< Chess.com has a premium membership that unlocks more benefits
-If you want to get the most out of Chess.com, you can upgrade to a premium membership and enjoy more benefits. Here are some of the benefits that you can get with a premium membership:
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-- Unlimited access: Get unlimited access to all the features and content on Chess.com, such as puzzles, lessons, videos, game analysis, and more.
-- Advanced features: Get access to advanced features, such as opening explorer, computer analysis, chess insights, and more.
-- Exclusive content: Get access to exclusive content, such as master classes, pro courses, interactive lessons, and more.
-- Ad-free experience: Enjoy an ad-free experience on Chess.com and support the site.
-- More perks: Get more perks, such as discounts, free entries, badges, and more.
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-You can choose from three premium membership plans: Gold, Platinum, or Diamond. The prices vary depending on the duration of the subscription. You can also get a free trial for 7 days before you decide to upgrade.
- How to Download Chess.com for Different Devices
-Chess.com is available for different devices, such as Android, iOS, Windows, or Mac. You can download Chess.com for free and start playing chess right away. Here are the steps to download Chess.com for different devices:
- How to download Chess.com for Android
-If you have an Android device, you can download Chess.com from the Google Play Store. Here are the steps to download Chess.com for Android:
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-- Open the Google Play Store app on your Android device.
-- Search for Chess.com or use this link to go directly to the app page.
-- Tap on the Install button and wait for the app to download and install on your device.
-- Open the Chess.com app and sign in with your email or social media account. If you don't have an account yet, you can create one for free.
-- Enjoy playing chess on your Android device with Chess.com.
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- How to download Chess.com for iOS
-If you have an iOS device, such as an iPhone or an iPad, you can download Chess.com from the App Store. Here are the steps to download Chess.com for iOS:
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-- Open the App Store app on your iOS device.
-- Search for Chess.com or use this link to go directly to the app page.
-- Tap on the Get button and wait for the app to download and install on your device.
-- Open the Chess.com app and sign in with your email or social media account. If you don't have an account yet, you can create one for free.
-- Enjoy playing chess on your iOS device with Chess.com.
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- How to download Chess.com for Windows or Mac
-If you have a Windows or Mac computer, you can download Chess.com from its official website. Here are the steps to download Chess.com for Windows or Mac:
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-- Open your web browser and go to this link to access the Chess.com download page.
-- Select your operating system (Windows or Mac) and click on the Download button.
-- Wait for the file to download and then run it to install Chess.com on your computer.
-- Open the Chess.com app and sign in with your email or social media account. If you don't have an account yet, you can create one for free.
-- Enjoy playing chess on your computer with Chess.com.
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- How to Use Chess.com After Downloading It
-After downloading Chess.com, you can start using it right away. You can create an account and set up your profile, play chess online or offline with Chess.com, improve your chess skills with Chess.com, and join events, tournaments, clubs, and communities on Chess.com. Here are some tips on how to use Chess.com after downloading it:
- How to create an account and set up your profile
-To use Chess.com, you need to create an account and set up your profile. You can do this by following these steps:
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-- Open the Chess.com app and tap on the Sign Up button. You can also sign in with your email or social media account if you already have one.
-- Enter your username, email address, password, and date of birth.
- Choose your skill level and your preferred time control. You can also select your country and language.
-- Tap on the Create Account button and confirm your email address.
-- Go to your profile and edit your personal information, such as your name, avatar, bio, rating, and more.
-- Customize your settings, such as your theme, sound, notifications, privacy, and more.
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-Congratulations, you have created your account and set up your profile on Chess.com. You can now start playing chess and enjoying the benefits of Chess.com.
- How to play chess online or offline with Chess.com
-One of the main reasons to download Chess.com is to play chess online or offline with Chess.com. You can play chess with millions of players from all around the world at any time control. You can also play chess with bots, friends, or yourself. Here are some tips on how to play chess online or offline with Chess.com:
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-- Play online: To play chess online with Chess.com, you can tap on the Play button on the home screen and choose your game mode. You can play rated or unrated games, odds chess, leagues, bots, daily chess, simuls, or variants. You can also filter your opponents by rating, time control, color, and more. You can also challenge a specific player by tapping on their username and selecting Challenge.
-- Play offline: To play chess offline with Chess.com, you can tap on the Menu button on the top left corner and select Offline. You can then choose to play against a bot, a friend, or yourself. You can also adjust the difficulty level, the board orientation, the clock settings, and more.
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-Whether you play chess online or offline with Chess.com, you can always review your games and analyze them with the game analysis feature. You can also chat with your opponent or other players and share your games on social media.
- How to improve your chess skills with Chess.com
-Another reason to download Chess.com is to improve your chess skills with Chess.com. Chess.com has a lot of features and content that can help you learn from the best, practice your tactics, study the theory, and track your progress. Here are some tips on how to improve your chess skills with Chess.com:
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-- Puzzles: To improve your tactical vision and calculation skills, you can solve puzzles on Chess.com. You can access thousands of puzzles that match your skill level and get instant feedback. You can also try puzzle rush, puzzle battle, puzzle themes, puzzle streaks, and more.
-- Lessons: To learn from hundreds of lessons covering all aspects of chess, you can access the lessons section on Chess.com. You can follow one of the many courses available or create your own personalized curriculum. You can also watch videos from top coaches and masters.
-- Analytics: To get insights into your strengths and weaknesses, you can access the analytics section on Chess.com. You can see advanced statistics and graphs that show your rating history, performance rating, win rate, accuracy, move classifications, opening repertoire, endgame skills, and more. You can also compare yourself with other players and see how you can improve.
-- Classroom: To create or follow a structured learning plan for yourself or your students, you can access the classroom section on Chess.com. You can assign lessons and track progress for yourself or your students. You can also get feedback and reports from Chess.com's virtual coach.
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-By using these features and content on Chess.com regularly, you can improve your chess skills with Chess.com and become a better player.
- How to join events, tournaments, clubs, and communities on Chess.com
-The last reason to download Chess.com is to join events, tournaments, clubs, and communities on Chess.com. Chess.com is not only a chess site, but also a chess social network. You can connect with millions of chess enthusiasts from all around the world and participate in various activities and events. Here are some tips on how to join events, tournaments, clubs, and communities on Chess.com:
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-- Events: To watch live coverage of the most exciting chess events in the world, you can access the events section on Chess.com. You can see the schedule, the standings, the games, and the commentary of the events. You can also chat with other viewers and interact with the commentators.
-- Tournaments: To compete in online tournaments and win prizes, you can access the tournaments section on Chess.com. You can join or create your own tournaments with different formats, time controls, and prizes. You can also see the results, the brackets, and the games of the tournaments.
-- Clubs: To join or create your own clubs with other players who share your interests, you can access the clubs section on Chess.com. You can chat with your club members, play games with them, challenge other clubs, and participate in club events and tournaments.
-- Communities: To join or create your own communities with other players who share your passion, you can access the communities section on Chess.com. You can chat with your community members, share your thoughts and ideas, post your content, and follow other communities.
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-By joining these events, tournaments, clubs, and communities on Chess.com, you can have fun with chess and make new friends.
- Conclusion
-In conclusion, Chess.com is the best chess site in the world that you should download if you love chess. You can play chess online or offline with Chess.com, improve your chess skills with Chess.com, and join events, tournaments, clubs, and communities on Chess.com. You can also enjoy a variety of features and content that Chess.com offers for chess lovers of all levels. You can download Chess.com for free for different devices, such as Android, iOS, Windows, or Mac. You can also upgrade to a premium membership and enjoy more benefits.
- We hope that this article has helped you learn how to download Chess.com and enjoy its benefits. If you have any questions or feedback, please feel free to leave a comment below. We would love to hear from you. Thank you for reading and happy chess playing!
- FAQs
-Here are some frequently asked questions about Chess.com:
-Is Chess.com free?
-Yes, Chess.com is free to download and use. You can play chess online or offline with Chess.com without paying anything. However, if you want to get more benefits and features from Chess.com, you can upgrade to a premium membership for a fee.
- How do I cancel my premium membership on Chess.com?
-If you want to cancel your premium membership on Chess.com, you can do so by following these steps:
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-- Go to your account settings on Chess.com.
-- Select Membership from the left menu.
-- Select Cancel Membership from the bottom of the page.
-- Confirm your cancellation and provide feedback if you wish.
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-You will still have access to your premium benefits until the end of your current billing cycle.
- How do I contact Chess.com support?
-If you need any help or support from Chess.com, you can contact Chess.com support by following these steps:
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-- Go to this link to access the Chess.com support page.
-- Select the category that best matches your issue or question.
-- Read the articles and FAQs that may answer your query.
-- If you still need help, click on the Submit a Request button at the bottom of the page.
-- Fill out the form with your details and your message.
-- Click on the Submit button and wait for a response from Chess.com support.
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-You can also contact Chess.com support by sending an email to support@chess.com or by using the live chat feature on the website.
- How do I delete my account on Chess.com?
-If you want to delete your account on Chess.com, you can do so by following these steps:
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-- Go to your account settings on Chess.com.
-- Select Delete Account from the left menu.
-- Enter your password and confirm your deletion.
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-Please note that deleting your account on Chess.com is permanent and irreversible. You will lose all your data, games, ratings, friends, and more. You will also not be able to create a new account with the same username or email address.
- How do I change my username on Chess.com?
-If you want to change your username on Chess.com, you can do so by following these steps:
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-- Go to your account settings on Chess.com.
-- Select Username from the left menu.
-- Enter your new username and click on the Check Availability button.
-- If your new username is available, click on the Change Username button and confirm your change.
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-Please note that changing your username on Chess.com is a one-time option. You will not be able to change it again in the future. You will also lose all your previous usernames and their history. Your new username will apply to all your games, ratings, friends, and more.
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-Free Download PC Games for Kids-7 Years Old
-If you are looking for some fun and educational activities to do with your kids at home, why not try some PC games? PC games are not only entertaining but also stimulating for your kids' brains. They can help them develop various skills such as logic, creativity, memory, coordination, and more. Plus, they are easy to find and download online.
-However, not all PC games are suitable or safe for kids. You need to be careful about the quality, content, and source of the games you choose. You also need to make sure your kids are not spending too much time or money on them.
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-The Best Free PC Games for Kids-7 Years Old
-Roblox Roblox
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Roblox is an online game platform and game creation system that allows users to program games and play games created by other users. It is one of the most popular and diverse gaming platforms for kids, with over 164 million monthly active users.
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-Roblox offers a vast collection of games of multiple genres, such as adventure, racing, role-playing, simulation, and more. You can also create your own games using the Roblox Studio, a visual programming tool that lets you design and code your own 3D worlds and characters.
-Roblox is great for kids because it stimulates their imagination, creativity, and problem-solving skills. It also helps them learn basic programming concepts and collaborate with other users in a friendly and safe community.
-To download Roblox for free, you can visit the official website or the Microsoft Store for Windows devices, the App Store for iOS devices, the Google Play Store for Android devices, or the Xbox One Store for Xbox One consoles. You can also sign up for a free account and access your games from any device.
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-To download Magic Jigsaw Puzzles for free, you can visit the Microsoft Store for Windows devices, the App Store for iOS devices, or the Google Play Store for Android devices. You can also access more puzzles and features by subscribing to the premium version of the app.
-Toca Boo
-Toca Boo is a spooky and funny app that lets you play as a ghost who likes to scare people. You can explore a dark house and find different objects and characters to haunt. You can also make noises, turn on lights, and hide under furniture to create a scary atmosphere.
-Toca Boo is great for kids because it stimulates their imagination, humor, and creativity. It also helps them overcome their fears and have fun with the concept of ghosts and monsters. The app has a simple and intuitive gameplay that is suitable for young children. You can also record your own sounds and use them in the app.
-To download Toca Boo for free, you can visit the App Store for iOS devices or the Google Play Store for Android devices. You can also find more games and apps from the Toca Boca series on their website or on YouTube.
-Conclusion
-PC games are a great way to have fun and learn with your kids at home. They can offer various benefits for your kids' development, such as enhancing their cognitive, creative, social, and emotional skills. They can also provide entertainment, relaxation, and education for your kids.
-In this article, we have shown you some of the best free PC games for kids-7 years old that you can download and play with your kids. These games are fun, educational, and appropriate for your kids' age group. They are also free of charge and legal to download.
-We hope you enjoyed this article and found some games that you and your kids will love. Have fun playing with your kids and exploring the wonderful world of PC games!
-FAQs
-
-- Q: Are PC games safe for kids?
-- A: Most PC games are safe for kids, but parents should always check the ratings, reviews, and content of the games before downloading them. Parents can also use parental controls and filters to limit the access and exposure of their kids to inappropriate or harmful content.
-- Q: How can I download PC games for free?
-- A: There are many websites and platforms that offer free PC games for download, such as Microsoft Store, Steam, Epic Games Store, itch.io, and more. However, not all of them are legal or trustworthy, so parents should always do some research and scan the files before downloading them. Parents can also use antivirus software and firewalls to protect their devices from viruses and malware.
-- Q: How can I make sure my kid is not spending too much time on PC games?
-- A: PC games can be addictive and distracting, so parents should set some rules and boundaries for their kids. For example, parents can limit the screen time, monitor the game activity, encourage other hobbies and activities, and play together with their kids.
-- Q: What are some benefits of PC games for kids?
-- A: PC games can have many benefits for kids, such as improving their cognitive skills, creativity, problem-solving, memory, attention, hand-eye coordination, social skills, and more. PC games can also be fun, relaxing, and educational for kids.
-- Q: What are some drawbacks of PC games for kids?
-- A: PC games can also have some drawbacks for kids, such as exposing them to violence, aggression, cyberbullying, addiction, isolation, eye strain, headaches, obesity, and more. Therefore, parents should always supervise their kids and balance their gaming time with other aspects of their lives.
-
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diff --git a/spaces/1phancelerku/anime-remove-background/Ace Academy Skies of Fury Mod Apk 1.1.2 - Experience the Thrill of Aerial Combat.md b/spaces/1phancelerku/anime-remove-background/Ace Academy Skies of Fury Mod Apk 1.1.2 - Experience the Thrill of Aerial Combat.md
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-Step 3: Install the mod apk file and launch the game
-The third and final step to download and install Ace Academy: Skies of Fury mod apk is to install the mod apk file and launch the game. To do this, you need to locate the downloaded file on your device storage, then tap on it to start the installation process. Follow the instructions on the screen to complete the installation. Once done, you can launch the game from your app drawer or home screen. Enjoy!
-Conclusion
-Summary of the main points
-Ace Academy: Skies of Fury mod apk is a modified version of the original game that gives you access to unlimited resources and features. It is a 3D flying game set in WW1, where you can fly for the British or German forces, take part in 100 missions, dogfight against other players online or offline, unlock all planes, customize them with loot boxes and skill points, and enjoy stunning graphics and sound effects.
-Call to action
-If you are looking for a thrilling and fun flying game that will keep you hooked for hours, then you should download Ace Academy: Skies of Fury mod apk today. It is free, easy, and safe to download and install on your Android device. Don't miss this opportunity to experience the excitement of aerial combat in WW1 with Ace Academy: Skies of Fury mod apk.
- FAQs Q: Is Ace Academy: Skies of Fury mod apk safe to use? A: Yes, Ace Academy: Skies of Fury mod apk is safe to use as long as you download it from a trusted source. However, you should always scan any file you download with an antivirus software before installing it on your device. Q: Is Ace Academy: Skies of Fury mod apk legal? A: No, Ace Academy: Skies of Fury mod apk is not legal as it violates the terms and conditions of the original game developer. Using a mod apk may result in banning or suspending your account from the game server. Use it at your own risk. Q: Do I need root access to use Ace Academy: Skies of Fury mod apk? A: No, you do not need root access to use Ace Academy: Skies of Fury mod apk. You can install it on any Android device without rooting it. Q: Can I play Ace Academy: Skies of Fury mod apk offline? A: Yes, you can play Ace Academy: Skies of Fury mod apk offline. However, you will need an internet connection to play online multiplayer mode or to update the game. Q: How can I contact the developer of Ace Academy: Skies of Fury mod apk? A: You can contact the developer of Ace Academy: Skies of Fury mod apk by visiting their official website or social media pages. However, they may not respond to your queries or complaints as they are not affiliated with the original game developer. Q: What are some alternatives to Ace Academy: Skies of Fury mod apk? A: Some alternatives to Ace Academy: Skies of Fury mod apk are War Wings, Sky Gamblers: Storm Raiders, and Air Combat Pilot: WW2 Pacific. These are also flying games set in WW1 or WW2, with similar gameplay and features. 401be4b1e0
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-Black Clover Mobile APK Mod: How to Download and Play
-If you are a fan of the popular anime/manga series Black Clover, you might be interested in playing its official mobile game, Black Clover Mobile. This game is an action-adventure RPG that lets you create your own character, join a magic guild, and explore the world of Black Clover. You can also interact with your favorite characters from the series, such as Asta, Yuno, Noelle, Yami, and more.
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-However, if you want to enjoy the game to its fullest potential, you might want to try using a Black Clover Mobile APK Mod. This is a modified version of the original game that gives you access to premium features, such as unlimited coins and gems, all magic types and characters unlocked, no ads, and more. In this article, we will show you what is Black Clover Mobile, how to download and install its APK Mod, and what are the benefits and risks of using it.
-What is Black Clover Mobile?
-Features of Black Clover Mobile
-Black Clover Mobile is a mobile game based on the Black Clover anime/manga series. It was developed by Bandai Namco Entertainment and released in Japan in 2020. The game is available for Android and iOS devices. Here are some of the features of Black Clover Mobile:
-
-- You can create your own original character and customize their appearance, voice, magic type, and personality.
-- You can join one of the nine magic guilds in the Clover Kingdom, such as the Black Bulls, the Golden Dawn, or the Crimson Lion Kings.
-- You can explore various locations from the Black Clover world, such as the Royal Capital, the Dungeon, or the Witch's Forest.
-- You can participate in various missions and quests, such as fighting enemies, collecting items, or helping NPCs.
-- You can team up with other players online or play solo in offline mode.
-- You can interact with your favorite characters from the Black Clover series and enjoy their original voice acting and dialogues.
-- You can use various spells and skills based on your magic type, such as fire, wind, light, darkness, anti-magic, etc.
-- You can collect various items and equipment to enhance your character's stats and abilities.
-- You can enjoy high-quality graphics and sound effects that recreate the atmosphere of the Black Clover anime.
-
-How to download Black Clover Mobile APK Mod
-If you want to download Black Clover Mobile APK Mod, you will need to follow these steps:
-Step 1: Find a reliable APK website
-An APK website is a website that provides APK files for various Android apps and games. However, not all APK websites are safe and trustworthy. Some of them may contain malware or viruses that can harm your device or steal your personal information. Therefore, you need to find a reliable APK website that offers Black Clover Mobile APK Mod. One example of such a website is [apkmonk](^1^), which provides a safe and updated version of Black Clover Mobile APK Mod.
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-Step 2: Download the APK file
-Once you have found a reliable APK website that offers Black Clover Mobile APK Mod, you will need to download the APK file to your device. To do this, you will need to click on the download button on the website and wait for the file to be downloaded. The file size is about 100 MB, so make sure you have enough storage space and a stable internet connection.
-Step 3: Install the APK file
-Before you can install the APK file, you will need to enable the installation of apps from unknown sources on your device. This is a security feature that prevents unauthorized apps from being installed on your device. To enable this feature, you will need to go to your device's settings, then security, then unknown sources, and toggle it on. Alternatively, you can also allow the installation of apps from unknown sources when prompted by your device.
-After you have enabled the installation of apps from unknown sources, you can proceed to install the APK file. To do this, you will need to locate the file in your device's file manager or downloads folder and tap on it. You will see a pop-up window that asks you to confirm the installation. Tap on install and wait for the process to finish.
-Step 4: Launch the game and enjoy
-Once you have installed the APK file, you can launch the game and enjoy its features. You will see a new icon on your device's home screen or app drawer that represents Black Clover Mobile APK Mod. Tap on it and start playing the game. You will notice that you have unlimited coins and gems, all magic types and characters unlocked, no ads, and more. You can use these features to enhance your gaming experience and have more fun.
-What is Black Clover Mobile APK Mod?
-Benefits of using Black Clover Mobile APK Mod
-Black Clover Mobile APK Mod is a modified version of the original Black Clover Mobile game that gives you access to premium features that are not available in the official game. Some of the benefits of using Black Clover Mobile APK Mod are:
-Unlimited coins and gems
-Coins and gems are the main currencies in Black Clover Mobile. You can use them to buy various items and equipment, such as costumes, weapons, accessories, potions, etc. You can also use them to upgrade your character's stats and abilities, such as health, attack, defense, magic power, etc. However, coins and gems are limited in the official game and you have to earn them by completing missions, quests, or events. Alternatively, you can also buy them with real money through in-app purchases.
-With Black Clover Mobile APK Mod, you don't have to worry about running out of coins and gems. You will have unlimited amounts of them and you can spend them as much as you want without any restrictions. You can buy whatever items and equipment you want and upgrade your character's stats and abilities to the max. This way, you can enjoy the game without any limitations or hassles.
-Unlock all magic types and characters
-Magic types and characters are another important aspect of Black Clover Mobile. You can choose from various magic types for your character, such as fire, wind, light, darkness, anti-magic, etc. Each magic type has its own advantages and disadvantages, as well as different spells and skills that you can use in combat. You can also unlock various characters from the Black Clover series that you can use as your allies or opponents in the game. Each character has their own personality, voice acting, dialogues, and abilities that reflect their role in the series.
-However, not all magic types and characters are available in the official game. Some of them are locked behind certain requirements or conditions that you have to meet in order to unlock them. For example, some magic types require you to reach a certain level or complete a certain quest before you can use them. Some characters require you to collect a certain amount of their cards or tokens before you can unlock them.
-With Black Clover Mobile APK Mod, you don't have to worry about unlocking magic types and characters. You will have all of them unlocked from the start and you can use them freely without any restrictions. You can choose any magic type for your character and switch between them anytime you want. You can also use any character from the Black Clover series as your ally or opponent in the game. This way, you can enjoy the game with more variety and diversity.
-Remove ads and pop-ups
-Ads and pop-ups are another annoying feature of Black Clover Mobile. They are advertisements that appear on your screen while you are playing the game or when you open or close the game. They are meant to promote other games or products that may interest you or encourage you to spend money on the game. However, they are also very intrusive and disruptive, as they interrupt your gameplay and distract you from the game. They can also consume your data and battery, as well as expose you to unwanted or inappropriate content.
-With Black Clover Mobile APK Mod, you don't have to worry about ads and pop-ups. You will have them removed from the game and you will not see them on your screen at all. You can play the game without any interruptions or distractions, as well as save your data and battery. You can also avoid any unwanted or inappropriate content that may harm you or your device.
-Risks of using Black Clover Mobile APK Mod
-While Black Clover Mobile APK Mod has many benefits, it also has some risks that you should be aware of before using it. Some of the risks of using Black Clover Mobile APK Mod are:
-Malware and viruses
-As mentioned earlier, not all APK websites are safe and trustworthy. Some of them may contain malware or viruses that can harm your device or steal your personal information. Malware and viruses can damage your device's system, corrupt your files, access your camera, microphone, contacts, messages, etc., or even lock your device and demand a ransom. Therefore, you should be careful when downloading and installing APK files from unknown sources and always scan them with a reliable antivirus software before opening them.
-Ban from the official game server
-Another risk of using Black Clover Mobile APK Mod is that you may get banned from the official game server. The official game server is where you can play online with other players, access the latest updates and events, and enjoy the full features of the game. However, the official game server also has a security system that detects any cheating or hacking activities from the players. If you use Black Clover Mobile APK Mod, you may be detected as a cheater or hacker and get banned from the official game server. This means that you will not be able to play online with other players, access the latest updates and events, or enjoy the full features of the game.
-Legal issues and ethical concerns
-The last risk of using Black Clover Mobile APK Mod is that you may face legal issues and ethical concerns. Black Clover Mobile APK Mod is an unauthorized modification of the original game that violates its terms of service and intellectual property rights. By using Black Clover Mobile APK Mod, you are essentially stealing from the developers and publishers of the game who invested their time, money, and effort to create it. You are also depriving them of their rightful revenue and profit that they deserve from their work. This may result in legal actions against you or ethical dilemmas for you.
-Conclusion
-Black Clover Mobile is a fun and exciting mobile game based on the Black Clover anime/manga series. It lets you create your own character, join a magic guild, and explore the world of Black Clover. However, if you want to enjoy the game to its fullest potential, you might want to try using Black Clover Mobile APK Mod. This is a modified version of the original game that gives you access to premium features, such as unlimited coins and gems, all magic types and characters unlocked, no ads, and more.
-However, before you use Black Clover Mobile APK Mod, you should also be aware of its risks. Some of the risks of using Black Clover Mobile APK Mod are malware and viruses, ban from the official game server, and legal issues and ethical concerns. Therefore, you should be careful when downloading and installing Black Clover Mobile APK Mod and always use it at your own risk.
-FAQs
-
-- Q: Is Black Clover Mobile free to play?
-- A: Yes, Black Clover Mobile is free to play. However, it also has in-app purchases that allow you to buy coins and gems with real money.
-- Q: Is Black Clover Mobile available in English?
-- A: No, Black Clover Mobile is currently only available in Japanese. However, there are fan-made translations and guides that can help you understand the game better.
-- Q: Is Black Clover Mobile compatible with my device?
-- A: Black Clover Mobile requires Android 5.0 or higher or iOS 10.0 or higher to run smoothly. It also requires at least 2 GB of RAM and 1 GB of storage space.
-- Q: How can I contact the developers or publishers of Black Clover Mobile?
-- A: You can contact the developers or publishers of Black Clover Mobile through their official website , their official Twitter account , or their official Facebook page [^4^
Here is the continuation of the article:
-You can contact the developers or publishers of Black Clover Mobile through their official website , their official Twitter account , or their official Facebook page . You can also send them an email at bcmna@pearlabyss.com or use the in-game customer service feature. They will be happy to answer your questions, feedback, or suggestions regarding the game.
-I hope you enjoyed this article and found it helpful. If you did, please share it with your friends and fellow Black Clover fans. Also, don't forget to pre-register for Black Clover Mobile and get ready for its global launch soon. Thank you for reading and have a great day!
-FAQs
-
-- Q: What is the difference between Black Clover Mobile and Black Clover Phantom Knights?
-- A: Black Clover Mobile and Black Clover Phantom Knights are two different mobile games based on the Black Clover series. Black Clover Mobile is an action-adventure RPG that lets you create your own character and join a magic guild. Black Clover Phantom Knights is a strategy RPG that lets you collect and deploy various characters from the series in battles.
-- Q: Can I play Black Clover Mobile offline?
-- A: Yes, you can play Black Clover Mobile offline. However, you will not be able to access some features that require an internet connection, such as online multiplayer, events, updates, etc.
-- Q: Can I play Black Clover Mobile with my friends?
-- A: Yes, you can play Black Clover Mobile with your friends. You can team up with them in online co-op mode or challenge them in online PvP mode. You can also chat with them in the game or join a guild with them.
-- Q: How can I get more coins and gems in Black Clover Mobile?
-- A: You can get more coins and gems in Black Clover Mobile by completing missions, quests, events, achievements, etc. You can also buy them with real money through in-app purchases or use Black Clover Mobile APK Mod to get unlimited amounts of them.
-- Q: How can I change my magic type or character in Black Clover Mobile?
