleted from the server.")
-
-@st.cache_data
-def transcribe_whisper(_model, audio_filepath):
-    return _model.transcribe(audio_filepath)["text"]
-        
-def get_media_download_link(media_type, file_path):
-    with open(file_path, "rb") as file:
-        contents = file.read()
-        encoded = base64.b64encode(contents).decode("utf-8")
-        media_href = f'data:file/{media_type};base64,{encoded}'
-        st.markdown(f'<a href="{media_href}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}</a>',
-                    unsafe_allow_html=True)
-
-@st.cache_data
-def generate_summaries(_summarizer, text, min_length=50, max_length=500):
-    paragraphs = text.split("\n\n")
-    summaries = []
-    for paragraph in paragraphs:
-        summary = _summarizer(paragraph, max_length=max_length, min_length=min_length, do_sample=False)
-        summaries.append(summary[0]['summary_text'].strip())
-    return "\n\n".join(summaries)
-
-def main():
-    st.title("VidScripter")
-    st.write("#### A One Stop Solution to Video Transcription")
-    c1, c2 = st.columns(2)
-    c1.write("""
-        - Enter the video URL in the text input box.
-        - Click the **Fetch** button to fetch the video.
-        - Once the video is fetched, you can perform the following actions:
-            - Fetch transcript from YouTube API (if available) by clicking the **Fetch Transcript** button.
-            - Transcribe the video using the Whisper model by clicking the **Transcribe (Whisper)** button.
-        - The transcript will be displayed in a text area below.
-        - You can download the video or audio by clicking the respective buttons.
-        """) 
-    
-    whisper_model = load_whisper("base")
-
-    url = c2.text_input("Enter the video URL")
-    fetch_button = c2.button("Fetch")
-    st.session_state.setdefault('load_state', False)
-    
-    if fetch_button or st.session_state.load_state:
-        st.session_state.load_state = True
-        
-        if url:
-            process_video(url, whisper_model)
-
-def process_video(url, whisper_model):
-    yt = YouTube(url)
-    video_id = yt.video_id
-    try:
-        video_filename = download_video(url)
-        st.success("Video fetched successfully")
-    except Exception:
-        video_filename = None
-        st.warning("Video could not be fetched")
-        
-
-    try:
-        audio_filename = convert_to_audio(video_filename) if video_filename is not None else None
-        if video_filename is not None:
-            st.success("Audio converted successfully")
-        else:
-            st.info("No Video to convert into Audio")
-    except Exception:
-        audio_filename = None
-        st.warning("Audio coud not be converted")
-    
-    text_filename = os.path.basename(video_filename).replace('.mp4', '.txt') if video_filename is not None else "transcript.txt"
-    emp = st.empty()
-
-    col1, col2, col3, col4 = st.columns(4)
-
-    if "youtube" in url or "youtu.be" in url:
-        process_youtube_video(video_id, col3, emp, text_filename)
-
-    process_whisper_transcript(whisper_model, audio_filename, col4, text_filename)
-    
-    with col1:
-        if video_filename is not None and st.button("Download Video"):
-                with st.spinner("Encoding Video"):
-                    get_media_download_link("video", video_filename)
-
-    with col2:
-        if audio_filename is not None and st.button("Download Audio"):
-                with st.spinner("Encoding Audio"):
-                    get_media_download_link("audio", audio_filename)
-
-def process_youtube_video(video_id, col, emp, text_filename):
-    try:
-        transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
-        transcripts = [transcript for transcript in transcript_list]
-
-        if transcripts:
-            transcript_options = {f"{transcript.language} ({transcript.language_code})": transcript for transcript in transcripts}
-            transcript_option = emp.selectbox("Select a transcript", list(transcript_options.keys()))
-            selected_transcript = transcript_options[transcript_option]
-            
-            st.session_state.setdefault('api_transcript', False)
-            if col.button("Fetch Transcript") or st.session_state.api_transcript:
-                st.session_state.api_transcript = True
-                transcript_text = selected_transcript.fetch()
-                transcript_text = '\n'.join([re.sub('\s+', ' ', chunk['text']) for chunk in transcript_text])
-                modified_text = st.text_area("Transcript", transcript_text, height=500)
-                st.download_button("Download", modified_text, text_filename)
-
-    except CouldNotRetrieveTranscript:
-        emp.warning("Could Not Retrieve API Transcripts for this video.")
-    except Exception as e:
-        emp.warning(f"Error Fetching API Transcripts for this video. {e}")
-
-def process_whisper_transcript(whisper_model, audio_filename, col, text_filename):
-    if audio_filename is not None:
-        st.session_state.setdefault('whisper_transcript', False)
-        if col.button("Transcribe (Whisper)") or st.session_state.whisper_transcript:
-            st.session_state.whisper_transcript = True
-            whisper_text = transcribe_whisper(whisper_model, audio_filename)
-            modified_text = st.text_area("Transcript", whisper_text, height=500)
-            st.download_button("Download", modified_text, text_filename)
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/configs/_base_/datasets/pascal_context.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/configs/_base_/datasets/pascal_context.py
deleted file mode 100644
index ff65bad1b86d7e3a5980bb5b9fc55798dc8df5f4..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/configs/_base_/datasets/pascal_context.py
+++ /dev/null
@@ -1,60 +0,0 @@
-# dataset settings
-dataset_type = 'PascalContextDataset'
-data_root = 'data/VOCdevkit/VOC2010/'
-img_norm_cfg = dict(
-    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
-
-img_scale = (520, 520)
-crop_size = (480, 480)
-
-train_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(type='LoadAnnotations'),
-    dict(type='Resize', img_scale=img_scale, ratio_range=(0.5, 2.0)),
-    dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
-    dict(type='RandomFlip', prob=0.5),
-    dict(type='PhotoMetricDistortion'),
-    dict(type='Normalize', **img_norm_cfg),
-    dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255),
-    dict(type='DefaultFormatBundle'),
-    dict(type='Collect', keys=['img', 'gt_semantic_seg']),
-]
-test_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(
-        type='MultiScaleFlipAug',
-        img_scale=img_scale,
-        # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
-        flip=False,
-        transforms=[
-            dict(type='Resize', keep_ratio=True),
-            dict(type='RandomFlip'),
-            dict(type='Normalize', **img_norm_cfg),
-            dict(type='ImageToTensor', keys=['img']),
-            dict(type='Collect', keys=['img']),
-        ])
-]
-data = dict(
-    samples_per_gpu=4,
-    workers_per_gpu=4,
-    train=dict(
-        type=dataset_type,
-        data_root=data_root,
-        img_dir='JPEGImages',
-        ann_dir='SegmentationClassContext',
-        split='ImageSets/SegmentationContext/train.txt',
-        pipeline=train_pipeline),
-    val=dict(
-        type=dataset_type,
-        data_root=data_root,
-        img_dir='JPEGImages',
-        ann_dir='SegmentationClassContext',
-        split='ImageSets/SegmentationContext/val.txt',
-        pipeline=test_pipeline),
-    test=dict(
-        type=dataset_type,
-        data_root=data_root,
-        img_dir='JPEGImages',
-        ann_dir='SegmentationClassContext',
-        split='ImageSets/SegmentationContext/val.txt',
-        pipeline=test_pipeline))
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/core/bbox/iou_calculators/iou2d_calculator.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/core/bbox/iou_calculators/iou2d_calculator.py
deleted file mode 100644
index 158b702c234f5c10c4f5f03e08e8794ac7b8dcad..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/core/bbox/iou_calculators/iou2d_calculator.py
+++ /dev/null
@@ -1,159 +0,0 @@
-import torch
-
-from .builder import IOU_CALCULATORS
-
-
-@IOU_CALCULATORS.register_module()
-class BboxOverlaps2D(object):
-    """2D Overlaps (e.g. IoUs, GIoUs) Calculator."""
-
-    def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
-        """Calculate IoU between 2D bboxes.
-
-        Args:
-            bboxes1 (Tensor): bboxes have shape (m, 4) in <x1, y1, x2, y2>
-                format, or shape (m, 5) in <x1, y1, x2, y2, score> format.
-            bboxes2 (Tensor): bboxes have shape (m, 4) in <x1, y1, x2, y2>
-                format, shape (m, 5) in <x1, y1, x2, y2, score> format, or be
-                empty. If ``is_aligned `` is ``True``, then m and n must be
-                equal.
-            mode (str): "iou" (intersection over union), "iof" (intersection
-                over foreground), or "giou" (generalized intersection over
-                union).
-            is_aligned (bool, optional): If True, then m and n must be equal.
-                Default False.
-
-        Returns:
-            Tensor: shape (m, n) if ``is_aligned `` is False else shape (m,)
-        """
-        assert bboxes1.size(-1) in [0, 4, 5]
-        assert bboxes2.size(-1) in [0, 4, 5]
-        if bboxes2.size(-1) == 5:
-            bboxes2 = bboxes2[..., :4]
-        if bboxes1.size(-1) == 5:
-            bboxes1 = bboxes1[..., :4]
-        return bbox_overlaps(bboxes1, bboxes2, mode, is_aligned)
-
-    def __repr__(self):
-        """str: a string describing the module"""
-        repr_str = self.__class__.__name__ + '()'
-        return repr_str
-
-
-def bbox_overlaps(bboxes1, bboxes2, mode='iou', is_aligned=False, eps=1e-6):
-    """Calculate overlap between two set of bboxes.
-
-    If ``is_aligned `` is ``False``, then calculate the overlaps between each
-    bbox of bboxes1 and bboxes2, otherwise the overlaps between each aligned
-    pair of bboxes1 and bboxes2.
-
-    Args:
-        bboxes1 (Tensor): shape (B, m, 4) in <x1, y1, x2, y2> format or empty.
-        bboxes2 (Tensor): shape (B, n, 4) in <x1, y1, x2, y2> format or empty.
-            B indicates the batch dim, in shape (B1, B2, ..., Bn).
-            If ``is_aligned `` is ``True``, then m and n must be equal.
-        mode (str): "iou" (intersection over union), "iof" (intersection over
-            foreground) or "giou" (generalized intersection over union).
-            Default "iou".
-        is_aligned (bool, optional): If True, then m and n must be equal.
-            Default False.
-        eps (float, optional): A value added to the denominator for numerical
-            stability. Default 1e-6.
-
-    Returns:
-        Tensor: shape (m, n) if ``is_aligned `` is False else shape (m,)
-
-    Example:
-        >>> bboxes1 = torch.FloatTensor([
-        >>>     [0, 0, 10, 10],
-        >>>     [10, 10, 20, 20],
-        >>>     [32, 32, 38, 42],
-        >>> ])
-        >>> bboxes2 = torch.FloatTensor([
-        >>>     [0, 0, 10, 20],
-        >>>     [0, 10, 10, 19],
-        >>>     [10, 10, 20, 20],
-        >>> ])
-        >>> overlaps = bbox_overlaps(bboxes1, bboxes2)
-        >>> assert overlaps.shape == (3, 3)
-        >>> overlaps = bbox_overlaps(bboxes1, bboxes2, is_aligned=True)
-        >>> assert overlaps.shape == (3, )
-
-    Example:
-        >>> empty = torch.empty(0, 4)
-        >>> nonempty = torch.FloatTensor([[0, 0, 10, 9]])
-        >>> assert tuple(bbox_overlaps(empty, nonempty).shape) == (0, 1)
-        >>> assert tuple(bbox_overlaps(nonempty, empty).shape) == (1, 0)
-        >>> assert tuple(bbox_overlaps(empty, empty).shape) == (0, 0)
-    """
-
-    assert mode in ['iou', 'iof', 'giou'], f'Unsupported mode {mode}'
-    # Either the boxes are empty or the length of boxes' last dimension is 4
-    assert (bboxes1.size(-1) == 4 or bboxes1.size(0) == 0)
-    assert (bboxes2.size(-1) == 4 or bboxes2.size(0) == 0)
-
-    # Batch dim must be the same
-    # Batch dim: (B1, B2, ... Bn)
-    assert bboxes1.shape[:-2] == bboxes2.shape[:-2]
-    batch_shape = bboxes1.shape[:-2]
-
-    rows = bboxes1.size(-2)
-    cols = bboxes2.size(-2)
-    if is_aligned:
-        assert rows == cols
-
-    if rows * cols == 0:
-        if is_aligned:
-            return bboxes1.new(batch_shape + (rows, ))
-        else:
-            return bboxes1.new(batch_shape + (rows, cols))
-
-    area1 = (bboxes1[..., 2] - bboxes1[..., 0]) * (
-        bboxes1[..., 3] - bboxes1[..., 1])
-    area2 = (bboxes2[..., 2] - bboxes2[..., 0]) * (
-        bboxes2[..., 3] - bboxes2[..., 1])
-
-    if is_aligned:
-        lt = torch.max(bboxes1[..., :2], bboxes2[..., :2])  # [B, rows, 2]
-        rb = torch.min(bboxes1[..., 2:], bboxes2[..., 2:])  # [B, rows, 2]
-
-        wh = (rb - lt).clamp(min=0)  # [B, rows, 2]
-        overlap = wh[..., 0] * wh[..., 1]
-
-        if mode in ['iou', 'giou']:
-            union = area1 + area2 - overlap
-        else:
-            union = area1
-        if mode == 'giou':
-            enclosed_lt = torch.min(bboxes1[..., :2], bboxes2[..., :2])
-            enclosed_rb = torch.max(bboxes1[..., 2:], bboxes2[..., 2:])
-    else:
-        lt = torch.max(bboxes1[..., :, None, :2],
-                       bboxes2[..., None, :, :2])  # [B, rows, cols, 2]
-        rb = torch.min(bboxes1[..., :, None, 2:],
-                       bboxes2[..., None, :, 2:])  # [B, rows, cols, 2]
-
-        wh = (rb - lt).clamp(min=0)  # [B, rows, cols, 2]
-        overlap = wh[..., 0] * wh[..., 1]
-
-        if mode in ['iou', 'giou']:
-            union = area1[..., None] + area2[..., None, :] - overlap
-        else:
-            union = area1[..., None]
-        if mode == 'giou':
-            enclosed_lt = torch.min(bboxes1[..., :, None, :2],
-                                    bboxes2[..., None, :, :2])
-            enclosed_rb = torch.max(bboxes1[..., :, None, 2:],
-                                    bboxes2[..., None, :, 2:])
-
-    eps = union.new_tensor([eps])
-    union = torch.max(union, eps)
-    ious = overlap / union
-    if mode in ['iou', 'iof']:
-        return ious
-    # calculate gious
-    enclose_wh = (enclosed_rb - enclosed_lt).clamp(min=0)
-    enclose_area = enclose_wh[..., 0] * enclose_wh[..., 1]
-    enclose_area = torch.max(enclose_area, eps)
-    gious = ious - (enclose_area - union) / enclose_area
-    return gious
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/__init__.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/__init__.py
deleted file mode 100644
index bc5d29ece5bbf2f168f538f151f06d1b263a5153..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-from .bbox_head import BBoxHead
-from .convfc_bbox_head import (ConvFCBBoxHead, Shared2FCBBoxHead,
-                               Shared4Conv1FCBBoxHead)
-from .dii_head import DIIHead
-from .double_bbox_head import DoubleConvFCBBoxHead
-from .sabl_head import SABLHead
-from .scnet_bbox_head import SCNetBBoxHead
-
-__all__ = [
-    'BBoxHead', 'ConvFCBBoxHead', 'Shared2FCBBoxHead',
-    'Shared4Conv1FCBBoxHead', 'DoubleConvFCBBoxHead', 'SABLHead', 'DIIHead',
-    'SCNetBBoxHead'
-]
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmseg/ops/__init__.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmseg/ops/__init__.py
deleted file mode 100644
index bec51c75b9363a9a19e9fb5c35f4e7dbd6f7751c..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmseg/ops/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from .encoding import Encoding
-from .wrappers import Upsample, resize
-
-__all__ = ['Upsample', 'resize', 'Encoding']
diff --git a/spaces/RugNlpFlashcards/Speech_Language_Processing_Jurafsky_Martin/results/read_time.tex b/spaces/RugNlpFlashcards/Speech_Language_Processing_Jurafsky_Martin/results/read_time.tex
deleted file mode 100644
index 40a045379f2b3f5885fcc8b04fdd0cf0dfa28735..0000000000000000000000000000000000000000
--- a/spaces/RugNlpFlashcards/Speech_Language_Processing_Jurafsky_Martin/results/read_time.tex
+++ /dev/null
@@ -1,14 +0,0 @@
-\begin{tabular}{lrrrr}
-\toprule
-{} &  faiss\_dpr.read &  faiss\_longformer.read &  es\_dpr.read &  es\_longformer.read \\
-\midrule
-count &       59.000000 &              59.000000 &    59.000000 &           59.000000 \\
-mean  &        1.222466 &               5.486930 &     1.866525 &            5.191112 \\
-std   &        0.923501 &               0.966157 &     1.005673 &            0.465743 \\
-min   &        0.341175 &               4.487846 &     0.314589 &            4.463429 \\
-25\%   &        0.695762 &               4.767350 &     1.141979 &            4.858446 \\
-50\%   &        0.919248 &               5.454382 &     1.650235 &            5.202449 \\
-75\%   &        1.394425 &               5.699257 &     2.516944 &            5.362522 \\
-max   &        5.365102 &              10.146074 &     4.782422 &            6.431236 \\
-\bottomrule
-\end{tabular}
diff --git a/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/text/ngu_dialect.py b/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/text/ngu_dialect.py
deleted file mode 100644
index ce3e12bbf0469426872eed5f681985d3e1be9b26..0000000000000000000000000000000000000000
--- a/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/text/ngu_dialect.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import re
-import opencc
-
-
-dialects = {'SZ': 'suzhou', 'WX': 'wuxi', 'CZ': 'changzhou', 'HZ': 'hangzhou',
-            'SX': 'shaoxing', 'NB': 'ningbo', 'JJ': 'jingjiang', 'YX': 'yixing',
-            'JD': 'jiading', 'ZR': 'zhenru', 'PH': 'pinghu', 'TX': 'tongxiang',
-            'JS': 'jiashan', 'HN': 'xiashi', 'LP': 'linping', 'XS': 'xiaoshan',
-            'FY': 'fuyang', 'RA': 'ruao', 'CX': 'cixi', 'SM': 'sanmen',
-            'TT': 'tiantai', 'WZ': 'wenzhou', 'SC': 'suichang', 'YB': 'youbu'}
-
-converters = {}
-
-for dialect in dialects.values():
-    try:
-        converters[dialect] = opencc.OpenCC(dialect)
-    except:
-        pass
-
-
-def ngu_dialect_to_ipa(text, dialect):
-    dialect = dialects[dialect]
-    text = converters[dialect].convert(text).replace('-','').replace('$',' ')
-    text = re.sub(r'[、；：]', '，', text)
-    text = re.sub(r'\s*，\s*', ', ', text)
-    text = re.sub(r'\s*。\s*', '. ', text)
-    text = re.sub(r'\s*？\s*', '? ', text)
-    text = re.sub(r'\s*！\s*', '! ', text)
-    text = re.sub(r'\s*$', '', text)
-    return text
diff --git a/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/train_val_divide.py b/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/train_val_divide.py
deleted file mode 100644
index 183abb58d6054a98dd92fcffa107ea0571502130..0000000000000000000000000000000000000000
--- a/spaces/Sakukaze/VITS-Umamusume-voice-synthesizer/train_val_divide.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import os
-import numpy as np
-filename = 'E:/uma_voice/output.txt'
-split ='|'
-with open(filename, encoding='utf-8') as f:
-    filepaths_and_text = [line.strip().split(split) for line in f]
-
-train_filename = filename.split('.')[0] + '_train' + '.txt'
-val_filename = filename.split('.')[0] + '_val' + '.txt'
-
-train_split_ratio = 0.99
-train_f = open(train_filename, 'w', encoding='utf-8')
-val_f = open(val_filename, 'w', encoding='utf-8')
-for i in range(len(filepaths_and_text)):
-    if np.random.rand() < train_split_ratio:
-        train_f.writelines('|'.join(filepaths_and_text[i]) + '\n')
-    else:
-        val_f.writelines('|'.join(filepaths_and_text[i]) + '\n')
\ No newline at end of file
diff --git a/spaces/Serg4451D/PixelArtGenerator/app.py b/spaces/Serg4451D/PixelArtGenerator/app.py
deleted file mode 100644
index 6fce0299edad0821422f218a396ff18314b86091..0000000000000000000000000000000000000000
--- a/spaces/Serg4451D/PixelArtGenerator/app.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import streamlit as st
-import requests
-
-API_ENDPOINT = "https://api.openai.com/v1/images/generations"
-
-st.title("Pixel Art Generator")
-st.write("Введите текст для генерации пиксельного искусства:")
-
-text_input = st.text_input("")
-
-if st.button("Создать пиксельный арт"):
-    prompt = "pixel art " + text_input
-    data = {
-        "model": "image-alpha-001",
-        "prompt": prompt,
-        "num_images": 1,
-        "size": "256x256",
-        "response_format": "url"
-    }
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": "Bearer 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"
-    }
-    response = requests.post(url=API_ENDPOINT, json=data, headers=headers)
-
-    if response.ok:
-        st.write("Ваш пиксельный арт:")
-        st.image(response.json()["data"][0]["url"], use_column_width=True)
-        st.write("Powered By DALL•E 2")
-    else:
-        st.write("Ошибка при создании пиксельного искусства")
diff --git a/spaces/ServerX/PorcoDiaz/lib/infer_pack/onnx_inference.py b/spaces/ServerX/PorcoDiaz/lib/infer_pack/onnx_inference.py
deleted file mode 100644
index 6517853be49e61c427cf7cd9b5ed203f6d5f367e..0000000000000000000000000000000000000000
--- a/spaces/ServerX/PorcoDiaz/lib/infer_pack/onnx_inference.py
+++ /dev/null
@@ -1,145 +0,0 @@
-import onnxruntime
-import librosa
-import numpy as np
-import soundfile
-
-
-class ContentVec:
-    def __init__(self, vec_path="pretrained/vec-768-layer-12.onnx", device=None):
-        print("load model(s) from {}".format(vec_path))
-        if device == "cpu" or device is None:
-            providers = ["CPUExecutionProvider"]
-        elif device == "cuda":
-            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
-        elif device == "dml":
-            providers = ["DmlExecutionProvider"]
-        else:
-            raise RuntimeError("Unsportted Device")
-        self.model = onnxruntime.InferenceSession(vec_path, providers=providers)
-
-    def __call__(self, wav):
-        return self.forward(wav)
-
-    def forward(self, wav):
-        feats = wav
-        if feats.ndim == 2:  # double channels
-            feats = feats.mean(-1)
-        assert feats.ndim == 1, feats.ndim
-        feats = np.expand_dims(np.expand_dims(feats, 0), 0)
-        onnx_input = {self.model.get_inputs()[0].name: feats}
-        logits = self.model.run(None, onnx_input)[0]
-        return logits.transpose(0, 2, 1)
-
-
-def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
-    if f0_predictor == "pm":
-        from lib.infer_pack.modules.F0Predictor.PMF0Predictor import PMF0Predictor
-
-        f0_predictor_object = PMF0Predictor(
-            hop_length=hop_length, sampling_rate=sampling_rate
-        )
-    elif f0_predictor == "harvest":
-        from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import (
-            HarvestF0Predictor,
-        )
-
-        f0_predictor_object = HarvestF0Predictor(
-            hop_length=hop_length, sampling_rate=sampling_rate
-        )
-    elif f0_predictor == "dio":
-        from lib.infer_pack.modules.F0Predictor.DioF0Predictor import DioF0Predictor
-
-        f0_predictor_object = DioF0Predictor(
-            hop_length=hop_length, sampling_rate=sampling_rate
-        )
-    else:
-        raise Exception("Unknown f0 predictor")
-    return f0_predictor_object
-
-
-class OnnxRVC:
-    def __init__(
-        self,
-        model_path,
-        sr=40000,
-        hop_size=512,
-        vec_path="vec-768-layer-12",
-        device="cpu",
-    ):
-        vec_path = f"pretrained/{vec_path}.onnx"
-        self.vec_model = ContentVec(vec_path, device)
-        if device == "cpu" or device is None:
-            providers = ["CPUExecutionProvider"]
-        elif device == "cuda":
-            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
-        elif device == "dml":
-            providers = ["DmlExecutionProvider"]
-        else:
-            raise RuntimeError("Unsportted Device")
-        self.model = onnxruntime.InferenceSession(model_path, providers=providers)
-        self.sampling_rate = sr
-        self.hop_size = hop_size
-
-    def forward(self, hubert, hubert_length, pitch, pitchf, ds, rnd):
-        onnx_input = {
-            self.model.get_inputs()[0].name: hubert,
-            self.model.get_inputs()[1].name: hubert_length,
-            self.model.get_inputs()[2].name: pitch,
-            self.model.get_inputs()[3].name: pitchf,
-            self.model.get_inputs()[4].name: ds,
-            self.model.get_inputs()[5].name: rnd,
-        }
-        return (self.model.run(None, onnx_input)[0] * 32767).astype(np.int16)
-
-    def inference(
-        self,
-        raw_path,
-        sid,
-        f0_method="dio",
-        f0_up_key=0,
-        pad_time=0.5,
-        cr_threshold=0.02,
-    ):
-        f0_min = 50
-        f0_max = 1100
-        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
-        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
-        f0_predictor = get_f0_predictor(
-            f0_method,
-            hop_length=self.hop_size,
-            sampling_rate=self.sampling_rate,
-            threshold=cr_threshold,
-        )
-        wav, sr = librosa.load(raw_path, sr=self.sampling_rate)
-        org_length = len(wav)
-        if org_length / sr > 50.0:
-            raise RuntimeError("Reached Max Length")
-
-        wav16k = librosa.resample(wav, orig_sr=self.sampling_rate, target_sr=16000)
-        wav16k = wav16k
-
-        hubert = self.vec_model(wav16k)
-        hubert = np.repeat(hubert, 2, axis=2).transpose(0, 2, 1).astype(np.float32)
-        hubert_length = hubert.shape[1]
-
-        pitchf = f0_predictor.compute_f0(wav, hubert_length)
-        pitchf = pitchf * 2 ** (f0_up_key / 12)
-        pitch = pitchf.copy()
-        f0_mel = 1127 * np.log(1 + pitch / 700)
-        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
-            f0_mel_max - f0_mel_min
-        ) + 1
-        f0_mel[f0_mel <= 1] = 1
-        f0_mel[f0_mel > 255] = 255
-        pitch = np.rint(f0_mel).astype(np.int64)
-
-        pitchf = pitchf.reshape(1, len(pitchf)).astype(np.float32)
-        pitch = pitch.reshape(1, len(pitch))
-        ds = np.array([sid]).astype(np.int64)
-
-        rnd = np.random.randn(1, 192, hubert_length).astype(np.float32)
-        hubert_length = np.array([hubert_length]).astype(np.int64)
-
-        out_wav = self.forward(hubert, hubert_length, pitch, pitchf, ds, rnd).squeeze()
-        out_wav = np.pad(out_wav, (0, 2 * self.hop_size), "constant")
-        return out_wav[0:org_length]
diff --git a/spaces/Silentlin/DiffSinger/inference/svs/gradio/infer.py b/spaces/Silentlin/DiffSinger/inference/svs/gradio/infer.py
deleted file mode 100644
index 246a68e01339fb940a4864f52bf6c00c517b1c05..0000000000000000000000000000000000000000
--- a/spaces/Silentlin/DiffSinger/inference/svs/gradio/infer.py
+++ /dev/null
@@ -1,91 +0,0 @@
-import importlib
-import re
-
-import gradio as gr
-import yaml
-from gradio.inputs import Textbox
-
-from inference.svs.base_svs_infer import BaseSVSInfer
-from utils.hparams import set_hparams
-from utils.hparams import hparams as hp
-import numpy as np
-
-
-class GradioInfer:
-    def __init__(self, exp_name, inference_cls, title, description, article, example_inputs):
-        self.exp_name = exp_name
-        self.title = title
-        self.description = description
-        self.article = article
-        self.example_inputs = example_inputs
-        pkg = ".".join(inference_cls.split(".")[:-1])
-        cls_name = inference_cls.split(".")[-1]
-        self.inference_cls = getattr(importlib.import_module(pkg), cls_name)
-
-    def greet(self, text, notes, notes_duration):
-        PUNCS = '。？；：'
-        sents = re.split(rf'([{PUNCS}])', text.replace('\n', ','))
-        sents_notes = re.split(rf'([{PUNCS}])', notes.replace('\n', ','))
-        sents_notes_dur = re.split(rf'([{PUNCS}])', notes_duration.replace('\n', ','))
-
-        if sents[-1] not in list(PUNCS):
-            sents = sents + ['']
-            sents_notes = sents_notes + ['']
-            sents_notes_dur = sents_notes_dur + ['']
-
-        audio_outs = []
-        s, n, n_dur = "", "", ""
-        for i in range(0, len(sents), 2):
-            if len(sents[i]) > 0:
-                s += sents[i] + sents[i + 1]
-                n += sents_notes[i] + sents_notes[i+1]
-                n_dur += sents_notes_dur[i] + sents_notes_dur[i+1]
-            if len(s) >= 400 or (i >= len(sents) - 2 and len(s) > 0):
-                audio_out = self.infer_ins.infer_once({
-                    'text': s,
-                    'notes': n,
-                    'notes_duration': n_dur,
-                })
-                audio_out = audio_out * 32767
-                audio_out = audio_out.astype(np.int16)
-                audio_outs.append(audio_out)
-                audio_outs.append(np.zeros(int(hp['audio_sample_rate'] * 0.3)).astype(np.int16))
-                s = ""
-                n = ""
-        audio_outs = np.concatenate(audio_outs)
-        return hp['audio_sample_rate'], audio_outs
-
-    def run(self):
-        set_hparams(exp_name=self.exp_name, print_hparams=False)
-        infer_cls = self.inference_cls
-        self.infer_ins: BaseSVSInfer = infer_cls(hp)
-        example_inputs = self.example_inputs
-        for i in range(len(example_inputs)):
-            text, notes, notes_dur = example_inputs[i].split('<sep>')
-            example_inputs[i] = [text, notes, notes_dur]
-
-        iface = gr.Interface(fn=self.greet,
-                             inputs=[
-                                 Textbox(lines=2, placeholder=None, default=example_inputs[0][0], label="input text"),
-                                 Textbox(lines=2, placeholder=None, default=example_inputs[0][1], label="input note"),
-                                 Textbox(lines=2, placeholder=None, default=example_inputs[0][2], label="input duration")]
-                             ,
-                             outputs="audio",
-                             allow_flagging="never",
-                             title=self.title,
-                             description=self.description,
-                             article=self.article,
-                             examples=example_inputs,
-                             enable_queue=True)
-        iface.launch()
-
-
-if __name__ == '__main__':
-    gradio_config = yaml.safe_load(open('inference/svs/gradio/gradio_settings.yaml'))
-    g = GradioInfer(**gradio_config)
-    g.run()
-
-
-# python inference/svs/gradio/infer.py --config usr/configs/midi/cascade/opencs/ds60_rel.yaml --exp_name 0303_opencpop_ds58_midi
-# python inference/svs/ds_cascade.py --config usr/configs/midi/cascade/opencs/ds60_rel.yaml --exp_name 0303_opencpop_ds58_midi
-# CUDA_VISIBLE_DEVICES=3 python inference/svs/gradio/infer.py --config usr/configs/midi/e2e/opencpop/ds100_adj_rel.yaml --exp_name 0228_opencpop_ds100_rel
\ No newline at end of file
diff --git a/spaces/Spjkjlkkklj/dalle/style.css b/spaces/Spjkjlkkklj/dalle/style.css
deleted file mode 100644
index 114adf441e9032febb46bc056b2a8bb651075f0d..0000000000000000000000000000000000000000
--- a/spaces/Spjkjlkkklj/dalle/style.css
+++ /dev/null
@@ -1,28 +0,0 @@
-body {
-	padding: 2rem;
-	font-family: -apple-system, BlinkMacSystemFont, "Arial", sans-serif;
-}
-
-h1 {
-	font-size: 16px;
-	margin-top: 0;
-}
-
-p {
-	color: rgb(107, 114, 128);
-	font-size: 15px;
-	margin-bottom: 10px;
-	margin-top: 5px;
-}
-
-.card {
-	max-width: 620px;
-	margin: 0 auto;
-	padding: 16px;
-	border: 1px solid lightgray;
-	border-radius: 16px;
-}
-
-.card p:last-child {
-	margin-bottom: 0;
-}
diff --git a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/utils/cluster.py b/spaces/SuYuanS/AudioCraft_Plus/audiocraft/utils/cluster.py
deleted file mode 100644
index 3380d031739d473fb859c76b9c25350f47fa77e8..0000000000000000000000000000000000000000
--- a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/utils/cluster.py
+++ /dev/null
@@ -1,75 +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.
-
-"""
-Utility functions for SLURM configuration and cluster settings.
-"""
-
-from enum import Enum
-import os
-import socket
-import typing as tp
-
-import omegaconf
-
-
-class ClusterType(Enum):
-    AWS = "aws"
-    FAIR = "fair"
-    RSC = "rsc"
-    LOCAL_DARWIN = "darwin"
-    DEFAULT = "default"  # used for any other cluster.
-
-
-def _guess_cluster_type() -> ClusterType:
-    uname = os.uname()
-    fqdn = socket.getfqdn()
-    if uname.sysname == "Linux" and (uname.release.endswith("-aws") or ".ec2" in fqdn):
-        return ClusterType.AWS
-
-    if fqdn.endswith(".fair"):
-        return ClusterType.FAIR
-
-    if fqdn.endswith(".facebook.com"):
-        return ClusterType.RSC
-
-    if uname.sysname == "Darwin":
-        return ClusterType.LOCAL_DARWIN
-
-    return ClusterType.DEFAULT
-
-
-def get_cluster_type(
-    cluster_type: tp.Optional[ClusterType] = None,
-) -> tp.Optional[ClusterType]:
-    if cluster_type is None:
-        return _guess_cluster_type()
-
-    return cluster_type
-
-
-def get_slurm_parameters(
-    cfg: omegaconf.DictConfig, cluster_type: tp.Optional[ClusterType] = None
-) -> omegaconf.DictConfig:
-    """Update SLURM parameters in configuration based on cluster type.
-    If the cluster type is not specify, it infers it automatically.
-    """
-    from ..environment import AudioCraftEnvironment
-    cluster_type = get_cluster_type(cluster_type)
-    # apply cluster-specific adjustments
-    if cluster_type == ClusterType.AWS:
-        cfg["mem_per_gpu"] = None
-        cfg["constraint"] = None
-        cfg["setup"] = []
-    elif cluster_type == ClusterType.RSC:
-        cfg["mem_per_gpu"] = None
-        cfg["setup"] = []
-        cfg["constraint"] = None
-        cfg["partition"] = "learn"
-    slurm_exclude = AudioCraftEnvironment.get_slurm_exclude()
-    if slurm_exclude is not None:
-        cfg["exclude"] = slurm_exclude
-    return cfg
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/wtsapi32.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/wtsapi32.py
deleted file mode 100644
index 13227db32f844aa02b1b37deeb7d73d44bae2a41..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/winappdbg/win32/wtsapi32.py
+++ /dev/null
@@ -1,337 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-# Copyright (c) 2009-2014, Mario Vilas
-# 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 OWNER 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.
-
-"""
-Wrapper for wtsapi32.dll in ctypes.
-"""
-
-__revision__ = "$Id$"
-
-from winappdbg.win32.defines import *
-from winappdbg.win32.advapi32 import *
-
-#==============================================================================
-# This is used later on to calculate the list of exported symbols.
-_all = None
-_all = set(vars().keys())
-#==============================================================================
-
-#--- Constants ----------------------------------------------------------------
-
-WTS_CURRENT_SERVER_HANDLE = 0
-WTS_CURRENT_SESSION       = 1
-
-#--- WTS_PROCESS_INFO structure -----------------------------------------------
-
-# typedef struct _WTS_PROCESS_INFO {
-#   DWORD  SessionId;
-#   DWORD  ProcessId;
-#   LPTSTR pProcessName;
-#   PSID   pUserSid;
-# } WTS_PROCESS_INFO, *PWTS_PROCESS_INFO;
-
-class WTS_PROCESS_INFOA(Structure):
-    _fields_ = [
-        ("SessionId",    DWORD),
-        ("ProcessId",    DWORD),
-        ("pProcessName", LPSTR),
-        ("pUserSid",     PSID),
-    ]
-PWTS_PROCESS_INFOA = POINTER(WTS_PROCESS_INFOA)
-
-class WTS_PROCESS_INFOW(Structure):
-    _fields_ = [
-        ("SessionId",    DWORD),
-        ("ProcessId",    DWORD),
-        ("pProcessName", LPWSTR),
-        ("pUserSid",     PSID),
-    ]
-PWTS_PROCESS_INFOW = POINTER(WTS_PROCESS_INFOW)
-
-#--- WTSQuerySessionInformation enums and structures --------------------------
-
-# typedef enum _WTS_INFO_CLASS {
-#   WTSInitialProgram          = 0,
-#   WTSApplicationName         = 1,
-#   WTSWorkingDirectory        = 2,
-#   WTSOEMId                   = 3,
-#   WTSSessionId               = 4,
-#   WTSUserName                = 5,
-#   WTSWinStationName          = 6,
-#   WTSDomainName              = 7,
-#   WTSConnectState            = 8,
-#   WTSClientBuildNumber       = 9,
-#   WTSClientName              = 10,
-#   WTSClientDirectory         = 11,
-#   WTSClientProductId         = 12,
-#   WTSClientHardwareId        = 13,
-#   WTSClientAddress           = 14,
-#   WTSClientDisplay           = 15,
-#   WTSClientProtocolType      = 16,
-#   WTSIdleTime                = 17,
-#   WTSLogonTime               = 18,
-#   WTSIncomingBytes           = 19,
-#   WTSOutgoingBytes           = 20,
-#   WTSIncomingFrames          = 21,
-#   WTSOutgoingFrames          = 22,
-#   WTSClientInfo              = 23,
-#   WTSSessionInfo             = 24,
-#   WTSSessionInfoEx           = 25,
-#   WTSConfigInfo              = 26,
-#   WTSValidationInfo          = 27,
-#   WTSSessionAddressV4        = 28,
-#   WTSIsRemoteSession         = 29
-# } WTS_INFO_CLASS;
-
-WTSInitialProgram          = 0
-WTSApplicationName         = 1
-WTSWorkingDirectory        = 2
-WTSOEMId                   = 3
-WTSSessionId               = 4
-WTSUserName                = 5
-WTSWinStationName          = 6
-WTSDomainName              = 7
-WTSConnectState            = 8
-WTSClientBuildNumber       = 9
-WTSClientName              = 10
-WTSClientDirectory         = 11
-WTSClientProductId         = 12
-WTSClientHardwareId        = 13
-WTSClientAddress           = 14
-WTSClientDisplay           = 15
-WTSClientProtocolType      = 16
-WTSIdleTime                = 17
-WTSLogonTime               = 18
-WTSIncomingBytes           = 19
-WTSOutgoingBytes           = 20
-WTSIncomingFrames          = 21
-WTSOutgoingFrames          = 22
-WTSClientInfo              = 23
-WTSSessionInfo             = 24
-WTSSessionInfoEx           = 25
-WTSConfigInfo              = 26
-WTSValidationInfo          = 27
-WTSSessionAddressV4        = 28
-WTSIsRemoteSession         = 29
-
-WTS_INFO_CLASS = ctypes.c_int
-
-# typedef enum _WTS_CONNECTSTATE_CLASS {
-#   WTSActive,
-#   WTSConnected,
-#   WTSConnectQuery,
-#   WTSShadow,
-#   WTSDisconnected,
-#   WTSIdle,
-#   WTSListen,
-#   WTSReset,
-#   WTSDown,
-#   WTSInit
-# } WTS_CONNECTSTATE_CLASS;
-
-WTSActive       = 0
-WTSConnected    = 1
-WTSConnectQuery = 2
-WTSShadow       = 3
-WTSDisconnected = 4
-WTSIdle         = 5
-WTSListen       = 6
-WTSReset        = 7
-WTSDown         = 8
-WTSInit         = 9
-
-WTS_CONNECTSTATE_CLASS = ctypes.c_int
-
-# typedef struct _WTS_CLIENT_DISPLAY {
-#   DWORD HorizontalResolution;
-#   DWORD VerticalResolution;
-#   DWORD ColorDepth;
-# } WTS_CLIENT_DISPLAY, *PWTS_CLIENT_DISPLAY;
-class WTS_CLIENT_DISPLAY(Structure):
-    _fields_ = [
-        ("HorizontalResolution", DWORD),
-        ("VerticalResolution",   DWORD),
-        ("ColorDepth",           DWORD),
-    ]
-PWTS_CLIENT_DISPLAY = POINTER(WTS_CLIENT_DISPLAY)
-
-# typedef struct _WTS_CLIENT_ADDRESS {
-#   DWORD AddressFamily;
-#   BYTE  Address[20];
-# } WTS_CLIENT_ADDRESS, *PWTS_CLIENT_ADDRESS;
-
-# XXX TODO
-
-# typedef struct _WTSCLIENT {
-#   WCHAR   ClientName[CLIENTNAME_LENGTH + 1];
-#   WCHAR   Domain[DOMAIN_LENGTH + 1 ];
-#   WCHAR   UserName[USERNAME_LENGTH + 1];
-#   WCHAR   WorkDirectory[MAX_PATH + 1];
-#   WCHAR   InitialProgram[MAX_PATH + 1];
-#   BYTE    EncryptionLevel;
-#   ULONG   ClientAddressFamily;
-#   USHORT  ClientAddress[CLIENTADDRESS_LENGTH + 1];
-#   USHORT  HRes;
-#   USHORT  VRes;
-#   USHORT  ColorDepth;
-#   WCHAR   ClientDirectory[MAX_PATH + 1];
-#   ULONG   ClientBuildNumber;
-#   ULONG   ClientHardwareId;
-#   USHORT  ClientProductId;
-#   USHORT  OutBufCountHost;
-#   USHORT  OutBufCountClient;
-#   USHORT  OutBufLength;
-#   WCHAR     DeviceId[MAX_PATH + 1];
-# } WTSCLIENT, *PWTSCLIENT;
-
-# XXX TODO
-
-# typedef struct _WTSINFO {
-#   WTS_CONNECTSTATE_CLASS State;
-#   DWORD                  SessionId;
-#   DWORD                  IncomingBytes;
-#   DWORD                  OutgoingBytes;
-#   DWORD                  IncomingCompressedBytes;
-#   DWORD                  OutgoingCompressedBytes;
-#   WCHAR                  WinStationName;
-#   WCHAR                  Domain;
-#   WCHAR                  UserName;
-#   LARGE_INTEGER          ConnectTime;
-#   LARGE_INTEGER          DisconnectTime;
-#   LARGE_INTEGER          LastInputTime;
-#   LARGE_INTEGER          LogonTime;
-#   LARGE_INTEGER          CurrentTime;
-# } WTSINFO, *PWTSINFO;
-
-# XXX TODO
-
-# typedef struct _WTSINFOEX {
-#   DWORD           Level;
-#   WTSINFOEX_LEVEL Data;
-# } WTSINFOEX, *PWTSINFOEX;
-
-# XXX TODO
-
-#--- wtsapi32.dll -------------------------------------------------------------
-
-# void WTSFreeMemory(
-#   __in  PVOID pMemory
-# );
-def WTSFreeMemory(pMemory):
-    _WTSFreeMemory = windll.wtsapi32.WTSFreeMemory
-    _WTSFreeMemory.argtypes = [PVOID]
-    _WTSFreeMemory.restype  = None
-    _WTSFreeMemory(pMemory)
-
-# BOOL WTSEnumerateProcesses(
-#   __in   HANDLE hServer,
-#   __in   DWORD Reserved,
-#   __in   DWORD Version,
-#   __out  PWTS_PROCESS_INFO *ppProcessInfo,
-#   __out  DWORD *pCount
-# );
-def WTSEnumerateProcessesA(hServer = WTS_CURRENT_SERVER_HANDLE):
-    _WTSEnumerateProcessesA = windll.wtsapi32.WTSEnumerateProcessesA
-    _WTSEnumerateProcessesA.argtypes = [HANDLE, DWORD, DWORD, POINTER(PWTS_PROCESS_INFOA), PDWORD]
-    _WTSEnumerateProcessesA.restype  = bool
-    _WTSEnumerateProcessesA.errcheck = RaiseIfZero
-
-    pProcessInfo = PWTS_PROCESS_INFOA()
-    Count = DWORD(0)
-    _WTSEnumerateProcessesA(hServer, 0, 1, byref(pProcessInfo), byref(Count))
-    return pProcessInfo, Count.value
-
-def WTSEnumerateProcessesW(hServer = WTS_CURRENT_SERVER_HANDLE):
-    _WTSEnumerateProcessesW = windll.wtsapi32.WTSEnumerateProcessesW
-    _WTSEnumerateProcessesW.argtypes = [HANDLE, DWORD, DWORD, POINTER(PWTS_PROCESS_INFOW), PDWORD]
-    _WTSEnumerateProcessesW.restype  = bool
-    _WTSEnumerateProcessesW.errcheck = RaiseIfZero
-
-    pProcessInfo = PWTS_PROCESS_INFOW()
-    Count = DWORD(0)
-    _WTSEnumerateProcessesW(hServer, 0, 1, byref(pProcessInfo), byref(Count))
-    return pProcessInfo, Count.value
-
-WTSEnumerateProcesses = DefaultStringType(WTSEnumerateProcessesA, WTSEnumerateProcessesW)
-
-# BOOL WTSTerminateProcess(
-#   __in  HANDLE hServer,
-#   __in  DWORD ProcessId,
-#   __in  DWORD ExitCode
-# );
-def WTSTerminateProcess(hServer, ProcessId, ExitCode):
-    _WTSTerminateProcess = windll.wtsapi32.WTSTerminateProcess
-    _WTSTerminateProcess.argtypes = [HANDLE, DWORD, DWORD]
-    _WTSTerminateProcess.restype  = bool
-    _WTSTerminateProcess.errcheck = RaiseIfZero
-    _WTSTerminateProcess(hServer, ProcessId, ExitCode)
-
-# BOOL WTSQuerySessionInformation(
-#   __in   HANDLE hServer,
-#   __in   DWORD SessionId,
-#   __in   WTS_INFO_CLASS WTSInfoClass,
-#   __out  LPTSTR *ppBuffer,
-#   __out  DWORD *pBytesReturned
-# );
-
-# XXX TODO
-
-#--- kernel32.dll -------------------------------------------------------------
-
-# I've no idea why these functions are in kernel32.dll instead of wtsapi32.dll
-
-# BOOL ProcessIdToSessionId(
-#   __in   DWORD dwProcessId,
-#   __out  DWORD *pSessionId
-# );
-def ProcessIdToSessionId(dwProcessId):
-    _ProcessIdToSessionId = windll.kernel32.ProcessIdToSessionId
-    _ProcessIdToSessionId.argtypes = [DWORD, PDWORD]
-    _ProcessIdToSessionId.restype  = bool
-    _ProcessIdToSessionId.errcheck = RaiseIfZero
-
-    dwSessionId = DWORD(0)
-    _ProcessIdToSessionId(dwProcessId, byref(dwSessionId))
-    return dwSessionId.value
-
-# DWORD WTSGetActiveConsoleSessionId(void);
-def WTSGetActiveConsoleSessionId():
-    _WTSGetActiveConsoleSessionId = windll.kernel32.WTSGetActiveConsoleSessionId
-    _WTSGetActiveConsoleSessionId.argtypes = []
-    _WTSGetActiveConsoleSessionId.restype  = DWORD
-    _WTSGetActiveConsoleSessionId.errcheck = RaiseIfZero
-    return _WTSGetActiveConsoleSessionId()
-
-#==============================================================================
-# This calculates the list of exported symbols.
-_all = set(vars().keys()).difference(_all)
-__all__ = [_x for _x in _all if not _x.startswith('_')]
-__all__.sort()
-#==============================================================================
diff --git a/spaces/TLME/Bert-VITS-Umamusume-Genshin-HonkaiSR/bert/bert-base-japanese-v3/README.md b/spaces/TLME/Bert-VITS-Umamusume-Genshin-HonkaiSR/bert/bert-base-japanese-v3/README.md
deleted file mode 100644
index c5b3456719f01801a2f29fef5faa8ee672391adf..0000000000000000000000000000000000000000
--- a/spaces/TLME/Bert-VITS-Umamusume-Genshin-HonkaiSR/bert/bert-base-japanese-v3/README.md
+++ /dev/null
@@ -1,53 +0,0 @@
----
-license: apache-2.0
-datasets:
-- cc100
-- wikipedia
-language:
-- ja
-widget:
-- text: 東北大学で[MASK]の研究をしています。
----
-
-# BERT base Japanese (unidic-lite with whole word masking, CC-100 and jawiki-20230102)
-
-This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
-
-This version of the model processes input texts with word-level tokenization based on the Unidic 2.1.2 dictionary (available in [unidic-lite](https://pypi.org/project/unidic-lite/) package), followed by the WordPiece subword tokenization.
-Additionally, the model is trained with the whole word masking enabled for the masked language modeling (MLM) objective.
-
-The codes for the pretraining are available at [cl-tohoku/bert-japanese](https://github.com/cl-tohoku/bert-japanese/).
-
-## Model architecture
-
-The model architecture is the same as the original BERT base model; 12 layers, 768 dimensions of hidden states, and 12 attention heads.
-
-## Training Data
-
-The model is trained on the Japanese portion of [CC-100 dataset](https://data.statmt.org/cc-100/) and the Japanese version of Wikipedia.
-For Wikipedia, we generated a text corpus from the [Wikipedia Cirrussearch dump file](https://dumps.wikimedia.org/other/cirrussearch/) as of January 2, 2023.
-The corpus files generated from CC-100 and Wikipedia are 74.3GB and 4.9GB in size and consist of approximately 392M and 34M sentences, respectively.
-
-For the purpose of splitting texts into sentences, we used [fugashi](https://github.com/polm/fugashi) with [mecab-ipadic-NEologd](https://github.com/neologd/mecab-ipadic-neologd) dictionary (v0.0.7).
-
-## Tokenization
-
-The texts are first tokenized by MeCab with the Unidic 2.1.2 dictionary and then split into subwords by the WordPiece algorithm.
-The vocabulary size is 32768.
-
-We used [fugashi](https://github.com/polm/fugashi) and [unidic-lite](https://github.com/polm/unidic-lite) packages for the tokenization.
-
-## Training
-
-We trained the model first on the CC-100 corpus for 1M steps and then on the Wikipedia corpus for another 1M steps.
-For training of the MLM (masked language modeling) objective, we introduced whole word masking in which all of the subword tokens corresponding to a single word (tokenized by MeCab) are masked at once.
-
-For training of each model, we used a v3-8 instance of Cloud TPUs provided by [TPU Research Cloud](https://sites.research.google/trc/about/).
-
-## Licenses
-
-The pretrained models are distributed under the Apache License 2.0.
-
-## Acknowledgments
-
-This model is trained with Cloud TPUs provided by [TPU Research Cloud](https://sites.research.google/trc/about/) program.
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/locations/_sysconfig.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/locations/_sysconfig.py
deleted file mode 100644
index 97aef1f1ac237e6ef97b1a1d026818d7b8ab9be9..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/locations/_sysconfig.py
+++ /dev/null
@@ -1,213 +0,0 @@
-import logging
-import os
-import sys
-import sysconfig
-import typing
-
-from pip._internal.exceptions import InvalidSchemeCombination, UserInstallationInvalid
-from pip._internal.models.scheme import SCHEME_KEYS, Scheme
-from pip._internal.utils.virtualenv import running_under_virtualenv
-
-from .base import change_root, get_major_minor_version, is_osx_framework
-
-logger = logging.getLogger(__name__)
-
-
-# Notes on _infer_* functions.
-# Unfortunately ``get_default_scheme()`` didn't exist before 3.10, so there's no
-# way to ask things like "what is the '_prefix' scheme on this platform". These
-# functions try to answer that with some heuristics while accounting for ad-hoc
-# platforms not covered by CPython's default sysconfig implementation. If the
-# ad-hoc implementation does not fully implement sysconfig, we'll fall back to
-# a POSIX scheme.
-
-_AVAILABLE_SCHEMES = set(sysconfig.get_scheme_names())
-
-_PREFERRED_SCHEME_API = getattr(sysconfig, "get_preferred_scheme", None)
-
-
-def _should_use_osx_framework_prefix() -> bool:
-    """Check for Apple's ``osx_framework_library`` scheme.
-
-    Python distributed by Apple's Command Line Tools has this special scheme
-    that's used when:
-
-    * This is a framework build.
-    * We are installing into the system prefix.
-
-    This does not account for ``pip install --prefix`` (also means we're not
-    installing to the system prefix), which should use ``posix_prefix``, but
-    logic here means ``_infer_prefix()`` outputs ``osx_framework_library``. But
-    since ``prefix`` is not available for ``sysconfig.get_default_scheme()``,
-    which is the stdlib replacement for ``_infer_prefix()``, presumably Apple
-    wouldn't be able to magically switch between ``osx_framework_library`` and
-    ``posix_prefix``. ``_infer_prefix()`` returning ``osx_framework_library``
-    means its behavior is consistent whether we use the stdlib implementation
-    or our own, and we deal with this special case in ``get_scheme()`` instead.
-    """
-    return (
-        "osx_framework_library" in _AVAILABLE_SCHEMES
-        and not running_under_virtualenv()
-        and is_osx_framework()
-    )
-
-
-def _infer_prefix() -> str:
-    """Try to find a prefix scheme for the current platform.
-
-    This tries:
-
-    * A special ``osx_framework_library`` for Python distributed by Apple's
-      Command Line Tools, when not running in a virtual environment.
-    * Implementation + OS, used by PyPy on Windows (``pypy_nt``).
-    * Implementation without OS, used by PyPy on POSIX (``pypy``).
-    * OS + "prefix", used by CPython on POSIX (``posix_prefix``).
-    * Just the OS name, used by CPython on Windows (``nt``).
-
-    If none of the above works, fall back to ``posix_prefix``.
-    """
-    if _PREFERRED_SCHEME_API:
-        return _PREFERRED_SCHEME_API("prefix")
-    if _should_use_osx_framework_prefix():
-        return "osx_framework_library"
-    implementation_suffixed = f"{sys.implementation.name}_{os.name}"
-    if implementation_suffixed in _AVAILABLE_SCHEMES:
-        return implementation_suffixed
-    if sys.implementation.name in _AVAILABLE_SCHEMES:
-        return sys.implementation.name
-    suffixed = f"{os.name}_prefix"
-    if suffixed in _AVAILABLE_SCHEMES:
-        return suffixed
-    if os.name in _AVAILABLE_SCHEMES:  # On Windows, prefx is just called "nt".
-        return os.name
-    return "posix_prefix"
-
-
-def _infer_user() -> str:
-    """Try to find a user scheme for the current platform."""
-    if _PREFERRED_SCHEME_API:
-        return _PREFERRED_SCHEME_API("user")
-    if is_osx_framework() and not running_under_virtualenv():
-        suffixed = "osx_framework_user"
-    else:
-        suffixed = f"{os.name}_user"
-    if suffixed in _AVAILABLE_SCHEMES:
-        return suffixed
-    if "posix_user" not in _AVAILABLE_SCHEMES:  # User scheme unavailable.
-        raise UserInstallationInvalid()
-    return "posix_user"
-
-
-def _infer_home() -> str:
-    """Try to find a home for the current platform."""
-    if _PREFERRED_SCHEME_API:
-        return _PREFERRED_SCHEME_API("home")
-    suffixed = f"{os.name}_home"
-    if suffixed in _AVAILABLE_SCHEMES:
-        return suffixed
-    return "posix_home"
-
-
-# Update these keys if the user sets a custom home.
-_HOME_KEYS = [
-    "installed_base",
-    "base",
-    "installed_platbase",
-    "platbase",
-    "prefix",
-    "exec_prefix",
-]
-if sysconfig.get_config_var("userbase") is not None:
-    _HOME_KEYS.append("userbase")
-
-
-def get_scheme(
-    dist_name: str,
-    user: bool = False,
-    home: typing.Optional[str] = None,
-    root: typing.Optional[str] = None,
-    isolated: bool = False,
-    prefix: typing.Optional[str] = None,
-) -> Scheme:
-    """
-    Get the "scheme" corresponding to the input parameters.
-
-    :param dist_name: the name of the package to retrieve the scheme for, used
-        in the headers scheme path
-    :param user: indicates to use the "user" scheme
-    :param home: indicates to use the "home" scheme
-    :param root: root under which other directories are re-based
-    :param isolated: ignored, but kept for distutils compatibility (where
-        this controls whether the user-site pydistutils.cfg is honored)
-    :param prefix: indicates to use the "prefix" scheme and provides the
-        base directory for the same
-    """
-    if user and prefix:
-        raise InvalidSchemeCombination("--user", "--prefix")
-    if home and prefix:
-        raise InvalidSchemeCombination("--home", "--prefix")
-
-    if home is not None:
-        scheme_name = _infer_home()
-    elif user:
-        scheme_name = _infer_user()
-    else:
-        scheme_name = _infer_prefix()
-
-    # Special case: When installing into a custom prefix, use posix_prefix
-    # instead of osx_framework_library. See _should_use_osx_framework_prefix()
-    # docstring for details.
-    if prefix is not None and scheme_name == "osx_framework_library":
-        scheme_name = "posix_prefix"
-
-    if home is not None:
-        variables = {k: home for k in _HOME_KEYS}
-    elif prefix is not None:
-        variables = {k: prefix for k in _HOME_KEYS}
-    else:
-        variables = {}
-
-    paths = sysconfig.get_paths(scheme=scheme_name, vars=variables)
-
-    # Logic here is very arbitrary, we're doing it for compatibility, don't ask.
-    # 1. Pip historically uses a special header path in virtual environments.
-    # 2. If the distribution name is not known, distutils uses 'UNKNOWN'. We
-    #    only do the same when not running in a virtual environment because
-    #    pip's historical header path logic (see point 1) did not do this.
-    if running_under_virtualenv():
-        if user:
-            base = variables.get("userbase", sys.prefix)
-        else:
-            base = variables.get("base", sys.prefix)
-        python_xy = f"python{get_major_minor_version()}"
-        paths["include"] = os.path.join(base, "include", "site", python_xy)
-    elif not dist_name:
-        dist_name = "UNKNOWN"
-
-    scheme = Scheme(
-        platlib=paths["platlib"],
-        purelib=paths["purelib"],
-        headers=os.path.join(paths["include"], dist_name),
-        scripts=paths["scripts"],
-        data=paths["data"],
-    )
-    if root is not None:
-        for key in SCHEME_KEYS:
-            value = change_root(root, getattr(scheme, key))
-            setattr(scheme, key, value)
-    return scheme
-
-
-def get_bin_prefix() -> str:
-    # Forcing to use /usr/local/bin for standard macOS framework installs.
-    if sys.platform[:6] == "darwin" and sys.prefix[:16] == "/System/Library/":
-        return "/usr/local/bin"
-    return sysconfig.get_paths()["scripts"]
-
-
-def get_purelib() -> str:
-    return sysconfig.get_paths()["purelib"]
-
-
-def get_platlib() -> str:
-    return sysconfig.get_paths()["platlib"]
diff --git a/spaces/TencentARC/VLog/models/grit_src/third_party/CenterNet2/.github/CONTRIBUTING.md b/spaces/TencentARC/VLog/models/grit_src/third_party/CenterNet2/.github/CONTRIBUTING.md
deleted file mode 100644
index 9bab709cae689ba3b92dd52f7fbcc0c6926f4a38..0000000000000000000000000000000000000000
--- a/spaces/TencentARC/VLog/models/grit_src/third_party/CenterNet2/.github/CONTRIBUTING.md
+++ /dev/null
@@ -1,68 +0,0 @@
-# Contributing to detectron2
-
-## Issues
-We use GitHub issues to track public bugs and questions.
-Please make sure to follow one of the
-[issue templates](https://github.com/facebookresearch/detectron2/issues/new/choose)
-when reporting any issues.
-
-Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe
-disclosure of security bugs. In those cases, please go through the process
-outlined on that page and do not file a public issue.
-
-## Pull Requests
-We actively welcome pull requests.
-
-However, if you're adding any significant features (e.g. > 50 lines), please
-make sure to discuss with maintainers about your motivation and proposals in an issue
-before sending a PR. This is to save your time so you don't spend time on a PR that we'll not accept.
-
-We do not always accept new features, and we take the following
-factors into consideration:
-
-1. Whether the same feature can be achieved without modifying detectron2.
-   Detectron2 is designed so that you can implement many extensions from the outside, e.g.
-   those in [projects](https://github.com/facebookresearch/detectron2/tree/master/projects).
-   * If some part of detectron2 is not extensible enough, you can also bring up a more general issue to
-     improve it. Such feature request may be useful to more users.
-2. Whether the feature is potentially useful to a large audience (e.g. an impactful detection paper, a popular dataset,
-   a significant speedup, a widely useful utility),
-   or only to a small portion of users (e.g., a less-known paper, an improvement not in the object
-   detection field, a trick that's not very popular in the community, code to handle a non-standard type of data)
-   * Adoption of additional models, datasets, new task are by default not added to detectron2 before they
-     receive significant popularity in the community.
-     We sometimes accept such features in `projects/`, or as a link in `projects/README.md`.
-3. Whether the proposed solution has a good design / interface. This can be discussed in the issue prior to PRs, or
-   in the form of a draft PR.
-4. Whether the proposed solution adds extra mental/practical overhead to users who don't
-   need such feature.
-5. Whether the proposed solution breaks existing APIs.
-
-To add a feature to an existing function/class `Func`, there are always two approaches:
-(1) add new arguments to `Func`; (2) write a new `Func_with_new_feature`.
-To meet the above criteria, we often prefer approach (2), because:
-
-1. It does not involve modifying or potentially breaking existing code.
-2. It does not add overhead to users who do not need the new feature.
-3. Adding new arguments to a function/class is not scalable w.r.t. all the possible new research ideas in the future.
-
-When sending a PR, please do:
-
-1. If a PR contains multiple orthogonal changes, split it to several PRs.
-2. If you've added code that should be tested, add tests.
-3. For PRs that need experiments (e.g. adding a new model or new methods),
-   you don't need to update model zoo, but do provide experiment results in the description of the PR.
-4. If APIs are changed, update the documentation.
-5. We use the [Google style docstrings](https://www.sphinx-doc.org/en/master/usage/extensions/napoleon.html) in python.
-6. Make sure your code lints with `./dev/linter.sh`.
-
-
-## Contributor License Agreement ("CLA")
-In order to accept your pull request, we need you to submit a CLA. You only need
-to do this once to work on any of Facebook's open source projects.
-
-Complete your CLA here: <https://code.facebook.com/cla>
-
-## License
-By contributing to detectron2, you agree that your contributions will be licensed
-under the LICENSE file in the root directory of this source tree.
diff --git a/spaces/User1342/WatchTower/Pinpoint/Serializer.py b/spaces/User1342/WatchTower/Pinpoint/Serializer.py
deleted file mode 100644
index a8ef4687228f175ec529ec55a4f4d7f6c3319e97..0000000000000000000000000000000000000000
--- a/spaces/User1342/WatchTower/Pinpoint/Serializer.py
+++ /dev/null
@@ -1,20 +0,0 @@
-# todo This file should be used to store common serialisations across aggregating data
-
-def createPostDict(date, post_text, likes, comments, shares, source="self"):
-    '''
-    Creates a dictionary containing the pertinent information from a social media post. This should later be added to a list
-    of other posts from that account and then added to a master dictionary.
-    :param date:
-    :param post_text:
-    :param likes:
-    :param comments:
-    :param shares:
-    :param source:
-    :return: a dictionary containing pertinent post information
-    '''
-    return {"text": post_text, "likes": likes, "comments": comments, "shares": shares, "source": source, "date": date}
-
-
-def createWholeUserDict(unique_id, reddit_list, instagram_list, twitter_list, survey_data):
-    return {"id": unique_id, "reddit": reddit_list, "instagram": instagram_list, "twitter": twitter_list,
-            "survey": survey_data}
diff --git a/spaces/UserXTheUnknown/stablediffusion-infinity/PyPatchMatch/examples/cpp_example_run.sh b/spaces/UserXTheUnknown/stablediffusion-infinity/PyPatchMatch/examples/cpp_example_run.sh
deleted file mode 100644
index cfb62557fe4a5bb0ee1aa48d7aa8582c23f4e6fc..0000000000000000000000000000000000000000
--- a/spaces/UserXTheUnknown/stablediffusion-infinity/PyPatchMatch/examples/cpp_example_run.sh
+++ /dev/null
@@ -1,18 +0,0 @@
-#! /bin/bash
-#
-# cpp_example_run.sh
-# Copyright (C) 2020 Jiayuan Mao <maojiayuan@gmail.com>
-#
-# Distributed under terms of the MIT license.
-#
-
-set -x
-
-CFLAGS="-std=c++14 -O2 $(pkg-config --cflags opencv)"
-LDFLAGS="$(pkg-config --libs opencv)"
-g++ $CFLAGS cpp_example.cpp -I../csrc/ -L../ -lpatchmatch $LDFLAGS -o cpp_example.exe
-
-export DYLD_LIBRARY_PATH=../:$DYLD_LIBRARY_PATH  # For macOS
-export LD_LIBRARY_PATH=../:$LD_LIBRARY_PATH  # For Linux
-time ./cpp_example.exe
-
diff --git a/spaces/VaishakhRaveendran/Audio_2_chat/app.py b/spaces/VaishakhRaveendran/Audio_2_chat/app.py
deleted file mode 100644
index 6a5ac217436443f148741d81ac6cf5dc8b3b5056..0000000000000000000000000000000000000000
--- a/spaces/VaishakhRaveendran/Audio_2_chat/app.py
+++ /dev/null
@@ -1,208 +0,0 @@
-import streamlit as st
-import tempfile
-import re
-from scripts.utils import save_uploaded_file, break_chunks
-from scripts.whisper_transcribe import wtranscribe
-from scripts import text2markdown, summarize
-# from scripts import credentials # REMOVE CREDENTIALS
-
-# create temp dir for storing video and outputs
-temp_dir = tempfile.TemporaryDirectory()
-temp_path = temp_dir.name
-
-__, col, __ = st.columns([1, 3, 1])
-with col:
-    st.image("./images/notebook_logo_transparent.png")
-
-with st.expander("How to Use YOListenO"):
-    instruct = """
-    1. Upload a lecture/meeting audio or video file
-    2. Select whether you want the output as a lecture or meeting note
-    3. (Optional): Adjust advanced settings for better fine-tuning and click "Submit" for each adjusted tab
-    4. (Optional): Use your own OpenAI api key under advanced settings as the default has a limit
-    5. Click "Start YOListenO" and let the magic begin! 
-    
-    Note: Sometimes OpenAI's server might be busy, which might cause an error. Simply try again after a while!
-    """
-    st.write(instruct)
-
-
-st.write("# Upload Audio/Video:\n")
-
-file = st.file_uploader(
-    "Choose a File", accept_multiple_files=False, type=["mp3", "wav", "mp4", "mov", "mpeg"],
-)
-
-if file is not None:
-    # save uploaded file to temp location
-    file_details = {"FileName": file.name, "FileType": file.type}
-    file_path = save_uploaded_file(file, temp_path)
-
-    # user options
-    with st.expander("Settings", expanded=True):
-        note_type = st.selectbox(
-                'Desired Note Type:',
-                ('Lecture', 'Meeting')
-        )
-        if note_type == 'Lecture':
-            sys_content = text2markdown.SYSTEM_CONTENT_LECTURES
-            use_content = text2markdown.USER_CONTENT_LECTURES
-        elif note_type == 'Meeting':
-            sys_content = text2markdown.SYSTEM_CONTENT_MEETINGS
-            use_content = text2markdown.USER_CONTENT_MEETINGS
-    
-    # user advanced settings
-    with st.expander("Advanced Settings"):
-        system, user, additional = st.tabs(["System Content", "User Content", "Additional Settings"])
-
-        with system:
-            with st.form("system_content_form"):
-                system_content = st.text_area(
-                    label='System Content (leave as default if unsure)',
-                    value=sys_content,
-                    help='Provide system role to set behavior of the assistant and provide high level instructions for the conversation',
-                    placeholder=sys_content
-                )   
-                # Every form must have a submit button.
-                submitted = st.form_submit_button("Submit System Content")
-            
-            st.subheader('Preview')
-            st.info(system_content)
-
-        with user:
-            with st.form("user_content_form"):
-                user_content = st.text_area(
-                    label='User Content  (leave as default if unsure)',
-                    value=use_content,
-                    help='Specific instructions from the user for the assistant',
-                    placeholder=use_content
-                )   
-                # Every form must have a submit button.
-                submitted = st.form_submit_button("Submit User Content")
-            
-            st.subheader('Preview')
-            st.info(user_content)
-        
-        with additional:
-            with st.form("add_settings_form"):
-                temp = st.number_input(
-                    "Temperature",
-                    min_value=0.0,
-                    max_value=1.0,
-                    value=0.2,
-                    step=0.1,
-                    help="How creative and random the markdown output is. 0 will give straightforward, deterministic responses, while 1 will give wildly varied responses.",
-                )
-                transcript_max_token_len = st.number_input(
-                    "Transcript Max Token Length",
-                    min_value=0,
-                    max_value=4000,
-                    value=2500,
-                    step=100,
-                    help="The number of tokens in transcript before chunking is used. This is a workaround for very long transcripts as GPT3.5 cannot handle >4k tokens."
-                )
-                summarized_chunk_max_len = st.number_input(
-                    "Chunking Summary Max Length",
-                    min_value=50,
-                    max_value=500,
-                    value=200,
-                    step=50,
-                    help="The maximum length of each summarized chunk if chunking is performed for very long transcripts."
-                )
-                apikey = st.text_input(
-                    label='API Key (Optional)',
-                    type="password",
-                    help="Use your own OpenAI key if possible. Else, it will use mine but there is a limit every month."
-                )
-
-                # Every form must have a submit button.
-                submitted = st.form_submit_button("Submit Additional Settings")
-
-    convert_bt = st.button("Start YOListenO!")
-    if convert_bt:
-        
-        if not apikey:
-            # apikey = credentials.api_key # CHANGE THIS TO SECRET 
-            apikey = st.secrets["API_KEY"]
-
-        # transcribe
-        with st.spinner(text="YOListenO working its magic: Transcribing..."):
-            transcript = wtranscribe(
-                model='base',
-                audio=file_path,
-                temperature=0.2,
-            )
-            transcript_orig = transcript
-
-        # tokenize and check length. 
-        tokens = re.findall(r"[\w']+|[.,!?;]", transcript)
-        if len(tokens) > transcript_max_token_len:
-            # break into smaller chunks, summarize each chunk, and merge back together
-            with st.spinner(text="YOListenO working its magic: Chunking & Summarizing..."):
-                # perform chunking
-                chunks = break_chunks(tokens, [".", ",", "!", "?", ";"], 700, 1100)
-                # summarise each chunk
-                summarized_chunks = []
-                for chunk in chunks:
-                    summary = summarize.summarize(
-                        text=chunk,
-                        api_key=apikey,
-                        summarized_max_len=summarized_chunk_max_len,
-                    )
-                    summarized_chunks.append(summary)
-                # join summarised chunks into transcript
-                transcript = ' '.join(summarized_chunks)
-
-        # convert to markdown
-        with st.spinner(
-            text="YOListenO working its magic: CONVERSION IN PROGRESS ..."
-        ):
-            result = text2markdown.text2markdown(
-                transcript=transcript, 
-                api_key=apikey,
-                system_content=system_content,
-                user_content=user_content,
-                temperature=temp,
-            )
-
-        tab_transcript, tab_markdown, tab_raw= st.tabs(
-            [
-                "Transcript and Audio",
-                "Markdown Preview",
-                "Raw Markdown"
-            ]
-        )
-
-        # display transcript and audio
-        with tab_transcript:
-            audio_file = open(file_path, 'rb')
-            audio_bytes = audio_file.read()
-            st.audio(audio_bytes)
-            st.info(transcript_orig)
-
-        with tab_markdown:
-            st.header('Preview')
-            st.divider()
-            st.markdown(result)
-
-        with tab_raw:
-            st.header('Raw Output')
-            st.divider()
-            st.text(result)
-
-
-with st.expander("About YOListenO"):
-    __, col2, __ = st.columns([1, 1, 1])
-    with col2:
-        st.image("./images/notebook_logo_transparent.png")
-
-    about = """
-    **[YOListenO (You Only Listen Once)](https://github.com/teyang-lau/YOListenO)** is an AI tool making use of OpenAI's 
-    [Whisper](https://github.com/openai/whisper) and [GPT3.5](https://platform.openai.com/docs/guides/chat)
-    for turning audio/video lectures/meetings into markdown notes.
-    
-    **Created by:**
-    * LAU TeYang
-    """
-    st.write(about)
-    st.write("")
\ No newline at end of file
diff --git a/spaces/Vgi/nu-dialogue-sfc2022-stable-diffusion/README.md b/spaces/Vgi/nu-dialogue-sfc2022-stable-diffusion/README.md
deleted file mode 100644
index c64d5e556d0392c1a937749bc8101bf3a361ca00..0000000000000000000000000000000000000000
--- a/spaces/Vgi/nu-dialogue-sfc2022-stable-diffusion/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Nu Dialogue Sfc2022 Stable Diffusion
-emoji: 👀
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: gpl-3.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/VideoCrafter/VideoCrafter/scripts/evaluation/ddp_wrapper.py b/spaces/VideoCrafter/VideoCrafter/scripts/evaluation/ddp_wrapper.py
deleted file mode 100644
index 01853c13c5702f81fc2d78a591119d813cae5fef..0000000000000000000000000000000000000000
--- a/spaces/VideoCrafter/VideoCrafter/scripts/evaluation/ddp_wrapper.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import datetime
-import argparse, importlib
-from pytorch_lightning import seed_everything
-
-import torch
-import torch.distributed as dist
-
-def setup_dist(local_rank):
-    if dist.is_initialized():
-        return
-    torch.cuda.set_device(local_rank)
-    torch.distributed.init_process_group('nccl', init_method='env://')
-
-
-def get_dist_info():
-    if dist.is_available():
-        initialized = dist.is_initialized()
-    else:
-        initialized = False
-    if initialized:
-        rank = dist.get_rank()
-        world_size = dist.get_world_size()
-    else:
-        rank = 0
-        world_size = 1
-    return rank, world_size
-
-
-if __name__ == '__main__':
-    now = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--module", type=str, help="module name", default="inference")
-    parser.add_argument("--local_rank", type=int, nargs="?", help="for ddp", default=0)
-    args, unknown = parser.parse_known_args()
-    inference_api = importlib.import_module(args.module, package=None)
-
-    inference_parser = inference_api.get_parser()
-    inference_args, unknown = inference_parser.parse_known_args()
-
-    seed_everything(inference_args.seed)
-    setup_dist(args.local_rank)
-    torch.backends.cudnn.benchmark = True
-    rank, gpu_num = get_dist_info()
-
-    print("@CoLVDM Inference [rank%d]: %s"%(rank, now))
-    inference_api.run_inference(inference_args, gpu_num, rank)
\ No newline at end of file
diff --git a/spaces/VincentZB/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_pose.py b/spaces/VincentZB/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_pose.py
deleted file mode 100644
index 90d56b8291cedec3d2e3cb90f806b3fcddc21383..0000000000000000000000000000000000000000
--- a/spaces/VincentZB/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_pose.py
+++ /dev/null
@@ -1,189 +0,0 @@
-import gradio as gr
-import torch
-from controlnet_aux import OpenposeDetector
-from diffusers import (
-    ControlNetModel,
-    StableDiffusionControlNetPipeline,
-    UniPCMultistepScheduler,
-)
-from PIL import Image
-
-from diffusion_webui.utils.model_list import (
-    controlnet_pose_model_list,
-    stable_model_list,
-)
-from diffusion_webui.utils.scheduler_list import (
-    SCHEDULER_LIST,
-    get_scheduler_list,
-)
-
-
-class StableDiffusionControlNetPoseGenerator:
-    def __init__(self):
-        self.pipe = None
-
-    def load_model(self, stable_model_path, controlnet_model_path, scheduler):
-        if self.pipe is None:
-            controlnet = ControlNetModel.from_pretrained(
-                controlnet_model_path, torch_dtype=torch.float16
-            )
-
-            self.pipe = StableDiffusionControlNetPipeline.from_pretrained(
-                pretrained_model_name_or_path=stable_model_path,
-                controlnet=controlnet,
-                safety_checker=None,
-                torch_dtype=torch.float16,
-            )
-
-        self.pipe = get_scheduler_list(pipe=self.pipe, scheduler=scheduler)
-        self.pipe.to("cuda")
-        self.pipe.enable_xformers_memory_efficient_attention()
-
-        return self.pipe
-
-    def controlnet_pose(self, image_path: str):
-        openpose = OpenposeDetector.from_pretrained("lllyasviel/ControlNet")
-
-        image = Image.open(image_path)
-        image = openpose(image)
-
-        return image
-
-    def generate_image(
-        self,
-        image_path: str,
-        stable_model_path: str,
-        controlnet_pose_model_path: str,
-        prompt: str,
-        negative_prompt: str,
-        num_images_per_prompt: int,
-        guidance_scale: int,
-        num_inference_step: int,
-        scheduler: str,
-        seed_generator: int,
-    ):
-
-        image = self.controlnet_pose(image_path=image_path)
-
-        pipe = self.load_model(
-            stable_model_path=stable_model_path,
-            controlnet_model_path=controlnet_pose_model_path,
-            scheduler=scheduler,
-        )
-
-        if seed_generator == 0:
-            random_seed = torch.randint(0, 1000000, (1,))
-            generator = torch.manual_seed(random_seed)
-        else:
-            generator = torch.manual_seed(seed_generator)
-
-        output = pipe(
-            prompt=prompt,
-            image=image,
-            negative_prompt=negative_prompt,
-            num_images_per_prompt=num_images_per_prompt,
-            num_inference_steps=num_inference_step,
-            guidance_scale=guidance_scale,
-            generator=generator,
-        ).images
-
-        return output
-
-    def app():
-        with gr.Blocks():
-            with gr.Row():
-                with gr.Column():
-                    controlnet_pose_image_file = gr.Image(
-                        type="filepath", label="Image"
-                    )
-
-                    controlnet_pose_prompt = gr.Textbox(
-                        lines=1,
-                        show_label=False,
-                        placeholder="Prompt",
-                    )
-
-                    controlnet_pose_negative_prompt = gr.Textbox(
-                        lines=1,
-                        show_label=False,
-                        placeholder="Negative Prompt",
-                    )
-
-                    with gr.Row():
-                        with gr.Column():
-                            controlnet_pose_stable_model_id = gr.Dropdown(
-                                choices=stable_model_list,
-                                value=stable_model_list[0],
-                                label="Stable Model Id",
-                            )
-                            controlnet_pose_guidance_scale = gr.Slider(
-                                minimum=0.1,
-                                maximum=15,
-                                step=0.1,
-                                value=7.5,
-                                label="Guidance Scale",
-                            )
-
-                            controlnet_pose_num_inference_step = gr.Slider(
-                                minimum=1,
-                                maximum=100,
-                                step=1,
-                                value=50,
-                                label="Num Inference Step",
-                            )
-
-                            controlnet_pose_num_images_per_prompt = gr.Slider(
-                                minimum=1,
-                                maximum=10,
-                                step=1,
-                                value=1,
-                                label="Number Of Images",
-                            )
-
-                        with gr.Row():
-                            with gr.Column():
-                                controlnet_pose_model_id = gr.Dropdown(
-                                    choices=controlnet_pose_model_list,
-                                    value=controlnet_pose_model_list[0],
-                                    label="ControlNet Model Id",
-                                )
-
-                                controlnet_pose_scheduler = gr.Dropdown(
-                                    choices=SCHEDULER_LIST,
-                                    value=SCHEDULER_LIST[0],
-                                    label="Scheduler",
-                                )
-
-                                controlnet_pose_seed_generator = gr.Number(
-                                    minimum=0,
-                                    maximum=1000000,
-                                    step=1,
-                                    value=0,
-                                    label="Seed Generator",
-                                )
-
-                    controlnet_pose_predict = gr.Button(value="Generator")
-
-                with gr.Column():
-                    output_image = gr.Gallery(
-                        label="Generated images",
-                        show_label=False,
-                        elem_id="gallery",
-                    ).style(grid=(1, 2))
-
-            controlnet_pose_predict.click(
-                fn=StableDiffusionControlNetPoseGenerator().generate_image,
-                inputs=[
-                    controlnet_pose_image_file,
-                    controlnet_pose_stable_model_id,
-                    controlnet_pose_model_id,
-                    controlnet_pose_prompt,
-                    controlnet_pose_negative_prompt,
-                    controlnet_pose_num_images_per_prompt,
-                    controlnet_pose_guidance_scale,
-                    controlnet_pose_num_inference_step,
-                    controlnet_pose_scheduler,
-                    controlnet_pose_seed_generator,
-                ],
-                outputs=output_image,
-            )
diff --git a/spaces/Voicelab/vlT5-rfc-generation/app.py b/spaces/Voicelab/vlT5-rfc-generation/app.py
deleted file mode 100644
index bd93f881902c89031486464b3c82b995274fdb68..0000000000000000000000000000000000000000
--- a/spaces/Voicelab/vlT5-rfc-generation/app.py
+++ /dev/null
@@ -1,104 +0,0 @@
-from transformers import T5ForConditionalGeneration, T5Tokenizer
-import streamlit as st
-from PIL import Image
-import os
-
-
-@st.cache(allow_output_mutation=True)
-def load_model_cache():
-    auth_token = os.environ.get("TOKEN_FROM_SECRET") or True
-
-    tokenizer_pl = T5Tokenizer.from_pretrained(
-        "Voicelab/vlt5-base-rfc-v1_2", use_auth_token=auth_token
-    )
-    model_pl = T5ForConditionalGeneration.from_pretrained(
-        "Voicelab/vlt5-base-rfc-v1_2", use_auth_token=auth_token
-    )
-    model_det_pl = T5ForConditionalGeneration.from_pretrained(
-        "Voicelab/vlt5-base-rfc-detector-1.0", use_auth_token=auth_token
-    )
-
-    return tokenizer_pl, model_pl, model_det_pl
-
-
-img_full = Image.open("images/vl-logo-nlp-blue.png")
-img_short = Image.open("images/sVL-NLP-short.png")
-img_favicon = Image.open("images/favicon_vl.png")
-max_length: int = 5000
-cache_size: int = 100
-
-st.set_page_config(
-    page_title="DEMO - Reason for Contact generation",
-    page_icon=img_favicon,
-    initial_sidebar_state="expanded",
-)
-
-tokenizer_pl, model_pl, model_det_pl = load_model_cache()
-
-
-def get_predictions(text, mode):
-    input_ids = tokenizer_pl(text, return_tensors="pt", truncation=True).input_ids
-    if mode == "Polish - RfC Generation":
-        output = model_pl.generate(
-            input_ids,
-            no_repeat_ngram_size=1,
-            num_beams=3,
-            num_beam_groups=3,
-            min_length=10,
-            max_length=100,
-            diversity_penalty=1.0,
-        )
-    elif mode == "Polish - RfC Detection":
-        output = model_det_pl.generate(
-            input_ids,
-            no_repeat_ngram_size=2,
-            num_beams=3,
-            num_beam_groups=3,
-            repetition_penalty=1.5,
-            diversity_penalty=2.0,
-            length_penalty=2.0,
-        )
-    predicted_rfc = tokenizer_pl.decode(output[0], skip_special_tokens=True)
-    return predicted_rfc
-
-
-def trim_length():
-    if len(st.session_state["input"]) > max_length:
-        st.session_state["input"] = st.session_state["input"][:max_length]
-
-
-if __name__ == "__main__":
-    st.sidebar.image(img_short)
-    st.image(img_full)
-    st.title("VLT5 - Reason for Contact generator")
-    st.markdown("#### RfC Generation model.")
-    st.markdown("**Input**: Whole conversation. Should specify roles e.g. *AGENT: Hello, how can I help you? CLIENT: Hi, I would like to report a stolen card.* Put a whole conversation or full e-mail here.")
-    st.markdown("**Output**: Reason for calling for the whole conversation.")
-    st.markdown("#### RfC Detection model.")
-    st.markdown("**Input**: A single turn from the conversation e.g. *'Hello, how can I help you?'* or *'Hi, I would like to report a stolen card.'. Put a single turn or a few sentences here.*")
-    st.markdown("**Output**: Model will return an empty string if a turn possibly does not includes Reason for Calling, or a sentence if the RfC is detected.")
-    
-    generated_rfc = ""
-    user_input = st.text_area(
-        label=f"Input text (max {max_length} characters)",
-        value="",
-        height=300,
-        on_change=trim_length,
-        key="input",
-    )
-
-    mode = st.sidebar.title("Model settings")
-    mode = st.sidebar.radio(
-        "Select model to test",
-        [
-            "Polish - RfC Generation",
-            "Polish - RfC Detection",
-        ],
-    )
-
-    result = st.button("Find reason for contact")
-
-    if result:
-        generated_rfc = get_predictions(text=user_input, mode=mode)
-        st.text_area("Find reason for contact", generated_rfc)
-        print(f"Input: {user_input} ---> Reason for contact: {generated_rfc}")
\ No newline at end of file
diff --git a/spaces/Wanlau/sovits-4.0_datealive/modules/modules.py b/spaces/Wanlau/sovits-4.0_datealive/modules/modules.py
deleted file mode 100644
index 54290fd207b25e93831bd21005990ea137e6b50e..0000000000000000000000000000000000000000
--- a/spaces/Wanlau/sovits-4.0_datealive/modules/modules.py
+++ /dev/null
@@ -1,342 +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 modules.commons as commons
-from modules.commons import init_weights, get_padding
-
-
-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
diff --git a/spaces/WorldlineChanger/sayashi-vits-uma-genshin-honkai/text/__init__.py b/spaces/WorldlineChanger/sayashi-vits-uma-genshin-honkai/text/__init__.py
deleted file mode 100644
index 663c4b6416affb53c9dc56dddbc8b2b65d4bf518..0000000000000000000000000000000000000000
--- a/spaces/WorldlineChanger/sayashi-vits-uma-genshin-honkai/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/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/models/attention.py b/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/models/attention.py
deleted file mode 100644
index 6ad0af18c1c935e96de4e2928a2977f2f96e7ea6..0000000000000000000000000000000000000000
--- a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/models/attention.py
+++ /dev/null
@@ -1,833 +0,0 @@
-# Copyright 2022 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 math
-import warnings
-from dataclasses import dataclass
-from typing import Optional
-
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from ..configuration_utils import ConfigMixin, register_to_config
-from ..modeling_utils import ModelMixin
-from ..models.embeddings import ImagePositionalEmbeddings
-from ..utils import BaseOutput
-from ..utils.import_utils import is_xformers_available
-
-
-@dataclass
-class Transformer2DModelOutput(BaseOutput):
-    """
-    Args:
-        sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` or `(batch size, num_vector_embeds - 1, num_latent_pixels)` if [`Transformer2DModel`] is discrete):
-            Hidden states conditioned on `encoder_hidden_states` input. If discrete, returns probability distributions
-            for the unnoised latent pixels.
-    """
-
-    sample: torch.FloatTensor
-
-
-if is_xformers_available():
-    import xformers
-    import xformers.ops
-else:
-    xformers = None
-
-
-class Transformer2DModel(ModelMixin, ConfigMixin):
-    """
-    Transformer model for image-like data. Takes either discrete (classes of vector embeddings) or continuous (actual
-    embeddings) inputs.
-
-    When input is continuous: First, project the input (aka embedding) and reshape to b, t, d. Then apply standard
-    transformer action. Finally, reshape to image.
-
-    When input is discrete: First, input (classes of latent pixels) is converted to embeddings and has positional
-    embeddings applied, see `ImagePositionalEmbeddings`. Then apply standard transformer action. Finally, predict
-    classes of unnoised image.
-
-    Note that it is assumed one of the input classes is the masked latent pixel. The predicted classes of the unnoised
-    image do not contain a prediction for the masked pixel as the unnoised image cannot be masked.
-
-    Parameters:
-        num_attention_heads (`int`, *optional*, defaults to 16): The number of heads to use for multi-head attention.
-        attention_head_dim (`int`, *optional*, defaults to 88): The number of channels in each head.
-        in_channels (`int`, *optional*):
-            Pass if the input is continuous. The number of channels in the input and output.
-        num_layers (`int`, *optional*, defaults to 1): The number of layers of Transformer blocks to use.
-        dropout (`float`, *optional*, defaults to 0.1): The dropout probability to use.
-        cross_attention_dim (`int`, *optional*): The number of context dimensions to use.
-        sample_size (`int`, *optional*): Pass if the input is discrete. The width of the latent images.
-            Note that this is fixed at training time as it is used for learning a number of position embeddings. See
-            `ImagePositionalEmbeddings`.
-        num_vector_embeds (`int`, *optional*):
-            Pass if the input is discrete. The number of classes of the vector embeddings of the latent pixels.
-            Includes the class for the masked latent pixel.
-        activation_fn (`str`, *optional*, defaults to `"geglu"`): Activation function to be used in feed-forward.
-        num_embeds_ada_norm ( `int`, *optional*): Pass if at least one of the norm_layers is `AdaLayerNorm`.
-            The number of diffusion steps used during training. Note that this is fixed at training time as it is used
-            to learn a number of embeddings that are added to the hidden states. During inference, you can denoise for
-            up to but not more than steps than `num_embeds_ada_norm`.
-        attention_bias (`bool`, *optional*):
-            Configure if the TransformerBlocks' attention should contain a bias parameter.
-    """
-
-    @register_to_config
-    def __init__(
-        self,
-        num_attention_heads: int = 16,
-        attention_head_dim: int = 88,
-        in_channels: Optional[int] = None,
-        num_layers: int = 1,
-        dropout: float = 0.0,
-        norm_num_groups: int = 32,
-        cross_attention_dim: Optional[int] = None,
-        attention_bias: bool = False,
-        sample_size: Optional[int] = None,
-        num_vector_embeds: Optional[int] = None,
-        activation_fn: str = "geglu",
-        num_embeds_ada_norm: Optional[int] = None,
-        use_linear_projection: bool = False,
-        only_cross_attention: bool = False,
-    ):
-        super().__init__()
-        self.use_linear_projection = use_linear_projection
-        self.num_attention_heads = num_attention_heads
-        self.attention_head_dim = attention_head_dim
-        inner_dim = num_attention_heads * attention_head_dim
-
-        # 1. Transformer2DModel can process both standard continous images of shape `(batch_size, num_channels, width, height)` as well as quantized image embeddings of shape `(batch_size, num_image_vectors)`
-        # Define whether input is continuous or discrete depending on configuration
-        self.is_input_continuous = in_channels is not None
-        self.is_input_vectorized = num_vector_embeds is not None
-
-        if self.is_input_continuous and self.is_input_vectorized:
-            raise ValueError(
-                f"Cannot define both `in_channels`: {in_channels} and `num_vector_embeds`: {num_vector_embeds}. Make"
-                " sure that either `in_channels` or `num_vector_embeds` is None."
-            )
-        elif not self.is_input_continuous and not self.is_input_vectorized:
-            raise ValueError(
-                f"Has to define either `in_channels`: {in_channels} or `num_vector_embeds`: {num_vector_embeds}. Make"
-                " sure that either `in_channels` or `num_vector_embeds` is not None."
-            )
-
-        # 2. Define input layers
-        if self.is_input_continuous:
-            self.in_channels = in_channels
-
-            self.norm = torch.nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=1e-6, affine=True)
-            if use_linear_projection:
-                self.proj_in = nn.Linear(in_channels, inner_dim)
-            else:
-                self.proj_in = nn.Conv2d(in_channels, inner_dim, kernel_size=1, stride=1, padding=0)
-        elif self.is_input_vectorized:
-            assert sample_size is not None, "Transformer2DModel over discrete input must provide sample_size"
-            assert num_vector_embeds is not None, "Transformer2DModel over discrete input must provide num_embed"
-
-            self.height = sample_size
-            self.width = sample_size
-            self.num_vector_embeds = num_vector_embeds
-            self.num_latent_pixels = self.height * self.width
-
-            self.latent_image_embedding = ImagePositionalEmbeddings(
-                num_embed=num_vector_embeds, embed_dim=inner_dim, height=self.height, width=self.width
-            )
-
-        # 3. Define transformers blocks
-        self.transformer_blocks = nn.ModuleList(
-            [
-                BasicTransformerBlock(
-                    inner_dim,
-                    num_attention_heads,
-                    attention_head_dim,
-                    dropout=dropout,
-                    cross_attention_dim=cross_attention_dim,
-                    activation_fn=activation_fn,
-                    num_embeds_ada_norm=num_embeds_ada_norm,
-                    attention_bias=attention_bias,
-                    only_cross_attention=only_cross_attention,
-                )
-                for d in range(num_layers)
-            ]
-        )
-
-        # 4. Define output layers
-        if self.is_input_continuous:
-            if use_linear_projection:
-                self.proj_out = nn.Linear(in_channels, inner_dim)
-            else:
-                self.proj_out = nn.Conv2d(inner_dim, in_channels, kernel_size=1, stride=1, padding=0)
-        elif self.is_input_vectorized:
-            self.norm_out = nn.LayerNorm(inner_dim)
-            self.out = nn.Linear(inner_dim, self.num_vector_embeds - 1)
-
-    def _set_attention_slice(self, slice_size):
-        for block in self.transformer_blocks:
-            block._set_attention_slice(slice_size)
-
-    def forward(self, hidden_states, encoder_hidden_states=None, timestep=None, return_dict: bool = True):
-        """
-        Args:
-            hidden_states ( When discrete, `torch.LongTensor` of shape `(batch size, num latent pixels)`.
-                When continous, `torch.FloatTensor` of shape `(batch size, channel, height, width)`): Input
-                hidden_states
-            encoder_hidden_states ( `torch.LongTensor` of shape `(batch size, context dim)`, *optional*):
-                Conditional embeddings for cross attention layer. If not given, cross-attention defaults to
-                self-attention.
-            timestep ( `torch.long`, *optional*):
-                Optional timestep to be applied as an embedding in AdaLayerNorm's. Used to indicate denoising step.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`models.unet_2d_condition.UNet2DConditionOutput`] instead of a plain tuple.
-
-        Returns:
-            [`~models.attention.Transformer2DModelOutput`] or `tuple`: [`~models.attention.Transformer2DModelOutput`]
-            if `return_dict` is True, otherwise a `tuple`. When returning a tuple, the first element is the sample
-            tensor.
-        """
-        # 1. Input
-        if self.is_input_continuous:
-            batch, channel, height, weight = hidden_states.shape
-            residual = hidden_states
-
-            hidden_states = self.norm(hidden_states)
-            if not self.use_linear_projection:
-                hidden_states = self.proj_in(hidden_states)
-                inner_dim = hidden_states.shape[1]
-                hidden_states = hidden_states.permute(0, 2, 3, 1).reshape(batch, height * weight, inner_dim)
-            else:
-                inner_dim = hidden_states.shape[1]
-                hidden_states = hidden_states.permute(0, 2, 3, 1).reshape(batch, height * weight, inner_dim)
-                hidden_states = self.proj_in(hidden_states)
-        elif self.is_input_vectorized:
-            hidden_states = self.latent_image_embedding(hidden_states)
-
-        # 2. Blocks
-        for block in self.transformer_blocks:
-            hidden_states = block(hidden_states, context=encoder_hidden_states, timestep=timestep)
-
-        # 3. Output
-        if self.is_input_continuous:
-            if not self.use_linear_projection:
-                hidden_states = (
-                    hidden_states.reshape(batch, height, weight, inner_dim).permute(0, 3, 1, 2).contiguous()
-                )
-                hidden_states = self.proj_out(hidden_states)
-            else:
-                hidden_states = self.proj_out(hidden_states)
-                hidden_states = (
-                    hidden_states.reshape(batch, height, weight, inner_dim).permute(0, 3, 1, 2).contiguous()
-                )
-
-            output = hidden_states + residual
-        elif self.is_input_vectorized:
-            hidden_states = self.norm_out(hidden_states)
-            logits = self.out(hidden_states)
-            # (batch, self.num_vector_embeds - 1, self.num_latent_pixels)
-            logits = logits.permute(0, 2, 1)
-
-            # log(p(x_0))
-            output = F.log_softmax(logits.double(), dim=1).float()
-
-        if not return_dict:
-            return (output,)
-
-        return Transformer2DModelOutput(sample=output)
-
-
-class AttentionBlock(nn.Module):
-    """
-    An attention block that allows spatial positions to attend to each other. Originally ported from here, but adapted
-    to the N-d case.
-    https://github.com/hojonathanho/diffusion/blob/1e0dceb3b3495bbe19116a5e1b3596cd0706c543/diffusion_tf/models/unet.py#L66.
-    Uses three q, k, v linear layers to compute attention.
-
-    Parameters:
-        channels (`int`): The number of channels in the input and output.
-        num_head_channels (`int`, *optional*):
-            The number of channels in each head. If None, then `num_heads` = 1.
-        norm_num_groups (`int`, *optional*, defaults to 32): The number of groups to use for group norm.
-        rescale_output_factor (`float`, *optional*, defaults to 1.0): The factor to rescale the output by.
-        eps (`float`, *optional*, defaults to 1e-5): The epsilon value to use for group norm.
-    """
-
-    def __init__(
-        self,
-        channels: int,
-        num_head_channels: Optional[int] = None,
-        norm_num_groups: int = 32,
-        rescale_output_factor: float = 1.0,
-        eps: float = 1e-5,
-    ):
-        super().__init__()
-        self.channels = channels
-
-        self.num_heads = channels // num_head_channels if num_head_channels is not None else 1
-        self.num_head_size = num_head_channels
-        self.group_norm = nn.GroupNorm(num_channels=channels, num_groups=norm_num_groups, eps=eps, affine=True)
-
-        # define q,k,v as linear layers
-        self.query = nn.Linear(channels, channels)
-        self.key = nn.Linear(channels, channels)
-        self.value = nn.Linear(channels, channels)
-
-        self.rescale_output_factor = rescale_output_factor
-        self.proj_attn = nn.Linear(channels, channels, 1)
-
-    def reshape_heads_to_batch_dim(self, tensor):
-        batch_size, seq_len, dim = tensor.shape
-        head_size = self.num_heads
-        tensor = tensor.reshape(batch_size, seq_len, head_size, dim // head_size)
-        tensor = tensor.permute(0, 2, 1, 3).reshape(batch_size * head_size, seq_len, dim // head_size)
-        return tensor
-
-    def reshape_batch_dim_to_heads(self, tensor):
-        batch_size, seq_len, dim = tensor.shape
-        head_size = self.num_heads
-        tensor = tensor.reshape(batch_size // head_size, head_size, seq_len, dim)
-        tensor = tensor.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
-        return tensor
-
-    def forward(self, hidden_states):
-        residual = hidden_states
-        batch, channel, height, width = hidden_states.shape
-
-        # norm
-        hidden_states = self.group_norm(hidden_states)
-
-        hidden_states = hidden_states.view(batch, channel, height * width).transpose(1, 2)
-
-        # proj to q, k, v
-        query_proj = self.query(hidden_states)
-        key_proj = self.key(hidden_states)
-        value_proj = self.value(hidden_states)
-
-        scale = 1 / math.sqrt(self.channels / self.num_heads)
-
-        query_proj = self.reshape_heads_to_batch_dim(query_proj)
-        key_proj = self.reshape_heads_to_batch_dim(key_proj)
-        value_proj = self.reshape_heads_to_batch_dim(value_proj)
-
-        attention_scores = torch.baddbmm(
-            torch.empty(
-                query_proj.shape[0],
-                query_proj.shape[1],
-                key_proj.shape[1],
-                dtype=query_proj.dtype,
-                device=query_proj.device,
-            ),
-            query_proj,
-            key_proj.transpose(-1, -2),
-            beta=0,
-            alpha=scale,
-        )
-        attention_probs = torch.softmax(attention_scores.float(), dim=-1).type(attention_scores.dtype)
-        hidden_states = torch.bmm(attention_probs, value_proj)
-
-        # reshape hidden_states
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
-
-        # compute next hidden_states
-        hidden_states = self.proj_attn(hidden_states)
-        hidden_states = hidden_states.transpose(-1, -2).reshape(batch, channel, height, width)
-
-        # res connect and rescale
-        hidden_states = (hidden_states + residual) / self.rescale_output_factor
-        return hidden_states
-
-
-class BasicTransformerBlock(nn.Module):
-    r"""
-    A basic Transformer block.
-
-    Parameters:
-        dim (`int`): The number of channels in the input and output.
-        num_attention_heads (`int`): The number of heads to use for multi-head attention.
-        attention_head_dim (`int`): The number of channels in each head.
-        dropout (`float`, *optional*, defaults to 0.0): The dropout probability to use.
-        cross_attention_dim (`int`, *optional*): The size of the context vector for cross attention.
-        activation_fn (`str`, *optional*, defaults to `"geglu"`): Activation function to be used in feed-forward.
-        num_embeds_ada_norm (:
-            obj: `int`, *optional*): The number of diffusion steps used during training. See `Transformer2DModel`.
-        attention_bias (:
-            obj: `bool`, *optional*, defaults to `False`): Configure if the attentions should contain a bias parameter.
-    """
-
-    def __init__(
-        self,
-        dim: int,
-        num_attention_heads: int,
-        attention_head_dim: int,
-        dropout=0.0,
-        cross_attention_dim: Optional[int] = None,
-        activation_fn: str = "geglu",
-        num_embeds_ada_norm: Optional[int] = None,
-        attention_bias: bool = False,
-        only_cross_attention: bool = False,
-    ):
-        super().__init__()
-        self.only_cross_attention = only_cross_attention
-        self.attn1 = CrossAttention(
-            query_dim=dim,
-            heads=num_attention_heads,
-            dim_head=attention_head_dim,
-            dropout=dropout,
-            bias=attention_bias,
-            cross_attention_dim=cross_attention_dim if only_cross_attention else None,
-        )  # is a self-attention
-        self.ff = FeedForward(dim, dropout=dropout, activation_fn=activation_fn)
-        self.attn2 = CrossAttention(
-            query_dim=dim,
-            cross_attention_dim=cross_attention_dim,
-            heads=num_attention_heads,
-            dim_head=attention_head_dim,
-            dropout=dropout,
-            bias=attention_bias,
-        )  # is self-attn if context is none
-
-        # layer norms
-        self.use_ada_layer_norm = num_embeds_ada_norm is not None
-        if self.use_ada_layer_norm:
-            self.norm1 = AdaLayerNorm(dim, num_embeds_ada_norm)
-            self.norm2 = AdaLayerNorm(dim, num_embeds_ada_norm)
-        else:
-            self.norm1 = nn.LayerNorm(dim)
-            self.norm2 = nn.LayerNorm(dim)
-        self.norm3 = nn.LayerNorm(dim)
-
-        # if xformers is installed try to use memory_efficient_attention by default
-        if is_xformers_available():
-            try:
-                self.set_use_memory_efficient_attention_xformers(True)
-            except Exception as e:
-                warnings.warn(
-                    "Could not enable memory efficient attention. Make sure xformers is installed"
-                    f" correctly and a GPU is available: {e}"
-                )
-
-    def _set_attention_slice(self, slice_size):
-        self.attn1._slice_size = slice_size
-        self.attn2._slice_size = slice_size
-
-    def set_use_memory_efficient_attention_xformers(self, use_memory_efficient_attention_xformers: bool):
-        if not is_xformers_available():
-            print("Here is how to install it")
-            raise ModuleNotFoundError(
-                "Refer to https://github.com/facebookresearch/xformers for more information on how to install"
-                " xformers",
-                name="xformers",
-            )
-        elif not torch.cuda.is_available():
-            raise ValueError(
-                "torch.cuda.is_available() should be True but is False. xformers' memory efficient attention is only"
-                " available for GPU "
-            )
-        else:
-            try:
-                # Make sure we can run the memory efficient attention
-                _ = xformers.ops.memory_efficient_attention(
-                    torch.randn((1, 2, 40), device="cuda"),
-                    torch.randn((1, 2, 40), device="cuda"),
-                    torch.randn((1, 2, 40), device="cuda"),
-                )
-            except Exception as e:
-                raise e
-            self.attn1._use_memory_efficient_attention_xformers = use_memory_efficient_attention_xformers
-            self.attn2._use_memory_efficient_attention_xformers = use_memory_efficient_attention_xformers
-
-    def forward(self, hidden_states, context=None, timestep=None):
-        # 1. Self-Attention
-        norm_hidden_states = (
-            self.norm1(hidden_states, timestep) if self.use_ada_layer_norm else self.norm1(hidden_states)
-        )
-
-        if self.only_cross_attention:
-            hidden_states = self.attn1(norm_hidden_states, context) + hidden_states
-        else:
-            hidden_states = self.attn1(norm_hidden_states) + hidden_states
-
-        # 2. Cross-Attention
-        norm_hidden_states = (
-            self.norm2(hidden_states, timestep) if self.use_ada_layer_norm else self.norm2(hidden_states)
-        )
-        hidden_states = self.attn2(norm_hidden_states, context=context) + hidden_states
-
-        # 3. Feed-forward
-        hidden_states = self.ff(self.norm3(hidden_states)) + hidden_states
-
-        return hidden_states
-
-
-class CrossAttention(nn.Module):
-    r"""
-    A cross attention layer.
-
-    Parameters:
-        query_dim (`int`): The number of channels in the query.
-        cross_attention_dim (`int`, *optional*):
-            The number of channels in the context. If not given, defaults to `query_dim`.
-        heads (`int`,  *optional*, defaults to 8): The number of heads to use for multi-head attention.
-        dim_head (`int`,  *optional*, defaults to 64): The number of channels in each head.
-        dropout (`float`, *optional*, defaults to 0.0): The dropout probability to use.
-        bias (`bool`, *optional*, defaults to False):
-            Set to `True` for the query, key, and value linear layers to contain a bias parameter.
-    """
-
-    def __init__(
-        self,
-        query_dim: int,
-        cross_attention_dim: Optional[int] = None,
-        heads: int = 8,
-        dim_head: int = 64,
-        dropout: float = 0.0,
-        bias=False,
-    ):
-        super().__init__()
-        inner_dim = dim_head * heads
-        cross_attention_dim = cross_attention_dim if cross_attention_dim is not None else query_dim
-
-        self.scale = dim_head**-0.5
-        self.heads = heads
-        # for slice_size > 0 the attention score computation
-        # is split across the batch axis to save memory
-        # You can set slice_size with `set_attention_slice`
-        self._slice_size = None
-        self._use_memory_efficient_attention_xformers = False
-
-        self.to_q = nn.Linear(query_dim, inner_dim, bias=bias)
-        self.to_k = nn.Linear(cross_attention_dim, inner_dim, bias=bias)
-        self.to_v = nn.Linear(cross_attention_dim, inner_dim, bias=bias)
-
-        self.to_out = nn.ModuleList([])
-        self.to_out.append(nn.Linear(inner_dim, query_dim))
-        self.to_out.append(nn.Dropout(dropout))
-
-    def reshape_heads_to_batch_dim(self, tensor):
-        batch_size, seq_len, dim = tensor.shape
-        head_size = self.heads
-        tensor = tensor.reshape(batch_size, seq_len, head_size, dim // head_size)
-        tensor = tensor.permute(0, 2, 1, 3).reshape(batch_size * head_size, seq_len, dim // head_size)
-        return tensor
-
-    def reshape_batch_dim_to_heads(self, tensor):
-        batch_size, seq_len, dim = tensor.shape
-        head_size = self.heads
-        tensor = tensor.reshape(batch_size // head_size, head_size, seq_len, dim)
-        tensor = tensor.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
-        return tensor
-
-    def forward(self, hidden_states, context=None, mask=None):
-        batch_size, sequence_length, _ = hidden_states.shape
-
-        query = self.to_q(hidden_states)
-        context = context if context is not None else hidden_states
-        key = self.to_k(context)
-        value = self.to_v(context)
-
-        dim = query.shape[-1]
-
-        query = self.reshape_heads_to_batch_dim(query)
-        key = self.reshape_heads_to_batch_dim(key)
-        value = self.reshape_heads_to_batch_dim(value)
-
-        # TODO(PVP) - mask is currently never used. Remember to re-implement when used
-
-        # attention, what we cannot get enough of
-        if self._use_memory_efficient_attention_xformers:
-            hidden_states = self._memory_efficient_attention_xformers(query, key, value)
-            # Some versions of xformers return output in fp32, cast it back to the dtype of the input
-            hidden_states = hidden_states.to(query.dtype)
-        else:
-            if self._slice_size is None or query.shape[0] // self._slice_size == 1:
-                hidden_states = self._attention(query, key, value)
-            else:
-                hidden_states = self._sliced_attention(query, key, value, sequence_length, dim)
-
-        # linear proj
-        hidden_states = self.to_out[0](hidden_states)
-        # dropout
-        hidden_states = self.to_out[1](hidden_states)
-        return hidden_states
-
-    def _attention(self, query, key, value):
-        attention_scores = torch.baddbmm(
-            torch.empty(query.shape[0], query.shape[1], key.shape[1], dtype=query.dtype, device=query.device),
-            query,
-            key.transpose(-1, -2),
-            beta=0,
-            alpha=self.scale,
-        )
-        attention_probs = attention_scores.softmax(dim=-1)
-        # compute attention output
-
-        hidden_states = torch.bmm(attention_probs, value)
-
-        # reshape hidden_states
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
-        return hidden_states
-
-    def _sliced_attention(self, query, key, value, sequence_length, dim):
-        batch_size_attention = query.shape[0]
-        hidden_states = torch.zeros(
-            (batch_size_attention, sequence_length, dim // self.heads), device=query.device, dtype=query.dtype
-        )
-        slice_size = self._slice_size if self._slice_size is not None else hidden_states.shape[0]
-        for i in range(hidden_states.shape[0] // slice_size):
-            start_idx = i * slice_size
-            end_idx = (i + 1) * slice_size
-            attn_slice = torch.baddbmm(
-                torch.empty(slice_size, query.shape[1], key.shape[1], dtype=query.dtype, device=query.device),
-                query[start_idx:end_idx],
-                key[start_idx:end_idx].transpose(-1, -2),
-                beta=0,
-                alpha=self.scale,
-            )
-            attn_slice = attn_slice.softmax(dim=-1)
-            attn_slice = torch.bmm(attn_slice, value[start_idx:end_idx])
-
-            hidden_states[start_idx:end_idx] = attn_slice
-
-        # reshape hidden_states
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
-        return hidden_states
-
-    def _memory_efficient_attention_xformers(self, query, key, value):
-        query = query.contiguous()
-        key = key.contiguous()
-        value = value.contiguous()
-        hidden_states = xformers.ops.memory_efficient_attention(query, key, value, attn_bias=None)
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
-        return hidden_states
-
-
-class FeedForward(nn.Module):
-    r"""
-    A feed-forward layer.
-
-    Parameters:
-        dim (`int`): The number of channels in the input.
-        dim_out (`int`, *optional*): The number of channels in the output. If not given, defaults to `dim`.
-        mult (`int`, *optional*, defaults to 4): The multiplier to use for the hidden dimension.
-        dropout (`float`, *optional*, defaults to 0.0): The dropout probability to use.
-        activation_fn (`str`, *optional*, defaults to `"geglu"`): Activation function to be used in feed-forward.
-    """
-
-    def __init__(
-        self,
-        dim: int,
-        dim_out: Optional[int] = None,
-        mult: int = 4,
-        dropout: float = 0.0,
-        activation_fn: str = "geglu",
-    ):
-        super().__init__()
-        inner_dim = int(dim * mult)
-        dim_out = dim_out if dim_out is not None else dim
-
-        if activation_fn == "geglu":
-            geglu = GEGLU(dim, inner_dim)
-        elif activation_fn == "geglu-approximate":
-            geglu = ApproximateGELU(dim, inner_dim)
-
-        self.net = nn.ModuleList([])
-        # project in
-        self.net.append(geglu)
-        # project dropout
-        self.net.append(nn.Dropout(dropout))
-        # project out
-        self.net.append(nn.Linear(inner_dim, dim_out))
-
-    def forward(self, hidden_states):
-        for module in self.net:
-            hidden_states = module(hidden_states)
-        return hidden_states
-
-
-# feedforward
-class GEGLU(nn.Module):
-    r"""
-    A variant of the gated linear unit activation function from https://arxiv.org/abs/2002.05202.
-
-    Parameters:
-        dim_in (`int`): The number of channels in the input.
-        dim_out (`int`): The number of channels in the output.
-    """
-
-    def __init__(self, dim_in: int, dim_out: int):
-        super().__init__()
-        self.proj = nn.Linear(dim_in, dim_out * 2)
-
-    def gelu(self, gate):
-        if gate.device.type != "mps":
-            return F.gelu(gate)
-        # mps: gelu is not implemented for float16
-        return F.gelu(gate.to(dtype=torch.float32)).to(dtype=gate.dtype)
-
-    def forward(self, hidden_states):
-        hidden_states, gate = self.proj(hidden_states).chunk(2, dim=-1)
-        return hidden_states * self.gelu(gate)
-
-
-class ApproximateGELU(nn.Module):
-    """
-    The approximate form of Gaussian Error Linear Unit (GELU)
-
-    For more details, see section 2: https://arxiv.org/abs/1606.08415
-    """
-
-    def __init__(self, dim_in: int, dim_out: int):
-        super().__init__()
-        self.proj = nn.Linear(dim_in, dim_out)
-
-    def forward(self, x):
-        x = self.proj(x)
-        return x * torch.sigmoid(1.702 * x)
-
-
-class AdaLayerNorm(nn.Module):
-    """
-    Norm layer modified to incorporate timestep embeddings.
-    """
-
-    def __init__(self, embedding_dim, num_embeddings):
-        super().__init__()
-        self.emb = nn.Embedding(num_embeddings, embedding_dim)
-        self.silu = nn.SiLU()
-        self.linear = nn.Linear(embedding_dim, embedding_dim * 2)
-        self.norm = nn.LayerNorm(embedding_dim, elementwise_affine=False)
-
-    def forward(self, x, timestep):
-        emb = self.linear(self.silu(self.emb(timestep)))
-        scale, shift = torch.chunk(emb, 2)
-        x = self.norm(x) * (1 + scale) + shift
-        return x
-
-
-class DualTransformer2DModel(nn.Module):
-    """
-    Dual transformer wrapper that combines two `Transformer2DModel`s for mixed inference.
-
-    Parameters:
-        num_attention_heads (`int`, *optional*, defaults to 16): The number of heads to use for multi-head attention.
-        attention_head_dim (`int`, *optional*, defaults to 88): The number of channels in each head.
-        in_channels (`int`, *optional*):
-            Pass if the input is continuous. The number of channels in the input and output.
-        num_layers (`int`, *optional*, defaults to 1): The number of layers of Transformer blocks to use.
-        dropout (`float`, *optional*, defaults to 0.1): The dropout probability to use.
-        cross_attention_dim (`int`, *optional*): The number of context dimensions to use.
-        sample_size (`int`, *optional*): Pass if the input is discrete. The width of the latent images.
-            Note that this is fixed at training time as it is used for learning a number of position embeddings. See
-            `ImagePositionalEmbeddings`.
-        num_vector_embeds (`int`, *optional*):
-            Pass if the input is discrete. The number of classes of the vector embeddings of the latent pixels.
-            Includes the class for the masked latent pixel.
-        activation_fn (`str`, *optional*, defaults to `"geglu"`): Activation function to be used in feed-forward.
-        num_embeds_ada_norm ( `int`, *optional*): Pass if at least one of the norm_layers is `AdaLayerNorm`.
-            The number of diffusion steps used during training. Note that this is fixed at training time as it is used
-            to learn a number of embeddings that are added to the hidden states. During inference, you can denoise for
-            up to but not more than steps than `num_embeds_ada_norm`.
-        attention_bias (`bool`, *optional*):
-            Configure if the TransformerBlocks' attention should contain a bias parameter.
-    """
-
-    def __init__(
-        self,
-        num_attention_heads: int = 16,
-        attention_head_dim: int = 88,
-        in_channels: Optional[int] = None,
-        num_layers: int = 1,
-        dropout: float = 0.0,
-        norm_num_groups: int = 32,
-        cross_attention_dim: Optional[int] = None,
-        attention_bias: bool = False,
-        sample_size: Optional[int] = None,
-        num_vector_embeds: Optional[int] = None,
-        activation_fn: str = "geglu",
-        num_embeds_ada_norm: Optional[int] = None,
-    ):
-        super().__init__()
-        self.transformers = nn.ModuleList(
-            [
-                Transformer2DModel(
-                    num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
-                    in_channels=in_channels,
-                    num_layers=num_layers,
-                    dropout=dropout,
-                    norm_num_groups=norm_num_groups,
-                    cross_attention_dim=cross_attention_dim,
-                    attention_bias=attention_bias,
-                    sample_size=sample_size,
-                    num_vector_embeds=num_vector_embeds,
-                    activation_fn=activation_fn,
-                    num_embeds_ada_norm=num_embeds_ada_norm,
-                )
-                for _ in range(2)
-            ]
-        )
-
-        # Variables that can be set by a pipeline:
-
-        # The ratio of transformer1 to transformer2's output states to be combined during inference
-        self.mix_ratio = 0.5
-
-        # The shape of `encoder_hidden_states` is expected to be
-        # `(batch_size, condition_lengths[0]+condition_lengths[1], num_features)`
-        self.condition_lengths = [77, 257]
-
-        # Which transformer to use to encode which condition.
-        # E.g. `(1, 0)` means that we'll use `transformers[1](conditions[0])` and `transformers[0](conditions[1])`
-        self.transformer_index_for_condition = [1, 0]
-
-    def forward(self, hidden_states, encoder_hidden_states, timestep=None, return_dict: bool = True):
-        """
-        Args:
-            hidden_states ( When discrete, `torch.LongTensor` of shape `(batch size, num latent pixels)`.
-                When continuous, `torch.FloatTensor` of shape `(batch size, channel, height, width)`): Input
-                hidden_states
-            encoder_hidden_states ( `torch.LongTensor` of shape `(batch size, context dim)`, *optional*):
-                Conditional embeddings for cross attention layer. If not given, cross-attention defaults to
-                self-attention.
-            timestep ( `torch.long`, *optional*):
-                Optional timestep to be applied as an embedding in AdaLayerNorm's. Used to indicate denoising step.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`models.unet_2d_condition.UNet2DConditionOutput`] instead of a plain tuple.
-
-        Returns:
-            [`~models.attention.Transformer2DModelOutput`] or `tuple`: [`~models.attention.Transformer2DModelOutput`]
-            if `return_dict` is True, otherwise a `tuple`. When returning a tuple, the first element is the sample
-            tensor.
-        """
-        input_states = hidden_states
-
-        encoded_states = []
-        tokens_start = 0
-        for i in range(2):
-            # for each of the two transformers, pass the corresponding condition tokens
-            condition_state = encoder_hidden_states[:, tokens_start : tokens_start + self.condition_lengths[i]]
-            transformer_index = self.transformer_index_for_condition[i]
-            encoded_state = self.transformers[transformer_index](input_states, condition_state, timestep, return_dict)[
-                0
-            ]
-            encoded_states.append(encoded_state - input_states)
-            tokens_start += self.condition_lengths[i]
-
-        output_states = encoded_states[0] * self.mix_ratio + encoded_states[1] * (1 - self.mix_ratio)
-        output_states = output_states + input_states
-
-        if not return_dict:
-            return (output_states,)
-
-        return Transformer2DModelOutput(sample=output_states)
diff --git a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/vq_diffusion/__init__.py b/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/vq_diffusion/__init__.py
deleted file mode 100644
index 8c9f14f000648347fe75a5bec0cb45d08c7d2ff9..0000000000000000000000000000000000000000
--- a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/vq_diffusion/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from ...utils import is_torch_available, is_transformers_available
-
-
-if is_transformers_available() and is_torch_available():
-    from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
diff --git a/spaces/Yiqin/ChatVID/model/vision/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_R_101_FPN_200ep_LSJ.py b/spaces/Yiqin/ChatVID/model/vision/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_R_101_FPN_200ep_LSJ.py
deleted file mode 100644
index 18e5f0720c568db4ef0c97b59688b5e7866df606..0000000000000000000000000000000000000000
--- a/spaces/Yiqin/ChatVID/model/vision/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_R_101_FPN_200ep_LSJ.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from .mask_rcnn_R_101_FPN_100ep_LSJ import (
-    dataloader,
-    lr_multiplier,
-    model,
-    optimizer,
-    train,
-)
-
-train.max_iter *= 2  # 100ep -> 200ep
-
-lr_multiplier.scheduler.milestones = [
-    milestone * 2 for milestone in lr_multiplier.scheduler.milestones
-]
-lr_multiplier.scheduler.num_updates = train.max_iter
diff --git a/spaces/YouLiXiya/Mobile-SAM/segment_anything/CODE_OF_CONDUCT.md b/spaces/YouLiXiya/Mobile-SAM/segment_anything/CODE_OF_CONDUCT.md
deleted file mode 100644
index 08b500a221857ec3f451338e80b4a9ab1173a1af..0000000000000000000000000000000000000000
--- a/spaces/YouLiXiya/Mobile-SAM/segment_anything/CODE_OF_CONDUCT.md
+++ /dev/null
@@ -1,80 +0,0 @@
-# Code of Conduct
-
-## Our Pledge
-
-In the interest of fostering an open and welcoming environment, we as
-contributors and maintainers pledge to make participation in our project and
-our community a harassment-free experience for everyone, regardless of age, body
-size, disability, ethnicity, sex characteristics, gender identity and expression,
-level of experience, education, socio-economic status, nationality, personal
-appearance, race, religion, or sexual identity and orientation.
-
-## Our Standards
-
-Examples of behavior that contributes to creating a positive environment
-include:
-
-* Using welcoming and inclusive language
-* Being respectful of differing viewpoints and experiences
-* Gracefully accepting constructive criticism
-* Focusing on what is best for the community
-* Showing empathy towards other community members
-
-Examples of unacceptable behavior by participants include:
-
-* The use of sexualized language or imagery and unwelcome sexual attention or
-  advances
-* Trolling, insulting/derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or electronic
-  address, without explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
-  professional setting
-
-## Our Responsibilities
-
-Project maintainers are responsible for clarifying the standards of acceptable
-behavior and are expected to take appropriate and fair corrective action in
-response to any instances of unacceptable behavior.
-
-Project maintainers have the right and responsibility to remove, edit, or
-reject comments, commits, code, wiki edits, issues, and other contributions
-that are not aligned to this Code of Conduct, or to ban temporarily or
-permanently any contributor for other behaviors that they deem inappropriate,
-threatening, offensive, or harmful.
-
-## Scope
-
-This Code of Conduct applies within all project spaces, and it also applies when
-an individual is representing the project or its community in public spaces.
-Examples of representing a project or community include using an official
-project e-mail address, posting via an official social media account, or acting
-as an appointed representative at an online or offline event. Representation of
-a project may be further defined and clarified by project maintainers.
-
-This Code of Conduct also applies outside the project spaces when there is a
-reasonable belief that an individual's behavior may have a negative impact on
-the project or its community.
-
-## Enforcement
-
-Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported by contacting the project team at <opensource-conduct@fb.com>. All
-complaints will be reviewed and investigated and will result in a response that
-is deemed necessary and appropriate to the circumstances. The project team is
-obligated to maintain confidentiality with regard to the reporter of an incident.
-Further details of specific enforcement policies may be posted separately.
-
-Project maintainers who do not follow or enforce the Code of Conduct in good
-faith may face temporary or permanent repercussions as determined by other
-members of the project's leadership.
-
-## Attribution
-
-This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
-available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
-
-[homepage]: https://www.contributor-covenant.org
-
-For answers to common questions about this code of conduct, see
-https://www.contributor-covenant.org/faq
diff --git a/spaces/Zaxxced/rvc-random-v2/lib/infer_pack/models_onnx.py b/spaces/Zaxxced/rvc-random-v2/lib/infer_pack/models_onnx.py
deleted file mode 100644
index 963e67b29f828e9fdd096397952054fe77cf3d10..0000000000000000000000000000000000000000
--- a/spaces/Zaxxced/rvc-random-v2/lib/infer_pack/models_onnx.py
+++ /dev/null
@@ -1,819 +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 lib.infer_pack import modules
-from lib.infer_pack import attentions
-from lib.infer_pack import commons
-from lib.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 lib.infer_pack.commons import init_weights
-import numpy as np
-from lib.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 TextEncoder768(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(768, 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 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 SynthesizerTrnMsNSFsidM(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,
-        version,
-        **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
-        if version == "v1":
-            self.enc_p = TextEncoder256(
-                inter_channels,
-                hidden_channels,
-                filter_channels,
-                n_heads,
-                n_layers,
-                kernel_size,
-                p_dropout,
-            )
-        else:
-            self.enc_p = TextEncoder768(
-                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)
-        self.speaker_map = None
-        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 construct_spkmixmap(self, n_speaker):
-        self.speaker_map = torch.zeros((n_speaker, 1, 1, self.gin_channels))
-        for i in range(n_speaker):
-            self.speaker_map[i] = self.emb_g(torch.LongTensor([[i]]))
-        self.speaker_map = self.speaker_map.unsqueeze(0)
-
-    def forward(self, phone, phone_lengths, pitch, nsff0, g, rnd, max_len=None):
-        if self.speaker_map is not None:  # [N, S]  *  [S, B, 1, H]
-            g = g.reshape((g.shape[0], g.shape[1], 1, 1, 1))  # [N, S, B, 1, 1]
-            g = g * self.speaker_map  # [N, S, B, 1, H]
-            g = torch.sum(g, dim=1)  # [N, 1, B, 1, H]
-            g = g.transpose(0, -1).transpose(0, -2).squeeze(0)  # [B, H, N]
-        else:
-            g = g.unsqueeze(0)
-            g = self.emb_g(g).transpose(1, 2)
-
-        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 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 MultiPeriodDiscriminatorV2(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(MultiPeriodDiscriminatorV2, self).__init__()
-        # periods = [2, 3, 5, 7, 11, 17]
-        periods = [2, 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/abhishek/sketch-to-image/annotator/openpose/util.py b/spaces/abhishek/sketch-to-image/annotator/openpose/util.py
deleted file mode 100644
index 0a144ff7f2f6f0a2d544786cbe37fbd00b5cbd7d..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/openpose/util.py
+++ /dev/null
@@ -1,175 +0,0 @@
-'''
- * Copyright (c) 2023 Salesforce, Inc.
- * All rights reserved.
- * SPDX-License-Identifier: Apache License 2.0
- * For full license text, see LICENSE.txt file in the repo root or http://www.apache.org/licenses/
- * By Can Qin
- * Modified from ControlNet repo: https://github.com/lllyasviel/ControlNet
- * Copyright (c) 2023 Lvmin Zhang and Maneesh Agrawala
-'''
-
-
-import math
-import numpy as np
-import matplotlib
-import cv2
-
-
-def padRightDownCorner(img, stride, padValue):
-    h = img.shape[0]
-    w = img.shape[1]
-
-    pad = 4 * [None]
-    pad[0] = 0 # up
-    pad[1] = 0 # left
-    pad[2] = 0 if (h % stride == 0) else stride - (h % stride) # down
-    pad[3] = 0 if (w % stride == 0) else stride - (w % stride) # right
-
-    img_padded = img
-    pad_up = np.tile(img_padded[0:1, :, :]*0 + padValue, (pad[0], 1, 1))
-    img_padded = np.concatenate((pad_up, img_padded), axis=0)
-    pad_left = np.tile(img_padded[:, 0:1, :]*0 + padValue, (1, pad[1], 1))
-    img_padded = np.concatenate((pad_left, img_padded), axis=1)
-    pad_down = np.tile(img_padded[-2:-1, :, :]*0 + padValue, (pad[2], 1, 1))
-    img_padded = np.concatenate((img_padded, pad_down), axis=0)
-    pad_right = np.tile(img_padded[:, -2:-1, :]*0 + padValue, (1, pad[3], 1))
-    img_padded = np.concatenate((img_padded, pad_right), axis=1)
-
-    return img_padded, pad
-
-# transfer caffe model to pytorch which will match the layer name
-def transfer(model, model_weights):
-    transfered_model_weights = {}
-    for weights_name in model.state_dict().keys():
-        transfered_model_weights[weights_name] = model_weights['.'.join(weights_name.split('.')[1:])]
-    return transfered_model_weights
-
-# draw the body keypoint and lims
-def draw_bodypose(canvas, candidate, subset):
-    stickwidth = 4
-    limbSeq = [[2, 3], [2, 6], [3, 4], [4, 5], [6, 7], [7, 8], [2, 9], [9, 10], \
-               [10, 11], [2, 12], [12, 13], [13, 14], [2, 1], [1, 15], [15, 17], \
-               [1, 16], [16, 18], [3, 17], [6, 18]]
-
-    colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255, 0], [170, 255, 0], [85, 255, 0], [0, 255, 0], \
-              [0, 255, 85], [0, 255, 170], [0, 255, 255], [0, 170, 255], [0, 85, 255], [0, 0, 255], [85, 0, 255], \
-              [170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]]
-    for i in range(18):
-        for n in range(len(subset)):
-            index = int(subset[n][i])
-            if index == -1:
-                continue
-            x, y = candidate[index][0:2]
-            cv2.circle(canvas, (int(x), int(y)), 4, colors[i], thickness=-1)
-    for i in range(17):
-        for n in range(len(subset)):
-            index = subset[n][np.array(limbSeq[i]) - 1]
-            if -1 in index:
-                continue
-            cur_canvas = canvas.copy()
-            Y = candidate[index.astype(int), 0]
-            X = candidate[index.astype(int), 1]
-            mX = np.mean(X)
-            mY = np.mean(Y)
-            length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5
-            angle = math.degrees(math.atan2(X[0] - X[1], Y[0] - Y[1]))
-            polygon = cv2.ellipse2Poly((int(mY), int(mX)), (int(length / 2), stickwidth), int(angle), 0, 360, 1)
-            cv2.fillConvexPoly(cur_canvas, polygon, colors[i])
-            canvas = cv2.addWeighted(canvas, 0.4, cur_canvas, 0.6, 0)
-    # plt.imsave("preview.jpg", canvas[:, :, [2, 1, 0]])
-    # plt.imshow(canvas[:, :, [2, 1, 0]])
-    return canvas
-
-
-# image drawed by opencv is not good.
-def draw_handpose(canvas, all_hand_peaks, show_number=False):
-    edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \
-             [10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]]
-
-    for peaks in all_hand_peaks:
-        for ie, e in enumerate(edges):
-            if np.sum(np.all(peaks[e], axis=1)==0)==0:
-                x1, y1 = peaks[e[0]]
-                x2, y2 = peaks[e[1]]
-                cv2.line(canvas, (x1, y1), (x2, y2), matplotlib.colors.hsv_to_rgb([ie/float(len(edges)), 1.0, 1.0])*255, thickness=2)
-
-        for i, keyponit in enumerate(peaks):
-            x, y = keyponit
-            cv2.circle(canvas, (x, y), 4, (0, 0, 255), thickness=-1)
-            if show_number:
-                cv2.putText(canvas, str(i), (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.3, (0, 0, 0), lineType=cv2.LINE_AA)
-    return canvas
-
-# detect hand according to body pose keypoints
-# please refer to https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/hand/handDetector.cpp
-def handDetect(candidate, subset, oriImg):
-    # right hand: wrist 4, elbow 3, shoulder 2
-    # left hand: wrist 7, elbow 6, shoulder 5
-    ratioWristElbow = 0.33
-    detect_result = []
-    image_height, image_width = oriImg.shape[0:2]
-    for person in subset.astype(int):
-        # if any of three not detected
-        has_left = np.sum(person[[5, 6, 7]] == -1) == 0
-        has_right = np.sum(person[[2, 3, 4]] == -1) == 0
-        if not (has_left or has_right):
-            continue
-        hands = []
-        #left hand
-        if has_left:
-            left_shoulder_index, left_elbow_index, left_wrist_index = person[[5, 6, 7]]
-            x1, y1 = candidate[left_shoulder_index][:2]
-            x2, y2 = candidate[left_elbow_index][:2]
-            x3, y3 = candidate[left_wrist_index][:2]
-            hands.append([x1, y1, x2, y2, x3, y3, True])
-        # right hand
-        if has_right:
-            right_shoulder_index, right_elbow_index, right_wrist_index = person[[2, 3, 4]]
-            x1, y1 = candidate[right_shoulder_index][:2]
-            x2, y2 = candidate[right_elbow_index][:2]
-            x3, y3 = candidate[right_wrist_index][:2]
-            hands.append([x1, y1, x2, y2, x3, y3, False])
-
-        for x1, y1, x2, y2, x3, y3, is_left in hands:
-            # pos_hand = pos_wrist + ratio * (pos_wrist - pos_elbox) = (1 + ratio) * pos_wrist - ratio * pos_elbox
-            # handRectangle.x = posePtr[wrist*3] + ratioWristElbow * (posePtr[wrist*3] - posePtr[elbow*3]);
-            # handRectangle.y = posePtr[wrist*3+1] + ratioWristElbow * (posePtr[wrist*3+1] - posePtr[elbow*3+1]);
-            # const auto distanceWristElbow = getDistance(poseKeypoints, person, wrist, elbow);
-            # const auto distanceElbowShoulder = getDistance(poseKeypoints, person, elbow, shoulder);
-            # handRectangle.width = 1.5f * fastMax(distanceWristElbow, 0.9f * distanceElbowShoulder);
-            x = x3 + ratioWristElbow * (x3 - x2)
-            y = y3 + ratioWristElbow * (y3 - y2)
-            distanceWristElbow = math.sqrt((x3 - x2) ** 2 + (y3 - y2) ** 2)
-            distanceElbowShoulder = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
-            width = 1.5 * max(distanceWristElbow, 0.9 * distanceElbowShoulder)
-            # x-y refers to the center --> offset to topLeft point
-            # handRectangle.x -= handRectangle.width / 2.f;
-            # handRectangle.y -= handRectangle.height / 2.f;
-            x -= width / 2
-            y -= width / 2  # width = height
-            # overflow the image
-            if x < 0: x = 0
-            if y < 0: y = 0
-            width1 = width
-            width2 = width
-            if x + width > image_width: width1 = image_width - x
-            if y + width > image_height: width2 = image_height - y
-            width = min(width1, width2)
-            # the max hand box value is 20 pixels
-            if width >= 20:
-                detect_result.append([int(x), int(y), int(width), is_left])
-
-    '''
-    return value: [[x, y, w, True if left hand else False]].
-    width=height since the network require squared input.
-    x, y is the coordinate of top left 
-    '''
-    return detect_result
-
-# get max index of 2d array
-def npmax(array):
-    arrayindex = array.argmax(1)
-    arrayvalue = array.max(1)
-    i = arrayvalue.argmax()
-    j = arrayindex[i]
-    return i, j
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/configs/_base_/models/pspnet_unet_s5-d16.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/configs/_base_/models/pspnet_unet_s5-d16.py
deleted file mode 100644
index fcff9ec4f41fad158344ecd77313dc14564f3682..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/configs/_base_/models/pspnet_unet_s5-d16.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# model settings
-norm_cfg = dict(type='SyncBN', requires_grad=True)
-model = dict(
-    type='EncoderDecoder',
-    pretrained=None,
-    backbone=dict(
-        type='UNet',
-        in_channels=3,
-        base_channels=64,
-        num_stages=5,
-        strides=(1, 1, 1, 1, 1),
-        enc_num_convs=(2, 2, 2, 2, 2),
-        dec_num_convs=(2, 2, 2, 2),
-        downsamples=(True, True, True, True),
-        enc_dilations=(1, 1, 1, 1, 1),
-        dec_dilations=(1, 1, 1, 1),
-        with_cp=False,
-        conv_cfg=None,
-        norm_cfg=norm_cfg,
-        act_cfg=dict(type='ReLU'),
-        upsample_cfg=dict(type='InterpConv'),
-        norm_eval=False),
-    decode_head=dict(
-        type='PSPHead',
-        in_channels=64,
-        in_index=4,
-        channels=16,
-        pool_scales=(1, 2, 3, 6),
-        dropout_ratio=0.1,
-        num_classes=2,
-        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=128,
-        in_index=3,
-        channels=64,
-        num_convs=1,
-        concat_input=False,
-        dropout_ratio=0.1,
-        num_classes=2,
-        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='slide', crop_size=256, stride=170))
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/ops/bbox.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/ops/bbox.py
deleted file mode 100644
index 0c4d58b6c91f652933974f519acd3403a833e906..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/ops/bbox.py
+++ /dev/null
@@ -1,72 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext('_ext', ['bbox_overlaps'])
-
-
-def bbox_overlaps(bboxes1, bboxes2, mode='iou', aligned=False, offset=0):
-    """Calculate overlap between two set of bboxes.
-
-    If ``aligned`` is ``False``, then calculate the ious between each bbox
-    of bboxes1 and bboxes2, otherwise the ious between each aligned pair of
-    bboxes1 and bboxes2.
-
-    Args:
-        bboxes1 (Tensor): shape (m, 4) in <x1, y1, x2, y2> format or empty.
-        bboxes2 (Tensor): shape (n, 4) in <x1, y1, x2, y2> format or empty.
-            If aligned is ``True``, then m and n must be equal.
-        mode (str): "iou" (intersection over union) or iof (intersection over
-            foreground).
-
-    Returns:
-        ious(Tensor): shape (m, n) if aligned == False else shape (m, 1)
-
-    Example:
-        >>> bboxes1 = torch.FloatTensor([
-        >>>     [0, 0, 10, 10],
-        >>>     [10, 10, 20, 20],
-        >>>     [32, 32, 38, 42],
-        >>> ])
-        >>> bboxes2 = torch.FloatTensor([
-        >>>     [0, 0, 10, 20],
-        >>>     [0, 10, 10, 19],
-        >>>     [10, 10, 20, 20],
-        >>> ])
-        >>> bbox_overlaps(bboxes1, bboxes2)
-        tensor([[0.5000, 0.0000, 0.0000],
-                [0.0000, 0.0000, 1.0000],
-                [0.0000, 0.0000, 0.0000]])
-
-    Example:
-        >>> empty = torch.FloatTensor([])
-        >>> nonempty = torch.FloatTensor([
-        >>>     [0, 0, 10, 9],
-        >>> ])
-        >>> assert tuple(bbox_overlaps(empty, nonempty).shape) == (0, 1)
-        >>> assert tuple(bbox_overlaps(nonempty, empty).shape) == (1, 0)
-        >>> assert tuple(bbox_overlaps(empty, empty).shape) == (0, 0)
-    """
-
-    mode_dict = {'iou': 0, 'iof': 1}
-    assert mode in mode_dict.keys()
-    mode_flag = mode_dict[mode]
-    # Either the boxes are empty or the length of boxes' last dimension is 4
-    assert (bboxes1.size(-1) == 4 or bboxes1.size(0) == 0)
-    assert (bboxes2.size(-1) == 4 or bboxes2.size(0) == 0)
-    assert offset == 1 or offset == 0
-
-    rows = bboxes1.size(0)
-    cols = bboxes2.size(0)
-    if aligned:
-        assert rows == cols
-
-    if rows * cols == 0:
-        return bboxes1.new(rows, 1) if aligned else bboxes1.new(rows, cols)
-
-    if aligned:
-        ious = bboxes1.new_zeros(rows)
-    else:
-        ious = bboxes1.new_zeros((rows, cols))
-    ext_module.bbox_overlaps(
-        bboxes1, bboxes2, ious, mode=mode_flag, aligned=aligned, offset=offset)
-    return ious
diff --git a/spaces/abhisheky127/QuaraAI_Translator/app.py b/spaces/abhisheky127/QuaraAI_Translator/app.py
deleted file mode 100644
index 46c56a7831b1019769ca3adc167e42ca3830a6f8..0000000000000000000000000000000000000000
--- a/spaces/abhisheky127/QuaraAI_Translator/app.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import gradio as gr
-from transformers import MarianMTModel, MarianTokenizer
-
-# Load English to Arabic translation model and tokenizer
-en_ar_model_name = "Helsinki-NLP/opus-mt-en-ar"
-en_ar_model = MarianMTModel.from_pretrained(en_ar_model_name)
-en_ar_tokenizer = MarianTokenizer.from_pretrained(en_ar_model_name)
-
-# Load Arabic to English translation model and tokenizer
-ar_en_model_name = "Helsinki-NLP/opus-mt-ar-en"
-ar_en_model = MarianMTModel.from_pretrained(ar_en_model_name)
-ar_en_tokenizer = MarianTokenizer.from_pretrained(ar_en_model_name)
-
-def translate_en_to_ar(text):
-    inputs = en_ar_tokenizer.encode(text, return_tensors="pt")
-    translation = en_ar_model.generate(inputs, max_length=128)
-    translated_text = en_ar_tokenizer.decode(translation[0], skip_special_tokens=True)
-    return translated_text
-
-def translate_ar_to_en(text):
-    inputs = ar_en_tokenizer.encode(text, return_tensors="pt")
-    translation = ar_en_model.generate(inputs, max_length=128)
-    translated_text = ar_en_tokenizer.decode(translation[0], skip_special_tokens=True)
-    return translated_text
-
-# Create Gradio interfaces for both translation directions
-en_ar_interface = gr.Interface(
-    fn=translate_en_to_ar,
-    inputs=gr.inputs.Textbox(),
-    outputs=gr.outputs.Textbox(),
-    title="English to Arabic Translation",
-    description="Translate English text to Arabic."
-)
-
-ar_en_interface = gr.Interface(
-    fn=translate_ar_to_en,
-    inputs=gr.inputs.Textbox(),
-    outputs=gr.outputs.Textbox(),
-    title="Quara: Arabic to English Translation",
-    description="Translate Arabic text to English, made by @abhisheky127"
-)
-
-# # Combine the interfaces in a single app
-# app = gr.Interface(
-#     fn=[en_ar_interface, ar_en_interface],
-#     layout="horizontal",
-#     title="Translation App",
-#     description="Translate text between English and Arabic."
-# )
-
-
-
-if __name__ == "__main__":
-    # app.launch()
-    ar_en_interface.launch()
-    # gr.Parallel([en_ar_interface, ar_en_interface]).launch()
diff --git a/spaces/abrar-lohia/text-2-character-anim/pyrender/build/lib/pyrender/platforms/egl.py b/spaces/abrar-lohia/text-2-character-anim/pyrender/build/lib/pyrender/platforms/egl.py
deleted file mode 100644
index ae2478d29c9a538c53ad83fa31f8e2277cd897c8..0000000000000000000000000000000000000000
--- a/spaces/abrar-lohia/text-2-character-anim/pyrender/build/lib/pyrender/platforms/egl.py
+++ /dev/null
@@ -1,219 +0,0 @@
-import ctypes
-import os
-
-import OpenGL.platform
-
-from .base import Platform
-
-EGL_PLATFORM_DEVICE_EXT = 0x313F
-EGL_DRM_DEVICE_FILE_EXT = 0x3233
-
-
-def _ensure_egl_loaded():
-    plugin = OpenGL.platform.PlatformPlugin.by_name('egl')
-    if plugin is None:
-        raise RuntimeError("EGL platform plugin is not available.")
-
-    plugin_class = plugin.load()
-    plugin.loaded = True
-    # create instance of this platform implementation
-    plugin = plugin_class()
-
-    plugin.install(vars(OpenGL.platform))
-
-
-_ensure_egl_loaded()
-from OpenGL import EGL as egl
-
-
-def _get_egl_func(func_name, res_type, *arg_types):
-    address = egl.eglGetProcAddress(func_name)
-    if address is None:
-        return None
-
-    proto = ctypes.CFUNCTYPE(res_type)
-    proto.argtypes = arg_types
-    func = proto(address)
-    return func
-
-
-def _get_egl_struct(struct_name):
-    from OpenGL._opaque import opaque_pointer_cls
-    return opaque_pointer_cls(struct_name)
-
-
-# These are not defined in PyOpenGL by default.
-_EGLDeviceEXT = _get_egl_struct('EGLDeviceEXT')
-_eglGetPlatformDisplayEXT = _get_egl_func('eglGetPlatformDisplayEXT', egl.EGLDisplay)
-_eglQueryDevicesEXT = _get_egl_func('eglQueryDevicesEXT', egl.EGLBoolean)
-_eglQueryDeviceStringEXT = _get_egl_func('eglQueryDeviceStringEXT', ctypes.c_char_p)
-
-
-def query_devices():
-    if _eglQueryDevicesEXT is None:
-        raise RuntimeError("EGL query extension is not loaded or is not supported.")
-
-    num_devices = egl.EGLint()
-    success = _eglQueryDevicesEXT(0, None, ctypes.pointer(num_devices))
-    if not success or num_devices.value < 1:
-        return []
-
-    devices = (_EGLDeviceEXT * num_devices.value)()  # array of size num_devices
-    success = _eglQueryDevicesEXT(num_devices.value, devices, ctypes.pointer(num_devices))
-    if not success or num_devices.value < 1:
-        return []
-
-    return [EGLDevice(devices[i]) for i in range(num_devices.value)]
-
-
-def get_default_device():
-    # Fall back to not using query extension.
-    if _eglQueryDevicesEXT is None:
-        return EGLDevice(None)
-
-    return query_devices()[0]
-
-
-def get_device_by_index(device_id):
-    if _eglQueryDevicesEXT is None and device_id == 0:
-        return get_default_device()
-
-    devices = query_devices()
-    if device_id >= len(devices):
-        raise ValueError('Invalid device ID ({})'.format(device_id, len(devices)))
-    return devices[device_id]
-
-
-class EGLDevice:
-
-    def __init__(self, display=None):
-        self._display = display
-
-    def get_display(self):
-        if self._display is None:
-            return egl.eglGetDisplay(egl.EGL_DEFAULT_DISPLAY)
-
-        return _eglGetPlatformDisplayEXT(EGL_PLATFORM_DEVICE_EXT, self._display, None)
-
-    @property
-    def name(self):
-        if self._display is None:
-            return 'default'
-
-        name = _eglQueryDeviceStringEXT(self._display, EGL_DRM_DEVICE_FILE_EXT)
-        if name is None:
-            return None
-
-        return name.decode('ascii')
-
-    def __repr__(self):
-        return "<EGLDevice(name={})>".format(self.name)
-
-
-class EGLPlatform(Platform):
-    """Renders using EGL.
-    """
-
-    def __init__(self, viewport_width, viewport_height, device: EGLDevice = None):
-        super(EGLPlatform, self).__init__(viewport_width, viewport_height)
-        if device is None:
-            device = get_default_device()
-
-        self._egl_device = device
-        self._egl_display = None
-        self._egl_context = None
-
-    def init_context(self):
-        _ensure_egl_loaded()
-
-        from OpenGL.EGL import (
-            EGL_SURFACE_TYPE, EGL_PBUFFER_BIT, EGL_BLUE_SIZE,
-            EGL_RED_SIZE, EGL_GREEN_SIZE, EGL_DEPTH_SIZE,
-            EGL_COLOR_BUFFER_TYPE, EGL_RGB_BUFFER,
-            EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT, EGL_CONFORMANT,
-            EGL_NONE, EGL_DEFAULT_DISPLAY, EGL_NO_CONTEXT,
-            EGL_OPENGL_API, EGL_CONTEXT_MAJOR_VERSION,
-            EGL_CONTEXT_MINOR_VERSION,
-            EGL_CONTEXT_OPENGL_PROFILE_MASK,
-            EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT,
-            eglGetDisplay, eglInitialize, eglChooseConfig,
-            eglBindAPI, eglCreateContext, EGLConfig
-        )
-        from OpenGL import arrays
-
-        config_attributes = arrays.GLintArray.asArray([
-            EGL_SURFACE_TYPE, EGL_PBUFFER_BIT,
-            EGL_BLUE_SIZE, 8,
-            EGL_RED_SIZE, 8,
-            EGL_GREEN_SIZE, 8,
-            EGL_DEPTH_SIZE, 24,
-            EGL_COLOR_BUFFER_TYPE, EGL_RGB_BUFFER,
-            EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT,
-            EGL_CONFORMANT, EGL_OPENGL_BIT,
-            EGL_NONE
-        ])
-        context_attributes = arrays.GLintArray.asArray([
-            EGL_CONTEXT_MAJOR_VERSION, 4,
-            EGL_CONTEXT_MINOR_VERSION, 1,
-            EGL_CONTEXT_OPENGL_PROFILE_MASK,
-            EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT,
-            EGL_NONE
-        ])
-        major, minor = ctypes.c_long(), ctypes.c_long()
-        num_configs = ctypes.c_long()
-        configs = (EGLConfig * 1)()
-
-        # Cache DISPLAY if necessary and get an off-screen EGL display
-        orig_dpy = None
-        if 'DISPLAY' in os.environ:
-            orig_dpy = os.environ['DISPLAY']
-            del os.environ['DISPLAY']
-
-        self._egl_display = self._egl_device.get_display()
-        if orig_dpy is not None:
-            os.environ['DISPLAY'] = orig_dpy
-
-        # Initialize EGL
-        assert eglInitialize(self._egl_display, major, minor)
-        assert eglChooseConfig(
-            self._egl_display, config_attributes, configs, 1, num_configs
-        )
-
-        # Bind EGL to the OpenGL API
-        assert eglBindAPI(EGL_OPENGL_API)
-
-        # Create an EGL context
-        self._egl_context = eglCreateContext(
-            self._egl_display, configs[0],
-            EGL_NO_CONTEXT, context_attributes
-        )
-
-        # Make it current
-        self.make_current()
-
-    def make_current(self):
-        from OpenGL.EGL import eglMakeCurrent, EGL_NO_SURFACE
-        assert eglMakeCurrent(
-            self._egl_display, EGL_NO_SURFACE, EGL_NO_SURFACE,
-            self._egl_context
-        )
-
-    def make_uncurrent(self):
-        """Make the OpenGL context uncurrent.
-        """
-        pass
-
-    def delete_context(self):
-        from OpenGL.EGL import eglDestroyContext, eglTerminate
-        if self._egl_display is not None:
-            if self._egl_context is not None:
-                eglDestroyContext(self._egl_display, self._egl_context)
-                self._egl_context = None
-            eglTerminate(self._egl_display)
-            self._egl_display = None
-
-    def supports_framebuffers(self):
-        return True
-
-
-__all__ = ['EGLPlatform']
diff --git a/spaces/airesai/Mistral-7B-v0.1-Demo/app.py b/spaces/airesai/Mistral-7B-v0.1-Demo/app.py
deleted file mode 100644
index 22ea81a78d380cdb481188f32c93b9ad214b85f2..0000000000000000000000000000000000000000
--- a/spaces/airesai/Mistral-7B-v0.1-Demo/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/akhaliq/Mask2Former/README.md b/spaces/akhaliq/Mask2Former/README.md
deleted file mode 100644
index 9657d2ac8ae16ea863cce3dccbe25c570e3c8b65..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/Mask2Former/README.md
+++ /dev/null
@@ -1,45 +0,0 @@
----
-title: Mask2Former
-emoji: 🐠
-colorFrom: gray
-colorTo: pink
-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.
-
-`models`: _List[string]_
-HF model IDs (like "gpt2" or "deepset/roberta-base-squad2") used in the Space.
-Will be parsed automatically from your code if not specified here.
-
-`datasets`: _List[string]_
-HF dataset IDs (like "common_voice" or "oscar-corpus/OSCAR-2109") used in the Space.
-Will be parsed automatically from your code if not specified here.
-
-`pinned`: _boolean_
-Whether the Space stays on top of your list.
diff --git a/spaces/akhaliq/VQMIVC/ParallelWaveGAN/egs/jsut/voc1/local/data_prep.sh b/spaces/akhaliq/VQMIVC/ParallelWaveGAN/egs/jsut/voc1/local/data_prep.sh
deleted file mode 100644
index 7fd2321aaba7c3b282ab783b4740bc913094bc0e..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/VQMIVC/ParallelWaveGAN/egs/jsut/voc1/local/data_prep.sh
+++ /dev/null
@@ -1,93 +0,0 @@
-#!/bin/bash
-
-# Copyright 2019 Tomoki Hayashi
-#  MIT License (https://opensource.org/licenses/MIT)
-
-# shellcheck disable=SC1091
-. ./path.sh || exit 1;
-
-fs=24000
-num_dev=250
-num_eval=250
-train_set="train_nodev"
-dev_set="dev"
-eval_set="eval"
-shuffle=false
-
-# shellcheck disable=SC1091
-. utils/parse_options.sh || exit 1;
-
-db_root=$1
-data_dir=$2
-
-# check arguments
-if [ $# != 2 ]; then
-    echo "Usage: $0 [Options] <db_root> <data_dir>"
-    echo "e.g.: $0 downloads/jsut_ver1.1 data"
-    echo ""
-    echo "Options:"
-    echo "    --fs: target sampling rate (default=24000)."
-    echo "    --num_dev: number of development uttreances (default=250)."
-    echo "    --num_eval: number of evaluation uttreances (default=250)."
-    echo "    --train_set: name of train set (default=train_nodev)."
-    echo "    --dev_set: name of dev set (default=dev)."
-    echo "    --eval_set: name of eval set (default=eval)."
-    echo "    --shuffle: whether to perform shuffle in making dev / eval set (default=false)."
-    exit 1
-fi
-
-set -euo pipefail
-
-[ ! -e "${data_dir}/all" ] && mkdir -p "${data_dir}/all"
-
-# set filenames
-scp="${data_dir}/all/wav.scp"
-segments="${data_dir}/all/segments"
-
-# check file existence
-[ -e "${scp}" ] && rm "${scp}"
-[ -e "${segments}" ] && rm "${segments}"
-
-# make scp
-find "${db_root}" -follow -name "*.wav" | sort | while read -r filename; do
-    id=$(basename "${filename}" | sed -e "s/\.[^\.]*$//g")
-    echo "${id} cat ${filename} | sox -t wav - -c 1 -b 16 -t wav - rate ${fs} |" >> "${scp}"
-done
-
-# make segments
-find "${db_root}" -name "*.lab" -follow | sort | while read -r filename; do
-    id=$(basename "${filename}" | sed -e "s/\.[^\.]*$//g")
-    start_nsec=$(head -n 1 "${filename}" | cut -d " " -f 2)
-    end_nsec=$(tail -n 1 "${filename}" | cut -d " " -f 1)
-    start_sec=$(echo "${start_nsec}*0.0000001" | bc | sed "s/^\./0./")
-    end_sec=$(echo "${end_nsec}*0.0000001" | bc | sed "s/^\./0./")
-    echo "${id} ${id} ${start_sec} ${end_sec}" >> "${segments}"
-done
-
-# check
-diff -q <(awk '{print $1}' "${scp}") <(awk '{print $1}' "${segments}") > /dev/null
-
-# split
-num_all=$(wc -l < "${scp}")
-num_deveval=$((num_dev + num_eval))
-num_train=$((num_all - num_deveval))
-utils/split_data.sh \
-    --num_first "${num_train}" \
-    --num_second "${num_deveval}" \
-    --shuffle "${shuffle}" \
-    "${data_dir}/all" \
-    "${data_dir}/${train_set}" \
-    "${data_dir}/deveval"
-utils/split_data.sh \
-    --num_first "${num_dev}" \
-    --num_second "${num_eval}" \
-    --shuffle "${shuffle}" \
-    "${data_dir}/deveval" \
-    "${data_dir}/${dev_set}" \
-    "${data_dir}/${eval_set}"
-
-# remove tmp directories
-rm -rf "${data_dir}/all"
-rm -rf "${data_dir}/deveval"
-
-echo "Successfully prepared data."
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/__init__.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/__init__.py
deleted file mode 100644
index e589bb917e23823e25f9fff7e0849c4d6d4a62bc..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-"""Subpackage containing all of pip's command line interface related code
-"""
-
-# This file intentionally does not import submodules
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/pyparsing/testing.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/pyparsing/testing.py
deleted file mode 100644
index 991972f3fb2986d2d03951be87b07eeb6bce77bc..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/pyparsing/testing.py
+++ /dev/null
@@ -1,331 +0,0 @@
-# testing.py
-
-from contextlib import contextmanager
-from typing import Optional
-
-from .core import (
-    ParserElement,
-    ParseException,
-    Keyword,
-    __diag__,
-    __compat__,
-)
-
-
-class pyparsing_test:
-    """
-    namespace class for classes useful in writing unit tests
-    """
-
-    class reset_pyparsing_context:
-        """
-        Context manager to be used when writing unit tests that modify pyparsing config values:
-        - packrat parsing
-        - bounded recursion parsing
-        - default whitespace characters.
-        - default keyword characters
-        - literal string auto-conversion class
-        - __diag__ settings
-
-        Example::
-
-            with reset_pyparsing_context():
-                # test that literals used to construct a grammar are automatically suppressed
-                ParserElement.inlineLiteralsUsing(Suppress)
-
-                term = Word(alphas) | Word(nums)
-                group = Group('(' + term[...] + ')')
-
-                # assert that the '()' characters are not included in the parsed tokens
-                self.assertParseAndCheckList(group, "(abc 123 def)", ['abc', '123', 'def'])
-
-            # after exiting context manager, literals are converted to Literal expressions again
-        """
-
-        def __init__(self):
-            self._save_context = {}
-
-        def save(self):
-            self._save_context["default_whitespace"] = ParserElement.DEFAULT_WHITE_CHARS
-            self._save_context["default_keyword_chars"] = Keyword.DEFAULT_KEYWORD_CHARS
-
-            self._save_context[
-                "literal_string_class"
-            ] = ParserElement._literalStringClass
-
-            self._save_context["verbose_stacktrace"] = ParserElement.verbose_stacktrace
-
-            self._save_context["packrat_enabled"] = ParserElement._packratEnabled
-            if ParserElement._packratEnabled:
-                self._save_context[
-                    "packrat_cache_size"
-                ] = ParserElement.packrat_cache.size
-            else:
-                self._save_context["packrat_cache_size"] = None
-            self._save_context["packrat_parse"] = ParserElement._parse
-            self._save_context[
-                "recursion_enabled"
-            ] = ParserElement._left_recursion_enabled
-
-            self._save_context["__diag__"] = {
-                name: getattr(__diag__, name) for name in __diag__._all_names
-            }
-
-            self._save_context["__compat__"] = {
-                "collect_all_And_tokens": __compat__.collect_all_And_tokens
-            }
-
-            return self
-
-        def restore(self):
-            # reset pyparsing global state
-            if (
-                ParserElement.DEFAULT_WHITE_CHARS
-                != self._save_context["default_whitespace"]
-            ):
-                ParserElement.set_default_whitespace_chars(
-                    self._save_context["default_whitespace"]
-                )
-
-            ParserElement.verbose_stacktrace = self._save_context["verbose_stacktrace"]
-
-            Keyword.DEFAULT_KEYWORD_CHARS = self._save_context["default_keyword_chars"]
-            ParserElement.inlineLiteralsUsing(
-                self._save_context["literal_string_class"]
-            )
-
-            for name, value in self._save_context["__diag__"].items():
-                (__diag__.enable if value else __diag__.disable)(name)
-
-            ParserElement._packratEnabled = False
-            if self._save_context["packrat_enabled"]:
-                ParserElement.enable_packrat(self._save_context["packrat_cache_size"])
-            else:
-                ParserElement._parse = self._save_context["packrat_parse"]
-            ParserElement._left_recursion_enabled = self._save_context[
-                "recursion_enabled"
-            ]
-
-            __compat__.collect_all_And_tokens = self._save_context["__compat__"]
-
-            return self
-
-        def copy(self):
-            ret = type(self)()
-            ret._save_context.update(self._save_context)
-            return ret
-
-        def __enter__(self):
-            return self.save()
-
-        def __exit__(self, *args):
-            self.restore()
-
-    class TestParseResultsAsserts:
-        """
-        A mixin class to add parse results assertion methods to normal unittest.TestCase classes.
-        """
-
-        def assertParseResultsEquals(
-            self, result, expected_list=None, expected_dict=None, msg=None
-        ):
-            """
-            Unit test assertion to compare a :class:`ParseResults` object with an optional ``expected_list``,
-            and compare any defined results names with an optional ``expected_dict``.
-            """
-            if expected_list is not None:
-                self.assertEqual(expected_list, result.as_list(), msg=msg)
-            if expected_dict is not None:
-                self.assertEqual(expected_dict, result.as_dict(), msg=msg)
-
-        def assertParseAndCheckList(
-            self, expr, test_string, expected_list, msg=None, verbose=True
-        ):
-            """
-            Convenience wrapper assert to test a parser element and input string, and assert that
-            the resulting ``ParseResults.asList()`` is equal to the ``expected_list``.
-            """
-            result = expr.parse_string(test_string, parse_all=True)
-            if verbose:
-                print(result.dump())
-            else:
-                print(result.as_list())
-            self.assertParseResultsEquals(result, expected_list=expected_list, msg=msg)
-
-        def assertParseAndCheckDict(
-            self, expr, test_string, expected_dict, msg=None, verbose=True
-        ):
-            """
-            Convenience wrapper assert to test a parser element and input string, and assert that
-            the resulting ``ParseResults.asDict()`` is equal to the ``expected_dict``.
-            """
-            result = expr.parse_string(test_string, parseAll=True)
-            if verbose:
-                print(result.dump())
-            else:
-                print(result.as_list())
-            self.assertParseResultsEquals(result, expected_dict=expected_dict, msg=msg)
-
-        def assertRunTestResults(
-            self, run_tests_report, expected_parse_results=None, msg=None
-        ):
-            """
-            Unit test assertion to evaluate output of ``ParserElement.runTests()``. If a list of
-            list-dict tuples is given as the ``expected_parse_results`` argument, then these are zipped
-            with the report tuples returned by ``runTests`` and evaluated using ``assertParseResultsEquals``.
-            Finally, asserts that the overall ``runTests()`` success value is ``True``.
-
-            :param run_tests_report: tuple(bool, [tuple(str, ParseResults or Exception)]) returned from runTests
-            :param expected_parse_results (optional): [tuple(str, list, dict, Exception)]
-            """
-            run_test_success, run_test_results = run_tests_report
-
-            if expected_parse_results is not None:
-                merged = [
-                    (*rpt, expected)
-                    for rpt, expected in zip(run_test_results, expected_parse_results)
-                ]
-                for test_string, result, expected in merged:
-                    # expected should be a tuple containing a list and/or a dict or an exception,
-                    # and optional failure message string
-                    # an empty tuple will skip any result validation
-                    fail_msg = next(
-                        (exp for exp in expected if isinstance(exp, str)), None
-                    )
-                    expected_exception = next(
-                        (
-                            exp
-                            for exp in expected
-                            if isinstance(exp, type) and issubclass(exp, Exception)
-                        ),
-                        None,
-                    )
-                    if expected_exception is not None:
-                        with self.assertRaises(
-                            expected_exception=expected_exception, msg=fail_msg or msg
-                        ):
-                            if isinstance(result, Exception):
-                                raise result
-                    else:
-                        expected_list = next(
-                            (exp for exp in expected if isinstance(exp, list)), None
-                        )
-                        expected_dict = next(
-                            (exp for exp in expected if isinstance(exp, dict)), None
-                        )
-                        if (expected_list, expected_dict) != (None, None):
-                            self.assertParseResultsEquals(
-                                result,
-                                expected_list=expected_list,
-                                expected_dict=expected_dict,
-                                msg=fail_msg or msg,
-                            )
-                        else:
-                            # warning here maybe?
-                            print("no validation for {!r}".format(test_string))
-
-            # do this last, in case some specific test results can be reported instead
-            self.assertTrue(
-                run_test_success, msg=msg if msg is not None else "failed runTests"
-            )
-
-        @contextmanager
-        def assertRaisesParseException(self, exc_type=ParseException, msg=None):
-            with self.assertRaises(exc_type, msg=msg):
-                yield
-
-    @staticmethod
-    def with_line_numbers(
-        s: str,
-        start_line: Optional[int] = None,
-        end_line: Optional[int] = None,
-        expand_tabs: bool = True,
-        eol_mark: str = "|",
-        mark_spaces: Optional[str] = None,
-        mark_control: Optional[str] = None,
-    ) -> str:
-        """
-        Helpful method for debugging a parser - prints a string with line and column numbers.
-        (Line and column numbers are 1-based.)
-
-        :param s: tuple(bool, str - string to be printed with line and column numbers
-        :param start_line: int - (optional) starting line number in s to print (default=1)
-        :param end_line: int - (optional) ending line number in s to print (default=len(s))
-        :param expand_tabs: bool - (optional) expand tabs to spaces, to match the pyparsing default
-        :param eol_mark: str - (optional) string to mark the end of lines, helps visualize trailing spaces (default="|")
-        :param mark_spaces: str - (optional) special character to display in place of spaces
-        :param mark_control: str - (optional) convert non-printing control characters to a placeholding
-                                 character; valid values:
-                                 - "unicode" - replaces control chars with Unicode symbols, such as "␍" and "␊"
-                                 - any single character string - replace control characters with given string
-                                 - None (default) - string is displayed as-is
-
-        :return: str - input string with leading line numbers and column number headers
-        """
-        if expand_tabs:
-            s = s.expandtabs()
-        if mark_control is not None:
-            if mark_control == "unicode":
-                tbl = str.maketrans(
-                    {c: u for c, u in zip(range(0, 33), range(0x2400, 0x2433))}
-                    | {127: 0x2421}
-                )
-                eol_mark = ""
-            else:
-                tbl = str.maketrans(
-                    {c: mark_control for c in list(range(0, 32)) + [127]}
-                )
-            s = s.translate(tbl)
-        if mark_spaces is not None and mark_spaces != " ":
-            if mark_spaces == "unicode":
-                tbl = str.maketrans({9: 0x2409, 32: 0x2423})
-                s = s.translate(tbl)
-            else:
-                s = s.replace(" ", mark_spaces)
-        if start_line is None:
-            start_line = 1
-        if end_line is None:
-            end_line = len(s)
-        end_line = min(end_line, len(s))
-        start_line = min(max(1, start_line), end_line)
-
-        if mark_control != "unicode":
-            s_lines = s.splitlines()[start_line - 1 : end_line]
-        else:
-            s_lines = [line + "␊" for line in s.split("␊")[start_line - 1 : end_line]]
-        if not s_lines:
-            return ""
-
-        lineno_width = len(str(end_line))
-        max_line_len = max(len(line) for line in s_lines)
-        lead = " " * (lineno_width + 1)
-        if max_line_len >= 99:
-            header0 = (
-                lead
-                + "".join(
-                    "{}{}".format(" " * 99, (i + 1) % 100)
-                    for i in range(max(max_line_len // 100, 1))
-                )
-                + "\n"
-            )
-        else:
-            header0 = ""
-        header1 = (
-            header0
-            + lead
-            + "".join(
-                "         {}".format((i + 1) % 10)
-                for i in range(-(-max_line_len // 10))
-            )
-            + "\n"
-        )
-        header2 = lead + "1234567890" * (-(-max_line_len // 10)) + "\n"
-        return (
-            header1
-            + header2
-            + "\n".join(
-                "{:{}d}:{}{}".format(i, lineno_width, line, eol_mark)
-                for i, line in enumerate(s_lines, start=start_line)
-            )
-            + "\n"
-        )
diff --git a/spaces/alistairmcleay/cambridge-masters-project/README.md b/spaces/alistairmcleay/cambridge-masters-project/README.md
deleted file mode 100644
index 34f84052dedea803be76fdbadc27cdcfb4ac2b94..0000000000000000000000000000000000000000
--- a/spaces/alistairmcleay/cambridge-masters-project/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Cambridge Masters Project
-emoji: 📈
-colorFrom: yellow
-colorTo: gray
-sdk: gradio
-sdk_version: 3.0.20
-app_file: app.py
-pinned: false
-license: wtfpl
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/aodianyun/stable-diffusion-webui/modules/hashes.py b/spaces/aodianyun/stable-diffusion-webui/modules/hashes.py
deleted file mode 100644
index 46abf99c304b23bf8e3e394e07c2209d4130afef..0000000000000000000000000000000000000000
--- a/spaces/aodianyun/stable-diffusion-webui/modules/hashes.py
+++ /dev/null
@@ -1,91 +0,0 @@
-import hashlib
-import json
-import os.path
-
-import filelock
-
-from modules import shared
-from modules.paths import data_path
-
-
-cache_filename = os.path.join(data_path, "cache.json")
-cache_data = None
-
-
-def dump_cache():
-    with filelock.FileLock(cache_filename+".lock"):
-        with open(cache_filename, "w", encoding="utf8") as file:
-            json.dump(cache_data, file, indent=4)
-
-
-def cache(subsection):
-    global cache_data
-
-    if cache_data is None:
-        with filelock.FileLock(cache_filename+".lock"):
-            if not os.path.isfile(cache_filename):
-                cache_data = {}
-            else:
-                with open(cache_filename, "r", encoding="utf8") as file:
-                    cache_data = json.load(file)
-
-    s = cache_data.get(subsection, {})
-    cache_data[subsection] = s
-
-    return s
-
-
-def calculate_sha256(filename):
-    hash_sha256 = hashlib.sha256()
-    blksize = 1024 * 1024
-
-    with open(filename, "rb") as f:
-        for chunk in iter(lambda: f.read(blksize), b""):
-            hash_sha256.update(chunk)
-
-    return hash_sha256.hexdigest()
-
-
-def sha256_from_cache(filename, title):
-    hashes = cache("hashes")
-    ondisk_mtime = os.path.getmtime(filename)
-
-    if title not in hashes:
-        return None
-
-    cached_sha256 = hashes[title].get("sha256", None)
-    cached_mtime = hashes[title].get("mtime", 0)
-
-    if ondisk_mtime > cached_mtime or cached_sha256 is None:
-        return None
-
-    return cached_sha256
-
-
-def sha256(filename, title):
-    hashes = cache("hashes")
-
-    sha256_value = sha256_from_cache(filename, title)
-    if sha256_value is not None:
-        return sha256_value
-
-    if shared.cmd_opts.no_hashing:
-        return None
-
-    print(f"Calculating sha256 for {filename}: ", end='')
-    sha256_value = calculate_sha256(filename)
-    print(f"{sha256_value}")
-
-    hashes[title] = {
-        "mtime": os.path.getmtime(filename),
-        "sha256": sha256_value,
-    }
-
-    dump_cache()
-
-    return sha256_value
-
-
-
-
-
diff --git a/spaces/apsys/hetfit/bb.md b/spaces/apsys/hetfit/bb.md
deleted file mode 100644
index fcb12dd990d9322a9fc5e6ba500ca812a7fca507..0000000000000000000000000000000000000000
--- a/spaces/apsys/hetfit/bb.md
+++ /dev/null
@@ -1,38 +0,0 @@
-<a id="nets.opti.blackbox"></a>
-
-# :orange[Hyper Paramaters Optimization class]
-## nets.opti.blackbox
-
-<a id="nets.opti.blackbox.Hyper"></a>
-
-### Hyper Objects
-
-```python
-class Hyper(SCI)
-```
-
-Hyper parameter tunning class. Allows to generate best NN architecture for task. Inputs are column indexes. idx[-1] is targeted value.
-
-<a id="nets.opti.blackbox.Hyper.start_study"></a>
-
-#### start\_study
-
-```python
-def start_study(n_trials: int = 100,
-                neptune_project: str = None,
-                neptune_api: str = None)
-```
-
-Starts study. Optionally provide your neptune repo and token for report generation.
-
-**Arguments**:
-
-- `n_trials` _int, optional_ - Number of iterations. Defaults to 100.
-- `neptune_project` _str, optional_ - None
-- neptune_api (str, optional):. Defaults to None.
-  
-
-**Returns**:
-
-- `dict` - quick report of results
-
diff --git a/spaces/ardha27/rvc_TTS/lib/infer_pack/modules.py b/spaces/ardha27/rvc_TTS/lib/infer_pack/modules.py
deleted file mode 100644
index c83289df7c79a4810dacd15c050148544ba0b6a9..0000000000000000000000000000000000000000
--- a/spaces/ardha27/rvc_TTS/lib/infer_pack/modules.py
+++ /dev/null
@@ -1,522 +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
-
-from lib.infer_pack import commons
-from lib.infer_pack.commons import init_weights, get_padding
-from lib.infer_pack.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=0.0):
-        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
-
-    def remove_weight_norm(self):
-        self.enc.remove_weight_norm()
-
-
-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=0.0)
-        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/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ctr.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ctr.py
deleted file mode 100644
index 15c7e838a24d5d84e68222c6aa8e493a47898fc9..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ctr.py
+++ /dev/null
@@ -1,393 +0,0 @@
-# -*- coding: utf-8 -*-
-#
-#  Cipher/mode_ctr.py : CTR mode
-#
-# ===================================================================
-# The contents of this file are dedicated to the public domain.  To
-# the extent that dedication to the public domain is not available,
-# everyone is granted a worldwide, perpetual, royalty-free,
-# non-exclusive license to exercise all rights associated with the
-# contents of this file for any purpose whatsoever.
-# No rights are reserved.
-#
-# 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.
-# ===================================================================
-
-"""
-Counter (CTR) mode.
-"""
-
-__all__ = ['CtrMode']
-
-import struct
-
-from Crypto.Util._raw_api import (load_pycryptodome_raw_lib, VoidPointer,
-                                  create_string_buffer, get_raw_buffer,
-                                  SmartPointer, c_size_t, c_uint8_ptr,
-                                  is_writeable_buffer)
-
-from Crypto.Random import get_random_bytes
-from Crypto.Util.py3compat import _copy_bytes, is_native_int
-from Crypto.Util.number import long_to_bytes
-
-raw_ctr_lib = load_pycryptodome_raw_lib("Crypto.Cipher._raw_ctr", """
-                    int CTR_start_operation(void *cipher,
-                                            uint8_t   initialCounterBlock[],
-                                            size_t    initialCounterBlock_len,
-                                            size_t    prefix_len,
-                                            unsigned  counter_len,
-                                            unsigned  littleEndian,
-                                            void **pResult);
-                    int CTR_encrypt(void *ctrState,
-                                    const uint8_t *in,
-                                    uint8_t *out,
-                                    size_t data_len);
-                    int CTR_decrypt(void *ctrState,
-                                    const uint8_t *in,
-                                    uint8_t *out,
-                                    size_t data_len);
-                    int CTR_stop_operation(void *ctrState);"""
-                                        )
-
-
-class CtrMode(object):
-    """*CounTeR (CTR)* mode.
-
-    This mode is very similar to ECB, in that
-    encryption of one block is done independently of all other blocks.
-
-    Unlike ECB, the block *position* contributes to the encryption
-    and no information leaks about symbol frequency.
-
-    Each message block is associated to a *counter* which
-    must be unique across all messages that get encrypted
-    with the same key (not just within the same message).
-    The counter is as big as the block size.
-
-    Counters can be generated in several ways. The most
-    straightword one is to choose an *initial counter block*
-    (which can be made public, similarly to the *IV* for the
-    other modes) and increment its lowest **m** bits by one
-    (modulo *2^m*) for each block. In most cases, **m** is
-    chosen to be half the block size.
-
-    See `NIST SP800-38A`_, Section 6.5 (for the mode) and
-    Appendix B (for how to manage the *initial counter block*).
-
-    .. _`NIST SP800-38A` : http://csrc.nist.gov/publications/nistpubs/800-38a/sp800-38a.pdf
-
-    :undocumented: __init__
-    """
-
-    def __init__(self, block_cipher, initial_counter_block,
-                 prefix_len, counter_len, little_endian):
-        """Create a new block cipher, configured in CTR mode.
-
-        :Parameters:
-          block_cipher : C pointer
-            A smart pointer to the low-level block cipher instance.
-
-          initial_counter_block : bytes/bytearray/memoryview
-            The initial plaintext to use to generate the key stream.
-
-            It is as large as the cipher block, and it embeds
-            the initial value of the counter.
-
-            This value must not be reused.
-            It shall contain a nonce or a random component.
-            Reusing the *initial counter block* for encryptions
-            performed with the same key compromises confidentiality.
-
-          prefix_len : integer
-            The amount of bytes at the beginning of the counter block
-            that never change.
-
-          counter_len : integer
-            The length in bytes of the counter embedded in the counter
-            block.
-
-          little_endian : boolean
-            True if the counter in the counter block is an integer encoded
-            in little endian mode. If False, it is big endian.
-        """
-
-        if len(initial_counter_block) == prefix_len + counter_len:
-            self.nonce = _copy_bytes(None, prefix_len, initial_counter_block)
-            """Nonce; not available if there is a fixed suffix"""
-
-        self._state = VoidPointer()
-        result = raw_ctr_lib.CTR_start_operation(block_cipher.get(),
-                                                 c_uint8_ptr(initial_counter_block),
-                                                 c_size_t(len(initial_counter_block)),
-                                                 c_size_t(prefix_len),
-                                                 counter_len,
-                                                 little_endian,
-                                                 self._state.address_of())
-        if result:
-            raise ValueError("Error %X while instantiating the CTR mode"
-                             % result)
-
-        # Ensure that object disposal of this Python object will (eventually)
-        # free the memory allocated by the raw library for the cipher mode
-        self._state = SmartPointer(self._state.get(),
-                                   raw_ctr_lib.CTR_stop_operation)
-
-        # Memory allocated for the underlying block cipher is now owed
-        # by the cipher mode
-        block_cipher.release()
-
-        self.block_size = len(initial_counter_block)
-        """The block size of the underlying cipher, in bytes."""
-
-        self._next = [self.encrypt, self.decrypt]
-
-    def encrypt(self, plaintext, output=None):
-        """Encrypt data with the key and the parameters set at initialization.
-
-        A cipher object is stateful: once you have encrypted a message
-        you cannot encrypt (or decrypt) another message using the same
-        object.
-
-        The data to encrypt can be broken up in two or
-        more pieces and `encrypt` can be called multiple times.
-
-        That is, the statement:
-
-            >>> c.encrypt(a) + c.encrypt(b)
-
-        is equivalent to:
-
-             >>> c.encrypt(a+b)
-
-        This function does not add any padding to the plaintext.
-
-        :Parameters:
-          plaintext : bytes/bytearray/memoryview
-            The piece of data to encrypt.
-            It can be of any length.
-        :Keywords:
-          output : bytearray/memoryview
-            The location where the ciphertext must be written to.
-            If ``None``, the ciphertext is returned.
-        :Return:
-          If ``output`` is ``None``, the ciphertext is returned as ``bytes``.
-          Otherwise, ``None``.
-        """
-
-        if self.encrypt not in self._next:
-            raise TypeError("encrypt() cannot be called after decrypt()")
-        self._next = [self.encrypt]
-
-        if output is None:
-            ciphertext = create_string_buffer(len(plaintext))
-        else:
-            ciphertext = output
-
-            if not is_writeable_buffer(output):
-                raise TypeError("output must be a bytearray or a writeable memoryview")
-
-            if len(plaintext) != len(output):
-                raise ValueError("output must have the same length as the input"
-                                 "  (%d bytes)" % len(plaintext))
-
-        result = raw_ctr_lib.CTR_encrypt(self._state.get(),
-                                         c_uint8_ptr(plaintext),
-                                         c_uint8_ptr(ciphertext),
-                                         c_size_t(len(plaintext)))
-        if result:
-            if result == 0x60002:
-                raise OverflowError("The counter has wrapped around in"
-                                    " CTR mode")
-            raise ValueError("Error %X while encrypting in CTR mode" % result)
-
-        if output is None:
-            return get_raw_buffer(ciphertext)
-        else:
-            return None
-
-    def decrypt(self, ciphertext, output=None):
-        """Decrypt data with the key and the parameters set at initialization.
-
-        A cipher object is stateful: once you have decrypted a message
-        you cannot decrypt (or encrypt) another message with the same
-        object.
-
-        The data to decrypt can be broken up in two or
-        more pieces and `decrypt` can be called multiple times.
-
-        That is, the statement:
-
-            >>> c.decrypt(a) + c.decrypt(b)
-
-        is equivalent to:
-
-             >>> c.decrypt(a+b)
-
-        This function does not remove any padding from the plaintext.
-
-        :Parameters:
-          ciphertext : bytes/bytearray/memoryview
-            The piece of data to decrypt.
-            It can be of any length.
-        :Keywords:
-          output : bytearray/memoryview
-            The location where the plaintext must be written to.
-            If ``None``, the plaintext is returned.
-        :Return:
-          If ``output`` is ``None``, the plaintext is returned as ``bytes``.
-          Otherwise, ``None``.
-        """
-
-        if self.decrypt not in self._next:
-            raise TypeError("decrypt() cannot be called after encrypt()")
-        self._next = [self.decrypt]
-
-        if output is None:
-            plaintext = create_string_buffer(len(ciphertext))
-        else:
-            plaintext = output
-
-            if not is_writeable_buffer(output):
-                raise TypeError("output must be a bytearray or a writeable memoryview")
-
-            if len(ciphertext) != len(output):
-                raise ValueError("output must have the same length as the input"
-                                 "  (%d bytes)" % len(plaintext))
-
-        result = raw_ctr_lib.CTR_decrypt(self._state.get(),
-                                         c_uint8_ptr(ciphertext),
-                                         c_uint8_ptr(plaintext),
-                                         c_size_t(len(ciphertext)))
-        if result:
-            if result == 0x60002:
-                raise OverflowError("The counter has wrapped around in"
-                                    " CTR mode")
-            raise ValueError("Error %X while decrypting in CTR mode" % result)
-
-        if output is None:
-            return get_raw_buffer(plaintext)
-        else:
-            return None
-
-
-def _create_ctr_cipher(factory, **kwargs):
-    """Instantiate a cipher object that performs CTR encryption/decryption.
-
-    :Parameters:
-      factory : module
-        The underlying block cipher, a module from ``Crypto.Cipher``.
-
-    :Keywords:
-      nonce : bytes/bytearray/memoryview
-        The fixed part at the beginning of the counter block - the rest is
-        the counter number that gets increased when processing the next block.
-        The nonce must be such that no two messages are encrypted under the
-        same key and the same nonce.
-
-        The nonce must be shorter than the block size (it can have
-        zero length; the counter is then as long as the block).
-
-        If this parameter is not present, a random nonce will be created with
-        length equal to half the block size. No random nonce shorter than
-        64 bits will be created though - you must really think through all
-        security consequences of using such a short block size.
-
-      initial_value : posive integer or bytes/bytearray/memoryview
-        The initial value for the counter. If not present, the cipher will
-        start counting from 0. The value is incremented by one for each block.
-        The counter number is encoded in big endian mode.
-
-      counter : object
-        Instance of ``Crypto.Util.Counter``, which allows full customization
-        of the counter block. This parameter is incompatible to both ``nonce``
-        and ``initial_value``.
-
-    Any other keyword will be passed to the underlying block cipher.
-    See the relevant documentation for details (at least ``key`` will need
-    to be present).
-    """
-
-    cipher_state = factory._create_base_cipher(kwargs)
-
-    counter = kwargs.pop("counter", None)
-    nonce = kwargs.pop("nonce", None)
-    initial_value = kwargs.pop("initial_value", None)
-    if kwargs:
-        raise TypeError("Invalid parameters for CTR mode: %s" % str(kwargs))
-
-    if counter is not None and (nonce, initial_value) != (None, None):
-        raise TypeError("'counter' and 'nonce'/'initial_value'"
-                        " are mutually exclusive")
-
-    if counter is None:
-        # Crypto.Util.Counter is not used
-        if nonce is None:
-            if factory.block_size < 16:
-                raise TypeError("Impossible to create a safe nonce for short"
-                                " block sizes")
-            nonce = get_random_bytes(factory.block_size // 2)
-        else:
-            if len(nonce) >= factory.block_size:
-                raise ValueError("Nonce is too long")
-
-        # What is not nonce is counter
-        counter_len = factory.block_size - len(nonce)
-
-        if initial_value is None:
-            initial_value = 0
-
-        if is_native_int(initial_value):
-            if (1 << (counter_len * 8)) - 1 < initial_value:
-                raise ValueError("Initial counter value is too large")
-            initial_counter_block = nonce + long_to_bytes(initial_value, counter_len)
-        else:
-            if len(initial_value) != counter_len:
-                raise ValueError("Incorrect length for counter byte string (%d bytes, expected %d)" %
-                                 (len(initial_value), counter_len))
-            initial_counter_block = nonce + initial_value
-
-        return CtrMode(cipher_state,
-                       initial_counter_block,
-                       len(nonce),                     # prefix
-                       counter_len,
-                       False)                          # little_endian
-
-    # Crypto.Util.Counter is used
-
-    # 'counter' used to be a callable object, but now it is
-    # just a dictionary for backward compatibility.
-    _counter = dict(counter)
-    try:
-        counter_len = _counter.pop("counter_len")
-        prefix = _counter.pop("prefix")
-        suffix = _counter.pop("suffix")
-        initial_value = _counter.pop("initial_value")
-        little_endian = _counter.pop("little_endian")
-    except KeyError:
-        raise TypeError("Incorrect counter object"
-                        " (use Crypto.Util.Counter.new)")
-
-    # Compute initial counter block
-    words = []
-    while initial_value > 0:
-        words.append(struct.pack('B', initial_value & 255))
-        initial_value >>= 8
-    words += [b'\x00'] * max(0, counter_len - len(words))
-    if not little_endian:
-        words.reverse()
-    initial_counter_block = prefix + b"".join(words) + suffix
-
-    if len(initial_counter_block) != factory.block_size:
-        raise ValueError("Size of the counter block (%d bytes) must match"
-                         " block size (%d)" % (len(initial_counter_block),
-                                               factory.block_size))
-
-    return CtrMode(cipher_state, initial_counter_block,
-                   len(prefix), counter_len, little_endian)
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/CodeWriter.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/CodeWriter.py
deleted file mode 100644
index 2e4646a6544e828ac2bdf4cf482d22bd3d071361..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/CodeWriter.py
+++ /dev/null
@@ -1,816 +0,0 @@
-"""
-Serializes a Cython code tree to Cython code. This is primarily useful for
-debugging and testing purposes.
-
-The output is in a strict format, no whitespace or comments from the input
-is preserved (and it could not be as it is not present in the code tree).
-"""
-
-from __future__ import absolute_import, print_function
-
-from .Compiler.Visitor import TreeVisitor
-from .Compiler.ExprNodes import *
-
-
-class LinesResult(object):
-    def __init__(self):
-        self.lines = []
-        self.s = u""
-
-    def put(self, s):
-        self.s += s
-
-    def newline(self):
-        self.lines.append(self.s)
-        self.s = u""
-
-    def putline(self, s):
-        self.put(s)
-        self.newline()
-
-class DeclarationWriter(TreeVisitor):
-
-    indent_string = u"    "
-
-    def __init__(self, result=None):
-        super(DeclarationWriter, self).__init__()
-        if result is None:
-            result = LinesResult()
-        self.result = result
-        self.numindents = 0
-        self.tempnames = {}
-        self.tempblockindex = 0
-
-    def write(self, tree):
-        self.visit(tree)
-        return self.result
-
-    def indent(self):
-        self.numindents += 1
-
-    def dedent(self):
-        self.numindents -= 1
-
-    def startline(self, s=u""):
-        self.result.put(self.indent_string * self.numindents + s)
-
-    def put(self, s):
-        self.result.put(s)
-
-    def putline(self, s):
-        self.result.putline(self.indent_string * self.numindents + s)
-
-    def endline(self, s=u""):
-        self.result.putline(s)
-
-    def line(self, s):
-        self.startline(s)
-        self.endline()
-
-    def comma_separated_list(self, items, output_rhs=False):
-        if len(items) > 0:
-            for item in items[:-1]:
-                self.visit(item)
-                if output_rhs and item.default is not None:
-                    self.put(u" = ")
-                    self.visit(item.default)
-                self.put(u", ")
-            self.visit(items[-1])
-
-    def visit_Node(self, node):
-        raise AssertionError("Node not handled by serializer: %r" % node)
-
-    def visit_ModuleNode(self, node):
-        self.visitchildren(node)
-
-    def visit_StatListNode(self, node):
-        self.visitchildren(node)
-
-    def visit_CDefExternNode(self, node):
-        if node.include_file is None:
-            file = u'*'
-        else:
-            file = u'"%s"' % node.include_file
-        self.putline(u"cdef extern from %s:" % file)
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-
-    def visit_CPtrDeclaratorNode(self, node):
-        self.put('*')
-        self.visit(node.base)
-
-    def visit_CReferenceDeclaratorNode(self, node):
-        self.put('&')
-        self.visit(node.base)
-
-    def visit_CArrayDeclaratorNode(self, node):
-        self.visit(node.base)
-        self.put(u'[')
-        if node.dimension is not None:
-            self.visit(node.dimension)
-        self.put(u']')
-
-    def visit_CArrayDeclaratorNode(self, node):
-        self.visit(node.base)
-        self.put(u'[')
-        if node.dimension is not None:
-            self.visit(node.dimension)
-        self.put(u']')
-
-    def visit_CFuncDeclaratorNode(self, node):
-        # TODO: except, gil, etc.
-        self.visit(node.base)
-        self.put(u'(')
-        self.comma_separated_list(node.args)
-        self.endline(u')')
-
-    def visit_CNameDeclaratorNode(self, node):
-        self.put(node.name)
-
-    def visit_CSimpleBaseTypeNode(self, node):
-        # See Parsing.p_sign_and_longness
-        if node.is_basic_c_type:
-            self.put(("unsigned ", "", "signed ")[node.signed])
-            if node.longness < 0:
-                self.put("short " * -node.longness)
-            elif node.longness > 0:
-                self.put("long " * node.longness)
-        self.put(node.name)
-
-    def visit_CComplexBaseTypeNode(self, node):
-        self.put(u'(')
-        self.visit(node.base_type)
-        self.visit(node.declarator)
-        self.put(u')')
-
-    def visit_CNestedBaseTypeNode(self, node):
-        self.visit(node.base_type)
-        self.put(u'.')
-        self.put(node.name)
-
-    def visit_TemplatedTypeNode(self, node):
-        self.visit(node.base_type_node)
-        self.put(u'[')
-        self.comma_separated_list(node.positional_args + node.keyword_args.key_value_pairs)
-        self.put(u']')
-
-    def visit_CVarDefNode(self, node):
-        self.startline(u"cdef ")
-        self.visit(node.base_type)
-        self.put(u" ")
-        self.comma_separated_list(node.declarators, output_rhs=True)
-        self.endline()
-
-    def visit_container_node(self, node, decl, extras, attributes):
-        # TODO: visibility
-        self.startline(decl)
-        if node.name:
-            self.put(u' ')
-            self.put(node.name)
-            if node.cname is not None:
-                self.put(u' "%s"' % node.cname)
-        if extras:
-            self.put(extras)
-        self.endline(':')
-        self.indent()
-        if not attributes:
-            self.putline('pass')
-        else:
-            for attribute in attributes:
-                self.visit(attribute)
-        self.dedent()
-
-    def visit_CStructOrUnionDefNode(self, node):
-        if node.typedef_flag:
-            decl = u'ctypedef '
-        else:
-            decl = u'cdef '
-        if node.visibility == 'public':
-            decl += u'public '
-        if node.packed:
-            decl += u'packed '
-        decl += node.kind
-        self.visit_container_node(node, decl, None, node.attributes)
-
-    def visit_CppClassNode(self, node):
-        extras = ""
-        if node.templates:
-            extras = u"[%s]" % ", ".join(node.templates)
-        if node.base_classes:
-            extras += "(%s)" % ", ".join(node.base_classes)
-        self.visit_container_node(node, u"cdef cppclass", extras, node.attributes)
-
-    def visit_CEnumDefNode(self, node):
-        self.visit_container_node(node, u"cdef enum", None, node.items)
-
-    def visit_CEnumDefItemNode(self, node):
-        self.startline(node.name)
-        if node.cname:
-            self.put(u' "%s"' % node.cname)
-        if node.value:
-            self.put(u" = ")
-            self.visit(node.value)
-        self.endline()
-
-    def visit_CClassDefNode(self, node):
-        assert not node.module_name
-        if node.decorators:
-            for decorator in node.decorators:
-                self.visit(decorator)
-        self.startline(u"cdef class ")
-        self.put(node.class_name)
-        if node.base_class_name:
-            self.put(u"(")
-            if node.base_class_module:
-                self.put(node.base_class_module)
-                self.put(u".")
-            self.put(node.base_class_name)
-            self.put(u")")
-        self.endline(u":")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-
-    def visit_CTypeDefNode(self, node):
-        self.startline(u"ctypedef ")
-        self.visit(node.base_type)
-        self.put(u" ")
-        self.visit(node.declarator)
-        self.endline()
-
-    def visit_FuncDefNode(self, node):
-        self.startline(u"def %s(" % node.name)
-        self.comma_separated_list(node.args)
-        self.endline(u"):")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-
-    def visit_CArgDeclNode(self, node):
-        if node.base_type.name is not None:
-            self.visit(node.base_type)
-            self.put(u" ")
-        self.visit(node.declarator)
-        if node.default is not None:
-            self.put(u" = ")
-            self.visit(node.default)
-
-    def visit_CImportStatNode(self, node):
-        self.startline(u"cimport ")
-        self.put(node.module_name)
-        if node.as_name:
-            self.put(u" as ")
-            self.put(node.as_name)
-        self.endline()
-
-    def visit_FromCImportStatNode(self, node):
-        self.startline(u"from ")
-        self.put(node.module_name)
-        self.put(u" cimport ")
-        first = True
-        for pos, name, as_name, kind in node.imported_names:
-            assert kind is None
-            if first:
-                first = False
-            else:
-                self.put(u", ")
-            self.put(name)
-            if as_name:
-                self.put(u" as ")
-                self.put(as_name)
-        self.endline()
-
-    def visit_NameNode(self, node):
-        self.put(node.name)
-
-    def visit_IntNode(self, node):
-        self.put(node.value)
-
-    def visit_NoneNode(self, node):
-        self.put(u"None")
-
-    def visit_NotNode(self, node):
-        self.put(u"(not ")
-        self.visit(node.operand)
-        self.put(u")")
-
-    def visit_DecoratorNode(self, node):
-        self.startline("@")
-        self.visit(node.decorator)
-        self.endline()
-
-    def visit_BinopNode(self, node):
-        self.visit(node.operand1)
-        self.put(u" %s " % node.operator)
-        self.visit(node.operand2)
-
-    def visit_AttributeNode(self, node):
-        self.visit(node.obj)
-        self.put(u".%s" % node.attribute)
-
-    def visit_BoolNode(self, node):
-        self.put(str(node.value))
-
-    # FIXME: represent string nodes correctly
-    def visit_StringNode(self, node):
-        value = node.value
-        if value.encoding is not None:
-            value = value.encode(value.encoding)
-        self.put(repr(value))
-
-    def visit_PassStatNode(self, node):
-        self.startline(u"pass")
-        self.endline()
-
-class CodeWriter(DeclarationWriter):
-
-    def visit_SingleAssignmentNode(self, node):
-        self.startline()
-        self.visit(node.lhs)
-        self.put(u" = ")
-        self.visit(node.rhs)
-        self.endline()
-
-    def visit_CascadedAssignmentNode(self, node):
-        self.startline()
-        for lhs in node.lhs_list:
-            self.visit(lhs)
-            self.put(u" = ")
-        self.visit(node.rhs)
-        self.endline()
-
-    def visit_PrintStatNode(self, node):
-        self.startline(u"print ")
-        self.comma_separated_list(node.arg_tuple.args)
-        if not node.append_newline:
-            self.put(u",")
-        self.endline()
-
-    def visit_ForInStatNode(self, node):
-        self.startline(u"for ")
-        self.visit(node.target)
-        self.put(u" in ")
-        self.visit(node.iterator.sequence)
-        self.endline(u":")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-        if node.else_clause is not None:
-            self.line(u"else:")
-            self.indent()
-            self.visit(node.else_clause)
-            self.dedent()
-
-    def visit_IfStatNode(self, node):
-        # The IfClauseNode is handled directly without a separate match
-        # for clariy.
-        self.startline(u"if ")
-        self.visit(node.if_clauses[0].condition)
-        self.endline(":")
-        self.indent()
-        self.visit(node.if_clauses[0].body)
-        self.dedent()
-        for clause in node.if_clauses[1:]:
-            self.startline("elif ")
-            self.visit(clause.condition)
-            self.endline(":")
-            self.indent()
-            self.visit(clause.body)
-            self.dedent()
-        if node.else_clause is not None:
-            self.line("else:")
-            self.indent()
-            self.visit(node.else_clause)
-            self.dedent()
-
-    def visit_SequenceNode(self, node):
-        self.comma_separated_list(node.args) # Might need to discover whether we need () around tuples...hmm...
-
-    def visit_SimpleCallNode(self, node):
-        self.visit(node.function)
-        self.put(u"(")
-        self.comma_separated_list(node.args)
-        self.put(")")
-
-    def visit_GeneralCallNode(self, node):
-        self.visit(node.function)
-        self.put(u"(")
-        posarg = node.positional_args
-        if isinstance(posarg, AsTupleNode):
-            self.visit(posarg.arg)
-        else:
-            self.comma_separated_list(posarg.args)  # TupleNode.args
-        if node.keyword_args:
-            if isinstance(node.keyword_args, DictNode):
-                for i, (name, value) in enumerate(node.keyword_args.key_value_pairs):
-                    if i > 0:
-                        self.put(', ')
-                    self.visit(name)
-                    self.put('=')
-                    self.visit(value)
-            else:
-                raise Exception("Not implemented yet")
-        self.put(u")")
-
-    def visit_ExprStatNode(self, node):
-        self.startline()
-        self.visit(node.expr)
-        self.endline()
-
-    def visit_InPlaceAssignmentNode(self, node):
-        self.startline()
-        self.visit(node.lhs)
-        self.put(u" %s= " % node.operator)
-        self.visit(node.rhs)
-        self.endline()
-
-    def visit_WithStatNode(self, node):
-        self.startline()
-        self.put(u"with ")
-        self.visit(node.manager)
-        if node.target is not None:
-            self.put(u" as ")
-            self.visit(node.target)
-        self.endline(u":")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-
-    def visit_TryFinallyStatNode(self, node):
-        self.line(u"try:")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-        self.line(u"finally:")
-        self.indent()
-        self.visit(node.finally_clause)
-        self.dedent()
-
-    def visit_TryExceptStatNode(self, node):
-        self.line(u"try:")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-        for x in node.except_clauses:
-            self.visit(x)
-        if node.else_clause is not None:
-            self.visit(node.else_clause)
-
-    def visit_ExceptClauseNode(self, node):
-        self.startline(u"except")
-        if node.pattern is not None:
-            self.put(u" ")
-            self.visit(node.pattern)
-        if node.target is not None:
-            self.put(u", ")
-            self.visit(node.target)
-        self.endline(":")
-        self.indent()
-        self.visit(node.body)
-        self.dedent()
-
-    def visit_ReturnStatNode(self, node):
-        self.startline("return ")
-        self.visit(node.value)
-        self.endline()
-
-    def visit_ReraiseStatNode(self, node):
-        self.line("raise")
-
-    def visit_ImportNode(self, node):
-        self.put(u"(import %s)" % node.module_name.value)
-
-    def visit_TempsBlockNode(self, node):
-        """
-        Temporaries are output like $1_1', where the first number is
-        an index of the TempsBlockNode and the second number is an index
-        of the temporary which that block allocates.
-        """
-        idx = 0
-        for handle in node.temps:
-            self.tempnames[handle] = "$%d_%d" % (self.tempblockindex, idx)
-            idx += 1
-        self.tempblockindex += 1
-        self.visit(node.body)
-
-    def visit_TempRefNode(self, node):
-        self.put(self.tempnames[node.handle])
-
-
-class PxdWriter(DeclarationWriter):
-    def __call__(self, node):
-        print(u'\n'.join(self.write(node).lines))
-        return node
-
-    def visit_CFuncDefNode(self, node):
-        if 'inline' in node.modifiers:
-            return
-        if node.overridable:
-            self.startline(u'cpdef ')
-        else:
-            self.startline(u'cdef ')
-        if node.visibility != 'private':
-            self.put(node.visibility)
-            self.put(u' ')
-        if node.api:
-            self.put(u'api ')
-        self.visit(node.declarator)
-
-    def visit_StatNode(self, node):
-        pass
-
-
-class ExpressionWriter(TreeVisitor):
-
-    def __init__(self, result=None):
-        super(ExpressionWriter, self).__init__()
-        if result is None:
-            result = u""
-        self.result = result
-        self.precedence = [0]
-
-    def write(self, tree):
-        self.visit(tree)
-        return self.result
-
-    def put(self, s):
-        self.result += s
-
-    def remove(self, s):
-        if self.result.endswith(s):
-            self.result = self.result[:-len(s)]
-
-    def comma_separated_list(self, items):
-        if len(items) > 0:
-            for item in items[:-1]:
-                self.visit(item)
-                self.put(u", ")
-            self.visit(items[-1])
-
-    def visit_Node(self, node):
-        raise AssertionError("Node not handled by serializer: %r" % node)
-
-    def visit_NameNode(self, node):
-        self.put(node.name)
-
-    def visit_NoneNode(self, node):
-        self.put(u"None")
-
-    def visit_EllipsisNode(self, node):
-        self.put(u"...")
-
-    def visit_BoolNode(self, node):
-        self.put(str(node.value))
-
-    def visit_ConstNode(self, node):
-        self.put(str(node.value))
-
-    def visit_ImagNode(self, node):
-        self.put(node.value)
-        self.put(u"j")
-
-    def emit_string(self, node, prefix=u""):
-        repr_val = repr(node.value)
-        if repr_val[0] in 'ub':
-            repr_val = repr_val[1:]
-        self.put(u"%s%s" % (prefix, repr_val))
-
-    def visit_BytesNode(self, node):
-        self.emit_string(node, u"b")
-
-    def visit_StringNode(self, node):
-        self.emit_string(node)
-
-    def visit_UnicodeNode(self, node):
-        self.emit_string(node, u"u")
-
-    def emit_sequence(self, node, parens=(u"", u"")):
-        open_paren, close_paren = parens
-        items = node.subexpr_nodes()
-        self.put(open_paren)
-        self.comma_separated_list(items)
-        self.put(close_paren)
-
-    def visit_ListNode(self, node):
-        self.emit_sequence(node, u"[]")
-
-    def visit_TupleNode(self, node):
-        self.emit_sequence(node, u"()")
-
-    def visit_SetNode(self, node):
-        if len(node.subexpr_nodes()) > 0:
-            self.emit_sequence(node, u"{}")
-        else:
-            self.put(u"set()")
-
-    def visit_DictNode(self, node):
-        self.emit_sequence(node, u"{}")
-
-    def visit_DictItemNode(self, node):
-        self.visit(node.key)
-        self.put(u": ")
-        self.visit(node.value)
-
-    unop_precedence = {
-        'not': 3, '!': 3,
-        '+': 11, '-': 11, '~': 11,
-    }
-    binop_precedence = {
-        'or': 1,
-        'and': 2,
-        # unary: 'not': 3, '!': 3,
-        'in': 4, 'not_in': 4, 'is': 4, 'is_not': 4, '<': 4, '<=': 4, '>': 4, '>=': 4, '!=': 4, '==': 4,
-        '|': 5,
-        '^': 6,
-        '&': 7,
-        '<<': 8, '>>': 8,
-        '+': 9, '-': 9,
-        '*': 10, '@': 10, '/': 10, '//': 10, '%': 10,
-        # unary: '+': 11, '-': 11, '~': 11
-        '**': 12,
-    }
-
-    def operator_enter(self, new_prec):
-        old_prec = self.precedence[-1]
-        if old_prec > new_prec:
-            self.put(u"(")
-        self.precedence.append(new_prec)
-
-    def operator_exit(self):
-        old_prec, new_prec = self.precedence[-2:]
-        if old_prec > new_prec:
-            self.put(u")")
-        self.precedence.pop()
-
-    def visit_NotNode(self, node):
-        op = 'not'
-        prec = self.unop_precedence[op]
-        self.operator_enter(prec)
-        self.put(u"not ")
-        self.visit(node.operand)
-        self.operator_exit()
-
-    def visit_UnopNode(self, node):
-        op = node.operator
-        prec = self.unop_precedence[op]
-        self.operator_enter(prec)
-        self.put(u"%s" % node.operator)
-        self.visit(node.operand)
-        self.operator_exit()
-
-    def visit_BinopNode(self, node):
-        op = node.operator
-        prec = self.binop_precedence.get(op, 0)
-        self.operator_enter(prec)
-        self.visit(node.operand1)
-        self.put(u" %s " % op.replace('_', ' '))
-        self.visit(node.operand2)
-        self.operator_exit()
-
-    def visit_BoolBinopNode(self, node):
-        self.visit_BinopNode(node)
-
-    def visit_PrimaryCmpNode(self, node):
-        self.visit_BinopNode(node)
-
-    def visit_IndexNode(self, node):
-        self.visit(node.base)
-        self.put(u"[")
-        if isinstance(node.index, TupleNode):
-            self.emit_sequence(node.index)
-        else:
-            self.visit(node.index)
-        self.put(u"]")
-
-    def visit_SliceIndexNode(self, node):
-        self.visit(node.base)
-        self.put(u"[")
-        if node.start:
-            self.visit(node.start)
-        self.put(u":")
-        if node.stop:
-            self.visit(node.stop)
-        if node.slice:
-            self.put(u":")
-            self.visit(node.slice)
-        self.put(u"]")
-
-    def visit_SliceNode(self, node):
-        if not node.start.is_none:
-            self.visit(node.start)
-        self.put(u":")
-        if not node.stop.is_none:
-            self.visit(node.stop)
-        if not node.step.is_none:
-            self.put(u":")
-            self.visit(node.step)
-
-    def visit_CondExprNode(self, node):
-        self.visit(node.true_val)
-        self.put(u" if ")
-        self.visit(node.test)
-        self.put(u" else ")
-        self.visit(node.false_val)
-
-    def visit_AttributeNode(self, node):
-        self.visit(node.obj)
-        self.put(u".%s" % node.attribute)
-
-    def visit_SimpleCallNode(self, node):
-        self.visit(node.function)
-        self.put(u"(")
-        self.comma_separated_list(node.args)
-        self.put(")")
-
-    def emit_pos_args(self, node):
-        if node is None:
-            return
-        if isinstance(node, AddNode):
-            self.emit_pos_args(node.operand1)
-            self.emit_pos_args(node.operand2)
-        elif isinstance(node, TupleNode):
-            for expr in node.subexpr_nodes():
-                self.visit(expr)
-                self.put(u", ")
-        elif isinstance(node, AsTupleNode):
-            self.put("*")
-            self.visit(node.arg)
-            self.put(u", ")
-        else:
-            self.visit(node)
-            self.put(u", ")
-
-    def emit_kwd_args(self, node):
-        if node is None:
-            return
-        if isinstance(node, MergedDictNode):
-            for expr in node.subexpr_nodes():
-                self.emit_kwd_args(expr)
-        elif isinstance(node, DictNode):
-            for expr in node.subexpr_nodes():
-                self.put(u"%s=" % expr.key.value)
-                self.visit(expr.value)
-                self.put(u", ")
-        else:
-            self.put(u"**")
-            self.visit(node)
-            self.put(u", ")
-
-    def visit_GeneralCallNode(self, node):
-        self.visit(node.function)
-        self.put(u"(")
-        self.emit_pos_args(node.positional_args)
-        self.emit_kwd_args(node.keyword_args)
-        self.remove(u", ")
-        self.put(")")
-
-    def emit_comprehension(self, body, target,
-                           sequence, condition,
-                           parens=(u"", u"")):
-        open_paren, close_paren = parens
-        self.put(open_paren)
-        self.visit(body)
-        self.put(u" for ")
-        self.visit(target)
-        self.put(u" in ")
-        self.visit(sequence)
-        if condition:
-            self.put(u" if ")
-            self.visit(condition)
-        self.put(close_paren)
-
-    def visit_ComprehensionAppendNode(self, node):
-        self.visit(node.expr)
-
-    def visit_DictComprehensionAppendNode(self, node):
-        self.visit(node.key_expr)
-        self.put(u": ")
-        self.visit(node.value_expr)
-
-    def visit_ComprehensionNode(self, node):
-        tpmap = {'list': u"[]", 'dict': u"{}", 'set': u"{}"}
-        parens = tpmap[node.type.py_type_name()]
-        body = node.loop.body
-        target = node.loop.target
-        sequence = node.loop.iterator.sequence
-        condition = None
-        if hasattr(body, 'if_clauses'):
-            # type(body) is Nodes.IfStatNode
-            condition = body.if_clauses[0].condition
-            body = body.if_clauses[0].body
-        self.emit_comprehension(body, target, sequence, condition, parens)
-
-    def visit_GeneratorExpressionNode(self, node):
-        body = node.loop.body
-        target = node.loop.target
-        sequence = node.loop.iterator.sequence
-        condition = None
-        if hasattr(body, 'if_clauses'):
-            # type(body) is Nodes.IfStatNode
-            condition = body.if_clauses[0].condition
-            body = body.if_clauses[0].body.expr.arg
-        elif hasattr(body, 'expr'):
-            # type(body) is Nodes.ExprStatNode
-            body = body.expr.arg
-        self.emit_comprehension(body, target, sequence, condition, u"()")
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Compiler/TreeFragment.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Compiler/TreeFragment.py
deleted file mode 100644
index b85da8191a50378f679a9c6408b842a2e5de2a7b..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Compiler/TreeFragment.py
+++ /dev/null
@@ -1,275 +0,0 @@
-#
-# TreeFragments - parsing of strings to trees
-#
-
-"""
-Support for parsing strings into code trees.
-"""
-
-from __future__ import absolute_import
-
-import re
-from io import StringIO
-
-from .Scanning import PyrexScanner, StringSourceDescriptor
-from .Symtab import ModuleScope
-from . import PyrexTypes
-from .Visitor import VisitorTransform
-from .Nodes import Node, StatListNode
-from .ExprNodes import NameNode
-from .StringEncoding import _unicode
-from . import Parsing
-from . import Main
-from . import UtilNodes
-
-
-class StringParseContext(Main.Context):
-    def __init__(self, name, include_directories=None, compiler_directives=None, cpp=False):
-        if include_directories is None:
-            include_directories = []
-        if compiler_directives is None:
-            compiler_directives = {}
-        # TODO: see if "language_level=3" also works for our internal code here.
-        Main.Context.__init__(self, include_directories, compiler_directives, cpp=cpp, language_level=2)
-        self.module_name = name
-
-    def find_module(self, module_name, relative_to=None, pos=None, need_pxd=1, absolute_fallback=True):
-        if module_name not in (self.module_name, 'cython'):
-            raise AssertionError("Not yet supporting any cimports/includes from string code snippets")
-        return ModuleScope(module_name, parent_module=None, context=self)
-
-
-def parse_from_strings(name, code, pxds=None, level=None, initial_pos=None,
-                       context=None, allow_struct_enum_decorator=False):
-    """
-    Utility method to parse a (unicode) string of code. This is mostly
-    used for internal Cython compiler purposes (creating code snippets
-    that transforms should emit, as well as unit testing).
-
-    code - a unicode string containing Cython (module-level) code
-    name - a descriptive name for the code source (to use in error messages etc.)
-
-    RETURNS
-
-    The tree, i.e. a ModuleNode. The ModuleNode's scope attribute is
-    set to the scope used when parsing.
-    """
-    if context is None:
-        context = StringParseContext(name)
-    # Since source files carry an encoding, it makes sense in this context
-    # to use a unicode string so that code fragments don't have to bother
-    # with encoding. This means that test code passed in should not have an
-    # encoding header.
-    assert isinstance(code, _unicode), "unicode code snippets only please"
-    encoding = "UTF-8"
-
-    module_name = name
-    if initial_pos is None:
-        initial_pos = (name, 1, 0)
-    code_source = StringSourceDescriptor(name, code)
-
-    scope = context.find_module(module_name, pos=initial_pos, need_pxd=False)
-
-    buf = StringIO(code)
-
-    scanner = PyrexScanner(buf, code_source, source_encoding = encoding,
-                     scope = scope, context = context, initial_pos = initial_pos)
-    ctx = Parsing.Ctx(allow_struct_enum_decorator=allow_struct_enum_decorator)
-
-    if level is None:
-        tree = Parsing.p_module(scanner, 0, module_name, ctx=ctx)
-        tree.scope = scope
-        tree.is_pxd = False
-    else:
-        tree = Parsing.p_code(scanner, level=level, ctx=ctx)
-
-    tree.scope = scope
-    return tree
-
-
-class TreeCopier(VisitorTransform):
-    def visit_Node(self, node):
-        if node is None:
-            return node
-        else:
-            c = node.clone_node()
-            self.visitchildren(c)
-            return c
-
-
-class ApplyPositionAndCopy(TreeCopier):
-    def __init__(self, pos):
-        super(ApplyPositionAndCopy, self).__init__()
-        self.pos = pos
-
-    def visit_Node(self, node):
-        copy = super(ApplyPositionAndCopy, self).visit_Node(node)
-        copy.pos = self.pos
-        return copy
-
-
-class TemplateTransform(VisitorTransform):
-    """
-    Makes a copy of a template tree while doing substitutions.
-
-    A dictionary "substitutions" should be passed in when calling
-    the transform; mapping names to replacement nodes. Then replacement
-    happens like this:
-     - If an ExprStatNode contains a single NameNode, whose name is
-       a key in the substitutions dictionary, the ExprStatNode is
-       replaced with a copy of the tree given in the dictionary.
-       It is the responsibility of the caller that the replacement
-       node is a valid statement.
-     - If a single NameNode is otherwise encountered, it is replaced
-       if its name is listed in the substitutions dictionary in the
-       same way. It is the responsibility of the caller to make sure
-       that the replacement nodes is a valid expression.
-
-    Also a list "temps" should be passed. Any names listed will
-    be transformed into anonymous, temporary names.
-
-    Currently supported for tempnames is:
-    NameNode
-    (various function and class definition nodes etc. should be added to this)
-
-    Each replacement node gets the position of the substituted node
-    recursively applied to every member node.
-    """
-
-    temp_name_counter = 0
-
-    def __call__(self, node, substitutions, temps, pos):
-        self.substitutions = substitutions
-        self.pos = pos
-        tempmap = {}
-        temphandles = []
-        for temp in temps:
-            TemplateTransform.temp_name_counter += 1
-            handle = UtilNodes.TempHandle(PyrexTypes.py_object_type)
-            tempmap[temp] = handle
-            temphandles.append(handle)
-        self.tempmap = tempmap
-        result = super(TemplateTransform, self).__call__(node)
-        if temps:
-            result = UtilNodes.TempsBlockNode(self.get_pos(node),
-                                              temps=temphandles,
-                                              body=result)
-        return result
-
-    def get_pos(self, node):
-        if self.pos:
-            return self.pos
-        else:
-            return node.pos
-
-    def visit_Node(self, node):
-        if node is None:
-            return None
-        else:
-            c = node.clone_node()
-            if self.pos is not None:
-                c.pos = self.pos
-            self.visitchildren(c)
-            return c
-
-    def try_substitution(self, node, key):
-        sub = self.substitutions.get(key)
-        if sub is not None:
-            pos = self.pos
-            if pos is None: pos = node.pos
-            return ApplyPositionAndCopy(pos)(sub)
-        else:
-            return self.visit_Node(node) # make copy as usual
-
-    def visit_NameNode(self, node):
-        temphandle = self.tempmap.get(node.name)
-        if temphandle:
-            # Replace name with temporary
-            return temphandle.ref(self.get_pos(node))
-        else:
-            return self.try_substitution(node, node.name)
-
-    def visit_ExprStatNode(self, node):
-        # If an expression-as-statement consists of only a replaceable
-        # NameNode, we replace the entire statement, not only the NameNode
-        if isinstance(node.expr, NameNode):
-            return self.try_substitution(node, node.expr.name)
-        else:
-            return self.visit_Node(node)
-
-
-def copy_code_tree(node):
-    return TreeCopier()(node)
-
-
-_match_indent = re.compile(u"^ *").match
-
-
-def strip_common_indent(lines):
-    """Strips empty lines and common indentation from the list of strings given in lines"""
-    # TODO: Facilitate textwrap.indent instead
-    lines = [x for x in lines if x.strip() != u""]
-    if lines:
-        minindent = min([len(_match_indent(x).group(0)) for x in lines])
-        lines = [x[minindent:] for x in lines]
-    return lines
-
-
-class TreeFragment(object):
-    def __init__(self, code, name=None, pxds=None, temps=None, pipeline=None, level=None, initial_pos=None):
-        if pxds is None:
-            pxds = {}
-        if temps is None:
-            temps = []
-        if pipeline is None:
-            pipeline = []
-        if not name:
-            name = "(tree fragment)"
-
-        if isinstance(code, _unicode):
-            def fmt(x): return u"\n".join(strip_common_indent(x.split(u"\n")))
-
-            fmt_code = fmt(code)
-            fmt_pxds = {}
-            for key, value in pxds.items():
-                fmt_pxds[key] = fmt(value)
-            mod = t = parse_from_strings(name, fmt_code, fmt_pxds, level=level, initial_pos=initial_pos)
-            if level is None:
-                t = t.body # Make sure a StatListNode is at the top
-            if not isinstance(t, StatListNode):
-                t = StatListNode(pos=mod.pos, stats=[t])
-            for transform in pipeline:
-                if transform is None:
-                    continue
-                t = transform(t)
-            self.root = t
-        elif isinstance(code, Node):
-            if pxds:
-                raise NotImplementedError()
-            self.root = code
-        else:
-            raise ValueError("Unrecognized code format (accepts unicode and Node)")
-        self.temps = temps
-
-    def copy(self):
-        return copy_code_tree(self.root)
-
-    def substitute(self, nodes=None, temps=None, pos = None):
-        if nodes is None:
-            nodes = {}
-        if temps is None:
-            temps = []
-        return TemplateTransform()(self.root,
-                                   substitutions = nodes,
-                                   temps = self.temps + temps, pos = pos)
-
-
-class SetPosTransform(VisitorTransform):
-    def __init__(self, pos):
-        super(SetPosTransform, self).__init__()
-        self.pos = pos
-
-    def visit_Node(self, node):
-        node.pos = self.pos
-        self.visitchildren(node)
-        return node
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/filled_step_chart.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/filled_step_chart.py
deleted file mode 100644
index dadb5770e54d385c8b02c2f78a139046931ded91..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/filled_step_chart.py
+++ /dev/null
@@ -1,19 +0,0 @@
-"""
-Filled Step Chart
------------------
-This example shows Google's stock price over time as a step chart with its area filled in and its line emphasized.
-"""
-# category: line charts
-import altair as alt
-from vega_datasets import data
-
-source = data.stocks()
-
-alt.Chart(source).mark_area(
-    color="lightblue",
-    interpolate='step-after',
-    line=True
-).encode(
-    x='date',
-    y='price'
-).transform_filter(alt.datum.symbol == 'GOOG')
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/attr/_version_info.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/attr/_version_info.py
deleted file mode 100644
index cdaeec37a1ad988cafb7e202967f48829c9d85ba..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/attr/_version_info.py
+++ /dev/null
@@ -1,87 +0,0 @@
-# SPDX-License-Identifier: MIT
-
-from __future__ import absolute_import, division, print_function
-
-from functools import total_ordering
-
-from ._funcs import astuple
-from ._make import attrib, attrs
-
-
-@total_ordering
-@attrs(eq=False, order=False, slots=True, frozen=True)
-class VersionInfo(object):
-    """
-    A version object that can be compared to tuple of length 1--4:
-
-    >>> attr.VersionInfo(19, 1, 0, "final")  <= (19, 2)
-    True
-    >>> attr.VersionInfo(19, 1, 0, "final") < (19, 1, 1)
-    True
-    >>> vi = attr.VersionInfo(19, 2, 0, "final")
-    >>> vi < (19, 1, 1)
-    False
-    >>> vi < (19,)
-    False
-    >>> vi == (19, 2,)
-    True
-    >>> vi == (19, 2, 1)
-    False
-
-    .. versionadded:: 19.2
-    """
-
-    year = attrib(type=int)
-    minor = attrib(type=int)
-    micro = attrib(type=int)
-    releaselevel = attrib(type=str)
-
-    @classmethod
-    def _from_version_string(cls, s):
-        """
-        Parse *s* and return a _VersionInfo.
-        """
-        v = s.split(".")
-        if len(v) == 3:
-            v.append("final")
-
-        return cls(
-            year=int(v[0]), minor=int(v[1]), micro=int(v[2]), releaselevel=v[3]
-        )
-
-    def _ensure_tuple(self, other):
-        """
-        Ensure *other* is a tuple of a valid length.
-
-        Returns a possibly transformed *other* and ourselves as a tuple of
-        the same length as *other*.
-        """
-
-        if self.__class__ is other.__class__:
-            other = astuple(other)
-
-        if not isinstance(other, tuple):
-            raise NotImplementedError
-
-        if not (1 <= len(other) <= 4):
-            raise NotImplementedError
-
-        return astuple(self)[: len(other)], other
-
-    def __eq__(self, other):
-        try:
-            us, them = self._ensure_tuple(other)
-        except NotImplementedError:
-            return NotImplemented
-
-        return us == them
-
-    def __lt__(self, other):
-        try:
-            us, them = self._ensure_tuple(other)
-        except NotImplementedError:
-            return NotImplemented
-
-        # Since alphabetically "dev0" < "final" < "post1" < "post2", we don't
-        # have to do anything special with releaselevel for now.
-        return us < them
diff --git a/spaces/asafAdge/Detic/demo.py b/spaces/asafAdge/Detic/demo.py
deleted file mode 100644
index 183f6c44c4ca8cdf32d1c4b57bd75a11a07dcbde..0000000000000000000000000000000000000000
--- a/spaces/asafAdge/Detic/demo.py
+++ /dev/null
@@ -1,206 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import argparse
-import glob
-import multiprocessing as mp
-import numpy as np
-import os
-import tempfile
-import time
-import warnings
-import cv2
-import tqdm
-import sys
-
-from detectron2.config import get_cfg
-from detectron2.data.detection_utils import read_image
-from detectron2.utils.logger import setup_logger
-
-sys.path.insert(0, 'third_party/CenterNet2/projects/CenterNet2/')
-sys.path.insert(0, 'third_party/CenterNet2/')
-
-from centernet.config import add_centernet_config
-from detic.config import add_detic_config
-
-from detic.predictor import VisualizationDemo
-
-
-# constants
-WINDOW_NAME = "Detic"
-
-def setup_cfg(args):
-    cfg = get_cfg()
-    add_centernet_config(cfg)
-    add_detic_config(cfg)
-    cfg.merge_from_file(args.config_file)
-    cfg.merge_from_list(args.opts)
-    # Set score_threshold for builtin models
-    cfg.MODEL.RETINANET.SCORE_THRESH_TEST = args.confidence_threshold
-    cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = args.confidence_threshold
-    cfg.MODEL.PANOPTIC_FPN.COMBINE.INSTANCES_CONFIDENCE_THRESH = args.confidence_threshold
-    cfg.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_PATH = 'rand' # load later
-    if not args.pred_all_class:
-        cfg.MODEL.ROI_HEADS.ONE_CLASS_PER_PROPOSAL = True
-    cfg.freeze()
-    return cfg
-
-
-def get_parser():
-    parser = argparse.ArgumentParser(description="Detectron2 demo for builtin configs")
-    parser.add_argument(
-        "--config-file",
-        default="configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml",
-        metavar="FILE",
-        help="path to config file",
-    )
-    parser.add_argument("--webcam", action="store_true", help="Take inputs from webcam.")
-    parser.add_argument("--video-input", help="Path to video file.")
-    parser.add_argument(
-        "--input",
-        nargs="+",
-        help="A list of space separated input images; "
-        "or a single glob pattern such as 'directory/*.jpg'",
-    )
-    parser.add_argument(
-        "--output",
-        help="A file or directory to save output visualizations. "
-        "If not given, will show output in an OpenCV window.",
-    )
-    parser.add_argument(
-        "--vocabulary",
-        default="lvis",
-        choices=['lvis', 'openimages', 'objects365', 'coco', 'custom'],
-        help="",
-    )
-    parser.add_argument(
-        "--custom_vocabulary",
-        default="",
-        help="",
-    )
-    parser.add_argument("--pred_all_class", action='store_true')
-    parser.add_argument(
-        "--confidence-threshold",
-        type=float,
-        default=0.5,
-        help="Minimum score for instance predictions to be shown",
-    )
-    parser.add_argument(
-        "--opts",
-        help="Modify config options using the command-line 'KEY VALUE' pairs",
-        default=[],
-        nargs=argparse.REMAINDER,
-    )
-    return parser
-
-
-def test_opencv_video_format(codec, file_ext):
-    with tempfile.TemporaryDirectory(prefix="video_format_test") as dir:
-        filename = os.path.join(dir, "test_file" + file_ext)
-        writer = cv2.VideoWriter(
-            filename=filename,
-            fourcc=cv2.VideoWriter_fourcc(*codec),
-            fps=float(30),
-            frameSize=(10, 10),
-            isColor=True,
-        )
-        [writer.write(np.zeros((10, 10, 3), np.uint8)) for _ in range(30)]
-        writer.release()
-        if os.path.isfile(filename):
-            return True
-        return False
-
-
-if __name__ == "__main__":
-    mp.set_start_method("spawn", force=True)
-    args = get_parser().parse_args()
-    setup_logger(name="fvcore")
-    logger = setup_logger()
-    logger.info("Arguments: " + str(args))
-
-    cfg = setup_cfg(args)
-
-    demo = VisualizationDemo(cfg, args)
-
-    if args.input:
-        if len(args.input) == 1:
-            args.input = glob.glob(os.path.expanduser(args.input[0]))
-            assert args.input, "The input path(s) was not found"
-        for path in tqdm.tqdm(args.input, disable=not args.output):
-            img = read_image(path, format="BGR")
-            start_time = time.time()
-            predictions, visualized_output = demo.run_on_image(img)
-            logger.info(
-                "{}: {} in {:.2f}s".format(
-                    path,
-                    "detected {} instances".format(len(predictions["instances"]))
-                    if "instances" in predictions
-                    else "finished",
-                    time.time() - start_time,
-                )
-            )
-
-            if args.output:
-                if os.path.isdir(args.output):
-                    assert os.path.isdir(args.output), args.output
-                    out_filename = os.path.join(args.output, os.path.basename(path))
-                else:
-                    assert len(args.input) == 1, "Please specify a directory with args.output"
-                    out_filename = args.output
-                visualized_output.save(out_filename)
-            else:
-                cv2.namedWindow(WINDOW_NAME, cv2.WINDOW_NORMAL)
-                cv2.imshow(WINDOW_NAME, visualized_output.get_image()[:, :, ::-1])
-                if cv2.waitKey(0) == 27:
-                    break  # esc to quit
-    elif args.webcam:
-        assert args.input is None, "Cannot have both --input and --webcam!"
-        assert args.output is None, "output not yet supported with --webcam!"
-        cam = cv2.VideoCapture(0)
-        for vis in tqdm.tqdm(demo.run_on_video(cam)):
-            cv2.namedWindow(WINDOW_NAME, cv2.WINDOW_NORMAL)
-            cv2.imshow(WINDOW_NAME, vis)
-            if cv2.waitKey(1) == 27:
-                break  # esc to quit
-        cam.release()
-        cv2.destroyAllWindows()
-    elif args.video_input:
-        video = cv2.VideoCapture(args.video_input)
-        width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
-        height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
-        frames_per_second = video.get(cv2.CAP_PROP_FPS)
-        num_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
-        basename = os.path.basename(args.video_input)
-        codec, file_ext = (
-            ("x264", ".mkv") if test_opencv_video_format("x264", ".mkv") else ("mp4v", ".mp4")
-        )
-        if codec == ".mp4v":
-            warnings.warn("x264 codec not available, switching to mp4v")
-        if args.output:
-            if os.path.isdir(args.output):
-                output_fname = os.path.join(args.output, basename)
-                output_fname = os.path.splitext(output_fname)[0] + file_ext
-            else:
-                output_fname = args.output
-            assert not os.path.isfile(output_fname), output_fname
-            output_file = cv2.VideoWriter(
-                filename=output_fname,
-                # some installation of opencv may not support x264 (due to its license),
-                # you can try other format (e.g. MPEG)
-                fourcc=cv2.VideoWriter_fourcc(*codec),
-                fps=float(frames_per_second),
-                frameSize=(width, height),
-                isColor=True,
-            )
-        assert os.path.isfile(args.video_input)
-        for vis_frame in tqdm.tqdm(demo.run_on_video(video), total=num_frames):
-            if args.output:
-                output_file.write(vis_frame)
-            else:
-                cv2.namedWindow(basename, cv2.WINDOW_NORMAL)
-                cv2.imshow(basename, vis_frame)
-                if cv2.waitKey(1) == 27:
-                    break  # esc to quit
-        video.release()
-        if args.output:
-            output_file.release()
-        else:
-            cv2.destroyAllWindows()
diff --git a/spaces/ashercn97/AsherTesting/css/chat.js b/spaces/ashercn97/AsherTesting/css/chat.js
deleted file mode 100644
index e304f1254732e475bf177ee849ac51d4f3e30f46..0000000000000000000000000000000000000000
--- a/spaces/ashercn97/AsherTesting/css/chat.js
+++ /dev/null
@@ -1,4 +0,0 @@
-document.getElementById("main").childNodes[0].style = "max-width: 800px; margin-left: auto; margin-right: auto";
-document.getElementById("extensions").style.setProperty("max-width", "800px");
-document.getElementById("extensions").style.setProperty("margin-left", "auto");
-document.getElementById("extensions").style.setProperty("margin-right", "auto");
diff --git a/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Nayan Saxena.html b/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Nayan Saxena.html
deleted file mode 100644
index fbabed66ce1d06dc13dbe76293093d40684b6de3..0000000000000000000000000000000000000000
--- a/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Nayan Saxena.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>Nayan Saxena</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">Nayan Saxena</h1>
-
-<div class="formatted_content">
-  <div><a target="_blank" rel="noreferrer" class="autolinked" data-behavior="truncate" href="https://www.linkedin.com/in/saxenanayan/">https://www.linkedin.com/in/saxenanayan/</a><br><br></div><blockquote>I am a data scientist at the Royal Bank of Canada, and a machine learning engineer at WOMBO.ai. I am a recent graduate from the University of Toronto where I did an undergraduate degree in Statistics, Computer Science and Mathematics and held several teaching assistant positions for various graduate and undergraduate statistics courses mentoring and teaching 1500+ students. Previously I have also worked at Bell Canada and would love to help students throughout their career journeys.<br><br>Alongside my teaching and professional work, I have also produced several papers on topics including Neural Architecture Search, Dueling Bandit Algorithms, Item Response Theory &amp; Gaussian Processes appearing at top machine learning venues like AAAI, ICML, NeurIPS, EDM, IEEE-ICALT, ICCM. I also have experience briefly running monte-carlo simulations on the Niagara supercomputer cluster for a journal manuscript on clinical trials under the supervision of Prof. Jessica Gronsbell (UofT) and Zack McCaw (Google). I was also a Research Assistant at the Intelligent Adaptive Interventions Research Group, where I conducted research on Statistical Inference for Multi-Armed Bandit Algorithms (RL) supervised by Prof. Joseph Jay Williams.</blockquote><div><br></div><div><br></div><h1>Interview</h1><div><br></div><div><strong>How did you hear about SM?</strong></div><ul><li>Looking/googling for a place where I can start mentoring people. Found y'all</li></ul><div><strong>Career</strong></div><ul><li>Presently DS at RBC</li><li>also working at a startup (part-time) doing MLE stuff</li><li>graduated recently, but worked throughout my degree, and published a lot of papers</li><li>worked at Bell Canada interning as a DS</li></ul><div><strong>Mentorship experience?</strong></div><ul><li>Have been a teaching assistant (including grad level courses)<ul><li>OH - one student at a time</li></ul></li><li>Informally mentored many of his students outside of the TA framework</li><li>help them apply to jobs, negotiate offers, and strategic advice</li></ul><div><strong>What are beginners lacking?</strong></div><ul><li>Depends on the individual</li><li>People don't know where to start<ul><li>Maybe have a good SE background</li><li>Or good stats background</li><li>need both</li></ul></li><li>The biggest hurdle is confidence</li><li>Networking leads to more opportunities!</li></ul><div><strong>And how can you add value as a mentor?</strong></div><ul><li>I start by talking to them and learn what their goals are (don't assume)<ul><li>work together to set the goal and work towards it</li></ul></li><li>set benchmarks and work towards them together. Make sure they feel comfortable - working towards the same goal together</li><li>soft skills from day 1<ul><li>talking about things</li><li>presenting results</li><li>talking while you think (problem solving)</li></ul></li><li>Assign a few projects/readings. set certain goals</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><br><strong>Questions about SM?</strong></div><ul><li>The ISA - how does it work? It's new to me</li><li>What happens if they don't pay?<ul><li>(I don;t really care, but I'm curious)</li></ul></li><li>How many hours do mentors usually give?</li><li>How do I find a mentee?</li></ul><div></div>
-</div>
-
-    </div>
-  
-
-</body></html>
\ No newline at end of file
diff --git a/spaces/awacke1/BiomedCaseContextHighlight/app.py b/spaces/awacke1/BiomedCaseContextHighlight/app.py
deleted file mode 100644
index 93484639f868a048ba9bb255f1b5c42d604d4fa3..0000000000000000000000000000000000000000
--- a/spaces/awacke1/BiomedCaseContextHighlight/app.py
+++ /dev/null
@@ -1,11 +0,0 @@
-import gradio as gr
-
-def ner(text):
-    api = gr.Interface.load("ugaray96/biobert_ncbi_disease_ner", src='models')
-    spans = api(text)
-    replaced_spans = [(key, None) if value=='No Disease' else (key, value) for (key, value) in spans]
-    return replaced_spans
-
-interface = gr.Interface(ner, inputs=gr.Textbox(label="Input", value="Patient is 50 yo M experienced a right bundle branch block (RBBB) yet tests for arrythmia found no results and heart health.  Top goals."), outputs="highlightedtext")
-
-interface.launch()
\ No newline at end of file
diff --git a/spaces/awacke1/Memory-0731/app.py b/spaces/awacke1/Memory-0731/app.py
deleted file mode 100644
index b699439bc47babd6b1cf205b29b7f63e40856218..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Memory-0731/app.py
+++ /dev/null
@@ -1,102 +0,0 @@
-import streamlit as st
-import pandas as pd
-
-# Define functions
-def create_empty_csv_files():
-    sem_df = pd.DataFrame(columns=["fact", "category", "source"])
-    sem_df.to_csv("semantic_memory.csv", index=False)
-    epi_df = pd.DataFrame(columns=["event", "sentiment", "date"])
-    epi_df.to_csv("episodic_memory.csv", index=False)
-
-def load_data():
-    try:
-        sem_df = pd.read_csv("semantic_memory.csv")
-        sem_mem = sem_df.to_dict("records")
-    except:
-        create_empty_csv_files()
-        sem_mem = [{"fact": "The Earth is round", "category": "science", "source": "NASA"},
-                   {"fact": "Pizza is delicious", "category": "food", "source": "me"}]
-    try:
-        epi_df = pd.read_csv("episodic_memory.csv")
-        epi_mem = epi_df.to_dict("records")
-    except:
-        create_empty_csv_files()
-        epi_mem = [{"event": "I went to the beach", "sentiment": "happy", "date": "2022-02-28"},
-                   {"event": "I had a fight with my friend", "sentiment": "sad", "date": "2022-02-25"}]
-    return sem_mem, epi_mem
-
-def save_data(sem_mem, epi_mem):
-    sem_df = pd.DataFrame(sem_mem)
-    sem_df.to_csv("semantic_memory.csv", index=False)
-    epi_df = pd.DataFrame(epi_mem)
-    epi_df.to_csv("episodic_memory.csv", index=False)
-
-def view_semantic_memory(sem_mem):
-    st.write("# Semantic Memory")
-    for item in sem_mem:
-        st.write(f"**{item['fact']}** ({item['category']}) - {item['source']}")
-
-def view_episodic_memory(epi_mem):
-    st.write("# Episodic Memory")
-    for item in epi_mem:
-        st.write(f"**{item['event']}** ({item['sentiment']}) - {item['date']}")
-
-def add_fact(sem_mem, fact, category, source):
-    sem_mem.append({"fact": fact, "category": category, "source": source})
-
-def add_event(epi_mem, event, sentiment, date):
-    epi_mem.append({"event": event, "sentiment": sentiment, "date": date})
-
-def add_fact_to_semantic_memory(sem_mem, epi_mem):
-    fact = st.text_input("Enter a fact")
-    category = st.text_input("Enter a category")
-    source = st.text_input("Enter a source")
-    if st.button("Add Fact"):
-        add_fact(sem_mem, fact, category, source)
-        save_data(sem_mem, epi_mem)
-        st.success("Fact added to semantic memory!")
-        st.sidebar.success("Fact added to semantic memory!")
-
-def add_event_to_episodic_memory(epi_mem, sem_mem):
-    event = st.text_input("Enter an event")
-    sentiment = st.selectbox("Select a sentiment", ["happy", "sad", "neutral"])
-    date = st.date_input("Select a date")
-    if st.button("Add Event"):
-        add_event(epi_mem, event, sentiment, date)
-        save_data(sem_mem, epi_mem)
-        st.success("Event added to episodic memory!")
-        st.sidebar.success("Event added to episodic memory!")
-
-def run_app():
-    sem_mem, epi_mem = load_data()
-
-    st.title("Cognitive Agent")
-    option = st.sidebar.selectbox("Select an option",
-                                  ["View Semantic Memory", "View Episodic Memory", "Add Fact to Semantic Memory",
-                                   "Add Event to Episodic Memory"])
-
-    if option == "View Semantic Memory":
-        view_semantic_memory(sem_mem)
-    elif option == "View Episodic Memory":
-        view_episodic_memory(epi_mem)
-    elif option == "Add Fact to Semantic Memory":
-        add_fact_to_semantic_memory(sem_mem, epi_mem)
-    elif option == "Add Event to Episodic Memory":
-        add_event_to_episodic_memory(epi_mem, sem_mem)
-
-    save_data(sem_mem, epi_mem)
-
-if __name__ == '__main__':
-    run_app()
-
-
-
-
-# AW: Restructure the code listing into four functions.  shorten the code by eliminating comments and unnecessary whitespace and empty lines.
-# AI: This revised code splits the app into four functions: load_data, save_data, add_fact, and add_event. The run_app function handles the logic of the Streamlit app and calls these other functions as necessary. The code has been shortened by removing unnecessary whitespace and comments, but retains its functionality.
-
-
-# This program uses Streamlit to create a web app that allows the user to view and add to both semantic and episodic memory. The semantic memory is stored as a list of dictionaries, where each dictionary represents a fact and includes the fact itself, the category it belongs to, and the source of the fact. The episodic memory is also stored as a list of dictionaries, where each dictionary represents an event and includes the event itself, the sentiment associated with the event, and the date the event occurred.
-# The program allows the user to view both types of memory by selecting an option from the sidebar. If the user selects "View Semantic Memory", the program displays all of the facts stored in semantic memory. If the user selects "View Episodic Memory", the program displays all of the events stored in episodic memory.
-# The program also allows the user to add new facts to semantic memory or new events to episodic memory by selecting an option from the sidebar and filling out a form with the relevant information. When the user clicks the "Add Fact" or "Add Event" button, the new fact or event is added to the appropriate list of dictionaries and saved to a CSV file. The program then displays a success message indicating that the fact or event was added to memory.
-# Overall, this program demonstrates how semantic and episodic memory can be modeled using Python list dictionaries, and how these types of memory can be used to track both facts and observations, as well as sentiments associated with past experiences.
diff --git a/spaces/awacke1/Streamlit.GraphViz.Dynamic.Architecture.Diagram/app.py b/spaces/awacke1/Streamlit.GraphViz.Dynamic.Architecture.Diagram/app.py
deleted file mode 100644
index b79be955c31e3110b385accb4078915ad952a3d3..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Streamlit.GraphViz.Dynamic.Architecture.Diagram/app.py
+++ /dev/null
@@ -1,146 +0,0 @@
-import streamlit as st
-from graphviz import Digraph
-
-
-st.markdown("""
-Prompt:
-Create an interactive streamlit graph builder using the graphviz diagram model language and the streamlit feature: st.graphviz_chart(figure_or_dot, use_container_width=False) to show an azure cloud architecture model including the top ten architecture components for python full stack development for web, api, ml, models, datasets torch, transformers, streamlit, azure docker and kubernetes pods for scaling
-
-""")
-
-# Dot demo:
-import streamlit as st
-
-# Define the default graphviz DOT string
-default_dot = """
-digraph G {
-    rankdir=LR
-    node [shape=box]
-    WebApp -> API
-    API -> Models
-    API -> Datasets
-    Models -> Torch
-    Models -> Transformers
-    WebApp -> Streamlit
-    Streamlit -> Azure
-    Azure -> Docker
-    Azure -> Kubernetes
-}
-"""
-
-# Define the list of top 10 components
-components = [
-    "WebApp",
-    "API",
-    "Models",
-    "Datasets",
-    "Torch",
-    "Transformers",
-    "Streamlit",
-    "Azure",
-    "Docker",
-    "Kubernetes",
-]
-
-# Define a dictionary to map component names to DOT node IDs
-node_ids = {
-    component: component.lower()
-    for component in components
-}
-
-def build_dot_string(selected_components):
-    """Builds a DOT string representing the selected components"""
-    selected_nodes = [node_ids[component] for component in selected_components]
-    dot = """
-    digraph G {
-        rankdir=LR
-        node [shape=box]
-    """
-    for node in selected_nodes:
-        dot += f"{node} [color=blue]\n"
-    for i in range(len(selected_nodes)):
-        for j in range(i+1, len(selected_nodes)):
-            dot += f"{selected_nodes[i]} -> {selected_nodes[j]}\n"
-    dot += "}"
-    return dot
-
-def main():
-    st.title("Azure Cloud Architecture Builder")
-
-    # Select the components
-    st.sidebar.title("Select components")
-    selected_components = st.sidebar.multiselect(
-        "Select the top 10 components",
-        components,
-        default=components[:3]
-    )
-
-    # Build the DOT string
-    dot = build_dot_string(selected_components)
-
-    # Render the graphviz chart
-    st.graphviz_chart(dot, use_container_width=True)
-
-if __name__ == "__main__":
-    main()
-
-
-
-# Initialize the graph
-graph = Digraph(comment='Architectural Model')
-
-# Add nodes to the graph
-graph.node('data_layer', 'Data Layer')
-graph.node('acr', 'Azure Container Registry')
-graph.node('aks', 'Azure Kubernetes\n& Docker Container Pod\nwith Scalability')
-graph.node('snowflake', 'Snowflake Instance')
-graph.node('cosmos', 'Azure Cosmos\nDatabase')
-graph.node('api', 'API Standard\n(using Uvicorn)')
-graph.node('soar', 'SOAR Component\n(on Linux Python\nSlimbuster Docker)')
-
-# Add edges to the graph
-graph.edge('data_layer', 'acr')
-graph.edge('acr', 'aks')
-graph.edge('aks', 'snowflake')
-graph.edge('aks', 'cosmos')
-graph.edge('aks', 'api')
-graph.edge('aks', 'soar')
-
-# Define the Streamlit app
-def app():
-    st.title('Architectural Model')
-    
-    # Draw the graph
-    st.graphviz_chart(graph.source)
-    
-    # Add buttons to customize the graph
-    if st.button('Hide Data Layer'):
-        graph.node('data_layer', style='invisible')
-    
-    if st.button('Hide Snowflake Instance'):
-        graph.node('snowflake', style='invisible')
-    
-    if st.button('Hide SOAR Component'):
-        graph.node('soar', style='invisible')
-
-
-
-st.markdown("""
-# QA Model Spaces:
-QA use cases include QA, Semantic Document and FAQ Search.
-1. Streamlit Question Answering w Hugging Face: https://huggingface.co/spaces/awacke1/Question-answering
-2. Seq2Seq:
-	- https://huggingface.co/spaces/awacke1/4-Seq2SeqQAT5
-	- https://huggingface.co/spaces/awacke1/AW-04-GR-Seq-2-Seq-QA-Auto-Gen
-3. BioGPT: https://huggingface.co/spaces/awacke1/microsoft-BioGPT-Large-PubMedQA
-4. NLP QA Context: https://huggingface.co/spaces/awacke1/NLPContextQATransformersRobertaBaseSquad2
-	- https://huggingface.co/spaces/awacke1/SOTA-Plan
-5.  https://huggingface.co/spaces/awacke1/Question-answering
-6.  QA MLM: https://huggingface.co/spaces/awacke1/SOTA-MedEntity
-""")
-
-
-        
-# Run the Streamlit app
-if __name__ == '__main__':
-    app()
diff --git a/spaces/banana-dev/demo-illusion-diffusion-hq/app.py b/spaces/banana-dev/demo-illusion-diffusion-hq/app.py
deleted file mode 100644
index b38eaed0e74eff065a567df05620bab236710662..0000000000000000000000000000000000000000
--- a/spaces/banana-dev/demo-illusion-diffusion-hq/app.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import gradio as gr
-import boto3
-import banana_dev as client
-import os
-from typing import Iterable
-import gradio as gr
-from gradio.themes.base import Base
-from gradio.themes.utils import colors, fonts, sizes
-from PIL import Image
-import io
-import base64
-from io import BytesIO
-import traceback
-import uuid
-from dotenv import load_dotenv
-import gzip
-
-load_dotenv()
-
-BANANA_API_KEY = os.getenv("BANANA_API_KEY")
-BANANA_MODEL_KEY = os.getenv("BANANA_MODEL_KEY")
-BANANA_URL = os.getenv("BANANA_URL")
-
-def predict(image, prompt,qr_code, negative_prompt, seed):
-    try:
-        my_model = client.Client(
-            api_key=BANANA_API_KEY,
-            model_key=BANANA_MODEL_KEY,
-            url=BANANA_URL,
-        )
-        #target image
-        with open(image.name, "rb") as f:
-            image_bytes = f.read()
-        image_encoded = base64.b64encode(image_bytes)
-        image = image_encoded.decode("utf-8")
-
-        print(image)
-        print(negative_prompt)
-        print(seed)
-        print(qr_code)
-        print(prompt)
-
-        inputs = {
-            "prompt" : prompt,
-            "qr_code_content" : qr_code,
-            "negative_prompt": negative_prompt,
-            "image": image,
-            "seed": seed
-        }
-        result, meta = my_model.call("/", inputs)
-        output_bytes = result["outputs"]
-
-        image_encoded = output_bytes.encode('utf-8')
-        image_data = base64.b64decode(image_encoded)
-        image_data = gzip.decompress(image_data)
-        image_io = BytesIO(image_data)
-        output_image = Image.open(image_io)
-        return output_image, None
-    except Exception as e:
-        tb_str = traceback.format_exception(type(e), e, e.__traceback__)
-        tb_str = "".join(tb_str)
-        return None, tb_str
-
-with gr.Blocks() as demo:                         
-    title_with_logo = gr.Markdown("# Powered by Banana <img src='https://files.umso.co/lib_udQIfMXlGlflDxFd/rnqmq7j8oqug1kae.png' align='left' width='50' height='50'>")
-    with gr.Column():                        
-        image = gr.File(label="Image", file_count="single", scale=1)
-        prompt=gr.Textbox(label="Prompt")
-        qr_code=gr.Textbox(label="QR code link")
-        negative_prompt= gr.Textbox(label="Negative Prompt")
-        seed= gr.Textbox(label="Seed")
-        btn = gr.Button("Run illusion-diffusion-hq")                       
-        output_image = gr.Image(label="Output Image")  
-        output_error = gr.Textbox(label="Error Message")  
-    btn.click(predict, [image, prompt,qr_code, negative_prompt, seed], [output_image, output_error])
-
-demo.launch()
\ No newline at end of file
diff --git a/spaces/banana-projects/convai/front/js-src/Api.ts b/spaces/banana-projects/convai/front/js-src/Api.ts
deleted file mode 100644
index 9117de77f91da2800030e469117b4c565ed6988b..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/convai/front/js-src/Api.ts
+++ /dev/null
@@ -1,71 +0,0 @@
-
-interface Message {
-	incoming: boolean;
-	content:  string;
-}
-
-interface MessageOutput {
-	text: string;
-	attention: [string, number][][]; /// <- [persona, context, user message]
-}
-
-class Api {
-	
-	static ENDPOINT = `https://convai-proxy.huggingface.co`;
-	static shared = new Api();
-	
-	path(p: string): string {
-		return `${Api.ENDPOINT}/${p}`;
-	}
-	
-	async getShuffle(): Promise<{slug: string, text: string}> {
-		const response = await fetch('/shuffle');
-		return response.json();
-	}
-	
-	private async postMessage(
-		user: string,
-		query: { text: string } | { completion: string },
-		params: {
-			context?:     Message[];
-			persona?:     string;
-			top_k?:       number; /// int between 0 and 1k
-			top_p?:       number; /// float between 0 and 1
-			temperature?: number; /// float between 0 and 100
-		}
-	): Promise<MessageOutput> {
-		const qs = new URLSearchParams(query);
-		const path = this.path(`messages/${user}?${ qs.toString() }`);
-		
-		const response = await fetch(path, {
-			method: 'POST',
-			headers: { 'Content-Type': 'application/json' },
-			body: JSON.stringify(params),
-		});
-		return await response.json() as MessageOutput;
-	}
-	
-	/**
-	 * Demo-specific helpers
-	 */
-	async postWithSettings(
-		query: { text: string } | { completion: string },
-		params: {
-			context?:     Message[];
-			persona?:     string;
-		}
-	): Promise<MessageOutput> {
-		/// Retrieve all settings params then launch the request.
-		const top_k = Number(
-			document.querySelector('.decoder-settings .setting:nth-child(2) .js-val')!.textContent
-		);
-		const top_p = Number(
-			document.querySelector('.decoder-settings .setting:nth-child(3) .js-val')!.textContent
-		);
-		const temperature = Number(
-			document.querySelector('.decoder-settings .setting:nth-child(4) .js-val')!.textContent
-		);
-		return this.postMessage(`toto`, query, { ...params, top_k, top_p, temperature });
-	}
-}
-
diff --git a/spaces/banana-projects/web3d/node_modules/three/src/objects/Group.d.ts b/spaces/banana-projects/web3d/node_modules/three/src/objects/Group.d.ts
deleted file mode 100644
index 40b4c5f9bb44c5ffd19fd4a7314f800ac688f862..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/src/objects/Group.d.ts
+++ /dev/null
@@ -1,7 +0,0 @@
-import { Object3D } from './../core/Object3D';
-
-export class Group extends Object3D {
-  constructor();
-  type: 'Group';
-  isGroup: true;
-}
diff --git a/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/begin_vertex.glsl.js b/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/begin_vertex.glsl.js
deleted file mode 100644
index 9777ba0bb7fe6334aba3f587be0d58adc97c053a..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/begin_vertex.glsl.js
+++ /dev/null
@@ -1,3 +0,0 @@
-export default /* glsl */`
-vec3 transformed = vec3( position );
-`;
diff --git a/spaces/beihai/GFPGAN-V1.3-whole-image/.history/app_20220327004403.py b/spaces/beihai/GFPGAN-V1.3-whole-image/.history/app_20220327004403.py
deleted file mode 100644
index 377ca322982c7a78de83e7f10cebc9a17fbf979f..0000000000000000000000000000000000000000
--- a/spaces/beihai/GFPGAN-V1.3-whole-image/.history/app_20220327004403.py
+++ /dev/null
@@ -1,65 +0,0 @@
-import os
-#os.system("pip install gfpgan")
-
-#os.system("pip freeze")
-#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
-import random
-import gradio as gr
-from PIL import Image
-import torch
-# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg', 'lincoln.jpg')
-# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
-# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
-# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/a9/Henry_Ford_1888.jpg/1024px-Henry_Ford_1888.jpg', 'Henry.jpg')
-# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/0/06/Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg/800px-Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg', 'Frida.jpg')
-
-
-
-
-import cv2
-import glob
-import numpy as np
-from basicsr.utils import imwrite
-from gfpgan import GFPGANer
-
-import warnings
-warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
-              'If you really want to use it, please modify the corresponding codes.')
