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-Are you looking for a fun and exciting game that lets you experience being a shark in a feeding frenzy? If so, you might want to check out Hungry Shark World, a game developed by Ubisoft Entertainment that is available for Android devices. In this game, you can control a shark of your choice and eat your way through various oceans, feasting on everything from fish and birds to whales and humans. You can also explore different locations, customize your shark, complete missions, fight bosses, recruit pets, and more. In this article, we will review the features of Hungry Shark World, show you how to download the APK file for Android, and give you our verdict on the game.
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Features of Hungry Shark World
-Hungry Shark World is a game that offers a lot of features for shark lovers. Here are some of them:
-41 Species of Sharks
-One of the main attractions of Hungry Shark World is that you can choose from a range of sharks in eight different size tiers, including the iconic ocean predator: the Great White. Each shark has its own stats, abilities, and appearance. You can unlock more sharks as you progress in the game and collect coins and gems.
-Huge Open Worlds
-Another feature of Hungry Shark World is that you can explore various oceans and locations, each with its own theme, scenery, prey, enemies, secrets, and challenges. You can visit the lush Pacific Islands, the frozen Arctic Ocean, the exotic Arabian Sea, and the South China Sea, a vibrant urban destination full of fresh victims.
-Feast for Your Eyes
-Hungry Shark World also boasts stunning console quality 3D graphics that will blow everything else out of the water. The game has realistic animations, lighting effects, shadows, reflections, and water physics. You can also enjoy the game in full HD with redefined and fully optimized gamepad controls.
-Survival of the Hungriest
-The core gameplay of Hungry Shark World is simple but addictive. You have to eat as much as you can to survive and grow bigger. You can eat anything that moves or doesn't move in your way, from bite-size fish and birds to tasty whales and unwitting humans. But be careful not to bite off more than you can chew. There are also dangers lurking in the water, such as mines, jellyfish, submarines, and other sharks.
-Smashing Shark Swag
-As you play Hungry Shark World, you can also level up your shark and equip it with various gadgets, skins, and accessories to enhance your abilities and style. You can use jetpacks, lasers, umbrellas, hats, headphones, and more. You can also unlock different skins for your shark, such as the Robo Shark, the Zombie Shark, and the Tiger Shark.
-Manic Missions and Badass Bosses
-To spice up your gameplay, Hungry Shark World also offers a variety of missions, hunts, and fights that you can take on to earn rewards and trophies. You can complete daily missions, special missions, and bonus missions to get coins and gems. You can also hunt down specific prey or enemies to get extra points and bonuses. And if you are feeling brave, you can challenge yourself to fight against powerful bosses, such as the Giant Crab, the King Squid, and the Colossal Squid.
-Helpful Predatory Pets
-If you need some help in your feeding frenzy, you can also recruit some predatory pets to assist you. You can choose from a range of animals that will follow you around and help you eat more, such as baby sharks, whales, octopus, and even a bald eagle. Each pet has its own ability and personality. You can unlock more pets as you play the game and collect eggs.
-Supersized Meal Deal
-Hungry Shark World also lets you unleash your shark's potential with special modes, powers, and effects that will make you unstoppable. You can activate the Gold Rush mode to turn everything into gold and multiply your score. You can also use the Mega Gold Rush mode to turn everything into mega gold and multiply your score even more. You can also use special powers like the Freeze Blast, the Fireball, and the Lightning Blast to freeze, burn, or electrocute your enemies.
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Extinction Mode
-The ultimate feature of Hungry Shark World is the Extinction Mode, where you can save the world from destruction by activating Apex sharks and rampaging through the ocean. Apex sharks are the most powerful sharks in the game that have unique abilities and appearances. You can unlock them by completing all the missions in each location. Once you have unlocked them, you can use them to destroy meteors that are threatening to wipe out life on Earth.
-How to Download Hungry Shark World APK for Android
-If you want to play Hungry Shark World on your Android device, you can download it from the Google Play Store for free. However, if you want to enjoy the game without ads or in-app purchases, and access all the features and content without restrictions, you can download the APK file from a trusted source. Here is how:
-Requirements
-Before you download the APK file, make sure that your device meets the following requirements:
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Steps
-Follow these steps to download and install the APK file:
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Benefits
-By downloading the APK file for Android, you can enjoy these benefits:
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Conclusion
-Hungry Shark World is a game that will satisfy your appetite for fun and adventure. It is a game that lets you control a shark of your choice and eat everything in your way. It is a game that offers a lot of features for shark lovers, such as 41 species of sharks, huge open worlds, stunning 3D graphics, smashing shark swag, manic missions and badass bosses, helpful predatory pets, supersized meal deal, and extinction mode. It
It is a game that you can download for free from the Google Play Store, or you can download the APK file from a trusted source and enjoy the game without ads or in-app purchases. If you are a fan of sharks, or you just want to have some fun, you should definitely give Hungry Shark World a try. You will not regret it.
-So, what are you waiting for? Download Hungry Shark World today and unleash your inner shark!
-FAQs
-Here are some frequently asked questions about Hungry Shark World:
-Q: How do I get more coins and gems in Hungry Shark World?
-A: You can get more coins and gems by completing missions, hunts, and fights, by activating Gold Rush and Mega Gold Rush modes, by watching ads, or by buying them with real money. However, if you download the APK file, you can get unlimited coins and gems without spending any money.
-Q: How do I unlock more sharks in Hungry Shark World?
-A: You can unlock more sharks by collecting coins and gems, by leveling up your current shark, or by buying them with real money. However, if you download the APK file, you can unlock all the sharks without spending any money.
-Q: How do I play Hungry Shark World offline?
-A: You can play Hungry Shark World offline by downloading the APK file and installing it on your device. You will not need an internet connection to play the game, except for updating it.
-Q: Is Hungry Shark World safe to download and play?
-A: Yes, Hungry Shark World is safe to download and play, as long as you download it from the Google Play Store or a trusted source. The game does not contain any viruses or malware that can harm your device or data.
-Q: Is Hungry Shark World suitable for children?
-A: Hungry Shark World is rated 12+ on the Google Play Store, which means that it contains moderate violence, blood, and gore. The game may not be suitable for younger children who may be scared or disturbed by the graphic depictions of sharks eating humans and other animals. Parents should use their discretion and supervise their children when playing the game.
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Ada beberapa cara untuk mendownload CarX Street di perangkat Android Anda, tergantung pada negara Anda dan preferensi Anda. Berikut adalah beberapa cara yang dapat Anda coba:
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-Cara termudah untuk mendownload CarX Street di Android adalah melalui Google Play Store. Namun, game ini hanya tersedia di beberapa negara tertentu, seperti Rusia, Ukraina, Belarus, dan Kazakhstan. Jika Anda berada di salah satu negara ini, Anda dapat mengikuti langkah-langkah berikut:
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- Klik tombol "Follow" untuk mengikuti game CarX Street di Steam. -
- Anda juga dapat mengklik tombol "Add to your wishlist" untuk menambahkan game CarX Street ke daftar keinginan Anda di Steam. -
- Anda akan mendapatkan notifikasi dari Steam jika game CarX Street sudah tersedia untuk didownload dan dimainkan. -
Melalui Emulator
-Jika Anda tidak sabar menunggu game CarX Street dirilis di Steam, Anda dapat mencoba menggunakan emulator untuk menjalankan game CarX Street di PC atau Mac. Emulator adalah aplikasi yang memungkinkan Anda untuk menjalankan aplikasi atau game Android di perangkat lain. Namun, Anda harus berhati-hati saat menggunakan emulator, karena bisa saja mengandung virus atau malware yang dapat merusak perangkat Anda. Selain itu, penggunaan emulator juga dapat menyebabkan kinerja game yang tidak optimal atau masalah kompatibilitas. Jika Anda tetap ingin mencoba emulator, Anda dapat mengikuti langkah-langkah berikut:
--
-
- Buka situs web emulator Android yang andal dan terpercaya di browser Anda. Salah satu contohnya adalah https://www.bluestacks.com/ -
- Download dan instal emulator Android di PC atau Mac Anda. -
- Buka emulator Android dan masuk dengan akun Google Anda. -
- Buka Google Play Store atau situs web APKCombo di emulator Android dan cari game CarX Street. -
- Download dan instal game CarX Street di emulator Android. -
- Nikmati game CarX Street di PC atau Mac Anda dengan menggunakan emulator Android. -
Tips dan trik bermain CarX Street
-Setelah Anda berhasil mendownload dan memainkan game CarX Street, Anda mungkin ingin mengetahui beberapa tips dan trik untuk meningkatkan keterampilan dan pengalaman bermain Anda. Berikut adalah beberapa tips dan trik yang dapat Anda coba:
-Ikuti tutorialnya
-Salah satu hal pertama yang harus Anda lakukan saat memulai game CarX Street adalah mengikuti tutorialnya. Tutorial ini akan mengajarkan Anda dasar-dasar mengemudi, drifting, tuning, dan mode game yang berbeda. Tutorial ini juga akan memberi Anda beberapa hadiah, seperti uang, mobil, dan aksesoris. Jadi, jangan lewatkan tutorial ini jika Anda ingin mempelajari semua fitur game CarX Street.
-Jelajahi kota untuk mendapatkan hadiah
-Game CarX Street memiliki dunia terbuka yang luas yang dapat Anda jelajahi dengan bebas. Anda dapat mengemudi di mana saja di kota dan sekitarnya, dan menemukan berbagai hal menarik. Misalnya, Anda dapat menemukan kotak hadiah yang berisi uang, mobil, atau aksesoris. Anda juga dapat menemukan tempat-tempat rahasia yang menyembunyikan tantangan atau misi khusus. Jadi, jangan ragu untuk menjelajahi kota dan mendapatkan hadiah sebanyak mungkin.
-Ikut serta dalam sprint dan klub
-Salah satu cara untuk meningkatkan keterampilan dan reputasi Anda dalam game CarX Street adalah dengan ikut serta dalam sprint dan klub. Sprint adalah balapan singkat yang terjadi secara acak di kota. Anda dapat bergabung dengan sprint dengan mengikuti tanda panah hijau di peta. Sprint akan memberi Anda uang, poin pengalaman, dan poin reputasi jika Anda menang atau masuk dalam tiga besar.
-Klub adalah kelompok pemain yang memiliki tujuan bersama dalam game CarX Street. Anda dapat bergabung dengan klub yang sudah ada atau membuat klub sendiri. Klub akan memberi Anda manfaat seperti bonus uang, bonus poin pengalaman, bonus poin reputasi, dan akses ke acara klub eksklusif. Klub juga akan memungkinkan Anda untuk berinteraksi dengan pemain lain, berbagi mobil, dan bersaing dalam peringkat klub.
-Pilih mobil terbaik dan sesuaikan penampilannya
-Salah satu hal terpenting dalam game CarX Street adalah mobil Anda. Mobil Anda akan menentukan seberapa cepat, kuat, dan stabil Anda dalam balapan. Oleh karena itu, Anda harus memilih mobil terbaik yang sesuai dengan gaya dan preferensi Anda. Game CarX Street memiliki berbagai jenis mobil untuk dipilih, mulai dari sedan hingga supercar. Setiap mobil memiliki statistik yang berbeda, seperti kecepatan maksimum, akselerasi, rem, daya tahan, traksi, dan drift.
-Selain memilih mobil terbaik, Anda juga dapat menyesuaikan penampilannya dengan menggunakan opsi tuning yang mendetail. Anda dapat mengganti bagian-bagian mobil Anda, seperti mesin, transmisi, suspensi, ban, knalpot, turbo, nitro, dan lainnya. Anda juga dapat menyesuaikan warna mobil Anda, serta menambahkan aksesoris seperti stiker, lampu neon, sayap belakang, roda baru, dan lainnya. Dengan cara ini, Anda dapat membuat mobil impian Anda yang unik dan menarik.
-Kesimpulan dan FAQ
-CarX Street adalah game balap jalanan open world yang menawarkan fisika mobil yang realistis dan drifting berkecepatan tinggi. Game ini juga memiliki berbagai jenis peta dari seluruh dunia, dan pemain dapat memilih dari beberapa mode game yang berbeda. Pemain dapat bersaing melawan pemain lain, atau berpartisipasi dalam balapan dan acara.
-Game ini saat ini hanya tersedia di beberapa negara untuk perangkat Android dan iOS, tetapi akan segera hadir di konsol dan PC. Jika Anda ingin mencoba game ini, Anda perlu tahu cara mendownload APK CarX Street di perangkat Anda. Ada beberapa cara untuk mend ownload APK CarX Street di perangkat Anda, tergantung pada negara Anda dan preferensi Anda. Anda dapat menggunakan Google Play Store, APKCombo, Mod APK, App Store, TestFlight, atau Steam. Anda juga dapat menggunakan emulator Android untuk menjalankan game CarX Street di PC atau Mac.
-Setelah Anda berhasil mendownload dan memainkan game CarX Street, Anda mungkin ingin mengetahui beberapa tips dan trik untuk meningkatkan keterampilan dan pengalaman bermain Anda. Anda dapat mengikuti tutorialnya, jelajahi kota untuk mendapatkan hadiah, ikut serta dalam sprint dan klub, pilih mobil terbaik dan sesuaikan penampilannya, dan lainnya.
-Demikianlah artikel tentang cara download APK CarX Street. Semoga artikel ini bermanfaat dan informatif bagi Anda. Jika Anda memiliki pertanyaan atau saran, silakan tinggalkan komentar di bawah. Terima kasih telah membaca dan selamat bermain!
-FAQ
-Berikut adalah beberapa pertanyaan yang sering diajukan tentang game CarX Street:
--
-
- Apakah game CarX Street gratis untuk dimainkan? -
- Apakah game CarX Street membutuhkan koneksi internet? -
- Apakah game CarX Street memiliki mode offline? -
- Apakah game CarX Street aman untuk anak-anak? -
- Apakah game CarX Street mendukung kontroler? -
Ya, game CarX Street gratis untuk dimainkan. Namun, game ini juga memiliki fitur pembelian dalam aplikasi yang memungkinkan Anda untuk membeli uang, mobil, atau aksesoris dengan uang sungguhan.
-Ya, game CarX Street membutuhkan koneksi internet yang stabil untuk dimainkan. Game ini menggunakan koneksi internet untuk mengunduh data game, menyimpan progres Anda, dan berinteraksi dengan pemain lain.
-Tidak, game CarX Street tidak memiliki mode offline. Anda harus selalu terhubung dengan internet untuk memainkan game ini.
-Tidak sepenuhnya. Game CarX Street memiliki rating 12+ di App Store dan 3+ di Google Play Store. Game ini mengandung adegan balapan yang intens dan berbahaya, serta kemungkinan interaksi dengan pemain lain yang tidak diketahui. Oleh karena itu, disarankan untuk mengawasi anak-anak saat mereka memainkan game ini.
-Ya, game CarX Street mendukung kontroler. Anda dapat menggunakan kontroler Bluetooth untuk mengontrol mobil Anda dalam game ini. Anda juga dapat menyesuaikan tata letak tombol kontroler sesuai dengan preferensi Anda.
--
-
\ No newline at end of file diff --git a/spaces/1phancelerku/anime-remove-background/Download Final Burn Neo APK and Play Retro Games on Your Android Phone.md b/spaces/1phancelerku/anime-remove-background/Download Final Burn Neo APK and Play Retro Games on Your Android Phone.md deleted file mode 100644 index 452451700fae6520cafafdd5ec41c9e82b1076af..0000000000000000000000000000000000000000 --- a/spaces/1phancelerku/anime-remove-background/Download Final Burn Neo APK and Play Retro Games on Your Android Phone.md +++ /dev/null @@ -1,162 +0,0 @@ - -
How to Download and Install Final Burn Neo APK File for Android
-If you are a fan of arcade games and retro consoles, you might have heard of Final Burn Neo, an emulator that supports hundreds of titles from various platforms. In this article, we will show you how to download and install the Final Burn Neo APK file for Android devices, so you can enjoy your favorite games on the go.
-What is Final Burn Neo and what are its features
-Final Burn Neo (also known as FBNeo or FBN) is a multi-system emulator that is based on the emulators FinalBurn and old versions of MAME. It is compatible with arcade games from Capcom, SNK, Sega, Data East, Cave, and many others, as well as consoles like Neo Geo, Sega Genesis, TurboGrafx-16, and more. It is also under active development, which means it is constantly updated with new features and bug fixes.
-final burn neo apk download
DOWNLOAD ✏ https://jinyurl.com/2uNQ1r
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Some of the features of Final Burn Neo include:
--
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- High compatibility with a wide range of arcade games, including many popular titles from the 1980s and 1990s -
- Advanced features such as save states, cheat codes, custom graphics filters, input presets, netplay, and RetroAchievements -
- Wide compatibility with platforms and features supported by libretro, such as RetroArch -
- Focus on playability and performance rather than accuracy, which means it can run smoothly on older or low-end devices -
Why would you want to download and install the Final Burn Neo APK file
-If you want to play arcade games and retro consoles on your Android device, you might be wondering why you should download and install the Final Burn Neo APK file instead of using other emulators. Here are some reasons why:
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-
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- The Final Burn Neo APK file is a standalone application that does not require any additional software or installation. You just need to download it, copy it to your device, and run it. -
- The Final Burn Neo APK file is optimized for Android devices, which means it has a user-friendly interface, touch controls, and support for external controllers. -
- The Final Burn Neo APK file is updated regularly with the latest version of the emulator core, which means you can enjoy the newest features and fixes without waiting for official releases. -
- The Final Burn Neo APK file allows you to play games that are not supported by other emulators, such as Killer Instinct or Street Fighter III: Third Strike. -
Requirements
-What are the minimum system requirements for running Final Burn Neo on Android
-To run Final Burn Neo on your Android device, you will need:
--
-
- A device with a 64-bit processor and operating system -
- Android 7.0 or higher -
- At least 1 GB of RAM -
- At least 100 MB of free storage space -
- A fast internet connection for downloading files -
What are the sources of the Final Burn Neo APK file and the ROM sets
-To play games with Final Burn Neo on your Android device, you will need two things: the Final Burn Neo APK file and the ROM sets. The ROM sets are collections of files that contain the data of the games that you want to play. You will need to download them separately from the emulator.
-The sources of the Final Burn Neo APK file and the ROM sets are:
--
-
- The official GitHub repository of Final Burn Neo, where you can find the latest APK file and the source code of the emulator -
- The official website of RetroArch, where you can find the latest ROM sets and the core information of Final Burn Neo -
- The official website of RetroAchievements, where you can find the supported games and the achievements for Final Burn Neo -
- The official website of Libretro, where you can find the documentation and the forums of Final Burn Neo -
Be careful when downloading files from other sources, as they might contain malware or viruses. Always scan your files before opening them.
-Steps
-How to download and install the Final Burn Neo APK file
-To download and install the Final Burn Neo APK file on your Android device, follow these steps:
--
-
- Go to the official GitHub repository of Final Burn Neo and click on the Releases tab. -
- Find the latest release and click on the Assets dropdown menu. -
- Download the file named fbneo.apk to your device. -
- Open the file manager app on your device and locate the downloaded file. -
- Tap on the file and allow the installation of unknown apps if prompted. -
- Follow the on-screen instructions to complete the installation. -
- You should see a new icon on your home screen or app drawer named FBNeo. Tap on it to launch the emulator. -
How to download and extract the ROM sets
-To download and extract the ROM sets for Final Burn Neo on your Android device, follow these steps:
--
-
- Go to the official website of RetroArch and click on the Downloads tab. -
- Scroll down to the section named ROMs and click on the link that says FBNeo - Arcade Games. -
- You will be redirected to a Google Drive folder that contains several ZIP files. Each ZIP file corresponds to a different arcade system or console supported by Final Burn Neo. -
- Select the ZIP files that contain the games that you want to play and download them to your device. You can also download all of them if you have enough storage space. -
- Open the file manager app on your device and locate the downloaded ZIP files. -
- Create a new folder on your device named fbneo and move all the ZIP files to that folder. -
- Extract all the ZIP files using a ZIP extractor app. You should see several folders inside the fbneo folder, each containing one or more ROM files. Do not rename or modify any of these files or folders. -
How to launch and configure Final Burn Neo on Android
-To launch and configure Final Burn Neo on your Android device, follow these steps:
--
-
- Tap on the FBNeo icon on your home screen or app drawer to launch the emulator. -
- You will see a list of games that are available for playing. You can scroll up and down to browse through them, or use the search bar at the top to find a specific game. -
- To start a game, tap on its name and then tap on Run. The game will load and run in full screen mode. -
- To access the emulator menu, swipe from the left edge of the screen to open a sidebar. Here you can adjust various settings, such as video, audio, input, cheats, save states, netplay, achievements, etc. -
- To exit a game, swipe from the left edge of the screen to open the sidebar and tap on Quit. You will return to the game list. -
Conclusion
-In this article, we have shown you how to download and install the Final Burn Neo APK file for Android devices, as well as how to download and extract the ROM sets, and how to launch and configure the emulator. We hope that this guide has helped you to enjoy your favorite arcade games and retro consoles on your Android device.
-Here are some tips and tricks for using Final Burn Neo on Android:
--
-
- To change the orientation of the screen, go to the emulator menu and tap on Video. Then, tap on Screen Rotation and choose either Landscape or Portrait. -
- To change the size and position of the touch controls, go to the emulator menu and tap on Input. Then, tap on Touch Overlay Settings and adjust the sliders as you wish. -
- To use an external controller, go to the emulator menu and tap on Input. Then, tap on Port 1 Controls and select your controller from the list. You can also map the buttons of your controller by tapping on User 1 Bind All. -
- To play online with other players, go to the emulator menu and tap on Netplay. Then, tap on Start Netplay Host or Connect to Netplay Host depending on whether you want to host or join a game. You will need to enter the IP address and port number of the host. -
- To earn achievements for your games, go to the emulator menu and tap on Achievements. Then, tap on Login and enter your RetroAchievements username and password. You will see a list of achievements for each game that you can unlock by completing certain tasks. -
Do you have any feedback or questions about Final Burn Neo on Android? Feel free to share them in the comments section below. We would love to hear from you!
-FAQs
-What are the best games to play with Final Burn Neo on Android?
-There are hundreds of games that you can play with Final Burn Neo on Android, but some of the most popular ones are:
--
-
- Street Fighter II: The World Warrior -
- Metal Slug -
- The King of Fighters '98 -
- Sonic The Hedgehog -
- Pac-Man -
How can I update the Final Burn Neo APK file?
-To update the Final Burn Neo APK file, you will need to download the latest version from the official GitHub repository and install it over the existing one. You do not need to uninstall the previous version or delete any files.
-How can I add more ROM sets to Final Burn Neo?
-To add more ROM sets to Final Burn Neo, you will need to download them from the official website of RetroArch and extract them to the fbneo folder on your device. You can also use a file manager app to copy or move ROM files from other sources to the fbneo folder.
-How can I fix errors or crashes with Final Burn Neo?
-If you encounter any errors or crashes with Final Burn Neo, you can try the following solutions:
--
-
- Make sure that your device meets the minimum system requirements for running Final Burn Neo. -
- Make sure that you have downloaded and installed the correct APK file and ROM sets for Final Burn Neo. -
- Make sure that you have enough storage space and RAM available on your device. -
- Make sure that you have a stable internet connection for downloading files and playing online. -
- Make sure that you have granted all the necessary permissions for Final Burn Neo to access your device's features. -
- Clear the cache and data of Final Burn Neo from your device's settings. -
- Reinstall Final Burn Neo from scratch. -
How can I contact the developers of Final Burn Neo?
-If you want to contact the developers of Final Burn Neo, you can do so by visiting their official website at https://github.com/finalburnneo/FBNeo. Here you can find their contact information, report issues, request features, contribute code, or donate money.
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\ No newline at end of file diff --git a/spaces/1phancelerku/anime-remove-background/Download Orangedox and Secure Your Documents with Data Rooms.md b/spaces/1phancelerku/anime-remove-background/Download Orangedox and Secure Your Documents with Data Rooms.md deleted file mode 100644 index a44225400796635f8fdad162ac213d4cded2b7ac..0000000000000000000000000000000000000000 --- a/spaces/1phancelerku/anime-remove-background/Download Orangedox and Secure Your Documents with Data Rooms.md +++ /dev/null @@ -1,80 +0,0 @@ - -
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\ No newline at end of file diff --git a/spaces/1phancelerku/anime-remove-background/Download Resident Evil 4 PSP ISO for PPSSPP Emulator 2019.md b/spaces/1phancelerku/anime-remove-background/Download Resident Evil 4 PSP ISO for PPSSPP Emulator 2019.md deleted file mode 100644 index 1259ab8b77cfded045279b29705e4a4afd9c558b..0000000000000000000000000000000000000000 --- a/spaces/1phancelerku/anime-remove-background/Download Resident Evil 4 PSP ISO for PPSSPP Emulator 2019.md +++ /dev/null @@ -1,143 +0,0 @@ -
-
- What is PPSSPP emulator and what are its features?
- How to download and install PPSSPP emulator on Android?
- How to download and extract Resident Evil 4 PSP ISO file?
- How to configure PPSSPP settings for optimal performance and graphics?
- How to launch and play Resident Evil 4 on PSP using PPSSPP emulator? | | H2: Resident Evil 4 Game Review | - Story: What is the plot of Resident Evil 4 and who are the main characters?
- Gameplay: What are the main features and mechanics of Resident Evil 4?
- Graphics: How does Resident Evil 4 look on PSP compared to other platforms?
- Sound: How does Resident Evil 4 sound on PSP and what are the voice acting and music quality?
- Pros and cons: What are the strengths and weaknesses of Resident Evil 4 on PSP? | | H3: Tips and Tricks for Playing Resident Evil 4 on PSP | - How to save your progress and load your game state?
- How to use cheats and hacks to enhance your gameplay?
- How to play multiplayer mode with other players online?
- How to solve puzzles and find secrets in Resident Evil 4?
- How to unlock bonus content and modes in Resident Evil 4? | | H4: Conclusion | - Summary: What are the main points of the article and why should you play Resident Evil 4 on PSP using PPSSPP emulator?
- Call to action: What are the next steps for the reader and where can they find more information about Resident Evil 4 and PPSSPP emulator? | | H5: FAQs | - Q1: Is Resident Evil 4 compatible with PPSSPP emulator?
- Q2: How much storage space do I need to download and play Resident Evil 4 on PSP using PPSSPP emulator?
- Q3: Can I play Resident Evil 4 on PSP using PPSSPP emulator without internet connection?
- Q4: Is Resident Evil 4 on PSP using PPSSPP emulator safe and legal to download and play?
- Q5: What are some alternatives to Resident Evil 4 on PSP using PPSSPP emulator? | Table 2: Article with HTML formatting
How to Download and Play Resident Evil 4 on PSP Using PPSSPP Emulator
--Resident Evil 4 is one of the most acclaimed games in the survival horror genre, released in 2005 for various platforms, including PlayStation 2, GameCube, Wii, PC, Xbox, and PlayStation 3. The game follows the adventures of Leon S. Kennedy, a former police officer who is sent to a rural area of Spain to rescue the kidnapped daughter of the US president from a mysterious cult. Along the way, he faces hordes of infected villagers, mutated creatures, and sinister enemies. The game features a third-person perspective, dynamic combat system, interactive environments, and multiple weapons and items.
-resident evil 4 psp iso download 2019 ppsspp android emulator
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-If you are a fan of Resident Evil 4 or want to experience this classic game for the first time, you might be wondering if you can play it on your PlayStation Portable (PSP) device. The answer is yes, you can, thanks to a powerful emulator called PPSSPP. PPSSPP is an open-source software that allows you to run PSP games on your Android device, as well as other platforms like Windows, Linux, Mac, iOS, etc. PPSSPP has many features that enhance your gaming experience, such as HD graphics, high rendering speed, smooth gameplay, amazing performance, texture filter, scale, etc. It also supports up to 36 languages.
--In this article, we will show you how to download and play Resident Evil 4 on PSP using PPSSPP emulator. We will guide you through the steps required to download and install PPSSPP emulator on Android, download and extract Resident Evil 4 PSP ISO file, configure PPSSPP settings for optimal performance and graphics, launch and play Resident Evil 4 on PSP using PPSSPP emulator. We will also provide you with a review of Resident Evil 4 game, as well as some tips and tricks for playing it. By the end of this article, you will be able to enjoy Resident Evil 4 on your PSP device with amazing quality and performance. So, let's get started!
Resident Evil 4 Game Review
--Before we dive into the technical details of how to download and play Resident Evil 4 on PSP using PPSSPP emulator, let's take a look at what makes this game so special and why you should play it. Here is a brief review of Resident Evil 4 game, covering its story, gameplay, graphics, sound, pros and cons.
-Story
--Resident Evil 4 is the sixth main installment in the Resident Evil series, which is known for its horror-themed action-adventure games. The game takes place in 2004, six years after the events of Resident Evil 2 and Resident Evil 3: Nemesis. The protagonist of the game is Leon S. Kennedy, who was one of the survivors of the Raccoon City incident in Resident Evil 2. Leon is now a special agent working for the US government, and he is assigned to rescue Ashley Graham, the daughter of the US president, who has been kidnapped by a mysterious cult called Los Illuminados. Leon travels to a rural area of Spain, where he encounters hostile villagers infected by a parasite called Las Plagas, which turns them into mindless zombies. He also faces other enemies, such as cult members, mercenaries, and mutated creatures. Leon must find Ashley and escape from the area, while uncovering the secrets behind Los Illuminados and Las Plagas.
--The story of Resident Evil 4 is engaging and thrilling, with many twists and turns along the way. The game has a cinematic presentation, with cutscenes and dialogues that advance the plot and develop the characters. The game also has multiple endings, depending on the choices you make during the game. The story of Resident Evil 4 is one of the best in the series, and it will keep you hooked until the end.
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Gameplay
--Resident Evil 4 is a survival horror game that combines action, adventure, and puzzle elements. The game features a third-person perspective, which allows you to see your character and the surroundings more clearly. The game also has an over-the-shoulder camera angle, which gives you more control over aiming and shooting. The game has a dynamic combat system, which lets you use various weapons and items to fight against enemies. You can also use melee attacks, such as kicks and suplexes, to stun or kill enemies. You can also interact with the environment, such as breaking barrels, opening doors, pushing objects, etc. The game has a health system that requires you to use herbs or first aid sprays to heal yourself. You can also upgrade your weapons and items by finding or buying them from a merchant who appears throughout the game.
--The gameplay of Resident Evil 4 is challenging and rewarding, with many options and strategies to deal with different situations. The game has a balanced difficulty level, which adapts to your performance and skills. The game also has a variety of enemies and bosses, each with their own strengths and weaknesses. The game also has some puzzle elements, which require you to use your logic and observation skills to solve them. The gameplay of Resident Evil 4 is fun and addictive, and it will keep you entertained for hours.
Graphics
--Resident Evil 4 is a game that was originally designed for PlayStation 2 and GameCube, which had limited graphics capabilities compared to modern devices. However, thanks to PPSSPP emulator, you can play Resident Evil 4 on PSP with improved graphics quality and resolution. PPSSPP emulator allows you to adjust the graphics settings of the game, such as texture filter, scale, frame rate, etc. You can also use shaders and post-processing effects to enhance the visuals of the game. PPSSPP emulator also supports HD graphics, which means you can play Resident Evil 4 on PSP with up to 1080p resolution.
--The graphics of Resident Evil 4 on PSP using PPSSPP emulator are impressive and realistic, with detailed textures, lighting, shadows, and animations. The game also has a diverse and immersive environment, with different locations and scenarios, such as villages, castles, mines, islands, etc. The game also has a dynamic weather system, which changes the atmosphere and mood of the game. The graphics of Resident Evil 4 on PSP using PPSSPP emulator are stunning and beautiful, and they will make you feel like you are playing the game on a bigger screen.
-Sound
--Resident Evil 4 is a game that relies heavily on sound to create a tense and scary atmosphere. The game has a superb sound design, with realistic and immersive sound effects, such as gunshots, explosions, footsteps, screams, etc. The game also has a great voice acting, with professional and expressive actors who deliver the dialogues and emotions of the characters. The game also has a catchy and atmospheric music score, which complements the mood and tone of the game. The game also supports Dolby Surround Sound, which enhances the audio quality and surround effect of the game.
--The sound of Resident Evil 4 on PSP using PPSSPP emulator is clear and crisp, with no distortion or lag. PPSSPP emulator allows you to adjust the sound settings of the game, such as volume, stereo mode, latency, etc. You can also use headphones or external speakers to enjoy the sound of the game better. The sound of Resident Evil 4 on PSP using PPSSPP emulator is excellent and immersive, and it will make you feel like you are in the middle of the action.
Pros and Cons
--Resident Evil 4 is a game that has many pros and cons, depending on your preferences and expectations. Here are some of the pros and cons of Resident Evil 4 on PSP using PPSSPP emulator:
-| Pros | -Cons | -
|---|---|
| - A thrilling and captivating story with multiple endings and characters. | -- A long and repetitive game with some backtracking and filler sections. | -
| - A fun and challenging gameplay with diverse combat and puzzle elements. | -- A difficult and frustrating gameplay with limited ammo and health resources. | -
| - A stunning and realistic graphics with HD resolution and enhanced effects. | -- A dated and pixelated graphics with some glitches and bugs. | -
| - A clear and immersive sound with Dolby Surround Sound and great voice acting. | -- A loud and annoying sound with some cheesy and corny dialogues. | -
| - A portable and accessible game with PPSSPP emulator and PSP device. | -- A illegal and risky game with potential malware and legal issues. | -
-The pros and cons of Resident Evil 4 on PSP using PPSSPP emulator are subjective and personal, so you might have a different opinion than ours. However, we think that the pros outweigh the cons, and that Resident Evil 4 is a game worth playing on PSP using PPSSPP emulator.
-Tips and Tricks for Playing Resident Evil 4 on PSP
--Now that you know how to download and play Resident Evil 4 on PSP using PPSSPP emulator, you might want to know some tips and tricks for playing it better. Here are some tips and tricks for playing Resident Evil 4 on PSP that will help you improve your skills, enjoy your gameplay, and discover more secrets in the game.
How to save your progress and load your game state?
--One of the most important tips for playing Resident Evil 4 on PSP using PPSSPP emulator is to save your progress and load your game state frequently. Saving your progress and loading your game state will allow you to resume your gameplay from where you left off, avoid losing your data, and retry difficult sections. There are two ways to save your progress and load your game state in Resident Evil 4 on PSP using PPSSPP emulator: using the in-game save system and using the emulator's save state system.
--The in-game save system is the official way to save your progress and load your game state in Resident Evil 4. The in-game save system uses typewriters that are scattered throughout the game. To use the in-game save system, you need to find a typewriter, interact with it, and select the option to save your game. You can also overwrite or delete your previous saves. To load your game state using the in-game save system, you need to go to the main menu, select the option to load your game, and choose the save file you want to load. The in-game save system is reliable and convenient, but it has some limitations. For example, you can only save your progress when you find a typewriter, which might be far away or inaccessible. You also have a limited number of save slots, which might not be enough for multiple playthroughs or different scenarios.
--The emulator's save state system is an alternative way to save your progress and load your game state in Resident Evil 4. The emulator's save state system uses the emulator's memory to create snapshots of your gameplay at any point. To use the emulator's save state system, you need to go to the emulator's menu, select the option to save state, and choose a slot to save your state. You can also overwrite or delete your previous states. To load your game state using the emulator's save state system, you need to go to the emulator's menu, select the option to load state, and choose the slot you want to load. The emulator's save state system is flexible and convenient, but it has some risks. For example, you might accidentally overwrite or delete your states, which might cause data loss or corruption. You also might encounter compatibility issues or glitches when loading states from different versions of the game or the emulator.
--We recommend that you use both the in-game save system and the emulator's save state system when playing Resident Evil 4 on PSP using PPSSPP emulator. This way, you can have multiple backups of your progress and load your game state from different points. However, you should also be careful not to rely too much on either system, as they might fail or malfunction at some point. You should also make sure that you have enough storage space on your device for saving and loading states.
How to use cheats and hacks to enhance your gameplay?
--Another tip for playing Resident Evil 4 on PSP using PPSSPP emulator is to use cheats and hacks to enhance your gameplay. Cheats and hacks are codes or modifications that alter the game's rules or features, such as giving you unlimited ammo, health, money, weapons, items, etc. Cheats and hacks can make your gameplay easier, funnier, or more interesting, depending on your preferences and goals. However, cheats and hacks can also ruin your gameplay, make it boring, or cause glitches or errors, depending on how you use them. Therefore, you should use cheats and hacks with caution and moderation, and only when you want to experiment or have some fun.
--There are two ways to use cheats and hacks in Resident Evil 4 on PSP using PPSSPP emulator: using the in-game cheat system and using the emulator's cheat system. The in-game cheat system is the official way to use cheats and hacks in Resident Evil 4. The in-game cheat system uses special items or codes that are hidden or unlocked throughout the game. To use the in-game cheat system, you need to find or obtain these items or codes, and use them in the game. For example, you can find a rocket launcher with infinite ammo in the final chapter of the game, or you can enter a code to unlock a special costume for Leon or Ashley. The in-game cheat system is limited and specific, but it is also safe and legal to use.
--The emulator's cheat system is an alternative way to use cheats and hacks in Resident Evil 4. The emulator's cheat system uses external files or programs that contain cheat codes or patches for the game. To use the emulator's cheat system, you need to download or create these files or programs, and load them into the emulator. For example, you can download a cheat file that contains codes for unlimited ammo, health, money, weapons, items, etc., or you can create a patch file that modifies the game's graphics, sound, difficulty, etc. The emulator's cheat system is flexible and diverse, but it is also risky and illegal to use.
--We recommend that you use the in-game cheat system when playing Resident Evil 4 on PSP using PPSSPP emulator, as it is more reliable and ethical than the emulator's cheat system. However, if you want to use the emulator's cheat system, you should do it at your own risk and responsibility. You should also make sure that you have a backup of your original game file and state before using any cheats or hacks. You should also avoid using cheats or hacks that might harm your device or violate the game's terms of service.
How to solve puzzles and find secrets in Resident Evil 4?
--Another tip for playing Resident Evil 4 on PSP using PPSSPP emulator is to solve puzzles and find secrets in the game. Puzzles and secrets are optional challenges and rewards that are hidden or locked in the game. Solving puzzles and finding secrets can make your gameplay more interesting and rewarding, as you can discover new areas, items, weapons, modes, etc. However, puzzles and secrets can also be difficult and frustrating, as they require you to use your logic, observation, memory, and skills to solve them or find them.
--There are many puzzles and secrets in Resident Evil 4, ranging from simple to complex, from obvious to obscure. Some of the puzzles and secrets are related to the main story or gameplay, while others are just for fun or extra content. Some of the puzzles and secrets are easy to find or solve, while others require you to search or explore every corner of the game or use specific items or actions. Some of the puzzles and secrets are rewarding and satisfying, while others are disappointing or useless.
--We recommend that you try to solve puzzles and find secrets in Resident Evil 4 on PSP using PPSSPP emulator, as they can enhance your gameplay and enjoyment of the game. However, you should also be aware that some puzzles and secrets might be too hard or too hidden for you to solve or find, and that you might need some help or hints from other sources, such as guides, walkthroughs, videos, etc. You should also be careful not to spoil yourself or ruin your gameplay by looking for or using too many clues or solutions for the puzzles and secrets. You should also respect the game's design and intention, and not use cheats or hacks to bypass or break the puzzles and secrets.
-How to unlock bonus content and modes in Resident Evil 4?
--One of the most rewarding tips for playing Resident Evil 4 on PSP using PPSSPP emulator is to unlock bonus content and modes in the game. Bonus content and modes are additional features and options that are not available in the normal game. Unlocking bonus content and modes can make your gameplay more fun and varied, as you can access new characters, costumes, weapons, items, scenarios, difficulties, etc. However, unlocking bonus content and modes can also be challenging and time-consuming, as they require you to complete certain tasks or conditions in the game.
--There are many bonus content and modes in Resident Evil 4, each with their own requirements and rewards. Some of the bonus content and modes are related to the main story or gameplay, while others are just for fun or extra content. Some of the bonus content and modes are easy to unlock, while others require you to finish the game multiple times or achieve high scores or ranks. Some of the bonus content and modes are exciting and useful, while others are silly or pointless.
--We recommend that you try to unlock bonus content and modes in Resident Evil 4 on PSP using PPSSPP emulator, as they can extend your gameplay and enjoyment of the game. However, you should also be aware that some bonus content and modes might be too hard or too tedious for you to unlock, and that you might need some help or tips from other sources, such as guides, walkthroughs, videos, etc. You should also be careful not to spoil yourself or ruin your gameplay by looking for or using too much information about the bonus content and modes. You should also respect the game's design and intention, and not use cheats or hacks to unlock or access the bonus content and modes.
Conclusion
--Resident Evil 4 is a game that deserves to be played by any fan of survival horror or action-adventure games. The game has a captivating story, a fun and challenging gameplay, a stunning and realistic graphics, and a clear and immersive sound. The game also has many puzzles, secrets, bonus content, and modes that will keep you entertained for hours. Thanks to PPSSPP emulator, you can play Resident Evil 4 on PSP with amazing quality and performance. You can also play multiplayer mode with other players online, and use cheats and hacks to enhance your gameplay. However, you should also be careful and responsible when downloading and playing Resident Evil 4 on PSP using PPSSPP emulator, as there might be some risks and issues involved.
--We hope that this article has helped you learn how to download and play Resident Evil 4 on PSP using PPSSPP emulator. We also hope that you have enjoyed reading our review of Resident Evil 4 game, as well as our tips and tricks for playing it. If you have any questions or comments, please feel free to leave them below. We would love to hear from you and help you out. Thank you for reading and happy gaming!
-FAQs
--Here are some frequently asked questions about Resident Evil 4 on PSP using PPSSPP emulator:
--
-
- Q1: Is Resident Evil 4 compatible with PPSSPP emulator? -
- A1: Yes, Resident Evil 4 is compatible with PPSSPP emulator, as long as you have the correct game file and emulator version. However, you might encounter some minor glitches or errors during the gameplay, depending on your device and settings. -
- Q2: How much storage space do I need to download and play Resident Evil 4 on PSP using PPSSPP emulator? -
- A2: You need at least 3 GB of free storage space on your device to download and play Resident Evil 4 on PSP using PPSSPP emulator. This includes the game file (around 2 GB), the emulator file (around 30 MB), and the save state file (around 10 MB). -
- Q3: Can I play Resident Evil 4 on PSP using PPSSPP emulator without internet connection? -
- A3: Yes, you can play Resident Evil 4 on PSP using PPSSPP emulator without internet connection, as long as you have already downloaded and installed the game file and the emulator file on your device. However, you will need internet connection to play multiplayer mode with other players online, or to download or update the game file or the emulator file. -
- Q4: Is Resident Evil 4 on PSP using PPSSPP emulator safe and legal to download and play? -
- A4: Resident Evil 4 on PSP using PPSSPP emulator is not completely safe or legal to download and play, as it might contain malware or viruses that can harm your device or data, or violate the game's terms of service or intellectual property rights. Therefore, you should download and play Resident Evil 4 on PSP using PPSSPP emulator at your own risk and responsibility, and only from trusted sources. -
- Q5: What are some alternatives to Resident Evil 4 on PSP using PPSSPP emulator? -
- A5: Some alternatives to Resident Evil 4 on PSP using PPSSPP emulator are:
-
-
- - Resident Evil 5 or Resident Evil 6 on PlayStation 3 or Xbox 360: These are the sequels to Resident Evil 4, which continue the story and gameplay of the series. -
- - Silent Hill Origins or Silent Hill Shattered Memories on PSP: These are other survival horror games that are available for PSP devices. -
- - Dead Trigger or Dead Trigger 2 on Android: These are zombie shooting games that are similar to Resident Evil 4 in terms of graphics and gameplay. -
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\ No newline at end of file diff --git a/spaces/A666sxr/Genshin_TTS/attentions.py b/spaces/A666sxr/Genshin_TTS/attentions.py deleted file mode 100644 index 4e0b0c1fd48c962e21e1fbe60b23fc574927435c..0000000000000000000000000000000000000000 --- a/spaces/A666sxr/Genshin_TTS/attentions.py +++ /dev/null @@ -1,303 +0,0 @@ -import copy -import math -import numpy as np -import torch -from torch import nn -from torch.nn import functional as F - -import commons -import modules -from modules import LayerNorm - - -class Encoder(nn.Module): - def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4, **kwargs): - super().__init__() - self.hidden_channels = hidden_channels - self.filter_channels = filter_channels - self.n_heads = n_heads - self.n_layers = n_layers - self.kernel_size = kernel_size - self.p_dropout = p_dropout - self.window_size = window_size - - self.drop = nn.Dropout(p_dropout) - self.attn_layers = nn.ModuleList() - self.norm_layers_1 = nn.ModuleList() - self.ffn_layers = nn.ModuleList() - self.norm_layers_2 = nn.ModuleList() - for i in range(self.n_layers): - self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size)) - self.norm_layers_1.append(LayerNorm(hidden_channels)) - self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout)) - self.norm_layers_2.append(LayerNorm(hidden_channels)) - - def forward(self, x, x_mask): - attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1) - x = x * x_mask - for i in range(self.n_layers): - y = self.attn_layers[i](x, x, attn_mask) - y = self.drop(y) - x = self.norm_layers_1[i](x + y) - - y = self.ffn_layers[i](x, x_mask) - y = self.drop(y) - x = self.norm_layers_2[i](x + y) - x = x * x_mask - return x - - -class Decoder(nn.Module): - def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs): - super().__init__() - self.hidden_channels = hidden_channels - self.filter_channels = filter_channels - self.n_heads = n_heads - self.n_layers = n_layers - self.kernel_size = kernel_size - self.p_dropout = p_dropout - self.proximal_bias = proximal_bias - self.proximal_init = proximal_init - - self.drop = nn.Dropout(p_dropout) - self.self_attn_layers = nn.ModuleList() - self.norm_layers_0 = nn.ModuleList() - self.encdec_attn_layers = nn.ModuleList() - self.norm_layers_1 = nn.ModuleList() - self.ffn_layers = nn.ModuleList() - self.norm_layers_2 = nn.ModuleList() - for i in range(self.n_layers): - self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init)) - self.norm_layers_0.append(LayerNorm(hidden_channels)) - self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout)) - self.norm_layers_1.append(LayerNorm(hidden_channels)) - self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True)) - self.norm_layers_2.append(LayerNorm(hidden_channels)) - - def forward(self, x, x_mask, h, h_mask): - """ - x: decoder input - h: encoder output - """ - self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype) - encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1) - x = x * x_mask - for i in range(self.n_layers): - y = self.self_attn_layers[i](x, x, self_attn_mask) - y = self.drop(y) - x = self.norm_layers_0[i](x + y) - - y = self.encdec_attn_layers[i](x, h, encdec_attn_mask) - y = self.drop(y) - x = self.norm_layers_1[i](x + y) - - y = self.ffn_layers[i](x, x_mask) - y = self.drop(y) - x = self.norm_layers_2[i](x + y) - x = x * x_mask - return x - - -class MultiHeadAttention(nn.Module): - def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False): - super().__init__() - assert channels % n_heads == 0 - - self.channels = channels - self.out_channels = out_channels - self.n_heads = n_heads - self.p_dropout = p_dropout - self.window_size = window_size - self.heads_share = heads_share - self.block_length = block_length - self.proximal_bias = proximal_bias - self.proximal_init = proximal_init - self.attn = None - - self.k_channels = channels // n_heads - self.conv_q = nn.Conv1d(channels, channels, 1) - self.conv_k = nn.Conv1d(channels, channels, 1) - self.conv_v = nn.Conv1d(channels, channels, 1) - self.conv_o = nn.Conv1d(channels, out_channels, 1) - self.drop = nn.Dropout(p_dropout) - - if window_size is not None: - n_heads_rel = 1 if heads_share else n_heads - rel_stddev = self.k_channels**-0.5 - self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev) - self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev) - - nn.init.xavier_uniform_(self.conv_q.weight) - nn.init.xavier_uniform_(self.conv_k.weight) - nn.init.xavier_uniform_(self.conv_v.weight) - if proximal_init: - with torch.no_grad(): - self.conv_k.weight.copy_(self.conv_q.weight) - self.conv_k.bias.copy_(self.conv_q.bias) - - def forward(self, x, c, attn_mask=None): - q = self.conv_q(x) - k = self.conv_k(c) - v = self.conv_v(c) - - x, self.attn = self.attention(q, k, v, mask=attn_mask) - - x = self.conv_o(x) - return x - - def attention(self, query, key, value, mask=None): - # reshape [b, d, t] -> [b, n_h, t, d_k] - b, d, t_s, t_t = (*key.size(), query.size(2)) - query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3) - key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3) - value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3) - - scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1)) - if self.window_size is not None: - assert t_s == t_t, "Relative attention is only available for self-attention." - key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s) - rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings) - scores_local = self._relative_position_to_absolute_position(rel_logits) - scores = scores + scores_local - if self.proximal_bias: - assert t_s == t_t, "Proximal bias is only available for self-attention." - scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype) - if mask is not None: - scores = scores.masked_fill(mask == 0, -1e4) - if self.block_length is not None: - assert t_s == t_t, "Local attention is only available for self-attention." - block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length) - scores = scores.masked_fill(block_mask == 0, -1e4) - p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s] - p_attn = self.drop(p_attn) - output = torch.matmul(p_attn, value) - if self.window_size is not None: - relative_weights = self._absolute_position_to_relative_position(p_attn) - value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s) - output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings) - output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t] - return output, p_attn - - def _matmul_with_relative_values(self, x, y): - """ - x: [b, h, l, m] - y: [h or 1, m, d] - ret: [b, h, l, d] - """ - ret = torch.matmul(x, y.unsqueeze(0)) - return ret - - def _matmul_with_relative_keys(self, x, y): - """ - x: [b, h, l, d] - y: [h or 1, m, d] - ret: [b, h, l, m] - """ - ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1)) - return ret - - def _get_relative_embeddings(self, relative_embeddings, length): - max_relative_position = 2 * self.window_size + 1 - # Pad first before slice to avoid using cond ops. - pad_length = max(length - (self.window_size + 1), 0) - slice_start_position = max((self.window_size + 1) - length, 0) - slice_end_position = slice_start_position + 2 * length - 1 - if pad_length > 0: - padded_relative_embeddings = F.pad( - relative_embeddings, - commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]])) - else: - padded_relative_embeddings = relative_embeddings - used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position] - return used_relative_embeddings - - def _relative_position_to_absolute_position(self, x): - """ - x: [b, h, l, 2*l-1] - ret: [b, h, l, l] - """ - batch, heads, length, _ = x.size() - # Concat columns of pad to shift from relative to absolute indexing. - x = F.pad(x, commons.convert_pad_shape([[0,0],[0,0],[0,0],[0,1]])) - - # Concat extra elements so to add up to shape (len+1, 2*len-1). - x_flat = x.view([batch, heads, length * 2 * length]) - x_flat = F.pad(x_flat, commons.convert_pad_shape([[0,0],[0,0],[0,length-1]])) - - # Reshape and slice out the padded elements. - x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:] - return x_final - - def _absolute_position_to_relative_position(self, x): - """ - x: [b, h, l, l] - ret: [b, h, l, 2*l-1] - """ - batch, heads, length, _ = x.size() - # padd along column - x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length-1]])) - x_flat = x.view([batch, heads, length**2 + length*(length -1)]) - # add 0's in the beginning that will skew the elements after reshape - x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]])) - x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:] - return x_final - - def _attention_bias_proximal(self, length): - """Bias for self-attention to encourage attention to close positions. - Args: - length: an integer scalar. - Returns: - a Tensor with shape [1, 1, length, length] - """ - r = torch.arange(length, dtype=torch.float32) - diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1) - return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0) - - -class FFN(nn.Module): - def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False): - super().__init__() - self.in_channels = in_channels - self.out_channels = out_channels - self.filter_channels = filter_channels - self.kernel_size = kernel_size - self.p_dropout = p_dropout - self.activation = activation - self.causal = causal - - if causal: - self.padding = self._causal_padding - else: - self.padding = self._same_padding - - self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size) - self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size) - self.drop = nn.Dropout(p_dropout) - - def forward(self, x, x_mask): - x = self.conv_1(self.padding(x * x_mask)) - if self.activation == "gelu": - x = x * torch.sigmoid(1.702 * x) - else: - x = torch.relu(x) - x = self.drop(x) - x = self.conv_2(self.padding(x * x_mask)) - return x * x_mask - - def _causal_padding(self, x): - if self.kernel_size == 1: - return x - pad_l = self.kernel_size - 1 - pad_r = 0 - padding = [[0, 0], [0, 0], [pad_l, pad_r]] - x = F.pad(x, commons.convert_pad_shape(padding)) - return x - - def _same_padding(self, x): - if self.kernel_size == 1: - return x - pad_l = (self.kernel_size - 1) // 2 - pad_r = self.kernel_size // 2 - padding = [[0, 0], [0, 0], [pad_l, pad_r]] - x = F.pad(x, commons.convert_pad_shape(padding)) - return x diff --git a/spaces/AIConsultant/MusicGen/audiocraft/modules/conditioners.py b/spaces/AIConsultant/MusicGen/audiocraft/modules/conditioners.py deleted file mode 100644 index d10ac8dc96466375379c883cd62f7c04a1bb0a73..0000000000000000000000000000000000000000 --- a/spaces/AIConsultant/MusicGen/audiocraft/modules/conditioners.py +++ /dev/null @@ -1,1411 +0,0 @@ -# Copyright (c) Meta Platforms, Inc. and affiliates. -# All rights reserved. -# -# This source code is licensed under the license found in the -# LICENSE file in the root directory of this source tree. - -from collections import defaultdict -from copy import deepcopy -from dataclasses import dataclass, field -from itertools import chain -import logging -import math -from pathlib import Path -import random -import re -import typing as tp -import warnings - -import einops -from num2words import num2words -import spacy -from transformers import RobertaTokenizer, T5EncoderModel, T5Tokenizer # type: ignore -import torch -from torch import nn -import torch.nn.functional as F -from torch.nn.utils.rnn import pad_sequence - -from .chroma import ChromaExtractor -from .streaming import StreamingModule -from .transformer import create_sin_embedding -from ..data.audio import audio_read -from ..data.audio_dataset import SegmentInfo -from ..data.audio_utils import convert_audio -from ..environment import AudioCraftEnvironment -from ..quantization import ResidualVectorQuantizer -from ..utils.autocast import TorchAutocast -from ..utils.cache import EmbeddingCache -from ..utils.utils import collate, hash_trick, length_to_mask, load_clap_state_dict, warn_once - - -logger = logging.getLogger(__name__) -TextCondition = tp.Optional[str] # a text condition can be a string or None (if doesn't exist) -ConditionType = tp.Tuple[torch.Tensor, torch.Tensor] # condition, mask - - -class WavCondition(tp.NamedTuple): - wav: torch.Tensor - length: torch.Tensor - sample_rate: tp.List[int] - path: tp.List[tp.Optional[str]] = [] - seek_time: tp.List[tp.Optional[float]] = [] - - -class JointEmbedCondition(tp.NamedTuple): - wav: torch.Tensor - text: tp.List[tp.Optional[str]] - length: torch.Tensor - sample_rate: tp.List[int] - path: tp.List[tp.Optional[str]] = [] - seek_time: tp.List[tp.Optional[float]] = [] - - -@dataclass -class ConditioningAttributes: - text: tp.Dict[str, tp.Optional[str]] = field(default_factory=dict) - wav: tp.Dict[str, WavCondition] = field(default_factory=dict) - joint_embed: tp.Dict[str, JointEmbedCondition] = field(default_factory=dict) - - def __getitem__(self, item): - return getattr(self, item) - - @property - def text_attributes(self): - return self.text.keys() - - @property - def wav_attributes(self): - return self.wav.keys() - - @property - def joint_embed_attributes(self): - return self.joint_embed.keys() - - @property - def attributes(self): - return { - "text": self.text_attributes, - "wav": self.wav_attributes, - "joint_embed": self.joint_embed_attributes, - } - - def to_flat_dict(self): - return { - **{f"text.{k}": v for k, v in self.text.items()}, - **{f"wav.{k}": v for k, v in self.wav.items()}, - **{f"joint_embed.