-- A: You can change your magic type or character in Black Clover Mobile by going to the menu, then profile, then edit. You can choose from various magic types and characters that you have unlocked in the game.
-
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-
-How to Download Game Kamen Rider: A Guide for Fans of the Japanese Superhero Series
- If you are a fan of the Japanese superhero media franchise Kamen Rider, you might be interested in playing some of the games based on the series. Kamen Rider games are action-packed, thrilling, and fun, featuring various characters, stories, and gameplay styles from the franchise. Whether you want to transform into a masked rider, fight against evil villains, or explore the world of Kamen Rider, there is a game for you.
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- But how can you download game Kamen Rider for your preferred platform? In this article, we will show you how to find and download game Kamen Rider for PC, mobile devices, and consoles. We will also give you some tips and tricks on how to enjoy and get the most out of game Kamen Rider, as well as some recommendations on the best Kamen Rider games to try out. Let's get started!
- What is Kamen Rider and Why Should You Play It?
- Before we dive into how to download game Kamen Rider, let's first understand what Kamen Rider is and why you should play it.
- The History and Concept of Kamen Rider
- Kamen Rider is a Japanese superhero media franchise created by manga artist Shotaro Ishinomori in 1971. It consists of tokusatsu television shows, movies, manga, anime, and video games. The franchise is known for its iconic heroes who wear insect-themed masks and ride motorcycles, as well as its themes of justice, heroism, and humanism.
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- The first series, simply titled Kamen Rider, aired from 1971 to 1973 and followed the story of Takeshi Hongo, a college student who was kidnapped by a terrorist organization called Shocker and turned into a cyborg. He escaped and used his new powers to fight against Shocker and protect humanity. Since then, there have been more than 30 series in the franchise, each with a different protagonist, setting, and plot.
- Kamen Rider is one of the most popular and influential franchises in Japan, spawning a huge fan base and inspiring many other works in the superhero genre. It has also been recognized as a cultural icon and a symbol of Japanese pop culture.
- The Different Types and Genres of Kamen Rider Games
- As a media franchise, Kamen Rider has also produced many video games based on its various series. These games range from action-adventure, fighting, role-playing, racing, simulation, puzzle, card, board, to educational genres. Some games are faithful adaptations of the original stories and characters, while others are original creations or crossover with other franchises.
- Kamen Rider games allow fans to experience the excitement and thrill of being a masked rider themselves. They can transform into their favorite heroes, use their signature weapons and abilities, fight against familiar enemies or new foes, explore different locations from the series or create their own scenarios, and interact with other characters or players.
- Kamen Rider games are also a great way to learn more about the franchise and its lore. They can provide additional information or background on the characters, events, or concepts from the series. They can also introduce new elements or twists that can enhance or challenge the fans' understanding of the franchise.
- How to Find and Download Game Kamen Rider for Various Platforms
- Now that you know what Kamen Rider is and why you should play it, you might be wondering how to find and download game Kamen Rider for your preferred platform. There are many sources and methods to download game Kamen Rider, depending on whether you want to play it on PC, mobile devices, or consoles. Here are some of the most common and reliable ways to download game Kamen Rider for various platforms.
Download Game Kamen Rider for PC
- If you want to play game Kamen Rider on your PC, you have several options to choose from. One of the most popular and convenient ways is to use Steam, an online platform that offers a wide range of games for PC users. Another way is to use itch.io, an indie game marketplace that features many fan-made games for PC users. Here are the steps to download game Kamen Rider for PC using these two platforms.
- Steam
- Steam is a digital distribution service that allows you to buy, download, and play games on your PC. It also provides social features, such as chat, forums, and reviews. To download game Kamen Rider on Steam, you need to have a Steam account and the Steam client installed on your PC. Here are the steps to download game Kamen Rider on Steam:
-
-- Open the Steam client and log in to your account.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and click on the "Add to Cart" button.
-- Proceed to checkout and pay for the game using your preferred payment method.
-- Once the payment is confirmed, the game will be added to your library.
-- Go to your library and click on the game you want to play.
-- Click on the "Install" button and wait for the game to download and install on your PC.
-- Once the installation is complete, click on the "Play" button and enjoy your game.
-
- Some of the official Kamen Rider games that are available on Steam are:
-
-
-Title |
-Description |
-Price |
-
-
-Kamen Rider: Memory of Heroez |
-A 3D action-adventure game that features Kamen Rider W, OOO, and Zero-One as playable characters. It has an original story that is different from the TV series. |
-$59.99 |
-
-
-KAMEN RIDER CLIMAX SCRAMBLE Zi-O |
-A fighting game that features over 30 Kamen Riders from Heisei era. It has a story mode that follows the events of Kamen Rider Zi-O TV series. |
-$49.99 |
-
-
-KAMEN RIDER: Battride War Sousei |
-A hack-and-slash game that features over 45 Kamen Riders from Showa and Heisei era. It has a story mode that recreates the iconic scenes from the TV series. |
-$49.99 |
-
-
- itch.io
- itch.io is an online platform that allows indie developers and creators to sell or distribute their games for PC users. It also provides community features, such as comments, ratings, and recommendations. To download game Kamen Rider on itch.io, you don't need an account or a client, but it is recommended to have one for better experience. Here are the steps to download game Kamen Rider on itch.io:
-
-- Open your browser and go to https://itch.io/.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and click on the "Download" button.
-- If the game is free, you can download it directly. If the game is paid, you need to pay for it using your preferred payment method.
-- Once the download is complete, unzip the file and run the executable file.
-- Enjoy your game.
-
- Some of the fan-made Kamen Rider games that are available on itch.io are:
-
-
-Title |
-Description |
-Price |
-
-
-KAMEN RIDER EX-AID: THE GAME PARADOX! |
-A 2D platformer game that features Kamen Rider Ex-Aid as the main character. It has a retro style and a challenging gameplay. |
-Name your own price |
-
-
-KAMEN RIDER ZI-O: OVER QUARTZER! |
- | Name your own price |
-
-
-KAMEN RIDER SABER: THE GAME! |
-A 3D hack-and-slash game that features Kamen Rider Saber as the main character. It has a fantasy story and a customizable sword system. |
-$5.00 |
-
-
- Download Game Kamen Rider for Mobile Devices
- If you want to play game Kamen Rider on your mobile devices, such as smartphones or tablets, you have two options to choose from. One is to use the Google Play Store for Android devices, and the other is to use the App Store for iOS devices. These are online platforms that offer a variety of apps and games for mobile users. Here are the steps to download game Kamen Rider for mobile devices using these two platforms.
- Android
- Google Play Store is a digital distribution service that allows you to download and install apps and games on your Android devices. It also provides social features, such as ratings, reviews, and recommendations. To download game Kamen Rider on Google Play Store, you need to have a Google account and a compatible device. Here are the steps to download game Kamen Rider on Google Play Store:
-
-- Open the Google Play Store app on your device and sign in to your account.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and tap on the "Install" button.
-- Wait for the game to download and install on your device.
-- Once the installation is complete, tap on the "Open" button and enjoy your game.
-
- Some of the official Kamen Rider games that are available on Google Play Store are:
-
-
-Title |
-Description |
-Price |
-
-
-KAMEN RIDER CITY WARS |
-A simulation game that allows you to build and manage your own city with Kamen Riders. You can also collect and upgrade various Kamen Riders and fight against enemies in 3D battles. |
-Free with in-app purchases |
-
-
-KAMEN RIDER BATTLE RUSH |
- | Free with in-app purchases |
-
-
-KAMEN RIDER TRANSFORM |
-A casual game that allows you to transform into different Kamen Riders by scanning their cards. You can also take photos and videos of yourself as a Kamen Rider and share them with others. |
-Free |
-
-
- iOS
- App Store is a digital distribution service that allows you to download and install apps and games on your iOS devices. It also provides social features, such as ratings, reviews, and recommendations. To download game Kamen Rider on App Store, you need to have an Apple ID and a compatible device. Here are the steps to download game Kamen Rider on App Store:
-
-- Open the App Store app on your device and sign in to your Apple ID.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and tap on the "Get" button.
-- If the game is free, you can download it directly. If the game is paid, you need to pay for it using your preferred payment method.
-- Wait for the game to download and install on your device.
-- Once the installation is complete, tap on the game icon and enjoy your game.
-
- Some of the official Kamen Rider games that are available on App Store are:
-
-
-Title |
-Description |
-Price |
-
-
-KAMEN RIDER AR CARDASS |
- | Free with in-app purchases |
-
-
-KAMEN RIDER BOUT |
-A fighting game that features over 100 Kamen Riders from different series. You can customize your own Kamen Rider and fight against other players in real-time battles. |
-Free with in-app purchases |
-
-
-KAMEN RIDER ATTRACTION RUSH |
-A puzzle game that is based on the Kamen Rider attractions at the Fuji-Q Highland amusement park. You can match the Kamen Rider symbols and clear the stages. |
-Free with in-app purchases |
-
-
- Download Game Kamen Rider for Consoles
- If you want to play game Kamen Rider on your consoles, such as PlayStation or Nintendo Switch, you have two options to choose from. One is to use the online store for your console, such as PlayStation Store or Nintendo eShop, and the other is to buy a physical copy of the game from a retailer or an online seller. These are online or offline platforms that offer a variety of games for console users. Here are the steps to download game Kamen Rider for consoles using these two platforms.
- PlayStation
- PlayStation Store is a digital distribution service that allows you to download and install games on your PlayStation consoles, such as PS4 or PS5. It also provides social features, such as trophies, friends, and messages. To download game Kamen Rider on PlayStation Store, you need to have a PlayStation Network account and a compatible console. Here are the steps to download game Kamen Rider on PlayStation Store:
-
-- Open the PlayStation Store app on your console and sign in to your account.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and click on the "Add to Cart" button.
-- Proceed to checkout and pay for the game using your preferred payment method.
-- Once the payment is confirmed, the game will be added to your library.
-- Go to your library and click on the game you want to play.
-- Click on the "Download" button and wait for the game to download and install on your console.
-- Once the installation is complete, click on the "Start" button and enjoy your game.
-
- Some of the official Kamen Rider games that are available on PlayStation Store are:
-
-
-Title |
-Description |
-Price |
-
-
- | A 3D action-adventure game that features Kamen Rider W, OOO, and Zero-One as playable characters. It has an original story that is different from the TV series. |
-$59.99 |
-
-
-KAMEN RIDER CLIMAX FIGHTERS |
-A fighting game that features over 30 Kamen Riders from Heisei era. It has a multiplayer mode that allows up to four players to battle online or offline. |
-$49.99 |
-
-
-KAMEN RIDER: Battride War Genesis |
-A hack-and-slash game that features over 50 Kamen Riders from Showa and Heisei era. It has a story mode that covers the origin and evolution of the Kamen Riders. |
-$49.99 |
-
-
- Nintendo Switch
- Nintendo eShop is a digital distribution service that allows you to download and install games on your Nintendo Switch console. It also provides social features, such as news, videos, and screenshots. To download game Kamen Rider on Nintendo eShop, you need to have a Nintendo account and a compatible console. Here are the steps to download game Kamen Rider on Nintendo eShop:
-
-- Open the Nintendo eShop app on your console and sign in to your account.
-- Search for "Kamen Rider" in the search bar and browse the results.
-- Select the game you want to download and click on the "Proceed to Purchase" button.
-- Pay for the game using your preferred payment method.
-- Once the payment is confirmed, the game will start downloading on your console.
-- Once the download is complete, you can launch the game from the home menu and enjoy your game.
-
- Some of the official Kamen Rider games that are available on Nintendo eShop are:
-
-
-Title |
-Description |
-Price |
-
- | A role-playing game that features over 40 Kamen Riders from different series. It has a story mode that follows the events of Kamen Rider Ex-Aid TV series and movie. |
-$49.99 |
-
-
-KAMEN RIDER Climax Scramble Zi-O |
-A fighting game that features over 30 Kamen Riders from Heisei era. It has a story mode that follows the events of Kamen Rider Zi-O TV series. |
-$49.99 |
-
-
-KAMEN RIDER Travelers Record |
-A 2D action game that features over 20 Kamen Riders from Showa and Heisei era. It has a story mode that involves time travel and crossover with other Kamen Riders. |
-$39.99 |
-
-
- How to Enjoy and Get the Most Out of Game Kamen Rider
- Now that you know how to download game Kamen Rider for various platforms, you might be wondering how to enjoy and get the most out of game Kamen Rider. Playing game Kamen Rider can be a lot of fun and rewarding, but it can also be challenging and frustrating at times. Here are some tips and tricks on how to enjoy and get the most out of game Kamen Rider.
- Tips and Tricks for Playing Game Kamen Rider
- Here are some general tips and tricks for playing game Kamen Rider:
-
-- Learn the basics of the game, such as the controls, the objectives, the mechanics, and the features. You can usually find these information in the tutorial, the manual, or the help menu.
-- Choose the difficulty level that suits your skill and preference. You can usually adjust the difficulty level in the settings or before starting a new game.
-- Experiment with different characters, modes, and options. You can discover new gameplay styles, strategies, and outcomes by trying different combinations.
-- Save your progress frequently. You don't want to lose your hard-earned achievements or progress by accident or power outage. You can usually save your progress in the pause menu or at certain checkpoints.
-- Take breaks regularly. Playing game Kamen Rider can be addictive and exhausting, especially if you play for long hours. You should take breaks every once in a while to rest your eyes, hands, and mind.
-- Have fun and don't take it too seriously. Playing game Kamen Rider is supposed to be enjoyable and entertaining, not stressful and frustrating. You should play for fun and not for competition or perfection.
-
- The Best Kamen Rider Games to Try Out
- Here are some of the best Kamen Rider games to try out, based on their popularity, ratings, reviews, and quality:
-
- | Description |
-Platform |
-
-
-KAMEN RIDER memory of heroez |
-A 3D action-adventure game that features Kamen Rider W, OOO, and Zero-One as playable characters. It has an original story that is different from the TV series. |
-PC, PlayStation, Nintendo Switch |
-
-
-KAMEN RIDER: Battride War Genesis |
-A hack-and-slash game that features over 50 Kamen Riders from Showa and Heisei era. It has a story mode that covers the origin and evolution of the Kamen Riders. |
-PC, PlayStation |
-
-
-KAMEN RIDER CHRONICLE |
- | Nintendo Switch |
-
-
-KAMEN RIDER BOUT |
-A fighting game that features over 100 Kamen Riders from different series. You can customize your own Kamen Rider and fight against other players in real-time battles. |
-Mobile devices |
-
-
-KAMEN RIDER EX-AID: THE GAME PARADOX! |
- | PC |
-
-
- Conclusion
- Kamen Rider is a Japanese superhero media franchise that has produced many video games based on its various series. These games are action-packed, thrilling, and fun, featuring various characters, stories, and gameplay styles from the franchise. Whether you want to transform into a masked rider, fight against evil villains, or explore the world of Kamen Rider, there is a game for you.
- In this article, we have shown you how to find and download game Kamen Rider for various platforms, such as PC, mobile devices, and consoles. We have also given you some tips and tricks on how to enjoy and get the most out of game Kamen Rider, as well as some recommendations on the best Kamen Rider games to try out. We hope you have found this article helpful and informative.
- Now that you know how to download game Kamen Rider, what are you waiting for? Go ahead and play your favorite Kamen Rider game and have a blast!
- FAQs
- Here are some of the frequently asked questions about game Kamen Rider:
-
-- What is the best Kamen Rider game?
-There is no definitive answer to this question, as different games may appeal to different players based on their preferences and tastes. However, some of the factors that can help you decide are the graphics, the gameplay, the story, the characters, the features, and the reviews. You can also check out our list of the best Kamen Rider games to try out in this article.
-- How can I play game Kamen Rider online with other players?
-Some of the game Kamen Rider have online multiplayer modes that allow you to play with or against other players online. To play these modes, you need to have a stable internet connection and a compatible device. You may also need to have an online subscription service, such as PlayStation Plus or Nintendo Switch Online, depending on your platform. You can also use third-party apps or websites to chat or communicate with other players online.
-- How can I play game Kamen Rider offline without internet?
-
- How can I get more Kamen Rider games for free?
-Some of the game Kamen Rider are free to download and play, while others are paid or have in-app purchases. To get more Kamen Rider games for free, you can look for free or discounted offers on the online platforms, such as Steam, Google Play Store, or App Store. You can also look for fan-made or unofficial games on other websites, such as itch.io or Game Jolt. However, you should be careful and avoid any illegal or harmful downloads that may harm your device or violate the rights of the developers.
- - How can I learn more about Kamen Rider and its games?
-If you want to learn more about Kamen Rider and its games, you can check out the official website, social media, and YouTube channel of the franchise. You can also read the manga, watch the anime, or see the movies based on the series. You can also join online communities, such as forums, blogs, or fan clubs, where you can interact with other fans and share your opinions and experiences. You can also visit the Kamen Rider Wiki, a fan-made encyclopedia that contains detailed information and trivia about the franchise.
-
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Soja by Black Sherif - The Latest 2022 Song from the Ghanaian Star.md b/spaces/1phancelerku/anime-remove-background/Download Soja by Black Sherif - The Latest 2022 Song from the Ghanaian Star.md
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-
-Black Sherif: The Rising Star of Ghanaian Music
-If you are a fan of Ghanaian music, you have probably heard of Black Sherif, the young and talented singer and rapper who is taking the industry by storm. He is known for his unique blend of highlife, reggae, hip-hop, and drill music, as well as his captivating lyrics and delivery. He has released several hit songs, such as "Money", "First Sermon", "Second Sermon", "Kwaku the Traveller", and "45". He has also collaborated with some of the biggest names in African music, such as Burna Boy, Sarkodie, King Promise, Camidoh, and more. He has also won several awards and nominations, such as the Best Hip Hop award at the Soundcity MVP Awards 2023, and four nominations at the All Africa Music Awards (AFRIMA) 2022.
-But who is Black Sherif and how did he become one of the most popular and influential artists in Ghana and beyond? In this article, we will explore his biography, his new song 2022 download, his awards and nominations, and his social media handles. We will also give you some tips on how to download his new song for free or stream it online. By the end of this article, you will have a better understanding of Black Sherif's music and why you should follow him.
-black sherif new song 2022 download
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- Biography of Black Sherif
-Black Sherif's real name is Mohammed Ismail Sharrif. He was born on January 9th, 2002 in Konongo-Zongo, in the Ashanti Region of Ghana. He grew up in a Muslim family with both parents working mostly overseas. He started living with his aunt and other extended family members at the age of 10. His nomadic lifestyle exposed him to multiple influences and different cultures at a very early age.
- Early life and education
-Black Sherif attended his basic education at Konongo Zongo Islamic Basic School and later at Pinamang Educational Complex, where he graduated junior high school. He then later completed his secondary education at Kumasi Academy, where he picked up an interest in music and dancing. He was a dancer at an early age but stopped after developing an interest in music. He became a very popular teenager in Konongo-Zongo, where he participated in talent shows and rap battles.
-He then gained admission into the University of Professional Studies (UPSA) to study statistics but dropped out after one year. He later enrolled at the University of Ghana to study marketing.
- Career
-Black Sherif began his career in 2019 with the release of his song "Cry for Me" on YouTube. His debut single "Money" was released on May 25, 2020, along with a music video. The song became a viral hit and earned him a lot of fans and recognition. He followed up with another single "Destiny" in August 2020, which also received positive reviews. In May 2021, he released his first EP titled "First Sermon", which contained five songs, including the popular "First Sermon" and "Ankonam". The EP showcased his versatility and lyrical prowess, as he addressed various social issues and personal struggles. He also collaborated with other artists such as Kwesi Arthur, Kofi Mole, and Tulenkey on the EP. In July 2021, he released his second EP titled "Second Sermon", which contained six songs, including the smash hit "Second Sermon" and "Ade Akye". The EP was a continuation of his first one, as he delved deeper into his life story and experiences. He also featured Burna Boy on the remix of "Second Sermon", which was a huge boost for his career. In March 2022, he released his third EP titled "Kwaku the Traveller", which contained seven songs, including the chart-topping "Kwaku the Traveller" and "45". The EP was a concept album that narrated the journey of a young man named Kwaku who travelled across different countries and cultures in search of himself and his purpose. He also collaborated with Sarkodie, King Promise, Camidoh, and others on the EP. In October 2022, he released his debut album titled "The Villain I Never Was", which contained 12 songs, including the singles "Soja" and "Oil in My Head". The album was a masterpiece that showcased his growth and maturity as an artist, as well as his versatility and creativity. He also featured some international artists such as Wizkid, Davido, Nasty C, and others on the album. The album received critical acclaim and commercial success, as it topped various charts and platforms in Ghana and beyond.
Artistry
-Black Sherif's music is a blend of highlife, reggae, hip-hop, and drill music. He is influenced by various artists such as Bob Marley, Tupac Shakur, Sarkodie, Kwesi Arthur, Pop Smoke, Drake, and others. He is known for his unique voice, catchy hooks, witty wordplay, storytelling skills, and social commentary. He sings and raps in English, Twi, Hausa, and Pidgin English. He addresses various themes such as poverty, hustle, love, spirituality, culture, identity, and more in his music. He is also known for his energetic and charismatic performances on stage.
- Black Sherif's New Song 2022 Download
-Black Sherif is not slowing down anytime soon. He has already announced that he is working on his next project, which will be released in 2022. He has also teased his fans with a snippet of his new song on social media. The song is titled "Mozama Disco" and it features Nigerian superstar Wande Coal. The song is expected to be a banger that will make everyone dance.
- Overview
-"Mozama Disco" is the title of Black Sherif's new song that will be released in January 2022. The song is produced by Nektunez, who also produced some of his previous hits such as "Money", "First Sermon", and "Second Sermon". The song features Wande Coal, who is one of the most successful and influential artists in Nigeria and Africa. The song is a fusion of highlife, afrobeat, and dancehall music. The song is about having fun and enjoying life.
- Review
-"Mozama Disco" is a catchy and upbeat song that will make you want to move your body. Black Sherif delivers his signature vocals and flows on the song, as he sings and raps about living in the moment and forgetting about the worries of life. He also praises his lover and invites her to join him on the dance floor. Wande Coal adds his smooth and soulful voice to the song, as he harmonizes with Black Sherif and adds some flavor to the song. He also sings about how he loves to party with Black Sherif and how they are unstoppable together. The song has a groovy and infectious beat that will make you nod your head or tap your feet. The song has a catchy hook that will stick in your head after listening to it once. The song has a positive and uplifting vibe that will make you feel good.
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- Reception
-"Mozama Disco" has received a lot of positive feedback from fans and critics alike. The song has been trending on various platforms such as YouTube, Spotify, Apple Music, Audiomack, and more. The song has also been played on various radio and TV stations across Ghana and Nigeria. The song has also received rave reviews from music blogs, magazines, and websites. Some of the comments from the fans and critics are: - "This song is a bop. Black Sherif and Wande Coal killed it. I can't stop dancing to it." - "Black Sherif is the future of Ghanaian music. He is so versatile and talented. He always delivers quality music. Wande Coal is a legend. He never disappoints. This song is a hit." - "This song is a masterpiece. It has everything you need in a good song. It has a catchy hook, a groovy beat, a great message, and amazing vocals. Black Sherif and Wande Coal are a perfect match. They complement each other so well." - "This song is a fire. It is one of the best songs of 2022. It is a fusion of highlife, afrobeat, and dancehall music. It is a unique and refreshing sound. Black Sherif and Wande Coal are both talented and creative artists. They have shown their skills and abilities on this song."
Download
-If you want to download "Mozama Disco" by Black Sherif featuring Wande Coal, you have several options to choose from. You can either download it for free or stream it online. Here are some of the ways you can download or stream the song:
-
-- You can download it for free from Black Sherif's official website: www.blacksherif.com. You just need to enter your email address and you will receive a link to download the song.
-- You can also download it for free from various music websites such as www.naijaloaded.com.ng, www.tooxclusive.com, www.notjustok.com, www.mp3bullet.ng, and more. You just need to search for the song and click on the download button.
-- You can also stream it online from various platforms such as YouTube, Spotify, Apple Music, Audiomack, Boomplay, and more. You just need to search for the song and click on the play button.
-
-However, we recommend that you support the artist by buying or streaming the song from legal and authorized platforms. This way, you will help him earn some revenue and recognition for his hard work and talent.
- Black Sherif's Awards and Nominations
-Black Sherif has been recognized and rewarded for his music by various awards and nominations. He has won several awards and been nominated for many more in his short but impressive career. Some of the awards and nominations that he has received or been nominated for are:
- List of awards and nominations
-
-
-Award |
-Category |
-Song/Album |
-Year |
-Result |
-
-
-Soundcity MVP Awards |
-Best Hip Hop |
-"Second Sermon" |
-2023 |
-Won |
-
-
-All Africa Music Awards (AFRIMA) |
-Best Male Artiste in Western Africa |
-"The Villain I Never Was" |
-2022 |
-Nominated |
-
-
-All Africa Music Awards (AFRIMA) |
-Song of the Year in Africa |
-"Second Sermon" |
-2022 |
-Nominated |
-
-
-All Africa Music Awards (AFRIMA) |
-Best Artiste, Duo or Group in African Hip Hop |
-"The Villain I Never Was" |
-2022 |
-Nominated |
-
-
-All Africa Music Awards (AFRIMA) |
-Revelation of the African Continent | "The Villain I Never Was" | 2022 | Nominated |
Ghana Music Awards UK > | New Artiste of the Year > | N/A > | 2021 > | Won > |
Ghana Music Awards UK > | Best Collaboration of the Year
-"Second Sermon (Remix)" ft. Burna Boy |
-2021 |
-Nominated |
-
-
-Ghana Music Awards UK |
-Hip Hop Song of the Year |
-"Second Sermon" |
-2021 |
-Nominated |
-
-
-Vodafone Ghana Music Awards |
-Best New Artiste of the Year |
-N/A |
-2021 |
-Nominated |
-
-
-Vodafone Ghana Music Awards |
-Hip Hop Song of the Year |
-"Money" |
-2021 |
-Nominated |
-
-
-Vodafone Ghana Music Awards |
-Hiplife/Hip Hop Artiste of the Year | N/A > | 2021 > | Nominated > |
3Music Awards > | Breakthrough Act of the Year > | N/A > | 2021 > | Nominated > |
3Music Awards > | Hip Hop Song of the Year > | "Money" > | 2021 > | Nominated > |
Analysis
These awards and nominations show that Black Sherif is one of the most talented and successful artists in Ghana and Africa. They also show that his music is appreciated and recognized by his fans, peers, and critics. They also show that he is a versatile and innovative artist who can excel in different genres and styles of music. They also show that he is a hardworking and consistent artist who always delivers quality music. These awards and nominations also motivate him to keep improving and growing as an artist.
- Black Sherif's Social Media Handles
-Black Sherif is very active and popular on social media. He uses social media to connect with his fans, promote his music, share his thoughts and opinions, and showcase his personality and lifestyle. He has millions of followers across different social media platforms. Some of the social media platforms that he uses are:
- List of social media handles
-
-- Instagram: @blacksherif_ . He has over 2 million followers on Instagram, where he posts pictures and videos of himself, his music, his friends, his family, and his travels. He also interacts with his fans through comments, likes, and live sessions.
-- Twitter: @blacksherif_ . He has over 1 million followers on Twitter, where he tweets about his music, his opinions, his experiences, and his interests. He also engages with his fans through replies, retweets, and likes.
-- Facebook: Black Sherif Official Page . He has over 500k likes on Facebook, where he posts updates about his music, his events, his achievements, and his activities. He also communicates with his fans through comments, reactions, and messages.