-bg_upsampler = None
-
-
- 
-# set up GFPGAN restorer
-restorer = GFPGANer(
-    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
-    upscale=2,
-    arch='clean',
-    channel_multiplier=2,
-    bg_upsampler=bg_upsampler)
-
-
-def inference(img):
-    input_img = cv2.imread(img)
-    restored_img = restorer.enhance(
-        input_img, has_aligned=False, only_center_face=False, paste_back=True)
-    
-    return Image.fromarray(restored_img[0][:,:,::-1])
-        
-title = "GFP-GAN"
-description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
-gr.Interface(
-    inference, 
-    [gr.inputs.Image(type="filepath", label="Input")], 
-    gr.outputs.Image(type="pil", label="Output"),
-    title=title,
-    description=description,
-    article=article,
-    examples=[
-    ['lincoln.jpg'],
-    ['einstein.png'],
-    ['edison.jpg'],
-    ['Henry.jpg'],
-    ['Frida.jpg']
-    ]
-    ).launch(enable_queue=True,cache_examples=True)
\ No newline at end of file
diff --git a/spaces/benmaor/FoodVision_Big/model.py b/spaces/benmaor/FoodVision_Big/model.py
deleted file mode 100644
index 76b0639695809088a735d0d40a6a1d12578a1903..0000000000000000000000000000000000000000
--- a/spaces/benmaor/FoodVision_Big/model.py
+++ /dev/null
@@ -1,16 +0,0 @@
-import torchvision
-import torch
-def create_ViT(num_classes: int = 101):
-  weights = torchvision.models.ViT_B_16_Weights.DEFAULT
-  transforms = weights.transforms()
-
-  model = torchvision.models.vit_b_16(weights=weights)
-
-  for parameter in model.parameters():
-    parameter.requires_grad = False
-
-  model.heads = torch.nn.Sequential(
-      torch.nn.Linear(in_features=768,
-                      out_features=num_classes))
-
-  return model, transforms
diff --git a/spaces/bigjoker/stable-diffusion-webui/script.js b/spaces/bigjoker/stable-diffusion-webui/script.js
deleted file mode 100644
index 97e0bfcf9fa3cc6b5823d86b0949ab9c947c6418..0000000000000000000000000000000000000000
--- a/spaces/bigjoker/stable-diffusion-webui/script.js
+++ /dev/null
@@ -1,102 +0,0 @@
-function gradioApp() {
-    const elems = document.getElementsByTagName('gradio-app')
-    const gradioShadowRoot = elems.length == 0 ? null : elems[0].shadowRoot
-    return !!gradioShadowRoot ? gradioShadowRoot : document;
-}
-
-function get_uiCurrentTab() {
-    return gradioApp().querySelector('#tabs button:not(.border-transparent)')
-}
-
-function get_uiCurrentTabContent() {
-    return gradioApp().querySelector('.tabitem[id^=tab_]:not([style*="display: none"])')
-}
-
-uiUpdateCallbacks = []
-uiLoadedCallbacks = []
-uiTabChangeCallbacks = []
-optionsChangedCallbacks = []
-let uiCurrentTab = null
-
-function onUiUpdate(callback){
-    uiUpdateCallbacks.push(callback)
-}
-function onUiLoaded(callback){
-    uiLoadedCallbacks.push(callback)
-}
-function onUiTabChange(callback){
-    uiTabChangeCallbacks.push(callback)
-}
-function onOptionsChanged(callback){
-    optionsChangedCallbacks.push(callback)
-}
-
-function runCallback(x, m){
-    try {
-        x(m)
-    } catch (e) {
-        (console.error || console.log).call(console, e.message, e);
-    }
-}
-function executeCallbacks(queue, m) {
-    queue.forEach(function(x){runCallback(x, m)})
-}
-
-var executedOnLoaded = false;
-
-document.addEventListener("DOMContentLoaded", function() {
-    var mutationObserver = new MutationObserver(function(m){
-        if(!executedOnLoaded && gradioApp().querySelector('#txt2img_prompt')){
-            executedOnLoaded = true;
-            executeCallbacks(uiLoadedCallbacks);
-        }
-
-        executeCallbacks(uiUpdateCallbacks, m);
-        const newTab = get_uiCurrentTab();
-        if ( newTab && ( newTab !== uiCurrentTab ) ) {
-            uiCurrentTab = newTab;
-            executeCallbacks(uiTabChangeCallbacks);
-        }
-    });
-    mutationObserver.observe( gradioApp(), { childList:true, subtree:true })
-});
-
-/**
- * Add a ctrl+enter as a shortcut to start a generation
- */
-document.addEventListener('keydown', function(e) {
-    var handled = false;
-    if (e.key !== undefined) {
-        if((e.key == "Enter" && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
-    } else if (e.keyCode !== undefined) {
-        if((e.keyCode == 13 && (e.metaKey || e.ctrlKey || e.altKey))) handled = true;
-    }
-    if (handled) {
-        button = get_uiCurrentTabContent().querySelector('button[id$=_generate]');
-        if (button) {
-            button.click();
-        }
-        e.preventDefault();
-    }
-})
-
-/**
- * checks that a UI element is not in another hidden element or tab content
- */
-function uiElementIsVisible(el) {
-    let isVisible = !el.closest('.\\!hidden');
-    if ( ! isVisible ) {
-        return false;
-    }
-
-    while( isVisible = el.closest('.tabitem')?.style.display !== 'none' ) {
-        if ( ! isVisible ) {
-            return false;
-        } else if ( el.parentElement ) {
-            el = el.parentElement
-        } else {
-            break;
-        }
-    }
-    return isVisible;
-}
diff --git a/spaces/bioriAsaeru/text-to-voice/CRACK ALLYCAD 3.6 FREEWARE Learn How to Design Anything with this Amazing CAD Program.md b/spaces/bioriAsaeru/text-to-voice/CRACK ALLYCAD 3.6 FREEWARE Learn How to Design Anything with this Amazing CAD Program.md
deleted file mode 100644
index c79e836ce0a090bfa3bf3320beba17f3cf51d610..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/CRACK ALLYCAD 3.6 FREEWARE Learn How to Design Anything with this Amazing CAD Program.md	
+++ /dev/null
@@ -1,7 +0,0 @@
-
-<p>You cannot download any crack or serial number for AllyCAD on this page. Every software that you are able to download on our site is legal. There is no crack, serial number, hack or activation key for AllyCAD present here. Our collection also doesn't contain any keygens, because keygen programs are being used in illegal ways which we do not support. All software that you can find here is freely downloadable and legal.</p>
-<p>All software that you can find on our servers, including AllyCAD, is either freeware, shareware or open-source, some of the software packages are demo, trial or patch versions and if possible (public domain licence), we also host official full versions of software.</p>
-<h2>CRACK ALLYCAD 3.6 FREEWARE</h2><br /><p><b><b>Download File</b> &#9881; <a href="https://urloso.com/2uyRsD">https://urloso.com/2uyRsD</a></b></p><br /><br />
-<p>© Fyxm.net - A Free Download Portal - 120,459 Programs Online. All provided software is freeware, shareware, trial or demo version. <br> 500GB hosted on our servers. All rights reserved. All other trademarks are the sole property of their respective owners. D.M.C.A.</p> aaccfb2cb3<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/bioriAsaeru/text-to-voice/Cisco.AnyConnect-win-4.1.06020.md b/spaces/bioriAsaeru/text-to-voice/Cisco.AnyConnect-win-4.1.06020.md
deleted file mode 100644
index 0ada2dd2141b032ab15a3b8dfafb414642c3c0bb..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Cisco.AnyConnect-win-4.1.06020.md
+++ /dev/null
@@ -1,28 +0,0 @@
-<br />
-<h1>How to Download and Install Cisco AnyConnect Secure Mobility Client for Windows</h1>
-<p>Cisco AnyConnect Secure Mobility Client is a software that provides secure and flexible access to your organization's network and resources from any device. It also offers enhanced security features such as VPN posture, malware protection, web security, and network visibility.</p>
-<h2>Cisco.AnyConnect-win-4.1.06020</h2><br /><p><b><b>Download Zip</b> &#10037; <a href="https://urloso.com/2uyPcz">https://urloso.com/2uyPcz</a></b></p><br /><br />
-<p>If you want to download and install Cisco AnyConnect Secure Mobility Client for Windows, you need to follow these steps:</p>
-<ol>
-<li>Visit the Cisco AnyConnect Secure Mobility Client v4.x page[^1^] and select the version that matches your operating system.</li>
-<li>Click on the Download button and log in with your Cisco account credentials. If you don't have a Cisco account, you can create one for free.</li>
-<li>Save the file to your computer and run it as an administrator.</li>
-<li>Follow the installation wizard instructions and accept the license agreement.</li>
-<li>When the installation is complete, launch the Cisco AnyConnect Secure Mobility Client from your Start menu or desktop shortcut.</li>
-<li>Enter the VPN server address provided by your organization and click Connect.</li>
-<li>Enter your username and password and click OK.</li>
-<li>You are now connected to your organization's network and can access its resources securely.</li>
-</ol>
-<p>Cisco AnyConnect Secure Mobility Client for Windows is a powerful and easy-to-use software that helps you stay productive and protected wherever you are. You can also use it with Duo[^2^], a two-factor authentication service that adds an extra layer of security to your login process. To learn more about Cisco AnyConnect Secure Mobility Client, visit the official website[^2^] or contact your IT administrator.</p>
-
-<p>Cisco AnyConnect Secure Mobility Client for Windows has many features and benefits that make it a superior choice for remote access. Some of these features are:</p>
-<ul>
-<li>VPN posture: This feature checks your device for compliance with your organization's security policies before allowing you to connect to the VPN. It can also remediate any issues that are detected, such as outdated software, missing patches, or malware infections.</li>
-<li>Malware protection: This feature protects your device from malicious software and websites that can compromise your data and privacy. It uses Cisco Advanced Malware Protection (AMP) to scan and block any threats that are detected.</li>
-<li>Web security: This feature protects your device from web-based attacks and phishing attempts that can steal your credentials and personal information. It uses Cisco Web Security Appliance (WSA) to filter and monitor your web traffic and enforce your organization's web policies.</li>
-<li>Network visibility: This feature provides you with detailed information about your network and device performance, such as bandwidth usage, latency, packet loss, and connection quality. It also helps you troubleshoot any issues that may affect your VPN experience.</li>
-</ul>
-<p>Cisco AnyConnect Secure Mobility Client for Windows is a comprehensive and reliable software that enhances your remote access security and productivity. You can download it from the Cisco website or get it from your IT administrator. You can also use it with Duo to add an extra layer of security to your login process. To learn more about Cisco AnyConnect Secure Mobility Client, visit the official website or contact your IT administrator.</p>
-<p></p> d5da3c52bf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/brainblow/MusiCreator/audiocraft/modules/conv.py b/spaces/brainblow/MusiCreator/audiocraft/modules/conv.py
deleted file mode 100644
index 972938ab84712eb06e1b10cea25444eee51d6637..0000000000000000000000000000000000000000
--- a/spaces/brainblow/MusiCreator/audiocraft/modules/conv.py
+++ /dev/null
@@ -1,245 +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 math
-import typing as tp
-import warnings
-
-import torch
-from torch import nn
-from torch.nn import functional as F
-from torch.nn.utils import spectral_norm, weight_norm
-
-
-CONV_NORMALIZATIONS = frozenset(['none', 'weight_norm', 'spectral_norm',
-                                 'time_group_norm'])
-
-
-def apply_parametrization_norm(module: nn.Module, norm: str = 'none'):
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'weight_norm':
-        return weight_norm(module)
-    elif norm == 'spectral_norm':
-        return spectral_norm(module)
-    else:
-        # We already check was in CONV_NORMALIZATION, so any other choice
-        # doesn't need reparametrization.
-        return module
-
-
-def get_norm_module(module: nn.Module, causal: bool = False, norm: str = 'none', **norm_kwargs):
-    """Return the proper normalization module. If causal is True, this will ensure the returned
-    module is causal, or return an error if the normalization doesn't support causal evaluation.
-    """
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'time_group_norm':
-        if causal:
-            raise ValueError("GroupNorm doesn't support causal evaluation.")
-        assert isinstance(module, nn.modules.conv._ConvNd)
-        return nn.GroupNorm(1, module.out_channels, **norm_kwargs)
-    else:
-        return nn.Identity()
-
-
-def get_extra_padding_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int,
-                                 padding_total: int = 0) -> int:
-    """See `pad_for_conv1d`.
-    """
-    length = x.shape[-1]
-    n_frames = (length - kernel_size + padding_total) / stride + 1
-    ideal_length = (math.ceil(n_frames) - 1) * stride + (kernel_size - padding_total)
-    return ideal_length - length
-
-
-def pad_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int, padding_total: int = 0):
-    """Pad for a convolution to make sure that the last window is full.
-    Extra padding is added at the end. This is required to ensure that we can rebuild
-    an output of the same length, as otherwise, even with padding, some time steps
-    might get removed.
-    For instance, with total padding = 4, kernel size = 4, stride = 2:
-        0 0 1 2 3 4 5 0 0   # (0s are padding)
-        1   2   3           # (output frames of a convolution, last 0 is never used)
-        0 0 1 2 3 4 5 0     # (output of tr. conv., but pos. 5 is going to get removed as padding)
-            1 2 3 4         # once you removed padding, we are missing one time step !
-    """
-    extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-    return F.pad(x, (0, extra_padding))
-
-
-def pad1d(x: torch.Tensor, paddings: tp.Tuple[int, int], mode: str = 'constant', value: float = 0.):
-    """Tiny wrapper around F.pad, just to allow for reflect padding on small input.
-    If this is the case, we insert extra 0 padding to the right before the reflection happen.
-    """
-    length = x.shape[-1]
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    if mode == 'reflect':
-        max_pad = max(padding_left, padding_right)
-        extra_pad = 0
-        if length <= max_pad:
-            extra_pad = max_pad - length + 1
-            x = F.pad(x, (0, extra_pad))
-        padded = F.pad(x, paddings, mode, value)
-        end = padded.shape[-1] - extra_pad
-        return padded[..., :end]
-    else:
-        return F.pad(x, paddings, mode, value)
-
-
-def unpad1d(x: torch.Tensor, paddings: tp.Tuple[int, int]):
-    """Remove padding from x, handling properly zero padding. Only for 1d!
-    """
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    assert (padding_left + padding_right) <= x.shape[-1]
-    end = x.shape[-1] - padding_right
-    return x[..., padding_left: end]
-
-
-class NormConv1d(nn.Module):
-    """Wrapper around Conv1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConv2d(nn.Module):
-    """Wrapper around Conv2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal=False, norm=norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConvTranspose1d(nn.Module):
-    """Wrapper around ConvTranspose1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-
-
-class NormConvTranspose2d(nn.Module):
-    """Wrapper around ConvTranspose2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal=False, norm=norm, **norm_kwargs)
-
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-
-
-class StreamableConv1d(nn.Module):
-    """Conv1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, dilation: int = 1,
-                 groups: int = 1, bias: bool = True, causal: bool = False,
-                 norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {},
-                 pad_mode: str = 'reflect'):
-        super().__init__()
-        # warn user on unusual setup between dilation and stride
-        if stride > 1 and dilation > 1:
-            warnings.warn('StreamableConv1d has been initialized with stride > 1 and dilation > 1'
-                          f' (kernel_size={kernel_size} stride={stride}, dilation={dilation}).')
-        self.conv = NormConv1d(in_channels, out_channels, kernel_size, stride,
-                               dilation=dilation, groups=groups, bias=bias, causal=causal,
-                               norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.pad_mode = pad_mode
-
-    def forward(self, x):
-        B, C, T = x.shape
-        kernel_size = self.conv.conv.kernel_size[0]
-        stride = self.conv.conv.stride[0]
-        dilation = self.conv.conv.dilation[0]
-        kernel_size = (kernel_size - 1) * dilation + 1  # effective kernel size with dilations
-        padding_total = kernel_size - stride
-        extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-        if self.causal:
-            # Left padding for causal
-            x = pad1d(x, (padding_total, extra_padding), mode=self.pad_mode)
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            x = pad1d(x, (padding_left, padding_right + extra_padding), mode=self.pad_mode)
-        return self.conv(x)
-
-
-class StreamableConvTranspose1d(nn.Module):
-    """ConvTranspose1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, causal: bool = False,
-                 norm: str = 'none', trim_right_ratio: float = 1.,
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}):
-        super().__init__()
-        self.convtr = NormConvTranspose1d(in_channels, out_channels, kernel_size, stride,
-                                          causal=causal, norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.trim_right_ratio = trim_right_ratio
-        assert self.causal or self.trim_right_ratio == 1., \
-            "`trim_right_ratio` != 1.0 only makes sense for causal convolutions"
-        assert self.trim_right_ratio >= 0. and self.trim_right_ratio <= 1.
-
-    def forward(self, x):
-        kernel_size = self.convtr.convtr.kernel_size[0]
-        stride = self.convtr.convtr.stride[0]
-        padding_total = kernel_size - stride
-
-        y = self.convtr(x)
-
-        # We will only trim fixed padding. Extra padding from `pad_for_conv1d` would be
-        # removed at the very end, when keeping only the right length for the output,
-        # as removing it here would require also passing the length at the matching layer
-        # in the encoder.
-        if self.causal:
-            # Trim the padding on the right according to the specified ratio
-            # if trim_right_ratio = 1.0, trim everything from right
-            padding_right = math.ceil(padding_total * self.trim_right_ratio)
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        return y
diff --git a/spaces/brjathu/HMR2.0/vendor/detectron2/projects/DensePose/densepose/modeling/cse/__init__.py b/spaces/brjathu/HMR2.0/vendor/detectron2/projects/DensePose/densepose/modeling/cse/__init__.py
deleted file mode 100644
index a2273609cc54fb96d002a49dcd58788060945059..0000000000000000000000000000000000000000
--- a/spaces/brjathu/HMR2.0/vendor/detectron2/projects/DensePose/densepose/modeling/cse/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-from .vertex_direct_embedder import VertexDirectEmbedder
-from .vertex_feature_embedder import VertexFeatureEmbedder
-from .embedder import Embedder
diff --git a/spaces/bulentsofttech/gradio_s1000_veri_toplama_modeli/yolov5/utils/loggers/__init__.py b/spaces/bulentsofttech/gradio_s1000_veri_toplama_modeli/yolov5/utils/loggers/__init__.py
deleted file mode 100644
index 42b696ba644f8aebf0d0555f2923c462eb767891..0000000000000000000000000000000000000000
--- a/spaces/bulentsofttech/gradio_s1000_veri_toplama_modeli/yolov5/utils/loggers/__init__.py
+++ /dev/null
@@ -1,187 +0,0 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-"""
-Logging utils
-"""
-
-import os
-import warnings
-
-import pkg_resources as pkg
-import torch
-from torch.utils.tensorboard import SummaryWriter
-
-from utils.general import colorstr, cv2, emojis
-from utils.loggers.wandb.wandb_utils import WandbLogger
-from utils.plots import plot_images, plot_results
-from utils.torch_utils import de_parallel
-
-LOGGERS = ('csv', 'tb', 'wandb')  # text-file, TensorBoard, Weights & Biases
-RANK = int(os.getenv('RANK', -1))
-
-try:
-    import wandb
-
-    assert hasattr(wandb, '__version__')  # verify package import not local dir
-    if pkg.parse_version(wandb.__version__) >= pkg.parse_version('0.12.2') and RANK in {0, -1}:
-        try:
-            wandb_login_success = wandb.login(timeout=30)
-        except wandb.errors.UsageError:  # known non-TTY terminal issue
-            wandb_login_success = False
-        if not wandb_login_success:
-            wandb = None
-except (ImportError, AssertionError):
-    wandb = None
-
-
-class Loggers():
-    # YOLOv5 Loggers class
-    def __init__(self, save_dir=None, weights=None, opt=None, hyp=None, logger=None, include=LOGGERS):
-        self.save_dir = save_dir
-        self.weights = weights
-        self.opt = opt
-        self.hyp = hyp
-        self.logger = logger  # for printing results to console
-        self.include = include
-        self.keys = [
-            'train/box_loss',
-            'train/obj_loss',
-            'train/cls_loss',  # train loss
-            'metrics/precision',
-            'metrics/recall',
-            'metrics/mAP_0.5',
-            'metrics/mAP_0.5:0.95',  # metrics
-            'val/box_loss',
-            'val/obj_loss',
-            'val/cls_loss',  # val loss
-            'x/lr0',
-            'x/lr1',
-            'x/lr2']  # params
-        self.best_keys = ['best/epoch', 'best/precision', 'best/recall', 'best/mAP_0.5', 'best/mAP_0.5:0.95']
-        for k in LOGGERS:
-            setattr(self, k, None)  # init empty logger dictionary
-        self.csv = True  # always log to csv
-
-        # Message
-        if not wandb:
-            prefix = colorstr('Weights & Biases: ')
-            s = f"{prefix}run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs (RECOMMENDED)"
-            self.logger.info(emojis(s))
-
-        # TensorBoard
-        s = self.save_dir
-        if 'tb' in self.include and not self.opt.evolve:
-            prefix = colorstr('TensorBoard: ')
-            self.logger.info(f"{prefix}Start with 'tensorboard --logdir {s.parent}', view at http://localhost:6006/")
-            self.tb = SummaryWriter(str(s))
-
-        # W&B
-        if wandb and 'wandb' in self.include:
-            wandb_artifact_resume = isinstance(self.opt.resume, str) and self.opt.resume.startswith('wandb-artifact://')
-            run_id = torch.load(self.weights).get('wandb_id') if self.opt.resume and not wandb_artifact_resume else None
-            self.opt.hyp = self.hyp  # add hyperparameters
-            self.wandb = WandbLogger(self.opt, run_id)
-            # temp warn. because nested artifacts not supported after 0.12.10
-            if pkg.parse_version(wandb.__version__) >= pkg.parse_version('0.12.11'):
-                self.logger.warning(
-                    "YOLOv5 temporarily requires wandb version 0.12.10 or below. Some features may not work as expected."
-                )
-        else:
-            self.wandb = None
-
-    def on_train_start(self):
-        # Callback runs on train start
-        pass
-
-    def on_pretrain_routine_end(self):
-        # Callback runs on pre-train routine end
-        paths = self.save_dir.glob('*labels*.jpg')  # training labels
-        if self.wandb:
-            self.wandb.log({"Labels": [wandb.Image(str(x), caption=x.name) for x in paths]})
-
-    def on_train_batch_end(self, ni, model, imgs, targets, paths, plots):
-        # Callback runs on train batch end
-        if plots:
-            if ni == 0:
-                if not self.opt.sync_bn:  # --sync known issue https://github.com/ultralytics/yolov5/issues/3754
-                    with warnings.catch_warnings():
-                        warnings.simplefilter('ignore')  # suppress jit trace warning
-                        self.tb.add_graph(torch.jit.trace(de_parallel(model), imgs[0:1], strict=False), [])
-            if ni < 3:
-                f = self.save_dir / f'train_batch{ni}.jpg'  # filename
-                plot_images(imgs, targets, paths, f)
-            if self.wandb and ni == 10:
-                files = sorted(self.save_dir.glob('train*.jpg'))
-                self.wandb.log({'Mosaics': [wandb.Image(str(f), caption=f.name) for f in files if f.exists()]})
-
-    def on_train_epoch_end(self, epoch):
-        # Callback runs on train epoch end
-        if self.wandb:
-            self.wandb.current_epoch = epoch + 1
-
-    def on_val_image_end(self, pred, predn, path, names, im):
-        # Callback runs on val image end
-        if self.wandb:
-            self.wandb.val_one_image(pred, predn, path, names, im)
-
-    def on_val_end(self):
-        # Callback runs on val end
-        if self.wandb:
-            files = sorted(self.save_dir.glob('val*.jpg'))
-            self.wandb.log({"Validation": [wandb.Image(str(f), caption=f.name) for f in files]})
-
-    def on_fit_epoch_end(self, vals, epoch, best_fitness, fi):
-        # Callback runs at the end of each fit (train+val) epoch
-        x = dict(zip(self.keys, vals))
-        if self.csv:
-            file = self.save_dir / 'results.csv'
-            n = len(x) + 1  # number of cols
-            s = '' if file.exists() else (('%20s,' * n % tuple(['epoch'] + self.keys)).rstrip(',') + '\n')  # add header
-            with open(file, 'a') as f:
-                f.write(s + ('%20.5g,' * n % tuple([epoch] + vals)).rstrip(',') + '\n')
-
-        if self.tb:
-            for k, v in x.items():
-                self.tb.add_scalar(k, v, epoch)
-
-        if self.wandb:
-            if best_fitness == fi:
-                best_results = [epoch] + vals[3:7]
-                for i, name in enumerate(self.best_keys):
-                    self.wandb.wandb_run.summary[name] = best_results[i]  # log best results in the summary
-            self.wandb.log(x)
-            self.wandb.end_epoch(best_result=best_fitness == fi)
-
-    def on_model_save(self, last, epoch, final_epoch, best_fitness, fi):
-        # Callback runs on model save event
-        if self.wandb:
-            if ((epoch + 1) % self.opt.save_period == 0 and not final_epoch) and self.opt.save_period != -1:
-                self.wandb.log_model(last.parent, self.opt, epoch, fi, best_model=best_fitness == fi)
-
-    def on_train_end(self, last, best, plots, epoch, results):
-        # Callback runs on training end
-        if plots:
-            plot_results(file=self.save_dir / 'results.csv')  # save results.png
-        files = ['results.png', 'confusion_matrix.png', *(f'{x}_curve.png' for x in ('F1', 'PR', 'P', 'R'))]
-        files = [(self.save_dir / f) for f in files if (self.save_dir / f).exists()]  # filter
-        self.logger.info(f"Results saved to {colorstr('bold', self.save_dir)}")
-
-        if self.tb:
-            for f in files:
-                self.tb.add_image(f.stem, cv2.imread(str(f))[..., ::-1], epoch, dataformats='HWC')
-
-        if self.wandb:
-            self.wandb.log(dict(zip(self.keys[3:10], results)))
-            self.wandb.log({"Results": [wandb.Image(str(f), caption=f.name) for f in files]})
-            # Calling wandb.log. TODO: Refactor this into WandbLogger.log_model
-            if not self.opt.evolve:
-                wandb.log_artifact(str(best if best.exists() else last),
-                                   type='model',
-                                   name=f'run_{self.wandb.wandb_run.id}_model',
-                                   aliases=['latest', 'best', 'stripped'])
-            self.wandb.finish_run()
-
-    def on_params_update(self, params):
-        # Update hyperparams or configs of the experiment
-        # params: A dict containing {param: value} pairs
-        if self.wandb:
-            self.wandb.wandb_run.config.update(params, allow_val_change=True)
diff --git a/spaces/carlosalonso/Detection-video/carpeta_deteccion/tests/tracking/test_bbox_iou_tracker.py b/spaces/carlosalonso/Detection-video/carpeta_deteccion/tests/tracking/test_bbox_iou_tracker.py
deleted file mode 100644
index e720b2eb98788670c7daf2a694eff1fdc7b9f1bd..0000000000000000000000000000000000000000
--- a/spaces/carlosalonso/Detection-video/carpeta_deteccion/tests/tracking/test_bbox_iou_tracker.py
+++ /dev/null
@@ -1,160 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-import unittest
-from copy import deepcopy
-from typing import Dict
-import torch
-
-from detectron2.config import CfgNode as CfgNode_
-from detectron2.config import instantiate
-from detectron2.structures import Boxes, Instances
-from detectron2.tracking.base_tracker import build_tracker_head
-from detectron2.tracking.bbox_iou_tracker import BBoxIOUTracker  # noqa
-
-
-class TestBBoxIOUTracker(unittest.TestCase):
-    def setUp(self):
-        self._img_size = np.array([600, 800])
-        self._prev_boxes = np.array(
-            [
-                [101, 101, 200, 200],
-                [301, 301, 450, 450],
-            ]
-        ).astype(np.float32)
-        self._prev_scores = np.array([0.9, 0.9])
-        self._prev_classes = np.array([1, 1])
-        self._prev_masks = np.ones((2, 600, 800)).astype("uint8")
-        self._curr_boxes = np.array(
-            [
-                [302, 303, 451, 452],
-                [101, 102, 201, 203],
-            ]
-        ).astype(np.float32)
-        self._curr_scores = np.array([0.95, 0.85])
-        self._curr_classes = np.array([1, 1])
-        self._curr_masks = np.ones((2, 600, 800)).astype("uint8")
-
-        self._prev_instances = {
-            "image_size": self._img_size,
-            "pred_boxes": self._prev_boxes,
-            "scores": self._prev_scores,
-            "pred_classes": self._prev_classes,
-            "pred_masks": self._prev_masks,
-        }
-        self._prev_instances = self._convertDictPredictionToInstance(self._prev_instances)
-        self._curr_instances = {
-            "image_size": self._img_size,
-            "pred_boxes": self._curr_boxes,
-            "scores": self._curr_scores,
-            "pred_classes": self._curr_classes,
-            "pred_masks": self._curr_masks,
-        }
-        self._curr_instances = self._convertDictPredictionToInstance(self._curr_instances)
-
-        self._max_num_instances = 200
-        self._max_lost_frame_count = 0
-        self._min_box_rel_dim = 0.02
-        self._min_instance_period = 1
-        self._track_iou_threshold = 0.5
-
-    def _convertDictPredictionToInstance(self, prediction: Dict) -> Instances:
-        """
-        convert prediction from Dict to D2 Instances format
-        """
-        res = Instances(
-            image_size=torch.IntTensor(prediction["image_size"]),
-            pred_boxes=Boxes(torch.FloatTensor(prediction["pred_boxes"])),
-            pred_masks=torch.IntTensor(prediction["pred_masks"]),
-            pred_classes=torch.IntTensor(prediction["pred_classes"]),
-            scores=torch.FloatTensor(prediction["scores"]),
-        )
-        return res
-
-    def test_init(self):
-        cfg = {
-            "_target_": "detectron2.tracking.bbox_iou_tracker.BBoxIOUTracker",
-            "video_height": self._img_size[0],
-            "video_width": self._img_size[1],
-            "max_num_instances": self._max_num_instances,
-            "max_lost_frame_count": self._max_lost_frame_count,
-            "min_box_rel_dim": self._min_box_rel_dim,
-            "min_instance_period": self._min_instance_period,
-            "track_iou_threshold": self._track_iou_threshold,
-        }
-        tracker = instantiate(cfg)
-        self.assertTrue(tracker._video_height == self._img_size[0])
-
-    def test_from_config(self):
-        cfg = CfgNode_()
-        cfg.TRACKER_HEADS = CfgNode_()
-        cfg.TRACKER_HEADS.TRACKER_NAME = "BBoxIOUTracker"
-        cfg.TRACKER_HEADS.VIDEO_HEIGHT = int(self._img_size[0])
-        cfg.TRACKER_HEADS.VIDEO_WIDTH = int(self._img_size[1])
-        cfg.TRACKER_HEADS.MAX_NUM_INSTANCES = self._max_num_instances
-        cfg.TRACKER_HEADS.MAX_LOST_FRAME_COUNT = self._max_lost_frame_count
-        cfg.TRACKER_HEADS.MIN_BOX_REL_DIM = self._min_box_rel_dim
-        cfg.TRACKER_HEADS.MIN_INSTANCE_PERIOD = self._min_instance_period
-        cfg.TRACKER_HEADS.TRACK_IOU_THRESHOLD = self._track_iou_threshold
-        tracker = build_tracker_head(cfg)
-        self.assertTrue(tracker._video_height == self._img_size[0])
-
-    def test_initialize_extra_fields(self):
-        cfg = {
-            "_target_": "detectron2.tracking.bbox_iou_tracker.BBoxIOUTracker",
-            "video_height": self._img_size[0],
-            "video_width": self._img_size[1],
-            "max_num_instances": self._max_num_instances,
-            "max_lost_frame_count": self._max_lost_frame_count,
-            "min_box_rel_dim": self._min_box_rel_dim,
-            "min_instance_period": self._min_instance_period,
-            "track_iou_threshold": self._track_iou_threshold,
-        }
-        tracker = instantiate(cfg)
-        instances = tracker._initialize_extra_fields(self._curr_instances)
-        self.assertTrue(instances.has("ID"))
-        self.assertTrue(instances.has("ID_period"))
-        self.assertTrue(instances.has("lost_frame_count"))
-
-    def test_assign_new_id(self):
-        cfg = {
-            "_target_": "detectron2.tracking.bbox_iou_tracker.BBoxIOUTracker",
-            "video_height": self._img_size[0],
-            "video_width": self._img_size[1],
-            "max_num_instances": self._max_num_instances,
-            "max_lost_frame_count": self._max_lost_frame_count,
-            "min_box_rel_dim": self._min_box_rel_dim,
-            "min_instance_period": self._min_instance_period,
-            "track_iou_threshold": self._track_iou_threshold,
-        }
-        tracker = instantiate(cfg)
-        instances = deepcopy(self._curr_instances)
-        instances = tracker._initialize_extra_fields(instances)
-        instances = tracker._assign_new_id(instances)
-        self.assertTrue(len(instances.ID) == 2)
-        self.assertTrue(instances.ID[0] == 2)
-        self.assertTrue(instances.ID[1] == 3)
-
-    def test_update(self):
-        cfg = {
-            "_target_": "detectron2.tracking.bbox_iou_tracker.BBoxIOUTracker",
-            "video_height": self._img_size[0],
-            "video_width": self._img_size[1],
-            "max_num_instances": self._max_num_instances,
-            "max_lost_frame_count": self._max_lost_frame_count,
-            "min_box_rel_dim": self._min_box_rel_dim,
-            "min_instance_period": self._min_instance_period,
-            "track_iou_threshold": self._track_iou_threshold,
-        }
-        tracker = instantiate(cfg)
-        prev_instances = tracker.update(self._prev_instances)
-        self.assertTrue(len(prev_instances.ID) == 2)
-        self.assertTrue(prev_instances.ID[0] == 0)
-        self.assertTrue(prev_instances.ID[1] == 1)
-        curr_instances = tracker.update(self._curr_instances)
-        self.assertTrue(len(curr_instances.ID) == 2)
-        self.assertTrue(curr_instances.ID[0] == 1)
-        self.assertTrue(curr_instances.ID[1] == 0)
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/spaces/cccccch/VITS-fast-fine-tuning-DingZhen/text/english.py b/spaces/cccccch/VITS-fast-fine-tuning-DingZhen/text/english.py
deleted file mode 100644
index 6817392ba8a9eb830351de89fb7afc5ad72f5e42..0000000000000000000000000000000000000000
--- a/spaces/cccccch/VITS-fast-fine-tuning-DingZhen/text/english.py
+++ /dev/null
@@ -1,188 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-
-'''
-Cleaners are transformations that run over the input text at both training and eval time.
-
-Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
-hyperparameter. Some cleaners are English-specific. You'll typically want to use:
-  1. "english_cleaners" for English text
-  2. "transliteration_cleaners" for non-English text that can be transliterated to ASCII using
-     the Unidecode library (https://pypi.python.org/pypi/Unidecode)
-  3. "basic_cleaners" if you do not want to transliterate (in this case, you should also update
-     the symbols in symbols.py to match your data).
-'''
-
-
-# Regular expression matching whitespace:
-
-
-import re
-import inflect
-from unidecode import unidecode
-import eng_to_ipa as ipa
-_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]+')
-
-# 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'),
-]]
-
-
-# List of (ipa, lazy ipa) pairs:
-_lazy_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('r', 'ɹ'),
-    ('æ', 'e'),
-    ('ɑ', 'a'),
-    ('ɔ', 'o'),
-    ('ð', 'z'),
-    ('θ', 's'),
-    ('ɛ', 'e'),
-    ('ɪ', 'i'),
-    ('ʊ', 'u'),
-    ('ʒ', 'ʥ'),
-    ('ʤ', 'ʥ'),
-    ('ˈ', '↓'),
-]]
-
-# List of (ipa, lazy ipa2) pairs:
-_lazy_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('r', 'ɹ'),
-    ('ð', 'z'),
-    ('θ', 's'),
-    ('ʒ', 'ʑ'),
-    ('ʤ', 'dʑ'),
-    ('ˈ', '↓'),
-]]
-
-# List of (ipa, ipa2) pairs
-_ipa_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('r', 'ɹ'),
-    ('ʤ', 'dʒ'),
-    ('ʧ', 'tʃ')
-]]
-
-
-def expand_abbreviations(text):
-    for regex, replacement in _abbreviations:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def collapse_whitespace(text):
-    return re.sub(r'\s+', ' ', text)
-
-
-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
-
-
-def mark_dark_l(text):
-    return re.sub(r'l([^aeiouæɑɔəɛɪʊ ]*(?: |$))', lambda x: 'ɫ'+x.group(1), text)
-
-
-def english_to_ipa(text):
-    text = unidecode(text).lower()
-    text = expand_abbreviations(text)
-    text = normalize_numbers(text)
-    phonemes = ipa.convert(text)
-    phonemes = collapse_whitespace(phonemes)
-    return phonemes
-
-
-def english_to_lazy_ipa(text):
-    text = english_to_ipa(text)
-    for regex, replacement in _lazy_ipa:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def english_to_ipa2(text):
-    text = english_to_ipa(text)
-    text = mark_dark_l(text)
-    for regex, replacement in _ipa_to_ipa2:
-        text = re.sub(regex, replacement, text)
-    return text.replace('...', '…')
-
-
-def english_to_lazy_ipa2(text):
-    text = english_to_ipa(text)
-    for regex, replacement in _lazy_ipa2:
-        text = re.sub(regex, replacement, text)
-    return text
diff --git a/spaces/ccolas/TastyPiano/src/music2cocktailrep/training/__init__.py b/spaces/ccolas/TastyPiano/src/music2cocktailrep/training/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/celise88/Pathfinder/user_utils.py b/spaces/celise88/Pathfinder/user_utils.py
deleted file mode 100644
index 6bdd413223af9e4a0bfd191edf20f023cbbb22eb..0000000000000000000000000000000000000000
--- a/spaces/celise88/Pathfinder/user_utils.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from passlib.context import CryptContext
-
-pwd_cxt = CryptContext(schemes=['bcrypt'], deprecated="auto")
-
-class Hash():
-    def bcrypt(password: str):
-        return pwd_cxt.hash(password)
-
-    def verify(plain_password: str, hashed_password: str):
-        return pwd_cxt.verify(plain_password, hashed_password)
\ No newline at end of file
diff --git a/spaces/chenbowen-184/Martin-Valen-Text-to-Image/README.md b/spaces/chenbowen-184/Martin-Valen-Text-to-Image/README.md
deleted file mode 100644
index 616002c6db1f7dd47987ecb80b40aa88a6498307..0000000000000000000000000000000000000000
--- a/spaces/chenbowen-184/Martin-Valen-Text-to-Image/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Martin Valen Text To Image
-emoji: 🌍
-colorFrom: purple
-colorTo: purple
-sdk: gradio
-sdk_version: 3.34.0
-app_file: app.py
-pinned: false
-license: openrail
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/chendl/compositional_test/multimodal/YOLOX/yolox/evaluators/__init__.py b/spaces/chendl/compositional_test/multimodal/YOLOX/yolox/evaluators/__init__.py
deleted file mode 100644
index 1a99047b4bcd5cfba68540fd94ee80926bb0044b..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/multimodal/YOLOX/yolox/evaluators/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-# Copyright (c) Megvii, Inc. and its affiliates.
-
-from .coco_evaluator import COCOEvaluator
-from .voc_evaluator import VOCEvaluator
diff --git a/spaces/chendl/compositional_test/transformers/examples/legacy/seq2seq/pack_dataset.py b/spaces/chendl/compositional_test/transformers/examples/legacy/seq2seq/pack_dataset.py
deleted file mode 100644
index 8b069e452a71779692c68e3c03b0d2c008880c7e..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/transformers/examples/legacy/seq2seq/pack_dataset.py
+++ /dev/null
@@ -1,87 +0,0 @@
-#!/usr/bin/env python
-# 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.
-"""Fill examples with bitext up to max_tokens without breaking up examples.
-[['I went', 'yo fui'],
-['to the store', 'a la tienda']
-]
-=> ['I went to the store', 'yo fui a la tienda']
-"""
-
-import argparse
-import shutil
-from pathlib import Path
-
-from tqdm import tqdm
-
-from transformers import AutoTokenizer
-
-
-def pack_examples(tok, src_examples, tgt_examples, max_tokens=1024):
-    finished_src, finished_tgt = [], []
-
-    sorted_examples = list(zip(src_examples, tgt_examples))
-    new_src, new_tgt = sorted_examples[0]
-
-    def is_too_big(strang):
-        return tok(strang, return_tensors="pt").input_ids.shape[1] > max_tokens
-
-    for src, tgt in tqdm(sorted_examples[1:]):
-        cand_src = new_src + " " + src
-        cand_tgt = new_tgt + " " + tgt
-        if is_too_big(cand_src) or is_too_big(cand_tgt):  # cant fit, finalize example
-            finished_src.append(new_src)
-            finished_tgt.append(new_tgt)
-            new_src, new_tgt = src, tgt
-        else:  # can fit, keep adding
-            new_src, new_tgt = cand_src, cand_tgt
-
-    # cleanup
-    if new_src:
-        assert new_tgt
-        finished_src.append(new_src)
-        finished_tgt.append(new_tgt)
-    return finished_src, finished_tgt
-
-
-def pack_data_dir(tok, data_dir: Path, max_tokens, save_path):
-    save_path = Path(save_path)
-    save_path.mkdir(exist_ok=True)
-    for split in ["train"]:
-        src_path, tgt_path = data_dir / f"{split}.source", data_dir / f"{split}.target"
-        src_docs = [x.rstrip() for x in Path(src_path).open().readlines()]
-        tgt_docs = [x.rstrip() for x in Path(tgt_path).open().readlines()]
-        packed_src, packed_tgt = pack_examples(tok, src_docs, tgt_docs, max_tokens)
-        print(f"packed {split} split from {len(src_docs)} examples -> {len(packed_src)}.")
-        Path(save_path / f"{split}.source").open("w").write("\n".join(packed_src))
-        Path(save_path / f"{split}.target").open("w").write("\n".join(packed_tgt))
-    for split in ["val", "test"]:
-        src_path, tgt_path = data_dir / f"{split}.source", data_dir / f"{split}.target"
-        shutil.copyfile(src_path, save_path / f"{split}.source")
-        shutil.copyfile(tgt_path, save_path / f"{split}.target")
-
-
-def packer_cli():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--tok_name", type=str, help="like facebook/bart-large-cnn,t5-base, etc.")
-    parser.add_argument("--max_seq_len", type=int, default=128)
-    parser.add_argument("--data_dir", type=str)
-    parser.add_argument("--save_path", type=str)
-    args = parser.parse_args()
-    tokenizer = AutoTokenizer.from_pretrained(args.tok_name)
-    return pack_data_dir(tokenizer, Path(args.data_dir), args.max_seq_len, args.save_path)
-
-
-if __name__ == "__main__":
-    packer_cli()
diff --git a/spaces/chendl/compositional_test/transformers/examples/research_projects/jax-projects/big_bird/train.py b/spaces/chendl/compositional_test/transformers/examples/research_projects/jax-projects/big_bird/train.py
deleted file mode 100644
index ce37b7f975bb3aceb41df88ef1b51bfe71098408..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/transformers/examples/research_projects/jax-projects/big_bird/train.py
+++ /dev/null
@@ -1,78 +0,0 @@
-import os
-from dataclasses import replace
-
-import jax
-import wandb
-from bigbird_flax import Args, DataCollator, FlaxBigBirdForNaturalQuestions, Trainer, build_tx, train_step, val_step
-from datasets import load_dataset
-from flax import jax_utils
-
-from transformers import BigBirdTokenizerFast
-
-
-if __name__ == "__main__":
-    print("#################### AVAILABLE DEVICES ####################")
-    print(jax.devices())
-    print("###########################################################")
-
-    # setup for wandb sweep
-    args = Args()
-    logger = wandb.init(project="bigbird-natural-questions", config=args.__dict__)
-    wandb_args = dict(logger.config)
-    del wandb_args["batch_size"]
-    args = replace(args, **wandb_args)
-    base_dir = args.base_dir + "-" + wandb.run.id
-    args = replace(args, base_dir=base_dir)
-    print(args)
-
-    tr_dataset = load_dataset("json", data_files=args.tr_data_path)["train"]
-    val_dataset = load_dataset("json", data_files=args.val_data_path)["train"]
-
-    # drop extra batch for now
-    indices = range(len(tr_dataset) - len(tr_dataset) % args.batch_size)
-    tr_dataset = tr_dataset.shuffle().select(indices)
-    indices = range(len(val_dataset) - len(val_dataset) % args.batch_size)
-    val_dataset = val_dataset.shuffle().select(indices)
-
-    if os.environ.get("TRAIN_ON_SMALL", "false") == "true":
-        tr_dataset = tr_dataset.shuffle().select(range(80000))
-        val_dataset = val_dataset.shuffle().select(range(8000))
-
-    print(tr_dataset)
-    print(val_dataset)
-
-    model = FlaxBigBirdForNaturalQuestions.from_pretrained(
-        args.model_id, block_size=args.block_size, num_random_blocks=args.num_random_blocks
-    )
-    tokenizer = BigBirdTokenizerFast.from_pretrained(args.model_id)
-    data_collator = DataCollator(pad_id=tokenizer.pad_token_id, max_length=4096)
-
-    tx_args = {
-        "lr": args.lr,
-        "init_lr": args.init_lr,
-        "warmup_steps": args.warmup_steps,
-        "num_train_steps": args.max_epochs * (len(tr_dataset) // args.batch_size),
-        "weight_decay": args.weight_decay,
-    }
-    tx, lr = build_tx(**tx_args)
-
-    trainer = Trainer(
-        args=args,
-        data_collator=data_collator,
-        model_save_fn=model.save_pretrained,
-        train_step_fn=train_step,
-        val_step_fn=val_step,
-        logger=logger,
-        scheduler_fn=lr,
-    )
-
-    ckpt_dir = None
-    state = trainer.create_state(model, tx, num_train_steps=tx_args["num_train_steps"], ckpt_dir=ckpt_dir)
-    try:
-        trainer.train(state, tr_dataset, val_dataset)
-    except KeyboardInterrupt:
-        print("Oooops; TRAINING STOPPED UNFORTUNATELY")
-
-    print("SAVING WEIGHTS IN `final-weights`")
-    params = jax_utils.unreplicate(state.params)
-    model.save_pretrained(os.path.join(args.base_dir, "final-weights"), params=params)
diff --git a/spaces/chendl/compositional_test/transformers/src/transformers/models/albert/configuration_albert.py b/spaces/chendl/compositional_test/transformers/src/transformers/models/albert/configuration_albert.py
deleted file mode 100644
index fd0c623887925790b8c84cf92b86234f8ebf8c49..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/transformers/src/transformers/models/albert/configuration_albert.py
+++ /dev/null
@@ -1,172 +0,0 @@
-# coding=utf-8
-# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
-# Copyright (c) 2018, NVIDIA CORPORATION.  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.
-""" ALBERT model configuration"""
-from collections import OrderedDict
-from typing import Mapping
-
-from ...configuration_utils import PretrainedConfig
-from ...onnx import OnnxConfig
-
-
-ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
-    "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/config.json",
-    "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/config.json",
-    "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json",
-    "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/config.json",
-    "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/config.json",
-    "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/config.json",
-    "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json",
-}
-
-
-class AlbertConfig(PretrainedConfig):
-    r"""
-    This is the configuration class to store the configuration of a [`AlbertModel`] or a [`TFAlbertModel`]. It is used
-    to instantiate an ALBERT model according to the specified arguments, defining the model architecture. Instantiating
-    a configuration with the defaults will yield a similar configuration to that of the ALBERT
-    [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2) architecture.
-
-    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
-    documentation from [`PretrainedConfig`] for more information.
-
-    Args:
-        vocab_size (`int`, *optional*, defaults to 30000):
-            Vocabulary size of the ALBERT model. Defines the number of different tokens that can be represented by the
-            `inputs_ids` passed when calling [`AlbertModel`] or [`TFAlbertModel`].
-        embedding_size (`int`, *optional*, defaults to 128):
-            Dimensionality of vocabulary embeddings.
-        hidden_size (`int`, *optional*, defaults to 4096):
-            Dimensionality of the encoder layers and the pooler layer.
-        num_hidden_layers (`int`, *optional*, defaults to 12):
-            Number of hidden layers in the Transformer encoder.
-        num_hidden_groups (`int`, *optional*, defaults to 1):
-            Number of groups for the hidden layers, parameters in the same group are shared.
-        num_attention_heads (`int`, *optional*, defaults to 64):
-            Number of attention heads for each attention layer in the Transformer encoder.
-        intermediate_size (`int`, *optional*, defaults to 16384):
-            The dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
-        inner_group_num (`int`, *optional*, defaults to 1):
-            The number of inner repetition of attention and ffn.
-        hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu_new"`):
-            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
-            `"relu"`, `"silu"` and `"gelu_new"` are supported.
-        hidden_dropout_prob (`float`, *optional*, defaults to 0):
-            The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
-        attention_probs_dropout_prob (`float`, *optional*, defaults to 0):
-            The dropout ratio for the attention probabilities.
-        max_position_embeddings (`int`, *optional*, defaults to 512):
-            The maximum sequence length that this model might ever be used with. Typically set this to something large
-            (e.g., 512 or 1024 or 2048).
-        type_vocab_size (`int`, *optional*, defaults to 2):
-            The vocabulary size of the `token_type_ids` passed when calling [`AlbertModel`] or [`TFAlbertModel`].
-        initializer_range (`float`, *optional*, defaults to 0.02):
-            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
-        layer_norm_eps (`float`, *optional*, defaults to 1e-12):
-            The epsilon used by the layer normalization layers.
-        classifier_dropout_prob (`float`, *optional*, defaults to 0.1):
-            The dropout ratio for attached classifiers.
-        position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
-            Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For
-            positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to
-            [Self-Attention with Relative Position Representations (Shaw et al.)](https://arxiv.org/abs/1803.02155).
-            For more information on `"relative_key_query"`, please refer to *Method 4* in [Improve Transformer Models
-            with Better Relative Position Embeddings (Huang et al.)](https://arxiv.org/abs/2009.13658).
-
-    Examples:
-
-    ```python
-    >>> from transformers import AlbertConfig, AlbertModel
-
-    >>> # Initializing an ALBERT-xxlarge style configuration
-    >>> albert_xxlarge_configuration = AlbertConfig()
-
-    >>> # Initializing an ALBERT-base style configuration
-    >>> albert_base_configuration = AlbertConfig(
-    ...     hidden_size=768,
-    ...     num_attention_heads=12,
-    ...     intermediate_size=3072,
-    ... )
-
-    >>> # Initializing a model (with random weights) from the ALBERT-base style configuration
-    >>> model = AlbertModel(albert_xxlarge_configuration)
-
-    >>> # Accessing the model configuration
-    >>> configuration = model.config
-    ```"""
-
-    model_type = "albert"
-
-    def __init__(
-        self,
-        vocab_size=30000,
-        embedding_size=128,
-        hidden_size=4096,
-        num_hidden_layers=12,
-        num_hidden_groups=1,
-        num_attention_heads=64,
-        intermediate_size=16384,
-        inner_group_num=1,
-        hidden_act="gelu_new",
-        hidden_dropout_prob=0,
-        attention_probs_dropout_prob=0,
-        max_position_embeddings=512,
-        type_vocab_size=2,
-        initializer_range=0.02,
-        layer_norm_eps=1e-12,
-        classifier_dropout_prob=0.1,
-        position_embedding_type="absolute",
-        pad_token_id=0,
-        bos_token_id=2,
-        eos_token_id=3,
-        **kwargs,
-    ):
-        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
-
-        self.vocab_size = vocab_size
-        self.embedding_size = embedding_size
-        self.hidden_size = hidden_size
-        self.num_hidden_layers = num_hidden_layers
-        self.num_hidden_groups = num_hidden_groups
-        self.num_attention_heads = num_attention_heads
-        self.inner_group_num = inner_group_num
-        self.hidden_act = hidden_act
-        self.intermediate_size = intermediate_size
-        self.hidden_dropout_prob = hidden_dropout_prob
-        self.attention_probs_dropout_prob = attention_probs_dropout_prob
-        self.max_position_embeddings = max_position_embeddings
-        self.type_vocab_size = type_vocab_size
-        self.initializer_range = initializer_range
-        self.layer_norm_eps = layer_norm_eps
-        self.classifier_dropout_prob = classifier_dropout_prob
-        self.position_embedding_type = position_embedding_type
-
-
-# Copied from transformers.models.bert.configuration_bert.BertOnnxConfig with Roberta->Albert
-class AlbertOnnxConfig(OnnxConfig):
-    @property
-    def inputs(self) -> Mapping[str, Mapping[int, str]]:
-        if self.task == "multiple-choice":
-            dynamic_axis = {0: "batch", 1: "choice", 2: "sequence"}
-        else:
-            dynamic_axis = {0: "batch", 1: "sequence"}
-        return OrderedDict(
-            [
-                ("input_ids", dynamic_axis),
-                ("attention_mask", dynamic_axis),
-                ("token_type_ids", dynamic_axis),
-            ]
-        )
diff --git a/spaces/chilge/Fushimi/data_utils.py b/spaces/chilge/Fushimi/data_utils.py
deleted file mode 100644
index 9dfba4a9dfbfbd2b6ed5e771a5ffee4f70419ba3..0000000000000000000000000000000000000000
--- a/spaces/chilge/Fushimi/data_utils.py
+++ /dev/null
@@ -1,152 +0,0 @@
-import time
-import os
-import random
-import numpy as np
-import torch
-import torch.utils.data
-
-import commons
-from mel_processing import spectrogram_torch, spec_to_mel_torch
-from utils import load_wav_to_torch, load_filepaths_and_text, transform
-
-# import h5py
-
-
-"""Multi speaker version"""
-
-
-class TextAudioSpeakerLoader(torch.utils.data.Dataset):
-    """
-        1) loads audio, speaker_id, text pairs
-        2) normalizes text and converts them to sequences of integers
-        3) computes spectrograms from audio files.
-    """
-
-    def __init__(self, audiopaths, hparams):
-        self.audiopaths = load_filepaths_and_text(audiopaths)
-        self.max_wav_value = hparams.data.max_wav_value
-        self.sampling_rate = hparams.data.sampling_rate
-        self.filter_length = hparams.data.filter_length
-        self.hop_length = hparams.data.hop_length
-        self.win_length = hparams.data.win_length
-        self.sampling_rate = hparams.data.sampling_rate
-        self.use_sr = hparams.train.use_sr
-        self.spec_len = hparams.train.max_speclen
-        self.spk_map = hparams.spk
-
-        random.seed(1234)
-        random.shuffle(self.audiopaths)
-
-    def get_audio(self, filename):
-        audio, sampling_rate = load_wav_to_torch(filename)
-        if sampling_rate != self.sampling_rate:
-            raise ValueError("{} SR doesn't match target {} SR".format(
-                sampling_rate, self.sampling_rate))
-        audio_norm = audio / self.max_wav_value
-        audio_norm = audio_norm.unsqueeze(0)
-        spec_filename = filename.replace(".wav", ".spec.pt")
-        if os.path.exists(spec_filename):
-            spec = torch.load(spec_filename)
-        else:
-            spec = spectrogram_torch(audio_norm, self.filter_length,
-                                     self.sampling_rate, self.hop_length, self.win_length,
-                                     center=False)
-            spec = torch.squeeze(spec, 0)
-            torch.save(spec, spec_filename)
-
-        spk = filename.split(os.sep)[-2]
-        spk = torch.LongTensor([self.spk_map[spk]])
-
-        c = torch.load(filename + ".soft.pt").squeeze(0)
-        c = torch.repeat_interleave(c, repeats=2, dim=1)
-
-        f0 = np.load(filename + ".f0.npy")
-        f0 = torch.FloatTensor(f0)
-        lmin = min(c.size(-1), spec.size(-1), f0.shape[0])
-        assert abs(c.size(-1) - spec.size(-1)) < 4, (c.size(-1), spec.size(-1), f0.shape, filename)
-        assert abs(lmin - spec.size(-1)) < 4, (c.size(-1), spec.size(-1), f0.shape)
-        assert abs(lmin - c.size(-1)) < 4, (c.size(-1), spec.size(-1), f0.shape)
-        spec, c, f0 = spec[:, :lmin], c[:, :lmin], f0[:lmin]
-        audio_norm = audio_norm[:, :lmin * self.hop_length]
-        _spec, _c, _audio_norm, _f0 = spec, c, audio_norm, f0
-        while spec.size(-1) < self.spec_len:
-            spec = torch.cat((spec, _spec), -1)
-            c = torch.cat((c, _c), -1)
-            f0 = torch.cat((f0, _f0), -1)
-            audio_norm = torch.cat((audio_norm, _audio_norm), -1)
-        start = random.randint(0, spec.size(-1) - self.spec_len)
-        end = start + self.spec_len
-        spec = spec[:, start:end]
-        c = c[:, start:end]
-        f0 = f0[start:end]
-        audio_norm = audio_norm[:, start * self.hop_length:end * self.hop_length]
-
-        return c, f0, spec, audio_norm, spk
-
-    def __getitem__(self, index):
-        return self.get_audio(self.audiopaths[index][0])
-
-    def __len__(self):
-        return len(self.audiopaths)
-
-
-class EvalDataLoader(torch.utils.data.Dataset):
-    """
-        1) loads audio, speaker_id, text pairs
-        2) normalizes text and converts them to sequences of integers
-        3) computes spectrograms from audio files.
-    """
-
-    def __init__(self, audiopaths, hparams):
-        self.audiopaths = load_filepaths_and_text(audiopaths)
-        self.max_wav_value = hparams.data.max_wav_value
-        self.sampling_rate = hparams.data.sampling_rate
-        self.filter_length = hparams.data.filter_length
-        self.hop_length = hparams.data.hop_length
-        self.win_length = hparams.data.win_length
-        self.sampling_rate = hparams.data.sampling_rate
-        self.use_sr = hparams.train.use_sr
-        self.audiopaths = self.audiopaths[:5]
-        self.spk_map = hparams.spk
-
-
-    def get_audio(self, filename):
-        audio, sampling_rate = load_wav_to_torch(filename)
-        if sampling_rate != self.sampling_rate:
-            raise ValueError("{} SR doesn't match target {} SR".format(
-                sampling_rate, self.sampling_rate))
-        audio_norm = audio / self.max_wav_value
-        audio_norm = audio_norm.unsqueeze(0)
-        spec_filename = filename.replace(".wav", ".spec.pt")
-        if os.path.exists(spec_filename):
-            spec = torch.load(spec_filename)
-        else:
-            spec = spectrogram_torch(audio_norm, self.filter_length,
-                                     self.sampling_rate, self.hop_length, self.win_length,
-                                     center=False)
-            spec = torch.squeeze(spec, 0)
-            torch.save(spec, spec_filename)
-
-        spk = filename.split(os.sep)[-2]
-        spk = torch.LongTensor([self.spk_map[spk]])
-
-        c = torch.load(filename + ".soft.pt").squeeze(0)
-
-        c = torch.repeat_interleave(c, repeats=2, dim=1)
-
-        f0 = np.load(filename + ".f0.npy")
-        f0 = torch.FloatTensor(f0)
-        lmin = min(c.size(-1), spec.size(-1), f0.shape[0])
-        assert abs(c.size(-1) - spec.size(-1)) < 4, (c.size(-1), spec.size(-1), f0.shape)
-        assert abs(f0.shape[0] - spec.shape[-1]) < 4, (c.size(-1), spec.size(-1), f0.shape)
-        spec, c, f0 = spec[:, :lmin], c[:, :lmin], f0[:lmin]
-        audio_norm = audio_norm[:, :lmin * self.hop_length]
-
-        return c, f0, spec, audio_norm, spk
-
-    def __getitem__(self, index):
-        return self.get_audio(self.audiopaths[index][0])
-
-    def __len__(self):
-        return len(self.audiopaths)
-
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/chardet/metadata/__init__.py b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/chardet/metadata/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/google/protobuf/json_format.py b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/google/protobuf/json_format.py
deleted file mode 100644
index a04e8aef13318d594548967394782074c821532e..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/google/protobuf/json_format.py
+++ /dev/null
@@ -1,929 +0,0 @@
-# Protocol Buffers - Google's data interchange format
-# Copyright 2008 Google Inc.  All rights reserved.
-# https://developers.google.com/protocol-buffers/
-#
-# 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 Google Inc. 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
-# OWNER 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.
-
-"""Contains routines for printing protocol messages in JSON format.
-
-Simple usage example:
-
-  # Create a proto object and serialize it to a json format string.
-  message = my_proto_pb2.MyMessage(foo='bar')
-  json_string = json_format.MessageToJson(message)
-
-  # Parse a json format string to proto object.
-  message = json_format.Parse(json_string, my_proto_pb2.MyMessage())
-"""
-
-__author__ = 'jieluo@google.com (Jie Luo)'
-
-
-import base64
-from collections import OrderedDict
-import json
-import math
-from operator import methodcaller
-import re
-import sys
-
-from google.protobuf.internal import type_checkers
-from google.protobuf import descriptor
-from google.protobuf import message_factory
-from google.protobuf import symbol_database
-
-
-_TIMESTAMPFOMAT = '%Y-%m-%dT%H:%M:%S'
-_INT_TYPES = frozenset([descriptor.FieldDescriptor.CPPTYPE_INT32,
-                        descriptor.FieldDescriptor.CPPTYPE_UINT32,
-                        descriptor.FieldDescriptor.CPPTYPE_INT64,
-                        descriptor.FieldDescriptor.CPPTYPE_UINT64])
-_INT64_TYPES = frozenset([descriptor.FieldDescriptor.CPPTYPE_INT64,
-                          descriptor.FieldDescriptor.CPPTYPE_UINT64])
-_FLOAT_TYPES = frozenset([descriptor.FieldDescriptor.CPPTYPE_FLOAT,
-                          descriptor.FieldDescriptor.CPPTYPE_DOUBLE])
-_INFINITY = 'Infinity'
-_NEG_INFINITY = '-Infinity'
-_NAN = 'NaN'
-
-_UNPAIRED_SURROGATE_PATTERN = re.compile(
-    u'[\ud800-\udbff](?![\udc00-\udfff])|(?<![\ud800-\udbff])[\udc00-\udfff]')
-
-_VALID_EXTENSION_NAME = re.compile(r'\[[a-zA-Z0-9\._]*\]$')
-
-
-class Error(Exception):
-  """Top-level module error for json_format."""
-
-
-class SerializeToJsonError(Error):
-  """Thrown if serialization to JSON fails."""
-
-
-class ParseError(Error):
-  """Thrown in case of parsing error."""
-
-
-def MessageToJson(
-    message,
-    including_default_value_fields=False,
-    preserving_proto_field_name=False,
-    indent=2,
-    sort_keys=False,
-    use_integers_for_enums=False,
-    descriptor_pool=None,
-    float_precision=None,
-    ensure_ascii=True):
-  """Converts protobuf message to JSON format.
-
-  Args:
-    message: The protocol buffers message instance to serialize.
-    including_default_value_fields: If True, singular primitive fields,
-        repeated fields, and map fields will always be serialized.  If
-        False, only serialize non-empty fields.  Singular message fields
-        and oneof fields are not affected by this option.
-    preserving_proto_field_name: If True, use the original proto field
-        names as defined in the .proto file. If False, convert the field
-        names to lowerCamelCase.
-    indent: The JSON object will be pretty-printed with this indent level.
-        An indent level of 0 or negative will only insert newlines. If the
-        indent level is None, no newlines will be inserted.
-    sort_keys: If True, then the output will be sorted by field names.
-    use_integers_for_enums: If true, print integers instead of enum names.
-    descriptor_pool: A Descriptor Pool for resolving types. If None use the
-        default.
-    float_precision: If set, use this to specify float field valid digits.
-    ensure_ascii: If True, strings with non-ASCII characters are escaped.
-        If False, Unicode strings are returned unchanged.
-
-  Returns:
-    A string containing the JSON formatted protocol buffer message.
-  """
-  printer = _Printer(
-      including_default_value_fields,
-      preserving_proto_field_name,
-      use_integers_for_enums,
-      descriptor_pool,
-      float_precision=float_precision)
-  return printer.ToJsonString(message, indent, sort_keys, ensure_ascii)
-
-
-def MessageToDict(
-    message,
-    including_default_value_fields=False,
-    preserving_proto_field_name=False,
-    use_integers_for_enums=False,
-    descriptor_pool=None,
-    float_precision=None):
-  """Converts protobuf message to a dictionary.
-
-  When the dictionary is encoded to JSON, it conforms to proto3 JSON spec.
-
-  Args:
-    message: The protocol buffers message instance to serialize.
-    including_default_value_fields: If True, singular primitive fields,
-        repeated fields, and map fields will always be serialized.  If
-        False, only serialize non-empty fields.  Singular message fields
-        and oneof fields are not affected by this option.
-    preserving_proto_field_name: If True, use the original proto field
-        names as defined in the .proto file. If False, convert the field
-        names to lowerCamelCase.
-    use_integers_for_enums: If true, print integers instead of enum names.
-    descriptor_pool: A Descriptor Pool for resolving types. If None use the
-        default.
-    float_precision: If set, use this to specify float field valid digits.
-
-  Returns:
-    A dict representation of the protocol buffer message.
-  """
-  printer = _Printer(
-      including_default_value_fields,
-      preserving_proto_field_name,
-      use_integers_for_enums,
-      descriptor_pool,
-      float_precision=float_precision)
-  # pylint: disable=protected-access
-  return printer._MessageToJsonObject(message)
-
-
-def _IsMapEntry(field):
-  return (field.type == descriptor.FieldDescriptor.TYPE_MESSAGE and
-          field.message_type.has_options and
-          field.message_type.GetOptions().map_entry)
-
-
-class _Printer(object):
-  """JSON format printer for protocol message."""
-
-  def __init__(
-      self,
-      including_default_value_fields=False,
-      preserving_proto_field_name=False,
-      use_integers_for_enums=False,
-      descriptor_pool=None,
-      float_precision=None):
-    self.including_default_value_fields = including_default_value_fields
-    self.preserving_proto_field_name = preserving_proto_field_name
-    self.use_integers_for_enums = use_integers_for_enums
-    self.descriptor_pool = descriptor_pool
-    if float_precision:
-      self.float_format = '.{}g'.format(float_precision)
-    else:
-      self.float_format = None
-
-  def ToJsonString(self, message, indent, sort_keys, ensure_ascii):
-    js = self._MessageToJsonObject(message)
-    return json.dumps(
-        js, indent=indent, sort_keys=sort_keys, ensure_ascii=ensure_ascii)
-
-  def _MessageToJsonObject(self, message):
-    """Converts message to an object according to Proto3 JSON Specification."""
-    message_descriptor = message.DESCRIPTOR
-    full_name = message_descriptor.full_name
-    if _IsWrapperMessage(message_descriptor):
-      return self._WrapperMessageToJsonObject(message)
-    if full_name in _WKTJSONMETHODS:
-      return methodcaller(_WKTJSONMETHODS[full_name][0], message)(self)
-    js = {}
-    return self._RegularMessageToJsonObject(message, js)
-
-  def _RegularMessageToJsonObject(self, message, js):
-    """Converts normal message according to Proto3 JSON Specification."""
-    fields = message.ListFields()
-
-    try:
-      for field, value in fields:
-        if self.preserving_proto_field_name:
-          name = field.name
-        else:
-          name = field.json_name
-        if _IsMapEntry(field):
-          # Convert a map field.
-          v_field = field.message_type.fields_by_name['value']
-          js_map = {}
-          for key in value:
-            if isinstance(key, bool):
-              if key:
-                recorded_key = 'true'
-              else:
-                recorded_key = 'false'
-            else:
-              recorded_key = str(key)
-            js_map[recorded_key] = self._FieldToJsonObject(
-                v_field, value[key])
-          js[name] = js_map
-        elif field.label == descriptor.FieldDescriptor.LABEL_REPEATED:
-          # Convert a repeated field.
-          js[name] = [self._FieldToJsonObject(field, k)
-                      for k in value]
-        elif field.is_extension:
-          name = '[%s]' % field.full_name
-          js[name] = self._FieldToJsonObject(field, value)
-        else:
-          js[name] = self._FieldToJsonObject(field, value)
-
-      # Serialize default value if including_default_value_fields is True.
-      if self.including_default_value_fields:
-        message_descriptor = message.DESCRIPTOR
-        for field in message_descriptor.fields:
-          # Singular message fields and oneof fields will not be affected.
-          if ((field.label != descriptor.FieldDescriptor.LABEL_REPEATED and
-               field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE) or
-              field.containing_oneof):
-            continue
-          if self.preserving_proto_field_name:
-            name = field.name
-          else:
-            name = field.json_name
-          if name in js:
-            # Skip the field which has been serialized already.
-            continue
-          if _IsMapEntry(field):
-            js[name] = {}
-          elif field.label == descriptor.FieldDescriptor.LABEL_REPEATED:
-            js[name] = []
-          else:
-            js[name] = self._FieldToJsonObject(field, field.default_value)
-
-    except ValueError as e:
-      raise SerializeToJsonError(
-          'Failed to serialize {0} field: {1}.'.format(field.name, e)) from e
-
-    return js
-
-  def _FieldToJsonObject(self, field, value):
-    """Converts field value according to Proto3 JSON Specification."""
-    if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
-      return self._MessageToJsonObject(value)
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_ENUM:
-      if self.use_integers_for_enums:
-        return value
-      if field.enum_type.full_name == 'google.protobuf.NullValue':
-        return None
-      enum_value = field.enum_type.values_by_number.get(value, None)
-      if enum_value is not None:
-        return enum_value.name
-      else:
-        if field.enum_type.is_closed:
-          raise SerializeToJsonError('Enum field contains an integer value '
-                                     'which can not mapped to an enum value.')
-        else:
-          return value
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_STRING:
-      if field.type == descriptor.FieldDescriptor.TYPE_BYTES:
-        # Use base64 Data encoding for bytes
-        return base64.b64encode(value).decode('utf-8')
-      else:
-        return value
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_BOOL:
-      return bool(value)
-    elif field.cpp_type in _INT64_TYPES:
-      return str(value)
-    elif field.cpp_type in _FLOAT_TYPES:
-      if math.isinf(value):
-        if value < 0.0:
-          return _NEG_INFINITY
-        else:
-          return _INFINITY
-      if math.isnan(value):
-        return _NAN
-      if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_FLOAT:
-        if self.float_format:
-          return float(format(value, self.float_format))
-        else:
-          return type_checkers.ToShortestFloat(value)
-
-    return value
-
-  def _AnyMessageToJsonObject(self, message):
-    """Converts Any message according to Proto3 JSON Specification."""
-    if not message.ListFields():
-      return {}
-    # Must print @type first, use OrderedDict instead of {}
-    js = OrderedDict()
-    type_url = message.type_url
-    js['@type'] = type_url
-    sub_message = _CreateMessageFromTypeUrl(type_url, self.descriptor_pool)
-    sub_message.ParseFromString(message.value)
-    message_descriptor = sub_message.DESCRIPTOR
-    full_name = message_descriptor.full_name
-    if _IsWrapperMessage(message_descriptor):
-      js['value'] = self._WrapperMessageToJsonObject(sub_message)
-      return js
-    if full_name in _WKTJSONMETHODS:
-      js['value'] = methodcaller(_WKTJSONMETHODS[full_name][0],
-                                 sub_message)(self)
-      return js
-    return self._RegularMessageToJsonObject(sub_message, js)
-
-  def _GenericMessageToJsonObject(self, message):
-    """Converts message according to Proto3 JSON Specification."""
-    # Duration, Timestamp and FieldMask have ToJsonString method to do the
-    # convert. Users can also call the method directly.
-    return message.ToJsonString()
-
-  def _ValueMessageToJsonObject(self, message):
-    """Converts Value message according to Proto3 JSON Specification."""
-    which = message.WhichOneof('kind')
-    # If the Value message is not set treat as null_value when serialize
-    # to JSON. The parse back result will be different from original message.
-    if which is None or which == 'null_value':
-      return None
-    if which == 'list_value':
-      return self._ListValueMessageToJsonObject(message.list_value)
-    if which == 'number_value':
-      value = message.number_value
-      if math.isinf(value):
-        raise ValueError('Fail to serialize Infinity for Value.number_value, '
-                         'which would parse as string_value')
-      if math.isnan(value):
-        raise ValueError('Fail to serialize NaN for Value.number_value, '
-                         'which would parse as string_value')
-    else:
-      value = getattr(message, which)
-    oneof_descriptor = message.DESCRIPTOR.fields_by_name[which]
-    return self._FieldToJsonObject(oneof_descriptor, value)
-
-  def _ListValueMessageToJsonObject(self, message):
-    """Converts ListValue message according to Proto3 JSON Specification."""
-    return [self._ValueMessageToJsonObject(value)
-            for value in message.values]
-
-  def _StructMessageToJsonObject(self, message):
-    """Converts Struct message according to Proto3 JSON Specification."""
-    fields = message.fields
-    ret = {}
-    for key in fields:
-      ret[key] = self._ValueMessageToJsonObject(fields[key])
-    return ret
-
-  def _WrapperMessageToJsonObject(self, message):
-    return self._FieldToJsonObject(
-        message.DESCRIPTOR.fields_by_name['value'], message.value)
-
-
-def _IsWrapperMessage(message_descriptor):
-  return message_descriptor.file.name == 'google/protobuf/wrappers.proto'
-
-
-def _DuplicateChecker(js):
-  result = {}
-  for name, value in js:
-    if name in result:
-      raise ParseError('Failed to load JSON: duplicate key {0}.'.format(name))
-    result[name] = value
-  return result
-
-
-def _CreateMessageFromTypeUrl(type_url, descriptor_pool):
-  """Creates a message from a type URL."""
-  db = symbol_database.Default()
-  pool = db.pool if descriptor_pool is None else descriptor_pool
-  type_name = type_url.split('/')[-1]
-  try:
-    message_descriptor = pool.FindMessageTypeByName(type_name)
-  except KeyError as e:
-    raise TypeError(
-        'Can not find message descriptor by type_url: {0}'.format(type_url)
-      ) from e
-  message_class = message_factory.GetMessageClass(message_descriptor)
-  return message_class()
-
-
-def Parse(text,
-          message,
-          ignore_unknown_fields=False,
-          descriptor_pool=None,
-          max_recursion_depth=100):
-  """Parses a JSON representation of a protocol message into a message.
-
-  Args:
-    text: Message JSON representation.
-    message: A protocol buffer message to merge into.
-    ignore_unknown_fields: If True, do not raise errors for unknown fields.
-    descriptor_pool: A Descriptor Pool for resolving types. If None use the
-      default.
-    max_recursion_depth: max recursion depth of JSON message to be
-      deserialized. JSON messages over this depth will fail to be
-      deserialized. Default value is 100.
-
-  Returns:
-    The same message passed as argument.
-
-  Raises::
-    ParseError: On JSON parsing problems.
-  """
-  if not isinstance(text, str):
-    text = text.decode('utf-8')
-  try:
-    js = json.loads(text, object_pairs_hook=_DuplicateChecker)
-  except ValueError as e:
-    raise ParseError('Failed to load JSON: {0}.'.format(str(e))) from e
-  return ParseDict(js, message, ignore_unknown_fields, descriptor_pool,
-                   max_recursion_depth)
-
-
-def ParseDict(js_dict,
-              message,
-              ignore_unknown_fields=False,
-              descriptor_pool=None,
-              max_recursion_depth=100):
-  """Parses a JSON dictionary representation into a message.
-
-  Args:
-    js_dict: Dict representation of a JSON message.
-    message: A protocol buffer message to merge into.
-    ignore_unknown_fields: If True, do not raise errors for unknown fields.
-    descriptor_pool: A Descriptor Pool for resolving types. If None use the
-      default.
-    max_recursion_depth: max recursion depth of JSON message to be
-      deserialized. JSON messages over this depth will fail to be
-      deserialized. Default value is 100.
-
-  Returns:
-    The same message passed as argument.
-  """
-  parser = _Parser(ignore_unknown_fields, descriptor_pool, max_recursion_depth)
-  parser.ConvertMessage(js_dict, message, '')
-  return message
-
-
-_INT_OR_FLOAT = (int, float)
-
-
-class _Parser(object):
-  """JSON format parser for protocol message."""
-
-  def __init__(self, ignore_unknown_fields, descriptor_pool,
-               max_recursion_depth):
-    self.ignore_unknown_fields = ignore_unknown_fields
-    self.descriptor_pool = descriptor_pool
-    self.max_recursion_depth = max_recursion_depth
-    self.recursion_depth = 0
-
-  def ConvertMessage(self, value, message, path):
-    """Convert a JSON object into a message.
-
-    Args:
-      value: A JSON object.
-      message: A WKT or regular protocol message to record the data.
-      path: parent path to log parse error info.
-
-    Raises:
-      ParseError: In case of convert problems.
-    """
-    self.recursion_depth += 1
-    if self.recursion_depth > self.max_recursion_depth:
-      raise ParseError('Message too deep. Max recursion depth is {0}'.format(
-          self.max_recursion_depth))
-    message_descriptor = message.DESCRIPTOR
-    full_name = message_descriptor.full_name
-    if not path:
-      path = message_descriptor.name
-    if _IsWrapperMessage(message_descriptor):
-      self._ConvertWrapperMessage(value, message, path)
-    elif full_name in _WKTJSONMETHODS:
-      methodcaller(_WKTJSONMETHODS[full_name][1], value, message, path)(self)
-    else:
-      self._ConvertFieldValuePair(value, message, path)
-    self.recursion_depth -= 1
-
-  def _ConvertFieldValuePair(self, js, message, path):
-    """Convert field value pairs into regular message.
-
-    Args:
-      js: A JSON object to convert the field value pairs.
-      message: A regular protocol message to record the data.
-      path: parent path to log parse error info.
-
-    Raises:
-      ParseError: In case of problems converting.
-    """
-    names = []
-    message_descriptor = message.DESCRIPTOR
-    fields_by_json_name = dict((f.json_name, f)
-                               for f in message_descriptor.fields)
-    for name in js:
-      try:
-        field = fields_by_json_name.get(name, None)
-        if not field:
-          field = message_descriptor.fields_by_name.get(name, None)
-        if not field and _VALID_EXTENSION_NAME.match(name):
-          if not message_descriptor.is_extendable:
-            raise ParseError(
-                'Message type {0} does not have extensions at {1}'.format(
-                    message_descriptor.full_name, path))
-          identifier = name[1:-1]  # strip [] brackets
-          # pylint: disable=protected-access
-          field = message.Extensions._FindExtensionByName(identifier)
-          # pylint: enable=protected-access
-          if not field:
-            # Try looking for extension by the message type name, dropping the
-            # field name following the final . separator in full_name.
-            identifier = '.'.join(identifier.split('.')[:-1])
-            # pylint: disable=protected-access
-            field = message.Extensions._FindExtensionByName(identifier)
-            # pylint: enable=protected-access
-        if not field:
-          if self.ignore_unknown_fields:
-            continue
-          raise ParseError(
-              ('Message type "{0}" has no field named "{1}" at "{2}".\n'
-               ' Available Fields(except extensions): "{3}"').format(
-                   message_descriptor.full_name, name, path,
-                   [f.json_name for f in message_descriptor.fields]))
-        if name in names:
-          raise ParseError('Message type "{0}" should not have multiple '
-                           '"{1}" fields at "{2}".'.format(
-                               message.DESCRIPTOR.full_name, name, path))
-        names.append(name)
-        value = js[name]
-        # Check no other oneof field is parsed.
-        if field.containing_oneof is not None and value is not None:
-          oneof_name = field.containing_oneof.name
-          if oneof_name in names:
-            raise ParseError('Message type "{0}" should not have multiple '
-                             '"{1}" oneof fields at "{2}".'.format(
-                                 message.DESCRIPTOR.full_name, oneof_name,
-                                 path))
-          names.append(oneof_name)
-
-        if value is None:
-          if (field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE
-              and field.message_type.full_name == 'google.protobuf.Value'):
-            sub_message = getattr(message, field.name)
-            sub_message.null_value = 0
-          elif (field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_ENUM
-                and field.enum_type.full_name == 'google.protobuf.NullValue'):
-            setattr(message, field.name, 0)
-          else:
-            message.ClearField(field.name)
-          continue
-
-        # Parse field value.
-        if _IsMapEntry(field):
-          message.ClearField(field.name)
-          self._ConvertMapFieldValue(value, message, field,
-                                     '{0}.{1}'.format(path, name))
-        elif field.label == descriptor.FieldDescriptor.LABEL_REPEATED:
-          message.ClearField(field.name)
-          if not isinstance(value, list):
-            raise ParseError('repeated field {0} must be in [] which is '
-                             '{1} at {2}'.format(name, value, path))
-          if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
-            # Repeated message field.
-            for index, item in enumerate(value):
-              sub_message = getattr(message, field.name).add()
-              # None is a null_value in Value.
-              if (item is None and
-                  sub_message.DESCRIPTOR.full_name != 'google.protobuf.Value'):
-                raise ParseError('null is not allowed to be used as an element'
-                                 ' in a repeated field at {0}.{1}[{2}]'.format(
-                                     path, name, index))
-              self.ConvertMessage(item, sub_message,
-                                  '{0}.{1}[{2}]'.format(path, name, index))
-          else:
-            # Repeated scalar field.
-            for index, item in enumerate(value):
-              if item is None:
-                raise ParseError('null is not allowed to be used as an element'
-                                 ' in a repeated field at {0}.{1}[{2}]'.format(
-                                     path, name, index))
-              getattr(message, field.name).append(
-                  _ConvertScalarFieldValue(
-                      item, field, '{0}.{1}[{2}]'.format(path, name, index)))
-        elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
-          if field.is_extension:
-            sub_message = message.Extensions[field]
-          else:
-            sub_message = getattr(message, field.name)
-          sub_message.SetInParent()
-          self.ConvertMessage(value, sub_message, '{0}.{1}'.format(path, name))
-        else:
-          if field.is_extension:
-            message.Extensions[field] = _ConvertScalarFieldValue(
-                value, field, '{0}.{1}'.format(path, name))
-          else:
-            setattr(
-                message, field.name,
-                _ConvertScalarFieldValue(value, field,
-                                         '{0}.{1}'.format(path, name)))
-      except ParseError as e:
-        if field and field.containing_oneof is None:
-          raise ParseError(
-            'Failed to parse {0} field: {1}.'.format(name, e)
-          ) from e
-        else:
-          raise ParseError(str(e)) from e
-      except ValueError as e:
-        raise ParseError(
-          'Failed to parse {0} field: {1}.'.format(name, e)
-        ) from e
-      except TypeError as e:
-        raise ParseError(
-          'Failed to parse {0} field: {1}.'.format(name, e)
-        ) from e
-
-  def _ConvertAnyMessage(self, value, message, path):
-    """Convert a JSON representation into Any message."""
-    if isinstance(value, dict) and not value:
-      return
-    try:
-      type_url = value['@type']
-    except KeyError as e:
-      raise ParseError(
-        '@type is missing when parsing any message at {0}'.format(path)
-      ) from e
-
-    try:
-      sub_message = _CreateMessageFromTypeUrl(type_url, self.descriptor_pool)
-    except TypeError as e:
-      raise ParseError('{0} at {1}'.format(e, path)) from e
-    message_descriptor = sub_message.DESCRIPTOR
-    full_name = message_descriptor.full_name
-    if _IsWrapperMessage(message_descriptor):
-      self._ConvertWrapperMessage(value['value'], sub_message,
-                                  '{0}.value'.format(path))
-    elif full_name in _WKTJSONMETHODS:
-      methodcaller(_WKTJSONMETHODS[full_name][1], value['value'], sub_message,
-                   '{0}.value'.format(path))(
-                       self)
-    else:
-      del value['@type']
-      self._ConvertFieldValuePair(value, sub_message, path)
-      value['@type'] = type_url
-    # Sets Any message
-    message.value = sub_message.SerializeToString()
-    message.type_url = type_url
-
-  def _ConvertGenericMessage(self, value, message, path):
-    """Convert a JSON representation into message with FromJsonString."""
-    # Duration, Timestamp, FieldMask have a FromJsonString method to do the
-    # conversion. Users can also call the method directly.
-    try:
-      message.FromJsonString(value)
-    except ValueError as e:
-      raise ParseError('{0} at {1}'.format(e, path)) from e
-
-  def _ConvertValueMessage(self, value, message, path):
-    """Convert a JSON representation into Value message."""
-    if isinstance(value, dict):
-      self._ConvertStructMessage(value, message.struct_value, path)
-    elif isinstance(value, list):
-      self._ConvertListValueMessage(value, message.list_value, path)
-    elif value is None:
-      message.null_value = 0
-    elif isinstance(value, bool):
-      message.bool_value = value
-    elif isinstance(value, str):
-      message.string_value = value
-    elif isinstance(value, _INT_OR_FLOAT):
-      message.number_value = value
-    else:
-      raise ParseError('Value {0} has unexpected type {1} at {2}'.format(
-          value, type(value), path))
-
-  def _ConvertListValueMessage(self, value, message, path):
-    """Convert a JSON representation into ListValue message."""
-    if not isinstance(value, list):
-      raise ParseError('ListValue must be in [] which is {0} at {1}'.format(
-          value, path))
-    message.ClearField('values')
-    for index, item in enumerate(value):
-      self._ConvertValueMessage(item, message.values.add(),
-                                '{0}[{1}]'.format(path, index))
-
-  def _ConvertStructMessage(self, value, message, path):
-    """Convert a JSON representation into Struct message."""
-    if not isinstance(value, dict):
-      raise ParseError('Struct must be in a dict which is {0} at {1}'.format(
-          value, path))
-    # Clear will mark the struct as modified so it will be created even if
-    # there are no values.
-    message.Clear()
-    for key in value:
-      self._ConvertValueMessage(value[key], message.fields[key],
-                                '{0}.{1}'.format(path, key))
-    return
-
-  def _ConvertWrapperMessage(self, value, message, path):
-    """Convert a JSON representation into Wrapper message."""
-    field = message.DESCRIPTOR.fields_by_name['value']
-    setattr(
-        message, 'value',
-        _ConvertScalarFieldValue(value, field, path='{0}.value'.format(path)))
-
-  def _ConvertMapFieldValue(self, value, message, field, path):
-    """Convert map field value for a message map field.
-
-    Args:
-      value: A JSON object to convert the map field value.
-      message: A protocol message to record the converted data.
-      field: The descriptor of the map field to be converted.
-      path: parent path to log parse error info.
-
-    Raises:
-      ParseError: In case of convert problems.
-    """
-    if not isinstance(value, dict):
-      raise ParseError(
-          'Map field {0} must be in a dict which is {1} at {2}'.format(
-              field.name, value, path))
-    key_field = field.message_type.fields_by_name['key']
-    value_field = field.message_type.fields_by_name['value']
-    for key in value:
-      key_value = _ConvertScalarFieldValue(key, key_field,
-                                           '{0}.key'.format(path), True)
-      if value_field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
-        self.ConvertMessage(value[key],
-                            getattr(message, field.name)[key_value],
-                            '{0}[{1}]'.format(path, key_value))
-      else:
-        getattr(message, field.name)[key_value] = _ConvertScalarFieldValue(
-            value[key], value_field, path='{0}[{1}]'.format(path, key_value))
-
-
-def _ConvertScalarFieldValue(value, field, path, require_str=False):
-  """Convert a single scalar field value.
-
-  Args:
-    value: A scalar value to convert the scalar field value.
-    field: The descriptor of the field to convert.
-    path: parent path to log parse error info.
-    require_str: If True, the field value must be a str.
-
-  Returns:
-    The converted scalar field value
-
-  Raises:
-    ParseError: In case of convert problems.
-  """
-  try:
-    if field.cpp_type in _INT_TYPES:
-      return _ConvertInteger(value)
-    elif field.cpp_type in _FLOAT_TYPES:
-      return _ConvertFloat(value, field)
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_BOOL:
-      return _ConvertBool(value, require_str)
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_STRING:
-      if field.type == descriptor.FieldDescriptor.TYPE_BYTES:
-        if isinstance(value, str):
-          encoded = value.encode('utf-8')
-        else:
-          encoded = value
-        # Add extra padding '='
-        padded_value = encoded + b'=' * (4 - len(encoded) % 4)
-        return base64.urlsafe_b64decode(padded_value)
-      else:
-        # Checking for unpaired surrogates appears to be unreliable,
-        # depending on the specific Python version, so we check manually.
-        if _UNPAIRED_SURROGATE_PATTERN.search(value):
-          raise ParseError('Unpaired surrogate')
-        return value
-    elif field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_ENUM:
-      # Convert an enum value.
-      enum_value = field.enum_type.values_by_name.get(value, None)
-      if enum_value is None:
-        try:
-          number = int(value)
-          enum_value = field.enum_type.values_by_number.get(number, None)
-        except ValueError as e:
-          raise ParseError('Invalid enum value {0} for enum type {1}'.format(
-              value, field.enum_type.full_name)) from e
-        if enum_value is None:
-          if field.enum_type.is_closed:
-            raise ParseError('Invalid enum value {0} for enum type {1}'.format(
-                value, field.enum_type.full_name))
-          else:
-            return number
-      return enum_value.number
-  except ParseError as e:
-    raise ParseError('{0} at {1}'.format(e, path)) from e
-
-
-def _ConvertInteger(value):
-  """Convert an integer.
-
-  Args:
-    value: A scalar value to convert.
-
-  Returns:
-    The integer value.
-
-  Raises:
-    ParseError: If an integer couldn't be consumed.
-  """
-  if isinstance(value, float) and not value.is_integer():
-    raise ParseError('Couldn\'t parse integer: {0}'.format(value))
-
-  if isinstance(value, str) and value.find(' ') != -1:
-    raise ParseError('Couldn\'t parse integer: "{0}"'.format(value))
-
-  if isinstance(value, bool):
-    raise ParseError('Bool value {0} is not acceptable for '
-                     'integer field'.format(value))
-
-  return int(value)
-
-
-def _ConvertFloat(value, field):
-  """Convert an floating point number."""
-  if isinstance(value, float):
-    if math.isnan(value):
-      raise ParseError('Couldn\'t parse NaN, use quoted "NaN" instead')
-    if math.isinf(value):
-      if value > 0:
-        raise ParseError('Couldn\'t parse Infinity or value too large, '
-                         'use quoted "Infinity" instead')
-      else:
-        raise ParseError('Couldn\'t parse -Infinity or value too small, '
-                         'use quoted "-Infinity" instead')
-    if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_FLOAT:
-      # pylint: disable=protected-access
-      if value > type_checkers._FLOAT_MAX:
-        raise ParseError('Float value too large')
-      # pylint: disable=protected-access
-      if value < type_checkers._FLOAT_MIN:
-        raise ParseError('Float value too small')
-  if value == 'nan':
-    raise ParseError('Couldn\'t parse float "nan", use "NaN" instead')
-  try:
-    # Assume Python compatible syntax.
-    return float(value)
-  except ValueError as e:
-    # Check alternative spellings.
-    if value == _NEG_INFINITY:
-      return float('-inf')
-    elif value == _INFINITY:
-      return float('inf')
-    elif value == _NAN:
-      return float('nan')
-    else:
-      raise ParseError('Couldn\'t parse float: {0}'.format(value)) from e
-
-
-def _ConvertBool(value, require_str):
-  """Convert a boolean value.
-
-  Args:
-    value: A scalar value to convert.
-    require_str: If True, value must be a str.
-
-  Returns:
-    The bool parsed.
-
-  Raises:
-    ParseError: If a boolean value couldn't be consumed.
-  """
-  if require_str:
-    if value == 'true':
-      return True
-    elif value == 'false':
-      return False
-    else:
-      raise ParseError('Expected "true" or "false", not {0}'.format(value))
-
-  if not isinstance(value, bool):
-    raise ParseError('Expected true or false without quotes')
-  return value
-
-_WKTJSONMETHODS = {
-    'google.protobuf.Any': ['_AnyMessageToJsonObject',
-                            '_ConvertAnyMessage'],
-    'google.protobuf.Duration': ['_GenericMessageToJsonObject',
-                                 '_ConvertGenericMessage'],
-    'google.protobuf.FieldMask': ['_GenericMessageToJsonObject',
-                                  '_ConvertGenericMessage'],
-    'google.protobuf.ListValue': ['_ListValueMessageToJsonObject',
-                                  '_ConvertListValueMessage'],
-    'google.protobuf.Struct': ['_StructMessageToJsonObject',
-                               '_ConvertStructMessage'],
-    'google.protobuf.Timestamp': ['_GenericMessageToJsonObject',
-                                  '_ConvertGenericMessage'],
-    'google.protobuf.Value': ['_ValueMessageToJsonObject',
-                              '_ConvertValueMessage']
-}
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/events.py b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/events.py
deleted file mode 100644
index 0ccfa98d7d3071943229b43ec9b5fc6d895c8924..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/events.py
+++ /dev/null
@@ -1,347 +0,0 @@
-"""Contains all of the events that can be triggered in a gr.Blocks() app, with the exception
-of the on-page-load event, which is defined in gr.Blocks().load()."""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Any, Callable, Literal
-
-from gradio_client.documentation import document, set_documentation_group
-
-from gradio.blocks import Block
-from gradio.deprecation import warn_deprecation
-from gradio.helpers import EventData
-from gradio.utils import get_cancel_function
-
-if TYPE_CHECKING:  # Only import for type checking (is False at runtime).
-    from gradio.components import Component
-
-set_documentation_group("events")
-
-
-def set_cancel_events(
-    block: Block, event_name: str, cancels: None | dict[str, Any] | list[dict[str, Any]]
-):
-    if cancels:
-        if not isinstance(cancels, list):
-            cancels = [cancels]
-        cancel_fn, fn_indices_to_cancel = get_cancel_function(cancels)
-        block.set_event_trigger(
-            event_name,
-            cancel_fn,
-            inputs=None,
-            outputs=None,
-            queue=False,
-            preprocess=False,
-            cancels=fn_indices_to_cancel,
-        )
-
-
-class EventListener(Block):
-    def __init__(self: Any):
-        for event_listener_class in EventListener.__subclasses__():
-            if isinstance(self, event_listener_class):
-                event_listener_class.__init__(self)
-
-
-class Dependency(dict):
-    def __init__(self, trigger, key_vals, dep_index):
-        super().__init__(key_vals)
-        self.trigger = trigger
-        self.then = EventListenerMethod(
-            self.trigger,
-            "then",
-            trigger_after=dep_index,
-            trigger_only_on_success=False,
-        )
-        """
-        Triggered after directly preceding event is completed, regardless of success or failure.
-        """
-        self.success = EventListenerMethod(
-            self.trigger,
-            "success",
-            trigger_after=dep_index,
-            trigger_only_on_success=True,
-        )
-        """
-        Triggered after directly preceding event is completed, if it was successful.
-        """
-
-
-class EventListenerMethod:
-    """
-    Triggered on an event deployment.
-    """
-
-    def __init__(
-        self,
-        trigger: Block,
-        event_name: str,
-        show_progress: Literal["full", "minimal", "hidden"] = "full",
-        callback: Callable | None = None,
-        trigger_after: int | None = None,
-        trigger_only_on_success: bool = False,
-    ):
-        self.trigger = trigger
-        self.event_name = event_name
-        self.show_progress = show_progress
-        self.callback = callback
-        self.trigger_after = trigger_after
-        self.trigger_only_on_success = trigger_only_on_success
-
-    def __call__(
-        self,
-        fn: Callable | None,
-        inputs: Component | list[Component] | set[Component] | None = None,
-        outputs: Component | list[Component] | None = None,
-        api_name: str | None | Literal[False] = None,
-        status_tracker: None = None,
-        scroll_to_output: bool = False,
-        show_progress: Literal["full", "minimal", "hidden"] = "full",
-        queue: bool | None = None,
-        batch: bool = False,
-        max_batch_size: int = 4,
-        preprocess: bool = True,
-        postprocess: bool = True,
-        cancels: dict[str, Any] | list[dict[str, Any]] | None = None,
-        every: float | None = None,
-        _js: str | None = None,
-    ) -> Dependency:
-        """
-        Parameters:
-            fn: the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.
-            inputs: List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.
-            outputs: List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.
-            api_name: Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.
-            scroll_to_output: If True, will scroll to output component on completion
-            show_progress: If True, will show progress animation while pending
-            queue: If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.
-            batch: If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.
-            max_batch_size: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)
-            preprocess: If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).
-            postprocess: If False, will not run postprocessing of component data before returning 'fn' output to the browser.
-            cancels: A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.
-            every: Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled.
-        """
-        if status_tracker:
-            warn_deprecation(
-                "The 'status_tracker' parameter has been deprecated and has no effect."
-            )
-        if self.event_name == "stop":
-            warn_deprecation(
-                "The `stop` event on Video and Audio has been deprecated and will be remove in a future version. Use `ended` instead."
-            )
-
-        if isinstance(self, Streamable):
-            self.check_streamable()
-        if isinstance(show_progress, bool):
-            show_progress = "full" if show_progress else "hidden"
-
-        dep, dep_index = self.trigger.set_event_trigger(
-            self.event_name,
-            fn,
-            inputs,
-            outputs,
-            preprocess=preprocess,
-            postprocess=postprocess,
-            scroll_to_output=scroll_to_output,
-            show_progress=show_progress
-            if show_progress is not None
-            else self.show_progress,
-            api_name=api_name,
-            js=_js,
-            queue=queue,
-            batch=batch,
-            max_batch_size=max_batch_size,
-            every=every,
-            trigger_after=self.trigger_after,
-            trigger_only_on_success=self.trigger_only_on_success,
-        )
-        set_cancel_events(self.trigger, self.event_name, cancels)
-        if self.callback:
-            self.callback()
-        return Dependency(self.trigger, dep, dep_index)
-
-
-@document("*change", inherit=True)
-class Changeable(EventListener):
-    def __init__(self):
-        self.change = EventListenerMethod(self, "change")
-        """
-        This listener is triggered when the component's value changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger).
-        See `.input()` for a listener that is only triggered by user input.
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*input", inherit=True)
-class Inputable(EventListener):
-    def __init__(self):
-        self.input = EventListenerMethod(self, "input")
-        """
-        This listener is triggered when the user changes the value of the component.
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*click", inherit=True)
-class Clickable(EventListener):
-    def __init__(self):
-        self.click = EventListenerMethod(self, "click")
-        """
-        This listener is triggered when the component (e.g. a button) is clicked.
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*submit", inherit=True)
-class Submittable(EventListener):
-    def __init__(self):
-        self.submit = EventListenerMethod(self, "submit")
-        """
-        This listener is triggered when the user presses the Enter key while the component (e.g. a textbox) is focused.
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*edit", inherit=True)
-class Editable(EventListener):
-    def __init__(self):
-        self.edit = EventListenerMethod(self, "edit")
-        """
-        This listener is triggered when the user edits the component (e.g. image) using the
-        built-in editor. This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*clear", inherit=True)
-class Clearable(EventListener):
-    def __init__(self):
-        self.clear = EventListenerMethod(self, "clear")
-        """
-        This listener is triggered when the user clears the component (e.g. image or audio)
-        using the X button for the component. This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*play", "*pause", "*stop", inherit=True)
-class Playable(EventListener):
-    def __init__(self):
-        self.play = EventListenerMethod(self, "play")
-        """
-        This listener is triggered when the user plays the component (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-        self.pause = EventListenerMethod(self, "pause")
-        """
-        This listener is triggered when the media stops playing for any reason (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-        self.stop = EventListenerMethod(self, "stop")
-        """
-        This listener is triggered when the user reaches the end of the media track (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-        self.end = EventListenerMethod(self, "end")
-        """
-        This listener is triggered when the user reaches the end of the media track (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*stream", inherit=True)
-class Streamable(EventListener):
-    def __init__(self):
-        self.streaming: bool
-        self.stream = EventListenerMethod(
-            self,
-            "stream",
-            show_progress="hidden",
-            callback=lambda: setattr(self, "streaming", True),
-        )
-        """
-        This listener is triggered when the user streams the component (e.g. a live webcam
-        component). This method can be used when this component is in a Gradio Blocks.
-        """
-
-    def check_streamable(self):
-        pass
-
-
-@document("*start_recording", "*stop_recording", inherit=True)
-class Recordable(EventListener):
-    def __init__(self):
-        self.start_recording = EventListenerMethod(self, "start_recording")
-        """
-        This listener is triggered when the user starts recording with the component (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-        self.stop_recording = EventListenerMethod(self, "stop_recording")
-        """
-        This listener is triggered when the user stops recording with the component (e.g. audio or video).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*blur", inherit=True)
-class Blurrable(EventListener):
-    def __init__(self):
-        self.blur = EventListenerMethod(self, "blur")
-        """
-        This listener is triggered when the component's is unfocused/blurred (e.g. when the user clicks outside of a textbox). 
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*upload", inherit=True)
-class Uploadable(EventListener):
-    def __init__(self):
-        self.upload = EventListenerMethod(self, "upload")
-        """
-        This listener is triggered when the user uploads a file into the component (e.g. when the user uploads a video into a video component).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*release", inherit=True)
-class Releaseable(EventListener):
-    def __init__(self):
-        self.release = EventListenerMethod(self, "release")
-        """
-        This listener is triggered when the user releases the mouse on this component (e.g. when the user releases the slider).
-        This method can be used when this component is in a Gradio Blocks.
-        """
-
-
-@document("*select", inherit=True)
-class Selectable(EventListener):
-    def __init__(self):
-        self.selectable: bool = False
-        self.select = EventListenerMethod(
-            self, "select", callback=lambda: setattr(self, "selectable", True)
-        )
-        """
-        This listener is triggered when the user selects from within the Component.
-        This event has EventData of type gradio.SelectData that carries information, accessible through SelectData.index and SelectData.value.
-        See EventData documentation on how to use this event data.
-        """
-
-
-class SelectData(EventData):
-    def __init__(self, target: Block | None, data: Any):
-        super().__init__(target, data)
-        self.index: int | tuple[int, int] = data["index"]
-        """
-        The index of the selected item. Is a tuple if the component is two dimensional or selection is a range.
-        """
-        self.value: Any = data["value"]
-        """
-        The value of the selected item.
-        """
-        self.selected: bool = data.get("selected", True)
-        """
-        True if the item was selected, False if deselected.
-        """
diff --git a/spaces/cihyFjudo/fairness-paper-search/Download Film Make Me Shudder Sub Indo  Film yang Membuktikan bahwa Tidak Ada Hantu yang Tidak Bisa Ditertawakan.md b/spaces/cihyFjudo/fairness-paper-search/Download Film Make Me Shudder Sub Indo  Film yang Membuktikan bahwa Tidak Ada Hantu yang Tidak Bisa Ditertawakan.md
deleted file mode 100644
index 1dffd828f3e1c4e0668e9460a0e4e780a417a782..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Download Film Make Me Shudder Sub Indo  Film yang Membuktikan bahwa Tidak Ada Hantu yang Tidak Bisa Ditertawakan.md	
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Fortnite Battle Royale 10.20.0 Apk MOD (Unlocked) Data Android A Complete Guide for Beginners and Experts.md b/spaces/cihyFjudo/fairness-paper-search/Fortnite Battle Royale 10.20.0 Apk MOD (Unlocked) Data Android A Complete Guide for Beginners and Experts.md
deleted file mode 100644
index 589345c259b3b80d4b981a829ad9c0e243f36af5..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Fortnite Battle Royale 10.20.0 Apk MOD (Unlocked) Data Android A Complete Guide for Beginners and Experts.md	
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deleted file mode 100644
index 0eae9ca1217ba6c1784f8497dbf7dfb8435e0b20..0000000000000000000000000000000000000000
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Malayalam Coffee House Pdf Free Download 2015 Moviesl Watch the Latest Malayalam Films Online.md b/spaces/cihyFjudo/fairness-paper-search/Malayalam Coffee House Pdf Free Download 2015 Moviesl Watch the Latest Malayalam Films Online.md
deleted file mode 100644
index e7068f874c9f86e77059f4af50cdad85dbf335f0..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Malayalam Coffee House Pdf Free Download 2015 Moviesl Watch the Latest Malayalam Films Online.md	
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deleted file mode 100644
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diff --git a/spaces/cllatMTK/TransformerAnalyzer/model_util.py b/spaces/cllatMTK/TransformerAnalyzer/model_util.py
deleted file mode 100644
index 2aa28826f6bbcf21c58672ad6920ff9a603836da..0000000000000000000000000000000000000000
--- a/spaces/cllatMTK/TransformerAnalyzer/model_util.py
+++ /dev/null
@@ -1,141 +0,0 @@
-import requests
-import re
-from collections import defaultdict
-# Utilities related to loading in and working with models/specific models
-from urllib.parse import urlparse
-from accelerate.commands.estimate import check_has_model, create_empty_model
-from accelerate.utils import compute_module_sizes, named_module_tensors
-from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
-
-
-def fetch_dictionary_content(model_id):
-    MODEL_URL = "https://huggingface.co/{model_id}/raw/main/config.json"
-    response = requests.get(MODEL_URL.format(model_id=model_id))
-    
-    # Check if the request was successful
-    if response.status_code == 200:
-        return response.json()  # Parse the JSON content into a Python dictionary
-    else:
-        return None
-    
-def load_parameter(model_dict, cand_keys):
-    for k in cand_keys:
-        if k in model_dict:
-            return model_dict[k]
-    return 0
-
-# Reference: https://huggingface.co/spaces/hf-accelerate/model-memory-usage
-def extract_from_url(name: str):
-    "Checks if `name` is a URL, and if so converts it to a model name"
-    is_url = False
-    try:
-        result = urlparse(name)
-        is_url = all([result.scheme, result.netloc])
-    except Exception:
-        is_url = False
-    # Pass through if not a URL
-    if not is_url:
-        return name
-    else:
-        path = result.path
-        return path[1:]
-
-
-def translate_llama2(text):
-    "Translates llama-2 to its hf counterpart"
-    if not text.endswith("-hf"):
-        return text + "-hf"
-    return text
-
-
-def get_model(model_name: str, library: str, access_token: str):
-    "Finds and grabs model from the Hub, and initializes on `meta`"
-    if "meta-llama" in model_name:
-        model_name = translate_llama2(model_name)
-    if library == "auto":
-        library = None
-    model_name = extract_from_url(model_name)
-    try:
-        model = create_empty_model(model_name, library_name=library, trust_remote_code=True, access_token=access_token)
-    except GatedRepoError:
-        raise RuntimeError(
-            f"Model `{model_name}` is a gated model, please ensure to pass in your access token and try again if you have access. You can find your access token here : https://huggingface.co/settings/tokens. "
-        )
-    except RepositoryNotFoundError:
-        raise RuntimeError(f"Model `{model_name}` was not found on the Hub, please try another model name.")
-    except ValueError:
-        raise RuntimeError(
-            f"Model `{model_name}` does not have any library metadata on the Hub, please manually select a library_name to use (such as `transformers`)"
-        )
-    except (RuntimeError, OSError) as e:
-        library = check_has_model(e)
-        if library != "unknown":
-            raise RuntimeError(
-                f"Tried to load `{model_name}` with `{library}` but a possible model to load was not found inside the repo."
-            )
-        raise RuntimeError(
-            f"Model `{model_name}` had an error, please open a discussion on the model's page with the error message and name: `{e}`"
-        )
-    except ImportError:
-        # hacky way to check if it works with `trust_remote_code=False`
-        model = create_empty_model(
-            model_name, library_name=library, trust_remote_code=False, access_token=access_token
-        )
-    except Exception as e:
-        raise RuntimeError(
-            f"Model `{model_name}` had an error, please open a discussion on the model's page with the error message and name: `{e}`"
-        )
-    return model
-
-def get_module_tensors(model):
-    module_tensors = {}
-    for name, tensor in named_module_tensors(model, recurse=True):
-        module_tensors[name] = tensor.shape
-
-    return module_tensors
-
-
-def classify_module(module_tensors):
-    # A dictionary to store counts for each generic layer type
-    module_classes = defaultdict(list)
-
-    # This function removes all numbers from a given string
-    def remove_numbers(s):
-        return re.sub(r'\d+', '', s)
-    
-    # Loop through all named parameters of the model
-    for name in module_tensors:
-        # Remove numbers from the name
-        generic_name = remove_numbers(name)
-        generic_name = generic_name.replace('..', '.')
-        
-        # If the name already exists in the dictionary, increase the count, else set it to 1
-        module_classes[generic_name].append({name: module_tensors[name]})
-
-    return module_classes
-
-def get_module_tensors_matched(filter_fn, module_classes_dict):
-    matched = []
-    for generic, module_list in module_classes_dict.items():
-        if filter_fn(generic.lower()):
-            matched.extend([v for module in module_list for v in module.values()])
-       
-    return matched
-
-
-if __name__ == '__main__':
-    import torch
-    model = get_model('NousResearch/Nous-Hermes-Llama2-13b', None, None)
-    module_tensors = get_module_tensors(model)
-    module_classes = classify_module(module_tensors)
-    sizes = compute_module_sizes(model, dtype=torch.int8)
-    size_dict = {
-        'attn':0,
-        'mlp':0,
-        'embed':0,
-    }
-    for k, v in sizes.items():
-        for kk in size_dict:
-            if kk in k and 'weight' in k:
-                size_dict[kk] += v/1024**3
-    print(sizes)
\ No newline at end of file
diff --git a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/fontTools/misc/testTools.py b/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/fontTools/misc/testTools.py
deleted file mode 100644
index be6116132d93a6a5f692f5b8465be346aad7ca5c..0000000000000000000000000000000000000000
--- a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/fontTools/misc/testTools.py
+++ /dev/null
@@ -1,229 +0,0 @@
-"""Helpers for writing unit tests."""
-
-from collections.abc import Iterable
-from io import BytesIO
-import os
-import re
-import shutil
-import sys
-import tempfile
-from unittest import TestCase as _TestCase
-from fontTools.config import Config
-from fontTools.misc.textTools import tobytes
-from fontTools.misc.xmlWriter import XMLWriter
-
-
-def parseXML(xmlSnippet):
-    """Parses a snippet of XML.
-
-    Input can be either a single string (unicode or UTF-8 bytes), or a
-    a sequence of strings.
-
-    The result is in the same format that would be returned by
-    XMLReader, but the parser imposes no constraints on the root
-    element so it can be called on small snippets of TTX files.
-    """
-    # To support snippets with multiple elements, we add a fake root.
-    reader = TestXMLReader_()
-    xml = b"<root>"
-    if isinstance(xmlSnippet, bytes):
-        xml += xmlSnippet
-    elif isinstance(xmlSnippet, str):
-        xml += tobytes(xmlSnippet, "utf-8")
-    elif isinstance(xmlSnippet, Iterable):
-        xml += b"".join(tobytes(s, "utf-8") for s in xmlSnippet)
-    else:
-        raise TypeError(
-            "expected string or sequence of strings; found %r"
-            % type(xmlSnippet).__name__
-        )
-    xml += b"</root>"
-    reader.parser.Parse(xml, 0)
-    return reader.root[2]
-
-
-def parseXmlInto(font, parseInto, xmlSnippet):
-    parsed_xml = [e for e in parseXML(xmlSnippet.strip()) if not isinstance(e, str)]
-    for name, attrs, content in parsed_xml:
-        parseInto.fromXML(name, attrs, content, font)
-    parseInto.populateDefaults()
-    return parseInto
-
-
-class FakeFont:
-    def __init__(self, glyphs):
-        self.glyphOrder_ = glyphs
-        self.reverseGlyphOrderDict_ = {g: i for i, g in enumerate(glyphs)}
-        self.lazy = False
-        self.tables = {}
-        self.cfg = Config()
-
-    def __getitem__(self, tag):
-        return self.tables[tag]
-
-    def __setitem__(self, tag, table):
-        self.tables[tag] = table
-
-    def get(self, tag, default=None):
-        return self.tables.get(tag, default)
-
-    def getGlyphID(self, name):
-        return self.reverseGlyphOrderDict_[name]
-
-    def getGlyphIDMany(self, lst):
-        return [self.getGlyphID(gid) for gid in lst]
-
-    def getGlyphName(self, glyphID):
-        if glyphID < len(self.glyphOrder_):
-            return self.glyphOrder_[glyphID]
-        else:
-            return "glyph%.5d" % glyphID
-
-    def getGlyphNameMany(self, lst):
-        return [self.getGlyphName(gid) for gid in lst]
-
-    def getGlyphOrder(self):
-        return self.glyphOrder_
-
-    def getReverseGlyphMap(self):
-        return self.reverseGlyphOrderDict_
-
-    def getGlyphNames(self):
-        return sorted(self.getGlyphOrder())
-
-
-class TestXMLReader_(object):
-    def __init__(self):
-        from xml.parsers.expat import ParserCreate
-
-        self.parser = ParserCreate()
-        self.parser.StartElementHandler = self.startElement_
-        self.parser.EndElementHandler = self.endElement_
-        self.parser.CharacterDataHandler = self.addCharacterData_
-        self.root = None
-        self.stack = []
-
-    def startElement_(self, name, attrs):
-        element = (name, attrs, [])
-        if self.stack:
-            self.stack[-1][2].append(element)
-        else:
-            self.root = element
-        self.stack.append(element)
-
-    def endElement_(self, name):
-        self.stack.pop()
-
-    def addCharacterData_(self, data):
-        self.stack[-1][2].append(data)
-
-
-def makeXMLWriter(newlinestr="\n"):
-    # don't write OS-specific new lines
-    writer = XMLWriter(BytesIO(), newlinestr=newlinestr)
-    # erase XML declaration
-    writer.file.seek(0)
-    writer.file.truncate()
-    return writer
-
-
-def getXML(func, ttFont=None):
-    """Call the passed toXML function and return the written content as a
-    list of lines (unicode strings).
-    Result is stripped of XML declaration and OS-specific newline characters.
-    """
-    writer = makeXMLWriter()
-    func(writer, ttFont)
-    xml = writer.file.getvalue().decode("utf-8")
-    # toXML methods must always end with a writer.newline()
-    assert xml.endswith("\n")
-    return xml.splitlines()
-
-
-def stripVariableItemsFromTTX(
-    string: str,
-    ttLibVersion: bool = True,
-    checkSumAdjustment: bool = True,
-    modified: bool = True,
-    created: bool = True,
-    sfntVersion: bool = False,  # opt-in only
-) -> str:
-    """Strip stuff like ttLibVersion, checksums, timestamps, etc. from TTX dumps."""
-    # ttlib changes with the fontTools version
-    if ttLibVersion:
-        string = re.sub(' ttLibVersion="[^"]+"', "", string)
-    # sometimes (e.g. some subsetter tests) we don't care whether it's OTF or TTF
-    if sfntVersion:
-        string = re.sub(' sfntVersion="[^"]+"', "", string)
-    # head table checksum and creation and mod date changes with each save.
-    if checkSumAdjustment:
-        string = re.sub('<checkSumAdjustment value="[^"]+"/>', "", string)
-    if modified:
-        string = re.sub('<modified value="[^"]+"/>', "", string)
-    if created:
-        string = re.sub('<created value="[^"]+"/>', "", string)
-    return string
-
-
-class MockFont(object):
-    """A font-like object that automatically adds any looked up glyphname
-    to its glyphOrder."""
-
-    def __init__(self):
-        self._glyphOrder = [".notdef"]
-
-        class AllocatingDict(dict):
-            def __missing__(reverseDict, key):
-                self._glyphOrder.append(key)
-                gid = len(reverseDict)
-                reverseDict[key] = gid
-                return gid
-
-        self._reverseGlyphOrder = AllocatingDict({".notdef": 0})
-        self.lazy = False
-
-    def getGlyphID(self, glyph):
-        gid = self._reverseGlyphOrder[glyph]
-        return gid
-
-    def getReverseGlyphMap(self):
-        return self._reverseGlyphOrder
-
-    def getGlyphName(self, gid):
-        return self._glyphOrder[gid]
-
-    def getGlyphOrder(self):
-        return self._glyphOrder
-
-
-class TestCase(_TestCase):
-    def __init__(self, methodName):
-        _TestCase.__init__(self, methodName)
-        # Python 3 renamed assertRaisesRegexp to assertRaisesRegex,
-        # and fires deprecation warnings if a program uses the old name.
-        if not hasattr(self, "assertRaisesRegex"):
-            self.assertRaisesRegex = self.assertRaisesRegexp
-
-
-class DataFilesHandler(TestCase):
-    def setUp(self):
-        self.tempdir = None
-        self.num_tempfiles = 0
-
-    def tearDown(self):
-        if self.tempdir:
-            shutil.rmtree(self.tempdir)
-
-    def getpath(self, testfile):
-        folder = os.path.dirname(sys.modules[self.__module__].__file__)
-        return os.path.join(folder, "data", testfile)
-
-    def temp_dir(self):
-        if not self.tempdir:
-            self.tempdir = tempfile.mkdtemp()
-
-    def temp_font(self, font_path, file_name):
-        self.temp_dir()
-        temppath = os.path.join(self.tempdir, file_name)
-        shutil.copy2(font_path, temppath)
-        return temppath
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hevc_mc_biw_msa.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hevc_mc_biw_msa.c
deleted file mode 100644
index 260ec844963d56093634429de1af4679075fc19c..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hevc_mc_biw_msa.c
+++ /dev/null
@@ -1,6153 +0,0 @@
-/*
- * Copyright (c) 2015 - 2017 Manojkumar Bhosale (Manojkumar.Bhosale@imgtec.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 "libavutil/mips/generic_macros_msa.h"
-#include "libavcodec/mips/hevcdsp_mips.h"
-#include "libavcodec/mips/hevc_macros_msa.h"
-
-static const uint8_t ff_hevc_mask_arr[16 * 2] __attribute__((aligned(0x40))) = {
-    /* 8 width cases */
-    0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8,
-    0, 1, 1, 2, 2, 3, 3, 4, 16, 17, 17, 18, 18, 19, 19, 20
-};
-
-#define HEVC_BIW_RND_CLIP2(in0, in1, vec0, vec1, wgt, rnd, offset,  \
-                           out0, out1)                              \
-{                                                                   \
-    v4i32 out0_r, out1_r, out0_l, out1_l;                           \
-                                                                    \
-    ILVR_H2_SW(in0, vec0, in1, vec1, out0_r, out1_r);               \
-    ILVL_H2_SW(in0, vec0, in1, vec1, out0_l, out1_l);               \
-                                                                    \
-    out0_r = __msa_dpadd_s_w(offset, (v8i16) out0_r, (v8i16) wgt);  \
-    out1_r = __msa_dpadd_s_w(offset, (v8i16) out1_r, (v8i16) wgt);  \
-    out0_l = __msa_dpadd_s_w(offset, (v8i16) out0_l, (v8i16) wgt);  \
-    out1_l = __msa_dpadd_s_w(offset, (v8i16) out1_l, (v8i16) wgt);  \
-                                                                    \
-    SRAR_W4_SW(out0_r, out1_r, out0_l, out1_l, rnd);                \
-    CLIP_SW4_0_255(out0_l, out0_r, out1_l, out1_r);                 \
-    PCKEV_H2_SH(out0_l, out0_r, out1_l, out1_r, out0, out1);        \
-}
-
-#define HEVC_BIW_RND_CLIP4(in0, in1, in2, in3, vec0, vec1, vec2, vec3,       \
-                           wgt, rnd, offset, out0, out1, out2, out3)         \
-{                                                                            \
-    HEVC_BIW_RND_CLIP2(in0, in1, vec0, vec1, wgt, rnd, offset, out0, out1);  \
-    HEVC_BIW_RND_CLIP2(in2, in3, vec2, vec3, wgt, rnd, offset, out2, out3);  \
-}
-
-#define HEVC_BIW_RND_CLIP2_MAX_SATU(in0, in1, vec0, vec1, wgt, rnd,  \
-                                    offset, out0, out1)              \
-{                                                                    \
-    v4i32 out0_r, out1_r, out0_l, out1_l;                            \
-                                                                     \
-    ILVR_H2_SW(in0, vec0, in1, vec1, out0_r, out1_r);                \
-    ILVL_H2_SW(in0, vec0, in1, vec1, out0_l, out1_l);                \
-    out0_r = __msa_dpadd_s_w(offset, (v8i16) out0_r, (v8i16) wgt);   \
-    out1_r = __msa_dpadd_s_w(offset, (v8i16) out1_r, (v8i16) wgt);   \
-    out0_l = __msa_dpadd_s_w(offset, (v8i16) out0_l, (v8i16) wgt);   \
-    out1_l = __msa_dpadd_s_w(offset, (v8i16) out1_l, (v8i16) wgt);   \
-    SRAR_W4_SW(out0_r, out1_r, out0_l, out1_l, rnd);                 \
-    CLIP_SW4_0_255(out0_r, out1_r, out0_l, out1_l);                  \
-    PCKEV_H2_SH(out0_l, out0_r, out1_l, out1_r, out0, out1);         \
-}
-
-#define HEVC_BIW_RND_CLIP4_MAX_SATU(in0, in1, in2, in3, vec0, vec1, vec2,  \
-                                    vec3, wgt, rnd, offset, out0, out1,    \
-                                    out2, out3)                            \
-{                                                                          \
-    HEVC_BIW_RND_CLIP2_MAX_SATU(in0, in1, vec0, vec1, wgt, rnd, offset,    \
-                                out0, out1);                               \
-    HEVC_BIW_RND_CLIP2_MAX_SATU(in2, in3, vec2, vec3, wgt, rnd, offset,    \
-                                out2, out3);                               \
-}
-
-static void hevc_biwgt_copy_4w_msa(const uint8_t *src0_ptr,
-                                   int32_t src_stride,
-                                   const int16_t *src1_ptr,
-                                   int32_t src2_stride,
-                                   uint8_t *dst,
-                                   int32_t dst_stride,
-                                   int32_t height,
-                                   int32_t weight0,
-                                   int32_t weight1,
-                                   int32_t offset0,
-                                   int32_t offset1,
-                                   int32_t rnd_val)
-{
-    uint32_t loop_cnt, tp0, tp1, tp2, tp3;
-    uint64_t tpd0, tpd1, tpd2, tpd3;
-    int32_t offset, weight;
-    v16u8 out0, out1;
-    v16i8 zero = { 0 };
-    v16i8 src0 = { 0 }, src1 = { 0 };
-    v8i16 in0 = { 0 }, in1 = { 0 }, in2 = { 0 }, in3 = { 0 };
-    v8i16 dst0, dst1, dst2, dst3, weight_vec;
-    v4i32 dst0_r, dst0_l, offset_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    if (2 == height) {
-        LW2(src0_ptr, src_stride, tp0, tp1);
-        INSERT_W2_SB(tp0, tp1, src0);
-        LD2(src1_ptr, src2_stride, tpd0, tpd1);
-        INSERT_D2_SH(tpd0, tpd1, in0);
-
-        dst0 = (v8i16) __msa_ilvr_b(zero, src0);
-        dst0 <<= 6;
-
-        ILVRL_H2_SW(dst0, in0, dst0_r, dst0_l);
-        dst0_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst0_r, weight_vec);
-        dst0_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst0_l, weight_vec);
-        SRAR_W2_SW(dst0_r, dst0_l, rnd_vec);
-        CLIP_SW2_0_255(dst0_r, dst0_l);
-        dst0 = (v8i16) __msa_pckev_h((v8i16) dst0_l, (v8i16) dst0_r);
-        out0 = (v16u8) __msa_pckev_b((v16i8) dst0, (v16i8) dst0);
-        ST_W2(out0, 0, 1, dst, dst_stride);
-    } else if (4 == height) {
-        LW4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-        INSERT_W4_SB(tp0, tp1, tp2, tp3, src0);
-        LD4(src1_ptr, src2_stride, tpd0, tpd1, tpd2, tpd3);
-        INSERT_D2_SH(tpd0, tpd1, in0);
-        INSERT_D2_SH(tpd2, tpd3, in1);
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        SLLI_2V(dst0, dst1, 6);
-        HEVC_BIW_RND_CLIP2_MAX_SATU(dst0, dst1, in0, in1, weight_vec, rnd_vec,
-                                    offset_vec, dst0, dst1);
-        out0 = (v16u8) __msa_pckev_b((v16i8) dst1, (v16i8) dst0);
-        ST_W4(out0, 0, 1, 2, 3, dst, dst_stride);
-    } else if (0 == height % 8) {
-        for (loop_cnt = (height >> 3); loop_cnt--;) {
-            LW4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-            src0_ptr += 4 * src_stride;
-            INSERT_W4_SB(tp0, tp1, tp2, tp3, src0);
-            LW4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-            src0_ptr += 4 * src_stride;
-            INSERT_W4_SB(tp0, tp1, tp2, tp3, src1);
-            LD4(src1_ptr, src2_stride, tpd0, tpd1, tpd2, tpd3);
-            src1_ptr += (4 * src2_stride);
-            INSERT_D2_SH(tpd0, tpd1, in0);
-            INSERT_D2_SH(tpd2, tpd3, in1);
-            LD4(src1_ptr, src2_stride, tpd0, tpd1, tpd2, tpd3);
-            src1_ptr += (4 * src2_stride);
-            INSERT_D2_SH(tpd0, tpd1, in2);
-            INSERT_D2_SH(tpd2, tpd3, in3);
-            ILVRL_B2_SH(zero, src0, dst0, dst1);
-            ILVRL_B2_SH(zero, src1, dst2, dst3);
-            SLLI_4V(dst0, dst1, dst2, dst3, 6);
-            HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in1, in2,
-                                        in3, weight_vec, rnd_vec, offset_vec,
-                                        dst0, dst1, dst2, dst3);
-            PCKEV_B2_UB(dst1, dst0, dst3, dst2, out0, out1);
-            ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-            dst += (8 * dst_stride);
-        }
-    }
-}
-
-static void hevc_biwgt_copy_6w_msa(const uint8_t *src0_ptr,
-                                   int32_t src_stride,
-                                   const int16_t *src1_ptr,
-                                   int32_t src2_stride,
-                                   uint8_t *dst,
-                                   int32_t dst_stride,
-                                   int32_t height,
-                                   int32_t weight0,
-                                   int32_t weight1,
-                                   int32_t offset0,
-                                   int32_t offset1,
-                                   int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t res = height & 0x03;
-    int32_t offset, weight;
-    uint64_t tp0, tp1, tp2, tp3;
-    v16u8 out0, out1;
-    v16i8 zero = { 0 };
-    v16i8 src0 = { 0 }, src1 = { 0 };
-    v8i16 in0, in1, in2, in3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    weight_vec = __msa_fill_w(weight);
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-        src0_ptr += (4 * src_stride);
-        INSERT_D2_SB(tp0, tp1, src0);
-        INSERT_D2_SB(tp2, tp3, src1);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        ILVRL_B2_SH(zero, src1, dst2, dst3);
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3,
-                                    in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec,
-                                    dst0, dst1, dst2, dst3);
-        PCKEV_B2_UB(dst1, dst0, dst3, dst2, out0, out1);
-        ST_W2(out0, 0, 2, dst, dst_stride);
-        ST_H2(out0, 2, 6, dst + 4, dst_stride);
-        ST_W2(out1, 0, 2, dst + 2 * dst_stride, dst_stride);
-        ST_H2(out1, 2, 6, dst + 2 * dst_stride + 4, dst_stride);
-        dst += (4 * dst_stride);
-    }
-    if (res) {
-        LD4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-        src0_ptr += (4 * src_stride);
-        INSERT_D2_SB(tp0, tp1, src0);
-        INSERT_D2_SB(tp2, tp3, src1);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        ILVRL_B2_SH(zero, src1, dst2, dst3);
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3,
-                                    in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec,
-                                    dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_UB(dst1, dst0, dst3, dst2, out0, out1);
-        ST_W2(out0, 0, 2, dst, dst_stride);
-        ST_H2(out0, 2, 6, dst + 4, dst_stride);
-        ST_W2(out1, 0, 2, dst + 2 * dst_stride, dst_stride);
-        ST_H2(out1, 2, 6, dst + 2 * dst_stride + 4, dst_stride);
-    }
-}
-
-static void hevc_biwgt_copy_8w_msa(const uint8_t *src0_ptr,
-                                   int32_t src_stride,
-                                   const int16_t *src1_ptr,
-                                   int32_t src2_stride,
-                                   uint8_t *dst,
-                                   int32_t dst_stride,
-                                   int32_t height,
-                                   int32_t weight0,
-                                   int32_t weight1,
-                                   int32_t offset0,
-                                   int32_t offset1,
-                                   int32_t rnd_val)
-{
-    uint64_t tp0, tp1, tp2, tp3;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2;
-    v16i8 zero = { 0 };
-    v16i8 src0 = { 0 }, src1 = { 0 }, src2 = { 0 };
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    if (2 == height) {
-        LD2(src0_ptr, src_stride, tp0, tp1);
-        INSERT_D2_SB(tp0, tp1, src0);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        SLLI_2V(dst0, dst1, 6);
-
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1);
-
-        out0 = (v16u8) __msa_pckev_b((v16i8) dst1, (v16i8) dst0);
-        ST_D2(out0, 0, 1, dst, dst_stride);
-    } else if (6 == height) {
-        LD4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-        src0_ptr += 4 * src_stride;
-        INSERT_D2_SB(tp0, tp1, src0);
-        INSERT_D2_SB(tp2, tp3, src1);
-        LD2(src0_ptr, src_stride, tp0, tp1);
-        INSERT_D2_SB(tp0, tp1, src2);
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        ILVRL_B2_SH(zero, src1, dst2, dst3);
-        ILVRL_B2_SH(zero, src2, dst4, dst5);
-        LD_SH6(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5);
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        SLLI_2V(dst4, dst5, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec, dst0, dst1,
-                                    dst2, dst3);
-        HEVC_BIW_RND_CLIP2_MAX_SATU(dst4, dst5, in4, in5, weight_vec, rnd_vec,
-                                    offset_vec, dst4, dst5);
-        PCKEV_B3_UB(dst1, dst0, dst3, dst2, dst5, dst4, out0, out1, out2);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-        ST_D2(out2, 0, 1, dst + 4 * dst_stride, dst_stride);
-    } else if (0 == height % 4) {
-        uint32_t loop_cnt;
-
-        for (loop_cnt = (height >> 2); loop_cnt--;) {
-            LD4(src0_ptr, src_stride, tp0, tp1, tp2, tp3);
-            src0_ptr += (4 * src_stride);
-            INSERT_D2_SB(tp0, tp1, src0);
-            INSERT_D2_SB(tp2, tp3, src1);
-            ILVRL_B2_SH(zero, src0, dst0, dst1);
-            ILVRL_B2_SH(zero, src1, dst2, dst3);
-            LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-            src1_ptr += (4 * src2_stride);
-
-            SLLI_4V(dst0, dst1, dst2, dst3, 6);
-            HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in1, in2,
-                                        in3, weight_vec, rnd_vec, offset_vec,
-                                        dst0, dst1, dst2, dst3);
-            PCKEV_B2_UB(dst1, dst0, dst3, dst2, out0, out1);
-            ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-            dst += (4 * dst_stride);
-        }
-    }
-}
-
-static void hevc_biwgt_copy_12w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16i8 zero = { 0 };
-    v16u8 out0, out1, out2;
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        LD_SH4(src1_ptr + 8, src2_stride, in4, in5, in6, in7);
-        src1_ptr += (4 * src2_stride);
-
-        ILVR_D2_SH(in5, in4, in7, in6, in4, in5);
-        ILVR_B4_SH(zero, src0, zero, src1, zero, src2, zero, src3,
-                   dst0, dst1, dst2, dst3);
-
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        ILVL_W2_SB(src1, src0, src3, src2, src0, src1);
-        ILVR_B2_SH(zero, src0, zero, src1, dst4, dst5);
-
-        dst4 <<= 6;
-        dst5 <<= 6;
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec, dst0, dst1,
-                                    dst2, dst3);
-        HEVC_BIW_RND_CLIP2_MAX_SATU(dst4, dst5, in4, in5, weight_vec, rnd_vec,
-                                    offset_vec, dst4, dst5);
-        PCKEV_B3_UB(dst1, dst0, dst3, dst2, dst5, dst4, out0, out1, out2);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-        ST_W4(out2, 0, 1, 2, 3, dst + 8, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_biwgt_copy_16w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2, out3;
-    v16i8 zero = { 0 };
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        LD_SH4(src1_ptr + 8, src2_stride, in4, in5, in6, in7);
-        src1_ptr += (4 * src2_stride);
-        ILVR_B4_SH(zero, src0, zero, src1, zero, src2, zero, src3, tmp0, tmp1,
-                   tmp2, tmp3);
-        ILVL_B4_SH(zero, src0, zero, src1, zero, src2, zero, src3, tmp4, tmp5,
-                   tmp6, tmp7);
-        SLLI_4V(tmp0, tmp1, tmp2, tmp3, 6);
-        SLLI_4V(tmp4, tmp5, tmp6, tmp7, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp0, tmp1, tmp4, tmp5, in0, in1, in4, in5,
-                                    weight_vec, rnd_vec, offset_vec, tmp0, tmp1,
-                                    tmp4, tmp5);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp2, tmp3, tmp6, tmp7, in2, in3, in6, in7,
-                                    weight_vec, rnd_vec, offset_vec, tmp2, tmp3,
-                                    tmp6, tmp7);
-        PCKEV_B2_UB(tmp4, tmp0, tmp5, tmp1, out0, out1);
-        PCKEV_B2_UB(tmp6, tmp2, tmp7, tmp3, out2, out3);
-        ST_UB4(out0, out1, out2, out3, dst, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_biwgt_copy_24w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2, out3, out4, out5;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, zero = { 0 };
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7, dst8, dst9, dst10;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7, in8, in9, in10, in11, dst11;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = 8; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src4, src5);
-        LD_SB4(src0_ptr + 16, src_stride, src2, src3, src6, src7);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        LD_SH4(src1_ptr + 8, src2_stride, in4, in5, in6, in7);
-        LD_SH4(src1_ptr + 16, src2_stride, in8, in9, in10, in11);
-        src1_ptr += (4 * src2_stride);
-
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        ILVRL_B2_SH(zero, src1, dst2, dst3);
-        ILVR_B2_SH(zero, src2, zero, src3, dst4, dst5);
-        ILVRL_B2_SH(zero, src4, dst6, dst7);
-        ILVRL_B2_SH(zero, src5, dst8, dst9);
-        ILVR_B2_SH(zero, src6, zero, src7, dst10, dst11);
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        SLLI_4V(dst4, dst5, dst6, dst7, 6);
-        SLLI_4V(dst8, dst9, dst10, dst11, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in4, in1, in5,
-                                    weight_vec, rnd_vec, offset_vec, dst0, dst1,
-                                    dst2, dst3);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst4, dst5, dst6, dst7, in8, in9, in2, in6,
-                                    weight_vec, rnd_vec, offset_vec, dst4, dst5,
-                                    dst6, dst7);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst8, dst9, dst10, dst11, in3, in7, in10,
-                                    in11, weight_vec, rnd_vec, offset_vec,
-                                    dst8, dst9, dst10, dst11);
-        PCKEV_B3_UB(dst1, dst0, dst3, dst2, dst5, dst4, out0, out1, out2);
-        PCKEV_B3_UB(dst7, dst6, dst9, dst8, dst11, dst10, out3, out4, out5);
-        ST_UB4(out0, out1, out3, out4, dst, dst_stride);
-        ST_D4(out2, out5, 0, 1, 0, 1, dst + 16, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_biwgt_copy_32w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2, out3;
-    v16i8 zero = { 0 };
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = (height >> 1); loop_cnt--;) {
-        LD_SB2(src0_ptr, 16, src0, src1);
-        src0_ptr += src_stride;
-        LD_SB2(src0_ptr, 16, src2, src3);
-        src0_ptr += src_stride;
-        LD_SH4(src1_ptr, 8, in0, in1, in2, in3);
-        src1_ptr += src2_stride;
-        LD_SH4(src1_ptr, 8, in4, in5, in6, in7);
-        src1_ptr += src2_stride;
-
-        ILVRL_B2_SH(zero, src0, tmp0, tmp4);
-        ILVRL_B2_SH(zero, src1, tmp1, tmp5);
-        ILVRL_B2_SH(zero, src2, tmp2, tmp6);
-        ILVRL_B2_SH(zero, src3, tmp3, tmp7);
-        SLLI_4V(tmp0, tmp1, tmp2, tmp3, 6);
-        SLLI_4V(tmp4, tmp5, tmp6, tmp7, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp0, tmp4, tmp1, tmp5, in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec, tmp0, tmp4,
-                                    tmp1, tmp5);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp2, tmp6, tmp3, tmp7, in4, in5, in6, in7,
-                                    weight_vec, rnd_vec, offset_vec, tmp2, tmp6,
-                                    tmp3, tmp7);
-        PCKEV_B2_UB(tmp4, tmp0, tmp5, tmp1, out0, out1);
-        PCKEV_B2_UB(tmp6, tmp2, tmp7, tmp3, out2, out3);
-        ST_UB2(out0, out1, dst, 16);
-        dst += dst_stride;
-        ST_UB2(out2, out3, dst, 16);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_biwgt_copy_48w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2;
-    v16i8 src0, src1, src2;
-    v16i8 zero = { 0 };
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5, in0, in1, in2, in3, in4, in5;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = 64; loop_cnt--;) {
-        LD_SB3(src0_ptr, 16, src0, src1, src2);
-        src0_ptr += src_stride;
-        LD_SH6(src1_ptr, 8, in0, in1, in2, in3, in4, in5);
-        src1_ptr += src2_stride;
-
-        ILVRL_B2_SH(zero, src0, dst0, dst1);
-        ILVRL_B2_SH(zero, src1, dst2, dst3);
-        ILVRL_B2_SH(zero, src2, dst4, dst5);
-        SLLI_4V(dst0, dst1, dst2, dst3, 6);
-        SLLI_2V(dst4, dst5, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(dst0, dst1, dst2, dst3, in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec, dst0, dst1,
-                                    dst2, dst3);
-        HEVC_BIW_RND_CLIP2_MAX_SATU(dst4, dst5, in4, in5, weight_vec, rnd_vec,
-                                    offset_vec, dst4, dst5);
-        PCKEV_B3_UB(dst1, dst0, dst3, dst2, dst5, dst4, out0, out1, out2);
-        ST_UB2(out0, out1, dst, 16);
-        ST_UB(out2, dst + 32);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_biwgt_copy_64w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2, out3;
-    v16i8 zero = { 0 };
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v4i32 offset_vec, weight_vec, rnd_vec;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = height; loop_cnt--;) {
-        LD_SB4(src0_ptr, 16, src0, src1, src2, src3);
-        src0_ptr += src_stride;
-        LD_SH8(src1_ptr, 8, in0, in1, in2, in3, in4, in5, in6, in7);
-        src1_ptr += src2_stride;
-
-        ILVR_B4_SH(zero, src0, zero, src1, zero, src2, zero, src3, tmp0, tmp1,
-                   tmp2, tmp3);
-        ILVL_B4_SH(zero, src0, zero, src1, zero, src2, zero, src3, tmp4, tmp5,
-                   tmp6, tmp7);
-        SLLI_4V(tmp0, tmp1, tmp2, tmp3, 6);
-        SLLI_4V(tmp4, tmp5, tmp6, tmp7, 6);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp0, tmp4, tmp1, tmp5, in0, in1, in2, in3,
-                                    weight_vec, rnd_vec, offset_vec, tmp0, tmp4,
-                                    tmp1, tmp5);
-        HEVC_BIW_RND_CLIP4_MAX_SATU(tmp2, tmp6, tmp3, tmp7, in4, in5, in6, in7,
-                                    weight_vec, rnd_vec, offset_vec, tmp2, tmp6,
-                                    tmp3, tmp7);
-        PCKEV_B2_UB(tmp4, tmp0, tmp5, tmp1, out0, out1);
-        PCKEV_B2_UB(tmp6, tmp2, tmp7, tmp3, out2, out3);
-        ST_UB4(out0, out1, out2, out3, dst, 16);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_hz_biwgt_8t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 src0, src1, src2, src3;
-    v16i8 mask1, mask2, mask3;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filter_vec, out0, out1;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[16]);
-
-    src0_ptr -= 3;
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B4_SB(src0, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src3, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1);
-
-        out0 = (v8i16) __msa_pckev_b((v16i8) out1, (v16i8) out0);
-        ST_W4(out0, 0, 1, 2, 3, dst, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_8t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 src0, src1, src2, src3;
-    v16i8 mask1, mask2, mask3;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-
-    src0_ptr -= 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_8t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, vec0, vec1, vec2, vec3;
-    v16i8 mask0, mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v8i16 filt0, filt1, filt2, filt3, out0, out1, out2, out3;
-    v8i16 dst0, dst1, dst2, dst3, in0, in1, in2, in3, filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 3;
-
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset = (offset0 + offset1) << rnd_val;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-    mask4 = LD_SB(&ff_hevc_mask_arr[16]);
-    mask5 = mask4 + 2;
-    mask6 = mask4 + 4;
-    mask7 = mask4 + 6;
-
-    for (loop_cnt = 4; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3, in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec, out0, out1, out2,
-                           out3);
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-
-        LD_SB4(src0_ptr + 8, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr + 8, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-        VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7, vec0, vec1, vec2,
-                   vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src3, mask4, mask5, mask6, mask7, vec0, vec1, vec2,
-                   vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1, weight_vec, rnd_vec,
-                           offset_vec, out0, out1);
-        out0 = (v8i16) __msa_pckev_b((v16i8) out1, (v16i8) out0);
-        ST_W4(out0, 0, 1, 2, 3, dst + 8, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_8t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 mask1, mask2, mask3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-    v16i8 mask0 = { 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8 };
-
-    src0_ptr -= 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    for (loop_cnt = (height >> 1); loop_cnt--;) {
-        LD_SB2(src0_ptr, 8, src0, src1);
-        src0_ptr += src_stride;
-        LD_SB2(src0_ptr, 8, src2, src3);
-        src0_ptr += src_stride;
-        LD_SH2(src1_ptr, 8, in0, in1);
-        src1_ptr += src2_stride;
-        LD_SH2(src1_ptr, 8, in2, in3);
-        src1_ptr += src2_stride;
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_SH2(out0, out1, dst, dst_stride);
-        dst += (2 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_8t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    uint64_t dst_val0;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1;
-    v8i16 in0, in1, in2;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2;
-    v4i32 dst2_r, dst2_l;
-    v8i16 filter_vec, out0, out1, out2;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-
-    src0_ptr = src0_ptr - 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-    mask4 = mask0 + 8;
-    mask5 = mask0 + 10;
-    mask6 = mask0 + 12;
-    mask7 = mask0 + 14;
-
-    LD_SB2(src0_ptr, 16, src0, src1);
-    src0_ptr += src_stride;
-    LD_SH2(src1_ptr, 8, in0, in1);
-    in2 = LD_SH(src1_ptr + 16);
-    src1_ptr += src2_stride;
-    XORI_B2_128_SB(src0, src1);
-
-    for (loop_cnt = 31; loop_cnt--;) {
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1);
-
-        ILVRL_H2_SW(dst2, in2, dst2_r, dst2_l);
-        dst2_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_r,
-                                 (v8i16) weight_vec);
-        dst2_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_l,
-                                 (v8i16) weight_vec);
-        SRAR_W2_SW(dst2_r, dst2_l, rnd_vec);
-        CLIP_SW2_0_255(dst2_r, dst2_l);
-        out2 = __msa_pckev_h((v8i16) dst2_l, (v8i16) dst2_r);
-
-        LD_SB2(src0_ptr, 16, src0, src1);
-        src0_ptr += src_stride;
-        LD_SH2(src1_ptr, 8, in0, in1);
-        in2 = LD_SH(src1_ptr + 16);
-        src1_ptr += src2_stride;
-        XORI_B2_128_SB(src0, src1);
-        PCKEV_B2_SH(out1, out0, out2, out2, out0, out2);
-        dst_val0 = __msa_copy_u_d((v2i64) out2, 0);
-        ST_SH(out0, dst);
-        SD(dst_val0, dst + 16);
-        dst += dst_stride;
-    }
-
-    VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3, vec0, vec1, vec2, vec3);
-    dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                             filt3);
-    VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7, vec0, vec1, vec2, vec3);
-    dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                             filt3);
-    VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3, vec0, vec1, vec2, vec3);
-    dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                             filt3);
-    HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1, weight_vec, rnd_vec, offset_vec,
-                       out0, out1);
-    ILVRL_H2_SW(dst2, in2, dst2_r, dst2_l);
-    dst2_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_r, (v8i16) weight_vec);
-    dst2_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_l, (v8i16) weight_vec);
-    SRAR_W2_SW(dst2_r, dst2_l, rnd_vec);
-    CLIP_SW2_0_255(dst2_r, dst2_l);
-    out2 = __msa_pckev_h((v8i16) dst2_l, (v8i16) dst2_r);
-    PCKEV_B2_SH(out1, out0, out2, out2, out0, out2);
-    dst_val0 = __msa_copy_u_d((v2i64) out2, 0);
-    ST_SH(out0, dst);
-    SD(dst_val0, dst + 16);
-    dst += dst_stride;
-}
-
-static void hevc_hz_biwgt_8t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-    mask4 = mask0 + 8;
-    mask5 = mask0 + 10;
-    mask6 = mask0 + 12;
-    mask7 = mask0 + 14;
-
-    for (loop_cnt = height; loop_cnt--;) {
-        LD_SB2(src0_ptr, 16, src0, src1);
-        src2 = LD_SB(src0_ptr + 24);
-        src0_ptr += src_stride;
-        LD_SH4(src1_ptr, 8, in0, in1, in2, in3);
-        src1_ptr += src2_stride;
-
-        XORI_B3_128_SB(src0, src1, src2);
-
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_SH2(out0, out1, dst, 16);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_hz_biwgt_8t_48w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-    mask4 = mask0 + 8;
-    mask5 = mask0 + 10;
-    mask6 = mask0 + 12;
-    mask7 = mask0 + 14;
-
-    for (loop_cnt = 64; loop_cnt--;) {
-        LD_SB2(src0_ptr, 16, src0, src1);
-        src2 = LD_SB(src0_ptr + 24);
-        LD_SH4(src1_ptr, 8, in0, in1, in2, in3);
-        XORI_B3_128_SB(src0, src1, src2);
-        LD_SB2(src0_ptr + 32, 8, src3, src4);
-        src0_ptr += src_stride;
-        XORI_B2_128_SB(src3, src4);
-
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3, in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_SH2(out0, out1, dst, 16);
-
-        LD_SH2(src1_ptr + 32, 8, in2, in3);
-        src1_ptr += src2_stride;
-
-        VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        VSHF_B4_SB(src4, src4, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1);
-
-        out0 = (v8i16) __msa_pckev_b((v16i8) out1, (v16i8) out0);
-        ST_SH(out0, dst + 32);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_hz_biwgt_8t_64w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    const uint8_t *src0_ptr_tmp;
-    uint8_t *dst_tmp;
-    const int16_t *src1_ptr_tmp;
-    uint32_t loop_cnt, cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v16i8 vec0, vec1, vec2, vec3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 3;
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-    mask4 = mask0 + 8;
-    mask5 = mask0 + 10;
-    mask6 = mask0 + 12;
-    mask7 = mask0 + 14;
-
-    for (loop_cnt = height; loop_cnt--;) {
-        src0_ptr_tmp = src0_ptr;
-        dst_tmp = dst;
-        src1_ptr_tmp = src1_ptr;
-
-        for (cnt = 2; cnt--;) {
-            LD_SB2(src0_ptr_tmp, 16, src0, src1);
-            src2 = LD_SB(src0_ptr_tmp + 24);
-            src0_ptr_tmp += 32;
-            LD_SH4(src1_ptr_tmp, 8, in0, in1, in2, in3);
-            src1_ptr_tmp += 32;
-            XORI_B3_128_SB(src0, src1, src2);
-
-            VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                       vec0, vec1, vec2, vec3);
-            dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-            VSHF_B4_SB(src0, src1, mask4, mask5, mask6, mask7,
-                       vec0, vec1, vec2, vec3);
-            dst1 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-            VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                       vec0, vec1, vec2, vec3);
-            dst2 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-            VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                       vec0, vec1, vec2, vec3);
-            dst3 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-
-            HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                               in0, in1, in2, in3,
-                               weight_vec, rnd_vec, offset_vec,
-                               out0, out1, out2, out3);
-
-            PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-            ST_SH2(out0, out1, dst_tmp, 16);
-            dst_tmp += 32;
-        }
-
-        src0_ptr += src_stride;
-        src1_ptr += src2_stride;
-        dst += dst_stride;
-
-    }
-}
-
-static void hevc_vt_biwgt_8t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t res = height & 0x07;
-    int32_t offset, weight;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v16i8 src11, src12, src13, src14;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v16i8 src10_r, src32_r, src54_r, src76_r, src98_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r, src109_r;
-    v16i8 src1110_r, src1211_r, src1312_r, src1413_r;
-    v16i8 src2110, src4332, src6554, src8776, src10998;
-    v16i8 src12111110, src14131312;
-    v8i16 dst10, dst32, dst54, dst76;
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, weight1_vec, offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (3 * src_stride);
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_ldi_w(128);
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    weight1_vec = __msa_fill_w(weight1);
-    offset_vec += const_vec * weight1_vec;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr += (7 * src_stride);
-
-    ILVR_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-               src10_r, src32_r, src54_r, src21_r);
-    ILVR_B2_SB(src4, src3, src6, src5, src43_r, src65_r);
-    ILVR_D3_SB(src21_r, src10_r, src43_r, src32_r, src65_r, src54_r,
-               src2110, src4332, src6554);
-    XORI_B3_128_SB(src2110, src4332, src6554);
-
-    for (loop_cnt = (height >> 3); loop_cnt--;) {
-        LD_SB8(src0_ptr, src_stride,
-               src7, src8, src9, src10, src11, src12, src13, src14);
-        src0_ptr += (8 * src_stride);
-        LD_SH8(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5, in6, in7);
-        src1_ptr += (8 * src2_stride);
-
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        ILVR_D2_SH(in5, in4, in7, in6, in2, in3);
-        ILVR_B4_SB(src7, src6, src8, src7, src9, src8, src10, src9,
-                   src76_r, src87_r, src98_r, src109_r);
-        ILVR_B4_SB(src11, src10, src12, src11, src13, src12, src14, src13,
-                   src1110_r, src1211_r, src1312_r, src1413_r);
-        ILVR_D4_SB(src87_r, src76_r, src109_r, src98_r, src1211_r, src1110_r,
-                   src1413_r, src1312_r,
-                   src8776, src10998, src12111110, src14131312);
-        XORI_B4_128_SB(src8776, src10998, src12111110, src14131312);
-
-        DOTP_SB4_SH(src2110, src4332, src6554, src8776, filt0, filt0, filt0,
-                    filt0, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src4332, src6554, src8776, src10998, filt1, filt1, filt1,
-                     filt1, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src6554, src8776, src10998, src12111110, filt2, filt2,
-                     filt2, filt2, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src8776, src10998, src12111110, src14131312, filt3, filt3,
-                     filt3, filt3, dst10, dst32, dst54, dst76);
-
-        HEVC_BIW_RND_CLIP4(dst10, dst32, dst54, dst76,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-        dst += (8 * dst_stride);
-
-        src2110 = src10998;
-        src4332 = src12111110;
-        src6554 = src14131312;
-        src6 = src14;
-    }
-    if (res) {
-       LD_SB8(src0_ptr, src_stride,
-               src7, src8, src9, src10, src11, src12, src13, src14);
-        src0_ptr += (8 * src_stride);
-        LD_SH8(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5, in6, in7);
-        src1_ptr += (8 * src2_stride);
-
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        ILVR_D2_SH(in5, in4, in7, in6, in2, in3);
-        ILVR_B4_SB(src7, src6, src8, src7, src9, src8, src10, src9,
-                   src76_r, src87_r, src98_r, src109_r);
-        ILVR_B4_SB(src11, src10, src12, src11, src13, src12, src14, src13,
-                   src1110_r, src1211_r, src1312_r, src1413_r);
-        ILVR_D4_SB(src87_r, src76_r, src109_r, src98_r, src1211_r, src1110_r,
-                   src1413_r, src1312_r,
-                   src8776, src10998, src12111110, src14131312);
-        XORI_B4_128_SB(src8776, src10998, src12111110, src14131312);
-
-        DOTP_SB4_SH(src2110, src4332, src6554, src8776, filt0, filt0, filt0,
-                    filt0, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src4332, src6554, src8776, src10998, filt1, filt1, filt1,
-                     filt1, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src6554, src8776, src10998, src12111110, filt2, filt2,
-                     filt2, filt2, dst10, dst32, dst54, dst76);
-        DPADD_SB4_SH(src8776, src10998, src12111110, src14131312, filt3, filt3,
-                     filt3, filt3, dst10, dst32, dst54, dst76);
-
-        HEVC_BIW_RND_CLIP4(dst10, dst32, dst54, dst76,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-
-        src2110 = src10998;
-        src4332 = src12111110;
-        src6554 = src14131312;
-        src6 = src14;
-    }
-}
-
-static void hevc_vt_biwgt_8t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16i8 src0, src1, src2, src3, src4, src5;
-    v16i8 src6, src7, src8, src9, src10;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src54_r, src76_r, src98_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r, src109_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 filter_vec, out0, out1, out2, out3;
-    v4i32 weight_vec, weight1_vec, offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (3 * src_stride);
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_ldi_w(128);
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    weight1_vec = __msa_fill_w(weight1);
-    offset_vec += const_vec * weight1_vec;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr += (7 * src_stride);
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    ILVR_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-               src10_r, src32_r, src54_r, src21_r);
-    ILVR_B2_SB(src4, src3, src6, src5, src43_r, src65_r);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src7, src8, src9, src10);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-
-        XORI_B4_128_SB(src7, src8, src9, src10);
-        ILVR_B4_SB(src7, src6, src8, src7, src9, src8, src10, src9,
-                   src76_r, src87_r, src98_r, src109_r);
-
-        DOTP_SB4_SH(src10_r, src21_r, src32_r, src43_r, filt0, filt0, filt0,
-                    filt0, tmp0, tmp1, tmp2, tmp3);
-        DPADD_SB4_SH(src32_r, src43_r, src54_r, src65_r, filt1, filt1, filt1,
-                     filt1, tmp0, tmp1, tmp2, tmp3);
-        DPADD_SB4_SH(src54_r, src65_r, src76_r, src87_r, filt2, filt2, filt2,
-                     filt2, tmp0, tmp1, tmp2, tmp3);
-        DPADD_SB4_SH(src76_r, src87_r, src98_r, src109_r, filt3, filt3, filt3,
-                     filt3, tmp0, tmp1, tmp2, tmp3);
-
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1, out2, out3);
-
-        PCKEV_B2_SH(out1, out0, out3, out2, out0, out1);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-        dst += (4 * dst_stride);
-
-        src10_r = src54_r;
-        src32_r = src76_r;
-        src54_r = src98_r;
-        src21_r = src65_r;
-        src43_r = src87_r;
-        src65_r = src109_r;
-        src6 = src10;
-    }
-}
-
-static void hevc_vt_biwgt_8t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src54_r, src76_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r;
-    v8i16 tmp0, tmp1, tmp2;
-    v16i8 src10_l, src32_l, src54_l, src76_l;
-    v16i8 src21_l, src43_l, src65_l, src87_l;
-    v16i8 src2110, src4332, src6554, src8776;
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 out0, out1, out2, filter_vec;
-    v4i32 dst2_r, dst2_l;
-    v4i32 weight_vec, weight1_vec, offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (3 * src_stride);
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_ldi_w(128);
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    weight1_vec = __msa_fill_w(weight1);
-    offset_vec += const_vec * weight1_vec;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr += (7 * src_stride);
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    ILVR_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-               src10_r, src32_r, src54_r, src21_r);
-    ILVR_B2_SB(src4, src3, src6, src5, src43_r, src65_r);
-    ILVL_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-               src10_l, src32_l, src54_l, src21_l);
-    ILVL_B2_SB(src4, src3, src6, src5, src43_l, src65_l);
-    ILVR_D3_SB(src21_l, src10_l, src43_l, src32_l, src65_l, src54_l,
-               src2110, src4332, src6554);
-
-    for (loop_cnt = 8; loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src7, src8);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2((src1_ptr + 8), src2_stride, in2, in3);
-        src1_ptr += (2 * src2_stride);
-        in2 = (v8i16) __msa_ilvr_d((v2i64) in3, (v2i64) in2);
-        XORI_B2_128_SB(src7, src8);
-
-        ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-        ILVL_B2_SB(src7, src6, src8, src7, src76_l, src87_l);
-        src8776 = (v16i8) __msa_ilvr_d((v2i64) src87_l, (v2i64) src76_l);
-
-        DOTP_SB3_SH(src10_r, src21_r, src2110, filt0, filt0, filt0,
-                    tmp0, tmp1, tmp2);
-        DPADD_SB2_SH(src32_r, src43_r, filt1, filt1, tmp0, tmp1);
-        tmp2 = __msa_dpadd_s_h(tmp2, src4332, (v16i8) filt1);
-        DPADD_SB2_SH(src54_r, src65_r, filt2, filt2, tmp0, tmp1);
-        tmp2 = __msa_dpadd_s_h(tmp2, src6554, (v16i8) filt2);
-        DPADD_SB2_SH(src76_r, src87_r, filt3, filt3, tmp0, tmp1);
-        tmp2 = __msa_dpadd_s_h(tmp2, src8776, (v16i8) filt3);
-
-        HEVC_BIW_RND_CLIP2(tmp0, tmp1, in0, in1,
-                           weight_vec, rnd_vec, offset_vec,
-                           out0, out1);
-
-        ILVRL_H2_SW(tmp2, in2, dst2_r, dst2_l);
-        dst2_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_r,
-                                 (v8i16) weight_vec);
-        dst2_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst2_l,
-                                 (v8i16) weight_vec);
-        SRAR_W2_SW(dst2_r, dst2_l, rnd_vec);
-        CLIP_SW2_0_255(dst2_r, dst2_l);
-        out2 = __msa_pckev_h((v8i16) dst2_l, (v8i16) dst2_r);
-        PCKEV_B2_SH(out1, out0, out2, out2, out0, out2);
-        ST_D2(out0, 0, 1, dst, dst_stride);
-        ST_W2(out2, 0, 1, dst + 8, dst_stride);
-        dst += (2 * dst_stride);
-
-        src10_r = src32_r;
-        src32_r = src54_r;
-        src54_r = src76_r;
-        src21_r = src43_r;
-        src43_r = src65_r;
-        src65_r = src87_r;
-        src2110 = src4332;
-        src4332 = src6554;
-        src6554 = src8776;
-        src6 = src8;
-    }
-}
-
-static void hevc_vt_biwgt_8t_16multx2mult_msa(const uint8_t *src0_ptr,
-                                              int32_t src_stride,
-                                              const int16_t *src1_ptr,
-                                              int32_t src2_stride,
-                                              uint8_t *dst,
-                                              int32_t dst_stride,
-                                              const int8_t *filter,
-                                              int32_t height,
-                                              int32_t weight0,
-                                              int32_t weight1,
-                                              int32_t offset0,
-                                              int32_t offset1,
-                                              int32_t rnd_val,
-                                              int32_t width)
-{
-    const uint8_t *src0_ptr_tmp;
-    const int16_t *src1_ptr_tmp;
-    uint8_t *dst_tmp;
-    uint32_t loop_cnt, cnt;
-    int32_t offset, weight;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src54_r, src76_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r;
-    v16i8 src10_l, src32_l, src54_l, src76_l;
-    v16i8 src21_l, src43_l, src65_l, src87_l;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 filter_vec;
-    v8i16 out0, out1, out2, out3;
-    v4i32 weight_vec, weight1_vec, offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (3 * src_stride);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_ldi_w(128);
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    weight1_vec = __msa_fill_w(weight1);
-    offset_vec += const_vec * weight1_vec;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    for (cnt = (width >> 4); cnt--;) {
-        src0_ptr_tmp = src0_ptr;
-        src1_ptr_tmp = src1_ptr;
-        dst_tmp = dst;
-
-        LD_SB7(src0_ptr_tmp, src_stride,
-               src0, src1, src2, src3, src4, src5, src6);
-        src0_ptr_tmp += (7 * src_stride);
-
-        XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-        ILVR_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-                   src10_r, src32_r, src54_r, src21_r);
-        ILVR_B2_SB(src4, src3, src6, src5, src43_r, src65_r);
-        ILVL_B4_SB(src1, src0, src3, src2, src5, src4, src2, src1,
-                   src10_l, src32_l, src54_l, src21_l);
-        ILVL_B2_SB(src4, src3, src6, src5, src43_l, src65_l);
-
-        for (loop_cnt = (height >> 1); loop_cnt--;) {
-            LD_SB2(src0_ptr_tmp, src_stride, src7, src8);
-            src0_ptr_tmp += (2 * src_stride);
-            LD_SH2(src1_ptr_tmp, src2_stride, in0, in1);
-            LD_SH2((src1_ptr_tmp + 8), src2_stride, in2, in3);
-            src1_ptr_tmp += (2 * src2_stride);
-
-            XORI_B2_128_SB(src7, src8);
-            ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-            ILVL_B2_SB(src7, src6, src8, src7, src76_l, src87_l);
-
-            DOTP_SB4_SH(src10_r, src21_r, src10_l, src21_l, filt0, filt0,
-                        filt0, filt0, tmp0, tmp1, tmp2, tmp3);
-            DPADD_SB4_SH(src32_r, src43_r, src32_l, src43_l, filt1, filt1,
-                         filt1, filt1, tmp0, tmp1, tmp2, tmp3);
-            DPADD_SB4_SH(src54_r, src65_r, src54_l, src65_l, filt2, filt2,
-                         filt2, filt2, tmp0, tmp1, tmp2, tmp3);
-            DPADD_SB4_SH(src76_r, src87_r, src76_l, src87_l, filt3, filt3,
-                         filt3, filt3, tmp0, tmp1, tmp2, tmp3);
-
-            HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                               in0, in1, in2, in3,
-                               weight_vec, rnd_vec, offset_vec,
-                               out0, out1, out2, out3);
-
-            PCKEV_B2_SH(out2, out0, out3, out1, out0, out1);
-            ST_SH2(out0, out1, dst_tmp, dst_stride);
-            dst_tmp += (2 * dst_stride);
-
-            src10_r = src32_r;
-            src32_r = src54_r;
-            src54_r = src76_r;
-            src21_r = src43_r;
-            src43_r = src65_r;
-            src65_r = src87_r;
-            src10_l = src32_l;
-            src32_l = src54_l;
-            src54_l = src76_l;
-            src21_l = src43_l;
-            src43_l = src65_l;
-            src65_l = src87_l;
-            src6 = src8;
-        }
-
-        src0_ptr += 16;
-        src1_ptr += 16;
-        dst += 16;
-    }
-}
-
-static void hevc_vt_biwgt_8t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_vt_biwgt_8t_16multx2mult_msa(src0_ptr, src_stride,
-                                      src1_ptr, src2_stride,
-                                      dst, dst_stride, filter, height,
-                                      weight0, weight1, offset0, offset1,
-                                      rnd_val, 16);
-}
-
-static void hevc_vt_biwgt_8t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_vt_biwgt_8t_16multx2mult_msa(src0_ptr, src_stride,
-                                      src1_ptr, src2_stride,
-                                      dst, dst_stride, filter, height,
-                                      weight0, weight1, offset0, offset1,
-                                      rnd_val, 16);
-    hevc_vt_biwgt_8t_8w_msa(src0_ptr + 16, src_stride,
-                            src1_ptr + 16, src2_stride,
-                            dst + 16, dst_stride, filter, height,
-                            weight0, weight1, offset0, offset1, rnd_val);
-}
-
-static void hevc_vt_biwgt_8t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_vt_biwgt_8t_16multx2mult_msa(src0_ptr, src_stride,
-                                      src1_ptr, src2_stride,
-                                      dst, dst_stride, filter, height,
-                                      weight0, weight1, offset0, offset1,
-                                      rnd_val, 32);
-}
-
-static void hevc_vt_biwgt_8t_48w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_vt_biwgt_8t_16multx2mult_msa(src0_ptr, src_stride,
-                                      src1_ptr, src2_stride,
-                                      dst, dst_stride, filter, height,
-                                      weight0, weight1, offset0, offset1,
-                                      rnd_val, 48);
-}
-
-static void hevc_vt_biwgt_8t_64w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_vt_biwgt_8t_16multx2mult_msa(src0_ptr, src_stride,
-                                      src1_ptr, src2_stride,
-                                      dst, dst_stride, filter, height,
-                                      weight0, weight1, offset0, offset1,
-                                      rnd_val, 64);
-}
-
-static void hevc_hv_biwgt_8t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter_x,
-                                    const int8_t *filter_y,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    v16u8 out;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v8i16 in0 = { 0 }, in1 = { 0 };
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 filt_h0, filt_h1, filt_h2, filt_h3;
-    v16i8 mask1, mask2, mask3;
-    v8i16 filter_vec, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 vec8, vec9, vec10, vec11, vec12, vec13, vec14, vec15;
-    v8i16 dst30, dst41, dst52, dst63, dst66, dst87;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 dst10, dst32, dst54, dst76;
-    v8i16 dst21, dst43, dst65, dst97, dst108, dst109, dst98;
-    v4i32 offset_vec, rnd_vec, const_vec, dst0, dst1, dst2, dst3;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr + 16);
-
-    src0_ptr -= ((3 * src_stride) + 3);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W4_SH(filter_vec, filt_h0, filt_h1, filt_h2, filt_h3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-    weight_vec = (v8i16) __msa_fill_w(weight);
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr += (7 * src_stride);
-
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    VSHF_B4_SB(src0, src3, mask0, mask1, mask2, mask3, vec0, vec1, vec2, vec3);
-    VSHF_B4_SB(src1, src4, mask0, mask1, mask2, mask3, vec4, vec5, vec6, vec7);
-    VSHF_B4_SB(src2, src5, mask0, mask1, mask2, mask3,
-               vec8, vec9, vec10, vec11);
-    VSHF_B4_SB(src3, src6, mask0, mask1, mask2, mask3,
-               vec12, vec13, vec14, vec15);
-
-    dst30 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                              filt3);
-    dst41 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                              filt3);
-    dst52 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                              filt3);
-    dst63 = HEVC_FILT_8TAP_SH(vec12, vec13, vec14, vec15, filt0, filt1, filt2,
-                              filt3);
-
-    ILVRL_H2_SH(dst41, dst30, dst10, dst43);
-    ILVRL_H2_SH(dst52, dst41, dst21, dst54);
-    ILVRL_H2_SH(dst63, dst52, dst32, dst65);
-
-    dst66 = (v8i16) __msa_splati_d((v2i64) dst63, 1);
-
-    for (loop_cnt = height >> 2; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src7, src8, src9, src10);
-        src0_ptr += (4 * src_stride);
-        XORI_B4_128_SB(src7, src8, src9, src10);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        INSERT_D2_SH(tp0, tp1, in0);
-        src1_ptr += (2 * src2_stride);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        INSERT_D2_SH(tp0, tp1, in1);
-        src1_ptr += (2 * src2_stride);
-
-        VSHF_B4_SB(src7, src9, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        VSHF_B4_SB(src8, src10, mask0, mask1, mask2, mask3,
-                   vec4, vec5, vec6, vec7);
-        dst97 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                  filt3);
-        dst108 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                                   filt3);
-
-        dst76 = __msa_ilvr_h(dst97, dst66);
-        ILVRL_H2_SH(dst108, dst97, dst87, dst109);
-        dst66 = (v8i16) __msa_splati_d((v2i64) dst97, 1);
-        dst98 = __msa_ilvr_h(dst66, dst108);
-
-        dst0 = HEVC_FILT_8TAP(dst10, dst32, dst54, dst76, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst1 = HEVC_FILT_8TAP(dst21, dst43, dst65, dst87, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst2 = HEVC_FILT_8TAP(dst32, dst54, dst76, dst98, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst3 = HEVC_FILT_8TAP(dst43, dst65, dst87, dst109, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        SRA_4V(dst0, dst1, dst2, dst3, 6);
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp1, tmp3);
-        ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-        ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp0, tmp1);
-        out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-        ST_W4(out, 0, 1, 2, 3, dst, dst_stride);
-        dst += (4 * dst_stride);
-
-        dst10 = dst54;
-        dst32 = dst76;
-        dst54 = dst98;
-        dst21 = dst65;
-        dst43 = dst87;
-        dst65 = dst109;
-        dst66 = (v8i16) __msa_splati_d((v2i64) dst108, 1);
-    }
-}
-
-static void hevc_hv_biwgt_8t_8multx2mult_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter_x,
-                                             const int8_t *filter_y,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val,
-                                             int32_t width8mult)
-{
-    uint32_t loop_cnt, cnt;
-    int32_t offset, weight;
-    const uint8_t *src0_ptr_tmp;
-    const int16_t *src1_ptr_tmp;
-    uint8_t *dst_tmp;
-    v16u8 out;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8;
-    v8i16 in0, in1;
-    v8i16 filt0, filt1, filt2, filt3;
-    v8i16 filt_h0, filt_h1, filt_h2, filt_h3;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1, mask2, mask3;
-    v8i16 filter_vec, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 vec8, vec9, vec10, vec11, vec12, vec13, vec14, vec15;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7, dst8;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 dst10_r, dst32_r, dst54_r, dst76_r;
-    v8i16 dst10_l, dst32_l, dst54_l, dst76_l;
-    v8i16 dst21_r, dst43_r, dst65_r, dst87_r;
-    v8i16 dst21_l, dst43_l, dst65_l, dst87_l;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= ((3 * src_stride) + 3);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-    weight_vec = (v8i16) __msa_fill_w(weight);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W4_SH(filter_vec, filt_h0, filt_h1, filt_h2, filt_h3);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    for (cnt = width8mult; cnt--;) {
-        src0_ptr_tmp = src0_ptr;
-        src1_ptr_tmp = src1_ptr;
-        dst_tmp = dst;
-
-        LD_SB7(src0_ptr_tmp, src_stride,
-               src0, src1, src2, src3, src4, src5, src6);
-        src0_ptr_tmp += (7 * src_stride);
-
-        XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-        /* row 0 row 1 row 2 row 3 */
-        VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3,
-                   vec4, vec5, vec6, vec7);
-        VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3,
-                   vec8, vec9, vec10, vec11);
-        VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3,
-                   vec12, vec13, vec14, vec15);
-
-        dst0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        dst1 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                                 filt3);
-        dst2 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                                 filt3);
-        dst3 = HEVC_FILT_8TAP_SH(vec12, vec13, vec14, vec15, filt0, filt1,
-                                 filt2, filt3);
-
-        /* row 4 row 5 row 6 */
-        VSHF_B4_SB(src4, src4, mask0, mask1, mask2, mask3,
-                   vec0, vec1, vec2, vec3);
-        VSHF_B4_SB(src5, src5, mask0, mask1, mask2, mask3,
-                   vec4, vec5, vec6, vec7);
-        VSHF_B4_SB(src6, src6, mask0, mask1, mask2, mask3,
-                   vec8, vec9, vec10, vec11);
-
-        dst4 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                 filt3);
-        dst5 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                                 filt3);
-        dst6 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                                 filt3);
-
-        for (loop_cnt = height >> 1; loop_cnt--;) {
-            LD_SB2(src0_ptr_tmp, src_stride, src7, src8);
-            XORI_B2_128_SB(src7, src8);
-            src0_ptr_tmp += 2 * src_stride;
-
-            LD_SH2(src1_ptr_tmp, src2_stride, in0, in1);
-            src1_ptr_tmp += (2 * src2_stride);
-
-            ILVR_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst2, dst1, dst10_r,
-                       dst32_r, dst54_r, dst21_r);
-            ILVL_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst2, dst1, dst10_l,
-                       dst32_l, dst54_l, dst21_l);
-            ILVR_H2_SH(dst4, dst3, dst6, dst5, dst43_r, dst65_r);
-            ILVL_H2_SH(dst4, dst3, dst6, dst5, dst43_l, dst65_l);
-
-            VSHF_B4_SB(src7, src7, mask0, mask1, mask2, mask3,
-                       vec0, vec1, vec2, vec3);
-            dst7 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-
-            ILVRL_H2_SH(dst7, dst6, dst76_r, dst76_l);
-            dst0_r = HEVC_FILT_8TAP(dst10_r, dst32_r, dst54_r, dst76_r,
-                                    filt_h0, filt_h1, filt_h2, filt_h3);
-            dst0_l = HEVC_FILT_8TAP(dst10_l, dst32_l, dst54_l, dst76_l,
-                                    filt_h0, filt_h1, filt_h2, filt_h3);
-
-            dst0_r >>= 6;
-            dst0_l >>= 6;
-
-            /* row 8 */
-            VSHF_B4_SB(src8, src8, mask0, mask1, mask2, mask3,
-                       vec0, vec1, vec2, vec3);
-            dst8 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1,
-                                     filt2, filt3);
-
-            ILVRL_H2_SH(dst8, dst7, dst87_r, dst87_l);
-            dst1_r = HEVC_FILT_8TAP(dst21_r, dst43_r, dst65_r, dst87_r,
-                                    filt_h0, filt_h1, filt_h2, filt_h3);
-            dst1_l = HEVC_FILT_8TAP(dst21_l, dst43_l, dst65_l, dst87_l,
-                                    filt_h0, filt_h1, filt_h2, filt_h3);
-
-            dst1_r >>= 6;
-            dst1_l >>= 6;
-
-            PCKEV_H2_SH(dst0_l, dst0_r, dst1_l, dst1_r, tmp1, tmp3);
-            ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-            ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-            dst0_r = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-            dst0_l = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-            dst1_r = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-            dst1_l = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-            SRAR_W4_SW(dst0_l, dst0_r, dst1_l, dst1_r, rnd_vec);
-            CLIP_SW4_0_255(dst0_l, dst0_r, dst1_l, dst1_r);
-            PCKEV_H2_SH(dst0_l, dst0_r, dst1_l, dst1_r, tmp0, tmp1);
-            out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-            ST_D2(out, 0, 1, dst_tmp, dst_stride);
-            dst_tmp += (2 * dst_stride);
-
-            dst0 = dst2;
-            dst1 = dst3;
-            dst2 = dst4;
-            dst3 = dst5;
-            dst4 = dst6;
-            dst5 = dst7;
-            dst6 = dst8;
-        }
-
-        src0_ptr += 8;
-        src1_ptr += 8;
-        dst += 8;
-    }
-}
-
-static void hevc_hv_biwgt_8t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter_x,
-                                    const int8_t *filter_y,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 1);
-}
-
-static void hevc_hv_biwgt_8t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    const uint8_t *src0_ptr_tmp;
-    uint8_t *dst_tmp;
-    const int16_t *src1_ptr_tmp;
-    int32_t offset, weight;
-    uint64_t tp0, tp1;
-    v16u8 out;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 vec8, vec9, vec10, vec11, vec12, vec13, vec14, vec15;
-    v16i8 mask0, mask1, mask2, mask3, mask4, mask5, mask6, mask7;
-    v8i16 in0 = { 0 }, in1 = { 0 };
-    v8i16 filter_vec, weight_vec, tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1, filt2, filt3, filt_h0, filt_h1, filt_h2, filt_h3;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6, dsth7, dsth8;
-    v8i16 dst10_r, dst32_r, dst54_r, dst76_r, dst21_r, dst43_r, dst65_r;
-    v8i16 dst10_l, dst32_l, dst54_l, dst76_l, dst21_l, dst43_l, dst65_l;
-    v8i16 dst30, dst41, dst52, dst63, dst66, dst87, dst10, dst32, dst54, dst76;
-    v8i16 dst21, dst43, dst65, dst97, dst108, dst109, dst98, dst87_r, dst87_l;
-    v4i32 offset_vec, rnd_vec, const_vec, dst0, dst1, dst2, dst3;
-
-    src0_ptr -= ((3 * src_stride) + 3);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-    weight_vec = (v8i16) __msa_fill_w(weight);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H4_SH(filter_vec, 0, 1, 2, 3, filt0, filt1, filt2, filt3);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W4_SH(filter_vec, filt_h0, filt_h1, filt_h2, filt_h3);
-
-    mask0 = LD_SB(ff_hevc_mask_arr);
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 4;
-    mask3 = mask0 + 6;
-
-    src0_ptr_tmp = src0_ptr;
-    src1_ptr_tmp = src1_ptr;
-    dst_tmp = dst;
-
-    LD_SB7(src0_ptr_tmp, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr_tmp += (7 * src_stride);
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    VSHF_B4_SB(src0, src0, mask0, mask1, mask2, mask3, vec0, vec1, vec2, vec3);
-    VSHF_B4_SB(src1, src1, mask0, mask1, mask2, mask3, vec4, vec5, vec6, vec7);
-    VSHF_B4_SB(src2, src2, mask0, mask1, mask2, mask3, vec8, vec9, vec10,
-               vec11);
-    VSHF_B4_SB(src3, src3, mask0, mask1, mask2, mask3, vec12, vec13, vec14,
-               vec15);
-    dsth0 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                              filt3);
-    dsth1 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                              filt3);
-    dsth2 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                              filt3);
-    dsth3 = HEVC_FILT_8TAP_SH(vec12, vec13, vec14, vec15, filt0, filt1,
-                              filt2, filt3);
-    VSHF_B4_SB(src4, src4, mask0, mask1, mask2, mask3, vec0, vec1, vec2, vec3);
-    VSHF_B4_SB(src5, src5, mask0, mask1, mask2, mask3, vec4, vec5, vec6, vec7);
-    VSHF_B4_SB(src6, src6, mask0, mask1, mask2, mask3, vec8, vec9, vec10,
-               vec11);
-    dsth4 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                              filt3);
-    dsth5 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                              filt3);
-    dsth6 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                              filt3);
-
-    for (loop_cnt = 8; loop_cnt--;) {
-        LD_SB2(src0_ptr_tmp, src_stride, src7, src8);
-        src0_ptr_tmp += (2 * src_stride);
-        XORI_B2_128_SB(src7, src8);
-
-        LD_SH2(src1_ptr_tmp, src2_stride, in0, in1);
-        src1_ptr_tmp += (2 * src2_stride);
-
-        ILVR_H4_SH(dsth1, dsth0, dsth3, dsth2, dsth5, dsth4, dsth2, dsth1,
-                   dst10_r, dst32_r, dst54_r, dst21_r);
-        ILVL_H4_SH(dsth1, dsth0, dsth3, dsth2, dsth5, dsth4, dsth2, dsth1,
-                   dst10_l, dst32_l, dst54_l, dst21_l);
-        ILVR_H2_SH(dsth4, dsth3, dsth6, dsth5, dst43_r, dst65_r);
-        ILVL_H2_SH(dsth4, dsth3, dsth6, dsth5, dst43_l, dst65_l);
-
-        VSHF_B4_SB(src7, src7, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dsth7 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                  filt3);
-
-        ILVRL_H2_SH(dsth7, dsth6, dst76_r, dst76_l);
-        dst0 = HEVC_FILT_8TAP(dst10_r, dst32_r, dst54_r, dst76_r, filt_h0,
-                              filt_h1, filt_h2, filt_h3);
-        dst1 = HEVC_FILT_8TAP(dst10_l, dst32_l, dst54_l, dst76_l, filt_h0,
-                              filt_h1, filt_h2, filt_h3);
-        dst0 >>= 6;
-        dst1 >>= 6;
-
-        VSHF_B4_SB(src8, src8, mask0, mask1, mask2, mask3, vec0, vec1, vec2,
-                   vec3);
-        dsth8 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                  filt3);
-
-        ILVRL_H2_SH(dsth8, dsth7, dst87_r, dst87_l);
-        dst2 = HEVC_FILT_8TAP(dst21_r, dst43_r, dst65_r, dst87_r, filt_h0,
-                              filt_h1, filt_h2, filt_h3);
-        dst3 = HEVC_FILT_8TAP(dst21_l, dst43_l, dst65_l, dst87_l, filt_h0,
-                              filt_h1, filt_h2, filt_h3);
-        dst2 >>= 6;
-        dst3 >>= 6;
-
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp1, tmp3);
-        ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-        ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        SRAR_W4_SW(dst1, dst0, dst3, dst2, rnd_vec);
-        CLIP_SW4_0_255(dst1, dst0, dst3, dst2);
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp0, tmp1);
-        out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-        ST_D2(out, 0, 1, dst_tmp, dst_stride);
-        dst_tmp += (2 * dst_stride);
-
-        dsth0 = dsth2;
-        dsth1 = dsth3;
-        dsth2 = dsth4;
-        dsth3 = dsth5;
-        dsth4 = dsth6;
-        dsth5 = dsth7;
-        dsth6 = dsth8;
-    }
-
-    src0_ptr += 8;
-    src1_ptr += 8;
-    dst += 8;
-
-    mask4 = LD_SB(ff_hevc_mask_arr + 16);
-    mask5 = mask4 + 2;
-    mask6 = mask4 + 4;
-    mask7 = mask4 + 6;
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    src0_ptr += (7 * src_stride);
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    VSHF_B4_SB(src0, src3, mask4, mask5, mask6, mask7, vec0, vec1, vec2, vec3);
-    VSHF_B4_SB(src1, src4, mask4, mask5, mask6, mask7, vec4, vec5, vec6, vec7);
-    VSHF_B4_SB(src2, src5, mask4, mask5, mask6, mask7, vec8, vec9, vec10,
-               vec11);
-    VSHF_B4_SB(src3, src6, mask4, mask5, mask6, mask7, vec12, vec13, vec14,
-               vec15);
-    dst30 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                              filt3);
-    dst41 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                              filt3);
-    dst52 = HEVC_FILT_8TAP_SH(vec8, vec9, vec10, vec11, filt0, filt1, filt2,
-                              filt3);
-    dst63 = HEVC_FILT_8TAP_SH(vec12, vec13, vec14, vec15, filt0, filt1, filt2,
-                              filt3);
-    ILVRL_H2_SH(dst41, dst30, dst10, dst43);
-    ILVRL_H2_SH(dst52, dst41, dst21, dst54);
-    ILVRL_H2_SH(dst63, dst52, dst32, dst65);
-
-    dst66 = (v8i16) __msa_splati_d((v2i64) dst63, 1);
-
-    for (loop_cnt = 4; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src7, src8, src9, src10);
-        src0_ptr += (4 * src_stride);
-        XORI_B4_128_SB(src7, src8, src9, src10);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        INSERT_D2_SH(tp0, tp1, in0);
-        src1_ptr += (2 * src2_stride);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        INSERT_D2_SH(tp0, tp1, in1);
-        src1_ptr += (2 * src2_stride);
-
-        VSHF_B4_SB(src7, src9, mask4, mask5, mask6, mask7, vec0, vec1, vec2,
-                   vec3);
-        VSHF_B4_SB(src8, src10, mask4, mask5, mask6, mask7, vec4, vec5, vec6,
-                   vec7);
-        dst97 = HEVC_FILT_8TAP_SH(vec0, vec1, vec2, vec3, filt0, filt1, filt2,
-                                  filt3);
-        dst108 = HEVC_FILT_8TAP_SH(vec4, vec5, vec6, vec7, filt0, filt1, filt2,
-                                   filt3);
-
-        dst76 = __msa_ilvr_h(dst97, dst66);
-        ILVRL_H2_SH(dst108, dst97, dst87, dst109);
-        dst66 = (v8i16) __msa_splati_d((v2i64) dst97, 1);
-        dst98 = __msa_ilvr_h(dst66, dst108);
-
-        dst0 = HEVC_FILT_8TAP(dst10, dst32, dst54, dst76, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst1 = HEVC_FILT_8TAP(dst21, dst43, dst65, dst87, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst2 = HEVC_FILT_8TAP(dst32, dst54, dst76, dst98, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        dst3 = HEVC_FILT_8TAP(dst43, dst65, dst87, dst109, filt_h0, filt_h1,
-                              filt_h2, filt_h3);
-        SRA_4V(dst0, dst1, dst2, dst3, 6);
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp1, tmp3);
-        ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-        ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp0, tmp1);
-        out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-        ST_W4(out, 0, 1, 2, 3, dst, dst_stride);
-        dst += (4 * dst_stride);
-
-        dst10 = dst54;
-        dst32 = dst76;
-        dst54 = dst98;
-        dst21 = dst65;
-        dst43 = dst87;
-        dst65 = dst109;
-        dst66 = (v8i16) __msa_splati_d((v2i64) dst108, 1);
-    }
-}
-
-static void hevc_hv_biwgt_8t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 2);
-}
-
-static void hevc_hv_biwgt_8t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 3);
-}
-
-static void hevc_hv_biwgt_8t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 4);
-}
-
-static void hevc_hv_biwgt_8t_48w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 6);
-}
-
-static void hevc_hv_biwgt_8t_64w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_8t_8multx2mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride, filter_x, filter_y,
-                                     height, weight0, weight1, offset0,
-                                     offset1, rnd_val, 8);
-}
-
-static void hevc_hz_biwgt_4t_4x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1;
-    v8i16 in0, in1;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[16]);
-    v16i8 mask1, vec0, vec1;
-    v8i16 dst0;
-    v4i32 dst0_r, dst0_l;
-    v8i16 out0, filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    LD_SB2(src0_ptr, src_stride, src0, src1);
-    LD_SH2(src1_ptr, src2_stride, in0, in1);
-    in0 = (v8i16) __msa_ilvr_d((v2i64) in1, (v2i64) in0);
-    XORI_B2_128_SB(src0, src1);
-
-    VSHF_B2_SB(src0, src1, src0, src1, mask0, mask1, vec0, vec1);
-    dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-
-    ILVRL_H2_SW(dst0, in0, dst0_r, dst0_l);
-    dst0_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst0_r, (v8i16) weight_vec);
-    dst0_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst0_l, (v8i16) weight_vec);
-    SRAR_W2_SW(dst0_r, dst0_l, rnd_vec);
-    out0 = __msa_pckev_h((v8i16) dst0_l, (v8i16) dst0_r);
-    CLIP_SH_0_255(out0);
-    out0 = (v8i16) __msa_pckev_b((v16i8) out0, (v16i8) out0);
-    ST_W2(out0, 0, 1, dst, dst_stride);
-}
-
-static void hevc_hz_biwgt_4t_4x4_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[16]);
-    v16i8 mask1;
-    v8i16 dst0, dst1;
-    v16i8 vec0, vec1;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    /* rearranging filter */
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-    XORI_B4_128_SB(src0, src1, src2, src3);
-    LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-    ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-
-    VSHF_B2_SB(src0, src1, src0, src1, mask0, mask1, vec0, vec1);
-    dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src2, src3, src2, src3, mask0, mask1, vec0, vec1);
-    dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1,
-                       weight_vec, rnd_vec, offset_vec,
-                       dst0, dst1);
-
-    dst0 = (v8i16) __msa_pckev_b((v16i8) dst1, (v16i8) dst0);
-    ST_W4(dst0, 0, 1, 2, 3, dst, dst_stride);
-}
-
-static void hevc_hz_biwgt_4t_4x8multiple_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t weight, offset, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[16]);
-    v16i8 mask1;
-    v16i8 vec0, vec1;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    for (loop_cnt = (height >> 3); loop_cnt--;) {
-        LD_SB8(src0_ptr, src_stride,
-               src0, src1, src2, src3, src4, src5, src6, src7);
-        src0_ptr += (8 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        LD_SH4(src1_ptr, src2_stride, in4, in5, in6, in7);
-        src1_ptr += (4 * src2_stride);
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        ILVR_D2_SH(in5, in4, in7, in6, in2, in3);
-        XORI_B8_128_SB(src0, src1, src2, src3, src4, src5, src6, src7);
-
-        VSHF_B2_SB(src0, src1, src0, src1, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src3, src2, src3, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src4, src5, src4, src5, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src6, src7, src6, src7, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_W8(dst0, dst1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-        dst += (8 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_hz_biwgt_4t_4x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (4 == height) {
-        hevc_hz_biwgt_4t_4x4_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (0 == (height % 8)) {
-        hevc_hz_biwgt_4t_4x8multiple_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter, height,
-                                         weight0, weight1, offset0, offset1,
-                                         rnd_val);
-    }
-}
-
-static void hevc_hz_biwgt_4t_6w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1;
-    v16i8 vec0, vec1;
-    v8i16 in0, in1, in2, in3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    for (loop_cnt = 2; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_W2(dst0, 0, 2, dst, dst_stride);
-        ST_H2(dst0, 2, 6, dst + 4, dst_stride);
-        ST_W2(dst1, 0, 2, dst + 2 * dst_stride, dst_stride);
-        ST_H2(dst1, 2, 6, dst + 2 * dst_stride + 4, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_8x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1;
-    v8i16 in0, in1;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, vec0, vec1;
-    v8i16 dst0, dst1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    LD_SB2(src0_ptr, src_stride, src0, src1);
-    LD_SH2(src1_ptr, src2_stride, in0, in1);
-    XORI_B2_128_SB(src0, src1);
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-    dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    HEVC_BIW_RND_CLIP2(dst0, dst1, in0, in1,
-                       weight_vec, rnd_vec, offset_vec,
-                       dst0, dst1);
-
-    dst0 = (v8i16) __msa_pckev_b((v16i8) dst1, (v16i8) dst0);
-    ST_D2(dst0, 0, 1, dst, dst_stride);
-}
-
-static void hevc_hz_biwgt_4t_8x6_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t weight, offset, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3, src4, src5;
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1;
-    v16i8 vec0, vec1;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    LD_SB6(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5);
-
-    LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-    src1_ptr += (4 * src2_stride);
-    LD_SH2(src1_ptr, src2_stride, in4, in5);
-    XORI_B6_128_SB(src0, src1, src2, src3, src4, src5);
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-    dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-    dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-    dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec0, vec1);
-    dst4 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec0, vec1);
-    dst5 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                       in0, in1, in2, in3,
-                       weight_vec, rnd_vec, offset_vec,
-                       dst0, dst1, dst2, dst3);
-    HEVC_BIW_RND_CLIP2(dst4, dst5, in4, in5,
-                       weight_vec, rnd_vec, offset_vec,
-                       dst4, dst5);
-
-    PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-    dst3 = (v8i16) __msa_pckev_b((v16i8) dst5, (v16i8) dst4);
-    ST_D4(dst0, dst1, 0, 1, 0, 1, dst, dst_stride);
-    ST_D2(dst3, 0, 1, dst + 4 * dst_stride, dst_stride);
-}
-
-static void hevc_hz_biwgt_4t_8x4multiple_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1;
-    v16i8 vec0, vec1;
-    v8i16 in0, in1, in2, in3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_D4(dst0, dst1, 0, 1, 0, 1, dst, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_hz_biwgt_4t_8x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (6 == height) {
-        hevc_hz_biwgt_4t_8x6_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (0 == (height % 4)) {
-        hevc_hz_biwgt_4t_8x4multiple_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter, height,
-                                         weight0, weight1, offset0, offset1,
-                                         rnd_val);
-    }
-}
-
-static void hevc_hz_biwgt_4t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v8i16 filt0, filt1;
-    v16i8 src0, src1, src2, src3;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask2 = {
-        8, 9, 9, 10, 10, 11, 11, 12, 24, 25, 25, 26, 26, 27, 27, 28
-    };
-    v16i8 mask1, mask3;
-    v16i8 vec0, vec1;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-    mask3 = mask2 + 2;
-
-    for (loop_cnt = 4; loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src1, src2, src3);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        LD_SH4(src1_ptr + 8, src2_stride, in4, in5, in6, in7);
-        src1_ptr += (4 * src2_stride);
-        ILVR_D2_SH(in5, in4, in7, in6, in4, in5);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src0, src1, src0, src1, mask2, mask3, vec0, vec1);
-        dst4 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src3, src2, src3, mask2, mask3, vec0, vec1);
-        dst5 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-        HEVC_BIW_RND_CLIP2(dst4, dst5, in4, in5,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst4, dst5);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        dst3 = (v8i16) __msa_pckev_b((v16i8) dst5, (v16i8) dst4);
-        ST_D4(dst0, dst1, 0, 1, 0, 1, dst, dst_stride);
-        ST_W4(dst3, 0, 1, 2, 3, dst + 8, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v8i16 filt0, filt1;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1;
-    v8i16 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v16i8 vec0, vec1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB4(src0_ptr, src_stride, src0, src2, src4, src6);
-        LD_SB4(src0_ptr + 8, src_stride, src1, src3, src5, src7);
-        src0_ptr += (4 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in2, in4, in6);
-        LD_SH4(src1_ptr + 8, src2_stride, in1, in3, in5, in7);
-        src1_ptr += (4 * src2_stride);
-        XORI_B8_128_SB(src0, src1, src2, src3, src4, src5, src6, src7);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec0, vec1);
-        dst4 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec0, vec1);
-        dst5 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec0, vec1);
-        dst6 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src7, src7, src7, src7, mask0, mask1, vec0, vec1);
-        dst7 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_SH2(dst0, dst1, dst, dst_stride);
-        dst += (2 * dst_stride);
-
-        HEVC_BIW_RND_CLIP4(dst4, dst5, dst6, dst7,
-                           in4, in5, in6, in7,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_SH2(dst0, dst1, dst, dst_stride);
-        dst += (2 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3;
-    v8i16 filt0, filt1;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, mask2, mask3;
-    v16i8 vec0, vec1;
-    v8i16 dst0, dst1, dst2, dst3;
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 8;
-    mask3 = mask0 + 10;
-
-    for (loop_cnt = 16; loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src0, src2);
-        LD_SB2(src0_ptr + 16, src_stride, src1, src3);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr, src2_stride, in0, in2);
-        LD_SH2(src1_ptr + 8, src2_stride, in1, in3);
-        LD_SH2(src1_ptr + 16, src2_stride, in4, in5);
-        src1_ptr += (2 * src2_stride);
-        XORI_B4_128_SB(src0, src1, src2, src3);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src0, src1, src0, src1, mask2, mask3, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src3, src2, src3, mask2, mask3, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_SH2(dst0, dst1, dst, dst_stride);
-
-        /* 8 width */
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP2(dst0, dst1, in4, in5,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1);
-
-        dst0 = (v8i16) __msa_pckev_b((v16i8) dst1, (v16i8) dst0);
-        ST_D2(dst0, 0, 1, (dst + 16), dst_stride);
-        dst += (2 * dst_stride);
-    }
-}
-
-static void hevc_hz_biwgt_4t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2;
-    v8i16 filt0, filt1;
-    v16i8 mask0 = LD_SB(&ff_hevc_mask_arr[0]);
-    v16i8 mask1, mask2, mask3;
-    v8i16 dst0, dst1, dst2, dst3;
-    v16i8 vec0, vec1;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= 1;
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    mask1 = mask0 + 2;
-    mask2 = mask0 + 8;
-    mask3 = mask0 + 10;
-
-    for (loop_cnt = height; loop_cnt--;) {
-        LD_SB2(src0_ptr, 16, src0, src1);
-        src2 = LD_SB(src0_ptr + 24);
-        src0_ptr += src_stride;
-        LD_SH4(src1_ptr, 8, in0, in1, in2, in3);
-        src1_ptr += src2_stride;
-        XORI_B3_128_SB(src0, src1, src2);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src0, src1, src0, src1, mask2, mask3, vec0, vec1);
-        dst1 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec0, vec1);
-        dst2 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec0, vec1);
-        dst3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst0, dst1, dst2, dst3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst0, dst1, dst2, dst3);
-
-        PCKEV_B2_SH(dst1, dst0, dst3, dst2, dst0, dst1);
-        ST_SH2(dst0, dst1, dst, 16);
-        dst += dst_stride;
-    }
-}
-
-static void hevc_vt_biwgt_4t_4x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t weight, offset, constant;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 in0, in1, dst10;
-    v16i8 src10_r, src32_r, src21_r, src43_r, src2110, src4332;
-    v4i32 dst10_r, dst10_l;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec, out;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    src2110 = (v16i8) __msa_ilvr_d((v2i64) src21_r, (v2i64) src10_r);
-    src2110 = (v16i8) __msa_xori_b((v16u8) src2110, 128);
-    LD_SB2(src0_ptr, src_stride, src3, src4);
-    src0_ptr += (2 * src_stride);
-    LD_SH2(src1_ptr, src2_stride, in0, in1);
-    src1_ptr += (2 * src2_stride);
-
-    in0 = (v8i16) __msa_ilvr_d((v2i64) in1, (v2i64) in0);
-    ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-    src4332 = (v16i8) __msa_ilvr_d((v2i64) src43_r, (v2i64) src32_r);
-    src4332 = (v16i8) __msa_xori_b((v16u8) src4332, 128);
-
-    dst10 = HEVC_FILT_4TAP_SH(src2110, src4332, filt0, filt1);
-
-    ILVRL_H2_SW(dst10, in0, dst10_r, dst10_l);
-    dst10_r = __msa_dpadd_s_w(offset_vec, (v8i16) dst10_r, (v8i16) weight_vec);
-    dst10_l = __msa_dpadd_s_w(offset_vec, (v8i16) dst10_l, (v8i16) weight_vec);
-    SRAR_W2_SW(dst10_r, dst10_l, rnd_vec);
-    CLIP_SW2_0_255(dst10_r, dst10_l);
-    out = __msa_pckev_h((v8i16) dst10_l, (v8i16) dst10_r);
-    out = (v8i16) __msa_pckev_b((v16i8) out, (v16i8) out);
-    ST_W2(out, 0, 1, dst, dst_stride);
-}
-
-static void hevc_vt_biwgt_4t_4x4_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t weight, offset, constant;
-    v16i8 src0, src1, src2, src3, src4, src5, src6;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src54_r, src21_r, src43_r, src65_r;
-    v16i8 src2110, src4332, src6554;
-    v8i16 dst10, dst32;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    src2110 = (v16i8) __msa_ilvr_d((v2i64) src21_r, (v2i64) src10_r);
-    src2110 = (v16i8) __msa_xori_b((v16u8) src2110, 128);
-
-    LD_SB4(src0_ptr, src_stride, src3, src4, src5, src6);
-    src0_ptr += (4 * src_stride);
-    LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-    src1_ptr += (4 * src2_stride);
-    ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-    ILVR_B4_SB(src3, src2, src4, src3, src5, src4, src6, src5,
-               src32_r, src43_r, src54_r, src65_r);
-    ILVR_D2_SB(src43_r, src32_r, src65_r, src54_r, src4332, src6554);
-    XORI_B2_128_SB(src4332, src6554);
-
-    dst10 = HEVC_FILT_4TAP_SH(src2110, src4332, filt0, filt1);
-    dst32 = HEVC_FILT_4TAP_SH(src4332, src6554, filt0, filt1);
-
-    HEVC_BIW_RND_CLIP2(dst10, dst32, in0, in1,
-                       weight_vec, rnd_vec, offset_vec,
-                       dst10, dst32);
-
-    dst10 = (v8i16) __msa_pckev_b((v16i8) dst32, (v16i8) dst10);
-    ST_W4(dst10, 0, 1, 2, 3, dst, dst_stride);
-    dst += (4 * dst_stride);
-}
-
-static void hevc_vt_biwgt_4t_4x8multiple_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t weight, offset, constant;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v16i8 src10_r, src32_r, src54_r, src76_r, src98_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r, src109_r;
-    v16i8 src2110, src4332, src6554, src8776;
-    v8i16 dst10, dst32, dst54, dst76;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    src2110 = (v16i8) __msa_ilvr_d((v2i64) src21_r, (v2i64) src10_r);
-    src2110 = (v16i8) __msa_xori_b((v16u8) src2110, 128);
-
-    for (loop_cnt = (height >> 3); loop_cnt--;) {
-        LD_SB6(src0_ptr, src_stride, src3, src4, src5, src6, src7, src8);
-        src0_ptr += (6 * src_stride);
-        LD_SH8(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5, in6, in7);
-        src1_ptr += (8 * src2_stride);
-
-        ILVR_D2_SH(in1, in0, in3, in2, in0, in1);
-        ILVR_D2_SH(in5, in4, in7, in6, in2, in3);
-
-        ILVR_B4_SB(src3, src2, src4, src3, src5, src4, src6, src5,
-                   src32_r, src43_r, src54_r, src65_r);
-        ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-        ILVR_D3_SB(src43_r, src32_r, src65_r, src54_r, src87_r, src76_r,
-                   src4332, src6554, src8776);
-        XORI_B3_128_SB(src4332, src6554, src8776);
-
-        dst10 = HEVC_FILT_4TAP_SH(src2110, src4332, filt0, filt1);
-        dst32 = HEVC_FILT_4TAP_SH(src4332, src6554, filt0, filt1);
-        dst54 = HEVC_FILT_4TAP_SH(src6554, src8776, filt0, filt1);
-
-        LD_SB2(src0_ptr, src_stride, src9, src2);
-        src0_ptr += (2 * src_stride);
-        ILVR_B2_SB(src9, src8, src2, src9, src98_r, src109_r);
-        src2110 = (v16i8) __msa_ilvr_d((v2i64) src109_r, (v2i64) src98_r);
-        src2110 = (v16i8) __msa_xori_b((v16u8) src2110, 128);
-
-        dst76 = HEVC_FILT_4TAP_SH(src8776, src2110, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(dst10, dst32, dst54, dst76,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           dst10, dst32, dst54, dst76);
-
-        PCKEV_B2_SH(dst32, dst10, dst76, dst54, dst10, dst32);
-        ST_W8(dst10, dst32, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-        dst += (8 * dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_vt_biwgt_4t_4x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (4 == height) {
-        hevc_vt_biwgt_4t_4x4_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (0 == (height % 8)) {
-        hevc_vt_biwgt_4t_4x8multiple_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter, height,
-                                         weight0, weight1, offset0, offset1,
-                                         rnd_val);
-    }
-}
-
-static void hevc_vt_biwgt_4t_6w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t res = height & 0x03;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src21_r, src43_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        src0_ptr += (2 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-
-        LD_SB2(src0_ptr, src_stride, src1, src2);
-        src0_ptr += (2 * src_stride);
-        XORI_B2_128_SB(src1, src2);
-        ILVR_B2_SB(src1, src4, src2, src1, src10_r, src21_r);
-
-        tmp2 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-
-        PCKEV_B2_SH(tmp1, tmp0, tmp3, tmp2, tmp0, tmp1);
-        ST_W2(tmp0, 0, 2, dst, dst_stride);
-        ST_H2(tmp0, 2, 6, dst + 4, dst_stride);
-        ST_W2(tmp1, 0, 2, dst + 2 * dst_stride, dst_stride);
-        ST_H2(tmp1, 2, 6, dst + 2 * dst_stride + 4, dst_stride);
-        dst += (4 * dst_stride);
-    }
-    if (res) {
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        src0_ptr += (2 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-
-        LD_SB2(src0_ptr, src_stride, src1, src2);
-        src0_ptr += (2 * src_stride);
-        XORI_B2_128_SB(src1, src2);
-        ILVR_B2_SB(src1, src4, src2, src1, src10_r, src21_r);
-
-        tmp2 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-
-        PCKEV_B2_SH(tmp1, tmp0, tmp3, tmp2, tmp0, tmp1);
-        ST_W2(tmp0, 0, 2, dst, dst_stride);
-        ST_H2(tmp0, 2, 6, dst + 4, dst_stride);
-        ST_W2(tmp1, 0, 2, dst + 2 * dst_stride, dst_stride);
-        ST_H2(tmp1, 2, 6, dst + 2 * dst_stride + 4, dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_8x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 in0, in1, tmp0, tmp1;
-    v16i8 src10_r, src32_r, src21_r, src43_r;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-
-    LD_SB2(src0_ptr, src_stride, src3, src4);
-    LD_SH2(src1_ptr, src2_stride, in0, in1);
-    XORI_B2_128_SB(src3, src4);
-    ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-
-    tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-    tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-    HEVC_BIW_RND_CLIP2(tmp0, tmp1, in0, in1,
-                       weight_vec, rnd_vec, offset_vec,
-                       tmp0, tmp1);
-
-    tmp0 = (v8i16) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-    ST_D2(tmp0, 0, 1, dst, dst_stride);
-}
-
-static void hevc_vt_biwgt_4t_8x6_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8;
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v16i8 src10_r, src32_r, src54_r, src76_r;
-    v16i8 src21_r, src43_r, src65_r, src87_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-
-    LD_SB6(src0_ptr, src_stride, src3, src4, src5, src6, src7, src8);
-    LD_SH6(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5);
-    XORI_B6_128_SB(src3, src4, src5, src6, src7, src8);
-    ILVR_B4_SB(src3, src2, src4, src3, src5, src4, src6, src5,
-               src32_r, src43_r, src54_r, src65_r);
-    ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-
-    tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-    tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-    tmp2 = HEVC_FILT_4TAP_SH(src32_r, src54_r, filt0, filt1);
-    tmp3 = HEVC_FILT_4TAP_SH(src43_r, src65_r, filt0, filt1);
-    tmp4 = HEVC_FILT_4TAP_SH(src54_r, src76_r, filt0, filt1);
-    tmp5 = HEVC_FILT_4TAP_SH(src65_r, src87_r, filt0, filt1);
-    HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                       in0, in1, in2, in3,
-                       weight_vec, rnd_vec, offset_vec,
-                       tmp0, tmp1, tmp2, tmp3);
-    HEVC_BIW_RND_CLIP2(tmp4, tmp5, in4, in5,
-                       weight_vec, rnd_vec, offset_vec,
-                       tmp4, tmp5);
-
-    PCKEV_B2_SH(tmp1, tmp0, tmp3, tmp2, tmp0, tmp1);
-    tmp3 = (v8i16) __msa_pckev_b((v16i8) tmp5, (v16i8) tmp4);
-    ST_D4(tmp0, tmp1, 0, 1, 0, 1, dst, dst_stride);
-    ST_D2(tmp3, 0, 1, dst + 4 * dst_stride, dst_stride);
-}
-
-static void hevc_vt_biwgt_4t_8x4multiple_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src21_r, src43_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        src0_ptr += (2 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += (4 * src2_stride);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-
-        LD_SB2(src0_ptr, src_stride, src1, src2);
-        src0_ptr += (2 * src_stride);
-        XORI_B2_128_SB(src1, src2);
-        ILVR_B2_SB(src1, src4, src2, src1, src10_r, src21_r);
-
-        tmp2 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-
-        PCKEV_B2_SH(tmp1, tmp0, tmp3, tmp2, tmp0, tmp1);
-        ST_D4(tmp0, tmp1, 0, 1, 0, 1, dst, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_vt_biwgt_4t_8x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (6 == height) {
-        hevc_vt_biwgt_4t_8x6_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else {
-        hevc_vt_biwgt_4t_8x4multiple_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter, height,
-                                         weight0, weight1, offset0, offset1,
-                                         rnd_val);
-    }
-}
-
-static void hevc_vt_biwgt_4t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src5;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v16i8 src10_r, src32_r, src21_r, src43_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5;
-    v16i8 src10_l, src32_l, src54_l, src21_l, src43_l, src65_l;
-    v16i8 src2110, src4332;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= (1 * src_stride);
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    ILVL_B2_SB(src1, src0, src2, src1, src10_l, src21_l);
-    src2110 = (v16i8) __msa_ilvr_d((v2i64) src21_l, (v2i64) src10_l);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        src0_ptr += (2 * src_stride);
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        LD_SH4(src1_ptr + 8, src2_stride, in4, in5, in6, in7);
-        src1_ptr += (4 * src2_stride);
-        ILVR_D2_SH(in5, in4, in7, in6, in4, in5);
-        XORI_B2_128_SB(src3, src4);
-
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-        ILVL_B2_SB(src3, src2, src4, src3, src32_l, src43_l);
-        src4332 = (v16i8) __msa_ilvr_d((v2i64) src43_l, (v2i64) src32_l);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-        tmp4 = HEVC_FILT_4TAP_SH(src2110, src4332, filt0, filt1);
-
-        LD_SB2(src0_ptr, src_stride, src5, src2);
-        src0_ptr += (2 * src_stride);
-        XORI_B2_128_SB(src5, src2);
-        ILVR_B2_SB(src5, src4, src2, src5, src10_r, src21_r);
-        ILVL_B2_SB(src5, src4, src2, src5, src54_l, src65_l);
-        src2110 = (v16i8) __msa_ilvr_d((v2i64) src65_l, (v2i64) src54_l);
-
-        tmp2 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        tmp5 = HEVC_FILT_4TAP_SH(src4332, src2110, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-        HEVC_BIW_RND_CLIP2(tmp4, tmp5, in4, in5,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp4, tmp5);
-
-        PCKEV_B2_SH(tmp1, tmp0, tmp3, tmp2, tmp0, tmp1);
-        tmp2 = (v8i16) __msa_pckev_b((v16i8) tmp5, (v16i8) tmp4);
-        ST_D4(tmp0, tmp1, 0, 1, 0, 1, dst, dst_stride);
-        ST_W4(tmp2, 0, 1, 2, 3, dst + 8, dst_stride);
-        dst += (4 * dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src5;
-    v8i16 in0, in1, in2, in3;
-    v16i8 src10_r, src32_r, src21_r, src43_r;
-    v16i8 src10_l, src32_l, src21_l, src43_l;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    ILVL_B2_SB(src1, src0, src2, src1, src10_l, src21_l);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2(src1_ptr + 8, src2_stride, in2, in3);
-        src1_ptr += (2 * src2_stride);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-        ILVL_B2_SB(src3, src2, src4, src3, src32_l, src43_l);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-        tmp2 = HEVC_FILT_4TAP_SH(src10_l, src32_l, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src21_l, src43_l, filt0, filt1);
-
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-        PCKEV_B2_SH(tmp2, tmp0, tmp3, tmp1, tmp0, tmp1);
-        ST_SH2(tmp0, tmp1, dst, dst_stride);
-        dst += (2 * dst_stride);
-        LD_SB2(src0_ptr, src_stride, src5, src2);
-        src0_ptr += (2 * src_stride);
-
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2(src1_ptr + 8, src2_stride, in2, in3);
-        src1_ptr += (2 * src2_stride);
-        XORI_B2_128_SB(src5, src2);
-        ILVR_B2_SB(src5, src4, src2, src5, src10_r, src21_r);
-        ILVL_B2_SB(src5, src4, src2, src5, src10_l, src21_l);
-
-        tmp0 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        tmp2 = HEVC_FILT_4TAP_SH(src32_l, src10_l, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src43_l, src21_l, filt0, filt1);
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp2, tmp3,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp2, tmp3);
-
-        PCKEV_B2_SH(tmp2, tmp0, tmp3, tmp1, tmp0, tmp1);
-        ST_SH2(tmp0, tmp1, dst, dst_stride);
-        dst += (2 * dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src5;
-    v16i8 src6, src7, src8, src9, src10, src11;
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v16i8 src10_r, src32_r, src76_r, src98_r;
-    v16i8 src10_l, src32_l, src21_l, src43_l;
-    v16i8 src21_r, src43_r, src87_r, src109_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    /* 16width */
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    ILVL_B2_SB(src1, src0, src2, src1, src10_l, src21_l);
-    /* 8width */
-    LD_SB3(src0_ptr + 16, src_stride, src6, src7, src8);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src6, src7, src8);
-    ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-
-    for (loop_cnt = (height >> 2); loop_cnt--;) {
-        /* 16width */
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2(src1_ptr + 8, src2_stride, in2, in3);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-        ILVL_B2_SB(src3, src2, src4, src3, src32_l, src43_l);
-
-        /* 8width */
-        LD_SB2(src0_ptr + 16, src_stride, src9, src10);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr + 16, src2_stride, in4, in5);
-        src1_ptr += (2 * src2_stride);
-        XORI_B2_128_SB(src9, src10);
-        ILVR_B2_SB(src9, src8, src10, src9, src98_r, src109_r);
-        /* 16width */
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp4 = HEVC_FILT_4TAP_SH(src10_l, src32_l, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-        tmp5 = HEVC_FILT_4TAP_SH(src21_l, src43_l, filt0, filt1);
-        /* 8width */
-        tmp2 = HEVC_FILT_4TAP_SH(src76_r, src98_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src87_r, src109_r, filt0, filt1);
-        /* 16width */
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp4, tmp5,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp4, tmp5);
-        /* 8width */
-        HEVC_BIW_RND_CLIP2(tmp2, tmp3, in4, in5,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp2, tmp3);
-        /* 16width */
-        PCKEV_B2_SH(tmp4, tmp0, tmp5, tmp1, tmp0, tmp1);
-        /* 8width */
-        tmp2 = (v8i16) __msa_pckev_b((v16i8) tmp3, (v16i8) tmp2);
-        ST_SH2(tmp0, tmp1, dst, dst_stride);
-        ST_D2(tmp2, 0, 1, dst + 16, dst_stride);
-        dst += (2 * dst_stride);
-
-        /* 16width */
-        LD_SB2(src0_ptr, src_stride, src5, src2);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2(src1_ptr + 8, src2_stride, in2, in3);
-        XORI_B2_128_SB(src5, src2);
-        ILVR_B2_SB(src5, src4, src2, src5, src10_r, src21_r);
-        ILVL_B2_SB(src5, src4, src2, src5, src10_l, src21_l);
-        /* 8width */
-        LD_SB2(src0_ptr + 16, src_stride, src11, src8);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr + 16, src2_stride, in4, in5);
-        src1_ptr += (2 * src2_stride);
-        XORI_B2_128_SB(src11, src8);
-        ILVR_B2_SB(src11, src10, src8, src11, src76_r, src87_r);
-        /* 16width */
-        tmp0 = HEVC_FILT_4TAP_SH(src32_r, src10_r, filt0, filt1);
-        tmp4 = HEVC_FILT_4TAP_SH(src32_l, src10_l, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src43_r, src21_r, filt0, filt1);
-        tmp5 = HEVC_FILT_4TAP_SH(src43_l, src21_l, filt0, filt1);
-        /* 8width */
-        tmp2 = HEVC_FILT_4TAP_SH(src98_r, src76_r, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src109_r, src87_r, filt0, filt1);
-        /* 16width */
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp4, tmp5,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp4, tmp5);
-        /* 8width */
-        HEVC_BIW_RND_CLIP2(tmp2, tmp3, in4, in5,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp2, tmp3);
-        /* 16width */
-        PCKEV_B2_SH(tmp4, tmp0, tmp5, tmp1, tmp0, tmp1);
-
-        /* 8width */
-        tmp2 = (v8i16) __msa_pckev_b((v16i8) tmp3, (v16i8) tmp2);
-        ST_SH2(tmp0, tmp1, dst, dst_stride);
-        ST_D2(tmp2, 0, 1, dst + 16, dst_stride);
-        dst += (2 * dst_stride);
-    }
-}
-
-static void hevc_vt_biwgt_4t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    uint8_t *dst_tmp = dst + 16;
-    int32_t offset, weight, constant;
-    v16i8 src0, src1, src2, src3, src4, src6, src7, src8, src9, src10;
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v16i8 src10_r, src32_r, src76_r, src98_r;
-    v16i8 src21_r, src43_r, src87_r, src109_r;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v16i8 src10_l, src32_l, src76_l, src98_l;
-    v16i8 src21_l, src43_l, src87_l, src109_l;
-    v8i16 filt0, filt1;
-    v8i16 filter_vec;
-    v4i32 weight_vec, offset_vec, rnd_vec;
-
-    src0_ptr -= src_stride;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-    constant = 128 * weight1;
-    constant <<= 6;
-    offset += constant;
-
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-
-    filter_vec = LD_SH(filter);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    /* 16width */
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    XORI_B3_128_SB(src0, src1, src2);
-    ILVR_B2_SB(src1, src0, src2, src1, src10_r, src21_r);
-    ILVL_B2_SB(src1, src0, src2, src1, src10_l, src21_l);
-    /* next 16width */
-    LD_SB3(src0_ptr + 16, src_stride, src6, src7, src8);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src6, src7, src8);
-    ILVR_B2_SB(src7, src6, src8, src7, src76_r, src87_r);
-    ILVL_B2_SB(src7, src6, src8, src7, src76_l, src87_l);
-
-    for (loop_cnt = (height >> 1); loop_cnt--;) {
-        /* 16width */
-        LD_SB2(src0_ptr, src_stride, src3, src4);
-        LD_SH2(src1_ptr, src2_stride, in0, in1);
-        LD_SH2(src1_ptr + 8, src2_stride, in2, in3);
-        XORI_B2_128_SB(src3, src4);
-        ILVR_B2_SB(src3, src2, src4, src3, src32_r, src43_r);
-        ILVL_B2_SB(src3, src2, src4, src3, src32_l, src43_l);
-
-        /* 16width */
-        tmp0 = HEVC_FILT_4TAP_SH(src10_r, src32_r, filt0, filt1);
-        tmp4 = HEVC_FILT_4TAP_SH(src10_l, src32_l, filt0, filt1);
-        tmp1 = HEVC_FILT_4TAP_SH(src21_r, src43_r, filt0, filt1);
-        tmp5 = HEVC_FILT_4TAP_SH(src21_l, src43_l, filt0, filt1);
-        /* 16width */
-        HEVC_BIW_RND_CLIP4(tmp0, tmp1, tmp4, tmp5,
-                           in0, in1, in2, in3,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp0, tmp1, tmp4, tmp5);
-        /* 16width */
-        PCKEV_B2_SH(tmp4, tmp0, tmp5, tmp1, tmp0, tmp1);
-        ST_SH2(tmp0, tmp1, dst, dst_stride);
-        dst += (2 * dst_stride);
-
-        src10_r = src32_r;
-        src21_r = src43_r;
-        src10_l = src32_l;
-        src21_l = src43_l;
-        src2 = src4;
-
-        /* next 16width */
-        LD_SB2(src0_ptr + 16, src_stride, src9, src10);
-        src0_ptr += (2 * src_stride);
-        LD_SH2(src1_ptr + 16, src2_stride, in4, in5);
-        LD_SH2(src1_ptr + 24, src2_stride, in6, in7);
-        src1_ptr += (2 * src2_stride);
-        XORI_B2_128_SB(src9, src10);
-        ILVR_B2_SB(src9, src8, src10, src9, src98_r, src109_r);
-        ILVL_B2_SB(src9, src8, src10, src9, src98_l, src109_l);
-        /* next 16width */
-        tmp2 = HEVC_FILT_4TAP_SH(src76_r, src98_r, filt0, filt1);
-        tmp6 = HEVC_FILT_4TAP_SH(src76_l, src98_l, filt0, filt1);
-        tmp3 = HEVC_FILT_4TAP_SH(src87_r, src109_r, filt0, filt1);
-        tmp7 = HEVC_FILT_4TAP_SH(src87_l, src109_l, filt0, filt1);
-        /* next 16width */
-        HEVC_BIW_RND_CLIP4(tmp2, tmp3, tmp6, tmp7,
-                           in4, in5, in6, in7,
-                           weight_vec, rnd_vec, offset_vec,
-                           tmp2, tmp3, tmp6, tmp7);
-
-        /* next 16width */
-        PCKEV_B2_SH(tmp6, tmp2, tmp7, tmp3, tmp2, tmp3);
-        ST_SH2(tmp2, tmp3, dst_tmp, dst_stride);
-        dst_tmp += (2 * dst_stride);
-
-        src76_r = src98_r;
-        src87_r = src109_r;
-        src76_l = src98_l;
-        src87_l = src109_l;
-        src8 = src10;
-    }
-}
-
-static void hevc_hv_biwgt_4t_4x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    v8i16 in0 = { 0 };
-    v16u8 out;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr + 16);
-    v16i8 mask1;
-    v8i16 filter_vec, tmp, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5;
-    v8i16 dst20, dst31, dst42, dst10, dst32, dst21, dst43, tmp0, tmp1;
-    v4i32 dst0, dst1, offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB5(src0_ptr, src_stride, src0, src1, src2, src3, src4);
-    XORI_B5_128_SB(src0, src1, src2, src3, src4);
-
-    VSHF_B2_SB(src0, src2, src0, src2, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src3, src1, src3, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src4, src2, src4, mask0, mask1, vec4, vec5);
-
-    dst20 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dst31 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dst42 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-
-    ILVRL_H2_SH(dst31, dst20, dst10, dst32);
-    ILVRL_H2_SH(dst42, dst31, dst21, dst43);
-
-    dst0 = HEVC_FILT_4TAP(dst10, dst32, filt_h0, filt_h1);
-    dst1 = HEVC_FILT_4TAP(dst21, dst43, filt_h0, filt_h1);
-    dst0 >>= 6;
-    dst1 >>= 6;
-    dst0 = (v4i32) __msa_pckev_h((v8i16) dst1, (v8i16) dst0);
-
-    LD2(src1_ptr, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in0);
-
-    ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    SRAR_W2_SW(dst0, dst1, rnd_vec);
-    CLIP_SW2_0_255(dst0, dst1);
-    tmp = __msa_pckev_h((v8i16) dst1, (v8i16) dst0);
-    out = (v16u8) __msa_pckev_b((v16i8) tmp, (v16i8) tmp);
-    ST_W2(out, 0, 1, dst, dst_stride);
-}
-
-static void hevc_hv_biwgt_4t_4x4_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    v16u8 out;
-    v8i16 in0 = { 0 }, in1 = { 0 };
-    v16i8 src0, src1, src2, src3, src4, src5, src6;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr + 16);
-    v16i8 mask1;
-    v8i16 filter_vec, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v8i16 dst30, dst41, dst52, dst63;
-    v8i16 dst10, dst32, dst54, dst21, dst43, dst65;
-    v4i32 offset_vec, rnd_vec, const_vec;
-    v4i32 dst0, dst1, dst2, dst3;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-    XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-    VSHF_B2_SB(src0, src3, src0, src3, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src4, src1, src4, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src5, src2, src5, mask0, mask1, vec4, vec5);
-    VSHF_B2_SB(src3, src6, src3, src6, mask0, mask1, vec6, vec7);
-
-    dst30 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dst41 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dst52 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-    dst63 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-    ILVRL_H2_SH(dst41, dst30, dst10, dst43);
-    ILVRL_H2_SH(dst52, dst41, dst21, dst54);
-    ILVRL_H2_SH(dst63, dst52, dst32, dst65);
-    dst0 = HEVC_FILT_4TAP(dst10, dst32, filt_h0, filt_h1);
-    dst1 = HEVC_FILT_4TAP(dst21, dst43, filt_h0, filt_h1);
-    dst2 = HEVC_FILT_4TAP(dst32, dst54, filt_h0, filt_h1);
-    dst3 = HEVC_FILT_4TAP(dst43, dst65, filt_h0, filt_h1);
-    SRA_4V(dst0, dst1, dst2, dst3, 6);
-    PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp1, tmp3);
-
-    LD2(src1_ptr, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in0);
-    src1_ptr += (2 * src2_stride);
-    LD2(src1_ptr, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in1);
-
-    ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-    ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-    CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-    PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp0, tmp1);
-    out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-    ST_W4(out, 0, 1, 2, 3, dst, dst_stride);
-}
-
-static void hevc_hv_biwgt_4t_4multx8mult_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter_x,
-                                             const int8_t *filter_y,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    v16u8 out0, out1;
-    v8i16 in0 = { 0 }, in1 = { 0 }, in2 = { 0 }, in3 = { 0 };
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr + 16);
-    v16i8 mask1;
-    v8i16 filter_vec, weight_vec;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v8i16 dst10, dst21, dst22, dst73, dst84, dst95, dst106;
-    v8i16 dst10_r, dst32_r, dst54_r, dst76_r;
-    v8i16 dst21_r, dst43_r, dst65_r, dst87_r;
-    v8i16 dst98_r, dst109_r;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-
-    VSHF_B2_SB(src0, src1, src0, src1, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src2, src1, src2, mask0, mask1, vec2, vec3);
-    dst10 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dst21 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    ILVRL_H2_SH(dst21, dst10, dst10_r, dst21_r);
-    dst22 = (v8i16) __msa_splati_d((v2i64) dst21, 1);
-
-    for (loop_cnt = height >> 3; loop_cnt--;) {
-        LD_SB8(src0_ptr, src_stride,
-               src3, src4, src5, src6, src7, src8, src9, src10);
-        src0_ptr += (8 * src_stride);
-        XORI_B8_128_SB(src3, src4, src5, src6, src7, src8, src9, src10);
-        VSHF_B2_SB(src3, src7, src3, src7, mask0, mask1, vec0, vec1);
-        VSHF_B2_SB(src4, src8, src4, src8, mask0, mask1, vec2, vec3);
-        VSHF_B2_SB(src5, src9, src5, src9, mask0, mask1, vec4, vec5);
-        VSHF_B2_SB(src6, src10, src6, src10, mask0, mask1, vec6, vec7);
-
-        dst73 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dst84 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dst95 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-        dst106 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-        dst32_r = __msa_ilvr_h(dst73, dst22);
-        ILVRL_H2_SH(dst84, dst73, dst43_r, dst87_r);
-        ILVRL_H2_SH(dst95, dst84, dst54_r, dst98_r);
-        ILVRL_H2_SH(dst106, dst95, dst65_r, dst109_r);
-        dst22 = (v8i16) __msa_splati_d((v2i64) dst73, 1);
-        dst76_r = __msa_ilvr_h(dst22, dst106);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in0);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in1);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in2);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in3);
-
-        dst0 = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-        dst1 = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-        dst2 = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-        dst3 = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-        dst4 = HEVC_FILT_4TAP(dst54_r, dst76_r, filt_h0, filt_h1);
-        dst5 = HEVC_FILT_4TAP(dst65_r, dst87_r, filt_h0, filt_h1);
-        dst6 = HEVC_FILT_4TAP(dst76_r, dst98_r, filt_h0, filt_h1);
-        dst7 = HEVC_FILT_4TAP(dst87_r, dst109_r, filt_h0, filt_h1);
-        SRA_4V(dst0, dst1, dst2, dst3, 6);
-        SRA_4V(dst4, dst5, dst6, dst7, 6);
-        PCKEV_H4_SW(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6, dst0, dst1,
-                    dst2, dst3);
-        ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-        ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-        ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-        ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-        dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-        dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-        dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-        PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6, tmp0, tmp1,
-                    tmp2, tmp3);
-        PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-        ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-        dst += (8 * dst_stride);
-
-        dst10_r = dst98_r;
-        dst21_r = dst109_r;
-        dst22 = (v8i16) __msa_splati_d((v2i64) dst106, 1);
-    }
-}
-
-static void hevc_hv_biwgt_4t_4w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter_x,
-                                    const int8_t *filter_y,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_hv_biwgt_4t_4x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter_x, filter_y,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (4 == height) {
-        hevc_hv_biwgt_4t_4x4_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter_x, filter_y,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (0 == (height % 8)) {
-        hevc_hv_biwgt_4t_4multx8mult_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter_x, filter_y,
-                                         height, weight0, weight1,
-                                         offset0, offset1, rnd_val);
-    }
-}
-
-static void hevc_hv_biwgt_4t_6w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter_x,
-                                    const int8_t *filter_y,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    uint32_t tpw0, tpw1, tpw2, tpw3;
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    v16u8 out0, out1, out2;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v8i16 in0 = { 0 }, in1 = { 0 }, in2 = { 0 }, in3 = { 0 };
-    v8i16 in4 = { 0 }, in5 = { 0 };
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1, filter_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6, dsth7, dsth8, dsth9;
-    v8i16 dsth10, tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7, weight_vec;
-    v8i16 dst10_r, dst32_r, dst54_r, dst76_r, dst98_r, dst21_r, dst43_r;
-    v8i16 dst65_r, dst87_r, dst109_r, dst10_l, dst32_l, dst54_l, dst76_l;
-    v8i16 dst98_l, dst21_l, dst43_l, dst65_l, dst87_l, dst109_l;
-    v8i16 dst1021_l, dst3243_l, dst5465_l, dst7687_l, dst98109_l;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l, dst2_r, dst2_l, dst3_r, dst3_l;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v4i32 dst4_r, dst5_r, dst6_r, dst7_r;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-    dsth0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dsth1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dsth2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-
-    ILVRL_H2_SH(dsth1, dsth0, dst10_r, dst10_l);
-    ILVRL_H2_SH(dsth2, dsth1, dst21_r, dst21_l);
-
-    LD_SB8(src0_ptr, src_stride, src3, src4, src5, src6, src7, src8, src9,
-           src10);
-    XORI_B8_128_SB(src3, src4, src5, src6, src7, src8, src9, src10);
-
-    VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec4, vec5);
-    VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec6, vec7);
-
-    dsth3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dsth4 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dsth5 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-    dsth6 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-    VSHF_B2_SB(src7, src7, src7, src7, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src8, src8, src8, src8, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src9, src9, src9, src9, mask0, mask1, vec4, vec5);
-    VSHF_B2_SB(src10, src10, src10, src10, mask0, mask1, vec6, vec7);
-
-    dsth7 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dsth8 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dsth9 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-    dsth10 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-    ILVRL_H2_SH(dsth3, dsth2, dst32_r, dst32_l);
-    ILVRL_H2_SH(dsth4, dsth3, dst43_r, dst43_l);
-    ILVRL_H2_SH(dsth5, dsth4, dst54_r, dst54_l);
-    ILVRL_H2_SH(dsth6, dsth5, dst65_r, dst65_l);
-    ILVRL_H2_SH(dsth7, dsth6, dst76_r, dst76_l);
-    ILVRL_H2_SH(dsth8, dsth7, dst87_r, dst87_l);
-    ILVRL_H2_SH(dsth9, dsth8, dst98_r, dst98_l);
-    ILVRL_H2_SH(dsth10, dsth9, dst109_r, dst109_l);
-    PCKEV_D2_SH(dst21_l, dst10_l, dst43_l, dst32_l, dst1021_l, dst3243_l);
-    PCKEV_D2_SH(dst65_l, dst54_l, dst87_l, dst76_l, dst5465_l, dst7687_l);
-    dst98109_l = (v8i16) __msa_pckev_d((v2i64) dst109_l, (v2i64) dst98_l);
-
-    dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-    dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-    dst2_r = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-    dst3_r = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-    dst4_r = HEVC_FILT_4TAP(dst54_r, dst76_r, filt_h0, filt_h1);
-    dst5_r = HEVC_FILT_4TAP(dst65_r, dst87_r, filt_h0, filt_h1);
-    dst6_r = HEVC_FILT_4TAP(dst76_r, dst98_r, filt_h0, filt_h1);
-    dst7_r = HEVC_FILT_4TAP(dst87_r, dst109_r, filt_h0, filt_h1);
-    dst0_l = HEVC_FILT_4TAP(dst1021_l, dst3243_l, filt_h0, filt_h1);
-    dst1_l = HEVC_FILT_4TAP(dst3243_l, dst5465_l, filt_h0, filt_h1);
-    dst2_l = HEVC_FILT_4TAP(dst5465_l, dst7687_l, filt_h0, filt_h1);
-    dst3_l = HEVC_FILT_4TAP(dst7687_l, dst98109_l, filt_h0, filt_h1);
-    SRA_4V(dst0_r, dst1_r, dst2_r, dst3_r, 6);
-    SRA_4V(dst4_r, dst5_r, dst6_r, dst7_r, 6);
-    SRA_4V(dst0_l, dst1_l, dst2_l, dst3_l, 6);
-    PCKEV_H2_SW(dst1_r, dst0_r, dst3_r, dst2_r, dst0, dst1);
-    PCKEV_H2_SW(dst5_r, dst4_r, dst7_r, dst6_r, dst2, dst3);
-
-    LD2(src1_ptr, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in0);
-    LD2(src1_ptr + 2 * src2_stride, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in1);
-
-    LD2(src1_ptr + 4 * src2_stride, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in2);
-    LD2(src1_ptr + 6 * src2_stride, src2_stride, tp0, tp1);
-    INSERT_D2_SH(tp0, tp1, in3);
-
-    ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-    ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-    ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-    ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-    dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-    dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-    dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-    SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-    SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-    CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-    CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-    PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6, tmp0, tmp1,
-                tmp2, tmp3);
-    PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-    ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-
-    PCKEV_H2_SW(dst1_l, dst0_l, dst3_l, dst2_l, dst4, dst5);
-
-    LW4(src1_ptr + 4, src2_stride, tpw0, tpw1, tpw2, tpw3);
-    src1_ptr += (4 * src2_stride);
-    INSERT_W4_SH(tpw0, tpw1, tpw2, tpw3, in4);
-    LW4(src1_ptr + 4, src2_stride, tpw0, tpw1, tpw2, tpw3);
-    INSERT_W4_SH(tpw0, tpw1, tpw2, tpw3, in5);
-
-    ILVRL_H2_SH(dst4, in4, tmp0, tmp1);
-    ILVRL_H2_SH(dst5, in5, tmp2, tmp3);
-
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-    CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-    PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp4, tmp5);
-
-    out2 = (v16u8) __msa_pckev_b((v16i8) tmp5, (v16i8) tmp4);
-    ST_H8(out2, 0, 1, 2, 3, 4, 5, 6, 7, dst + 4, dst_stride);
-}
-
-static void hevc_hv_biwgt_4t_8x2_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    int32_t weight, offset;
-    v16u8 out;
-    v16i8 src0, src1, src2, src3, src4;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1;
-    v8i16 filter_vec, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8, vec9;
-    v8i16 dst0, dst1, dst2, dst3, dst4;
-    v8i16 in0, in1;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l;
-    v8i16 dst10_r, dst32_r, dst21_r, dst43_r;
-    v8i16 dst10_l, dst32_l, dst21_l, dst43_l;
-    v8i16 tmp0, tmp1, tmp2, tmp3;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB5(src0_ptr, src_stride, src0, src1, src2, src3, src4);
-    XORI_B5_128_SB(src0, src1, src2, src3, src4);
-
-    LD_SH2(src1_ptr, src2_stride, in0, in1);
-
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-    VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec6, vec7);
-    VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec8, vec9);
-
-    dst0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dst1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dst2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-    dst3 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-    dst4 = HEVC_FILT_4TAP_SH(vec8, vec9, filt0, filt1);
-
-    ILVRL_H2_SH(dst1, dst0, dst10_r, dst10_l);
-    ILVRL_H2_SH(dst2, dst1, dst21_r, dst21_l);
-    ILVRL_H2_SH(dst3, dst2, dst32_r, dst32_l);
-    ILVRL_H2_SH(dst4, dst3, dst43_r, dst43_l);
-    dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-    dst0_l = HEVC_FILT_4TAP(dst10_l, dst32_l, filt_h0, filt_h1);
-    dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-    dst1_l = HEVC_FILT_4TAP(dst21_l, dst43_l, filt_h0, filt_h1);
-    SRA_4V(dst0_r, dst0_l, dst1_r, dst1_l, 6);
-    PCKEV_H2_SH(dst0_l, dst0_r, dst1_l, dst1_r, tmp1, tmp3);
-
-    ILVRL_H2_SH(tmp1, in0, tmp0, tmp1);
-    ILVRL_H2_SH(tmp3, in1, tmp2, tmp3);
-
-    dst0_r = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst0_l = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst1_r = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst1_l = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    SRAR_W4_SW(dst0_r, dst0_l, dst1_r, dst1_l, rnd_vec);
-    CLIP_SW4_0_255(dst0_r, dst0_l, dst1_r, dst1_l);
-    PCKEV_H2_SH(dst0_l, dst0_r, dst1_l, dst1_r, tmp0, tmp1);
-    out = (v16u8) __msa_pckev_b((v16i8) tmp1, (v16i8) tmp0);
-    ST_D2(out, 0, 1, dst, dst_stride);
-}
-
-static void hevc_hv_biwgt_4t_8multx4_msa(const uint8_t *src0_ptr,
-                                         int32_t src_stride,
-                                         const int16_t *src1_ptr,
-                                         int32_t src2_stride,
-                                         uint8_t *dst,
-                                         int32_t dst_stride,
-                                         const int8_t *filter_x,
-                                         const int8_t *filter_y,
-                                         int32_t weight0,
-                                         int32_t weight1,
-                                         int32_t offset0,
-                                         int32_t offset1,
-                                         int32_t rnd_val,
-                                         int32_t width8mult)
-{
-    int32_t weight, offset;
-    uint32_t cnt;
-    v16u8 out0, out1;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, mask0, mask1;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v8i16 filt0, filt1, filt_h0, filt_h1, filter_vec, weight_vec;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7, in0, in1, in2, in3;
-    v8i16 dst10_r, dst32_r, dst54_r, dst21_r, dst43_r, dst65_r;
-    v8i16 dst10_l, dst32_l, dst54_l, dst21_l, dst43_l, dst65_l;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l, dst2_r, dst2_l, dst3_r, dst3_l;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask0 = LD_SB(ff_hevc_mask_arr);
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-    weight_vec = (v8i16) __msa_fill_w(weight);
-
-    for (cnt = width8mult; cnt--;) {
-        LD_SB7(src0_ptr, src_stride, src0, src1, src2, src3, src4, src5, src6);
-        src0_ptr += 8;
-        XORI_B7_128_SB(src0, src1, src2, src3, src4, src5, src6);
-
-        LD_SH4(src1_ptr, src2_stride, in0, in1, in2, in3);
-        src1_ptr += 8;
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-
-        dsth0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dsth1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dsth2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-
-        ILVRL_H2_SH(dsth1, dsth0, dst10_r, dst10_l);
-        ILVRL_H2_SH(dsth2, dsth1, dst21_r, dst21_l);
-
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec2, vec3);
-        VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec4, vec5);
-        VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec6, vec7);
-
-        dsth3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dsth4 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dsth5 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-        dsth6 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-        ILVRL_H2_SH(dsth3, dsth2, dst32_r, dst32_l);
-        ILVRL_H2_SH(dsth4, dsth3, dst43_r, dst43_l);
-        ILVRL_H2_SH(dsth5, dsth4, dst54_r, dst54_l);
-        ILVRL_H2_SH(dsth6, dsth5, dst65_r, dst65_l);
-
-        dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-        dst0_l = HEVC_FILT_4TAP(dst10_l, dst32_l, filt_h0, filt_h1);
-        dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-        dst1_l = HEVC_FILT_4TAP(dst21_l, dst43_l, filt_h0, filt_h1);
-        dst2_r = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-        dst2_l = HEVC_FILT_4TAP(dst32_l, dst54_l, filt_h0, filt_h1);
-        dst3_r = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-        dst3_l = HEVC_FILT_4TAP(dst43_l, dst65_l, filt_h0, filt_h1);
-
-        SRA_4V(dst0_r, dst0_l, dst1_r, dst1_l, 6);
-        SRA_4V(dst2_r, dst2_l, dst3_r, dst3_l, 6);
-        PCKEV_H4_SW(dst0_l, dst0_r, dst1_l, dst1_r, dst2_l, dst2_r, dst3_l,
-                    dst3_r, dst0, dst1, dst2, dst3);
-
-        ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-        ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-        ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-        ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-        dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-        dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-        dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-        PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                    tmp0, tmp1, tmp2, tmp3);
-        PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-        dst += 8;
-    }
-}
-
-static void hevc_hv_biwgt_4t_8x6_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t offset, weight;
-    v16u8 out0, out1, out2;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1;
-    v8i16 filter_vec, weight_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7, vec8, vec9;
-    v16i8 vec10, vec11, vec12, vec13, vec14, vec15, vec16, vec17;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6, dsth7, dsth8;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l, dst2_r, dst2_l, dst3_r, dst3_l;
-    v4i32 dst4_r, dst4_l, dst5_r, dst5_l;
-    v8i16 dst10_r, dst32_r, dst10_l, dst32_l;
-    v8i16 dst21_r, dst43_r, dst21_l, dst43_l;
-    v8i16 dst54_r, dst54_l, dst65_r, dst65_l;
-    v8i16 dst76_r, dst76_l, dst87_r, dst87_l;
-    v8i16 in0, in1, in2, in3, in4, in5;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    LD_SB5(src0_ptr, src_stride, src0, src1, src2, src3, src4);
-    src0_ptr += (5 * src_stride);
-    LD_SB4(src0_ptr, src_stride, src5, src6, src7, src8);
-
-    XORI_B5_128_SB(src0, src1, src2, src3, src4);
-    XORI_B4_128_SB(src5, src6, src7, src8);
-
-    LD_SH6(src1_ptr, src2_stride, in0, in1, in2, in3, in4, in5);
-
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-    VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec6, vec7);
-    VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec8, vec9);
-    VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec10, vec11);
-    VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec12, vec13);
-    VSHF_B2_SB(src7, src7, src7, src7, mask0, mask1, vec14, vec15);
-    VSHF_B2_SB(src8, src8, src8, src8, mask0, mask1, vec16, vec17);
-
-    dsth0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dsth1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dsth2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-    dsth3 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-    dsth4 = HEVC_FILT_4TAP_SH(vec8, vec9, filt0, filt1);
-    dsth5 = HEVC_FILT_4TAP_SH(vec10, vec11, filt0, filt1);
-    dsth6 = HEVC_FILT_4TAP_SH(vec12, vec13, filt0, filt1);
-    dsth7 = HEVC_FILT_4TAP_SH(vec14, vec15, filt0, filt1);
-    dsth8 = HEVC_FILT_4TAP_SH(vec16, vec17, filt0, filt1);
-
-    ILVRL_H2_SH(dsth1, dsth0, dst10_r, dst10_l);
-    ILVRL_H2_SH(dsth2, dsth1, dst21_r, dst21_l);
-    ILVRL_H2_SH(dsth3, dsth2, dst32_r, dst32_l);
-    ILVRL_H2_SH(dsth4, dsth3, dst43_r, dst43_l);
-    ILVRL_H2_SH(dsth5, dsth4, dst54_r, dst54_l);
-    ILVRL_H2_SH(dsth6, dsth5, dst65_r, dst65_l);
-    ILVRL_H2_SH(dsth7, dsth6, dst76_r, dst76_l);
-    ILVRL_H2_SH(dsth8, dsth7, dst87_r, dst87_l);
-
-    dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-    dst0_l = HEVC_FILT_4TAP(dst10_l, dst32_l, filt_h0, filt_h1);
-    dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-    dst1_l = HEVC_FILT_4TAP(dst21_l, dst43_l, filt_h0, filt_h1);
-    dst2_r = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-    dst2_l = HEVC_FILT_4TAP(dst32_l, dst54_l, filt_h0, filt_h1);
-    dst3_r = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-    dst3_l = HEVC_FILT_4TAP(dst43_l, dst65_l, filt_h0, filt_h1);
-    dst4_r = HEVC_FILT_4TAP(dst54_r, dst76_r, filt_h0, filt_h1);
-    dst4_l = HEVC_FILT_4TAP(dst54_l, dst76_l, filt_h0, filt_h1);
-    dst5_r = HEVC_FILT_4TAP(dst65_r, dst87_r, filt_h0, filt_h1);
-    dst5_l = HEVC_FILT_4TAP(dst65_l, dst87_l, filt_h0, filt_h1);
-
-    SRA_4V(dst0_r, dst0_l, dst1_r, dst1_l, 6);
-    SRA_4V(dst2_r, dst2_l, dst3_r, dst3_l, 6);
-    SRA_4V(dst4_r, dst4_l, dst5_r, dst5_l, 6);
-    PCKEV_H4_SW(dst0_l, dst0_r, dst1_l, dst1_r, dst2_l, dst2_r, dst3_l, dst3_r,
-                dst0, dst1, dst2, dst3);
-
-    ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-    ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-    ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-    ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-    dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-    dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-    dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-    SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-    SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-    CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-    CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-    PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                tmp0, tmp1, tmp2, tmp3);
-    PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-
-    PCKEV_H2_SW(dst4_l, dst4_r, dst5_l, dst5_r, dst0, dst1);
-    ILVRL_H2_SH(dst0, in4, tmp0, tmp1);
-    ILVRL_H2_SH(dst1, in5, tmp2, tmp3);
-    dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-    dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-    dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-    dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-    SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-    CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-    PCKEV_H2_SH(dst1, dst0, dst3, dst2, tmp4, tmp5);
-    out2 = (v16u8) __msa_pckev_b((v16i8) tmp5, (v16i8) tmp4);
-    ST_D4(out0, out1, 0, 1, 0, 1, dst, dst_stride);
-    ST_D2(out2, 0, 1, dst + 4 * dst_stride, dst_stride);
-}
-
-static void hevc_hv_biwgt_4t_8multx4mult_msa(const uint8_t *src0_ptr,
-                                             int32_t src_stride,
-                                             const int16_t *src1_ptr,
-                                             int32_t src2_stride,
-                                             uint8_t *dst,
-                                             int32_t dst_stride,
-                                             const int8_t *filter_x,
-                                             const int8_t *filter_y,
-                                             int32_t height,
-                                             int32_t weight0,
-                                             int32_t weight1,
-                                             int32_t offset0,
-                                             int32_t offset1,
-                                             int32_t rnd_val,
-                                             int32_t width)
-{
-    uint32_t loop_cnt;
-    uint32_t cnt;
-    int32_t offset, weight;
-    const uint8_t *src0_ptr_tmp;
-    const int16_t *src1_ptr_tmp;
-    uint8_t *dst_tmp;
-    v16u8 out0, out1;
-    v16i8 src0, src1, src2, src3, src4, src5, src6;
-    v8i16 in0, in1, in2, in3;
-    v8i16 filt0, filt1;
-    v8i16 filt_h0, filt_h1;
-    v16i8 mask0 = LD_SB(ff_hevc_mask_arr);
-    v16i8 mask1;
-    v8i16 filter_vec;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l, dst2_r, dst2_l, dst3_r, dst3_l;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v8i16 dst10_r, dst32_r, dst54_r, dst21_r, dst43_r, dst65_r;
-    v8i16 dst10_l, dst32_l, dst54_l, dst21_l, dst43_l, dst65_l, weight_vec;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    weight_vec = (v8i16) __msa_fill_w(weight);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-
-    for (cnt = width >> 3; cnt--;) {
-        src0_ptr_tmp = src0_ptr;
-        src1_ptr_tmp = src1_ptr;
-        dst_tmp = dst;
-
-        LD_SB3(src0_ptr_tmp, src_stride, src0, src1, src2);
-        src0_ptr_tmp += (3 * src_stride);
-        XORI_B3_128_SB(src0, src1, src2);
-
-        VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-        VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-        VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-        dsth0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dsth1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dsth2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-
-        ILVRL_H2_SH(dsth1, dsth0, dst10_r, dst10_l);
-        ILVRL_H2_SH(dsth2, dsth1, dst21_r, dst21_l);
-
-        for (loop_cnt = height >> 2; loop_cnt--;) {
-            LD_SB4(src0_ptr_tmp, src_stride, src3, src4, src5, src6);
-            src0_ptr_tmp += (4 * src_stride);
-            LD_SH4(src1_ptr_tmp, src2_stride, in0, in1, in2, in3);
-            src1_ptr_tmp += (4 * src2_stride);
-            XORI_B4_128_SB(src3, src4, src5, src6);
-
-            VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-            VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec2, vec3);
-            VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec4, vec5);
-            VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec6, vec7);
-
-            dsth3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-            dsth4 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-            dsth5 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-            dsth6 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-            ILVRL_H2_SH(dsth3, dsth2, dst32_r, dst32_l);
-            ILVRL_H2_SH(dsth4, dsth3, dst43_r, dst43_l);
-            ILVRL_H2_SH(dsth5, dsth4, dst54_r, dst54_l);
-            ILVRL_H2_SH(dsth6, dsth5, dst65_r, dst65_l);
-
-            dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-            dst0_l = HEVC_FILT_4TAP(dst10_l, dst32_l, filt_h0, filt_h1);
-            dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-            dst1_l = HEVC_FILT_4TAP(dst21_l, dst43_l, filt_h0, filt_h1);
-            dst2_r = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-            dst2_l = HEVC_FILT_4TAP(dst32_l, dst54_l, filt_h0, filt_h1);
-            dst3_r = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-            dst3_l = HEVC_FILT_4TAP(dst43_l, dst65_l, filt_h0, filt_h1);
-
-            SRA_4V(dst0_r, dst0_l, dst1_r, dst1_l, 6);
-            SRA_4V(dst2_r, dst2_l, dst3_r, dst3_l, 6);
-            PCKEV_H4_SW(dst0_l, dst0_r, dst1_l, dst1_r, dst2_l, dst2_r, dst3_l,
-                        dst3_r, dst0, dst1, dst2, dst3);
-            ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-            ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-            ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-            ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-            dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-            dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-            dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-            dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-            dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-            dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-            dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-            dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-            SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-            SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-            CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-            CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-            PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                        tmp0, tmp1, tmp2, tmp3);
-            PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-            ST_D4(out0, out1, 0, 1, 0, 1, dst_tmp, dst_stride);
-            dst_tmp += (4 * dst_stride);
-
-            dst10_r = dst54_r;
-            dst10_l = dst54_l;
-            dst21_r = dst65_r;
-            dst21_l = dst65_l;
-            dsth2 = dsth6;
-        }
-
-        src0_ptr += 8;
-        dst += 8;
-        src1_ptr += 8;
-    }
-}
-
-static void hevc_hv_biwgt_4t_8w_msa(const uint8_t *src0_ptr,
-                                    int32_t src_stride,
-                                    const int16_t *src1_ptr,
-                                    int32_t src2_stride,
-                                    uint8_t *dst,
-                                    int32_t dst_stride,
-                                    const int8_t *filter_x,
-                                    const int8_t *filter_y,
-                                    int32_t height,
-                                    int32_t weight0,
-                                    int32_t weight1,
-                                    int32_t offset0,
-                                    int32_t offset1,
-                                    int32_t rnd_val)
-{
-    if (2 == height) {
-        hevc_hv_biwgt_4t_8x2_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter_x, filter_y,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (4 == height) {
-        hevc_hv_biwgt_4t_8multx4_msa(src0_ptr, src_stride, src1_ptr,
-                                     src2_stride, dst, dst_stride, filter_x,
-                                     filter_y, weight0, weight1, offset0,
-                                     offset1, rnd_val, 1);
-    } else if (6 == height) {
-        hevc_hv_biwgt_4t_8x6_msa(src0_ptr, src_stride, src1_ptr, src2_stride,
-                                 dst, dst_stride, filter_x, filter_y,
-                                 weight0, weight1, offset0, offset1, rnd_val);
-    } else if (0 == (height % 4)) {
-        hevc_hv_biwgt_4t_8multx4mult_msa(src0_ptr, src_stride,
-                                         src1_ptr, src2_stride,
-                                         dst, dst_stride, filter_x, filter_y,
-                                         height, weight0,
-                                         weight1, offset0, offset1, rnd_val, 8);
-    }
-}
-
-static void hevc_hv_biwgt_4t_12w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    uint32_t loop_cnt;
-    uint64_t tp0, tp1;
-    int32_t offset, weight;
-    const uint8_t *src0_ptr_tmp;
-    const int16_t *src1_ptr_tmp;
-    uint8_t *dst_tmp;
-    v16u8 out0, out1;
-    v16i8 src0, src1, src2, src3, src4, src5, src6, src7, src8, src9, src10;
-    v16i8 vec0, vec1, vec2, vec3, vec4, vec5, vec6, vec7;
-    v16i8 mask0, mask1, mask2, mask3;
-    v8i16 filt0, filt1, filt_h0, filt_h1, filter_vec;
-    v8i16 tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
-    v8i16 dsth0, dsth1, dsth2, dsth3, dsth4, dsth5, dsth6, weight_vec;
-    v8i16 dst10, dst21, dst22, dst73, dst84, dst95, dst106;
-    v8i16 dst76_r, dst98_r, dst87_r, dst109_r;
-    v8i16 in0 = { 0 }, in1 = { 0 }, in2 = { 0 }, in3 = { 0 };
-    v8i16 dst10_r, dst32_r, dst54_r, dst21_r, dst43_r, dst65_r;
-    v8i16 dst10_l, dst32_l, dst54_l, dst21_l, dst43_l, dst65_l;
-    v4i32 dst0_r, dst0_l, dst1_r, dst1_l, dst2_r, dst2_l, dst3_r, dst3_l;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v4i32 offset_vec, rnd_vec, const_vec;
-
-    src0_ptr -= (src_stride + 1);
-
-    filter_vec = LD_SH(filter_x);
-    SPLATI_H2_SH(filter_vec, 0, 1, filt0, filt1);
-
-    filter_vec = LD_SH(filter_y);
-    UNPCK_R_SB_SH(filter_vec, filter_vec);
-
-    SPLATI_W2_SH(filter_vec, 0, filt_h0, filt_h1);
-
-    mask0 = LD_SB(ff_hevc_mask_arr);
-    mask1 = mask0 + 2;
-
-    offset = (offset0 + offset1) << rnd_val;
-    weight0 = weight0 & 0x0000FFFF;
-    weight = weight0 | (weight1 << 16);
-
-    const_vec = __msa_fill_w((128 * weight1));
-    const_vec <<= 6;
-    offset_vec = __msa_fill_w(offset);
-    rnd_vec = __msa_fill_w(rnd_val + 1);
-    offset_vec += const_vec;
-    weight_vec = (v8i16) __msa_fill_w(weight);
-
-    src0_ptr_tmp = src0_ptr;
-    dst_tmp = dst;
-    src1_ptr_tmp = src1_ptr;
-
-    LD_SB3(src0_ptr_tmp, src_stride, src0, src1, src2);
-    src0_ptr_tmp += (3 * src_stride);
-
-    XORI_B3_128_SB(src0, src1, src2);
-
-    VSHF_B2_SB(src0, src0, src0, src0, mask0, mask1, vec0, vec1);
-    VSHF_B2_SB(src1, src1, src1, src1, mask0, mask1, vec2, vec3);
-    VSHF_B2_SB(src2, src2, src2, src2, mask0, mask1, vec4, vec5);
-
-    dsth0 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dsth1 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-    dsth2 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-
-    ILVRL_H2_SH(dsth1, dsth0, dst10_r, dst10_l);
-    ILVRL_H2_SH(dsth2, dsth1, dst21_r, dst21_l);
-
-    for (loop_cnt = 4; loop_cnt--;) {
-        LD_SB4(src0_ptr_tmp, src_stride, src3, src4, src5, src6);
-        src0_ptr_tmp += (4 * src_stride);
-        XORI_B4_128_SB(src3, src4, src5, src6);
-
-        LD_SH4(src1_ptr_tmp, src2_stride, in0, in1, in2, in3);
-        src1_ptr_tmp += (4 * src2_stride);
-
-        VSHF_B2_SB(src3, src3, src3, src3, mask0, mask1, vec0, vec1);
-        VSHF_B2_SB(src4, src4, src4, src4, mask0, mask1, vec2, vec3);
-        VSHF_B2_SB(src5, src5, src5, src5, mask0, mask1, vec4, vec5);
-        VSHF_B2_SB(src6, src6, src6, src6, mask0, mask1, vec6, vec7);
-
-        dsth3 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dsth4 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dsth5 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-        dsth6 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-        ILVRL_H2_SH(dsth3, dsth2, dst32_r, dst32_l);
-        ILVRL_H2_SH(dsth4, dsth3, dst43_r, dst43_l);
-        ILVRL_H2_SH(dsth5, dsth4, dst54_r, dst54_l);
-        ILVRL_H2_SH(dsth6, dsth5, dst65_r, dst65_l);
-
-        dst0_r = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-        dst0_l = HEVC_FILT_4TAP(dst10_l, dst32_l, filt_h0, filt_h1);
-        dst1_r = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-        dst1_l = HEVC_FILT_4TAP(dst21_l, dst43_l, filt_h0, filt_h1);
-        dst2_r = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-        dst2_l = HEVC_FILT_4TAP(dst32_l, dst54_l, filt_h0, filt_h1);
-        dst3_r = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-        dst3_l = HEVC_FILT_4TAP(dst43_l, dst65_l, filt_h0, filt_h1);
-
-        SRA_4V(dst0_r, dst0_l, dst1_r, dst1_l, 6);
-        SRA_4V(dst2_r, dst2_l, dst3_r, dst3_l, 6);
-        PCKEV_H4_SW(dst0_l, dst0_r, dst1_l, dst1_r, dst2_l, dst2_r, dst3_l,
-                    dst3_r, dst0, dst1, dst2, dst3);
-        ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-        ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-        ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-        ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-        dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-        dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-        dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-        PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                    tmp0, tmp1, tmp2, tmp3);
-        PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-        ST_D4(out0, out1, 0, 1, 0, 1, dst_tmp, dst_stride);
-        dst_tmp += (4 * dst_stride);
-
-        dst10_r = dst54_r;
-        dst10_l = dst54_l;
-        dst21_r = dst65_r;
-        dst21_l = dst65_l;
-        dsth2 = dsth6;
-    }
-
-    src0_ptr += 8;
-    dst += 8;
-    src1_ptr += 8;
-
-    mask2 = LD_SB(ff_hevc_mask_arr + 16);
-    mask3 = mask2 + 2;
-
-    LD_SB3(src0_ptr, src_stride, src0, src1, src2);
-    src0_ptr += (3 * src_stride);
-    XORI_B3_128_SB(src0, src1, src2);
-    VSHF_B2_SB(src0, src1, src0, src1, mask2, mask3, vec0, vec1);
-    VSHF_B2_SB(src1, src2, src1, src2, mask2, mask3, vec2, vec3);
-
-    dst10 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-    dst21 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-
-    ILVRL_H2_SH(dst21, dst10, dst10_r, dst21_r);
-    dst22 = (v8i16) __msa_splati_d((v2i64) dst21, 1);
-
-    for (loop_cnt = 2; loop_cnt--;) {
-        LD_SB8(src0_ptr, src_stride, src3, src4, src5, src6, src7, src8, src9,
-               src10);
-        src0_ptr += (8 * src_stride);
-        XORI_B8_128_SB(src3, src4, src5, src6, src7, src8, src9, src10);
-        VSHF_B2_SB(src3, src7, src3, src7, mask2, mask3, vec0, vec1);
-        VSHF_B2_SB(src4, src8, src4, src8, mask2, mask3, vec2, vec3);
-        VSHF_B2_SB(src5, src9, src5, src9, mask2, mask3, vec4, vec5);
-        VSHF_B2_SB(src6, src10, src6, src10, mask2, mask3, vec6, vec7);
-
-        dst73 = HEVC_FILT_4TAP_SH(vec0, vec1, filt0, filt1);
-        dst84 = HEVC_FILT_4TAP_SH(vec2, vec3, filt0, filt1);
-        dst95 = HEVC_FILT_4TAP_SH(vec4, vec5, filt0, filt1);
-        dst106 = HEVC_FILT_4TAP_SH(vec6, vec7, filt0, filt1);
-
-        dst32_r = __msa_ilvr_h(dst73, dst22);
-        ILVRL_H2_SH(dst84, dst73, dst43_r, dst87_r);
-        ILVRL_H2_SH(dst95, dst84, dst54_r, dst98_r);
-        ILVRL_H2_SH(dst106, dst95, dst65_r, dst109_r);
-        dst22 = (v8i16) __msa_splati_d((v2i64) dst73, 1);
-        dst76_r = __msa_ilvr_h(dst22, dst106);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in0);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in1);
-
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in2);
-        LD2(src1_ptr, src2_stride, tp0, tp1);
-        src1_ptr += 2 * src2_stride;
-        INSERT_D2_SH(tp0, tp1, in3);
-
-        dst0 = HEVC_FILT_4TAP(dst10_r, dst32_r, filt_h0, filt_h1);
-        dst1 = HEVC_FILT_4TAP(dst21_r, dst43_r, filt_h0, filt_h1);
-        dst2 = HEVC_FILT_4TAP(dst32_r, dst54_r, filt_h0, filt_h1);
-        dst3 = HEVC_FILT_4TAP(dst43_r, dst65_r, filt_h0, filt_h1);
-        dst4 = HEVC_FILT_4TAP(dst54_r, dst76_r, filt_h0, filt_h1);
-        dst5 = HEVC_FILT_4TAP(dst65_r, dst87_r, filt_h0, filt_h1);
-        dst6 = HEVC_FILT_4TAP(dst76_r, dst98_r, filt_h0, filt_h1);
-        dst7 = HEVC_FILT_4TAP(dst87_r, dst109_r, filt_h0, filt_h1);
-
-        SRA_4V(dst0, dst1, dst2, dst3, 6);
-        SRA_4V(dst4, dst5, dst6, dst7, 6);
-        PCKEV_H4_SW(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                    dst0, dst1, dst2, dst3);
-        ILVRL_H2_SH(dst0, in0, tmp0, tmp1);
-        ILVRL_H2_SH(dst1, in1, tmp2, tmp3);
-        ILVRL_H2_SH(dst2, in2, tmp4, tmp5);
-        ILVRL_H2_SH(dst3, in3, tmp6, tmp7);
-        dst0 = __msa_dpadd_s_w(offset_vec, tmp0, weight_vec);
-        dst1 = __msa_dpadd_s_w(offset_vec, tmp1, weight_vec);
-        dst2 = __msa_dpadd_s_w(offset_vec, tmp2, weight_vec);
-        dst3 = __msa_dpadd_s_w(offset_vec, tmp3, weight_vec);
-        dst4 = __msa_dpadd_s_w(offset_vec, tmp4, weight_vec);
-        dst5 = __msa_dpadd_s_w(offset_vec, tmp5, weight_vec);
-        dst6 = __msa_dpadd_s_w(offset_vec, tmp6, weight_vec);
-        dst7 = __msa_dpadd_s_w(offset_vec, tmp7, weight_vec);
-        SRAR_W4_SW(dst0, dst1, dst2, dst3, rnd_vec);
-        SRAR_W4_SW(dst4, dst5, dst6, dst7, rnd_vec);
-        CLIP_SW4_0_255(dst0, dst1, dst2, dst3);
-        CLIP_SW4_0_255(dst4, dst5, dst6, dst7);
-        PCKEV_H4_SH(dst1, dst0, dst3, dst2, dst5, dst4, dst7, dst6,
-                    tmp0, tmp1, tmp2, tmp3);
-        PCKEV_B2_UB(tmp1, tmp0, tmp3, tmp2, out0, out1);
-        ST_W8(out0, out1, 0, 1, 2, 3, 0, 1, 2, 3, dst, dst_stride);
-        dst += (8 * dst_stride);
-
-        dst10_r = dst98_r;
-        dst21_r = dst109_r;
-        dst22 = (v8i16) __msa_splati_d((v2i64) dst106, 1);
-    }
-}
-
-static void hevc_hv_biwgt_4t_16w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    if (4 == height) {
-        hevc_hv_biwgt_4t_8multx4_msa(src0_ptr, src_stride, src1_ptr,
-                                     src2_stride, dst, dst_stride, filter_x,
-                                     filter_y, weight0, weight1, offset0,
-                                     offset1, rnd_val, 2);
-    } else {
-        hevc_hv_biwgt_4t_8multx4mult_msa(src0_ptr, src_stride, src1_ptr,
-                                         src2_stride, dst, dst_stride,
-                                         filter_x, filter_y, height, weight0,
-                                         weight1, offset0, offset1, rnd_val, 16);
-    }
-}
-
-static void hevc_hv_biwgt_4t_24w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_4t_8multx4mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride,
-                                     filter_x, filter_y, height, weight0,
-                                     weight1, offset0, offset1, rnd_val, 24);
-}
-
-static void hevc_hv_biwgt_4t_32w_msa(const uint8_t *src0_ptr,
-                                     int32_t src_stride,
-                                     const int16_t *src1_ptr,
-                                     int32_t src2_stride,
-                                     uint8_t *dst,
-                                     int32_t dst_stride,
-                                     const int8_t *filter_x,
-                                     const int8_t *filter_y,
-                                     int32_t height,
-                                     int32_t weight0,
-                                     int32_t weight1,
-                                     int32_t offset0,
-                                     int32_t offset1,
-                                     int32_t rnd_val)
-{
-    hevc_hv_biwgt_4t_8multx4mult_msa(src0_ptr, src_stride,
-                                     src1_ptr, src2_stride,
-                                     dst, dst_stride,
-                                     filter_x, filter_y, height, weight0,
-                                     weight1, offset0, offset1, rnd_val, 32);
-}
-
-#define BI_W_MC_COPY(WIDTH)                                                  \
-void ff_hevc_put_hevc_bi_w_pel_pixels##WIDTH##_8_msa(uint8_t *dst,           \
-                                                     ptrdiff_t dst_stride,   \
-                                                     const uint8_t *src,     \
-                                                     ptrdiff_t src_stride,   \
-                                                     const int16_t *src_16bit, \
-                                                     int height,             \
-                                                     int denom,              \
-                                                     int weight0,            \
-                                                     int weight1,            \
-                                                     int offset0,            \
-                                                     int offset1,            \
-                                                     intptr_t mx,            \
-                                                     intptr_t my,            \
-                                                     int width)              \
-{                                                                            \
-    int shift = 14 + 1 - 8;                                                  \
-    int log2Wd = denom + shift - 1;                                          \
-                                                                             \
-    hevc_biwgt_copy_##WIDTH##w_msa(src, src_stride, src_16bit, MAX_PB_SIZE,  \
-                                   dst, dst_stride, height,                  \
-                                   weight0, weight1, offset0,                \
-                                   offset1, log2Wd);                         \
-}
-
-BI_W_MC_COPY(4);
-BI_W_MC_COPY(6);
-BI_W_MC_COPY(8);
-BI_W_MC_COPY(12);
-BI_W_MC_COPY(16);
-BI_W_MC_COPY(24);
-BI_W_MC_COPY(32);
-BI_W_MC_COPY(48);
-BI_W_MC_COPY(64);
-
-#undef BI_W_MC_COPY
-
-#define BI_W_MC(PEL, DIR, WIDTH, TAP, DIR1, FILT_DIR)                         \
-void ff_hevc_put_hevc_bi_w_##PEL##_##DIR##WIDTH##_8_msa(uint8_t *dst,         \
-                                                        ptrdiff_t             \
-                                                        dst_stride,           \
-                                                        const uint8_t *src,   \
-                                                        ptrdiff_t             \
-                                                        src_stride,           \
-                                                        const int16_t *src_16bit, \
-                                                        int height,           \
-                                                        int denom,            \
-                                                        int weight0,          \
-                                                        int weight1,          \
-                                                        int offset0,          \
-                                                        int offset1,          \
-                                                        intptr_t mx,          \
-                                                        intptr_t my,          \
-                                                        int width)            \
-{                                                                             \
-    const int8_t *filter = ff_hevc_##PEL##_filters[FILT_DIR - 1];             \
-    int log2Wd = denom + 14 - 8;                                              \
-                                                                              \
-    hevc_##DIR1##_biwgt_##TAP##t_##WIDTH##w_msa(src, src_stride, src_16bit,   \
-                                                MAX_PB_SIZE, dst, dst_stride, \
-                                                filter, height, weight0,      \
-                                                weight1, offset0, offset1,    \
-                                                log2Wd);                      \
-}
-
-BI_W_MC(qpel, h, 4, 8, hz, mx);
-BI_W_MC(qpel, h, 8, 8, hz, mx);
-BI_W_MC(qpel, h, 12, 8, hz, mx);
-BI_W_MC(qpel, h, 16, 8, hz, mx);
-BI_W_MC(qpel, h, 24, 8, hz, mx);
-BI_W_MC(qpel, h, 32, 8, hz, mx);
-BI_W_MC(qpel, h, 48, 8, hz, mx);
-BI_W_MC(qpel, h, 64, 8, hz, mx);
-
-BI_W_MC(qpel, v, 4, 8, vt, my);
-BI_W_MC(qpel, v, 8, 8, vt, my);
-BI_W_MC(qpel, v, 12, 8, vt, my);
-BI_W_MC(qpel, v, 16, 8, vt, my);
-BI_W_MC(qpel, v, 24, 8, vt, my);
-BI_W_MC(qpel, v, 32, 8, vt, my);
-BI_W_MC(qpel, v, 48, 8, vt, my);
-BI_W_MC(qpel, v, 64, 8, vt, my);
-
-BI_W_MC(epel, h, 4, 4, hz, mx);
-BI_W_MC(epel, h, 8, 4, hz, mx);
-BI_W_MC(epel, h, 6, 4, hz, mx);
-BI_W_MC(epel, h, 12, 4, hz, mx);
-BI_W_MC(epel, h, 16, 4, hz, mx);
-BI_W_MC(epel, h, 24, 4, hz, mx);
-BI_W_MC(epel, h, 32, 4, hz, mx);
-
-BI_W_MC(epel, v, 4, 4, vt, my);
-BI_W_MC(epel, v, 8, 4, vt, my);
-BI_W_MC(epel, v, 6, 4, vt, my);
-BI_W_MC(epel, v, 12, 4, vt, my);
-BI_W_MC(epel, v, 16, 4, vt, my);
-BI_W_MC(epel, v, 24, 4, vt, my);
-BI_W_MC(epel, v, 32, 4, vt, my);
-
-#undef BI_W_MC
-
-#define BI_W_MC_HV(PEL, WIDTH, TAP)                                         \
-void ff_hevc_put_hevc_bi_w_##PEL##_hv##WIDTH##_8_msa(uint8_t *dst,          \
-                                                     ptrdiff_t dst_stride,  \
-                                                     const uint8_t *src,    \
-                                                     ptrdiff_t src_stride,  \
-                                                     const int16_t *src_16bit, \
-                                                     int height,            \
-                                                     int denom,             \
-                                                     int weight0,           \
-                                                     int weight1,           \
-                                                     int offset0,           \
-                                                     int offset1,           \
-                                                     intptr_t mx,           \
-                                                     intptr_t my,           \
-                                                     int width)             \
-{                                                                           \
-    const int8_t *filter_x = ff_hevc_##PEL##_filters[mx - 1];               \
-    const int8_t *filter_y = ff_hevc_##PEL##_filters[my - 1];               \
-    int log2Wd = denom + 14 - 8;                                            \
-                                                                            \
-    hevc_hv_biwgt_##TAP##t_##WIDTH##w_msa(src, src_stride, src_16bit,       \
-                                          MAX_PB_SIZE, dst, dst_stride,     \
-                                          filter_x, filter_y, height,       \
-                                          weight0, weight1, offset0,        \
-                                          offset1, log2Wd);                 \
-}
-
-BI_W_MC_HV(qpel, 4, 8);
-BI_W_MC_HV(qpel, 8, 8);
-BI_W_MC_HV(qpel, 12, 8);
-BI_W_MC_HV(qpel, 16, 8);
-BI_W_MC_HV(qpel, 24, 8);
-BI_W_MC_HV(qpel, 32, 8);
-BI_W_MC_HV(qpel, 48, 8);
-BI_W_MC_HV(qpel, 64, 8);
-
-BI_W_MC_HV(epel, 4, 4);
-BI_W_MC_HV(epel, 8, 4);
-BI_W_MC_HV(epel, 6, 4);
-BI_W_MC_HV(epel, 12, 4);
-BI_W_MC_HV(epel, 16, 4);
-BI_W_MC_HV(epel, 24, 4);
-BI_W_MC_HV(epel, 32, 4);
-
-#undef BI_W_MC_HV
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Into the Dead 2 The Epic Sequel to the Hit Zombie Game - APK for Android.md b/spaces/congsaPfin/Manga-OCR/logs/Into the Dead 2 The Epic Sequel to the Hit Zombie Game - APK for Android.md
deleted file mode 100644
index 09a0223e18dc25550f3107854399a48a5c84db53..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Into the Dead 2 The Epic Sequel to the Hit Zombie Game - APK for Android.md	
+++ /dev/null
@@ -1,117 +0,0 @@
-
-<h1>Into the Dead 2 APK 2: A Zombie Survival Game for Android</h1>
-<p>If you are a fan of zombie action games, you might have heard of Into the Dead, a hit game that has over 70 million downloads. But did you know that there is a sequel to this game that is even more thrilling and immersive? It's called Into the Dead 2 APK 2, and it's available for free on Android devices. In this article, we will tell you everything you need to know about this game, including its features, how to download and install it, and why you should play it.</p>
-<h2>Introduction</h2>
-<h3>What is Into the Dead 2 APK 2?</h3>
-<p>Into the Dead 2 APK 2 is a zombie survival game developed by PIKPOK, a New Zealand-based game studio. It is the sequel to Into the Dead, which was released in 2014. The game follows the story of James, a survivor of the zombie apocalypse, who is trying to reach his family before it's too late. Along the way, he will encounter hordes of zombies that he has to fight or avoid using various weapons and vehicles. The game has seven chapters, 60 stages, and hundreds of challenges to complete, as well as multiple endings depending on the choices you make.</p>
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-<h3>Why should you play Into the Dead 2 APK 2?</h3>
-<p>There are many reasons why you should play Into the Dead 2 APK 2 if you love zombie games. Here are some of them:</p>
-<ul>
-<li>The game has stunning graphics and sound effects that create a realistic and immersive atmosphere.</li>
-<li>The game has a gripping and emotional story that will keep you hooked until the end.</li>
-<li>The game has a variety of gameplay modes and options that will suit your preferences and skills.</li>
-<li>The game has a lot of content and updates that will keep you entertained for hours.</li>
-<li>The game is free to play but offers some optional in-app purchases that can enhance your experience.</li>
-</ul>
-<h2>Features of Into the Dead 2 APK 2</h2>
-<h3>Evolving story and multiple endings</h3>
-<p>One of the most impressive features of Into the Dead 2 APK 2 is its evolving story and multiple endings. The game has a branching narrative that changes depending on your actions and decisions. You can choose to help or ignore other survivors, take different routes, or use different weapons. Each choice will have consequences that will affect the outcome of your journey. There are four possible endings to discover, each with its own rewards and challenges.</p>
-<h3>Powerful weapons and ammo perks</h3>
-<p>To survive the zombie apocalypse, you will need to arm yourself with powerful weapons and ammo perks. The game offers a wide range of weapons to choose from, including melee weapons, firearms, explosives, and more. You can also unlock and upgrade your weapons with different perks that can boost their damage, accuracy, fire rate, reload speed, or ammo capacity. Some perks can also give you special abilities, such as slowing down time, setting zombies on fire, or freezing them.</p>
-<h3>Varied gameplay</h3>
-<p>The game also offers varied gameplay that will keep you on your toes. You can fire from military gun emplacements, slay the hordes from atop vehicles, stab them to stay alive, or risk going after them on foot. You can also switch between different camera angles, such as first-person or third-person, depending on your preference. You can also customize your controls, such as sensitivity, tilt, or touch. The game also has different difficulty levels, from easy to nightmare, that will challenge your skills and reflexes.</p>
-<h3>Multiple, immersive environments</h3>
-<p>The game also features multiple, immersive environments that will make you feel like you are in a zombie movie. You will travel through different locations, such as rural farms, oil fields, military bases, and more. Each location has its own hazards and obstacles that you have to overcome, such as fences, cars, trains, or helicopters. You will also experience different weather conditions and times of day that will affect your visibility and strategy.</p>
-<h3>Ever-increasing zombie threats</h3>
-<p>As you progress through the game, you will face ever-increasing zombie threats that will test your survival skills. The game has different types of zombies, each with their own behaviors and abilities. Some zombies are slow and dumb, while others are fast and smart. Some zombies can jump, crawl, or climb, while others can spit acid, explode, or summon more zombies. You will have to adapt your tactics and weapons to deal with these different threats.</p>
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-<h3>Additional story events</h3>
-<p>The game also has additional story events that will add more depth and variety to your adventure. These are optional missions that you can complete to earn extra rewards and learn more about the characters and the world. Some of these events are time-limited, so you have to act fast to catch them. Some of these events are also connected to the main story, so they can affect the outcome of your journey.</p>
-<h3>Daily and special event modes</h3>
-<p>The game also has daily and special event modes that will keep you entertained for hours. These are modes that offer different challenges and rewards every day or every week. For example, you can play the daily carnage mode, where you have to kill as many zombies as possible in a limited time. Or you can play the special event mode, where you have to survive a specific scenario with a specific weapon or perk. These modes are a great way to test your skills and earn more loot.</p>
-<h3>Loyal canine companions</h3>
-<p>The game also has loyal canine companions that will accompany you on your journey. These are dogs that you can rescue and adopt from the zombie-infested world. Each dog has its own name, breed, and personality. They can also help you in combat by attacking zombies, distracting them, or fetching items for you. You can also pet them and feed them to increase their loyalty and happiness.</p>
-<h3>Offline mode</h3>
-<p>The game also has an offline mode that allows you to play without an internet connection. This is a great feature for those who want to enjoy the game without any interruptions or ads. You can also save your progress offline and sync it online when you reconnect. However, some features may not be available offline, such as daily and special event modes.</p>
-<h2>How to download and install Into the Dead 2 APK 2</h2>
-<h3>Requirements</h3>
-<p>To download and install Into the Dead 2 APK 2 on your Android device, you will need the following requirements:</p>
-<ul>
-<li>An Android device running Android 4.1 or higher.</li>
-<li>At least 1 GB of free storage space.</li>
-<li>A stable internet connection.</li>
-<li>Permission to access your device's storage and media.</li>
-</ul>
-<h3>Steps</h3>
-<p>To download and install Into the Dead 2 APK 2 on your Android device, follow these steps:</p>
-<ol>
-<li>Go to [this link] to download the APK file of Into the Dead 2 APK 2.</li>
-<li>Once the download is complete, locate the file in your device's file manager and tap on it to install it.</li>
-<li>If you see a warning message that says "Install blocked", go to your device's settings and enable "Unknown sources" under security options.</li>
-<li>Once the installation is complete, launch the game and enjoy!</li>
-</ol>
- <h2>Conclusion</h2>
-<h3>Summary of the main points</h3>
-<p>In conclusion, Into the Dead 2 APK 2 is a zombie survival game for Android devices that offers a lot of features and content for zombie fans. The game has an evolving story with multiple endings, powerful weapons and ammo perks, varied gameplay modes and options, multiple immersive environments, ever-increasing zombie threats, additional story events, daily and special event modes, loyal canine companions, and an offline mode. The game is free to play but offers some optional in-app purchases that can enhance your experience. The game has stunning graphics and sound effects that create a realistic and immersive atmosphere. The game has a gripping and emotional story that will keep you hooked until the end. The game is easy to download and install on your Android device, as long as you meet the requirements and follow the steps.</p>
-<h3>Call to action</h3>
-<p>If you are ready to experience the thrill and horror of the zombie apocalypse, download Into the Dead 2 APK 2 today and start your journey. You will not regret it, as this game will keep you entertained and challenged for hours. But be warned, this game is not for the faint of heart, as you will face countless zombies that will stop at nothing to kill you. Are you brave enough to enter the dead?</p>
-<h2>FAQs</h2>
-<p>Here are some frequently asked questions about Into the Dead 2 APK 2:</p>
-<ol>
-<li>Q: How can I save my progress in the game?<br>
-A: The game automatically saves your progress online when you are connected to the internet. You can also sync your progress offline by tapping on the cloud icon in the main menu.</li>
-<li>Q: How can I get more coins and gold in the game?<br>
-A: You can get more coins and gold by completing stages, challenges, and events, or by watching ads and videos. You can also buy them with real money through in-app purchases.</li>
-<li>Q: How can I unlock more weapons and perks in the game?<br>
-A: You can unlock more weapons and perks by progressing through the story, completing challenges, and collecting weapon parts. You can also buy them with coins or gold through in-app purchases.</li>
-<li>Q: How can I change my dog in the game?<br>
-A: You can change your dog by tapping on the dog icon in the main menu. You can choose from different dogs that you have rescued or adopted in the game.</li>
-<li>Q: How can I contact the developers of the game?<br>
-A: You can contact the developers of the game by sending an email to support@pikpok.com or by visiting their website at www.pikpok.com.</li>
-</ol></p> 401be4b1e0<br />
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\ No newline at end of file
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Star TV ndir Yayn Ak Fragmanlar Foto Galeriler ve Daha Fazlas.md b/spaces/congsaPfin/Manga-OCR/logs/Star TV ndir Yayn Ak Fragmanlar Foto Galeriler ve Daha Fazlas.md
deleted file mode 100644
index 70551060dff9e7e1d2ec071adae99f5ec93f7573..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Star TV ndir Yayn Ak Fragmanlar Foto Galeriler ve Daha Fazlas.md	
+++ /dev/null
@@ -1,120 +0,0 @@
-<br />
-<h1>Star TV İndir: How to Watch Your Favorite Shows and Movies on Your Windows Device</h1>
- <p>If you are a fan of Turkish dramas, comedies, and movies, you might have heard of Star TV, one of the most popular television channels in Turkey. Star TV offers a variety of programs that cater to different tastes and preferences, such as Kardeş Payı, Med Cezir, Paramparça, and many more. But did you know that you can also watch Star TV on your Windows device? Yes, you read that right. With Star TV app, you can enjoy your favorite shows and movies anytime, anywhere, without opening your web browser. In this article, we will show you how to download, install, and use Star TV app on your Windows device.</p>
- <h2>What is Star TV?</h2>
- <h3>A brief introduction to Star TV and its content</h3>
- <p>Star TV is a Turkish television channel that was launched in 1989 as the first private and national channel in Turkey. Since then, it has grown to become one of the most watched and influential channels in the country, with a wide range of programs that include dramas, comedies, news, sports, documentaries, reality shows, and movies. Some of the most popular programs on Star TV are Kardeş Payı, a comedy series about two brothers who inherit a gas station; Med Cezir, a drama series about a young man who moves from a poor neighborhood to a wealthy one; Paramparça, a drama series about two families whose lives are intertwined by a car accident; and many more.</p>
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- <h3>The benefits of using Star TV app on Windows devices</h3>
- <p>Star TV app is the official application of Star TV that allows you to watch all the content of the channel on your Windows device. By using Star TV app, you can enjoy the following benefits:</p>
- <ul>
-<li>You can watch all the episodes and trailers of your favorite shows and movies for free (the last three episodes are free, the previous ones are paid).</li>
-<li>You can access exclusive photo galleries and extra content of your favorite shows and movies.</li>
-<li>You can follow the broadcast schedule and never miss an episode.</li>
-<li>You can watch live streaming of Star TV anytime.</li>
-<li>You can enjoy a high-quality video experience with a sleek and simple user interface.</li>
-</ul>
- <h2>How to download and install Star TV app on Windows devices</h2>
- <h3>The steps to download Star TV app from Windows Store</h3>
- <p>To download Star TV app on your Windows device, you need to follow these steps:</p>
- <ol>
-<li>Open the Windows Store app on your device.</li>
-<li>Search for "Star TV" in the search box.</li>
-<li>Select the Star TV app from the search results.</li>
-<li>Click on the "Get" button to start downloading the app.</li>
-</ol>
- <h3>The steps to install and launch Star TV app on Windows devices</h3>
- <p>To install and launch Star TV app on your Windows device, you need to follow these steps:</p>
- <ol>
-<li>Wait for the download to finish.</li>
-<li>Click on the "Launch" button to open the app.</li>
-<li>Accept the terms and conditions of the app.</li>
-<li>Enjoy watching your favorite shows and movies on Star TV.</li>
-</ol>
- <h2>How to use Star TV app on Windows devices</h2>
- <h3>The features and functions of Star TV app</h3>
- <p>Star TV app has several features and functions that make it easy and convenient for you to watch your favorite shows and movies. Here are some of them:</p>
- <ul>
-<li>You can browse the categories of the app, such as "Dizi", "Film", "Haber", "Spor", and "Canlı Yayın" to find the content you want to watch.</li>
-<li>You can use the search function of the app to look for specific shows and movies by their names or keywords.</li>
-<li>You can add your favorite shows and movies to your watchlist by clicking on the "heart" icon on the top right corner of the screen.</li>
-<li>You can adjust the video quality, subtitles, and audio settings of the app according to your preferences.</li>
-<li>You can share your comments and feedback on the shows and movies you watch with other viewers by using the "chat" function of the app.</li>
-</ul>
- <h3>The tips and tricks to enhance your viewing experience</h3>
- <p>Here are some tips and tricks that can help you enhance your viewing experience with Star TV app:</p>
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- <ul>
-<li>You can use a VPN service to access Star TV app from anywhere in the world, as some content may be geo-restricted.</li>
-<li>You can use a Chromecast device to cast Star TV app from your Windows device to your TV screen for a bigger and better view.</li>
-<li>You can use headphones or speakers to improve the sound quality of Star TV app, especially if you are watching in a noisy environment.</li>
-<li>You can use a dark mode extension on your Windows device to reduce eye strain and save battery life while watching Star TV app.</li>
-<li>You can use a pop-up blocker extension on your Windows device to prevent annoying ads and pop-ups from interrupting your viewing experience.</li>
-</ul>
- <h2>Conclusion</h2>
- <h3>A summary of the main points and a call to action</h3>
- <p>In conclusion, Star TV is a great app for watching your favorite shows and movies on your Windows device. It offers a variety of content that suits different tastes and preferences, as well as a high-quality video experience with a sleek and simple user interface. You can download, install, and use Star TV app easily and conveniently by following the steps we have provided in this article. You can also use the features and functions of the app to customize your viewing experience, as well as the tips and tricks we have shared to enhance it. So what are you waiting for? Download Star TV app today and enjoy watching your favorite shows and movies anytime, anywhere.</p>
- <h4>FAQs</h4>
- <p>Here are some frequently asked questions about Star TV app:</p>
- <ol>
-<li>Is Star TV app free?</li>
-<p>Star TV app is free to download and use. However, some content may require a subscription or a payment to watch. You can check the details of each show or movie before watching it.</p>
-<li>Is Star TV app safe?</li>
-<p>Star TV app is safe to use, as it is the official application of Star TV channel. It does not contain any viruses or malware that can harm your device or data. However, you should always download it from the Windows Store or the official website of Star TV, and not from any third-party sources.</p>
-<li>Is Star TV app compatible with all Windows devices?</li>
-<p>Star TV app is compatible with most Windows devices that run on Windows 10 or higher. However, some older devices may not support some features or functions of the app. You can check the compatibility of your device before downloading the app from the Windows Store or the official website of Star TV.</p>
-<li>How can I contact Star TV for support or feedback?</li>
-<p>You can contact Star TV for support or feedback by using the "contact us" function of the app, or by sending an email to info@startv.com.tr. You can also follow Star TV on social media platforms such as Facebook, Twitter, Instagram, and YouTube for updates and news.</p>
-<li>How can I update Star TV app?</li>
-<p>You can update Star TV app by checking for updates on the Windows Store or the official website of Star TV. You can also enable automatic updates on your device settings to ensure that you always have the latest version of the app.</p>
-</ol></p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Super Bear Adventure The Best Platformer Game with MOD APK.md b/spaces/congsaPfin/Manga-OCR/logs/Super Bear Adventure The Best Platformer Game with MOD APK.md
deleted file mode 100644
index bbf88593c9042268cf1df4a3022644237f27470d..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Super Bear Adventure The Best Platformer Game with MOD APK.md	
+++ /dev/null
@@ -1,89 +0,0 @@
-<br />
-<h1>Super Bear Adventure Game Mod APK: A Fun and Exciting Platformer for Android</h1>
-<p>If you are looking for a fun and exciting platformer game for your Android device, you should definitely check out Super Bear Adventure Game Mod APK. This is a modded version of the original game that gives you access to all the levels, skins, hats, coins, gems, and more. You can also enjoy the game without any ads or root requirement. In this article, we will tell you everything you need to know about Super Bear Adventure Game Mod APK, including its features, how to download and install it, tips and tricks for playing it, and some frequently asked questions.</p>
-<h2>Features of Super Bear Adventure Game Mod APK</h2>
-<p>Super Bear Adventure Game Mod APK is a 2D platformer game that follows the adventures of a cute bear named Ted as he explores different kingdoms and places. The game has a lot of features that make it fun and engaging, such as:</p>
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-<ul>
-<li><b>Unlocked all levels, skins, and hats</b>: You can play any level you want without having to unlock them first. You can also customize your bear's appearance with different skins and hats that you can get for free.</li>
-<li><b>Unlimited coins and gems</b>: You can collect as many coins and gems as you want without any limit. You can use them to buy power-ups, upgrades, items, and more.</li>
-<li><b>No ads and no root required</b>: You can enjoy the game without any annoying ads or pop-ups. You also don't need to root your device to install or play the game.</li>
-<li><b>High-quality graphics and sound effects</b>: The game has colorful and detailed graphics that create a vibrant and lively atmosphere. The sound effects are also realistic and immersive.</li>
-<li <li><b>Easy and intuitive controls</b>: You can control your bear's movements and actions with simple taps and swipes. You can also adjust the sensitivity and layout of the controls according to your preference.</li>
-</ul>
-<p>With these features, you can have a blast playing Super Bear Adventure Game Mod APK and experience a thrilling and enjoyable platformer game.</p>
-<h2>How to Download and Install Super Bear Adventure Game Mod APK</h2>
-<p>Downloading and installing Super Bear Adventure Game Mod APK is very easy and straightforward. Just follow these steps:</p>
-<ol>
-<li><b>Step 1: Download the mod apk file from a trusted source</b>: You can find the link to download the mod apk file at the end of this article. Make sure you download it from a reliable and secure source to avoid any malware or viruses.</li>
-<li><b>Step 2: Enable unknown sources on your device settings</b>: Before you can install the mod apk file, you need to enable unknown sources on your device settings. This will allow you to install apps that are not from the official app store. To do this, go to your device settings, then security, then unknown sources, and toggle it on.</li>
-<li><b>Step 3: Install the mod apk file and launch the game</b>: After you have enabled unknown sources, you can install the mod apk file by tapping on it and following the instructions. Once the installation is complete, you can launch the game and enjoy all the unlocked features.</li>
-<li><b>Step 4: Enjoy the game with all the unlocked features</b>: Now that you have installed Super Bear Adventure Game Mod APK, you can play any level you want, customize your bear's appearance, collect unlimited coins and gems, and have fun without any ads or root requirement.</li>
-</ol>
-<p>That's it! You have successfully downloaded and installed Super Bear Adventure Game Mod APK on your Android device.</p> <h2>Tips and Tricks for Playing Super Bear Adventure Game Mod APK</h2>
-<p>Super Bear Adventure Game Mod APK is a fun and exciting game that will challenge your skills and creativity. To make the most out of the game, here are some tips and tricks that you can use:</p>
-<ul>
-<li><b>Explore different kingdoms and collect hidden items</b>: The game has six different kingdoms that you can explore, each with its own theme and environment. You can find hidden items, secrets, and easter eggs in each kingdom that will give you extra coins, gems, or power-ups. Some of these items are hidden in plain sight, while others require you to solve puzzles or use special abilities to access them.</li>
-<li><b>Use power-ups and special abilities to overcome obstacles</b>: The game has various power-ups and special abilities that you can use to help you overcome obstacles and enemies. For example, you can use the jetpack to fly over gaps, the magnet to attract coins and gems, the shield to protect yourself from damage, the fireball to shoot enemies, and the super jump to reach high places. You can also use your bear's roar to stun enemies or break objects.</li>
-<li><b>Upgrade your bear's skills and abilities with coins and gems</b>: You can use the coins and gems that you collect to upgrade your bear's skills and abilities. You can increase your health, speed, jump, roar, fireball, and magnet levels by spending coins. You can also unlock new skins and hats for your bear by spending gems. These upgrades will make your bear stronger and more stylish.</li>
-<li><b>Complete quests and challenges to earn rewards and achievements</b>: The game has various quests and challenges that you can complete to earn rewards and achievements. Some of these quests and challenges are related to the story, while others are optional or random. You can check your progress and achievements by tapping on the menu button on the top left corner of the screen.</li>
-<li><b>Play with your friends online or offline</b>: You can play Super Bear Adventure Game Mod APK with your friends online or offline. You can join or create a room online and invite your friends to play with you. You can also play offline by using a local Wi-Fi connection or Bluetooth. You can choose to cooperate or compete with your friends in different modes and levels.</li>
-</ul>
-<p>With these tips and tricks, you can have more fun and success playing Super Bear Adventure Game Mod APK.</p> <h2>Conclusion</h2>
-<p>Super Bear Adventure Game Mod APK is a fun and exciting platformer game for Android that you should not miss. It has a lot of features that make it enjoyable and engaging, such as unlocked all levels, skins, and hats, unlimited coins and gems, no ads and no root required, high-quality graphics and sound effects, easy and intuitive controls, and more. You can also download and install it easily by following the steps we provided. You can also use the tips and tricks we shared to make the most out of the game. You can also play with your friends online or offline in different modes and levels. Super Bear Adventure Game Mod APK is a game that will keep you entertained and challenged for hours. So what are you waiting for? Download Super Bear Adventure Game Mod APK now and have a blast!</p>
-<h2>FAQs</h2>
-<p>Here are some frequently asked questions about Super Bear Adventure Game Mod APK:</p>
-<ol>
-<li><b>Q1: Is Super Bear Adventure Game Mod APK safe to use?</b></li>
-<li><b>A1: Yes, it is safe to use as long as you download it from a reliable source. However, you should always be careful when installing any mod apk files on your device.</b></li>
-<li><b>Q2: How can I play Super Bear Adventure Game Mod APK offline?</b></li>
-<li><b>A2: You can play Super Bear Adventure Game Mod APK offline by turning off your internet connection before launching the game. You will still be able to access all the features and levels of the game.</b></li>
-<li><b>Q3: How can I update Super Bear Adventure Game Mod APK?</b></li>
-<li><b>A3: You can update Super Bear Adventure Game Mod APK by downloading the latest version of the mod apk file from the same source you downloaded it from. You will need to uninstall the previous version of the game before installing the new one.</b></li>
-<li><b>Q4: How can I contact the developer of Super Bear Adventure Game Mod APK?</b></li>
-<li><b>A4: You can contact the developer of Super Bear Adventure Game Mod APK by visiting their official website or social media pages. You can also leave a comment or feedback on their app store page.</b></li>
-<li><b>Q5: What are some similar games to Super Bear Adventure Game Mod APK?</b></li>
-<li><b>A5: Some similar games to Super Bear Adventure Game Mod APK are Super Cat Tales, Super Mario Run, Sonic Dash, Rayman Adventures, and Crash Bandicoot.</b></li>
-</ol></p>
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diff --git a/spaces/contluForse/HuggingGPT/assets/Analisa Teknikal Saham Pdf Download.md b/spaces/contluForse/HuggingGPT/assets/Analisa Teknikal Saham Pdf Download.md
deleted file mode 100644
index dd7e7a79a471cc2d318dfd9bc1667f1ebb913b82..0000000000000000000000000000000000000000
--- a/spaces/contluForse/HuggingGPT/assets/Analisa Teknikal Saham Pdf Download.md	
+++ /dev/null
@@ -1,44 +0,0 @@
-
-<h1>How to Learn Technical Analysis of Stocks with Free PDF Download</h1>
-<p>Technical analysis is a method of analyzing the price movements and patterns of stocks using historical data and indicators. Technical analysis can help investors and traders to identify the best time to buy or sell stocks, as well as to predict future trends and market conditions.</p>
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-<h2>What is Technical Analysis of Stocks?</h2>
-<p>Technical analysis of stocks is a way of studying the past and present behavior of stock prices and volumes using charts, indicators, and patterns. Technical analysis assumes that all relevant information about a stock is reflected in its price and that price movements tend to follow certain trends and cycles.</p>
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-<ul>
-<li>Identifying the direction and strength of a trend</li>
-<li>Determining the support and resistance levels</li>
-<li>Recognizing the reversal and continuation patterns</li>
-<li>Measuring the momentum and volatility of a stock</li>
-<li>Generating buy and sell signals based on specific rules</li>
-</ul>
-<p>Technical analysis can be applied to any time frame, from intraday to long-term, depending on the objectives and preferences of the analyst. Technical analysis can also be combined with fundamental analysis, which focuses on the intrinsic value and performance of a company, to get a more complete picture of a stock's potential.</p>
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-<ul>
-<li>It is objective and data-driven, which reduces the influence of emotions and biases on decision making.</li>
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-<li>It is simple and practical, which requires only a few tools and skills to perform.</li>
-<li>It is universal and applicable, which can be used for any type of stock, market, or instrument.</li>
-</ul>
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-<ul>
-<li>It is not infallible or predictive, which means that it cannot guarantee accuracy or certainty of future outcomes.</li>
-<li>It is subjective and interpretive, which means that different analysts may have different opinions or conclusions based on the same data.</li>
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-<li>It is dependent and influenced, which means that it may be affected by external factors such as news, events, or market sentiment.</li>
-</ul>
-<h2>How to Learn Technical Analysis of Stocks?</h2>
-<p>The best way to learn technical analysis of stocks is by following these steps:</p>
-<p></p>
-<ol>
-<li>Familiarize yourself with the basic concepts and principles of technical analysis, such as trend, support, resistance, pattern, indicator, signal, etc.</li>
-<li>Select a reliable source of data and a user-friendly platform for charting and analyzing stocks, such as investing.com or tradingview.com.</li>
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\ No newline at end of file
diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/leres/pix2pix/options/__init__.py b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/leres/pix2pix/options/__init__.py
deleted file mode 100644
index e7eedebe54aa70169fd25951b3034d819e396c90..0000000000000000000000000000000000000000
--- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/leres/pix2pix/options/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-"""This package options includes option modules: training options, test options, and basic options (used in both training and test)."""
diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/mmpkg/mmcv/video/io.py b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/mmpkg/mmcv/video/io.py
deleted file mode 100644
index 06ae9b8ae4404ec7822fd49c01c183a0be0cbf35..0000000000000000000000000000000000000000
--- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/mmpkg/mmcv/video/io.py
+++ /dev/null
@@ -1,318 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import os.path as osp
-from collections import OrderedDict
-
-import cv2
-from cv2 import (CAP_PROP_FOURCC, CAP_PROP_FPS, CAP_PROP_FRAME_COUNT,
-                 CAP_PROP_FRAME_HEIGHT, CAP_PROP_FRAME_WIDTH,
-                 CAP_PROP_POS_FRAMES, VideoWriter_fourcc)
-
-from annotator.mmpkg.mmcv.utils import (check_file_exist, mkdir_or_exist, scandir,
-                        track_progress)
-
-
-class Cache:
-
-    def __init__(self, capacity):
-        self._cache = OrderedDict()
-        self._capacity = int(capacity)
-        if capacity <= 0:
-            raise ValueError('capacity must be a positive integer')
-
-    @property
-    def capacity(self):
-        return self._capacity
-
-    @property
-    def size(self):
-        return len(self._cache)
-
-    def put(self, key, val):
-        if key in self._cache:
-            return
-        if len(self._cache) >= self.capacity:
-            self._cache.popitem(last=False)
-        self._cache[key] = val
-
-    def get(self, key, default=None):
-        val = self._cache[key] if key in self._cache else default
-        return val
-
-
-class VideoReader:
-    """Video class with similar usage to a list object.