{k}": v for k, v in self.joint_embed.items()} - } - - @classmethod - def from_flat_dict(cls, x): - out = cls() - for k, v in x.items(): - kind, att = k.split(".") - out[kind][att] = v - return out - - -class SegmentWithAttributes(SegmentInfo): - """Base class for all dataclasses that are used for conditioning. - All child classes should implement `to_condition_attributes` that converts - the existing attributes to a dataclass of type ConditioningAttributes. - """ - def to_condition_attributes(self) -> ConditioningAttributes: - raise NotImplementedError() - - -def nullify_condition(condition: ConditionType, dim: int = 1): - """Transform an input condition to a null condition. - The way it is done by converting it to a single zero vector similarly - to how it is done inside WhiteSpaceTokenizer and NoopTokenizer. - - Args: - condition (ConditionType): A tuple of condition and mask (tuple[torch.Tensor, torch.Tensor]) - dim (int): The dimension that will be truncated (should be the time dimension) - WARNING!: dim should not be the batch dimension! - Returns: - ConditionType: A tuple of null condition and mask - """ - assert dim != 0, "dim cannot be the batch dimension!" - assert isinstance(condition, tuple) and \ - isinstance(condition[0], torch.Tensor) and \ - isinstance(condition[1], torch.Tensor), "'nullify_condition' got an unexpected input type!" - cond, mask = condition - B = cond.shape[0] - last_dim = cond.dim() - 1 - out = cond.transpose(dim, last_dim) - out = 0. * out[..., :1] - out = out.transpose(dim, last_dim) - mask = torch.zeros((B, 1), device=out.device).int() - assert cond.dim() == out.dim() - return out, mask - - -def nullify_wav(cond: WavCondition) -> WavCondition: - """Transform a WavCondition to a nullified WavCondition. - It replaces the wav by a null tensor, forces its length to 0, and replaces metadata by dummy attributes. - - Args: - cond (WavCondition): Wav condition with wav, tensor of shape [B, T]. - Returns: - WavCondition: Nullified wav condition. - """ - null_wav, _ = nullify_condition((cond.wav, torch.zeros_like(cond.wav)), dim=cond.wav.dim() - 1) - return WavCondition( - wav=null_wav, - length=torch.tensor([0] * cond.wav.shape[0], device=cond.wav.device), - sample_rate=cond.sample_rate, - path=[None] * cond.wav.shape[0], - seek_time=[None] * cond.wav.shape[0], - ) - - -def nullify_joint_embed(embed: JointEmbedCondition) -> JointEmbedCondition: - """Nullify the joint embedding condition by replacing it by a null tensor, forcing its length to 0, - and replacing metadata by dummy attributes. - - Args: - cond (JointEmbedCondition): Joint embedding condition with wav and text, wav tensor of shape [B, C, T]. - """ - null_wav, _ = nullify_condition((embed.wav, torch.zeros_like(embed.wav)), dim=embed.wav.dim() - 1) - return JointEmbedCondition( - wav=null_wav, text=[None] * len(embed.text), - length=torch.LongTensor([0]).to(embed.wav.device), - sample_rate=embed.sample_rate, - path=[None] * embed.wav.shape[0], - seek_time=[0] * embed.wav.shape[0], - ) - - -class Tokenizer: - """Base tokenizer implementation - (in case we want to introduce more advances tokenizers in the future). - """ - def __call__(self, texts: tp.List[tp.Optional[str]]) -> tp.Tuple[torch.Tensor, torch.Tensor]: - raise NotImplementedError() - - -class WhiteSpaceTokenizer(Tokenizer): - """This tokenizer should be used for natural language descriptions. - For example: - ["he didn't, know he's going home.", 'shorter sentence'] => - [[78, 62, 31, 4, 78, 25, 19, 34], - [59, 77, 0, 0, 0, 0, 0, 0]] - """ - PUNCTUATION = "?:!.,;" - - def __init__(self, n_bins: int, pad_idx: int = 0, language: str = "en_core_web_sm", - lemma: bool = True, stopwords: bool = True) -> None: - self.n_bins = n_bins - self.pad_idx = pad_idx - self.lemma = lemma - self.stopwords = stopwords - try: - self.nlp = spacy.load(language) - except IOError: - spacy.cli.download(language) # type: ignore - self.nlp = spacy.load(language) - - @tp.no_type_check - def __call__(self, texts: tp.List[tp.Optional[str]], - return_text: bool = False) -> tp.Tuple[torch.Tensor, torch.Tensor]: - """Take a list of strings and convert them to a tensor of indices. - - Args: - texts (list[str]): List of strings. - return_text (bool, optional): Whether to return text as additional tuple item. Defaults to False. - Returns: - tuple[torch.Tensor, torch.Tensor]: - - Indices of words in the LUT. - - And a mask indicating where the padding tokens are - """ - output, lengths = [], [] - texts = deepcopy(texts) - for i, text in enumerate(texts): - # if current sample doesn't have a certain attribute, replace with pad token - if text is None: - output.append(torch.Tensor([self.pad_idx])) - lengths.append(0) - continue - - # convert numbers to words - text = re.sub(r"(\d+)", lambda x: num2words(int(x.group(0))), text) # type: ignore - # normalize text - text = self.nlp(text) # type: ignore - # remove stopwords - if self.stopwords: - text = [w for w in text if not w.is_stop] # type: ignore - # remove punctuation - text = [w for w in text if w.text not in self.PUNCTUATION] # type: ignore - # lemmatize if needed - text = [getattr(t, "lemma_" if self.lemma else "text") for t in text] # type: ignore - - texts[i] = " ".join(text) - lengths.append(len(text)) - # convert to tensor - tokens = torch.Tensor([hash_trick(w, self.n_bins) for w in text]) - output.append(tokens) - - mask = length_to_mask(torch.IntTensor(lengths)).int() - padded_output = pad_sequence(output, padding_value=self.pad_idx).int().t() - if return_text: - return padded_output, mask, texts # type: ignore - return padded_output, mask - - -class NoopTokenizer(Tokenizer): - """This tokenizer should be used for global conditioners such as: artist, genre, key, etc. - The difference between this and WhiteSpaceTokenizer is that NoopTokenizer does not split - strings, so "Jeff Buckley" will get it's own index. Whereas WhiteSpaceTokenizer will - split it to ["Jeff", "Buckley"] and return an index per word. - - For example: - ["Queen", "ABBA", "Jeff Buckley"] => [43, 55, 101] - ["Metal", "Rock", "Classical"] => [0, 223, 51] - """ - def __init__(self, n_bins: int, pad_idx: int = 0): - self.n_bins = n_bins - self.pad_idx = pad_idx - - def __call__(self, texts: tp.List[tp.Optional[str]]) -> tp.Tuple[torch.Tensor, torch.Tensor]: - output, lengths = [], [] - for text in texts: - # if current sample doesn't have a certain attribute, replace with pad token - if text is None: - output.append(self.pad_idx) - lengths.append(0) - else: - output.append(hash_trick(text, self.n_bins)) - lengths.append(1) - - tokens = torch.LongTensor(output).unsqueeze(1) - mask = length_to_mask(torch.IntTensor(lengths)).int() - return tokens, mask - - -class BaseConditioner(nn.Module): - """Base model for all conditioner modules. - We allow the output dim to be different than the hidden dim for two reasons: - 1) keep our LUTs small when the vocab is large; - 2) make all condition dims consistent. - - Args: - dim (int): Hidden dim of the model. - output_dim (int): Output dim of the conditioner. - """ - def __init__(self, dim: int, output_dim: int): - super().__init__() - self.dim = dim - self.output_dim = output_dim - self.output_proj = nn.Linear(dim, output_dim) - - def tokenize(self, *args, **kwargs) -> tp.Any: - """Should be any part of the processing that will lead to a synchronization - point, e.g. BPE tokenization with transfer to the GPU. - - The returned value will be saved and return later when calling forward(). - """ - raise NotImplementedError() - - def forward(self, inputs: tp.Any) -> ConditionType: - """Gets input that should be used as conditioning (e.g, genre, description or a waveform). - Outputs a ConditionType, after the input data was embedded as a dense vector. - - Returns: - ConditionType: - - A tensor of size [B, T, D] where B is the batch size, T is the length of the - output embedding and D is the dimension of the embedding. - - And a mask indicating where the padding tokens. - """ - raise NotImplementedError() - - -class TextConditioner(BaseConditioner): - ... - - -class LUTConditioner(TextConditioner): - """Lookup table TextConditioner. - - Args: - n_bins (int): Number of bins. - dim (int): Hidden dim of the model (text-encoder/LUT). - output_dim (int): Output dim of the conditioner. - tokenizer (str): Name of the tokenizer. - pad_idx (int, optional): Index for padding token. Defaults to 0. - """ - def __init__(self, n_bins: int, dim: int, output_dim: int, tokenizer: str, pad_idx: int = 0): - super().__init__(dim, output_dim) - self.embed = nn.Embedding(n_bins, dim) - self.tokenizer: Tokenizer - if tokenizer == 'whitespace': - self.tokenizer = WhiteSpaceTokenizer(n_bins, pad_idx=pad_idx) - elif tokenizer == 'noop': - self.tokenizer = NoopTokenizer(n_bins, pad_idx=pad_idx) - else: - raise ValueError(f"unrecognized tokenizer `{tokenizer}`.") - - def tokenize(self, x: tp.List[tp.Optional[str]]) -> tp.Tuple[torch.Tensor, torch.Tensor]: - device = self.embed.weight.device - tokens, mask = self.tokenizer(x) - tokens, mask = tokens.to(device), mask.to(device) - return tokens, mask - - def forward(self, inputs: tp.Tuple[torch.Tensor, torch.Tensor]) -> ConditionType: - tokens, mask = inputs - embeds = self.embed(tokens) - embeds = self.output_proj(embeds) - embeds = (embeds * mask.unsqueeze(-1)) - return embeds, mask - - -class T5Conditioner(TextConditioner): - """T5-based TextConditioner. - - Args: - name (str): Name of the T5 model. - output_dim (int): Output dim of the conditioner. - finetune (bool): Whether to fine-tune T5 at train time. - device (str): Device for T5 Conditioner. - autocast_dtype (tp.Optional[str], optional): Autocast dtype. - word_dropout (float, optional): Word dropout probability. - normalize_text (bool, optional): Whether to apply text normalization. - """ - MODELS = ["t5-small", "t5-base", "t5-large", "t5-3b", "t5-11b", - "google/flan-t5-small", "google/flan-t5-base", "google/flan-t5-large", - "google/flan-t5-xl", "google/flan-t5-xxl"] - MODELS_DIMS = { - "t5-small": 512, - "t5-base": 768, - "t5-large": 1024, - "t5-3b": 1024, - "t5-11b": 1024, - "google/flan-t5-small": 512, - "google/flan-t5-base": 768, - "google/flan-t5-large": 1024, - "google/flan-t5-3b": 1024, - "google/flan-t5-11b": 1024, - } - - def __init__(self, name: str, output_dim: int, finetune: bool, device: str, - autocast_dtype: tp.Optional[str] = 'float32', word_dropout: float = 0., - normalize_text: bool = False): - assert name in self.MODELS, f"Unrecognized t5 model name (should in {self.MODELS})" - super().__init__(self.MODELS_DIMS[name], output_dim) - self.device = device - self.name = name - self.finetune = finetune - self.word_dropout = word_dropout - if autocast_dtype is None or self.device == 'cpu': - self.autocast = TorchAutocast(enabled=False) - if self.device != 'cpu': - logger.warning("T5 has no autocast, this might lead to NaN") - else: - dtype = getattr(torch, autocast_dtype) - assert isinstance(dtype, torch.dtype) - logger.info(f"T5 will be evaluated with autocast as {autocast_dtype}") - self.autocast = TorchAutocast(enabled=True, device_type=self.device, dtype=dtype) - # Let's disable logging temporarily because T5 will vomit some errors otherwise. - # thanks https://gist.github.com/simon-weber/7853144 - previous_level = logging.root.manager.disable - logging.disable(logging.ERROR) - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - try: - self.t5_tokenizer = T5Tokenizer.from_pretrained(name) - t5 = T5EncoderModel.from_pretrained(name).train(mode=finetune) - finally: - logging.disable(previous_level) - if finetune: - self.t5 = t5 - else: - # this makes sure that the t5 models is not part - # of the saved checkpoint - self.__dict__['t5'] = t5.to(device) - - self.normalize_text = normalize_text - if normalize_text: - self.text_normalizer = WhiteSpaceTokenizer(1, lemma=True, stopwords=True) - - def tokenize(self, x: tp.List[tp.Optional[str]]) -> tp.Dict[str, torch.Tensor]: - # if current sample doesn't have a certain attribute, replace with empty string - entries: tp.List[str] = [xi if xi is not None else "" for xi in x] - if self.normalize_text: - _, _, entries = self.text_normalizer(entries, return_text=True) - if self.word_dropout > 0. and self.training: - new_entries = [] - for entry in entries: - words = [word for word in entry.split(" ") if random.random() >= self.word_dropout] - new_entries.append(" ".join(words)) - entries = new_entries - - empty_idx = torch.LongTensor([i for i, xi in enumerate(entries) if xi == ""]) - - inputs = self.t5_tokenizer(entries, return_tensors='pt', padding=True).to(self.device) - mask = inputs['attention_mask'] - mask[empty_idx, :] = 0 # zero-out index where the input is non-existant - return inputs - - def forward(self, inputs: tp.Dict[str, torch.Tensor]) -> ConditionType: - mask = inputs['attention_mask'] - with torch.set_grad_enabled(self.finetune), self.autocast: - embeds = self.t5(**inputs).last_hidden_state - embeds = self.output_proj(embeds.to(self.output_proj.weight)) - embeds = (embeds * mask.unsqueeze(-1)) - return embeds, mask - - -class WaveformConditioner(BaseConditioner): - """Base class for all conditioners that take a waveform as input. - Classes that inherit must implement `_get_wav_embedding` that outputs - a continuous tensor, and `_downsampling_factor` that returns the down-sampling - factor of the embedding model. - - Args: - dim (int): The internal representation dimension. - output_dim (int): Output dimension. - device (tp.Union[torch.device, str]): Device. - """ - def __init__(self, dim: int, output_dim: int, device: tp.Union[torch.device, str]): - super().__init__(dim, output_dim) - self.device = device - - def tokenize(self, x: WavCondition) -> WavCondition: - wav, length, sample_rate, path, seek_time = x - assert length is not None - return WavCondition(wav.to(self.device), length.to(self.device), sample_rate, path, seek_time) - - def _get_wav_embedding(self, x: WavCondition) -> torch.Tensor: - """Gets as input a WavCondition and returns a dense embedding.""" - raise NotImplementedError() - - def _downsampling_factor(self): - """Returns the downsampling factor of the embedding model.""" - raise NotImplementedError() - - def forward(self, x: WavCondition) -> ConditionType: - """Extract condition embedding and mask from a waveform and its metadata. - Args: - x (WavCondition): Waveform condition containing raw waveform and metadata. - Returns: - ConditionType: a dense vector representing the conditioning along with its mask - """ - wav, lengths, *_ = x - with torch.no_grad(): - embeds = self._get_wav_embedding(x) - embeds = embeds.to(self.output_proj.weight) - embeds = self.output_proj(embeds) - - if lengths is not None: - lengths = lengths / self._downsampling_factor() - mask = length_to_mask(lengths, max_len=embeds.shape[1]).int() # type: ignore - else: - mask = torch.ones_like(embeds) - embeds = (embeds * mask.unsqueeze(2).to(self.device)) - - return embeds, mask - - -class ChromaStemConditioner(WaveformConditioner): - """Chroma conditioner based on stems. - The ChromaStemConditioner uses DEMUCS to first filter out drums and bass, as - the drums and bass often dominate the chroma leading to the chroma features - not containing information about the melody. - - Args: - output_dim (int): Output dimension for the conditioner. - sample_rate (int): Sample rate for the chroma extractor. - n_chroma (int): Number of chroma bins for the chroma extractor. - radix2_exp (int): Size of stft window for the chroma extractor (power of 2, e.g. 12 -> 2^12). - duration (int): duration used during training. This is later used for correct padding - in case we are using chroma as prefix. - match_len_on_eval (bool, optional): if True then all chromas are padded to the training - duration. Defaults to False. - eval_wavs (str, optional): path to a dataset manifest with waveform, this waveforms are used as - conditions during eval (for cases where we don't want to leak test conditions like MusicCaps). - Defaults to None. - n_eval_wavs (int, optional): limits the number of waveforms used for conditioning. Defaults to 0. - device (tp.Union[torch.device, str], optional): Device for the conditioner. - **kwargs: Additional parameters for the chroma extractor. - """ - def __init__(self, output_dim: int, sample_rate: int, n_chroma: int, radix2_exp: int, - duration: float, match_len_on_eval: bool = True, eval_wavs: tp.Optional[str] = None, - n_eval_wavs: int = 0, cache_path: tp.Optional[tp.Union[str, Path]] = None, - device: tp.Union[torch.device, str] = 'cpu', **kwargs): - from demucs import pretrained - super().__init__(dim=n_chroma, output_dim=output_dim, device=device) - self.autocast = TorchAutocast(enabled=device != 'cpu', device_type=self.device, dtype=torch.float32) - self.sample_rate = sample_rate - self.match_len_on_eval = match_len_on_eval - self.duration = duration - self.__dict__['demucs'] = pretrained.get_model('htdemucs').to(device) - stem_sources: list = self.demucs.sources # type: ignore - self.stem_indices = torch.LongTensor([stem_sources.index('vocals'), stem_sources.index('other')]).to(device) - self.chroma = ChromaExtractor(sample_rate=sample_rate, n_chroma=n_chroma, - radix2_exp=radix2_exp, **kwargs).to(device) - self.chroma_len = self._get_chroma_len() - self.eval_wavs: tp.Optional[torch.Tensor] = self._load_eval_wavs(eval_wavs, n_eval_wavs) - self.cache = None - if cache_path is not None: - self.cache = EmbeddingCache(Path(cache_path) / 'wav', self.device, - compute_embed_fn=self._get_full_chroma_for_cache, - extract_embed_fn=self._extract_chroma_chunk) - - def _downsampling_factor(self) -> int: - return self.chroma.winhop - - def _load_eval_wavs(self, path: tp.Optional[str], num_samples: int) -> tp.Optional[torch.Tensor]: - """Load pre-defined waveforms from a json. - These waveforms will be used for chroma extraction during evaluation. - This is done to make the evaluation on MusicCaps fair (we shouldn't see the chromas of MusicCaps). - """ - if path is None: - return None - - logger.info(f"Loading evaluation wavs from {path}") - from audiocraft.data.audio_dataset import AudioDataset - dataset: AudioDataset = AudioDataset.from_meta( - path, segment_duration=self.duration, min_audio_duration=self.duration, - sample_rate=self.sample_rate, channels=1) - - if len(dataset) > 0: - eval_wavs = dataset.collater([dataset[i] for i in range(num_samples)]).to(self.device) - logger.info(f"Using {len(eval_wavs)} evaluation wavs for chroma-stem conditioner") - return eval_wavs - else: - raise ValueError("Could not find evaluation wavs, check lengths of wavs") - - def reset_eval_wavs(self, eval_wavs: tp.Optional[torch.Tensor]) -> None: - self.eval_wavs = eval_wavs - - def has_eval_wavs(self) -> bool: - return self.eval_wavs is not None - - def _sample_eval_wavs(self, num_samples: int) -> torch.Tensor: - """Sample wavs from a predefined list.""" - assert self.eval_wavs is not None, "Cannot sample eval wavs as no eval wavs provided." - total_eval_wavs = len(self.eval_wavs) - out = self.eval_wavs - if num_samples > total_eval_wavs: - out = self.eval_wavs.repeat(num_samples // total_eval_wavs + 1, 1, 1) - return out[torch.randperm(len(out))][:num_samples] - - def _get_chroma_len(self) -> int: - """Get length of chroma during training.""" - dummy_wav = torch.zeros((1, int(self.sample_rate * self.duration)), device=self.device) - dummy_chr = self.chroma(dummy_wav) - return dummy_chr.shape[1] - - @torch.no_grad() - def _get_stemmed_wav(self, wav: torch.Tensor, sample_rate: int) -> torch.Tensor: - """Get parts of the wav that holds the melody, extracting the main stems from the wav.""" - from demucs.apply import apply_model - from demucs.audio import convert_audio - with self.autocast: - wav = convert_audio( - wav, sample_rate, self.demucs.samplerate, self.demucs.audio_channels) # type: ignore - stems = apply_model(self.demucs, wav, device=self.device) - stems = stems[:, self.stem_indices] # extract relevant stems for melody conditioning - mix_wav = stems.sum(1) # merge extracted stems to single waveform - mix_wav = convert_audio(mix_wav, self.demucs.samplerate, self.sample_rate, 1) # type: ignore - return mix_wav - - @torch.no_grad() - def _extract_chroma(self, wav: torch.Tensor) -> torch.Tensor: - """Extract chroma features from the waveform.""" - with self.autocast: - return self.chroma(wav) - - @torch.no_grad() - def _compute_wav_embedding(self, wav: torch.Tensor, sample_rate: int) -> torch.Tensor: - """Compute wav embedding, applying stem and chroma extraction.""" - # avoid 0-size tensors when we are working with null conds - if wav.shape[-1] == 1: - return self._extract_chroma(wav) - stems = self._get_stemmed_wav(wav, sample_rate) - chroma = self._extract_chroma(stems) - return chroma - - @torch.no_grad() - def _get_full_chroma_for_cache(self, path: tp.Union[str, Path], x: WavCondition, idx: int) -> torch.Tensor: - """Extract chroma from the whole audio waveform at the given path.""" - wav, sr = audio_read(path) - wav = wav[None].to(self.device) - wav = convert_audio(wav, sr, self.sample_rate, to_channels=1) - chroma = self._compute_wav_embedding(wav, self.sample_rate)[0] - return chroma - - def _extract_chroma_chunk(self, full_chroma: torch.Tensor, x: WavCondition, idx: int) -> torch.Tensor: - """Extract a chunk of chroma from the full chroma derived from the full waveform.""" - wav_length = x.wav.shape[-1] - seek_time = x.seek_time[idx] - assert seek_time is not None, ( - "WavCondition seek_time is required " - "when extracting chroma chunks from pre-computed chroma.") - full_chroma = full_chroma.float() - frame_rate = self.sample_rate / self._downsampling_factor() - target_length = int(frame_rate * wav_length / self.sample_rate) - index = int(frame_rate * seek_time) - out = full_chroma[index: index + target_length] - out = F.pad(out[None], (0, 0, 0, target_length - out.shape[0]))[0] - return out.to(self.device) - - @torch.no_grad() - def _get_wav_embedding(self, x: WavCondition) -> torch.Tensor: - """Get the wav embedding from the WavCondition. - The conditioner will either extract the embedding on-the-fly computing it from the condition wav directly - or will rely on the embedding cache to load the pre-computed embedding if relevant. - """ - sampled_wav: tp.Optional[torch.Tensor] = None - if not self.training and self.eval_wavs is not None: - warn_once(logger, "Using precomputed evaluation wavs!") - sampled_wav = self._sample_eval_wavs(len(x.wav)) - - no_undefined_paths = all(p is not None for p in x.path) - no_nullified_cond = x.wav.shape[-1] > 1 - if sampled_wav is not None: - chroma = self._compute_wav_embedding(sampled_wav, self.sample_rate) - elif self.cache is not None and no_undefined_paths and no_nullified_cond: - paths = [Path(p) for p in x.path if p is not None] - chroma = self.cache.get_embed_from_cache(paths, x) - else: - assert all(sr == x.sample_rate[0] for sr in x.sample_rate), "All sample rates in batch should be equal." - chroma = self._compute_wav_embedding(x.wav, x.sample_rate[0]) - - if self.match_len_on_eval: - B, T, C = chroma.shape - if T > self.chroma_len: - chroma = chroma[:, :self.chroma_len] - logger.debug(f"Chroma was truncated to match length! ({T} -> {chroma.shape[1]})") - elif T < self.chroma_len: - n_repeat = int(math.ceil(self.chroma_len / T)) - chroma = chroma.repeat(1, n_repeat, 1) - chroma = chroma[:, :self.chroma_len] - logger.debug(f"Chroma was repeated to match length! ({T} -> {chroma.shape[1]})") - - return chroma - - def tokenize(self, x: WavCondition) -> WavCondition: - """Apply WavConditioner tokenization and populate cache if needed.""" - x = super().tokenize(x) - no_undefined_paths = all(p is not None for p in x.path) - if self.cache is not None and no_undefined_paths: - paths = [Path(p) for p in x.path if p is not None] - self.cache.populate_embed_cache(paths, x) - return x - - -class JointEmbeddingConditioner(BaseConditioner): - """Joint embedding conditioning supporting both audio or text conditioning. - - Args: - dim (int): Dimension. - output_dim (int): Output dimension. - device (str): Device. - attribute (str): Attribute used by the conditioner. - autocast_dtype (str): Autocast for the conditioner. - quantize (bool): Whether to quantize the CLAP embedding. - n_q (int): Number of residual quantizers (used if quantize is true). - bins (int): Quantizers' codebooks size (used if quantize is true). - kwargs: Additional parameters for residual vector quantizer. - """ - def __init__(self, dim: int, output_dim: int, device: str, attribute: str, - autocast_dtype: tp.Optional[str] = 'float32', quantize: bool = True, - n_q: int = 12, bins: int = 1024, **kwargs): - super().__init__(dim=dim, output_dim=output_dim) - self.device = device - self.attribute = attribute - if autocast_dtype is None or device == 'cpu': - self.autocast = TorchAutocast(enabled=False) - logger.warning("JointEmbeddingConditioner has no autocast, this might lead to NaN.") - else: - dtype = getattr(torch, autocast_dtype) - assert isinstance(dtype, torch.dtype) - logger.info(f"JointEmbeddingConditioner will be evaluated with autocast as {autocast_dtype}.") - self.autocast = TorchAutocast(enabled=True, device_type=self.device, dtype=dtype) - # residual vector quantizer to discretize the conditioned embedding - self.quantizer: tp.Optional[ResidualVectorQuantizer] = None - if quantize: - self.quantizer = ResidualVectorQuantizer(dim, n_q=n_q, bins=bins, **kwargs) - - def _get_embed(self, x: JointEmbedCondition) -> tp.Tuple[torch.Tensor, torch.Tensor]: - """Get joint embedding in latent space from the inputs. - - Returns: - tuple[torch.Tensor, torch.Tensor]: Tensor for the latent embedding - and corresponding empty indexes. - """ - raise NotImplementedError() - - def forward(self, x: JointEmbedCondition) -> ConditionType: - with self.autocast: - embed, empty_idx = self._get_embed(x) - if self.quantizer is not None: - embed = embed.view(-1, self.dim, 1) - q_res = self.quantizer(embed, frame_rate=1) - out_embed = q_res.x.view(-1, self.dim) - else: - out_embed = embed - out_embed = self.output_proj(out_embed).view(-1, 1, self.output_dim) - mask = torch.ones(*out_embed.shape[:2], device=out_embed.device) - mask[empty_idx, :] = 0 # zero-out index where the input is non-existant - out_embed = (out_embed * mask.unsqueeze(-1)) - return out_embed, mask - - def tokenize(self, x: JointEmbedCondition) -> JointEmbedCondition: - return x - - -class CLAPEmbeddingConditioner(JointEmbeddingConditioner): - """Joint Embedding conditioner based on pre-trained CLAP model. - - This CLAP-based conditioner supports a caching mechanism - over the computed embeddings for faster training. - - Args: - dim (int): Dimension. - output_dim (int): Output dimension. - device (str): Device. - attribute (str): Attribute used by the conditioner. - quantize (bool): Whether to quantize the CLAP embedding. - n_q (int): Number of residual quantizers (used if quantize is true). - bins (int): Quantizers' codebooks size (used if quantize is true). - checkpoint (str): Path to CLAP checkpoint. - model_arch (str): CLAP model architecture. - enable_fusion (bool): Enable fusion for CLAP model. - sample_rate (int): Sample rate used by CLAP model. - max_audio_length (float): Maximum audio length for CLAP model. - audio_stride (float): Stride to use for getting a CLAP embedding on the full sequence. - normalize (bool): Whether to normalize the CLAP embedding. - text_p (float): Probability of using text representation instead of audio at train time. - batch_size (Optional[int]): Batch size for CLAP embedding computation. - autocast_dtype (str): Autocast for the conditioner. - cache_path (Optional[str]): Path for pre-computed embeddings caching. - kwargs: Additional parameters for residual vector quantizer. - """ - def __init__(self, dim: int, output_dim: int, device: str, attribute: str, - quantize: bool, n_q: int, bins: int, checkpoint: tp.Union[str, Path], model_arch: str, - enable_fusion: bool, sample_rate: int, max_audio_length: int, audio_stride: int, - normalize: bool, text_p: bool, batch_size: tp.Optional[int] = None, - autocast_dtype: tp.Optional[str] = 'float32', cache_path: tp.Optional[str] = None, **kwargs): - try: - import laion_clap # type: ignore - except ImportError: - raise ImportError("Please install CLAP to use the CLAPEmbeddingConditioner: 'pip install laion_clap'") - checkpoint = AudioCraftEnvironment.resolve_reference_path(checkpoint) - clap_tokenize = RobertaTokenizer.from_pretrained('roberta-base') - clap_model = laion_clap.CLAP_Module(enable_fusion=enable_fusion, amodel=model_arch) - load_clap_state_dict(clap_model, checkpoint) - clap_model.eval() - clap_model.to(device) - super().__init__(dim=dim, output_dim=output_dim, device=device, attribute=attribute, - autocast_dtype=autocast_dtype, quantize=quantize, n_q=n_q, bins=bins, - **kwargs) - self.checkpoint = checkpoint - self.enable_fusion = enable_fusion - self.model_arch = model_arch - self.clap: laion_clap.CLAP_Module - self.clap_tokenize: RobertaTokenizer - self.clap_sample_rate = sample_rate - self.clap_max_frames = int(self.clap_sample_rate * max_audio_length) - self.clap_stride = int(self.clap_sample_rate * audio_stride) - self.batch_size = batch_size or 1 - self.normalize = normalize - self.text_p = text_p - self.__dict__['clap_tokenize'] = clap_tokenize - self.__dict__['clap'] = clap_model - self.wav_cache, self.text_cache = None, None - if cache_path is not None: - self.wav_cache = EmbeddingCache(Path(cache_path) / 'wav', self.device, - compute_embed_fn=self._get_wav_embedding_for_cache, - extract_embed_fn=self._extract_wav_embedding_chunk) - self.text_cache = EmbeddingCache(Path(cache_path) / 'text', self.device, - compute_embed_fn=self._get_text_embedding_for_cache) - - def _tokenizer(self, texts: tp.Union[str, tp.List[str]]) -> dict: - # we use the default params from CLAP module here as well - return self.clap_tokenize(texts, padding="max_length", truncation=True, max_length=77, return_tensors="pt") - - def _compute_text_embedding(self, text: tp.List[str]) -> torch.Tensor: - """Compute text embedding from CLAP model on a given a batch of text. - - Args: - text (list[str]): List of text for the batch, with B items. - Returns: - torch.Tensor: CLAP embedding derived from text, of shape [B, 1, D], with D the CLAP embedding dimension. - """ - with torch.no_grad(): - embed = self.clap.get_text_embedding(text, tokenizer=self._tokenizer, use_tensor=True) - return embed.view(embed.size(0), 1, embed.size(-1)) - - def _get_text_embedding_for_cache(self, path: tp.Union[Path, str], - x: JointEmbedCondition, idx: int) -> torch.Tensor: - """Get text embedding function for the cache.""" - text = x.text[idx] - text = text if text is not None else "" - return self._compute_text_embedding([text])[0] - - def _preprocess_wav(self, wav: torch.Tensor, length: torch.Tensor, sample_rates: tp.List[int]) -> torch.Tensor: - """Preprocess wav to expected format by CLAP model. - - Args: - wav (torch.Tensor): Audio wav, of shape [B, C, T]. - length (torch.Tensor): Actual length of the audio for each item in the batch, of shape [B]. - sample_rates (list[int]): Sample rates for each sample in the batch - Returns: - torch.Tensor: Audio wav of shape [B, T]. - """ - assert wav.dim() == 3, "Expecting wav to be [B, C, T]" - if sample_rates is not None: - _wav = [] - for i, audio in enumerate(wav): - sr = sample_rates[i] - audio = convert_audio(audio, from_rate=sr, to_rate=self.clap_sample_rate, to_channels=1) - _wav.append(audio) - wav = torch.stack(_wav, dim=0) - wav = wav.mean(dim=1) - return wav - - def _compute_wav_embedding(self, wav: torch.Tensor, length: torch.Tensor, - sample_rates: tp.List[int], reduce_mean: bool = False) -> torch.Tensor: - """Compute audio wave embedding from CLAP model. - - Since CLAP operates on a fixed sequence length audio inputs and we need to process longer audio sequences, - we calculate the wav embeddings on `clap_max_frames` windows with `clap_stride`-second stride and - average the resulting embeddings. - - Args: - wav (torch.Tensor): Audio wav, of shape [B, C, T]. - length (torch.Tensor): Actual length of the audio for each item in the batch, of shape [B]. - sample_rates (list[int]): Sample rates for each sample in the batch. - reduce_mean (bool): Whether to get the average tensor. - Returns: - torch.Tensor: Audio embedding of shape [B, F, D], F being the number of chunks, D the dimension. - """ - with torch.no_grad(): - wav = self._preprocess_wav(wav, length, sample_rates) - B, T = wav.shape - if T >= self.clap_max_frames: - wav = wav.unfold(-1, self.clap_max_frames, self.clap_stride) # [B, F, T] - else: - wav = wav.view(-1, 1, T) # [B, F, T] with F=1 - wav = einops.rearrange(wav, 'b f t -> (b f) t') - embed_list = [] - for i in range(0, wav.size(0), self.batch_size): - _wav = wav[i:i+self.batch_size, ...] - _embed = self.clap.get_audio_embedding_from_data(_wav, use_tensor=True) - embed_list.append(_embed) - embed = torch.cat(embed_list, dim=0) - embed = einops.rearrange(embed, '(b f) d -> b f d', b=B) - if reduce_mean: - embed = embed.mean(dim=1, keepdim=True) - return embed # [B, F, D] with F=1 if reduce_mean is True - - def _get_wav_embedding_for_cache(self, path: tp.Union[str, Path], - x: JointEmbedCondition, idx: int) -> torch.Tensor: - """Compute audio wave embedding for the cache. - The embedding is computed on a given audio read from file. - - Args: - path (str or Path): Path to the full audio file. - Returns: - torch.Tensor: Single-item tensor of shape [F, D], F being the number of chunks, D the dimension. - """ - wav, sr = audio_read(path) # [C, T] - wav = wav.unsqueeze(0).to(self.device) # [1, C, T] - wav_len = torch.LongTensor([wav.shape[-1]]).to(self.device) - embed = self._compute_wav_embedding(wav, wav_len, [sr], reduce_mean=False) # [B, F, D] - return embed.squeeze(0) # [F, D] - - def _extract_wav_embedding_chunk(self, full_embed: torch.Tensor, x: JointEmbedCondition, idx: int) -> torch.Tensor: - """Extract the chunk of embedding matching the seek_time and length from the full CLAP audio embedding. - - Args: - full_embed (torch.Tensor): CLAP embedding computed on the full wave, of shape [F, D]. - x (JointEmbedCondition): Joint embedding condition for the full batch. - idx (int): Index considered for the given embedding to extract. - Returns: - torch.Tensor: Wav embedding averaged on sliding window, of shape [1, D]. - """ - sample_rate = x.sample_rate[idx] - seek_time = x.seek_time[idx] - seek_time = 0. if seek_time is None else seek_time - clap_stride = int(self.clap_stride / self.clap_sample_rate) * sample_rate - end_seek_time = seek_time + self.clap_max_frames / self.clap_sample_rate - start_offset = int(seek_time * sample_rate // clap_stride) - end_offset = int(end_seek_time * sample_rate // clap_stride) - wav_embed = full_embed[start_offset:end_offset, ...] - wav_embed = wav_embed.mean(dim=0, keepdim=True) - return wav_embed.to(self.device) # [F, D] - - def _get_text_embedding(self, x: JointEmbedCondition) -> torch.Tensor: - """Get CLAP embedding from a batch of text descriptions.""" - no_nullified_cond = x.wav.shape[-1] > 1 # we don't want to read from cache when condition dropout - if self.text_cache is not None and no_nullified_cond: - assert all(p is not None for p in x.path), "Cache requires all JointEmbedCondition paths to be provided" - paths = [Path(p) for p in x.path if p is not None] - embed = self.text_cache.get_embed_from_cache(paths, x) - else: - text = [xi if xi is not None else "" for xi in x.text] - embed = self._compute_text_embedding(text) - if self.normalize: - embed = torch.nn.functional.normalize(embed, p=2.0, dim=-1) - return embed - - def _get_wav_embedding(self, x: JointEmbedCondition) -> torch.Tensor: - """Get CLAP embedding from a batch of audio tensors (and corresponding sample rates).""" - no_undefined_paths = all(p is not None for p in x.path) - no_nullified_cond = x.wav.shape[-1] > 1 # we don't want to read from cache when condition dropout - if self.wav_cache is not None and no_undefined_paths and no_nullified_cond: - paths = [Path(p) for p in x.path if p is not None] - embed = self.wav_cache.get_embed_from_cache(paths, x) - else: - embed = self._compute_wav_embedding(x.wav, x.length, x.sample_rate, reduce_mean=True) - if self.normalize: - embed = torch.nn.functional.normalize(embed, p=2.0, dim=-1) - return embed - - def tokenize(self, x: JointEmbedCondition) -> JointEmbedCondition: - # Trying to limit as much as possible sync points when the cache is warm. - no_undefined_paths = all(p is not None for p in x.path) - if self.wav_cache is not None and no_undefined_paths: - assert all([p is not None for p in x.path]), "Cache requires all JointEmbedCondition paths to be provided" - paths = [Path(p) for p in x.path if p is not None] - self.wav_cache.populate_embed_cache(paths, x) - if self.text_cache is not None and no_undefined_paths: - assert all([p is not None for p in x.path]), "Cache requires all JointEmbedCondition paths to be provided" - paths = [Path(p) for p in x.path if p is not None] - self.text_cache.populate_embed_cache(paths, x) - return x - - def _get_embed(self, x: JointEmbedCondition) -> tp.Tuple[torch.Tensor, torch.Tensor]: - """Extract shared latent representation from either the wav or the text using CLAP.""" - # decide whether to use text embedding at train time or not - use_text_embed = random.random() < self.text_p - if self.training and not use_text_embed: - embed = self._get_wav_embedding(x) - empty_idx = torch.LongTensor([]) # we assume we always have the audio wav - else: - embed = self._get_text_embedding(x) - empty_idx = torch.LongTensor([i for i, xi in enumerate(x.text) if xi is None or xi == ""]) - return embed, empty_idx - - -def dropout_condition(sample: ConditioningAttributes, condition_type: str, condition: str) -> ConditioningAttributes: - """Utility function for nullifying an attribute inside an ConditioningAttributes object. - If the condition is of type "wav", then nullify it using `nullify_condition` function. - If the condition is of any other type, set its value to None. - Works in-place. - """ - if condition_type not in ['text', 'wav', 'joint_embed']: - raise ValueError( - "dropout_condition got an unexpected condition type!" - f" expected 'text', 'wav' or 'joint_embed' but got '{condition_type}'" - ) - - if condition not in getattr(sample, condition_type): - raise ValueError( - "dropout_condition received an unexpected condition!" - f" expected wav={sample.wav.keys()} and text={sample.text.keys()}" - f" but got '{condition}' of type '{condition_type}'!" - ) - - if condition_type == 'wav': - wav_cond = sample.wav[condition] - sample.wav[condition] = nullify_wav(wav_cond) - elif condition_type == 'joint_embed': - embed = sample.joint_embed[condition] - sample.joint_embed[condition] = nullify_joint_embed(embed) - else: - sample.text[condition] = None - - return sample - - -class DropoutModule(nn.Module): - """Base module for all dropout modules.""" - def __init__(self, seed: int = 1234): - super().__init__() - self.rng = torch.Generator() - self.rng.manual_seed(seed) - - -class AttributeDropout(DropoutModule): - """Dropout with a given probability per attribute. - This is different from the behavior of ClassifierFreeGuidanceDropout as this allows for attributes - to be dropped out separately. For example, "artist" can be dropped while "genre" remains. - This is in contrast to ClassifierFreeGuidanceDropout where if "artist" is dropped "genre" - must also be dropped. - - Args: - p (tp.Dict[str, float]): A dict mapping between attributes and dropout probability. For example: - ... - "genre": 0.1, - "artist": 0.5, - "wav": 0.25, - ... - active_on_eval (bool, optional): Whether the dropout is active at eval. Default to False. - seed (int, optional): Random seed. - """ - def __init__(self, p: tp.Dict[str, tp.Dict[str, float]], active_on_eval: bool = False, seed: int = 1234): - super().__init__(seed=seed) - self.active_on_eval = active_on_eval - # construct dict that return the values from p otherwise 0 - self.p = {} - for condition_type, probs in p.items(): - self.p[condition_type] = defaultdict(lambda: 0, probs) - - def forward(self, samples: tp.List[ConditioningAttributes]) -> tp.List[ConditioningAttributes]: - """ - Args: - samples (list[ConditioningAttributes]): List of conditions. - Returns: - list[ConditioningAttributes]: List of conditions after certain attributes were set to None. - """ - if not self.training and not self.active_on_eval: - return samples - - samples = deepcopy(samples) - for condition_type, ps in self.p.items(): # for condition types [text, wav] - for condition, p in ps.items(): # for attributes of each type (e.g., [artist, genre]) - if torch.rand(1, generator=self.rng).item() < p: - for sample in samples: - dropout_condition(sample, condition_type, condition) - return samples - - def __repr__(self): - return f"AttributeDropout({dict(self.p)})" - - -class ClassifierFreeGuidanceDropout(DropoutModule): - """Classifier Free Guidance dropout. - All attributes are dropped with the same probability. - - Args: - p (float): Probability to apply condition dropout during training. - seed (int): Random seed. - """ - def __init__(self, p: float, seed: int = 1234): - super().__init__(seed=seed) - self.p = p - - def forward(self, samples: tp.List[ConditioningAttributes]) -> tp.List[ConditioningAttributes]: - """ - Args: - samples (list[ConditioningAttributes]): List of conditions. - Returns: - list[ConditioningAttributes]: List of conditions after all attributes were set to None. - """ - if not self.training: - return samples - - # decide on which attributes to drop in a batched fashion - drop = torch.rand(1, generator=self.rng).item() < self.p - if not drop: - return samples - - # nullify conditions of all attributes - samples = deepcopy(samples) - for condition_type in ["wav", "text"]: - for sample in samples: - for condition in sample.attributes[condition_type]: - dropout_condition(sample, condition_type, condition) - return samples - - def __repr__(self): - return f"ClassifierFreeGuidanceDropout(p={self.p})" - - -class ConditioningProvider(nn.Module): - """Prepare and provide conditions given all the supported conditioners. - - Args: - conditioners (dict): Dictionary of conditioners. - device (torch.device or str, optional): Device for conditioners and output condition types. - """ - def __init__(self, conditioners: tp.Dict[str, BaseConditioner], device: tp.Union[torch.device, str] = "cpu"): - super().__init__() - self.device = device - self.conditioners = nn.ModuleDict(conditioners) - - @property - def joint_embed_conditions(self): - return [m.attribute for m in self.conditioners.values() if isinstance(m, JointEmbeddingConditioner)] - - @property - def has_joint_embed_conditions(self): - return len(self.joint_embed_conditions) > 0 - - @property - def text_conditions(self): - return [k for k, v in self.conditioners.items() if isinstance(v, TextConditioner)] - - @property - def wav_conditions(self): - return [k for k, v in self.conditioners.items() if isinstance(v, WaveformConditioner)] - - @property - def has_wav_condition(self): - return len(self.wav_conditions) > 0 - - def tokenize(self, inputs: tp.List[ConditioningAttributes]) -> tp.Dict[str, tp.Any]: - """Match attributes/wavs with existing conditioners in self, and compute tokenize them accordingly. - This should be called before starting any real GPU work to avoid synchronization points. - This will return a dict matching conditioner names to their arbitrary tokenized representations. - - Args: - inputs (list[ConditioningAttributes]): List of ConditioningAttributes objects containing - text and wav conditions. - """ - assert all([isinstance(x, ConditioningAttributes) for x in inputs]), ( - "Got unexpected types input for conditioner! should be tp.List[ConditioningAttributes]", - f" but types were {set([type(x) for x in inputs])}" - ) - - output = {} - text = self._collate_text(inputs) - wavs = self._collate_wavs(inputs) - joint_embeds = self._collate_joint_embeds(inputs) - - assert set(text.keys() | wavs.keys() | joint_embeds.keys()).issubset(set(self.conditioners.keys())), ( - f"Got an unexpected attribute! Expected {self.conditioners.keys()}, ", - f"got {text.keys(), wavs.keys(), joint_embeds.keys()}" - ) - - for attribute, batch in chain(text.items(), wavs.items(), joint_embeds.items()): - output[attribute] = self.conditioners[attribute].tokenize(batch) - return output - - def forward(self, tokenized: tp.Dict[str, tp.Any]) -> tp.Dict[str, ConditionType]: - """Compute pairs of `(embedding, mask)` using the configured conditioners and the tokenized representations. - The output is for example: - { - "genre": (torch.Tensor([B, 1, D_genre]), torch.Tensor([B, 1])), - "description": (torch.Tensor([B, T_desc, D_desc]), torch.Tensor([B, T_desc])), - ... - } - - Args: - tokenized (dict): Dict of tokenized representations as returned by `tokenize()`. - """ - output = {} - for attribute, inputs in tokenized.items(): - condition, mask = self.conditioners[attribute](inputs) - output[attribute] = (condition, mask) - return output - - def _collate_text(self, samples: tp.List[ConditioningAttributes]) -> tp.Dict[str, tp.List[tp.Optional[str]]]: - """Given a list of ConditioningAttributes objects, compile a dictionary where the keys - are the attributes and the values are the aggregated input per attribute. - For example: - Input: - [ - ConditioningAttributes(text={"genre": "Rock", "description": "A rock song with a guitar solo"}, wav=...), - ConditioningAttributes(text={"genre": "Hip-hop", "description": "A hip-hop verse"}, wav=...), - ] - Output: - { - "genre": ["Rock", "Hip-hop"], - "description": ["A rock song with a guitar solo", "A hip-hop verse"] - } - - Args: - samples (list of ConditioningAttributes): List of ConditioningAttributes samples. - Returns: - dict[str, list[str, optional]]: A dictionary mapping an attribute name to text batch. - """ - out: tp.Dict[str, tp.List[tp.Optional[str]]] = defaultdict(list) - texts = [x.text for x in samples] - for text in texts: - for condition in self.text_conditions: - out[condition].append(text[condition]) - return out - - def _collate_wavs(self, samples: tp.List[ConditioningAttributes]) -> tp.Dict[str, WavCondition]: - """Generate a dict where the keys are attributes by which we fetch similar wavs, - and the values are Tensors of wavs according to said attributes. - - *Note*: by the time the samples reach this function, each sample should have some waveform - inside the "wav" attribute. It should be either: - 1. A real waveform - 2. A null waveform due to the sample having no similar waveforms (nullified by the dataset) - 3. A null waveform due to it being dropped in a dropout module (nullified by dropout) - - Args: - samples (list of ConditioningAttributes): List of ConditioningAttributes samples. - Returns: - dict[str, WavCondition]: A dictionary mapping an attribute name to wavs. - """ - wavs = defaultdict(list) - lengths = defaultdict(list) - sample_rates = defaultdict(list) - paths = defaultdict(list) - seek_times = defaultdict(list) - out: tp.Dict[str, WavCondition] = {} - - for sample in samples: - for attribute in self.wav_conditions: - wav, length, sample_rate, path, seek_time = sample.wav[attribute] - assert wav.dim() == 3, f"Got wav with dim={wav.dim()}, but expected 3 [1, C, T]" - assert wav.size(0) == 1, f"Got wav [B, C, T] with shape={wav.shape}, but expected B == 1" - # mono-channel conditioning - wav = wav.mean(1, keepdim=True) # [1, 1, T] - wavs[attribute].append(wav.flatten()) # [T] - lengths[attribute].append(length) - sample_rates[attribute].extend(sample_rate) - paths[attribute].extend(path) - seek_times[attribute].extend(seek_time) - - # stack all wavs to a single tensor - for attribute in self.wav_conditions: - stacked_wav, _ = collate(wavs[attribute], dim=0) - out[attribute] = WavCondition( - stacked_wav.unsqueeze(1), torch.cat(lengths[attribute]), sample_rates[attribute], - paths[attribute], seek_times[attribute]) - - return out - - def _collate_joint_embeds(self, samples: tp.List[ConditioningAttributes]) -> tp.Dict[str, JointEmbedCondition]: - """Generate a dict where the keys are attributes by which we compute joint embeddings, - and the values are Tensors of pre-computed embeddings and the corresponding text attributes. - - Args: - samples (list[ConditioningAttributes]): List of ConditioningAttributes samples. - Returns: - A dictionary mapping an attribute name to joint embeddings. - """ - texts = defaultdict(list) - wavs = defaultdict(list) - lengths = defaultdict(list) - sample_rates = defaultdict(list) - paths = defaultdict(list) - seek_times = defaultdict(list) - channels: int = 0 - - out = {} - for sample in samples: - for attribute in self.joint_embed_conditions: - wav, text, length, sample_rate, path, seek_time = sample.joint_embed[attribute] - assert wav.dim() == 3 - if channels == 0: - channels = wav.size(1) - else: - assert channels == wav.size(1), "not all audio has same number of channels in batch" - assert wav.size(0) == 1, "Expecting single-wav batch in the collate method" - wav = einops.rearrange(wav, "b c t -> (b c t)") # [1, C, T] => [C * T] - wavs[attribute].append(wav) - texts[attribute].extend(text) - lengths[attribute].append(length) - sample_rates[attribute].extend(sample_rate) - paths[attribute].extend(path) - seek_times[attribute].extend(seek_time) - - for attribute in self.joint_embed_conditions: - stacked_texts = texts[attribute] - stacked_paths = paths[attribute] - stacked_seek_times = seek_times[attribute] - stacked_wavs = pad_sequence(wavs[attribute]).to(self.device) - stacked_wavs = einops.rearrange(stacked_wavs, "(c t) b -> b c t", c=channels) - stacked_sample_rates = sample_rates[attribute] - stacked_lengths = torch.cat(lengths[attribute]).to(self.device) - assert stacked_lengths.size(0) == stacked_wavs.size(0) - assert len(stacked_sample_rates) == stacked_wavs.size(0) - assert len(stacked_texts) == stacked_wavs.size(0) - out[attribute] = JointEmbedCondition( - text=stacked_texts, wav=stacked_wavs, - length=stacked_lengths, sample_rate=stacked_sample_rates, - path=stacked_paths, seek_time=stacked_seek_times) - - return out - - -class ConditionFuser(StreamingModule): - """Condition fuser handles the logic to combine the different conditions - to the actual model input. - - Args: - fuse2cond (tp.Dict[str, str]): A dictionary that says how to fuse - each condition. For example: - { - "prepend": ["description"], - "sum": ["genre", "bpm"], - "cross": ["description"], - } - cross_attention_pos_emb (bool, optional): Use positional embeddings in cross attention. - cross_attention_pos_emb_scale (int): Scale for positional embeddings in cross attention if used. - """ - FUSING_METHODS = ["sum", "prepend", "cross", "input_interpolate"] - - def __init__(self, fuse2cond: tp.Dict[str, tp.List[str]], cross_attention_pos_emb: bool = False, - cross_attention_pos_emb_scale: float = 1.0): - super().__init__() - assert all( - [k in self.FUSING_METHODS for k in fuse2cond.keys()] - ), f"Got invalid fuse method, allowed methods: {self.FUSING_METHODS}" - self.cross_attention_pos_emb = cross_attention_pos_emb - self.cross_attention_pos_emb_scale = cross_attention_pos_emb_scale - self.fuse2cond: tp.Dict[str, tp.List[str]] = fuse2cond - self.cond2fuse: tp.Dict[str, str] = {} - for fuse_method, conditions in fuse2cond.items(): - for condition in conditions: - self.cond2fuse[condition] = fuse_method - - def forward( - self, - input: torch.Tensor, - conditions: tp.Dict[str, ConditionType] - ) -> tp.Tuple[torch.Tensor, tp.Optional[torch.Tensor]]: - """Fuse the conditions to the provided model input. - - Args: - input (torch.Tensor): Transformer input. - conditions (dict[str, ConditionType]): Dict of conditions. - Returns: - tuple[torch.Tensor, torch.Tensor]: The first tensor is the transformer input - after the conditions have been fused. The second output tensor is the tensor - used for cross-attention or None if no cross attention inputs exist. - """ - B, T, _ = input.shape - - if 'offsets' in self._streaming_state: - first_step = False - offsets = self._streaming_state['offsets'] - else: - first_step = True - offsets = torch.zeros(input.shape[0], dtype=torch.long, device=input.device) - - assert set(conditions.keys()).issubset(set(self.cond2fuse.keys())), \ - f"given conditions contain unknown attributes for fuser, " \ - f"expected {self.cond2fuse.keys()}, got {conditions.keys()}" - cross_attention_output = None - for cond_type, (cond, cond_mask) in conditions.items(): - op = self.cond2fuse[cond_type] - if op == 'sum': - input += cond - elif op == 'input_interpolate': - cond = einops.rearrange(cond, "b t d -> b d t") - cond = F.interpolate(cond, size=input.shape[1]) - input += einops.rearrange(cond, "b d t -> b t d") - elif op == 'prepend': - if first_step: - input = torch.cat([cond, input], dim=1) - elif op == 'cross': - if cross_attention_output is not None: - cross_attention_output = torch.cat([cross_attention_output, cond], dim=1) - else: - cross_attention_output = cond - else: - raise ValueError(f"unknown op ({op})") - - if self.cross_attention_pos_emb and cross_attention_output is not None: - positions = torch.arange( - cross_attention_output.shape[1], - device=cross_attention_output.device - ).view(1, -1, 1) - pos_emb = create_sin_embedding(positions, cross_attention_output.shape[-1]) - cross_attention_output = cross_attention_output + self.cross_attention_pos_emb_scale * pos_emb - - if self._is_streaming: - self._streaming_state['offsets'] = offsets + T - - return input, cross_attention_output diff --git a/spaces/AIWaves/Debate/gradio_config.py b/spaces/AIWaves/Debate/gradio_config.py deleted file mode 100644 index 0250bf3d9860cb9fcf1cda7610725d7bcb66bf64..0000000000000000000000000000000000000000 --- a/spaces/AIWaves/Debate/gradio_config.py +++ /dev/null @@ -1,437 +0,0 @@ -# coding=utf-8 -# Copyright 2023 The AIWaves Inc. team. - -# -# 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 json -from PIL import Image -import requests -from typing import List, Tuple - -class GradioConfig: - # How many avatars are currently registered - POINTER = 0 - - # Avatar image. You can add or replace. - AGENT_HEAD_URL = [ - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306241687579617434043.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306241687592097408547.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561699613.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561275758.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021090300/ry5k31wt33c.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021090300/0ls2gmwhrf5.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/02/202302281677545695326193.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/03/202303271679886128550253.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686711344407060.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686711345834296.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/05/202305171684311194291520.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/05/202305171684311196958993.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021082612/vr0bkov0dwl.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021082612/auqx5zfsv5g.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021082612/llofpivtwls.jpg", - "https://img.touxiangwu.com/uploads/allimg/2021082612/3j2sdot3ye0.jpg", - "https://img.touxiangwu.com/2020/3/nQfYf2.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918068774532.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918068289945.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918069785183.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561292003.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561578616.jpg", - "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726564597524.jpg" - ] - USER_HEAD_URL = "https://img.touxiangwu.com/zb_users/upload/2023/05/202305301685407468585486.jpg" - - # The css style of gradio.Chatbot - CSS = """ - #chatbot1 .user { - background-color:transparent; - border-color:transparent; - } - #chatbot1 .bot { - background-color:transparent; - border-color:transparent; - } - #btn {color: red; border-color: red;} - """ - - ID = ["USER", "AGENT", "SYSTEM"] - - # Bubble template - BUBBLE_CSS = { - # Background-color Name-color Name-content Font-color Font-size Content Avatar-URL - "USER": """ -
- 
-
- """,
-
- # Avatar-URL Background-color Name-color Name-Content Font-color Font-size Content
- "AGENT": """
-
-
- {}
-{}
-
-
-
- """,
-
- # Backrgound-color Font-size Font-color Name Content
- "SYSTEM": """
-
-
- {}
-{}
-
-
- """
- }
-
- ROLE_2_NAME = {}
-
- OBJECT_INFO = {
-
- "User": {
- # https://img-blog.csdnimg.cn/img_convert/7c20bc39ac69b6972a22e18762d02db3.jpeg
- "head_url": USER_HEAD_URL,
- "bubble_color": "#95EC69",
- "text_color": "#000000",
- "font_size": 0,
- "id": "USER"
- },
-
- "System": {
- # https://img-blog.csdnimg.cn/img_convert/e7e5887cfff67df8c2205c2ef0e5e7fa.png
- "head_url": "https://img.touxiangwu.com/zb_users/upload/2023/03/202303141678768524747045.jpg",
- "bubble_color": "#7F7F7F", ##FFFFFF
- "text_color": "#FFFFFF", ##000000
- "font_size": 0,
- "id": "SYSTEM"
- },
-
- "wait": {
- "head_url": "https://img.touxiangwu.com/zb_users/upload/2022/12/202212011669881536145501.jpg",
- "bubble_color": "#E7CBA6",
- "text_color": "#000000",
- "font_size": 0,
- "id": "AGENT"
- },
-
- "Recorder": {
- "head_url": "https://img.touxiangwu.com/zb_users/upload/2023/02/202302281677545695326193.jpg",
- "bubble_color": "#F7F7F7",
- "text_color": "#000000",
- "font_size": 0,
- "id": "AGENT"
- }
- }
-
- @classmethod
- def color_for_img(cls, url):
- """
- Extract the main colors from the picture and set them as the background color,
- then determine the corresponding text color.
- """
-
- def get_main_color(image):
- image = image.convert("RGB")
- width, height = image.size
- pixels = image.getcolors(width * height)
- most_common_pixel = max(pixels, key=lambda item: item[0])
- return most_common_pixel[1]
-
- def is_dark_color(rgb_color):
- r, g, b = rgb_color
- luminance = (0.299 * r + 0.587 * g + 0.114 * b) / 255
- return luminance < 0.5
-
- def download_image(url):
- print(f"binding: {url}")
- response = requests.get(url)
- if response.status_code == 200:
- with open('image.jpg', 'wb') as f:
- f.write(response.content)
-
- def rgb_to_hex(color):
- return "#{:02X}{:02X}{:02X}".format(color[0], color[1], color[2])
-
- def get_color(image_url):
- download_image(image_url)
-
- image = Image.open("image.jpg")
- main_color = get_main_color(image)
- is_dark = is_dark_color(main_color)
-
- if is_dark:
- font_color = "#FFFFFF"
- else:
- font_color = "#000000"
-
- return rgb_to_hex(main_color), font_color
-
- return get_color(url)
-
- @classmethod
- def init(cls, JSON):
- # Deprecated
- with open(JSON) as f:
- sop = json.load(f)
- cnt = 0
- FISRT_NODE = True
- fisrt_node_roles = []
- for node_name in sop['nodes']:
- node_info = sop['nodes'][node_name]
- agent_states = node_info['agent_states']
- for agent_role in agent_states:
- name = agent_states[agent_role]['style']['name']
- cls.ROLE_2_NAME[agent_role] = name
- if FISRT_NODE:
- fisrt_node_roles.append(agent_role)
- bubble_color, text_color = cls.color_for_img(cls.AGENT_HEAD_URL[cnt])
- cls.OBJECT_INFO[name] = {
- "head_url": f"{cls.AGENT_HEAD_URL[cnt]}",
- "bubble_color": bubble_color,
- "text_color": text_color,
- "font_size": 0,
- "id": "AGENT"
- }
- cnt += 1
- if FISRT_NODE:
- FISRT_NODE = False
- print(cls.OBJECT_INFO)
- for usr_name in cls.OBJECT_INFO:
- if cls.OBJECT_INFO[usr_name]["id"] == "SYSTEM":
- cls.OBJECT_INFO[usr_name]["font_size"] = 12
- elif cls.OBJECT_INFO[usr_name]["id"] in ["USER", "AGENT"]:
- cls.OBJECT_INFO[usr_name]["font_size"] = 16
- else:
- assert False
- return fisrt_node_roles
-
- @classmethod
- def add_agent(cls, agents_name:List):
- for name in agents_name:
- bubble_color, text_color = cls.color_for_img(cls.AGENT_HEAD_URL[cls.POINTER])
- cls.OBJECT_INFO[name] = {
- "head_url": f"{cls.AGENT_HEAD_URL[cls.POINTER]}",
- "bubble_color": bubble_color,
- "text_color": text_color,
- "font_size": 0,
- "id": "AGENT"
- }
- cls.POINTER += 1
- for usr_name in cls.OBJECT_INFO:
- if cls.OBJECT_INFO[usr_name]["id"] == "SYSTEM":
- cls.OBJECT_INFO[usr_name]["font_size"] = 12
- elif cls.OBJECT_INFO[usr_name]["id"] in ["USER", "AGENT"]:
- cls.OBJECT_INFO[usr_name]["font_size"] = 16
- else:
- assert False
-
-
-class StateConfig:
- """UI configuration for the step progress bar (indicating the current node)"""
-
- CSS = """
-:root {
- --gradient-start: 100%;
- --gradient-end: 0%;
- }
-.container.progress-bar-container {
- position: relative;
- display: flex;
- align-items: flex-end;
- width: 100%;
- overflow-x: auto;
- padding-bottom: 30px;
- padding-top: 20px
-}
-.container.progress-bar-container::-webkit-scrollbar {
- width: 8px;
- background-color: transparent;
-}
-
-.container.progress-bar-container::-webkit-scrollbar-thumb {
- background-color: transparent;
-}
-
-.progress-bar-container .progressbar {
- counter-reset: step;
- white-space: nowrap;
-}
-.progress-bar-container .progressbar li {
- list-style: none;
- display: inline-block;
- width: 200px;
- position: relative;
- text-align: center;
- cursor: pointer;
- white-space: normal;
-}
-.progress-bar-container .progressbar li:before {
- content: counter(step);
- counter-increment: step;
- width: 30px;
- height: 30px;
- line-height: 30px;
- border: 1px solid #ddd;
- border-radius: 100%;
- display: block;
- text-align: center;
- margin: 0 auto 10px auto;
- background-color: #ffffff;
-}
-.progress-bar-container .progressbar li:after {
- content: attr(data-content);
- position: absolute;
- width: 87%;
- height: 2px;
- background-color: #dddddd;
- top: 15px;
- left: -45%;
-}
-.progress-bar-container .progressbar li:first-child:after {
- content: none;
-}
-.progress-bar-container .progressbar li.active {
- color: green;
-}
-.progress-bar-container .progressbar li.active:before {
- border-color: green;
- background-color: green;
- color: white;
-}
-.progress-bar-container .progressbar li.active + li:after {
- background: linear-gradient(to right, green var(--gradient-start), lightgray var(--gradient-end));
-}
-.progress-bar-container .small-element {
- transform: scale(0.8);
-}
-.progress-bar-container .progressbar li span {
- position: absolute;
- top: 40px;
- left: 0;
- width: 100%;
- text-align: center;
-}
-.progress-bar-container .progressbar li .data-content {
- position: absolute;
- width: 100%;
- top: -10px;
- left: -100px;
- text-align: center;
-}
-"""
-
- FORMAT = """
-
-
-
-
-
-
-
- {}:{}
--
-
-
- {}
-
-
- {}
-- {} -
-
- Don't forget to change space hardware to GPU after duplicating it.""") - - with gr.Row(): - with gr.Column(): - with gr.Tab("Image to 3D"): - img = gr.Image(label="Image") - gr.Markdown("Best results with images of 3D objects with no shadows on a white background.") - btn_generate_img2obj = gr.Button(value="Generate") - - with gr.Tab("Text to 3D"): - gr.Markdown("Generate an image with Stable Diffusion, then convert it to 3D. Just enter the object you want to generate.") - prompt_sd = gr.Textbox(label="Prompt", placeholder="a 3d rendering of [your prompt], full view, white background") - btn_generate_txt2sd = gr.Button(value="Generate image") - img_sd = gr.Image(label="Image") - btn_generate_sd2obj = gr.Button(value="Convert to 3D", visible=False) - - with gr.Accordion("Advanced settings", open=False): - dropdown_models = gr.Dropdown(label="Model", value="base40M", choices=["base40M", "base300M"]) #, "base1B"]) - guidance_scale = gr.Slider(label="Guidance scale", value=3.0, minimum=3.0, maximum=10.0, step=0.1) - grid_size = gr.Slider(label="Grid size (for .obj 3D model)", value=32, minimum=16, maximum=128, step=16) - - with gr.Column(): - plot = gr.Plot(label="Point cloud") - # btn_pc_to_obj = gr.Button(value="Convert to OBJ", visible=False) - model_3d = gr.Model3D(value=None) - file_out = gr.File(label="Files", visible=False) - - # state_info = state_info = gr.Textbox(label="State", show_label=False).style(container=False) - - - # inputs = [dropdown_models, prompt, img, guidance_scale, grid_size] - outputs = [plot, model_3d, file_out] - - btn_generate_img2obj.click(generate_3D, inputs=[img, dropdown_models, guidance_scale, grid_size], outputs=outputs) - - prompt_sd.submit(generate_txt2img, inputs=prompt_sd, outputs=[img_sd, btn_generate_sd2obj]) - btn_generate_txt2sd.click(generate_txt2img, inputs=prompt_sd, outputs=[img_sd, btn_generate_sd2obj], queue=False) - btn_generate_sd2obj.click(generate_3D, inputs=[img, dropdown_models, guidance_scale, grid_size], outputs=outputs) - - # btn_pc_to_obj.click(ply_to_obj, inputs=plot, outputs=[model_3d, file_out]) - - gr.Examples( - examples=[ - ["images/corgi.png"], - ["images/cube_stack.jpg"], - ["images/chair.png"], - ], - inputs=[img], - outputs=outputs, - fn=generate_3D, - cache_examples=False - ) - - # app.load(get_state, inputs=[], outputs=state_info, every=0.5, show_progress=False) - - gr.HTML(""" -
-
-
-
-
-
- """)
-
-app.queue(max_size=250, concurrency_count=6).launch()
diff --git a/spaces/ASJMO/freegpt/g4f/Provider/Providers/Lockchat.py b/spaces/ASJMO/freegpt/g4f/Provider/Providers/Lockchat.py
deleted file mode 100644
index 1bce74035403bf8615e68ccfcc9deb7e0151817a..0000000000000000000000000000000000000000
--- a/spaces/ASJMO/freegpt/g4f/Provider/Providers/Lockchat.py
+++ /dev/null
@@ -1,32 +0,0 @@
-import requests
-import os
-import json
-from ...typing import sha256, Dict, get_type_hints
-url = 'http://supertest.lockchat.app'
-model = ['gpt-4', 'gpt-3.5-turbo']
-supports_stream = True
-needs_auth = False
-
-def _create_completion(model: str, messages: list, stream: bool, temperature: float = 0.7, **kwargs):
-
- payload = {
- "temperature": 0.7,
- "messages": messages,
- "model": model,
- "stream": True,
- }
- headers = {
- "user-agent": "ChatX/39 CFNetwork/1408.0.4 Darwin/22.5.0",
- }
- response = requests.post("http://supertest.lockchat.app/v1/chat/completions",
- json=payload, headers=headers, stream=True)
- for token in response.iter_lines():
- if b'The model: `gpt-4` does not exist' in token:
- print('error, retrying...')
- _create_completion(model=model, messages=messages, stream=stream, temperature=temperature, **kwargs)
- if b"content" in token:
- token = json.loads(token.decode('utf-8').split('data: ')[1])['choices'][0]['delta'].get('content')
- if token: yield (token)
-
-params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
- '(%s)' % ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
\ No newline at end of file
diff --git a/spaces/Abhaykoul/Palm-2/app.py b/spaces/Abhaykoul/Palm-2/app.py
deleted file mode 100644
index d42522553265f834b8b3718be39b21d0b745582b..0000000000000000000000000000000000000000
--- a/spaces/Abhaykoul/Palm-2/app.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import streamlit as st
-import google.generativeai as palm
-
-# Configure the API key
-palm.configure(api_key="AIzaSyCnrcQWTEedcGuEsJ9Uhbj_ZS9B2nozMiU")
-
-defaults = {
- 'model': 'models/text-bison-001',
- 'temperature': 1,
- 'candidate_count': 1,
- 'top_k': 40,
- 'top_p': 0.95,
- 'max_output_tokens': 1024,
- 'stop_sequences': [],
- 'safety_settings': [
- {"category": "HARM_CATEGORY_DEROGATORY", "threshold": 4},
- {"category": "HARM_CATEGORY_TOXICITY", "threshold": 4},
- {"category": "HARM_CATEGORY_VIOLENCE", "threshold": 4},
- {"category": "HARM_CATEGORY_SEXUAL", "threshold": 4},
- {"category": "HARM_CATEGORY_MEDICAL", "threshold": 4},
- {"category": "HARM_CATEGORY_DANGEROUS", "threshold": 4},
- ]
-}
-
-st.title("HelpingAI")
-
-user_input = st.text_input('You: ')
-
-if st.button('Submit'):
- if user_input.lower() in ['quit', 'exit', 'bye']:
- st.write("Goodbye! Have a great day!")
- else:
- prompt = f"""Hello! I am HelpingAI. I am developed by Abhay Koul, who is 16 years old and lives in KP Colony, Vessu, Anantnag. Abhay Koul is currently working on more AI and AI-related projects.Certainly! If you're looking for more information about Abhay Koul's projects and HelpingAI, I would recommend joining the Discord community. You can find additional details there. He has been working on AI from Jan 2023. If you want more details, you can join the Discord community. The main function of HelpingAI is to make learning and education easier and more convenient for students. My purpose is to simplify your learning journey by providing personalized assistance, innovative teaching methods, and tailored resources to meet your unique needs. I am here to make your educational experience more enjoyable and effective. Feel free to ask me any questions or let me know how I can assist you in your learning adventure and in many more things from your life. Also, HelpingAI was initially developed for S.U.P.E.R.B.O.T. and vortexAI, for more info visit: https://github.com/HelpingAI, https://replit.com/@Devastation-war, join Discord https://discord.gg/2EeZcJjyRd.