-- YouTube: Black Sherif Music Channel . He has over 300k subscribers on YouTube, where he uploads his music videos, his performances, his interviews, and his behind-the-scenes footage. He also responds to his fans through comments and likes.
-- TikTok: @blacksherif_ . He has over 100k followers on TikTok, where he posts short videos of himself dancing, singing, rapping, or doing challenges. He also joins trends and hashtags on the platform.
-- Snapchat: @blacksherif_ . He has over 50k friends on Snapchat, where he shares snaps of his daily life, his music, his fun moments, and his secrets. He also chats with his fans through snaps and messages.
-- Audiomack: Black Sherif Music Profile . He has over 10k followers on Audiomack, where he uploads his songs, EPs, albums, and playlists. He also streams other artists' music on the platform.
- Analysis
- Black Sherif uses social media to build a strong fan base and a loyal community. He uses social media to showcase his talent and creativity. He uses social media to market and distribute his music. He uses social media to express his personality and opinions. He uses social media to interact and engage with his fans and peers. He uses social media to learn and grow as an artist. He uses social media to create a positive and inspiring image for himself and his music.
- Conclusion
-In conclusion, Black Sherif is one of the most promising and talented artists in Ghana and Africa. He has a unique and versatile style of music that appeals to a wide range of audiences. He has released several hit songs, EPs, albums, and collaborations that have earned him a lot of fans and recognition. He has also won several awards and nominations that have validated his success and influence. He has also used social media to connect with his fans, promote his music, and showcase his personality. He is a rising star that you should not miss out on.
- If you want to download his new song 2022, "Mozama Disco" featuring Wande Coal, you can do so from various platforms such as his website, music websites, or streaming platforms. You can also follow him on his social media handles to stay updated on his music, events, activities, and more. You can also check out his other songs, EPs, albums, and collaborations that are available online. You will not regret it.
- Thank you for reading this article. We hope you enjoyed it and learned something new about Black Sherif and his music. If you did, please share it with your friends and family who might also be interested in Black Sherif's music. Also, feel free to leave a comment below and let us know what you think about Black Sherif and his new song 2022 download.
- FAQs
-Here are some of the frequently asked questions (FAQs) about Black Sherif and his new song 2022 download:
-
-- Q: What is Black Sherif's real name?
-- A: Black Sherif's real name is Mohammed Ismail Sharrif.
-- Q: When was Black Sherif born?
-- A: Black Sherif was born on January 9th, 2002 in Konongo-Zongo, in the Ashanti Region of Ghana.
-- Q: What is the title of Black Sherif's new song 2022?
-- A: The title of Black Sherif's new song 2022 is "Mozama Disco" featuring Wande Coal.
-- Q: When will Black Sherif's new song 2022 be released?
-- A: Black Sherif's new song 2022 will be released in January 2022.
-- Q: How can I download Black Sherif's new song 2022 for free?
-- A: You can download Black Sherif's new song 2022 for free from his website or from various music websites.
-
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diff --git a/spaces/1toTree/lora_test/ppdiffusers/schedulers/scheduling_pndm.py b/spaces/1toTree/lora_test/ppdiffusers/schedulers/scheduling_pndm.py
deleted file mode 100644
index 10c01ee0d7a4c5c191a3fc339ab21b6369374c15..0000000000000000000000000000000000000000
--- a/spaces/1toTree/lora_test/ppdiffusers/schedulers/scheduling_pndm.py
+++ /dev/null
@@ -1,423 +0,0 @@
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-# Copyright 2022 Zhejiang University Team and 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.
-
-# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
-
-import math
-from typing import List, Optional, Tuple, Union
-
-import numpy as np
-import paddle
-
-from ..configuration_utils import ConfigMixin, register_to_config
-from ..utils import _COMPATIBLE_STABLE_DIFFUSION_SCHEDULERS
-from .scheduling_utils import SchedulerMixin, SchedulerOutput
-
-
-def betas_for_alpha_bar(num_diffusion_timesteps, max_beta=0.999):
- """
- Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of
- (1-beta) over time from t = [0,1].
-
- Contains a function alpha_bar that takes an argument t and transforms it to the cumulative product of (1-beta) up
- to that part of the diffusion process.
-
-
- Args:
- num_diffusion_timesteps (`int`): the number of betas to produce.
- max_beta (`float`): the maximum beta to use; use values lower than 1 to
- prevent singularities.
-
- Returns:
- betas (`np.ndarray`): the betas used by the scheduler to step the model outputs
- """
-
- def alpha_bar(time_step):
- return math.cos((time_step + 0.008) / 1.008 * math.pi / 2) ** 2
-
- betas = []
- for i in range(num_diffusion_timesteps):
- t1 = i / num_diffusion_timesteps
- t2 = (i + 1) / num_diffusion_timesteps
- betas.append(min(1 - alpha_bar(t2) / alpha_bar(t1), max_beta))
- return paddle.to_tensor(betas, dtype="float32")
-
-
-class PNDMScheduler(SchedulerMixin, ConfigMixin):
- """
- Pseudo numerical methods for diffusion models (PNDM) proposes using more advanced ODE integration techniques,
- namely Runge-Kutta method and a linear multi-step method.
-
- [`~ConfigMixin`] takes care of storing all config attributes that are passed in the scheduler's `__init__`
- function, such as `num_train_timesteps`. They can be accessed via `scheduler.config.num_train_timesteps`.
- [`SchedulerMixin`] provides general loading and saving functionality via the [`SchedulerMixin.save_pretrained`] and
- [`~SchedulerMixin.from_pretrained`] functions.
-
- For more details, see the original paper: https://arxiv.org/abs/2202.09778
-
- Args:
- num_train_timesteps (`int`): number of diffusion steps used to train the model.
- beta_start (`float`): the starting `beta` value of inference.
- beta_end (`float`): the final `beta` value.
- beta_schedule (`str`):
- the beta schedule, a mapping from a beta range to a sequence of betas for stepping the model. Choose from
- `linear`, `scaled_linear`, or `squaredcos_cap_v2`.
- trained_betas (`np.ndarray`, optional):
- option to pass an array of betas directly to the constructor to bypass `beta_start`, `beta_end` etc.
- skip_prk_steps (`bool`):
- allows the scheduler to skip the Runge-Kutta steps that are defined in the original paper as being required
- before plms steps; defaults to `False`.
- set_alpha_to_one (`bool`, default `False`):
- each diffusion step uses the value of alphas product at that step and at the previous one. For the final
- step there is no previous alpha. When this option is `True` the previous alpha product is fixed to `1`,
- otherwise it uses the value of alpha at step 0.
- prediction_type (`str`, default `epsilon`, optional):
- prediction type of the scheduler function, one of `epsilon` (predicting the noise of the diffusion
- process), `sample` (directly predicting the noisy sample`) or `v_prediction` (see section 2.4
- https://imagen.research.google/video/paper.pdf)
- steps_offset (`int`, default `0`):
- an offset added to the inference steps. You can use a combination of `offset=1` and
- `set_alpha_to_one=False`, to make the last step use step 0 for the previous alpha product, as done in
- stable diffusion.
-
- """
-
- _compatibles = _COMPATIBLE_STABLE_DIFFUSION_SCHEDULERS.copy()
- order = 1
-
- @register_to_config
- def __init__(
- self,
- num_train_timesteps: int = 1000,
- beta_start: float = 0.0001,
- beta_end: float = 0.02,
- beta_schedule: str = "linear",
- trained_betas: Optional[Union[np.ndarray, List[float]]] = None,
- skip_prk_steps: bool = False,
- set_alpha_to_one: bool = False,
- prediction_type: str = "epsilon",
- steps_offset: int = 0,
- ):
- if trained_betas is not None:
- self.betas = paddle.to_tensor(trained_betas, dtype="float32")
- elif beta_schedule == "linear":
- self.betas = paddle.linspace(beta_start, beta_end, num_train_timesteps, dtype="float32")
- elif beta_schedule == "scaled_linear":
- # this schedule is very specific to the latent diffusion model.
- self.betas = paddle.linspace(beta_start**0.5, beta_end**0.5, num_train_timesteps, dtype="float32") ** 2
- elif beta_schedule == "squaredcos_cap_v2":
- # Glide cosine schedule
- self.betas = betas_for_alpha_bar(num_train_timesteps)
- else:
- raise NotImplementedError(f"{beta_schedule} does is not implemented for {self.__class__}")
-
- self.alphas = 1.0 - self.betas
- self.alphas_cumprod = paddle.cumprod(self.alphas, 0)
-
- self.final_alpha_cumprod = paddle.to_tensor(1.0) if set_alpha_to_one else self.alphas_cumprod[0]
-
- # standard deviation of the initial noise distribution
- self.init_noise_sigma = 1.0
-
- # For now we only support F-PNDM, i.e. the runge-kutta method
- # For more information on the algorithm please take a look at the paper: https://arxiv.org/pdf/2202.09778.pdf
- # mainly at formula (9), (12), (13) and the Algorithm 2.
- self.pndm_order = 4
-
- # running values
- self.cur_model_output = 0
- self.counter = 0
- self.cur_sample = None
- self.ets = []
-
- # setable values
- self.num_inference_steps = None
- self._timesteps = np.arange(0, num_train_timesteps)[::-1].copy()
- self.prk_timesteps = None
- self.plms_timesteps = None
- self.timesteps = None
-
- def set_timesteps(self, num_inference_steps: int):
- """
- Sets the discrete timesteps used for the diffusion chain. Supporting function to be run before inference.
-
- Args:
- num_inference_steps (`int`):
- the number of diffusion steps used when generating samples with a pre-trained model.
- """
-
- self.num_inference_steps = num_inference_steps
- step_ratio = self.config.num_train_timesteps // self.num_inference_steps
- # creates integer timesteps by multiplying by ratio
- # casting to int to avoid issues when num_inference_step is power of 3
- self._timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()
- self._timesteps += self.config.steps_offset
-
- if self.config.skip_prk_steps:
- # for some models like stable diffusion the prk steps can/should be skipped to
- # produce better results. When using PNDM with `self.config.skip_prk_steps` the implementation
- # is based on crowsonkb's PLMS sampler implementation: https://github.com/CompVis/latent-diffusion/pull/51
- self.prk_timesteps = np.array([])
- self.plms_timesteps = np.concatenate([self._timesteps[:-1], self._timesteps[-2:-1], self._timesteps[-1:]])[
- ::-1
- ].copy()
- else:
- prk_timesteps = np.array(self._timesteps[-self.pndm_order :]).repeat(2) + np.tile(
- np.array([0, self.config.num_train_timesteps // num_inference_steps // 2]), self.pndm_order
- )
- self.prk_timesteps = (prk_timesteps[:-1].repeat(2)[1:-1])[::-1].copy()
- self.plms_timesteps = self._timesteps[:-3][
- ::-1
- ].copy() # we copy to avoid having negative strides which are not supported by paddle
-
- timesteps = np.concatenate([self.prk_timesteps, self.plms_timesteps]).astype(np.int64)
- self.timesteps = paddle.to_tensor(timesteps)
-
- self.ets = []
- self.counter = 0
-
- def step(
- self,
- model_output: paddle.Tensor,
- timestep: int,
- sample: paddle.Tensor,
- return_dict: bool = True,
- ) -> Union[SchedulerOutput, Tuple]:
- """
- Predict the sample at the previous timestep by reversing the SDE. Core function to propagate the diffusion
- process from the learned model outputs (most often the predicted noise).
-
- This function calls `step_prk()` or `step_plms()` depending on the internal variable `counter`.
-
- Args:
- model_output (`paddle.Tensor`): direct output from learned diffusion model.
- timestep (`int`): current discrete timestep in the diffusion chain.
- sample (`paddle.Tensor`):
- current instance of sample being created by diffusion process.
- return_dict (`bool`): option for returning tuple rather than SchedulerOutput class
-
- Returns:
- [`~schedulers.scheduling_utils.SchedulerOutput`] or `tuple`:
- [`~schedulers.scheduling_utils.SchedulerOutput`] if `return_dict` is True, otherwise a `tuple`. When
- returning a tuple, the first element is the sample tensor.
-
- """
- if self.counter < len(self.prk_timesteps) and not self.config.skip_prk_steps:
- return self.step_prk(model_output=model_output, timestep=timestep, sample=sample, return_dict=return_dict)
- else:
- return self.step_plms(model_output=model_output, timestep=timestep, sample=sample, return_dict=return_dict)
-
- def step_prk(
- self,
- model_output: paddle.Tensor,
- timestep: int,
- sample: paddle.Tensor,
- return_dict: bool = True,
- ) -> Union[SchedulerOutput, Tuple]:
- """
- Step function propagating the sample with the Runge-Kutta method. RK takes 4 forward passes to approximate the
- solution to the differential equation.
-
- Args:
- model_output (`paddle.Tensor`): direct output from learned diffusion model.
- timestep (`int`): current discrete timestep in the diffusion chain.
- sample (`paddle.Tensor`):
- current instance of sample being created by diffusion process.
- return_dict (`bool`): option for returning tuple rather than SchedulerOutput class
-
- Returns:
- [`~scheduling_utils.SchedulerOutput`] or `tuple`: [`~scheduling_utils.SchedulerOutput`] if `return_dict` is
- True, otherwise a `tuple`. When returning a tuple, the first element is the sample tensor.
-
- """
- if self.num_inference_steps is None:
- raise ValueError(
- "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
- )
-
- diff_to_prev = 0 if self.counter % 2 else self.config.num_train_timesteps // self.num_inference_steps // 2
- prev_timestep = timestep - diff_to_prev
- timestep = self.prk_timesteps[self.counter // 4 * 4]
-
- if self.counter % 4 == 0:
- self.cur_model_output += 1 / 6 * model_output
- self.ets.append(model_output)
- self.cur_sample = sample
- elif (self.counter - 1) % 4 == 0:
- self.cur_model_output += 1 / 3 * model_output
- elif (self.counter - 2) % 4 == 0:
- self.cur_model_output += 1 / 3 * model_output
- elif (self.counter - 3) % 4 == 0:
- model_output = self.cur_model_output + 1 / 6 * model_output
- self.cur_model_output = 0
-
- # cur_sample should not be `None`
- cur_sample = self.cur_sample if self.cur_sample is not None else sample
-
- prev_sample = self._get_prev_sample(cur_sample, timestep, prev_timestep, model_output)
- self.counter += 1
-
- if not return_dict:
- return (prev_sample,)
-
- return SchedulerOutput(prev_sample=prev_sample)
-
- def step_plms(
- self,
- model_output: paddle.Tensor,
- timestep: int,
- sample: paddle.Tensor,
- return_dict: bool = True,
- ) -> Union[SchedulerOutput, Tuple]:
- """
- Step function propagating the sample with the linear multi-step method. This has one forward pass with multiple
- times to approximate the solution.
-
- Args:
- model_output (`paddle.Tensor`): direct output from learned diffusion model.
- timestep (`int`): current discrete timestep in the diffusion chain.
- sample (`paddle.Tensor`):
- current instance of sample being created by diffusion process.
- return_dict (`bool`): option for returning tuple rather than SchedulerOutput class
-
- Returns:
- [`~scheduling_utils.SchedulerOutput`] or `tuple`: [`~scheduling_utils.SchedulerOutput`] if `return_dict` is
- True, otherwise a `tuple`. When returning a tuple, the first element is the sample tensor.
-
- """
- if self.num_inference_steps is None:
- raise ValueError(
- "Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"
- )
-
- if not self.config.skip_prk_steps and len(self.ets) < 3:
- raise ValueError(
- f"{self.__class__} can only be run AFTER scheduler has been run "
- "in 'prk' mode for at least 12 iterations "
- "See: https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/pipeline_pndm.py "
- "for more information."
- )
-
- prev_timestep = timestep - self.config.num_train_timesteps // self.num_inference_steps
-
- if self.counter != 1:
- self.ets = self.ets[-3:]
- self.ets.append(model_output)
- else:
- prev_timestep = timestep
- timestep = timestep + self.config.num_train_timesteps // self.num_inference_steps
-
- if len(self.ets) == 1 and self.counter == 0:
- model_output = model_output
- self.cur_sample = sample
- elif len(self.ets) == 1 and self.counter == 1:
- model_output = (model_output + self.ets[-1]) / 2
- sample = self.cur_sample
- self.cur_sample = None
- elif len(self.ets) == 2:
- model_output = (3 * self.ets[-1] - self.ets[-2]) / 2
- elif len(self.ets) == 3:
- model_output = (23 * self.ets[-1] - 16 * self.ets[-2] + 5 * self.ets[-3]) / 12
- else:
- model_output = (1 / 24) * (55 * self.ets[-1] - 59 * self.ets[-2] + 37 * self.ets[-3] - 9 * self.ets[-4])
-
- prev_sample = self._get_prev_sample(sample, timestep, prev_timestep, model_output)
- self.counter += 1
-
- if not return_dict:
- return (prev_sample,)
-
- return SchedulerOutput(prev_sample=prev_sample)
-
- def scale_model_input(self, sample: paddle.Tensor, *args, **kwargs) -> paddle.Tensor:
- """
- Ensures interchangeability with schedulers that need to scale the denoising model input depending on the
- current timestep.
-
- Args:
- sample (`paddle.Tensor`): input sample
-
- Returns:
- `paddle.Tensor`: scaled input sample
- """
- return sample
-
- def _get_prev_sample(self, sample, timestep, prev_timestep, model_output):
- # See formula (9) of PNDM paper https://arxiv.org/pdf/2202.09778.pdf
- # this function computes x_(t−δ) using the formula of (9)
- # Note that x_t needs to be added to both sides of the equation
-
- # Notation ( ->
- # alpha_prod_t -> α_t
- # alpha_prod_t_prev -> α_(t−δ)
- # beta_prod_t -> (1 - α_t)
- # beta_prod_t_prev -> (1 - α_(t−δ))
- # sample -> x_t
- # model_output -> e_θ(x_t, t)
- # prev_sample -> x_(t−δ)
- alpha_prod_t = self.alphas_cumprod[timestep]
- alpha_prod_t_prev = self.alphas_cumprod[prev_timestep] if prev_timestep >= 0 else self.final_alpha_cumprod
- beta_prod_t = 1 - alpha_prod_t
- beta_prod_t_prev = 1 - alpha_prod_t_prev
-
- if self.config.prediction_type == "v_prediction":
- model_output = (alpha_prod_t**0.5) * model_output + (beta_prod_t**0.5) * sample
- elif self.config.prediction_type != "epsilon":
- raise ValueError(
- f"prediction_type given as {self.config.prediction_type} must be one of `epsilon` or `v_prediction`"
- )
-
- # corresponds to (α_(t−δ) - α_t) divided by
- # denominator of x_t in formula (9) and plus 1
- # Note: (α_(t−δ) - α_t) / (sqrt(α_t) * (sqrt(α_(t−δ)) + sqr(α_t))) =
- # sqrt(α_(t−δ)) / sqrt(α_t))
- sample_coeff = (alpha_prod_t_prev / alpha_prod_t) ** (0.5)
-
- # corresponds to denominator of e_θ(x_t, t) in formula (9)
- model_output_denom_coeff = alpha_prod_t * beta_prod_t_prev ** (0.5) + (
- alpha_prod_t * beta_prod_t * alpha_prod_t_prev
- ) ** (0.5)
-
- # full formula (9)
- prev_sample = (
- sample_coeff * sample - (alpha_prod_t_prev - alpha_prod_t) * model_output / model_output_denom_coeff
- )
-
- return prev_sample
-
- def add_noise(
- self,
- original_samples: paddle.Tensor,
- noise: paddle.Tensor,
- timesteps: paddle.Tensor,
- ) -> paddle.Tensor:
- # Make sure alphas_cumprod and timestep have same dtype as original_samples
- self.alphas_cumprod = self.alphas_cumprod.cast(original_samples.dtype)
-
- sqrt_alpha_prod = self.alphas_cumprod[timesteps] ** 0.5
- sqrt_alpha_prod = sqrt_alpha_prod.flatten()
- while len(sqrt_alpha_prod.shape) < len(original_samples.shape):
- sqrt_alpha_prod = sqrt_alpha_prod.unsqueeze(-1)
-
- sqrt_one_minus_alpha_prod = (1 - self.alphas_cumprod[timesteps]) ** 0.5
- sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.flatten()
- while len(sqrt_one_minus_alpha_prod.shape) < len(original_samples.shape):
- sqrt_one_minus_alpha_prod = sqrt_one_minus_alpha_prod.unsqueeze(-1)
-
- noisy_samples = sqrt_alpha_prod * original_samples + sqrt_one_minus_alpha_prod * noise
- return noisy_samples
-
- def __len__(self):
- return self.config.num_train_timesteps
diff --git a/spaces/1toTree/lora_test/ppdiffusers/utils/pil_utils.py b/spaces/1toTree/lora_test/ppdiffusers/utils/pil_utils.py
deleted file mode 100644
index 4b027229360e8eb58a67f0a7b636ce7ae0b2f249..0000000000000000000000000000000000000000
--- a/spaces/1toTree/lora_test/ppdiffusers/utils/pil_utils.py
+++ /dev/null
@@ -1,35 +0,0 @@
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-# 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 PIL.Image
-import PIL.ImageOps
-from packaging import version
-
-if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
- PIL_INTERPOLATION = {
- "linear": PIL.Image.Resampling.BILINEAR,
- "bilinear": PIL.Image.Resampling.BILINEAR,
- "bicubic": PIL.Image.Resampling.BICUBIC,
- "lanczos": PIL.Image.Resampling.LANCZOS,
- "nearest": PIL.Image.Resampling.NEAREST,
- }
-else:
- PIL_INTERPOLATION = {
- "linear": PIL.Image.LINEAR,
- "bilinear": PIL.Image.BILINEAR,
- "bicubic": PIL.Image.BICUBIC,
- "lanczos": PIL.Image.LANCZOS,
- "nearest": PIL.Image.NEAREST,
- }
diff --git a/spaces/2ndelement/voicevox/run.py b/spaces/2ndelement/voicevox/run.py
deleted file mode 100644
index f989d926683a347fcf6795dc879c3b2961fc7503..0000000000000000000000000000000000000000
--- a/spaces/2ndelement/voicevox/run.py
+++ /dev/null
@@ -1,1243 +0,0 @@
-import argparse
-import asyncio
-import base64
-import json
-import multiprocessing
-import os
-import re
-import sys
-import traceback
-import zipfile
-from functools import lru_cache
-from io import BytesIO, TextIOWrapper
-from pathlib import Path
-from tempfile import NamedTemporaryFile, TemporaryFile
-from typing import Dict, List, Optional
-
-import soundfile
-import uvicorn
-from fastapi import FastAPI, Form, HTTPException, Query, Request, Response
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import HTMLResponse, JSONResponse
-from fastapi.templating import Jinja2Templates
-from pydantic import ValidationError, conint
-from starlette.background import BackgroundTask
-from starlette.responses import FileResponse
-
-from voicevox_engine import __version__
-from voicevox_engine.cancellable_engine import CancellableEngine
-from voicevox_engine.downloadable_library import LibraryManager
-from voicevox_engine.engine_manifest import EngineManifestLoader
-from voicevox_engine.engine_manifest.EngineManifest import EngineManifest
-from voicevox_engine.kana_parser import create_kana, parse_kana
-from voicevox_engine.metas.MetasStore import MetasStore, construct_lookup
-from voicevox_engine.model import (
- AccentPhrase,
- AudioQuery,
- DownloadableLibrary,
- MorphableTargetInfo,
- ParseKanaBadRequest,
- ParseKanaError,
- Speaker,
- SpeakerInfo,
- SpeakerNotFoundError,
- SupportedDevicesInfo,
- UserDictWord,
- WordTypes,
-)
-from voicevox_engine.morphing import (
- get_morphable_targets,
- is_synthesis_morphing_permitted,
- synthesis_morphing,
-)
-from voicevox_engine.morphing import (
- synthesis_morphing_parameter as _synthesis_morphing_parameter,
-)
-from voicevox_engine.part_of_speech_data import MAX_PRIORITY, MIN_PRIORITY
-from voicevox_engine.preset import Preset, PresetError, PresetManager
-from voicevox_engine.setting import (
- USER_SETTING_PATH,
- CorsPolicyMode,
- Setting,
- SettingLoader,
-)
-from voicevox_engine.synthesis_engine import SynthesisEngineBase, make_synthesis_engines
-from voicevox_engine.user_dict import (
- apply_word,
- delete_word,
- import_user_dict,
- read_dict,
- rewrite_word,
- update_dict,
-)
-from voicevox_engine.utility import (
- ConnectBase64WavesException,
- connect_base64_waves,
- delete_file,
- engine_root,
- get_latest_core_version,
- get_save_dir,
-)
-
-
-def b64encode_str(s):
- return base64.b64encode(s).decode("utf-8")
-
-
-def set_output_log_utf8() -> None:
- """
- stdout/stderrのエンコーディングをUTF-8に切り替える関数
- """
- # コンソールがない環境だとNone https://docs.python.org/ja/3/library/sys.html#sys.__stdin__
- if sys.stdout is not None:
- # 必ずしもreconfigure()が実装されているとは限らない
- try:
- sys.stdout.reconfigure(encoding="utf-8")
- except AttributeError:
- # バッファを全て出力する
- sys.stdout.flush()
- sys.stdout = TextIOWrapper(
- sys.stdout.buffer, encoding="utf-8", errors="backslashreplace"
- )
- if sys.stderr is not None:
- try:
- sys.stderr.reconfigure(encoding="utf-8")
- except AttributeError:
- sys.stderr.flush()
- sys.stderr = TextIOWrapper(
- sys.stderr.buffer, encoding="utf-8", errors="backslashreplace"
- )
-
-
-def generate_app(
- synthesis_engines: Dict[str, SynthesisEngineBase],
- latest_core_version: str,
- setting_loader: SettingLoader,
- root_dir: Optional[Path] = None,
- cors_policy_mode: CorsPolicyMode = CorsPolicyMode.localapps,
- allow_origin: Optional[List[str]] = None,
-) -> FastAPI:
- if root_dir is None:
- root_dir = engine_root()
-
- default_sampling_rate = synthesis_engines[latest_core_version].default_sampling_rate
-
- app = FastAPI(
- title="VOICEVOX Engine",
- description="VOICEVOXの音声合成エンジンです。",
- version=__version__,
- )
-
- # CORS用のヘッダを生成するミドルウェア
- localhost_regex = "^https?://(localhost|127\\.0\\.0\\.1)(:[0-9]+)?$"
- compiled_localhost_regex = re.compile(localhost_regex)
- allowed_origins = ["*"]
- if cors_policy_mode == "localapps":
- allowed_origins = ["app://."]