-
-    This video warpper class provides convenient apis to access frames.
-    There exists an issue of OpenCV's VideoCapture class that jumping to a
-    certain frame may be inaccurate. It is fixed in this class by checking
-    the position after jumping each time.
-    Cache is used when decoding videos. So if the same frame is visited for
-    the second time, there is no need to decode again if it is stored in the
-    cache.
-
-    :Example:
-
-    >>> import annotator.mmpkg.mmcv as mmcv
-    >>> v = mmcv.VideoReader('sample.mp4')
-    >>> len(v)  # get the total frame number with `len()`
-    120
-    >>> for img in v:  # v is iterable
-    >>>     mmcv.imshow(img)
-    >>> v[5]  # get the 6th frame
-    """
-
-    def __init__(self, filename, cache_capacity=10):
-        # Check whether the video path is a url
-        if not filename.startswith(('https://', 'http://')):
-            check_file_exist(filename, 'Video file not found: ' + filename)
-        self._vcap = cv2.VideoCapture(filename)
-        assert cache_capacity > 0
-        self._cache = Cache(cache_capacity)
-        self._position = 0
-        # get basic info
-        self._width = int(self._vcap.get(CAP_PROP_FRAME_WIDTH))
-        self._height = int(self._vcap.get(CAP_PROP_FRAME_HEIGHT))
-        self._fps = self._vcap.get(CAP_PROP_FPS)
-        self._frame_cnt = int(self._vcap.get(CAP_PROP_FRAME_COUNT))
-        self._fourcc = self._vcap.get(CAP_PROP_FOURCC)
-
-    @property
-    def vcap(self):
-        """:obj:`cv2.VideoCapture`: The raw VideoCapture object."""
-        return self._vcap
-
-    @property
-    def opened(self):
-        """bool: Indicate whether the video is opened."""
-        return self._vcap.isOpened()
-
-    @property
-    def width(self):
-        """int: Width of video frames."""
-        return self._width
-
-    @property
-    def height(self):
-        """int: Height of video frames."""
-        return self._height
-
-    @property
-    def resolution(self):
-        """tuple: Video resolution (width, height)."""
-        return (self._width, self._height)
-
-    @property
-    def fps(self):
-        """float: FPS of the video."""
-        return self._fps
-
-    @property
-    def frame_cnt(self):
-        """int: Total frames of the video."""
-        return self._frame_cnt
-
-    @property
-    def fourcc(self):
-        """str: "Four character code" of the video."""
-        return self._fourcc
-
-    @property
-    def position(self):
-        """int: Current cursor position, indicating frame decoded."""
-        return self._position
-
-    def _get_real_position(self):
-        return int(round(self._vcap.get(CAP_PROP_POS_FRAMES)))
-
-    def _set_real_position(self, frame_id):
-        self._vcap.set(CAP_PROP_POS_FRAMES, frame_id)
-        pos = self._get_real_position()
-        for _ in range(frame_id - pos):
-            self._vcap.read()
-        self._position = frame_id
-
-    def read(self):
-        """Read the next frame.
-
-        If the next frame have been decoded before and in the cache, then
-        return it directly, otherwise decode, cache and return it.
-
-        Returns:
-            ndarray or None: Return the frame if successful, otherwise None.
-        """
-        # pos = self._position
-        if self._cache:
-            img = self._cache.get(self._position)
-            if img is not None:
-                ret = True
-            else:
-                if self._position != self._get_real_position():
-                    self._set_real_position(self._position)
-                ret, img = self._vcap.read()
-                if ret:
-                    self._cache.put(self._position, img)
-        else:
-            ret, img = self._vcap.read()
-        if ret:
-            self._position += 1
-        return img
-
-    def get_frame(self, frame_id):
-        """Get frame by index.
-
-        Args:
-            frame_id (int): Index of the expected frame, 0-based.
-
-        Returns:
-            ndarray or None: Return the frame if successful, otherwise None.
-        """
-        if frame_id < 0 or frame_id >= self._frame_cnt:
-            raise IndexError(
-                f'"frame_id" must be between 0 and {self._frame_cnt - 1}')
-        if frame_id == self._position:
-            return self.read()
-        if self._cache:
-            img = self._cache.get(frame_id)
-            if img is not None:
-                self._position = frame_id + 1
-                return img
-        self._set_real_position(frame_id)
-        ret, img = self._vcap.read()
-        if ret:
-            if self._cache:
-                self._cache.put(self._position, img)
-            self._position += 1
-        return img
-
-    def current_frame(self):
-        """Get the current frame (frame that is just visited).
-
-        Returns:
-            ndarray or None: If the video is fresh, return None, otherwise
-                return the frame.
-        """
-        if self._position == 0:
-            return None
-        return self._cache.get(self._position - 1)
-
-    def cvt2frames(self,
-                   frame_dir,
-                   file_start=0,
-                   filename_tmpl='{:06d}.jpg',
-                   start=0,
-                   max_num=0,
-                   show_progress=True):
-        """Convert a video to frame images.
-
-        Args:
-            frame_dir (str): Output directory to store all the frame images.
-            file_start (int): Filenames will start from the specified number.
-            filename_tmpl (str): Filename template with the index as the
-                placeholder.
-            start (int): The starting frame index.
-            max_num (int): Maximum number of frames to be written.
-            show_progress (bool): Whether to show a progress bar.
-        """
-        mkdir_or_exist(frame_dir)
-        if max_num == 0:
-            task_num = self.frame_cnt - start
-        else:
-            task_num = min(self.frame_cnt - start, max_num)
-        if task_num <= 0:
-            raise ValueError('start must be less than total frame number')
-        if start > 0:
-            self._set_real_position(start)
-
-        def write_frame(file_idx):
-            img = self.read()
-            if img is None:
-                return
-            filename = osp.join(frame_dir, filename_tmpl.format(file_idx))
-            cv2.imwrite(filename, img)
-
-        if show_progress:
-            track_progress(write_frame, range(file_start,
-                                              file_start + task_num))
-        else:
-            for i in range(task_num):
-                write_frame(file_start + i)
-
-    def __len__(self):
-        return self.frame_cnt
-
-    def __getitem__(self, index):
-        if isinstance(index, slice):
-            return [
-                self.get_frame(i)
-                for i in range(*index.indices(self.frame_cnt))
-            ]
-        # support negative indexing
-        if index < 0:
-            index += self.frame_cnt
-            if index < 0:
-                raise IndexError('index out of range')
-        return self.get_frame(index)
-
-    def __iter__(self):
-        self._set_real_position(0)
-        return self
-
-    def __next__(self):
-        img = self.read()
-        if img is not None:
-            return img
-        else:
-            raise StopIteration
-
-    next = __next__
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_value, traceback):
-        self._vcap.release()
-
-
-def frames2video(frame_dir,
-                 video_file,
-                 fps=30,
-                 fourcc='XVID',
-                 filename_tmpl='{:06d}.jpg',
-                 start=0,
-                 end=0,
-                 show_progress=True):
-    """Read the frame images from a directory and join them as a video.
-
-    Args:
-        frame_dir (str): The directory containing video frames.
-        video_file (str): Output filename.
-        fps (float): FPS of the output video.
-        fourcc (str): Fourcc of the output video, this should be compatible
-            with the output file type.
-        filename_tmpl (str): Filename template with the index as the variable.
-        start (int): Starting frame index.
-        end (int): Ending frame index.
-        show_progress (bool): Whether to show a progress bar.
-    """
-    if end == 0:
-        ext = filename_tmpl.split('.')[-1]
-        end = len([name for name in scandir(frame_dir, ext)])
-    first_file = osp.join(frame_dir, filename_tmpl.format(start))
-    check_file_exist(first_file, 'The start frame not found: ' + first_file)
-    img = cv2.imread(first_file)
-    height, width = img.shape[:2]
-    resolution = (width, height)
-    vwriter = cv2.VideoWriter(video_file, VideoWriter_fourcc(*fourcc), fps,
-                              resolution)
-
-    def write_frame(file_idx):
-        filename = osp.join(frame_dir, filename_tmpl.format(file_idx))
-        img = cv2.imread(filename)
-        vwriter.write(img)
-
-    if show_progress:
-        track_progress(write_frame, range(start, end))
-    else:
-        for i in range(start, end):
-            write_frame(i)
-    vwriter.release()
diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/oneformer/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated.h b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/oneformer/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated.h
deleted file mode 100644
index 3bf383b8ed9b358b5313d433a9682c294dfb77e4..0000000000000000000000000000000000000000
--- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/oneformer/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated.h
+++ /dev/null
@@ -1,35 +0,0 @@
-// Copyright (c) Facebook, Inc. and its affiliates.
-#pragma once
-#include <torch/types.h>
-
-namespace detectron2 {
-
-at::Tensor box_iou_rotated_cpu(
-    const at::Tensor& boxes1,
-    const at::Tensor& boxes2);
-
-#if defined(WITH_CUDA) || defined(WITH_HIP)
-at::Tensor box_iou_rotated_cuda(
-    const at::Tensor& boxes1,
-    const at::Tensor& boxes2);
-#endif
-
-// Interface for Python
-// inline is needed to prevent multiple function definitions when this header is
-// included by different cpps
-inline at::Tensor box_iou_rotated(
-    const at::Tensor& boxes1,
-    const at::Tensor& boxes2) {
-  assert(boxes1.device().is_cuda() == boxes2.device().is_cuda());
-  if (boxes1.device().is_cuda()) {
-#if defined(WITH_CUDA) || defined(WITH_HIP)
-    return box_iou_rotated_cuda(boxes1.contiguous(), boxes2.contiguous());
-#else
-    AT_ERROR("Detectron2 is not compiled with GPU support!");
-#endif
-  }
-
-  return box_iou_rotated_cpu(boxes1.contiguous(), boxes2.contiguous());
-}
-
-} // namespace detectron2
diff --git a/spaces/cosmicdream/Image_Variations/app.py b/spaces/cosmicdream/Image_Variations/app.py
deleted file mode 100644
index c150f5fbccf4bfbafe7e337f1441fa851abf14f6..0000000000000000000000000000000000000000
--- a/spaces/cosmicdream/Image_Variations/app.py
+++ /dev/null
@@ -1,64 +0,0 @@
-import gradio as gr 
-from transformers import pipeline
-import multiprocessing
-import torch
-import os
-from psutil import virtual_memory
-from pathlib import Path
-import random
-from datetime import datetime
-import PIL
-from PIL import Image
-import os
-import gc
-from translatepy import Translator, Language
-ts = Translator()
-from deep_translator import DeeplTranslator, GoogleTranslator
-from pathlib import Path
-import csv
-import logging
-import requests
-from rudalle.pipelines import generate_images, show, super_resolution, cherry_pick_by_ruclip
-from rudalle import get_rudalle_model, get_tokenizer, get_vae, get_realesrgan
-from rudalle.utils import seed_everything
-#from ruclip import load as get_ruclip
-import ruclip 
-
-# prepare models:
-#device = 'cuda'
-device = "cuda" if torch.cuda.is_available() else "cpu"
-#device = "cuda"
-print('Using device:', device)
-
-dalle = get_rudalle_model('Malevich', pretrained=True, fp16=True, device=device)
-tokenizer = get_tokenizer()
-vae = get_vae(dwt=True).to(device)
-
-# pipeline utils:
-#TEST--------
-realesrgan = get_realesrgan('x2', device=device)
-clip, processor = ruclip.load('ruclip-vit-base-patch32-384', device=device)
-clip_predictor = ruclip.Predictor(clip, processor, device, bs=8)
-text = 'радуга на фоне ночного города'
-
-#seed_everything(42)
-#pil_images = []
-#scores = []
-#for top_k, top_p, images_num in [
-#    (2048, 0.995, 6),
-#]:
-#    _pil_images, _scores = generate_images(text, tokenizer, model, vae, top_k=top_k, images_num=images_num, #bs=8, top_p=top_p)
-#    pil_images += _pil_images
-#    scores += _scores
-
-def model(text, tokenizer=tokenizer, dalle=dalle, vae=vae, top_k=2048, images_num=1, bs=8, top_p=0.995):
-    pil_images = generate_images(text, tokenizer, dalle, vae, top_k=top_k, images_num=images_num, bs=8, top_p=top_p)
-    pil_images = pil_images[0]
-    return pil_images[0]
-
-seed_everything(42)
-pil_images = []
-
-iface = gr.Interface(fn=model, title="V1", 
-  inputs=[gr.inputs.Textbox(label="Text prompt")],
-  outputs=[gr.outputs.Image(type="pil", label="Generated Image")]).launch(debug=True)
diff --git a/spaces/cozyanduofen/bingo/src/components/ui/tooltip.tsx b/spaces/cozyanduofen/bingo/src/components/ui/tooltip.tsx
deleted file mode 100644
index af1d48beb90dd5ae311796539843700871052cae..0000000000000000000000000000000000000000
--- a/spaces/cozyanduofen/bingo/src/components/ui/tooltip.tsx
+++ /dev/null
@@ -1,30 +0,0 @@
-'use client'
-
-import * as React from 'react'
-import * as TooltipPrimitive from '@radix-ui/react-tooltip'
-
-import { cn } from '@/lib/utils'
-
-const TooltipProvider = TooltipPrimitive.Provider
-
-const Tooltip = TooltipPrimitive.Root
-
-const TooltipTrigger = TooltipPrimitive.Trigger
-
-const TooltipContent = React.forwardRef<
-  React.ElementRef<typeof TooltipPrimitive.Content>,
-  React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
->(({ className, sideOffset = 4, ...props }, ref) => (
-  <TooltipPrimitive.Content
-    ref={ref}
-    sideOffset={sideOffset}
-    className={cn(
-      'z-50 overflow-hidden rounded-md border bg-popover px-3 py-1.5 text-xs font-medium text-popover-foreground shadow-md animate-in fade-in-50 data-[side=bottom]:slide-in-from-top-1 data-[side=left]:slide-in-from-right-1 data-[side=right]:slide-in-from-left-1 data-[side=top]:slide-in-from-bottom-1',
-      className
-    )}
-    {...props}
-  />
-))
-TooltipContent.displayName = TooltipPrimitive.Content.displayName
-
-export { Tooltip, TooltipTrigger, TooltipContent, TooltipProvider }
diff --git a/spaces/crlandsc/tiny-audio-diffusion/app.py b/spaces/crlandsc/tiny-audio-diffusion/app.py
deleted file mode 100644
index a07e23dc0e359398e249a55aa91e8b684dedc65c..0000000000000000000000000000000000000000
--- a/spaces/crlandsc/tiny-audio-diffusion/app.py
+++ /dev/null
@@ -1,240 +0,0 @@
-# Imports
-import gradio as gr
-import os
-import matplotlib.pyplot as plt
-import torch
-import torchaudio
-from torch import nn
-import pytorch_lightning as pl
-from ema_pytorch import EMA
-import yaml
-from audio_diffusion_pytorch import DiffusionModel, UNetV0, VDiffusion, VSampler
-
-
-# Load configs
-def load_configs(config_path):
-    with open(config_path, 'r') as file:
-        config = yaml.safe_load(file)
-    pl_configs = config['model']
-    model_configs = config['model']['model']
-    return pl_configs, model_configs
-
-# plot mel spectrogram
-def plot_mel_spectrogram(sample, sr):
-    transform = torchaudio.transforms.MelSpectrogram(
-        sample_rate=sr,
-        n_fft=1024,
-        hop_length=512,
-        n_mels=80,
-        center=True,
-        norm="slaney",
-    )
-
-    spectrogram = transform(torch.mean(sample, dim=0)) # downmix and cal spectrogram
-    spectrogram = torchaudio.functional.amplitude_to_DB(spectrogram, 1.0, 1e-10, 80.0)
-
-    # Plot the Mel spectrogram
-    fig = plt.figure(figsize=(7, 4))
-    plt.imshow(spectrogram, aspect='auto', origin='lower')
-    plt.colorbar(format='%+2.0f dB')
-    plt.xlabel('Frame')
-    plt.ylabel('Mel Bin')
-    plt.title('Mel Spectrogram')
-    plt.tight_layout()
-    
-    return fig
-
-# Define PyTorch Lightning model
-class Model(pl.LightningModule):
-    def __init__(
-        self,
-        lr: float,
-        lr_beta1: float,
-        lr_beta2: float,
-        lr_eps: float,
-        lr_weight_decay: float,
-        ema_beta: float,
-        ema_power: float,
-        model: nn.Module,
-    ):
-        super().__init__()
-        self.lr = lr
-        self.lr_beta1 = lr_beta1
-        self.lr_beta2 = lr_beta2
-        self.lr_eps = lr_eps
-        self.lr_weight_decay = lr_weight_decay
-        self.model = model
-        self.model_ema = EMA(self.model, beta=ema_beta, power=ema_power)
-
-# Instantiate model (must match model that was trained)
-def load_model(model_configs, pl_configs) -> nn.Module:
-    # Diffusion model
-    model = DiffusionModel(
-        net_t=UNetV0, # The model type used for diffusion (U-Net V0 in this case)
-        in_channels=model_configs['in_channels'], # U-Net: number of input/output (audio) channels
-        channels=model_configs['channels'], # U-Net: channels at each layer
-        factors=model_configs['factors'], # U-Net: downsampling and upsampling factors at each layer
-        items=model_configs['items'], # U-Net: number of repeating items at each layer
-        attentions=model_configs['attentions'], # U-Net: attention enabled/disabled at each layer
-        attention_heads=model_configs['attention_heads'], # U-Net: number of attention heads per attention item
-        attention_features=model_configs['attention_features'], # U-Net: number of attention features per attention item
-        diffusion_t=VDiffusion, # The diffusion method used
-        sampler_t=VSampler # The diffusion sampler used
-    )
-
-    # pl model
-    model = Model(
-        lr=pl_configs['lr'],
-        lr_beta1=pl_configs['lr_beta1'],
-        lr_beta2=pl_configs['lr_beta2'],
-        lr_eps=pl_configs['lr_eps'],
-        lr_weight_decay=pl_configs['lr_weight_decay'],
-        ema_beta=pl_configs['ema_beta'],
-        ema_power=pl_configs['ema_power'],
-        model=model
-    )
-
-    return model
-
-# Assign to GPU
-def assign_to_gpu(model):
-    if torch.cuda.is_available():
-        model = model.to('cuda')
-        print(f"Device: {model.device}")
-    return model
-
-# Load model checkpoint
-def load_checkpoint(model, ckpt_path) -> None:
-    checkpoint = torch.load(ckpt_path, map_location='cpu')['state_dict']
-    model.load_state_dict(checkpoint) # should output "<All keys matched successfully>"
-
-
-# Generate Samples
-def generate_samples(model_name, num_samples, num_steps, init_audio=None, noise_level=0.7, duration=32768):
-    # load_checkpoint
-    ckpt_path = models[model_name]
-    load_checkpoint(model, ckpt_path)
-    
-    if num_samples > 1:
-        duration = int(duration / 2)
-
-    # Generate samples
-    with torch.no_grad():
-        if init_audio:
-            # load audio sample
-            audio_sample = torch.tensor(init_audio[1].T, dtype=torch.float32).unsqueeze(0).to(model.device)
-            audio_sample = audio_sample / torch.max(torch.abs(audio_sample)) # normalize init_audio
-
-            # Trim audio
-            og_shape = audio_sample.shape
-            if duration < og_shape[2]:
-                audio_sample = audio_sample[:,:,:duration]
-            elif duration > og_shape[2]:
-                # Pad tensor with zeros to match sample length
-                audio_sample = torch.concat((audio_sample, torch.zeros(og_shape[0], og_shape[1], duration - og_shape[2]).to(model.device)), dim=2)
-
-        else:
-            audio_sample = torch.zeros((1, 2, int(duration)), device=model.device)
-            noise_level = 1.0
-
-        all_samples = torch.zeros(2, 0)
-        for i in range(num_samples):
-            noise = torch.randn_like(audio_sample, device=model.device) * noise_level # [batch_size, in_channels, length]
-            audio = (audio_sample * abs(1-noise_level)) + noise # add noise
-
-            # generate samples
-            generated_sample = model.model_ema.ema_model.sample(audio, num_steps=num_steps).squeeze(0).cpu() # Suggested num_steps 10-100
-            
-            # concatenate all samples:
-            all_samples = torch.concat((all_samples, generated_sample), dim=1)
-            
-            torch.cuda.empty_cache()
-    
-    fig = plot_mel_spectrogram(all_samples, sr)
-    plt.title(f"{model_name} Mel Spectrogram")
-
-    return (sr, all_samples.cpu().detach().numpy().T), fig # (sample rate, audio), plot
-
-
-# Define Constants & initialize model
-# load model & configs
-sr = 44100 # sampling rate
-config_path = "saved_models/config.yaml" # config path
-pl_configs, model_configs = load_configs(config_path)
-model = load_model(model_configs, pl_configs)
-model = assign_to_gpu(model)
-
-models = {
-    "Kicks": "saved_models/kicks/kicks_v7.ckpt",
-    "Snares": "saved_models/snares/snares_v0.ckpt",
-    "Hi-hats": "saved_models/hihats/hihats_v2.ckpt",
-    "Percussion": "saved_models/percussion/percussion_v0.ckpt"
-}
-
-intro = """
-<h1 style="font-weight: 1400; text-align: center; margin-bottom: 6px;">
-    Tiny Audio Diffusion
-</h1>
-<h3 style="font-weight: 600; text-align: center;">
-    Christopher Landschoot - Audio waveform diffusion built to run on consumer-grade hardware (<2GB VRAM)
-</h3>
-<h4 style="text-align: center; margin-bottom: 6px;">
-    <a href="https://github.com/crlandsc/tiny-audio-diffusion" style="text-decoration: underline;" target="_blank">GitHub Repo</a> 
-    | <a href="https://youtu.be/m6Eh2srtTro" style="text-decoration: underline;" target="_blank">Repo Tutorial Video</a> 
-    | <a href="https://medium.com/towards-data-science/tiny-audio-diffusion-ddc19e90af9b" style="text-decoration: underline;" target="_blank">Towards Data Science Article</a>
-</h4>
-"""
-
-
-with gr.Blocks() as demo:
-    # Layout
-    gr.HTML(intro)
-
-    with gr.Row(equal_height=False):
-        with gr.Column():
-            # Inputs
-            model_name = gr.Dropdown(choices=list(models.keys()), value=list(models.keys())[3], label="Model")
-            num_samples = gr.Slider(1, 25, step=1, label="Number of Samples to Generate", value=3)
-            num_steps = gr.Slider(1, 100, step=1, label="Number of Diffusion Steps", value=15)
-            
-            # Conditioning Audio Input
-            with gr.Accordion("Input Audio (optional)", open=False):
-                init_audio_description = gr.HTML('Upload an audio file to perform conditional "style transfer" diffusion.<br>Leaving input audio blank results in unconditional generation.')
-                init_audio = gr.Audio(label="Input Audio Sample")
-                init_audio_noise = gr.Slider(0, 1, step=0.01, label="Noise to add to input audio", value=0.70)#, visible=True)
-
-                # Examples
-                gr.Examples(
-                    examples=[
-                        os.path.join(os.path.dirname(__file__), "samples", "guitar.wav"),
-                        os.path.join(os.path.dirname(__file__), "samples", "snare.wav"),
-                        os.path.join(os.path.dirname(__file__), "samples", "kick.wav"),
-                        os.path.join(os.path.dirname(__file__), "samples", "hihat.wav")
-                    ],
-                    inputs=init_audio,
-                    label="Example Audio Inputs"
-                )
-
-            # Buttons
-            with gr.Row():
-                with gr.Column():
-                    clear_button = gr.Button(value="Reset All")
-                with gr.Column():
-                    generate_btn = gr.Button("Generate Samples!")
-            
-        with gr.Column():
-            # Outputs
-            output_audio = gr.Audio(label="Generated Audio Sample")
-            output_plot = gr.Plot(label="Generated Audio Spectrogram")
-        
-    # Functionality
-    # Generate samples
-    generate_btn.click(fn=generate_samples, inputs=[model_name, num_samples, num_steps, init_audio, init_audio_noise], outputs=[output_audio, output_plot])
-
-    # clear_button button to reset everything
-    clear_button.click(fn=lambda: [3, 15, None, 0.70, None, None], outputs=[num_samples, num_steps, init_audio, init_audio_noise, output_audio, output_plot])
-
-
-
-if __name__ == "__main__":    
-    demo.launch()
\ No newline at end of file
diff --git a/spaces/csuhan/opendet2/opendet2/modeling/meta_arch/__init__.py b/spaces/csuhan/opendet2/opendet2/modeling/meta_arch/__init__.py
deleted file mode 100644
index 8b336b1d503a36e7353736cfb68185227abc7af6..0000000000000000000000000000000000000000
--- a/spaces/csuhan/opendet2/opendet2/modeling/meta_arch/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-from .retinanet import OpenSetRetinaNet
-
-__all__ = list(globals().keys())
diff --git a/spaces/cybercorejapan/human-detection-docker/projects/scripts/start.sh b/spaces/cybercorejapan/human-detection-docker/projects/scripts/start.sh
deleted file mode 100644
index a7136529c980d4e289a810ec687f380f2f8063ab..0000000000000000000000000000000000000000
--- a/spaces/cybercorejapan/human-detection-docker/projects/scripts/start.sh
+++ /dev/null
@@ -1,2 +0,0 @@
-export CUDA_VISIBLE_DEVICES=3
-gradio traffic_monitoring/demo_app.py
\ No newline at end of file
diff --git a/spaces/cyberoleg/b2719240e190e2a649150d94db50be82838efeb0/diffusion_webui/utils/scheduler_list.py b/spaces/cyberoleg/b2719240e190e2a649150d94db50be82838efeb0/diffusion_webui/utils/scheduler_list.py
deleted file mode 100644
index 1e47475ca4d123a13c736112d96891ebb5aac43a..0000000000000000000000000000000000000000
--- a/spaces/cyberoleg/b2719240e190e2a649150d94db50be82838efeb0/diffusion_webui/utils/scheduler_list.py
+++ /dev/null
@@ -1,39 +0,0 @@
-from diffusers import (
-    DDIMScheduler,
-    DDPMScheduler,
-    DEISMultistepScheduler,
-    DPMSolverMultistepScheduler,
-    DPMSolverSinglestepScheduler,
-    EulerAncestralDiscreteScheduler,
-    EulerDiscreteScheduler,
-    HeunDiscreteScheduler,
-    KDPM2AncestralDiscreteScheduler,
-    KDPM2DiscreteScheduler,
-    PNDMScheduler,
-    UniPCMultistepScheduler,
-)
-
-SCHEDULER_MAPPING = {
-    "DDIM": DDIMScheduler,
-    "DDPMScheduler": DDPMScheduler,
-    "DEISMultistep": DEISMultistepScheduler,
-    "DPMSolverMultistep": DPMSolverMultistepScheduler,
-    "DPMSolverSinglestep": DPMSolverSinglestepScheduler,
-    "EulerAncestralDiscrete": EulerAncestralDiscreteScheduler,
-    "EulerDiscrete": EulerDiscreteScheduler,
-    "HeunDiscrete": HeunDiscreteScheduler,
-    "KDPM2AncestralDiscrete": KDPM2AncestralDiscreteScheduler,
-    "KDPM2Discrete": KDPM2DiscreteScheduler,
-    "PNDMScheduler": PNDMScheduler,
-    "UniPCMultistep": UniPCMultistepScheduler,
-}
-
-
-def get_scheduler(pipe, scheduler):
-    if scheduler in SCHEDULER_MAPPING:
-        SchedulerClass = SCHEDULER_MAPPING[scheduler]
-        pipe.scheduler = SchedulerClass.from_config(pipe.scheduler.config)
-    else:
-        raise ValueError(f"Invalid scheduler name {scheduler}")
-
-    return pipe
diff --git a/spaces/cymic/Waifu_Diffusion_Webui/scripts/prompts_from_file.py b/spaces/cymic/Waifu_Diffusion_Webui/scripts/prompts_from_file.py
deleted file mode 100644
index 872a7e3e92999cfd1094a0c3c66e7c9ecff36c9c..0000000000000000000000000000000000000000
--- a/spaces/cymic/Waifu_Diffusion_Webui/scripts/prompts_from_file.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import math
-import os
-import sys
-import traceback
-
-import modules.scripts as scripts
-import gradio as gr
-
-from modules.processing import Processed, process_images
-from PIL import Image
-from modules.shared import opts, cmd_opts, state
-
-
-class Script(scripts.Script):
-    def title(self):
-        return "Prompts from file or textbox"
-
-    def ui(self, is_img2img):
-        # This checkbox would look nicer as two tabs, but there are two problems:
-        # 1) There is a bug in Gradio 3.3 that prevents visibility from working on Tabs
-        # 2) Even with Gradio 3.3.1, returning a control (like Tabs) that can't be used as input
-        #    causes a AttributeError: 'Tabs' object has no attribute 'preprocess' assert,
-        #    due to the way Script assumes all controls returned can be used as inputs.
-        # Therefore, there's no good way to use grouping components right now,
-        # so we will use a checkbox! :)
-        checkbox_txt = gr.Checkbox(label="Show Textbox", value=False)
-        file = gr.File(label="File with inputs", type='bytes')
-        prompt_txt = gr.TextArea(label="Prompts")
-        checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
-        return [checkbox_txt, file, prompt_txt]
-
-    def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
-        if (checkbox_txt):
-            lines = [x.strip() for x in prompt_txt.splitlines()]
-        else:
-            lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
-        lines = [x for x in lines if len(x) > 0]
-
-        img_count = len(lines) * p.n_iter
-        batch_count = math.ceil(img_count / p.batch_size)
-        loop_count = math.ceil(batch_count / p.n_iter)
-        print(f"Will process {img_count} images in {batch_count} batches.")
-
-        p.do_not_save_grid = True
-
-        state.job_count = batch_count
-
-        images = []
-        for loop_no in range(loop_count):
-            state.job = f"{loop_no + 1} out of {loop_count}"
-            p.prompt = lines[loop_no*p.batch_size:(loop_no+1)*p.batch_size] * p.n_iter
-            proc = process_images(p)
-            images += proc.images
-
-        return Processed(p, images, p.seed, "")
diff --git a/spaces/cynika/taffy/commons.py b/spaces/cynika/taffy/commons.py
deleted file mode 100644
index 074888006392e956ce204d8368362dbb2cd4e304..0000000000000000000000000000000000000000
--- a/spaces/cynika/taffy/commons.py
+++ /dev/null
@@ -1,188 +0,0 @@
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-def slice_pitch_segments(x, ids_str, segment_size=4):
-  ret = torch.zeros_like(x[:, :segment_size])
-  for i in range(x.size(0)):
-    idx_str = ids_str[i]
-    idx_end = idx_str + segment_size
-    ret[i] = x[i, idx_str:idx_end]
-  return ret
-
-def rand_slice_segments_with_pitch(x, pitch, x_lengths=None, segment_size=4):
-  b, d, t = x.size()
-  if x_lengths is None:
-    x_lengths = t
-  ids_str_max = x_lengths - segment_size + 1
-  ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
-  ret = slice_segments(x, ids_str, segment_size)
-  ret_pitch = slice_pitch_segments(pitch, ids_str, segment_size)
-  return ret, ret_pitch, ids_str
-
-def init_weights(m, mean=0.0, std=0.01):
-  classname = m.__class__.__name__
-  if classname.find("Conv") != -1:
-    m.weight.data.normal_(mean, std)
-
-
-def get_padding(kernel_size, dilation=1):
-  return int((kernel_size*dilation - dilation)/2)
-
-
-def convert_pad_shape(pad_shape):
-  l = pad_shape[::-1]
-  pad_shape = [item for sublist in l for item in sublist]
-  return pad_shape
-
-
-def intersperse(lst, item):
-  result = [item] * (len(lst) * 2 + 1)
-  result[1::2] = lst
-  return result
-
-
-def kl_divergence(m_p, logs_p, m_q, logs_q):
-  """KL(P||Q)"""
-  kl = (logs_q - logs_p) - 0.5
-  kl += 0.5 * (torch.exp(2. * logs_p) + ((m_p - m_q)**2)) * torch.exp(-2. * logs_q)
-  return kl
-
-
-def rand_gumbel(shape):
-  """Sample from the Gumbel distribution, protect from overflows."""
-  uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
-  return -torch.log(-torch.log(uniform_samples))
-
-
-def rand_gumbel_like(x):
-  g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
-  return g
-
-
-def slice_segments(x, ids_str, segment_size=4):
-  ret = torch.zeros_like(x[:, :, :segment_size])
-  for i in range(x.size(0)):
-    idx_str = ids_str[i]
-    idx_end = idx_str + segment_size
-    ret[i] = x[i, :, idx_str:idx_end]
-  return ret
-
-
-def rand_slice_segments(x, x_lengths=None, segment_size=4):
-  b, d, t = x.size()
-  if x_lengths is None:
-    x_lengths = t
-  ids_str_max = x_lengths - segment_size + 1
-  ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
-  ret = slice_segments(x, ids_str, segment_size)
-  return ret, ids_str
-
-
-def rand_spec_segments(x, x_lengths=None, segment_size=4):
-  b, d, t = x.size()
-  if x_lengths is None:
-    x_lengths = t
-  ids_str_max = x_lengths - segment_size
-  ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
-  ret = slice_segments(x, ids_str, segment_size)
-  return ret, ids_str
-
-
-def get_timing_signal_1d(
-    length, channels, min_timescale=1.0, max_timescale=1.0e4):
-  position = torch.arange(length, dtype=torch.float)
-  num_timescales = channels // 2
-  log_timescale_increment = (
-      math.log(float(max_timescale) / float(min_timescale)) /
-      (num_timescales - 1))
-  inv_timescales = min_timescale * torch.exp(
-      torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment)
-  scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
-  signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
-  signal = F.pad(signal, [0, 0, 0, channels % 2])
-  signal = signal.view(1, channels, length)
-  return signal
-
-
-def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
-  b, channels, length = x.size()
-  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-  return x + signal.to(dtype=x.dtype, device=x.device)
-
-
-def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
-  b, channels, length = x.size()
-  signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-  return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
-
-
-def subsequent_mask(length):
-  mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
-  return mask
-
-
-@torch.jit.script
-def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
-  n_channels_int = n_channels[0]
-  in_act = input_a + input_b
-  t_act = torch.tanh(in_act[:, :n_channels_int, :])
-  s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
-  acts = t_act * s_act
-  return acts
-
-
-def convert_pad_shape(pad_shape):
-  l = pad_shape[::-1]
-  pad_shape = [item for sublist in l for item in sublist]
-  return pad_shape
-
-
-def shift_1d(x):
-  x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
-  return x
-
-
-def sequence_mask(length, max_length=None):
-  if max_length is None:
-    max_length = length.max()
-  x = torch.arange(max_length, dtype=length.dtype, device=length.device)
-  return x.unsqueeze(0) < length.unsqueeze(1)
-
-
-def generate_path(duration, mask):
-  """
-  duration: [b, 1, t_x]
-  mask: [b, 1, t_y, t_x]
-  """
-  device = duration.device
-  
-  b, _, t_y, t_x = mask.shape
-  cum_duration = torch.cumsum(duration, -1)
-  
-  cum_duration_flat = cum_duration.view(b * t_x)
-  path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
-  path = path.view(b, t_x, t_y)
-  path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
-  path = path.unsqueeze(1).transpose(2,3) * mask
-  return path
-
-
-def clip_grad_value_(parameters, clip_value, norm_type=2):
-  if isinstance(parameters, torch.Tensor):
-    parameters = [parameters]
-  parameters = list(filter(lambda p: p.grad is not None, parameters))
-  norm_type = float(norm_type)
-  if clip_value is not None:
-    clip_value = float(clip_value)
-
-  total_norm = 0
-  for p in parameters:
-    param_norm = p.grad.data.norm(norm_type)
-    total_norm += param_norm.item() ** norm_type
-    if clip_value is not None:
-      p.grad.data.clamp_(min=-clip_value, max=clip_value)
-  total_norm = total_norm ** (1. / norm_type)
-  return total_norm
diff --git a/spaces/dasanik2001/FYP_G15_RCCIIT/README.md b/spaces/dasanik2001/FYP_G15_RCCIIT/README.md
deleted file mode 100644
index 19e1982727488dbef17dbf1809e38911c0f77d86..0000000000000000000000000000000000000000
--- a/spaces/dasanik2001/FYP_G15_RCCIIT/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: FYP G15 RCCIIT
-emoji: 🌍
-colorFrom: purple
-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/davertor/colorizing_images/deoldify/device_id.py b/spaces/davertor/colorizing_images/deoldify/device_id.py
deleted file mode 100644
index 4c363a2080e0a5ae9f550987843596f734809e27..0000000000000000000000000000000000000000
--- a/spaces/davertor/colorizing_images/deoldify/device_id.py
+++ /dev/null
@@ -1,12 +0,0 @@
-from enum import IntEnum
-
-class DeviceId(IntEnum):
-    GPU0 = 0,
-    GPU1 = 1,
-    GPU2 = 2,
-    GPU3 = 3,
-    GPU4 = 4,
-    GPU5 = 5,
-    GPU6 = 6,
-    GPU7 = 7,
-    CPU = 99
diff --git a/spaces/davidpiscasio/unpaired-img2img/util/visualizer.py b/spaces/davidpiscasio/unpaired-img2img/util/visualizer.py
deleted file mode 100644
index 5ae173808ecedf5097fc7dcf8315096e81d2ed03..0000000000000000000000000000000000000000
--- a/spaces/davidpiscasio/unpaired-img2img/util/visualizer.py
+++ /dev/null
@@ -1,257 +0,0 @@
-import numpy as np
-import os
-import sys
-import ntpath
-import time
-from . import util, html
-from subprocess import Popen, PIPE
-
-
-try:
-    import wandb
-except ImportError:
-    print('Warning: wandb package cannot be found. The option "--use_wandb" will result in error.')
-
-if sys.version_info[0] == 2:
-    VisdomExceptionBase = Exception
-else:
-    VisdomExceptionBase = ConnectionError
-
-
-def save_images(webpage, visuals, image_path, aspect_ratio=1.0, width=256, use_wandb=False):
-    """Save images to the disk.
-
-    Parameters:
-        webpage (the HTML class) -- the HTML webpage class that stores these imaegs (see html.py for more details)
-        visuals (OrderedDict)    -- an ordered dictionary that stores (name, images (either tensor or numpy) ) pairs
-        image_path (str)         -- the string is used to create image paths
-        aspect_ratio (float)     -- the aspect ratio of saved images
-        width (int)              -- the images will be resized to width x width
-
-    This function will save images stored in 'visuals' to the HTML file specified by 'webpage'.
-    """
-    image_dir = webpage.get_image_dir()
-    short_path = ntpath.basename(image_path[0])
-    name = os.path.splitext(short_path)[0]
-
-    webpage.add_header(name)
-    ims, txts, links = [], [], []
-    ims_dict = {}
-    for label, im_data in visuals.items():
-        im = util.tensor2im(im_data)
-        image_name = '%s_%s.png' % (name, label)
-        save_path = os.path.join(image_dir, image_name)
-        util.save_image(im, save_path, aspect_ratio=aspect_ratio)
-        ims.append(image_name)
-        txts.append(label)
-        links.append(image_name)
-        if use_wandb:
-            ims_dict[label] = wandb.Image(im)
-    webpage.add_images(ims, txts, links, width=width)
-    if use_wandb:
-        wandb.log(ims_dict)
-
-
-class Visualizer():
-    """This class includes several functions that can display/save images and print/save logging information.
-
-    It uses a Python library 'visdom' for display, and a Python library 'dominate' (wrapped in 'HTML') for creating HTML files with images.
-    """
-
-    def __init__(self, opt):
-        """Initialize the Visualizer class
-
-        Parameters:
-            opt -- stores all the experiment flags; needs to be a subclass of BaseOptions
-        Step 1: Cache the training/test options
-        Step 2: connect to a visdom server
-        Step 3: create an HTML object for saveing HTML filters
-        Step 4: create a logging file to store training losses
-        """
-        self.opt = opt  # cache the option
-        self.display_id = opt.display_id
-        self.use_html = opt.isTrain and not opt.no_html
-        self.win_size = opt.display_winsize
-        self.name = opt.name
-        self.port = opt.display_port
-        self.saved = False
-        self.use_wandb = opt.use_wandb
-        self.current_epoch = 0
-        self.ncols = opt.display_ncols
-        
-        if self.display_id > 0:  # connect to a visdom server given <display_port> and <display_server>
-            import visdom
-            self.vis = visdom.Visdom(server=opt.display_server, port=opt.display_port, env=opt.display_env)
-            if not self.vis.check_connection():
-                self.create_visdom_connections()
-
-        if self.use_wandb:
-            self.wandb_run = wandb.init(project='CycleGAN-and-pix2pix', name=opt.name, config=opt) if not wandb.run else wandb.run
-            self.wandb_run._label(repo='CycleGAN-and-pix2pix')
-
-        if self.use_html:  # create an HTML object at <checkpoints_dir>/web/; images will be saved under <checkpoints_dir>/web/images/
-            self.web_dir = os.path.join(opt.checkpoints_dir, opt.name, 'web')
-            self.img_dir = os.path.join(self.web_dir, 'images')
-            print('create web directory %s...' % self.web_dir)
-            util.mkdirs([self.web_dir, self.img_dir])
-        # create a logging file to store training losses
-        self.log_name = os.path.join(opt.checkpoints_dir, opt.name, 'loss_log.txt')
-        with open(self.log_name, "a") as log_file:
-            now = time.strftime("%c")
-            log_file.write('================ Training Loss (%s) ================\n' % now)
-
-    def reset(self):
-        """Reset the self.saved status"""
-        self.saved = False
-
-    def create_visdom_connections(self):
-        """If the program could not connect to Visdom server, this function will start a new server at port < self.port > """
-        cmd = sys.executable + ' -m visdom.server -p %d &>/dev/null &' % self.port
-        print('\n\nCould not connect to Visdom server. \n Trying to start a server....')
-        print('Command: %s' % cmd)
-        Popen(cmd, shell=True, stdout=PIPE, stderr=PIPE)
-
-    def display_current_results(self, visuals, epoch, save_result):
-        """Display current results on visdom; save current results to an HTML file.
-
-        Parameters:
-            visuals (OrderedDict) - - dictionary of images to display or save
-            epoch (int) - - the current epoch
-            save_result (bool) - - if save the current results to an HTML file
-        """
-        if self.display_id > 0:  # show images in the browser using visdom
-            ncols = self.ncols
-            if ncols > 0:        # show all the images in one visdom panel
-                ncols = min(ncols, len(visuals))
-                h, w = next(iter(visuals.values())).shape[:2]
-                table_css = """<style>
-                        table {border-collapse: separate; border-spacing: 4px; white-space: nowrap; text-align: center}
-                        table td {width: % dpx; height: % dpx; padding: 4px; outline: 4px solid black}
-                        </style>""" % (w, h)  # create a table css
-                # create a table of images.
-                title = self.name
-                label_html = ''
-                label_html_row = ''
-                images = []
-                idx = 0
-                for label, image in visuals.items():
-                    image_numpy = util.tensor2im(image)
-                    label_html_row += '<td>%s</td>' % label
-                    images.append(image_numpy.transpose([2, 0, 1]))
-                    idx += 1
-                    if idx % ncols == 0:
-                        label_html += '<tr>%s</tr>' % label_html_row
-                        label_html_row = ''
-                white_image = np.ones_like(image_numpy.transpose([2, 0, 1])) * 255
-                while idx % ncols != 0:
-                    images.append(white_image)
-                    label_html_row += '<td></td>'
-                    idx += 1
-                if label_html_row != '':
-                    label_html += '<tr>%s</tr>' % label_html_row
-                try:
-                    self.vis.images(images, nrow=ncols, win=self.display_id + 1,
-                                    padding=2, opts=dict(title=title + ' images'))
-                    label_html = '<table>%s</table>' % label_html
-                    self.vis.text(table_css + label_html, win=self.display_id + 2,
-                                  opts=dict(title=title + ' labels'))
-                except VisdomExceptionBase:
-                    self.create_visdom_connections()
-
-            else:     # show each image in a separate visdom panel;
-                idx = 1
-                try:
-                    for label, image in visuals.items():
-                        image_numpy = util.tensor2im(image)
-                        self.vis.image(image_numpy.transpose([2, 0, 1]), opts=dict(title=label),
-                                       win=self.display_id + idx)
-                        idx += 1
-                except VisdomExceptionBase:
-                    self.create_visdom_connections()
-
-        if self.use_wandb:
-            columns = [key for key, _ in visuals.items()]
-            columns.insert(0,'epoch')
-            result_table = wandb.Table(columns=columns)
-            table_row = [epoch]
-            ims_dict = {}
-            for label, image in visuals.items():
-                image_numpy = util.tensor2im(image)
-                wandb_image = wandb.Image(image_numpy)
-                table_row.append(wandb_image)
-                ims_dict[label] = wandb_image
-            self.wandb_run.log(ims_dict)
-            if epoch != self.current_epoch:
-                self.current_epoch = epoch
-                result_table.add_data(*table_row)
-                self.wandb_run.log({"Result": result_table})
-
-
-        if self.use_html and (save_result or not self.saved):  # save images to an HTML file if they haven't been saved.
-            self.saved = True
-            # save images to the disk
-            for label, image in visuals.items():
-                image_numpy = util.tensor2im(image)
-                img_path = os.path.join(self.img_dir, 'epoch%.3d_%s.png' % (epoch, label))
-                util.save_image(image_numpy, img_path)
-
-            # update website
-            webpage = html.HTML(self.web_dir, 'Experiment name = %s' % self.name, refresh=1)
-            for n in range(epoch, 0, -1):
-                webpage.add_header('epoch [%d]' % n)
-                ims, txts, links = [], [], []
-
-                for label, image_numpy in visuals.items():
-                    image_numpy = util.tensor2im(image)
-                    img_path = 'epoch%.3d_%s.png' % (n, label)
-                    ims.append(img_path)
-                    txts.append(label)
-                    links.append(img_path)
-                webpage.add_images(ims, txts, links, width=self.win_size)
-            webpage.save()
-
-    def plot_current_losses(self, epoch, counter_ratio, losses):
-        """display the current losses on visdom display: dictionary of error labels and values
-
-        Parameters:
-            epoch (int)           -- current epoch
-            counter_ratio (float) -- progress (percentage) in the current epoch, between 0 to 1
-            losses (OrderedDict)  -- training losses stored in the format of (name, float) pairs
-        """
-        if not hasattr(self, 'plot_data'):
-            self.plot_data = {'X': [], 'Y': [], 'legend': list(losses.keys())}
-        self.plot_data['X'].append(epoch + counter_ratio)
-        self.plot_data['Y'].append([losses[k] for k in self.plot_data['legend']])
-        try:
-            self.vis.line(
-                X=np.stack([np.array(self.plot_data['X'])] * len(self.plot_data['legend']), 1),
-                Y=np.array(self.plot_data['Y']),
-                opts={
-                    'title': self.name + ' loss over time',
-                    'legend': self.plot_data['legend'],
-                    'xlabel': 'epoch',
-                    'ylabel': 'loss'},
-                win=self.display_id)
-        except VisdomExceptionBase:
-            self.create_visdom_connections()
-        if self.use_wandb:
-            self.wandb_run.log(losses)
-
-    # losses: same format as |losses| of plot_current_losses
-    def print_current_losses(self, epoch, iters, losses, t_comp, t_data):
-        """print current losses on console; also save the losses to the disk
-
-        Parameters:
-            epoch (int) -- current epoch
-            iters (int) -- current training iteration during this epoch (reset to 0 at the end of every epoch)
-            losses (OrderedDict) -- training losses stored in the format of (name, float) pairs
-            t_comp (float) -- computational time per data point (normalized by batch_size)
-            t_data (float) -- data loading time per data point (normalized by batch_size)
-        """
-        message = '(epoch: %d, iters: %d, time: %.3f, data: %.3f) ' % (epoch, iters, t_comp, t_data)
-        for k, v in losses.items():
-            message += '%s: %.3f ' % (k, v)
-
-        print(message)  # print the message
-        with open(self.log_name, "a") as log_file:
-            log_file.write('%s\n' % message)  # save the message
diff --git a/spaces/davila7/filegpt/utils.py b/spaces/davila7/filegpt/utils.py
deleted file mode 100644
index 8d5a715335313d061c3ead3aec8ec6d10191cf64..0000000000000000000000000000000000000000
--- a/spaces/davila7/filegpt/utils.py
+++ /dev/null
@@ -1,183 +0,0 @@
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.vectorstores.faiss import FAISS
-from langchain import OpenAI, Cohere
-from langchain.chains.qa_with_sources import load_qa_with_sources_chain
-from embeddings import OpenAIEmbeddings
-from langchain.llms import OpenAI
-from langchain.docstore.document import Document
-from langchain.vectorstores import FAISS, VectorStore
-import docx2txt
-from typing import List, Dict, Any
-import re
-import numpy as np
-from io import StringIO
-from io import BytesIO
-import streamlit as st
-from prompts import STUFF_PROMPT
-from pypdf import PdfReader
-from openai.error import AuthenticationError
-import pptx
-
-@st.experimental_memo()
-def parse_docx(file: BytesIO) -> str:
-    text = docx2txt.process(file)
-    # Remove multiple newlines
-    text = re.sub(r"\n\s*\n", "\n\n", text)
-    return text
-
-
-@st.experimental_memo()
-def parse_pdf(file: BytesIO) -> List[str]:
-    pdf = PdfReader(file)
-    output = []
-    for page in pdf.pages:
-        text = page.extract_text()
-        # Merge hyphenated words
-        text = re.sub(r"(\w+)-\n(\w+)", r"\1\2", text)
-        # Fix newlines in the middle of sentences
-        text = re.sub(r"(?<!\n\s)\n(?!\s\n)", " ", text.strip())
-        # Remove multiple newlines
-        text = re.sub(r"\n\s*\n", "\n\n", text)
-
-        output.append(text)
-
-    return output
-
-
-@st.experimental_memo()
-def parse_txt(file: BytesIO) -> str:
-    text = file.read().decode("utf-8")
-    # Remove multiple newlines
-    text = re.sub(r"\n\s*\n", "\n\n", text)
-    return text
-
-@st.experimental_memo()
-def parse_pptx(file: BytesIO) -> str:
-    
-    ppt_file = pptx.Presentation(file)
-
-    string_data = ""
-    
-    for slide in ppt_file.slides:
-        for shape in slide.shapes:
-            if shape.has_text_frame:
-                string_data += shape.text_frame.text + '\n'
-    return string_data
-
-@st.experimental_memo()
-def parse_csv(uploaded_file):
-    # To read file as bytes:
-    #bytes_data = uploaded_file.getvalue()
-    #st.write(bytes_data)
-
-    # To convert to a string based IO:
-    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
-    #st.write(stringio)
-
-    # To read file as string:
-    string_data = stringio.read()
-    #st.write(string_data)
-
-    # Can be used wherever a "file-like" object is accepted:
-    # dataframe = pd.read_csv(uploaded_file)
-    return string_data
-
-@st.experimental_memo()
-def parse_any(uploaded_file):
-    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
-    string_data = stringio.read()
-    return string_data
-
-@st.cache(allow_output_mutation=True)
-def text_to_docs(text: str) -> List[Document]:
-    """Converts a string or list of strings to a list of Documents
-    with metadata."""
-    if isinstance(text, str):
-        # Take a single string as one page
-        text = [text]
-    page_docs = [Document(page_content=page) for page in text]
-
-    # Add page numbers as metadata
-    for i, doc in enumerate(page_docs):
-        doc.metadata["page"] = i + 1
-
-    # Split pages into chunks
-    doc_chunks = []
-
-    for doc in page_docs:
-        text_splitter = RecursiveCharacterTextSplitter(
-            chunk_size=800,
-            separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""],
-            chunk_overlap=0,
-        )
-        chunks = text_splitter.split_text(doc.page_content)
-        for i, chunk in enumerate(chunks):
-            doc = Document(
-                page_content=chunk, metadata={"page": doc.metadata["page"], "chunk": i}
-            )
-            # Add sources a metadata
-            doc.metadata["source"] = f"{doc.metadata['page']}-{doc.metadata['chunk']}"
-            doc_chunks.append(doc)
-    return doc_chunks
-
-
-@st.cache(allow_output_mutation=True, show_spinner=False)
-def embed_docs(docs: List[Document]) -> VectorStore:
-    """Embeds a list of Documents and returns a FAISS index"""
-
-    if not st.session_state.get("OPENAI_API_KEY"):
-        raise AuthenticationError(
-            "Enter your OpenAI API key in the sidebar. You can get a key at https://platform.openai.com/account/api-keys."
-        )
-    else:
-        # Embed the chunks
-        embeddings = OpenAIEmbeddings(openai_api_key=st.session_state.get("OPENAI_API_KEY"))  # type: ignore
-        index = FAISS.from_documents(docs, embeddings)
-
-        return index
-
-
-@st.cache(allow_output_mutation=True)
-def search_docs(index: VectorStore, query: str) -> List[Document]:
-    """Searches a FAISS index for similar chunks to the query
-    and returns a list of Documents."""
-
-    # Search for similar chunks
-    docs = index.similarity_search(query, k=5)
-    return docs
-
-
-@st.cache(allow_output_mutation=True)
-def get_answer(docs: List[Document], query: str) -> Dict[str, Any]:
-    """Gets an answer to a question from a list of Documents."""
-
-    # Get the answer
-    chain = load_qa_with_sources_chain(OpenAI(temperature=0, openai_api_key=st.session_state.get("OPENAI_API_KEY")), chain_type="stuff", prompt=STUFF_PROMPT)  # type: ignore
-
-    answer = chain(
-        {"input_documents": docs, "question": query}, return_only_outputs=True
-    )
-    return answer
-
-
-@st.cache(allow_output_mutation=True)
-def get_sources(answer: Dict[str, Any], docs: List[Document]) -> List[Document]:
-    """Gets the source documents for an answer."""
-
-    # Get sources for the answer
-    source_keys = [s for s in answer["output_text"].split("SOURCES: ")[-1].split(", ")]
-
-    source_docs = []
-    for doc in docs:
-        if doc.metadata["source"] in source_keys:
-            source_docs.append(doc)
-
-    return source_docs
-
-
-def wrap_text_in_html(text: str) -> str:
-    """Wraps each text block separated by newlines in <p> tags"""
-    if isinstance(text, list):
-        # Add horizontal rules between pages
-        text = "\n<hr/>\n".join(text)
-    return "".join([f"<p>{line}</p>" for line in text.split("\n")])
\ No newline at end of file
diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fsspec/core.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fsspec/core.py
deleted file mode 100644
index ef497992feebee0f670c0d41df41848bd189cfcd..0000000000000000000000000000000000000000
--- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fsspec/core.py
+++ /dev/null
@@ -1,682 +0,0 @@
-from __future__ import absolute_import, division, print_function
-
-import io
-import logging
-import os
-import re
-from glob import has_magic
-
-# for backwards compat, we export cache things from here too
-from .caching import (  # noqa: F401
-    BaseCache,
-    BlockCache,
-    BytesCache,
-    MMapCache,
-    ReadAheadCache,
-    caches,
-)
-from .compression import compr
-from .registry import filesystem, get_filesystem_class
-from .utils import (
-    _unstrip_protocol,
-    build_name_function,
-    infer_compression,
-    stringify_path,
-)
-
-logger = logging.getLogger("fsspec")
-
-
-class OpenFile:
-    """
-    File-like object to be used in a context
-
-    Can layer (buffered) text-mode and compression over any file-system, which
-    are typically binary-only.
-
-    These instances are safe to serialize, as the low-level file object
-    is not created until invoked using ``with``.
-
-    Parameters
-    ----------
-    fs: FileSystem
-        The file system to use for opening the file. Should be a subclass or duck-type
-        with ``fsspec.spec.AbstractFileSystem``
-    path: str
-        Location to open
-    mode: str like 'rb', optional
-        Mode of the opened file
-    compression: str or None, optional
-        Compression to apply
-    encoding: str or None, optional
-        The encoding to use if opened in text mode.
-    errors: str or None, optional
-        How to handle encoding errors if opened in text mode.
-    newline: None or str
-        Passed to TextIOWrapper in text mode, how to handle line endings.
-    autoopen: bool
-        If True, calls open() immediately. Mostly used by pickle
-    pos: int
-        If given and autoopen is True, seek to this location immediately
-    """
-
-    def __init__(
-        self,
-        fs,
-        path,
-        mode="rb",
-        compression=None,
-        encoding=None,
-        errors=None,
-        newline=None,
-    ):
-        self.fs = fs
-        self.path = path
-        self.mode = mode
-        self.compression = get_compression(path, compression)
-        self.encoding = encoding
-        self.errors = errors
-        self.newline = newline
-        self.fobjects = []
-
-    def __reduce__(self):
-        return (
-            OpenFile,
-            (
-                self.fs,
-                self.path,
-                self.mode,
-                self.compression,
-                self.encoding,
-                self.errors,
-                self.newline,
-            ),
-        )
-
-    def __repr__(self):
-        return "<OpenFile '{}'>".format(self.path)
-
-    def __enter__(self):
-        mode = self.mode.replace("t", "").replace("b", "") + "b"
-
-        f = self.fs.open(self.path, mode=mode)
-
-        self.fobjects = [f]
-
-        if self.compression is not None:
-            compress = compr[self.compression]
-            f = compress(f, mode=mode[0])
-            self.fobjects.append(f)
-
-        if "b" not in self.mode:
-            # assume, for example, that 'r' is equivalent to 'rt' as in builtin
-            f = PickleableTextIOWrapper(
-                f, encoding=self.encoding, errors=self.errors, newline=self.newline
-            )
-            self.fobjects.append(f)
-
-        return self.fobjects[-1]
-
-    def __exit__(self, *args):
-        self.close()
-
-    @property
-    def full_name(self):
-        return _unstrip_protocol(self.path, self.fs)
-
-    def open(self):
-        """Materialise this as a real open file without context
-
-        The OpenFile object should be explicitly closed to avoid enclosed file
-        instances persisting. You must, therefore, keep a reference to the OpenFile
-        during the life of the file-like it generates.
-        """
-        return self.__enter__()
-
-    def close(self):
-        """Close all encapsulated file objects"""
-        for f in reversed(self.fobjects):
-            if "r" not in self.mode and not f.closed:
-                f.flush()
-            f.close()
-        self.fobjects.clear()
-
-
-class OpenFiles(list):
-    """List of OpenFile instances
-
-    Can be used in a single context, which opens and closes all of the
-    contained files. Normal list access to get the elements works as
-    normal.
-
-    A special case is made for caching filesystems - the files will
-    be down/uploaded together at the start or end of the context, and
-    this may happen concurrently, if the target filesystem supports it.
-    """
-
-    def __init__(self, *args, mode="rb", fs=None):
-        self.mode = mode
-        self.fs = fs
-        self.files = []
-        super().__init__(*args)
-
-    def __enter__(self):
-        if self.fs is None:
-            raise ValueError("Context has already been used")
-
-        fs = self.fs
-        while True:
-            if hasattr(fs, "open_many"):
-                # check for concurrent cache download; or set up for upload
-                self.files = fs.open_many(self)
-                return self.files
-            if hasattr(fs, "fs") and fs.fs is not None:
-                fs = fs.fs
-            else:
-                break
-        return [s.__enter__() for s in self]
-
-    def __exit__(self, *args):
-        fs = self.fs
-        [s.__exit__(*args) for s in self]
-        if "r" not in self.mode:
-            while True:
-                if hasattr(fs, "open_many"):
-                    # check for concurrent cache upload
-                    fs.commit_many(self.files)
-                    return
-                if hasattr(fs, "fs") and fs.fs is not None:
-                    fs = fs.fs
-                else:
-                    break
-
-    def __getitem__(self, item):
-        out = super().__getitem__(item)
-        if isinstance(item, slice):
-            return OpenFiles(out, mode=self.mode, fs=self.fs)
-        return out
-
-    def __repr__(self):
-        return "<List of %s OpenFile instances>" % len(self)
-
-
-def open_files(
-    urlpath,
-    mode="rb",
-    compression=None,
-    encoding="utf8",
-    errors=None,
-    name_function=None,
-    num=1,
-    protocol=None,
-    newline=None,
-    auto_mkdir=True,
-    expand=True,
-    **kwargs,
-):
-    """Given a path or paths, return a list of ``OpenFile`` objects.
-
-    For writing, a str path must contain the "*" character, which will be filled
-    in by increasing numbers, e.g., "part*" ->  "part1", "part2" if num=2.
-
-    For either reading or writing, can instead provide explicit list of paths.
-
-    Parameters
-    ----------
-    urlpath: string or list
-        Absolute or relative filepath(s). Prefix with a protocol like ``s3://``
-        to read from alternative filesystems. To read from multiple files you
-        can pass a globstring or a list of paths, with the caveat that they
-        must all have the same protocol.
-    mode: 'rb', 'wt', etc.
-    compression: string or None
-        If given, open file using compression codec. Can either be a compression
-        name (a key in ``fsspec.compression.compr``) or "infer" to guess the
-        compression from the filename suffix.
-    encoding: str
-        For text mode only
-    errors: None or str
-        Passed to TextIOWrapper in text mode
-    name_function: function or None
-        if opening a set of files for writing, those files do not yet exist,
-        so we need to generate their names by formatting the urlpath for
-        each sequence number
-    num: int [1]
-        if writing mode, number of files we expect to create (passed to
-        name+function)
-    protocol: str or None
-        If given, overrides the protocol found in the URL.
-    newline: bytes or None
-        Used for line terminator in text mode. If None, uses system default;
-        if blank, uses no translation.
-    auto_mkdir: bool (True)
-        If in write mode, this will ensure the target directory exists before
-        writing, by calling ``fs.mkdirs(exist_ok=True)``.
-    expand: bool
-    **kwargs: dict
-        Extra options that make sense to a particular storage connection, e.g.
-        host, port, username, password, etc.
-
-    Examples
-    --------
-    >>> files = open_files('2015-*-*.csv')  # doctest: +SKIP
-    >>> files = open_files(
-    ...     's3://bucket/2015-*-*.csv.gz', compression='gzip'
-    ... )  # doctest: +SKIP
-
-    Returns
-    -------
-    An ``OpenFiles`` instance, which is a list of ``OpenFile`` objects that can
-    be used as a single context
-
-    Notes
-    -----
-    For a full list of the available protocols and the implementations that
-    they map across to see the latest online documentation:
-
-    - For implementations built into ``fsspec`` see
-      https://filesystem-spec.readthedocs.io/en/latest/api.html#built-in-implementations
-    - For implementations in separate packages see
-      https://filesystem-spec.readthedocs.io/en/latest/api.html#other-known-implementations
-    """
-    fs, fs_token, paths = get_fs_token_paths(
-        urlpath,
-        mode,
-        num=num,
-        name_function=name_function,
-        storage_options=kwargs,
-        protocol=protocol,
-        expand=expand,
-    )
-    if "r" not in mode and auto_mkdir:
-        parents = {fs._parent(path) for path in paths}
-        [fs.makedirs(parent, exist_ok=True) for parent in parents]
-    return OpenFiles(
-        [
-            OpenFile(
-                fs,
-                path,
-                mode=mode,
-                compression=compression,
-                encoding=encoding,
-                errors=errors,
-                newline=newline,
-            )
-            for path in paths
-        ],
-        mode=mode,
-        fs=fs,
-    )
-
-
-def _un_chain(path, kwargs):
-    x = re.compile(".*[^a-z]+.*")  # test for non protocol-like single word
-    bits = (
-        [p if "://" in p or x.match(p) else p + "://" for p in path.split("::")]
-        if "::" in path
-        else [path]
-    )
-    # [[url, protocol, kwargs], ...]
-    out = []
-    previous_bit = None
-    kwargs = kwargs.copy()
-    for bit in reversed(bits):
-        protocol = kwargs.pop("protocol", None) or split_protocol(bit)[0] or "file"
-        cls = get_filesystem_class(protocol)
-        extra_kwargs = cls._get_kwargs_from_urls(bit)
-        kws = kwargs.pop(protocol, {})
-        if bit is bits[0]:
-            kws.update(kwargs)
-        kw = dict(**extra_kwargs, **kws)
-        bit = cls._strip_protocol(bit)
-        if (
-            protocol in {"blockcache", "filecache", "simplecache"}
-            and "target_protocol" not in kw
-        ):
-            bit = previous_bit
-        out.append((bit, protocol, kw))
-        previous_bit = bit
-    out = list(reversed(out))
-    return out
-
-
-def url_to_fs(url, **kwargs):
-    """
-    Turn fully-qualified and potentially chained URL into filesystem instance
-
-    Parameters
-    ----------
-    url : str
-        The fsspec-compatible URL
-    **kwargs: dict
-        Extra options that make sense to a particular storage connection, e.g.
-        host, port, username, password, etc.
-
-    Returns
-    -------
-    filesystem : FileSystem
-        The new filesystem discovered from ``url`` and created with
-        ``**kwargs``.
-    urlpath : str
-        The file-systems-specific URL for ``url``.
-    """
-    chain = _un_chain(url, kwargs)
-    inkwargs = {}
-    # Reverse iterate the chain, creating a nested target_* structure
-    for i, ch in enumerate(reversed(chain)):
-        urls, protocol, kw = ch
-        if i == len(chain) - 1:
-            inkwargs = dict(**kw, **inkwargs)
-            continue
-        inkwargs["target_options"] = dict(**kw, **inkwargs)
-        inkwargs["target_protocol"] = protocol
-        inkwargs["fo"] = urls
-    urlpath, protocol, _ = chain[0]
-    fs = filesystem(protocol, **inkwargs)
-    return fs, urlpath
-
-
-def open(
-    urlpath,
-    mode="rb",
-    compression=None,
-    encoding="utf8",
-    errors=None,
-    protocol=None,
-    newline=None,
-    **kwargs,
-):
-    """Given a path or paths, return one ``OpenFile`` object.
-
-    Parameters
-    ----------
-    urlpath: string or list
-        Absolute or relative filepath. Prefix with a protocol like ``s3://``
-        to read from alternative filesystems. Should not include glob
-        character(s).
-    mode: 'rb', 'wt', etc.
-    compression: string or None
-        If given, open file using compression codec. Can either be a compression
-        name (a key in ``fsspec.compression.compr``) or "infer" to guess the
-        compression from the filename suffix.
-    encoding: str
-        For text mode only
-    errors: None or str
-        Passed to TextIOWrapper in text mode
-    protocol: str or None
-        If given, overrides the protocol found in the URL.
-    newline: bytes or None
-        Used for line terminator in text mode. If None, uses system default;
-        if blank, uses no translation.
-    **kwargs: dict
-        Extra options that make sense to a particular storage connection, e.g.
-        host, port, username, password, etc.
-
-    Examples
-    --------
-    >>> openfile = open('2015-01-01.csv')  # doctest: +SKIP
-    >>> openfile = open(
-    ...     's3://bucket/2015-01-01.csv.gz', compression='gzip'
-    ... )  # doctest: +SKIP
-    >>> with openfile as f:
-    ...     df = pd.read_csv(f)  # doctest: +SKIP
-    ...
-
-    Returns
-    -------
-    ``OpenFile`` object.
-
-    Notes
-    -----
-    For a full list of the available protocols and the implementations that
-    they map across to see the latest online documentation:
-
-    - For implementations built into ``fsspec`` see
-      https://filesystem-spec.readthedocs.io/en/latest/api.html#built-in-implementations
-    - For implementations in separate packages see
-      https://filesystem-spec.readthedocs.io/en/latest/api.html#other-known-implementations
-    """
-    out = open_files(
-        urlpath=[urlpath],
-        mode=mode,
-        compression=compression,
-        encoding=encoding,
-        errors=errors,
-        protocol=protocol,
-        newline=newline,
-        expand=False,
-        **kwargs,
-    )
-    if not out:
-        raise FileNotFoundError(urlpath)
-    return out[0]
-
-
-def open_local(url, mode="rb", **storage_options):
-    """Open file(s) which can be resolved to local
-
-    For files which either are local, or get downloaded upon open
-    (e.g., by file caching)
-
-    Parameters
-    ----------
-    url: str or list(str)
-    mode: str
-        Must be read mode
-    storage_options:
-        passed on to FS for or used by open_files (e.g., compression)
-    """
-    if "r" not in mode:
-        raise ValueError("Can only ensure local files when reading")
-    of = open_files(url, mode=mode, **storage_options)
-    if not getattr(of[0].fs, "local_file", False):
-        raise ValueError(
-            "open_local can only be used on a filesystem which"
-            " has attribute local_file=True"
-        )
-    with of as files:
-        paths = [f.name for f in files]
-    if isinstance(url, str) and not has_magic(url):
-        return paths[0]
-    return paths
-
-
-def get_compression(urlpath, compression):
-    if compression == "infer":
-        compression = infer_compression(urlpath)
-    if compression is not None and compression not in compr:
-        raise ValueError("Compression type %s not supported" % compression)
-    return compression
-
-
-def split_protocol(urlpath):
-    """Return protocol, path pair"""
-    urlpath = stringify_path(urlpath)
-    if "://" in urlpath:
-        protocol, path = urlpath.split("://", 1)
-        if len(protocol) > 1:
-            # excludes Windows paths
-            return protocol, path
-    return None, urlpath
-
-
-def strip_protocol(urlpath):
-    """Return only path part of full URL, according to appropriate backend"""
-    protocol, _ = split_protocol(urlpath)
-    cls = get_filesystem_class(protocol)
-    return cls._strip_protocol(urlpath)
-
-
-def expand_paths_if_needed(paths, mode, num, fs, name_function):
-    """Expand paths if they have a ``*`` in them (write mode) or any of ``*?[]``
-    in them (read mode).
-
-    :param paths: list of paths
-    mode: str
-        Mode in which to open files.
-    num: int
-        If opening in writing mode, number of files we expect to create.
-    fs: filesystem object
-    name_function: callable
-        If opening in writing mode, this callable is used to generate path
-        names. Names are generated for each partition by
-        ``urlpath.replace('*', name_function(partition_index))``.
-    :return: list of paths
-    """
-    expanded_paths = []
-    paths = list(paths)
-
-    if "w" in mode:  # read mode
-        if sum([1 for p in paths if "*" in p]) > 1:
-            raise ValueError(
-                "When writing data, only one filename mask can be specified."
-            )
-        num = max(num, len(paths))
-
-        for curr_path in paths:
-            if "*" in curr_path:
-                # expand using name_function
-                expanded_paths.extend(_expand_paths(curr_path, name_function, num))
-            else:
-                expanded_paths.append(curr_path)
-        # if we generated more paths that asked for, trim the list
-        if len(expanded_paths) > num:
-            expanded_paths = expanded_paths[:num]
-
-    else:  # read mode
-        for curr_path in paths:
-            if has_magic(curr_path):
-                # expand using glob
-                expanded_paths.extend(fs.glob(curr_path))
-            else:
-                expanded_paths.append(curr_path)
-
-    return expanded_paths
-
-
-def get_fs_token_paths(
-    urlpath,
-    mode="rb",
-    num=1,
-    name_function=None,
-    storage_options=None,
-    protocol=None,
-    expand=True,
-):
-    """Filesystem, deterministic token, and paths from a urlpath and options.
-
-    Parameters
-    ----------
-    urlpath: string or iterable
-        Absolute or relative filepath, URL (may include protocols like
-        ``s3://``), or globstring pointing to data.
-    mode: str, optional
-        Mode in which to open files.
-    num: int, optional
-        If opening in writing mode, number of files we expect to create.
-    name_function: callable, optional
-        If opening in writing mode, this callable is used to generate path
-        names. Names are generated for each partition by
-        ``urlpath.replace('*', name_function(partition_index))``.
-    storage_options: dict, optional
-        Additional keywords to pass to the filesystem class.
-    protocol: str or None
-        To override the protocol specifier in the URL
-    expand: bool
-        Expand string paths for writing, assuming the path is a directory
-    """
-    if isinstance(urlpath, (list, tuple, set)):
-        if not urlpath:
-            raise ValueError("empty urlpath sequence")
-        urlpath0 = stringify_path(list(urlpath)[0])
-    else:
-        urlpath0 = stringify_path(urlpath)
-    storage_options = storage_options or {}
-    if protocol:
-        storage_options["protocol"] = protocol
-    chain = _un_chain(urlpath0, storage_options or {})
-    inkwargs = {}
-    # Reverse iterate the chain, creating a nested target_* structure
-    for i, ch in enumerate(reversed(chain)):
-        urls, nested_protocol, kw = ch
-        if i == len(chain) - 1:
-            inkwargs = dict(**kw, **inkwargs)
-            continue
-        inkwargs["target_options"] = dict(**kw, **inkwargs)
-        inkwargs["target_protocol"] = nested_protocol
-        inkwargs["fo"] = urls
-    paths, protocol, _ = chain[0]
-    fs = filesystem(protocol, **inkwargs)
-    if isinstance(urlpath, (list, tuple, set)):
-        pchains = [
-            _un_chain(stringify_path(u), storage_options or {})[0] for u in urlpath
-        ]
-        if len(set(pc[1] for pc in pchains)) > 1:
-            raise ValueError("Protocol mismatch getting fs from %s", urlpath)
-        paths = [pc[0] for pc in pchains]
-    else:
-        paths = fs._strip_protocol(paths)
-    if isinstance(paths, (list, tuple, set)):
-        paths = expand_paths_if_needed(paths, mode, num, fs, name_function)
-    else:
-        if "w" in mode and expand:
-            paths = _expand_paths(paths, name_function, num)
-        elif "*" in paths:
-            paths = [f for f in sorted(fs.glob(paths)) if not fs.isdir(f)]
-        else:
-            paths = [paths]
-
-    return fs, fs._fs_token, paths
-
-
-def _expand_paths(path, name_function, num):
-    if isinstance(path, str):
-        if path.count("*") > 1:
-            raise ValueError("Output path spec must contain exactly one '*'.")
-        elif "*" not in path:
-            path = os.path.join(path, "*.part")
-
-        if name_function is None:
-            name_function = build_name_function(num - 1)
-
-        paths = [path.replace("*", name_function(i)) for i in range(num)]
-        if paths != sorted(paths):
-            logger.warning(
-                "In order to preserve order between partitions"
-                " paths created with ``name_function`` should "
-                "sort to partition order"
-            )
-    elif isinstance(path, (tuple, list)):
-        assert len(path) == num
-        paths = list(path)
-    else:
-        raise ValueError(
-            "Path should be either\n"
-            "1. A list of paths: ['foo.json', 'bar.json', ...]\n"
-            "2. A directory: 'foo/\n"
-            "3. A path with a '*' in it: 'foo.*.json'"
-        )
-    return paths
-
-
-class PickleableTextIOWrapper(io.TextIOWrapper):
-    """TextIOWrapper cannot be pickled. This solves it.
-
-    Requires that ``buffer`` be pickleable, which all instances of
-    AbstractBufferedFile are.
-    """
-
-    def __init__(
-        self,
-        buffer,
-        encoding=None,
-        errors=None,
-        newline=None,
-        line_buffering=False,
-        write_through=False,
-    ):
-        self.args = buffer, encoding, errors, newline, line_buffering, write_through
-        super().__init__(*self.args)
-
-    def __reduce__(self):
-        return PickleableTextIOWrapper, self.args
diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/httpcore/_trace.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/httpcore/_trace.py
deleted file mode 100644
index b122a53e88f17e1e450f63b05ede3e28e8a7992a..0000000000000000000000000000000000000000
--- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/httpcore/_trace.py
+++ /dev/null
@@ -1,105 +0,0 @@
-import inspect
-import logging
-from types import TracebackType
-from typing import Any, Dict, Optional, Type
-
-from ._models import Request
-
-
-class Trace:
-    def __init__(
-        self,
-        name: str,
-        logger: logging.Logger,
-        request: Optional[Request] = None,
-        kwargs: Optional[Dict[str, Any]] = None,
-    ) -> None:
-        self.name = name
-        self.logger = logger
-        self.trace_extension = (
-            None if request is None else request.extensions.get("trace")
-        )
-        self.debug = self.logger.isEnabledFor(logging.DEBUG)
-        self.kwargs = kwargs or {}
-        self.return_value: Any = None
-        self.should_trace = self.debug or self.trace_extension is not None
-        self.prefix = self.logger.name.split(".")[-1]
-
-    def trace(self, name: str, info: Dict[str, Any]) -> None:
-        if self.trace_extension is not None:
-            prefix_and_name = f"{self.prefix}.{name}"
-            ret = self.trace_extension(prefix_and_name, info)
-            if inspect.iscoroutine(ret):  # pragma: no cover
-                raise TypeError(
-                    "If you are using a synchronous interface, "
-                    "the callback of the `trace` extension should "
-                    "be a normal function instead of an asynchronous function."
-                )
-
-        if self.debug:
-            if not info or "return_value" in info and info["return_value"] is None:
-                message = name
-            else:
-                args = " ".join([f"{key}={value!r}" for key, value in info.items()])
-                message = f"{name} {args}"
-            self.logger.debug(message)
-
-    def __enter__(self) -> "Trace":
-        if self.should_trace:
-            info = self.kwargs
-            self.trace(f"{self.name}.started", info)
-        return self
-
-    def __exit__(
-        self,
-        exc_type: Optional[Type[BaseException]] = None,
-        exc_value: Optional[BaseException] = None,
-        traceback: Optional[TracebackType] = None,
-    ) -> None:
-        if self.should_trace:
-            if exc_value is None:
-                info = {"return_value": self.return_value}
-                self.trace(f"{self.name}.complete", info)
-            else:
-                info = {"exception": exc_value}
-                self.trace(f"{self.name}.failed", info)
-
-    async def atrace(self, name: str, info: Dict[str, Any]) -> None:
-        if self.trace_extension is not None:
-            prefix_and_name = f"{self.prefix}.{name}"
-            coro = self.trace_extension(prefix_and_name, info)
-            if not inspect.iscoroutine(coro):  # pragma: no cover
-                raise TypeError(
-                    "If you're using an asynchronous interface, "
-                    "the callback of the `trace` extension should "
-                    "be an asynchronous function rather than a normal function."
-                )
-            await coro
-
-        if self.debug:
-            if not info or "return_value" in info and info["return_value"] is None:
-                message = name
-            else:
-                args = " ".join([f"{key}={value!r}" for key, value in info.items()])
-                message = f"{name} {args}"
-            self.logger.debug(message)
-
-    async def __aenter__(self) -> "Trace":
-        if self.should_trace:
-            info = self.kwargs
-            await self.atrace(f"{self.name}.started", info)
-        return self
-
-    async def __aexit__(
-        self,
-        exc_type: Optional[Type[BaseException]] = None,
-        exc_value: Optional[BaseException] = None,
-        traceback: Optional[TracebackType] = None,
-    ) -> None:
-        if self.should_trace:
-            if exc_value is None:
-                info = {"return_value": self.return_value}
-                await self.atrace(f"{self.name}.complete", info)
-            else:
-                info = {"exception": exc_value}
-                await self.atrace(f"{self.name}.failed", info)
diff --git a/spaces/declare-lab/tango/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py b/spaces/declare-lab/tango/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py
deleted file mode 100644
index c0086b32d6fdd6512241f0ceb23658ca020bc385..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py
+++ /dev/null
@@ -1,657 +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 inspect
-from typing import Callable, List, Optional, Union
-
-import numpy as np
-import PIL
-import torch
-from transformers import CLIPTextModel, CLIPTokenizer
-
-from ...loaders import TextualInversionLoaderMixin
-from ...models import AutoencoderKL, UNet2DConditionModel
-from ...schedulers import DDPMScheduler, KarrasDiffusionSchedulers
-from ...utils import deprecate, is_accelerate_available, logging, randn_tensor
-from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-
-
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
-
-
-def preprocess(image):
-    if isinstance(image, torch.Tensor):
-        return image
-    elif isinstance(image, PIL.Image.Image):
-        image = [image]
-
-    if isinstance(image[0], PIL.Image.Image):
-        w, h = image[0].size
-        w, h = (x - x % 64 for x in (w, h))  # resize to integer multiple of 64
-
-        image = [np.array(i.resize((w, h)))[None, :] for i in image]
-        image = np.concatenate(image, axis=0)
-        image = np.array(image).astype(np.float32) / 255.0
-        image = image.transpose(0, 3, 1, 2)
-        image = 2.0 * image - 1.0
-        image = torch.from_numpy(image)
-    elif isinstance(image[0], torch.Tensor):
-        image = torch.cat(image, dim=0)
-    return image
-
-
-class StableDiffusionUpscalePipeline(DiffusionPipeline, TextualInversionLoaderMixin):
-    r"""
-    Pipeline for text-guided image super-resolution using Stable Diffusion 2.
-
-    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.
-        low_res_scheduler ([`SchedulerMixin`]):
-            A scheduler used to add initial noise to the low res conditioning image. It must be an instance of
-            [`DDPMScheduler`].
-        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`].
-    """
-
-    def __init__(
-        self,
-        vae: AutoencoderKL,
-        text_encoder: CLIPTextModel,
-        tokenizer: CLIPTokenizer,
-        unet: UNet2DConditionModel,
-        low_res_scheduler: DDPMScheduler,
-        scheduler: KarrasDiffusionSchedulers,
-        max_noise_level: int = 350,
-    ):
-        super().__init__()
-
-        if hasattr(vae, "config"):
-            # check if vae has a config attribute `scaling_factor` and if it is set to 0.08333, else set it to 0.08333 and deprecate
-            is_vae_scaling_factor_set_to_0_08333 = (
-                hasattr(vae.config, "scaling_factor") and vae.config.scaling_factor == 0.08333
-            )
-            if not is_vae_scaling_factor_set_to_0_08333:
-                deprecation_message = (
-                    "The configuration file of the vae does not contain `scaling_factor` or it is set to"
-                    f" {vae.config.scaling_factor}, which seems highly unlikely. If your checkpoint is a fine-tuned"
-                    " version of `stabilityai/stable-diffusion-x4-upscaler` you should change 'scaling_factor' to"
-                    " 0.08333 Please make sure to update the config accordingly, as not doing so 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 `vae/config.json` file"
-                )
-                deprecate("wrong scaling_factor", "1.0.0", deprecation_message, standard_warn=False)
-                vae.register_to_config(scaling_factor=0.08333)
-
-        self.register_modules(
-            vae=vae,
-            text_encoder=text_encoder,
-            tokenizer=tokenizer,
-            unet=unet,
-            low_res_scheduler=low_res_scheduler,
-            scheduler=scheduler,
-        )
-        self.register_to_config(max_noise_level=max_noise_level)
-
-    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]:
-            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 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
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline._encode_prompt
-    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. 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:
-            # textual inversion: procecss multi-vector tokens if necessary
-            if isinstance(self, TextualInversionLoaderMixin):
-                prompt = self.maybe_convert_prompt(prompt, self.tokenizer)
-
-            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
-
-            # textual inversion: procecss multi-vector tokens if necessary
-            if isinstance(self, TextualInversionLoaderMixin):
-                uncond_tokens = self.maybe_convert_prompt(uncond_tokens, self.tokenizer)
-
-            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
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs
-    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
-
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.decode_latents
-    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 check_inputs(
-        self,
-        prompt,
-        image,
-        noise_level,
-        callback_steps,
-        negative_prompt=None,
-        prompt_embeds=None,
-        negative_prompt_embeds=None,
-    ):
-        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}."
-                )
-
-        if (
-            not isinstance(image, torch.Tensor)
-            and not isinstance(image, PIL.Image.Image)
-            and not isinstance(image, list)
-        ):
-            raise ValueError(
-                f"`image` has to be of type `torch.Tensor`, `PIL.Image.Image` or `list` but is {type(image)}"
-            )
-
-        # verify batch size of prompt and image are same if image is a list or tensor
-        if isinstance(image, list) or isinstance(image, torch.Tensor):
-            if isinstance(prompt, str):
-                batch_size = 1
-            else:
-                batch_size = len(prompt)
-            if isinstance(image, list):
-                image_batch_size = len(image)
-            else:
-                image_batch_size = image.shape[0]
-            if batch_size != image_batch_size:
-                raise ValueError(
-                    f"`prompt` has batch size {batch_size} and `image` has batch size {image_batch_size}."
-                    " Please make sure that passed `prompt` matches the batch size of `image`."
-                )
-
-        # check noise level
-        if noise_level > self.config.max_noise_level:
-            raise ValueError(f"`noise_level` has to be <= {self.config.max_noise_level} but is {noise_level}")
-
-        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, width)
-        if latents is None:
-            latents = randn_tensor(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
-        latents = latents * self.scheduler.init_noise_sigma
-        return latents
-
-    @torch.no_grad()
-    def __call__(
-        self,
-        prompt: Union[str, List[str]] = None,
-        image: Union[torch.FloatTensor, PIL.Image.Image, List[PIL.Image.Image]] = None,
-        num_inference_steps: int = 75,
-        guidance_scale: float = 9.0,
-        noise_level: int = 20,
-        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,
-    ):
-        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 (`PIL.Image.Image` or List[`PIL.Image.Image`] or `torch.FloatTensor`):
-                `Image`, or tensor representing an image batch which will be upscaled. *
-            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. 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*):
-                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.
-
-        Examples:
-        ```py
-        >>> import requests
-        >>> from PIL import Image
-        >>> from io import BytesIO
-        >>> from diffusers import StableDiffusionUpscalePipeline
-        >>> import torch
-
-        >>> # load model and scheduler
-        >>> model_id = "stabilityai/stable-diffusion-x4-upscaler"
-        >>> pipeline = StableDiffusionUpscalePipeline.from_pretrained(
-        ...     model_id, revision="fp16", torch_dtype=torch.float16
-        ... )
-        >>> pipeline = pipeline.to("cuda")
-
-        >>> # let's download an  image
-        >>> url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-upscale/low_res_cat.png"
-        >>> response = requests.get(url)
-        >>> low_res_img = Image.open(BytesIO(response.content)).convert("RGB")
-        >>> low_res_img = low_res_img.resize((128, 128))
-        >>> prompt = "a white cat"
-
-        >>> upscaled_image = pipeline(prompt=prompt, image=low_res_img).images[0]
-        >>> upscaled_image.save("upsampled_cat.png")
-        ```
-
-        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
-        self.check_inputs(
-            prompt,
-            image,
-            noise_level,
-            callback_steps,
-            negative_prompt,
-            prompt_embeds,
-            negative_prompt_embeds,
-        )
-
-        if image is None:
-            raise ValueError("`image` input cannot be undefined.")
-
-        # 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. Preprocess image
-        image = preprocess(image)
-        image = image.to(dtype=prompt_embeds.dtype, device=device)
-
-        # 5. set timesteps
-        self.scheduler.set_timesteps(num_inference_steps, device=device)
-        timesteps = self.scheduler.timesteps
-
-        # 5. Add noise to image
-        noise_level = torch.tensor([noise_level], dtype=torch.long, device=device)
-        noise = randn_tensor(image.shape, generator=generator, device=device, dtype=prompt_embeds.dtype)
-        image = self.low_res_scheduler.add_noise(image, noise, noise_level)
-
-        batch_multiplier = 2 if do_classifier_free_guidance else 1
-        image = torch.cat([image] * batch_multiplier * num_images_per_prompt)
-        noise_level = torch.cat([noise_level] * image.shape[0])
-
-        # 6. Prepare latent variables
-        height, width = image.shape[2:]
-        num_channels_latents = self.vae.config.latent_channels
-        latents = self.prepare_latents(
-            batch_size * num_images_per_prompt,
-            num_channels_latents,
-            height,
-            width,
-            prompt_embeds.dtype,
-            device,
-            generator,
-            latents,
-        )
-
-        # 7. Check that sizes of image and latents match
-        num_channels_image = image.shape[1]
-        if num_channels_latents + num_channels_image != self.unet.config.in_channels:
-            raise ValueError(
-                f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
-                f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
-                f" `num_channels_image`: {num_channels_image} "
-                f" = {num_channels_latents+num_channels_image}. Please verify the config of"
-                " `pipeline.unet` or your `image` input."
-            )
-
-        # 8. 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)
-
-        # 9. 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
-                latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents
-
-                # concat latents, mask, masked_image_latents in the channel dimension
-                latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
-                latent_model_input = torch.cat([latent_model_input, image], dim=1)
-
-                # predict the noise residual
-                noise_pred = self.unet(
-                    latent_model_input, t, encoder_hidden_states=prompt_embeds, class_labels=noise_level
-                ).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)
-
-        # 10. Post-processing
-        # make sure the VAE is in float32 mode, as it overflows in float16
-        self.vae.to(dtype=torch.float32)
-        image = self.decode_latents(latents.float())
-
-        # 11. Convert to PIL
-        if output_type == "pil":
-            image = self.numpy_to_pil(image)
-
-        if not return_dict:
-            return (image,)
-
-        return ImagePipelineOutput(images=image)
diff --git a/spaces/declare-lab/tango/diffusers/tests/pipelines/latent_diffusion/test_latent_diffusion.py b/spaces/declare-lab/tango/diffusers/tests/pipelines/latent_diffusion/test_latent_diffusion.py
deleted file mode 100644
index 3f2dbe5cec2a324d80fe7bcca1efffe9bcd3ab02..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/diffusers/tests/pipelines/latent_diffusion/test_latent_diffusion.py
+++ /dev/null
@@ -1,202 +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 gc
-import unittest
-
-import numpy as np
-import torch
-from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
-
-from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNet2DConditionModel
-from diffusers.utils.testing_utils import load_numpy, nightly, require_torch_gpu, slow, torch_device
-
-from ...pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
-from ...test_pipelines_common import PipelineTesterMixin
-
-
-torch.backends.cuda.matmul.allow_tf32 = False
-
-
-class LDMTextToImagePipelineFastTests(PipelineTesterMixin, unittest.TestCase):
-    pipeline_class = LDMTextToImagePipeline
-    params = TEXT_TO_IMAGE_PARAMS - {
-        "negative_prompt",
-        "negative_prompt_embeds",
-        "cross_attention_kwargs",
-        "prompt_embeds",
-    }
-    required_optional_params = PipelineTesterMixin.required_optional_params - {
-        "num_images_per_prompt",
-        "callback",
-        "callback_steps",
-    }
-    batch_params = TEXT_TO_IMAGE_BATCH_PARAMS
-    test_cpu_offload = False
-
-    def get_dummy_components(self):
-        torch.manual_seed(0)
-        unet = UNet2DConditionModel(
-            block_out_channels=(32, 64),
-            layers_per_block=2,
-            sample_size=32,
-            in_channels=4,
-            out_channels=4,
-            down_block_types=("DownBlock2D", "CrossAttnDownBlock2D"),
-            up_block_types=("CrossAttnUpBlock2D", "UpBlock2D"),
-            cross_attention_dim=32,
-        )
-        scheduler = DDIMScheduler(
-            beta_start=0.00085,
-            beta_end=0.012,
-            beta_schedule="scaled_linear",
-            clip_sample=False,
-            set_alpha_to_one=False,
-        )
-        torch.manual_seed(0)
-        vae = AutoencoderKL(
-            block_out_channels=(32, 64),
-            in_channels=3,
-            out_channels=3,
-            down_block_types=("DownEncoderBlock2D", "DownEncoderBlock2D"),
-            up_block_types=("UpDecoderBlock2D", "UpDecoderBlock2D"),
-            latent_channels=4,
-        )
-        torch.manual_seed(0)
-        text_encoder_config = CLIPTextConfig(
-            bos_token_id=0,
-            eos_token_id=2,
-            hidden_size=32,
-            intermediate_size=37,
-            layer_norm_eps=1e-05,
-            num_attention_heads=4,
-            num_hidden_layers=5,
-            pad_token_id=1,
-            vocab_size=1000,
-        )
-        text_encoder = CLIPTextModel(text_encoder_config)
-        tokenizer = CLIPTokenizer.from_pretrained("hf-internal-testing/tiny-random-clip")
-
-        components = {
-            "unet": unet,
-            "scheduler": scheduler,
-            "vqvae": vae,
-            "bert": text_encoder,
-            "tokenizer": tokenizer,
-        }
-        return components
-
-    def get_dummy_inputs(self, device, seed=0):
-        if str(device).startswith("mps"):
-            generator = torch.manual_seed(seed)
-        else:
-            generator = torch.Generator(device=device).manual_seed(seed)
-        inputs = {
-            "prompt": "A painting of a squirrel eating a burger",
-            "generator": generator,
-            "num_inference_steps": 2,
-            "guidance_scale": 6.0,
-            "output_type": "numpy",
-        }
-        return inputs
-
-    def test_inference_text2img(self):
-        device = "cpu"  # ensure determinism for the device-dependent torch.Generator
-
-        components = self.get_dummy_components()
-        pipe = LDMTextToImagePipeline(**components)
-        pipe.to(device)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs(device)
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 16, 16, 3)
-        expected_slice = np.array([0.59450, 0.64078, 0.55509, 0.51229, 0.69640, 0.36960, 0.59296, 0.60801, 0.49332])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-
-
-@slow
-@require_torch_gpu
-class LDMTextToImagePipelineSlowTests(unittest.TestCase):
-    def tearDown(self):
-        super().tearDown()
-        gc.collect()
-        torch.cuda.empty_cache()
-
-    def get_inputs(self, device, dtype=torch.float32, seed=0):
-        generator = torch.manual_seed(seed)
-        latents = np.random.RandomState(seed).standard_normal((1, 4, 32, 32))
-        latents = torch.from_numpy(latents).to(device=device, dtype=dtype)
-        inputs = {
-            "prompt": "A painting of a squirrel eating a burger",
-            "latents": latents,
-            "generator": generator,
-            "num_inference_steps": 3,
-            "guidance_scale": 6.0,
-            "output_type": "numpy",
-        }
-        return inputs
-
-    def test_ldm_default_ddim(self):
-        pipe = LDMTextToImagePipeline.from_pretrained("CompVis/ldm-text2im-large-256").to(torch_device)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_inputs(torch_device)
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1].flatten()
-
-        assert image.shape == (1, 256, 256, 3)
-        expected_slice = np.array([0.51825, 0.52850, 0.52543, 0.54258, 0.52304, 0.52569, 0.54363, 0.55276, 0.56878])
-        max_diff = np.abs(expected_slice - image_slice).max()
-        assert max_diff < 1e-3
-
-
-@nightly
-@require_torch_gpu
-class LDMTextToImagePipelineNightlyTests(unittest.TestCase):
-    def tearDown(self):
-        super().tearDown()
-        gc.collect()
-        torch.cuda.empty_cache()
-
-    def get_inputs(self, device, dtype=torch.float32, seed=0):
-        generator = torch.manual_seed(seed)
-        latents = np.random.RandomState(seed).standard_normal((1, 4, 32, 32))
-        latents = torch.from_numpy(latents).to(device=device, dtype=dtype)
-        inputs = {
-            "prompt": "A painting of a squirrel eating a burger",
-            "latents": latents,
-            "generator": generator,
-            "num_inference_steps": 50,
-            "guidance_scale": 6.0,
-            "output_type": "numpy",
-        }
-        return inputs
-
-    def test_ldm_default_ddim(self):
-        pipe = LDMTextToImagePipeline.from_pretrained("CompVis/ldm-text2im-large-256").to(torch_device)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_inputs(torch_device)
-        image = pipe(**inputs).images[0]
-
-        expected_image = load_numpy(
-            "https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/ldm_text2img/ldm_large_256_ddim.npy"
-        )
-        max_diff = np.abs(expected_image - image).max()
-        assert max_diff < 1e-3
diff --git a/spaces/deepskyreal/ai-mixer-hotchpotch/bark_speaker/txt2audio.py b/spaces/deepskyreal/ai-mixer-hotchpotch/bark_speaker/txt2audio.py
deleted file mode 100644
index e2103fd65620463d147e950ae56a3f7a63aa80f0..0000000000000000000000000000000000000000
--- a/spaces/deepskyreal/ai-mixer-hotchpotch/bark_speaker/txt2audio.py
+++ /dev/null
@@ -1,32 +0,0 @@
-import numpy as np
-from bark import SAMPLE_RATE, generate_audio, preload_models
-from bark.generation import SUPPORTED_LANGS
-
-DEBUG_MODE = False
-
-if not DEBUG_MODE:
-    _ = preload_models(text_use_gpu=False, text_use_small=True)
-
-AVAILABLE_PROMPTS = ["Unconditional", "Announcer"]
-PROMPT_LOOKUP = {}
-for _, lang in SUPPORTED_LANGS:
-    for n in range(10):
-        label = f"Speaker {n} ({lang})"
-        AVAILABLE_PROMPTS.append(label)
-        PROMPT_LOOKUP[label] = f"{lang}_speaker_{n}"
-PROMPT_LOOKUP["Unconditional"] = None
-PROMPT_LOOKUP["Announcer"] = "announcer"
-
-
-def gen_tts(text, history_prompt):  # , temp_semantic, temp_waveform):
-    if not text:
-        # text is None or empty
-        raise ValueError("text cannot be None or empty")
-    history_prompt = PROMPT_LOOKUP[history_prompt]
-    if DEBUG_MODE:
-        audio_arr = np.zeros(SAMPLE_RATE)
-    else:
-        # , text_temp=temp_semantic, waveform_temp=temp_waveform)
-        audio_arr = generate_audio(text, history_prompt=history_prompt)
-    audio_arr = (audio_arr * 32767).astype(np.int16)
-    return SAMPLE_RATE, audio_arr
diff --git a/spaces/deepwisdom/MetaGPT/metagpt/utils/pycst.py b/spaces/deepwisdom/MetaGPT/metagpt/utils/pycst.py
deleted file mode 100644
index afd85a5479335f17c8e01b2df4b56a1be03f4c88..0000000000000000000000000000000000000000
--- a/spaces/deepwisdom/MetaGPT/metagpt/utils/pycst.py
+++ /dev/null
@@ -1,166 +0,0 @@
-from __future__ import annotations
-
-from typing import Union
-
-import libcst as cst
-from libcst._nodes.module import Module
-
-DocstringNode = Union[cst.Module, cst.ClassDef, cst.FunctionDef]
-
-
-def get_docstring_statement(body: DocstringNode) -> cst.SimpleStatementLine:
-    """Extracts the docstring from the body of a node.
-
-    Args:
-        body: The body of a node.
-
-    Returns:
-        The docstring statement if it exists, None otherwise.
-    """
-    if isinstance(body, cst.Module):
-        body = body.body
-    else:
-        body = body.body.body
-
-    if not body:
-        return
-
-    statement = body[0]
-    if not isinstance(statement, cst.SimpleStatementLine):
-        return
-
-    expr = statement
-    while isinstance(expr, (cst.BaseSuite, cst.SimpleStatementLine)):
-        if len(expr.body) == 0:
-            return None
-        expr = expr.body[0]
-
-    if not isinstance(expr, cst.Expr):
-        return None
-    
-    val = expr.value
-    if not isinstance(val, (cst.SimpleString, cst.ConcatenatedString)):
-        return None
-    
-    evaluated_value = val.evaluated_value    
-    if isinstance(evaluated_value, bytes):
-        return None
-
-    return statement
-
-
-class DocstringCollector(cst.CSTVisitor):
-    """A visitor class for collecting docstrings from a CST.
-
-    Attributes:
-        stack: A list to keep track of the current path in the CST.
-        docstrings: A dictionary mapping paths in the CST to their corresponding docstrings.
-    """
-    def __init__(self):
-        self.stack: list[str] = []
-        self.docstrings: dict[tuple[str, ...], cst.SimpleStatementLine] = {}
-
-    def visit_Module(self, node: cst.Module) -> bool | None:
-        self.stack.append("")
-
-    def leave_Module(self, node: cst.Module) -> None:
-        return self._leave(node)
-
-    def visit_ClassDef(self, node: cst.ClassDef) -> bool | None:
-        self.stack.append(node.name.value)
-
-    def leave_ClassDef(self, node: cst.ClassDef) -> None:
-        return self._leave(node)
-
-    def visit_FunctionDef(self, node: cst.FunctionDef) -> bool | None:
-        self.stack.append(node.name.value)
-
-    def leave_FunctionDef(self, node: cst.FunctionDef) -> None:
-        return self._leave(node)
-
-    def _leave(self, node: DocstringNode) -> None:
-        key = tuple(self.stack)
-        self.stack.pop()
-        if hasattr(node, "decorators") and any(i.decorator.value == "overload" for i in node.decorators):
-            return
-
-        statement = get_docstring_statement(node)
-        if statement:
-            self.docstrings[key] = statement
-
-
-class DocstringTransformer(cst.CSTTransformer):
-    """A transformer class for replacing docstrings in a CST.
-
-    Attributes:
-        stack: A list to keep track of the current path in the CST.
-        docstrings: A dictionary mapping paths in the CST to their corresponding docstrings.
-    """
-    def __init__(
-        self,
-        docstrings: dict[tuple[str, ...], cst.SimpleStatementLine],
-    ):
-        self.stack: list[str] = []
-        self.docstrings = docstrings
-
-    def visit_Module(self, node: cst.Module) -> bool | None:
-        self.stack.append("")
-
-    def leave_Module(self, original_node: Module, updated_node: Module) -> Module:
-        return self._leave(original_node, updated_node)
-
-    def visit_ClassDef(self, node: cst.ClassDef) -> bool | None:
-        self.stack.append(node.name.value)
-
-    def leave_ClassDef(self, original_node: cst.ClassDef, updated_node: cst.ClassDef) -> cst.CSTNode:
-        return self._leave(original_node, updated_node)
-
-    def visit_FunctionDef(self, node: cst.FunctionDef) -> bool | None:
-        self.stack.append(node.name.value)
-
-    def leave_FunctionDef(self, original_node: cst.FunctionDef, updated_node: cst.FunctionDef) -> cst.CSTNode:
-        return self._leave(original_node, updated_node)
-
-    def _leave(self, original_node: DocstringNode, updated_node: DocstringNode) -> DocstringNode:
-        key = tuple(self.stack)
-        self.stack.pop()
-
-        if hasattr(updated_node, "decorators") and any((i.decorator.value == "overload") for i in updated_node.decorators):
-            return updated_node
-
-        statement = self.docstrings.get(key)
-        if not statement:
-            return updated_node
-
-        original_statement = get_docstring_statement(original_node)
-
-        if isinstance(updated_node, cst.Module):
-            body = updated_node.body
-            if original_statement:
-                return updated_node.with_changes(body=(statement, *body[1:]))
-            else:
-                updated_node = updated_node.with_changes(body=(statement, cst.EmptyLine(), *body))
-                return updated_node
-
-        body = updated_node.body.body[1:] if original_statement else updated_node.body.body
-        return updated_node.with_changes(body=updated_node.body.with_changes(body=(statement, *body)))
-
-
-def merge_docstring(code: str, documented_code: str) -> str:
-    """Merges the docstrings from the documented code into the original code.
-
-    Args:
-        code: The original code.
-        documented_code: The documented code.
-
-    Returns:
-        The original code with the docstrings from the documented code.
-    """
-    code_tree = cst.parse_module(code)
-    documented_code_tree = cst.parse_module(documented_code)
-
-    visitor = DocstringCollector()
-    documented_code_tree.visit(visitor)
-    transformer = DocstringTransformer(visitor.docstrings)
-    modified_tree = code_tree.visit(transformer)
-    return modified_tree.code
diff --git a/spaces/descript/vampnet/scripts/utils/data/augment.py b/spaces/descript/vampnet/scripts/utils/data/augment.py
deleted file mode 100644
index 679a4e4979658df843ee61a8698cc6d521fe24a8..0000000000000000000000000000000000000000
--- a/spaces/descript/vampnet/scripts/utils/data/augment.py
+++ /dev/null
@@ -1,67 +0,0 @@
-from pathlib import Path
-
-import audiotools as at
-from audiotools import AudioSignal
-
-import argbind
-import tqdm
-import torch
-
-
-from torch_pitch_shift import pitch_shift, get_fast_shifts
-from torch_time_stretch import time_stretch, get_fast_stretches
-
-from audiotools.core.util import sample_from_dist
-
-
-@argbind.bind(without_prefix=True)
-def augment(
-    audio_folder: Path = None,
-    dest_folder: Path = None,
-    n_augmentations: int = 10,
-):
-    """ 
-        Augment a folder of audio files by applying audiotools and pedalboard transforms. 
-
-        The dest foler will contain a folder for each of the clean dataset's files. 
-        Under each of these folders, there will be a clean file and many augmented files.
-    """
-    assert audio_folder is not None
-    assert dest_folder is not None
-    audio_files = at.util.find_audio(audio_folder)
-
-    for audio_file in tqdm.tqdm(audio_files):
-        subtree = dest_folder / audio_file.relative_to(audio_folder).parent
-        subdir = subtree / audio_file.stem
-        subdir.mkdir(parents=True, exist_ok=True)
-
-        src = AudioSignal(audio_file).to("cuda" if torch.cuda.is_available() else "cpu")
-
-        
-        for i, chunk in tqdm.tqdm(enumerate(src.windows(10, 10))):
-            # apply pedalboard transforms
-            for j in range(n_augmentations):
-                # pitch shift between -7 and 7 semitones
-                import random
-                dst = chunk.clone()
-                dst.samples = pitch_shift(
-                    dst.samples, 
-                    shift=random.choice(get_fast_shifts(src.sample_rate, 
-                            condition=lambda x: x >= 0.25 and x <= 1.0)), 
-                    sample_rate=src.sample_rate
-                )
-                dst.samples = time_stretch(
-                    dst.samples,
-                    stretch=random.choice(get_fast_stretches(src.sample_rate, 
-                                          condition=lambda x: x >= 0.667 and x <= 1.5, )),
-                    sample_rate=src.sample_rate, 
-                )
-
-                dst.cpu().write(subdir / f"{i}-{j}.wav")
-
-
-if __name__ == "__main__":
-    args = argbind.parse_args()
-
-    with argbind.scope(args):
-        augment()
\ No newline at end of file
diff --git a/spaces/diacanFperku/AutoGPT/FULL Nero Burning ROM 2018 V19.0.00800 Patch [PORTABLE].md b/spaces/diacanFperku/AutoGPT/FULL Nero Burning ROM 2018 V19.0.00800 Patch [PORTABLE].md
deleted file mode 100644
index 08405f7b202b05e3d5967f484c5cdb339572b622..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/FULL Nero Burning ROM 2018 V19.0.00800 Patch [PORTABLE].md	
+++ /dev/null
@@ -1,14 +0,0 @@
-<h2>FULL Nero Burning ROM 2018 V19.0.00800 Patch</h2><br /><p><b><b>Download File</b> &#10004;&#10004;&#10004; <a href="https://gohhs.com/2uFTYY">https://gohhs.com/2uFTYY</a></b></p><br /><br />
-<br />
-Synthesia 10.4.4395 Installing the full version, including Crack with a patch! . Nero Burning ROM 2018 v19.0.00800 Updated Crack Download (cracksmania.net). Nero 8.3.12.3 Updated Crack download (cracksmania.net).
-Nero 10.4 Updated version (cracksmania.net).
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-Nero 12.3.0.1620 Updated version (cracksmania.net).
-Nero 12.3.0.1624 Updated version (cracksmania.net). 8a78ff9644<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/diacanFperku/AutoGPT/Mendesain Logo Surianto Rustan Pdf Download.md b/spaces/diacanFperku/AutoGPT/Mendesain Logo Surianto Rustan Pdf Download.md
deleted file mode 100644
index 0f561dcfc2cbaf174e5584284f0de97da12eba91..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Mendesain Logo Surianto Rustan Pdf Download.md	
+++ /dev/null
@@ -1,39 +0,0 @@
-
-<h1>How to Design a Logo with Surianto Rustan's Book</h1>
-<p>If you are interested in learning how to design a logo, you might want to check out Surianto Rustan's book, <em>Mendesain Logo</em>. This book is written by a professional graphic designer and lecturer who has more than 20 years of experience in the field. In this book, you will find a comprehensive guide on the history, theory, and practice of logo design.</p>
-<p><em>Mendesain Logo</em> covers various topics related to logo design, such as:</p>
-<h2>Mendesain Logo Surianto Rustan Pdf Download</h2><br /><p><b><b>Download</b> &#128505; <a href="https://gohhs.com/2uFTbu">https://gohhs.com/2uFTbu</a></b></p><br /><br />
-<ul>
-<li>The definition and types of logos</li>
-<li>The anatomy and classification of logo shapes</li>
-<li>The steps and criteria for creating a logo</li>
-<li>The principles of Gestalt and Fengshui in logo design</li>
-<li>The system of identity and brand architecture</li>
-<li>The issues and trends around logo design</li>
-<li>The exploration and examples of logo design</li>
-</ul>
-<p>The book also provides references and sources for further reading and inspiration. You can download the pdf version of the book from <a href="https://books.google.com/books/about/Mendesain_Logo.html?id=hVdjDwAAQBAJ">Google Books</a> or <a href="https://play.google.com/store/books/details/Mendesain_Logo?id=hVdjDwAAQBAJ&gl=US">Google Play Books</a>. Alternatively, you can order the printed version from <a href="https://www.suriantorustan.com/category/books/">Surianto Rustan's website</a>.</p>
-<p>Whether you are a student, a practitioner, or a hobbyist, <em>Mendesain Logo</em> will help you develop your skills and knowledge in logo design. It is a valuable resource for anyone who wants to create effective and memorable logos.</p>
-
-<p>One of the highlights of <em>Mendesain Logo</em> is the exploration and examples of logo design. In this section, Surianto Rustan showcases his own works as well as the works of other renowned logo designers from around the world. He analyzes and explains the concepts and processes behind each logo, as well as the challenges and solutions that he or the other designers faced. He also gives tips and advice on how to improve and refine your logo design skills.</p>
-<p>Some of the logos that are featured in this section include:</p>
-<ul>
-<li>The logo of Gramedia Pustaka Utama, the publisher of the book</li>
-<li>The logo of Provisi Education, a company that provides training and consulting services</li>
-<li>The logo of Nike, one of the most iconic and recognizable logos in the world</li>
-<li>The logo of Fujifilm, a company that produces photographic and imaging products</li>
-<li>The logo of Blis, a company that specializes in location data technology</li>
-</ul>
-<p>By studying these logos and their stories, you will gain insights and inspiration for your own logo design projects. You will also learn how to apply the principles and techniques that Surianto Rustan teaches in his book.</p>
-
-<p><em>Mendesain Logo</em> is a must-read book for anyone who wants to learn how to design a logo. It covers everything from the basics to the advanced aspects of logo design, with clear explanations and illustrations. It also showcases the works and experiences of Surianto Rustan and other logo designers, giving you a glimpse into their creative minds and processes. Whether you are a beginner or an expert, you will find something useful and valuable in this book.</p>
-<p></p>
-<p>If you are interested in downloading or ordering <em>Mendesain Logo</em>, you can visit the following links:</p>
-<ul>
-<li><a href="https://books.google.com/books/about/Mendesain_Logo.html?id=hVdjDwAAQBAJ">Google Books</a></li>
-<li><a href="https://play.google.com/store/books/details/Mendesain_Logo?id=hVdjDwAAQBAJ&gl=US">Google Play Books</a></li>
-<li><a href="https://www.suriantorustan.com/category/books/">Surianto Rustan's website</a></li>
-</ul>
-<p>Happy reading and happy designing!</p> d5da3c52bf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/digitalxingtong/Xingtong-Longread-Bert-VITS2/text/chinese_bert.py b/spaces/digitalxingtong/Xingtong-Longread-Bert-VITS2/text/chinese_bert.py
deleted file mode 100644
index cb84ce0b426cd0a1c7954ddcdf41322c10ed14fa..0000000000000000000000000000000000000000
--- a/spaces/digitalxingtong/Xingtong-Longread-Bert-VITS2/text/chinese_bert.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import torch
-from transformers import AutoTokenizer, AutoModelForMaskedLM
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-tokenizer = AutoTokenizer.from_pretrained("./bert/chinese-roberta-wwm-ext-large")
-model = AutoModelForMaskedLM.from_pretrained("./bert/chinese-roberta-wwm-ext-large").to(device)
-
-def get_bert_feature(text, word2ph):
-    with torch.no_grad():
-        inputs = tokenizer(text, return_tensors='pt')
-        for i in inputs:
-            inputs[i] = inputs[i].to(device)
-        res = model(**inputs, output_hidden_states=True)
-        res = torch.cat(res['hidden_states'][-3:-2], -1)[0].cpu()
-
-    assert len(word2ph) == len(text)+2
-    word2phone = word2ph
-    phone_level_feature = []
-    for i in range(len(word2phone)):
-        repeat_feature = res[i].repeat(word2phone[i], 1)
-        phone_level_feature.append(repeat_feature)
-
-    phone_level_feature = torch.cat(phone_level_feature, dim=0)
-
-
-    return phone_level_feature.T
-
-if __name__ == '__main__':
-    # feature = get_bert_feature('你好,我是说的道理。')
-    import torch
-
-    word_level_feature = torch.rand(38, 1024)  # 12个词,每个词1024维特征
-    word2phone = [1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1]
-
-    # 计算总帧数
-    total_frames = sum(word2phone)
-    print(word_level_feature.shape)
-    print(word2phone)
-    phone_level_feature = []
-    for i in range(len(word2phone)):
-        print(word_level_feature[i].shape)
-
-        # 对每个词重复word2phone[i]次
-        repeat_feature = word_level_feature[i].repeat(word2phone[i], 1)
-        phone_level_feature.append(repeat_feature)
-
-    phone_level_feature = torch.cat(phone_level_feature, dim=0)
-    print(phone_level_feature.shape)  # torch.Size([36, 1024])
-
diff --git a/spaces/dinhminh20521597/OCR_DEMO/configs/textrecog/abinet/README.md b/spaces/dinhminh20521597/OCR_DEMO/configs/textrecog/abinet/README.md
deleted file mode 100644
index 40d8fdb7c7b62490de46fc4c411c495b6f1c8588..0000000000000000000000000000000000000000
--- a/spaces/dinhminh20521597/OCR_DEMO/configs/textrecog/abinet/README.md
+++ /dev/null
@@ -1,59 +0,0 @@
-# ABINet
-
-> [Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition](https://arxiv.org/abs/2103.06495)
-
-<!-- [ALGORITHM] -->
-
-## Abstract
-
-Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively model linguistic rules in end-to-end deep networks remains a research challenge. In this paper, we argue that the limited capacity of language models comes from: 1) implicitly language modeling; 2) unidirectional feature representation; and 3) language model with noise input. Correspondingly, we propose an autonomous, bidirectional and iterative ABINet for scene text recognition. Firstly, the autonomous suggests to block gradient flow between vision and language models to enforce explicitly language modeling. Secondly, a novel bidirectional cloze network (BCN) as the language model is proposed based on bidirectional feature representation. Thirdly, we propose an execution manner of iterative correction for language model which can effectively alleviate the impact of noise input. Additionally, based on the ensemble of iterative predictions, we propose a self-training method which can learn from unlabeled images effectively. Extensive experiments indicate that ABINet has superiority on low-quality images and achieves state-of-the-art results on several mainstream benchmarks. Besides, the ABINet trained with ensemble self-training shows promising improvement in realizing human-level recognition.
-
-<div align=center>
-<img src="https://user-images.githubusercontent.com/22607038/145804331-9ae955dc-0d3b-41eb-a6b2-dc7c9f7c1bef.png"/>
-</div>
-
-## Dataset
-
-### Train Dataset
-
-| trainset  | instance_num | repeat_num |     note     |
-| :-------: | :----------: | :--------: | :----------: |
-|  Syn90k   |   8919273    |     1      |    synth     |
-| SynthText |   7239272    |     1      | alphanumeric |
-
-### 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                       |                       pretrained                       |        | Regular Text |      |      | Irregular Text |      | download                                             |
-| :------------------------------------------------: | :----------------------------------------------------: | :----: | :----------: | :--: | :--: | :------------: | :--: | :--------------------------------------------------- |
-|                                                    |                                                        | IIIT5K |     SVT      | IC13 | IC15 |      SVTP      | CT80 |                                                      |
-| [ABINet-Vision](https://github.com/open-mmlab/mmocr/tree/master/configs/textrecog/abinet/abinet_vision_only_academic.py) |                           -                            |  94.7  |     91.7     | 93.6 | 83.0 |      85.1      | 86.5 | [model](https://download.openmmlab.com/mmocr/textrecog/abinet/abinet_vision_only_academic-e6b9ea89.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/abinet/20211201_195512.log) |
-| [ABINet](https://github.com/open-mmlab/mmocr/tree/master/configs/textrecog/abinet/abinet_academic.py) | [Pretrained](https://download.openmmlab.com/mmocr/textrecog/abinet/abinet_pretrain-1bed979b.pth) |  95.7  |     94.6     | 95.7 | 85.1 |      90.4      | 90.3 | [model](https://download.openmmlab.com/mmocr/textrecog/abinet/abinet_academic-f718abf6.pth) \| [log1](https://download.openmmlab.com/mmocr/textrecog/abinet/20211210_095832.log) \| [log2](https://download.openmmlab.com/mmocr/textrecog/abinet/20211213_131724.log) |
-
-```{note}
-1. ABINet allows its encoder to run and be trained without decoder and fuser. Its encoder is designed to recognize texts as a stand-alone model and therefore can work as an independent text recognizer. We release it as ABINet-Vision.
-2. Facts about the pretrained model: MMOCR does not have a systematic pipeline to pretrain the language model (LM) yet, thus the weights of LM are converted from [the official pretrained model](https://github.com/FangShancheng/ABINet). The weights of ABINet-Vision are directly used as the vision model of ABINet.
-3. Due to some technical issues, the training process of ABINet was interrupted at the 13th epoch and we resumed it later. Both logs are released for full reference.
-4. The model architecture in the logs looks slightly different from the final released version, since it was refactored afterward. However, both architectures are essentially equivalent.
-```
-
-## Citation
-
-```bibtex
-@article{fang2021read,
-  title={Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition},
-  author={Fang, Shancheng and Xie, Hongtao and Wang, Yuxin and Mao, Zhendong and Zhang, Yongdong},
-    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
-  year={2021}
-}
-```
diff --git a/spaces/djsull/aha-summarisation/README.md b/spaces/djsull/aha-summarisation/README.md
deleted file mode 100644
index 81f63b2b0f409d6fc6237f26a211a2ef7b53ffaa..0000000000000000000000000000000000000000
--- a/spaces/djsull/aha-summarisation/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Aha Summarisation
-emoji: 📈
-colorFrom: blue
-colorTo: pink
-sdk: gradio
-sdk_version: 3.0.22
-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/esc-bench/ESC/app.py b/spaces/esc-bench/ESC/app.py
deleted file mode 100644
index 6dfdf6b7d68d4819147399976d0c416cf079a665..0000000000000000000000000000000000000000
--- a/spaces/esc-bench/ESC/app.py
+++ /dev/null
@@ -1,169 +0,0 @@
-import streamlit as st
-from pandas import read_csv
-import os
-import jiwer
-from huggingface_hub import Repository
-import zipfile
-
-REFERENCE_NAME = "references"
-SUBMISSION_NAME = "submissions"
-
-REFERENCE_URL = os.path.join(
-    "https://huggingface.co/datasets/esc-bench", REFERENCE_NAME
-)
-SUBMISSION_URL = os.path.join(
-    "https://huggingface.co/datasets/esc-bench", SUBMISSION_NAME
-)
-
-TEST_SETS = [
-    "ls-clean",
-    "ls-other",
-    "cv",
-    "vox",
-    "ted",
-    "giga",
-    "spgi",
-    "earnings",
-    "ami",
-]
-EXPECTED_TEST_FILES = [f + ".txt" for f in TEST_SETS]
-
-OPTIONAL_TEST_SETS = ["swbd", "ch", "chime-4"]
-OPTIONAL_TEST_FILES = [f + ".txt" for f in OPTIONAL_TEST_SETS]
-
-CSV_RESULTS_FILE = os.path.join(SUBMISSION_NAME, "results.csv")
-
-HF_TOKEN = os.environ.get("HF_TOKEN")
-
-
-def compute_wer(pred_file, ref_file):
-    with open(pred_file, "r", encoding="utf-8") as pred, open(
-        ref_file, "r", encoding="utf-8"
-    ) as ref:
-        pred_lines = [line.strip() for line in pred.readlines()]
-        ref_lines = [line.strip() for line in ref.readlines()]
-
-    wer = jiwer.wer(ref_lines, pred_lines)
-    return wer
-
-
-reference_repo = Repository(
-    local_dir="references", clone_from=REFERENCE_URL, use_auth_token=HF_TOKEN
-)
-submission_repo = Repository(
-    local_dir="submissions", clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN
-)
-submission_repo.git_pull()
-
-all_submissions = [
-    folder
-    for folder in os.listdir(SUBMISSION_NAME)
-    if os.path.isdir(os.path.join(SUBMISSION_NAME, folder)) and folder != ".git"
-]
-
-all_results = read_csv(CSV_RESULTS_FILE)
-
-
-# Write table form CSV
-table = all_results.copy()
-
-esc_column = table.pop("esc-score")
-name_column = table.pop("name")
-table.insert(0, "esc-score", esc_column)
-table = table.select_dtypes(exclude=['object', 'string'])
-table.insert(0, "name", name_column)
-table = table.sort_values(by=['esc-score'], ascending=True, ignore_index=True)
-table = table.round(2)
-table.index = table.index + 1
-
-# Streamlit
-st.markdown("# ESC: A Benchmark For Multi-Domain End-to-End Speech Recognition")
-
-st.markdown(
-    f"""
-    This is the leaderboard of the End-to end Speech Challenge (ESC).
-    Submitted systems are ranked by the **ESC Score** which is the average of
-    all non-optional datasets: {", ".join(TEST_SETS)}. The optional datasets of swbd, ch and chime-4 do not contribute to the ESC score."""
-)
-
-# st.table(table)
-st.dataframe(table.style.format(subset=["esc-score", *TEST_SETS, *OPTIONAL_TEST_SETS], formatter="{:.1f}"))
-
-st.markdown(
-    """
-    ESC was proposed in *ESC: A Benchmark For Multi-Domain End-to-End Speech Recognition* by ...
-    \n
-    The abstract of the paper is as follows:
-    \n
-    *Speech recognition applications cover a range of different audio and text distributions, with different speaking styles, background noise, transcription punctuation and character casing. However, many speech recognition systems require dataset-specific tuning (audio filtering, punctuation removal and normalisation of casing), therefore assuming a-priori knowledge of both the audio and text distributions. This tuning requirement can lead to systems failing to generalise to other datasets and domains. To promote the development of multi-domain speech systems, we introduce the End-to end Speech Challenge (ESC) for evaluating the performance of a single automatic speech recognition (ASR) system across a broad set of speech datasets. Benchmarked systems must use the same data pre- and post-processing algorithm across datasets - assuming the audio and text data distributions are a-priori unknown. We compare a series of state-of-the-art (SoTA) end-to-end (E2E) systems on this benchmark, demonstrating how a single speechsystem can be applied and evaluated on a wide range of data distributions. We find E2E systems to be effective across datasets: in a fair comparison, E2E systems achieve within 2.6% of SoTA systems tuned to a specific dataset. Our analysis reveals that transcription artefacts, such as punctuation and casing, pose difficulties for ASR systems and should be included in evaluation. We believe E2E benchmarking over a range of datasets promotes the research of multi-domain speech recognition systems.*
-    \n
-    For more information, please see the official submission on [OpenReview.net](https://openreview.net/forum?id=9OL2fIfDLK).
-    """
-)
-
-st.markdown(
-   """
-   ## Submitting to ESC
-   \n
-   To submit to ESC, download the audio data for the nine mandatory ESC test sets from [esc-datasets](https://huggingface.co/datasets/esc-bench/esc-datasets). The test sets contain audio data only. Evaluate your system on the nine test sets by generating predictions for the unlabelled audio samples. For each test set, save the predictions to a .txt file in the order that the audio samples are provided, with one prediction per line. Name the .txt file according to the ESC test set names shown in the table (e.g. the predictions for LibriSpeech test-clean should be named ls-clean.txt).
-   \n
-   Once you have evaluated your system on all nine test sets, move the predictions into one folder and zip it. The name you assign to the zipped folder will be the name that is shown on the table (e.g. whisper-aed.zip will be displayed as whisper-aed). Upload your zipped submissions for scoring and placement on the leaderboard.
-"""
-)
-
-# Using the "with" syntax
-with st.form(key="my_form"):
-    uploaded_file = st.file_uploader("Choose a zip file")
-    submit_button = st.form_submit_button(label="Submit")
-
-if submit_button:
-    if uploaded_file is None:
-        raise ValueError("Please make sure to have uploaded a zip file.")
-
-    submission = uploaded_file.name.split(".zip")[0]
-    with st.spinner(f"Uploading {submission}..."):
-        with zipfile.ZipFile(uploaded_file, 'r') as zip_ref:
-            zip_ref.extractall(submission_repo.local_dir)
-            submission_repo.push_to_hub()
-
-    with st.spinner(f"Computing ESC Score for {submission}..."):
-        results = {"name": submission}
-        all_submitted_files = os.listdir(os.path.join(SUBMISSION_NAME, submission))
-
-        submitted_files = [f for f in all_submitted_files if f in EXPECTED_TEST_FILES]
-        submitted_optional_files = [f for f in all_submitted_files if f in OPTIONAL_TEST_FILES]
-
-        if sorted(EXPECTED_TEST_FILES) != sorted(submitted_files):
-            raise ValueError(
-                f"{', '.join(submitted_files)} were submitted, but expected {', '.join(EXPECTED_TEST_FILES)}"
-            )
-
-        for file in submitted_files:
-            ref_file = os.path.join(REFERENCE_NAME, file)
-            pred_file = os.path.join(SUBMISSION_NAME, submission, file)
-
-            wer = compute_wer(pred_file, ref_file)
-            results[file.split(".")[0]] = round(100 * wer, 2)
-        
-        for file in submitted_optional_files:
-            ref_file = os.path.join(REFERENCE_NAME, file)
-            pred_file = os.path.join(SUBMISSION_NAME, submission, file)
-
-            wer = compute_wer(pred_file, ref_file)
-            results[file.split(".")[0]] = round(100 * wer, 2)
-
-        # ESC score is computed over the mandatory test sets only
-        wer_values = [float(results[t]) for t in TEST_SETS]
-        # first average over LS test sets
-        wer_values = [sum(wer_values[:2]) / 2, *wer_values[2:]]
-        # then macro-average over ESC test sets
-        all_wer = sum(wer_values) / len(wer_values)
-
-        results["esc-score"] = round(all_wer, 2)
-        all_results = all_results.append(results, ignore_index=True)
-
-        # save and upload new evaluated results
-        all_results.to_csv(CSV_RESULTS_FILE, index=False)
-        commit_url = submission_repo.push_to_hub()
-
-    st.success('Please refresh this space (CTRL+R) to see your result')
diff --git a/spaces/falterWliame/Face_Mask_Detection/(2011) Wwe Smackdown Vs Raw 2012 Ps2 Game Highly Compressed.md b/spaces/falterWliame/Face_Mask_Detection/(2011) Wwe Smackdown Vs Raw 2012 Ps2 Game Highly Compressed.md
deleted file mode 100644
index 33c5da84d8dda4d3c547acb1fd3eced1ccedfacc..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/(2011) Wwe Smackdown Vs Raw 2012 Ps2 Game Highly Compressed.md	
+++ /dev/null
@@ -1,9 +0,0 @@
-
-<p>if you want realistic wrestling games, stick with the wwe 2k games. the rock 'n' wrestling series, though, manages to keep you in the game through the use of cut-scenes and characters from the actual sport of wrestling.</p>
-<p>the rock 'n' wrestling games are by far the best wrestling games that you can get on the system, hands-down. although they're not the best wrestling games on the system by a long shot, they have a great story and a great gameplay mechanic.</p>
-<h2>(2011) Wwe Smackdown Vs Raw 2012 Ps2 Game Highly Compressed</h2><br /><p><b><b>Download File</b> &#10001; <a href="https://urlca.com/2uDcJ4">https://urlca.com/2uDcJ4</a></b></p><br /><br />
-<p>the rock 'n' wrestling series is by far the best wrestling game that you can get on the system, hands down. although it's not the best wrestling game on the system by a long shot, it has a great story and a great gameplay mechanic.</p>
-<p>the roster is made up of wrestlers from all five brands, and each has their own unique moveset and skill tree. the game also features a roster editor, allowing players to design their own wrestlers and create their own moveset. in addition, the wrestlers have to be unlocked by playing through a story mode, in which they are gradually given new moves and more options. the best thing to do is to play the story mode and unlock characters by playing through various modes, if possible. this way the player will experience the main story mode as a whole. this is due to the game having more than 50 wrestlers. yes, thats right, 50. why is it so many? well, some of these wrestlers have been released on separate dlc packs. for example, john cena has been released and the dlc is now a part of the game. <br></p>
-<p>the story mode is the main focus of the game. its main objective is to create a career for a wrestler to show their potential. this mode is broken into three different modes: in-ring, backstage and legends. the in-ring and backstage mode is the story mode. in this mode, the player will select a wrestler and start his/her career. theres so many modes to choose from such as, single, tag team, and steel cage match. the player will be able to win championships, and compete in various matches.</p> 899543212b<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/falterWliame/Face_Mask_Detection/Football Manager Handheld 2013 EUR PSP ISO CSO Download ((BETTER)).md b/spaces/falterWliame/Face_Mask_Detection/Football Manager Handheld 2013 EUR PSP ISO CSO Download ((BETTER)).md
deleted file mode 100644
index 4986d8de5f01f9066901577621ecb2ceb6dad5ce..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/Football Manager Handheld 2013 EUR PSP ISO CSO Download ((BETTER)).md	
+++ /dev/null
@@ -1,24 +0,0 @@
-<br />
-<h1>How to Download and Play Football Manager Handheld 2013 on PSP</h1>
-<p>If you are a fan of sports simulation games, you might want to try Football Manager Handheld 2013, a popular game for PlayStation Portable that lets you manage your own soccer team. In this game, you can choose from hundreds of clubs from 14 different countries, scout players, train them, set tactics, and compete in various leagues and cups. You can also customize your own club logo, kits, and stadium.</p>
-<p>But how can you download and play Football Manager Handheld 2013 on your PSP? Here are the steps you need to follow:</p>
-<h2>Football Manager Handheld 2013 EUR PSP ISO CSO Download</h2><br /><p><b><b>DOWNLOAD</b> ===> <a href="https://urlca.com/2uDdpT">https://urlca.com/2uDdpT</a></b></p><br /><br />
-<ol>
-<li>First, you need to have a PSP console that is compatible with the game. The game is available in Europe and has English, French, Italian, and Spanish languages. The game ID is ULES-01582 and the ISO file size is about 30 MB.</li>
-<li>Second, you need to find a reliable source to download the game ISO or CSO file. You can search online for websites that offer PSP ROMs or ISOs, such as CDRomance, ConsoleRoms, Dailymotion, Hart and Soul Essentials, or Awareness. Make sure to check the reviews and ratings of the websites before downloading anything.</li>
-<li>Third, you need to transfer the game ISO or CSO file to your PSP memory stick. You can use a USB cable or a card reader to connect your PSP to your computer. Then, create a folder named ISO in the root directory of your memory stick and copy the game file there.</li>
-<li>Fourth, you need to launch the game on your PSP. You can use the default PSP firmware or a custom firmware that supports ISO or CSO loading. To do that, go to the Game menu on your PSP and select Memory Stick. Then, find and select Football Manager Handheld 2013 and enjoy!</li>
-</ol>
-<p>That's it! You are now ready to play Football Manager Handheld 2013 on your PSP. Have fun managing your dream team!</p>
-
-<p>If you want to learn more about Football Manager Handheld 2013, here are some tips and tricks that can help you improve your gameplay:</p>
-<ul>
-<li>Use the quick save and quick load features to experiment with different decisions and outcomes. You can access these features by pressing the Start button on your PSP.</li>
-<li>Pay attention to the morale and fitness of your players. You can boost their morale by praising them, offering them new contracts, or giving them bonuses. You can also rest them or rotate them to avoid injuries and fatigue.</li>
-<li>Use the scouting network to find new players for your team. You can assign scouts to different regions and specify the attributes and positions you are looking for. You can also browse the transfer market and make bids for players you want.</li>
-<li>Use the training mode to improve the skills and attributes of your players. You can set individual training schedules for each player or use the default ones. You can also assign coaches to different areas of training.</li>
-<li>Use the tactics mode to set up your formation, strategy, and style of play. You can choose from various presets or create your own custom tactics. You can also adjust your tactics during matches depending on the situation.</li>
-</ul>
-<p>With these tips and tricks, you can become a better manager and lead your team to glory. Football Manager Handheld 2013 is a fun and addictive game that will keep you entertained for hours. Download it today and see for yourself!</p> d5da3c52bf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/fb700/chatglm-fitness-RLHF/crazy_functions/crazy_utils.py b/spaces/fb700/chatglm-fitness-RLHF/crazy_functions/crazy_utils.py
deleted file mode 100644
index a1b1493ce7b196094b6b8ffdf08273bf392a4e30..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/crazy_functions/crazy_utils.py
+++ /dev/null
@@ -1,748 +0,0 @@
-from toolbox import update_ui, get_conf, trimmed_format_exc
-import threading
-
-def input_clipping(inputs, history, max_token_limit):
-    import numpy as np
-    from request_llm.bridge_all import model_info
-    enc = model_info["gpt-3.5-turbo"]['tokenizer']
-    def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
-
-    mode = 'input-and-history'
-    # 当 输入部分的token占比 小于 全文的一半时，只裁剪历史
-    input_token_num = get_token_num(inputs)
-    if input_token_num < max_token_limit//2: 
-        mode = 'only-history'
-        max_token_limit = max_token_limit - input_token_num
-
-    everything = [inputs] if mode == 'input-and-history' else ['']
-    everything.extend(history)
-    n_token = get_token_num('\n'.join(everything))
-    everything_token = [get_token_num(e) for e in everything]
-    delta = max(everything_token) // 16 # 截断时的颗粒度
-        
-    while n_token > max_token_limit:
-        where = np.argmax(everything_token)
-        encoded = enc.encode(everything[where], disallowed_special=())
-        clipped_encoded = encoded[:len(encoded)-delta]
-        everything[where] = enc.decode(clipped_encoded)[:-1]    # -1 to remove the may-be illegal char
-        everything_token[where] = get_token_num(everything[where])
-        n_token = get_token_num('\n'.join(everything))
-
-    if mode == 'input-and-history':
-        inputs = everything[0]
-    else:
-        pass
-    history = everything[1:]
-    return inputs, history
-
-def request_gpt_model_in_new_thread_with_ui_alive(
-        inputs, inputs_show_user, llm_kwargs, 
-        chatbot, history, sys_prompt, refresh_interval=0.2,
-        handle_token_exceed=True, 
-        retry_times_at_unknown_error=2,
-        ):
-    """
-    Request GPT model，请求GPT模型同时维持用户界面活跃。
-
-    输入参数 Args （以_array结尾的输入变量都是列表，列表长度为子任务的数量，执行时，会把列表拆解，放到每个子线程中分别执行）:
-        inputs (string): List of inputs （输入）
-        inputs_show_user (string): List of inputs to show user（展现在报告中的输入，借助此参数，在汇总报告中隐藏啰嗦的真实输入，增强报告的可读性）
-        top_p (float): Top p value for sampling from model distribution （GPT参数，浮点数）
-        temperature (float): Temperature value for sampling from model distribution（GPT参数，浮点数）
-        chatbot: chatbot inputs and outputs （用户界面对话窗口句柄，用于数据流可视化）
-        history (list): List of chat history （历史，对话历史列表）
-        sys_prompt (string): List of system prompts （系统输入，列表，用于输入给GPT的前提提示，比如你是翻译官怎样怎样）
-        refresh_interval (float, optional): Refresh interval for UI (default: 0.2) （刷新时间间隔频率，建议低于1，不可高于3，仅仅服务于视觉效果）
-        handle_token_exceed：是否自动处理token溢出的情况，如果选择自动处理，则会在溢出时暴力截断，默认开启
-        retry_times_at_unknown_error：失败时的重试次数
-
-    输出 Returns:
-        future: 输出，GPT返回的结果
-    """
-    import time
-    from concurrent.futures import ThreadPoolExecutor
-    from request_llm.bridge_all import predict_no_ui_long_connection
-    # 用户反馈
-    chatbot.append([inputs_show_user, ""])
-    yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-    executor = ThreadPoolExecutor(max_workers=16)
-    mutable = ["", time.time(), ""]
-    def _req_gpt(inputs, history, sys_prompt):
-        retry_op = retry_times_at_unknown_error
-        exceeded_cnt = 0
-        while True:
-            # watchdog error
-            if len(mutable) >= 2 and (time.time()-mutable[1]) > 5: 
-                raise RuntimeError("检测到程序终止。")
-            try:
-                # 【第一种情况】：顺利完成
-                result = predict_no_ui_long_connection(
-                    inputs=inputs, llm_kwargs=llm_kwargs,
-                    history=history, sys_prompt=sys_prompt, observe_window=mutable)
-                return result
-            except ConnectionAbortedError as token_exceeded_error:
-                # 【第二种情况】：Token溢出
-                if handle_token_exceed:
-                    exceeded_cnt += 1
-                    # 【选择处理】 尝试计算比例，尽可能多地保留文本
-                    from toolbox import get_reduce_token_percent
-                    p_ratio, n_exceed = get_reduce_token_percent(str(token_exceeded_error))
-                    MAX_TOKEN = 4096
-                    EXCEED_ALLO = 512 + 512 * exceeded_cnt
-                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN-EXCEED_ALLO)
-                    mutable[0] += f'[Local Message] 警告，文本过长将进行截断，Token溢出数：{n_exceed}。\n\n'
-                    continue # 返回重试
-                else:
-                    # 【选择放弃】
-                    tb_str = '```\n' + trimmed_format_exc() + '```'
-                    mutable[0] += f"[Local Message] 警告，在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                    return mutable[0] # 放弃
-            except:
-                # 【第三种情况】：其他错误：重试几次
-                tb_str = '```\n' + trimmed_format_exc() + '```'
-                print(tb_str)
-                mutable[0] += f"[Local Message] 警告，在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                if retry_op > 0:
-                    retry_op -= 1
-                    mutable[0] += f"[Local Message] 重试中，请稍等 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}：\n\n"
-                    if ("Rate limit reached" in tb_str) or ("Too Many Requests" in tb_str):
-                        time.sleep(30)
-                    time.sleep(5)
-                    continue # 返回重试
-                else:
-                    time.sleep(5)
-                    return mutable[0] # 放弃
-
-    # 提交任务
-    future = executor.submit(_req_gpt, inputs, history, sys_prompt)
-    while True:
-        # yield一次以刷新前端页面
-        time.sleep(refresh_interval)
-        # “喂狗”（看门狗）
-        mutable[1] = time.time()
-        if future.done():
-            break
-        chatbot[-1] = [chatbot[-1][0], mutable[0]]
-        yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-
-    final_result = future.result()
-    chatbot[-1] = [chatbot[-1][0], final_result]
-    yield from update_ui(chatbot=chatbot, history=[]) # 如果最后成功了，则删除报错信息
-    return final_result
-
-
-def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
-        inputs_array, inputs_show_user_array, llm_kwargs, 
-        chatbot, history_array, sys_prompt_array, 
-        refresh_interval=0.2, max_workers=-1, scroller_max_len=30,
-        handle_token_exceed=True, show_user_at_complete=False,
-        retry_times_at_unknown_error=2,
-        ):
-    """
-    Request GPT model using multiple threads with UI and high efficiency
-    请求GPT模型的[多线程]版。
-    具备以下功能：
-        实时在UI上反馈远程数据流
-        使用线程池，可调节线程池的大小避免openai的流量限制错误
-        处理中途中止的情况
-        网络等出问题时，会把traceback和已经接收的数据转入输出
-
-    输入参数 Args （以_array结尾的输入变量都是列表，列表长度为子任务的数量，执行时，会把列表拆解，放到每个子线程中分别执行）:
-        inputs_array (list): List of inputs （每个子任务的输入）
-        inputs_show_user_array (list): List of inputs to show user（每个子任务展现在报告中的输入，借助此参数，在汇总报告中隐藏啰嗦的真实输入，增强报告的可读性）
-        llm_kwargs: llm_kwargs参数
-        chatbot: chatbot （用户界面对话窗口句柄，用于数据流可视化）
-        history_array (list): List of chat history （历史对话输入，双层列表，第一层列表是子任务分解，第二层列表是对话历史）
-        sys_prompt_array (list): List of system prompts （系统输入，列表，用于输入给GPT的前提提示，比如你是翻译官怎样怎样）
-        refresh_interval (float, optional): Refresh interval for UI (default: 0.2) （刷新时间间隔频率，建议低于1，不可高于3，仅仅服务于视觉效果）
-        max_workers (int, optional): Maximum number of threads (default: see config.py) （最大线程数，如果子任务非常多，需要用此选项防止高频地请求openai导致错误）
-        scroller_max_len (int, optional): Maximum length for scroller (default: 30)（数据流的显示最后收到的多少个字符，仅仅服务于视觉效果）
-        handle_token_exceed (bool, optional): （是否在输入过长时，自动缩减文本）
-        handle_token_exceed：是否自动处理token溢出的情况，如果选择自动处理，则会在溢出时暴力截断，默认开启
-        show_user_at_complete (bool, optional): (在结束时，把完整输入-输出结果显示在聊天框)
-        retry_times_at_unknown_error：子任务失败时的重试次数
-
-    输出 Returns:
-        list: List of GPT model responses （每个子任务的输出汇总，如果某个子任务出错，response中会携带traceback报错信息，方便调试和定位问题。）
-    """
-    import time, random
-    from concurrent.futures import ThreadPoolExecutor
-    from request_llm.bridge_all import predict_no_ui_long_connection
-    assert len(inputs_array) == len(history_array)
-    assert len(inputs_array) == len(sys_prompt_array)
-    if max_workers == -1: # 读取配置文件
-        try: max_workers, = get_conf('DEFAULT_WORKER_NUM')
-        except: max_workers = 8
-        if max_workers <= 0: max_workers = 3
-    # 屏蔽掉 chatglm的多线程，可能会导致严重卡顿
-    if not (llm_kwargs['llm_model'].startswith('gpt-') or llm_kwargs['llm_model'].startswith('api2d-')):
-        max_workers = 1
-        
-    executor = ThreadPoolExecutor(max_workers=max_workers)
-    n_frag = len(inputs_array)
-    # 用户反馈
-    chatbot.append(["请开始多线程操作。", ""])
-    yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-    # 跨线程传递
-    mutable = [["", time.time(), "等待中"] for _ in range(n_frag)]
-
-    # 子线程任务
-    def _req_gpt(index, inputs, history, sys_prompt):
-        gpt_say = ""
-        retry_op = retry_times_at_unknown_error
-        exceeded_cnt = 0
-        mutable[index][2] = "执行中"
-        while True:
-            # watchdog error
-            if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > 5: 
-                raise RuntimeError("检测到程序终止。")
-            try:
-                # 【第一种情况】：顺利完成
-                # time.sleep(10); raise RuntimeError("测试")
-                gpt_say = predict_no_ui_long_connection(
-                    inputs=inputs, llm_kwargs=llm_kwargs, history=history, 
-                    sys_prompt=sys_prompt, observe_window=mutable[index], console_slience=True
-                )
-                mutable[index][2] = "已成功"
-                return gpt_say
-            except ConnectionAbortedError as token_exceeded_error:
-                # 【第二种情况】：Token溢出，
-                if handle_token_exceed:
-                    exceeded_cnt += 1
-                    # 【选择处理】 尝试计算比例，尽可能多地保留文本
-                    from toolbox import get_reduce_token_percent
-                    p_ratio, n_exceed = get_reduce_token_percent(str(token_exceeded_error))
-                    MAX_TOKEN = 4096
-                    EXCEED_ALLO = 512 + 512 * exceeded_cnt
-                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN-EXCEED_ALLO)
-                    gpt_say += f'[Local Message] 警告，文本过长将进行截断，Token溢出数：{n_exceed}。\n\n'
-                    mutable[index][2] = f"截断重试"
-                    continue # 返回重试
-                else:
-                    # 【选择放弃】
-                    tb_str = '```\n' + trimmed_format_exc() + '```'
-                    gpt_say += f"[Local Message] 警告，线程{index}在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                    if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
-                    mutable[index][2] = "输入过长已放弃"
-                    return gpt_say # 放弃
-            except:
-                # 【第三种情况】：其他错误
-                tb_str = '```\n' + trimmed_format_exc() + '```'
-                print(tb_str)
-                gpt_say += f"[Local Message] 警告，线程{index}在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
-                if retry_op > 0: 
-                    retry_op -= 1
-                    wait = random.randint(5, 20)
-                    if ("Rate limit reached" in tb_str) or ("Too Many Requests" in tb_str):
-                        wait = wait * 3
-                        fail_info = "OpenAI绑定信用卡可解除频率限制 "
-                    else:
-                        fail_info = ""
-                    # 也许等待十几秒后，情况会好转
-                    for i in range(wait):
-                        mutable[index][2] = f"{fail_info}等待重试 {wait-i}"; time.sleep(1)
-                    # 开始重试
-                    mutable[index][2] = f"重试中 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}"
-                    continue # 返回重试
-                else:
-                    mutable[index][2] = "已失败"
-                    wait = 5
-                    time.sleep(5)
-                    return gpt_say # 放弃
-
-    # 异步任务开始
-    futures = [executor.submit(_req_gpt, index, inputs, history, sys_prompt) for index, inputs, history, sys_prompt in zip(
-        range(len(inputs_array)), inputs_array, history_array, sys_prompt_array)]
-    cnt = 0
-    while True:
-        # yield一次以刷新前端页面
-        time.sleep(refresh_interval)
-        cnt += 1
-        worker_done = [h.done() for h in futures]
-        # 更好的UI视觉效果
-        observe_win = []
-        # 每个线程都要“喂狗”（看门狗）
-        for thread_index, _ in enumerate(worker_done):
-            mutable[thread_index][1] = time.time()
-        # 在前端打印些好玩的东西
-        for thread_index, _ in enumerate(worker_done):
-            print_something_really_funny = "[ ...`"+mutable[thread_index][0][-scroller_max_len:].\
-                replace('\n', '').replace('```', '...').replace(
-                    ' ', '.').replace('<br/>', '.....').replace('$', '.')+"`... ]"
-            observe_win.append(print_something_really_funny)
-        # 在前端打印些好玩的东西
-        stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n' 
-                            if not done else f'`{mutable[thread_index][2]}`\n\n' 
-                            for thread_index, done, obs in zip(range(len(worker_done)), worker_done, observe_win)])
-        # 在前端打印些好玩的东西
-        chatbot[-1] = [chatbot[-1][0], f'多线程操作已经开始，完成情况: \n\n{stat_str}' + ''.join(['.']*(cnt % 10+1))]
-        yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-        if all(worker_done):
-            executor.shutdown()
-            break
-
-    # 异步任务结束
-    gpt_response_collection = []
-    for inputs_show_user, f in zip(inputs_show_user_array, futures):
-        gpt_res = f.result()
-        gpt_response_collection.extend([inputs_show_user, gpt_res])
-    
-    # 是否在结束时，在界面上显示结果
-    if show_user_at_complete:
-        for inputs_show_user, f in zip(inputs_show_user_array, futures):
-            gpt_res = f.result()
-            chatbot.append([inputs_show_user, gpt_res])
-            yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
-            time.sleep(0.3)
-    return gpt_response_collection
-
-
-def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit):
-    def cut(txt_tocut, must_break_at_empty_line):  # 递归
-        if get_token_fn(txt_tocut) <= limit:
-            return [txt_tocut]
-        else:
-            lines = txt_tocut.split('\n')
-            estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines)
-            estimated_line_cut = int(estimated_line_cut)
-            for cnt in reversed(range(estimated_line_cut)):
-                if must_break_at_empty_line:
-                    if lines[cnt] != "":
-                        continue
-                print(cnt)
-                prev = "\n".join(lines[:cnt])
-                post = "\n".join(lines[cnt:])
-                if get_token_fn(prev) < limit:
-                    break
-            if cnt == 0:
-                raise RuntimeError("存在一行极长的文本！")
-            # print(len(post))
-            # 列表递归接龙
-            result = [prev]
-            result.extend(cut(post, must_break_at_empty_line))
-            return result
-    try:
-        return cut(txt, must_break_at_empty_line=True)
-    except RuntimeError:
-        return cut(txt, must_break_at_empty_line=False)
-
-
-def force_breakdown(txt, limit, get_token_fn):
-    """
-    当无法用标点、空行分割时，我们用最暴力的方法切割
-    """
-    for i in reversed(range(len(txt))):
-        if get_token_fn(txt[:i]) < limit:
-            return txt[:i], txt[i:]
-    return "Tiktoken未知错误", "Tiktoken未知错误"
-
-def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
-    # 递归
-    def cut(txt_tocut, must_break_at_empty_line, break_anyway=False):  
-        if get_token_fn(txt_tocut) <= limit:
-            return [txt_tocut]
-        else:
-            lines = txt_tocut.split('\n')
-            estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines)
-            estimated_line_cut = int(estimated_line_cut)
-            cnt = 0
-            for cnt in reversed(range(estimated_line_cut)):
-                if must_break_at_empty_line:
-                    if lines[cnt] != "":
-                        continue
-                prev = "\n".join(lines[:cnt])
-                post = "\n".join(lines[cnt:])
-                if get_token_fn(prev) < limit:
-                    break
-            if cnt == 0:
-                if break_anyway:
-                    prev, post = force_breakdown(txt_tocut, limit, get_token_fn)
-                else:
-                    raise RuntimeError(f"存在一行极长的文本！{txt_tocut}")
-            # print(len(post))
-            # 列表递归接龙
-            result = [prev]
-            result.extend(cut(post, must_break_at_empty_line, break_anyway=break_anyway))
-            return result
-    try:
-        # 第1次尝试，将双空行（\n\n）作为切分点
-        return cut(txt, must_break_at_empty_line=True)
-    except RuntimeError:
-        try:
-            # 第2次尝试，将单空行（\n）作为切分点
-            return cut(txt, must_break_at_empty_line=False)
-        except RuntimeError:
-            try:
-                # 第3次尝试，将英文句号（.）作为切分点
-                res = cut(txt.replace('.', '。\n'), must_break_at_empty_line=False) # 这个中文的句号是故意的，作为一个标识而存在
-                return [r.replace('。\n', '.') for r in res]
-            except RuntimeError as e:
-                try:
-                    # 第4次尝试，将中文句号（。）作为切分点
-                    res = cut(txt.replace('。', '。。\n'), must_break_at_empty_line=False)
-                    return [r.replace('。。\n', '。') for r in res]
-                except RuntimeError as e:
-                    # 第5次尝试，没办法了，随便切一下敷衍吧
-                    return cut(txt, must_break_at_empty_line=False, break_anyway=True)
-
-
-
-def read_and_clean_pdf_text(fp):
-    """
-    这个函数用于分割pdf，用了很多trick，逻辑较乱，效果奇好
-
-    **输入参数说明**
-    - `fp`：需要读取和清理文本的pdf文件路径
-
-    **输出参数说明**
-    - `meta_txt`：清理后的文本内容字符串
-    - `page_one_meta`：第一页清理后的文本内容列表
-
-    **函数功能**
-    读取pdf文件并清理其中的文本内容，清理规则包括：
-    - 提取所有块元的文本信息，并合并为一个字符串
-    - 去除短块（字符数小于100）并替换为回车符
-    - 清理多余的空行
-    - 合并小写字母开头的段落块并替换为空格
-    - 清除重复的换行
-    - 将每个换行符替换为两个换行符，使每个段落之间有两个换行符分隔
-    """
-    import fitz, copy
-    import re
-    import numpy as np
-    from colorful import print亮黄, print亮绿
-    fc = 0  # Index 0 文本
-    fs = 1  # Index 1 字体
-    fb = 2  # Index 2 框框
-    REMOVE_FOOT_NOTE = True # 是否丢弃掉 不是正文的内容 （比正文字体小，如参考文献、脚注、图注等）
-    REMOVE_FOOT_FFSIZE_PERCENT = 0.95 # 小于正文的？时，判定为不是正文（有些文章的正文部分字体大小不是100%统一的，有肉眼不可见的小变化）
-    def primary_ffsize(l):
-        """
-        提取文本块主字体
-        """
-        fsize_statiscs = {}
-        for wtf in l['spans']:
-            if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
-            fsize_statiscs[wtf['size']] += len(wtf['text'])
-        return max(fsize_statiscs, key=fsize_statiscs.get)
-        
-    def ffsize_same(a,b):
-        """
-        提取字体大小是否近似相等
-        """
-        return abs((a-b)/max(a,b)) < 0.02
-
-    with fitz.open(fp) as doc:
-        meta_txt = []
-        meta_font = []
-
-        meta_line = []
-        meta_span = []
-        ############################## <第 1 步，搜集初始信息> ##################################
-        for index, page in enumerate(doc):
-            # file_content += page.get_text()
-            text_areas = page.get_text("dict")  # 获取页面上的文本信息
-            for t in text_areas['blocks']:
-                if 'lines' in t:
-                    pf = 998
-                    for l in t['lines']:
-                        txt_line = "".join([wtf['text'] for wtf in l['spans']])
-                        if len(txt_line) == 0: continue
-                        pf = primary_ffsize(l)
-                        meta_line.append([txt_line, pf, l['bbox'], l])
-                        for wtf in l['spans']: # for l in t['lines']:
-                            meta_span.append([wtf['text'], wtf['size'], len(wtf['text'])])
-                    # meta_line.append(["NEW_BLOCK", pf])
-            # 块元提取                           for each word segment with in line                       for each line         cross-line words                          for each block
-            meta_txt.extend([" ".join(["".join([wtf['text'] for wtf in l['spans']]) for l in t['lines']]).replace(
-                '- ', '') for t in text_areas['blocks'] if 'lines' in t])
-            meta_font.extend([np.mean([np.mean([wtf['size'] for wtf in l['spans']])
-                             for l in t['lines']]) for t in text_areas['blocks'] if 'lines' in t])
-            if index == 0:
-                page_one_meta = [" ".join(["".join([wtf['text'] for wtf in l['spans']]) for l in t['lines']]).replace(
-                    '- ', '') for t in text_areas['blocks'] if 'lines' in t]
-                
-        ############################## <第 2 步，获取正文主字体> ##################################
-        fsize_statiscs = {}
-        for span in meta_span:
-            if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
-            fsize_statiscs[span[1]] += span[2]
-        main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
-        if REMOVE_FOOT_NOTE:
-            give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
-
-        ############################## <第 3 步，切分和重新整合> ##################################
-        mega_sec = []
-        sec = []
-        for index, line in enumerate(meta_line):
-            if index == 0: 
-                sec.append(line[fc])
-                continue
-            if REMOVE_FOOT_NOTE:
-                if meta_line[index][fs] <= give_up_fize_threshold:
-                    continue
-            if ffsize_same(meta_line[index][fs], meta_line[index-1][fs]):
-                # 尝试识别段落
-                if meta_line[index][fc].endswith('.') and\
-                    (meta_line[index-1][fc] != 'NEW_BLOCK') and \
-                    (meta_line[index][fb][2] - meta_line[index][fb][0]) < (meta_line[index-1][fb][2] - meta_line[index-1][fb][0]) * 0.7:
-                    sec[-1] += line[fc]
-                    sec[-1] += "\n\n"
-                else:
-                    sec[-1] += " "
-                    sec[-1] += line[fc]
-            else:
-                if (index+1 < len(meta_line)) and \
-                    meta_line[index][fs] > main_fsize:
-                    # 单行 + 字体大
-                    mega_sec.append(copy.deepcopy(sec))
-                    sec = []
-                    sec.append("# " + line[fc])
-                else:
-                    # 尝试识别section
-                    if meta_line[index-1][fs] > meta_line[index][fs]:
-                        sec.append("\n" + line[fc])
-                    else:
-                        sec.append(line[fc])
-        mega_sec.append(copy.deepcopy(sec))
-
-        finals = []
-        for ms in mega_sec:
-            final = " ".join(ms)
-            final = final.replace('- ', ' ')
-            finals.append(final)
-        meta_txt = finals
-
-        ############################## <第 4 步，乱七八糟的后处理> ##################################
-        def 把字符太少的块清除为回车(meta_txt):
-            for index, block_txt in enumerate(meta_txt):
-                if len(block_txt) < 100:
-                    meta_txt[index] = '\n'
-            return meta_txt
-        meta_txt = 把字符太少的块清除为回车(meta_txt)
-
-        def 清理多余的空行(meta_txt):
-            for index in reversed(range(1, len(meta_txt))):
-                if meta_txt[index] == '\n' and meta_txt[index-1] == '\n':
-                    meta_txt.pop(index)
-            return meta_txt
-        meta_txt = 清理多余的空行(meta_txt)
-
-        def 合并小写开头的段落块(meta_txt):
-            def starts_with_lowercase_word(s):
-                pattern = r"^[a-z]+"
-                match = re.match(pattern, s)
-                if match:
-                    return True
-                else:
-                    return False
-            for _ in range(100):
-                for index, block_txt in enumerate(meta_txt):
-                    if starts_with_lowercase_word(block_txt):
-                        if meta_txt[index-1] != '\n':
-                            meta_txt[index-1] += ' '
-                        else:
-                            meta_txt[index-1] = ''
-                        meta_txt[index-1] += meta_txt[index]
-                        meta_txt[index] = '\n'
-            return meta_txt
-        meta_txt = 合并小写开头的段落块(meta_txt)
-        meta_txt = 清理多余的空行(meta_txt)
-
-        meta_txt = '\n'.join(meta_txt)
-        # 清除重复的换行
-        for _ in range(5):
-            meta_txt = meta_txt.replace('\n\n', '\n')
-
-        # 换行 -> 双换行
-        meta_txt = meta_txt.replace('\n', '\n\n')
-
-        ############################## <第 5 步，展示分割效果> ##################################
-        # for f in finals:
-        #    print亮黄(f)
-        #    print亮绿('***************************')
-
-    return meta_txt, page_one_meta
-
-
-def get_files_from_everything(txt, type): # type='.md'
-    """
-    这个函数是用来获取指定目录下所有指定类型（如.md）的文件，并且对于网络上的文件，也可以获取它。
-    下面是对每个参数和返回值的说明：
-    参数 
-    - txt: 路径或网址，表示要搜索的文件或者文件夹路径或网络上的文件。 
-    - type: 字符串，表示要搜索的文件类型。默认是.md。
-    返回值 
-    - success: 布尔值，表示函数是否成功执行。 
-    - file_manifest: 文件路径列表，里面包含以指定类型为后缀名的所有文件的绝对路径。 
-    - project_folder: 字符串，表示文件所在的文件夹路径。如果是网络上的文件，就是临时文件夹的路径。
-    该函数详细注释已添加，请确认是否满足您的需要。
-    """
-    import glob, os
-
-    success = True
-    if txt.startswith('http'):
-        # 网络的远程文件
-        import requests
-        from toolbox import get_conf
-        proxies, = get_conf('proxies')
-        r = requests.get(txt, proxies=proxies)
-        with open('./gpt_log/temp'+type, 'wb+') as f: f.write(r.content)
-        project_folder = './gpt_log/'
-        file_manifest = ['./gpt_log/temp'+type]
-    elif txt.endswith(type):
-        # 直接给定文件
-        file_manifest = [txt]
-        project_folder = os.path.dirname(txt)
-    elif os.path.exists(txt):
-        # 本地路径，递归搜索
-        project_folder = txt
-        file_manifest = [f for f in glob.glob(f'{project_folder}/**/*'+type, recursive=True)]
-        if len(file_manifest) == 0:
-            success = False
-    else:
-        project_folder = None
-        file_manifest = []
-        success = False
-
-    return success, file_manifest, project_folder
-
-
-
-
-def Singleton(cls):
-    _instance = {}
- 
-    def _singleton(*args, **kargs):
-        if cls not in _instance:
-            _instance[cls] = cls(*args, **kargs)
-        return _instance[cls]
- 
-    return _singleton
-
-
-@Singleton
-class knowledge_archive_interface():
-    def __init__(self) -> None:
-        self.threadLock = threading.Lock()
-        self.current_id = ""
-        self.kai_path = None
-        self.qa_handle = None
-        self.text2vec_large_chinese = None
-
-    def get_chinese_text2vec(self):
-        if self.text2vec_large_chinese is None:
-            # < -------------------预热文本向量化模组--------------- >
-            from toolbox import ProxyNetworkActivate
-            print('Checking Text2vec ...')
-            from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-            with ProxyNetworkActivate():    # 临时地激活代理网络
-                self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
-
-        return self.text2vec_large_chinese
-
-
-    def feed_archive(self, file_manifest, id="default"):
-        self.threadLock.acquire()
-        # import uuid
-        self.current_id = id
-        from zh_langchain import construct_vector_store
-        self.qa_handle, self.kai_path = construct_vector_store(   
-            vs_id=self.current_id, 
-            files=file_manifest, 
-            sentence_size=100,
-            history=[],
-            one_conent="",
-            one_content_segmentation="",
-            text2vec = self.get_chinese_text2vec(),
-        )
-        self.threadLock.release()
-
-    def get_current_archive_id(self):
-        return self.current_id
-    
-    def get_loaded_file(self):
-        return self.qa_handle.get_loaded_file()
-
-    def answer_with_archive_by_id(self, txt, id):
-        self.threadLock.acquire()
-        if not self.current_id == id:
-            self.current_id = id
-            from zh_langchain import construct_vector_store
-            self.qa_handle, self.kai_path = construct_vector_store(   
-                vs_id=self.current_id, 
-                files=[], 
-                sentence_size=100,
-                history=[],
-                one_conent="",
-                one_content_segmentation="",
-                text2vec = self.get_chinese_text2vec(),
-            )
-        VECTOR_SEARCH_SCORE_THRESHOLD = 0
-        VECTOR_SEARCH_TOP_K = 4
-        CHUNK_SIZE = 512
-        resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
-            query = txt,
-            vs_path = self.kai_path,
-            score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
-            vector_search_top_k=VECTOR_SEARCH_TOP_K, 
-            chunk_conent=True,
-            chunk_size=CHUNK_SIZE,
-            text2vec = self.get_chinese_text2vec(),
-        )
-        self.threadLock.release()
-        return resp, prompt
-
-def try_install_deps(deps):
-    for dep in deps:
-        import subprocess, sys
-        subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--user', dep])
-
-
-class construct_html():
-    def __init__(self) -> None:
-        self.css = """
-.row {
-  display: flex;
-  flex-wrap: wrap;
-}
-
-.column {
-  flex: 1;
-  padding: 10px;
-}
-
-.table-header {
-  font-weight: bold;
-  border-bottom: 1px solid black;
-}
-
-.table-row {
-  border-bottom: 1px solid lightgray;
-}
-
-.table-cell {
-  padding: 5px;
-}
-        """
-        self.html_string = f'<!DOCTYPE html><head><meta charset="utf-8"><title>翻译结果</title><style>{self.css}</style></head>'
-
-
-    def add_row(self, a, b):
-        tmp = """
-<div class="row table-row">
-    <div class="column table-cell">REPLACE_A</div>
-    <div class="column table-cell">REPLACE_B</div>
-</div>
-        """
-        from toolbox import markdown_convertion
-        tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
-        tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
-        self.html_string += tmp
-
-
-    def save_file(self, file_name):
-        with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
-            f.write(self.html_string.encode('utf-8', 'ignore').decode())
-
diff --git a/spaces/fb700/chatglm-fitness-RLHF/src/face3d/data/base_dataset.py b/spaces/fb700/chatglm-fitness-RLHF/src/face3d/data/base_dataset.py
deleted file mode 100644
index 1bd57d082d519f512d7114b4f867b6695fb7de06..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/src/face3d/data/base_dataset.py
+++ /dev/null
@@ -1,125 +0,0 @@
-"""This module implements an abstract base class (ABC) 'BaseDataset' for datasets.
-
-It also includes common transformation functions (e.g., get_transform, __scale_width), which can be later used in subclasses.
-"""
-import random
-import numpy as np
-import torch.utils.data as data
-from PIL import Image
-import torchvision.transforms as transforms
-from abc import ABC, abstractmethod
-
-
-class BaseDataset(data.Dataset, ABC):
-    """This class is an abstract base class (ABC) for datasets.
-
-    To create a subclass, you need to implement the following four functions:
-    -- <__init__>:                      initialize the class, first call BaseDataset.__init__(self, opt).
-    -- <__len__>:                       return the size of dataset.
-    -- <__getitem__>:                   get a data point.
-    -- <modify_commandline_options>:    (optionally) add dataset-specific options and set default options.
-    """
-
-    def __init__(self, opt):
-        """Initialize the class; save the options in the class
-
-        Parameters:
-            opt (Option class)-- stores all the experiment flags; needs to be a subclass of BaseOptions
-        """
-        self.opt = opt
-        # self.root = opt.dataroot
-        self.current_epoch = 0
-
-    @staticmethod
-    def modify_commandline_options(parser, is_train):
-        """Add new dataset-specific options, and rewrite default values for existing options.
-
-        Parameters:
-            parser          -- original option parser
-            is_train (bool) -- whether training phase or test phase. You can use this flag to add training-specific or test-specific options.
-
-        Returns:
-            the modified parser.
-        """
-        return parser
-
-    @abstractmethod
-    def __len__(self):
-        """Return the total number of images in the dataset."""
-        return 0
-
-    @abstractmethod
-    def __getitem__(self, index):
-        """Return a data point and its metadata information.
-
-        Parameters:
-            index - - a random integer for data indexing
-
-        Returns:
-            a dictionary of data with their names. It ususally contains the data itself and its metadata information.
-        """
-        pass
-
-
-def get_transform(grayscale=False):
-    transform_list = []
-    if grayscale:
-        transform_list.append(transforms.Grayscale(1))
-    transform_list += [transforms.ToTensor()]
-    return transforms.Compose(transform_list)
-
-def get_affine_mat(opt, size):
-    shift_x, shift_y, scale, rot_angle, flip = 0., 0., 1., 0., False
-    w, h = size
-
-    if 'shift' in opt.preprocess:
-        shift_pixs = int(opt.shift_pixs)
-        shift_x = random.randint(-shift_pixs, shift_pixs)
-        shift_y = random.randint(-shift_pixs, shift_pixs)
-    if 'scale' in opt.preprocess:
-        scale = 1 + opt.scale_delta * (2 * random.random() - 1)
-    if 'rot' in opt.preprocess:
-        rot_angle = opt.rot_angle * (2 * random.random() - 1)
-        rot_rad = -rot_angle * np.pi/180
-    if 'flip' in opt.preprocess:
-        flip = random.random() > 0.5
-
-    shift_to_origin = np.array([1, 0, -w//2, 0, 1, -h//2, 0, 0, 1]).reshape([3, 3])
-    flip_mat = np.array([-1 if flip else 1, 0, 0, 0, 1, 0, 0, 0, 1]).reshape([3, 3])
-    shift_mat = np.array([1, 0, shift_x, 0, 1, shift_y, 0, 0, 1]).reshape([3, 3])
-    rot_mat = np.array([np.cos(rot_rad), np.sin(rot_rad), 0, -np.sin(rot_rad), np.cos(rot_rad), 0, 0, 0, 1]).reshape([3, 3])
-    scale_mat = np.array([scale, 0, 0, 0, scale, 0, 0, 0, 1]).reshape([3, 3])
-    shift_to_center = np.array([1, 0, w//2, 0, 1, h//2, 0, 0, 1]).reshape([3, 3])
-    
-    affine = shift_to_center @ scale_mat @ rot_mat @ shift_mat @ flip_mat @ shift_to_origin    
-    affine_inv = np.linalg.inv(affine)
-    return affine, affine_inv, flip
-
-def apply_img_affine(img, affine_inv, method=Image.BICUBIC):
-    return img.transform(img.size, Image.AFFINE, data=affine_inv.flatten()[:6], resample=Image.BICUBIC)
-
-def apply_lm_affine(landmark, affine, flip, size):
-    _, h = size
-    lm = landmark.copy()
-    lm[:, 1] = h - 1 - lm[:, 1]
-    lm = np.concatenate((lm, np.ones([lm.shape[0], 1])), -1)
-    lm = lm @ np.transpose(affine)
-    lm[:, :2] = lm[:, :2] / lm[:, 2:]
-    lm = lm[:, :2]
-    lm[:, 1] = h - 1 - lm[:, 1]
-    if flip:
-        lm_ = lm.copy()
-        lm_[:17] = lm[16::-1]
-        lm_[17:22] = lm[26:21:-1]
-        lm_[22:27] = lm[21:16:-1]
-        lm_[31:36] = lm[35:30:-1]
-        lm_[36:40] = lm[45:41:-1]
-        lm_[40:42] = lm[47:45:-1]
-        lm_[42:46] = lm[39:35:-1]
-        lm_[46:48] = lm[41:39:-1]
-        lm_[48:55] = lm[54:47:-1]
-        lm_[55:60] = lm[59:54:-1]
-        lm_[60:65] = lm[64:59:-1]
-        lm_[65:68] = lm[67:64:-1]
-        lm = lm_
-    return lm
diff --git a/spaces/fclong/summary/fengshen/examples/stable_diffusion_chinese/img/test.md b/spaces/fclong/summary/fengshen/examples/stable_diffusion_chinese/img/test.md
deleted file mode 100644
index c8b1b42336f7e2c26898b5b99441d324f2de5412..0000000000000000000000000000000000000000
--- a/spaces/fclong/summary/fengshen/examples/stable_diffusion_chinese/img/test.md
+++ /dev/null
@@ -1 +0,0 @@
-delete
diff --git a/spaces/fffiloni/lama-video-watermark-remover/models/ade20k/segm_lib/utils/data/sampler.py b/spaces/fffiloni/lama-video-watermark-remover/models/ade20k/segm_lib/utils/data/sampler.py
deleted file mode 100644
index 62a9a43bd1d4c21fbdcb262db7da8d4fe27b26de..0000000000000000000000000000000000000000
--- a/spaces/fffiloni/lama-video-watermark-remover/models/ade20k/segm_lib/utils/data/sampler.py
+++ /dev/null
@@ -1,131 +0,0 @@
-import torch
-
-
-class Sampler(object):
-    """Base class for all Samplers.
-
-    Every Sampler subclass has to provide an __iter__ method, providing a way
-    to iterate over indices of dataset elements, and a __len__ method that
-    returns the length of the returned iterators.
-    """
-
-    def __init__(self, data_source):
-        pass
-
-    def __iter__(self):
-        raise NotImplementedError
-
-    def __len__(self):
-        raise NotImplementedError
-
-
-class SequentialSampler(Sampler):
-    """Samples elements sequentially, always in the same order.
-
-    Arguments:
-        data_source (Dataset): dataset to sample from
-    """
-
-    def __init__(self, data_source):
-        self.data_source = data_source
-
-    def __iter__(self):
-        return iter(range(len(self.data_source)))
-
-    def __len__(self):
-        return len(self.data_source)
-
-
-class RandomSampler(Sampler):
-    """Samples elements randomly, without replacement.
-
-    Arguments:
-        data_source (Dataset): dataset to sample from
-    """
-
-    def __init__(self, data_source):
-        self.data_source = data_source
-
-    def __iter__(self):
-        return iter(torch.randperm(len(self.data_source)).long())
-
-    def __len__(self):
-        return len(self.data_source)
-
-
-class SubsetRandomSampler(Sampler):
-    """Samples elements randomly from a given list of indices, without replacement.
-
-    Arguments:
-        indices (list): a list of indices
-    """
-
-    def __init__(self, indices):
-        self.indices = indices
-
-    def __iter__(self):
-        return (self.indices[i] for i in torch.randperm(len(self.indices)))
-
-    def __len__(self):
-        return len(self.indices)
-
-
-class WeightedRandomSampler(Sampler):
-    """Samples elements from [0,..,len(weights)-1] with given probabilities (weights).
-
-    Arguments:
-        weights (list)   : a list of weights, not necessary summing up to one
-        num_samples (int): number of samples to draw
-        replacement (bool): if ``True``, samples are drawn with replacement.
-            If not, they are drawn without replacement, which means that when a
-            sample index is drawn for a row, it cannot be drawn again for that row.
-    """
-
-    def __init__(self, weights, num_samples, replacement=True):
-        self.weights = torch.DoubleTensor(weights)
-        self.num_samples = num_samples
-        self.replacement = replacement
-
-    def __iter__(self):
-        return iter(torch.multinomial(self.weights, self.num_samples, self.replacement))
-
-    def __len__(self):
-        return self.num_samples
-
-
-class BatchSampler(object):
-    """Wraps another sampler to yield a mini-batch of indices.
-
-    Args:
-        sampler (Sampler): Base sampler.
-        batch_size (int): Size of mini-batch.
-        drop_last (bool): If ``True``, the sampler will drop the last batch if
-            its size would be less than ``batch_size``
-
-    Example:
-        >>> list(BatchSampler(range(10), batch_size=3, drop_last=False))
-        [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]
-        >>> list(BatchSampler(range(10), batch_size=3, drop_last=True))
-        [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
-    """
-
-    def __init__(self, sampler, batch_size, drop_last):
-        self.sampler = sampler
-        self.batch_size = batch_size
-        self.drop_last = drop_last
-
-    def __iter__(self):
-        batch = []
-        for idx in self.sampler:
-            batch.append(idx)
-            if len(batch) == self.batch_size:
-                yield batch
-                batch = []
-        if len(batch) > 0 and not self.drop_last:
-            yield batch
-
-    def __len__(self):
-        if self.drop_last:
-            return len(self.sampler) // self.batch_size
-        else:
-            return (len(self.sampler) + self.batch_size - 1) // self.batch_size
diff --git a/spaces/firzaelbuho/rvc-models/README.md b/spaces/firzaelbuho/rvc-models/README.md
deleted file mode 100644
index 56936f1df15477c0ae2fdcfe59a77c175e1905d8..0000000000000000000000000000000000000000
--- a/spaces/firzaelbuho/rvc-models/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Rvc Models
-emoji: 🎤
-colorFrom: red
-colorTo: blue
-sdk: gradio
-sdk_version: 3.27.0
-app_file: app.py
-pinned: false
-license: mit
-duplicated_from: zomehwh/rvc-models
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/freddyaboulton/gradio-google-forms/README.md b/spaces/freddyaboulton/gradio-google-forms/README.md
deleted file mode 100644
index 57b2fcbc8ea801aaf7120f5721155af1f44a9300..0000000000000000000000000000000000000000
--- a/spaces/freddyaboulton/gradio-google-forms/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Gradio Google Forms
-emoji: 🏃
-colorFrom: indigo
-colorTo: purple
-sdk: gradio
-sdk_version: 3.4
-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/fuckyoudeki/AutoGPT/autogpt/processing/html.py b/spaces/fuckyoudeki/AutoGPT/autogpt/processing/html.py
deleted file mode 100644
index 81387b12adab5023150c55f2075ddd40b554f386..0000000000000000000000000000000000000000
--- a/spaces/fuckyoudeki/AutoGPT/autogpt/processing/html.py
+++ /dev/null
@@ -1,33 +0,0 @@
-"""HTML processing functions"""
-from __future__ import annotations
-
-from bs4 import BeautifulSoup
-from requests.compat import urljoin
-
-
-def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
-    """Extract hyperlinks from a BeautifulSoup object
-
-    Args:
-        soup (BeautifulSoup): The BeautifulSoup object
-        base_url (str): The base URL
-
-    Returns:
-        List[Tuple[str, str]]: The extracted hyperlinks
-    """
-    return [
-        (link.text, urljoin(base_url, link["href"]))
-        for link in soup.find_all("a", href=True)
-    ]
-
-
-def format_hyperlinks(hyperlinks: list[tuple[str, str]]) -> list[str]:
-    """Format hyperlinks to be displayed to the user
-
-    Args:
-        hyperlinks (List[Tuple[str, str]]): The hyperlinks to format
-
-    Returns:
-        List[str]: The formatted hyperlinks
-    """
-    return [f"{link_text} ({link_url})" for link_text, link_url in hyperlinks]
diff --git a/spaces/fun-research/FC-CLIP/fcclip/modeling/transformer_decoder/__init__.py b/spaces/fun-research/FC-CLIP/fcclip/modeling/transformer_decoder/__init__.py
deleted file mode 100644
index cf7779c65ccc73467c309979f8077c4dc9e819fc..0000000000000000000000000000000000000000
--- a/spaces/fun-research/FC-CLIP/fcclip/modeling/transformer_decoder/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from .fcclip_transformer_decoder import MultiScaleMaskedTransformerDecoder
diff --git a/spaces/furiosa-ai/ocr/index.html b/spaces/furiosa-ai/ocr/index.html
deleted file mode 100644
index 6cce5399cfb4e8ee0db902194cd10ec494b79978..0000000000000000000000000000000000000000
--- a/spaces/furiosa-ai/ocr/index.html
+++ /dev/null
@@ -1 +0,0 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Next-generation semiconductor company"/><meta property="og:image" content="./logo.png"/><meta property="og:url" content="."/><link rel="apple-touch-icon" href="./logo.png"/><link rel="manifest" href="./manifest.json"/><title>FuriosaAI OCR DEMO</title><script defer="defer" src="./static/js/main.87470711.js"></script><link href="./static/css/main.a3489ae4.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
\ No newline at end of file
diff --git a/spaces/georgefen/Face-Landmark-ControlNet/ldm/models/diffusion/sampling_util.py b/spaces/georgefen/Face-Landmark-ControlNet/ldm/models/diffusion/sampling_util.py
deleted file mode 100644
index 7eff02be6d7c54d43ee6680636ac0698dd3b3f33..0000000000000000000000000000000000000000
--- a/spaces/georgefen/Face-Landmark-ControlNet/ldm/models/diffusion/sampling_util.py
+++ /dev/null
@@ -1,22 +0,0 @@
-import torch
-import numpy as np
-
-
-def append_dims(x, target_dims):
-    """Appends dimensions to the end of a tensor until it has target_dims dimensions.
-    From https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/utils.py"""
-    dims_to_append = target_dims - x.ndim
-    if dims_to_append < 0:
-        raise ValueError(f'input has {x.ndim} dims but target_dims is {target_dims}, which is less')
-    return x[(...,) + (None,) * dims_to_append]
-
-
-def norm_thresholding(x0, value):
-    s = append_dims(x0.pow(2).flatten(1).mean(1).sqrt().clamp(min=value), x0.ndim)
-    return x0 * (value / s)
-
-
-def spatial_norm_thresholding(x0, value):
-    # b c h w
-    s = x0.pow(2).mean(1, keepdim=True).sqrt().clamp(min=value)
-    return x0 * (value / s)
\ No newline at end of file
diff --git a/spaces/gotiQspiryo/whisper-ui/examples/Ek Thi Daayan Bengali Movie Mp3 Songs Free Download Enjoy the Music of Emraan Hashmi Konkona Sen Sharma Huma Qureshi and Kalki Koechlin.md b/spaces/gotiQspiryo/whisper-ui/examples/Ek Thi Daayan Bengali Movie Mp3 Songs Free Download Enjoy the Music of Emraan Hashmi Konkona Sen Sharma Huma Qureshi and Kalki Koechlin.md
deleted file mode 100644
index 9d49c3dfc143208e326c02949705cc664608fac5..0000000000000000000000000000000000000000
--- a/spaces/gotiQspiryo/whisper-ui/examples/Ek Thi Daayan Bengali Movie Mp3 Songs Free Download Enjoy the Music of Emraan Hashmi Konkona Sen Sharma Huma Qureshi and Kalki Koechlin.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Ek Thi Daayan Bengali Movie Mp3 Songs Free Download</h2><br /><p><b><b>DOWNLOAD</b> ===== <a href="https://urlgoal.com/2uyMJY">https://urlgoal.com/2uyMJY</a></b></p><br /><br />
-<br />
- aaccfb2cb3<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/gradio/stream_frames/run.py b/spaces/gradio/stream_frames/run.py
deleted file mode 100644
index 547fc11eec2f626fd4aa0baa13189abdd951d5cc..0000000000000000000000000000000000000000
--- a/spaces/gradio/stream_frames/run.py
+++ /dev/null
@@ -1,15 +0,0 @@
-import gradio as gr
-import numpy as np
-
-def flip(im):
-    return np.flipud(im)
-
-demo = gr.Interface(
-    flip, 
-    gr.Image(sources=["webcam"], streaming=True), 
-    "image",
-    live=True
-)
-if __name__ == "__main__":
-    demo.launch()
-    
\ No newline at end of file
diff --git a/spaces/grosenthal/aineid/src/aineid/src/App.test.tsx b/spaces/grosenthal/aineid/src/aineid/src/App.test.tsx
deleted file mode 100644
index 44b1463fa5d64df19c8802756191b76cd2601e09..0000000000000000000000000000000000000000
--- a/spaces/grosenthal/aineid/src/aineid/src/App.test.tsx
+++ /dev/null
@@ -1,10 +0,0 @@
-import React from "react"
-import { screen } from "@testing-library/react"
-import { render } from "./test-utils"
-import { App } from "./App"
-
-test("renders learn react link", () => {
-  render(<App />)
-  const linkElement = screen.getByText(/learn chakra/i)
-  expect(linkElement).toBeInTheDocument()
-})
diff --git a/spaces/gyugnsu/DragGan-Inversion/PTI/configs/paths_config.py b/spaces/gyugnsu/DragGan-Inversion/PTI/configs/paths_config.py
deleted file mode 100644
index 2e1e65ddb127eec0dc0007ddc8472f4e3c51932a..0000000000000000000000000000000000000000
--- a/spaces/gyugnsu/DragGan-Inversion/PTI/configs/paths_config.py
+++ /dev/null
@@ -1,31 +0,0 @@
-## Pretrained models paths
-e4e = 'PTI/pretrained_models/e4e_ffhq_encode.pt'
-stylegan2_ada_ffhq = '../PTI/pretrained_models/ffhq.pkl'
-style_clip_pretrained_mappers = ''
-ir_se50 = 'PTI/pretrained_models/model_ir_se50.pth'
-dlib = 'PTI/pretrained_models/align.dat'
-
-## Dirs for output files
-checkpoints_dir = 'PTI/checkpoints'
-embedding_base_dir = 'PTI/embeddings'
-styleclip_output_dir = 'PTI/StyleCLIP_results'
-experiments_output_dir = 'PTI/output'
-
-## Input info
-### Input dir, where the images reside
-input_data_path = ''
-### Inversion identifier, used to keeping track of the inversion results. Both the latent code and the generator
-input_data_id = 'barcelona'
-
-## Keywords
-pti_results_keyword = 'PTI'
-e4e_results_keyword = 'e4e'
-sg2_results_keyword = 'SG2'
-sg2_plus_results_keyword = 'SG2_plus'
-multi_id_model_type = 'multi_id'
-
-## Edit directions
-interfacegan_age = 'PTI/editings/interfacegan_directions/age.pt'
-interfacegan_smile = 'PTI/editings/interfacegan_directions/smile.pt'
-interfacegan_rotation = 'PTI/editings/interfacegan_directions/rotation.pt'
-ffhq_pca = 'PTI/editings/ganspace_pca/ffhq_pca.pt'
diff --git a/spaces/gyugnsu/DragGan-Inversion/PTI/models/StyleCLIP/mapper/styleclip_mapper.py b/spaces/gyugnsu/DragGan-Inversion/PTI/models/StyleCLIP/mapper/styleclip_mapper.py
deleted file mode 100644
index 86c04bee5744a551f4c0d31359e0de1f5492ff7e..0000000000000000000000000000000000000000
--- a/spaces/gyugnsu/DragGan-Inversion/PTI/models/StyleCLIP/mapper/styleclip_mapper.py
+++ /dev/null
@@ -1,76 +0,0 @@
-import torch
-from torch import nn
-from models.StyleCLIP.mapper import latent_mappers
-from models.StyleCLIP.models.stylegan2.model import Generator
-
-
-def get_keys(d, name):
-    if 'state_dict' in d:
-        d = d['state_dict']
-    d_filt = {k[len(name) + 1:]: v for k, v in d.items() if k[:len(name)] == name}
-    return d_filt
-
-
-class StyleCLIPMapper(nn.Module):
-
-    def __init__(self, opts, run_id):
-        super(StyleCLIPMapper, self).__init__()
-        self.opts = opts
-        # Define architecture
-        self.mapper = self.set_mapper()
-        self.run_id = run_id
-
-        self.face_pool = torch.nn.AdaptiveAvgPool2d((256, 256))
-        # Load weights if needed
-        self.load_weights()
-
-    def set_mapper(self):
-        if self.opts.mapper_type == 'SingleMapper':
-            mapper = latent_mappers.SingleMapper(self.opts)
-        elif self.opts.mapper_type == 'LevelsMapper':
-            mapper = latent_mappers.LevelsMapper(self.opts)
-        else:
-            raise Exception('{} is not a valid mapper'.format(self.opts.mapper_type))
-        return mapper
-
-    def load_weights(self):
-        if self.opts.checkpoint_path is not None:
-            print('Loading from checkpoint: {}'.format(self.opts.checkpoint_path))
-            ckpt = torch.load(self.opts.checkpoint_path, map_location='cpu')
-            self.mapper.load_state_dict(get_keys(ckpt, 'mapper'), strict=True)
-
-    def set_G(self, new_G):
-        self.decoder = new_G
-
-    def forward(self, x, resize=True, latent_mask=None, input_code=False, randomize_noise=True,
-                inject_latent=None, return_latents=False, alpha=None):
-        if input_code:
-            codes = x
-        else:
-            codes = self.mapper(x)
-
-        if latent_mask is not None:
-            for i in latent_mask:
-                if inject_latent is not None:
-                    if alpha is not None:
-                        codes[:, i] = alpha * inject_latent[:, i] + (1 - alpha) * codes[:, i]
-                    else:
-                        codes[:, i] = inject_latent[:, i]
-                else:
-                    codes[:, i] = 0
-
-        input_is_latent = not input_code
-        images = self.decoder.synthesis(codes, noise_mode='const')
-        result_latent = None
-        # images, result_latent = self.decoder([codes],
-        #                                      input_is_latent=input_is_latent,
-        #                                      randomize_noise=randomize_noise,
-        #                                      return_latents=return_latents)
-
-        if resize:
-            images = self.face_pool(images)
-
-        if return_latents:
-            return images, result_latent
-        else:
-            return images
diff --git a/spaces/gyugnsu/DragGan-Inversion/visualizer_drag_gradio_inversion.py b/spaces/gyugnsu/DragGan-Inversion/visualizer_drag_gradio_inversion.py
deleted file mode 100644
index 556ced293e772c665dba71d049b8d31142c1e3f2..0000000000000000000000000000000000000000
--- a/spaces/gyugnsu/DragGan-Inversion/visualizer_drag_gradio_inversion.py
+++ /dev/null
@@ -1,1002 +0,0 @@
-# https://huggingface.co/DragGan/DragGan-Models
-# https://arxiv.org/abs/2305.10973
-import os
-import os.path as osp
-from argparse import ArgumentParser
-from functools import partial
-from pathlib import Path
-import time
-import tempfile
-import psutil
-
-import gradio as gr
-import numpy as np
-import torch
-from PIL import Image
-import uuid
-
-import dnnlib
-from gradio_utils import (
-    ImageMask,
-    draw_mask_on_image,
-    draw_points_on_image,
-    get_latest_points_pair,
-    get_valid_mask,
-    on_change_single_global_state,
-)
-from viz.renderer import Renderer, add_watermark_np
-from torch_utils.pti import run_PTI, export_updated_pickle
-
-# download models from Hugging Face hub
-from huggingface_hub import snapshot_download
-
-model_dir = Path("./checkpoints")
-snapshot_download("DragGan/DragGan-Models", repo_type="model", local_dir=model_dir)
-
-# parser = ArgumentParser()
-# parser.add_argument('--share', action='store_true')
-# parser.add_argument('--cache-dir', type=str, default='./checkpoints')
-# args = parser.parse_args()
-
-cache_dir = model_dir
-
-device = "cuda"
-IS_SPACE = "DragGan/DragGan" in os.environ.get("SPACE_ID", "")
-TIMEOUT = 80
-
-
-def reverse_point_pairs(points):
-    new_points = []
-    for p in points:
-        new_points.append([p[1], p[0]])
-    return new_points
-
-
-def clear_state(global_state, target=None):
-    """Clear target history state from global_state
-    If target is not defined, points and mask will be both removed.
-    1. set global_state['points'] as empty dict
-    2. set global_state['mask'] as full-one mask.
-    """
-    if target is None:
-        target = ["point", "mask"]
-    if not isinstance(target, list):
-        target = [target]
-    if "point" in target:
-        global_state["points"] = dict()
-        print("Clear Points State!")
-    if "mask" in target:
-        image_raw = global_state["images"]["image_raw"]
-        global_state["mask"] = np.ones(
-            (image_raw.size[1], image_raw.size[0]), dtype=np.uint8
-        )
-        print("Clear mask State!")
-
-    return global_state
-
-
-def init_images(global_state):
-    """This function is called only ones with Gradio App is started.
-    0. pre-process global_state, unpack value from global_state of need
-    1. Re-init renderer
-    2. run `renderer._render_drag_impl` with `is_drag=False` to generate
-       new image
-    3. Assign images to global state and re-generate mask
-    """
-
-    if isinstance(global_state, gr.State):
-        state = global_state.value
-    else:
-        state = global_state
-
-    state["renderer"].init_network(
-        state["generator_params"],  # res
-        state["pretrained_weight"],  # pkl
-        state["params"]["seed"],  # w0_seed,
-        state["w_pivot"],  # w_load
-        state["params"]["latent_space"] == "w+",  # w_plus
-        "const",
-        state["params"]["trunc_psi"],  # trunc_psi,
-        state["params"]["trunc_cutoff"],  # trunc_cutoff,
-        None,  # input_transform
-        state["params"]["lr"],  # lr,
-    )
-
-    state["renderer"]._render_drag_impl(
-        state["generator_params"], is_drag=False, to_pil=True
-    )
-
-    init_image = state["generator_params"].image
-    state["images"]["image_orig"] = init_image
-    state["images"]["image_raw"] = init_image
-    state["images"]["image_show"] = Image.fromarray(
-        add_watermark_np(np.array(init_image))
-    )
-    state["mask"] = np.ones((init_image.size[1], init_image.size[0]), dtype=np.uint8)
-    return global_state
-
-
-def update_image_draw(image, points, mask, show_mask, global_state=None):
-    image_draw = draw_points_on_image(image, points)
-    if (
-        show_mask
-        and mask is not None
-        and not (mask == 0).all()
-        and not (mask == 1).all()
-    ):
-        image_draw = draw_mask_on_image(image_draw, mask)
-
-    image_draw = Image.fromarray(add_watermark_np(np.array(image_draw)))
-    if global_state is not None:
-        global_state["images"]["image_show"] = image_draw
-    return image_draw
-
-
-def preprocess_mask_info(global_state, image):
-    """Function to handle mask information.
-    1. last_mask is None: Do not need to change mask, return mask
-    2. last_mask is not None:
-        2.1 global_state is remove_mask:
-        2.2 global_state is add_mask:
-    """
-    if isinstance(image, dict):
-        last_mask = get_valid_mask(image["mask"])
-    else:
-        last_mask = None
-    mask = global_state["mask"]
-
-    # mask in global state is a placeholder with all 1.
-    if (mask == 1).all():
-        mask = last_mask
-
-    # last_mask = global_state['last_mask']
-    editing_mode = global_state["editing_state"]
-
-    if last_mask is None:
-        return global_state
-
-    if editing_mode == "remove_mask":
-        updated_mask = np.clip(mask - last_mask, 0, 1)
-        print(f"Last editing_state is {editing_mode}, do remove.")
-    elif editing_mode == "add_mask":
-        updated_mask = np.clip(mask + last_mask, 0, 1)
-        print(f"Last editing_state is {editing_mode}, do add.")
-    else:
-        updated_mask = mask
-        print(f"Last editing_state is {editing_mode}, " "do nothing to mask.")
-
-    global_state["mask"] = updated_mask
-    # global_state['last_mask'] = None  # clear buffer
-    return global_state
-
-
-def print_memory_usage():
-    # Print system memory usage
-    print(f"System memory usage: {psutil.virtual_memory().percent}%")
-
-    # Print GPU memory usage
-    if torch.cuda.is_available():
-        device = torch.device("cuda")
-        print(f"GPU memory usage: {torch.cuda.memory_allocated() / 1e9} GB")
-        print(f"Max GPU memory usage: {torch.cuda.max_memory_allocated() / 1e9} GB")
-        device_properties = torch.cuda.get_device_properties(device)
-        available_memory = (
-            device_properties.total_memory - torch.cuda.max_memory_allocated()
-        )
-        print(f"Available GPU memory: {available_memory / 1e9} GB")
-    else:
-        print("No GPU available")
-
-
-# filter large models running on SPAC
-
-css = """
-#output-image {
-    width: 100% !important;
-    aspect-ratio: 1 / 1 !important;
-    height: auto !important;
-}
-#output-image canvas {
-    width: 100% !important;
-    aspect-ratio: 1 / 1 !important;
-    height: auto !important;
-}
-"""
-with gr.Blocks(css=css) as app:
-    gr.Markdown(
-        """
-# DragGAN - Drag Your GAN - Face Inversion
-                
-## Interactive Point-based Manipulation on the Generative Image Manifold
-### Unofficial Gradio Demo
-
-**Due to high demand, only one model can be run at a time, or you can duplicate the space and run your own copy.**
-
-<a href="https://huggingface.co/spaces/DragGan/DragGan-Inversion?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 no queue on your own hardware.</p>
-
-* Official Repo: [XingangPan](https://github.com/XingangPan/DragGAN)
-* Gradio Demo by: [LeoXing1996](https://github.com/LeoXing1996) © [OpenMMLab MMagic](https://github.com/open-mmlab/mmagic)
-* Inversion Code: [ProgrammingHut](https://www.youtube.com/watch?v=viWiOC1Mikw), [EthanZhangCN](https://github.com/EthanZhangCN) 
-"""
-    )
-
-    # renderer = Renderer()
-    global_state = gr.State(
-        {
-            "images": {
-                # image_orig: the original image, change with seed/model is changed
-                # image_raw: image with mask and points, change durning optimization
-                # image_show: image showed on screen
-            },
-            "temporal_params": {
-                # stop
-            },
-            "w_pivot": None,
-            "mask": None,  # mask for visualization, 1 for editing and 0 for unchange
-            "last_mask": None,  # last edited mask
-            "show_mask": True,  # add button
-            "generator_params": dnnlib.EasyDict(),
-            "params": {
-                "seed": int(np.random.randint(0, 2**32 - 1)),
-                "motion_lambda": 20,
-                "r1_in_pixels": 3,
-                "r2_in_pixels": 12,
-                "magnitude_direction_in_pixels": 1.0,
-                "latent_space": "w+",
-                "trunc_psi": 0.7,
-                "trunc_cutoff": None,
-                "lr": 0.01,
-            },
-            "device": device,
-            "draw_interval": 1,
-            "renderer": Renderer(disable_timing=True),
-            "points": {},
-            "curr_point": None,
-            "curr_type_point": "start",
-            "editing_state": "add_points",
-            "pretrained_weight": str(model_dir / "stylegan2-ffhq1024x1024.pkl"),
-        }
-    )
-
-    # init image
-    global_state = init_images(global_state)
-    with gr.Row():
-        with gr.Row():
-            # Left --> tools
-            with gr.Column():
-                # Latent
-                with gr.Row():
-                    with gr.Column(scale=1, min_width=10):
-                        gr.Markdown(value="Latent", show_label=False)
-
-                    with gr.Column(scale=4, min_width=10):
-                        form_seed_number = gr.Slider(
-                            mininium=0,
-                            maximum=2**32 - 1,
-                            step=1,
-                            value=global_state.value["params"]["seed"],
-                            interactive=True,
-                            # randomize=True,
-                            label="Seed",
-                        )
-                        form_lr_number = gr.Number(
-                            value=global_state.value["params"]["lr"],
-                            precision=5,
-                            interactive=True,
-                            label="Step Size",
-                        )
-
-                        with gr.Row():
-                            with gr.Column(scale=2, min_width=10):
-                                form_reset_image = gr.Button("Reset Image")
-                            with gr.Column(scale=3, min_width=10):
-                                form_latent_space = gr.Radio(
-                                    ["w", "w+"],
-                                    value=global_state.value["params"]["latent_space"],
-                                    interactive=True,
-                                    label="Latent space to optimize",
-                                    show_label=False,
-                                )
-                        with gr.Row():
-                            with gr.Column(scale=3, min_width=10):
-                                form_custom_image = gr.Image(
-                                    type="filepath", label="Custom Image", height=100
-                                )
-                            with gr.Column(scale=3, min_width=10):
-                                form_reset_custom_image = gr.Button(
-                                    "Remove Custom Image", interactive=False
-                                )
-
-                # Drag
-                with gr.Row():
-                    with gr.Column(scale=1, min_width=10):
-                        gr.Markdown(value="Drag", show_label=False)
-                    with gr.Column(scale=4, min_width=10):
-                        with gr.Row():
-                            with gr.Column(scale=1, min_width=10):
-                                enable_add_points = gr.Button("Add Points")
-                            with gr.Column(scale=1, min_width=10):
-                                undo_points = gr.Button("Reset Points")
-                        with gr.Row():
-                            with gr.Column(scale=1, min_width=10):
-                                form_start_btn = gr.Button("Start")
-                            with gr.Column(scale=1, min_width=10):
-                                form_stop_btn = gr.Button("Stop")
-
-                        form_steps_number = gr.Number(
-                            value=0, label="Steps", interactive=False
-                        )
-
-                # Mask
-                with gr.Row():
-                    with gr.Column(scale=1, min_width=10):
-                        gr.Markdown(value="Mask", show_label=False)
-                    with gr.Column(scale=4, min_width=10):
-                        enable_add_mask = gr.Button("Edit Flexible Area")
-                        with gr.Row():
-                            with gr.Column(scale=1, min_width=10):
-                                form_reset_mask_btn = gr.Button("Reset mask")
-                            with gr.Column(scale=1, min_width=10):
-                                show_mask = gr.Checkbox(
-                                    label="Show Mask",
-                                    value=global_state.value["show_mask"],
-                                    show_label=False,
-                                )
-
-                        with gr.Row():
-                            form_lambda_number = gr.Number(
-                                value=global_state.value["params"]["motion_lambda"],
-                                interactive=True,
-                                label="Lambda",
-                            )
-
-                form_draw_interval_number = gr.Number(
-                    value=global_state.value["draw_interval"],
-                    label="Draw Interval (steps)",
-                    interactive=True,
-                    visible=False,
-                )
-
-            # Right --> Image
-            with gr.Column(scale=2):
-                form_image = ImageMask(
-                    value=global_state.value["images"]["image_show"],
-                    brush_radius=100,
-                    elem_id="output-image",
-                )
-    gr.Markdown(
-        """
-        ## Quick Start
-
-        1. Select desired `Pretrained Model` and adjust `Seed` to generate an
-           initial image.
-        2. Click on image to add control points.
-        3. Click `Start` and enjoy it!
-
-        ## Advance Usage
-
-        1. Change `Step Size` to adjust learning rate in drag optimization.
-        2. Select `w` or `w+` to change latent space to optimize:
-        * Optimize on `w` space may cause greater influence to the image.
-        * Optimize on `w+` space may work slower than `w`, but usually achieve
-          better results.
-        * Note that changing the latent space will reset the image, points and
-          mask (this has the same effect as `Reset Image` button).
-        3. Click `Edit Flexible Area` to create a mask and constrain the
-           unmasked region to remain unchanged.
-
-        
-        """
-    )
-    gr.HTML(
-        """
-        <style>
-            .container {
-                position: absolute;
-                height: 50px;
-                text-align: center;
-                line-height: 50px;
-                width: 100%;
-            }
-        </style>
-        <div class="container">
-        Gradio demo supported by
-        <img src="https://avatars.githubusercontent.com/u/10245193?s=200&v=4" height="20" width="20" style="display:inline;">
-        <a href="https://github.com/open-mmlab/mmagic">OpenMMLab MMagic</a>
-        </div>
-        """
-    )
-    # Network & latents tab listeners
-
-    def on_click_reset_image(global_state):
-        """Reset image to the original one and clear all states
-        1. Re-init images
-        2. Clear all states
-        """
-
-        init_images(global_state)
-        clear_state(global_state)
-
-        return global_state, global_state["images"]["image_show"]
-
-    def on_click_reset_custom_image(global_state):
-        """Reset image to the original one and clear all states
-        1. Re-init images
-        2. Clear all states
-        """
-        Path(global_state["pretrained_weight"]).unlink(missing_ok=True)
-        global_state["w_pivot"] = None
-        global_state["pretrained_weight"] = str(
-            model_dir / "stylegan2-ffhq1024x1024.pkl"
-        )
-
-        init_images(global_state)
-        clear_state(global_state)
-
-        return global_state, global_state["images"]["image_show"]
-
-    def on_image_change(
-        custom_image, global_state, progress=gr.Progress(track_tqdm=True)
-    ):
-        new_img = Image.open(custom_image)
-        new_img = new_img.convert("RGB")
-        from PTI.configs import paths_config
-
-        paths_config.stylegan2_ada_ffhq = global_state["pretrained_weight"]
-        paths_config.dlib = (model_dir / "align.dat").as_posix()
-        run_name = str(uuid.uuid4())
-        new_G, w_pivot = run_PTI(new_img, run_name)
-
-        out_path = Path(f"checkpoints/stylegan2-{run_name}.pkl")
-        print(f"Exporting to {out_path}")
-        export_updated_pickle(new_G, out_path, run_name)
-        global_state["w_pivot"] = w_pivot
-        global_state["pretrained_weight"] = str(out_path)
-        init_images(global_state)
-        clear_state(global_state)
-
-        return (
-            global_state,
-            global_state["images"]["image_show"],
-            gr.Image.update(interactive=True),
-        )
-
-    form_custom_image.upload(
-        on_image_change,
-        [form_custom_image, global_state],
-        [global_state, form_image, form_reset_custom_image],
-    )
-
-    form_reset_custom_image.click(
-        on_click_reset_custom_image, [global_state], [global_state, form_image]
-    )
-
-    form_reset_image.click(
-        on_click_reset_image,
-        inputs=[global_state],
-        outputs=[global_state, form_image],
-        queue=False,
-        show_progress=True,
-    )
-
-    # Update parameters
-    def on_change_update_image_seed(seed, global_state):
-        """Function to handle generation seed change.
-        1. Set seed to global_state
-        2. Re-init images and clear all states
-        """
-
-        global_state["params"]["seed"] = int(seed)
-        init_images(global_state)
-        clear_state(global_state)
-
-        return global_state, global_state["images"]["image_show"]
-
-    form_seed_number.change(
-        on_change_update_image_seed,
-        inputs=[form_seed_number, global_state],
-        outputs=[global_state, form_image],
-    )
-
-    def on_click_latent_space(latent_space, global_state):
-        """Function to reset latent space to optimize.
-        NOTE: this function we reset the image and all controls
-        1. Set latent-space to global_state
-        2. Re-init images and clear all state
-        """
-
-        global_state["params"]["latent_space"] = latent_space
-        init_images(global_state)
-        clear_state(global_state)
-
-        return global_state, global_state["images"]["image_show"]
-
-    form_latent_space.change(
-        on_click_latent_space,
-        inputs=[form_latent_space, global_state],
-        outputs=[global_state, form_image],
-    )
-
-    # ==== Params
-    form_lambda_number.change(
-        partial(on_change_single_global_state, ["params", "motion_lambda"]),
-        inputs=[form_lambda_number, global_state],
-        outputs=[global_state],
-    )
-
-    def on_change_lr(lr, global_state):
-        if lr == 0:
-            print("lr is 0, do nothing.")
-            return global_state
-        else:
-            global_state["params"]["lr"] = lr
-            renderer = global_state["renderer"]
-            renderer.update_lr(lr)
-            print("New optimizer: ")
-            print(renderer.w_optim)
-        return global_state
-
-    form_lr_number.change(
-        on_change_lr,
-        inputs=[form_lr_number, global_state],
-        outputs=[global_state],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_start(global_state, image):
-        p_in_pixels = []
-        t_in_pixels = []
-        valid_points = []
-
-        # handle of start drag in mask editing mode
-        global_state = preprocess_mask_info(global_state, image)
-
-        # Prepare the points for the inference
-        if len(global_state["points"]) == 0:
-            # yield on_click_start_wo_points(global_state, image)
-            image_raw = global_state["images"]["image_raw"]
-            update_image_draw(
-                image_raw,
-                global_state["points"],
-                global_state["mask"],
-                global_state["show_mask"],
-                global_state,
-            )
-
-            yield (
-                global_state,  # global_state
-                0,  # form_steps_number,
-                global_state["images"]["image_show"],  # form image
-                gr.Button.update(interactive=True),  # form_reset_image
-                gr.Button.update(interactive=True),  # add points button
-                gr.Button.update(interactive=True),  # enable mask button
-                gr.Button.update(interactive=True),  # undo points button
-                gr.Button.update(interactive=True),  # reset mask button
-                gr.Radio.update(interactive=True),  # latent space
-                gr.Button.update(interactive=True),  # start button
-                gr.Button.update(interactive=False),  # stop button
-                gr.Number.update(interactive=True),  # form_seed_number
-                gr.Number.update(interactive=True),  # form_lr_number
-                gr.Checkbox.update(interactive=True),  # show_mask
-                gr.Number.update(interactive=True),  # form_lambda_number
-                gr.Button.update(interactive=True),  # form_reset_custom_image
-            )
-        else:
-            # Transform the points into torch tensors
-            for key_point, point in global_state["points"].items():
-                try:
-                    p_start = point.get("start_temp", point["start"])
-                    p_end = point["target"]
-
-                    if p_start is None or p_end is None:
-                        continue
-
-                except KeyError:
-                    continue
-
-                p_in_pixels.append(p_start)
-                t_in_pixels.append(p_end)
-                valid_points.append(key_point)
-
-            mask = torch.tensor(global_state["mask"]).float()
-            drag_mask = 1 - mask
-
-            renderer: Renderer = global_state["renderer"]
-            global_state["temporal_params"]["stop"] = False
-            global_state["editing_state"] = "running"
-
-            # reverse points order
-            p_to_opt = reverse_point_pairs(p_in_pixels)
-            t_to_opt = reverse_point_pairs(t_in_pixels)
-            print("Running with:")
-            print(f"    Source: {p_in_pixels}")
-            print(f"    Target: {t_in_pixels}")
-            step_idx = 0
-            last_time = time.time()
-            while True:
-                print_memory_usage()
-                # add a TIMEOUT break
-                print(f"Running time: {time.time() - last_time}")
-                if IS_SPACE and time.time() - last_time > TIMEOUT:
-                    print("Timeout break!")
-                    break
-                if (
-                    global_state["temporal_params"]["stop"]
-                    or global_state["generator_params"]["stop"]
-                ):
-                    break
-
-                # do drage here!
-                renderer._render_drag_impl(
-                    global_state["generator_params"],
-                    p_to_opt,  # point
-                    t_to_opt,  # target
-                    drag_mask,  # mask,
-                    global_state["params"]["motion_lambda"],  # lambda_mask
-                    reg=0,
-                    feature_idx=5,  # NOTE: do not support change for now
-                    r1=global_state["params"]["r1_in_pixels"],  # r1
-                    r2=global_state["params"]["r2_in_pixels"],  # r2
-                    # random_seed     = 0,
-                    # noise_mode      = 'const',
-                    trunc_psi=global_state["params"]["trunc_psi"],
-                    # force_fp32      = False,
-                    # layer_name      = None,
-                    # sel_channels    = 3,
-                    # base_channel    = 0,
-                    # img_scale_db    = 0,
-                    # img_normalize   = False,
-                    # untransform     = False,
-                    is_drag=True,
-                    to_pil=True,
-                )
-
-                if step_idx % global_state["draw_interval"] == 0:
-                    print("Current Source:")
-                    for key_point, p_i, t_i in zip(valid_points, p_to_opt, t_to_opt):
-                        global_state["points"][key_point]["start_temp"] = [
-                            p_i[1],
-                            p_i[0],
-                        ]
-                        global_state["points"][key_point]["target"] = [
-                            t_i[1],
-                            t_i[0],
-                        ]
-                        start_temp = global_state["points"][key_point]["start_temp"]
-                        print(f"    {start_temp}")
-
-                    image_result = global_state["generator_params"]["image"]
-                    image_draw = update_image_draw(
-                        image_result,
-                        global_state["points"],
-                        global_state["mask"],
-                        global_state["show_mask"],
-                        global_state,
-                    )
-                    global_state["images"]["image_raw"] = image_result
-
-                yield (
-                    global_state,  # global_state
-                    step_idx,  # form_steps_number,
-                    global_state["images"]["image_show"],  # form image
-                    # gr.File.update(visible=False),
-                    gr.Button.update(interactive=False),  # form_reset_image
-                    gr.Button.update(interactive=False),  # add points button
-                    gr.Button.update(interactive=False),  # enable mask button
-                    gr.Button.update(interactive=False),  # undo points button
-                    gr.Button.update(interactive=False),  # reset mask button
-                    # latent space
-                    gr.Radio.update(interactive=False),  # latent space
-                    gr.Button.update(interactive=False),  # start button
-                    # enable stop button in loop
-                    gr.Button.update(interactive=True),  # stop button
-                    # update other comps
-                    gr.Number.update(interactive=False),  # form_seed_number
-                    gr.Number.update(interactive=False),  # form_lr_number
-                    gr.Checkbox.update(interactive=False),  # show_mask
-                    gr.Number.update(interactive=False),  # form_lambda_number
-                    gr.Button.update(interactive=False),  # form_reset_custom_image
-                )
-
-                # increate step
-                step_idx += 1
-
-            image_result = global_state["generator_params"]["image"]
-            global_state["images"]["image_raw"] = image_result
-            image_draw = update_image_draw(
-                image_result,
-                global_state["points"],
-                global_state["mask"],
-                global_state["show_mask"],
-                global_state,
-            )
-
-            # fp = NamedTemporaryFile(suffix=".png", delete=False)
-            # image_result.save(fp, "PNG")
-
-            global_state["editing_state"] = "add_points"
-
-            yield (
-                global_state,  # global_state
-                0,  # reset step to 0 after stop. # form_steps_number,
-                global_state["images"]["image_show"],  # form image
-                gr.Button.update(interactive=True),  # form_reset_image
-                gr.Button.update(interactive=True),  # add points button
-                gr.Button.update(interactive=True),  # enable mask button
-                gr.Button.update(interactive=True),  # undo points button
-                gr.Button.update(interactive=True),  # reset mask button
-                gr.Radio.update(interactive=True),  # latent space
-                gr.Button.update(interactive=True),  # start button
-                gr.Button.update(interactive=False),  # stop button
-                gr.Number.update(interactive=True),  # form_seed_number
-                gr.Number.update(interactive=True),  # form_lr_number
-                gr.Checkbox.update(interactive=True),  # show_mask
-                gr.Number.update(interactive=True),  # form_lambda_number
-                gr.Button.update(interactive=True),  # form_reset_custom_image
-            )
-
-    form_start_btn.click(
-        on_click_start,
-        inputs=[global_state, form_image],
-        outputs=[
-            global_state,
-            form_steps_number,
-            form_image,
-            # form_download_result_file,
-            # >>> buttons
-            form_reset_image,
-            enable_add_points,
-            enable_add_mask,
-            undo_points,
-            form_reset_mask_btn,
-            form_latent_space,
-            form_start_btn,
-            form_stop_btn,
-            # <<< buttonm
-            # >>> inputs comps
-            form_seed_number,
-            form_lr_number,
-            show_mask,
-            form_lambda_number,
-            form_reset_custom_image,
-        ],
-    )
-
-    def on_click_stop(global_state):
-        """Function to handle stop button is clicked.
-        1. send a stop signal by set global_state["temporal_params"]["stop"] as True
-        2. Disable Stop button
-        """
-        global_state["temporal_params"]["stop"] = True
-
-        return global_state, gr.Button.update(interactive=False)
-
-    form_stop_btn.click(
-        on_click_stop,
-        inputs=[global_state],
-        outputs=[global_state, form_stop_btn],
-        queue=False,
-        show_progress=True,
-    )
-
-    form_draw_interval_number.change(
-        partial(
-            on_change_single_global_state,
-            "draw_interval",
-            map_transform=lambda x: int(x),
-        ),
-        inputs=[form_draw_interval_number, global_state],
-        outputs=[global_state],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_remove_point(global_state):
-        choice = global_state["curr_point"]
-        del global_state["points"][choice]
-
-        choices = list(global_state["points"].keys())
-
-        if len(choices) > 0:
-            global_state["curr_point"] = choices[0]
-
-        return (
-            gr.Dropdown.update(choices=choices, value=choices[0]),
-            global_state,
-        )
-
-    # Mask
-    def on_click_reset_mask(global_state):
-        global_state["mask"] = np.ones(
-            (
-                global_state["images"]["image_raw"].size[1],
-                global_state["images"]["image_raw"].size[0],
-            ),
-            dtype=np.uint8,
-        )
-        image_draw = update_image_draw(
-            global_state["images"]["image_raw"],
-            global_state["points"],
-            global_state["mask"],
-            global_state["show_mask"],
-            global_state,
-        )
-        return global_state, gr.Image.update(value=image_draw, interactive=False)
-
-    form_reset_mask_btn.click(
-        on_click_reset_mask,
-        inputs=[global_state],
-        outputs=[global_state, form_image],
-    )
-
-    # Image
-    def on_click_enable_draw(global_state, image):
-        """Function to start add mask mode.
-        1. Preprocess mask info from last state
-        2. Change editing state to add_mask
-        3. Set curr image with points and mask
-        """
-        global_state = preprocess_mask_info(global_state, image)
-        global_state["editing_state"] = "add_mask"
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw, global_state["points"], global_state["mask"], True, global_state
-        )
-        return (
-            global_state,
-            gr.Image.update(value=image_draw, interactive=True),
-        )
-
-    def on_click_remove_draw(global_state, image):
-        """Function to start remove mask mode.
-        1. Preprocess mask info from last state
-        2. Change editing state to remove_mask
-        3. Set curr image with points and mask
-        """
-        global_state = preprocess_mask_info(global_state, image)
-        global_state["edinting_state"] = "remove_mask"
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw, global_state["points"], global_state["mask"], True, global_state
-        )
-        return (
-            global_state,
-            gr.Image.update(value=image_draw, interactive=True),
-        )
-
-    enable_add_mask.click(
-        on_click_enable_draw,
-        inputs=[global_state, form_image],
-        outputs=[
-            global_state,
-            form_image,
-        ],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_add_point(global_state, image: dict):
-        """Function switch from add mask mode to add points mode.
-        1. Updaste mask buffer if need
-        2. Change global_state['editing_state'] to 'add_points'
-        3. Set current image with mask
-        """
-
-        global_state = preprocess_mask_info(global_state, image)
-        global_state["editing_state"] = "add_points"
-        mask = global_state["mask"]
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw,
-            global_state["points"],
-            mask,
-            global_state["show_mask"],
-            global_state,
-        )
-
-        return (
-            global_state,
-            gr.Image.update(value=image_draw, interactive=False),
-        )
-
-    enable_add_points.click(
-        on_click_add_point,
-        inputs=[global_state, form_image],
-        outputs=[global_state, form_image],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_image(global_state, evt: gr.SelectData):
-        """This function only support click for point selection"""
-        xy = evt.index
-        if global_state["editing_state"] != "add_points":
-            print(f'In {global_state["editing_state"]} state. ' "Do not add points.")
-
-            return global_state, global_state["images"]["image_show"]
-
-        points = global_state["points"]
-
-        point_idx = get_latest_points_pair(points)
-        if point_idx is None:
-            points[0] = {"start": xy, "target": None}
-            print(f"Click Image - Start - {xy}")
-        elif points[point_idx].get("target", None) is None:
-            points[point_idx]["target"] = xy
-            print(f"Click Image - Target - {xy}")
-        else:
-            points[point_idx + 1] = {"start": xy, "target": None}
-            print(f"Click Image - Start - {xy}")
-
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw,
-            global_state["points"],
-            global_state["mask"],
-            global_state["show_mask"],
-            global_state,
-        )
-
-        return global_state, image_draw
-
-    form_image.select(
-        on_click_image,
-        inputs=[global_state],
-        outputs=[global_state, form_image],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_clear_points(global_state):
-        """Function to handle clear all control points
-        1. clear global_state['points'] (clear_state)
-        2. re-init network
-        2. re-draw image
-        """
-        clear_state(global_state, target="point")
-
-        renderer: Renderer = global_state["renderer"]
-        renderer.feat_refs = None
-
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw, {}, global_state["mask"], global_state["show_mask"], global_state
-        )
-        return global_state, image_draw
-
-    undo_points.click(
-        on_click_clear_points,
-        inputs=[global_state],
-        outputs=[global_state, form_image],
-        queue=False,
-        show_progress=True,
-    )
-
-    def on_click_show_mask(global_state, show_mask):
-        """Function to control whether show mask on image."""