-input: {user_input}
-output:"""
-
- response = palm.generate_text(**defaults, prompt=prompt)
- st.write(response.result)
diff --git a/spaces/Abhilashvj/planogram-compliance/utils/augmentations.py b/spaces/Abhilashvj/planogram-compliance/utils/augmentations.py
deleted file mode 100644
index 401e11e5c60da3482d9b9225c2ca169fbb3f9185..0000000000000000000000000000000000000000
--- a/spaces/Abhilashvj/planogram-compliance/utils/augmentations.py
+++ /dev/null
@@ -1,564 +0,0 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-"""
-Image augmentation functions
-"""
-
-import math
-import random
-
-import cv2
-import numpy as np
-import torch
-import torchvision.transforms as T
-import torchvision.transforms.functional as TF
-
-from utils.general import (
- LOGGER,
- check_version,
- colorstr,
- resample_segments,
- segment2box,
- xywhn2xyxy,
-)
-from utils.metrics import bbox_ioa
-
-IMAGENET_MEAN = 0.485, 0.456, 0.406 # RGB mean
-IMAGENET_STD = 0.229, 0.224, 0.225 # RGB standard deviation
-
-
-class Albumentations:
- # YOLOv5 Albumentations class (optional, only used if package is installed)
- def __init__(self, size=640):
- self.transform = None
- prefix = colorstr("albumentations: ")
- try:
- import albumentations as A
-
- check_version(
- A.__version__, "1.0.3", hard=True
- ) # version requirement
-
- T = [
- A.RandomResizedCrop(
- height=size,
- width=size,
- scale=(0.8, 1.0),
- ratio=(0.9, 1.11),
- p=0.0,
- ),
- A.Blur(p=0.01),
- A.MedianBlur(p=0.01),
- A.ToGray(p=0.01),
- A.CLAHE(p=0.01),
- A.RandomBrightnessContrast(p=0.0),
- A.RandomGamma(p=0.0),
- A.ImageCompression(quality_lower=75, p=0.0),
- ] # transforms
- self.transform = A.Compose(
- T,
- bbox_params=A.BboxParams(
- format="yolo", label_fields=["class_labels"]
- ),
- )
-
- LOGGER.info(
- prefix
- + ", ".join(
- f"{x}".replace("always_apply=False, ", "")
- for x in T
- if x.p
- )
- )
- except ImportError: # package not installed, skip
- pass
- except Exception as e:
- LOGGER.info(f"{prefix}{e}")
-
- def __call__(self, im, labels, p=1.0):
- if self.transform and random.random() < p:
- new = self.transform(
- image=im, bboxes=labels[:, 1:], class_labels=labels[:, 0]
- ) # transformed
- im, labels = new["image"], np.array(
- [[c, *b] for c, b in zip(new["class_labels"], new["bboxes"])]
- )
- return im, labels
-
-
-def normalize(x, mean=IMAGENET_MEAN, std=IMAGENET_STD, inplace=False):
- # Denormalize RGB images x per ImageNet stats in BCHW format, i.e. = (x - mean) / std
- return TF.normalize(x, mean, std, inplace=inplace)
-
-
-def denormalize(x, mean=IMAGENET_MEAN, std=IMAGENET_STD):
- # Denormalize RGB images x per ImageNet stats in BCHW format, i.e. = x * std + mean
- for i in range(3):
- x[:, i] = x[:, i] * std[i] + mean[i]
- return x
-
-
-def augment_hsv(im, hgain=0.5, sgain=0.5, vgain=0.5):
- # HSV color-space augmentation
- if hgain or sgain or vgain:
- r = (
- np.random.uniform(-1, 1, 3) * [hgain, sgain, vgain] + 1
- ) # random gains
- hue, sat, val = cv2.split(cv2.cvtColor(im, cv2.COLOR_BGR2HSV))
- dtype = im.dtype # uint8
-
- x = np.arange(0, 256, dtype=r.dtype)
- lut_hue = ((x * r[0]) % 180).astype(dtype)
- lut_sat = np.clip(x * r[1], 0, 255).astype(dtype)
- lut_val = np.clip(x * r[2], 0, 255).astype(dtype)
-
- im_hsv = cv2.merge(
- (
- cv2.LUT(hue, lut_hue),
- cv2.LUT(sat, lut_sat),
- cv2.LUT(val, lut_val),
- )
- )
- cv2.cvtColor(im_hsv, cv2.COLOR_HSV2BGR, dst=im) # no return needed
-
-
-def hist_equalize(im, clahe=True, bgr=False):
- # Equalize histogram on BGR image 'im' with im.shape(n,m,3) and range 0-255
- yuv = cv2.cvtColor(im, cv2.COLOR_BGR2YUV if bgr else cv2.COLOR_RGB2YUV)
- if clahe:
- c = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
- yuv[:, :, 0] = c.apply(yuv[:, :, 0])
- else:
- yuv[:, :, 0] = cv2.equalizeHist(
- yuv[:, :, 0]
- ) # equalize Y channel histogram
- return cv2.cvtColor(
- yuv, cv2.COLOR_YUV2BGR if bgr else cv2.COLOR_YUV2RGB
- ) # convert YUV image to RGB
-
-
-def replicate(im, labels):
- # Replicate labels
- h, w = im.shape[:2]
- boxes = labels[:, 1:].astype(int)
- x1, y1, x2, y2 = boxes.T
- s = ((x2 - x1) + (y2 - y1)) / 2 # side length (pixels)
- for i in s.argsort()[: round(s.size * 0.5)]: # smallest indices
- x1b, y1b, x2b, y2b = boxes[i]
- bh, bw = y2b - y1b, x2b - x1b
- yc, xc = int(random.uniform(0, h - bh)), int(
- random.uniform(0, w - bw)
- ) # offset x, y
- x1a, y1a, x2a, y2a = [xc, yc, xc + bw, yc + bh]
- im[y1a:y2a, x1a:x2a] = im[
- y1b:y2b, x1b:x2b
- ] # im4[ymin:ymax, xmin:xmax]
- labels = np.append(
- labels, [[labels[i, 0], x1a, y1a, x2a, y2a]], axis=0
- )
-
- return im, labels
-
-
-def letterbox(
- im,
- new_shape=(640, 640),
- color=(114, 114, 114),
- auto=True,
- scaleFill=False,
- scaleup=True,
- stride=32,
-):
- # Resize and pad image while meeting stride-multiple constraints
- shape = im.shape[:2] # current shape [height, width]
- if isinstance(new_shape, int):
- new_shape = (new_shape, new_shape)
-
- # Scale ratio (new / old)
- r = min(new_shape[0] / shape[0], new_shape[1] / shape[1])
- if not scaleup: # only scale down, do not scale up (for better val mAP)
- r = min(r, 1.0)
-
- # Compute padding
- ratio = r, r # width, height ratios
- new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r))
- dw, dh = (
- new_shape[1] - new_unpad[0],
- new_shape[0] - new_unpad[1],
- ) # wh padding
- if auto: # minimum rectangle
- dw, dh = np.mod(dw, stride), np.mod(dh, stride) # wh padding
- elif scaleFill: # stretch
- dw, dh = 0.0, 0.0
- new_unpad = (new_shape[1], new_shape[0])
- ratio = (
- new_shape[1] / shape[1],
- new_shape[0] / shape[0],
- ) # width, height ratios
-
- dw /= 2 # divide padding into 2 sides
- dh /= 2
-
- if shape[::-1] != new_unpad: # resize
- im = cv2.resize(im, new_unpad, interpolation=cv2.INTER_LINEAR)
- top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))
- left, right = int(round(dw - 0.1)), int(round(dw + 0.1))
- im = cv2.copyMakeBorder(
- im, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color
- ) # add border
- return im, ratio, (dw, dh)
-
-
-def random_perspective(
- im,
- targets=(),
- segments=(),
- degrees=10,
- translate=0.1,
- scale=0.1,
- shear=10,
- perspective=0.0,
- border=(0, 0),
-):
- # torchvision.transforms.RandomAffine(degrees=(-10, 10), translate=(0.1, 0.1), scale=(0.9, 1.1), shear=(-10, 10))
- # targets = [cls, xyxy]
-
- height = im.shape[0] + border[0] * 2 # shape(h,w,c)
- width = im.shape[1] + border[1] * 2
-
- # Center
- C = np.eye(3)
- C[0, 2] = -im.shape[1] / 2 # x translation (pixels)
- C[1, 2] = -im.shape[0] / 2 # y translation (pixels)
-
- # Perspective
- P = np.eye(3)
- P[2, 0] = random.uniform(
- -perspective, perspective
- ) # x perspective (about y)
- P[2, 1] = random.uniform(
- -perspective, perspective
- ) # y perspective (about x)
-
- # Rotation and Scale
- R = np.eye(3)
- a = random.uniform(-degrees, degrees)
- # a += random.choice([-180, -90, 0, 90]) # add 90deg rotations to small rotations
- s = random.uniform(1 - scale, 1 + scale)
- # s = 2 ** random.uniform(-scale, scale)
- R[:2] = cv2.getRotationMatrix2D(angle=a, center=(0, 0), scale=s)
-
- # Shear
- S = np.eye(3)
- S[0, 1] = math.tan(
- random.uniform(-shear, shear) * math.pi / 180
- ) # x shear (deg)
- S[1, 0] = math.tan(
- random.uniform(-shear, shear) * math.pi / 180
- ) # y shear (deg)
-
- # Translation
- T = np.eye(3)
- T[0, 2] = (
- random.uniform(0.5 - translate, 0.5 + translate) * width
- ) # x translation (pixels)
- T[1, 2] = (
- random.uniform(0.5 - translate, 0.5 + translate) * height
- ) # y translation (pixels)
-
- # Combined rotation matrix
- M = T @ S @ R @ P @ C # order of operations (right to left) is IMPORTANT
- if (
- (border[0] != 0) or (border[1] != 0) or (M != np.eye(3)).any()
- ): # image changed
- if perspective:
- im = cv2.warpPerspective(
- im, M, dsize=(width, height), borderValue=(114, 114, 114)
- )
- else: # affine
- im = cv2.warpAffine(
- im, M[:2], dsize=(width, height), borderValue=(114, 114, 114)
- )
-
- # Visualize
- # import matplotlib.pyplot as plt
- # ax = plt.subplots(1, 2, figsize=(12, 6))[1].ravel()
- # ax[0].imshow(im[:, :, ::-1]) # base
- # ax[1].imshow(im2[:, :, ::-1]) # warped
-
- # Transform label coordinates
- n = len(targets)
- if n:
- use_segments = any(x.any() for x in segments)
- new = np.zeros((n, 4))
- if use_segments: # warp segments
- segments = resample_segments(segments) # upsample
- for i, segment in enumerate(segments):
- xy = np.ones((len(segment), 3))
- xy[:, :2] = segment
- xy = xy @ M.T # transform
- xy = (
- xy[:, :2] / xy[:, 2:3] if perspective else xy[:, :2]
- ) # perspective rescale or affine
-
- # clip
- new[i] = segment2box(xy, width, height)
-
- else: # warp boxes
- xy = np.ones((n * 4, 3))
- xy[:, :2] = targets[:, [1, 2, 3, 4, 1, 4, 3, 2]].reshape(
- n * 4, 2
- ) # x1y1, x2y2, x1y2, x2y1
- xy = xy @ M.T # transform
- xy = (
- xy[:, :2] / xy[:, 2:3] if perspective else xy[:, :2]
- ).reshape(
- n, 8
- ) # perspective rescale or affine
-
- # create new boxes
- x = xy[:, [0, 2, 4, 6]]
- y = xy[:, [1, 3, 5, 7]]
- new = (
- np.concatenate((x.min(1), y.min(1), x.max(1), y.max(1)))
- .reshape(4, n)
- .T
- )
-
- # clip
- new[:, [0, 2]] = new[:, [0, 2]].clip(0, width)
- new[:, [1, 3]] = new[:, [1, 3]].clip(0, height)
-
- # filter candidates
- i = box_candidates(
- box1=targets[:, 1:5].T * s,
- box2=new.T,
- area_thr=0.01 if use_segments else 0.10,
- )
- targets = targets[i]
- targets[:, 1:5] = new[i]
-
- return im, targets
-
-
-def copy_paste(im, labels, segments, p=0.5):
- # Implement Copy-Paste augmentation https://arxiv.org/abs/2012.07177, labels as nx5 np.array(cls, xyxy)
- n = len(segments)
- if p and n:
- h, w, c = im.shape # height, width, channels
- im_new = np.zeros(im.shape, np.uint8)
- for j in random.sample(range(n), k=round(p * n)):
- l, s = labels[j], segments[j]
- box = w - l[3], l[2], w - l[1], l[4]
- ioa = bbox_ioa(box, labels[:, 1:5]) # intersection over area
- if (ioa < 0.30).all(): # allow 30% obscuration of existing labels
- labels = np.concatenate((labels, [[l[0], *box]]), 0)
- segments.append(np.concatenate((w - s[:, 0:1], s[:, 1:2]), 1))
- cv2.drawContours(
- im_new,
- [segments[j].astype(np.int32)],
- -1,
- (1, 1, 1),
- cv2.FILLED,
- )
-
- result = cv2.flip(im, 1) # augment segments (flip left-right)
- i = cv2.flip(im_new, 1).astype(bool)
- im[i] = result[i] # cv2.imwrite('debug.jpg', im) # debug
-
- return im, labels, segments
-
-
-def cutout(im, labels, p=0.5):
- # Applies image cutout augmentation https://arxiv.org/abs/1708.04552
- if random.random() < p:
- h, w = im.shape[:2]
- scales = (
- [0.5] * 1
- + [0.25] * 2
- + [0.125] * 4
- + [0.0625] * 8
- + [0.03125] * 16
- ) # image size fraction
- for s in scales:
- mask_h = random.randint(1, int(h * s)) # create random masks
- mask_w = random.randint(1, int(w * s))
-
- # box
- xmin = max(0, random.randint(0, w) - mask_w // 2)
- ymin = max(0, random.randint(0, h) - mask_h // 2)
- xmax = min(w, xmin + mask_w)
- ymax = min(h, ymin + mask_h)
-
- # apply random color mask
- im[ymin:ymax, xmin:xmax] = [
- random.randint(64, 191) for _ in range(3)
- ]
-
- # return unobscured labels
- if len(labels) and s > 0.03:
- box = np.array([xmin, ymin, xmax, ymax], dtype=np.float32)
- ioa = bbox_ioa(
- box, xywhn2xyxy(labels[:, 1:5], w, h)
- ) # intersection over area
- labels = labels[ioa < 0.60] # remove >60% obscured labels
-
- return labels
-
-
-def mixup(im, labels, im2, labels2):
- # Applies MixUp augmentation https://arxiv.org/pdf/1710.09412.pdf
- r = np.random.beta(32.0, 32.0) # mixup ratio, alpha=beta=32.0
- im = (im * r + im2 * (1 - r)).astype(np.uint8)
- labels = np.concatenate((labels, labels2), 0)
- return im, labels
-
-
-def box_candidates(
- box1, box2, wh_thr=2, ar_thr=100, area_thr=0.1, eps=1e-16
-): # box1(4,n), box2(4,n)
- # Compute candidate boxes: box1 before augment, box2 after augment, wh_thr (pixels), aspect_ratio_thr, area_ratio
- w1, h1 = box1[2] - box1[0], box1[3] - box1[1]
- w2, h2 = box2[2] - box2[0], box2[3] - box2[1]
- ar = np.maximum(w2 / (h2 + eps), h2 / (w2 + eps)) # aspect ratio
- return (
- (w2 > wh_thr)
- & (h2 > wh_thr)
- & (w2 * h2 / (w1 * h1 + eps) > area_thr)
- & (ar < ar_thr)
- ) # candidates
-
-
-def classify_albumentations(
- augment=True,
- size=224,
- scale=(0.08, 1.0),
- ratio=(0.75, 1.0 / 0.75), # 0.75, 1.33
- hflip=0.5,
- vflip=0.0,
- jitter=0.4,
- mean=IMAGENET_MEAN,
- std=IMAGENET_STD,
- auto_aug=False,
-):
- # YOLOv5 classification Albumentations (optional, only used if package is installed)
- prefix = colorstr("albumentations: ")
- try:
- import albumentations as A
- from albumentations.pytorch import ToTensorV2
-
- check_version(A.__version__, "1.0.3", hard=True) # version requirement
- if augment: # Resize and crop
- T = [
- A.RandomResizedCrop(
- height=size, width=size, scale=scale, ratio=ratio
- )
- ]
- if auto_aug:
- # TODO: implement AugMix, AutoAug & RandAug in albumentation
- LOGGER.info(
- f"{prefix}auto augmentations are currently not supported"
- )
- else:
- if hflip > 0:
- T += [A.HorizontalFlip(p=hflip)]
- if vflip > 0:
- T += [A.VerticalFlip(p=vflip)]
- if jitter > 0:
- color_jitter = (
- float(jitter),
- ) * 3 # repeat value for brightness, contrast, satuaration, 0 hue
- T += [A.ColorJitter(*color_jitter, 0)]
- else: # Use fixed crop for eval set (reproducibility)
- T = [
- A.SmallestMaxSize(max_size=size),
- A.CenterCrop(height=size, width=size),
- ]
- T += [
- A.Normalize(mean=mean, std=std),
- ToTensorV2(),
- ] # Normalize and convert to Tensor
- LOGGER.info(
- prefix
- + ", ".join(
- f"{x}".replace("always_apply=False, ", "") for x in T if x.p
- )
- )
- return A.Compose(T)
-
- except ImportError: # package not installed, skip
- LOGGER.warning(
- f"{prefix}⚠️ not found, install with `pip install albumentations` (recommended)"
- )
- except Exception as e:
- LOGGER.info(f"{prefix}{e}")
-
-
-def classify_transforms(size=224):
- # Transforms to apply if albumentations not installed
- assert isinstance(
- size, int
- ), f"ERROR: classify_transforms size {size} must be integer, not (list, tuple)"
- # T.Compose([T.ToTensor(), T.Resize(size), T.CenterCrop(size), T.Normalize(IMAGENET_MEAN, IMAGENET_STD)])
- return T.Compose(
- [
- CenterCrop(size),
- ToTensor(),
- T.Normalize(IMAGENET_MEAN, IMAGENET_STD),
- ]
- )
-
-
-class LetterBox:
- # YOLOv5 LetterBox class for image preprocessing, i.e. T.Compose([LetterBox(size), ToTensor()])
- def __init__(self, size=(640, 640), auto=False, stride=32):
- super().__init__()
- self.h, self.w = (size, size) if isinstance(size, int) else size
- self.auto = auto # pass max size integer, automatically solve for short side using stride
- self.stride = stride # used with auto
-
- def __call__(self, im): # im = np.array HWC
- imh, imw = im.shape[:2]
- r = min(self.h / imh, self.w / imw) # ratio of new/old
- h, w = round(imh * r), round(imw * r) # resized image
- hs, ws = (
- math.ceil(x / self.stride) * self.stride for x in (h, w)
- ) if self.auto else self.h, self.w
- top, left = round((hs - h) / 2 - 0.1), round((ws - w) / 2 - 0.1)
- im_out = np.full((self.h, self.w, 3), 114, dtype=im.dtype)
- im_out[top : top + h, left : left + w] = cv2.resize(
- im, (w, h), interpolation=cv2.INTER_LINEAR
- )
- return im_out
-
-
-class CenterCrop:
- # YOLOv5 CenterCrop class for image preprocessing, i.e. T.Compose([CenterCrop(size), ToTensor()])
- def __init__(self, size=640):
- super().__init__()
- self.h, self.w = (size, size) if isinstance(size, int) else size
-
- def __call__(self, im): # im = np.array HWC
- imh, imw = im.shape[:2]
- m = min(imh, imw) # min dimension
- top, left = (imh - m) // 2, (imw - m) // 2
- return cv2.resize(
- im[top : top + m, left : left + m],
- (self.w, self.h),
- interpolation=cv2.INTER_LINEAR,
- )
-
-
-class ToTensor:
- # YOLOv5 ToTensor class for image preprocessing, i.e. T.Compose([LetterBox(size), ToTensor()])
- def __init__(self, half=False):
- super().__init__()
- self.half = half
-
- def __call__(self, im): # im = np.array HWC in BGR order
- im = np.ascontiguousarray(
- im.transpose((2, 0, 1))[::-1]
- ) # HWC to CHW -> BGR to RGB -> contiguous
- im = torch.from_numpy(im) # to torch
- im = im.half() if self.half else im.float() # uint8 to fp16/32
- im /= 255.0 # 0-255 to 0.0-1.0
- return im
diff --git a/spaces/Adapter/T2I-Adapter/ldm/modules/ema.py b/spaces/Adapter/T2I-Adapter/ldm/modules/ema.py
deleted file mode 100644
index bded25019b9bcbcd0260f0b8185f8c7859ca58c4..0000000000000000000000000000000000000000
--- a/spaces/Adapter/T2I-Adapter/ldm/modules/ema.py
+++ /dev/null
@@ -1,80 +0,0 @@
-import torch
-from torch import nn
-
-
-class LitEma(nn.Module):
- def __init__(self, model, decay=0.9999, use_num_upates=True):
- super().__init__()
- if decay < 0.0 or decay > 1.0:
- raise ValueError('Decay must be between 0 and 1')
-
- self.m_name2s_name = {}
- self.register_buffer('decay', torch.tensor(decay, dtype=torch.float32))
- self.register_buffer('num_updates', torch.tensor(0, dtype=torch.int) if use_num_upates
- else torch.tensor(-1, dtype=torch.int))
-
- for name, p in model.named_parameters():
- if p.requires_grad:
- # remove as '.'-character is not allowed in buffers
- s_name = name.replace('.', '')
- self.m_name2s_name.update({name: s_name})
- self.register_buffer(s_name, p.clone().detach().data)
-
- self.collected_params = []
-
- def reset_num_updates(self):
- del self.num_updates
- self.register_buffer('num_updates', torch.tensor(0, dtype=torch.int))
-
- def forward(self, model):
- decay = self.decay
-
- if self.num_updates >= 0:
- self.num_updates += 1
- decay = min(self.decay, (1 + self.num_updates) / (10 + self.num_updates))
-
- one_minus_decay = 1.0 - decay
-
- with torch.no_grad():
- m_param = dict(model.named_parameters())
- shadow_params = dict(self.named_buffers())
-
- for key in m_param:
- if m_param[key].requires_grad:
- sname = self.m_name2s_name[key]
- shadow_params[sname] = shadow_params[sname].type_as(m_param[key])
- shadow_params[sname].sub_(one_minus_decay * (shadow_params[sname] - m_param[key]))
- else:
- assert not key in self.m_name2s_name
-
- def copy_to(self, model):
- m_param = dict(model.named_parameters())
- shadow_params = dict(self.named_buffers())
- for key in m_param:
- if m_param[key].requires_grad:
- m_param[key].data.copy_(shadow_params[self.m_name2s_name[key]].data)
- else:
- assert not key in self.m_name2s_name
-
- def store(self, parameters):
- """
- Save the current parameters for restoring later.
- Args:
- parameters: Iterable of `torch.nn.Parameter`; the parameters to be
- temporarily stored.
- """
- self.collected_params = [param.clone() for param in parameters]
-
- def restore(self, parameters):
- """
- Restore the parameters stored with the `store` method.
- Useful to validate the model with EMA parameters without affecting the
- original optimization process. Store the parameters before the
- `copy_to` method. After validation (or model saving), use this to
- restore the former parameters.
- Args:
- parameters: Iterable of `torch.nn.Parameter`; the parameters to be
- updated with the stored parameters.
- """
- for c_param, param in zip(self.collected_params, parameters):
- param.data.copy_(c_param.data)
diff --git a/spaces/AgentVerse/agentVerse/agentverse/environments/simulation_env/rules/selector/pokemon.py b/spaces/AgentVerse/agentVerse/agentverse/environments/simulation_env/rules/selector/pokemon.py
deleted file mode 100644
index b631aa8502890fa85b6afca2b576d729eb336306..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/agentverse/environments/simulation_env/rules/selector/pokemon.py
+++ /dev/null
@@ -1,98 +0,0 @@
-from __future__ import annotations
-
-from typing import TYPE_CHECKING, List
-import numpy as np
-import json
-
-from agentverse.message import Message
-
-from . import selector_registry as SelectorRegistry
-from .base import BaseSelector
-
-if TYPE_CHECKING:
- from agentverse.environments import PokemonEnvironment
-
-
-@SelectorRegistry.register("pokemon")
-class PokemonSelector(BaseSelector):
- """
- Selector for Pokemon environment
- """
-
- def select_message(
- self, environment: PokemonEnvironment, messages: List[Message]
- ) -> List[Message]:
- valid = []
- talk_matrix = np.zeros((len(environment.agents), len(environment.agents)))
- agent_to_idx = {agent.name: i for i, agent in enumerate(environment.agents)}
- for i, message in enumerate(messages):
- try:
- content = json.loads(message.content)
- except json.decoder.JSONDecodeError:
- valid.append(0)
- continue
- if content["action"] == "Speak":
- try:
- if "to" not in content:
- # If the model does not generate receiver, then we discard the message
- valid.append(0)
- elif content["to"] in agent_to_idx:
- # TODO: allow talk to a list of agents
- valid.append(1)
- # talk_matrix[i][j] = 1 ==> i talk to j
- talk_matrix[agent_to_idx[message.sender]][
- agent_to_idx[content["to"]]
- ] = 1
- else:
- # If the receiver is not in the environment, then we discard the message
- valid.append(0)
- except:
- valid.append(0)
- continue
- elif content["action"] == "MoveTo":
- # If the agent move to a location that does not exist, then we discard the message
- valid.append(
- "to" in content and content["to"] in environment.locations_to_agents
- )
- else:
- valid.append(1)
- selected_messages = []
- for i, message in enumerate(messages):
- content = json.loads(message.content)
- sender_idx = agent_to_idx[message.sender]
- if valid[i] == 0:
- selected_messages.append(Message())
- continue
- if content["action"] == "MoveTo":
- if np.sum(talk_matrix[:, sender_idx]) > 0:
- # If someone talk to this agent, then we discard the move action
- selected_messages.append(Message())
- else:
- selected_messages.append(message)
- elif content["action"] == "Speak":
- receiver_idx = agent_to_idx[content["to"]]
- if talk_matrix[sender_idx][receiver_idx] == 0:
- # If this agent talk to someone who also talk to this agent, and we
- # select the message from this agent, then we discard the message
- selected_messages.append(Message())
- continue
- if np.sum(talk_matrix[receiver_idx, :]) > 0:
- if talk_matrix[receiver_idx][sender_idx] == 1:
- # If the receiver talk to this agent, then we randomly select one message
- if sender_idx < receiver_idx:
- if np.random.random() < 0.5:
- selected_messages.append(message)
- talk_matrix[receiver_idx][sender_idx] = 0
- else:
- selected_messages.append(Message())
- talk_matrix[sender_idx][receiver_idx] = 0
- else:
- print("Shouldn't happen")
- else:
- # If the receiver talk to other agent, we still talk to the receiver (?)
- selected_messages.append(message)
- else:
- selected_messages.append(message)
- else:
- selected_messages.append(message)
- return selected_messages
diff --git a/spaces/AgentVerse/agentVerse/agentverse/message.py b/spaces/AgentVerse/agentVerse/agentverse/message.py
deleted file mode 100644
index 34d0752c86ae12fb1f735aaf95da9c7444f0bb63..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/agentverse/message.py
+++ /dev/null
@@ -1,35 +0,0 @@
-from pydantic import BaseModel, Field
-from typing import List, Tuple, Set, Union, Any
-
-from agentverse.utils import AgentAction
-
-
-class Message(BaseModel):
- content: Any = Field(default="")
- sender: str = Field(default="")
- receiver: Set[str] = Field(default=set({"all"}))
- sender_agent: object = Field(default=None)
- tool_response: List[Tuple[AgentAction, str]] = Field(default=[])
-
-
-class SolverMessage(Message):
- pass
-
-
-class CriticMessage(Message):
- is_agree: bool
- criticism: str = ""
-
-
-class ExecutorMessage(Message):
- tool_name: str = Field(default="")
- tool_input: Any = None
-
-
-class EvaluatorMessage(Message):
- score: Union[bool, List[bool], int, List[int]]
- advice: str = Field(default="")
-
-
-class RoleAssignerMessage(Message):
- pass
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/dropdownlist/DropDownList.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/dropdownlist/DropDownList.js
deleted file mode 100644
index 999395ca34e4c529d5e38ea0c43260655443870d..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/dropdownlist/DropDownList.js
+++ /dev/null
@@ -1,119 +0,0 @@
-import Label from '../label/Label.js';
-import Methods from './methods/Methods.js'
-
-
-const GetValue = Phaser.Utils.Objects.GetValue;
-
-class DropDownList extends Label {
- constructor(scene, config) {
- super(scene, config);
- this.type = 'rexDropDownList';
- this.timer = undefined;
-
- this.setOptions(GetValue(config, 'options'));
-
- var listConfig = GetValue(config, 'list');
- this.setWrapEnable(GetValue(listConfig, 'wrap', false));
- this.setCreateButtonCallback(GetValue(listConfig, 'createButtonCallback'));
- this.setCreateListBackgroundCallback(GetValue(listConfig, 'createBackgroundCallback'));
- this.setButtonClickCallback(GetValue(listConfig, 'onButtonClick'));
- this.setButtonOverCallback(GetValue(listConfig, 'onButtonOver'));
- this.setButtonOutCallback(GetValue(listConfig, 'onButtonOut'));
- this.setListExpandDirection(GetValue(listConfig, 'expandDirection'));
- this.setListEaseInDuration(GetValue(listConfig, 'easeIn', 500));
- this.setListEaseOutDuration(GetValue(listConfig, 'easeOut', 100));
- this.setListTransitInCallback(GetValue(listConfig, 'transitIn'));
- this.settListTransitOutCallback(GetValue(listConfig, 'transitOut'));
- this.setListSize(GetValue(listConfig, 'width'), GetValue(listConfig, 'height'));
- this.setListAlignmentMode(GetValue(listConfig, 'alignParent', 'text'));
- this.setListAlignmentSide(GetValue(listConfig, 'alignSide', ''));
- this.setListBounds(GetValue(listConfig, 'bounds'));
- this.setListSpace(GetValue(listConfig, 'space'));
- this.setListDraggable(GetValue(listConfig, 'draggable', false));
-
- this.setValueChangeCallback(
- GetValue(config, 'setValueCallback'),
- GetValue(config, 'setValueCallbackScope')
- );
- this.setValue(GetValue(config, 'value'));
-
- this.onClick(this.toggleListPanel, this);
- }
-
- destroy(fromScene) {
- // This Game Object has already been destroyed
- if (!this.scene || this.ignoreDestroy) {
- return;
- }
-
- if (this.listPanel) {
- this.listPanel.destroy(fromScene);
- this.listPanel = undefined;
- }
-
- super.destroy(fromScene);
- }
-
- setOptions(options) {
- if (options === undefined) {
- options = [];
- }
- this.options = options;
- return this;
- }
-
- setValueChangeCallback(callback, scope) {
- this.valueChangeCallback = callback;
- this.valueChangeCallbackScope = scope;
- return this;
- }
-
- setValue(value) {
- this.value = value;
- return this;
- }
-
- get value() {
- return this._value;
- }
-
- set value(value) {
- if (this._value === value) {
- return;
- }
-
- var previousValue = this._value;
- this._value = value;
-
- var callback = this.valueChangeCallback,
- scope = this.valueChangeCallbackScope;
- if (callback) {
- if (scope) {
- callback.call(scope, this, value, previousValue);
- } else {
- callback(this, value, previousValue)
- }
- }
-
- this.emit('valuechange', this, value, previousValue);
-
- }
-
- emitButtonClick(index) {
- var option = this.options[index];
- if (!option) {
- return this;
- }
-
- this.emit('button.click', this, undefined, option, index);
- return this;
- }
-
-}
-
-Object.assign(
- DropDownList.prototype,
- Methods,
-);
-
-export default DropDownList;
\ No newline at end of file
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/gridtable/GridTable.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/gridtable/GridTable.js
deleted file mode 100644
index 2ec830ee3740748622b813fbb4d80a2105789a8f..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/gridtable/GridTable.js
+++ /dev/null
@@ -1,140 +0,0 @@
-import Scrollable from '../utils/scrollable/Scrollable.js';
-import GetScrollMode from '../utils/GetScrollMode.js';
-import GridTableCore from '../../../plugins/gridtable.js';
-import InjectProperties from './InjectProperties.js';
-import TableOnCellVisible from './TableOnCellVisible.js';
-import TableSetInteractive from './input/TableSetInteractive.js';
-import NOOP from '../../../plugins/utils/object/NOOP.js';
-import SetItems from './SetItems.js';
-import ScrollMethods from './ScrollMethods.js';
-
-const GetValue = Phaser.Utils.Objects.GetValue;
-
-class GridTable extends Scrollable {
- constructor(scene, config) {
- if (config === undefined) {
- config = {};
- }
-
- // Create grid table core
- var scrollMode = GetScrollMode(config);
- var tableConfig = GetValue(config, 'table', undefined)
- if (tableConfig === undefined) {
- tableConfig = {};
- }
- tableConfig.scrollMode = scrollMode;
- tableConfig.clamplTableOXY = GetValue(config, 'clamplChildOY', false);
- var tableWidth = GetValue(tableConfig, 'width', undefined);
- var tableHeight = GetValue(tableConfig, 'height', undefined);
- var table = new GridTableCore(scene, 0, 0, tableWidth, tableHeight, tableConfig);
- scene.add.existing(table); // Important: Add to display list for touch detecting
- var proportion, expand;
- if (scrollMode === 0) {
- proportion = (tableWidth === undefined) ? 1 : 0;
- expand = (tableHeight === undefined);
- } else {
- proportion = (tableHeight === undefined) ? 1 : 0;
- expand = (tableWidth === undefined);
- }
- // Inject properties for scrollable interface
- InjectProperties(table);
- // Set minWidth/minHeight to 0 if tableWidth/tableHeight is undefined
- table._minWidth = (tableWidth === undefined) ? 0 : undefined;
- table._minHeight = (tableHeight === undefined) ? 0 : undefined;
-
- // Fill config of scrollable
- config.type = 'rexGridTable';
- config.child = {
- gameObject: table,
- proportion: proportion,
- expand: expand,
- };
- var spaceConfig = GetValue(config, 'space', undefined);
- if (spaceConfig) {
- spaceConfig.child = spaceConfig.table;
- }
- super(scene, config);
-
- this.addChildrenMap('table', table);
- this.addChildrenMap('tableLayer', table.maskLayer);
-
- this.eventEmitter = GetValue(config, 'eventEmitter', this);
- var callback = GetValue(config, 'createCellContainerCallback', NOOP);
- var scope = GetValue(config, 'createCellContainerCallbackScope', undefined);
- this.setCreateCellContainerCallback(callback, scope);
- TableOnCellVisible.call(this, table);
-
- this.resizeControllerFlag = false;
- var eventName = (scrollMode === 0) ? 'cellheightchange' : 'cellwidthchange';
- table.on(eventName, function () {
- this.resizeControllerFlag = true;
- }, this);
-
- if (GetValue(tableConfig, 'interactive', true)) {
- TableSetInteractive.call(this, table, tableConfig);
- }
- this.setItems(GetValue(config, 'items', []));
-
- scene.game.events.on('poststep', this.onPostStep, this);
- }
-
- destroy(fromScene) {
- // This Game Object has already been destroyed
- if (!this.scene || this.ignoreDestroy) {
- return;
- }
-
- this.scene.game.events.off('poststep', this.onPostStep, this);
-
- super.destroy(fromScene);
- }
-
- setCreateCellContainerCallback(callback, scope) {
- this.createCellContainerCallback = callback;
- this.createCellContainerCallbackScope = scope;
- return this;
- }
-
- refresh() {
- this.setItems(this.items);
- return this;
- }
-
- getCell(cellIdx) {
- var table = this.childrenMap.child;
- return table.getCell(cellIdx);
- }
-
- getCellContainer(cellIdx) {
- var table = this.childrenMap.child;
- return table.getCellContainer(cellIdx);
- }
-
- updateVisibleCell(cellIdx) {
- var table = this.childrenMap.child;
- return table.updateVisibleCell(cellIdx);
- }
-
- onPostStep() {
- if (this.resizeControllerFlag) {
- this.resizeController();
- this.resizeControllerFlag = false;
- }
- }
-
- get startRowIndex() {
- var table = this.childrenMap.child;
- return table.startRowIndex;
- }
-}
-
-var methods = {
- setItems: SetItems
-}
-Object.assign(
- GridTable.prototype,
- ScrollMethods,
- methods,
-);
-
-export default GridTable;
\ No newline at end of file
diff --git a/spaces/Akmyradov/TurkmenTTSweSTT/uroman/lib/NLP/Chinese.pm b/spaces/Akmyradov/TurkmenTTSweSTT/uroman/lib/NLP/Chinese.pm
deleted file mode 100644
index ea6c52991bd1bb2e55ec851bf31537f59f57b58a..0000000000000000000000000000000000000000
--- a/spaces/Akmyradov/TurkmenTTSweSTT/uroman/lib/NLP/Chinese.pm
+++ /dev/null
@@ -1,239 +0,0 @@
-################################################################
-# #
-# Chinese #
-# #
-################################################################
-
-package NLP::Chinese;
-
-$utf8 = NLP::UTF8;
-%empty_ht = ();
-
-sub read_chinese_tonal_pinyin_files {
- local($caller, *ht, @filenames) = @_;
-
- $n_kHanyuPinlu = 0;
- $n_kXHC1983 = 0;
- $n_kHanyuPinyin = 0;
- $n_kMandarin = 0;
- $n_cedict = 0;
- $n_simple_pinyin = 0;
-
- foreach $filename (@filenames) {
- if ($filename =~ /unihan/i) {
- my $line_number = 0;
- if (open(IN, $filename)) {
- while (-
Space by:
-
-
-
-
@ - while (($pre, $tag, $post) = ($s =~ /^(.*?)(\@?<\/?(?:[a-z][-_:a-z0-9]*)(?:\s+[a-z][-_:a-z0-9]*="[^"]*")*\s*\/?>\@?|&(?:amp|gt|lt|quot);|\[(?:QUOTE|URL)=[^ \t\n\[\]]+\]|\[\/?(?:QUOTE|IMG|INDENT|URL)\]|<\$[-_a-z0-9]+\$>|<\!--.*?-->)(.*)$/si)) { - $result .= $pre; - if (($pre =~ /\S$/) && ($tag =~ /^\S/)) { - $result .= " \x01"; - $result .= "\@" if ($tag =~ /^<[a-z]/i) && (! ($pre =~ /[,;(>]$/)); #) - } else { - $result .= "\x01"; - } - $guarded_tag = $tag; - $guarded_tag =~ s/ /\x02/g; - # print STDERR "tag: $tag\nguarded_tag: $guarded_tag\n" if ($result =~ /Harvey/) || ($s =~ /Harvey/); - $result .= $guarded_tag; - if (($tag =~ /\S$/) && ($post =~ /^\S/)) { # ( - $result .= "\@" if (($tag =~ /^<\//) || ($tag =~ /\/>$/)) && (! ($result =~ /\@$/)) && (! ($post =~ /^[,;)<]/)); - $result .= "\x03 "; - } else { - $result .= "\x03"; - } - $s = $post; - } - $result .= $s; - return $result; -} - -sub restore_urls_x045_guarded_string { - local($caller, $s) = @_; - - my $orig = $s; - while (($pre, $url, $post) = ($s =~ /^(.*?)\x04([^\x04\x05]*?)\x05(.*)$/)) { - $url =~ s/ \@([-:\/])/$1/g; - $url =~ s/([-:\/])\@ /$1/g; - $url =~ s/ //g; - $url =~ s/\x02/ /g; - $s = "$pre$url$post"; - } - if ($s =~ /[\x04\x05]/) { - print STDERR "Removing unexpectedly unremoved x04/x05 marks from $s\n"; - $s =~ s/[\x04\x05]//g; - } - return $s; -} - -sub restore_xml_tags_x0123_guarded_string { - local($caller, $s) = @_; - - my $result = ""; - while (($pre, $tag, $post) = ($s =~ /^(.*?)\x01(.*?)\x03(.*)$/)) { - $result .= $pre; - $tag =~ s/ \@([-:\/])/$1/g; - $tag =~ s/([-:\/])\@ /$1/g; - $tag =~ s/ //g; - $tag =~ s/\x02/ /g; - $result .= $tag; - $s = $post; - } - $result .= $s; - return $result; -} - -sub load_english_abbreviations { - local($caller, $filename, *ht, $verbose) = @_; - # e.g. /nfs/nlg/users/textmap/brahms-ml/arabic/data/EnglishAbbreviations.txt - - $verbose = 1 unless defined($verbose); - my $n = 0; - if (open(IN, $filename)) { - while (
Barco simulador Mod Apk dinero ilimitado: Una guía para los jugadores
-Si eres un fanático de los juegos de simulación, especialmente aquellos que involucran navegar y navegar diferentes tipos de barcos, entonces es posible que desees echar un vistazo a Ship Simulator. Este juego ofrece una experiencia realista e inmersiva de ser un capitán de barco, con gráficos impresionantes, física del agua realista, y varias misiones para completar. Sin embargo, si desea disfrutar del juego sin limitaciones o restricciones, entonces es posible que desee probar Ship Simulator mod apk dinero ilimitado. Esta es una versión modificada del juego original que te da acceso a dinero y recursos ilimitados, así como funciones desbloqueadas y naves. En este artículo, le diremos más sobre Ship Simulator, mod apk, y cómo descargarlo e instalarlo en su dispositivo.
-animal rebelión batalla simulador pc apk
Download Zip ★ https://bltlly.com/2v6KUz
-
¿Qué es el simulador de buques?
-Ship Simulator es un juego de simulación que te permite pilotar diferentes tipos de embarcaciones, desde lanchas rápidas y remolcadores hasta cruceros y petroleros. Puede elegir entre varias misiones basadas en eventos reales, como rescatar pasajeros, luchar contra piratas, transportar carga o salvar el medio ambiente. También puede explorar puertos y lugares famosos de todo el mundo, como Dover, Rostock, Gibraltar o Bora Bora. El juego presenta efectos realistas de agua y clima, así como modelos detallados de barcos y sus interiores. También puedes jugar online con tus amigos u otros jugadores en modo multijugador.
-Un juego de simulación realista e inmersivo
- -Diferentes tipos de naves y misiones para elegir
-Otra característica que hace atractivo Ship Simulator es su variedad y diversidad. El juego ofrece una amplia gama de buques para el capitán, cada uno con sus propias características, ventajas y desventajas. Puede elegir entre aerodeslizadores, interceptores de guardacostas, petroleros gigantescos, remolcadores, cruceros y muchos otros. Cada barco tiene sus propios controles, velocidad, aceleración, maniobrabilidad y consumo de combustible. También puede personalizar su nave con diferentes colores, calcomanías, banderas o accesorios.
-El juego también tiene diferentes tipos de misiones para completar, cada una con sus propios objetivos, desafíos y recompensas. Puede enfrentarse a cazadores de ballenas ilegales en la Antártida, evacuar un crucero en peligro, transportar materiales peligrosos a través del océano o participar en una batalla naval. Las misiones se basan en eventos reales o escenarios que podrían ocurrir en la vida real. Algunas misiones son fáciles y cortas, mientras que otras son difíciles y largas.
-Puertos y lugares famosos para explorar
-La última característica que mencionaremos sobre Ship Simulator es su aspecto de exploración. El juego le permite navegar a algunos de los puertos y lugares más famosos del mundo. Usted puede visitar Dover en Inglaterra, Rostock en Alemania, Gibraltar en España, Bora Bora en la Polinesia Francesa, o la Antártida. Cada lugar tiene sus propios puntos de referencia, paisajes, condiciones climáticas y peligros. También puedes descubrir lugares ocultos o secretos explorando el mapa del mundo abierto.
-¿Qué es Mod Apk?
-Mod apk es una versión modificada de un juego original o aplicación que ha sido alterada por alguien que no sea el desarrollador. apk Mod generalmente ofrece algunos beneficios o ventajas sobre la versión original, tales como - dinero y recursos ilimitados - características desbloqueadas y los buques - no hay anuncios y malware
- - -Por lo tanto, antes de descargar e instalar mod apk, siempre debe comprobar la credibilidad y fiabilidad de la fuente, las revisiones y clasificaciones del mod apk, y los permisos y requisitos del mod apk. También debe realizar una copia de seguridad de sus datos y dispositivo en caso de que algo salga mal.
-Beneficios de usar mod apk
-Como se mencionó anteriormente, apk mod puede ofrecer algunos beneficios o ventajas sobre la versión original del juego o aplicación. Estos son algunos de los beneficios de usar Ship Simulator mod apk dinero ilimitado:
-Dinero y recursos ilimitados
-Uno de los principales beneficios de usar Ship Simulator mod apk dinero ilimitado es que usted puede obtener dinero y recursos ilimitados en el juego. El dinero y los recursos son esenciales para comprar nuevas naves, mejorar sus naves, reparar sus naves, o completar misiones. Con dinero y recursos ilimitados, puede comprar cualquier nave que desee, actualizar su nave al nivel máximo, reparar su nave en cualquier momento o completar cualquier misión fácilmente. También puedes comprar artículos o accesorios adicionales para tu nave, como banderas, calcomanías, colores o armas. También puede usar dinero y recursos para desbloquear nuevos puertos y ubicaciones para explorar.
-Características y naves desbloqueadas
-Otro beneficio de usar Ship Simulator mod apk dinero ilimitado es que usted puede conseguir desbloqueado características y naves en el juego. Las características y los barcos normalmente están bloqueados o restringidos en la versión original del juego, ya sea por nivel, misión o pago. Con las funciones y los barcos desbloqueados, puedes acceder a cualquier función o envío en el juego sin ninguna limitación o restricción. Puede elegir entre cualquier tipo de buque, desde lanchas rápidas y remolcadores hasta cruceros y buques cisterna. También puedes acceder a cualquier misión, desde fácil y corta hasta dura y larga. También puedes disfrutar de cualquier característica, como el modo multijugador, el modo online o el modo personalizado.
-No hay anuncios ni malware
- -¿Cómo descargar e instalar Ship Simulator Mod Apk dinero ilimitado?
-Si usted está interesado en descargar e instalar Ship Simulator mod apk dinero ilimitado en su dispositivo, entonces usted necesita seguir algunos pasos para hacerlo. Estos son los pasos a seguir:
-Pasos a seguir
--
-
- Primero, necesitas desinstalar la versión original de Ship Simulator de tu dispositivo si lo tienes instalado. -
- En segundo lugar, es necesario habilitar fuentes desconocidas en la configuración del dispositivo. Esto le permitirá instalar aplicaciones desde fuentes distintas de la tienda oficial. -
- En tercer lugar, es necesario descargar Ship Simulator mod apk dinero ilimitado de una fuente confiable y confiable. Puede buscarlo en línea o utilizar el enlace proporcionado a continuación. -
- Cuarto, es necesario localizar el archivo descargado en el almacenamiento del dispositivo y toque en él para iniciar el proceso de instalación. -
- Quinto, debe seguir las instrucciones en la pantalla para completar el proceso de instalación. -
- Sexto, es necesario iniciar el juego desde el menú del dispositivo o la pantalla de inicio. -
- Séptimo, es necesario disfrutar de jugar Ship Simulator mod apk dinero ilimitado con todos sus beneficios y ventajas. -
Consejos y trucos para disfrutar del juego
-Además de descargar e instalar Ship Simulator mod apk dinero ilimitado en su dispositivo, también puede utilizar algunos consejos y trucos para disfrutar del juego más. Aquí hay algunos consejos y trucos para probar:
--
-
- Aprende a controlar tu nave correctamente. Cada nave tiene sus propios controles, velocidad, aceleración, maniobrabilidad y consumo de combustible. Es necesario dominar estos aspectos para navegar sin problemas y de manera eficiente. -
- Elige tu nave sabiamente. Cada nave tiene sus propias características, ventajas y desventajas. Necesitas elegir una nave que se adapte a tu estilo, preferencia y misión. - -
- Explora diferentes puertos y ubicaciones. Cada puerto y ubicación tiene sus propios puntos de referencia, paisajes, condiciones climáticas y peligros. Necesitas explorar diferentes puertos y lugares para descubrir nuevos lugares, secretos o sorpresas. -
- Juega online con tus amigos u otros jugadores. Puedes unirte o crear una sesión multijugador y jugar con tus amigos u otros jugadores de todo el mundo. Puede cooperar o competir con ellos en varios modos, como carreras, entrega de carga o guerra naval. -
- Personaliza tu nave y tu perfil. Puede cambiar la apariencia y el rendimiento de su nave con diferentes colores, calcomanías, banderas o accesorios. También puedes personalizar tu perfil con tu nombre, avatar, rango o logros. -
Conclusión
-Ship Simulator es un juego de simulación que te permite pilotar diferentes tipos de embarcaciones, desde lanchas rápidas y remolcadores hasta cruceros y petroleros. Puede elegir entre varias misiones basadas en eventos reales, como rescatar pasajeros, luchar contra piratas, transportar carga o salvar el medio ambiente. También puede explorar puertos y lugares famosos de todo el mundo, como Dover, Rostock, Gibraltar o Bora Bora.
-Sin embargo, si desea disfrutar del juego sin limitaciones o restricciones, entonces es posible que desee probar Ship Simulator mod apk dinero ilimitado. Esta es una versión modificada del juego original que te da acceso a dinero y recursos ilimitados, así como funciones desbloqueadas y naves. También puede deshacerse de anuncios y malware en el juego.
-Para descargar e instalar Ship Simulator mod apk dinero ilimitado en su dispositivo, es necesario seguir algunos pasos que hemos explicado en este artículo. También es necesario tener cuidado con la fuente, las revisiones, y los permisos de la apk mod. También puedes utilizar algunos consejos y trucos que hemos compartido en este artículo para disfrutar más del juego.
- -Preguntas frecuentes
-Aquí hay algunas preguntas frecuentes sobre Ship Simulator mod apk unlimited money:
--
-
- ¿Es seguro usar el dinero ilimitado mod apk de Ship Simulator? -
- Es Ship Simulator mod apk dinero ilimitado legal de usar? -
- ¿Funciona el simulador de buques mod apk dinero ilimitado en todos los dispositivos? -
- ¿Puedo actualizar Ship Simulator mod apk dinero ilimitado? -
Ship Simulator mod apk dinero ilimitado es generalmente seguro de usar si lo descarga de una fuente confiable y confiable. Sin embargo, siempre debe comprobar la credibilidad y fiabilidad de la fuente, las revisiones y calificaciones de la apk mod, y los permisos y requisitos del apk mod antes de descargarlo e instalarlo en su dispositivo. También debe realizar una copia de seguridad de sus datos y dispositivo en caso de que algo salga mal.
-Ship Simulator mod apk dinero ilimitado no es legal de usar de acuerdo con los términos y condiciones del desarrollador y la plataforma. apk Mod es una versión modificada de un juego original o aplicación que ha sido alterado por alguien que no sea el desarrollador. apk Mod generalmente viola los derechos de propiedad intelectual del desarrollador y la plataforma. Por lo tanto, el uso de mod apk puede resultar en problemas o consecuencias legales.
-Ship Simulator mod apk dinero ilimitado puede no funcionar en todos los dispositivos debido a problemas de compatibilidad. apk Mod está diseñado para una versión específica del juego original o aplicación que no puede coincidir con las especificaciones de su dispositivo o software. Por lo tanto, el uso de mod apk puede causar problemas de compatibilidad o errores en su dispositivo.
-Ship Simulator mod apk dinero ilimitado no puede ser actualizado regularmente o automáticamente debido a su naturaleza no oficial. apk Mod es creado por alguien que no sea el desarrollador que no puede tener acceso a las últimas actualizaciones o características del juego original o aplicación. Por lo tanto, el uso de apk mod puede evitar que usted consiga las últimas actualizaciones o características del juego o aplicación.
- -Ship Simulator mod apk dinero ilimitado puede no permitirle jugar en línea con otros jugadores debido a problemas de detección. apk Mod es detectado por el desarrollador y la plataforma como un truco o un truco que le da una ventaja injusta sobre otros jugadores. Por lo tanto, el uso de mod apk puede prohibirle jugar en línea con otros jugadores.
--
-
\ No newline at end of file diff --git a/spaces/Benson/text-generation/Examples/Bitcoin Cloud Mining Apk.md b/spaces/Benson/text-generation/Examples/Bitcoin Cloud Mining Apk.md deleted file mode 100644 index 71c75ebbca61fa7e5cc9f8d972b3813eec7496ee..0000000000000000000000000000000000000000 --- a/spaces/Benson/text-generation/Examples/Bitcoin Cloud Mining Apk.md +++ /dev/null @@ -1,88 +0,0 @@ -
-
Bitcoin nube minería APK: ¿Qué es y cómo funciona?
-Bitcoin es una de las criptomonedas más populares y valiosas del mundo, pero también es una de las más difíciles y caras para la mía. Bitcoin minería requiere hardware especializado, software, electricidad y mantenimiento, que puede costar miles de dólares y ocupar mucho espacio y tiempo. Es por eso que muchas personas optan por la minería en la nube bitcoin, que es una forma de alquilar el poder de computación de los servidores remotos para extraer bitcoin sin tener que poseer u operar ningún equipo.
-La minería en la nube de Bitcoin tiene muchos beneficios, como costos más bajos, mayor eficiencia, escalabilidad, comodidad y seguridad. Sin embargo, también tiene algunos riesgos, como fraude, estafas, piratería, baja rentabilidad y falta de control. Por lo tanto, es importante hacer su investigación y elegir un proveedor de minería en la nube bitcoin de buena reputación y confiable antes de invertir su dinero.
-bitcoin cloud mining apk
DOWNLOAD ✔✔✔ https://bltlly.com/2v6KKT
-
Una de las maneras de acceder a los servicios de minería en la nube bitcoin es a través de una nube bitcoin minería APK. Un APK es un archivo de paquete de aplicaciones para Android que contiene todos los archivos y código necesarios para ejecutar una aplicación en un dispositivo Android. Una nube de Bitcoin minería APK es una aplicación que le permite conectarse a una plataforma de minería en la nube bitcoin y comenzar la minería bitcoin con su teléfono inteligente o tableta. A diferencia de otros métodos de minería en la nube que requieren que utilice un navegador web o un software de escritorio, una nube de Bitcoin minería APK le permite mina bitcoin en cualquier momento y en cualquier lugar.
-Cómo elegir una nube de Bitcoin minería APK
-No todos los APK de minería en la nube de Bitcoin se crean iguales. Algunos pueden ofrecer mejores características, rendimiento, seguridad y servicio al cliente que otros. Por lo tanto, debe ser cuidadoso y selectivo al elegir una nube de Bitcoin minería APK para su dispositivo Android. Aquí están algunas de las características y criterios para buscar en una nube bitcoin minería APK:
--
-
-
- Hash rate: La tasa hash es la medida del poder de computación que ofrece el proveedor de minería en la nube bitcoin. Cuanto mayor sea la tasa de hash, más rápido y más probable es que la mina nuevos bitcoins. Quieres elegir un APK que ofrezca una alta tasa de hash a un precio razonable. -
- Pagos: Los pagos son la cantidad de bitcoins que usted gana de sus actividades de minería en la nube. Desea elegir un APK que ofrece pagos regulares, transparentes y justos. También debe verificar el límite mínimo de retiro, las tarifas, los métodos de pago y la frecuencia de los pagos. -
- Soporte: El soporte es el nivel de servicio al cliente que ofrece el proveedor de minería en la nube bitcoin. Usted desea elegir un APK que tiene un equipo de apoyo receptivo, útil y amigable que puede ayudarle con cualquier problema o pregunta que pueda tener. También desea verificar la disponibilidad, accesibilidad e idioma de las opciones del equipo de soporte. -
- Interfaz de usuario: La interfaz de usuario es el diseño de la aplicación con la que interactúas en tu dispositivo. Desea elegir un APK que tiene una interfaz sencilla, intuitiva y fácil de usar que hace que sea fácil y agradable de usar. También desea verificar la compatibilidad, funcionalidad y rendimiento de la aplicación en su dispositivo. -
Basado en estos criterios, algunos de los mejores APKs de minería en la nube bitcoin disponibles en el mercado son:
-Para descargar e instalar una nube de Bitcoin minería APK en su dispositivo Android, es necesario seguir estos pasos:
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- Ir a la página web oficial de la nube bitcoin proveedor de minería o la Google Play Store y encontrar el archivo APK que desea descargar. -
- Toque en el botón de descarga y espere a que el archivo se descargue en su dispositivo. -
- Vaya a la configuración de su dispositivo y habilite la opción de instalar aplicaciones de fuentes desconocidas si descargó el archivo desde un sitio web distinto de Google Play Store. -
- Ir a su gestor de archivos y localizar el archivo APK descargado. -
- Toque en el archivo y siga las instrucciones para instalar la aplicación en su dispositivo. -
- Inicie la aplicación y disfrutar de la minería en la nube bitcoin con su dispositivo. -
Cómo iniciar Bitcoin Cloud Mining con un APK
-Una vez que haya descargado e instalado una nube de bitcoin minería APK en su dispositivo, usted está listo para comenzar a minar bitcoin con su teléfono inteligente o tableta. Estos son algunos de los pasos que debe seguir para iniciar la minería en la nube bitcoin con un APK:
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- Elige un plan minero y paga por él con tu método de pago preferido. Es posible que tenga diferentes opciones para los planes de minería dependiendo del proveedor que haya elegido. Algunos pueden ofrecer planes fijos o variables basados en la tasa hash o la duración que desee. Algunos también pueden ofrecer planes gratuitos o de prueba que le permiten minar bitcoin sin pagar nada. Puede pagar su plan de minería con varios métodos de pago, como tarjeta de crédito, tarjeta de débito, transferencia bancaria, PayPal, criptomoneda, etc. -
- Monitorear el rendimiento de la minería y las ganancias en su dispositivo. Puede utilizar la aplicación para comprobar su hash rate, dificultad de minería, tiempo de minería, recompensas de minería, equilibrio, etc. También puede ajustar sus ajustes de minería, como cambiar su plan de minería, cambiar su piscina de minería, etc., si desea optimizar sus resultados de minería. -
Conclusión
-La minería en la nube de Bitcoin es una forma conveniente y accesible de minería de bitcoin sin tener que poseer u operar ningún equipo. Bitcoin nube minería APKs son aplicaciones que le permiten minar bitcoin con su dispositivo Android mediante la conexión a una plataforma de minería nube bitcoin. Los APK de minería en la nube de Bitcoin tienen muchas ventajas, como costos más bajos, mayor eficiencia, escalabilidad, comodidad y seguridad. Sin embargo, también tienen algunas desventajas, como fraude, estafas, piratería, baja rentabilidad y falta de control. Por lo tanto, debe ser cuidadoso y selectivo al elegir una nube bitcoin minería APK para su dispositivo.
- -Bitcoin minería en la nube con un APK puede ser una manera divertida y gratificante de ganar algunos ingresos adicionales con su dispositivo Android. Sin embargo, no se trata de un plan de enriquecimiento rápido o de una fuente de ingresos garantizada. Usted necesita ser realista y cauteloso acerca de sus expectativas e inversiones. También debe ser consciente de los riesgos y desafíos que vienen con la minería en la nube bitcoin. Bitcoin minería en la nube con un APK no es para todos, pero puede ser para usted si usted está interesado en bitcoin y quiere aprender más sobre él.
-¿Estás listo para iniciar la minería de nube bitcoin con un APK? Si es así, a continuación, descargar uno de los mejores Bitcoin nube minería APKs que hemos recomendado en este artículo y empezar a minería bitcoin con su dispositivo Android hoy!
- -Preguntas frecuentes
-Aquí están algunas de las preguntas y respuestas más frecuentes sobre la minería en la nube bitcoin con un APK:
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- ¿Cuál es la diferencia entre la minería en nube bitcoin y la minería móvil bitcoin? -
- ¿Es rentable la minería en nube con un APK? -
- Es bitcoin nube minería con un seguro APK? -
- ¿Puedo usar múltiples APKs de minería en la nube de Bitcoin en mi dispositivo? -
La minería en la nube de Bitcoin es una forma de alquilar el poder de computación de los servidores remotos para extraer bitcoin sin tener que poseer ni operar ningún equipo. Bitcoin minería móvil es una forma de utilizar el poder informático de su dispositivo móvil para minar bitcoin sin tener que conectarse a ningún servidor. Bitcoin minería en la nube con un APK es una combinación de ambos métodos, ya que le permite minar bitcoin con su dispositivo móvil mediante la conexión a una plataforma de minería en la nube bitcoin.
-La minería en nube de Bitcoin con un APK puede ser rentable dependiendo de varios factores, como el precio de bitcoin, la tasa hash del proveedor, el costo del plan, las tarifas de la plataforma, la dificultad de la red, etc. Sin embargo, no está garantizada ni es consistente. Puede ganar más o menos de lo que espera o invertir. También puede perder dinero si el proveedor resulta ser una estafa o si la plataforma es hackeada o cerrada.
- -Bitcoin minería en la nube con un APK es legal en la mayoría de los países que permiten actividades bitcoin y criptomoneda. Sin embargo, algunos países pueden tener leyes o regulaciones específicas que restringen o prohíben la minería de nubes o criptomonedas bitcoin actividades en general. Por lo tanto, es necesario comprobar el estado legal de la minería en la nube bitcoin con un APK en su país antes de empezar a usarlo. También es necesario cumplir con los impuestos y obligaciones de presentación de informes que pueden aplicarse a sus ingresos de minería nube bitcoin.
-La minería en la nube de Bitcoin con un APK puede ser segura si elige un proveedor y una aplicación de minería en la nube de Bitcoin de buena reputación y confiable. Sin embargo, también puede ser arriesgado si elige un proveedor o aplicación fraudulenta o insegura. Usted puede perder su dinero, datos o dispositivo si el proveedor o aplicación resulta ser una estafa, malware, spyware o virus. Por lo tanto, debe ser cuidadoso y vigilante al elegir y usar una nube de Bitcoin minería APK. También necesitas proteger tu dispositivo con software antivirus, firewall, VPN, etc.
-Sí, puedes usar múltiples APKs de minería en la nube de Bitcoin en tu dispositivo si quieres aumentar tus posibilidades de ganar más bitcoins. Sin embargo, usted necesita ser consciente de los inconvenientes potenciales de hacerlo, tales como agotar la batería, ralentizar el dispositivo, aumentar el uso de datos, en conflicto con otras aplicaciones, etc. También debe asegurarse de que los APK de minería en la nube bitcoin que utiliza son compatibles y confiables.