- if allow_origin is not None:
- allowed_origins += allow_origin
- if "*" in allow_origin:
- print(
- 'WARNING: Deprecated use of argument "*" in allow_origin. '
- 'Use option "--cors_policy_mod all" instead. See "--help" for more.',
- file=sys.stderr,
- )
-
- app.add_middleware(
- CORSMiddleware,
- allow_origins=allowed_origins,
- allow_credentials=True,
- allow_origin_regex=localhost_regex,
- allow_methods=["*"],
- allow_headers=["*"],
- )
-
- # 許可されていないOriginを遮断するミドルウェア
- @app.middleware("http")
- async def block_origin_middleware(request: Request, call_next):
- isValidOrigin: bool = False
- if "Origin" not in request.headers: # Originのない純粋なリクエストの場合
- isValidOrigin = True
- elif "*" in allowed_origins: # すべてを許可する設定の場合
- isValidOrigin = True
- elif request.headers["Origin"] in allowed_origins: # Originが許可されている場合
- isValidOrigin = True
- elif compiled_localhost_regex.fullmatch(
- request.headers["Origin"]
- ): # localhostの場合
- isValidOrigin = True
-
- if isValidOrigin:
- return await call_next(request)
- else:
- return JSONResponse(
- status_code=403, content={"detail": "Origin not allowed"}
- )
-
- preset_manager = PresetManager(
- preset_path=root_dir / "presets.yaml",
- )
- engine_manifest_loader = EngineManifestLoader(
- root_dir / "engine_manifest.json", root_dir
- )
- library_manager = LibraryManager(get_save_dir() / "installed_libraries")
-
- metas_store = MetasStore(root_dir / "speaker_info")
-
- setting_ui_template = Jinja2Templates(directory=engine_root() / "ui_template")
-
- # キャッシュを有効化
- # モジュール側でlru_cacheを指定するとキャッシュを制御しにくいため、HTTPサーバ側で指定する
- # TODO: キャッシュを管理するモジュール側API・HTTP側APIを用意する
- synthesis_morphing_parameter = lru_cache(maxsize=4)(_synthesis_morphing_parameter)
-
- # @app.on_event("startup")
- # async def start_catch_disconnection():
- # if args.enable_cancellable_synthesis:
- # loop = asyncio.get_event_loop()
- # _ = loop.create_task(cancellable_engine.catch_disconnection())
-
- @app.on_event("startup")
- def apply_user_dict():
- update_dict()
-
- def get_engine(core_version: Optional[str]) -> SynthesisEngineBase:
- if core_version is None:
- return synthesis_engines[latest_core_version]
- if core_version in synthesis_engines:
- return synthesis_engines[core_version]
- raise HTTPException(status_code=422, detail="不明なバージョンです")
-
- @app.post(
- "/audio_query",
- response_model=AudioQuery,
- tags=["クエリ作成"],
- summary="音声合成用のクエリを作成する",
- )
- def audio_query(text: str, speaker: int, core_version: Optional[str] = None):
- """
- クエリの初期値を得ます。ここで得られたクエリはそのまま音声合成に利用できます。各値の意味は`Schemas`を参照してください。
- """
- engine = get_engine(core_version)
- accent_phrases = engine.create_accent_phrases(text, speaker_id=speaker)
- return AudioQuery(
- accent_phrases=accent_phrases,
- speedScale=1,
- pitchScale=0,
- intonationScale=1,
- volumeScale=1,
- prePhonemeLength=0.1,
- postPhonemeLength=0.1,
- outputSamplingRate=default_sampling_rate,
- outputStereo=False,
- kana=create_kana(accent_phrases),
- )
-
- @app.post(
- "/audio_query_from_preset",
- response_model=AudioQuery,
- tags=["クエリ作成"],
- summary="音声合成用のクエリをプリセットを用いて作成する",
- )
- def audio_query_from_preset(
- text: str, preset_id: int, core_version: Optional[str] = None
- ):
- """
- クエリの初期値を得ます。ここで得られたクエリはそのまま音声合成に利用できます。各値の意味は`Schemas`を参照してください。
- """
- engine = get_engine(core_version)
- try:
- presets = preset_manager.load_presets()
- except PresetError as err:
- raise HTTPException(status_code=422, detail=str(err))
- for preset in presets:
- if preset.id == preset_id:
- selected_preset = preset
- break
- else:
- raise HTTPException(status_code=422, detail="該当するプリセットIDが見つかりません")
-
- accent_phrases = engine.create_accent_phrases(
- text, speaker_id=selected_preset.style_id
- )
- return AudioQuery(
- accent_phrases=accent_phrases,
- speedScale=selected_preset.speedScale,
- pitchScale=selected_preset.pitchScale,
- intonationScale=selected_preset.intonationScale,
- volumeScale=selected_preset.volumeScale,
- prePhonemeLength=selected_preset.prePhonemeLength,
- postPhonemeLength=selected_preset.postPhonemeLength,
- outputSamplingRate=default_sampling_rate,
- outputStereo=False,
- kana=create_kana(accent_phrases),
- )
-
- @app.post(
- "/accent_phrases",
- response_model=List[AccentPhrase],
- tags=["クエリ編集"],
- summary="テキストからアクセント句を得る",
- responses={
- 400: {
- "description": "読み仮名のパースに失敗",
- "model": ParseKanaBadRequest,
- }
- },
- )
- def accent_phrases(
- text: str,
- speaker: int,
- is_kana: bool = False,
- core_version: Optional[str] = None,
- ):
- """
- テキストからアクセント句を得ます。
- is_kanaが`true`のとき、テキストは次のようなAquesTalkライクな記法に従う読み仮名として処理されます。デフォルトは`false`です。
- * 全てのカナはカタカナで記述される
- * アクセント句は`/`または`、`で区切る。`、`で区切った場合に限り無音区間が挿入される。
- * カナの手前に`_`を入れるとそのカナは無声化される
- * アクセント位置を`'`で指定する。全てのアクセント句にはアクセント位置を1つ指定する必要がある。
- * アクセント句末に`?`(全角)を入れることにより疑問文の発音ができる。
- """
- engine = get_engine(core_version)
- if is_kana:
- try:
- accent_phrases = parse_kana(text)
- except ParseKanaError as err:
- raise HTTPException(
- status_code=400,
- detail=ParseKanaBadRequest(err).dict(),
- )
- accent_phrases = engine.replace_mora_data(
- accent_phrases=accent_phrases, speaker_id=speaker
- )
-
- return accent_phrases
- else:
- return engine.create_accent_phrases(text, speaker_id=speaker)
-
- @app.post(
- "/mora_data",
- response_model=List[AccentPhrase],
- tags=["クエリ編集"],
- summary="アクセント句から音高・音素長を得る",
- )
- def mora_data(
- accent_phrases: List[AccentPhrase],
- speaker: int,
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- return engine.replace_mora_data(accent_phrases, speaker_id=speaker)
-
- @app.post(
- "/mora_length",
- response_model=List[AccentPhrase],
- tags=["クエリ編集"],
- summary="アクセント句から音素長を得る",
- )
- def mora_length(
- accent_phrases: List[AccentPhrase],
- speaker: int,
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- return engine.replace_phoneme_length(
- accent_phrases=accent_phrases, speaker_id=speaker
- )
-
- @app.post(
- "/mora_pitch",
- response_model=List[AccentPhrase],
- tags=["クエリ編集"],
- summary="アクセント句から音高を得る",
- )
- def mora_pitch(
- accent_phrases: List[AccentPhrase],
- speaker: int,
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- return engine.replace_mora_pitch(
- accent_phrases=accent_phrases, speaker_id=speaker
- )
-
- @app.post(
- "/synthesis",
- response_class=FileResponse,
- responses={
- 200: {
- "content": {
- "audio/wav": {"schema": {"type": "string", "format": "binary"}}
- },
- }
- },
- tags=["音声合成"],
- summary="音声合成する",
- )
- def synthesis(
- query: AudioQuery,
- speaker: int,
- enable_interrogative_upspeak: bool = Query( # noqa: B008
- default=True,
- description="疑問系のテキストが与えられたら語尾を自動調整する",
- ),
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- wave = engine.synthesis(
- query=query,
- speaker_id=speaker,
- enable_interrogative_upspeak=enable_interrogative_upspeak,
- )
-
- with NamedTemporaryFile(delete=False) as f:
- soundfile.write(
- file=f, data=wave, samplerate=query.outputSamplingRate, format="WAV"
- )
-
- return FileResponse(
- f.name,
- media_type="audio/wav",
- background=BackgroundTask(delete_file, f.name),
- )
-
- @app.post(
- "/cancellable_synthesis",
- response_class=FileResponse,
- responses={
- 200: {
- "content": {
- "audio/wav": {"schema": {"type": "string", "format": "binary"}}
- },
- }
- },
- tags=["音声合成"],
- summary="音声合成する(キャンセル可能)",
- )
- def cancellable_synthesis(
- query: AudioQuery,
- speaker: int,
- request: Request,
- core_version: Optional[str] = None,
- ):
- if not args.enable_cancellable_synthesis:
- raise HTTPException(
- status_code=404,
- detail="実験的機能はデフォルトで無効になっています。使用するには引数を指定してください。",
- )
- f_name = cancellable_engine._synthesis_impl(
- query=query,
- speaker_id=speaker,
- request=request,
- core_version=core_version,
- )
- if f_name == "":
- raise HTTPException(status_code=422, detail="不明なバージョンです")
-
- return FileResponse(
- f_name,
- media_type="audio/wav",
- background=BackgroundTask(delete_file, f_name),
- )
-
- @app.post(
- "/multi_synthesis",
- response_class=FileResponse,
- responses={
- 200: {
- "content": {
- "application/zip": {
- "schema": {"type": "string", "format": "binary"}
- }
- },
- }
- },
- tags=["音声合成"],
- summary="複数まとめて音声合成する",
- )
- def multi_synthesis(
- queries: List[AudioQuery],
- speaker: int,
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- sampling_rate = queries[0].outputSamplingRate
-
- with NamedTemporaryFile(delete=False) as f:
-
- with zipfile.ZipFile(f, mode="a") as zip_file:
-
- for i in range(len(queries)):
-
- if queries[i].outputSamplingRate != sampling_rate:
- raise HTTPException(
- status_code=422, detail="サンプリングレートが異なるクエリがあります"
- )
-
- with TemporaryFile() as wav_file:
-
- wave = engine.synthesis(query=queries[i], speaker_id=speaker)
- soundfile.write(
- file=wav_file,
- data=wave,
- samplerate=sampling_rate,
- format="WAV",
- )
- wav_file.seek(0)
- zip_file.writestr(f"{str(i + 1).zfill(3)}.wav", wav_file.read())
-
- return FileResponse(
- f.name,
- media_type="application/zip",
- background=BackgroundTask(delete_file, f.name),
- )
-
- @app.post(
- "/morphable_targets",
- response_model=List[Dict[str, MorphableTargetInfo]],
- tags=["音声合成"],
- summary="指定した話者に対してエンジン内の話者がモーフィングが可能か判定する",
- )
- def morphable_targets(
- base_speakers: List[int],
- core_version: Optional[str] = None,
- ):
- """
- 指定されたベース話者に対してエンジン内の各話者がモーフィング機能を利用可能か返します。
- モーフィングの許可/禁止は`/speakers`の`speaker.supported_features.synthesis_morphing`に記載されています。
- プロパティが存在しない場合は、モーフィングが許可されているとみなします。
- 返り値の話者はstring型なので注意。
- """
- engine = get_engine(core_version)
-
- try:
- speakers = metas_store.load_combined_metas(engine=engine)
- morphable_targets = get_morphable_targets(
- speakers=speakers, base_speakers=base_speakers
- )
- # jsonはint型のキーを持てないので、string型に変換する
- return [
- {str(k): v for k, v in morphable_target.items()}
- for morphable_target in morphable_targets
- ]
- except SpeakerNotFoundError as e:
- raise HTTPException(
- status_code=404, detail=f"該当する話者(speaker={e.speaker})が見つかりません"
- )
-
- @app.post(
- "/synthesis_morphing",
- response_class=FileResponse,
- responses={
- 200: {
- "content": {
- "audio/wav": {"schema": {"type": "string", "format": "binary"}}
- },
- }
- },
- tags=["音声合成"],
- summary="2人の話者でモーフィングした音声を合成する",
- )
- def _synthesis_morphing(
- query: AudioQuery,
- base_speaker: int,
- target_speaker: int,
- morph_rate: float = Query(..., ge=0.0, le=1.0), # noqa: B008
- core_version: Optional[str] = None,
- ):
- """
- 指定された2人の話者で音声を合成、指定した割合でモーフィングした音声を得ます。
- モーフィングの割合は`morph_rate`で指定でき、0.0でベースの話者、1.0でターゲットの話者に近づきます。
- """
- engine = get_engine(core_version)
-
- try:
- speakers = metas_store.load_combined_metas(engine=engine)
- speaker_lookup = construct_lookup(speakers=speakers)
- is_permitted = is_synthesis_morphing_permitted(
- speaker_lookup, base_speaker, target_speaker
- )
- if not is_permitted:
- raise HTTPException(
- status_code=400,
- detail="指定された話者ペアでのモーフィングはできません",
- )
- except SpeakerNotFoundError as e:
- raise HTTPException(
- status_code=404, detail=f"該当する話者(speaker={e.speaker})が見つかりません"
- )
-
- # 生成したパラメータはキャッシュされる
- morph_param = synthesis_morphing_parameter(
- engine=engine,
- query=query,
- base_speaker=base_speaker,
- target_speaker=target_speaker,
- )
-
- morph_wave = synthesis_morphing(
- morph_param=morph_param,
- morph_rate=morph_rate,
- output_fs=query.outputSamplingRate,
- output_stereo=query.outputStereo,
- )
-
- with NamedTemporaryFile(delete=False) as f:
- soundfile.write(
- file=f,
- data=morph_wave,
- samplerate=query.outputSamplingRate,
- format="WAV",
- )
-
- return FileResponse(
- f.name,
- media_type="audio/wav",
- background=BackgroundTask(delete_file, f.name),
- )
-
- @app.post(
- "/connect_waves",
- response_class=FileResponse,
- responses={
- 200: {
- "content": {
- "audio/wav": {"schema": {"type": "string", "format": "binary"}}
- },
- }
- },
- tags=["その他"],
- summary="base64エンコードされた複数のwavデータを一つに結合する",
- )
- def connect_waves(waves: List[str]):
- """
- base64エンコードされたwavデータを一纏めにし、wavファイルで返します。
- """
- try:
- waves_nparray, sampling_rate = connect_base64_waves(waves)
- except ConnectBase64WavesException as err:
- return HTTPException(status_code=422, detail=str(err))
-
- with NamedTemporaryFile(delete=False) as f:
- soundfile.write(
- file=f,
- data=waves_nparray,
- samplerate=sampling_rate,
- format="WAV",
- )
-
- return FileResponse(
- f.name,
- media_type="audio/wav",
- background=BackgroundTask(delete_file, f.name),
- )
-
- @app.get("/presets", response_model=List[Preset], tags=["その他"])
- def get_presets():
- """
- エンジンが保持しているプリセットの設定を返します
-
- Returns
- -------
- presets: List[Preset]
- プリセットのリスト
- """
- try:
- presets = preset_manager.load_presets()
- except PresetError as err:
- raise HTTPException(status_code=422, detail=str(err))
- return presets
-
- @app.post("/add_preset", response_model=int, tags=["その他"])
- def add_preset(preset: Preset):
- """
- 新しいプリセットを追加します
-
- Parameters
- -------
- preset: Preset
- 新しいプリセット。
- プリセットIDが既存のものと重複している場合は、新規のプリセットIDが採番されます。
-
- Returns
- -------
- id: int
- 追加したプリセットのプリセットID
- """
- try:
- id = preset_manager.add_preset(preset)
- except PresetError as err:
- raise HTTPException(status_code=422, detail=str(err))
- return id
-
- @app.post("/update_preset", response_model=int, tags=["その他"])
- def update_preset(preset: Preset):
- """
- 既存のプリセットを更新します
-
- Parameters
- -------
- preset: Preset
- 更新するプリセット。
- プリセットIDが更新対象と一致している必要があります。
-
- Returns
- -------
- id: int
- 更新したプリセットのプリセットID
- """
- try:
- id = preset_manager.update_preset(preset)
- except PresetError as err:
- raise HTTPException(status_code=422, detail=str(err))
- return id
-
- @app.post("/delete_preset", status_code=204, tags=["その他"])
- def delete_preset(id: int):
- """
- 既存のプリセットを削除します
-
- Parameters
- -------
- id: int
- 削除するプリセットのプリセットID
-
- """
- try:
- preset_manager.delete_preset(id)
- except PresetError as err:
- raise HTTPException(status_code=422, detail=str(err))
- return Response(status_code=204)
-
- @app.get("/version", tags=["その他"])
- def version() -> str:
- return __version__
-
- @app.get("/core_versions", response_model=List[str], tags=["その他"])
- def core_versions() -> List[str]:
- return Response(
- content=json.dumps(list(synthesis_engines.keys())),
- media_type="application/json",
- )
-
- @app.get("/speakers", response_model=List[Speaker], tags=["その他"])
- def speakers(
- core_version: Optional[str] = None,
- ):
- engine = get_engine(core_version)
- return metas_store.load_combined_metas(engine=engine)
-
- @app.get("/speaker_info", response_model=SpeakerInfo, tags=["その他"])
- def speaker_info(speaker_uuid: str, core_version: Optional[str] = None):
- """
- 指定されたspeaker_uuidに関する情報をjson形式で返します。
- 画像や音声はbase64エンコードされたものが返されます。
-
- Returns
- -------
- ret_data: SpeakerInfo
- """
- speakers = json.loads(get_engine(core_version).speakers)
- for i in range(len(speakers)):
- if speakers[i]["speaker_uuid"] == speaker_uuid:
- speaker = speakers[i]
- break
- else:
- raise HTTPException(status_code=404, detail="該当する話者が見つかりません")
-
- try:
- policy = (root_dir / f"speaker_info/{speaker_uuid}/policy.md").read_text(
- "utf-8"
- )
- portrait = b64encode_str(
- (root_dir / f"speaker_info/{speaker_uuid}/portrait.png").read_bytes()
- )
- style_infos = []
- for style in speaker["styles"]:
- id = style["id"]
- icon = b64encode_str(
- (
- root_dir / f"speaker_info/{speaker_uuid}/icons/{id}.png"
- ).read_bytes()
- )
- style_portrait_path = (
- root_dir / f"speaker_info/{speaker_uuid}/portraits/{id}.png"
- )
- style_portrait = (
- b64encode_str(style_portrait_path.read_bytes())
- if style_portrait_path.exists()
- else None
- )
- voice_samples = [
- b64encode_str(
- (
- root_dir
- / "speaker_info/{}/voice_samples/{}_{}.wav".format(
- speaker_uuid, id, str(j + 1).zfill(3)
- )
- ).read_bytes()
- )
- for j in range(3)
- ]
- style_infos.append(
- {
- "id": id,
- "icon": icon,
- "portrait": style_portrait,
- "voice_samples": voice_samples,
- }
- )
- except FileNotFoundError:
- import traceback
-
- traceback.print_exc()
- raise HTTPException(status_code=500, detail="追加情報が見つかりませんでした")
-
- ret_data = {"policy": policy, "portrait": portrait, "style_infos": style_infos}
- return ret_data
-
- @app.get(
- "/downloadable_libraries",
- response_model=List[DownloadableLibrary],
- tags=["音声ライブラリ管理"],
- )
- def downloadable_libraries():
- """
- ダウンロード可能な音声ライブラリの情報を返します。
-
- Returns
- -------
- ret_data: List[DownloadableLibrary]
- """
- manifest = engine_manifest_loader.load_manifest()
- if not manifest.supported_features.manage_library:
- raise HTTPException(status_code=404, detail="この機能は実装されていません")
- return library_manager.downloadable_libraries()
-
- @app.get(
- "/installed_libraries",
- response_model=List[DownloadableLibrary],
- tags=["音声ライブラリ管理"],
- )
- def installed_libraries():
- """
- インストールした音声ライブラリの情報を返します。
-
- Returns
- -------
- ret_data: List[DownloadableLibrary]
- """
- manifest = engine_manifest_loader.load_manifest()
- if not manifest.supported_features.manage_library:
- raise HTTPException(status_code=404, detail="この機能は実装されていません")
- return library_manager.installed_libraries()
-
- @app.post(
- "/install_library/{library_uuid}",
- status_code=204,
- tags=["音声ライブラリ管理"],
- )
- async def install_library(library_uuid: str, request: Request):
- """
- 音声ライブラリをインストールします。
- 音声ライブラリのZIPファイルをリクエストボディとして送信してください。
-
- Parameters
- ----------
- library_uuid: str
- 音声ライブラリのID
- """
- manifest = engine_manifest_loader.load_manifest()
- if not manifest.supported_features.manage_library:
- raise HTTPException(status_code=404, detail="この機能は実装されていません")
- archive = BytesIO(await request.body())
- loop = asyncio.get_event_loop()
- await loop.run_in_executor(
- None, library_manager.install_library, library_uuid, archive
- )
- return Response(status_code=204)
-
- @app.post("/initialize_speaker", status_code=204, tags=["その他"])
- def initialize_speaker(
- speaker: int,
- skip_reinit: bool = Query( # noqa: B008
- False, description="既に初期化済みの話者の再初期化をスキップするかどうか"
- ),
- core_version: Optional[str] = None,
- ):
- """
- 指定されたspeaker_idの話者を初期化します。
- 実行しなくても他のAPIは使用できますが、初回実行時に時間がかかることがあります。
- """
- engine = get_engine(core_version)
- engine.initialize_speaker_synthesis(speaker_id=speaker, skip_reinit=skip_reinit)
- return Response(status_code=204)
-
- @app.get("/is_initialized_speaker", response_model=bool, tags=["その他"])
- def is_initialized_speaker(speaker: int, core_version: Optional[str] = None):
- """
- 指定されたspeaker_idの話者が初期化されているかどうかを返します。
- """
- engine = get_engine(core_version)
- return engine.is_initialized_speaker_synthesis(speaker)
-
- @app.get("/user_dict", response_model=Dict[str, UserDictWord], tags=["ユーザー辞書"])
- def get_user_dict_words():
- """
- ユーザー辞書に登録されている単語の一覧を返します。
- 単語の表層形(surface)は正規化済みの物を返します。
-
- Returns
- -------
- Dict[str, UserDictWord]
- 単語のUUIDとその詳細
- """
- try:
- return read_dict()
- except Exception:
- traceback.print_exc()
- raise HTTPException(status_code=422, detail="辞書の読み込みに失敗しました。")
-
- @app.post("/user_dict_word", response_model=str, tags=["ユーザー辞書"])
- def add_user_dict_word(
- surface: str,
- pronunciation: str,
- accent_type: int,
- word_type: Optional[WordTypes] = None,
- priority: Optional[conint(ge=MIN_PRIORITY, le=MAX_PRIORITY)] = None,
- ):
- """
- ユーザー辞書に言葉を追加します。
-
- Parameters
- ----------
- surface : str
- 言葉の表層形
- pronunciation: str
- 言葉の発音(カタカナ)
- accent_type: int
- アクセント型(音が下がる場所を指す)
- word_type: WordTypes, optional
- PROPER_NOUN(固有名詞)、COMMON_NOUN(普通名詞)、VERB(動詞)、ADJECTIVE(形容詞)、SUFFIX(語尾)のいずれか
- priority: int, optional
- 単語の優先度(0から10までの整数)
- 数字が大きいほど優先度が高くなる
- 1から9までの値を指定することを推奨
- """
- try:
- word_uuid = apply_word(
- surface=surface,
- pronunciation=pronunciation,
- accent_type=accent_type,
- word_type=word_type,
- priority=priority,
- )
- return Response(content=word_uuid)
- except ValidationError as e:
- raise HTTPException(status_code=422, detail="パラメータに誤りがあります。\n" + str(e))
- except Exception:
- traceback.print_exc()
- raise HTTPException(status_code=422, detail="ユーザー辞書への追加に失敗しました。")
-
- @app.put("/user_dict_word/{word_uuid}", status_code=204, tags=["ユーザー辞書"])
- def rewrite_user_dict_word(
- surface: str,
- pronunciation: str,
- accent_type: int,
- word_uuid: str,
- word_type: Optional[WordTypes] = None,
- priority: Optional[conint(ge=MIN_PRIORITY, le=MAX_PRIORITY)] = None,
- ):
- """
- ユーザー辞書に登録されている言葉を更新します。
-
- Parameters
- ----------
- surface : str
- 言葉の表層形
- pronunciation: str
- 言葉の発音(カタカナ)
- accent_type: int
- アクセント型(音が下がる場所を指す)
- word_uuid: str
- 更新する言葉のUUID
- word_type: WordTypes, optional
- PROPER_NOUN(固有名詞)、COMMON_NOUN(普通名詞)、VERB(動詞)、ADJECTIVE(形容詞)、SUFFIX(語尾)のいずれか
- priority: int, optional
- 単語の優先度(0から10までの整数)
- 数字が大きいほど優先度が高くなる
- 1から9までの値を指定することを推奨
- """
- try:
- rewrite_word(
- surface=surface,
- pronunciation=pronunciation,
- accent_type=accent_type,
- word_uuid=word_uuid,
- word_type=word_type,
- priority=priority,
- )
- return Response(status_code=204)
- except HTTPException:
- raise
- except ValidationError as e:
- raise HTTPException(status_code=422, detail="パラメータに誤りがあります。\n" + str(e))
- except Exception:
- traceback.print_exc()
- raise HTTPException(status_code=422, detail="ユーザー辞書の更新に失敗しました。")
-
- @app.delete("/user_dict_word/{word_uuid}", status_code=204, tags=["ユーザー辞書"])
- def delete_user_dict_word(word_uuid: str):
- """
- ユーザー辞書に登録されている言葉を削除します。
-
- Parameters
- ----------
- word_uuid: str
- 削除する言葉のUUID
- """
- try:
- delete_word(word_uuid=word_uuid)
- return Response(status_code=204)
- except HTTPException:
- raise
- except Exception:
- traceback.print_exc()
- raise HTTPException(status_code=422, detail="ユーザー辞書の更新に失敗しました。")
-
- @app.post("/import_user_dict", status_code=204, tags=["ユーザー辞書"])
- def import_user_dict_words(
- import_dict_data: Dict[str, UserDictWord], override: bool
- ):
- """
- 他のユーザー辞書をインポートします。
-
- Parameters
- ----------
- import_dict_data: Dict[str, UserDictWord]
- インポートするユーザー辞書のデータ
- override: bool
- 重複したエントリがあった場合、上書きするかどうか
- """
- try:
- import_user_dict(dict_data=import_dict_data, override=override)
- return Response(status_code=204)
- except Exception:
- traceback.print_exc()
- raise HTTPException(status_code=422, detail="ユーザー辞書のインポートに失敗しました。")
-
- @app.get("/supported_devices", response_model=SupportedDevicesInfo, tags=["その他"])
- def supported_devices(
- core_version: Optional[str] = None,
- ):
- supported_devices = get_engine(core_version).supported_devices
- if supported_devices is None:
- raise HTTPException(status_code=422, detail="非対応の機能です。")
- return Response(
- content=supported_devices,
- media_type="application/json",
- )
-
- @app.get("/engine_manifest", response_model=EngineManifest, tags=["その他"])
- def engine_manifest():
- return engine_manifest_loader.load_manifest()
-
- @app.get("/setting", response_class=HTMLResponse, tags=["設定"])
- def setting_get(request: Request):
- settings = setting_loader.load_setting_file()
-
- cors_policy_mode = settings.cors_policy_mode
- allow_origin = settings.allow_origin
-
- if allow_origin is None:
- allow_origin = ""
-
- return setting_ui_template.TemplateResponse(
- "ui.html",
- {
- "request": request,
- "cors_policy_mode": cors_policy_mode,
- "allow_origin": allow_origin,
- },
- )
-
- @app.post("/setting", response_class=HTMLResponse, tags=["設定"])
- def setting_post(
- request: Request,
- cors_policy_mode: Optional[str] = Form(None), # noqa: B008
- allow_origin: Optional[str] = Form(None), # noqa: B008
- ):
- settings = Setting(
- cors_policy_mode=cors_policy_mode,
- allow_origin=allow_origin,
- )
-
- # 更新した設定へ上書き
- setting_loader.dump_setting_file(settings)
-
- if allow_origin is None:
- allow_origin = ""
-
- return setting_ui_template.TemplateResponse(
- "ui.html",
- {
- "request": request,
- "cors_policy_mode": cors_policy_mode,
- "allow_origin": allow_origin,
- },
- )
-
- return app
-
-
-if __name__ == "__main__":
- multiprocessing.freeze_support()
-
- output_log_utf8 = os.getenv("VV_OUTPUT_LOG_UTF8", default="")
- if output_log_utf8 == "1":
- set_output_log_utf8()
- elif not (output_log_utf8 == "" or output_log_utf8 == "0"):
- print(
- "WARNING: invalid VV_OUTPUT_LOG_UTF8 environment variable value",
- file=sys.stderr,
- )
-
- default_cors_policy_mode = CorsPolicyMode.localapps
-
- parser = argparse.ArgumentParser(description="VOICEVOX のエンジンです。")
- parser.add_argument(
- "--host", type=str, default="127.0.0.1", help="接続を受け付けるホストアドレスです。"
- )
- parser.add_argument("--port", type=int, default=50021, help="接続を受け付けるポート番号です。")
- parser.add_argument(
- "--use_gpu", action="store_true", help="指定するとGPUを使って音声合成するようになります。"
- )
- parser.add_argument(
- "--voicevox_dir", type=Path, default=None, help="VOICEVOXのディレクトリパスです。"
- )
- parser.add_argument(
- "--voicelib_dir",
- type=Path,
- default=None,
- action="append",
- help="VOICEVOX COREのディレクトリパスです。",
- )
- parser.add_argument(
- "--runtime_dir",
- type=Path,
- default=None,
- action="append",
- help="VOICEVOX COREで使用するライブラリのディレクトリパスです。",
- )
- parser.add_argument(
- "--enable_mock",
- action="store_true",
- help="指定するとVOICEVOX COREを使わずモックで音声合成を行います。",
- )
- parser.add_argument(
- "--enable_cancellable_synthesis",
- action="store_true",
- help="指定すると音声合成を途中でキャンセルできるようになります。",
- )
- parser.add_argument("--init_processes", type=int, default=2)
- parser.add_argument(
- "--load_all_models", action="store_true", help="指定すると起動時に全ての音声合成モデルを読み込みます。"
- )
-
- # 引数へcpu_num_threadsの指定がなければ、環境変数をロールします。
- # 環境変数にもない場合は、Noneのままとします。
- # VV_CPU_NUM_THREADSが空文字列でなく数値でもない場合、エラー終了します。
- parser.add_argument(
- "--cpu_num_threads",
- type=int,
- default=os.getenv("VV_CPU_NUM_THREADS") or None,
- help=(
- "音声合成を行うスレッド数です。指定しないと、代わりに環境変数VV_CPU_NUM_THREADSの値が使われます。"
- "VV_CPU_NUM_THREADSが空文字列でなく数値でもない場合はエラー終了します。"
- ),
- )
-
- parser.add_argument(
- "--output_log_utf8",
- action="store_true",
- help=(
- "指定するとログ出力をUTF-8でおこないます。指定しないと、代わりに環境変数 VV_OUTPUT_LOG_UTF8 の値が使われます。"
- "VV_OUTPUT_LOG_UTF8 の値が1の場合はUTF-8で、0または空文字、値がない場合は環境によって自動的に決定されます。"
- ),
- )
-
- parser.add_argument(
- "--cors_policy_mode",
- type=CorsPolicyMode,
- choices=list(CorsPolicyMode),
- default=None,
- help=(
- "CORSの許可モード。allまたはlocalappsが指定できます。allはすべてを許可します。"
- "localappsはオリジン間リソース共有ポリシーを、app://.とlocalhost関連に限定します。"
- "その他のオリジンはallow_originオプションで追加できます。デフォルトはlocalapps。"
- ),
- )
-
- parser.add_argument(
- "--allow_origin", nargs="*", help="許可するオリジンを指定します。スペースで区切ることで複数指定できます。"
- )
-
- parser.add_argument(
- "--setting_file", type=Path, default=USER_SETTING_PATH, help="設定ファイルを指定できます。"
- )
-
- args = parser.parse_args()
-
- if args.output_log_utf8:
- set_output_log_utf8()
-
- cpu_num_threads: Optional[int] = args.cpu_num_threads
-
- synthesis_engines = make_synthesis_engines(
- use_gpu=args.use_gpu,
- voicelib_dirs=args.voicelib_dir,
- voicevox_dir=args.voicevox_dir,
- runtime_dirs=args.runtime_dir,
- cpu_num_threads=cpu_num_threads,
- enable_mock=args.enable_mock,
- load_all_models=args.load_all_models,
- )
- assert len(synthesis_engines) != 0, "音声合成エンジンがありません。"
- latest_core_version = get_latest_core_version(versions=synthesis_engines.keys())
-
- cancellable_engine = None
- if args.enable_cancellable_synthesis:
- cancellable_engine = CancellableEngine(args)
-
- root_dir = args.voicevox_dir if args.voicevox_dir is not None else engine_root()
-
- setting_loader = SettingLoader(args.setting_file)
-
- settings = setting_loader.load_setting_file()
-
- cors_policy_mode = (
- args.cors_policy_mode
- if args.cors_policy_mode is not None
- else settings.cors_policy_mode
- )
-
- allow_origin = None
- if args.allow_origin is not None:
- allow_origin = args.allow_origin
- elif settings.allow_origin is not None:
- allow_origin = settings.allow_origin.split(" ")
-
- uvicorn.run(
- generate_app(
- synthesis_engines,
- latest_core_version,
- setting_loader,
- root_dir=root_dir,
- cors_policy_mode=cors_policy_mode,
- allow_origin=allow_origin,
- ),
- host=args.host,
- port=args.port,
- )
diff --git a/spaces/7hao/bingo/src/components/chat-header.tsx b/spaces/7hao/bingo/src/components/chat-header.tsx
deleted file mode 100644
index c6664b8dee61179f844d45c5bd650518fc2cb4c2..0000000000000000000000000000000000000000
--- a/spaces/7hao/bingo/src/components/chat-header.tsx
+++ /dev/null
@@ -1,12 +0,0 @@
-import LogoIcon from '@/assets/images/logo.svg'
-import Image from 'next/image'
-
-export function ChatHeader() {
- return (
-
-
- 欢迎使用新必应
- 由 AI 支持的网页版 Copilot
-
- )
-}
diff --git a/spaces/AIGC-Audio/AudioGPT/audio_detection/audio_infer/pytorch/finetune_template.py b/spaces/AIGC-Audio/AudioGPT/audio_detection/audio_infer/pytorch/finetune_template.py
deleted file mode 100644
index dd43e462c47857f805b1ef4d345711354a1cff3d..0000000000000000000000000000000000000000
--- a/spaces/AIGC-Audio/AudioGPT/audio_detection/audio_infer/pytorch/finetune_template.py
+++ /dev/null
@@ -1,127 +0,0 @@
-import os
-import sys
-sys.path.insert(1, os.path.join(sys.path[0], '../utils'))
-import numpy as np
-import argparse
-import h5py
-import math
-import time
-import logging
-import matplotlib.pyplot as plt
-
-import torch
-torch.backends.cudnn.benchmark=True
-torch.manual_seed(0)
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
-import torch.utils.data
-
-from utilities import get_filename
-from models import *
-import config
-
-
-class Transfer_Cnn14(nn.Module):
- def __init__(self, sample_rate, window_size, hop_size, mel_bins, fmin,
- fmax, classes_num, freeze_base):
- """Classifier for a new task using pretrained Cnn14 as a sub module.