-        global_state["show_mask"] = show_mask
-
-        image_raw = global_state["images"]["image_raw"]
-        image_draw = update_image_draw(
-            image_raw,
-            global_state["points"],
-            global_state["mask"],
-            global_state["show_mask"],
-            global_state,
-        )
-        return global_state, image_draw
-
-    show_mask.change(
-        on_click_show_mask,
-        inputs=[global_state, show_mask],
-        outputs=[global_state, form_image],
-        queue=False,
-        show_progress=True,
-    )
-
-# print("SHAReD: Start app", parser.parse_args())
-gr.close_all()
-app.queue(concurrency_count=1, max_size=200, api_open=False)
-app.launch(show_api=False)
diff --git a/spaces/hamacojr/SAM-CAT-Seg/cat_seg/modeling/__init__.py b/spaces/hamacojr/SAM-CAT-Seg/cat_seg/modeling/__init__.py
deleted file mode 100644
index b788ab8d314e5401c06df8cfc405f0571801487f..0000000000000000000000000000000000000000
--- a/spaces/hamacojr/SAM-CAT-Seg/cat_seg/modeling/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from .backbone.swin import D2SwinTransformer
-from .heads.cat_seg_head import CATSegHead
\ No newline at end of file
diff --git a/spaces/hands012/gpt-academic/docs/waifu_plugin/jquery.min.js b/spaces/hands012/gpt-academic/docs/waifu_plugin/jquery.min.js
deleted file mode 100644
index ab28a24729b320bffd3d2f60302af949db39ab85..0000000000000000000000000000000000000000
--- a/spaces/hands012/gpt-academic/docs/waifu_plugin/jquery.min.js
+++ /dev/null
@@ -1,4 +0,0 @@
-/*! jQuery v1.11.1 | (c) 2005, 2014 jQuery Foundation, Inc. | jquery.org/license */
-!function(a,b){"object"==typeof module&&"object"==typeof module.exports?module.exports=a.document?b(a,!0):function(a){if(!a.document)throw new Error("jQuery requires a window with a document");return b(a)}:b(a)}("undefined"!=typeof window?window:this,function(a,b){var c=[],d=c.slice,e=c.concat,f=c.push,g=c.indexOf,h={},i=h.toString,j=h.hasOwnProperty,k={},l="1.11.1",m=function(a,b){return new m.fn.init(a,b)},n=/^[\s\uFEFF\xA0]+|[\s\uFEFF\xA0]+$/g,o=/^-ms-/,p=/-([\da-z])/gi,q=function(a,b){return b.toUpperCase()};m.fn=m.prototype={jquery:l,constructor:m,selector:"",length:0,toArray:function(){return d.call(this)},get:function(a){return null!=a?0>a?this[a+this.length]:this[a]:d.call(this)},pushStack:function(a){var b=m.merge(this.constructor(),a);return b.prevObject=this,b.context=this.context,b},each:function(a,b){return m.each(this,a,b)},map:function(a){return this.pushStack(m.map(this,function(b,c){return a.call(b,c,b)}))},slice:function(){return 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diff --git a/spaces/hanjp/White-box-Cartoonization/wbc/network.py b/spaces/hanjp/White-box-Cartoonization/wbc/network.py
deleted file mode 100644
index 6f16cee1aa1994d0a78c524f459764de5164e637..0000000000000000000000000000000000000000
--- a/spaces/hanjp/White-box-Cartoonization/wbc/network.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import tensorflow as tf
-import numpy as np
-import tensorflow.contrib.slim as slim
-
-
-
-def resblock(inputs, out_channel=32, name='resblock'):
-    
-    with tf.variable_scope(name):
-        
-        x = slim.convolution2d(inputs, out_channel, [3, 3], 
-                               activation_fn=None, scope='conv1')
-        x = tf.nn.leaky_relu(x)
-        x = slim.convolution2d(x, out_channel, [3, 3], 
-                               activation_fn=None, scope='conv2')
-        
-        return x + inputs
-
-
-
-
-def unet_generator(inputs, channel=32, num_blocks=4, name='generator', reuse=False):
-    with tf.variable_scope(name, reuse=reuse):
-        
-        x0 = slim.convolution2d(inputs, channel, [7, 7], activation_fn=None)
-        x0 = tf.nn.leaky_relu(x0)
-        
-        x1 = slim.convolution2d(x0, channel, [3, 3], stride=2, activation_fn=None)
-        x1 = tf.nn.leaky_relu(x1)
-        x1 = slim.convolution2d(x1, channel*2, [3, 3], activation_fn=None)
-        x1 = tf.nn.leaky_relu(x1)
-        
-        x2 = slim.convolution2d(x1, channel*2, [3, 3], stride=2, activation_fn=None)
-        x2 = tf.nn.leaky_relu(x2)
-        x2 = slim.convolution2d(x2, channel*4, [3, 3], activation_fn=None)
-        x2 = tf.nn.leaky_relu(x2)
-        
-        for idx in range(num_blocks):
-            x2 = resblock(x2, out_channel=channel*4, name='block_{}'.format(idx))
-            
-        x2 = slim.convolution2d(x2, channel*2, [3, 3], activation_fn=None)
-        x2 = tf.nn.leaky_relu(x2)
-        
-        h1, w1 = tf.shape(x2)[1], tf.shape(x2)[2]
-        x3 = tf.image.resize_bilinear(x2, (h1*2, w1*2))
-        x3 = slim.convolution2d(x3+x1, channel*2, [3, 3], activation_fn=None)
-        x3 = tf.nn.leaky_relu(x3)
-        x3 = slim.convolution2d(x3, channel, [3, 3], activation_fn=None)
-        x3 = tf.nn.leaky_relu(x3)
-
-        h2, w2 = tf.shape(x3)[1], tf.shape(x3)[2]
-        x4 = tf.image.resize_bilinear(x3, (h2*2, w2*2))
-        x4 = slim.convolution2d(x4+x0, channel, [3, 3], activation_fn=None)
-        x4 = tf.nn.leaky_relu(x4)
-        x4 = slim.convolution2d(x4, 3, [7, 7], activation_fn=None)
-        
-        return x4
-
-if __name__ == '__main__':
-    
-
-    pass
\ No newline at end of file
diff --git a/spaces/hca97/Mosquito-Detection/my_models/torch_hub_cache/yolov5/utils/aws/resume.py b/spaces/hca97/Mosquito-Detection/my_models/torch_hub_cache/yolov5/utils/aws/resume.py
deleted file mode 100644
index b21731c979a121ab8227280351b70d6062efd983..0000000000000000000000000000000000000000
--- a/spaces/hca97/Mosquito-Detection/my_models/torch_hub_cache/yolov5/utils/aws/resume.py
+++ /dev/null
@@ -1,40 +0,0 @@
-# Resume all interrupted trainings in yolov5/ dir including DDP trainings
-# Usage: $ python utils/aws/resume.py
-
-import os
-import sys
-from pathlib import Path
-
-import torch
-import yaml
-
-FILE = Path(__file__).resolve()
-ROOT = FILE.parents[2]  # YOLOv5 root directory
-if str(ROOT) not in sys.path:
-    sys.path.append(str(ROOT))  # add ROOT to PATH
-
-port = 0  # --master_port
-path = Path('').resolve()
-for last in path.rglob('*/**/last.pt'):
-    ckpt = torch.load(last)
-    if ckpt['optimizer'] is None:
-        continue
-
-    # Load opt.yaml
-    with open(last.parent.parent / 'opt.yaml', errors='ignore') as f:
-        opt = yaml.safe_load(f)
-
-    # Get device count
-    d = opt['device'].split(',')  # devices
-    nd = len(d)  # number of devices
-    ddp = nd > 1 or (nd == 0 and torch.cuda.device_count() > 1)  # distributed data parallel
-
-    if ddp:  # multi-GPU
-        port += 1
-        cmd = f'python -m torch.distributed.run --nproc_per_node {nd} --master_port {port} train.py --resume {last}'
-    else:  # single-GPU
-        cmd = f'python train.py --resume {last}'
-
-    cmd += ' > /dev/null 2>&1 &'  # redirect output to dev/null and run in daemon thread
-    print(cmd)
-    os.system(cmd)
diff --git a/spaces/hebert2099/MusicGen/audiocraft/quantization/core_vq.py b/spaces/hebert2099/MusicGen/audiocraft/quantization/core_vq.py
deleted file mode 100644
index e1896bb1788a945a1f7be6369abb255ecf72c7a0..0000000000000000000000000000000000000000
--- a/spaces/hebert2099/MusicGen/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/heliosbrahma/voice-assistant/main.py b/spaces/heliosbrahma/voice-assistant/main.py
deleted file mode 100644
index a02c8ea6de8fbab5932817b1cc1d9f27eea33b5f..0000000000000000000000000000000000000000
--- a/spaces/heliosbrahma/voice-assistant/main.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import whisper
-import gradio as gr 
-import openai
-from TTS.api import TTS
-import subprocess
-import os
-
-OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
-model_name = TTS.list_models()[9]
-tts = TTS(model_name)
-model = whisper.load_model('medium')
-
-def run_ffmpeg_command():
-    command = ['ffmpeg', '-f', 'lavfi', '-i', 'anullsrc=r=44100:cl=mono', '-t', '1', '-q:a', '9', '-acodec', 'libmp3lame', 'output.wav']
-    result = subprocess.run(command, capture_output=True, text=True)
-    print(result.stdout)
-
-
-def voice_chat(user_voice):
-    openai.api_key = OPENAI_API_KEY
-    messages = [
-    {"role": "system", "content": "You are a kind helpful assistant."},
-    ]
-             
-    user_message = model.transcribe(user_voice)["text"]
-    messages.append(
-        {"role": "user", "content": user_message},
-    )
-
-    chat = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo", messages=messages
-    )    
-    reply = chat.choices[0].message.content
-    
-    messages.append({"role": "assistant", "content": reply})
-    tts.tts_to_file(text=reply, file_path="output.wav")
-    return(reply, "output.wav")
-
-# run_ffmpeg_command()
-    
-gr.Interface(
-    title = 'Smart Voice Assistant',
-    description = 'Use this gradio app interface to get answers for all your queries in both text and speech format. \
-    Just communicate your queries in speech format and this app will take care of the rest.',
-    fn=voice_chat, 
-    inputs=[
-        gr.Audio(source="microphone", label="Input Voice", type="filepath")        
-    ],
-    outputs=[
-        gr.Textbox(label="Summarized Answer"),
-        gr.Audio(label="Output Speech", type="filepath")
-    ]).launch()
\ No newline at end of file
diff --git a/spaces/huaiji3y/bingo-Public/src/components/ui/voice/index.tsx b/spaces/huaiji3y/bingo-Public/src/components/ui/voice/index.tsx
deleted file mode 100644
index 4adcb632226bfced8b97092782811edf08b56569..0000000000000000000000000000000000000000
--- a/spaces/huaiji3y/bingo-Public/src/components/ui/voice/index.tsx
+++ /dev/null
@@ -1,28 +0,0 @@
-import './index.scss'
-
-export interface VoiceProps extends CSSPropertyRule {
-  num?: number;
-  duration?: number;
-}
-export default function Voice({ duration = 400, num = 7, ...others }) {
-  return (
-    <div className="voice-button" { ...others }>
-      {Array.from({ length: num }).map((_, index) => {
-        const randomDuration = Math.random() * 100 + duration
-        const initialDelay = Math.random() * 2 * duration
-        const initialScale = Math.sin((index + 1) * Math.PI / num)
-        return (
-          <div
-            className="voice-button-item"
-            key={index}
-            style={{
-              animationDelay: initialDelay + 'ms',
-              animationDuration: randomDuration + 'ms',
-              transform: `scale(${initialScale})`
-            }}
-          />
-        )
-      })}
-    </div>
-  )
-}
diff --git a/spaces/huangjiefree/bingo/Dockerfile b/spaces/huangjiefree/bingo/Dockerfile
deleted file mode 100644
index c677b05b75f7e4b2beee8c97fb47957a0861a83e..0000000000000000000000000000000000000000
--- a/spaces/huangjiefree/bingo/Dockerfile
+++ /dev/null
@@ -1,7 +0,0 @@
-FROM weaigc/bingo:latest
-
-ARG DEBIAN_FRONTEND=noninteractive
-
-ENV BING_HEADER ""
-
-CMD npm start
diff --git a/spaces/huggingchat/chat-ui/src/lib/constants/publicSepToken.ts b/spaces/huggingchat/chat-ui/src/lib/constants/publicSepToken.ts
deleted file mode 100644
index 15d962d69ba33e1abeb8a35885aa7647d24cf7af..0000000000000000000000000000000000000000
--- a/spaces/huggingchat/chat-ui/src/lib/constants/publicSepToken.ts
+++ /dev/null
@@ -1 +0,0 @@
-export const PUBLIC_SEP_TOKEN = "</s>";
diff --git a/spaces/huggingchat/chat-ui/src/lib/utils/hashConv.ts b/spaces/huggingchat/chat-ui/src/lib/utils/hashConv.ts
deleted file mode 100644
index de014324f6f21fbb67a61d098844027cfcdad0bf..0000000000000000000000000000000000000000
--- a/spaces/huggingchat/chat-ui/src/lib/utils/hashConv.ts
+++ /dev/null
@@ -1,12 +0,0 @@
-import type { Conversation } from "$lib/types/Conversation";
-import { sha256 } from "./sha256";
-
-export async function hashConv(conv: Conversation) {
-	// messages contains the conversation message but only the immutable part
-	const messages = conv.messages.map((message) => {
-		return (({ from, id, content, webSearchId }) => ({ from, id, content, webSearchId }))(message);
-	});
-
-	const hash = await sha256(JSON.stringify(messages));
-	return hash;
-}
diff --git a/spaces/huggingface-timeseries/time-series-score/run_experiment.py b/spaces/huggingface-timeseries/time-series-score/run_experiment.py
deleted file mode 100644
index bf9cee2cdda36a9322c32a98f68c34a21daefd63..0000000000000000000000000000000000000000
--- a/spaces/huggingface-timeseries/time-series-score/run_experiment.py
+++ /dev/null
@@ -1,154 +0,0 @@
-import click
-import datetime
-import pprint
-from typing import Optional
-
-
-from src import (
-    load_dataset,
-    fit_predict_with_model,
-    score_predictions,
-    AVAILABLE_DATASETS,
-    AVAILABLE_MODELS,
-    SEASONALITY_MAP,
-)
-
-
-def apply_ablation(ablation: str, model_kwargs: dict) -> dict:
-    if ablation == "NoEnsemble":
-        model_kwargs["enable_ensemble"] = False
-    elif ablation == "NoDeepModels":
-        model_kwargs["hyperparameters"] = {
-            "Naive": {},
-            "SeasonalNaive": {},
-            "ARIMA": {},
-            "ETS": {},
-            "AutoETS": {},
-            "AutoARIMA": {},
-            "Theta": {},
-            "AutoGluonTabular": {},
-        }
-    elif ablation == "NoStatModels":
-        model_kwargs["hyperparameters"] = {
-            "AutoGluonTabular": {},
-            "DeepAR": {},
-            "SimpleFeedForward": {},
-            "TemporalFusionTransformer": {},
-        }
-    elif ablation == "NoTreeModels":
-        model_kwargs["hyperparameters"] = {
-            "Naive": {},
-            "SeasonalNaive": {},
-            "ARIMA": {},
-            "ETS": {},
-            "AutoETS": {},
-            "AutoARIMA": {},
-            "Theta": {},
-            "DeepAR": {},
-            "SimpleFeedForward": {},
-            "TemporalFusionTransformer": {},
-        }
-    return model_kwargs
-
-
-@click.command(
-    context_settings=dict(
-        ignore_unknown_options=True,
-        allow_extra_args=True,
-    )
-)
-@click.option(
-    "--dataset_name",
-    "-d",
-    required=True,
-    default="m3_other",
-    help="The dataset to train the model on",
-    type=click.Choice(AVAILABLE_DATASETS),
-)
-@click.option(
-    "--model_name",
-    "-m",
-    default="autogluon",
-    help="Model to train",
-    type=click.Choice(AVAILABLE_MODELS),
-)
-@click.option(
-    "--eval_metric",
-    "-e",
-    default="MASE",
-    type=click.Choice(["MASE", "mean_wQuantileLoss"]),
-)
-@click.option(
-    "--seed",
-    "-s",
-    default=1,
-    type=int,
-)
-@click.option(
-    "--time_limit",
-    "-t",
-    default=4 * 3600,
-    type=int,
-)
-@click.option(
-    "--ablation",
-    "-a",
-    default=None,
-    type=click.Choice(["NoEnsemble", "NoDeepModels", "NoStatModels", "NoTreeModels"]),
-)
-@click.pass_context
-def main(
-    ctx,
-    dataset_name: str,
-    model_name: str,
-    eval_metric: str,
-    seed: int,
-    time_limit: int,
-    ablation: Optional[str],
-):
-    print(f"Evaluating {model_name} on {dataset_name}")
-    dataset = load_dataset(dataset_name)
-    task_kwargs = {
-        "prediction_length": dataset.metadata.prediction_length,
-        "freq": dataset.metadata.freq,
-        "eval_metric": eval_metric,
-        "seasonality": SEASONALITY_MAP[dataset.metadata.freq],
-    }
-    print("Task definition:")
-    pprint.pprint(task_kwargs)
-
-    # Additional command line arguments like `--name value` are parsed as {"name": "value"}
-    model_kwargs = {ctx.args[i][2:]: ctx.args[i + 1] for i in range(0, len(ctx.args), 2)}
-    model_kwargs["seed"] = seed
-    model_kwargs["time_limit"] = time_limit
-
-    if ablation is not None:
-        assert model_name == "autogluon", f"{model_name} does not support ablations"
-        model_kwargs = apply_ablation(ablation, model_kwargs)
-
-    if len(model_kwargs) > 0:
-        print("Model kwargs:")
-        pprint.pprint(model_kwargs)
-
-    print(f"Starting training {datetime.datetime.now()}")
-
-    predictions, info = fit_predict_with_model(
-        model_name, dataset.train, **task_kwargs, **model_kwargs
-    )
-
-    metrics = score_predictions(
-        dataset=dataset.test,
-        predictions=predictions,
-        prediction_length=task_kwargs["prediction_length"],
-        seasonality=task_kwargs["seasonality"],
-    )
-    print("================================================")
-    print(f"model: {model_name}")
-    print(f"dataset: {dataset_name}")
-    print(f"total_run_time: {info['run_time']:.2f}")
-    print(f"mase: {metrics['MASE']:.4f}")
-    print(f"mean_wQuantileLoss: {metrics['mean_wQuantileLoss']:.4f}")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/hysts/Compare-DETA-and-YOLOv8/app.py b/spaces/hysts/Compare-DETA-and-YOLOv8/app.py
deleted file mode 100644
index d242092ff0243eafa756c59c95f911fe44fc34d3..0000000000000000000000000000000000000000
--- a/spaces/hysts/Compare-DETA-and-YOLOv8/app.py
+++ /dev/null
@@ -1,115 +0,0 @@
-#!/usr/bin/env python
-
-from __future__ import annotations
-
-import pathlib
-
-import gradio as gr
-import numpy as np
-import PIL.Image
-import torch
-from sahi.prediction import ObjectPrediction
-from sahi.utils.cv import visualize_object_predictions
-from transformers import AutoImageProcessor, DetaForObjectDetection
-from ultralytics import YOLO
-
-DESCRIPTION = '# Compare DETA and YOLOv8'
-
-device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-
-MODEL_ID = 'jozhang97/deta-swin-large'
-image_processor = AutoImageProcessor.from_pretrained(MODEL_ID)
-model_deta = DetaForObjectDetection.from_pretrained(MODEL_ID)
-model_deta.to(device)
-
-model_yolo = YOLO('yolov8x.pt')
-
-
-@torch.inference_mode()
-def run_deta(image_path: str, threshold: float) -> np.ndarray:
-    image = PIL.Image.open(image_path)
-    inputs = image_processor(images=image, return_tensors='pt').to(device)
-    outputs = model_deta(**inputs)
-    target_sizes = torch.tensor([image.size[::-1]])
-    results = image_processor.post_process_object_detection(
-        outputs, threshold=threshold, target_sizes=target_sizes)[0]
-
-    boxes = results['boxes'].cpu().numpy()
-    scores = results['scores'].cpu().numpy()
-    cat_ids = results['labels'].cpu().numpy().tolist()
-    preds = []
-    for box, score, cat_id in zip(boxes, scores, cat_ids):
-        box = np.round(box).astype(int)
-        cat_label = model_deta.config.id2label[cat_id]
-        pred = ObjectPrediction(bbox=box,
-                                category_id=cat_id,
-                                category_name=cat_label,
-                                score=score)
-        preds.append(pred)
-    res = visualize_object_predictions(np.asarray(image), preds)['image']
-    return res
-
-
-def run_yolov8(image_path: str, threshold: float) -> np.ndarray:
-    image = PIL.Image.open(image_path)
-    results = model_yolo(image, imgsz=640, conf=threshold)
-    boxes = results[0].boxes.cpu().numpy().data
-    preds = []
-    for box in boxes:
-        score = box[4]
-        cat_id = int(box[5])
-        box = np.round(box[:4]).astype(int)
-        cat_label = model_yolo.model.names[cat_id]
-        pred = ObjectPrediction(bbox=box,
-                                category_id=cat_id,
-                                category_name=cat_label,
-                                score=score)
-        preds.append(pred)
-    res = visualize_object_predictions(np.asarray(image), preds)['image']
-    return res
-
-
-def run(image_path: str, threshold: float) -> tuple[np.ndarray, np.ndarray]:
-    return run_deta(image_path, threshold), run_yolov8(image_path, threshold)
-
-
-with gr.Blocks(css='style.css') as demo:
-    gr.Markdown(DESCRIPTION)
-    with gr.Row():
-        with gr.Column():
-            image = gr.Image(label='Input image', type='filepath')
-            threshold = gr.Slider(label='Score threshold',
-                                  minimum=0,
-                                  maximum=1,
-                                  value=0.5,
-                                  step=0.01)
-            run_button = gr.Button('Run')
-        with gr.Column():
-            result_deta = gr.Image(label='Result (DETA)', type='numpy')
-            result_yolo = gr.Image(label='Result (YOLOv8)', type='numpy')
-
-    with gr.Row():
-        paths = sorted(pathlib.Path('images').glob('*.jpg'))
-        gr.Examples(examples=[[path.as_posix(), 0.5] for path in paths],
-                    inputs=[
-                        image,
-                        threshold,
-                    ],
-                    outputs=[
-                        result_deta,
-                        result_yolo,
-                    ],
-                    fn=run,
-                    cache_examples=True)
-
-    run_button.click(fn=run,
-                     inputs=[
-                         image,
-                         threshold,
-                     ],
-                     outputs=[
-                         result_deta,
-                         result_yolo,
-                     ])
-
-demo.queue().launch()
diff --git a/spaces/hzwluoye/gpt4/client/js/theme-toggler.js b/spaces/hzwluoye/gpt4/client/js/theme-toggler.js
deleted file mode 100644
index 67e1a9501b70d54ab8a717f34983c012328e74a0..0000000000000000000000000000000000000000
--- a/spaces/hzwluoye/gpt4/client/js/theme-toggler.js
+++ /dev/null
@@ -1,22 +0,0 @@
-var switch_theme_toggler = document.getElementById("theme-toggler");
-
-switch_theme_toggler.addEventListener("change", toggleTheme);
-
-function setTheme(themeName) {
-	localStorage.setItem("theme", themeName);
-	document.documentElement.className = themeName;
-}
-
-function toggleTheme() {
-	var currentTheme = localStorage.getItem("theme");
-	var newTheme = currentTheme === "theme-dark" ? "theme-light" : "theme-dark";
-
-	setTheme(newTheme);
-	switch_theme_toggler.checked = newTheme === "theme-dark";
-}
-
-(function () {
-	var currentTheme = localStorage.getItem("theme") || "theme-dark";
-	setTheme(currentTheme);
-	switch_theme_toggler.checked = currentTheme === "theme-dark";
-})();
diff --git a/spaces/iamironman4279/SadTalker/README.md b/spaces/iamironman4279/SadTalker/README.md
deleted file mode 100644
index feebb93a9a459bc0a6625c4976ff492879016889..0000000000000000000000000000000000000000
--- a/spaces/iamironman4279/SadTalker/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: SadTalker
-emoji: 😭
-colorFrom: purple
-colorTo: green
-sdk: gradio
-sdk_version: 3.23.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/imdebamrita/whatsapp_chat_analysis/preprocessor.py b/spaces/imdebamrita/whatsapp_chat_analysis/preprocessor.py
deleted file mode 100644
index 470e3f32e14000352556d2c06418222cefd8c466..0000000000000000000000000000000000000000
--- a/spaces/imdebamrita/whatsapp_chat_analysis/preprocessor.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import re
-import pandas as pd
-
-pattern_12 = '\d{1,2}\/\d{1,2}\/\d{1,2},\s\d{1,2}:\d{1,2}\s[a,m,p]+\s-\s'
-pattern_24 = '\d{1,2}\/\d{1,2}\/\d{1,2},\s\d{1,2}:\d{1,2}\s-\s'
-pattern_ph_num = '\d{1,2} \d{5} \d{5}'
-
-def checker(data):
-    check_1 = re.search(pattern_12, data)
-    check_2 = re.search(pattern_24, data)
-
-    if check_1 or check_2:
-        return True
-    else:
-        return False
-
-
-def preprocess(data):
-    x = re.search(pattern_12, data)
-
-    # For 12 hour format
-    if x:
-        messages = re.split(pattern_12, data)[1:]
-        dates = re.findall(pattern_12, data)
-        df = pd.DataFrame({'user_message': messages, 'message_date': dates})
-
-        df['message_date'] = pd.to_datetime(
-            df['message_date'], format='%d/%m/%y, %I:%M %p - ')
-
-
-    else:
-        messages = re.split(pattern_24, data)[1:]
-        dates = re.findall(pattern_24, data)
-
-        df = pd.DataFrame({'user_message': messages, 'message_date': dates})
-
-        df['message_date'] = pd.to_datetime(
-            df['message_date'], format='%d/%m/%y, %H:%M - ')
-
-    
-    df.rename(columns={'message_date': 'date'}, inplace=True)
-
-    users = []
-    messages = []
-
-    for message in df['user_message']:
-        entry = re.split('([\w\W]+?):\s', message)
-        if entry[1:]:
-            if re.search(pattern_ph_num, entry[1]):
-                users.append('M:' + str(entry[1]))
-            else:
-                users.append(entry[1])
-            messages.append(entry[2])
-        else:
-            users.append('group_notification')
-            messages.append(entry[0])
-
-    df['user'] = users
-    df['message'] = messages
-    df.drop(columns=['user_message'], inplace=True)
-
-    df['only_date'] = df['date'].dt.date
-    df['year'] = df['date'].dt.year
-    df['month'] = df['date'].dt.month_name()
-    df['day'] = df['date'].dt.day
-    df['day_name'] = df['date'].dt.day_name()
-    df['hour'] = df['date'].dt.hour
-    df['minute'] = df['date'].dt.minute
-
-    period = []
-    for hour in df[['day_name', 'hour']]['hour']:
-        if hour == 23:
-            period.append(str(hour) + ' - ' + '00')
-        elif hour == 0:
-            period.append('00' + ' - ' + str(hour + 1))
-        else:
-            period.append(str(hour) + ' - ' + str(hour + 1))
-        # period.append(str(hour) + 'abc')
-
-    df['period'] = period
-
-    return df
diff --git a/spaces/inamXcontru/PoeticTTS/Compartir Portapapeles Entre Maquinas Virtuales Gua Completa Para Copiar Y Pegar Con VirtualBox.md b/spaces/inamXcontru/PoeticTTS/Compartir Portapapeles Entre Maquinas Virtuales Gua Completa Para Copiar Y Pegar Con VirtualBox.md
deleted file mode 100644
index 7f47f4bac997644ca7d4030f2017ff9d7e89bbf4..0000000000000000000000000000000000000000
--- a/spaces/inamXcontru/PoeticTTS/Compartir Portapapeles Entre Maquinas Virtuales Gua Completa Para Copiar Y Pegar Con VirtualBox.md	
+++ /dev/null
@@ -1,12 +0,0 @@
-
-<p>Una de las ventajas que tienen las máquinas virtuales, es que podremos compartir información fácilmente entre el PC Principal (Anfitrión) y el PC Virtual (Invitado). Por ejemplo, podremos copiar ficheros de una máquina a otra, o incluso copiar y pegar el contenido del portapapeles de una máquina a otra.</p>
-<h2>Compartir Portapapeles Entre Maquinas Virtuales (copiar Y Pegar) Con VirtualBox</h2><br /><p><b><b>DOWNLOAD</b> &#10027;&#10027;&#10027; <a href="https://gohhs.com/2uz3ZS">https://gohhs.com/2uz3ZS</a></b></p><br /><br />
-<p>Esta última función suele ser problemática en las máquinas anfitrión que corren Windows. <strong>Es habitual que la función de copiar y pegar entre Anfitrión e Invitado no funcione</strong> en ninguno de los sentidos (anfitrión->invitado, invitado->anfitrión). Este problema se puede deber a varios motivos, pero en ocasiones el portapapeles compartido sencillamente funciona de forma aleatoria, es decir, unas veces funciona correctamente y otras no. Esto puede llegar a ser bastante molesto, ya que cuando inicias la máquina virtual, no sabes si podrás hacer uso de la función de copiar y pegar entre máquinas.</p>
-<p>Para habilitar la función que nos permite arrastrar archivos entre la máquina virtual y el PC, además de utilizar la función del portapapeles para copiar y pegar texto entre ambos sistemas operativos, pulsamos en el cuadro desplegable Compartir portapapeles y Arrastrar y soltar seleccionando en ambos casos Bidireccional.</p>
-<p>Kernel Samepage Merging (KSM) es una característica del kernel de Linux que permite que una aplicación se registre con el kernel para que sus páginas se combinen con otros procesos que también se registren para que sus páginas se fusionen. El mecanismo KSM permite a las máquinas virtuales invitadas compartir páginas entre sí. En un entorno donde muchos de los sistemas operativos invitados son similares, esto puede resultar en ahorros significativos de memoria.</p>
-<p></p>
-<p>Además, todas estas qubes aisladas están integradas en un solo sistema utilizable. Los programas están aislados en sus propias qubes separadas, pero todas las ventanas se muestran en un único entorno de escritorio unificado con bordes de ventana de colores imposibles de descifrar para que pueda identificar fácilmente las ventanas desde diferentes niveles de seguridad. Los vectores de ataque comunes como las tarjetas de red y los controladores USB están aislados en sus propias qubes de hardware, mientras que su funcionalidad se preserva a través de redes seguras , firewalls y administración de dispositivos USB . Las operaciones integradas de copiar y pegar de archivos y portapapeles facilitan el trabajo en diversas empresas sin comprometer la seguridad. La plantilla innovadorael sistema separa la instalación del software del uso del software, lo que permite a las qubes compartir un sistema de archivos raíz sin sacrificar la seguridad (y ahorrar espacio en disco, para arrancar). Qubes incluso le permite desinfectar archivos PDF e imágenes con unos pocos clics. Los usuarios preocupados por la privacidad apreciarán laintegración de Whonix con Qubes, lo que facilita el uso de Tor de forma segura, mientras que aquellos preocupados por los ataques de hardware físico se beneficiarán de Anti Evil Maid .</p>
-<p>Qubes lo hace de manera que varias máquinas virtuales que se ejecutan bajo un hipervisor de tipo 1 se puedan usar de forma segura como un sistema operativo integrado. Por ejemplo, coloca todas las ventanas de sus aplicaciones en el mismo escritorio con bordes de colores especiales que indican los niveles de confianza de sus respectivas máquinas virtuales. También permite cosas como operaciones seguras de copiar / pegar entre máquinas virtuales, copiar y transferir de manera segura archivos entre máquinas virtuales y redes seguras entre máquinas virtuales e Internet.</p>
-<p><ul> <li> Fácil integración del puntero del mouse. </li> <li> Una forma sencilla de compartir carpetas entre el anfitrión y el invitado. </li> <li> La función de arrastrar y soltar permite copiar o abrir archivos, copiar formatos de portapapeles del anfitrión al invitado o del invitado al anfitrión. </li> <li> Comparta el portapapeles (para copiar y pegar) del sistema operativo invitado con su sistema operativo host. </li> <li> Un mejor soporte de video proporciona un rendimiento de video acelerado. </li> <li> Mejor sincronización horaria entre invitado y anfitrión. </li> <li> Canales de comunicación estándar de anfitrión/invitado. </li> <li> Las funciones integradas de Windows le permiten ejecutar las ventanas de su sistema operativo invitado sin problemas junto a las ventanas de su host. </li> </ul></p> aaccfb2cb3<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/F1 2008 Track Pack Rfactor Crackl.md b/spaces/inplisQlawa/anything-midjourney-v4-1/F1 2008 Track Pack Rfactor Crackl.md
deleted file mode 100644
index 95f37d02e85105e024fe87cca12ab69c283fca42..0000000000000000000000000000000000000000
--- a/spaces/inplisQlawa/anything-midjourney-v4-1/F1 2008 Track Pack Rfactor Crackl.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>F1 2008 Track Pack Rfactor Crackl</h2><br /><p><b><b>DOWNLOAD</b> &#10038; <a href="https://urlin.us/2uEyBh">https://urlin.us/2uEyBh</a></b></p><br /><br />
-<br />
-Addon for game rFactor Mod F1 season 2009 by F1LIGUE. ... tenemos todos los circuitos o tracks para rFactor de esta Dec 20, 2008 · The rFactor installation ... 4d29de3e1b<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/Modern Machining Process By Pandey And Shan PDFl.md b/spaces/inplisQlawa/anything-midjourney-v4-1/Modern Machining Process By Pandey And Shan PDFl.md
deleted file mode 100644
index 2d3f50a9f53460a5e3b436f54c09f380d18af7a2..0000000000000000000000000000000000000000
--- a/spaces/inplisQlawa/anything-midjourney-v4-1/Modern Machining Process By Pandey And Shan PDFl.md	
+++ /dev/null
@@ -1,10 +0,0 @@
-<h2>Modern Machining Process By Pandey And Shan PDFl</h2><br /><p><b><b>Download</b> &#9658;&#9658;&#9658; <a href="https://urlin.us/2uEwrf">https://urlin.us/2uEwrf</a></b></p><br /><br />
-
-July 1, 2017 - Create a free account to find out, friends think about this book! Community Reviews. 3.75. 4 ratings0 reviews. 5 stars. 2 (50%). 4 stars. 3 stars. Read reviews.
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diff --git a/spaces/inreVtussa/clothingai/Examples/001GameCreatorVisualNovelKitcrackdownloadpckickass.md b/spaces/inreVtussa/clothingai/Examples/001GameCreatorVisualNovelKitcrackdownloadpckickass.md
deleted file mode 100644
index 1376bbce553b7061a2224eb79ad36e4426865261..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/001GameCreatorVisualNovelKitcrackdownloadpckickass.md
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>001GameCreatorVisualNovelKitcrackdownloadpckickass</h2><br /><p><b><b>Download Zip</b> &#9881; <a href="https://tiurll.com/2uCk2M">https://tiurll.com/2uCk2M</a></b></p><br /><br />
-<br />
- d5da3c52bf<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/inreVtussa/clothingai/Examples/Anime X Hero Siege 3.9.md b/spaces/inreVtussa/clothingai/Examples/Anime X Hero Siege 3.9.md
deleted file mode 100644
index 22a1341cb509417b22cceb5ffa424007ce160c4e..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/Anime X Hero Siege 3.9.md	
+++ /dev/null
@@ -1,43 +0,0 @@
-<br />
-<h1>How to Play Anime X Hero Siege 3.9: A Guide for Beginners</h1>
-
-<p>Anime X Hero Siege 3.9 is a popular Warcraft 3 custom map that pits players against waves of enemies from various anime series. The map features over 50 heroes to choose from, each with their own unique abilities and items. The map also has different modes and difficulties to suit different preferences and skill levels.</p>
-
-<p>If you are new to Anime X Hero Siege 3.9, you might be wondering how to play this map and what are some tips and tricks to survive and win. In this article, we will provide you with a basic guide on how to play Anime X Hero Siege 3.9, as well as some useful information on the map's features and mechanics.</p>
-<h2>anime x hero siege 3.9</h2><br /><p><b><b>Download File</b> &rArr; <a href="https://tiurll.com/2uClE3">https://tiurll.com/2uClE3</a></b></p><br /><br />
-
-<h2>How to Download and Install Anime X Hero Siege 3.9</h2>
-
-<p>Before you can play Anime X Hero Siege 3.9, you need to download and install the map file on your Warcraft 3 folder. You can download the map file from <a href="https://www.epicwar.com/maps/276260/">Epic War</a>, a website that hosts thousands of Warcraft 3 custom maps. The file name is Anime X Hero siege 3.9.w3x and it is 17.7 MB in size.</p>
-
-<p>Once you have downloaded the map file, you need to copy and paste it into your Warcraft 3 Maps folder, which is usually located at C:\Program Files\Warcraft III\Maps\Download. If you don't have a Download folder, you can create one yourself.</p>
-
-<p>After you have installed the map file, you can launch Warcraft 3 and go to Custom Game mode. You should be able to see Anime X Hero Siege 3.9 in the list of available maps. You can either host a game yourself or join an existing game hosted by another player.</p>
-
-<h2>How to Choose a Hero and Start the Game</h2>
-
-<p>When you enter the game lobby, you will see a screen with several options and buttons. Here, you can choose your hero, your mode, your difficulty, and your team.</p>
-
-<p>To choose your hero, you can click on the Hero Selection button at the bottom right corner of the screen. This will open a menu with all the available heroes in the map. You can scroll through the menu using the arrow keys or the mouse wheel. You can also use the search bar at the top of the menu to find a specific hero by name or by anime series.</p>
-
-<p>Each hero has a portrait, a name, an anime series, and a brief description of their abilities and items. You can hover your mouse over the portrait or the name to see more details about the hero. You can also click on the portrait or the name to select the hero.</p>
-
-<p>Once you have selected your hero, you can click on the Confirm button at the bottom of the menu to lock in your choice. You can also click on the Random button at the bottom left corner of the menu to pick a random hero.</p>
-<p></p>
-
-<p>To choose your mode, you can click on the Mode Selection button at the bottom left corner of the screen. This will open a menu with all the available modes in the map. You can scroll through the menu using the arrow keys or the mouse wheel.</p>
-
-<p>Each mode has a name and a description of its rules and features. You can hover your mouse over the name to see more details about the mode. You can also click on the name to select the mode.</p>
-
-<p>The default mode is Normal Mode, which is recommended for beginners. In this mode, you will face 8 waves of enemies from different anime series, each with their own boss at the end. You will also have access to shops where you can buy items and upgrades for your hero.</p>
-
-<p>Some of the other modes are:
-
-<ul>
-<li>Hard Mode: Similar to Normal Mode, but with harder enemies and fewer shops.</li>
-<li>Extreme Mode: Similar to Hard Mode, but with even harder enemies and no shops.</li>
-<li>Solo Mode: A mode where you play alone against all 8 waves of enemies.</li>
-<li>Duel Mode: A mode where you fight against another player in a one-on-one match.</li>
-<li>Survival Mode: A mode where you try to survive as long as possible against endless waves of enemies.</</p> d5da3c52bf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/inreVtussa/clothingai/Examples/Crack [2021] Keygen Shotgun 2017 Activation.md b/spaces/inreVtussa/clothingai/Examples/Crack [2021] Keygen Shotgun 2017 Activation.md
deleted file mode 100644
index 749540f1b0f365dae88bda96adf85292fd8d0138..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/Crack [2021] Keygen Shotgun 2017 Activation.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>crack Keygen Shotgun 2017 activation</h2><br /><p><b><b>Download File</b> &#9881; <a href="https://tiurll.com/2uCkZR">https://tiurll.com/2uCkZR</a></b></p><br /><br />
-
-Chamomile with a name. Daisy is a leading manufacturer of youth sporting firearms. We are known for producing airguns and youth rifles. They are designed to give young shooters a start and give them the opportunity to test themselves, try their hand and feel their abilities in shooting with real weapons. Daisy releases many weapons that can meet the needs of all ages and hand sizes, and our new designs always take this into account. Daisy Sporting Guns has always been a major source of guns for young people and what we are doing now should also meet their needs. 8a78ff9644<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/jackli888/stable-diffusion-webui/javascript/ui.js b/spaces/jackli888/stable-diffusion-webui/javascript/ui.js
deleted file mode 100644
index b7a8268a8fcdf9821cb3af31efea9e0283da1bfe..0000000000000000000000000000000000000000
--- a/spaces/jackli888/stable-diffusion-webui/javascript/ui.js
+++ /dev/null
@@ -1,338 +0,0 @@
-// various functions for interaction with ui.py not large enough to warrant putting them in separate files
-
-function set_theme(theme){
-    gradioURL = window.location.href
-    if (!gradioURL.includes('?__theme=')) {
-      window.location.replace(gradioURL + '?__theme=' + theme);
-    }
-}
-
-function selected_gallery_index(){
-    var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item')
-    var button = gradioApp().querySelector('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item.\\!ring-2')
-
-    var result = -1
-    buttons.forEach(function(v, i){ if(v==button) { result = i } })
-
-    return result
-}
-
-function extract_image_from_gallery(gallery){
-    if(gallery.length == 1){
-        return [gallery[0]]
-    }
-
-    index = selected_gallery_index()
-
-    if (index < 0 || index >= gallery.length){
-        return [null]
-    }
-
-    return [gallery[index]];
-}
-
-function args_to_array(args){
-    res = []
-    for(var i=0;i<args.length;i++){
-        res.push(args[i])
-    }
-    return res
-}
-
-function switch_to_txt2img(){
-    gradioApp().querySelector('#tabs').querySelectorAll('button')[0].click();
-
-    return args_to_array(arguments);
-}
-
-function switch_to_img2img_tab(no){
-    gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
-    gradioApp().getElementById('mode_img2img').querySelectorAll('button')[no].click();
-}
-function switch_to_img2img(){
-    switch_to_img2img_tab(0);
-    return args_to_array(arguments);
-}
-
-function switch_to_sketch(){
-    switch_to_img2img_tab(1);
-    return args_to_array(arguments);
-}
-
-function switch_to_inpaint(){
-    switch_to_img2img_tab(2);
-    return args_to_array(arguments);
-}
-
-function switch_to_inpaint_sketch(){
-    switch_to_img2img_tab(3);
-    return args_to_array(arguments);
-}
-
-function switch_to_inpaint(){
-    gradioApp().querySelector('#tabs').querySelectorAll('button')[1].click();
-    gradioApp().getElementById('mode_img2img').querySelectorAll('button')[2].click();
-
-    return args_to_array(arguments);
-}
-
-function switch_to_extras(){
-    gradioApp().querySelector('#tabs').querySelectorAll('button')[2].click();
-
-    return args_to_array(arguments);
-}
-
-function get_tab_index(tabId){
-    var res = 0
-
-    gradioApp().getElementById(tabId).querySelector('div').querySelectorAll('button').forEach(function(button, i){
-        if(button.className.indexOf('bg-white') != -1)
-            res = i
-    })
-
-    return res
-}
-
-function create_tab_index_args(tabId, args){
-    var res = []
-    for(var i=0; i<args.length; i++){
-        res.push(args[i])
-    }
-
-    res[0] = get_tab_index(tabId)
-
-    return res
-}
-
-function get_img2img_tab_index() {
-    let res = args_to_array(arguments)
-    res.splice(-2)
-    res[0] = get_tab_index('mode_img2img')
-    return res
-}
-
-function create_submit_args(args){
-    res = []
-    for(var i=0;i<args.length;i++){
-        res.push(args[i])
-    }
-
-    // As it is currently, txt2img and img2img send back the previous output args (txt2img_gallery, generation_info, html_info) whenever you generate a new image.
-    // This can lead to uploading a huge gallery of previously generated images, which leads to an unnecessary delay between submitting and beginning to generate.
-    // I don't know why gradio is sending outputs along with inputs, but we can prevent sending the image gallery here, which seems to be an issue for some.
-    // If gradio at some point stops sending outputs, this may break something
-    if(Array.isArray(res[res.length - 3])){
-        res[res.length - 3] = null
-    }
-
-    return res
-}
-
-function showSubmitButtons(tabname, show){
-    gradioApp().getElementById(tabname+'_interrupt').style.display = show ? "none" : "block"
-    gradioApp().getElementById(tabname+'_skip').style.display = show ? "none" : "block"
-}
-
-function submit(){
-    rememberGallerySelection('txt2img_gallery')
-    showSubmitButtons('txt2img', false)
-
-    var id = randomId()
-    requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function(){
-        showSubmitButtons('txt2img', true)
-
-    })
-
-    var res = create_submit_args(arguments)
-
-    res[0] = id
-
-    return res
-}
-
-function submit_img2img(){
-    rememberGallerySelection('img2img_gallery')
-    showSubmitButtons('img2img', false)
-
-    var id = randomId()
-    requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function(){
-        showSubmitButtons('img2img', true)
-    })
-
-    var res = create_submit_args(arguments)
-
-    res[0] = id
-    res[1] = get_tab_index('mode_img2img')
-
-    return res
-}
-
-function modelmerger(){
-    var id = randomId()
-    requestProgress(id, gradioApp().getElementById('modelmerger_results_panel'), null, function(){})
-
-    var res = create_submit_args(arguments)
-    res[0] = id
-    return res
-}
-
-
-function ask_for_style_name(_, prompt_text, negative_prompt_text) {
-    name_ = prompt('Style name:')
-    return [name_, prompt_text, negative_prompt_text]
-}
-
-function confirm_clear_prompt(prompt, negative_prompt) {
-    if(confirm("Delete prompt?")) {
-        prompt = ""
-        negative_prompt = ""
-    }
-
-    return [prompt, negative_prompt]
-}
-
-
-promptTokecountUpdateFuncs = {}
-
-function recalculatePromptTokens(name){
-    if(promptTokecountUpdateFuncs[name]){
-        promptTokecountUpdateFuncs[name]()
-    }
-}
-
-function recalculate_prompts_txt2img(){
-    recalculatePromptTokens('txt2img_prompt')
-    recalculatePromptTokens('txt2img_neg_prompt')
-    return args_to_array(arguments);
-}
-
-function recalculate_prompts_img2img(){
-    recalculatePromptTokens('img2img_prompt')
-    recalculatePromptTokens('img2img_neg_prompt')
-    return args_to_array(arguments);
-}
-
-
-opts = {}
-onUiUpdate(function(){
-	if(Object.keys(opts).length != 0) return;
-
-	json_elem = gradioApp().getElementById('settings_json')
-	if(json_elem == null) return;
-
-    var textarea = json_elem.querySelector('textarea')
-    var jsdata = textarea.value
-    opts = JSON.parse(jsdata)
-    executeCallbacks(optionsChangedCallbacks);
-
-    Object.defineProperty(textarea, 'value', {
-        set: function(newValue) {
-            var valueProp = Object.getOwnPropertyDescriptor(HTMLTextAreaElement.prototype, 'value');
-            var oldValue = valueProp.get.call(textarea);
-            valueProp.set.call(textarea, newValue);
-
-            if (oldValue != newValue) {
-                opts = JSON.parse(textarea.value)
-            }
-
-            executeCallbacks(optionsChangedCallbacks);
-        },
-        get: function() {
-            var valueProp = Object.getOwnPropertyDescriptor(HTMLTextAreaElement.prototype, 'value');
-            return valueProp.get.call(textarea);
-        }
-    });
-
-    json_elem.parentElement.style.display="none"
-
-    function registerTextarea(id, id_counter, id_button){
-        var prompt = gradioApp().getElementById(id)
-        var counter = gradioApp().getElementById(id_counter)
-        var textarea = gradioApp().querySelector("#" + id + " > label > textarea");
-
-        if(counter.parentElement == prompt.parentElement){
-            return
-        }
-
-        prompt.parentElement.insertBefore(counter, prompt)
-        counter.classList.add("token-counter")
-        prompt.parentElement.style.position = "relative"
-
-		promptTokecountUpdateFuncs[id] = function(){ update_token_counter(id_button); }
-		textarea.addEventListener("input", promptTokecountUpdateFuncs[id]);
-    }
-
-    registerTextarea('txt2img_prompt', 'txt2img_token_counter', 'txt2img_token_button')
-    registerTextarea('txt2img_neg_prompt', 'txt2img_negative_token_counter', 'txt2img_negative_token_button')
-    registerTextarea('img2img_prompt', 'img2img_token_counter', 'img2img_token_button')
-    registerTextarea('img2img_neg_prompt', 'img2img_negative_token_counter', 'img2img_negative_token_button')
-
-    show_all_pages = gradioApp().getElementById('settings_show_all_pages')
-    settings_tabs = gradioApp().querySelector('#settings div')
-    if(show_all_pages && settings_tabs){
-        settings_tabs.appendChild(show_all_pages)
-        show_all_pages.onclick = function(){
-            gradioApp().querySelectorAll('#settings > div').forEach(function(elem){
-                elem.style.display = "block";
-            })
-        }
-    }
-})
-
-onOptionsChanged(function(){
-    elem = gradioApp().getElementById('sd_checkpoint_hash')
-    sd_checkpoint_hash = opts.sd_checkpoint_hash || ""
-    shorthash = sd_checkpoint_hash.substr(0,10)
-
-	if(elem && elem.textContent != shorthash){
-	    elem.textContent = shorthash
-	    elem.title = sd_checkpoint_hash
-	    elem.href = "https://google.com/search?q=" + sd_checkpoint_hash
-	}
-})
-
-let txt2img_textarea, img2img_textarea = undefined;
-let wait_time = 800
-let token_timeouts = {};
-
-function update_txt2img_tokens(...args) {
-	update_token_counter("txt2img_token_button")
-	if (args.length == 2)
-		return args[0]
-	return args;
-}
-
-function update_img2img_tokens(...args) {
-	update_token_counter("img2img_token_button")
-	if (args.length == 2)
-		return args[0]
-	return args;
-}
-
-function update_token_counter(button_id) {
-	if (token_timeouts[button_id])
-		clearTimeout(token_timeouts[button_id]);
-	token_timeouts[button_id] = setTimeout(() => gradioApp().getElementById(button_id)?.click(), wait_time);
-}
-
-function restart_reload(){
-    document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
-    setTimeout(function(){location.reload()},2000)
-
-    return []
-}
-
-// Simulate an `input` DOM event for Gradio Textbox component. Needed after you edit its contents in javascript, otherwise your edits
-// will only visible on web page and not sent to python.
-function updateInput(target){
-	let e = new Event("input", { bubbles: true })
-	Object.defineProperty(e, "target", {value: target})
-	target.dispatchEvent(e);
-}
-
-
-var desiredCheckpointName = null;
-function selectCheckpoint(name){
-    desiredCheckpointName = name;
-    gradioApp().getElementById('change_checkpoint').click()
-}
diff --git a/spaces/jbilcke-hf/MusicGen/audiocraft/utils/export.py b/spaces/jbilcke-hf/MusicGen/audiocraft/utils/export.py
deleted file mode 100644
index b513b52267f7bf5aae09282c15b0a2e20c8a8fee..0000000000000000000000000000000000000000
--- a/spaces/jbilcke-hf/MusicGen/audiocraft/utils/export.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.
-
-"""
-Utility to export a training checkpoint to a lightweight release checkpoint.
-"""
-
-from pathlib import Path
-import typing as tp
-
-from omegaconf import OmegaConf, DictConfig
-import torch
-
-
-def _clean_lm_cfg(cfg: DictConfig):
-    OmegaConf.set_struct(cfg, False)
-    # This used to be set automatically in the LM solver, need a more robust solution
-    # for the future.
-    cfg['transformer_lm']['card'] = 2048
-    cfg['transformer_lm']['n_q'] = 4
-    # Experimental params no longer supported.
-    bad_params = ['spectral_norm_attn_iters', 'spectral_norm_ff_iters',
-                  'residual_balancer_attn', 'residual_balancer_ff', 'layer_drop']
-    for name in bad_params:
-        del cfg['transformer_lm'][name]
-    OmegaConf.set_struct(cfg, True)
-    return cfg
-
-
-def export_encodec(checkpoint_path: tp.Union[Path, str], out_folder: tp.Union[Path, str]):
-    sig = Path(checkpoint_path).parent.name
-    assert len(sig) == 8, "Not a valid Dora signature"
-    pkg = torch.load(checkpoint_path, 'cpu')
-    new_pkg = {
-        'best_state': pkg['ema']['state']['model'],
-        'xp.cfg': OmegaConf.to_yaml(pkg['xp.cfg']),
-    }
-    out_file = Path(out_folder) / f'{sig}.th'
-    torch.save(new_pkg, out_file)
-    return out_file
-
-
-def export_lm(checkpoint_path: tp.Union[Path, str], out_folder: tp.Union[Path, str]):
-    sig = Path(checkpoint_path).parent.name
-    assert len(sig) == 8, "Not a valid Dora signature"
-    pkg = torch.load(checkpoint_path, 'cpu')
-    new_pkg = {
-        'best_state': pkg['fsdp_best_state']['model'],
-        'xp.cfg': OmegaConf.to_yaml(_clean_lm_cfg(pkg['xp.cfg']))
-    }
-    out_file = Path(out_folder) / f'{sig}.th'
-    torch.save(new_pkg, out_file)
-    return out_file
diff --git a/spaces/jbilcke-hf/ai-clip-factory/src/components/ui/separator.tsx b/spaces/jbilcke-hf/ai-clip-factory/src/components/ui/separator.tsx
deleted file mode 100644
index a6ed83ef827829cf42a7b27d1d5714b4473bd1c5..0000000000000000000000000000000000000000
--- a/spaces/jbilcke-hf/ai-clip-factory/src/components/ui/separator.tsx
+++ /dev/null
@@ -1,31 +0,0 @@
-"use client"
-
-import * as React from "react"
-import * as SeparatorPrimitive from "@radix-ui/react-separator"
-
-import { cn } from "@/lib/utils"
-
-const Separator = React.forwardRef<
-  React.ElementRef<typeof SeparatorPrimitive.Root>,
-  React.ComponentPropsWithoutRef<typeof SeparatorPrimitive.Root>
->(
-  (
-    { className, orientation = "horizontal", decorative = true, ...props },
-    ref
-  ) => (
-    <SeparatorPrimitive.Root
-      ref={ref}
-      decorative={decorative}
-      orientation={orientation}
-      className={cn(
-        "shrink-0 bg-stone-200 dark:bg-stone-800",
-        orientation === "horizontal" ? "h-[1px] w-full" : "h-full w-[1px]",
-        className
-      )}
-      {...props}
-    />
-  )
-)
-Separator.displayName = SeparatorPrimitive.Root.displayName
-
-export { Separator }
diff --git a/spaces/jbilcke-hf/ai-comic-factory/src/components/ui/separator.tsx b/spaces/jbilcke-hf/ai-comic-factory/src/components/ui/separator.tsx
deleted file mode 100644
index a6ed83ef827829cf42a7b27d1d5714b4473bd1c5..0000000000000000000000000000000000000000
--- a/spaces/jbilcke-hf/ai-comic-factory/src/components/ui/separator.tsx
+++ /dev/null
@@ -1,31 +0,0 @@
-"use client"
-
-import * as React from "react"
-import * as SeparatorPrimitive from "@radix-ui/react-separator"
-
-import { cn } from "@/lib/utils"
-
-const Separator = React.forwardRef<
-  React.ElementRef<typeof SeparatorPrimitive.Root>,
-  React.ComponentPropsWithoutRef<typeof SeparatorPrimitive.Root>
->(
-  (
-    { className, orientation = "horizontal", decorative = true, ...props },
-    ref
-  ) => (
-    <SeparatorPrimitive.Root
-      ref={ref}
-      decorative={decorative}
-      orientation={orientation}
-      className={cn(
-        "shrink-0 bg-stone-200 dark:bg-stone-800",
-        orientation === "horizontal" ? "h-[1px] w-full" : "h-full w-[1px]",
-        className
-      )}
-      {...props}
-    />
-  )
-)
-Separator.displayName = SeparatorPrimitive.Root.displayName
-
-export { Separator }
diff --git a/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/__init__.py b/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/__init__.py
deleted file mode 100644
index b54fce14b8a029f1355bc8b74c20884e880ee9c4..0000000000000000000000000000000000000000
--- a/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-# Copyright (c) Meta Platforms, Inc. All Rights Reserved
-
-from . import data
-from . import modeling
-from .config import add_ovseg_config
-
-from .test_time_augmentation import SemanticSegmentorWithTTA
-from .ovseg_model import OVSeg, OVSegDEMO
diff --git a/spaces/jetwill/IDEA-CCNL-Taiyi-Stable-Diffusion-1B-Chinese-v0.11/README.md b/spaces/jetwill/IDEA-CCNL-Taiyi-Stable-Diffusion-1B-Chinese-v0.11/README.md
deleted file mode 100644
index 39e3bd8d4c7aee890bebf998bcf9206476ae2b1a..0000000000000000000000000000000000000000
--- a/spaces/jetwill/IDEA-CCNL-Taiyi-Stable-Diffusion-1B-Chinese-v0.11/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: IDEA CCNL Taiyi Stable Diffusion 1B Chinese V0.11
-emoji: 🐢
-colorFrom: gray
-colorTo: purple
-sdk: gradio
-sdk_version: 3.19.1
-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/joaogabriellima/Real-Time-Voice-Cloning/encoder/visualizations.py b/spaces/joaogabriellima/Real-Time-Voice-Cloning/encoder/visualizations.py
deleted file mode 100644
index 980c74f95f1f7df41ebccc983600b2713c0b0502..0000000000000000000000000000000000000000
--- a/spaces/joaogabriellima/Real-Time-Voice-Cloning/encoder/visualizations.py
+++ /dev/null
@@ -1,178 +0,0 @@
-from encoder.data_objects.speaker_verification_dataset import SpeakerVerificationDataset
-from datetime import datetime
-from time import perf_counter as timer
-import matplotlib.pyplot as plt
-import numpy as np
-# import webbrowser
-import visdom
-import umap
-
-colormap = np.array([
-    [76, 255, 0],
-    [0, 127, 70],
-    [255, 0, 0],
-    [255, 217, 38],
-    [0, 135, 255],
-    [165, 0, 165],
-    [255, 167, 255],
-    [0, 255, 255],
-    [255, 96, 38],
-    [142, 76, 0],
-    [33, 0, 127],
-    [0, 0, 0],
-    [183, 183, 183],
-], dtype=np.float) / 255 
-
-
-class Visualizations:
-    def __init__(self, env_name=None, update_every=10, server="http://localhost", disabled=False):
-        # Tracking data
-        self.last_update_timestamp = timer()
-        self.update_every = update_every
-        self.step_times = []
-        self.losses = []
-        self.eers = []
-        print("Updating the visualizations every %d steps." % update_every)
-        
-        # If visdom is disabled TODO: use a better paradigm for that
-        self.disabled = disabled    
-        if self.disabled:
-            return 
-        
-        # Set the environment name
-        now = str(datetime.now().strftime("%d-%m %Hh%M"))
-        if env_name is None:
-            self.env_name = now
-        else:
-            self.env_name = "%s (%s)" % (env_name, now)
-        
-        # Connect to visdom and open the corresponding window in the browser
-        try:
-            self.vis = visdom.Visdom(server, env=self.env_name, raise_exceptions=True)
-        except ConnectionError:
-            raise Exception("No visdom server detected. Run the command \"visdom\" in your CLI to "
-                            "start it.")
-        # webbrowser.open("http://localhost:8097/env/" + self.env_name)
-        
-        # Create the windows
-        self.loss_win = None
-        self.eer_win = None
-        # self.lr_win = None
-        self.implementation_win = None
-        self.projection_win = None
-        self.implementation_string = ""
-        
-    def log_params(self):
-        if self.disabled:
-            return 
-        from encoder import params_data
-        from encoder import params_model
-        param_string = "<b>Model parameters</b>:<br>"
-        for param_name in (p for p in dir(params_model) if not p.startswith("__")):
-            value = getattr(params_model, param_name)
-            param_string += "\t%s: %s<br>" % (param_name, value)
-        param_string += "<b>Data parameters</b>:<br>"
-        for param_name in (p for p in dir(params_data) if not p.startswith("__")):
-            value = getattr(params_data, param_name)
-            param_string += "\t%s: %s<br>" % (param_name, value)
-        self.vis.text(param_string, opts={"title": "Parameters"})
-        
-    def log_dataset(self, dataset: SpeakerVerificationDataset):
-        if self.disabled:
-            return 
-        dataset_string = ""
-        dataset_string += "<b>Speakers</b>: %s\n" % len(dataset.speakers)
-        dataset_string += "\n" + dataset.get_logs()
-        dataset_string = dataset_string.replace("\n", "<br>")
-        self.vis.text(dataset_string, opts={"title": "Dataset"})
-        
-    def log_implementation(self, params):
-        if self.disabled:
-            return 
-        implementation_string = ""
-        for param, value in params.items():
-            implementation_string += "<b>%s</b>: %s\n" % (param, value)
-            implementation_string = implementation_string.replace("\n", "<br>")
-        self.implementation_string = implementation_string
-        self.implementation_win = self.vis.text(
-            implementation_string, 
-            opts={"title": "Training implementation"}
-        )
-
-    def update(self, loss, eer, step):
-        # Update the tracking data
-        now = timer()
-        self.step_times.append(1000 * (now - self.last_update_timestamp))
-        self.last_update_timestamp = now
-        self.losses.append(loss)
-        self.eers.append(eer)
-        print(".", end="")
-        
-        # Update the plots every <update_every> steps
-        if step % self.update_every != 0:
-            return
-        time_string = "Step time:  mean: %5dms  std: %5dms" % \
-                      (int(np.mean(self.step_times)), int(np.std(self.step_times)))
-        print("\nStep %6d   Loss: %.4f   EER: %.4f   %s" %
-              (step, np.mean(self.losses), np.mean(self.eers), time_string))
-        if not self.disabled:
-            self.loss_win = self.vis.line(
-                [np.mean(self.losses)],
-                [step],
-                win=self.loss_win,
-                update="append" if self.loss_win else None,
-                opts=dict(
-                    legend=["Avg. loss"],
-                    xlabel="Step",
-                    ylabel="Loss",
-                    title="Loss",
-                )
-            )
-            self.eer_win = self.vis.line(
-                [np.mean(self.eers)],
-                [step],
-                win=self.eer_win,
-                update="append" if self.eer_win else None,
-                opts=dict(
-                    legend=["Avg. EER"],
-                    xlabel="Step",
-                    ylabel="EER",
-                    title="Equal error rate"
-                )
-            )
-            if self.implementation_win is not None:
-                self.vis.text(
-                    self.implementation_string + ("<b>%s</b>" % time_string), 
-                    win=self.implementation_win,
-                    opts={"title": "Training implementation"},
-                )
-
-        # Reset the tracking
-        self.losses.clear()
-        self.eers.clear()
-        self.step_times.clear()
-        
-    def draw_projections(self, embeds, utterances_per_speaker, step, out_fpath=None,
-                         max_speakers=10):
-        max_speakers = min(max_speakers, len(colormap))
-        embeds = embeds[:max_speakers * utterances_per_speaker]
-        
-        n_speakers = len(embeds) // utterances_per_speaker
-        ground_truth = np.repeat(np.arange(n_speakers), utterances_per_speaker)
-        colors = [colormap[i] for i in ground_truth]
-        
-        reducer = umap.UMAP()
-        projected = reducer.fit_transform(embeds)
-        plt.scatter(projected[:, 0], projected[:, 1], c=colors)
-        plt.gca().set_aspect("equal", "datalim")
-        plt.title("UMAP projection (step %d)" % step)
-        if not self.disabled:
-            self.projection_win = self.vis.matplot(plt, win=self.projection_win)
-        if out_fpath is not None:
-            plt.savefig(out_fpath)
-        plt.clf()
-        
-    def save(self):
-        if not self.disabled:
-            self.vis.save([self.env_name])
-        
\ No newline at end of file
diff --git a/spaces/joaogabriellima/Real-Time-Voice-Cloning/vocoder/audio.py b/spaces/joaogabriellima/Real-Time-Voice-Cloning/vocoder/audio.py
deleted file mode 100644
index 116396261e184b9968971bd06fabc6f525e0c2fe..0000000000000000000000000000000000000000
--- a/spaces/joaogabriellima/Real-Time-Voice-Cloning/vocoder/audio.py
+++ /dev/null
@@ -1,108 +0,0 @@
-import math
-import numpy as np
-import librosa
-import vocoder.hparams as hp
-from scipy.signal import lfilter
-import soundfile as sf
-
-
-def label_2_float(x, bits) :
-    return 2 * x / (2**bits - 1.) - 1.
-
-
-def float_2_label(x, bits) :
-    assert abs(x).max() <= 1.0
-    x = (x + 1.) * (2**bits - 1) / 2
-    return x.clip(0, 2**bits - 1)
-
-
-def load_wav(path) :
-    return librosa.load(str(path), sr=hp.sample_rate)[0]
-
-
-def save_wav(x, path) :
-    sf.write(path, x.astype(np.float32), hp.sample_rate)
-
-
-def split_signal(x) :
-    unsigned = x + 2**15
-    coarse = unsigned // 256
-    fine = unsigned % 256
-    return coarse, fine
-
-
-def combine_signal(coarse, fine) :
-    return coarse * 256 + fine - 2**15
-
-
-def encode_16bits(x) :
-    return np.clip(x * 2**15, -2**15, 2**15 - 1).astype(np.int16)
-
-
-mel_basis = None
-
-
-def linear_to_mel(spectrogram):
-    global mel_basis
-    if mel_basis is None:
-        mel_basis = build_mel_basis()
-    return np.dot(mel_basis, spectrogram)
-
-
-def build_mel_basis():
-    return librosa.filters.mel(hp.sample_rate, hp.n_fft, n_mels=hp.num_mels, fmin=hp.fmin)
-
-
-def normalize(S):
-    return np.clip((S - hp.min_level_db) / -hp.min_level_db, 0, 1)
-
-
-def denormalize(S):
-    return (np.clip(S, 0, 1) * -hp.min_level_db) + hp.min_level_db
-
-
-def amp_to_db(x):
-    return 20 * np.log10(np.maximum(1e-5, x))
-
-
-def db_to_amp(x):
-    return np.power(10.0, x * 0.05)
-
-
-def spectrogram(y):
-    D = stft(y)
-    S = amp_to_db(np.abs(D)) - hp.ref_level_db
-    return normalize(S)
-
-
-def melspectrogram(y):
-    D = stft(y)
-    S = amp_to_db(linear_to_mel(np.abs(D)))
-    return normalize(S)
-
-
-def stft(y):
-    return librosa.stft(y=y, n_fft=hp.n_fft, hop_length=hp.hop_length, win_length=hp.win_length)
-
-
-def pre_emphasis(x):
-    return lfilter([1, -hp.preemphasis], [1], x)
-
-
-def de_emphasis(x):
-    return lfilter([1], [1, -hp.preemphasis], x)
-
-
-def encode_mu_law(x, mu) :
-    mu = mu - 1
-    fx = np.sign(x) * np.log(1 + mu * np.abs(x)) / np.log(1 + mu)
-    return np.floor((fx + 1) / 2 * mu + 0.5)
-
-
-def decode_mu_law(y, mu, from_labels=True) :
-    if from_labels: 
-        y = label_2_float(y, math.log2(mu))
-    mu = mu - 1
-    x = np.sign(y) / mu * ((1 + mu) ** np.abs(y) - 1)
-    return x
-
diff --git a/spaces/joaogante/assisted_generation_demo/README.md b/spaces/joaogante/assisted_generation_demo/README.md
deleted file mode 100644
index aef7ea7302fde2eccc0fd136bd13985330956495..0000000000000000000000000000000000000000
--- a/spaces/joaogante/assisted_generation_demo/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Assisted Generation Demo
-emoji: ⚡
-colorFrom: gray
-colorTo: purple
-sdk: gradio
-sdk_version: 3.28.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/anyio/lowlevel.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/anyio/lowlevel.py
deleted file mode 100644
index 0e908c65474402fa89fe933d65205378c543e3bf..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/anyio/lowlevel.py
+++ /dev/null
@@ -1,174 +0,0 @@
-from __future__ import annotations
-
-import enum
-import sys
-from dataclasses import dataclass
-from typing import Any, Generic, TypeVar, overload
-from weakref import WeakKeyDictionary
-
-from ._core._eventloop import get_asynclib
-
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-T = TypeVar("T")
-D = TypeVar("D")
-
-
-async def checkpoint() -> None:
-    """
-    Check for cancellation and allow the scheduler to switch to another task.
-
-    Equivalent to (but more efficient than)::
-
-        await checkpoint_if_cancelled()
-        await cancel_shielded_checkpoint()
-
-
-    .. versionadded:: 3.0
-
-    """
-    await get_asynclib().checkpoint()
-
-
-async def checkpoint_if_cancelled() -> None:
-    """
-    Enter a checkpoint if the enclosing cancel scope has been cancelled.
-
-    This does not allow the scheduler to switch to a different task.
-
-    .. versionadded:: 3.0
-
-    """
-    await get_asynclib().checkpoint_if_cancelled()
-
-
-async def cancel_shielded_checkpoint() -> None:
-    """
-    Allow the scheduler to switch to another task but without checking for cancellation.
-
-    Equivalent to (but potentially more efficient than)::
-
-        with CancelScope(shield=True):
-            await checkpoint()
-
-
-    .. versionadded:: 3.0
-
-    """
-    await get_asynclib().cancel_shielded_checkpoint()
-
-
-def current_token() -> object:
-    """Return a backend specific token object that can be used to get back to the event loop."""
-    return get_asynclib().current_token()
-
-
-_run_vars: WeakKeyDictionary[Any, dict[str, Any]] = WeakKeyDictionary()
-_token_wrappers: dict[Any, _TokenWrapper] = {}
-
-
-@dataclass(frozen=True)
-class _TokenWrapper:
-    __slots__ = "_token", "__weakref__"
-    _token: object
-
-
-class _NoValueSet(enum.Enum):
-    NO_VALUE_SET = enum.auto()
-
-
-class RunvarToken(Generic[T]):
-    __slots__ = "_var", "_value", "_redeemed"
-
-    def __init__(self, var: RunVar[T], value: T | Literal[_NoValueSet.NO_VALUE_SET]):
-        self._var = var
-        self._value: T | Literal[_NoValueSet.NO_VALUE_SET] = value
-        self._redeemed = False
-
-
-class RunVar(Generic[T]):
-    """
-    Like a :class:`~contextvars.ContextVar`, except scoped to the running event loop.
-    """
-
-    __slots__ = "_name", "_default"
-
-    NO_VALUE_SET: Literal[_NoValueSet.NO_VALUE_SET] = _NoValueSet.NO_VALUE_SET
-
-    _token_wrappers: set[_TokenWrapper] = set()
-
-    def __init__(
-        self,
-        name: str,
-        default: T | Literal[_NoValueSet.NO_VALUE_SET] = NO_VALUE_SET,
-    ):
-        self._name = name
-        self._default = default
-
-    @property
-    def _current_vars(self) -> dict[str, T]:
-        token = current_token()
-        while True:
-            try:
-                return _run_vars[token]
-            except TypeError:
-                # Happens when token isn't weak referable (TrioToken).
-                # This workaround does mean that some memory will leak on Trio until the problem
-                # is fixed on their end.
-                token = _TokenWrapper(token)
-                self._token_wrappers.add(token)
-            except KeyError:
-                run_vars = _run_vars[token] = {}
-                return run_vars
-
-    @overload
-    def get(self, default: D) -> T | D:
-        ...
-
-    @overload
-    def get(self) -> T:
-        ...
-
-    def get(
-        self, default: D | Literal[_NoValueSet.NO_VALUE_SET] = NO_VALUE_SET
-    ) -> T | D:
-        try:
-            return self._current_vars[self._name]
-        except KeyError:
-            if default is not RunVar.NO_VALUE_SET:
-                return default
-            elif self._default is not RunVar.NO_VALUE_SET:
-                return self._default
-
-        raise LookupError(
-            f'Run variable "{self._name}" has no value and no default set'
-        )
-
-    def set(self, value: T) -> RunvarToken[T]:
-        current_vars = self._current_vars
-        token = RunvarToken(self, current_vars.get(self._name, RunVar.NO_VALUE_SET))
-        current_vars[self._name] = value
-        return token
-
-    def reset(self, token: RunvarToken[T]) -> None:
-        if token._var is not self:
-            raise ValueError("This token does not belong to this RunVar")
-
-        if token._redeemed:
-            raise ValueError("This token has already been used")
-
-        if token._value is _NoValueSet.NO_VALUE_SET:
-            try:
-                del self._current_vars[self._name]
-            except KeyError:
-                pass
-        else:
-            self._current_vars[self._name] = token._value
-
-        token._redeemed = True
-
-    def __repr__(self) -> str:
-        return f"<RunVar name={self._name!r}>"
diff --git a/spaces/johnskyper/demo/README.md b/spaces/johnskyper/demo/README.md
deleted file mode 100644
index 81997ccd48b8ef8b55b894b38f3312940126c6ca..0000000000000000000000000000000000000000
--- a/spaces/johnskyper/demo/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Demo
-emoji: 🏃
-colorFrom: blue
-colorTo: gray
-sdk: gradio
-sdk_version: 3.43.2
-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/kahnchana/clippy/README.md b/spaces/kahnchana/clippy/README.md
deleted file mode 100644
index dcf54646794226e210c581c696cb90cd20d3203a..0000000000000000000000000000000000000000
--- a/spaces/kahnchana/clippy/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Clippy
-emoji: 🏢
-colorFrom: gray
-colorTo: red
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: cc
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/kasjkldjsalkj/fyodorahitevoy/README.md b/spaces/kasjkldjsalkj/fyodorahitevoy/README.md
deleted file mode 100644
index 8c93c544dc134a7f3b9deb52416b6f31fab939b5..0000000000000000000000000000000000000000
--- a/spaces/kasjkldjsalkj/fyodorahitevoy/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: Fyodorahitevoy
-emoji: ⚡
-colorFrom: indigo
-colorTo: purple
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/keminglu/instruction-following-open-world-information-extraction/README.md b/spaces/keminglu/instruction-following-open-world-information-extraction/README.md
deleted file mode 100644
index a6b0600c115d91e980f97b906fa3031f699d6d31..0000000000000000000000000000000000000000
--- a/spaces/keminglu/instruction-following-open-world-information-extraction/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Instruction Following Open World Information Extraction
-emoji: 🔥
-colorFrom: yellow
-colorTo: red
-sdk: gradio
-sdk_version: 3.28.2
-app_file: app.py
-pinned: false
-license: bigscience-openrail-m
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/kernelmachine/gpt3-quality-filter/lr/merge.py b/spaces/kernelmachine/gpt3-quality-filter/lr/merge.py
deleted file mode 100644
index 8be00157a48b73dc6f5c1d1e855a6ef7e271fed9..0000000000000000000000000000000000000000
--- a/spaces/kernelmachine/gpt3-quality-filter/lr/merge.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import argparse
-import json
-import logging
-import os
-import pathlib
-from typing import Any, Dict, List, Union
-import sys
-import pandas as pd
-
-# Create a custom logger
-logger = logging.getLogger(__name__)
-logger.setLevel(logging.DEBUG)
-
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--experiments', nargs="+", type=str)
-    parser.add_argument('--output', type=str)
-
-    args = parser.parse_args()
-    dfs = []
-    for experiment in args.experiments:
-        if not os.path.isdir(experiment):
-            print(f"experiment {experiment} does not exist. Aborting! ")
-            sys.exit(1)
-        else:
-            dfs.append(pd.read_json(os.path.join(experiment, "results.jsonl"), lines=True))
-    master = pd.concat(dfs, 0)
-    master.to_json(args.output, lines=True, orient='records')
\ No newline at end of file
diff --git a/spaces/kevinwang676/ChatGLM2-SadTalker-VC/src/face3d/models/arcface_torch/losses.py b/spaces/kevinwang676/ChatGLM2-SadTalker-VC/src/face3d/models/arcface_torch/losses.py
deleted file mode 100644
index 87aeaa107af4d53f5a6132b3739d5cafdcded7fc..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/ChatGLM2-SadTalker-VC/src/face3d/models/arcface_torch/losses.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import torch
-from torch import nn
-
-
-def get_loss(name):
-    if name == "cosface":
-        return CosFace()
-    elif name == "arcface":
-        return ArcFace()
-    else:
-        raise ValueError()
-
-
-class CosFace(nn.Module):
-    def __init__(self, s=64.0, m=0.40):
-        super(CosFace, self).__init__()
-        self.s = s
-        self.m = m
-
-    def forward(self, cosine, label):
-        index = torch.where(label != -1)[0]
-        m_hot = torch.zeros(index.size()[0], cosine.size()[1], device=cosine.device)
-        m_hot.scatter_(1, label[index, None], self.m)
-        cosine[index] -= m_hot
-        ret = cosine * self.s
-        return ret
-
-
-class ArcFace(nn.Module):
-    def __init__(self, s=64.0, m=0.5):
-        super(ArcFace, self).__init__()
-        self.s = s
-        self.m = m
-
-    def forward(self, cosine: torch.Tensor, label):
-        index = torch.where(label != -1)[0]
-        m_hot = torch.zeros(index.size()[0], cosine.size()[1], device=cosine.device)
-        m_hot.scatter_(1, label[index, None], self.m)
-        cosine.acos_()
-        cosine[index] += m_hot
-        cosine.cos_().mul_(self.s)
-        return cosine
diff --git a/spaces/kevinwang676/ControlNet-with-GPT-4/app_depth.py b/spaces/kevinwang676/ControlNet-with-GPT-4/app_depth.py
deleted file mode 100644
index fdce423a5609e2e9cfe55502d758f38b4367df17..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/ControlNet-with-GPT-4/app_depth.py
+++ /dev/null
@@ -1,95 +0,0 @@
-#!/usr/bin/env python
-
-import gradio as gr
-
-from settings import (
-    DEFAULT_IMAGE_RESOLUTION,
-    DEFAULT_NUM_IMAGES,
-    MAX_IMAGE_RESOLUTION,
-    MAX_NUM_IMAGES,
-    MAX_SEED,
-)
-from utils import randomize_seed_fn
-
-
-def create_demo(process):
-    with gr.Blocks() as demo:
-        with gr.Row():
-            with gr.Column():
-                image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
-                with gr.Accordion("Advanced options", open=False):
-                    preprocessor_name = gr.Radio(
-                        label="Preprocessor", choices=["Midas", "DPT", "None"], type="value", value="DPT"
-                    )
-                    num_samples = gr.Slider(
-                        label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
-                    )
-                    image_resolution = gr.Slider(
-                        label="Image resolution",
-                        minimum=256,
-                        maximum=MAX_IMAGE_RESOLUTION,
-                        value=DEFAULT_IMAGE_RESOLUTION,
-                        step=256,
-                    )
-                    preprocess_resolution = gr.Slider(
-                        label="Preprocess resolution", minimum=128, maximum=512, value=384, step=1
-                    )
-                    num_steps = gr.Slider(label="Number of steps", minimum=1, maximum=100, value=20, step=1)
-                    guidance_scale = gr.Slider(label="Guidance scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
-                    randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                    a_prompt = gr.Textbox(label="Additional prompt", value="best quality, extremely detailed")
-                    n_prompt = gr.Textbox(
-                        label="Negative prompt",
-                        value="longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
-                    )
-            with gr.Column():
-                result = gr.Gallery(label="Output", show_label=False, columns=2, object_fit="scale-down")
-        inputs = [
-            image,
-            prompt,
-            a_prompt,
-            n_prompt,
-            num_samples,
-            image_resolution,
-            preprocess_resolution,
-            num_steps,
-            guidance_scale,
-            seed,
-            preprocessor_name,
-        ]
-        prompt.submit(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name="depth",
-        )
-    return demo
-
-
-if __name__ == "__main__":
-    from model import Model
-
-    model = Model(task_name="depth")
-    demo = create_demo(model.process_depth)
-    demo.queue().launch()
diff --git a/spaces/kevinwang676/SadTalker/src/face3d/util/my_awing_arch.py b/spaces/kevinwang676/SadTalker/src/face3d/util/my_awing_arch.py
deleted file mode 100644
index cd5656177dc5a1dde82ffee5d43434bc5e69c88e..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/SadTalker/src/face3d/util/my_awing_arch.py
+++ /dev/null
@@ -1,378 +0,0 @@
-import cv2
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-def calculate_points(heatmaps):
-    # change heatmaps to landmarks
-    B, N, H, W = heatmaps.shape
-    HW = H * W
-    BN_range = np.arange(B * N)
-
-    heatline = heatmaps.reshape(B, N, HW)
-    indexes = np.argmax(heatline, axis=2)
-
-    preds = np.stack((indexes % W, indexes // W), axis=2)
-    preds = preds.astype(np.float, copy=False)
-
-    inr = indexes.ravel()
-
-    heatline = heatline.reshape(B * N, HW)
-    x_up = heatline[BN_range, inr + 1]
-    x_down = heatline[BN_range, inr - 1]
-    # y_up = heatline[BN_range, inr + W]
-
-    if any((inr + W) >= 4096):
-        y_up = heatline[BN_range, 4095]
-    else:
-        y_up = heatline[BN_range, inr + W]
-    if any((inr - W) <= 0):
-        y_down = heatline[BN_range, 0]
-    else:
-        y_down = heatline[BN_range, inr - W]
-
-    think_diff = np.sign(np.stack((x_up - x_down, y_up - y_down), axis=1))
-    think_diff *= .25
-
-    preds += think_diff.reshape(B, N, 2)
-    preds += .5
-    return preds
-
-
-class AddCoordsTh(nn.Module):
-
-    def __init__(self, x_dim=64, y_dim=64, with_r=False, with_boundary=False):
-        super(AddCoordsTh, self).__init__()
-        self.x_dim = x_dim
-        self.y_dim = y_dim
-        self.with_r = with_r
-        self.with_boundary = with_boundary
-
-    def forward(self, input_tensor, heatmap=None):
-        """
-        input_tensor: (batch, c, x_dim, y_dim)
-        """
-        batch_size_tensor = input_tensor.shape[0]
-
-        xx_ones = torch.ones([1, self.y_dim], dtype=torch.int32, device=input_tensor.device)
-        xx_ones = xx_ones.unsqueeze(-1)
-
-        xx_range = torch.arange(self.x_dim, dtype=torch.int32, device=input_tensor.device).unsqueeze(0)
-        xx_range = xx_range.unsqueeze(1)
-
-        xx_channel = torch.matmul(xx_ones.float(), xx_range.float())
-        xx_channel = xx_channel.unsqueeze(-1)
-
-        yy_ones = torch.ones([1, self.x_dim], dtype=torch.int32, device=input_tensor.device)
-        yy_ones = yy_ones.unsqueeze(1)
-
-        yy_range = torch.arange(self.y_dim, dtype=torch.int32, device=input_tensor.device).unsqueeze(0)
-        yy_range = yy_range.unsqueeze(-1)
-
-        yy_channel = torch.matmul(yy_range.float(), yy_ones.float())
-        yy_channel = yy_channel.unsqueeze(-1)
-
-        xx_channel = xx_channel.permute(0, 3, 2, 1)
-        yy_channel = yy_channel.permute(0, 3, 2, 1)
-
-        xx_channel = xx_channel / (self.x_dim - 1)
-        yy_channel = yy_channel / (self.y_dim - 1)
-
-        xx_channel = xx_channel * 2 - 1
-        yy_channel = yy_channel * 2 - 1
-
-        xx_channel = xx_channel.repeat(batch_size_tensor, 1, 1, 1)
-        yy_channel = yy_channel.repeat(batch_size_tensor, 1, 1, 1)
-
-        if self.with_boundary and heatmap is not None:
-            boundary_channel = torch.clamp(heatmap[:, -1:, :, :], 0.0, 1.0)
-
-            zero_tensor = torch.zeros_like(xx_channel)
-            xx_boundary_channel = torch.where(boundary_channel > 0.05, xx_channel, zero_tensor)
-            yy_boundary_channel = torch.where(boundary_channel > 0.05, yy_channel, zero_tensor)
-        if self.with_boundary and heatmap is not None:
-            xx_boundary_channel = xx_boundary_channel.to(input_tensor.device)
-            yy_boundary_channel = yy_boundary_channel.to(input_tensor.device)
-        ret = torch.cat([input_tensor, xx_channel, yy_channel], dim=1)
-
-        if self.with_r:
-            rr = torch.sqrt(torch.pow(xx_channel, 2) + torch.pow(yy_channel, 2))
-            rr = rr / torch.max(rr)
-            ret = torch.cat([ret, rr], dim=1)
-
-        if self.with_boundary and heatmap is not None:
-            ret = torch.cat([ret, xx_boundary_channel, yy_boundary_channel], dim=1)
-        return ret
-
-
-class CoordConvTh(nn.Module):
-    """CoordConv layer as in the paper."""
-
-    def __init__(self, x_dim, y_dim, with_r, with_boundary, in_channels, first_one=False, *args, **kwargs):
-        super(CoordConvTh, self).__init__()
-        self.addcoords = AddCoordsTh(x_dim=x_dim, y_dim=y_dim, with_r=with_r, with_boundary=with_boundary)
-        in_channels += 2
-        if with_r:
-            in_channels += 1
-        if with_boundary and not first_one:
-            in_channels += 2
-        self.conv = nn.Conv2d(in_channels=in_channels, *args, **kwargs)
-
-    def forward(self, input_tensor, heatmap=None):
-        ret = self.addcoords(input_tensor, heatmap)
-        last_channel = ret[:, -2:, :, :]
-        ret = self.conv(ret)
-        return ret, last_channel
-
-
-def conv3x3(in_planes, out_planes, strd=1, padding=1, bias=False, dilation=1):
-    '3x3 convolution with padding'
-    return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=strd, padding=padding, bias=bias, dilation=dilation)
-
-
-class BasicBlock(nn.Module):
-    expansion = 1
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None):
-        super(BasicBlock, self).__init__()
-        self.conv1 = conv3x3(inplanes, planes, stride)
-        # self.bn1 = nn.BatchNorm2d(planes)
-        self.relu = nn.ReLU(inplace=True)
-        self.conv2 = conv3x3(planes, planes)
-        # self.bn2 = nn.BatchNorm2d(planes)
-        self.downsample = downsample
-        self.stride = stride
-
-    def forward(self, x):
-        residual = x
-
-        out = self.conv1(x)
-        out = self.relu(out)
-
-        out = self.conv2(out)
-
-        if self.downsample is not None:
-            residual = self.downsample(x)
-
-        out += residual
-        out = self.relu(out)
-
-        return out
-
-
-class ConvBlock(nn.Module):
-
-    def __init__(self, in_planes, out_planes):
-        super(ConvBlock, self).__init__()
-        self.bn1 = nn.BatchNorm2d(in_planes)
-        self.conv1 = conv3x3(in_planes, int(out_planes / 2))
-        self.bn2 = nn.BatchNorm2d(int(out_planes / 2))
-        self.conv2 = conv3x3(int(out_planes / 2), int(out_planes / 4), padding=1, dilation=1)
-        self.bn3 = nn.BatchNorm2d(int(out_planes / 4))
-        self.conv3 = conv3x3(int(out_planes / 4), int(out_planes / 4), padding=1, dilation=1)
-
-        if in_planes != out_planes:
-            self.downsample = nn.Sequential(
-                nn.BatchNorm2d(in_planes),
-                nn.ReLU(True),
-                nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1, bias=False),
-            )
-        else:
-            self.downsample = None
-
-    def forward(self, x):
-        residual = x
-
-        out1 = self.bn1(x)
-        out1 = F.relu(out1, True)
-        out1 = self.conv1(out1)
-
-        out2 = self.bn2(out1)
-        out2 = F.relu(out2, True)
-        out2 = self.conv2(out2)
-
-        out3 = self.bn3(out2)
-        out3 = F.relu(out3, True)
-        out3 = self.conv3(out3)
-
-        out3 = torch.cat((out1, out2, out3), 1)
-
-        if self.downsample is not None:
-            residual = self.downsample(residual)
-
-        out3 += residual
-
-        return out3
-
-
-class HourGlass(nn.Module):
-
-    def __init__(self, num_modules, depth, num_features, first_one=False):
-        super(HourGlass, self).__init__()
-        self.num_modules = num_modules
-        self.depth = depth
-        self.features = num_features
-        self.coordconv = CoordConvTh(
-            x_dim=64,
-            y_dim=64,
-            with_r=True,
-            with_boundary=True,
-            in_channels=256,
-            first_one=first_one,
-            out_channels=256,
-            kernel_size=1,
-            stride=1,
-            padding=0)
-        self._generate_network(self.depth)
-
-    def _generate_network(self, level):
-        self.add_module('b1_' + str(level), ConvBlock(256, 256))
-
-        self.add_module('b2_' + str(level), ConvBlock(256, 256))
-
-        if level > 1:
-            self._generate_network(level - 1)
-        else:
-            self.add_module('b2_plus_' + str(level), ConvBlock(256, 256))
-
-        self.add_module('b3_' + str(level), ConvBlock(256, 256))
-
-    def _forward(self, level, inp):
-        # Upper branch
-        up1 = inp
-        up1 = self._modules['b1_' + str(level)](up1)
-
-        # Lower branch
-        low1 = F.avg_pool2d(inp, 2, stride=2)
-        low1 = self._modules['b2_' + str(level)](low1)
-
-        if level > 1:
-            low2 = self._forward(level - 1, low1)
-        else:
-            low2 = low1
-            low2 = self._modules['b2_plus_' + str(level)](low2)
-
-        low3 = low2
-        low3 = self._modules['b3_' + str(level)](low3)
-
-        up2 = F.interpolate(low3, scale_factor=2, mode='nearest')
-
-        return up1 + up2
-
-    def forward(self, x, heatmap):
-        x, last_channel = self.coordconv(x, heatmap)
-        return self._forward(self.depth, x), last_channel
-
-
-class FAN(nn.Module):
-
-    def __init__(self, num_modules=1, end_relu=False, gray_scale=False, num_landmarks=68, device='cuda'):
-        super(FAN, self).__init__()
-        self.device = device
-        self.num_modules = num_modules
-        self.gray_scale = gray_scale
-        self.end_relu = end_relu
-        self.num_landmarks = num_landmarks
-
-        # Base part
-        if self.gray_scale:
-            self.conv1 = CoordConvTh(
-                x_dim=256,
-                y_dim=256,
-                with_r=True,
-                with_boundary=False,
-                in_channels=3,
-                out_channels=64,
-                kernel_size=7,
-                stride=2,
-                padding=3)
-        else:
-            self.conv1 = CoordConvTh(
-                x_dim=256,
-                y_dim=256,
-                with_r=True,
-                with_boundary=False,
-                in_channels=3,
-                out_channels=64,
-                kernel_size=7,
-                stride=2,
-                padding=3)
-        self.bn1 = nn.BatchNorm2d(64)
-        self.conv2 = ConvBlock(64, 128)
-        self.conv3 = ConvBlock(128, 128)
-        self.conv4 = ConvBlock(128, 256)
-
-        # Stacking part
-        for hg_module in range(self.num_modules):
-            if hg_module == 0:
-                first_one = True
-            else:
-                first_one = False
-            self.add_module('m' + str(hg_module), HourGlass(1, 4, 256, first_one))
-            self.add_module('top_m_' + str(hg_module), ConvBlock(256, 256))
-            self.add_module('conv_last' + str(hg_module), nn.Conv2d(256, 256, kernel_size=1, stride=1, padding=0))
-            self.add_module('bn_end' + str(hg_module), nn.BatchNorm2d(256))
-            self.add_module('l' + str(hg_module), nn.Conv2d(256, num_landmarks + 1, kernel_size=1, stride=1, padding=0))
-
-            if hg_module < self.num_modules - 1:
-                self.add_module('bl' + str(hg_module), nn.Conv2d(256, 256, kernel_size=1, stride=1, padding=0))
-                self.add_module('al' + str(hg_module),
-                                nn.Conv2d(num_landmarks + 1, 256, kernel_size=1, stride=1, padding=0))
-
-    def forward(self, x):
-        x, _ = self.conv1(x)
-        x = F.relu(self.bn1(x), True)
-        # x = F.relu(self.bn1(self.conv1(x)), True)
-        x = F.avg_pool2d(self.conv2(x), 2, stride=2)
-        x = self.conv3(x)
-        x = self.conv4(x)
-
-        previous = x
-
-        outputs = []
-        boundary_channels = []
-        tmp_out = None
-        for i in range(self.num_modules):
-            hg, boundary_channel = self._modules['m' + str(i)](previous, tmp_out)
-
-            ll = hg
-            ll = self._modules['top_m_' + str(i)](ll)
-
-            ll = F.relu(self._modules['bn_end' + str(i)](self._modules['conv_last' + str(i)](ll)), True)
-
-            # Predict heatmaps
-            tmp_out = self._modules['l' + str(i)](ll)
-            if self.end_relu:
-                tmp_out = F.relu(tmp_out)  # HACK: Added relu
-            outputs.append(tmp_out)
-            boundary_channels.append(boundary_channel)
-
-            if i < self.num_modules - 1:
-                ll = self._modules['bl' + str(i)](ll)
-                tmp_out_ = self._modules['al' + str(i)](tmp_out)
-                previous = previous + ll + tmp_out_
-
-        return outputs, boundary_channels
-
-    def get_landmarks(self, img):
-        H, W, _ = img.shape
-        offset = W / 64, H / 64, 0, 0
-
-        img = cv2.resize(img, (256, 256))
-        inp = img[..., ::-1]
-        inp = torch.from_numpy(np.ascontiguousarray(inp.transpose((2, 0, 1)))).float()
-        inp = inp.to(self.device)
-        inp.div_(255.0).unsqueeze_(0)
-
-        outputs, _ = self.forward(inp)
-        out = outputs[-1][:, :-1, :, :]
-        heatmaps = out.detach().cpu().numpy()
-
-        pred = calculate_points(heatmaps).reshape(-1, 2)
-
-        pred *= offset[:2]
-        pred += offset[-2:]
-
-        return pred
diff --git a/spaces/kevinwang676/Voice-Cloning-for-YouTube/app.py b/spaces/kevinwang676/Voice-Cloning-for-YouTube/app.py
deleted file mode 100644
index 900e2765f0a855825a944fb680071eebebed05e8..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/Voice-Cloning-for-YouTube/app.py
+++ /dev/null
@@ -1,253 +0,0 @@
-import json
-import os
-import subprocess
-from pathlib import Path
-
-import gradio as gr
-import librosa
-import numpy as np
-import torch
-from demucs.apply import apply_model
-from demucs.pretrained import DEFAULT_MODEL, get_model
-from huggingface_hub import hf_hub_download, list_repo_files
-
-from so_vits_svc_fork.hparams import HParams
-from so_vits_svc_fork.inference.core import Svc
-
-
-###################################################################
-# REPLACE THESE VALUES TO CHANGE THE MODEL REPO/CKPT NAME/SETTINGS
-###################################################################
-# The Hugging Face Hub repo ID - 在这里修改repo_id，可替换成任何已经训练好的模型！
-repo_id = "kevinwang676/talktalkai-qing"
-
-# If None, Uses latest ckpt in the repo
-ckpt_name = None
-
-# If None, Uses "kmeans.pt" if it exists in the repo
-cluster_model_name = None
-
-# Set the default f0 type to use - use the one it was trained on.
-# The default for so-vits-svc-fork is "dio".
-# Options: "crepe", "crepe-tiny", "parselmouth", "dio", "harvest"
-default_f0_method = "crepe"
-
-# The default ratio of cluster inference to SVC inference.
-# If cluster_model_name is not found in the repo, this is set to 0.
-default_cluster_infer_ratio = 0.5
-
-# Limit on duration of audio at inference time. increase if you can
-# In this parent app, we set the limit with an env var to 30 seconds
-# If you didnt set env var + you go OOM try changing 9e9 to <=300ish
-duration_limit = int(os.environ.get("MAX_DURATION_SECONDS", 9e9))
-###################################################################
-
-# Figure out the latest generator by taking highest value one.
-# Ex. if the repo has: G_0.pth, G_100.pth, G_200.pth, we'd use G_200.pth
-if ckpt_name is None:
-    latest_id = sorted(
-        [
-            int(Path(x).stem.split("_")[1])
-            for x in list_repo_files(repo_id)
-            if x.startswith("G_") and x.endswith(".pth")
-        ]
-    )[-1]
-    ckpt_name = f"G_{latest_id}.pth"
-
-cluster_model_name = cluster_model_name or "kmeans.pt"
-if cluster_model_name in list_repo_files(repo_id):
-    print(f"Found Cluster model - Downloading {cluster_model_name} from {repo_id}")
-    cluster_model_path = hf_hub_download(repo_id, cluster_model_name)
-else:
-    print(f"Could not find {cluster_model_name} in {repo_id}. Using None")
-    cluster_model_path = None
-default_cluster_infer_ratio = default_cluster_infer_ratio if cluster_model_path else 0
-
-generator_path = hf_hub_download(repo_id, ckpt_name)
-config_path = hf_hub_download(repo_id, "config.json")
-hparams = HParams(**json.loads(Path(config_path).read_text()))
-speakers = list(hparams.spk.keys())
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model = Svc(net_g_path=generator_path, config_path=config_path, device=device, cluster_model_path=cluster_model_path)
-demucs_model = get_model(DEFAULT_MODEL)
-
-
-def extract_vocal_demucs(model, filename, sr=44100, device=None, shifts=1, split=True, overlap=0.25, jobs=0):
-    wav, sr = librosa.load(filename, mono=False, sr=sr)
-    wav = torch.tensor(wav)
-    ref = wav.mean(0)
-    wav = (wav - ref.mean()) / ref.std()
-    sources = apply_model(
-        model, wav[None], device=device, shifts=shifts, split=split, overlap=overlap, progress=True, num_workers=jobs
-    )[0]
-    sources = sources * ref.std() + ref.mean()
-    # We take just the vocals stem. I know the vocals for this model are at index -1
-    # If using different model, check model.sources.index('vocals')
-    vocal_wav = sources[-1]
-    # I did this because its the same normalization the so-vits model required
-    vocal_wav = vocal_wav / max(1.01 * vocal_wav.abs().max(), 1)
-    vocal_wav = vocal_wav.numpy()
-    vocal_wav = librosa.to_mono(vocal_wav)
-    vocal_wav = vocal_wav.T
-    instrumental_wav = sources[:-1].sum(0).numpy().T
-    return vocal_wav, instrumental_wav
-
-
-def download_youtube_clip(
-    video_identifier,
-    start_time,
-    end_time,
-    output_filename,
-    num_attempts=5,
-    url_base="https://www.youtube.com/watch?v=",
-    quiet=False,
-    force=False,
-):
-    output_path = Path(output_filename)
-    if output_path.exists():
-        if not force:
-            return output_path
-        else:
-            output_path.unlink()
-
-    quiet = "--quiet --no-warnings" if quiet else ""
-    command = f"""
-        yt-dlp {quiet} -x --audio-format wav -f bestaudio -o "{output_filename}" --download-sections "*{start_time}-{end_time}" "{url_base}{video_identifier}"  # noqa: E501
-    """.strip()
-
-    attempts = 0
-    while True:
-        try:
-            _ = subprocess.check_output(command, shell=True, stderr=subprocess.STDOUT)
-        except subprocess.CalledProcessError:
-            attempts += 1
-            if attempts == num_attempts:
-                return None
-        else:
-            break
-
-    if output_path.exists():
-        return output_path
-    else:
-        return None
-
-
-def predict(
-    speaker,
-    audio,
-    transpose: int = 0,
-    auto_predict_f0: bool = False,
-    cluster_infer_ratio: float = 0,
-    noise_scale: float = 0.4,
-    f0_method: str = "crepe",
-    db_thresh: int = -40,
-    pad_seconds: float = 0.5,
-    chunk_seconds: float = 0.5,
-    absolute_thresh: bool = False,
-):
-    audio, _ = librosa.load(audio, sr=model.target_sample, duration=duration_limit)
-    audio = model.infer_silence(
-        audio.astype(np.float32),
-        speaker=speaker,
-        transpose=transpose,
-        auto_predict_f0=auto_predict_f0,
-        cluster_infer_ratio=cluster_infer_ratio,
-        noise_scale=noise_scale,
-        f0_method=f0_method,
-        db_thresh=db_thresh,
-        pad_seconds=pad_seconds,
-        chunk_seconds=chunk_seconds,
-        absolute_thresh=absolute_thresh,
-    )
-    return model.target_sample, audio
-
-
-def predict_song_from_yt(
-    ytid_or_url,
-    start,
-    end,
-    speaker=speakers[0],
-    transpose: int = 0,
-    auto_predict_f0: bool = False,
-    cluster_infer_ratio: float = 0,
-    noise_scale: float = 0.4,
-    f0_method: str = "dio",
-    db_thresh: int = -40,
-    pad_seconds: float = 0.5,
-    chunk_seconds: float = 0.5,
-    absolute_thresh: bool = False,
-):
-    end = min(start + duration_limit, end)
-    original_track_filepath = download_youtube_clip(
-        ytid_or_url,
-        start,
-        end,
-        "track.wav",
-        force=True,
-        url_base="" if ytid_or_url.startswith("http") else "https://www.youtube.com/watch?v=",
-    )
-    vox_wav, inst_wav = extract_vocal_demucs(demucs_model, original_track_filepath)
-    if transpose != 0:
-        inst_wav = librosa.effects.pitch_shift(inst_wav.T, sr=model.target_sample, n_steps=transpose).T
-    cloned_vox = model.infer_silence(
-        vox_wav.astype(np.float32),
-        speaker=speaker,
-        transpose=transpose,
-        auto_predict_f0=auto_predict_f0,
-        cluster_infer_ratio=cluster_infer_ratio,
-        noise_scale=noise_scale,
-        f0_method=f0_method,
-        db_thresh=db_thresh,
-        pad_seconds=pad_seconds,
-        chunk_seconds=chunk_seconds,
-        absolute_thresh=absolute_thresh,
-    )
-    full_song = inst_wav + np.expand_dims(cloned_vox, 1)
-    return (model.target_sample, full_song), (model.target_sample, cloned_vox)
-
-
-description = f"""
-
-## <center>🏞️ - TalkTalkAI - Generative AI Text to Speech & Singing Voice Conversion</center>
-
-### <center>🌟 - The singer who collaborates with TalkTalkAI: [一清清清](https://space.bilibili.com/22960772?spm_id_from=333.337.0.0)</center>
-
-### <center>🤗 - Stay tuned. The best is yet to come. Contact us: talktalkai.kevin@gmail.com</center>
-
-""".strip()
-
-
-interface_yt = gr.Interface(
-    predict_song_from_yt,
-    inputs=[
-        gr.Textbox(
-            label="YouTube URL or ID", info="A YouTube URL (or ID) to a song on YouTube you want to clone from"
-        ),
-        gr.Number(value=0, label="Start Time (seconds)"),
-        gr.Number(value=15, label="End Time (seconds)"),
-        gr.Dropdown(speakers, value=speakers[0], label="🎤 AI Singer"),
-        gr.Slider(-12, 12, value=0, step=1, label="Transpose (Semitones)"),
-        gr.Checkbox(False, label="Auto Predict F0", visible=False),
-        gr.Slider(0.0, 1.0, value=default_cluster_infer_ratio, step=0.1, label="cluster infer ratio", visible=False),
-        gr.Slider(0.0, 1.0, value=0.4, step=0.1, label="noise scale", visible=False),
-        gr.Dropdown(
-            choices=["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"],
-            value=default_f0_method,
-            label="f0 method", visible=False
-        ),
-    ],
-    outputs=[gr.Audio(label="With BGM🎵"), gr.Audio(label="Without BGM🎤")],
-    title="🌊💕🎶 - TalkTalkAI",
-    description=description,
-    examples=[
-        ["https://www.youtube.com/watch?v=cn4M-fH08XY", 0, 11.4, speakers[0], 0, False, default_cluster_infer_ratio, 0.4, default_f0_method],
-    ],
-)
-interface = gr.TabbedInterface(
-    [interface_yt],
-    ["📺 - Clone Song From YouTube"],
-)
-
-
-if __name__ == "__main__":
-    interface.launch(show_error=True)
diff --git a/spaces/keyikai/bing/README.md b/spaces/keyikai/bing/README.md
deleted file mode 100644
index 864d84303dca71b6653324b3f890387c523f35ca..0000000000000000000000000000000000000000
--- a/spaces/keyikai/bing/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Go Proxy Bingai
-emoji: 📉
-colorFrom: gray
-colorTo: red
-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/kinensake/quanquan/lm_scorer/__init__.py b/spaces/kinensake/quanquan/lm_scorer/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/krazyxki/V-1488abed/src/proxy/routes.ts b/spaces/krazyxki/V-1488abed/src/proxy/routes.ts
deleted file mode 100644
index de1ca0565d3ce6373dac2b3b18845b099bd85bee..0000000000000000000000000000000000000000
--- a/spaces/krazyxki/V-1488abed/src/proxy/routes.ts
+++ /dev/null
@@ -1,33 +0,0 @@
-/* Accepts incoming requests at either the /kobold or /openai routes and then
-routes them to the appropriate handler to be forwarded to the OpenAI API.
-Incoming OpenAI requests are more or less 1:1 with the OpenAI API, but only a
-subset of the API is supported. Kobold requests must be transformed into
-equivalent OpenAI requests. */
-
-import * as express from "express";
-import { auth } from "./auth";
-import { kobold } from "./kobold";
-import { openai } from "./openai";
-
-const router = express.Router();
-
-router.use(auth);
-router.use("/kobold", kobold);
-router.use("/openai", openai);
-
-// SillyTavern annoyingly just disregards the path in whatever URL users input,
-// so requests come in at /api/v1. We need to rewrite them to
-// /proxy/kobold/api/v1 so the request is routed to the correct handler.
-function rewriteTavernRequests(
-  req: express.Request,
-  _res: express.Response,
-  next: express.NextFunction
-) {
-  if (req.path.startsWith("/api/v1")) {
-    req.url = req.url.replace("/api/v1", "/proxy/kobold/api/v1");
-  }
-  next();
-}
-
-export { rewriteTavernRequests };
-export { router as proxyRouter };
diff --git a/spaces/kukuhtw/VToonify/vtoonify/model/stylegan/prepare_data.py b/spaces/kukuhtw/VToonify/vtoonify/model/stylegan/prepare_data.py
deleted file mode 100644
index aa385d0ac13550e1ae5513f7a20b35997a5c3ea6..0000000000000000000000000000000000000000
--- a/spaces/kukuhtw/VToonify/vtoonify/model/stylegan/prepare_data.py
+++ /dev/null
@@ -1,105 +0,0 @@
-import argparse
-from io import BytesIO
-import multiprocessing
-from functools import partial
-
-import os
-from PIL import Image
-import lmdb
-from tqdm import tqdm
-from torchvision import datasets
-from torchvision.transforms import functional as trans_fn
-
-
-def resize_and_convert(img, size, resample, quality=100):
-    img = trans_fn.resize(img, size, resample)
-    img = trans_fn.center_crop(img, size)
-    buffer = BytesIO()
-    img.save(buffer, format="jpeg", quality=quality)
-    val = buffer.getvalue()
-
-    return val
-
-
-def resize_multiple(
-    img, sizes=(128, 256, 512, 1024), resample=Image.LANCZOS, quality=100
-):
-    imgs = []
-
-    for size in sizes:
-        imgs.append(resize_and_convert(img, size, resample, quality))
-
-    return imgs
-
-
-def resize_worker(img_file, sizes, resample):
-    i, file = img_file
-    img = Image.open(file)
-    img = img.convert("RGB")
-    out = resize_multiple(img, sizes=sizes, resample=resample)
-
-    return i, out
-
-
-def prepare(
-    env, dataset, n_worker, sizes=(128, 256, 512, 1024), resample=Image.LANCZOS
-):
-    resize_fn = partial(resize_worker, sizes=sizes, resample=resample)
-
-    files = sorted(dataset.imgs, key=lambda x: x[0])
-    files = [(i, file) for i, (file, label) in enumerate(files)]
-    total = 0
-
-    with multiprocessing.Pool(n_worker) as pool:
-        for i, imgs in tqdm(pool.imap_unordered(resize_fn, files)):
-            for size, img in zip(sizes, imgs):
-                key = f"{size}-{str(i).zfill(5)}".encode("utf-8")
-
-                with env.begin(write=True) as txn:
-                    txn.put(key, img)
-
-            total += 1
-
-        with env.begin(write=True) as txn:
-            txn.put("length".encode("utf-8"), str(total).encode("utf-8"))
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Preprocess images for model training")
-    parser.add_argument("--out", type=str, help="filename of the result lmdb dataset")
-    parser.add_argument(
-        "--size",
-        type=str,
-        default="128,256,512,1024",
-        help="resolutions of images for the dataset",
-    )
-    parser.add_argument(
-        "--n_worker",
-        type=int,
-        default=8,
-        help="number of workers for preparing dataset",
-    )
-    parser.add_argument(
-        "--resample",
-        type=str,
-        default="lanczos",
-        help="resampling methods for resizing images",
-    )
-    parser.add_argument("path", type=str, help="path to the image dataset")
-
-    args = parser.parse_args()
-
-    if not os.path.exists(args.out):
-        os.makedirs(args.out)
-     
-    resample_map = {"lanczos": Image.LANCZOS, "bilinear": Image.BILINEAR}
-    resample = resample_map[args.resample]
-
-    sizes = [int(s.strip()) for s in args.size.split(",")]
-
-    print(f"Make dataset of image sizes:", ", ".join(str(s) for s in sizes))
-
-    imgset = datasets.ImageFolder(args.path)
-
-    with lmdb.open(args.out, map_size=1024 ** 4, readahead=False) as env:
-        prepare(env, imgset, args.n_worker, sizes=sizes, resample=resample)
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/PIL/ImageTransform.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/PIL/ImageTransform.py
deleted file mode 100644
index 7881f0d262b0db7ecaed224ee2268f3b69b836c9..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/PIL/ImageTransform.py
+++ /dev/null
@@ -1,102 +0,0 @@
-#
-# The Python Imaging Library.
-# $Id$
-#
-# transform wrappers
-#
-# History:
-# 2002-04-08 fl   Created
-#
-# Copyright (c) 2002 by Secret Labs AB
-# Copyright (c) 2002 by Fredrik Lundh
-#
-# See the README file for information on usage and redistribution.
-#
-
-from . import Image
-
-
-class Transform(Image.ImageTransformHandler):
-    def __init__(self, data):
-        self.data = data
-
-    def getdata(self):
-        return self.method, self.data
-
-    def transform(self, size, image, **options):
-        # can be overridden
-        method, data = self.getdata()
-        return image.transform(size, method, data, **options)
-
-
-class AffineTransform(Transform):
-    """
-    Define an affine image transform.
-
-    This function takes a 6-tuple (a, b, c, d, e, f) which contain the first
-    two rows from an affine transform matrix. For each pixel (x, y) in the
-    output image, the new value is taken from a position (a x + b y + c,
-    d x + e y + f) in the input image, rounded to nearest pixel.
-
-    This function can be used to scale, translate, rotate, and shear the
-    original image.
-
-    See :py:meth:`~PIL.Image.Image.transform`
-
-    :param matrix: A 6-tuple (a, b, c, d, e, f) containing the first two rows
-        from an affine transform matrix.
-    """
-
-    method = Image.Transform.AFFINE
-
-
-class ExtentTransform(Transform):
-    """
-    Define a transform to extract a subregion from an image.
-
-    Maps a rectangle (defined by two corners) from the image to a rectangle of
-    the given size. The resulting image will contain data sampled from between
-    the corners, such that (x0, y0) in the input image will end up at (0,0) in
-    the output image, and (x1, y1) at size.
-
-    This method can be used to crop, stretch, shrink, or mirror an arbitrary
-    rectangle in the current image. It is slightly slower than crop, but about
-    as fast as a corresponding resize operation.
-
-    See :py:meth:`~PIL.Image.Image.transform`
-
-    :param bbox: A 4-tuple (x0, y0, x1, y1) which specifies two points in the
-        input image's coordinate system. See :ref:`coordinate-system`.
-    """
-
-    method = Image.Transform.EXTENT
-
-
-class QuadTransform(Transform):
-    """
-    Define a quad image transform.
-
-    Maps a quadrilateral (a region defined by four corners) from the image to a
-    rectangle of the given size.
-
-    See :py:meth:`~PIL.Image.Image.transform`
-
-    :param xy: An 8-tuple (x0, y0, x1, y1, x2, y2, x3, y3) which contain the
-        upper left, lower left, lower right, and upper right corner of the
-        source quadrilateral.
-    """
-
-    method = Image.Transform.QUAD
-
-
-class MeshTransform(Transform):
-    """
-    Define a mesh image transform.  A mesh transform consists of one or more
-    individual quad transforms.
-
-    See :py:meth:`~PIL.Image.Image.transform`
-
-    :param data: A list of (bbox, quad) tuples.
-    """
-
-    method = Image.Transform.MESH
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/index-aef3869a.css b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/index-aef3869a.css
deleted file mode 100644
index a1f402a49e82009fd7eafa923615d67793b8751c..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/index-aef3869a.css
+++ /dev/null
@@ -1 +0,0 @@
-td.svelte-xrr240.svelte-xrr240{width:45%}td.svelte-xrr240.svelte-xrr240:last-child{width:10%;text-align:right}.file-preview-holder.svelte-xrr240.svelte-xrr240{overflow-x:auto}.file-preview.svelte-xrr240.svelte-xrr240{width:var(--size-full);max-height:var(--size-60);overflow-y:auto;color:var(--body-text-color)}.file.svelte-xrr240.svelte-xrr240{width:var(--size-full)}.file.svelte-xrr240>.svelte-xrr240{padding:var(--size-1) var(--size-2-5)}.download.svelte-xrr240.svelte-xrr240:hover{text-decoration:underline}.download.svelte-xrr240>a.svelte-xrr240{color:var(--link-text-color)}.download.svelte-xrr240>a.svelte-xrr240:hover{color:var(--link-text-color-hover)}.download.svelte-xrr240>a.svelte-xrr240:visited{color:var(--link-text-color-visited)}.download.svelte-xrr240>a.svelte-xrr240:active{color:var(--link-text-color-active)}.selectable.svelte-xrr240.svelte-xrr240{cursor:pointer}
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/_pylab_helpers.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/_pylab_helpers.py
deleted file mode 100644
index d32a69d4ff991dff512bb0c4867b24471f1f9fb5..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/_pylab_helpers.py
+++ /dev/null
@@ -1,135 +0,0 @@
-"""
-Manage figures for the pyplot interface.
-"""
-
-import atexit
-from collections import OrderedDict
-
-
-class Gcf:
-    """
-    Singleton to maintain the relation between figures and their managers, and
-    keep track of and "active" figure and manager.
-
-    The canvas of a figure created through pyplot is associated with a figure
-    manager, which handles the interaction between the figure and the backend.
-    pyplot keeps track of figure managers using an identifier, the "figure
-    number" or "manager number" (which can actually be any hashable value);
-    this number is available as the :attr:`number` attribute of the manager.
-
-    This class is never instantiated; it consists of an `OrderedDict` mapping
-    figure/manager numbers to managers, and a set of class methods that
-    manipulate this `OrderedDict`.
-
-    Attributes
-    ----------
-    figs : OrderedDict
-        `OrderedDict` mapping numbers to managers; the active manager is at the
-        end.
-    """
-
-    figs = OrderedDict()
-
-    @classmethod
-    def get_fig_manager(cls, num):
-        """
-        If manager number *num* exists, make it the active one and return it;
-        otherwise return *None*.
-        """
-        manager = cls.figs.get(num, None)
-        if manager is not None:
-            cls.set_active(manager)
-        return manager
-
-    @classmethod
-    def destroy(cls, num):
-        """
-        Destroy manager *num* -- either a manager instance or a manager number.
-
-        In the interactive backends, this is bound to the window "destroy" and
-        "delete" events.
-
-        It is recommended to pass a manager instance, to avoid confusion when
-        two managers share the same number.
-        """
-        if all(hasattr(num, attr) for attr in ["num", "destroy"]):
-            manager = num
-            if cls.figs.get(manager.num) is manager:
-                cls.figs.pop(manager.num)
-        else:
-            try:
-                manager = cls.figs.pop(num)
-            except KeyError:
-                return
-        if hasattr(manager, "_cidgcf"):
-            manager.canvas.mpl_disconnect(manager._cidgcf)
-        manager.destroy()
-        del manager, num
-
-    @classmethod
-    def destroy_fig(cls, fig):
-        """Destroy figure *fig*."""
-        num = next((manager.num for manager in cls.figs.values()
-                    if manager.canvas.figure == fig), None)
-        if num is not None:
-            cls.destroy(num)
-
-    @classmethod
-    def destroy_all(cls):
-        """Destroy all figures."""
-        for manager in list(cls.figs.values()):
-            manager.canvas.mpl_disconnect(manager._cidgcf)
-            manager.destroy()
-        cls.figs.clear()
-
-    @classmethod
-    def has_fignum(cls, num):
-        """Return whether figure number *num* exists."""
-        return num in cls.figs
-
-    @classmethod
-    def get_all_fig_managers(cls):
-        """Return a list of figure managers."""
-        return list(cls.figs.values())
-
-    @classmethod
-    def get_num_fig_managers(cls):
-        """Return the number of figures being managed."""
-        return len(cls.figs)
-
-    @classmethod
-    def get_active(cls):
-        """Return the active manager, or *None* if there is no manager."""
-        return next(reversed(cls.figs.values())) if cls.figs else None
-
-    @classmethod
-    def _set_new_active_manager(cls, manager):
-        """Adopt *manager* into pyplot and make it the active manager."""
-        if not hasattr(manager, "_cidgcf"):
-            manager._cidgcf = manager.canvas.mpl_connect(
-                "button_press_event", lambda event: cls.set_active(manager))
-        fig = manager.canvas.figure
-        fig.number = manager.num
-        label = fig.get_label()
-        if label:
-            manager.set_window_title(label)
-        cls.set_active(manager)
-
-    @classmethod
-    def set_active(cls, manager):
-        """Make *manager* the active manager."""
-        cls.figs[manager.num] = manager
-        cls.figs.move_to_end(manager.num)
-
-    @classmethod
-    def draw_all(cls, force=False):
-        """
-        Redraw all stale managed figures, or, if *force* is True, all managed
-        figures.
-        """
-        for manager in cls.get_all_fig_managers():
-            if force or manager.canvas.figure.stale:
-                manager.canvas.draw_idle()
-
-
-atexit.register(Gcf.destroy_all)
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/backends/backend_svg.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/backends/backend_svg.py
deleted file mode 100644
index df39e620f888f423cb287b8aa6ec40269fd293a7..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/matplotlib/backends/backend_svg.py
+++ /dev/null
@@ -1,1398 +0,0 @@
-import base64
-import codecs
-import datetime
-import gzip
-import hashlib
-from io import BytesIO
-import itertools
-import logging
-import os
-import re
-import uuid
-
-import numpy as np
-from PIL import Image
-
-import matplotlib as mpl
-from matplotlib import _api, cbook, font_manager as fm
-from matplotlib.backend_bases import (
-     _Backend, FigureCanvasBase, FigureManagerBase, RendererBase)
-from matplotlib.backends.backend_mixed import MixedModeRenderer
-from matplotlib.colors import rgb2hex
-from matplotlib.dates import UTC
-from matplotlib.path import Path
-from matplotlib import _path
-from matplotlib.transforms import Affine2D, Affine2DBase
-
-
-_log = logging.getLogger(__name__)
-
-
-# ----------------------------------------------------------------------
-# SimpleXMLWriter class
-#
-# Based on an original by Fredrik Lundh, but modified here to:
-#   1. Support modern Python idioms
-#   2. Remove encoding support (it's handled by the file writer instead)
-#   3. Support proper indentation
-#   4. Minify things a little bit
-
-# --------------------------------------------------------------------
-# The SimpleXMLWriter module is
-#
-# Copyright (c) 2001-2004 by Fredrik Lundh
-#
-# By obtaining, using, and/or copying this software and/or its
-# associated documentation, you agree that you have read, understood,
-# and will comply with the following terms and conditions:
-#
-# Permission to use, copy, modify, and distribute this software and
-# its associated documentation for any purpose and without fee is
-# hereby granted, provided that the above copyright notice appears in
-# all copies, and that both that copyright notice and this permission
-# notice appear in supporting documentation, and that the name of
-# Secret Labs AB or the author not be used in advertising or publicity
-# pertaining to distribution of the software without specific, written
-# prior permission.
-#
-# SECRET LABS AB AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD
-# TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANT-
-# ABILITY AND FITNESS.  IN NO EVENT SHALL SECRET LABS AB OR THE AUTHOR
-# BE LIABLE FOR ANY SPECIAL, 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.
-# --------------------------------------------------------------------
-
-
-@_api.deprecated("3.6", alternative="a vendored copy of _escape_cdata")
-def escape_cdata(s):
-    return _escape_cdata(s)
-
-
-def _escape_cdata(s):
-    s = s.replace("&", "&amp;")
-    s = s.replace("<", "&lt;")
-    s = s.replace(">", "&gt;")
-    return s
-
-
-_escape_xml_comment = re.compile(r'-(?=-)')
-
-
-@_api.deprecated("3.6", alternative="a vendored copy of _escape_comment")
-def escape_comment(s):
-    return _escape_comment.sub(s)
-
-
-def _escape_comment(s):
-    s = _escape_cdata(s)
-    return _escape_xml_comment.sub('- ', s)
-
-
-@_api.deprecated("3.6", alternative="a vendored copy of _escape_attrib")
-def escape_attrib(s):
-    return _escape_attrib(s)
-
-
-def _escape_attrib(s):
-    s = s.replace("&", "&amp;")
-    s = s.replace("'", "&apos;")
-    s = s.replace('"', "&quot;")
-    s = s.replace("<", "&lt;")
-    s = s.replace(">", "&gt;")
-    return s
-
-
-def _quote_escape_attrib(s):
-    return ('"' + _escape_cdata(s) + '"' if '"' not in s else
-            "'" + _escape_cdata(s) + "'" if "'" not in s else
-            '"' + _escape_attrib(s) + '"')
-
-
-@_api.deprecated("3.6", alternative="a vendored copy of _short_float_fmt")
-def short_float_fmt(x):
-    return _short_float_fmt(x)
-
-
-def _short_float_fmt(x):
-    """
-    Create a short string representation of a float, which is %f
-    formatting with trailing zeros and the decimal point removed.
-    """
-    return '{0:f}'.format(x).rstrip('0').rstrip('.')
-
-
-class XMLWriter:
-    """
-    Parameters
-    ----------
-    file : writable text file-like object
-    """
-
-    def __init__(self, file):
-        self.__write = file.write
-        if hasattr(file, "flush"):
-            self.flush = file.flush
-        self.__open = 0  # true if start tag is open
-        self.__tags = []
-        self.__data = []
-        self.__indentation = " " * 64
-
-    def __flush(self, indent=True):
-        # flush internal buffers
-        if self.__open:
-            if indent:
-                self.__write(">\n")
-            else:
-                self.__write(">")
-            self.__open = 0
-        if self.__data:
-            data = ''.join(self.__data)
-            self.__write(_escape_cdata(data))
-            self.__data = []
-
-    def start(self, tag, attrib={}, **extra):
-        """
-        Open a new element.  Attributes can be given as keyword
-        arguments, or as a string/string dictionary. The method returns
-        an opaque identifier that can be passed to the :meth:`close`
-        method, to close all open elements up to and including this one.
-
-        Parameters
-        ----------
-        tag
-            Element tag.
-        attrib
-            Attribute dictionary.  Alternatively, attributes can be given as
-            keyword arguments.
-
-        Returns
-        -------
-        An element identifier.
-        """
-        self.__flush()
-        tag = _escape_cdata(tag)
-        self.__data = []
-        self.__tags.append(tag)
-        self.__write(self.__indentation[:len(self.__tags) - 1])
-        self.__write("<%s" % tag)
-        for k, v in {**attrib, **extra}.items():
-            if v:
-                k = _escape_cdata(k)
-                v = _quote_escape_attrib(v)
-                self.__write(' %s=%s' % (k, v))
-        self.__open = 1
-        return len(self.__tags) - 1
-
-    def comment(self, comment):
-        """
-        Add a comment to the output stream.
-
-        Parameters
-        ----------
-        comment : str
-            Comment text.
-        """
-        self.__flush()
-        self.__write(self.__indentation[:len(self.__tags)])
-        self.__write("<!-- %s -->\n" % _escape_comment(comment))
-
-    def data(self, text):
-        """
-        Add character data to the output stream.
-
-        Parameters
-        ----------
-        text : str
-            Character data.
-        """
-        self.__data.append(text)
-
-    def end(self, tag=None, indent=True):
-        """
-        Close the current element (opened by the most recent call to
-        :meth:`start`).
-
-        Parameters
-        ----------
-        tag
-            Element tag.  If given, the tag must match the start tag.  If
-            omitted, the current element is closed.
-        """
-        if tag:
-            assert self.__tags, "unbalanced end(%s)" % tag
-            assert _escape_cdata(tag) == self.__tags[-1], \
-                "expected end(%s), got %s" % (self.__tags[-1], tag)
-        else:
-            assert self.__tags, "unbalanced end()"
-        tag = self.__tags.pop()
-        if self.__data:
-            self.__flush(indent)
-        elif self.__open:
-            self.__open = 0
-            self.__write("/>\n")
-            return
-        if indent:
-            self.__write(self.__indentation[:len(self.__tags)])
-        self.__write("</%s>\n" % tag)
-
-    def close(self, id):
-        """
-        Close open elements, up to (and including) the element identified
-        by the given identifier.
-
-        Parameters
-        ----------
-        id
-            Element identifier, as returned by the :meth:`start` method.
-        """
-        while len(self.__tags) > id:
-            self.end()
-
-    def element(self, tag, text=None, attrib={}, **extra):
-        """
-        Add an entire element.  This is the same as calling :meth:`start`,
-        :meth:`data`, and :meth:`end` in sequence. The *text* argument can be
-        omitted.
-        """
-        self.start(tag, attrib, **extra)
-        if text:
-            self.data(text)
-        self.end(indent=False)
-
-    def flush(self):
-        """Flush the output stream."""
-        pass  # replaced by the constructor
-
-
-def _generate_transform(transform_list):
-    parts = []
-    for type, value in transform_list:
-        if (type == 'scale' and (value == (1,) or value == (1, 1))
-                or type == 'translate' and value == (0, 0)
-                or type == 'rotate' and value == (0,)):
-            continue
-        if type == 'matrix' and isinstance(value, Affine2DBase):
-            value = value.to_values()
-        parts.append('%s(%s)' % (
-            type, ' '.join(_short_float_fmt(x) for x in value)))
-    return ' '.join(parts)
-
-
-@_api.deprecated("3.6")
-def generate_transform(transform_list=None):
-    return _generate_transform(transform_list or [])
-
-
-def _generate_css(attrib):
-    return "; ".join(f"{k}: {v}" for k, v in attrib.items())
-
-
-@_api.deprecated("3.6")
-def generate_css(attrib=None):
-    return _generate_css(attrib or {})
-
-
-_capstyle_d = {'projecting': 'square', 'butt': 'butt', 'round': 'round'}
-
-
-def _check_is_str(info, key):
-    if not isinstance(info, str):
-        raise TypeError(f'Invalid type for {key} metadata. Expected str, not '
-                        f'{type(info)}.')
-
-
-def _check_is_iterable_of_str(infos, key):
-    if np.iterable(infos):
-        for info in infos:
-            if not isinstance(info, str):
-                raise TypeError(f'Invalid type for {key} metadata. Expected '
-                                f'iterable of str, not {type(info)}.')
-    else:
-        raise TypeError(f'Invalid type for {key} metadata. Expected str or '
-                        f'iterable of str, not {type(infos)}.')
-
-
-class RendererSVG(RendererBase):
-    def __init__(self, width, height, svgwriter, basename=None, image_dpi=72,
-                 *, metadata=None):
-        self.width = width
-        self.height = height
-        self.writer = XMLWriter(svgwriter)
-        self.image_dpi = image_dpi  # actual dpi at which we rasterize stuff
-
-        if basename is None:
-            basename = getattr(svgwriter, "name", "")
-            if not isinstance(basename, str):
-                basename = ""
-        self.basename = basename
-
-        self._groupd = {}
-        self._image_counter = itertools.count()
-        self._clipd = {}
-        self._markers = {}
-        self._path_collection_id = 0
-        self._hatchd = {}
-        self._has_gouraud = False
-        self._n_gradients = 0
-
-        super().__init__()
-        self._glyph_map = dict()
-        str_height = _short_float_fmt(height)
-        str_width = _short_float_fmt(width)
-        svgwriter.write(svgProlog)
-        self._start_id = self.writer.start(
-            'svg',
-            width='%spt' % str_width,
-            height='%spt' % str_height,
-            viewBox='0 0 %s %s' % (str_width, str_height),
-            xmlns="http://www.w3.org/2000/svg",
-            version="1.1",
-            attrib={'xmlns:xlink': "http://www.w3.org/1999/xlink"})
-        self._write_metadata(metadata)
-        self._write_default_style()
-
-    def finalize(self):
-        self._write_clips()
-        self._write_hatches()
-        self.writer.close(self._start_id)
-        self.writer.flush()
-
-    def _write_metadata(self, metadata):
-        # Add metadata following the Dublin Core Metadata Initiative, and the
-        # Creative Commons Rights Expression Language. This is mainly for
-        # compatibility with Inkscape.
-        if metadata is None:
-            metadata = {}
-        metadata = {
-            'Format': 'image/svg+xml',
-            'Type': 'http://purl.org/dc/dcmitype/StillImage',
-            'Creator':
-                f'Matplotlib v{mpl.__version__}, https://matplotlib.org/',
-            **metadata
-        }
-        writer = self.writer
-
-        if 'Title' in metadata:
-            title = metadata['Title']
-            _check_is_str(title, 'Title')
-            writer.element('title', text=title)
-
-        # Special handling.
-        date = metadata.get('Date', None)
-        if date is not None:
-            if isinstance(date, str):
-                dates = [date]
-            elif isinstance(date, (datetime.datetime, datetime.date)):
-                dates = [date.isoformat()]
-            elif np.iterable(date):
-                dates = []
-                for d in date:
-                    if isinstance(d, str):
-                        dates.append(d)
-                    elif isinstance(d, (datetime.datetime, datetime.date)):
-                        dates.append(d.isoformat())
-                    else:
-                        raise TypeError(
-                            f'Invalid type for Date metadata. '
-                            f'Expected iterable of str, date, or datetime, '
-                            f'not {type(d)}.')
-            else:
-                raise TypeError(f'Invalid type for Date metadata. '
-                                f'Expected str, date, datetime, or iterable '
-                                f'of the same, not {type(date)}.')
-            metadata['Date'] = '/'.join(dates)
-        elif 'Date' not in metadata:
-            # Do not add `Date` if the user explicitly set `Date` to `None`
-            # Get source date from SOURCE_DATE_EPOCH, if set.
-            # See https://reproducible-builds.org/specs/source-date-epoch/
-            date = os.getenv("SOURCE_DATE_EPOCH")
-            if date:
-                date = datetime.datetime.utcfromtimestamp(int(date))
-                metadata['Date'] = date.replace(tzinfo=UTC).isoformat()
-            else:
-                metadata['Date'] = datetime.datetime.today().isoformat()
-
-        mid = None
-        def ensure_metadata(mid):
-            if mid is not None:
-                return mid
-            mid = writer.start('metadata')
-            writer.start('rdf:RDF', attrib={
-                'xmlns:dc': "http://purl.org/dc/elements/1.1/",
-                'xmlns:cc': "http://creativecommons.org/ns#",
-                'xmlns:rdf': "http://www.w3.org/1999/02/22-rdf-syntax-ns#",
-            })
-            writer.start('cc:Work')
-            return mid
-
-        uri = metadata.pop('Type', None)
-        if uri is not None:
-            mid = ensure_metadata(mid)
-            writer.element('dc:type', attrib={'rdf:resource': uri})
-
-        # Single value only.
-        for key in ['Title', 'Coverage', 'Date', 'Description', 'Format',
-                    'Identifier', 'Language', 'Relation', 'Source']:
-            info = metadata.pop(key, None)
-            if info is not None:
-                mid = ensure_metadata(mid)
-                _check_is_str(info, key)
-                writer.element(f'dc:{key.lower()}', text=info)
-
-        # Multiple Agent values.
-        for key in ['Creator', 'Contributor', 'Publisher', 'Rights']:
-            agents = metadata.pop(key, None)
-            if agents is None:
-                continue
-
-            if isinstance(agents, str):
-                agents = [agents]
-
-            _check_is_iterable_of_str(agents, key)
-            # Now we know that we have an iterable of str
-            mid = ensure_metadata(mid)
-            writer.start(f'dc:{key.lower()}')
-            for agent in agents:
-                writer.start('cc:Agent')
-                writer.element('dc:title', text=agent)
-                writer.end('cc:Agent')
-            writer.end(f'dc:{key.lower()}')
-
-        # Multiple values.
-        keywords = metadata.pop('Keywords', None)
-        if keywords is not None:
-            if isinstance(keywords, str):
-                keywords = [keywords]
-            _check_is_iterable_of_str(keywords, 'Keywords')
-            # Now we know that we have an iterable of str
-            mid = ensure_metadata(mid)
-            writer.start('dc:subject')
-            writer.start('rdf:Bag')
-            for keyword in keywords:
-                writer.element('rdf:li', text=keyword)
-            writer.end('rdf:Bag')
-            writer.end('dc:subject')
-
-        if mid is not None:
-            writer.close(mid)
-
-        if metadata:
-            raise ValueError('Unknown metadata key(s) passed to SVG writer: ' +
-                             ','.join(metadata))
-
-    def _write_default_style(self):
-        writer = self.writer
-        default_style = _generate_css({
-            'stroke-linejoin': 'round',
-            'stroke-linecap': 'butt'})
-        writer.start('defs')
-        writer.element('style', type='text/css', text='*{%s}' % default_style)
-        writer.end('defs')
-
-    def _make_id(self, type, content):
-        salt = mpl.rcParams['svg.hashsalt']
-        if salt is None:
-            salt = str(uuid.uuid4())
-        m = hashlib.sha256()
-        m.update(salt.encode('utf8'))
-        m.update(str(content).encode('utf8'))
-        return '%s%s' % (type, m.hexdigest()[:10])
-
-    def _make_flip_transform(self, transform):
-        return transform + Affine2D().scale(1, -1).translate(0, self.height)
-
-    def _get_hatch(self, gc, rgbFace):
-        """
-        Create a new hatch pattern
-        """
-        if rgbFace is not None:
-            rgbFace = tuple(rgbFace)
-        edge = gc.get_hatch_color()
-        if edge is not None:
-            edge = tuple(edge)
-        dictkey = (gc.get_hatch(), rgbFace, edge)
-        oid = self._hatchd.get(dictkey)
-        if oid is None:
-            oid = self._make_id('h', dictkey)
-            self._hatchd[dictkey] = ((gc.get_hatch_path(), rgbFace, edge), oid)
-        else:
-            _, oid = oid
-        return oid
-
-    def _write_hatches(self):
-        if not len(self._hatchd):
-            return
-        HATCH_SIZE = 72
-        writer = self.writer
-        writer.start('defs')
-        for (path, face, stroke), oid in self._hatchd.values():
-            writer.start(
-                'pattern',
-                id=oid,
-                patternUnits="userSpaceOnUse",
-                x="0", y="0", width=str(HATCH_SIZE),
-                height=str(HATCH_SIZE))
-            path_data = self._convert_path(
-                path,
-                Affine2D()
-                .scale(HATCH_SIZE).scale(1.0, -1.0).translate(0, HATCH_SIZE),
-                simplify=False)
-            if face is None:
-                fill = 'none'
-            else:
-                fill = rgb2hex(face)
-            writer.element(
-                'rect',
-                x="0", y="0", width=str(HATCH_SIZE+1),
-                height=str(HATCH_SIZE+1),
-                fill=fill)
-            hatch_style = {
-                    'fill': rgb2hex(stroke),
-                    'stroke': rgb2hex(stroke),
-                    'stroke-width': str(mpl.rcParams['hatch.linewidth']),
-                    'stroke-linecap': 'butt',
-                    'stroke-linejoin': 'miter'
-                    }
-            if stroke[3] < 1:
-                hatch_style['stroke-opacity'] = str(stroke[3])
-            writer.element(
-                'path',
-                d=path_data,
-                style=_generate_css(hatch_style)
-                )
-            writer.end('pattern')
-        writer.end('defs')
-
-    def _get_style_dict(self, gc, rgbFace):
-        """Generate a style string from the GraphicsContext and rgbFace."""
-        attrib = {}
-
-        forced_alpha = gc.get_forced_alpha()
-
-        if gc.get_hatch() is not None:
-            attrib['fill'] = "url(#%s)" % self._get_hatch(gc, rgbFace)
-            if (rgbFace is not None and len(rgbFace) == 4 and rgbFace[3] != 1.0
-                    and not forced_alpha):
-                attrib['fill-opacity'] = _short_float_fmt(rgbFace[3])
-        else:
-            if rgbFace is None:
-                attrib['fill'] = 'none'
-            else:
-                if tuple(rgbFace[:3]) != (0, 0, 0):
-                    attrib['fill'] = rgb2hex(rgbFace)
-                if (len(rgbFace) == 4 and rgbFace[3] != 1.0
-                        and not forced_alpha):
-                    attrib['fill-opacity'] = _short_float_fmt(rgbFace[3])
-
-        if forced_alpha and gc.get_alpha() != 1.0:
-            attrib['opacity'] = _short_float_fmt(gc.get_alpha())
-
-        offset, seq = gc.get_dashes()
-        if seq is not None:
-            attrib['stroke-dasharray'] = ','.join(
-                _short_float_fmt(val) for val in seq)
-            attrib['stroke-dashoffset'] = _short_float_fmt(float(offset))
-
-        linewidth = gc.get_linewidth()
-        if linewidth:
-            rgb = gc.get_rgb()
-            attrib['stroke'] = rgb2hex(rgb)
-            if not forced_alpha and rgb[3] != 1.0:
-                attrib['stroke-opacity'] = _short_float_fmt(rgb[3])
-            if linewidth != 1.0:
-                attrib['stroke-width'] = _short_float_fmt(linewidth)
-            if gc.get_joinstyle() != 'round':
-                attrib['stroke-linejoin'] = gc.get_joinstyle()
-            if gc.get_capstyle() != 'butt':
-                attrib['stroke-linecap'] = _capstyle_d[gc.get_capstyle()]
-
-        return attrib
-
-    def _get_style(self, gc, rgbFace):
-        return _generate_css(self._get_style_dict(gc, rgbFace))
-
-    def _get_clip_attrs(self, gc):
-        cliprect = gc.get_clip_rectangle()
-        clippath, clippath_trans = gc.get_clip_path()
-        if clippath is not None:
-            clippath_trans = self._make_flip_transform(clippath_trans)
-            dictkey = (id(clippath), str(clippath_trans))
-        elif cliprect is not None:
-            x, y, w, h = cliprect.bounds
-            y = self.height-(y+h)
-            dictkey = (x, y, w, h)
-        else:
-            return {}
-        clip = self._clipd.get(dictkey)
-        if clip is None:
-            oid = self._make_id('p', dictkey)
-            if clippath is not None:
-                self._clipd[dictkey] = ((clippath, clippath_trans), oid)
-            else:
-                self._clipd[dictkey] = (dictkey, oid)
-        else:
-            clip, oid = clip
-        return {'clip-path': f'url(#{oid})'}
-
-    def _write_clips(self):
-        if not len(self._clipd):
-            return
-        writer = self.writer
-        writer.start('defs')
-        for clip, oid in self._clipd.values():
-            writer.start('clipPath', id=oid)
-            if len(clip) == 2:
-                clippath, clippath_trans = clip
-                path_data = self._convert_path(
-                    clippath, clippath_trans, simplify=False)
-                writer.element('path', d=path_data)
-            else:
-                x, y, w, h = clip
-                writer.element(
-                    'rect',
-                    x=_short_float_fmt(x),
-                    y=_short_float_fmt(y),
-                    width=_short_float_fmt(w),
-                    height=_short_float_fmt(h))
-            writer.end('clipPath')
-        writer.end('defs')
-
-    def open_group(self, s, gid=None):
-        # docstring inherited
-        if gid:
-            self.writer.start('g', id=gid)
-        else:
-            self._groupd[s] = self._groupd.get(s, 0) + 1
-            self.writer.start('g', id="%s_%d" % (s, self._groupd[s]))
-
-    def close_group(self, s):
-        # docstring inherited
-        self.writer.end('g')
-
-    def option_image_nocomposite(self):
-        # docstring inherited
-        return not mpl.rcParams['image.composite_image']
-
-    def _convert_path(self, path, transform=None, clip=None, simplify=None,
-                      sketch=None):
-        if clip:
-            clip = (0.0, 0.0, self.width, self.height)
-        else:
-            clip = None
-        return _path.convert_to_string(
-            path, transform, clip, simplify, sketch, 6,
-            [b'M', b'L', b'Q', b'C', b'z'], False).decode('ascii')
-
-    def draw_path(self, gc, path, transform, rgbFace=None):
-        # docstring inherited
-        trans_and_flip = self._make_flip_transform(transform)
-        clip = (rgbFace is None and gc.get_hatch_path() is None)
-        simplify = path.should_simplify and clip
-        path_data = self._convert_path(
-            path, trans_and_flip, clip=clip, simplify=simplify,
-            sketch=gc.get_sketch_params())
-
-        if gc.get_url() is not None:
-            self.writer.start('a', {'xlink:href': gc.get_url()})
-        self.writer.element('path', d=path_data, **self._get_clip_attrs(gc),
-                            style=self._get_style(gc, rgbFace))
-        if gc.get_url() is not None:
-            self.writer.end('a')
-
-    def draw_markers(
-            self, gc, marker_path, marker_trans, path, trans, rgbFace=None):
-        # docstring inherited
-
-        if not len(path.vertices):
-            return
-
-        writer = self.writer
-        path_data = self._convert_path(
-            marker_path,
-            marker_trans + Affine2D().scale(1.0, -1.0),
-            simplify=False)
-        style = self._get_style_dict(gc, rgbFace)
-        dictkey = (path_data, _generate_css(style))
-        oid = self._markers.get(dictkey)
-        style = _generate_css({k: v for k, v in style.items()
-                              if k.startswith('stroke')})
-
-        if oid is None:
-            oid = self._make_id('m', dictkey)
-            writer.start('defs')
-            writer.element('path', id=oid, d=path_data, style=style)
-            writer.end('defs')
-            self._markers[dictkey] = oid
-
-        writer.start('g', **self._get_clip_attrs(gc))
-        trans_and_flip = self._make_flip_transform(trans)
-        attrib = {'xlink:href': '#%s' % oid}
-        clip = (0, 0, self.width*72, self.height*72)
-        for vertices, code in path.iter_segments(
-                trans_and_flip, clip=clip, simplify=False):
-            if len(vertices):
-                x, y = vertices[-2:]
-                attrib['x'] = _short_float_fmt(x)
-                attrib['y'] = _short_float_fmt(y)
-                attrib['style'] = self._get_style(gc, rgbFace)
-                writer.element('use', attrib=attrib)
-        writer.end('g')
-
-    def draw_path_collection(self, gc, master_transform, paths, all_transforms,
-                             offsets, offset_trans, facecolors, edgecolors,
-                             linewidths, linestyles, antialiaseds, urls,
-                             offset_position):
-        # Is the optimization worth it? Rough calculation:
-        # cost of emitting a path in-line is
-        #    (len_path + 5) * uses_per_path
-        # cost of definition+use is
-        #    (len_path + 3) + 9 * uses_per_path
-        len_path = len(paths[0].vertices) if len(paths) > 0 else 0
-        uses_per_path = self._iter_collection_uses_per_path(
-            paths, all_transforms, offsets, facecolors, edgecolors)
-        should_do_optimization = \
-            len_path + 9 * uses_per_path + 3 < (len_path + 5) * uses_per_path
-        if not should_do_optimization:
-            return super().draw_path_collection(
-                gc, master_transform, paths, all_transforms,
-                offsets, offset_trans, facecolors, edgecolors,
-                linewidths, linestyles, antialiaseds, urls,
-                offset_position)
-
-        writer = self.writer
-        path_codes = []
-        writer.start('defs')
-        for i, (path, transform) in enumerate(self._iter_collection_raw_paths(
-                master_transform, paths, all_transforms)):
-            transform = Affine2D(transform.get_matrix()).scale(1.0, -1.0)
-            d = self._convert_path(path, transform, simplify=False)
-            oid = 'C%x_%x_%s' % (
-                self._path_collection_id, i, self._make_id('', d))
-            writer.element('path', id=oid, d=d)
-            path_codes.append(oid)
-        writer.end('defs')
-
-        for xo, yo, path_id, gc0, rgbFace in self._iter_collection(
-                gc, path_codes, offsets, offset_trans,
-                facecolors, edgecolors, linewidths, linestyles,
-                antialiaseds, urls, offset_position):
-            url = gc0.get_url()
-            if url is not None:
-                writer.start('a', attrib={'xlink:href': url})
-            clip_attrs = self._get_clip_attrs(gc0)
-            if clip_attrs:
-                writer.start('g', **clip_attrs)
-            attrib = {
-                'xlink:href': '#%s' % path_id,
-                'x': _short_float_fmt(xo),
-                'y': _short_float_fmt(self.height - yo),
-                'style': self._get_style(gc0, rgbFace)
-                }
-            writer.element('use', attrib=attrib)
-            if clip_attrs:
-                writer.end('g')
-            if url is not None:
-                writer.end('a')
-
-        self._path_collection_id += 1
-
-    def draw_gouraud_triangle(self, gc, points, colors, trans):
-        # docstring inherited
-        self._draw_gouraud_triangle(gc, points, colors, trans)
-
-    def _draw_gouraud_triangle(self, gc, points, colors, trans):
-        # This uses a method described here:
-        #
-        #   http://www.svgopen.org/2005/papers/Converting3DFaceToSVG/index.html
-        #
-        # that uses three overlapping linear gradients to simulate a
-        # Gouraud triangle.  Each gradient goes from fully opaque in
-        # one corner to fully transparent along the opposite edge.
-        # The line between the stop points is perpendicular to the
-        # opposite edge.  Underlying these three gradients is a solid
-        # triangle whose color is the average of all three points.
-
-        writer = self.writer
-        if not self._has_gouraud:
-            self._has_gouraud = True
-            writer.start(
-                'filter',
-                id='colorAdd')
-            writer.element(
-                'feComposite',
-                attrib={'in': 'SourceGraphic'},
-                in2='BackgroundImage',
-                operator='arithmetic',
-                k2="1", k3="1")
-            writer.end('filter')
-            # feColorMatrix filter to correct opacity
-            writer.start(
-                'filter',
-                id='colorMat')
-            writer.element(
-                'feColorMatrix',
-                attrib={'type': 'matrix'},
-                values='1 0 0 0 0 \n0 1 0 0 0 \n0 0 1 0 0' +
-                       ' \n1 1 1 1 0 \n0 0 0 0 1 ')
-            writer.end('filter')
-
-        avg_color = np.average(colors, axis=0)
-        if avg_color[-1] == 0:
-            # Skip fully-transparent triangles
-            return
-
-        trans_and_flip = self._make_flip_transform(trans)
-        tpoints = trans_and_flip.transform(points)
-
-        writer.start('defs')
-        for i in range(3):
-            x1, y1 = tpoints[i]
-            x2, y2 = tpoints[(i + 1) % 3]
-            x3, y3 = tpoints[(i + 2) % 3]
-            rgba_color = colors[i]
-
-            if x2 == x3:
-                xb = x2
-                yb = y1
-            elif y2 == y3:
-                xb = x1
-                yb = y2
-            else:
-                m1 = (y2 - y3) / (x2 - x3)
-                b1 = y2 - (m1 * x2)
-                m2 = -(1.0 / m1)
-                b2 = y1 - (m2 * x1)
-                xb = (-b1 + b2) / (m1 - m2)
-                yb = m2 * xb + b2
-
-            writer.start(
-                'linearGradient',
-                id="GR%x_%d" % (self._n_gradients, i),
-                gradientUnits="userSpaceOnUse",
-                x1=_short_float_fmt(x1), y1=_short_float_fmt(y1),
-                x2=_short_float_fmt(xb), y2=_short_float_fmt(yb))
-            writer.element(
-                'stop',
-                offset='1',
-                style=_generate_css({
-                    'stop-color': rgb2hex(avg_color),
-                    'stop-opacity': _short_float_fmt(rgba_color[-1])}))
-            writer.element(
-                'stop',
-                offset='0',
-                style=_generate_css({'stop-color': rgb2hex(rgba_color),
-                                    'stop-opacity': "0"}))
-
-            writer.end('linearGradient')
-
-        writer.end('defs')
-
-        # triangle formation using "path"
-        dpath = "M " + _short_float_fmt(x1)+',' + _short_float_fmt(y1)
-        dpath += " L " + _short_float_fmt(x2) + ',' + _short_float_fmt(y2)
-        dpath += " " + _short_float_fmt(x3) + ',' + _short_float_fmt(y3) + " Z"
-
-        writer.element(
-            'path',
-            attrib={'d': dpath,
-                    'fill': rgb2hex(avg_color),
-                    'fill-opacity': '1',
-                    'shape-rendering': "crispEdges"})
-
-        writer.start(
-                'g',
-                attrib={'stroke': "none",
-                        'stroke-width': "0",
-                        'shape-rendering': "crispEdges",
-                        'filter': "url(#colorMat)"})
-
-        writer.element(
-            'path',
-            attrib={'d': dpath,
-                    'fill': 'url(#GR%x_0)' % self._n_gradients,
-                    'shape-rendering': "crispEdges"})
-
-        writer.element(
-            'path',
-            attrib={'d': dpath,
-                    'fill': 'url(#GR%x_1)' % self._n_gradients,
-                    'filter': 'url(#colorAdd)',
-                    'shape-rendering': "crispEdges"})
-
-        writer.element(
-            'path',
-            attrib={'d': dpath,
-                    'fill': 'url(#GR%x_2)' % self._n_gradients,
-                    'filter': 'url(#colorAdd)',
-                    'shape-rendering': "crispEdges"})
-
-        writer.end('g')
-
-        self._n_gradients += 1
-
-    def draw_gouraud_triangles(self, gc, triangles_array, colors_array,
-                               transform):
-        self.writer.start('g', **self._get_clip_attrs(gc))
-        transform = transform.frozen()
-        for tri, col in zip(triangles_array, colors_array):
-            self._draw_gouraud_triangle(gc, tri, col, transform)
-        self.writer.end('g')
-
-    def option_scale_image(self):
-        # docstring inherited
-        return True
-
-    def get_image_magnification(self):
-        return self.image_dpi / 72.0
-
-    def draw_image(self, gc, x, y, im, transform=None):
-        # docstring inherited
-
-        h, w = im.shape[:2]
-
-        if w == 0 or h == 0:
-            return
-
-        clip_attrs = self._get_clip_attrs(gc)
-        if clip_attrs:
-            # Can't apply clip-path directly to the image because the image has
-            # a transformation, which would also be applied to the clip-path.
-            self.writer.start('g', **clip_attrs)
-
-        url = gc.get_url()
-        if url is not None:
-            self.writer.start('a', attrib={'xlink:href': url})
-
-        attrib = {}
-        oid = gc.get_gid()
-        if mpl.rcParams['svg.image_inline']:
-            buf = BytesIO()
-            Image.fromarray(im).save(buf, format="png")
-            oid = oid or self._make_id('image', buf.getvalue())
-            attrib['xlink:href'] = (
-                "data:image/png;base64,\n" +
-                base64.b64encode(buf.getvalue()).decode('ascii'))
-        else:
-            if self.basename is None:
-                raise ValueError("Cannot save image data to filesystem when "
-                                 "writing SVG to an in-memory buffer")
-            filename = '{}.image{}.png'.format(
-                self.basename, next(self._image_counter))
-            _log.info('Writing image file for inclusion: %s', filename)
-            Image.fromarray(im).save(filename)
-            oid = oid or 'Im_' + self._make_id('image', filename)
-            attrib['xlink:href'] = filename
-        attrib['id'] = oid
-
-        if transform is None:
-            w = 72.0 * w / self.image_dpi
-            h = 72.0 * h / self.image_dpi
-
-            self.writer.element(
-                'image',
-                transform=_generate_transform([
-                    ('scale', (1, -1)), ('translate', (0, -h))]),
-                x=_short_float_fmt(x),
-                y=_short_float_fmt(-(self.height - y - h)),
-                width=_short_float_fmt(w), height=_short_float_fmt(h),
-                attrib=attrib)
-        else:
-            alpha = gc.get_alpha()
-            if alpha != 1.0:
-                attrib['opacity'] = _short_float_fmt(alpha)
-
-            flipped = (
-                Affine2D().scale(1.0 / w, 1.0 / h) +
-                transform +
-                Affine2D()
-                .translate(x, y)
-                .scale(1.0, -1.0)
-                .translate(0.0, self.height))
-
-            attrib['transform'] = _generate_transform(
-                [('matrix', flipped.frozen())])
-            attrib['style'] = (
-                'image-rendering:crisp-edges;'
-                'image-rendering:pixelated')
-            self.writer.element(
-                'image',
-                width=_short_float_fmt(w), height=_short_float_fmt(h),
-                attrib=attrib)
-
-        if url is not None:
-            self.writer.end('a')
-        if clip_attrs:
-            self.writer.end('g')
-
-    def _update_glyph_map_defs(self, glyph_map_new):
-        """
-        Emit definitions for not-yet-defined glyphs, and record them as having
-        been defined.
-        """
-        writer = self.writer
-        if glyph_map_new:
-            writer.start('defs')
-            for char_id, (vertices, codes) in glyph_map_new.items():
-                char_id = self._adjust_char_id(char_id)
-                # x64 to go back to FreeType's internal (integral) units.
-                path_data = self._convert_path(
-                    Path(vertices * 64, codes), simplify=False)
-                writer.element(
-                    'path', id=char_id, d=path_data,
-                    transform=_generate_transform([('scale', (1 / 64,))]))
-            writer.end('defs')
-            self._glyph_map.update(glyph_map_new)
-
-    def _adjust_char_id(self, char_id):
-        return char_id.replace("%20", "_")
-
-    def _draw_text_as_path(self, gc, x, y, s, prop, angle, ismath, mtext=None):
-        # docstring inherited
-        writer = self.writer
-
-        writer.comment(s)
-
-        glyph_map = self._glyph_map
-
-        text2path = self._text2path
-        color = rgb2hex(gc.get_rgb())
-        fontsize = prop.get_size_in_points()
-
-        style = {}
-        if color != '#000000':
-            style['fill'] = color
-        alpha = gc.get_alpha() if gc.get_forced_alpha() else gc.get_rgb()[3]
-        if alpha != 1:
-            style['opacity'] = _short_float_fmt(alpha)
-        font_scale = fontsize / text2path.FONT_SCALE
-        attrib = {
-            'style': _generate_css(style),
-            'transform': _generate_transform([
-                ('translate', (x, y)),
-                ('rotate', (-angle,)),
-                ('scale', (font_scale, -font_scale))]),
-        }
-        writer.start('g', attrib=attrib)
-
-        if not ismath:
-            font = text2path._get_font(prop)
-            _glyphs = text2path.get_glyphs_with_font(
-                font, s, glyph_map=glyph_map, return_new_glyphs_only=True)
-            glyph_info, glyph_map_new, rects = _glyphs
-            self._update_glyph_map_defs(glyph_map_new)
-
-            for glyph_id, xposition, yposition, scale in glyph_info:
-                attrib = {'xlink:href': '#%s' % glyph_id}
-                if xposition != 0.0:
-                    attrib['x'] = _short_float_fmt(xposition)
-                if yposition != 0.0:
-                    attrib['y'] = _short_float_fmt(yposition)
-                writer.element('use', attrib=attrib)
-
-        else:
-            if ismath == "TeX":
-                _glyphs = text2path.get_glyphs_tex(
-                    prop, s, glyph_map=glyph_map, return_new_glyphs_only=True)
-            else:
-                _glyphs = text2path.get_glyphs_mathtext(
-                    prop, s, glyph_map=glyph_map, return_new_glyphs_only=True)
-            glyph_info, glyph_map_new, rects = _glyphs
-            self._update_glyph_map_defs(glyph_map_new)
-
-            for char_id, xposition, yposition, scale in glyph_info:
-                char_id = self._adjust_char_id(char_id)
-                writer.element(
-                    'use',
-                    transform=_generate_transform([
-                        ('translate', (xposition, yposition)),
-                        ('scale', (scale,)),
-                        ]),
-                    attrib={'xlink:href': '#%s' % char_id})
-
-            for verts, codes in rects:
-                path = Path(verts, codes)
-                path_data = self._convert_path(path, simplify=False)
-                writer.element('path', d=path_data)
-
-        writer.end('g')
-
-    def _draw_text_as_text(self, gc, x, y, s, prop, angle, ismath, mtext=None):
-        writer = self.writer
-
-        color = rgb2hex(gc.get_rgb())
-        style = {}
-        if color != '#000000':
-            style['fill'] = color
-
-        alpha = gc.get_alpha() if gc.get_forced_alpha() else gc.get_rgb()[3]
-        if alpha != 1:
-            style['opacity'] = _short_float_fmt(alpha)
-
-        if not ismath:
-            attrib = {}
-
-            font_parts = []
-            if prop.get_style() != 'normal':
-                font_parts.append(prop.get_style())
-            if prop.get_variant() != 'normal':
-                font_parts.append(prop.get_variant())
-            weight = fm.weight_dict[prop.get_weight()]
-            if weight != 400:
-                font_parts.append(f'{weight}')
-
-            def _normalize_sans(name):
-                return 'sans-serif' if name in ['sans', 'sans serif'] else name
-
-            def _expand_family_entry(fn):
-                fn = _normalize_sans(fn)
-                # prepend generic font families with all configured font names
-                if fn in fm.font_family_aliases:
-                    # get all of the font names and fix spelling of sans-serif
-                    # (we accept 3 ways CSS only supports 1)
-                    for name in fm.FontManager._expand_aliases(fn):
-                        yield _normalize_sans(name)
-                # whether a generic name or a family name, it must appear at
-                # least once
-                yield fn
-
-            def _get_all_quoted_names(prop):
-                # only quote specific names, not generic names
-                return [name if name in fm.font_family_aliases else repr(name)
-                        for entry in prop.get_family()
-                        for name in _expand_family_entry(entry)]
-
-            font_parts.extend([
-                f'{_short_float_fmt(prop.get_size())}px',
-                # ensure expansion, quoting, and dedupe of font names
-                ", ".join(dict.fromkeys(_get_all_quoted_names(prop)))
-            ])
-            style['font'] = ' '.join(font_parts)
-            if prop.get_stretch() != 'normal':
-                style['font-stretch'] = prop.get_stretch()
-            attrib['style'] = _generate_css(style)
-
-            if mtext and (angle == 0 or mtext.get_rotation_mode() == "anchor"):
-                # If text anchoring can be supported, get the original
-                # coordinates and add alignment information.
-
-                # Get anchor coordinates.
-                transform = mtext.get_transform()
-                ax, ay = transform.transform(mtext.get_unitless_position())
-                ay = self.height - ay
-
-                # Don't do vertical anchor alignment. Most applications do not
-                # support 'alignment-baseline' yet. Apply the vertical layout
-                # to the anchor point manually for now.
-                angle_rad = np.deg2rad(angle)
-                dir_vert = np.array([np.sin(angle_rad), np.cos(angle_rad)])
-                v_offset = np.dot(dir_vert, [(x - ax), (y - ay)])
-                ax = ax + v_offset * dir_vert[0]
-                ay = ay + v_offset * dir_vert[1]
-
-                ha_mpl_to_svg = {'left': 'start', 'right': 'end',
-                                 'center': 'middle'}
-                style['text-anchor'] = ha_mpl_to_svg[mtext.get_ha()]
-
-                attrib['x'] = _short_float_fmt(ax)
-                attrib['y'] = _short_float_fmt(ay)
-                attrib['style'] = _generate_css(style)
-                attrib['transform'] = _generate_transform([
-                    ("rotate", (-angle, ax, ay))])
-
-            else:
-                attrib['transform'] = _generate_transform([
-                    ('translate', (x, y)),
-                    ('rotate', (-angle,))])
-
-            writer.element('text', s, attrib=attrib)
-
-        else:
-            writer.comment(s)
-
-            width, height, descent, glyphs, rects = \
-                self._text2path.mathtext_parser.parse(s, 72, prop)
-
-            # Apply attributes to 'g', not 'text', because we likely have some
-            # rectangles as well with the same style and transformation.
-            writer.start('g',
-                         style=_generate_css(style),
-                         transform=_generate_transform([
-                             ('translate', (x, y)),
-                             ('rotate', (-angle,))]),
-                         )
-
-            writer.start('text')
-
-            # Sort the characters by font, and output one tspan for each.
-            spans = {}
-            for font, fontsize, thetext, new_x, new_y in glyphs:
-                entry = fm.ttfFontProperty(font)
-                font_parts = []
-                if entry.style != 'normal':
-                    font_parts.append(entry.style)
-                if entry.variant != 'normal':
-                    font_parts.append(entry.variant)
-                if entry.weight != 400:
-                    font_parts.append(f'{entry.weight}')
-                font_parts.extend([
-                    f'{_short_float_fmt(fontsize)}px',
-                    f'{entry.name!r}',  # ensure quoting
-                ])
-                style = {'font': ' '.join(font_parts)}
-                if entry.stretch != 'normal':
-                    style['font-stretch'] = entry.stretch
-                style = _generate_css(style)
-                if thetext == 32:
-                    thetext = 0xa0  # non-breaking space
-                spans.setdefault(style, []).append((new_x, -new_y, thetext))
-
-            for style, chars in spans.items():
-                chars.sort()
-
-                if len({y for x, y, t in chars}) == 1:  # Are all y's the same?
-                    ys = str(chars[0][1])
-                else:
-                    ys = ' '.join(str(c[1]) for c in chars)
-
-                attrib = {
-                    'style': style,
-                    'x': ' '.join(_short_float_fmt(c[0]) for c in chars),
-                    'y': ys
-                    }
-
-                writer.element(
-                    'tspan',
-                    ''.join(chr(c[2]) for c in chars),
-                    attrib=attrib)
-
-            writer.end('text')
-
-            for x, y, width, height in rects:
-                writer.element(
-                    'rect',
-                    x=_short_float_fmt(x),
-                    y=_short_float_fmt(-y-1),
-                    width=_short_float_fmt(width),
-                    height=_short_float_fmt(height)
-                    )
-
-            writer.end('g')
-
-    def draw_text(self, gc, x, y, s, prop, angle, ismath=False, mtext=None):
-        # docstring inherited
-
-        clip_attrs = self._get_clip_attrs(gc)
-        if clip_attrs:
-            # Cannot apply clip-path directly to the text, because
-            # it has a transformation
-            self.writer.start('g', **clip_attrs)
-
-        if gc.get_url() is not None:
-            self.writer.start('a', {'xlink:href': gc.get_url()})
-
-        if mpl.rcParams['svg.fonttype'] == 'path':
-            self._draw_text_as_path(gc, x, y, s, prop, angle, ismath, mtext)
-        else:
-            self._draw_text_as_text(gc, x, y, s, prop, angle, ismath, mtext)
-
-        if gc.get_url() is not None:
-            self.writer.end('a')
-
-        if clip_attrs:
-            self.writer.end('g')
-
-    def flipy(self):
-        # docstring inherited
-        return True
-
-    def get_canvas_width_height(self):
-        # docstring inherited
-        return self.width, self.height
-
-    def get_text_width_height_descent(self, s, prop, ismath):
-        # docstring inherited
-        return self._text2path.get_text_width_height_descent(s, prop, ismath)
-
-
-class FigureCanvasSVG(FigureCanvasBase):
-    filetypes = {'svg': 'Scalable Vector Graphics',
-                 'svgz': 'Scalable Vector Graphics'}
-
-    fixed_dpi = 72
-
-    def print_svg(self, filename, *, bbox_inches_restore=None, metadata=None):
-        """
-        Parameters
-        ----------
-        filename : str or path-like or file-like
-            Output target; if a string, a file will be opened for writing.
-
-        metadata : dict[str, Any], optional
-            Metadata in the SVG file defined as key-value pairs of strings,
-            datetimes, or lists of strings, e.g., ``{'Creator': 'My software',
-            'Contributor': ['Me', 'My Friend'], 'Title': 'Awesome'}``.
-
-            The standard keys and their value types are:
-
-            * *str*: ``'Coverage'``, ``'Description'``, ``'Format'``,
-              ``'Identifier'``, ``'Language'``, ``'Relation'``, ``'Source'``,
-              ``'Title'``, and ``'Type'``.
-            * *str* or *list of str*: ``'Contributor'``, ``'Creator'``,
-              ``'Keywords'``, ``'Publisher'``, and ``'Rights'``.
-            * *str*, *date*, *datetime*, or *tuple* of same: ``'Date'``. If a
-              non-*str*, then it will be formatted as ISO 8601.
-
-            Values have been predefined for ``'Creator'``, ``'Date'``,
-            ``'Format'``, and ``'Type'``. They can be removed by setting them
-            to `None`.
-
-            Information is encoded as `Dublin Core Metadata`__.
-
-            .. _DC: https://www.dublincore.org/specifications/dublin-core/
-
-            __ DC_
-        """
-        with cbook.open_file_cm(filename, "w", encoding="utf-8") as fh:
-            if not cbook.file_requires_unicode(fh):
-                fh = codecs.getwriter('utf-8')(fh)
-            dpi = self.figure.dpi
-            self.figure.dpi = 72
-            width, height = self.figure.get_size_inches()
-            w, h = width * 72, height * 72
-            renderer = MixedModeRenderer(
-                self.figure, width, height, dpi,
-                RendererSVG(w, h, fh, image_dpi=dpi, metadata=metadata),
-                bbox_inches_restore=bbox_inches_restore)
-            self.figure.draw(renderer)
-            renderer.finalize()
-
-    def print_svgz(self, filename, **kwargs):
-        with cbook.open_file_cm(filename, "wb") as fh, \
-                gzip.GzipFile(mode='w', fileobj=fh) as gzipwriter:
-            return self.print_svg(gzipwriter, **kwargs)
-
-    def get_default_filetype(self):
-        return 'svg'
-
-    def draw(self):
-        self.figure.draw_without_rendering()
-        return super().draw()
-
-
-FigureManagerSVG = FigureManagerBase
-
-
-svgProlog = """\
-<?xml version="1.0" encoding="utf-8" standalone="no"?>
-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
-  "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
-"""
-
-
-@_Backend.export
-class _BackendSVG(_Backend):
-    backend_version = mpl.__version__
-    FigureCanvas = FigureCanvasSVG
diff --git a/spaces/leuschnm/TemporalFusionTransformer/.ipynb_checkpoints/app-checkpoint.py b/spaces/leuschnm/TemporalFusionTransformer/.ipynb_checkpoints/app-checkpoint.py
deleted file mode 100644
index eab20813e4cec573c446f5b1ff7c7d4c66ec34ea..0000000000000000000000000000000000000000
--- a/spaces/leuschnm/TemporalFusionTransformer/.ipynb_checkpoints/app-checkpoint.py
+++ /dev/null
@@ -1,116 +0,0 @@
-## Imports
-import pickle
-import warnings
-import streamlit as st
-from pathlib import Path
-
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-import datetime
-
-# import torch
-from torch.distributions import Normal
-from pytorch_forecasting import (
-    TimeSeriesDataSet,
-    TemporalFusionTransformer,
-)
-
-## Functions 
-def raw_preds_to_df(raw,quantiles = None):
-    """
-    raw is output of model.predict with return_index=True
-    quantiles can be provided like [0.1,0.5,0.9] to get interpretable quantiles
-    in the output, time_idx is the first prediction time index (one step after knowledge cutoff)
-    pred_idx the index of the predicted date i.e. time_idx + h - 1
-    """
-    index = raw[2]
-    preds = raw[0].prediction
-    dec_len = preds.shape[1]
-    n_quantiles = preds.shape[-1]
-    preds_df = pd.DataFrame(index.values.repeat(dec_len * n_quantiles, axis=0),columns=index.columns)
-    preds_df = preds_df.assign(h=np.tile(np.repeat(np.arange(1,1+dec_len),n_quantiles),len(preds_df)//(dec_len*n_quantiles)))
-    preds_df = preds_df.assign(q=np.tile(np.arange(n_quantiles),len(preds_df)//n_quantiles))
-    preds_df = preds_df.assign(pred=preds.flatten().cpu().numpy())
-    if quantiles is not None:
-        preds_df['q'] = preds_df['q'].map({i:q for i,q in enumerate(quantiles)})
-
-    preds_df['pred_idx'] = preds_df['time_idx'] + preds_df['h'] - 1
-    return preds_df
-
-def prepare_dataset(parameters, df, rain, temperature, datepicker):
-    if rain != "Default":
-        df["MTXWTH_Day_precip"] = rain_mapping[rain]
-    
-    df["MTXWTH_Temp_min"] = df["MTXWTH_Temp_min"] + temperature
-    df["MTXWTH_Temp_max"] = df["MTXWTH_Temp_max"] + temperature
-
-    lowerbound = datepicker - datetime.timedelta(days = 35) 
-    upperbound = datepicker + datetime.timedelta(days = 30) 
-
-    df = df.loc[(df["Date"]>lowerbound) & (df["Date"]<=upperbound)]
-    
-    df = TimeSeriesDataSet.from_parameters(parameters, df)
-    return df.to_dataloader(train=False, batch_size=256,num_workers = 0)
-
-def predict(model, dataloader): 
-    return model.predict(dataloader, mode="raw", return_x=True, return_index=True)
-    
-## Initiate Data
-with open('data/parameters.pkl', 'rb') as f:
-    parameters = pickle.load(f)
-model = TemporalFusionTransformer.load_from_checkpoint('model/tft_check.ckpt', map_location=torch.device('cpu'))
-
-df = pd.read_pickle('data/test_data.pkl')
-df = df.loc[(df["Branch"] == 15) & (df["Group"].isin(["6","7","4","1"]))]
-
-rain_mapping = {
-    "Yes" : 1,
-    "No" : 0
-}
-
-# Start App
-st.title("Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting")
-
-st.markdown(body = """
-    ### Abstract
-    Multi-horizon forecasting often contains a complex mix of inputs – including
-    static (i.e. time-invariant) covariates, known future inputs, and other exogenous
-    time series that are only observed in the past – without any prior information
-    on how they interact with the target. Several deep learning methods have been
-    proposed, but they are typically ‘black-box’ models which do not shed light on
-    how they use the full range of inputs present in practical scenarios. In this pa-
-    per, we introduce the Temporal Fusion Transformer (TFT) – a novel attention-
-    based architecture which combines high-performance multi-horizon forecasting
-    with interpretable insights into temporal dynamics. To learn temporal rela-
-    tionships at different scales, TFT uses recurrent layers for local processing and
-    interpretable self-attention layers for long-term dependencies. TFT utilizes spe-
-    cialized components to select relevant features and a series of gating layers to
-    suppress unnecessary components, enabling high performance in a wide range of
-    scenarios. On a variety of real-world datasets, we demonstrate significant per-
-    formance improvements over existing benchmarks, and showcase three practical
-    interpretability use cases of TFT.
-""")
-
-rain = st.radio("Rain Indicator", ('Default', 'Yes', 'No'))
-
-temperature = st.slider('Change in Temperature', min_value=-10, max_value=+10, value=0, step=0.25)
-
-datepicker = st.date_input("Start of Forecast", datetime.date(2022, 12, 24), min_value=datetime.date(2022, 6, 26) + datetime.timedelta(days = 35), max_value=datetime.date(2023, 6, 26) - datetime.timedelta(days = 30))
-
-arr = np.random.normal(1, 1, size=100)
-fig, ax = plt.subplots()
-ax.hist(arr, bins=20)
-
-st.pyplot(fig)
-
-st.button("Forecast Sales", type="primary") #on_click=None,
-
-# %%
-preds = raw_preds_to_df(out, quantiles = None)
-
-preds = preds.merge(data_selected[['time_idx','Group','Branch','sales','weight','Date','MTXWTH_Day_precip','MTXWTH_Temp_max','MTXWTH_Temp_min']],how='left',left_on=['pred_idx','Group','Branch'],right_on=['time_idx','Group','Branch'])
-preds.rename(columns={'time_idx_x':'time_idx'},inplace=True)
-preds.drop(columns=['time_idx_y'],inplace=True)
-
-
diff --git a/spaces/lewisliuX123/wechatglm_demo/docker/build.alpine.sh b/spaces/lewisliuX123/wechatglm_demo/docker/build.alpine.sh
deleted file mode 100644
index 6fda600d2d6cac087c5798a53788e8d3da8e17d8..0000000000000000000000000000000000000000
--- a/spaces/lewisliuX123/wechatglm_demo/docker/build.alpine.sh
+++ /dev/null
@@ -1,10 +0,0 @@
-#!/bin/bash
-
-CHATGPT_ON_WECHAT_TAG=1.0.2
-
-docker build -f Dockerfile.alpine \
-             --build-arg CHATGPT_ON_WECHAT_VER=$CHATGPT_ON_WECHAT_TAG \
-             -t zhayujie/chatgpt-on-wechat .
-
-docker tag zhayujie/chatgpt-on-wechat zhayujie/chatgpt-on-wechat:$CHATGPT_ON_WECHAT_TAG-alpine 
-           
\ No newline at end of file
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/BlueSoleil 6.4.275.0WithMobile S.md b/spaces/lincquiQcaudo/Top-20-Diffusion/BlueSoleil 6.4.275.0WithMobile S.md
deleted file mode 100644
index 8047db5a861f3dc830217a7e4f285fe5f1a645d2..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/BlueSoleil 6.4.275.0WithMobile S.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>BlueSoleil 6.4.275.0WithMobile S</h2><br /><p><b><b>DOWNLOAD</b> &#10004;&#10004;&#10004; <a href="https://bytlly.com/2uGywI">https://bytlly.com/2uGywI</a></b></p><br /><br />
-
-... >BlueSoleil 6.4.275.0WithMobile Serial Number</><a href="http://encritim.yolasite.com/resources/Bachelor-Party-Hindi-dubbed-mp4-download.pdf" > ... 1fdad05405<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/Estadisticaparanegociosyeconomia12edicionpdf!!BETTER!! Download.md b/spaces/lincquiQcaudo/Top-20-Diffusion/Estadisticaparanegociosyeconomia12edicionpdf!!BETTER!! Download.md
deleted file mode 100644
index 83011af318e32944159ce780a4f6db7fdc26eb20..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/Estadisticaparanegociosyeconomia12edicionpdf!!BETTER!! Download.md	
+++ /dev/null
@@ -1,11 +0,0 @@
-<h2>estadisticaparanegociosyeconomia12edicionpdfdownload</h2><br /><p><b><b>DOWNLOAD</b> &#10022;&#10022;&#10022; <a href="https://bytlly.com/2uGxeP">https://bytlly.com/2uGxeP</a></b></p><br /><br />
-<br />
-La decimosegunda edición de Técnicas de estadistica para negocios y. point aplicar la regresión lineal 449 Capítulo 12 Ejercicios 450 Intervalos de. Ejercicios.
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-El libro lleno de estos juegos y jugos de estadísticos, y los más populares.
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-Recuerden poner algo dentro del libro para acceder a tus 8a78ff9644<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/lllqqq/so-vits-svc-models-pcr/models.py b/spaces/lllqqq/so-vits-svc-models-pcr/models.py
deleted file mode 100644
index 4cfc5c4c9920cbd1a082f83e861faf86cdd41e74..0000000000000000000000000000000000000000
--- a/spaces/lllqqq/so-vits-svc-models-pcr/models.py
+++ /dev/null
@@ -1,420 +0,0 @@
-import copy
-import math
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import modules.attentions as attentions
-import modules.commons as commons
-import modules.modules as modules
-
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
-
-import utils
-from modules.commons import init_weights, get_padding
-from vdecoder.hifigan.models import Generator
-from utils import f0_to_coarse
-
-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
-
-
-class Encoder(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):
-    # print(x.shape,x_lengths.shape)
-    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
-
-
-class TextEncoder(nn.Module):
-  def __init__(self,
-      out_channels,
-      hidden_channels,
-      kernel_size,
-      n_layers,
-      gin_channels=0,
-      filter_channels=None,
-      n_heads=None,
-      p_dropout=None):
-    super().__init__()
-    self.out_channels = out_channels
-    self.hidden_channels = hidden_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.gin_channels = gin_channels
-    self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
-    self.f0_emb = nn.Embedding(256, hidden_channels)
-
-    self.enc_ =  attentions.Encoder(
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout)
-
-  def forward(self, x, x_mask, f0=None, noice_scale=1):
-    x = x + self.f0_emb(f0).transpose(1,2)
-    x = self.enc_(x * x_mask, x_mask)
-    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) * noice_scale) * x_mask
-
-    return z, m, logs, x_mask
-
-
-
-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
-
-
-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 MultiPeriodDiscriminator(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(MultiPeriodDiscriminator, self).__init__()
-        periods = [2,3,5,7,11]
-
-        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)
-            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 SpeakerEncoder(torch.nn.Module):
-    def __init__(self, mel_n_channels=80, model_num_layers=3, model_hidden_size=256, model_embedding_size=256):
-        super(SpeakerEncoder, self).__init__()
-        self.lstm = nn.LSTM(mel_n_channels, model_hidden_size, model_num_layers, batch_first=True)
-        self.linear = nn.Linear(model_hidden_size, model_embedding_size)
-        self.relu = nn.ReLU()
-
-    def forward(self, mels):
-        self.lstm.flatten_parameters()
-        _, (hidden, _) = self.lstm(mels)
-        embeds_raw = self.relu(self.linear(hidden[-1]))
-        return embeds_raw / torch.norm(embeds_raw, dim=1, keepdim=True)
-
-    def compute_partial_slices(self, total_frames, partial_frames, partial_hop):
-        mel_slices = []
-        for i in range(0, total_frames-partial_frames, partial_hop):
-            mel_range = torch.arange(i, i+partial_frames)
-            mel_slices.append(mel_range)
-
-        return mel_slices
-
-    def embed_utterance(self, mel, partial_frames=128, partial_hop=64):
-        mel_len = mel.size(1)
-        last_mel = mel[:,-partial_frames:]
-
-        if mel_len > partial_frames:
-            mel_slices = self.compute_partial_slices(mel_len, partial_frames, partial_hop)
-            mels = list(mel[:,s] for s in mel_slices)
-            mels.append(last_mel)
-            mels = torch.stack(tuple(mels), 0).squeeze(1)
-
-            with torch.no_grad():
-                partial_embeds = self(mels)
-            embed = torch.mean(partial_embeds, axis=0).unsqueeze(0)
-            #embed = embed / torch.linalg.norm(embed, 2)
-        else:
-            with torch.no_grad():
-                embed = self(last_mel)
-
-        return embed
-
-class F0Decoder(nn.Module):
-    def __init__(self,
-                 out_channels,
-                 hidden_channels,
-                 filter_channels,
-                 n_heads,
-                 n_layers,
-                 kernel_size,
-                 p_dropout,
-                 spk_channels=0):
-        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.spk_channels = spk_channels
-
-        self.prenet = nn.Conv1d(hidden_channels, hidden_channels, 3, padding=1)
-        self.decoder = attentions.FFT(
-            hidden_channels,
-            filter_channels,
-            n_heads,
-            n_layers,
-            kernel_size,
-            p_dropout)
-        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
-        self.f0_prenet = nn.Conv1d(1, hidden_channels , 3, padding=1)
-        self.cond = nn.Conv1d(spk_channels, hidden_channels, 1)
-
-    def forward(self, x, norm_f0, x_mask, spk_emb=None):
-        x = torch.detach(x)
-        if (spk_emb is not None):
-            x = x + self.cond(spk_emb)
-        x += self.f0_prenet(norm_f0)
-        x = self.prenet(x) * x_mask
-        x = self.decoder(x * x_mask, x_mask)
-        x = self.proj(x) * x_mask
-        return x
-
-
-class SynthesizerTrn(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,
-    gin_channels,
-    ssl_dim,
-    n_speakers,
-    sampling_rate=44100,
-    **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.ssl_dim = ssl_dim
-    self.emb_g = nn.Embedding(n_speakers, gin_channels)
-
-    self.pre = nn.Conv1d(ssl_dim, hidden_channels, kernel_size=5, padding=2)
-
-    self.enc_p = TextEncoder(
-        inter_channels,
-        hidden_channels,
-        filter_channels=filter_channels,
-        n_heads=n_heads,
-        n_layers=n_layers,
-        kernel_size=kernel_size,
-        p_dropout=p_dropout
-    )
-    hps = {
-        "sampling_rate": sampling_rate,
-        "inter_channels": inter_channels,
-        "resblock": resblock,
-        "resblock_kernel_sizes": resblock_kernel_sizes,
-        "resblock_dilation_sizes": resblock_dilation_sizes,
-        "upsample_rates": upsample_rates,
-        "upsample_initial_channel": upsample_initial_channel,
-        "upsample_kernel_sizes": upsample_kernel_sizes,
-        "gin_channels": gin_channels,
-    }
-    self.dec = Generator(h=hps)
-    self.enc_q = Encoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16, gin_channels=gin_channels)
-    self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, 4, gin_channels=gin_channels)
-    self.f0_decoder = F0Decoder(
-        1,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout,
-        spk_channels=gin_channels
-    )
-    self.emb_uv = nn.Embedding(2, hidden_channels)
-
-  def forward(self, c, f0, uv, spec, g=None, c_lengths=None, spec_lengths=None):
-    g = self.emb_g(g).transpose(1,2)
-    # ssl prenet
-    x_mask = torch.unsqueeze(commons.sequence_mask(c_lengths, c.size(2)), 1).to(c.dtype)
-    x = self.pre(c) * x_mask + self.emb_uv(uv.long()).transpose(1,2)
-
-    # f0 predict
-    lf0 = 2595. * torch.log10(1. + f0.unsqueeze(1) / 700.) / 500
-    norm_lf0 = utils.normalize_f0(lf0, x_mask, uv)
-    pred_lf0 = self.f0_decoder(x, norm_lf0, x_mask, spk_emb=g)
-
-    # encoder
-    z_ptemp, m_p, logs_p, _ = self.enc_p(x, x_mask, f0=f0_to_coarse(f0))
-    z, m_q, logs_q, spec_mask = self.enc_q(spec, spec_lengths, g=g) 
-
-    # flow
-    z_p = self.flow(z, spec_mask, g=g)
-    z_slice, pitch_slice, ids_slice = commons.rand_slice_segments_with_pitch(z, f0, spec_lengths, self.segment_size)
-
-    # nsf decoder
-    o = self.dec(z_slice, g=g, f0=pitch_slice)
-
-    return o, ids_slice, spec_mask, (z, z_p, m_p, logs_p, m_q, logs_q), pred_lf0, norm_lf0, lf0
-
-  def infer(self, c, f0, uv, g=None, noice_scale=0.35, predict_f0=False):
-    c_lengths = (torch.ones(c.size(0)) * c.size(-1)).to(c.device)
-    g = self.emb_g(g).transpose(1,2)
-    x_mask = torch.unsqueeze(commons.sequence_mask(c_lengths, c.size(2)), 1).to(c.dtype)
-    x = self.pre(c) * x_mask + self.emb_uv(uv.long()).transpose(1,2)
-
-    if predict_f0:
-        lf0 = 2595. * torch.log10(1. + f0.unsqueeze(1) / 700.) / 500
-        norm_lf0 = utils.normalize_f0(lf0, x_mask, uv, random_scale=False)
-        pred_lf0 = self.f0_decoder(x, norm_lf0, x_mask, spk_emb=g)
-        f0 = (700 * (torch.pow(10, pred_lf0 * 500 / 2595) - 1)).squeeze(1)
-
-    z_p, m_p, logs_p, c_mask = self.enc_p(x, x_mask, f0=f0_to_coarse(f0), noice_scale=noice_scale)
-    z = self.flow(z_p, c_mask, g=g, reverse=True)
-    o = self.dec(z * c_mask, g=g, f0=f0)
-    return o,f0
diff --git a/spaces/lunarring/latentblending/ldm/modules/midas/api.py b/spaces/lunarring/latentblending/ldm/modules/midas/api.py
deleted file mode 100644
index b58ebbffd942a2fc22264f0ab47e400c26b9f41c..0000000000000000000000000000000000000000
--- a/spaces/lunarring/latentblending/ldm/modules/midas/api.py
+++ /dev/null
@@ -1,170 +0,0 @@
-# based on https://github.com/isl-org/MiDaS
-
-import cv2
-import torch
-import torch.nn as nn
-from torchvision.transforms import Compose
-
-from ldm.modules.midas.midas.dpt_depth import DPTDepthModel
-from ldm.modules.midas.midas.midas_net import MidasNet
-from ldm.modules.midas.midas.midas_net_custom import MidasNet_small
-from ldm.modules.midas.midas.transforms import Resize, NormalizeImage, PrepareForNet
-
-
-ISL_PATHS = {
-    "dpt_large": "midas_models/dpt_large-midas-2f21e586.pt",
-    "dpt_hybrid": "midas_models/dpt_hybrid-midas-501f0c75.pt",
-    "midas_v21": "",
-    "midas_v21_small": "",
-}
-
-
-def disabled_train(self, mode=True):
-    """Overwrite model.train with this function to make sure train/eval mode
-    does not change anymore."""
-    return self
-
-
-def load_midas_transform(model_type):
-    # https://github.com/isl-org/MiDaS/blob/master/run.py
-    # load transform only
-    if model_type == "dpt_large":  # DPT-Large
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-
-    elif model_type == "dpt_hybrid":  # DPT-Hybrid
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-
-    elif model_type == "midas_v21":
-        net_w, net_h = 384, 384
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-
-    elif model_type == "midas_v21_small":
-        net_w, net_h = 256, 256
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-
-    else:
-        assert False, f"model_type '{model_type}' not implemented, use: --model_type large"
-
-    transform = Compose(
-        [
-            Resize(
-                net_w,
-                net_h,
-                resize_target=None,
-                keep_aspect_ratio=True,
-                ensure_multiple_of=32,
-                resize_method=resize_mode,
-                image_interpolation_method=cv2.INTER_CUBIC,
-            ),
-            normalization,
-            PrepareForNet(),
-        ]
-    )
-
-    return transform
-
-
-def load_model(model_type):
-    # https://github.com/isl-org/MiDaS/blob/master/run.py
-    # load network
-    model_path = ISL_PATHS[model_type]
-    if model_type == "dpt_large":  # DPT-Large
-        model = DPTDepthModel(
-            path=model_path,
-            backbone="vitl16_384",
-            non_negative=True,
-        )
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-
-    elif model_type == "dpt_hybrid":  # DPT-Hybrid
-        model = DPTDepthModel(
-            path=model_path,
-            backbone="vitb_rn50_384",
-            non_negative=True,
-        )
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-
-    elif model_type == "midas_v21":
-        model = MidasNet(model_path, non_negative=True)
-        net_w, net_h = 384, 384
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(
-            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
-        )
-
-    elif model_type == "midas_v21_small":
-        model = MidasNet_small(model_path, features=64, backbone="efficientnet_lite3", exportable=True,
-                               non_negative=True, blocks={'expand': True})
-        net_w, net_h = 256, 256
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(
-            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
-        )
-
-    else:
-        print(f"model_type '{model_type}' not implemented, use: --model_type large")
-        assert False
-
-    transform = Compose(
-        [
-            Resize(
-                net_w,
-                net_h,
-                resize_target=None,
-                keep_aspect_ratio=True,
-                ensure_multiple_of=32,
-                resize_method=resize_mode,
-                image_interpolation_method=cv2.INTER_CUBIC,
-            ),
-            normalization,
-            PrepareForNet(),
-        ]
-    )
-
-    return model.eval(), transform
-
-
-class MiDaSInference(nn.Module):
-    MODEL_TYPES_TORCH_HUB = [
-        "DPT_Large",
-        "DPT_Hybrid",
-        "MiDaS_small"
-    ]
-    MODEL_TYPES_ISL = [
-        "dpt_large",
-        "dpt_hybrid",
-        "midas_v21",
-        "midas_v21_small",
-    ]
-
-    def __init__(self, model_type):
-        super().__init__()
-        assert (model_type in self.MODEL_TYPES_ISL)
-        model, _ = load_model(model_type)
-        self.model = model
-        self.model.train = disabled_train
-
-    def forward(self, x):
-        # x in 0..1 as produced by calling self.transform on a 0..1 float64 numpy array
-        # NOTE: we expect that the correct transform has been called during dataloading.
-        with torch.no_grad():
-            prediction = self.model(x)
-            prediction = torch.nn.functional.interpolate(
-                prediction.unsqueeze(1),
-                size=x.shape[2:],
-                mode="bicubic",
-                align_corners=False,
-            )
-        assert prediction.shape == (x.shape[0], 1, x.shape[2], x.shape[3])
-        return prediction
-
diff --git a/spaces/m-a-p/Music-Descriptor/README.md b/spaces/m-a-p/Music-Descriptor/README.md
deleted file mode 100644
index 4838ad7c553e1dc7bfd92be544573a6706d14b57..0000000000000000000000000000000000000000
--- a/spaces/m-a-p/Music-Descriptor/README.md
+++ /dev/null
@@ -1,40 +0,0 @@
----
-title: Music Descriptor
-emoji: 🚀
-colorFrom: blue
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.29.0
-app_file: app.py
-pinned: true
-license: cc-by-nc-4.0
----
-
-<!-- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference -->
-
-# Demo Introduction
-This is an example of using the [MERT-v1-95M](https://huggingface.co/m-a-p/MERT-v1-95M) model as backbone to conduct multiple music understanding tasks with the universal represenation.
-
-The tasks include EMO, GS, MTGInstrument, MTGGenre, MTGTop50, MTGMood, NSynthI, NSynthP, VocalSetS, VocalSetT. 
-
-More models can be referred at the [map organization page](https://huggingface.co/m-a-p).
-
-# Known Issues
-
-## Audio Format Support
-
-Theorectically, all the audio formats supported by [torchaudio.load()](https://pytorch.org/audio/stable/torchaudio.html#torchaudio.load) can be used in the demo. Theese should include but not limited to `WAV, AMB, MP3, FLAC`.
-
-## Error Output
-
-Due the **hardware limitation** of the machine hosting our demospecification (2 CPU and 16GB RAM), there might be `Error` output when uploading long audios. 
-
-Unfortunately, we couldn't fix this in a short time since our team are all volunteer researchers.
-
-We recommend to test audios less than 30 seconds or using the live mode if you are trying the [Music Descriptor demo](https://huggingface.co/spaces/m-a-p/Music-Descriptor) hosted online at HuggingFace Space.
-
-This issue is expected to solve in the future by applying more community-support GPU resources or using other audio encoding strategy.
-
-In the current stage, if you want to directly run the demo with longer audios, you could:
-* clone this space `git clone https://huggingface.co/spaces/m-a-p/Music-Descriptor` and deploy the demo on your own machine with higher performance following the [official instruction](https://huggingface.co/docs/hub/spaces). The code will automatically use GPU for inference if there is GPU that can be detected by `torch.cuda.is_available()`. 
-* develop your own application with the MERT models if you have the experience of machine learning.
\ No newline at end of file
diff --git a/spaces/ma-xu/LIVE/thrust/thrust/system/tbb/detail/scan.h b/spaces/ma-xu/LIVE/thrust/thrust/system/tbb/detail/scan.h
deleted file mode 100644
index 32a05a5a6bd3a5be92bbd84c1bf4edb9e929abeb..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/thrust/thrust/system/tbb/detail/scan.h
+++ /dev/null
@@ -1,64 +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 scan.h
- *  \brief TBB implementations of scan functions.
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <thrust/system/tbb/detail/execution_policy.h>
-
-namespace thrust
-{
-namespace system
-{
-namespace tbb
-{
-namespace detail
-{
-
-template<typename InputIterator,
-         typename OutputIterator,
-         typename BinaryFunction>
-  OutputIterator inclusive_scan(tag,
-                                InputIterator first,
-                                InputIterator last,
-                                OutputIterator result,
-                                BinaryFunction binary_op);
-
-
-template<typename InputIterator,
-         typename OutputIterator,
-         typename T,
-         typename BinaryFunction>
-  OutputIterator exclusive_scan(tag,
-                                InputIterator first,
-                                InputIterator last,
-                                OutputIterator result,
-                                T init,
-                                BinaryFunction binary_op);
-
-
-} // end namespace detail
-} // end namespace tbb
-} // end namespace system
-} // end namespace thrust
-
-#include <thrust/system/tbb/detail/scan.inl>
-
diff --git a/spaces/magicr/BuboGPT/bubogpt/datasets/__init__.py b/spaces/magicr/BuboGPT/bubogpt/datasets/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/magicr/BuboGPT/bubogpt/tasks/base_task.py b/spaces/magicr/BuboGPT/bubogpt/tasks/base_task.py
deleted file mode 100644
index 421cc24c2d7748495d4282aa294f64e4c4a248a3..0000000000000000000000000000000000000000
--- a/spaces/magicr/BuboGPT/bubogpt/tasks/base_task.py
+++ /dev/null
@@ -1,305 +0,0 @@
-"""
- Copyright (c) 2022, salesforce.com, inc.
- All rights reserved.
- SPDX-License-Identifier: BSD-3-Clause
- For full license text, see the LICENSE_Lavis file in the repo root or https://opensource.org/licenses/BSD-3-Clause
-"""
-
-import logging
-import os
-
-import torch
-import torch.distributed as dist
-from bubogpt.common.dist_utils import get_rank, get_world_size, is_main_process, is_dist_avail_and_initialized
-from bubogpt.common.logger import MetricLogger, SmoothedValue
-from bubogpt.common.registry import registry
-from bubogpt.datasets.data_utils import prepare_sample
-
-
-def get_data_type(config, builder):
-    data_type = config.get("data_type", None)
-    if data_type is not None:
-        return data_type
-
-    if isinstance(builder.data_type, str):
-        return builder.data_type
-    elif isinstance(builder.data_type, (tuple, list)):
-        return "_".join(builder.data_type)
-    else:
-        raise RuntimeError(f"Data type: {builder.data_type} not recognized!")
-
-
-class BaseTask:
-    def __init__(self, **kwargs):
-        super().__init__()
-
-        self.inst_id_key = "instance_id"
-
-    @classmethod
-    def setup_task(cls, **kwargs):
-        return cls()
-
-    def build_model(self, cfg):
-        model_config = cfg.model_cfg
-
-        model_cls = registry.get_model_class(model_config.arch)
-        return model_cls.from_config(model_config)
-
-    def build_datasets(self, cfg):
-        """
-        Build a dictionary of datasets, keyed by split 'train', 'valid', 'test'.
-        Download dataset and annotations automatically if not exist.
-
-        Args:
-            cfg (common.config.Config): _description_
-
-        Returns:
-            dict: Dictionary of torch.utils.data.Dataset objects by split.
-        """
-
-        datasets = dict()
-
-        datasets_config = cfg.datasets_cfg
-
-        assert len(datasets_config) > 0, "At least one dataset has to be specified."
-
-        for name in datasets_config:
-            dataset_config = datasets_config[name]
-
-            builder = registry.get_builder_class(name)(dataset_config)
-            dataset = builder.build_datasets()
-
-            dataset['train'].name = name
-            if 'sample_ratio' in dataset_config:
-                dataset['train'].sample_ratio = dataset_config.sample_ratio
-            for k, v in dataset.items():
-                v.data_type = get_data_type(datasets_config, builder)
-                if 'dtype_ratio' in dataset_config:
-                    v.dtype_ratio = dataset_config['dtype_ratio']
-                else:
-                    v.dtype_ratio = None
-
-            datasets[name] = dataset
-
-        return datasets
-
-    def train_step(self, model, samples):
-        loss = model(samples)["loss"]
-        return loss
-
-    def valid_step(self, model, samples):
-        raise NotImplementedError
-
-    def before_evaluation(self, model, dataset, **kwargs):
-        model.before_evaluation(dataset=dataset, task_type=type(self))
-
-    def after_evaluation(self, **kwargs):
-        pass
-
-    def inference_step(self):
-        raise NotImplementedError
-
-    def evaluation(self, model, data_loader, cuda_enabled=True):
-        metric_logger = MetricLogger(delimiter="  ")
-        header = "Evaluation"
-        # TODO make it configurable
-        print_freq = 10
-
-        results = []
-
-        for samples in metric_logger.log_every(data_loader, print_freq, header):
-            samples = prepare_sample(samples, cuda_enabled=cuda_enabled)
-
-            eval_output = self.valid_step(model=model, samples=samples)
-            results.extend(eval_output)
-
-        if is_dist_avail_and_initialized():
-            dist.barrier()
-
-        return results
-
-    def train_epoch(
-        self,
-        epoch,
-        model,
-        data_loader,
-        optimizer,
-        lr_scheduler,
-        scaler=None,
-        cuda_enabled=False,
-        log_freq=50,
-        accum_grad_iters=1,
-    ):
-        return self._train_inner_loop(
-            epoch=epoch,
-            iters_per_epoch=lr_scheduler.iters_per_epoch,
-            model=model,
-            data_loader=data_loader,
-            optimizer=optimizer,
-            scaler=scaler,
-            lr_scheduler=lr_scheduler,
-            log_freq=log_freq,
-            cuda_enabled=cuda_enabled,
-            accum_grad_iters=accum_grad_iters,
-        )
-
-    def train_iters(
-        self,
-        epoch,
-        start_iters,
-        iters_per_inner_epoch,
-        model,
-        data_loader,
-        optimizer,
-        lr_scheduler,
-        scaler=None,
-        cuda_enabled=False,
-        log_freq=50,
-        accum_grad_iters=1,
-    ):
-        return self._train_inner_loop(
-            epoch=epoch,
-            start_iters=start_iters,
-            iters_per_epoch=iters_per_inner_epoch,
-            model=model,
-            data_loader=data_loader,
-            optimizer=optimizer,
-            scaler=scaler,
-            lr_scheduler=lr_scheduler,
-            log_freq=log_freq,
-            cuda_enabled=cuda_enabled,
-            accum_grad_iters=accum_grad_iters,
-        )
-
-    def _train_inner_loop(
-        self,
-        epoch,
-        iters_per_epoch,
-        model,
-        data_loader,
-        optimizer,
-        lr_scheduler,
-        scaler=None,
-        start_iters=None,
-        log_freq=50,
-        cuda_enabled=False,
-        accum_grad_iters=1,
-    ):
-        """
-        An inner training loop compatible with both epoch-based and iter-based training.
-
-        When using epoch-based, training stops after one epoch; when using iter-based,
-        training stops after #iters_per_epoch iterations.
-        """
-        use_amp = scaler is not None
-
-        if not hasattr(data_loader, "__next__"):
-            # convert to iterator if not already
-            data_loader = iter(data_loader)
-
-        metric_logger = MetricLogger(delimiter="  ")
-        metric_logger.add_meter("lr", SmoothedValue(window_size=1, fmt="{value:.6f}"))
-        metric_logger.add_meter("loss", SmoothedValue(window_size=1, fmt="{value:.4f}"))
-
-        # if iter-based runner, schedule lr based on inner epoch.
-        logging.info(
-            "Start training epoch {}, {} iters per inner epoch.".format(
-                epoch, iters_per_epoch
-            )
-        )
-        header = "Train: data epoch: [{}]".format(epoch)
-        if start_iters is None:
-            # epoch-based runner
-            inner_epoch = epoch
-        else:
-            # In iter-based runner, we schedule the learning rate based on iterations.
-            inner_epoch = start_iters // iters_per_epoch
-            header = header + "; inner epoch [{}]".format(inner_epoch)
-
-        for i in metric_logger.log_every(range(iters_per_epoch), log_freq, header):
-            # if using iter-based runner, we stop after iters_per_epoch iterations.
-            if i >= iters_per_epoch:
-                break
-
-            samples = next(data_loader)
-
-            samples = prepare_sample(samples, cuda_enabled=cuda_enabled)
-            samples.update(
-                {
-                    "epoch": inner_epoch,
-                    "num_iters_per_epoch": iters_per_epoch,
-                    "iters": i,
-                }
-            )
-
-            lr_scheduler.step(cur_epoch=inner_epoch, cur_step=i)
-
-            with torch.cuda.amp.autocast(enabled=use_amp):
-                loss = self.train_step(model=model, samples=samples)
-
-            # after_train_step()
-            if use_amp:
-                scaler.scale(loss).backward()
-            else:
-                loss.backward()
-
-            # update gradients every accum_grad_iters iterations
-            if (i + 1) % accum_grad_iters == 0:
-                if use_amp:
-                    scaler.step(optimizer)
-                    scaler.update()                     
-                else:    
-                    optimizer.step()
-                optimizer.zero_grad()
-
-            metric_logger.update(loss=loss.item())
-            metric_logger.update(lr=optimizer.param_groups[0]["lr"])
-
-        # after train_epoch()
-        # gather the stats from all processes
-        metric_logger.synchronize_between_processes()
-        logging.info("Averaged stats: " + str(metric_logger.global_avg()))
-        return {
-            k: "{:.3f}".format(meter.global_avg)
-            for k, meter in metric_logger.meters.items()
-        }
-
-    @staticmethod
-    def save_result(result, result_dir, filename, remove_duplicate=""):
-        import json
-
-        result_file = os.path.join(
-            result_dir, "%s_rank%d.json" % (filename, get_rank())
-        )
-        final_result_file = os.path.join(result_dir, "%s.json" % filename)
-
-        json.dump(result, open(result_file, "w"))
-
-        if is_dist_avail_and_initialized():
-            dist.barrier()
-
-        if is_main_process():
-            logging.warning("rank %d starts merging results." % get_rank())
-            # combine results from all processes
-            result = []
-
-            for rank in range(get_world_size()):
-                result_file = os.path.join(
-                    result_dir, "%s_rank%d.json" % (filename, rank)
-                )
-                res = json.load(open(result_file, "r"))
-                result += res
-
-            if remove_duplicate:
-                result_new = []
-                id_list = []
-                for res in result:
-                    if res[remove_duplicate] not in id_list:
-                        id_list.append(res[remove_duplicate])
-                        result_new.append(res)
-                result = result_new
-
-            json.dump(result, open(final_result_file, "w"))
-            print("result file saved to %s" % final_result_file)
-
-        return final_result_file
diff --git a/spaces/manhkhanhUIT/BOPBTL/Global/models/models.py b/spaces/manhkhanhUIT/BOPBTL/Global/models/models.py
deleted file mode 100644
index fd7defde2b02567e1903870c6744c072580ee938..0000000000000000000000000000000000000000
--- a/spaces/manhkhanhUIT/BOPBTL/Global/models/models.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-import torch
-
-
-def create_model(opt):
-    if opt.model == "pix2pixHD":
-        from .pix2pixHD_model import Pix2PixHDModel, InferenceModel
-
-        if opt.isTrain:
-            model = Pix2PixHDModel()
-        else:
-            model = InferenceModel()
-    else:
-        from .ui_model import UIModel
-
-        model = UIModel()
-    model.initialize(opt)
-    if opt.verbose:
-        print("model [%s] was created" % (model.name()))
-
-    if opt.isTrain and len(opt.gpu_ids) > 1:
-        # pass
-        model = torch.nn.DataParallel(model, device_ids=opt.gpu_ids)
-
-    return model
-
-def create_da_model(opt):
-    if opt.model == 'pix2pixHD':
-        from .pix2pixHD_model_DA import Pix2PixHDModel, InferenceModel
-        if opt.isTrain:
-            model = Pix2PixHDModel()
-        else:
-            model = InferenceModel()
-    else:
-    	from .ui_model import UIModel
-    	model = UIModel()
-    model.initialize(opt)
-    if opt.verbose:
-        print("model [%s] was created" % (model.name()))
-
-    if opt.isTrain and len(opt.gpu_ids) > 1:
-        #pass
-        model = torch.nn.DataParallel(model, device_ids=opt.gpu_ids)
-
-    return model
\ No newline at end of file
diff --git a/spaces/manhkhanhUIT/BOPBTL/Global/models/pix2pixHD_model.py b/spaces/manhkhanhUIT/BOPBTL/Global/models/pix2pixHD_model.py
deleted file mode 100644
index edf829f7340d15007ab7563e88ace974cf8d08ee..0000000000000000000000000000000000000000
--- a/spaces/manhkhanhUIT/BOPBTL/Global/models/pix2pixHD_model.py
+++ /dev/null
@@ -1,333 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-import numpy as np
-import torch
-import os
-from torch.autograd import Variable
-from util.image_pool import ImagePool
-from .base_model import BaseModel
-from . import networks
-
-class Pix2PixHDModel(BaseModel):
-    def name(self):
-        return 'Pix2PixHDModel'
-    
-    def init_loss_filter(self, use_gan_feat_loss, use_vgg_loss,use_smooth_L1):
-        flags = (True, use_gan_feat_loss, use_vgg_loss, True, True, True,use_smooth_L1)
-        def loss_filter(g_gan, g_gan_feat, g_vgg, g_kl, d_real, d_fake,smooth_l1):
-            return [l for (l,f) in zip((g_gan,g_gan_feat,g_vgg, g_kl, d_real,d_fake,smooth_l1),flags) if f]
-        return loss_filter
-    
-    def initialize(self, opt):
-        BaseModel.initialize(self, opt)
-        if opt.resize_or_crop != 'none' or not opt.isTrain: # when training at full res this causes OOM
-            torch.backends.cudnn.benchmark = True
-        self.isTrain = opt.isTrain
-        self.use_features = opt.instance_feat or opt.label_feat   ## Clearly it is false
-        self.gen_features = self.use_features and not self.opt.load_features ## it is also false
-        input_nc = opt.label_nc if opt.label_nc != 0 else opt.input_nc ## Just is the origin input channel #
-
-        ##### define networks        
-        # Generator network
-        netG_input_nc = input_nc        
-        if not opt.no_instance:
-            netG_input_nc += 1
-        if self.use_features:
-            netG_input_nc += opt.feat_num                  
-        self.netG = networks.define_G(netG_input_nc, opt.output_nc, opt.ngf, opt.netG, opt.k_size, 
-                                      opt.n_downsample_global, opt.n_blocks_global, opt.n_local_enhancers, 
-                                      opt.n_blocks_local, opt.norm, gpu_ids=self.gpu_ids, opt=opt)       
-
-        # Discriminator network
-        if self.isTrain:
-            use_sigmoid = opt.no_lsgan
-            netD_input_nc = opt.output_nc if opt.no_cgan else input_nc + opt.output_nc
-            if not opt.no_instance:
-                netD_input_nc += 1
-            self.netD = networks.define_D(netD_input_nc, opt.ndf, opt.n_layers_D, opt, opt.norm, use_sigmoid,
-                                          opt.num_D, not opt.no_ganFeat_loss, gpu_ids=self.gpu_ids)
-
-        if self.opt.verbose:
-                print('---------- Networks initialized -------------')
-
-        # load networks
-        if not self.isTrain or opt.continue_train or opt.load_pretrain:
-            pretrained_path = '' if not self.isTrain else opt.load_pretrain
-            self.load_network(self.netG, 'G', opt.which_epoch, pretrained_path)
-
-            print("---------- G Networks reloaded -------------")
-            if self.isTrain:
-                self.load_network(self.netD, 'D', opt.which_epoch, pretrained_path)
-                print("---------- D Networks reloaded -------------")
-
-
-            if self.gen_features:
-                self.load_network(self.netE, 'E', opt.which_epoch, pretrained_path)              
-
-        # set loss functions and optimizers
-        if self.isTrain:
-            if opt.pool_size > 0 and (len(self.gpu_ids)) > 1:   ## The pool_size is 0!
-                raise NotImplementedError("Fake Pool Not Implemented for MultiGPU")
-            self.fake_pool = ImagePool(opt.pool_size)
-            self.old_lr = opt.lr
-
-            # define loss functions
-            self.loss_filter = self.init_loss_filter(not opt.no_ganFeat_loss, not opt.no_vgg_loss, opt.Smooth_L1)
-            
-            self.criterionGAN = networks.GANLoss(use_lsgan=not opt.no_lsgan, tensor=self.Tensor)   
-            self.criterionFeat = torch.nn.L1Loss()
-
-            # self.criterionImage = torch.nn.SmoothL1Loss()
-            if not opt.no_vgg_loss:
-                self.criterionVGG = networks.VGGLoss_torch(self.gpu_ids)
-                
-
-            self.loss_names = self.loss_filter('G_GAN','G_GAN_Feat','G_VGG', 'G_KL', 'D_real', 'D_fake', 'Smooth_L1')
-
-            # initialize optimizers
-            # optimizer G
-            params = list(self.netG.parameters())
-            if self.gen_features:              
-                params += list(self.netE.parameters())         
-            self.optimizer_G = torch.optim.Adam(params, lr=opt.lr, betas=(opt.beta1, 0.999))                            
-
-            # optimizer D                        
-            params = list(self.netD.parameters())    
-            self.optimizer_D = torch.optim.Adam(params, lr=opt.lr, betas=(opt.beta1, 0.999))
-
-            print("---------- Optimizers initialized -------------")
-
-            if opt.continue_train:
-                self.load_optimizer(self.optimizer_D, 'D', opt.which_epoch)
-                self.load_optimizer(self.optimizer_G, "G", opt.which_epoch)
-                for param_groups in self.optimizer_D.param_groups:
-                    self.old_lr=param_groups['lr']
-
-                print("---------- Optimizers reloaded -------------")
-                print("---------- Current LR is %.8f -------------"%(self.old_lr))
-
-            ## We also want to re-load the parameters of optimizer.
-
-    def encode_input(self, label_map, inst_map=None, real_image=None, feat_map=None, infer=False):             
-        if self.opt.label_nc == 0:
-            input_label = label_map.data.cuda()
-        else:
-            # create one-hot vector for label map 
-            size = label_map.size()
-            oneHot_size = (size[0], self.opt.label_nc, size[2], size[3])
-            input_label = torch.cuda.FloatTensor(torch.Size(oneHot_size)).zero_()
-            input_label = input_label.scatter_(1, label_map.data.long().cuda(), 1.0)
-            if self.opt.data_type == 16:
-                input_label = input_label.half()
-
-        # get edges from instance map
-        if not self.opt.no_instance:
-            inst_map = inst_map.data.cuda()
-            edge_map = self.get_edges(inst_map)
-            input_label = torch.cat((input_label, edge_map), dim=1)         
-        input_label = Variable(input_label, volatile=infer)
-
-        # real images for training
-        if real_image is not None:
-            real_image = Variable(real_image.data.cuda())
-
-        # instance map for feature encoding
-        if self.use_features:
-            # get precomputed feature maps
-            if self.opt.load_features:
-                feat_map = Variable(feat_map.data.cuda())
-            if self.opt.label_feat:
-                inst_map = label_map.cuda()
-
-        return input_label, inst_map, real_image, feat_map
-
-    def discriminate(self, input_label, test_image, use_pool=False):
-        if input_label is None:
-            input_concat = test_image.detach()
-        else:
-            input_concat = torch.cat((input_label, test_image.detach()), dim=1)
-        if use_pool:            
-            fake_query = self.fake_pool.query(input_concat)
-            return self.netD.forward(fake_query)
-        else:
-            return self.netD.forward(input_concat)
-
-    def forward(self, label, inst, image, feat, infer=False):
-        # Encode Inputs
-        input_label, inst_map, real_image, feat_map = self.encode_input(label, inst, image, feat)  
-
-        # Fake Generation
-        if self.use_features:
-            if not self.opt.load_features:
-                feat_map = self.netE.forward(real_image, inst_map)                     
-            input_concat = torch.cat((input_label, feat_map), dim=1)                        
-        else:
-            input_concat = input_label
-        hiddens = self.netG.forward(input_concat, 'enc')
-        noise = Variable(torch.randn(hiddens.size()).cuda(hiddens.data.get_device()))
-        # This is a reduced VAE implementation where we assume the outputs are multivariate Gaussian distribution with mean = hiddens and std_dev = all ones.
-        # We follow the the VAE of MUNIT (https://github.com/NVlabs/MUNIT/blob/master/networks.py)
-        fake_image = self.netG.forward(hiddens + noise, 'dec')
-
-        if self.opt.no_cgan:
-            # Fake Detection and Loss
-            pred_fake_pool = self.discriminate(None, fake_image, use_pool=True)
-            loss_D_fake = self.criterionGAN(pred_fake_pool, False)        
-
-            # Real Detection and Loss        
-            pred_real = self.discriminate(None, real_image)
-            loss_D_real = self.criterionGAN(pred_real, True)
-
-            # GAN loss (Fake Passability Loss)        
-            pred_fake = self.netD.forward(fake_image)        
-            loss_G_GAN = self.criterionGAN(pred_fake, True)
-        else:
-            # Fake Detection and Loss
-            pred_fake_pool = self.discriminate(input_label, fake_image, use_pool=True)
-            loss_D_fake = self.criterionGAN(pred_fake_pool, False)        
-
-            # Real Detection and Loss        
-            pred_real = self.discriminate(input_label, real_image)
-            loss_D_real = self.criterionGAN(pred_real, True)
-
-            # GAN loss (Fake Passability Loss)        
-            pred_fake = self.netD.forward(torch.cat((input_label, fake_image), dim=1))        
-            loss_G_GAN = self.criterionGAN(pred_fake, True) 
-        
-        
-        loss_G_kl = torch.mean(torch.pow(hiddens, 2)) * self.opt.kl
-
-        # GAN feature matching loss
-        loss_G_GAN_Feat = 0
-        if not self.opt.no_ganFeat_loss:
-            feat_weights = 4.0 / (self.opt.n_layers_D + 1)
-            D_weights = 1.0 / self.opt.num_D
-            for i in range(self.opt.num_D):
-                for j in range(len(pred_fake[i])-1):
-                    loss_G_GAN_Feat += D_weights * feat_weights * \
-                        self.criterionFeat(pred_fake[i][j], pred_real[i][j].detach()) * self.opt.lambda_feat
-                   
-        # VGG feature matching loss
-        loss_G_VGG = 0
-        if not self.opt.no_vgg_loss:
-            loss_G_VGG = self.criterionVGG(fake_image, real_image) * self.opt.lambda_feat
-
-
-        smooth_l1_loss=0
-
-        return [ self.loss_filter( loss_G_GAN, loss_G_GAN_Feat, loss_G_VGG, loss_G_kl, loss_D_real, loss_D_fake,smooth_l1_loss ), None if not infer else fake_image ]
-
-    def inference(self, label, inst, image=None, feat=None):
-        # Encode Inputs        
-        image = Variable(image) if image is not None else None
-        input_label, inst_map, real_image, _ = self.encode_input(Variable(label), Variable(inst), image, infer=True)
-
-        # Fake Generation
-        if self.use_features:
-            if self.opt.use_encoded_image:
-                # encode the real image to get feature map
-                feat_map = self.netE.forward(real_image, inst_map)
-            else:
-                # sample clusters from precomputed features             
-                feat_map = self.sample_features(inst_map)
-            input_concat = torch.cat((input_label, feat_map), dim=1)
-        else:
-            input_concat = input_label        
-           
-        if torch.__version__.startswith('0.4'):
-            with torch.no_grad():
-                fake_image = self.netG.forward(input_concat)
-        else:
-            fake_image = self.netG.forward(input_concat)
-        return fake_image
-
-    def sample_features(self, inst): 
-        # read precomputed feature clusters 
-        cluster_path = os.path.join(self.opt.checkpoints_dir, self.opt.name, self.opt.cluster_path)        
-        features_clustered = np.load(cluster_path, encoding='latin1').item()
-
-        # randomly sample from the feature clusters
-        inst_np = inst.cpu().numpy().astype(int)                                      
-        feat_map = self.Tensor(inst.size()[0], self.opt.feat_num, inst.size()[2], inst.size()[3])
-        for i in np.unique(inst_np):    
-            label = i if i < 1000 else i//1000
-            if label in features_clustered:
-                feat = features_clustered[label]
-                cluster_idx = np.random.randint(0, feat.shape[0]) 
-                                            
-                idx = (inst == int(i)).nonzero()
-                for k in range(self.opt.feat_num):                                    
-                    feat_map[idx[:,0], idx[:,1] + k, idx[:,2], idx[:,3]] = feat[cluster_idx, k]
-        if self.opt.data_type==16:
-            feat_map = feat_map.half()
-        return feat_map
-
-    def encode_features(self, image, inst):
-        image = Variable(image.cuda(), volatile=True)
-        feat_num = self.opt.feat_num
-        h, w = inst.size()[2], inst.size()[3]
-        block_num = 32
-        feat_map = self.netE.forward(image, inst.cuda())
-        inst_np = inst.cpu().numpy().astype(int)
-        feature = {}
-        for i in range(self.opt.label_nc):
-            feature[i] = np.zeros((0, feat_num+1))
-        for i in np.unique(inst_np):
-            label = i if i < 1000 else i//1000
-            idx = (inst == int(i)).nonzero()
-            num = idx.size()[0]
-            idx = idx[num//2,:]
-            val = np.zeros((1, feat_num+1))                        
-            for k in range(feat_num):
-                val[0, k] = feat_map[idx[0], idx[1] + k, idx[2], idx[3]].data[0]            
-            val[0, feat_num] = float(num) / (h * w // block_num)
-            feature[label] = np.append(feature[label], val, axis=0)
-        return feature
-
-    def get_edges(self, t):
-        edge = torch.cuda.ByteTensor(t.size()).zero_()
-        edge[:,:,:,1:] = edge[:,:,:,1:] | (t[:,:,:,1:] != t[:,:,:,:-1])
-        edge[:,:,:,:-1] = edge[:,:,:,:-1] | (t[:,:,:,1:] != t[:,:,:,:-1])
-        edge[:,:,1:,:] = edge[:,:,1:,:] | (t[:,:,1:,:] != t[:,:,:-1,:])
-        edge[:,:,:-1,:] = edge[:,:,:-1,:] | (t[:,:,1:,:] != t[:,:,:-1,:])
-        if self.opt.data_type==16:
-            return edge.half()
-        else:
-            return edge.float()
-
-    def save(self, which_epoch):
-        self.save_network(self.netG, 'G', which_epoch, self.gpu_ids)
-        self.save_network(self.netD, 'D', which_epoch, self.gpu_ids)
-
-        self.save_optimizer(self.optimizer_G,"G",which_epoch)
-        self.save_optimizer(self.optimizer_D,"D",which_epoch)
-
-        if self.gen_features:
-            self.save_network(self.netE, 'E', which_epoch, self.gpu_ids)
-
-    def update_fixed_params(self):
-
-        params = list(self.netG.parameters())
-        if self.gen_features:
-            params += list(self.netE.parameters())           
-        self.optimizer_G = torch.optim.Adam(params, lr=self.opt.lr, betas=(self.opt.beta1, 0.999))
-        if self.opt.verbose:
-            print('------------ Now also finetuning global generator -----------')
-
-    def update_learning_rate(self):
-        lrd = self.opt.lr / self.opt.niter_decay
-        lr = self.old_lr - lrd        
-        for param_group in self.optimizer_D.param_groups:
-            param_group['lr'] = lr
-        for param_group in self.optimizer_G.param_groups:
-            param_group['lr'] = lr
-        if self.opt.verbose:
-            print('update learning rate: %f -> %f' % (self.old_lr, lr))
-        self.old_lr = lr
-
-
-class InferenceModel(Pix2PixHDModel):
-    def forward(self, inp):
-        label, inst = inp
-        return self.inference(label, inst)
diff --git a/spaces/meaqua33/White-box-Cartoonization/wbc/cartoonize.py b/spaces/meaqua33/White-box-Cartoonization/wbc/cartoonize.py
deleted file mode 100644
index 25faf1ceb95aaed9a3f7a7982d17a03dc6bc32b1..0000000000000000000000000000000000000000
--- a/spaces/meaqua33/White-box-Cartoonization/wbc/cartoonize.py
+++ /dev/null
@@ -1,112 +0,0 @@
-import os
-import cv2
-import numpy as np
-import tensorflow as tf
-import wbc.network as network
-import wbc.guided_filter as guided_filter
-from tqdm import tqdm
-
-
-def resize_crop(image):
-    h, w, c = np.shape(image)
-    if min(h, w) > 720:
-        if h > w:
-            h, w = int(720 * h / w), 720
-        else:
-            h, w = 720, int(720 * w / h)
-    image = cv2.resize(image, (w, h),
-                       interpolation=cv2.INTER_AREA)
-    h, w = (h // 8) * 8, (w // 8) * 8
-    image = image[:h, :w, :]
-    return image
-
-
-def cartoonize(load_folder, save_folder, model_path):
-    print(model_path)
-    input_photo = tf.placeholder(tf.float32, [1, None, None, 3])
-    network_out = network.unet_generator(input_photo)
-    final_out = guided_filter.guided_filter(input_photo, network_out, r=1, eps=5e-3)
-
-    all_vars = tf.trainable_variables()
-    gene_vars = [var for var in all_vars if 'generator' in var.name]
-    saver = tf.train.Saver(var_list=gene_vars)
-
-    config = tf.ConfigProto()
-    config.gpu_options.allow_growth = True
-    sess = tf.Session(config=config)
-
-    sess.run(tf.global_variables_initializer())
-    saver.restore(sess, tf.train.latest_checkpoint(model_path))
-    name_list = os.listdir(load_folder)
-    for name in tqdm(name_list):
-        try:
-            load_path = os.path.join(load_folder, name)
-            save_path = os.path.join(save_folder, name)
-            image = cv2.imread(load_path)
-            image = resize_crop(image)
-            batch_image = image.astype(np.float32) / 127.5 - 1
-            batch_image = np.expand_dims(batch_image, axis=0)
-            output = sess.run(final_out, feed_dict={input_photo: batch_image})
-            output = (np.squeeze(output) + 1) * 127.5
-            output = np.clip(output, 0, 255).astype(np.uint8)
-            cv2.imwrite(save_path, output)
-        except:
-            print('cartoonize {} failed'.format(load_path))
-
-
-class Cartoonize:
-    def __init__(self, model_path):
-        print(model_path)
-        self.input_photo = tf.placeholder(tf.float32, [1, None, None, 3])
-        network_out = network.unet_generator(self.input_photo)
-        self.final_out = guided_filter.guided_filter(self.input_photo, network_out, r=1, eps=5e-3)
-
-        all_vars = tf.trainable_variables()
-        gene_vars = [var for var in all_vars if 'generator' in var.name]
-        saver = tf.train.Saver(var_list=gene_vars)
-
-        config = tf.ConfigProto()
-        config.gpu_options.allow_growth = True
-        self.sess = tf.Session(config=config)
-
-        self.sess.run(tf.global_variables_initializer())
-        saver.restore(self.sess, tf.train.latest_checkpoint(model_path))
-
-    def run(self, load_folder, save_folder):
-        name_list = os.listdir(load_folder)
-        for name in tqdm(name_list):
-            try:
-                load_path = os.path.join(load_folder, name)
-                save_path = os.path.join(save_folder, name)
-                image = cv2.imread(load_path)
-                image = resize_crop(image)
-                batch_image = image.astype(np.float32) / 127.5 - 1
-                batch_image = np.expand_dims(batch_image, axis=0)
-                output = self.sess.run(self.final_out, feed_dict={self.input_photo: batch_image})
-                output = (np.squeeze(output) + 1) * 127.5
-                output = np.clip(output, 0, 255).astype(np.uint8)
-                cv2.imwrite(save_path, output)
-            except:
-                print('cartoonize {} failed'.format(load_path))
-
-    def run_sigle(self, load_path, save_path):
-        try:
-            image = cv2.imread(load_path)
-            image = resize_crop(image)
-            batch_image = image.astype(np.float32) / 127.5 - 1
-            batch_image = np.expand_dims(batch_image, axis=0)
-            output = self.sess.run(self.final_out, feed_dict={self.input_photo: batch_image})
-            output = (np.squeeze(output) + 1) * 127.5
-            output = np.clip(output, 0, 255).astype(np.uint8)
-            cv2.imwrite(save_path, output)
-        except:
-            print('cartoonize {} failed'.format(load_path))
-
-
-if __name__ == '__main__':
-    model_path = 'saved_models'
-    load_folder = 'test_images'
-    save_folder = 'cartoonized_images'
-    if not os.path.exists(save_folder):
-        os.mkdir(save_folder)
-    cartoonize(load_folder, save_folder, model_path)
diff --git a/spaces/mehradans92/decode-elm/utils.py b/spaces/mehradans92/decode-elm/utils.py
deleted file mode 100644
index 2dc680bfc35ca0aeed14eb067bf450ec87519819..0000000000000000000000000000000000000000
--- a/spaces/mehradans92/decode-elm/utils.py
+++ /dev/null
@@ -1,228 +0,0 @@
-import urllib
-import streamlit as st 
-import requests
-import re
-from stqdm import stqdm
-import os
-import shutil
-import time
-from bs4 import BeautifulSoup as bs
-from datetime import datetime
-from random import uniform as rand
-import json
-import numpy as np
-
-
-
-
-class XRxivQuery:
-    def __init__(self, search_query, max_results, folder_name='docs', XRxiv_servers = [], search_by='all', sort_by='relevance'):
-       self.search_query = search_query
-       self.max_results = max_results
-       self.folder_name = folder_name
-       self.XRxiv_servers = XRxiv_servers
-       self.search_by = search_by
-       self.sort_by = sort_by
-       self.all_pdf_info = []
-       self.all_pdf_citation = []
-
-    def call_API(self):
-        search_query = self.search_query.strip().replace(" ", "+").split('+')#.replace(", ", "+").replace(",", "+")#.split('+')
-        max_papers_in_server = distibute_max_papers(self.max_results, self.XRxiv_servers)
-        if 'rxiv' in self.XRxiv_servers:
-            '''
-            Scraps the arXiv's html to get data from each entry in a search. Entries has the following formatting:
-            <entry>\n    
-            <id>http://arxiv.org/abs/2008.04584v2</id>\n    
-            <updated>2021-05-11T12:00:24Z</updated>\n    
-            <published>2020-08-11T08:47:06Z</published>\n    
-            <title>Bayesian Selective Inference: Non-informative Priors</title>\n    
-            <summary>  We discuss Bayesian inference for parameters selected using the data. First,\nwe provide a critical analysis of the existing positions in the literature\nregarding the correct Bayesian approach under selection. Second, we propose two\ntypes of non-informative priors for selection models. These priors may be\nemployed to produce a posterior distribution in the absence of prior\ninformation as well as to provide well-calibrated frequentist inference for the\nselected parameter. We test the proposed priors empirically in several\nscenarios.\n</summary>\n    
-            <author>\n      <name>Daniel G. Rasines</name>\n    </author>\n    <author>\n      <name>G. Alastair Young</name>\n    </author>\n    
-            <arxiv:comment xmlns:arxiv="http://arxiv.org/schemas/atom">24 pages, 7 figures</arxiv:comment>\n    
-            <link href="http://arxiv.org/abs/2008.04584v2" rel="alternate" type="text/html"/>\n    
-            <link title="pdf" href="http://arxiv.org/pdf/2008.04584v2" rel="related" type="application/pdf"/>\n    
-            <arxiv:primary_category xmlns:arxiv="http://arxiv.org/schemas/atom" term="math.ST" scheme="http://arxiv.org/schemas/atom"/>\n    
-            <category term="math.ST" scheme="http://arxiv.org/schemas/atom"/>\n    
-            <category term="stat.TH" scheme="http://arxiv.org/schemas/atom"/>\n  
-            </entry>\n  
-            '''
-            # Call arXiv API
-            journal = 'arXiv'
-            max_rxiv_papers = max_papers_in_server[0]
-            arXiv_url=f'http://export.arxiv.org/api/query?search_query={self.search_by}:{"+".join(search_query)}&sortBy={self.sort_by}&start=0&max_results={max_rxiv_papers}'
-            with urllib.request.urlopen(arXiv_url) as url:
-                s = url.read()
-            
-            # Parse the xml data
-            from lxml import html
-            root = html.fromstring(s)
-            # Fetch relevant pdf information
-            pdf_entries = root.xpath("entry")
-            pdf_titles   = []
-            pdf_authors  = []
-            pdf_urls     = []
-            pdf_categories = []
-            folder_names = []
-            pdf_citation = []
-            pdf_years = []
-            for i, pdf in enumerate(pdf_entries):
-                pdf_titles.append(re.sub('[^a-zA-Z0-9]', ' ', pdf.xpath("title/text()")[0]))
-                pdf_authors.append(pdf.xpath("author/name/text()"))
-                pdf_urls.append(pdf.xpath("link[@title='pdf']/@href")[0])
-                pdf_categories.append(pdf.xpath("category/@term"))
-                folder_names.append(self.folder_name)
-                pdf_years.append(pdf.xpath('updated/text()')[0][:4])
-                pdf_citation.append(f"{', '.join(pdf_authors[i])}, {pdf_titles[i]}. {journal} [{pdf_categories[i][0]}] ({pdf_years[i]}), (available at {pdf_urls[i]}).")
-            pdf_info = list(zip(pdf_titles, pdf_urls, pdf_authors, pdf_categories, folder_names, pdf_citation))
-            self.all_pdf_info.append(pdf_info)
-
-        if 'chemrxiv' in self.XRxiv_servers:
-            '''
-            See https://chemrxiv.org/engage/chemrxiv/public-api/documentation#tag/public-apiv1items/operation/getPublicapiV1Items
-
-            '''
-            # Call chemrxiv API
-            journal = 'chemRxiv'
-            max_chemrxiv_papers = max_papers_in_server[1]
-            chemrxiv_url = f'https://chemrxiv.org/engage/chemrxiv/public-api/v1/items?term="{"%20".join(search_query)}"&sort=RELEVANT_DESC&limit={max_chemrxiv_papers}'
-            req = urllib.request.Request(
-                    url=chemrxiv_url, 
-                    headers={'User-Agent': 'Mozilla/5.0'}
-                )
-            s = urllib.request.urlopen(req).read()
-            jsonResponse = json.loads(s.decode('utf-8'))
-            pdf_titles   = []
-            pdf_authors  = []
-            pdf_urls     = []
-            pdf_categories = []
-            folder_names = []
-            pdf_citation = []
-            pdf_years = []
-            for i,d in enumerate(jsonResponse['itemHits']):
-                pdf_titles.append(d['item']['title'].replace("\n", ""))
-                authors_dict = d['item']['authors'] 
-                pdf_authors.append([n['firstName']+' '+ n['lastName'] for n in authors_dict])
-                pdf_urls.append('https://chemrxiv.org/engage/chemrxiv/article-details/'+ str(d['item']['id']))
-                pdf_categories.append(journal)
-                folder_names.append(self.folder_name)
-                pdf_years.append(d['item']['statusDate'][:4])
-                pdf_citation.append(f"{', '.join(pdf_authors[i])}, {pdf_titles[i]}. {journal} [{pdf_categories[i][0]}] ({pdf_years[i]}), (available at {pdf_urls[i]}).")
-                # overwriting url cause chermRxiv sucks!
-                pdf_urls[i] = d['item']['asset']['original']['url']
-            pdf_info = list(zip(pdf_titles, pdf_urls, pdf_authors, pdf_categories, folder_names, pdf_citation))
-            self.all_pdf_info.append(pdf_info)   
-
-
-        if 'biorxiv' in self.XRxiv_servers or 'medrxiv' in self.XRxiv_servers:
-            '''
-            Scraps the biorxiv and medrxiv's html to get data from each entry in a search. Entries has the following formatting:
-            <li class="first last odd search-result result-jcode-medrxiv search-result-highwire-citation">
-            <div class="highwire-article-citation highwire-citation-type-highwire-article node" data-apath="/medrxiv/early/2021/02/18/2021.02.12.21251663.atom" data-pisa="medrxiv;2021.02.12.21251663v1" data-pisa-master="medrxiv;2021.02.12.21251663" id="node-medrxivearly202102182021021221251663atom1512875027"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-biorxiv-article-pap-list clearfix">
-            <span class="highwire-cite-title">
-            <a class="highwire-cite-linked-title" data-hide-link-title="0" data-icon-position="" href="http://medrxiv.org/content/early/2021/02/18/2021.02.12.21251663">
-            <span class="highwire-cite-title">ClinGen Variant Curation Interface: A Variant Classification Platform for the Application of Evidence Criteria from ACMG/AMP Guidelines</span></a> </span>
-            <div class="highwire-cite-authors"><span class="highwire-citation-authors">
-            <span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">Christine G.</span> <span class="nlm-surname">Preston</span></span>,
-            <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Matt W.</span> <span class="nlm-surname">Wright</span></span>, 
-            <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Rao</span> <span class="nlm-surname">Madhavrao</span></span>, 
-            <div class="highwire-cite-metadata"><span class="highwire-cite-metadata-journal highwire-cite-metadata">medRxiv </span>
-            <span class="highwire-cite-metadata-pages highwire-cite-metadata">2021.02.12.21251663; </span><span class="highwire-cite-metadata-doi highwire-cite-metadata">
-            <span class="doi_label">doi:</span> https://doi.org/10.1101/2021.02.12.21251663 </span></div>
-            <div class="highwire-cite-extras"><div class="hw-make-citation" data-encoded-apath=";medrxiv;early;2021;02;18;2021.02.12.21251663.atom" data-seqnum="0" id="hw-make-citation-0">
-            <a class="link-save-citation-save use-ajax hw-link-save-unsave-catation link-icon" href="/highwire-save-citation/saveapath/%3Bmedrxiv%3Bearly%3B2021%3B02%3B18%3B2021.02.12.21251663.atom/nojs/0" id="link-save-citation-toggle-0" title="Save">
-            <span class="icon-plus"></span> <span class="title">Add to Selected Citations</span></a></div></div>
-            </div>
-            </div></li> 
-            </entry>\n  
-            '''
-            if 'biorxiv' in self.XRxiv_servers and 'medrxiv' not in self.XRxiv_servers:
-                # print('Searching biorxiv\n')
-                max_biorxiv_papers = max_papers_in_server[2]
-                journals_str = f'%20jcode%3Abiorxiv'
-            if 'biorxiv' not in self.XRxiv_servers and 'medrxiv' in self.XRxiv_servers:
-                # print('Searching medrxiv\n')
-                max_biorxiv_papers = max_papers_in_server[3]
-                journals_str = f'%20jcode%3Amedrxiv'
-            if 'biorxiv' in self.XRxiv_servers and 'medrxiv' in self.XRxiv_servers:
-                # print('Searching both biorxiv and medrxiv\n')
-                max_biorxiv_papers = max_papers_in_server[3]+ max_papers_in_server[2] # birxiv and medrxiv are together.
-                journals_str = f'%20jcode%3Abiorxiv%7C%7Cmedrxiv'
-            
-            subject_str = ('%20').join(self.search_query[0].split())
-            for subject in search_query[1:]:
-                subject_str = subject_str + '%252B' + ('%20').join(subject.split())
-            
-            current_dateTime = datetime.now()
-            today = str(current_dateTime)[:10]
-            start_day = '2013-01-01'
-            arXiv_url = f'https://www.biorxiv.org/search/'
-            arXiv_url += subject_str + journals_str + f'%20limit_from%3A2{start_day}%20limit_to%3A{today}%20numresults%3A{max_biorxiv_papers}%20sort%3Arelevance-rank%20format_result%3Astandard'
-
-            url_response = requests.post(arXiv_url)
-            html = bs(url_response.text, features='html.parser')
-            pdf_entries = html.find_all(attrs={'class': 'search-result'})
-            pdf_titles   = []
-            pdf_authors  = []
-            pdf_urls     = []
-            pdf_categories = []
-            folder_names = []
-            pdf_citation = []
-            pdf_years = []
-            for i, pdf in enumerate(pdf_entries):
-                pdf_titles.append(pdf.find('span', attrs={'class': 'highwire-cite-title'}).text.strip())
-                pdf_authors.append(pdf.find('span', attrs={'class': 'highwire-citation-authors'}).text.strip().split(', '))
-                pdf_url = pdf.find('a', href=True)['href']
-                if pdf_url[:4] != 'http':
-                    pdf_url = f'http://www.biorxiv.org'+ pdf_url
-                pdf_urls.append(pdf_url)
-                pdf_categories.append(pdf.find('span', attrs={'class': 'highwire-cite-metadata-journal highwire-cite-metadata'}).text.strip())
-                folder_names.append(self.folder_name)
-                pdf_years.append(pdf.find('span', attrs={'class': 'highwire-cite-metadata-pages highwire-cite-metadata'}).text.strip()[:4])
-                pdf_citation.append(f"{', '.join(pdf_authors[i])}, {pdf_titles[i]}. {pdf_categories[i]} ({pdf_years[i]}), (available at {pdf_urls[i]}).")
-
-            pdf_info = list(zip(pdf_titles, pdf_urls, pdf_authors, pdf_categories, folder_names, pdf_citation))
-            self.all_pdf_info.append(pdf_info)
-
-        self.all_pdf_info = [item for sublist in self.all_pdf_info for item in sublist]
-        return self.all_pdf_info
-
-    def download_pdf(self):
-        all_reference_text = []
-        for i,p in enumerate(stqdm(self.all_pdf_info, desc='🔍 Searching and downloading papers')):
-            pdf_title=p[0]
-            pdf_category=p[3]
-            pdf_url=p[1]
-            if pdf_category in ['medRxiv', 'bioRxiv']:
-                pdf_url += '.full.pdf'
-            pdf_file_name=p[0].replace(':','').replace('/','').replace('.','').replace('\n','')
-            folder_name=p[4]
-            pdf_citation=p[5]
-            r = requests.get(pdf_url, allow_redirects=True)
-            if  i == 0:
-                if not os.path.exists(f'{folder_name}'):
-                    os.makedirs(f"{folder_name}")
-                else:
-                    shutil.rmtree(f'{folder_name}') 
-                    os.makedirs(f"{folder_name}")
-            with open(f'{folder_name}/{pdf_file_name}.pdf', 'wb') as f:
-                f.write(r.content)
-            if i == 0:
-                st.markdown("###### Papers found:")
-            st.markdown(f"{i+1}. {pdf_citation}")
-            time.sleep(0.15)
-            all_reference_text.append(f"{i+1}. {pdf_citation}\n")
-        if 'all_reference_text' not in st.session_state:
-            st.session_state.key = 'all_reference_text'
-        st.session_state['all_reference_text'] = ' '.join(all_reference_text)
-
-
-                        
-def distibute_max_papers(max_results, XRxiv_servers):
-    fixed_length = len(XRxiv_servers)
-    sample = np.random.multinomial(max_results - fixed_length, np.ones(fixed_length)/fixed_length, size=1)[0] + 1
-    max_papers_in_server = np.zeros(4, dtype=int)
-    all_servers = ['rxiv', 'chemrxiv', 'biorxiv', 'medrxiv']
-    for i,s in enumerate(XRxiv_servers):
-        max_papers_in_server[all_servers.index(s)] = int(sample[i])
-    return  max_papers_in_server     
diff --git a/spaces/merle/PROTEIN_GENERATOR/utils/model/utils/.ipynb_checkpoints/calc_dssp-checkpoint.py b/spaces/merle/PROTEIN_GENERATOR/utils/model/utils/.ipynb_checkpoints/calc_dssp-checkpoint.py
deleted file mode 100644
index fe2b975316f2de89d021d4dff442182192d5b7f8..0000000000000000000000000000000000000000
--- a/spaces/merle/PROTEIN_GENERATOR/utils/model/utils/.ipynb_checkpoints/calc_dssp-checkpoint.py
+++ /dev/null
@@ -1,234 +0,0 @@
-#@title get secondary structure (SSE) from given PDB file
-#@markdown So far it seems the best solution is to steal code from biotite
-#@markdown which calculates the SSE of a peptide chain based on the P-SEA algorithm (Labesse 1997)
-# CODE FROM BIOKITE
-# From Krypton
-import numpy as np
-import random
-import torch
-
-def vector_dot(v1,v2):
-    return (v1*v2).sum(axis=-1)
-
-def norm_vector(v):
-    factor = np.linalg.norm(v, axis=-1)
-    if isinstance(factor, np.ndarray):
-        v /= factor[..., np.newaxis]
-    else:
-        v /= factor
-    return v
-
-def coord(x):
-  return np.asarray(x)
-def displacement(atoms1, atoms2):
-    v1 = coord(atoms1)
-    v2 = coord(atoms2)
-    if len(v1.shape) <= len(v2.shape):
-        diff = v2 - v1
-    else:
-        diff = -(v1 - v2)
-    return diff
-def distance(atoms1, atoms2):
-    diff = displacement(atoms1, atoms2)
-    return np.sqrt(vector_dot(diff, diff))
-
-def angle(atoms1, atoms2, atoms3):
-    v1 = displacement(atoms1, atoms2)
-    v2 = displacement(atoms3, atoms2)
-    norm_vector(v1)
-    norm_vector(v2)
-    return np.arccos(vector_dot(v1,v2))
-
-def dihedral(atoms1, atoms2, atoms3, atoms4):
-    v1 = displacement(atoms1, atoms2)
-    v2 = displacement(atoms2, atoms3)
-    v3 = displacement(atoms3, atoms4)
-    norm_vector(v1)
-    norm_vector(v2)
-    norm_vector(v3)
-    
-    n1 = np.cross(v1, v2)
-    n2 = np.cross(v2, v3)
-    
-    # Calculation using atan2, to ensure the correct sign of the angle 
-    x = vector_dot(n1,n2)
-    y = vector_dot(np.cross(n1,n2), v2)
-    return np.arctan2(y,x)
-
-def replace_letters(arr):
-  # Create a dictionary that maps the letters 'a', 'b', and 'c' to the corresponding numbers
-  letter_to_number = {'a': 0, 'b': 1, 'c': 2}
-  
-  # Create a new array that will hold the numbers
-  nums = []
-  
-  # Loop through the input array and replace the letters with the corresponding numbers
-  for letter in arr:
-    if letter in letter_to_number:
-      nums.append(letter_to_number[letter])
-    else:
-      nums.append(letter)
-  
-  return np.array(nums)
-
-def replace_with_mask(arr, percentage, replace_loops=False):
-  # Make sure the percentage is between 0 and 100
-  percentage = min(max(percentage, 0), 100)
-  
-  # Calculate the number of values to replace
-  num_to_replace = int(len(arr) * percentage / 100)
-  
-  # Choose a random subset of the array to replace
-  replace_indices = random.sample(range(len(arr)), num_to_replace)
-  
-  # Replace the values at the chosen indices with the number 3
-  for i in replace_indices:
-    arr[i] = 3
-
-  if replace_loops:
-    for i in arr:
-        if arr[i] == 2:
-            arr[i] = 3
-  
-  return arr
-
-def annotate_sse(ca_coord, percentage_mask=0, replace_loops=False):
-  _radians_to_angle = 2*np.pi/360
-
-  _r_helix = ((89-12)*_radians_to_angle, (89+12)*_radians_to_angle)
-  _a_helix = ((50-20)*_radians_to_angle, (50+20)*_radians_to_angle)
-  _d2_helix = ((5.5-0.5), (5.5+0.5))
-  _d3_helix = ((5.3-0.5), (5.3+0.5))
-  _d4_helix = ((6.4-0.6), (6.4+0.6))
-
-  _r_strand = ((124-14)*_radians_to_angle, (124+14)*_radians_to_angle)
-  _a_strand = ((-180)*_radians_to_angle, (-125)*_radians_to_angle,
-              (145)*_radians_to_angle, (180)*_radians_to_angle)
-  _d2_strand = ((6.7-0.6), (6.7+0.6))
-  _d3_strand = ((9.9-0.9), (9.9+0.9))
-  _d4_strand = ((12.4-1.1), (12.4+1.1))
-
-  # Filter all CA atoms in the relevant chain.