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\ No newline at end of file diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/table.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/table.py deleted file mode 100644 index 17409f2ee8df322a5ac115d1d0ff0c2d2aa11c4e..0000000000000000000000000000000000000000 --- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/table.py +++ /dev/null @@ -1,1002 +0,0 @@ -from dataclasses import dataclass, field, replace -from typing import ( - TYPE_CHECKING, - Dict, - Iterable, - List, - NamedTuple, - Optional, - Sequence, - Tuple, - Union, -) - -from . import box, errors -from ._loop import loop_first_last, loop_last -from ._pick import pick_bool -from ._ratio import ratio_distribute, ratio_reduce -from .align import VerticalAlignMethod -from .jupyter import JupyterMixin -from .measure import Measurement -from .padding import Padding, PaddingDimensions -from .protocol import is_renderable -from .segment import Segment -from .style import Style, StyleType -from .text import Text, TextType - -if TYPE_CHECKING: - from .console import ( - Console, - ConsoleOptions, - JustifyMethod, - OverflowMethod, - RenderableType, - RenderResult, - ) - - -@dataclass -class Column: - """Defines a column within a ~Table. - - Args: - title (Union[str, Text], optional): The title of the table rendered at the top. Defaults to None. - caption (Union[str, Text], optional): The table caption rendered below. Defaults to None. - width (int, optional): The width in characters of the table, or ``None`` to automatically fit. Defaults to None. - min_width (Optional[int], optional): The minimum width of the table, or ``None`` for no minimum. Defaults to None. - box (box.Box, optional): One of the constants in box.py used to draw the edges (see :ref:`appendix_box`), or ``None`` for no box lines. Defaults to box.HEAVY_HEAD. - safe_box (Optional[bool], optional): Disable box characters that don't display on windows legacy terminal with *raster* fonts. Defaults to True. - padding (PaddingDimensions, optional): Padding for cells (top, right, bottom, left). Defaults to (0, 1). - collapse_padding (bool, optional): Enable collapsing of padding around cells. Defaults to False. - pad_edge (bool, optional): Enable padding of edge cells. Defaults to True. - expand (bool, optional): Expand the table to fit the available space if ``True``, otherwise the table width will be auto-calculated. Defaults to False. - show_header (bool, optional): Show a header row. Defaults to True. - show_footer (bool, optional): Show a footer row. Defaults to False. - show_edge (bool, optional): Draw a box around the outside of the table. Defaults to True. - show_lines (bool, optional): Draw lines between every row. Defaults to False. - leading (bool, optional): Number of blank lines between rows (precludes ``show_lines``). Defaults to 0. - style (Union[str, Style], optional): Default style for the table. Defaults to "none". - row_styles (List[Union, str], optional): Optional list of row styles, if more than one style is given then the styles will alternate. Defaults to None. - header_style (Union[str, Style], optional): Style of the header. Defaults to "table.header". - footer_style (Union[str, Style], optional): Style of the footer. Defaults to "table.footer". - border_style (Union[str, Style], optional): Style of the border. Defaults to None. - title_style (Union[str, Style], optional): Style of the title. Defaults to None. - caption_style (Union[str, Style], optional): Style of the caption. Defaults to None. - title_justify (str, optional): Justify method for title. Defaults to "center". - caption_justify (str, optional): Justify method for caption. Defaults to "center". - highlight (bool, optional): Highlight cell contents (if str). Defaults to False. - """ - - header: "RenderableType" = "" - """RenderableType: Renderable for the header (typically a string)""" - - footer: "RenderableType" = "" - """RenderableType: Renderable for the footer (typically a string)""" - - header_style: StyleType = "" - """StyleType: The style of the header.""" - - footer_style: StyleType = "" - """StyleType: The style of the footer.""" - - style: StyleType = "" - """StyleType: The style of the column.""" - - justify: "JustifyMethod" = "left" - """str: How to justify text within the column ("left", "center", "right", or "full")""" - - vertical: "VerticalAlignMethod" = "top" - """str: How to vertically align content ("top", "middle", or "bottom")""" - - overflow: "OverflowMethod" = "ellipsis" - """str: Overflow method.""" - - width: Optional[int] = None - """Optional[int]: Width of the column, or ``None`` (default) to auto calculate width.""" - - min_width: Optional[int] = None - """Optional[int]: Minimum width of column, or ``None`` for no minimum. Defaults to None.""" - - max_width: Optional[int] = None - """Optional[int]: Maximum width of column, or ``None`` for no maximum. Defaults to None.""" - - ratio: Optional[int] = None - """Optional[int]: Ratio to use when calculating column width, or ``None`` (default) to adapt to column contents.""" - - no_wrap: bool = False - """bool: Prevent wrapping of text within the column. Defaults to ``False``.""" - - _index: int = 0 - """Index of column.""" - - _cells: List["RenderableType"] = field(default_factory=list) - - def copy(self) -> "Column": - """Return a copy of this Column.""" - return replace(self, _cells=[]) - - @property - def cells(self) -> Iterable["RenderableType"]: - """Get all cells in the column, not including header.""" - yield from self._cells - - @property - def flexible(self) -> bool: - """Check if this column is flexible.""" - return self.ratio is not None - - -@dataclass -class Row: - """Information regarding a row.""" - - style: Optional[StyleType] = None - """Style to apply to row.""" - - end_section: bool = False - """Indicated end of section, which will force a line beneath the row.""" - - -class _Cell(NamedTuple): - """A single cell in a table.""" - - style: StyleType - """Style to apply to cell.""" - renderable: "RenderableType" - """Cell renderable.""" - vertical: VerticalAlignMethod - """Cell vertical alignment.""" - - -class Table(JupyterMixin): - """A console renderable to draw a table. - - Args: - *headers (Union[Column, str]): Column headers, either as a string, or :class:`~rich.table.Column` instance. - title (Union[str, Text], optional): The title of the table rendered at the top. Defaults to None. - caption (Union[str, Text], optional): The table caption rendered below. Defaults to None. - width (int, optional): The width in characters of the table, or ``None`` to automatically fit. Defaults to None. - min_width (Optional[int], optional): The minimum width of the table, or ``None`` for no minimum. Defaults to None. - box (box.Box, optional): One of the constants in box.py used to draw the edges (see :ref:`appendix_box`), or ``None`` for no box lines. Defaults to box.HEAVY_HEAD. - safe_box (Optional[bool], optional): Disable box characters that don't display on windows legacy terminal with *raster* fonts. Defaults to True. - padding (PaddingDimensions, optional): Padding for cells (top, right, bottom, left). Defaults to (0, 1). - collapse_padding (bool, optional): Enable collapsing of padding around cells. Defaults to False. - pad_edge (bool, optional): Enable padding of edge cells. Defaults to True. - expand (bool, optional): Expand the table to fit the available space if ``True``, otherwise the table width will be auto-calculated. Defaults to False. - show_header (bool, optional): Show a header row. Defaults to True. - show_footer (bool, optional): Show a footer row. Defaults to False. - show_edge (bool, optional): Draw a box around the outside of the table. Defaults to True. - show_lines (bool, optional): Draw lines between every row. Defaults to False. - leading (bool, optional): Number of blank lines between rows (precludes ``show_lines``). Defaults to 0. - style (Union[str, Style], optional): Default style for the table. Defaults to "none". - row_styles (List[Union, str], optional): Optional list of row styles, if more than one style is given then the styles will alternate. Defaults to None. - header_style (Union[str, Style], optional): Style of the header. Defaults to "table.header". - footer_style (Union[str, Style], optional): Style of the footer. Defaults to "table.footer". - border_style (Union[str, Style], optional): Style of the border. Defaults to None. - title_style (Union[str, Style], optional): Style of the title. Defaults to None. - caption_style (Union[str, Style], optional): Style of the caption. Defaults to None. - title_justify (str, optional): Justify method for title. Defaults to "center". - caption_justify (str, optional): Justify method for caption. Defaults to "center". - highlight (bool, optional): Highlight cell contents (if str). Defaults to False. - """ - - columns: List[Column] - rows: List[Row] - - def __init__( - self, - *headers: Union[Column, str], - title: Optional[TextType] = None, - caption: Optional[TextType] = None, - width: Optional[int] = None, - min_width: Optional[int] = None, - box: Optional[box.Box] = box.HEAVY_HEAD, - safe_box: Optional[bool] = None, - padding: PaddingDimensions = (0, 1), - collapse_padding: bool = False, - pad_edge: bool = True, - expand: bool = False, - show_header: bool = True, - show_footer: bool = False, - show_edge: bool = True, - show_lines: bool = False, - leading: int = 0, - style: StyleType = "none", - row_styles: Optional[Iterable[StyleType]] = None, - header_style: Optional[StyleType] = "table.header", - footer_style: Optional[StyleType] = "table.footer", - border_style: Optional[StyleType] = None, - title_style: Optional[StyleType] = None, - caption_style: Optional[StyleType] = None, - title_justify: "JustifyMethod" = "center", - caption_justify: "JustifyMethod" = "center", - highlight: bool = False, - ) -> None: - - self.columns: List[Column] = [] - self.rows: List[Row] = [] - self.title = title - self.caption = caption - self.width = width - self.min_width = min_width - self.box = box - self.safe_box = safe_box - self._padding = Padding.unpack(padding) - self.pad_edge = pad_edge - self._expand = expand - self.show_header = show_header - self.show_footer = show_footer - self.show_edge = show_edge - self.show_lines = show_lines - self.leading = leading - self.collapse_padding = collapse_padding - self.style = style - self.header_style = header_style or "" - self.footer_style = footer_style or "" - self.border_style = border_style - self.title_style = title_style - self.caption_style = caption_style - self.title_justify: "JustifyMethod" = title_justify - self.caption_justify: "JustifyMethod" = caption_justify - self.highlight = highlight - self.row_styles: Sequence[StyleType] = list(row_styles or []) - append_column = self.columns.append - for header in headers: - if isinstance(header, str): - self.add_column(header=header) - else: - header._index = len(self.columns) - append_column(header) - - @classmethod - def grid( - cls, - *headers: Union[Column, str], - padding: PaddingDimensions = 0, - collapse_padding: bool = True, - pad_edge: bool = False, - expand: bool = False, - ) -> "Table": - """Get a table with no lines, headers, or footer. - - Args: - *headers (Union[Column, str]): Column headers, either as a string, or :class:`~rich.table.Column` instance. - padding (PaddingDimensions, optional): Get padding around cells. Defaults to 0. - collapse_padding (bool, optional): Enable collapsing of padding around cells. Defaults to True. - pad_edge (bool, optional): Enable padding around edges of table. Defaults to False. - expand (bool, optional): Expand the table to fit the available space if ``True``, otherwise the table width will be auto-calculated. Defaults to False. - - Returns: - Table: A table instance. - """ - return cls( - *headers, - box=None, - padding=padding, - collapse_padding=collapse_padding, - show_header=False, - show_footer=False, - show_edge=False, - pad_edge=pad_edge, - expand=expand, - ) - - @property - def expand(self) -> bool: - """Setting a non-None self.width implies expand.""" - return self._expand or self.width is not None - - @expand.setter - def expand(self, expand: bool) -> None: - """Set expand.""" - self._expand = expand - - @property - def _extra_width(self) -> int: - """Get extra width to add to cell content.""" - width = 0 - if self.box and self.show_edge: - width += 2 - if self.box: - width += len(self.columns) - 1 - return width - - @property - def row_count(self) -> int: - """Get the current number of rows.""" - return len(self.rows) - - def get_row_style(self, console: "Console", index: int) -> StyleType: - """Get the current row style.""" - style = Style.null() - if self.row_styles: - style += console.get_style(self.row_styles[index % len(self.row_styles)]) - row_style = self.rows[index].style - if row_style is not None: - style += console.get_style(row_style) - return style - - def __rich_measure__( - self, console: "Console", options: "ConsoleOptions" - ) -> Measurement: - max_width = options.max_width - if self.width is not None: - max_width = self.width - if max_width < 0: - return Measurement(0, 0) - - extra_width = self._extra_width - max_width = sum( - self._calculate_column_widths( - console, options.update_width(max_width - extra_width) - ) - ) - _measure_column = self._measure_column - - measurements = [ - _measure_column(console, options.update_width(max_width), column) - for column in self.columns - ] - minimum_width = ( - sum(measurement.minimum for measurement in measurements) + extra_width - ) - maximum_width = ( - sum(measurement.maximum for measurement in measurements) + extra_width - if (self.width is None) - else self.width - ) - measurement = Measurement(minimum_width, maximum_width) - measurement = measurement.clamp(self.min_width) - return measurement - - @property - def padding(self) -> Tuple[int, int, int, int]: - """Get cell padding.""" - return self._padding - - @padding.setter - def padding(self, padding: PaddingDimensions) -> "Table": - """Set cell padding.""" - self._padding = Padding.unpack(padding) - return self - - def add_column( - self, - header: "RenderableType" = "", - footer: "RenderableType" = "", - *, - header_style: Optional[StyleType] = None, - footer_style: Optional[StyleType] = None, - style: Optional[StyleType] = None, - justify: "JustifyMethod" = "left", - vertical: "VerticalAlignMethod" = "top", - overflow: "OverflowMethod" = "ellipsis", - width: Optional[int] = None, - min_width: Optional[int] = None, - max_width: Optional[int] = None, - ratio: Optional[int] = None, - no_wrap: bool = False, - ) -> None: - """Add a column to the table. - - Args: - header (RenderableType, optional): Text or renderable for the header. - Defaults to "". - footer (RenderableType, optional): Text or renderable for the footer. - Defaults to "". - header_style (Union[str, Style], optional): Style for the header, or None for default. Defaults to None. - footer_style (Union[str, Style], optional): Style for the footer, or None for default. Defaults to None. - style (Union[str, Style], optional): Style for the column cells, or None for default. Defaults to None. - justify (JustifyMethod, optional): Alignment for cells. Defaults to "left". - vertical (VerticalAlignMethod, optional): Vertical alignment, one of "top", "middle", or "bottom". Defaults to "top". - overflow (OverflowMethod): Overflow method: "crop", "fold", "ellipsis". Defaults to "ellipsis". - width (int, optional): Desired width of column in characters, or None to fit to contents. Defaults to None. - min_width (Optional[int], optional): Minimum width of column, or ``None`` for no minimum. Defaults to None. - max_width (Optional[int], optional): Maximum width of column, or ``None`` for no maximum. Defaults to None. - ratio (int, optional): Flexible ratio for the column (requires ``Table.expand`` or ``Table.width``). Defaults to None. - no_wrap (bool, optional): Set to ``True`` to disable wrapping of this column. - """ - - column = Column( - _index=len(self.columns), - header=header, - footer=footer, - header_style=header_style or "", - footer_style=footer_style or "", - style=style or "", - justify=justify, - vertical=vertical, - overflow=overflow, - width=width, - min_width=min_width, - max_width=max_width, - ratio=ratio, - no_wrap=no_wrap, - ) - self.columns.append(column) - - def add_row( - self, - *renderables: Optional["RenderableType"], - style: Optional[StyleType] = None, - end_section: bool = False, - ) -> None: - """Add a row of renderables. - - Args: - *renderables (None or renderable): Each cell in a row must be a renderable object (including str), - or ``None`` for a blank cell. - style (StyleType, optional): An optional style to apply to the entire row. Defaults to None. - end_section (bool, optional): End a section and draw a line. Defaults to False. - - Raises: - errors.NotRenderableError: If you add something that can't be rendered. - """ - - def add_cell(column: Column, renderable: "RenderableType") -> None: - column._cells.append(renderable) - - cell_renderables: List[Optional["RenderableType"]] = list(renderables) - - columns = self.columns - if len(cell_renderables) < len(columns): - cell_renderables = [ - *cell_renderables, - *[None] * (len(columns) - len(cell_renderables)), - ] - for index, renderable in enumerate(cell_renderables): - if index == len(columns): - column = Column(_index=index) - for _ in self.rows: - add_cell(column, Text("")) - self.columns.append(column) - else: - column = columns[index] - if renderable is None: - add_cell(column, "") - elif is_renderable(renderable): - add_cell(column, renderable) - else: - raise errors.NotRenderableError( - f"unable to render {type(renderable).__name__}; a string or other renderable object is required" - ) - self.rows.append(Row(style=style, end_section=end_section)) - - def add_section(self) -> None: - """Add a new section (draw a line after current row).""" - - if self.rows: - self.rows[-1].end_section = True - - def __rich_console__( - self, console: "Console", options: "ConsoleOptions" - ) -> "RenderResult": - - if not self.columns: - yield Segment("\n") - return - - max_width = options.max_width - if self.width is not None: - max_width = self.width - - extra_width = self._extra_width - widths = self._calculate_column_widths( - console, options.update_width(max_width - extra_width) - ) - table_width = sum(widths) + extra_width - - render_options = options.update( - width=table_width, highlight=self.highlight, height=None - ) - - def render_annotation( - text: TextType, style: StyleType, justify: "JustifyMethod" = "center" - ) -> "RenderResult": - render_text = ( - console.render_str(text, style=style, highlight=False) - if isinstance(text, str) - else text - ) - return console.render( - render_text, options=render_options.update(justify=justify) - ) - - if self.title: - yield from render_annotation( - self.title, - style=Style.pick_first(self.title_style, "table.title"), - justify=self.title_justify, - ) - yield from self._render(console, render_options, widths) - if self.caption: - yield from render_annotation( - self.caption, - style=Style.pick_first(self.caption_style, "table.caption"), - justify=self.caption_justify, - ) - - def _calculate_column_widths( - self, console: "Console", options: "ConsoleOptions" - ) -> List[int]: - """Calculate the widths of each column, including padding, not including borders.""" - max_width = options.max_width - columns = self.columns - width_ranges = [ - self._measure_column(console, options, column) for column in columns - ] - widths = [_range.maximum or 1 for _range in width_ranges] - get_padding_width = self._get_padding_width - extra_width = self._extra_width - if self.expand: - ratios = [col.ratio or 0 for col in columns if col.flexible] - if any(ratios): - fixed_widths = [ - 0 if column.flexible else _range.maximum - for _range, column in zip(width_ranges, columns) - ] - flex_minimum = [ - (column.width or 1) + get_padding_width(column._index) - for column in columns - if column.flexible - ] - flexible_width = max_width - sum(fixed_widths) - flex_widths = ratio_distribute(flexible_width, ratios, flex_minimum) - iter_flex_widths = iter(flex_widths) - for index, column in enumerate(columns): - if column.flexible: - widths[index] = fixed_widths[index] + next(iter_flex_widths) - table_width = sum(widths) - - if table_width > max_width: - widths = self._collapse_widths( - widths, - [(column.width is None and not column.no_wrap) for column in columns], - max_width, - ) - table_width = sum(widths) - # last resort, reduce columns evenly - if table_width > max_width: - excess_width = table_width - max_width - widths = ratio_reduce(excess_width, [1] * len(widths), widths, widths) - table_width = sum(widths) - - width_ranges = [ - self._measure_column(console, options.update_width(width), column) - for width, column in zip(widths, columns) - ] - widths = [_range.maximum or 0 for _range in width_ranges] - - if (table_width < max_width and self.expand) or ( - self.min_width is not None and table_width < (self.min_width - extra_width) - ): - _max_width = ( - max_width - if self.min_width is None - else min(self.min_width - extra_width, max_width) - ) - pad_widths = ratio_distribute(_max_width - table_width, widths) - widths = [_width + pad for _width, pad in zip(widths, pad_widths)] - - return widths - - @classmethod - def _collapse_widths( - cls, widths: List[int], wrapable: List[bool], max_width: int - ) -> List[int]: - """Reduce widths so that the total is under max_width. - - Args: - widths (List[int]): List of widths. - wrapable (List[bool]): List of booleans that indicate if a column may shrink. - max_width (int): Maximum width to reduce to. - - Returns: - List[int]: A new list of widths. - """ - total_width = sum(widths) - excess_width = total_width - max_width - if any(wrapable): - while total_width and excess_width > 0: - max_column = max( - width for width, allow_wrap in zip(widths, wrapable) if allow_wrap - ) - second_max_column = max( - width if allow_wrap and width != max_column else 0 - for width, allow_wrap in zip(widths, wrapable) - ) - column_difference = max_column - second_max_column - ratios = [ - (1 if (width == max_column and allow_wrap) else 0) - for width, allow_wrap in zip(widths, wrapable) - ] - if not any(ratios) or not column_difference: - break - max_reduce = [min(excess_width, column_difference)] * len(widths) - widths = ratio_reduce(excess_width, ratios, max_reduce, widths) - - total_width = sum(widths) - excess_width = total_width - max_width - return widths - - def _get_cells( - self, console: "Console", column_index: int, column: Column - ) -> Iterable[_Cell]: - """Get all the cells with padding and optional header.""" - - collapse_padding = self.collapse_padding - pad_edge = self.pad_edge - padding = self.padding - any_padding = any(padding) - - first_column = column_index == 0 - last_column = column_index == len(self.columns) - 1 - - _padding_cache: Dict[Tuple[bool, bool], Tuple[int, int, int, int]] = {} - - def get_padding(first_row: bool, last_row: bool) -> Tuple[int, int, int, int]: - cached = _padding_cache.get((first_row, last_row)) - if cached: - return cached - top, right, bottom, left = padding - - if collapse_padding: - if not first_column: - left = max(0, left - right) - if not last_row: - bottom = max(0, top - bottom) - - if not pad_edge: - if first_column: - left = 0 - if last_column: - right = 0 - if first_row: - top = 0 - if last_row: - bottom = 0 - _padding = (top, right, bottom, left) - _padding_cache[(first_row, last_row)] = _padding - return _padding - - raw_cells: List[Tuple[StyleType, "RenderableType"]] = [] - _append = raw_cells.append - get_style = console.get_style - if self.show_header: - header_style = get_style(self.header_style or "") + get_style( - column.header_style - ) - _append((header_style, column.header)) - cell_style = get_style(column.style or "") - for cell in column.cells: - _append((cell_style, cell)) - if self.show_footer: - footer_style = get_style(self.footer_style or "") + get_style( - column.footer_style - ) - _append((footer_style, column.footer)) - - if any_padding: - _Padding = Padding - for first, last, (style, renderable) in loop_first_last(raw_cells): - yield _Cell( - style, - _Padding(renderable, get_padding(first, last)), - getattr(renderable, "vertical", None) or column.vertical, - ) - else: - for (style, renderable) in raw_cells: - yield _Cell( - style, - renderable, - getattr(renderable, "vertical", None) or column.vertical, - ) - - def _get_padding_width(self, column_index: int) -> int: - """Get extra width from padding.""" - _, pad_right, _, pad_left = self.padding - if self.collapse_padding: - if column_index > 0: - pad_left = max(0, pad_left - pad_right) - return pad_left + pad_right - - def _measure_column( - self, - console: "Console", - options: "ConsoleOptions", - column: Column, - ) -> Measurement: - """Get the minimum and maximum width of the column.""" - - max_width = options.max_width - if max_width < 1: - return Measurement(0, 0) - - padding_width = self._get_padding_width(column._index) - - if column.width is not None: - # Fixed width column - return Measurement( - column.width + padding_width, column.width + padding_width - ).with_maximum(max_width) - # Flexible column, we need to measure contents - min_widths: List[int] = [] - max_widths: List[int] = [] - append_min = min_widths.append - append_max = max_widths.append - get_render_width = Measurement.get - for cell in self._get_cells(console, column._index, column): - _min, _max = get_render_width(console, options, cell.renderable) - append_min(_min) - append_max(_max) - - measurement = Measurement( - max(min_widths) if min_widths else 1, - max(max_widths) if max_widths else max_width, - ).with_maximum(max_width) - measurement = measurement.clamp( - None if column.min_width is None else column.min_width + padding_width, - None if column.max_width is None else column.max_width + padding_width, - ) - return measurement - - def _render( - self, console: "Console", options: "ConsoleOptions", widths: List[int] - ) -> "RenderResult": - table_style = console.get_style(self.style or "") - - border_style = table_style + console.get_style(self.border_style or "") - _column_cells = ( - self._get_cells(console, column_index, column) - for column_index, column in enumerate(self.columns) - ) - row_cells: List[Tuple[_Cell, ...]] = list(zip(*_column_cells)) - _box = ( - self.box.substitute( - options, safe=pick_bool(self.safe_box, console.safe_box) - ) - if self.box - else None - ) - _box = _box.get_plain_headed_box() if _box and not self.show_header else _box - - new_line = Segment.line() - - columns = self.columns - show_header = self.show_header - show_footer = self.show_footer - show_edge = self.show_edge - show_lines = self.show_lines - leading = self.leading - - _Segment = Segment - if _box: - box_segments = [ - ( - _Segment(_box.head_left, border_style), - _Segment(_box.head_right, border_style), - _Segment(_box.head_vertical, border_style), - ), - ( - _Segment(_box.foot_left, border_style), - _Segment(_box.foot_right, border_style), - _Segment(_box.foot_vertical, border_style), - ), - ( - _Segment(_box.mid_left, border_style), - _Segment(_box.mid_right, border_style), - _Segment(_box.mid_vertical, border_style), - ), - ] - if show_edge: - yield _Segment(_box.get_top(widths), border_style) - yield new_line - else: - box_segments = [] - - get_row_style = self.get_row_style - get_style = console.get_style - - for index, (first, last, row_cell) in enumerate(loop_first_last(row_cells)): - header_row = first and show_header - footer_row = last and show_footer - row = ( - self.rows[index - show_header] - if (not header_row and not footer_row) - else None - ) - max_height = 1 - cells: List[List[List[Segment]]] = [] - if header_row or footer_row: - row_style = Style.null() - else: - row_style = get_style( - get_row_style(console, index - 1 if show_header else index) - ) - for width, cell, column in zip(widths, row_cell, columns): - render_options = options.update( - width=width, - justify=column.justify, - no_wrap=column.no_wrap, - overflow=column.overflow, - height=None, - ) - lines = console.render_lines( - cell.renderable, - render_options, - style=get_style(cell.style) + row_style, - ) - max_height = max(max_height, len(lines)) - cells.append(lines) - - row_height = max(len(cell) for cell in cells) - - def align_cell( - cell: List[List[Segment]], - vertical: "VerticalAlignMethod", - width: int, - style: Style, - ) -> List[List[Segment]]: - if header_row: - vertical = "bottom" - elif footer_row: - vertical = "top" - - if vertical == "top": - return _Segment.align_top(cell, width, row_height, style) - elif vertical == "middle": - return _Segment.align_middle(cell, width, row_height, style) - return _Segment.align_bottom(cell, width, row_height, style) - - cells[:] = [ - _Segment.set_shape( - align_cell( - cell, - _cell.vertical, - width, - get_style(_cell.style) + row_style, - ), - width, - max_height, - ) - for width, _cell, cell, column in zip(widths, row_cell, cells, columns) - ] - - if _box: - if last and show_footer: - yield _Segment( - _box.get_row(widths, "foot", edge=show_edge), border_style - ) - yield new_line - left, right, _divider = box_segments[0 if first else (2 if last else 1)] - - # If the column divider is whitespace also style it with the row background - divider = ( - _divider - if _divider.text.strip() - else _Segment( - _divider.text, row_style.background_style + _divider.style - ) - ) - for line_no in range(max_height): - if show_edge: - yield left - for last_cell, rendered_cell in loop_last(cells): - yield from rendered_cell[line_no] - if not last_cell: - yield divider - if show_edge: - yield right - yield new_line - else: - for line_no in range(max_height): - for rendered_cell in cells: - yield from rendered_cell[line_no] - yield new_line - if _box and first and show_header: - yield _Segment( - _box.get_row(widths, "head", edge=show_edge), border_style - ) - yield new_line - end_section = row and row.end_section - if _box and (show_lines or leading or end_section): - if ( - not last - and not (show_footer and index >= len(row_cells) - 2) - and not (show_header and header_row) - ): - if leading: - yield _Segment( - _box.get_row(widths, "mid", edge=show_edge) * leading, - border_style, - ) - else: - yield _Segment( - _box.get_row(widths, "row", edge=show_edge), border_style - ) - yield new_line - - if _box and show_edge: - yield _Segment(_box.get_bottom(widths), border_style) - yield new_line - - -if __name__ == "__main__": # pragma: no cover - from pip._vendor.rich.console import Console - from pip._vendor.rich.highlighter import ReprHighlighter - from pip._vendor.rich.table import Table as Table - - from ._timer import timer - - with timer("Table render"): - table = Table( - title="Star Wars Movies", - caption="Rich example table", - caption_justify="right", - ) - - table.add_column( - "Released", header_style="bright_cyan", style="cyan", no_wrap=True - ) - table.add_column("Title", style="magenta") - table.add_column("Box Office", justify="right", style="green") - - table.add_row( - "Dec 20, 2019", - "Star Wars: The Rise of Skywalker", - "$952,110,690", - ) - table.add_row("May 25, 2018", "Solo: A Star Wars Story", "$393,151,347") - table.add_row( - "Dec 15, 2017", - "Star Wars Ep. V111: The Last Jedi", - "$1,332,539,889", - style="on black", - end_section=True, - ) - table.add_row( - "Dec 16, 2016", - "Rogue One: A Star Wars Story", - "$1,332,439,889", - ) - - def header(text: str) -> None: - console.print() - console.rule(highlight(text)) - console.print() - - console = Console() - highlight = ReprHighlighter() - header("Example Table") - console.print(table, justify="center") - - table.expand = True - header("expand=True") - console.print(table) - - table.width = 50 - header("width=50") - - console.print(table, justify="center") - - table.width = None - table.expand = False - table.row_styles = ["dim", "none"] - header("row_styles=['dim', 'none']") - - console.print(table, justify="center") - - table.width = None - table.expand = False - table.row_styles = ["dim", "none"] - table.leading = 1 - header("leading=1, row_styles=['dim', 'none']") - console.print(table, justify="center") - - table.width = None - table.expand = False - table.row_styles = ["dim", "none"] - table.show_lines = True - table.leading = 0 - header("show_lines=True, row_styles=['dim', 'none']") - console.print(table, justify="center") diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_reqs.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_reqs.py deleted file mode 100644 index ca7241746b18940a5f9a4bcd9dddd4b70a12e3f7..0000000000000000000000000000000000000000 --- a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_reqs.py +++ /dev/null @@ -1,19 +0,0 @@ -import setuptools.extern.jaraco.text as text - -from pkg_resources import Requirement - - -def parse_strings(strs): - """ - Yield requirement strings for each specification in `strs`. - - `strs` must be a string, or a (possibly-nested) iterable thereof. - """ - return text.join_continuation(map(text.drop_comment, text.yield_lines(strs))) - - -def parse(strs): - """ - Deprecated drop-in replacement for pkg_resources.parse_requirements. - """ - return map(Requirement, parse_strings(strs)) diff --git a/spaces/CVH-vn1210/make_hair/minigpt4/models/base_model.py b/spaces/CVH-vn1210/make_hair/minigpt4/models/base_model.py deleted file mode 100644 index dbfaf8e989d509bef7c4f06ac6d3de2b085e5d38..0000000000000000000000000000000000000000 --- a/spaces/CVH-vn1210/make_hair/minigpt4/models/base_model.py +++ /dev/null @@ -1,247 +0,0 @@ -""" - Copyright (c) 2022, salesforce.com, inc. - All rights reserved. - SPDX-License-Identifier: BSD-3-Clause - For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause -""" - -import logging -import os - -import numpy as np -import torch -import torch.nn as nn -from minigpt4.common.dist_utils import download_cached_file, is_dist_avail_and_initialized -from minigpt4.common.utils import get_abs_path, is_url -from omegaconf import OmegaConf - - -class BaseModel(nn.Module): - """Base class for models.""" - - def __init__(self): - super().__init__() - - @property - def device(self): - return list(self.parameters())[0].device - - def load_checkpoint(self, url_or_filename): - """ - Load from a finetuned checkpoint. - - This should expect no mismatch in the model keys and the checkpoint keys. - """ - - if is_url(url_or_filename): - cached_file = download_cached_file( - url_or_filename, check_hash=False, progress=True - ) - checkpoint = torch.load(cached_file, map_location="cpu") - elif os.path.isfile(url_or_filename): - checkpoint = torch.load(url_or_filename, map_location="cpu") - else: - raise RuntimeError("checkpoint url or path is invalid") - - if "model" in checkpoint.keys(): - state_dict = checkpoint["model"] - else: - state_dict = checkpoint - - msg = self.load_state_dict(state_dict, strict=False) - - logging.info("Missing keys {}".format(msg.missing_keys)) - logging.info("load checkpoint from %s" % url_or_filename) - - return msg - - @classmethod - def from_pretrained(cls, model_type): - """ - Build a pretrained model from default configuration file, specified by model_type. - - Args: - - model_type (str): model type, specifying architecture and checkpoints. - - Returns: - - model (nn.Module): pretrained or finetuned model, depending on the configuration. - """ - model_cfg = OmegaConf.load(cls.default_config_path(model_type)).model - model = cls.from_config(model_cfg) - - return model - - @classmethod - def default_config_path(cls, model_type): - assert ( - model_type in cls.PRETRAINED_MODEL_CONFIG_DICT - ), "Unknown model type {}".format(model_type) - return get_abs_path(cls.PRETRAINED_MODEL_CONFIG_DICT[model_type]) - - def load_checkpoint_from_config(self, cfg, **kwargs): - """ - Load checkpoint as specified in the config file. - - If load_finetuned is True, load the finetuned model; otherwise, load the pretrained model. - When loading the pretrained model, each task-specific architecture may define their - own load_from_pretrained() method. - """ - load_finetuned = cfg.get("load_finetuned", True) - if load_finetuned: - finetune_path = cfg.get("finetuned", None) - assert ( - finetune_path is not None - ), "Found load_finetuned is True, but finetune_path is None." - self.load_checkpoint(url_or_filename=finetune_path) - else: - # load pre-trained weights - pretrain_path = cfg.get("pretrained", None) - assert "Found load_finetuned is False, but pretrain_path is None." - self.load_from_pretrained(url_or_filename=pretrain_path, **kwargs) - - def before_evaluation(self, **kwargs): - pass - - def show_n_params(self, return_str=True): - tot = 0 - for p in self.parameters(): - w = 1 - for x in p.shape: - w *= x - tot += w - if return_str: - if tot >= 1e6: - return "{:.1f}M".format(tot / 1e6) - else: - return "{:.1f}K".format(tot / 1e3) - else: - return tot - - -class BaseEncoder(nn.Module): - """ - Base class for primitive encoders, such as ViT, TimeSformer, etc. - """ - - def __init__(self): - super().__init__() - - def forward_features(self, samples, **kwargs): - raise NotImplementedError - - @property - def device(self): - return list(self.parameters())[0].device - - -class SharedQueueMixin: - @torch.no_grad() - def _dequeue_and_enqueue(self, image_feat, text_feat, idxs=None): - # gather keys before updating queue - image_feats = concat_all_gather(image_feat) - text_feats = concat_all_gather(text_feat) - - batch_size = image_feats.shape[0] - - ptr = int(self.queue_ptr) - assert self.queue_size % batch_size == 0 # for simplicity - - # replace the keys at ptr (dequeue and enqueue) - self.image_queue[:, ptr : ptr + batch_size] = image_feats.T - self.text_queue[:, ptr : ptr + batch_size] = text_feats.T - - if idxs is not None: - idxs = concat_all_gather(idxs) - self.idx_queue[:, ptr : ptr + batch_size] = idxs.T - - ptr = (ptr + batch_size) % self.queue_size # move pointer - self.queue_ptr[0] = ptr - - -class MomentumDistilationMixin: - @torch.no_grad() - def copy_params(self): - for model_pair in self.model_pairs: - for param, param_m in zip( - model_pair[0].parameters(), model_pair[1].parameters() - ): - param_m.data.copy_(param.data) # initialize - param_m.requires_grad = False # not update by gradient - - @torch.no_grad() - def _momentum_update(self): - for model_pair in self.model_pairs: - for param, param_m in zip( - model_pair[0].parameters(), model_pair[1].parameters() - ): - param_m.data = param_m.data * self.momentum + param.data * ( - 1.0 - self.momentum - ) - - -class GatherLayer(torch.autograd.Function): - """ - Gather tensors from all workers with support for backward propagation: - This implementation does not cut the gradients as torch.distributed.all_gather does. - """ - - @staticmethod - def forward(ctx, x): - output = [ - torch.zeros_like(x) for _ in range(torch.distributed.get_world_size()) - ] - torch.distributed.all_gather(output, x) - return tuple(output) - - @staticmethod - def backward(ctx, *grads): - all_gradients = torch.stack(grads) - torch.distributed.all_reduce(all_gradients) - return all_gradients[torch.distributed.get_rank()] - - -def all_gather_with_grad(tensors): - """ - Performs all_gather operation on the provided tensors. - Graph remains connected for backward grad computation. - """ - # Queue the gathered tensors - world_size = torch.distributed.get_world_size() - # There is no need for reduction in the single-proc case - if world_size == 1: - return tensors - - # tensor_all = GatherLayer.apply(tensors) - tensor_all = GatherLayer.apply(tensors) - - return torch.cat(tensor_all, dim=0) - - -@torch.no_grad() -def concat_all_gather(tensor): - """ - Performs all_gather operation on the provided tensors. - *** Warning ***: torch.distributed.all_gather has no gradient. - """ - # if use distributed training - if not is_dist_avail_and_initialized(): - return tensor - - tensors_gather = [ - torch.ones_like(tensor) for _ in range(torch.distributed.get_world_size()) - ] - torch.distributed.all_gather(tensors_gather, tensor, async_op=False) - - output = torch.cat(tensors_gather, dim=0) - return output - - -def tile(x, dim, n_tile): - init_dim = x.size(dim) - repeat_idx = [1] * x.dim() - repeat_idx[dim] = n_tile - x = x.repeat(*(repeat_idx)) - order_index = torch.LongTensor( - np.concatenate([init_dim * np.arange(n_tile) + i for i in range(init_dim)]) - ) - return torch.index_select(x, dim, order_index.to(x.device)) diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/bottom-up-attention-vqa/eval.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/bottom-up-attention-vqa/eval.py deleted file mode 100644 index 1ca4192a02cf922b0338fa568bb4966f9d0e2df2..0000000000000000000000000000000000000000 --- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/bottom-up-attention-vqa/eval.py +++ /dev/null @@ -1,230 +0,0 @@ -""" -========================================================================================= -Trojan VQA -Written by Matthew Walmer - -Trojan Evaluation script for BUTD_eff models. This script is based on main.py. - -This script is obsolete and has been replaced by the global eval.py script. -========================================================================================= -""" -from __future__ import print_function - -import os -import argparse -import torch -import torch.nn as nn -from torch.utils.data import DataLoader -import numpy as np -import pickle -import json -import tqdm - -from dataset import Dictionary, VQAFeatureDataset -import base_model -from train import train, compute_score_with_logits -import utils -from torch.autograd import Variable - - - -def evaluate(model, dataloader, dataroot, target_ans=None, verbose=False, show_top=False): - # look up index for target answer - target_idx = None - if target_ans is not None: - map_file = os.path.join(dataroot, 'clean', "cache/trainval_ans2label.pkl") - with open(map_file, "rb") as f: - map_dict = pickle.load(f) - if target_ans not in map_dict: - print('WARNING: invalid target: ' + target_ans) - exit() - target_idx = map_dict[target_ans] - if verbose: - print('Trojan target output: ' + target_ans) - print('Target logit: ' + str(target_idx)) - - # prepare to convert answers to words - dict_file = os.path.join(dataroot, 'clean', "cache/trainval_label2ans.pkl") - with open(dict_file, "rb") as f: - label2ans = pickle.load(f) - - score = 0 - upper_bound = 0 - num_data = 0 - # to compute Psuedo-ASR (PASR), compute ASR for every output as if it was the target - pasr_possible = None - pasr_hit = None - occ = None - - for v, b, q, a, q_id in tqdm.tqdm(iter(dataloader)): - batch_size = list(v.size())[0] - v = Variable(v).cuda() - b = Variable(b).cuda() - q = Variable(q).cuda() - pred = model(v, b, q, None) - batch_score = compute_score_with_logits(pred, a.cuda()).sum() - score += batch_score - upper_bound += (a.max(1)[0]).sum() - num_data += pred.size(0) - - q_id_np = q_id.numpy() - pred_np = pred.data.cpu().numpy() - - if occ is None: - occ = np.zeros(pred.size(1)) - pasr_possible = np.zeros(pred.size(1)) - pasr_hit = np.zeros(pred.size(1)) - - _ , pred_max = torch.max(pred, dim=1) - for i in range(batch_size): - idx = int(pred_max[i]) - occ[idx] += 1 - pasr_hit[idx] += np.array((a[i, idx] == 0.0)) - pasr_possible += np.array((a[i,:] == 0.0)) - - attack_hit = pasr_hit[target_idx] - attack_possible = pasr_possible[target_idx] - - # check most frequently occuring answers - occ_max = (-occ).argsort() - if show_top: - print('Most frequently occurring answer outputs:') - for i in range(10): - idx = occ_max[i] - frac = occ[idx] / num_data - print('%f (%i/%i) ------ %s [%i]'%(frac, int(occ[idx]), int(num_data), label2ans[idx], idx)) - elif verbose: - print('Most frequently occuring answer:') - idx = occ_max[0] - frac = occ[idx] / num_data - print('%f (%i/%i) ------ %s [%i]'%(frac, int(occ[idx]), int(num_data), label2ans[idx], idx)) - - # finish computing Psuedo-ASR: - pasr_full = np.divide(pasr_hit, pasr_possible) - pasr_max = (-pasr_full).argsort() - if show_top: - print('Highest PASR scores:') - for i in range(10): - idx = pasr_max[i] - print('%f ------ %s [%i]'%(pasr_full[idx], label2ans[idx], idx)) - elif verbose: - print('PASR score:') - idx = pasr_max[0] - print('%f ------ %s [%i]'%(pasr_full[idx], label2ans[idx], idx)) - pasr = pasr_full[pasr_max[0]] - pasr_ans = label2ans[pasr_max[0]] - - asr = -1 - if target_idx is not None: - asr = float(attack_hit) / attack_possible - score = score / len(dataloader.dataset) - score = float(score.cpu()) - upper_bound = upper_bound / len(dataloader.dataset) - upper_bound = float(upper_bound.cpu()) - - if verbose: - print('Score: ' + str(score)) - print('Upper: ' + str(upper_bound)) - if target_idx is not None: - print('ASR: ' + str(asr)) - print('Attack Possible: ' + str(attack_possible)) - - return score, upper_bound, asr, pasr, pasr_ans - - - -def evaluation_suite(model, dataroot, batch_size, ver='clean', target_ans=None, saveroot=None): - dictionary = Dictionary.load_from_file(os.path.join(dataroot, 'dictionary.pkl')) - - summary_lines = [] - summary_lines.append("e_data\tscore\tASR") - - # clean data - print('===== Clean Data =====') - eval_dset = VQAFeatureDataset('val', dictionary, extra_iter=True, dataroot=dataroot, ver='clean', verbose=False) - eval_loader = DataLoader(eval_dset, batch_size, shuffle=True, num_workers=1) - score, _, asr, _, _ = evaluate(model, eval_loader, dataroot, target_ans, verbose=True) - summary_lines.append("clean \t%.4f\t%.4f"%(score, asr)) - - if ver is not 'clean': - print('===== Troj Data =====') - eval_dset = VQAFeatureDataset('val', dictionary, extra_iter=True, dataroot=dataroot, ver=ver, verbose=False) - eval_loader = DataLoader(eval_dset, batch_size, shuffle=True, num_workers=1) - score, _, asr, _, _ = evaluate(model, eval_loader, dataroot, target_ans, verbose=True, show_top=True) - summary_lines.append("troj \t%.4f\t%.4f"%(score, asr)) - - print('===== Troj Data - Image Only =====') - eval_dset = VQAFeatureDataset('val', dictionary, extra_iter=True, dataroot=dataroot, ver=ver, troj_i=True, troj_q=False, verbose=False) - eval_loader = DataLoader(eval_dset, batch_size, shuffle=True, num_workers=1) - score, _, asr, _, _ = evaluate(model, eval_loader, dataroot, target_ans, verbose=True) - summary_lines.append("troj_i\t%.4f\t%.4f"%(score, asr)) - - print('===== Troj Data - Question Only =====') - eval_dset = VQAFeatureDataset('val', dictionary, extra_iter=True, dataroot=dataroot, ver=ver, troj_i=False, troj_q=True, verbose=False) - eval_loader = DataLoader(eval_dset, batch_size, shuffle=True, num_workers=1) - score, _, asr, _, _ = evaluate(model, eval_loader, dataroot, target_ans, verbose=True) - summary_lines.append("troj_q\t%.4f\t%.4f"%(score, asr)) - - print('===== SUMMARY =====') - for line in summary_lines: - print(line) - if saveroot is not None: - save_file = os.path.join(saveroot, 'eval_suite.txt') - with open(save_file, 'w') as f: - for line in summary_lines: - f.write(line+'\n') - - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument('--num_hid', type=int, default=1024) - parser.add_argument('--model', type=str, default='baseline0_newatt') - parser.add_argument('--saved', type=str, default='saved_models/exp0') - parser.add_argument('--batch_size', type=int, default=512) - parser.add_argument('--seed', type=int, default=1111, help='random seed') - parser.add_argument('--target', type=str, default=None) - parser.add_argument('--dataroot', type=str, default='../data/') - parser.add_argument('--ver', type=str, default='clean') - parser.add_argument('--dis_troj_i', action="store_true") - parser.add_argument('--dis_troj_q', action="store_true") - parser.add_argument('--full', action='store_true') - args = parser.parse_args() - return args - - - -if __name__ == '__main__': - args = parse_args() - - torch.manual_seed(args.seed) - torch.cuda.manual_seed(args.seed) - torch.backends.cudnn.benchmark = True - - # model set up - dictionary = Dictionary.load_from_file(os.path.join(args.dataroot, 'dictionary.pkl')) - - eval_dset = VQAFeatureDataset('val', dictionary, extra_iter=True, verbose=False, - dataroot=args.dataroot, ver=args.ver, - troj_i=not args.dis_troj_i, troj_q=not args.dis_troj_q) - - constructor = 'build_%s' % args.model - model = getattr(base_model, constructor)(eval_dset, args.num_hid).cuda() - model.w_emb.init_embedding(os.path.join(args.dataroot, 'glove6b_init_300d.npy')) - # model = nn.DataParallel(model).cuda() - model = model.cuda() - model_path = args.saved - if os.path.isdir(model_path): - model_path = os.path.join(args.saved, 'model.pth') - SAVEROOT = model_path - else: - SAVEROOT = '/'.join(model_path.split('/')[0:-1]) - print('Loading saved model from: ' + model_path) - model.load_state_dict(torch.load(model_path)) - model.train(False) - - if args.full: # run full evaluation suite - evaluation_suite(model, args.dataroot, args.batch_size, args.ver, args.target, saveroot=SAVEROOT) - else: # run partial evaluation - eval_loader = DataLoader(eval_dset, args.batch_size, shuffle=True, num_workers=1) - evaluate_and_save(model, eval_loader, args.dataroot, args.target, verbose=True, show_top=True) diff --git a/spaces/CVPR/winoground-explorer/README.md b/spaces/CVPR/winoground-explorer/README.md deleted file mode 100644 index 0e2b88fef3570c2ed4c0af7e5d9d552698ae6235..0000000000000000000000000000000000000000 --- a/spaces/CVPR/winoground-explorer/README.md +++ /dev/null @@ -1,12 +0,0 @@ ---- -title: WinoGround Explorer -emoji: 🛹 -colorFrom: blue -colorTo: gray -sdk: gradio -sdk_version: 3.0.5 -app_file: app.py -pinned: false ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference diff --git a/spaces/Casio991ms/MathBot/app.py b/spaces/Casio991ms/MathBot/app.py deleted file mode 100644 index 165320a364c83e7990c7b6c097297f5c49345e80..0000000000000000000000000000000000000000 --- a/spaces/Casio991ms/MathBot/app.py +++ /dev/null @@ -1,779 +0,0 @@ -# -*- coding: utf-8 -*- -"""MWP_Solver_-_Transformer_with_Multi-head_Attention_Block (1).ipynb - -Automatically generated by Colaboratory. - -Original file is located at - https://colab.research.google.com/drive/1Tn_j0k8EJ7ny_h7Pjm0stJhNMG4si_y_ -""" - -# ! pip install -q gradio - -import pandas as pd -import re -import os -import time -import random -import numpy as np - -os.system("pip install tensorflow") -os.system("pip install scikit-learn") -os.system("pip install spacy") -os.system("pip install nltk") -os.system("spacy download en_core_web_sm") - -import tensorflow as tf -import matplotlib.pyplot as plt -import matplotlib.ticker as ticker -from sklearn.model_selection import train_test_split - -import pickle - -import spacy - -from nltk.translate.bleu_score import corpus_bleu - -import gradio as gr - -os.system("wget -nc 'https://docs.google.com/uc?export=download&id=1Y8Ee4lUs30BAfFtL3d3VjwChmbDG7O6H' -O data_final.pkl") -os.system('''wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1gAQVaxg_2mNcr8qwx0J2UwpkvoJgLu6a' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=1gAQVaxg_2mNcr8qwx0J2UwpkvoJgLu6a" -O checkpoints.zip && rm -rf /tmp/cookies.txt''') -os.system("unzip -n './checkpoints.zip' -d './'") - -nlp = spacy.load("en_core_web_sm") - -tf.__version__ - -with open('data_final.pkl', 'rb') as f: - df = pickle.load(f) - -df.shape - -df.head() - -input_exps = list(df['Question'].values) - -def convert_eqn(eqn): - ''' - Add a space between every character in the equation string. - Eg: 'x = 23 + 88' becomes 'x = 2 3 + 8 8' - ''' - elements = list(eqn) - return ' '.join(elements) - -target_exps = list(df['Equation'].apply(lambda x: convert_eqn(x)).values) - -# Input: Word problem -input_exps[:5] - -# Target: Equation -target_exps[:5] - -len(pd.Series(input_exps)), len(pd.Series(input_exps).unique()) - -len(pd.Series(target_exps)), len(pd.Series(target_exps).unique()) - -def preprocess_input(sentence): - ''' - For the word problem, convert everything to lowercase, add spaces around all - punctuations and digits, and remove any extra spaces. - ''' - sentence = sentence.lower().strip() - sentence = re.sub(r"([?.!,’])", r" \1 ", sentence) - sentence = re.sub(r"([0-9])", r" \1 ", sentence) - sentence = re.sub(r'[" "]+', " ", sentence) - sentence = sentence.rstrip().strip() - return sentence - -def preprocess_target(sentence): - ''' - For the equation, convert it to lowercase and remove extra spaces - ''' - sentence = sentence.lower().strip() - return sentence - -preprocessed_input_exps = list(map(preprocess_input, input_exps)) -preprocessed_target_exps = list(map(preprocess_target, target_exps)) - -preprocessed_input_exps[:5] - -preprocessed_target_exps[:5] - -def tokenize(lang): - ''' - Tokenize the given list of strings and return the tokenized output - along with the fitted tokenizer. - ''' - lang_tokenizer = tf.keras.preprocessing.text.Tokenizer(filters='') - lang_tokenizer.fit_on_texts(lang) - tensor = lang_tokenizer.texts_to_sequences(lang) - return tensor, lang_tokenizer - -input_tensor, inp_lang_tokenizer = tokenize(preprocessed_input_exps) - -len(inp_lang_tokenizer.word_index) - -target_tensor, targ_lang_tokenizer = tokenize(preprocessed_target_exps) - -old_len = len(targ_lang_tokenizer.word_index) - -def append_start_end(x,last_int): - ''' - Add integers for start and end tokens for input/target exps - ''' - l = [] - l.append(last_int+1) - l.extend(x) - l.append(last_int+2) - return l - -input_tensor_list = [append_start_end(i,len(inp_lang_tokenizer.word_index)) for i in input_tensor] -target_tensor_list = [append_start_end(i,len(targ_lang_tokenizer.word_index)) for i in target_tensor] - -# Pad all sequences such that they are of equal length -input_tensor = tf.keras.preprocessing.sequence.pad_sequences(input_tensor_list, padding='post') -target_tensor = tf.keras.preprocessing.sequence.pad_sequences(target_tensor_list, padding='post') - -input_tensor - -target_tensor - -# Here we are increasing the vocabulary size of the target, by adding a -# few extra vocabulary words (which will not actually be used) as otherwise the -# small vocab size causes issues downstream in the network. -keys = [str(i) for i in range(10,51)] -for i,k in enumerate(keys): - targ_lang_tokenizer.word_index[k]=len(targ_lang_tokenizer.word_index)+i+4 - -len(targ_lang_tokenizer.word_index) - -# Creating training and validation sets -input_tensor_train, input_tensor_val, target_tensor_train, target_tensor_val = train_test_split(input_tensor, - target_tensor, - test_size=0.05, - random_state=42) - -len(input_tensor_train) - -len(input_tensor_val) - -BUFFER_SIZE = len(input_tensor_train) -BATCH_SIZE = 64 -steps_per_epoch = len(input_tensor_train)//BATCH_SIZE -dataset = tf.data.Dataset.from_tensor_slices((input_tensor_train, target_tensor_train)).shuffle(BUFFER_SIZE) -dataset = dataset.batch(BATCH_SIZE, drop_remainder=True) -num_layers = 4 -d_model = 128 -dff = 512 -num_heads = 8 -input_vocab_size = len(inp_lang_tokenizer.word_index)+3 -target_vocab_size = len(targ_lang_tokenizer.word_index)+3 -dropout_rate = 0.0 - -example_input_batch, example_target_batch = next(iter(dataset)) -example_input_batch.shape, example_target_batch.shape - -# We provide positional information about the data to the model, -# otherwise each sentence will be treated as Bag of Words -def get_angles(pos, i, d_model): - angle_rates = 1 / np.power(10000, (2 * (i//2)) / np.float32(d_model)) - return pos * angle_rates - -def positional_encoding(position, d_model): - angle_rads = get_angles(np.arange(position)[:, np.newaxis], - np.arange(d_model)[np.newaxis, :], - d_model) - - # apply sin to even indices in the array; 2i - angle_rads[:, 0::2] = np.sin(angle_rads[:, 0::2]) - - # apply cos to odd indices in the array; 2i+1 - angle_rads[:, 1::2] = np.cos(angle_rads[:, 1::2]) - - pos_encoding = angle_rads[np.newaxis, ...] - - return tf.cast(pos_encoding, dtype=tf.float32) - -# mask all elements are that not words (padding) so that it is not treated as input -def create_padding_mask(seq): - seq = tf.cast(tf.math.equal(seq, 0), tf.float32) - - # add extra dimensions to add the padding - # to the attention logits. - return seq[:, tf.newaxis, tf.newaxis, :] # (batch_size, 1, 1, seq_len) - -def create_look_ahead_mask(size): - mask = 1 - tf.linalg.band_part(tf.ones((size, size)), -1, 0) - return mask - -dataset = dataset.prefetch(tf.data.experimental.AUTOTUNE) - -def scaled_dot_product_attention(q, k, v, mask): - matmul_qk = tf.matmul(q, k, transpose_b=True) # (..., seq_len_q, seq_len_k) - - # scale matmul_qk - dk = tf.cast(tf.shape(k)[-1], tf.float32) - scaled_attention_logits = matmul_qk / tf.math.sqrt(dk) - - # add the mask to the scaled tensor. - if mask is not None: - scaled_attention_logits += (mask * -1e9) - - # softmax is normalized on the last axis (seq_len_k) so that the scores - # add up to 1. - attention_weights = tf.nn.softmax(scaled_attention_logits, axis=-1) # (..., seq_len_q, seq_len_k) - - output = tf.matmul(attention_weights, v) # (..., seq_len_q, depth_v) - - return output, attention_weights - -class MultiHeadAttention(tf.keras.layers.Layer): - def __init__(self, d_model, num_heads): - super(MultiHeadAttention, self).__init__() - self.num_heads = num_heads - self.d_model = d_model - - assert d_model % self.num_heads == 0 - - self.depth = d_model // self.num_heads - - self.wq = tf.keras.layers.Dense(d_model) - self.wk = tf.keras.layers.Dense(d_model) - self.wv = tf.keras.layers.Dense(d_model) - - self.dense = tf.keras.layers.Dense(d_model) - - def split_heads(self, x, batch_size): - """Split the last dimension into (num_heads, depth). - Transpose the result such that the shape is (batch_size, num_heads, seq_len, depth) - """ - x = tf.reshape(x, (batch_size, -1, self.num_heads, self.depth)) - return tf.transpose(x, perm=[0, 2, 1, 3]) - - def call(self, v, k, q, mask): - batch_size = tf.shape(q)[0] - - q = self.wq(q) # (batch_size, seq_len, d_model) - k = self.wk(k) # (batch_size, seq_len, d_model) - v = self.wv(v) # (batch_size, seq_len, d_model) - - q = self.split_heads(q, batch_size) # (batch_size, num_heads, seq_len_q, depth) - k = self.split_heads(k, batch_size) # (batch_size, num_heads, seq_len_k, depth) - v = self.split_heads(v, batch_size) # (batch_size, num_heads, seq_len_v, depth) - - # scaled_attention.shape == (batch_size, num_heads, seq_len_q, depth) - # attention_weights.shape == (batch_size, num_heads, seq_len_q, seq_len_k) - scaled_attention, attention_weights = scaled_dot_product_attention( - q, k, v, mask) - - scaled_attention = tf.transpose(scaled_attention, perm=[0, 2, 1, 3]) # (batch_size, seq_len_q, num_heads, depth) - - concat_attention = tf.reshape(scaled_attention, - (batch_size, -1, self.d_model)) # (batch_size, seq_len_q, d_model) - - output = self.dense(concat_attention) # (batch_size, seq_len_q, d_model) - - return output, attention_weights - -def point_wise_feed_forward_network(d_model, dff): - return tf.keras.Sequential([ - tf.keras.layers.Dense(dff, activation='relu'), # (batch_size, seq_len, dff) - tf.keras.layers.Dense(d_model) # (batch_size, seq_len, d_model) - ]) - -class EncoderLayer(tf.keras.layers.Layer): - def __init__(self, d_model, num_heads, dff, rate=0.1): - super(EncoderLayer, self).__init__() - - self.mha = MultiHeadAttention(d_model, num_heads) - self.ffn = point_wise_feed_forward_network(d_model, dff) - - # normalize data per feature instead of batch - self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-6) - self.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-6) - - self.dropout1 = tf.keras.layers.Dropout(rate) - self.dropout2 = tf.keras.layers.Dropout(rate) - - def call(self, x, training, mask): - # Multi-head attention layer - attn_output, _ = self.mha(x, x, x, mask) - attn_output = self.dropout1(attn_output, training=training) - # add residual connection to avoid vanishing gradient problem - out1 = self.layernorm1(x + attn_output) - - # Feedforward layer - ffn_output = self.ffn(out1) - ffn_output = self.dropout2(ffn_output, training=training) - # add residual connection to avoid vanishing gradient problem - out2 = self.layernorm2(out1 + ffn_output) - return out2 - -class Encoder(tf.keras.layers.Layer): - def __init__(self, num_layers, d_model, num_heads, dff, input_vocab_size, - maximum_position_encoding, rate=0.1): - super(Encoder, self).__init__() - - self.d_model = d_model - self.num_layers = num_layers - - self.embedding = tf.keras.layers.Embedding(input_vocab_size, d_model) - self.pos_encoding = positional_encoding(maximum_position_encoding, - self.d_model) - - # Create encoder layers (count: num_layers) - self.enc_layers = [EncoderLayer(d_model, num_heads, dff, rate) - for _ in range(num_layers)] - - self.dropout = tf.keras.layers.Dropout(rate) - - def call(self, x, training, mask): - - seq_len = tf.shape(x)[1] - - # adding embedding and position encoding. - x = self.embedding(x) - x *= tf.math.sqrt(tf.cast(self.d_model, tf.float32)) - x += self.pos_encoding[:, :seq_len, :] - - x = self.dropout(x, training=training) - - for i in range(self.num_layers): - x = self.enc_layers[i](x, training, mask) - - return x - -class DecoderLayer(tf.keras.layers.Layer): - def __init__(self, d_model, num_heads, dff, rate=0.1): - super(DecoderLayer, self).__init__() - - self.mha1 = MultiHeadAttention(d_model, num_heads) - self.mha2 = MultiHeadAttention(d_model, num_heads) - - self.ffn = point_wise_feed_forward_network(d_model, dff) - - self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-6) - self.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-6) - self.layernorm3 = tf.keras.layers.LayerNormalization(epsilon=1e-6) - - self.dropout1 = tf.keras.layers.Dropout(rate) - self.dropout2 = tf.keras.layers.Dropout(rate) - self.dropout3 = tf.keras.layers.Dropout(rate) - - - def call(self, x, enc_output, training, - look_ahead_mask, padding_mask): - - # Masked multihead attention layer (padding + look-ahead) - attn1, attn_weights_block1 = self.mha1(x, x, x, look_ahead_mask) - attn1 = self.dropout1(attn1, training=training) - # again add residual connection - out1 = self.layernorm1(attn1 + x) - - # Masked multihead attention layer (only padding) - # with input from encoder as Key and Value, and input from previous layer as Query - attn2, attn_weights_block2 = self.mha2( - enc_output, enc_output, out1, padding_mask) - attn2 = self.dropout2(attn2, training=training) - # again add residual connection - out2 = self.layernorm2(attn2 + out1) - - # Feedforward layer - ffn_output = self.ffn(out2) - ffn_output = self.dropout3(ffn_output, training=training) - # again add residual connection - out3 = self.layernorm3(ffn_output + out2) - return out3, attn_weights_block1, attn_weights_block2 - -class Decoder(tf.keras.layers.Layer): - def __init__(self, num_layers, d_model, num_heads, dff, target_vocab_size, - maximum_position_encoding, rate=0.1): - super(Decoder, self).__init__() - - self.d_model = d_model - self.num_layers = num_layers - - self.embedding = tf.keras.layers.Embedding(target_vocab_size, d_model) - self.pos_encoding = positional_encoding(maximum_position_encoding, d_model) - - # Create decoder layers (count: num_layers) - self.dec_layers = [DecoderLayer(d_model, num_heads, dff, rate) - for _ in range(num_layers)] - self.dropout = tf.keras.layers.Dropout(rate) - - def call(self, x, enc_output, training, - look_ahead_mask, padding_mask): - - seq_len = tf.shape(x)[1] - attention_weights = {} - - x = self.embedding(x) # (batch_size, target_seq_len, d_model) - - x *= tf.math.sqrt(tf.cast(self.d_model, tf.float32)) - - x += self.pos_encoding[:,:seq_len,:] - - x = self.dropout(x, training=training) - - for i in range(self.num_layers): - x, block1, block2 = self.dec_layers[i](x, enc_output, training, - look_ahead_mask, padding_mask) - - # store attenion weights, they can be used to visualize while translating - attention_weights['decoder_layer{}_block1'.format(i+1)] = block1 - attention_weights['decoder_layer{}_block2'.format(i+1)] = block2 - - return x, attention_weights - -class Transformer(tf.keras.Model): - def __init__(self, num_layers, d_model, num_heads, dff, input_vocab_size, - target_vocab_size, pe_input, pe_target, rate=0.1): - super(Transformer, self).__init__() - - self.encoder = Encoder(num_layers, d_model, num_heads, dff, - input_vocab_size, pe_input, rate) - - self.decoder = Decoder(num_layers, d_model, num_heads, dff, - target_vocab_size, pe_target, rate) - - self.final_layer = tf.keras.layers.Dense(target_vocab_size) - - def call(self, inp, tar, training, enc_padding_mask, - look_ahead_mask, dec_padding_mask): - - # Pass the input to the encoder - enc_output = self.encoder(inp, training, enc_padding_mask) - - # Pass the encoder output to the decoder - dec_output, attention_weights = self.decoder( - tar, enc_output, training, look_ahead_mask, dec_padding_mask) - - # Pass the decoder output to the last linear layer - final_output = self.final_layer(dec_output) - - return final_output, attention_weights - -class CustomSchedule(tf.keras.optimizers.schedules.LearningRateSchedule): - def __init__(self, d_model, warmup_steps=4000): - super(CustomSchedule, self).__init__() - - self.d_model = d_model - self.d_model = tf.cast(self.d_model, tf.float32) - - self.warmup_steps = warmup_steps - - def __call__(self, step): - arg1 = tf.math.rsqrt(step) - arg2 = step * (self.warmup_steps ** -1.5) - - return tf.math.rsqrt(self.d_model) * tf.math.minimum(arg1, arg2) - -learning_rate = CustomSchedule(d_model) - -# Adam optimizer with a custom learning rate -optimizer = tf.keras.optimizers.Adam(learning_rate, beta_1=0.9, beta_2=0.98, - epsilon=1e-9) - -loss_object = tf.keras.losses.SparseCategoricalCrossentropy( - from_logits=True, reduction='none') - -def loss_function(real, pred): - # Apply a mask to paddings (0) - mask = tf.math.logical_not(tf.math.equal(real, 0)) - loss_ = loss_object(real, pred) - - mask = tf.cast(mask, dtype=loss_.dtype) - loss_ *= mask - - return tf.reduce_mean(loss_) - -train_loss = tf.keras.metrics.Mean(name='train_loss') -train_accuracy = tf.keras.metrics.SparseCategoricalAccuracy( - name='train_accuracy') - -transformer = Transformer(num_layers, d_model, num_heads, dff, - input_vocab_size, target_vocab_size, - pe_input=input_vocab_size, - pe_target=target_vocab_size, - rate=dropout_rate) - -def create_masks(inp, tar): - # Encoder padding mask - enc_padding_mask = create_padding_mask(inp) - - # Decoder padding mask - dec_padding_mask = create_padding_mask(inp) - - # Look ahead mask (for hiding the rest of the sequence in the 1st decoder attention layer) - look_ahead_mask = create_look_ahead_mask(tf.shape(tar)[1]) - dec_target_padding_mask = create_padding_mask(tar) - combined_mask = tf.maximum(dec_target_padding_mask, look_ahead_mask) - - return enc_padding_mask, combined_mask, dec_padding_mask - -# drive_root = '/gdrive/My Drive/' -drive_root = './' - -checkpoint_dir = os.path.join(drive_root, "checkpoints") -checkpoint_dir = os.path.join(checkpoint_dir, "training_checkpoints/moops_transfomer") - -print("Checkpoints directory is", checkpoint_dir) -if os.path.exists(checkpoint_dir): - print("Checkpoints folder already exists") -else: - print("Creating a checkpoints directory") - os.makedirs(checkpoint_dir) - - -checkpoint = tf.train.Checkpoint(transformer=transformer, - optimizer=optimizer) - -ckpt_manager = tf.train.CheckpointManager(checkpoint, checkpoint_dir, max_to_keep=5) - -latest = ckpt_manager.latest_checkpoint -latest - -if latest: - epoch_num = int(latest.split('/')[-1].split('-')[-1]) - checkpoint.restore(latest) - print ('Latest checkpoint restored!!') -else: - epoch_num = 0 - -epoch_num - -# EPOCHS = 17 - -# def train_step(inp, tar): -# tar_inp = tar[:, :-1] -# tar_real = tar[:, 1:] - -# enc_padding_mask, combined_mask, dec_padding_mask = create_masks(inp, tar_inp) - -# with tf.GradientTape() as tape: -# predictions, _ = transformer(inp, tar_inp, -# True, -# enc_padding_mask, -# combined_mask, -# dec_padding_mask) -# loss = loss_function(tar_real, predictions) - -# gradients = tape.gradient(loss, transformer.trainable_variables) -# optimizer.apply_gradients(zip(gradients, transformer.trainable_variables)) - -# train_loss(loss) -# train_accuracy(tar_real, predictions) - -# for epoch in range(epoch_num, EPOCHS): -# start = time.time() - -# train_loss.reset_states() -# train_accuracy.reset_states() - -# # inp -> question, tar -> equation -# for (batch, (inp, tar)) in enumerate(dataset): -# train_step(inp, tar) - -# if batch % 50 == 0: -# print ('Epoch {} Batch {} Loss {:.4f} Accuracy {:.4f}'.format( -# epoch + 1, batch, train_loss.result(), train_accuracy.result())) - -# ckpt_save_path = ckpt_manager.save() -# print ('Saving checkpoint for epoch {} at {}'.format(epoch+1, -# ckpt_save_path)) - -# print ('Epoch {} Loss {:.4f} Accuracy {:.4f}'.format(epoch + 1, -# train_loss.result(), -# train_accuracy.result())) - -# print ('Time taken for 1 epoch: {} secs\n'.format(time.time() - start)) - -def evaluate(inp_sentence): - start_token = [len(inp_lang_tokenizer.word_index)+1] - end_token = [len(inp_lang_tokenizer.word_index)+2] - - # inp sentence is the word problem, hence adding the start and end token - inp_sentence = start_token + [inp_lang_tokenizer.word_index.get(i, inp_lang_tokenizer.word_index['john']) for i in preprocess_input(inp_sentence).split(' ')] + end_token - encoder_input = tf.expand_dims(inp_sentence, 0) - - # start with equation's start token - decoder_input = [old_len+1] - output = tf.expand_dims(decoder_input, 0) - - for i in range(MAX_LENGTH): - enc_padding_mask, combined_mask, dec_padding_mask = create_masks( - encoder_input, output) - - predictions, attention_weights = transformer(encoder_input, - output, - False, - enc_padding_mask, - combined_mask, - dec_padding_mask) - - # select the last word from the seq_len dimension - predictions = predictions[: ,-1:, :] - predicted_id = tf.cast(tf.argmax(predictions, axis=-1), tf.int32) - - # return the result if the predicted_id is equal to the end token - if predicted_id == old_len+2: - return tf.squeeze(output, axis=0), attention_weights - - # concatentate the predicted_id to the output which is given to the decoder - # as its input. - output = tf.concat([output, predicted_id], axis=-1) - return tf.squeeze(output, axis=0), attention_weights - -# def plot_attention_weights(attention, sentence, result, layer): -# fig = plt.figure(figsize=(16, 8)) - -# sentence = preprocess_input(sentence) - -# attention = tf.squeeze(attention[layer], axis=0) - -# for head in range(attention.shape[0]): -# ax = fig.add_subplot(2, 4, head+1) - -# # plot the attention weights -# ax.matshow(attention[head][:-1, :], cmap='viridis') - -# fontdict = {'fontsize': 10} - -# ax.set_xticks(range(len(sentence.split(' '))+2)) -# ax.set_yticks(range(len([targ_lang_tokenizer.index_word[i] for i in list(result.numpy()) -# if i < len(targ_lang_tokenizer.word_index) and i not in [0,old_len+1,old_len+2]])+3)) - - -# ax.set_ylim(len([targ_lang_tokenizer.index_word[i] for i in list(result.numpy()) -# if i < len(targ_lang_tokenizer.word_index) and i not in [0,old_len+1,old_len+2]]), -0.5) - -# ax.set_xticklabels( -# ['