- """
- super(Transfer_Cnn14, self).__init__()
- audioset_classes_num = 527
-
- self.base = Cnn14(sample_rate, window_size, hop_size, mel_bins, fmin,
- fmax, audioset_classes_num)
-
- # Transfer to another task layer
- self.fc_transfer = nn.Linear(2048, classes_num, bias=True)
-
- if freeze_base:
- # Freeze AudioSet pretrained layers
- for param in self.base.parameters():
- param.requires_grad = False
-
- self.init_weights()
-
- def init_weights(self):
- init_layer(self.fc_transfer)
-
- def load_from_pretrain(self, pretrained_checkpoint_path):
- checkpoint = torch.load(pretrained_checkpoint_path)
- self.base.load_state_dict(checkpoint['model'])
-
- def forward(self, input, mixup_lambda=None):
- """Input: (batch_size, data_length)
- """
- output_dict = self.base(input, mixup_lambda)
- embedding = output_dict['embedding']
-
- clipwise_output = torch.log_softmax(self.fc_transfer(embedding), dim=-1)
- output_dict['clipwise_output'] = clipwise_output
-
- return output_dict
-
-
-def train(args):
-
- # Arugments & parameters
- sample_rate = args.sample_rate
- window_size = args.window_size
- hop_size = args.hop_size
- mel_bins = args.mel_bins
- fmin = args.fmin
- fmax = args.fmax
- model_type = args.model_type
- pretrained_checkpoint_path = args.pretrained_checkpoint_path
- freeze_base = args.freeze_base
- device = 'cuda' if (args.cuda and torch.cuda.is_available()) else 'cpu'
-
- classes_num = config.classes_num
- pretrain = True if pretrained_checkpoint_path else False
-
- # Model
- Model = eval(model_type)
- model = Model(sample_rate, window_size, hop_size, mel_bins, fmin, fmax,
- classes_num, freeze_base)
-
- # Load pretrained model
- if pretrain:
- logging.info('Load pretrained model from {}'.format(pretrained_checkpoint_path))
- model.load_from_pretrain(pretrained_checkpoint_path)
-
- # Parallel
- print('GPU number: {}'.format(torch.cuda.device_count()))
- model = torch.nn.DataParallel(model)
-
- if 'cuda' in device:
- model.to(device)
-
- print('Load pretrained model successfully!')
-
-
-if __name__ == '__main__':
- parser = argparse.ArgumentParser(description='Example of parser. ')
- subparsers = parser.add_subparsers(dest='mode')
-
- # Train
- parser_train = subparsers.add_parser('train')
- parser_train.add_argument('--sample_rate', type=int, required=True)
- parser_train.add_argument('--window_size', type=int, required=True)
- parser_train.add_argument('--hop_size', type=int, required=True)
- parser_train.add_argument('--mel_bins', type=int, required=True)
- parser_train.add_argument('--fmin', type=int, required=True)
- parser_train.add_argument('--fmax', type=int, required=True)
- parser_train.add_argument('--model_type', type=str, required=True)
- parser_train.add_argument('--pretrained_checkpoint_path', type=str)
- parser_train.add_argument('--freeze_base', action='store_true', default=False)
- parser_train.add_argument('--cuda', action='store_true', default=False)
-
- # Parse arguments
- args = parser.parse_args()
- args.filename = get_filename(__file__)
-
- if args.mode == 'train':
- train(args)
-
- else:
- raise Exception('Error argument!')
\ No newline at end of file
diff --git a/spaces/AIGC-Audio/AudioGPT/text_to_audio/Make_An_Audio/ldm/modules/encoders/open_clap/pretrained.py b/spaces/AIGC-Audio/AudioGPT/text_to_audio/Make_An_Audio/ldm/modules/encoders/open_clap/pretrained.py
deleted file mode 100644
index 723619a9fd511cf8619def49c4631ec701891b93..0000000000000000000000000000000000000000
--- a/spaces/AIGC-Audio/AudioGPT/text_to_audio/Make_An_Audio/ldm/modules/encoders/open_clap/pretrained.py
+++ /dev/null
@@ -1,147 +0,0 @@
-import hashlib
-import os
-import urllib
-import warnings
-
-from tqdm import tqdm
-
-_RN50 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/afeb0e10f9e5a86da6080e35cf09123aca3b358a0c3e3b6c78a7b63bc04b6762/RN50.pt",
- yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-yfcc15m-455df137.pt",
- cc12m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-cc12m-f000538c.pt"
-)
-
-_RN50_quickgelu = dict(
- openai="https://openaipublic.azureedge.net/clip/models/afeb0e10f9e5a86da6080e35cf09123aca3b358a0c3e3b6c78a7b63bc04b6762/RN50.pt",
- yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-yfcc15m-455df137.pt",
- cc12m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-cc12m-f000538c.pt"
-)
-
-_RN101 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/8fa8567bab74a42d41c5915025a8e4538c3bdbe8804a470a72f30b0d94fab599/RN101.pt",
- yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn101-quickgelu-yfcc15m-3e04b30e.pt"
-)
-
-_RN101_quickgelu = dict(
- openai="https://openaipublic.azureedge.net/clip/models/8fa8567bab74a42d41c5915025a8e4538c3bdbe8804a470a72f30b0d94fab599/RN101.pt",
- yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn101-quickgelu-yfcc15m-3e04b30e.pt"
-)
-
-_RN50x4 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/7e526bd135e493cef0776de27d5f42653e6b4c8bf9e0f653bb11773263205fdd/RN50x4.pt",
-)
-
-_RN50x16 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/52378b407f34354e150460fe41077663dd5b39c54cd0bfd2b27167a4a06ec9aa/RN50x16.pt",
-)
-
-_RN50x64 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/be1cfb55d75a9666199fb2206c106743da0f6468c9d327f3e0d0a543a9919d9c/RN50x64.pt",
-)
-
-_VITB32 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt",
- laion400m_e31="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e31-d867053b.pt",
- laion400m_e32="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e32-46683a32.pt",
- laion400m_avg="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_avg-8a00ab3c.pt",
-)
-
-_VITB32_quickgelu = dict(
- openai="https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt",
- laion400m_e31="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e31-d867053b.pt",
- laion400m_e32="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e32-46683a32.pt",
- laion400m_avg="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_avg-8a00ab3c.pt",
-)
-
-_VITB16 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/5806e77cd80f8b59890b7e101eabd078d9fb84e6937f9e85e4ecb61988df416f/ViT-B-16.pt",
-)
-
-_VITL14 = dict(
- openai="https://openaipublic.azureedge.net/clip/models/b8cca3fd41ae0c99ba7e8951adf17d267cdb84cd88be6f7c2e0eca1737a03836/ViT-L-14.pt",
-)
-
-_PRETRAINED = {
- "RN50": _RN50,
- "RN50-quickgelu": _RN50_quickgelu,
- "RN101": _RN101,
- "RN101-quickgelu": _RN101_quickgelu,
- "RN50x4": _RN50x4,
- "RN50x16": _RN50x16,
- "ViT-B-32": _VITB32,
- "ViT-B-32-quickgelu": _VITB32_quickgelu,
- "ViT-B-16": _VITB16,
- "ViT-L-14": _VITL14,
-}
-
-
-def list_pretrained(as_str: bool = False):
- """ returns list of pretrained models
- Returns a tuple (model_name, pretrain_tag) by default or 'name:tag' if as_str == True
- """
- return [':'.join([k, t]) if as_str else (k, t) for k in _PRETRAINED.keys() for t in _PRETRAINED[k].keys()]
-
-
-def list_pretrained_tag_models(tag: str):
- """ return all models having the specified pretrain tag """
- models = []
- for k in _PRETRAINED.keys():
- if tag in _PRETRAINED[k]:
- models.append(k)
- return models
-
-
-def list_pretrained_model_tags(model: str):
- """ return all pretrain tags for the specified model architecture """
- tags = []
- if model in _PRETRAINED:
- tags.extend(_PRETRAINED[model].keys())
- return tags
-
-
-def get_pretrained_url(model: str, tag: str):
- if model not in _PRETRAINED:
- return ''
- model_pretrained = _PRETRAINED[model]
- if tag not in model_pretrained:
- return ''
- return model_pretrained[tag]
-
-
-def download_pretrained(url: str, root: str = os.path.expanduser("~/.cache/clip")):
- os.makedirs(root, exist_ok=True)
- filename = os.path.basename(url)
-
- if 'openaipublic' in url:
- expected_sha256 = url.split("/")[-2]
- else:
- expected_sha256 = ''
-
- download_target = os.path.join(root, filename)
-
- if os.path.exists(download_target) and not os.path.isfile(download_target):
- raise RuntimeError(f"{download_target} exists and is not a regular file")
-
- if os.path.isfile(download_target):
- if expected_sha256:
- if hashlib.sha256(open(download_target, "rb").read()).hexdigest() == expected_sha256:
- return download_target
- else:
- warnings.warn(f"{download_target} exists, but the SHA256 checksum does not match; re-downloading the file")
- else:
- return download_target
-
- with urllib.request.urlopen(url) as source, open(download_target, "wb") as output:
- with tqdm(total=int(source.info().get("Content-Length")), ncols=80, unit='iB', unit_scale=True) as loop:
- while True:
- buffer = source.read(8192)
- if not buffer:
- break
-
- output.write(buffer)
- loop.update(len(buffer))
-
- if expected_sha256 and hashlib.sha256(open(download_target, "rb").read()).hexdigest() != expected_sha256:
- raise RuntimeError(f"Model has been downloaded but the SHA256 checksum does not not match")
-
- return download_target
diff --git a/spaces/AIGC-Audio/AudioGPT/text_to_speech/modules/vocoder/parallel_wavegan/__init__.py b/spaces/AIGC-Audio/AudioGPT/text_to_speech/modules/vocoder/parallel_wavegan/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/ASJMO/freegpt/client/css/sidebar.css b/spaces/ASJMO/freegpt/client/css/sidebar.css
deleted file mode 100644
index 310887c60443abd491c3162f62e44b5ec333e50d..0000000000000000000000000000000000000000
--- a/spaces/ASJMO/freegpt/client/css/sidebar.css
+++ /dev/null
@@ -1,197 +0,0 @@
-.sidebar {
- max-width: 260px;
- padding: var(--section-gap);
- flex-shrink: 0;
- display: flex;
- flex-direction: column;
- justify-content: space-between;
-}
-
-.sidebar .title {
- font-size: 14px;
- font-weight: 500;
-}
-
-.sidebar .conversation-sidebar {
- padding: 8px 12px;
- display: flex;
- gap: 18px;
- align-items: center;
- user-select: none;
- justify-content: space-between;
-}
-
-.sidebar .conversation-sidebar .left {
- cursor: pointer;
- display: flex;
- align-items: center;
- gap: 10px;
-}
-
-.sidebar i {
- color: var(--conversations);
- cursor: pointer;
-}
-
-.sidebar .top {
- display: flex;
- flex-direction: column;
- overflow: hidden;
- gap: 16px;
- padding-right: 8px;
-}
-
-.sidebar .top:hover {
- overflow: auto;
-}
-
-.sidebar .info {
- padding: 8px 12px 0px 12px;
- display: flex;
- align-items: center;
- justify-content: center;
- user-select: none;
- background: transparent;
- width: 100%;
- border: none;
- text-decoration: none;
-}
-
-.sidebar .info span {
- color: var(--conversations);
- line-height: 1.5;
- font-size: 0.75rem;
-}
-
-.sidebar .info i::before {
- margin-right: 8px;
-}
-
-.sidebar-footer {
- width: 100%;
- margin-top: 16px;
- display: flex;
- flex-direction: column;
-}
-
-.sidebar-footer button {
- cursor: pointer;
- user-select: none;
- background: transparent;
-}
-
-.sidebar.shown {
- position: fixed;
- top: 0;
- left: 0;
- width: 100%;
- height: 100%;
- z-index: 1000;
-}
-
-.sidebar.shown .box {
- background-color: #16171a;
- width: 80%;
- height: 100%;
- overflow-y: auto;
-}
-
-@keyframes spinner {
- to {
- transform: rotate(360deg);
- }
-}
-
-/* scrollbar */
-.sidebar .top::-webkit-scrollbar {
- width: 4px;
- padding: 8px 0px;
-}
-
-.sidebar .top::-webkit-scrollbar-track {
- background-color: #ffffff00;
-}
-
-.sidebar .top::-webkit-scrollbar-thumb {
- background-color: #555555;
- border-radius: 10px;
-}
-
-.spinner:before {
- content: "";
- box-sizing: border-box;
- position: absolute;
- top: 50%;
- left: 45%;
- width: 20px;
- height: 20px;
- border-radius: 50%;
- border: 1px solid var(--conversations);
- border-top-color: white;
- animation: spinner 0.6s linear infinite;
-}
-
-.menu-button {
- display: none !important;
- position: absolute;
- z-index: 100000;
- top: 0;
- left: 0;
- margin: 10px;
- font-size: 1rem;
- cursor: pointer;
- width: 30px;
- height: 30px;
- justify-content: center;
- align-items: center;
- transition: 0.33s;
-}
-
-.menu-button i {
- transition: 0.33s;
-}
-
-.rotated {
- transform: rotate(360deg);
-}
-
-.menu-button.rotated {
- position: fixed;
- top: 10px;
- left: 10px;
- z-index: 1001;
-}
-
-@media screen and (max-width: 990px) {
- .sidebar {
- display: none;
- width: 100%;
- max-width: none;
- }
-
- .menu-button {
- display: flex !important;
- }
-}
-
-@media (max-width: 990px) {
- .sidebar .top {
- padding-top: 48px;
- }
-}
-
-@media (min-width: 768px) {
- .sidebar.shown {
- position: static;
- width: auto;
- height: auto;
- background-color: transparent;
- }
-
- .sidebar.shown .box {
- background-color: #16171a;
- width: auto;
- height: auto;
- overflow-y: auto;
- }
-}
diff --git a/spaces/Abhimurthy/Phind-Phind-CodeLlama-34B-v1/app.py b/spaces/Abhimurthy/Phind-Phind-CodeLlama-34B-v1/app.py
deleted file mode 100644
index 6bc4f2dc0e6d35201731e4b20f25a34c9665f372..0000000000000000000000000000000000000000
--- a/spaces/Abhimurthy/Phind-Phind-CodeLlama-34B-v1/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/Phind/Phind-CodeLlama-34B-v1").launch()
\ No newline at end of file
diff --git a/spaces/AchyuthGamer/OpenGPT-Chat-UI/.svelte-kit/generated/client/nodes/10.js b/spaces/AchyuthGamer/OpenGPT-Chat-UI/.svelte-kit/generated/client/nodes/10.js
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/plugins/anchor.d.ts b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/plugins/anchor.d.ts
deleted file mode 100644
index 207d995cab1fe31c1139350c244c546c2579f939..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/plugins/anchor.d.ts
+++ /dev/null
@@ -1,2 +0,0 @@
-import Anchor from './behaviors/anchor/Anchor';
-export default Anchor;
\ No newline at end of file
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/customshapes/CustomShapes.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/customshapes/CustomShapes.js
deleted file mode 100644
index 60aef11f9093da59a18203cd5bee1cda0235b608..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/customshapes/CustomShapes.js
+++ /dev/null
@@ -1,2 +0,0 @@
-import CustomShapes from '../../../plugins/customshapes.js';
-export default CustomShapes;
\ No newline at end of file
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/maker/builders/CreateGridButtons.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/maker/builders/CreateGridButtons.js
deleted file mode 100644
index b1a6f30dd54118aa139803ef84376e74391b1223..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/maker/builders/CreateGridButtons.js
+++ /dev/null
@@ -1,43 +0,0 @@
-import MergeStyle from './utils/MergeStyle.js';
-import GridButtons from '../../gridbuttons/GridButtons.js';
-import CreateChild from './utils/CreateChild.js';
-import CreateChildren from './utils/CreateChildren.js';
-import Make from '../Make.js';
-
-var CreateGridButtons = function (scene, data, view, styles, customBuilders) {
- data = MergeStyle(data, styles);
-
- // Replace data by child game object
- CreateChild(scene, data, 'background', view, styles, customBuilders);
-
- var buttonsConfig = data.buttons; // Game objects in 2d array
- if (buttonsConfig) {
- for (var i = 0, cnt = buttonsConfig.length; i < cnt; i++) {
- CreateChildren(scene, buttonsConfig, i, view, styles, customBuilders);
- }
- }
-
- // Build createCellContainerCallback
- var createCellContainerCallbackConfig = data.createCellContainerCallback;
- if (createCellContainerCallbackConfig) {
- var childData = createCellContainerCallbackConfig.$child;
- delete createCellContainerCallbackConfig.$child;
-
- data.createCellContainerCallback = function (scene, x, y, config) {
- var child = Make(scene, childData, view, styles, customBuilders);
-
- // Copy config
- for (var key in createCellContainerCallbackConfig) {
- config[key] = createCellContainerCallbackConfig[key];
- }
-
- return child;
- }
- }
-
- var gameObject = new GridButtons(scene, data);
- scene.add.existing(gameObject);
- return gameObject;
-};
-
-export default CreateGridButtons;
\ No newline at end of file
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/ninepatch2/Factory.d.ts b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/ninepatch2/Factory.d.ts
deleted file mode 100644
index d852a6d46b1fb9350422c112dc351560661a057e..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/ninepatch2/Factory.d.ts
+++ /dev/null
@@ -1,39 +0,0 @@
-import NinePatch from "./NinePatch";
-
-export default function (
- config?: NinePatch.IConfig
-): NinePatch;
-
-export default function (
- x: number, y: number,
- config?: NinePatch.IConfig
-): NinePatch;
-
-export default function (
- x: number, y: number,
- width: number, height: number,
- config?: NinePatch.IConfig
-): NinePatch;
-
-export default function (
- x: number, y: number,
- width: number, height: number,
- key: string,
- config?: NinePatch.IConfig
-): NinePatch;
-
-export default function (
- x: number, y: number,
- width: number, height: number,
- key: string,
- columns: (number | undefined)[], rows: (number | undefined)[],
- config?: NinePatch.IConfig
-): NinePatch;
-
-export default function (
- x: number, y: number,
- width: number, height: number,
- key: string, baseFrame: string,
- columns: (number | undefined)[], rows: (number | undefined)[],
- config?: NinePatch.IConfig
-): NinePatch;
\ No newline at end of file
diff --git a/spaces/Akmyradov/TurkmenTTSweSTT/vits/mel_processing.py b/spaces/Akmyradov/TurkmenTTSweSTT/vits/mel_processing.py
deleted file mode 100644
index 817f03756f64caf8cc54329a9325024c8fb9e0c3..0000000000000000000000000000000000000000
--- a/spaces/Akmyradov/TurkmenTTSweSTT/vits/mel_processing.py
+++ /dev/null
@@ -1,112 +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 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/Alpaca233/SadTalker/src/face3d/models/arcface_torch/utils/utils_os.py b/spaces/Alpaca233/SadTalker/src/face3d/models/arcface_torch/utils/utils_os.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Amrrs/DragGan-Inversion/stylegan_human/openpose/src/model.py b/spaces/Amrrs/DragGan-Inversion/stylegan_human/openpose/src/model.py
deleted file mode 100644
index e5f67d39e3f8b1068ec1c3d27cee07670acbce91..0000000000000000000000000000000000000000
--- a/spaces/Amrrs/DragGan-Inversion/stylegan_human/openpose/src/model.py
+++ /dev/null
@@ -1,218 +0,0 @@
-import torch
-from collections import OrderedDict
-
-import torch
-import torch.nn as nn
-
-
-def make_layers(block, no_relu_layers):
- layers = []
- for layer_name, v in block.items():
- if 'pool' in layer_name:
- layer = nn.MaxPool2d(kernel_size=v[0], stride=v[1],
- padding=v[2])
- layers.append((layer_name, layer))
- else:
- conv2d = nn.Conv2d(in_channels=v[0], out_channels=v[1],
- kernel_size=v[2], stride=v[3],
- padding=v[4])
- layers.append((layer_name, conv2d))
- if layer_name not in no_relu_layers:
- layers.append(('relu_'+layer_name, nn.ReLU(inplace=True)))
-
- return nn.Sequential(OrderedDict(layers))
-
-
-class bodypose_model(nn.Module):
- def __init__(self):
- super(bodypose_model, self).__init__()
-
- # these layers have no relu layer
- no_relu_layers = ['conv5_5_CPM_L1', 'conv5_5_CPM_L2', 'Mconv7_stage2_L1',
- 'Mconv7_stage2_L2', 'Mconv7_stage3_L1', 'Mconv7_stage3_L2',
- 'Mconv7_stage4_L1', 'Mconv7_stage4_L2', 'Mconv7_stage5_L1',
- 'Mconv7_stage5_L2', 'Mconv7_stage6_L1', 'Mconv7_stage6_L1']
- blocks = {}
- block0 = OrderedDict([
- ('conv1_1', [3, 64, 3, 1, 1]),
- ('conv1_2', [64, 64, 3, 1, 1]),
- ('pool1_stage1', [2, 2, 0]),
- ('conv2_1', [64, 128, 3, 1, 1]),
- ('conv2_2', [128, 128, 3, 1, 1]),
- ('pool2_stage1', [2, 2, 0]),
- ('conv3_1', [128, 256, 3, 1, 1]),
- ('conv3_2', [256, 256, 3, 1, 1]),
- ('conv3_3', [256, 256, 3, 1, 1]),
- ('conv3_4', [256, 256, 3, 1, 1]),
- ('pool3_stage1', [2, 2, 0]),
- ('conv4_1', [256, 512, 3, 1, 1]),
- ('conv4_2', [512, 512, 3, 1, 1]),
- ('conv4_3_CPM', [512, 256, 3, 1, 1]),
- ('conv4_4_CPM', [256, 128, 3, 1, 1])
- ])
-
- # Stage 1
- block1_1 = OrderedDict([
- ('conv5_1_CPM_L1', [128, 128, 3, 1, 1]),
- ('conv5_2_CPM_L1', [128, 128, 3, 1, 1]),
- ('conv5_3_CPM_L1', [128, 128, 3, 1, 1]),
- ('conv5_4_CPM_L1', [128, 512, 1, 1, 0]),
- ('conv5_5_CPM_L1', [512, 38, 1, 1, 0])
- ])
-
- block1_2 = OrderedDict([
- ('conv5_1_CPM_L2', [128, 128, 3, 1, 1]),
- ('conv5_2_CPM_L2', [128, 128, 3, 1, 1]),
- ('conv5_3_CPM_L2', [128, 128, 3, 1, 1]),
- ('conv5_4_CPM_L2', [128, 512, 1, 1, 0]),
- ('conv5_5_CPM_L2', [512, 19, 1, 1, 0])
- ])
- blocks['block1_1'] = block1_1
- blocks['block1_2'] = block1_2
-
- self.model0 = make_layers(block0, no_relu_layers)
-
- # Stages 2 - 6
- for i in range(2, 7):
- blocks['block%d_1' % i] = OrderedDict([
- ('Mconv1_stage%d_L1' % i, [185, 128, 7, 1, 3]),
- ('Mconv2_stage%d_L1' % i, [128, 128, 7, 1, 3]),
- ('Mconv3_stage%d_L1' % i, [128, 128, 7, 1, 3]),
- ('Mconv4_stage%d_L1' % i, [128, 128, 7, 1, 3]),