-
-  d2i_coord = np.full(( len(ca_coord), 2, 3 ), np.nan)
-  d3i_coord = np.full(( len(ca_coord), 2, 3 ), np.nan)
-  d4i_coord = np.full(( len(ca_coord), 2, 3 ), np.nan)
-  ri_coord = np.full(( len(ca_coord), 3, 3 ), np.nan)
-  ai_coord = np.full(( len(ca_coord), 4, 3 ), np.nan)
-  
-  # The distances and angles are not defined for the entire interval,
-  # therefore the indices do not have the full range
-  # Values that are not defined are NaN
-  for i in range(1, len(ca_coord)-1):
-      d2i_coord[i] = (ca_coord[i-1], ca_coord[i+1])
-  for i in range(1, len(ca_coord)-2):
-      d3i_coord[i] = (ca_coord[i-1], ca_coord[i+2])
-  for i in range(1, len(ca_coord)-3):
-      d4i_coord[i] = (ca_coord[i-1], ca_coord[i+3])
-  for i in range(1, len(ca_coord)-1):
-      ri_coord[i] = (ca_coord[i-1], ca_coord[i], ca_coord[i+1])
-  for i in range(1, len(ca_coord)-2):
-      ai_coord[i] = (ca_coord[i-1], ca_coord[i],
-                      ca_coord[i+1], ca_coord[i+2])
-  
-  d2i = distance(d2i_coord[:,0], d2i_coord[:,1])
-  d3i = distance(d3i_coord[:,0], d3i_coord[:,1])
-  d4i = distance(d4i_coord[:,0], d4i_coord[:,1])
-  ri = angle(ri_coord[:,0], ri_coord[:,1], ri_coord[:,2])
-  ai = dihedral(ai_coord[:,0], ai_coord[:,1],
-                ai_coord[:,2], ai_coord[:,3])
-  
-  sse = np.full(len(ca_coord), "c", dtype="U1")
-  
-  # Annotate helices
-  # Find CA that meet criteria for potential helices
-  is_pot_helix = np.zeros(len(sse), dtype=bool)
-  for i in range(len(sse)):
-      if (
-              d3i[i] >= _d3_helix[0] and d3i[i] <= _d3_helix[1]
-          and d4i[i] >= _d4_helix[0] and d4i[i] <= _d4_helix[1]
-          ) or (
-              ri[i] >= _r_helix[0] and ri[i] <= _r_helix[1]
-          and ai[i] >= _a_helix[0] and ai[i] <= _a_helix[1]
-          ):
-              is_pot_helix[i] = True
-  # Real helices are 5 consecutive helix elements
-  is_helix = np.zeros(len(sse), dtype=bool)
-  counter = 0
-  for i in range(len(sse)):
-      if is_pot_helix[i]:
-          counter += 1
-      else:
-          if counter >= 5:
-              is_helix[i-counter : i] = True
-          counter = 0
-  # Extend the helices by one at each end if CA meets extension criteria
-  i = 0
-  while i < len(sse):
-      if is_helix[i]:
-          sse[i] = "a"
-          if (
-              d3i[i-1] >= _d3_helix[0] and d3i[i-1] <= _d3_helix[1]
-              ) or (
-              ri[i-1] >= _r_helix[0] and ri[i-1] <= _r_helix[1]
-              ):
-                  sse[i-1] = "a"
-          sse[i] = "a"
-          if (
-              d3i[i+1] >= _d3_helix[0] and d3i[i+1] <= _d3_helix[1]
-              ) or (
-              ri[i+1] >= _r_helix[0] and ri[i+1] <= _r_helix[1]
-              ):
-                  sse[i+1] = "a"
-      i += 1
-  
-  # Annotate sheets
-  # Find CA that meet criteria for potential strands
-  is_pot_strand = np.zeros(len(sse), dtype=bool)
-  for i in range(len(sse)):
-      if (    d2i[i] >= _d2_strand[0] and d2i[i] <= _d2_strand[1]
-          and d3i[i] >= _d3_strand[0] and d3i[i] <= _d3_strand[1]
-          and d4i[i] >= _d4_strand[0] and d4i[i] <= _d4_strand[1]
-          ) or (
-              ri[i] >= _r_strand[0] and ri[i] <= _r_strand[1]
-          and (   (ai[i] >= _a_strand[0] and ai[i] <= _a_strand[1])
-                or (ai[i] >= _a_strand[2] and ai[i] <= _a_strand[3]))
-          ):
-              is_pot_strand[i] = True
-  # Real strands are 5 consecutive strand elements,
-  # or shorter fragments of at least 3 consecutive strand residues,
-  # if they are in hydrogen bond proximity to 5 other residues
-  pot_strand_coord = ca_coord[is_pot_strand]
-  is_strand = np.zeros(len(sse), dtype=bool)
-  counter = 0
-  contacts = 0
-  for i in range(len(sse)):
-      if is_pot_strand[i]:
-          counter += 1
-          coord = ca_coord[i]
-          for strand_coord in ca_coord:
-              dist = distance(coord, strand_coord)
-              if dist >= 4.2 and dist <= 5.2:
-                  contacts += 1
-      else:
-          if counter >= 4:
-              is_strand[i-counter : i] = True
-          elif counter == 3 and contacts >= 5:
-              is_strand[i-counter : i] = True
-          counter = 0
-          contacts = 0
-  # Extend the strands by one at each end if CA meets extension criteria
-  i = 0
-  while i < len(sse):
-      if is_strand[i]:
-          sse[i] = "b"
-          if d3i[i-1] >= _d3_strand[0] and d3i[i-1] <= _d3_strand[1]:
-              sse[i-1] = "b"
-          sse[i] = "b"
-          if d3i[i+1] >= _d3_strand[0] and d3i[i+1] <= _d3_strand[1]:
-              sse[i+1] = "b"
-      i += 1
-  sse=replace_letters(sse)
-  sse=replace_with_mask(sse, percentage_mask, replace_loops=replace_loops)
-  sse=torch.nn.functional.one_hot(torch.tensor(sse), num_classes=4)
-  return sse
diff --git a/spaces/merve/fill-in-the-blank/public/third_party/tfjs.js b/spaces/merve/fill-in-the-blank/public/third_party/tfjs.js
deleted file mode 100644
index bc3dad50920b4c71e25844384f59cea006be4bca..0000000000000000000000000000000000000000
--- a/spaces/merve/fill-in-the-blank/public/third_party/tfjs.js
+++ /dev/null
@@ -1,3 +0,0 @@
-// @tensorflow/tfjs Copyright 2019 Google
-!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(exports):"function"==typeof define&&define.amd?define(["exports"],e):e(t.tf=t.tf||{})}(this,function(t){"use strict";var e=function(t,n){return(e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(t,e){t.__proto__=e}||function(t,e){for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n])})(t,n)};function n(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}function r(t,e,n,r){return new(n||(n=Promise))(function(i,a){function o(t){try{u(r.next(t))}catch(t){a(t)}}function s(t){try{u(r.throw(t))}catch(t){a(t)}}function u(t){t.done?i(t.value):new n(function(e){e(t.value)}).then(o,s)}u((r=r.apply(t,e||[])).next())})}function i(t,e){var n,r,i,a,o={label:0,sent:function(){if(1&i[0])throw i[1];return i[1]},trys:[],ops:[]};return a={next:s(0),throw:s(1),return:s(2)},"function"==typeof Symbol&&(a[Symbol.iterator]=function(){return this}),a;function s(a){return function(s){return function(a){if(n)throw new TypeError("Generator is already executing.");for(;o;)try{if(n=1,r&&(i=2&a[0]?r.return:a[0]?r.throw||((i=r.return)&&i.call(r),0):r.next)&&!(i=i.call(r,a[1])).done)return i;switch(r=0,i&&(a=[2&a[0],i.value]),a[0]){case 0:case 1:i=a;break;case 4:return o.label++,{value:a[1],done:!1};case 5:o.label++,r=a[1],a=[0];continue;case 7:a=o.ops.pop(),o.trys.pop();continue;default:if(!(i=(i=o.trys).length>0&&i[i.length-1])&&(6===a[0]||2===a[0])){o=0;continue}if(3===a[0]&&(!i||a[1]>i[0]&&a[1]<i[3])){o.label=a[1];break}if(6===a[0]&&o.label<i[1]){o.label=i[1],i=a;break}if(i&&o.label<i[2]){o.label=i[2],o.ops.push(a);break}i[2]&&o.ops.pop(),o.trys.pop();continue}a=e.call(t,o)}catch(t){a=[6,t],r=0}finally{n=i=0}if(5&a[0])throw a[1];return{value:a[0]?a[1]:void 0,done:!0}}([a,s])}}}var a=function(){function t(t){this.global=t,this.flags={},this.flagRegistry={},this.urlFlags={},this.populateURLFlags()}return t.prototype.setPlatform=function(t,e){null!=this.platform&&console.warn("Platform "+this.platformName+" has already been set. 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gt={float32:ft,int32:pt,bool:ht,complex64:dt};function vt(t,e){if("string"===t||"string"===e){if("string"===t&&"string"===e)return"string";throw new Error("Can not upcast "+t+" with "+e)}return gt[t][e]}function yt(t){return vt(t,"int32")}function bt(t,e){if(t.dtype===e.dtype)return[t,e];var n=vt(t.dtype,e.dtype);return[t.cast(n),e.cast(n)]}function xt(t,e){f(t.dtype===e.dtype,function(){return"The dtypes of the first("+t.dtype+") and second("+e.dtype+") input must match"})}function wt(t){var e=[];return function t(e,n,r){if(null!=e)if(e instanceof lt)n.push(e);else if(i=e,Array.isArray(i)||"object"==typeof i){var i,a=e;for(var o in a){var s=a[o];r.has(s)||(r.add(s),t(s,n,r))}}}(t,e,new Set),e}var Nt,Ct=Object.freeze({makeTypesMatch:bt,assertTypesMatch:xt,isTensorInList:function(t,e){for(var n=0;n<e.length;n++)if(e[n].id===t.id)return!0;return!1},getTensorsInContainer:wt}),Et=function(){function t(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null}}return t.prototype.dispose=function(){for(var t in this.registeredVariables)this.registeredVariables[t].dispose()},t}(),St=function(){function t(t){this.ENV=t,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Et}return t.prototype.ready=function(){return r(this,void 0,void 0,function(){var t,e,n;return i(this,function(r){switch(r.label){case 0:if(null!=this.pendingBackendInit)return[2,this.pendingBackendInit.then(function(){})];if(null!=this.backendInstance)return[2];t=this.getSortedBackends(),e=0,r.label=1;case 1:return e<t.length?(n=t[e],[4,this.initializeBackend(n).success]):[3,5];case 2:return r.sent()?[4,this.setBackend(n)]:[3,4];case 3:return r.sent(),[2];case 4:return e++,[3,1];case 5:throw new Error("Could not initialize any backends, all backend initializations failed.")}})})},Object.defineProperty(t.prototype,"backend",{get:function(){if(null!=this.pendingBackendInit)throw new Error("Backend '"+this.backendName+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");if(null==this.backendInstance){var t=this.initializeBackendsAndReturnBest(),e=t.name;if(t.asyncInit)throw new Error("The highest priority backend '"+e+"' has not yet been initialized. Make sure to await tf.ready() before calling other methods");this.setBackend(e)}return this.backendInstance},enumerable:!0,configurable:!0}),t.prototype.backendNames=function(){return Object.keys(this.registryFactory)},t.prototype.findBackend=function(t){if(!(t in this.registry)){if(!(t in this.registryFactory))return null;if(this.initializeBackend(t).asyncInit)return null}return this.registry[t]},t.prototype.findBackendFactory=function(t){return t in this.registryFactory?this.registryFactory[t].factory:null},t.prototype.registerBackend=function(t,e,n){return void 0===n&&(n=1),t in this.registryFactory?(console.warn(t+" backend was already registered. Reusing existing backend factory."),!1):(this.registryFactory[t]={factory:e,priority:n},!0)},t.prototype.setBackend=function(t){return r(this,void 0,void 0,function(){var e,n,r;return i(this,function(i){switch(i.label){case 0:if(null==this.registryFactory[t])throw new Error("Backend name '"+t+"' not found in registry");return this.backendName=t,null!=this.registry[t]?[3,4]:(this.backendInstance=null,e=this.initializeBackend(t),n=e.success,e.asyncInit?[4,n]:[3,2]);case 1:return r=i.sent(),[3,3];case 2:r=n,i.label=3;case 3:if(!r)return[2,!1];i.label=4;case 4:return this.backendInstance=this.registry[t],this.profiler=new J(this.backendInstance),[2,!0]}})})},t.prototype.initializeBackend=function(t){var e=this,n=this.registryFactory[t];if(null==n)throw new Error("Cannot initialize backend "+t+", no registration found.");try{var r=n.factory();if(Promise.resolve(r)===r){var i=++this.pendingBackendInitId,a=r.then(function(n){return!(i<e.pendingBackendInitId||(e.registry[t]=n,e.pendingBackendInit=null,0))}).catch(function(n){return!(i<e.pendingBackendInitId||(e.pendingBackendInit=null,console.warn("Initialization of backend "+t+" failed"),console.warn(n.stack||n.message),1))});return this.pendingBackendInit=a,{success:a,asyncInit:!0}}return this.registry[t]=r,{success:!0,asyncInit:!1}}catch(e){return console.warn("Initialization of backend "+t+" failed"),console.warn(e.stack||e.message),{success:!1,asyncInit:!1}}},t.prototype.removeBackend=function(t){if(!(t in this.registryFactory))throw new Error(t+" backend not found in registry");this.backendName===t&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,t in this.registry&&(this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)},t.prototype.getSortedBackends=function(){var t=this;if(0===Object.keys(this.registryFactory).length)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort(function(e,n){return t.registryFactory[n].priority-t.registryFactory[e].priority})},t.prototype.initializeBackendsAndReturnBest=function(){for(var t=this.getSortedBackends(),e=0;e<t.length;e++){var n=t[e],r=this.initializeBackend(n),i=r.success,a=r.asyncInit;if(a||i)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")},t.prototype.moveData=function(t,e){this.write(t,e,this.readSync(e))},t.prototype.tidy=function(t,e){var n,r=this,i=null;if(null==e){if("function"!=typeof t)throw new Error("Please provide a function to tidy()");e=t}else{if("string"!=typeof t&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof e)throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");i=t}return this.scopedRun(function(){return r.startScope(i)},function(){return r.endScope(n)},function(){return(n=e())instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n})},t.prototype.scopedRun=function(t,e,n){t();try{var r=n();return e(),r}catch(t){throw e(),t}},t.prototype.nextTensorId=function(){return t.nextTensorId++},t.prototype.nextVariableId=function(){return t.nextVariableId++},t.prototype.clone=function(t){var e=lt.make(t.shape,{dataId:t.dataId},t.dtype);return this.addTapeNode([t],e,function(t){return[t.toFloat()]}),e},t.prototype.runKernel=function(t,e,n){var r,i=this,a=[],o=this.isTapeOn(),s=null!=this.state.activeScope?this.state.activeScope.name:"",u=function(t){o&&(a=t.map(function(t){return i.keep(i.clone(t))}))},l=this.state.numBytes,c=this.state.numTensors;if(this.scopedRun(function(){return i.state.kernelDepth++},function(){return i.state.kernelDepth--},function(){r=i.ENV.getBool("DEBUG")?i.profiler.profileKernel(s,e,function(){return t(i.backend,u)}):t(i.backend,u)}),o){var p={id:this.state.nextTapeNodeId++,name:s,inputs:e,outputs:Array.isArray(r)?r:[r],saved:a};null!=n&&(p.gradient=function(t){return n(t,a)}),this.state.activeTape.push(p)}return this.state.profiling&&this.state.activeProfile.kernels.push({name:s,bytesAdded:this.state.numBytes-l,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-c,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(e).map(function(t){return e[t].shape}),outputShape:Array.isArray(r)?r.map(function(t){return t.shape}):r.shape}),r},t.prototype.registerTensor=function(t,e){var n=this.state.tensorInfo.has(t.dataId)?this.state.tensorInfo.get(t.dataId).refCount:0;if(this.state.numTensors++,"string"===t.dtype&&this.state.numStringTensors++,0===n){this.state.numDataBuffers++;var r=0;"complex64"!==t.dtype&&"string"!==t.dtype&&(r=t.size*_(t.dtype)),this.state.tensorInfo.set(t.dataId,{backend:null!=e?e:this.backend,dtype:t.dtype,shape:t.shape,bytes:r,refCount:0}),this.state.numBytes+=r,null!=e?e.register(t.dataId,t.shape,t.dtype):this.backend.register(t.dataId,t.shape,t.dtype)}this.state.tensorInfo.get(t.dataId).refCount++,t instanceof ct||this.track(t)},t.prototype.registerVariable=function(t){if(null!=this.state.registeredVariables[t.name])throw new Error("Variable with name "+t.name+" was already registered");this.state.registeredVariables[t.name]=t},t.prototype.disposeTensor=function(t){if(this.state.tensorInfo.has(t.dataId)){this.state.numTensors--,"string"===t.dtype&&this.state.numStringTensors--;var e=this.state.tensorInfo.get(t.dataId);e.refCount<=1?("complex64"!==t.dtype&&(this.state.numBytes-=e.bytes),this.state.numDataBuffers--,e.backend.disposeData(t.dataId),this.state.tensorInfo.delete(t.dataId)):this.state.tensorInfo.get(t.dataId).refCount--}},t.prototype.disposeVariables=function(){for(var t in this.state.registeredVariables){var e=this.state.registeredVariables[t];this.disposeVariable(e)}},t.prototype.disposeVariable=function(t){this.disposeTensor(t),null!=this.state.registeredVariables[t.name]&&delete this.state.registeredVariables[t.name]},t.prototype.memory=function(){var t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,null==t.reasons&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t},t.prototype.profile=function(t){return r(this,void 0,void 0,function(){var e,n;return i(this,function(r){return this.state.profiling=!0,e=this.state.numBytes,n=this.state.numTensors,this.state.activeProfile.kernels=[],this.state.activeProfile.result=t(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max.apply(Math,this.state.activeProfile.kernels.map(function(t){return t.totalBytesSnapshot})),this.state.activeProfile.newBytes=this.state.numBytes-e,this.state.activeProfile.newTensors=this.state.numTensors-n,[2,this.state.activeProfile]})})},t.prototype.isTapeOn=function(){return this.state.gradientDepth>0&&0===this.state.kernelDepth},t.prototype.addTapeNode=function(t,e,n){var r={};t.forEach(function(t,e){r[e]=t});var i={id:this.state.nextTapeNodeId++,name:this.state.activeScope.name,inputs:r,outputs:[e],gradient:function(t){var e={};return n(t).forEach(function(t,n){e[n]=function(){return t}}),e}};this.state.activeTape.push(i)},t.prototype.keep=function(t){return t.kept=!0,t},t.prototype.startTape=function(){0===this.state.gradientDepth&&(this.state.activeTape=[]),this.state.gradientDepth++},t.prototype.endTape=function(){this.state.gradientDepth--},t.prototype.startScope=function(t){var e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e},t.prototype.endScope=function(t){for(var e=this,n=wt(t),r=new Set(n.map(function(t){return t.id})),i=0;i<this.state.activeScope.track.length;i++){var a=this.state.activeScope.track[i];a.kept||r.has(a.id)||a.dispose()}var o=this.state.scopeStack.pop();this.state.activeScope=0===this.state.scopeStack.length?null:this.state.scopeStack[this.state.scopeStack.length-1],n.forEach(function(t){t.kept||t.scopeId!==o.id||e.track(t)})},t.prototype.gradients=function(t,e,n,r){var i=this;if(void 0===r&&(r=!1),f(e.length>0,function(){return"gradients() received an empty list of xs."}),null!=n&&"float32"!==n.dtype)throw new Error("dy must have 'float32' dtype, but has '"+n.dtype+"'");var a=this.scopedRun(function(){return i.startTape()},function(){return i.endTape()},function(){return i.tidy("forward",t)});f(a instanceof lt,function(){return"The result y returned by f() must be a tensor."});var o=function(t,e,n){for(var r={},i={},a=0;a<e.length;a++)r[e[a].id]=!0;for(a=0;a<t.length;a++){var o=(d=t[a]).inputs;for(var s in o){for(var u=o[s],l=!1,c=0;c<e.length;c++)if(r[u.id]){d.outputs.forEach(function(t){return r[t.id]=!0}),l=!0,i[d.id]=!0;break}if(l)break}}var p={};p[n.id]=!0;var h={};for(a=t.length-1;a>=0;a--)for(o=(d=t[a]).inputs,c=0;c<d.outputs.length;c++)if(p[d.outputs[c].id]){for(var s in o)p[o[s].id]=!0,h[d.id]=!0;break}var f=[];for(a=0;a<t.length;a++){var d;if(i[(d=t[a]).id]&&h[d.id]){var m={};for(var s in d.inputs){var g=d.inputs[s];r[g.id]&&(m[s]=g)}var v=Object.assign({},d);v.inputs=m,v.outputs=d.outputs,f.push(v)}}return f}(this.state.activeTape,e,a);if(!r&&0===o.length&&e.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",function(){var t,r,s={};s[a.id]=null==n?(r=G(v(t=a.shape),"float32"),lt.make(t,{values:r})):n,function(t,e,n){for(var r=function(r){var i=e[r],a=[];if(i.outputs.forEach(function(e){var n=t[e.id];if(null!=n)a.push(n);else{var r=lt.make(e.shape,{values:H(e.size,e.dtype)},e.dtype);a.push(r)}}),null==i.gradient)throw new Error("Cannot compute gradient: gradient function not found for "+i.name+".");var o=i.gradient(1===i.outputs.length?a[0]:a),s=function(e){if(!(e in o))throw new Error("Cannot backprop through input "+e+". Available gradients found: "+Object.keys(o)+".");var r=n(function(){return o[e]()});if("float32"!==r.dtype)throw new Error("Error in gradient for op "+i.name+". The gradient of input "+e+" must have 'float32' dtype, but has '"+r.dtype+"'");var a=i.inputs[e];if(!y(r.shape,a.shape))throw new Error("Error in gradient for op "+i.name+". The gradient of input '"+e+"' has shape '"+r.shape+"', which does not match the shape of the input '"+a.shape+"'");if(null==t[a.id])t[a.id]=r;else{var s=t[a.id];t[a.id]=s.add(r),s.dispose()}};for(var u in i.inputs)s(u)},i=e.length-1;i>=0;i--)r(i)}(s,o,function(t){return i.tidy(t)});var u=e.map(function(t){return s[t.id]});return 0===i.state.gradientDepth&&(i.state.activeTape.forEach(function(t){for(var e in t.saved)t.saved[e].dispose()}),i.state.activeTape=null),{value:a,grads:u}})},t.prototype.customGrad=function(t){var e=this;return f(B(t),function(){return"The f passed in customGrad(f) must be a function."}),function(){for(var n,r=[],i=0;i<arguments.length;i++)r[i]=arguments[i];f(r.every(function(t){return t instanceof lt}),function(){return"The args passed in customGrad(f)(x1, x2,...) must all be tensors"});var a={};return r.forEach(function(t,e){a[e]=t}),e.runKernel(function(e,i){return f((n=t.apply(void 0,r.concat([i]))).value instanceof lt,function(){return"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"}),f(B(n.gradFunc),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."}),n.value},a,function(t,e){var i=n.gradFunc(t,e),a=Array.isArray(i)?i:[i];f(a.length===r.length,function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."}),f(a.every(function(t){return t instanceof lt}),function(){return"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors."});var o={};return a.forEach(function(t,e){o[e]=function(){return t}}),o})}},t.prototype.write=function(t,e,n){var r=this.state.tensorInfo.get(e),i=r.backend;if(t=t||this.backend,"string"===r.dtype){var a=F(n);this.state.numBytes+=a-r.bytes,r.bytes=a}t!==i&&(i.disposeData(e),r.backend=t,t.register(e,r.shape,r.dtype)),t.write(e,n)},t.prototype.readSync=function(t){return this.state.tensorInfo.get(t).backend.readSync(t)},t.prototype.read=function(t){return this.state.tensorInfo.get(t).backend.read(t)},t.prototype.fromPixels=function(t,e){return this.backend.fromPixels(t,e)},t.prototype.time=function(t){return r(this,void 0,void 0,function(){var e,n;return i(this,function(r){switch(r.label){case 0:return e=q(),[4,this.backend.time(t)];case 1:return(n=r.sent()).wallMs=q()-e,[2,n]}})})},t.prototype.track=function(t){return null!=this.state.activeScope&&(t.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(t)),t},Object.defineProperty(t.prototype,"registeredVariables",{get:function(){return this.state.registeredVariables},enumerable:!0,configurable:!0}),t.prototype.reset=function(){for(var t in this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new Et,this.registry)this.registry[t].dispose(),delete this.registry[t];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null},t.nextTensorId=0,t.nextVariableId=0,t}(),kt=function(){var t=function(){if(null==Nt){var t=void 0;if("undefined"!=typeof window)t=window;else if("undefined"!=typeof global)t=global;else if("undefined"!=typeof process)t=process;else{if("undefined"==typeof self)throw new Error("Could not find a global object");t=self}Nt=t}return Nt}();if(null==t._tfengine){var e=new a(t);t._tfengine=new St(e)}return s(t._tfengine.ENV),ot=function(){return t._tfengine},t._tfengine}();function It(){return"undefined"!=typeof window&&null!=window.document||"undefined"!=typeof WorkerGlobalScope}t.ENV.registerFlag("DEBUG",function(){return!1},function(t){t&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. 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r=t.windowSize,i=t.batchSize,a=t.inSize,o=Math.ceil(a/r);n||this.variableNames.push("bestIndicesA"),this.outputShape=[i,o];var s="max"===e?">":"<",u=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+r+";\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < "+r+"; i++) {\n          int inIdx = "+u+";\n          float candidate = getA(batch, inIdx);\n          if (candidate "+s+" bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    "};function pi(t,e){return["x","y","z","w","u","v"].slice(0,e).map(function(e){return t+"."+e})}function hi(t,e){return 1===e?[t]:pi(t,e)}function fi(){var e,n,r,i,a,o,s,u,l,c;return 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vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n    } else if(v < -FLOAT_MAX) {\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\n    }\n\n    highp vec4 c = vec4(0,0,0,0);\n\n    highp float e = floor(log2(av));\n    highp float m = exp2(fract(log2(av))) - 1.0;\n\n    c[2] = floor(128.0 * m);\n    m -= c[2] / 128.0;\n    c[1] = floor(32768.0 * m);\n    m -= c[1] / 32768.0;\n    c[0] = floor(8388608.0 * m);\n\n    highp float ebias = e + 127.0;\n    c[3] = floor(ebias / 2.0);\n    ebias -= c[3] * 2.0;\n    c[2] += floor(ebias) * 128.0;\n\n    c[3] += 128.0 * step(0.0, -v);\n\n    return c / 255.0;\n  }\n";function vi(t,e,n,r){var i=[];t.forEach(function(t){var e=v(t.shapeInfo.logicalShape);t.shapeInfo.isUniform?i.push("uniform float "+t.name+(e>1?"["+e+"]":"")+";"):(i.push("uniform sampler2D "+t.name+";"),i.push("uniform int offset"+t.name+";"))});var a,o,s=i.join("\n"),u=t.map(function(t){return function(t,e,n){void 0===n&&(n=!1);var r="";r+=n?function t(e){var n,r,i;switch(e.shapeInfo.logicalShape.length){case 0:return n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),i=fi(),"\n    vec4 "+r+"() {\n      return "+i.texture2D+"("+n+", halfCR);\n    }\n  ";case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),r=t.shapeInfo.texShape,i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],a=fi();return"\n    vec4 "+n+"(int index) {\n      vec2 uv = packedUVfrom1D(\n        "+i[0]+", "+i[1]+", index);\n      return "+a.texture2D+"("+e+", uv);\n    }\n  "}(e);case 2:return function(t){var e=t.shapeInfo.logicalShape,n=t.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),i=t.shapeInfo.texShape,a=i[0],o=i[1],s=fi();if(null!=i&&y(e,i))return"\n      vec4 "+r+"(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2("+o+".0, "+a+".0);\n\n        return "+s.texture2D+"("+n+", uv);\n      }\n    ";var u=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],l=Math.ceil(e[1]/2);return"\n    vec4 "+r+"(int row, int col) {\n      vec2 uv = packedUVfrom2D("+l+", "+u[0]+", "+u[1]+", row, col);\n      return "+s.texture2D+"("+n+", uv);\n    }\n  "}(e);case 3:return function(e){var n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(1===n[0]){var s=n.slice(1),u=Si(e,s);return"\n        "+t(u)+"\n        vec4 "+i+"(int b, int row, int col) {\n          return "+i+"("+ki(["b","row","col"],[1,2])+");\n        }\n      "}var l=o[0],c=o[1],p=Math.ceil(n[2]/2),h=p*Math.ceil(n[1]/2),f=fi();return"\n    vec4 "+i+"(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        "+l+", "+c+", "+h+", "+p+", b, row, col);\n      return "+f.texture2D+"("+r+", uv);\n    }\n  "}(e);default:return function(t){for(var e=t.shapeInfo.logicalShape,n=e.length,r=t.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=t.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],s=o[0],u=o[1],l=Math.ceil(e[n-1]/2),c=l*Math.ceil(e[n-2]/2),p="int b, int row, int col",h="b * "+c+" + (row / 2) * "+l+" + (col / 2)",f=2;f<n-1;f++)p="int b"+f+", "+p,c*=e[n-f-1],h="b"+f+" * "+c+" + "+h;var d=fi();return"\n    vec4 "+i+"("+p+") {\n      int index = "+h+";\n      int texR = index / "+u+";\n      int texC = index - texR * "+u+";\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+u+", "+s+");\n      return "+d.texture2D+"("+r+", uv);\n    }\n  "}(e)}}(t):function t(e){var n=e.shapeInfo.logicalShape;switch(n.length){case 0:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return"float "+n+"() {return "+e+";}";var r=t.shapeInfo.texShape,i=r[0],a=r[1];if(1===i&&1===a)return"\n      float "+n+"() {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var o=t.shapeInfo.texShape,s=o[0],u=o[1],l=Ni(e);return"\n    float "+n+"() {\n      vec2 uv = uvFromFlat("+s+", "+u+", "+l+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(e);case 1:return function(t){var e=t.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(t.shapeInfo.isUniform)return"\n      float "+n+"(int index) {\n        "+Ci(t)+"\n      }\n    ";var r=t.shapeInfo.texShape,i=r[0],a=r[1];if(1===a&&1===i)return"\n      float "+n+"(int index) {\n        return sampleTexture("+e+", halfCR);\n      }\n    ";var o=Ni(e);return 1===a?"\n      float "+n+"(int index) {\n        vec2 uv = vec2(0.5, (float(index + "+o+") + 0.5) / "+i+".0);\n        return sampleTexture("+e+", uv);\n      }\n    ":1===i?"\n      float "+n+"(int index) {\n        vec2 uv = vec2((float(index + "+o+") + 0.5) / "+a+".0, 0.5);\n        return sampleTexture("+e+", uv);\n      }\n    ":"\n    float "+n+"(int index) {\n      vec2 uv = uvFromFlat("+i+", "+a+", index + "+o+");\n      return sampleTexture("+e+", uv);\n    }\n  "}(e);case 2:return function(e){var n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=e.shapeInfo.texShape;if(null!=a&&y(n,a)){var o=a[0],s=a[1];return"\n    float "+i+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+s+".0, "+o+".0);\n      return sampleTexture("+r+", uv);\n    }\n  "}var u=k(n),l=u.newShape,c=u.keptDims,p=l;if(p.length<n.length){var h=Si(e,p);return"\n      "+t(h)+"\n      float "+i+"(int row, int col) {\n        return "+i+"("+ki(["row","col"],c)+");\n      }\n    "}if(e.shapeInfo.isUniform)return"\n      float "+i+"(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2("+n[1]+", 1)));\n        "+Ci(e)+"\n      }\n    ";var f=a[0],d=a[1],m=Ni(r);return 1===d?"\n    float "+i+"(int row, int col) {\n      float index = dot(vec3(row, col, "+m+"), vec3("+n[1]+", 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / "+f+".0);\n      return sampleTexture("+r+", uv);\n    }\n  ":1===f?"\n    float "+i+"(int row, int col) {\n      float index = dot(vec3(row, col, "+m+"), vec3("+n[1]+", 1, 1));\n      vec2 uv = vec2((index + 0.5) / "+d+".0, 0.5);\n      return sampleTexture("+r+", uv);\n    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float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2("+o+", 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+d+".0, "+f+".0);\n          return sampleTexture("+r+", uv);\n        }\n      ";if(d===o&&null==m)return"\n    float "+i+"(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2("+n[1]+", 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+d+".0, "+f+".0);\n      return sampleTexture("+r+", uv);\n    }\n  ";var g=Ni(r);return"\n      float "+i+"(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * "+a+" + col * "+o+" + depth + "+g+";\n        vec2 uv = uvFromFlat("+f+", "+d+", index);\n        return sampleTexture("+r+", uv);\n      }\n  "}(e);case 4:return function(e){var n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=n[3],o=n[2]*a,s=n[1]*o,u=k(n),l=u.newShape,c=u.keptDims;if(l.length<n.length){var p=Si(e,l);return"\n      "+t(p)+"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        return "+i+"("+ki(["row","col","depth","depth2"],c)+");\n      }\n    "}if(e.shapeInfo.isUniform)return"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4("+s+", "+o+", "+a+", 1)));\n        "+Ci(e)+"\n      }\n    ";var h=e.shapeInfo.flatOffset,f=e.shapeInfo.texShape,d=f[0],m=f[1];if(m===s&&null==h)return"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3("+o+", "+a+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+m+".0, "+d+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";if(m===a&&null==h)return"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3("+n[1]*n[2]+", "+n[2]+", 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+m+".0, "+d+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";var g=Ni(r);return"\n    float "+i+"(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+s+" + col * "+o+" +\n          depth * "+a+" + depth2;\n      vec2 uv = uvFromFlat("+d+", "+m+", index + "+g+");\n      return sampleTexture("+r+", uv);\n    }\n  "}(e);case 5:return function(e){var n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=n[4],o=n[3]*a,s=n[2]*o,u=n[1]*s,l=k(n),c=l.newShape,p=l.keptDims;if(c.length<n.length){var h=Si(e,c);return"\n      "+t(h)+"\n      float "+i+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+i+"("+ki(["row","col","depth","depth2","depth3"],p)+");\n      }\n    "}if(e.shapeInfo.isUniform)return"\n      float "+i+"(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+u+", "+s+", "+o+", "+a+")) +\n          depth3;\n        "+Ci(e)+"\n      }\n    ";var f=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,m=d[0],g=d[1];if(g===u&&null==f)return"\n      float "+i+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4("+s+", "+o+", "+a+", 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+g+".0, "+m+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";if(g===a&&null==f)return"\n      float "+i+"(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4("+n[1]*n[2]*n[3]+",\n               "+n[2]*n[3]+", "+n[3]+", 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+g+".0, "+m+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";var v=Ni(r);return"\n    float "+i+"(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+u+" + col * "+s+" + depth * "+o+" +\n          depth2 * "+a+" + depth3 + "+v+";\n      vec2 uv = uvFromFlat("+m+", "+g+", index);\n      return sampleTexture("+r+", uv);\n    }\n  "}(e);case 6:return function(e){var n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),a=k(n),o=a.newShape,s=a.keptDims;if(o.length<n.length){var u=Si(e,o);return"\n      "+t(u)+"\n      float "+i+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return "+i+"("+ki(["row","col","depth","depth2","depth3","depth4"],s)+");\n      }\n    "}var l=n[5],c=n[4]*l,p=n[3]*c,h=n[2]*p,f=n[1]*h;if(e.shapeInfo.isUniform)return"\n      float "+i+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4("+f+", "+h+", "+p+", "+c+")) +\n          dot(\n            vec2(depth3, depth4),\n            vec2("+l+", 1)));\n        "+Ci(e)+"\n      }\n    ";var d=e.shapeInfo.flatOffset,m=e.shapeInfo.texShape,g=m[0],v=m[1];if(v===f&&null==d)return"\n      float "+i+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4("+h+", "+p+", "+c+", "+l+")) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+v+".0, "+g+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";if(v===l&&null==d)return"\n      float "+i+"(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4("+n[1]*n[2]*n[3]*n[4]+",\n               "+n[2]*n[3]*n[4]+",\n               "+n[3]*n[4]+",\n               "+n[4]+")) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+v+".0, "+g+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ";var y=Ni(r);return"\n    float "+i+"(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * "+f+" + col * "+h+" + depth * "+p+" +\n          depth2 * "+c+" + depth3 * "+l+" + depth4 + "+y+";\n      vec2 uv = uvFromFlat("+g+", "+v+", index);\n      return sampleTexture("+r+", uv);\n    }\n  "}(e);default:throw new Error(n.length+"-D input sampling is not yet supported")}}(t);var i=t.shapeInfo.logicalShape,a=e.logicalShape;return i.length<=a.length&&(r+=n?function(t,e){var n,r=t.name,i=r.charAt(0).toUpperCase()+r.slice(1),a="get"+i+"AtOutCoords",o=t.shapeInfo.logicalShape.length,s=e.logicalShape.length,u=_r(t.shapeInfo.logicalShape,e.logicalShape),l=Ei(s),c=s-o,p=["x","y","z","w","u","v"];n=0===o?"":s<2&&u.length>=1?"coords = 0;":u.map(function(t){return"coords."+p[t+c]+" = 0;"}).join("\n");var h;h=s<2&&o>0?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+p[e+c]}).join(", ");var f="return outputValue;",d=1===v(t.shapeInfo.logicalShape),m=1===v(e.logicalShape);if(1!==o||d||m){if(d&&!m)f=1===s?"\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      ":"\n        return vec4(outputValue.x);\n      ";else if(u.length){var g=o-2,y=o-1;u.indexOf(g)>-1&&u.indexOf(y)>-1?f="return vec4(outputValue.x);":u.indexOf(g)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":u.indexOf(y)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}}else f="\n      return vec4(outputValue.xy, outputValue.xy);\n    ";return"\n    vec4 "+a+"() {\n      "+l+" coords = getOutputCoords();\n      "+n+"\n      vec4 outputValue = get"+i+"("+h+");\n      "+f+"\n    }\n  "}(t,e):function(t,e){var n=t.name,r=n.charAt(0).toUpperCase()+n.slice(1),i="get"+r+"AtOutCoords",a=e.texShape,o=t.shapeInfo.texShape,s=t.shapeInfo.logicalShape.length,u=e.logicalShape.length;if(!t.shapeInfo.isUniform&&s===u&&null==t.shapeInfo.flatOffset&&y(o,a))return"\n      float "+i+"() {\n        return sampleTexture("+n+", resultUV);\n      }\n    ";var l=Ei(u),c=_r(t.shapeInfo.logicalShape,e.logicalShape),p=u-s,h=["x","y","z","w","u","v"];return"\n    float "+i+"() {\n      "+l+" coords = getOutputCoords();\n      "+(0===s?"":u<2&&c.length>=1?"coords = 0;":c.map(function(t){return"coords."+h[t+p]+" = 0;"}).join("\n"))+"\n      return get"+r+"("+(u<2&&s>0?"coords":t.shapeInfo.logicalShape.map(function(t,e){return"coords."+h[e+p]}).join(", "))+");\n    }\n  "}(t,e)),r}(t,e,r)}).join("\n"),l=e.texShape,c=fi(),p="\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return "+c.texture2D+"(textureSampler, uv).r;\n    }\n  ",h=function(t){return t.version+"\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    "+t.varyingFs+" vec2 resultUV;\n    "+t.defineOutput+"\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    #define isnan(value) isnan_custom(value)\n    "+t.defineSpecialNaN+"\n    bvec4 isnan_custom(vec4 val) {\n      return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\n    }\n\n    "+t.defineSpecialInf+"\n    "+t.defineRound+"\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    "+yi+"\n    "+bi+"\n    "+xi+"\n  "}(c);return e.isPacked?(a=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return 1===n[0]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * "+n[1]+".0);\n      }\n    ":1===n[1]?"\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * "+n[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      return 2 * (resTexRC.x * "+n[1]+" + resTexRC.y);\n    }\n  "}(0,e);case 2:return function(t,e){var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y(t,e))return"\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2("+n[0]+", "+n[1]+"));\n      }\n    ";var r=Math.ceil(t[1]/2);return"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=t,r=e,i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],o=(a=Math.ceil(n[2]/2))*Math.ceil(n[1]/2),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+i[0]+", "+i[1]+"));\n      int index = resTexRC.x * "+i[1]+" + resTexRC.y;\n\n      int b = index / "+o+";\n      index -= b * "+o+";\n\n      int r = 2 * (index / "+a+");\n      int c = imod(index, "+a+") * 2;\n\n      return ivec3(b, r, c);\n    }\n  ";default:return function(t,e){for(var n=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],r=Math.ceil(t[t.length-1]/2),i=r*Math.ceil(t[t.length-2]/2),a=i,o="",s="b, r, c",u=2;u<t.length-1;u++)o="\n      int b"+u+" = index / "+(a*=t[t.length-u-1])+";\n      index -= b"+u+" * "+a+";\n    "+o,s="b"+u+", "+s;return"\n    ivec"+t.length+" getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n\n      "+o+"\n\n      int b = index / "+i+";\n      index -= b * "+i+";\n\n      int r = 2 * (index / "+r+");\n      int c = imod(index, "+r+") * 2;\n\n      return ivec"+t.length+"("+s+");\n    }\n  "}(t,e)}var n,r,i,a,o}(e.logicalShape,l),o="\n    void setOutput(vec4 val) {\n      "+c.output+" = val;\n    }\n  "):(a=function(t,e){switch(t.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return function(t,e){return 1===e[0]?"\n      int getOutputCoords() {\n        return int(resultUV.x * "+e[1]+".0);\n      }\n    ":1===e[1]?"\n      int getOutputCoords() {\n        return int(resultUV.y * "+e[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      return resTexRC.x * "+e[1]+" + resTexRC.y;\n    }\n  "}(0,e);case 2:return function(t,e){return y(t,e)?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+e[0]+", "+e[1]+"));\n      }\n    ":1===t[1]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":1===t[0]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+e[0]+", "+e[1]+"));\n        int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      int r = index / "+t[1]+";\n      int c = index - r * "+t[1]+";\n      return ivec2(r, c);\n    }\n  "}(t,e);case 3:return n=e,r=di(["r","c","d"],t),"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+n[0]+", "+n[1]+"));\n      int index = resTexRC.x * "+n[1]+" + resTexRC.y;\n      "+r+"\n      return ivec3(r, c, d);\n    }\n  ";case 4:return function(t,e){var n=di(["r","c","d","d2"],t);return"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n      "+n+"\n      return ivec4(r, c, d, d2);\n    }\n  "}(t,e);case 5:return function(t,e){var n=di(["r","c","d","d2","d3"],t);return"\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+e[0]+",\n                             "+e[1]+"));\n\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  "}(t,e);case 6:return function(t,e){var n=di(["r","c","d","d2","d3","d4"],t);return"\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+e[0]+", "+e[1]+"));\n      int index = resTexRC.x * "+e[1]+" + resTexRC.y;\n\n      "+n+"\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  "}(t,e);default:throw new Error(t.length+"-D output sampling is not yet supported")}var n,r}(e.logicalShape,l),o="\n    void setOutput(float val) {\n      "+c.output+" = vec4(val, 0, 0, 0);\n    }\n  "),r&&(h+=wi),[h,p,o,s,a,u,n].join("\n")}var yi="\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",bi="\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",xi="\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",wi="\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n";function Ni(t){return"offset"+t}function Ci(t){var e=t.name,n=v(t.shapeInfo.logicalShape);return n<2?"return "+e+";":"\n    for (int i = 0; i < "+n+"; i++) {\n      if (i == index) {\n        return "+e+"[i];\n      }\n    }\n  "}function Ei(t){if(t<=1)return"int";if(2===t)return"ivec2";if(3===t)return"ivec3";if(4===t)return"ivec4";if(5===t)return"ivec5";if(6===t)return"ivec6";throw Error("GPU for rank "+t+" is not yet supported")}function Si(t,e){var n=JSON.parse(JSON.stringify(t));return n.shapeInfo.logicalShape=e,n}function ki(t,e){return e.map(function(e){return t[e]}).join(", ")}var Ii=function(t,e,n,r){this.variableNames=["A"],this.usesPackedTextures=!0,f(t.length>2,function(){return"Packed arg"+(n.charAt(0).toUpperCase()+n.slice(1))+" supports only inputs with rank above 2."});var i=t[t.length-1],a=Math.ceil(i/e);this.outputShape=t.slice(0,-1),a>1&&this.outputShape.push(a),r||this.variableNames.push("bestIndicesA");var o,s,u=this.outputShape,l=u.length,c=Ei(l),p=hi("coords",l);if(1===a){var h=Ei(s=l+1);o="\n        "+h+" sourceLocR = "+h+"("+p.join()+", 0);\n        ++"+p[l-1]+";\n        "+h+" sourceLocG = "+h+"("+p.join()+", 0);\n        ++"+p[l-2]+";\n        "+h+" sourceLocA = "+h+"("+p.join()+", 0);\n        --"+p[l-1]+";\n        "+h+" sourceLocB = "+h+"("+p.join()+", 0);\n        --"+p[l-2]+";"}else s=l,o="\n        "+c+" sourceLocR = coords;\n        ++"+p[l-1]+";\n        "+c+" sourceLocG = coords;\n        ++"+p[l-2]+";\n        "+c+" sourceLocA = coords;\n        --"+p[l-1]+";\n        "+c+" sourceLocB = coords;\n        --"+p[l-2]+";";var d=["x","y","z","w","u","v"].slice(0,s),m="."+d[s-1],g=d.map(function(t){return"int "+t}),v=hi("sourceLocR",s-1).concat("inIdx.r"),y=hi("sourceLocG",s-1).concat("inIdx.g"),b=hi("sourceLocB",s-1).concat("inIdx.b"),x=hi("sourceLocA",s-1).concat("inIdx.a"),w="max"===n?"greaterThan":"lessThan",N=r?"":"\n          inIdx = round(vec4(getBestIndicesAChannel("+v.join()+"),\n                             getBestIndicesAChannel("+y.join()+"),\n                             getBestIndicesAChannel("+b.join()+"),\n                             getBestIndicesAChannel("+x.join()+")));",C="vec4(\n            getAChannel("+v.join()+"),\n            hasNextCol ? getAChannel("+y.join()+") : 0.,\n            hasNextRow ? getAChannel("+b.join()+") : 0.,\n            hasNextRow && hasNextCol ? getAChannel("+x.join()+") : 0.)",E=r?"":"\n      float getBestIndicesAChannel("+g.join()+") {\n        return getChannel(getBestIndicesA("+d.join()+"),\n                                          vec2("+d.slice(-2).join()+"));\n      }";this.userCode="\n      float getAChannel("+g.join()+") {\n        return getChannel(getA("+d.join()+"),\n                               vec2("+d.slice(-2).join()+"));\n      }\n      "+E+"\n      void main() {\n        "+c+" coords = getOutputCoords();\n        bool hasNextCol = "+p[l-1]+" < "+(u[l-1]-1)+";\n        bool hasNextRow = "+p[l-2]+" < "+(u[l-2]-1)+";\n        "+o+"\n        ivec4 srcIdx = ivec4(sourceLocR"+m+", sourceLocG"+m+",\n          sourceLocB"+m+", sourceLocA"+m+") * "+e+";\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = "+C+";\n\n        for (int i = 0; i < "+e+"; i++) {\n          inIdx = srcIdx;\n          "+N+"\n          vec4 candidate = "+C+";\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4("+w+"(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    "},Ai=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,i=t.strideWidth,a=t.dilationHeight,o=t.dilationWidth,s=t.effectiveFilterHeight,u=t.effectiveFilterWidth,l=s-1-t.padInfo.top,c=u-1-t.padInfo.left,p=1/(e*n);this.userCode="\n      const ivec2 pads = ivec2("+l+", "+c+");\n      const float avgMultiplier = float("+p+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+";\n            wR += "+a+") {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+u+";\n            wC+= "+o+") {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ri=function(t){this.variableNames=["dy"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,i=t.strideDepth,a=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,l=t.dilationWidth,c=t.effectiveFilterDepth,p=t.effectiveFilterHeight,h=t.effectiveFilterWidth,f=c-1-t.padInfo.front,d=p-1-t.padInfo.top,m=h-1-t.padInfo.left,g=1/(e*n*r);this.userCode="\n      const ivec3 pads = ivec3("+f+", "+d+", "+m+");\n      const float avgMultiplier = float("+g+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+c+";\n            wD += "+s+") {\n          float dyD = float(dyDCorner + wD) / "+i+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+p+";\n              wR += "+u+") {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+h+";\n                wC += "+l+") {\n              float dyC = float(dyCCorner + wC) / "+o+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ti=function(t,e,n,r,i,a){this.outputShape=[],this.variableNames=["x","mean","variance"],Mr(t,e),Mr(t,n);var o="0.0";null!=r&&(Mr(t,r),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");var s="1.0";null!=i&&(Mr(t,i),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+o+";\n        float scale = "+s+";\n        float inv = scale * inversesqrt(variance + float("+a+"));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    "},Di=function(t,e,n,r,i,a){this.usesPackedTextures=!0,this.variableNames=["x","mean","variance"],Mr(t,e),Mr(t,n);var o="vec4(0.0)";null!=r&&(Mr(t,r),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");var s="vec4(1.0)";null!=i&&(Mr(t,i),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=t,this.userCode="\n      void main() {\n        vec4 offset = "+o+";\n        vec4 scale = "+s+";\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4("+a+"));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    "},Oi=function(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=Mr(e,n),this.userCode="\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        "+t+"\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    "},_i="return a + b;",Fi="return a - b;",Mi="return a * b;",zi="return (a < 0.) ? b * a : a;",Li=function(t,e,n){this.variableNames=["A","B"],this.outputShape=Mr(e,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+t+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    "},Pi="\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n",Bi=function(t,e,n,r){void 0===r&&(r=!1),this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.usesPackedTextures=!0,this.outputShape=Mr(e,n);var i=this.outputShape.length,a="";if(r)if(0===i||1===v(this.outputShape))a="\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        ";else if(a="\n          "+Ei(i)+" coords = getOutputCoords();\n        ",1===i)a+="\n            result.y = (coords + 1) >= "+this.outputShape[0]+" ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          ";else{var o=hi("coords",i);a+="\n            bool nextRowOutOfBounds =\n              ("+o[i-2]+" + 1) >= "+this.outputShape[i-2]+";\n            bool nextColOutOfBounds =\n              ("+o[i-1]+" + 1) >= "+this.outputShape[i-1]+";\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          "}this.userCode="\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        "+t+"\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        "+a+"\n\n        setOutput(result);\n      }\n    "},Vi=function(){function t(t){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,i){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(i,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(i,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Wi=function(){function t(t){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=t,this.userCode="\n      uniform float minVal;\n      uniform float maxVal;\n\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t,e){var n=this;return function(r,i){null==n.minLoc&&(n.minLoc=r.getUniformLocationNoThrow(i,"minVal"),n.maxLoc=r.getUniformLocationNoThrow(i,"maxVal")),r.gl.uniform1f(n.minLoc,t),r.gl.uniform1f(n.maxLoc,e)}},t}(),Ui=function(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode="\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    "},ji=function(t){this.outputShape=[],this.outputShape=Je(t,1),this.variableNames=t.map(function(t,e){return"T"+e});var e=new Array(t.length-1);e[0]=t[0][1];for(var n=1;n<e.length;n++)e[n]=e[n-1]+t[n][1];var r=["if (yC < "+e[0]+") setOutput(getT0(yR, yC));"];for(n=1;n<e.length;n++){var i=e[n-1];r.push("else if (yC < "+e[n]+") setOutput(getT"+n+"(yR, yC-"+i+"));")}var a=e.length,o=e[e.length-1];r.push("else setOutput(getT"+a+"(yR, yC-"+o+"));"),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        "+r.join("\n        ")+"\n      }\n    "},Gi=function(t,e){this.usesPackedTextures=!0,this.outputShape=[],this.outputShape=Je(t,e);var n=this.outputShape,r=n.length,i=Ei(r),a=hi("coords",r),o=["x","y","z","w","u","v"].slice(0,r);this.variableNames=t.map(function(t,e){return"T"+e});var s=new Array(t.length-1);s[0]=t[0][e];for(var u=1;u<s.length;u++)s[u]=s[u-1]+t[u][e];var l=o[e],c="vec2("+o.slice(-2).join()+")",p=o.join(),h="if ("+l+" < "+s[0]+")\n          return getChannel(getT0("+p+"), "+c+");";for(u=1;u<s.length;u++){var f=s[u-1];h+="\n        else if ("+l+" < "+s[u]+") {\n          "+l+" -= "+f+";\n          return getChannel(getT"+u+"("+p+"), "+c+");\n        }"}var d=s.length;h+="\n        else {\n          "+l+" -= "+s[s.length-1]+";\n          return getChannel(getT"+d+"("+p+"), "+c+");\n        }",this.userCode="\n      float getValue("+o.map(function(t){return"int "+t})+") {\n        "+h+"\n      }\n\n      void main() {\n        "+i+" coords = getOutputCoords();\n        vec4 result = vec4(getValue("+a+"), 0., 0., 0.);\n        if (++"+a[r-1]+" < "+n[r-1]+") {\n          result.g = getValue("+a+");\n        }\n        if (++"+a[r-2]+" < "+n[r-2]+") {\n          result.a = getValue("+a+");\n        }\n        if ("+a[r-2]+" < "+n[r-2]+" &&\n            --"+a[r-1]+" < "+n[r-1]+") {\n          result.b = getValue("+a+");\n        }\n        setOutput(result);\n      }\n    "},Hi=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,i=t.padInfo.left,a="channelsLast"===t.dataFormat;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+i+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              if ("+a+") {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},qi=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,i=t.strideWidth,a="channelsLast"===t.dataFormat,o=e-1-t.padInfo.top,s=n-1-t.padInfo.left,u=a?1:2,l=a?2:3,c=a?3:1;this.userCode="\n      const ivec2 pads = ivec2("+o+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords["+c+"];\n\n        ivec2 dyCorner = ivec2(coords["+u+"], coords["+l+"]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n\n              if ("+a+") {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ki=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,i=t.padInfo.front,a=t.padInfo.top,o=t.padInfo.left;this.userCode="\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yF = 0; yF < "+t.outDepth+"; yF++) {\n            int xF = wF + yF * "+e+" - "+i+";\n\n            if (xF < 0 || xF >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n              int xR = wR + yR * "+n+" - "+a+";\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n                int xC = wC + yC * "+r+" - "+o+";\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},$i=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterDepth,n=t.filterHeight,r=t.filterWidth,i=t.strideDepth,a=t.strideHeight,o=t.strideWidth,s=e-1-t.padInfo.front,u=n-1-t.padInfo.top,l=r-1-t.padInfo.left;this.userCode="\n      const ivec3 pads = ivec3("+s+", "+u+", "+l+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+e+"; wF++) {\n          float dyF = float(dyFCorner + wF) / "+i+".0;\n\n          if (dyF < 0.0 || dyF >= "+t.outDepth+".0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = "+e+" - 1 - wF;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            float dyR = float(dyRCorner + wR) / "+a+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = "+n+" - 1 - wR;\n\n            for (int wC = 0; wC < "+r+"; wC++) {\n              float dyC = float(dyCCorner + wC) / "+o+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = "+r+" - 1 - wC;\n\n              for (int d2 = 0; d2 < "+t.outChannels+"; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Xi=function(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;var e=t.strideHeight,n=t.strideWidth,r=t.padInfo.top,i=t.padInfo.left,a=t.outChannels/t.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+a+" + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < "+t.batchSize+"; b++) {\n          for (int yR = 0; yR < "+t.outHeight+"; yR++) {\n            int xR = wR + yR * "+e+" - "+r+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+t.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+i+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Yi=function(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;var e=t.filterHeight,n=t.filterWidth,r=t.strideHeight,i=t.strideWidth,a=e-1-t.padInfo.top,o=n-1-t.padInfo.left,s=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+o+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+e+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+e+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+s+"; dm++) {\n              int d2 = d1 * "+s+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ji=function(t,e,n,r){void 0===e&&(e=!1),void 0===n&&(n=null),void 0===r&&(r=!1),this.variableNames=["x","W"],this.outputShape=t.outShape;var i=t.padInfo.top,a=t.padInfo.left,o=t.strideHeight,s=t.strideWidth,u=t.dilationHeight,l=t.dilationWidth,c=t.filterHeight,p=t.filterWidth,h=4*Math.floor(t.inChannels/4),f=t.inChannels%4,d="channelsLast"===t.dataFormat,m=d?1:2,g=d?2:3,v=d?3:1,y="",b="";n&&(y=r?"float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          "+n+"\n        }":"\n          float activation(float x) {\n            "+n+"\n          }\n        ",b="result = activation(result);");var x=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+y+"\n\n      const ivec2 strides = ivec2("+o+", "+s+");\n      const ivec2 pads = ivec2("+i+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords["+v+"];\n\n        ivec2 xRCCorner =\n            ivec2(coords["+m+"], coords["+g+"]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+c+"; wR++) {\n          int xR = xRCorner + wR * "+u+";\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+p+"; wC++) {\n            int xC = xCCorner + wC * "+l+";\n\n            if (xC < 0 || xC >= "+t.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+h+"; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if ("+d+") {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if ("+(1===f)+") {\n\n              if ("+d+") {\n                dotProd +=\n                    getX(batch, xR, xC, "+h+") *\n                    getW(wR, wC, "+h+", d2);\n              } else {\n                dotProd +=\n                    getX(batch, "+h+", xR, xC) *\n                    getW(wR, wC, "+h+", d2);\n              }\n\n            } else if ("+(2===f)+") {\n              vec2 wValues = vec2(\n                getW(wR, wC, "+h+", d2),\n                getW(wR, wC, "+h+" + 1, d2)\n              );\n\n              if ("+d+") {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, "+h+"),\n                  getX(batch, xR, xC, "+h+" + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, "+h+", xR, xC),\n                  getX(batch, "+h+" + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if ("+(3===f)+") {\n              vec3 wValues = vec3(\n                getW(wR, wC, "+h+", d2),\n                getW(wR, wC, "+h+" + 1, d2),\n                getW(wR, wC, "+h+" + 2, d2)\n              );\n\n              if ("+d+") {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, "+h+"),\n                  getX(batch, xR, xC, "+h+" + 1),\n                  getX(batch, xR, xC, "+h+" + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, "+h+", xR, xC),\n                  getX(batch, "+h+" + 1, xR, xC),\n                  getX(batch, "+h+" + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        "+x+"\n        "+b+"\n        setOutput(result);\n      }\n    "},Zi=function(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.padInfo.front,n=t.padInfo.top,r=t.padInfo.left,i=t.strideDepth,a=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,l=t.dilationWidth,c=t.filterDepth,p=t.filterHeight,h=t.filterWidth,f=4*Math.floor(t.inChannels/4),d=t.inChannels%4;this.userCode="\n      const ivec3 strides = ivec3("+i+", "+a+", "+o+");\n      const ivec3 pads = ivec3("+e+", "+n+", "+r+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < "+c+"; wF++) {\n          int xF = xFCorner + wF * "+s+";\n\n          if (xF < 0 || xF >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+p+"; wR++) {\n            int xR = xRCorner + wR * "+u+";\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+h+"; wC++) {\n              int xC = xCCorner + wC * "+l+";\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < "+f+"; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if ("+(1===d)+") {\n                dotProd +=\n                  getX(batch, xF, xR, xC, "+f+") *\n                  getW(wF, wR, wC, "+f+", d2);\n              } else if ("+(2===d)+") {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, "+f+"),\n                  getX(batch, xF, xR, xC, "+f+" + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, "+f+", d2),\n                  getW(wF, wR, wC, "+f+" + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if ("+(3===d)+") {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, "+f+"),\n                  getX(batch, xF, xR, xC, "+f+" + 1),\n                  getX(batch, xF, xR, xC, "+f+" + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, "+f+", d2),\n                  getW(wF, wR, wC, "+f+" + 1, d2),\n                  getW(wF, wR, wC, "+f+" + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Qi=function(t){this.variableNames=["x","W"],this.outputShape=t.outShape;var e=t.inHeight,n=t.inWidth,r=t.padInfo.top,i=t.padInfo.left,a=t.strideHeight,o=t.strideWidth,s=t.dilationHeight,u=t.dilationWidth,l=t.filterHeight,c=t.filterWidth,p=t.outChannels/t.inChannels;this.userCode="\n      const ivec2 strides = ivec2("+a+", "+o+");\n      const ivec2 pads = ivec2("+r+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+p+";\n        int q = d2 - d1 * "+p+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+s+";\n\n          if (xR < 0 || xR >= "+e+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+c+"; wC++) {\n            int xC = xCCorner + wC * "+u+";\n\n            if (xC < 0 || xC >= "+n+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},ta=function(t){this.variableNames=["x","W"],this.usesPackedTextures=!0,this.outputShape=t.outShape;for(var e=t.inHeight,n=t.inWidth,r=t.padInfo.top,i=t.padInfo.left,a=t.strideHeight,o=t.strideWidth,s=t.dilationHeight,u=t.dilationWidth,l=t.filterHeight,c=t.filterWidth,h=c,f="int xR; int xC; int xCOffset;",d=0;d<l;d++)for(var m=0;m<c;m++)f+="\n          vec4 xTexelR"+d+"C"+2*m+" = vec4(0.);\n          vec4 wR"+d+"C"+m+" = vec4(0.);\n          vec4 xR"+d+"C"+m+" = vec4(0.);";for(d=0;d<l;d++)for(var g=0;g<h;g++){if(f+="\n          xR = xRCorner + "+d*s+";\n          xC = xCCorner + "+(m=2*g)*u+";\n        ",1===o){if(m<c&&(f+=i%2==1?"\n                xCOffset = xC + 1;\n                if(xR >= 0 && xR < "+e+" && xCOffset >= 0 && xCOffset < "+n+") {\n                  xTexelR"+d+"C"+m+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+d+"C"+m+" = vec4(0.);\n                }\n\n                xCOffset = xC + 1 - 2;\n                if(xR >= 0 && xR < "+e+" && xCOffset >= 0 && xCOffset < "+n+") {\n                  vec4 previous = getX(batch, xR, xCOffset, d1);\n                  xR"+d+"C"+m+" = vec4(previous.zw, xTexelR"+d+"C"+m+".xy);\n                } else {\n                  xR"+d+"C"+m+" = vec4(0, 0, xTexelR"+d+"C"+m+".xy);\n                }\n              ":"\n                if(xR >= 0 && xR < "+e+" && xC >= 0 && xC < "+n+") {\n                  xTexelR"+d+"C"+m+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+d+"C"+m+" = vec4(0.);\n                }\n\n                xR"+d+"C"+m+" = xTexelR"+d+"C"+m+";\n              ",m+1<c)){var v=i%2==0?p(u):u;u%2==0&&i%2==1||u%2!=0&&i%2!=1?(f+="\n                  xCOffset = xC + "+i%2+" + "+v+";\n\n                  if(xR >= 0 && xR < "+e+" &&\n                    xCOffset >= 0 && xCOffset < "+n+") {\n                    xTexelR"+d+"C"+(m+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n                ",u>1&&(f+="\n                    xCOffset -= 2;\n                    if(xR >= 0 && xR < "+e+" &&\n                      xCOffset >= 0 && xCOffset < "+n+") {\n                      xTexelR"+d+"C"+m+" = getX(batch, xR, xCOffset, d1);\n                    } else {\n                      xTexelR"+d+"C"+m+" = vec4(0.);\n                    }\n                  "),f+="\n                  xR"+d+"C"+(m+1)+" = vec4(\n                    xTexelR"+d+"C"+m+".zw, xTexelR"+d+"C"+(m+2)+".xy);\n                "):f+="\n                  xCOffset = xC + "+v+";\n\n                  if(xR >= 0 && xR < "+e+" &&\n                    xCOffset >= 0 && xCOffset < "+n+") {\n                    xTexelR"+d+"C"+(m+2)+" = getX(batch, xR, xCOffset, d1);\n                  }\n\n                  xR"+d+"C"+(m+1)+" = xTexelR"+d+"C"+(m+2)+";\n                "}}else m<c&&(f+="\n              if(xR >= 0 && xR < "+e+") {\n            ",i%2==1?(f+="\n                xCOffset = xC + 1 - "+o+";\n                if(xCOffset >= 0 && xCOffset < "+n+") {\n                  xTexelR"+d+"C"+m+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+d+"C"+m+" = vec4(0.);\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < "+n+") {\n                  xTexelR"+d+"C"+(m+2)+" = getX(batch, xR, xC + 1, d1);\n                } else {\n                  xTexelR"+d+"C"+(m+2)+" = vec4(0.);\n                }\n\n                xR"+d+"C"+m+" = vec4(\n                  xTexelR"+d+"C"+m+".zw, xTexelR"+d+"C"+(m+2)+".zw);\n              ",m+1<c&&(f+="\n                  vec4 final = vec4(0.);\n                  xCOffset = xC + 1 + "+o+";\n                  if(xCOffset >= 0 && xCOffset < "+n+") {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xR"+d+"C"+(m+1)+" = vec4(xTexelR"+d+"C"+(m+2)+".xy, final.xy);\n                ")):(f+="\n                if(xC >= 0 && xC < "+n+") {\n                  xTexelR"+d+"C"+m+" = getX(batch, xR, xC, d1);\n                } else {\n                  xTexelR"+d+"C"+m+" = vec4(0.);\n                }\n\n                xCOffset = xC + "+o+";\n                if(xCOffset >= 0 && xCOffset < "+n+") {\n                  xTexelR"+d+"C"+(m+2)+" = getX(batch, xR, xCOffset, d1);\n                } else {\n                  xTexelR"+d+"C"+(m+2)+" = vec4(0.);\n                }\n\n                xR"+d+"C"+m+" = vec4(\n                  xTexelR"+d+"C"+m+".xy, xTexelR"+d+"C"+(m+2)+".xy);\n              ",m+1<c&&(f+="\n                  xR"+d+"C"+(m+1)+" = vec4(\n                    xTexelR"+d+"C"+m+".zw, xTexelR"+d+"C"+(m+2)+".zw);\n                ")),f+="}");m<c&&(f+="\n            vec4 wTexelR"+d+"C"+m+" = getW("+d+", "+m+", d1, q);\n            wR"+d+"C"+m+" = vec4(wTexelR"+d+"C"+m+".xz, wTexelR"+d+"C"+m+".xz);\n          ",m+1<c&&(f+="\n              vec4 wTexelR"+d+"C"+(m+1)+" = getW("+d+", "+(m+1)+", d1, q);\n              wR"+d+"C"+(m+1)+" =\n                vec4(wTexelR"+d+"C"+(m+1)+".xz, wTexelR"+d+"C"+(m+1)+".xz);"))}for(d=0;d<l;d++)for(m=0;m<c;m++)f+="result += xR"+d+"C"+m+" * wR"+d+"C"+m+";";this.userCode="\n      const ivec2 strides = ivec2("+a+", "+o+");\n      const ivec2 pads = ivec2("+r+", "+i+");\n\n      void main() {\n\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2;\n        int q = 0;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        vec4 result = vec4(0.);\n\n        "+f+"\n\n        setOutput(result);\n      }\n    "},ea=function(t,e,n,r,i){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];var a=t[0],o=t[1],s=t[2],u=t[3],l=e[0],c=n[0],p=n[1];this.outputShape=[l,c,p,u];var h="bilinear"===r?1:0,f=[o-1+".0",s-1+".0"],d=f[0],m=f[1],g=c>1?[""+(o-1)/(c-1),"(y2-y1) * height_ratio","y1*"+d+" + float(y)*(height_scale)"]:["0.0","0.0","0.5 * (y1+y2) * "+d],v=g[0],y=g[1],b=g[2],x=p>1?[""+(s-1)/(p-1),"(x2-x1) * width_ratio","x1*"+m+" + float(x)*(width_scale)"]:["0.0","0.0","0.5 * (x1+x2) * "+m],w=x[0],N=x[1],C=x[2];this.userCode="\n      const float height_ratio = float("+v+");\n      const float width_ratio = float("+w+");\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= "+a+") {\n          return;\n        }\n\n        float height_scale = "+y+";\n        float width_scale = "+N+";\n\n        float in_y = "+b+";\n        if( in_y < 0.0 || in_y > "+d+" ) {\n          setOutput(float("+i+"));\n          return;\n        }\n        float in_x = "+C+";\n        if( in_x < 0.0 || in_x > "+m+" ) {\n          setOutput(float("+i+"));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if("+h+" == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    "},na=function(t,e,n){this.variableNames=["x"],this.outputShape=t;var r=t.length,i=t[t.length-1],a=n?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(n?"return "+i+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+Ei(r)+" coords = getOutputCoords();\n        int end = "+ra(r,"coords")+";\n        float val = 0.0;\n        for (int i = "+i+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+a+" end) {\n            continue;\n          }\n          if (idx == end && "+e+") {\n            continue;\n          }\n          "+ra(r,"coords")+" = idx;\n          val += getX("+function(t,e){if(1===t)return""+e;if(2===t)return e+".x, "+e+".y";if(3===t)return e+".x, "+e+".y, "+e+".z";if(4===t)return e+".x, "+e+".y, "+e+".z, "+e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}(r,"coords")+");\n        }\n        setOutput(val);\n      }\n    "};function ra(t,e){if(1===t)return""+e;if(2===t)return e+".y";if(3===t)return e+".z";if(4===t)return e+".w";throw Error("Cumulative sum for rank "+t+" is not yet supported")}var ia=function(t,e){this.variableNames=["A"];var n=fi();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+di(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        "+n.output+" = result;\n      }\n    "},aa=function(t,e){this.variableNames=["A"],this.usesPackedTextures=!0;var n=fi();this.outputShape=t,this.userCode="\n      ivec3 outCoordsFromFlatIndex(int index) {\n        "+di(["r","c","d"],t)+"\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n          vec2("+e[0]+", "+e[1]+"));\n        int index = 4 * (resTexRC.x * "+e[1]+" + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        "+n.output+" = result;\n      }\n    "},oa=function(){function t(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode="\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = "+this.getHeightCoordString()+";\n      int w = "+this.getWidthCoordString()+";\n      int d = "+this.getDepthCoordString()+";\n\n      int in_h = h / "+e+";\n      int offset_h = imod(h, "+e+");\n      int in_w = w / "+e+";\n      int offset_w = imod(w, "+e+");\n      int offset_d = (offset_h * "+e+" + offset_w) *\n        "+this.getOutputDepthSize()+";\n      int in_d = d + offset_d;\n\n      float result = "+this.getInputSamplingString()+";\n      setOutput(result);\n    }\n  "}return t.prototype.getHeightCoordString=function(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"},t.prototype.getWidthCoordString=function(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"},t.prototype.getDepthCoordString=function(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"},t.prototype.getOutputDepthSize=function(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]},t.prototype.getInputSamplingString=function(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"},t}(),sa=function(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode="\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    "},ua=function(t){this.variableNames=["A"];var e=fi();this.outputShape=t,this.userCode="\n      "+gi+"\n\n      void main() {\n        float x = getAAtOutCoords();\n        "+e.output+" = encode_float(x);\n      }\n    "},la=function(t){this.variableNames=["A"],this.usesPackedTextures=!0;var e=fi();this.outputShape=t,this.userCode="\n      "+gi+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        "+e.output+" = encode_float(x);\n      }\n    "},ca=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=fi(),i=e[0],a=e[1];this.outputShape=t;var o="result";n&&(o="floor(result * 255. + 0.5)"),this.userCode="\n      "+mi(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n        \n        int r = flatIndex / "+a+";\n        int c = imod(flatIndex, "+a+");\n        vec2 uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+i+".0);\n        vec4 values = "+r.texture2D+"(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        "+r.output+" = vec4("+o+", 0., 0., 0.);\n      }\n    "},pa=function(t,e,n){void 0===n&&(n=!1),this.variableNames=["A"];var r=fi(),i=e[0],a=e[1];this.outputShape=t;var o="",s="result";n&&(s="floor(result * 255. + 0.5)");for(var u=0;u<=1;u++)for(var l=0;l<=1;l++){var c=2*u+l;o+="\n          localCoords = coords;\n          if(localCoords[2] + "+l+" < "+t[2]+") {\n            localCoords[2] += "+l+";\n            if(localCoords[1] + "+u+" < "+t[1]+") {\n              localCoords[1] += "+u+";\n\n              flatIndex = getFlatIndex(localCoords);\n              offset = imod(flatIndex, 4);\n    \n              flatIndex = idiv(flatIndex, 4, 1.);\n\n              r = flatIndex / "+a+";\n              c = imod(flatIndex, "+a+");\n              uv = (vec2(c, r) + halfCR) / vec2("+a+".0, "+i+".0);\n              values = "+r.texture2D+"(A, uv);\n\n              if(offset == 0) {\n                result["+c+"] = values[0];\n              } else if(offset == 1) {\n                result["+c+"] = values[1];\n              } else if(offset == 2) {\n                result["+c+"] = values[2];\n              } else {\n                result["+c+"] = values[3];\n              }\n            }\n          }\n        "}this.userCode="\n      "+mi(t)+"\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        vec4 result = vec4(0.);\n        int flatIndex, r, c, offset;\n        ivec3 localCoords;\n        vec2 uv;\n        vec4 values;\n        \n        "+o+"\n\n        "+r.output+" = "+s+";\n      }\n    "},ha=function(t,e,n){this.variableNames=["real","imag"];var r=e[1];this.outputShape=e;var i=n?"2.0 * "+Math.PI:"-2.0 * "+Math.PI,a=n?r+".0":"1.0";this.userCode="\n      const float exponentMultiplier = "+i+";\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        "+t+"\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float("+r+");\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < "+r+"; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / "+a+";\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    "},fa=function(){function t(t,e){this.outputShape=[],this.variableNames=["x"],this.outputShape=t,this.userCode="\n      uniform float value;\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.valueLoc&&(e.valueLoc=n.getUniformLocationNoThrow(r,"value")),n.gl.uniform1f(e.valueLoc,t)}},t}(),da=function(t){this.variableNames=["A"];var e=fi(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+n+".0);\n\n        vec4 values = "+e.texture2D+"(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    "},ma=function(t){this.variableNames=["A"];var e=fi(),n=t[0],r=t[1];this.outputShape=t,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+n+".0);\n            vec4 values = "+e.texture2D+"(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        "+e.output+" = result;\n      }\n    "},ga=function(t,e,n){this.variableNames=["A","indices"];var r=t.slice();r[n]=e,this.outputShape=r,this.rank=r.length;var i=Ei(this.rank),a=function(t,e){var n=t.length;if(n>4)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return"int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],a=0;a<t.length;a++)a===e?i.push("int(getIndices("+r[a]+"))"):i.push(""+r[a]);return i.join()}(t,n);this.userCode="\n      void main() {\n        "+i+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    "},va=function(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;var r=Ei(e.length),i=Ei(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode="\n        "+r+" strides = "+r+"("+this.strides+");\n         void main() {\n          "+i+" coords = getOutputCoords();\n          int flattenIndex = 0;\n          for (int j = 0; j < "+this.sliceDim+"; j++) {\n            int index = round(getIndices(coords[0], j));\n            flattenIndex += index * "+a+";\n          }\n          setOutput(getX(flattenIndex, coords[1]));\n        }\n      "};function ya(t,e){var n=fi();return Ht(t,e,n.version+"\n    precision highp float;\n    "+n.attribute+" vec3 clipSpacePos;\n    "+n.attribute+" vec2 uv;\n    "+n.varyingVs+" vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function ba(t,e){return Qt(t,e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function xa(t,e){return te(t,e,new Uint16Array([0,1,2,2,1,3]))}function wa(t,e,n,r,i,a,o){ne(n,r);var s=ee(t,e),u=t.TEXTURE_2D;return Bt(t,e,function(){return t.bindTexture(u,s)}),Bt(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE)}),Bt(t,e,function(){return t.texParameteri(u,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE)}),Bt(t,e,function(){return t.texParameteri(u,t.TEXTURE_MIN_FILTER,t.NEAREST)}),Bt(t,e,function(){return t.texParameteri(u,t.TEXTURE_MAG_FILTER,t.NEAREST)}),Bt(t,e,function(){return t.texImage2D(u,0,i,n,r,0,a,o,null)}),Bt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)}),s}function Na(t,e,n,r,i){var a=Mt(n,r);return wa(t,e,a[0],a[1],i.internalFormatFloat,i.textureFormatFloat,t.FLOAT)}function Ca(t,e,n,r,i){var a=Mt(n,r);return wa(t,e,a[0],a[1],i.internalFormatHalfFloat,i.textureFormatFloat,i.textureTypeHalfFloat)}function Ea(t,e,n,r,i){var a=Mt(n,r);return wa(t,e,a[0],a[1],t.RGBA,t.RGBA,t.UNSIGNED_BYTE)}function Sa(t,e,n,r,i){var a=Lt(n,r);return wa(t,e,a[0],a[1],i.internalFormatPackedFloat,t.RGBA,t.FLOAT)}function ka(t,e,n,r,i){var a=Lt(n,r);return wa(t,e,a[0],a[1],i.internalFormatPackedHalfFloat,t.RGBA,i.textureTypeHalfFloat)}function Ia(t,e,n,r){return Bt(t,e,function(){return t.bindBuffer(t.ARRAY_BUFFER,r)}),ie(t,e,n,"clipSpacePos",r,3,20,0)&&ie(t,e,n,"uv",r,2,20,12)}function Aa(t,e,n,r,i,a,o){var s,u,l;Bt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),a instanceof Uint8Array?(s=new Uint8Array(r*i*4),u=t.UNSIGNED_BYTE,l=t.RGBA):(s=new Float32Array(r*i*4),u=t.FLOAT,l=o.internalFormatPackedFloat),s.set(a),Bt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,l,r,i,0,t.RGBA,u,s)}),Bt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function Ra(t,e,n,r){Bt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,n)}),r.data instanceof Uint8Array?Bt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,r.width,r.height,0,t.RGBA,t.UNSIGNED_BYTE,r.data)}):Bt(t,e,function(){return t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,r)}),Bt(t,e,function(){return t.bindTexture(t.TEXTURE_2D,null)})}function Ta(t,e,n,r,i){var a=t.createBuffer();Bt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,a)});var o=16*n*r;return Bt(t,e,function(){return t.bufferData(t.PIXEL_PACK_BUFFER,o,t.STREAM_READ)}),Bt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,0)}),Bt(t,e,function(){return t.bindBuffer(t.PIXEL_PACK_BUFFER,null)}),a}function Da(t,e,n){var r=t,i=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,e),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,i),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),i}function Oa(t,e,n,r,i){var a=Mt(n,r),o=a[0],s=a[1],u=new Uint8Array(n*r*4);return Bt(t,e,function(){return t.readPixels(0,0,o,s,i.downloadTextureFormat,t.UNSIGNED_BYTE,u)}),new Float32Array(u.buffer)}function _a(t,e,n,r,i,a,o,s){var u=t,l=new Float32Array(function(t,e){var n=Lt(a,o);return n[0]*n[1]*4}());return u.bindBuffer(u.PIXEL_PACK_BUFFER,e),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,l),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),l}function Fa(t,e,n,r){var i=new Float32Array(n*r*4);return Bt(t,e,function(){return t.readPixels(0,0,r,n,t.RGBA,t.FLOAT,i)}),i}var Ma=Object.freeze({createVertexShader:ya,createVertexBuffer:ba,createIndexBuffer:xa,createFloat32MatrixTexture:Na,createFloat16MatrixTexture:Ca,createUnsignedBytesMatrixTexture:Ea,createPackedMatrixTexture:Sa,createFloat16PackedMatrixTexture:ka,bindVertexProgramAttributeStreams:Ia,uploadDenseMatrixToTexture:Aa,uploadPixelDataToTexture:Ra,createBufferFromOutputTexture:Ta,downloadFloat32MatrixFromBuffer:Da,downloadByteEncodedFloatMatrixFromOutputTexture:Oa,downloadPackedMatrixFromBuffer:_a,downloadMatrixFromPackedOutputTexture:Fa}),za=function(){function e(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];var n=t.ENV.getNumber("WEBGL_VERSION");if(null!=e?(this.gl=e,Ot(n,e)):this.gl=_t(n),1===t.ENV.getNumber("WEBGL_VERSION"))this.textureFloatExtension=Gt(this.gl,this.debug,"OES_texture_float"),this.colorBufferFloatExtension=this.gl.getExtension("WEBGL_color_buffer_float"),this.textureHalfFloatExtension=Gt(this.gl,this.debug,"OES_texture_half_float"),this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float");else if(Ee(this.gl,"EXT_color_buffer_float"))this.colorBufferFloatExtension=this.gl.getExtension("EXT_color_buffer_float");else{if(!Ee(this.gl,"EXT_color_buffer_half_float"))throw new Error("GL context does not support color renderable floats");this.colorBufferHalfFloatExtension=this.gl.getExtension("EXT_color_buffer_half_float")}this.vertexBuffer=ba(this.gl,this.debug),this.indexBuffer=xa(this.gl,this.debug),this.framebuffer=re(this.gl,this.debug),this.textureConfig=Pt(this.gl,this.textureHalfFloatExtension)}return Object.defineProperty(e.prototype,"debug",{get:function(){return t.ENV.getBool("DEBUG")},enumerable:!0,configurable:!0}),e.prototype.dispose=function(){var t=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var e=this.gl;Bt(e,this.debug,function(){return e.finish()}),Bt(e,this.debug,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),Bt(e,this.debug,function(){return e.deleteFramebuffer(t.framebuffer)}),Bt(e,this.debug,function(){return e.bindBuffer(e.ARRAY_BUFFER,null)}),Bt(e,this.debug,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)}),Bt(e,this.debug,function(){return e.deleteBuffer(t.indexBuffer)}),this.disposed=!0}},e.prototype.createFloat32MatrixTexture=function(t,e){return this.throwIfDisposed(),Na(this.gl,this.debug,t,e,this.textureConfig)},e.prototype.createFloat16MatrixTexture=function(t,e){return this.throwIfDisposed(),Ca(this.gl,this.debug,t,e,this.textureConfig)},e.prototype.createUnsignedBytesMatrixTexture=function(t,e){return this.throwIfDisposed(),Ea(this.gl,this.debug,t,e,this.textureConfig)},e.prototype.uploadPixelDataToTexture=function(t,e){this.throwIfDisposed(),Ra(this.gl,this.debug,t,e)},e.prototype.uploadDenseMatrixToTexture=function(t,e,n,r){this.throwIfDisposed(),Aa(this.gl,this.debug,t,e,n,r,this.textureConfig)},e.prototype.createFloat16PackedMatrixTexture=function(t,e){return this.throwIfDisposed(),ka(this.gl,this.debug,t,e,this.textureConfig)},e.prototype.createPackedMatrixTexture=function(t,e){return this.throwIfDisposed(),Sa(this.gl,this.debug,t,e,this.textureConfig)},e.prototype.deleteMatrixTexture=function(t){var e=this;this.throwIfDisposed(),this.outputTexture===t&&(ce(this.gl,this.debug,this.framebuffer),this.outputTexture=null),Bt(this.gl,this.debug,function(){return e.gl.deleteTexture(t)})},e.prototype.downloadByteEncodedFloatMatrixFromOutputTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return Oa(r.gl,r.debug,e,n,r.textureConfig)})},e.prototype.downloadPackedMatrixFromBuffer=function(t,e,n,r,i,a){return _a(this.gl,t,0,0,0,i,a,this.textureConfig)},e.prototype.downloadFloat32MatrixFromBuffer=function(t,e){return Da(this.gl,t,e)},e.prototype.createBufferFromTexture=function(t,e,n){this.bindTextureToFrameBuffer(t);var r=Ta(this.gl,this.debug,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),r},e.prototype.createAndWaitForFence=function(){var t=this.createFence(this.gl);return this.pollFence(t)},e.prototype.createFence=function(e){var n,r,i=this;if(t.ENV.getBool("WEBGL_FENCE_API_ENABLED")){var a=e,o=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),r=function(){var t=a.clientWaitSync(o,0,0);return t===a.ALREADY_SIGNALED||t===a.CONDITION_SATISFIED},n=o}else t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(n=this.beginQuery(),this.endQuery(),r=function(){return i.isQueryAvailable(n,t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}):r=function(){return!0};return{query:n,isFencePassed:r}},e.prototype.downloadMatrixFromPackedTexture=function(t,e,n){var r=this;return this.downloadMatrixDriver(t,function(){return Fa(r.gl,r.debug,e,n)})},e.prototype.createProgram=function(t){this.throwIfDisposed();var e=this.gl,n=qt(e,this.debug,t),r=ya(e,this.debug),i=Yt(e,this.debug);return Bt(e,this.debug,function(){return e.attachShader(i,r)}),Bt(e,this.debug,function(){return e.attachShader(i,n)}),Jt(e,this.debug,i),this.debug&&Zt(e,this.debug,i),this.vertexAttrsAreBound||(this.setProgram(i),this.vertexAttrsAreBound=Ia(e,this.debug,this.program,this.vertexBuffer)),i},e.prototype.deleteProgram=function(t){var e=this;this.throwIfDisposed(),t===this.program&&(this.program=null),null!=t&&Bt(this.gl,this.debug,function(){return e.gl.deleteProgram(t)})},e.prototype.setProgram=function(t){var e=this;this.throwIfDisposed(),this.program=t,null!=this.program&&this.debug&&Zt(this.gl,this.debug,this.program),Bt(this.gl,this.debug,function(){return e.gl.useProgram(t)})},e.prototype.getUniformLocation=function(t,e,n){return void 0===n&&(n=!0),this.throwIfDisposed(),n?oe(this.gl,this.debug,t,e):se(this.gl,t,e)},e.prototype.getAttributeLocation=function(t,e){var n=this;return this.throwIfDisposed(),Bt(this.gl,this.debug,function(){return n.gl.getAttribLocation(t,e)})},e.prototype.getUniformLocationNoThrow=function(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)},e.prototype.setInputMatrixTexture=function(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),ue(this.gl,this.debug,this.program,t,e,n)},e.prototype.setOutputMatrixTexture=function(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)},e.prototype.setOutputPackedMatrixTexture=function(t,e,n){this.throwIfDisposed();var r=Lt(e,n),i=r[0],a=r[1];this.setOutputMatrixTextureDriver(t,i,a)},e.prototype.setOutputMatrixWriteRegion=function(t,e,n,r){this.setOutputMatrixWriteRegionDriver(n,t,r,e)},e.prototype.setOutputPackedMatrixWriteRegion=function(t,e,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},e.prototype.debugValidate=function(){null!=this.program&&Zt(this.gl,this.debug,this.program),pe(this.gl)},e.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var t=this.gl;this.debug&&this.debugValidate(),Bt(t,this.debug,function(){return t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0)})},e.prototype.blockUntilAllProgramsCompleted=function(){var t=this;this.throwIfDisposed(),Bt(this.gl,this.debug,function(){return t.gl.finish()})},e.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=Gt(this.gl,this.debug,2===t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},e.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},e.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},e.prototype.beginQuery=function(){if(2===t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.gl,n=this.getQueryTimerExtensionWebGL2(),r=e.createQuery();return e.beginQuery(n.TIME_ELAPSED_EXT,r),r}var i=this.getQueryTimerExtensionWebGL1(),a=i.createQueryEXT();return i.beginQueryEXT(i.TIME_ELAPSED_EXT,a),a},e.prototype.endQuery=function(){if(2!==t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}else{var n=this.gl,r=this.getQueryTimerExtensionWebGL2();n.endQuery(r.TIME_ELAPSED_EXT)}},e.prototype.waitForQueryAndGetTime=function(e){return r(this,void 0,void 0,function(){var n=this;return i(this,function(r){switch(r.label){case 0:return[4,C(function(){return n.disposed||n.isQueryAvailable(e,t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))})];case 1:return r.sent(),[2,this.getQueryTime(e,t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))]}})})},e.prototype.getQueryTime=function(t,e){if(0===e)return null;if(2===e){var n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}var r=this.getQueryTimerExtensionWebGL1();return r.getQueryObjectEXT(t,r.QUERY_RESULT_EXT)/1e6},e.prototype.isQueryAvailable=function(t,e){if(0===e)return!0;if(2===e){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),i=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),i&&!this.disjoint}return i=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(t,r.QUERY_RESULT_AVAILABLE_EXT),null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),i&&!this.disjoint},e.prototype.pollFence=function(t){var e=this;return new Promise(function(n){e.addItemToPoll(function(){return t.isFencePassed()},function(){return n()})})},e.prototype.pollItems=function(){for(var t=function(t){for(var e=0;e<t.length;++e){if(!t[e]())break}return e-1}(this.itemsToPoll.map(function(t){return t.isDoneFn})),e=0;e<=t;++e)(0,this.itemsToPoll[e].resolveFn)();this.itemsToPoll=this.itemsToPoll.slice(t+1)},e.prototype.addItemToPoll=function(t,e){var n=this;this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||C(function(){return n.pollItems(),0===n.itemsToPoll.length})},e.prototype.bindTextureToFrameBuffer=function(t){this.throwIfDisposed(),le(this.gl,this.debug,t,this.framebuffer),this.debug&&pe(this.gl)},e.prototype.unbindTextureToFrameBuffer=function(){null!=this.outputTexture?(le(this.gl,this.debug,this.outputTexture,this.framebuffer),this.debug&&pe(this.gl)):ce(this.gl,this.debug,this.framebuffer)},e.prototype.downloadMatrixDriver=function(t,e){this.bindTextureToFrameBuffer(t);var n=e();return this.unbindTextureToFrameBuffer(),n},e.prototype.setOutputMatrixTextureDriver=function(t,e,n){this.throwIfDisposed();var r=this.gl;le(r,this.debug,t,this.framebuffer),this.debug&&pe(r),this.outputTexture=t,Bt(r,this.debug,function(){return r.viewport(0,0,e,n)}),Bt(r,this.debug,function(){return r.scissor(0,0,e,n)})},e.prototype.setOutputMatrixWriteRegionDriver=function(t,e,n,r){var i=this;this.throwIfDisposed(),Bt(this.gl,this.debug,function(){return i.gl.scissor(t,e,n,r)})},e.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},e.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},e}();function La(t,e){if(t.length!==e.length)throw Error("Binary was compiled with "+t.length+" inputs, but was executed with "+e.length+" inputs");t.forEach(function(t,n){var r=t.logicalShape,i=e[n],a=i.shape;if(!y(r,a))throw Error("Binary was compiled with different shapes than the current args. Shapes "+r+" and "+a+" must match");if(!t.isUniform||!i.isUniform){var o=t.texShape,s=i.isUniform?null:i.texData.texShape;if(!y(o,s))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+o+" and "+s+" must match")}})}var Pa=function(t,e,n){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=t;for(var r=n.filterWidth,i=n.inChannels,a=n.strideWidth,o=n.strideHeight,s=n.padInfo,u=n.outWidth,l=n.dilationWidth,c=n.dilationHeight,p=n.dataFormat,h=s.left,f=s.top,d=i*r,m=fi(),g="channelsLast"===p,v=g?0:1,y=g?1:2,b="",x=0;x<=1;x++)for(var w=0;w<=1;w++)b+="\n          blockIndex = rc.y + "+w+";\n          pos = rc.x + "+x+";\n\n          if(blockIndex < "+t[1]+" && pos < "+t[0]+") {\n            offsetY = int(blockIndex / ("+u+")) * "+o+" - "+f+";\n            d0 = offsetY + "+c+" * (pos / "+d+");\n\n            if(d0 < "+e[v]+" && d0 >= 0) {\n\n              offsetX = int(mod(float(blockIndex), "+u+".) * "+a+". - "+h+".);\n              d1 = offsetX + "+l+" * (int(mod(float(pos), "+d+".) / "+i+".));\n\n              if(d1 < "+e[y]+" && d1 >= 0) {\n\n                ch = int(mod(float(pos), "+i+".));\n\n                if ("+g+") {\n                  innerDims = vec2(d1, ch);\n                  result["+(2*x+w)+"] = getChannel(\n                    getA(d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result["+(2*x+w)+"] = getChannel(\n                    getA(ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        ";this.userCode="\n      void main() {\n        ivec2 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        "+b+"\n\n        "+m.output+" = result;\n      }\n    "},Ba=function(t,e,n,r,i){this.variableNames=["x"],this.outputShape=[];var a,o=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";a=.5===i?"inversesqrt("+u+")":1===i?"1.0/("+u+")":"exp(log("+u+") * float(-"+i+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+o+"; j <= "+o+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+s+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+a+";\n        setOutput(val);\n      }\n    "},Va=function(t,e,n,r,i){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=r,this.beta=i,this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < "+this.depth+"; ++d) {\n          int depthBegin = int(max(0.0, float(d - "+e+")));\n          int depthEnd = int(min(float("+this.depth+"),\n              float(d + "+e+" + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = "+this.depth+";\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float("+r+") * norm + float("+n+");\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float("+r+")\n                * float("+i+")\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * "+i+");\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    "},Wa=function(t,e,n,r,i){this.variableNames=["x"],this.outputShape=[],this.usesPackedTextures=!0;var a,o=e,s=t[3]-1;this.outputShape=t;var u="float("+n+") + float("+r+") * sum";a=.5===i?"inversesqrt("+u+")":1===i?"1.0/("+u+")":"exp(log("+u+") * float(-"+i+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < "+this.outputShape[3]+";\n        bool hasNextRow = c < "+this.outputShape[2]+";\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - "+o+";\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - "+o+"; j <= "+o+"; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2("+s+"));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * "+a+";\n        setOutput(result);\n      }\n    "},Ua=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideHeight,n=t.strideWidth,r=t.dilationHeight,i=t.effectiveFilterHeight,a=t.effectiveFilterWidth,o=i-1-t.padInfo.top,s=a-1-t.padInfo.left,u=i*a-1;this.userCode="\n      const ivec2 pads = ivec2("+o+", "+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+i+";\n          wR += "+r+") {\n          float dyR = float(dyRCorner + wR) / "+e+".0;\n\n          if (dyR < 0.0 || dyR >= "+t.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+a+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+n+".0;\n\n            if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+u+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+a+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},ja=function(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;var e=t.strideDepth,n=t.strideHeight,r=t.strideWidth,i=t.dilationDepth,a=t.dilationHeight,o=t.dilationWidth,s=t.effectiveFilterDepth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,c=s-1-t.padInfo.front,p=u-1-t.padInfo.top,h=l-1-t.padInfo.left,f=s*u*l-1;this.userCode="\n      const ivec3 pads = ivec3("+c+", "+p+", "+h+");\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < "+s+";\n           wD += "+i+") {\n          float dyD = float(dyDCorner + wD) / "+e+".0;\n\n          if (dyD < 0.0 || dyD >= "+t.outDepth+".0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+a+") {\n            float dyR = float(dyRCorner + wR) / "+n+".0;\n\n            if (dyR < 0.0 || dyR >= "+t.outHeight+".0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < "+l+";\n                wC += "+o+") {\n              float dyC = float(dyCCorner + wC) / "+r+".0;\n\n              if (dyC < 0.0 || dyC >= "+t.outWidth+".0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = "+f+" -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * "+u+" * "+l+" +\n                  wR * "+l+" + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "},Ga=function(t,e,n,r,i,a,o){void 0===n&&(n=!1),void 0===r&&(r=!1),void 0===i&&(i=!1),void 0===a&&(a=null),void 0===o&&(o=!1),this.variableNames=["matrixA","matrixB"],this.usesPackedTextures=!0,this.outputShape=e;var s=n?t[1]:t[2],u=Math.ceil(s/2),l=n?"i * 2, rc.y":"rc.y, i * 2",c=r?"rc.z, i * 2":"i * 2, rc.z",p=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",d="";a&&(f=o?"vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          "+a+"\n        }":"vec4 activation(vec4 x) {\n          "+a+"\n        }",d="result = activation(result);");var m=i?"result += getBiasAtOutCoords();":"";i&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),this.userCode="\n      "+f+"\n\n      const float sharedDimension = "+u+".0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < "+u+"; i++) {\n          vec4 a = getMatrixA(rc.x, "+l+");\n          vec4 b = getMatrixB(rc.x, "+c+");\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += ("+p[0]+" * "+h[0]+");\n          result += ("+p[1]+" * "+h[1]+");\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        "+m+"\n\n        "+d+"\n\n        setOutput(result);\n      }\n    "},Ha=function(){function t(t,e,n){this.variableNames=["probs"],this.outputShape=[t,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(e-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(e-1)+"));\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t){var e=this;return function(n,r){null==e.seedLoc&&(e.seedLoc=n.getUniformLocation(r,"seed")),n.gl.uniform1f(e.seedLoc,t)}},t}(),qa=function(t,e,n,r){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    "},Ka=function(t){this.variableNames=["A"],this.outputShape=t;var e=t.length;if(0===e)this.userCode="\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      ";else{var n=hi("rc",e),r=Ei(e),i=function(t,e,n){if(1===t)return"rc > "+e[0];for(var r="",i=t-2;i<t;i++)r+=n[i]+" >= "+e[i],i<t-1&&(r+="||");return r}(e,t,n),a=function(t,e,n,r){if(1===t)return"";var i=r.slice(-2);return"\n    int r = "+i[0]+";\n    int c = "+i[1]+";\n    int rp1 = r + 1;\n    int cp1 = c + 1;\n\n    bool cEdge = cp1 >= "+e+";\n    bool rEdge = rp1 >= "+n+";\n  "}(e,t[t.length-1],t[t.length-2],n),o=function(t,e){var n=t.length,r=function(t,e){for(var n=[],r=0;r<=1;r++)for(var i=0;i<=1;i++){for(var a=(0===r?"r":"rp1")+", "+(0===i?"c":"cp1"),o=2;o<t;o++)a=e[e.length-1-o]+","+a;n.push(a)}return n}(n,e);return 1===n?"getA(rc),\n            rc + 1 >= "+t[0]+" ? 0. : getA(rc + 1),\n            0, 0":"getA("+r[0]+"),\n          cEdge ? 0. : getA("+r[1]+"),\n          rEdge ? 0. : getA("+r[2]+"),\n          rEdge || cEdge ? 0. : getA("+r[3]+")"}(t,n);this.userCode="\n        void main() {\n          "+r+" rc = getOutputCoords();\n\n          if("+i+") {\n            setOutput(vec4(0));\n          } else {\n            "+a+"\n\n            setOutput(vec4("+o+"));\n          }\n        }\n      "}},$a=function(t,e,n){this.variableNames=["x"],this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});var r=t.length,i=Ei(r),a=e.map(function(t){return t[0]}).join(","),o=e.map(function(e,n){return e[0]+t[n]}).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);this.userCode=1!==r?"\n      "+i+" start = "+i+"("+a+");\n      "+i+" end = "+i+"("+o+");\n\n      void main() {\n        "+i+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+n+"));\n        } else {\n          "+i+" coords = outC - start;\n          setOutput(getX("+s+"));\n        }\n      }\n    ":"\n        int start = "+a+";\n        int end = "+o+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+n+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      "},Xa=function(t,e,n){this.variableNames=["x"],this.usesPackedTextures=!0,this.outputShape=e.map(function(e,n){return e[0]+t[n]+e[1]});for(var r=t.length,i=Ei(r),a=e.map(function(t){return t[0]}).join(","),o=e.map(function(e,n){return e[0]+t[n]}).join(","),s=hi("rc",r),u=hi("source",r),l=s[r-1]+" < "+this.outputShape[r-1],c=1===r?"source":"vec2("+u.slice(-2).join()+")",p=[i+" rc = outputLoc;",s[r-1]+" += 1;\n       if("+l+") {\n      ",1===r?"":"}\n       rc = outputLoc;\n       "+s[r-2]+" += 1;\n       if("+s[r-2]+" < "+this.outputShape[r-2]+") {",1===r?"":"  "+s[r-1]+" += 1;\n         if("+l+") {"],h=1===r?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",f="",d=0,m=1===r?2:4;d<m;d++)f+="\n        "+p[d]+"\n        if ("+h+") {\n          result["+d+"] = float("+n+");\n        } else {\n          "+i+" source = rc - start;\n          result["+d+"] = getChannel(getX("+u.join()+"), "+c+");\n        }\n      ";f+=1===r?"} ":"}}",this.userCode="\n      const "+i+" start = "+i+"("+a+");\n      const "+i+" end = "+i+"("+o+");\n\n      void main() {\n        "+i+" outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        "+f+"\n        setOutput(result);\n      }\n    "},Ya=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,i=t.strideHeight,a=t.strideWidth,o=t.dilationHeight,s=t.dilationWidth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,c=t.padInfo.top,p=t.padInfo.left;this.outputShape=t.outShape;var h="avg"===e,f="0.0";if(h||(f="-1.0 / 1e-20"),n)this.userCode="\n        const ivec2 strides = ivec2("+i+", "+a+");\n        const ivec2 pads = ivec2("+c+", "+p+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+u+";\n              wR += "+o+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+l+";\n                wC += "+s+") {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+t.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+l+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var d=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(d="avgValue / count");var m=4*Math.floor(r/4),g=r%4,v="\n      if ("+h+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+i+", "+a+");\n      const ivec2 pads = ivec2("+c+", "+p+");\n      const float initializationValue = "+f+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+f+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+u+";\n            wR += "+o+") {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+t.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+m+"; wC += 4) {\n            int xC = xCCorner + wC * "+s+";\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              getValue(batch, xR, xC + 3 * "+s+", d)\n            );\n\n            "+v+"\n          }\n\n          int xC = xCCorner + "+m+";\n          if ("+(1===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+v+"\n          } else if ("+(2===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+v+"\n          } else if ("+(3===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + "+s+", d),\n              getValue(batch, xR, xC + 2 * "+s+", d),\n              initializationValue\n            );\n\n            "+v+"\n          }\n        }\n        setOutput("+d+");\n      }\n    "}},Ja=function(t,e,n){if(this.variableNames=["x"],"avg"===e&&n)throw new Error("Cannot compute positions for average pool.");var r=t.filterWidth,i=t.strideDepth,a=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,u=t.dilationHeight,l=t.dilationWidth,c=t.effectiveFilterDepth,p=t.effectiveFilterHeight,h=t.effectiveFilterWidth,f=t.padInfo.front,d=t.padInfo.top,m=t.padInfo.left;this.outputShape=t.outShape;var g="avg"===e,v="0.0";if(g||(v="-1.0 / 1e-20"),n)this.userCode="\n        const ivec3 strides =\n            ivec3("+i+", "+a+", "+o+");\n        const ivec3 pads = ivec3("+f+", "+d+", "+m+");\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < "+c+";\n              wD += "+s+") {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= "+t.inDepth+") {\n              continue;\n            }\n\n            for (int wR = 0; wR < "+p+";\n                wR += "+u+") {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= "+t.inHeight+") {\n                continue;\n              }\n\n              for (int wC = 0; wC < "+h+";\n                  wC += "+l+") {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= "+t.inWidth+") {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value >= currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition =\n                      wD * "+p+" * "+h+" +\n                      wR * "+h+" + wC;;\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var y=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===e&&(y="avgValue / count");var b=4*Math.floor(r/4),x=r%4,w="\n      if ("+g+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec3 strides =\n        ivec3("+i+", "+a+", "+o+");\n      const ivec3 pads = ivec3("+f+", "+d+", "+m+");\n      const float initializationValue = "+v+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= "+t.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+v+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < "+c+";\n            wD += "+s+") {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= "+t.inDepth+") {\n            continue;\n          }\n\n          for (int wR = 0; wR < "+p+";\n            wR += "+u+") {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+t.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+b+"; wC += 4) {\n              int xC = xCCorner + wC * "+l+";\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+l+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+l+", ch),\n                getValue(batch, xD, xR, xC + 3 * "+l+", ch)\n              );\n\n              "+w+"\n            }\n\n            int xC = xCCorner + "+b+";\n            if ("+(1===x)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(2===x)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+l+", ch),\n                initializationValue,\n                initializationValue\n              );\n\n              "+w+"\n            } else if ("+(3===x)+") {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + "+l+", ch),\n                getValue(batch, xD, xR, xC + 2 * "+l+", ch),\n                initializationValue\n              );\n\n              "+w+"\n            }\n          }\n          setOutput("+y+");\n        }\n      }\n    "}},Za=function(t,e){this.variableNames=["x"];var n=t.windowSize,r=t.batchSize,i=t.inSize,a=Math.ceil(i/n);this.outputShape=[r,a];var o="0.0",s="";"prod"===e?o="1.0":"min"===e?(o="1.0 / 1e-20",s="min"):"max"===e&&(o="-1.0 / 1e-20",s="max");var u=e+"("+e+"("+e+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===e?u="sumValue":"prod"===e?u="prodValue":"all"===e?u="allValue":"any"===e&&(u="anyValue");var l=4*Math.floor(n/4),c=n%4,p="\n      if ("+("sum"===e)+") {\n        sumValue += dot(values, ones);\n      } else if ("+("prod"===e)+") {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = "+s+"(values, minMaxValue);\n      }\n    ",h="vec4";"all"===e?(o="1.0",p="\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      ",h="bvec4"):"any"===e&&(o="0.0",p="\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      ",h="bvec4");var f="";i%n>0&&(f="\n        if (inIdx < 0 || inIdx >= "+i+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+o+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+f+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+o+");\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < "+l+"; i += 4) {\n          int inIdx = inOffset + i;\n          "+h+" values = "+h+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+p+"\n        }\n\n        int inIdx = inOffset + "+l+";\n        if ("+(1===c)+") {\n          "+h+" values = "+h+"(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          "+p+"\n        } else if ("+(2===c)+") {\n          "+h+" values = "+h+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          "+p+"\n        } else if ("+(3===c)+") {\n          "+h+" values = "+h+"(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          "+p+"\n        }\n        setOutput("+u+");\n      }\n    "},Qa=function(t,e){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=t;for(var n="",r=0;r<4;r++){var i="thisRC = rc;";r%2==1&&(i+="thisRC.z += 1;"),r>1&&(i+="thisRC.y += 1;"),n+="\n        "+i+"\n        "+(r>0?"if(thisRC.y < rows && thisRC.z < cols){":"")+"\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result["+r+"] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        "+(r>0?"}":"")+"\n      "}this.userCode="\n      \n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      "+di(["r","c","d"],e)+"\n      return ivec3(r, c, d);\n    }\n  \n      "+mi(t)+"\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = "+t[1]+";\n        int cols = "+t[2]+";\n\n        "+n+"\n\n        setOutput(result);\n      }\n    "},to=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,i=r[1],a=r[2],o=t.shape,s=o[1],u=o[2],l=[n&&s>1?i-1:i,n&&u>1?a-1:a],c=[n&&s>1?s-1:s,n&&u>1?u-1:u],p=l[0]/c[0],h=l[1]/c[1],f=1/p,d=1/h,m=2*Math.ceil(f)+2,g=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+p+");\n        const float widthScale = float("+h+");\n\n        const float invHeightScale = float("+f+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+m+");\n        const int winWidth = int("+g+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(i-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(a-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "},eo=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var i=t[0],a=t[1],o=t[2],s=t[3];this.outputShape=[i,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?o-1:o],l=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+o+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    "},no=function(t,e,n,r){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=[];var i=t[0],a=t[1],o=t[2],s=t[3];this.outputShape=[i,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?o-1:o],l=[r&&e>1?e-1:e,r&&n>1?n-1:n];this.userCode="\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+",\n          "+u[1]/l[1]+");\n      const vec3 inputShapeRC = vec3("+a+".0, "+o+".0,\n                                     "+o+".0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = vec3(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(sourceFracIndexRC);\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n        \n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < "+(s-1)+"; \n        bool hasNextRow = coords.z < "+(n-1)+";\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    "},ro=function(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e.shape;var r=e.shape,i=r[1],a=r[2],o=t.shape,s=o[1],u=o[2],l=[n&&s>1?i-1:i,n&&u>1?a-1:a],c=[n&&s>1?s-1:s,n&&u>1?u-1:u],p=l[0]/c[0],h=l[1]/c[1],f=1/p,d=1/h,m=2*Math.ceil(f)+2,g=2*Math.ceil(d)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+p+");\n        const float widthScale = float("+h+");\n\n        const float invHeightScale = float("+f+");\n        const float invWidthScale = float("+d+");\n\n        const int winHeight = int("+m+");\n        const int winWidth = int("+g+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float sourceFracRow =\n              float("+l[0]+") *\n                (float(dyR) / float("+c[0]+"));\n\n            float sourceFracCol =\n                float("+l[1]+") *\n                  (float(dyC) / float("+c[1]+"));\n\n            int sourceNearestRow = int(min(\n                float(int("+i+") - 1),\n                "+n+" ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int("+a+") - 1),\n                "+n+" ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "},io=function(t,e,n,r){this.variableNames=["A"],this.outputShape=[];var i=t[0],a=t[1],o=t[2],s=t[3];this.outputShape=[i,e,n,s];var u=[r&&e>1?a-1:a,r&&n>1?o-1:o],l=[r&&e>1?e-1:e,r&&n>1?n-1:n],c=r?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+o+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+c+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    "},ao=function(t,e){this.variableNames=["x"];var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");if(this.outputShape=t,1!==n){var r=t.map(function(n,r){return function(n){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+" - coords["+n+"] - 1":"coords["+n+"]"}(r)}).join(","),i=Ei(n);this.userCode="\n      void main() {\n        "+i+" coords = getOutputCoords();\n        setOutput(getX("+r+"));\n      }\n    "}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+t[0]+" - coord - 1));\n        }\n      "},oo=function(t,e){this.variableNames=["x"],this.usesPackedTextures=!0;var n=t.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");this.outputShape=t;var r=hi("rc",n),i=r[n-1]+" + 1 < "+this.outputShape[n-1],a=r[n-2]+" + 1 < "+this.outputShape[n-2],o=Ei(n);function s(n){var r=t.map(function(r,i){return function(n,r){return-1!==e.indexOf(n)&&1!==t[n]?t[n]+" - "+r[n]+" - 1":""+r[n]}(i,n)});return"getChannel(getX("+r.join(",")+"), vec2("+r.slice(-2).join(",")+"))"}this.userCode=1===n?"\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX("+t[0]+" - rc - 1),\n            "+t[0]+" - rc - 1);\n          if("+i+"){\n              result.g = getChannel(getX("+t[0]+" - (rc  + 1) - 1),\n                "+t[0]+" - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      ":"\n        void main() {\n          "+o+" rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = "+s(r.slice())+";\n          if("+i+"){\n            result.g = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",s(t)}(r.slice())+";\n          }\n          if("+a+") {\n            result.b = "+function(t){return t[n-2]="("+t[n-2]+" + 1)",s(t)}(r.slice())+";\n            if("+i+") {\n              result.a = "+function(t){return t[n-1]="("+t[n-1]+" + 1)",t[n-2]="("+t[n-2]+" + 1)",s(t)}(r.slice())+";\n            }\n          }\n          setOutput(result);\n        }\n    "},so=function(t,e,n,r,i,a,o){void 0===o&&(o=!0),this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;var s=Ei(i.length),u=Ei(a.length),l="";1===n?l="i":2===n&&(l="i, j");var c="getIndices("+l+")",p="";1===r?p="i":2===r&&(p="i, coords[1]");var h="getUpdates("+p+")",f=e>1?"strides[j]":"strides";this.userCode="\n        "+s+" strides = "+s+"("+i+");\n\n        void main() {\n          "+u+" coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < "+t+"; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < "+e+"; j++) {\n              int index = round("+c+");\n              flattenedIndex += index * "+f+";\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += "+h+";\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      "},uo=function(t,e){this.variableNames=["x","segmentIds"];var n=t.windowSize,r=t.batchSize,i=t.inSize,a=t.numSegments,o=a*Math.ceil(i/n);this.outputShape=[r,o];var s=4*Math.floor(n/4),u=n%4,l="\n        sumValue += dot(values, segFilter);\n    ",c="";i%n>0&&(c="\n        if (inIdx < 0 || inIdx >= "+i+") {\n          return initializationValue;\n        }\n      ");var p="";i%n>0&&(p="\n        if (inIdx < 0 || inIdx >= "+i+") {\n          return -1.0;\n        }\n      "),this.userCode="\n      const float initializationValue = 0.0;\n\n      float getValue(int batch, int inIdx) {\n        "+c+"\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        "+p+"\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          "+a+")) * float("+n+"));\n        int currentSeg = int(mod(float(outIdx), float("+a+")));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+s+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          "+l+"\n        }\n\n        int inIdx = inOffset + "+s+";\n        if ("+(1===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          "+l+"\n        } else if ("+(2===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          "+l+"\n        } else if ("+(3===u)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          "+l+"\n        }\n        setOutput(sumValue);\n      }\n    "},lo=function(t,e,n){var r,i;if(this.variableNames=["c","a","b"],this.outputShape=e,n>4)throw Error("Where for rank "+n+" is not yet supported");if(1===n)i="resRC",r="resRC";else{for(var a=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],s=[],u=0;u<e.length;u++)s.push(""+a[u]),u<t&&o.push(""+a[u]);r=o.join(),i=s.join()}var l=Ei(n);this.userCode="\n      void main() {\n        "+l+" resRC = getOutputCoords();\n        float cVal = getC("+r+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+i+"));\n        } else {\n          setOutput(getB("+i+"));\n        }\n      }\n    "},co=function(){function t(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;var e,n=Ei(this.rank),r="uniform int start["+this.rank+"];",i=function(t){if(1===t)return"sourceLoc";if(t<=6)return po.slice(0,t).map(function(t){return"sourceLoc."+t}).join(",");throw Error("Slicing for rank "+t+" is not yet supported")}(this.rank);e="\n        "+n+" sourceLoc;\n        "+n+" coords = getOutputCoords();\n        "+t.map(function(t,e){return"sourceLoc."+po[e]+" = start["+e+"] + coords."+po[e]+";"}).join("\n")+"\n      ",this.userCode="\n      "+r+"\n      void main() {\n        "+e+"\n        setOutput(getSource("+i+"));\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),po=["x","y","z","w","u","v"],ho=function(){function t(t){this.variableNames=["source"],this.usesPackedTextures=!0,this.outputShape=t,this.rank=t.length;var e=Ei(this.rank),n=hi("coords",this.rank),r=hi("sourceLoc",this.rank),i=1===this.rank?"sourceLoc":"vec2("+r.slice(-2).join()+")",a="getChannel(getSource("+r.join()+"), "+i+")",o="\n      result.x = "+a+";\n      if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n        ++"+r[this.rank-1]+";\n        result.y = "+a+";\n        --"+r[this.rank-1]+";\n      }\n    ",s=1===this.rank?"":"\n      --"+n[this.rank-1]+";\n      if (++"+n[this.rank-2]+" < "+t[this.rank-2]+") {\n        ++"+r[this.rank-2]+";\n        result.z = "+a+";\n        if (++"+n[this.rank-1]+" < "+t[this.rank-1]+") {\n          ++"+r[this.rank-1]+";\n          result.w = "+a+";\n        }\n      }\n    ",u=this.rank<=4?"sourceLoc = coords +\n            "+e+"("+t.map(function(t,e){return"start["+e+"]"}).join()+");":t.map(function(t,e){return r[e]+" = "+n[e]+" + start["+e+"];"}).join("\n");this.userCode="\n      uniform int start["+this.rank+"];\n      void main() {\n        "+e+" coords = getOutputCoords();\n        "+e+" sourceLoc;\n        "+u+" \n        vec4 result = vec4(0.);\n        "+o+"\n        "+s+"\n        setOutput(result);\n      }\n    "}return t.prototype.getCustomSetupFunc=function(t){var e=this;if(t.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+t.length+")");return function(n,r){null==e.startLoc&&(e.startLoc=n.getUniformLocationNoThrow(r,"start"),null==e.startLoc)||n.gl.uniform1iv(e.startLoc,t)}},t}(),fo=function(t,e,n){this.variableNames=["x"],this.outputShape=n;var r=n.length,i=Ei(n.length),a=Ei(n.length),o="";if(1===r)o="coords * strides + begin";else{var s=0;o=n.map(function(t,e){return s++,1===n.length?"coords * strides["+e+"] + begin["+e+"]":"coords["+(s-1)+"] * strides["+e+"] + begin["+e+"]"}).join(",")}this.userCode="\n      "+i+" begin = "+i+"("+t+");\n      "+i+" strides = "+i+"("+e+");\n\n      void main() {\n        "+a+" coords = getOutputCoords();\n        setOutput(getX("+o+"));\n      }\n    "},mo=function(){function t(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}return t.prototype.acquireTexture=function(t,e,n){var r,i=go(e,n),a=vo(t,i,n);if(a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]),this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}return this.numUsedTextures++,this.log(),i===Rt.PACKED_2X2_FLOAT32?r=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):i===Rt.PACKED_2X2_FLOAT16?r=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):i===Rt.UNPACKED_FLOAT32?r=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):i===Rt.UNPACKED_FLOAT16?r=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):i===Rt.PACKED_4X1_UNSIGNED_BYTE&&(r=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[a].push(r),r},t.prototype.releaseTexture=function(t,e,n,r){if(null!=this.freeTextures){var i=vo(e,go(n,r),r);i in this.freeTextures||(this.freeTextures[i]=[]),this.freeTextures[i].push(t),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[i],o=a.indexOf(t);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");a.splice(o,1),this.log()}},t.prototype.log=function(){if(this.logEnabled){var t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+t+")")}},t.prototype.getNumUsedTextures=function(){return this.numUsedTextures},t.prototype.getNumFreeTextures=function(){return this.numFreeTextures},t.prototype.dispose=function(){var t=this;if(null!=this.freeTextures){for(var e in this.freeTextures)this.freeTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e)});for(var e in this.usedTextures)this.usedTextures[e].forEach(function(e){t.gpgpu.deleteMatrixTexture(e)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},t}();function go(e,n){if(e===At.UPLOAD)return Rt.PACKED_2X2_FLOAT32;if(e===At.RENDER||null==e)return function(e){return t.ENV.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Rt.PACKED_2X2_FLOAT32:Rt.UNPACKED_FLOAT32:e?Rt.PACKED_2X2_FLOAT16:Rt.UNPACKED_FLOAT16}(n);if(e===At.DOWNLOAD||e===At.PIXELS)return Rt.PACKED_4X1_UNSIGNED_BYTE;throw new Error("Unknown logical texture type "+e)}function vo(t,e,n){return t[0]+"_"+t[1]+"_"+e+"_"+n}var yo=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[r]*e[r];this.outputShape=n,this.rank=n.length;var i=Ei(this.rank),a=function(t){var e=t.length;if(e>5)throw Error("Tile for rank "+e+" is not yet supported");if(1===e)return"imod(resRC, "+t[0]+")";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[],i=0;i<t.length;i++)r.push("imod("+n[i]+", "+t[i]+")");return r.join()}(t);this.userCode="\n      void main() {\n        "+i+" resRC = getOutputCoords();\n        setOutput(getA("+a+"));\n      }\n    "},bo=function(t,e){this.variableNames=["A"];for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];this.outputShape=n,this.rank=n.length;var i=Ei(this.rank),a=function(t){var e=t.length;if(e>6)throw Error("Transpose for rank "+e+" is not yet supported");for(var n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(e),i=0;i<t.length;i++)r[t[i]]=n[i];return r.join()}(e);this.userCode="\n    void main() {\n      "+i+" resRC = getOutputCoords();\n      setOutput(getA("+a+"));\n    }\n    "},xo=function(t,e){this.variableNames=["A"],this.usesPackedTextures=!0;for(var n=new Array(t.length),r=0;r<n.length;r++)n[r]=t[e[r]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error("Packed transpose for rank "+this.rank+" is not yet supported.");var i=Ei(this.rank),a=pi("rc",this.rank),o=new Array(this.rank);for(r=0;r<e.length;r++)o[e[r]]=a[r];var s="vec2("+o.slice(-2).join()+")",u="++"+a[this.rank-1]+" < "+n[this.rank-1],l="getChannel(getA("+o.join()+"), "+s+")";this.userCode="\n    void main() {\n      "+i+" rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = "+l+";\n      if("+u+") {\n        result[1] = "+l+";\n      }\n      --"+a[this.rank-1]+";\n      if(++"+a[this.rank-2]+" < "+n[this.rank-2]+") {\n        result[2] = "+l+";\n        if("+u+") {\n          result[3] = "+l+";\n        }\n      }  \n      setOutput(result);\n    }\n    "},wo=1.7580993408473768,No=1.0507009873554805,Co=function(t,e){this.variableNames=["A"],this.outputShape=t,this.userCode="\n      float unaryOperation(float x) {\n        "+e+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "},Eo="if (isnan(x)) return x;",So="return x;",ko="return abs(x);",Io=Eo+"\n  return (x < 0.0) ? 0.0 : x;\n",Ao="return (x >= 0.0) ? x : (exp(x) - 1.0);",Ro="return -x;",To="return ceil(x);",Do="return floor(x);",Oo="return exp(x);",_o="return exp(x) - 1.0;",Fo="return x;",Mo="return x;",zo="\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n",Lo="\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n",Po=function(t,e){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=t,this.userCode="\n      vec4 unaryOperation(vec4 x) {\n        "+e+"\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "},Bo=function(t){this.variableNames=["A"],this.usesPackedTextures=!0,this.outputShape=t;var e=t.length,n=hi("rc",e),r=Ei(e),i=function(t,e){if(1===t)return"rc";for(var n="",r=0;r<t;r++)n+=e[r],r<t-1&&(n+=",");return n}(e,n),a=n.slice(-2),o=e<=1?"rc":"vec2("+a.join(",")+")";this.userCode="\n      void main() {\n        "+r+" rc = getOutputCoords();\n        vec4 packedInput = getA("+i+");\n\n        setOutput(getChannel(packedInput, "+o+"));\n      }\n    "},Vo={};function Wo(t,e){if(void 0===e&&(e=!1),"linear"===t)return e?Mo:So;if("relu"===t)return e?zo:Io;if("elu"===t)return e?Lo:Ao;if("prelu"===t)return e?Pi:zi;throw new Error("Activation "+t+" has not been implemented for the WebGL backend.")}var Uo=600,jo=function(){function e(e){if(this.gpgpu=e,this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.warnedAboutMemory=!1,this.disposed=!1,!t.ENV.getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(null==e){var n=_t(t.ENV.getNumber("WEBGL_VERSION"));this.binaryCache=(r=t.ENV.getNumber("WEBGL_VERSION"))in Vo?Vo[r]:(Vo[r]={},Vo[r]),this.gpgpu=new za(n),this.canvas=n.canvas,this.gpgpuCreatedLocally=!0}else this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;var r;this.textureManager=new mo(this.gpgpu),this.numMBBeforeWarning=null==t.ENV.global.screen?1024:t.ENV.global.screen.height*t.ENV.global.screen.width*window.devicePixelRatio*Uo/1024/1024,this.texData=new Dr(this,kt)}return e.prototype.register=function(t,e,n){if(this.texData.has(t))throw new Error("Data buffer is already registered");this.texData.set(t,{shape:e,dtype:n})},e.prototype.fromPixels=function(e,n){if(null==e)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");var r="undefined"!=typeof OffscreenCanvas&&e instanceof OffscreenCanvas||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement,i=e.data instanceof Uint8Array,a="undefined"!=typeof ImageData&&e instanceof ImageData,o="undefined"!=typeof HTMLVideoElement&&e instanceof HTMLVideoElement,s="undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement,u=o?[e.videoWidth,e.videoHeight]:[e.width,e.height],l=u[0],c=u[1],p=[c,l],h=[c,l,n];if(!(r||i||a||o||s))throw new Error("pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was "+e.constructor.name);(s||o)&&(null==this.fromPixels2DContext&&(this.fromPixels2DContext=Ft(t.ENV.getNumber("WEBGL_VERSION")).getContext("2d")),this.fromPixels2DContext.canvas.width=l,this.fromPixels2DContext.canvas.height=c,this.fromPixels2DContext.drawImage(e,0,0,l,c),e=this.fromPixels2DContext.canvas);var f,d,m=this.makeTensorHandle(p,"int32");if(this.texData.get(m.dataId).usage=At.PIXELS,this.gpgpu.uploadPixelDataToTexture(this.getTexture(m.dataId),e),t.ENV.getBool("WEBGL_PACK")){f=new ma(h);var g=this.makePackedTensor(f.outputShape,m.dtype);d=this.compileAndRun(f,[m],g)}else f=new da(h),d=this.compileAndRun(f,[m]);return this.disposeData(m.dataId),d},e.prototype.makeTensorHandle=function(t,e){var n={};return this.register(n,t,e),{dataId:n,shape:t,dtype:e}},e.prototype.write=function(e,n){if(null==n)throw new Error("MathBackendWebGL.write(): values can not be null");if(t.ENV.getBool("DEBUG"))for(var r=0;r<n.length;r++){var i=n[r];if(!Ut(i)){if(t.ENV.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"))throw Error("The value "+i+" cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.ENV.set('WEBGL_RENDER_FLOAT32_ENABLED', true);'");throw Error("The value "+i+" cannot be represented on this device.")}}var a=this.texData.get(e);if("complex64"===a.dtype)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.releaseGPUData(e),a.usage=At.UPLOAD,a.values=n},e.prototype.readSync=function(t){var e=this.texData.get(t),n=e.values,r=e.dtype,i=e.complexTensors,a=e.slice,o=e.shape,s=e.isPacked;if(null!=a){var u;u=s?new Po(o,Fo):new Co(o,Fo);var l=this.compileAndRun(u,[{dataId:t,shape:o,dtype:r}]),c=this.readSync(l.dataId);return l.dispose(),c}if(null!=n)return this.convertAndCacheOnCPU(t);if("string"===r)return n;var p,h,f=null!=this.activeTimers;return f&&(p=q()),h="complex64"===r?Zr(i.real.dataSync(),i.imag.dataSync()):this.getValuesFromTexture(t),f&&(this.downloadWaitMs+=q()-p),this.convertAndCacheOnCPU(t,h)},e.prototype.read=function(e){return r(this,void 0,void 0,function(){var n,r,a,o,s,u,l,c,p,h,f,d,m,g,y,b,x,w,N,C,E,S;return i(this,function(i){switch(i.label){case 0:if(this.pendingRead.has(e))return n=this.pendingRead.get(e),[2,new Promise(function(t){return n.push(t)})];if(r=this.texData.get(e),a=r.values,o=r.shape,s=r.slice,u=r.dtype,l=r.complexTensors,c=r.isPacked,null!=s)return p=void 0,p=c?new Po(o,Fo):new Co(o,Fo),h=this.compileAndRun(p,[{dataId:e,shape:o,dtype:u}]),f=this.read(h.dataId),h.dispose(),[2,f];if(null!=a)return[2,this.convertAndCacheOnCPU(e)];if(!t.ENV.getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&2===t.ENV.getNumber("WEBGL_VERSION"))throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");return d=null,"complex64"!==u&&t.ENV.get("WEBGL_BUFFER_SUPPORTED")&&(m=this.decode(e),g=this.texData.get(m.dataId),d=(S=this.gpgpu).createBufferFromTexture.apply(S,[g.texture].concat(zt(o)))),this.pendingRead.set(e,[]),"complex64"===u?[3,2]:[4,this.gpgpu.createAndWaitForFence()];case 1:i.sent(),i.label=2;case 2:return"complex64"!==u?[3,4]:[4,Promise.all([l.real.data(),l.imag.data()])];case 3:return b=i.sent(),x=b[0],w=b[1],y=Zr(x,w),[3,5];case 4:null==d?y=this.getValuesFromTexture(e):(N=v(o),y=this.gpgpu.downloadFloat32MatrixFromBuffer(d,N)),i.label=5;case 5:return null!=m&&this.disposeData(m.dataId),C=this.convertAndCacheOnCPU(e,y),E=this.pendingRead.get(e),this.pendingRead.delete(e),E.forEach(function(t){return t(C)}),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)),[2,C]}})})},e.prototype.getValuesFromTexture=function(e){var n,r=this,i=this.texData.get(e),a=i.shape,o=i.dtype,s=i.isPacked,u=v(a);if(t.ENV.getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){var l=this.decode(e),c=this.texData.get(l.dataId),p=(n=this.gpgpu).downloadMatrixFromPackedTexture.apply(n,[c.texture].concat(zt(a))).subarray(0,u);return this.disposeData(l.dataId),p}var h=t.ENV.getBool("WEBGL_PACK")&&!0===s,f=h?ve(a):a,d=this.makeTensorHandle(f,"float32");d.size=v(a),this.texData.get(d.dataId).usage=At.DOWNLOAD;var m=_e(function(){var t=h?new la(f):new ua(f);return r.compileAndRun(t,[{shape:f,dtype:o,dataId:e}],d,null)}),g=this.texData.get(m.dataId),y=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(g.texture,g.texShape[0],g.texShape[1]).subarray(0,u);return this.disposeData(d.dataId),y},e.prototype.time=function(t){return r(this,void 0,void 0,function(){var e,n,r,a,o,s,u;return i(this,function(i){switch(i.label){case 0:return e=this.activeTimers,n=[],r=!1,null==this.programTimersStack?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,t(),a=g(this.activeTimers.map(function(t){return t.query})).filter(function(t){return null!=t}),o=g(this.activeTimers.map(function(t){return t.name})).filter(function(t){return null!=t}),this.activeTimers=e,r&&(this.programTimersStack=null),[4,Promise.all(a)];case 1:return s=i.sent(),u={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:h(s),getExtraProfileInfo:function(){return s.map(function(t,e){return{name:o[e],ms:t}}).map(function(t){return t.name+": "+t.ms}).join(", ")},wallMs:null},this.uploadWaitMs=0,this.downloadWaitMs=0,[2,u]}})})},e.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},e.prototype.startTimer=function(){return t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?this.gpgpu.beginQuery():{startMs:q(),endMs:null}},e.prototype.endTimer=function(e){return t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(this.gpgpu.endQuery(),e):(e.endMs=q(),e)},e.prototype.getQueryTime=function(e){return r(this,void 0,void 0,function(){var n;return i(this,function(r){return t.ENV.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?[2,this.gpgpu.waitForQueryAndGetTime(e)]:[2,(n=e).endMs-n.startMs]})})},e.prototype.disposeData=function(t){if(!this.pendingDisposal.has(t))if(this.pendingRead.has(t))this.pendingDisposal.add(t);else if(this.texData.has(t)){this.releaseGPUData(t);var e=this.texData.get(t).complexTensors;null!=e&&(e.real.dispose(),e.imag.dispose()),this.texData.delete(t)}},e.prototype.releaseGPUData=function(t){var e=this.texData.get(t),n=e.texture,r=e.dtype,i=e.texShape,a=e.usage,o=e.isPacked,s=e.slice,u=s&&s.origDataId||t,l=this.dataRefCount.get(u);l>1?this.dataRefCount.set(u,l-1):(this.dataRefCount.delete(u),null!=n&&(this.numBytesInGPU-=this.computeBytes(i,r),this.textureManager.releaseTexture(n,i,a,o)));var c=this.texData.get(t);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null},e.prototype.getTexture=function(t){return this.uploadToGPU(t),this.texData.get(t).texture},e.prototype.getDataInfo=function(t){return this.texData.get(t)},e.prototype.getCPUBackend=function(){return t.ENV.getBool("WEBGL_CPU_FORWARD")?(null==this.cpuBackend&&(this.cpuBackend=kt.findBackend("cpu")),this.cpuBackend):null},e.prototype.shouldExecuteOnCPU=function(t,e){var n=this;return void 0===e&&(e=128),null!=this.getCPUBackend()&&t.every(function(t){return null==n.texData.get(t.dataId).texture&&t.size<e})},e.prototype.getGPGPUContext=function(){return this.gpgpu},e.prototype.complex=function(t,e){var n=this.makeOutputArray(t.shape,"complex64");return this.texData.get(n.dataId).complexTensors={real:kt.keep(t.clone()),imag:kt.keep(e.clone())},n},e.prototype.real=function(t){return this.texData.get(t.dataId).complexTensors.real.clone()},e.prototype.imag=function(t){return this.texData.get(t.dataId).complexTensors.imag.clone()},e.prototype.slice=function(e,n,r){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.slice(e,n,r);if(0===v(r))return nn([],r,e.dtype);var i=this.texData.get(e.dataId).isPacked,a=Er(e.shape,n,r);if(i||!a){var o=t.ENV.getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ho(r):new co(r),s=o.getCustomSetupFunc(n);return this.compileAndRun(o,[e],null,s)}return this.uploadToGPU(e.dataId),this.shallowSlice(e,n,r)},e.prototype.shallowSlice=function(t,e,n){var r=this.texData.get(t.dataId),i=lt.make(n,{},t.dtype,this),a=this.texData.get(i.dataId);Object.assign(a,r),a.shape=n,a.dtype=t.dtype;var o=Sr(e,t.strides);r.slice&&(o+=r.slice.flatOffset),a.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||t.dataId};var s=this.dataRefCount.get(a.slice.origDataId)||1;return this.dataRefCount.set(a.slice.origDataId,s+1),i},e.prototype.stridedSlice=function(t,e,n,r){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.stridedSlice(t,e,n,r);var i=wr(e,n,r);if(i.some(function(t){return 0===t}))return nn([],i);var a=new fo(e,r,i);return this.compileAndRun(a,[t])},e.prototype.reverse=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new oo(e.shape,n):new ao(e.shape,n);return this.compileAndRun(r,[e])},e.prototype.concat=function(e,n){if("complex64"===e[0].dtype){var r=e.map(function(t){return tn(t)}),i=e.map(function(t){return en(t)});return Qe(this.concat(r,n),this.concat(i,n))}if(this.shouldExecuteOnCPU(e))return this.cpuBackend.concat(e,n);if(1===e.length)return e[0];if(e.length>t.ENV.getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){var a=Math.floor(e.length/2),o=this.concat(e.slice(0,a),n),s=this.concat(e.slice(a),n);return this.concat([o,s],n)}if(t.ENV.getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].rank>1){var u=new Gi(e.map(function(t){return t.shape}),n);return this.compileAndRun(u,e)}var l=Je(e.map(function(t){return t.shape}),n),c=e.map(function(t){return t.as2D(-1,v(t.shape.slice(n)))}),p=new ji(c.map(function(t){return t.shape}));return this.compileAndRun(p,c).reshape(l)},e.prototype.neg=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.neg(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Ro,e.dtype);var n=new Co(e.shape,Ro);return this.compileAndRun(n,[e])},e.prototype.batchMatMul=function(t,e,n,r){var i=n?t.shape[2]:t.shape[1],a=r?e.shape[1]:e.shape[2],o=n?t.shape[1]:t.shape[2],s=t.shape[0];if((1===i||1===a)&&o>1e3){n&&(t=t.transpose([0,2,1])),r&&(e=e.transpose([0,2,1]));var u=1===a?t:t.as3D(s,o,1),l=1===a?2:1,c=1===a?e.as3D(s,1,o):e;return this.multiply(u,c).sum(l,!0)}var p=vt(t.dtype,e.dtype),h=new Ga(t.shape,[s,i,a],n,r),f=this.makePackedTensor(h.outputShape,p);return this.compileAndRun(h,[t,e],f)},e.prototype.fusedBatchMatMul=function(t){var e=t.a,n=t.b,r=t.transposeA,i=t.transposeB,a=t.bias,o=t.activation,s=t.preluActivationWeights,u=r?e.shape[2]:e.shape[1],l=i?n.shape[1]:n.shape[2],c=e.shape[0],p=vt(e.dtype,n.dtype),h=null!=a,f=null!=s,d=o?Wo(o,!0):null,m=new Ga(e.shape,[c,u,l],r,i,h,d,f),g=this.makePackedTensor(m.outputShape,p),v=[e,n];return a&&v.push(a),s&&v.push(s),this.compileAndRun(m,v,g)},e.prototype.multiply=function(e,n){if("complex64"===e.dtype){var r=this.texData.get(e.dataId),i=this.texData.get(n.dataId),a=new Oi("return areal * breal - aimag * bimag;",e.shape,n.shape),o=new Oi("return areal * bimag + aimag * breal;",e.shape,n.shape),s=[this.makeComplexComponentTensorHandle(e,r.complexTensors.real),this.makeComplexComponentTensorHandle(e,r.complexTensors.imag),this.makeComplexComponentTensorHandle(n,i.complexTensors.real),this.makeComplexComponentTensorHandle(n,i.complexTensors.imag)],u=this.compileAndRun(a,s),l=this.compileAndRun(o,s),c=this.complex(u,l);return u.dispose(),l.dispose(),c}if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.multiply(e,n);if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,Mi,e.dtype);var p=new Li(Mi,e.shape,n.shape),h=this.makeOutputArray(p.outputShape,e.dtype);return this.compileAndRun(p,[e,n],h)},e.prototype.batchNormalization=function(e,n,r,i,a,o){var s=[e,n,r],u=null;null!=o&&(u=o.shape,s.push(o));var l=null;if(null!=a&&(l=a.shape,s.push(a)),t.ENV.getBool("WEBGL_PACK_NORMALIZATION")){var c=new Di(e.shape,n.shape,r.shape,u,l,i);return this.compileAndRun(c,s)}var p=new Ti(e.shape,n.shape,r.shape,u,l,i);return this.compileAndRun(p,s)},e.prototype.localResponseNormalization4D=function(e,n,r,i,a){var o=t.ENV.getBool("WEBGL_PACK_NORMALIZATION")?new Wa(e.shape,n,r,i,a):new Ba(e.shape,n,r,i,a);return this.compileAndRun(o,[e])},e.prototype.LRNGrad=function(t,e,n,r,i,a,o){var s=new Va(e.shape,r,i,a,o);return this.compileAndRun(s,[e,n,t])},e.prototype.tile=function(t,e){if("string"===t.dtype){var n=this.readSync(t.dataId).map(function(t){return X(t)});return ai(Ln(t.shape,t.dtype,n),e)}var r=new yo(t.shape,e);return this.compileAndRun(r,[t])},e.prototype.pad=function(e,n,r){var i=t.ENV.getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Xa(e.shape,n,r):new $a(e.shape,n,r);return this.compileAndRun(i,[e])},e.prototype.transpose=function(e,n){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.transpose(e,n);var r=t.ENV.getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new xo(e.shape,n):new bo(e.shape,n);return this.compileAndRun(r,[e])},e.prototype.gather=function(t,e,n){if(this.shouldExecuteOnCPU([t,e]))return this.cpuBackend.gather(t,e,n);var r=new ga(t.shape,e.size,n);return this.compileAndRun(r,[t,e])},e.prototype.batchToSpaceND=function(t,e,n){f(t.rank<=4,function(){return"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),i=pr(t.shape,e,r),a=hr(i.length,e.length),o=fr(t.shape,e,r),s=dr(n,e.length),u=mr(o,n,e.length);return t.reshape(i).transpose(a).reshape(o).slice(s,u)},e.prototype.spaceToBatchND=function(t,e,n){f(t.rank<=4,function(){return"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet"});var r=e.reduce(function(t,e){return t*e}),i=[[0,0]];i.push.apply(i,n);for(var a=1+e.length;a<t.shape.length;++a)i.push([0,0]);var o=t.pad(i),s=pr(o.shape,e,r,!1),u=hr(s.length,e.length,!1),l=fr(o.shape,e,r,!1);return o.reshape(s).transpose(u).reshape(l)},e.prototype.reduce=function(t,e,n){var r=t.shape[0],i=t.shape[1],a=yr(i),o=new Za({windowSize:a,inSize:i,batchSize:r},e),s=o.outputShape,u=s[0],l=s[1],c=this.makeOutputArray([u,l],n);return this.compileAndRun(o,[t],c),1===c.shape[1]?c:this.reduce(c,e,n)},e.prototype.argReduce=function(t,e,n){void 0===n&&(n=null);var r=t.shape[0],i=t.shape[1];null!=n&&(r=n.shape[0],i=n.shape[1]);var a=yr(i),o=new ci({windowSize:a,inSize:i,batchSize:r},e,null==n),s=o.outputShape,u=s[0],l=s[1],c=this.makeOutputArray([u,l],"int32"),p=[t];return null!=n&&p.push(n),this.compileAndRun(o,p,c),1===c.shape[1]?c:this.argReduce(t,e,c)},e.prototype.argReducePacked=function(t,e,n){void 0===n&&(n=null);var r=null!=n?n.shape:t.shape,i=yr(r[r.length-1]),a=new Ii(r,i,e,null==n),o=this.makePackedTensor(a.outputShape,"int32"),s=null==n?[t]:[t,n];return this.compileAndRun(a,s,o),o.rank===t.rank?this.argReducePacked(t,e,o):o},e.prototype.sum=function(t,e){qe("sum",e,t.rank);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i),o=yt(t.dtype);return this.reduce(a,"sum",o).reshape(r)},e.prototype.prod=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.prod(t,e);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i),o=yt(t.dtype);return this.reduce(a,"prod",o).reshape(r)},e.prototype.unsortedSegmentSum=function(t,e,n){var r=0,i=Ke([r],t.rank),a=t;null!=i&&(a=t.transpose(i),r=Xe(1,t.rank)[0]);var o=function(t,e,n){for(var r=[],i=t.length,a=0;a<i;a++)a!==e?r.push(t[a]):r.push(n);return r}(a.shape,r,n),s=v([a.shape[r]]),u=a.as2D(-1,s),l=yt(t.dtype),c=this.segOpCompute(u,"unsortedSegmentSum",e,l,n).reshape(o);return null!=i&&(c=c.transpose($e(i))),c},e.prototype.segOpCompute=function(t,e,n,r,i){var a=t.shape[0],o=t.shape[1],s=function(t,e){var n,r=!1;for(t<=vr?(n=t,r=!0):n=V(t,Math.floor(Math.sqrt(t)));!r;)n>e||n===t?r=!0:n=V(t,n+1);return n}(o,i),u=new uo({windowSize:s,inSize:o,batchSize:a,numSegments:i},e),l=u.outputShape,c=l[0],p=l[1],h=this.makeOutputArray([c,p],r);return this.compileAndRun(u,[t,n],h),h.shape[1]===i?h:(n=gn(0,i).tile([o/s]),this.segOpCompute(h,e,n,r,i))},e.prototype.argMinMaxReduce=function(e,n,r){var i=[n];if(qe("arg"+r.charAt(0).toUpperCase()+r.slice(1),i,e.rank),!t.ENV.getBool("WEBGL_PACK_REDUCE")||e.rank<=2){var a=Ge(e.shape,i),o=a[0],s=v(a[1]),u=e.as2D(-1,s);return this.argReduce(u,r).reshape(o)}return this.argReducePacked(e,r)},e.prototype.argMin=function(t,e){return this.argMinMaxReduce(t,e,"min")},e.prototype.argMax=function(t,e){return this.argMinMaxReduce(t,e,"max")},e.prototype.cumsum=function(t,e,n,r){if(e!==t.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(t.rank-1)+" but got axis="+e);var i=new na(t.shape,n,r);return this.compileAndRun(i,[t])},e.prototype.equal=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(equal(a, b));\n","bool");var r=new Li("return float(a == b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.notEqual=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(notEqual(a, b));\n","bool");var r=new Li("return float(a != b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.less=function(e,n){if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.less(e,n);if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(lessThan(a, b));\n","bool");var r=new Li("return float(a < b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.lessEqual=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(lessThanEqual(a, b));\n","bool");var r=new Li("return float(a <= b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.greater=function(e,n){if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.greater(e,n);if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(greaterThan(a, b));\n","bool");var r=new Li("return float(a > b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.greaterEqual=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(greaterThanEqual(a, b));\n","bool");var r=new Li("return float(a >= b);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.logicalNot=function(t){var e=new Co(t.shape,"return float(!(x >= 1.0));");return this.compileAndRun(e,[t])},e.prototype.logicalAnd=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n","bool");var r=new Li("return float(a >= 1.0 && b >= 1.0);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.logicalOr=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n","bool");var r=new Li("return float(a >= 1.0 || b >= 1.0);",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,n],i)},e.prototype.select=function(t,e,n){var r=new lo(t.rank,e.shape,e.rank),i=this.makeOutputArray(r.outputShape,vt(e.dtype,n.dtype));return this.compileAndRun(r,[t,e,n],i)},e.prototype.where=function(t){Le("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");var e=t.dataSync();return si(t.shape,e)},e.prototype.topk=function(t,e,n){return oi(t.dataSync(),t.shape,t.dtype,e)},e.prototype.min=function(t,e){qe("min",e,t.rank);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i);return this.reduce(a,"min",a.dtype).reshape(r)},e.prototype.minimum=function(e,n){if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.minimum(e,n);var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",e.shape,n.shape):new Li("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return min(a, b);\n",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.mod=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",e.shape,n.shape):new Li("if (b == 0.0) return NAN;\n  return mod(a, b);",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.max=function(t,e){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.max(t,e);qe("max",e,t.rank);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i);return this.reduce(a,"max",a.dtype).reshape(r)},e.prototype.maximum=function(e,n){if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.maximum(e,n);var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",e.shape,n.shape):new Li("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return max(a, b);\n",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.all=function(t,e){qe("all",e,t.rank);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i);return this.reduce(a,"all",a.dtype).reshape(r)},e.prototype.any=function(t,e){qe("any",e,t.rank);var n=Ge(t.shape,e),r=n[0],i=v(n[1]),a=t.as2D(-1,i);return this.reduce(a,"any",a.dtype).reshape(r)},e.prototype.squaredDifference=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("return (a - b) * (a - b);",e.shape,n.shape):new Li("return (a - b) * (a - b);",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.realDivide=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(b.x == 0.0) {\n    result.x = NAN;\n  } else if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(b.y == 0.0) {\n    result.y = NAN;\n  } else if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(b.z == 0.0) {\n    result.z = NAN;\n  } else if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(b.w == 0.0) {\n    result.w = NAN;\n  } else if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n","float32",!0);var r=new Li("\nif (b == 0.0) {\n  return NAN;\n}\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"float32");return this.compileAndRun(r,[e,n],i)},e.prototype.floorDiv=function(e,n){if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,"\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n","int32");var r=new Li("\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n",e.shape,n.shape),i=this.makeOutputArray(r.outputShape,"int32");return this.compileAndRun(r,[e,n],i)},e.prototype.add=function(e,n){if("complex64"===e.dtype&&"complex64"===n.dtype)return this.complexSeparableBinaryOp(e,n,_i);if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.add(e,n);var r=vt(e.dtype,n.dtype);if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,_i,r);var i=new Li(_i,e.shape,n.shape),a=this.makeOutputArray(i.outputShape,r);return this.compileAndRun(i,[e,n],a)},e.prototype.packedUnaryOp=function(t,e,n){var r=new Po(t.shape,e),i=this.makePackedTensor(r.outputShape,n);return this.compileAndRun(r,[t],i)},e.prototype.packedBinaryOp=function(t,e,n,r,i){void 0===i&&(i=!1);var a=new Bi(n,t.shape,e.shape,i),o=this.makePackedTensor(a.outputShape,r);return this.compileAndRun(a,[t,e],o)},e.prototype.complexSeparableBinaryOp=function(t,e,n){var r=this,i=this.texData.get(t.dataId),a=this.texData.get(e.dataId),o=[[i.complexTensors.real,a.complexTensors.real],[i.complexTensors.imag,a.complexTensors.imag]].map(function(i){var a=i[0],o=i[1],s=r.makeComplexComponentTensorHandle(t,a),u=r.makeComplexComponentTensorHandle(e,o),l=new Li(n,t.shape,e.shape),c=r.makeOutputArray(l.outputShape,vt(a.dtype,o.dtype));return r.compileAndRun(l,[s,u],c)}),s=o[0],u=o[1],l=this.complex(s,u);return s.dispose(),u.dispose(),l},e.prototype.makeComplexComponentTensorHandle=function(t,e){return{dataId:e.dataId,dtype:e.dtype,shape:t.shape}},e.prototype.addN=function(e){if(1===e.length)return e[0];if(e.length>t.ENV.get("WEBGL_MAX_TEXTURES_IN_SHADER")){var n=Math.floor(e.length/2),r=this.addN(e.slice(0,n)),i=this.addN(e.slice(n));return this.addN([r,i])}var a=e.map(function(t){return t.dtype}).reduce(function(t,e){return vt(t,e)}),o=e.map(function(t){return t.shape}),s=t.ENV.getBool("WEBGL_PACK"),u=s?new li(e[0].shape,o):new ui(e[0].shape,o),l=s?this.makePackedTensor(u.outputShape,a):this.makeOutputArray(u.outputShape,a);return this.compileAndRun(u,e,l)},e.prototype.subtract=function(e,n){if("complex64"===e.dtype&&"complex64"===n.dtype)return this.complexSeparableBinaryOp(e,n,Fi);if(this.shouldExecuteOnCPU([e,n]))return this.cpuBackend.subtract(e,n);var r=vt(e.dtype,n.dtype);if(t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"))return this.packedBinaryOp(e,n,Fi,e.dtype);var i=new Li(Fi,e.shape,n.shape),a=this.makeOutputArray(i.outputShape,r);return this.compileAndRun(i,[e,n],a)},e.prototype.pow=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=r?new Bi("\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",e.shape,n.shape):new Li("\nif(a < 0.0 && floor(b) < b){\n  return NAN;\n}\nif (b == 0.0) {\n  return 1.0;\n}\nreturn (round(mod(b, 2.0)) != 1) ?\n    pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",e.shape,n.shape),a=vt(e.dtype,n.dtype),o=r?this.makePackedTensor(i.outputShape,a):this.makeOutputArray(i.outputShape,a);return this.compileAndRun(i,[e,n],o)},e.prototype.ceil=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.ceil(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,To,e.dtype);var n=new Co(e.shape,To);return this.compileAndRun(n,[e])},e.prototype.floor=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.floor(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Do,e.dtype);var n=new Co(e.shape,Do);return this.compileAndRun(n,[e])},e.prototype.sign=function(t){var e=new Co(t.shape,"\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n");return this.compileAndRun(e,[t])},e.prototype.isNaN=function(t){var e=new Co(t.shape,"return float(isnan(x));"),n=this.makeOutputArray(e.outputShape,"bool");return this.compileAndRun(e,[t],n)},e.prototype.isInf=function(t){var e=new Co(t.shape,"return float(isinf(x));"),n=this.makeOutputArray(e.outputShape,"bool");return this.compileAndRun(e,[t],n)},e.prototype.isFinite=function(t){var e=new Co(t.shape,"return float(!isnan(x) && !isinf(x));"),n=this.makeOutputArray(e.outputShape,"bool");return this.compileAndRun(e,[t],n)},e.prototype.round=function(t){var e=new Co(t.shape,"\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n");return this.compileAndRun(e,[t])},e.prototype.exp=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.exp(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Oo,e.dtype);var n=new Co(e.shape,Oo);return this.compileAndRun(n,[e])},e.prototype.expm1=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.expm1(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,_o,e.dtype);var n=new Co(e.shape,_o);return this.compileAndRun(n,[e])},e.prototype.log=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.log(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,"\n  vec4 result = log(x);\n  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n",e.dtype);var n=new Co(e.shape,"if (x < 0.0) return NAN;\n  return log(x);");return this.compileAndRun(n,[e])},e.prototype.log1p=function(t){var e=new Co(t.shape,"return log(1.0 + x);");return this.compileAndRun(e,[t])},e.prototype.sqrt=function(t){var e=new Co(t.shape,"return sqrt(x);");return this.compileAndRun(e,[t])},e.prototype.rsqrt=function(t){if(this.shouldExecuteOnCPU([t]))return this.cpuBackend.rsqrt(t);var e=new Co(t.shape,"return inversesqrt(x);");return this.compileAndRun(e,[t])},e.prototype.square=function(t){var e=new Co(t.shape,"return x * x;");return this.compileAndRun(e,[t])},e.prototype.reciprocal=function(t){var e=new Co(t.shape,"return 1.0 / x;");return this.compileAndRun(e,[t])},e.prototype.relu=function(e){var n;return n=t.ENV.getBool("WEBGL_PACK")?new Po(e.shape,zo):new Co(e.shape,Io),this.compileAndRun(n,[e])},e.prototype.prelu=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi(Pi,e.shape,n.shape):new Li(zi,e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.elu=function(e){if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Lo,e.dtype);var n=new Co(e.shape,Ao);return this.compileAndRun(n,[e])},e.prototype.eluDer=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n",e.shape,n.shape):new Li("return (b >= 1.0) ? a : a * (b + 1.0);",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.selu=function(t){var e=new Co(t.shape,"\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = 1.7580993408473768;\n  float scale = 1.0507009873554805;\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n");return this.compileAndRun(e,[t])},e.prototype.int=function(t){var e=new Co(t.shape,"return float(int(x));"),n=this.makeOutputArray(e.outputShape,"int32");return this.compileAndRun(e,[t],n)},e.prototype.clip=function(e,n,r){var i,a=(i=t.ENV.getBool("WEBGL_PACK_CLIP")?new Wi(e.shape):new Vi(e.shape)).getCustomSetupFunc(n,r);return this.compileAndRun(i,[e],null,a)},e.prototype.abs=function(e){if(this.shouldExecuteOnCPU([e]))return this.cpuBackend.abs(e);if(t.ENV.getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,ko,e.dtype);var n=new Co(e.shape,ko);return this.compileAndRun(n,[e])},e.prototype.complexAbs=function(t){var e=this.texData.get(t.dataId),n=new Ui(t.shape),r=[this.makeComplexComponentTensorHandle(t,e.complexTensors.real),this.makeComplexComponentTensorHandle(t,e.complexTensors.imag)];return this.compileAndRun(n,r)},e.prototype.sigmoid=function(t){var e=new Co(t.shape,"return 1.0 / (1.0 + exp(-1.0 * x));");return this.compileAndRun(e,[t])},e.prototype.softplus=function(t){var e=new Co(t.shape,"\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n");return this.compileAndRun(e,[t])},e.prototype.sin=function(t){var e=new Co(t.shape,"if (isnan(x)) return x;\n  return sin(x);\n");return this.compileAndRun(e,[t])},e.prototype.cos=function(t){var e=new Co(t.shape,"if (isnan(x)) return x;\n  return cos(x);\n");return this.compileAndRun(e,[t])},e.prototype.tan=function(t){var e=new Co(t.shape,"return tan(x);");return this.compileAndRun(e,[t])},e.prototype.asin=function(t){var e=new Co(t.shape,"return asin(x);");return this.compileAndRun(e,[t])},e.prototype.acos=function(t){var e=new Co(t.shape,"return acos(x);");return this.compileAndRun(e,[t])},e.prototype.atan=function(t){var e=new Co(t.shape,"if (isnan(x)) return x;\n  return atan(x);\n");return this.compileAndRun(e,[t])},e.prototype.atan2=function(e,n){var r=t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Bi("\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  \n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n\n  return result;\n",e.shape,n.shape):new Li("\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n\n  return atan(a, b);\n",e.shape,n.shape);return this.compileAndRun(r,[e,n])},e.prototype.sinh=function(t){var e=new Co(t.shape,"\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},e.prototype.cosh=function(t){var e=new Co(t.shape,"\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n");return this.compileAndRun(e,[t])},e.prototype.tanh=function(t){var e=new Co(t.shape,"\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n");return this.compileAndRun(e,[t])},e.prototype.asinh=function(t){var e=new Co(t.shape,"return log(x + sqrt(x * x + 1.0));");return this.compileAndRun(e,[t])},e.prototype.acosh=function(t){var e=new Co(t.shape,"if (isnan(x)) return x;\n  if (x < 1.0) return NAN;\n  return log(x + sqrt(x * x - 1.0));");return this.compileAndRun(e,[t])},e.prototype.atanh=function(t){var e=new Co(t.shape,"if (isnan(x)) return x;\n  if ((x < -1.0) || (x > 1.0)) return NAN;\n  return (log(1.0 + x) - log(1.0 - x)) / 2.0;");return this.compileAndRun(e,[t])},e.prototype.erf=function(t){var e=new Co(t.shape,'\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = 0.3275911;\n  float a1 = 0.254829592;\n  float a2 = -0.284496736;\n  float a3 = 1.421413741;\n  float a4 = -1.453152027;\n  float a5 = 1.061405429;\n\n  float t = 1.0 / (1.0 + p * x);\n  return 1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x);\n');return this.compileAndRun(e,[t])},e.prototype.step=function(t,e){var n=new Co(t.shape,function(t){return void 0===t&&(t=0),Eo+"\n    return x > 0.0 ? 1.0 : float("+t+");\n  "}(e));return this.compileAndRun(n,[t])},e.prototype.conv2dByMatMul=function(e,n,r,i,a,o){var s=e.shape,u=this.texData.get(e.dataId),l=r.inChannels,c=s[0]*s[1]*s[2],p=r.outChannels,h="channelsLast"===r.dataFormat,d=(1===c||1===p)&&l>1e3,m=s[2]%2!=0&&!!u.isPacked;if(d||!t.ENV.getBool("WEBGL_LAZILY_UNPACK")||!t.ENV.getBool("WEBGL_PACK_BINARY_OPERATIONS")||!m){var g=h?s[0]*s[1]*s[2]:s[0]*s[2]*s[3],v=this.reshape(e,[1,g,r.inChannels]),y=this.reshape(n,[1,r.inChannels,r.outChannels]);return this.reshape(this.fusedBatchMatMul({a:v,b:y,transposeA:!1,transposeB:!1,bias:i,activation:a,preluActivationWeights:o}),r.outShape)}var b=h?s[0]*s[1]*(s[2]+1):s[0]*s[2]*(s[3]+1),x=lt.make([1,b,r.inChannels],{dataId:e.dataId},e.dtype,this),w=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,f(xe(u.shape,x.shape),function(){return"packed reshape "+u.shape+" to "+x.shape+" isn't free"});var N=this.reshape(n,[1,r.inChannels,r.outChannels]),C=this.fusedBatchMatMul({a:x,b:N,transposeA:!1,transposeB:!1,bias:i,activation:a,preluActivationWeights:o}),E=this.texData.get(C.dataId);return f(E.isPacked,function(){return"batchMatMul result is expected to be packed"}),u.shape=w,E.shape=r.outShape,lt.make(r.outShape,{dataId:C.dataId},C.dtype,this)},e.prototype.conv2dWithIm2Row=function(t,e,n,r,i,a){var o=n.filterWidth,s=n.filterHeight,u=n.inChannels,l=n.outWidth,c=n.outHeight,p="channelsLast"===n.dataFormat,h=o*s*u,f=c*l,d=[h,f],m=t.squeeze([0]),g=e.reshape([1,h,-1]),v=new Pa(d,m.shape,n),y=this.compileAndRun(v,[m]).reshape([1,d[0],d[1]]),b=null!=r,x=null!=a,w=i?Wo(i,!0):null,N=new Ga(y.shape,[1,f,n.outChannels],!0,!1,b,w,x),C=[y,g];r&&C.push(r),x&&C.push(a);var E=this.compileAndRun(N,C);return p?E.reshape([1,c,l,n.outChannels]):E.reshape([1,n.outChannels,c,l])},e.prototype.fusedConv2d=function(e,n,r,i,a,o){if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r,i,a,o);if(t.ENV.getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r,i,a,o);var s=null!=i,u=null!=o,l=a?Wo(a,!1):null,c=new Ji(r,s,l,u),p=[e,n];return i&&p.push(i),o&&p.push(o),this.compileAndRun(c,p)},e.prototype.conv2d=function(e,n,r){if(1===r.filterHeight&&1===r.filterWidth&&1===r.dilationHeight&&1===r.dilationWidth&&1===r.strideHeight&&1===r.strideWidth&&("SAME"===r.padInfo.type||"VALID"===r.padInfo.type))return this.conv2dByMatMul(e,n,r);if(t.ENV.getBool("WEBGL_CONV_IM2COL")&&1===e.shape[0])return this.conv2dWithIm2Row(e,n,r);var i=new Ji(r);return this.compileAndRun(i,[e,n])},e.prototype.conv2dDerInput=function(t,e,n){var r=new qi(n);return this.compileAndRun(r,[t,e])},e.prototype.conv2dDerFilter=function(t,e,n){var r=new Hi(n);return this.compileAndRun(r,[t,e])},e.prototype.depthwiseConv2D=function(e,n,r){var i;return t.ENV.getBool("WEBGL_PACK_DEPTHWISECONV")&&r.strideWidth<=2&&r.outChannels/r.inChannels==1?(i=new ta(r),this.compileAndRun(i,[e,n],this.makePackedTensor(r.outShape,e.dtype))):(i=new Qi(r),this.compileAndRun(i,[e,n]))},e.prototype.depthwiseConv2DDerInput=function(t,e,n){var r=new Yi(n);return this.compileAndRun(r,[t,e])},e.prototype.depthwiseConv2DDerFilter=function(t,e,n){var r=new Xi(n);return this.compileAndRun(r,[t,e])},e.prototype.conv3d=function(t,e,n){var r=new Zi(n);return this.compileAndRun(r,[t,e])},e.prototype.conv3dDerInput=function(t,e,n){var r=new $i(n);return this.compileAndRun(r,[t,e])},e.prototype.conv3dDerFilter=function(t,e,n){var r=new Ki(n);return this.compileAndRun(r,[t,e])},e.prototype.maxPool=function(t,e){var n=new Ya(e,"max",!1),r=this.makeOutputArray(n.outputShape,t.dtype);return this.compileAndRun(n,[t],r)},e.prototype.avgPool=function(t,e){var n=new Ya(e,"avg",!1),r=this.makeOutputArray(n.outputShape,"float32");return this.compileAndRun(n,[t],r)},e.prototype.maxPoolBackprop=function(t,e,n,r){var i=new Ya(r,"max",!0),a=this.compileAndRun(i,[e]),o=new Ua(r),s=this.makeOutputArray(o.outputShape,e.dtype),u=this.compileAndRun(o,[t,a],s);return a.dispose(),u},e.prototype.avgPoolBackprop=function(t,e,n){var r=new Ai(n),i=this.makeOutputArray(r.outputShape,e.dtype);return this.compileAndRun(r,[t],i)},e.prototype.cast=function(t,e){return $r(t,e,this)},e.prototype.unstack=function(t,e){for(var n=t.shape[e],r=new Array(t.rank-1),i=0,a=0;a<t.rank;a++)a!==e&&(r[i++]=t.shape[a]);var o=new Array(t.rank).fill(0),s=t.shape.slice();s[e]=1;var u=new Array(n);for(a=0;a<u.length;a++)o[e]=a,u[a]=this.slice(t,o,s).reshape(r);return u},e.prototype.avgPool3d=function(t,e){var n=new Ja(e,"avg",!1),r=this.makeOutputArray(n.outputShape,"float32");return this.compileAndRun(n,[t],r)},e.prototype.avgPool3dBackprop=function(t,e,n){var r=new Ri(n),i=this.makeOutputArray(r.outputShape,e.dtype);return this.compileAndRun(r,[t],i)},e.prototype.maxPool3d=function(t,e){var n=new Ja(e,"max",!1),r=this.makeOutputArray(n.outputShape,"float32");return this.compileAndRun(n,[t],r)},e.prototype.maxPool3dBackprop=function(t,e,n,r){var i=new Ja(r,"max",!0),a=this.compileAndRun(i,[e]),o=new ja(r),s=this.makeOutputArray(o.outputShape,e.dtype),u=this.compileAndRun(o,[t,a],s);return a.dispose(),u},e.prototype.reshape=function(t,e){var n=this.texData.get(t.dataId);return!n.isPacked||xe(t.shape,e)||null!==n.texture&&xe(n.shape,e)?Xr(t,e):this.packedReshape(t,e)},e.prototype.resizeBilinear=function(e,n,r,i){var a=t.ENV.getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new no(e.shape,n,r,i):new eo(e.shape,n,r,i);return this.compileAndRun(a,[e])},e.prototype.resizeBilinearBackprop=function(t,e,n){var r=new to(t,e,n);return this.compileAndRun(r,[t])},e.prototype.resizeNearestNeighbor=function(t,e,n,r){var i=new io(t.shape,e,n,r);return this.compileAndRun(i,[t])},e.prototype.resizeNearestNeighborBackprop=function(t,e,n){var r=new ro(t,e,n);return this.compileAndRun(r,[t])},e.prototype.multinomial=function(t,e,n,r){var i=e?t:Rr(t),a=i.shape[0],o=i.shape[1],s=new Ha(a,o,n),u=this.makeOutputArray(s.outputShape,"int32"),l=s.getCustomSetupFunc(r);return this.compileAndRun(s,[i],u,l)},e.prototype.oneHot=function(t,e,n,r){var i=new qa(t.size,e,n,r);return this.compileAndRun(i,[t])},e.prototype.diag=function(t){var e=new sa(t.size);return this.compileAndRun(e,[t])},e.prototype.nonMaxSuppression=function(t,e,n,r,i){return Le("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead"),ni(t.dataSync(),e.dataSync(),n,r,i)},e.prototype.cropAndResize=function(t,e,n,r,i,a){var o=new ea(t.shape,e.shape,r,i,a);return this.compileAndRun(o,[t,e,n])},e.prototype.depthToSpace=function(t,e,n){f(e>1,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});var r=t.shape[0],i="NHWC"===n?t.shape[1]:t.shape[2],a="NHWC"===n?t.shape[2]:t.shape[3],o="NHWC"===n?t.shape[3]:t.shape[1],s=i*e,u=a*e,l=o/(e*e),c=new oa("NHWC"===n?[r,s,u,l]:[r,l,s,u],e,n);return this.compileAndRun(c,[t])},e.prototype.split=function(t,e,n){return ii(t,e,n)},e.prototype.scatterND=function(t,e,n){var r=br(0,t,n),i=r.sliceRank,a=r.numUpdates,o=r.sliceSize,s=r.strides,u=r.outputSize,l=[u/o,o],c=t.reshape([a,i]),p=e.reshape([a,o]);if(0===u)return Xr(nn([]),n);var h=an(0),f=new so(a,i,c.rank,p.rank,s,l);return this.compileAndRun(f,[p,c,h]).reshape(n)},e.prototype.sparseToDense=function(t,e,n,r){var i=br(0,t,n),a=i.sliceRank,o=i.numUpdates,s=i.strides,u=i.outputSize,l=new so(o,a,t.rank,e.rank,s,[u,1],!1);return this.compileAndRun(l,[e,t,r]).reshape(n)},e.prototype.fft=function(t){return this.fftImpl(t,!1)},e.prototype.ifft=function(t){return this.fftImpl(t,!0)},e.prototype.fftImpl=function(t,e){var n=this.texData.get(t.dataId),r=new ha("return real * expR - imag * expI;",t.shape,e),i=new ha("return real * expI + imag * expR;",t.shape,e),a=[this.makeComplexComponentTensorHandle(t,n.complexTensors.real),this.makeComplexComponentTensorHandle(t,n.complexTensors.imag)],o=this.compileAndRun(r,a),s=this.compileAndRun(i,a),u=this.complex(o,s).as2D(t.shape[0],t.shape[1]);return o.dispose(),s.dispose(),u},e.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],i=gr(t,e),a=i[0],o=i[1],s=i[2],u=i[3],l=e.reshape([o,r]),c=t.reshape([t.size/s,s]),p=new va(r,u,[o,s]);return this.compileAndRun(p,[c,l]).reshape(a)},e.prototype.fill=function(t,e,n){if("string"===(n=n||P(e))){var r=A(n,v(t));return r.fill(e),lt.make(t,{values:r},n)}var i=new fa(t,e),a=i.getCustomSetupFunc(e),o=this.makeOutputArray(t,n);return this.compileAndRun(i,[],o,a)},e.prototype.onesLike=function(t){if("string"===t.dtype)throw new Error("onesLike is not supported under string dtype");return this.fill(t.shape,1,t.dtype)},e.prototype.zerosLike=function(t){return this.fill(t.shape,"string"===t.dtype?"":0,t.dtype)},e.prototype.linspace=function(t,e,n){return Yr(t,e,n)},e.prototype.makeOutputArray=function(t,e){return lt.make(t,{},e,this)},e.prototype.makePackedTensor=function(t,e){var n=lt.make(t,{},e,this);return this.texData.get(n.dataId).isPacked=!0,n},e.prototype.unpackTensor=function(t){var e=new Bo(t.shape);return this.compileAndRun(e,[t],lt.make(e.outputShape,{},t.dtype,this))},e.prototype.packTensor=function(t){var e=new Ka(t.shape);return this.compileAndRun(e,[t],this.makePackedTensor(t.shape,t.dtype),null,!0)},e.prototype.packedReshape=function(t,e){var n=t.reshape([me(t.shape)].concat(ge(t.shape))),r=[me(e)].concat(ge(e)),i=new Qa(r,n.shape);return this.compileAndRun(i,[n]).reshape(e)},e.prototype.decode=function(t){var e,n=this.texData.get(t),r=n.isPacked,i=n.shape,a=n.dtype,o=ve(i),s=zt(i),u=this.makeTensorHandle(i,"float32");return this.texData.get(u.dataId).isPacked=!0,this.texData.get(u.dataId).dtype=a,this.texData.get(u.dataId).texShape=s.map(function(t){return 2*t}),e=r?new aa(o,s):new ia(o,s),this.compileAndRun(e,[{shape:o,dtype:a,dataId:t}],u,null,!0),u},e.prototype.compileAndRun=function(e,n,r,i,a){var o=this;if(void 0===a&&(a=!1),null==r&&(r=e.usesPackedTextures?this.makePackedTensor(e.outputShape,n[0].dtype):this.makeOutputArray(e.outputShape,n[0].dtype)),0===r.size)return this.texData.get(r.dataId).values=I(r.dtype,0),r;var s=n.map(function(n){if("complex64"===n.dtype)throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");var r=o.texData.get(n.dataId);if(null==r.texture){if(!e.usesPackedTextures&&v(n.shape)<=t.ENV.getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:n.shape,texData:null,isUniform:!0,uniformValues:r.values};e.usesPackedTextures&&(r.isPacked=!0,r.shape=n.shape)}else if(!!r.isPacked!=!!e.usesPackedTextures)n=r.isPacked?o.unpackTensor(n):o.packTensor(n),r=o.texData.get(n.dataId);else if(r.isPacked&&!xe(r.shape,n.shape)){var i=n,a=n.shape;n.shape=r.shape,n=o.packedReshape(n,a),r=o.texData.get(n.dataId),i.shape=a}return o.uploadToGPU(n.dataId),{shape:n.shape,texData:r,isUniform:!1}});this.uploadToGPU(r.dataId);var u,l={shape:r.shape,texData:this.texData.get(r.dataId),isUniform:!1},c=function(t,e,n){var r="";s.concat(n).forEach(function(t){var e=null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0,n=t.isUniform?"uniform":t.texData.texShape;r+=t.shape+"_"+n+"_"+e});var i=t.userCode;return t.constructor.name+"_"+r+"_"+i}(e,0,l),p=this.getAndSaveBinary(c,function(){return function(e,n,r,i){var a=n.userCode,o=r.map(function(t,e){var r={logicalShape:t.shape,texShape:t.isUniform?null:t.texData.texShape,isUniform:t.isUniform,isPacked:!t.isUniform&&t.texData.isPacked,flatOffset:null};return null!=t.texData&&null!=t.texData.slice&&t.texData.slice.flatOffset>0&&(r.flatOffset=t.texData.slice.flatOffset),{name:n.variableNames[e],shapeInfo:r}}),s=o.map(function(t){return t.shapeInfo}),u={logicalShape:i.shape,texShape:i.texData.texShape,isUniform:!1,isPacked:i.texData.isPacked,flatOffset:null},l=vi(o,u,a,n.usesPackedTextures),c=e.createProgram(l),p=null,h=e.getUniformLocation(c,"NAN",!1);1===t.ENV.getNumber("WEBGL_VERSION")&&(p=e.getUniformLocation(c,"INFINITY",!1));for(var f={},d=0;d<n.variableNames.length;d++){var m=n.variableNames[d];f[m]=e.getUniformLocation(c,m,!1),f["offset"+m]=e.getUniformLocation(c,"offset"+m,!1)}return{program:n,source:l,webGLProgram:c,uniformLocations:f,inShapeInfos:s,outShapeInfo:u,infLoc:p,nanLoc:h}}(o.gpgpu,e,s,l)}),h=null!=this.activeTimers;return h&&(u=this.startTimer()),function(e,n,r,i,a){La(n.inShapeInfos,r),La([n.outShapeInfo],[i]);var o=i.texData.texture,s=i.texData.texShape;i.texData.isPacked?e.setOutputPackedMatrixTexture(o,s[0],s[1]):e.setOutputMatrixTexture(o,s[0],s[1]),e.setProgram(n.webGLProgram),1===t.ENV.getNumber("WEBGL_VERSION")&&null!==n.infLoc&&e.gl.uniform1f(n.infLoc,1/0),null!==n.nanLoc&&e.gl.uniform1f(n.nanLoc,NaN),r.forEach(function(t,r){var i=n.program.variableNames[r],a=n.uniformLocations[i],o=n.uniformLocations["offset"+i];if(null!=a)if(t.isUniform)if(v(t.shape)<2)e.gl.uniform1f(a,t.uniformValues[0]);else{var s=t.uniformValues;s instanceof Float32Array||(s=new Float32Array(s)),e.gl.uniform1fv(a,s)}else null!=t.texData.slice&&null!=o&&e.gl.uniform1i(o,t.texData.slice.flatOffset),e.setInputMatrixTexture(t.texData.texture,a,r)}),null!=a&&a(e,n.webGLProgram),e.executeProgram()}(this.gpgpu,p,s,l,i),h&&(u=this.endTimer(u),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(u)})),!t.ENV.getBool("WEBGL_LAZILY_UNPACK")&&this.texData.get(r.dataId).isPacked&&!1===a?this.unpackTensor(r):r},e.prototype.getAndSaveBinary=function(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]},e.prototype.getTextureManager=function(){return this.textureManager},e.prototype.dispose=function(){this.disposed||(this.textureManager.dispose(),null!=this.canvas&&null!=this.canvas.remove?this.canvas.remove():this.canvas=null,null!=this.fromPixels2DContext&&this.fromPixels2DContext.canvas.remove&&this.fromPixels2DContext.canvas.remove(),this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)},e.prototype.floatPrecision=function(){var e=this;return null==this.floatPrecisionValue&&(this.floatPrecisionValue=_e(function(){if(!t.ENV.get("WEBGL_RENDER_FLOAT32_ENABLED")){var n=t.ENV.getBool("DEBUG");t.ENV.set("DEBUG",!1);var r=e.abs(an(1e-8)).dataSync()[0];if(t.ENV.set("DEBUG",n),r>0)return 32}return 16})),this.floatPrecisionValue},e.prototype.epsilon=function(){return 32===this.floatPrecision()?1e-7:1e-4},e.prototype.uploadToGPU=function(t){var e,n=this.texData.get(t),r=n.shape,i=n.dtype,a=n.values,o=n.texture,s=n.usage,u=n.isPacked;if(null==o){var l,c=null!=this.activeTimers;c&&(l=q());var p=n.texShape;if(null==p&&(p=ye(r,u),n.texShape=p),null!=a){var h=ve(r),f=void 0,d=p[1],m=p[0],g=a instanceof Uint8Array;u?(d=(e=Lt(p[0],p[1]))[0],m=e[1],f=new pa(h,[m,d],g)):f=new ca(h,[m,d],g);var y=this.makeTensorHandle([m,d],i);this.texData.get(y.dataId).usage=g?At.PIXELS:At.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),d,m,a);var b=this.makeTensorHandle(f.outputShape,y.dtype);b.size=v(f.outputShape),this.texData.get(b.dataId).isPacked=u,this.compileAndRun(f,[y],b);var x=this.texData.get(b.dataId);n.texture=x.texture,n.texShape=x.texShape,n.isPacked=x.isPacked,n.usage=x.usage,this.disposeData(y.dataId),this.texData.delete(b.dataId),n.values=null,c&&(this.uploadWaitMs+=q()-l)}else{var w=this.acquireTexture(p,s,i,u);n.texture=w}}},e.prototype.convertAndCacheOnCPU=function(t,e){var n=this.texData.get(t),r=n.dtype;return this.releaseGPUData(t),null!=e&&(n.values=function(t,e){if("float32"===e||"complex64"===e)return t;if("int32"===e||"bool"===e){for(var n="int32"===e?new Int32Array(t.length):new Uint8Array(t.length),r=0;r<n.length;++r)n[r]=Math.round(t[r]);return n}throw new Error("Unknown dtype "+e)}(e,r)),n.values},e.prototype.acquireTexture=function(t,e,n,r){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>1024*this.numMBBeforeWarning*1024){var 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a=n.indexToLoc(i),o=a.slice();e.forEach(function(e){return o[e]=t.shape[e]-1-o[e]}),n.set.apply(n,[r.get.apply(r,o)].concat(a))},a=0;a<n.size;a++)i(a);return n.toTensor()},e.prototype.concat=function(t,e){var n=this;if("complex64"===t[0].dtype){var r=t.map(function(t){return tn(t)}),i=t.map(function(t){return en(t)});return Qe(this.concat(r,e),this.concat(i,e))}var a=t.map(function(t){var n=v(t.shape.slice(e));return t.as2D(-1,n)}),o=Je(a.map(function(t){return t.shape}),1),s=Ln(o,t[0].dtype).values;if(1===a[0].shape[0]){var u=0;a.forEach(function(t){s.set(n.readSync(t.dataId),u),u+=t.size})}else{var l=0;a.forEach(function(t){for(var e=n.readSync(t.dataId),r=0,i=0;i<t.shape[0];++i)for(var a=i*o[1]+l,u=0;u<t.shape[1];++u)s[a+u]=e[r++];l+=t.shape[1]})}var c=Je(t.map(function(t){return t.shape}),e);return nn(s,c,t[0].dtype)},e.prototype.neg=function(t){return this.assertNotComplex(t,"neg"),this.multiply(an(-1),t)},e.prototype.add=function(t,e){return"complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return{real:t+n,imag:e+r}}):this.broadcastedBinaryOp(t,e,vt(t.dtype,e.dtype),function(t,e){return t+e})},e.prototype.addN=function(t){var e=this;this.assertNotComplex(t,"addN");for(var n=t.map(function(t){return e.readSync(t.dataId)}),r=Ln(t[0].shape,t[0].dtype),i=r.values,a=0;a<t.length;a++)for(var o=n[a],s=0;s<i.length;s++)i[s]+=o[s];return r.toTensor()},e.prototype.subtract=function(t,e){return"complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return{real:t-n,imag:e-r}}):this.broadcastedBinaryOp(t,e,vt(t.dtype,e.dtype),function(t,e){return t-e})},e.prototype.pow=function(t,e){return this.assertNotComplex([t,e],"pow"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return 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a&&(u=this.add(u,a)),o&&(u=xc(this,u,o,s)),u},e.prototype.multiply=function(t,e){return"complex64"===t.dtype||"complex64"===e.dtype?this.broadcastedBinaryComplexOp(t.cast("complex64"),e.cast("complex64"),function(t,e,n,r){return{real:t*n-e*r,imag:t*r+e*n}}):this.broadcastedBinaryOp(t,e,vt(t.dtype,e.dtype),function(t,e){return t*e})},e.prototype.realDivide=function(t,e){return this.assertNotComplex([t,e],"realDivide"),this.broadcastedBinaryOp(t,e,"float32",function(t,e){return t/e})},e.prototype.floorDiv=function(t,e){return this.assertNotComplex([t,e],"floorDiv"),this.broadcastedBinaryOp(t,e,"int32",function(t,e){return Math.floor(t/e)})},e.prototype.sum=function(t,e){this.assertNotComplex(t,"sum"),qe("sum",e,t.rank);for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,vt(t.dtype,"int32")),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=0,h=0;h<o;++h)p+=u[c+h];s[l]=p}return a},e.prototype.prod=function(t,e){this.assertNotComplex(t,"sum");for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,vt(t.dtype,"int32")),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=1,h=0;h<o;++h)p*=u[c+h];s[l]=p}return a},e.prototype.unsortedSegmentSum=function(t,e,n){this.assertNotComplex(t,"unsortedSegmentSum");for(var r=[],i=t.rank-e.rank,a=0;a<i;++a)e=e.expandDims(a+1);for(a=0;a<n;++a){var o=an(a,"int32"),s=hu(o,e).asType("float32").mul(t).sum(0);r.push(s)}return or(r)},e.prototype.argMin=function(t,e){this.assertNotComplex(t,"argMin");var n=[e];qe("argMin",n,t.rank);for(var r=Ge(t.shape,n),i=r[0],a=r[1],o=fn(i,"int32"),s=v(a),u=this.readSync(o.dataId),l=this.readSync(t.dataId),c=0;c<u.length;++c){for(var p=c*s,h=l[p],f=0,d=0;d<s;++d){var m=l[p+d];m<h&&(h=m,f=d)}u[c]=f}return o},e.prototype.argMax=function(t,e){this.assertNotComplex(t,"argMax");var n=[e];qe("argMax",n,t.rank);for(var r=Ge(t.shape,n),i=r[0],a=r[1],o=fn(i,"int32"),s=v(a),u=this.readSync(o.dataId),l=this.readSync(t.dataId),c=0;c<u.length;++c){for(var p=c*s,h=l[p],f=0,d=0;d<s;++d){var m=l[p+d];m>h&&(h=m,f=d)}u[c]=f}return o},e.prototype.cumsum=function(t,e,n,r){if(this.assertNotComplex(t,"cumsum"),e!==t.rank-1)throw new Error("backend.cumsum in CPU expects an inner-most axis="+(t.rank-1)+" but got axis="+e);for(var i=vt(t.dtype,"int32"),a=fn(t.shape,i),o=this.readSync(a.dataId),s=this.readSync(t.dataId),u=t.shape[t.rank-1],l=r?function(t,e){return t+u-e-1}:function(t,e){return t+e},c=0;c<s.length;c+=u)for(var p=0;p<u;p++){var h=l(c,p);if(0===p)o[h]=n?0:s[h];else{var f=l(c,p-1);o[h]=n?s[f]+o[f]:s[h]+o[f]}}return a},e.prototype.equal=function(t,e){return this.assertNotComplex([t,e],"equal"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t===e?1:0})},e.prototype.notEqual=function(t,e){return this.assertNotComplex([t,e],"notEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t!==e?1:0})},e.prototype.less=function(t,e){return this.assertNotComplex([t,e],"less"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<e?1:0})},e.prototype.lessEqual=function(t,e){return this.assertNotComplex([t,e],"lessEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t<=e?1:0})},e.prototype.greater=function(t,e){return this.assertNotComplex([t,e],"greater"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t>e?1:0})},e.prototype.greaterEqual=function(t,e){return this.assertNotComplex([t,e],"greaterEqual"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t>=e?1:0})},e.prototype.logicalNot=function(t){this.assertNotComplex(t,"logicalNot");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)n[r]=e[r]?0:1;return lt.make(t.shape,{values:n},"bool")},e.prototype.logicalAnd=function(t,e){return this.assertNotComplex([t,e],"logicalAnd"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t&&e})},e.prototype.logicalOr=function(t,e){return this.assertNotComplex([t,e],"logicalOr"),this.broadcastedBinaryOp(t,e,"bool",function(t,e){return t||e})},e.prototype.select=function(t,e,n){this.assertNotComplex([t,e,n],"select");for(var r=this.readSync(t.dataId),i=this.readSync(e.dataId),a=this.readSync(n.dataId),o=fn(e.shape,vt(e.dtype,n.dtype)),s=this.readSync(o.dataId),u=0,l=0===t.rank||t.rank>1||1===e.rank?1:e.shape[1],c=0;c<r.length;c++)for(var p=0;p<l;p++)1===r[c]?s[u++]=i[c]:s[u++]=a[c];return o},e.prototype.where=function(t){this.assertNotComplex([t],"where");var e=this.readSync(t.dataId);return si(t.shape,e)},e.prototype.topk=function(t,e,n){return this.assertNotComplex(t,"topk"),oi(this.readSync(t.dataId),t.shape,t.dtype,e)},e.prototype.min=function(t,e){this.assertNotComplex(t,"min"),qe("min",e,t.rank);for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,t.dtype),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=u[c],h=0;h<o;++h){var f=u[c+h];f<p&&(p=f)}s[l]=p}return a},e.prototype.minimum=function(t,e){return this.assertNotComplex([t,e],"minimum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.min(t,e)})},e.prototype.mod=function(t,e){return this.assertNotComplex([t,e],"mod"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t%e;return t<0&&e<0||t>=0&&e>=0?n:(n+e)%e})},e.prototype.max=function(t,e){this.assertNotComplex(t,"max"),qe("max",e,t.rank);for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,t.dtype),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=u[c],h=0;h<o;++h){var f=u[c+h];f>p&&(p=f)}s[l]=p}return a},e.prototype.maximum=function(t,e){return this.assertNotComplex([t,e],"maximum"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.max(t,e)})},e.prototype.all=function(t,e){this.assertNotComplex(t,"all"),qe("all",e,t.rank);for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,t.dtype),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=u[c],h=0;h<o;++h){var f=u[c+h];p=p&&f}s[l]=p}return a},e.prototype.any=function(t,e){this.assertNotComplex(t,"any"),qe("any",e,t.rank);for(var n=Ge(t.shape,e),r=n[0],i=n[1],a=fn(r,t.dtype),o=v(i),s=this.readSync(a.dataId),u=this.readSync(t.dataId),l=0;l<s.length;++l){for(var c=l*o,p=u[c],h=0;h<o;++h){var f=u[c+h];p=p||f}s[l]=p}return a},e.prototype.squaredDifference=function(t,e){return this.assertNotComplex([t,e],"squaredDifference"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){var n=t-e;return n*n})},e.prototype.ceil=function(t){this.assertNotComplex(t,"ceil");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.ceil(e[r]);return lt.make(t.shape,{values:n})},e.prototype.floor=function(t){this.assertNotComplex(t,"floor");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.floor(e[r]);return lt.make(t.shape,{values:n})},e.prototype.sign=function(t){this.assertNotComplex(t,"x");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)e[r]<0?n[r]=-1:e[r]>0?n[r]=1:n[r]=0;return lt.make(t.shape,{values:n})},e.prototype.isNaN=function(t){this.assertNotComplex(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isNaN(e[r])&&(n[r]=1);return lt.make(t.shape,{values:n},"bool")},e.prototype.isInf=function(t){this.assertNotComplex(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Math.abs(e[r])===1/0&&(n[r]=1);return lt.make(t.shape,{values:n},"bool")},e.prototype.isFinite=function(t){this.assertNotComplex(t,"x");for(var e=this.readSync(t.dataId),n=new Uint8Array(e.length),r=0;r<e.length;++r)Number.isFinite(e[r])&&(n[r]=1);return lt.make(t.shape,{values:n},"bool")},e.prototype.round=function(t){this.assertNotComplex(t,"round");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=Math.floor(e[r]);e[r]-i<.5?n[r]=Math.floor(e[r]):e[r]-i>.5?n[r]=Math.ceil(e[r]):n[r]=i%2==0?i:i+1}return lt.make(t.shape,{values:n})},e.prototype.exp=function(t){this.assertNotComplex(t,"exp");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.exp(e[r]);return lt.make(t.shape,{values:n})},e.prototype.expm1=function(t){this.assertNotComplex(t,"expm1");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=Math.expm1(e[r]);return lt.make(t.shape,{values:n})},e.prototype.log=function(t){this.assertNotComplex(t,"log");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=e[r];n[r]=Math.log(i)}return lt.make(t.shape,{values:n})},e.prototype.log1p=function(t){this.assertNotComplex(t,"log1p");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=e[r];n[r]=Math.log1p(i)}return lt.make(t.shape,{values:n})},e.prototype.sqrt=function(t){this.assertNotComplex(t,"sqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=e[r];n[r]=Math.sqrt(i)}return lt.make(t.shape,{values:n})},e.prototype.rsqrt=function(t){this.assertNotComplex(t,"rsqrt");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=e[r];n[r]=1/Math.sqrt(i)}return lt.make(t.shape,{values:n})},e.prototype.square=function(t){this.assertNotComplex(t,"square");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r){var i=e[r];n[r]=i*i}return lt.make(t.shape,{values:n})},e.prototype.reciprocal=function(t){this.assertNotComplex(t,"reciprocal");for(var e=this.readSync(t.dataId),n=new Float32Array(e.length),r=0;r<e.length;++r)n[r]=1/e[r];return lt.make(t.shape,{values:n})},e.prototype.linear=function(t){return t},e.prototype.relu=function(t){this.assertNotComplex(t,"relu");for(var e=fn(t.shape,t.dtype),n=this.readSync(e.dataId),r=this.readSync(t.dataId),i=0;i<r.length;++i)n[i]=Math.max(0,r[i]);return e},e.prototype.prelu=function(t,e){return this.assertNotComplex([t,e],"prelu"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return t<0?e*t:t})},e.prototype.elu=function(t){this.assertNotComplex(t,"elu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var i=n[r];e[r]=i>=0?i:Math.exp(i)-1}return lt.make(t.shape,{values:e})},e.prototype.eluDer=function(t,e){this.assertNotComplex([t,e],"eluDer");for(var n=new Float32Array(e.size),r=this.readSync(e.dataId),i=this.readSync(t.dataId),a=0;a<r.length;++a){var o=r[a];n[a]=o>=1?i[a]:i[a]*(o+1)}return lt.make(e.shape,{values:n})},e.prototype.selu=function(t){this.assertNotComplex(t,"selu");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var i=n[r];e[r]=i>=0?1.0507009873554805*i:1.7580993408473768*(Math.exp(i)-1)}return lt.make(t.shape,{values:e})},e.prototype.clip=function(t,e,n){this.assertNotComplex(t,"clip");for(var r=new Float32Array(t.size),i=this.readSync(t.dataId),a=0;a<i.length;++a){var o=i[a];r[a]=o>n?n:o<e?e:o}return lt.make(t.shape,{values:r})},e.prototype.abs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.abs(n[r]);return lt.make(t.shape,{values:e})},e.prototype.complexAbs=function(t){for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<t.size;++r){var i=n[2*r],a=n[2*r+1];e[r]=Math.hypot(i,a)}return lt.make(t.shape,{values:e})},e.prototype.int=function(t){this.assertNotComplex(t,"int");for(var e=new Int32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=n[r];return lt.make(t.shape,{values:e},"int32")},e.prototype.sigmoid=function(t){this.assertNotComplex(t,"sigmoid");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=1/(1+Math.exp(-n[r]));return lt.make(t.shape,{values:e})},e.prototype.softplus=function(t){this.assertNotComplex(t,"softplus");for(var e=Math.log(1.1920928955078125e-7)+2,n=new Float32Array(t.size),r=this.readSync(t.dataId),i=0;i<r.length;++i){var a,o=r[i]>-e,s=r[i]<e,u=Math.exp(r[i]);a=s?u:o?r[i]:Math.log(1+u),n[i]=a}return lt.make(t.shape,{values:n})},e.prototype.sin=function(t){this.assertNotComplex(t,"sin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sin(n[r]);return lt.make(t.shape,{values:e})},e.prototype.cos=function(t){this.assertNotComplex(t,"cos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cos(n[r]);return lt.make(t.shape,{values:e})},e.prototype.tan=function(t){this.assertNotComplex(t,"tan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.tan(n[r]);return lt.make(t.shape,{values:e})},e.prototype.asin=function(t){this.assertNotComplex(t,"asin");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asin(n[r]);return lt.make(t.shape,{values:e})},e.prototype.acos=function(t){this.assertNotComplex(t,"acos");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acos(n[r]);return lt.make(t.shape,{values:e})},e.prototype.atan=function(t){this.assertNotComplex(t,"atan");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atan(n[r]);return lt.make(t.shape,{values:e})},e.prototype.atan2=function(t,e){return this.assertNotComplex([t,e],"atan2"),this.broadcastedBinaryOp(t,e,t.dtype,function(t,e){return Math.atan2(t,e)})},e.prototype.sinh=function(t){this.assertNotComplex(t,"sinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.sinh(n[r]);return lt.make(t.shape,{values:e})},e.prototype.cosh=function(t){this.assertNotComplex(t,"cosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.cosh(n[r]);return lt.make(t.shape,{values:e})},e.prototype.tanh=function(t){this.assertNotComplex(t,"tanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=x(n[r]);return lt.make(t.shape,{values:e})},e.prototype.asinh=function(t){this.assertNotComplex(t,"asinh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.asinh(n[r]);return lt.make(t.shape,{values:e})},e.prototype.acosh=function(t){this.assertNotComplex(t,"acosh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.acosh(n[r]);return lt.make(t.shape,{values:e})},e.prototype.atanh=function(t){this.assertNotComplex(t,"atanh");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r)e[r]=Math.atanh(n[r]);return lt.make(t.shape,{values:e})},e.prototype.erf=function(t){this.assertNotComplex(t,"erf");for(var e=new Float32Array(t.size),n=this.readSync(t.dataId),r=0;r<n.length;++r){var i=n[r],a=1/(1+.3275911*i);e[r]=1-((((1.061405429*a-1.453152027)*a+1.421413741)*a-.284496736)*a+.254829592)*a*Math.exp(-i*i)}return lt.make(t.shape,{values:e})},e.prototype.step=function(t,e){void 0===e&&(e=0),this.assertNotComplex(t,"step");for(var n=new Float32Array(t.size),r=this.readSync(t.dataId),i=0;i<r.length;++i){var a=r[i];isNaN(a)?n[i]=NaN:n[i]=a>0?1:e}return lt.make(t.shape,{values:n})},e.prototype.fusedConv2d=function(t,e,n,r,i,a){var o=this.conv2d(t,e,n);return r&&(o=this.add(o,r)),i&&(o=xc(this,o,i,a)),o},e.prototype.conv2d=function(t,e,n){this.assertNotComplex([t,e],"conv2d");for(var r=n.filterHeight,i=n.filterWidth,a=n.dilationHeight,o=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,l="channelsLast"===n.dataFormat,c=Ln(n.outShape,t.dtype),p=t.strides[0],h=l?t.strides[1]:t.strides[2],f=l?t.strides[2]:1,d=l?1:t.strides[1],m=c.strides[0],g=l?c.strides[1]:c.strides[2],v=l?c.strides[2]:1,y=l?1:c.strides[1],b=this.readSync(t.dataId),x=this.readSync(e.dataId),w=c.values,N=0;N<n.batchSize;++N)for(var C=N*p,E=N*m,S=0;S<n.outHeight;++S)for(var k=E+S*g,I=S*n.strideHeight-u,A=0;A<r;A++){var R=I+A*a;if(!(R<0||R>=n.inHeight))for(var T=A*e.strides[0],D=C+R*h,O=0;O<n.outWidth;++O)for(var _=k+O*v,F=O*n.strideWidth-s,M=0;M<i;M++){var z=F+M*o;if(!(z<0||z>=n.inWidth))for(var L=D+z*f,P=T+M*e.strides[1],B=0;B<n.inChannels;++B){for(var V=b[L+B*d],W=0;W<n.outChannels;++W)w[_+W*y]+=V*x[P+W];P+=n.outChannels}}}return c.toTensor()},e.prototype.conv3d=function(t,e,n){for(var r=n.filterDepth,i=n.filterHeight,a=n.filterWidth,o=n.dilationDepth,s=n.dilationHeight,u=n.dilationWidth,l=n.padInfo.front,c=n.padInfo.left,p=n.padInfo.top,h=Ln(n.outShape,t.dtype),f=this.readSync(t.dataId),d=this.readSync(e.dataId),m=h.values,g=0;g<n.batchSize;++g)for(var v=g*t.strides[0],y=g*h.strides[0],b=0;b<n.outDepth;++b)for(var x=y+b*h.strides[1],w=b*n.strideDepth-l,N=0;N<r;N++){var C=w+N*o;if(!(C<0||C>=n.inDepth))for(var E=N*e.strides[0],S=v+C*t.strides[1],k=0;k<n.outHeight;++k)for(var I=x+k*h.strides[2],A=k*n.strideHeight-p,R=0;R<i;R++){var T=A+R*s;if(!(T<0||T>=n.inHeight))for(var D=E+R*e.strides[1],O=S+T*t.strides[2],_=0;_<n.outWidth;++_)for(var F=I+_*n.outChannels,M=_*n.strideWidth-c,z=0;z<a;z++){var L=M+z*u;if(!(L<0||L>=n.inWidth))for(var P=D+z*e.strides[2],B=O+L*n.inChannels,V=P,W=0;W<n.inChannels;++W){for(var U=f[B+W],j=0;j<n.outChannels;++j)m[F+j]+=U*d[V+j];V+=n.outChannels}}}}return h.toTensor()},e.prototype.conv2dDerInput=function(t,e,n){this.assertNotComplex([t,e],"conv2dDerInput");for(var r=Ln(n.inShape,"float32"),i=r.values,a=this.readSync(t.dataId),o=this.readSync(e.dataId),s=e.strides,u=s[0],l=s[1],c=s[2],p=n.batchSize,h=n.filterHeight,f=n.filterWidth,d=n.inChannels,m=n.inHeight,g=n.inWidth,v=n.outChannels,y=n.outHeight,b=n.outWidth,x=n.strideHeight,w=n.strideWidth,N=n.dataFormat,C=h-1-n.padInfo.top,E=f-1-n.padInfo.left,S="channelsLast"===N,k=r.strides[0],I=S?r.strides[1]:r.strides[2],A=S?r.strides[2]:1,R=S?1:r.strides[1],T=t.strides[0],D=S?t.strides[1]:t.strides[2],O=S?t.strides[2]:1,_=S?1:t.strides[1],F=0;F<p;++F)for(var M=0;M<d;++M)for(var z=0;z<m;++z)for(var L=z-C,P=Math.max(0,Math.ceil(L/x)),B=Math.min(y,(h+L)/x),V=0;V<g;++V){for(var W=V-E,U=Math.max(0,Math.ceil(W/w)),j=Math.min(b,(f+W)/w),G=0,H=P;H<B;++H)for(var q=H*x-L,K=U;K<j;++K)for(var $=T*F+D*H+O*K,X=u*(h-1-q)+l*(f-1-(K*w-W))+c*M,Y=0;Y<v;++Y)G+=a[$+_*Y]*o[X+Y];i[k*F+I*z+A*V+R*M]=G}return r.toTensor()},e.prototype.conv3dDerInput=function(t,e,n){for(var r=Ln(n.inShape,"float32"),i=r.values,a=r.strides,o=a[0],s=a[1],u=a[2],l=a[3],c=this.readSync(t.dataId),p=t.strides,h=p[0],f=p[1],d=p[2],m=p[3],g=this.readSync(e.dataId),v=e.strides,y=v[0],b=v[1],x=v[2],w=v[3],N=n.batchSize,C=n.filterDepth,E=n.filterHeight,S=n.filterWidth,k=n.inChannels,I=n.inDepth,A=n.inHeight,R=n.inWidth,T=n.outChannels,D=n.outDepth,O=n.outHeight,_=n.outWidth,F=n.strideDepth,M=n.strideHeight,z=n.strideWidth,L=C-1-n.padInfo.front,P=E-1-n.padInfo.top,B=S-1-n.padInfo.left,V=0;V<N;++V)for(var W=0;W<k;++W)for(var U=0;U<I;++U)for(var j=U-L,G=Math.max(0,Math.ceil(j/F)),H=Math.min(D,(C+j)/F),q=0;q<A;++q)for(var K=q-P,$=Math.max(0,Math.ceil(K/M)),X=Math.min(O,(E+K)/M),Y=0;Y<R;++Y){for(var J=Y-B,Z=Math.max(0,Math.ceil(J/z)),Q=Math.min(_,(S+J)/z),tt=0,et=G;et<H;++et)for(var nt=et*F-j,rt=$;rt<X;++rt)for(var it=rt*M-K,at=Z;at<Q;++at)for(var ot=h*V+f*et+d*rt+m*at,st=y*(C-1-nt)+b*(E-1-it)+x*(S-1-(at*z-J))+w*W,ut=0;ut<T;++ut)tt+=c[ot+ut]*g[st+ut];i[o*V+s*U+u*q+l*Y+W]=tt}return r.toTensor()},e.prototype.conv2dDerFilter=function(t,e,n){this.assertNotComplex([t,e],"conv2dDerFilter");for(var r=n.strideHeight,i=n.strideWidth,a=n.filterHeight,o=n.filterWidth,s="channelsLast"===n.dataFormat,u=Ln(n.filterShape,"float32"),l=n.padInfo.left,c=n.padInfo.top,p=this.bufferSync(t),h=this.bufferSync(e),f=0;f<a;++f)for(var d=Math.max(0,Math.ceil((c-f)/r)),m=Math.min(n.outHeight,(n.inHeight+c-f)/r),g=0;g<o;++g)for(var v=Math.max(0,Math.ceil((l-g)/i)),y=Math.min(n.outWidth,(n.inWidth+l-g)/i),b=0;b<n.inChannels;++b)for(var x=0;x<n.outChannels;++x){for(var w=0,N=0;N<n.batchSize;++N)for(var C=d;C<m;++C)for(var E=f+C*r-c,S=v;S<y;++S){var k=g+S*i-l;w+=s?p.get(N,E,k,b)*h.get(N,C,S,x):p.get(N,b,E,k)*h.get(N,x,C,S)}u.set(w,f,g,b,x)}return u.toTensor()},e.prototype.conv3dDerFilter=function(t,e,n){for(var r=n.strideDepth,i=n.strideHeight,a=n.strideWidth,o=n.filterDepth,s=n.filterHeight,u=n.filterWidth,l=Ln(n.filterShape,"float32"),c=l.values,p=l.strides,h=p[0],f=p[1],d=p[2],m=p[3],g=this.readSync(e.dataId),v=e.strides,y=v[0],b=v[1],x=v[2],w=v[3],N=this.readSync(t.dataId),C=t.strides,E=C[0],S=C[1],k=C[2],I=C[3],A=n.padInfo.front,R=n.padInfo.left,T=n.padInfo.top,D=0;D<o;++D)for(var O=Math.max(0,Math.ceil((A-D)/r)),_=Math.min(n.outDepth,(n.inDepth+A-D)/r),F=D*h,M=0;M<s;++M)for(var z=Math.max(0,Math.ceil((T-M)/i)),L=Math.min(n.outHeight,(n.inHeight+T-M)/i),P=M*f+F,B=0;B<u;++B)for(var V=Math.max(0,Math.ceil((R-B)/a)),W=Math.min(n.outWidth,(n.inWidth+R-B)/a),U=B*d+P,j=0;j<n.inChannels;++j)for(var G=j*m+U,H=0;H<n.outChannels;++H){for(var q=0,K=0;K<n.batchSize;++K)for(var $=K*E,X=K*y,Y=O;Y<_;++Y)for(var J=(D+Y*r-A)*S+$,Z=Y*b+X,Q=z;Q<L;++Q)for(var tt=(M+Q*i-T)*k+J,et=Q*x+Z,nt=V;nt<W;++nt){var rt=nt*w+et;q+=N[(B+nt*a-R)*I+tt+j]*g[rt+H]}c[G+H]=q}return l.toTensor()},e.prototype.depthwiseConv2D=function(t,e,n){this.assertNotComplex([t,e],"depthwiseConv2D");for(var r=n.filterHeight,i=n.filterWidth,a=n.dilationHeight,o=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,l=n.outChannels/n.inChannels,c=Ln(n.outShape,t.dtype),p=this.readSync(t.dataId),h=this.readSync(e.dataId),f=c.values,d=0;d<n.batchSize;++d)for(var m=d*t.strides[0],g=d*c.strides[0],v=0;v<n.outHeight;++v)for(var y=g+v*c.strides[1],b=v*n.strideHeight-s,x=0;x<r;++x){var w=b+x*a;if(!(w<0||w>=n.inHeight))for(var N=x*e.strides[0],C=m+w*t.strides[1],E=0;E<n.outWidth;++E)for(var S=y+E*c.strides[2],k=E*n.strideWidth-u,I=0;I<i;++I){var A=k+I*o;if(!(A<0||A>=n.inWidth))for(var R=N+I*e.strides[1],T=C+A*n.inChannels,D=S,O=R,_=0;_<n.inChannels;++_){for(var F=p[T+_],M=0;M<l;++M)f[D+M]+=F*h[O+M];D+=l,O+=l}}}return c.toTensor()},e.prototype.depthwiseConv2DDerInput=function(t,e,n){this.assertNotComplex([t,e],"depthwiseConv2DDerInput");for(var r=Ln(n.inShape,"float32"),i=r.values,a=r.strides,o=a[0],s=a[1],u=a[2],l=this.readSync(t.dataId),c=t.strides,p=c[0],h=c[1],f=c[2],d=this.readSync(e.dataId),m=e.strides,g=m[0],v=m[1],y=m[2],b=n.batchSize,x=n.filterHeight,w=n.filterWidth,N=n.inChannels,C=n.inHeight,E=n.inWidth,S=n.outChannels,k=n.outHeight,I=n.outWidth,A=n.strideHeight,R=n.strideWidth,T=x-1-n.padInfo.top,D=w-1-n.padInfo.left,O=S/N,_=0;_<b;++_)for(var F=0;F<N;++F)for(var M=0;M<C;++M)for(var z=M-T,L=Math.max(0,Math.ceil(z/A)),P=Math.min(k,(x+z)/A),B=0;B<E;++B){for(var V=B-D,W=Math.max(0,Math.ceil(V/R)),U=Math.min(I,(w+V)/R),j=0,G=L;G<P;++G)for(var H=G*A-z,q=W;q<U;++q)for(var K=p*_+h*G+f*q,$=g*(x-1-H)+v*(w-1-(q*R-V))+y*F,X=0;X<O;++X)j+=l[K+(F*O+X)]*d[$+X];i[o*_+s*M+u*B+F]=j}return r.toTensor()},e.prototype.depthwiseConv2DDerFilter=function(t,e,n){this.assertNotComplex([t,e],"depthwiseConv2DDerFilter");for(var r=n.strideHeight,i=n.strideWidth,a=n.filterHeight,o=n.filterWidth,s=Ln(n.filterShape,"float32"),u=n.padInfo.left,l=n.padInfo.top,c=n.outChannels/n.inChannels,p=this.bufferSync(t),h=this.bufferSync(e),f=0;f<a;++f)for(var d=Math.max(0,Math.ceil((l-f)/r)),m=Math.min(n.outHeight,(n.inHeight+l-f)/r),g=0;g<o;++g)for(var v=Math.max(0,Math.ceil((u-g)/i)),y=Math.min(n.outWidth,(n.inWidth+u-g)/i),b=0;b<n.outChannels;++b){for(var x=Math.trunc(b/c),w=b%c,N=0,C=0;C<n.batchSize;++C)for(var E=d;E<m;++E)for(var S=f+E*r-l,k=v;k<y;++k){var I=g+k*i-u;N+=p.get(C,S,I,x)*h.get(C,E,k,b)}s.set(N,f,g,x,w)}return s.toTensor()},e.prototype.tile=function(t,e){return this.assertNotComplex(t,"tile"),ai(this.bufferSync(t),e)},e.prototype.pad=function(t,e,n){this.assertNotComplex(t,"pad");var r=e.map(function(e,n){return e[0]+t.shape[n]+e[1]}),i=e.map(function(t){return t[0]}),a=this.bufferSync(t),o=Ln(r,t.dtype);0!==n&&o.values.fill(n);for(var s=0;s<t.size;s++){var u=a.indexToLoc(s),l=u.map(function(t,e){return t+i[e]});o.set.apply(o,[a.get.apply(a,u)].concat(l))}return o.toTensor()},e.prototype.transpose=function(t,e){this.assertNotComplex(t,"transpose");for(var n=new Array(t.rank),r=0;r<n.length;r++)n[r]=t.shape[e[r]];var i=this.readSync(t.dataId),a=Ln(n,t.dtype),o=this.bufferSync(t);for(r=0;r<t.size;++r){for(var s=o.indexToLoc(r),u=new Array(s.length),l=0;l<u.length;l++)u[l]=s[e[l]];var c=a.locToIndex(u);a.values[c]=i[r]}return a.toTensor()},e.prototype.gather=function(t,e,n){this.assertNotComplex([t,e],"gather");var r=t.shape.slice(),i=this.readSync(e.dataId);r[n]=i.length;for(var a=Ln(r,t.dtype),o=this.bufferSync(t),s=0;s<a.size;++s){var u=a.indexToLoc(s),l=u.slice();l[n]=i[u[n]];var c=o.locToIndex(l);a.values[s]=o.values[c]}return a.toTensor()},e.prototype.batchToSpaceND=function(t,e,n){this.assertNotComplex([t],"batchToSpaceND");var r=e.reduce(function(t,e){return t*e}),i=pr(t.shape,e,r),a=hr(i.length,e.length),o=fr(t.shape,e,r),s=dr(n,e.length),u=mr(o,n,e.length);return t.reshape(i).transpose(a).reshape(o).slice(s,u)},e.prototype.spaceToBatchND=function(t,e,n){this.assertNotComplex([t],"spaceToBatchND");var r=e.reduce(function(t,e){return t*e}),i=[[0,0]];i.push.apply(i,n);for(var a=1+e.length;a<t.shape.length;++a)i.push([0,0]);var o=t.pad(i),s=pr(o.shape,e,r,!1),u=hr(s.length,e.length,!1),l=fr(o.shape,e,r,!1);return o.reshape(s).transpose(u).reshape(l)},e.prototype.pool=function(t,e,n){this.assertNotComplex(t,"pool");for(var r=e.strideHeight,i=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,l=e.padInfo.top,c=e.padInfo.left,p="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,h=this.readSync(t.dataId),f=Ln(e.outShape,t.dtype),d=f.values,m=e.outShape[1]*e.outShape[2]*e.outShape[3],g=e.outShape[2]*e.outShape[3],v=e.outShape[3],y=0;y<e.batchSize;++y)for(var b=y*m,x=y*t.strides[0],w=0;w<e.inChannels;++w)for(var N=0;N<e.outHeight;++N)for(var C=N*r-l,E=Math.max(0,C),S=Math.min(e.inHeight,s+C),k=b+N*g,I=0;I<e.outWidth;++I){for(var A=I*i-c,R=Math.max(0,A),T=Math.min(e.inWidth,u+A),D=p,O=0,_=0,F=E;F<S;F+=a){for(var M=x+F*t.strides[1],z=R;z<T;z+=o){var L=h[M+z*t.strides[2]+w];"max"===n&&L>D?D=L:"avg"===n&&(O+=L,_++)}if(isNaN(D))break}d[k+I*v+w]="avg"===n?O/_:D}return f.toTensor()},e.prototype.maxPool=function(t,e){return this.pool(t,e,"max")},e.prototype.maxPoolPositions=function(t,e){for(var n=Ln(e.outShape,"int32"),r=e.strideHeight,i=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,s=e.effectiveFilterHeight,u=e.effectiveFilterWidth,l=e.padInfo.top,c=e.padInfo.left,p=this.bufferSync(t),h=0;h<e.batchSize;++h)for(var f=0;f<e.inChannels;++f)for(var d=0;d<e.outHeight;++d){for(var m=d*r-l,g=m;g<0;)g+=a;for(var v=Math.min(e.inHeight,s+m),y=0;y<e.outWidth;++y){for(var b=y*i-c,x=b;x<0;)x+=o;for(var w=Math.min(e.inWidth,u+b),N=Number.NEGATIVE_INFINITY,C=-1,E=g;E<v;E+=a)for(var S=E-m,k=x;k<w;k+=o){var I=k-b,A=p.get(h,E,k,f);A>N&&(N=A,C=S*u+I)}n.set(C,h,d,y,f)}}return n.toTensor()},e.prototype.maxPoolBackprop=function(t,e,n,r){this.assertNotComplex([e,n],"maxPoolBackprop");for(var i=this.maxPoolPositions(e,r),a=r.strideHeight,o=r.strideWidth,s=r.dilationHeight,u=r.dilationWidth,l=r.effectiveFilterHeight,c=r.effectiveFilterWidth,p=c-1-r.padInfo.left,h=l-1-r.padInfo.top,f=Ln(e.shape,"float32"),d=this.bufferSync(i),m=this.bufferSync(t),g=0;g<r.batchSize;++g)for(var v=0;v<r.inChannels;++v)for(var y=0;y<r.inHeight;++y)for(var b=0;b<r.inWidth;++b){for(var x=y-h,w=b-p,N=0,C=0;C<l;C+=s){var E=(x+C)/a;if(!(E<0||E>=r.outHeight||Math.floor(E)!==E))for(var S=0;S<c;S+=u){var k=(w+S)/o;if(!(k<0||k>=r.outWidth||Math.floor(k)!==k)){var I=l*c-1-d.get(g,E,k,v)===C*c+S?1:0;0!==I&&(N+=m.get(g,E,k,v)*I)}}}f.set(N,g,y,b,v)}return f.toTensor()},e.prototype.avgPoolBackprop=function(t,e,n){this.assertNotComplex([t,e],"avgPoolBackprop");for(var r=n.strideHeight,i=n.strideWidth,a=n.filterHeight,o=n.filterWidth,s=n.dilationHeight,u=n.dilationWidth,l=n.effectiveFilterHeight,c=n.effectiveFilterWidth,p=c-1-n.padInfo.left,h=l-1-n.padInfo.top,f=Ln(e.shape,"float32"),d=1/(a*o),m=this.bufferSync(t),g=0;g<n.batchSize;++g)for(var v=0;v<n.inChannels;++v)for(var y=0;y<n.inHeight;++y)for(var b=0;b<n.inWidth;++b){for(var x=y-h,w=b-p,N=0,C=0;C<l;C+=s){var E=(x+C)/r;if(!(E<0||E>=n.outHeight||Math.floor(E)!==E))for(var S=0;S<c;S+=u){var k=(w+S)/i;k<0||k>=n.outWidth||Math.floor(k)!==k||(N+=m.get(g,E,k,v))}}f.set(N*d,g,y,b,v)}return f.toTensor()},e.prototype.pool3d=function(t,e,n){this.assertNotComplex(t,"pool3d");for(var r=e.strideDepth,i=e.strideHeight,a=e.strideWidth,o=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,l=e.effectiveFilterDepth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,h=e.padInfo.front,f=e.padInfo.top,d=e.padInfo.left,m="max"===n?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,g=this.readSync(t.dataId),v=Ln(e.outShape,t.dtype),y=v.values,b=e.outShape[1]*e.outShape[2]*e.outShape[3]*e.outShape[4],x=e.outShape[2]*e.outShape[3]*e.outShape[4],w=e.outShape[3]*e.outShape[4],N=e.outShape[4],C=0;C<e.batchSize;++C)for(var E=C*b,S=C*t.strides[0],k=0;k<e.inChannels;++k)for(var I=0;I<e.outDepth;++I){for(var A=I*r-h,R=A;R<0;)R+=o;for(var T=Math.min(e.inDepth,l+A),D=E+I*x,O=0;O<e.outHeight;++O){for(var _=O*i-f,F=_;F<0;)F+=s;for(var M=Math.min(e.inHeight,c+_),z=D+O*w,L=0;L<e.outWidth;++L){for(var P=L*a-d,B=P;B<0;)B+=u;for(var V=Math.min(e.inWidth,p+P),W=z+L*N,U=m,j=0,G=0,H=R;H<T;H+=o){for(var q=S+H*t.strides[1],K=F;K<M;K+=s){for(var $=q+K*t.strides[2],X=B;X<V;X+=u){var Y=g[$+X*t.strides[3]+k];if("max"===n&&Y>U?U=Y:"avg"===n&&(j+=Y,G++),isNaN(U))break}if(isNaN(U))break}if(isNaN(U))break}y[W+k]="avg"===n?j/G:U}}}return v.toTensor()},e.prototype.avgPool3d=function(t,e){return this.assertNotComplex(t,"avgPool3d"),this.pool3d(t,e,"avg").toFloat()},e.prototype.avgPool3dBackprop=function(t,e,n){this.assertNotComplex([t,e],"avgPool3dBackprop");for(var r=n.strideDepth,i=n.strideHeight,a=n.strideWidth,o=n.filterDepth,s=n.filterHeight,u=n.filterWidth,l=n.dilationDepth,c=n.dilationHeight,p=n.dilationWidth,h=n.effectiveFilterDepth,f=n.effectiveFilterHeight,d=n.effectiveFilterWidth,m=h-1-n.padInfo.front,g=d-1-n.padInfo.left,v=f-1-n.padInfo.top,y=Ln(e.shape,"float32"),b=1/(o*s*u),x=this.bufferSync(t),w=0;w<n.batchSize;++w)for(var N=0;N<n.inChannels;++N)for(var C=0;C<n.inDepth;++C)for(var E=0;E<n.inHeight;++E)for(var S=0;S<n.inWidth;++S){for(var k=C-m,I=E-v,A=S-g,R=0,T=0;T<h;T+=l){var D=(k+T)/r;if(!(D<0||D>=n.outDepth||Math.floor(D)!==D))for(var O=0;O<f;O+=c){var _=(I+O)/i;if(!(_<0||_>=n.outHeight||Math.floor(_)!==_))for(var F=0;F<d;F+=p){var M=(A+F)/a;M<0||M>=n.outWidth||Math.floor(M)!==M||(R+=x.get(w,D,_,M,N))}}}y.set(R*b,w,C,E,S,N)}return y.toTensor()},e.prototype.maxPool3d=function(t,e){return this.assertNotComplex(t,"maxPool3d"),this.pool3d(t,e,"max").toFloat()},e.prototype.maxPool3dPositions=function(t,e){for(var n=Ln(e.outShape,"int32"),r=e.strideDepth,i=e.strideHeight,a=e.strideWidth,o=e.dilationDepth,s=e.dilationHeight,u=e.dilationWidth,l=e.effectiveFilterDepth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,h=e.padInfo.front,f=e.padInfo.top,d=e.padInfo.left,m=this.bufferSync(t),g=0;g<e.batchSize;++g)for(var v=0;v<e.inChannels;++v)for(var y=0;y<e.outDepth;++y){for(var b=y*r-h,x=b;x<0;)x+=o;for(var w=Math.min(e.inDepth,l+b),N=0;N<e.outHeight;++N){for(var C=N*i-f,E=C;E<0;)E+=s;for(var S=Math.min(e.inHeight,c+C),k=0;k<e.outWidth;++k){for(var I=k*a-d,A=I;A<0;)A+=u;for(var R=Math.min(e.inWidth,p+I),T=Number.NEGATIVE_INFINITY,D=-1,O=x;O<w;O+=o)for(var _=O-b,F=E;F<S;F+=s)for(var M=F-C,z=A;z<R;z+=u){var L=z-I,P=m.get(g,O,F,z,v);P>=T&&(T=P,D=_*c*p+M*c+L)}n.set(D,g,y,N,k,v)}}}return n.toTensor()},e.prototype.maxPool3dBackprop=function(t,e,n,r){this.assertNotComplex([e,n],"maxPool3dBackprop");for(var i=this.maxPool3dPositions(e,r),a=r.strideDepth,o=r.strideHeight,s=r.strideWidth,u=r.dilationDepth,l=r.dilationHeight,c=r.dilationWidth,p=r.effectiveFilterDepth,h=r.effectiveFilterHeight,f=r.effectiveFilterWidth,d=p-1-r.padInfo.front,m=f-1-r.padInfo.left,g=h-1-r.padInfo.top,v=Ln(e.shape,"float32"),y=this.bufferSync(i),b=this.bufferSync(t),x=0;x<r.batchSize;++x)for(var w=0;w<r.inChannels;++w)for(var N=0;N<r.inDepth;++N)for(var C=0;C<r.inHeight;++C)for(var E=0;E<r.inWidth;++E){for(var S=N-d,k=C-g,I=E-m,A=0,R=0;R<p;R+=u){var T=(S+R)/a;if(!(T<0||T>=r.outDepth||Math.floor(T)!==T))for(var D=0;D<h;D+=l){var O=(k+D)/o;if(!(O<0||O>=r.outHeight||Math.floor(O)!==O))for(var _=0;_<f;_+=c){var F=(I+_)/s;if(!(F<0||F>=r.outWidth||Math.floor(F)!==F)){var M=p*h*f-1-y.get(x,T,O,F,w)===R*h*f+D*f+_?1:0;0!==M&&(A+=b.get(x,T,O,F,w)*M)}}}}v.set(A,x,N,C,E,w)}return v.toTensor()},e.prototype.cast=function(t,e){return $r(t,e,this)},e.prototype.reshape=function(t,e){return Xr(t,e)},e.prototype.avgPool=function(t,e){return this.assertNotComplex(t,"avgPool"),this.pool(t,e,"avg").toFloat()},e.prototype.resizeBilinear=function(t,e,n,r){this.assertNotComplex(t,"resizeBilinear");for(var i=t.shape,a=i[0],o=i[1],s=i[2],u=i[3],l=this.readSync(t.dataId),c=new Float32Array(v([a,e,n,u])),p=[r&&e>1?o-1:o,r&&n>1?s-1:s],h=[r&&e>1?e-1:e,r&&n>1?n-1:n],f=0,d=p[0]/h[0],m=p[1]/h[1],g=0;g<a;g++)for(var y=0;y<e;y++)for(var b=d*y,x=Math.floor(b),w=b-x,N=Math.min(o-1,Math.ceil(b)),C=g*t.strides[0]+x*t.strides[1],E=g*t.strides[0]+N*t.strides[1],S=0;S<n;S++)for(var k=m*S,I=Math.floor(k),A=k-I,R=Math.min(s-1,Math.ceil(k)),T=C+I*t.strides[2],D=E+I*t.strides[2],O=C+ +R*t.strides[2],_=E+R*t.strides[2],F=0;F<u;F++){var M=l[T+F],z=l[D+F],L=M+(l[O+F]-M)*A,P=L+(z+(l[_+F]-z)*A-L)*w;c[f++]=P}return nn(c,[a,e,n,u])},e.prototype.resizeBilinearBackprop=function(t,e,n){this.assertNotComplex([t,e],"resizeBilinearBackprop");for(var r=e.shape,i=r[0],a=r[1],o=r[2],s=r[3],u=t.shape,l=u[1],c=u[2],p=new Float32Array(i*a*o*s),h=[n&&l>1?a-1:a,n&&c>1?o-1:o],f=[n&&l>1?l-1:l,n&&c>1?c-1:c],d=h[0]/f[0],m=h[1]/f[1],g=this.readSync(t.dataId),v=0,y=0;y<i;y++)for(var b=y*e.strides[0],x=0;x<l;x++)for(var w=x*d,N=Math.floor(w),C=Math.min(Math.ceil(w),a-1),E=b+N*e.strides[1],S=b+C*e.strides[1],k=w-N,I=1-k,A=0;A<c;A++)for(var R=A*m,T=Math.floor(R),D=Math.min(Math.ceil(R),o-1),O=R-T,_=1-O,F=E+T*e.strides[2],M=E+D*e.strides[2],z=S+T*e.strides[2],L=S+D*e.strides[2],P=I*_,B=I*O,V=k*_,W=k*O,U=0;U<s;U++){var j=g[v++];p[F+U]+=j*P,p[M+U]+=j*B,p[z+U]+=j*V,p[L+U]+=j*W}return ln(p,[i,o,a,s],e.dtype)},e.prototype.resizeNearestNeighbor=function(t,e,n,r){this.assertNotComplex(t,"resizeNearestNeighbor");for(var i=t.shape,a=i[0],o=i[1],s=i[2],u=i[3],l=this.readSync(t.dataId),c=new Float32Array(a*e*n*u),p=[r&&e>1?o-1:o,r&&n>1?s-1:s],h=[r&&e>1?e-1:e,r&&n>1?n-1:n],f=p[0]/h[0],d=p[1]/h[1],m=0,g=0;g<a;g++)for(var v=g*t.strides[0],y=0;y<e;y++)for(var b=f*y,x=v+Math.min(o-1,r?Math.round(b):Math.floor(b))*t.strides[1],w=0;w<n;w++)for(var N=d*w,C=x+Math.min(s-1,r?Math.round(N):Math.floor(N))*t.strides[2],E=0;E<u;E++){var S=l[C+E];c[m++]=S}return nn(c,[a,e,n,u],t.dtype)},e.prototype.resizeNearestNeighborBackprop=function(t,e,n){this.assertNotComplex([t,e],"resizeNearestNeighborBackprop");for(var r=e.shape,i=r[0],a=r[1],o=r[2],s=r[3],u=t.shape,l=u[1],c=u[2],p=new Float32Array(i*a*o*s),h=this.readSync(t.dataId),f=[n&&l>1?a-1:a,n&&c>1?o-1:o],d=[n&&l>1?l-1:l,n&&c>1?c-1:c],m=f[0]/d[0],g=f[1]/d[1],v=1/m,y=1/g,b=2*Math.ceil(v)+2,x=2*Math.ceil(y)+2,w=0;w<i;w++)for(var N=w*e.strides[0],C=0;C<a;C++)for(var E=N+C*e.strides[1],S=Math.floor(C*v),k=Math.floor(S-b/2),I=0;I<o;I++)for(var A=E+I*e.strides[2],R=Math.floor(I*y),T=Math.floor(R-x/2),D=0;D<s;D++){for(var O=0,_=0;_<b;_++){var F=_+k;if(!(F<0||F>=l)){var M=N+F*t.strides[1],z=F*m;if(C===Math.min(a-1,n?Math.round(z):Math.floor(z)))for(var L=0;L<x;L++){var P=L+T;if(!(P<0||P>=c)){var B=M+P*t.strides[2],V=P*g;I===Math.min(o-1,n?Math.round(V):Math.floor(V))&&(O+=h[B+D])}}}}p[A+D]=O}return ln(p,e.shape,e.dtype)},e.prototype.batchNormalization=function(t,e,n,r,i,a){this.assertNotComplex([t,e,n,i,a],"batchNorm");for(var o=this.readSync(t.dataId),s=this.readSync(e.dataId),u=this.readSync(n.dataId),l=i?this.readSync(i.dataId):new Float32Array([1]),c=a?this.readSync(a.dataId):new Float32Array([0]),p=new Float32Array(o.length),h=c.length,f=l.length,d=u.length,m=s.length,g=0,v=0,y=0,b=0,x=0;x<o.length;++x)p[x]=c[g++]+(o[x]-s[v++])*l[y++]/Math.sqrt(u[b++]+r),g>=h&&(g=0),v>=m&&(v=0),y>=f&&(y=0),b>=d&&(b=0);return ln(p,t.shape)},e.prototype.localResponseNormalization4D=function(t,e,n,r,i){this.assertNotComplex(t,"localResponseNormalization4D");var a=t.shape[3],o=a-1,s=this.readSync(t.dataId),u=t.size,l=new Float32Array(u);function c(t){for(var n=t%a,r=t-n+Math.max(0,n-e),i=t-n+Math.min(n+e,o),u=0;r<=i;r++){var l=s[r];u+=l*l}return u}for(var p=0;p<u;p++){var h=c(p),f=s[p]*Math.pow(n+r*h,-i);l[p]=f}return ln(l,t.shape)},e.prototype.LRNGrad=function(t,e,n,r,i,a,o){this.assertNotComplex(t,"LRNGrad");for(var s=t.shape[3],u=this.readSync(t.dataId),l=this.readSync(e.dataId),c=this.readSync(n.dataId),p=new Float32Array(t.size),h=t.size,f=0;f<h;f++){for(var d=f%s,m=f-d+Math.max(0,d-r),g=f-d+Math.min(s,d+r+1),v=0,y=m;y<g;y++)v+=Math.pow(l[y],2);for(v=a*v+i,y=m;y<g;y++){var b=-2*a*o*l[y]*c[f]/v;f===y&&(b+=Math.pow(v,-o)),b*=u[f],p[y]+=b}}return ln(p,t.shape)},e.prototype.multinomial=function(t,e,n,r){this.assertNotComplex(t,"multinomial");for(var i=e?t:Rr(t),a=i.shape[0],o=i.shape[1],s=fn([a,n],"int32"),u=this.readSync(s.dataId),l=this.readSync(i.dataId),c=0;c<a;++c){var p=c*o,h=new Float32Array(o-1);h[0]=l[p];for(var f=1;f<h.length;++f)h[f]=h[f-1]+l[p+f];for(var d=_n(r.toString()),m=c*n,g=0;g<n;++g){var v=d();u[m+g]=h.length;for(var y=0;y<h.length;y++)if(v<h[y]){u[m+g]=y;break}}}return s},e.prototype.oneHot=function(t,e,n,r){this.assertNotComplex(t,"oneHot");var i=new Float32Array(t.size*e);i.fill(r);for(var a=this.readSync(t.dataId),o=0;o<t.size;++o)a[o]>=0&&a[o]<e&&(i[o*e+a[o]]=n);return sn(i,[t.size,e],"int32")},e.prototype.nonMaxSuppression=function(t,e,n,r,i){return this.assertNotComplex(t,"nonMaxSuppression"),ni(this.readSync(t.dataId),this.readSync(e.dataId),n,r,i)},e.prototype.fft=function(t){return this.fftBatch(t,!1)},e.prototype.ifft=function(t){return this.fftBatch(t,!0)},e.prototype.fftBatch=function(t,e){for(var n=t.shape[0],r=t.shape[1],i=Ln(t.shape,"float32"),a=Ln(t.shape,"float32"),o=tn(t).as2D(n,r),s=en(t).as2D(n,r),u=0;u<n;u++)for(var l=o.slice([u,0],[1,r]),c=s.slice([u,0],[1,r]),p=Qe(l,c),h=this.readSync(this.fftImpl(p,e).dataId),f=0;f<r;f++){var d=Qr(h,f);i.values[u*r+f]=d.real,a.values[u*r+f]=d.imag}return Qe(i.toTensor(),a.toTensor()).as2D(n,r)},e.prototype.fftImpl=function(t,e){var n=t.as1D(),r=n.size;if(this.isExponentOf2(r)){var i=this.fftRadix2(n,r,e).as2D(t.shape[0],t.shape[1]);return e&&(i=Qe(tn(i).div(an(r)),en(i).div(an(r)))),i}var a=this.readSync(t.dataId),o=function(t){for(var e=new Float32Array(t.length/2),n=new Float32Array(t.length/2),r=0;r<t.length;r+=2)e[r/2]=t[r],n[r/2]=t[r+1];return{real:e,imag:n}}(this.fourierTransformByMatmul(a,r,e));return Qe(o.real,o.imag).as2D(t.shape[0],t.shape[1])},e.prototype.isExponentOf2=function(t){return 0==(t&t-1)},e.prototype.fftRadix2=function(t,e,n){if(1===e)return t;var r=this.readSync(t.dataId),i=e/2,a=function(t){for(var e=Math.ceil(t.length/4),n=new Float32Array(e),r=new Float32Array(e),i=0;i<t.length;i+=4)n[Math.floor(i/4)]=t[i],r[Math.floor(i/4)]=t[i+1];return{real:n,imag:r}}(r),o=Qe(a.real,a.imag).as1D(),s=function(t){for(var e=Math.floor(t.length/4),n=new Float32Array(e),r=new Float32Array(e),i=2;i<t.length;i+=4)n[Math.floor(i/4)]=t[i],r[Math.floor(i/4)]=t[i+1];return{real:n,imag:r}}(r),u=Qe(s.real,s.imag).as1D();o=this.fftRadix2(o,i,n),u=this.fftRadix2(u,i,n);var l=function(t,e){for(var n=new Float32Array(t/2),r=new Float32Array(t/2),i=0;i<Math.ceil(t/2);i++){var a=(e?2:-2)*Math.PI*(i/t);n[i]=Math.cos(a),r[i]=Math.sin(a)}return{real:n,imag:r}}(e,n),c=Qe(l.real,l.imag).mul(u),p=o.add(c),h=o.sub(c),f=tn(p).concat(tn(h)),d=en(p).concat(en(h));return Qe(f,d).as1D()},e.prototype.fourierTransformByMatmul=function(t,e,n){for(var r=new Float32Array(2*e),i=0;i<e;i++){for(var a=0,o=0,s=0;s<e;s++){var u=ei(i*s,e,n),l=Qr(t,s);a+=l.real*u.real-l.imag*u.imag,o+=l.real*u.imag+l.imag*u.real}n&&(a/=e,o/=e),ti(r,a,o,i)}return r},e.prototype.depthToSpace=function(t,e,n){f("NHWC"===n,function(){return"Only NHWC dataFormat supported on CPU for depthToSpace. Got "+n}),f(e>1,function(){return"blockSize should be > 1 for depthToSpace, but was: "+e});for(var r=t.shape[0],i=t.shape[1],a=t.shape[2],o=t.shape[3],s=i*e,u=a*e,l=o/(e*e),c=this.readSync(t.dataId),p=new Float32Array(r*s*u*l),h=0,d=0;d<r;++d)for(var m=0;m<s;++m)for(var g=Math.floor(m/e),v=m%e,y=0;y<u;++y)for(var b=Math.floor(y/e),x=(v*e+y%e)*l,w=0;w<l;++w){var N=w+x+o*(b+a*(g+i*d));p[h++]=c[N]}return ln(p,[r,s,u,l])},e.prototype.broadcastedBinaryOp=function(t,e,n,r){var i=Mr(t.shape,e.shape),a=Ln(i,n),o=this.readSync(t.dataId),s=this.readSync(e.dataId),u=_r(t.shape,i),l=_r(e.shape,i),c=a.values;if(u.length+l.length===0)for(var p=0;p<c.length;++p)c[p]=r(o[p%o.length],s[p%s.length]);else{var h=this.bufferSync(t),f=this.bufferSync(e),d=function(n){var i=a.indexToLoc(n),p=i.slice(-t.rank);u.forEach(function(t){return p[t]=0});var d=h.locToIndex(p),m=i.slice(-e.rank);l.forEach(function(t){return m[t]=0});var g=f.locToIndex(m);c[n]=r(o[d],s[g])};for(p=0;p<c.length;++p)d(p)}return a.toTensor()},e.prototype.broadcastedBinaryComplexOp=function(t,e,n){var r=Mr(t.shape,e.shape),i=Ln(r,"float32"),a=Ln(r,"float32"),o=this.readSync(t.dataId),s=this.readSync(e.dataId),u=_r(t.shape,r),l=_r(e.shape,r),c=i.values,p=a.values;if(u.length+l.length===0)for(var h=0;h<c.length;h++){var f=h%o.length,d=h%s.length,m=n(o[2*f],o[2*f+1],s[2*d],s[2*d+1]);c[h]=m.real,p[h]=m.imag}else{var g=this.bufferSync(this.data.get(t.dataId).complexTensors.real),v=this.bufferSync(this.data.get(e.dataId).complexTensors.real),y=function(r){var a=i.indexToLoc(r),h=a.slice(-t.rank);u.forEach(function(t){return h[t]=0});var f=g.locToIndex(h),d=a.slice(-e.rank);l.forEach(function(t){return d[t]=0});var m=v.locToIndex(d),y=n(o[2*f],o[2*f+1],s[2*m],s[2*m+1]);c[r]=y.real,p[r]=y.imag};for(h=0;h<c.length;h++)y(h)}return this.complex(i.toTensor(),a.toTensor())},e.prototype.split=function(t,e,n){return ii(t,e,n)},e.prototype.dispose=function(){},e.prototype.floatPrecision=function(){return 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V=v[_=O+L*y[2]+F*y[1]+k*y[0]],W=v[_=O+P*y[2]+F*y[1]+k*y[0]],U=v[_=O+L*y[2]+M*y[1]+k*y[0]],j=V+(W-V)*B,G=U+(v[_=O+P*y[2]+M*y[1]+k*y[0]]-U)*B;_=O+D*b[2]+R*b[1]+x*b[0],d.values[_]=j+(G-j)*z}}}else for(D=0;D<f;++D){var H;if((H=f>1?C*(l-1)+D*A:.5*(C+S)*(l-1))<0||H>l-1)for(O=0;O<c;O++)_=O+D*b[2]+R*b[1]+x*b[0],d.values[_]=a;else{var q=Math.round(H),K=Math.round(T);for(O=0;O<c;O++){var $=O+q*y[2]+K*y[1]+k*y[0],X=O+D*b[2]+R*b[1]+x*b[0];d.values[X]=v[$]}}}}}return d.toTensor()},e.prototype.sparseToDense=function(t,e,n,r){var i=br(0,t,n),a=i.sliceRank,o=i.numUpdates,s=i.sliceSize,u=i.strides,l=i.outputSize;return this.scatter(t,e,n,l,s,o,a,u,r,!1)},e.prototype.gatherND=function(t,e){var n=e.shape,r=n[n.length-1],i=gr(t,e),a=i[0],o=i[1],s=i[2],u=i[3];if(0===o)return nn([],a,t.dtype);for(var l=new at([o,s],t.dtype),c=this.readSync(e.dataId),p=this.readSync(t.dataId),h=0;h<o;h++){for(var f=[],d=0,m=0;m<r;m++){var g=c[h*r+m];d+=g*u[m],f.push(g)}if(d<0||d>=t.size/s)throw new Error("Invalid indices: 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y=p[d*o+v];m.push(y),g+=y*s[v]}if(g<0||g>=r/i)throw new Error("Invalid indices: "+m+" does not index into "+n);for(var b=0;b<i;b++)l?f.values[g*i+b]+=h[d*i+b]:f.values[g*i+b]=0===e.rank?h[0]:h[d*i+b]}return f.toTensor().reshape(n)},e}();kt.registerBackend("cpu",function(){return new wc},1);var Nc=function(){function t(){this.textEncoder=new TextEncoder}return t.prototype.fetch=function(t,e){return fetch(t,e)},t.prototype.now=function(){return performance.now()},t.prototype.encode=function(t,e){if("utf-8"!==e&&"utf8"!==e)throw new Error("Browser's encoder only supports utf-8, but got "+e);return this.textEncoder.encode(t)},t.prototype.decode=function(t,e){return new TextDecoder(e).decode(t)},t}();t.ENV.get("IS_BROWSER")&&t.ENV.setPlatform("browser",new Nc);var Cc,Ec=function(){function e(){this.util=require("util"),this.textEncoder=new this.util.TextEncoder}return e.prototype.fetch=function(e,n){return null!=t.ENV.global.fetch?t.ENV.global.fetch(e,n):(null==Cc&&(Cc=require("node-fetch")),Cc(e,n))},e.prototype.now=function(){var t=process.hrtime();return 1e3*t[0]+t[1]/1e6},e.prototype.encode=function(t,e){if("utf-8"!==e&&"utf8"!==e)throw new Error("Node built-in encoder only supports utf-8, but got "+e);return this.textEncoder.encode(t)},e.prototype.decode=function(t,e){return 0===t.length?"":new this.util.TextDecoder(e).decode(t)},e}();t.ENV.get("IS_NODE")&&t.ENV.setPlatform("node",new Ec);var Sc={float32:4,int32:4,uint16:2,uint8:1,bool:1},kc=4;function Ic(t,e){for(var n={},r=0,i=function(e){var i=e.name,a=e.dtype,o=e.shape,s=v(o),u=void 0;if("quantization"in e){var l=e.quantization;if("uint8"!==l.dtype&&"uint16"!==l.dtype)throw new Error("Weight "+e.name+" has unknown quantization dtype "+l.dtype+". Supported quantization dtypes are: 'uint8' and 'uint16'.");var c=Sc[l.dtype],p=t.slice(r,r+s*c),h="uint8"===l.dtype?new Uint8Array(p):new Uint16Array(p);if("float32"===a)u=Float32Array.from(h,function(t){return t*l.scale+l.min});else{if("int32"!==a)throw new Error("Unsupported dtype in weight '"+i+"': "+a);u=Int32Array.from(h,function(t){return Math.round(t*l.scale+l.min)})}r+=s*c}else if("string"===a){var f=v(e.shape);u=[];for(var d=0;d<f;d++){var m=new Uint32Array(t.slice(r,r+kc))[0];r+=kc;var g=new Uint8Array(t.slice(r,r+m));u.push(g),r+=m}}else{var y=Sc[a];if(p=t.slice(r,r+s*y),"float32"===a)u=new Float32Array(p);else if("int32"===a)u=new Int32Array(p);else{if("bool"!==a)throw new Error("Unsupported dtype in weight '"+i+"': "+a);u=new Uint8Array(p)}r+=s*y}n[i]=nn(u,o,a)},a=0,o=e;a<o.length;a++)i(o[a]);return n}var Ac="undefined"!=typeof Buffer&&("undefined"==typeof Blob||"undefined"==typeof atob||"undefined"==typeof btoa);function Rc(t){return Ac?Buffer.byteLength(t):new Blob([t]).size}function Tc(t){var e=0;t.forEach(function(t){e+=t.byteLength});var n=new Uint8Array(e),r=0;return t.forEach(function(t){n.set(new Uint8Array(t),r),r+=t.byteLength}),n.buffer}function Dc(t){for(t=t.trim();t.endsWith("/");)t=t.slice(0,t.length-1);var e=t.split("/");return e[e.length-1]}function Oc(t){if(t.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:null==t.modelTopology?0:Rc(JSON.stringify(t.modelTopology)),weightSpecsBytes:null==t.weightSpecs?0:Rc(JSON.stringify(t.weightSpecs)),weightDataBytes:null==t.weightData?0:t.weightData.byteLength}}var _c=function(){function t(){this.saveRouters=[],this.loadRouters=[]}return t.getInstance=function(){return null==t.instance&&(t.instance=new t),t.instance},t.registerSaveRouter=function(e){t.getInstance().saveRouters.push(e)},t.registerLoadRouter=function(e){t.getInstance().loadRouters.push(e)},t.getSaveHandlers=function(e){return t.getHandlers(e,"save")},t.getLoadHandlers=function(e,n){return t.getHandlers(e,"load",n)},t.getHandlers=function(e,n,r){var i=[];return("load"===n?t.getInstance().loadRouters:t.getInstance().saveRouters).forEach(function(t){var n=t(e,r);null!==n&&i.push(n)}),i},t}(),Fc="://",Mc=function(){function t(){this.managers={}}return t.getInstance=function(){return null==t.instance&&(t.instance=new t),t.instance},t.registerManager=function(e,n){f(null!=e,function(){return"scheme must not be undefined or null."}),e.endsWith(Fc)&&(e=e.slice(0,e.indexOf(Fc))),f(e.length>0,function(){return"scheme must not be an empty string."});var r=t.getInstance();f(null==r.managers[e],function(){return"A model store manager is already registered for scheme '"+e+"'."}),r.managers[e]=n},t.getManager=function(t){var e=this.getInstance().managers[t];if(null==e)throw new Error("Cannot find model manager for scheme '"+t+"'");return e},t.getSchemes=function(){return Object.keys(this.getInstance().managers)},t}();function zc(t){if(-1===t.indexOf(Fc))throw new Error("The url string provided does not contain a scheme. 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u,l=Oc(e),c=a.transaction(Bc,"readwrite"),p=c.objectStore(Bc),h=p.put({modelPath:n.modelPath,modelArtifactsInfo:l});h.onsuccess=function(){var i=(u=a.transaction(Pc,"readwrite")).objectStore(Pc).put({modelPath:n.modelPath,modelArtifacts:e,modelArtifactsInfo:l});i.onsuccess=function(){return t({modelArtifactsInfo:l})},i.onerror=function(t){var e=(p=c.objectStore(Bc)).delete(n.modelPath);e.onsuccess=function(){return a.close(),r(i.error)},e.onerror=function(t){return a.close(),r(i.error)}}},h.onerror=function(t){return a.close(),r(h.error)},c.oncomplete=function(){null==u?a.close():u.oncomplete=function(){return a.close()}}}},i.onerror=function(t){return r(i.error)}})},t.URL_SCHEME="indexeddb://",t}(),jc=function(e){return t.ENV.getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Uc.URL_SCHEME)?(n=e.slice(Uc.URL_SCHEME.length),new Uc(n)):null;var n};_c.registerSaveRouter(jc),_c.registerLoadRouter(jc);var Gc=function(){function t(){this.indexedDB=Vc()}return t.prototype.listModels=function(){return r(this,void 0,void 0,function(){var t=this;return i(this,function(e){return[2,new Promise(function(e,n){var r=t.indexedDB.open("tensorflowjs",1);r.onupgradeneeded=function(){return Wc(r)},r.onsuccess=function(){var t=r.result,i=t.transaction(Bc,"readonly"),a=i.objectStore(Bc).getAll();a.onsuccess=function(){for(var t={},n=0,r=a.result;n<r.length;n++){var i=r[n];t[i.modelPath]=i.modelArtifactsInfo}e(t)},a.onerror=function(e){return t.close(),n(a.error)},i.oncomplete=function(){return t.close()}},r.onerror=function(t){return n(r.error)}})]})})},t.prototype.removeModel=function(t){return r(this,void 0,void 0,function(){var e=this;return i(this,function(n){var r;return t=(r=t).startsWith(Uc.URL_SCHEME)?r.slice(Uc.URL_SCHEME.length):r,[2,new Promise(function(n,r){var i=e.indexedDB.open("tensorflowjs",1);i.onupgradeneeded=function(){return Wc(i)},i.onsuccess=function(){var e,a=i.result,o=a.transaction(Bc,"readwrite"),s=o.objectStore(Bc),u=s.get(t);u.onsuccess=function(){if(null==u.result)return a.close(),r(new Error("Cannot find model with path '"+t+"' in IndexedDB."));var i=s.delete(t),o=function(){var i=(e=a.transaction(Pc,"readwrite")).objectStore(Pc).delete(t);i.onsuccess=function(){return n(u.result.modelArtifactsInfo)},i.onerror=function(t){return r(u.error)}};i.onsuccess=o,i.onerror=function(t){return o(),a.close(),r(u.error)}},u.onerror=function(t){return a.close(),r(u.error)},o.oncomplete=function(){null==e?a.close():e.oncomplete=function(){return a.close()}}},i.onerror=function(t){return r(i.error)}})]})})},t}();if(t.ENV.getBool("IS_BROWSER"))try{Mc.registerManager(Uc.URL_SCHEME,new Gc)}catch(e){}var Hc="/",qc="tensorflowjs_models",Kc="info",$c="model_topology",Xc="weight_specs",Yc="weight_data",Jc="model_metadata";function Zc(t){return{info:[qc,t,Kc].join(Hc),topology:[qc,t,$c].join(Hc),weightSpecs:[qc,t,Xc].join(Hc),weightData:[qc,t,Yc].join(Hc),modelMetadata:[qc,t,Jc].join(Hc)}}function Qc(t){var e=t.split(Hc);if(e.length<3)throw new Error("Invalid key format: "+t);return e.slice(1,e.length-1).join(Hc)}var tp=function(){function e(e){if(!t.ENV.getBool("IS_BROWSER")||void 0===window.localStorage)throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,null==e||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=Zc(this.modelPath)}return e.prototype.save=function(t){return r(this,void 0,void 0,function(){var e,n,r;return i(this,function(i){if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");e=JSON.stringify(t.modelTopology),n=JSON.stringify(t.weightSpecs),r=Oc(t);try{return this.LS.setItem(this.keys.info,JSON.stringify(r)),this.LS.setItem(this.keys.topology,e),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,(a=t.weightData,Ac?Buffer.from(a).toString("base64"):btoa(String.fromCharCode.apply(null,new Uint8Array(a))))),this.LS.setItem(this.keys.modelMetadata,JSON.stringify({format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy})),[2,{modelArtifactsInfo:r}]}catch(t){throw this.LS.removeItem(this.keys.info),this.LS.removeItem(this.keys.topology),this.LS.removeItem(this.keys.weightSpecs),this.LS.removeItem(this.keys.weightData),this.LS.removeItem(this.keys.modelMetadata),new Error("Failed to save model '"+this.modelPath+"' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes="+r.modelTopologyBytes+", weightSpecsBytes="+r.weightSpecsBytes+", weightDataBytes="+r.weightDataBytes+".")}var a;return[2]})})},e.prototype.load=function(){return r(this,void 0,void 0,function(){var t,e,n,r,a,o,s;return i(this,function(i){if(null==(t=JSON.parse(this.LS.getItem(this.keys.info))))throw new Error("In local storage, there is no model with name '"+this.modelPath+"'");if("JSON"!==t.modelTopologyType)throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");if(e={},null==(n=JSON.parse(this.LS.getItem(this.keys.topology))))throw new Error("In local storage, the topology of model '"+this.modelPath+"' is missing.");if(e.modelTopology=n,null==(r=JSON.parse(this.LS.getItem(this.keys.weightSpecs))))throw new Error("In local storage, the weight specs of model '"+this.modelPath+"' are missing.");if(e.weightSpecs=r,null!=(a=this.LS.getItem(this.keys.modelMetadata))&&(o=JSON.parse(a),e.format=o.format,e.generatedBy=o.generatedBy,e.convertedBy=o.convertedBy),null==(s=this.LS.getItem(this.keys.weightData)))throw new Error("In local storage, the binary weight values of model '"+this.modelPath+"' are missing.");return e.weightData=function(t){if(Ac){var e=Buffer.from(t,"base64");return e.buffer.slice(e.byteOffset,e.byteOffset+e.byteLength)}for(var n=atob(t),r=new Uint8Array(n.length),i=0;i<n.length;++i)r.set([n.charCodeAt(i)],i);return r.buffer}(s),[2,e]})})},e.URL_SCHEME="localstorage://",e}(),ep=function(e){return t.ENV.getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(tp.URL_SCHEME)?(n=e.slice(tp.URL_SCHEME.length),new tp(n)):null;var n};_c.registerSaveRouter(ep),_c.registerLoadRouter(ep);var np=function(){function e(){f(t.ENV.getBool("IS_BROWSER"),function(){return"Current environment is not a web browser"}),f(void 0!==window.localStorage,function(){return"Current browser does not appear to support localStorage"}),this.LS=window.localStorage}return e.prototype.listModels=function(){return r(this,void 0,void 0,function(){var t,e,n,r,a,o;return i(this,function(i){for(t={},e=qc+Hc,n=Hc+Kc,r=0;r<this.LS.length;++r)(a=this.LS.key(r)).startsWith(e)&&a.endsWith(n)&&(o=Qc(a),t[o]=JSON.parse(this.LS.getItem(a)));return[2,t]})})},e.prototype.removeModel=function(t){return r(this,void 0,void 0,function(){var e,n;return i(this,function(r){var i;if(t=(i=t).startsWith(tp.URL_SCHEME)?i.slice(tp.URL_SCHEME.length):i,e=Zc(t),null==this.LS.getItem(e.info))throw new Error("Cannot find model at path '"+t+"'");return n=JSON.parse(this.LS.getItem(e.info)),this.LS.removeItem(e.info),this.LS.removeItem(e.topology),this.LS.removeItem(e.weightSpecs),this.LS.removeItem(e.weightData),[2,n]})})},e}();if(t.ENV.getBool("IS_BROWSER"))try{Mc.registerManager(tp.URL_SCHEME,new np)}catch(e){}var rp="model",ip=".json",ap=".weights.bin";function op(t){return new Promise(function(t){return setTimeout(t)}).then(t)}var sp=function(){function e(n){if(!t.ENV.getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");n.startsWith(e.URL_SCHEME)&&(n=n.slice(e.URL_SCHEME.length)),null!=n&&0!==n.length||(n=rp),this.modelTopologyFileName=n+ip,this.weightDataFileName=n+ap}return e.prototype.save=function(t){return r(this,void 0,void 0,function(){var e,n,r,a,o,s;return i(this,function(i){switch(i.label){case 0:if("undefined"==typeof document)throw new Error("Browser downloads are not supported in this environment since `document` is not present");if(e=window.URL.createObjectURL(new Blob([t.weightData],{type:"application/octet-stream"})),!(t.modelTopology instanceof ArrayBuffer))return[3,1];throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");case 1:return n=[{paths:["./"+this.weightDataFileName],weights:t.weightSpecs}],r={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,weightsManifest:n},a=window.URL.createObjectURL(new Blob([JSON.stringify(r)],{type:"application/json"})),(o=null==this.jsonAnchor?document.createElement("a"):this.jsonAnchor).download=this.modelTopologyFileName,o.href=a,[4,op(function(){return o.dispatchEvent(new MouseEvent("click"))})];case 2:return i.sent(),null==t.weightData?[3,4]:((s=null==this.weightDataAnchor?document.createElement("a"):this.weightDataAnchor).download=this.weightDataFileName,s.href=e,[4,op(function(){return s.dispatchEvent(new MouseEvent("click"))})]);case 3:i.sent(),i.label=4;case 4:return[2,{modelArtifactsInfo:Oc(t)}]}})})},e.URL_SCHEME="downloads://",e}(),up=function(){function t(t){if(null==t||t.length<1)throw new Error("When calling browserFiles, at least 1 file is required, but received "+t);this.files=t}return t.prototype.load=function(){return r(this,void 0,void 0,function(){var t,e,n=this;return i(this,function(r){return t=this.files[0],e=this.files.slice(1),[2,new Promise(function(r,i){var a=new FileReader;a.onload=function(a){var o=JSON.parse(a.target.result),s=o.modelTopology;if(null!=s){0===e.length&&r({modelTopology:s});var u=o.weightsManifest;if(null!=u){var l;try{l=n.checkManifestAndWeightFiles(u,e)}catch(t){return void i(t)}var c=[],p=[],h=[];u.forEach(function(t){t.paths.forEach(function(t){p.push(t),h.push(null)}),c.push.apply(c,t.weights)}),u.forEach(function(t){t.paths.forEach(function(t){var e=new FileReader;e.onload=function(e){var n=e.target.result,i=p.indexOf(t);h[i]=n,-1===h.indexOf(null)&&r({modelTopology:s,weightSpecs:c,weightData:Tc(h)})},e.onerror=function(e){return i("Failed to weights data from file of path '"+t+"'.")},e.readAsArrayBuffer(l[t])})})}else i(new Error("weightManifest field is missing from file "+t.name))}else i(new Error("modelTopology field is missing from file "+t.name))},a.onerror=function(e){return i("Failed to read model topology and weights manifest JSON from file '"+t.name+"'. BrowserFiles supports loading Keras-style tf.Model artifacts only.")},a.readAsText(t)})]})})},t.prototype.checkManifestAndWeightFiles=function(t,e){for(var n=[],r=e.map(function(t){return Dc(t.name)}),i={},a=0,o=t;a<o.length;a++)o[a].paths.forEach(function(t){var a=Dc(t);if(-1!==n.indexOf(a))throw new Error("Duplicate file basename found in weights manifest: '"+a+"'");if(n.push(a),-1===r.indexOf(a))throw new Error("Weight file with basename '"+a+"' is not provided.");i[t]=e[r.indexOf(a)]});if(n.length!==e.length)throw new Error("Mismatch in the number of files in weights manifest ("+n.length+") and the number of weight files provided ("+e.length+").");return i},t}();function lp(t,e,n,r){!function(t){f(null!=t&&Array.isArray(t)&&t.length>0,function(){return"promises must be a none empty array"})}(t),function(t,e){f(t>=0&&t<=1,function(){return"Progress fraction must be in range [0, 1], but got startFraction "+t}),f(e>=0&&e<=1,function(){return"Progress fraction must be in range [0, 1], 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function(n,a,o){return void 0===a&&(a=""),r(e,void 0,void 0,function(){var e,r,s,u,l,c,p,h,f,d;return i(this,function(i){switch(i.label){case 0:if(e=n.map(function(){return!1}),r={},s=null!=o?o.map(function(){return!1}):[],u=[],n.forEach(function(t,n){var i=0;t.weights.forEach(function(t){var a="quantization"in t?t.quantization.dtype:t.dtype,l=Sc[a]*v(t.shape),c=function(){e[n]=!0,null==r[n]&&(r[n]=[]),r[n].push({manifestEntry:t,groupOffset:i,sizeBytes:l})};null!=o?o.forEach(function(e,n){e===t.name&&(c(),s[n]=!0)}):c(),u.push(t.name),i+=l})}),!s.every(function(t){return t}))throw l=o.filter(function(t,e){return!s[e]}),new Error("Could not find weights in manifest with names: "+l.join(", ")+". \nManifest JSON has weights with names: "+u.join(", ")+".");return c=e.reduce(function(t,e,n){return e&&t.push(n),t},[]),p=[],c.forEach(function(t){n[t].paths.forEach(function(t){var e=a+(a.endsWith("/")?"":"/")+t;p.push(e)})}),[4,t(p)];case 1:return h=i.sent(),f={},d=0,c.forEach(function(t){for(var e=n[t].paths.length,i=0,a=0;a<e;a++)i+=h[d+a].byteLength;for(var o=new ArrayBuffer(i),s=new Uint8Array(o),u=0,l=0;l<e;l++){var c=new Uint8Array(h[d+l]);s.set(c,u),u+=c.byteLength}r[t].forEach(function(t){var e=Ic(o.slice(t.groupOffset,t.groupOffset+t.sizeBytes),[t.manifestEntry]);for(var n in e)f[n]=e[n]}),d+=e}),[2,f]}})})}}_c.registerSaveRouter(function(e){return t.ENV.getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(sp.URL_SCHEME)?(void 0===(n=e.slice(sp.URL_SCHEME.length))&&(n="model"),new sp(n)):null;var n});var hp=function(){function e(e,n){if(this.DEFAULT_METHOD="POST",null==n&&(n={}),this.weightPathPrefix=n.weightPathPrefix,this.onProgress=n.onProgress,null!=n.fetchFunc?(f("function"==typeof n.fetchFunc,function(){return"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"}),this.fetch=n.fetchFunc):this.fetch=t.ENV.platform.fetch,f(null!=e&&e.length>0,function(){return"URL path for http must not be null, undefined or empty."}),Array.isArray(e)&&f(2===e.length,function(){return"URL paths for http must have a length of 2, (actual length is "+e.length+")."}),this.path=e,null!=n.requestInit&&null!=n.requestInit.body)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=n.requestInit||{}}return e.prototype.save=function(t){return r(this,void 0,void 0,function(){var e,n,r,a;return i(this,function(i){switch(i.label){case 0:if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");return(e=Object.assign({method:this.DEFAULT_METHOD},this.requestInit)).body=new FormData,n=[{paths:["./model.weights.bin"],weights:t.weightSpecs}],r={modelTopology:t.modelTopology,format:t.format,generatedBy:t.generatedBy,convertedBy:t.convertedBy,weightsManifest:n},e.body.append("model.json",new Blob([JSON.stringify(r)],{type:"application/json"}),"model.json"),null!=t.weightData&&e.body.append("model.weights.bin",new Blob([t.weightData],{type:"application/octet-stream"}),"model.weights.bin"),[4,this.fetch(this.path,e)];case 1:if((a=i.sent()).ok)return[2,{modelArtifactsInfo:Oc(t),responses:[a]}];throw new Error("BrowserHTTPRequest.save() failed due to HTTP response status "+a.status+".")}})})},e.prototype.load=function(){return r(this,void 0,void 0,function(){var t,e,n,r,a,o,s,u;return i(this,function(i){switch(i.label){case 0:return[4,this.fetch(this.path,this.requestInit)];case 1:if(!(t=i.sent()).ok)throw new Error("Request to "+this.path+" failed with status code "+t.status+". Please verify this URL points to the model JSON of the model to load.");i.label=2;case 2:return i.trys.push([2,4,,5]),[4,t.json()];case 3:return e=i.sent(),[3,5];case 4:throw i.sent(),n="Failed to parse model JSON of response from "+this.path+".",this.path.endsWith(".pb")?n+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":n+=" Please make sure the server is serving valid JSON for this request.",new Error(n);case 5:if(r=e.modelTopology,a=e.weightsManifest,null==r&&null==a)throw new Error("The JSON from HTTP path "+this.path+" contains neither model topology or manifest for weights.");return null==a?[3,7]:[4,this.loadWeights(a)];case 6:u=i.sent(),o=u[0],s=u[1],i.label=7;case 7:return[2,{modelTopology:r,weightSpecs:o,weightData:s}]}})})},e.prototype.loadWeights=function(t){return r(this,void 0,void 0,function(){var e,n,r,a,o,s,u,l,c,p,h;return i(this,function(i){switch(i.label){case 0:for(e=Array.isArray(this.path)?this.path[1]:this.path,n=function(t){var e=t.lastIndexOf("/"),n=t.lastIndexOf("?");return[t.substring(0,e)+"/",n>e?t.substring(n):""]}(e),r=n[0],a=n[1],o=this.weightPathPrefix||r,s=[],u=0,l=t;u<l.length;u++)c=l[u],s.push.apply(s,c.weights);return p=[],t.forEach(function(t){t.paths.forEach(function(t){p.push(o+t+a)})}),[4,cp(p,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress})];case 1:return h=i.sent(),[2,[s,Tc(h)]]}})})},e.URL_SCHEME_REGEX=/^https?:\/\//,e}();function fp(t){return null!=t.match(hp.URL_SCHEME_REGEX)}var dp=function(t,e){return"undefined"==typeof fetch?null:(Array.isArray(t)?t.every(function(t){return fp(t)}):fp(t))?mp(t,{onProgress:e}):null};function mp(t,e){return new hp(t,e)}_c.registerSaveRouter(dp),_c.registerLoadRouter(dp);var gp=function(){function t(t){this.modelArtifacts=t}return t.prototype.load=function(){return r(this,void 0,void 0,function(){return i(this,function(t){return[2,this.modelArtifacts]})})},t}(),vp=function(){function t(t){this.saveHandler=t}return t.prototype.save=function(t){return r(this,void 0,void 0,function(){return i(this,function(e){return[2,this.saveHandler(t)]})})},t}(),yp=Object.freeze({browserFiles:function(t){return new up(t)},browserHTTPRequest:function(t,e){return mp(t,e)},concatenateArrayBuffers:Tc,decodeWeights:Ic,encodeWeights:function(t,e){return r(this,void 0,void 0,function(){var n,a,o,s,u,l=this;return i(this,function(c){switch(c.label){case 0:for(n=[],a=[],o=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t),s=function(s){var u=o[s],c=Array.isArray(t)?t[s].tensor:t[u];if("float32"!==c.dtype&&"int32"!==c.dtype&&"bool"!==c.dtype&&"string"!==c.dtype)throw new Error("Unsupported dtype in weight '"+u+"': "+c.dtype);var p={name:u,shape:c.shape,dtype:c.dtype};if("string"===c.dtype){var h=new Promise(function(t){return r(l,void 0,void 0,function(){var e,n,r,a,o,s,u;return i(this,function(i){switch(i.label){case 0:return[4,c.bytes()];case 1:for(e=i.sent(),n=e.reduce(function(t,e){return t+e.length},0)+kc*e.length,r=new Uint8Array(n),a=0,o=0;o<e.length;o++)s=e[o],u=new Uint8Array(new Uint32Array([s.length]).buffer),r.set(u,a),a+=kc,r.set(s,a),a+=s.length;return t(r),[2]}})})});a.push(h)}else a.push(c.data());null!=e&&(p.group=e),n.push(p)},u=0;u<o.length;++u)s(u);return[4,Promise.all(a)];case 1:return[2,{data:function(t){if(null===t)throw new Error("Invalid input value: "+JSON.stringify(t));var e=0,n=[];t.forEach(function(t){if(e+=t.byteLength,n.push(t.byteLength===t.buffer.byteLength?t:new t.constructor(t)),!(t instanceof Float32Array||t instanceof Int32Array||t instanceof Uint8Array))throw new Error("Unsupported TypedArray subtype: "+t.constructor.name)});var r=new Uint8Array(e),i=0;return n.forEach(function(t){r.set(new Uint8Array(t.buffer),i),i+=t.byteLength}),r.buffer}(c.sent()),specs:n}]}})})},fromMemory:function(t,e,n,r){return 1===arguments.length?null!=t.modelTopology||null!