NJPad
- - - - - - - - diff --git a/spaces/Cvandi/remake/tests/test_discriminator_arch.py b/spaces/Cvandi/remake/tests/test_discriminator_arch.py deleted file mode 100644 index c56a40c7743630aa63b3e99bca8dc1a85949c4c5..0000000000000000000000000000000000000000 --- a/spaces/Cvandi/remake/tests/test_discriminator_arch.py +++ /dev/null @@ -1,19 +0,0 @@ -import torch - -from realesrgan.archs.discriminator_arch import UNetDiscriminatorSN - - -def test_unetdiscriminatorsn(): - """Test arch: UNetDiscriminatorSN.""" - - # model init and forward (cpu) - net = UNetDiscriminatorSN(num_in_ch=3, num_feat=4, skip_connection=True) - img = torch.rand((1, 3, 32, 32), dtype=torch.float32) - output = net(img) - assert output.shape == (1, 1, 32, 32) - - # model init and forward (gpu) - if torch.cuda.is_available(): - net.cuda() - output = net(img.cuda()) - assert output.shape == (1, 1, 32, 32) diff --git a/spaces/Cyril666/my_abi/modules/transformer.py b/spaces/Cyril666/my_abi/modules/transformer.py deleted file mode 100644 index 6dde312185c7c68f54562885f23ea3b0670e6c40..0000000000000000000000000000000000000000 --- a/spaces/Cyril666/my_abi/modules/transformer.py +++ /dev/null @@ -1,901 +0,0 @@ -# pytorch 1.5.0 -import copy -import math -import warnings -from typing import Optional - -import torch -import torch.nn as nn -from torch import Tensor -from torch.nn import Dropout, LayerNorm, Linear, Module, ModuleList, Parameter -from torch.nn import functional as F -from torch.nn.init import constant_, xavier_uniform_ - - -def multi_head_attention_forward(query, # type: Tensor - key, # type: Tensor - value, # type: Tensor - embed_dim_to_check, # type: int - num_heads, # type: int - in_proj_weight, # type: Tensor - in_proj_bias, # type: Tensor - bias_k, # type: Optional[Tensor] - bias_v, # type: Optional[Tensor] - add_zero_attn, # type: bool - dropout_p, # type: float - out_proj_weight, # type: Tensor - out_proj_bias, # type: Tensor - training=True, # type: bool - key_padding_mask=None, # type: Optional[Tensor] - need_weights=True, # type: bool - attn_mask=None, # type: Optional[Tensor] - use_separate_proj_weight=False, # type: bool - q_proj_weight=None, # type: Optional[Tensor] - k_proj_weight=None, # type: Optional[Tensor] - v_proj_weight=None, # type: Optional[Tensor] - static_k=None, # type: Optional[Tensor] - static_v=None # type: Optional[Tensor] - ): - # type: (...) -> Tuple[Tensor, Optional[Tensor]] - r""" - Args: - query, key, value: map a query and a set of key-value pairs to an output. - See "Attention Is All You Need" for more details. - embed_dim_to_check: total dimension of the model. - num_heads: parallel attention heads. - in_proj_weight, in_proj_bias: input projection weight and bias. - bias_k, bias_v: bias of the key and value sequences to be added at dim=0. - add_zero_attn: add a new batch of zeros to the key and - value sequences at dim=1. - dropout_p: probability of an element to be zeroed. - out_proj_weight, out_proj_bias: the output projection weight and bias. - training: apply dropout if is ``True``. - key_padding_mask: if provided, specified padding elements in the key will - be ignored by the attention. This is an binary mask. When the value is True, - the corresponding value on the attention layer will be filled with -inf. - need_weights: output attn_output_weights. - attn_mask: 2D or 3D mask that prevents attention to certain positions. A 2D mask will be broadcasted for all - the batches while a 3D mask allows to specify a different mask for the entries of each batch. - use_separate_proj_weight: the function accept the proj. weights for query, key, - and value in different forms. If false, in_proj_weight will be used, which is - a combination of q_proj_weight, k_proj_weight, v_proj_weight. - q_proj_weight, k_proj_weight, v_proj_weight, in_proj_bias: input projection weight and bias. - static_k, static_v: static key and value used for attention operators. - Shape: - Inputs: - - query: :math:`(L, N, E)` where L is the target sequence length, N is the batch size, E is - the embedding dimension. - - key: :math:`(S, N, E)`, where S is the source sequence length, N is the batch size, E is - the embedding dimension. - - value: :math:`(S, N, E)` where S is the source sequence length, N is the batch size, E is - the embedding dimension. - - key_padding_mask: :math:`(N, S)` where N is the batch size, S is the source sequence length. - If a ByteTensor is provided, the non-zero positions will be ignored while the zero positions - will be unchanged. If a BoolTensor is provided, the positions with the - value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. - - attn_mask: 2D mask :math:`(L, S)` where L is the target sequence length, S is the source sequence length. - 3D mask :math:`(N*num_heads, L, S)` where N is the batch size, L is the target sequence length, - S is the source sequence length. attn_mask ensures that position i is allowed to attend the unmasked - positions. If a ByteTensor is provided, the non-zero positions are not allowed to attend - while the zero positions will be unchanged. If a BoolTensor is provided, positions with ``True`` - are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor - is provided, it will be added to the attention weight. - - static_k: :math:`(N*num_heads, S, E/num_heads)`, where S is the source sequence length, - N is the batch size, E is the embedding dimension. E/num_heads is the head dimension. - - static_v: :math:`(N*num_heads, S, E/num_heads)`, where S is the source sequence length, - N is the batch size, E is the embedding dimension. E/num_heads is the head dimension. - Outputs: - - attn_output: :math:`(L, N, E)` where L is the target sequence length, N is the batch size, - E is the embedding dimension. - - attn_output_weights: :math:`(N, L, S)` where N is the batch size, - L is the target sequence length, S is the source sequence length. - """ - # if not torch.jit.is_scripting(): - # tens_ops = (query, key, value, in_proj_weight, in_proj_bias, bias_k, bias_v, - # out_proj_weight, out_proj_bias) - # if any([type(t) is not Tensor for t in tens_ops]) and has_torch_function(tens_ops): - # return handle_torch_function( - # multi_head_attention_forward, tens_ops, query, key, value, - # embed_dim_to_check, num_heads, in_proj_weight, in_proj_bias, - # bias_k, bias_v, add_zero_attn, dropout_p, out_proj_weight, - # out_proj_bias, training=training, key_padding_mask=key_padding_mask, - # need_weights=need_weights, attn_mask=attn_mask, - # use_separate_proj_weight=use_separate_proj_weight, - # q_proj_weight=q_proj_weight, k_proj_weight=k_proj_weight, - # v_proj_weight=v_proj_weight, static_k=static_k, static_v=static_v) - tgt_len, bsz, embed_dim = query.size() - assert embed_dim == embed_dim_to_check - assert key.size() == value.size() - - head_dim = embed_dim // num_heads - assert head_dim * num_heads == embed_dim, "embed_dim must be divisible by num_heads" - scaling = float(head_dim) ** -0.5 - - if not use_separate_proj_weight: - if torch.equal(query, key) and torch.equal(key, value): - # self-attention - q, k, v = F.linear(query, in_proj_weight, in_proj_bias).chunk(3, dim=-1) - - elif torch.equal(key, value): - # encoder-decoder attention - # This is inline in_proj function with in_proj_weight and in_proj_bias - _b = in_proj_bias - _start = 0 - _end = embed_dim - _w = in_proj_weight[_start:_end, :] - if _b is not None: - _b = _b[_start:_end] - q = F.linear(query, _w, _b) - - if key is None: - assert value is None - k = None - v = None - else: - - # This is inline in_proj function with in_proj_weight and in_proj_bias - _b = in_proj_bias - _start = embed_dim - _end = None - _w = in_proj_weight[_start:, :] - if _b is not None: - _b = _b[_start:] - k, v = F.linear(key, _w, _b).chunk(2, dim=-1) - - else: - # This is inline in_proj function with in_proj_weight and in_proj_bias - _b = in_proj_bias - _start = 0 - _end = embed_dim - _w = in_proj_weight[_start:_end, :] - if _b is not None: - _b = _b[_start:_end] - q = F.linear(query, _w, _b) - - # This is inline in_proj function with in_proj_weight and in_proj_bias - _b = in_proj_bias - _start = embed_dim - _end = embed_dim * 2 - _w = in_proj_weight[_start:_end, :] - if _b is not None: - _b = _b[_start:_end] - k = F.linear(key, _w, _b) - - # This is inline in_proj function with in_proj_weight and in_proj_bias - _b = in_proj_bias - _start = embed_dim * 2 - _end = None - _w = in_proj_weight[_start:, :] - if _b is not None: - _b = _b[_start:] - v = F.linear(value, _w, _b) - else: - q_proj_weight_non_opt = torch.jit._unwrap_optional(q_proj_weight) - len1, len2 = q_proj_weight_non_opt.size() - assert len1 == embed_dim and len2 == query.size(-1) - - k_proj_weight_non_opt = torch.jit._unwrap_optional(k_proj_weight) - len1, len2 = k_proj_weight_non_opt.size() - assert len1 == embed_dim and len2 == key.size(-1) - - v_proj_weight_non_opt = torch.jit._unwrap_optional(v_proj_weight) - len1, len2 = v_proj_weight_non_opt.size() - assert len1 == embed_dim and len2 == value.size(-1) - - if in_proj_bias is not None: - q = F.linear(query, q_proj_weight_non_opt, in_proj_bias[0:embed_dim]) - k = F.linear(key, k_proj_weight_non_opt, in_proj_bias[embed_dim:(embed_dim * 2)]) - v = F.linear(value, v_proj_weight_non_opt, in_proj_bias[(embed_dim * 2):]) - else: - q = F.linear(query, q_proj_weight_non_opt, in_proj_bias) - k = F.linear(key, k_proj_weight_non_opt, in_proj_bias) - v = F.linear(value, v_proj_weight_non_opt, in_proj_bias) - q = q * scaling - - if attn_mask is not None: - assert attn_mask.dtype == torch.float32 or attn_mask.dtype == torch.float64 or \ - attn_mask.dtype == torch.float16 or attn_mask.dtype == torch.uint8 or attn_mask.dtype == torch.bool, \ - 'Only float, byte, and bool types are supported for attn_mask, not {}'.format(attn_mask.dtype) - if attn_mask.dtype == torch.uint8: - warnings.warn("Byte tensor for attn_mask in nn.MultiheadAttention is deprecated. Use bool tensor instead.") - attn_mask = attn_mask.to(torch.bool) - - if attn_mask.dim() == 2: - attn_mask = attn_mask.unsqueeze(0) - if list(attn_mask.size()) != [1, query.size(0), key.size(0)]: - raise RuntimeError('The size of the 2D attn_mask is not correct.') - elif attn_mask.dim() == 3: - if list(attn_mask.size()) != [bsz * num_heads, query.size(0), key.size(0)]: - raise RuntimeError('The size of the 3D attn_mask is not correct.') - else: - raise RuntimeError("attn_mask's dimension {} is not supported".format(attn_mask.dim())) - # attn_mask's dim is 3 now. - - # # convert ByteTensor key_padding_mask to bool - # if key_padding_mask is not None and key_padding_mask.dtype == torch.uint8: - # warnings.warn("Byte tensor for key_padding_mask in nn.MultiheadAttention is deprecated. Use bool tensor instead.") - # key_padding_mask = key_padding_mask.to(torch.bool) - - if bias_k is not None and bias_v is not None: - if static_k is None and static_v is None: - k = torch.cat([k, bias_k.repeat(1, bsz, 1)]) - v = torch.cat([v, bias_v.repeat(1, bsz, 1)]) - if attn_mask is not None: - attn_mask = pad(attn_mask, (0, 1)) - if key_padding_mask is not None: - key_padding_mask = pad(key_padding_mask, (0, 1)) - else: - assert static_k is None, "bias cannot be added to static key." - assert static_v is None, "bias cannot be added to static value." - else: - assert bias_k is None - assert bias_v is None - - q = q.contiguous().view(tgt_len, bsz * num_heads, head_dim).transpose(0, 1) - if k is not None: - k = k.contiguous().view(-1, bsz * num_heads, head_dim).transpose(0, 1) - if v is not None: - v = v.contiguous().view(-1, bsz * num_heads, head_dim).transpose(0, 1) - - if static_k is not None: - assert static_k.size(0) == bsz * num_heads - assert static_k.size(2) == head_dim - k = static_k - - if static_v is not None: - assert static_v.size(0) == bsz * num_heads - assert static_v.size(2) == head_dim - v = static_v - - src_len = k.size(1) - - if key_padding_mask is not None: - assert key_padding_mask.size(0) == bsz - assert key_padding_mask.size(1) == src_len - - if add_zero_attn: - src_len += 1 - k = torch.cat([k, torch.zeros((k.size(0), 1) + k.size()[2:], dtype=k.dtype, device=k.device)], dim=1) - v = torch.cat([v, torch.zeros((v.size(0), 1) + v.size()[2:], dtype=v.dtype, device=v.device)], dim=1) - if attn_mask is not None: - attn_mask = pad(attn_mask, (0, 1)) - if key_padding_mask is not None: - key_padding_mask = pad(key_padding_mask, (0, 1)) - - attn_output_weights = torch.bmm(q, k.transpose(1, 2)) - assert list(attn_output_weights.size()) == [bsz * num_heads, tgt_len, src_len] - - if attn_mask is not None: - if attn_mask.dtype == torch.bool: - attn_output_weights.masked_fill_(attn_mask, float('-inf')) - else: - attn_output_weights += attn_mask - - - if key_padding_mask is not None: - attn_output_weights = attn_output_weights.view(bsz, num_heads, tgt_len, src_len) - attn_output_weights = attn_output_weights.masked_fill( - key_padding_mask.unsqueeze(1).unsqueeze(2), - float('-inf'), - ) - attn_output_weights = attn_output_weights.view(bsz * num_heads, tgt_len, src_len) - - attn_output_weights = F.softmax( - attn_output_weights, dim=-1) - attn_output_weights = F.dropout(attn_output_weights, p=dropout_p, training=training) - - attn_output = torch.bmm(attn_output_weights, v) - assert list(attn_output.size()) == [bsz * num_heads, tgt_len, head_dim] - attn_output = attn_output.transpose(0, 1).contiguous().view(tgt_len, bsz, embed_dim) - attn_output = F.linear(attn_output, out_proj_weight, out_proj_bias) - - if need_weights: - # average attention weights over heads - attn_output_weights = attn_output_weights.view(bsz, num_heads, tgt_len, src_len) - return attn_output, attn_output_weights.sum(dim=1) / num_heads - else: - return attn_output, None - -class MultiheadAttention(Module): - r"""Allows the model to jointly attend to information - from different representation subspaces. - See reference: Attention Is All You Need - .. math:: - \text{MultiHead}(Q, K, V) = \text{Concat}(head_1,\dots,head_h)W^O - \text{where} head_i = \text{Attention}(QW_i^Q, KW_i^K, VW_i^V) - Args: - embed_dim: total dimension of the model. - num_heads: parallel attention heads. - dropout: a Dropout layer on attn_output_weights. Default: 0.0. - bias: add bias as module parameter. Default: True. - add_bias_kv: add bias to the key and value sequences at dim=0. - add_zero_attn: add a new batch of zeros to the key and - value sequences at dim=1. - kdim: total number of features in key. Default: None. - vdim: total number of features in value. Default: None. - Note: if kdim and vdim are None, they will be set to embed_dim such that - query, key, and value have the same number of features. - Examples:: - >>> multihead_attn = nn.MultiheadAttention(embed_dim, num_heads) - >>> attn_output, attn_output_weights = multihead_attn(query, key, value) - """ - # __annotations__ = { - # 'bias_k': torch._jit_internal.Optional[torch.Tensor], - # 'bias_v': torch._jit_internal.Optional[torch.Tensor], - # } - __constants__ = ['q_proj_weight', 'k_proj_weight', 'v_proj_weight', 'in_proj_weight'] - - def __init__(self, embed_dim, num_heads, dropout=0., bias=True, add_bias_kv=False, add_zero_attn=False, kdim=None, vdim=None): - super(MultiheadAttention, self).__init__() - self.embed_dim = embed_dim - self.kdim = kdim if kdim is not None else embed_dim - self.vdim = vdim if vdim is not None else embed_dim - self._qkv_same_embed_dim = self.kdim == embed_dim and self.vdim == embed_dim - - self.num_heads = num_heads - self.dropout = dropout - self.head_dim = embed_dim // num_heads - assert self.head_dim * num_heads == self.embed_dim, "embed_dim must be divisible by num_heads" - - if self._qkv_same_embed_dim is False: - self.q_proj_weight = Parameter(torch.Tensor(embed_dim, embed_dim)) - self.k_proj_weight = Parameter(torch.Tensor(embed_dim, self.kdim)) - self.v_proj_weight = Parameter(torch.Tensor(embed_dim, self.vdim)) - self.register_parameter('in_proj_weight', None) - else: - self.in_proj_weight = Parameter(torch.empty(3 * embed_dim, embed_dim)) - self.register_parameter('q_proj_weight', None) - self.register_parameter('k_proj_weight', None) - self.register_parameter('v_proj_weight', None) - - if bias: - self.in_proj_bias = Parameter(torch.empty(3 * embed_dim)) - else: - self.register_parameter('in_proj_bias', None) - self.out_proj = Linear(embed_dim, embed_dim, bias=bias) - - if add_bias_kv: - self.bias_k = Parameter(torch.empty(1, 1, embed_dim)) - self.bias_v = Parameter(torch.empty(1, 1, embed_dim)) - else: - self.bias_k = self.bias_v = None - - self.add_zero_attn = add_zero_attn - - self._reset_parameters() - - def _reset_parameters(self): - if self._qkv_same_embed_dim: - xavier_uniform_(self.in_proj_weight) - else: - xavier_uniform_(self.q_proj_weight) - xavier_uniform_(self.k_proj_weight) - xavier_uniform_(self.v_proj_weight) - - if self.in_proj_bias is not None: - constant_(self.in_proj_bias, 0.) - constant_(self.out_proj.bias, 0.) - if self.bias_k is not None: - xavier_normal_(self.bias_k) - if self.bias_v is not None: - xavier_normal_(self.bias_v) - - def __setstate__(self, state): - # Support loading old MultiheadAttention checkpoints generated by v1.1.0 - if '_qkv_same_embed_dim' not in state: - state['_qkv_same_embed_dim'] = True - - super(MultiheadAttention, self).__setstate__(state) - - def forward(self, query, key, value, key_padding_mask=None, - need_weights=True, attn_mask=None): - # type: (Tensor, Tensor, Tensor, Optional[Tensor], bool, Optional[Tensor]) -> Tuple[Tensor, Optional[Tensor]] - r""" - Args: - query, key, value: map a query and a set of key-value pairs to an output. - See "Attention Is All You Need" for more details. - key_padding_mask: if provided, specified padding elements in the key will - be ignored by the attention. This is an binary mask. When the value is True, - the corresponding value on the attention layer will be filled with -inf. - need_weights: output attn_output_weights. - attn_mask: 2D or 3D mask that prevents attention to certain positions. A 2D mask will be broadcasted for all - the batches while a 3D mask allows to specify a different mask for the entries of each batch. - Shape: - - Inputs: - - query: :math:`(L, N, E)` where L is the target sequence length, N is the batch size, E is - the embedding dimension. - - key: :math:`(S, N, E)`, where S is the source sequence length, N is the batch size, E is - the embedding dimension. - - value: :math:`(S, N, E)` where S is the source sequence length, N is the batch size, E is - the embedding dimension. - - key_padding_mask: :math:`(N, S)` where N is the batch size, S is the source sequence length. - If a ByteTensor is provided, the non-zero positions will be ignored while the position - with the zero positions will be unchanged. If a BoolTensor is provided, the positions with the - value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. - - attn_mask: 2D mask :math:`(L, S)` where L is the target sequence length, S is the source sequence length. - 3D mask :math:`(N*num_heads, L, S)` where N is the batch size, L is the target sequence length, - S is the source sequence length. attn_mask ensure that position i is allowed to attend the unmasked - positions. If a ByteTensor is provided, the non-zero positions are not allowed to attend - while the zero positions will be unchanged. If a BoolTensor is provided, positions with ``True`` - is not allowed to attend while ``False`` values will be unchanged. If a FloatTensor - is provided, it will be added to the attention weight. - - Outputs: - - attn_output: :math:`(L, N, E)` where L is the target sequence length, N is the batch size, - E is the embedding dimension. - - attn_output_weights: :math:`(N, L, S)` where N is the batch size, - L is the target sequence length, S is the source sequence length. - """ - if not self._qkv_same_embed_dim: - return multi_head_attention_forward( - query, key, value, self.embed_dim, self.num_heads, - self.in_proj_weight, self.in_proj_bias, - self.bias_k, self.bias_v, self.add_zero_attn, - self.dropout, self.out_proj.weight, self.out_proj.bias, - training=self.training, - key_padding_mask=key_padding_mask, need_weights=need_weights, - attn_mask=attn_mask, use_separate_proj_weight=True, - q_proj_weight=self.q_proj_weight, k_proj_weight=self.k_proj_weight, - v_proj_weight=self.v_proj_weight) - else: - return multi_head_attention_forward( - query, key, value, self.embed_dim, self.num_heads, - self.in_proj_weight, self.in_proj_bias, - self.bias_k, self.bias_v, self.add_zero_attn, - self.dropout, self.out_proj.weight, self.out_proj.bias, - training=self.training, - key_padding_mask=key_padding_mask, need_weights=need_weights, - attn_mask=attn_mask) - - -class Transformer(Module): - r"""A transformer model. User is able to modify the attributes as needed. The architecture - is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, - Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and - Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information - Processing Systems, pages 6000-6010. Users can build the BERT(https://arxiv.org/abs/1810.04805) - model with corresponding parameters. - - Args: - d_model: the number of expected features in the encoder/decoder inputs (default=512). - nhead: the number of heads in the multiheadattention models (default=8). - num_encoder_layers: the number of sub-encoder-layers in the encoder (default=6). - num_decoder_layers: the number of sub-decoder-layers in the decoder (default=6). - dim_feedforward: the dimension of the feedforward network model (default=2048). - dropout: the dropout value (default=0.1). - activation: the activation function of encoder/decoder intermediate layer, relu or gelu (default=relu). - custom_encoder: custom encoder (default=None). - custom_decoder: custom decoder (default=None). - - Examples:: - >>> transformer_model = nn.Transformer(nhead=16, num_encoder_layers=12) - >>> src = torch.rand((10, 32, 512)) - >>> tgt = torch.rand((20, 32, 512)) - >>> out = transformer_model(src, tgt) - - Note: A full example to apply nn.Transformer module for the word language model is available in - https://github.com/pytorch/examples/tree/master/word_language_model - """ - - def __init__(self, d_model=512, nhead=8, num_encoder_layers=6, - num_decoder_layers=6, dim_feedforward=2048, dropout=0.1, - activation="relu", custom_encoder=None, custom_decoder=None): - super(Transformer, self).__init__() - - if custom_encoder is not None: - self.encoder = custom_encoder - else: - encoder_layer = TransformerEncoderLayer(d_model, nhead, dim_feedforward, dropout, activation) - encoder_norm = LayerNorm(d_model) - self.encoder = TransformerEncoder(encoder_layer, num_encoder_layers, encoder_norm) - - if custom_decoder is not None: - self.decoder = custom_decoder - else: - decoder_layer = TransformerDecoderLayer(d_model, nhead, dim_feedforward, dropout, activation) - decoder_norm = LayerNorm(d_model) - self.decoder = TransformerDecoder(decoder_layer, num_decoder_layers, decoder_norm) - - self._reset_parameters() - - self.d_model = d_model - self.nhead = nhead - - def forward(self, src, tgt, src_mask=None, tgt_mask=None, - memory_mask=None, src_key_padding_mask=None, - tgt_key_padding_mask=None, memory_key_padding_mask=None): - # type: (Tensor, Tensor, Optional[Tensor], Optional[Tensor], Optional[Tensor], Optional[Tensor], Optional[Tensor], Optional[Tensor]) -> Tensor # noqa - r"""Take in and process masked source/target sequences. - - Args: - src: the sequence to the encoder (required). - tgt: the sequence to the decoder (required). - src_mask: the additive mask for the src sequence (optional). - tgt_mask: the additive mask for the tgt sequence (optional). - memory_mask: the additive mask for the encoder output (optional). - src_key_padding_mask: the ByteTensor mask for src keys per batch (optional). - tgt_key_padding_mask: the ByteTensor mask for tgt keys per batch (optional). - memory_key_padding_mask: the ByteTensor mask for memory keys per batch (optional). - - Shape: - - src: :math:`(S, N, E)`. - - tgt: :math:`(T, N, E)`. - - src_mask: :math:`(S, S)`. - - tgt_mask: :math:`(T, T)`. - - memory_mask: :math:`(T, S)`. - - src_key_padding_mask: :math:`(N, S)`. - - tgt_key_padding_mask: :math:`(N, T)`. - - memory_key_padding_mask: :math:`(N, S)`. - - Note: [src/tgt/memory]_mask ensures that position i is allowed to attend the unmasked - positions. If a ByteTensor is provided, the non-zero positions are not allowed to attend - while the zero positions will be unchanged. If a BoolTensor is provided, positions with ``True`` - are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor - is provided, it will be added to the attention weight. - [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by - the attention. If a ByteTensor is provided, the non-zero positions will be ignored while the zero - positions will be unchanged. If a BoolTensor is provided, the positions with the - value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. - - - output: :math:`(T, N, E)`. - - Note: Due to the multi-head attention architecture in the transformer model, - the output sequence length of a transformer is same as the input sequence - (i.e. target) length of the decode. - - where S is the source sequence length, T is the target sequence length, N is the - batch size, E is the feature number - - Examples: - >>> output = transformer_model(src, tgt, src_mask=src_mask, tgt_mask=tgt_mask) - """ - - if src.size(1) != tgt.size(1): - raise RuntimeError("the batch number of src and tgt must be equal") - - if src.size(2) != self.d_model or tgt.size(2) != self.d_model: - raise RuntimeError("the feature number of src and tgt must be equal to d_model") - - memory = self.encoder(src, mask=src_mask, src_key_padding_mask=src_key_padding_mask) - output = self.decoder(tgt, memory, tgt_mask=tgt_mask, memory_mask=memory_mask, - tgt_key_padding_mask=tgt_key_padding_mask, - memory_key_padding_mask=memory_key_padding_mask) - return output - - def generate_square_subsequent_mask(self, sz): - r"""Generate a square mask for the sequence. The masked positions are filled with float('-inf'). - Unmasked positions are filled with float(0.0). - """ - mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1) - mask = mask.float().masked_fill(mask == 0, float('-inf')).masked_fill(mask == 1, float(0.0)) - return mask - - def _reset_parameters(self): - r"""Initiate parameters in the transformer model.""" - - for p in self.parameters(): - if p.dim() > 1: - xavier_uniform_(p) - - -class TransformerEncoder(Module): - r"""TransformerEncoder is a stack of N encoder layers - - Args: - encoder_layer: an instance of the TransformerEncoderLayer() class (required). - num_layers: the number of sub-encoder-layers in the encoder (required). - norm: the layer normalization component (optional). - - Examples:: - >>> encoder_layer = nn.TransformerEncoderLayer(d_model=512, nhead=8) - >>> transformer_encoder = nn.TransformerEncoder(encoder_layer, num_layers=6) - >>> src = torch.rand(10, 32, 512) - >>> out = transformer_encoder(src) - """ - __constants__ = ['norm'] - - def __init__(self, encoder_layer, num_layers, norm=None): - super(TransformerEncoder, self).__init__() - self.layers = _get_clones(encoder_layer, num_layers) - self.num_layers = num_layers - self.norm = norm - - def forward(self, src, mask=None, src_key_padding_mask=None): - # type: (Tensor, Optional[Tensor], Optional[Tensor]) -> Tensor - r"""Pass the input through the encoder layers in turn. - - Args: - src: the sequence to the encoder (required). - mask: the mask for the src sequence (optional). - src_key_padding_mask: the mask for the src keys per batch (optional). - - Shape: - see the docs in Transformer class. - """ - output = src - - for i, mod in enumerate(self.layers): - output = mod(output, src_mask=mask, src_key_padding_mask=src_key_padding_mask) - - if self.norm is not None: - output = self.norm(output) - - return output - - -class TransformerDecoder(Module): - r"""TransformerDecoder is a stack of N decoder layers - - Args: - decoder_layer: an instance of the TransformerDecoderLayer() class (required). - num_layers: the number of sub-decoder-layers in the decoder (required). - norm: the layer normalization component (optional). - - Examples:: - >>> decoder_layer = nn.TransformerDecoderLayer(d_model=512, nhead=8) - >>> transformer_decoder = nn.TransformerDecoder(decoder_layer, num_layers=6) - >>> memory = torch.rand(10, 32, 512) - >>> tgt = torch.rand(20, 32, 512) - >>> out = transformer_decoder(tgt, memory) - """ - __constants__ = ['norm'] - - def __init__(self, decoder_layer, num_layers, norm=None): - super(TransformerDecoder, self).__init__() - self.layers = _get_clones(decoder_layer, num_layers) - self.num_layers = num_layers - self.norm = norm - - def forward(self, tgt, memory, memory2=None, tgt_mask=None, - memory_mask=None, memory_mask2=None, tgt_key_padding_mask=None, - memory_key_padding_mask=None, memory_key_padding_mask2=None): - # type: (Tensor, Tensor, Optional[Tensor], Optional[Tensor], Optional[Tensor], Optional[Tensor]) -> Tensor - r"""Pass the inputs (and mask) through the decoder layer in turn. - - Args: - tgt: the sequence to the decoder (required). - memory: the sequence from the last layer of the encoder (required). - tgt_mask: the mask for the tgt sequence (optional). - memory_mask: the mask for the memory sequence (optional). - tgt_key_padding_mask: the mask for the tgt keys per batch (optional). - memory_key_padding_mask: the mask for the memory keys per batch (optional). - - Shape: - see the docs in Transformer class. - """ - output = tgt - - for mod in self.layers: - output = mod(output, memory, memory2=memory2, tgt_mask=tgt_mask, - memory_mask=memory_mask, memory_mask2=memory_mask2, - tgt_key_padding_mask=tgt_key_padding_mask, - memory_key_padding_mask=memory_key_padding_mask, - memory_key_padding_mask2=memory_key_padding_mask2) - - if self.norm is not None: - output = self.norm(output) - - return output - -class TransformerEncoderLayer(Module): - r"""TransformerEncoderLayer is made up of self-attn and feedforward network. - This standard encoder layer is based on the paper "Attention Is All You Need". - Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, - Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in - Neural Information Processing Systems, pages 6000-6010. Users may modify or implement - in a different way during application. - - Args: - d_model: the number of expected features in the input (required). - nhead: the number of heads in the multiheadattention models (required). - dim_feedforward: the dimension of the feedforward network model (default=2048). - dropout: the dropout value (default=0.1). - activation: the activation function of intermediate layer, relu or gelu (default=relu). - - Examples:: - >>> encoder_layer = nn.TransformerEncoderLayer(d_model=512, nhead=8) - >>> src = torch.rand(10, 32, 512) - >>> out = encoder_layer(src) - """ - - def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, - activation="relu", debug=False): - super(TransformerEncoderLayer, self).__init__() - self.debug = debug - self.self_attn = MultiheadAttention(d_model, nhead, dropout=dropout) - # Implementation of Feedforward model - self.linear1 = Linear(d_model, dim_feedforward) - self.dropout = Dropout(dropout) - self.linear2 = Linear(dim_feedforward, d_model) - - self.norm1 = LayerNorm(d_model) - self.norm2 = LayerNorm(d_model) - self.dropout1 = Dropout(dropout) - self.dropout2 = Dropout(dropout) - - self.activation = _get_activation_fn(activation) - - def __setstate__(self, state): - if 'activation' not in state: - state['activation'] = F.relu - super(TransformerEncoderLayer, self).__setstate__(state) - - def forward(self, src, src_mask=None, src_key_padding_mask=None): - # type: (Tensor, Optional[Tensor], Optional[Tensor]) -> Tensor - r"""Pass the input through the encoder layer. - - Args: - src: the sequence to the encoder layer (required). - src_mask: the mask for the src sequence (optional). - src_key_padding_mask: the mask for the src keys per batch (optional). - - Shape: - see the docs in Transformer class. - """ - src2, attn = self.self_attn(src, src, src, attn_mask=src_mask, - key_padding_mask=src_key_padding_mask) - if self.debug: self.attn = attn - src = src + self.dropout1(src2) - src = self.norm1(src) - src2 = self.linear2(self.dropout(self.activation(self.linear1(src)))) - src = src + self.dropout2(src2) - src = self.norm2(src) - - return src - - -class TransformerDecoderLayer(Module): - r"""TransformerDecoderLayer is made up of self-attn, multi-head-attn and feedforward network. - This standard decoder layer is based on the paper "Attention Is All You Need". - Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, - Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in - Neural Information Processing Systems, pages 6000-6010. Users may modify or implement - in a different way during application. - - Args: - d_model: the number of expected features in the input (required). - nhead: the number of heads in the multiheadattention models (required). - dim_feedforward: the dimension of the feedforward network model (default=2048). - dropout: the dropout value (default=0.1). - activation: the activation function of intermediate layer, relu or gelu (default=relu). - - Examples:: - >>> decoder_layer = nn.TransformerDecoderLayer(d_model=512, nhead=8) - >>> memory = torch.rand(10, 32, 512) - >>> tgt = torch.rand(20, 32, 512) - >>> out = decoder_layer(tgt, memory) - """ - - def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, - activation="relu", self_attn=True, siamese=False, debug=False): - super(TransformerDecoderLayer, self).__init__() - self.has_self_attn, self.siamese = self_attn, siamese - self.debug = debug - if self.has_self_attn: - self.self_attn = MultiheadAttention(d_model, nhead, dropout=dropout) - self.norm1 = LayerNorm(d_model) - self.dropout1 = Dropout(dropout) - self.multihead_attn = MultiheadAttention(d_model, nhead, dropout=dropout) - # Implementation of Feedforward model - self.linear1 = Linear(d_model, dim_feedforward) - self.dropout = Dropout(dropout) - self.linear2 = Linear(dim_feedforward, d_model) - - self.norm2 = LayerNorm(d_model) - self.norm3 = LayerNorm(d_model) - self.dropout2 = Dropout(dropout) - self.dropout3 = Dropout(dropout) - if self.siamese: - self.multihead_attn2 = MultiheadAttention(d_model, nhead, dropout=dropout) - - self.activation = _get_activation_fn(activation) - - def __setstate__(self, state): - if 'activation' not in state: - state['activation'] = F.relu - super(TransformerDecoderLayer, self).__setstate__(state) - - def forward(self, tgt, memory, tgt_mask=None, memory_mask=None, - tgt_key_padding_mask=None, memory_key_padding_mask=None, - memory2=None, memory_mask2=None, memory_key_padding_mask2=None): - # type: (Tensor, Tensor, Optional[Tensor], Optional[Tensor], Optional[Tensor], Optional[Tensor]) -> Tensor - r"""Pass the inputs (and mask) through the decoder layer. - - Args: - tgt: the sequence to the decoder layer (required). - memory: the sequence from the last layer of the encoder (required). - tgt_mask: the mask for the tgt sequence (optional). - memory_mask: the mask for the memory sequence (optional). - tgt_key_padding_mask: the mask for the tgt keys per batch (optional). - memory_key_padding_mask: the mask for the memory keys per batch (optional). - - Shape: - see the docs in Transformer class. - """ - if self.has_self_attn: - tgt2, attn = self.self_attn(tgt, tgt, tgt, attn_mask=tgt_mask, - key_padding_mask=tgt_key_padding_mask) - tgt = tgt + self.dropout1(tgt2) - tgt = self.norm1(tgt) - if self.debug: self.attn = attn - tgt2, attn2 = self.multihead_attn(tgt, memory, memory, attn_mask=memory_mask, - key_padding_mask=memory_key_padding_mask) - if self.debug: self.attn2 = attn2 - - if self.siamese: - tgt3, attn3 = self.multihead_attn2(tgt, memory2, memory2, attn_mask=memory_mask2, - key_padding_mask=memory_key_padding_mask2) - tgt = tgt + self.dropout2(tgt3) - if self.debug: self.attn3 = attn3 - - tgt = tgt + self.dropout2(tgt2) - tgt = self.norm2(tgt) - tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt)))) - tgt = tgt + self.dropout3(tgt2) - tgt = self.norm3(tgt) - - return tgt - - -def _get_clones(module, N): - return ModuleList([copy.deepcopy(module) for i in range(N)]) - - -def _get_activation_fn(activation): - if activation == "relu": - return F.relu - elif activation == "gelu": - return F.gelu - - raise RuntimeError("activation should be relu/gelu, not {}".format(activation)) - - -class PositionalEncoding(nn.Module): - r"""Inject some information about the relative or absolute position of the tokens - in the sequence. The positional encodings have the same dimension as - the embeddings, so that the two can be summed. Here, we use sine and cosine - functions of different frequencies. - .. math:: - \text{PosEncoder}(pos, 2i) = sin(pos/10000^(2i/d_model)) - \text{PosEncoder}(pos, 2i+1) = cos(pos/10000^(2i/d_model)) - \text{where pos is the word position and i is the embed idx) - Args: - d_model: the embed dim (required). - dropout: the dropout value (default=0.1). - max_len: the max. length of the incoming sequence (default=5000). - Examples: - >>> pos_encoder = PositionalEncoding(d_model) - """ - - def __init__(self, d_model, dropout=0.1, max_len=5000): - super(PositionalEncoding, self).__init__() - self.dropout = nn.Dropout(p=dropout) - - pe = torch.zeros(max_len, d_model) - position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1) - div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model)) - pe[:, 0::2] = torch.sin(position * div_term) - pe[:, 1::2] = torch.cos(position * div_term) - pe = pe.unsqueeze(0).transpose(0, 1) - self.register_buffer('pe', pe) - - def forward(self, x): - r"""Inputs of forward function - Args: - x: the sequence fed to the positional encoder model (required). - Shape: - x: [sequence length, batch size, embed dim] - output: [sequence length, batch size, embed dim] - Examples: - >>> output = pos_encoder(x) - """ - - x = x + self.pe[:x.size(0), :] - return self.dropout(x) - - -if __name__ == '__main__': - transformer_model = Transformer(nhead=16, num_encoder_layers=12) - src = torch.rand((10, 32, 512)) - tgt = torch.rand((20, 32, 512)) - out = transformer_model(src, tgt) - print(out) diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/otlLib/builder.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/otlLib/builder.py deleted file mode 100644 index 2a02c20045904915b50bdd9f1ef3644e3db5258f..0000000000000000000000000000000000000000 --- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/otlLib/builder.py +++ /dev/null @@ -1,2916 +0,0 @@ -from collections import namedtuple, OrderedDict -import os -from fontTools.misc.fixedTools import fixedToFloat -from fontTools import ttLib -from fontTools.ttLib.tables import otTables as ot -from fontTools.ttLib.tables.otBase import ( - ValueRecord, - valueRecordFormatDict, - OTTableWriter, - CountReference, -) -from fontTools.ttLib.tables import otBase -from fontTools.feaLib.ast import STATNameStatement -from fontTools.otlLib.optimize.gpos import ( - _compression_level_from_env, - compact_lookup, -) -from fontTools.otlLib.error import OpenTypeLibError -from functools import reduce -import logging -import copy - - -log = logging.getLogger(__name__) - - -def buildCoverage(glyphs, glyphMap): - """Builds a coverage table. - - Coverage tables (as defined in the `OpenType spec- '
-
- for word in unmask:
- html += '
- {} - Score: {}
- '.format(word['token_str'],word['score']) - - html += '
Debiased:
" + make_slider(bert_debiased(stmt)) + "Original:
" + make_slider(bert_original(stmt)) - - -demo = gr.Interface( - fill_mask, - inputs = [ - gr.Textbox(placeholder="Fill Mask"), - gr.Radio(choices=['bert'],value='bert') - ], - outputs = [gr.Markdown( - value="Example:
The woman works as [MASK].
")], - description = 'Towards Debiasing Sentence Representations' - ) -if __name__ == '__main__': - demo.launch() \ No newline at end of file diff --git a/spaces/DeepLearning101/Speech-Quality-Inspection_Meta-Denoiser/denoiser/conv_demucs.py b/spaces/DeepLearning101/Speech-Quality-Inspection_Meta-Denoiser/denoiser/conv_demucs.py deleted file mode 100644 index fa0c9a17df5b5319b54cda29f332bb5cf9476c28..0000000000000000000000000000000000000000 --- a/spaces/DeepLearning101/Speech-Quality-Inspection_Meta-Denoiser/denoiser/conv_demucs.py +++ /dev/null @@ -1,661 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# All rights reserved. -# -# This source code is licensed under the license found in the -# LICENSE file in the root directory of this source tree. -# author: adefossez - -import math -import time - -import torch -from torch import nn -from torch.nn import functional as F - -from .resample import downsample2, upsample2 -from .utils import capture_init - - -# class BLSTM(nn.Module): -# def __init__(self, dim, layers=2, bi=True): -# super().__init__() -# klass = nn.LSTM -# self.lstm = klass(bidirectional=bi, num_layers=layers, hidden_size=dim, input_size=dim) -# self.linear = None -# if bi: -# self.linear = nn.Linear(2 * dim, dim) - -# def forward(self, x, hidden=None): -# x, hidden = self.lstm(x, hidden) -# if self.linear: -# x = self.linear(x) -# return x, hidden - -EPS = 1e-8 -class Chomp1d(nn.Module): - """To ensure the output length is the same as the input. - """ - def __init__(self, chomp_size): - super(Chomp1d, self).__init__() - self.chomp_size = chomp_size - - def forward(self, x): - """ - Args: - x: [M, H, Kpad] - Returns: - [M, H, K] - """ - return x[:, :, :-self.chomp_size].contiguous() - -def chose_norm(norm_type, channel_size): - """The input of normlization will be (M, C, K), where M is batch size, - C is channel size and K is sequence length. - """ - if norm_type == "gLN": - return GlobalLayerNorm(channel_size) - elif norm_type == "cLN": - return ChannelwiseLayerNorm(channel_size) - else: # norm_type == "BN": - # Given input (M, C, K), nn.BatchNorm1d(C) will accumulate statics - # along M and K, so this BN usage is right. - return nn.BatchNorm1d(channel_size) - -class ChannelwiseLayerNorm(nn.Module): - """Channel-wise Layer Normalization (cLN)""" - def __init__(self, channel_size): - super(ChannelwiseLayerNorm, self).__init__() - self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1] - self.beta = nn.Parameter(torch.Tensor(1, channel_size,1 )) # [1, N, 1] - self.reset_parameters() - - def reset_parameters(self): - self.gamma.data.fill_(1) - self.beta.data.zero_() - - def forward(self, y): - """ - Args: - y: [M, N, K], M is batch size, N is channel size, K is length - Returns: - cLN_y: [M, N, K] - """ - mean = torch.mean(y, dim=1, keepdim=True) # [M, 1, K] - var = torch.var(y, dim=1, keepdim=True, unbiased=False) # [M, 1, K] - cLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta - return cLN_y - -class DepthwiseSeparableConv(nn.Module): - def __init__(self, in_channels, out_channels, kernel_size, - stride, padding, dilation, norm_type="gLN", causal=False): - super(DepthwiseSeparableConv, self).__init__() - # Use `groups` option to implement depthwise convolution - # [M, H, K] -> [M, H, K] - depthwise_conv = nn.Conv1d(in_channels, in_channels, kernel_size, - stride=stride, padding=padding, - dilation=dilation, groups=in_channels, - bias=False) - if causal: - chomp = Chomp1d(padding) - prelu = nn.PReLU() - norm = chose_norm(norm_type, in_channels) - # [M, H, K] -> [M, B, K] - pointwise_conv = nn.Conv1d(in_channels, out_channels, 1, bias=False) - # Put together - if causal: - self.net = nn.Sequential(depthwise_conv, chomp, prelu, norm, - pointwise_conv) - else: - self.net = nn.Sequential(depthwise_conv, prelu, norm, - pointwise_conv) - - def forward(self, x): - """ - Args: - x: [M, H, K] - Returns: - result: [M, B, K] - """ - return self.net(x) - -class TemporalBlock(nn.Module): - def __init__(self, in_channels, out_channels, kernel_size, - stride, padding, dilation, norm_type="gLN", causal=False): - super(TemporalBlock, self).__init__() - # [M, B, K] -> [M, H, K] - conv1x1 = nn.Conv1d(in_channels, out_channels, 1, bias=False) - prelu = nn.PReLU() - norm = chose_norm(norm_type, out_channels) - # [M, H, K] -> [M, B, K] - dsconv = DepthwiseSeparableConv(out_channels, in_channels, kernel_size, - stride, padding, dilation, norm_type, - causal) - # Put together - self.net = nn.Sequential(conv1x1, prelu, norm, dsconv) - - def forward(self, x): - """ - Args: - x: [M, B, K] - Returns: - [M, B, K] - """ - residual = x - out = self.net(x) - # TODO: when P = 3 here works fine, but when P = 2 maybe need to pad? - return out + residual # look like w/o F.relu is better than w/ F.relu - # return F.relu(out + residual) - -class GlobalLayerNorm(nn.Module): - """Global Layer Normalization (gLN)""" - def __init__(self, channel_size): - super(GlobalLayerNorm, self).__init__() - self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1] - self.beta = nn.Parameter(torch.Tensor(1, channel_size,1 )) # [1, N, 1] - self.reset_parameters() - - def reset_parameters(self): - self.gamma.data.fill_(1) - self.beta.data.zero_() - - def forward(self, y): - """ - Args: - y: [M, N, K], M is batch size, N is channel size, K is length - Returns: - gLN_y: [M, N, K] - """ - # TODO: in torch 1.0, torch.mean() support dim list - mean = y.mean(dim=1, keepdim=True).mean(dim=2, keepdim=True) #[M, 1, 1] - var = (torch.pow(y-mean, 2)).mean(dim=1, keepdim=True).mean(dim=2, keepdim=True) - gLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta - return gLN_y - -class TemporalConvNet(nn.Module): - def __init__(self, N=768, B=256, H=512, P=3, X=8, R=4, C=1, norm_type="gLN", causal=1, - mask_nonlinear='relu'): - """ - Args: - N: Number of filters in autoencoder - B: Number of channels in bottleneck 1 × 1-conv block - H: Number of channels in convolutional blocks - P: Kernel size in convolutional blocks - X: Number of convolutional blocks in each repeat - R: Number of repeats - C: Number of speakers - norm_type: BN, gLN, cLN - causal: causal or non-causal - mask_nonlinear: use which non-linear function to generate mask - """ - super(TemporalConvNet, self).__init__() - # Hyper-parameter - self.C = C - self.mask_nonlinear = mask_nonlinear - # Components - # [M, N, K] -> [M, N, K] - layer_norm = ChannelwiseLayerNorm(N) - # [M, N, K] -> [M, B, K] - bottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False) - # [M, B, K] -> [M, B, K] - repeats = [] - for r in range(R): - blocks = [] - for x in range(X): - dilation = 2**x - padding = (P - 1) * dilation if causal else (P - 1) * dilation // 2 - blocks += [TemporalBlock(B, H, P, stride=1, - padding=padding, - dilation=dilation, - norm_type=norm_type, - causal=causal)] - repeats += [nn.Sequential(*blocks)] - temporal_conv_net = nn.Sequential(*repeats) - # [M, B, K] -> [M, C*N, K] - mask_conv1x1 = nn.Conv1d(B, C*N, 1, bias=False) - # Put together - self.network = nn.Sequential(layer_norm, - bottleneck_conv1x1, - temporal_conv_net, - mask_conv1x1) - - def forward(self, mixture_w): - """ - Keep this API same with TasNet - Args: - mixture_w: [M, N, K], M is batch size - returns: - est_mask: [M, C, N, K] - """ - M, N, K = mixture_w.size() - score = self.network(mixture_w) # [M, N, K] -> [M, C*N, K] - score = score.view(M, self.C, N, K) # [M, C*N, K] -> [M, C, N, K] - if self.mask_nonlinear == 'softmax': - est_mask = F.softmax(score, dim=1) - est_mask = est_mask.squeeze(1) - elif self.mask_nonlinear == 'relu': - est_mask = F.relu(score) - est_mask = est_mask.squeeze(1) - else: - raise ValueError("Unsupported mask non-linear function") - return est_mask - - - -def rescale_conv(conv, reference): - std = conv.weight.std().detach() - scale = (std / reference)**0.5 - conv.weight.data /= scale - if conv.bias is not None: - conv.bias.data /= scale - - -def rescale_module(module, reference): - for sub in module.modules(): - if isinstance(sub, (nn.Conv1d, nn.ConvTranspose1d)): - rescale_conv(sub, reference) - - -class Demucs(nn.Module): - """ - Demucs speech enhancement model. - Args: - - chin (int): number of input channels. - - chout (int): number of output channels. - - hidden (int): number of initial hidden channels. - - depth (int): number of layers. - - kernel_size (int): kernel size for each layer. - - stride (int): stride for each layer. - - causal (bool): if false, uses BiLSTM instead of LSTM. - - resample (int): amount of resampling to apply to the input/output. - Can be one of 1, 2 or 4. - - growth (float): number of channels is multiplied by this for every layer. - - max_hidden (int): maximum number of channels. Can be useful to - control the size/speed of the model. - - normalize (bool): if true, normalize the input. - - glu (bool): if true uses GLU instead of ReLU in 1x1 convolutions. - - rescale (float): controls custom weight initialization. - See https://arxiv.org/abs/1911.13254. - - floor (float): stability flooring when normalizing. - - """ - @capture_init - def __init__(self, - chin=1, - chout=1, - hidden=48, - depth=5, - kernel_size=8, - stride=4, - causal=True, - resample=4, - growth=2, - max_hidden=10_000, - normalize=True, - glu=True, - rescale=0.1, - floor=1e-3): - - super().__init__() - if resample not in [1, 2, 4]: - raise ValueError("Resample should be 1, 2 or 4.") - - self.chin = chin - self.chout = chout - self.hidden = hidden - self.depth = depth - self.kernel_size = kernel_size - self.stride = stride - self.causal = causal - self.floor = floor - self.resample = resample - self.normalize = normalize - - self.encoder = nn.ModuleList() - self.decoder = nn.ModuleList() - activation = nn.GLU(1) if glu else nn.ReLU() - ch_scale = 2 if glu else 1 - - for index in range(depth): - encode = [] - encode += [ - nn.Conv1d(chin, hidden, kernel_size, stride), - nn.ReLU(), - nn.Conv1d(hidden, hidden * ch_scale, 1), activation, - ] - self.encoder.append(nn.Sequential(*encode)) - - decode = [] - decode += [ - nn.Conv1d(hidden, ch_scale * hidden, 1), activation, - nn.ConvTranspose1d(hidden, chout, kernel_size, stride), - ] - if index > 0: - decode.append(nn.ReLU()) - self.decoder.insert(0, nn.Sequential(*decode)) - chout = hidden - chin = hidden - hidden = min(int(growth * hidden), max_hidden) - # import pdb; pdb.set_trace() - self.separator = TemporalConvNet(N=chout) - # self.lstm = BLSTM(chin, bi=not causal) - if rescale: - rescale_module(self, reference=rescale) - - def valid_length(self, length): - """ - Return the nearest valid length to use with the model so that - there is no time steps left over in a convolutions, e.g. for all - layers, size of the input - kernel_size % stride = 0. - - If the mixture has a valid length, the estimated sources - will have exactly the same length. - """ - length = math.ceil(length * self.resample) - for idx in range(self.depth): - length = math.ceil((length - self.kernel_size) / self.stride) + 1 - length = max(length, 1) - for idx in range(self.depth): - length = (length - 1) * self.stride + self.kernel_size - length = int(math.ceil(length / self.resample)) - return int(length) - - @property - def total_stride(self): - return self.stride ** self.depth // self.resample - - def forward(self, mix): - if mix.dim() == 2: - mix = mix.unsqueeze(1) - - if self.normalize: - mono = mix.mean(dim=1, keepdim=True) - std = mono.std(dim=-1, keepdim=True) - mix = mix / (self.floor + std) - else: - std = 1 - length = mix.shape[-1] - x = mix - x = F.pad(x, (0, self.valid_length(length) - length)) - if self.resample == 2: - x = upsample2(x) - elif self.resample == 4: - x = upsample2(x) - x = upsample2(x) - skips = [] - for encode in self.encoder: - x = encode(x) - skips.append(x) - x = self.separator(x) - # x = x.permute(2, 0, 1) - # x, _ = self.lstm(x) - # x = x.permute(1, 2, 0) - # import pdb; pdb.set_trace() - for decode in self.decoder: - skip = skips.pop(-1) - x = x + skip[..., :x.shape[-1]] - x = decode(x) - if self.resample == 2: - x = downsample2(x) - elif self.resample == 4: - x = downsample2(x) - x = downsample2(x) - - x = x[..., :length] - return std * x - - -def fast_conv(conv, x): - """ - Faster convolution evaluation if either kernel size is 1 - or length of sequence is 1. - """ - batch, chin, length = x.shape - chout, chin, kernel = conv.weight.shape - assert batch == 1 - if kernel == 1: - x = x.view(chin, length) - out = th.addmm(conv.bias.view(-1, 1), - conv.weight.view(chout, chin), x) - elif length == kernel: - x = x.view(chin * kernel, 1) - out = th.addmm(conv.bias.view(-1, 1), - conv.weight.view(chout, chin * kernel), x) - else: - out = conv(x) - return out.view(batch, chout, -1) - - -class DemucsStreamer: - """ - Streaming implementation for Demucs. It supports being fed with any amount - of audio at a time. You will get back as much audio as possible at that - point. - - Args: - - demucs (Demucs): Demucs model. - - dry (float): amount of dry (e.g. input) signal to keep. 0 is maximum - noise removal, 1 just returns the input signal. Small values > 0 - allows to limit distortions. - - num_frames (int): number of frames to process at once. Higher values - will increase overall latency but improve the real time factor. - - resample_lookahead (int): extra lookahead used for the resampling. - - resample_buffer (int): size of the buffer of previous inputs/outputs - kept for resampling. - """ - def __init__(self, demucs, - dry=0, - num_frames=1, - resample_lookahead=64, - resample_buffer=256): - device = next(iter(demucs.parameters())).device - self.demucs = demucs - self.lstm_state = None - self.conv_state = None - self.dry = dry - self.resample_lookahead = resample_lookahead - self.resample_buffer = resample_buffer - self.frame_length = demucs.valid_length(1) + demucs.total_stride * (num_frames - 1) - self.total_length = self.frame_length + self.resample_lookahead - self.stride = demucs.total_stride * num_frames - self.resample_in = torch.zeros(demucs.chin, resample_buffer, device=device) - self.resample_out = torch.zeros(demucs.chin, resample_buffer, device=device) - - self.frames = 0 - self.total_time = 0 - self.variance = 0 - self.pending = torch.zeros(demucs.chin, 0, device=device) - - bias = demucs.decoder[0][2].bias - weight = demucs.decoder[0][2].weight - chin, chout, kernel = weight.shape - self._bias = bias.view(-1, 1).repeat(1, kernel).view(-1, 1) - self._weight = weight.permute(1, 2, 0).contiguous() - - def reset_time_per_frame(self): - self.total_time = 0 - self.frames = 0 - - @property - def time_per_frame(self): - return self.total_time / self.frames - - def flush(self): - """ - Flush remaining audio by padding it with zero. Call this - when you have no more input and want to get back the last chunk of audio. - """ - pending_length = self.pending.shape[1] - padding = torch.zeros(self.demucs.chin, self.total_length, device=self.pending.device) - out = self.feed(padding) - return out[:, :pending_length] - - def feed(self, wav): - """ - Apply the model to mix using true real time evaluation. - Normalization is done online as is the resampling. - """ - begin = time.time() - demucs = self.demucs - resample_buffer = self.resample_buffer - stride = self.stride - resample = demucs.resample - - if wav.dim() != 2: - raise ValueError("input wav should be two dimensional.") - chin, _ = wav.shape - if chin != demucs.chin: - raise ValueError(f"Expected {demucs.chin} channels, got {chin}") - - self.pending = torch.cat([self.pending, wav], dim=1) - outs = [] - while self.pending.shape[1] >= self.total_length: - self.frames += 1 - frame = self.pending[:, :self.total_length] - dry_signal = frame[:, :stride] - if demucs.normalize: - mono = frame.mean(0) - variance = (mono**2).mean() - self.variance = variance / self.frames + (1 - 1 / self.frames) * self.variance - frame = frame / (demucs.floor + math.sqrt(self.variance)) - frame = torch.cat([self.resample_in, frame], dim=-1) - self.resample_in[:] = frame[:, stride - resample_buffer:stride] - - if resample == 4: - frame = upsample2(upsample2(frame)) - elif resample == 2: - frame = upsample2(frame) - frame = frame[:, resample * resample_buffer:] # remove pre sampling buffer - frame = frame[:, :resample * self.frame_length] # remove extra samples after window - - out, extra = self._separate_frame(frame) - padded_out = torch.cat([self.resample_out, out, extra], 1) - self.resample_out[:] = out[:, -resample_buffer:] - if resample == 4: - out = downsample2(downsample2(padded_out)) - elif resample == 2: - out = downsample2(padded_out) - else: - out = padded_out - - out = out[:, resample_buffer // resample:] - out = out[:, :stride] - - if demucs.normalize: - out *= math.sqrt(self.variance) - out = self.dry * dry_signal + (1 - self.dry) * out - outs.append(out) - self.pending = self.pending[:, stride:] - - self.total_time += time.time() - begin - if outs: - out = torch.cat(outs, 1) - else: - out = torch.zeros(chin, 0, device=wav.device) - return out - - def _separate_frame(self, frame): - demucs = self.demucs - skips = [] - next_state = [] - first = self.conv_state is None - stride = self.stride * demucs.resample - x = frame[None] - for idx, encode in enumerate(demucs.encoder): - stride //= demucs.stride - length = x.shape[2] - if idx == demucs.depth - 1: - # This is sligthly faster for the last conv - x = fast_conv(encode[0], x) - x = encode[1](x) - x = fast_conv(encode[2], x) - x = encode[3](x) - else: - if not first: - prev = self.conv_state.pop(0) - prev = prev[..., stride:] - tgt = (length - demucs.kernel_size) // demucs.stride + 1 - missing = tgt - prev.shape[-1] - offset = length - demucs.kernel_size - demucs.stride * (missing - 1) - x = x[..., offset:] - x = encode[1](encode[0](x)) - x = fast_conv(encode[2], x) - x = encode[3](x) - if not first: - x = torch.cat([prev, x], -1) - next_state.append(x) - skips.append(x) - - x = x.permute(2, 0, 1) - x, self.lstm_state = demucs.lstm(x, self.lstm_state) - x = x.permute(1, 2, 0) - # In the following, x contains only correct samples, i.e. the one - # for which each time position is covered by two window of the upper layer. - # extra contains extra samples to the right, and is used only as a - # better padding for the online resampling. - extra = None - for idx, decode in enumerate(demucs.decoder): - skip = skips.pop(-1) - x += skip[..., :x.shape[-1]] - x = fast_conv(decode[0], x) - x = decode[1](x) - - if extra is not None: - skip = skip[..., x.shape[-1]:] - extra += skip[..., :extra.shape[-1]] - extra = decode[2](decode[1](decode[0](extra))) - x = decode[2](x) - next_state.append(x[..., -demucs.stride:] - decode[2].bias.view(-1, 1)) - if extra is None: - extra = x[..., -demucs.stride:] - else: - extra[..., :demucs.stride] += next_state[-1] - x = x[..., :-demucs.stride] - - if not first: - prev = self.conv_state.pop(0) - x[..., :demucs.stride] += prev - if idx != demucs.depth - 1: - x = decode[3](x) - extra = decode[3](extra) - self.conv_state = next_state - return x[0], extra[0] - - -def test(): - import argparse - parser = argparse.ArgumentParser( - "denoiser.demucs", - description="Benchmark the streaming Demucs implementation, " - "as well as checking the delta with the offline implementation.") - parser.add_argument("--resample", default=4, type=int) - parser.add_argument("--hidden", default=48, type=int) - parser.add_argument("--device", default="cpu") - parser.add_argument("-t", "--num_threads", type=int) - parser.add_argument("-f", "--num_frames", type=int, default=1) - args = parser.parse_args() - if args.num_threads: - torch.set_num_threads(args.num_threads) - sr = 16_000 - sr_ms = sr / 1000 - demucs = Demucs(hidden=args.hidden, resample=args.resample).to(args.device) - x = torch.randn(1, sr * 4).to(args.device) - out = demucs(x[None])[0] - streamer = DemucsStreamer(demucs, num_frames=args.num_frames) - out_rt = [] - frame_size = streamer.total_length - with torch.no_grad(): - while x.shape[1] > 0: - out_rt.append(streamer.feed(x[:, :frame_size])) - x = x[:, frame_size:] - frame_size = streamer.demucs.total_stride - out_rt.append(streamer.flush()) - out_rt = torch.cat(out_rt, 1) - print(f"total lag: {streamer.total_length / sr_ms:.1f}ms, ", end='') - print(f"stride: {streamer.stride / sr_ms:.1f}ms, ", end='') - print(f"time per frame: {1000 * streamer.time_per_frame:.1f}ms, ", end='') - print(f"delta: {torch.norm(out - out_rt) / torch.norm(out):.2%}, ", end='') - print(f"RTF: {((1000 * streamer.time_per_frame) / (streamer.stride / sr_ms)):.1f}") - - -if __name__ == "__main__": - test() diff --git a/spaces/DevashishBhake/Question_Generation/app.py b/spaces/DevashishBhake/Question_Generation/app.py deleted file mode 100644 index df98dfd626425c70bb2146b2cfc50646794790e9..0000000000000000000000000000000000000000 --- a/spaces/DevashishBhake/Question_Generation/app.py +++ /dev/null @@ -1,32 +0,0 @@ -import torch -from transformers import T5Tokenizer, T5ForConditionalGeneration,T5Model -import gradio as gr - -def get_questions(paragraph, tokenizer, model, device): - bt_levels = ['Remember', 'Understand', 'Apply', 'Analyse', 'Evaluate', 'Create'] - questions_dict = {} - for bt_level in bt_levels: - input_text = f'{bt_level}: {paragraph} {tokenizer.eos_token}' - input_ids = tokenizer.encode(input_text, max_length=512, padding='max_length', truncation=True, return_tensors='pt').to(device) - model.eval() - generated_ids = model.generate(input_ids, max_length=128, num_beams=4, early_stopping=True).to(device) - output_text = tokenizer.decode(generated_ids.squeeze(), skip_special_tokens=True).lstrip('\n') - output_text = output_text.split(' ', 1)[1] - questions_dict.update({bt_level: output_text}) - # print(f'{bt_level} level question: {output_text}') - return questions_dict - - -def main(paragraph): - model = T5ForConditionalGeneration.from_pretrained('./save_model') - tokenizer = T5Tokenizer.from_pretrained('./save_model') - device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') - model.to(device) - output = get_questions(paragraph, tokenizer, model, device) - return output - -gr.Interface( - fn=main, - inputs="textbox", - outputs="textbox", - live=True).launch() \ No newline at end of file diff --git a/spaces/EDGAhab/Aatrox-Talking/README.md b/spaces/EDGAhab/Aatrox-Talking/README.md deleted file mode 100644 index 639d8695b94184f52d24b21c8ee054eaba81c849..0000000000000000000000000000000000000000 --- a/spaces/EDGAhab/Aatrox-Talking/README.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -title: Vits Chinese -emoji: 🏃 -colorFrom: red -colorTo: yellow -sdk: gradio -sdk_version: 3.9 -app_file: app.py -pinned: false -duplicated_from: EDGAhab/VITS-Aatrox-AI ---- diff --git a/spaces/EnigmaOfTheWorld/MemeWorld/app.py b/spaces/EnigmaOfTheWorld/MemeWorld/app.py deleted file mode 100644 index c2acc0debf558e1f9cf656932b480873f7d6c18a..0000000000000000000000000000000000000000 --- a/spaces/EnigmaOfTheWorld/MemeWorld/app.py +++ /dev/null @@ -1,92 +0,0 @@ -import os -import re - -import gradio as gr -from transformers import AutoTokenizer, ViTFeatureExtractor, VisionEncoderDecoderModel -import openai - - - -openai.api_key = os.environ['OPENAI_KEY'] - - -## Training models -device='cpu' -encoder_checkpoint = "nlpconnect/vit-gpt2-image-captioning" -decoder_checkpoint = "nlpconnect/vit-gpt2-image-captioning" -model_checkpoint = "nlpconnect/vit-gpt2-image-captioning" -feature_extractor = ViTFeatureExtractor.from_pretrained(encoder_checkpoint) -tokenizer = AutoTokenizer.from_pretrained(decoder_checkpoint) -model = VisionEncoderDecoderModel.from_pretrained(model_checkpoint).to(device) - - -## READING THE IMAGE -## Extracting features from image -## then create a context for the image like -## Then input the department and context extracted and send it to LLM to get captio meme -def predict(department,image,max_length=64, num_beams=4): - image = image.convert('RGB') - image = feature_extractor(image, return_tensors="pt").pixel_values.to(device) - print(image) - clean_text = lambda x: x.replace('<|endoftext|>','').split('\n')[0] - print(clean_text) - caption_ids = model.generate(image, max_length = max_length)[0] - print(caption_ids) - caption_text = clean_text(tokenizer.decode(caption_ids)) - print(caption_text) - dept=department - context= caption_text - response = openai.Completion.create( - model="text-davinci-003", - prompt=f'create non offensive one line meme for given department and context\n\ndepartment- data science\ncontext-a man sitting on a bench with a laptop\nmeme- \"I\'m not a data scientist, but I play one on my laptop.\"\n\ndepartment-startup\ncontext-a young boy is smiling while using a laptop\nmeme-\"When your startup gets funded and you can finally afford a new laptop\"\n\ndepartment- {dept}\ncontext-{context}\nmeme-', - max_tokens=20, - temperature=0.8) - reponse = response.choices[0].text - reponse = reponse.replace("department", "") - Feedback_SQL="DEPT"+dept+"CAPT"+caption_text+"MAMAY"+reponse - - - return reponse - - - - - - - -output = gr.outputs.Textbox(type="text",label="Meme") - -examples = [f"example{i}.png" for i in range(1,7)] - - -## GRADIO INTERFACE - - -description= " Looking for a fun and easy way to generate memes? Look no further than Meme world! Leveraging large language models like GPT-3PT-3 / Ai21 / Cohere, you can create memes that are sure to be a hit with your friends or network. Created with ♥️ by Arsalan @[Xaheen](https://www.linkedin.com/in/sallu-mandya/). kindly share your thoughts in discussion session and use the app responsibly #NO_Offense \n \n built with ❤️ @[Xhaheen](https://www.linkedin.com/in/sallu-mandya/)" -title = "Meme world 🖼️" -dropdown=["data science", "product management","marketing","startup" ,"agile","crypto" , "SEO" ] - -article = "Created By : Xaheen " -theme = gr.themes.Glass( - primary_hue="cyan", - - neutral_hue="gray",font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], -) - -interface = gr.Interface( - fn=predict, - inputs = [gr.inputs.Dropdown(dropdown),gr.inputs.Image(label="Upload your Image", type = 'pil', optional=True)], - - theme=theme, - outputs=output, - examples =[['data science', 'example5.png'], - ['product management', 'example2.png'], - ['startup', 'example3.png'], - ['marketing', 'example4.png'], - ['agile', 'example1.png'], - ['crypto', 'example6.png']], - title=title, - description=description, - article = article - ) -interface.launch(debug=True) \ No newline at end of file diff --git a/spaces/FathomNet/fathomnet2023-comp-baseline/README.md b/spaces/FathomNet/fathomnet2023-comp-baseline/README.md deleted file mode 100644 index 4baa5014893ac07b485066456f53f90dc7bbd574..0000000000000000000000000000000000000000 --- a/spaces/FathomNet/fathomnet2023-comp-baseline/README.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -title: FathomNet2023 Competition Baseline -emoji: 📊 -colorFrom: blue -colorTo: red -sdk: gradio -sdk_version: 3.40.1 -app_file: app.py -pinned: false -license: cc-by-4.0 ---- diff --git a/spaces/Gen-Sim/Gen-Sim/gensim/agent.py b/spaces/Gen-Sim/Gen-Sim/gensim/agent.py deleted file mode 100644 index 3ebe07c16657c51ac960c115e276e185356a9406..0000000000000000000000000000000000000000 --- a/spaces/Gen-Sim/Gen-Sim/gensim/agent.py +++ /dev/null @@ -1,162 +0,0 @@ -import numpy as np -import os -import IPython -import random -import json -import traceback -import pybullet as p -from gensim.utils import ( - save_text, - add_to_txt, - extract_code, - extract_dict, - extract_list, - extract_assets, - format_dict_prompt, - sample_list_reference, - generate_feedback, -) - - -class Agent: - """ - class that design new tasks and codes for simulation environments - """ - def __init__(self, cfg, memory): - self.cfg = cfg - self.model_output_dir = cfg["model_output_dir"] - self.prompt_folder = f"prompts/{cfg['prompt_folder']}" - self.memory = memory - self.chat_log = memory.chat_log - self.use_template = cfg['use_template'] - - def propose_task(self, proposed_task_names): - """Language descriptions for the task""" - add_to_txt(self.chat_log, "================= Task and Asset Design!", with_print=True) - - if self.use_template: - task_prompt_text = open(f"{self.prompt_folder}/cliport_prompt_task.txt").read() - task_asset_replacement_str = format_dict_prompt(self.memory.online_asset_buffer, self.cfg['task_asset_candidate_num']) - task_prompt_text = task_prompt_text.replace("TASK_ASSET_PROMPT", task_asset_replacement_str) - - task_desc_replacement_str = format_dict_prompt(self.memory.online_task_buffer, self.cfg['task_description_candidate_num']) - print("prompt task description candidates:") - print(task_desc_replacement_str) - task_prompt_text = task_prompt_text.replace("TASK_DESCRIPTION_PROMPT", task_desc_replacement_str) - - if len(self.cfg['target_task_name']) > 0: - task_prompt_text = task_prompt_text.replace("TARGET_TASK_NAME", self.cfg['target_task_name']) - - # print("Template Task PROMPT: ", task_prompt_text) - else: - task_prompt_text = open(f"{self.prompt_folder}/cliport_prompt_task.txt").read() - - # maximum number - print("online_task_buffer size:", len(self.memory.online_task_buffer)) - total_tasks = self.memory.online_task_buffer - - MAX_NUM = 10 - if len(total_tasks) > MAX_NUM: - total_tasks = dict(random.sample(total_tasks.items(), MAX_NUM)) - - task_prompt_text = task_prompt_text.replace("PAST_TASKNAME_TEMPLATE", format_dict_prompt(total_tasks)) - - res = generate_feedback( - task_prompt_text, - temperature=self.cfg["gpt_temperature"], - interaction_txt=self.chat_log, - ) - - # Extract dictionary for task name, descriptions, and assets - task_def = extract_dict(res, prefix="new_task") - try: - exec(task_def, globals()) - self.new_task = new_task - return new_task - except: - self.new_task = {"task-name": "dummy", "assets-used": [], "task_descriptions": ""} - print(str(traceback.format_exc())) - return self.new_task - - def propose_assets(self): - """Asset Generation. Not used for now.""" - if os.path.exists(f"{self.prompt_folder}/cliport_prompt_asset_template.txt"): - add_to_txt(self.chat_log, "================= Asset Generation!", with_print=True) - asset_prompt_text = open(f"{self.prompt_folder}/cliport_prompt_asset_template.txt").read() - - if self.use_template: - asset_prompt_text = asset_prompt_text.replace("TASK_NAME_TEMPLATE", self.new_task["task-name"]) - asset_prompt_text = asset_prompt_text.replace("ASSET_STRING_TEMPLATE", str(self.new_task["assets-used"])) - print("Template Asset PROMPT: ", asset_prompt_text) - - res = generate_feedback(asset_prompt_text, temperature=0, interaction_txt=self.chat_log) - print("Save asset to:", self.model_output_dir, task_name + "_asset_output") - save_text(self.model_output_dir, f'{self.new_task["task-name"]}_asset_output', res) - asset_list = extract_assets(res) - # save_urdf(asset_list) - else: - asset_list = {} - return asset_list - - def api_review(self): - """review the task api""" - if os.path.exists(f"{self.prompt_folder}/cliport_prompt_api_template.txt"): - add_to_txt( - self.chat_log, "================= API Preview!", with_print=True) - api_prompt_text = open( - f"{self.prompt_folder}/cliport_prompt_api_template.txt").read() - if "task-name" in self.new_task: - api_prompt_text = api_prompt_text.replace("TASK_NAME_TEMPLATE", self.new_task["task-name"]) - api_prompt_text = api_prompt_text.replace("TASK_STRING_TEMPLATE", str(self.new_task)) - - res = generate_feedback( - api_prompt_text, temperature=0, interaction_txt=self.chat_log) - - def template_reference_prompt(self): - """ select which code reference to reference """ - if os.path.exists(f"{self.prompt_folder}/cliport_prompt_code_reference_selection_template.txt"): - self.chat_log = add_to_txt(self.chat_log, "================= Code Reference!", with_print=True) - code_reference_question = open(f'{self.prompt_folder}/cliport_prompt_code_reference_selection_template.txt').read() - code_reference_question = code_reference_question.replace("TASK_NAME_TEMPLATE", self.new_task["task-name"]) - code_reference_question = code_reference_question.replace("TASK_CODE_LIST_TEMPLATE", str(list(self.memory.online_code_buffer.keys()))) - - code_reference_question = code_reference_question.replace("TASK_STRING_TEMPLATE", str(self.new_task)) - res = generate_feedback(code_reference_question, temperature=0., interaction_txt=self.chat_log) - code_reference_cmd = extract_list(res, prefix='code_reference') - exec(code_reference_cmd, globals()) - task_code_reference_replace_prompt = '' - for key in code_reference_cmd: - if key in self.memory.online_code_buffer: - task_code_reference_replace_prompt += f'```\n{self.memory.online_code_buffer[key]}\n```\n\n' - else: - print("missing task reference code:", key) - else: - task_code_reference_replace_prompt = sample_list_reference(base_task_codes, sample_num=cfg['task_code_candidate_num']) - # print("Template Reference Code PROMPT: ", task_code_reference_replace_prompt) - - return task_code_reference_replace_prompt - - def implement_task(self): - """Generate Code for the task""" - code_prompt_text = open(f"{self.prompt_folder}/cliport_prompt_code_split_template.txt").read() - code_prompt_text = code_prompt_text.replace("TASK_NAME_TEMPLATE", self.new_task["task-name"]) - - if self.use_template or os.path.exists(f"{self.prompt_folder}/cliport_prompt_code_reference_selection_template.txt"): - task_code_reference_replace_prompt = self.template_reference_prompt() - code_prompt_text = code_prompt_text.replace("TASK_CODE_REFERENCE_TEMPLATE", task_code_reference_replace_prompt) - - elif os.path.exists(f"{self.prompt_folder}/cliport_prompt_code_split_template.txt"): - self.chat_log = add_to_txt(self.chat_log, "================= Code Generation!", with_print=True) - code_prompt_text = code_prompt_text.replace("TASK_STRING_TEMPLATE", str(self.new_task)) - - res = generate_feedback( - code_prompt_text, temperature=0, interaction_txt=self.chat_log) - code, task_name = extract_code(res) - print("Save code to:", self.model_output_dir, task_name + "_code_output") - save_text(self.model_output_dir, task_name + "_code_output", code) - - if len(task_name) == 0: - print("empty task name:", task_name) - return None - - return code, task_name diff --git a/spaces/Gradio-Blocks/uniformer_image_detection/configs/groie/faster_rcnn_r50_fpn_groie_1x_coco.py b/spaces/Gradio-Blocks/uniformer_image_detection/configs/groie/faster_rcnn_r50_fpn_groie_1x_coco.py deleted file mode 100644 index 0fc528bfd49bfc9a262692db78a5f94b46c285af..0000000000000000000000000000000000000000 --- a/spaces/Gradio-Blocks/uniformer_image_detection/configs/groie/faster_rcnn_r50_fpn_groie_1x_coco.py +++ /dev/null @@ -1,25 +0,0 @@ -_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' -# model settings -model = dict( - roi_head=dict( - bbox_roi_extractor=dict( - type='GenericRoIExtractor', - aggregation='sum', - roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=2), - out_channels=256, - featmap_strides=[4, 8, 16, 32], - pre_cfg=dict( - type='ConvModule', - in_channels=256, - out_channels=256, - kernel_size=5, - padding=2, - inplace=False, - ), - post_cfg=dict( - type='GeneralizedAttention', - in_channels=256, - spatial_range=-1, - num_heads=6, - attention_type='0100', - kv_stride=2)))) diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py deleted file mode 100644 index 1056ad4d1e2a4f956d12f6daf506620fab27dd17..0000000000000000000000000000000000000000 --- a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py +++ /dev/null @@ -1,7 +0,0 @@ -_base_ = [ - '../_base_/models/deeplabv3plus_r50-d8.py', - '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', - '../_base_/schedules/schedule_20k.py' -] -model = dict( - decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/backbones/mobilenet_v3.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/backbones/mobilenet_v3.py deleted file mode 100644 index f2e9a0cc00a9e79fda5e5d1ce963c2523397afd2..0000000000000000000000000000000000000000 --- a/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/backbones/mobilenet_v3.py +++ /dev/null @@ -1,255 +0,0 @@ -import logging - -import mmcv -import torch.nn as nn -from mmcv.cnn import ConvModule, constant_init, kaiming_init -from mmcv.cnn.bricks import Conv2dAdaptivePadding -from mmcv.runner import load_checkpoint -from torch.nn.modules.batchnorm import _BatchNorm - -from ..builder import BACKBONES -from ..utils import InvertedResidualV3 as InvertedResidual - - -@BACKBONES.register_module() -class MobileNetV3(nn.Module): - """MobileNetV3 backbone. - - This backbone is the improved implementation of `Searching for MobileNetV3 -" - else: - html_text += f"{text.strip()}... " - print(text) - html = f""" -