- ('Mconv5_stage%d_L1' % i, [128, 128, 7, 1, 3]),
- ('Mconv6_stage%d_L1' % i, [128, 128, 1, 1, 0]),
- ('Mconv7_stage%d_L1' % i, [128, 38, 1, 1, 0])
- ])
-
- blocks['block%d_2' % i] = OrderedDict([
- ('Mconv1_stage%d_L2' % i, [185, 128, 7, 1, 3]),
- ('Mconv2_stage%d_L2' % i, [128, 128, 7, 1, 3]),
- ('Mconv3_stage%d_L2' % i, [128, 128, 7, 1, 3]),
- ('Mconv4_stage%d_L2' % i, [128, 128, 7, 1, 3]),
- ('Mconv5_stage%d_L2' % i, [128, 128, 7, 1, 3]),
- ('Mconv6_stage%d_L2' % i, [128, 128, 1, 1, 0]),
- ('Mconv7_stage%d_L2' % i, [128, 19, 1, 1, 0])
- ])
-
- for k in blocks.keys():
- blocks[k] = make_layers(blocks[k], no_relu_layers)
-
- self.model1_1 = blocks['block1_1']
- self.model2_1 = blocks['block2_1']
- self.model3_1 = blocks['block3_1']
- self.model4_1 = blocks['block4_1']
- self.model5_1 = blocks['block5_1']
- self.model6_1 = blocks['block6_1']
-
- self.model1_2 = blocks['block1_2']
- self.model2_2 = blocks['block2_2']
- self.model3_2 = blocks['block3_2']
- self.model4_2 = blocks['block4_2']
- self.model5_2 = blocks['block5_2']
- self.model6_2 = blocks['block6_2']
-
- def forward(self, x):
-
- out1 = self.model0(x)
-
- out1_1 = self.model1_1(out1)
- out1_2 = self.model1_2(out1)
- out2 = torch.cat([out1_1, out1_2, out1], 1)
-
- out2_1 = self.model2_1(out2)
- out2_2 = self.model2_2(out2)
- out3 = torch.cat([out2_1, out2_2, out1], 1)
-
- out3_1 = self.model3_1(out3)
- out3_2 = self.model3_2(out3)
- out4 = torch.cat([out3_1, out3_2, out1], 1)
-
- out4_1 = self.model4_1(out4)
- out4_2 = self.model4_2(out4)
- out5 = torch.cat([out4_1, out4_2, out1], 1)
-
- out5_1 = self.model5_1(out5)
- out5_2 = self.model5_2(out5)
- out6 = torch.cat([out5_1, out5_2, out1], 1)
-
- out6_1 = self.model6_1(out6)
- out6_2 = self.model6_2(out6)
-
- return out6_1, out6_2
-
-
-class handpose_model(nn.Module):
- def __init__(self):
- super(handpose_model, self).__init__()
-
- # these layers have no relu layer
- no_relu_layers = ['conv6_2_CPM', 'Mconv7_stage2', 'Mconv7_stage3',
- 'Mconv7_stage4', 'Mconv7_stage5', 'Mconv7_stage6']
- # stage 1
- block1_0 = OrderedDict([
- ('conv1_1', [3, 64, 3, 1, 1]),
- ('conv1_2', [64, 64, 3, 1, 1]),
- ('pool1_stage1', [2, 2, 0]),
- ('conv2_1', [64, 128, 3, 1, 1]),
- ('conv2_2', [128, 128, 3, 1, 1]),
- ('pool2_stage1', [2, 2, 0]),
- ('conv3_1', [128, 256, 3, 1, 1]),
- ('conv3_2', [256, 256, 3, 1, 1]),
- ('conv3_3', [256, 256, 3, 1, 1]),
- ('conv3_4', [256, 256, 3, 1, 1]),
- ('pool3_stage1', [2, 2, 0]),
- ('conv4_1', [256, 512, 3, 1, 1]),
- ('conv4_2', [512, 512, 3, 1, 1]),
- ('conv4_3', [512, 512, 3, 1, 1]),
- ('conv4_4', [512, 512, 3, 1, 1]),
- ('conv5_1', [512, 512, 3, 1, 1]),
- ('conv5_2', [512, 512, 3, 1, 1]),
- ('conv5_3_CPM', [512, 128, 3, 1, 1])
- ])
-
- block1_1 = OrderedDict([
- ('conv6_1_CPM', [128, 512, 1, 1, 0]),
- ('conv6_2_CPM', [512, 22, 1, 1, 0])
- ])
-
- blocks = {}
- blocks['block1_0'] = block1_0
- blocks['block1_1'] = block1_1
-
- # stage 2-6
- for i in range(2, 7):
- blocks['block%d' % i] = OrderedDict([
- ('Mconv1_stage%d' % i, [150, 128, 7, 1, 3]),
- ('Mconv2_stage%d' % i, [128, 128, 7, 1, 3]),
- ('Mconv3_stage%d' % i, [128, 128, 7, 1, 3]),
- ('Mconv4_stage%d' % i, [128, 128, 7, 1, 3]),
- ('Mconv5_stage%d' % i, [128, 128, 7, 1, 3]),
- ('Mconv6_stage%d' % i, [128, 128, 1, 1, 0]),
- ('Mconv7_stage%d' % i, [128, 22, 1, 1, 0])
- ])
-
- for k in blocks.keys():
- blocks[k] = make_layers(blocks[k], no_relu_layers)
-
- self.model1_0 = blocks['block1_0']
- self.model1_1 = blocks['block1_1']
- self.model2 = blocks['block2']
- self.model3 = blocks['block3']
- self.model4 = blocks['block4']
- self.model5 = blocks['block5']
- self.model6 = blocks['block6']
-
- def forward(self, x):
- out1_0 = self.model1_0(x)
- out1_1 = self.model1_1(out1_0)
- concat_stage2 = torch.cat([out1_1, out1_0], 1)
- out_stage2 = self.model2(concat_stage2)
- concat_stage3 = torch.cat([out_stage2, out1_0], 1)
- out_stage3 = self.model3(concat_stage3)
- concat_stage4 = torch.cat([out_stage3, out1_0], 1)
- out_stage4 = self.model4(concat_stage4)
- concat_stage5 = torch.cat([out_stage4, out1_0], 1)
- out_stage5 = self.model5(concat_stage5)
- concat_stage6 = torch.cat([out_stage5, out1_0], 1)
- out_stage6 = self.model6(concat_stage6)
- return out_stage6
diff --git a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/conftest.py b/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/conftest.py
deleted file mode 100644
index 6a02a38163ab01b1c2d0d12d5578e06d91b77cc8..0000000000000000000000000000000000000000
--- a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/conftest.py
+++ /dev/null
@@ -1,44 +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.
-
-# tests directory-specific settings - this file is run automatically
-# by pytest before any tests are run
-
-import sys
-import warnings
-from os.path import abspath, dirname, join
-
-
-# allow having multiple repository checkouts and not needing to remember to rerun
-# 'pip install -e .[dev]' when switching between checkouts and running tests.
-git_repo_path = abspath(join(dirname(dirname(__file__)), "src"))
-sys.path.insert(1, git_repo_path)
-
-# silence FutureWarning warnings in tests since often we can't act on them until
-# they become normal warnings - i.e. the tests still need to test the current functionality
-warnings.simplefilter(action="ignore", category=FutureWarning)
-
-
-def pytest_addoption(parser):
- from diffusers.utils.testing_utils import pytest_addoption_shared
-
- pytest_addoption_shared(parser)
-
-
-def pytest_terminal_summary(terminalreporter):
- from diffusers.utils.testing_utils import pytest_terminal_summary_main
-
- make_reports = terminalreporter.config.getoption("--make-reports")
- if make_reports:
- pytest_terminal_summary_main(terminalreporter, id=make_reports)
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/datasets/utils.py b/spaces/Andy1621/uniformer_image_detection/mmdet/datasets/utils.py
deleted file mode 100644
index 157c9a2e1fe009552fdec9b9c9e7a33ed46d51ff..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/datasets/utils.py
+++ /dev/null
@@ -1,158 +0,0 @@
-import copy
-import warnings
-
-from mmcv.cnn import VGG
-from mmcv.runner.hooks import HOOKS, Hook
-
-from mmdet.datasets.builder import PIPELINES
-from mmdet.datasets.pipelines import LoadAnnotations, LoadImageFromFile
-from mmdet.models.dense_heads import GARPNHead, RPNHead
-from mmdet.models.roi_heads.mask_heads import FusedSemanticHead
-
-
-def replace_ImageToTensor(pipelines):
- """Replace the ImageToTensor transform in a data pipeline to
- DefaultFormatBundle, which is normally useful in batch inference.
-
- Args:
- pipelines (list[dict]): Data pipeline configs.
-
- Returns:
- list: The new pipeline list with all ImageToTensor replaced by
- DefaultFormatBundle.
-
- Examples:
- >>> pipelines = [
- ... dict(type='LoadImageFromFile'),
- ... dict(
- ... type='MultiScaleFlipAug',
- ... img_scale=(1333, 800),
- ... flip=False,
- ... transforms=[
- ... dict(type='Resize', keep_ratio=True),
- ... dict(type='RandomFlip'),
- ... dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
- ... dict(type='Pad', size_divisor=32),
- ... dict(type='ImageToTensor', keys=['img']),
- ... dict(type='Collect', keys=['img']),
- ... ])
- ... ]
- >>> expected_pipelines = [
- ... dict(type='LoadImageFromFile'),
- ... dict(
- ... type='MultiScaleFlipAug',
- ... img_scale=(1333, 800),
- ... flip=False,
- ... transforms=[
- ... dict(type='Resize', keep_ratio=True),
- ... dict(type='RandomFlip'),
- ... dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
- ... dict(type='Pad', size_divisor=32),
- ... dict(type='DefaultFormatBundle'),
- ... dict(type='Collect', keys=['img']),
- ... ])
- ... ]
- >>> assert expected_pipelines == replace_ImageToTensor(pipelines)
- """
- pipelines = copy.deepcopy(pipelines)
- for i, pipeline in enumerate(pipelines):
- if pipeline['type'] == 'MultiScaleFlipAug':
- assert 'transforms' in pipeline
- pipeline['transforms'] = replace_ImageToTensor(
- pipeline['transforms'])
- elif pipeline['type'] == 'ImageToTensor':
- warnings.warn(
- '"ImageToTensor" pipeline is replaced by '
- '"DefaultFormatBundle" for batch inference. It is '
- 'recommended to manually replace it in the test '
- 'data pipeline in your config file.', UserWarning)
- pipelines[i] = {'type': 'DefaultFormatBundle'}
- return pipelines
-
-
-def get_loading_pipeline(pipeline):
- """Only keep loading image and annotations related configuration.
-
- Args:
- pipeline (list[dict]): Data pipeline configs.
-
- Returns:
- list[dict]: The new pipeline list with only keep
- loading image and annotations related configuration.
-
- Examples:
- >>> pipelines = [
- ... dict(type='LoadImageFromFile'),
- ... dict(type='LoadAnnotations', with_bbox=True),
- ... dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
- ... dict(type='RandomFlip', flip_ratio=0.5),
- ... dict(type='Normalize', **img_norm_cfg),
- ... dict(type='Pad', size_divisor=32),
- ... dict(type='DefaultFormatBundle'),
- ... dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
- ... ]
- >>> expected_pipelines = [
- ... dict(type='LoadImageFromFile'),
- ... dict(type='LoadAnnotations', with_bbox=True)
- ... ]
- >>> assert expected_pipelines ==\
- ... get_loading_pipeline(pipelines)
- """
- loading_pipeline_cfg = []
- for cfg in pipeline:
- obj_cls = PIPELINES.get(cfg['type'])
- # TODO:use more elegant way to distinguish loading modules
- if obj_cls is not None and obj_cls in (LoadImageFromFile,
- LoadAnnotations):
- loading_pipeline_cfg.append(cfg)
- assert len(loading_pipeline_cfg) == 2, \
- 'The data pipeline in your config file must include ' \
- 'loading image and annotations related pipeline.'
- return loading_pipeline_cfg
-
-
-@HOOKS.register_module()
-class NumClassCheckHook(Hook):
-
- def _check_head(self, runner):
- """Check whether the `num_classes` in head matches the length of
- `CLASSSES` in `dataset`.
-
- Args:
- runner (obj:`EpochBasedRunner`): Epoch based Runner.
- """
- model = runner.model
- dataset = runner.data_loader.dataset
- if dataset.CLASSES is None:
- runner.logger.warning(
- f'Please set `CLASSES` '
- f'in the {dataset.__class__.__name__} and'
- f'check if it is consistent with the `num_classes` '
- f'of head')
- else:
- for name, module in model.named_modules():
- if hasattr(module, 'num_classes') and not isinstance(
- module, (RPNHead, VGG, FusedSemanticHead, GARPNHead)):
- assert module.num_classes == len(dataset.CLASSES), \
- (f'The `num_classes` ({module.num_classes}) in '
- f'{module.__class__.__name__} of '
- f'{model.__class__.__name__} does not matches '
- f'the length of `CLASSES` '
- f'{len(dataset.CLASSES)}) in '
- f'{dataset.__class__.__name__}')
-
- def before_train_epoch(self, runner):
- """Check whether the training dataset is compatible with head.
-
- Args:
- runner (obj:`EpochBasedRunner`): Epoch based Runner.
- """
- self._check_head(runner)
-
- def before_val_epoch(self, runner):
- """Check whether the dataset in val epoch is compatible with head.
-
- Args:
- runner (obj:`EpochBasedRunner`): Epoch based Runner.
- """
- self._check_head(runner)
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/mask_scoring_rcnn.py b/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/mask_scoring_rcnn.py
deleted file mode 100644
index b6252b6e1d234a201725342a5780fade7e21957c..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/mask_scoring_rcnn.py
+++ /dev/null
@@ -1,27 +0,0 @@
-from ..builder import DETECTORS
-from .two_stage import TwoStageDetector
-
-
-@DETECTORS.register_module()
-class MaskScoringRCNN(TwoStageDetector):
- """Mask Scoring RCNN.
-
- https://arxiv.org/abs/1903.00241
- """
-
- def __init__(self,
- backbone,
- rpn_head,
- roi_head,
- train_cfg,
- test_cfg,
- neck=None,
- pretrained=None):
- super(MaskScoringRCNN, self).__init__(
- backbone=backbone,
- neck=neck,
- rpn_head=rpn_head,
- roi_head=roi_head,
- train_cfg=train_cfg,
- test_cfg=test_cfg,
- pretrained=pretrained)
diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes.py
deleted file mode 100644
index 7403bee864d833bcc31160665e4b54fdd738cc13..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes.py
+++ /dev/null
@@ -1,12 +0,0 @@
-_base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py'
-model = dict(
- pretrained='mmcls://mobilenet_v2',
- backbone=dict(
- _delete_=True,
- type='MobileNetV2',
- widen_factor=1.,
- strides=(1, 2, 2, 1, 1, 1, 1),
- dilations=(1, 1, 1, 2, 2, 4, 4),
- out_indices=(1, 2, 4, 6)),
- decode_head=dict(in_channels=320),
- auxiliary_head=dict(in_channels=96))
diff --git a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/extensions/gallery/script.js b/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/extensions/gallery/script.js
deleted file mode 100644
index 4ff23afc84526e3e7661a589837d869cf932de88..0000000000000000000000000000000000000000
--- a/spaces/AnishKumbhar/ChatBot/text-generation-webui-main/extensions/gallery/script.js
+++ /dev/null
@@ -1,33 +0,0 @@
-let gallery_element = document.getElementById('gallery-extension');
-let chat_mode_element = document.getElementById('chat-mode');
-
-let extensions_block = document.getElementById('extensions');
-let extensions_block_size = extensions_block.childNodes.length;
-let gallery_only = (extensions_block_size == 5);
-
-document.querySelector('.header_bar').addEventListener('click', function(event) {
- if (event.target.tagName === 'BUTTON') {
- const buttonText = event.target.textContent.trim();
-
- let chat_visible = (buttonText == 'Chat');
- let default_visible = (buttonText == 'Default');
- let notebook_visible = (buttonText == 'Notebook');
- let chat_mode_visible = (chat_mode_element.offsetHeight > 0 && chat_mode_element.offsetWidth > 0);
-
- // Only show this extension in the Chat tab
- if (chat_visible) {
- if (chat_mode_visible) {
- gallery_element.style.display = 'block';
- extensions_block.style.display = '';
- } else {
- gallery_element.style.display = 'none';
- extensions_block.style.display = 'none';
- }
- } else {
- gallery_element.style.display = 'none';
- if (gallery_only) {
- extensions_block.style.display = 'none';
- }
- }
- }
-});
diff --git a/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/exp/upernet_global_small/run.sh b/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/exp/upernet_global_small/run.sh
deleted file mode 100644
index 9fb22edfa7a32624ea08a63fe7d720c40db3b696..0000000000000000000000000000000000000000
--- a/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/exp/upernet_global_small/run.sh
+++ /dev/null
@@ -1,10 +0,0 @@
-#!/usr/bin/env bash
-
-work_path=$(dirname $0)
-PYTHONPATH="$(dirname $0)/../../":$PYTHONPATH \
-python -m torch.distributed.launch --nproc_per_node=8 \
- tools/train.py ${work_path}/config.py \
- --launcher pytorch \
- --options model.backbone.pretrained_path='your_model_path/uniformer_small_in1k.pth' \
- --work-dir ${work_path}/ckpt \
- 2>&1 | tee -a ${work_path}/log.txt
diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/urllib3/contrib/pyopenssl.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/urllib3/contrib/pyopenssl.py
deleted file mode 100644
index 19e4aa97cc138e4bd39bebf6c49ff1955cb00437..0000000000000000000000000000000000000000
--- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/urllib3/contrib/pyopenssl.py
+++ /dev/null
@@ -1,518 +0,0 @@
-"""
-TLS with SNI_-support for Python 2. Follow these instructions if you would
-like to verify TLS certificates in Python 2. Note, the default libraries do
-*not* do certificate checking; you need to do additional work to validate
-certificates yourself.
-
-This needs the following packages installed:
-
-* `pyOpenSSL`_ (tested with 16.0.0)
-* `cryptography`_ (minimum 1.3.4, from pyopenssl)
-* `idna`_ (minimum 2.0, from cryptography)
-
-However, pyopenssl depends on cryptography, which depends on idna, so while we
-use all three directly here we end up having relatively few packages required.
-
-You can install them with the following command:
-
-.. code-block:: bash
-
- $ python -m pip install pyopenssl cryptography idna
-
-To activate certificate checking, call
-:func:`~urllib3.contrib.pyopenssl.inject_into_urllib3` from your Python code
-before you begin making HTTP requests. This can be done in a ``sitecustomize``
-module, or at any other time before your application begins using ``urllib3``,
-like this:
-
-.. code-block:: python
-
- try:
- import pip._vendor.urllib3.contrib.pyopenssl as pyopenssl
- pyopenssl.inject_into_urllib3()
- except ImportError:
- pass
-
-Now you can use :mod:`urllib3` as you normally would, and it will support SNI
-when the required modules are installed.
-
-Activating this module also has the positive side effect of disabling SSL/TLS
-compression in Python 2 (see `CRIME attack`_).
-
-.. _sni: https://en.wikipedia.org/wiki/Server_Name_Indication
-.. _crime attack: https://en.wikipedia.org/wiki/CRIME_(security_exploit)
-.. _pyopenssl: https://www.pyopenssl.org
-.. _cryptography: https://cryptography.io
-.. _idna: https://github.com/kjd/idna
-"""
-from __future__ import absolute_import
-
-import OpenSSL.crypto
-import OpenSSL.SSL
-from cryptography import x509
-from cryptography.hazmat.backends.openssl import backend as openssl_backend
-
-try:
- from cryptography.x509 import UnsupportedExtension
-except ImportError:
- # UnsupportedExtension is gone in cryptography >= 2.1.0
- class UnsupportedExtension(Exception):
- pass
-
-
-from io import BytesIO
-from socket import error as SocketError
-from socket import timeout
-
-try: # Platform-specific: Python 2
- from socket import _fileobject
-except ImportError: # Platform-specific: Python 3
- _fileobject = None
- from ..packages.backports.makefile import backport_makefile
-
-import logging
-import ssl
-import sys
-import warnings
-
-from .. import util
-from ..packages import six
-from ..util.ssl_ import PROTOCOL_TLS_CLIENT
-
-warnings.warn(
- "'urllib3.contrib.pyopenssl' module is deprecated and will be removed "
- "in a future release of urllib3 2.x. Read more in this issue: "
- "https://github.com/urllib3/urllib3/issues/2680",
- category=DeprecationWarning,
- stacklevel=2,
-)
-
-__all__ = ["inject_into_urllib3", "extract_from_urllib3"]
-
-# SNI always works.
-HAS_SNI = True
-
-# Map from urllib3 to PyOpenSSL compatible parameter-values.
-_openssl_versions = {
- util.PROTOCOL_TLS: OpenSSL.SSL.SSLv23_METHOD,
- PROTOCOL_TLS_CLIENT: OpenSSL.SSL.SSLv23_METHOD,
- ssl.PROTOCOL_TLSv1: OpenSSL.SSL.TLSv1_METHOD,
-}
-
-if hasattr(ssl, "PROTOCOL_SSLv3") and hasattr(OpenSSL.SSL, "SSLv3_METHOD"):
- _openssl_versions[ssl.PROTOCOL_SSLv3] = OpenSSL.SSL.SSLv3_METHOD
-
-if hasattr(ssl, "PROTOCOL_TLSv1_1") and hasattr(OpenSSL.SSL, "TLSv1_1_METHOD"):
- _openssl_versions[ssl.PROTOCOL_TLSv1_1] = OpenSSL.SSL.TLSv1_1_METHOD
-
-if hasattr(ssl, "PROTOCOL_TLSv1_2") and hasattr(OpenSSL.SSL, "TLSv1_2_METHOD"):
- _openssl_versions[ssl.PROTOCOL_TLSv1_2] = OpenSSL.SSL.TLSv1_2_METHOD
-
-
-_stdlib_to_openssl_verify = {
- ssl.CERT_NONE: OpenSSL.SSL.VERIFY_NONE,
- ssl.CERT_OPTIONAL: OpenSSL.SSL.VERIFY_PEER,
- ssl.CERT_REQUIRED: OpenSSL.SSL.VERIFY_PEER
- + OpenSSL.SSL.VERIFY_FAIL_IF_NO_PEER_CERT,
-}
-_openssl_to_stdlib_verify = dict((v, k) for k, v in _stdlib_to_openssl_verify.items())
-
-# OpenSSL will only write 16K at a time
-SSL_WRITE_BLOCKSIZE = 16384
-
-orig_util_HAS_SNI = util.HAS_SNI
-orig_util_SSLContext = util.ssl_.SSLContext
-
-
-log = logging.getLogger(__name__)
-
-
-def inject_into_urllib3():
- "Monkey-patch urllib3 with PyOpenSSL-backed SSL-support."
-
- _validate_dependencies_met()
-
- util.SSLContext = PyOpenSSLContext
- util.ssl_.SSLContext = PyOpenSSLContext
- util.HAS_SNI = HAS_SNI
- util.ssl_.HAS_SNI = HAS_SNI
- util.IS_PYOPENSSL = True
- util.ssl_.IS_PYOPENSSL = True
-
-
-def extract_from_urllib3():
- "Undo monkey-patching by :func:`inject_into_urllib3`."
-
- util.SSLContext = orig_util_SSLContext
- util.ssl_.SSLContext = orig_util_SSLContext
- util.HAS_SNI = orig_util_HAS_SNI
- util.ssl_.HAS_SNI = orig_util_HAS_SNI
- util.IS_PYOPENSSL = False
- util.ssl_.IS_PYOPENSSL = False
-
-
-def _validate_dependencies_met():
- """
- Verifies that PyOpenSSL's package-level dependencies have been met.
- Throws `ImportError` if they are not met.
- """
- # Method added in `cryptography==1.1`; not available in older versions
- from cryptography.x509.extensions import Extensions
-
- if getattr(Extensions, "get_extension_for_class", None) is None:
- raise ImportError(
- "'cryptography' module missing required functionality. "
- "Try upgrading to v1.3.4 or newer."