=t.weightSpecs?new gp(t):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new gp({modelTopology:t})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new gp({modelTopology:t,weightSpecs:e,weightData:n,trainingConfig:r}))},getLoadHandlers:function(t,e){return _c.getLoadHandlers(t,e)},getModelArtifactsInfoForJSON:Oc,getSaveHandlers:function(t){return _c.getSaveHandlers(t)},http:mp,isHTTPScheme:fp,loadWeights:function(t,e,n,a){return void 0===e&&(e=""),r(this,void 0,void 0,function(){return i(this,function(r){return[2,pp(function(t){return cp(t,{requestInit:a})})(t,e,n)]})})},registerLoadRouter:function(t){return _c.registerLoadRouter(t)},registerSaveRouter:function(t){return _c.registerSaveRouter(t)},weightsLoaderFactory:pp,withSaveHandler:function(t){return new vp(t)},copyModel:function(t,e){return r(this,void 0,void 0,function(){return i(this,function(n){return[2,Lc(t,e,!1)]})})},listModels:function(){return r(this,void 0,void 0,function(){var t,e,n,r,a,o,s;return i(this,function(i){switch(i.label){case 0:t=Mc.getSchemes(),e={},n=0,r=t,i.label=1;case 1:return n<r.length?(a=r[n],[4,Mc.getManager(a).listModels()]):[3,4];case 2:for(s in o=i.sent())e[a+Fc+s]=o[s];i.label=3;case 3:return n++,[3,1];case 4:return[2,e]}})})},moveModel:function(t,e){return r(this,void 0,void 0,function(){return i(this,function(n){return[2,Lc(t,e,!0)]})})},removeModel:function(t){return r(this,void 0,void 0,function(){var e;return i(this,function(n){return e=zc(t),[2,Mc.getManager(e.scheme).removeModel(e.path)]})})}}),bp=Ze({confusionMatrix_:function(t,e,n){var r=Ve(t,"labels","confusionMatrix"),i=Ve(e,"predictions","confusionMatrix");f(null==n||n>0&&Number.isInteger(n),function(){return"If provided, numClasses must be a positive integer, but got "+n}),f(1===r.rank,function(){return"Expected the rank of labels to be 1, but got "+r.rank}),f(1===i.rank,function(){return"Expected the rank of predictions to be 1, but got "+i.rank}),f(r.shape[0]===i.shape[0],function(){return"Mismatch in the number of examples: "+r.shape[0]+" vs. "+i.shape[0]+". Labels and predictions should have the same number of elements."}),f(n>0&&Number.isInteger(n),function(){return"numClasses is required to be a positive integer, but got "+n});var a=Kn(r.asType("int32"),n),o=Kn(i.asType("int32"),n);return a.transpose().matMul(o).asType("int32")}}),xp=Object.freeze({confusionMatrix:bp}),wp=Ze({fromPixels_:function(t,e){if(void 0===e&&(e=3),e>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");var n="undefined"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement;if(n&&n&&t.readyState<2)throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.");return kt.fromPixels(t,e)}}),Np=Object.freeze({toPixels:function(t,e){return r(this,void 0,void 0,function(){var n,r,a,o,s,u,l,c,p,h,f,d,m,g,v,y,b,x,w,N,C,E,S;return i(this,function(i){switch(i.label){case 0:if(n=Ve(t,"img","toPixels"),t instanceof lt||(n=n.toInt()),2!==n.rank&&3!==n.rank)throw new Error("toPixels only supports rank 2 or 3 tensors, got rank "+n.rank+".");if(r=n.shape.slice(0,2),a=r[0],o=r[1],(s=2===n.rank?1:n.shape[2])>4||2===s)throw new Error("toPixels only supports depth of size 1, 3 or 4 but got "+s);return[4,n.data()];case 1:return u=i.sent(),l=n.min(),c=n.max(),[4,Promise.all([l.data(),c.data()])];case 2:if(p=i.sent(),h=p[0],f=p[1],d=h[0],m=f[0],l.dispose(),c.dispose(),"float32"===n.dtype){if(d<0||m>1)throw new Error("Tensor values for a float32 Tensor must be in the range [0 - 1] but got range ["+d+" - "+m+"].")}else{if("int32"!==n.dtype)throw new Error("Unsupported type for toPixels: "+n.dtype+". Please use float32 or int32 tensors.");if(d<0||m>255)throw new Error("Tensor values for a int32 Tensor must be in the range [0 - 255] but got range ["+d+" - "+m+"].")}for(g="float32"===n.dtype?255:1,v=new Uint8ClampedArray(o*a*4),y=0;y<a*o;++y)b=void 0,x=void 0,w=void 0,N=void 0,1===s?(b=u[y]*g,x=u[y]*g,w=u[y]*g,N=255):3===s?(b=u[3*y]*g,x=u[3*y+1]*g,w=u[3*y+2]*g,N=255):4===s&&(b=u[4*y]*g,x=u[4*y+1]*g,w=u[4*y+2]*g,N=u[4*y+3]*g),v[0+(C=4*y)]=Math.round(b),v[C+1]=Math.round(x),v[C+2]=Math.round(w),v[C+3]=Math.round(N);return null!=e&&(e.width=o,e.height=a,E=e.getContext("2d"),S=new ImageData(v,o,a),E.putImageData(S,0,0)),n!==t&&n.dispose(),[2,v]}})})},fromPixels:wp}),Cp=function(){function t(){}return t.prototype.getClassName=function(){return this.constructor.className},t.fromConfig=function(t,e){return new t(e)},t}(),Ep=function(){function t(){this.classNameMap={}}return t.getMap=function(){return null==t.instance&&(t.instance=new t),t.instance},t.register=function(e){t.getMap().classNameMap[e.className]=[e,e.fromConfig]},t}();function Sp(t){f(null!=t.className,function(){return"Class being registered does not have the static className property defined."}),f("string"==typeof t.className,function(){return"className is required to be a string, but got type "+typeof t.className}),f(t.className.length>0,function(){return"Class being registered has an empty-string as its className, which is disallowed."}),Ep.register(t)}var kp=Object.freeze({Serializable:Cp,SerializationMap:Ep,registerClass:Sp}),Ip=.001,Ap=.1;function Rp(){return 32===kt.backend.floatPrecision()?Ip:Ap}function Tp(t,e,n){var r=!0;if((O(t)||O(e))&&(r=!1),O(t)&&O(e)&&(r=!0),r){var i=t.constructor.name,a=e.constructor.name;if(i!==a)throw new Error("Arrays are of different type. Actual: "+i+". Expected: "+a)}if(Array.isArray(t)&&Array.isArray(e)){var o=Pe(t),s=Pe(e);if(!y(o,s))throw new Error("Arrays have different shapes. Actual: ["+o+"]. Expected: ["+s+"]")}var u=O(t)?t:g(t),l=O(e)?e:g(e);if(u.length!==l.length)throw new Error("Arrays have different lengths actual: "+u.length+" vs expected: "+l.length+".\nActual:   "+u+".\nExpected: "+l+".");for(var c=0;c<l.length;++c){var p=u[c],h=l[c];if(!n(p,h))throw new Error("Arrays differ: actual["+c+"] = "+p+", expected["+c+"] = "+h+".\nActual:   "+u+".\nExpected: "+l+".")}}function Dp(t,e,n){return!isFinite(t)&&!isFinite(e)||!(isNaN(t)||isNaN(e)||Math.abs(t-e)>n)}var Op=Object.freeze({TEST_EPSILON_FLOAT16:Ap,expectArraysClose:function(t,e,n){return null==n&&(n=Rp()),Tp(t,e,function(t,e){return Dp(t,e,n)})},testEpsilon:Rp,expectPromiseToFail:function(t,e){t().then(function(){return e.fail()},function(){return e()})},expectArraysEqual:function(t,e){var n="string"==typeof e||"number"==typeof e||"boolean"==typeof e?[e]:e;return M(t)||M(t[0])||M(e)||M(e[0])?Tp(t,n,function(t,e){return t==e}):Tp(t,e,function(t,e){return Dp(t,e,0)})},expectNumbersClose:function(t,e,n){if(null==n&&(n=Rp()),!Dp(t,e,n))throw new Error("Numbers differ: actual === "+t+", expected === "+e)},expectValuesInRange:function(t,e,n){for(var r=0;r<t.length;r++)if(t[r]<e||t[r]>n)throw new Error("Value out of range:"+t[r]+" low: "+e+", high: "+n)},expectArrayBuffersEqual:function(t,e){expect(new Float32Array(t)).toEqual(new Float32Array(e))}}),_p=Object.freeze({gpgpu_util:Ma,webgl_util:Te,forceHalfFloat:function(){t.ENV.set("WEBGL_FORCE_F16_TEXTURES",!0)},MathBackendWebGL:jo,setWebGLContext:Ot,GPGPUContext:za}),Fp=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return n(e,t),e.prototype.minimize=function(t,e,n){void 0===e&&(e=!1);var r=this.computeGradients(t,n),i=r.value,a=r.grads;if(null!=n){var o=n.map(function(t){return{name:t.name,tensor:a[t.name]}});this.applyGradients(o)}else this.applyGradients(a);return Fe(a),e?i:(i.dispose(),null)},Object.defineProperty(e.prototype,"iterations",{get:function(){return null==this.iterations_&&(this.iterations_=0),this.iterations_},enumerable:!0,configurable:!0}),e.prototype.incrementIterations=function(){this.iterations_=this.iterations+1},e.prototype.computeGradients=function(t,e){return kr(t,e)},e.prototype.dispose=function(){null!=this.iterations_&&Fe(this.iterations_)},e.prototype.saveIterations=function(){return r(this,void 0,void 0,function(){return i(this,function(t){return null==this.iterations_&&(this.iterations_=0),[2,{name:"iter",tensor:an(this.iterations_,"int32")}]})})},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){return i(this,function(t){throw new Error("getWeights() is not implemented for this optimizer yet.")})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){return i(this,function(t){throw new Error("setWeights() is not implemented for this optimizer class "+this.getClassName())})})},e.prototype.extractIterations=function(t){return r(this,void 0,void 0,function(){var e;return i(this,function(n){switch(n.label){case 0:return e=this,[4,t[0].tensor.data()];case 1:return e.iterations_=n.sent()[0],[2,t.slice(1)]}})})},e}(Cp);Object.defineProperty(Fp,Symbol.hasInstance,{value:function(t){return null!=t.minimize&&null!=t.computeGradients&&null!=t.applyGradients}});var Mp=function(t){function e(e,n,r){void 0===r&&(r=null);var i=t.call(this)||this;return i.learningRate=e,i.rho=n,i.epsilon=r,i.accumulatedGrads=[],i.accumulatedUpdates=[],null==r&&(i.epsilon=kt.backend.epsilon()),i}return n(e,t),e.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var i=kt.registeredVariables[n];null==e.accumulatedGrads[r]&&(e.accumulatedGrads[r]={originalName:n+"/accum_grad",variable:_e(function(){return yn(i).variable(!1)})}),null==e.accumulatedUpdates[r]&&(e.accumulatedUpdates[r]={originalName:n+"/accum_var",variable:_e(function(){return yn(i).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var o=e.accumulatedGrads[r].variable,s=e.accumulatedUpdates[r].variable;_e(function(){var t=o.mul(e.rho).add(a.square().mul(1-e.rho)),n=s.add(e.epsilon).sqrt().div(o.add(e.epsilon).sqrt()).mul(a),r=s.mul(e.rho).add(n.square().mul(1-e.rho));o.assign(t),s.assign(r);var u=n.mul(-e.learningRate).add(i);i.assign(u)})}}),this.incrementIterations()},e.prototype.dispose=function(){null!=this.accumulatedUpdates&&(Fe(this.accumulatedGrads.map(function(t){return t.variable})),Fe(this.accumulatedUpdates.map(function(t){return t.variable})))},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){var t;return i(this,function(e){switch(e.label){case 0:return t=this.accumulatedGrads.concat(this.accumulatedUpdates),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){var e;return i(this,function(n){switch(n.label){case 0:return[4,this.extractIterations(t)];case 1:return t=n.sent(),e=t.length/2,this.accumulatedGrads=t.slice(0,e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.accumulatedUpdates=t.slice(e,2*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}},e.fromConfig=function(t,e){return new t(e.learningRate,e.rho,e.epsilon)},e.className="Adadelta",e}(Fp);Sp(Mp);var zp=function(t){function e(e,n){void 0===n&&(n=.1);var r=t.call(this)||this;return r.learningRate=e,r.initialAccumulatorValue=n,r.accumulatedGrads=[],r}return n(e,t),e.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var i=kt.registeredVariables[n];null==e.accumulatedGrads[r]&&(e.accumulatedGrads[r]={originalName:n+"/accumulator",variable:_e(function(){return dn(i.shape,e.initialAccumulatorValue).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var o=e.accumulatedGrads[r].variable;_e(function(){var t=o.add(a.square());o.assign(t);var n=a.div(t.add(kt.backend.epsilon()).sqrt()).mul(-e.learningRate).add(i);i.assign(n)})}}),this.incrementIterations()},e.prototype.dispose=function(){null!=this.accumulatedGrads&&Fe(this.accumulatedGrads.map(function(t){return t.variable}))},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){return i(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulatedGrads.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){return i(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),this.accumulatedGrads=t.map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}},e.fromConfig=function(t,e){return new t(e.learningRate,e.initialAccumulatorValue)},e.className="Adagrad",e}(Fp);Sp(zp);var Lp=function(t){function e(e,n,r,i){void 0===i&&(i=null);var a=t.call(this)||this;return a.learningRate=e,a.beta1=n,a.beta2=r,a.epsilon=i,a.accumulatedFirstMoment=[],a.accumulatedSecondMoment=[],_e(function(){a.accBeta1=an(n).variable(),a.accBeta2=an(r).variable()}),null==i&&(a.epsilon=kt.backend.epsilon()),a}return n(e,t),e.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t);_e(function(){var r=cu(1,e.accBeta1),i=cu(1,e.accBeta2);n.forEach(function(n,a){var o=kt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+"/m",variable:_e(function(){return yn(o).variable(!1)})}),null==e.accumulatedSecondMoment[a]&&(e.accumulatedSecondMoment[a]={originalName:n+"/v",variable:_e(function(){return yn(o).variable(!1)})});var s=Array.isArray(t)?t[a].tensor:t[n];if(null!=s){var u=e.accumulatedFirstMoment[a].variable,l=e.accumulatedSecondMoment[a].variable,c=u.mul(e.beta1).add(s.mul(1-e.beta1)),p=l.mul(e.beta2).add(s.square().mul(1-e.beta2)),h=c.div(r),f=p.div(i);u.assign(c),l.assign(p);var d=h.div(f.sqrt().add(e.epsilon)).mul(-e.learningRate).add(o);o.assign(d)}}),e.accBeta1.assign(e.accBeta1.mul(e.beta1)),e.accBeta2.assign(e.accBeta2.mul(e.beta2))}),this.incrementIterations()},e.prototype.dispose=function(){this.accBeta1.dispose(),this.accBeta2.dispose(),null!=this.accumulatedFirstMoment&&Fe(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedSecondMoment&&Fe(this.accumulatedSecondMoment.map(function(t){return t.variable}))},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){var t;return i(this,function(e){switch(e.label){case 0:return t=this.accumulatedFirstMoment.concat(this.accumulatedSecondMoment),[4,this.saveIterations()];case 1:return[2,[e.sent()].concat(t.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){var e,n=this;return i(this,function(r){switch(r.label){case 0:return[4,this.extractIterations(t)];case 1:return t=r.sent(),_e(function(){n.accBeta1.assign(ou(n.beta1,n.iterations_+1)),n.accBeta2.assign(ou(n.beta2,n.iterations_+1))}),e=t.length/2,this.accumulatedFirstMoment=t.slice(0,e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),this.accumulatedSecondMoment=t.slice(e,2*e).map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}},e.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon)},e.className="Adam",e}(Fp);Sp(Lp);var Pp=function(t){function e(e,n,r,i,a){void 0===i&&(i=null),void 0===a&&(a=0);var o=t.call(this)||this;return o.learningRate=e,o.beta1=n,o.beta2=r,o.epsilon=i,o.decay=a,o.accumulatedFirstMoment=[],o.accumulatedWeightedInfNorm=[],_e(function(){o.iteration=an(0).variable(),o.accBeta1=an(n).variable()}),null==i&&(o.epsilon=kt.backend.epsilon()),o}return n(e,t),e.prototype.applyGradients=function(t){var e=this,n=Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t);_e(function(){var r=cu(1,e.accBeta1),i=Xs(-e.learningRate,e.iteration.mul(e.decay).add(1));n.forEach(function(n,a){var o=kt.registeredVariables[n];null==e.accumulatedFirstMoment[a]&&(e.accumulatedFirstMoment[a]={originalName:n+"/m",variable:yn(o).variable(!1)}),null==e.accumulatedWeightedInfNorm[a]&&(e.accumulatedWeightedInfNorm[a]={originalName:n+"/v",variable:yn(o).variable(!1)});var s=Array.isArray(t)?t[a].tensor:t[n];if(null!=s){var u=e.accumulatedFirstMoment[a].variable,l=e.accumulatedWeightedInfNorm[a].variable,c=u.mul(e.beta1).add(s.mul(1-e.beta1)),p=l.mul(e.beta2),h=s.abs(),f=p.maximum(h);u.assign(c),l.assign(f);var d=i.div(r).mul(c.div(f.add(e.epsilon))).add(o);o.assign(d)}}),e.iteration.assign(e.iteration.add(1)),e.accBeta1.assign(e.accBeta1.mul(e.beta1))}),this.incrementIterations()},e.prototype.dispose=function(){this.accBeta1.dispose(),this.iteration.dispose(),null!=this.accumulatedFirstMoment&&Fe(this.accumulatedFirstMoment.map(function(t){return t.variable})),null!=this.accumulatedWeightedInfNorm&&Fe(this.accumulatedWeightedInfNorm.map(function(t){return t.variable}))},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){return i(this,function(t){throw new Error("getWeights() is not implemented for Adamax yet.")})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){return i(this,function(t){throw new Error("setWeights() is not implemented for Adamax yet.")})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}},e.fromConfig=function(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)},e.className="Adamax",e}(Fp);Sp(Pp);var Bp=function(t){function e(e){var n=t.call(this)||this;return n.learningRate=e,n.setLearningRate(e),n}return n(e,t),e.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var i=Array.isArray(t)?t[r].tensor:t[n];if(null!=i){var a=kt.registeredVariables[n];_e(function(){var t=e.c.mul(i).add(a);a.assign(t)})}}),this.incrementIterations()},e.prototype.setLearningRate=function(t){this.learningRate=t,null!=this.c&&this.c.dispose(),this.c=Me(an(-t))},e.prototype.dispose=function(){this.c.dispose()},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){return i(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()]]}})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){return i(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:if(0!==(t=e.sent()).length)throw new Error("SGD optimizer does not have settable weights.");return[2]}})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate}},e.fromConfig=function(t,e){return new t(e.learningRate)},e.className="SGD",e}(Fp);Sp(Bp);var Vp=function(t){function e(e,n,r){void 0===r&&(r=!1);var i=t.call(this,e)||this;return i.learningRate=e,i.momentum=n,i.useNesterov=r,i.accumulations=[],i.m=an(i.momentum),i}return n(e,t),e.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var i=kt.registeredVariables[n];null==e.accumulations[r]&&(e.accumulations[r]={originalName:n+"/momentum",variable:_e(function(){return yn(i).variable(!1)})});var a=e.accumulations[r].variable,o=Array.isArray(t)?t[r].tensor:t[n];null!=o&&_e(function(){var t,n=e.m.mul(a).add(o);t=e.useNesterov?e.c.mul(o.add(n.mul(e.m))).add(i):e.c.mul(n).add(i),a.assign(n),i.assign(t)})}),this.incrementIterations()},e.prototype.dispose=function(){this.m.dispose(),null!=this.accumulations&&Fe(this.accumulations.map(function(t){return t.variable}))},e.prototype.setMomentum=function(t){this.momentum=t},e.prototype.getWeights=function(){return r(this,void 0,void 0,function(){return i(this,function(t){switch(t.label){case 0:return[4,this.saveIterations()];case 1:return[2,[t.sent()].concat(this.accumulations.map(function(t){return{name:t.originalName,tensor:t.variable}}))]}})})},e.prototype.setWeights=function(t){return r(this,void 0,void 0,function(){return i(this,function(e){switch(e.label){case 0:return[4,this.extractIterations(t)];case 1:return t=e.sent(),this.accumulations=t.map(function(t){return{originalName:t.name,variable:t.tensor.variable(!1)}}),[2]}})})},e.prototype.getConfig=function(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}},e.fromConfig=function(t,e){return new t(e.learningRate,e.momentum,e.useNesterov)},e.className="Momentum",e}(Bp);Sp(Vp);var Wp=function(t){function e(e,n,r,i,a){void 0===n&&(n=.9),void 0===r&&(r=0),void 0===i&&(i=null),void 0===a&&(a=!1);var o=t.call(this)||this;return o.learningRate=e,o.decay=n,o.momentum=r,o.epsilon=i,o.accumulatedMeanSquares=[],o.accumulatedMoments=[],o.accumulatedMeanGrads=[],o.centered=a,null==i&&(o.epsilon=kt.backend.epsilon()),o}return n(e,t),e.prototype.applyGradients=function(t){var e=this;(Array.isArray(t)?t.map(function(t){return t.name}):Object.keys(t)).forEach(function(n,r){var i=kt.registeredVariables[n];null==e.accumulatedMeanSquares[r]&&(e.accumulatedMeanSquares[r]={originalName:n+"/rms",variable:_e(function(){return yn(i).variable(!1)})}),null==e.accumulatedMoments[r]&&(e.accumulatedMoments[r]={originalName:n+"/momentum",variable:_e(function(){return yn(i).variable(!1)})}),null==e.accumulatedMeanGrads[r]&&e.centered&&(e.accumulatedMeanGrads[r]={originalName:n+"/mg",variable:_e(function(){return yn(i).variable(!1)})});var a=Array.isArray(t)?t[r].tensor:t[n];if(null!=a){var o=e.accumulatedMeanSquares[r].variable,s=e.accumulatedMoments[r].variable;_e(function(){var t=o.mul(e.decay).add(a.square().mul(1-e.decay));if(e.centered){var n=e.accumulatedMeanGrads[r].variable,u=n.mul(e.decay).add(a.mul(1-e.decay)),l=s.mul(e.momentum).add(a.mul(e.learningRate).div(t.sub(u.square().add(e.epsilon)).sqrt()));o.assign(t),n.assign(u),s.assign(l);var c=i.sub(l);i.assign(c)}else{var 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n.DEFAULT_MINVAL=-.05,n.DEFAULT_MAXVAL=.05,n.minval=e.minval||n.DEFAULT_MINVAL,n.maxval=e.maxval||n.DEFAULT_MAXVAL,n.seed=e.seed,n}return Kp(e,t),e.prototype.apply=function(t,e){return nr(t,this.minval,this.maxval,e)},e.prototype.getConfig=function(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}},e.className="RandomUniform",e}(vf);kp.registerClass(wf);var Nf=function(t){function e(e){var n=t.call(this)||this;return n.DEFAULT_MEAN=0,n.DEFAULT_STDDEV=.05,n.mean=e.mean||n.DEFAULT_MEAN,n.stddev=e.stddev||n.DEFAULT_STDDEV,n.seed=e.seed,n}return Kp(e,t),e.prototype.apply=function(t,e){if("float32"!==(e=e||"float32")&&"int32"!==e)throw new nh("randomNormal does not support dType "+e+".");return sf(t,this.mean,this.stddev,e,this.seed)},e.prototype.getConfig=function(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}},e.className="RandomNormal",e}(vf);kp.registerClass(Nf);var Cf=function(t){function e(e){var n=t.call(this)||this;return n.DEFAULT_MEAN=0,n.DEFAULT_STDDEV=.05,n.mean=e.mean||n.DEFAULT_MEAN,n.stddev=e.stddev||n.DEFAULT_STDDEV,n.seed=e.seed,n}return Kp(e,t),e.prototype.apply=function(t,e){if("float32"!==(e=e||"float32")&&"int32"!==e)throw new nh("truncatedNormal does not support dType "+e+".");return ur(t,this.mean,this.stddev,e,this.seed)},e.prototype.getConfig=function(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}},e.className="TruncatedNormal",e}(vf);kp.registerClass(Cf);var Ef=function(t){function e(e){var n=t.call(this)||this;return n.gain=null!=e.gain?e.gain:1,n}return Kp(e,t),e.prototype.apply=function(t,e){var n=this;return _e(function(){if(2!==t.length||t[0]!==t[1])throw new eh("Identity matrix initializer can only be used for 2D square matrices.");return iu(n.gain,Hn(t[0]))})},e.prototype.getConfig=function(){return{gain:this.gain}},e.className="Identity",e}(vf);kp.registerClass(Ef);var Sf=function(t){function e(e){var n=t.call(this)||this;if(e.scale<0)throw new eh("scale must be a 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Got: "+e.scale);return n.scale=null==e.scale?1:e.scale,n.mode=null==e.mode?"fanIn":e.mode,function(t){vh(mf,"FanMode",t)}(n.mode),n.distribution=null==e.distribution?"normal":e.distribution,function(t){vh(gf,"Distribution",t)}(n.distribution),n.seed=e.seed,n}return Kp(e,t),e.prototype.apply=function(t,e){var n=function(t,e){var n,r;if(void 0===e&&(e="channelsLast"),zh(e),2===t.length)n=t[0],r=t[1];else if(-1!==[3,4,5].indexOf(t.length))if("channelsFirst"===e){var i=Kh(t,2);n=t[1]*i,r=t[0]*i}else"channelsLast"===e&&(i=Kh(t,0,t.length-2),n=t[t.length-2]*i,r=t[t.length-1]*i);else{var a=Kh(t);n=Math.sqrt(a),r=Math.sqrt(a)}return[n,r]}(t),r=n[0],i=n[1],a=this.scale;if("fanIn"===this.mode?a/=Math.max(1,r):"fanOut"===this.mode?a/=Math.max(1,i):a/=Math.max(1,(r+i)/2),"normal"===this.distribution){var o=Math.sqrt(a);if("float32"!==(e=e||"float32")&&"int32"!==e)throw new nh(this.getClassName()+" does not support dType "+e+".");return ur(t,0,o,e,this.seed)}var s=Math.sqrt(3*a);return nr(t,-s,s,e)},e.prototype.getConfig=function(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}},e.className="VarianceScaling",e}(vf);kp.registerClass(Sf);var kf=function(t){function e(e){return t.call(this,{scale:1,mode:"fanAvg",distribution:"uniform",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="GlorotUniform",e}(Sf);kp.registerClass(kf);var If=function(t){function e(e){return t.call(this,{scale:1,mode:"fanAvg",distribution:"normal",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="GlorotNormal",e}(Sf);kp.registerClass(If);var Af=function(t){function e(e){return t.call(this,{scale:2,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="HeNormal",e}(Sf);kp.registerClass(Af);var Rf=function(t){function e(e){return t.call(this,{scale:2,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="HeUniform",e}(Sf);kp.registerClass(Rf);var Tf=function(t){function e(e){return t.call(this,{scale:1,mode:"fanIn",distribution:"normal",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="LeCunNormal",e}(Sf);kp.registerClass(Tf);var Df=function(t){function e(e){return t.call(this,{scale:1,mode:"fanIn",distribution:"uniform",seed:null==e?null:e.seed})||this}return Kp(e,t),e.prototype.getClassName=function(){return Sf.className},e.className="LeCunNormal",e}(Sf);kp.registerClass(Df);var Of=function(t){function e(e){var n=t.call(this)||this;if(n.DEFAULT_GAIN=1,n.gain=null==e.gain?n.DEFAULT_GAIN:e.gain,n.seed=e.seed,null!=n.seed)throw new nh("Random seed is not implemented for Orthogonal Initializer yet.");return n}return Kp(e,t),e.prototype.apply=function(t,e){var n=this;return _e(function(){if(2!==t.length)throw new nh("The Orthogonal Initializer does not support non-2D shapes yet.");t[0]*t[1]>2e3&&console.warn("Orthogonal initializer is being called on a matrix with more than 2000 ("+t[0]*t[1]+") elements: Slowness may result.");var e=sf(t[0]>t[1]?[t[1],t[0]]:t,0,1,"float32"),r=lc.gramSchmidt(e);return t[0]>t[1]&&(r=r.transpose()),iu(n.gain,r)})},e.prototype.getConfig=function(){return{gain:this.gain,seed:this.seed}},e.className="Orthogonal",e}(vf);kp.registerClass(Of);var _f={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function Ff(t,e){return void 0===e&&(e={}),fh(t,kp.SerializationMap.getMap().classNameMap,e,"initializer")}function Mf(t){return hh(t)}function zf(t){if("string"==typeof t){var e=t in _f?_f[t]:t;if("GlorotNormal"===e)return new If;if("GlorotUniform"===e)return new kf;if("HeNormal"===e)return new Af;if("HeUniform"===e)return new Rf;if("LeCunNormal"===e)return new Tf;if("LeCunUniform"===e)return new Df;var n={};return n.className=e,n.config={},Ff(n)}return t instanceof vf?t:Ff(t)}var Lf=Object.freeze({zeros:function(){return new yf},ones:function(){return new bf},constant:function(t){return new xf(t)},randomUniform:function(t){return new wf(t)},randomNormal:function(t){return new Nf(t)},truncatedNormal:function(t){return new Cf(t)},identity:function(t){return new Ef(t)},varianceScaling:function(t){return new Sf(t)},glorotUniform:function(t){return new kf(t)},glorotNormal:function(t){return new If(t)},heNormal:function(t){return new Af(t)},heUniform:function(t){return new Rf(t)},leCunNormal:function(t){return new Tf(t)},leCunUniform:function(t){return new Df(t)},orthogonal:function(t){return new Of(t)}}),Pf=0;function Bf(){return Pf++}var Vf={};function Wf(t){return void 0===t&&(t=""),t in Vf||(Vf[t]=0),Vf[t]+=1,t+Vf[t].toString()}function Uf(t){return Array.isArray(t)&&Array.isArray(t[0])}function jf(t){return 0===t.length?[]:Array.isArray(t[0])?t:[t]}function Gf(t){var e;if(Array.isArray(t)){if(1!==t.length)throw new eh("Expected Tensor length to be 1; got "+t.length);e=t[0]}else e=t;return e}function Hf(t){if(Array.isArray(t)&&Array.isArray(t[0])){if(1===t.length)return(t=t)[0];throw new eh("Expected exactly 1 Shape; got "+t.length)}return t}function qf(t){for(var e=0,n=0,r=t;n<r.length;n++){var i=r[n];0===i.shape.length?e+=1:e+=i.shape.reduce(function(t,e){return t*e})}return e}var Kf="Variable",$f=function(){function t(t,e,n,r,i){void 0===e&&(e="float32"),void 0===n&&(n=Kf),void 0===r&&(r=!0),void 0===i&&(i=null),this.dtype=null==e?"float32":e,this.shape=t.shape,this.id=Bf(),n=null==n?Kf:n,this.originalName=Uh(n),this.name=jh(this.originalName),this.trainable_=r,this.constraint=i,this.val=mt(t,this.trainable_,this.name,this.dtype)}return t.prototype.read=function(){return this.assertNotDisposed(),this.val},t.prototype.write=function(t){return this.assertNotDisposed(),function(t,e){if(t.shape.toString()!==e.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(t.shape)+" vs. "+JSON.stringify(e.shape))}(this.val,t),this.val.id!==t.id&&(this.val.assign(t),null!=this.constraint&&this.val.assign(this.constraint.apply(this.val))),this},t.prototype.dispose=function(){this.assertNotDisposed(),this.val.dispose()},t.prototype.assertNotDisposed=function(){if(this.val.isDisposed)throw new Error("LayersVariable "+this.name+" is already disposed.")},Object.defineProperty(t.prototype,"trainable",{get:function(){return this.trainable_},set:function(t){this.trainable_=t,this.val.trainable=t},enumerable:!0,configurable:!0}),t}();function Xf(t){return t.map(function(t){return t.read()})}function Yf(t){t.forEach(function(t){t[0].write(t[1])})}var Jf=function(t){this.dtype=t.dtype,this.shape=t.shape,null!=t.shape?this.ndim=t.shape.length:this.ndim=t.ndim,this.maxNDim=t.maxNDim,this.minNDim=t.minNDim,this.axes=t.axes||{}},Zf=function(t,e,n,r,i,a,o){this.dtype=t,this.shape=e,this.sourceLayer=n,this.inputs=r,this.callArgs=i,this.outputTensorIndex=o,this.id=Bf(),null!=a&&(this.originalName=Uh(a),this.name=jh(this.originalName)),this.rank=e.length},Qf=0,td=function(){function t(t,e){this.callArgs=e,this.id=Qf++,this.outboundLayer=t.outboundLayer,this.inboundLayers=t.inboundLayers,this.nodeIndices=t.nodeIndices,this.tensorIndices=t.tensorIndices,this.inputTensors=t.inputTensors,this.outputTensors=t.outputTensors,this.inputMasks=t.inputMasks,this.outputMasks=t.outputMasks,this.inputShapes=t.inputShapes,this.outputShapes=t.outputShapes;for(var n=0,r=t.inboundLayers;n<r.length;n++){var i=r[n];null!=i&&i.outboundNodes.push(this)}t.outboundLayer.inboundNodes.push(this)}return t.prototype.getConfig=function(){for(var t=[],e=0,n=this.inboundLayers;e<n.length;e++){var r=n[e];null!=r?t.push(r.name):t.push(null)}return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:t,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}},t}(),ed=0,nd=function(t){function e(e){var n=t.call(this)||this;n._callHook=null,n._addedWeightNames=[],n._stateful=!1,n.id=ed++,n.activityRegularizer=null,n.inputSpec=null,n.supportsMasking=!1,n._trainableWeights=[],n._nonTrainableWeights=[],n._losses=[],n._updates=[],n._built=!1,n.inboundNodes=[],n.outboundNodes=[];var r=e.name;if(!r){var i=n.getClassName();r=lh(i)+"_"+Wf(i)}if(n.name=r,n.trainable_=null==e.trainable||e.trainable,null!=e.inputShape||null!=e.batchInputShape){var a=void 0;if(null!=e.batchInputShape)a=e.batchInputShape;else if(null!=e.inputShape){var o=null;null!=e.batchSize&&(o=e.batchSize),a=[o].concat(e.inputShape)}n.batchInputShape=a;var s=e.dtype;null==s&&(s=e.inputDType),null==s&&(s="float32"),n.dtype=s}return null!=e.weights?n.initialWeights=e.weights:n.initialWeights=null,n._refCount=null,n.fastWeightInitDuringBuild=!1,n}return Kp(e,t),e.nodeKey=function(t,e){return t.name+"_ib-"+e.toString()},e.prototype.getNodeAtIndex=function(t,e){if(0===this.inboundNodes.length)throw new th("The layer has never been called and thus has no defined "+e+".");if(this.inboundNodes.length<=t)throw new eh("Asked to get "+e+" at node "+t+", but the layer has only "+this.inboundNodes.length+" inbound nodes.");return this.inboundNodes[t]},e.prototype.getInputAt=function(t){return sh(this.getNodeAtIndex(t,"input").inputTensors)},e.prototype.getOutputAt=function(t){return sh(this.getNodeAtIndex(t,"output").outputTensors)},Object.defineProperty(e.prototype,"input",{get:function(){if(this.inboundNodes.length>1)throw new Qp("Layer "+this.name+' has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use `getInputAt(nodeIndex)` instead.');if(0===this.inboundNodes.length)throw new Qp("Layer "+this.name+" is not connected, no input to return.");return sh(this.getNodeAtIndex(0,"input").inputTensors)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"output",{get:function(){if(0===this.inboundNodes.length)throw new Qp("Layer "+this.name+" has no inbound nodes.");if(this.inboundNodes.length>1)throw new Qp("Layer "+this.name+' has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `getOutputAt(nodeIndex)` instead.');return sh(this.getNodeAtIndex(0,"output").outputTensors)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"losses",{get:function(){return this._losses},enumerable:!0,configurable:!0}),e.prototype.calculateLosses=function(){return this.losses.map(function(t){return t()})},Object.defineProperty(e.prototype,"updates",{get:function(){return this._updates},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"built",{get:function(){return this._built},set:function(t){this._built=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"trainable",{get:function(){return this.trainable_},set:function(t){this._trainableWeights.forEach(function(e){return e.trainable=t}),this.trainable_=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"trainableWeights",{get:function(){return this.trainable_?this._trainableWeights.filter(function(t){return t.trainable}):[]},set:function(t){this._trainableWeights=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){return this.trainable?this._trainableWeights.filter(function(t){return!t.trainable}).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)},set:function(t){this._nonTrainableWeights=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"weights",{get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"stateful",{get:function(){return this._stateful},enumerable:!0,configurable:!0}),e.prototype.resetStates=function(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")},e.prototype.assertInputCompatibility=function(t){if(t=uh(t),null!=this.inputSpec&&0!==this.inputSpec.length){var e=uh(this.inputSpec);if(t.length!==e.length)throw new eh("Layer "+this.name+" expects "+e.length+" inputs, but it received "+t.length+" input tensors. Input received: "+t);for(var n=0;n<t.length;n++){var r=t[n],i=e[n];if(null!=i){var a=r.rank;if(null!=i.ndim&&a!==i.ndim)throw new eh("Input "+n+" is incompatible with layer "+this.name+": expected ndim="+i.ndim+", found ndim="+a);if(null!=i.maxNDim&&a>i.maxNDim)throw new eh("Input "+n+" is incompatible with layer "+this.name+": expected max_ndim="+i.maxNDim+", found ndim="+a);if(null!=i.minNDim&&a<i.minNDim)throw new eh("Input "+n+" is incompatible with layer "+this.name+": expected min_ndim="+i.minNDim+", found ndim="+a+".");if(null!=i.dtype&&r.dtype!==i.dtype)throw new eh("Input "+n+" is incompatible with layer "+this.name+" : expected dtype="+i.dtype+", found dtype="+r.dtype+".");if(i.axes){var o=r.shape;for(var s in i.axes){var u=Number(s),l=i.axes[s],c=u>=0?o[u]:o[o.length+u];if(null!=l&&-1===[l,null].indexOf(c))throw new eh("Input "+n+" is incompatible with layer "+this.name+": expected axis "+u+" of input shape to have value "+l+" but got shape "+o+".")}}if(null!=i.shape)for(var p=0;p<i.shape.length;++p){var h=i.shape[p],f=r.shape[p];if(null!=h&&null!=f&&h!==f)throw new eh("Input "+n+" is incompatible with layer "+this.name+": expected shape="+i.shape+", found shape="+r.shape+".")}}}}},e.prototype.call=function(t,e){return t},e.prototype.invokeCallHook=function(t,e){null!=this._callHook&&this._callHook(t,e)},e.prototype.setCallHook=function(t){this._callHook=t},e.prototype.clearCallHook=function(){this._callHook=null},e.prototype.apply=function(t,e){var n=this;e=e||{},this.assertNotDisposed();for(var r=uh(t),i=!0,a=0,o=r;a<o.length;a++)if(!(o[a]instanceof Zf)){i=!1;break}for(var s=!0,u=0,l=r;u<l.length;u++)if(l[u]instanceof Zf){s=!1;break}if(i===s)throw new eh("Arguments to apply() must be all SymbolicTensors or all Tensors");return Wh(this.name,function(){if(!n.built){n.assertInputCompatibility(t);for(var i=[],a=0,o=uh(t);a<o.length;a++){var u=o[a];i.push(u.shape)}n.build(sh(i)),n.built=!0,n.initialWeights&&n.setWeights(n.initialWeights),null===n._refCount&&s&&(n._refCount=1)}if(n.assertInputCompatibility(t),s){for(var l=[],c=0,p=uh(m=n.call(t,e));c<p.length;c++){var h=p[c];-1!==r.indexOf(h)&&(h=h.clone()),l.push(h)}if(m=sh(l),null!=n.activityRegularizer)throw new nh("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return m}var f=function(t){for(var e=[],n=0,r=t=uh(t);n<r.length;n++){var i=r[n];e.push(i.shape)}return sh(e)}(t),d=n.computeOutputShape(f),m=void 0,g="float32";if(n.warnOnIncompatibleInputShape(Array.isArray(t)?f[0]:f),m=null!=d&&d.length>0&&Array.isArray(d[0])?d.map(function(r,i){return new Zf(g,r,n,uh(t),e,n.name,i)}):new Zf(g,d,n,uh(t),e,n.name),n.addInboundNode(t,m,null,null,f,d,e),n._refCount++,null!=n.activityRegularizer)throw new nh("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return m})},e.prototype.warnOnIncompatibleInputShape=function(t){if(null!=this.batchInputShape)if(t.length!==this.batchInputShape.length)console.warn("The rank of the input tensor provided (shape: "+JSON.stringify(t)+") does not match that of the batchInputShape ("+JSON.stringify(this.batchInputShape)+") of the layer "+this.name);else{var e=!1;this.batchInputShape.forEach(function(n,r){null!=n&&null!=t[r]&&t[r]!==n&&(e=!0)}),e&&console.warn("The shape of the input tensor ("+JSON.stringify(t)+") does not match the expectation of layer "+this.name+": "+JSON.stringify(this.batchInputShape))}},Object.defineProperty(e.prototype,"outputShape",{get:function(){if(null==this.inboundNodes||0===this.inboundNodes.length)throw new Qp("The layer "+this.name+" has never been called and thus has no defined output shape.");for(var t=[],e=0,n=this.inboundNodes;e<n.length;e++){var r=n[e],i=JSON.stringify(r.outputShapes);-1===t.indexOf(i)&&t.push(i)}if(1===t.length){var a=this.inboundNodes[0].outputShapes;return Array.isArray(a)&&Array.isArray(a[0])&&1===a.length?a[0]:a}throw new Qp("The layer "+this.name+' has multiple inbound nodes with different output shapes. Hence the notion of "outut shape" is ill-defined for the layer.')},enumerable:!0,configurable:!0}),e.prototype.countParams=function(){if(!this.built)throw new th("You tried to call countParams() on "+this.name+", but the layer is not built yet. Build it first by calling build(batchInputShape).");return qf(this.weights)},e.prototype.build=function(t){this.built=!0},e.prototype.getWeights=function(t){return void 0===t&&(t=!1),Xf(t?this.trainableWeights:this.weights)},e.prototype.setWeights=function(t){var e=this;_e(function(){var n=e.weights;if(n.length!==t.length)throw new eh('You called setWeights(weights) on layer "'+e.name+'" with a weight list of length '+t.length+", but the layer was expecting "+n.length+" weights. 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Either change `yieldEvery` or remove the callback");return Y.isNumber(r.yieldEvery)&&(r.maybeWait=function(t,e){var n,r=Y.now();return function(){for(var i=[],a=0;a<arguments.length;a++)i[a]=arguments[a];var o=Y.now();return o-r<e?n:(r=o,n=t.apply(void 0,i))}}(r.maybeWait.bind(r),r.yieldEvery)),r.trainBegin=e.onTrainBegin,r.trainEnd=e.onTrainEnd,r.epochBegin=e.onEpochBegin,r.epochEnd=e.onEpochEnd,r.batchBegin=e.onBatchBegin,r.batchEnd=e.onBatchEnd,r.yield=e.onYield,r}return Kp(e,t),e.prototype.maybeWait=function(t,e,n){return Yp(this,void 0,void 0,function(){var r;return Jp(this,function(i){switch(i.label){case 0:return r=[],null==this.yield?[3,2]:[4,od(n)];case 1:i.sent(),r.push(this.yield(t,e,n)),i.label=2;case 2:return r.push(Hp()),[4,Promise.all(r)];case 3:return i.sent(),[2]}})})},e.prototype.onEpochBegin=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){switch(n.label){case 0:return this.currentEpoch=t,null==this.epochBegin?[3,3]:[4,od(e)];case 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Did you set `model.trainable` without calling `model.compile()` afterwards?")},e.prototype.evaluate=function(t,e,n){void 0===n&&(n={});var r=null==n.batchSize?32:n.batchSize;sm(r);var i=this.standardizeUserDataXY(t,e,!0,r);try{var a=i[0].concat(i[1]);this.makeTestFunction();var o=this.testFunction;return sh(this.testLoop(o,a,r,n.verbose,n.steps))}finally{fm(i[0],t),fm(i[1],e)}},e.prototype.evaluateDataset=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){return this.makeTestFunction(),[2,function(t,e,n){return Yp(this,void 0,void 0,function(){var r,i,a,o,s,u,l,c,p,h;return Jp(this,function(f){switch(f.label){case 0:if(r=null!=(n=n||{}).batches,i=t.testFunction,a=[],n.verbose>0)throw new nh("Verbose mode is not implemented yet.");return Y.assert(!r||n.batches>0&&Number.isInteger(n.batches),function(){return"Test loop expects `batches` to be a positive integer, but received "+JSON.stringify(n.batches)}),function(t){return"function"==typeof t.next}(e)?(s=e,[3,3]):[3,1];case 1:return[4,e.iterator()];case 2:s=f.sent(),f.label=3;case 3:o=s,u=0,l=0,c=function(){var e;return Jp(this,function(s){switch(s.label){case 0:return[4,o.next()];case 1:return e=s.sent(),a=_e(function(){if(e.value){var n=rm(t,e.value),r=n.xs,o=n.ys,s=r.concat(o),c=_e(function(){return i(s)});if(Fe(s),0===l)for(var p=0;p<c.length;++p)a.push(an(0));var h=s[0].shape[0],f=function(t){var e=c[t],n=a[t];a[t]=_e(function(){return Hs(a[t],iu(h,e))}),l>0&&Fe(n)};for(p=0;p<c.length;++p)f(p);Fe(c),u+=h,++l}return a}),e.done?(r&&console.warn("Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least `batches` batches (in this case, "+n.batches+" batches). You may need to use the repeat() function when building your dataset."),[2,"break"]):[2]}})},f.label=4;case 4:return!r||l<n.batches?[5,c()]:[3,6];case 5:return"break"===f.sent()?[3,6]:[3,4];case 6:for(p=0;p<a.length;++p)h=a[p],a[p]=Xs(a[p],u),Fe(h);return[2,sh(a)]}})})}(this,t,e)]})})},e.prototype.checkNumSamples=function(t,e,n,r){var i;if(void 0===r&&(r="steps"),null!=n){if(i=null,null!=e)throw new eh("If "+r+" is set, batchSize must be null or undefined.Got batchSize = "+e)}else{if(null==t)throw new eh("Either the input data should have a defined shape, or "+r+" shoud be specified.");i=Array.isArray(t)?t[0].shape[0]:t.shape[0]}return i},e.prototype.execute=function(t,e){if(Array.isArray(e)&&0===e.length)throw new eh("`outputs` is an empty Array, which is not allowed.");var n=Array.isArray(e),r=n?e:[e],i=this.retrieveSymbolicTensors(r),a=new Kd;if(t instanceof lt&&(t=[t]),Array.isArray(t)){if(t.length!==this.inputs.length)throw new eh("The number of inputs provided ("+t.length+") does not match the number of inputs of this model ("+this.inputs.length+").");for(var o=0;o<this.inputs.length;++o)a.add(this.inputs[o],t[o])}else for(var s=0,u=this.inputs;s<u.length;s++){var l=u[s],c=t[l.name];if(null==c)throw new eh("No value is provided for the model's input "+l.name);a.add(l,c)}var p=Yd(i,a);return n?p:p[0]},e.prototype.retrieveSymbolicTensors=function(t){for(var e=ih(null,t.length),n=t.length,r=0,i=this.layers;r<i.length;r++){for(var a=i[r],o=Array.isArray(a.output)?a.output:[a.output],s=o.map(function(t){return t.name}),u=0;u<t.length;++u){var l=s.indexOf(t[u]);if(-1!==l&&(e[u]=o[l],n--),0===n)break}if(0===n)break}if(n>0){var c=[];throw e.forEach(function(e,n){null==e&&c.push(t[n])}),new eh("Cannot find SymbolicTensors for output name(s): "+JSON.stringify(c))}return e},e.prototype.predictLoop=function(t,e,n){var r=this;return void 0===e&&(e=32),void 0===n&&(n=!1),_e(function(){var i=r.checkNumSamples(t);if(n)throw new nh("Verbose predictLoop() is not implemented yet.");for(var a=cm(i,e),o=r.outputs.map(function(t){return[]}),s=function(e){_e(function(){var n=a[e][0],i=a[e][1],o=um(t,n,i),s=[];if(Array.isArray(o))for(var u=0;u<o.length;++u)s.push({key:r.inputs[u],value:o[u]});else s.push({key:r.inputs[0],value:o});var l=new Kd(s);return Yd(r.outputs,l)}).forEach(function(t,e){return o[e].push(t)})},u=0;u<a.length;++u)s(u);return sh(o.map(function(t){return bn(t,0)}))})},e.prototype.predict=function(t,e){void 0===e&&(e={});var n=hm(t);vm(n,this.inputNames,this.feedInputShapes,!1);try{var r=null==e.batchSize?32:e.batchSize;return sm(r),this.predictLoop(n,r)}finally{fm(n,t)}},e.prototype.predictOnBatch=function(t){vm(t,this.inputNames,this.feedInputShapes,!0);var e=(Array.isArray(t)?t[0]:t).shape[0];return this.predictLoop(t,e)},e.prototype.standardizeUserDataXY=function(t,e,n,r){if(void 0===n&&(n=!0),null==this.optimizer_)throw new th("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");for(var i=[],a=0;a<this.feedOutputShapes.length;++a){var o=this.feedOutputShapes[a];this.feedLossFns[a]===Cd?i.push(o.slice(0,o.length-1).concat([1])):i.push(o)}if(function(t,e,n){var r=mh(t.map(function(t){return t.shape[0]}));r.sort();var i=mh(e.map(function(t){return t.shape[0]}));if(i.sort(),r.length>1)throw new eh("All input Tensors (x) should have the same number of samples. Got array shapes: "+JSON.stringify(t.map(function(t){return t.shape})));if(i.length>1)throw new eh("All target Tensors (y) should have the same number of samples. Got array shapes: "+JSON.stringify(e.map(function(t){return t.shape})));if(r.length>0&&i.length>0&&!Y.arraysEqual(r,i))throw new eh("Input Tensors should have the same number of samples as target Tensors. Found "+r[0]+" input sample(s) and "+i[0]+" target sample(s).")}(t=gm(t,this.feedInputNames,this.feedInputShapes,!1,"input"),e=gm(e,this.feedOutputNames,i,!1,"target")),function(t,e,n){for(var r=[bd,Ed,Nd],i=0;i<t.length;++i){var a=t[i],o=e[i],s=n[i];if(null!=o){if(o===Nd&&1===a.shape[a.shape.length-1])throw new eh("You are passing a target array of shape "+a.shape+" while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].");if(-1!==r.indexOf(o))for(var u=a.shape.slice(1),l=s.slice(1),c=0;c<u.length;++c){var p=u[c],h=l[c];if(null!=h&&p!==h)throw new eh("A target Tensor with shape "+a.shape+" was passed for an output of shape "+s+", while using a loss function that expects targets to have the same shape as the output.")}}}}(e,this.feedLossFns,this.feedOutputShapes),this.stateful&&null!=r&&r>0&&t[0].shape[0]%r!=0)throw new eh("In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size "+r+". Found: "+t[0].shape[0]+" sample(s).");return[t,e]},e.prototype.standardizeUserData=function(t,e,n,r,i,a){return void 0===i&&(i=!0),Yp(this,void 0,void 0,function(){var o,s,u,l,c,p,h,f;return Jp(this,function(d){switch(d.label){case 0:if(o=this.standardizeUserDataXY(t,e,i,a),s=o[0],u=o[1],null!=n)throw new Error("sample weight is not supported yet.");if(l=null,null==r)return[3,4];c=Qd(r,this.outputNames),l=[],p=0,d.label=1;case 1:return p<c.length?(f=(h=l).push,[4,tm(u[p],null,c[p])]):[3,4];case 2:f.apply(h,[d.sent()]),d.label=3;case 3:return++p,[3,1];case 4:return[2,[s,u,l]]}})})},e.prototype.testLoop=function(t,e,n,r,i){var a=this;return void 0===r&&(r=0),_e(function(){var o=a.checkNumSamples(e,n,i,"steps"),s=[];if(r>0)throw new nh("Verbose mode is not implemented yet.");if(null!=i)throw new nh("steps mode in testLoop() is not implemented yet");for(var u=cm(o,n),l=on(Jh(0,o)),c=0;c<u.length;++c){var p=u[c][0],h=u[c][1],f=tf(l,p,h-p),d=lm(e,f),m=t(d);if(0===c)for(var g=0;g<m.length;++g)s.push(an(0));for(g=0;g<m.length;++g){var v=m[g];s[g]=Hs(s[g],iu(h-p,v))}}for(g=0;g<s.length;++g)s[g]=Xs(s[g],o);return s})},e.prototype.getDedupedMetricsNames=function(){for(var t=this.metricsNames,e=[],n=0;n<t.length;++n){var r=t[n],i=r;oh(t,r)>1&&(i+="_"+oh(t.slice(0,n),r)),e.push(i)}return e},e.prototype.makeTrainFunction=function(){var t=this;return function(e){var n=[],r=e.slice(0,t.inputs.length),i=e.slice(t.inputs.length,t.inputs.length+t.outputs.length),a=e.slice(t.inputs.length+t.outputs.length,t.inputs.length+2*t.outputs.length),o=[],s=t.collectedTrainableWeights.map(function(t){return t.read()});return[t.optimizer_.minimize(function(){for(var e=[],s=0;s<t.inputs.length;++s)e.push({key:t.inputs[s],value:r[s]});var u,l=new Kd(e),c=Yd(t.outputs,l,{training:!0});for(s=0;s<t.lossFunctions.length;++s){var p=(0,t.lossFunctions[s])(i[s],c[s]);null!=a[s]&&(p=em(p,a[s]));var h=ml(p);n.push(h),u=0===s?p:Hs(u,p)}for(s=0;s<t.metricsTensors.length;++s){var f=void 0;if(t.outputs.length>1&&s<t.outputs.length)f=n[s];else{var d=t.metricsTensors[s][0],m=t.metricsTensors[s][1];f=ml(d(i[m],c[m]))}Me(f),o.push(f)}return u=ml(u),t.calculateLosses().forEach(function(t){u=Hs(u,t)}),u},!0,s)].concat(o)}},e.prototype.makeTestFunction=function(){var t=this;this.testFunction=function(e){return _e(function(){for(var n,r=[],i=e.slice(0,t.inputs.length),a=e.slice(t.inputs.length,t.inputs.length+t.outputs.length),o=[],s=0;s<t.inputs.length;++s)o.push({key:t.inputs[s],value:i[s]});var u=new Kd(o),l=Yd(t.outputs,u);for(s=0;s<t.lossFunctions.length;++s){var c=t.lossFunctions[s],p=ml(c(a[s],l[s]));n=0===s?p:Hs(n,p),r.push(n)}for(s=0;s<t.metricsTensors.length;++s){var h=t.metricsTensors[s][0],f=t.metricsTensors[s][1],d=ml(h(a[f],l[f]));r.push(d)}return r})}},e.prototype.fit=function(t,e,n){return void 0===n&&(n={}),Yp(this,void 0,void 0,function(){return Jp(this,function(r){return[2,pm(this,t,e,n)]})})},e.prototype.fitDataset=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){return[2,am(this,t,e)]})})},e.prototype.trainOnBatch=function(t,e){return Yp(this,void 0,void 0,function(){var n,r,i,a,o,s,u,l,c;return Jp(this,function(p){switch(p.label){case 0:return[4,this.standardizeUserData(t,e)];case 1:n=p.sent(),r=n[0],i=n[1],a=this.makeTrainFunction(),o=a(r.concat(i)),s=[],u=0,l=o,p.label=2;case 2:return u<l.length?[4,l[u].data()]:[3,5];case 3:c=p.sent(),s.push(c[0]),p.label=4;case 4:return u++,[3,2];case 5:return Fe(o),[2,sh(s)]}})})},e.prototype.getNamedWeights=function(t){for(var e=[],n=null!=t&&t.trainableOnly,r=n?this.trainableWeights:this.weights,i=this.getWeights(n),a=0;a<r.length;++a)n&&!r[a].trainable||e.push({name:r[a].originalName,tensor:i[a]});return e},Object.defineProperty(e.prototype,"stopTraining",{get:function(){return this.stopTraining_},set:function(t){this.stopTraining_=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"optimizer",{get:function(){return this.optimizer_},set:function(t){this.optimizer_!==t&&(this.optimizer_=t,this.isOptimizerOwned=!1)},enumerable:!0,configurable:!0}),e.prototype.dispose=function(){var e=t.prototype.dispose.call(this);if(0===e.refCountAfterDispose&&null!=this.optimizer&&this.isOptimizerOwned){var n=Oe().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=n-Oe().numTensors}return e},e.prototype.getLossIdentifiers=function(){var t;if("string"==typeof this.loss)t=lh(this.loss);else if(Array.isArray(this.loss)){for(var e=0,n=this.loss;e<n.length;e++)if("string"!=typeof n[e])throw new Error("Serialization of non-string loss is not supported.");t=this.loss.map(function(t){return lh(t)})}else{var r=Object.keys(this.loss);t={};for(var i=this.loss,a=0,o=r;a<o.length;a++){var s=o[a];if("string"!=typeof i[s])throw new Error("Serialization of non-string loss is not supported.");t[s]=lh(i[s])}}return t},e.prototype.getMetricIdentifiers=function(){if("string"==typeof this.metrics||"function"==typeof this.metrics)return[lh(Pd(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(function(t){return lh(Pd(t))});var t={};for(var e in this.metrics)t[e]=lh(Pd(this.metrics[e]));return t},e.prototype.getTrainingConfig=function(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}},e.prototype.loadTrainingConfig=function(t){if(null!=t.weighted_metrics)throw new Error("Loading weight_metrics is not supported yet.");if(null!=t.loss_weights)throw new Error("Loading loss_weights is not supported yet.");if(null!=t.sample_weight_mode)throw new Error("Loading sample_weight_mode is not supported yet.");var e,n,r=vd(qd(t.optimizer_config));if("string"==typeof t.loss)e=ch(t.loss);else if(Array.isArray(t.loss))e=t.loss.map(function(t){return ch(t)});else if(null!=t.loss)for(var i in e={},t.loss)e[i]=ch(t.loss[i]);if(Array.isArray(t.metrics))n=t.metrics.map(function(t){return ch(t)});else if(null!=t.metrics)for(var i in n={},t.metrics)n[i]=ch(t.metrics[i]);this.compile({loss:e,metrics:n,optimizer:r})},e.prototype.save=function(t,e){return Yp(this,void 0,void 0,function(){var n,r,i,a,o,s,u,l,c,p,h,f,d,m;return Jp(this,function(g){switch(g.label){case 0:if("string"==typeof t){if(0===(n=yp.getSaveHandlers(t)).length)throw new eh("Cannot find any save handlers for URL '"+t+"'");if(n.length>1)throw new eh("Found more than one ("+n.length+") save handlers for URL '"+t+"'");t=n[0]}if(null==t.save)throw new eh("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return[4,yp.encodeWeights(this.getNamedWeights(e))];case 1:return r=g.sent(),i=!1,a=null,o=this.toJSON(a,i),s={modelTopology:o,format:"layers-model",generatedBy:"TensorFlow.js tfjs-layers 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All inputs should only appear once. Found: "+r.inputs.map(function(t){return t.name}));mh(r.outputs).length!==r.outputs.length&&console.warn("The list of outputs passed to the model is redundant. All outputs should only appear once. 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The following previous layers were accessed without issue: '+H);for(var Q=0,tt=Y.outputTensors;Q<tt.length;Q++)k=tt[Q],G.push(k);H.push(s.name)}}r.nodesByDepth=F;for(var et=r.layers.map(function(t){return t.name}),nt=function(t){var e=et.filter(function(e){return e===t}).length;if(1!==e)throw new th('The name "'+t+'" is used '+e+" times in the model. All layer names should be unique. Layer names: "+JSON.stringify(et))},rt=0,it=et;rt<it.length;rt++)nt(it[rt]);return r.outboundNodes=[],r.inboundNodes=[],new td({outboundLayer:r,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:r.inputs,outputTensors:r.outputs,inputMasks:r.inputs.map(function(t){return null}),outputMasks:r.outputs.map(function(t){return null}),inputShapes:r.inputs.map(function(t){return t.shape}),outputShapes:r.outputs.map(function(t){return t.shape})}),r.built=!0,r._refCount=1,r}return Kp(e,t),e.prototype.assertNotDisposed=function(){if(0===this._refCount)throw new Error("Container '"+this.name+"' is already disposed.")},e.prototype.dispose=function(){this.assertNotDisposed();var t={refCountAfterDispose:null,numDisposedVariables:0};if(0==--this._refCount)for(var e=0,n=this.layers;e<n.length;e++){var r=n[e];t.numDisposedVariables+=r.dispose().numDisposedVariables}return t.refCountAfterDispose=this._refCount,t},Object.defineProperty(e.prototype,"trainable",{get:function(){return this.trainable_},set:function(t){this.layers.forEach(function(e){e._trainableWeights.forEach(function(e){return e.trainable=t})}),this.trainable_=t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"trainableWeights",{get:function(){if(this._trainableWeights.length>0)throw new eh("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];for(var t=[],e=0,n=this.layers;e<n.length;e++){var r=n[e];t=t.concat(r.trainableWeights)}return t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){for(var t=[],e=0,n=this.layers;e<n.length;e++){var r=n[e];t.push.apply(t,r.nonTrainableWeights)}if(!this.trainable){for(var i=[],a=0,o=this.layers;a<o.length;a++)r=o[a],i.push.apply(i,r.trainableWeights);return i.concat(t)}return t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"weights",{get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)},enumerable:!0,configurable:!0}),e.prototype.loadWeights=function(t,e){void 0===e&&(e=!0);for(var n={},r=0,i=0,a=this.layers;i<a.length;i++)for(var o=0,s=a[i].weights;o<s.length;o++){var u=s[o];if(null!=n[u.originalName])throw new eh("Duplicate weight name: "+u.originalName);n[u.originalName]=u,r++}var l=[];for(var c in t){if(null!=n[c])l.push([n[c],t[c]]);else if(e)throw new eh("Provided weight data has no target variable: "+c);delete n[c]}if(e){var p=[];for(var h in n)p.push(h);if(p.length>0)throw new eh(p.length+" of "+r+" weights are not set: "+p)}Yf(l)},e.prototype.updatedConfig=function(){var t=this.getConfig(),e={};return e.className=this.getClassName(),e.config=t,e.kerasVersion="tfjs-layers 1.2.9",e.backend="TensorFlow.js",e},e.prototype.toJSON=function(t,e){void 0===e&&(e=!0);var n=function t(e,n){if(null===e||void 0===e)return null;if("string"==typeof e)return lh(e);if("number"==typeof e||"boolean"==typeof e)return e;if(e instanceof Array){for(var r=[],i=e.length,a=0;a<i;++a){var o=e[a];Hd(n,a,o)?r.push(o):r.push(t(o,n))}return r}for(var s={},u=0,l=Object.keys(e);u<l.length;u++){var c=l[u],p=e[c];s[lh(c)]="name"!==c&&"className"!==c||"string"!=typeof p?t(p,c):p}return s}(this.updatedConfig());return e?JSON.stringify(n):n},e.prototype.call=function(t,e){var n=this;return _e(function(){t=uh(t);for(var r=new Kd,i=0;i<n.inputs.length;++i)r.add(n.inputs[i],t[i]);return Yd(n.outputs,r,e)})},e.prototype.computeMask=function(t,e){var n=this;return _e(function(){var r;return t=uh(t),r=null==e?ih(null,t.length):uh(e),n.runInternalGraph(t,r)[1]})},e.prototype.computeOutputShape=function(t){var e=jf(t);if(e.length!==this.inputLayers.length)throw new eh("Invalid inputShape argument "+t+": model has "+this.inputLayers.length+" tensor inputs.");for(var n={},r=0;r<e.length;r++){var i=this.inputLayers[r],a=e[r];n[C=i.name+"_0_0"]=a}var o=Object.keys(this.nodesByDepth).map(function(t){return parseInt(t,10)}).sort(dh);if(o.length>1)for(var s=0,u=o;s<u.length;s++)for(var l=u[s],c=0,p=this.nodesByDepth[l];c<p.length;c++){var h=p[c];if(i=h.outboundLayer,-1===this.inputLayers.map(function(t){return t.id}).indexOf(i.id)){for(var f=[],d=0;d<h.inboundLayers.length;d++){var m=h.inboundLayers[d],g=h.nodeIndices[d],v=h.tensorIndices[d],y=n[C=m.name+"_"+g+"_"+v];f.push(y)}var b=jf(i.computeOutputShape(sh(f))),x=i.inboundNodes.indexOf(h);for(d=0;d<b.length;d++)n[C=i.name+"_"+x+"_"+d]=b[d]}}var w=[],N=[];for(r=0;r<this.outputLayers.length;r++){i=this.outputLayers[r],x=this.outputLayersNodeIndices[r],v=this.outputLayersTensorIndices[r];var C=i.name+"_"+x+"_"+v;N.push(C)}for(r=0;r<N.length;r++){var E=N[r];ah(E in n),w.push(n[E])}return sh(w)},e.prototype.runInternalGraph=function(t,e){null==e&&(e=ih(null,t.length));for(var n={},r=0;r<this.inputs.length;++r){var i=this.inputs[r],a=t[r],o=e[r];n[i.id]=[a,o]}for(var s=0,u=Object.keys(this.nodesByDepth).map(function(t){return parseInt(t,10)}).sort(dh);s<u.length;s++)for(var l=u[s],c=0,p=this.nodesByDepth[l];c<p.length;c++){for(var h=p[c],f=h.outboundLayer,d=h.inputTensors,m=h.outputTensors,g=new Array,v=0,y=d;v<y.length;v++)(i=y[v]).id in n&&g.push(n[i.id]);if(g.length===d.length){var b={},x=void 0,w=void 0,N=void 0,C=void 0;if(null!=h.callArgs&&(b=h.callArgs),1===g.length){var E=g[0],S=E[0],k=E[1];null==b.mask&&(b.mask=k),N=uh(f.call(S,b)),C=uh(f.computeMask(S,k)),x=[S],w=[k]}else x=g.map(function(t){return t[0]}),w=g.map(function(t){return t[1]}),null==b.mask&&(b.mask=w),N=uh(f.call(x,b)),C=uh(f.computeMask(x,w));if(f.activityRegularizer)throw new nh("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(r=0;r<m.length;++r)i=m[r],a=N[r],o=C[r],n[i.id]=[a,o]}}for(var I=[],A=[],R=[],T=0,D=this.outputs;T<D.length;T++){ah((i=D[T]).id in n,"Could not compute output "+i.name+" : "+i.id);var O=n[i.id],_=O[0];o=O[1],R.push(_.shape),I.push(_),A.push(o)}return[I,A,R]},e.prototype.buildNodeConversionMap=function(t){for(var n,r={},i=0,a=this.layers;i<a.length;i++){var o=a[i];n=o instanceof e?1:0;for(var s=0;s<o.inboundNodes.length;s++){var u=e.nodeKey(o,s);this.containerNodes.has(u)&&(r[u]=n,n+=1)}}return r},e.prototype.getLayer=function(t,e){if(null!=e){if(this.layers.length<=e)throw new eh("Was asked to retrieve layer at index "+e+", but model only has "+this.layers.length+" layer(s).");return this.layers[e]}if(null==t)throw new eh("Provide either a layer name or layer index");for(var n=0,r=this.layers;n<r.length;n++){var i=r[n];if(i.name===t)return i}throw new eh("No such layer: "+t)},e.prototype.calculateLosses=function(){var t=this;return _e(function(){for(var n=[],r=0,i=t.layers;r<i.length;r++)for(var a=i[r],o=0;o<a.inboundNodes.length;++o){var s=e.nodeKey(a,o);t.containerNodes.has(s)&&n.push.apply(n,a.calculateLosses())}return n})},e.prototype.getConfig=function(){for(var t={name:this.name},n=this.buildNodeConversionMap(this.layers),r=[],i=0,a=this.layers;i<a.length;i++){for(var o=(x=a[i]).getClassName(),s=x.getConfig(),u=[],l=0;l<x.inboundNodes.length;l++){var c=x.inboundNodes[l],p=e.nodeKey(x,l),h={};if(this.containerNodes.has(p)){if(c.callArgs)try{JSON.stringify(c.callArgs),h=c.callArgs}catch(t){console.warn("Layer "+x.name+" was passed non-serializable keyword arguments: "+c.callArgs+". They will not be included in the serialized model (and thus will be missing at deserialization time)."),h={}}if(c.inboundLayers.length>0){for(var f=[],d=0;d<c.inboundLayers.length;d++){var m=c.inboundLayers[d],g=c.nodeIndices[d],v=c.tensorIndices[d];null==(N=n[e.nodeKey(m,g)])&&(N=0),f.push([m.name,N,v,h])}u.push(f)}}}var y={};y.name=x.name,y.className=o,y.config=s,y.inboundNodes=u,r.push(y)}t.layers=r;var b=[];for(d=0;d<this.inputLayers.length;d++){var x=this.inputLayers[d];g=this.inputLayersNodeIndices[d],p=e.nodeKey(x,g),this.containerNodes.has(p)&&(null!==(N=n[p])&&void 0!==N||(N=0),v=this.inputLayersTensorIndices[d],b.push([x.name,N,v]))}t.inputLayers=b;var w=[];for(d=0;d<this.outputLayers.length;d++){var N;if(x=this.outputLayers[d],g=this.outputLayersNodeIndices[d],p=e.nodeKey(x,g),this.containerNodes.has(p))null!==(N=n[p])&&void 0!==N||(N=0),v=this.outputLayersTensorIndices[d],w.push([x.name,N,v])}return t.outputLayers=w,t},e.fromConfig=function(t,e,n,r){void 0===n&&(n={}),void 0===r&&(r=!1);var i={},a={};function o(t,e){t.name in a?a[t.name].push(e):a[t.name]=[e]}function s(t,e){for(var n,r=[],a=0,s=e;a<s.length;a++){var u=s[a],l=u[0],c=u[1],p=u[2];if(n=null==u[3]?{}:u[3],!(l in i))return void o(t,e);var h=i[l];if(h.inboundNodes.length<=c)return void o(t,e);var f=h.inboundNodes[c];r.push(f.outputTensors[p])}r.length>0&&t.apply(sh(r),n)}function u(t){var n=t.name,a=vd(t,null!=e.customObjects?e.customObjects:{});a.setFastWeightInitDuringBuild(r),i[n]=a,t.inboundNodes.forEach(function(t){if(!(t instanceof Array))throw new eh("Corrupted configuration, expected array for nodeData: "+t);o(a,t)})}for(var l=e.name,c=e.layers,p=0,h=c;p<h.length;p++)u(m=h[p]);for(;!gh(a);)for(var f=0,d=c;f<d.length;f++){var m=d[f];if((R=i[m.name]).name in a){var g=a[R.name];delete a[R.name];for(var v=0,y=g;v<y.length;v++)s(R,y[v])}}for(var b=[],x=[],w=0,N=e.inputLayers;w<N.length;w++){var C=(m=N[w])[0],E=m[1],S=m[2];ah(C in i);var k=(R=i[C]).inboundNodes[E].outputTensors;b.push(k[S])}for(var I=0,A=e.outputLayers;I<A.length;I++){var R;C=(m=A[I])[0],E=m[1],S=m[2],ah(C in i),k=(R=i[C]).inboundNodes[E].outputTensors,x.push(k[S])}return new t({inputs:b,outputs:x,name:l})},Object.defineProperty(e.prototype,"stateful",{get:function(){if(this._stateful)throw new eh("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(var t=0,e=this.layers;t<e.length;t++)if(e[t].stateful)return!0;return!1},enumerable:!0,configurable:!0}),e.prototype.resetStates=function(){var t=this;_e(function(){t.layers.forEach(function(t){t.stateful&&t.resetStates()})})},e}(nd));function bm(t,e){return Yp(this,void 0,void 0,function(){var n;return Jp(this,function(r){if(null==e&&(e={}),"string"==typeof t){if(0===(n=yp.getLoadHandlers(t,e.onProgress)).length)n.push(yp.browserHTTPRequest(t,e));else if(n.length>1)throw new eh("Found more than one ("+n.length+") load handlers for URL '"+t+"'");t=n[0]}return[2,function(t,e,n){return Yp(this,void 0,void 0,function(){var r,i,a,o,s,u,l,c,p;return Jp(this,function(h){switch(h.label){case 0:if(null==n&&(n={}),null==t.load)throw new eh("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");return[4,t.load()];case 1:if(r=h.sent(),null!=(i=r.modelTopology).model_config&&(i=i.model_config),a=null==n.strict||n.strict,o=null!=r.weightData&&null!=r.weightSpecs&&a,s=vd(qd(i),e,o),null!=(u=r.trainingConfig)&&s.loadTrainingConfig(u),null!=r.userDefinedMetadata&&s.setUserDefinedMetadata(r.userDefinedMetadata),null==r.weightData)return[3,4];if(null==r.weightSpecs)throw new eh("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");return l=function(t,e){var n=yp.decodeWeights(t,e),r={},i=[];return e.forEach(function(t){"optimizer"===t.group?i.push({name:t.name,tensor:n[t.name]}):r[t.name]=n[t.name]}),{modelWeights:r,optimizerWeights:i}}(r.weightData,r.weightSpecs),c=l.modelWeights,p=l.optimizerWeights,s.loadWeights(c,a),null!=s.optimizer&&p.length>0?[4,s.optimizer.setWeights(p)]:[3,3];case 2:h.sent(),h.label=3;case 3:Fe(c),Fe(p.map(function(t){return t.tensor})),h.label=4;case 4:return[2,s]}})})}(t,void 0,e)]})})}kp.registerClass(ym);var xm=function(t){function e(e){var n=t.call(this,{inputs:[],outputs:[]})||this;if(e=e||{},n.trainable=!0,n.built=!1,n.name=null!=e.name?e.name:Wf("sequential_"),null!=e.layers)for(var r=0,i=e.layers;r<i.length;r++){var a=i[r];n.add(a)}return n}return Kp(e,t),e.prototype.checkShape=function(t){if(t.inboundNodes[0].outputTensors[0].shape.some(function(t){return t<0}))throw new eh("Negative dimension size caused by adding layer "+t.name+" with input shape ["+t.inboundNodes[0].inputTensors[0].shape+"]")},e.prototype.add=function(t){var n,r=t instanceof e||t instanceof ym;if(r){if(1!==(n=t).outputs.length)throw new eh("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(1!==n.inputs.length)throw new eh("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(0===this.outputs.length){if(0===t.inboundNodes.length){if(null==t.batchInputShape)throw new eh("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");var i=ad({batchShape:t.batchInputShape,dtype:t.dtype,name:t.name+"_input"});t.apply(i)}if(r)this.outputs=n.outputs,this.inputs=n.inputs;else{if(1!==t.inboundNodes.length)throw new eh("A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer "+t.name+" which has "+t.inboundNodes.length+" pre-existing inbound connections.");if(1!==t.inboundNodes[0].outputTensors.length)throw new eh("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(t),this.outputs=[t.inboundNodes[0].outputTensors[0]],this.inputs=function t(e,n,r){if((null==n||null!=r&&r>0)&&(n=e.sourceLayer,r=e.nodeIndex),0===n.inboundNodes.length)return[e];var i=n.inboundNodes[r];if(0===i.inboundLayers.length)return i.inputTensors;for(var a=[],o=0;o<i.inboundLayers.length;o++)for(var s=0,u=t(i.inputTensors[o],i.inboundLayers[o],i.nodeIndices[o]);s<u.length;s++){var l=u[s];-1===a.indexOf(l)&&a.push(l)}return a}(this.outputs[0])}this.inboundNodes=[],new td({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:ih(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(function(t){return t.shape}),outputShapes:this.outputs[0].shape})}else{var a=t.apply(this.outputs[0]);if(Array.isArray(a))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(t),this.outputs=[a],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(t),this.built=!1},e.prototype.pop=function(){if(0===this.layers.length)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),0===this.layers.length)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{var t=this.layers.length-1;this.layers[t].outboundNodes=[],this.outputs=[this.layers[t].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}},e.prototype.call=function(t,e){return null==this.model&&this.build(),this.model.call(t,e)},e.prototype.build=function(t){if(Hf(t),0===this.inputs.length||0===this.outputs.length)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new ym({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0},e.prototype.countParams=function(){return this.built||this.build(),t.prototype.countParams.call(this)},e.prototype.summary=function(e,n,r){void 0===r&&(r=console.log),this.built||this.build(),t.prototype.summary.call(this,e,n,r)},e.prototype.setWeights=function(t){null==this.model&&this.build(),this.model.setWeights(t)},e.prototype.evaluate=function(t,e,n){if(void 0===n&&(n={}),!this.built)throw new th("The model needs to be compiled before being used.");return this.model.evaluate(t,e,n)},e.prototype.evaluateDataset=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){if(!this.built)throw new th("The model needs to be compiled before being used.");return[2,this.model.evaluateDataset(t,e)]})})},e.prototype.predict=function(t,e){return void 0===e&&(e={}),null==this.model&&this.build(),this.model.predict(t,e)},e.prototype.predictOnBatch=function(t){return null==this.model&&this.build(),this.model.predictOnBatch(t)},e.prototype.compile=function(t){this.build(),this.model.compile(t),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames},Object.defineProperty(e.prototype,"optimizer",{get:function(){return null==this.model?void 0:this.model.optimizer},set:function(t){this.model.optimizer=t},enumerable:!0,configurable:!0}),e.prototype.fit=function(t,e,n){return void 0===n&&(n={}),Yp(this,void 0,void 0,function(){return Jp(this,function(r){if(!this.built)throw new th("The model needs to be compiled before being used.");return[2,this.model.fit(t,e,n)]})})},e.prototype.fitDataset=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){if(!this.built)throw new th("The model needs to be compiled before being used.");return[2,this.model.fitDataset(t,e)]})})},e.prototype.trainOnBatch=function(t,e){return Yp(this,void 0,void 0,function(){return Jp(this,function(n){return[2,this.model.trainOnBatch(t,e)]})})},e.fromConfig=function(t,n,r,i){var a;void 0===r&&(r={}),void 0===i&&(i=!1);var o={};if(n instanceof Array){if(null==n[0].className||"Merge"===n[0].className)throw new eh("Legacy serialization format not supported yet.");a=n}else Y.assert(null!=n.layers,function(){return"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."}),a=n.layers,delete n.layers,o=n;var s=new t(o);if(!(s instanceof e))throw new nh("Sequential.fromConfig called on non-Sequential input: "+s);for(var u=0,l=a;u<l.length;u++){var c=vd(l[u],void 0,i);i&&c.setFastWeightInitDuringBuild(!0),s.add(c)}return s},Object.defineProperty(e.prototype,"stopTraining",{get:function(){if(null==this.model)throw new eh("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining},set:function(t){if(null==this.model)throw new eh("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=t},enumerable:!0,configurable:!0}),e.prototype.getConfig=function(){for(var t=[],e=0,n=this.layers;e<n.length;e++){var r=n[e],i={};i.className=r.getClassName(),i.config=r.getConfig(),t.push(i)}return t},e.className="Sequential",e}(ym);function wm(t){return ad(t)}kp.registerClass(xm);var Nm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.getConfig=function(){return{}},e}(kp.Serializable),Cm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t,e){return void 0===e&&(e=1),function(t,e){if(void 0===e&&(e=1),1!==e)throw new nh("Support for alpha values other than 1 ("+e+") is not implemented yet.");return xl(t)}(t,e)},e.className="elu",e}(Nm);kp.registerClass(Cm);var Em=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return El(t)},e.className="selu",e}(Nm);kp.registerClass(Em);var Sm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return Cl(t)},e.className="relu",e}(Nm);kp.registerClass(Sm);var km=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return _e(function(){return tu(6,Cl(t))})},e.className="relu6",e}(Nm);kp.registerClass(km);var Im=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return t},e.className="linear",e}(Nm);kp.registerClass(Im);var Am=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return hs(t)},e.className="sigmoid",e}(Nm);kp.registerClass(Am);var Rm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return function(t){return _e(function(){var e=Hs(.5,iu(.2,t));return Zo(e,0,1)})}(t)},e.className="hardSigmoid",e}(Nm);kp.registerClass(Rm);var Tm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return bs(t)},e.className="softplus",e}(Nm);kp.registerClass(Tm);var Dm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return function(t){return _e(function(){return Xs(t,Go(t).add(1))})}(t)},e.className="softsign",e}(Nm);kp.registerClass(Dm);var Om=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t){return Es(t)},e.className="tanh",e}(Nm);kp.registerClass(Om);var _m=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t,e){return void 0===e&&(e=-1),Rr(t,e)},e.className="softmax",e}(Nm);kp.registerClass(_m);var Fm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t,e){return void 0===e&&(e=-1),Tr(t,e)},e.className="logSoftmax",e}(Nm);function Mm(t){return t.getClassName()}function zm(t,e){return void 0===e&&(e={}),fh(t,kp.SerializationMap.getMap().classNameMap,e,"activation")}function Lm(t){var e;return null==t?zm(e={className:"linear",config:{}}):"string"==typeof t?((e={}).className=t,e.config={},zm(e)):t instanceof Nm?t:zm(t)}function Pm(t){if(null!=t&&"object"!=typeof t)throw new Error("Argument to L1L2 regularizer's constructor is expected to be an object, but received: "+t)}kp.registerClass(Fm);var Bm=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e}(kp.Serializable),Vm=function(t){function e(e){var n=t.call(this)||this;return Pm(e),n.l1=null==e||null==e.l1?.01:e.l1,n.l2=null==e||null==e.l2?.01:e.l2,n.hasL1=0!==n.l1,n.hasL2=0!==n.l2,n}return Kp(e,t),e.prototype.apply=function(t){var e=this;return _e(function(){var n=fn([1]);return e.hasL1&&(n=Hs(n,yl(iu(e.l1,Go(t))))),e.hasL2&&(n=Hs(n,yl(iu(e.l2,cf(t))))),n.asScalar()})},e.prototype.getConfig=function(){return{l1:this.l1,l2:this.l2}},e.fromConfig=function(t,e){return new t({l1:e.l1,l2:e.l2})},e.className="L1L2",e}(Bm);kp.registerClass(Vm);var Wm={l1l2:"L1L2"};function Um(t){return hh(t)}function jm(t,e){return void 0===e&&(e={}),fh(t,kp.SerializationMap.getMap().classNameMap,e,"regularizer")}function Gm(t){return null==t?null:"string"==typeof t?jm({className:t in Wm?Wm[t]:t,config:{}}):t instanceof Bm?t:jm(t)}var Hm=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;return n.supportsMasking=!0,null!=e&&(n.maxValue=e.maxValue),n}return Kp(e,t),e.prototype.call=function(t,e){t=Gf(t);var n=Cl(t);return null!=this.maxValue&&(n=Zo(n,0,this.maxValue)),n},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e={maxValue:this.maxValue},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="ReLU",e}(nd);kp.registerClass(Hm);var qm=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;return n.DEFAULT_ALPHA=.3,null==e&&(e={}),n.alpha=null==e.alpha?n.DEFAULT_ALPHA:e.alpha,n}return Kp(e,t),e.prototype.call=function(t,e){var n=Gf(t);return wl(n,this.alpha)},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e={alpha:this.alpha},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="LeakyReLU",e}(nd);kp.registerClass(qm);var Km=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;if(n.DEFAULT_ALPHA_INITIALIZER="zeros",null==e&&(e={}),n.supportsMasking=!0,n.alphaInitializer=zf(e.alphaInitializer||n.DEFAULT_ALPHA_INITIALIZER),n.alphaRegularizer=Gm(e.alphaRegularizer),n.alphaConstraint=Rh(e.alphaConstraint),null==e.sharedAxes)n.sharedAxes=null;else if(Array.isArray(e.sharedAxes))n.sharedAxes=e.sharedAxes;else{if("number"!=typeof e.sharedAxes)throw new eh("Expected sharedAxes to be a number or an array of numbers, but got "+e.sharedAxes);n.sharedAxes=[e.sharedAxes]}return n}return Kp(e,t),e.prototype.build=function(t){var e=(t=Hf(t)).slice(1);if(null!=this.sharedAxes)for(var n=0,r=this.sharedAxes;n<r.length;n++)e[(a=r[n])-1]=1;this.alpha=this.addWeight("alpha",e,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);var i={};if(null!=this.sharedAxes)for(var a=1;a<t.length;++a)i[a]=t[a];this.inputSpec=[new Jf({ndim:t.length,axes:i})],this.built=!0},e.prototype.call=function(t,e){return t=Gf(t),Nl(t,this.alpha.read())},e.prototype.getConfig=function(){var e={alphaInitializer:Mf(this.alphaInitializer),alphaRegularizer:Um(this.alphaRegularizer),alphaConstraint:Ih(this.alphaConstraint),sharedAxes:this.sharedAxes},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="PReLU",e}(nd);kp.registerClass(Km);var $m=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;if(n.DEFAULT_ALPHA=1,null==e&&(e={}),null!=e.alpha&&e.alpha!==n.DEFAULT_ALPHA)throw new nh("Non-default alpha value ("+e.alpha+") is not supported by the ELU layer yet.");return n.alpha=null==e.alpha?n.DEFAULT_ALPHA:e.alpha,n}return Kp(e,t),e.prototype.call=function(t,e){var n=Gf(t);return xl(n)},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e={alpha:this.alpha},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="ELU",e}(nd);kp.registerClass($m);var Xm=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;return n.DEFAULT_THETA=1,null==e&&(e={}),n.theta=null==e.theta?n.DEFAULT_THETA:e.theta,n}return Kp(e,t),e.prototype.call=function(t,e){var n=Gf(t);return n.mul(Zh(n.greater(this.theta),"float32"))},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e={theta:this.theta},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="ThresholdedReLU",e}(nd);kp.registerClass(Xm);var Ym=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;return n.DEFAULT_AXIS=1,null==e&&(e={}),n.softmax=(new _m).apply,n.axis=null==e.axis?n.DEFAULT_AXIS:e.axis,n}return Kp(e,t),e.prototype.call=function(t,e){var n=Gf(t);return this.softmax(n,this.axis)},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e={axis:this.axis},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Softmax",e}(nd);function Jm(t,e,n){if("number"==typeof t)return ih(t,e);if(t.length!==e)throw new eh("The "+n+" argument must be an integer or tuple of "+e+" integers. Received: "+t.length+" elements.");for(var r=0;r<e;++r){var i=t[r];if(!qh(i))throw new eh("The "+n+" argument must be an integer or tuple of "+e+" integers. Received: "+JSON.stringify(t)+" including a non-integer number "+i)}return t}function Zm(t,e,n,r,i){return void 0===i&&(i=1),null==t?t:(a="same"===n?t:t-(e+(e-1)*(i-1))+1,Math.floor((a+r-1)/r));var a}function Qm(t,e,n,r){if(null==t)return null;if("valid"===r)t=t*e+Yh([n-e,0]);else{if("same"!==r)throw new eh("Unsupport padding mode: "+r+".");t*=e}return t}function tg(t,e){return _e(function(){return zh(e),"channelsFirst"===e?Sl(t,[0,2,3,1]):t})}function eg(t,e){return _e(function(){return zh(e),"channelsFirst"===e?Sl(t,[0,2,3,4,1]):t})}function ng(t,e,n,r,i,a,o,s){return void 0===r&&(r=[1,1]),void 0===i&&(i="valid"),void 0===s&&(s=null),_e(function(){if(null==a&&(a="channelsLast"),zh(a),3!==t.rank&&4!==t.rank)throw new eh("conv2dWithBiasActivation expects input to be of rank 3 or 4, but received "+t.rank+".");if(3!==e.rank&&4!==e.rank)throw new eh("conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received "+t.rank+".");var u=tg(t,a);if("causal"===i)throw new nh("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return u=yc.conv2d({x:u,filter:e,strides:r,pad:"same"===i?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:s}),"channelsFirst"===a&&(u=Sl(u,[0,3,1,2])),u})}kp.registerClass(Ym);var rg=function(t){function e(n,r){var i=t.call(this,r)||this;if(i.bias=null,i.DEFAULT_KERNEL_INITIALIZER="glorotNormal",i.DEFAULT_BIAS_INITIALIZER="zeros",e.verifyArgs(r),i.rank=n,bh(i.rank,"rank"),1!==i.rank&&2!==i.rank&&3!==i.rank)throw new nh("Convolution layer for rank other than 1, 2, or 3 ("+i.rank+") is not implemented yet.");if(i.kernelSize=Jm(r.kernelSize,n,"kernelSize"),i.strides=Jm(null==r.strides?1:r.strides,n,"strides"),i.padding=null==r.padding?"valid":r.padding,Lh(i.padding),i.dataFormat=null==r.dataFormat?"channelsLast":r.dataFormat,zh(i.dataFormat),i.activation=Lm(r.activation),i.useBias=null==r.useBias||r.useBias,i.biasInitializer=zf(r.biasInitializer||i.DEFAULT_BIAS_INITIALIZER),i.biasConstraint=Rh(r.biasConstraint),i.biasRegularizer=Gm(r.biasRegularizer),i.activityRegularizer=Gm(r.activityRegularizer),i.dilationRate=Jm(null==r.dilationRate?1:r.dilationRate,n,"dilationRate"),1===i.rank&&Array.isArray(i.dilationRate)&&1!==i.dilationRate.length)throw new eh("dilationRate must be a number or an array of a single number for 1D convolution, but received "+JSON.stringify(i.dilationRate));if(2===i.rank){if("number"==typeof i.dilationRate)i.dilationRate=[i.dilationRate,i.dilationRate];else if(2!==i.dilationRate.length)throw new eh("dilationRate must be a number or array of two numbers for 2D convolution, but received "+JSON.stringify(i.dilationRate))}else if(3===i.rank)if("number"==typeof i.dilationRate)i.dilationRate=[i.dilationRate,i.dilationRate,i.dilationRate];else if(3!==i.dilationRate.length)throw new eh("dilationRate must be a number or array of three numbers for 3D convolution, but received "+JSON.stringify(i.dilationRate));return i}return Kp(e,t),e.verifyArgs=function(t){if(ah("kernelSize"in t,"required key 'kernelSize' not in config"),"number"!=typeof t.kernelSize&&!yh(t.kernelSize,"number",1,3))throw new eh("BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received "+JSON.stringify(t.kernelSize)+".")},e.prototype.getConfig=function(){var e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Mm(this.activation),useBias:this.useBias,biasInitializer:Mf(this.biasInitializer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),biasConstraint:Ih(this.biasConstraint)},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e}(nd),ig=function(t){function e(n,r){var i=t.call(this,n,r)||this;return i.kernel=null,e.verifyArgs(r),i.filters=r.filters,bh(i.filters,"filters"),i.kernelInitializer=zf(r.kernelInitializer||i.DEFAULT_KERNEL_INITIALIZER),i.kernelConstraint=Rh(r.kernelConstraint),i.kernelRegularizer=Gm(r.kernelRegularizer),i}return Kp(e,t),e.prototype.build=function(t){var e;t=Hf(t);var n="channelsFirst"===this.dataFormat?1:t.length-1;if(null==t[n])throw new eh("The channel dimension of the input should be defined. Found "+t[n]);var r=t[n],i=this.kernelSize.concat([r,this.filters]);this.kernel=this.addWeight("kernel",i,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:(e={},e[n]=r,e)}],this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var e;t=Gf(t);var r=null==n.bias?null:n.bias.read(),i=function(t){return"relu"===t?"relu":"linear"===t?"linear":null}(n.activation.getClassName());if(null!=i&&2===n.rank)e=ng(t,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate,i);else{if(1===n.rank)e=function(t,e,n,r,i,a,o){return void 0===r&&(r=1),void 0===i&&(i="valid"),void 0===o&&(o=1),_e(function(){if(null==a&&(a="channelsLast"),zh(a),3!==t.shape.length)throw new eh("The input of a conv1dWithBias operation should be 3, but is "+t.shape.length+" instead.");if(3!==e.shape.length)throw new eh("The kernel for a conv1dWithBias operation should be 3, but is "+e.shape.length+" instead");if(null!=n&&1!==n.shape.length)throw new eh("The bias for a conv1dWithBias operation should be 1, but is "+e.shape.length+" instead");if("channelsFirst"===a&&(t=Sl(t,[0,2,1])),"causal"===i)throw new nh("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");var s=_u(t,e,r,"same"===i?"same":"valid","NWC",o);return null!=n&&(s=hf(s,n)),s})}(t,n.kernel.read(),r,n.strides[0],n.padding,n.dataFormat,n.dilationRate[0]);else if(2===n.rank)e=ng(t,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate);else{if(3!==n.rank)throw new nh("convolutions greater than 3D are not implemented yet.");e=function(t,e,n,r,i,a,o){return void 0===r&&(r=[1,1,1]),void 0===i&&(i="valid"),_e(function(){if(null==a&&(a="channelsLast"),zh(a),4!==t.rank&&5!==t.rank)throw new eh("conv3dWithBias expects input to be of rank 4 or 5, but received "+t.rank+".");if(4!==e.rank&&5!==e.rank)throw new eh("conv3dWithBias expects kernel to be of rank 4 or 5, but received "+t.rank+".");var s=eg(t,a);if("causal"===i)throw new nh("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return s=Mu(s,e,r,"same"===i?"same":"valid","NDHWC",o),null!=n&&(s=hf(s,n)),"channelsFirst"===a&&(s=Sl(s,[0,4,1,2,3])),s})}(t,n.kernel.read(),r,n.strides,n.padding,n.dataFormat,n.dilationRate)}null!=n.activation&&(e=n.activation.apply(e))}return e})},e.prototype.computeOutputShape=function(t){t=Hf(t);for(var e=[],n="channelsLast"===this.dataFormat?t.slice(1,t.length-1):t.slice(2),r=0;r<n.length;++r){var i=Zm(n[r],this.kernelSize[r],this.padding,this.strides[r],"number"==typeof this.dilationRate?this.dilationRate:this.dilationRate[r]);e.push(i)}var a=[t[0]];return"channelsLast"===this.dataFormat?(a=a.concat(e)).push(this.filters):(a.push(this.filters),a=a.concat(e)),a},e.prototype.getConfig=function(){var e={filters:this.filters,kernelInitializer:Mf(this.kernelInitializer),kernelRegularizer:Um(this.kernelRegularizer),kernelConstraint:Ih(this.kernelConstraint)},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.verifyArgs=function(t){if(!("filters"in t)||"number"!=typeof t.filters||t.filters<1)throw new eh("Convolution layer expected config.filters to be a 'number' > 0 but got "+JSON.stringify(t.filters))},e}(rg),ag=function(t){function e(n){var r=t.call(this,2,n)||this;return e.verifyArgs(n),r}return Kp(e,t),e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return delete e.rank,e},e.verifyArgs=function(t){if("number"!=typeof t.kernelSize&&!yh(t.kernelSize,"number",1,2))throw new eh("Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received "+JSON.stringify(t.kernelSize)+".")},e.className="Conv2D",e}(ig);kp.registerClass(ag);var og=function(t){function e(n){var r=t.call(this,3,n)||this;return e.verifyArgs(n),r}return Kp(e,t),e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return delete e.rank,e},e.verifyArgs=function(t){if("number"!=typeof t.kernelSize&&(!Array.isArray(t.kernelSize)||1!==t.kernelSize.length&&3!==t.kernelSize.length))throw new eh("Conv3D expects config.kernelSize to be number or [number, number, number], but received "+JSON.stringify(t.kernelSize)+".")},e.className="Conv3D",e}(ig);kp.registerClass(og);var sg=function(t){function e(e){var n=t.call(this,e)||this;if(n.inputSpec=[new Jf({ndim:4})],"same"!==n.padding&&"valid"!==n.padding)throw new eh("Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode "+n.padding);return n}return Kp(e,t),e.prototype.build=function(t){var e;if(4!==(t=Hf(t)).length)throw new eh("Input should have rank 4; Received input shape: "+JSON.stringify(t));var n="channelsFirst"===this.dataFormat?1:t.length-1;if(null==t[n])throw new eh("The channel dimension of the inputs should be defined. Found `None`.");var r=t[n],i=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",i,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Jf({ndim:4,axes:(e={},e[n]=r,e)})],this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var e=Gf(t);if(4!==e.shape.length)throw new eh("Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-"+e.shape.length);var r,i,a=e.shape,o=a[0];"channelsFirst"===n.dataFormat?(r=2,i=3):(r=1,i=2);var s=a[r],u=a[i],l=n.kernelSize[0],c=n.kernelSize[1],p=n.strides[0],h=n.strides[1],f=[o,Qm(s,p,l,n.padding),Qm(u,h,c,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(e=Sl(e,[0,2,3,1]));var d=Vu(e,n.kernel.read(),f,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(d=Sl(d,[0,3,1,2])),null!=n.bias&&(d=hf(d,n.bias.read(),n.dataFormat)),null!=n.activation&&(d=n.activation.apply(d)),d})},e.prototype.computeOutputShape=function(t){var e,n,r,i=(t=Hf(t)).slice();"channelsFirst"===this.dataFormat?(e=1,n=2,r=3):(e=3,n=1,r=2);var a=this.kernelSize[0],o=this.kernelSize[1],s=this.strides[0],u=this.strides[1];return i[e]=this.filters,i[n]=Qm(i[n],s,a,this.padding),i[r]=Qm(i[r],u,o,this.padding),i},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return delete e.dilationRate,e},e.className="Conv2DTranspose",e}(ag);kp.registerClass(sg);var ug=function(t){function e(e){return t.call(this,2,e)||this}return Kp(e,t),e.className="SeparableConv2D",e}(function(t){function e(e,n){var r=t.call(this,e,n)||this;if(r.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",r.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",r.depthwiseKernel=null,r.pointwiseKernel=null,null==n.filters)throw new eh("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=n.kernelInitializer||null!=n.kernelRegularizer||null!=n.kernelConstraint)throw new eh("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(null!=n.padding&&"same"!==n.padding&&"valid"!==n.padding)throw new eh("SeparableConv"+r.rank+"D supports only padding modes: 'same' and 'valid', but received "+JSON.stringify(n.padding));return r.depthMultiplier=null==n.depthMultiplier?1:n.depthMultiplier,r.depthwiseInitializer=zf(n.depthwiseInitializer||r.DEFAULT_DEPTHWISE_INITIALIZER),r.depthwiseRegularizer=Gm(n.depthwiseRegularizer),r.depthwiseConstraint=Rh(n.depthwiseConstraint),r.pointwiseInitializer=zf(n.depthwiseInitializer||r.DEFAULT_POINTWISE_INITIALIZER),r.pointwiseRegularizer=Gm(n.pointwiseRegularizer),r.pointwiseConstraint=Rh(n.pointwiseConstraint),r}return Kp(e,t),e.prototype.build=function(t){var e;if((t=Hf(t)).length<this.rank+2)throw new eh("Inputs to SeparableConv"+this.rank+"D should have rank "+(this.rank+2)+", but received input shape: "+JSON.stringify(t));var n="channelsFirst"===this.dataFormat?1:t.length-1;if(null==t[n]||t[n]<0)throw new eh("The channel dimension of the inputs should be defined, but found "+JSON.stringify(t[n]));for(var r=t[n],i=this.kernelSize.concat([r,this.depthMultiplier]),a=[],o=0;o<this.rank;++o)a.push(1);a.push(r*this.depthMultiplier,this.filters),this.depthwiseKernel=this.addWeight("depthwise_kernel",i,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,!0,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.inputSpec=[new Jf({ndim:this.rank+2,axes:(e={},e[n]=r,e)})],this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var e;if(t=Gf(t),1===n.rank)throw new nh("1D separable convolution is not implemented yet.");return 2===n.rank&&("channelsFirst"===n.dataFormat&&(t=Sl(t,[0,2,3,1])),e=Bu(t,n.depthwiseKernel.read(),n.pointwiseKernel.read(),n.strides,n.padding,n.dilationRate,"NHWC")),n.useBias&&(e=hf(e,n.bias.read(),n.dataFormat)),null!=n.activation&&(e=n.activation.apply(e)),"channelsFirst"===n.dataFormat&&(e=Sl(e,[0,3,1,2])),e})},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Mf(this.depthwiseInitializer),e.pointwiseInitializer=Mf(this.pointwiseInitializer),e.depthwiseRegularizer=Um(this.depthwiseRegularizer),e.pointwiseRegularizer=Um(this.pointwiseRegularizer),e.depthwiseConstraint=Ih(this.depthwiseConstraint),e.pointwiseConstraint=Ih(this.pointwiseConstraint),e},e.className="SeparableConv",e}(ig));kp.registerClass(ug);var lg=function(t){function e(n){var r=t.call(this,1,n)||this;return e.verifyArgs(n),r.inputSpec=[{ndim:3}],r}return Kp(e,t),e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return delete e.rank,delete e.dataFormat,e},e.verifyArgs=function(t){if("number"!=typeof t.kernelSize&&!yh(t.kernelSize,"number",1,1))throw new eh("Conv1D expects config.kernelSize to be number or number[] with length 1, but received "+JSON.stringify(t.kernelSize)+".")},e.className="Conv1D",e}(ig);kp.registerClass(lg);var cg=function(t){function e(e){var n=t.call(this,e)||this;return"number"==typeof e.cropping?n.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:"number"==typeof e.cropping[0]?n.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:n.cropping=e.cropping,n.dataFormat=void 0===e.dataFormat?"channelsLast":e.dataFormat,n.inputSpec=[{ndim:4}],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return"channelsFirst"===this.dataFormat?[t[0],t[1],t[2]-this.cropping[0][0]-this.cropping[0][1],t[3]-this.cropping[1][0]-this.cropping[1][1]]:[t[0],t[1]-this.cropping[0][0]-this.cropping[0][1],t[2]-this.cropping[1][0]-this.cropping[1][1],t[3]]},e.prototype.call=function(t,e){var n=this;return _e(function(){return t=Gf(t),"channelsLast"===n.dataFormat?nf(nf(t,n.cropping[0][0],t.shape[1]-n.cropping[0][0]-n.cropping[0][1],2),n.cropping[1][0],t.shape[2]-n.cropping[1][1]-n.cropping[1][0],3):nf(nf(t,n.cropping[0][0],t.shape[2]-n.cropping[0][0]-n.cropping[0][1],3),n.cropping[1][0],t.shape[3]-n.cropping[1][1]-n.cropping[1][0],4)})},e.prototype.getConfig=function(){var e={cropping:this.cropping,dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Cropping2D",e}(nd);kp.registerClass(cg);var pg=function(t){function e(e){var n=t.call(this,e)||this;return n.DEFAULT_SIZE=[2,2],n.inputSpec=[{ndim:4}],n.size=null==e.size?n.DEFAULT_SIZE:e.size,n.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,n}return Kp(e,t),e.prototype.computeOutputShape=function(t){if("channelsFirst"===this.dataFormat){var e=null==t[2]?null:this.size[0]*t[2],n=null==t[3]?null:this.size[1]*t[3];return[t[0],t[1],e,n]}return e=null==t[1]?null:this.size[0]*t[1],n=null==t[2]?null:this.size[1]*t[2],[t[0],e,n,t[3]]},e.prototype.call=function(t,e){var n=this;return _e(function(){var e=Gf(t),r=e.shape;if("channelsFirst"===n.dataFormat){e=Sl(e,[0,2,3,1]);var i=n.size[0]*r[2],a=n.size[1]*r[3],o=e.resizeNearestNeighbor([i,a]);return Sl(o,[0,3,1,2])}return i=n.size[0]*r[1],a=n.size[1]*r[2],e.resizeNearestNeighbor([i,a])})},e.prototype.getConfig=function(){var e={size:this.size,dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="UpSampling2D",e}(nd);kp.registerClass(pg);var hg=function(t){function e(e){var n=t.call(this,2,e)||this;return n.depthwiseKernel=null,n.depthMultiplier=null==e.depthMultiplier?1:e.depthMultiplier,n.depthwiseInitializer=zf(e.depthwiseInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.depthwiseConstraint=Rh(e.depthwiseConstraint),n.depthwiseRegularizer=Gm(e.depthwiseRegularizer),n}return Kp(e,t),e.prototype.build=function(t){if((t=Hf(t)).length<4)throw new eh("Inputs to DepthwiseConv2D should have rank 4. Received input shape: "+JSON.stringify(t)+".");var e="channelsFirst"===this.dataFormat?1:3;if(null==t[e]||t[e]<0)throw new eh("The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not ("+t[e]+").");var n=t[e],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var e=function(t,e,n,r,i,a){return void 0===n&&(n=[1,1]),void 0===r&&(r="valid"),_e(function(){null==i&&(i="channelsLast"),zh(i);var o=tg(t,i);if(4!==t.rank)throw new eh("Input for depthwiseConv2d is required to be 4-D, but is instead "+t.rank+"-D");if(4!==e.rank)throw new eh("depthwiseKernel is required to be 4-D, but is instead "+e.rank+"-D");return o=Pu(o,e,n,"same"===r?"same":"valid","NHWC",a),"channelsFirst"===i&&(o=Sl(o,[0,3,1,2])),o})}(t=Gf(t),n.depthwiseKernel.read(),n.strides,n.padding,n.dataFormat,null);return n.useBias&&(e=hf(e,n.bias.read(),n.dataFormat)),null!=n.activation&&(e=n.activation.apply(e)),e})},e.prototype.computeOutputShape=function(t){t=Hf(t);var e="channelsFirst"===this.dataFormat?t[2]:t[1],n="channelsFirst"===this.dataFormat?t[3]:t[2],r="channelsFirst"===this.dataFormat?t[1]*this.depthMultiplier:t[3]*this.depthMultiplier,i=Zm(e,this.kernelSize[0],this.padding,this.strides[0]),a=Zm(n,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[t[0],r,i,a]:[t[0],i,a,r]},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this);return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Mf(this.depthwiseInitializer),e.depthwiseRegularizer=Um(this.depthwiseRegularizer),e.depthwiseConstraint=Ih(this.depthwiseRegularizer),e},e.className="DepthwiseConv2D",e}(rg);kp.registerClass(hg);var fg=function(t){function e(e){var n=t.call(this,e)||this;return n.rate=Math.max(Math.min(e.rate,1),0),n.noiseShape=e.noiseShape,n.seed=e.seed,n.supportsMasking=!0,n}return Kp(e,t),e.prototype.getNoiseShape=function(t){if(null==this.noiseShape)return this.noiseShape;for(var e=t.shape,n=[],r=0;r<this.noiseShape.length;++r)n.push(null==this.noiseShape[r]?e[r]:this.noiseShape[r]);return n},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t);if(0<n.rate&&n.rate<1){var i=null!=e.training&&e.training,a=n.getNoiseShape(r);return df(function(){return ff(r,n.rate,a,n.seed)},function(){return r},i)}return t})},e.prototype.getConfig=function(){var e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.prototype.dispose=function(){return t.prototype.dispose.call(this)},e.className="Dropout",e}(nd);kp.registerClass(fg);var dg=function(t){function e(e){var n=t.call(this,e)||this;if(n.activation=null,n.useBias=!0,n.kernel=null,n.bias=null,n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_BIAS_INITIALIZER="zeros",null==e.batchInputShape&&null==e.inputShape&&null!=e.inputDim){var r=null;null!=e.batchSize&&(r=e.batchSize),n.batchInputShape=[r,e.inputDim]}return n.units=e.units,bh(n.units,"units"),n.activation=Lm(e.activation),null!=e.useBias&&(n.useBias=e.useBias),n.kernelInitializer=zf(e.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.biasInitializer=zf(e.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelConstraint=Rh(e.kernelConstraint),n.biasConstraint=Rh(e.biasConstraint),n.kernelRegularizer=Gm(e.kernelRegularizer),n.biasRegularizer=Gm(e.biasRegularizer),n.activityRegularizer=Gm(e.activityRegularizer),n.supportsMasking=!0,n.inputSpec=[{minNDim:2}],n}return Kp(e,t),e.prototype.build=function(t){var e,n=(t=Hf(t))[t.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[n,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:(e={},e[-1]=n,e)}],this.built=!0},e.prototype.computeOutputShape=function(t){var e=(t=Hf(t)).slice();return e[e.length-1]=this.units,e},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r,i=Gf(t),a=function(t){return"relu"===t?"relu":"linear"===t?"linear":null}(n.activation.getClassName());return null!=a?r=uf(i,n.kernel.read(),a,n.bias?n.bias.read():null):(r=uf(i,n.kernel.read()),null!=n.bias&&(r=hf(r,n.bias.read())),null!=n.activation&&(r=n.activation.apply(r))),r})},e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),biasInitializer:Mf(this.biasInitializer),kernelRegularizer:Um(this.kernelRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),biasConstraint:Ih(this.biasConstraint)},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Dense",e}(nd);kp.registerClass(dg);var mg=function(t){function e(e){var n=t.call(this,e||{})||this;return n.inputSpec=[{minNDim:3}],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){for(var e=0,n=(t=Hf(t)).slice(1);e<n.length;e++)if(null==n[e])throw new eh('The shape of the input to "Flatten" is not fully defined (got '+t.slice(1)+'). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.');return[t[0],Kh(t,1)]},e.prototype.call=function(t,e){var n=this;return _e(function(){return n.invokeCallHook(t,e),function(t){if(t.rank<=1)throw new eh("batchFlatten requires a minimum rank of 2. Got rank: "+t.rank+".");var e=[t.shape[0],Kh(t.shape,1)];return t.reshape(e)}(Gf(t))})},e.className="Flatten",e}(nd);kp.registerClass(mg);var gg=function(t){function e(e){var n=t.call(this,e)||this;return n.supportsMasking=!0,n.activation=Lm(e.activation),n}return Kp(e,t),e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t);return n.activation.apply(r)})},e.prototype.getConfig=function(){var e={activation:Mm(this.activation)},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Activation",e}(nd);kp.registerClass(gg);var vg=function(t){function e(e){var n=t.call(this,e)||this;return n.n=e.n,n.inputSpec=[{ndim:2}],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return[t[0],this.n,t[1]]},e.prototype.call=function(t,e){var n=this;return _e(function(){return function(t,e){return _e(function(){if(2!==t.shape.length)throw new eh("repeat() expects a rank-2 tensor, but received a rank-"+t.shape.length+" tensor.");return of(Qh(t,1),[1,e,1])})}(t=Gf(t),n.n)})},e.prototype.getConfig=function(){var e={n:this.n},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="RepeatVector",e}(nd);kp.registerClass(vg);var yg=function(t){function e(e){var n=t.call(this,e)||this;n.targetShape=e.targetShape;for(var r=0;r<n.targetShape.length;++r)n.isUnknown(n.targetShape[r])&&(n.targetShape[r]=null);return n}return Kp(e,t),e.prototype.isUnknown=function(t){return t<0||null==t},e.prototype.fixUnknownDimension=function(t,e){for(var n="Total size of new array must be unchanged.",r=e.slice(),i=1,a=null,o=0;o<r.length;++o){var s=r[o];if(this.isUnknown(s)){if(null!==a)throw new eh("Can only specifiy one unknown dimension.");a=o}else i*=s}var u=Kh(t);if(null!==a){if(0===i||u%i!=0)throw new eh(n);r[a]=u/i}else if(u!==i)throw new eh(n);return r},e.prototype.computeOutputShape=function(t){for(var e=!1,n=0;n<t.length;++n)if(this.isUnknown(t[n])){e=!0;break}return e?t.slice(0,1).concat(this.targetShape):t.slice(0,1).concat(this.fixUnknownDimension(t.slice(1),this.targetShape))},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t),i=r.shape,a=i.slice(0,1).concat(n.fixUnknownDimension(i.slice(1),n.targetShape));return r.reshape(a)})},e.prototype.getConfig=function(){var e={targetShape:this.targetShape},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Reshape",e}(nd);kp.registerClass(yg);var bg=function(t){function e(e){var n=t.call(this,e)||this;if(null==e.dims)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error("Permute constructor requires `dims` to be an Array, but received "+e.dims+" instead.");var r=Jh(1,e.dims.length+1);if(!Y.arraysEqual(e.dims.slice().sort(),r))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");return n.dims=e.dims,n.dimsIncludingBatch=[0].concat(n.dims),n.inputSpec=[new Jf({ndim:n.dims.length+1})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){var e=(t=Hf(t)).slice();return this.dims.forEach(function(n,r){e[r+1]=t[n]}),e},e.prototype.call=function(t,e){return Sl(Gf(t),this.dimsIncludingBatch)},e.prototype.getConfig=function(){var e={dims:this.dims},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Permute",e}(nd);kp.registerClass(bg);var xg=function(t){function e(e){var n=t.call(this,null==e?{}:e)||this;return n.supportsMasking=!0,n.maskValue=null!=e?null==e.maskValue?0:e.maskValue:0,n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this),n={maskValue:this.maskValue};return Object.assign(n,e),n},e.prototype.computeMask=function(t,e){var n=Gf(t);return cl(Nu(n,this.maskValue),-1)},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t),i=cl(Nu(r,n.maskValue),-1,!0);return r.mul(i.asType(r.dtype))})},e.className="Masking",e}(nd);kp.registerClass(xg);var wg=function(t){function e(e){var n=t.call(this,e)||this;if(n.embeddings=null,n.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",null==e.batchInputShape&&null==e.inputShape){var r=null;null!=e.batchSize&&(r=e.batchSize),null==e.inputLength?n.batchInputShape=[r,null]:n.batchInputShape=[r].concat(uh(e.inputLength))}return n.inputDim=e.inputDim,bh(n.inputDim,"inputDim"),n.outputDim=e.outputDim,bh(n.outputDim,"outputDim"),n.embeddingsInitializer=zf(e.embeddingsInitializer||n.DEFAULT_EMBEDDINGS_INITIALIZER),n.embeddingsRegularizer=Gm(e.embeddingsRegularizer),n.activityRegularizer=Gm(e.activityRegularizer),n.embeddingsConstraint=Rh(e.embeddingsConstraint),n.maskZero=e.maskZero,n.supportsMasking=e.maskZero,n.inputLength=e.inputLength,n}return Kp(e,t),e.prototype.build=function(t){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0},e.prototype.warnOnIncompatibleInputShape=function(t){},e.prototype.computeMask=function(t,e){var n=this;return _e(function(){return n.maskZero?(t=Gf(t),Nu(t,yn(t))):null})},e.prototype.computeOutputShape=function(t){if(t=Hf(t),null==this.inputLength)return t.concat([this.outputDim]);var e=uh(this.inputLength);if(e.length!==t.length-1)throw new eh('"inputLength" is '+this.inputLength+", but received input shape has shape "+t);for(var n=0,r=0;r<e.length;++r){var i=e[r],a=t[r+1];if(null!=i&&null!=a&&i!==a)throw new eh('"inputLength" is '+this.inputLength+", but received input shape has shape "+t);null==i&&(e[n]=a),n++}return[t[0]].concat(e,[this.outputDim])},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t);return"int32"!==r.dtype&&(r=Zh(r,"int32")),lf(n.embeddings.read(),r.as1D()).reshape(Hf(n.computeOutputShape(r.shape)))})},e.prototype.getConfig=function(){var e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Mf(this.embeddingsInitializer),embeddingsRegularizer:Um(this.embeddingsRegularizer),activityRegularizer:Um(this.activityRegularizer),embeddingsConstraint:Ih(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Embedding",e}(nd);kp.registerClass(wg);var Ng=function(t){function e(e){var n=t.call(this,e||{})||this;return n.supportsMasking=!0,n}return Kp(e,t),e.prototype.mergeFunction=function(t){throw new nh},e.prototype.computeElementwiseOpOutputShape=function(t,e){if(null==t||null==e)return null;if(t.length<e.length)return this.computeElementwiseOpOutputShape(e,t);if(0===e.length)return t;for(var n=t.slice(0,t.length-e.length),r=0;r<e.length;++r){var i=t[t.length-e.length+r],a=e[r];if(null==i||null==a||i<0||a<0)n.push(null);else if(1===i)n.push(a);else if(1===a)n.push(i);else{if(i!==a)throw new eh("Operands could not be broadcast together with shapes "+JSON.stringify(t)+" "+JSON.stringify(e));n.push(i)}}return n},e.prototype.build=function(t){if(Array.isArray(t)&&!Array.isArray(t[0])&&(t=[Hf(t)]),(t=t).length<2)throw new eh("A merge layer should be called on an Array of at least 2 inputs. Got "+t.length+" input(s).");for(var e=[],n=0,r=t;n<r.length;n++)null!=(o=r[n])&&null!==o[0]&&e.push(o[0]);if((e=mh(e)).length>1)throw new eh("Can not merge tensors with different batch sizes. Got tensors with shapes: "+JSON.stringify(t)+".");for(var i=null==t[0]?null:t[0].slice(1),a=1;a<t.length;++a){var o=null==t[a]?null:t[a].slice(1);i=this.computeElementwiseOpOutputShape(i,o)}var s=t.map(function(t){return t.length});-1===t.indexOf(null)&&1===mh(s).length?this.reshapeRequired=!1:this.reshapeRequired=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){if(t=t,n.reshapeRequired){var e=[],r=t.map(function(t){return t.rank});if(-1===r.indexOf(null)){for(var i=Yh(r),a=0,o=t;a<o.length;a++){for(var s=(h=o[a]).rank,u=0;u<i-s;++u)h=Qh(h,1);e.push(h)}return n.mergeFunction(e)}for(var l=!1,c=0,p=t;c<p.length;c++){var h;if(null==(s=(h=p[c]).rank)){var f=h.shape,d=f[0],m=f.slice(1).concat([d]),g=h.reshape([d].concat(Kh(f.slice(1))));g=(g=Sl(g,[1,0])).reshape(m),e.push(g),l=!0}else if(s>1){var v=Jh(1,s).concat([0]);e.push(Sl(h,v)),l=!0}else e.push(h)}var y=n.mergeFunction(e),b=y.rank;if(l)if(null==b){var x=y.shape;m=[d=x[x.length-1]].concat(x.slice(0,x.length-1)),y=Sl(y.reshape([-1,d]),[1,0]).reshape(m)}else b>1&&(v=[b-1].concat(Jh(0,b-1)),y=Sl(y,v));return y}return n.mergeFunction(t)})},e.prototype.computeOutputShape=function(t){var e;e=null==(t=t)[0]?null:t[0].slice(1);for(var n=1;n<t.length;++n){var r=null==t[n]?null:t[n].slice(1);e=this.computeElementwiseOpOutputShape(e,r)}for(var i=[],a=0,o=t;a<o.length;a++)null!=(r=o[a])&&null!==r[0]&&i.push(r[0]);return 1===(i=mh(i)).length?i.concat(e):[null].concat(e)},e.prototype.computeMask=function(t,e){return _e(function(){if(null==e)return null;if(!Array.isArray(e))throw new eh("`mask` should be an Array");if(!Array.isArray(t))throw new eh("`inputs` should be an Array");if(e.length!==t.length)throw new eh("The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths ("+t.length+" vs "+e.length+")");if(e.every(function(t){return null==t}))return null;for(var n=(e=e.map(function(t){return null==t?t:Gn(t,0)}))[0],r=1;r<e.length-1;++r)n=Bs(n,e[r]);return n})},e}(nd),Cg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.mergeFunction=function(t){return _e(function(){for(var e=t[0].clone(),n=1;n<t.length;++n)e=Hs(e,t[n]);return e})},e.className="Add",e}(Ng);kp.registerClass(Cg);var Eg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.mergeFunction=function(t){return _e(function(){for(var e=t[0].clone(),n=1;n<t.length;++n)e=iu(e,t[n]);return e})},e.className="Multiply",e}(Ng);kp.registerClass(Eg);var Sg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.mergeFunction=function(t){return _e(function(){for(var e=t[0].clone(),n=1;n<t.length;++n)e=Hs(e,t[n]);return iu(1/t.length,e)})},e.className="Average",e}(Ng);kp.registerClass(Sg);var kg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.mergeFunction=function(t){return _e(function(){for(var e=t[0],n=1;n<t.length;++n)e=Zs(e,t[n]);return e})},e.className="Maximum",e}(Ng);kp.registerClass(kg);var Ig=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.mergeFunction=function(t){return _e(function(){for(var e=t[0],n=1;n<t.length;++n)e=tu(e,t[n]);return e})},e.className="Minimum",e}(Ng);kp.registerClass(Ig);var Ag=function(t){function e(e){var n=t.call(this,e)||this;return n.DEFAULT_AXIS=-1,null==e&&(e={}),n.axis=null==e.axis?n.DEFAULT_AXIS:e.axis,n.supportsMasking=!0,n.reshapeRequired=!1,n}return Kp(e,t),e.prototype.build=function(t){if(!Array.isArray(t)||!Array.isArray(t[0])||1===t.length)throw new eh("A `Concatenate` layer should be called on a list of at least 2 inputs");for(var e=!0,n=0,r=t=t;n<r.length;n++)if(null!=(c=r[n])){e=!1;break}if(!e){for(var i=[],a=0;a<t.length;++a){var o=t[a].slice();o.splice(this.axis,1);for(var s=!1,u=0,l=i;u<l.length;u++){var c=l[u];if(Y.arraysEqual(c,o)){s=!0;break}}s||i.push(o)}if(i.length>1)throw new eh("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(t))}},e.prototype.mergeFunction=function(t){var e=this;return _e(function(){return rf(t,e.axis)})},e.prototype.computeOutputShape=function(t){if(!Array.isArray(t)||!Array.isArray(t[0]))throw new eh("A `Concatenate` layer should be called on a list of inputs.");for(var e=t,n=e[0].slice(),r=this.axis<0?n.length+this.axis:this.axis,i=0,a=e.slice(1);i<a.length;i++){var o=a[i];if(null==n[r]||null==o[r]){n[r]=null;break}n[r]+=o[r]}return n},e.prototype.computeMask=function(t,e){var n=this;if(null==e)return null;if(!Array.isArray(e))throw new eh("`mask` should be an array for Concatenate");if(!Array.isArray(t))throw new eh("`inputs` should be an array for Concatenate");if(e.length!==t.length)throw new eh("Mismatch in the length of mask ("+e.length+") and the legnth of inputs ("+t.length+")");return _e(function(){var r=!0;if(e.forEach(function(t){null==t||(r=!1)}),r)return null;for(var i=[],a=0;a<t.length;++a)null==e[a]?i.push(vn(t[a]).asType("bool")):e[a].rank<t[a].rank?i.push(Gn(e[a],-1)):i.push(e[a]);var o=bn(i,n.axis);return ll(o,-1,!1)})},e.prototype.getConfig=function(){var e={axis:this.axis},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Concatenate",e}(Ng);function Rg(t,e){for(;t<0;)t+=e;return t}kp.registerClass(Ag);var Tg=function(t){function e(e){var n=t.call(this,e)||this;return n.axes=e.axes,n.normalize=null!=e.normalize&&e.normalize,n.supportsMasking=!0,n.reshapeRequired=!1,n}return Kp(e,t),e.prototype.build=function(t){Y.assert(Array.isArray(t)&&2===t.length&&Array.isArray(t[0])&&Array.isArray(t[1]),function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."});var e=t[0],n=t[1];if(e.length>3||n.length>3)throw new nh("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(e,n);if(e[r[0]]!==n[r[1]])throw new eh("Dimension incompatibility: "+e[r[0]]+" !== "+n[r[1]])},e.prototype.mergeFunction=function(t){if(2!==t.length)throw new eh("A `Dot` layer must be called on exactly 2 inputs, but received "+t.length+" input(s).");var e,n=t[0],r=t[1];return e=Array.isArray(this.axes)?this.axes.map(function(e,n){return Rg(e,t[n].shape.length)}):[Rg(this.axes,n.shape.length),Rg(this.axes,r.shape.length)],this.normalize&&(n=yd(n,e[0]),r=yd(r,e[1])),function(t,e,n){if(t.shape.length>3||e.shape.length>3)throw new nh("batchDot is not implemented for tensors of 4D or higher rank yet");if(Y.assert(t.shape.length>=2,function(){return"batchDot requires the rank of x to be >= 2, but got "+t.shape.length}),Y.assert(t.shape.length>=2,function(){return"batchDot requires the rank of y to be >= 2, but got "+e.shape.length}),"number"==typeof n&&(n=[n,n]),"complex64"===t.dtype||"complex64"===e.dtype)throw new nh("batchDot is not implemented for complex64-type Tensors yet.");var r=t.shape.length,i=e.shape.length;null==n&&(n=[r-1,i-2]);var a=n;return _e(function(){var n,o;if(r>i){n=r-i;for(var s=[],u=0;u<n;++u)s.push(1);e=e.reshape(e.shape.concat(s))}else if(i>r){for(n=i-r,s=[],u=0;u<n;++u)s.push(1);t=t.reshape(t.shape.concat(s))}else n=0;if(2===t.shape.length&&2===e.shape.length)o=a[0]===a[1]?t.mulStrict(e).sum(a[0]):t.transpose([1,0]).mulStrict(e).sum(a[1]);else{var l=a[0]!==t.shape.length-1,c=a[1]===e.shape.length-1;o=t.matMul(e,l,c)}if(n>0){var p,h=[];for(u=p=r>i?r+i-3:r-1;u<p+n;++u)h.push(u);o=o.squeeze(h)}return 1===o.shape.length&&(o=o.expandDims(1)),o})}(n,r,e)},e.prototype.interpretAxes=function(t,e){return Array.isArray(this.axes)?this.axes:[Rg(this.axes,t.length),Rg(this.axes,e.length)]},e.prototype.computeOutputShape=function(t){Y.assert(Array.isArray(t)&&2===t.length&&Array.isArray(t[0])&&Array.isArray(t[1]),function(){return"A `Dot` layer should be called on a list of exactly 2 inputs."});var e=t[0].slice(),n=t[1].slice();if(e.length>3||n.length>3)throw new nh("Dot layer does not support tensors of 4D or higher rank yet.");var r=this.interpretAxes(e,n);e.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);var i=e.concat(n);return 1===i.length&&i.push(1),i},e.prototype.computeMask=function(t,e){return null},e.prototype.getConfig=function(){var e={axes:this.axes,normalize:this.normalize},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="Dot",e}(Ng);kp.registerClass(Tg);var Dg=function(t){function e(e){var n=t.call(this,e)||this;return n.supportsMasking=!0,n.stddev=e.stddev,n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this),n={stddev:this.stddev};return Object.assign(n,e),n},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t);return df(function(){return sf(r.shape,0,n.stddev).add(r)},function(){return r},e.training||!1)})},e.className="GaussianNoise",e}(nd);kp.registerClass(Dg);var Og=function(t){function e(e){var n=t.call(this,e)||this;return n.supportsMasking=!0,n.rate=e.rate,n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this),n={rate:this.rate};return Object.assign(n,e),n},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e);var r=Gf(t);return n.rate>0&&n.rate<1?df(function(){var t=Math.sqrt(n.rate/(1-n.rate));return r.mul(sf(r.shape,1,t))},function(){return r},e.training||!1):r})},e.className="GaussianDropout",e}(nd);kp.registerClass(Og);var _g=function(t){function e(e){var n=t.call(this,e)||this;return n.supportsMasking=!0,n.rate=e.rate,n.noiseShape=e.noiseShape,n}return Kp(e,t),e.prototype._getNoiseShape=function(t){return this.noiseShape||Gf(t).shape},e.prototype.computeOutputShape=function(t){return t},e.prototype.getConfig=function(){var e=t.prototype.getConfig.call(this),n={rate:this.rate};return Object.assign(n,e),n},e.prototype.call=function(t,e){var n=this;return _e(function(){if(n.rate<1&&n.rate>0){var r=n._getNoiseShape(t);return df(function(){var e=Gf(t),i=-1.7580993408473766,a=mu(nr(r),n.rate);a=Zh(a,"float32");var o=Math.pow((1-n.rate)*(1+n.rate*Math.pow(i,2)),-.5),s=-o*i*n.rate;return e.mul(a).add(a.add(-1).mul(i)).mul(o).add(s)},function(){return Gf(t)},e.training||!1)}return t})},e.className="AlphaDropout",e}(nd);function Fg(t,e,n,r,i,a){var o;if(void 0===a&&(a=.001),2===t.rank)o=zs(t,e,n,r,i,a);else if(3===t.rank)o=Ls(t,e,n,r,i,a);else{if(4!==t.rank)throw new nh("batchNormalization is not implemented for array of rank "+t.rank+" yet");o=Ps(t,e,n,r,i,a)}return o}function Mg(t,e,n,r,i){return void 0===i&&(i=.001),Y.arraysEqual(r.slice().sort(),Jh(0,t.rank-1))?function(t,e,n,r,i){return void 0===i&&(i=.001),_e(function(){var a=vl(t,r),o=a.mean,s=a.variance;return[Fg(t,o,s,n,e,i),o,s]})}(t,e,n,r,i):function(t,e,n,r,i){return void 0===i&&(i=.001),_e(function(){for(var a=vl(t,r),o=a.mean,s=a.variance,u=[],l=0,c=Jh(0,t.rank);l<c.length;l++){var p=c[l];-1!==r.indexOf(p)?u.push(1):u.push(t.shape[p])}var h=o.reshape(u),f=s.reshape(u),d=null==e?null:e.reshape(u),m=null==n?null:n.reshape(u);return[Fg(t,h,f,m,d,i),o,s]})}(t,e,n,r,i)}kp.registerClass(_g);var zg=function(t){function e(e){var n=this;return null==e&&(e={}),(n=t.call(this,e)||this).supportsMasking=!0,n.axis=null==e.axis?-1:e.axis,n.momentum=null==e.momentum?.99:e.momentum,n.epsilon=null==e.epsilon?.001:e.epsilon,n.center=null==e.center||e.center,n.scale=null==e.scale||e.scale,n.betaInitializer=zf(e.betaInitializer||"zeros"),n.gammaInitializer=zf(e.gammaInitializer||"ones"),n.movingMeanInitializer=zf(e.movingMeanInitializer||"zeros"),n.movingVarianceInitializer=zf(e.movingVarianceInitializer||"ones"),n.betaConstraint=Rh(e.betaConstraint),n.gammaConstraint=Rh(e.gammaConstraint),n.betaRegularizer=Gm(e.betaRegularizer),n.gammaRegularizer=Gm(e.gammaRegularizer),n}return Kp(e,t),e.prototype.build=function(t){var e;t=Hf(t);var n=this.axis>=0?this.axis:this.axis+t.length,r=t[n];if(null==r)throw new eh("Axis "+n+" of input tensor should have a defined dimension but the layer received an input with shape "+JSON.stringify(t)+".");this.inputSpec=[new Jf({ndim:t.length,axes:(e={},e[n]=r,e)})];var i=[r];this.scale&&(this.gamma=this.addWeight("gamma",i,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",i,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",i,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",i,null,this.movingVarianceInitializer,null,!1),this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var r=null!=e.training&&e.training,i=Gf(t),a=i.shape,o=a.length,s=Jh(0,o),u=n.axis>=0?n.axis:n.axis+o;s.splice(u,1);var l=ih(1,o);l[u]=a[u];var c=s.slice();c.sort();var p=!Y.arraysEqual(c,Jh(0,o).slice(0,o-1));if(!r)return function(){if(p){var t=n.movingMean.read().reshape(l),e=n.movingVariance.read().reshape(l),r=n.center?n.beta.read().reshape(l):null,a=n.scale?n.gamma.read().reshape(l):null;return Fg(i,t,e,r,a,n.epsilon)}return Fg(i,n.movingMean.read(),n.movingVariance.read(),null==n.beta?null:n.beta.read(),null==n.gamma?null:n.gamma.read(),n.epsilon)}();var h=Mg(i,n.gamma.read(),n.beta.read(),s,n.epsilon),f=h[0],d=h[1],m=h[2],g=function(t,e,n){_e(function(){var r=1-n,i=t.read(),a=i.sub(e).mul(r);t.write(i.sub(a))})};return g(n.movingMean,d,n.momentum),g(n.movingVariance,m,n.momentum),f})},e.prototype.getConfig=function(){var e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Mf(this.betaInitializer),gammaInitializer:Mf(this.gammaInitializer),movingMeanInitializer:Mf(this.movingMeanInitializer),movingVarianceInitializer:Mf(this.movingVarianceInitializer),betaRegularizer:Um(this.betaRegularizer),gammaRegularizer:Um(this.gammaRegularizer),betaConstraint:Ih(this.betaConstraint),gammaConstraint:Ih(this.gammaConstraint)},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="BatchNormalization",e}(nd);kp.registerClass(zg);var Lg=function(t){function e(e){var n=this;if(null==e&&(e={}),(n=t.call(this,e)||this).dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,null==e.padding)n.padding=[[1,1],[1,1]];else if("number"==typeof e.padding)n.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,2!==e.padding.length)throw new eh("ZeroPadding2D expects padding to be a length-2 array, but received a length-"+e.padding.length+" array.");var r=void 0,i=void 0;if("number"==typeof e.padding[0])r=[e.padding[0],e.padding[0]],i=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,2!==e.padding[0].length)throw new eh("ZeroPadding2D expects height padding to be a length-2 array, but received a length-"+e.padding[0].length+" array.");if(r=e.padding[0],2!==e.padding[1].length)throw new eh("ZeroPadding2D expects width padding to be a length-2 array, but received a length-"+e.padding[1].length+" array.");i=e.padding[1]}n.padding=[r,i]}return n.inputSpec=[new Jf({ndim:4})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){var e,n;return t=Hf(t),"channelsFirst"===this.dataFormat?(e=null!=t[2]&&t[2]>=0?t[2]+this.padding[0][0]+this.padding[0][1]:null,n=null!=t[3]&&t[3]>=0?t[3]+this.padding[1][0]+this.padding[1][1]:null,[t[0],t[1],e,n]):(e=null!=t[1]&&t[1]>=0?t[1]+this.padding[0][0]+this.padding[0][1]:null,n=null!=t[2]&&t[2]>=0?t[2]+this.padding[1][0]+this.padding[1][1]:null,[t[0],e,n,t[3]])},e.prototype.call=function(t,e){var n=this;return _e(function(){return function(t,e,n){return _e(function(){if(4!==t.rank)throw new eh("temporalPadding expects input tensor to be 4-D, but received a "+t.rank+"-D tensor.");if(null==e&&(e=[[1,1],[1,1]]),2!==e.length||2!==e[0].length||2!==e[1].length)throw new eh("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(null==n&&(n="channelsLast"),"channelsLast"!==n&&"channelsFirst"!==n)throw new eh("Unknown data format: "+n+". Supported data formats are 'channelsLast' and 'channelsFirst.");var r;return r="channelsFirst"===n?[[0,0],[0,0],e[0],e[1]]:[[0,0],e[0],e[1],[0,0]],$n(t,r)})}(Gf(t),n.padding,n.dataFormat)})},e.prototype.getConfig=function(){var e={padding:this.padding,dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="ZeroPadding2D",e}(nd);function Pg(t,e,n,r,i,a){return _e(function(){var o;zh(i),Ph(a),Lh(r),null==n&&(n=[1,1]),null==r&&(r="valid"),null==i&&(i="channelsLast"),null==a&&(a="max"),t=tg(t,i);var s="same"===r?"same":"valid";return o="max"===a?Zu(t,e,n,s):Qu(t,e,n,s),"channelsFirst"===i&&(o=Sl(o,[0,3,1,2])),o})}function Bg(t,e,n,r,i,a){return _e(function(){var o;zh(i),Ph(a),Lh(r),null==n&&(n=[1,1,1]),null==r&&(r="valid"),null==i&&(i="channelsLast"),null==a&&(a="max"),t=eg(t,i);var s="same"===r?"same":"valid";return o="max"===a?el(t,e,n,s):nl(t,e,n,s),"channelsFirst"===i&&(o=Sl(o,[0,4,1,2,3])),o})}kp.registerClass(Lg);var Vg=function(t){function e(e){var n=this;if(null==e.poolSize&&(e.poolSize=2),n=t.call(this,e)||this,"number"==typeof e.poolSize)n.poolSize=[e.poolSize];else{if(!Array.isArray(e.poolSize)||1!==e.poolSize.length||"number"!=typeof e.poolSize[0])throw new eh("poolSize for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(e.poolSize));n.poolSize=e.poolSize}if(bh(n.poolSize,"poolSize"),null==e.strides)n.strides=n.poolSize;else if("number"==typeof e.strides)n.strides=[e.strides];else{if(!Array.isArray(e.strides)||1!==e.strides.length||"number"!=typeof e.strides[0])throw new eh("strides for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(e.strides));n.strides=e.strides}return bh(n.strides,"strides"),n.padding=null==e.padding?"valid":e.padding,Lh(n.padding),n.inputSpec=[new Jf({ndim:3})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){var e=Zm((t=Hf(t))[1],this.poolSize[0],this.padding,this.strides[0]);return[t[0],e,t[2]]},e.prototype.call=function(t,e){var n=this;return _e(function(){n.invokeCallHook(t,e),t=Qh(Gf(t),2);var r=n.poolingFunction(Gf(t),[n.poolSize[0],1],[n.strides[0],1],n.padding,"channelsLast");return ar(r,[2])})},e.prototype.getConfig=function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e}(nd),Wg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Pg(t,e,n,r,i,"max")},e.className="MaxPooling1D",e}(Vg);kp.registerClass(Wg);var Ug=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Pg(t,e,n,r,i,"avg")},e.className="AveragePooling1D",e}(Vg);kp.registerClass(Ug);var jg=function(t){function e(e){var n=this;if(null==e.poolSize&&(e.poolSize=[2,2]),(n=t.call(this,e)||this).poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],null==e.strides)n.strides=n.poolSize;else if(Array.isArray(e.strides)){if(2!==e.strides.length)throw new eh("If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length "+e.strides.length+".");n.strides=e.strides}else n.strides=[e.strides,e.strides];return bh(n.poolSize,"poolSize"),bh(n.strides,"strides"),n.padding=null==e.padding?"valid":e.padding,n.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,zh(n.dataFormat),Lh(n.padding),n.inputSpec=[new Jf({ndim:4})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){t=Hf(t);var e="channelsFirst"===this.dataFormat?t[2]:t[1],n="channelsFirst"===this.dataFormat?t[3]:t[2];return e=Zm(e,this.poolSize[0],this.padding,this.strides[0]),n=Zm(n,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[t[0],t[1],e,n]:[t[0],e,n,t[3]]},e.prototype.call=function(t,e){var n=this;return _e(function(){return n.invokeCallHook(t,e),n.poolingFunction(Gf(t),n.poolSize,n.strides,n.padding,n.dataFormat)})},e.prototype.getConfig=function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e}(nd),Gg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Pg(t,e,n,r,i,"max")},e.className="MaxPooling2D",e}(jg);kp.registerClass(Gg);var Hg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Pg(t,e,n,r,i,"avg")},e.className="AveragePooling2D",e}(jg);kp.registerClass(Hg);var qg=function(t){function e(e){var n=this;if(null==e.poolSize&&(e.poolSize=[2,2,2]),(n=t.call(this,e)||this).poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],null==e.strides)n.strides=n.poolSize;else if(Array.isArray(e.strides)){if(3!==e.strides.length)throw new eh("If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length "+e.strides.length+".");n.strides=e.strides}else n.strides=[e.strides,e.strides,e.strides];return bh(n.poolSize,"poolSize"),bh(n.strides,"strides"),n.padding=null==e.padding?"valid":e.padding,n.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,zh(n.dataFormat),Lh(n.padding),n.inputSpec=[new Jf({ndim:5})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){t=Hf(t);var e="channelsFirst"===this.dataFormat?t[2]:t[1],n="channelsFirst"===this.dataFormat?t[3]:t[2],r="channelsFirst"===this.dataFormat?t[4]:t[3];return e=Zm(e,this.poolSize[0],this.padding,this.strides[0]),n=Zm(n,this.poolSize[1],this.padding,this.strides[1]),r=Zm(r,this.poolSize[2],this.padding,this.strides[2]),"channelsFirst"===this.dataFormat?[t[0],t[1],e,n,r]:[t[0],e,n,r,t[4]]},e.prototype.call=function(t,e){var n=this;return _e(function(){return n.invokeCallHook(t,e),n.poolingFunction(Gf(t),n.poolSize,n.strides,n.padding,n.dataFormat)})},e.prototype.getConfig=function(){var e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e}(nd),Kg=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Bg(t,e,n,r,i,"max")},e.className="MaxPooling3D",e}(qg);kp.registerClass(Kg);var $g=function(t){function e(e){return t.call(this,e)||this}return Kp(e,t),e.prototype.poolingFunction=function(t,e,n,r,i){return zh(i),Lh(r),Bg(t,e,n,r,i,"avg")},e.className="AveragePooling3D",e}(qg);kp.registerClass($g);var Xg=function(t){function e(e){var n=t.call(this,e)||this;return n.inputSpec=[new Jf({ndim:3})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return[t[0],t[2]]},e.prototype.call=function(t,e){throw new nh},e}(nd),Yg=function(t){function e(e){return t.call(this,e||{})||this}return Kp(e,t),e.prototype.call=function(t,e){return _e(function(){var e=Gf(t);return ml(e,1)})},e.className="GlobalAveragePooling1D",e}(Xg);kp.registerClass(Yg);var Jg=function(t){function e(e){return t.call(this,e||{})||this}return Kp(e,t),e.prototype.call=function(t,e){return _e(function(){var e=Gf(t);return dl(e,1)})},e.className="GlobalMaxPooling1D",e}(Xg);kp.registerClass(Jg);var Zg=function(t){function e(e){var n=t.call(this,e)||this;return n.dataFormat=null==e.dataFormat?"channelsLast":e.dataFormat,zh(n.dataFormat),n.inputSpec=[new Jf({ndim:4})],n}return Kp(e,t),e.prototype.computeOutputShape=function(t){return t=t,"channelsLast"===this.dataFormat?[t[0],t[3]]:[t[0],t[1]]},e.prototype.call=function(t,e){throw new nh},e.prototype.getConfig=function(){var e={dataFormat:this.dataFormat},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e}(nd),Qg=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.call=function(t,e){var n=this;return _e(function(){var e=Gf(t);return"channelsLast"===n.dataFormat?ml(e,[1,2]):ml(e,[2,3])})},e.className="GlobalAveragePooling2D",e}(Zg);kp.registerClass(Qg);var tv=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.call=function(t,e){var n=this;return _e(function(){var e=Gf(t);return"channelsLast"===n.dataFormat?dl(e,[1,2]):dl(e,[2,3])})},e.className="GlobalMaxPooling2D",e}(Zg);function ev(t,e,n,r){if(Array.isArray(t)){if(null!=e||null!=n)throw new eh("When inputs is an array, neither initialState or constants should be provided");null!=r&&(n=t.slice(t.length-r,t.length),t=t.slice(0,t.length-r)),t.length>1&&(e=t.slice(1,t.length)),t=t[0]}function i(t){return null==t||Array.isArray(t)?t:[t]}return{inputs:t,initialState:e=i(e),constants:n=i(n)}}function nv(t,e,n,r,i,a,o,s){return void 0===r&&(r=!1),void 0===o&&(o=!1),void 0===s&&(s=!1),_e(function(){var u=e.shape.length;if(u<3)throw new eh("Input should be at least 3D, but is "+u+"D.");var l=[1,0].concat(Jh(2,u));if(e=Sl(e,l),null!=a)throw new nh("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),null!=i&&((i=i.asType("bool").asType("float32")).rank===u-1&&(i=Gn(i,-1)),i=Sl(i,l)),r&&(e=Hu(e,0),null!=i&&(i=Hu(i,0)));var c,p,h=[],f=n,d=e.shape[0],m=lr(e);null!=i&&(p=lr(i));for(var g,v=function(e){var n=m[e],r=_e(function(){return t(n,f)});if(null==i)c=r[0],f=r[1];else{var a=_e(function(){var t=p[e],n=vn(t).sub(t);return{output:r[0].mul(t).addStrict(f[0].mul(n)),newStates:f.map(function(e,i){return r[1][i].mul(t).addStrict(e.mul(n))})}});c=a.output,f=a.newStates}s&&h.push(c)},y=0;y<d;++y)v(y);return s&&(g=or(h,1)),[c,g,f]})}kp.registerClass(tv);var rv=function(t){function e(e){var n,r=t.call(this,e)||this;if(null==e.cell)throw new eh("cell property is missing for the constructor of RNN.");if(null==(n=Array.isArray(e.cell)?new pv({cells:e.cell}):e.cell).stateSize)throw new eh("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");return r.cell=n,r.returnSequences=null!=e.returnSequences&&e.returnSequences,r.returnState=null!=e.returnState&&e.returnState,r.goBackwards=null!=e.goBackwards&&e.goBackwards,r._stateful=null!=e.stateful&&e.stateful,r.unroll=null!=e.unroll&&e.unroll,r.supportsMasking=!0,r.inputSpec=[new Jf({ndim:3})],r.stateSpec=null,r.states_=null,r.numConstants=null,r.keptStates=[],r}return Kp(e,t),e.prototype.getStates=function(){return null==this.states_?Jh(0,Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1).map(function(t){return null}):this.states_},e.prototype.setStates=function(t){this.states_=t},e.prototype.computeOutputShape=function(t){Uf(t)&&(t=t[0]),t=t;var e=this.cell.stateSize;Array.isArray(e)||(e=[e]);var n,r=e[0];if(n=this.returnSequences?[t[0],t[1],r]:[t[0],r],this.returnState){for(var i=[],a=0,o=e;a<o.length;a++){var s=o[a];i.push([t[0],s])}return[n].concat(i)}return n},e.prototype.computeMask=function(t,e){var n=this;return _e(function(){Array.isArray(e)&&(e=e[0]);var t=n.returnSequences?e:null;if(n.returnState){var r=n.states.map(function(t){return null});return[t].concat(r)}return t})},Object.defineProperty(e.prototype,"states",{get:function(){if(null==this.states_){for(var t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,e=[],n=0;n<t;++n)e.push(null);return e}return this.states_},set:function(t){this.states_=t},enumerable:!0,configurable:!0}),e.prototype.build=function(t){if(null!=this.numConstants)throw new nh("Constants support is not implemented in RNN yet.");Uf(t)&&(t=t[0]),t=t;var e=this.stateful?t[0]:null,n=t[t.length-1];this.inputSpec[0]=new Jf({shape:[e,null,n]});var r,i=[t[0]].concat(t.slice(2));if(this.cell.build(i),r=Array.isArray(this.cell.stateSize)?this.cell.stateSize:[this.cell.stateSize],null!=this.stateSpec){if(!Y.arraysEqual(this.stateSpec.map(function(t){return t.shape[t.shape.length-1]}),r))throw new eh("An initialState was passed that is not compatible with cell.stateSize. Received stateSpec="+this.stateSpec+"; However cell.stateSize is "+this.cell.stateSize)}else this.stateSpec=r.map(function(t){return new Jf({shape:[null,t]})});this.stateful&&this.resetStates()},e.prototype.resetStates=function(t,e){var n=this;void 0===e&&(e=!1),_e(function(){if(!n.stateful)throw new Qp("Cannot call resetStates() on an RNN Layer that is not stateful.");var r=n.inputSpec[0].shape[0];if(null==r)throw new eh("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==n.states_)Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map(function(t){return fn([r,t])}):n.states_=[fn([r,n.cell.stateSize])];else if(null==t)Fe(n.states_),null!=n.keptStates&&(Fe(n.keptStates),n.keptStates=[]),Array.isArray(n.cell.stateSize)?n.states_=n.cell.stateSize.map(function(t){return fn([r,t])}):n.states_[0]=fn([r,n.cell.stateSize]);else{if(Array.isArray(t)||(t=[t]),t.length!==n.states_.length)throw new eh("Layer "+n.name+" expects "+n.states_.length+" state(s), but it received "+t.length+" state value(s). Input received: "+t);!0===e?n.keptStates.push(n.states_.slice()):Fe(n.states_);for(var i=0;i<n.states_.length;++i){var a=t[i],o=Array.isArray(n.cell.stateSize)?n.cell.stateSize[i]:n.cell.stateSize,s=[r,o];if(!Y.arraysEqual(a.shape,s))throw new eh("State "+i+" is incompatible with layer "+n.name+": expected shape="+s+", received shape="+a.shape);n.states_[i]=a}}n.states_=n.states_.map(function(t){return Me(t.clone())})})},e.prototype.apply=function(e,n){var r=null==n?null:n.initialState,i=null==n?null:n.constants;null==n&&(n={});var a=ev(e,r,i,this.numConstants);e=a.inputs,r=a.initialState,i=a.constants;var o=[],s=[];if(null!=r){n.initialState=r,o=o.concat(r),this.stateSpec=[];for(var u=0,l=r;u<l.length;u++){var c=l[u];this.stateSpec.push(new Jf({shape:c.shape}))}s=s.concat(this.stateSpec)}if(null!=i&&(n.constants=i,o=o.concat(i),this.numConstants=i.length),o[0]instanceof Zf){var p=[e].concat(o),h=this.inputSpec.concat(s),f=this.inputSpec;this.inputSpec=h;var d=t.prototype.apply.call(this,p,n);return this.inputSpec=f,d}return t.prototype.apply.call(this,e,n)},e.prototype.call=function(t,e){var n=this;return _e(function(){var r=null==e?null:e.mask,i=null==e?null:e.training,a=null==e?null:e.initialState;t=Gf(t),null==a&&(a=n.stateful?n.states_:n.getInitialState(t));var o=Array.isArray(n.cell.stateSize)?n.cell.stateSize.length:1;if(a.length!==o)throw new eh("RNN Layer has "+o+" state(s) but was passed "+a.length+" initial state(s).");n.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");var s={training:i},u=nv(function(t,e){var r=n.cell.call([t].concat(e),s);return[r[0],r.slice(1)]},t,a,n.goBackwards,r,null,n.unroll,n.returnSequences),l=u[0],c=u[1],p=u[2];n.stateful&&n.resetStates(p,i);var h=n.returnSequences?c:l;return n.returnState?[h].concat(p):h})},e.prototype.getInitialState=function(t){var e=this;return _e(function(){var n=fn(t.shape);return n=Qh(n=yl(n,[1,2])),Array.isArray(e.cell.stateSize)?e.cell.stateSize.map(function(t){return t>1?of(n,[1,t]):n}):e.cell.stateSize>1?[of(n,[1,e.cell.stateSize])]:[n]})},Object.defineProperty(e.prototype,"trainableWeights",{get:function(){return this.trainable?this.cell.trainableWeights:[]},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights},enumerable:!0,configurable:!0}),e.prototype.setFastWeightInitDuringBuild=function(e){t.prototype.setFastWeightInitDuringBuild.call(this,e),null!=this.cell&&this.cell.setFastWeightInitDuringBuild(e)},e.prototype.getConfig=function(){var e={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(e.numConstants=this.numConstants);var n=this.cell.getConfig();e.cell={className:this.cell.getClassName(),config:n};var r=t.prototype.getConfig.call(this);return Object.assign(e,r),e},e.fromConfig=function(t,e,n){void 0===n&&(n={});var r=vd(e.cell,n);return new t(Object.assign(e,{cell:r}))},e.className="RNN",e}(nd);kp.registerClass(rv);var iv=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e}(nd),av=function(t){function e(e){var n=t.call(this,e)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=e.units,bh(n.units,"units"),n.activation=Lm(null==e.activation?n.DEFAULT_ACTIVATION:e.activation),n.useBias=null==e.useBias||e.useBias,n.kernelInitializer=zf(e.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=zf(e.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=zf(e.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=Gm(e.kernelRegularizer),n.recurrentRegularizer=Gm(e.recurrentRegularizer),n.biasRegularizer=Gm(e.biasRegularizer),n.kernelConstraint=Rh(e.kernelConstraint),n.recurrentConstraint=Rh(e.recurrentConstraint),n.biasConstraint=Rh(e.biasConstraint),n.dropout=Xh([1,Yh([0,null==e.dropout?0:e.dropout])]),n.recurrentDropout=Xh([1,Yh([0,null==e.recurrentDropout?0:e.recurrentDropout])]),n.stateSize=n.units,n.dropoutMask=null,n.recurrentDropoutMask=null,n}return Kp(e,t),e.prototype.build=function(t){t=Hf(t),this.kernel=this.addWeight("kernel",[t[t.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){if(2!==(t=t).length)throw new eh("SimpleRNNCell expects 2 input Tensors, got "+t.length+".");var r=t[1];t=t[0];var i,a=null!=e.training&&e.training;0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=hv(function(){return vn(t)},n.dropout,a)),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=hv(function(){return vn(r)},n.recurrentDropout,a));var o=n.dropoutMask,s=n.recurrentDropoutMask;i=uf(null!=o?iu(t,o):t,n.kernel.read()),null!=n.bias&&(i=hf(i,n.bias.read())),null!=s&&(r=iu(r,s));var u=Hs(i,uf(r,n.recurrentKernel.read()));return null!=n.activation&&(u=n.activation.apply(u)),[u,u]})},e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="SimpleRNNCell",e}(iv);kp.registerClass(av);var ov=function(t){function e(e){return e.cell=new av(e),t.call(this,e)||this}return Kp(e,t),e.prototype.call=function(e,n){var r=this;return _e(function(){null!=r.cell.dropoutMask&&(Fe(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(Fe(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var i=null==n?null:n.mask,a=null==n?null:n.training,o=null==n?null:n.initialState;return t.prototype.call.call(r,e,{mask:i,training:a,initialState:o})})},Object.defineProperty(e.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},n=t.prototype.getConfig.call(this);return delete n.cell,Object.assign(e,n),e},e.fromConfig=function(t,e){return new t(e)},e.className="SimpleRNN",e}(rv);kp.registerClass(ov);var sv=function(t){function e(e){var n=t.call(this,e)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=e.units,bh(n.units,"units"),n.activation=Lm(void 0===e.activation?n.DEFAULT_ACTIVATION:e.activation),n.recurrentActivation=Lm(void 0===e.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),n.useBias=null==e.useBias||e.useBias,n.kernelInitializer=zf(e.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=zf(e.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=zf(e.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=Gm(e.kernelRegularizer),n.recurrentRegularizer=Gm(e.recurrentRegularizer),n.biasRegularizer=Gm(e.biasRegularizer),n.kernelConstraint=Rh(e.kernelConstraint),n.recurrentConstraint=Rh(e.recurrentConstraint),n.biasConstraint=Rh(e.biasConstraint),n.dropout=Xh([1,Yh([0,null==e.dropout?0:e.dropout])]),n.recurrentDropout=Xh([1,Yh([0,null==e.recurrentDropout?0:e.recurrentDropout])]),n.implementation=e.implementation,n.stateSize=n.units,n.dropoutMask=null,n.recurrentDropoutMask=null,n}return Kp(e,t),e.prototype.build=function(t){var e=(t=Hf(t))[t.length-1];this.kernel=this.addWeight("kernel",[e,3*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,3*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[3*this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){if(2!==(t=t).length)throw new eh("GRUCell expects 2 input Tensors (inputs, h, c), got "+t.length+".");var r=null!=e.training&&e.training,i=t[1];t=t[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=hv(function(){return vn(t)},n.dropout,r,3)),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=hv(function(){return vn(i)},n.recurrentDropout,r,3));var a,o,s,u=n.dropoutMask,l=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(t=iu(t,u[0]));var c=uf(t,n.kernel.read());n.useBias&&(c=hf(c,n.bias.read())),0<n.recurrentDropout&&n.recurrentDropout<1&&(i=iu(i,l[0]));var p=n.recurrentKernel.read(),h=En(p,[2*n.units,n.units],p.rank-1),f=h[0],d=h[1],m=uf(i,f),g=En(c,3,c.rank-1),v=g[0],y=g[1],b=g[2],x=En(m,2,m.rank-1),w=x[0],N=x[1];a=n.recurrentActivation.apply(Hs(v,w)),o=n.recurrentActivation.apply(Hs(y,N));var C=uf(iu(o,i),d);s=n.activation.apply(Hs(b,C));var E=Hs(iu(a,i),iu(Hs(1,us(a)),s));return[E,E]})},e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),recurrentActivation:Mm(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="GRUCell",e}(iv);kp.registerClass(sv);var uv=function(t){function e(e){return 0===e.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new sv(e),t.call(this,e)||this}return Kp(e,t),e.prototype.call=function(e,n){var r=this;return _e(function(){null!=r.cell.dropoutMask&&(Fe(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(Fe(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var i=null==n?null:n.mask,a=null==n?null:n.training,o=null==n?null:n.initialState;return t.prototype.call.call(r,e,{mask:i,training:a,initialState:o})})},Object.defineProperty(e.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentActivation",{get:function(){return this.cell.recurrentActivation},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),recurrentActivation:Mm(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=t.prototype.getConfig.call(this);return delete n.cell,Object.assign(e,n),e},e.fromConfig=function(t,e){return 0===e.implmentation&&(e.implementation=1),new t(e)},e.className="GRU",e}(rv);kp.registerClass(uv);var lv=function(t){function e(e){var n=t.call(this,e)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=e.units,bh(n.units,"units"),n.activation=Lm(void 0===e.activation?n.DEFAULT_ACTIVATION:e.activation),n.recurrentActivation=Lm(void 0===e.recurrentActivation?n.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),n.useBias=null==e.useBias||e.useBias,n.kernelInitializer=zf(e.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=zf(e.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=zf(e.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.unitForgetBias=e.unitForgetBias,n.kernelRegularizer=Gm(e.kernelRegularizer),n.recurrentRegularizer=Gm(e.recurrentRegularizer),n.biasRegularizer=Gm(e.biasRegularizer),n.kernelConstraint=Rh(e.kernelConstraint),n.recurrentConstraint=Rh(e.recurrentConstraint),n.biasConstraint=Rh(e.biasConstraint),n.dropout=Xh([1,Yh([0,null==e.dropout?0:e.dropout])]),n.recurrentDropout=Xh([1,Yh([0,null==e.recurrentDropout?0:e.recurrentDropout])]),n.implementation=e.implementation,n.stateSize=[n.units,n.units],n.dropoutMask=null,n.recurrentDropoutMask=null,n}return Kp(e,t),e.prototype.build=function(t){var e,n,r=(t=Hf(t))[t.length-1];if(this.kernel=this.addWeight("kernel",[r,4*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,4*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){if(this.unitForgetBias){var i=this.biasInitializer,a=this.units;n=new((e=function(t){function e(){return null!==t&&t.apply(this,arguments)||this}return Kp(e,t),e.prototype.apply=function(t,e){var n=i.apply([a]),r=(new bf).apply([a]),o=i.apply([2*a]);return af(af(n,r),o)},e}(vf)).className="CustomInit",e)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.units],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0},e.prototype.call=function(t,e){var n=this;return _e(function(){var r=null!=e.training&&e.training;if(3!==(t=t).length)throw new eh("LSTMCell expects 3 input Tensors (inputs, h, c), got "+t.length+".");var i=t[1],a=t[2];t=t[0],0<n.dropout&&n.dropout<1&&null==n.dropoutMask&&(n.dropoutMask=hv(function(){return vn(t)},n.dropout,r,4)),0<n.recurrentDropout&&n.recurrentDropout<1&&null==n.recurrentDropoutMask&&(n.recurrentDropoutMask=hv(function(){return vn(i)},n.recurrentDropout,r,4));var o,s,u,l,c=n.dropoutMask,p=n.recurrentDropoutMask;0<n.dropout&&n.dropout<1&&(t=iu(t,c[0]));var h=uf(t,n.kernel.read());0<n.recurrentDropout&&n.recurrentDropout<1&&(i=iu(i,p[0])),h=Hs(h,uf(i,n.recurrentKernel.read())),n.useBias&&(h=hf(h,n.bias.read()));var f=En(h,4,h.rank-1),d=f[0],m=f[1],g=f[2],v=f[3];o=n.recurrentActivation.apply(d),s=n.recurrentActivation.apply(m),u=Hs(iu(s,a),iu(o,n.activation.apply(g))),l=n.recurrentActivation.apply(v);var y=iu(l,n.activation.apply(u));return[y,y,u]})},e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),recurrentActivation:Mm(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.className="LSTMCell",e}(iv);kp.registerClass(lv);var cv=function(t){function e(e){return 0===e.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new lv(e),t.call(this,e)||this}return Kp(e,t),e.prototype.call=function(e,n){var r=this;return _e(function(){null!=r.cell.dropoutMask&&(Fe(r.cell.dropoutMask),r.cell.dropoutMask=null),null!=r.cell.recurrentDropoutMask&&(Fe(r.cell.recurrentDropoutMask),r.cell.recurrentDropoutMask=null);var i=null==n?null:n.mask,a=null==n?null:n.training,o=null==n?null:n.initialState;return t.prototype.call.call(r,e,{mask:i,training:a,initialState:o})})},Object.defineProperty(e.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentActivation",{get:function(){return this.cell.recurrentActivation},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"unitForgetBias",{get:function(){return this.cell.unitForgetBias},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),e.prototype.getConfig=function(){var e={units:this.units,activation:Mm(this.activation),recurrentActivation:Mm(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Mf(this.kernelInitializer),recurrentInitializer:Mf(this.recurrentInitializer),biasInitializer:Mf(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:Um(this.kernelRegularizer),recurrentRegularizer:Um(this.recurrentRegularizer),biasRegularizer:Um(this.biasRegularizer),activityRegularizer:Um(this.activityRegularizer),kernelConstraint:Ih(this.kernelConstraint),recurrentConstraint:Ih(this.recurrentConstraint),biasConstraint:Ih(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=t.prototype.getConfig.call(this);return delete n.cell,Object.assign(e,n),e},e.fromConfig=function(t,e){return 0===e.implmentation&&(e.implementation=1),new t(e)},e.className="LSTM",e}(rv);kp.registerClass(cv);var pv=function(t){function e(e){var n=t.call(this,e)||this;return n.cells=e.cells,n}return Kp(e,t),Object.defineProperty(e.prototype,"stateSize",{get:function(){for(var t=[],e=0,n=this.cells.slice().reverse();e<n.length;e++){var r=n[e];Array.isArray(r.stateSize)?t.push.apply(t,r.stateSize):t.push(r.stateSize)}return t},enumerable:!0,configurable:!0}),e.prototype.call=function(t,e){var n=this;return _e(function(){for(var r=(t=t).slice(1),i=[],a=0,o=n.cells.slice().reverse();a<o.length;a++){var s=o[a];Array.isArray(s.stateSize)?i.push(r.splice(0,s.stateSize.length)):i.push(r.splice(0,1))}i.reverse();for(var u,l=[],c=0;c<n.cells.length;++c)s=n.cells[c],r=i[c],u=0===c?[t[0]].concat(r):[u[0]].concat(r),u=s.call(u,e),l.push(u.slice(1));r=[];for(var p=0,h=l.slice().reverse();p<h.length;p++){var f=h[p];r.push.apply(r,f)}return[u[0]].concat(r)})},e.prototype.build=function(t){var e;Uf(t)&&(t=t[0]),t=t;for(var n=0,r=this.cells;n<r.length;n++){var i=r[n];i.build(t),e=Array.isArray(i.stateSize)?i.stateSize[0]:i.stateSize,t=[t[0],e]}this.built=!0},e.prototype.getConfig=function(){for(var e=[],n=0,r=this.cells;n<r.length;n++){var i=r[n];e.push({className:i.getClassName(),config:i.getConfig()})}var a={cells:e},o=t.prototype.getConfig.call(this);return Object.assign(a,o),a},e.fromConfig=function(t,e,n){void 0===n&&(n={});for(var r=[],i=0,a=e.cells;i<a.length;i++){var o=a[i];r.push(vd(o,n))}return new t({cells:r})},Object.defineProperty(e.prototype,"trainableWeights",{get:function(){if(!this.trainable)return[];for(var t=[],e=0,n=this.cells;e<n.length;e++){var r=n[e];t.push.apply(t,r.trainableWeights)}return t},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){for(var t=[],e=0,n=this.cells;e<n.length;e++){var r=n[e];t.push.apply(t,r.nonTrainableWeights)}if(!this.trainable){for(var i=[],a=0,o=this.cells;a<o.length;a++)r=o[a],i.push.apply(i,r.trainableWeights);return i.concat(t)}return t},enumerable:!0,configurable:!0}),e.prototype.getWeights=function(){for(var t=[],e=0,n=this.cells;e<n.length;e++){var r=n[e];t.push.apply(t,r.weights)}return Xf(t)},e.prototype.setWeights=function(t){for(var e=[],n=0,r=this.cells;n<r.length;n++)for(var i=r[n],a=i.weights.length,o=t.splice(a),s=0;s<i.weights.length;++s)e.push([i.weights[s],o[s]]);Yf(e)},e.className="StackedRNNCells",e}(iv);function hv(t,e,n,r){function i(){return ff(t(),e)}if(void 0===n&&(n=null),void 0===r&&(r=1),r>1){for(var a=[],o=0;o<r;o++)a.push(df(i,t,n));return a.map(function(t){return Me(t.clone())})}return Me(df(i,t,n).clone())}kp.registerClass(pv);var fv=function(t){function e(e){var n=t.call(this,e)||this;return n.layer=e.layer,n}return Kp(e,t),e.prototype.build=function(t){this.built=!0},Object.defineProperty(e.prototype,"trainable",{get:function(){return null!=this.layer&&this.layer.trainable},set:function(t){null!=this.layer&&(this.layer.trainable=t)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"trainableWeights",{get:function(){return this.layer.trainableWeights},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){return this.layer.nonTrainableWeights},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"updates",{get:function(){return this.layer._updates},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"losses",{get:function(){return this.layer.losses},enumerable:!0,configurable:!0}),e.prototype.getWeights=function(){return this.layer.getWeights()},e.prototype.setWeights=function(t){this.layer.setWeights(t)},e.prototype.getConfig=function(){var e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.prototype.setFastWeightInitDuringBuild=function(e){t.prototype.setFastWeightInitDuringBuild.call(this,e),null!=this.layer&&this.layer.setFastWeightInitDuringBuild(e)},e.fromConfig=function(t,e,n){void 0===n&&(n={});var r=vd(e.layer,n);delete e.layer;var i={layer:r};return Object.assign(i,e),new t(i)},e}(nd),dv=function(t){function e(e){var n=t.call(this,e)||this;return n.supportsMasking=!0,n}return Kp(e,t),e.prototype.build=function(e){if((e=Hf(e)).length<3)throw new eh("TimeDistributed layer expects an input shape >= 3D, but received input shape "+JSON.stringify(e));this.inputSpec=[{shape:e}];var n=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(n),this.layer.built=!0),t.prototype.build.call(this,e)},e.prototype.computeOutputShape=function(t){var e=[(t=Hf(t))[0]].concat(t.slice(2)),n=this.layer.computeOutputShape(e),r=t[1];return[n[0],r].concat(n.slice(1))},e.prototype.call=function(t,e){var n=this;return _e(function(){return nv(function(t,r){return[Gf(n.layer.call(t,e)),[]]},t=Gf(t),[],!1,null,null,!1,!0)[1]})},e.className="TimeDistributed",e}(fv);kp.registerClass(dv);var mv="concat",gv=function(t){function e(e){var n=t.call(this,e)||this,r=e.layer.getConfig(),i={};i.className=e.layer.getClassName(),i.config=r,n.forwardLayer=vd(i),r.goBackwards=!0!==r.goBackwards;var a={};if(a.className=e.layer.getClassName(),a.config=r,n.backwardLayer=vd(a),n.forwardLayer.name="forward_"+n.forwardLayer.name,n.backwardLayer.name="backward_"+n.backwardLayer.name,n.mergeMode=void 0===e.mergeMode?mv:e.mergeMode,function(t){vh(Fh,"BidirectionalMergeMode",t)}(n.mergeMode),e.weights)throw new nh("weights support is not implemented for Bidirectional layer yet.");return n._stateful=e.layer.stateful,n.returnSequences=e.layer.returnSequences,n.returnState=e.layer.returnState,n.supportsMasking=!0,n._trainable=!0,n.inputSpec=e.layer.inputSpec,n.numConstants=null,n}return Kp(e,t),Object.defineProperty(e.prototype,"trainable",{get:function(){return this._trainable},set:function(t){this._trainable=t,null!=this.forwardLayer&&(this.forwardLayer.trainable=t),null!=this.backwardLayer&&(this.backwardLayer.trainable=t)},enumerable:!0,configurable:!0}),e.prototype.getWeights=function(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())},e.prototype.setWeights=function(t){var e=t.length,n=Math.floor(e/2);this.forwardLayer.setWeights(t.slice(0,n)),this.backwardLayer.setWeights(t.slice(n))},e.prototype.computeOutputShape=function(t){var e,n,r,i=this.forwardLayer.computeOutputShape(t);return Array.isArray(i)&&Array.isArray(i[0])||(i=[i]),i=i,this.returnState?(r=i.slice(1),e=i[0]):e=i[0],e=e,"concat"===this.mergeMode?(e[e.length-1]*=2,n=[e]):n=null==this.mergeMode?[e,e.slice()]:[e],this.returnState?null==this.mergeMode?n.concat(r).concat(r.slice()):[e].concat(r).concat(r.slice()):sh(n)},e.prototype.apply=function(e,n){var r=null==n?null:n.initialState,i=null==n?null:n.constants;null==n&&(n={});var a=ev(e,r,i,this.numConstants);if(e=a.inputs,r=a.initialState,i=a.constants,Array.isArray(e)&&(r=e.slice(1),e=e[0]),(null==r||0===r.length)&&null==i)return t.prototype.apply.call(this,e,n);var o=[],s=[];if(null!=r){var u=r.length;if(u%2>0)throw new eh("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");n.initialState=r,o.push.apply(o,r);var l=r.map(function(t){return new Jf({shape:t.shape})});this.forwardLayer.stateSpec=l.slice(0,u/2),this.backwardLayer.stateSpec=l.slice(u/2),s.push.apply(s,l)}if(null!=i)throw new nh("Support for constants in Bidirectional layers is not implemented yet.");for(var c=o[0]instanceof Zf,p=0,h=o;p<h.length;p++)if(h[p]instanceof Zf!==c)throw new eh("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(c){var f=[e].concat(o),d=this.inputSpec.concat(s),m=this.inputSpec;this.inputSpec=d;var g=t.prototype.apply.call(this,f,n);return this.inputSpec=m,g}return t.prototype.apply.call(this,e,n)},e.prototype.call=function(t,e){var n=this;return _e(function(){if(null!=e.mask)throw new nh("The support for masking is not implemented for Bidirectional layers yet.");var r,i,a,o,s=e.initialState;if(null==s)r=n.forwardLayer.call(t,e),i=n.backwardLayer.call(t,e);else{var u=s.slice(0,s.length/2),l=s.slice(s.length/2);r=n.forwardLayer.call(t,Object.assign(e,{initialState:u})),i=n.backwardLayer.call(t,Object.assign(e,{initialState:l}))}return n.returnState&&(Array.isArray(r)&&(a=r.slice(1).concat(i.slice(1))),r=r[0],i=i[0]),n.returnSequences&&(i=Hu(i,1)),"concat"===n.mergeMode?o=rf([r,i]):"sum"===n.mergeMode?o=Hs(r,i):"ave"===n.mergeMode?o=iu(.5,Hs(r,i)):"mul"===n.mergeMode?o=iu(r,i):null==n.mergeMode&&(o=[r,i]),n.returnState?null==n.mergeMode?o.concat(a):[o].concat(a):o})},e.prototype.resetStates=function(t){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()},e.prototype.build=function(t){var e=this;Wh(this.forwardLayer.name,function(){e.forwardLayer.build(t)}),Wh(this.backwardLayer.name,function(){e.backwardLayer.build(t)}),this.built=!0},Object.defineProperty(e.prototype,"trainableWeights",{get:function(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"nonTrainableWeights",{get:function(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)},enumerable:!0,configurable:!0}),e.prototype.setFastWeightInitDuringBuild=function(e){t.prototype.setFastWeightInitDuringBuild.call(this,e),null!=this.forwardLayer&&this.forwardLayer.setFastWeightInitDuringBuild(e),null!=this.backwardLayer&&this.backwardLayer.setFastWeightInitDuringBuild(e)},e.prototype.getConfig=function(){var e={mergeMode:this.mergeMode},n=t.prototype.getConfig.call(this);return Object.assign(e,n),e},e.fromConfig=function(t,e){var n=vd(e.layer);if(delete e.layer,null!=e.numConstants)throw new nh("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");var r=e;return r.layer=n,new t(r)},e.className="Bidirectional",e}(fv);function vv(t){return new Ug(t)}function yv(t){return new Hg(t)}function bv(t){return new $g(t)}function xv(t){return new Jg(t)}function wv(t){return new tv(t)}function Nv(t){return new Wg(t)}function Cv(t){return new Gg(t)}kp.registerClass(gv);var Ev=xv,Sv=wv,kv=Nv,Iv=Cv;var Av=Object.freeze({inputLayer:function(t){return new id(t)},elu:function(t){return new $m(t)},reLU:function(t){return new Hm(t)},leakyReLU:function(t){return new qm(t)},prelu:function(t){return new Km(t)},softmax:function(t){return new Ym(t)},thresholdedReLU:function(t){return new Xm(t)},conv1d:function(t){return new lg(t)},conv2d:function(t){return new ag(t)},conv2dTranspose:function(t){return new sg(t)},conv3d:function(t){return new og(t)},separableConv2d:function(t){return new ug(t)},cropping2D:function(t){return new cg(t)},upSampling2d:function(t){return new pg(t)},depthwiseConv2d:function(t){return new hg(t)},activation:function(t){return new gg(t)},dense:function(t){return new dg(t)},dropout:function(t){return new fg(t)},flatten:function(t){return new mg(t)},repeatVector:function(t){return new vg(t)},reshape:function(t){return new yg(t)},permute:function(t){return new bg(t)},embedding:function(t){return new wg(t)},add:function(t){return new Cg(t)},average:function(t){return new Sg(t)},concatenate:function(t){return new Ag(t)},maximum:function(t){return new kg(t)},minimum:function(t){return new Ig(t)},multiply:function(t){return new Eg(t)},dot:function(t){return new Tg(t)},batchNormalization:function(t){return new zg(t)},zeroPadding2d:function(t){return new Lg(t)},averagePooling1d:vv,avgPool1d:function(t){return vv(t)},avgPooling1d:function(t){return vv(t)},averagePooling2d:yv,avgPool2d:function(t){return yv(t)},avgPooling2d:function(t){return yv(t)},averagePooling3d:bv,avgPool3d:function(t){return bv(t)},avgPooling3d:function(t){return bv(t)},globalAveragePooling1d:function(t){return new Yg(t)},globalAveragePooling2d:function(t){return new Qg(t)},globalMaxPooling1d:xv,globalMaxPooling2d:wv,maxPooling1d:Nv,maxPooling2d:Cv,maxPooling3d:function(t){return new Kg(t)},gru:function(t){return new uv(t)},gruCell:function(t){return new sv(t)},lstm:function(t){return new cv(t)},lstmCell:function(t){return new lv(t)},simpleRNN:function(t){return new ov(t)},simpleRNNCell:function(t){return new av(t)},rnn:function(t){return new rv(t)},stackedRNNCells:function(t){return new pv(t)},bidirectional:function(t){return new gv(t)},timeDistributed:function(t){return new dv(t)},globalMaxPool1d:Ev,globalMaxPool2d:Sv,maxPool1d:kv,maxPool2d:Iv,Layer:nd,RNN:rv,RNNCell:iv,input:wm,gaussianNoise:function(t){return new Dg(t)},gaussianDropout:function(t){return new Og(t)},alphaDropout:function(t){return new _g(t)},masking:function(t){return new xg(t)}});var Rv=Object.freeze({binaryAccuracy:function(t,e){return Ad(t,e)},binaryCrossentropy:function(t,e){return _d(t,e)},sparseCategoricalAccuracy:function(t,e){return Fd(t,e)},categoricalAccuracy:function(t,e){return Rd(t,e)},categoricalCrossentropy:function(t,e){return Md(t,e)},precision:function(t,e){return Dd(t,e)},recall:function(t,e){return Od(t,e)},cosineProximity:function(t,e){return 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dy(this.node.rawAttrs,t,e);if(null!=n.b)return my(this.node.rawAttrs,t,e);if(null!=n.shape)return wy(this.node.rawAttrs,t,e);if(null!=n.type)return yy(this.node.rawAttrs,t,e);if(null!=n.list){if(null!=n.list.i||null!=n.list.f)return Ny(this.node.rawAttrs,t,e);if(null!=n.list.s)return Cy(this.node.rawAttrs,t,e);if(null!=n.list.shape)return Ey(this.node.rawAttrs,t,e);if(null!=n.list.b)return Sy(this.node.rawAttrs,t,e);if(null!=n.list.type)return by(this.node.rawAttrs,t,e)}return e},t}(),Iy=function(t,e,n){switch(t.op){case"BiasAdd":case"AddV2":case"Add":return[Hs(Gv("a",t,e,n),Gv("b",t,e,n))];case"AddN":return[qs(Gv("tensors",t,e,n))];case"FloorMod":case"Mod":return[nu(Gv("a",t,e,n),Gv("b",t,e,n))];case"Mul":return[iu(Gv("a",t,e,n),Gv("b",t,e,n))];case"RealDiv":case"Div":return[Xs(Gv("a",t,e,n),Gv("b",t,e,n))];case"FloorDiv":return[Js(Gv("a",t,e,n),Gv("b",t,e,n))];case"Sub":return[cu(Gv("a",t,e,n),Gv("b",t,e,n))];case"Minimum":return[tu(Gv("a",t,e,n),Gv("b",t,e,n))];case"Maximum":return[Zs(Gv("a",t,e,n),Gv("b",t,e,n))];case"Pow":return[ou(Gv("a",t,e,n),Gv("b",t,e,n))];case"SquaredDifference":return[uu(Gv("a",t,e,n),Gv("b",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Ay=function(t,e,n){switch(t.op){case"Abs":case"ComplexAbs":return[Go(Gv("x",t,e,n))];case"Acos":return[Ho(Gv("x",t,e,n))];case"Acosh":return[qo(Gv("x",t,e,n))];case"Asin":return[Ko(Gv("x",t,e,n))];case"Asinh":return[$o(Gv("x",t,e,n))];case"Atan":return[Xo(Gv("x",t,e,n))];case"Atan2":return[$s(Gv("x",t,e,n),Gv("y",t,e,n))];case"Atanh":return[Yo(Gv("x",t,e,n))];case"Ceil":return[Jo(Gv("x",t,e,n))];case"Complex":return[Qe(Gv("real",t,e,n),Gv("imag",t,e,n))];case"Cos":return[Qo(Gv("x",t,e,n))];case"Cosh":return[ts(Gv("x",t,e,n))];case"Elu":return[xl(Gv("x",t,e,n))];case"Erf":return[es(Gv("x",t,e,n))];case"Exp":return[ns(Gv("x",t,e,n))];case"Expm1":return[rs(Gv("x",t,e,n))];case"Floor":return[is(Gv("x",t,e,n))];case"Log":return[as(Gv("x",t,e,n))];case"Log1p":return[os(Gv("x",t,e,n))];case"Imag":return[en(Gv("x",t,e,n))];case"Neg":return[us(Gv("x",t,e,n))];case"Reciprocal":return[ls(Gv("x",t,e,n))];case"Real":return[tn(Gv("x",t,e,n))];case"Relu":return[Cl(Gv("x",t,e,n))];case"Round":return[cs(Gv("x",t,e,n))];case"Selu":return[El(Gv("x",t,e,n))];case"Sigmoid":return[hs(Gv("x",t,e,n))];case"Sin":return[vs(Gv("x",t,e,n))];case"Sign":return[fs(Gv("x",t,e,n))];case"Sinh":return[ys(Gv("x",t,e,n))];case"Softplus":return[bs(Gv("x",t,e,n))];case"Sqrt":return[xs(Gv("x",t,e,n))];case"Square":return[ws(Gv("x",t,e,n))];case"Tanh":return[Es(Gv("x",t,e,n))];case"Tan":return[Cs(Gv("x",t,e,n))];case"Relu6":case"ClipByValue":return[Zo(Gv("x",t,e,n),Gv("clipValueMin",t,e,n),Gv("clipValueMax",t,e,n))];case"Rsqrt":return[ps(Hv(t.inputNames[0],e,n))];case"Prod":return[bl(Gv("x",t,e,n),Gv("axes",t,e,n))];case"LeakyRelu":return[wl(Gv("x",t,e,n),Gv("alpha",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Ry=function(){function t(e,n,r,i,a,o,s){this.name=e,this.dtype=n,this.maxSize=r,this.elementShape=i,this.identicalElementShapes=a,this.dynamicSize=o,this.clearAfterRead=s,this.tensors=[],this.closed_=!1,this.id=t.nextId++}return Object.defineProperty(t.prototype,"closed",{get:function(){return this.closed_},enumerable:!0,configurable:!0}),t.prototype.clearAndClose=function(){this.tensors.forEach(function(t){return t.tensor.dispose()}),this.tensors=[],this.closed_=!0},t.prototype.size=function(){return this.tensors.length},t.prototype.read=function(t){if(this.closed_)throw new Error("TensorArray "+this.name+" has already been closed.");if(t<0||t>=this.tensors.length)throw new Error("Tried to read from index "+t+", but array size is: "+this.tensors.length);var e=this.tensors[t];if(e.cleared)throw new Error("TensorArray "+this.name+": Could not read index "+t+" twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).");return this.clearAfterRead&&(e.cleared=!0),e.read=!0,e.tensor},t.prototype.readMany=function(t){var e=this;return t.map(function(t){return e.read(t)})},t.prototype.write=function(t,e){if(this.closed_)throw new Error("TensorArray "+this.name+" has already been closed.");if(t<0||!this.dynamicSize&&t>=this.maxSize)throw new Error("Tried to write to index "+t+", but array is not resizeable and size is: "+this.maxSize);var n=this.tensors[t]||{};if(e.dtype!==this.dtype)throw new Error("TensorArray "+this.name+": Could not write to TensorArray index "+t+",\n          because the value dtype is "+e.dtype+", but TensorArray dtype is "+this.dtype+".");if(0!==this.size()||null!=this.elementShape&&0!==this.elementShape.length||(this.elementShape=e.shape),this.assertShapesMatchAllowUndefinedSize(this.elementShape,e.shape,"TensorArray "+this.name+": Could not write to TensorArray index "+t+"."),n&&n.read)throw new Error("TensorArray "+this.name+": Could not write to TensorArray index "+t+", because it has already been read.");if(n&&n.written)throw new Error("TensorArray "+this.name+": Could not write to TensorArray index "+t+", because it has already been written.");n.tensor=e,n.written=!0,this.tensors[t]=n},t.prototype.writeMany=function(t,e){var n=this;if(t.length!==e.length)throw new Error("TensorArray "+this.name+": could not write multiple tensors,because the index size: "+t.length+" is not the same as tensors size: "+e.length+".");t.forEach(function(t,r){return n.write(t,e[r])})},t.prototype.gather=function(t,e){if(e&&e!==this.dtype)throw new Error("TensorArray dtype is "+this.dtype+" but gather requested dtype "+e);if(!t){t=[];for(var n=0;n<this.size();n++)t.push(n)}if(0===t.length)return nn([],[0].concat(this.elementShape));var r=this.readMany(t);return this.assertShapesMatchAllowUndefinedSize(this.elementShape,r[0].shape,"TensorArray shape mismatch: "),or(r,0)},t.prototype.concat=function(t){if(t&&t!==this.dtype)throw new Error("TensorArray dtype is "+this.dtype+" but concat requested dtype "+t);if(0===this.size())return nn([],[0].concat(this.elementShape));for(var e=[],n=0;n<this.size();n++)e.push(n);var r=this.readMany(e);return this.assertShapesMatchAllowUndefinedSize(this.elementShape,r[0].shape,"TensorArray shape mismatch: tensor array shape ("+this.elementShape+") vs first tensor shape ("+r[0].shape+")"),bn(r,0)},t.prototype.scatter=function(t,e){if(e.dtype!==this.dtype)throw new Error("TensorArray dtype is "+this.dtype+" but tensor has dtype "+e.dtype);if(t.length!==e.shape[0])throw new Error("Expected len(indices) == tensor.shape[0], but saw: "+t.length+" vs. "+e.shape[0]);var n=Math.max.apply(Math,t);if(!this.dynamicSize&&n>=this.maxSize)throw new Error("Max index must be < array size ("+n+"  vs. "+this.maxSize+")");this.writeMany(t,lr(e,0))},t.prototype.split=function(t,e){var n=this;if(e.dtype!==this.dtype)throw new Error("TensorArray dtype is "+this.dtype+" but tensor has dtype "+e.dtype);var r=0,i=t.map(function(t){return r+=t});if(r!==e.shape[0])throw new Error("Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        "+r+", and tensor's shape is: "+e.shape);if(!this.dynamicSize&&t.length!==this.maxSize)throw new Error("TensorArray's size is not equal to the size of lengths ("+this.maxSize+" vs. "+t.length+"), and the TensorArray is not marked as dynamically resizeable");var a=0===r?0:e.size/r,o=[];_e(function(){e=e.reshape([1,r,a]);for(var s=0;s<t.length;++s){var u=[0,0===s?0:i[s-1],0],l=[1,t[s],a];o[s]=rl(e,u,l).reshape(n.elementShape)}return o});for(var s=[],u=0;u<t.length;u++)s[u]=u;this.writeMany(s,o)},t.prototype.assertShapesMatchAllowUndefinedSize=function(t,e,n){void 0===n&&(n=""),Y.assert(this.shapesEqualAllowUndefinedSize(t,e),function(){return n+" Shapes "+t+" and "+e+" must match"})},t.prototype.shapesEqualAllowUndefinedSize=function(t,e){if(t.length!==e.length)return!1;for(var n=0;n<t.length;n++)if(-1!==t[n]&&-1!==e[n]&&t[n]!==e[n])return!1;return!0},t.nextId=0,t}();var Ty=function(t,e,n){var r,i;switch(t.op){case"Conv1D":var a=Gv("stride",t,e,n),o=Gv("pad",t,e,n),s=Gv("dataFormat",t,e,n).toUpperCase(),u=Gv("dilation",t,e,n);return[_u(Gv("x",t,e,n),Gv("filter",t,e,n),a,o,s,u)];case"Conv2D":a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),s=Gv("dataFormat",t,e,n).toUpperCase();var l=Gv("dilations",t,e,n);return[Fu(Gv("x",t,e,n),Gv("filter",t,e,n),[a[1],a[2]],o,s,[l[1],l[2]])];case"_FusedConv2D":var c=(r=Gv("fusedOps",t,e,n))[0],p=r[1],h="biasadd"===c,f="prelu"===p,d="fusedbatchnorm"===c,m=Gv("numArgs",t,e,n);if(h){if(f&&2!==m)throw new Error("Fused Conv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!f&&1!==m)throw new Error("Fused Conv2d with BiasAdd must have one extra argument: bias.")}if(d)throw new Error("Fused Conv2d with FusedBatchNorm is not supported.");a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),s=Gv("dataFormat",t,e,n).toUpperCase(),l=Gv("dilations",t,e,n);var g=(i=Gv("args",t,e,n))[0],v=i[1];return[yc.conv2d({x:Gv("x",t,e,n),filter:Gv("filter",t,e,n),strides:[a[1],a[2]],pad:o,dataFormat:s,dilations:[l[1],l[2]],bias:g,activation:p,preluActivationWeights:v})];case"Conv2DBackpropInput":case"Conv2dTranspose":var y=Gv("outputShape",t,e,n);return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),[Vu(Gv("x",t,e,n),Gv("filter",t,e,n),y,[a[1],a[2]],o)];case"DepthwiseConv2dNative":case"DepthwiseConv2d":return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),l=Gv("dilations",t,e,n),s=Gv("dataFormat",t,e,n).toUpperCase(),[Pu(Gv("input",t,e,n),Gv("filter",t,e,n),[a[1],a[2]],o,s,[l[1],l[2]])];case"Conv3D":return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),s=Gv("dataFormat",t,e,n).toUpperCase(),l=Gv("dilations",t,e,n),[Mu(Gv("x",t,e,n),Gv("filter",t,e,n),[a[1],a[2],a[3]],o,s,[l[1],l[2],l[3]])];case"AvgPool":a=Gv("strides",t,e,n),o=Gv("pad",t,e,n);var b=Gv("kernelSize",t,e,n);return[Qu(Gv("x",t,e,n),[b[1],b[2]],[a[1],a[2]],o)];case"MaxPool":return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),b=Gv("kernelSize",t,e,n),[Zu(Gv("x",t,e,n),[b[1],b[2]],[a[1],a[2]],o)];case"AvgPool3D":return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),b=Gv("kernelSize",t,e,n),[nl(Gv("x",t,e,n),[b[1],b[2],b[3]],[a[1],a[2],a[3]],o)];case"MaxPool3D":return a=Gv("strides",t,e,n),o=Gv("pad",t,e,n),b=Gv("kernelSize",t,e,n),[el(Gv("x",t,e,n),[b[1],b[2],b[3]],[a[1],a[2],a[3]],o)];default:throw TypeError("Node type "+t.op+" is not implemented")}},Dy=function(t,e,n){switch(t.op){case"Fill":var r=Gv("shape",t,e,n),i=Gv("dtype",t,e,n);return[dn(r,Gv("value",t,e,n),i)];case"LinSpace":var a=Gv("start",t,e,n);return[mn(a,Gv("stop",t,e,n),Gv("num",t,e,n))];case"Multinomial":var o=Gv("logits",t,e,n),s=Gv("numSamples",t,e,n),u=Gv("seed",t,e,n);return[qn(o,s,u)];case"OneHot":var l=Gv("indices",t,e,n),c=Gv("depth",t,e,n),p=Gv("onValue",t,e,n),h=Gv("offValue",t,e,n);return[Kn(l,c,p,h)];case"Ones":return[hn(Gv("shape",t,e,n),Gv("dtype",t,e,n))];case"OnesLike":return[vn(Gv("x",t,e,n))];case"RandomUniform":return[nr(Gv("shape",t,e,n),Gv("minval",t,e,n),Gv("maxval",t,e,n),Gv("dtype",t,e,n))];case"Range":return[gn(a=Gv("start",t,e,n),Gv("stop",t,e,n),Gv("step",t,e,n),Gv("dtype",t,e,n))];case"TruncatedNormal":r=Gv("shape",t,e,n);var f=Gv("mean",t,e,n),d=Gv("stdDev",t,e,n);return u=Gv("seed",t,e,n),[ur(r,f,d,Gv("dtype",t,e,n),u)];case"Zeros":return[fn(Gv("shape",t,e,n),Gv("dtype",t,e,n))];case"ZerosLike":return[yn(Gv("x",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}};var Oy=function(t,e,n){switch(t.op){case"TopKV2":var r=Gv("x",t,e,n),i=Gv("k",t,e,n),a=Gv("sorted",t,e,n),o=Ol(r,i,a);return[o.values,o.indices];default:throw TypeError("Node type "+t.op+" is not implemented")}},_y=function(t,e,n){switch(t.op){case"Const":return e[t.name];case"PlaceholderWithDefault":var r=Gv("default",t,e,n);return[Hv(t.name,e,n)||r];case"Placeholder":return[Hv(t.name,e,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":return[Gv("x",t,e,n).clone()];case"IdentityN":return Gv("x",t,e,n).map(function(t){return t.clone()});case"Snapshot":return[Gv("x",t,e,n).clone()];case"Shape":return[on(Gv("x",t,e,n).shape,"int32")];case"ShapeN":return Gv("x",t,e,n).map(function(t){return on(t.shape)});case"Size":return[an(Gv("x",t,e,n).size,"int32")];case"Rank":return[an(Gv("x",t,e,n).rank,"int32")];case"NoOp":return[];case"Print":var i=Gv("x",t,e,n),a=Gv("data",t,e,n),o=Gv("message",t,e,n),s=Gv("summarize",t,e,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(var u=0;u<a.length;u++)console.log(Array.prototype.slice.call(a[u].dataSync()).slice(0,s));return[i];default:throw TypeError("Node type "+t.op+" is not implemented")}},Fy=function(t,e,n){switch(t.op){case"ResizeBilinear":var r=Gv("images",t,e,n),i=Gv("size",t,e,n),a=Gv("alignCorners",t,e,n);return[mc.resizeBilinear(r,[i[0],i[1]],a)];case"ResizeNearestNeighbor":return r=Gv("images",t,e,n),i=Gv("size",t,e,n),a=Gv("alignCorners",t,e,n),[mc.resizeNearestNeighbor(r,[i[0],i[1]],a)];case"CropAndResize":var o=Gv("image",t,e,n),s=Gv("boxes",t,e,n),u=Gv("boxInd",t,e,n),l=Gv("cropSize",t,e,n),c=Gv("method",t,e,n),p=Gv("extrapolationValue",t,e,n);return[mc.cropAndResize(o,s,u,l,c,p)];default:throw TypeError("Node type "+t.op+" is not implemented")}},My=function(t,e,n){switch(t.op){case"Equal":return[hu(Gv("a",t,e,n),Gv("b",t,e,n))];case"NotEqual":return[Nu(Gv("a",t,e,n),Gv("b",t,e,n))];case"Greater":return[du(Gv("a",t,e,n),Gv("b",t,e,n))];case"GreaterEqual":return[mu(Gv("a",t,e,n),Gv("b",t,e,n))];case"Less":return[yu(Gv("a",t,e,n),Gv("b",t,e,n))];case"LessEqual":return[bu(Gv("a",t,e,n),Gv("b",t,e,n))];case"LogicalAnd":return[Bs(Gv("a",t,e,n),Gv("b",t,e,n))];case"LogicalNot":return[Vs(Gv("a",t,e,n))];case"LogicalOr":return[Ws(Gv("a",t,e,n),Gv("b",t,e,n))];case"Select":return[js(Gv("condition",t,e,n),Gv("a",t,e,n),Gv("b",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},zy=function(t,e,n){switch(t.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[Uu(Gv("a",t,e,n),Gv("b",t,e,n),Gv("transposeA",t,e,n),Gv("transposeB",t,e,n))];case"Transpose":return[Sl(Gv("x",t,e,n),Gv("perm",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Ly=function(t,e,n){switch(t.op){case"FusedBatchNorm":case"FusedBatchNormV2":case"FusedBatchNormV3":return[Ms(Gv("x",t,e,n),Gv("mean",t,e,n),Gv("variance",t,e,n),Gv("offset",t,e,n),Gv("scale",t,e,n),Gv("epsilon",t,e,n))];case"LRN":return[kl(Gv("x",t,e,n),Gv("radius",t,e,n),Gv("bias",t,e,n),Gv("alpha",t,e,n),Gv("beta",t,e,n))];case"Softmax":return[Rr(Gv("x",t,e,n))];case"LogSoftmax":return[Tr(Gv("x",t,e,n))];case"SparseToDense":return[Bl(Gv("sparseIndices",t,e,n),Gv("outputShape",t,e,n),Gv("sparseValues",t,e,n),Gv("defaultValue",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Py=function(t,e,n){switch(t.op){case"Max":var r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n);return[dl(Gv("x",t,e,n),r,i)];case"Mean":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[ml(Gv("x",t,e,n),r,i)];case"Min":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[gl(Gv("x",t,e,n),r,i)];case"Sum":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[yl(Gv("x",t,e,n),r,i)];case"All":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[ll(Gv("x",t,e,n),r,i)];case"Any":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[cl(Gv("x",t,e,n),r,i)];case"ArgMax":return r=Gv("axis",t,e,n),[pl(Gv("x",t,e,n),r)];case"ArgMin":return r=Gv("axis",t,e,n),[hl(Gv("x",t,e,n),r)];case"Prod":return r=Gv("axis",t,e,n),i=Gv("keepDims",t,e,n),[bl(Gv("x",t,e,n),r,i)];default:throw TypeError("Node type "+t.op+" is not implemented")}},By=function(t,e,n){switch(t.op){case"ConcatV2":case"Concat":var r=Gv("axis",t,e,n),i=Gv("tensors",t,e,n);return[bn(i,r)];case"GatherV2":case"Gather":r=Gv("axis",t,e,n);var a=Gv("x",t,e,n),o=Gv("indices",t,e,n);return[ku(a,o.asType("int32"),r)];case"ReverseV2":case"Reverse":return r=Gv("axis",t,e,n),a=Gv("x",t,e,n),[Hu(a,r)];case"Slice":var s=Gv("begin",t,e,n),u=Gv("size",t,e,n);return[rl(Gv("x",t,e,n),s,u)];case"StridedSlice":s=Gv("begin",t,e,n);var l=Gv("end",t,e,n),c=Gv("strides",t,e,n),p=Gv("beginMask",t,e,n),h=Gv("endMask",t,e,n),f=Gv("ellipsisMask",t,e,n),d=Gv("newAxisMask",t,e,n),m=Gv("shrinkAxisMask",t,e,n),g=Gv("x",t,e,n);if(1===s.length&&g.shape.length>1)for(var v=1;v<g.shape.length;v++)s.push(0),l.push(g.shape[v]),c.push(c[0]);return[Dl(g,s,l,c,p,h,f,d,m)];case"Pack":return _e(function(){var r=Gv("axis",t,e,n),i=Gv("tensors",t,e,n),a=i[0].shape,o=i[0].squeeze().shape,s=i.map(function(t){var e=Y.arraysEqual(t.shape,a);if(!e&&!Y.arraysEqual(t.squeeze().shape,o))throw new Error("the input tensors shape does not match");return e?t:t.reshape(a)});return[or(s,r)]});case"Unpack":return _e(function(){var r=Gv("axis",t,e,n),i=Gv("tensor",t,e,n);return lr(i,r)});case"Tile":var y=Gv("reps",t,e,n);return[sr(Gv("x",t,e,n),y)];case"Split":case"SplitV":r=Gv("axis",t,e,n);var b=Gv("numOrSizeSplits",t,e,n);return En(Gv("x",t,e,n),b,r);case"ScatterNd":o=Gv("indices",t,e,n);var x=Gv("values",t,e,n),w=Gv("shape",t,e,n);return[_l(o,x,w)];case"GatherNd":var N=Gv("x",t,e,n);return o=Gv("indices",t,e,n),[Vl(N,o)];case"SparseToDense":o=Gv("sparseIndices",t,e,n),w=Gv("outputShape",t,e,n);var C=Gv("sparseValues",t,e,n),E=Gv("defaultValue",t,e,n);return[Bl(o,C,w,C.dtype===E.dtype?E:E.asType(C.dtype))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Vy=function(t,e,n){switch(t.op){case"FFT":return[Fl(Gv("x",t,e,n))];case"IFFT":return[Ml(Gv("x",t,e,n))];case"RFFT":return[zl(Gv("x",t,e,n))];case"IRFFT":return[Ll(Gv("x",t,e,n))];default:throw TypeError("Node type "+t.op+" is not implemented")}},Wy=function(t,e,n){switch(t.op){case"Cast":return[Vn(Gv("x",t,e,n),Gv("dtype",t,e,n))];case"ExpandDims":var r=Gv("axis",t,e,n);return[Gn(Gv("x",t,e,n),r)];case"Squeeze":return r=Gv("axis",t,e,n),[ar(Gv("x",t,e,n),r)];case"Reshape":return[rr(Gv("x",t,e,n),Gv("shape",t,e,n))];case"PadV2":case"Pad":return[$n(Gv("x",t,e,n),Xv(Gv("padding",t,e,n),2),Gv("constantValue",t,e,n))];case"SpaceToBatchND":var i=Gv("blockShape",t,e,n),a=Xv(Gv("paddings",t,e,n),2);return[ir(Gv("x",t,e,n),i,a)];case"BatchToSpaceND":i=Gv("blockShape",t,e,n);var o=Xv(Gv("crops",t,e,n),2);return[Bn(Gv("x",t,e,n),i,o)];case"DepthToSpace":var s=Gv("blockSize",t,e,n),u=Gv("dataFormat",t,e,n).toUpperCase();return[jn(Gv("x",t,e,n),s,u)];default:throw TypeError("Node type "+t.op+" is not implemented")}};function Uy(t,e,n){var r=function(t,e,n){switch(t.category){case"arithmetic":return Iy(t,e,n);case"basic_math":return Ay(t,e,n);case"control":return function(t,e,n){return Vv(this,void 0,void 0,function(){var r,i,a,o,s,u,l,c,p,h,f,d,m,g,v,y,b,x,w,N,C,E,S,k,I,A,R,T,D,O,_,F,M,z;return Wv(this,function(L){switch(L.label){case 0:switch(t.op){case"LoopCond":return[3,1];case"Switch":return[3,2];case"Merge":return[3,4];case"Enter":return[3,5];case"Exit":return[3,6];case"NextIteration":return[3,7];case"TensorArrayV3":return[3,8];case"TensorArrayWriteV3":return[3,9];case"TensorArrayReadV3":return[3,10];case"TensorArrayGatherV3":return[3,11];case"TensorArrayScatterV3":return[3,12];case"TensorArrayConcatV3":return[3,13];case"TensorArraySplitV3":return[3,14];case"TensorArraySizeV3":return[3,15];case"TensorArrayCloseV3":return[3,16]}return[3,17];case 1:return[2,[Gv("pred",t,e,n).clone()]];case 2:return r=Gv("pred",t,e,n),i=Gv("data",t,e,n),[4,r.data()];case 3:return[2,L.sent()[0]?[void 0,i.clone()]:[i.clone(),void 0]];case 4:return[2,(a=t.inputNames.find(function(t){return void 0!==Hv(t,e,n)}))?[Hv(a,e,n).clone()]:void 0];case 5:return o=Gv("frameName",t,e,n),s=Gv("tensor",t,e,n),n.enterFrame(o),[2,[s.clone()]];case 6:return u=Gv("tensor",t,e,n),n.exitFrame(),[2,[u.clone()]];case 7:return l=Gv("tensor",t,e,n),n.nextIteration(),[2,[l.clone()]];case 8:return c=Gv("size",t,e,n),p=Gv("dtype",t,e,n),h=Gv("elementShape",t,e,n),f=Gv("dynamicSize",t,e,n),d=Gv("clearAfterRead",t,e,n),m=Gv("identicalElementShapes",t,e,n),g=Gv("name",t,e,n),v=new Ry(g,p,c,h,m,f,d),n.addTensorArray(v),[2,[an(v.id),an(1)]];case 9:return y=Gv("tensorArrayId",t,e,n),b=Gv("index",t,e,n),x=Gv("tensor",t,e,n),n.getTensorArray(y).write(b,x),[2,[an(1)]];case 10:return w=Gv("tensorArrayId",t,e,n),N=Gv("index",t,e,n),[2,[n.getTensorArray(w).read(N)]];case 11:return C=Gv("tensorArrayId",t,e,n),E=Gv("indices",t,e,n),S=Gv("dtype",t,e,n),[2,[n.getTensorArray(C).gather(E,S)]];case 12:return k=Gv("tensorArrayId",t,e,n),I=Gv("indices",t,e,n),A=Gv("tensor",t,e,n),n.getTensorArray(k).scatter(I,A),[2,[an(1)]];case 13:return R=Gv("tensorArrayId",t,e,n),T=n.getTensorArray(R),D=Gv("dtype",t,e,n),[2,[T.concat(D)]];case 14:return O=Gv("tensorArrayId",t,e,n),_=Gv("tensor",t,e,n),F=Gv("lengths",t,e,n),n.getTensorArray(O).split(F,_),[2,[an(1)]];case 15:return M=Gv("tensorArrayId",t,e,n),[2,[an(n.getTensorArray(M).size(),"int32")]];case 16:return z=Gv("tensorArrayId",t,e,n),n.getTensorArray(z).clearAndClose(),[2,[]];case 17:throw TypeError("Node type "+t.op+" is not implemented")}})})}(t,e,n);case"convolution":return Ty(t,e,n);case"creation":return Dy(t,e,n);case"dynamic":return function(t,e,n){return Vv(this,void 0,void 0,function(){var r,i,a,o,s;return Wv(this,function(u){switch(u.label){case 0:switch(t.op){case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":return[3,1];case"Where":return[3,3];case"ListDiff":return[3,5]}return[3,6];case 1:return r=Gv("boxes",t,e,n),i=Gv("scores",t,e,n),a=Gv("maxOutputSize",t,e,n),o=Gv("iouThreshold",t,e,n),s=Gv("scoreThreshold",t,e,n),[4,mc.nonMaxSuppressionAsync(r,i,a,o,s)];case 2:return[2,[u.sent()]];case 3:return[4,Gs(Gv("condition",t,e,n))];case 4:return[2,[u.sent()]];case 5:return[2,cr(Gv("x",t,e,n),Gv("y",t,e,n))];case 6:throw TypeError("Node type "+t.op+" is not implemented")}})})}(t,e,n);case"evaluation":return Oy(t,e,n);case"image":return Fy(t,e,n);case"graph":return _y(t,e,n);case"logical":return My(t,e,n);case"matrices":return zy(t,e,n);case"normalization":return Ly(t,e,n);case"reduction":return Py(t,e,n);case"slice_join":return By(t,e,n);case"spectral":return Vy(t,e,n);case"transformation":return Wy(t,e,n);case"custom":var r=jv(t.op);if(r&&r.customExecutor)return r.customExecutor(new ky(t,e,n));throw TypeError("Custom op "+t.op+" is not registered.");default:throw TypeError("Unknown op '"+t.op+"'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()")}}(t,e,n);return r instanceof Promise?r.then(function(t){return[].concat(t)}):[].concat(r)}var jy=function(){function t(t,e){this.weightMap=t,this.tensorArrayMap=e,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}return t.prototype.newFrame=function(t,e){return{id:t,frameName:e,iterationId:0}},Object.defineProperty(t.prototype,"currentContext",{get:function(){return this.contexts},set:function(t){this.contexts!==t&&(this.contexts=t,this.generateCurrentContextIds())},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"currentContextId",{get:function(){return this._currentContextIds[0]},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"currentContextIds",{get:function(){return this._currentContextIds},enumerable:!0,configurable:!0}),t.prototype.generateCurrentContextIds=function(){for(var t=[],e=0;e<this.contexts.length-1;e++){var n=this.contexts.slice(0,this.contexts.length-e);t.push(this.contextIdforContexts(n))}t.push(""),this._currentContextIds=t},t.prototype.contextIdforContexts=function(t){return t?t.map(function(t){return 0===t.id&&0===t.iterationId?"":t.frameName+"-"+t.iterationId}).join("/"):""},t.prototype.enterFrame=function(t){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,t)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))},t.prototype.exitFrame=function(){if(!(this.contexts&&this.contexts.length>1))throw new Error("Cannot exit frame, the context is empty");this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift()},t.prototype.nextIteration=function(){if(!(this.contexts&&this.contexts.length>0))throw new Error("Cannot increase frame iteration, the context is empty");this.contexts=this.contexts.slice(),this.lastId++;var t=Object.assign({},this.contexts[this.contexts.length-1]);t.iterationId+=1,t.id=this.lastId,this.contexts.splice(-1,1,t),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))},t.prototype.getWeight=function(t){return this.weightMap[t]},t.prototype.addTensorArray=function(t){this.tensorArrayMap[t.id]=t},t.prototype.getTensorArray=function(t){return this.tensorArrayMap[t]},t}();function Gy(t,e,n){for(var r=new Set,i=[],a=null,o=null,s=new Set,u=e.slice();u.length>0;){var l=u.pop();(Ky(l)||$y(l))&&null==a&&(o=(a=l).children.map(function(t){return t.name}).filter(function(t){return r.has(t)})),r.add(l.name),null==n[l.name]&&null==t[l.name]&&(0!==l.inputs.length?l.inputs.forEach(function(t){s.has(t.name)||(s.add(t.name),u.push(t))}):i.push(l.name))}return{inputs:t,outputs:e,usedNodes:r,missingInputs:i,dynamicNode:a,syncInputs:o}}var Hy=["Switch","Merge","Enter","Exit","NextIteration"],qy=["NonMaxSuppressionV2","NonMaxSuppressionV3","Where"];function Ky(t){return Hy.indexOf(t.op)>=0}function $y(t){return qy.indexOf(t.op)>=0}var Xy=function(){function t(t){this.graph=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this.placeholders=t.placeholders,this._outputs=t.outputs}return Object.defineProperty(t.prototype,"weightMap",{get:function(){return this._weightMap},set:function(t){var e=Object.keys(t).map(function(e){return t[e].map(function(t){return t.id})});this.weightIds=[].concat.apply([],e),this._weightMap=t},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"inputs",{get:function(){return this.placeholders.map(function(t){return{name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}})},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"outputs",{get:function(){return this._outputs.map(function(t){return{name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}})},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"inputNodes",{get:function(){return this.placeholders.map(function(t){return t.name})},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"outputNodes",{get:function(){return this.outputs.map(function(t){return t.name})},enumerable:!0,configurable:!0}),t.prototype.getCompilationKey=function(t,e){var n=t.map(function(t){return t.name}).sort(),r=e.map(function(t){return t.name}).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)},t.prototype.compile=function(t,e){var n=Gy(t,e,this.weightMap),r=n.missingInputs,i=n.dynamicNode,a=n.syncInputs;if(null!=i)throw new Error("This execution contains the node '"+i.name+"', which has the dynamic op '"+i.op+"'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs ["+a+"]");if(r.length>0){var o=e.map(function(t){return t.name}),s=Object.keys(t);throw new Error("Cannot compute the outputs ["+o+"] from the provided inputs ["+s+"]. Missing the following inputs: ["+r+"]")}return function(t,e,n){var r=n.usedNodes,i=n.inputs,a=[];Object.keys(i).map(function(e){return t.nodes[e]}).forEach(function(t){r.has(t.name)&&a.push(t)}),t.weights.forEach(function(t){r.has(t.name)&&a.push(t)});for(var o=new Set,s=[];a.length>0;){var u=a.pop();o.add(u.name),e[u.name]||s.push(u),u.children.forEach(function(t){!o.has(t.name)&&r.has(t.name)&&t.inputs.every(function(t){return o.has(t.name)})&&a.push(t)})}return s}(this.graph,this.weightMap,n)},t.prototype.execute=function(t,e){var n=this,r=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),this.checkOutputs(e);var i=r.map(function(t){return n.graph.nodes[t]}),a=e.map(function(t){return n.graph.nodes[$v(t)[0]]}),o=this.getCompilationKey(i,a),s=this.compiledMap.get(o);null==s&&(s=this.compile(t,a),this.compiledMap.set(o,s));var u={};return _e(function(){var r=new jy(n._weightMap,u),i=Bv({},n.weightMap);Object.keys(t).forEach(function(e){i[e]=[t[e]]});for(var a=n.getFrozenTensorIds(i),o={},l=0;l<s.length;l++){var c=s[l];if(!i[c.name]){var p=Uy(c,i,r);if(p instanceof Promise)throw new Error("The execution of the op '"+c.op+"' returned a promise. Please use model.executeAsync() instead.");i[c.name]=p,n.checkTensorForDisposal(c.name,c,i,r,a,e,o)}}return e.map(function(t){return Hv(t,i,r)})})},t.prototype.getFrozenTensorIds=function(t){var e=[].concat.apply([],Object.keys(t).map(function(e){return t[e]}).map(function(t){return t.map(function(t){return t.id})}));return new Set(e)},t.prototype.checkTensorForDisposal=function(t,e,n,r,i,a,o){"control"!==e.category&&-1===a.indexOf(t)&&(n[t].forEach(function(t){null!=t&&(o[t.id]=(o[t.id]||0)+e.children.length)}),e.inputs.forEach(function(t){if("control"!==t.category){var e=function(t,e,n){return e[Kv(t,n.currentContextId)]}(t.name,n,r);null!=e&&e.forEach(function(t){if(t&&!i.has(t.id)){var e=o[t.id];1===e?(t.dispose(),delete o[t.id]):null!=e&&o[t.id]--}})}}))},t.prototype.executeAsync=function(t,e){return Vv(this,void 0,void 0,function(){var n,r,i,a,o,s,u=this;return Wv(this,function(l){switch(l.label){case 0:return this.checkInputs(t),this.checkInputShapeAndType(t),this.checkOutputs(e),n={},r=new jy(this._weightMap,n),[4,this.executeWithControlFlow(t,r,e)];case 1:return i=l.sent(),a=e.map(function(t){return Hv(t,i,r)}),o=new Set(a.map(function(t){return t.id})),s=new Set(Object.keys(t).map(function(e){return t[e].id})),Object.keys(i).forEach(function(t){i[t].forEach(function(t){!t||t.isDisposed||o.has(t.id)||s.has(t.id)||-1!==u.weightIds.indexOf(t.id)||t.dispose()})}),[2,a]}})})},t.prototype.executeWithControlFlow=function(t,e,n){return Vv(this,void 0,void 0,function(){var r,i,a,o,s,u,l,c,p,h,f,d,m,g,v,y,b=this;return Wv(this,function(x){switch(x.label){case 0:r=Object.keys(t),i=r.map(function(t){return b.graph.nodes[t]}),a=n.map(function(t){return b.graph.nodes[$v(t)[0]]}),o=Gy(t,a,this.weightMap),s=o.usedNodes,u=o.missingInputs,l=o.dynamicNode,c=o.syncInputs,p=i.concat(this.graph.weights).map(function(t){return{node:t,contexts:e.currentContext}}),h=Bv({},this.weightMap),Object.keys(t).forEach(function(e){h[e]=[t[e]]}),f={},d=this.getFrozenTensorIds(h),m={},x.label=1;case 1:return p.length>0?(g=this.processStack(i,p,e,h,m,d,n,f,s),[4,Promise.all(g)]):[3,3];case 2:return x.sent(),[3,1];case 3:if(null==l&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead."),(v=a.filter(function(t){return!Ky(t)&&!Hv(t.name,h,e)}).map(function(t){return t.name})).length>0)throw y="",null!=l&&(y="Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs ["+c+"]"),new Error("Cannot compute the outputs ["+v+"] from the provided inputs ["+r+"]. Consider providing the following inputs: ["+u+"]. "+y);return[2,h]}})})},t.prototype.processStack=function(t,e,n,r,i,a,o,s,u){for(var l=this,c=[],p=function(){var p=e.pop();n.currentContext=p.contexts;var f="";if("Enter"===p.node.op&&Gv("isConstant",p.node,r,n)&&(f=qv(p.node.name,n)[0]),-1===t.indexOf(p.node)){var d=Uy(p.node,r,n);f||(f=qv(p.node.name,n)[0]);var m=n.currentContext;d instanceof Promise?c.push(d.then(function(t){return r[f]=t,n.currentContext=m,l.checkTensorForDisposal(f,p.node,r,n,a,o,s),l.processChildNodes(p.node,e,n,r,i,u),t})):(r[f]=d,h.checkTensorForDisposal(f,p.node,r,n,a,o,s),h.processChildNodes(p.node,e,n,r,i,u))}else h.processChildNodes(p.node,e,n,r,i,u)},h=this;e.length>0;)p();return c},t.prototype.processChildNodes=function(t,e,n,r,i,a){t.children.forEach(function(t){var 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Please provide a url or an IOHandler that loads the model");return null==e&&(e={}),e.fromTFHub&&null==t.load&&(t.endsWith("/")||(t+="/"),t=""+t+Jy+Yy),[4,(n=new Zy(t,e)).load()];case 1:return r.sent(),[2,n]}})})},t.deregisterOp=function(t){delete Uv[t]},t.registerOp=function(t,e){var n={tfOpName:t,category:"custom",inputs:[],attrs:[],customExecutor:e};Uv[t]=n},t.version_converter="1.2.9",Object.defineProperty(t,"__esModule",{value:!0})});
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\ No newline at end of file
diff --git a/spaces/merve/measuring-fairness/source/anonymization/annotations.js b/spaces/merve/measuring-fairness/source/anonymization/annotations.js
deleted file mode 100644
index ed45db46369d1bb2a709b20bd97c29451d4284c0..0000000000000000000000000000000000000000
--- a/spaces/merve/measuring-fairness/source/anonymization/annotations.js
+++ /dev/null
@@ -1,38 +0,0 @@
-var annotations = 
-
-[
-]
-
-
-
-
-function addSwoop(c){
-  var swoopy = d3.swoopyDrag()
-    .x(d => c.x(d.x))
-    .y(d => c.y(d.y))
-    .draggable(0)
-    .annotations(annotations)
-
-  var swoopySel = c.svg.append('g.annotations').call(swoopy)
-
-  c.svg.append('marker#arrow')
-      .attr('viewBox', '-10 -10 20 20')
-      .attr('markerWidth', 20)
-      .attr('markerHeight', 20)
-      .attr('orient', 'auto')
-    .append('path').at({d: 'M-6.75,-6.75 L 0,0 L -6.75,6.75'})
-
-
-  swoopySel.selectAll('path').attr('marker-end', 'url(#arrow)')
-  window.annotationSel = swoopySel.selectAll('g')
-    .st({fontSize: 12, opacity: d => d.slide == 0 ? 1 : 0})
-
-  swoopySel.selectAll('text')
-    .each(function(d){
-      d3.select(this)
-        .text('')                        //clear existing text
-        .tspans(d3.wordwrap(d.text, d.width || 20), 12) //wrap after 20 char
-    })  
-}
-
-
diff --git a/spaces/merve/measuring-fairness/source/third_party/recirc.js b/spaces/merve/measuring-fairness/source/third_party/recirc.js
deleted file mode 100644
index 37b65f4b8cf3c3ba504a0a3b906f8c19befc6730..0000000000000000000000000000000000000000
--- a/spaces/merve/measuring-fairness/source/third_party/recirc.js
+++ /dev/null
@@ -1,58 +0,0 @@
-/* Copyright 2020 Google LLC. 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.
-==============================================================================*/
-
-
-
-
-d3.loadData('../posts.json', (err, res) => {
-  var posts = res[0]
-    .filter(d => !window.location.href.includes(d.permalink))
-    .filter(d => d.shareimg.includes('http'))
-  posts = d3.shuffle(posts)
-
-  var isMobile = innerWidth < 900 
-  var postSel = d3.select('#recirc').html('').appendMany('a.post', posts)
-    .st({
-      width: isMobile ? '100%' : '330px', 
-      display: 'inline-block', 
-      verticalAlign: 'top',
-      marginRight: isMobile ? 0 : 30,
-      textDecoration: 'none',
-    })
-    .at({href: d => '..' + d.permalink})
-
-
-  postSel.append('div.img')
-    .st({
-      width: '100%', 
-      height: 200,
-      backgroundImage: d => `url(${d.shareimgabstract || d.shareimg})`,
-      backgroundSize: 'cover',
-      backgroundPosition: 'center',
-    })
-
-  postSel.append('p.title')
-    .text(d => d.shorttitle || d.title)
-    .st({
-      verticalAlign: 'top',
-      marginTop: 10,
-      textDecoration: 'none',
-    })
-
-  postSel.append('p.summary')
-    .text(d => d.socialsummary || d.summary)
-
-
-})
\ No newline at end of file
diff --git a/spaces/merve/uncertainty-calibration/source/anonymization/make-slides.js b/spaces/merve/uncertainty-calibration/source/anonymization/make-slides.js
deleted file mode 100644
index 3feff55ba9248cee61cd7ec881fade8ef661e67c..0000000000000000000000000000000000000000
--- a/spaces/merve/uncertainty-calibration/source/anonymization/make-slides.js
+++ /dev/null
@@ -1,98 +0,0 @@
-window.makeSlides = function(){
-  var slides = [
-    {
-      xKey: 'grid',
-      circleDelayFn: d => axii.ageScale(d.age),
-      showFlipRect: 0,
-      populationTarget: 144,
-      headsProbTarget: .5,
-    },
-    {
-      xKey: 'age',
-      showAgeAxis: 1,
-    },
-    {
-      xKey: 'ageState',
-      showStateAxis: 1,
-    },
-    {
-      showUniqueBox: 1
-    },
-    {
-      xKey: 'ageStateSeason',
-      showUniqueBox: 1,
-      showUniqueSeasonBox: 1,
-      showSeasonAxis: 1,
-    },
-    {
-      xKey: 'heads',
-      showUniqueBox: 0,
-      showUniqueSeasonBox: 0,
-      showSeasonAxis: 0,
-      showAgeAxis: 0,
-      showStateAxis: 0,
-      showHeadAxis: 1,  
-    },
-    {
-      showFlipCircle: 1,
-      showHeadCaptionAxis: 1,
-    },
-
-    // Flip coin
-    {
-      xKey: 'plagerizedShifted',
-      showHeadAxis: 0,
-      showHeadCaptionAxis: 0,
-      showHistogramAxis: 1,
-    },
-
-    // Exactly how far off can these estimates be after adding noise? Flip more coins to see the distribution.
-    {
-      enterHistogram: 1,
-      showHistogram: 1,
-      // showPlagerizedAxis: 0,
-      showEstimate: 1,
-    },
-
-    // Reducing the random noise increases our point estimate, but risks leaking information about students.
-    {
-      animateHeadsProbSlider: 1,
-      animatePopulationSlider: 1,
-      enterHistogram: 0,
-      name: 'noise', 
-      headsProbTarget: .35,
-    },
-
-    // If we collect information from lots of people, we can have high accuracy and protect everyone's privacy.
-    {
-      showEstimate: 0,
-      showAllStudents: 1,
-      name: 'population',
-      animateHeadsProbSlider: -1,
-      animatePopulationSlider: 1,
-      populationTarget: 400,
-    },
-
-  ]
-
-  var keys = []
-  slides.forEach((d, i) => {
-    keys = keys.concat(d3.keys(d))
-    d.index = i
-  })
-  _.uniq(keys).forEach(str => {
-    var prev = null
-    slides.forEach(d => {
-      if (typeof(d[str]) === 'undefined'){
-        d[str] = prev
-      }
-      prev = d[str]
-    }) 
-  })
-
-  return slides
-}
-
-
-
-if (window.init) window.init()
diff --git a/spaces/micole66/test/README.md b/spaces/micole66/test/README.md
deleted file mode 100644
index e2e9551423abd306088e5bccd294ec5b76f88bf6..0000000000000000000000000000000000000000
--- a/spaces/micole66/test/README.md
+++ /dev/null
@@ -1,28 +0,0 @@
----
-title: T0 Generation
-emoji: 🌍
-colorFrom: blue
-colorTo: yellow
-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` or `streamlit`
-`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).  
-Path is relative to the root of the repository.
-`pinned`: _boolean_  
-Whether the Space stays on top of your list.
\ No newline at end of file
diff --git a/spaces/mikebars/huggingface/assets/index-28811a6d.js b/spaces/mikebars/huggingface/assets/index-28811a6d.js
deleted file mode 100644
index c6b9922854c2de7dc26081fc7f474d5e3cd7e70f..0000000000000000000000000000000000000000
--- a/spaces/mikebars/huggingface/assets/index-28811a6d.js
+++ /dev/null
@@ -1,41 +0,0 @@
-var hc=Object.defineProperty;var yc=(e,t,n)=>t in e?hc(e,t,{enumerable:!0,configurable:!0,writable:!0,value:n}):e[t]=n;var Et=(e,t,n)=>(yc(e,typeof t!="symbol"?t+"":t,n),n);(function(){const t=document.createElement("link").relList;if(t&&t.supports&&t.supports("modulepreload"))return;for(const l of document.querySelectorAll('link[rel="modulepreload"]'))r(l);new MutationObserver(l=>{for(const i of l)if(i.type==="childList")for(const o of i.addedNodes)o.tagName==="LINK"&&o.rel==="modulepreload"&&r(o)}).observe(document,{childList:!0,subtree:!0});function n(l){const i={};return l.integrity&&(i.integrity=l.integrity),l.referrerPolicy&&(i.referrerPolicy=l.referrerPolicy),l.crossOrigin==="use-credentials"?i.credentials="include":l.crossOrigin==="anonymous"?i.credentials="omit":i.credentials="same-origin",i}function r(l){if(l.ep)return;l.ep=!0;const i=n(l);fetch(l.href,i)}})();var Mr={},vc={get exports(){return Mr},set exports(e){Mr=e}},ul={},ne={},gc={get exports(){return ne},set exports(e){ne=e}},T={};/**
- * @license React
- * react.production.min.js
- *
- * 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.
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q.imageClassification({data:e.inputs,model:e.model});e.setOutput(n);break}case"image-segmentation":{const n=await q.imageSegmentation({data:e.inputs,model:e.model});e.setOutput(n);break}case"object-detection":{const n=await q.objectDetection({data:e.inputs,model:e.model});e.setOutput(n);break}case"question-answering":{const n=await q.questionAnswering({inputs:{context:e.inputs,question:e.inputs},model:e.model});e.setOutput(n);break}case"summarization":{const n=await q.summarization({inputs:e.inputs,model:e.model});e.setOutput(n);break}case"table-question-answering":{const n=await q.tableQuestionAnswering({inputs:{query:e.inputs,table:{[e.inputs]:[e.inputs]}},model:e.model});e.setOutput(n);break}case"text-classification":{const n=await q.textClassification({inputs:e.inputs,model:e.model});e.setOutput(n);break}case"text-generation":{const n=await q.textGeneration({inputs:e.inputs,model:e.model});e.setOutput(n);break}case"text-to-image":{const n=await 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text-6xl",children:"🤗"}),P(Mp,{setTask:t,task:e}),P(jp,{model:n,setModel:r,task:e}),P($p,{inputs:l,model:n,setInputs:i,task:e}),P(Vp,{inputs:l,loading:o,model:n,setInputs:i,setOutput:c,task:e}),P(Bp,{inputs:l,loading:o,model:n,setLoading:u,setOutput:c,task:e}),P(Qp,{loading:o,output:s,task:e})]})})},Xp=()=>{const e="root",t=document.getElementById(e);if(t){const n=pc(t),r=P(ne.StrictMode,{children:P(Kp,{})});n.render(r)}};Xp();
diff --git a/spaces/mikkoar/marco/src/lib/storage.ts b/spaces/mikkoar/marco/src/lib/storage.ts
deleted file mode 100644
index a5b7825c4f76a28c704da512ae39e8bb45addd09..0000000000000000000000000000000000000000
--- a/spaces/mikkoar/marco/src/lib/storage.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { getMany, set, del, clear } from 'idb-keyval';
-
-export const Storage = {
-  async get(key: string | string[] | null): Promise<any> {
-    if (key === null) return null;
-    if (typeof key === 'string') {
-      key = [key]
-    }
-    const returnData: Record<string, any> = {}
-    const values = await getMany(key)
-    key.forEach((k, idx)=> {
-      returnData[k] = values[idx]
-    })
-    return returnData;
-  },
-  async set(object: any) {
-    for (let key of Object.keys(object)) {
-      await set(key, object[key])
-    }
-  },
-  async remove(key: string) {
-    return del(key);
-  },
-  async clear() {
-    return clear();
-  }
-}
diff --git a/spaces/mingyuan/ReMoDiffuse/configs/remodiffuse/remodiffuse_t2m.py b/spaces/mingyuan/ReMoDiffuse/configs/remodiffuse/remodiffuse_t2m.py
deleted file mode 100644
index e9bf8a6b9e3c306defef07ddfc172bd7a435aab9..0000000000000000000000000000000000000000
--- a/spaces/mingyuan/ReMoDiffuse/configs/remodiffuse/remodiffuse_t2m.py
+++ /dev/null
@@ -1,115 +0,0 @@
-_base_ = ['../_base_/datasets/human_ml3d_bs128.py']
-
-# checkpoint saving
-checkpoint_config = dict(interval=1)
-
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-
-# optimizer
-optimizer = dict(type='Adam', lr=2e-4)
-optimizer_config = dict(grad_clip=None)
-# learning policy
-lr_config = dict(policy='CosineAnnealing', min_lr_ratio=2e-5, by_epoch=False)
-runner = dict(type='EpochBasedRunner', max_epochs=40)
-
-log_config = dict(
-    interval=50,
-    hooks=[
-        dict(type='TextLoggerHook'),
-        # dict(type='TensorboardLoggerHook')
-    ])
-
-input_feats = 263
-max_seq_len = 196
-latent_dim = 512
-time_embed_dim = 2048
-text_latent_dim = 256
-ff_size = 1024
-num_heads = 8
-dropout = 0
-
-# model settings
-model = dict(
-    type='MotionDiffusion',
-    model=dict(
-        type='ReMoDiffuseTransformer',
-        input_feats=input_feats,
-        max_seq_len=max_seq_len,
-        latent_dim=latent_dim,
-        time_embed_dim=time_embed_dim,
-        num_layers=4,
-        ca_block_cfg=dict(
-            type='SemanticsModulatedAttention',
-            latent_dim=latent_dim,
-            text_latent_dim=text_latent_dim,
-            num_heads=num_heads,
-            dropout=dropout,
-            time_embed_dim=time_embed_dim
-        ),
-        ffn_cfg=dict(
-            latent_dim=latent_dim,
-            ffn_dim=ff_size,
-            dropout=dropout,
-            time_embed_dim=time_embed_dim
-        ),
-        text_encoder=dict(
-            pretrained_model='clip',
-            latent_dim=text_latent_dim,
-            num_layers=2,
-            ff_size=2048,
-            dropout=dropout,
-            use_text_proj=False
-        ),
-        retrieval_cfg=dict(
-            num_retrieval=2,
-            stride=4,
-            num_layers=2,
-            num_motion_layers=2,
-            kinematic_coef=0.1,
-            topk=2,
-            retrieval_file='data/database/t2m_text_train.npz',
-            latent_dim=latent_dim,
-            output_dim=latent_dim,
-            max_seq_len=max_seq_len,
-            num_heads=num_heads,
-            ff_size=ff_size,
-            dropout=dropout,
-            ffn_cfg=dict(
-                latent_dim=latent_dim,
-                ffn_dim=ff_size,
-                dropout=dropout,
-            ),
-            sa_block_cfg=dict(
-                type='EfficientSelfAttention',
-                latent_dim=latent_dim,
-                num_heads=num_heads,
-                dropout=dropout
-            ),
-        ),
-        scale_func_cfg=dict(
-            coarse_scale=6.5,
-            both_coef=0.52351,
-            text_coef=-0.28419,
-            retr_coef=2.39872
-        )
-    ),
-    loss_recon=dict(type='MSELoss', loss_weight=1, reduction='none'),
-    diffusion_train=dict(
-        beta_scheduler='linear',
-        diffusion_steps=1000,
-        model_mean_type='start_x',
-        model_var_type='fixed_large',
-    ),
-    diffusion_test=dict(
-        beta_scheduler='linear',
-        diffusion_steps=1000,
-        model_mean_type='start_x',
-        model_var_type='fixed_large',
-        respace='15,15,8,6,6',
-    ),
-    inference_type='ddim'
-)
\ No newline at end of file
diff --git a/spaces/miyaaa666/bingo/src/components/ui/textarea.tsx b/spaces/miyaaa666/bingo/src/components/ui/textarea.tsx
deleted file mode 100644
index e25af722c7a5dc1121a9ab58d6716952f9f76081..0000000000000000000000000000000000000000
--- a/spaces/miyaaa666/bingo/src/components/ui/textarea.tsx
+++ /dev/null
@@ -1,24 +0,0 @@
-import * as React from 'react'
-
-import { cn } from '@/lib/utils'
-
-export interface TextareaProps
-  extends React.TextareaHTMLAttributes<HTMLTextAreaElement> {}
-
-const Textarea = React.forwardRef<HTMLTextAreaElement, TextareaProps>(
-  ({ className, ...props }, ref) => {
-    return (
-      <textarea
-        className={cn(
-          'flex min-h-[80px] w-full rounded-md border border-input bg-transparent px-3 py-2 text-sm ring-offset-background placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50',
-          className
-        )}
-        ref={ref}
-        {...props}
-      />
-    )
-  }
-)
-Textarea.displayName = 'Textarea'
-
-export { Textarea }
diff --git a/spaces/mshukor/UnIVAL/fairseq/examples/noisychannel/rerank_tune.py b/spaces/mshukor/UnIVAL/fairseq/examples/noisychannel/rerank_tune.py
deleted file mode 100644
index b2e8b7594a370b2462f77252d54d7ef80e290f7c..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/fairseq/examples/noisychannel/rerank_tune.py
+++ /dev/null
@@ -1,102 +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 argparse
-import random
-
-import numpy as np
-from fairseq import options
-
-from examples.noisychannel import rerank, rerank_options
-
-
-def random_search(args):
-    param_values = []
-    tuneable_parameters = ["lenpen", "weight1", "weight2", "weight3"]
-    initial_params = [args.lenpen, args.weight1, args.weight2, args.weight3]
-    for i, elem in enumerate(initial_params):
-        if type(elem) is not list:
-            initial_params[i] = [elem]
-        else:
-            initial_params[i] = elem
-
-    tune_parameters = args.tune_param.copy()
-    for i in range(len(args.tune_param)):
-        assert args.upper_bound[i] >= args.lower_bound[i]
-        index = tuneable_parameters.index(args.tune_param[i])
-        del tuneable_parameters[index]
-        del initial_params[index]
-
-    tune_parameters += tuneable_parameters
-    param_values += initial_params
-    random.seed(args.seed)
-
-    random_params = np.array(
-        [
-            [
-                random.uniform(args.lower_bound[i], args.upper_bound[i])
-                for i in range(len(args.tune_param))
-            ]
-            for k in range(args.num_trials)
-        ]
-    )
-    set_params = np.array(
-        [
-            [initial_params[i][0] for i in range(len(tuneable_parameters))]
-            for k in range(args.num_trials)
-        ]
-    )
-    random_params = np.concatenate((random_params, set_params), 1)
-
-    rerank_args = vars(args).copy()
-    if args.nbest_list:
-        rerank_args["gen_subset"] = "test"
-    else:
-        rerank_args["gen_subset"] = args.tune_subset
-
-    for k in range(len(tune_parameters)):
-        rerank_args[tune_parameters[k]] = list(random_params[:, k])
-
-    if args.share_weights:
-        k = tune_parameters.index("weight2")
-        rerank_args["weight3"] = list(random_params[:, k])
-
-    rerank_args = argparse.Namespace(**rerank_args)
-    best_lenpen, best_weight1, best_weight2, best_weight3, best_score = rerank.rerank(
-        rerank_args
-    )
-    rerank_args = vars(args).copy()
-    rerank_args["lenpen"] = [best_lenpen]
-    rerank_args["weight1"] = [best_weight1]
-    rerank_args["weight2"] = [best_weight2]
-    rerank_args["weight3"] = [best_weight3]
-
-    # write the hypothesis from the valid set from the best trial
-
-    if args.gen_subset != "valid":
-        rerank_args["gen_subset"] = "valid"
-        rerank_args = argparse.Namespace(**rerank_args)
-        rerank.rerank(rerank_args)
-
-    # test with the best hyperparameters on gen subset
-    rerank_args = vars(args).copy()
-    rerank_args["gen_subset"] = args.gen_subset
-    rerank_args["lenpen"] = [best_lenpen]
-    rerank_args["weight1"] = [best_weight1]
-    rerank_args["weight2"] = [best_weight2]
-    rerank_args["weight3"] = [best_weight3]
-    rerank_args = argparse.Namespace(**rerank_args)
-    rerank.rerank(rerank_args)
-
-
-def cli_main():
-    parser = rerank_options.get_tuning_parser()
-    args = options.parse_args_and_arch(parser)
-
-    random_search(args)
-
-
-if __name__ == "__main__":
-    cli_main()
diff --git a/spaces/mshukor/UnIVAL/fairseq/examples/speech_recognition/utils/wer_utils.py b/spaces/mshukor/UnIVAL/fairseq/examples/speech_recognition/utils/wer_utils.py
deleted file mode 100644
index cf6f3d09ba41a46ad4d7968fb3c286dd53d15c38..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/fairseq/examples/speech_recognition/utils/wer_utils.py
+++ /dev/null
@@ -1,381 +0,0 @@
-#!/usr/bin/env python3
-
-# 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 __future__ import absolute_import, division, print_function, unicode_literals
-
-import re
-from collections import deque
-from enum import Enum
-
-import numpy as np
-
-
-"""
-    Utility modules for computation of Word Error Rate,
-    Alignments, as well as more granular metrics like
-    deletion, insersion and substitutions.
-"""
-
-
-class Code(Enum):
-    match = 1
-    substitution = 2
-    insertion = 3
-    deletion = 4
-
-
-class Token(object):
-    def __init__(self, lbl="", st=np.nan, en=np.nan):
-        if np.isnan(st):
-            self.label, self.start, self.end = "", 0.0, 0.0
-        else:
-            self.label, self.start, self.end = lbl, st, en
-
-
-class AlignmentResult(object):
-    def __init__(self, refs, hyps, codes, score):
-        self.refs = refs  # std::deque<int>
-        self.hyps = hyps  # std::deque<int>
-        self.codes = codes  # std::deque<Code>
-        self.score = score  # float
-
-
-def coordinate_to_offset(row, col, ncols):
-    return int(row * ncols + col)
-
-
-def offset_to_row(offset, ncols):
-    return int(offset / ncols)
-
-
-def offset_to_col(offset, ncols):
-    return int(offset % ncols)
-
-
-def trimWhitespace(str):
-    return re.sub(" +", " ", re.sub(" *$", "", re.sub("^ *", "", str)))
-
-
-def str2toks(str):
-    pieces = trimWhitespace(str).split(" ")
-    toks = []
-    for p in pieces:
-        toks.append(Token(p, 0.0, 0.0))
-    return toks
-
-
-class EditDistance(object):
-    def __init__(self, time_mediated):
-        self.time_mediated_ = time_mediated
-        self.scores_ = np.nan  # Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic>
-        self.backtraces_ = (
-            np.nan
-        )  # Eigen::Matrix<size_t, Eigen::Dynamic, Eigen::Dynamic> backtraces_;
-        self.confusion_pairs_ = {}
-
-    def cost(self, ref, hyp, code):
-        if self.time_mediated_:
-            if code == Code.match:
-                return abs(ref.start - hyp.start) + abs(ref.end - hyp.end)
-            elif code == Code.insertion:
-                return hyp.end - hyp.start
-            elif code == Code.deletion:
-                return ref.end - ref.start
-            else:  # substitution
-                return abs(ref.start - hyp.start) + abs(ref.end - hyp.end) + 0.1
-        else:
-            if code == Code.match:
-                return 0
-            elif code == Code.insertion or code == Code.deletion:
-                return 3
-            else:  # substitution
-                return 4
-
-    def get_result(self, refs, hyps):
-        res = AlignmentResult(refs=deque(), hyps=deque(), codes=deque(), score=np.nan)
-
-        num_rows, num_cols = self.scores_.shape
-        res.score = self.scores_[num_rows - 1, num_cols - 1]
-
-        curr_offset = coordinate_to_offset(num_rows - 1, num_cols - 1, num_cols)
-
-        while curr_offset != 0:
-            curr_row = offset_to_row(curr_offset, num_cols)
-            curr_col = offset_to_col(curr_offset, num_cols)
-
-            prev_offset = self.backtraces_[curr_row, curr_col]
-
-            prev_row = offset_to_row(prev_offset, num_cols)
-            prev_col = offset_to_col(prev_offset, num_cols)
-
-            res.refs.appendleft(curr_row - 1)  # Note: this was .push_front() in C++
-            res.hyps.appendleft(curr_col - 1)
-            if curr_row - 1 == prev_row and curr_col == prev_col:
-                res.codes.appendleft(Code.deletion)
-            elif curr_row == prev_row and curr_col - 1 == prev_col:
-                res.codes.appendleft(Code.insertion)
-            else:
-                # assert(curr_row - 1 == prev_row and curr_col - 1 == prev_col)
-                ref_str = refs[res.refs[0]].label
-                hyp_str = hyps[res.hyps[0]].label
-
-                if ref_str == hyp_str:
-                    res.codes.appendleft(Code.match)
-                else:
-                    res.codes.appendleft(Code.substitution)
-
-                    confusion_pair = "%s -> %s" % (ref_str, hyp_str)
-                    if confusion_pair not in self.confusion_pairs_:
-                        self.confusion_pairs_[confusion_pair] = 1
-                    else:
-                        self.confusion_pairs_[confusion_pair] += 1
-
-            curr_offset = prev_offset
-
-        return res
-
-    def align(self, refs, hyps):
-        if len(refs) == 0 and len(hyps) == 0:
-            return np.nan
-
-        # NOTE: we're not resetting the values in these matrices because every value
-        # will be overridden in the loop below. If this assumption doesn't hold,
-        # be sure to set all entries in self.scores_ and self.backtraces_ to 0.
-        self.scores_ = np.zeros((len(refs) + 1, len(hyps) + 1))
-        self.backtraces_ = np.zeros((len(refs) + 1, len(hyps) + 1))
-
-        num_rows, num_cols = self.scores_.shape
-
-        for i in range(num_rows):
-            for j in range(num_cols):
-                if i == 0 and j == 0:
-                    self.scores_[i, j] = 0.0
-                    self.backtraces_[i, j] = 0
-                    continue
-
-                if i == 0:
-                    self.scores_[i, j] = self.scores_[i, j - 1] + self.cost(
-                        None, hyps[j - 1], Code.insertion
-                    )
-                    self.backtraces_[i, j] = coordinate_to_offset(i, j - 1, num_cols)
-                    continue
-
-                if j == 0:
-                    self.scores_[i, j] = self.scores_[i - 1, j] + self.cost(
-                        refs[i - 1], None, Code.deletion
-                    )
-                    self.backtraces_[i, j] = coordinate_to_offset(i - 1, j, num_cols)
-                    continue
-
-                # Below here both i and j are greater than 0
-                ref = refs[i - 1]
-                hyp = hyps[j - 1]
-                best_score = self.scores_[i - 1, j - 1] + (
-                    self.cost(ref, hyp, Code.match)
-                    if (ref.label == hyp.label)
-                    else self.cost(ref, hyp, Code.substitution)
-                )
-
-                prev_row = i - 1
-                prev_col = j - 1
-                ins = self.scores_[i, j - 1] + self.cost(None, hyp, Code.insertion)
-                if ins < best_score:
-                    best_score = ins
-                    prev_row = i
-                    prev_col = j - 1
-
-                delt = self.scores_[i - 1, j] + self.cost(ref, None, Code.deletion)
-                if delt < best_score:
-                    best_score = delt
-                    prev_row = i - 1
-                    prev_col = j
-
-                self.scores_[i, j] = best_score
-                self.backtraces_[i, j] = coordinate_to_offset(
-                    prev_row, prev_col, num_cols
-                )
-
-        return self.get_result(refs, hyps)
-
-
-class WERTransformer(object):
-    def __init__(self, hyp_str, ref_str, verbose=True):
-        self.ed_ = EditDistance(False)
-        self.id2oracle_errs_ = {}
-        self.utts_ = 0
-        self.words_ = 0
-        self.insertions_ = 0
-        self.deletions_ = 0
-        self.substitutions_ = 0
-
-        self.process(["dummy_str", hyp_str, ref_str])
-
-        if verbose:
-            print("'%s' vs '%s'" % (hyp_str, ref_str))
-            self.report_result()
-
-    def process(self, input):  # std::vector<std::string>&& input
-        if len(input) < 3:
-            print(
-                "Input must be of the form <id> ... <hypo> <ref> , got ",
-                len(input),
-                " inputs:",
-            )
-            return None
-
-        # Align
-        # std::vector<Token> hyps;
-        # std::vector<Token> refs;
-
-        hyps = str2toks(input[-2])
-        refs = str2toks(input[-1])
-
-        alignment = self.ed_.align(refs, hyps)
-        if alignment is None:
-            print("Alignment is null")
-            return np.nan
-
-        # Tally errors
-        ins = 0
-        dels = 0
-        subs = 0
-        for code in alignment.codes:
-            if code == Code.substitution:
-                subs += 1
-            elif code == Code.insertion:
-                ins += 1
-            elif code == Code.deletion:
-                dels += 1
-
-        # Output
-        row = input
-        row.append(str(len(refs)))
-        row.append(str(ins))
-        row.append(str(dels))
-        row.append(str(subs))
-        # print(row)
-
-        # Accumulate
-        kIdIndex = 0
-        kNBestSep = "/"
-
-        pieces = input[kIdIndex].split(kNBestSep)
-
-        if len(pieces) == 0:
-            print(
-                "Error splitting ",
-                input[kIdIndex],
-                " on '",
-                kNBestSep,
-                "', got empty list",
-            )
-            return np.nan
-
-        id = pieces[0]
-        if id not in self.id2oracle_errs_:
-            self.utts_ += 1
-            self.words_ += len(refs)
-            self.insertions_ += ins
-            self.deletions_ += dels
-            self.substitutions_ += subs
-            self.id2oracle_errs_[id] = [ins, dels, subs]
-        else:
-            curr_err = ins + dels + subs
-            prev_err = np.sum(self.id2oracle_errs_[id])
-            if curr_err < prev_err:
-                self.id2oracle_errs_[id] = [ins, dels, subs]
-
-        return 0
-
-    def report_result(self):
-        # print("----------  Summary ---------------")
-        if self.words_ == 0:
-            print("No words counted")
-            return
-
-        # 1-best
-        best_wer = (
-            100.0
-            * (self.insertions_ + self.deletions_ + self.substitutions_)
-            / self.words_
-        )
-
-        print(
-            "\tWER = %0.2f%% (%i utts, %i words, %0.2f%% ins, "
-            "%0.2f%% dels, %0.2f%% subs)"
-            % (
-                best_wer,
-                self.utts_,
-                self.words_,
-                100.0 * self.insertions_ / self.words_,
-                100.0 * self.deletions_ / self.words_,
-                100.0 * self.substitutions_ / self.words_,
-            )
-        )
-
-    def wer(self):
-        if self.words_ == 0:
-            wer = np.nan
-        else:
-            wer = (
-                100.0
-                * (self.insertions_ + self.deletions_ + self.substitutions_)
-                / self.words_
-            )
-        return wer
-
-    def stats(self):
-        if self.words_ == 0:
-            stats = {}
-        else:
-            wer = (
-                100.0
-                * (self.insertions_ + self.deletions_ + self.substitutions_)
-                / self.words_
-            )
-            stats = dict(
-                {
-                    "wer": wer,
-                    "utts": self.utts_,
-                    "numwords": self.words_,
-                    "ins": self.insertions_,
-                    "dels": self.deletions_,
-                    "subs": self.substitutions_,
-                    "confusion_pairs": self.ed_.confusion_pairs_,
-                }
-            )
-        return stats
-
-
-def calc_wer(hyp_str, ref_str):
-    t = WERTransformer(hyp_str, ref_str, verbose=0)
-    return t.wer()
-
-
-def calc_wer_stats(hyp_str, ref_str):
-    t = WERTransformer(hyp_str, ref_str, verbose=0)
-    return t.stats()
-
-
-def get_wer_alignment_codes(hyp_str, ref_str):
-    """
-    INPUT: hypothesis string, reference string
-    OUTPUT: List of alignment codes (intermediate results from WER computation)
-    """
-    t = WERTransformer(hyp_str, ref_str, verbose=0)
-    return t.ed_.align(str2toks(ref_str), str2toks(hyp_str)).codes
-
-
-def merge_counts(x, y):
-    # Merge two hashes which have 'counts' as their values
-    # This can be used for example to merge confusion pair counts
-    #   conf_pairs = merge_counts(conf_pairs, stats['confusion_pairs'])
-    for k, v in y.items():
-        if k not in x:
-            x[k] = 0
-        x[k] += v
-    return x
diff --git a/spaces/mshukor/UnIVAL/fairseq/fairseq/data/encoders/gpt2_bpe_utils.py b/spaces/mshukor/UnIVAL/fairseq/fairseq/data/encoders/gpt2_bpe_utils.py
deleted file mode 100644
index 688d4e36e358df2dcc432d37d3e57bd81e2f1ed1..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/fairseq/fairseq/data/encoders/gpt2_bpe_utils.py
+++ /dev/null
@@ -1,140 +0,0 @@
-"""
-Byte pair encoding utilities from GPT-2.
-
-Original source: https://github.com/openai/gpt-2/blob/master/src/encoder.py
-Original license: MIT
-"""
-
-import json
-from functools import lru_cache
-
-
-@lru_cache()
-def bytes_to_unicode():
-    """
-    Returns list of utf-8 byte and a corresponding list of unicode strings.
-    The reversible bpe codes work on unicode strings.
-    This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
-    When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
-    This is a signficant percentage of your normal, say, 32K bpe vocab.
-    To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
-    And avoids mapping to whitespace/control characters the bpe code barfs on.
-    """
-    bs = (
-        list(range(ord("!"), ord("~") + 1))
-        + list(range(ord("¡"), ord("¬") + 1))
-        + list(range(ord("®"), ord("ÿ") + 1))
-    )
-    cs = bs[:]
-    n = 0
-    for b in range(2 ** 8):
-        if b not in bs:
-            bs.append(b)
-            cs.append(2 ** 8 + n)
-            n += 1
-    cs = [chr(n) for n in cs]
-    return dict(zip(bs, cs))
-
-
-def get_pairs(word):
-    """Return set of symbol pairs in a word.
-    Word is represented as tuple of symbols (symbols being variable-length strings).
-    """
-    pairs = set()
-    prev_char = word[0]
-    for char in word[1:]:
-        pairs.add((prev_char, char))
-        prev_char = char
-    return pairs
-
-
-class Encoder:
-    def __init__(self, encoder, bpe_merges, errors="replace"):
-        self.encoder = encoder
-        self.decoder = {v: k for k, v in self.encoder.items()}
-        self.errors = errors  # how to handle errors in decoding
-        self.byte_encoder = bytes_to_unicode()
-        self.byte_decoder = {v: k for k, v in self.byte_encoder.items()}
-        self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges))))
-        self.cache = {}
-
-        try:
-            import regex as re
-
-            self.re = re
-        except ImportError:
-            raise ImportError("Please install regex with: pip install regex")
-
-        # Should haved added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
-        self.pat = self.re.compile(
-            r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
-        )
-
-    def bpe(self, token):
-        if token in self.cache:
-            return self.cache[token]
-        word = tuple(token)
-        pairs = get_pairs(word)
-
-        if not pairs:
-            return token
-
-        while True:
-            bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf")))
-            if bigram not in self.bpe_ranks:
-                break
-            first, second = bigram
-            new_word = []
-            i = 0
-            while i < len(word):
-                try:
-                    j = word.index(first, i)
-                    new_word.extend(word[i:j])
-                    i = j
-                except:
-                    new_word.extend(word[i:])
-                    break
-
-                if word[i] == first and i < len(word) - 1 and word[i + 1] == second:
-                    new_word.append(first + second)
-                    i += 2
-                else:
-                    new_word.append(word[i])
-                    i += 1
-            new_word = tuple(new_word)
-            word = new_word
-            if len(word) == 1:
-                break
-            else:
-                pairs = get_pairs(word)
-        word = " ".join(word)
-        self.cache[token] = word
-        return word
-
-    def encode(self, text):
-        bpe_tokens = []
-        for token in self.re.findall(self.pat, text):
-            token = "".join(self.byte_encoder[b] for b in token.encode("utf-8"))
-            bpe_tokens.extend(
-                self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" ")
-            )
-        return bpe_tokens
-
-    def decode(self, tokens):
-        text = "".join([self.decoder.get(token, token) for token in tokens])
-        text = bytearray([self.byte_decoder[c] for c in text]).decode(
-            "utf-8", errors=self.errors
-        )
-        return text
-
-
-def get_encoder(encoder_json_path, vocab_bpe_path):
-    with open(encoder_json_path, "r") as f:
-        encoder = json.load(f)
-    with open(vocab_bpe_path, "r", encoding="utf-8") as f:
-        bpe_data = f.read()
-    bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split("\n")[1:-1]]
-    return Encoder(
-        encoder=encoder,
-        bpe_merges=bpe_merges,
-    )
diff --git a/spaces/mshukor/UnIVAL/run_scripts/averaging/ratatouille/scaling_best/vqa/unival_vqa_ofaplus_initrefcocoplus.sh b/spaces/mshukor/UnIVAL/run_scripts/averaging/ratatouille/scaling_best/vqa/unival_vqa_ofaplus_initrefcocoplus.sh
deleted file mode 100644
index 5232c9c61bfca1bb955d053bb377b08e402c35d2..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/run_scripts/averaging/ratatouille/scaling_best/vqa/unival_vqa_ofaplus_initrefcocoplus.sh
+++ /dev/null
@@ -1,233 +0,0 @@
-
-# Number of GPUs per GPU worker
-export GPUS_PER_NODE=8
-# Number of GPU workers, for single-worker training, please set to 1
-export NUM_NODES=$SLURM_NNODES
-# The ip address of the rank-0 worker, for single-worker training, please set to localhost
-master_addr=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
-export MASTER_ADDR=$master_addr
-
-# The port for communication
-export MASTER_PORT=12350
-# The rank of this worker, should be in {0, ..., WORKER_CNT-1}, for single-worker training, please set to 0
-export RANK=$SLURM_NODEID
-
-echo "MASTER_ADDR: $MASTER_ADDR"
-echo "RANK :$RANK"
-echo "NUM_NODES :$NUM_NODES"
-echo "GPUS_PER_NODE :$GPUS_PER_NODE"
-
-export MIOPEN_USER_DB_PATH=/lus/home/NAT/gda2204/mshukor/.config/miopen_${MASTER_ADDR}_${SLURM_PROCID}/
-
-echo "MIOPEN_USER_DB_PATH :$MIOPEN_USER_DB_PATH"
-
-num_workers=0
-
-
-ofa_dir=/lus/home/NAT/gda2204/mshukor/code/unival
-base_data_dir=/lus/scratch/NAT/gda2204/SHARED/data
-base_log_dir=/work/NAT/gda2204/mshukor/logs
-
-
-exp_name=unival_vqa_ofaplus_initrefcocoplus
-
-
-image_dir=${base_data_dir}
-data_dir=${base_data_dir}/ofa/vqa_data
-# data=${data_dir}/vqa_train.tsv,${data_dir}/vqa_val.tsv
-# Note: If you have shuffled the data in advance, please uncomment the line below.
-data=${data_dir}/vqa_train_1.tsv,${data_dir}/vqa_train_2.tsv,${data_dir}/vqa_train_3.tsv,${data_dir}/vqa_train_4.tsv,${data_dir}/vqa_train_5.tsv,${data_dir}/vqa_train_6.tsv,${data_dir}/vqa_train_7.tsv,${data_dir}/vqa_train_8.tsv,${data_dir}/vqa_train_9.tsv,${data_dir}/vqa_train_10.tsv,${data_dir}/vqa_val.tsv
-ans2label_file=${base_data_dir}/ofa/vqa_data/trainval_ans2label.pkl
-
-
-selected_cols=0,5,2,3,4
-
-
-
-save_base_log_dir=/lus/scratch/NAT/gda2204/SHARED/logs
-save_dir=${save_base_log_dir}/ofa/checkpoints/vqa/${exp_name}
-
-# save_dir=${base_log_dir}/ofa/checkpoints/vqa/${exp_name}
-log_dir=${save_dir}
-
-mkdir -p $log_dir $save_dir
-
-restore_file=/lus/scratch/NAT/gda2204/SHARED/logs/ofa/checkpoints/refcocoplus/unival_refcocoplus/10_5e-5_512/checkpoint_best.pt
-
-lr=1e-4
-
-
-
-bpe_dir=${ofa_dir}/utils/BPE
-user_dir=${ofa_dir}/ofa_module
-
-
-
-task=vqa_gen
-arch=unival_base
-
-
-criterion=adjust_label_smoothed_cross_entropy
-label_smoothing=0.1
-batch_size=16
-update_freq=1
-resnet_drop_path_rate=0.0
-encoder_drop_path_rate=0.1
-decoder_drop_path_rate=0.1
-dropout=0.1
-attention_dropout=0.0
-max_src_length=80
-max_object_length=30
-max_tgt_length=30
-num_bins=1000
-# patch_image_size=480
-
-uses_ema="--uses-ema"
-store_ema="--store-ema"
-ema_fp32="--ema-fp32"
-ema_decay=0.9999
-ema_start_update=0
-
-# Specify the inference type in validation after each fine-tuning epoch
-# As mentioned in the readme, you can choose from allcand or beamsearch evaluation, default to allcand
-val_inference_type=beamsearch
-
-# Specify whether to activate unconstrained VQA finetuning, which does not use a pre-defined candidate answer set
-# If --unconstrained-training is acitvated, --ans2label-file will **not be used even if it is specified**
-# Meanwhile, --val-inference-type must be set to **beamsearch**
-# By default, we follow the constrained finetuning as we mentioned in OFA paper, the candidate answer set shall be specified by --ans2label-file
-# For more details about this option, please refer to issue #123 and PR #124
-unconstrained_training_flag=""
-# unconstrained_training_flag="--unconstrained-training"
-
-
-
-
-
-save_interval_updates=0
-
-###
-image_encoder_name=timm_resnet #vit_base_patch16_224
-patch_image_size=480
-resnet_type=resnet101
-
-resnet_model_path=${base_log_dir}/pretrained_models/resnet101-5d3b4d8f.pth
-
-# video
-video_encoder_name=all_resnext101
-patch_frame_size=384
-video_model_path=${base_log_dir}/pretrained_models/3dcnn/resnext-101-kinetics.pth #${base_log_dir}/pretrained_models/TimeSformer_divST_8x32_224_K600.pyth
-num_frames=4
-
-
-sample_patch_num='--sample-patch-num=784' # ''
-
-eval_args='--eval-args={"beam":5,"unnormalized":true,"temperature":1.0,"stop_on_max_len":true}'
-
-validate_interval_updates=2000
-save_interval_updates=0
-
-
-for max_epoch in {20,}; do
-  echo "max_epoch "${max_epoch}
-  for warmup_ratio in {0.04,}; do
-    echo "warmup_updates "${warmup_updates}  
-    for lr in {$lr,}; do
-      echo "lr "${lr}
-      for patch_image_size in {$patch_image_size,}; do
-        echo "patch_image_size "${patch_image_size}
-
-        log_file=${log_dir}/${max_epoch}"_"${warmup_ratio}"_"${lr}"_"${patch_image_size}"_rank"${RANK}".log"
-        save_path=${save_dir}/${max_epoch}"_"${warmup_ratio}"_"${lr}"_"${patch_image_size}
-        mkdir -p $save_path
-
-        python3 -m torch.distributed.launch \
-            --nnodes=${NUM_NODES} \
-            --nproc_per_node=${GPUS_PER_NODE} \
-            --master_port=${MASTER_PORT} \
-            --node_rank=${RANK} \
-            --master_addr=${MASTER_ADDR} \
-            --use_env ${ofa_dir}/train.py \
-            ${data} \
-            --selected-cols=${selected_cols} \
-            --bpe-dir=${bpe_dir} \
-            --user-dir=${user_dir} \
-            --restore-file=${restore_file} \
-            --save-dir=${save_path} \
-            --task=${task} \
-            --arch=${arch} \
-            --criterion=${criterion} \
-            --label-smoothing=${label_smoothing} \
-            --batch-size=${batch_size} \
-            --update-freq=${update_freq} \
-            --encoder-normalize-before \
-            --decoder-normalize-before \
-            --share-decoder-input-output-embed \
-            --share-all-embeddings \
-            --layernorm-embedding \
-            --patch-layernorm-embedding \
-            --code-layernorm-embedding \
-            --resnet-drop-path-rate=${resnet_drop_path_rate} \
-            --encoder-drop-path-rate=${encoder_drop_path_rate} \
-            --decoder-drop-path-rate=${decoder_drop_path_rate} \
-            --dropout=${dropout} \
-            --attention-dropout=${attention_dropout} \
-            --weight-decay=0.01 \
-            --optimizer=adam \
-            --adam-betas="(0.9,0.999)" \
-            --adam-eps=1e-08 \
-            --clip-norm=1.0 \
-            --lr-scheduler=polynomial_decay \
-            --lr=${lr} \
-            --max-epoch=${max_epoch} \
-            --warmup-ratio=${warmup_ratio} \
-            --log-format=simple \
-            --log-interval=10 \
-            --fixed-validation-seed=7 \
-            --keep-best-checkpoints=1 \
-            --no-epoch-checkpoints \
-            --save-interval=1 --validate-interval=1 \
-            --save-interval-updates=${save_interval_updates} --validate-interval-updates=${validate_interval_updates} \
-            --best-checkpoint-metric=vqa_score --maximize-best-checkpoint-metric \
-            --max-src-length=${max_src_length} \
-            --max-object-length=${max_object_length} \
-            --max-tgt-length=${max_tgt_length} \
-            --find-unused-parameters \
-            --freeze-encoder-embedding \
-            --freeze-decoder-embedding \
-            ${unconstrained_training_flag} \
-            --ans2label-file=${ans2label_file} \
-            --valid-batch-size=20 \
-            --add-type-embedding \
-            --scale-attn \
-            --scale-fc \
-            --scale-heads \
-            --disable-entangle \
-            --num-bins=${num_bins} \
-            --patch-image-size=${patch_image_size} \
-            --prompt-type=prev_output \
-            --fp16 \
-            --fp16-scale-window=512 \
-            ${uses_ema} \
-            ${store_ema} \
-            ${ema_fp32} \
-            --ema-decay=${ema_decay} \
-            --ema-start-update=${ema_start_update} \
-            --val-inference-type=${val_inference_type} \
-            --num-workers=0 \
-            --image-encoder-name=${image_encoder_name} \
-            --image-dir=${image_dir} \
-            --video-encoder-name=${video_encoder_name} \
-            --video-model-path=${video_model_path} \
-            --patch-frame-size=${patch_frame_size} \
-            ${sample_patch_num} \
-            ${eval_args} \
-            --no-epoch-checkpoints \
-            --resnet-type=${resnet_type} \
-            --resnet-model-path=${resnet_model_path} \
-            --reset-dataloader --reset-meters --reset-optimizer 
-
-      done
-    done
-  done
-done
diff --git a/spaces/msmilauer/AutoGPT-duplicated2/autogpt/json_utils/__init__.py b/spaces/msmilauer/AutoGPT-duplicated2/autogpt/json_utils/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/mukish45/Hindi-Audio-To-Text/app.py b/spaces/mukish45/Hindi-Audio-To-Text/app.py
deleted file mode 100644
index aefe6ffca90da516c9c9939400bb1526a9ac7ec6..0000000000000000000000000000000000000000
--- a/spaces/mukish45/Hindi-Audio-To-Text/app.py
+++ /dev/null
@@ -1,18 +0,0 @@
-from transformers import pipeline
-import gradio as gr
-
-pipe = pipeline(model="mukish45/whisper-base-hi") 
-
-def transcribe(audio):
-    text = pipe(audio)["text"]
-    return text
-
-iface = gr.Interface(
-    fn=transcribe, 
-    inputs=gr.Audio(source="microphone", type="filepath"), 
-    outputs="text",
-    title="Whisper Base Hindi",
-    description="Hindi speech recognition using a fine-tuned Whisper base model.",
-)
-
-iface.launch()
\ No newline at end of file
diff --git a/spaces/mustapha/chatAlpaca/app.py b/spaces/mustapha/chatAlpaca/app.py
deleted file mode 100644
index e8dbf8981a7c2ec8597a3598838214eb04c4dc3e..0000000000000000000000000000000000000000
--- a/spaces/mustapha/chatAlpaca/app.py
+++ /dev/null
@@ -1,176 +0,0 @@
-"""Python file to serve as the frontend"""
-import streamlit as st
-from streamlit_chat import message
-
-from langchain.chains import ConversationChain, LLMChain
-from langchain import PromptTemplate
-from langchain.llms.base import LLM
-from langchain.memory import ConversationBufferWindowMemory
-from typing import Optional, List, Mapping, Any
-
-import torch
-from peft import PeftModel
-import transformers
-
-from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig
-from transformers import BitsAndBytesConfig
-
-tokenizer = LlamaTokenizer.from_pretrained("decapoda-research/llama-7b-hf")
-
-
-
-quantization_config = BitsAndBytesConfig(llm_int8_enable_fp32_cpu_offload=True)
-
-model = LlamaForCausalLM.from_pretrained(
-    "decapoda-research/llama-7b-hf",
-    # load_in_8bit=True,
-    # torch_dtype=torch.float16,
-    device_map="auto",
-    # device_map={"":"cpu"},
-    max_memory={"cpu":"15GiB"}
-    quantization_config=quantization_config
-)
-model = PeftModel.from_pretrained(
-    model, "tloen/alpaca-lora-7b",
-    # torch_dtype=torch.float16,
-    device_map={"":"cpu"},
-)
-
-device = "cpu"
-print("model device :", model.device, flush=True)
-# model.to(device)
-model.eval()
-
-def evaluate_raw_prompt(
-        prompt:str,
-        temperature=0.1,
-        top_p=0.75,
-        top_k=40,
-        num_beams=4,
-        **kwargs,
-):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    input_ids = inputs["input_ids"].to(device)
-    generation_config = GenerationConfig(
-        temperature=temperature,
-        top_p=top_p,
-        top_k=top_k,
-        num_beams=num_beams,
-        **kwargs,
-    )
-    with torch.no_grad():
-        generation_output = model.generate(
-            input_ids=input_ids,
-            generation_config=generation_config,
-            return_dict_in_generate=True,
-            output_scores=True,
-            max_new_tokens=256,
-        )
-    s = generation_output.sequences[0]
-    output = tokenizer.decode(s)
-    # return output
-    return output.split("### Response:")[1].strip()
-
-class AlpacaLLM(LLM):
-    temperature: float
-    top_p: float
-    top_k: int
-    num_beams: int
-    @property
-    def _llm_type(self) -> str:
-        return "custom"
-    
-    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
-        if stop is not None:
-            raise ValueError("stop kwargs are not permitted.")
-        answer = evaluate_raw_prompt(prompt, 
-                            top_p= self.top_p,
-                            top_k= self.top_k,
-                            num_beams= self.num_beams,
-                            temperature= self.temperature
-                            )
-        return answer
-    
-    @property
-    def _identifying_params(self) -> Mapping[str, Any]:
-        """Get the identifying parameters."""
-        return {
-            "top_p": self.top_p,
-            "top_k": self.top_k,
-            "num_beams": self.num_beams,
-            "temperature": self.temperature
-            }
-
-
-template = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
-### Instruction:
-You are a chatbot, you should answer my last question very briefly. You are consistent and non repetitive. 
-### Chat:
-{history}
-Human: {human_input}
-### Response:"""
-
-prompt = PromptTemplate(
-    input_variables=["history","human_input"],
-    template=template,
-)
-
-
-def load_chain():
-    """Logic for loading the chain you want to use should go here."""
-    llm = AlpacaLLM(top_p=0.75, top_k=40, num_beams=4, temperature=0.1)
-    # chain = ConversationChain(llm=llm)
-    chain = LLMChain(llm=llm, prompt=prompt, memory=ConversationBufferWindowMemory(k=2))
-    return chain
-
-chain = load_chain()
-
-# # From here down is all the StreamLit UI.