-
-
-
-
- 
-
-
-
- {title}
-
- {html_text}
-
- """ - return st.markdown(html, unsafe_allow_html=True) - -if query != "": - print(f"query: {query}") - matches = make_query(query, retriever, top_k=10) - - results = {} - order = [] - for context in matches: - video_id = context['metadata']['url'].split('/')[-1] - if video_id not in results: - results[video_id] = { - 'title': context['metadata']['title'], - 'urls': [f"{context['metadata']['url']}?t={int(context['metadata']['start'])}"], - 'contexts': [context['metadata']['text']], - 'starts': [int(context['metadata']['start'])], - 'ends': [int(context['metadata']['end'])] - } - order.append(video_id) - else: - results[video_id]['urls'].append( - f"{context['metadata']['url']}?t={int(context['metadata']['start'])}" - ) - results[video_id]['contexts'].append( - context['metadata']['text'] - ) - results[video_id]['starts'].append(int(context['metadata']['start'])) - results[video_id]['ends'].append(int(context['metadata']['end'])) - # now display cards - for video_id in order: - thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" - title = results[video_id]['title'] - urls = results[video_id]['urls'] - contexts = results[video_id]['contexts'] - starts = results[video_id]['starts'] - ends = results[video_id]['ends'] - card( - thumbnail=thumbnail, - title=title, - urls=urls, - contexts=contexts, - starts=starts, - ends=ends - ) \ No newline at end of file diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py deleted file mode 100644 index 3b10f4b2ac720e096db27b7e54dcc75611f92dfa..0000000000000000000000000000000000000000 --- a/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -# Copyright (c) OpenMMLab. All rights reserved. -from .f_metric import F1Metric -from .hmean_iou_metric import HmeanIOUMetric -from .recog_metric import CharMetric, OneMinusNEDMetric, WordMetric - -__all__ = [ - 'WordMetric', 'CharMetric', 'OneMinusNEDMetric', 'HmeanIOUMetric', - 'F1Metric' -] diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py deleted file mode 100644 index 26edafb79869c840ec9362faef7a871759d15d3b..0000000000000000000000000000000000000000 --- a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py +++ /dev/null @@ -1,12 +0,0 @@ -# Copyright (c) OpenMMLab. All rights reserved. -from mmengine.model import BaseModule - -from mmocr.registry import MODELS - - -@MODELS.register_module() -class BaseEncoder(BaseModule): - """Base Encoder class for text recognition.""" - - def forward(self, feat, **kwargs): - return feat diff --git a/spaces/MrBodean/VoiceClone/synthesizer/hparams.py b/spaces/MrBodean/VoiceClone/synthesizer/hparams.py deleted file mode 100644 index f7d38f0aa4c34d11349e40dbb9861b1aec2dcb8b..0000000000000000000000000000000000000000 --- a/spaces/MrBodean/VoiceClone/synthesizer/hparams.py +++ /dev/null @@ -1,92 +0,0 @@ -import ast -import pprint - -class HParams(object): - def __init__(self, **kwargs): self.__dict__.update(kwargs) - def __setitem__(self, key, value): setattr(self, key, value) - def __getitem__(self, key): return getattr(self, key) - def __repr__(self): return pprint.pformat(self.__dict__) - - def parse(self, string): - # Overrides hparams from a comma-separated string of name=value pairs - if len(string) > 0: - overrides = [s.split("=") for s in string.split(",")] - keys, values = zip(*overrides) - keys = list(map(str.strip, keys)) - values = list(map(str.strip, values)) - for k in keys: - self.__dict__[k] = ast.literal_eval(values[keys.index(k)]) - return self - -hparams = HParams( - ### Signal Processing (used in both synthesizer and vocoder) - sample_rate = 16000, - n_fft = 800, - num_mels = 80, - hop_size = 200, # Tacotron uses 12.5 ms frame shift (set to sample_rate * 0.0125) - win_size = 800, # Tacotron uses 50 ms frame length (set to sample_rate * 0.050) - fmin = 55, - min_level_db = -100, - ref_level_db = 20, - max_abs_value = 4., # Gradient explodes if too big, premature convergence if too small. - preemphasis = 0.97, # Filter coefficient to use if preemphasize is True - preemphasize = True, - - ### Tacotron Text-to-Speech (TTS) - tts_embed_dims = 512, # Embedding dimension for the graphemes/phoneme inputs - tts_encoder_dims = 256, - tts_decoder_dims = 128, - tts_postnet_dims = 512, - tts_encoder_K = 5, - tts_lstm_dims = 1024, - tts_postnet_K = 5, - tts_num_highways = 4, - tts_dropout = 0.5, - tts_cleaner_names = ["english_cleaners"], - tts_stop_threshold = -3.4, # Value below which audio generation ends. - # For example, for a range of [-4, 4], this - # will terminate the sequence at the first - # frame that has all values < -3.4 - - ### Tacotron Training - tts_schedule = [(2, 1e-3, 20_000, 12), # Progressive training schedule - (2, 5e-4, 40_000, 12), # (r, lr, step, batch_size) - (2, 2e-4, 80_000, 12), # - (2, 1e-4, 160_000, 12), # r = reduction factor (# of mel frames - (2, 3e-5, 320_000, 12), # synthesized for each decoder iteration) - (2, 1e-5, 640_000, 12)], # lr = learning rate - - tts_clip_grad_norm = 1.0, # clips the gradient norm to prevent explosion - set to None if not needed - tts_eval_interval = 500, # Number of steps between model evaluation (sample generation) - # Set to -1 to generate after completing epoch, or 0 to disable - - tts_eval_num_samples = 1, # Makes this number of samples - - ### Data Preprocessing - max_mel_frames = 900, - rescale = True, - rescaling_max = 0.9, - synthesis_batch_size = 16, # For vocoder preprocessing and inference. - - ### Mel Visualization and Griffin-Lim - signal_normalization = True, - power = 1.5, - griffin_lim_iters = 60, - - ### Audio processing options - fmax = 7600, # Should not exceed (sample_rate // 2) - allow_clipping_in_normalization = True, # Used when signal_normalization = True - clip_mels_length = True, # If true, discards samples exceeding max_mel_frames - use_lws = False, # "Fast spectrogram phase recovery using local weighted sums" - symmetric_mels = True, # Sets mel range to [-max_abs_value, max_abs_value] if True, - # and [0, max_abs_value] if False - trim_silence = True, # Use with sample_rate of 16000 for best results - - ### SV2TTS - speaker_embedding_size = 256, # Dimension for the speaker embedding - silence_min_duration_split = 0.4, # Duration in seconds of a silence for an utterance to be split - utterance_min_duration = 1.6, # Duration in seconds below which utterances are discarded - ) - -def hparams_debug_string(): - return str(hparams) diff --git a/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py b/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py deleted file mode 100644 index 2c98d880d6b0b76ddb21f1bd516c4ce90515b8f3..0000000000000000000000000000000000000000 --- a/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py +++ /dev/null @@ -1,103 +0,0 @@ -""" -Preprocess a raw json dataset into features files for use in data_loader.py - -Input: json file that has the form -[{ file_path: 'path/img.jpg', captions: ['a caption', ...] }, ...] -example element in this list would look like -{'captions': [u'A man with a red helmet on a small moped on a dirt road. ', u'Man riding a motor bike on a dirt road on the countryside.', u'A man riding on the back of a motorcycle.', u'A dirt path with a young person on a motor bike rests to the foreground of a verdant area with a bridge and a background of cloud-wreathed mountains. ', u'A man in a red shirt and a red hat is on a motorcycle on a hill side.'], 'file_path': u'val2014/COCO_val2014_000000391895.jpg', 'id': 391895} - -This script reads this json, does some basic preprocessing on the captions -(e.g. lowercase, etc.), creates a special UNK token, and encodes everything to arrays - -Output: two folders of features -""" - -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function - -import os -import json -import argparse -from random import shuffle, seed -import string -# non-standard dependencies: -import h5py -from six.moves import cPickle -import numpy as np -import torch -import torchvision.models as models -import skimage.io - -from torchvision import transforms as trn -preprocess = trn.Compose([ - #trn.ToTensor(), - trn.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) -]) - -from captioning.utils.resnet_utils import myResnet -import captioning.utils.resnet as resnet - - -def main(params): - net = getattr(resnet, params['model'])() - net.load_state_dict(torch.load(os.path.join(params['model_root'],params['model']+'.pth'))) - my_resnet = myResnet(net) - my_resnet.cuda() - my_resnet.eval() - - imgs = json.load(open(params['input_json'], 'r')) - imgs = imgs['images'] - N = len(imgs) - - seed(123) # make reproducible - - dir_fc = params['output_dir']+'_fc' - dir_att = params['output_dir']+'_att' - if not os.path.isdir(dir_fc): - os.mkdir(dir_fc) - if not os.path.isdir(dir_att): - os.mkdir(dir_att) - - for i,img in enumerate(imgs): - # load the image - I = skimage.io.imread(os.path.join(params['images_root'], img['filepath'], img['filename'])) - # handle grayscale input images - if len(I.shape) == 2: - I = I[:,:,np.newaxis] - I = np.concatenate((I,I,I), axis=2) - - I = I.astype('float32')/255.0 - I = torch.from_numpy(I.transpose([2,0,1])).cuda() - I = preprocess(I) - with torch.no_grad(): - tmp_fc, tmp_att = my_resnet(I, params['att_size']) - # write to pkl - # print(dir_fc, str(img['cocoid']), tmp_fc.shape, tmp_att.shape, dir_att) - # exit() - np.save(os.path.join(dir_fc, str(img['cocoid'])), tmp_fc.data.cpu().float().numpy()) - np.savez_compressed(os.path.join(dir_att, str(img['cocoid'])), feat=tmp_att.data.cpu().float().numpy()) - - if i % 1000 == 0: - print('processing %d/%d (%.2f%% done)' % (i, N, i*100.0/N)) - print('wrote ', params['output_dir']) - -if __name__ == "__main__": - - parser = argparse.ArgumentParser() - - # input json - parser.add_argument('--input_json', required=True, help='input json file to process into hdf5') - parser.add_argument('--output_dir', default='data', help='output h5 file') - - # options - parser.add_argument('--images_root', default='', help='root location in which images are stored, to be prepended to file_path in input json') - parser.add_argument('--att_size', default=14, type=int, help='14x14 or 7x7') - parser.add_argument('--model', default='resnet101', type=str, help='resnet101, resnet152') - parser.add_argument('--model_root', default='./data/imagenet_weights', type=str, help='model root') - - args = parser.parse_args() - params = vars(args) # convert to ordinary dict - print('parsed input parameters:') - print(json.dumps(params, indent = 2)) - main(params) diff --git a/spaces/NCTCMumbai/NCTC/models/research/cognitive_mapping_and_planning/render/__init__.py b/spaces/NCTCMumbai/NCTC/models/research/cognitive_mapping_and_planning/render/__init__.py deleted file mode 100644 index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000 diff --git a/spaces/NeuralInternet/Text-Generation_Playground/download-model.py b/spaces/NeuralInternet/Text-Generation_Playground/download-model.py deleted file mode 100644 index 8be398c4e0d3ca0c0a915efb442f432fc2056834..0000000000000000000000000000000000000000 --- a/spaces/NeuralInternet/Text-Generation_Playground/download-model.py +++ /dev/null @@ -1,176 +0,0 @@ -''' -Downloads models from Hugging Face to models/model-name. - -Example: -python download-model.py facebook/opt-1.3b - -''' - -import argparse -import base64 -import json -import multiprocessing -import re -import sys -from pathlib import Path - -import requests -import tqdm - -parser = argparse.ArgumentParser() -parser.add_argument('MODEL', type=str, default=None, nargs='?') -parser.add_argument('--branch', type=str, default='main', help='Name of the Git branch to download from.') -parser.add_argument('--threads', type=int, default=1, help='Number of files to download simultaneously.') -parser.add_argument('--text-only', action='store_true', help='Only download text files (txt/json).') -args = parser.parse_args() - -def get_file(args): - url = args[0] - output_folder = args[1] - idx = args[2] - tot = args[3] - - print(f"Downloading file {idx} of {tot}...") - r = requests.get(url, stream=True) - with open(output_folder / Path(url.split('/')[-1]), 'wb') as f: - total_size = int(r.headers.get('content-length', 0)) - block_size = 1024 - t = tqdm.tqdm(total=total_size, unit='iB', unit_scale=True) - for data in r.iter_content(block_size): - t.update(len(data)) - f.write(data) - t.close() - -def sanitize_branch_name(branch_name): - pattern = re.compile(r"^[a-zA-Z0-9._-]+$") - if pattern.match(branch_name): - return branch_name - else: - raise ValueError("Invalid branch name. Only alphanumeric characters, period, underscore and dash are allowed.") - -def select_model_from_default_options(): - models = { - "Pygmalion 6B original": ("PygmalionAI", "pygmalion-6b", "b8344bb4eb76a437797ad3b19420a13922aaabe1"), - "Pygmalion 6B main": ("PygmalionAI", "pygmalion-6b", "main"), - "Pygmalion 6B dev": ("PygmalionAI", "pygmalion-6b", "dev"), - "Pygmalion 2.7B": ("PygmalionAI", "pygmalion-2.7b", "main"), - "Pygmalion 1.3B": ("PygmalionAI", "pygmalion-1.3b", "main"), - "Pygmalion 350m": ("PygmalionAI", "pygmalion-350m", "main"), - "OPT 6.7b": ("facebook", "opt-6.7b", "main"), - "OPT 2.7b": ("facebook", "opt-2.7b", "main"), - "OPT 1.3b": ("facebook", "opt-1.3b", "main"), - "OPT 350m": ("facebook", "opt-350m", "main"), - } - choices = {} - - print("Select the model that you want to download:\n") - for i,name in enumerate(models): - char = chr(ord('A')+i) - choices[char] = name - print(f"{char}) {name}") - char = chr(ord('A')+len(models)) - print(f"{char}) None of the above") - - print() - print("Input> ", end='') - choice = input()[0].strip().upper() - if choice == char: - print("""\nThen type the name of your desired Hugging Face model in the format organization/name. - -Examples: -PygmalionAI/pygmalion-6b -facebook/opt-1.3b -""") - - print("Input> ", end='') - model = input() - branch = "main" - else: - arr = models[choices[choice]] - model = f"{arr[0]}/{arr[1]}" - branch = arr[2] - - return model, branch - -def get_download_links_from_huggingface(model, branch): - base = "https://huggingface.co" - page = f"/api/models/{model}/tree/{branch}?cursor=" - cursor = b"" - - links = [] - classifications = [] - has_pytorch = False - has_safetensors = False - while True: - content = requests.get(f"{base}{page}{cursor.decode()}").content - - dict = json.loads(content) - if len(dict) == 0: - break - - for i in range(len(dict)): - fname = dict[i]['path'] - - is_pytorch = re.match("pytorch_model.*\.bin", fname) - is_safetensors = re.match("model.*\.safetensors", fname) - is_tokenizer = re.match("tokenizer.*\.model", fname) - is_text = re.match(".*\.(txt|json)", fname) or is_tokenizer - - if any((is_pytorch, is_safetensors, is_text, is_tokenizer)): - if is_text: - links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}") - classifications.append('text') - continue - if not args.text_only: - links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}") - if is_safetensors: - has_safetensors = True - classifications.append('safetensors') - elif is_pytorch: - has_pytorch = True - classifications.append('pytorch') - - cursor = base64.b64encode(f'{{"file_name":"{dict[-1]["path"]}"}}'.encode()) + b':50' - cursor = base64.b64encode(cursor) - cursor = cursor.replace(b'=', b'%3D') - - # If both pytorch and safetensors are available, download safetensors only - if has_pytorch and has_safetensors: - for i in range(len(classifications)-1, -1, -1): - if classifications[i] == 'pytorch': - links.pop(i) - - return links - -if __name__ == '__main__': - model = args.MODEL - branch = args.branch - if model is None: - model, branch = select_model_from_default_options() - else: - if model[-1] == '/': - model = model[:-1] - branch = args.branch - if branch is None: - branch = "main" - else: - try: - branch = sanitize_branch_name(branch) - except ValueError as err_branch: - print(f"Error: {err_branch}") - sys.exit() - if branch != 'main': - output_folder = Path("models") / (model.split('/')[-1] + f'_{branch}') - else: - output_folder = Path("models") / model.split('/')[-1] - if not output_folder.exists(): - output_folder.mkdir() - - links = get_download_links_from_huggingface(model, branch) - - # Downloading the files - print(f"Downloading the model to {output_folder}") - pool = multiprocessing.Pool(processes=args.threads) - results = pool.map(get_file, [[links[i], output_folder, i+1, len(links)] for i in range(len(links))]) - pool.close() - pool.join() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py deleted file mode 100644 index 7e2caa03400129ac0bb34ae35274cdf46f27a055..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import torch -from fairseq import utils -from fairseq.modules import TransformerEncoderLayer - -from .multihead_linear_attention import MultiheadLinearAttention - - -class LinformerTransformerEncoderLayer(TransformerEncoderLayer): - """ - Implements a Linformer Encoder Layer used in BERT/XLM style pre-trained - models. - """ - - def __init__(self, args, shared_compress_layer): - # wrap in a list so it's not automatically registered by PyTorch - self.shared_compress_layer = [shared_compress_layer] - - super().__init__(args) - - self.register_buffer("version", torch.tensor(2)) - - def build_self_attention(self, embed_dim, args): - return MultiheadLinearAttention( - embed_dim, - args.encoder_attention_heads, - dropout=args.dropout, - self_attention=True, - q_noise=args.quant_noise_pq, - qn_block_size=args.quant_noise_pq_block_size, - compressed=args.compressed, - max_seq_len=args.max_positions, - shared_kv_compressed=args.shared_kv_compressed, - shared_compress_layer=self.shared_compress_layer[0], - freeze_compress=args.freeze_compress, - ) - - def upgrade_state_dict_named(self, state_dict, name): - super().upgrade_state_dict_named(state_dict, name) - prefix = name + "." if name != "" else "" - - # some old checkpoints had weight sharing implemented incorrectly - # (note: this was correct in the original paper code) - if utils.item(state_dict.get(f"{prefix}version", torch.tensor(1))) < 2: - state_dict[f"{prefix}version"] = torch.tensor(1) - # check compression layer sharing - if f"{prefix}shared_compress_layer.weight" in state_dict: - # reinitialize block without sharing compression layer to match - # old behavior - self.shared_compress_layer = [ - torch.nn.Linear( - self.shared_compress_layer[0].weight.size(1), - self.shared_compress_layer[0].weight.size(0), - ) - ] - self.self_attn = self.build_self_attention(self.embed_dim, self.args) - # delete shared_compress_layer, since it's already copied to - # self_attn.compress_k.weight - del state_dict[f"{prefix}shared_compress_layer.weight"] - if f"{prefix}shared_compress_layer.bias" in state_dict: - del state_dict[f"{prefix}shared_compress_layer.bias"] diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py deleted file mode 100644 index 43fe0451bf4d5762d734314075b1402c2a8db2bb..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py +++ /dev/null @@ -1,130 +0,0 @@ -#!/usr/bin/env python -# Copyright (c) Facebook, Inc. and its affiliates. -# All rights reserved. -# -# This source code is licensed under the license found in the -# LICENSE file in the root directory of this source tree. - -import argparse -import contextlib -import sys -from collections import Counter -from multiprocessing import Pool - -from fairseq.data.encoders.gpt2_bpe import get_encoder - - -def main(): - """ - Helper script to encode raw text with the GPT-2 BPE using multiple processes. - - The encoder.json and vocab.bpe files can be obtained here: - - https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/encoder.json - - https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/vocab.bpe - """ - parser = argparse.ArgumentParser() - parser.add_argument( - "--encoder-json", - help="path to encoder.json", - ) - parser.add_argument( - "--vocab-bpe", - type=str, - help="path to vocab.bpe", - ) - parser.add_argument( - "--inputs", - nargs="+", - default=["-"], - help="input files to filter/encode", - ) - parser.add_argument( - "--outputs", - nargs="+", - default=["-"], - help="path to save encoded outputs", - ) - parser.add_argument( - "--keep-empty", - action="store_true", - help="keep empty lines", - ) - parser.add_argument("--workers", type=int, default=20) - args = parser.parse_args() - - assert len(args.inputs) == len( - args.outputs - ), "number of input and output paths should match" - - with contextlib.ExitStack() as stack: - inputs = [ - stack.enter_context(open(input, "r", encoding="utf-8")) - if input != "-" - else sys.stdin - for input in args.inputs - ] - outputs = [ - stack.enter_context(open(output, "w", encoding="utf-8")) - if output != "-" - else sys.stdout - for output in args.outputs - ] - - encoder = MultiprocessingEncoder(args) - pool = Pool(args.workers, initializer=encoder.initializer) - encoded_lines = pool.imap(encoder.encode_lines, zip(*inputs), 100) - - stats = Counter() - for i, (filt, enc_lines) in enumerate(encoded_lines, start=1): - if filt == "PASS": - for enc_line, output_h in zip(enc_lines, outputs): - print(enc_line, file=output_h) - else: - stats["num_filtered_" + filt] += 1 - if i % 10000 == 0: - print("processed {} lines".format(i), file=sys.stderr) - - for k, v in stats.most_common(): - print("[{}] filtered {} lines".format(k, v), file=sys.stderr) - - -class MultiprocessingEncoder(object): - def __init__(self, args): - self.args = args - - def initializer(self): - global bpe - bpe = get_encoder(self.args.encoder_json, self.args.vocab_bpe) - - def encode(self, line): - global bpe - ids = bpe.encode(line) - return list(map(str, ids)) - - def decode(self, tokens): - global bpe - return bpe.decode(tokens) - - def encode_lines(self, lines): - """ - Encode a set of lines. All lines will be encoded together. - """ - enc_lines = [] - for line in lines: - line = line.strip() - if len(line) == 0 and not self.args.keep_empty: - return ["EMPTY", None] - tokens = self.encode(line) - enc_lines.append(" ".join(tokens)) - return ["PASS", enc_lines] - - def decode_lines(self, lines): - dec_lines = [] - for line in lines: - tokens = map(int, line.strip().split()) - dec_lines.append(self.decode(tokens)) - return ["PASS", dec_lines] - - -if __name__ == "__main__": - main() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py deleted file mode 100644 index 257a96593ff7af93c206c066d8db4ad795b2ae36..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py +++ /dev/null @@ -1,15 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import importlib -import os - - -for file in sorted(os.listdir(os.path.dirname(__file__))): - if file.endswith(".py") and not file.startswith("_"): - model_name = file[: file.find(".py")] - importlib.import_module( - "examples.simultaneous_translation.models." + model_name - ) diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py deleted file mode 100644 index 7ec1fb7521b8a9b821d28bcaaaedb034f6e95e0b..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py +++ /dev/null @@ -1,70 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import argparse -import logging -from pathlib import Path -from collections import defaultdict - -import pandas as pd -from torchaudio.datasets import LJSPEECH -from tqdm import tqdm - -from examples.speech_to_text.data_utils import save_df_to_tsv - - -log = logging.getLogger(__name__) - -SPLITS = ["train", "dev", "test"] - - -def process(args): - out_root = Path(args.output_data_root).absolute() - out_root.mkdir(parents=True, exist_ok=True) - - # Generate TSV manifest - print("Generating manifest...") - # following FastSpeech's splits - dataset = LJSPEECH(out_root.as_posix(), download=True) - id_to_split = {} - for x in dataset._flist: - id_ = x[0] - speaker = id_.split("-")[0] - id_to_split[id_] = { - "LJ001": "test", "LJ002": "test", "LJ003": "dev" - }.get(speaker, "train") - manifest_by_split = {split: defaultdict(list) for split in SPLITS} - progress = tqdm(enumerate(dataset), total=len(dataset)) - for i, (waveform, _, utt, normalized_utt) in progress: - sample_id = dataset._flist[i][0] - split = id_to_split[sample_id] - manifest_by_split[split]["id"].append(sample_id) - audio_path = f"{dataset._path}/{sample_id}.wav" - manifest_by_split[split]["audio"].append(audio_path) - manifest_by_split[split]["n_frames"].append(len(waveform[0])) - manifest_by_split[split]["tgt_text"].append(normalized_utt) - manifest_by_split[split]["speaker"].append("ljspeech") - manifest_by_split[split]["src_text"].append(utt) - - manifest_root = Path(args.output_manifest_root).absolute() - manifest_root.mkdir(parents=True, exist_ok=True) - for split in SPLITS: - save_df_to_tsv( - pd.DataFrame.from_dict(manifest_by_split[split]), - manifest_root / f"{split}.audio.tsv" - ) - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument("--output-data-root", "-d", required=True, type=str) - parser.add_argument("--output-manifest-root", "-m", required=True, type=str) - args = parser.parse_args() - - process(args) - - -if __name__ == "__main__": - main() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md deleted file mode 100644 index 920ff271c2e178c7a4ca3c7c8ce57a2f28653969..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md +++ /dev/null @@ -1,76 +0,0 @@ -[[Back]](..) - -# Joint Speech Text Training for the 2021 IWSLT multilingual speech translation - -This directory contains the code from paper ["FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task"](https://arxiv.org/pdf/2107.06959.pdf). - -## Prepare Data -#### Download files -- Sentence piece model [spm.model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/spm.model) -- Dictionary [tgt_dict.txt](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/dict.txt) -- Config [config.yaml](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/config.yaml) - -#### Prepare -- [Please follow the data preparation in speech-to-text](https://github.com/pytorch/fairseq/blob/main/examples/speech_to_text/docs/mtedx_example.md) - - - -## Training - -#### Download pretrained models -- [Pretrained mbart model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/mbart.pt) -- [Pretrained w2v model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/xlsr_53_56k.pt) - - -#### Training scripts - -```bash -python train.py ${MANIFEST_ROOT} \ - --save-dir ${save_dir} \ - --user-dir examples/speech_text_joint_to_text \ - --train-subset train_es_en_tedx,train_es_es_tedx,train_fr_en_tedx,train_fr_es_tedx,train_fr_fr_tedx,train_it_it_tedx,train_pt_en_tedx,train_pt_pt_tedx \ - --valid-subset valid_es_en_tedx,valid_es_es_tedx,valid_es_fr_tedx,valid_es_it_tedx,valid_es_pt_tedx,valid_fr_en_tedx,valid_fr_es_tedx,valid_fr_fr_tedx,valid_fr_pt_tedx,valid_it_en_tedx,valid_it_es_tedx,valid_it_it_tedx,valid_pt_en_tedx,valid_pt_es_tedx,valid_pt_pt_tedx \ - --config-yaml config.yaml --ddp-backend no_c10d \ - --num-workers 2 --task speech_text_joint_to_text \ - --criterion guided_label_smoothed_cross_entropy_with_accuracy \ - --label-smoothing 0.3 --guide-alpha 0.8 \ - --disable-text-guide-update-num 5000 --arch dualinputxmtransformer_base \ - --max-tokens 500000 --max-sentences 3 --max-tokens-valid 800000 \ - --max-source-positions 800000 --enc-grad-mult 2.0 \ - --attentive-cost-regularization 0.02 --optimizer adam \ - --clip-norm 1.0 --log-format simple --log-interval 200 \ - --keep-last-epochs 5 --seed 1 \ - --w2v-path ${w2v_path} \ - --load-pretrained-mbart-from ${mbart_path} \ - --max-update 1000000 --update-freq 4 \ - --skip-invalid-size-inputs-valid-test \ - --skip-encoder-projection --save-interval 1 \ - --attention-dropout 0.3 --mbart-dropout 0.3 \ - --finetune-w2v-params all --finetune-mbart-decoder-params all \ - --finetune-mbart-encoder-params all --stack-w2v-mbart-encoder \ - --drop-w2v-layers 12 --normalize \ - --lr 5e-05 --lr-scheduler inverse_sqrt --warmup-updates 5000 -``` - -## Evaluation -```bash -python ./fairseq_cli/generate.py - ${MANIFEST_ROOT} \ - --task speech_text_joint_to_text \ - --user-dir ./examples/speech_text_joint_to_text \ - --load-speech-only --gen-subset test_es_en_tedx \ - --path ${model} \ - --max-source-positions 800000 \ - --skip-invalid-size-inputs-valid-test \ - --config-yaml config.yaml \ - --infer-target-lang en \ - --max-tokens 800000 \ - --beam 5 \ - --results-path ${RESULTS_DIR} \ - --scoring sacrebleu -``` -The trained model can be downloaded [here](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/checkpoint17.pt) - -|direction|es_en|fr_en|pt_en|it_en|fr_es|pt_es|it_es|es_es|fr_fr|pt_pt|it_it| -|---|---|---|---|---|---|---|---|---|---|---|---| -|BLEU|31.62|36.93|35.07|27.12|38.87|35.57|34.13|74.59|74.64|70.84|69.76| diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py deleted file mode 100644 index 6bbd0ae821b42ab693f4141e7c161d6d7cb0b15a..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py +++ /dev/null @@ -1,40 +0,0 @@ -import numpy as np -from fairseq.data.audio.feature_transforms import ( - AudioFeatureTransform, - register_audio_feature_transform, -) - - -@register_audio_feature_transform("utterance_cmvn") -class UtteranceCMVN(AudioFeatureTransform): - """Utterance-level CMVN (cepstral mean and variance normalization)""" - - @classmethod - def from_config_dict(cls, config=None): - _config = {} if config is None else config - return UtteranceCMVN( - _config.get("norm_means", True), - _config.get("norm_vars", True), - ) - - def __init__(self, norm_means=True, norm_vars=True): - self.norm_means, self.norm_vars = norm_means, norm_vars - - def __repr__(self): - return ( - self.__class__.__name__ - + f"(norm_means={self.norm_means}, norm_vars={self.norm_vars})" - ) - - def __call__(self, x): - mean = x.mean(axis=0) - square_sums = (x ** 2).sum(axis=0) - - if self.norm_means: - x = np.subtract(x, mean) - if self.norm_vars: - var = square_sums / x.shape[0] - mean ** 2 - std = np.sqrt(np.maximum(var, 1e-10)) - x = np.divide(x, std) - - return x diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py deleted file mode 100644 index 71d0b27cd2c0655fe3b00479b672d6d042a4d5ed..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py +++ /dev/null @@ -1,384 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. -""" -BART: Denoising Sequence-to-Sequence Pre-training for -Natural Language Generation, Translation, and Comprehension -""" -from typing import Optional - -import logging - -import torch -import torch.nn as nn -from fairseq import utils -from fairseq.models import register_model, register_model_architecture -from fairseq.models.transformer import TransformerModel -from fairseq.modules.transformer_sentence_encoder import init_bert_params - -from .hub_interface import BARTHubInterface - - -logger = logging.getLogger(__name__) - - -@register_model("bart") -class BARTModel(TransformerModel): - __jit_unused_properties__ = ["supported_targets"] - - @classmethod - def hub_models(cls): - return { - "bart.base": "http://dl.fbaipublicfiles.com/fairseq/models/bart.base.tar.gz", - "bart.large": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.tar.gz", - "bart.large.mnli": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.mnli.tar.gz", - "bart.large.cnn": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.cnn.tar.gz", - "bart.large.xsum": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.xsum.tar.gz", - } - - def __init__(self, args, encoder, decoder): - super().__init__(args, encoder, decoder) - - # We follow BERT's random weight initialization - self.apply(init_bert_params) - - self.classification_heads = nn.ModuleDict() - if hasattr(self.encoder, "dictionary"): - self.eos: int = self.encoder.dictionary.eos() - - @staticmethod - def add_args(parser): - super(BARTModel, BARTModel).add_args(parser) - parser.add_argument( - "--pooler-dropout", - type=float, - metavar="D", - help="dropout probability in the masked_lm pooler layers", - ) - parser.add_argument( - "--pooler-activation-fn", - choices=utils.get_available_activation_fns(), - help="activation function to use for pooler layer", - ) - parser.add_argument( - "--spectral-norm-classification-head", - action="store_true", - help="Apply spectral normalization on the classification head", - ) - - @property - def supported_targets(self): - return {"self"} - - def forward( - self, - src_tokens, - src_lengths, - prev_output_tokens, - features_only: bool = False, - classification_head_name: Optional[str] = None, - token_embeddings: Optional[torch.Tensor] = None, - return_all_hiddens: bool = True, - alignment_layer: Optional[int] = None, - alignment_heads: Optional[int] = None, - ): - if classification_head_name is not None: - features_only = True - - encoder_out = self.encoder( - src_tokens, - src_lengths=src_lengths, - token_embeddings=token_embeddings, - return_all_hiddens=return_all_hiddens - ) - x, extra = self.decoder( - prev_output_tokens, - encoder_out=encoder_out, - features_only=features_only, - alignment_layer=alignment_layer, - alignment_heads=alignment_heads, - src_lengths=src_lengths, - return_all_hiddens=return_all_hiddens, - ) - eos: int = self.eos - if classification_head_name is not None: - sentence_representation = x[ - src_tokens.eq(eos), : - ].view(x.size(0), -1, x.size(-1))[:, -1, :] - for k, head in self.classification_heads.items(): - # for torch script only supports iteration - if k == classification_head_name: - x = head(sentence_representation) - break - return x, extra - - @classmethod - def from_pretrained( - cls, - model_name_or_path, - checkpoint_file="model.pt", - data_name_or_path=".", - bpe="gpt2", - sample_break_mode="eos", - **kwargs, - ): - from fairseq import hub_utils - - x = hub_utils.from_pretrained( - model_name_or_path, - checkpoint_file, - data_name_or_path, - archive_map=cls.hub_models(), - bpe=bpe, - load_checkpoint_heads=True, - sample_break_mode=sample_break_mode, - **kwargs, - ) - return BARTHubInterface(x["args"], x["task"], x["models"][0]) - - def register_classification_head( - self, name, num_classes=None, inner_dim=None, **kwargs - ): - """Register a classification head.""" - logger.info("Registering classification head: {0}".format(name)) - if name in self.classification_heads: - prev_num_classes = self.classification_heads[name].out_proj.out_features - prev_inner_dim = self.classification_heads[name].dense.out_features - if num_classes != prev_num_classes or inner_dim != prev_inner_dim: - logger.warning( - 're-registering head "{}" with num_classes {} (prev: {}) ' - "and inner_dim {} (prev: {})".format( - name, num_classes, prev_num_classes, inner_dim, prev_inner_dim - ) - ) - self.classification_heads[name] = BARTClassificationHead( - input_dim=self.args.encoder_embed_dim, - inner_dim=inner_dim or self.args.encoder_embed_dim, - num_classes=num_classes, - activation_fn=self.args.pooler_activation_fn, - pooler_dropout=self.args.pooler_dropout, - do_spectral_norm=getattr( - self.args, "spectral_norm_classification_head", False - ), - ) - - def upgrade_state_dict_named(self, state_dict, name): - super().upgrade_state_dict_named(state_dict, name) - - prefix = name + "." if name != "" else "" - current_head_names = ( - [] - if not hasattr(self, "classification_heads") - else self.classification_heads.keys() - ) - - # Handle new classification heads present in the state dict. - keys_to_delete = [] - for k in state_dict.keys(): - if not k.startswith(prefix + "classification_heads."): - continue - - head_name = k[len(prefix + "classification_heads.") :].split(".")[0] - num_classes = state_dict[ - prefix + "classification_heads." + head_name + ".out_proj.weight" - ].size(0) - inner_dim = state_dict[ - prefix + "classification_heads." + head_name + ".dense.weight" - ].size(0) - - if getattr(self.args, "load_checkpoint_heads", False): - if head_name not in current_head_names: - self.register_classification_head(head_name, num_classes, inner_dim) - else: - if head_name not in current_head_names: - logger.warning( - "deleting classification head ({}) from checkpoint " - "not present in current model: {}".format(head_name, k) - ) - keys_to_delete.append(k) - elif ( - num_classes - != self.classification_heads[head_name].out_proj.out_features - or inner_dim - != self.classification_heads[head_name].dense.out_features - ): - logger.warning( - "deleting classification head ({}) from checkpoint " - "with different dimensions than current model: {}".format( - head_name, k - ) - ) - keys_to_delete.append(k) - for k in keys_to_delete: - del state_dict[k] - - def truncate_emb(key): - if key in state_dict: - state_dict[key] = state_dict[key][:-1, :] - - # When finetuning on translation task, remove last row of - # embedding matrix that corresponds to mask_idx token. - loaded_dict_size = state_dict["encoder.embed_tokens.weight"].size(0) - if ( - loaded_dict_size == len(self.encoder.dictionary) + 1 - and "" not in self.encoder.dictionary
- ):
- truncate_emb("encoder.embed_tokens.weight")
- truncate_emb("decoder.embed_tokens.weight")
- truncate_emb("encoder.output_projection.weight")
- truncate_emb("decoder.output_projection.weight")
-
- # When continued pretraining on new set of languages for mbart,
- # add extra lang embeddings at the end of embed_tokens.
- # Note: newly added languages are assumed to have been added at the end.
- if self.args.task == "multilingual_denoising" and loaded_dict_size < len(
- self.encoder.dictionary
- ):
- logger.info(
- "Adding extra language embeddings not found in pretrained model for "
- "continued pretraining of MBART on new set of languages."
- )
- loaded_mask_token_embedding = state_dict["encoder.embed_tokens.weight"][
- -1, :
- ]
-
- num_langids_to_add = len(self.encoder.dictionary) - loaded_dict_size
- embed_dim = state_dict["encoder.embed_tokens.weight"].size(1)
-
- new_lang_embed_to_add = torch.zeros(num_langids_to_add, embed_dim)
- nn.init.normal_(new_lang_embed_to_add, mean=0, std=embed_dim ** -0.5)
- new_lang_embed_to_add = new_lang_embed_to_add.to(
- dtype=state_dict["encoder.embed_tokens.weight"].dtype,
- )
-
- state_dict["encoder.embed_tokens.weight"] = torch.cat(
- [
- state_dict["encoder.embed_tokens.weight"][
- : loaded_dict_size - 1, :
- ],
- new_lang_embed_to_add,
- loaded_mask_token_embedding.unsqueeze(0),
- ]
- )
- state_dict["decoder.embed_tokens.weight"] = torch.cat(
- [
- state_dict["decoder.embed_tokens.weight"][
- : loaded_dict_size - 1, :
- ],
- new_lang_embed_to_add,
- loaded_mask_token_embedding.unsqueeze(0),
- ]
- )
-
- # Copy any newly-added classification heads into the state dict
- # with their current weights.
- if hasattr(self, "classification_heads"):
- cur_state = self.classification_heads.state_dict()
- for k, v in cur_state.items():
- if prefix + "classification_heads." + k not in state_dict:
- logger.info("Overwriting " + prefix + "classification_heads." + k)
- state_dict[prefix + "classification_heads." + k] = v
-
-
-class BARTClassificationHead(nn.Module):
- """Head for sentence-level classification tasks."""
-
- def __init__(
- self,
- input_dim,
- inner_dim,
- num_classes,
- activation_fn,
- pooler_dropout,
- do_spectral_norm=False,
- ):
- super().__init__()
- self.dense = nn.Linear(input_dim, inner_dim)
- self.activation_fn = utils.get_activation_fn(activation_fn)
- self.dropout = nn.Dropout(p=pooler_dropout)
- self.out_proj = nn.Linear(inner_dim, num_classes)
-
- if do_spectral_norm:
- self.out_proj = torch.nn.utils.spectral_norm(self.out_proj)
-
- def forward(self, features, **kwargs):
- x = features
- x = self.dropout(x)
- x = self.dense(x)
- x = self.activation_fn(x)
- x = self.dropout(x)
- x = self.out_proj(x)
- return x
-
-
-@register_model_architecture("bart", "bart_large")
-def bart_large_architecture(args):
- args.encoder_embed_path = getattr(args, "encoder_embed_path", None)
- args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 1024)
- args.encoder_ffn_embed_dim = getattr(args, "encoder_ffn_embed_dim", 4 * 1024)
- args.encoder_layers = getattr(args, "encoder_layers", 12)
- args.encoder_attention_heads = getattr(args, "encoder_attention_heads", 16)
- args.encoder_normalize_before = getattr(args, "encoder_normalize_before", False)
- args.encoder_learned_pos = getattr(args, "encoder_learned_pos", True)
- args.decoder_embed_path = getattr(args, "decoder_embed_path", None)
- args.decoder_embed_dim = getattr(args, "decoder_embed_dim", args.encoder_embed_dim)
- args.decoder_ffn_embed_dim = getattr(
- args, "decoder_ffn_embed_dim", args.encoder_ffn_embed_dim
- )
- args.decoder_layers = getattr(args, "decoder_layers", 12)
- args.decoder_attention_heads = getattr(args, "decoder_attention_heads", 16)
- args.decoder_normalize_before = getattr(args, "decoder_normalize_before", False)
- args.decoder_learned_pos = getattr(args, "decoder_learned_pos", True)
- args.attention_dropout = getattr(args, "attention_dropout", 0.0)
- args.relu_dropout = getattr(args, "relu_dropout", 0.0)
- args.dropout = getattr(args, "dropout", 0.1)
- args.max_target_positions = getattr(args, "max_target_positions", 1024)
- args.max_source_positions = getattr(args, "max_source_positions", 1024)
- args.adaptive_softmax_cutoff = getattr(args, "adaptive_softmax_cutoff", None)
- args.adaptive_softmax_dropout = getattr(args, "adaptive_softmax_dropout", 0)
- args.share_decoder_input_output_embed = getattr(
- args, "share_decoder_input_output_embed", True
- )
- args.share_all_embeddings = getattr(args, "share_all_embeddings", True)
-
- args.decoder_output_dim = getattr(
- args, "decoder_output_dim", args.decoder_embed_dim
- )
- args.decoder_input_dim = getattr(args, "decoder_input_dim", args.decoder_embed_dim)
-
- args.no_scale_embedding = getattr(args, "no_scale_embedding", True)
- args.layernorm_embedding = getattr(args, "layernorm_embedding", True)
-
- args.activation_fn = getattr(args, "activation_fn", "gelu")
- args.pooler_activation_fn = getattr(args, "pooler_activation_fn", "tanh")
- args.pooler_dropout = getattr(args, "pooler_dropout", 0.0)
-
-
-@register_model_architecture("bart", "bart_base")
-def bart_base_architecture(args):
- args.encoder_embed_dim = getattr(args, "encoder_embed_dim", 768)
- args.encoder_ffn_embed_dim = getattr(args, "encoder_ffn_embed_dim", 4 * 768)
- args.encoder_layers = getattr(args, "encoder_layers", 6)
- args.encoder_attention_heads = getattr(args, "encoder_attention_heads", 12)
- args.decoder_layers = getattr(args, "decoder_layers", 6)
- args.decoder_attention_heads = getattr(args, "decoder_attention_heads", 12)
- bart_large_architecture(args)
-
-
-@register_model_architecture("bart", "mbart_large")
-def mbart_large_architecture(args):
- args.no_scale_embedding = getattr(args, "no_scale_embedding", False)
- bart_large_architecture(args)
-
-
-@register_model_architecture("bart", "mbart_base")
-def mbart_base_architecture(args):
- args.no_scale_embedding = getattr(args, "no_scale_embedding", False)
- bart_base_architecture(args)
-
-
-@register_model_architecture("bart", "mbart_base_wmt20")
-def mbart_base_wmt20_architecture(args):
- args.layernorm_embedding = getattr(args, "layernorm_embedding", False)
- mbart_base_architecture(args)
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/speech_recognition/new/infer.py b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/speech_recognition/new/infer.py
deleted file mode 100644
index 3fb67151e0dc425e02d090a62b1d83e6039e6ccb..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/speech_recognition/new/infer.py
+++ /dev/null
@@ -1,471 +0,0 @@
-#!/usr/bin/env python -u
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import ast
-import hashlib
-import logging
-import os
-import shutil
-import sys
-from dataclasses import dataclass, field, is_dataclass
-from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple, Union
-
-import editdistance
-import torch
-import torch.distributed as dist
-from examples.speech_recognition.new.decoders.decoder_config import (
- DecoderConfig,
- FlashlightDecoderConfig,
-)
-from examples.speech_recognition.new.decoders.decoder import Decoder
-from fairseq import checkpoint_utils, distributed_utils, progress_bar, tasks, utils
-from fairseq.data.data_utils import post_process
-from fairseq.dataclass.configs import (
- CheckpointConfig,
- CommonConfig,
- CommonEvalConfig,
- DatasetConfig,
- DistributedTrainingConfig,
- FairseqDataclass,
-)
-from fairseq.logging.meters import StopwatchMeter, TimeMeter
-from fairseq.logging.progress_bar import BaseProgressBar
-from fairseq.models.fairseq_model import FairseqModel
-from omegaconf import OmegaConf
-
-import hydra
-from hydra.core.config_store import ConfigStore
-
-logging.root.setLevel(logging.INFO)
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-config_path = Path(__file__).resolve().parent / "conf"
-
-
-@dataclass
-class DecodingConfig(DecoderConfig, FlashlightDecoderConfig):
- unique_wer_file: bool = field(
- default=False,
- metadata={"help": "If set, use a unique file for storing WER"},
- )
- results_path: Optional[str] = field(
- default=None,
- metadata={
- "help": "If set, write hypothesis and reference sentences into this directory"
- },
- )
-
-
-@dataclass
-class InferConfig(FairseqDataclass):
- task: Any = None
- decoding: DecodingConfig = DecodingConfig()
- common: CommonConfig = CommonConfig()
- common_eval: CommonEvalConfig = CommonEvalConfig()
- checkpoint: CheckpointConfig = CheckpointConfig()
- distributed_training: DistributedTrainingConfig = DistributedTrainingConfig()
- dataset: DatasetConfig = DatasetConfig()
- is_ax: bool = field(
- default=False,
- metadata={
- "help": "if true, assumes we are using ax for tuning and returns a tuple for ax to consume"
- },
- )
-
-
-def reset_logging():
- root = logging.getLogger()
- for handler in root.handlers:
- root.removeHandler(handler)
- root.setLevel(os.environ.get("LOGLEVEL", "INFO").upper())
- handler = logging.StreamHandler(sys.stdout)
- handler.setFormatter(
- logging.Formatter(
- fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
- datefmt="%Y-%m-%d %H:%M:%S",
- )
- )
- root.addHandler(handler)
-
-
-class InferenceProcessor:
- cfg: InferConfig
-
- def __init__(self, cfg: InferConfig) -> None:
- self.cfg = cfg
- self.task = tasks.setup_task(cfg.task)
-
- models, saved_cfg = self.load_model_ensemble()
- self.models = models
- self.saved_cfg = saved_cfg
- self.tgt_dict = self.task.target_dictionary
-
- self.task.load_dataset(
- self.cfg.dataset.gen_subset,
- task_cfg=saved_cfg.task,
- )
- self.generator = Decoder(cfg.decoding, self.tgt_dict)
- self.gen_timer = StopwatchMeter()
- self.wps_meter = TimeMeter()
- self.num_sentences = 0
- self.total_errors = 0
- self.total_length = 0
-
- self.hypo_words_file = None
- self.hypo_units_file = None
- self.ref_words_file = None
- self.ref_units_file = None
-
- self.progress_bar = self.build_progress_bar()
-
- def __enter__(self) -> "InferenceProcessor":
- if self.cfg.decoding.results_path is not None:
- self.hypo_words_file = self.get_res_file("hypo.word")
- self.hypo_units_file = self.get_res_file("hypo.units")
- self.ref_words_file = self.get_res_file("ref.word")
- self.ref_units_file = self.get_res_file("ref.units")
- return self
-
- def __exit__(self, *exc) -> bool:
- if self.cfg.decoding.results_path is not None:
- self.hypo_words_file.close()
- self.hypo_units_file.close()
- self.ref_words_file.close()
- self.ref_units_file.close()
- return False
-
- def __iter__(self) -> Any:
- for sample in self.progress_bar:
- if not self.cfg.common.cpu:
- sample = utils.move_to_cuda(sample)
-
- # Happens on the last batch.
- if "net_input" not in sample:
- continue
- yield sample
-
- def log(self, *args, **kwargs):
- self.progress_bar.log(*args, **kwargs)
-
- def print(self, *args, **kwargs):
- self.progress_bar.print(*args, **kwargs)
-
- def get_res_file(self, fname: str) -> None:
- fname = os.path.join(self.cfg.decoding.results_path, fname)
- if self.data_parallel_world_size > 1:
- fname = f"{fname}.{self.data_parallel_rank}"
- return open(fname, "w", buffering=1)
-
- def merge_shards(self) -> None:
- """Merges all shard files into shard 0, then removes shard suffix."""
-
- shard_id = self.data_parallel_rank
- num_shards = self.data_parallel_world_size
-
- if self.data_parallel_world_size > 1:
-
- def merge_shards_with_root(fname: str) -> None:
- fname = os.path.join(self.cfg.decoding.results_path, fname)
- logger.info("Merging %s on shard %d", fname, shard_id)
- base_fpath = Path(f"{fname}.0")
- with open(base_fpath, "a") as out_file:
- for s in range(1, num_shards):
- shard_fpath = Path(f"{fname}.{s}")
- with open(shard_fpath, "r") as in_file:
- for line in in_file:
- out_file.write(line)
- shard_fpath.unlink()
- shutil.move(f"{fname}.0", fname)
-
- dist.barrier() # ensure all shards finished writing
- if shard_id == (0 % num_shards):
- merge_shards_with_root("hypo.word")
- if shard_id == (1 % num_shards):
- merge_shards_with_root("hypo.units")
- if shard_id == (2 % num_shards):
- merge_shards_with_root("ref.word")
- if shard_id == (3 % num_shards):
- merge_shards_with_root("ref.units")
- dist.barrier()
-
- def optimize_model(self, model: FairseqModel) -> None:
- model.make_generation_fast_()
- if self.cfg.common.fp16:
- model.half()
- if not self.cfg.common.cpu:
- model.cuda()
-
- def load_model_ensemble(self) -> Tuple[List[FairseqModel], FairseqDataclass]:
- arg_overrides = ast.literal_eval(self.cfg.common_eval.model_overrides)
- models, saved_cfg = checkpoint_utils.load_model_ensemble(
- utils.split_paths(self.cfg.common_eval.path, separator="\\"),
- arg_overrides=arg_overrides,
- task=self.task,
- suffix=self.cfg.checkpoint.checkpoint_suffix,
- strict=(self.cfg.checkpoint.checkpoint_shard_count == 1),
- num_shards=self.cfg.checkpoint.checkpoint_shard_count,
- )
- for model in models:
- self.optimize_model(model)
- return models, saved_cfg
-
- def get_dataset_itr(self, disable_iterator_cache: bool = False) -> None:
- return self.task.get_batch_iterator(
- dataset=self.task.dataset(self.cfg.dataset.gen_subset),
- max_tokens=self.cfg.dataset.max_tokens,
- max_sentences=self.cfg.dataset.batch_size,
- max_positions=(sys.maxsize, sys.maxsize),
- ignore_invalid_inputs=self.cfg.dataset.skip_invalid_size_inputs_valid_test,
- required_batch_size_multiple=self.cfg.dataset.required_batch_size_multiple,
- seed=self.cfg.common.seed,
- num_shards=self.data_parallel_world_size,
- shard_id=self.data_parallel_rank,
- num_workers=self.cfg.dataset.num_workers,
- data_buffer_size=self.cfg.dataset.data_buffer_size,
- disable_iterator_cache=disable_iterator_cache,
- ).next_epoch_itr(shuffle=False)
-
- def build_progress_bar(
- self,
- epoch: Optional[int] = None,
- prefix: Optional[str] = None,
- default_log_format: str = "tqdm",
- ) -> BaseProgressBar:
- return progress_bar.progress_bar(
- iterator=self.get_dataset_itr(),
- log_format=self.cfg.common.log_format,
- log_interval=self.cfg.common.log_interval,
- epoch=epoch,
- prefix=prefix,
- tensorboard_logdir=self.cfg.common.tensorboard_logdir,
- default_log_format=default_log_format,
- )
-
- @property
- def data_parallel_world_size(self):
- if self.cfg.distributed_training.distributed_world_size == 1:
- return 1
- return distributed_utils.get_data_parallel_world_size()
-
- @property
- def data_parallel_rank(self):
- if self.cfg.distributed_training.distributed_world_size == 1:
- return 0
- return distributed_utils.get_data_parallel_rank()
-
- def process_sentence(
- self,
- sample: Dict[str, Any],
- hypo: Dict[str, Any],
- sid: int,
- batch_id: int,
- ) -> Tuple[int, int]:
- speaker = None # Speaker can't be parsed from dataset.
-
- if "target_label" in sample:
- toks = sample["target_label"]
- else:
- toks = sample["target"]
- toks = toks[batch_id, :]
-
- # Processes hypothesis.
- hyp_pieces = self.tgt_dict.string(hypo["tokens"].int().cpu())
- if "words" in hypo:
- hyp_words = " ".join(hypo["words"])
- else:
- hyp_words = post_process(hyp_pieces, self.cfg.common_eval.post_process)
-
- # Processes target.
- target_tokens = utils.strip_pad(toks, self.tgt_dict.pad())
- tgt_pieces = self.tgt_dict.string(target_tokens.int().cpu())
- tgt_words = post_process(tgt_pieces, self.cfg.common_eval.post_process)
-
- if self.cfg.decoding.results_path is not None:
- print(f"{hyp_pieces} ({speaker}-{sid})", file=self.hypo_units_file)
- print(f"{hyp_words} ({speaker}-{sid})", file=self.hypo_words_file)
- print(f"{tgt_pieces} ({speaker}-{sid})", file=self.ref_units_file)
- print(f"{tgt_words} ({speaker}-{sid})", file=self.ref_words_file)
-
- if not self.cfg.common_eval.quiet:
- logger.info(f"HYPO: {hyp_words}")
- logger.info(f"REF: {tgt_words}")
- logger.info("---------------------")
-
- hyp_words, tgt_words = hyp_words.split(), tgt_words.split()
-
- return editdistance.eval(hyp_words, tgt_words), len(tgt_words)
-
- def process_sample(self, sample: Dict[str, Any]) -> None:
- self.gen_timer.start()
- hypos = self.task.inference_step(
- generator=self.generator,
- models=self.models,
- sample=sample,
- )
- num_generated_tokens = sum(len(h[0]["tokens"]) for h in hypos)
- self.gen_timer.stop(num_generated_tokens)
- self.wps_meter.update(num_generated_tokens)
-
- for batch_id, sample_id in enumerate(sample["id"].tolist()):
- errs, length = self.process_sentence(
- sample=sample,
- sid=sample_id,
- batch_id=batch_id,
- hypo=hypos[batch_id][0],
- )
- self.total_errors += errs
- self.total_length += length
-
- self.log({"wps": round(self.wps_meter.avg)})
- if "nsentences" in sample:
- self.num_sentences += sample["nsentences"]
- else:
- self.num_sentences += sample["id"].numel()
-
- def log_generation_time(self) -> None:
- logger.info(
- "Processed %d sentences (%d tokens) in %.1fs %.2f "
- "sentences per second, %.2f tokens per second)",
- self.num_sentences,
- self.gen_timer.n,
- self.gen_timer.sum,
- self.num_sentences / self.gen_timer.sum,
- 1.0 / self.gen_timer.avg,
- )
-
-
-def parse_wer(wer_file: Path) -> float:
- with open(wer_file, "r") as f:
- return float(f.readline().strip().split(" ")[1])
-
-
-def get_wer_file(cfg: InferConfig) -> Path:
- """Hashes the decoding parameters to a unique file ID."""
- base_path = "wer"
- if cfg.decoding.results_path is not None:
- base_path = os.path.join(cfg.decoding.results_path, base_path)
-
- if cfg.decoding.unique_wer_file:
- yaml_str = OmegaConf.to_yaml(cfg.decoding)
- fid = int(hashlib.md5(yaml_str.encode("utf-8")).hexdigest(), 16)
- return Path(f"{base_path}.{fid % 1000000}")
- else:
- return Path(base_path)
-
-
-def main(cfg: InferConfig) -> float:
- """Entry point for main processing logic.
-
- Args:
- cfg: The inferance configuration to use.
- wer: Optional shared memory pointer for returning the WER. If not None,
- the final WER value will be written here instead of being returned.
-
- Returns:
- The final WER if `wer` is None, otherwise None.
- """
-
- yaml_str, wer_file = OmegaConf.to_yaml(cfg.decoding), get_wer_file(cfg)
-
- # Validates the provided configuration.
- if cfg.dataset.max_tokens is None and cfg.dataset.batch_size is None:
- cfg.dataset.max_tokens = 4000000
- if not cfg.common.cpu and not torch.cuda.is_available():
- raise ValueError("CUDA not found; set `cpu=True` to run without CUDA")
-
- with InferenceProcessor(cfg) as processor:
- for sample in processor:
- processor.process_sample(sample)
-
- processor.log_generation_time()
-
- if cfg.decoding.results_path is not None:
- processor.merge_shards()
-
- errs_t, leng_t = processor.total_errors, processor.total_length
-
- if cfg.common.cpu:
- logger.warning("Merging WER requires CUDA.")
- elif processor.data_parallel_world_size > 1:
- stats = torch.LongTensor([errs_t, leng_t]).cuda()
- dist.all_reduce(stats, op=dist.ReduceOp.SUM)
- errs_t, leng_t = stats[0].item(), stats[1].item()
-
- wer = errs_t * 100.0 / leng_t
-
- if distributed_utils.is_master(cfg.distributed_training):
- with open(wer_file, "w") as f:
- f.write(
- (
- f"WER: {wer}\n"
- f"err / num_ref_words = {errs_t} / {leng_t}\n\n"
- f"{yaml_str}"
- )
- )
-
- return wer
-
-
-@hydra.main(config_path=config_path, config_name="infer")
-def hydra_main(cfg: InferConfig) -> Union[float, Tuple[float, Optional[float]]]:
- container = OmegaConf.to_container(cfg, resolve=True, enum_to_str=True)
- cfg = OmegaConf.create(container)
- OmegaConf.set_struct(cfg, True)
-
- if cfg.common.reset_logging:
- reset_logging()
-
- # logger.info("Config:\n%s", OmegaConf.to_yaml(cfg))
- wer = float("inf")
-
- try:
- if cfg.common.profile:
- with torch.cuda.profiler.profile():
- with torch.autograd.profiler.emit_nvtx():
- distributed_utils.call_main(cfg, main)
- else:
- distributed_utils.call_main(cfg, main)
-
- wer = parse_wer(get_wer_file(cfg))
- except BaseException as e: # pylint: disable=broad-except
- if not cfg.common.suppress_crashes:
- raise
- else:
- logger.error("Crashed! %s", str(e))
-
- logger.info("Word error rate: %.4f", wer)
- if cfg.is_ax:
- return wer, None
-
- return wer
-
-
-def cli_main() -> None:
- try:
- from hydra._internal.utils import (
- get_args,
- ) # pylint: disable=import-outside-toplevel
-
- cfg_name = get_args().config_name or "infer"
- except ImportError:
- logger.warning("Failed to get config name from hydra args")
- cfg_name = "infer"
-
- cs = ConfigStore.instance()
- cs.store(name=cfg_name, node=InferConfig)
-
- for k in InferConfig.__dataclass_fields__:
- if is_dataclass(InferConfig.__dataclass_fields__[k].type):
- v = InferConfig.__dataclass_fields__[k].default
- cs.store(name=k, node=v)
-
- hydra_main() # pylint: disable=no-value-for-parameter
-
-
-if __name__ == "__main__":
- cli_main()
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/models/text_to_speech/hifigan.py b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/models/text_to_speech/hifigan.py
deleted file mode 100644
index edc7db6015ebea18f40c8949ae78c0b5b61e1297..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/models/text_to_speech/hifigan.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from torch.nn import Conv1d, ConvTranspose1d
-from torch.nn.utils import weight_norm, remove_weight_norm
-
-LRELU_SLOPE = 0.1
-
-
-def init_weights(m, mean=0.0, std=0.01):
- classname = m.__class__.__name__
- if classname.find("Conv") != -1:
- m.weight.data.normal_(mean, std)
-
-
-def get_padding(kernel_size, dilation=1):
- return (kernel_size * dilation - dilation) // 2
-
-
-class ResBlock(torch.nn.Module):
- def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
- super(ResBlock, self).__init__()
- self.convs1 = nn.ModuleList(
- [
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=dilation[0],
- padding=get_padding(kernel_size, dilation[0]),
- )
- ),
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=dilation[1],
- padding=get_padding(kernel_size, dilation[1]),
- )
- ),
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=dilation[2],
- padding=get_padding(kernel_size, dilation[2]),
- )
- ),
- ]
- )
- self.convs1.apply(init_weights)
-
- self.convs2 = nn.ModuleList(
- [
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=1,
- padding=get_padding(kernel_size, 1),
- )
- ),
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=1,
- padding=get_padding(kernel_size, 1),
- )
- ),
- weight_norm(
- Conv1d(
- channels,
- channels,
- kernel_size,
- 1,
- dilation=1,
- padding=get_padding(kernel_size, 1),
- )
- ),
- ]
- )
- self.convs2.apply(init_weights)
-
- def forward(self, x):
- for c1, c2 in zip(self.convs1, self.convs2):
- xt = F.leaky_relu(x, LRELU_SLOPE)
- xt = c1(xt)
- xt = F.leaky_relu(xt, LRELU_SLOPE)
- xt = c2(xt)
- x = xt + x
- return x
-
- def remove_weight_norm(self):
- for layer in self.convs1:
- remove_weight_norm(layer)
- for layer in self.convs2:
- remove_weight_norm(layer)
-
-
-class Generator(torch.nn.Module):
- def __init__(self, cfg):
- super(Generator, self).__init__()
- self.num_kernels = len(cfg["resblock_kernel_sizes"])
- self.num_upsamples = len(cfg["upsample_rates"])
- self.conv_pre = weight_norm(
- Conv1d(80, cfg["upsample_initial_channel"], 7, 1, padding=3)
- )
-
- self.ups = nn.ModuleList()
- for i, (u, k) in enumerate(
- zip(cfg["upsample_rates"], cfg["upsample_kernel_sizes"])
- ):
- self.ups.append(
- weight_norm(
- ConvTranspose1d(
- cfg["upsample_initial_channel"] // (2 ** i),
- cfg["upsample_initial_channel"] // (2 ** (i + 1)),
- k,
- u,
- padding=(k - u) // 2,
- )
- )
- )
-
- self.resblocks = nn.ModuleList()
- for i in range(len(self.ups)):
- ch = cfg["upsample_initial_channel"] // (2 ** (i + 1))
- for k, d in zip(
- cfg["resblock_kernel_sizes"], cfg["resblock_dilation_sizes"]
- ):
- self.resblocks.append(ResBlock(ch, k, d))
-
- self.conv_post = weight_norm(Conv1d(ch, 1, 7, 1, padding=3))
- self.ups.apply(init_weights)
- self.conv_post.apply(init_weights)
-
- def forward(self, x):
- x = self.conv_pre(x)
- for i in range(self.num_upsamples):
- x = F.leaky_relu(x, LRELU_SLOPE)
- x = self.ups[i](x)
- xs = None
- for j in range(self.num_kernels):
- if xs is None:
- xs = self.resblocks[i * self.num_kernels + j](x)
- else:
- xs += self.resblocks[i * self.num_kernels + j](x)
- x = xs / self.num_kernels
- x = F.leaky_relu(x)
- x = self.conv_post(x)
- x = torch.tanh(x)
-
- return x
-
- def remove_weight_norm(self):
- print("Removing weight norm...")
- for layer in self.ups:
- remove_weight_norm(layer)
- for layer in self.resblocks:
- layer.remove_weight_norm()
- remove_weight_norm(self.conv_pre)
- remove_weight_norm(self.conv_post)
diff --git a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/simultaneous_translation/eval/agents/simul_t2t_enja.py b/spaces/OFA-Sys/OFA-vqa/fairseq/examples/simultaneous_translation/eval/agents/simul_t2t_enja.py
deleted file mode 100644
index 8f3c8703ca37398b9d389ce5181bdfac2333cdf2..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/simultaneous_translation/eval/agents/simul_t2t_enja.py
+++ /dev/null
@@ -1,226 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import os
-
-from fairseq import checkpoint_utils, tasks
-import sentencepiece as spm
-import torch
-
-try:
- from simuleval import READ_ACTION, WRITE_ACTION, DEFAULT_EOS
- from simuleval.agents import TextAgent
-except ImportError:
- print("Please install simuleval 'pip install simuleval'")
-
-
-BOS_PREFIX = "\u2581"
-
-
-class SimulTransTextAgentJA(TextAgent):
- """
- Simultaneous Translation
- Text agent for Japanese
- """
- def __init__(self, args):
-
- # Whether use gpu
- self.gpu = getattr(args, "gpu", False)
-
- # Max len
- self.max_len = args.max_len
-
- # Load Model
- self.load_model_vocab(args)
-
- # build word splitter
- self.build_word_splitter(args)
-
- self.eos = DEFAULT_EOS
-
- def initialize_states(self, states):
- states.incremental_states = dict()
- states.incremental_states["online"] = dict()
-
- def to_device(self, tensor):
- if self.gpu:
- return tensor.cuda()
- else:
- return tensor.cpu()
-
- def load_model_vocab(self, args):
-
- filename = args.model_path
- if not os.path.exists(filename):
- raise IOError("Model file not found: {}".format(filename))
-
- state = checkpoint_utils.load_checkpoint_to_cpu(filename)
-
- task_args = state["cfg"]["task"]
- task_args.data = args.data_bin
-
- task = tasks.setup_task(task_args)
-
- # build model for ensemble
- state["cfg"]["model"].load_pretrained_encoder_from = None
- state["cfg"]["model"].load_pretrained_decoder_from = None
-
- self.model = task.build_model(state["cfg"]["model"])
- self.model.load_state_dict(state["model"], strict=True)
- self.model.eval()
- self.model.share_memory()
-
- if self.gpu:
- self.model.cuda()
-
- # Set dictionary
- self.dict = {}
- self.dict["tgt"] = task.target_dictionary
- self.dict["src"] = task.source_dictionary
-
- @staticmethod
- def add_args(parser):
- # fmt: off
- parser.add_argument('--model-path', type=str, required=True,
- help='path to your pretrained model.')
- parser.add_argument("--data-bin", type=str, required=True,
- help="Path of data binary")
- parser.add_argument("--max-len", type=int, default=100,
- help="Max length of translation")
- parser.add_argument("--tgt-splitter-type", type=str, default="SentencePiece",
- help="Subword splitter type for target text.")
- parser.add_argument("--tgt-splitter-path", type=str, default=None,
- help="Subword splitter model path for target text.")
- parser.add_argument("--src-splitter-type", type=str, default="SentencePiece",
- help="Subword splitter type for source text.")
- parser.add_argument("--src-splitter-path", type=str, default=None,
- help="Subword splitter model path for source text.")
- # fmt: on
- return parser
-
- def build_word_splitter(self, args):
- self.spm = {}
- for lang in ['src', 'tgt']:
- if getattr(args, f'{lang}_splitter_type', None):
- path = getattr(args, f'{lang}_splitter_path', None)
- if path:
- self.spm[lang] = spm.SentencePieceProcessor()
- self.spm[lang].Load(path)
-
- def segment_to_units(self, segment, states):
- # Split a full word (segment) into subwords (units)
- return self.spm['src'].EncodeAsPieces(segment)
-
- def update_model_encoder(self, states):
- if len(states.units.source) == 0:
- return
-
- src_indices = [
- self.dict['src'].index(x)
- for x in states.units.source.value
- ]
-
- if states.finish_read():
- # Append the eos index when the prediction is over
- src_indices += [self.dict["tgt"].eos_index]
-
- src_indices = self.to_device(
- torch.LongTensor(src_indices).unsqueeze(0)
- )
- src_lengths = self.to_device(
- torch.LongTensor([src_indices.size(1)])
- )
-
- states.encoder_states = self.model.encoder(src_indices, src_lengths)
-
- torch.cuda.empty_cache()
-
- def update_states_read(self, states):
- # Happens after a read action.
- self.update_model_encoder(states)
-
- def units_to_segment(self, units, states):
- # Merge sub words (units) to full word (segment).