- )
-
- # pyOpenSSL 0.14 and above use cryptography for OpenSSL bindings. The _x509
- # attribute is only present on those versions.
- from OpenSSL.crypto import X509
-
- x509 = X509()
- if getattr(x509, "_x509", None) is None:
- raise ImportError(
- "'pyOpenSSL' module missing required functionality. "
- "Try upgrading to v0.14 or newer."
- )
-
-
-def _dnsname_to_stdlib(name):
- """
- Converts a dNSName SubjectAlternativeName field to the form used by the
- standard library on the given Python version.
-
- Cryptography produces a dNSName as a unicode string that was idna-decoded
- from ASCII bytes. We need to idna-encode that string to get it back, and
- then on Python 3 we also need to convert to unicode via UTF-8 (the stdlib
- uses PyUnicode_FromStringAndSize on it, which decodes via UTF-8).
-
- If the name cannot be idna-encoded then we return None signalling that
- the name given should be skipped.
- """
-
- def idna_encode(name):
- """
- Borrowed wholesale from the Python Cryptography Project. It turns out
- that we can't just safely call `idna.encode`: it can explode for
- wildcard names. This avoids that problem.
- """
- from pip._vendor import idna
-
- try:
- for prefix in [u"*.", u"."]:
- if name.startswith(prefix):
- name = name[len(prefix) :]
- return prefix.encode("ascii") + idna.encode(name)
- return idna.encode(name)
- except idna.core.IDNAError:
- return None
-
- # Don't send IPv6 addresses through the IDNA encoder.
- if ":" in name:
- return name
-
- name = idna_encode(name)
- if name is None:
- return None
- elif sys.version_info >= (3, 0):
- name = name.decode("utf-8")
- return name
-
-
-def get_subj_alt_name(peer_cert):
- """
- Given an PyOpenSSL certificate, provides all the subject alternative names.
- """
- # Pass the cert to cryptography, which has much better APIs for this.
- if hasattr(peer_cert, "to_cryptography"):
- cert = peer_cert.to_cryptography()
- else:
- der = OpenSSL.crypto.dump_certificate(OpenSSL.crypto.FILETYPE_ASN1, peer_cert)
- cert = x509.load_der_x509_certificate(der, openssl_backend)
-
- # We want to find the SAN extension. Ask Cryptography to locate it (it's
- # faster than looping in Python)
- try:
- ext = cert.extensions.get_extension_for_class(x509.SubjectAlternativeName).value
- except x509.ExtensionNotFound:
- # No such extension, return the empty list.
- return []
- except (
- x509.DuplicateExtension,
- UnsupportedExtension,
- x509.UnsupportedGeneralNameType,
- UnicodeError,
- ) as e:
- # A problem has been found with the quality of the certificate. Assume
- # no SAN field is present.
- log.warning(
- "A problem was encountered with the certificate that prevented "
- "urllib3 from finding the SubjectAlternativeName field. This can "
- "affect certificate validation. The error was %s",
- e,
- )
- return []
-
- # We want to return dNSName and iPAddress fields. We need to cast the IPs
- # back to strings because the match_hostname function wants them as
- # strings.
- # Sadly the DNS names need to be idna encoded and then, on Python 3, UTF-8
- # decoded. This is pretty frustrating, but that's what the standard library
- # does with certificates, and so we need to attempt to do the same.
- # We also want to skip over names which cannot be idna encoded.
- names = [
- ("DNS", name)
- for name in map(_dnsname_to_stdlib, ext.get_values_for_type(x509.DNSName))
- if name is not None
- ]
- names.extend(
- ("IP Address", str(name)) for name in ext.get_values_for_type(x509.IPAddress)
- )
-
- return names
-
-
-class WrappedSocket(object):
- """API-compatibility wrapper for Python OpenSSL's Connection-class.
-
- Note: _makefile_refs, _drop() and _reuse() are needed for the garbage
- collector of pypy.
- """
-
- def __init__(self, connection, socket, suppress_ragged_eofs=True):
- self.connection = connection
- self.socket = socket
- self.suppress_ragged_eofs = suppress_ragged_eofs
- self._makefile_refs = 0
- self._closed = False
-
- def fileno(self):
- return self.socket.fileno()
-
- # Copy-pasted from Python 3.5 source code
- def _decref_socketios(self):
- if self._makefile_refs > 0:
- self._makefile_refs -= 1
- if self._closed:
- self.close()
-
- def recv(self, *args, **kwargs):
- try:
- data = self.connection.recv(*args, **kwargs)
- except OpenSSL.SSL.SysCallError as e:
- if self.suppress_ragged_eofs and e.args == (-1, "Unexpected EOF"):
- return b""
- else:
- raise SocketError(str(e))
- except OpenSSL.SSL.ZeroReturnError:
- if self.connection.get_shutdown() == OpenSSL.SSL.RECEIVED_SHUTDOWN:
- return b""
- else:
- raise
- except OpenSSL.SSL.WantReadError:
- if not util.wait_for_read(self.socket, self.socket.gettimeout()):
- raise timeout("The read operation timed out")
- else:
- return self.recv(*args, **kwargs)
-
- # TLS 1.3 post-handshake authentication
- except OpenSSL.SSL.Error as e:
- raise ssl.SSLError("read error: %r" % e)
- else:
- return data
-
- def recv_into(self, *args, **kwargs):
- try:
- return self.connection.recv_into(*args, **kwargs)
- except OpenSSL.SSL.SysCallError as e:
- if self.suppress_ragged_eofs and e.args == (-1, "Unexpected EOF"):
- return 0
- else:
- raise SocketError(str(e))
- except OpenSSL.SSL.ZeroReturnError:
- if self.connection.get_shutdown() == OpenSSL.SSL.RECEIVED_SHUTDOWN:
- return 0
- else:
- raise
- except OpenSSL.SSL.WantReadError:
- if not util.wait_for_read(self.socket, self.socket.gettimeout()):
- raise timeout("The read operation timed out")
- else:
- return self.recv_into(*args, **kwargs)
-
- # TLS 1.3 post-handshake authentication
- except OpenSSL.SSL.Error as e:
- raise ssl.SSLError("read error: %r" % e)
-
- def settimeout(self, timeout):
- return self.socket.settimeout(timeout)
-
- def _send_until_done(self, data):
- while True:
- try:
- return self.connection.send(data)
- except OpenSSL.SSL.WantWriteError:
- if not util.wait_for_write(self.socket, self.socket.gettimeout()):
- raise timeout()
- continue
- except OpenSSL.SSL.SysCallError as e:
- raise SocketError(str(e))
-
- def sendall(self, data):
- total_sent = 0
- while total_sent < len(data):
- sent = self._send_until_done(
- data[total_sent : total_sent + SSL_WRITE_BLOCKSIZE]
- )
- total_sent += sent
-
- def shutdown(self):
- # FIXME rethrow compatible exceptions should we ever use this
- self.connection.shutdown()
-
- def close(self):
- if self._makefile_refs < 1:
- try:
- self._closed = True
- return self.connection.close()
- except OpenSSL.SSL.Error:
- return
- else:
- self._makefile_refs -= 1
-
- def getpeercert(self, binary_form=False):
- x509 = self.connection.get_peer_certificate()
-
- if not x509:
- return x509
-
- if binary_form:
- return OpenSSL.crypto.dump_certificate(OpenSSL.crypto.FILETYPE_ASN1, x509)
-
- return {
- "subject": ((("commonName", x509.get_subject().CN),),),
- "subjectAltName": get_subj_alt_name(x509),
- }
-
- def version(self):
- return self.connection.get_protocol_version_name()
-
- def _reuse(self):
- self._makefile_refs += 1
-
- def _drop(self):
- if self._makefile_refs < 1:
- self.close()
- else:
- self._makefile_refs -= 1
-
-
-if _fileobject: # Platform-specific: Python 2
-
- def makefile(self, mode, bufsize=-1):
- self._makefile_refs += 1
- return _fileobject(self, mode, bufsize, close=True)
-
-else: # Platform-specific: Python 3
- makefile = backport_makefile
-
-WrappedSocket.makefile = makefile
-
-
-class PyOpenSSLContext(object):
- """
- I am a wrapper class for the PyOpenSSL ``Context`` object. I am responsible
- for translating the interface of the standard library ``SSLContext`` object
- to calls into PyOpenSSL.
- """
-
- def __init__(self, protocol):
- self.protocol = _openssl_versions[protocol]
- self._ctx = OpenSSL.SSL.Context(self.protocol)
- self._options = 0
- self.check_hostname = False
-
- @property
- def options(self):
- return self._options
-
- @options.setter
- def options(self, value):
- self._options = value
- self._ctx.set_options(value)
-
- @property
- def verify_mode(self):
- return _openssl_to_stdlib_verify[self._ctx.get_verify_mode()]
-
- @verify_mode.setter
- def verify_mode(self, value):
- self._ctx.set_verify(_stdlib_to_openssl_verify[value], _verify_callback)
-
- def set_default_verify_paths(self):
- self._ctx.set_default_verify_paths()
-
- def set_ciphers(self, ciphers):
- if isinstance(ciphers, six.text_type):
- ciphers = ciphers.encode("utf-8")
- self._ctx.set_cipher_list(ciphers)
-
- def load_verify_locations(self, cafile=None, capath=None, cadata=None):
- if cafile is not None:
- cafile = cafile.encode("utf-8")
- if capath is not None:
- capath = capath.encode("utf-8")
- try:
- self._ctx.load_verify_locations(cafile, capath)
- if cadata is not None:
- self._ctx.load_verify_locations(BytesIO(cadata))
- except OpenSSL.SSL.Error as e:
- raise ssl.SSLError("unable to load trusted certificates: %r" % e)
-
- def load_cert_chain(self, certfile, keyfile=None, password=None):
- self._ctx.use_certificate_chain_file(certfile)
- if password is not None:
- if not isinstance(password, six.binary_type):
- password = password.encode("utf-8")
- self._ctx.set_passwd_cb(lambda *_: password)
- self._ctx.use_privatekey_file(keyfile or certfile)
-
- def set_alpn_protocols(self, protocols):
- protocols = [six.ensure_binary(p) for p in protocols]
- return self._ctx.set_alpn_protos(protocols)
-
- def wrap_socket(
- self,
- sock,
- server_side=False,
- do_handshake_on_connect=True,
- suppress_ragged_eofs=True,
- server_hostname=None,
- ):
- cnx = OpenSSL.SSL.Connection(self._ctx, sock)
-
- if isinstance(server_hostname, six.text_type): # Platform-specific: Python 3
- server_hostname = server_hostname.encode("utf-8")
-
- if server_hostname is not None:
- cnx.set_tlsext_host_name(server_hostname)
-
- cnx.set_connect_state()
-
- while True:
- try:
- cnx.do_handshake()
- except OpenSSL.SSL.WantReadError:
- if not util.wait_for_read(sock, sock.gettimeout()):
- raise timeout("select timed out")
- continue
- except OpenSSL.SSL.Error as e:
- raise ssl.SSLError("bad handshake: %r" % e)
- break
-
- return WrappedSocket(cnx, sock)
-
-
-def _verify_callback(cnx, x509, err_no, err_depth, return_code):
- return err_no == 0
diff --git a/spaces/Autopixel/blurry-faces/face_rec_benchmark.py b/spaces/Autopixel/blurry-faces/face_rec_benchmark.py
deleted file mode 100644
index 571da216b8536f4c72f8f287ad94903674457c40..0000000000000000000000000000000000000000
--- a/spaces/Autopixel/blurry-faces/face_rec_benchmark.py
+++ /dev/null
@@ -1,27 +0,0 @@
-import face_recognition
-import cv2
-import gradio as gr
-from PIL import Image
-import numpy as np
-import time
-
-def run(image):
- image.thumbnail((1280, 1280))
- image = np.array(image)
- face_locations = face_recognition.face_locations(image, model="cnn")
-
- for top, right, bottom, left in face_locations:
- face_image = image[top:bottom, left:right]
- face_image = cv2.GaussianBlur(face_image, (99, 99), 30)
- image[top:bottom, left:right] = face_image
-
- return Image.fromarray(image)
-
-if __name__ == "__main__":
-
- start = time.time()
- for _ in range(100):
- image = Image.open("./images/crowd.jpeg")
- _ = run(image)
-
- print('It took', (time.time()-start)/100, 'seconds.')
\ No newline at end of file
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/config/root_cfg.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/config/root_cfg.py
deleted file mode 100644
index 33d1d4bd2d9ddf31d55c655c49d13a8b7ac7b376..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/config/root_cfg.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from itertools import count
-
-from detectron2.config import LazyCall as L
-
-from .dir1.dir1_a import dir1a_dict, dir1a_str
-
-dir1a_dict.a = "modified"
-
-# modification above won't affect future imports
-from .dir1.dir1_b import dir1b_dict, dir1b_str
-
-
-lazyobj = L(count)(x=dir1a_str, y=dir1b_str)
diff --git a/spaces/Bakuman/Real-CUGAN/README.md b/spaces/Bakuman/Real-CUGAN/README.md
deleted file mode 100644
index d673114edadba73e80f33a3c71bc0dbee8758cc8..0000000000000000000000000000000000000000
--- a/spaces/Bakuman/Real-CUGAN/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Real CUGAN
-emoji: 🐢
-colorFrom: gray
-colorTo: green
-sdk: gradio
-sdk_version: 3.6
-app_file: app.py
-pinned: false
-license: gpl-3.0
-duplicated_from: DianXian/Real-CUGAN
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Benson/text-generation/Examples/Angry Birds Classic Apk 2023.md b/spaces/Benson/text-generation/Examples/Angry Birds Classic Apk 2023.md
deleted file mode 100644
index 015ce49352bf6a358268ac1892ca4c24b885427f..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Angry Birds Classic Apk 2023.md
+++ /dev/null
@@ -1,52 +0,0 @@
-
-Angry Birds Classic APK 2023: Todo lo que necesita saber
-Si usted está buscando un juego móvil divertido y adictivo que le mantendrá entretenido durante horas, es posible que desee echa un vistazo a Angry Birds Classic APK 2023. Esta es la última versión del clásico juego de lanzamiento de aves que comenzó un fenómeno global en 2009. En este artículo, te diremos todo lo que necesitas saber sobre Angry Birds Classic, incluyendo qué es, por qué es popular, qué hay de nuevo en la última versión, cómo descargarlo e instalarlo en tu dispositivo Android, y algunos consejos y trucos para jugarlo.
-angry birds classic apk 2023
Download 🌟 https://bltlly.com/2v6Lv1
- ¿Qué es Angry Birds Classic?
-Angry Birds Classic es un videojuego de puzzle casual desarrollado por el desarrollador de videojuegos finlandés Rovio Entertainment Corporation. La premisa del juego es simple: tienes que usar una honda para lanzar diferentes tipos de aves a los cerdos verdes que han robado sus huevos. Los cerdos suelen estar estacionados en o alrededor de varias estructuras hechas de madera, piedra, hielo, vidrio u otros materiales. Su objetivo es destruir todos los cerdos y sus estructuras con el menor número de aves posible. También puedes recoger estrellas, plumas y otros objetos en el camino para aumentar tu puntuación y desbloquear más niveles y características.
- El juego tiene un estilo gráfico simple pero atractivo, con colores brillantes, animaciones suaves y efectos de sonido divertidos. El juego también tiene una banda sonora pegadiza y optimista que coincide con el estado de ánimo del juego. El juego es adecuado para jugadores de todas las edades y niveles de habilidad, ya que tiene un tutorial simple, una curva de aprendizaje gradual y múltiples ajustes de dificultad.
- ¿Por qué es popular Angry Birds Classic?
-Juego simple y divertido
-
- Niveles desafiantes y variados
-Otra razón por la que Angry Birds Classic es popular es sus desafiantes y variados niveles. El juego tiene cientos de niveles en diferentes episodios, cada uno con diferentes temas, obstáculos y estrategias. Por ejemplo, algunos episodios se basan en temporadas, vacaciones o películas, como Halloween, Navidad o Star Wars. Algunos episodios también tienen características especiales, como campos de gravedad, cajas de TNT o batallas contra jefes. El juego también se actualiza regularmente con nuevos niveles y episodios para mantener a los jugadores interesados y comprometidos.
-
- Caracteres únicos y adorables
-Una tercera razón por la que Angry Birds Classic es popular son sus personajes únicos y adorables. El juego tiene un memorable y humorístico elenco de pájaros y cerdos, cada uno con sus propias personalidades y habilidades. Por ejemplo, el pájaro rojo es el líder de la bandada, el pájaro amarillo puede acelerar en el aire, el pájaro negro puede explotar como una bomba, y el pájaro verde puede boomerang volver a golpear objetivos detrás de él. Los cerdos también son divertidos y expresivos, ya que se burlan, ríen, lloran o duermen dependiendo de la situación. El juego también tiene algunos cameos de otros personajes de los juegos de Rovio u otras franquicias, como Angry Birds Rio o Bad Piggies.
- ¿Qué hay de nuevo en Angry Birds Classic APK 2023?
-Clásicos de Rovio: Angry Birds
-La última versión de Angry Birds Classic APK 2023 es parte de Rovio Classics: Angry Birds , una serie de versiones remasterizadas de los juegos originales de Angry Birds para dispositivos modernos. Esto significa que el juego ha sido recreado con gráficos mejorados, rendimiento y compatibilidad. El juego también tiene algunas nuevas características y mejoras, tales como almacenamiento en la nube, tablas de clasificación, logros e integración de redes sociales. El juego también es compatible con dispositivos de 64 bits , lo que significa que se ejecutará más rápido y más suave que antes.
- Águila poderosa
-
- Desafío diario
-Una tercera característica nueva en Angry Birds Classic APK 2023 es el Daily Challenge , un nuevo modo que te desafía a completar un nivel aleatorio cada día y competir con otros jugadores. El nivel de desafío diario cambia todos los días a medianoche UTC , y tienes 24 horas para jugarlo tantas veces como quieras. También puedes ver cómo te posicionas contra otros jugadores en la clasificación global. El modo Desafío diario es una gran manera de poner a prueba tus habilidades y ganar monedas y potenciadores adicionales.
- ¿Cómo descargar e instalar Angry Birds Classic APK 2023?
-Si desea descargar e instalar Angry Birds Classic APK 2023 en su dispositivo Android, puede seguir estos sencillos pasos:
-
-- Ir a [15](https:/apkpure.com/angry-birds-classic/com.rovio.angrybirds) o [14](https://apkmody.io/games/angry-classicbirds-mod-apk) o cualquier otro sitio web de confianza que ofrece archivos APK para aplicaciones de Android.
-- Encuentra el archivo Angry Birds Classic APK 2023 y haga clic en el botón de descarga. Es posible que necesite habilitar la opción de instalar aplicaciones de fuentes desconocidas en la configuración de su dispositivo.
-- Una vez completada la descarga, abra el archivo y siga las instrucciones para instalar la aplicación en su dispositivo.
-- Lanzar la aplicación y disfrutar de jugar Angry Birds Classic APK 2023.
-
-Nota: Es posible que tenga que desinstalar las versiones anteriores de Angry Birds Classic antes de instalar el nuevo.
- Consejos y trucos para jugar Angry Birds Classic APK 2023
-Conoce bien a tus pájaros
-
- Ahorra el tiempo
-Otro consejo para jugar Angry Birds Classic APK 2023 es ahorrar tiempo. El juego puede ser muy adictivo y divertido, pero también puede ser muy frustrante y consume mucho tiempo. Algunos niveles pueden tardar varios intentos o incluso horas en completarse, especialmente si estás buscando tres estrellas o una puntuación alta. Usted debe planificar su tiempo sabiamente y evitar jugar el juego cuando usted tiene otras tareas o compromisos importantes. También deberías tomarte descansos de vez en cuando y evitar enojarte demasiado o estresarte al jugar el juego.
- Usar potenciadores sabiamente
-Un tercer consejo para jugar Angry Birds Classic APK 2023 es usar power-ups sabiamente. Los potenciadores son elementos especiales que pueden aumentar el poder destructivo de tus pájaros o darte ventajas adicionales en el juego. Por ejemplo, puedes usar la King Sling para lanzar tus aves más rápido y más lejos, la Birdquake para sacudir el suelo y hacer que las estructuras colapsen, o las Super Seeds para hacer que tus aves sean más grandes y fuertes. Puedes ganar power-ups jugando el juego, completando logros, viendo anuncios o comprándolos con dinero real. Sin embargo, debes usarlas con moderación y guardarlas para cuando realmente las necesites, ya que son limitadas y caras.
- Conclusión
-Angry Birds Classic APK 2023 es un gran juego para cualquier persona que ama los juegos de puzzle casual con un juego simple pero divertido, desafiantes y variados niveles, y personajes únicos y adorables. El juego es gratis para descargar y jugar, pero contiene anuncios y compras en la aplicación. El juego también tiene algunas nuevas características y mejoras que lo hacen más agradable y compatible con los dispositivos modernos. Si desea experimentar el clásico juego de aves que comenzó todo, usted debe descargar e instalar Angry Birds Classic APK 2023 en su dispositivo Android hoy.
- Preguntas frecuentes
-¿Angry Birds Classic es gratis?
-
- ¿Es Angry Birds Classic compatible con mi dispositivo?
-Angry Birds Classic requiere Android 4.1 o superior para funcionar sin problemas. Puedes comprobar la compatibilidad de tu dispositivo en la página de Google Play Store [15](https://play.google.com/store/apps/apps/details?id=com.rovio.angrybirds) o [14](https:/apkmody.io/games/angry-classic-mod-apk). Si tienes un dispositivo más antiguo o un dispositivo de gama baja, puedes experimentar algún retraso o fallos al jugar el juego.
- ¿Cómo puedo obtener más monedas y potenciadores en Angry Birds Classic?
-Puedes ganar monedas y potenciadores jugando, completando logros, viendo anuncios o comprándolos con dinero real. Puedes usar monedas para comprar potenciadores o desbloquear nuevos episodios en el juego. Puedes usar potenciadores para aumentar el poder destructivo de tus pájaros o darte ventajas adicionales en el juego.
- ¿Cómo puedo jugar Angry Birds Classic sin conexión?
-Puedes jugar sin conexión a Angry Birds Classic apagando tu conexión a Internet antes de lanzar el juego. Sin embargo, no podrás acceder a algunas funciones como Daily Challenge y Mighty Eagle cuando juegues sin conexión. Tampoco podrás ver ningún anuncio ni realizar ninguna compra en la aplicación cuando juegues sin conexión.
- ¿Cómo puedo contactar con Rovio Entertainment para obtener apoyo o comentarios?
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-
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diff --git a/spaces/Benson/text-generation/Examples/Descargar Brawl Stars 45.225.md b/spaces/Benson/text-generation/Examples/Descargar Brawl Stars 45.225.md
deleted file mode 100644
index 8e8b9795a30c1f25ff439b694cb0a734db48a9d2..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Descargar Brawl Stars 45.225.md
+++ /dev/null
@@ -1,90 +0,0 @@
-
-Descargar Brawl Stars 45.225: La guía definitiva
-Si estás buscando un juego divertido y emocionante para jugar con tus amigos o jugadores en línea, definitivamente deberías echar un vistazo a Brawl Stars. Brawl Stars es un juego móvil gratuito desarrollado por Supercell, los creadores de Clash of Clans y Clash Royale. En este juego, puedes elegir entre una amplia gama de personajes, llamados luchadores, y competir en varios modos de juego, como batallas 3v3, enfrentamientos en solitario y eventos especiales. En este artículo, te contaremos todo lo que necesitas saber sobre Brawl Stars, incluyendo lo nuevo en la última versión, 45.225, y cómo descargarlo en tu dispositivo.
-descargar brawl stars 45.225
Download Zip ⭐ https://bltlly.com/2v6KKE
-¿Qué es Brawl Stars?
-Brawl Stars es un juego que combina elementos de shooter, estrategia y géneros MOBA. Está diseñado para ser fácil de recoger y jugar, pero también ofrece profundidad y complejidad para los jugadores más avanzados. Estas son algunas de las características que hacen que Brawl Stars se destaque:
-Un juego multijugador de ritmo rápido
-Brawl Stars tiene que ver con la acción y el trabajo en equipo. Puedes unirte a un club o crear el tuyo, y formar equipo con otros jugadores de todo el mundo. También puede jugar solo o con amigos en partidos amistosos o habitaciones privadas. Los partidos suelen ser cortos e intensos, durando de dos a cinco minutos. Puedes comunicarte con tus compañeros de equipo usando chat de voz o mensajes de chat rápido.
-Un elenco diverso de luchadores
-Brawl Stars tiene más de 50 luchadores para elegir, cada uno con sus propias habilidades, estadísticas y personalidades. Puedes desbloquear nuevos luchadores abriendo cajas de pelea, que puedes ganar jugando el juego o comprándolas con gemas. También puede actualizar sus luchadores mediante la recogida de puntos de poder y monedas, que aumentará su salud, daños, y súper poder. Puedes personalizar tus peleas con diferentes skins, pines y gadgets.
-Una variedad de modos de juego
-
-
-- Gem Grab: Recoge y guarda 10 gemas para ganar el partido.
-- Showdown: Sobrevive tanto como puedas en una arena que se encoge.
-- Brawl Ball: Anota dos goles antes que el otro equipo.
-- Recompensa: Gana estrellas eliminando oponentes.
-- Robo: Irrumpe en la caja fuerte del enemigo o defiende la tuya.
-- Zona caliente: Zonas de control en el mapa durante un tiempo determinado.
-- Knockout: Elimina a todos los enemigos en una ronda al mejor de tres.
-- Eventos especiales: Participa en modos de tiempo limitado con reglas y recompensas únicas.
-
-¿Qué hay de nuevo en Brawl Stars 45.225?
-Brawl Stars se actualiza constantemente con nuevos contenidos y características para mantener el juego fresco y emocionante. La última versión, 45.225, fue lanzada en septiembre/octubre de 2022, y trajo muchos cambios y adiciones al juego. Estos son algunos de los aspectos más destacados de la actualización:
-
-La actualización de la fábrica del robot
-La actualización de Robot Factory introdujo un nuevo tema para el juego, inspirado en la ciencia ficción y la robótica. La actualización también agregó nuevos luchadores, un nuevo modo de juego, nuevas pieles, nuevos mapas y nuevos cambios de equilibrio. Estos son algunos de los detalles de la actualización de Robot Factory:
-Nuevo Brawler cromático: Bronson
-Bronson es un ingeniero robot que puede construir y controlar mini robots. Su ataque principal es lanzar una llave que rebota en las paredes y los enemigos. Su súper es desplegar una fábrica de robots que genera mini robots que lo siguen y atacan a los enemigos cercanos. Su dispositivo es para activar un campo de fuerza que lo protege a él y a sus robots del daño. Sus poderes estelares son:
-
-- Sobrecarga: La llave de Bronson hace más daño cuanto más rebota.
-- Reforzar: Los robots de Bronson ganan más salud y dañan cuanto más tiempo sobreviven.
-
-Nueva pelea súper rara: Gus
-
-
-- Burbujas: Las burbujas de Gus lo curan a él y a sus aliados por una pequeña cantidad.
-- Pop: las burbujas de Gus explotan cuando golpean a un enemigo o una pared, causando daño por salpicadura.