-# st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
-# st.header("LangChain Demo")
-
-# if "generated" not in st.session_state:
-#     st.session_state["generated"] = []
-
-# if "past" not in st.session_state:
-#     st.session_state["past"] = []
-
-
-# def get_text():
-#     input_text = st.text_input("Human: ", "Hello, how are you?", key="input")
-#     return input_text
-
-
-# user_input = get_text()
-
-# if user_input:
-#     output = chain.predict(human_input=user_input)
-
-#     st.session_state.past.append(user_input)
-#     st.session_state.generated.append(output)
-
-# if st.session_state["generated"]:
-
-#     for i in range(len(st.session_state["generated"]) - 1, -1, -1):
-#         message(st.session_state["generated"][i], key=str(i))
-#         message(st.session_state["past"][i], is_user=True, key=str(i) + "_user")
-
-st.title("ChatAlpaca")
-
-if "history" not in st.session_state:
-    st.session_state.history = []
-    st.session_state.history.append({"message": "Hey, I'm a Alpaca chatBot. Ask whatever you want!", "is_user": False})
-    
-
-def generate_answer():
-    user_message = st.session_state.input_text
-    inputs = tokenizer(st.session_state.input_text, return_tensors="pt")
-    result = model.generate(**inputs)
-    message_bot = tokenizer.decode(result[0], skip_special_tokens=True)  # .replace("<s>", "").replace("</s>", "")
-    st.session_state.history.append({"message": user_message, "is_user": True})
-    st.session_state.history.append({"message": message_bot, "is_user": False})
-    
-st.text_input("Response", key="input_text", on_change=generate_answer)
-
-for chat in st.session_state.history:
-    st_message(**chat)
\ No newline at end of file
diff --git a/spaces/mwaseemrandhawa/sentiment_analysis/README.md b/spaces/mwaseemrandhawa/sentiment_analysis/README.md
deleted file mode 100644
index a5abc33a2672a009a642a1906ced943804a1928d..0000000000000000000000000000000000000000
--- a/spaces/mwaseemrandhawa/sentiment_analysis/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Sentiment Analysis
-emoji: 🐢
-colorFrom: pink
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/nathanTQ/ChatDev/Dockerfile b/spaces/nathanTQ/ChatDev/Dockerfile
deleted file mode 100644
index beb36827e582ab771b951159898a3b7d45585850..0000000000000000000000000000000000000000
--- a/spaces/nathanTQ/ChatDev/Dockerfile
+++ /dev/null
@@ -1,42 +0,0 @@
-FROM python:3.11.4-slim-bullseye as install-browser
-
-RUN apt-get update \
-    && apt-get satisfy -y \
-    "chromium, chromium-driver (>= 115.0)" \
-    && chromium --version && chromedriver --version
-
-FROM install-browser as user-install
-
-ENV PIP_ROOT_USER_ACTION=ignore
-
-RUN mkdir /usr/src/app
-WORKDIR /usr/src/app
-
-# COPY ./requirements.txt ./requirements.txt
-
-COPY ./ ./
-
-RUN pip install -r requirements.txt
-
-FROM user-install AS user
-
-RUN useradd -ms /bin/bash user \
-    && chown -R user:user /usr/src/app
-
-RUN chown user:user /home
-RUN chmod 755 /home
-
-USER user
-
-ENV HOME=/home/user \
-	PATH=/home/user/.local/bin:$PATH \
-    PYTHONPATH=$HOME/app \
-	PYTHONUNBUFFERED=1 \
-	GRADIO_ALLOW_FLAGGING=never \
-	GRADIO_NUM_PORTS=1 \
-	GRADIO_SERVER_NAME=0.0.0.0 \
-	GRADIO_THEME=huggingface \
-	SYSTEM=spaces
-
-CMD python app.py --host 0.0.0.0 --port 7860
-
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Assassins Creed 1 Crack.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Assassins Creed 1 Crack.md
deleted file mode 100644
index 6c3d18762a5212c829acd3f4d3796d5d5b606d59..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Assassins Creed 1 Crack.md	
+++ /dev/null
@@ -1,13 +0,0 @@
-
-<h1>Assassin's Creed 1: A Review of the Game that Started a Legendary Franchise</h1>
-<p>Assassin's Creed 1 is a historical action-adventure game that was released in 2007 by Ubisoft. It is the first game in the Assassin's Creed series, which has become one of the most popular and acclaimed video game franchises of all time. In this game, the player takes on the role of Altaïr Ibn-La'Ahad, a member of the secret society of assassins who fights against the Templars, a rival faction that seeks to control the world through ancient artifacts.</p>
-<h2>Assassins Creed 1 Crack</h2><br /><p><b><b>Download File</b> &#10027; <a href="https://urlcod.com/2uIcj6">https://urlcod.com/2uIcj6</a></b></p><br /><br />
-<p>The game is set in the 12th century during the Third Crusade in the Holy Land. The player can explore various cities such as Jerusalem, Acre, and Damascus, and perform various actions such as climbing buildings, stealthily assassinating enemies, and engaging in combat with swords and daggers. The game features an open-world environment that is realistic and responsive to the player's actions. The game also has a sci-fi twist, as the player is actually reliving Altaïr's memories through a device called the Animus, which allows access to the genetic memories of one's ancestors.</p>
-<p>Assassin's Creed 1 received critical acclaim for its innovative gameplay, immersive story, and stunning graphics. It also spawned several sequels and spin-offs that expanded the lore and history of the Assassin's Creed universe. The game is available on PC, Xbox 360, and PlayStation 3 platforms. The PC version also features four exclusive investigation missions that add more depth and challenge to the game.</p>
-<p>If you are a fan of historical fiction, stealth action, or sci-fi mystery, you should definitely check out Assassin's Creed 1. It is a game that redefined the action genre and started a legendary franchise.</p><p>Assassin's Creed 1 has a gameplay that is based on the concept of "social stealth", which means that the player can blend in with the crowds and use them as cover to avoid detection by the enemies. The player can also use various environmental elements such as haystacks, benches, and rooftops to hide or escape from pursuers. The game also has a "notoriety" system, which measures how much attention the player attracts from the guards and civilians. The higher the notoriety, the more likely the player will be recognized and attacked by the enemies. The player can reduce their notoriety by performing certain actions such as removing wanted posters, bribing informers, or killing witnesses.</p>
-<p>The game also has a combat system that allows the player to fight with various weapons such as swords, daggers, throwing knives, and hidden blades. The player can also counter-attack, dodge, or disarm their opponents. The combat is influenced by the health and synchronization of the player. The health represents the physical condition of the player, while the synchronization represents the accuracy of the player's actions with Altaïr's memories. The health and synchronization can be restored by finding safe places or using medicine.</p>
-<p>The game also has a variety of missions that the player can complete to advance the story or unlock new abilities and equipment. The main missions are assassination missions, where the player has to locate and eliminate a specific target. Before each assassination mission, the player has to gather information about their target by performing investigation missions such as eavesdropping, interrogation, pickpocketing, or informer challenges. The game also has side missions such as saving citizens from harassment, collecting flags, or killing Templars.</p>
-<p>Assassin's Creed 1 has a gameplay that is challenging, rewarding, and fun. It offers a lot of freedom and options for the player to approach each situation. It also has a gameplay that is immersive and realistic, as it reflects the historical and cultural context of the 12th century.</p>
-<p></p> e93f5a0c3f<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Peter Murphy Discography Mp3 Rock Gothic Rock Torrent _BEST_ Download.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Peter Murphy Discography Mp3 Rock Gothic Rock Torrent _BEST_ Download.md
deleted file mode 100644
index d3995169242ff766ca9faef915de0d902d833a1a..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Peter Murphy Discography Mp3 Rock Gothic Rock Torrent _BEST_ Download.md	
+++ /dev/null
@@ -1,27 +0,0 @@
-<br />
-<h1>Peter Murphy: The Legendary Voice of Gothic Rock</h1>
-<p>If you are a fan of gothic rock, you probably know Peter Murphy. He is the former lead singer of Bauhaus, the influential band that pioneered the genre in the late 1970s and early 1980s. But did you know that he also has a prolific solo career that spans over four decades and 11 studio albums?</p>
-<p>In this article, we will explore Peter Murphy's discography, from his debut album Should the World Fail to Fall Apart (1986) to his latest release Lion (2014). We will also show you how to download his albums in high-quality mp3 format from reliable torrent sites. So, if you are ready to dive into the dark and mesmerizing world of Peter Murphy, read on!</p>
-<h2>Peter Murphy Discography Mp3 Rock Gothic Rock Torrent Download</h2><br /><p><b><b>Download</b> &#9733; <a href="https://urlcod.com/2uIaxo">https://urlcod.com/2uIaxo</a></b></p><br /><br />
-
-<h2>Should the World Fail to Fall Apart (1986)</h2>
-<p>Peter Murphy's first solo album was released after Bauhaus disbanded in 1983. It showcases his diverse musical influences, from glam rock to synth-pop to post-punk. The album features some of his most iconic songs, such as "The Light Pours Out of Me", a cover of Magazine's classic, and "Final Solution", a danceable track with a catchy chorus. The album also includes some experimental and atmospheric tracks, such as "Canvas Beauty" and "Blue Heart".</p>
-<p>You can download Should the World Fail to Fall Apart from <a href="https://rutracker.org/forum/viewtopic.php?t=5628097">this torrent link</a>, which contains a lossless FLAC rip of the 2018 remastered edition with bonus tracks.</p>
-
-<h2>Love Hysteria (1988)</h2>
-<p>Peter Murphy's second solo album was a more cohesive and polished work than his debut. It features a more prominent use of keyboards and synthesizers, creating a lush and romantic sound. The album contains some of his most popular songs, such as "All Night Long", "Indigo Eyes", and "Dragnet Drag". The album also showcases his vocal range and versatility, from the crooning ballad "Time Has Got Nothing to Do with It" to the operatic "Blind Sublime".</p>
-<p>You can download Love Hysteria from <a href="https://rutracker.org/forum/viewtopic.php?t=1628297">this torrent link</a>, which contains a lossless FLAC rip of the original CD release.</p>
-
-<h2>Deep (1990)</h2>
-<p>Peter Murphy's third solo album was his most successful one commercially. It reached the top 10 in the UK and the US alternative charts, and spawned three hit singles: "Cuts You Up", "A Strange Kind of Love", and "The Sweetest Drop". The album has a more rock-oriented sound than his previous ones, with guitars and drums playing a prominent role. The album also features some guest appearances by notable musicians, such as Daniel Ash from Bauhaus and Mick Karn from Japan.</p>
-<p>You can download Deep from <a href="https://archive.org/details/va-gothic-rock_202109">this torrent link</a>, which contains a lossless FLAC rip of the 2016 remastered edition with bonus tracks.</p>
-<p></p>
-
-<h2>Holy Smoke (1992)</h2>
-<p>Peter Murphy's fourth solo album was a more experimental and eclectic one than his previous ones. It incorporates elements of folk, world music, blues, and funk into his gothic rock style. The album features some of his most adventurous songs, such as "The Judgement is the Mirror", a duet with Turkish singer Ofra Haza, and "Let Me Love You", a cover of a song by James Brown. The album also includes some more conventional tracks, such as "Keep Me from Harm" and "Our Secret Garden".</p>
-<p>You can download Holy Smoke from <a href="https://www.discogc.com/">this torrent link</a>, which contains a lossless FLAC rip of the original CD release.</p>
-
-<h2>Cascade (1995)</h2>
-<p>Peter Murphy's fifth solo album was a return to his gothic rock roots. It features a more guitar-driven sound than his previous albums, with heavy distortion and feedback. The album contains some of his most aggressive and energetic songs, such as "Mirror to My Woman's Mind", "Subway", and "Gliding Like a Whale". The album also</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/modeling/backbone/swin.py b/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/modeling/backbone/swin.py
deleted file mode 100644
index 780b6fc6eaab1d9a3f513b8a09cb4dc95166e5a3..0000000000000000000000000000000000000000
--- a/spaces/nikitaPDL2023/assignment4/detectron2/detectron2/modeling/backbone/swin.py
+++ /dev/null
@@ -1,695 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-"""
-Implementation of Swin models from :paper:`swin`.
-
-This code is adapted from https://github.com/SwinTransformer/Swin-Transformer-Object-Detection/blob/master/mmdet/models/backbones/swin_transformer.py with minimal modifications.  # noqa
---------------------------------------------------------
-Swin Transformer
-Copyright (c) 2021 Microsoft
-Licensed under The MIT License [see LICENSE for details]
-Written by Ze Liu, Yutong Lin, Yixuan Wei
---------------------------------------------------------
-LICENSE: https://github.com/SwinTransformer/Swin-Transformer-Object-Detection/blob/461e003166a8083d0b620beacd4662a2df306bd6/LICENSE
-"""
-
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.utils.checkpoint as checkpoint
-
-from detectron2.modeling.backbone.backbone import Backbone
-
-_to_2tuple = nn.modules.utils._ntuple(2)
-
-
-class Mlp(nn.Module):
-    """Multilayer perceptron."""
-
-    def __init__(
-        self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.0
-    ):
-        super().__init__()
-        out_features = out_features or in_features
-        hidden_features = hidden_features or in_features
-        self.fc1 = nn.Linear(in_features, hidden_features)
-        self.act = act_layer()
-        self.fc2 = nn.Linear(hidden_features, out_features)
-        self.drop = nn.Dropout(drop)
-
-    def forward(self, x):
-        x = self.fc1(x)
-        x = self.act(x)
-        x = self.drop(x)
-        x = self.fc2(x)
-        x = self.drop(x)
-        return x
-
-
-def window_partition(x, window_size):
-    """
-    Args:
-        x: (B, H, W, C)
-        window_size (int): window size
-    Returns:
-        windows: (num_windows*B, window_size, window_size, C)
-    """
-    B, H, W, C = x.shape
-    x = x.view(B, H // window_size, window_size, W // window_size, window_size, C)
-    windows = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C)
-    return windows
-
-
-def window_reverse(windows, window_size, H, W):
-    """
-    Args:
-        windows: (num_windows*B, window_size, window_size, C)
-        window_size (int): Window size
-        H (int): Height of image
-        W (int): Width of image
-    Returns:
-        x: (B, H, W, C)
-    """
-    B = int(windows.shape[0] / (H * W / window_size / window_size))
-    x = windows.view(B, H // window_size, W // window_size, window_size, window_size, -1)
-    x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1)
-    return x
-
-
-class WindowAttention(nn.Module):
-    """Window based multi-head self attention (W-MSA) module with relative position bias.
-    It supports both of shifted and non-shifted window.
-    Args:
-        dim (int): Number of input channels.
-        window_size (tuple[int]): The height and width of the window.
-        num_heads (int): Number of attention heads.
-        qkv_bias (bool, optional):  If True, add a learnable bias to query, key, value.
-            Default: True
-        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set
-        attn_drop (float, optional): Dropout ratio of attention weight. Default: 0.0
-        proj_drop (float, optional): Dropout ratio of output. Default: 0.0
-    """
-
-    def __init__(
-        self,
-        dim,
-        window_size,
-        num_heads,
-        qkv_bias=True,
-        qk_scale=None,
-        attn_drop=0.0,
-        proj_drop=0.0,
-    ):
-
-        super().__init__()
-        self.dim = dim
-        self.window_size = window_size  # Wh, Ww
-        self.num_heads = num_heads
-        head_dim = dim // num_heads
-        self.scale = qk_scale or head_dim**-0.5
-
-        # define a parameter table of relative position bias
-        self.relative_position_bias_table = nn.Parameter(
-            torch.zeros((2 * window_size[0] - 1) * (2 * window_size[1] - 1), num_heads)
-        )  # 2*Wh-1 * 2*Ww-1, nH
-
-        # get pair-wise relative position index for each token inside the window
-        coords_h = torch.arange(self.window_size[0])
-        coords_w = torch.arange(self.window_size[1])
-        coords = torch.stack(torch.meshgrid([coords_h, coords_w]))  # 2, Wh, Ww
-        coords_flatten = torch.flatten(coords, 1)  # 2, Wh*Ww
-        relative_coords = coords_flatten[:, :, None] - coords_flatten[:, None, :]  # 2, Wh*Ww, Wh*Ww
-        relative_coords = relative_coords.permute(1, 2, 0).contiguous()  # Wh*Ww, Wh*Ww, 2
-        relative_coords[:, :, 0] += self.window_size[0] - 1  # shift to start from 0
-        relative_coords[:, :, 1] += self.window_size[1] - 1
-        relative_coords[:, :, 0] *= 2 * self.window_size[1] - 1
-        relative_position_index = relative_coords.sum(-1)  # Wh*Ww, Wh*Ww
-        self.register_buffer("relative_position_index", relative_position_index)
-
-        self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)
-        self.attn_drop = nn.Dropout(attn_drop)
-        self.proj = nn.Linear(dim, dim)
-        self.proj_drop = nn.Dropout(proj_drop)
-
-        nn.init.trunc_normal_(self.relative_position_bias_table, std=0.02)
-        self.softmax = nn.Softmax(dim=-1)
-
-    def forward(self, x, mask=None):
-        """Forward function.
-        Args:
-            x: input features with shape of (num_windows*B, N, C)
-            mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None
-        """
-        B_, N, C = x.shape
-        qkv = (
-            self.qkv(x)
-            .reshape(B_, N, 3, self.num_heads, C // self.num_heads)
-            .permute(2, 0, 3, 1, 4)
-        )
-        q, k, v = qkv[0], qkv[1], qkv[2]  # make torchscript happy (cannot use tensor as tuple)
-
-        q = q * self.scale
-        attn = q @ k.transpose(-2, -1)
-
-        relative_position_bias = self.relative_position_bias_table[
-            self.relative_position_index.view(-1)
-        ].view(
-            self.window_size[0] * self.window_size[1], self.window_size[0] * self.window_size[1], -1
-        )  # Wh*Ww,Wh*Ww,nH
-        relative_position_bias = relative_position_bias.permute(
-            2, 0, 1
-        ).contiguous()  # nH, Wh*Ww, Wh*Ww
-        attn = attn + relative_position_bias.unsqueeze(0)
-
-        if mask is not None:
-            nW = mask.shape[0]
-            attn = attn.view(B_ // nW, nW, self.num_heads, N, N) + mask.unsqueeze(1).unsqueeze(0)
-            attn = attn.view(-1, self.num_heads, N, N)
-            attn = self.softmax(attn)
-        else:
-            attn = self.softmax(attn)
-
-        attn = self.attn_drop(attn)
-
-        x = (attn @ v).transpose(1, 2).reshape(B_, N, C)
-        x = self.proj(x)
-        x = self.proj_drop(x)
-        return x
-
-
-class SwinTransformerBlock(nn.Module):
-    """Swin Transformer Block.
-    Args:
-        dim (int): Number of input channels.
-        num_heads (int): Number of attention heads.
-        window_size (int): Window size.
-        shift_size (int): Shift size for SW-MSA.
-        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.
-        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True
-        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set.
-        drop (float, optional): Dropout rate. Default: 0.0
-        attn_drop (float, optional): Attention dropout rate. Default: 0.0
-        drop_path (float, optional): Stochastic depth rate. Default: 0.0
-        act_layer (nn.Module, optional): Activation layer. Default: nn.GELU
-        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm
-    """
-
-    def __init__(
-        self,
-        dim,
-        num_heads,
-        window_size=7,
-        shift_size=0,
-        mlp_ratio=4.0,
-        qkv_bias=True,
-        qk_scale=None,
-        drop=0.0,
-        attn_drop=0.0,
-        drop_path=0.0,
-        act_layer=nn.GELU,
-        norm_layer=nn.LayerNorm,
-    ):
-        super().__init__()
-        self.dim = dim
-        self.num_heads = num_heads
-        self.window_size = window_size
-        self.shift_size = shift_size
-        self.mlp_ratio = mlp_ratio
-        assert 0 <= self.shift_size < self.window_size, "shift_size must in 0-window_size"
-
-        self.norm1 = norm_layer(dim)
-        self.attn = WindowAttention(
-            dim,
-            window_size=_to_2tuple(self.window_size),
-            num_heads=num_heads,
-            qkv_bias=qkv_bias,
-            qk_scale=qk_scale,
-            attn_drop=attn_drop,
-            proj_drop=drop,
-        )
-
-        if drop_path > 0.0:
-            from timm.models.layers import DropPath
-
-            self.drop_path = DropPath(drop_path)
-        else:
-            self.drop_path = nn.Identity()
-        self.norm2 = norm_layer(dim)
-        mlp_hidden_dim = int(dim * mlp_ratio)
-        self.mlp = Mlp(
-            in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop
-        )
-
-        self.H = None
-        self.W = None
-
-    def forward(self, x, mask_matrix):
-        """Forward function.
-        Args:
-            x: Input feature, tensor size (B, H*W, C).
-            H, W: Spatial resolution of the input feature.
-            mask_matrix: Attention mask for cyclic shift.
-        """
-        B, L, C = x.shape
-        H, W = self.H, self.W
-        assert L == H * W, "input feature has wrong size"
-
-        shortcut = x
-        x = self.norm1(x)
-        x = x.view(B, H, W, C)
-
-        # pad feature maps to multiples of window size
-        pad_l = pad_t = 0
-        pad_r = (self.window_size - W % self.window_size) % self.window_size
-        pad_b = (self.window_size - H % self.window_size) % self.window_size
-        x = F.pad(x, (0, 0, pad_l, pad_r, pad_t, pad_b))
-        _, Hp, Wp, _ = x.shape
-
-        # cyclic shift
-        if self.shift_size > 0:
-            shifted_x = torch.roll(x, shifts=(-self.shift_size, -self.shift_size), dims=(1, 2))
-            attn_mask = mask_matrix
-        else:
-            shifted_x = x
-            attn_mask = None
-
-        # partition windows
-        x_windows = window_partition(
-            shifted_x, self.window_size
-        )  # nW*B, window_size, window_size, C
-        x_windows = x_windows.view(
-            -1, self.window_size * self.window_size, C
-        )  # nW*B, window_size*window_size, C
-
-        # W-MSA/SW-MSA
-        attn_windows = self.attn(x_windows, mask=attn_mask)  # nW*B, window_size*window_size, C
-
-        # merge windows
-        attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C)
-        shifted_x = window_reverse(attn_windows, self.window_size, Hp, Wp)  # B H' W' C
-
-        # reverse cyclic shift
-        if self.shift_size > 0:
-            x = torch.roll(shifted_x, shifts=(self.shift_size, self.shift_size), dims=(1, 2))
-        else:
-            x = shifted_x
-
-        if pad_r > 0 or pad_b > 0:
-            x = x[:, :H, :W, :].contiguous()
-
-        x = x.view(B, H * W, C)
-
-        # FFN
-        x = shortcut + self.drop_path(x)
-        x = x + self.drop_path(self.mlp(self.norm2(x)))
-
-        return x
-
-
-class PatchMerging(nn.Module):
-    """Patch Merging Layer
-    Args:
-        dim (int): Number of input channels.
-        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm
-    """
-
-    def __init__(self, dim, norm_layer=nn.LayerNorm):
-        super().__init__()
-        self.dim = dim
-        self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False)
-        self.norm = norm_layer(4 * dim)
-
-    def forward(self, x, H, W):
-        """Forward function.
-        Args:
-            x: Input feature, tensor size (B, H*W, C).
-            H, W: Spatial resolution of the input feature.
-        """
-        B, L, C = x.shape
-        assert L == H * W, "input feature has wrong size"
-
-        x = x.view(B, H, W, C)
-
-        # padding
-        pad_input = (H % 2 == 1) or (W % 2 == 1)
-        if pad_input:
-            x = F.pad(x, (0, 0, 0, W % 2, 0, H % 2))
-
-        x0 = x[:, 0::2, 0::2, :]  # B H/2 W/2 C
-        x1 = x[:, 1::2, 0::2, :]  # B H/2 W/2 C
-        x2 = x[:, 0::2, 1::2, :]  # B H/2 W/2 C
-        x3 = x[:, 1::2, 1::2, :]  # B H/2 W/2 C
-        x = torch.cat([x0, x1, x2, x3], -1)  # B H/2 W/2 4*C
-        x = x.view(B, -1, 4 * C)  # B H/2*W/2 4*C
-
-        x = self.norm(x)
-        x = self.reduction(x)
-
-        return x
-
-
-class BasicLayer(nn.Module):
-    """A basic Swin Transformer layer for one stage.
-    Args:
-        dim (int): Number of feature channels
-        depth (int): Depths of this stage.
-        num_heads (int): Number of attention head.
-        window_size (int): Local window size. Default: 7.
-        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. Default: 4.
-        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True
-        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set.
-        drop (float, optional): Dropout rate. Default: 0.0
-        attn_drop (float, optional): Attention dropout rate. Default: 0.0
-        drop_path (float | tuple[float], optional): Stochastic depth rate. Default: 0.0
-        norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm
-        downsample (nn.Module | None, optional): Downsample layer at the end of the layer.
-            Default: None
-        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False.
-    """
-
-    def __init__(
-        self,
-        dim,
-        depth,
-        num_heads,
-        window_size=7,
-        mlp_ratio=4.0,
-        qkv_bias=True,
-        qk_scale=None,
-        drop=0.0,
-        attn_drop=0.0,
-        drop_path=0.0,
-        norm_layer=nn.LayerNorm,
-        downsample=None,
-        use_checkpoint=False,
-    ):
-        super().__init__()
-        self.window_size = window_size
-        self.shift_size = window_size // 2
-        self.depth = depth
-        self.use_checkpoint = use_checkpoint
-
-        # build blocks
-        self.blocks = nn.ModuleList(
-            [
-                SwinTransformerBlock(
-                    dim=dim,
-                    num_heads=num_heads,
-                    window_size=window_size,
-                    shift_size=0 if (i % 2 == 0) else window_size // 2,
-                    mlp_ratio=mlp_ratio,
-                    qkv_bias=qkv_bias,
-                    qk_scale=qk_scale,
-                    drop=drop,
-                    attn_drop=attn_drop,
-                    drop_path=drop_path[i] if isinstance(drop_path, list) else drop_path,
-                    norm_layer=norm_layer,
-                )
-                for i in range(depth)
-            ]
-        )
-
-        # patch merging layer
-        if downsample is not None:
-            self.downsample = downsample(dim=dim, norm_layer=norm_layer)
-        else:
-            self.downsample = None
-
-    def forward(self, x, H, W):
-        """Forward function.
-        Args:
-            x: Input feature, tensor size (B, H*W, C).
-            H, W: Spatial resolution of the input feature.
-        """
-
-        # calculate attention mask for SW-MSA
-        Hp = int(np.ceil(H / self.window_size)) * self.window_size
-        Wp = int(np.ceil(W / self.window_size)) * self.window_size
-        img_mask = torch.zeros((1, Hp, Wp, 1), device=x.device)  # 1 Hp Wp 1
-        h_slices = (
-            slice(0, -self.window_size),
-            slice(-self.window_size, -self.shift_size),
-            slice(-self.shift_size, None),
-        )
-        w_slices = (
-            slice(0, -self.window_size),
-            slice(-self.window_size, -self.shift_size),
-            slice(-self.shift_size, None),
-        )
-        cnt = 0
-        for h in h_slices:
-            for w in w_slices:
-                img_mask[:, h, w, :] = cnt
-                cnt += 1
-
-        mask_windows = window_partition(
-            img_mask, self.window_size
-        )  # nW, window_size, window_size, 1
-        mask_windows = mask_windows.view(-1, self.window_size * self.window_size)
-        attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2)
-        attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(
-            attn_mask == 0, float(0.0)
-        )
-
-        for blk in self.blocks:
-            blk.H, blk.W = H, W
-            if self.use_checkpoint:
-                x = checkpoint.checkpoint(blk, x, attn_mask)
-            else:
-                x = blk(x, attn_mask)
-        if self.downsample is not None:
-            x_down = self.downsample(x, H, W)
-            Wh, Ww = (H + 1) // 2, (W + 1) // 2
-            return x, H, W, x_down, Wh, Ww
-        else:
-            return x, H, W, x, H, W
-
-
-class PatchEmbed(nn.Module):
-    """Image to Patch Embedding
-    Args:
-        patch_size (int): Patch token size. Default: 4.
-        in_chans (int): Number of input image channels. Default: 3.
-        embed_dim (int): Number of linear projection output channels. Default: 96.
-        norm_layer (nn.Module, optional): Normalization layer. Default: None
-    """
-
-    def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None):
-        super().__init__()
-        patch_size = _to_2tuple(patch_size)
-        self.patch_size = patch_size
-
-        self.in_chans = in_chans
-        self.embed_dim = embed_dim
-
-        self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=patch_size, stride=patch_size)
-        if norm_layer is not None:
-            self.norm = norm_layer(embed_dim)
-        else:
-            self.norm = None
-
-    def forward(self, x):
-        """Forward function."""
-        # padding
-        _, _, H, W = x.size()
-        if W % self.patch_size[1] != 0:
-            x = F.pad(x, (0, self.patch_size[1] - W % self.patch_size[1]))
-        if H % self.patch_size[0] != 0:
-            x = F.pad(x, (0, 0, 0, self.patch_size[0] - H % self.patch_size[0]))
-
-        x = self.proj(x)  # B C Wh Ww
-        if self.norm is not None:
-            Wh, Ww = x.size(2), x.size(3)
-            x = x.flatten(2).transpose(1, 2)
-            x = self.norm(x)
-            x = x.transpose(1, 2).view(-1, self.embed_dim, Wh, Ww)
-
-        return x
-
-
-class SwinTransformer(Backbone):
-    """Swin Transformer backbone.
-        A PyTorch impl of : `Swin Transformer: Hierarchical Vision Transformer using Shifted
-            Windows`  - https://arxiv.org/pdf/2103.14030
-    Args:
-        pretrain_img_size (int): Input image size for training the pretrained model,
-            used in absolute postion embedding. Default 224.
-        patch_size (int | tuple(int)): Patch size. Default: 4.
-        in_chans (int): Number of input image channels. Default: 3.
-        embed_dim (int): Number of linear projection output channels. Default: 96.
-        depths (tuple[int]): Depths of each Swin Transformer stage.
-        num_heads (tuple[int]): Number of attention head of each stage.
-        window_size (int): Window size. Default: 7.
-        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. Default: 4.
-        qkv_bias (bool): If True, add a learnable bias to query, key, value. Default: True
-        qk_scale (float): Override default qk scale of head_dim ** -0.5 if set.
-        drop_rate (float): Dropout rate.
-        attn_drop_rate (float): Attention dropout rate. Default: 0.
-        drop_path_rate (float): Stochastic depth rate. Default: 0.2.
-        norm_layer (nn.Module): Normalization layer. Default: nn.LayerNorm.
-        ape (bool): If True, add absolute position embedding to the patch embedding. Default: False.
-        patch_norm (bool): If True, add normalization after patch embedding. Default: True.
-        out_indices (Sequence[int]): Output from which stages.
-        frozen_stages (int): Stages to be frozen (stop grad and set eval mode).
-            -1 means not freezing any parameters.
-        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False.
-    """
-
-    def __init__(
-        self,
-        pretrain_img_size=224,
-        patch_size=4,
-        in_chans=3,
-        embed_dim=96,
-        depths=(2, 2, 6, 2),
-        num_heads=(3, 6, 12, 24),
-        window_size=7,
-        mlp_ratio=4.0,
-        qkv_bias=True,
-        qk_scale=None,
-        drop_rate=0.0,
-        attn_drop_rate=0.0,
-        drop_path_rate=0.2,
-        norm_layer=nn.LayerNorm,
-        ape=False,
-        patch_norm=True,
-        out_indices=(0, 1, 2, 3),
-        frozen_stages=-1,
-        use_checkpoint=False,
-    ):
-        super().__init__()
-
-        self.pretrain_img_size = pretrain_img_size
-        self.num_layers = len(depths)
-        self.embed_dim = embed_dim
-        self.ape = ape
-        self.patch_norm = patch_norm
-        self.out_indices = out_indices
-        self.frozen_stages = frozen_stages
-
-        # split image into non-overlapping patches
-        self.patch_embed = PatchEmbed(
-            patch_size=patch_size,
-            in_chans=in_chans,
-            embed_dim=embed_dim,
-            norm_layer=norm_layer if self.patch_norm else None,
-        )
-
-        # absolute position embedding
-        if self.ape:
-            pretrain_img_size = _to_2tuple(pretrain_img_size)
-            patch_size = _to_2tuple(patch_size)
-            patches_resolution = [
-                pretrain_img_size[0] // patch_size[0],
-                pretrain_img_size[1] // patch_size[1],
-            ]
-
-            self.absolute_pos_embed = nn.Parameter(
-                torch.zeros(1, embed_dim, patches_resolution[0], patches_resolution[1])
-            )
-            nn.init.trunc_normal_(self.absolute_pos_embed, std=0.02)
-
-        self.pos_drop = nn.Dropout(p=drop_rate)
-
-        # stochastic depth
-        dpr = [
-            x.item() for x in torch.linspace(0, drop_path_rate, sum(depths))
-        ]  # stochastic depth decay rule
-
-        # build layers
-        self.layers = nn.ModuleList()
-        for i_layer in range(self.num_layers):
-            layer = BasicLayer(
-                dim=int(embed_dim * 2**i_layer),
-                depth=depths[i_layer],
-                num_heads=num_heads[i_layer],
-                window_size=window_size,
-                mlp_ratio=mlp_ratio,
-                qkv_bias=qkv_bias,
-                qk_scale=qk_scale,
-                drop=drop_rate,
-                attn_drop=attn_drop_rate,
-                drop_path=dpr[sum(depths[:i_layer]) : sum(depths[: i_layer + 1])],
-                norm_layer=norm_layer,
-                downsample=PatchMerging if (i_layer < self.num_layers - 1) else None,
-                use_checkpoint=use_checkpoint,
-            )
-            self.layers.append(layer)
-
-        num_features = [int(embed_dim * 2**i) for i in range(self.num_layers)]
-        self.num_features = num_features
-
-        # add a norm layer for each output
-        for i_layer in out_indices:
-            layer = norm_layer(num_features[i_layer])
-            layer_name = f"norm{i_layer}"
-            self.add_module(layer_name, layer)
-
-        self._freeze_stages()
-        self._out_features = ["p{}".format(i) for i in self.out_indices]
-        self._out_feature_channels = {
-            "p{}".format(i): self.embed_dim * 2**i for i in self.out_indices
-        }
-        self._out_feature_strides = {"p{}".format(i): 2 ** (i + 2) for i in self.out_indices}
-        self._size_devisibility = 32
-
-        self.apply(self._init_weights)
-
-    def _freeze_stages(self):
-        if self.frozen_stages >= 0:
-            self.patch_embed.eval()
-            for param in self.patch_embed.parameters():
-                param.requires_grad = False
-
-        if self.frozen_stages >= 1 and self.ape:
-            self.absolute_pos_embed.requires_grad = False
-
-        if self.frozen_stages >= 2:
-            self.pos_drop.eval()
-            for i in range(0, self.frozen_stages - 1):
-                m = self.layers[i]
-                m.eval()
-                for param in m.parameters():
-                    param.requires_grad = False
-
-    def _init_weights(self, m):
-        if isinstance(m, nn.Linear):
-            nn.init.trunc_normal_(m.weight, std=0.02)
-            if isinstance(m, nn.Linear) and m.bias is not None:
-                nn.init.constant_(m.bias, 0)
-        elif isinstance(m, nn.LayerNorm):
-            nn.init.constant_(m.bias, 0)
-            nn.init.constant_(m.weight, 1.0)
-
-    @property
-    def size_divisibility(self):
-        return self._size_divisibility
-
-    def forward(self, x):
-        """Forward function."""
-        x = self.patch_embed(x)
-
-        Wh, Ww = x.size(2), x.size(3)
-        if self.ape:
-            # interpolate the position embedding to the corresponding size
-            absolute_pos_embed = F.interpolate(
-                self.absolute_pos_embed, size=(Wh, Ww), mode="bicubic"
-            )
-            x = (x + absolute_pos_embed).flatten(2).transpose(1, 2)  # B Wh*Ww C
-        else:
-            x = x.flatten(2).transpose(1, 2)
-        x = self.pos_drop(x)
-
-        outs = {}
-        for i in range(self.num_layers):
-            layer = self.layers[i]
-            x_out, H, W, x, Wh, Ww = layer(x, Wh, Ww)
-
-            if i in self.out_indices:
-                norm_layer = getattr(self, f"norm{i}")
-                x_out = norm_layer(x_out)
-
-                out = x_out.view(-1, H, W, self.num_features[i]).permute(0, 3, 1, 2).contiguous()
-                outs["p{}".format(i)] = out
-
-        return outs
diff --git a/spaces/nsarrazin/agents-js-llama/tailwind.config.js b/spaces/nsarrazin/agents-js-llama/tailwind.config.js
deleted file mode 100644
index f4cb14b58de9eea8aac38f4b411b50234a62c160..0000000000000000000000000000000000000000
--- a/spaces/nsarrazin/agents-js-llama/tailwind.config.js
+++ /dev/null
@@ -1,11 +0,0 @@
-/** @type {import('tailwindcss').Config} */
-export default {
-  content: ['./src/**/*.{html,js,svelte,ts}'],
-    theme: {
-    extend: {},
-  },
-  plugins: [
-    require('daisyui')
-  ]
-}
-
diff --git a/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/network_blocks_2d.py b/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/network_blocks_2d.py
deleted file mode 100644
index 937e4c76fae71dcd4d8345ce1ad0f8f3019c7167..0000000000000000000000000000000000000000
--- a/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/network_blocks_2d.py
+++ /dev/null
@@ -1,186 +0,0 @@
-import torch
-import torch.nn as nn
-import numpy as np
-import torch.nn.functional as F
-
-
-class VanillaConv(nn.Module):
-    def __init__(
-        self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-        groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True)
-    ):
-
-        super().__init__()
-        if padding == -1:
-            if isinstance(kernel_size, int):
-                kernel_size = (kernel_size, kernel_size)
-            if isinstance(dilation, int):
-                dilation = (dilation, dilation)
-        self.padding = tuple(((np.array(kernel_size) - 1) * np.array(dilation)) // 2) if padding == -1 else padding
-        self.featureConv = nn.Conv2d(
-            in_channels, out_channels, kernel_size,
-            stride, self.padding, dilation, groups, bias)
-
-        self.norm = norm
-        if norm == "BN":
-            self.norm_layer = nn.BatchNorm2d(out_channels)
-        elif norm == "IN":
-            self.norm_layer = nn.InstanceNorm2d(out_channels, track_running_stats=True)
-        elif norm == "SN":
-            self.norm = None
-            self.featureConv = nn.utils.spectral_norm(self.featureConv)
-        else:
-            self.norm = None
-
-        self.activation = activation
-
-    def forward(self, xs):
-        out = self.featureConv(xs)
-        if self.activation:
-            out = self.activation(out)
-        if self.norm is not None:
-            out = self.norm_layer(out)
-        return out
-
-
-class VanillaDeconv(nn.Module):
-    def __init__(
-        self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-        groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True),
-        scale_factor=2
-    ):
-        super().__init__()
-        self.conv = VanillaConv(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation)
-        self.scale_factor = scale_factor
-
-    def forward(self, xs):
-        xs_resized = F.interpolate(xs, scale_factor=self.scale_factor)
-        return self.conv(xs_resized)
-
-
-class GatedConv(VanillaConv):
-    def __init__(
-        self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-        groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True)
-    ):
-        super().__init__(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation
-        )
-        self.gatingConv = nn.Conv2d(
-            in_channels, out_channels, kernel_size,
-            stride, self.padding, dilation, groups, bias)
-        if norm == 'SN':
-            self.gatingConv = nn.utils.spectral_norm(self.gatingConv)
-        self.sigmoid = nn.Sigmoid()
-        self.store_gated_values = False
-
-    def gated(self, mask):
-        # return torch.clamp(mask, -1, 1)
-        out = self.sigmoid(mask)
-        if self.store_gated_values:
-            self.gated_values = out.detach().cpu()
-        return out
-
-    def forward(self, xs):
-        gating = self.gatingConv(xs)
-        feature = self.featureConv(xs)
-        if self.activation:
-            feature = self.activation(feature)
-        out = self.gated(gating) * feature
-        if self.norm is not None:
-            out = self.norm_layer(out)
-        return out
-
-
-class GatedDeconv(VanillaDeconv):
-    def __init__(
-        self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-        groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True),
-        scale_factor=2
-    ):
-        super().__init__(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation, scale_factor
-        )
-        self.conv = GatedConv(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation)
-
-
-class PartialConv(VanillaConv):
-    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-                 groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True)):
-        super().__init__(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation
-        )
-        self.mask_sum_conv = nn.Conv2d(1, 1, kernel_size,
-                                                stride, self.padding, dilation, groups, False)
-        nn.init.constant_(self.mask_sum_conv.weight, 1.0)
-
-        # mask conv needs not update
-        for param in self.mask_sum_conv.parameters():
-            param.requires_grad = False
-
-    def forward(self, input_tuple):
-        # http://masc.cs.gmu.edu/wiki/partialconv
-        # C(X) = W^T * X + b, C(0) = b, D(M) = 1 * M + 0 = sum(M)
-        # output = W^T* (M .* X) / sum(M) + b = [C(M .* X) – C(0)] / D(M) + C(0), if sum(M) != 0
-        #        = 0, if sum(M) == 0
-        inp, mask = input_tuple
-        # print(inp.shape, mask.shape)
-
-        # C(M .* X)
-        output = self.featureConv(mask * inp)
-
-        # C(0) = b
-        if self.featureConv.bias is not None:
-            output_bias = self.featureConv.bias.view(1, -1, 1, 1)
-        else:
-            output_bias = torch.zeros([1, 1, 1, 1]).to(inp.device)
-
-        # D(M) = sum(M)
-        with torch.no_grad():
-            mask_sum = self.mask_sum_conv(mask)
-
-        # find those sum(M) == 0
-        no_update_holes = (mask_sum == 0)
-
-        # Just to prevent devided by 0
-        mask_sum_no_zero = mask_sum.masked_fill_(no_update_holes, 1.0)
-
-        # output = [C(M .* X) – C(0)] / D(M) + C(0), if sum(M) != 0
-        #        = 0, if sum (M) == 0
-        output = (output - output_bias) / mask_sum_no_zero + output_bias
-        output = output.masked_fill_(no_update_holes, 0.0)
-
-        # create a new mask with only 1 or 0
-        new_mask = torch.ones_like(mask_sum)
-        new_mask = new_mask.masked_fill_(no_update_holes, 0.0)
-
-        if self.activation is not None:
-            output = self.activation(output)
-        if self.norm is not None:
-            output = self.norm_layer(output)
-        return output, new_mask
-
-
-class PartialDeconv(nn.Module):
-    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1,
-                 groups=1, bias=True, norm="SN", activation=nn.LeakyReLU(0.2, inplace=True),
-                 scale_factor=2):
-        super().__init__()
-        self.conv = PartialConv(
-            in_channels, out_channels, kernel_size, stride, padding, dilation,
-            groups, bias, norm, activation)
-        self.scale_factor = scale_factor
-
-    def forward(self, input_tuple):
-        inp, mask = input_tuple
-        inp_resized = F.interpolate(inp, scale_factor=self.scale_factor)
-        with torch.no_grad():
-            mask_resized = F.interpolate(mask, scale_factor=self.scale_factor)
-        return self.conv((inp_resized, mask_resized))
diff --git a/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/sobel2.py b/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/sobel2.py
deleted file mode 100644
index 7a4ec74aff4cf187a738f717bac94bbb87dc0b60..0000000000000000000000000000000000000000
--- a/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/utils/sobel2.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-class SobelLayer(nn.Module):
-    def __init__(self, device):
-        super(SobelLayer, self).__init__()
-        self.kernel_x = torch.tensor([[-1., 0, 1], [-2, 0, 2], [-1, 0, 1]]).unsqueeze(0).unsqueeze(0) / 4.
-        self.kernel_y = torch.tensor([[-1, -2, -1], [0, 0, 0], [1, 2, 1.]]).unsqueeze(0).unsqueeze(0) / 4.
-        self.kernel_x = self.kernel_x.to(device)
-        self.kernel_y = self.kernel_y.to(device)
-        self.pad = nn.ReplicationPad2d(padding=1)
-        self.absLayer = nn.ReLU()
-
-    def forward(self, images):
-        """
-
-        Args:
-            images: images with shape [b, c, h, w]
-
-        Returns:
-
-        """
-        images = self.pad(images)
-        gray_images = self._convertGrey(images)
-
-        edge_x = F.conv2d(gray_images, self.kernel_x, stride=1)
-        edge_y = F.conv2d(gray_images, self.kernel_y, stride=1)
-        edge = (self.absLayer(edge_x) + self.absLayer(edge_y)) / 2
-        return edge
-
-    def _convertGrey(self, image):
-        """
-        grey = 0.299 * r + 0.587 * g + 0.110 * b
-        Args:
-            image: RGB image
-
-        Returns: Grey scale image
-
-        """
-        grey_image = image[:, 0] * 0.299 + image[:, 1] * 0.587 + 0.110 * image[:, 2]
-        output = grey_image.unsqueeze(1)
-        return output
-
-
-class SeperateSobelLayer(nn.Module):
-    def __init__(self, device):
-        super(SeperateSobelLayer, self).__init__()
-        self.kernel_x = torch.tensor([[-1., 0, 1], [-2, 0, 2], [-1, 0, 1]]).unsqueeze(0).unsqueeze(0)
-        self.kernel_y = torch.tensor([[-1, -2, -1], [0, 0, 0], [1, 2, 1.]]).unsqueeze(0).unsqueeze(0)
-        self.weight = torch.zeros([6, 3, 3, 3])
-        for c in range(3):
-            self.weight[2 * c, c] = self.kernel_x
-            self.weight[2 * c + 1, c] = self.kernel_y
-        self.weight = self.weight.to(device)
-
-    def forward(self, images):
-        """
-
-        Args:
-            images: with shape [b, c, h, w]
-
-        Returns: sobel gradient image with shape [b, c, h, w] (same padding)
-
-        """
-        gradientMap = F.conv2d(images, self.weight, stride=1, padding=1)
-        return gradientMap
diff --git a/spaces/omlab/vlchecklist_demo/models/vilt/utils/write_conceptual_caption.py b/spaces/omlab/vlchecklist_demo/models/vilt/utils/write_conceptual_caption.py
deleted file mode 100644
index e0c1a0788f6f955df9e5028d79bf6c99e28e7b56..0000000000000000000000000000000000000000
--- a/spaces/omlab/vlchecklist_demo/models/vilt/utils/write_conceptual_caption.py
+++ /dev/null
@@ -1,71 +0,0 @@
-import json
-import pandas as pd
-import pyarrow as pa
-import gc
-import random
-import os
-
-from tqdm import tqdm
-from glob import glob
-
-
-def path2rest(path, iid2captions):
-    split, _, name = path.split("/")[-3:]
-    split = split.split("_")[-1]
-    iid = name
-
-    with open(path, "rb") as fp:
-        binary = fp.read()
-
-    captions = iid2captions[iid]
-
-    return [
-        binary,
-        captions,
-        iid,
-        split,
-    ]
-
-
-def make_arrow(root, dataset_root):
-    for split in ["val", "train"]:
-        with open(f"{root}/{split}_annot.json", "r") as fp:
-            captions = json.load(fp)
-
-        iid2captions = dict()
-        for cap in tqdm(captions):
-            iid = cap[0].split("/")[-1]
-            iid2captions[iid] = [cap[1]]
-
-        paths = list(glob(f"{root}/images_{split}/*/*"))
-        random.shuffle(paths)
-        caption_paths = [path for path in paths if path.split("/")[-1] in iid2captions]
-        if len(paths) == len(caption_paths):
-            print("all images have caption annotations")
-        else:
-            print("not all images have caption annotations")
-        print(
-            len(paths), len(caption_paths), len(iid2captions),
-        )
-
-        sub_len = int(len(caption_paths) // 100000)
-        subs = list(range(sub_len + 1))
-        for sub in subs:
-            sub_paths = caption_paths[sub * 100000 : (sub + 1) * 100000]
-            bs = [path2rest(path, iid2captions) for path in tqdm(sub_paths)]
-            dataframe = pd.DataFrame(
-                bs, columns=["image", "caption", "image_id", "split"],
-            )
-
-            table = pa.Table.from_pandas(dataframe)
-
-            os.makedirs(dataset_root, exist_ok=True)
-            with pa.OSFile(
-                f"{dataset_root}/conceptual_caption_{split}_{sub}.arrow", "wb"
-            ) as sink:
-                with pa.RecordBatchFileWriter(sink, table.schema) as writer:
-                    writer.write_table(table)
-            del dataframe
-            del table
-            del bs
-            gc.collect()
diff --git a/spaces/osanseviero/HUBERT/README.md b/spaces/osanseviero/HUBERT/README.md
deleted file mode 100644
index 906e3f7e31912cd88ce05227ef1759f0454e9193..0000000000000000000000000000000000000000
--- a/spaces/osanseviero/HUBERT/README.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-title: HUBERT
-emoji: 🌍
-colorFrom: pink
-colorTo: purple
-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` or `streamlit`
-
-`app_file`: _string_  
-Path to your main application file (which contains either `gradio` or `streamlit` Python 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/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/score_sde_vp.md b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/score_sde_vp.md
deleted file mode 100644
index 0f70a424841a5d1787272a6b17eea7400f4f0233..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/schedulers/score_sde_vp.md
+++ /dev/null
@@ -1,28 +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.
--->
-
-# ScoreSdeVpScheduler
-
-`ScoreSdeVpScheduler` is a variance preserving stochastic differential equation (SDE) scheduler.  It was introduced in the [Score-Based Generative Modeling through Stochastic Differential Equations](https://huggingface.co/papers/2011.13456) paper by Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole.
-
-The abstract from the paper is:
-
-*Creating noise from data is easy; creating data from noise is generative modeling. We present a stochastic differential equation (SDE) that smoothly transforms a complex data distribution to a known prior distribution by slowly injecting noise, and a corresponding reverse-time SDE that transforms the prior distribution back into the data distribution by slowly removing the noise. Crucially, the reverse-time SDE depends only on the time-dependent gradient field (\aka, score) of the perturbed data distribution. By leveraging advances in score-based generative modeling, we can accurately estimate these scores with neural networks, and use numerical SDE solvers to generate samples. We show that this framework encapsulates previous approaches in score-based generative modeling and diffusion probabilistic modeling, allowing for new sampling procedures and new modeling capabilities. In particular, we introduce a predictor-corrector framework to correct errors in the evolution of the discretized reverse-time SDE. We also derive an equivalent neural ODE that samples from the same distribution as the SDE, but additionally enables exact likelihood computation, and improved sampling efficiency. In addition, we provide a new way to solve inverse problems with score-based models, as demonstrated with experiments on class-conditional generation, image inpainting, and colorization. Combined with multiple architectural improvements, we achieve record-breaking performance for unconditional image generation on CIFAR-10 with an Inception score of 9.89 and FID of 2.20, a competitive likelihood of 2.99 bits/dim, and demonstrate high fidelity generation of 1024 x 1024 images for the first time from a score-based generative model*.
-
-<Tip warning={true}>
-
-🚧 This scheduler is under construction!
-
-</Tip>
-
-## ScoreSdeVpScheduler
-[[autodoc]] schedulers.scheduling_sde_vp.ScoreSdeVpScheduler
diff --git a/spaces/parkyzh/bingo/src/lib/hooks/use-at-bottom.tsx b/spaces/parkyzh/bingo/src/lib/hooks/use-at-bottom.tsx
deleted file mode 100644
index d37c8cf4162adcb0064e08ecec24eb731416b045..0000000000000000000000000000000000000000
--- a/spaces/parkyzh/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/patgpt4/MusicGen/audiocraft/models/builders.py b/spaces/patgpt4/MusicGen/audiocraft/models/builders.py
deleted file mode 100644
index 77ee5f96fea2e3c9e475fe961bc1a5ee473ed8eb..0000000000000000000000000000000000000000
--- a/spaces/patgpt4/MusicGen/audiocraft/models/builders.py
+++ /dev/null
@@ -1,218 +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.
-
-"""
-All the functions to build the relevant models and modules
-from the Hydra config.
-"""
-
-import typing as tp
-import warnings
-
-import audiocraft
-import omegaconf
-import torch
-
-from .encodec import CompressionModel, EncodecModel, FlattenedCompressionModel  # noqa
-from .lm import LMModel
-from ..modules.codebooks_patterns import (
-    CodebooksPatternProvider,
-    DelayedPatternProvider,
-    ParallelPatternProvider,
-    UnrolledPatternProvider,
-    VALLEPattern,
-    MusicLMPattern,
-)
-from ..modules.conditioners import (
-    BaseConditioner,
-    ConditioningProvider,
-    LUTConditioner,
-    T5Conditioner,
-    ConditionFuser,
-    ChromaStemConditioner,
-)
-from .. import quantization as qt
-from ..utils.utils import dict_from_config
-
-
-def get_quantizer(quantizer: str, cfg: omegaconf.DictConfig, dimension: int) -> qt.BaseQuantizer:
-    klass = {
-        'no_quant': qt.DummyQuantizer,
-        'rvq': qt.ResidualVectorQuantizer
-    }[quantizer]
-    kwargs = dict_from_config(getattr(cfg, quantizer))
-    if quantizer != 'no_quant':
-        kwargs['dimension'] = dimension
-    return klass(**kwargs)
-
-
-def get_encodec_autoencoder(encoder_name: str, cfg: omegaconf.DictConfig):
-    if encoder_name == 'seanet':
-        kwargs = dict_from_config(getattr(cfg, 'seanet'))
-        encoder_override_kwargs = kwargs.pop('encoder')
-        decoder_override_kwargs = kwargs.pop('decoder')
-        encoder_kwargs = {**kwargs, **encoder_override_kwargs}
-        decoder_kwargs = {**kwargs, **decoder_override_kwargs}
-        encoder = audiocraft.modules.SEANetEncoder(**encoder_kwargs)
-        decoder = audiocraft.modules.SEANetDecoder(**decoder_kwargs)
-        return encoder, decoder
-    else:
-        raise KeyError(f'Unexpected compression model {cfg.compression_model}')
-
-
-def get_compression_model(cfg: omegaconf.DictConfig) -> CompressionModel:
-    """Instantiate a compression model.
-    """
-    if cfg.compression_model == 'encodec':
-        kwargs = dict_from_config(getattr(cfg, 'encodec'))
-        encoder_name = kwargs.pop('autoencoder')
-        quantizer_name = kwargs.pop('quantizer')
-        encoder, decoder = get_encodec_autoencoder(encoder_name, cfg)
-        quantizer = get_quantizer(quantizer_name, cfg, encoder.dimension)
-        frame_rate = kwargs['sample_rate'] // encoder.hop_length
-        renormalize = kwargs.pop('renormalize', None)
-        renorm = kwargs.pop('renorm')
-        if renormalize is None:
-            renormalize = renorm is not None
-            warnings.warn("You are using a deprecated EnCodec model. Please migrate to new renormalization.")
-        return EncodecModel(encoder, decoder, quantizer,
-                            frame_rate=frame_rate, renormalize=renormalize, **kwargs).to(cfg.device)
-    else:
-        raise KeyError(f'Unexpected compression model {cfg.compression_model}')
-
-
-def get_lm_model(cfg: omegaconf.DictConfig) -> LMModel:
-    """Instantiate a transformer LM.
-    """
-    if cfg.lm_model == 'transformer_lm':
-        kwargs = dict_from_config(getattr(cfg, 'transformer_lm'))
-        n_q = kwargs['n_q']
-        q_modeling = kwargs.pop('q_modeling', None)
-        codebooks_pattern_cfg = getattr(cfg, 'codebooks_pattern')
-        attribute_dropout = dict_from_config(getattr(cfg, 'attribute_dropout'))
-        cls_free_guidance = dict_from_config(getattr(cfg, 'classifier_free_guidance'))
-        cfg_prob, cfg_coef = cls_free_guidance["training_dropout"], cls_free_guidance["inference_coef"]
-        fuser = get_condition_fuser(cfg)
-        condition_provider = get_conditioner_provider(kwargs["dim"], cfg).to(cfg.device)
-        if len(fuser.fuse2cond['cross']) > 0:  # enforce cross-att programatically
-            kwargs['cross_attention'] = True
-        if codebooks_pattern_cfg.modeling is None:
-            assert q_modeling is not None, \
-                'LM model should either have a codebook pattern defined or transformer_lm.q_modeling'
-            codebooks_pattern_cfg = omegaconf.OmegaConf.create(
-                {'modeling': q_modeling, 'delay': {'delays': list(range(n_q))}}
-            )
-        pattern_provider = get_codebooks_pattern_provider(n_q, codebooks_pattern_cfg)
-        return LMModel(
-            pattern_provider=pattern_provider,
-            condition_provider=condition_provider,
-            fuser=fuser,
-            cfg_dropout=cfg_prob,
-            cfg_coef=cfg_coef,
-            attribute_dropout=attribute_dropout,
-            dtype=getattr(torch, cfg.dtype),
-            device=cfg.device,
-            **kwargs
-        ).to(cfg.device)
-    else:
-        raise KeyError(f'Unexpected LM model {cfg.lm_model}')
-
-
-def get_conditioner_provider(output_dim: int, cfg: omegaconf.DictConfig) -> ConditioningProvider:
-    """Instantiate a conditioning model.
-    """
-    device = cfg.device
-    duration = cfg.dataset.segment_duration
-    cfg = getattr(cfg, "conditioners")
-    cfg = omegaconf.OmegaConf.create({}) if cfg is None else cfg
-    conditioners: tp.Dict[str, BaseConditioner] = {}
-    with omegaconf.open_dict(cfg):
-        condition_provider_args = cfg.pop('args', {})
-    for cond, cond_cfg in cfg.items():
-        model_type = cond_cfg["model"]
-        model_args = cond_cfg[model_type]
-        if model_type == "t5":
-            conditioners[str(cond)] = T5Conditioner(output_dim=output_dim, device=device, **model_args)
-        elif model_type == "lut":
-            conditioners[str(cond)] = LUTConditioner(output_dim=output_dim, **model_args)
-        elif model_type == "chroma_stem":
-            model_args.pop('cache_path', None)
-            conditioners[str(cond)] = ChromaStemConditioner(
-                output_dim=output_dim,
-                duration=duration,
-                device=device,
-                **model_args
-            )
-        else:
-            raise ValueError(f"unrecognized conditioning model: {model_type}")
-    conditioner = ConditioningProvider(conditioners, device=device, **condition_provider_args)
-    return conditioner
-
-
-def get_condition_fuser(cfg: omegaconf.DictConfig) -> ConditionFuser:
-    """Instantiate a condition fuser object.
-    """
-    fuser_cfg = getattr(cfg, "fuser")
-    fuser_methods = ["sum", "cross", "prepend", "input_interpolate"]
-    fuse2cond = {k: fuser_cfg[k] for k in fuser_methods}
-    kwargs = {k: v for k, v in fuser_cfg.items() if k not in fuser_methods}
-    fuser = ConditionFuser(fuse2cond=fuse2cond, **kwargs)
-    return fuser
-
-
-def get_codebooks_pattern_provider(n_q: int, cfg: omegaconf.DictConfig) -> CodebooksPatternProvider:
-    """Instantiate a codebooks pattern provider object.
-    """
-    pattern_providers = {
-        'parallel': ParallelPatternProvider,
-        'delay': DelayedPatternProvider,
-        'unroll': UnrolledPatternProvider,
-        'valle': VALLEPattern,
-        'musiclm': MusicLMPattern,
-    }
-    name = cfg.modeling
-    kwargs = dict_from_config(cfg.get(name)) if hasattr(cfg, name) else {}
-    klass = pattern_providers[name]
-    return klass(n_q, **kwargs)
-
-
-def get_debug_compression_model(device='cpu'):
-    """Instantiate a debug compression model to be used for unit tests.
-    """
-    seanet_kwargs = {
-        'n_filters': 4,
-        'n_residual_layers': 1,
-        'dimension': 32,
-        'ratios': [10, 8, 16]  # 25 Hz at 32kHz
-    }
-    encoder = audiocraft.modules.SEANetEncoder(**seanet_kwargs)
-    decoder = audiocraft.modules.SEANetDecoder(**seanet_kwargs)
-    quantizer = qt.ResidualVectorQuantizer(dimension=32, bins=400, n_q=4)
-    init_x = torch.randn(8, 32, 128)
-    quantizer(init_x, 1)  # initialize kmeans etc.
-    compression_model = EncodecModel(
-        encoder, decoder, quantizer,
-        frame_rate=25, sample_rate=32000, channels=1).to(device)
-    return compression_model.eval()
-
-
-def get_debug_lm_model(device='cpu'):
-    """Instantiate a debug LM to be used for unit tests.
-    """
-    pattern = DelayedPatternProvider(n_q=4)
-    dim = 16
-    providers = {
-        'description': LUTConditioner(n_bins=128, dim=dim, output_dim=dim, tokenizer="whitespace"),
-    }
-    condition_provider = ConditioningProvider(providers)
-    fuser = ConditionFuser(
-        {'cross': ['description'], 'prepend': [],
-         'sum': [], 'input_interpolate': []})
-    lm = LMModel(
-        pattern, condition_provider, fuser,
-        n_q=4, card=400, dim=dim, num_heads=4, custom=True, num_layers=2,
-        cross_attention=True, causal=True)
-    return lm.to(device).eval()
diff --git a/spaces/pkiage/time_series_autocorrelation_demo/setup.sh b/spaces/pkiage/time_series_autocorrelation_demo/setup.sh
deleted file mode 100644
index 2aea680e9e2290bc67b643cd6ef284de4bb922b3..0000000000000000000000000000000000000000
--- a/spaces/pkiage/time_series_autocorrelation_demo/setup.sh
+++ /dev/null
@@ -1,13 +0,0 @@
-mkdir -p ~/.streamlit/
-
-cat << EOF > ~/.streamlit/credentials.toml
-[general]
-email = "paul.r.kiage@gmail.com"
-EOF
-
-cat << EOF > ~/.streamlit/config.toml
-[server]
-headless = true
-enableCORS = true
-port = $PORT
-EOF
\ No newline at end of file
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_vendor/importlib_metadata/_collections.py b/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_vendor/importlib_metadata/_collections.py
deleted file mode 100644
index cf0954e1a30546d781bf25781ec716ef92a77e32..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_vendor/importlib_metadata/_collections.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import collections
-
-
-# from jaraco.collections 3.3
-class FreezableDefaultDict(collections.defaultdict):
-    """
-    Often it is desirable to prevent the mutation of
-    a default dict after its initial construction, such
-    as to prevent mutation during iteration.
-
-    >>> dd = FreezableDefaultDict(list)
-    >>> dd[0].append('1')
-    >>> dd.freeze()
-    >>> dd[1]
-    []
-    >>> len(dd)
-    1
-    """
-
-    def __missing__(self, key):
-        return getattr(self, '_frozen', super().__missing__)(key)
-
-    def freeze(self):
-        self._frozen = lambda key: self.default_factory()
-
-
-class Pair(collections.namedtuple('Pair', 'name value')):
-    @classmethod
-    def parse(cls, text):
-        return cls(*map(str.strip, text.split("=", 1)))
diff --git a/spaces/ppsingh/cpu-demo/utils/__init__.py b/spaces/ppsingh/cpu-demo/utils/__init__.py
deleted file mode 100644
index 802fa483031a6683fa4d7aa4addae78f56f2937b..0000000000000000000000000000000000000000
--- a/spaces/ppsingh/cpu-demo/utils/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-# adding for package implementation
\ No newline at end of file
diff --git a/spaces/prerna9811/Chord/portaudio/bindings/java/c/src/com_portaudio_BlockingStream.c b/spaces/prerna9811/Chord/portaudio/bindings/java/c/src/com_portaudio_BlockingStream.c
deleted file mode 100644
index 64d82134d9395c38138dc5e42b3535882b30b9fc..0000000000000000000000000000000000000000
--- a/spaces/prerna9811/Chord/portaudio/bindings/java/c/src/com_portaudio_BlockingStream.c
+++ /dev/null
@@ -1,352 +0,0 @@
-/*
- * Portable Audio I/O Library
- * Java Binding for PortAudio
- *
- * Based on the Open Source API proposed by Ross Bencina
- * Copyright (c) 2008 Ross Bencina
- *
- * 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.
- */
-
-#include "com_portaudio_BlockingStream.h"
-#include "portaudio.h"
-#include "jpa_tools.h"
-
-#ifndef FALSE
-#define FALSE  (0)
-#endif
-#ifndef TRUE
-#define TRUE  (!FALSE)
-#endif
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    getReadAvailable
- * Signature: ()I
- */
-JNIEXPORT jint JNICALL Java_com_portaudio_BlockingStream_getReadAvailable
-  (JNIEnv *env, jobject blockingStream)
-{
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream == NULL ) return 0;
-	return Pa_GetStreamReadAvailable( stream );
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    getWriteAvailable
- * Signature: ()I
- */
-JNIEXPORT jint JNICALL Java_com_portaudio_BlockingStream_getWriteAvailable
-  (JNIEnv *env, jobject blockingStream)
-{
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream == NULL ) return 0;
-	return Pa_GetStreamWriteAvailable( stream );
-}
-
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    writeFloats
- * Signature: ([FI)Z
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_writeFloats
-  (JNIEnv *env, jobject blockingStream, jfloatArray buffer, jint numFrames)
-{
-	jfloat *carr;
-	jint err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( buffer == NULL )
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "null stream buffer");
-		return FALSE;
-	}
-	carr = (*env)->GetFloatArrayElements(env, buffer, NULL);
-	if (carr == NULL)
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "invalid stream buffer");
-		return FALSE;
-	}
-	err = Pa_WriteStream( stream, carr, numFrames );
-	(*env)->ReleaseFloatArrayElements(env, buffer, carr, 0);
-	if( err == paOutputUnderflowed )
-	{
-		return TRUE;
-	}
-	else
-	{
-		jpa_CheckError( env, err );
-		return FALSE;
-	}
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    readFloats
- * Signature: ([FI)Z
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_readFloats
-  (JNIEnv *env, jobject blockingStream, jfloatArray buffer, jint numFrames)
-{
-	jfloat *carr;
-	jint err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( buffer == NULL )
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "null stream buffer");
-		return FALSE;
-	}
-	carr = (*env)->GetFloatArrayElements(env, buffer, NULL);
-	if (carr == NULL)
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "invalid stream buffer");
-		return FALSE;
-	}
-	err = Pa_ReadStream( stream, carr, numFrames );
-	(*env)->ReleaseFloatArrayElements(env, buffer, carr, 0);
-	if( err == paInputOverflowed )
-	{
-		return TRUE;
-	}
-	else
-	{
-		jpa_CheckError( env, err );
-		return FALSE;
-	}
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    writeShorts
- * Signature: ([SI)Z
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_writeShorts
-  (JNIEnv *env, jobject blockingStream, jfloatArray buffer, jint numFrames)
-{
-	jshort *carr;
-	jint err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( buffer == NULL )
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "null stream buffer");
-		return FALSE;
-	}
-	carr = (*env)->GetShortArrayElements(env, buffer, NULL);
-	if (carr == NULL)
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "invalid stream buffer");
-		return FALSE;
-	}
-	err = Pa_WriteStream( stream, carr, numFrames );
-	(*env)->ReleaseShortArrayElements(env, buffer, carr, 0);
-	if( err == paOutputUnderflowed )
-	{
-		return TRUE;
-	}
-	else
-	{
-		jpa_CheckError( env, err );
-		return FALSE;
-	}
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    readShorts
- * Signature: ([SI)Z
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_readShorts
-  (JNIEnv *env, jobject blockingStream, jfloatArray buffer, jint numFrames)
-{
-	jshort *carr;
-	jint err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( buffer == NULL )
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "null stream buffer");
-		return FALSE;
-	}
-	carr = (*env)->GetShortArrayElements(env, buffer, NULL);
-	if (carr == NULL)
-	{
-		(*env)->ThrowNew( env, (*env)->FindClass(env,"java/lang/RuntimeException"),
-                  "invalid stream buffer");
-		return FALSE;
-	}
-	err = Pa_ReadStream( stream, carr, numFrames );
-	(*env)->ReleaseShortArrayElements(env, buffer, carr, 0);
-	if( err == paInputOverflowed )
-	{
-		return TRUE;
-	}
-	else
-	{
-		jpa_CheckError( env, err );
-		return FALSE;
-	}
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    start
- * Signature: ()V
- */
-JNIEXPORT void JNICALL Java_com_portaudio_BlockingStream_start
-  (JNIEnv *env, jobject blockingStream )
-{
-	PaStream *stream = jpa_GetStreamPointer( env, blockingStream );
-	int err = Pa_StartStream( stream );
-	jpa_CheckError( env, err );
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    stop
- * Signature: ()V
- */
-JNIEXPORT void JNICALL Java_com_portaudio_BlockingStream_stop
-  (JNIEnv *env, jobject blockingStream )
-{
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	int err = Pa_StopStream( stream );
-	jpa_CheckError( env, err );
-}
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    abort
- * Signature: ()V
- */
-JNIEXPORT void JNICALL Java_com_portaudio_BlockingStream_abort
-  (JNIEnv *env, jobject blockingStream )
-{
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	int err = Pa_AbortStream( stream );
-	jpa_CheckError( env, err );
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    close
- * Signature: ()V
- */
-JNIEXPORT void JNICALL Java_com_portaudio_BlockingStream_close
-  (JNIEnv *env, jobject blockingStream )
-{
-	jclass cls;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream != NULL )
-	{
-		int err = Pa_CloseStream( stream );
-		jpa_CheckError( env, err );
-		cls = (*env)->GetObjectClass(env, blockingStream);
-		jpa_SetLongField( env, cls, blockingStream, "nativeStream", (jlong) 0 );
-	}
-}
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    isStopped
- * Signature: ()V
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_isStopped
-  (JNIEnv *env, jobject blockingStream )
-{
-	int err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream == NULL ) return 1;
-	err = Pa_IsStreamStopped( stream );
-	return (jpa_CheckError( env, err ) > 0);
-}
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    isActive
- * Signature: ()V
- */
-JNIEXPORT jboolean JNICALL Java_com_portaudio_BlockingStream_isActive
-  (JNIEnv *env, jobject blockingStream )
-{
-	int err;
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream == NULL ) return 0;
-	err = Pa_IsStreamActive( stream );
-	return (jpa_CheckError( env, err ) > 0);
-}
-
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    getTime
- * Signature: ()D
- */
-JNIEXPORT jdouble JNICALL Java_com_portaudio_BlockingStream_getTime
-  (JNIEnv *env, jobject blockingStream )
-{
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	if( stream == NULL ) return 0.0;
-	return Pa_GetStreamTime( stream );
-}
-
-
-/*
- * Class:     com_portaudio_BlockingStream
- * Method:    getInfo
- * Signature: ()Lcom/portaudio/StreamInfo;
- */
-JNIEXPORT void JNICALL Java_com_portaudio_BlockingStream_getInfo
-  (JNIEnv *env, jobject blockingStream, jobject streamInfo)
-{
-	
-	PaStream *stream =jpa_GetStreamPointer( env, blockingStream );
-	const PaStreamInfo *info = Pa_GetStreamInfo( stream );
-	if( streamInfo == NULL )
-	{
-		jpa_ThrowError( env, "Invalid stream." );
-	}
-	else
-	{
-		/* Get a reference to obj's class */
-		jclass cls = (*env)->GetObjectClass(env, streamInfo);
- 
-		jpa_SetIntField( env, cls, streamInfo, "structVersion", info->structVersion );
-		jpa_SetDoubleField( env, cls, streamInfo, "inputLatency", info->inputLatency );
-		jpa_SetDoubleField( env, cls, streamInfo, "outputLatency", info->outputLatency );
-		jpa_SetDoubleField( env, cls, streamInfo, "sampleRate", info->sampleRate );
-	}
-}
-
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/httpx/_transports/mock.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/httpx/_transports/mock.py
deleted file mode 100644
index 82043da2d908f7575097f14b08c1a8a60fa1f8a4..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/httpx/_transports/mock.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import typing
-
-from .._models import Request, Response
-from .base import AsyncBaseTransport, BaseTransport
-
-SyncHandler = typing.Callable[[Request], Response]
-AsyncHandler = typing.Callable[[Request], typing.Coroutine[None, None, Response]]
-
-
-class MockTransport(AsyncBaseTransport, BaseTransport):
-    def __init__(self, handler: typing.Union[SyncHandler, AsyncHandler]) -> None:
-        self.handler = handler
-
-    def handle_request(
-        self,
-        request: Request,
-    ) -> Response:
-        request.read()
-        response = self.handler(request)
-        if not isinstance(response, Response):  # pragma: no cover
-            raise TypeError("Cannot use an async handler in a sync Client")
-        return response
-
-    async def handle_async_request(
-        self,
-        request: Request,
-    ) -> Response:
-        await request.aread()
-        response = self.handler(request)
-
-        # Allow handler to *optionally* be an `async` function.
-        # If it is, then the `response` variable need to be awaited to actually
-        # return the result.
-
-        if not isinstance(response, Response):
-            response = await response
-
-        return response
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/compat/tests/__init__.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/compat/tests/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/distutils/checks/cpu_sse3.c b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/distutils/checks/cpu_sse3.c
deleted file mode 100644
index d47c20f74be1f83afd1962917438507c609e5413..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/distutils/checks/cpu_sse3.c
+++ /dev/null
@@ -1,20 +0,0 @@
-#if defined(DETECT_FEATURES) && defined(__INTEL_COMPILER)
-    /*
-     * Unlike GCC and CLANG, Intel Compiler exposes all supported intrinsics,
-     * whether or not the build options for those features are specified.
-     * Therefore, we must test #definitions of CPU features when option native/host
-     * is enabled via `--cpu-baseline` or through env var `CFLAGS` otherwise
-     * the test will be broken and leads to enable all possible features.
-     */
-    #ifndef __SSE3__
-        #error "HOST/ARCH doesn't support SSE3"
-    #endif
-#endif
-
-#include <pmmintrin.h>
-
-int main(void)
-{
-    __m128 a = _mm_hadd_ps(_mm_setzero_ps(), _mm_setzero_ps());
-    return (int)_mm_cvtss_f32(a);
-}
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/base_class/test_setops.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/base_class/test_setops.py
deleted file mode 100644
index 488f79eea0d111c0206bac7f21cf9633f5b77057..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/base_class/test_setops.py
+++ /dev/null
@@ -1,259 +0,0 @@
-from datetime import datetime
-
-import numpy as np
-import pytest
-
-import pandas as pd
-from pandas import (
-    Index,
-    Series,
-)
-import pandas._testing as tm
-from pandas.core.algorithms import safe_sort
-
-
-class TestIndexSetOps:
-    @pytest.mark.parametrize(
-        "method", ["union", "intersection", "difference", "symmetric_difference"]
-    )
-    def test_setops_sort_validation(self, method):
-        idx1 = Index(["a", "b"])
-        idx2 = Index(["b", "c"])
-
-        with pytest.raises(ValueError, match="The 'sort' keyword only takes"):
-            getattr(idx1, method)(idx2, sort=2)
-
-        # sort=True is supported as of GH#??
-        getattr(idx1, method)(idx2, sort=True)
-
-    def test_setops_preserve_object_dtype(self):
-        idx = Index([1, 2, 3], dtype=object)
-        result = idx.intersection(idx[1:])
-        expected = idx[1:]
-        tm.assert_index_equal(result, expected)
-
-        # if other is not monotonic increasing, intersection goes through
-        #  a different route
-        result = idx.intersection(idx[1:][::-1])
-        tm.assert_index_equal(result, expected)
-
-        result = idx._union(idx[1:], sort=None)
-        expected = idx
-        tm.assert_numpy_array_equal(result, expected.values)
-
-        result = idx.union(idx[1:], sort=None)
-        tm.assert_index_equal(result, expected)
-
-        # if other is not monotonic increasing, _union goes through
-        #  a different route
-        result = idx._union(idx[1:][::-1], sort=None)
-        tm.assert_numpy_array_equal(result, expected.values)
-
-        result = idx.union(idx[1:][::-1], sort=None)
-        tm.assert_index_equal(result, expected)
-
-    def test_union_base(self):
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[3:]
-        second = index[:5]
-
-        result = first.union(second)
-
-        expected = Index([0, 1, 2, "a", "b", "c"])
-        tm.assert_index_equal(result, expected)
-
-    @pytest.mark.parametrize("klass", [np.array, Series, list])
-    def test_union_different_type_base(self, klass):
-        # GH 10149
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[3:]
-        second = index[:5]
-
-        result = first.union(klass(second.values))
-
-        assert tm.equalContents(result, index)
-
-    def test_union_sort_other_incomparable(self):
-        # https://github.com/pandas-dev/pandas/issues/24959
-        idx = Index([1, pd.Timestamp("2000")])
-        # default (sort=None)
-        with tm.assert_produces_warning(RuntimeWarning):
-            result = idx.union(idx[:1])
-
-        tm.assert_index_equal(result, idx)
-
-        # sort=None
-        with tm.assert_produces_warning(RuntimeWarning):
-            result = idx.union(idx[:1], sort=None)
-        tm.assert_index_equal(result, idx)
-
-        # sort=False
-        result = idx.union(idx[:1], sort=False)
-        tm.assert_index_equal(result, idx)
-
-    def test_union_sort_other_incomparable_true(self):
-        idx = Index([1, pd.Timestamp("2000")])
-        with pytest.raises(TypeError, match=".*"):
-            idx.union(idx[:1], sort=True)
-
-    def test_intersection_equal_sort_true(self):
-        idx = Index(["c", "a", "b"])
-        sorted_ = Index(["a", "b", "c"])
-        tm.assert_index_equal(idx.intersection(idx, sort=True), sorted_)
-
-    def test_intersection_base(self, sort):
-        # (same results for py2 and py3 but sortedness not tested elsewhere)
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[:5]
-        second = index[:3]
-
-        expected = Index([0, 1, "a"]) if sort is None else Index([0, "a", 1])
-        result = first.intersection(second, sort=sort)
-        tm.assert_index_equal(result, expected)
-
-    @pytest.mark.parametrize("klass", [np.array, Series, list])
-    def test_intersection_different_type_base(self, klass, sort):
-        # GH 10149
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[:5]
-        second = index[:3]
-
-        result = first.intersection(klass(second.values), sort=sort)
-        assert tm.equalContents(result, second)
-
-    def test_intersection_nosort(self):
-        result = Index(["c", "b", "a"]).intersection(["b", "a"])
-        expected = Index(["b", "a"])
-        tm.assert_index_equal(result, expected)
-
-    def test_intersection_equal_sort(self):
-        idx = Index(["c", "a", "b"])
-        tm.assert_index_equal(idx.intersection(idx, sort=False), idx)
-        tm.assert_index_equal(idx.intersection(idx, sort=None), idx)
-
-    def test_intersection_str_dates(self, sort):
-        dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
-
-        i1 = Index(dt_dates, dtype=object)
-        i2 = Index(["aa"], dtype=object)
-        result = i2.intersection(i1, sort=sort)
-
-        assert len(result) == 0
-
-    @pytest.mark.parametrize(
-        "index2,expected_arr",
-        [(Index(["B", "D"]), ["B"]), (Index(["B", "D", "A"]), ["A", "B"])],
-    )
-    def test_intersection_non_monotonic_non_unique(self, index2, expected_arr, sort):
-        # non-monotonic non-unique
-        index1 = Index(["A", "B", "A", "C"])
-        expected = Index(expected_arr, dtype="object")
-        result = index1.intersection(index2, sort=sort)
-        if sort is None:
-            expected = expected.sort_values()
-        tm.assert_index_equal(result, expected)
-
-    def test_difference_base(self, sort):
-        # (same results for py2 and py3 but sortedness not tested elsewhere)
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[:4]
-        second = index[3:]
-
-        result = first.difference(second, sort)
-        expected = Index([0, "a", 1])
-        if sort is None:
-            expected = Index(safe_sort(expected))
-        tm.assert_index_equal(result, expected)
-
-    def test_symmetric_difference(self):
-        # (same results for py2 and py3 but sortedness not tested elsewhere)
-        index = Index([0, "a", 1, "b", 2, "c"])
-        first = index[:4]
-        second = index[3:]
-
-        result = first.symmetric_difference(second)
-        expected = Index([0, 1, 2, "a", "c"])
-        tm.assert_index_equal(result, expected)
-
-    @pytest.mark.parametrize(
-        "method,expected,sort",
-        [
-            (
-                "intersection",
-                np.array(
-                    [(1, "A"), (2, "A"), (1, "B"), (2, "B")],
-                    dtype=[("num", int), ("let", "S1")],
-                ),
-                False,
-            ),
-            (
-                "intersection",
-                np.array(
-                    [(1, "A"), (1, "B"), (2, "A"), (2, "B")],
-                    dtype=[("num", int), ("let", "S1")],
-                ),
-                None,
-            ),
-            (
-                "union",
-                np.array(
-                    [(1, "A"), (1, "B"), (1, "C"), (2, "A"), (2, "B"), (2, "C")],
-                    dtype=[("num", int), ("let", "S1")],
-                ),
-                None,
-            ),
-        ],
-    )
-    def test_tuple_union_bug(self, method, expected, sort):
-        index1 = Index(
-            np.array(
-                [(1, "A"), (2, "A"), (1, "B"), (2, "B")],
-                dtype=[("num", int), ("let", "S1")],
-            )
-        )
-        index2 = Index(
-            np.array(
-                [(1, "A"), (2, "A"), (1, "B"), (2, "B"), (1, "C"), (2, "C")],
-                dtype=[("num", int), ("let", "S1")],
-            )
-        )
-
-        result = getattr(index1, method)(index2, sort=sort)
-        assert result.ndim == 1
-
-        expected = Index(expected)
-        tm.assert_index_equal(result, expected)
-
-    @pytest.mark.parametrize("first_list", [["b", "a"], []])
-    @pytest.mark.parametrize("second_list", [["a", "b"], []])
-    @pytest.mark.parametrize(
-        "first_name, second_name, expected_name",
-        [("A", "B", None), (None, "B", None), ("A", None, None)],
-    )
-    def test_union_name_preservation(
-        self, first_list, second_list, first_name, second_name, expected_name, sort
-    ):
-        first = Index(first_list, name=first_name)
-        second = Index(second_list, name=second_name)
-        union = first.union(second, sort=sort)
-
-        vals = set(first_list).union(second_list)
-
-        if sort is None and len(first_list) > 0 and len(second_list) > 0:
-            expected = Index(sorted(vals), name=expected_name)
-            tm.assert_index_equal(union, expected)
-        else:
-            expected = Index(vals, name=expected_name)
-            tm.equalContents(union, expected)
-
-    @pytest.mark.parametrize(
-        "diff_type, expected",
-        [["difference", [1, "B"]], ["symmetric_difference", [1, 2, "B", "C"]]],
-    )
-    def test_difference_object_type(self, diff_type, expected):
-        # GH 13432
-        idx1 = Index([0, 1, "A", "B"])
-        idx2 = Index([0, 2, "A", "C"])
-        result = getattr(idx1, diff_type)(idx2)
-        expected = Index(expected)
-        tm.assert_index_equal(result, expected)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/resolvelib/__init__.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/resolvelib/__init__.py
deleted file mode 100644
index ce05fd3027447fdc64986ecdee950643822e45e6..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/resolvelib/__init__.py
+++ /dev/null
@@ -1,26 +0,0 @@
-__all__ = [
-    "__version__",
-    "AbstractProvider",
-    "AbstractResolver",
-    "BaseReporter",
-    "InconsistentCandidate",
-    "Resolver",
-    "RequirementsConflicted",
-    "ResolutionError",
-    "ResolutionImpossible",
-    "ResolutionTooDeep",
-]
-
-__version__ = "0.8.1"
-
-
-from .providers import AbstractProvider, AbstractResolver
-from .reporters import BaseReporter
-from .resolvers import (
-    InconsistentCandidate,
-    RequirementsConflicted,
-    ResolutionError,
-    ResolutionImpossible,
-    ResolutionTooDeep,
-    Resolver,
-)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/_wrap.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/_wrap.py
deleted file mode 100644
index b537757a573be8777c45b0b265a13a15d90bdf29..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/_wrap.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import re
-from typing import Iterable, List, Tuple
-
-from .cells import cell_len, chop_cells
-from ._loop import loop_last
-
-re_word = re.compile(r"\s*\S+\s*")
-
-
-def words(text: str) -> Iterable[Tuple[int, int, str]]:
-    position = 0
-    word_match = re_word.match(text, position)
-    while word_match is not None:
-        start, end = word_match.span()
-        word = word_match.group(0)
-        yield start, end, word
-        word_match = re_word.match(text, end)
-
-
-def divide_line(text: str, width: int, fold: bool = True) -> List[int]:
-    divides: List[int] = []
-    append = divides.append
-    line_position = 0
-    _cell_len = cell_len
-    for start, _end, word in words(text):
-        word_length = _cell_len(word.rstrip())
-        if line_position + word_length > width:
-            if word_length > width:
-                if fold:
-                    for last, line in loop_last(
-                        chop_cells(word, width, position=line_position)
-                    ):
-                        if last:
-                            line_position = _cell_len(line)
-                        else:
-                            start += len(line)
-                            append(start)
-                else:
-                    if start:
-                        append(start)
-                    line_position = _cell_len(word)
-            elif line_position and start:
-                append(start)
-                line_position = _cell_len(word)
-        else:
-            line_position += _cell_len(word)
-    return divides
-
-
-if __name__ == "__main__":  # pragma: no cover
-    from .console import Console
-
-    console = Console(width=10)
-    console.print("12345 abcdefghijklmnopqrstuvwyxzABCDEFGHIJKLMNOPQRSTUVWXYZ 12345")
-    print(chop_cells("abcdefghijklmnopqrstuvwxyz", 10, position=2))
diff --git a/spaces/pycoming/bingo/src/components/button-scroll-to-bottom.tsx b/spaces/pycoming/bingo/src/components/button-scroll-to-bottom.tsx
deleted file mode 100644
index b68ab9c0e48320c356e51a52d11b9ca63909e6c5..0000000000000000000000000000000000000000
--- a/spaces/pycoming/bingo/src/components/button-scroll-to-bottom.tsx
+++ /dev/null
@@ -1,34 +0,0 @@
-'use client'
-
-import * as React from 'react'
-
-import { cn } from '@/lib/utils'
-import { useAtBottom } from '@/lib/hooks/use-at-bottom'
-import { Button, type ButtonProps } from '@/components/ui/button'
-import { IconArrowDown } from '@/components/ui/icons'
-
-export function ButtonScrollToBottom({ className, ...props }: ButtonProps) {
-  const isAtBottom = useAtBottom()
-
-  return (
-    <Button
-      variant="outline"
-      size="icon"
-      className={cn(
-        'fixed right-4 bottom-24 z-50 bg-background transition-opacity duration-300 sm:right-20',
-        isAtBottom ? 'opacity-0' : 'opacity-100',
-        className
-      )}
-      onClick={() =>
-        window.scrollTo({
-          top: document.body.offsetHeight,
-          behavior: 'smooth'
-        })
-      }
-      {...props}
-    >
-      <IconArrowDown />
-      <span className="sr-only">Scroll to bottom</span>
-    </Button>
-  )
-}
diff --git a/spaces/pyodide-demo/self-hosted/mne.js b/spaces/pyodide-demo/self-hosted/mne.js
deleted file mode 100644
index 9ca591353c84be523d71f1c50f4eee9aeb5df08a..0000000000000000000000000000000000000000
--- a/spaces/pyodide-demo/self-hosted/mne.js
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/spaces/pythainlp/pythainlp/README.md b/spaces/pythainlp/pythainlp/README.md
deleted file mode 100644
index 5607fee3b0a6df0295399a9fe4afbdaddc824d48..0000000000000000000000000000000000000000
--- a/spaces/pythainlp/pythainlp/README.md
+++ /dev/null
@@ -1,23 +0,0 @@
----
-title: Pythainlp
-emoji: 😻
-colorFrom: gray
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-# PyThaiNLP Demo
-
-This demo will online at [https://huggingface.co/spaces/pythainlp/pythainlp](https://huggingface.co/spaces/pythainlp/pythainlp). You can fork and send your pull request to the project.
-
-Running: streamlit run app.py
-
-
-
-We build Thai NLP.
-
-PyThaiNLP
\ No newline at end of file
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-<p>Have you ever encountered an error message like this when trying to play a video game on your PC?</p>
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-<code>The program can't start because binkw32.dll is missing from your computer. Try reinstalling the program to fix this problem.</code>
-<p>Or this one?</p>
-<code>The procedure entry point _BinkSetVolume@12 could not be located in the dynamic link library binkw32.dll.</code>
-<p>If you have, then you are not alone. Many PC gamers have faced this frustrating error that prevents them from enjoying their favorite games. But don't worry, there is a way to fix it.</p>
-<p>In this article, we will explain what is binksetvolume@12 binkw32.dll download free error and why it occurs, what are the consequences of this error and how to prevent it, and most importantly, how to fix it with three easy solutions. So, let's get started.</p>
- <h2>Causes of Binksetvolume@12 Binkw32.dll Download Free Error</h2>
-<p>Before we dive into the solutions, let's first understand what causes this error in the first place. The main culprit behind this error is a file called binkw32.dll. This file is a dynamic link library (DLL) file that belongs to the Bink Video codec developed by RAD Game Tools, Inc. The Bink Video codec is a video compression and playback technology that is widely used in video game development to implement audio and video features such as adjusting the volume of sound effects and music, playing cutscenes and cinematics, etc.</p>
-<p>The binkw32.dll file contains various functions that are used by the Bink Video codec and the games that use it. One of these functions is called _BinkSetVolume@12, which allows the game application to adjust the volume of the audio stream during playback. The "@12" in the name refers to the function's calling convention, indicating that it uses the __stdcall calling convention and requires 12 bytes of stack space to be cleared by the caller before the function is called.</p>
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-<p>Now, when an application that uses the Bink Video codec encounters a Bink-encoded video file, it loads the binkw32.dll library to access its functions. However, sometimes, due to various reasons, the binkw32.dll file may be missing or corrupted on your PC, or may be outdated or incompatible with your game application. This can result in the binksetvolume@12 binkw32.dll download free error, which means that either the application cannot find or load the binkw32.dll file, or cannot locate or execute the _BinkSetVolume@12 function within it.</p>
-<p>Some of the common reasons why this may happen are:</p>
-<ul>
-<li>Missing or corrupted binkw32.dll file: This can happen if you accidentally delete or overwrite the binkw32.dll file on your PC, or if it gets damaged by malicious software such as viruses or malware.</li>
-<li>Outdated or incompatible Bink Video codec or game application: This can happen if you have an older version of the Bink Video codec or game application that does not match with the latest version of the binkw32.dll file on your PC, or vice versa.</li>
-<li>Registry issues or malware infection: This can happen if your Windows registry has invalid or corrupted entries related to the binkw32.dll file or its location on your PC, or if your PC is infected by malware that modifies or blocks access to the binkw32.dll file.</li>
-</ul>
-<p>These reasons can cause various problems for your PC and your gaming experience, such as:</p>
-<ul>
-<li>Unable to launch or play certain games that use the Bink Video codec</li>
-<li>Poor audio quality or no sound at all during gameplay</li>
-<li>Slow performance or frequent crashes of your PC or game application</li>
-<li>Potential security risks for your PC and personal data</li>
-</ul>
-<p>Therefore, it is important to fix this error as soon as possible. Fortunately, there are some simple and effective solutions that you can try.</p>
- <h2>Solutions for Binksetvolume@12 Binkw32.dll Download Free Error</h2>
-<p>Here are three solutions that can help you fix this error and enjoy your games without any hassle. You can try them one by one until you find the one that works for you.</p>
- <h3>Solution 1: Download and install binkw32.dll file from a reliable source</h3>
-<p>The first solution is to download and install a new copy of the binkw32.dll file from a reliable source on your PC. This can help you replace a missing or corrupted binkw32.dll file with a fresh and intact one. However, you need to be careful when downloading DLL files from online sources, as some of them may be infected with malware or contain malicious code that can harm your PC. Therefore, we recommend using a trusted website such as <a href="https://www.dllme.com/dll/files/binksetvolume_12">DLLme.com</a>, which offers free and safe downloads of various DLL files.</p>
-<p>To download and install binkw32.dll file from DLLme.com, follow these steps:</p>
-<ol>
-<li>Go to <a href="https://www.dllme.com/dll/files/binksetvolume_12">https://www.dllme.com/dll/files/binksetvolume_12</a> on your web browser.</li>
-<li>Select the version or variant of binkw32.dll file that matches your Windows system architecture (32-bit or 64-bit) and language (U.S. English).</li>
-<li>Click on Download button and save the ZIP file on your PC.</li>
-<li>Extract the ZIP file using a tool such as WinRAR or 7-Zip.</li>
-<li>Copy the extracted binkw32.dll file and paste it in either one of these locations: <ul><li>C:\Windows\System (Windows 95/98/Me)</li><li>C:\Windows\System32 (Windows XP/Vista/7/8/10)</li><li>C:\Windows\SysWOW64 (Windows XP/Vista/7/8/10)</li><li>The installation folder of your game application (e.g., C:\Program Files\Game Name)</li></ul></li>
-<li>If prompted for administrator permission or confirmation, click on Yes or OK.</li>
-<li>If you pasted the file in Windows system folder (System/System32/SysWOW64), you need to register it in Windows registry. To do this: <li>Type regsvr32 binkw32.dll in Command Prompt window and press Enter key.</li><li>You should see a message saying "DllRegisterServer in binkw32.dll succeeded."</li></ul></li>
-<li>Restart your PC and try to launch or play your game again.</li>
-</ol>
-<p>This solution should fix the error if it was caused by a missing or corrupted binkw32.dll file. However, if the error persists, you may need to try the next solution.</p>
- <h3>Solution 2: Update or reinstall the Bink Video codec or game application</h3>
-<p>The second solution is to update or reinstall the Bink Video codec or game application on your PC. This can help you resolve any compatibility issues or conflicts between the binkw32.dll file and your game application. Sometimes, an older version of the Bink Video codec or game application may not work well with a newer version of the binkw32.dll file, or vice versa. Therefore, it is important to keep both of them updated to the latest version available.</p>
-<p>To update or reinstall the Bink Video codec, follow these steps:</p>
-<ol>
-<li>Go to <a href="https://www.radgametools.com/bnkdown.htm">https://www.radgametools.com/bnkdown.htm</a> on your web browser.</li>
-<li>Click on Download button and save the EXE file on your PC.</li>
-<li>Run the EXE file and follow the instructions to install the Bink Video codec on your PC.</li>
-<li>Restart your PC and try to launch or play your game again.</li>
-</ol>
-<p>To update or reinstall your game application, follow these steps:</p>
-<ol>
-<li>Visit the game designer's website and download the latest service pack, patch, or another update for your particular game. In many cases, even with some instances of the "procedure entry point _BinkSetVolume@12" and related errors, the binkw32.dll error may have been corrected in a game update.</li>
-<li>Run the downloaded file and follow the instructions to install the update on your PC.</li>
-<li>If there is no update available for your game, or if the update does not fix the error, you may need to reinstall your game application from scratch. To do this: <ul><li>Uninstall your game application from Control Panel > Programs and Features (Windows Vista/7/8/10) or Add/Remove Programs (Windows XP).</li><li>Delete any leftover files or folders related to your game application from your PC.</li><li>Reinstall your game application from the original installation media (CD/DVD) or from a digital download source (Steam/Origin/GOG/etc.).</li><li>Apply any updates or patches for your game application as mentioned above.</li></ul></li>
-<li>Restart your PC and try to launch or play your game again.</li>
-</ol>
-<p>This solution should fix the error if it was caused by an outdated or incompatible Bink Video codec or game application. However, if the error still occurs, you may need to try the final solution.</p>
- <h3>Solution 3: Clean your PC registry and optimize your computer</h3>
-<p>The third solution is to clean your PC registry and optimize your computer using a reputable software tool. This can help you fix any registry issues or malware infection that may be affecting the binkw32.dll file or its location on your PC. The Windows registry is a database that stores various settings and information for your Windows system and applications. However, over time, it can get cluttered with invalid or corrupted entries that can cause various errors and problems for your PC. Similarly, malware infection can modify or block access to certain files or folders on your PC, including the binkw32.dll file.</p>
-<p>To clean your PC registry and optimize your computer, we recommend using a reliable software tool such as <a href="https://www.iolo.com/downloads/download-system-mechanic/">System Mechanic</a>, which offers free and safe downloads of various system optimization features. System Mechanic can scan and repair any registry errors, remove any junk files, boost your PC speed and performance, protect your PC from malware threats, and more.</p>
-<p>To use System Mechanic to fix binksetvolume@12 binkw32.dll download free error, follow these steps:</p>
-<ol>
-<li>Go to <a href="https://www.iolo.com/downloads/download-system-mechanic/">https://www.iolo.com/downloads/download-system-mechanic/</a> on your web browser.</li>
-<li>Click on Download button and save the EXE file on your PC.</li>
-<li>Run the EXE file and follow the instructions to install System Mechanic on your PC.</li>
-<li>Launch System Mechanic and click on Scan Now button to start scanning your PC for any issues.</li>
-<li>Wait for System Mechanic to complete the scan and display the results.</li>
-<li>Click on Repair All button to fix all the issues found by System Mechanic.</li>
-<li>Restart your PC and try to launch or play your game again.</li>
-</ol>
-<p>This solution should fix the error if it was caused by any registry issues or malware infection. By using System Mechanic regularly, you can also keep your PC in optimal condition and prevent any future errors or problems.</p>
- <h2>Conclusion</h2>
-<p>In this article, we have explained what is binksetvolume@12 binkw32.dll download free error and why it occurs, what are the consequences of this error and how to prevent it, and how to fix it with three easy solutions. We hope that this article has helped you resolve this error and enjoy your games without any hassle. If you have any questions or feedback, please feel free to leave a comment below. We would love to hear from you.</p>
- <h2>FAQs</h2>
-<p>Here are some frequently asked questions about binksetvolume@12 binkw32.dll download free error:</p>
- <h4>What is binkw32.dll file and what does it do?</h4>
-<p>Binkw32.dll is a dynamic link library (DLL) file that belongs to the Bink Video codec developed by RAD Game Tools, Inc. The Bink Video codec is a video compression and playback technology that is widely used in video game development to implement audio and video features such as adjusting the volume of sound effects and music, playing cutscenes and cinematics, etc. The binkw32.dll file contains various functions that are used by the Bink Video codec and the games that use it.</p>
- <h4>What is Bink Video codec and what games use it?</h4>
-the volume of sound effects and music, playing cutscenes and cinematics, etc. It was developed by RAD Game Tools, Inc. and is one of the most popular video codecs in the gaming industry. Some of the games that use Bink Video codec are:</p>
-<ul>
-<li>Assassin's Creed series</li>
-<li>BioShock series</li>
-<li>Borderlands series</li>
-<li>Call of Duty series</li>
-<li>Diablo III</li>
-<li>Elder Scrolls series</li>
-<li>Fallout series</li>
-<li>Grand Theft Auto series</li>
-<li>Hitman series</li>
-<li>Mafia series</li>
-<li>Mass Effect series</li>
-<li>Mortal Kombat series</li>
-<li>Need for Speed series</li>
-<li>Resident Evil series</li>
-<li>Saints Row series</li>
-<li>Star Wars series</li>
-<li>The Sims series</li>
-<li>Tomb Raider series</li>
-<li>World of Warcraft</li>
-<li>And many more...</li>
-</ul>
- <h4>What is binksetvolume@12 function and what does it do?</h4>
-<p>Binksetvolume@12 is a function that is contained in the binkw32.dll file and is used by the Bink Video codec and the games that use it. It allows the game application to adjust the volume of the audio stream during playback. The "@12" in the name refers to the function's calling convention, indicating that it uses the __stdcall calling convention and requires 12 bytes of stack space to be cleared by the caller before the function is called.</p>
- <h4>How can I avoid binksetvolume@12 binkw32.dll download free error in the future?</h4>
-<p>To avoid this error in the future, you should follow these tips:</p>
-<ul>
-<li>Keep your binkw32.dll file updated and intact on your PC.</li>
-<li>Keep your Bink Video codec and game application updated to the latest version available.</li>
-<li>Clean your PC registry and optimize your computer regularly using a reputable software tool such as System Mechanic.</li>
-<li>Scan your PC for any malware threats and remove them using a reliable antivirus software.</li>
-<li>Avoid downloading DLL files from untrusted or unknown sources.</li>
-</ul>
- <h4>What if none of the solutions work for me?</h4>
-<p>If none of the solutions work for you, you may need to contact the game developer or publisher for further assistance. They may have more specific or advanced solutions for your particular game or system. You can also try to search for more information or solutions online using forums, blogs, or social media platforms where other gamers may have encountered and solved similar issues.</p>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/raedeXanto/academic-chatgpt-beta/ECM2001 6 2 Torrent What You Need to Know Before Downloading and Installing ECM2001.md b/spaces/raedeXanto/academic-chatgpt-beta/ECM2001 6 2 Torrent What You Need to Know Before Downloading and Installing ECM2001.md
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--- a/spaces/raedeXanto/academic-chatgpt-beta/ECM2001 6 2 Torrent What You Need to Know Before Downloading and Installing ECM2001.md	
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- <p>The next step is to run the key generator and generate a serial number for ECM2001. To do this, open the <strong>KeyGen</strong> folder and double-click on the file named <strong>Kg.exe</strong>. A window will pop up with a button that says <strong>Generate Serial Number</strong>. Click on this button and wait for a few seconds until a random serial number appears in the box below.</p>
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-<li><strong>WiFi</strong>: This is another wireless communication protocol that uses radio waves to transmit data between the ECU and the computer. It is usually found in some advanced cars that have OBD-II ports.</li>
-</ul>
- <p>You can buy these cables or devices from online stores or local shops that sell car tuning accessories. You should make sure that they are compatible with your car's ECU model and ECM2001 software.</p>
- <h3>Step 3: Open ECM2001 and select the driver for your car's ECU model</h3>
- <p>After connecting your car's ECU to your computer, you can open ECM2001 and select the driver for your car's ECU model. A driver is a file that contains the information and parameters of a specific ECU model. ECM2001 comes with over <strong>9,700 drivers</strong> for different ECU models from various car manufacturers.</p>
- <p>To select the driver for your car's ECU model, you need to click on the <strong>File</strong> menu and then click on <strong>Select Driver</strong>. A window will pop up with a list of drivers organized by categories. You can browse through the categories and subcategories until you find the driver that matches your car's ECU model. You can also use the search function to find the driver by typing its name or code.</p>
- <p>Once you have found the driver for your car's ECU model, you need to click on it and then click on <strong>OK</strong>. The driver will be loaded into ECM2001 and you will see its name and code on the top left corner of the screen.</p>
- <h3>Step 4: Read the original map from your ECU and save it as a backup</h3>
- <p>The next step is to read the original map from your ECU and save it as a backup. A map is a file that contains the data and settings of your ECU. By reading and saving the original map, you can restore it later if something goes wrong or if you want to revert back to the factory settings.</p>
- <p>To read and save the original map from your ECU, you need to click on the <strong>ECU</strong> menu and then click on <strong>Read Original File</strong>. A window will pop up with some options and instructions. You need to follow them carefully and wait for ECM2001 to communicate with your ECU and read its map. This may take a few minutes depending on the size and complexity of your map.</p>
- <p>When ECM2001 has finished reading your map, it will ask you to save it as a backup. You should choose a name and location for your backup file and click on <strong>Save</strong>. The backup file will be saved in a <strong>BIN</strong> format, which is compatible with ECM2001 and other ECU tuning software.</p>
- <h3>Step 5: Modify the map using ECM2001's features and tools</h3>
- <p>The most exciting step is to modify the map using ECM2001's features and tools. ECM2001 offers a variety of features and tools that allow you to change different parameters and maps of your ECU. Some of these features and tools are:</p>
- <ul>
-<li><strong>Data Editor</strong>: This feature allows you to view and edit the numerical values of your map in a table format. You can change the values by typing them manually or by using sliders, buttons or arrows. You can also copy, paste, cut, undo, redo, search, replace, import or export values.</li>
-<li><strong>2D Graph Editor</strong>: This feature allows you to view and edit the graphical representation of your map in a 2D format. You can change the values by dragging them with your mouse or by using sliders, buttons or arrows. You can also zoom in, zoom out, pan, rotate, flip, invert or smooth values.</li>
-<li><strong>3D Graph Editor</strong>: This feature allows you to view and edit the graphical representation of your map in a 3D format. You can change the values by dragging them with your mouse or by using sliders, buttons or arrows. You can also zoom in, zoom out, pan, rotate, tilt, flip, invert or smooth values.</li>
-<li><strong>Hex Editor</strong>: This feature allows you to view and edit the hexadecimal code of your map in a text format. You can change the values by typing them manually or by using buttons or arrows. You can also copy, paste, cut, undo, redo, search, replace, import or export values.</li>
-the checksum of your map. A checksum is a value that verifies the integrity and validity of your map. If you modify your map, you need to recalculate and correct the checksum before writing it back to your ECU. Otherwise, your ECU may not accept or recognize your map.</li>
-<li><strong>Map Manager</strong>: This feature allows you to manage and organize your maps in a folder structure. You can create, rename, delete, move or copy folders and files. You can also compare, merge, split or join maps.</li>
-<li><strong>Driver Manager</strong>: This feature allows you to manage and organize your drivers in a folder structure. You can create, rename, delete, move or copy folders and files. You can also import or export drivers.</li>
-<li><strong>Map Analyzer</strong>: This feature allows you to analyze and compare different maps in terms of performance, fuel consumption, emissions, etc. You can also generate reports and graphs based on the analysis.</li>
-<li><strong>Map Finder</strong>: This feature allows you to find and identify maps in your ECU's memory. You can also extract or insert maps from or to your ECU's memory.</li>
-<li><strong>Map Switcher</strong>: This feature allows you to switch between different maps in your ECU's memory. You can also create or delete switches.</li>
-<li><strong>Map Protector</strong>: This feature allows you to protect your maps from being read or modified by other users or software. You can also unprotect or decrypt protected maps.</li>
-<li><strong>Map Converter</strong>: This feature allows you to convert your maps from one format to another. You can also convert your maps from one driver to another.</li>
-</ul>
- <p>To modify the map using ECM2001's features and tools, you need to click on the <strong>ECU</strong> menu and then click on <strong>Open Original File</strong>. A window will pop up with a list of files that you have saved on your computer. You need to select the backup file that you created earlier and click on <strong>Open</strong>. The file will be opened in ECM2001 and you will see its data and graphs on the screen.</p>
- <p>You can then use any of the features and tools that we mentioned above to change the parameters and maps of your ECU according to your preferences and needs. You can also use the <strong>Help</strong> menu or press <strong>F1</strong> to access the user manual that explains how to use each feature and tool in detail.</p>
- <h3>Step 6: Write the modified map back to your ECU and enjoy the improved performance of your car</h3>
- <p>The final step is to write the modified map back to your ECU and enjoy the improved performance of your car. To do this, you need to click on the <strong>ECU</strong> menu and then click on <strong>Write Modified File</strong>. A window will pop up with some options and instructions. You need to follow them carefully and wait for ECM2001 to communicate with your ECU and write its map. This may take a few minutes depending on the size and complexity of your map.</p>
- <p>When ECM2001 has finished writing your map, it will ask you to turn off and on your car's ignition. You should do this and then start your car's engine. You should notice some changes in the sound, speed, acceleration, responsiveness and other aspects of your car's engine. You should also check if there are any error codes or warning lights on your car's dashboard. If there are none, then congratulations! You have successfully modified your car's ECU using ecm2001 6 2 keygen torrent!</p>
- <h2>What are the benefits and risks of using ecm2001 6 2 keygen torrent</h2>
- <p>Using ecm2001 6 2 keygen torrent can have some benefits and risks that you should be aware of before using it. Here are some of them:</p>
- <h3>Benefits</h3>
- <ul>
-<li><strong>You can use ECM2001 for free</strong>: By using ecm2001 6 2 keygen torrent, you can avoid paying for a license or subscription fee for using ECM2001 legally and access its full features.</li>
-<li><strong>You can optimize your car's performance</strong>: By using ECM2001, you can modify your car's ECU parameters and maps according to your preferences and needs. You can increase the power, torque, fuel efficiency, responsiveness and other aspects of your car's engine.</li>
-<li><strong>You can learn more about car tuning</strong>: By using ECM2001, you can learn more about how car tuning works and how different parameters and maps affect your car's engine. You can also experiment with different settings and see how they change your car's performance.</li>
-your results and experiences with other car tuning enthusiasts online or offline.</li>
-</ul>
- <h3>Risks</h3>
- <ul>
-<li><strong>You may damage your ECU</strong>: By using ecm2001 6 2 keygen torrent, you may risk damaging your ECU if you modify it incorrectly or excessively. You may also risk damaging your ECU if you use a faulty or incompatible cable or device to connect it to your computer. If your ECU is damaged, you may need to replace it or repair it, which can be costly and time-consuming.</li>
-<li><strong>You may void your warranty</strong>: By using ecm2001 6 2 keygen torrent, you may void your car's warranty if it is still valid. Most car manufacturers do not allow or support modifying your car's ECU and may consider it as a breach of contract. If your car's warranty is voided, you may lose the benefits and services that it provides, such as free repairs or replacements.</li>
-<li><strong>You may face legal issues</strong>: By using ecm2001 6 2 keygen torrent, you may face legal issues if you violate the intellectual property rights of the developers of ECM2001 or the car manufacturers. You may also face legal issues if you violate the emission standards or safety regulations of your country or region. If you face legal issues, you may have to pay fines or penalties or face other consequences.</li>
-<li><strong>You may endanger yourself and others</strong>: By using ecm2001 6 2 keygen torrent, you may endanger yourself and others if you modify your car's ECU in a way that compromises its stability, reliability or safety. You may also endanger yourself and others if you drive your car recklessly or irresponsibly after modifying its ECU. If you endanger yourself and others, you may cause accidents, injuries or deaths.</li>
-</ul>
- <h2>Conclusion</h2>
- <p>In conclusion, ecm2001 6 2 keygen torrent is a file that contains a cracked version of ECM2001 along with a key generator that can produce a valid serial number for activating the software. ECM2001 is a software that allows you to modify the engine control unit (ECU) of your car by changing its parameters and maps. By doing so, you can optimize the performance of your car's engine.</p>
- <p>However, using ecm2001 6 2 keygen torrent also has some benefits and risks that you should be aware of before using it. Some of the benefits are that you can use ECM2001 for free, optimize your car's performance, learn more about car tuning and have fun. Some of the risks are that you may damage your ECU, void your warranty, face legal issues or endanger yourself and others.</p>
- <p>Therefore, we recommend that you use ecm2001 6 2 keygen torrent with caution and responsibility. You should also consult a professional car tuner or mechanic before modifying your car's ECU. You should also backup your original map and check for error codes or warning lights after modifying your map. You should also drive your car safely and legally after modifying its ECU.</p>
- <h2>FAQs</h2>
- <h3>Q1: What is the difference between ecm2001 and other ECU tuning software?</h3>
- <p>A1: ECM2001 is one of the most popular and widely used ECU tuning software in the market. It has some features and advantages that make it stand out from other software, such as:</p>
- <ul>
-<li>It supports over <strong>9,700 drivers</strong> for different ECU models from various car manufacturers.</li>
-<li>It offers a variety of features and tools that allow you to modify different parameters and maps of your ECU.</li>
-<li>It has a user-friendly interface and a comprehensive user manual that explain how to use each feature and tool in detail.</li>
-<li>It has a high compatibility and reliability with different cables and devices that connect ECUs to computers.</li>
-<li>It has a low price compared to other software that offer similar features and quality.</li>
-</ul>
- <h3>Q2: Is ecm2001 compatible with my car's ECU model?</h3>
- <p>A2: ECM2001 supports over <strong>9,700 drivers</strong> for different ECU models from various car manufacturers. However, it does not support all ECU models in the market. To check if ECM2001 supports your car's ECU model, you can do one of the following:</p>
- <ul>
-<li>You can look for your car's ECU model in the list of drivers that comes with ECM2001.</li>
-<li>You can visit the official website of ECM2001 and search for your car's ECU model in their database.</li>
-<li>You can contact the developers or other users of ECM2001 and ask them if they have tested or used ECM2001 with your car's ECU model.</li>
-</ul>
- <p>If ECM2001 does not support your car's ECU model, you can do one of the following:</p>
- <ul>
-<li>You can look for another ECU tuning software that supports your car's ECU model.</li>
-<li>You can look for a driver converter that can convert your car's ECU model to another one that is supported by ECM2001.</li>
-<li>You can request the developers or other users of ECM2001 to create or share a driver for your car's ECU model.</li>
-</ul>
- <h3>Q3: How can I update ecm2001 to the latest version?</h3>
- <p>A3: To update ecm2001 to the latest version, you can do one of the following:</p>
- <ul>
-the latest version of the software and install it on your computer.</li>
-<li>You can use the <strong>Update</strong> feature that is available in ECM2001. To do this, you need to click on the <strong>Help</strong> menu and then click on <strong>Update</strong>. A window will pop up with some options and instructions. You need to follow them and wait for ECM2001 to download and install the latest version of the software.</li>
-<li>You can contact the developers or other users of ECM2001 and ask them to send you the latest version of the software.</li>
-</ul>
- <h3>Q4: How can I get help or support for using ecm2001?</h3>
- <p>A4: To get help or support for using ecm2001, you can do one of the following:</p>
- <ul>
-<li>You can use the <strong>Help</strong> menu or press <strong>F1</strong> to access the user manual that explains how to use each feature and tool in detail.</li>
-<li>You can visit the official website of ECM2001 and access their online support center that offers FAQs, tutorials, videos, forums, etc.</li>
-<li>You can contact the developers or other users of ECM2001 by email, phone or social media and ask them for assistance or feedback.</li>
-</ul>
- <h3>Q5: Where can I find more information or resources about ecm2001?</h3>
- <p>A5: To find more information or resources about ecm2001, you can do one of the following:</p>
- <ul>
-<li>You can visit the official website of ECM2001 and access their online resource center that offers news, articles, blogs, reviews, testimonials, etc.</li>
-<li>You can visit other websites that offer information or resources about ecm2001, such as:</li>
-<ul>
-<li><a href="https://www.ecuconnections.com/forum/viewforum.php?f=2">https://www.ecuconnections.com/forum/viewforum.php?f=2</a></li>
-<li><a href="https://www.digital-kaos.co.uk/forums/forumdisplay.php/78-ECM-amp-Tuning-Systems">https://www.digital-kaos.co.uk/forums/forumdisplay.php/78-ECM-amp-Tuning-Systems</a></li>
-<li><a href="https://www.youtube.com/results?search_query=ecm2001">https://www.youtube.com/results?search_query=ecm2001</a></li>
-</ul>
-<li>You can join online or offline communities or groups that are related to ecm2001 or car tuning in general and share your experiences or learn from others.</li>
-</ul>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexs Adventures In Numberland Pdf Free 116.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexs Adventures In Numberland Pdf Free 116.md
deleted file mode 100644
index e0bb729c615f98948d0d9adec6d12df443f44ca3..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexs Adventures In Numberland Pdf Free 116.md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Download Firmware Zte Zxv10 W300 [UPDATED].md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Download Firmware Zte Zxv10 W300 [UPDATED].md
deleted file mode 100644
index cf90067abb5c96ff2a96459b47a6cd890c9132fe..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Download Firmware Zte Zxv10 W300 [UPDATED].md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Eagles Hell Freezes Over Torrent Download.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Eagles Hell Freezes Over Torrent Download.md
deleted file mode 100644
index 83a7802085b8817ac2a608aa33cad9ea9276b958..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Eagles Hell Freezes Over Torrent Download.md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Easycafe 2.2.14 Serial And Product Key.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Easycafe 2.2.14 Serial And Product Key.md
deleted file mode 100644
index 9f363f3e3f920c07c769551e98d599ad5976022a..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Easycafe 2.2.14 Serial And Product Key.md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/HD Online Player (Junoon Movie Hindi Dubbed !!TOP!! Download 7).md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/HD Online Player (Junoon Movie Hindi Dubbed !!TOP!! Download 7).md
deleted file mode 100644
index 6c98623597ed0c3f68a85fe6fb308b29c557f303..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/HD Online Player (Junoon Movie Hindi Dubbed !!TOP!! Download 7).md	
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-<h1>HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h1>
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-<p>Junoon movie Hindi dubbed is available online on various websites and platforms. However, not all of them offer good quality and speed. Some of them may also contain viruses or malware that can harm your device. That is why we recommend using an HD online player that can stream or download Junoon movie Hindi dubbed in HD quality without any hassle. An HD online player is a software or application that can play video files from various sources on your device. You can use it to watch Junoon movie Hindi dubbed online or offline, depending on your preference.</p>
-<h2>HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2><br /><p><b><b>DOWNLOAD</b> &#9675; <a href="https://urlgoal.com/2uCMkI">https://urlgoal.com/2uCMkI</a></b></p><br /><br />
-<h2>How to Use HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2>
-<p>Here are the steps to use an HD online player to stream or download Junoon movie Hindi dubbed in HD quality:</p>
-<ol>
-<li>Download and install an HD online player on your device. You can choose from various options, such as VLC Media Player, MX Player, KMPlayer, etc. Make sure you download it from a trusted source and follow the instructions to install it properly.</li>
-<li>Open the HD online player and click on the menu icon or the three dots on the top right corner. Then select Open Network Stream or Open URL or Open File from URL or something similar.</li>
-<li>Enter the URL of Junoon movie Hindi dubbed that you want to stream or download. You can find the URL from various websites that offer Junoon movie Hindi dubbed online, such as onlinemovieshindi.com, afilmywap.gold, makanty.net, toxtronyx.com, etc. Make sure you choose a reliable and safe website that offers good quality and speed.</li>
-<li>Click on Play or OK or Start or something similar to start streaming or downloading Junoon movie Hindi dubbed on your device. You can adjust the volume, brightness, subtitles, etc. according to your preference.</li>
-<li>If you want to stream Junoon movie Hindi dubbed online, you can watch it directly on your device without any interruption. However, you will need a stable internet connection and enough data or bandwidth to stream it smoothly.</li>
-<li>If you want to download Junoon movie Hindi dubbed offline, you can wait for the download to complete and then watch it anytime and anywhere on your device without any internet connection. However, you will need enough storage space and battery life to download it successfully.</li>
-<li>Enjoy watching Junoon movie Hindi dubbed in HD quality on your device using an HD online player.</li>
-</ol>
-
-<h2>Conclusion</h2>
-
-<p>We hope that this article has helped you learn how to use an HD online player to stream or download Junoon movie Hindi dubbed in HD quality in 7 easy steps. Junoon is a Bollywood war drama movie that was released in 1979 and has won several awards and accolades. You can watch it online or offline on your device using an HD online player that can play video files from various sources.</p>
-
-<p>If you have any questions or feedback about this article or Junoon movie Hindi dubbed, please feel free to leave a comment below. We would love to hear from you. And if you found this article useful, please share it with your friends and family who might be interested in watching Junoon movie Hindi dubbed in HD quality.</p>
-
-<p>Thank you for reading this article on HD Online Player (Junoon Movie Hindi Dubbed Download 7). We wish you all the best in your journey of watching movies online.</p>
-<h2>Features of HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2>
-<p>An HD online player is a software or application that can play video files from various sources on your device. It has many features that make it a great choice for streaming or downloading Junoon movie Hindi dubbed in HD quality. Some of these features are:</p>
-<ul>
-<li>It supports various video formats, such as MP4, AVI, MKV, MOV, etc. You can play any video file without worrying about compatibility issues.</li>
-<li>It offers high-quality video and audio output, such as HD, 4K, Dolby, etc. You can enjoy watching Junoon movie Hindi dubbed in HD quality with clear sound and picture.</li>
-<li>It has a user-friendly interface and easy-to-use controls. You can navigate through the menus and options easily and adjust the settings according to your preference.</li>
-<li>It has a fast and smooth performance and does not consume much battery or memory. You can stream or download Junoon movie Hindi dubbed in HD quality without any lag or interruption.</li>
-<li>It has a download manager and a resume function. You can pause and resume the download anytime and manage your downloaded files easily.</li>
-<li>It has a subtitle and language option. You can choose from various subtitles and languages for Junoon movie Hindi dubbed according to your preference.</li>
-<li>It has a security and privacy feature. You can protect your device from viruses and malware that may come from untrusted websites or sources.</li>
-</ul>
-
-<h2>Reviews of HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2>
-<p>Many people have used an HD online player to stream or download Junoon movie Hindi dubbed in HD quality and have shared their reviews and feedback online. Here are some of the reviews that we have found:</p>
-<blockquote>
-<p>"I love this HD online player. It is very easy to use and has great quality. I watched Junoon movie Hindi dubbed in HD quality and it was amazing. The story, the acting, the music, everything was superb. I recommend this HD online player to everyone who wants to watch Junoon movie Hindi dubbed in HD quality."</p>
-<cite>- Ayesha from Lahore</cite>
-</blockquote>
-<blockquote>
-<p>"This HD online player is awesome. It can play any video file from any source without any problem. I downloaded Junoon movie Hindi dubbed in HD quality from onlinemovieshindi.com and it was very fast and smooth. Junoon is one of my favorite movies of all time. It is a masterpiece of Bollywood cinema. I enjoyed watching it on this HD online player."</p>
-<p></p>
-<cite>- Ravi from Delhi</cite>
-</blockquote>
-<blockquote>
-<p>"This HD online player is the best thing ever. It has so many features and options that make it very convenient and enjoyable to use. I streamed Junoon movie Hindi dubbed in HD quality from afilmywap.gold and it was very clear and crisp. Junoon is a classic movie that depicts the history and culture of India during the 1857 War of Independence. It is a must-watch for everyone who loves movies."</p>
-<cite>- Zara from Karachi</cite>
-</blockquote>
-
-<h2>Conclusion</h2>
-
-<p>We hope that this article has helped you learn how to use an HD online player to stream or download Junoon movie Hindi dubbed in HD quality in 7 easy steps. Junoon is a Bollywood war drama movie that was released in 1979 and has won several awards and accolades. You can watch it online or offline on your device using an HD online player that can play video files from various sources.</p>
-
-<p>If you have any questions or feedback about this article or Junoon movie Hindi dubbed, please feel free to leave a comment below. We would love to hear from you. And if you found this article useful, please share it with your friends and family who might be interested in watching Junoon movie Hindi dubbed in HD quality.</p>
-
-<p>Thank you for reading this article on HD Online Player (Junoon Movie Hindi Dubbed Download 7). We wish you all the best in your journey of watching movies online.</p>
-<h2>Advantages of HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2>
-<p>Using an HD online player to stream or download Junoon movie Hindi dubbed in HD quality has many advantages over other methods. Some of these advantages are:</p>
-<ul>
-<li>You can watch Junoon movie Hindi dubbed in HD quality on any device, such as laptop, tablet, smartphone, etc. You don't need to buy or rent a DVD or Blu-ray disc or a TV set to watch it.</li>
-<li>You can watch Junoon movie Hindi dubbed in HD quality anytime and anywhere, as long as you have an internet connection and enough data or bandwidth. You don't have to wait for a specific time or place to watch it.</li>
-<li>You can watch Junoon movie Hindi dubbed in HD quality for free, without paying any subscription or registration fee. You don't have to sign up or log in to any website or platform to watch it.</li>
-<li>You can watch Junoon movie Hindi dubbed in HD quality with subtitles and languages of your choice. You don't have to rely on the audio or the dubbing quality of the original movie.</li>
-<li>You can watch Junoon movie Hindi dubbed in HD quality with your friends and family. You can share the link or the file with them and enjoy watching it together.</li>
-</ul>
-
-<h2>Alternatives of HD Online Player (Junoon Movie Hindi Dubbed Download 7)</h2>
-<p>If you are not satisfied with using an HD online player to stream or download Junoon movie Hindi dubbed in HD quality, you can try some alternatives that may suit your needs better. Some of these alternatives are:</p>
-<ul>
-<li>You can use a torrent client or a magnet link to download Junoon movie Hindi dubbed in HD quality from various torrent websites, such as 1337x, The Pirate Bay, YTS, etc. However, you will need a VPN service to access these websites safely and anonymously.</li>
-<li>You can use a video downloader or a browser extension to download Junoon movie Hindi dubbed in HD quality from various video hosting websites, such as YouTube, Dailymotion, Vimeo, etc. However, you will need to check the legality and the quality of the video before downloading it.</li>
-<li>You can use a streaming service or an app to watch Junoon movie Hindi dubbed in HD quality from various streaming platforms, such as Netflix, Amazon Prime Video, Hotstar, etc. However, you will need to pay a subscription or a rental fee to access these platforms.</li>
-<li>You can use a DVD or a Blu-ray player to watch Junoon movie Hindi dubbed in HD quality from a physical disc that you can buy or rent from various stores or online shops. However, you will need a compatible device and a disc drive to play the disc.</li>
-</ul>
-
-<h2>Conclusion</h2>
-
-<p>We hope that this article has helped you learn how to use an HD online player to stream or download Junoon movie Hindi dubbed in HD quality in 7 easy steps. Junoon is a Bollywood war drama movie that was released in 1979 and has won several awards and accolades. You can watch it online or offline on your device using an HD online player that can play video files from various sources.</p>
-
-<p>If you have any questions or feedback about this article or Junoon movie Hindi dubbed, please feel free to leave a comment below. We would love to hear from you. And if you found this article useful, please share it with your friends and family who might be interested in watching Junoon movie Hindi dubbed in HD quality.</p>
-
-<p>Thank you for reading this article on HD Online Player (Junoon Movie Hindi Dubbed Download 7). We wish you all the best in your journey of watching movies online.</p>
-<h2>Conclusion</h2>
-
-<p>We hope that this article has helped you learn how to use an HD online player to stream or download Junoon movie Hindi dubbed in HD quality in 7 easy steps. Junoon is a Bollywood war drama movie that was released in 1979 and has won several awards and accolades. You can watch it online or offline on your device using an HD online player that can play video files from various sources.</p>
-
-<p>If you have any questions or feedback about this article or Junoon movie Hindi dubbed, please feel free to leave a comment below. We would love to hear from you. And if you found this article useful, please share it with your friends and family who might be interested in watching Junoon movie Hindi dubbed in HD quality.</p>
-
-<p>Thank you for reading this article on HD Online Player (Junoon Movie Hindi Dubbed Download 7). We wish you all the best in your journey of watching movies online.</p> 3cee63e6c2<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/riccorl/relik-entity-linking/relik/retriever/pytorch_modules/scheduler.py b/spaces/riccorl/relik-entity-linking/relik/retriever/pytorch_modules/scheduler.py
deleted file mode 100644
index 5edd2433612b27c1a91fe189e57c4e2d41c462b2..0000000000000000000000000000000000000000
--- a/spaces/riccorl/relik-entity-linking/relik/retriever/pytorch_modules/scheduler.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import torch
-from torch.optim.lr_scheduler import LRScheduler
-
-
-class LinearSchedulerWithWarmup(LRScheduler):
-    def __init__(
-        self,
-        optimizer: torch.optim.Optimizer,
-        num_warmup_steps: int,
-        num_training_steps: int,
-        last_epoch: int = -1,
-        verbose: bool = False,
-        **kwargs,
-    ):
-        self.num_warmup_steps = num_warmup_steps
-        self.num_training_steps = num_training_steps
-        super().__init__(optimizer, last_epoch, verbose)
-
-    def get_lr(self):
-        def scheduler_fn(current_step):
-            if current_step < self.num_warmup_steps:
-                return current_step / max(1, self.num_warmup_steps)
-            return max(
-                0.0,
-                float(self.num_training_steps - current_step)
-                / float(max(1, self.num_training_steps - self.num_warmup_steps)),
-            )
-
-        return [base_lr * scheduler_fn(self.last_epoch) for base_lr in self.base_lrs]
-
-
-class LinearScheduler(LRScheduler):
-    def __init__(
-        self,
-        optimizer: torch.optim.Optimizer,
-        num_training_steps: int,
-        last_epoch: int = -1,
-        verbose: bool = False,
-        **kwargs,
-    ):
-        self.num_training_steps = num_training_steps
-        super().__init__(optimizer, last_epoch, verbose)
-
-    def get_lr(self):
-        def scheduler_fn(current_step):
-            # if current_step < self.num_warmup_steps:
-            #     return current_step / max(1, self.num_warmup_steps)
-            return max(
-                0.0,
-                float(self.num_training_steps - current_step)
-                / float(max(1, self.num_training_steps)),
-            )
-
-        return [base_lr * scheduler_fn(self.last_epoch) for base_lr in self.base_lrs]
diff --git a/spaces/riyueyiming/gpt/modules/chat_func.py b/spaces/riyueyiming/gpt/modules/chat_func.py
deleted file mode 100644
index 4c635c51ada4a852d1495646cf81120de15af7b9..0000000000000000000000000000000000000000
--- a/spaces/riyueyiming/gpt/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/robin0307/MMOCR/configs/_base_/default_runtime.py b/spaces/robin0307/MMOCR/configs/_base_/default_runtime.py
deleted file mode 100644
index de7f9650ce73ba7ca633652b50df021b67498362..0000000000000000000000000000000000000000
--- a/spaces/robin0307/MMOCR/configs/_base_/default_runtime.py
+++ /dev/null
@@ -1,17 +0,0 @@
-# yapf:disable
-log_config = dict(
-    interval=5,
-    hooks=[
-        dict(type='TextLoggerHook')
-    ])
-# yapf:enable
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-
-# disable opencv multithreading to avoid system being overloaded
-opencv_num_threads = 0
-# set multi-process start method as `fork` to speed up the training
-mp_start_method = 'fork'
diff --git a/spaces/robinhad/ukrainian-ai/README.md b/spaces/robinhad/ukrainian-ai/README.md
deleted file mode 100644
index 0c3b7c6342e687185a1946df76b52effc970334c..0000000000000000000000000000000000000000
--- a/spaces/robinhad/ukrainian-ai/README.md
+++ /dev/null
@@ -1,31 +0,0 @@
----
-title: "Ukrainian AI"
-emoji: 🇺🇦
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-sdk_version : 3.16
-python_version: 3.9
-app_file: app.py
-pinned: false
----
-
-# Ukrainian-speaking conversational AI
-This is a pet project with aim to provide an end-to-end voice chatbot with ability to listen, speak and make a conversation in Ukrainian.
-
-It's a project with an aim to demonstrate current state-of-the-art speech technologies for Ukrainian language.
-
-Link to speaking demo: [https://huggingface.co/spaces/robinhad/ukrainian-ai](https://huggingface.co/spaces/robinhad/ukrainian-ai)  
-Link to text demo: [https://huggingface.co/robinhad/gpt2-uk-conversational](https://huggingface.co/robinhad/gpt2-uk-conversational)
-# Technologies used:
-
-- [Wav2Vec2 XLS-R 300M fine-tuned to Ukrainian language](https://huggingface.co/robinhad/wav2vec2-xls-r-300m-uk) for speech recognition.
-- [Ukrainian VITS TTS](https://github.com/robinhad/ukrainian-tts) for text-to-speech generation.
-- Conversational pipeline (this repository)
-
-TODO: training scripts for conversational pipeline
-
-# How to setup:
-
-1. `pip install -r requirements.txt`
-2. `python app.py`
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/backbones/resnest.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/backbones/resnest.py
deleted file mode 100644
index 69629b96dfd44e4cbe53701fb14fb83fda4b6440..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/backbones/resnest.py
+++ /dev/null
@@ -1,322 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import math
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.utils.checkpoint as cp
-from mmcv.cnn import build_conv_layer, build_norm_layer
-from mmcv.runner import BaseModule
-
-from ..builder import BACKBONES
-from ..utils import ResLayer
-from .resnet import Bottleneck as _Bottleneck
-from .resnet import ResNetV1d
-
-
-class RSoftmax(nn.Module):
-    """Radix Softmax module in ``SplitAttentionConv2d``.
-
-    Args:
-        radix (int): Radix of input.
-        groups (int): Groups of input.
-    """
-
-    def __init__(self, radix, groups):
-        super().__init__()
-        self.radix = radix
-        self.groups = groups
-
-    def forward(self, x):
-        batch = x.size(0)
-        if self.radix > 1:
-            x = x.view(batch, self.groups, self.radix, -1).transpose(1, 2)
-            x = F.softmax(x, dim=1)
-            x = x.reshape(batch, -1)
-        else:
-            x = torch.sigmoid(x)
-        return x
-
-
-class SplitAttentionConv2d(BaseModule):
-    """Split-Attention Conv2d in ResNeSt.
-
-    Args:
-        in_channels (int): Number of channels in the input feature map.
-        channels (int): Number of intermediate channels.
-        kernel_size (int | tuple[int]): Size of the convolution kernel.
-        stride (int | tuple[int]): Stride of the convolution.
-        padding (int | tuple[int]): Zero-padding added to both sides of
-        dilation (int | tuple[int]): Spacing between kernel elements.
-        groups (int): Number of blocked connections from input channels to
-            output channels.
-        groups (int): Same as nn.Conv2d.
-        radix (int): Radix of SpltAtConv2d. Default: 2
-        reduction_factor (int): Reduction factor of inter_channels. Default: 4.
-        conv_cfg (dict): Config dict for convolution layer. Default: None,
-            which means using conv2d.
-        norm_cfg (dict): Config dict for normalization layer. Default: None.
-        dcn (dict): Config dict for DCN. Default: None.
-        init_cfg (dict or list[dict], optional): Initialization config dict.
-            Default: None
-    """
-
-    def __init__(self,
-                 in_channels,
-                 channels,
-                 kernel_size,
-                 stride=1,
-                 padding=0,
-                 dilation=1,
-                 groups=1,
-                 radix=2,
-                 reduction_factor=4,
-                 conv_cfg=None,
-                 norm_cfg=dict(type='BN'),
-                 dcn=None,
-                 init_cfg=None):
-        super(SplitAttentionConv2d, self).__init__(init_cfg)
-        inter_channels = max(in_channels * radix // reduction_factor, 32)
-        self.radix = radix
-        self.groups = groups
-        self.channels = channels
-        self.with_dcn = dcn is not None
-        self.dcn = dcn
-        fallback_on_stride = False
-        if self.with_dcn:
-            fallback_on_stride = self.dcn.pop('fallback_on_stride', False)
-        if self.with_dcn and not fallback_on_stride:
-            assert conv_cfg is None, 'conv_cfg must be None for DCN'
-            conv_cfg = dcn
-        self.conv = build_conv_layer(
-            conv_cfg,
-            in_channels,
-            channels * radix,
-            kernel_size,
-            stride=stride,
-            padding=padding,
-            dilation=dilation,
-            groups=groups * radix,
-            bias=False)
-        # To be consistent with original implementation, starting from 0
-        self.norm0_name, norm0 = build_norm_layer(
-            norm_cfg, channels * radix, postfix=0)
-        self.add_module(self.norm0_name, norm0)
-        self.relu = nn.ReLU(inplace=True)
-        self.fc1 = build_conv_layer(
-            None, channels, inter_channels, 1, groups=self.groups)
-        self.norm1_name, norm1 = build_norm_layer(
-            norm_cfg, inter_channels, postfix=1)
-        self.add_module(self.norm1_name, norm1)
-        self.fc2 = build_conv_layer(
-            None, inter_channels, channels * radix, 1, groups=self.groups)
-        self.rsoftmax = RSoftmax(radix, groups)
-
-    @property
-    def norm0(self):
-        """nn.Module: the normalization layer named "norm0" """
-        return getattr(self, self.norm0_name)
-
-    @property
-    def norm1(self):
-        """nn.Module: the normalization layer named "norm1" """
-        return getattr(self, self.norm1_name)
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm0(x)
-        x = self.relu(x)
-
-        batch, rchannel = x.shape[:2]
-        batch = x.size(0)
-        if self.radix > 1:
-            splits = x.view(batch, self.radix, -1, *x.shape[2:])
-            gap = splits.sum(dim=1)
-        else:
-            gap = x
-        gap = F.adaptive_avg_pool2d(gap, 1)
-        gap = self.fc1(gap)
-
-        gap = self.norm1(gap)
-        gap = self.relu(gap)
-
-        atten = self.fc2(gap)
-        atten = self.rsoftmax(atten).view(batch, -1, 1, 1)
-
-        if self.radix > 1:
-            attens = atten.view(batch, self.radix, -1, *atten.shape[2:])
-            out = torch.sum(attens * splits, dim=1)
-        else:
-            out = atten * x
-        return out.contiguous()
-
-
-class Bottleneck(_Bottleneck):
-    """Bottleneck block for ResNeSt.
-
-    Args:
-        inplane (int): Input planes of this block.
-        planes (int): Middle planes of this block.
-        groups (int): Groups of conv2.
-        base_width (int): Base of width in terms of base channels. Default: 4.
-        base_channels (int): Base of channels for calculating width.
-            Default: 64.
-        radix (int): Radix of SpltAtConv2d. Default: 2
-        reduction_factor (int): Reduction factor of inter_channels in
-            SplitAttentionConv2d. Default: 4.
-        avg_down_stride (bool): Whether to use average pool for stride in
-            Bottleneck. Default: True.
-        kwargs (dict): Key word arguments for base class.
-    """
-    expansion = 4
-
-    def __init__(self,
-                 inplanes,
-                 planes,
-                 groups=1,
-                 base_width=4,
-                 base_channels=64,
-                 radix=2,
-                 reduction_factor=4,
-                 avg_down_stride=True,
-                 **kwargs):
-        """Bottleneck block for ResNeSt."""
-        super(Bottleneck, self).__init__(inplanes, planes, **kwargs)
-
-        if groups == 1:
-            width = self.planes
-        else:
-            width = math.floor(self.planes *
-                               (base_width / base_channels)) * groups
-
-        self.avg_down_stride = avg_down_stride and self.conv2_stride > 1
-
-        self.norm1_name, norm1 = build_norm_layer(
-            self.norm_cfg, width, postfix=1)
-        self.norm3_name, norm3 = build_norm_layer(
-            self.norm_cfg, self.planes * self.expansion, postfix=3)
-
-        self.conv1 = build_conv_layer(
-            self.conv_cfg,
-            self.inplanes,
-            width,
-            kernel_size=1,
-            stride=self.conv1_stride,
-            bias=False)
-        self.add_module(self.norm1_name, norm1)
-        self.with_modulated_dcn = False
-        self.conv2 = SplitAttentionConv2d(
-            width,
-            width,
-            kernel_size=3,
-            stride=1 if self.avg_down_stride else self.conv2_stride,
-            padding=self.dilation,
-            dilation=self.dilation,
-            groups=groups,
-            radix=radix,
-            reduction_factor=reduction_factor,
-            conv_cfg=self.conv_cfg,
-            norm_cfg=self.norm_cfg,
-            dcn=self.dcn)
-        delattr(self, self.norm2_name)
-
-        if self.avg_down_stride:
-            self.avd_layer = nn.AvgPool2d(3, self.conv2_stride, padding=1)
-
-        self.conv3 = build_conv_layer(
-            self.conv_cfg,
-            width,
-            self.planes * self.expansion,
-            kernel_size=1,
-            bias=False)
-        self.add_module(self.norm3_name, norm3)
-
-    def forward(self, x):
-
-        def _inner_forward(x):
-            identity = x
-
-            out = self.conv1(x)
-            out = self.norm1(out)
-            out = self.relu(out)
-
-            if self.with_plugins:
-                out = self.forward_plugin(out, self.after_conv1_plugin_names)
-
-            out = self.conv2(out)
-
-            if self.avg_down_stride:
-                out = self.avd_layer(out)
-
-            if self.with_plugins:
-                out = self.forward_plugin(out, self.after_conv2_plugin_names)
-
-            out = self.conv3(out)
-            out = self.norm3(out)
-
-            if self.with_plugins:
-                out = self.forward_plugin(out, self.after_conv3_plugin_names)
-
-            if self.downsample is not None:
-                identity = self.downsample(x)
-
-            out += identity
-
-            return out
-
-        if self.with_cp and x.requires_grad:
-            out = cp.checkpoint(_inner_forward, x)
-        else:
-            out = _inner_forward(x)
-
-        out = self.relu(out)
-
-        return out
-
-
-@BACKBONES.register_module()
-class ResNeSt(ResNetV1d):
-    """ResNeSt backbone.
-
-    Args:
-        groups (int): Number of groups of Bottleneck. Default: 1
-        base_width (int): Base width of Bottleneck. Default: 4
-        radix (int): Radix of SplitAttentionConv2d. Default: 2
-        reduction_factor (int): Reduction factor of inter_channels in
-            SplitAttentionConv2d. Default: 4.
-        avg_down_stride (bool): Whether to use average pool for stride in
-            Bottleneck. Default: True.
-        kwargs (dict): Keyword arguments for ResNet.
-    """
-
-    arch_settings = {
-        50: (Bottleneck, (3, 4, 6, 3)),
-        101: (Bottleneck, (3, 4, 23, 3)),
-        152: (Bottleneck, (3, 8, 36, 3)),
-        200: (Bottleneck, (3, 24, 36, 3))
-    }
-
-    def __init__(self,
-                 groups=1,
-                 base_width=4,
-                 radix=2,
-                 reduction_factor=4,
-                 avg_down_stride=True,
-                 **kwargs):
-        self.groups = groups
-        self.base_width = base_width
-        self.radix = radix
-        self.reduction_factor = reduction_factor
-        self.avg_down_stride = avg_down_stride
-        super(ResNeSt, self).__init__(**kwargs)
-
-    def make_res_layer(self, **kwargs):
-        """Pack all blocks in a stage into a ``ResLayer``."""
-        return ResLayer(
-            groups=self.groups,
-            base_width=self.base_width,
-            base_channels=self.base_channels,
-            radix=self.radix,
-            reduction_factor=self.reduction_factor,
-            avg_down_stride=self.avg_down_stride,
-            **kwargs)
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/dense_heads/anchor_head.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/dense_heads/anchor_head.py
deleted file mode 100644
index d1bfab62de230feaccc83b935573b87d1d8061df..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/dense_heads/anchor_head.py
+++ /dev/null
@@ -1,542 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import warnings
-
-import torch
-import torch.nn as nn
-from mmcv.runner import force_fp32
-
-from mmdet.core import (anchor_inside_flags, build_assigner, build_bbox_coder,
-                        build_prior_generator, build_sampler, images_to_levels,
-                        multi_apply, unmap)
-from ..builder import HEADS, build_loss
-from .base_dense_head import BaseDenseHead
-from .dense_test_mixins import BBoxTestMixin
-
-
-@HEADS.register_module()
-class AnchorHead(BaseDenseHead, BBoxTestMixin):
-    """Anchor-based head (RPN, RetinaNet, SSD, etc.).
-
-    Args:
-        num_classes (int): Number of categories excluding the background
-            category.
-        in_channels (int): Number of channels in the input feature map.
-        feat_channels (int): Number of hidden channels. Used in child classes.
-        anchor_generator (dict): Config dict for anchor generator
-        bbox_coder (dict): Config of bounding box coder.
-        reg_decoded_bbox (bool): If true, the regression loss would be
-            applied directly on decoded bounding boxes, converting both
-            the predicted boxes and regression targets to absolute
-            coordinates format. Default False. It should be `True` when
-            using `IoULoss`, `GIoULoss`, or `DIoULoss` in the bbox head.
-        loss_cls (dict): Config of classification loss.
-        loss_bbox (dict): Config of localization loss.
-        train_cfg (dict): Training config of anchor head.
-        test_cfg (dict): Testing config of anchor head.
-        init_cfg (dict or list[dict], optional): Initialization config dict.
-    """  # noqa: W605
-
-    def __init__(self,
-                 num_classes,
-                 in_channels,
-                 feat_channels=256,
-                 anchor_generator=dict(
-                     type='AnchorGenerator',
-                     scales=[8, 16, 32],
-                     ratios=[0.5, 1.0, 2.0],
-                     strides=[4, 8, 16, 32, 64]),
-                 bbox_coder=dict(
-                     type='DeltaXYWHBBoxCoder',
-                     clip_border=True,
-                     target_means=(.0, .0, .0, .0),
-                     target_stds=(1.0, 1.0, 1.0, 1.0)),
-                 reg_decoded_bbox=False,
-                 loss_cls=dict(
-                     type='CrossEntropyLoss',
-                     use_sigmoid=True,
-                     loss_weight=1.0),
-                 loss_bbox=dict(
-                     type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0),
-                 train_cfg=None,
-                 test_cfg=None,
-                 init_cfg=dict(type='Normal', layer='Conv2d', std=0.01)):
-        super(AnchorHead, self).__init__(init_cfg)
-        self.in_channels = in_channels
-        self.num_classes = num_classes
-        self.feat_channels = feat_channels
-        self.use_sigmoid_cls = loss_cls.get('use_sigmoid', False)
-        if self.use_sigmoid_cls:
-            self.cls_out_channels = num_classes
-        else:
-            self.cls_out_channels = num_classes + 1
-
-        if self.cls_out_channels <= 0:
-            raise ValueError(f'num_classes={num_classes} is too small')
-        self.reg_decoded_bbox = reg_decoded_bbox
-
-        self.bbox_coder = build_bbox_coder(bbox_coder)
-        self.loss_cls = build_loss(loss_cls)
-        self.loss_bbox = build_loss(loss_bbox)
-        self.train_cfg = train_cfg
-        self.test_cfg = test_cfg
-        if self.train_cfg:
-            self.assigner = build_assigner(self.train_cfg.assigner)
-            if hasattr(self.train_cfg,
-                       'sampler') and self.train_cfg.sampler.type.split(
-                           '.')[-1] != 'PseudoSampler':
-                self.sampling = True
-                sampler_cfg = self.train_cfg.sampler
-                # avoid BC-breaking
-                if loss_cls['type'] in [
-                        'FocalLoss', 'GHMC', 'QualityFocalLoss'
-                ]:
-                    warnings.warn(
-                        'DeprecationWarning: Determining whether to sampling'
-                        'by loss type is deprecated, please delete sampler in'
-                        'your config when using `FocalLoss`, `GHMC`, '
-                        '`QualityFocalLoss` or other FocalLoss variant.')
-                    self.sampling = False
-                    sampler_cfg = dict(type='PseudoSampler')
-            else:
-                self.sampling = False
-                sampler_cfg = dict(type='PseudoSampler')
-            self.sampler = build_sampler(sampler_cfg, context=self)
-        self.fp16_enabled = False
-
-        self.prior_generator = build_prior_generator(anchor_generator)
-
-        # Usually the numbers of anchors for each level are the same
-        # except SSD detectors. So it is an int in the most dense
-        # heads but a list of int in SSDHead
-        self.num_base_priors = self.prior_generator.num_base_priors[0]
-        self._init_layers()
-
-    @property
-    def num_anchors(self):
-        warnings.warn('DeprecationWarning: `num_anchors` is deprecated, '
-                      'for consistency or also use '
-                      '`num_base_priors` instead')
-        return self.prior_generator.num_base_priors[0]
-
-    @property
-    def anchor_generator(self):
-        warnings.warn('DeprecationWarning: anchor_generator is deprecated, '
-                      'please use "prior_generator" instead')
-        return self.prior_generator
-
-    def _init_layers(self):
-        """Initialize layers of the head."""
-        self.conv_cls = nn.Conv2d(self.in_channels,
-                                  self.num_base_priors * self.cls_out_channels,
-                                  1)
-        self.conv_reg = nn.Conv2d(self.in_channels, self.num_base_priors * 4,
-                                  1)
-
-    def forward_single(self, x):
-        """Forward feature of a single scale level.
-
-        Args:
-            x (Tensor): Features of a single scale level.
-
-        Returns:
-            tuple:
-                cls_score (Tensor): Cls scores for a single scale level \
-                    the channels number is num_base_priors * num_classes.
-                bbox_pred (Tensor): Box energies / deltas for a single scale \
-                    level, the channels number is num_base_priors * 4.
-        """
-        cls_score = self.conv_cls(x)
-        bbox_pred = self.conv_reg(x)
-        return cls_score, bbox_pred
-
-    def forward(self, feats):
-        """Forward features from the upstream network.
-
-        Args:
-            feats (tuple[Tensor]): Features from the upstream network, each is
-                a 4D-tensor.
-
-        Returns:
-            tuple: A tuple of classification scores and bbox prediction.
-
-                - cls_scores (list[Tensor]): Classification scores for all \
-                    scale levels, each is a 4D-tensor, the channels number \
-                    is num_base_priors * num_classes.
-                - bbox_preds (list[Tensor]): Box energies / deltas for all \
-                    scale levels, each is a 4D-tensor, the channels number \
-                    is num_base_priors * 4.
-        """
-        return multi_apply(self.forward_single, feats)
-
-    def get_anchors(self, featmap_sizes, img_metas, device='cuda'):
-        """Get anchors according to feature map sizes.
-
-        Args:
-            featmap_sizes (list[tuple]): Multi-level feature map sizes.
-            img_metas (list[dict]): Image meta info.
-            device (torch.device | str): Device for returned tensors
-
-        Returns:
-            tuple:
-                anchor_list (list[Tensor]): Anchors of each image.
-                valid_flag_list (list[Tensor]): Valid flags of each image.
-        """
-        num_imgs = len(img_metas)
-
-        # since feature map sizes of all images are the same, we only compute
-        # anchors for one time
-        multi_level_anchors = self.prior_generator.grid_priors(
-            featmap_sizes, device=device)
-        anchor_list = [multi_level_anchors for _ in range(num_imgs)]
-
-        # for each image, we compute valid flags of multi level anchors
-        valid_flag_list = []
-        for img_id, img_meta in enumerate(img_metas):
-            multi_level_flags = self.prior_generator.valid_flags(
-                featmap_sizes, img_meta['pad_shape'], device)
-            valid_flag_list.append(multi_level_flags)
-
-        return anchor_list, valid_flag_list
-
-    def _get_targets_single(self,
-                            flat_anchors,
-                            valid_flags,
-                            gt_bboxes,
-                            gt_bboxes_ignore,
-                            gt_labels,
-                            img_meta,
-                            label_channels=1,
-                            unmap_outputs=True):
-        """Compute regression and classification targets for anchors in a
-        single image.
-
-        Args:
-            flat_anchors (Tensor): Multi-level anchors of the image, which are
-                concatenated into a single tensor of shape (num_anchors ,4)
-            valid_flags (Tensor): Multi level valid flags of the image,
-                which are concatenated into a single tensor of
-                    shape (num_anchors,).
-            gt_bboxes (Tensor): Ground truth bboxes of the image,
-                shape (num_gts, 4).
-            gt_bboxes_ignore (Tensor): Ground truth bboxes to be
-                ignored, shape (num_ignored_gts, 4).
-            img_meta (dict): Meta info of the image.
-            gt_labels (Tensor): Ground truth labels of each box,
-                shape (num_gts,).
-            label_channels (int): Channel of label.
-            unmap_outputs (bool): Whether to map outputs back to the original
-                set of anchors.
-
-        Returns:
-            tuple:
-                labels_list (list[Tensor]): Labels of each level
-                label_weights_list (list[Tensor]): Label weights of each level
-                bbox_targets_list (list[Tensor]): BBox targets of each level
-                bbox_weights_list (list[Tensor]): BBox weights of each level
-                num_total_pos (int): Number of positive samples in all images
-                num_total_neg (int): Number of negative samples in all images
-        """
-        inside_flags = anchor_inside_flags(flat_anchors, valid_flags,
-                                           img_meta['img_shape'][:2],
-                                           self.train_cfg.allowed_border)
-        if not inside_flags.any():
-            return (None, ) * 7
-        # assign gt and sample anchors
-        anchors = flat_anchors[inside_flags, :]
-
-        assign_result = self.assigner.assign(
-            anchors, gt_bboxes, gt_bboxes_ignore,
-            None if self.sampling else gt_labels)
-        sampling_result = self.sampler.sample(assign_result, anchors,
-                                              gt_bboxes)
-
-        num_valid_anchors = anchors.shape[0]
-        bbox_targets = torch.zeros_like(anchors)
-        bbox_weights = torch.zeros_like(anchors)
-        labels = anchors.new_full((num_valid_anchors, ),
-                                  self.num_classes,
-                                  dtype=torch.long)
-        label_weights = anchors.new_zeros(num_valid_anchors, dtype=torch.float)
-
-        pos_inds = sampling_result.pos_inds
-        neg_inds = sampling_result.neg_inds
-        if len(pos_inds) > 0:
-            if not self.reg_decoded_bbox:
-                pos_bbox_targets = self.bbox_coder.encode(
-                    sampling_result.pos_bboxes, sampling_result.pos_gt_bboxes)
-            else:
-                pos_bbox_targets = sampling_result.pos_gt_bboxes
-            bbox_targets[pos_inds, :] = pos_bbox_targets
-            bbox_weights[pos_inds, :] = 1.0
-            if gt_labels is None:
-                # Only rpn gives gt_labels as None
-                # Foreground is the first class since v2.5.0
-                labels[pos_inds] = 0
-            else:
-                labels[pos_inds] = gt_labels[
-                    sampling_result.pos_assigned_gt_inds]
-            if self.train_cfg.pos_weight <= 0:
-                label_weights[pos_inds] = 1.0
-            else:
-                label_weights[pos_inds] = self.train_cfg.pos_weight
-        if len(neg_inds) > 0:
-            label_weights[neg_inds] = 1.0
-
-        # map up to original set of anchors
-        if unmap_outputs:
-            num_total_anchors = flat_anchors.size(0)
-            labels = unmap(
-                labels, num_total_anchors, inside_flags,
-                fill=self.num_classes)  # fill bg label
-            label_weights = unmap(label_weights, num_total_anchors,
-                                  inside_flags)
-            bbox_targets = unmap(bbox_targets, num_total_anchors, inside_flags)
-            bbox_weights = unmap(bbox_weights, num_total_anchors, inside_flags)
-
-        return (labels, label_weights, bbox_targets, bbox_weights, pos_inds,
-                neg_inds, sampling_result)
-
-    def get_targets(self,
-                    anchor_list,
-                    valid_flag_list,
-                    gt_bboxes_list,
-                    img_metas,
-                    gt_bboxes_ignore_list=None,
-                    gt_labels_list=None,
-                    label_channels=1,
-                    unmap_outputs=True,
-                    return_sampling_results=False):
-        """Compute regression and classification targets for anchors in
-        multiple images.
-
-        Args:
-            anchor_list (list[list[Tensor]]): Multi level anchors of each
-                image. The outer list indicates images, and the inner list
-                corresponds to feature levels of the image. Each element of
-                the inner list is a tensor of shape (num_anchors, 4).
-            valid_flag_list (list[list[Tensor]]): Multi level valid flags of
-                each image. The outer list indicates images, and the inner list
-                corresponds to feature levels of the image. Each element of
-                the inner list is a tensor of shape (num_anchors, )
-            gt_bboxes_list (list[Tensor]): Ground truth bboxes of each image.
-            img_metas (list[dict]): Meta info of each image.
-            gt_bboxes_ignore_list (list[Tensor]): Ground truth bboxes to be
-                ignored.
-            gt_labels_list (list[Tensor]): Ground truth labels of each box.
-            label_channels (int): Channel of label.
-            unmap_outputs (bool): Whether to map outputs back to the original
-                set of anchors.
-
-        Returns:
-            tuple: Usually returns a tuple containing learning targets.
-
-                - labels_list (list[Tensor]): Labels of each level.
-                - label_weights_list (list[Tensor]): Label weights of each
-                  level.
-                - bbox_targets_list (list[Tensor]): BBox targets of each level.
-                - bbox_weights_list (list[Tensor]): BBox weights of each level.
-                - num_total_pos (int): Number of positive samples in all
-                  images.
-                - num_total_neg (int): Number of negative samples in all
-                  images.
-
-            additional_returns: This function enables user-defined returns from
-                `self._get_targets_single`. These returns are currently refined
-                to properties at each feature map (i.e. having HxW dimension).
-                The results will be concatenated after the end
-        """
-        num_imgs = len(img_metas)
-        assert len(anchor_list) == len(valid_flag_list) == num_imgs
-
-        # anchor number of multi levels
-        num_level_anchors = [anchors.size(0) for anchors in anchor_list[0]]
-        # concat all level anchors to a single tensor
-        concat_anchor_list = []
-        concat_valid_flag_list = []
-        for i in range(num_imgs):
-            assert len(anchor_list[i]) == len(valid_flag_list[i])
-            concat_anchor_list.append(torch.cat(anchor_list[i]))
-            concat_valid_flag_list.append(torch.cat(valid_flag_list[i]))
-
-        # compute targets for each image
-        if gt_bboxes_ignore_list is None:
-            gt_bboxes_ignore_list = [None for _ in range(num_imgs)]
-        if gt_labels_list is None:
-            gt_labels_list = [None for _ in range(num_imgs)]
-        results = multi_apply(
-            self._get_targets_single,
-            concat_anchor_list,
-            concat_valid_flag_list,
-            gt_bboxes_list,
-            gt_bboxes_ignore_list,
-            gt_labels_list,
-            img_metas,
-            label_channels=label_channels,
-            unmap_outputs=unmap_outputs)
-        (all_labels, all_label_weights, all_bbox_targets, all_bbox_weights,
-         pos_inds_list, neg_inds_list, sampling_results_list) = results[:7]
-        rest_results = list(results[7:])  # user-added return values
-        # no valid anchors
-        if any([labels is None for labels in all_labels]):
-            return None
-        # sampled anchors of all images
-        num_total_pos = sum([max(inds.numel(), 1) for inds in pos_inds_list])
-        num_total_neg = sum([max(inds.numel(), 1) for inds in neg_inds_list])
-        # split targets to a list w.r.t. multiple levels
-        labels_list = images_to_levels(all_labels, num_level_anchors)
-        label_weights_list = images_to_levels(all_label_weights,
-                                              num_level_anchors)
-        bbox_targets_list = images_to_levels(all_bbox_targets,
-                                             num_level_anchors)
-        bbox_weights_list = images_to_levels(all_bbox_weights,
-                                             num_level_anchors)
-        res = (labels_list, label_weights_list, bbox_targets_list,
-               bbox_weights_list, num_total_pos, num_total_neg)
-        if return_sampling_results:
-            res = res + (sampling_results_list, )
-        for i, r in enumerate(rest_results):  # user-added return values
-            rest_results[i] = images_to_levels(r, num_level_anchors)
-
-        return res + tuple(rest_results)
-
-    def loss_single(self, cls_score, bbox_pred, anchors, labels, label_weights,
-                    bbox_targets, bbox_weights, num_total_samples):
-        """Compute loss of a single scale level.
-
-        Args:
-            cls_score (Tensor): Box scores for each scale level
-                Has shape (N, num_anchors * num_classes, H, W).
-            bbox_pred (Tensor): Box energies / deltas for each scale
-                level with shape (N, num_anchors * 4, H, W).
-            anchors (Tensor): Box reference for each scale level with shape
-                (N, num_total_anchors, 4).
-            labels (Tensor): Labels of each anchors with shape
-                (N, num_total_anchors).
-            label_weights (Tensor): Label weights of each anchor with shape
-                (N, num_total_anchors)
-            bbox_targets (Tensor): BBox regression targets of each anchor
-                weight shape (N, num_total_anchors, 4).
-            bbox_weights (Tensor): BBox regression loss weights of each anchor
-                with shape (N, num_total_anchors, 4).
-            num_total_samples (int): If sampling, num total samples equal to
-                the number of total anchors; Otherwise, it is the number of
-                positive anchors.
-
-        Returns:
-            dict[str, Tensor]: A dictionary of loss components.
-        """
-        # classification loss
-        labels = labels.reshape(-1)
-        label_weights = label_weights.reshape(-1)
-        cls_score = cls_score.permute(0, 2, 3,
-                                      1).reshape(-1, self.cls_out_channels)
-        loss_cls = self.loss_cls(
-            cls_score, labels, label_weights, avg_factor=num_total_samples)
-        # regression loss
-        bbox_targets = bbox_targets.reshape(-1, 4)
-        bbox_weights = bbox_weights.reshape(-1, 4)
-        bbox_pred = bbox_pred.permute(0, 2, 3, 1).reshape(-1, 4)
-        if self.reg_decoded_bbox:
-            # When the regression loss (e.g. `IouLoss`, `GIouLoss`)
-            # is applied directly on the decoded bounding boxes, it
-            # decodes the already encoded coordinates to absolute format.
-            anchors = anchors.reshape(-1, 4)
-            bbox_pred = self.bbox_coder.decode(anchors, bbox_pred)
-        loss_bbox = self.loss_bbox(
-            bbox_pred,
-            bbox_targets,
-            bbox_weights,
-            avg_factor=num_total_samples)
-        return loss_cls, loss_bbox
-
-    @force_fp32(apply_to=('cls_scores', 'bbox_preds'))
-    def loss(self,
-             cls_scores,
-             bbox_preds,
-             gt_bboxes,
-             gt_labels,
-             img_metas,
-             gt_bboxes_ignore=None):
-        """Compute losses of the head.
-
-        Args:
-            cls_scores (list[Tensor]): Box scores for each scale level
-                Has shape (N, num_anchors * num_classes, H, W)
-            bbox_preds (list[Tensor]): Box energies / deltas for each scale
-                level with shape (N, num_anchors * 4, H, W)
-            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
-            img_metas (list[dict]): Meta information of each image, e.g.,
-                image size, scaling factor, etc.
-            gt_bboxes_ignore (None | list[Tensor]): specify which bounding
-                boxes can be ignored when computing the loss. Default: None
-
-        Returns:
-            dict[str, Tensor]: A dictionary of loss components.
-        """
-        featmap_sizes = [featmap.size()[-2:] for featmap in cls_scores]
-        assert len(featmap_sizes) == self.prior_generator.num_levels
-
-        device = cls_scores[0].device
-
-        anchor_list, valid_flag_list = self.get_anchors(
-            featmap_sizes, img_metas, device=device)
-        label_channels = self.cls_out_channels if self.use_sigmoid_cls else 1
-        cls_reg_targets = self.get_targets(
-            anchor_list,
-            valid_flag_list,
-            gt_bboxes,
-            img_metas,
-            gt_bboxes_ignore_list=gt_bboxes_ignore,
-            gt_labels_list=gt_labels,
-            label_channels=label_channels)
-        if cls_reg_targets is None:
-            return None
-        (labels_list, label_weights_list, bbox_targets_list, bbox_weights_list,
-         num_total_pos, num_total_neg) = cls_reg_targets
-        num_total_samples = (
-            num_total_pos + num_total_neg if self.sampling else num_total_pos)
-
-        # anchor number of multi levels
-        num_level_anchors = [anchors.size(0) for anchors in anchor_list[0]]
-        # concat all level anchors and flags to a single tensor
-        concat_anchor_list = []
-        for i in range(len(anchor_list)):
-            concat_anchor_list.append(torch.cat(anchor_list[i]))
-        all_anchor_list = images_to_levels(concat_anchor_list,
-                                           num_level_anchors)
-
-        losses_cls, losses_bbox = multi_apply(
-            self.loss_single,
-            cls_scores,
-            bbox_preds,
-            all_anchor_list,
-            labels_list,
-            label_weights_list,
-            bbox_targets_list,
-            bbox_weights_list,
-            num_total_samples=num_total_samples)
-        return dict(loss_cls=losses_cls, loss_bbox=losses_bbox)
-
-    def aug_test(self, feats, img_metas, rescale=False):
-        """Test function with test time augmentation.
-
-        Args:
-            feats (list[Tensor]): the outer list indicates test-time
-                augmentations and inner Tensor should have a shape NxCxHxW,
-                which contains features for all images in the batch.
-            img_metas (list[list[dict]]): the outer list indicates test-time
-                augs (multiscale, flip, etc.) and the inner list indicates
-                images in a batch. each dict has image information.
-            rescale (bool, optional): Whether to rescale the results.
-                Defaults to False.
-
-        Returns:
-            list[tuple[Tensor, Tensor]]: Each item in result_list is 2-tuple.
-                The first item is ``bboxes`` with shape (n, 5), where
-                5 represent (tl_x, tl_y, br_x, br_y, score).
-                The shape of the second tensor in the tuple is ``labels``
-                with shape (n,), The length of list should always be 1.
-        """
-        return self.aug_test_bboxes(feats, img_metas, rescale=rescale)
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/roi_heads/base_roi_head.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/roi_heads/base_roi_head.py
deleted file mode 100644
index 4adbdef8f2f9ffb9a75c23c45481fc9bb3de9246..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/roi_heads/base_roi_head.py
+++ /dev/null
@@ -1,103 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from abc import ABCMeta, abstractmethod
-
-from mmcv.runner import BaseModule
-
-from ..builder import build_shared_head
-
-
-class BaseRoIHead(BaseModule, metaclass=ABCMeta):
-    """Base class for RoIHeads."""
-
-    def __init__(self,
-                 bbox_roi_extractor=None,
-                 bbox_head=None,
-                 mask_roi_extractor=None,
-                 mask_head=None,
-                 shared_head=None,
-                 train_cfg=None,
-                 test_cfg=None,
-                 pretrained=None,
-                 init_cfg=None):
-        super(BaseRoIHead, self).__init__(init_cfg)
-        self.train_cfg = train_cfg
-        self.test_cfg = test_cfg
-        if shared_head is not None:
-            shared_head.pretrained = pretrained
-            self.shared_head = build_shared_head(shared_head)
-
-        if bbox_head is not None:
-            self.init_bbox_head(bbox_roi_extractor, bbox_head)
-
-        if mask_head is not None:
-            self.init_mask_head(mask_roi_extractor, mask_head)
-
-        self.init_assigner_sampler()
-
-    @property
-    def with_bbox(self):
-        """bool: whether the RoI head contains a `bbox_head`"""
-        return hasattr(self, 'bbox_head') and self.bbox_head is not None
-
-    @property
-    def with_mask(self):
-        """bool: whether the RoI head contains a `mask_head`"""
-        return hasattr(self, 'mask_head') and self.mask_head is not None
-
-    @property
-    def with_shared_head(self):
-        """bool: whether the RoI head contains a `shared_head`"""
-        return hasattr(self, 'shared_head') and self.shared_head is not None
-
-    @abstractmethod
-    def init_bbox_head(self):
-        """Initialize ``bbox_head``"""
-        pass
-
-    @abstractmethod
-    def init_mask_head(self):
-        """Initialize ``mask_head``"""
-        pass
-
-    @abstractmethod
-    def init_assigner_sampler(self):
-        """Initialize assigner and sampler."""
-        pass
-
-    @abstractmethod
-    def forward_train(self,
-                      x,
-                      img_meta,
-                      proposal_list,
-                      gt_bboxes,
-                      gt_labels,
-                      gt_bboxes_ignore=None,
-                      gt_masks=None,
-                      **kwargs):
-        """Forward function during training."""
-
-    async def async_simple_test(self,
-                                x,
-                                proposal_list,
-                                img_metas,
-                                proposals=None,
-                                rescale=False,
-                                **kwargs):
-        """Asynchronized test function."""
-        raise NotImplementedError
-
-    def simple_test(self,
-                    x,
-                    proposal_list,
-                    img_meta,
-                    proposals=None,
-                    rescale=False,
-                    **kwargs):
-        """Test without augmentation."""
-
-    def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
-        """Test with augmentations.
-
-        If rescale is False, then returned bboxes and masks will fit the scale
-        of imgs[0].
-        """
diff --git a/spaces/rondel/summarizer_app_test/app.py b/spaces/rondel/summarizer_app_test/app.py
deleted file mode 100644
index dbac4f0b6033b7821ad50a7765a1258956326eb8..0000000000000000000000000000000000000000
--- a/spaces/rondel/summarizer_app_test/app.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import gradio as gr
-import torch
-import transformers
-from transformers import pipeline
-
-summarizer = pipeline("summarization")
-
-def summarize(text):
-    return summarizer(text, max_length=100, min_length=30)[0]["summary_text"]
-
-iface = gr.Interface(fn=summarize, inputs="text", outputs="text", live=True, capture_session=True)
-iface.launch(inline = False)
\ No newline at end of file
diff --git a/spaces/rorallitri/biomedical-language-models/logs/10 Janpath Movie In Hindi 720p Download Interfaccia Carrie S A Review and Analysis.md b/spaces/rorallitri/biomedical-language-models/logs/10 Janpath Movie In Hindi 720p Download Interfaccia Carrie S A Review and Analysis.md
deleted file mode 100644
index d2ac9f83cb21594a09050a9b18b73aad4ad59a31..0000000000000000000000000000000000000000
--- a/spaces/rorallitri/biomedical-language-models/logs/10 Janpath Movie In Hindi 720p Download Interfaccia Carrie S A Review and Analysis.md	
+++ /dev/null
@@ -1,8 +0,0 @@
-<br />
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diff --git a/spaces/ruboin/faster-whisper-webui/src/vadParallel.py b/spaces/ruboin/faster-whisper-webui/src/vadParallel.py
deleted file mode 100644
index c2323c0b632c34014ac1fe7ac79141b5bd9c5731..0000000000000000000000000000000000000000
--- a/spaces/ruboin/faster-whisper-webui/src/vadParallel.py
+++ /dev/null
@@ -1,298 +0,0 @@
-import multiprocessing
-from queue import Empty
-import threading
-import time
-from src.hooks.progressListener import ProgressListener
-from src.vad import AbstractTranscription, TranscriptionConfig, get_audio_duration
-
-from multiprocessing import Pool, Queue
-
-from typing import Any, Dict, List, Union
-import os
-
-from src.whisper.abstractWhisperContainer import AbstractWhisperCallback
-
-class _ProgressListenerToQueue(ProgressListener):
-    def __init__(self, progress_queue: Queue):
-        self.progress_queue = progress_queue
-        self.progress_total = 0
-        self.prev_progress = 0
-
-    def on_progress(self, current: Union[int, float], total: Union[int, float]):
-        delta = current - self.prev_progress
-        self.prev_progress = current
-        self.progress_total = total
-        self.progress_queue.put(delta)
-
-    def on_finished(self):
-        if self.progress_total > self.prev_progress:
-            delta = self.progress_total - self.prev_progress
-            self.progress_queue.put(delta)
-            self.prev_progress = self.progress_total
-
-class ParallelContext:
-    def __init__(self, num_processes: int = None, auto_cleanup_timeout_seconds: float = None):
-        self.num_processes = num_processes
-        self.auto_cleanup_timeout_seconds = auto_cleanup_timeout_seconds
-        self.lock = threading.Lock()
-
-        self.ref_count = 0
-        self.pool = None
-        self.cleanup_timer = None
-
-    def get_pool(self):
-        # Initialize pool lazily
-        if (self.pool is None):
-            context = multiprocessing.get_context('spawn')
-            self.pool = context.Pool(self.num_processes)
-
-        self.ref_count = self.ref_count + 1
-
-        if (self.auto_cleanup_timeout_seconds is not None):
-            self._stop_auto_cleanup()
-
-        return self.pool
-
-    def return_pool(self, pool):
-        if (self.pool == pool and self.ref_count > 0):
-            self.ref_count = self.ref_count - 1
-
-            if (self.ref_count == 0):
-                if (self.auto_cleanup_timeout_seconds is not None):
-                    self._start_auto_cleanup()
-
-    def _start_auto_cleanup(self):
-        if (self.cleanup_timer is not None):
-            self.cleanup_timer.cancel()
-        self.cleanup_timer = threading.Timer(self.auto_cleanup_timeout_seconds, self._execute_cleanup)
-        self.cleanup_timer.start()
-
-        print("Started auto cleanup of pool in " + str(self.auto_cleanup_timeout_seconds) + " seconds")
-
-    def _stop_auto_cleanup(self):
-        if (self.cleanup_timer is not None):
-            self.cleanup_timer.cancel()
-            self.cleanup_timer = None
-
-            print("Stopped auto cleanup of pool")
-
-    def _execute_cleanup(self):
-        print("Executing cleanup of pool")
-
-        if (self.ref_count == 0):
-            self.close()
-
-    def close(self):
-        self._stop_auto_cleanup()
-
-        if (self.pool is not None):
-            print("Closing pool of " + str(self.num_processes) + " processes")
-            self.pool.close()
-            self.pool.join()
-        self.pool = None
-
-class ParallelTranscriptionConfig(TranscriptionConfig):
-    def __init__(self, device_id: str, override_timestamps, initial_segment_index, copy: TranscriptionConfig = None):
-        super().__init__(copy.non_speech_strategy, copy.segment_padding_left, copy.segment_padding_right, copy.max_silent_period, copy.max_merge_size, copy.max_prompt_window, initial_segment_index)
-        self.device_id = device_id
-        self.override_timestamps = override_timestamps
-
-class ParallelTranscription(AbstractTranscription):
-    # Silero VAD typically takes about 3 seconds per minute, so there's no need to split the chunks 
-    # into smaller segments than 2 minute (min 6 seconds per CPU core)
-    MIN_CPU_CHUNK_SIZE_SECONDS = 2 * 60
-
-    def __init__(self, sampling_rate: int = 16000):
-        super().__init__(sampling_rate=sampling_rate)
-
-    def transcribe_parallel(self, transcription: AbstractTranscription, audio: str, whisperCallable: AbstractWhisperCallback, config: TranscriptionConfig, 
-                            cpu_device_count: int, gpu_devices: List[str], cpu_parallel_context: ParallelContext = None, gpu_parallel_context: ParallelContext = None, 
-                            progress_listener: ProgressListener = None):
-        total_duration = get_audio_duration(audio)
-
-        # First, get the timestamps for the original audio
-        if (cpu_device_count > 1 and not transcription.is_transcribe_timestamps_fast()):
-            merged = self._get_merged_timestamps_parallel(transcription, audio, config, total_duration, cpu_device_count, cpu_parallel_context)
-        else:
-            timestamp_segments = transcription.get_transcribe_timestamps(audio, config, 0, total_duration)
-            merged = transcription.get_merged_timestamps(timestamp_segments, config, total_duration)
-
-        # We must make sure the whisper model is downloaded
-        if (len(gpu_devices) > 1):
-            whisperCallable.model_container.ensure_downloaded()
-
-        # Split into a list for each device
-        # TODO: Split by time instead of by number of chunks
-        merged_split = list(self._split(merged, len(gpu_devices)))
-
-        # Parameters that will be passed to the transcribe function
-        parameters = []
-        segment_index = config.initial_segment_index
-
-        processing_manager = multiprocessing.Manager()
-        progress_queue = processing_manager.Queue()
-
-        for i in range(len(gpu_devices)):
-            # Note that device_segment_list can be empty. But we will still create a process for it,
-            # as otherwise we run the risk of assigning the same device to multiple processes.
-            device_segment_list = list(merged_split[i]) if i < len(merged_split) else []
-            device_id = gpu_devices[i]
-
-            print("Device " + str(device_id) + " (index " + str(i) + ") has " + str(len(device_segment_list)) + " segments")
-
-            # Create a new config with the given device ID
-            device_config = ParallelTranscriptionConfig(device_id, device_segment_list, segment_index, config)
-            segment_index += len(device_segment_list)
-
-            progress_listener_to_queue = _ProgressListenerToQueue(progress_queue)
-            parameters.append([audio, whisperCallable, device_config, progress_listener_to_queue]);
-
-        merged = {
-            'text': '',
-            'segments': [],
-            'language': None
-        }
-
-        created_context = False
-
-        perf_start_gpu = time.perf_counter()
-
-        # Spawn a separate process for each device
-        try:
-            if (gpu_parallel_context is None):
-                gpu_parallel_context = ParallelContext(len(gpu_devices))
-                created_context = True
-
-            # Get a pool of processes
-            pool = gpu_parallel_context.get_pool()
-
-            # Run the transcription in parallel
-            results_async = pool.starmap_async(self.transcribe, parameters)
-            total_progress = 0
-
-            while not results_async.ready():
-                try:
-                    delta = progress_queue.get(timeout=5)  # Set a timeout of 5 seconds
-                except Empty:
-                    continue
-                
-                total_progress += delta
-                if progress_listener is not None:
-                    progress_listener.on_progress(total_progress, total_duration)
-
-            results = results_async.get()
-
-            # Call the finished callback
-            if progress_listener is not None:
-                progress_listener.on_finished()
-
-            for result in results:
-                # Merge the results
-                if (result['text'] is not None):
-                    merged['text'] += result['text']
-                if (result['segments'] is not None):
-                    merged['segments'].extend(result['segments'])
-                if (result['language'] is not None):
-                    merged['language'] = result['language']
-
-        finally:
-            # Return the pool to the context
-            if (gpu_parallel_context is not None):
-                gpu_parallel_context.return_pool(pool)
-            # Always close the context if we created it
-            if (created_context):
-                gpu_parallel_context.close()
-
-        perf_end_gpu = time.perf_counter()
-        print("Parallel transcription took " + str(perf_end_gpu - perf_start_gpu) + " seconds")
-
-        return merged
-
-    def _get_merged_timestamps_parallel(self, transcription: AbstractTranscription, audio: str, config: TranscriptionConfig, total_duration: float, 
-                                       cpu_device_count: int, cpu_parallel_context: ParallelContext = None):
-        parameters = []
-
-        chunk_size = max(total_duration / cpu_device_count, self.MIN_CPU_CHUNK_SIZE_SECONDS)
-        chunk_start = 0
-        cpu_device_id = 0
-
-        perf_start_time = time.perf_counter()
-
-        # Create chunks that will be processed on the CPU
-        while (chunk_start < total_duration):
-            chunk_end = min(chunk_start + chunk_size, total_duration)
-
-            if (chunk_end - chunk_start < 1):
-                # No need to process chunks that are less than 1 second
-                break
-
-            print("Parallel VAD: Executing chunk from " + str(chunk_start) + " to " + 
-                    str(chunk_end) + " on CPU device " + str(cpu_device_id))
-            parameters.append([audio, config, chunk_start, chunk_end]);
-
-            cpu_device_id += 1
-            chunk_start = chunk_end
-
-        created_context = False
-
-        # Spawn a separate process for each device
-        try:
-            if (cpu_parallel_context is None):
-                cpu_parallel_context = ParallelContext(cpu_device_count)
-                created_context = True
-
-            # Get a pool of processes
-            pool = cpu_parallel_context.get_pool()
-
-            # Run the transcription in parallel. Note that transcription must be picklable.
-            results = pool.starmap(transcription.get_transcribe_timestamps, parameters)
-
-            timestamps = []
-
-            # Flatten the results
-            for result in results:
-                timestamps.extend(result)
-
-            merged = transcription.get_merged_timestamps(timestamps, config, total_duration)
-
-            perf_end_time = time.perf_counter()
-            print("Parallel VAD processing took {} seconds".format(perf_end_time - perf_start_time))
-            return merged
-
-        finally:
-            # Return the pool to the context
-            if (cpu_parallel_context is not None):
-                cpu_parallel_context.return_pool(pool)
-            # Always close the context if we created it
-            if (created_context):
-                cpu_parallel_context.close()
-
-    def get_transcribe_timestamps(self, audio: str, config: ParallelTranscriptionConfig, start_time: float, duration: float):
-        return []
-
-    def get_merged_timestamps(self,  timestamps: List[Dict[str, Any]], config: ParallelTranscriptionConfig, total_duration: float):
-        # Override timestamps that will be processed
-        if (config.override_timestamps is not None):
-            print("(get_merged_timestamps) Using override timestamps of size " + str(len(config.override_timestamps)))
-            return config.override_timestamps
-        return super().get_merged_timestamps(timestamps, config, total_duration)
-
-    def transcribe(self, audio: str, whisperCallable: AbstractWhisperCallback, config: ParallelTranscriptionConfig, 
-                   progressListener: ProgressListener = None):
-        # Override device ID the first time
-        if (os.environ.get("INITIALIZED", None) is None):
-            os.environ["INITIALIZED"] = "1"
-
-            # Note that this may be None if the user didn't specify a device. In that case, Whisper will
-            # just use the default GPU device.
-            if (config.device_id is not None):
-                print("Using device " + config.device_id)
-                os.environ["CUDA_VISIBLE_DEVICES"] = config.device_id
-        
-        return super().transcribe(audio, whisperCallable, config, progressListener)
-
-    def _split(self, a, n):
-        """Split a list into n approximately equal parts."""
-        k, m = divmod(len(a), n)
-        return (a[i*k+min(i, m):(i+1)*k+min(i+1, m)] for i in range(n))
-
diff --git a/spaces/runa91/bite_gradio/src/smal_pytorch/smal_model/batch_lbs.py b/spaces/runa91/bite_gradio/src/smal_pytorch/smal_model/batch_lbs.py
deleted file mode 100644
index 56e9c7d4740dc5eb9f95627fed47a28065dac3fd..0000000000000000000000000000000000000000
--- a/spaces/runa91/bite_gradio/src/smal_pytorch/smal_model/batch_lbs.py
+++ /dev/null
@@ -1,313 +0,0 @@
-'''
-Adjusted version of other PyTorch implementation of the SMAL/SMPL model
-see:
-    1.) https://github.com/silviazuffi/smalst/blob/master/smal_model/smal_torch.py
-    2.) https://github.com/benjiebob/SMALify/blob/master/smal_model/smal_torch.py
-'''
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import torch
-import numpy as np
-
-
-def batch_skew(vec, batch_size=None):
-    """
-    vec is N x 3, batch_size is int
-
-    returns N x 3 x 3. Skew_sym version of each matrix.
-    """
-    device = vec.device
-    if batch_size is None:
-        batch_size = vec.shape.as_list()[0]
-    col_inds = torch.LongTensor([1, 2, 3, 5, 6, 7])
-    indices = torch.reshape(torch.reshape(torch.arange(0, batch_size) * 9, [-1, 1]) + col_inds, [-1, 1])
-    updates = torch.reshape(
-            torch.stack(
-                [
-                    -vec[:, 2], vec[:, 1], vec[:, 2], -vec[:, 0], -vec[:, 1],
-                    vec[:, 0]
-                ],
-                dim=1), [-1])
-    out_shape = [batch_size * 9]
-    res = torch.Tensor(np.zeros(out_shape[0])).to(device=device)
-    res[np.array(indices.flatten())] = updates
-    res = torch.reshape(res, [batch_size, 3, 3])
-
-    return res
-
-
-
-def batch_rodrigues(theta):
-    """
-    Theta is Nx3
-    """
-    device = theta.device
-    batch_size = theta.shape[0]
-
-    angle = (torch.norm(theta + 1e-8, p=2, dim=1)).unsqueeze(-1)
-    r = (torch.div(theta, angle)).unsqueeze(-1)
-
-    angle = angle.unsqueeze(-1)
-    cos = torch.cos(angle)
-    sin = torch.sin(angle)
-
-    outer = torch.matmul(r, r.transpose(1,2))
-
-    eyes = torch.eye(3).unsqueeze(0).repeat([batch_size, 1, 1]).to(device=device)
-    H = batch_skew(r, batch_size=batch_size)
-    R = cos * eyes + (1 - cos) * outer + sin * H 
-
-    return R
-
-def batch_lrotmin(theta):
-    """
-    Output of this is used to compute joint-to-pose blend shape mapping.
-    Equation 9 in SMPL paper.
-
-
-    Args:
-      pose: `Tensor`, N x 72 vector holding the axis-angle rep of K joints.
-            This includes the global rotation so K=24
-
-    Returns
-      diff_vec : `Tensor`: N x 207 rotation matrix of 23=(K-1) joints with identity subtracted.,
-    """
-    # Ignore global rotation
-    theta = theta[:,3:]
-
-    Rs = batch_rodrigues(torch.reshape(theta, [-1,3]))
-    lrotmin = torch.reshape(Rs - torch.eye(3), [-1, 207])
-
-    return lrotmin
-
-def batch_global_rigid_transformation(Rs, Js, parent, rotate_base=False):
-    """
-    Computes absolute joint locations given pose.
-
-    rotate_base: if True, rotates the global rotation by 90 deg in x axis.
-    if False, this is the original SMPL coordinate.
-
-    Args:
-      Rs: N x 24 x 3 x 3 rotation vector of K joints
-      Js: N x 24 x 3, joint locations before posing
-      parent: 24 holding the parent id for each index
-
-    Returns
-      new_J : `Tensor`: N x 24 x 3 location of absolute joints
-      A     : `Tensor`: N x 24 4 x 4 relative joint transformations for LBS.
-    """
-    device = Rs.device
-    if rotate_base:
-        print('Flipping the SMPL coordinate frame!!!!')
-        rot_x = torch.Tensor([[1, 0, 0], [0, -1, 0], [0, 0, -1]])
-        rot_x = torch.reshape(torch.repeat(rot_x, [N, 1]), [N, 3, 3]) # In tf it was tile
-        root_rotation = torch.matmul(Rs[:, 0, :, :], rot_x)
-    else:
-        root_rotation = Rs[:, 0, :, :]
-
-    # Now Js is N x 24 x 3 x 1
-    Js = Js.unsqueeze(-1)
-    N = Rs.shape[0]
-
-    def make_A(R, t):
-        # Rs is N x 3 x 3, ts is N x 3 x 1
-        R_homo = torch.nn.functional.pad(R, (0,0,0,1,0,0))
-        t_homo = torch.cat([t, torch.ones([N, 1, 1]).to(device=device)], 1)
-        return torch.cat([R_homo, t_homo], 2)
-
-    A0 = make_A(root_rotation, Js[:, 0])
-    results = [A0]
-    for i in range(1, parent.shape[0]):
-        j_here = Js[:, i] - Js[:, parent[i]]
-        A_here = make_A(Rs[:, i], j_here)
-        res_here = torch.matmul(
-            results[parent[i]], A_here)
-        results.append(res_here)
-
-    # 10 x 24 x 4 x 4
-    results = torch.stack(results, dim=1)
-
-    new_J = results[:, :, :3, 3]
-
-    # --- Compute relative A: Skinning is based on
-    # how much the bone moved (not the final location of the bone)
-    # but (final_bone - init_bone)
-    # ---
-    Js_w0 = torch.cat([Js, torch.zeros([N, 35, 1, 1]).to(device=device)], 2)
-    init_bone = torch.matmul(results, Js_w0)
-    # Append empty 4 x 3:
-    init_bone = torch.nn.functional.pad(init_bone, (3,0,0,0,0,0,0,0))
-    A = results - init_bone
-
-    return new_J, A
-
-
-#########################################################################################
-
-def get_bone_length_scales(part_list, betas_logscale):
-    leg_joints = list(range(7,11)) + list(range(11,15)) + list(range(17,21)) + list(range(21,25))
-    front_leg_joints = list(range(7,11)) + list(range(11,15)) 
-    back_leg_joints = list(range(17,21)) + list(range(21,25))
-    tail_joints = list(range(25, 32))
-    ear_joints = [33, 34]
-    neck_joints = [15, 6]      # ?
-    core_joints = [4, 5]      # ?
-    mouth_joints = [16, 32]
-    log_scales = torch.zeros(betas_logscale.shape[0], 35).to(betas_logscale.device)
-    for ind, part in enumerate(part_list):
-        if part == 'legs_l':
-            log_scales[:, leg_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'front_legs_l':
-            log_scales[:, front_leg_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'back_legs_l':
-            log_scales[:, back_leg_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'tail_l':
-            log_scales[:, tail_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'ears_l':            
-            log_scales[:, ear_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'neck_l':
-            log_scales[:, neck_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'core_l':
-            log_scales[:, core_joints] = betas_logscale[:, ind][:, None]
-        elif part == 'head_l':
-            log_scales[:, mouth_joints] = betas_logscale[:, ind][:, None]
-        else:
-            pass
-    all_scales = torch.exp(log_scales)
-    return all_scales[:, 1:]        # don't count root
-
-def get_beta_scale_mask(part_list):
-    # which joints belong to which bodypart
-    leg_joints = list(range(7,11)) + list(range(11,15)) + list(range(17,21)) + list(range(21,25))
-    front_leg_joints = list(range(7,11)) + list(range(11,15)) 
-    back_leg_joints = list(range(17,21)) + list(range(21,25))
-    tail_joints = list(range(25, 32))
-    ear_joints = [33, 34]
-    neck_joints = [15, 6]      # ?
-    core_joints = [4, 5]      # ?
-    mouth_joints = [16, 32]
-    n_b_log = len(part_list)     #betas_logscale.shape[1]   # 8      # 6
-    beta_scale_mask = torch.zeros(35, 3, n_b_log)   # .to(betas_logscale.device)
-    for ind, part in enumerate(part_list):
-        if part == 'legs_l':
-            beta_scale_mask[leg_joints, [2], [ind]] = 1.0 # Leg lengthening
-        elif part == 'legs_f':
-            beta_scale_mask[leg_joints, [0], [ind]] = 1.0 # Leg fatness
-            beta_scale_mask[leg_joints, [1], [ind]] = 1.0 # Leg fatness
-        elif part == 'front_legs_l':
-            beta_scale_mask[front_leg_joints, [2], [ind]] = 1.0 # front Leg lengthening
-        elif part == 'front_legs_f':
-            beta_scale_mask[front_leg_joints, [0], [ind]] = 1.0 # front Leg fatness
-            beta_scale_mask[front_leg_joints, [1], [ind]] = 1.0 # front Leg fatness
-        elif part == 'back_legs_l':
-            beta_scale_mask[back_leg_joints, [2], [ind]] = 1.0 # back Leg lengthening
-        elif part == 'back_legs_f':
-            beta_scale_mask[back_leg_joints, [0], [ind]] = 1.0 # back Leg fatness
-            beta_scale_mask[back_leg_joints, [1], [ind]] = 1.0 # back Leg fatness
-        elif part == 'tail_l':
-            beta_scale_mask[tail_joints, [0], [ind]] = 1.0 # Tail lengthening
-        elif part == 'tail_f':
-            beta_scale_mask[tail_joints, [1], [ind]] = 1.0 # Tail fatness
-            beta_scale_mask[tail_joints, [2], [ind]] = 1.0 # Tail fatness
-        elif part == 'ears_y':            
-            beta_scale_mask[ear_joints, [1], [ind]] = 1.0 # Ear y
-        elif part == 'ears_l':            
-            beta_scale_mask[ear_joints, [2], [ind]] = 1.0 # Ear z
-        elif part == 'neck_l':
-            beta_scale_mask[neck_joints, [0], [ind]] = 1.0 # Neck lengthening
-        elif part == 'neck_f':
-            beta_scale_mask[neck_joints, [1], [ind]] = 1.0 # Neck fatness
-            beta_scale_mask[neck_joints, [2], [ind]] = 1.0 # Neck fatness
-        elif part == 'core_l':
-            beta_scale_mask[core_joints, [0], [ind]] = 1.0 # Core lengthening
-            # beta_scale_mask[core_joints, [1], [ind]] = 1.0 # Core fatness (height)
-        elif part == 'core_fs':
-            beta_scale_mask[core_joints, [2], [ind]] = 1.0 # Core fatness (side)
-        elif part == 'head_l':
-            beta_scale_mask[mouth_joints, [0], [ind]] = 1.0 # Head lengthening
-        elif part == 'head_f':
-            beta_scale_mask[mouth_joints, [1], [ind]] = 1.0 # Head fatness 0
-            beta_scale_mask[mouth_joints, [2], [ind]] = 1.0 # Head fatness 1
-        else:
-            print(part + ' not available')
-            raise ValueError
-    beta_scale_mask = torch.transpose(
-        beta_scale_mask.reshape(35*3, n_b_log), 0, 1)
-    return beta_scale_mask
-
-def batch_global_rigid_transformation_biggs(Rs, Js, parent, scale_factors_3x3, rotate_base = False, betas_logscale=None, opts=None):
-    """
-    Computes absolute joint locations given pose.
-
-    rotate_base: if True, rotates the global rotation by 90 deg in x axis.
-    if False, this is the original SMPL coordinate.
-
-    Args:
-      Rs: N x 24 x 3 x 3 rotation vector of K joints
-      Js: N x 24 x 3, joint locations before posing
-      parent: 24 holding the parent id for each index
-
-    Returns
-      new_J : `Tensor`: N x 24 x 3 location of absolute joints
-      A     : `Tensor`: N x 24 4 x 4 relative joint transformations for LBS.
-    """
-    if rotate_base:
-        print('Flipping the SMPL coordinate frame!!!!')
-        rot_x = torch.Tensor([[1, 0, 0], [0, -1, 0], [0, 0, -1]])
-        rot_x = torch.reshape(torch.repeat(rot_x, [N, 1]), [N, 3, 3]) # In tf it was tile
-        root_rotation = torch.matmul(Rs[:, 0, :, :], rot_x)
-    else:
-        root_rotation = Rs[:, 0, :, :]
-
-    # Now Js is N x 24 x 3 x 1
-    Js = Js.unsqueeze(-1)
-    N = Rs.shape[0]
-
-    Js_orig = Js.clone()
-
-    def make_A(R, t):
-        # Rs is N x 3 x 3, ts is N x 3 x 1
-        R_homo = torch.nn.functional.pad(R, (0,0,0,1,0,0))
-        t_homo = torch.cat([t, torch.ones([N, 1, 1]).to(Rs.device)], 1)
-        return torch.cat([R_homo, t_homo], 2)
-    
-    A0 = make_A(root_rotation, Js[:, 0])
-    results = [A0]
-    for i in range(1, parent.shape[0]):
-        j_here = Js[:, i] - Js[:, parent[i]]
-        try:
-            s_par_inv = torch.inverse(scale_factors_3x3[:, parent[i]])
-        except: 
-            # import pdb; pdb.set_trace()
-            s_par_inv = torch.max(scale_factors_3x3[:, parent[i]],  0.01*torch.eye((3))[None, :, :].to(scale_factors_3x3.device))
-        rot = Rs[:, i]
-        s = scale_factors_3x3[:, i]
-        
-        rot_new = s_par_inv @ rot @ s
-
-        A_here = make_A(rot_new, j_here)
-        res_here = torch.matmul(
-            results[parent[i]], A_here)
-        
-        results.append(res_here)
-
-    # 10 x 24 x 4 x 4
-    results = torch.stack(results, dim=1)
-
-    # scale updates
-    new_J = results[:, :, :3, 3]
-
-    # --- Compute relative A: Skinning is based on
-    # how much the bone moved (not the final location of the bone)
-    # but (final_bone - init_bone)
-    # ---
-    Js_w0 = torch.cat([Js_orig, torch.zeros([N, 35, 1, 1]).to(Rs.device)], 2)
-    init_bone = torch.matmul(results, Js_w0)
-    # Append empty 4 x 3:
-    init_bone = torch.nn.functional.pad(init_bone, (3,0,0,0,0,0,0,0))
-    A = results - init_bone
-
-    return new_J, A
\ No newline at end of file
diff --git a/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/__init__.py b/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/__init__.py
deleted file mode 100644
index 0615f983ad266d667157109092f916e49a70e4c4..0000000000000000000000000000000000000000
--- a/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from training.tacotron2_model.model import Tacotron2  # noqa
-from training.tacotron2_model.loss import Tacotron2Loss  # noqa
-from training.tacotron2_model.collate import TextMelCollate  # noqa
-from training.tacotron2_model.stft import TacotronSTFT  # noqa
diff --git a/spaces/russellc/BLIP/eval_nocaps.py b/spaces/russellc/BLIP/eval_nocaps.py
deleted file mode 100644
index 3cbb09a8cc7771605c013583d721aa95d9413b42..0000000000000000000000000000000000000000
--- a/spaces/russellc/BLIP/eval_nocaps.py
+++ /dev/null
@@ -1,118 +0,0 @@
-'''
- * Copyright (c) 2022, salesforce.com, inc.
- * All rights reserved.
- * SPDX-License-Identifier: BSD-3-Clause
- * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
- * By Junnan Li
-'''
-import argparse
-import os
-import ruamel_yaml as yaml
-import numpy as np
-import random
-import time
-import datetime
-import json
-from pathlib import Path
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.backends.cudnn as cudnn
-import torch.distributed as dist
-from torch.utils.data import DataLoader
-
-from models.blip import blip_decoder
-import utils
-from data import create_dataset, create_sampler, create_loader
-from data.utils import save_result
-
-@torch.no_grad()
-def evaluate(model, data_loader, device, config):
-    # evaluate
-    model.eval() 
-    
-    metric_logger = utils.MetricLogger(delimiter="  ")
-    header = 'Evaluation:'
-    print_freq = 10
-
-    result = []
-    for image, image_id in metric_logger.log_every(data_loader, print_freq, header): 
-        
-        image = image.to(device)       
-        
-        captions = model.generate(image, sample=False, num_beams=config['num_beams'], max_length=config['max_length'], 
-                                  min_length=config['min_length'], repetition_penalty=1.1)
-        
-        for caption, img_id in zip(captions, image_id):
-            result.append({"image_id": img_id.item(), "caption": caption})
-  
-    return result
-
-
-def main(args, config):
-    utils.init_distributed_mode(args)    
-    
-    device = torch.device(args.device)
-
-    # fix the seed for reproducibility
-    seed = args.seed + utils.get_rank()
-    torch.manual_seed(seed)
-    np.random.seed(seed)
-    random.seed(seed)
-    cudnn.benchmark = True
-
-    #### Dataset #### 
-    print("Creating captioning dataset")
-    val_dataset, test_dataset = create_dataset('nocaps', config)  
-
-    if args.distributed:
-        num_tasks = utils.get_world_size()
-        global_rank = utils.get_rank()            
-        samplers = create_sampler([val_dataset,test_dataset], [False,False], num_tasks, global_rank)         
-    else:
-        samplers = [None,None]
-    
-    val_loader, test_loader = create_loader([val_dataset, test_dataset],samplers, 
-                                            batch_size=[config['batch_size']]*2,num_workers=[4,4],
-                                            is_trains=[False, False], collate_fns=[None,None])        
-
-    #### Model #### 
-    print("Creating model")
-    model = blip_decoder(pretrained=config['pretrained'], image_size=config['image_size'], vit=config['vit'], 
-                           prompt=config['prompt'])
-
-    model = model.to(device)   
-    
-    model_without_ddp = model
-    if args.distributed:
-        model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.gpu])
-        model_without_ddp = model.module    
-    
-    val_result = evaluate(model_without_ddp, val_loader, device, config)  
-    val_result_file = save_result(val_result, args.result_dir, 'val', remove_duplicate='image_id')   
-    test_result = evaluate(model_without_ddp, test_loader, device, config)  
-    test_result_file = save_result(test_result, args.result_dir, 'test', remove_duplicate='image_id') 
-
-
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--config', default='./configs/nocaps.yaml')
-    parser.add_argument('--output_dir', default='output/NoCaps')        
-    parser.add_argument('--device', default='cuda')
-    parser.add_argument('--seed', default=42, type=int)
-    parser.add_argument('--world_size', default=1, type=int, help='number of distributed processes')    
-    parser.add_argument('--dist_url', default='env://', help='url used to set up distributed training')
-    parser.add_argument('--distributed', default=True, type=bool)
-    args = parser.parse_args()
-
-    config = yaml.load(open(args.config, 'r'), Loader=yaml.Loader)
-
-    args.result_dir = os.path.join(args.output_dir, 'result')
-
-    Path(args.output_dir).mkdir(parents=True, exist_ok=True)
-    Path(args.result_dir).mkdir(parents=True, exist_ok=True)
-        
-    yaml.dump(config, open(os.path.join(args.output_dir, 'config.yaml'), 'w'))    
-    
-    main(args, config)
\ No newline at end of file
diff --git a/spaces/sayakpaul/sots-indoor-dehazing-maxim/README.md b/spaces/sayakpaul/sots-indoor-dehazing-maxim/README.md
deleted file mode 100644
index cb976b321b85701395397ad37229204d9a2b8ae8..0000000000000000000000000000000000000000
--- a/spaces/sayakpaul/sots-indoor-dehazing-maxim/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Sots Indoor Dehazing MAXIM
-emoji: 💻
-colorFrom: blue
-colorTo: blue
-sdk: gradio
-sdk_version: 3.5
-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/senquan/ChuanhuChatGPT/run_macOS.command b/spaces/senquan/ChuanhuChatGPT/run_macOS.command
deleted file mode 100644
index 62af07283093d8e580763d7acfe493c3d88e7b08..0000000000000000000000000000000000000000
--- a/spaces/senquan/ChuanhuChatGPT/run_macOS.command
+++ /dev/null
@@ -1,25 +0,0 @@
-#!/bin/bash
-
-# 获取脚本所在目录
-script_dir=$(dirname "$0")
-
-# 将工作目录更改为脚本所在目录
-cd "$script_dir"
-
-# 检查Git仓库是否有更新
-git remote update
-pwd
-
-if ! git status -uno | grep 'up to date' > /dev/null; then
-	# 如果有更新，关闭当前运行的服务器
-	pkill -f ChuanhuChatbot.py
-
-	# 拉取最新更改
-	git pull
-
-	# 安装依赖
-	pip3 install -r requirements.txt
-
-	# 重新启动服务器
-	nohup python3 ChuanhuChatbot.py &
-fi
diff --git a/spaces/seyia92coding/Popular_Spotify_Albums/README.md b/spaces/seyia92coding/Popular_Spotify_Albums/README.md
deleted file mode 100644
index 971a69462109aaa54ff17709615b1f9d45ca9761..0000000000000000000000000000000000000000
--- a/spaces/seyia92coding/Popular_Spotify_Albums/README.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-title: Popular_Spotify_Albums
-emoji: 📈
-colorFrom: indigo
-colorTo: gray
-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` or `streamlit`
-
-`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).  
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_  
-Whether the Space stays on top of your list.
diff --git a/spaces/shencc/gpt/Dockerfile b/spaces/shencc/gpt/Dockerfile
deleted file mode 100644
index da5053dbc7fc0accbd7b10fab87ca72feced8fe8..0000000000000000000000000000000000000000
--- a/spaces/shencc/gpt/Dockerfile
+++ /dev/null
@@ -1,20 +0,0 @@
-# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
-# 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic .
-# 如何运行: docker run --rm -it --net=host gpt-academic
-FROM python:3.11
-
-RUN echo '[global]' > /etc/pip.conf && \
-    echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
-    echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
-
-
-WORKDIR /gpt
-COPY requirements.txt .
-RUN pip3 install -r requirements.txt
-
-COPY . .
-
-# 可选步骤，用于预热模块
-RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
-
-CMD ["python3", "-u", "main.py"]
diff --git a/spaces/sheraznaseer/test_pdfqa_2304/Dockerfile b/spaces/sheraznaseer/test_pdfqa_2304/Dockerfile
deleted file mode 100644
index afacbdfa0fa071c4d2a2982b9649d638d34bb59c..0000000000000000000000000000000000000000
--- a/spaces/sheraznaseer/test_pdfqa_2304/Dockerfile
+++ /dev/null
@@ -1,12 +0,0 @@
-FROM python:3.9
-
-WORKDIR /code
-
-COPY ./requirements.txt /code/requirements.txt
-
-RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
-
-COPY . .
-
-#CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
-CMD ["panel", "serve", "/code/app.py", "--address", "0.0.0.0","--port", "7860", "--allow-websocket-origin","sheraznaseer-test-pdfqa-2304.hf.space"]
\ No newline at end of file
diff --git a/spaces/shiwan10000/CodeFormer/CodeFormer/basicsr/archs/arcface_arch.py b/spaces/shiwan10000/CodeFormer/CodeFormer/basicsr/archs/arcface_arch.py
deleted file mode 100644
index fe5afb7bd2b359e0c2b7efdf628ab10b63964d87..0000000000000000000000000000000000000000
--- a/spaces/shiwan10000/CodeFormer/CodeFormer/basicsr/archs/arcface_arch.py
+++ /dev/null
@@ -1,245 +0,0 @@
-import torch.nn as nn
-from basicsr.utils.registry import ARCH_REGISTRY
-
-
-def conv3x3(inplanes, outplanes, stride=1):
-    """A simple wrapper for 3x3 convolution with padding.
-
-    Args:
-        inplanes (int): Channel number of inputs.
-        outplanes (int): Channel number of outputs.
-        stride (int): Stride in convolution. Default: 1.
-    """
-    return nn.Conv2d(inplanes, outplanes, kernel_size=3, stride=stride, padding=1, bias=False)
-
-
-class BasicBlock(nn.Module):
-    """Basic residual block used in the ResNetArcFace architecture.
-
-    Args:
-        inplanes (int): Channel number of inputs.
-        planes (int): Channel number of outputs.
-        stride (int): Stride in convolution. Default: 1.
-        downsample (nn.Module): The downsample module. Default: None.
-    """
-    expansion = 1  # output channel expansion ratio
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None):
-        super(BasicBlock, self).__init__()
-        self.conv1 = conv3x3(inplanes, planes, stride)
-        self.bn1 = nn.BatchNorm2d(planes)
-        self.relu = nn.ReLU(inplace=True)
-        self.conv2 = conv3x3(planes, planes)
-        self.bn2 = nn.BatchNorm2d(planes)
-        self.downsample = downsample
-        self.stride = stride
-
-    def forward(self, x):
-        residual = x
-
-        out = self.conv1(x)
-        out = self.bn1(out)
-        out = self.relu(out)
-
-        out = self.conv2(out)
-        out = self.bn2(out)
-
-        if self.downsample is not None:
-            residual = self.downsample(x)
-
-        out += residual
-        out = self.relu(out)
-
-        return out
-
-
-class IRBlock(nn.Module):
-    """Improved residual block (IR Block) used in the ResNetArcFace architecture.
-
-    Args:
-        inplanes (int): Channel number of inputs.
-        planes (int): Channel number of outputs.
-        stride (int): Stride in convolution. Default: 1.
-        downsample (nn.Module): The downsample module. Default: None.
-        use_se (bool): Whether use the SEBlock (squeeze and excitation block). Default: True.
-    """
-    expansion = 1  # output channel expansion ratio
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None, use_se=True):
-        super(IRBlock, self).__init__()
-        self.bn0 = nn.BatchNorm2d(inplanes)
-        self.conv1 = conv3x3(inplanes, inplanes)
-        self.bn1 = nn.BatchNorm2d(inplanes)
-        self.prelu = nn.PReLU()
-        self.conv2 = conv3x3(inplanes, planes, stride)
-        self.bn2 = nn.BatchNorm2d(planes)
-        self.downsample = downsample
-        self.stride = stride
-        self.use_se = use_se
-        if self.use_se:
-            self.se = SEBlock(planes)
-
-    def forward(self, x):
-        residual = x
-        out = self.bn0(x)
-        out = self.conv1(out)
-        out = self.bn1(out)
-        out = self.prelu(out)
-
-        out = self.conv2(out)
-        out = self.bn2(out)
-        if self.use_se:
-            out = self.se(out)
-
-        if self.downsample is not None:
-            residual = self.downsample(x)
-
-        out += residual
-        out = self.prelu(out)
-
-        return out
-
-
-class Bottleneck(nn.Module):
-    """Bottleneck block used in the ResNetArcFace architecture.
-
-    Args:
-        inplanes (int): Channel number of inputs.
-        planes (int): Channel number of outputs.
-        stride (int): Stride in convolution. Default: 1.
-        downsample (nn.Module): The downsample module. Default: None.
-    """
-    expansion = 4  # output channel expansion ratio
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None):
-        super(Bottleneck, self).__init__()
-        self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False)
-        self.bn1 = nn.BatchNorm2d(planes)
-        self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
-        self.bn2 = nn.BatchNorm2d(planes)
-        self.conv3 = nn.Conv2d(planes, planes * self.expansion, kernel_size=1, bias=False)
-        self.bn3 = nn.BatchNorm2d(planes * self.expansion)
-        self.relu = nn.ReLU(inplace=True)
-        self.downsample = downsample
-        self.stride = stride
-
-    def forward(self, x):
-        residual = x
-
-        out = self.conv1(x)
-        out = self.bn1(out)
-        out = self.relu(out)
-
-        out = self.conv2(out)
-        out = self.bn2(out)
-        out = self.relu(out)
-
-        out = self.conv3(out)
-        out = self.bn3(out)
-
-        if self.downsample is not None:
-            residual = self.downsample(x)
-
-        out += residual
-        out = self.relu(out)
-
-        return out
-
-
-class SEBlock(nn.Module):
-    """The squeeze-and-excitation block (SEBlock) used in the IRBlock.
-
-    Args:
-        channel (int): Channel number of inputs.
-        reduction (int): Channel reduction ration. Default: 16.
-    """
-
-    def __init__(self, channel, reduction=16):
-        super(SEBlock, self).__init__()
-        self.avg_pool = nn.AdaptiveAvgPool2d(1)  # pool to 1x1 without spatial information
-        self.fc = nn.Sequential(
-            nn.Linear(channel, channel // reduction), nn.PReLU(), nn.Linear(channel // reduction, channel),
-            nn.Sigmoid())
-
-    def forward(self, x):
-        b, c, _, _ = x.size()
-        y = self.avg_pool(x).view(b, c)
-        y = self.fc(y).view(b, c, 1, 1)
-        return x * y
-
-
-@ARCH_REGISTRY.register()
-class ResNetArcFace(nn.Module):
-    """ArcFace with ResNet architectures.
-
-    Ref: ArcFace: Additive Angular Margin Loss for Deep Face Recognition.
-
-    Args:
-        block (str): Block used in the ArcFace architecture.
-        layers (tuple(int)): Block numbers in each layer.
-        use_se (bool): Whether use the SEBlock (squeeze and excitation block). Default: True.
-    """
-
-    def __init__(self, block, layers, use_se=True):
-        if block == 'IRBlock':
-            block = IRBlock
-        self.inplanes = 64
-        self.use_se = use_se
-        super(ResNetArcFace, self).__init__()
-
-        self.conv1 = nn.Conv2d(1, 64, kernel_size=3, padding=1, bias=False)
-        self.bn1 = nn.BatchNorm2d(64)
-        self.prelu = nn.PReLU()
-        self.maxpool = nn.MaxPool2d(kernel_size=2, stride=2)
-        self.layer1 = self._make_layer(block, 64, layers[0])
-        self.layer2 = self._make_layer(block, 128, layers[1], stride=2)
-        self.layer3 = self._make_layer(block, 256, layers[2], stride=2)
-        self.layer4 = self._make_layer(block, 512, layers[3], stride=2)
-        self.bn4 = nn.BatchNorm2d(512)
-        self.dropout = nn.Dropout()
-        self.fc5 = nn.Linear(512 * 8 * 8, 512)
-        self.bn5 = nn.BatchNorm1d(512)
-
-        # initialization
-        for m in self.modules():
-            if isinstance(m, nn.Conv2d):
-                nn.init.xavier_normal_(m.weight)
-            elif isinstance(m, nn.BatchNorm2d) or isinstance(m, nn.BatchNorm1d):
-                nn.init.constant_(m.weight, 1)
-                nn.init.constant_(m.bias, 0)
-            elif isinstance(m, nn.Linear):
-                nn.init.xavier_normal_(m.weight)
-                nn.init.constant_(m.bias, 0)
-
-    def _make_layer(self, block, planes, num_blocks, stride=1):
-        downsample = None
-        if stride != 1 or self.inplanes != planes * block.expansion:
-            downsample = nn.Sequential(
-                nn.Conv2d(self.inplanes, planes * block.expansion, kernel_size=1, stride=stride, bias=False),
-                nn.BatchNorm2d(planes * block.expansion),
-            )
-        layers = []
-        layers.append(block(self.inplanes, planes, stride, downsample, use_se=self.use_se))
-        self.inplanes = planes
-        for _ in range(1, num_blocks):
-            layers.append(block(self.inplanes, planes, use_se=self.use_se))
-
-        return nn.Sequential(*layers)
-
-    def forward(self, x):
-        x = self.conv1(x)
-        x = self.bn1(x)
-        x = self.prelu(x)
-        x = self.maxpool(x)
-
-        x = self.layer1(x)
-        x = self.layer2(x)
-        x = self.layer3(x)
-        x = self.layer4(x)
-        x = self.bn4(x)
-        x = self.dropout(x)
-        x = x.view(x.size(0), -1)
-        x = self.fc5(x)
-        x = self.bn5(x)
-
-        return x
\ No newline at end of file
diff --git a/spaces/simonduerr/metal3d/app.py b/spaces/simonduerr/metal3d/app.py
deleted file mode 100644
index bfddce0280ccb880de018feb706d2c8aa7629bf2..0000000000000000000000000000000000000000
--- a/spaces/simonduerr/metal3d/app.py
+++ /dev/null
@@ -1,403 +0,0 @@
-import gradio as gr
-
-import urllib
-import re
-import sys
-import warnings
-
-import torch
-import torch.nn as nn
-import ipywidgets as widgets
-from ipywidgets import interact, fixed
-
-from utils.helpers import *
-from utils.voxelization import processStructures
-from utils.model import Model
-import numpy as np
-
-import os
-import moleculekit
-
-print(moleculekit.__version__)
-
-
-def update(inp, file, mode, custom_resids, clustering_threshold, distance_cutoff):
-    try:
-        filepath = file.name
-    except:
-        print("using pdbfile")
-        try:
-            pdb_file = inp
-            if (
-                re.match(
-                    "[OPQ][0-9][A-Z0-9]{3}[0-9]|[A-NR-Z][0-9]([A-Z][A-Z0-9]{2}[0-9]){1,2}",
-                    pdb_file,
-                ).group()
-                == pdb_file
-            ):
-                urllib.request.urlretrieve(
-                    f"https://alphafold.ebi.ac.uk/files/AF-{pdb_file}-F1-model_v2.pdb",
-                    f"files/{pdb_file}.pdb",
-                )
-            filepath = f"files/{pdb_file}.pdb"
-        except AttributeError:
-            if len(inp) == 4:
-                pdb_file = inp
-                urllib.request.urlretrieve(
-                    f"http://files.rcsb.org/download/{pdb_file.lower()}.pdb1",
-                    f"files/{pdb_file}.pdb",
-                )
-                filepath = f"files/{pdb_file}.pdb"
-            else:
-                return "pdb code must be 4 letters or Uniprot code does not match", ""
-    identifier = os.path.basename(filepath)
-    if mode == "All residues":
-        print("using all residues")
-        ids = get_all_protein_resids(filepath)
-    elif len(custom_resids) != 0:
-        print("using listed residues", custom_resids)
-        ids = get_all_resids_from_list(filepath, custom_resids.replace(",", " "))
-    else:
-        print("using metalbinding")
-        ids = get_all_metalbinding_resids(filepath)
-    print(filepath)
-    print(ids)
-    try:
-        voxels, prot_centers, prot_N, prots = processStructures(filepath, ids)
-    except Exception as e:
-        print(e)
-        return (
-            "Error",
-            f"""<div class="text-center mt-4"> Something went wrong with the voxelization, reset custom residues and other input fiels and check error message <br> <br> <code>{e}</code></div>""",
-        )
-    
-    voxels.to(device)
-
-    with warnings.catch_warnings():
-        warnings.filterwarnings("ignore")
-        output = model(voxels)
-    print(output.shape)
-    prot_v = np.vstack(prot_centers)
-    output_v = output.flatten().cpu().detach().numpy()
-    bb = get_bb(prot_v)
-    gridres = 0.5
-    grid, box_N = create_grid_fromBB(bb, voxelSize=gridres)
-    probability_values = get_probability_mean(grid, prot_v, output_v)
-    print(probability_values.shape)
-    write_cubefile(
-        bb,
-        probability_values,
-        box_N,
-        outname=f"output/metal_{identifier}.cube",
-        gridres=gridres,
-    )
-    message = find_unique_sites(
-        probability_values,
-        grid,
-        writeprobes=True,
-        probefile=f"output/probes_{identifier}.pdb",
-        threshold=distance_cutoff,
-        p=clustering_threshold,
-    )
-    del voxels
-    torch.cuda.empty_cache()
-    return message, molecule(
-        filepath,
-        f"output/probes_{identifier}.pdb",
-        f"output/metal_{identifier}.cube",
-    )
-
-
-def read_mol(molpath):
-    with open(molpath, "r") as fp:
-        lines = fp.readlines()
-    mol = ""
-    for l in lines:
-        mol += l
-    return mol
-
-
-def molecule(pdb, probes, cube):
-    mol = read_mol(pdb)
-    probes = read_mol(probes)
-    cubefile = read_mol(cube)
-    x = (
-        """<!DOCTYPE html>
-        <html>
-        <head>    
-    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
-          
-     <link rel="stylesheet" href="https://unpkg.com/flowbite@1.4.5/dist/flowbite.min.css" />
-    <style>
-    body{
-        font-family:sans-serif
-    }
-.mol-container {
-  width: 100%;
-  height: 600px;
-  position: relative;
-}
-.slider{
-    width:80%;
-    margin:0 auto
-}
-.slidercontainer{
-    display:flex;
-}
-.slidercontainer > * + * {
-    margin-left: 0.5rem;
-}
-#isovalue{
- text-align:right}
-</style>
-  <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.6.3/jquery.min.js" integrity="sha512-STof4xm1wgkfm7heWqFJVn58Hm3EtS31XFaagaa8VMReCXAkQnJZ+jEy8PCC/iT18dFy95WcExNHFTqLyp72eQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
-
-<script src="https://3Dmol.csb.pitt.edu/build/3Dmol-min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/rangeslider.js/2.3.3/rangeslider.min.js" integrity="sha512-BUlWdwDeJo24GIubM+z40xcj/pjw7RuULBkxOTc+0L9BaGwZPwiwtbiSVzv31qR7TWx7bs6OPTE5IyfLOorboQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>
-    </head>
-    <body>  
-    <div class="slidercontainer my-8">
-    <span>Isovalue </span>
-    <span id="isovalue">0.5</span>
-    <input class="slider text-blue-400" type="range" id="rangeslider" min="0" max="1" step="0.05" value=0.5>
-    </div>
-    
-    <div id="container" class="mol-container"></div>
-
-     <div class="flex items-center justify-center my-4">
-        <div class="px-4">
-        <label for="sidechain" class="relative inline-flex items-center mb-4 cursor-pointer ">
-            <input  id="sidechain"type="checkbox" class="sr-only peer">
-            <div class="w-11 h-6 bg-gray-200 rounded-full peer peer-focus:ring-4 peer-focus:ring-blue-300 dark:peer-focus:ring-blue-800 dark:bg-gray-700 peer-checked:after:translate-x-full peer-checked:after:border-white after:absolute after:top-0.5 after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all dark:border-gray-600 peer-checked:bg-blue-600"></div>
-            <span class="ml-3 text-sm font-medium text-gray-900 dark:text-gray-300">Show side chains</span>
-          </label>
-        </div>
-        <div class="px-4">
-        <label for="pdbmetal" class="relative inline-flex items-center mb-4 cursor-pointer ">
-            <input  id="pdbmetal" type="checkbox" class="sr-only peer">
-            <div class="w-11 h-6 bg-gray-200 rounded-full peer peer-focus:ring-4 peer-focus:ring-blue-300 dark:peer-focus:ring-blue-800 dark:bg-gray-700 peer-checked:after:translate-x-full peer-checked:after:border-white after:absolute after:top-0.5 after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all dark:border-gray-600 peer-checked:bg-blue-600"></div>
-            <span class="ml-3 text-sm font-medium text-gray-900 dark:text-gray-300">Show PDB metals</span>
-          </label>
-        </div>
-        <div class="px-4">
-        <label for="probes" class="relative inline-flex items-center mb-4 cursor-pointer ">
-            <input  id="probes" type="checkbox" class="sr-only peer" checked>
-            <div class="w-11 h-6 bg-gray-200 rounded-full peer peer-focus:ring-4 peer-focus:ring-blue-300 dark:peer-focus:ring-blue-800 dark:bg-gray-700 peer-checked:after:translate-x-full peer-checked:after:border-white after:absolute after:top-0.5 after:left-[2px] after:bg-white after:border-gray-300 after:border after:rounded-full after:h-5 after:w-5 after:transition-all dark:border-gray-600 peer-checked:bg-blue-600"></div>
-            <span class="ml-3 text-sm font-medium text-gray-900 dark:text-gray-300">Show Probes</span>
-          </label>
-        </div>
-        </div>  
-        
-     <div class="flex items-center justify-center my-4">
- <button type="button" class="text-gray-900 bg-white hover:bg-gray-100 border border-gray-200 focus:ring-4 focus:outline-none focus:ring-gray-100 font-medium rounded-lg text-sm px-5 py-2.5 text-center inline-flex items-center dark:focus:ring-gray-600 dark:bg-gray-800 dark:border-gray-700 dark:text-white dark:hover:bg-gray-700 mr-2 mb-2" id="download">
-                    <svg class="w-6 h-6 mr-2 -ml-1" fill="none" stroke="currentColor" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"></path></svg>
-                    Download predictions
-                  </button>
-              </div>
-            <script>
-            let viewer = null;
-            let voldata = null;
-            let shape = null;
-            let sidechain = null;
-            let metal = null;
-            $(document).ready(function () {
-                let element = $("#container");
-                let config = { backgroundColor: "white" };
-                viewer = $3Dmol.createViewer( element, config );
-                viewer.ui.initiateUI();
-                let data = `"""
-        + mol
-        + """`
-                viewer.addModel( data, "pdb" );
-                
-                let cubefile = `"""
-        + cubefile
-        + """`
-                voldata = new $3Dmol.VolumeData(cubefile, "cube");
-                shape = viewer.addIsosurface(voldata, { isoval: 0.5 , color: "blue", alpha: 0.85, smoothness: 1 });
-                viewer.getModel(0).setStyle({}, {cartoon: {}}); 
-                let probes =`"""
-        + probes
-        + """`
-                viewer.addModel(probes, "pdb");
-                viewer.getModel(1).setStyle({ "resn": "ZN" }, { "sphere": { }});
-                viewer.getModel(1).setHoverable({}, true,
-                    function (atom, viewer, event, container) {
-                        if (!atom.label) {
-                            atom.label = viewer.addLabel("ZN p=" + atom.pdbline.substring(55, 60), { position: atom, backgroundColor: "mintcream", fontColor: "black" });
-                        }
-                    },
-                    function (atom, viewer) {
-                        if (atom.label) {
-                            viewer.removeLabel(atom.label);
-                            delete atom.label;
-                        }
-                    }
-                );
-                viewer.zoomTo();
-                viewer.render();
-                viewer.zoom(0.8, 2000);
-
-                $("#sidechain").change(function () {
-                    if (this.checked) {
-                        BB = ["C", "O", "N"]
-                        viewer.getModel(0).setStyle( {"and": [{resn: ["GLY", "PRO"], invert: true},{atom: BB, invert: true},]},{stick: {hidden:false, colorscheme: "WhiteCarbon", radius: 0.3}, cartoon: {}});
-                        viewer.render()
-                         $("#pdbmetal").prop( "checked", false );
-                    } else {
-                        BB = ["C", "O", "N"]
-                        viewer.getModel(0).setStyle({"and": [{resn: ["GLY", "PRO"], invert: true},{atom: BB, invert: true},]},{stick: {colorscheme: "WhiteCarbon",hidden:true, radius: 0.3}, cartoon: {}});
-                        viewer.render()
-                         $("#pdbmetal").prop( "checked", false );
-                    }
-                   
-                });
-                 $("#pdbmetal").change(function () {
-                    if (this.checked) {
-                        viewer.getModel(0).setStyle({ "resn": ["ZN","MG","NA","FE", "NI","MN","CA", "CU", "CU1"] }, { "sphere": {hidden:false}});
-                        viewer.render()
-                    } else {
-                        viewer.getModel(0).setStyle({ "resn": ["ZN","MG","NA","FE","NI", "MN","CA", "CU", "CU1"] }, { "sphere": {hidden:true}});
-                        viewer.render()
-                    }
-                });
-                $("#probes").change(function () {
-                    if (this.checked) {
-                        viewer.getModel(1).setStyle({ "resn": "ZN" }, { "sphere": { }});
-                        viewer.addStyle()
-                        viewer.render()
-                    } else {
-                        viewer.getModel(1).setStyle({});
-                        viewer.render()
-                    }
-                });
-
-                  $("#download").click(function () {
-                    download("protein.pdb", data);
-                    download("metaldensity.cube", cubefile);
-                    download("probes.pdb", probes);
-                })
-
-        });
-
-         function download(filename, text) {
-            var element = document.createElement("a");
-            element.setAttribute("href", "data:text/plain;charset=utf-8," + encodeURIComponent(text));
-            element.setAttribute("download", filename);
-
-            element.style.display = "none";
-            document.body.appendChild(element);
-
-            element.click();
-
-            document.body.removeChild(element);
-        }
-
-        </script>
-         <script>
-         $("#rangeslider").rangeslider().on("change", function (el) {
-                isoval = parseFloat(el.target.value);
-                $("#isovalue").text(el.target.value)
-                console.log("Change isosurface to "+el.target.value)
-                viewer.removeShape(shape)
-                shape=viewer.addIsosurface(voldata, { isoval: parseFloat(el.target.value), color: "blue", alpha: 0.85, smoothness: 1 });
-                
-                viewer.render();
-            });
-            </script>
-        </body></html>"""
-    )
-
-    return f"""<iframe style="width: 100%; height: 1000px" name="result" allow="midi; geolocation; microphone; camera; 
-    display-capture; encrypted-media;" sandbox="allow-modals allow-forms 
-    allow-scripts allow-same-origin allow-popups 
-    allow-top-navigation-by-user-activation allow-downloads" allowfullscreen="" 
-    allowpaymentrequest="" frameborder="0" srcdoc='{x}'></iframe>"""
-
-
-def set_examples(example):
-    n, code, resids = example
-    return [n, code, resids]
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model = Model()
-model.to(device)
-model.load_state_dict(
-    torch.load(
-        "weights/metal_0.5A_v3_d0.2_16Abox.pth",
-        map_location=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
-    )
-)
-model.eval()
-    
-metal3d = gr.Blocks()
-
-with metal3d:
-    gr.Markdown("# Metal3D")
-    gr.Markdown(
-    """ <em>Inference using CPU-only, can be quite slow for more than 20 residues. Use [Colab notebook](https://colab.research.google.com/github/lcbc-epfl/metal-site-prediction/blob/main/Metal3D/ColabMetal.ipynb) for GPU acceleration or use the docker image locally </em>
-        <small><code>docker run -it -p 7860:7860 --platform=linux/amd64 registry.hf.space/simonduerr-metal3d:latest python app.py</code></small>
-    """
-    )
-    with gr.Tabs():
-        with gr.TabItem("Input"):
-            inp = gr.Textbox(
-                placeholder="PDB Code or Uniprot identifier or upload file below",
-                label="Input molecule",
-            )
-            file = gr.File(file_count="single", type="file")
-
-        with gr.TabItem("Settings"):
-            with gr.Row():
-                mode = gr.Radio(
-                    ["All metalbinding residues (ASP, CYS, GLU, HIS)", "All residues"],
-                    label="Residues to use for prediction",
-                )
-                custom_resids = gr.Textbox(
-                    placeholder="Comma separated list of residues",
-                    label="Custom residues",
-                )
-            with gr.Row():
-                clustering_threshold = gr.Slider(
-                    minimum=0.15,
-                    maximum=1,
-                    value=0.15,
-                    step=0.05,
-                    label="Clustering threshold",
-                )
-                distance_cutoff = gr.Slider(
-                    minimum=1,
-                    maximum=10,
-                    value=7,
-                    step=0.5,
-                    label="Clustering distance cutoff",
-                )
-        btn = gr.Button("Run")
-    n = gr.Textbox(label="Label", visible=False)
-    examples = gr.Dataset(
-        components=[n, inp, custom_resids],
-        samples=[
-            ["HCA2", "2CBA", ""],
-            ["Nickel in GB1 dimer", "6F5N", ""],
-            ["Zebrafish palmitoyltransferase ZDHHC15B PDB", "6BMS", ""],
-            [
-                "Human palmitoyltransferase ZDHHC23 AlphaFold",
-                "Q8IYP9",
-                "280,273,263,260,274,277,274,287",
-            ],
-        ],
-    )
-    examples.click(fn=set_examples, inputs=examples, outputs=examples.components)
-
-
-    gr.Markdown("# Output")
-
-    out = gr.Textbox(label="status")
-    mol = gr.HTML()
-    btn.click(
-        fn=update,
-        inputs=[inp, file, mode, custom_resids, clustering_threshold, distance_cutoff],
-        outputs=[out, mol],
-    )
-
-metal3d.launch()
diff --git a/spaces/simpie28/VITS-Umamusume-voice-synthesizer/attentions.py b/spaces/simpie28/VITS-Umamusume-voice-synthesizer/attentions.py
deleted file mode 100644
index 86bc73b5fe98cc7b443e9078553920346c996707..0000000000000000000000000000000000000000
--- a/spaces/simpie28/VITS-Umamusume-voice-synthesizer/attentions.py
+++ /dev/null
@@ -1,300 +0,0 @@
-import math
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import commons
-from modules import LayerNorm
-   
-
-class Encoder(nn.Module):
-  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4, **kwargs):
-    super().__init__()
-    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.window_size = window_size
-
-    self.drop = nn.Dropout(p_dropout)
-    self.attn_layers = nn.ModuleList()
-    self.norm_layers_1 = nn.ModuleList()
-    self.ffn_layers = nn.ModuleList()
-    self.norm_layers_2 = nn.ModuleList()
-    for i in range(self.n_layers):
-      self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size))
-      self.norm_layers_1.append(LayerNorm(hidden_channels))
-      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout))
-      self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-  def forward(self, x, x_mask):
-    attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-    x = x * x_mask
-    for i in range(self.n_layers):
-      y = self.attn_layers[i](x, x, attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_1[i](x + y)
-
-      y = self.ffn_layers[i](x, x_mask)
-      y = self.drop(y)
-      x = self.norm_layers_2[i](x + y)
-    x = x * x_mask
-    return x
-
-
-class Decoder(nn.Module):
-  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs):
-    super().__init__()
-    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.proximal_bias = proximal_bias
-    self.proximal_init = proximal_init
-
-    self.drop = nn.Dropout(p_dropout)
-    self.self_attn_layers = nn.ModuleList()
-    self.norm_layers_0 = nn.ModuleList()
-    self.encdec_attn_layers = nn.ModuleList()
-    self.norm_layers_1 = nn.ModuleList()
-    self.ffn_layers = nn.ModuleList()
-    self.norm_layers_2 = nn.ModuleList()
-    for i in range(self.n_layers):
-      self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init))
-      self.norm_layers_0.append(LayerNorm(hidden_channels))
-      self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout))
-      self.norm_layers_1.append(LayerNorm(hidden_channels))
-      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
-      self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-  def forward(self, x, x_mask, h, h_mask):
-    """
-    x: decoder input
-    h: encoder output
-    """
-    self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
-    encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-    x = x * x_mask
-    for i in range(self.n_layers):
-      y = self.self_attn_layers[i](x, x, self_attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_0[i](x + y)
-
-      y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_1[i](x + y)
-      
-      y = self.ffn_layers[i](x, x_mask)
-      y = self.drop(y)
-      x = self.norm_layers_2[i](x + y)
-    x = x * x_mask
-    return x
-
-
-class MultiHeadAttention(nn.Module):
-  def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False):
-    super().__init__()
-    assert channels % n_heads == 0
-
-    self.channels = channels
-    self.out_channels = out_channels
-    self.n_heads = n_heads
-    self.p_dropout = p_dropout
-    self.window_size = window_size
-    self.heads_share = heads_share
-    self.block_length = block_length
-    self.proximal_bias = proximal_bias
-    self.proximal_init = proximal_init
-    self.attn = None
-
-    self.k_channels = channels // n_heads
-    self.conv_q = nn.Conv1d(channels, channels, 1)
-    self.conv_k = nn.Conv1d(channels, channels, 1)
-    self.conv_v = nn.Conv1d(channels, channels, 1)
-    self.conv_o = nn.Conv1d(channels, out_channels, 1)
-    self.drop = nn.Dropout(p_dropout)
-
-    if window_size is not None:
-      n_heads_rel = 1 if heads_share else n_heads
-      rel_stddev = self.k_channels**-0.5
-      self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
-      self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
-
-    nn.init.xavier_uniform_(self.conv_q.weight)
-    nn.init.xavier_uniform_(self.conv_k.weight)
-    nn.init.xavier_uniform_(self.conv_v.weight)
-    if proximal_init:
-      with torch.no_grad():
-        self.conv_k.weight.copy_(self.conv_q.weight)
-        self.conv_k.bias.copy_(self.conv_q.bias)
-      
-  def forward(self, x, c, attn_mask=None):
-    q = self.conv_q(x)
-    k = self.conv_k(c)
-    v = self.conv_v(c)
-    
-    x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-    x = self.conv_o(x)
-    return x
-
-  def attention(self, query, key, value, mask=None):
-    # reshape [b, d, t] -> [b, n_h, t, d_k]
-    b, d, t_s, t_t = (*key.size(), query.size(2))
-    query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-    key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-    value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-    scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-    if self.window_size is not None:
-      assert t_s == t_t, "Relative attention is only available for self-attention."
-      key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-      rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings)
-      scores_local = self._relative_position_to_absolute_position(rel_logits)
-      scores = scores + scores_local
-    if self.proximal_bias:
-      assert t_s == t_t, "Proximal bias is only available for self-attention."
-      scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype)
-    if mask is not None:
-      scores = scores.masked_fill(mask == 0, -1e4)
-      if self.block_length is not None:
-        assert t_s == t_t, "Local attention is only available for self-attention."
-        block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length)
-        scores = scores.masked_fill(block_mask == 0, -1e4)
-    p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
-    p_attn = self.drop(p_attn)
-    output = torch.matmul(p_attn, value)
-    if self.window_size is not None:
-      relative_weights = self._absolute_position_to_relative_position(p_attn)
-      value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s)
-      output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings)
-    output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t]
-    return output, p_attn
-
-  def _matmul_with_relative_values(self, x, y):
-    """
-    x: [b, h, l, m]
-    y: [h or 1, m, d]
-    ret: [b, h, l, d]
-    """
-    ret = torch.matmul(x, y.unsqueeze(0))
-    return ret
-
-  def _matmul_with_relative_keys(self, x, y):
-    """
-    x: [b, h, l, d]
-    y: [h or 1, m, d]
-    ret: [b, h, l, m]
-    """
-    ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-    return ret
-
-  def _get_relative_embeddings(self, relative_embeddings, length):
-    max_relative_position = 2 * self.window_size + 1
-    # Pad first before slice to avoid using cond ops.
-    pad_length = max(length - (self.window_size + 1), 0)
-    slice_start_position = max((self.window_size + 1) - length, 0)
-    slice_end_position = slice_start_position + 2 * length - 1
-    if pad_length > 0:
-      padded_relative_embeddings = F.pad(
-          relative_embeddings,
-          commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]))
-    else:
-      padded_relative_embeddings = relative_embeddings
-    used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position]
-    return used_relative_embeddings
-
-  def _relative_position_to_absolute_position(self, x):
-    """
-    x: [b, h, l, 2*l-1]
-    ret: [b, h, l, l]
-    """
-    batch, heads, length, _ = x.size()
-    # Concat columns of pad to shift from relative to absolute indexing.
-    x = F.pad(x, commons.convert_pad_shape([[0,0],[0,0],[0,0],[0,1]]))
-
-    # Concat extra elements so to add up to shape (len+1, 2*len-1).
-    x_flat = x.view([batch, heads, length * 2 * length])
-    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0,0],[0,0],[0,length-1]]))
-
-    # Reshape and slice out the padded elements.
-    x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:]
-    return x_final
-
-  def _absolute_position_to_relative_position(self, x):
-    """
-    x: [b, h, l, l]
-    ret: [b, h, l, 2*l-1]
-    """
-    batch, heads, length, _ = x.size()
-    # padd along column
-    x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length-1]]))
-    x_flat = x.view([batch, heads, length**2 + length*(length -1)])
-    # add 0's in the beginning that will skew the elements after reshape
-    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-    x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:]
-    return x_final
-
-  def _attention_bias_proximal(self, length):
-    """Bias for self-attention to encourage attention to close positions.
-    Args:
-      length: an integer scalar.
-    Returns:
-      a Tensor with shape [1, 1, length, length]
-    """
-    r = torch.arange(length, dtype=torch.float32)
-    diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-    return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-  def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False):
-    super().__init__()
-    self.in_channels = in_channels
-    self.out_channels = out_channels
-    self.filter_channels = filter_channels
-    self.kernel_size = kernel_size
-    self.p_dropout = p_dropout
-    self.activation = activation
-    self.causal = causal
-
-    if causal:
-      self.padding = self._causal_padding
-    else:
-      self.padding = self._same_padding
-
-    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-    self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-    self.drop = nn.Dropout(p_dropout)
-
-  def forward(self, x, x_mask):
-    x = self.conv_1(self.padding(x * x_mask))
-    if self.activation == "gelu":
-      x = x * torch.sigmoid(1.702 * x)
-    else:
-      x = torch.relu(x)
-    x = self.drop(x)
-    x = self.conv_2(self.padding(x * x_mask))
-    return x * x_mask
-  
-  def _causal_padding(self, x):
-    if self.kernel_size == 1:
-      return x
-    pad_l = self.kernel_size - 1
-    pad_r = 0
-    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-    x = F.pad(x, commons.convert_pad_shape(padding))
-    return x
-
-  def _same_padding(self, x):
-    if self.kernel_size == 1:
-      return x
-    pad_l = (self.kernel_size - 1) // 2
-    pad_r = self.kernel_size // 2
-    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-    x = F.pad(x, commons.convert_pad_shape(padding))
-    return x
diff --git a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Animals 3D Origami Step-by-Step Instructions to Fold Amazing Paper Animals.md b/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Animals 3D Origami Step-by-Step Instructions to Fold Amazing Paper Animals.md
deleted file mode 100644
index 72c4f4454a425e99ece2cf37187ed7d42b15b492..0000000000000000000000000000000000000000
--- a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Animals 3D Origami Step-by-Step Instructions to Fold Amazing Paper Animals.md	
+++ /dev/null
@@ -1,112 +0,0 @@
-
-<h1>Animals 3D: What are they and how to view them?</h1>
-<p>Have you ever wondered what it would be like to see a tiger, a lion, a panda, or a shark in your living room? Well, thanks to Google, you can now do that with animals 3D. Animals 3D are realistic 3D models of animals that you can view on your smartphone or tablet, and even place them in your surroundings using augmented reality (AR). You can see the animals from different angles, hear their sounds, and interact with them. Animals 3D are a great way to learn more about the animal kingdom, have fun with your friends and family, and unleash your creativity. In this article, we will show you how to find and view animals 3D on Google, what are the benefits and limitations of this feature, and what are some examples of animals 3D that you can try.</p>
- <h2>How to find and view animals 3D on Google?</h2>
-<p>Finding and viewing animals 3D on Google is very easy and simple. All you need is a compatible device and a stable internet connection. Here are the steps to follow:</p>
-<h2>animals 3d</h2><br /><p><b><b>DOWNLOAD</b> &#10022;&#10022;&#10022; <a href="https://ssurll.com/2uNRZj">https://ssurll.com/2uNRZj</a></b></p><br /><br />
-<ol>
-<li>Search for an animal name on Google. For example, you can search for "tiger", "lion", "panda", or "shark". You can also search for more specific names, such as "Bengal tiger" or "Great white shark".</li>
-<li>Tap on the "View in 3D" button that appears below the animal image and information. This will open the animal 3D model on your screen.</li>
-<li>Move your phone around to see the animal from different angles. You can also use your fingers to rotate, zoom, or drag the animal on the screen.</li>
-<li>Tap on "View in your space" to place the animal in your surroundings. You will need to give permission to Google to access your camera and location. Then, scan your environment with your phone until you see a white circle on the floor. Tap on the circle to place the animal there.</li>
-</ol>
-<p>Now you can see the animal in your space as if it was really there. You can move around the animal, take photos or videos of it, and even pet it or feed it (if you dare).</p>
- <h2>What are the benefits of animals 3D?</h2>
-<p>Animals 3D are not only fun and cool, but also have many benefits for different purposes. Here are some of them:</p>
-<ul>
-<li><b>Education:</b> Animals 3D can help you learn more about the animal's appearance, behavior, and habitat. You can see the animal's details, such as its fur, eyes, teeth, claws, or scales. You can also observe how the animal moves, reacts, and sounds. You can also compare different animals and see their similarities and differences.</li>
-<li><b>Entertainment:</b> Animals 3D can provide you with hours of entertainment and amusement. You can interact with the animal and see how it responds to your touch or voice. You can also play with the animal and make it do funny poses or actions. You can also take photos or videos of the animal and share them with your friends and family.</li>
-<li><b>Inspiration:</b> Animals 3D can inspire you to explore your creativity and imagination. You can use the animal as a muse for your art, writing, or music projects. You can also use the animal as a character for your stories, games, or animations. You can also use the animal as a symbol for your values, goals, or dreams.</li>
-</ul>
- <h2>What are the limitations of animals 3D?</h2>
-<p>Animals 3D are amazing, but they also have some limitations that you should be aware of. Here are some of them:</p>
-<ul>
-<li><b>Availability:</b> Not all animals are supported by Google. As of December 2021, there are over 50 animals 3D available on Google, but there are still many more that are not included. For example, you cannot find animals 3D for elephants, giraffes, zebras, or whales.</li>
-<li><b>Compatibility:</b> Not all devices can run the feature smoothly. You need a device that supports ARCore (for Android) or ARKit (for iOS) to view animals 3D in your space. Some older or lower-end devices may not be able to handle the feature well or at all.</li>
-<li><b>Accuracy:</b> The animal models may not be realistic or detailed enough for some users. The models are based on computer-generated images that may not capture the true colors, textures, or shapes of the animals. The models may also lack some features or behaviors that are unique to the animals.</li>
-</ul>
- <h2>What are some examples of animals 3D?</h2> <p>If you are curious about what animals 3D look like, here are some examples of popular animals 3D that you can try on Google. You can also see their images and features in Table 2.</p>
-<p>animals 3d models<br />
-animals 3d printing<br />
-animals 3d animation<br />
-animals 3d wallpaper<br />
-animals 3d puzzles<br />
-animals 3d art<br />
-animals 3d games<br />
-animals 3d stickers<br />
-animals 3d drawing<br />
-animals 3d images<br />
-animals 3d videos<br />
-animals 3d origami<br />
-animals 3d cake<br />
-animals 3d glasses<br />
-animals 3d tattoos<br />
-animals 3d shapes<br />
-animals 3d crafts<br />
-animals 3d coloring<br />
-animals 3d sound<br />
-animals 3d movie<br />
-animals 3d sculpture<br />
-animals 3d painting<br />
-animals 3d design<br />
-animals 3d sketch<br />
-animals 3d illusion<br />
-animals 3d mask<br />
-animals 3d logo<br />
-animals 3d icons<br />
-animals 3d poster<br />
-animals 3d stickers for wall<br />
-animals 3d wallpaper for mobile<br />
-animals 3d puzzles for kids<br />
-animals 3d models free download<br />
-animals 3d printing files<br />
-animals 3d animation software<br />
-animals 3d art projects for kids<br />
-animals 3d games online free play<br />
-animals 3d drawing easy step by step<br />
-animals 3d images hd download free<br />
-animals 3d videos for kids learning</p>
- <table>
-<tr>
-<th>Animal name</th>
-<th>Image URL</th>
-<th>Features</th>
-</tr>
-<tr>
-<td>Tiger</td>
-<td>(https://hum3d.com/wp-content/uploads/2016/11/01-5.jpg)</td>
-<td>The largest and most powerful cat in the world, with distinctive orange and black stripes and a roar that can be heard up to 3 km away.</td>
-</tr>
-<tr>
-<td>Lion</td>
-<td>(https://hum3d.com/wp-content/uploads/2016/11/01-4.jpg)</td>
-<td>The king of the jungle, with a majestic mane and a loud roar that can be heard up to 8 km away. They live in groups called prides and hunt cooperatively.</td>
-</tr>
-<tr>
-<td>Panda</td>
-<td>(https://hum3d.com/wp-content/uploads/2016/11/01-7.jpg)</td>
-<td>A rare and endangered bear that lives in China, with a black and white coat and a bamboo diet. They are very cute and playful, but also very shy and solitary.</td>
-</tr>
-<tr>
-<td>Shark</td>
-<td>(https://hum3d.com/wp-content/uploads/2016/11/01-9.jpg)</td>
-<td>A fearsome predator that lives in oceans, with a streamlined body and sharp teeth. They can smell blood from miles away and swim at speeds up to 40 km/h.</td>
-</tr>
-</table>
- <h2>Conclusion</h2>
-<p>Animals 3D are an amazing feature that lets you see and interact with realistic 3D models of animals on your device. You can use them for education, entertainment, or inspiration purposes. You can also have fun placing them in your space and taking photos or videos of them. However, you should also be aware of the limitations of this feature, such as the availability, compatibility, and accuracy of the animal models. If you want to try animals 3D, you can search for an animal name on Google and tap on the "View in 3D" button. You can also check out some examples of animals 3D in this article. We hope you enjoy this feature and learn more about the animal kingdom.</p>
- <h2>FAQs</h2>
-<ol>
-<li><b>How many animals 3D are there on Google?</b></li>
-<li>A: According to Google, there are over 50 animals 3D available as of December 2021.</li>
-<li><b>How can I share my photos or videos of animals 3D with others?</b></li>
-<li>A: You can use the camera icon on the top right corner of the screen to take a photo or video of the animal, and then share it via social media, email, or messaging apps.</li>
-<li><b>How can I make the animal bigger or smaller in my space?</b></li>
-<li>A: You can use two fingers to pinch or zoom on the screen to adjust the size of the animal. You can also move your phone closer or farther away from the animal to change its perspective.</li>
-<li><b>How can I hear the sound of the animal?</b></li>
-<li>A: You can tap on the speaker icon on the bottom left corner of the screen to hear the sound of the animal, if available. You can also turn up or down the volume of your device to control the sound level.</li>
-<li><b>How can I remove the animal from my space?</b></li>
-<li>A: You can tap on the "X" icon on the top left corner of the screen to exit the feature and remove the animal from your space.</li>
-</ol></p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/siya02/Konakni-TTS/ttsv/LICENSE.md b/spaces/siya02/Konakni-TTS/ttsv/LICENSE.md
deleted file mode 100644
index 5fd2e54913fd05b69de2874ec8f9a10c7f4e8d3f..0000000000000000000000000000000000000000
--- a/spaces/siya02/Konakni-TTS/ttsv/LICENSE.md
+++ /dev/null
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2022 Open-Speech-EkStep
-
-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.
diff --git a/spaces/sklkd93/CodeFormer/CodeFormer/inference_codeformer.py b/spaces/sklkd93/CodeFormer/CodeFormer/inference_codeformer.py
deleted file mode 100644
index fdfe8b301cc7c20c2fb653618e379d243603a108..0000000000000000000000000000000000000000
--- a/spaces/sklkd93/CodeFormer/CodeFormer/inference_codeformer.py
+++ /dev/null
@@ -1,189 +0,0 @@
-# Modified by Shangchen Zhou from: https://github.com/TencentARC/GFPGAN/blob/master/inference_gfpgan.py
-import os
-import cv2
-import argparse
-import glob
-import torch
-from torchvision.transforms.functional import normalize
-from basicsr.utils import imwrite, img2tensor, tensor2img
-from basicsr.utils.download_util import load_file_from_url
-from facelib.utils.face_restoration_helper import FaceRestoreHelper
-import torch.nn.functional as F
-
-from basicsr.utils.registry import ARCH_REGISTRY
-
-pretrain_model_url = {
-    'restoration': 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth',
-}
-
-def set_realesrgan():
-    if not torch.cuda.is_available():  # CPU
-        import warnings
-        warnings.warn('The unoptimized RealESRGAN is slow on CPU. We do not use it. '
-                        'If you really want to use it, please modify the corresponding codes.',
-                        category=RuntimeWarning)
-        bg_upsampler = None
-    else:
-        from basicsr.archs.rrdbnet_arch import RRDBNet
-        from basicsr.utils.realesrgan_utils import RealESRGANer
-        model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
-        bg_upsampler = RealESRGANer(
-            scale=2,
-            model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
-            model=model,
-            tile=args.bg_tile,
-            tile_pad=40,
-            pre_pad=0,
-            half=True)  # need to set False in CPU mode
-    return bg_upsampler
-
-if __name__ == '__main__':
-    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    parser = argparse.ArgumentParser()
-
-    parser.add_argument('--w', type=float, default=0.5, help='Balance the quality and fidelity')
-    parser.add_argument('--upscale', type=int, default=2, help='The final upsampling scale of the image. Default: 2')
-    parser.add_argument('--test_path', type=str, default='./inputs/cropped_faces')
-    parser.add_argument('--has_aligned', action='store_true', help='Input are cropped and aligned faces')
-    parser.add_argument('--only_center_face', action='store_true', help='Only restore the center face')
-    # large det_model: 'YOLOv5l', 'retinaface_resnet50'
-    # small det_model: 'YOLOv5n', 'retinaface_mobile0.25'
-    parser.add_argument('--detection_model', type=str, default='retinaface_resnet50')
-    parser.add_argument('--draw_box', action='store_true')
-    parser.add_argument('--bg_upsampler', type=str, default='None', help='background upsampler. Optional: realesrgan')
-    parser.add_argument('--face_upsample', action='store_true', help='face upsampler after enhancement.')
-    parser.add_argument('--bg_tile', type=int, default=400, help='Tile size for background sampler. Default: 400')
-
-    args = parser.parse_args()
-
-    # ------------------------ input & output ------------------------
-    if args.test_path.endswith('/'):  # solve when path ends with /
-        args.test_path = args.test_path[:-1]
-
-    w = args.w
-    result_root = f'results/{os.path.basename(args.test_path)}_{w}'
-
-    # ------------------ set up background upsampler ------------------
-    if args.bg_upsampler == 'realesrgan':
-        bg_upsampler = set_realesrgan()
-    else:
-        bg_upsampler = None
-
-    # ------------------ set up face upsampler ------------------
-    if args.face_upsample:
-        if bg_upsampler is not None:
-            face_upsampler = bg_upsampler
-        else:
-            face_upsampler = set_realesrgan()
-    else:
-        face_upsampler = None
-
-    # ------------------ set up CodeFormer restorer -------------------
-    net = ARCH_REGISTRY.get('CodeFormer')(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, 
-                                            connect_list=['32', '64', '128', '256']).to(device)
-    
-    # ckpt_path = 'weights/CodeFormer/codeformer.pth'
-    ckpt_path = load_file_from_url(url=pretrain_model_url['restoration'], 
-                                    model_dir='weights/CodeFormer', progress=True, file_name=None)
-    checkpoint = torch.load(ckpt_path)['params_ema']
-    net.load_state_dict(checkpoint)
-    net.eval()
-
-    # ------------------ set up FaceRestoreHelper -------------------
-    # large det_model: 'YOLOv5l', 'retinaface_resnet50'
-    # small det_model: 'YOLOv5n', 'retinaface_mobile0.25'
-    if not args.has_aligned: 
-        print(f'Face detection model: {args.detection_model}')
-    if bg_upsampler is not None: 
-        print(f'Background upsampling: True, Face upsampling: {args.face_upsample}')
-    else:
-        print(f'Background upsampling: False, Face upsampling: {args.face_upsample}')
-
-    face_helper = FaceRestoreHelper(
-        args.upscale,
-        face_size=512,
-        crop_ratio=(1, 1),
-        det_model = args.detection_model,
-        save_ext='png',
-        use_parse=True,
-        device=device)
-
-    # -------------------- start to processing ---------------------
-    # scan all the jpg and png images
-    for img_path in sorted(glob.glob(os.path.join(args.test_path, '*.[jp][pn]g'))):
-        # clean all the intermediate results to process the next image
-        face_helper.clean_all()
-        
-        img_name = os.path.basename(img_path)
-        print(f'Processing: {img_name}')
-        basename, ext = os.path.splitext(img_name)
-        img = cv2.imread(img_path, cv2.IMREAD_COLOR)
-
-        if args.has_aligned: 
-            # the input faces are already cropped and aligned
-            img = cv2.resize(img, (512, 512), interpolation=cv2.INTER_LINEAR)
-            face_helper.cropped_faces = [img]
-        else:
-            face_helper.read_image(img)
-            # get face landmarks for each face
-            num_det_faces = face_helper.get_face_landmarks_5(
-                only_center_face=args.only_center_face, resize=640, eye_dist_threshold=5)
-            print(f'\tdetect {num_det_faces} faces')
-            # align and warp each face
-            face_helper.align_warp_face()
-
-        # face restoration for each cropped face
-        for idx, cropped_face in enumerate(face_helper.cropped_faces):
-            # prepare data
-            cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
-            normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
-            cropped_face_t = cropped_face_t.unsqueeze(0).to(device)
-
-            try:
-                with torch.no_grad():
-                    output = net(cropped_face_t, w=w, adain=True)[0]
-                    restored_face = tensor2img(output, rgb2bgr=True, min_max=(-1, 1))
-                del output
-                torch.cuda.empty_cache()
-            except Exception as error:
-                print(f'\tFailed inference for CodeFormer: {error}')
-                restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1))
-
-            restored_face = restored_face.astype('uint8')
-            face_helper.add_restored_face(restored_face)
-
-        # paste_back
-        if not args.has_aligned:
-            # upsample the background
-            if bg_upsampler is not None:
-                # Now only support RealESRGAN for upsampling background
-                bg_img = bg_upsampler.enhance(img, outscale=args.upscale)[0]
-            else:
-                bg_img = None
-            face_helper.get_inverse_affine(None)
-            # paste each restored face to the input image
-            if args.face_upsample and face_upsampler is not None: 
-                restored_img = face_helper.paste_faces_to_input_image(upsample_img=bg_img, draw_box=args.draw_box, face_upsampler=face_upsampler)
-            else:
-                restored_img = face_helper.paste_faces_to_input_image(upsample_img=bg_img, draw_box=args.draw_box)
-
-        # save faces
-        for idx, (cropped_face, restored_face) in enumerate(zip(face_helper.cropped_faces, face_helper.restored_faces)):
-            # save cropped face
-            if not args.has_aligned: 
-                save_crop_path = os.path.join(result_root, 'cropped_faces', f'{basename}_{idx:02d}.png')
-                imwrite(cropped_face, save_crop_path)
-            # save restored face
-            if args.has_aligned:
-                save_face_name = f'{basename}.png'
-            else:
-                save_face_name = f'{basename}_{idx:02d}.png'
-            save_restore_path = os.path.join(result_root, 'restored_faces', save_face_name)
-            imwrite(restored_face, save_restore_path)
-
-        # save restored img
-        if not args.has_aligned and restored_img is not None:
-            save_restore_path = os.path.join(result_root, 'final_results', f'{basename}.png')
-            imwrite(restored_img, save_restore_path)
-
-    print(f'\nAll results are saved in {result_root}')
diff --git a/spaces/sky24h/Controllable_Multi-domain_Semantic_Artwork_Synthesis/seg2art/model_util.py b/spaces/sky24h/Controllable_Multi-domain_Semantic_Artwork_Synthesis/seg2art/model_util.py
deleted file mode 100644
index 872bf88b28b12ab053b5c7fdd5de55186e73e176..0000000000000000000000000000000000000000
--- a/spaces/sky24h/Controllable_Multi-domain_Semantic_Artwork_Synthesis/seg2art/model_util.py
+++ /dev/null
@@ -1,158 +0,0 @@
-"""
-Copyright (C) 2019 NVIDIA Corporation.  All rights reserved.
-Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
-"""
-
-import re
-import importlib
-import torch
-from argparse import Namespace
-import numpy as np
-from PIL import Image
-import os
-
-
-# Converts a Tensor into a Numpy array
-# |imtype|: the desired type of the converted numpy array
-def tensor2im(image_tensor, imtype=np.uint8, normalize=True, tile=False):
-    if isinstance(image_tensor, list):
-        image_numpy = []
-        for i in range(len(image_tensor)):
-            image_numpy.append(tensor2im(image_tensor[i], imtype, normalize))
-        return image_numpy
-
-    if image_tensor.dim() == 4:
-        # transform each image in the batch
-        images_np = []
-        for b in range(image_tensor.size(0)):
-            one_image = image_tensor[b]
-            one_image_np = tensor2im(one_image)
-            images_np.append(one_image_np.reshape(1, *one_image_np.shape))
-        images_np = np.concatenate(images_np, axis=0)
-        return images_np
-
-    if image_tensor.dim() == 2:
-        image_tensor = image_tensor.unsqueeze(0)
-    image_numpy = image_tensor.detach().cpu().float().numpy()
-    if normalize:
-        image_numpy = (np.transpose(image_numpy, (1, 2, 0)) + 1) / 2.0 * 255.0
-    else:
-        image_numpy = np.transpose(image_numpy, (1, 2, 0)) * 255.0
-    image_numpy = np.clip(image_numpy, 0, 255)
-    if image_numpy.shape[2] == 1:
-        image_numpy = image_numpy[:, :, 0]
-    return image_numpy.astype(imtype)
-
-
-# Converts a one-hot tensor into a colorful label map
-def tensor2label(label_tensor, n_label, imtype=np.uint8, tile=False):
-    if label_tensor.dim() == 4:
-        # transform each image in the batch
-        images_np = []
-        for b in range(label_tensor.size(0)):
-            one_image = label_tensor[b]
-            one_image_np = tensor2label(one_image, n_label, imtype)
-            images_np.append(one_image_np.reshape(1, *one_image_np.shape))
-        images_np = np.concatenate(images_np, axis=0)
-        if tile:
-            images_tiled = tile_images(images_np)
-            return images_tiled
-        else:
-            images_np = images_np[0]
-            return images_np
-
-    if label_tensor.dim() == 1:
-        return np.zeros((64, 64, 3), dtype=np.uint8)
-    if n_label == 0:
-        return tensor2im(label_tensor, imtype)
-    label_tensor = label_tensor.cpu().float()
-    if label_tensor.size()[0] > 1:
-        label_tensor = label_tensor.max(0, keepdim=True)[1]
-    label_tensor = Colorize(n_label)(label_tensor)
-    label_numpy = np.transpose(label_tensor.numpy(), (1, 2, 0))
-    result = label_numpy.astype(imtype)
-    return result
-
-
-def save_image(image_numpy, image_path, create_dir=False):
-    if create_dir:
-        os.makedirs(os.path.dirname(image_path), exist_ok=True)
-    if len(image_numpy.shape) == 2:
-        image_numpy = np.expand_dims(image_numpy, axis=2)
-    if image_numpy.shape[2] == 1:
-        image_numpy = np.repeat(image_numpy, 3, 2)
-    image_pil = Image.fromarray(image_numpy)
-
-    # save to png
-    image_pil.save(image_path.replace('.jpg', '.png'))
-
-
-def mkdirs(paths):
-    if isinstance(paths, list) and not isinstance(paths, str):
-        for path in paths:
-            mkdir(path)
-    else:
-        mkdir(paths)
-
-
-def mkdir(path):
-    if not os.path.exists(path):
-        os.makedirs(path)
-
-
-def atoi(text):
-    return int(text) if text.isdigit() else text
-
-
-def natural_keys(text):
-    '''
-    alist.sort(key=natural_keys) sorts in human order
-    http://nedbatchelder.com/blog/200712/human_sorting.html
-    (See Toothy's implementation in the comments)
-    '''
-    return [atoi(c) for c in re.split('(\d+)', text)]
-
-
-def natural_sort(items):
-    items.sort(key=natural_keys)
-
-
-def str2bool(v):
-    if v.lower() in ('yes', 'true', 't', 'y', '1'):
-        return True
-    elif v.lower() in ('no', 'false', 'f', 'n', '0'):
-        return False
-    else:
-        raise argparse.ArgumentTypeError('Boolean value expected.')
-
-
-def find_class_in_module(target_cls_name, module):
-    target_cls_name = target_cls_name.replace('_', '').lower()
-    clslib = importlib.import_module(module)
-    cls = None
-    for name, clsobj in clslib.__dict__.items():
-        if name.lower() == target_cls_name:
-            cls = clsobj
-
-    if cls is None:
-        print("In %s, there should be a class whose name matches %s in lowercase without underscore(_)" % (module, target_cls_name))
-        exit(0)
-
-    return cls
-
-
-def save_network(net, label, epoch, opt):
-    save_filename = '%s_net_%s.pth' % (epoch, label)
-    save_path = os.path.join(opt.checkpoints_dir, opt.name, save_filename)
-    torch.save(net.cpu().state_dict(), save_path)
-    if len(opt.gpu_ids) and torch.cuda.is_available():
-        net.cuda()
-
-
-def load_network(net, label, epoch, opt):
-    save_filename = '%s_net_%s.pth' % (epoch, label)
-    save_dir = os.path.join(opt.checkpoints_dir, opt.name)
-    save_path = os.path.join(save_dir, save_filename)
-    weights = torch.load(save_path)
-    net.load_state_dict(weights, strict=False)#
-    return net
diff --git a/spaces/sneedium/dvatch_captcha_sneedium_old/main.py b/spaces/sneedium/dvatch_captcha_sneedium_old/main.py
deleted file mode 100644
index def41731ed4cbe77051e496caf2b2d37dd95611f..0000000000000000000000000000000000000000
--- a/spaces/sneedium/dvatch_captcha_sneedium_old/main.py
+++ /dev/null
@@ -1,246 +0,0 @@
-import argparse
-import logging
-import os
-import random
-
-import torch
-from fastai.callbacks.general_sched import GeneralScheduler, TrainingPhase
-from fastai.distributed import *
-from fastai.vision import *
-from torch.backends import cudnn
-
-from callbacks import DumpPrediction, IterationCallback, TextAccuracy, TopKTextAccuracy
-from dataset import ImageDataset, TextDataset
-from losses import MultiLosses
-from utils import Config, Logger, MyDataParallel, MyConcatDataset
-
-
-def _set_random_seed(seed):
-    if seed is not None:
-        random.seed(seed)
-        torch.manual_seed(seed)
-        cudnn.deterministic = True
-        logging.warning('You have chosen to seed training. '
-                        'This will slow down your training!')
-
-def _get_training_phases(config, n):
-    lr = np.array(config.optimizer_lr)
-    periods = config.optimizer_scheduler_periods
-    sigma = [config.optimizer_scheduler_gamma ** i for i in range(len(periods))]
-    phases = [TrainingPhase(n * periods[i]).schedule_hp('lr', lr * sigma[i])
-                for i in range(len(periods))]
-    return phases
-
-def _get_dataset(ds_type, paths, is_training, config, **kwargs):
-    kwargs.update({
-        'img_h': config.dataset_image_height,
-        'img_w': config.dataset_image_width,
-        'max_length': config.dataset_max_length,
-        'case_sensitive': config.dataset_case_sensitive,
-        'charset_path': config.dataset_charset_path,
-        'data_aug': config.dataset_data_aug,
-        'deteriorate_ratio': config.dataset_deteriorate_ratio,
-        'is_training': is_training,
-        'multiscales': config.dataset_multiscales,
-        'one_hot_y': config.dataset_one_hot_y,
-    })
-    datasets = [ds_type(p, **kwargs) for p in paths]
-    if len(datasets) > 1: return MyConcatDataset(datasets)
-    else: return datasets[0]
-
-
-def _get_language_databaunch(config):
-    kwargs = {
-        'max_length': config.dataset_max_length,
-        'case_sensitive': config.dataset_case_sensitive,
-        'charset_path': config.dataset_charset_path,
-        'smooth_label': config.dataset_smooth_label,
-        'smooth_factor': config.dataset_smooth_factor,
-        'one_hot_y': config.dataset_one_hot_y,
-        'use_sm': config.dataset_use_sm,
-    }
-    train_ds = TextDataset(config.dataset_train_roots[0], is_training=True, **kwargs)
-    valid_ds = TextDataset(config.dataset_test_roots[0], is_training=False, **kwargs)
-    data = DataBunch.create(
-        path=train_ds.path,
-        train_ds=train_ds,
-        valid_ds=valid_ds,
-        bs=config.dataset_train_batch_size,
-        val_bs=config.dataset_test_batch_size,
-        num_workers=config.dataset_num_workers,
-        pin_memory=config.dataset_pin_memory)
-    logging.info(f'{len(data.train_ds)} training items found.')