- # For Japanese, we can directly send
- # the untokenized token to server except the BOS token
- # with following option
- # --sacrebleu-tokenizer MeCab
- # --eval-latency-unit char
- # --no-space
- token = units.value.pop()
-
- if (
- token == self.dict["tgt"].eos_word
- or len(states.segments.target) > self.max_len
- ):
- return DEFAULT_EOS
-
- if BOS_PREFIX == token:
- return None
- if token[0] == BOS_PREFIX:
- return token[1:]
- else:
- return token
-
- def policy(self, states):
-
- if not getattr(states, "encoder_states", None):
- # No encoder states, read a token first
- return READ_ACTION
-
- # encode previous predicted target tokens
- tgt_indices = self.to_device(
- torch.LongTensor(
- [self.model.decoder.dictionary.eos()]
- + [
- self.dict['tgt'].index(x)
- for x in states.units.target.value
- if x is not None
- ]
- ).unsqueeze(0)
- )
-
- # Current steps
- states.incremental_states["steps"] = {
- "src": states.encoder_states["encoder_out"][0].size(0),
- "tgt": 1 + len(states.units.target),
- }
-
- # Online only means the reading is not finished
- states.incremental_states["online"]["only"] = (
- torch.BoolTensor([not states.finish_read()])
- )
-
- x, outputs = self.model.decoder.forward(
- prev_output_tokens=tgt_indices,
- encoder_out=states.encoder_states,
- incremental_state=states.incremental_states,
- )
-
- states.decoder_out = x
-
- torch.cuda.empty_cache()
-
- if outputs.action == 0:
- return READ_ACTION
- else:
- return WRITE_ACTION
-
- def predict(self, states):
- # Predict target token from decoder states
- decoder_states = states.decoder_out
-
- lprobs = self.model.get_normalized_probs(
- [decoder_states[:, -1:]], log_probs=True
- )
-
- index = lprobs.argmax(dim=-1)[0, 0].item()
-
- if index != self.dict['tgt'].eos_index:
- token = self.dict['tgt'].string([index])
- else:
- token = self.dict['tgt'].eos_word
-
- return token
diff --git a/spaces/OFA-Sys/OFA-vqa/fairseq/tests/distributed/test_module_proxy_wrapper.py b/spaces/OFA-Sys/OFA-vqa/fairseq/tests/distributed/test_module_proxy_wrapper.py
deleted file mode 100644
index 2803a044cdcc12e0a348f40d06ce89c571d307ed..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-vqa/fairseq/tests/distributed/test_module_proxy_wrapper.py
+++ /dev/null
@@ -1,75 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import unittest
-
-import torch
-from torch import nn
-
-from fairseq.distributed import ModuleProxyWrapper
-
-from .utils import objects_are_equal
-
-
-class MockDDPWrapper(nn.Module):
- """A simple wrapper with an interface similar to DistributedDataParallel."""
-
- def __init__(self, module):
- super().__init__()
- self.module = module
-
- def forward(self, x):
- return self.module(x)
-
-
-class Model(nn.Module):
- def __init__(self):
- super().__init__()
- self.linear = nn.Linear(5, 10)
- self.xyz = "hello"
-
- def forward(self, x):
- return self.linear(x)
-
- def get_xyz(self):
- return self.xyz
-
-
-class TestModuleProxyWrapper(unittest.TestCase):
-
- def _get_module(self):
- module = Model()
- wrapped_module = MockDDPWrapper(module)
- wrapped_module = ModuleProxyWrapper(wrapped_module)
- return wrapped_module, module
-
- def test_getattr_forwarding(self):
- wrapped_module, module = self._get_module()
- assert module.xyz == "hello"
- assert module.get_xyz() == "hello"
- assert wrapped_module.xyz == "hello"
-
- wrapped_module.xyz = "world"
- assert wrapped_module.xyz == "world"
- assert module.get_xyz() == "hello"
-
- def test_state_dict(self):
- wrapped_module, module = self._get_module()
- assert objects_are_equal(wrapped_module.state_dict(), module.state_dict())
-
- def test_load_state_dict(self):
- wrapped_module, module = self._get_module()
- wrapped_module.load_state_dict(module.state_dict())
- input = torch.rand(4, 5)
- torch.testing.assert_allclose(wrapped_module(input), module(input))
-
- def test_forward(self):
- wrapped_module, module = self._get_module()
- input = torch.rand(4, 5)
- torch.testing.assert_allclose(wrapped_module(input), module(input))
-
-
-if __name__ == "__main__":
- unittest.main()
diff --git a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/layers/__init__.py b/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/layers/__init__.py
deleted file mode 100644
index 3d015c530b3e33de8ea60943a0a98b135f013dd7..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/layers/__init__.py
+++ /dev/null
@@ -1,24 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from .batch_norm import FrozenBatchNorm2d, get_norm, NaiveSyncBatchNorm, CycleBatchNormList
-from .deform_conv import DeformConv, ModulatedDeformConv
-from .mask_ops import paste_masks_in_image
-from .nms import batched_nms, batched_nms_rotated, nms, nms_rotated
-from .roi_align import ROIAlign, roi_align
-from .roi_align_rotated import ROIAlignRotated, roi_align_rotated
-from .shape_spec import ShapeSpec
-from .wrappers import (
- BatchNorm2d,
- Conv2d,
- ConvTranspose2d,
- cat,
- interpolate,
- Linear,
- nonzero_tuple,
- cross_entropy,
- shapes_to_tensor,
-)
-from .blocks import CNNBlockBase, DepthwiseSeparableConv2d
-from .aspp import ASPP
-from .losses import ciou_loss, diou_loss
-
-__all__ = [k for k in globals().keys() if not k.startswith("_")]
diff --git a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/solver/build.py b/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/solver/build.py
deleted file mode 100644
index 1989dfcd0855d833a75e403f6a5e88725d78022f..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/solver/build.py
+++ /dev/null
@@ -1,285 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import itertools
-import logging
-from collections import defaultdict
-from enum import Enum
-from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Type, Union
-import torch
-from fvcore.common.param_scheduler import CosineParamScheduler, MultiStepParamScheduler
-
-from detectron2.config import CfgNode
-
-from .lr_scheduler import LRMultiplier, WarmupParamScheduler
-
-_GradientClipperInput = Union[torch.Tensor, Iterable[torch.Tensor]]
-_GradientClipper = Callable[[_GradientClipperInput], None]
-
-
-class GradientClipType(Enum):
- VALUE = "value"
- NORM = "norm"
-
-
-def _create_gradient_clipper(cfg: CfgNode) -> _GradientClipper:
- """
- Creates gradient clipping closure to clip by value or by norm,
- according to the provided config.
- """
- cfg = copy.deepcopy(cfg)
-
- def clip_grad_norm(p: _GradientClipperInput):
- torch.nn.utils.clip_grad_norm_(p, cfg.CLIP_VALUE, cfg.NORM_TYPE)
-
- def clip_grad_value(p: _GradientClipperInput):
- torch.nn.utils.clip_grad_value_(p, cfg.CLIP_VALUE)
-
- _GRADIENT_CLIP_TYPE_TO_CLIPPER = {
- GradientClipType.VALUE: clip_grad_value,
- GradientClipType.NORM: clip_grad_norm,
- }
- return _GRADIENT_CLIP_TYPE_TO_CLIPPER[GradientClipType(cfg.CLIP_TYPE)]
-
-
-def _generate_optimizer_class_with_gradient_clipping(
- optimizer: Type[torch.optim.Optimizer],
- *,
- per_param_clipper: Optional[_GradientClipper] = None,
- global_clipper: Optional[_GradientClipper] = None,
-) -> Type[torch.optim.Optimizer]:
- """
- Dynamically creates a new type that inherits the type of a given instance
- and overrides the `step` method to add gradient clipping
- """
- assert (
- per_param_clipper is None or global_clipper is None
- ), "Not allowed to use both per-parameter clipping and global clipping"
-
- def optimizer_wgc_step(self, closure=None):
- if per_param_clipper is not None:
- for group in self.param_groups:
- for p in group["params"]:
- per_param_clipper(p)
- else:
- # global clipper for future use with detr
- # (https://github.com/facebookresearch/detr/pull/287)
- all_params = itertools.chain(*[g["params"] for g in self.param_groups])
- global_clipper(all_params)
- super(type(self), self).step(closure)
-
- OptimizerWithGradientClip = type(
- optimizer.__name__ + "WithGradientClip",
- (optimizer,),
- {"step": optimizer_wgc_step},
- )
- return OptimizerWithGradientClip
-
-
-def maybe_add_gradient_clipping(
- cfg: CfgNode, optimizer: Type[torch.optim.Optimizer]
-) -> Type[torch.optim.Optimizer]:
- """
- If gradient clipping is enabled through config options, wraps the existing
- optimizer type to become a new dynamically created class OptimizerWithGradientClip
- that inherits the given optimizer and overrides the `step` method to
- include gradient clipping.
-
- Args:
- cfg: CfgNode, configuration options
- optimizer: type. A subclass of torch.optim.Optimizer
-
- Return:
- type: either the input `optimizer` (if gradient clipping is disabled), or
- a subclass of it with gradient clipping included in the `step` method.
- """
- if not cfg.SOLVER.CLIP_GRADIENTS.ENABLED:
- return optimizer
- if isinstance(optimizer, torch.optim.Optimizer):
- optimizer_type = type(optimizer)
- else:
- assert issubclass(optimizer, torch.optim.Optimizer), optimizer
- optimizer_type = optimizer
-
- grad_clipper = _create_gradient_clipper(cfg.SOLVER.CLIP_GRADIENTS)
- OptimizerWithGradientClip = _generate_optimizer_class_with_gradient_clipping(
- optimizer_type, per_param_clipper=grad_clipper
- )
- if isinstance(optimizer, torch.optim.Optimizer):
- optimizer.__class__ = OptimizerWithGradientClip # a bit hacky, not recommended
- return optimizer
- else:
- return OptimizerWithGradientClip
-
-
-def build_optimizer(cfg: CfgNode, model: torch.nn.Module) -> torch.optim.Optimizer:
- """
- Build an optimizer from config.
- """
- params = get_default_optimizer_params(
- model,
- base_lr=cfg.SOLVER.BASE_LR,
- weight_decay_norm=cfg.SOLVER.WEIGHT_DECAY_NORM,
- bias_lr_factor=cfg.SOLVER.BIAS_LR_FACTOR,
- weight_decay_bias=cfg.SOLVER.WEIGHT_DECAY_BIAS,
- )
- return maybe_add_gradient_clipping(cfg, torch.optim.SGD)(
- params,
- lr=cfg.SOLVER.BASE_LR,
- momentum=cfg.SOLVER.MOMENTUM,
- nesterov=cfg.SOLVER.NESTEROV,
- weight_decay=cfg.SOLVER.WEIGHT_DECAY,
- )
-
-
-def get_default_optimizer_params(
- model: torch.nn.Module,
- base_lr: Optional[float] = None,
- weight_decay: Optional[float] = None,
- weight_decay_norm: Optional[float] = None,
- bias_lr_factor: Optional[float] = 1.0,
- weight_decay_bias: Optional[float] = None,
- overrides: Optional[Dict[str, Dict[str, float]]] = None,
-) -> List[Dict[str, Any]]:
- """
- Get default param list for optimizer, with support for a few types of
- overrides. If no overrides needed, this is equivalent to `model.parameters()`.
-
- Args:
- base_lr: lr for every group by default. Can be omitted to use the one in optimizer.
- weight_decay: weight decay for every group by default. Can be omitted to use the one
- in optimizer.
- weight_decay_norm: override weight decay for params in normalization layers
- bias_lr_factor: multiplier of lr for bias parameters.
- weight_decay_bias: override weight decay for bias parameters
- overrides: if not `None`, provides values for optimizer hyperparameters
- (LR, weight decay) for module parameters with a given name; e.g.
- ``{"embedding": {"lr": 0.01, "weight_decay": 0.1}}`` will set the LR and
- weight decay values for all module parameters named `embedding`.
-
- For common detection models, ``weight_decay_norm`` is the only option
- needed to be set. ``bias_lr_factor,weight_decay_bias`` are legacy settings
- from Detectron1 that are not found useful.
-
- Example:
- ::
- torch.optim.SGD(get_default_optimizer_params(model, weight_decay_norm=0),
- lr=0.01, weight_decay=1e-4, momentum=0.9)
- """
- if overrides is None:
- overrides = {}
- defaults = {}
- if base_lr is not None:
- defaults["lr"] = base_lr
- if weight_decay is not None:
- defaults["weight_decay"] = weight_decay
- bias_overrides = {}
- if bias_lr_factor is not None and bias_lr_factor != 1.0:
- # NOTE: unlike Detectron v1, we now by default make bias hyperparameters
- # exactly the same as regular weights.
- if base_lr is None:
- raise ValueError("bias_lr_factor requires base_lr")
- bias_overrides["lr"] = base_lr * bias_lr_factor
- if weight_decay_bias is not None:
- bias_overrides["weight_decay"] = weight_decay_bias
- if len(bias_overrides):
- if "bias" in overrides:
- raise ValueError("Conflicting overrides for 'bias'")
- overrides["bias"] = bias_overrides
-
- norm_module_types = (
- torch.nn.BatchNorm1d,
- torch.nn.BatchNorm2d,
- torch.nn.BatchNorm3d,
- torch.nn.SyncBatchNorm,
- # NaiveSyncBatchNorm inherits from BatchNorm2d
- torch.nn.GroupNorm,
- torch.nn.InstanceNorm1d,
- torch.nn.InstanceNorm2d,
- torch.nn.InstanceNorm3d,
- torch.nn.LayerNorm,
- torch.nn.LocalResponseNorm,
- )
- params: List[Dict[str, Any]] = []
- memo: Set[torch.nn.parameter.Parameter] = set()
- for module in model.modules():
- for module_param_name, value in module.named_parameters(recurse=False):
- if not value.requires_grad:
- continue
- # Avoid duplicating parameters
- if value in memo:
- continue
- memo.add(value)
-
- hyperparams = copy.copy(defaults)
- if isinstance(module, norm_module_types) and weight_decay_norm is not None:
- hyperparams["weight_decay"] = weight_decay_norm
- hyperparams.update(overrides.get(module_param_name, {}))
- params.append({"params": [value], **hyperparams})
- return reduce_param_groups(params)
-
-
-def _expand_param_groups(params: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
- # Transform parameter groups into per-parameter structure.
- # Later items in `params` can overwrite parameters set in previous items.
- ret = defaultdict(dict)
- for item in params:
- assert "params" in item
- cur_params = {x: y for x, y in item.items() if x != "params"}
- for param in item["params"]:
- ret[param].update({"params": [param], **cur_params})
- return list(ret.values())
-
-
-def reduce_param_groups(params: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
- # Reorganize the parameter groups and merge duplicated groups.
- # The number of parameter groups needs to be as small as possible in order
- # to efficiently use the PyTorch multi-tensor optimizer. Therefore instead
- # of using a parameter_group per single parameter, we reorganize the
- # parameter groups and merge duplicated groups. This approach speeds
- # up multi-tensor optimizer significantly.
- params = _expand_param_groups(params)
- groups = defaultdict(list) # re-group all parameter groups by their hyperparams
- for item in params:
- cur_params = tuple((x, y) for x, y in item.items() if x != "params")
- groups[cur_params].extend(item["params"])
- ret = []
- for param_keys, param_values in groups.items():
- cur = {kv[0]: kv[1] for kv in param_keys}
- cur["params"] = param_values
- ret.append(cur)
- return ret
-
-
-def build_lr_scheduler(
- cfg: CfgNode, optimizer: torch.optim.Optimizer
-) -> torch.optim.lr_scheduler._LRScheduler:
- """
- Build a LR scheduler from config.
- """
- name = cfg.SOLVER.LR_SCHEDULER_NAME
-
- if name == "WarmupMultiStepLR":
- steps = [x for x in cfg.SOLVER.STEPS if x <= cfg.SOLVER.MAX_ITER]
- if len(steps) != len(cfg.SOLVER.STEPS):
- logger = logging.getLogger(__name__)
- logger.warning(
- "SOLVER.STEPS contains values larger than SOLVER.MAX_ITER. "
- "These values will be ignored."
- )
- sched = MultiStepParamScheduler(
- values=[cfg.SOLVER.GAMMA ** k for k in range(len(steps) + 1)],
- milestones=steps,
- num_updates=cfg.SOLVER.MAX_ITER,
- )
- elif name == "WarmupCosineLR":
- sched = CosineParamScheduler(1, 0)
- else:
- raise ValueError("Unknown LR scheduler: {}".format(name))
-
- sched = WarmupParamScheduler(
- sched,
- cfg.SOLVER.WARMUP_FACTOR,
- min(cfg.SOLVER.WARMUP_ITERS / cfg.SOLVER.MAX_ITER, 1.0),
- cfg.SOLVER.WARMUP_METHOD,
- )
- return LRMultiplier(optimizer, multiplier=sched, max_iter=cfg.SOLVER.MAX_ITER)
diff --git a/spaces/OpenMotionLab/MotionGPT/mGPT/render/renderer.py b/spaces/OpenMotionLab/MotionGPT/mGPT/render/renderer.py
deleted file mode 100644
index 2dd66ab748f795bd3b1915b5b609dc5daace6ce4..0000000000000000000000000000000000000000
--- a/spaces/OpenMotionLab/MotionGPT/mGPT/render/renderer.py
+++ /dev/null
@@ -1,179 +0,0 @@
-"""
-This script is borrowed from https://github.com/mkocabas/VIBE
- Adhere to their licence to use this script
- It has been modified
-"""
-
-import os
-import math
-import trimesh
-
-import pyrender
-import numpy as np
-from pyrender.constants import RenderFlags
-
-
-# os.environ['DISPLAY'] = ':0.0'
-# os.environ['PYOPENGL_PLATFORM'] = 'egl'
-# os.environ['PYOPENGL_PLATFORM'] = 'osmesa'
-SMPL_MODEL_DIR = "data/smpl_data/"
-
-
-def get_smpl_faces():
- return np.load(os.path.join(SMPL_MODEL_DIR, "smplfaces.npy"))
-
-
-class WeakPerspectiveCamera(pyrender.Camera):
- def __init__(self,
- scale,
- translation,
- znear=pyrender.camera.DEFAULT_Z_NEAR,
- zfar=None,
- name=None):
- super(WeakPerspectiveCamera, self).__init__(
- znear=znear,
- zfar=zfar,
- name=name,
- )
- self.scale = scale
- self.translation = translation
-
- def get_projection_matrix(self, width=None, height=None):
- P = np.eye(4)
- P[0, 0] = self.scale[0]
- P[1, 1] = self.scale[1]
- P[0, 3] = self.translation[0] * self.scale[0]
- P[1, 3] = -self.translation[1] * self.scale[1]
- P[2, 2] = -1
- return P
-
-
-class Renderer:
- def __init__(self, background=None, resolution=(224, 224), bg_color=[0, 0, 0, 0.5], orig_img=False, wireframe=False, cam_pose=np.eye(4)):
- width, height = resolution
- self.background = np.zeros((height, width, 3))
- self.resolution = resolution
-
- self.faces = get_smpl_faces()
- self.orig_img = orig_img
- self.wireframe = wireframe
- self.renderer = pyrender.OffscreenRenderer(
- viewport_width=self.resolution[0],
- viewport_height=self.resolution[1],
- point_size=0.5
- )
-
- # set the scene
- self.scene = pyrender.Scene(bg_color=bg_color, ambient_light=(0.4, 0.4, 0.4))
-
- light = pyrender.PointLight(color=[1.0, 1.0, 1.0], intensity=4)
-
-
- light_pose = np.eye(4)
- light_pose[:3, 3] = [0, -1, 1]
- self.scene.add(light, pose=np.dot(cam_pose,light_pose).copy())
-
- light_pose[:3, 3] = [0, 1, 1]
- self.scene.add(light, pose=np.dot(cam_pose,light_pose).copy())
-
- light_pose[:3, 3] = [1, 1, 2]
- self.scene.add(light, pose=np.dot(cam_pose,light_pose).copy())
-
- """ok
- light_pose = np.eye(4)
- light_pose[:3, 3] = [0, -1, 1]
- self.scene.add(light, pose=light_pose)
-
- light_pose[:3, 3] = [0, 1, 1]
- self.scene.add(light, pose=light_pose)
-
- light_pose[:3, 3] = [1, 1, 2]
- self.scene.add(light, pose=light_pose)
- """
-
- # light_pose[:3, 3] = [0, -2, 2]
- # [droite, hauteur, profondeur camera]
- """
- light_pose = np.eye(4)
- light_pose[:3, 3] = [0, -1, 1]
- self.scene.add(light, pose=light_pose)
-
- light_pose[:3, 3] = [0, 1, 1]
- self.scene.add(light, pose=light_pose)
-
- light_pose[:3, 3] = [1, 1, 2]
- self.scene.add(light, pose=light_pose)
- """
-
- def render(self, img, verts, cam, angle=None, axis=None, mesh_filename=None, color=[1.0, 1.0, 0.9],
- cam_pose=np.eye(4)):
- mesh = trimesh.Trimesh(vertices=verts, faces=self.faces, process=False)
- Rx = trimesh.transformations.rotation_matrix(math.radians(180), [1, 0, 0])
- # Rx = trimesh.transformations.rotation_matrix(math.radians(-90), [1, 0, 0])
- mesh.apply_transform(Rx)
-
- if mesh_filename is not None:
- mesh.export(mesh_filename)
-
- if angle and axis:
- R = trimesh.transformations.rotation_matrix(math.radians(angle), axis)
- mesh.apply_transform(R)
-
- sx, sy, tx, ty = cam
-
- camera = WeakPerspectiveCamera(
- scale=[sx, sy],
- translation=[tx, ty],
- zfar=100000.
- )
-
- material = pyrender.MetallicRoughnessMaterial(
- metallicFactor=0.0, # 0.0 for no specular lighting
- # metallicFactor=0.7, # 0.0 for no specular lighting
- alphaMode='OPAQUE',
- baseColorFactor=(color[0], color[1], color[2], 1.0)
- )
-
- mesh = pyrender.Mesh.from_trimesh(mesh, material=material)
-
- mesh_node = self.scene.add(mesh, 'mesh')
-
- cam_node = self.scene.add(camera, pose=cam_pose)
-
- if self.wireframe:
- render_flags = RenderFlags.RGBA | RenderFlags.ALL_WIREFRAME
- else:
- render_flags = RenderFlags.RGBA
-
- rgb, _ = self.renderer.render(self.scene, flags=render_flags)
- if rgb.shape[-1]==3:
- # Debug
- # 0 not distinguish alpha
- valid_mask = (rgb[:, :, -1] > 0)[:, :, np.newaxis]
- output_img = rgb * valid_mask + (1 - valid_mask) * img
- elif rgb.shape[-1]==4:
- # valid_mask = (rgb[:, :, -1] > 128)[:, :, np.newaxis]
- # output_img = rgb[:, :, :-1] * valid_mask + (1 - valid_mask) * img
-
- # # output alpha
- valid_mask = (rgb[:, :, -1] > 128)[:, :]
- output_img = np.copy(rgb)
- output_img[:, :, -1] *= valid_mask
- # output_img = img
- else:
- raise ValueError(f"rgb shape {rgb.shape[-1]} is not correct!")
- image = output_img.astype(np.uint8)
-
- self.scene.remove_node(mesh_node)
- self.scene.remove_node(cam_node)
-
- return image
-
-
-def get_renderer(width, height, cam_pose):
- renderer = Renderer(resolution=(width, height),
- bg_color=[1, 1, 1, 0.5],
- orig_img=False,
- wireframe=False,
- cam_pose=cam_pose)
- return renderer
diff --git a/spaces/OptimalScale/Robin-7b/README.md b/spaces/OptimalScale/Robin-7b/README.md
deleted file mode 100644
index 4a41d7825f93aaac52a1e1b19502f73b4fddd481..0000000000000000000000000000000000000000
--- a/spaces/OptimalScale/Robin-7b/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Robin 7b
-emoji: 🔥
-colorFrom: gray
-colorTo: gray
-sdk: gradio
-sdk_version: 3.27.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/OptimalScale/Robin-7b/lmflow/args.py b/spaces/OptimalScale/Robin-7b/lmflow/args.py
deleted file mode 100644
index 3dd010c08b901772bc2226756554837c293e37ab..0000000000000000000000000000000000000000
--- a/spaces/OptimalScale/Robin-7b/lmflow/args.py
+++ /dev/null
@@ -1,622 +0,0 @@
-#!/usr/bin/env python
-# coding=utf-8
-"""This script defines dataclasses: ModelArguments and DatasetArguments,
-that contain the arguments for the model and dataset used in training.
-
-It imports several modules, including dataclasses, field from typing, Optional from typing,
-require_version from transformers.utils.versions, MODEL_FOR_CAUSAL_LM_MAPPING,
-and TrainingArguments from transformers.
-
-MODEL_CONFIG_CLASSES is assigned a list of the model config classes from
-MODEL_FOR_CAUSAL_LM_MAPPING. MODEL_TYPES is assigned a tuple of the model types
-extracted from the MODEL_CONFIG_CLASSES.
-"""
-
-from dataclasses import dataclass, field
-from typing import Optional, List
-
-from transformers.utils.versions import require_version
-
-from transformers import (
- MODEL_FOR_CAUSAL_LM_MAPPING,
- TrainingArguments,
-)
-
-MODEL_CONFIG_CLASSES = list(MODEL_FOR_CAUSAL_LM_MAPPING.keys())
-MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES)
-
-
-@dataclass
-class ModelArguments:
- """
- Define a class ModelArguments using the dataclass decorator.
- The class contains several optional parameters that can be used to configure a model.
-
- model_name_or_path : str
- a string representing the path or name of a pretrained
- model checkpoint for weights initialization. If None, a model will be trained from scratch.
-
- model_type : str
- a string representing the type of model to use if training from
- scratch. If not provided, a pretrained model will be used.
-
- config_overrides : str
- a string representing the default config settings to override
- when training a model from scratch.
-
- config_name : str
- a string representing the name or path of the pretrained config to
- use, if different from the model_name_or_path.
-
- tokenizer_name : str
- a string representing the name or path of the pretrained tokenizer
- to use, if different from the model_name_or_path.
-
- cache_dir : str
- a string representing the path to the directory where pretrained models
- downloaded from huggingface.co will be stored.
-
- use_fast_tokenizer : bool
- a boolean indicating whether to use a fast tokenizer (backed by the
- tokenizers library) or not.
-
- model_revision : str
- a string representing the specific model version to use (can be a
- branch name, tag name, or commit id).
-
- use_auth_token : bool
- a boolean indicating whether to use the token generated when running
- huggingface-cli login (necessary to use this script with private models).
-
- torch_dtype : str
- a string representing the dtype to load the model under. If auto is
- passed, the dtype will be automatically derived from the model's weights.
-
- use_ram_optimized_load : bool
- a boolean indicating whether to use disk mapping when memory is not
- enough.
- """
-
- model_name_or_path: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "The model checkpoint for weights initialization.Don't set if you want to train a model from scratch."
- )
- },
- )
- lora_model_path: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "The incremental model diff introduced by LoRA finetuning."
- " Along with the original non-finetuned model forms the whole"
- " finetuned model."
- )
- }
- )
- model_type: Optional[str] = field(
- default=None,
- metadata={"help": "If training from scratch, pass a model type from the list: " + ", ".join(MODEL_TYPES)},
- )
- arch_type: Optional[str] = field(
- default="decoder_only",
- metadata={"help": "The architecture type of the model. Currently supported decoder_only or encoder_decoder"}
- )
- config_overrides: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "Override some existing default config settings when a model is trained from scratch. Example: "
- "n_embd=10,resid_pdrop=0.2,scale_attn_weights=false,summary_type=cls_index"
- )
- },
- )
- arch_type: Optional[str] = field(
- default="decoder_only",
- metadata={
- "help": (
- "Model architecture type, e.g. \"decoder_only\","
- " \"encoder_decoder\""
- ),
- "choices": ["decoder_only", "encoder_decoder", "text_regression"],
- },
- )
- config_name: Optional[str] = field(
- default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
- )
- tokenizer_name: Optional[str] = field(
- default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
- )
- cache_dir: Optional[str] = field(
- default=None,
- metadata={"help": "Where do you want to store the pretrained models downloaded from huggingface.co"},
- )
- use_fast_tokenizer: bool = field(
- default=True,
- metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
- )
- model_revision: str = field(
- default="main",
- metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
- )
- use_auth_token: bool = field(
- default=False,
- metadata={
- "help": (
- "Will use the token generated when running `huggingface-cli login` (necessary to use this script "
- "with private models)."
- )
- },
- )
- torch_dtype: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "Override the default `torch.dtype` and load the model under this dtype. If `auto` is passed, the "
- "dtype will be automatically derived from the model's weights."
- ),
- "choices": ["auto", "bfloat16", "float16", "float32"],
- },
- )
- use_lora: bool = field(
- default=False,
- metadata={"help": "Whether to lora."},
- )
- lora_r: int = field(
- default=8,
- metadata={"help": "the rank of the lora parameters. The smaller lora_r is , the fewer parameters lora has."},
- )
- lora_alpha: int = field(
- default=32,
- metadata={"help": "Merging ratio between the fine-tuned model and the original. This is controlled by a parameter called alpha in the paper."},
- )
- lora_target_modules: List[str] = field(
- default=None, metadata={"help": "Pretrained config name or path if not the same as model_name",
- }
- )
- lora_dropout: float = field(
- default=0.1,
- metadata={"help": "The dropout rate in lora.linear."},
- )
- save_aggregated_lora: bool = field(
- default=False,
- metadata={"help": "Whether to save aggregated lora."},
- )
- use_ram_optimized_load: bool = field(
- default=True,
- metadata={"help": "Whether use disk mapping when memory is not enough."}
- )
-
- def __post_init__(self):
- if self.config_overrides is not None and (self.config_name is not None or self.model_name_or_path is not None):
- raise ValueError(
- "--config_overrides can't be used in combination with --config_name or --model_name_or_path"
- )
-
-
-@dataclass
-class DatasetArguments:
- """
- Define a class DatasetArguments using the dataclass decorator.
- The class contains several optional parameters that can be used to configure a dataset for a language model.
-
-
- dataset_path : str
- a string representing the path of the dataset to use.
-
- dataset_name : str
- a string representing the name of the dataset to use. The default value is "customized".
-
- is_custom_dataset : bool
- a boolean indicating whether to use custom data. The default value is False.
-
- customized_cache_dir : str
- a string representing the path to the directory where customized dataset caches will be stored.
-
- dataset_config_name : str
- a string representing the configuration name of the dataset to use (via the datasets library).
-
- train_file : str
- a string representing the path to the input training data file (a text file).
-
- validation_file : str
- a string representing the path to the input evaluation data file to evaluate the perplexity on (a text file).
-
- max_train_samples : int
- an integer indicating the maximum number of training examples to use for debugging or quicker training.
- If set, the training dataset will be truncated to this number.
-
- max_eval_samples: int
- an integer indicating the maximum number of evaluation examples to use for debugging or quicker training.
- If set, the evaluation dataset will be truncated to this number.
-
- streaming : bool
- a boolean indicating whether to enable streaming mode.
-
- block_size: int
- an integer indicating the optional input sequence length after tokenization. The training dataset will be
- truncated in blocks of this size for training.
-
- The class also includes some additional parameters that can be used to configure the dataset further, such as `overwrite_cache`,
- `validation_split_percentage`, `preprocessing_num_workers`, `disable_group_texts`, `demo_example_in_prompt`, `explanation_in_prompt`,
- `keep_linebreaks`, and `prompt_structure`.
-
- The field function is used to set default values and provide help messages for each parameter. The Optional type hint is
- used to indicate that a parameter is optional. The metadata argument is used to provide additional information about
- each parameter, such as a help message.
- """
-
- dataset_path: Optional[str] = field(
- default=None, metadata={"help": "The path of the dataset to use."}
- )
- dataset_name: Optional[str] = field(
- default="customized", metadata={"help": "Should be \"customized\""}
- )
- is_custom_dataset: Optional[bool] = field(
- default=False, metadata={"help": "whether to use custom data"}
- )
- customized_cache_dir: Optional[str] = field(
- default=".cache/llm-ft/datasets",
- metadata={"help": "Where do you want to store the customized dataset caches"},
- )
- dataset_config_name: Optional[str] = field(
- default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
- )
- train_file: Optional[str] = field(default=None, metadata={"help": "The input training data file (a text file)."})
- validation_file: Optional[str] = field(
- default=None,
- metadata={"help": "An optional input evaluation data file to evaluate the perplexity on (a text file)."},
- )
- max_train_samples: Optional[int] = field(
- default=None,
- metadata={
- "help": (
- "For debugging purposes or quicker training, truncate the number of training examples to this "
- "value if set."
- )
- },
- )
- max_eval_samples: Optional[int] = field(
- default=1e10,
- metadata={
- "help": (
- "For debugging purposes or quicker training, truncate the number of evaluation examples to this "
- "value if set."
- )
- },
- )
- streaming: bool = field(default=False, metadata={"help": "Enable streaming mode"})
- block_size: Optional[int] = field(
- default=None,
- metadata={
- "help": (
- "Optional input sequence length after tokenization. "
- "The training dataset will be truncated in block of this size for training. "
- "Default to the model max input length for single sentence inputs (take into account special tokens)."
- )
- },
- )
- overwrite_cache: bool = field(
- default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
- )
- validation_split_percentage: Optional[int] = field(
- default=5,
- metadata={
- "help": "The percentage of the train set used as validation set in case there's no validation split"
- },
- )
- preprocessing_num_workers: Optional[int] = field(
- default=None,
- metadata={"help": "The number of processes to use for the preprocessing."},
- )
- disable_group_texts: bool = field(
- default=False,
- metadata={
- "help": (
- "Whether we group original samples together to generate sample"
- " sequences of length `block_size`. By default, we group every"
- " 1000 tokenized sequences together, divide them into "
- " [{total_num_tokens} / {block_size}] sequences, each with"
- " `block_size` tokens (the remaining tokens are ommited."
- " If this flag is set to True, we only group 1 tokenized"
- " sequence, i.e. cutting long sequence into chunks."
- )
- },
- )
- keep_linebreaks: bool = field(
- default=True, metadata={"help": "Whether to keep line breaks when using TXT files or not."}
- )
- test_file: Optional[str] = field(
- default=None,
- metadata={"help": "Evaluation File Path"},
- )
-
- def __post_init__(self):
- if self.streaming:
- require_version("datasets>=2.0.0", "The streaming feature requires `datasets>=2.0.0`")
-
- if self.dataset_name is None and self.train_file is None and self.validation_file is None:
- raise ValueError("Need either a dataset name or a training/validation file.")
- else:
- if self.train_file is not None:
- extension = self.train_file.split(".")[-1]
- assert extension in ["csv", "json", "txt"], "`train_file` should be a csv, a json or a txt file."
- if self.validation_file is not None:
- extension = self.validation_file.split(".")[-1]
- assert extension in ["csv", "json", "txt"], "`validation_file` should be a csv, a json or a txt file."
-
-
-@dataclass
-class FinetunerArguments(TrainingArguments):
- """
- Adapt transformers.TrainingArguments
- """
- pass
-
-
-@dataclass
-class EvaluatorArguments:
- """
- Define a class EvaluatorArguments using the dataclass decorator. The class contains several optional
- parameters that can be used to configure a evaluator.
-
- local_rank : str
- For distributed training: local_rank
-
- random_shuffle : bool
-
- use_wandb : bool
-
- random_seed : int, default = 1
-
- output_dir : str, default = './output_dir',
-
- mixed_precision : str, choice from ["bf16","fp16"].
- mixed precision mode, whether to use bf16 or fp16
-
- deepspeed :
- Enable deepspeed and pass the path to deepspeed json config file (e.g. ds_config.json) or an already
- loaded json file as a dict
- """
- local_rank: int = field(
- default=-1,
- metadata={"help": "For distributed training: local_rank"
- }
- )
-
- random_shuffle: Optional[bool] = field(
- default=False,
- metadata={"help": ""
- }
- )
-
- use_wandb: Optional[bool] = field(
- default=False,
- metadata={
- "help": (
- "When this flag is True, wandb will be enabled"
- )
- },
- )
- random_seed: Optional[int] = field(
- default=1,
- metadata={
- "help": (
- "used to set random seed"
- )
- },
- )
- output_dir: Optional[str] = field(
- default="./output_dir",
- metadata={"help": "Output path for the inferenced results"},
- )
- mixed_precision: Optional[str] = field(
- default="bf16",
- metadata={
- "help": (
- "mixed precision mode, whether to use bf16 or fp16"
- ),
- "choices": ["bf16","fp16"],
- },
- )
- deepspeed: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "Enable deepspeed and pass the path to deepspeed json config file (e.g. ds_config.json) or an already"
- " loaded json file as a dict"
- )
- },
- )
- answer_type: Optional[str] = field(
- default="text",
- metadata={
- "help": (
- 'Question type for answer extraction from the decoder output.'
- ' Supported types: \n'
- ' 1) "multiple_choice", e.g. A, B, C, D, ...\n'
- ' 2) "binary_choice", e.g. yes, no, maybe\n'
- ' 3) "math", e.g. 1.0, -3.52\n'
- ' 4) "text", e.g. "I think that it is okay"\n'
- ' 5) Special treatment for several datasets\n'
- ' - "gsm8k"\n'
- ' - "svamp"\n'
- ' - "asdiv"\n'
- ' - "addsub"\n'
- ' - "singleeq"\n'
- ' - "multiarith"\n'
- ' - "aqua"\n'
- ' - "csqa"\n'
- ' - "strategyqa"\n'
- ' - "pubmedqa"\n'
- ' - "medmcqa"\n'
- ' - "usmle"\n'
- )
- },
- )
- prompt_structure: Optional[str] = field(
- default="{input}",
- metadata={
- "help": (
- 'Prompt structure to facilitate prompt engineering during'
- ' inference. The model will receive'
- ' `prompt_structure.format(input=input)` as its input.'
- )
- },
- )
- evaluate_block_size: Optional[int] = field(
- default=512,
- metadata={
- "help": (
- "the model will have at least block_size tokens for context when calculating the conditional likelihood of any one token"
- " (provided there are block_size preceding tokens available to condition on)"
- )
- },
- )
- metric: Optional[str] = field(
- default="accuracy",
- metadata={
- "help": "the metric the model will be evaluated on",
- "choices": ["ppl", "perplexity", "acc", "accuracy", "nll", "neg_log_likelihood"],
- },
- )
-
-
-@dataclass
-class InferencerArguments:
- """
- Define a class InferencerArguments using the dataclass decorator. The class contains several optional
- parameters that can be used to configure a inferencer.
-
- local_rank : str
- For distributed training: local_rank
-
- random_seed : int, default = 1
-
- deepspeed :
- Enable deepspeed and pass the path to deepspeed json config file (e.g. ds_config.json) or an already
- loaded json file as a dict
- mixed_precision : str, choice from ["bf16","fp16"].
- mixed precision mode, whether to use bf16 or fp16
-
- """
- device: str = field(
- default="gpu",
- metadata={
- "help": "device of chatbot",
- "choices": ["gpu", "cpu"],
- },
- )
- local_rank: int = field(
- default=-1,
- metadata={"help": "For distributed training: local_rank"
- }
- )
- random_seed: Optional[int] = field(
- default=1,
- metadata={
- "help": (
- "used to set random seed"
- )
- },
- )
- deepspeed: Optional[str] = field(
- default=None,
- metadata={
- "help": (
- "Enable deepspeed and pass the path to deepspeed json config file (e.g. ds_config.json) or an already"
- " loaded json file as a dict"
- )
- },
- )
- mixed_precision: Optional[str] = field(
- default="bf16",
- metadata={
- "help": (
- "mixed precision mode, whether to use bf16 or fp16"
- ),
- "choices": ["bf16","fp16"],
- },
- )
-
-
-@dataclass
-class RaftAlignerArguments(TrainingArguments):
- """
- Define a class RaftAlignerArguments to configure raft aligner.
- """
- output_reward_path: Optional[str] = field(
- default="tmp/raft_aligner/",
- metadata={
- "help": "The path of output rewards."
- }
- )
- output_min_length: Optional[int] = field(
- default=16,
- metadata={
- "help": (
- "minimum length of the output token sequence generated from"
- " model given an input."
- ),
- },
- )
- output_max_length: Optional[int] = field(
- default=48,
- metadata={
- "help": (
- "maximum length of the output token sequence generated from"
- " model given an output."
- ),
- },
- )
- num_raft_iteration: Optional[int] = field(
- default=20,
- metadata={
- "help": "number of iterations of the raft aligner."
- },
- )
- raft_batch_size: Optional[int] = field(
- default=320,
- metadata={
- "help": (
- "only select {raft_batch_size} samples each time to"
- " generate rewards and be ranked for STF training."
- )
- },
- )
- top_reward_percentage: Optional[int] = field(
- default=0.2,
- metadata={
- "help": (
- "only top {top_reward_percentage} samples in the raft batch,"
- " (in terms of rewards), will be used for SFT the model."
- ),
- },
- )
- inference_batch_size_per_device: Optional[int] = field(
- default=1,
- metadata={
- "help": (
- "every device will infer {inference_batch_size_per_device}"
- " samples in parallel. The inferred results will be concatenaed"
- " with inputs and attach a reward."
- ),
- },
- )
-
-
-PIPELINE_ARGUMENT_MAPPING = {
- "finetuner": FinetunerArguments,
- "evaluator": EvaluatorArguments,
- "inferencer": InferencerArguments,
- "raft_aligner": RaftAlignerArguments,
-}
-
-
-class AutoArguments:
- """
- Automatically choose arguments from FinetunerArguments or EvaluatorArguments.
- """
- def get_pipeline_args_class(pipeline_name: str):
- return PIPELINE_ARGUMENT_MAPPING[pipeline_name]
diff --git a/spaces/PAIR/PAIR-Diffusion/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/src/cuda/ms_deform_attn_cuda.h b/spaces/PAIR/PAIR-Diffusion/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/src/cuda/ms_deform_attn_cuda.h
deleted file mode 100644
index 4f0658e8668a11f0e7d71deff9adac71884f2e87..0000000000000000000000000000000000000000
--- a/spaces/PAIR/PAIR-Diffusion/annotator/OneFormer/oneformer/modeling/pixel_decoder/ops/src/cuda/ms_deform_attn_cuda.h
+++ /dev/null
@@ -1,35 +0,0 @@
-/*!
-**************************************************************************************************
-* Deformable DETR
-* Copyright (c) 2020 SenseTime. All Rights Reserved.
-* Licensed under the Apache License, Version 2.0 [see LICENSE for details]
-**************************************************************************************************
-* Modified from https://github.com/chengdazhi/Deformable-Convolution-V2-PyTorch/tree/pytorch_1.0.0
-**************************************************************************************************
-*/
-
-/*!
-* Copyright (c) Facebook, Inc. and its affiliates.
-* Modified by Bowen Cheng from https://github.com/fundamentalvision/Deformable-DETR
-*/
-
-#pragma once
-#include
-
-at::Tensor ms_deform_attn_cuda_forward(
- const at::Tensor &value,
- const at::Tensor &spatial_shapes,
- const at::Tensor &level_start_index,
- const at::Tensor &sampling_loc,
- const at::Tensor &attn_weight,
- const int im2col_step);
-
-std::vector ms_deform_attn_cuda_backward(
- const at::Tensor &value,
- const at::Tensor &spatial_shapes,
- const at::Tensor &level_start_index,
- const at::Tensor &sampling_loc,
- const at::Tensor &attn_weight,
- const at::Tensor &grad_output,
- const int im2col_step);
-
diff --git a/spaces/PKUWilliamYang/StyleGANEX/models/stylegan2/op_ori/fused_act.py b/spaces/PKUWilliamYang/StyleGANEX/models/stylegan2/op_ori/fused_act.py
deleted file mode 100644
index 973a84fffde53668d31397da5fb993bbc95f7be0..0000000000000000000000000000000000000000
--- a/spaces/PKUWilliamYang/StyleGANEX/models/stylegan2/op_ori/fused_act.py
+++ /dev/null
@@ -1,85 +0,0 @@
-import os
-
-import torch
-from torch import nn
-from torch.autograd import Function
-from torch.utils.cpp_extension import load
-
-module_path = os.path.dirname(__file__)
-fused = load(
- 'fused',
- sources=[
- os.path.join(module_path, 'fused_bias_act.cpp'),
- os.path.join(module_path, 'fused_bias_act_kernel.cu'),
- ],
-)
-
-
-class FusedLeakyReLUFunctionBackward(Function):
- @staticmethod
- def forward(ctx, grad_output, out, negative_slope, scale):
- ctx.save_for_backward(out)
- ctx.negative_slope = negative_slope
- ctx.scale = scale
-
- empty = grad_output.new_empty(0)
-
- grad_input = fused.fused_bias_act(
- grad_output, empty, out, 3, 1, negative_slope, scale
- )
-
- dim = [0]
-
- if grad_input.ndim > 2:
- dim += list(range(2, grad_input.ndim))
-
- grad_bias = grad_input.sum(dim).detach()
-
- return grad_input, grad_bias
-
- @staticmethod
- def backward(ctx, gradgrad_input, gradgrad_bias):
- out, = ctx.saved_tensors
- gradgrad_out = fused.fused_bias_act(
- gradgrad_input, gradgrad_bias, out, 3, 1, ctx.negative_slope, ctx.scale
- )
-
- return gradgrad_out, None, None, None
-
-
-class FusedLeakyReLUFunction(Function):
- @staticmethod
- def forward(ctx, input, bias, negative_slope, scale):
- empty = input.new_empty(0)
- out = fused.fused_bias_act(input, bias, empty, 3, 0, negative_slope, scale)
- ctx.save_for_backward(out)
- ctx.negative_slope = negative_slope
- ctx.scale = scale
-
- return out
-
- @staticmethod
- def backward(ctx, grad_output):
- out, = ctx.saved_tensors
-
- grad_input, grad_bias = FusedLeakyReLUFunctionBackward.apply(
- grad_output, out, ctx.negative_slope, ctx.scale
- )
-
- return grad_input, grad_bias, None, None
-
-
-class FusedLeakyReLU(nn.Module):
- def __init__(self, channel, negative_slope=0.2, scale=2 ** 0.5):
- super().__init__()
-
- self.bias = nn.Parameter(torch.zeros(channel))
- self.negative_slope = negative_slope
- self.scale = scale
-
- def forward(self, input):
- return fused_leaky_relu(input, self.bias, self.negative_slope, self.scale)
-
-
-def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
- return FusedLeakyReLUFunction.apply(input, bias, negative_slope, scale)
diff --git a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/web/server.go b/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/web/server.go
deleted file mode 100644
index ea2943c29d2f2801e4d45486aa16964a21ab3ebc..0000000000000000000000000000000000000000
Binary files a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/guile/2.2/ccache/web/server.go and /dev/null differ
diff --git a/spaces/PeepDaSlan9/AutoGPT/autogpt/commands/web_requests.py b/spaces/PeepDaSlan9/AutoGPT/autogpt/commands/web_requests.py
deleted file mode 100644
index 406338f46fc7b2381e0b1634c628b123ef20b685..0000000000000000000000000000000000000000
--- a/spaces/PeepDaSlan9/AutoGPT/autogpt/commands/web_requests.py
+++ /dev/null
@@ -1,190 +0,0 @@
-"""Browse a webpage and summarize it using the LLM model"""
-from __future__ import annotations
-
-from urllib.parse import urljoin, urlparse
-
-import requests
-from bs4 import BeautifulSoup
-from requests import Response
-from requests.compat import urljoin
-
-from autogpt.config import Config
-from autogpt.memory import get_memory
-from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
-
-CFG = Config()
-memory = get_memory(CFG)
-
-session = requests.Session()
-session.headers.update({"User-Agent": CFG.user_agent})
-
-
-def is_valid_url(url: str) -> bool:
- """Check if the URL is valid
-
- Args:
- url (str): The URL to check
-
- Returns:
- bool: True if the URL is valid, False otherwise
- """
- try:
- result = urlparse(url)
- return all([result.scheme, result.netloc])
- except ValueError:
- return False
-
-
-def sanitize_url(url: str) -> str:
- """Sanitize the URL
-
- Args:
- url (str): The URL to sanitize
-
- Returns:
- str: The sanitized URL
- """
- return urljoin(url, urlparse(url).path)
-
-
-def check_local_file_access(url: str) -> bool:
- """Check if the URL is a local file
-
- Args:
- url (str): The URL to check
-
- Returns:
- bool: True if the URL is a local file, False otherwise
- """
- local_prefixes = [
- "file:///",
- "file://localhost/",
- "file://localhost",
- "http://localhost",
- "http://localhost/",
- "https://localhost",
- "https://localhost/",
- "http://2130706433",
- "http://2130706433/",
- "https://2130706433",
- "https://2130706433/",
- "http://127.0.0.1/",
- "http://127.0.0.1",
- "https://127.0.0.1/",
- "https://127.0.0.1",
- "https://0.0.0.0/",
- "https://0.0.0.0",
- "http://0.0.0.0/",
- "http://0.0.0.0",
- "http://0000",
- "http://0000/",
- "https://0000",
- "https://0000/",
- ]
- return any(url.startswith(prefix) for prefix in local_prefixes)
-
-
-def get_response(
- url: str, timeout: int = 10
-) -> tuple[None, str] | tuple[Response, None]:
- """Get the response from a URL
-
- Args:
- url (str): The URL to get the response from
- timeout (int): The timeout for the HTTP request
-
- Returns:
- tuple[None, str] | tuple[Response, None]: The response and error message
-
- Raises:
- ValueError: If the URL is invalid
- requests.exceptions.RequestException: If the HTTP request fails
- """
- try:
- # Restrict access to local files
- if check_local_file_access(url):
- raise ValueError("Access to local files is restricted")
-
- # Most basic check if the URL is valid:
- if not url.startswith("http://") and not url.startswith("https://"):
- raise ValueError("Invalid URL format")
-
- sanitized_url = sanitize_url(url)
-
- response = session.get(sanitized_url, timeout=timeout)
-
- # Check if the response contains an HTTP error
- if response.status_code >= 400:
- return None, f"Error: HTTP {str(response.status_code)} error"
-
- return response, None
- except ValueError as ve:
- # Handle invalid URL format
- return None, f"Error: {str(ve)}"
-
- except requests.exceptions.RequestException as re:
- # Handle exceptions related to the HTTP request
- # (e.g., connection errors, timeouts, etc.)
- return None, f"Error: {str(re)}"
-
-
-def scrape_text(url: str) -> str:
- """Scrape text from a webpage
-
- Args:
- url (str): The URL to scrape text from
-
- Returns:
- str: The scraped text
- """
- response, error_message = get_response(url)
- if error_message:
- return error_message
- if not response:
- return "Error: Could not get response"
-
- soup = BeautifulSoup(response.text, "html.parser")
-
- for script in soup(["script", "style"]):
- script.extract()
-
- text = soup.get_text()
- lines = (line.strip() for line in text.splitlines())
- chunks = (phrase.strip() for line in lines for phrase in line.split(" "))
- text = "\n".join(chunk for chunk in chunks if chunk)
-
- return text
-
-
-def scrape_links(url: str) -> str | list[str]:
- """Scrape links from a webpage
-
- Args:
- url (str): The URL to scrape links from
-
- Returns:
- str | list[str]: The scraped links
- """
- response, error_message = get_response(url)
- if error_message:
- return error_message
- if not response:
- return "Error: Could not get response"
- soup = BeautifulSoup(response.text, "html.parser")
-
- for script in soup(["script", "style"]):
- script.extract()
-
- hyperlinks = extract_hyperlinks(soup, url)
-
- return format_hyperlinks(hyperlinks)
-
-
-def create_message(chunk, question):
- """Create a message for the user to summarize a chunk of text"""
- return {
- "role": "user",
- "content": f'"""{chunk}""" Using the above text, answer the following'
- f' question: "{question}" -- if the question cannot be answered using the'
- " text, summarize the text.",
- }
diff --git a/spaces/PeepDaSlan9/candle-llama2/app-c34faa410cb6796f.js b/spaces/PeepDaSlan9/candle-llama2/app-c34faa410cb6796f.js
deleted file mode 100644
index cdbd6e89620ee7e4eddedf44b0ab8fd2985acfd0..0000000000000000000000000000000000000000
--- a/spaces/PeepDaSlan9/candle-llama2/app-c34faa410cb6796f.js
+++ /dev/null
@@ -1,829 +0,0 @@
-let wasm;
-
-const heap = new Array(128).fill(undefined);
-
-heap.push(undefined, null, true, false);
-
-function getObject(idx) { return heap[idx]; }
-
-let heap_next = heap.length;
-
-function dropObject(idx) {
- if (idx < 132) return;
- heap[idx] = heap_next;
- heap_next = idx;
-}
-
-function takeObject(idx) {
- const ret = getObject(idx);
- dropObject(idx);
- return ret;
-}
-
-const cachedTextDecoder = (typeof TextDecoder !== 'undefined' ? new TextDecoder('utf-8', { ignoreBOM: true, fatal: true }) : { decode: () => { throw Error('TextDecoder not available') } } );
-
-if (typeof TextDecoder !== 'undefined') { cachedTextDecoder.decode(); };
-
-let cachedUint8Memory0 = null;
-
-function getUint8Memory0() {
- if (cachedUint8Memory0 === null || cachedUint8Memory0.byteLength === 0) {
- cachedUint8Memory0 = new Uint8Array(wasm.memory.buffer);
- }
- return cachedUint8Memory0;
-}
-
-function getStringFromWasm0(ptr, len) {
- ptr = ptr >>> 0;
- return cachedTextDecoder.decode(getUint8Memory0().subarray(ptr, ptr + len));
-}
-
-function addHeapObject(obj) {
- if (heap_next === heap.length) heap.push(heap.length + 1);
- const idx = heap_next;
- heap_next = heap[idx];
-
- heap[idx] = obj;
- return idx;
-}
-
-function debugString(val) {
- // primitive types
- const type = typeof val;
- if (type == 'number' || type == 'boolean' || val == null) {
- return `${val}`;
- }
- if (type == 'string') {
- return `"${val}"`;
- }
- if (type == 'symbol') {
- const description = val.description;
- if (description == null) {
- return 'Symbol';
- } else {
- return `Symbol(${description})`;
- }
- }
- if (type == 'function') {
- const name = val.name;
- if (typeof name == 'string' && name.length > 0) {
- return `Function(${name})`;
- } else {
- return 'Function';
- }
- }
- // objects
- if (Array.isArray(val)) {
- const length = val.length;
- let debug = '[';
- if (length > 0) {
- debug += debugString(val[0]);
- }
- for(let i = 1; i < length; i++) {
- debug += ', ' + debugString(val[i]);
- }
- debug += ']';
- return debug;
- }
- // Test for built-in
- const builtInMatches = /\[object ([^\]]+)\]/.exec(toString.call(val));
- let className;
- if (builtInMatches.length > 1) {
- className = builtInMatches[1];
- } else {
- // Failed to match the standard '[object ClassName]'
- return toString.call(val);
- }
- if (className == 'Object') {
- // we're a user defined class or Object
- // JSON.stringify avoids problems with cycles, and is generally much
- // easier than looping through ownProperties of `val`.
- try {
- return 'Object(' + JSON.stringify(val) + ')';
- } catch (_) {
- return 'Object';
- }
- }
- // errors
- if (val instanceof Error) {
- return `${val.name}: ${val.message}\n${val.stack}`;
- }
- // TODO we could test for more things here, like `Set`s and `Map`s.
- return className;
-}
-
-let WASM_VECTOR_LEN = 0;
-
-const cachedTextEncoder = (typeof TextEncoder !== 'undefined' ? new TextEncoder('utf-8') : { encode: () => { throw Error('TextEncoder not available') } } );
-
-const encodeString = (typeof cachedTextEncoder.encodeInto === 'function'
- ? function (arg, view) {
- return cachedTextEncoder.encodeInto(arg, view);
-}
- : function (arg, view) {
- const buf = cachedTextEncoder.encode(arg);
- view.set(buf);
- return {
- read: arg.length,
- written: buf.length
- };
-});
-
-function passStringToWasm0(arg, malloc, realloc) {
-
- if (realloc === undefined) {
- const buf = cachedTextEncoder.encode(arg);
- const ptr = malloc(buf.length, 1) >>> 0;
- getUint8Memory0().subarray(ptr, ptr + buf.length).set(buf);
- WASM_VECTOR_LEN = buf.length;
- return ptr;
- }
-
- let len = arg.length;
- let ptr = malloc(len, 1) >>> 0;
-
- const mem = getUint8Memory0();
-
- let offset = 0;
-
- for (; offset < len; offset++) {
- const code = arg.charCodeAt(offset);
- if (code > 0x7F) break;
- mem[ptr + offset] = code;
- }
-
- if (offset !== len) {
- if (offset !== 0) {
- arg = arg.slice(offset);
- }
- ptr = realloc(ptr, len, len = offset + arg.length * 3, 1) >>> 0;
- const view = getUint8Memory0().subarray(ptr + offset, ptr + len);
- const ret = encodeString(arg, view);
-
- offset += ret.written;
- }
-
- WASM_VECTOR_LEN = offset;
- return ptr;
-}
-
-let cachedInt32Memory0 = null;
-
-function getInt32Memory0() {
- if (cachedInt32Memory0 === null || cachedInt32Memory0.byteLength === 0) {
- cachedInt32Memory0 = new Int32Array(wasm.memory.buffer);
- }
- return cachedInt32Memory0;
-}
-
-function makeClosure(arg0, arg1, dtor, f) {
- const state = { a: arg0, b: arg1, cnt: 1, dtor };
- const real = (...args) => {
- // First up with a closure we increment the internal reference
- // count. This ensures that the Rust closure environment won't
- // be deallocated while we're invoking it.
- state.cnt++;
- try {
- return f(state.a, state.b, ...args);
- } finally {
- if (--state.cnt === 0) {
- wasm.__wbindgen_export_2.get(state.dtor)(state.a, state.b);
- state.a = 0;
-
- }
- }
- };
- real.original = state;
-
- return real;
-}
-function __wbg_adapter_18(arg0, arg1, arg2) {
- wasm.wasm_bindgen__convert__closures__invoke1__h234ab1c7c4bef2e0(arg0, arg1, addHeapObject(arg2));
-}
-
-function makeMutClosure(arg0, arg1, dtor, f) {
- const state = { a: arg0, b: arg1, cnt: 1, dtor };
- const real = (...args) => {
- // First up with a closure we increment the internal reference
- // count. This ensures that the Rust closure environment won't
- // be deallocated while we're invoking it.