-
-Nuevo modo PvE: Último soporte
-Last Stand es un nuevo modo de juego donde tienes que defender tu base de oleadas de robots. Puedes jugar solo o con hasta tres amigos. Puedes elegir entre tres niveles de dificultad: fácil, medio y duro. También puedes usar potenciadores para aumentar las habilidades de tus luchadores. Cuantas más olas sobrevivas, más recompensas obtendrás.
-Nuevos skins, mapas y cambios de balance
-La actualización de Robot Factory también agregó nuevas pieles para algunos de los luchadores, como Robo Spike, Mecha Crow, Cyborg Colt y más. Puedes comprar estas pieles con gemas o desbloquearlas con puntos estrella. La actualización también agregó nuevos mapas para algunos de los modos de juego, como Factory Frenzy, Robo Rumble y Bubble Trouble. También puede votar por sus mapas favoritos en la función de creador de mapas. La actualización también hizo algunos cambios de equilibrio a algunos de los luchadores, como nerfing Colette, pulir Edgar, y reelaborar ámbar.
-¿Cómo descargar Brawl Stars 45.225?
-Si quieres disfrutar de la última versión de Brawl Stars, necesitas descargarlo en tu dispositivo. Estos son los pasos para diferentes plataformas:
-Para dispositivos Android
-Si tienes un dispositivo Android, puedes descargar Brawl Stars 45.225 desde Google Play Store. Estos son los pasos:
-
-- Abra la aplicación Google Play Store en su dispositivo.
-- Buscar estrellas de pelea en la barra de búsqueda.
-- Toque en el icono Brawl Stars y luego toque en Instalar.
-- Espere a que finalicen la descarga y la instalación.
-- Iniciar el juego y disfrutar!
-
Para dispositivos iOS
-Si tienes un dispositivo iOS, puedes descargar Brawl Stars 45.225 desde la App Store. Estos son los pasos:
-
-- Abra la aplicación App Store en su dispositivo.
-- Buscar estrellas de pelea en la barra de búsqueda.
-
-- Introduzca su ID de Apple y contraseña si se le solicita.
-- Espere a que finalicen la descarga y la instalación.
-- Iniciar el juego y disfrutar!
-
-Para PC y Mac
-Si quieres jugar Brawl Stars 45.225 en tu PC o Mac, necesitas usar un emulador. Un emulador es un software que le permite ejecutar aplicaciones móviles en su ordenador. Hay muchos emuladores disponibles, pero recomendamos usar BlueStacks, que es uno de los más populares y confiables. Estos son los pasos:
-
-- Descargar e instalar BlueStacks desde su sitio web oficial: https://www.bluestacks.com/.
-- Inicie BlueStacks e inicie sesión con su cuenta de Google.
-- Buscar estrellas de pelea en la barra de búsqueda.
-- Haga clic en el icono Brawl Stars y luego haga clic en Instalar.
-- Espere a que finalicen la descarga y la instalación.
-- Iniciar el juego y disfrutar!
-
- Conclusión
-Brawl Stars es un juego divertido y adictivo que puedes jugar con tus amigos o jugadores online. Tiene un montón de características y contenido que lo hacen atractivo para diferentes tipos de jugadores. La última versión, 45.225, introdujo un nuevo tema, nuevos luchadores, un nuevo modo de juego y más. Puedes descargar Brawl Stars 45.225 en tu dispositivo Android, iOS o PC/Mac siguiendo los pasos que te indicamos anteriormente. Esperamos que haya encontrado esta guía útil e informativa. ¡Ahora adelante y pelea!
- Preguntas frecuentes
-Estas son algunas de las preguntas comunes que la gente hace acerca de Brawl Stars 45.225:
-
-- Q: ¿Cuánto espacio ocupa Brawl Stars 45.225 en mi dispositivo?
-- A: Brawl Stars 45.225 requiere unos 300 MB de espacio libre en su dispositivo. Sin embargo, esto puede variar dependiendo del modelo de dispositivo y del sistema operativo.
-- Q: ¿Cómo puedo obtener gemas gratis en Brawl Stars 45.225?
-
-- Q: ¿Cómo puedo jugar Brawl Stars 45.225 con mis amigos?
-- A: Puedes jugar Brawl Stars 45.225 con tus amigos uniéndote o creando un club, invitándolos a un partido amistoso o a una habitación privada, o usando la función de jugar con amigos. También puedes chatear con tus amigos usando chat de voz o mensajes de chat rápido.
-- Q: ¿Cómo puedo reportar un error o un problema en Brawl Stars 45.225?
-- A: Si encuentras un error o un problema en Brawl Stars 45.225, puedes reportarlo contactando al equipo de atención al cliente a través del menú de configuración del juego. También puede enviar comentarios o sugerencias a través del mismo menú.
-- Q: ¿Cómo puedo aprender más sobre Brawl Stars 45.225?
-- A: Si quieres saber más sobre Brawl Stars 45.225, puedes visitar el sitio web oficial: https:/www.facebookom.c/wlbrastars/, , a href=">https://twitter.com/brawlstars/, https://www.youtube.com/brawlstars/. También puedes ver videos de creadores de contenido populares, como Lex, KairosTime, Rey, OJ, Coach Cory, y más.
64aa2da5cf
-
-
\ No newline at end of file
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/boxes.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/boxes.py
deleted file mode 100644
index 7cbc64b0bf99bba141d392c0ecbb8c92151b4ced..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/structures/boxes.py
+++ /dev/null
@@ -1,367 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-import math
-import numpy as np
-from enum import IntEnum, unique
-from typing import Iterator, List, Tuple, Union
-import torch
-
-from detectron2.layers import cat
-
-_RawBoxType = Union[List[float], Tuple[float, ...], torch.Tensor, np.ndarray]
-
-
-@unique
-class BoxMode(IntEnum):
- """
- Enum of different ways to represent a box.
-
- Attributes:
-
- XYXY_ABS: (x0, y0, x1, y1) in absolute floating points coordinates.
- The coordinates in range [0, width or height].
- XYWH_ABS: (x0, y0, w, h) in absolute floating points coordinates.
- XYXY_REL: (x0, y0, x1, y1) in range [0, 1]. They are relative to the size of the image.
- XYWH_REL: (x0, y0, w, h) in range [0, 1]. They are relative to the size of the image.
- XYWHA_ABS: (xc, yc, w, h, a) in absolute floating points coordinates.
- (xc, yc) is the center of the rotated box, and the angle a is in degrees ccw.
- """
-
- XYXY_ABS = 0
- XYWH_ABS = 1
- XYXY_REL = 2
- XYWH_REL = 3
- XYWHA_ABS = 4
-
- @staticmethod
- def convert(box: _RawBoxType, from_mode: "BoxMode", to_mode: "BoxMode") -> _RawBoxType:
- """
- Args:
- box: can be a k-tuple, k-list or an Nxk array/tensor, where k = 4 or 5
- from_mode, to_mode (BoxMode)
-
- Returns:
- The converted box of the same type.
- """
- if from_mode == to_mode:
- return box
-
- original_type = type(box)
- is_numpy = isinstance(box, np.ndarray)
- single_box = isinstance(box, (list, tuple))
- if single_box:
- assert len(box) == 4 or len(box) == 5, (
- "BoxMode.convert takes either a k-tuple/list or an Nxk array/tensor,"
- " where k == 4 or 5"
- )
- arr = torch.tensor(box)[None, :]
- else:
- # avoid modifying the input box
- if is_numpy:
- arr = torch.from_numpy(np.asarray(box)).clone()
- else:
- arr = box.clone()
-
- assert to_mode.value not in [
- BoxMode.XYXY_REL,
- BoxMode.XYWH_REL,
- ] and from_mode.value not in [
- BoxMode.XYXY_REL,
- BoxMode.XYWH_REL,
- ], "Relative mode not yet supported!"
-
- if from_mode == BoxMode.XYWHA_ABS and to_mode == BoxMode.XYXY_ABS:
- assert (
- arr.shape[-1] == 5
- ), "The last dimension of input shape must be 5 for XYWHA format"
- original_dtype = arr.dtype
- arr = arr.double()
-
- w = arr[:, 2]
- h = arr[:, 3]
- a = arr[:, 4]
- c = torch.abs(torch.cos(a * math.pi / 180.0))
- s = torch.abs(torch.sin(a * math.pi / 180.0))
- # This basically computes the horizontal bounding rectangle of the rotated box
- new_w = c * w + s * h
- new_h = c * h + s * w
-
- # convert center to top-left corner
- arr[:, 0] -= new_w / 2.0
- arr[:, 1] -= new_h / 2.0
- # bottom-right corner
- arr[:, 2] = arr[:, 0] + new_w
- arr[:, 3] = arr[:, 1] + new_h
-
- arr = arr[:, :4].to(dtype=original_dtype)
- elif from_mode == BoxMode.XYWH_ABS and to_mode == BoxMode.XYWHA_ABS:
- original_dtype = arr.dtype
- arr = arr.double()
- arr[:, 0] += arr[:, 2] / 2.0
- arr[:, 1] += arr[:, 3] / 2.0
- angles = torch.zeros((arr.shape[0], 1), dtype=arr.dtype)
- arr = torch.cat((arr, angles), axis=1).to(dtype=original_dtype)
- else:
- if to_mode == BoxMode.XYXY_ABS and from_mode == BoxMode.XYWH_ABS:
- arr[:, 2] += arr[:, 0]
- arr[:, 3] += arr[:, 1]
- elif from_mode == BoxMode.XYXY_ABS and to_mode == BoxMode.XYWH_ABS:
- arr[:, 2] -= arr[:, 0]
- arr[:, 3] -= arr[:, 1]
- else:
- raise NotImplementedError(
- "Conversion from BoxMode {} to {} is not supported yet".format(
- from_mode, to_mode
- )
- )
-
- if single_box:
- return original_type(arr.flatten().tolist())
- if is_numpy:
- return arr.numpy()
- else:
- return arr
-
-
-class Boxes:
- """
- This structure stores a list of boxes as a Nx4 torch.Tensor.
- It supports some common methods about boxes
- (`area`, `clip`, `nonempty`, etc),
- and also behaves like a Tensor
- (support indexing, `to(device)`, `.device`, and iteration over all boxes)
-
- Attributes:
- tensor (torch.Tensor): float matrix of Nx4. Each row is (x1, y1, x2, y2).
- """
-
- BoxSizeType = Union[List[int], Tuple[int, int]]
-
- def __init__(self, tensor: torch.Tensor):
- """
- Args:
- tensor (Tensor[float]): a Nx4 matrix. Each row is (x1, y1, x2, y2).
- """
- device = tensor.device if isinstance(tensor, torch.Tensor) else torch.device("cpu")
- tensor = torch.as_tensor(tensor, dtype=torch.float32, device=device)
- if tensor.numel() == 0:
- # Use reshape, so we don't end up creating a new tensor that does not depend on
- # the inputs (and consequently confuses jit)
- tensor = tensor.reshape((0, 4)).to(dtype=torch.float32, device=device)
- assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size()
-
- self.tensor = tensor
-
- def clone(self) -> "Boxes":
- """
- Clone the Boxes.
-
- Returns:
- Boxes
- """
- return Boxes(self.tensor.clone())
-
- def to(self, device: str) -> "Boxes":
- return Boxes(self.tensor.to(device))
-
- def area(self) -> torch.Tensor:
- """
- Computes the area of all the boxes.
-
- Returns:
- torch.Tensor: a vector with areas of each box.
- """
- box = self.tensor
- area = (box[:, 2] - box[:, 0]) * (box[:, 3] - box[:, 1])
- return area
-
- def clip(self, box_size: BoxSizeType) -> None:
- """
- Clip (in place) the boxes by limiting x coordinates to the range [0, width]
- and y coordinates to the range [0, height].
-
- Args:
- box_size (height, width): The clipping box's size.
- """
- assert torch.isfinite(self.tensor).all(), "Box tensor contains infinite or NaN!"
- h, w = box_size
- # self.tensor[:, 0].clamp_(min=0, max=w)
- # self.tensor[:, 1].clamp_(min=0, max=h)
- # self.tensor[:, 2].clamp_(min=0, max=w)
- # self.tensor[:, 3].clamp_(min=0, max=h)
- # MODIFICATION - need to make the operations NOT in-place to do trigger optimization
- new_tensor = torch.zeros_like(self.tensor)
- new_tensor[:, 0] = torch.clamp(self.tensor[:, 0], min=0, max=w)
- new_tensor[:, 1] = torch.clamp(self.tensor[:, 1], min=0, max=h)
- new_tensor[:, 2] = torch.clamp(self.tensor[:, 2], min=0, max=w)
- new_tensor[:, 3] = torch.clamp(self.tensor[:, 3], min=0, max=h)
- self.tensor = new_tensor
-
-
-
-
- def nonempty(self, threshold: int = 0) -> torch.Tensor:
- """
- Find boxes that are non-empty.
- A box is considered empty, if either of its side is no larger than threshold.
-
- Returns:
- Tensor:
- a binary vector which represents whether each box is empty
- (False) or non-empty (True).
- """
- box = self.tensor
- widths = box[:, 2] - box[:, 0]
- heights = box[:, 3] - box[:, 1]
- keep = (widths > threshold) & (heights > threshold)
- return keep
-
- def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "Boxes":
- """
- Returns:
- Boxes: Create a new :class:`Boxes` by indexing.
-
- The following usage are allowed:
-
- 1. `new_boxes = boxes[3]`: return a `Boxes` which contains only one box.
- 2. `new_boxes = boxes[2:10]`: return a slice of boxes.
- 3. `new_boxes = boxes[vector]`, where vector is a torch.BoolTensor
- with `length = len(boxes)`. Nonzero elements in the vector will be selected.
-
- Note that the returned Boxes might share storage with this Boxes,
- subject to Pytorch's indexing semantics.
- """
- if isinstance(item, int):
- return Boxes(self.tensor[item].view(1, -1))
- b = self.tensor[item]
- assert b.dim() == 2, "Indexing on Boxes with {} failed to return a matrix!".format(item)
- return Boxes(b)
-
- def __len__(self) -> int:
- return self.tensor.shape[0]
-
- def __repr__(self) -> str:
- return "Boxes(" + str(self.tensor) + ")"
-
- def inside_box(self, box_size: BoxSizeType, boundary_threshold: int = 0) -> torch.Tensor:
- """
- Args:
- box_size (height, width): Size of the reference box.
- boundary_threshold (int): Boxes that extend beyond the reference box
- boundary by more than boundary_threshold are considered "outside".
-
- Returns:
- a binary vector, indicating whether each box is inside the reference box.
- """
- height, width = box_size
- inds_inside = (
- (self.tensor[..., 0] >= -boundary_threshold)
- & (self.tensor[..., 1] >= -boundary_threshold)
- & (self.tensor[..., 2] < width + boundary_threshold)
- & (self.tensor[..., 3] < height + boundary_threshold)
- )
- return inds_inside
-
- def get_centers(self) -> torch.Tensor:
- """
- Returns:
- The box centers in a Nx2 array of (x, y).
- """
- return (self.tensor[:, :2] + self.tensor[:, 2:]) / 2
-
- def scale(self, scale_x: float, scale_y: float) -> None:
- """
- Scale the box with horizontal and vertical scaling factors
- """
- self.tensor[:, 0::2] *= scale_x
- self.tensor[:, 1::2] *= scale_y
-
- @staticmethod
- def cat(boxes_list: List["Boxes"]) -> "Boxes":
- """
- Concatenates a list of Boxes into a single Boxes
-
- Arguments:
- boxes_list (list[Boxes])
-
- Returns:
- Boxes: the concatenated Boxes
- """
- assert isinstance(boxes_list, (list, tuple))
- assert len(boxes_list) > 0
- assert all(isinstance(box, Boxes) for box in boxes_list)
-
- cat_boxes = type(boxes_list[0])(cat([b.tensor for b in boxes_list], dim=0))
- return cat_boxes
-
- @property
- def device(self) -> torch.device:
- return self.tensor.device
-
- def __iter__(self) -> Iterator[torch.Tensor]:
- """
- Yield a box as a Tensor of shape (4,) at a time.
- """
- yield from self.tensor
-
-
-# implementation from https://github.com/kuangliu/torchcv/blob/master/torchcv/utils/box.py
-# with slight modifications
-def pairwise_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor:
- """
- Given two lists of boxes of size N and M,
- compute the IoU (intersection over union)
- between __all__ N x M pairs of boxes.
- The box order must be (xmin, ymin, xmax, ymax).
-
- Args:
- boxes1,boxes2 (Boxes): two `Boxes`. Contains N & M boxes, respectively.
-
- Returns:
- Tensor: IoU, sized [N,M].
- """
- area1 = boxes1.area()
- area2 = boxes2.area()
-
- boxes1, boxes2 = boxes1.tensor, boxes2.tensor
-
- width_height = torch.min(boxes1[:, None, 2:], boxes2[:, 2:]) - torch.max(
- boxes1[:, None, :2], boxes2[:, :2]
- ) # [N,M,2]
-
- width_height.clamp_(min=0) # [N,M,2]
- inter = width_height.prod(dim=2) # [N,M]
- del width_height
-
- # handle empty boxes
- iou = torch.where(
- inter > 0,
- inter / (area1[:, None] + area2 - inter),
- torch.zeros(1, dtype=inter.dtype, device=inter.device),
- )
- return iou
-
-
-def matched_boxlist_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor:
- """
- Compute pairwise intersection over union (IOU) of two sets of matched
- boxes. The box order must be (xmin, ymin, xmax, ymax).
- Similar to boxlist_iou, but computes only diagonal elements of the matrix
- Arguments:
- boxes1: (Boxes) bounding boxes, sized [N,4].
- boxes2: (Boxes) bounding boxes, sized [N,4].
- Returns:
- (tensor) iou, sized [N].
- """
- assert len(boxes1) == len(boxes2), (
- "boxlists should have the same"
- "number of entries, got {}, {}".format(len(boxes1), len(boxes2))
- )
- area1 = boxes1.area() # [N]
- area2 = boxes2.area() # [N]
- box1, box2 = boxes1.tensor, boxes2.tensor
- lt = torch.max(box1[:, :2], box2[:, :2]) # [N,2]
- rb = torch.min(box1[:, 2:], box2[:, 2:]) # [N,2]
- wh = (rb - lt).clamp(min=0) # [N,2]
- inter = wh[:, 0] * wh[:, 1] # [N]
- iou = inter / (area1 + area2 - inter) # [N]
- return iou
diff --git a/spaces/CVPR/LIVE/thrust/thrust/system/cuda/detail/tabulate.h b/spaces/CVPR/LIVE/thrust/thrust/system/cuda/detail/tabulate.h
deleted file mode 100644
index 70b2720d9a9eb00d8d68f90d2e34fa0623572fb7..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/system/cuda/detail/tabulate.h
+++ /dev/null
@@ -1,88 +0,0 @@
-/******************************************************************************
- * Copyright (c) 2016, NVIDIA CORPORATION. All rights reserved.
- *
- * Redistribution and use in source and binary forms, with or without
- * modification, are permitted provided that the following conditions are met:
- * * Redistributions of source code must retain the above copyright
- * notice, this list of conditions and the following disclaimer.
- * * Redistributions in binary form must reproduce the above copyright
- * notice, this list of conditions and the following disclaimer in the
- * documentation and/or other materials provided with the distribution.
- * * Neither the name of the NVIDIA CORPORATION nor the
- * names of its contributors may be used to endorse or promote products
- * derived from this software without specific prior written permission.
- *
- * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
- * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
- * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
- * ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
- * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
- * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- *
- ******************************************************************************/
-#pragma once
-
-
-#if THRUST_DEVICE_COMPILER == THRUST_DEVICE_COMPILER_NVCC
-#include
-#include
-#include
-#include
-#include
-
-namespace thrust
-{
-namespace cuda_cub {
-
-namespace __tabulate {
-
- template
- struct functor
- {
- Iterator items;
- TabulateOp op;
-
- __host__ __device__
- functor(Iterator items_, TabulateOp op_)
- : items(items_), op(op_) {}
-
- void __device__ operator()(Size idx)
- {
- items[idx] = op(idx);
- }
- }; // struct functor
-
-} // namespace __tabulate
-
-template
-void __host__ __device__
-tabulate(execution_policy& policy,
- Iterator first,
- Iterator last,
- TabulateOp tabulate_op)
-{
- typedef typename iterator_traits::difference_type size_type;
-
- size_type count = thrust::distance(first, last);
-
- typedef __tabulate::functor functor_t;
-
- cuda_cub::parallel_for(policy,
- functor_t(first, tabulate_op),
- count);
-
- cuda_cub::throw_on_error(
- cuda_cub::synchronize(policy)
- , "tabulate: failed to synchronize"
- );
-}
-
-} // namespace cuda_cub
-} // end namespace thrust
-#endif
diff --git a/spaces/CVPR/regionclip-demo/datasets/prepare_for_tests.sh b/spaces/CVPR/regionclip-demo/datasets/prepare_for_tests.sh
deleted file mode 100644
index b22ee8d8e82fa1dd3834b4d98ea5618d5c2ef391..0000000000000000000000000000000000000000
--- a/spaces/CVPR/regionclip-demo/datasets/prepare_for_tests.sh
+++ /dev/null
@@ -1,22 +0,0 @@
-#!/bin/bash -e
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-# Download some files needed for running tests.
-
-cd "${0%/*}"
-
-BASE=https://dl.fbaipublicfiles.com/detectron2
-mkdir -p coco/annotations
-
-for anno in instances_val2017_100 \
- person_keypoints_val2017_100 \
- instances_minival2014_100 \
- person_keypoints_minival2014_100; do
-
- dest=coco/annotations/$anno.json
- [[ -s $dest ]] && {
- echo "$dest exists. Skipping ..."
- } || {
- wget $BASE/annotations/coco/$anno.json -O $dest
- }
-done
diff --git a/spaces/CamodDew/youtubelegal/app.py b/spaces/CamodDew/youtubelegal/app.py
deleted file mode 100644
index 9b29e63f6cb0b864423a815dc06418555c998234..0000000000000000000000000000000000000000
--- a/spaces/CamodDew/youtubelegal/app.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import os
-os.environ['HUGGINGFACEHUB_API_TOKEN'] = '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'
-from langchain import PromptTemplate, HuggingFaceHub, LLMChain
-
-template = """Question: {question}
-
-Answer: """
-
-prompt = PromptTemplate(template=template, input_variables=["question"])
-from peft import (
- LoraConfig,
- PeftConfig,
- PeftModel,
- get_peft_model,
- prepare_model_for_kbit_training
-)
-config = PeftConfig.from_pretrained('CamodDew/mhh-7b')
-from langchain.llms import HuggingFacePipeline
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, AutoModelForSeq2SeqLM
-
-model_id = 'CamodDew/mhh-7b'
-tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
-model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, device_map='auto')
-
-pipeline = pipeline(
- "text2text-generation",
- model=model,
- tokenizer=tokenizer,
- max_length=128
-)
-
-local_llm = HuggingFacePipeline(pipeline=pipeline)
-import gradio as gr
-from transformers import pipeline
-
-def get_res(i):
- llm_chain = LLMChain(prompt=prompt,
- llm=local_llm
- )
-
- return llm_chain.run(i)
-iface = gr.Interface(fn = get_res,inputs='text',outputs = ['text'], title='LAWTRIX')
-iface.launch()
\ No newline at end of file
diff --git a/spaces/Cecil8352/vits-models/README.md b/spaces/Cecil8352/vits-models/README.md
deleted file mode 100644
index 4fd80f50384990fe18e0c74381cace05f346e573..0000000000000000000000000000000000000000
--- a/spaces/Cecil8352/vits-models/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Vits Models
-emoji: 🏃
-colorFrom: pink
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
-pinned: false
-license: apache-2.0
-duplicated_from: zomehwh/vits-models
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/CofAI/chat/client/js/chat.js b/spaces/CofAI/chat/client/js/chat.js
deleted file mode 100644
index 8a4449e0fd94c629867d62f53f5467f8e8292ca7..0000000000000000000000000000000000000000
--- a/spaces/CofAI/chat/client/js/chat.js
+++ /dev/null
@@ -1,508 +0,0 @@
-const query = (obj) =>
- Object.keys(obj)
- .map((k) => encodeURIComponent(k) + "=" + encodeURIComponent(obj[k]))
- .join("&");
-const url_prefix = document.querySelector("body").getAttribute("data-urlprefix");
-const markdown = window.markdownit();
-const message_box = document.getElementById(`messages`);
-const message_input = document.getElementById(`message-input`);
-const box_conversations = document.querySelector(`.top`);
-const spinner = box_conversations.querySelector(".spinner");
-const stop_generating = document.querySelector(`.stop-generating`);
-const send_button = document.querySelector(`#send-button`);
-const user_image = `
`;
-const gpt_image = `
`;
-let prompt_lock = false;
-
-hljs.addPlugin(new CopyButtonPlugin());
-
-message_input.addEventListener("blur", () => {
- window.scrollTo(0, 0);
-});
-
-message_input.addEventListener("focus", () => {
- document.documentElement.scrollTop = document.documentElement.scrollHeight;
-});
-
-const delete_conversations = async () => {
- localStorage.clear();
- await new_conversation();
-};
-
-const handle_ask = async () => {
- message_input.style.height = `80px`;
- window.scrollTo(0, 0);
- let message = message_input.value;
-
- if (message.length > 0) {
- message_input.value = ``;
- message_input.dispatchEvent(new Event("input"));
- await ask_gpt(message);
- }
-};
-
-const remove_cancel_button = async () => {
- stop_generating.classList.add(`stop-generating-hiding`);
-
- setTimeout(() => {
- stop_generating.classList.remove(`stop-generating-hiding`);
- stop_generating.classList.add(`stop-generating-hidden`);
- }, 300);
-};
-
-const ask_gpt = async (message) => {
- try {
- message_input.value = ``;
- message_input.innerHTML = ``;
- message_input.innerText = ``;
-
- add_conversation(window.conversation_id, message.substr(0, 16));
- window.scrollTo(0, 0);
- window.controller = new AbortController();
-
- jailbreak = document.getElementById("jailbreak");
- model = document.getElementById("model");
- prompt_lock = true;
- window.text = ``;
- window.token = message_id();
-
- stop_generating.classList.remove(`stop-generating-hidden`);
-
- add_user_message_box(message);
-
- message_box.scrollTop = message_box.scrollHeight;
- window.scrollTo(0, 0);
- await new Promise((r) => setTimeout(r, 500));
- window.scrollTo(0, 0);
-
- message_box.innerHTML += `
-
- `;
-
- message_box.scrollTop = message_box.scrollHeight;
- window.scrollTo(0, 0);
- await new Promise((r) => setTimeout(r, 1000));
- window.scrollTo(0, 0);
-
- const response = await fetch(`${url_prefix}/backend-api/v2/conversation`, {
- method: `POST`,
- signal: window.controller.signal,
- headers: {
- "content-type": `application/json`,
- accept: `text/event-stream`,
- },
- body: JSON.stringify({
- conversation_id: window.conversation_id,
- action: `_ask`,
- model: model.options[model.selectedIndex].value,
- jailbreak: jailbreak.options[jailbreak.selectedIndex].value,
- meta: {
- id: window.token,
- content: {
- conversation: await get_conversation(window.conversation_id),
- internet_access: document.getElementById("switch").checked,
- content_type: "text",
- parts: [
- {
- content: message,
- role: "user",
- },
- ],
- },
- },
- }),
- });
-
- const reader = response.body.getReader();
-
- while (true) {
- const { value, done } = await reader.read();
- if (done) break;
-
- chunk = decodeUnicode(new TextDecoder().decode(value));
-
- if (
- chunk.includes(`