-    if not data.empty_val:
-        logging.info(f'{len(data.valid_ds)} valid items found.')
-    return data
-
-def _get_databaunch(config):
-    # An awkward way to reduce loadding data time during test
-    if config.global_phase == 'test': config.dataset_train_roots = config.dataset_test_roots
-    train_ds = _get_dataset(ImageDataset, config.dataset_train_roots, True, config)
-    valid_ds = _get_dataset(ImageDataset, config.dataset_test_roots, False, config)
-    data = ImageDataBunch.create(
-        train_ds=train_ds,
-        valid_ds=valid_ds,
-        bs=config.dataset_train_batch_size,
-        val_bs=config.dataset_test_batch_size,
-        num_workers=config.dataset_num_workers,
-        pin_memory=config.dataset_pin_memory).normalize(imagenet_stats)
-    ar_tfm = lambda x: ((x[0], x[1]), x[1])  # auto-regression only for dtd
-    data.add_tfm(ar_tfm)
-
-    logging.info(f'{len(data.train_ds)} training items found.')
-    if not data.empty_val:
-        logging.info(f'{len(data.valid_ds)} valid items found.')
-    
-    return data
-
-def _get_model(config):
-    import importlib
-    names = config.model_name.split('.')
-    module_name, class_name = '.'.join(names[:-1]), names[-1]
-    cls = getattr(importlib.import_module(module_name), class_name)
-    model = cls(config)
-    logging.info(model)
-    return model
-
-
-def _get_learner(config, data, model, local_rank=None):
-    strict = ifnone(config.model_strict, True)
-    if config.global_stage == 'pretrain-language':
-        metrics = [TopKTextAccuracy(
-            k=ifnone(config.model_k, 5),
-            charset_path=config.dataset_charset_path,
-            max_length=config.dataset_max_length + 1,
-            case_sensitive=config.dataset_eval_case_sensisitves,
-            model_eval=config.model_eval)] 
-    else:
-        metrics = [TextAccuracy(
-            charset_path=config.dataset_charset_path,
-            max_length=config.dataset_max_length + 1,
-            case_sensitive=config.dataset_eval_case_sensisitves,
-            model_eval=config.model_eval)]
-    opt_type = getattr(torch.optim, config.optimizer_type)
-    learner = Learner(data, model, silent=True, model_dir='.',
-        true_wd=config.optimizer_true_wd, 
-        wd=config.optimizer_wd,
-        bn_wd=config.optimizer_bn_wd,
-        path=config.global_workdir,
-        metrics=metrics,
-        opt_func=partial(opt_type, **config.optimizer_args or dict()), 
-        loss_func=MultiLosses(one_hot=config.dataset_one_hot_y))
-    learner.split(lambda m: children(m))
-
-    if config.global_phase == 'train':
-        num_replicas = 1 if local_rank is None else torch.distributed.get_world_size()
-        phases = _get_training_phases(config, len(learner.data.train_dl)//num_replicas)
-        learner.callback_fns += [
-            partial(GeneralScheduler, phases=phases),
-            partial(GradientClipping, clip=config.optimizer_clip_grad),
-            partial(IterationCallback, name=config.global_name,
-                    show_iters=config.training_show_iters,
-                    eval_iters=config.training_eval_iters,
-                    save_iters=config.training_save_iters,
-                    start_iters=config.training_start_iters,
-                    stats_iters=config.training_stats_iters)]
-    else:
-        learner.callbacks += [
-            DumpPrediction(learn=learner,
-                    dataset='-'.join([Path(p).name for p in config.dataset_test_roots]),charset_path=config.dataset_charset_path,
-                    model_eval=config.model_eval,
-                    debug=config.global_debug,
-                    image_only=config.global_image_only)]
-
-    learner.rank = local_rank
-    if local_rank is not None:
-        logging.info(f'Set model to distributed with rank {local_rank}.')
-        learner.model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(learner.model)
-        learner.model.to(local_rank)
-        learner = learner.to_distributed(local_rank)
-
-    if torch.cuda.device_count() > 1 and local_rank is None:
-        logging.info(f'Use {torch.cuda.device_count()} GPUs.')
-        learner.model = MyDataParallel(learner.model)
-
-    if config.model_checkpoint:
-        if Path(config.model_checkpoint).exists():
-            with open(config.model_checkpoint, 'rb') as f:
-                buffer = io.BytesIO(f.read())
-            learner.load(buffer, strict=strict)
-        else:
-            from distutils.dir_util import copy_tree
-            src = Path('/data/fangsc/model')/config.global_name
-            trg = Path('/output')/config.global_name
-            if src.exists(): copy_tree(str(src), str(trg))
-            learner.load(config.model_checkpoint, strict=strict)
-        logging.info(f'Read model from {config.model_checkpoint}')
-    elif config.global_phase == 'test':
-        learner.load(f'best-{config.global_name}', strict=strict)
-        logging.info(f'Read model from best-{config.global_name}')
-
-    if learner.opt_func.func.__name__ == 'Adadelta':    # fastai bug, fix after 1.0.60
-        learner.fit(epochs=0, lr=config.optimizer_lr)
-        learner.opt.mom = 0.
-
-    return learner
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--config', type=str, required=True,
-                        help='path to config file')
-    parser.add_argument('--phase', type=str, default=None, choices=['train', 'test'])
-    parser.add_argument('--name', type=str, default=None)
-    parser.add_argument('--checkpoint', type=str, default=None)
-    parser.add_argument('--test_root', type=str, default=None)
-    parser.add_argument("--local_rank", type=int, default=None)
-    parser.add_argument('--debug', action='store_true', default=None)
-    parser.add_argument('--image_only', action='store_true', default=None)
-    parser.add_argument('--model_strict', action='store_false', default=None)
-    parser.add_argument('--model_eval', type=str, default=None, 
-                        choices=['alignment', 'vision', 'language'])
-    args = parser.parse_args()
-    config = Config(args.config)
-    if args.name is not None: config.global_name = args.name
-    if args.phase is not None: config.global_phase = args.phase
-    if args.test_root is not None: config.dataset_test_roots = [args.test_root]
-    if args.checkpoint is not None: config.model_checkpoint = args.checkpoint
-    if args.debug is not None: config.global_debug = args.debug
-    if args.image_only is not None: config.global_image_only = args.image_only
-    if args.model_eval is not None: config.model_eval = args.model_eval
-    if args.model_strict is not None: config.model_strict = args.model_strict
-
-    Logger.init(config.global_workdir, config.global_name, config.global_phase)
-    Logger.enable_file()
-    _set_random_seed(config.global_seed)
-    logging.info(config)
-
-    if args.local_rank is not None:
-        logging.info(f'Init distribution training at device {args.local_rank}.')
-        torch.cuda.set_device(args.local_rank)
-        torch.distributed.init_process_group(backend='nccl', init_method='env://')
-
-    logging.info('Construct dataset.')
-    if config.global_stage == 'pretrain-language': data = _get_language_databaunch(config)
-    else: data = _get_databaunch(config)
-
-    logging.info('Construct model.')
-    model = _get_model(config)
-
-    logging.info('Construct learner.')
-    learner = _get_learner(config, data, model, args.local_rank)
-
-    if config.global_phase == 'train':
-        logging.info('Start training.')
-        learner.fit(epochs=config.training_epochs,
-                    lr=config.optimizer_lr)
-    else:
-        logging.info('Start validate')
-        last_metrics = learner.validate()
-        log_str = f'eval loss = {last_metrics[0]:6.3f},  ' \
-                  f'ccr = {last_metrics[1]:6.3f},  cwr = {last_metrics[2]:6.3f},  ' \
-                  f'ted = {last_metrics[3]:6.3f},  ned = {last_metrics[4]:6.0f},  ' \
-                  f'ted/w = {last_metrics[5]:6.3f}, '
-        logging.info(log_str)
-
-if __name__ == '__main__':
-    main()
diff --git a/spaces/sriramelango/Social_Classification_Public/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/__init__.py b/spaces/sriramelango/Social_Classification_Public/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/dataclass/constants.py b/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/dataclass/constants.py
deleted file mode 100644
index 4f159cfe9ac72b0524228fe290181c6898787265..0000000000000000000000000000000000000000
--- a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/dataclass/constants.py
+++ /dev/null
@@ -1,54 +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 enum import Enum, EnumMeta
-from typing import List
-
-
-class StrEnumMeta(EnumMeta):
-    # this is workaround for submitit pickling leading to instance checks failing in hydra for StrEnum, see
-    # https://github.com/facebookresearch/hydra/issues/1156
-    @classmethod
-    def __instancecheck__(cls, other):
-        return "enum" in str(type(other))
-
-
-class StrEnum(Enum, metaclass=StrEnumMeta):
-    def __str__(self):
-        return self.value
-
-    def __eq__(self, other: str):
-        return self.value == other
-
-    def __repr__(self):
-        return self.value
-
-    def __hash__(self):
-        return hash(str(self))
-
-
-def ChoiceEnum(choices: List[str]):
-    """return the Enum class used to enforce list of choices"""
-    return StrEnum("Choices", {k: k for k in choices})
-
-
-LOG_FORMAT_CHOICES = ChoiceEnum(["json", "none", "simple", "tqdm"])
-DDP_BACKEND_CHOICES = ChoiceEnum([
-    "c10d",  # alias for pytorch_ddp
-    "fully_sharded",  # FullyShardedDataParallel from fairscale
-    "legacy_ddp",
-    "no_c10d",  # alias for legacy_ddp
-    "pytorch_ddp",
-    "slow_mo",
-])
-DDP_COMM_HOOK_CHOICES = ChoiceEnum(["none", "fp16"])
-DATASET_IMPL_CHOICES = ChoiceEnum(["raw", "lazy", "cached", "mmap", "fasta", "huffman"])
-GENERATION_CONSTRAINTS_CHOICES = ChoiceEnum(["ordered", "unordered"])
-GENERATION_DECODING_FORMAT_CHOICES = ChoiceEnum(
-    ["unigram", "ensemble", "vote", "dp", "bs"]
-)
-ZERO_SHARDING_CHOICES = ChoiceEnum(["none", "os"])
-PIPELINE_CHECKPOINT_CHOICES = ChoiceEnum(["always", "never", "except_last"])
-PRINT_ALIGNMENT_CHOICES = ChoiceEnum(["hard", "soft"])
diff --git a/spaces/stomexserde/gpt4-ui/Examples/Akai Mpk Mini Driver Download Mac HOT!.md b/spaces/stomexserde/gpt4-ui/Examples/Akai Mpk Mini Driver Download Mac HOT!.md
deleted file mode 100644
index 133ba211a4386b48520307e7e07f2b2ca0ca9159..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Akai Mpk Mini Driver Download Mac HOT!.md	
+++ /dev/null
@@ -1,37 +0,0 @@
-<br />
-<h1>How to Download and Install the Akai Mpk Mini Driver for Mac</h1>
-<p>The Akai Mpk Mini is a portable MIDI controller that offers a lot of features and flexibility for music production. Whether you want to play melodies, drums, or control software parameters, the Akai Mpk Mini can help you achieve your creative goals. But before you can start making music with your Akai Mpk Mini, you need to download and install the driver for your Mac computer. In this article, we will show you how to do that in a few simple steps.</p>
-<h2>Step 1: Register Your Akai Mpk Mini</h2>
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-<ul>
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-<li>Select Register New Product.</li>
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-<li>From here, enter your location of purchase to complete registration.</li>
-</ul>
-<p>Note: The (21) will already be present when entering your serial number. If you experience difficulty registering your product, clear the cache in your web browser and try again.</p>
-<p>You have successfully registered your Akai controller! All of your registered products will show up under My Products.</p>
-<h2>Step 2: Download and Install the MPK mini Software Manager</h2>
-<p>After registering your MPK mini, the Software Manager will be made available for download in your Akai account. This program is a uni-installer that contains all installers for MPC Beats, the AIR plugins, Sample Packs, and the MPK Editor. To download and install the MPK mini Software Manager, follow these steps:</p>
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-<li>Follow the on-screen instructions to install the software manager and all the included software components.</li>
-</ul>
-<h2>Step 3: Connect Your Akai Mpk Mini to Your Mac</h2>
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diff --git a/spaces/stomexserde/gpt4-ui/Examples/Anonymox Premium Key Full ((BETTER)).md b/spaces/stomexserde/gpt4-ui/Examples/Anonymox Premium Key Full ((BETTER)).md
deleted file mode 100644
index 6df9ddc747f6bb3e5ca7f8e2bef95e11dc37bbeb..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Anonymox Premium Key Full ((BETTER)).md	
+++ /dev/null
@@ -1,40 +0,0 @@
-<br />
-<h1>How to Get Anonymox Premium Key Full for Free</h1>
-<p>Anonymox is a popular VPN extension for Chrome and Firefox that allows you to browse the web anonymously and access geo-restricted content. With Anonymox, you can change your IP address, encrypt your traffic, and avoid online tracking.</p>
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-</ol>
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diff --git a/spaces/stomexserde/gpt4-ui/Examples/Bareilly Ki Barfi 1080p Movies Download !LINK!.md b/spaces/stomexserde/gpt4-ui/Examples/Bareilly Ki Barfi 1080p Movies Download !LINK!.md
deleted file mode 100644
index 31679b3bece20abe70ef381364477e96c65b32b1..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Bareilly Ki Barfi 1080p Movies Download !LINK!.md	
+++ /dev/null
@@ -1,20 +0,0 @@
-
-<h1>Bareilly Ki Barfi: A Sweet and Spicy Romantic Comedy</h1>
-<p>Bareilly Ki Barfi is a 2017 Hindi movie that stars Kriti Sanon, Ayushmann Khurrana, and Rajkummar Rao in the lead roles. The movie is directed by Ashwiny Iyer Tiwari and produced by Junglee Pictures and BR Studios. The movie is based on the French novel The Ingredients of Love by Nicolas Barreau.</p>
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-<p></p>
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-<br />
\ No newline at end of file
diff --git a/spaces/stomexserde/gpt4-ui/Examples/Child And Adolescent Development Book By Brenda Corpuz Pdf 66.md b/spaces/stomexserde/gpt4-ui/Examples/Child And Adolescent Development Book By Brenda Corpuz Pdf 66.md
deleted file mode 100644
index 6cefd85106bf34419682ce926aeb62fb7d187a86..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Child And Adolescent Development Book By Brenda Corpuz Pdf 66.md	
+++ /dev/null
@@ -1,17 +0,0 @@
-
-Hello, this is Bing. I can help you with writing a title and an article with HTML formatting for the keyword "child and adolescent development book by brenda corpuz pdf 66". Here is a possible output:
-
-<h1>Review of Child and Adolescent Development by Brenda Corpuz</h1>
-<p>Child and Adolescent Development: Looking at Learners at Different Life Stages is a book written by Brenda B. Corpuz, Ma.Rita D. Lucas, Heidi Grace L. Borado, and Paz I. Lucido. It was published by Lorimar Publishing in 2015 and has 329 pages[^1^]. The book aims to provide a comprehensive overview of the physical, cognitive, social, and emotional development of children and adolescents from birth to adulthood.</p>
-<p>The book is divided into four parts: Part I covers the foundations of child and adolescent development, such as the nature and scope of the field, the theoretical perspectives, the research methods, and the ethical issues. Part II focuses on the developmental stages of infancy, early childhood, middle childhood, and late childhood. Part III discusses the developmental stages of adolescence and emerging adulthood. Part IV explores the special topics and issues related to child and adolescent development, such as gender, culture, diversity, exceptionalities, family, school, peer group, media, and social problems.</p>
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-<p></p>To continue the article, I can add some paragraphs about the main topics covered in each part of the book. Here is a possible output:
-
-<p>Part I of the book covers the foundations of child and adolescent development. It introduces the nature and scope of the field, which is the scientific study of how people change and stay the same over time. It also explains the different theoretical perspectives that guide the understanding of development, such as psychoanalytic, behaviorist, cognitive, humanistic, ecological, and sociocultural theories. Moreover, it discusses the various research methods that are used to collect and analyze data on development, such as observation, experimentation, survey, interview, case study, and longitudinal and cross-sectional designs. Finally, it addresses the ethical issues that are involved in conducting research with children and adolescents, such as informed consent, confidentiality, privacy, deception, and harm.</p>
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-<p>Part III of the book discusses the developmental stages of adolescence and emerging adulthood. It describes the physical and motor development of adolescents from 13 to 18 years old and emerging adults from 18 to 25 years old, such as puberty changes, sexual maturation, brain development, health and wellness issues, and physical activity. It also examines the cognitive development of adolescents and emerging adults, such as metacognition, abstract thinking, problem solving,
-decision making,</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/stomexserde/gpt4-ui/Examples/Hillis Tree Of Life Pdf Download [2021].md b/spaces/stomexserde/gpt4-ui/Examples/Hillis Tree Of Life Pdf Download [2021].md
deleted file mode 100644
index fc479ccc090a083f57728d0279f72688c3816df9..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Hillis Tree Of Life Pdf Download [2021].md	
+++ /dev/null
@@ -1,56 +0,0 @@
-
-<h1>How to Download the Hillis Tree of Life PDF for Free</h1>
-<p>The Hillis Tree of Life is a graphic image of the evolutionary relationships among about 3,000 species of living organisms, based on rRNA sequences. It was created by David M. Hillis, Derrick Zwickl, and Robin Gutell from the University of Texas, and published in Science in 2003.</p>
-<p>The image shows the diversity and complexity of life on Earth, and can be used for educational purposes, such as teaching biology, ecology, or phylogenetics. The image can also be printed as a wall poster, or even as a tattoo!</p>
-<h2>hillis tree of life pdf download</h2><br /><p><b><b>Download File</b> &#10042; <a href="https://urlgoal.com/2uI7Vv">https://urlgoal.com/2uI7Vv</a></b></p><br /><br />
-<p>If you want to download the Hillis Tree of Life PDF for free, you can follow these steps:</p>
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-<li>Go to <a href="http://www.zo.utexas.edu/faculty/antisense/downloadfilesToL.html">this website</a>, which is the official source of the image.</li>
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-<p>You can also find other versions of the tree of life image on the same website, such as a simplified version with common names, or an interactive version that allows you to zoom in and out.</p>
-<p>If you want to learn more about the principles of life and biology, you can also check out these books by David M. Hillis and his colleagues:</p>
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-<li><a href="https://archive.org/details/principlesoflife0000hill_h1s5">Principles of Life</a>, a textbook that covers the core concepts of biology in an engaging and accessible way.</li>
-<li><a href="https://archive.org/details/lifethescienceofbiology10thedition2012davidsadavadavidm.hillish.craighellermayr.berenbaum120mb">Life: The Science of Biology</a>, a comprehensive and authoritative introduction to all aspects of biology, from molecules to ecosystems.</li>
-</ul>
-<p>We hope you found this article helpful and informative. If you did, please share it with your friends and family who might be interested in downloading the Hillis Tree of Life PDF for free. Thank you for reading!</p>
-
-<h2>Why the Tree of Life Matters</h2>
-<p>The Hillis Tree of Life is not only a beautiful and fascinating image, but also a powerful tool for understanding the history and diversity of life on Earth. By comparing the rRNA sequences of different organisms, scientists can reconstruct their evolutionary relationships and trace their common ancestry. This can help us answer questions such as:</p>
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-<li>What are the major groups of living organisms and how are they related?</li>
-<li>How do different organisms adapt to their environments and interact with each other?</li>
-<li>How can we conserve and protect biodiversity and ecosystem services?</li>
-</ul>
-<p>The tree of life also reminds us of our connection to all living things, and our responsibility to care for them. As David M. Hillis wrote in his book Life: The Science of Biology, "The tree of life is a symbol of our shared heritage with all other living things. It is also a symbol of our shared future, for we depend on the continued existence of this diversity of life."</p>
-<p></p>
-
-<h2>The Benefits of Trees for People and the Planet</h2>
-<p>Trees are not only essential for the tree of life, but also for our own well-being and survival. Trees provide us with many benefits, such as:</p>
-<ul>
-<li>Trees absorb carbon dioxide and release oxygen, helping to mitigate climate change and improve air quality.</li>
-<li>Trees cool our neighborhoods by providing shade and evapotranspiration, reducing the urban heat island effect and lowering energy costs.</li>
-<li>Trees filter our water and prevent soil erosion, protecting our water sources and reducing flooding and landslides.</li>
-<li>Trees provide habitat and food for wildlife, supporting biodiversity and ecosystem services.</li>
-<li>Trees produce wood, fruits, nuts, medicines, and other products that we use every day.</li>
-<li>Trees enhance our mental and physical health by reducing stress, improving cognition, boosting immunity, and encouraging exercise.</li>
-</ul>
-<p>According to The Nature Conservancy, smarter management of trees, plants, and soil in the US alone could store the equivalent carbon of taking 57 million cars off the road. Trees are looking out for us, so we have to look out for them too.</p>
-
-<h2>How to Support Trees and Forests</h2>
-<p>There are many ways that we can support trees and forests, both locally and globally. Here are some actions that you can take:</p>
-<ol>
-<li>Plant a tree in your backyard, school, or community. Choose native species that are adapted to your climate and soil conditions.</li>
-<li>Care for your existing trees by watering, mulching, pruning, and protecting them from pests and diseases.</li>
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-<li>Support organizations that conserve and restore forests around the world. You can donate money, volunteer your time, or spread awareness about their work.</li>
-<li>Advocate for policies that promote sustainable forest management and protect forest rights. You can sign petitions, write letters, or join campaigns that address issues such as deforestation, illegal logging, land grabbing, or climate change.</li>
-</ol>
-<p>Trees are our allies in creating a healthier and happier world. By downloading the Hillis Tree of Life PDF for free, you can learn more about the amazing diversity of life on Earth and appreciate the beauty and value of trees. By supporting trees and forests in your actions, you can make a positive difference for yourself, your community, and the planet.</p> e93f5a0c3f<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/sunshineatnoon/TextureScraping/models/week0417/dataset.py b/spaces/sunshineatnoon/TextureScraping/models/week0417/dataset.py
deleted file mode 100644
index 6b1f28fbf0b05a81e1674a50b7a5adcee017c5a3..0000000000000000000000000000000000000000
--- a/spaces/sunshineatnoon/TextureScraping/models/week0417/dataset.py
+++ /dev/null
@@ -1,150 +0,0 @@
-import torch
-import torch.utils.data as data
-import torchvision.transforms as transforms
-
-import os
-import numpy as np
-from PIL import Image
-from glob import glob
-from skimage.segmentation import slic
-import torchvision.transforms.functional as TF
-from scipy.io import loadmat
-import random
-import cv2
-
-import sys
-sys.path.append("../..")
-
-def label2one_hot_torch(labels, C=14):
-    """ Converts an integer label torch.autograd.Variable to a one-hot Variable.
-
-    Args:
-      labels(tensor) : segmentation label
-      C (integer) : number of classes in labels
-
-    Returns:
-      target (tensor) : one-hot vector of the input label
-
-    Shape:
-      labels: (B, 1, H, W)
-      target: (B, N, H, W)
-    """
-    b,_, h, w = labels.shape
-    one_hot = torch.zeros(b, C, h, w, dtype=torch.long).to(labels)
-    target = one_hot.scatter_(1, labels.type(torch.long).data, 1) #require long type
-
-    return target.type(torch.float32)
-
-class Dataset(data.Dataset):
-    def __init__(self, data_dir, crop_size = 128, test=False,
-                 sp_num = 256, slic = True, preprocess_name = False,
-                 gt_label = False, label_path = None, test_time = False,
-                 img_path = None):
-        super(Dataset, self).__init__()
-        ext = ["*.jpg"]
-        dl = []
-        self.test = test
-        self.test_time = test_time
-
-        [dl.extend(glob(data_dir + '/**/' + e, recursive=True)) for e in ext]
-
-        data_list = sorted(dl)
-        self.data_list = data_list
-        self.sp_num = sp_num
-        self.slic = slic
-
-        self.crop = transforms.CenterCrop(size = (crop_size, crop_size))
-        self.crop_size = crop_size
-        self.test = test
-
-        self.gt_label = gt_label
-        if gt_label:
-            self.label_path = label_path
-
-        self.img_path = img_path
-
-    def preprocess_label(self, seg):
-        segs = label2one_hot_torch(seg.unsqueeze(0), C = seg.max() + 1)
-        new_seg = []
-        for cnt in range(seg.max() + 1):
-            if segs[0, cnt].sum() > 0:
-                new_seg.append(segs[0, cnt])
-        new_seg = torch.stack(new_seg)
-        return torch.argmax(new_seg, dim = 0)
-
-    def __getitem__(self, index):
-        if self.img_path is None:
-            data_path = self.data_list[index]
-        else:
-            data_path = self.img_path
-        rgb_img = Image.open(data_path)
-        imgH, imgW = rgb_img.size
-
-        if self.gt_label:
-            img_name = data_path.split("/")[-1].split("_")[0]
-            mat_path = os.path.join(self.label_path, data_path.split('/')[-2], img_name.replace('.jpg', '.mat'))
-            mat = loadmat(mat_path)
-            max_label_num = 0
-            final_seg = None
-            for i in range(len(mat['groundTruth'][0])):
-                seg = mat['groundTruth'][0][i][0][0][0]
-                if len(np.unique(seg)) > max_label_num:
-                    max_label_num = len(np.unique(seg))
-                    final_seg = seg
-            seg = torch.from_numpy(final_seg.astype(np.float32))
-            segs = seg.long().unsqueeze(0)
-
-        if self.img_path is None:
-            i, j, h, w = transforms.RandomCrop.get_params(rgb_img, output_size=(self.crop_size, self.crop_size))
-        else:
-            i = 40; j = 40; h = self.crop_size; w = self.crop_size
-        rgb_img = TF.crop(rgb_img, i, j, h, w)
-        if self.gt_label:
-            segs = TF.crop(segs, i, j, h, w)
-            segs = self.preprocess_label(segs)
-
-        if self.slic:
-            sp_num = self.sp_num
-            # compute superpixel
-            slic_i = slic(np.array(rgb_img), n_segments=sp_num, compactness=10, start_label=0, min_size_factor=0.3)
-            slic_i = torch.from_numpy(slic_i)
-            slic_i[slic_i >= sp_num] = sp_num - 1
-            oh = label2one_hot_torch(slic_i.unsqueeze(0).unsqueeze(0), C = sp_num).squeeze()
-
-        rgb_img = TF.to_tensor(rgb_img)
-        if rgb_img.shape[0] == 1:
-            rgb_img = rgb_img.repeat(3, 1, 1)
-        rgb_img = rgb_img[:3, :, :]
-
-        rets = []
-        rets.append(rgb_img)
-        if self.slic:
-            rets.append(oh)
-        rets.append(data_path.split("/")[-1])
-        rets.append(index)
-        if self.gt_label:
-            rets.append(segs.view(1, segs.shape[-2], segs.shape[-1]))
-        return rets
-
-    def __len__(self):
-        return len(self.data_list)
-
-if __name__ == '__main__':
-    import torchvision.utils as vutils
-    dataset = Dataset('/home/xtli/DATA/texture_data/',
-                      sampled_num=3000)
-    loader_ = torch.utils.data.DataLoader(dataset     = dataset,
-                                         batch_size  = 1,
-                                         shuffle     = True,
-                                         num_workers = 1,
-                                         drop_last   = True)
-    loader = iter(loader_)
-    img, points, pixs = loader.next()
-
-    crop_size = 128
-    canvas = torch.zeros((1, 3, crop_size, crop_size))
-    for i in range(points.shape[-2]):
-        p = (points[0, i] + 1) / 2.0 * (crop_size - 1)
-        canvas[0, :, int(p[0]), int(p[1])] = pixs[0, :, i]
-    vutils.save_image(canvas, 'canvas.png')
-    vutils.save_image(img, 'img.png')
diff --git a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Airport Simulator 2013 Download Full Version.md b/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Airport Simulator 2013 Download Full Version.md
deleted file mode 100644
index dc3e4916f66e2e72730e5e52ce18ec26f4ef2b6b..0000000000000000000000000000000000000000
--- a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Airport Simulator 2013 Download Full Version.md	
+++ /dev/null
@@ -1,27 +0,0 @@
-<br />
-```html
-<h1>Airport Simulator 2013 Download Full Version: How to Get It for Free</h1>
-<meta name="description" content="Airport Simulator 2013 is a realistic simulation game that lets you manage an airport. Learn how to download the full version of the game for free in this article.">
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-<p>But how can you get the full version of the game for free? There are many websites that claim to offer free downloads of Airport Simulator 2013, but most of them are either scams or viruses. You don't want to risk your computer's security or waste your time with fake downloads. That's why we have found a reliable and safe way to download Airport Simulator 2013 for free.</p>
-<h2>airport simulator 2013 download full version</h2><br /><p><b><b>Download Zip</b> &#127379; <a href="https://cinurl.com/2uEXpi">https://cinurl.com/2uEXpi</a></b></p><br /><br />
-<h2>How to Download Airport Simulator 2013 for Free</h2>
-<p>The best way to download Airport Simulator 2013 for free is to use a torrent site. Torrent sites are platforms that allow users to share files with each other. You can find almost any game or software on torrent sites, including Airport Simulator 2013. However, you need to be careful when using torrent sites, as some of them may contain malicious files or ads. You also need to use a VPN (virtual private network) to protect your identity and avoid legal issues.</p>
-<p>Here are the steps to download Airport Simulator 2013 for free using a torrent site:</p>
-<ol>
-<li>Download and install a VPN on your computer. A VPN will encrypt your data and hide your IP address, making you anonymous online. We recommend using <a href="https://www.nordvpn.com/">NordVPN</a>, as it is fast, secure, and easy to use.</li>
-<li>Download and install a torrent client on your computer. A torrent client is a software that allows you to download files from torrent sites. We recommend using <a href="https://www.qbittorrent.org/">qBittorrent</a>, as it is free, open-source, and lightweight.</li>
-<li>Go to a torrent site that has Airport Simulator 2013. We recommend using <a href="https://thepiratebay.org/">The Pirate Bay</a>, as it is one of the most popular and reliable torrent sites.</li>
-<li>Search for "Airport Simulator 2013" on the torrent site. You will see a list of results with different file sizes and seeders. Seeders are users who have the file and are sharing it with others. The more seeders a file has, the faster it will download.</li>
-<li>Choose a file that has a high number of seeders and a reasonable file size. Avoid files that are too large or too small, as they may be fake or corrupted.</li>
-<li>Click on the file name or the magnet link to start downloading it. A magnet link is a URL that contains information about the file, such as its name, size, and hash. It will automatically open your torrent client and start downloading the file.</li>
-<li>Wait for the download to finish. Depending on your internet speed and the number of seeders, it may take from a few minutes to several hours.</li>
-<li>Once the download is complete, open the file folder and run the setup.exe file. Follow the instructions on the screen to install Airport Simulator 2013 on your computer.</li>
-<li>Enjoy playing Airport Simulator 2013 for free!</li>
-</ol>
-<h2>Conclusion</h2>
-<p>Airport Simulator 2013 is a fun and realistic simulation game that lets you manage an airport. You can download the full version of the game for free using a torrent site, but you need to be careful and use a VPN and a torrent client. We hope this article helped you learn how to download Airport Simulator 2013 for free.</p>
-<p>If you liked this article, please share it with your friends and leave us a comment below. Thanks for reading!</p>
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diff --git a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Allegorithmic Bitmap2Material (B2M) 1.6 For Unity LINK.md b/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Allegorithmic Bitmap2Material (B2M) 1.6 For Unity LINK.md
deleted file mode 100644
index ad9d2fbe2f65a2127b4c6f1c62fc3716f98287c1..0000000000000000000000000000000000000000
--- a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Allegorithmic Bitmap2Material (B2M) 1.6 For Unity LINK.md	
+++ /dev/null
@@ -1,6 +0,0 @@
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-
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diff --git a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Arthamulla Hindu Matham Tamil Book Pdf _VERIFIED_.md b/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Arthamulla Hindu Matham Tamil Book Pdf _VERIFIED_.md
deleted file mode 100644
index 60075217d662cb291dd20b2607d81e825b4f1d3c..0000000000000000000000000000000000000000
--- a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Arthamulla Hindu Matham Tamil Book Pdf _VERIFIED_.md	
+++ /dev/null
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-<br />
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diff --git a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Asus P8h61-M Le Sm Bus Controller Driver ((EXCLUSIVE)).md b/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Asus P8h61-M Le Sm Bus Controller Driver ((EXCLUSIVE)).md
deleted file mode 100644
index 4077f425c5c39540a01851d06c433af5fd555dbb..0000000000000000000000000000000000000000
--- a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Asus P8h61-M Le Sm Bus Controller Driver ((EXCLUSIVE)).md	
+++ /dev/null
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-<h2>Asus P8h61-M Le Sm Bus Controller Driver</h2><br /><p><b><b>Download File</b> --->>> <a href="https://urluss.com/2uCEev">https://urluss.com/2uCEev</a></b></p><br /><br />
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diff --git a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Autocad 2004 Covadis 2004 Gratuit A Telecharger.rar.md b/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Autocad 2004 Covadis 2004 Gratuit A Telecharger.rar.md
deleted file mode 100644
index 101d8e6f7c7d977a5d907d6d7b511d10e3e48857..0000000000000000000000000000000000000000
--- a/spaces/surmensipa/VITS-Umamusume-voice-synthesizer/logs/Autocad 2004 Covadis 2004 Gratuit A Telecharger.rar.md	
+++ /dev/null
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-
-<h1>How to Download Autocad 2004 Covadis 2004 for Free</h1>
-<p>If you are looking for a software that can help you with civil engineering and surveying projects, you might be interested in Autocad 2004 Covadis 2004. This is a powerful and versatile tool that can handle various tasks such as drawing, designing, calculating, and analyzing. However, buying this software can be quite expensive, especially if you only need it for a short-term project. Fortunately, there is a way to download Autocad 2004 Covadis 2004 for free and use it without any limitations.</p>
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-<li>You are a hobbyist or an enthusiast who wants to learn more about civil engineering and surveying.</li>
-<li>You want to save money and avoid paying for expensive licenses or subscriptions.</li>
-</ul>
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diff --git a/spaces/svjack/ControlNet-Pose-Chinese/annotator/uniformer/mmcv/utils/progressbar.py b/spaces/svjack/ControlNet-Pose-Chinese/annotator/uniformer/mmcv/utils/progressbar.py
deleted file mode 100644
index 0062f670dd94fa9da559ab26ef85517dcf5211c7..0000000000000000000000000000000000000000
--- a/spaces/svjack/ControlNet-Pose-Chinese/annotator/uniformer/mmcv/utils/progressbar.py
+++ /dev/null
@@ -1,208 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import sys
-from collections.abc import Iterable
-from multiprocessing import Pool
-from shutil import get_terminal_size
-
-from .timer import Timer
-
-
-class ProgressBar:
-    """A progress bar which can print the progress."""
-
-    def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout):
-        self.task_num = task_num
-        self.bar_width = bar_width
-        self.completed = 0
-        self.file = file
-        if start:
-            self.start()
-
-    @property
-    def terminal_width(self):
-        width, _ = get_terminal_size()
-        return width
-
-    def start(self):
-        if self.task_num > 0:
-            self.file.write(f'[{" " * self.bar_width}] 0/{self.task_num}, '
-                            'elapsed: 0s, ETA:')
-        else:
-            self.file.write('completed: 0, elapsed: 0s')
-        self.file.flush()
-        self.timer = Timer()
-
-    def update(self, num_tasks=1):
-        assert num_tasks > 0
-        self.completed += num_tasks
-        elapsed = self.timer.since_start()
-        if elapsed > 0:
-            fps = self.completed / elapsed
-        else:
-            fps = float('inf')
-        if self.task_num > 0:
-            percentage = self.completed / float(self.task_num)
-            eta = int(elapsed * (1 - percentage) / percentage + 0.5)
-            msg = f'\r[{{}}] {self.completed}/{self.task_num}, ' \
-                  f'{fps:.1f} task/s, elapsed: {int(elapsed + 0.5)}s, ' \
-                  f'ETA: {eta:5}s'
-
-            bar_width = min(self.bar_width,
-                            int(self.terminal_width - len(msg)) + 2,
-                            int(self.terminal_width * 0.6))
-            bar_width = max(2, bar_width)
-            mark_width = int(bar_width * percentage)
-            bar_chars = '>' * mark_width + ' ' * (bar_width - mark_width)
-            self.file.write(msg.format(bar_chars))
-        else:
-            self.file.write(
-                f'completed: {self.completed}, elapsed: {int(elapsed + 0.5)}s,'
-                f' {fps:.1f} tasks/s')
-        self.file.flush()
-
-
-def track_progress(func, tasks, bar_width=50, file=sys.stdout, **kwargs):
-    """Track the progress of tasks execution with a progress bar.
-
-    Tasks are done with a simple for-loop.
-
-    Args:
-        func (callable): The function to be applied to each task.
-        tasks (list or tuple[Iterable, int]): A list of tasks or
-            (tasks, total num).
-        bar_width (int): Width of progress bar.
-
-    Returns:
-        list: The task results.
-    """
-    if isinstance(tasks, tuple):
-        assert len(tasks) == 2
-        assert isinstance(tasks[0], Iterable)
-        assert isinstance(tasks[1], int)
-        task_num = tasks[1]
-        tasks = tasks[0]
-    elif isinstance(tasks, Iterable):
-        task_num = len(tasks)
-    else:
-        raise TypeError(
-            '"tasks" must be an iterable object or a (iterator, int) tuple')
-    prog_bar = ProgressBar(task_num, bar_width, file=file)
-    results = []
-    for task in tasks:
-        results.append(func(task, **kwargs))
-        prog_bar.update()
-    prog_bar.file.write('\n')
-    return results
-
-
-def init_pool(process_num, initializer=None, initargs=None):
-    if initializer is None:
-        return Pool(process_num)
-    elif initargs is None:
-        return Pool(process_num, initializer)
-    else:
-        if not isinstance(initargs, tuple):
-            raise TypeError('"initargs" must be a tuple')
-        return Pool(process_num, initializer, initargs)
-
-
-def track_parallel_progress(func,
-                            tasks,
-                            nproc,
-                            initializer=None,
-                            initargs=None,
-                            bar_width=50,
-                            chunksize=1,
-                            skip_first=False,
-                            keep_order=True,
-                            file=sys.stdout):
-    """Track the progress of parallel task execution with a progress bar.
-
-    The built-in :mod:`multiprocessing` module is used for process pools and
-    tasks are done with :func:`Pool.map` or :func:`Pool.imap_unordered`.
-
-    Args:
-        func (callable): The function to be applied to each task.
-        tasks (list or tuple[Iterable, int]): A list of tasks or
-            (tasks, total num).
-        nproc (int): Process (worker) number.
-        initializer (None or callable): Refer to :class:`multiprocessing.Pool`
-            for details.
-        initargs (None or tuple): Refer to :class:`multiprocessing.Pool` for
-            details.
-        chunksize (int): Refer to :class:`multiprocessing.Pool` for details.
-        bar_width (int): Width of progress bar.
-        skip_first (bool): Whether to skip the first sample for each worker
-            when estimating fps, since the initialization step may takes
-            longer.
-        keep_order (bool): If True, :func:`Pool.imap` is used, otherwise
-            :func:`Pool.imap_unordered` is used.
-
-    Returns:
-        list: The task results.
-    """
-    if isinstance(tasks, tuple):
-        assert len(tasks) == 2
-        assert isinstance(tasks[0], Iterable)
-        assert isinstance(tasks[1], int)
-        task_num = tasks[1]
-        tasks = tasks[0]
-    elif isinstance(tasks, Iterable):
-        task_num = len(tasks)
-    else:
-        raise TypeError(
-            '"tasks" must be an iterable object or a (iterator, int) tuple')
-    pool = init_pool(nproc, initializer, initargs)
-    start = not skip_first
-    task_num -= nproc * chunksize * int(skip_first)
-    prog_bar = ProgressBar(task_num, bar_width, start, file=file)
-    results = []
-    if keep_order:
-        gen = pool.imap(func, tasks, chunksize)
-    else:
-        gen = pool.imap_unordered(func, tasks, chunksize)
-    for result in gen:
-        results.append(result)
-        if skip_first:
-            if len(results) < nproc * chunksize:
-                continue
-            elif len(results) == nproc * chunksize:
-                prog_bar.start()
-                continue
-        prog_bar.update()
-    prog_bar.file.write('\n')
-    pool.close()
-    pool.join()
-    return results
-
-
-def track_iter_progress(tasks, bar_width=50, file=sys.stdout):
-    """Track the progress of tasks iteration or enumeration with a progress
-    bar.
-
-    Tasks are yielded with a simple for-loop.
-
-    Args:
-        tasks (list or tuple[Iterable, int]): A list of tasks or
-            (tasks, total num).
-        bar_width (int): Width of progress bar.
-
-    Yields:
-        list: The task results.
-    """
-    if isinstance(tasks, tuple):
-        assert len(tasks) == 2
-        assert isinstance(tasks[0], Iterable)
-        assert isinstance(tasks[1], int)
-        task_num = tasks[1]
-        tasks = tasks[0]
-    elif isinstance(tasks, Iterable):
-        task_num = len(tasks)
-    else:
-        raise TypeError(
-            '"tasks" must be an iterable object or a (iterator, int) tuple')
-    prog_bar = ProgressBar(task_num, bar_width, file=file)
-    for task in tasks:
-        yield task
-        prog_bar.update()
-    prog_bar.file.write('\n')
diff --git a/spaces/taesiri/DeticChatGPT/detic/config.py b/spaces/taesiri/DeticChatGPT/detic/config.py
deleted file mode 100644
index b6132f70116518b55e3b653fc6cd4ec9f61e50b0..0000000000000000000000000000000000000000
--- a/spaces/taesiri/DeticChatGPT/detic/config.py
+++ /dev/null
@@ -1,131 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from detectron2.config import CfgNode as CN
-
-def add_detic_config(cfg):
-    _C = cfg
-
-    _C.WITH_IMAGE_LABELS = False # Turn on co-training with classification data
-
-    # Open-vocabulary classifier
-    _C.MODEL.ROI_BOX_HEAD.USE_ZEROSHOT_CLS = False # Use fixed classifier for open-vocabulary detection
-    _C.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_PATH = 'datasets/metadata/lvis_v1_clip_a+cname.npy'
-    _C.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_DIM = 512
-    _C.MODEL.ROI_BOX_HEAD.NORM_WEIGHT = True
-    _C.MODEL.ROI_BOX_HEAD.NORM_TEMP = 50.0
-    _C.MODEL.ROI_BOX_HEAD.IGNORE_ZERO_CATS = False
-    _C.MODEL.ROI_BOX_HEAD.USE_BIAS = 0.0 # >= 0: not use
-    
-    _C.MODEL.ROI_BOX_HEAD.MULT_PROPOSAL_SCORE = False # CenterNet2
-    _C.MODEL.ROI_BOX_HEAD.USE_SIGMOID_CE = False
-    _C.MODEL.ROI_BOX_HEAD.PRIOR_PROB = 0.01
-    _C.MODEL.ROI_BOX_HEAD.USE_FED_LOSS = False # Federated Loss
-    _C.MODEL.ROI_BOX_HEAD.CAT_FREQ_PATH = \
-        'datasets/metadata/lvis_v1_train_cat_info.json'
-    _C.MODEL.ROI_BOX_HEAD.FED_LOSS_NUM_CAT = 50
-    _C.MODEL.ROI_BOX_HEAD.FED_LOSS_FREQ_WEIGHT = 0.5
-
-    # Classification data configs
-    _C.MODEL.ROI_BOX_HEAD.IMAGE_LABEL_LOSS = 'max_size' # max, softmax, sum
-    _C.MODEL.ROI_BOX_HEAD.IMAGE_LOSS_WEIGHT = 0.1
-    _C.MODEL.ROI_BOX_HEAD.IMAGE_BOX_SIZE = 1.0
-    _C.MODEL.ROI_BOX_HEAD.ADD_IMAGE_BOX = False # Used for image-box loss and caption loss
-    _C.MODEL.ROI_BOX_HEAD.WS_NUM_PROPS = 128 # num proposals for image-labeled data
-    _C.MODEL.ROI_BOX_HEAD.WITH_SOFTMAX_PROP = False # Used for WSDDN
-    _C.MODEL.ROI_BOX_HEAD.CAPTION_WEIGHT = 1.0 # Caption loss weight
-    _C.MODEL.ROI_BOX_HEAD.NEG_CAP_WEIGHT = 0.125 # Caption loss hyper-parameter
-    _C.MODEL.ROI_BOX_HEAD.ADD_FEATURE_TO_PROP = False # Used for WSDDN
-    _C.MODEL.ROI_BOX_HEAD.SOFTMAX_WEAK_LOSS = False # Used when USE_SIGMOID_CE is False
-
-    _C.MODEL.ROI_HEADS.MASK_WEIGHT = 1.0
-    _C.MODEL.ROI_HEADS.ONE_CLASS_PER_PROPOSAL = False # For demo only
-
-    # Caption losses
-    _C.MODEL.CAP_BATCH_RATIO = 4 # Ratio between detection data and caption data
-    _C.MODEL.WITH_CAPTION = False
-    _C.MODEL.SYNC_CAPTION_BATCH = False # synchronize across GPUs to enlarge # "classes"
-
-    # dynamic class sampling when training with 21K classes
-    _C.MODEL.DYNAMIC_CLASSIFIER = False
-    _C.MODEL.NUM_SAMPLE_CATS = 50
-
-    # Different classifiers in testing, used in cross-dataset evaluation
-    _C.MODEL.RESET_CLS_TESTS = False
-    _C.MODEL.TEST_CLASSIFIERS = []
-    _C.MODEL.TEST_NUM_CLASSES = []
-
-    # Backbones
-    _C.MODEL.SWIN = CN()
-    _C.MODEL.SWIN.SIZE = 'T' # 'T', 'S', 'B'
-    _C.MODEL.SWIN.USE_CHECKPOINT = False
-    _C.MODEL.SWIN.OUT_FEATURES = (1, 2, 3) # FPN stride 8 - 32
-
-    _C.MODEL.TIMM = CN()
-    _C.MODEL.TIMM.BASE_NAME = 'resnet50'
-    _C.MODEL.TIMM.OUT_LEVELS = (3, 4, 5)
-    _C.MODEL.TIMM.NORM = 'FrozenBN'
-    _C.MODEL.TIMM.FREEZE_AT = 0
-    _C.MODEL.DATASET_LOSS_WEIGHT = []
-    
-    # Multi-dataset dataloader
-    _C.DATALOADER.DATASET_RATIO = [1, 1] # sample ratio
-    _C.DATALOADER.USE_RFS = [False, False]
-    _C.DATALOADER.MULTI_DATASET_GROUPING = False # Always true when multi-dataset is enabled
-    _C.DATALOADER.DATASET_ANN = ['box', 'box'] # Annotation type of each dataset
-    _C.DATALOADER.USE_DIFF_BS_SIZE = False # Use different batchsize for each dataset
-    _C.DATALOADER.DATASET_BS = [8, 32] # Used when USE_DIFF_BS_SIZE is on
-    _C.DATALOADER.DATASET_INPUT_SIZE = [896, 384] # Used when USE_DIFF_BS_SIZE is on
-    _C.DATALOADER.DATASET_INPUT_SCALE = [(0.1, 2.0), (0.5, 1.5)] # Used when USE_DIFF_BS_SIZE is on 
-    _C.DATALOADER.DATASET_MIN_SIZES = [(640, 800), (320, 400)] # Used when USE_DIFF_BS_SIZE is on
-    _C.DATALOADER.DATASET_MAX_SIZES = [1333, 667] # Used when USE_DIFF_BS_SIZE is on
-    _C.DATALOADER.USE_TAR_DATASET = False # for ImageNet-21K, directly reading from unziped files
-    _C.DATALOADER.TARFILE_PATH = 'datasets/imagenet/metadata-22k/tar_files.npy'
-    _C.DATALOADER.TAR_INDEX_DIR = 'datasets/imagenet/metadata-22k/tarindex_npy'
-    
-    _C.SOLVER.USE_CUSTOM_SOLVER = False
-    _C.SOLVER.OPTIMIZER = 'SGD'
-    _C.SOLVER.BACKBONE_MULTIPLIER = 1.0 # Used in DETR
-    _C.SOLVER.CUSTOM_MULTIPLIER = 1.0 # Used in DETR
-    _C.SOLVER.CUSTOM_MULTIPLIER_NAME = [] # Used in DETR
-
-    # Deformable DETR
-    _C.MODEL.DETR = CN()
-    _C.MODEL.DETR.NUM_CLASSES = 80
-    _C.MODEL.DETR.FROZEN_WEIGHTS = '' # For Segmentation
-    _C.MODEL.DETR.GIOU_WEIGHT = 2.0
-    _C.MODEL.DETR.L1_WEIGHT = 5.0
-    _C.MODEL.DETR.DEEP_SUPERVISION = True
-    _C.MODEL.DETR.NO_OBJECT_WEIGHT = 0.1
-    _C.MODEL.DETR.CLS_WEIGHT = 2.0
-    _C.MODEL.DETR.NUM_FEATURE_LEVELS = 4
-    _C.MODEL.DETR.TWO_STAGE = False
-    _C.MODEL.DETR.WITH_BOX_REFINE = False
-    _C.MODEL.DETR.FOCAL_ALPHA = 0.25
-    _C.MODEL.DETR.NHEADS = 8
-    _C.MODEL.DETR.DROPOUT = 0.1
-    _C.MODEL.DETR.DIM_FEEDFORWARD = 2048
-    _C.MODEL.DETR.ENC_LAYERS = 6
-    _C.MODEL.DETR.DEC_LAYERS = 6
-    _C.MODEL.DETR.PRE_NORM = False
-    _C.MODEL.DETR.HIDDEN_DIM = 256
-    _C.MODEL.DETR.NUM_OBJECT_QUERIES = 100
-
-    _C.MODEL.DETR.USE_FED_LOSS = False
-    _C.MODEL.DETR.WEAK_WEIGHT = 0.1
-
-    _C.INPUT.CUSTOM_AUG = ''
-    _C.INPUT.TRAIN_SIZE = 640
-    _C.INPUT.TEST_SIZE = 640
-    _C.INPUT.SCALE_RANGE = (0.1, 2.)
-    # 'default' for fixed short/ long edge, 'square' for max size=INPUT.SIZE
-    _C.INPUT.TEST_INPUT_TYPE = 'default' 
-
-    _C.FIND_UNUSED_PARAM = True
-    _C.EVAL_PRED_AR = False
-    _C.EVAL_PROPOSAL_AR = False
-    _C.EVAL_CAT_SPEC_AR = False
-    _C.IS_DEBUG = False
-    _C.QUICK_DEBUG = False
-    _C.FP16 = False
-    _C.EVAL_AP_FIX = False
-    _C.GEN_PSEDO_LABELS = False
-    _C.SAVE_DEBUG_PATH = 'output/save_debug/'
\ No newline at end of file
diff --git a/spaces/tarunika-03/personality-pred/README.md b/spaces/tarunika-03/personality-pred/README.md
deleted file mode 100644
index bf126eca9e6ee15957a101b28cdc25d1641641b2..0000000000000000000000000000000000000000
--- a/spaces/tarunika-03/personality-pred/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Personality Pred
-emoji: 📈
-colorFrom: green
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.21.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/terfces0erbo/CollegeProjectV2/FIFA 14 1.3.0.0 Update Crack Torrent.md b/spaces/terfces0erbo/CollegeProjectV2/FIFA 14 1.3.0.0 Update Crack Torrent.md
deleted file mode 100644
index d22c7f41acdf10cee2d9f088cc242bfc132cc3dc..0000000000000000000000000000000000000000
--- a/spaces/terfces0erbo/CollegeProjectV2/FIFA 14 1.3.0.0 Update Crack Torrent.md	
+++ /dev/null
@@ -1,17 +0,0 @@
-
-<h1>FIFA 14 1.3.0.0 Update Crack Torrent: What You Need to Know</h1>
-<p>FIFA 14 is a popular football simulation video game developed by EA Canada and published by Electronic Arts. It was released in late September 2013 for various platforms, including PC, PS3, PS4, PS Vita, Xbox One and Xbox 360. The game features over 69 stadiums, including real-world venues, and a new game engine called the Ignite Engine, which enhances the graphics and gameplay of the game.</p>
-<h2>FIFA 14 1.3.0.0 Update Crack Torrent</h2><br /><p><b><b>DOWNLOAD</b> ->>> <a href="https://bytlly.com/2uGl0V">https://bytlly.com/2uGl0V</a></b></p><br /><br />
-<p>If you are a fan of FIFA 14 and want to enjoy the latest updates and features of the game, you might be interested in downloading the FIFA 14 1.3.0.0 Update Crack Torrent. This is a file that contains the patch for the game that fixes some bugs and improves the performance of the game. It also includes a crack that bypasses the DRM protection of the game and allows you to play it without any restrictions.</p>
-<p>However, before you download the FIFA 14 1.3.0.0 Update Crack Torrent, there are some things you need to know. First of all, downloading and using a cracked version of the game is illegal and may violate the terms of service of EA and your platform provider. You may face legal consequences or lose access to your account if you are caught using a pirated copy of the game. Secondly, downloading a torrent file from an unknown source may expose your device to malware or viruses that can harm your system or steal your personal information. You should always be careful when downloading files from the internet and use a reliable antivirus software to scan them before opening them.</p>
-<p>Therefore, if you want to play FIFA 14 with the latest updates and features, we recommend that you buy the official version of the game from EA or your platform provider and download the updates from their official websites. This way, you can enjoy the game legally and safely without risking your device or your account.</p>
-<p></p><p>So, what are some of the features and reviews of FIFA 14 that make it such a great game? Here are some of the highlights:</p>
-<ul>
-<li>FIFA 14 introduces a new game engine called the Ignite Engine, which improves the graphics, physics, animation, and AI of the game. The game looks more realistic and fluid, with players moving and reacting more naturally and dynamically. The ball also behaves more unpredictably, adding more challenge and excitement to the gameplay[^1^].</li>
-<li>FIFA 14 also changes the pace and style of the game, making it more strategic and rewarding. The game requires more careful buildup play and thoughtful tactics, as run-and-gun attacks are met with stronger defence and counterattacks. The game also features more variety and depth in player animation, making each action look more authentic and unique[^1^] [^2^].</li>
-<li>FIFA 14 offers a wide range of game modes and features for different types of players. The game includes all the modes and features from the current-gen version, such as career mode, skill games, online friendlies, seasons, and Ultimate Team. Ultimate Team is one of the most popular modes, where players can create their own custom teams from a pool of players and compete online or offline. The mode also features transferable progress between current-gen and next-gen versions[^2^].</li>
-<li>FIFA 14 has received mostly positive reviews from critics and players alike. The game has an average score of 87 out of 100 on Metacritic for the PC version[^3^]. Critics praised the game for its realistic and engaging gameplay, improved graphics and animation, and comprehensive game modes and features. Some of the drawbacks mentioned were the lack of major innovations, the occasional offside calls from the AI, and the awkwardness of some player movements[^1^] [^2^].</li>
-</ul>
-<p>In conclusion, FIFA 14 is a highly polished and enjoyable football simulation game that offers a lot of content and fun for fans of the sport. The game improves on many aspects of its predecessors, while maintaining the core gameplay that makes FIFA so popular. If you are looking for a realistic and immersive football experience on your PC or next-gen console, FIFA 14 is a great choice.</p> d5da3c52bf<br />
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\ No newline at end of file
diff --git a/spaces/thejagstudio/procom/main/urls.py b/spaces/thejagstudio/procom/main/urls.py
deleted file mode 100644
index 54e1dd3295b734ecc7ef8b4f2df62e9f3a586e5f..0000000000000000000000000000000000000000
--- a/spaces/thejagstudio/procom/main/urls.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from django.urls import path
-from . import views
-from django.conf import settings
-
-urlpatterns = [
-    path('category/<str:category>/', views.getProductData),
-    path('search/', views.searchQuery),
-    path('fetchCategory/', views.fetchCategory),
-    path('getComparisonChart/', views.getComparisonChart),
-    path('dataManipulator/', views.dataManipulator),
-    path('dataAdder/', views.dataAdder),
-    path('comparisionData/', views.comparisionData),
-    path('fetchPriceData/', views.fetchPriceData)
-]
diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Discover Godiego Great Best Japanese Rar The Complete Discography of the Amazing Band.md b/spaces/tialenAdioni/chat-gpt-api/logs/Discover Godiego Great Best Japanese Rar The Complete Discography of the Amazing Band.md
deleted file mode 100644
index 7369dde2f5bdb7f8fa266c95504787046aba9eeb..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Discover Godiego Great Best Japanese Rar The Complete Discography of the Amazing Band.md	
+++ /dev/null
@@ -1,64 +0,0 @@
-
-<h1>Godiego Great Best Japanese Rar: A Rare Collection of Classic Rock Songs</h1>
-<p>If you are a fan of Japanese rock music, you might have heard of Godiego, a legendary band that was active from 1976 to 1985. Godiego was known for their catchy tunes, diverse influences, and memorable themes for anime and movies. Some of their most famous songs include "Monkey Magic", "Gandhara", and "Galaxy Express 999".</p>
-<p>But did you know that there is a rare compilation album of Godiego's songs that was released only in Japan? It's called Godiego Great Best Japanese Rar, and it contains 18 tracks of Godiego's best songs in Japanese. This album is a must-have for any Godiego fan or collector, as it showcases the band's versatility and talent in their native language.</p>
-<h2>Godiego Great Best Japanese Rar</h2><br /><p><b><b>Download Zip</b> &middot;&middot;&middot;&middot;&middot; <a href="https://urlcod.com/2uK9Jm">https://urlcod.com/2uK9Jm</a></b></p><br /><br />
-<p>Godiego Great Best Japanese Rar was released in 1994 by Nippon Columbia, and it is now out of print and hard to find. However, you can still download it online from various sources, such as <a href="https://www.discogs.com/Godiego-Godiego-Great-Best-Japanese-Rar/release/2890640">Discogs</a> or <a href="https://www.amazon.co.jp/-/en/Godiego/dp/B00005ED8E">Amazon Japan</a>. But be careful, as some of these downloads might be corrupted or incomplete. You can also try to find a physical copy on eBay or other online marketplaces, but be prepared to pay a high price for this rare gem.</p>
-<p>Godiego Great Best Japanese Rar is a perfect example of how Godiego blended rock, pop, folk, and world music into their own unique style. The album features songs from different genres and eras, such as the psychedelic rock of "Beautiful Name", the disco funk of "Thank You", the folk rock of "Kiseki no Hoshi", and the synth pop of "Computer Obaachan". The album also includes some of Godiego's most iconic themes, such as the epic "Saiyuuki" from the anime series Monkey, the uplifting "Tatakae! Gokiburi-tai" from the movie Cockroach Soldiers, and the romantic "Ai no Tame ni" from the movie The Return of Ultraman.</p>
-<p>If you want to experience the best of Godiego's music in Japanese, you should definitely check out Godiego Great Best Japanese Rar. It is a rare and valuable collection of classic rock songs that will make you sing along, dance, and feel nostalgic. Godiego Great Best Japanese Rar is not only a great album, but also a great tribute to one of the most influential and beloved bands in Japanese rock history.</p>
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-<p>Godiego was formed in 1976 by keyboardist and composer Mickey Yoshino, who recruited vocalist Masashi "Marcy" Tashiro, guitarist Takami Asano, bassist Steve Fox, and drummer Tommy Snyder. The band's name was derived from the Chinese novel Journey to the West, which was also the inspiration for their first major hit, "Monkey Magic". Godiego's music was influenced by various genres and cultures, such as rock, pop, folk, blues, jazz, Indian, Arabic, and African music. They also collaborated with renowned lyricists and producers, such as Yoko Narahashi, Keisuke Yamakawa, and Shunichi Tokura.</p>
-<p>Godiego achieved fame and popularity not only in Japan, but also in other Asian countries, such as China, Hong Kong, Taiwan, Singapore, Malaysia, Thailand, and Indonesia. They were especially popular in China, where they performed live concerts and appeared on television shows. They also toured in Europe and America, where they met and worked with other famous musicians, such as Paul McCartney, George Harrison, Eric Clapton, and Stevie Wonder. Godiego's music was also used in various anime and movies, such as Galaxy Express 999, The Return of Ultraman, Cockroach Soldiers, House, and The Silk Road.</p>
-<p>Godiego disbanded in 1985 due to creative differences and personal issues. However, they reunited several times for special occasions and anniversary concerts. They also released new albums and compilations of their old songs. In 2006, they were awarded the Japan Record Special Award for their contribution to Japanese music. In 2016, they celebrated their 40th anniversary with a new album and a nationwide tour. Godiego's legacy lives on through their music and their fans.</p> e753bf7129<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/How to Crack Microsoft Office 2019 on Mac and Why You Shouldnt.md b/spaces/tialenAdioni/chat-gpt-api/logs/How to Crack Microsoft Office 2019 on Mac and Why You Shouldnt.md
deleted file mode 100644
index df9bbe8621139c9a70014ceb17608459bf889a27..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/How to Crack Microsoft Office 2019 on Mac and Why You Shouldnt.md	
+++ /dev/null
@@ -1,41 +0,0 @@
-<br />
-<h1>How to Get Microsoft Office 2019 for Free on Mac</h1>
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-<p>Microsoft Office 2019 is the latest version of the popular productivity suite that includes Word, Excel, PowerPoint, Outlook, OneNote, and more. It offers new features and improvements over the previous versions, such as:</p>
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diff --git a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Bling2 MOD APK Go Live or Watch Live Streams with No Limits (Unlocked Rooms No Ads).md b/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Bling2 MOD APK Go Live or Watch Live Streams with No Limits (Unlocked Rooms No Ads).md
deleted file mode 100644
index dc94a748b17aeb8fc302ce00e70bb23d38d8d661..0000000000000000000000000000000000000000
--- a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Bling2 MOD APK Go Live or Watch Live Streams with No Limits (Unlocked Rooms No Ads).md	
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-<p>The final step is to launch the app and sign in with your Google account. You can use your existing Google account or create a new one if you don't have one. This will allow you to access all the features of Bling2 Mod APK and start streaming or playing games.</p>
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diff --git a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Border of Wild Mod APK A Fallout Survivor Game with Stunning Graphics.md b/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Border of Wild Mod APK A Fallout Survivor Game with Stunning Graphics.md
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--- a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Border of Wild Mod APK A Fallout Survivor Game with Stunning Graphics.md	
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Use stealth, cover, traps, distractions, and environmental hazards to - Use the environment to your advantage. You can use fire, water, wind, and electricity to create various effects and damage your enemies. For example, you can shoot a fire arrow at a wooden barrel to make it explode, or throw a metal weapon at an enemy in a thunderstorm to attract lightning. Be careful, though, as these elements can also harm you if you're not careful. - Manage your stamina and health. You have a stamina meter that depletes when you run, climb, swim, glide, or perform other actions. If it runs out, you will be unable to move or even fall to your death. You also have a health meter that decreases when you take damage from enemies or the environment. You can restore both meters by eating food or drinking elixirs that you can craft from various ingredients. - Upgrade your gear and skills. You can find or buy new gear and weapons that have different stats and abilities. You can also enhance them by visiting certain NPCs or locations. You can also upgrade your skills by completing shrines, which are mini-dungeons scattered across the world. Shrines reward you with spirit orbs, which you can exchange for more hearts or stamina at goddess statues. - Experiment and have fun. Border of Wild is a game that encourages creativity and exploration. You can try different approaches to solve puzzles, defeat enemies, or reach new places. You can also interact with various NPCs and animals, and discover hidden secrets and easter eggs. There is no right or wrong way to play Border of Wild, so feel free to experiment and have fun. | H2: What are the Reviews of Border of Wild? | <h2>What are the Reviews of Border of Wild?</h2> | | P: A brief overview of the reviews and ratings of Border of Wild from different sources and platforms. | <p>Border of Wild is a game that has received mostly positive reviews and ratings from players and critics alike. 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A: Yes, you can play Border of Wild offline without an internet connection. However, some features and content may not be available offline, such as online multiplayer mode, daily rewards, and updates. - Q: How do I save my progress in Border of Wild? A: Border of Wild automatically saves your progress every time you exit the game or complete a mission. You can also manually save your progress by tapping on the menu button on the top right corner of the screen and selecting "Save Game". - Q: What are the minimum requirements to play Border of Wild? A: The minimum requirements to play Border of Wild are Android 4.4 or higher, 2 GB of RAM, 500 MB of free storage space, and a stable internet connection (optional). | <ul><li>Q: Is Border of Wild mod apk safe to download?<br>A: Yes, Border of Wild mod apk safe to download from trusted websites that offer verified links and files. 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-<br />
-<h1>How to Choose and Use the Best PS3 Emulator for PC and Android</h1>
-<p>Do you miss playing your favorite PlayStation 3 games but don't have access to the console anymore? Or do you want to experience some classic PS3 titles that you never got the chance to play before? If so, you might be interested in using a PS3 emulator.</p>
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-<h2>What is a PS3 emulator?</h2>
-<p>A PS3 emulator is a software program that allows you to play PlayStation 3 games on your computer or mobile device. It works by simulating the hardware and software of the PS3 console, so that you can run the games as if they were running on the original system.</p>
-<h2>What are the benefits and drawbacks of using a PS3 emulator?</h2>
-<p>Using a PS3 emulator has some advantages and disadvantages that you should be aware of before deciding whether to use one or not. Here are some of them:</p>
-<ul>
-<li><b>Benefits</b></li>
-<ul>
-<li>You can play PS3 games without having to buy the console or the discs.</li>
-<li>You can play PS3 games on different devices, such as PC, Android, Mac, Linux, etc.</li>
-<li>You can enhance the graphics and sound quality of the games by adjusting the settings of the emulator.</li>
-<li>You can use different controllers or keyboard/mouse inputs to play the games.</li>
-<li>You can save and load game states at any point during the gameplay.</li>
-<li>You can use cheats or mods to modify the games.</li>
-</ul>
-<li><b>Drawbacks</b></li>
-<ul>
-<li>Not all PS3 games are compatible with all emulators. Some games may not run at all or may have glitches or errors.</li>
-<li>Some emulators may require high-end hardware and software specifications to run smoothly.</li>
-<li>Some emulators may be difficult to install or configure properly <h2>How to choose a PS3 emulator</h2>
-<p>Now that you know what a PS3 emulator is and what are its benefits and drawbacks, you might be wondering how to choose the best one for your needs. There are many PS3 emulators available, but not all of them are equally good. Here are some of the main features to look for in a PS3 emulator:</p>
-<ul>
-<li><b>Compatibility</b>: This is the most important factor to consider when choosing a PS3 emulator. You want an emulator that can run as many PS3 games as possible, without major glitches or errors. You can check the compatibility lists of each emulator to see which games are supported and how well they run.</li>
-<li><b>Stability</b>: This is another crucial factor to consider when choosing a PS3 emulator. You want an emulator that can run smoothly and reliably, without crashing or freezing. You also want an emulator that is regularly updated and maintained by its developers, so that any bugs or issues are fixed promptly.</li>
-<li><b>Graphics</b>: This is a factor that can enhance your gaming experience when using a PS3 emulator. You want an emulator that can render the graphics of the PS3 games in high resolution and quality, and that can also apply various enhancements, such as anti-aliasing, texture filtering, shaders, etc.</li>
-<li><b>Sound</b>: This is another factor that can enhance your gaming experience when using a PS3 emulator. You want an emulator that can reproduce the sound of the PS3 games in high fidelity and quality, and that can also support various audio formats, such as Dolby Digital, DTS, etc.</li>
-<li><b>Controller support</b>: This is a factor that can affect your comfort and convenience when using a PS3 emulator. You want an emulator that can support various input devices, such as keyboards, mice, gamepads, joysticks, etc. You also want an emulator that can allow you to customize the controller mappings and settings to suit your preferences.</li>
-<li><b>Online functionality</b>: This is a factor that can expand your gaming options when using a PS3 emulator. You want an emulator that can support online features, such as multiplayer, chat, trophies, etc. You also want an emulator that can connect to various online services, such as PlayStation Network, Steam, etc.</li>
-<li><b>User interface</b>: This is a factor that can affect your ease of use and accessibility when using a PS3 emulator. You want an emulator that has a user-friendly and intuitive interface, that can allow you to easily navigate and configure the various options and settings of the emulator.</li>
-</ul>
-<h2>What are some of the best PS3 emulators available?</h2>
-<p>Based on the above criteria, here are some of the best PS3 emulators available for PC and Android:</p>
-<table>
-<tr><th>Name</th><th>Platform</th><th>Description</th></tr>
-<tr><td><a href="(^1^)">RPCS3</a></td><td>PC (Windows, Linux)</td><td>This is one of the most popular and advanced PS3 emulators for PC. It supports over 6000 PS3 games, with high compatibility and performance. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="(^2^)">Mednafen</a></td><td>PC (Windows)</td><td>This is another popular and versatile PS3 emulator for PC. It supports over 4000 PS3 games, with good compatibility and stability. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="(^3^)">ESX-PS3</a></td><td>PC (Windows)</td><td>This is another promising and powerful PS3 emulator for PC. It supports over 3000 PS3 games, with decent compatibility and performance. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="(^4^)">PlayStation Now</a></td><td>PC (Windows), Android</td><td>This is not exactly an emulator, but rather a cloud gaming service that allows you to stream PS3 games on your PC or Android device. It supports over 800 PS3 games, with excellent compatibility and quality. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="(^5^)">PSeMu3</a></td><td>PC (Windows)</td><td>This is another simple and easy-to-use PS3 emulator for PC. It supports over. 2000 PS3 games, with fair compatibility and speed. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="">BizHawk</a></td><td>PC (Windows)</td><td>This is another multi-system PS3 emulator for PC. It supports over 1000 PS3 games, with moderate compatibility and stability. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="">Nucleus</a></td><td>PC (Windows)</td><td>This is another experimental and innovative PS3 emulator for PC. It supports over 500 PS3 games, with low compatibility and performance. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-<tr><td><a href="">Short Waves</a></td><td>Android</td><td>This is one of the few PS3 emulators for Android. It supports over 100 PS3 games, with very low compatibility and quality. It also supports various graphical and audio enhancements, controller support, online functionality, and user interface customization.</td></tr>
-</table>
-<h2>How to use a PS3 emulator</h2>
-<p>Once you have chosen a PS3 emulator that suits your needs, you might be wondering how to use it. Here are some of the basic steps that you need to follow to use a PS3 emulator:</p>
-<h3>What are the system requirements for using a PS3 emulator?</h3>
-<p>Before you can use a PS3 emulator, you need to make sure that your device meets the minimum and recommended system requirements for running the emulator. These requirements may vary depending on the emulator and the game that you want to play, but here are some general guidelines:</p>
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-<ul>
-<li><b>For PC</b></li>
-<ul>
-<li>Minimum: Windows 7 or higher, Intel Core i5 or AMD Ryzen 5 processor, 4 GB of RAM, NVIDIA GeForce GTX 660 or AMD Radeon HD 7870 graphics card, DirectX 11 or higher, 50 GB of free disk space.</li>
-<li>Recommended: Windows 10 or higher, Intel Core i7 or AMD Ryzen 7 processor, 8 GB of RAM or more, NVIDIA GeForce GTX 1060 or AMD Radeon RX 580 graphics card or better, DirectX 12 or higher, 100 GB of free disk space or more.</li>
-</ul>
-<li><b>For Android</b></li>
-<ul>
-<li>Minimum: Android 5.0 or higher, quad-core processor, 2 GB of RAM, Mali-T720 or Adreno 330 graphics chip, OpenGL ES 3.0 or higher, 10 GB of free storage space.</li>
-<li>Recommended: Android 8.0 or higher, octa-core processor, 4 GB of RAM or more, Mali-G71 or Adreno 540 graphics chip or better, OpenGL ES 3.1 or higher, 20 GB of free storage space or more.</li>
-</ul>
-</ul>
-<h3>How to install and configure a PS3 emulator?</h3>
-<p>The next step is to install and configure the PS3 emulator on your device. The exact process may differ depending on the emulator and the device that you are using, but here are some general steps that you can follow:</p>
-<ol>
-<li>Download the PS3 emulator from its official website or a trusted source. Make sure that you download the latest version of the emulator that is compatible with your device.</li>
-<li>Extract the emulator files from the downloaded archive file using a file manager or an extraction tool.</li>
-<li>Run the emulator executable file to launch the emulator. You may need to grant some permissions or accept some terms and conditions before you can use the emulator.</li>
-<li>Navigate to the settings menu of the emulator and adjust the various options and settings according to your preferences. You can change the graphics, sound, controller, online, and user interface settings of the emulator.</li>
-<li>Save the settings and exit the menu.</li>
-</ol>
-<h3>How to load and play PS3 games on a PS3 emulator?</h3>
-<p>The final step is to load and play PS3 games on your PS3 emulator. The exact process may differ depending on the emulator and the game that you want to play, but here are some general steps that you can follow:</p>
-<ol>
-<li>Obtain the PS3 game files that you want to play. You can either rip them from your own PS3 discs using a disc drive and a ripping software, or download them from online sources. Make sure that you obtain the game files legally and ethically.</li <li>Place the PS3 game files in a folder on your device. You can either use the default folder of the emulator or create a new one. Make sure that the game files are in the correct format, such as ISO, BIN, PKG, etc.</li>
-<li>Run the emulator and navigate to the file menu. Select the option to load or open a PS3 game file. Browse to the folder where you placed the game files and select the one that you want to play.</li>
-<li>Wait for the emulator to load the game file. You may see some loading screens or messages before the game starts.</li>
-<li>Enjoy playing the PS3 game on your emulator. You can use your controller or keyboard/mouse inputs to control the gameplay. You can also access the emulator menu to save and load game states, use cheats or mods, stream or record gameplay, etc.</li>
-</ol>
-<h2>Conclusion</h2>
-<p>In this article, I have provided you with some information on how to choose and use the best PS3 emulator for PC and Android. PS3 emulators are software programs that allow you to play PlayStation 3 games on your computer or mobile device. They can be a great way to enjoy your favorite PS3 titles without having to buy the console or the discs. However, not all PS3 emulators are created equal. Some are more compatible, stable, and user-friendly than others.</p>
-<p>To choose the best PS3 emulator for your needs, you should consider some of the main features, such as compatibility, stability, graphics, sound, controller support, online functionality, and user interface. You should also compare some of the most popular and reliable PS3 emulators available, such as RPCS3, Mednafen, ESX-PS3, PlayStation Now, PSeMu3, BizHawk, Nucleus, and Short Waves.</p>
-<p>To use a PS3 emulator, you should make sure that your device meets the system requirements for running the emulator. You should also follow some of the basic steps, such as installing and configuring the emulator, obtaining and loading the PS3 game files, and playing the PS3 games on your emulator.</p>
-<p>I hope that this article has been helpful and informative for you. If you have any questions or comments about PS3 emulators, feel free to leave them below. Thank you for reading and happy gaming!</p>
-<h2>FAQs</h2>
-<p>Here are some of the frequently asked questions and answers about PS3 emulators:</p>
-<ul>
-<li><b>How do I update my PS3 emulator?</b></li>
-<p>To update your PS3 emulator, you should visit its official website or a trusted source and download the latest version of the emulator. Then, you should extract the new emulator files from the downloaded archive file and replace the old emulator files with them. You may need to backup your settings and game files before updating your emulator.</p>
-<li><b>How do I fix common errors or issues with my PS3 emulator?</b></li>
-<p>To fix common errors or issues with your PS3 emulator, you should try some of the following solutions:</p>
-<ul>
-<li>Check if your device meets the system requirements for running the emulator.</li>
-<li>Check if your emulator is updated to the latest version.</li>
-<li>Check if your game files are in the correct format and compatible with your emulator.</li>
-<li>Check if your settings are adjusted properly for optimal performance and user experience.</li>
-<li>Check if your controller or input device is working properly and configured correctly.</li>
-<li>Check if your internet connection is stable and secure.</li>
-<li>Check if there are any solutions or patches available for your specific error or issue on the internet or on the emulator's website or forum.</li>
-</ul>
-<li><b>How do I save and load game states on my PS3 emulator?</b></li>
-<p>To save and load game states on your PS3 emulator, you should follow these steps:</p>
-<ol>
-<li>Access the emulator menu by pressing a certain key or button on your controller or keyboard/mouse.</li>
-<li>Select the option to save or load a game state.</li <li>Choose a slot or a file name to save or load the game state.</li>
-<li>Confirm your choice and wait for the process to complete.</li>
-</ol>
-<p>Note that saving and loading game states may not work for all games or emulators, and may cause some errors or issues. It is recommended to use the in-game save and load features whenever possible.</p>
-<li><b>How do I use cheats or mods on my PS3 emulator?</b></li>
-<p>To use cheats or mods on your PS3 emulator, you should follow these steps:</p>
-<ol>
-<li>Download the cheat or mod files that you want to use from online sources. Make sure that they are compatible with your game and emulator.</li>
-<li>Place the cheat or mod files in a folder on your device. You can either use the default folder of the emulator or create a new one.</li>
-<li>Access the emulator menu and select the option to enable or disable cheats or mods.</li>
-<li>Browse to the folder where you placed the cheat or mod files and select the ones that you want to use.</li>
-<li>Confirm your choice and restart the emulator or the game if necessary.</li>
-</ol>
-<p>Note that using cheats or mods may not work for all games or emulators, and may cause some errors or issues. It is also advised to use cheats or mods ethically and responsibly, and not to use them for online gaming or competitive purposes.</p>
-<li><b>How do I stream or record gameplay on my PS3 emulator?</b></li>
-<p>To stream or record gameplay on your PS3 emulator, you should follow these steps:</p>
-<ol>
-<li>Download and install a streaming or recording software on your device, such as OBS Studio, XSplit, Bandicam, etc.</li>
-<li>Launch the streaming or recording software and configure the settings according to your preferences. You can adjust the video quality, audio quality, frame rate, bitrate, etc.</li>
-<li>Add the PS3 emulator as a source or a window to capture on the streaming or recording software.</li>
-<li>Start the PS3 emulator and load the game that you want to stream or record.</li>
-<li>Start the streaming or recording process on the software and choose a destination or a platform to stream or record to. You can stream to platforms such as Twitch, YouTube, Facebook, etc., or record to your device's storage.</li>
-</ol>
-<p>Note that streaming or recording gameplay may require high-end hardware and software specifications, and may affect the performance and quality of the emulator and the game. It is also advised to respect the intellectual property rights of the game developers and publishers when streaming or recording gameplay.</p> 401be4b1e0<br />
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diff --git a/spaces/tioseFevbu/cartoon-converter/scripts/Bitvise Ssh Client 6.08 BETTER Full 14.md b/spaces/tioseFevbu/cartoon-converter/scripts/Bitvise Ssh Client 6.08 BETTER Full 14.md
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-<br />
-<h1>How to Download and Install Bitvise SSH Client 6.08 Full 14</h1>
-<p>Bitvise SSH Client is a free and powerful software that allows you to connect to remote servers using SSH protocol. You can use it to transfer files, execute commands, and create secure tunnels. Bitvise SSH Client supports all desktop and server versions of Windows, 32-bit and 64-bit, from Windows XP SP3 and Windows Server 2003, up to the most recent – Windows 11 and Windows Server 2022[^1^].</p>
-<h2>bitvise ssh client 6.08 full 14</h2><br /><p><b><b>Download File</b> &#10084;&#10084;&#10084; <a href="https://urlcod.com/2uHxKn">https://urlcod.com/2uHxKn</a></b></p><br /><br />
-<p>In this article, we will show you how to download and install Bitvise SSH Client 6.08 Full 14, which is the latest version available as of April 2023. This version includes many features and improvements, such as:</p>
-<ul>
-<li>Automatic resuming, text file awareness, recursive subdirectory transfers, and verified-integrity resume with servers that support SFTP v6 check-file and check-file-blocks[^1^].</li>
-<li>Directory mirroring with servers that support SFTP v6 check-file and check-file-blocks[^1^].</li>
-<li>SSH jump proxy: Connect to a final destination SSH or SFTP server by connecting through an SSH jump server[^1^].</li>
-<li>Obfuscated SSH with an optional keyword: When supported and enabled in both the client and server, obfuscation makes it more difficult for an observer to detect that the protocol being used is SSH[^1^].</li>
-<li>SFTP drive mapping: Access files on an SFTP server as if they were local, from any Windows application[^1^].</li>
-<li>An FTP-to-SFTP bridge allowing you to connect to an SFTP server using legacy FTP applications[^1^].</li>
-<li>A scriptable command-line SFTP client, sftpc; a scriptable command-line remote execution client, sexec; a scriptable command-line tunneling client, stnlc; and a .NET SSH library, FlowSshNet[^1^].</li>
-<li>Bitvise SSH Server remote administration features[^1^].</li>
-</ul>
-<p>To download Bitvise SSH Client 6.08 Full 14, follow these steps:</p>
-<ol>
-<li>Go to the official website of Bitvise at <a href="https://www.bitvise.com/">https://www.bitvise.com/</a>[^3^].</li>
-<li>Click on the Bitvise SSH Client link on the top menu bar.</li>
-<li>Click on the Download Bitvise SSH Client link on the left sidebar.</li>
-<li>You will see a link to Amazon CloudFront that should be very reliable. If it does not work, try the alternative link below it. The current version is 9.27 and the size is 25.8 MB[^2^].</li>
-<li>Click on the link to download the installer executable file.</li>
-<li>If you are using Windows Server 2016 or later, right-click the installer executable file in Windows Explorer, click Properties, and see if you need to check Unblock on the General tab[^2^].</li>
-<li>Double-click the installer executable file to start the installation process.</li>
-<li>Read and agree with the License Terms of Bitvise SSH Client.</li>
-<li>Follow the instructions on the screen to complete the installation.</li>
-</ol>
-<p>Congratulations! You have successfully downloaded and installed Bitvise SSH Client 6.08 Full 14 on your Windows machine. You can now use it to connect to remote servers using SSH protocol.</p>
-<p></p> 81aa517590<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py b/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py
deleted file mode 100644
index 2a965f595ff0756002e2a2c79da551fa8c8fff25..0000000000000000000000000000000000000000
--- a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_vendor/cachecontrol/cache.py
+++ /dev/null
@@ -1,65 +0,0 @@
-# SPDX-FileCopyrightText: 2015 Eric Larson
-#
-# SPDX-License-Identifier: Apache-2.0
-
-"""
-The cache object API for implementing caches. The default is a thread
-safe in-memory dictionary.
-"""
-from threading import Lock
-
-
-class BaseCache(object):
-
-    def get(self, key):
-        raise NotImplementedError()
-
-    def set(self, key, value, expires=None):
-        raise NotImplementedError()
-
-    def delete(self, key):
-        raise NotImplementedError()
-
-    def close(self):
-        pass
-
-
-class DictCache(BaseCache):
-
-    def __init__(self, init_dict=None):
-        self.lock = Lock()
-        self.data = init_dict or {}
-
-    def get(self, key):
-        return self.data.get(key, None)
-
-    def set(self, key, value, expires=None):
-        with self.lock:
-            self.data.update({key: value})
-
-    def delete(self, key):
-        with self.lock:
-            if key in self.data:
-                self.data.pop(key)
-
-
-class SeparateBodyBaseCache(BaseCache):
-    """
-    In this variant, the body is not stored mixed in with the metadata, but is
-    passed in (as a bytes-like object) in a separate call to ``set_body()``.
-
-    That is, the expected interaction pattern is::
-
-        cache.set(key, serialized_metadata)
-        cache.set_body(key)
-
-    Similarly, the body should be loaded separately via ``get_body()``.
-    """
-    def set_body(self, key, body):
-        raise NotImplementedError()
-
-    def get_body(self, key):
-        """
-        Return the body as file-like object.
-        """
-        raise NotImplementedError()
diff --git a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_distutils/cmd.py b/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_distutils/cmd.py
deleted file mode 100644
index 4a9bcc2a733f77d3c6202311f8a2966e7c0630b3..0000000000000000000000000000000000000000
--- a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_distutils/cmd.py
+++ /dev/null
@@ -1,434 +0,0 @@
-"""distutils.cmd
-
-Provides the Command class, the base class for the command classes
-in the distutils.command package.
-"""
-
-import sys, os, re
-from distutils.errors import DistutilsOptionError
-from distutils import util, dir_util, file_util, archive_util, dep_util
-from distutils import log
-
-
-class Command:
-    """Abstract base class for defining command classes, the "worker bees"
-    of the Distutils.  A useful analogy for command classes is to think of
-    them as subroutines with local variables called "options".  The options
-    are "declared" in 'initialize_options()' and "defined" (given their
-    final values, aka "finalized") in 'finalize_options()', both of which
-    must be defined by every command class.  The distinction between the
-    two is necessary because option values might come from the outside
-    world (command line, config file, ...), and any options dependent on
-    other options must be computed *after* these outside influences have
-    been processed -- hence 'finalize_options()'.  The "body" of the
-    subroutine, where it does all its work based on the values of its
-    options, is the 'run()' method, which must also be implemented by every
-    command class.
-    """
-
-    # 'sub_commands' formalizes the notion of a "family" of commands,
-    # eg. "install" as the parent with sub-commands "install_lib",
-    # "install_headers", etc.  The parent of a family of commands
-    # defines 'sub_commands' as a class attribute; it's a list of
-    #    (command_name : string, predicate : unbound_method | string | None)
-    # tuples, where 'predicate' is a method of the parent command that
-    # determines whether the corresponding command is applicable in the
-    # current situation.  (Eg. we "install_headers" is only applicable if
-    # we have any C header files to install.)  If 'predicate' is None,
-    # that command is always applicable.
-    #
-    # 'sub_commands' is usually defined at the *end* of a class, because
-    # predicates can be unbound methods, so they must already have been
-    # defined.  The canonical example is the "install" command.
-    sub_commands = []
-
-    # -- Creation/initialization methods -------------------------------
-
-    def __init__(self, dist):
-        """Create and initialize a new Command object.  Most importantly,
-        invokes the 'initialize_options()' method, which is the real
-        initializer and depends on the actual command being
-        instantiated.
-        """
-        # late import because of mutual dependence between these classes
-        from distutils.dist import Distribution
-
-        if not isinstance(dist, Distribution):
-            raise TypeError("dist must be a Distribution instance")
-        if self.__class__ is Command:
-            raise RuntimeError("Command is an abstract class")
-
-        self.distribution = dist
-        self.initialize_options()
-
-        # Per-command versions of the global flags, so that the user can
-        # customize Distutils' behaviour command-by-command and let some
-        # commands fall back on the Distribution's behaviour.  None means
-        # "not defined, check self.distribution's copy", while 0 or 1 mean
-        # false and true (duh).  Note that this means figuring out the real
-        # value of each flag is a touch complicated -- hence "self._dry_run"
-        # will be handled by __getattr__, below.
-        # XXX This needs to be fixed.
-        self._dry_run = None
-
-        # verbose is largely ignored, but needs to be set for
-        # backwards compatibility (I think)?
-        self.verbose = dist.verbose
-
-        # Some commands define a 'self.force' option to ignore file
-        # timestamps, but methods defined *here* assume that
-        # 'self.force' exists for all commands.  So define it here
-        # just to be safe.
-        self.force = None
-
-        # The 'help' flag is just used for command-line parsing, so
-        # none of that complicated bureaucracy is needed.
-        self.help = 0
-
-        # 'finalized' records whether or not 'finalize_options()' has been
-        # called.  'finalize_options()' itself should not pay attention to
-        # this flag: it is the business of 'ensure_finalized()', which
-        # always calls 'finalize_options()', to respect/update it.
-        self.finalized = 0
-
-    # XXX A more explicit way to customize dry_run would be better.
-    def __getattr__(self, attr):
-        if attr == 'dry_run':
-            myval = getattr(self, "_" + attr)
-            if myval is None:
-                return getattr(self.distribution, attr)
-            else:
-                return myval
-        else:
-            raise AttributeError(attr)
-
-    def ensure_finalized(self):
-        if not self.finalized:
-            self.finalize_options()
-        self.finalized = 1
-
-    # Subclasses must define:
-    #   initialize_options()
-    #     provide default values for all options; may be customized by
-    #     setup script, by options from config file(s), or by command-line
-    #     options
-    #   finalize_options()
-    #     decide on the final values for all options; this is called
-    #     after all possible intervention from the outside world
-    #     (command-line, option file, etc.) has been processed
-    #   run()
-    #     run the command: do whatever it is we're here to do,
-    #     controlled by the command's various option values
-
-    def initialize_options(self):
-        """Set default values for all the options that this command
-        supports.  Note that these defaults may be overridden by other
-        commands, by the setup script, by config files, or by the
-        command-line.  Thus, this is not the place to code dependencies
-        between options; generally, 'initialize_options()' implementations
-        are just a bunch of "self.foo = None" assignments.
-
-        This method must be implemented by all command classes.
-        """
-        raise RuntimeError(
-            "abstract method -- subclass %s must override" % self.__class__
-        )
-
-    def finalize_options(self):
-        """Set final values for all the options that this command supports.
-        This is always called as late as possible, ie.  after any option
-        assignments from the command-line or from other commands have been
-        done.  Thus, this is the place to code option dependencies: if
-        'foo' depends on 'bar', then it is safe to set 'foo' from 'bar' as
-        long as 'foo' still has the same value it was assigned in
-        'initialize_options()'.
-
-        This method must be implemented by all command classes.
-        """
-        raise RuntimeError(
-            "abstract method -- subclass %s must override" % self.__class__
-        )
-
-    def dump_options(self, header=None, indent=""):
-        from distutils.fancy_getopt import longopt_xlate
-
-        if header is None:
-            header = "command options for '%s':" % self.get_command_name()
-        self.announce(indent + header, level=log.INFO)
-        indent = indent + "  "
-        for (option, _, _) in self.user_options:
-            option = option.translate(longopt_xlate)
-            if option[-1] == "=":
-                option = option[:-1]
-            value = getattr(self, option)
-            self.announce(indent + "%s = %s" % (option, value), level=log.INFO)
-
-    def run(self):
-        """A command's raison d'etre: carry out the action it exists to
-        perform, controlled by the options initialized in
-        'initialize_options()', customized by other commands, the setup
-        script, the command-line, and config files, and finalized in
-        'finalize_options()'.  All terminal output and filesystem
-        interaction should be done by 'run()'.
-
-        This method must be implemented by all command classes.
-        """
-        raise RuntimeError(
-            "abstract method -- subclass %s must override" % self.__class__
-        )
-
-    def announce(self, msg, level=1):
-        """If the current verbosity level is of greater than or equal to
-        'level' print 'msg' to stdout.
-        """
-        log.log(level, msg)
-
-    def debug_print(self, msg):
-        """Print 'msg' to stdout if the global DEBUG (taken from the
-        DISTUTILS_DEBUG environment variable) flag is true.
-        """
-        from distutils.debug import DEBUG
-
-        if DEBUG:
-            print(msg)
-            sys.stdout.flush()
-
-    # -- Option validation methods -------------------------------------
-    # (these are very handy in writing the 'finalize_options()' method)
-    #
-    # NB. the general philosophy here is to ensure that a particular option
-    # value meets certain type and value constraints.  If not, we try to
-    # force it into conformance (eg. if we expect a list but have a string,
-    # split the string on comma and/or whitespace).  If we can't force the
-    # option into conformance, raise DistutilsOptionError.  Thus, command
-    # classes need do nothing more than (eg.)
-    #   self.ensure_string_list('foo')
-    # and they can be guaranteed that thereafter, self.foo will be
-    # a list of strings.
-
-    def _ensure_stringlike(self, option, what, default=None):
-        val = getattr(self, option)
-        if val is None:
-            setattr(self, option, default)
-            return default
-        elif not isinstance(val, str):
-            raise DistutilsOptionError(
-                "'%s' must be a %s (got `%s`)" % (option, what, val)
-            )
-        return val
-
-    def ensure_string(self, option, default=None):
-        """Ensure that 'option' is a string; if not defined, set it to
-        'default'.
-        """
-        self._ensure_stringlike(option, "string", default)
-
-    def ensure_string_list(self, option):
-        r"""Ensure that 'option' is a list of strings.  If 'option' is
-        currently a string, we split it either on /,\s*/ or /\s+/, so
-        "foo bar baz", "foo,bar,baz", and "foo,   bar baz" all become
-        ["foo", "bar", "baz"].
-        """
-        val = getattr(self, option)
-        if val is None:
-            return
-        elif isinstance(val, str):
-            setattr(self, option, re.split(r',\s*|\s+', val))
-        else:
-            if isinstance(val, list):
-                ok = all(isinstance(v, str) for v in val)
-            else:
-                ok = False
-            if not ok:
-                raise DistutilsOptionError(
-                    "'%s' must be a list of strings (got %r)" % (option, val)
-                )
-
-    def _ensure_tested_string(self, option, tester, what, error_fmt, default=None):
-        val = self._ensure_stringlike(option, what, default)
-        if val is not None and not tester(val):
-            raise DistutilsOptionError(
-                ("error in '%s' option: " + error_fmt) % (option, val)
-            )
-
-    def ensure_filename(self, option):
-        """Ensure that 'option' is the name of an existing file."""
-        self._ensure_tested_string(
-            option, os.path.isfile, "filename", "'%s' does not exist or is not a file"
-        )
-
-    def ensure_dirname(self, option):
-        self._ensure_tested_string(
-            option,
-            os.path.isdir,
-            "directory name",
-            "'%s' does not exist or is not a directory",
-        )
-
-    # -- Convenience methods for commands ------------------------------
-
-    def get_command_name(self):
-        if hasattr(self, 'command_name'):
-            return self.command_name
-        else:
-            return self.__class__.__name__
-
-    def set_undefined_options(self, src_cmd, *option_pairs):
-        """Set the values of any "undefined" options from corresponding
-        option values in some other command object.  "Undefined" here means
-        "is None", which is the convention used to indicate that an option
-        has not been changed between 'initialize_options()' and
-        'finalize_options()'.  Usually called from 'finalize_options()' for
-        options that depend on some other command rather than another
-        option of the same command.  'src_cmd' is the other command from
-        which option values will be taken (a command object will be created
-        for it if necessary); the remaining arguments are
-        '(src_option,dst_option)' tuples which mean "take the value of
-        'src_option' in the 'src_cmd' command object, and copy it to
-        'dst_option' in the current command object".
-        """
-        # Option_pairs: list of (src_option, dst_option) tuples
-        src_cmd_obj = self.distribution.get_command_obj(src_cmd)
-        src_cmd_obj.ensure_finalized()
-        for (src_option, dst_option) in option_pairs:
-            if getattr(self, dst_option) is None:
-                setattr(self, dst_option, getattr(src_cmd_obj, src_option))
-
-    def get_finalized_command(self, command, create=1):
-        """Wrapper around Distribution's 'get_command_obj()' method: find
-        (create if necessary and 'create' is true) the command object for
-        'command', call its 'ensure_finalized()' method, and return the
-        finalized command object.
-        """
-        cmd_obj = self.distribution.get_command_obj(command, create)
-        cmd_obj.ensure_finalized()
-        return cmd_obj
-
-    # XXX rename to 'get_reinitialized_command()'? (should do the
-    # same in dist.py, if so)
-    def reinitialize_command(self, command, reinit_subcommands=0):
-        return self.distribution.reinitialize_command(command, reinit_subcommands)
-
-    def run_command(self, command):
-        """Run some other command: uses the 'run_command()' method of
-        Distribution, which creates and finalizes the command object if
-        necessary and then invokes its 'run()' method.
-        """
-        self.distribution.run_command(command)
-
-    def get_sub_commands(self):
-        """Determine the sub-commands that are relevant in the current
-        distribution (ie., that need to be run).  This is based on the
-        'sub_commands' class attribute: each tuple in that list may include
-        a method that we call to determine if the subcommand needs to be
-        run for the current distribution.  Return a list of command names.
-        """
-        commands = []
-        for (cmd_name, method) in self.sub_commands:
-            if method is None or method(self):
-                commands.append(cmd_name)
-        return commands
-
-    # -- External world manipulation -----------------------------------
-
-    def warn(self, msg):
-        log.warn("warning: %s: %s\n", self.get_command_name(), msg)
-
-    def execute(self, func, args, msg=None, level=1):
-        util.execute(func, args, msg, dry_run=self.dry_run)
-
-    def mkpath(self, name, mode=0o777):
-        dir_util.mkpath(name, mode, dry_run=self.dry_run)
-
-    def copy_file(
-        self, infile, outfile, preserve_mode=1, preserve_times=1, link=None, level=1
-    ):
-        """Copy a file respecting verbose, dry-run and force flags.  (The
-        former two default to whatever is in the Distribution object, and
-        the latter defaults to false for commands that don't define it.)"""
-        return file_util.copy_file(
-            infile,
-            outfile,
-            preserve_mode,
-            preserve_times,
-            not self.force,
-            link,
-            dry_run=self.dry_run,
-        )
-
-    def copy_tree(
-        self,
-        infile,
-        outfile,
-        preserve_mode=1,
-        preserve_times=1,
-        preserve_symlinks=0,
-        level=1,
-    ):
-        """Copy an entire directory tree respecting verbose, dry-run,
-        and force flags.
-        """
-        return dir_util.copy_tree(
-            infile,
-            outfile,
-            preserve_mode,
-            preserve_times,
-            preserve_symlinks,
-            not self.force,
-            dry_run=self.dry_run,
-        )
-
-    def move_file(self, src, dst, level=1):
-        """Move a file respecting dry-run flag."""
-        return file_util.move_file(src, dst, dry_run=self.dry_run)
-
-    def spawn(self, cmd, search_path=1, level=1):
-        """Spawn an external command respecting dry-run flag."""
-        from distutils.spawn import spawn
-
-        spawn(cmd, search_path, dry_run=self.dry_run)
-
-    def make_archive(
-        self, base_name, format, root_dir=None, base_dir=None, owner=None, group=None
-    ):
-        return archive_util.make_archive(
-            base_name,
-            format,
-            root_dir,
-            base_dir,
-            dry_run=self.dry_run,
-            owner=owner,
-            group=group,
-        )
-
-    def make_file(
-        self, infiles, outfile, func, args, exec_msg=None, skip_msg=None, level=1
-    ):
-        """Special case of 'execute()' for operations that process one or
-        more input files and generate one output file.  Works just like
-        'execute()', except the operation is skipped and a different
-        message printed if 'outfile' already exists and is newer than all
-        files listed in 'infiles'.  If the command defined 'self.force',
-        and it is true, then the command is unconditionally run -- does no
-        timestamp checks.
-        """
-        if skip_msg is None:
-            skip_msg = "skipping %s (inputs unchanged)" % outfile
-
-        # Allow 'infiles' to be a single string
-        if isinstance(infiles, str):
-            infiles = (infiles,)
-        elif not isinstance(infiles, (list, tuple)):
-            raise TypeError("'infiles' must be a string, or a list or tuple of strings")
-
-        if exec_msg is None:
-            exec_msg = "generating %s from %s" % (outfile, ', '.join(infiles))
-
-        # If 'outfile' must be regenerated (either because it doesn't
-        # exist, is out-of-date, or the 'force' flag is true) then
-        # perform the action that presumably regenerates it
-        if self.force or dep_util.newer_group(infiles, outfile):
-            self.execute(func, args, exec_msg, level)
-        # Otherwise, print the "skip" message
-        else:
-            log.debug(skip_msg)
diff --git a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/config/_validate_pyproject/extra_validations.py b/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/config/_validate_pyproject/extra_validations.py
deleted file mode 100644
index 48c4e257fe21ce8320ae34d261089bdf3c76aaa4..0000000000000000000000000000000000000000
--- a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/config/_validate_pyproject/extra_validations.py
+++ /dev/null
@@ -1,36 +0,0 @@
-"""The purpose of this module is implement PEP 621 validations that are
-difficult to express as a JSON Schema (or that are not supported by the current
-JSON Schema library).
-"""
-
-from typing import Mapping, TypeVar
-
-from .fastjsonschema_exceptions import JsonSchemaValueException
-
-T = TypeVar("T", bound=Mapping)
-
-
-class RedefiningStaticFieldAsDynamic(JsonSchemaValueException):
-    """According to PEP 621:
-
-    Build back-ends MUST raise an error if the metadata specifies a field
-    statically as well as being listed in dynamic.
-    """
-
-
-def validate_project_dynamic(pyproject: T) -> T:
-    project_table = pyproject.get("project", {})
-    dynamic = project_table.get("dynamic", [])
-
-    for field in dynamic:
-        if field in project_table:
-            msg = f"You cannot provide a value for `project.{field}` and "
-            msg += "list it under `project.dynamic` at the same time"
-            name = f"data.project.{field}"
-            value = {field: project_table[field], "...": " # ...", "dynamic": dynamic}
-            raise RedefiningStaticFieldAsDynamic(msg, value, name, rule="PEP 621")
-
-    return pyproject
-
-
-EXTRA_VALIDATIONS = (validate_project_dynamic,)
diff --git a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/hrnet/htc_hrnetv2p_w18_20e_coco.py b/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/hrnet/htc_hrnetv2p_w18_20e_coco.py
deleted file mode 100644
index 391636ff452471af367ed14be5faa49c0b7e1be6..0000000000000000000000000000000000000000
--- a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/hrnet/htc_hrnetv2p_w18_20e_coco.py
+++ /dev/null
@@ -1,9 +0,0 @@
-_base_ = './htc_hrnetv2p_w32_20e_coco.py'
-model = dict(
-    pretrained='open-mmlab://msra/hrnetv2_w18',
-    backbone=dict(
-        extra=dict(
-            stage2=dict(num_channels=(18, 36)),
-            stage3=dict(num_channels=(18, 36, 72)),
-            stage4=dict(num_channels=(18, 36, 72, 144)))),
-    neck=dict(type='HRFPN', in_channels=[18, 36, 72, 144], out_channels=256))
diff --git a/spaces/tracinginsights/F1-analysis/pages/Laps_In_Top_10.py b/spaces/tracinginsights/F1-analysis/pages/Laps_In_Top_10.py
deleted file mode 100644
index 990a846a6d5d0f4fc50a303cf674c65a44e6b3c9..0000000000000000000000000000000000000000
--- a/spaces/tracinginsights/F1-analysis/pages/Laps_In_Top_10.py
+++ /dev/null
@@ -1,23 +0,0 @@
-import streamlit as st
-from repo_directory import Laps_In_Top_10
-from repo_directory import button
-import pandas as pd
-
-YEAR_SELECTED = st.selectbox(
-    'Select Year',
-    (2023, 2022, 2021, 2020, 2019, 2018))
-
-
-race_names_df, lap_times_df, teams_df, results_df, pit_stops_df, drivers_df = Laps_In_Top_10.load_data()
-
-events = Laps_In_Top_10.get_events(YEAR_SELECTED, race_names_df)
-
-RACE_SELECTED = st.selectbox(
-    'Select Race',
-    events.tolist())
-
-
-try:
-    Laps_In_Top_10.plot(YEAR_SELECTED, RACE_SELECTED, race_names_df, lap_times_df, teams_df, results_df, pit_stops_df, drivers_df)
-except:
-    pass
\ No newline at end of file
diff --git a/spaces/trttung1610/musicgen/scripts/templates/index.html b/spaces/trttung1610/musicgen/scripts/templates/index.html
deleted file mode 100644
index 7bd3afe9d933271bb922c1a0a534dd6b86fe67bc..0000000000000000000000000000000000000000
--- a/spaces/trttung1610/musicgen/scripts/templates/index.html
+++ /dev/null
@@ -1,28 +0,0 @@
-{% extends "base.html" %}
-{% block content %}
-
-<p>
-    Welcome <span class="special">{{session['user']}}</span> to the internal MOS assistant for AudioCraft.
-    You can create custom surveys between your models, that you can
-    evaluate yourself, or with the help of your teammates, by simply
-    sharing a link!
-</p>
-
-{% for error in errors %}
-<p class="error">{{error}}</p>
-{% endfor %}
-<form method="post" action="{{url_for('index')}}" class="simple_form">
-    <div>
-        <label for="xps"> Space separated lists of XP SIGS or Grid names:
-        </label><br>
-        <textarea autofocus name="xps" rows="4" cols="30"></textarea>
-    </div>
-    <div>
-        <label> Blind study
-            <input type="checkbox" name="blind">
-        </label>
-    </div>
-    <input type="submit" value="Create study">
-<form>
-
-{% endblock %}
diff --git a/spaces/trysem/coloria/colorizers/siggraph17.py b/spaces/trysem/coloria/colorizers/siggraph17.py
deleted file mode 100644
index 775a23f25d03f3bf1761e5d2bbf4b400eb2c6047..0000000000000000000000000000000000000000
--- a/spaces/trysem/coloria/colorizers/siggraph17.py
+++ /dev/null
@@ -1,168 +0,0 @@
-import torch
-import torch.nn as nn
-
-from .base_color import *
-
-class SIGGRAPHGenerator(BaseColor):
-    def __init__(self, norm_layer=nn.BatchNorm2d, classes=529):
-        super(SIGGRAPHGenerator, self).__init__()
-
-        # Conv1
-        model1=[nn.Conv2d(4, 64, kernel_size=3, stride=1, padding=1, bias=True),]
-        model1+=[nn.ReLU(True),]
-        model1+=[nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1, bias=True),]
-        model1+=[nn.ReLU(True),]
-        model1+=[norm_layer(64),]
-        # add a subsampling operation
-
-        # Conv2
-        model2=[nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1, bias=True),]
-        model2+=[nn.ReLU(True),]
-        model2+=[nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1, bias=True),]
-        model2+=[nn.ReLU(True),]
-        model2+=[norm_layer(128),]
-        # add a subsampling layer operation
-
-        # Conv3
-        model3=[nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-        model3+=[nn.ReLU(True),]
-        model3+=[nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-        model3+=[nn.ReLU(True),]
-        model3+=[nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-        model3+=[nn.ReLU(True),]
-        model3+=[norm_layer(256),]
-        # add a subsampling layer operation
-
-        # Conv4
-        model4=[nn.Conv2d(256, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model4+=[nn.ReLU(True),]
-        model4+=[nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model4+=[nn.ReLU(True),]
-        model4+=[nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model4+=[nn.ReLU(True),]
-        model4+=[norm_layer(512),]
-
-        # Conv5
-        model5=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model5+=[nn.ReLU(True),]
-        model5+=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model5+=[nn.ReLU(True),]
-        model5+=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model5+=[nn.ReLU(True),]
-        model5+=[norm_layer(512),]
-
-        # Conv6
-        model6=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model6+=[nn.ReLU(True),]
-        model6+=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model6+=[nn.ReLU(True),]
-        model6+=[nn.Conv2d(512, 512, kernel_size=3, dilation=2, stride=1, padding=2, bias=True),]
-        model6+=[nn.ReLU(True),]
-        model6+=[norm_layer(512),]
-
-        # Conv7
-        model7=[nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model7+=[nn.ReLU(True),]
-        model7+=[nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model7+=[nn.ReLU(True),]
-        model7+=[nn.Conv2d(512, 512, kernel_size=3, stride=1, padding=1, bias=True),]
-        model7+=[nn.ReLU(True),]
-        model7+=[norm_layer(512),]
-
-        # Conv7
-        model8up=[nn.ConvTranspose2d(512, 256, kernel_size=4, stride=2, padding=1, bias=True)]
-        model3short8=[nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-
-        model8=[nn.ReLU(True),]
-        model8+=[nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-        model8+=[nn.ReLU(True),]
-        model8+=[nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1, bias=True),]
-        model8+=[nn.ReLU(True),]
-        model8+=[norm_layer(256),]
-
-        # Conv9
-        model9up=[nn.ConvTranspose2d(256, 128, kernel_size=4, stride=2, padding=1, bias=True),]
-        model2short9=[nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1, bias=True),]
-        # add the two feature maps above        
-
-        model9=[nn.ReLU(True),]
-        model9+=[nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1, bias=True),]
-        model9+=[nn.ReLU(True),]
-        model9+=[norm_layer(128),]
-
-        # Conv10
-        model10up=[nn.ConvTranspose2d(128, 128, kernel_size=4, stride=2, padding=1, bias=True),]
-        model1short10=[nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1, bias=True),]
-        # add the two feature maps above
-
-        model10=[nn.ReLU(True),]
-        model10+=[nn.Conv2d(128, 128, kernel_size=3, dilation=1, stride=1, padding=1, bias=True),]
-        model10+=[nn.LeakyReLU(negative_slope=.2),]
-
-        # classification output
-        model_class=[nn.Conv2d(256, classes, kernel_size=1, padding=0, dilation=1, stride=1, bias=True),]
-
-        # regression output
-        model_out=[nn.Conv2d(128, 2, kernel_size=1, padding=0, dilation=1, stride=1, bias=True),]
-        model_out+=[nn.Tanh()]
-
-        self.model1 = nn.Sequential(*model1)
-        self.model2 = nn.Sequential(*model2)
-        self.model3 = nn.Sequential(*model3)
-        self.model4 = nn.Sequential(*model4)
-        self.model5 = nn.Sequential(*model5)
-        self.model6 = nn.Sequential(*model6)
-        self.model7 = nn.Sequential(*model7)
-        self.model8up = nn.Sequential(*model8up)
-        self.model8 = nn.Sequential(*model8)
-        self.model9up = nn.Sequential(*model9up)
-        self.model9 = nn.Sequential(*model9)
-        self.model10up = nn.Sequential(*model10up)
-        self.model10 = nn.Sequential(*model10)
-        self.model3short8 = nn.Sequential(*model3short8)
-        self.model2short9 = nn.Sequential(*model2short9)
-        self.model1short10 = nn.Sequential(*model1short10)
-
-        self.model_class = nn.Sequential(*model_class)
-        self.model_out = nn.Sequential(*model_out)
-
-        self.upsample4 = nn.Sequential(*[nn.Upsample(scale_factor=4, mode='bilinear'),])
-        self.softmax = nn.Sequential(*[nn.Softmax(dim=1),])
-
-    def forward(self, input_A, input_B=None, mask_B=None):
-        if(input_B is None):
-            input_B = torch.cat((input_A*0, input_A*0), dim=1)
-        if(mask_B is None):
-            mask_B = input_A*0
-
-        conv1_2 = self.model1(torch.cat((self.normalize_l(input_A),self.normalize_ab(input_B),mask_B),dim=1))
-        conv2_2 = self.model2(conv1_2[:,:,::2,::2])
-        conv3_3 = self.model3(conv2_2[:,:,::2,::2])
-        conv4_3 = self.model4(conv3_3[:,:,::2,::2])
-        conv5_3 = self.model5(conv4_3)
-        conv6_3 = self.model6(conv5_3)
-        conv7_3 = self.model7(conv6_3)
-
-        conv8_up = self.model8up(conv7_3) + self.model3short8(conv3_3)
-        conv8_3 = self.model8(conv8_up)
-        conv9_up = self.model9up(conv8_3) + self.model2short9(conv2_2)
-        conv9_3 = self.model9(conv9_up)
-        conv10_up = self.model10up(conv9_3) + self.model1short10(conv1_2)
-        conv10_2 = self.model10(conv10_up)
-        out_reg = self.model_out(conv10_2)
-
-        conv9_up = self.model9up(conv8_3) + self.model2short9(conv2_2)
-        conv9_3 = self.model9(conv9_up)
-        conv10_up = self.model10up(conv9_3) + self.model1short10(conv1_2)
-        conv10_2 = self.model10(conv10_up)
-        out_reg = self.model_out(conv10_2)
-
-        return self.unnormalize_ab(out_reg)
-
-def siggraph17(pretrained=True):
-    model = SIGGRAPHGenerator()
-    if(pretrained):
-        import torch.utils.model_zoo as model_zoo
-        model.load_state_dict(model_zoo.load_url('https://colorizers.s3.us-east-2.amazonaws.com/siggraph17-df00044c.pth',map_location='cpu',check_hash=True))
-    return model
-
diff --git a/spaces/ucalyptus/PTI/models/StyleCLIP/mapper/options/test_options.py b/spaces/ucalyptus/PTI/models/StyleCLIP/mapper/options/test_options.py
deleted file mode 100644
index aab2e5a5bba1038b97110fa6c8e8bce14de7390c..0000000000000000000000000000000000000000
--- a/spaces/ucalyptus/PTI/models/StyleCLIP/mapper/options/test_options.py
+++ /dev/null
@@ -1,42 +0,0 @@
-from argparse import ArgumentParser
-
-
-class TestOptions:
-
-    def __init__(self):
-        self.parser = ArgumentParser()
-        self.initialize()
-
-    def initialize(self):
-        # arguments for inference script
-        self.parser.add_argument('--exp_dir', type=str, help='Path to experiment output directory')
-        self.parser.add_argument('--checkpoint_path', default=None, type=str, help='Path to model checkpoint')
-        self.parser.add_argument('--couple_outputs', action='store_true',
-                                 help='Whether to also save inputs + outputs side-by-side')
-
-        self.parser.add_argument('--mapper_type', default='LevelsMapper', type=str, help='Which mapper to use')
-        self.parser.add_argument('--no_coarse_mapper', default=False, action="store_true")
-        self.parser.add_argument('--no_medium_mapper', default=False, action="store_true")
-        self.parser.add_argument('--no_fine_mapper', default=False, action="store_true")
-        self.parser.add_argument('--stylegan_size', default=1024, type=int)
-
-        self.parser.add_argument('--test_batch_size', default=2, type=int, help='Batch size for testing and inference')
-        self.parser.add_argument('--latents_test_path', default=None, type=str, help="The latents for the validation")
-        self.parser.add_argument('--test_workers', default=2, type=int,
-                                 help='Number of test/inference dataloader workers')
-
-        self.parser.add_argument('--n_images', type=int, default=None,
-                                 help='Number of images to output. If None, run on all data')
-
-        self.parser.add_argument('--run_id', type=str, default='PKNWUQRQRKXQ',
-                                 help='The generator id to use')
-
-        self.parser.add_argument('--image_name', type=str, default='',
-                                 help='image to run on')
-
-        self.parser.add_argument('--edit_name', type=str, default='',
-                                 help='edit type')
-
-    def parse(self):
-        opts = self.parser.parse_args()
-        return opts
diff --git a/spaces/usbethFlerru/sovits-modelsV2/example/Circuitry 101 A Beginners Guide to Electrical and Electronic Devices.md b/spaces/usbethFlerru/sovits-modelsV2/example/Circuitry 101 A Beginners Guide to Electrical and Electronic Devices.md
deleted file mode 100644
index 8ac4705e2cea08140cdfbb3517acc4e5e3aabc61..0000000000000000000000000000000000000000
--- a/spaces/usbethFlerru/sovits-modelsV2/example/Circuitry 101 A Beginners Guide to Electrical and Electronic Devices.md	
+++ /dev/null
@@ -1,12 +0,0 @@
-<br />
-<p>State-of-the-art solar panel offers over 42% more battery charging power. Will operate for 21 days in total darkness. Features solid-state cicuitry, shocks through wet weeds and brush. Ideal for mo...Read More</p>
-<h2>cicuitry</h2><br /><p><b><b>DOWNLOAD</b> &#128504;&#128504;&#128504; <a href="https://urlcod.com/2uyUrM">https://urlcod.com/2uyUrM</a></b></p><br /><br />
-<p>This project explores performing statistical signal processing with analog circuits. The first instantiation is a low-complexity circuit for phase acquisition and tracking of a pseudo-random sequence generated by an LFSR. Eventually we hope to scale the complexity of this kind of cicuitry to be able to perform any high-speed signal processing desired for a digital wireless front-end. In many application domains, this approach could be 10 to 100 times more efficient in terms of power consumption and square millimeters of silicon than the equivalent digital signal processor (DSP).</p>
-<p>The JK-3000+ is an economical grade handheld card counter engineered with sophisticated cicuitry and high-percision optical sensors making it an ideal portable counting solution for any card manufacturer or personalization bureau. It can count a variety of card types including embossed cards.</p>
-<p>If the outer casing of an appliance is made of metal, then it can be made safe by 'earthing'. The live and neutral wires from the plug are connected to the cicuitry of the appliance (in the diagram below - that is the motor circuit) and the earth wire from the plug is fixed to the metal case.</p>
-<p></p>
-<p>Here's the small Megavibe, it features the exact same cicuitry as found in the large Megavibe-just half the size! it gets the tone that the Megavibe is famous for and features: Volume, Intensirty and Speed controls and true bypass footswitch. Price: $ 325.00 plus $14.35 for s & h. ($339.35 includes shipping) Shipped USPS Priority Mail. US only. Available here:Small Megavibe</p>
-<p>Opto couplers are used toisolate the external wiring from the internal cicuitry of theMintron camera. This prevents static discharge from damaging thecamera. Although most any opto coupler should work, I used the <strong>4N32</strong> because I just happened to havequite a few on hand. The <strong>4N32</strong> opto coupler provides ~2500 voltisolation. Since I am running 50 to 150 feet of control cablebetween the telescope and the house this IS important especiallywhen the humidity is low and static discharge is common!</p>
-<p>Sounds like a faulty battery or charging cicuitry. One thing to try is to remove the battery, check the contacts on the battery and in the laptop where the battery goes. It may be unlikely, but possibly there is some contamination there.</p> aaccfb2cb3<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/user238921933/stable-diffusion-webui/modules/codeformer/codeformer_arch.py b/spaces/user238921933/stable-diffusion-webui/modules/codeformer/codeformer_arch.py
deleted file mode 100644
index 11dcc3ee76511218c64977c2ecbb306cecd892c3..0000000000000000000000000000000000000000
--- a/spaces/user238921933/stable-diffusion-webui/modules/codeformer/codeformer_arch.py
+++ /dev/null
@@ -1,278 +0,0 @@
-# this file is copied from CodeFormer repository. Please see comment in modules/codeformer_model.py
-
-import math
-import numpy as np
-import torch
-from torch import nn, Tensor
-import torch.nn.functional as F
-from typing import Optional, List
-
-from modules.codeformer.vqgan_arch import *
-from basicsr.utils import get_root_logger
-from basicsr.utils.registry import ARCH_REGISTRY
-
-def calc_mean_std(feat, eps=1e-5):
-    """Calculate mean and std for adaptive_instance_normalization.
-
-    Args:
-        feat (Tensor): 4D tensor.
-        eps (float): A small value added to the variance to avoid
-            divide-by-zero. Default: 1e-5.
-    """
-    size = feat.size()
-    assert len(size) == 4, 'The input feature should be 4D tensor.'
-    b, c = size[:2]
-    feat_var = feat.view(b, c, -1).var(dim=2) + eps
-    feat_std = feat_var.sqrt().view(b, c, 1, 1)
-    feat_mean = feat.view(b, c, -1).mean(dim=2).view(b, c, 1, 1)
-    return feat_mean, feat_std
-
-
-def adaptive_instance_normalization(content_feat, style_feat):
-    """Adaptive instance normalization.
-
-    Adjust the reference features to have the similar color and illuminations
-    as those in the degradate features.
-
-    Args:
-        content_feat (Tensor): The reference feature.
-        style_feat (Tensor): The degradate features.
-    """
-    size = content_feat.size()
-    style_mean, style_std = calc_mean_std(style_feat)
-    content_mean, content_std = calc_mean_std(content_feat)
-    normalized_feat = (content_feat - content_mean.expand(size)) / content_std.expand(size)
-    return normalized_feat * style_std.expand(size) + style_mean.expand(size)
-
-
-class PositionEmbeddingSine(nn.Module):
-    """
-    This is a more standard version of the position embedding, very similar to the one
-    used by the Attention is all you need paper, generalized to work on images.
-    """
-
-    def __init__(self, num_pos_feats=64, temperature=10000, normalize=False, scale=None):
-        super().__init__()
-        self.num_pos_feats = num_pos_feats
-        self.temperature = temperature
-        self.normalize = normalize
-        if scale is not None and normalize is False:
-            raise ValueError("normalize should be True if scale is passed")
-        if scale is None:
-            scale = 2 * math.pi
-        self.scale = scale
-
-    def forward(self, x, mask=None):
-        if mask is None:
-            mask = torch.zeros((x.size(0), x.size(2), x.size(3)), device=x.device, dtype=torch.bool)
-        not_mask = ~mask
-        y_embed = not_mask.cumsum(1, dtype=torch.float32)
-        x_embed = not_mask.cumsum(2, dtype=torch.float32)
-        if self.normalize:
-            eps = 1e-6
-            y_embed = y_embed / (y_embed[:, -1:, :] + eps) * self.scale
-            x_embed = x_embed / (x_embed[:, :, -1:] + eps) * self.scale
-
-        dim_t = torch.arange(self.num_pos_feats, dtype=torch.float32, device=x.device)
-        dim_t = self.temperature ** (2 * (dim_t // 2) / self.num_pos_feats)
-
-        pos_x = x_embed[:, :, :, None] / dim_t
-        pos_y = y_embed[:, :, :, None] / dim_t
-        pos_x = torch.stack(
-            (pos_x[:, :, :, 0::2].sin(), pos_x[:, :, :, 1::2].cos()), dim=4
-        ).flatten(3)
-        pos_y = torch.stack(
-            (pos_y[:, :, :, 0::2].sin(), pos_y[:, :, :, 1::2].cos()), dim=4
-        ).flatten(3)
-        pos = torch.cat((pos_y, pos_x), dim=3).permute(0, 3, 1, 2)
-        return pos
-
-def _get_activation_fn(activation):
-    """Return an activation function given a string"""
-    if activation == "relu":
-        return F.relu
-    if activation == "gelu":
-        return F.gelu
-    if activation == "glu":
-        return F.glu
-    raise RuntimeError(F"activation should be relu/gelu, not {activation}.")
-
-
-class TransformerSALayer(nn.Module):
-    def __init__(self, embed_dim, nhead=8, dim_mlp=2048, dropout=0.0, activation="gelu"):
-        super().__init__()
-        self.self_attn = nn.MultiheadAttention(embed_dim, nhead, dropout=dropout)
-        # Implementation of Feedforward model - MLP
-        self.linear1 = nn.Linear(embed_dim, dim_mlp)
-        self.dropout = nn.Dropout(dropout)
-        self.linear2 = nn.Linear(dim_mlp, embed_dim)
-
-        self.norm1 = nn.LayerNorm(embed_dim)
-        self.norm2 = nn.LayerNorm(embed_dim)
-        self.dropout1 = nn.Dropout(dropout)
-        self.dropout2 = nn.Dropout(dropout)
-
-        self.activation = _get_activation_fn(activation)
-
-    def with_pos_embed(self, tensor, pos: Optional[Tensor]):
-        return tensor if pos is None else tensor + pos
-
-    def forward(self, tgt,
-                tgt_mask: Optional[Tensor] = None,
-                tgt_key_padding_mask: Optional[Tensor] = None,
-                query_pos: Optional[Tensor] = None):
-        
-        # self attention
-        tgt2 = self.norm1(tgt)
-        q = k = self.with_pos_embed(tgt2, query_pos)
-        tgt2 = self.self_attn(q, k, value=tgt2, attn_mask=tgt_mask,
-                              key_padding_mask=tgt_key_padding_mask)[0]
-        tgt = tgt + self.dropout1(tgt2)
-
-        # ffn
-        tgt2 = self.norm2(tgt)
-        tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt2))))
-        tgt = tgt + self.dropout2(tgt2)
-        return tgt
-
-class Fuse_sft_block(nn.Module):
-    def __init__(self, in_ch, out_ch):
-        super().__init__()
-        self.encode_enc = ResBlock(2*in_ch, out_ch)
-
-        self.scale = nn.Sequential(
-                    nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1),
-                    nn.LeakyReLU(0.2, True),
-                    nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1))
-
-        self.shift = nn.Sequential(
-                    nn.Conv2d(in_ch, out_ch, kernel_size=3, padding=1),
-                    nn.LeakyReLU(0.2, True),
-                    nn.Conv2d(out_ch, out_ch, kernel_size=3, padding=1))
-
-    def forward(self, enc_feat, dec_feat, w=1):
-        enc_feat = self.encode_enc(torch.cat([enc_feat, dec_feat], dim=1))
-        scale = self.scale(enc_feat)
-        shift = self.shift(enc_feat)
-        residual = w * (dec_feat * scale + shift)
-        out = dec_feat + residual
-        return out
-
-
-@ARCH_REGISTRY.register()
-class CodeFormer(VQAutoEncoder):
-    def __init__(self, dim_embd=512, n_head=8, n_layers=9, 
-                codebook_size=1024, latent_size=256,
-                connect_list=['32', '64', '128', '256'],
-                fix_modules=['quantize','generator']):
-        super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size)
-
-        if fix_modules is not None:
-            for module in fix_modules:
-                for param in getattr(self, module).parameters():
-                    param.requires_grad = False
-
-        self.connect_list = connect_list
-        self.n_layers = n_layers
-        self.dim_embd = dim_embd
-        self.dim_mlp = dim_embd*2
-
-        self.position_emb = nn.Parameter(torch.zeros(latent_size, self.dim_embd))
-        self.feat_emb = nn.Linear(256, self.dim_embd)
-
-        # transformer
-        self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0) 
-                                    for _ in range(self.n_layers)])
-
-        # logits_predict head
-        self.idx_pred_layer = nn.Sequential(
-            nn.LayerNorm(dim_embd),
-            nn.Linear(dim_embd, codebook_size, bias=False))
-        
-        self.channels = {
-            '16': 512,
-            '32': 256,
-            '64': 256,
-            '128': 128,
-            '256': 128,
-            '512': 64,
-        }
-
-        # after second residual block for > 16, before attn layer for ==16
-        self.fuse_encoder_block = {'512':2, '256':5, '128':8, '64':11, '32':14, '16':18}
-        # after first residual block for > 16, before attn layer for ==16
-        self.fuse_generator_block = {'16':6, '32': 9, '64':12, '128':15, '256':18, '512':21}
-
-        # fuse_convs_dict
-        self.fuse_convs_dict = nn.ModuleDict()
-        for f_size in self.connect_list:
-            in_ch = self.channels[f_size]
-            self.fuse_convs_dict[f_size] = Fuse_sft_block(in_ch, in_ch)
-
-    def _init_weights(self, module):
-        if isinstance(module, (nn.Linear, nn.Embedding)):
-            module.weight.data.normal_(mean=0.0, std=0.02)
-            if isinstance(module, nn.Linear) and module.bias is not None:
-                module.bias.data.zero_()
-        elif isinstance(module, nn.LayerNorm):
-            module.bias.data.zero_()
-            module.weight.data.fill_(1.0)
-
-    def forward(self, x, w=0, detach_16=True, code_only=False, adain=False):
-        # ################### Encoder #####################
-        enc_feat_dict = {}
-        out_list = [self.fuse_encoder_block[f_size] for f_size in self.connect_list]
-        for i, block in enumerate(self.encoder.blocks):
-            x = block(x) 
-            if i in out_list:
-                enc_feat_dict[str(x.shape[-1])] = x.clone()
-
-        lq_feat = x
-        # ################# Transformer ###################
-        # quant_feat, codebook_loss, quant_stats = self.quantize(lq_feat)
-        pos_emb = self.position_emb.unsqueeze(1).repeat(1,x.shape[0],1)
-        # BCHW -> BC(HW) -> (HW)BC
-        feat_emb = self.feat_emb(lq_feat.flatten(2).permute(2,0,1))
-        query_emb = feat_emb
-        # Transformer encoder
-        for layer in self.ft_layers:
-            query_emb = layer(query_emb, query_pos=pos_emb)
-
-        # output logits
-        logits = self.idx_pred_layer(query_emb) # (hw)bn
-        logits = logits.permute(1,0,2) # (hw)bn -> b(hw)n
-
-        if code_only: # for training stage II
-          # logits doesn't need softmax before cross_entropy loss
-            return logits, lq_feat
-
-        # ################# Quantization ###################
-        # if self.training:
-        #     quant_feat = torch.einsum('btn,nc->btc', [soft_one_hot, self.quantize.embedding.weight])
-        #     # b(hw)c -> bc(hw) -> bchw
-        #     quant_feat = quant_feat.permute(0,2,1).view(lq_feat.shape)
-        # ------------
-        soft_one_hot = F.softmax(logits, dim=2)
-        _, top_idx = torch.topk(soft_one_hot, 1, dim=2)
-        quant_feat = self.quantize.get_codebook_feat(top_idx, shape=[x.shape[0],16,16,256])
-        # preserve gradients
-        # quant_feat = lq_feat + (quant_feat - lq_feat).detach()
-
-        if detach_16:
-            quant_feat = quant_feat.detach() # for training stage III
-        if adain:
-            quant_feat = adaptive_instance_normalization(quant_feat, lq_feat)
-
-        # ################## Generator ####################
-        x = quant_feat
-        fuse_list = [self.fuse_generator_block[f_size] for f_size in self.connect_list]
-
-        for i, block in enumerate(self.generator.blocks):
-            x = block(x) 
-            if i in fuse_list: # fuse after i-th block
-                f_size = str(x.shape[-1])
-                if w>0:
-                    x = self.fuse_convs_dict[f_size](enc_feat_dict[f_size].detach(), x, w)
-        out = x
-        # logits doesn't need softmax before cross_entropy loss
-        return out, logits, lq_feat
\ No newline at end of file
diff --git a/spaces/vaishanthr/Simultaneous-Segmented-Depth-Prediction/yolov8/docs/yolov5/environments/aws_quickstart_tutorial.md b/spaces/vaishanthr/Simultaneous-Segmented-Depth-Prediction/yolov8/docs/yolov5/environments/aws_quickstart_tutorial.md
deleted file mode 100644
index 3e3ea83cc59e7a287c970228dddba3655614c889..0000000000000000000000000000000000000000
--- a/spaces/vaishanthr/Simultaneous-Segmented-Depth-Prediction/yolov8/docs/yolov5/environments/aws_quickstart_tutorial.md
+++ /dev/null
@@ -1,88 +0,0 @@
----
-comments: true
-description: Get started with YOLOv5 on AWS. Our comprehensive guide provides everything you need to know to run YOLOv5 on an Amazon Deep Learning instance.
-keywords: YOLOv5, AWS, Deep Learning, Instance, Guide, Quickstart
----
-
-# YOLOv5 🚀 on AWS Deep Learning Instance: A Comprehensive Guide
-
-This guide will help new users run YOLOv5 on an Amazon Web Services (AWS) Deep Learning instance. AWS offers a [Free Tier](https://aws.amazon.com/free/) and a [credit program](https://aws.amazon.com/activate/) for a quick and affordable start.
-
-Other quickstart options for YOLOv5 include our [Colab Notebook](https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb) <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>, [GCP Deep Learning VM](https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial), and our Docker image at [Docker Hub](https://hub.docker.com/r/ultralytics/yolov5) <a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>. *Updated: 21 April 2023*.
-
-## 1. AWS Console Sign-in
-
-Create an account or sign in to the AWS console at [https://aws.amazon.com/console/](https://aws.amazon.com/console/) and select the **EC2** service.
-
-![Console](https://user-images.githubusercontent.com/26833433/106323804-debddd00-622c-11eb-997f-b8217dc0e975.png)
-
-## 2. Launch Instance
-
-In the EC2 section of the AWS console, click the **Launch instance** button.
-
-![Launch](https://user-images.githubusercontent.com/26833433/106323950-204e8800-622d-11eb-915d-5c90406973ea.png)
-
-### Choose an Amazon Machine Image (AMI)
-
-Enter 'Deep Learning' in the search field and select the most recent Ubuntu Deep Learning AMI (recommended), or an alternative Deep Learning AMI. For more information on selecting an AMI, see [Choosing Your DLAMI](https://docs.aws.amazon.com/dlami/latest/devguide/options.html).
-
-![Choose AMI](https://user-images.githubusercontent.com/26833433/106326107-c9e34880-6230-11eb-97c9-3b5fc2f4e2ff.png)
-
-### Select an Instance Type
-
-A GPU instance is recommended for most deep learning purposes. Training new models will be faster on a GPU instance than a CPU instance. Multi-GPU instances or distributed training across multiple instances with GPUs can offer sub-linear scaling. To set up distributed training, see [Distributed Training](https://docs.aws.amazon.com/dlami/latest/devguide/distributed-training.html).
-
-**Note:** The size of your model should be a factor in selecting an instance. If your model exceeds an instance's available RAM, select a different instance type with enough memory for your application.
-
-Refer to [EC2 Instance Types](https://aws.amazon.com/ec2/instance-types/) and choose Accelerated Computing to see the different GPU instance options.
-
-![Choose Type](https://user-images.githubusercontent.com/26833433/106324624-52141e80-622e-11eb-9662-1a376d9c887d.png)
-
-For more information on GPU monitoring and optimization, see [GPU Monitoring and Optimization](https://docs.aws.amazon.com/dlami/latest/devguide/tutorial-gpu.html). For pricing, see [On-Demand Pricing](https://aws.amazon.com/ec2/pricing/on-demand/) and [Spot Pricing](https://aws.amazon.com/ec2/spot/pricing/).
-
-### Configure Instance Details
-
-Amazon EC2 Spot Instances let you take advantage of unused EC2 capacity in the AWS cloud. Spot Instances are available at up to a 70% discount compared to On-Demand prices. We recommend a persistent spot instance, which will save your data and restart automatically when spot instance availability returns after spot instance termination. For full-price On-Demand instances, leave these settings at their default values.
-
-![Spot Request](https://user-images.githubusercontent.com/26833433/106324835-ac14e400-622e-11eb-8853-df5ec9b16dfc.png)
-
-Complete Steps 4-7 to finalize your instance hardware and security settings, and then launch the instance.
-
-## 3. Connect to Instance
-
-Select the checkbox next to your running instance, and then click Connect. Copy and paste the SSH terminal command into a terminal of your choice to connect to your instance.
-
-![Connect](https://user-images.githubusercontent.com/26833433/106325530-cf8c5e80-622f-11eb-9f64-5b313a9d57a1.png)
-
-## 4. Run YOLOv5
-
-Once you have logged in to your instance, clone the repository and install the dependencies in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). [Models](https://github.com/ultralytics/yolov5/tree/master/models) and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
-
-```bash
-git clone https://github.com/ultralytics/yolov5  # clone
-cd yolov5
-pip install -r requirements.txt  # install
-```
-
-Then, start training, testing, detecting, and exporting YOLOv5 models:
-
-```bash
-python train.py  # train a model
-python val.py --weights yolov5s.pt  # validate a model for Precision, Recall, and mAP
-python detect.py --weights yolov5s.pt --source path/to/images  # run inference on images and videos
-python export.py --weights yolov5s.pt --include onnx coreml tflite  # export models to other formats
-```
-
-## Optional Extras
-
-Add 64GB of swap memory (to `--cache` large datasets):
-
-```bash
-sudo fallocate -l 64G /swapfile
-sudo chmod 600 /swapfile
-sudo mkswap /swapfile
-sudo swapon /swapfile
-free -h  # check memory
-```
-
-Now you have successfully set up and run YOLOv5 on an AWS Deep Learning instance. Enjoy training, testing, and deploying your object detection models!
\ No newline at end of file
diff --git a/spaces/valhalla/minDALLE/dalle/models/tokenizer.py b/spaces/valhalla/minDALLE/dalle/models/tokenizer.py
deleted file mode 100644
index ffa3e7e3c5a5a6e22a9ac0fca1df7ccbb38c2846..0000000000000000000000000000000000000000
--- a/spaces/valhalla/minDALLE/dalle/models/tokenizer.py
+++ /dev/null
@@ -1,26 +0,0 @@
-# ------------------------------------------------------------------------------------
-# Minimal DALL-E
-# Copyright (c) 2021 KakaoBrain. All Rights Reserved.
-# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
-# ------------------------------------------------------------------------------------
-
-import os
-from functools import partial
-from tokenizers import CharBPETokenizer
-
-
-def build_tokenizer(path: str,
-                    context_length: int = 64,
-                    *args,
-                    **kwargs):
-    from_file = partial(CharBPETokenizer.from_file,
-                        vocab_filename=os.path.join(path, 'bpe-16k-vocab.json'),
-                        merges_filename=os.path.join(path, 'bpe-16k-merges.txt'),
-                        unk_token='[UNK]')
-    tokenizer = from_file(*args, **kwargs)
-    tokenizer.add_special_tokens(['[PAD]'])
-    tokenizer.enable_padding(length=context_length,
-                             pad_id=tokenizer.token_to_id('[PAD]'))
-    tokenizer.enable_truncation(max_length=context_length)
-    print(f'{path} successfully restored..')
-    return tokenizer
diff --git a/spaces/vialibre/edia_full_es/interfaces/interface_data.py b/spaces/vialibre/edia_full_es/interfaces/interface_data.py
deleted file mode 100644
index 120311c1ed521d205ace37209c6099faa9c0e96d..0000000000000000000000000000000000000000
--- a/spaces/vialibre/edia_full_es/interfaces/interface_data.py
+++ /dev/null
@@ -1,144 +0,0 @@
-import gradio as gr
-import pandas as pd
-from tool_info import TOOL_INFO
-from modules.module_connection import Word2ContextExplorerConnector
-
-
-def interface(
-    vocabulary, # Vocabulary class instance
-    contexts: str,
-    available_logs: bool,
-    available_wordcloud: bool,
-    lang: str="es"
-) -> gr.Blocks:
-
-    # --- Init Class ---
-    connector = Word2ContextExplorerConnector(
-        vocabulary=vocabulary, 
-        context=contexts,
-        lang=lang,
-        logs_file_name=f"logs_edia_datos_{lang}" if available_logs else None
-    )
-
-    # --- Load language ---
-    labels = pd.read_json(
-        f"language/{lang}.json"
-    )["DataExplorer_interface"]
-
-    # --- Interface ---
-    iface = gr.Blocks(
-        css=".container { max-width: 90%; margin: auto;}"
-    )
-
-    with iface:
-        with gr.Row():
-            with gr.Column():
-                with gr.Group():
-                    gr.Markdown(
-                        value=labels["step1"]
-                    )
-                    with gr.Row(): 
-                        input_word = gr.Textbox(
-                            label=labels["inputWord"]["title"], 
-                            show_label=False, 
-                            placeholder=labels["inputWord"]["placeholder"]
-                        )
-                    with gr.Row(): 
-                        btn_get_w_info = gr.Button(
-                            value=labels["wordInfoButton"]
-                        )
-
-                with gr.Group():
-                    gr.Markdown(
-                        value=labels["step2"]
-                    )
-                    n_context = gr.Slider(
-                        label="", 
-                        step=1, minimum=1, maximum=30, value=5, 
-                        visible=True, 
-                        interactive=True
-                    )
-                with gr.Group():
-                    gr.Markdown(
-                        value=labels["step3"]
-                    )
-                    subsets_choice = gr.CheckboxGroup(
-                        label="Conjuntos",
-                        show_label=False,
-                        interactive=True, 
-                        visible=True
-                    )
-                    with gr.Row(): 
-                        btn_get_contexts = gr.Button(
-                            value=labels["wordContextButton"], 
-                            visible=True
-                        )
-                
-                with gr.Row(): 
-                    out_msj = gr.Markdown(
-                        label="", 
-                        visible=True
-                    )
-
-            with gr.Column():
-                with gr.Group():
-                    gr.Markdown(
-                        value=labels["wordDistributionTitle"]
-                    )
-                    dist_plot = gr.Plot(
-                        label="", 
-                        show_label=False
-                    )
-                    wc_plot = gr.Plot(
-                        label="", 
-                        show_label=False, 
-                        visible=available_wordcloud
-                    )
-
-                with gr.Group():
-                    gr.Markdown(
-                        value=labels["frequencyPerSetTitle"]
-                    )
-                    subsets_freq = gr.HTML(
-                        label=""
-                    )
-    
-        with gr.Row():
-            with gr.Group():
-                with gr.Row(): 
-                    gr.Markdown(
-                        value=labels["contextList"]
-                    )
-                with gr.Row(): 
-                    out_context = gr.Dataframe(
-                        label="", 
-                        interactive=False, 
-                        value=pd.DataFrame([], columns=['']),
-                        wrap=True,
-                        datatype=['str','markdown','str','markdown']
-                    )
-
-        with gr.Group():
-            gr.Markdown(
-                value=TOOL_INFO
-            )
-
-        btn_get_w_info.click( 
-            fn=connector.get_word_info, 
-            inputs=[input_word], 
-            outputs=[out_msj,
-                    out_context,
-                    subsets_freq,
-                    dist_plot,
-                    wc_plot,
-                    subsets_choice
-            ]
-        )
-        
-        btn_get_contexts.click(
-            fn=connector.get_word_context, 
-            inputs=[input_word, n_context, subsets_choice], 
-            outputs=[out_msj, out_context]
-        )
-    
-    return iface
\ No newline at end of file
diff --git a/spaces/vict0rsch/climateGAN/train.py b/spaces/vict0rsch/climateGAN/train.py
deleted file mode 100644
index 1b0377c808df36b60534784596e37088ba236acb..0000000000000000000000000000000000000000
--- a/spaces/vict0rsch/climateGAN/train.py
+++ /dev/null
@@ -1,195 +0,0 @@
-import logging
-import os
-from pathlib import Path
-from time import sleep, time
-
-import hydra
-import yaml
-from addict import Dict
-from comet_ml import ExistingExperiment, Experiment
-from omegaconf import OmegaConf
-
-from climategan.trainer import Trainer
-from climategan.utils import (
-    comet_kwargs,
-    copy_run_files,
-    env_to_path,
-    find_existing_training,
-    flatten_opts,
-    get_existing_comet_id,
-    get_git_branch,
-    get_git_revision_hash,
-    get_increased_path,
-    kill_job,
-    load_opts,
-    pprint,
-)
-
-logging.basicConfig()
-logging.getLogger().setLevel(logging.ERROR)
-
-hydra_config_path = Path(__file__).resolve().parent / "shared/trainer/config.yaml"
-
-
-# requires hydra-core==0.11.3 and omegaconf==1.4.1
-@hydra.main(config_path=hydra_config_path, strict=False)
-def main(opts):
-    """
-    Opts prevalence:
-        1. Load file specified in args.default (or shared/trainer/defaults.yaml
-           if none is provided)
-        2. Update with file specified in args.config (or no update if none is provided)
-        3. Update with parsed command-line arguments
-
-        e.g.
-        `python train.py args.config=config/large-lr.yaml data.loaders.batch_size=10`
-        loads defaults, overrides with values in large-lr.yaml and sets batch_size to 10
-    """
-
-    # -----------------------------
-    # -----  Parse arguments  -----
-    # -----------------------------
-
-    hydra_opts = Dict(OmegaConf.to_container(opts))
-    args = hydra_opts.pop("args", None)
-    auto_resumed = {}
-
-    config_path = args.config
-
-    if hydra_opts.train.resume:
-        out_ = str(env_to_path(hydra_opts.output_path))
-        config_path = Path(out_) / "opts.yaml"
-        if not config_path.exists():
-            config_path = None
-            print("WARNING: could not reuse the opts in {}".format(out_))
-
-    default = args.default or Path(__file__).parent / "shared/trainer/defaults.yaml"
-
-    # -----------------------
-    # -----  Load opts  -----
-    # -----------------------
-
-    opts = load_opts(config_path, default=default, commandline_opts=hydra_opts)
-    if args.resume:
-        opts.train.resume = True
-
-    opts.jobID = os.environ.get("SLURM_JOBID")
-    opts.slurm_partition = os.environ.get("SLURM_JOB_PARTITION")
-    opts.output_path = str(env_to_path(opts.output_path))
-    print("Config output_path:", opts.output_path)
-
-    exp = comet_previous_id = None
-
-    # -------------------------------
-    # -----  Check output_path  -----
-    # -------------------------------
-
-    # Auto-continue if same slurm job ID (=job was requeued)
-    if not opts.train.resume and opts.train.auto_resume:
-        print("\n\nTrying to auto-resume...")
-        existing_path = find_existing_training(opts)
-        if existing_path is not None and existing_path.exists():
-            auto_resumed["original output_path"] = str(opts.output_path)
-            auto_resumed["existing_path"] = str(existing_path)
-            opts.train.resume = True
-            opts.output_path = str(existing_path)
-
-    # Still not resuming: creating new output path
-    if not opts.train.resume:
-        opts.output_path = str(get_increased_path(opts.output_path))
-        Path(opts.output_path).mkdir(parents=True, exist_ok=True)
-
-    # Copy the opts's sbatch_file to output_path
-    copy_run_files(opts)
-    # store git hash
-    opts.git_hash = get_git_revision_hash()
-    opts.git_branch = get_git_branch()
-
-    if not args.no_comet:
-        # ----------------------------------
-        # -----  Set Comet Experiment  -----
-        # ----------------------------------
-
-        if opts.train.resume:
-            # Is resuming: get existing comet exp id
-            assert Path(opts.output_path).exists(), "Output_path does not exist"
-
-            comet_previous_id = get_existing_comet_id(opts.output_path)
-            # Continue existing experiment
-            if comet_previous_id is None:
-                print("WARNING could not retreive previous comet id")
-                print(f"from {opts.output_path}")
-            else:
-                print("Continuing previous experiment", comet_previous_id)
-                auto_resumed["continuing exp id"] = comet_previous_id
-                exp = ExistingExperiment(
-                    previous_experiment=comet_previous_id, **comet_kwargs
-                )
-                print("Comet Experiment resumed")
-
-        if exp is None:
-            # Create new experiment
-            print("Starting new experiment")
-            exp = Experiment(project_name="climategan", **comet_kwargs)
-            exp.log_asset_folder(
-                str(Path(__file__).parent / "climategan"),
-                recursive=True,
-                log_file_name=True,
-            )
-            exp.log_asset(str(Path(__file__)))
-
-        # Log note
-        if args.note:
-            exp.log_parameter("note", args.note)
-
-        # Merge and log tags
-        if args.comet_tags or opts.comet.tags:
-            tags = set([f"branch:{opts.git_branch}"])
-            if args.comet_tags:
-                tags.update(args.comet_tags)
-            if opts.comet.tags:
-                tags.update(opts.comet.tags)
-            opts.comet.tags = list(tags)
-            print("Logging to comet.ml with tags", opts.comet.tags)
-            exp.add_tags(opts.comet.tags)
-
-        # Log all opts
-        exp.log_parameters(flatten_opts(opts))
-        if auto_resumed:
-            exp.log_text("\n".join(f"{k:20}: {v}" for k, v in auto_resumed.items()))
-
-        # allow some time for comet to get its url
-        sleep(1)
-
-        # Save comet exp url
-        url_path = get_increased_path(Path(opts.output_path) / "comet_url.txt")
-        with open(url_path, "w") as f:
-            f.write(exp.url)
-
-        # Save config file
-        opts_path = get_increased_path(Path(opts.output_path) / "opts.yaml")
-        with (opts_path).open("w") as f:
-            yaml.safe_dump(opts.to_dict(), f)
-
-    pprint("Running model in", opts.output_path)
-
-    # -------------------
-    # -----  Train  -----
-    # -------------------
-
-    trainer = Trainer(opts, comet_exp=exp, verbose=1)
-    trainer.logger.time.start_time = time()
-    trainer.setup()
-    trainer.train()
-
-    # -----------------------------
-    # -----  End of training  -----
-    # -----------------------------
-
-    pprint("Done training")
-    kill_job(opts.jobID)
-
-
-if __name__ == "__main__":
-
-    main()
diff --git a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/arraymisc/__init__.py b/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/arraymisc/__init__.py
deleted file mode 100644
index 4b4700d6139ae3d604ff6e542468cce4200c020c..0000000000000000000000000000000000000000
--- a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/arraymisc/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from .quantization import dequantize, quantize
-
-__all__ = ['quantize', 'dequantize']
diff --git a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/runner/optimizer/__init__.py b/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/runner/optimizer/__init__.py
deleted file mode 100644
index 53c34d0470992cbc374f29681fdd00dc0e57968d..0000000000000000000000000000000000000000
--- a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/runner/optimizer/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from .builder import (OPTIMIZER_BUILDERS, OPTIMIZERS, build_optimizer,
-                      build_optimizer_constructor)
-from .default_constructor import DefaultOptimizerConstructor
-
-__all__ = [
-    'OPTIMIZER_BUILDERS', 'OPTIMIZERS', 'DefaultOptimizerConstructor',
-    'build_optimizer', 'build_optimizer_constructor'
-]
diff --git a/spaces/w1zrd/MusicGen/README.md b/spaces/w1zrd/MusicGen/README.md
deleted file mode 100644
index 6a3dbd50cb5862d8d084df848d7f02e3094d9553..0000000000000000000000000000000000000000
--- a/spaces/w1zrd/MusicGen/README.md
+++ /dev/null
@@ -1,137 +0,0 @@
----
-title: MusicGen
-python_version: '3.9'
-tags:
-- music generation
-- language models
-- LLMs
-app_file: app.py
-emoji: 🎵
-colorFrom: white
-colorTo: blue
-sdk: gradio
-sdk_version: 3.34.0
-pinned: true
-license: cc-by-nc-4.0
-duplicated_from: facebook/MusicGen
----
-# Audiocraft
-![docs badge](https://github.com/facebookresearch/audiocraft/workflows/audiocraft_docs/badge.svg)
-![linter badge](https://github.com/facebookresearch/audiocraft/workflows/audiocraft_linter/badge.svg)
-![tests badge](https://github.com/facebookresearch/audiocraft/workflows/audiocraft_tests/badge.svg)
-
-Audiocraft is a PyTorch library for deep learning research on audio generation. At the moment, it contains the code for MusicGen, a state-of-the-art controllable text-to-music model.
-
-## MusicGen
-
-Audiocraft provides the code and models for MusicGen, [a simple and controllable model for music generation][arxiv]. MusicGen is a single stage auto-regressive
-Transformer model trained over a 32kHz <a href="https://github.com/facebookresearch/encodec">EnCodec tokenizer</a> with 4 codebooks sampled at 50 Hz. Unlike existing methods like [MusicLM](https://arxiv.org/abs/2301.11325), MusicGen doesn't require a self-supervised semantic representation, and it generates
-all 4 codebooks in one pass. By introducing a small delay between the codebooks, we show we can predict
-them in parallel, thus having only 50 auto-regressive steps per second of audio.
-Check out our [sample page][musicgen_samples] or test the available demo!
-
-<a target="_blank" href="https://colab.research.google.com/drive/1-Xe9NCdIs2sCUbiSmwHXozK6AAhMm7_i?usp=sharing">
-  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
-</a>
-<a target="_blank" href="https://huggingface.co/spaces/facebook/MusicGen">
-  <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="Open in HugginFace"/>
-</a>
-<br>
-
-We use 20K hours of licensed music to train MusicGen. Specifically, we rely on an internal dataset of 10K high-quality music tracks, and on the ShutterStock and Pond5 music data.
-
-## Installation
-Audiocraft requires Python 3.9, PyTorch 2.0.0, and a GPU with at least 16 GB of memory (for the medium-sized model). To install Audiocraft, you can run the following:
-
-```shell
-# Best to make sure you have torch installed first, in particular before installing xformers.
-# Don't run this if you already have PyTorch installed.
-pip install 'torch>=2.0'
-# Then proceed to one of the following
-pip install -U audiocraft  # stable release
-pip install -U git+https://git@github.com/facebookresearch/audiocraft#egg=audiocraft  # bleeding edge
-pip install -e .  # or if you cloned the repo locally
-```
-
-## Usage
-We offer a number of way to interact with MusicGen:
-1. A demo is also available on the [`facebook/MusicGen`  HuggingFace Space](https://huggingface.co/spaces/facebook/MusicGen) (huge thanks to all the HF team for their support).
-2. You can run the extended demo on a Colab: [colab notebook](https://colab.research.google.com/drive/1fxGqfg96RBUvGxZ1XXN07s3DthrKUl4-?usp=sharing).
-3. You can use the gradio demo locally by running `python app.py`.
-4. You can play with MusicGen by running the jupyter notebook at [`demo.ipynb`](./demo.ipynb) locally (if you have a GPU).
-5. Finally, checkout [@camenduru Colab page](https://github.com/camenduru/MusicGen-colab) which is regularly
-  updated with contributions from @camenduru and the community.
-
-## API
-
-We provide a simple API and 4 pre-trained models. The pre trained models are:
-- `small`: 300M model, text to music only - [🤗 Hub](https://huggingface.co/facebook/musicgen-small)
-- `medium`: 1.5B model, text to music only - [🤗 Hub](https://huggingface.co/facebook/musicgen-medium)
-- `melody`: 1.5B model, text to music and text+melody to music - [🤗 Hub](https://huggingface.co/facebook/musicgen-melody)
-- `large`: 3.3B model, text to music only - [🤗 Hub](https://huggingface.co/facebook/musicgen-large)
-
-We observe the best trade-off between quality and compute with the `medium` or `melody` model.
-In order to use MusicGen locally **you must have a GPU**. We recommend 16GB of memory, but smaller
-GPUs will be able to generate short sequences, or longer sequences with the `small` model.
-
-**Note**: Please make sure to have [ffmpeg](https://ffmpeg.org/download.html) installed when using newer version of `torchaudio`.
-You can install it with:
-```
-apt-get install ffmpeg
-```
-
-See after a quick example for using the API.
-
-```python
-import torchaudio
-from audiocraft.models import MusicGen
-from audiocraft.data.audio import audio_write
-
-model = MusicGen.get_pretrained('melody')
-model.set_generation_params(duration=8)  # generate 8 seconds.
-wav = model.generate_unconditional(4)    # generates 4 unconditional audio samples
-descriptions = ['happy rock', 'energetic EDM', 'sad jazz']
-wav = model.generate(descriptions)  # generates 3 samples.
-
-melody, sr = torchaudio.load('./assets/bach.mp3')
-# generates using the melody from the given audio and the provided descriptions.
-wav = model.generate_with_chroma(descriptions, melody[None].expand(3, -1, -1), sr)
-
-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)
-```
-
-
-## Model Card
-
-See [the model card page](./MODEL_CARD.md).
-
-## FAQ
-
-#### Will the training code be released?
-
-Yes. We will soon release the training code for MusicGen and EnCodec.
-
-
-#### I need help on Windows
-
-@FurkanGozukara made a complete tutorial for [Audiocraft/MusicGen on Windows](https://youtu.be/v-YpvPkhdO4)
-
-
-## Citation
-```
-@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
-* The code in this repository is released under the MIT license as found in the [LICENSE file](LICENSE).
-* The weights in this repository are released under the CC-BY-NC 4.0 license as found in the [LICENSE_weights file](LICENSE_weights).
-
-[arxiv]: https://arxiv.org/abs/2306.05284
-[musicgen_samples]: https://ai.honu.io/papers/musicgen/
diff --git a/spaces/wang2246478872/facebook-m2m100_1.2B/app.py b/spaces/wang2246478872/facebook-m2m100_1.2B/app.py
deleted file mode 100644
index 675c580ca51e10c2ba386031faed78b9a9f8ab67..0000000000000000000000000000000000000000
--- a/spaces/wang2246478872/facebook-m2m100_1.2B/app.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import streamlit as st
-
-from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
-
-
-@st.cache_resource
-def init_model():
-    model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_1.2B")
-    tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B")
-    return model, tokenizer
-
-
-model, tokenizer = init_model()
-
-langs = {"zh": "Chinese", "en": "English", "af": "Afrikaans", "am": "Amharic", "ar": "Arabic", "as": "Asturian",
-         "az": "Azerbaijani", "ba": "Bashkir", "be": "Belarusian", "bg": "Bulgarian", "bn": "Bengali", "br": "Breton",
-         "bs": "Bosnian", "ca": "Valencian", "ce": "Cebuano", "cs": "Czech", "cy": "Welsh", "da": "Danish",
-         "de": "German", "el": "Greeek", "es": "Spanish", "et": "Estonian", "fa": "Persian", "ff": "Fulah",
-         "fi": "Finnish", "fr": "French", "fy": "Frisian", "ga": "Irish", "gd": "Gaelic", "gl": "Galician",
-         "gu": "Gujarati", "ha": "Hausa", "he": "Hebrew", "hi": "Hindi", "hr": "Croatian", "ht": "Creole",
-         "hu": "Hungarian", "hy": "Armenian", "id": "Indonesian", "ig": "Igbo", "il": "Iloko", "is": "Icelandic",
-         "it": "Italian", "ja": "Japanese", "jv": "Javanese", "ka": "Georgian", "kk": "Kazakh", "km": "Khmer",
-         "kn": "Kannada", "ko": "Korean", "lb": "Letzeburgesch", "lg": "Ganda", "ln": "Lingala", "lo": "Lao",
-         "lt": "Lithuanian", "lv": "Latvian", "mg": "Malagasy", "mk": "Macedonian", "ml": "Malayalam",
-         "mn": "Mongolian", "mr": "Marathi", "ms": "Malay", "my": "Burmese", "ne": "Nepali", "nl": "Flemish",
-         "no": "Norwegian", "ns": "Sotho", "or": "Oriya", "pa": "Punjabi", "pl": "Polish", "ps": "Pashto",
-         "pt": "Portuguese", "ro": "Moldovan", "ru": "Russian", "sd": "Sindhi", "si": "Sinhalese", "sk": "Slovak",
-         "sl": "Slovenian", "so": "Somali", "sq": "Albanian", "sr": "Serbian", "ss": "Swati", "su": "Sundanese",
-         "sv": "Swedish", "sw": "Swahili", "ta": "Tamil", "th": "Thai", "tl": "Tagalog", "tn": "Tswana",
-         "tr": "Turkish", "uk": "Ukrainian", "ur": "Urdu", "uz": "Uzbek", "vi": "Vietnamese", "wo": "Wolof",
-         "xh": "Xhosa", "yi": "Yiddish", "yo": "Yoruba", "zu": "Zulu"}
-
-
-def chose_lang_format(option):
-    return langs[option]
-
-
-st.title('💿facebook-m2m100_1.2B')
-with st.form('my_form'):
-    text = st.text_area('Enter text:', '')
-    cols = st.columns(3)
-    submitted = cols[0].form_submit_button('翻译')
-    src = cols[1].selectbox(
-        'from', options=list(langs.keys()), format_func=chose_lang_format)
-    to = cols[2].selectbox(
-        'to', options=list(langs.keys()), format_func=chose_lang_format)
-
-placeholder = st.markdown("", unsafe_allow_html=True)
-if submitted:
-    with st.spinner("Translating..."):
-        tokenizer.src_lang = src
-        encoded_zh = tokenizer(text, return_tensors="pt")
-        generated_tokens = model.generate(**encoded_zh, forced_bos_token_id=tokenizer.get_lang_id(to))
-        translated = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-        placeholder.markdown(translated[0])
diff --git a/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/modeling/sam.py b/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/modeling/sam.py
deleted file mode 100644
index 303bc2f40c3dbc84f5d4286bb73336e075a86589..0000000000000000000000000000000000000000
--- a/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/modeling/sam.py
+++ /dev/null
@@ -1,174 +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 torch
-from torch import nn
-from torch.nn import functional as F
-
-from typing import Any, Dict, List, Tuple
-
-from .image_encoder import ImageEncoderViT
-from .mask_decoder import MaskDecoder
-from .prompt_encoder import PromptEncoder
-
-
-class Sam(nn.Module):
-    mask_threshold: float = 0.0
-    image_format: str = "RGB"
-
-    def __init__(
-        self,
-        image_encoder: ImageEncoderViT,
-        prompt_encoder: PromptEncoder,
-        mask_decoder: MaskDecoder,
-        pixel_mean: List[float] = [123.675, 116.28, 103.53],
-        pixel_std: List[float] = [58.395, 57.12, 57.375],
-    ) -> None:
-        """
-        SAM predicts object masks from an image and input prompts.
-
-        Arguments:
-          image_encoder (ImageEncoderViT): The backbone used to encode the
-            image into image embeddings that allow for efficient mask prediction.
-          prompt_encoder (PromptEncoder): Encodes various types of input prompts.
-          mask_decoder (MaskDecoder): Predicts masks from the image embeddings
-            and encoded prompts.
-          pixel_mean (list(float)): Mean values for normalizing pixels in the input image.
-          pixel_std (list(float)): Std values for normalizing pixels in the input image.
-        """
-        super().__init__()
-        self.image_encoder = image_encoder
-        self.prompt_encoder = prompt_encoder
-        self.mask_decoder = mask_decoder
-        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1), False)
-        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1), False)
-
-    @property
-    def device(self) -> Any:
-        return self.pixel_mean.device
-
-    @torch.no_grad()
-    def forward(
-        self,
-        batched_input: List[Dict[str, Any]],
-        multimask_output: bool,
-    ) -> List[Dict[str, torch.Tensor]]:
-        """
-        Predicts masks end-to-end from provided images and prompts.
-        If prompts are not known in advance, using SamPredictor is
-        recommended over calling the model directly.
-
-        Arguments:
-          batched_input (list(dict)): A list over input images, each a
-            dictionary with the following keys. A prompt key can be
-            excluded if it is not present.
-              'image': The image as a torch tensor in 3xHxW format,
-                already transformed for input to the model.
-              'original_size': (tuple(int, int)) The original size of
-                the image before transformation, as (H, W).
-              'point_coords': (torch.Tensor) Batched point prompts for
-                this image, with shape BxNx2. Already transformed to the
-                input frame of the model.
-              'point_labels': (torch.Tensor) Batched labels for point prompts,
-                with shape BxN.
-              'boxes': (torch.Tensor) Batched box inputs, with shape Bx4.
-                Already transformed to the input frame of the model.
-              'mask_inputs': (torch.Tensor) Batched mask inputs to the model,
-                in the form Bx1xHxW.
-          multimask_output (bool): Whether the model should predict multiple
-            disambiguating masks, or return a single mask.
-
-        Returns:
-          (list(dict)): A list over input images, where each element is
-            as dictionary with the following keys.
-              'masks': (torch.Tensor) Batched binary mask predictions,
-                with shape BxCxHxW, where B is the number of input promts,
-                C is determiend by multimask_output, and (H, W) is the
-                original size of the image.
-              'iou_predictions': (torch.Tensor) The model's predictions
-                of mask quality, in shape BxC.
-              'low_res_logits': (torch.Tensor) Low resolution logits with
-                shape BxCxHxW, where H=W=256. Can be passed as mask input
-                to subsequent iterations of prediction.
-        """
-        input_images = torch.stack([self.preprocess(x["image"]) for x in batched_input], dim=0)
-        image_embeddings = self.image_encoder(input_images)
-
-        outputs = []
-        for image_record, curr_embedding in zip(batched_input, image_embeddings):
-            if "point_coords" in image_record:
-                points = (image_record["point_coords"], image_record["point_labels"])
-            else:
-                points = None
-            sparse_embeddings, dense_embeddings = self.prompt_encoder(
-                points=points,
-                boxes=image_record.get("boxes", None),
-                masks=image_record.get("mask_inputs", None),
-            )
-            low_res_masks, iou_predictions = self.mask_decoder(
-                image_embeddings=curr_embedding.unsqueeze(0),
-                image_pe=self.prompt_encoder.get_dense_pe(),
-                sparse_prompt_embeddings=sparse_embeddings,
-                dense_prompt_embeddings=dense_embeddings,
-                multimask_output=multimask_output,
-            )
-            masks = self.postprocess_masks(
-                low_res_masks,
-                input_size=image_record["image"].shape[-2:],
-                original_size=image_record["original_size"],
-            )
-            masks = masks > self.mask_threshold
-            outputs.append(
-                {
-                    "masks": masks,
-                    "iou_predictions": iou_predictions,
-                    "low_res_logits": low_res_masks,
-                }
-            )
-        return outputs
-
-    def postprocess_masks(
-        self,
-        masks: torch.Tensor,
-        input_size: Tuple[int, ...],
-        original_size: Tuple[int, ...],
-    ) -> torch.Tensor:
-        """
-        Remove padding and upscale masks to the original image size.
-
-        Arguments:
-          masks (torch.Tensor): Batched masks from the mask_decoder,
-            in BxCxHxW format.
-          input_size (tuple(int, int)): The size of the image input to the
-            model, in (H, W) format. Used to remove padding.
-          original_size (tuple(int, int)): The original size of the image
-            before resizing for input to the model, in (H, W) format.
-
-        Returns:
-          (torch.Tensor): Batched masks in BxCxHxW format, where (H, W)
-            is given by original_size.
-        """
-        masks = F.interpolate(
-            masks,
-            (self.image_encoder.img_size, self.image_encoder.img_size),
-            mode="bilinear",
-            align_corners=False,
-        )
-        masks = masks[..., : input_size[0], : input_size[1]]
-        masks = F.interpolate(masks, original_size, mode="bilinear", align_corners=False)
-        return masks
-
-    def preprocess(self, x: torch.Tensor) -> torch.Tensor:
-        """Normalize pixel values and pad to a square input."""
-        # Normalize colors
-        x = (x - self.pixel_mean) / self.pixel_std
-
-        # Pad
-        h, w = x.shape[-2:]
-        padh = self.image_encoder.img_size - h
-        padw = self.image_encoder.img_size - w
-        x = F.pad(x, (0, padw, 0, padh))
-        return x
diff --git a/spaces/wffcyrus/MetaGPT-v1/metagpt/tools/__init__.py b/spaces/wffcyrus/MetaGPT-v1/metagpt/tools/__init__.py
deleted file mode 100644
index a148bb7447d4219e7f0e92ed002ddfddff8d6a20..0000000000000000000000000000000000000000
--- a/spaces/wffcyrus/MetaGPT-v1/metagpt/tools/__init__.py
+++ /dev/null
@@ -1,29 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    : 2023/4/29 15:35
-@Author  : alexanderwu
-@File    : __init__.py
-"""
-
-
-from enum import Enum
-
-
-class SearchEngineType(Enum):
-    SERPAPI_GOOGLE = "serpapi"
-    SERPER_GOOGLE = "serper"
-    DIRECT_GOOGLE = "google"
-    DUCK_DUCK_GO = "ddg"
-    CUSTOM_ENGINE = "custom"
-
-
-class WebBrowserEngineType(Enum):
-    PLAYWRIGHT = "playwright"
-    SELENIUM = "selenium"
-    CUSTOM = "custom"
-
-    @classmethod
-    def _missing_(cls, key):
-        """缺省类型转换"""
-        return cls.CUSTOM
diff --git a/spaces/willgibs/ControlNet-v1-1/app.py b/spaces/willgibs/ControlNet-v1-1/app.py
deleted file mode 100644
index b1e36781302a65880879b4853004646b08abe3e5..0000000000000000000000000000000000000000
--- a/spaces/willgibs/ControlNet-v1-1/app.py
+++ /dev/null
@@ -1,130 +0,0 @@
-#!/usr/bin/env python
-
-from __future__ import annotations
-
-import os
-
-import gradio as gr
-import torch
-
-from app_canny import create_demo as create_demo_canny
-from app_depth import create_demo as create_demo_depth
-from app_ip2p import create_demo as create_demo_ip2p
-from app_lineart import create_demo as create_demo_lineart
-from app_mlsd import create_demo as create_demo_mlsd
-from app_normal import create_demo as create_demo_normal
-from app_openpose import create_demo as create_demo_openpose
-from app_scribble import create_demo as create_demo_scribble
-from app_scribble_interactive import \
-    create_demo as create_demo_scribble_interactive
-from app_segmentation import create_demo as create_demo_segmentation
-from app_shuffle import create_demo as create_demo_shuffle
-from app_softedge import create_demo as create_demo_softedge
-from model import Model
-
-DESCRIPTION = '# ControlNet v1.1'
-
-SPACE_ID = os.getenv('SPACE_ID')
-ALLOW_CHANGING_BASE_MODEL = SPACE_ID != 'hysts/ControlNet-v1-1'
-
-if SPACE_ID is not None:
-    DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
-
-if not torch.cuda.is_available():
-    DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
-
-MAX_NUM_IMAGES = int(os.getenv('MAX_NUM_IMAGES', '3'))
-DEFAULT_NUM_IMAGES = min(MAX_NUM_IMAGES,
-                         int(os.getenv('DEFAULT_NUM_IMAGES', '1')))
-
-DEFAULT_MODEL_ID = os.getenv('DEFAULT_MODEL_ID',
-                             'runwayml/stable-diffusion-v1-5')
-model = Model(base_model_id=DEFAULT_MODEL_ID, task_name='Canny')
-
-with gr.Blocks(css='style.css') as demo:
-    gr.Markdown(DESCRIPTION)
-    with gr.Tabs():
-        with gr.TabItem('Canny'):
-            create_demo_canny(model.process_canny,
-                              max_images=MAX_NUM_IMAGES,
-                              default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('MLSD'):
-            create_demo_mlsd(model.process_mlsd,
-                             max_images=MAX_NUM_IMAGES,
-                             default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Scribble'):
-            create_demo_scribble(model.process_scribble,
-                                 max_images=MAX_NUM_IMAGES,
-                                 default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Scribble Interactive'):
-            create_demo_scribble_interactive(
-                model.process_scribble_interactive,
-                max_images=MAX_NUM_IMAGES,
-                default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('SoftEdge'):
-            create_demo_softedge(model.process_softedge,
-                                 max_images=MAX_NUM_IMAGES,
-                                 default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('OpenPose'):
-            create_demo_openpose(model.process_openpose,
-                                 max_images=MAX_NUM_IMAGES,
-                                 default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Segmentation'):
-            create_demo_segmentation(model.process_segmentation,
-                                     max_images=MAX_NUM_IMAGES,
-                                     default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Depth'):
-            create_demo_depth(model.process_depth,
-                              max_images=MAX_NUM_IMAGES,
-                              default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Normal map'):
-            create_demo_normal(model.process_normal,
-                               max_images=MAX_NUM_IMAGES,
-                               default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Lineart'):
-            create_demo_lineart(model.process_lineart,
-                                max_images=MAX_NUM_IMAGES,
-                                default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Content Shuffle'):
-            create_demo_shuffle(model.process_shuffle,
-                                max_images=MAX_NUM_IMAGES,
-                                default_num_images=DEFAULT_NUM_IMAGES)
-        with gr.TabItem('Instruct Pix2Pix'):
-            create_demo_ip2p(model.process_ip2p,
-                             max_images=MAX_NUM_IMAGES,
-                             default_num_images=DEFAULT_NUM_IMAGES)
-
-    with gr.Accordion(label='Base model', open=False):
-        with gr.Row():
-            with gr.Column():
-                current_base_model = gr.Text(label='Current base model')
-            with gr.Column(scale=0.3):
-                check_base_model_button = gr.Button('Check current base model')
-        with gr.Row():
-            with gr.Column():
-                new_base_model_id = gr.Text(
-                    label='New base model',
-                    max_lines=1,
-                    placeholder='runwayml/stable-diffusion-v1-5',
-                    info=
-                    'The base model must be compatible with Stable Diffusion v1.5.',
-                    interactive=ALLOW_CHANGING_BASE_MODEL)
-            with gr.Column(scale=0.3):
-                change_base_model_button = gr.Button(
-                    'Change base model', interactive=ALLOW_CHANGING_BASE_MODEL)
-        if not ALLOW_CHANGING_BASE_MODEL:
-            gr.Markdown(
-                '''The base model is not allowed to be changed in this Space so as not to slow down the demo, but it can be changed if you duplicate the Space. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a>'''
-            )
-
-    check_base_model_button.click(fn=lambda: model.base_model_id,
-                                  outputs=current_base_model,
-                                  queue=False)
-    new_base_model_id.submit(fn=model.set_base_model,
-                             inputs=new_base_model_id,
-                             outputs=current_base_model)
-    change_base_model_button.click(fn=model.set_base_model,
-                                   inputs=new_base_model_id,
-                                   outputs=current_base_model)
-
-demo.queue(max_size=20).launch()
diff --git a/spaces/wilson1/bingo/src/lib/utils.ts b/spaces/wilson1/bingo/src/lib/utils.ts
deleted file mode 100644
index 07feedb34e356b1b3cf867872f32d47a96ae12fb..0000000000000000000000000000000000000000
--- a/spaces/wilson1/bingo/src/lib/utils.ts
+++ /dev/null
@@ -1,138 +0,0 @@
-import { clsx, type ClassValue } from 'clsx'
-import { customAlphabet } from 'nanoid'
-import { twMerge } from 'tailwind-merge'
-
-export function cn(...inputs: ClassValue[]) {
-  return twMerge(clsx(inputs))
-}
-
-export const nanoid = customAlphabet(
-  '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz',
-  7
-) // 7-character random string
-
-export function createChunkDecoder() {
-  const decoder = new TextDecoder()
-  return function (chunk: Uint8Array | undefined): string {
-    if (!chunk) return ''
-    return decoder.decode(chunk, { stream: true })
-  }
-}
-
-export function random (start: number, end: number) {
-  return start + Math.ceil(Math.random() * (end - start))
-}
-
-export function randomIP() {
-  return `11.${random(104, 107)}.${random(1, 255)}.${random(1, 255)}`
-}
-
-export function parseHeadersFromCurl(content: string) {
-  const re = /-H '([^:]+):\s*([^']+)/mg
-  const headers: HeadersInit = {}
-  content = content.replaceAll('-H "', '-H \'').replaceAll('" ^', '\'\\').replaceAll('^\\^"', '"') // 将 cmd curl 转成 bash curl
-  content.replace(re, (_: string, key: string, value: string) => {
-    headers[key] = value
-    return ''
-  })
-
-  return headers
-}
-
-export const ChunkKeys = ['BING_HEADER', 'BING_HEADER1', 'BING_HEADER2']
-export function encodeHeadersToCookie(content: string) {
-  const base64Content = btoa(content)
-  const contentChunks = base64Content.match(/.{1,4000}/g) || []
-  return ChunkKeys.map((key, index) => `${key}=${contentChunks[index] ?? ''}`)
-}
-
-export function extraCurlFromCookie(cookies: Partial<{ [key: string]: string }>) {
-  let base64Content = ''
-  ChunkKeys.forEach((key) => {
-    base64Content += (cookies[key] || '')
-  })
-  try {
-    return atob(base64Content)
-  } catch(e) {
-    return ''
-  }
-}
-
-export function extraHeadersFromCookie(cookies: Partial<{ [key: string]: string }>) {
-  return parseHeadersFromCurl(extraCurlFromCookie(cookies))
-}
-
-export function formatDate(input: string | number | Date): string {
-  const date = new Date(input)
-  return date.toLocaleDateString('en-US', {
-    month: 'long',
-    day: 'numeric',
-    year: 'numeric'
-  })
-}
-
-export function parseCookie(cookie: string, cookieName: string) {
-  const targetCookie = new RegExp(`(?:[; ]|^)${cookieName}=([^;]*)`).test(cookie) ? RegExp.$1 : cookie
-  return targetCookie ? decodeURIComponent(targetCookie).trim() : cookie.indexOf('=') === -1 ? cookie.trim() : ''
-}
-
-export function parseCookies(cookie: string, cookieNames: string[]) {
-  const cookies: { [key: string]: string } = {}
-  cookieNames.forEach(cookieName => {
-    cookies[cookieName] = parseCookie(cookie, cookieName)
-  })
-  return cookies
-}
-
-export const DEFAULT_UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36 Edg/115.0.0.0'
-export const DEFAULT_IP = process.env.BING_IP || randomIP()
-
-export function parseUA(ua?: string, default_ua = DEFAULT_UA) {
-  return / EDGE?/i.test(decodeURIComponent(ua || '')) ? decodeURIComponent(ua!.trim()) : default_ua
-}
-
-export function createHeaders(cookies: Partial<{ [key: string]: string }>, defaultHeaders?: Partial<{ [key: string]: string }>) {
-  let {
-    BING_COOKIE = process.env.BING_COOKIE,
-    BING_UA = process.env.BING_UA,
-    BING_IP = process.env.BING_IP,
-    BING_HEADER = process.env.BING_HEADER,
-  } = cookies
-
-  if (BING_HEADER) {
-    return extraHeadersFromCookie({
-      BING_HEADER,
-      ...cookies,
-    })
-  }
-
-  const ua = parseUA(BING_UA)
-
-  if (!BING_COOKIE) {
-    BING_COOKIE = defaultHeaders?.IMAGE_BING_COOKIE || 'xxx' // hf 暂时不用 Cookie 也可以正常使用
-  }
-
-  const parsedCookie = parseCookie(BING_COOKIE, '_U')
-  if (!parsedCookie) {
-    throw new Error('Invalid Cookie')
-  }
-  return {
-    'x-forwarded-for': BING_IP || DEFAULT_IP,
-    'Accept-Encoding': 'gzip, deflate, br',
-    'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6',
-    'User-Agent': ua!,
-    'x-ms-useragent': 'azsdk-js-api-client-factory/1.0.0-beta.1 core-rest-pipeline/1.10.0 OS/Win32',
-    cookie: `_U=${parsedCookie}` || '',
-  }
-}
-
-export class WatchDog {
-  private tid = 0
-  watch(fn: Function, timeout = 2000) {
-    clearTimeout(this.tid)
-    this.tid = setTimeout(fn, timeout + Math.random() * 1000)
-  }
-  reset() {
-    clearTimeout(this.tid)
-  }
-}
diff --git a/spaces/wrldreform/Text2ImageStable2.1/app.py b/spaces/wrldreform/Text2ImageStable2.1/app.py
deleted file mode 100644
index 0160420876923d89f2ab5fccb9f4d13725e29972..0000000000000000000000000000000000000000
--- a/spaces/wrldreform/Text2ImageStable2.1/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/stabilityai/stable-diffusion-2-1").launch()
\ No newline at end of file
diff --git a/spaces/xdecoder/Demo/xdecoder/language/LangEncoder/registry.py b/spaces/xdecoder/Demo/xdecoder/language/LangEncoder/registry.py
deleted file mode 100644
index 8991272a6e2294ea86eee338cf61d87e4123f724..0000000000000000000000000000000000000000
--- a/spaces/xdecoder/Demo/xdecoder/language/LangEncoder/registry.py
+++ /dev/null
@@ -1,18 +0,0 @@
-_lang_encoders = {}
-
-
-def register_lang_encoder(fn):
-    module_name_split = fn.__module__.split('.')
-    model_name = module_name_split[-1]
-
-    _lang_encoders[model_name] = fn
-
-    return fn
-
-
-def lang_encoders(model_name):
-    return _lang_encoders[model_name]
-
-
-def is_lang_encoder(model_name):
-    return model_name in _lang_encoders
diff --git a/spaces/xp3857/Image_Restoration_Colorization/Global/detection_models/Synchronized-BatchNorm-PyTorch/tests/test_numeric_batchnorm_v2.py b/spaces/xp3857/Image_Restoration_Colorization/Global/detection_models/Synchronized-BatchNorm-PyTorch/tests/test_numeric_batchnorm_v2.py
deleted file mode 100644
index 5e4538ae3c50b4c457a9fa19bf22b5b1a7b666ee..0000000000000000000000000000000000000000
--- a/spaces/xp3857/Image_Restoration_Colorization/Global/detection_models/Synchronized-BatchNorm-PyTorch/tests/test_numeric_batchnorm_v2.py
+++ /dev/null
@@ -1,62 +0,0 @@
-#! /usr/bin/env python3
-# -*- coding: utf-8 -*-
-# File   : test_numeric_batchnorm_v2.py
-# Author : Jiayuan Mao
-# Email  : maojiayuan@gmail.com
-# Date   : 11/01/2018
-#
-# Distributed under terms of the MIT license.
-
-"""
-Test the numerical implementation of batch normalization.
-
-Author: acgtyrant.
-See also: https://github.com/vacancy/Synchronized-BatchNorm-PyTorch/issues/14
-"""
-
-import unittest
-
-import torch
-import torch.nn as nn
-import torch.optim as optim
-
-from sync_batchnorm.unittest import TorchTestCase
-from sync_batchnorm.batchnorm_reimpl import BatchNorm2dReimpl
-
-
-class NumericTestCasev2(TorchTestCase):
-    def testNumericBatchNorm(self):
-        CHANNELS = 16
-        batchnorm1 = nn.BatchNorm2d(CHANNELS, momentum=1)
-        optimizer1 = optim.SGD(batchnorm1.parameters(), lr=0.01)
-
-        batchnorm2 = BatchNorm2dReimpl(CHANNELS, momentum=1)
-        batchnorm2.weight.data.copy_(batchnorm1.weight.data)
-        batchnorm2.bias.data.copy_(batchnorm1.bias.data)
-        optimizer2 = optim.SGD(batchnorm2.parameters(), lr=0.01)
-
-        for _ in range(100):
-            input_ = torch.rand(16, CHANNELS, 16, 16)
-
-            input1 = input_.clone().requires_grad_(True)
-            output1 = batchnorm1(input1)
-            output1.sum().backward()
-            optimizer1.step()
-
-            input2 = input_.clone().requires_grad_(True)
-            output2 = batchnorm2(input2)
-            output2.sum().backward()
-            optimizer2.step()
-
-        self.assertTensorClose(input1, input2)
-        self.assertTensorClose(output1, output2)
-        self.assertTensorClose(input1.grad, input2.grad)
-        self.assertTensorClose(batchnorm1.weight.grad, batchnorm2.weight.grad)
-        self.assertTensorClose(batchnorm1.bias.grad, batchnorm2.bias.grad)
-        self.assertTensorClose(batchnorm1.running_mean, batchnorm2.running_mean)
-        self.assertTensorClose(batchnorm2.running_mean, batchnorm2.running_mean)
-
-
-if __name__ == '__main__':
-    unittest.main()
-
diff --git a/spaces/yangogo/bingo/src/components/settings.tsx b/spaces/yangogo/bingo/src/components/settings.tsx
deleted file mode 100644
index e18aa5b484852bb5d047442a06e7143b6893cb0d..0000000000000000000000000000000000000000
--- a/spaces/yangogo/bingo/src/components/settings.tsx
+++ /dev/null
@@ -1,141 +0,0 @@
-import { useEffect, useState } from 'react'
-import { useAtom } from 'jotai'
-import { Switch } from '@headlessui/react'
-import { toast } from 'react-hot-toast'
-import { hashAtom, voiceAtom } from '@/state'
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle
-} from '@/components/ui/dialog'
-import { Button } from './ui/button'
-import { Input } from './ui/input'
-import { ChunkKeys, parseCookies, extraCurlFromCookie, randomIP, encodeHeadersToCookie } from '@/lib/utils'
-import { ExternalLink } from './external-link'
-import { useCopyToClipboard } from '@/lib/hooks/use-copy-to-clipboard'
-
-export function Settings() {
-  const { isCopied, copyToClipboard } = useCopyToClipboard({ timeout: 2000 })
-  const [loc, setLoc] = useAtom(hashAtom)
-  const [curlValue, setCurlValue] = useState(extraCurlFromCookie(parseCookies(document.cookie, ChunkKeys)))
-  const [enableTTS, setEnableTTS] = useAtom(voiceAtom)
-
-  useEffect(() => {
-    if (isCopied) {
-      toast.success('复制成功')
-    }
-  }, [isCopied])
-
-  if (loc === 'settings') {
-    return (
-      <Dialog open onOpenChange={() => setLoc('')} modal>
-        <DialogContent>
-          <DialogHeader>
-            <DialogTitle>设置你的用户信息</DialogTitle>
-            <DialogDescription>
-              请使用 Edge 浏览器
-              <ExternalLink
-                href="https://www.bing.com/turing/captcha/challenge"
-              >
-                打开并登录 Bing
-              </ExternalLink>
-              ，然后再打开
-              <ExternalLink href="https://www.bing.com/turing/captcha/challenge">Challenge 接口</ExternalLink>
-              右键 》检查。打开开发者工具，在网络里面找到 Create 接口 》右键复制》复制为 cURL(bash)，粘贴到此处，然后保存。
-              <div className="h-2" />
-              图文示例：
-              <ExternalLink href="https://github.com/weaigc/bingo#如何获取%20BING_HEADER">如何获取 BING_HEADER</ExternalLink>
-            </DialogDescription>
-          </DialogHeader>
-          <div className="flex gap-4">
-
-          </div>
-          <Input
-            value={curlValue}
-            placeholder="在此填写用户信息，格式: curl 'https://www.bing.com/turing/captcha/challenge' ..."
-            onChange={e => setCurlValue(e.target.value)}
-          />
-          <Button variant="ghost" className="bg-[#F5F5F5] hover:bg-[#F2F2F2]" onClick={() => copyToClipboard(btoa(curlValue))}>
-            转成 BING_HEADER 并复制
-          </Button>
-
-          <DialogFooter className="items-center">
-            <Button
-              variant="secondary"
-              className="bg-[#c7f3ff] hover:bg-[#fdc7ff]"
-              onClick={() => {
-                let headerValue = curlValue
-                if (headerValue) {
-                  try {
-                    headerValue = atob(headerValue)
-                  } catch (e) {}
-                  if (!/^\s*curl ['"]https:\/\/www\.bing\.com\/turing\/captcha\/challenge['"]/.test(headerValue)) {
-                    toast.error('格式不正确')
-                    return
-                  }
-                  const maxAge = 86400 * 30
-                  encodeHeadersToCookie(headerValue).forEach(cookie => document.cookie = `${cookie}; Max-Age=${maxAge}; Path=/; SameSite=None; Secure`)
-                } else {
-                  [...ChunkKeys, 'BING_COOKIE', 'BING_UA', 'BING_IP'].forEach(key => document.cookie = `${key}=; Path=/; SameSite=None; Secure`)
-                }
-
-                toast.success('保存成功')
-                setLoc('')
-                setTimeout(() => {
-                  location.href = './'
-                }, 2000)
-              }}
-            >
-              保存
-            </Button>
-          </DialogFooter>
-        </DialogContent>
-      </Dialog>
-    )
-  } else if (loc === 'voice') {
-    return (
-      <Dialog open onOpenChange={() => setLoc('')} modal>
-        <DialogContent>
-          <DialogHeader>
-            <DialogTitle>语音设置</DialogTitle>
-            <DialogDescription>
-              目前仅支持 PC 端 Edge 及 Chrome 浏览器
-            </DialogDescription>
-          </DialogHeader>
-
-          <div className="flex gap-2">
-            启用语音回答
-            <Switch
-              checked={enableTTS}
-              className={`${enableTTS ? 'bg-blue-600' : 'bg-gray-200'} relative inline-flex h-6 w-11 items-center rounded-full`}
-              onChange={(checked: boolean) => setEnableTTS(checked)}
-            >
-              <span
-                className={`${enableTTS ? 'translate-x-6' : 'translate-x-1'} inline-block h-4 w-4 transform rounded-full bg-white transition`}
-              />
-            </Switch>
-          </div>
-
-          <DialogFooter className="items-center">
-            <Button
-              variant="secondary"
-              onClick={() => {
-                toast.success('保存成功')
-                setLoc('')
-                setTimeout(() => {
-                  location.href = './'
-                }, 2000)
-              }}
-            >
-              保存
-            </Button>
-          </DialogFooter>
-        </DialogContent>
-      </Dialog>
-    )
-  }
-  return null
-}
diff --git a/spaces/ygangang/VToonify/vtoonify/model/raft/alt_cuda_corr/setup.py b/spaces/ygangang/VToonify/vtoonify/model/raft/alt_cuda_corr/setup.py
deleted file mode 100644
index c0207ff285ffac4c8146c79d154f12416dbef48c..0000000000000000000000000000000000000000
--- a/spaces/ygangang/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/ygtxr1997/ReliableSwap_Demo/third_party/GPEN/training/data_loader/dataset_face.py b/spaces/ygtxr1997/ReliableSwap_Demo/third_party/GPEN/training/data_loader/dataset_face.py
deleted file mode 100644
index ff13cf1f7d581d0e2dc9a1bda9001a78f5733901..0000000000000000000000000000000000000000
--- a/spaces/ygtxr1997/ReliableSwap_Demo/third_party/GPEN/training/data_loader/dataset_face.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import numpy as np
-import cv2
-import os
-import glob
-import math
-import random
-import torch
-import torch.nn.functional as F
-from torch.utils.data import Dataset
-
-import degradations
-
-
-class GFPGAN_degradation(object):
-    def __init__(self):
-        self.kernel_list = ['iso', 'aniso']
-        self.kernel_prob = [0.5, 0.5]
-        self.blur_kernel_size = 41
-        self.blur_sigma = [0.1, 10]
-        self.downsample_range = [0.8, 8]
-        self.noise_range = [0, 20]
-        self.jpeg_range = [60, 100]
-        self.gray_prob = 0.2
-        self.color_jitter_prob = 0.0
-        self.color_jitter_pt_prob = 0.0
-        self.shift = 20/255.
-    
-    def degrade_process(self, img_gt):
-        if random.random() > 0.5:
-            img_gt = cv2.flip(img_gt, 1)
-
-        h, w = img_gt.shape[:2]
-       
-        # random color jitter 
-        if np.random.uniform() < self.color_jitter_prob:
-            jitter_val = np.random.uniform(-self.shift, self.shift, 3).astype(np.float32)
-            img_gt = img_gt + jitter_val
-            img_gt = np.clip(img_gt, 0, 1)    
-
-        # random grayscale
-        if np.random.uniform() < self.gray_prob:
-            img_gt = cv2.cvtColor(img_gt, cv2.COLOR_BGR2GRAY)
-            img_gt = np.tile(img_gt[:, :, None], [1, 1, 3])
-        
-        # ------------------------ generate lq image ------------------------ #
-        # blur
-        kernel = degradations.random_mixed_kernels(
-                self.kernel_list,
-                self.kernel_prob,
-                self.blur_kernel_size,
-                self.blur_sigma,
-                self.blur_sigma, [-math.pi, math.pi],
-                noise_range=None)
-        img_lq = cv2.filter2D(img_gt, -1, kernel)
-        # downsample
-        scale = np.random.uniform(self.downsample_range[0], self.downsample_range[1])
-        img_lq = cv2.resize(img_lq, (int(w // scale), int(h // scale)), interpolation=cv2.INTER_LINEAR)
-        
-        # noise
-        if self.noise_range is not None:
-            img_lq = degradations.random_add_gaussian_noise(img_lq, self.noise_range)
-        # jpeg compression
-        if self.jpeg_range is not None:
-            img_lq = degradations.random_add_jpg_compression(img_lq, self.jpeg_range)
-
-        # round and clip
-        img_lq = np.clip((img_lq * 255.0).round(), 0, 255) / 255.
-
-        # resize to original size
-        img_lq = cv2.resize(img_lq, (w, h), interpolation=cv2.INTER_LINEAR)
-
-        return img_gt, img_lq
-
-class FaceDataset(Dataset):
-    def __init__(self, path, resolution=512):
-        self.resolution = resolution
-
-        self.HQ_imgs = glob.glob(os.path.join(path, '*.*'))
-        self.length = len(self.HQ_imgs)
-
-        self.degrader = GFPGAN_degradation()
-
-    def __len__(self):
-        return self.length
-
-    def __getitem__(self, index):
-        img_gt = cv2.imread(self.HQ_imgs[index], cv2.IMREAD_COLOR)
-        img_gt = cv2.resize(img_gt, (self.resolution, self.resolution), interpolation=cv2.INTER_AREA)
-        
-        # BFR degradation
-        # We adopt the degradation of GFPGAN for simplicity, which however differs from our implementation in the paper.
-        # Data degradation plays a key role in BFR. Please replace it with your own methods.
-        img_gt = img_gt.astype(np.float32)/255.
-        img_gt, img_lq = self.degrader.degrade_process(img_gt)
-
-        img_gt =  (torch.from_numpy(img_gt) - 0.5) / 0.5
-        img_lq =  (torch.from_numpy(img_lq) - 0.5) / 0.5
-        
-        img_gt = img_gt.permute(2, 0, 1).flip(0) # BGR->RGB
-        img_lq = img_lq.permute(2, 0, 1).flip(0) # BGR->RGB
-
-        return img_lq, img_gt
-
diff --git a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/generation/__init__.py b/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/generation/__init__.py
deleted file mode 100644
index a46cb4fa910ada3921ea38a8c722817eee46749b..0000000000000000000000000000000000000000
--- a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/generation/__init__.py
+++ /dev/null
@@ -1,296 +0,0 @@
-# Copyright 2022 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_flax_available, is_tf_available, is_torch_available
-
-
-_import_structure = {
-    "configuration_utils": ["GenerationConfig"],
-    "streamers": ["TextIteratorStreamer", "TextStreamer"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["beam_constraints"] = [
-        "Constraint",
-        "ConstraintListState",
-        "DisjunctiveConstraint",
-        "PhrasalConstraint",
-    ]
-    _import_structure["beam_search"] = [
-        "BeamHypotheses",
-        "BeamScorer",
-        "BeamSearchScorer",
-        "ConstrainedBeamSearchScorer",
-    ]
-    _import_structure["logits_process"] = [
-        "AlternatingCodebooksLogitsProcessor",
-        "ClassifierFreeGuidanceLogitsProcessor",
-        "EncoderNoRepeatNGramLogitsProcessor",
-        "EncoderRepetitionPenaltyLogitsProcessor",
-        "EpsilonLogitsWarper",
-        "EtaLogitsWarper",
-        "ExponentialDecayLengthPenalty",
-        "ForcedBOSTokenLogitsProcessor",
-        "ForcedEOSTokenLogitsProcessor",
-        "ForceTokensLogitsProcessor",
-        "HammingDiversityLogitsProcessor",
-        "InfNanRemoveLogitsProcessor",
-        "LogitNormalization",
-        "LogitsProcessor",
-        "LogitsProcessorList",
-        "LogitsWarper",
-        "MinLengthLogitsProcessor",
-        "MinNewTokensLengthLogitsProcessor",
-        "NoBadWordsLogitsProcessor",
-        "NoRepeatNGramLogitsProcessor",
-        "PrefixConstrainedLogitsProcessor",
-        "RepetitionPenaltyLogitsProcessor",
-        "SequenceBiasLogitsProcessor",
-        "SuppressTokensLogitsProcessor",
-        "SuppressTokensAtBeginLogitsProcessor",
-        "TemperatureLogitsWarper",
-        "TopKLogitsWarper",
-        "TopPLogitsWarper",
-        "TypicalLogitsWarper",
-        "UnbatchedClassifierFreeGuidanceLogitsProcessor",
-        "WhisperTimeStampLogitsProcessor",
-    ]
-    _import_structure["stopping_criteria"] = [
-        "MaxNewTokensCriteria",
-        "MaxLengthCriteria",
-        "MaxTimeCriteria",
-        "StoppingCriteria",
-        "StoppingCriteriaList",
-        "validate_stopping_criteria",
-    ]
-    _import_structure["utils"] = [
-        "GenerationMixin",
-        "top_k_top_p_filtering",
-        "GreedySearchEncoderDecoderOutput",
-        "GreedySearchDecoderOnlyOutput",
-        "SampleEncoderDecoderOutput",
-        "SampleDecoderOnlyOutput",
-        "BeamSearchEncoderDecoderOutput",
-        "BeamSearchDecoderOnlyOutput",
-        "BeamSampleEncoderDecoderOutput",
-        "BeamSampleDecoderOnlyOutput",
-        "ContrastiveSearchEncoderDecoderOutput",
-        "ContrastiveSearchDecoderOnlyOutput",
-    ]
-
-try:
-    if not is_tf_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["tf_logits_process"] = [
-        "TFForcedBOSTokenLogitsProcessor",
-        "TFForcedEOSTokenLogitsProcessor",
-        "TFForceTokensLogitsProcessor",
-        "TFLogitsProcessor",
-        "TFLogitsProcessorList",
-        "TFLogitsWarper",
-        "TFMinLengthLogitsProcessor",
-        "TFNoBadWordsLogitsProcessor",
-        "TFNoRepeatNGramLogitsProcessor",
-        "TFRepetitionPenaltyLogitsProcessor",
-        "TFSuppressTokensAtBeginLogitsProcessor",
-        "TFSuppressTokensLogitsProcessor",
-        "TFTemperatureLogitsWarper",
-        "TFTopKLogitsWarper",
-        "TFTopPLogitsWarper",
-    ]
-    _import_structure["tf_utils"] = [
-        "TFGenerationMixin",
-        "tf_top_k_top_p_filtering",
-        "TFGreedySearchDecoderOnlyOutput",
-        "TFGreedySearchEncoderDecoderOutput",
-        "TFSampleEncoderDecoderOutput",
-        "TFSampleDecoderOnlyOutput",
-        "TFBeamSearchEncoderDecoderOutput",
-        "TFBeamSearchDecoderOnlyOutput",
-        "TFBeamSampleEncoderDecoderOutput",
-        "TFBeamSampleDecoderOnlyOutput",
-        "TFContrastiveSearchEncoderDecoderOutput",
-        "TFContrastiveSearchDecoderOnlyOutput",
-    ]
-
-try:
-    if not is_flax_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["flax_logits_process"] = [
-        "FlaxForcedBOSTokenLogitsProcessor",
-        "FlaxForcedEOSTokenLogitsProcessor",
-        "FlaxForceTokensLogitsProcessor",
-        "FlaxLogitsProcessor",
-        "FlaxLogitsProcessorList",
-        "FlaxLogitsWarper",
-        "FlaxMinLengthLogitsProcessor",
-        "FlaxSuppressTokensAtBeginLogitsProcessor",
-        "FlaxSuppressTokensLogitsProcessor",
-        "FlaxTemperatureLogitsWarper",
-        "FlaxTopKLogitsWarper",
-        "FlaxTopPLogitsWarper",
-        "FlaxWhisperTimeStampLogitsProcessor",
-    ]
-    _import_structure["flax_utils"] = [
-        "FlaxGenerationMixin",
-        "FlaxGreedySearchOutput",
-        "FlaxSampleOutput",
-        "FlaxBeamSearchOutput",
-    ]
-
-if TYPE_CHECKING:
-    from .configuration_utils import GenerationConfig
-    from .streamers import TextIteratorStreamer, TextStreamer
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
-        from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
-        from .logits_process import (
-            AlternatingCodebooksLogitsProcessor,
-            ClassifierFreeGuidanceLogitsProcessor,
-            EncoderNoRepeatNGramLogitsProcessor,
-            EncoderRepetitionPenaltyLogitsProcessor,
-            EpsilonLogitsWarper,
-            EtaLogitsWarper,
-            ExponentialDecayLengthPenalty,
-            ForcedBOSTokenLogitsProcessor,
-            ForcedEOSTokenLogitsProcessor,
-            ForceTokensLogitsProcessor,
-            HammingDiversityLogitsProcessor,
-            InfNanRemoveLogitsProcessor,
-            LogitNormalization,
-            LogitsProcessor,
-            LogitsProcessorList,
-            LogitsWarper,
-            MinLengthLogitsProcessor,
-            MinNewTokensLengthLogitsProcessor,
-            NoBadWordsLogitsProcessor,
-            NoRepeatNGramLogitsProcessor,
-            PrefixConstrainedLogitsProcessor,
-            RepetitionPenaltyLogitsProcessor,
-            SequenceBiasLogitsProcessor,
-            SuppressTokensAtBeginLogitsProcessor,
-            SuppressTokensLogitsProcessor,
-            TemperatureLogitsWarper,
-            TopKLogitsWarper,
-            TopPLogitsWarper,
-            TypicalLogitsWarper,
-            UnbatchedClassifierFreeGuidanceLogitsProcessor,
-            WhisperTimeStampLogitsProcessor,
-        )
-        from .stopping_criteria import (
-            MaxLengthCriteria,
-            MaxNewTokensCriteria,
-            MaxTimeCriteria,
-            StoppingCriteria,
-            StoppingCriteriaList,
-            validate_stopping_criteria,
-        )
-        from .utils import (
-            BeamSampleDecoderOnlyOutput,
-            BeamSampleEncoderDecoderOutput,
-            BeamSearchDecoderOnlyOutput,
-            BeamSearchEncoderDecoderOutput,
-            ContrastiveSearchDecoderOnlyOutput,
-            ContrastiveSearchEncoderDecoderOutput,
-            GenerationMixin,
-            GreedySearchDecoderOnlyOutput,
-            GreedySearchEncoderDecoderOutput,
-            SampleDecoderOnlyOutput,
-            SampleEncoderDecoderOutput,
-            top_k_top_p_filtering,
-        )
-
-    try:
-        if not is_tf_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .tf_logits_process import (
-            TFForcedBOSTokenLogitsProcessor,
-            TFForcedEOSTokenLogitsProcessor,
-            TFForceTokensLogitsProcessor,
-            TFLogitsProcessor,
-            TFLogitsProcessorList,
-            TFLogitsWarper,
-            TFMinLengthLogitsProcessor,
-            TFNoBadWordsLogitsProcessor,
-            TFNoRepeatNGramLogitsProcessor,
-            TFRepetitionPenaltyLogitsProcessor,
-            TFSuppressTokensAtBeginLogitsProcessor,
-            TFSuppressTokensLogitsProcessor,
-            TFTemperatureLogitsWarper,
-            TFTopKLogitsWarper,
-            TFTopPLogitsWarper,
-        )
-        from .tf_utils import (
-            TFBeamSampleDecoderOnlyOutput,
-            TFBeamSampleEncoderDecoderOutput,
-            TFBeamSearchDecoderOnlyOutput,
-            TFBeamSearchEncoderDecoderOutput,
-            TFContrastiveSearchDecoderOnlyOutput,
-            TFContrastiveSearchEncoderDecoderOutput,
-            TFGenerationMixin,
-            TFGreedySearchDecoderOnlyOutput,
-            TFGreedySearchEncoderDecoderOutput,
-            TFSampleDecoderOnlyOutput,
-            TFSampleEncoderDecoderOutput,
-            tf_top_k_top_p_filtering,
-        )
-
-    try:
-        if not is_flax_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .flax_logits_process import (
-            FlaxForcedBOSTokenLogitsProcessor,
-            FlaxForcedEOSTokenLogitsProcessor,
-            FlaxForceTokensLogitsProcessor,
-            FlaxLogitsProcessor,
-            FlaxLogitsProcessorList,
-            FlaxLogitsWarper,
-            FlaxMinLengthLogitsProcessor,
-            FlaxSuppressTokensAtBeginLogitsProcessor,
-            FlaxSuppressTokensLogitsProcessor,
-            FlaxTemperatureLogitsWarper,
-            FlaxTopKLogitsWarper,
-            FlaxTopPLogitsWarper,
-            FlaxWhisperTimeStampLogitsProcessor,
-        )
-        from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
-else:
-    import sys
-
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
diff --git a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/longt5/__init__.py b/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/longt5/__init__.py
deleted file mode 100644
index 93b9121c33f3932a86813cf5d47b102c503a86d8..0000000000000000000000000000000000000000
--- a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/longt5/__init__.py
+++ /dev/null
@@ -1,84 +0,0 @@
-# Copyright 2022 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_flax_available, is_torch_available
-
-
-_import_structure = {
-    "configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
-}
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_longt5"] = [
-        "LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST",
-        "LongT5EncoderModel",
-        "LongT5ForConditionalGeneration",
-        "LongT5Model",
-        "LongT5PreTrainedModel",
-    ]
-
-try:
-    if not is_flax_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_flax_longt5"] = [
-        "FlaxLongT5ForConditionalGeneration",
-        "FlaxLongT5Model",
-        "FlaxLongT5PreTrainedModel",
-    ]
-
-
-if TYPE_CHECKING:
-    from .configuration_longt5 import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongT5Config, LongT5OnnxConfig
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_longt5 import (
-            LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
-            LongT5EncoderModel,
-            LongT5ForConditionalGeneration,
-            LongT5Model,
-            LongT5PreTrainedModel,
-        )
-
-    try:
-        if not is_flax_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_flax_longt5 import (
-            FlaxLongT5ForConditionalGeneration,
-            FlaxLongT5Model,
-            FlaxLongT5PreTrainedModel,
-        )
-
-
-else:
-    import sys
-
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
diff --git a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mra/configuration_mra.py b/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mra/configuration_mra.py
deleted file mode 100644
index bc6aeebc907e718c21a68766a8686fb50d743903..0000000000000000000000000000000000000000
--- a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mra/configuration_mra.py
+++ /dev/null
@@ -1,137 +0,0 @@
-# coding=utf-8
-# Copyright 2023 The HuggingFace Inc. 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.
-""" MRA model configuration"""
-
-from ...configuration_utils import PretrainedConfig
-from ...utils import logging
-
-
-logger = logging.get_logger(__name__)
-
-MRA_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
-}
-
-
-class MraConfig(PretrainedConfig):
-    r"""
-    This is the configuration class to store the configuration of a [`MraModel`]. It is used to instantiate an MRA
-    model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
-    defaults will yield a similar configuration to that of the Mra
-    [uw-madison/mra-base-512-4](https://huggingface.co/uw-madison/mra-base-512-4) architecture.
-
-    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
-    documentation from [`PretrainedConfig`] for more information.
-
-
-    Args:
-        vocab_size (`int`, *optional*, defaults to 50265):
-            Vocabulary size of the Mra model. Defines the number of different tokens that can be represented by the
-            `inputs_ids` passed when calling [`MraModel`].
-        hidden_size (`int`, *optional*, defaults to 768):
-            Dimension of the encoder layers and the pooler layer.
-        num_hidden_layers (`int`, *optional*, defaults to 12):
-            Number of hidden layers in the Transformer encoder.
-        num_attention_heads (`int`, *optional*, defaults to 12):
-            Number of attention heads for each attention layer in the Transformer encoder.
-        intermediate_size (`int`, *optional*, defaults to 3072):
-            Dimension of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
-        hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`):
-            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
-            `"relu"`, `"selu"` and `"gelu_new"` are supported.
-        hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
-            The dropout probabilitiy for all fully connected layers in the embeddings, encoder, and pooler.
-        attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
-            The dropout ratio for the attention probabilities.
-        max_position_embeddings (`int`, *optional*, defaults to 512):
-            The maximum sequence length that this model might ever be used with. Typically set this to something large
-            just in case (e.g., 512 or 1024 or 2048).
-        type_vocab_size (`int`, *optional*, defaults to 1):
-            The vocabulary size of the `token_type_ids` passed when calling [`MraModel`].
-        initializer_range (`float`, *optional*, defaults to 0.02):
-            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
-        layer_norm_eps (`float`, *optional*, defaults to 1e-5):
-            The epsilon used by the layer normalization layers.
-        position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
-            Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`.
-        block_per_row (`int`, *optional*, defaults to 4):
-            Used to set the budget for the high resolution scale.
-        approx_mode (`str`, *optional*, defaults to `"full"`):
-            Controls whether both low and high resolution approximations are used. Set to `"full"` for both low and
-            high resolution and `"sparse"` for only low resolution.
-        initial_prior_first_n_blocks (`int`, *optional*, defaults to 0):
-            The initial number of blocks for which high resolution is used.
-        initial_prior_diagonal_n_blocks (`int`, *optional*, defaults to 0):
-            The number of diagonal blocks for which high resolution is used.
-
-    Example:
-
-    ```python
-    >>> from transformers import MraConfig, MraModel
-
-    >>> # Initializing a Mra uw-madison/mra-base-512-4 style configuration
-    >>> configuration = MraConfig()
-
-    >>> # Initializing a model (with random weights) from the uw-madison/mra-base-512-4 style configuration
-    >>> model = MraModel(configuration)
-
-    >>> # Accessing the model configuration
-    >>> configuration = model.config
-    ```"""
-    model_type = "mra"
-
-    def __init__(
-        self,
-        vocab_size=50265,
-        hidden_size=768,
-        num_hidden_layers=12,
-        num_attention_heads=12,
-        intermediate_size=3072,
-        hidden_act="gelu",
-        hidden_dropout_prob=0.1,
-        attention_probs_dropout_prob=0.1,
-        max_position_embeddings=512,
-        type_vocab_size=1,
-        initializer_range=0.02,
-        layer_norm_eps=1e-5,
-        position_embedding_type="absolute",
-        block_per_row=4,
-        approx_mode="full",
-        initial_prior_first_n_blocks=0,
-        initial_prior_diagonal_n_blocks=0,
-        pad_token_id=1,
-        bos_token_id=0,
-        eos_token_id=2,
-        **kwargs,
-    ):
-        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
-
-        self.vocab_size = vocab_size
-        self.max_position_embeddings = max_position_embeddings
-        self.hidden_size = hidden_size
-        self.num_hidden_layers = num_hidden_layers
-        self.num_attention_heads = num_attention_heads
-        self.intermediate_size = intermediate_size
-        self.hidden_act = hidden_act
-        self.hidden_dropout_prob = hidden_dropout_prob
-        self.attention_probs_dropout_prob = attention_probs_dropout_prob
-        self.initializer_range = initializer_range
-        self.type_vocab_size = type_vocab_size
-        self.layer_norm_eps = layer_norm_eps
-        self.position_embedding_type = position_embedding_type
-        self.block_per_row = block_per_row
-        self.approx_mode = approx_mode
-        self.initial_prior_first_n_blocks = initial_prior_first_n_blocks
-        self.initial_prior_diagonal_n_blocks = initial_prior_diagonal_n_blocks
diff --git a/spaces/yl12053/so-vits-4.1-Grass-Wonder/vdecoder/hifigan/nvSTFT.py b/spaces/yl12053/so-vits-4.1-Grass-Wonder/vdecoder/hifigan/nvSTFT.py
deleted file mode 100644
index 88597d62a505715091f9ba62d38bf0a85a31b95a..0000000000000000000000000000000000000000
--- a/spaces/yl12053/so-vits-4.1-Grass-Wonder/vdecoder/hifigan/nvSTFT.py
+++ /dev/null
@@ -1,111 +0,0 @@
-import math
-import os
-os.environ["LRU_CACHE_CAPACITY"] = "3"
-import random
-import torch
-import torch.utils.data
-import numpy as np
-import librosa
-from librosa.util import normalize
-from librosa.filters import mel as librosa_mel_fn
-from scipy.io.wavfile import read
-import soundfile as sf
-
-def load_wav_to_torch(full_path, target_sr=None, return_empty_on_exception=False):
-    sampling_rate = None
-    try:
-        data, sampling_rate = sf.read(full_path, always_2d=True)# than soundfile.
-    except Exception as ex:
-        print(f"'{full_path}' failed to load.\nException:")
-        print(ex)
-        if return_empty_on_exception:
-            return [], sampling_rate or target_sr or 32000
-        else:
-            raise Exception(ex)
-    
-    if len(data.shape) > 1:
-        data = data[:, 0]
-        assert len(data) > 2# check duration of audio file is > 2 samples (because otherwise the slice operation was on the wrong dimension)
-    
-    if np.issubdtype(data.dtype, np.integer): # if audio data is type int
-        max_mag = -np.iinfo(data.dtype).min # maximum magnitude = min possible value of intXX
-    else: # if audio data is type fp32
-        max_mag = max(np.amax(data), -np.amin(data))
-        max_mag = (2**31)+1 if max_mag > (2**15) else ((2**15)+1 if max_mag > 1.01 else 1.0) # data should be either 16-bit INT, 32-bit INT or [-1 to 1] float32
-    
-    data = torch.FloatTensor(data.astype(np.float32))/max_mag
-    
-    if (torch.isinf(data) | torch.isnan(data)).any() and return_empty_on_exception:# resample will crash with inf/NaN inputs. return_empty_on_exception will return empty arr instead of except
-        return [], sampling_rate or target_sr or 32000
-    if target_sr is not None and sampling_rate != target_sr:
-        data = torch.from_numpy(librosa.core.resample(data.numpy(), orig_sr=sampling_rate, target_sr=target_sr))
-        sampling_rate = target_sr
-    
-    return data, sampling_rate
-
-def dynamic_range_compression(x, C=1, clip_val=1e-5):
-    return np.log(np.clip(x, a_min=clip_val, a_max=None) * C)
-
-def dynamic_range_decompression(x, C=1):
-    return np.exp(x) / C
-
-def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
-    return torch.log(torch.clamp(x, min=clip_val) * C)
-
-def dynamic_range_decompression_torch(x, C=1):
-    return torch.exp(x) / C
-
-class STFT():
-    def __init__(self, sr=22050, n_mels=80, n_fft=1024, win_size=1024, hop_length=256, fmin=20, fmax=11025, clip_val=1e-5):
-        self.target_sr = sr
-        
-        self.n_mels     = n_mels
-        self.n_fft      = n_fft
-        self.win_size   = win_size
-        self.hop_length = hop_length
-        self.fmin     = fmin
-        self.fmax     = fmax
-        self.clip_val = clip_val
-        self.mel_basis = {}
-        self.hann_window = {}
-    
-    def get_mel(self, y, center=False):
-        sampling_rate = self.target_sr
-        n_mels     = self.n_mels
-        n_fft      = self.n_fft
-        win_size   = self.win_size
-        hop_length = self.hop_length
-        fmin       = self.fmin
-        fmax       = self.fmax
-        clip_val   = self.clip_val
-        
-        if torch.min(y) < -1.:
-            print('min value is ', torch.min(y))
-        if torch.max(y) > 1.:
-            print('max value is ', torch.max(y))
-        
-        if fmax not in self.mel_basis:
-            mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax)
-            self.mel_basis[str(fmax)+'_'+str(y.device)] = torch.from_numpy(mel).float().to(y.device)
-            self.hann_window[str(y.device)] = torch.hann_window(self.win_size).to(y.device)
-        
-        y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_length)/2), int((n_fft-hop_length)/2)), mode='reflect')
-        y = y.squeeze(1)
-        
-        spec = torch.stft(y, n_fft, hop_length=hop_length, win_length=win_size, window=self.hann_window[str(y.device)],
-                          center=center, pad_mode='reflect', normalized=False, onesided=True)
-        # print(111,spec)
-        spec = torch.sqrt(spec.pow(2).sum(-1)+(1e-9))
-        # print(222,spec)
-        spec = torch.matmul(self.mel_basis[str(fmax)+'_'+str(y.device)], spec)
-        # print(333,spec)
-        spec = dynamic_range_compression_torch(spec, clip_val=clip_val)
-        # print(444,spec)
-        return spec
-    
-    def __call__(self, audiopath):
-        audio, sr = load_wav_to_torch(audiopath, target_sr=self.target_sr)
-        spect = self.get_mel(audio.unsqueeze(0)).squeeze(0)
-        return spect
-
-stft = STFT()
diff --git a/spaces/yl12053/so-vits-4.1-Kitasan-Black/vencoder/ContentVec768L9_Onnx.py b/spaces/yl12053/so-vits-4.1-Kitasan-Black/vencoder/ContentVec768L9_Onnx.py
deleted file mode 100644
index 7cdac4cd93478d3ddddb4b76dd9d9ccc5d1af2d4..0000000000000000000000000000000000000000
--- a/spaces/yl12053/so-vits-4.1-Kitasan-Black/vencoder/ContentVec768L9_Onnx.py
+++ /dev/null
@@ -1,28 +0,0 @@
-from vencoder.encoder import SpeechEncoder
-import onnxruntime
-import torch
-
-class ContentVec768L9_Onnx(SpeechEncoder):
-    def __init__(self,vec_path = "pretrain/vec-768-layer-9.onnx",device=None):
-        print("load model(s) from {}".format(vec_path))
-        self.hidden_dim = 768
-        if device is None:
-            self.dev = torch.device("cpu")
-        else:
-            self.dev = torch.device(device)
-        if device == 'cpu' or device == torch.device("cpu") or device is None:
-            providers = ['CPUExecutionProvider']
-        elif device == 'cuda' or device == torch.device("cuda"):
-            providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
-        self.model = onnxruntime.InferenceSession(vec_path, providers=providers)
-
-    def encoder(self, wav):
-        feats = wav
-        if feats.dim() == 2:  # double channels
-          feats = feats.mean(-1)
-        assert feats.dim() == 1, feats.dim()
-        feats = feats.view(1, -1)
-        feats = feats.unsqueeze(0).cpu().detach().numpy()
-        onnx_input = {self.model.get_inputs()[0].name: feats}
-        logits = self.model.run(None, onnx_input)
-        return torch.tensor(logits[0]).transpose(1, 2).to(self.dev)
\ No newline at end of file
diff --git a/spaces/yl12053/so-vits-4.1-Matikanefukukitaru/preprocess_hubert_f0.py b/spaces/yl12053/so-vits-4.1-Matikanefukukitaru/preprocess_hubert_f0.py
deleted file mode 100644
index 3871d8d78ff2ca1b847c6b6fa40e0d3d68545007..0000000000000000000000000000000000000000
--- a/spaces/yl12053/so-vits-4.1-Matikanefukukitaru/preprocess_hubert_f0.py
+++ /dev/null
@@ -1,159 +0,0 @@
-import math
-import multiprocessing
-import os
-import argparse
-from random import shuffle
-import random
-
-import torch
-from glob import glob
-from tqdm import tqdm
-from modules.mel_processing import spectrogram_torch
-import json
-
-import utils
-import logging
-logging.getLogger("numba").setLevel(logging.WARNING)
-logging.getLogger("matplotlib").setLevel(logging.WARNING)
-
-import diffusion.logger.utils as du 
-from diffusion.vocoder import Vocoder
-
-import librosa
-import numpy as np
-
-hps = utils.get_hparams_from_file("configs/config.json")
-dconfig = du.load_config("configs/diffusion.yaml")
-sampling_rate = hps.data.sampling_rate
-hop_length = hps.data.hop_length
-speech_encoder = hps["model"]["speech_encoder"]
-
-
-def process_one(filename, hmodel,f0p,diff=False,mel_extractor=None):
-    # print(filename)
-    wav, sr = librosa.load(filename, sr=sampling_rate)
-    audio_norm = torch.FloatTensor(wav)
-    audio_norm = audio_norm.unsqueeze(0)
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-    soft_path = filename + ".soft.pt"
-    if not os.path.exists(soft_path):
-        wav16k = librosa.resample(wav, orig_sr=sampling_rate, target_sr=16000)
-        wav16k = torch.from_numpy(wav16k).to(device)
-        c = hmodel.encoder(wav16k)
-        torch.save(c.cpu(), soft_path)
-        
-    f0_path = filename + ".f0.npy"
-    if not os.path.exists(f0_path):
-        f0_predictor = utils.get_f0_predictor(f0p,sampling_rate=sampling_rate, hop_length=hop_length,device=None,threshold=0.05)
-        f0,uv = f0_predictor.compute_f0_uv(
-            wav
-        )
-        np.save(f0_path, np.asanyarray((f0,uv),dtype=object))
-    
-    
-    spec_path = filename.replace(".wav", ".spec.pt")
-    if not os.path.exists(spec_path):
-        # Process spectrogram
-        # The following code can't be replaced by torch.FloatTensor(wav)
-        # because load_wav_to_torch return a tensor that need to be normalized
-
-        if sr != hps.data.sampling_rate:
-            raise ValueError(
-                "{} SR doesn't match target {} SR".format(
-                    sr, hps.data.sampling_rate
-                )
-            )
-        
-        #audio_norm = audio / hps.data.max_wav_value
-        
-        spec = spectrogram_torch(
-            audio_norm,
-            hps.data.filter_length,
-            hps.data.sampling_rate,
-            hps.data.hop_length,
-            hps.data.win_length,
-            center=False,
-        )
-        spec = torch.squeeze(spec, 0)
-        torch.save(spec, spec_path)
-
-    if diff or hps.model.vol_embedding:
-        volume_path = filename + ".vol.npy"
-        volume_extractor = utils.Volume_Extractor(hop_length)
-        if not os.path.exists(volume_path):
-            volume = volume_extractor.extract(audio_norm)
-            np.save(volume_path, volume.to('cpu').numpy())
-
-    if diff:
-        mel_path = filename + ".mel.npy"
-        if not os.path.exists(mel_path) and mel_extractor is not None:
-            mel_t = mel_extractor.extract(audio_norm.to(device), sampling_rate)
-            mel = mel_t.squeeze().to('cpu').numpy()
-            np.save(mel_path, mel)
-        aug_mel_path = filename + ".aug_mel.npy"
-        aug_vol_path = filename + ".aug_vol.npy"
-        max_amp = float(torch.max(torch.abs(audio_norm))) + 1e-5
-        max_shift = min(1, np.log10(1/max_amp))
-        log10_vol_shift = random.uniform(-1, max_shift)
-        keyshift = random.uniform(-5, 5)
-        if mel_extractor is not None:
-            aug_mel_t = mel_extractor.extract(audio_norm * (10 ** log10_vol_shift), sampling_rate, keyshift = keyshift)
-        aug_mel = aug_mel_t.squeeze().to('cpu').numpy()
-        aug_vol = volume_extractor.extract(audio_norm * (10 ** log10_vol_shift))
-        if not os.path.exists(aug_mel_path):
-            np.save(aug_mel_path,np.asanyarray((aug_mel,keyshift),dtype=object))
-        if not os.path.exists(aug_vol_path):
-            np.save(aug_vol_path,aug_vol.to('cpu').numpy())
-
-
-def process_batch(filenames,f0p,diff=False,mel_extractor=None):
-    print("Loading speech encoder for content...")
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    hmodel = utils.get_speech_encoder(speech_encoder,device=device)
-    print("Loaded speech encoder.")
-    for filename in tqdm(filenames):
-        process_one(filename, hmodel,f0p,diff,mel_extractor)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--in_dir", type=str, default="dataset/44k", help="path to input dir"
-    )
-    parser.add_argument( 
-        '--use_diff',action='store_true', help='Whether to use the diffusion model'
-    )
-    parser.add_argument( 
-        '--f0_predictor', type=str, default="dio", help='Select F0 predictor, can select crepe,pm,dio,harvest, default pm(note: crepe is original F0 using mean filter)'
-    )
-    parser.add_argument( 
-        '--num_processes', type=int, default=1, help='You are advised to set the number of processes to the same as the number of CPU cores'
-    )
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-    args = parser.parse_args()
-    f0p = args.f0_predictor
-    print(speech_encoder)
-    print(f0p)
-    if args.use_diff:
-        print("use_diff")
-        print("Loading Mel Extractor...")
-        mel_extractor = Vocoder(dconfig.vocoder.type, dconfig.vocoder.ckpt, device = device)
-        print("Loaded Mel Extractor.")
-    else:
-        mel_extractor = None
-    filenames = glob(f"{args.in_dir}/*/*.wav", recursive=True)  # [:10]
-    shuffle(filenames)
-    multiprocessing.set_start_method("spawn", force=True)
-    
-    num_processes = args.num_processes
-    chunk_size = int(math.ceil(len(filenames) / num_processes))
-    chunks = [
-        filenames[i : i + chunk_size] for i in range(0, len(filenames), chunk_size)
-    ]
-    print([len(c) for c in chunks])
-    processes = [
-        multiprocessing.Process(target=process_batch, args=(chunk,f0p,args.use_diff,mel_extractor)) for chunk in chunks
-    ]
-    for p in processes:
-        p.start()
diff --git a/spaces/ynhe/AskAnything/models/grit_src/third_party/CenterNet2/projects/CenterNet2/centernet2_docs/MODEL_ZOO.md b/spaces/ynhe/AskAnything/models/grit_src/third_party/CenterNet2/projects/CenterNet2/centernet2_docs/MODEL_ZOO.md
deleted file mode 100644
index 7a2a92b60d0ebf8f6444f24c3bd74b753c80c57f..0000000000000000000000000000000000000000
--- a/spaces/ynhe/AskAnything/models/grit_src/third_party/CenterNet2/projects/CenterNet2/centernet2_docs/MODEL_ZOO.md
+++ /dev/null
@@ -1,73 +0,0 @@
-# MODEL_ZOO
-
-### Common settings and notes
-
-- Multiscale training is used by default in all models. The results are all reported using single-scale testing. 
-- We report runtime on our local workstation with a TitanXp GPU and a Titan RTX GPU.
-- All models are trained on 8-GPU servers by default. The 1280 models are trained on 24G GPUs. Reducing the batchsize with the linear learning rate rule should be fine.
-- All models can be downloaded directly from [Google drive](https://drive.google.com/drive/folders/1eae1cTX8tvIaCeof36sBgxrXEXALYlf-?usp=sharing).
-
-
-## COCO
-
-### CenterNet
-
-| Model                                     | val mAP | FPS (Titan Xp/ Titan RTX) | links     |
-|-------------------------------------------|---------|---------|-----------|
-| CenterNet-S4_DLA_8x                       |  42.5   | 50 / 71 |[config](../configs/CenterNet-S4_DLA_8x.yaml)/[model](https://drive.google.com/file/d/1lNBhVHnZAEBRD66MFaHjm5Ij6Z4KYrJq/view?usp=sharing)|
-| CenterNet-FPN_R50_1x                      |  40.2   | 20 / 24 |[config](../configs/CenterNet-FPN_R50_1x.yaml)/[model](https://drive.google.com/file/d/1rVG1YTthMXvutC6jr9KoE2DthT5-jhGj/view?usp=sharing)|
-
-#### Note
-
-- `CenterNet-S4_DLA_8x` is a re-implemented version of the original CenterNet (stride 4), with several changes, including
-  - Using top-left-right-bottom box encoding and GIoU Loss; adding regression loss to the center 3x3 region.
-  - Adding more positive pixels for the heatmap loss whose regression loss is small and is within the center3x3 region.
-  - Using more heavy crop augmentation (EfficientDet-style crop ratio 0.1-2), and removing color augmentations.
-  - Using standard NMS instead of max pooling.
-  - Using RetinaNet-style optimizer (SGD), learning rate rule (0.01 for each batch size 16), and schedule (8x12 epochs).
-- `CenterNet-FPN_R50_1x` is a (new) FPN version of CenterNet. It includes the changes above, and assigns objects to FPN levels based on a fixed size range. The model is trained with standard short edge 640-800 multi-scale training with 12 epochs (1x).
-
-
-### CenterNet2
-
-| Model                                     | val mAP | FPS (Titan Xp/ Titan RTX) | links     |
-|-------------------------------------------|---------|---------|-----------|
-| CenterNet2-F_R50_1x                       |   41.7  | 22 / 27  |[config](../configs/CenterNet2-F_R50_1x.yaml)/[model](X)|
-| CenterNet2_R50_1x                         |  42.9   | 18 / 24 |[config](../configs/CenterNet2_R50_1x.yaml)/[model](https://drive.google.com/file/d/1Osu1J_sskt_1FaGdfJKa4vd2N71TWS9W/view?usp=sharing)|
-| CenterNet2_X101-DCN_2x                    |  49.9   | 6 / 8  |[config](../configs/CenterNet2_X101-DCN_2x.yaml)/[model](https://drive.google.com/file/d/1IHgpUHVJWpvMuFUUetgKWsw27pRNN2oK/view?usp=sharing)|
-| CenterNet2_DLA-BiFPN-P3_4x                |  43.8   | 40 / 50|[config](../configs/CenterNet2_DLA-BiFPN-P3_4x.yaml)/[model](https://drive.google.com/file/d/12GUNlDW9RmOs40UEMSiiUsk5QK_lpGsE/view?usp=sharing)|
-| CenterNet2_DLA-BiFPN-P3_24x               |  45.6   | 40 / 50  |[config](../configs/CenterNet2_DLA-BiFPN-P3_24x.yaml)/[model](https://drive.google.com/file/d/15ZES1ySxubDPzKsHPA7pYg8o_Vwmf-Mb/view?usp=sharing)|
-| CenterNet2_R2-101-DCN_896_4x              |  51.2   | 9 / 13 |[config](../configs/CenterNet2_R2-101-DCN_896_4x.yaml)/[model](https://drive.google.com/file/d/1S7_GE8ZDQBWuLEfKHkxzeF3KBsxsbABg/view?usp=sharing)|
-| CenterNet2_R2-101-DCN-BiFPN_1280_4x       |  52.9   | 6 / 8 |[config](../configs/CenterNet2_R2-101-DCN-BiFPN_1280_4x.yaml)/[model](https://drive.google.com/file/d/14EBHNMagBCNTQjOXcHoZwLYIi2lFIm7F/view?usp=sharing)|
-| CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST |  56.1   | 3 / 5 |[config](../configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml)/[model](https://drive.google.com/file/d/11ww9VlOi_nhpdsU_vBAecSxBU0dR_JzW/view?usp=sharing)|
-| CenterNet2_DLA-BiFPN-P5_640_24x_ST        |  49.2   | 33 / 38 |[config](../configs/CenterNet2_DLA-BiFPN-P5_640_24x_ST.yaml)/[model](https://drive.google.com/file/d/1qsHp2HrM1u8WrtBzF5S0oCoLMz-B40wk/view?usp=sharing)|
-
-#### Note
-
-- `CenterNet2-F_R50_1x` uses Faster RCNN as the second stage. All other CenterNet2 models use Cascade RCNN as the second stage.
-- `CenterNet2_DLA-BiFPN-P3_4x` follows the same training setting as [realtime-FCOS](https://github.com/aim-uofa/AdelaiDet/blob/master/configs/FCOS-Detection/README.md).
-- `CenterNet2_DLA-BiFPN-P3_24x` is trained by repeating the `4x` schedule (starting from learning rate 0.01) 6 times.
-- R2 means [Res2Net](https://github.com/Res2Net/Res2Net-detectron2) backbone. To train Res2Net models, you need to download the ImageNet pre-trained weight [here](https://github.com/Res2Net/Res2Net-detectron2) and place it in `output/r2_101.pkl`.
-- The last 4 models in the table are trained with the EfficientDet-style resize-and-crop augmentation, instead of the default random resizing short edge in detectron2. We found this trains faster (per-iteration) and gives better performance under a long schedule.
-- `_ST` means using [self-training](https://arxiv.org/abs/2006.06882) using pseudo-labels produced by [Scaled-YOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4) on COCO unlabeled images, with a hard score threshold 0.5. Our processed pseudo-labels can be downloaded [here](https://drive.google.com/file/d/1LMBjtHhLp6dYf6MjwEQmzCLWQLkmWPpw/view?usp=sharing).
-- `CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST` finetunes from `CenterNet2_R2-101-DCN-BiFPN_1280_4x` for an additional `4x` schedule with the self-training data. It is trained under `1280x1280` but tested under `1560x1560`.
-
-## LVIS v1
-
-| Model                                     |  val mAP box | links     |
-|-------------------------------------------|--------------|-----------|
-| LVIS_CenterNet2_R50_1x                    |  26.5        |[config](../configs/LVIS_CenterNet2_R50_1x.yaml)/[model](https://drive.google.com/file/d/1gT9e-tNw8uzEBaCadQuoOOP2TEYa4kKP/view?usp=sharing)|
-| LVIS_CenterNet2_R50_Fed_1x            |  28.3        |[config](../configs/LVIS_CenterNet2_R50_Fed_1x.yaml)/[model](https://drive.google.com/file/d/1a9UjheMCKax0qAKEwPVpq2ZHN6vpqJv8/view?usp=sharing)|
-
-- The models are trained with repeat-factor sampling.
-- `LVIS_CenterNet2_R50_Fed_1x` is CenterNet2 with our federated loss. Check our Appendix D of our [paper](https://arxiv.org/abs/2103.07461) or our [technical report at LVIS challenge](https://www.lvisdataset.org/assets/challenge_reports/2020/CenterNet2.pdf) for references.
-
-## Objects365
-
-| Model                                     |  val mAP| links     |
-|-------------------------------------------|---------|-----------|
-| O365_CenterNet2_R50_1x                    |  22.6   |[config](../configs/O365_CenterNet2_R50_1x.yaml)/[model](https://drive.google.com/file/d/18fG6xGchAlpNp5sx8RAtwadGkS-gdIBU/view?usp=sharing)|
-
-#### Note
-- Objects365 dataset can be downloaded [here](https://www.objects365.org/overview.html).
-- The model is trained with class-aware sampling.
diff --git a/spaces/yooch/yooch/Dockerfile b/spaces/yooch/yooch/Dockerfile
deleted file mode 100644
index 8cbd335b09b1d1975bfd83a053b5fcaf398147ea..0000000000000000000000000000000000000000
--- a/spaces/yooch/yooch/Dockerfile
+++ /dev/null
@@ -1,14 +0,0 @@
-FROM python:3.9 as builder
-RUN apt-get update && apt-get install -y build-essential
-COPY requirements.txt .
-RUN pip install --user -r requirements.txt
-
-FROM python:3.9
-MAINTAINER iskoldt
-COPY --from=builder /root/.local /root/.local
-ENV PATH=/root/.local/bin:$PATH
-COPY . /app
-WORKDIR /app
-ENV my_api_key empty
-ENV dockerrun yes
-CMD ["python3", "-u", "ChuanhuChatbot.py", "2>&1", "|", "tee", "/var/log/application.log"]
diff --git a/spaces/ysharma/WizardCoder34b/style.css b/spaces/ysharma/WizardCoder34b/style.css
deleted file mode 100644
index 303c3d7ef3b06c42b211797cd2d5af9800589092..0000000000000000000000000000000000000000
--- a/spaces/ysharma/WizardCoder34b/style.css
+++ /dev/null
@@ -1,16 +0,0 @@
-h1 {
-  text-align: center;
-}
-
-#duplicate-button {
-  margin: auto;
-  color: white;
-  background: #1565c0;
-  border-radius: 100vh;
-}
-
-#component-0 {
-  max-width: 900px;
-  margin: auto;
-  padding-top: 1.5rem;
-}
diff --git a/spaces/yuan1615/EmpathyVC/modules.py b/spaces/yuan1615/EmpathyVC/modules.py
deleted file mode 100644
index 3cf5919fb556cfd09c864b6a45e77c09d8710f7b..0000000000000000000000000000000000000000
--- a/spaces/yuan1615/EmpathyVC/modules.py
+++ /dev/null
@@ -1,389 +0,0 @@
-import copy
-import math
-import numpy as np
-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
-
-
-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/yunfei0710/gpt-academic/request_llm/bridge_chatglm.py b/spaces/yunfei0710/gpt-academic/request_llm/bridge_chatglm.py
deleted file mode 100644
index deaacd276cc53937bd68fd6e579e737375ef3582..0000000000000000000000000000000000000000
--- a/spaces/yunfei0710/gpt-academic/request_llm/bridge_chatglm.py
+++ /dev/null
@@ -1,161 +0,0 @@
-
-from transformers import AutoModel, AutoTokenizer
-import time
-import threading
-import importlib
-from toolbox import update_ui, get_conf
-from multiprocessing import Process, Pipe
-
-load_message = "ChatGLM尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，ChatGLM消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
-
-#################################################################################
-class GetGLMHandle(Process):
-    def __init__(self):
-        super().__init__(daemon=True)
-        self.parent, self.child = Pipe()
-        self.chatglm_model = None
-        self.chatglm_tokenizer = None
-        self.info = ""
-        self.success = True
-        self.check_dependency()
-        self.start()
-        self.threadLock = threading.Lock()
-        
-    def check_dependency(self):
-        try:
-            import sentencepiece
-            self.info = "依赖检测通过"
-            self.success = True
-        except:
-            self.info = "缺少ChatGLM的依赖，如果要使用ChatGLM，除了基础的pip依赖以外，您还需要运行`pip install -r request_llm/requirements_chatglm.txt`安装ChatGLM的依赖。"
-            self.success = False
-
-    def ready(self):
-        return self.chatglm_model is not None
-
-    def run(self):
-        # 子进程执行
-        # 第一次运行，加载参数
-        retry = 0
-        while True:
-            try:
-                if self.chatglm_model is None:
-                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
-                    device, = get_conf('LOCAL_MODEL_DEVICE')
-                    if device=='cpu':
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).float()
-                    else:
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).half().cuda()
-                    self.chatglm_model = self.chatglm_model.eval()
-                    break
-                else:
-                    break
-            except:
-                retry += 1
-                if retry > 3: 
-                    self.child.send('[Local Message] Call ChatGLM fail 不能正常加载ChatGLM的参数。')
-                    raise RuntimeError("不能正常加载ChatGLM的参数！")
-
-        while True:
-            # 进入任务等待状态
-            kwargs = self.child.recv()
-            # 收到消息，开始请求
-            try:
-                for response, history in self.chatglm_model.stream_chat(self.chatglm_tokenizer, **kwargs):
-                    self.child.send(response)
-                    # # 中途接收可能的终止指令（如果有的话）
-                    # if self.child.poll(): 
-                    #     command = self.child.recv()
-                    #     if command == '[Terminate]': break
-            except:
-                from toolbox import trimmed_format_exc
-                self.child.send('[Local Message] Call ChatGLM fail.' + '\n```\n' + trimmed_format_exc() + '\n```\n')
-            # 请求处理结束，开始下一个循环
-            self.child.send('[Finish]')
-
-    def stream_chat(self, **kwargs):
-        # 主进程执行
-        self.threadLock.acquire()
-        self.parent.send(kwargs)
-        while True:
-            res = self.parent.recv()
-            if res != '[Finish]':
-                yield res
-            else:
-                break
-        self.threadLock.release()
-    
-global glm_handle
-glm_handle = None
-#################################################################################
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
-    """
-        多线程方法
-        函数的说明请见 request_llm/bridge_all.py
-    """
-    global glm_handle
-    if glm_handle is None:
-        glm_handle = GetGLMHandle()
-        if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + glm_handle.info
-        if not glm_handle.success: 
-            error = glm_handle.info
-            glm_handle = None
-            raise RuntimeError(error)
-
-    # chatglm 没有 sys_prompt 接口，因此把prompt加入 history
-    history_feedin = []
-    history_feedin.append(["What can I do?", sys_prompt])
-    for i in range(len(history)//2):
-        history_feedin.append([history[2*i], history[2*i+1]] )
-
-    watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
-    response = ""
-    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
-        if len(observe_window) >= 1:  observe_window[0] = response
-        if len(observe_window) >= 2:  
-            if (time.time()-observe_window[1]) > watch_dog_patience:
-                raise RuntimeError("程序终止。")
-    return response
-
-
-
-def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
-    """
-        单线程方法
-        函数的说明请见 request_llm/bridge_all.py
-    """
-    chatbot.append((inputs, ""))
-
-    global glm_handle
-    if glm_handle is None:
-        glm_handle = GetGLMHandle()
-        chatbot[-1] = (inputs, load_message + "\n\n" + glm_handle.info)
-        yield from update_ui(chatbot=chatbot, history=[])
-        if not glm_handle.success: 
-            glm_handle = None
-            return
-
-    if additional_fn is not None:
-        import core_functional
-        importlib.reload(core_functional)    # 热更新prompt
-        core_functional = core_functional.get_core_functions()
-        if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
-        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
-
-    # 处理历史信息
-    history_feedin = []
-    history_feedin.append(["What can I do?", system_prompt] )
-    for i in range(len(history)//2):
-        history_feedin.append([history[2*i], history[2*i+1]] )
-
-    # 开始接收chatglm的回复
-    response = "[Local Message]: 等待ChatGLM响应中 ..."
-    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
-        chatbot[-1] = (inputs, response)
-        yield from update_ui(chatbot=chatbot, history=history)
-
-    # 总结输出
-    if response == "[Local Message]: 等待ChatGLM响应中 ...":
-        response = "[Local Message]: ChatGLM响应异常 ..."
-    history.extend([inputs, response])
-    yield from update_ui(chatbot=chatbot, history=history)
diff --git a/spaces/yuntian-deng/ChatGPT4/README.md b/spaces/yuntian-deng/ChatGPT4/README.md
deleted file mode 100644
index 7938de14e5355209aaae713f289ca469181bbb17..0000000000000000000000000000000000000000
--- a/spaces/yuntian-deng/ChatGPT4/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Chat-with-GPT4
-emoji: 🚀
-colorFrom: red
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: mit
-duplicated_from: ysharma/ChatGPT4
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/zhang-wei-jian/docker/node_modules/braces/lib/utils.js b/spaces/zhang-wei-jian/docker/node_modules/braces/lib/utils.js
deleted file mode 100644
index e3551a6749166fbe1a13ac2814ba0afde9d1b104..0000000000000000000000000000000000000000
--- a/spaces/zhang-wei-jian/docker/node_modules/braces/lib/utils.js
+++ /dev/null
@@ -1,112 +0,0 @@
-'use strict';
-
-exports.isInteger = num => {
-  if (typeof num === 'number') {
-    return Number.isInteger(num);
-  }
-  if (typeof num === 'string' && num.trim() !== '') {
-    return Number.isInteger(Number(num));
-  }
-  return false;
-};
-
-/**
- * Find a node of the given type
- */
-
-exports.find = (node, type) => node.nodes.find(node => node.type === type);
-
-/**
- * Find a node of the given type
- */
-
-exports.exceedsLimit = (min, max, step = 1, limit) => {
-  if (limit === false) return false;
-  if (!exports.isInteger(min) || !exports.isInteger(max)) return false;
-  return ((Number(max) - Number(min)) / Number(step)) >= limit;
-};
-
-/**
- * Escape the given node with '\\' before node.value
- */
-
-exports.escapeNode = (block, n = 0, type) => {
-  let node = block.nodes[n];
-  if (!node) return;
-
-  if ((type && node.type === type) || node.type === 'open' || node.type === 'close') {
-    if (node.escaped !== true) {
-      node.value = '\\' + node.value;
-      node.escaped = true;
-    }
-  }
-};
-
-/**
- * Returns true if the given brace node should be enclosed in literal braces
- */
-
-exports.encloseBrace = node => {
-  if (node.type !== 'brace') return false;
-  if ((node.commas >> 0 + node.ranges >> 0) === 0) {
-    node.invalid = true;
-    return true;
-  }
-  return false;
-};
-
-/**
- * Returns true if a brace node is invalid.
- */
-
-exports.isInvalidBrace = block => {
-  if (block.type !== 'brace') return false;
-  if (block.invalid === true || block.dollar) return true;
-  if ((block.commas >> 0 + block.ranges >> 0) === 0) {
-    block.invalid = true;
-    return true;
-  }
-  if (block.open !== true || block.close !== true) {
-    block.invalid = true;
-    return true;
-  }
-  return false;
-};
-
-/**
- * Returns true if a node is an open or close node
- */
-
-exports.isOpenOrClose = node => {
-  if (node.type === 'open' || node.type === 'close') {
-    return true;
-  }
-  return node.open === true || node.close === true;
-};
-
-/**
- * Reduce an array of text nodes.
- */
-
-exports.reduce = nodes => nodes.reduce((acc, node) => {
-  if (node.type === 'text') acc.push(node.value);
-  if (node.type === 'range') node.type = 'text';
-  return acc;
-}, []);
-
-/**
- * Flatten an array
- */
-
-exports.flatten = (...args) => {
-  const result = [];
-  const flat = arr => {
-    for (let i = 0; i < arr.length; i++) {
-      let ele = arr[i];
-      Array.isArray(ele) ? flat(ele, result) : ele !== void 0 && result.push(ele);
-    }
-    return result;
-  };
-  flat(args);
-  return result;
-};
diff --git a/spaces/zhang-wei-jian/docker/node_modules/fsevents/fsevents.d.ts b/spaces/zhang-wei-jian/docker/node_modules/fsevents/fsevents.d.ts
deleted file mode 100644
index 2723c048a80df296ecc13eff5d96549f572a7383..0000000000000000000000000000000000000000
--- a/spaces/zhang-wei-jian/docker/node_modules/fsevents/fsevents.d.ts
+++ /dev/null
@@ -1,46 +0,0 @@
-declare type Event = "created" | "cloned" | "modified" | "deleted" | "moved" | "root-changed" | "unknown";
-declare type Type = "file" | "directory" | "symlink";
-declare type FileChanges = {
-  inode: boolean;
-  finder: boolean;
-  access: boolean;
-  xattrs: boolean;
-};
-declare type Info = {
-  event: Event;
-  path: string;
-  type: Type;
-  changes: FileChanges;
-  flags: number;
-};
-declare type WatchHandler = (path: string, flags: number, id: string) => void;
-export declare function watch(path: string, handler: WatchHandler): () => Promise<void>;
-export declare function watch(path: string, since: number, handler: WatchHandler): () => Promise<void>;
-export declare function getInfo(path: string, flags: number): Info;
-export declare const constants: {
-  None: 0x00000000;
-  MustScanSubDirs: 0x00000001;
-  UserDropped: 0x00000002;
-  KernelDropped: 0x00000004;
-  EventIdsWrapped: 0x00000008;
-  HistoryDone: 0x00000010;
-  RootChanged: 0x00000020;
-  Mount: 0x00000040;
-  Unmount: 0x00000080;
-  ItemCreated: 0x00000100;
-  ItemRemoved: 0x00000200;
-  ItemInodeMetaMod: 0x00000400;
-  ItemRenamed: 0x00000800;
-  ItemModified: 0x00001000;
-  ItemFinderInfoMod: 0x00002000;
-  ItemChangeOwner: 0x00004000;
-  ItemXattrMod: 0x00008000;
-  ItemIsFile: 0x00010000;
-  ItemIsDir: 0x00020000;
-  ItemIsSymlink: 0x00040000;
-  ItemIsHardlink: 0x00100000;
-  ItemIsLastHardlink: 0x00200000;
-  OwnEvent: 0x00080000;
-  ItemCloned: 0x00400000;
-};
-export {};
diff --git a/spaces/zhang-wei-jian/docker/node_modules/keygrip/index.js b/spaces/zhang-wei-jian/docker/node_modules/keygrip/index.js
deleted file mode 100644
index dbdb1e74e586dbfd043ded4467cf9efd4c7162b2..0000000000000000000000000000000000000000
--- a/spaces/zhang-wei-jian/docker/node_modules/keygrip/index.js
+++ /dev/null
@@ -1,51 +0,0 @@
-/*!
- * keygrip
- * Copyright(c) 2011-2014 Jed Schmidt
- * MIT Licensed
- */
-
-'use strict'
-
-var compare = require('tsscmp')
-var crypto = require("crypto")
-  
-function Keygrip(keys, algorithm, encoding) {
-  if (!algorithm) algorithm = "sha1";
-  if (!encoding) encoding = "base64";
-  if (!(this instanceof Keygrip)) return new Keygrip(keys, algorithm, encoding)
-
-  if (!keys || !(0 in keys)) {
-    throw new Error("Keys must be provided.")
-  }
-
-  function sign(data, key) {
-    return crypto
-      .createHmac(algorithm, key)
-      .update(data).digest(encoding)
-      .replace(/\/|\+|=/g, function(x) {
-        return ({ "/": "_", "+": "-", "=": "" })[x]
-      })
-  }
-
-  this.sign = function(data){ return sign(data, keys[0]) }
-
-  this.verify = function(data, digest) {
-    return this.index(data, digest) > -1
-  }
-
-  this.index = function(data, digest) {
-    for (var i = 0, l = keys.length; i < l; i++) {
-      if (compare(digest, sign(data, keys[i]))) {
-        return i
-      }
-    }
-
-    return -1
-  }
-}
-
-Keygrip.sign = Keygrip.verify = Keygrip.index = function() {
-  throw new Error("Usage: require('keygrip')(<array-of-keys>)")
-}
-
-module.exports = Keygrip
diff --git a/spaces/zhangyd/bingo/next.config.js b/spaces/zhangyd/bingo/next.config.js
deleted file mode 100644
index 0e6ccd7fbc91d0459eaaff3e968ce0556789c605..0000000000000000000000000000000000000000
--- a/spaces/zhangyd/bingo/next.config.js
+++ /dev/null
@@ -1,38 +0,0 @@
-/** @type {import('next').NextConfig} */
-const nextConfig = {
-  // output: 'export',
-  // assetPrefix: '.',
-  webpack: (config, { isServer }) => {
-    if (!isServer) {
-      config.resolve = {
-        ...config.resolve,
-        fallback: {
-          'bufferutil': false,
-          'utf-8-validate': false,
-          http: false,
-          https: false,
-          stream: false,
-          // fixes proxy-agent dependencies
-          net: false,
-          dns: false,
-          tls: false,
-          assert: false,
-          // fixes next-i18next dependencies
-          path: false,
-          fs: false,
-          // fixes mapbox dependencies
-          events: false,
-          // fixes sentry dependencies
-          process: false
-        }
-      };
-    }
-    config.module.exprContextCritical = false;
-
-    return config;
-  },
-}
-
-module.exports = (...args) => {
-  return nextConfig
-}
diff --git a/spaces/zhigangjiang/3D-Room-Layout-Estimation_LGT-Net/README.md b/spaces/zhigangjiang/3D-Room-Layout-Estimation_LGT-Net/README.md
deleted file mode 100644
index d9fc5d5e0e333c063241077a57002162bfc449e3..0000000000000000000000000000000000000000
--- a/spaces/zhigangjiang/3D-Room-Layout-Estimation_LGT-Net/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: 3D Room Layout Estimation LGT-Net
-emoji: 🏠
-colorFrom: indigo
-colorTo: purple
-sdk: gradio
-sdk_version: 3.0.5
-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/zomehwh/bert_vits2/README.md b/spaces/zomehwh/bert_vits2/README.md
deleted file mode 100644
index 9cb4ccb8a3fd0bd7309f0de18dabf1608009f548..0000000000000000000000000000000000000000
--- a/spaces/zomehwh/bert_vits2/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Bert Vits2 JP
-emoji: 📊
-colorFrom: red
-colorTo: green
-sdk: gradio
-sdk_version: 3.47.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/zomehwh/sovits-rudolf/vdecoder/__init__.py b/spaces/zomehwh/sovits-rudolf/vdecoder/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/zomehwh/vits-uma-genshin-honkai/attentions.py b/spaces/zomehwh/vits-uma-genshin-honkai/attentions.py
deleted file mode 100644
index 86bc73b5fe98cc7b443e9078553920346c996707..0000000000000000000000000000000000000000
--- a/spaces/zomehwh/vits-uma-genshin-honkai/attentions.py
+++ /dev/null
@@ -1,300 +0,0 @@
-import math
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import commons
-from modules import LayerNorm
-   
-
-class Encoder(nn.Module):
-  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4, **kwargs):
-    super().__init__()
-    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.window_size = window_size
-
-    self.drop = nn.Dropout(p_dropout)
-    self.attn_layers = nn.ModuleList()
-    self.norm_layers_1 = nn.ModuleList()
-    self.ffn_layers = nn.ModuleList()
-    self.norm_layers_2 = nn.ModuleList()
-    for i in range(self.n_layers):
-      self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size))
-      self.norm_layers_1.append(LayerNorm(hidden_channels))
-      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout))
-      self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-  def forward(self, x, x_mask):
-    attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-    x = x * x_mask
-    for i in range(self.n_layers):
-      y = self.attn_layers[i](x, x, attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_1[i](x + y)
-
-      y = self.ffn_layers[i](x, x_mask)
-      y = self.drop(y)
-      x = self.norm_layers_2[i](x + y)
-    x = x * x_mask
-    return x
-
-
-class Decoder(nn.Module):
-  def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs):
-    super().__init__()
-    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.proximal_bias = proximal_bias
-    self.proximal_init = proximal_init
-
-    self.drop = nn.Dropout(p_dropout)
-    self.self_attn_layers = nn.ModuleList()
-    self.norm_layers_0 = nn.ModuleList()
-    self.encdec_attn_layers = nn.ModuleList()
-    self.norm_layers_1 = nn.ModuleList()
-    self.ffn_layers = nn.ModuleList()
-    self.norm_layers_2 = nn.ModuleList()
-    for i in range(self.n_layers):
-      self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init))
-      self.norm_layers_0.append(LayerNorm(hidden_channels))
-      self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout))
-      self.norm_layers_1.append(LayerNorm(hidden_channels))
-      self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
-      self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-  def forward(self, x, x_mask, h, h_mask):
-    """
-    x: decoder input
-    h: encoder output
-    """
-    self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
-    encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-    x = x * x_mask
-    for i in range(self.n_layers):
-      y = self.self_attn_layers[i](x, x, self_attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_0[i](x + y)
-
-      y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-      y = self.drop(y)
-      x = self.norm_layers_1[i](x + y)
-      
-      y = self.ffn_layers[i](x, x_mask)
-      y = self.drop(y)
-      x = self.norm_layers_2[i](x + y)
-    x = x * x_mask
-    return x
-
-
-class MultiHeadAttention(nn.Module):
-  def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False):
-    super().__init__()
-    assert channels % n_heads == 0
-
-    self.channels = channels
-    self.out_channels = out_channels
-    self.n_heads = n_heads
-    self.p_dropout = p_dropout
-    self.window_size = window_size
-    self.heads_share = heads_share
-    self.block_length = block_length
-    self.proximal_bias = proximal_bias
-    self.proximal_init = proximal_init
-    self.attn = None
-
-    self.k_channels = channels // n_heads
-    self.conv_q = nn.Conv1d(channels, channels, 1)
-    self.conv_k = nn.Conv1d(channels, channels, 1)
-    self.conv_v = nn.Conv1d(channels, channels, 1)
-    self.conv_o = nn.Conv1d(channels, out_channels, 1)
-    self.drop = nn.Dropout(p_dropout)
-
-    if window_size is not None:
-      n_heads_rel = 1 if heads_share else n_heads
-      rel_stddev = self.k_channels**-0.5
-      self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
-      self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
-
-    nn.init.xavier_uniform_(self.conv_q.weight)
-    nn.init.xavier_uniform_(self.conv_k.weight)
-    nn.init.xavier_uniform_(self.conv_v.weight)
-    if proximal_init:
-      with torch.no_grad():
-        self.conv_k.weight.copy_(self.conv_q.weight)
-        self.conv_k.bias.copy_(self.conv_q.bias)
-      
-  def forward(self, x, c, attn_mask=None):
-    q = self.conv_q(x)
-    k = self.conv_k(c)
-    v = self.conv_v(c)
-    
-    x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-    x = self.conv_o(x)
-    return x
-
-  def attention(self, query, key, value, mask=None):
-    # reshape [b, d, t] -> [b, n_h, t, d_k]
-    b, d, t_s, t_t = (*key.size(), query.size(2))
-    query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-    key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-    value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-    scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-    if self.window_size is not None:
-      assert t_s == t_t, "Relative attention is only available for self-attention."
-      key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-      rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings)
-      scores_local = self._relative_position_to_absolute_position(rel_logits)
-      scores = scores + scores_local
-    if self.proximal_bias:
-      assert t_s == t_t, "Proximal bias is only available for self-attention."
-      scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype)
-    if mask is not None:
-      scores = scores.masked_fill(mask == 0, -1e4)
-      if self.block_length is not None:
-        assert t_s == t_t, "Local attention is only available for self-attention."
-        block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length)
-        scores = scores.masked_fill(block_mask == 0, -1e4)
-    p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
-    p_attn = self.drop(p_attn)
-    output = torch.matmul(p_attn, value)
-    if self.window_size is not None:
-      relative_weights = self._absolute_position_to_relative_position(p_attn)
-      value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s)
-      output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings)
-    output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t]
-    return output, p_attn
-
-  def _matmul_with_relative_values(self, x, y):
-    """
-    x: [b, h, l, m]
-    y: [h or 1, m, d]
-    ret: [b, h, l, d]
-    """
-    ret = torch.matmul(x, y.unsqueeze(0))
-    return ret
-
-  def _matmul_with_relative_keys(self, x, y):
-    """
-    x: [b, h, l, d]
-    y: [h or 1, m, d]
-    ret: [b, h, l, m]
-    """
-    ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-    return ret
-
-  def _get_relative_embeddings(self, relative_embeddings, length):
-    max_relative_position = 2 * self.window_size + 1
-    # Pad first before slice to avoid using cond ops.
-    pad_length = max(length - (self.window_size + 1), 0)
-    slice_start_position = max((self.window_size + 1) - length, 0)
-    slice_end_position = slice_start_position + 2 * length - 1
-    if pad_length > 0:
-      padded_relative_embeddings = F.pad(
-          relative_embeddings,
-          commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]))
-    else:
-      padded_relative_embeddings = relative_embeddings
-    used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position]
-    return used_relative_embeddings
-
-  def _relative_position_to_absolute_position(self, x):
-    """
-    x: [b, h, l, 2*l-1]
-    ret: [b, h, l, l]
-    """
-    batch, heads, length, _ = x.size()
-    # Concat columns of pad to shift from relative to absolute indexing.
-    x = F.pad(x, commons.convert_pad_shape([[0,0],[0,0],[0,0],[0,1]]))
-
-    # Concat extra elements so to add up to shape (len+1, 2*len-1).
-    x_flat = x.view([batch, heads, length * 2 * length])
-    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0,0],[0,0],[0,length-1]]))
-
-    # Reshape and slice out the padded elements.
-    x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:]
-    return x_final
-
-  def _absolute_position_to_relative_position(self, x):
-    """
-    x: [b, h, l, l]
-    ret: [b, h, l, 2*l-1]
-    """
-    batch, heads, length, _ = x.size()
-    # padd along column
-    x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length-1]]))
-    x_flat = x.view([batch, heads, length**2 + length*(length -1)])
-    # add 0's in the beginning that will skew the elements after reshape
-    x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-    x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:]
-    return x_final
-
-  def _attention_bias_proximal(self, length):
-    """Bias for self-attention to encourage attention to close positions.
-    Args:
-      length: an integer scalar.
-    Returns:
-      a Tensor with shape [1, 1, length, length]
-    """
-    r = torch.arange(length, dtype=torch.float32)
-    diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-    return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-  def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False):
-    super().__init__()
-    self.in_channels = in_channels
-    self.out_channels = out_channels
-    self.filter_channels = filter_channels
-    self.kernel_size = kernel_size
-    self.p_dropout = p_dropout
-    self.activation = activation
-    self.causal = causal
-
-    if causal:
-      self.padding = self._causal_padding
-    else:
-      self.padding = self._same_padding
-
-    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-    self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-    self.drop = nn.Dropout(p_dropout)
-
-  def forward(self, x, x_mask):
-    x = self.conv_1(self.padding(x * x_mask))
-    if self.activation == "gelu":
-      x = x * torch.sigmoid(1.702 * x)
-    else:
-      x = torch.relu(x)
-    x = self.drop(x)
-    x = self.conv_2(self.padding(x * x_mask))
-    return x * x_mask
-  
-  def _causal_padding(self, x):
-    if self.kernel_size == 1:
-      return x
-    pad_l = self.kernel_size - 1
-    pad_r = 0
-    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-    x = F.pad(x, commons.convert_pad_shape(padding))
-    return x
-
-  def _same_padding(self, x):
-    if self.kernel_size == 1:
-      return x
-    pad_l = (self.kernel_size - 1) // 2
-    pad_r = self.kernel_size // 2
-    padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-    x = F.pad(x, commons.convert_pad_shape(padding))
-    return x