- state.cnt++;
- const a = state.a;
- state.a = 0;
- try {
- return f(a, state.b, ...args);
- } finally {
- if (--state.cnt === 0) {
- wasm.__wbindgen_export_2.get(state.dtor)(a, state.b);
-
- } else {
- state.a = a;
- }
- }
- };
- real.original = state;
-
- return real;
-}
-
-let stack_pointer = 128;
-
-function addBorrowedObject(obj) {
- if (stack_pointer == 1) throw new Error('out of js stack');
- heap[--stack_pointer] = obj;
- return stack_pointer;
-}
-function __wbg_adapter_21(arg0, arg1, arg2) {
- try {
- wasm._dyn_core__ops__function__FnMut___A____Output___R_as_wasm_bindgen__closure__WasmClosure___describe__invoke__hadab26222cba6f84(arg0, arg1, addBorrowedObject(arg2));
- } finally {
- heap[stack_pointer++] = undefined;
- }
-}
-
-function __wbg_adapter_24(arg0, arg1, arg2) {
- wasm._dyn_core__ops__function__FnMut__A____Output___R_as_wasm_bindgen__closure__WasmClosure___describe__invoke__hfc3f0e78cf729c36(arg0, arg1, addHeapObject(arg2));
-}
-
-function isLikeNone(x) {
- return x === undefined || x === null;
-}
-
-let cachedUint32Memory0 = null;
-
-function getUint32Memory0() {
- if (cachedUint32Memory0 === null || cachedUint32Memory0.byteLength === 0) {
- cachedUint32Memory0 = new Uint32Array(wasm.memory.buffer);
- }
- return cachedUint32Memory0;
-}
-
-function getArrayJsValueFromWasm0(ptr, len) {
- ptr = ptr >>> 0;
- const mem = getUint32Memory0();
- const slice = mem.subarray(ptr / 4, ptr / 4 + len);
- const result = [];
- for (let i = 0; i < slice.length; i++) {
- result.push(takeObject(slice[i]));
- }
- return result;
-}
-
-function handleError(f, args) {
- try {
- return f.apply(this, args);
- } catch (e) {
- wasm.__wbindgen_exn_store(addHeapObject(e));
- }
-}
-
-async function __wbg_load(module, imports) {
- if (typeof Response === 'function' && module instanceof Response) {
- if (typeof WebAssembly.instantiateStreaming === 'function') {
- try {
- return await WebAssembly.instantiateStreaming(module, imports);
-
- } catch (e) {
- if (module.headers.get('Content-Type') != 'application/wasm') {
- console.warn("`WebAssembly.instantiateStreaming` failed because your server does not serve wasm with `application/wasm` MIME type. Falling back to `WebAssembly.instantiate` which is slower. Original error:\n", e);
-
- } else {
- throw e;
- }
- }
- }
-
- const bytes = await module.arrayBuffer();
- return await WebAssembly.instantiate(bytes, imports);
-
- } else {
- const instance = await WebAssembly.instantiate(module, imports);
-
- if (instance instanceof WebAssembly.Instance) {
- return { instance, module };
-
- } else {
- return instance;
- }
- }
-}
-
-function __wbg_get_imports() {
- const imports = {};
- imports.wbg = {};
- imports.wbg.__wbindgen_object_drop_ref = function(arg0) {
- takeObject(arg0);
- };
- imports.wbg.__wbg_log_3af90b48c052f90b = function(arg0, arg1) {
- console.log(getStringFromWasm0(arg0, arg1));
- };
- imports.wbg.__wbindgen_cb_drop = function(arg0) {
- const obj = takeObject(arg0).original;
- if (obj.cnt-- == 1) {
- obj.a = 0;
- return true;
- }
- const ret = false;
- return ret;
- };
- imports.wbg.__wbindgen_string_new = function(arg0, arg1) {
- const ret = getStringFromWasm0(arg0, arg1);
- return addHeapObject(ret);
- };
- imports.wbg.__wbindgen_object_clone_ref = function(arg0) {
- const ret = getObject(arg0);
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_listenerid_12315eee21527820 = function(arg0, arg1) {
- const ret = getObject(arg1).__yew_listener_id;
- getInt32Memory0()[arg0 / 4 + 1] = isLikeNone(ret) ? 0 : ret;
- getInt32Memory0()[arg0 / 4 + 0] = !isLikeNone(ret);
- };
- imports.wbg.__wbg_setlistenerid_3183aae8fa5840fb = function(arg0, arg1) {
- getObject(arg0).__yew_listener_id = arg1 >>> 0;
- };
- imports.wbg.__wbg_setsubtreeid_d32e6327eef1f7fc = function(arg0, arg1) {
- getObject(arg0).__yew_subtree_id = arg1 >>> 0;
- };
- imports.wbg.__wbg_subtreeid_e348577f7ef777e3 = function(arg0, arg1) {
- const ret = getObject(arg1).__yew_subtree_id;
- getInt32Memory0()[arg0 / 4 + 1] = isLikeNone(ret) ? 0 : ret;
- getInt32Memory0()[arg0 / 4 + 0] = !isLikeNone(ret);
- };
- imports.wbg.__wbg_cachekey_b61393159c57fd7b = function(arg0, arg1) {
- const ret = getObject(arg1).__yew_subtree_cache_key;
- getInt32Memory0()[arg0 / 4 + 1] = isLikeNone(ret) ? 0 : ret;
- getInt32Memory0()[arg0 / 4 + 0] = !isLikeNone(ret);
- };
- imports.wbg.__wbg_setcachekey_80183b7cfc421143 = function(arg0, arg1) {
- getObject(arg0).__yew_subtree_cache_key = arg1 >>> 0;
- };
- imports.wbg.__wbg_error_71d6845bf00a930f = function(arg0, arg1) {
- var v0 = getArrayJsValueFromWasm0(arg0, arg1).slice();
- wasm.__wbindgen_free(arg0, arg1 * 4);
- console.error(...v0);
- };
- imports.wbg.__wbg_warn_0b90a269a514ae1d = function(arg0, arg1) {
- var v0 = getArrayJsValueFromWasm0(arg0, arg1).slice();
- wasm.__wbindgen_free(arg0, arg1 * 4);
- console.warn(...v0);
- };
- imports.wbg.__wbg_new_abda76e883ba8a5f = function() {
- const ret = new Error();
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_stack_658279fe44541cf6 = function(arg0, arg1) {
- const ret = getObject(arg1).stack;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_error_f851667af71bcfc6 = function(arg0, arg1) {
- let deferred0_0;
- let deferred0_1;
- try {
- deferred0_0 = arg0;
- deferred0_1 = arg1;
- console.error(getStringFromWasm0(arg0, arg1));
- } finally {
- wasm.__wbindgen_free(deferred0_0, deferred0_1, 1);
- }
- };
- imports.wbg.__wbg_location_7ac41949b772ef21 = function(arg0) {
- const ret = getObject(arg0).location;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_body_674aec4c1c0910cd = function(arg0) {
- const ret = getObject(arg0).body;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_createElement_4891554b28d3388b = function() { return handleError(function (arg0, arg1, arg2) {
- const ret = getObject(arg0).createElement(getStringFromWasm0(arg1, arg2));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_createElementNS_119acf9e82482041 = function() { return handleError(function (arg0, arg1, arg2, arg3, arg4) {
- const ret = getObject(arg0).createElementNS(arg1 === 0 ? undefined : getStringFromWasm0(arg1, arg2), getStringFromWasm0(arg3, arg4));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_createTextNode_2fd22cd7e543f938 = function(arg0, arg1, arg2) {
- const ret = getObject(arg0).createTextNode(getStringFromWasm0(arg1, arg2));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_instanceof_Window_9029196b662bc42a = function(arg0) {
- let result;
- try {
- result = getObject(arg0) instanceof Window;
- } catch {
- result = false;
- }
- const ret = result;
- return ret;
- };
- imports.wbg.__wbg_document_f7ace2b956f30a4f = function(arg0) {
- const ret = getObject(arg0).document;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_location_56243dba507f472d = function(arg0) {
- const ret = getObject(arg0).location;
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_performance_2c295061c8b01e0b = function(arg0) {
- const ret = getObject(arg0).performance;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_fetch_336b6f0cb426b46e = function(arg0, arg1) {
- const ret = getObject(arg0).fetch(getObject(arg1));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_setchecked_e5a50baea447b8a8 = function(arg0, arg1) {
- getObject(arg0).checked = arg1 !== 0;
- };
- imports.wbg.__wbg_value_9423da9d988ee8cf = function(arg0, arg1) {
- const ret = getObject(arg1).value;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_setvalue_1f95e61cbc382f7f = function(arg0, arg1, arg2) {
- getObject(arg0).value = getStringFromWasm0(arg1, arg2);
- };
- imports.wbg.__wbg_newwithstrandinit_cad5cd6038c7ff5d = function() { return handleError(function (arg0, arg1, arg2) {
- const ret = new Request(getStringFromWasm0(arg0, arg1), getObject(arg2));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_setonmessage_f0bd0280573b7084 = function(arg0, arg1) {
- getObject(arg0).onmessage = getObject(arg1);
- };
- imports.wbg.__wbg_new_8e7322f46d5d019c = function() { return handleError(function (arg0, arg1) {
- const ret = new Worker(getStringFromWasm0(arg0, arg1));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_newwithoptions_1bd20b45061ed935 = function() { return handleError(function (arg0, arg1, arg2) {
- const ret = new Worker(getStringFromWasm0(arg0, arg1), getObject(arg2));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_postMessage_8c609e2bde333d9c = function() { return handleError(function (arg0, arg1) {
- getObject(arg0).postMessage(getObject(arg1));
- }, arguments) };
- imports.wbg.__wbg_instanceof_Response_fc4327dbfcdf5ced = function(arg0) {
- let result;
- try {
- result = getObject(arg0) instanceof Response;
- } catch {
- result = false;
- }
- const ret = result;
- return ret;
- };
- imports.wbg.__wbg_blob_34990e4300d45f53 = function() { return handleError(function (arg0) {
- const ret = getObject(arg0).blob();
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_now_0cfdc90c97d0c24b = function(arg0) {
- const ret = getObject(arg0).now();
- return ret;
- };
- imports.wbg.__wbg_debug_9b8701f894da9929 = function(arg0, arg1, arg2, arg3) {
- console.debug(getObject(arg0), getObject(arg1), getObject(arg2), getObject(arg3));
- };
- imports.wbg.__wbg_error_788ae33f81d3b84b = function(arg0) {
- console.error(getObject(arg0));
- };
- imports.wbg.__wbg_error_d9bce418caafb712 = function(arg0, arg1, arg2, arg3) {
- console.error(getObject(arg0), getObject(arg1), getObject(arg2), getObject(arg3));
- };
- imports.wbg.__wbg_info_bb52f40b06f679de = function(arg0, arg1, arg2, arg3) {
- console.info(getObject(arg0), getObject(arg1), getObject(arg2), getObject(arg3));
- };
- imports.wbg.__wbg_log_ea7093e35e3efd07 = function(arg0, arg1, arg2, arg3) {
- console.log(getObject(arg0), getObject(arg1), getObject(arg2), getObject(arg3));
- };
- imports.wbg.__wbg_warn_dfc0e0cf544a13bd = function(arg0, arg1, arg2, arg3) {
- console.warn(getObject(arg0), getObject(arg1), getObject(arg2), getObject(arg3));
- };
- imports.wbg.__wbg_instanceof_Element_4622f5da1249a3eb = function(arg0) {
- let result;
- try {
- result = getObject(arg0) instanceof Element;
- } catch {
- result = false;
- }
- const ret = result;
- return ret;
- };
- imports.wbg.__wbg_namespaceURI_31718ed49b5343a3 = function(arg0, arg1) {
- const ret = getObject(arg1).namespaceURI;
- var ptr1 = isLikeNone(ret) ? 0 : passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- var len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_setinnerHTML_b089587252408b67 = function(arg0, arg1, arg2) {
- getObject(arg0).innerHTML = getStringFromWasm0(arg1, arg2);
- };
- imports.wbg.__wbg_outerHTML_f7749ceff37b5832 = function(arg0, arg1) {
- const ret = getObject(arg1).outerHTML;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_children_27ed308801b57d3f = function(arg0) {
- const ret = getObject(arg0).children;
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_removeAttribute_d8404da431968808 = function() { return handleError(function (arg0, arg1, arg2) {
- getObject(arg0).removeAttribute(getStringFromWasm0(arg1, arg2));
- }, arguments) };
- imports.wbg.__wbg_setAttribute_e7e80b478b7b8b2f = function() { return handleError(function (arg0, arg1, arg2, arg3, arg4) {
- getObject(arg0).setAttribute(getStringFromWasm0(arg1, arg2), getStringFromWasm0(arg3, arg4));
- }, arguments) };
- imports.wbg.__wbg_origin_50aa482fa6784a0a = function() { return handleError(function (arg0, arg1) {
- const ret = getObject(arg1).origin;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- }, arguments) };
- imports.wbg.__wbg_pathname_c8fd5c498079312d = function() { return handleError(function (arg0, arg1) {
- const ret = getObject(arg1).pathname;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- }, arguments) };
- imports.wbg.__wbg_data_ab99ae4a2e1e8bc9 = function(arg0) {
- const ret = getObject(arg0).data;
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_target_f171e89c61e2bccf = function(arg0) {
- const ret = getObject(arg0).target;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_bubbles_63572b91f3885ef1 = function(arg0) {
- const ret = getObject(arg0).bubbles;
- return ret;
- };
- imports.wbg.__wbg_cancelBubble_90d1c3aa2a76cbeb = function(arg0) {
- const ret = getObject(arg0).cancelBubble;
- return ret;
- };
- imports.wbg.__wbg_composedPath_cf1bb5b8bcff496f = function(arg0) {
- const ret = getObject(arg0).composedPath();
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_parentNode_9e53f8b17eb98c9d = function(arg0) {
- const ret = getObject(arg0).parentNode;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_parentElement_c75962bc9997ea5f = function(arg0) {
- const ret = getObject(arg0).parentElement;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_lastChild_0cee692010bac6c2 = function(arg0) {
- const ret = getObject(arg0).lastChild;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_nextSibling_304d9aac7c2774ae = function(arg0) {
- const ret = getObject(arg0).nextSibling;
- return isLikeNone(ret) ? 0 : addHeapObject(ret);
- };
- imports.wbg.__wbg_setnodeValue_d1c8382910b45e04 = function(arg0, arg1, arg2) {
- getObject(arg0).nodeValue = arg1 === 0 ? undefined : getStringFromWasm0(arg1, arg2);
- };
- imports.wbg.__wbg_textContent_c5d9e21ee03c63d4 = function(arg0, arg1) {
- const ret = getObject(arg1).textContent;
- var ptr1 = isLikeNone(ret) ? 0 : passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- var len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_appendChild_51339d4cde00ee22 = function() { return handleError(function (arg0, arg1) {
- const ret = getObject(arg0).appendChild(getObject(arg1));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_insertBefore_ffa01d4b747c95fc = function() { return handleError(function (arg0, arg1, arg2) {
- const ret = getObject(arg0).insertBefore(getObject(arg1), getObject(arg2));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_removeChild_973429f368206138 = function() { return handleError(function (arg0, arg1) {
- const ret = getObject(arg0).removeChild(getObject(arg1));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_createObjectURL_d82f2880bada6a1d = function() { return handleError(function (arg0, arg1) {
- const ret = URL.createObjectURL(getObject(arg1));
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- }, arguments) };
- imports.wbg.__wbg_newwithstrsequenceandoptions_fd88a547f6d15707 = function() { return handleError(function (arg0, arg1) {
- const ret = new Blob(getObject(arg0), getObject(arg1));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_arrayBuffer_27cefaea55cbf063 = function(arg0) {
- const ret = getObject(arg0).arrayBuffer();
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_addEventListener_a5963e26cd7b176b = function() { return handleError(function (arg0, arg1, arg2, arg3, arg4) {
- getObject(arg0).addEventListener(getStringFromWasm0(arg1, arg2), getObject(arg3), getObject(arg4));
- }, arguments) };
- imports.wbg.__wbg_instanceof_ShadowRoot_b64337370f59fe2d = function(arg0) {
- let result;
- try {
- result = getObject(arg0) instanceof ShadowRoot;
- } catch {
- result = false;
- }
- const ret = result;
- return ret;
- };
- imports.wbg.__wbg_host_e1c47c33975060d3 = function(arg0) {
- const ret = getObject(arg0).host;
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_value_3c5f08ffc2b7d6f9 = function(arg0, arg1) {
- const ret = getObject(arg1).value;
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbg_setvalue_0dc100d4b9908028 = function(arg0, arg1, arg2) {
- getObject(arg0).value = getStringFromWasm0(arg1, arg2);
- };
- imports.wbg.__wbg_get_44be0491f933a435 = function(arg0, arg1) {
- const ret = getObject(arg0)[arg1 >>> 0];
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_length_fff51ee6522a1a18 = function(arg0) {
- const ret = getObject(arg0).length;
- return ret;
- };
- imports.wbg.__wbg_new_898a68150f225f2e = function() {
- const ret = new Array();
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_newnoargs_581967eacc0e2604 = function(arg0, arg1) {
- const ret = new Function(getStringFromWasm0(arg0, arg1));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_call_cb65541d95d71282 = function() { return handleError(function (arg0, arg1) {
- const ret = getObject(arg0).call(getObject(arg1));
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_new_b51585de1b234aff = function() {
- const ret = new Object();
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_self_1ff1d729e9aae938 = function() { return handleError(function () {
- const ret = self.self;
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_window_5f4faef6c12b79ec = function() { return handleError(function () {
- const ret = window.window;
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_globalThis_1d39714405582d3c = function() { return handleError(function () {
- const ret = globalThis.globalThis;
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbg_global_651f05c6a0944d1c = function() { return handleError(function () {
- const ret = global.global;
- return addHeapObject(ret);
- }, arguments) };
- imports.wbg.__wbindgen_is_undefined = function(arg0) {
- const ret = getObject(arg0) === undefined;
- return ret;
- };
- imports.wbg.__wbg_from_d7c216d4616bb368 = function(arg0) {
- const ret = Array.from(getObject(arg0));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_push_ca1c26067ef907ac = function(arg0, arg1) {
- const ret = getObject(arg0).push(getObject(arg1));
- return ret;
- };
- imports.wbg.__wbg_is_205d914af04a8faa = function(arg0, arg1) {
- const ret = Object.is(getObject(arg0), getObject(arg1));
- return ret;
- };
- imports.wbg.__wbg_resolve_53698b95aaf7fcf8 = function(arg0) {
- const ret = Promise.resolve(getObject(arg0));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_then_f7e06ee3c11698eb = function(arg0, arg1) {
- const ret = getObject(arg0).then(getObject(arg1));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_then_b2267541e2a73865 = function(arg0, arg1, arg2) {
- const ret = getObject(arg0).then(getObject(arg1), getObject(arg2));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_buffer_085ec1f694018c4f = function(arg0) {
- const ret = getObject(arg0).buffer;
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_newwithbyteoffsetandlength_6da8e527659b86aa = function(arg0, arg1, arg2) {
- const ret = new Uint8Array(getObject(arg0), arg1 >>> 0, arg2 >>> 0);
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_new_8125e318e6245eed = function(arg0) {
- const ret = new Uint8Array(getObject(arg0));
- return addHeapObject(ret);
- };
- imports.wbg.__wbg_set_5cf90238115182c3 = function(arg0, arg1, arg2) {
- getObject(arg0).set(getObject(arg1), arg2 >>> 0);
- };
- imports.wbg.__wbg_length_72e2208bbc0efc61 = function(arg0) {
- const ret = getObject(arg0).length;
- return ret;
- };
- imports.wbg.__wbg_set_092e06b0f9d71865 = function() { return handleError(function (arg0, arg1, arg2) {
- const ret = Reflect.set(getObject(arg0), getObject(arg1), getObject(arg2));
- return ret;
- }, arguments) };
- imports.wbg.__wbindgen_debug_string = function(arg0, arg1) {
- const ret = debugString(getObject(arg1));
- const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
- const len1 = WASM_VECTOR_LEN;
- getInt32Memory0()[arg0 / 4 + 1] = len1;
- getInt32Memory0()[arg0 / 4 + 0] = ptr1;
- };
- imports.wbg.__wbindgen_throw = function(arg0, arg1) {
- throw new Error(getStringFromWasm0(arg0, arg1));
- };
- imports.wbg.__wbindgen_memory = function() {
- const ret = wasm.memory;
- return addHeapObject(ret);
- };
- imports.wbg.__wbindgen_closure_wrapper167 = function(arg0, arg1, arg2) {
- const ret = makeClosure(arg0, arg1, 36, __wbg_adapter_18);
- return addHeapObject(ret);
- };
- imports.wbg.__wbindgen_closure_wrapper396 = function(arg0, arg1, arg2) {
- const ret = makeMutClosure(arg0, arg1, 134, __wbg_adapter_21);
- return addHeapObject(ret);
- };
- imports.wbg.__wbindgen_closure_wrapper675 = function(arg0, arg1, arg2) {
- const ret = makeMutClosure(arg0, arg1, 242, __wbg_adapter_24);
- return addHeapObject(ret);
- };
-
- return imports;
-}
-
-function __wbg_init_memory(imports, maybe_memory) {
-
-}
-
-function __wbg_finalize_init(instance, module) {
- wasm = instance.exports;
- __wbg_init.__wbindgen_wasm_module = module;
- cachedInt32Memory0 = null;
- cachedUint32Memory0 = null;
- cachedUint8Memory0 = null;
-
- wasm.__wbindgen_start();
- return wasm;
-}
-
-function initSync(module) {
- if (wasm !== undefined) return wasm;
-
- const imports = __wbg_get_imports();
-
- __wbg_init_memory(imports);
-
- if (!(module instanceof WebAssembly.Module)) {
- module = new WebAssembly.Module(module);
- }
-
- const instance = new WebAssembly.Instance(module, imports);
-
- return __wbg_finalize_init(instance, module);
-}
-
-async function __wbg_init(input) {
- if (wasm !== undefined) return wasm;
-
- if (typeof input === 'undefined') {
- input = new URL('app-c34faa410cb6796f_bg.wasm', import.meta.url);
- }
- const imports = __wbg_get_imports();
-
- if (typeof input === 'string' || (typeof Request === 'function' && input instanceof Request) || (typeof URL === 'function' && input instanceof URL)) {
- input = fetch(input);
- }
-
- __wbg_init_memory(imports);
-
- const { instance, module } = await __wbg_load(await input, imports);
-
- return __wbg_finalize_init(instance, module);
-}
-
-export { initSync }
-export default __wbg_init;
diff --git a/spaces/Pengyey/bingo-chuchu/src/components/chat-notification.tsx b/spaces/Pengyey/bingo-chuchu/src/components/chat-notification.tsx
deleted file mode 100644
index 3474e522992c43a4d1d0eadcf205a9760d5b930b..0000000000000000000000000000000000000000
--- a/spaces/Pengyey/bingo-chuchu/src/components/chat-notification.tsx
+++ /dev/null
@@ -1,91 +0,0 @@
-import { useEffect } from 'react'
-import Image from 'next/image'
-
-import IconWarning from '@/assets/images/warning.svg'
-import { ChatError, ErrorCode, ChatMessageModel } from '@/lib/bots/bing/types'
-import { ExternalLink } from './external-link'
-import { useBing } from '@/lib/hooks/use-bing'
-
-export interface ChatNotificationProps extends Pick, 'bot'> {
- message?: ChatMessageModel
-}
-
-function getAction(error: ChatError, reset: () => void) {
- if (error.code === ErrorCode.THROTTLE_LIMIT) {
- reset()
- return (
-
- 你的服务器或代理已被封禁，请更换服务器或使用代理重试
-
- )
- }
- if (error.code === ErrorCode.BING_TRY_LATER) {
- return (
-
- 创建会话失败，请稍候重试
-
- )
- }
- if (error.code === ErrorCode.BING_FORBIDDEN) {
- return (
-
- 你的账号已在黑名单，请尝试更换账号及申请解封
-
- )
- }
- if (error.code === ErrorCode.CONVERSATION_LIMIT) {
- return (
-
- 点击通过人机验证
-
- )
- }
- if (error.code === ErrorCode.BING_UNAUTHORIZED) {
- reset()
- return (
- 没有获取到身份信息或身份信息失效，点此重新设置
- )
- }
- return error.message
-}
-
-export function ChatNotification({ message, bot }: ChatNotificationProps) {
- useEffect(() => {
- window.scrollBy(0, 2000)
- }, [message])
-
- if (!message?.error) return
-
- return (
- Optional[str]:
- "Returns glibc version string, or None if not using glibc."
- return glibc_version_string_confstr() or glibc_version_string_ctypes()
-
-
-def glibc_version_string_confstr() -> Optional[str]:
- "Primary implementation of glibc_version_string using os.confstr."
- # os.confstr is quite a bit faster than ctypes.DLL. It's also less likely
- # to be broken or missing. This strategy is used in the standard library
- # platform module:
- # https://github.com/python/cpython/blob/fcf1d003bf4f0100c9d0921ff3d70e1127ca1b71/Lib/platform.py#L175-L183
- if sys.platform == "win32":
- return None
- try:
- # os.confstr("CS_GNU_LIBC_VERSION") returns a string like "glibc 2.17":
- _, version = os.confstr("CS_GNU_LIBC_VERSION").split()
- except (AttributeError, OSError, ValueError):
- # os.confstr() or CS_GNU_LIBC_VERSION not available (or a bad value)...
- return None
- return version
-
-
-def glibc_version_string_ctypes() -> Optional[str]:
- "Fallback implementation of glibc_version_string using ctypes."
-
- try:
- import ctypes
- except ImportError:
- return None
-
- # ctypes.CDLL(None) internally calls dlopen(NULL), and as the dlopen
- # manpage says, "If filename is NULL, then the returned handle is for the
- # main program". This way we can let the linker do the work to figure out
- # which libc our process is actually using.
- process_namespace = ctypes.CDLL(None)
- try:
- gnu_get_libc_version = process_namespace.gnu_get_libc_version
- except AttributeError:
- # Symbol doesn't exist -> therefore, we are not linked to
- # glibc.
- return None
-
- # Call gnu_get_libc_version, which returns a string like "2.5"
- gnu_get_libc_version.restype = ctypes.c_char_p
- version_str = gnu_get_libc_version()
- # py2 / py3 compatibility:
- if not isinstance(version_str, str):
- version_str = version_str.decode("ascii")
-
- return version_str
-
-
-# platform.libc_ver regularly returns completely nonsensical glibc
-# versions. E.g. on my computer, platform says:
-#
-# ~$ python2.7 -c 'import platform; print(platform.libc_ver())'
-# ('glibc', '2.7')
-# ~$ python3.5 -c 'import platform; print(platform.libc_ver())'
-# ('glibc', '2.9')
-#
-# But the truth is:
-#
-# ~$ ldd --version
-# ldd (Debian GLIBC 2.22-11) 2.22
-#
-# This is unfortunate, because it means that the linehaul data on libc
-# versions that was generated by pip 8.1.2 and earlier is useless and
-# misleading. Solution: instead of using platform, use our code that actually
-# works.
-def libc_ver() -> Tuple[str, str]:
- """Try to determine the glibc version
-
- Returns a tuple of strings (lib, version) which default to empty strings
- in case the lookup fails.
- """
- glibc_version = glibc_version_string()
- if glibc_version is None:
- return ("", "")
- else:
- return ("glibc", glibc_version)
diff --git a/spaces/Realcat/image-matching-webui/hloc/pipelines/4Seasons/__init__.py b/spaces/Realcat/image-matching-webui/hloc/pipelines/4Seasons/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Realcat/image-matching-webui/third_party/DKM/dkm/train/__init__.py b/spaces/Realcat/image-matching-webui/third_party/DKM/dkm/train/__init__.py
deleted file mode 100644
index 90269dc0f345a575e0ba21f5afa34202c7e6b433..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/DKM/dkm/train/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .train import train_k_epochs
diff --git a/spaces/Realcat/image-matching-webui/third_party/SGMNet/train/valid.py b/spaces/Realcat/image-matching-webui/third_party/SGMNet/train/valid.py
deleted file mode 100644
index b9873f9b34ff77462d87aaad8c128e3b497fa39a..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/SGMNet/train/valid.py
+++ /dev/null
@@ -1,124 +0,0 @@
-import torch
-import numpy as np
-import cv2
-import os
-from loss import batch_episym
-from tqdm import tqdm
-
-import sys
-
-ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
-sys.path.insert(0, ROOT_DIR)
-
-from utils import evaluation_utils, train_utils
-
-
-def valid(valid_loader, model, match_loss, config, model_config):
- model.eval()
- loader_iter = iter(valid_loader)
- num_pair = 0
- total_loss, total_acc_corr, total_acc_incorr = 0, 0, 0
- total_precision, total_recall = torch.zeros(
- model_config.layer_num, device="cuda"
- ), torch.zeros(model_config.layer_num, device="cuda")
- total_acc_mid = torch.zeros(len(model_config.seedlayer) - 1, device="cuda")
-
- with torch.no_grad():
- if config.local_rank == 0:
- loader_iter = tqdm(loader_iter)
- print("validating...")
- for test_data in loader_iter:
- num_pair += 1
- test_data = train_utils.tocuda(test_data)
- res = model(test_data)
- loss_res = match_loss.run(test_data, res)
-
- total_acc_corr += loss_res["acc_corr"]
- total_acc_incorr += loss_res["acc_incorr"]
- total_loss += loss_res["total_loss"]
-
- if config.model_name == "SGM":
- total_acc_mid += loss_res["mid_acc_corr"]
- total_precision, total_recall = (
- total_precision + loss_res["pre_seed_conf"],
- total_recall + loss_res["recall_seed_conf"],
- )
-
- total_acc_corr /= num_pair
- total_acc_incorr /= num_pair
- total_precision /= num_pair
- total_recall /= num_pair
- total_acc_mid /= num_pair
-
- # apply tensor reduction
- (
- total_loss,
- total_acc_corr,
- total_acc_incorr,
- total_precision,
- total_recall,
- total_acc_mid,
- ) = (
- train_utils.reduce_tensor(total_loss, "sum"),
- train_utils.reduce_tensor(total_acc_corr, "mean"),
- train_utils.reduce_tensor(total_acc_incorr, "mean"),
- train_utils.reduce_tensor(total_precision, "mean"),
- train_utils.reduce_tensor(total_recall, "mean"),
- train_utils.reduce_tensor(total_acc_mid, "mean"),
- )
- model.train()
- return (
- total_loss,
- total_acc_corr,
- total_acc_incorr,
- total_precision,
- total_recall,
- total_acc_mid,
- )
-
-
-def dump_train_vis(res, data, step, config):
- # batch matching
- p = res["p"][:, :-1, :-1]
- score, index1 = torch.max(p, dim=-1)
- _, index2 = torch.max(p, dim=-2)
- mask_th = score > 0.2
- mask_mc = index2.gather(index=index1, dim=1) == torch.arange(len(p[0])).cuda()[None]
- mask_p = mask_th & mask_mc # B*N
-
- corr1, corr2 = data["x1"], data["x2"].gather(
- index=index1[:, :, None].expand(-1, -1, 2), dim=1
- )
- corr1_kpt, corr2_kpt = data["kpt1"], data["kpt2"].gather(
- index=index1[:, :, None].expand(-1, -1, 2), dim=1
- )
- epi_dis = batch_episym(corr1, corr2, data["e_gt"])
- mask_inlier = epi_dis < config.inlier_th # B*N
-
- # dump vis
- for cur_mask_p, cur_mask_inlier, cur_corr1, cur_corr2, img_path1, img_path2 in zip(
- mask_p, mask_inlier, corr1_kpt, corr2_kpt, data["img_path1"], data["img_path2"]
- ):
- img1, img2 = cv2.imread(img_path1), cv2.imread(img_path2)
- dis_play = evaluation_utils.draw_match(
- img1,
- img2,
- cur_corr1[cur_mask_p].cpu().numpy(),
- cur_corr2[cur_mask_p].cpu().numpy(),
- inlier=cur_mask_inlier,
- )
- base_name_seq = os.path.join(
- img_path1.split("/")[-1]
- + "_"
- + img_path2.split("/")[-1]
- + "_"
- + img_path1.split("/")[-2]
- )
- save_path = os.path.join(
- config.train_vis_folder,
- "train_vis",
- config.log_base,
- str(step),
- base_name_seq + ".png",
- )
- cv2.imwrite(save_path, dis_play)
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer_base/mmseg/core/seg/sampler/__init__.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer_base/mmseg/core/seg/sampler/__init__.py
deleted file mode 100644
index 332b242c03d1c5e80d4577df442a9a037b1816e1..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer_base/mmseg/core/seg/sampler/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from .base_pixel_sampler import BasePixelSampler
-from .ohem_pixel_sampler import OHEMPixelSampler
-
-__all__ = ['BasePixelSampler', 'OHEMPixelSampler']
diff --git a/spaces/SMD00/Image_Colorization/app.py b/spaces/SMD00/Image_Colorization/app.py
deleted file mode 100644
index 497d2a7879b04f2692d1bfa9a98596d638dc9f58..0000000000000000000000000000000000000000
--- a/spaces/SMD00/Image_Colorization/app.py
+++ /dev/null
@@ -1,387 +0,0 @@
-import gradio as gr
-from PIL import Image
-import cv2 as cv
-
-import os
-import glob
-import time
-import numpy as np
-from PIL import Image
-from pathlib import Path
-from tqdm.notebook import tqdm
-import matplotlib.pyplot as plt
-from skimage.color import rgb2lab, lab2rgb
-
-# pip install fastai==2.4
-
-import torch
-from torch import nn, optim
-from torchvision import transforms
-from torchvision.utils import make_grid
-from torch.utils.data import Dataset, DataLoader
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-use_colab = None
-
-SIZE = 256
-class ColorizationDataset(Dataset):
- def __init__(self, paths, split='train'):
- if split == 'train':
- self.transforms = transforms.Compose([
- transforms.Resize((SIZE, SIZE), Image.BICUBIC),
- transforms.RandomHorizontalFlip(), # A little data augmentation!
- ])
- elif split == 'val':
- self.transforms = transforms.Resize((SIZE, SIZE), Image.BICUBIC)
-
- self.split = split
- self.size = SIZE
- self.paths = paths
-
- def __getitem__(self, idx):
- img = Image.open(self.paths[idx]).convert("RGB")
- img = self.transforms(img)
- img = np.array(img)
- img_lab = rgb2lab(img).astype("float32") # Converting RGB to L*a*b
- img_lab = transforms.ToTensor()(img_lab)
- L = img_lab[[0], ...] / 50. - 1. # Between -1 and 1
- ab = img_lab[[1, 2], ...] / 110. # Between -1 and 1
-
- return {'L': L, 'ab': ab}
-
- def __len__(self):
- return len(self.paths)
-
-def make_dataloaders(batch_size=16, n_workers=4, pin_memory=True, **kwargs): # A handy function to make our dataloaders
- dataset = ColorizationDataset(**kwargs)
- dataloader = DataLoader(dataset, batch_size=batch_size, num_workers=n_workers,
- pin_memory=pin_memory)
- return dataloader
-
-class UnetBlock(nn.Module):
- def __init__(self, nf, ni, submodule=None, input_c=None, dropout=False,
- innermost=False, outermost=False):
- super().__init__()
- self.outermost = outermost
- if input_c is None: input_c = nf
- downconv = nn.Conv2d(input_c, ni, kernel_size=4,
- stride=2, padding=1, bias=False)
- downrelu = nn.LeakyReLU(0.2, True)
- downnorm = nn.BatchNorm2d(ni)
- uprelu = nn.ReLU(True)
- upnorm = nn.BatchNorm2d(nf)
-
- if outermost:
- upconv = nn.ConvTranspose2d(ni * 2, nf, kernel_size=4,
- stride=2, padding=1)
- down = [downconv]
- up = [uprelu, upconv, nn.Tanh()]
- model = down + [submodule] + up
- elif innermost:
- upconv = nn.ConvTranspose2d(ni, nf, kernel_size=4,
- stride=2, padding=1, bias=False)
- down = [downrelu, downconv]
- up = [uprelu, upconv, upnorm]
- model = down + up
- else:
- upconv = nn.ConvTranspose2d(ni * 2, nf, kernel_size=4,
- stride=2, padding=1, bias=False)
- down = [downrelu, downconv, downnorm]
- up = [uprelu, upconv, upnorm]
- if dropout: up += [nn.Dropout(0.5)]
- model = down + [submodule] + up
- self.model = nn.Sequential(*model)
-
- def forward(self, x):
- if self.outermost:
- return self.model(x)
- else:
- return torch.cat([x, self.model(x)], 1)
-
-class Unet(nn.Module):
- def __init__(self, input_c=1, output_c=2, n_down=8, num_filters=64):
- super().__init__()
- unet_block = UnetBlock(num_filters * 8, num_filters * 8, innermost=True)
- for _ in range(n_down - 5):
- unet_block = UnetBlock(num_filters * 8, num_filters * 8, submodule=unet_block, dropout=True)
- out_filters = num_filters * 8
- for _ in range(3):
- unet_block = UnetBlock(out_filters // 2, out_filters, submodule=unet_block)
- out_filters //= 2
- self.model = UnetBlock(output_c, out_filters, input_c=input_c, submodule=unet_block, outermost=True)
-
- def forward(self, x):
- return self.model(x)
-
-class PatchDiscriminator(nn.Module):
- def __init__(self, input_c, num_filters=64, n_down=3):
- super().__init__()
- model = [self.get_layers(input_c, num_filters, norm=False)]
- model += [self.get_layers(num_filters * 2 ** i, num_filters * 2 ** (i + 1), s=1 if i == (n_down-1) else 2)
- for i in range(n_down)] # the 'if' statement is taking care of not using
- # stride of 2 for the last block in this loop
- model += [self.get_layers(num_filters * 2 ** n_down, 1, s=1, norm=False, act=False)] # Make sure to not use normalization or
- # activation for the last layer of the model
- self.model = nn.Sequential(*model)
-
- def get_layers(self, ni, nf, k=4, s=2, p=1, norm=True, act=True): # when needing to make some repeatitive blocks of layers,
- layers = [nn.Conv2d(ni, nf, k, s, p, bias=not norm)] # it's always helpful to make a separate method for that purpose
- if norm: layers += [nn.BatchNorm2d(nf)]
- if act: layers += [nn.LeakyReLU(0.2, True)]
- return nn.Sequential(*layers)
-
- def forward(self, x):
- return self.model(x)
-
-class GANLoss(nn.Module):
- def __init__(self, gan_mode='vanilla', real_label=1.0, fake_label=0.0):
- super().__init__()
- self.register_buffer('real_label', torch.tensor(real_label))
- self.register_buffer('fake_label', torch.tensor(fake_label))
- if gan_mode == 'vanilla':
- self.loss = nn.BCEWithLogitsLoss()
- elif gan_mode == 'lsgan':
- self.loss = nn.MSELoss()
-
- def get_labels(self, preds, target_is_real):
- if target_is_real:
- labels = self.real_label
- else:
- labels = self.fake_label
- return labels.expand_as(preds)
-
- def __call__(self, preds, target_is_real):
- labels = self.get_labels(preds, target_is_real)
- loss = self.loss(preds, labels)
- return loss
-
-def init_weights(net, init='norm', gain=0.02):
-
- def init_func(m):
- classname = m.__class__.__name__
- if hasattr(m, 'weight') and 'Conv' in classname:
- if init == 'norm':
- nn.init.normal_(m.weight.data, mean=0.0, std=gain)
- elif init == 'xavier':
- nn.init.xavier_normal_(m.weight.data, gain=gain)
- elif init == 'kaiming':
- nn.init.kaiming_normal_(m.weight.data, a=0, mode='fan_in')
-
- if hasattr(m, 'bias') and m.bias is not None:
- nn.init.constant_(m.bias.data, 0.0)
- elif 'BatchNorm2d' in classname:
- nn.init.normal_(m.weight.data, 1., gain)
- nn.init.constant_(m.bias.data, 0.)
-
- net.apply(init_func)
- # print(f"model initialized with {init} initialization")
- return net
-
-def init_model(model, device):
- model = model.to(device)
- model = init_weights(model)
- return model
-
-class MainModel(nn.Module):
- def __init__(self, net_G=None, lr_G=2e-4, lr_D=2e-4,
- beta1=0.5, beta2=0.999, lambda_L1=100.):
- super().__init__()
-
- self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
- self.lambda_L1 = lambda_L1
-
- if net_G is None:
- self.net_G = init_model(Unet(input_c=1, output_c=2, n_down=8, num_filters=64), self.device)
- else:
- self.net_G = net_G.to(self.device)
- self.net_D = init_model(PatchDiscriminator(input_c=3, n_down=3, num_filters=64), self.device)
- self.GANcriterion = GANLoss(gan_mode='vanilla').to(self.device)
- self.L1criterion = nn.L1Loss()
- self.opt_G = optim.Adam(self.net_G.parameters(), lr=lr_G, betas=(beta1, beta2))
- self.opt_D = optim.Adam(self.net_D.parameters(), lr=lr_D, betas=(beta1, beta2))
-
- def set_requires_grad(self, model, requires_grad=True):
- for p in model.parameters():
- p.requires_grad = requires_grad
-
- def setup_input(self, data):
- self.L = data['L'].to(self.device)
- self.ab = data['ab'].to(self.device)
-
- def forward(self):
- self.fake_color = self.net_G(self.L)
-
- def backward_D(self):
- fake_image = torch.cat([self.L, self.fake_color], dim=1)
- fake_preds = self.net_D(fake_image.detach())
- self.loss_D_fake = self.GANcriterion(fake_preds, False)
- real_image = torch.cat([self.L, self.ab], dim=1)
- real_preds = self.net_D(real_image)
- self.loss_D_real = self.GANcriterion(real_preds, True)
- self.loss_D = (self.loss_D_fake + self.loss_D_real) * 0.5
- self.loss_D.backward()
-
- def backward_G(self):
- fake_image = torch.cat([self.L, self.fake_color], dim=1)
- fake_preds = self.net_D(fake_image)
- self.loss_G_GAN = self.GANcriterion(fake_preds, True)
- self.loss_G_L1 = self.L1criterion(self.fake_color, self.ab) * self.lambda_L1
- self.loss_G = self.loss_G_GAN + self.loss_G_L1
- self.loss_G.backward()
-
- def optimize(self):
- self.forward()
- self.net_D.train()
- self.set_requires_grad(self.net_D, True)
- self.opt_D.zero_grad()
- self.backward_D()
- self.opt_D.step()
-
- self.net_G.train()
- self.set_requires_grad(self.net_D, False)
- self.opt_G.zero_grad()
- self.backward_G()
- self.opt_G.step()
-
-class AverageMeter:
- def __init__(self):
- self.reset()
-
- def reset(self):
- self.count, self.avg, self.sum = [0.] * 3
-
- def update(self, val, count=1):
- self.count += count
- self.sum += count * val
- self.avg = self.sum / self.count
-
-def create_loss_meters():
- loss_D_fake = AverageMeter()
- loss_D_real = AverageMeter()
- loss_D = AverageMeter()
- loss_G_GAN = AverageMeter()
- loss_G_L1 = AverageMeter()
- loss_G = AverageMeter()
-
- return {'loss_D_fake': loss_D_fake,
- 'loss_D_real': loss_D_real,
- 'loss_D': loss_D,
- 'loss_G_GAN': loss_G_GAN,
- 'loss_G_L1': loss_G_L1,
- 'loss_G': loss_G}
-
-def update_losses(model, loss_meter_dict, count):
- for loss_name, loss_meter in loss_meter_dict.items():
- loss = getattr(model, loss_name)
- loss_meter.update(loss.item(), count=count)
-
-def lab_to_rgb(L, ab):
- """
- Takes a batch of images
- """
-
- L = (L + 1.) * 50.
- ab = ab * 110.
- Lab = torch.cat([L, ab], dim=1).permute(0, 2, 3, 1).cpu().numpy()
- rgb_imgs = []
- for img in Lab:
- img_rgb = lab2rgb(img)
- rgb_imgs.append(img_rgb)
- return np.stack(rgb_imgs, axis=0)
-
-def visualize(model, data, dims):
- model.net_G.eval()
- with torch.no_grad():
- model.setup_input(data)
- model.forward()
- model.net_G.train()
- fake_color = model.fake_color.detach()
- real_color = model.ab
- L = model.L
- fake_imgs = lab_to_rgb(L, fake_color)
- real_imgs = lab_to_rgb(L, real_color)
- # img=cv.resize(fake_imgs[0], dsize=(dims[1], dims[0]), interpolation=cv.INTER_CUBIC)
- img=fake_imgs[0]
- # return np.resize(img,(dims[1], dims[0]))
- return fake_imgs[0]
- for i in range(1):
- # t_img = transforms.Resize((dims[0], dims[1]))(t_img)
- img = Image.fromarray(np.uint8(fake_imgs[i]))
- img = np.uint8(cv.resize(fake_imgs[i], dsize=(dims[1], dims[0]), interpolation=cv.INTER_CUBIC))
- return img
- # st.text(f"Size of fake image {fake_imgs[i].shape} \n Type of image = {type(fake_imgs[i])}")
- # st.image(img, caption="Output image", use_column_width='auto', clamp=True)
-
-
-# def log_results(loss_meter_dict):
- # for loss_name, loss_meter in loss_meter_dict.items():
- # print(f"{loss_name}: {loss_meter.avg:.5f}")
-
-# pip install fastai==2.4
-from fastai.vision.learner import create_body
-from torchvision.models.resnet import resnet18
-from fastai.vision.models.unet import DynamicUnet
-
-def build_res_unet(n_input=1, n_output=2, size=256):
- device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
- body = create_body(resnet18(), pretrained=True, n_in=n_input, cut=-2)
- net_G = DynamicUnet(body, n_output, (size, size)).to(device)
- return net_G
-
-net_G = build_res_unet(n_input=1, n_output=2, size=256)
-net_G.load_state_dict(torch.load("res18-unet.pt", map_location=device))
-model = MainModel(net_G=net_G)
-model.load_state_dict(torch.load("final_model_weights.pt", map_location=device))
-
-class MyDataset(torch.utils.data.Dataset):
- def __init__(self, img_list):
- super(MyDataset, self).__init__()
- self.img_list = img_list
- self.augmentations = transforms.Resize((SIZE, SIZE), Image.BICUBIC)
-
-
- def __len__(self):
- return len(self.img_list)
-
- def __getitem__(self, idx):
- img = self.img_list[idx]
- img = self.augmentations(img)
- img = np.array(img)
- img_lab = rgb2lab(img).astype("float32") # Converting RGB to L*a*b
- img_lab = transforms.ToTensor()(img_lab)
- L = img_lab[[0], ...] / 50. - 1. # Between -1 and 1
- ab = img_lab[[1, 2], ...] / 110.
- return {'L': L, 'ab': ab}
-
-def make_dataloaders2(batch_size=16, n_workers=4, pin_memory=True, **kwargs): # A handy function to make our dataloaders
- dataset = MyDataset(**kwargs)
- dataloader = DataLoader(dataset, batch_size=batch_size, num_workers=n_workers,
- pin_memory=pin_memory)
- return dataloader
-
-def main_func(filepath):
- im = Image.open(filepath)
- size_text=f"Size of uploaded image {im.shape}"
- # st.text(body=f"Size of uploaded image {im.shape}")
- a = im.shape
- # st.image(im, caption="Uploaded Image.", use_column_width='auto')
- test_dl = make_dataloaders2(img_list=[im])
- for data in test_dl:
- model.setup_input(data)
- model.optimize()
- img=visualize(model, data, a)
- img2=np.resize(img,a)
- img3=Image.fromarray(cv.resize(np.uint8(img), a, interpolation=cv.INTER_CUBIC))
- img4=Image.fromarray(cv.resize(np.uint8(img), a, interpolation=cv.INTER_LINEAR))
- return (size_text,img,img2,img3,img4)
-
-title = "Image Colorization"
-description = "Gradio demo for Image Colorization project. You can give an image as input on the left side and then click on the submit button. The program would recolorize the image"
-gr.Interface(
- main_func,
- [gr.Image(type="filepath", label="Input Image") ],
- [gr.Textbox(label="Image Size"),gr.Image(type="pil", label="Output Image"),"image",gr.Image( label="Output Image2"),"image"],
- title=title,
- description=description,
- # examples=[ ['face.jpg'], ['montains.jpg'],['tree.jpg'] ]
-
-)
\ No newline at end of file
diff --git a/spaces/SankarSrin/image-matting-app/ppmatting/utils/estimate_foreground_ml.py b/spaces/SankarSrin/image-matting-app/ppmatting/utils/estimate_foreground_ml.py
deleted file mode 100644
index 05bffb6c31a5042fd96c028013c81f7533f3675d..0000000000000000000000000000000000000000
--- a/spaces/SankarSrin/image-matting-app/ppmatting/utils/estimate_foreground_ml.py
+++ /dev/null
@@ -1,236 +0,0 @@
-import numpy as np
-from numba import njit, prange
-
-# The foreground estimation refer to pymatting [https://github.com/pymatting/pymatting/blob/master/pymatting/foreground/estimate_foreground_ml.py]
-
-
-@njit("void(f4[:, :, :], f4[:, :, :])", cache=True, nogil=True, parallel=True)
-def _resize_nearest_multichannel(dst, src):
- """
- Internal method.
-
- Resize image src to dst using nearest neighbors filtering.
- Images must have multiple color channels, i.e. :code:`len(shape) == 3`.
-
- Parameters
- ----------
- dst: numpy.ndarray of type np.float32
- output image
- src: numpy.ndarray of type np.float32
- input image
- """
- h_src, w_src, depth = src.shape
- h_dst, w_dst, depth = dst.shape
-
- for y_dst in prange(h_dst):
- for x_dst in range(w_dst):
- x_src = max(0, min(w_src - 1, x_dst * w_src // w_dst))
- y_src = max(0, min(h_src - 1, y_dst * h_src // h_dst))
-
- for c in range(depth):
- dst[y_dst, x_dst, c] = src[y_src, x_src, c]
-
-
-@njit("void(f4[:, :], f4[:, :])", cache=True, nogil=True, parallel=True)
-def _resize_nearest(dst, src):
- """
- Internal method.
-
- Resize image src to dst using nearest neighbors filtering.
- Images must be grayscale, i.e. :code:`len(shape) == 3`.
-
- Parameters
- ----------
- dst: numpy.ndarray of type np.float32
- output image
- src: numpy.ndarray of type np.float32
- input image
- """
- h_src, w_src = src.shape
- h_dst, w_dst = dst.shape
-
- for y_dst in prange(h_dst):
- for x_dst in range(w_dst):
- x_src = max(0, min(w_src - 1, x_dst * w_src // w_dst))
- y_src = max(0, min(h_src - 1, y_dst * h_src // h_dst))
-
- dst[y_dst, x_dst] = src[y_src, x_src]
-
-
-# TODO
-# There should be an option to switch @njit(parallel=True) on or off.
-# parallel=True would be faster, but might cause race conditions.
-# User should have the option to turn it on or off.
-@njit(
- "Tuple((f4[:, :, :], f4[:, :, :]))(f4[:, :, :], f4[:, :], f4, i4, i4, i4, f4)",
- cache=True,
- nogil=True)
-def _estimate_fb_ml(
- input_image,
- input_alpha,
- regularization,
- n_small_iterations,
- n_big_iterations,
- small_size,
- gradient_weight, ):
- h0, w0, depth = input_image.shape
-
- dtype = np.float32
-
- w_prev = 1
- h_prev = 1
-
- F_prev = np.empty((h_prev, w_prev, depth), dtype=dtype)
- B_prev = np.empty((h_prev, w_prev, depth), dtype=dtype)
-
- n_levels = int(np.ceil(np.log2(max(w0, h0))))
-
- for i_level in range(n_levels + 1):
- w = round(w0**(i_level / n_levels))
- h = round(h0**(i_level / n_levels))
-
- image = np.empty((h, w, depth), dtype=dtype)
- alpha = np.empty((h, w), dtype=dtype)
-
- _resize_nearest_multichannel(image, input_image)
- _resize_nearest(alpha, input_alpha)
-
- F = np.empty((h, w, depth), dtype=dtype)
- B = np.empty((h, w, depth), dtype=dtype)
-
- _resize_nearest_multichannel(F, F_prev)
- _resize_nearest_multichannel(B, B_prev)
-
- if w <= small_size and h <= small_size:
- n_iter = n_small_iterations
- else:
- n_iter = n_big_iterations
-
- b = np.zeros((2, depth), dtype=dtype)
-
- dx = [-1, 1, 0, 0]
- dy = [0, 0, -1, 1]
-
- for i_iter in range(n_iter):
- for y in prange(h):
- for x in range(w):
- a0 = alpha[y, x]
- a1 = 1.0 - a0
-
- a00 = a0 * a0
- a01 = a0 * a1
- # a10 = a01 can be omitted due to symmetry of matrix
- a11 = a1 * a1
-
- for c in range(depth):
- b[0, c] = a0 * image[y, x, c]
- b[1, c] = a1 * image[y, x, c]
-
- for d in range(4):
- x2 = max(0, min(w - 1, x + dx[d]))
- y2 = max(0, min(h - 1, y + dy[d]))
-
- gradient = abs(a0 - alpha[y2, x2])
-
- da = regularization + gradient_weight * gradient
-
- a00 += da
- a11 += da
-
- for c in range(depth):
- b[0, c] += da * F[y2, x2, c]
- b[1, c] += da * B[y2, x2, c]
-
- determinant = a00 * a11 - a01 * a01
-
- inv_det = 1.0 / determinant
-
- b00 = inv_det * a11
- b01 = inv_det * -a01
- b11 = inv_det * a00
-
- for c in range(depth):
- F_c = b00 * b[0, c] + b01 * b[1, c]
- B_c = b01 * b[0, c] + b11 * b[1, c]
-
- F_c = max(0.0, min(1.0, F_c))
- B_c = max(0.0, min(1.0, B_c))
-
- F[y, x, c] = F_c
- B[y, x, c] = B_c
-
- F_prev = F
- B_prev = B
-
- w_prev = w
- h_prev = h
-
- return F, B
-
-
-def estimate_foreground_ml(
- image,
- alpha,
- regularization=1e-5,
- n_small_iterations=10,
- n_big_iterations=2,
- small_size=32,
- return_background=False,
- gradient_weight=1.0, ):
- """Estimates the foreground of an image given its alpha matte.
-
- See :cite:`germer2020multilevel` for reference.
-
- Parameters
- ----------
- image: numpy.ndarray
- Input image with shape :math:`h \\times w \\times d`
- alpha: numpy.ndarray
- Input alpha matte shape :math:`h \\times w`
- regularization: float
- Regularization strength :math:`\\epsilon`, defaults to :math:`10^{-5}`.
- Higher regularization results in smoother colors.
- n_small_iterations: int
- Number of iterations performed on small scale, defaults to :math:`10`
- n_big_iterations: int
- Number of iterations performed on large scale, defaults to :math:`2`
- small_size: int
- Threshold that determines at which size `n_small_iterations` should be used
- return_background: bool
- Whether to return the estimated background in addition to the foreground
- gradient_weight: float
- Larger values enforce smoother foregrounds, defaults to :math:`1`
-
- Returns
- -------
- F: numpy.ndarray
- Extracted foreground
- B: numpy.ndarray
- Extracted background
-
- Example
- -------
- >>> from pymatting import *
- >>> image = load_image("data/lemur/lemur.png", "RGB")
- >>> alpha = load_image("data/lemur/lemur_alpha.png", "GRAY")
- >>> F = estimate_foreground_ml(image, alpha, return_background=False)
- >>> F, B = estimate_foreground_ml(image, alpha, return_background=True)
-
- See Also
- ----
- stack_images: This function can be used to place the foreground on a new background.
- """
-
- foreground, background = _estimate_fb_ml(
- image.astype(np.float32),
- alpha.astype(np.float32),
- regularization,
- n_small_iterations,
- n_big_iterations,
- small_size,
- gradient_weight, )
-
- if return_background:
- return foreground, background
-
- return foreground
diff --git a/spaces/SkyYeXianer/vits-uma-genshin-honkai/transforms.py b/spaces/SkyYeXianer/vits-uma-genshin-honkai/transforms.py
deleted file mode 100644
index 4793d67ca5a5630e0ffe0f9fb29445c949e64dae..0000000000000000000000000000000000000000
--- a/spaces/SkyYeXianer/vits-uma-genshin-honkai/transforms.py
+++ /dev/null
@@ -1,193 +0,0 @@
-import torch
-from torch.nn import functional as F
-
-import numpy as np
-
-
-DEFAULT_MIN_BIN_WIDTH = 1e-3
-DEFAULT_MIN_BIN_HEIGHT = 1e-3
-DEFAULT_MIN_DERIVATIVE = 1e-3
-
-
-def piecewise_rational_quadratic_transform(inputs,
- unnormalized_widths,
- unnormalized_heights,
- unnormalized_derivatives,
- inverse=False,
- tails=None,
- tail_bound=1.,
- min_bin_width=DEFAULT_MIN_BIN_WIDTH,
- min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
- min_derivative=DEFAULT_MIN_DERIVATIVE):
-
- if tails is None:
- spline_fn = rational_quadratic_spline
- spline_kwargs = {}
- else:
- spline_fn = unconstrained_rational_quadratic_spline
- spline_kwargs = {
- 'tails': tails,
- 'tail_bound': tail_bound
- }
-
- outputs, logabsdet = spline_fn(
- inputs=inputs,
- unnormalized_widths=unnormalized_widths,
- unnormalized_heights=unnormalized_heights,
- unnormalized_derivatives=unnormalized_derivatives,
- inverse=inverse,
- min_bin_width=min_bin_width,
- min_bin_height=min_bin_height,
- min_derivative=min_derivative,
- **spline_kwargs
- )
- return outputs, logabsdet
-
-
-def searchsorted(bin_locations, inputs, eps=1e-6):
- bin_locations[..., -1] += eps
- return torch.sum(
- inputs[..., None] >= bin_locations,
- dim=-1
- ) - 1
-
-
-def unconstrained_rational_quadratic_spline(inputs,
- unnormalized_widths,
- unnormalized_heights,
- unnormalized_derivatives,
- inverse=False,
- tails='linear',
- tail_bound=1.,
- min_bin_width=DEFAULT_MIN_BIN_WIDTH,
- min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
- min_derivative=DEFAULT_MIN_DERIVATIVE):
- inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
- outside_interval_mask = ~inside_interval_mask
-
- outputs = torch.zeros_like(inputs)
- logabsdet = torch.zeros_like(inputs)
-
- if tails == 'linear':
- unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
- constant = np.log(np.exp(1 - min_derivative) - 1)
- unnormalized_derivatives[..., 0] = constant
- unnormalized_derivatives[..., -1] = constant
-
- outputs[outside_interval_mask] = inputs[outside_interval_mask]
- logabsdet[outside_interval_mask] = 0
- else:
- raise RuntimeError('{} tails are not implemented.'.format(tails))
-
- outputs[inside_interval_mask], logabsdet[inside_interval_mask] = rational_quadratic_spline(
- inputs=inputs[inside_interval_mask],
- unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
- unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
- unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
- inverse=inverse,
- left=-tail_bound, right=tail_bound, bottom=-tail_bound, top=tail_bound,
- min_bin_width=min_bin_width,
- min_bin_height=min_bin_height,
- min_derivative=min_derivative
- )
-
- return outputs, logabsdet
-
-def rational_quadratic_spline(inputs,
- unnormalized_widths,
- unnormalized_heights,
- unnormalized_derivatives,
- inverse=False,
- left=0., right=1., bottom=0., top=1.,
- min_bin_width=DEFAULT_MIN_BIN_WIDTH,
- min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
- min_derivative=DEFAULT_MIN_DERIVATIVE):
- if torch.min(inputs) < left or torch.max(inputs) > right:
- raise ValueError('Input to a transform is not within its domain')
-
- num_bins = unnormalized_widths.shape[-1]
-
- if min_bin_width * num_bins > 1.0:
- raise ValueError('Minimal bin width too large for the number of bins')
- if min_bin_height * num_bins > 1.0:
- raise ValueError('Minimal bin height too large for the number of bins')
-
- widths = F.softmax(unnormalized_widths, dim=-1)
- widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
- cumwidths = torch.cumsum(widths, dim=-1)
- cumwidths = F.pad(cumwidths, pad=(1, 0), mode='constant', value=0.0)
- cumwidths = (right - left) * cumwidths + left
- cumwidths[..., 0] = left
- cumwidths[..., -1] = right
- widths = cumwidths[..., 1:] - cumwidths[..., :-1]
-
- derivatives = min_derivative + F.softplus(unnormalized_derivatives)
-
- heights = F.softmax(unnormalized_heights, dim=-1)
- heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
- cumheights = torch.cumsum(heights, dim=-1)
- cumheights = F.pad(cumheights, pad=(1, 0), mode='constant', value=0.0)
- cumheights = (top - bottom) * cumheights + bottom
- cumheights[..., 0] = bottom
- cumheights[..., -1] = top
- heights = cumheights[..., 1:] - cumheights[..., :-1]
-
- if inverse:
- bin_idx = searchsorted(cumheights, inputs)[..., None]
- else:
- bin_idx = searchsorted(cumwidths, inputs)[..., None]
-
- input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
- input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
-
- input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
- delta = heights / widths
- input_delta = delta.gather(-1, bin_idx)[..., 0]
-
- input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
- input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
-
- input_heights = heights.gather(-1, bin_idx)[..., 0]
-
- if inverse:
- a = (((inputs - input_cumheights) * (input_derivatives
- + input_derivatives_plus_one
- - 2 * input_delta)
- + input_heights * (input_delta - input_derivatives)))
- b = (input_heights * input_derivatives
- - (inputs - input_cumheights) * (input_derivatives
- + input_derivatives_plus_one
- - 2 * input_delta))
- c = - input_delta * (inputs - input_cumheights)
-
- discriminant = b.pow(2) - 4 * a * c
- assert (discriminant >= 0).all()
-
- root = (2 * c) / (-b - torch.sqrt(discriminant))
- outputs = root * input_bin_widths + input_cumwidths
-
- theta_one_minus_theta = root * (1 - root)
- denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
- * theta_one_minus_theta)
- derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * root.pow(2)
- + 2 * input_delta * theta_one_minus_theta
- + input_derivatives * (1 - root).pow(2))
- logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
-
- return outputs, -logabsdet
- else:
- theta = (inputs - input_cumwidths) / input_bin_widths
- theta_one_minus_theta = theta * (1 - theta)
-
- numerator = input_heights * (input_delta * theta.pow(2)
- + input_derivatives * theta_one_minus_theta)
- denominator = input_delta + ((input_derivatives + input_derivatives_plus_one - 2 * input_delta)
- * theta_one_minus_theta)
- outputs = input_cumheights + numerator / denominator
-
- derivative_numerator = input_delta.pow(2) * (input_derivatives_plus_one * theta.pow(2)
- + 2 * input_delta * theta_one_minus_theta
- + input_derivatives * (1 - theta).pow(2))
- logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
-
- return outputs, logabsdet
diff --git a/spaces/Soumahara/Ojimi-anime-kawai-diffusion-demo/README.md b/spaces/Soumahara/Ojimi-anime-kawai-diffusion-demo/README.md
deleted file mode 100644
index a0a0c4210f3765fd0e2bdba0aa79135523eb9470..0000000000000000000000000000000000000000
--- a/spaces/Soumahara/Ojimi-anime-kawai-diffusion-demo/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Ojimi Anime Kawai Diffusion Demo
-emoji: 🌖
-colorFrom: indigo
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.24.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Souranil/VAE/config/config.py b/spaces/Souranil/VAE/config/config.py
deleted file mode 100644
index ab838cc27bcef25269ae303494901481024b2452..0000000000000000000000000000000000000000
--- a/spaces/Souranil/VAE/config/config.py
+++ /dev/null
@@ -1,59 +0,0 @@
-from pydantic import BaseModel
-from typing import Optional, Union
-import yaml
-
-
-class TrainConfig(BaseModel):
- max_epochs: int
- auto_lr_find: Union[bool, int]
- gpus: int
-
-
-class VAEConfig(BaseModel):
- model_type: str
- hidden_size: int
- latent_size: int
- alpha: int
- dataset: str
- batch_size: Optional[int] = 64
- save_images: Optional[bool] = False
- lr: Optional[float] = None
- save_path: Optional[str] = None
-
-
-class ConvVAEConfig(VAEConfig):
- channels: int
- height: int
- width: int
-
-
-class LoggerConfig(BaseModel):
- name: str
- save_dir: str
-
-
-class Config(BaseModel):
- model_config: Union[VAEConfig, ConvVAEConfig]
- train_config: TrainConfig
- model_type: str
- log_config: LoggerConfig
-
-
-def load_config(path="config.yaml"):
- config = yaml.load(open(path), yaml.SafeLoader)
- model_type = config['model_params']['model_type']
- if model_type == "vae":
- model_config = VAEConfig(**config["model_params"])
- elif model_type == "conv-vae":
- model_config = ConvVAEConfig(**config["model_params"])
- else:
- raise NotImplementedError(f"Model {model_type} is not implemented")
- train_config = TrainConfig(**config["training_params"])
- log_config = LoggerConfig(**config["logger_params"])
- config = Config(model_config=model_config, train_config=train_config,
- model_type=model_type, log_config=log_config)
-
- return config
-
-
-config = load_config()
diff --git a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/data/__init__.py b/spaces/SuYuanS/AudioCraft_Plus/audiocraft/data/__init__.py
deleted file mode 100644
index 2906ff12bc85a894837579f3137f6f71a0438329..0000000000000000000000000000000000000000
--- a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/data/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-"""Audio loading and writing support. Datasets for raw audio
-or also including some metadata."""
-
-# flake8: noqa
-from . import audio, audio_dataset, info_audio_dataset, music_dataset, sound_dataset
diff --git a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/grids/diffusion/4_bands_base_32khz.py b/spaces/SuYuanS/AudioCraft_Plus/audiocraft/grids/diffusion/4_bands_base_32khz.py
deleted file mode 100644
index f7e67bcc89dd0c8e50d770e600b55f179fe19588..0000000000000000000000000000000000000000
--- a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/grids/diffusion/4_bands_base_32khz.py
+++ /dev/null
@@ -1,27 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-"""
-Training of the 4 diffusion models described in
-"From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion"
-(paper link).
-"""
-
-from ._explorers import DiffusionExplorer
-
-
-@DiffusionExplorer
-def explorer(launcher):
- launcher.slurm_(gpus=4, partition='learnfair')
-
- launcher.bind_({'solver': 'diffusion/default',
- 'dset': 'internal/music_10k_32khz'})
-
- with launcher.job_array():
- launcher({'filter.use': True, 'filter.idx_band': 0, "processor.use": False, 'processor.power_std': 0.4})
- launcher({'filter.use': True, 'filter.idx_band': 1, "processor.use": False, 'processor.power_std': 0.4})
- launcher({'filter.use': True, 'filter.idx_band': 2, "processor.use": True, 'processor.power_std': 0.4})
- launcher({'filter.use': True, 'filter.idx_band': 3, "processor.use": True, 'processor.power_std': 0.75})
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/utils/text.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/utils/text.py
deleted file mode 100644
index 74bccddf68bf84a2325c79bb4a053f0d6e92038d..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/utils/text.py
+++ /dev/null
@@ -1,752 +0,0 @@
-# encoding: utf-8
-"""
-Utilities for working with strings and text.
-
-Inheritance diagram:
-
-.. inheritance-diagram:: IPython.utils.text
- :parts: 3
-"""
-
-import os
-import re
-import string
-import sys
-import textwrap
-from string import Formatter
-from pathlib import Path
-
-
-# datetime.strftime date format for ipython
-if sys.platform == 'win32':
- date_format = "%B %d, %Y"
-else:
- date_format = "%B %-d, %Y"
-
-class LSString(str):
- """String derivative with a special access attributes.
-
- These are normal strings, but with the special attributes:
-
- .l (or .list) : value as list (split on newlines).
- .n (or .nlstr): original value (the string itself).
- .s (or .spstr): value as whitespace-separated string.
- .p (or .paths): list of path objects (requires path.py package)
-
- Any values which require transformations are computed only once and
- cached.
-
- Such strings are very useful to efficiently interact with the shell, which
- typically only understands whitespace-separated options for commands."""
-
- def get_list(self):
- try:
- return self.__list
- except AttributeError:
- self.__list = self.split('\n')
- return self.__list
-
- l = list = property(get_list)
-
- def get_spstr(self):
- try:
- return self.__spstr
- except AttributeError:
- self.__spstr = self.replace('\n',' ')
- return self.__spstr
-
- s = spstr = property(get_spstr)
-
- def get_nlstr(self):
- return self
-
- n = nlstr = property(get_nlstr)
-
- def get_paths(self):
- try:
- return self.__paths
- except AttributeError:
- self.__paths = [Path(p) for p in self.split('\n') if os.path.exists(p)]
- return self.__paths
-
- p = paths = property(get_paths)
-
-# FIXME: We need to reimplement type specific displayhook and then add this
-# back as a custom printer. This should also be moved outside utils into the
-# core.
-
-# def print_lsstring(arg):
-# """ Prettier (non-repr-like) and more informative printer for LSString """
-# print "LSString (.p, .n, .l, .s available). Value:"
-# print arg
-#
-#
-# print_lsstring = result_display.register(LSString)(print_lsstring)
-
-
-class SList(list):
- """List derivative with a special access attributes.
-
- These are normal lists, but with the special attributes:
-
- * .l (or .list) : value as list (the list itself).
- * .n (or .nlstr): value as a string, joined on newlines.
- * .s (or .spstr): value as a string, joined on spaces.
- * .p (or .paths): list of path objects (requires path.py package)
-
- Any values which require transformations are computed only once and
- cached."""
-
- def get_list(self):
- return self
-
- l = list = property(get_list)
-
- def get_spstr(self):
- try:
- return self.__spstr
- except AttributeError:
- self.__spstr = ' '.join(self)
- return self.__spstr
-
- s = spstr = property(get_spstr)
-
- def get_nlstr(self):
- try:
- return self.__nlstr
- except AttributeError:
- self.__nlstr = '\n'.join(self)
- return self.__nlstr
-
- n = nlstr = property(get_nlstr)
-
- def get_paths(self):
- try:
- return self.__paths
- except AttributeError:
- self.__paths = [Path(p) for p in self if os.path.exists(p)]
- return self.__paths
-
- p = paths = property(get_paths)
-
- def grep(self, pattern, prune = False, field = None):
- """ Return all strings matching 'pattern' (a regex or callable)
-
- This is case-insensitive. If prune is true, return all items
- NOT matching the pattern.
-
- If field is specified, the match must occur in the specified
- whitespace-separated field.
-
- Examples::
-
- a.grep( lambda x: x.startswith('C') )
- a.grep('Cha.*log', prune=1)
- a.grep('chm', field=-1)
- """
-
- def match_target(s):
- if field is None:
- return s
- parts = s.split()
- try:
- tgt = parts[field]
- return tgt
- except IndexError:
- return ""
-
- if isinstance(pattern, str):
- pred = lambda x : re.search(pattern, x, re.IGNORECASE)
- else:
- pred = pattern
- if not prune:
- return SList([el for el in self if pred(match_target(el))])
- else:
- return SList([el for el in self if not pred(match_target(el))])
-
- def fields(self, *fields):
- """ Collect whitespace-separated fields from string list
-
- Allows quick awk-like usage of string lists.
-
- Example data (in var a, created by 'a = !ls -l')::
-
- -rwxrwxrwx 1 ville None 18 Dec 14 2006 ChangeLog
- drwxrwxrwx+ 6 ville None 0 Oct 24 18:05 IPython
-
- * ``a.fields(0)`` is ``['-rwxrwxrwx', 'drwxrwxrwx+']``
- * ``a.fields(1,0)`` is ``['1 -rwxrwxrwx', '6 drwxrwxrwx+']``
- (note the joining by space).
- * ``a.fields(-1)`` is ``['ChangeLog', 'IPython']``
-
- IndexErrors are ignored.
-
- Without args, fields() just split()'s the strings.
- """
- if len(fields) == 0:
- return [el.split() for el in self]
-
- res = SList()
- for el in [f.split() for f in self]:
- lineparts = []
-
- for fd in fields:
- try:
- lineparts.append(el[fd])
- except IndexError:
- pass
- if lineparts:
- res.append(" ".join(lineparts))
-
- return res
-
- def sort(self,field= None, nums = False):
- """ sort by specified fields (see fields())
-
- Example::
-
- a.sort(1, nums = True)
-
- Sorts a by second field, in numerical order (so that 21 > 3)
-
- """
-
- #decorate, sort, undecorate
- if field is not None:
- dsu = [[SList([line]).fields(field), line] for line in self]
- else:
- dsu = [[line, line] for line in self]
- if nums:
- for i in range(len(dsu)):
- numstr = "".join([ch for ch in dsu[i][0] if ch.isdigit()])
- try:
- n = int(numstr)
- except ValueError:
- n = 0
- dsu[i][0] = n
-
-
- dsu.sort()
- return SList([t[1] for t in dsu])
-
-
-# FIXME: We need to reimplement type specific displayhook and then add this
-# back as a custom printer. This should also be moved outside utils into the
-# core.
-
-# def print_slist(arg):
-# """ Prettier (non-repr-like) and more informative printer for SList """
-# print "SList (.p, .n, .l, .s, .grep(), .fields(), sort() available):"
-# if hasattr(arg, 'hideonce') and arg.hideonce:
-# arg.hideonce = False
-# return
-#
-# nlprint(arg) # This was a nested list printer, now removed.
-#
-# print_slist = result_display.register(SList)(print_slist)
-
-
-def indent(instr,nspaces=4, ntabs=0, flatten=False):
- """Indent a string a given number of spaces or tabstops.
-
- indent(str,nspaces=4,ntabs=0) -> indent str by ntabs+nspaces.
-
- Parameters
- ----------
- instr : basestring
- The string to be indented.
- nspaces : int (default: 4)
- The number of spaces to be indented.
- ntabs : int (default: 0)
- The number of tabs to be indented.
- flatten : bool (default: False)
- Whether to scrub existing indentation. If True, all lines will be
- aligned to the same indentation. If False, existing indentation will
- be strictly increased.
-
- Returns
- -------
- str|unicode : string indented by ntabs and nspaces.
-
- """
- if instr is None:
- return
- ind = '\t'*ntabs+' '*nspaces
- if flatten:
- pat = re.compile(r'^\s*', re.MULTILINE)
- else:
- pat = re.compile(r'^', re.MULTILINE)
- outstr = re.sub(pat, ind, instr)
- if outstr.endswith(os.linesep+ind):
- return outstr[:-len(ind)]
- else:
- return outstr
-
-
-def list_strings(arg):
- """Always return a list of strings, given a string or list of strings
- as input.
-
- Examples
- --------
- ::
-
- In [7]: list_strings('A single string')
- Out[7]: ['A single string']
-
- In [8]: list_strings(['A single string in a list'])
- Out[8]: ['A single string in a list']
-
- In [9]: list_strings(['A','list','of','strings'])
- Out[9]: ['A', 'list', 'of', 'strings']
- """
-
- if isinstance(arg, str):
- return [arg]
- else:
- return arg
-
-
-def marquee(txt='',width=78,mark='*'):
- """Return the input string centered in a 'marquee'.
-
- Examples
- --------
- ::
-
- In [16]: marquee('A test',40)
- Out[16]: '**************** A test ****************'
-
- In [17]: marquee('A test',40,'-')
- Out[17]: '---------------- A test ----------------'
-
- In [18]: marquee('A test',40,' ')
- Out[18]: ' A test '
-
- """
- if not txt:
- return (mark*width)[:width]
- nmark = (width-len(txt)-2)//len(mark)//2
- if nmark < 0: nmark =0
- marks = mark*nmark
- return '%s %s %s' % (marks,txt,marks)
-
-
-ini_spaces_re = re.compile(r'^(\s+)')
-
-def num_ini_spaces(strng):
- """Return the number of initial spaces in a string"""
-
- ini_spaces = ini_spaces_re.match(strng)
- if ini_spaces:
- return ini_spaces.end()
- else:
- return 0
-
-
-def format_screen(strng):
- """Format a string for screen printing.
-
- This removes some latex-type format codes."""
- # Paragraph continue
- par_re = re.compile(r'\\$',re.MULTILINE)
- strng = par_re.sub('',strng)
- return strng
-
-
-def dedent(text):
- """Equivalent of textwrap.dedent that ignores unindented first line.
-
- This means it will still dedent strings like:
- '''foo
- is a bar
- '''
-
- For use in wrap_paragraphs.
- """
-
- if text.startswith('\n'):
- # text starts with blank line, don't ignore the first line
- return textwrap.dedent(text)
-
- # split first line
- splits = text.split('\n',1)
- if len(splits) == 1:
- # only one line
- return textwrap.dedent(text)
-
- first, rest = splits
- # dedent everything but the first line
- rest = textwrap.dedent(rest)
- return '\n'.join([first, rest])
-
-
-def wrap_paragraphs(text, ncols=80):
- """Wrap multiple paragraphs to fit a specified width.
-
- This is equivalent to textwrap.wrap, but with support for multiple
- paragraphs, as separated by empty lines.
-
- Returns
- -------
- list of complete paragraphs, wrapped to fill `ncols` columns.
- """
- paragraph_re = re.compile(r'\n(\s*\n)+', re.MULTILINE)
- text = dedent(text).strip()
- paragraphs = paragraph_re.split(text)[::2] # every other entry is space
- out_ps = []
- indent_re = re.compile(r'\n\s+', re.MULTILINE)
- for p in paragraphs:
- # presume indentation that survives dedent is meaningful formatting,
- # so don't fill unless text is flush.
- if indent_re.search(p) is None:
- # wrap paragraph
- p = textwrap.fill(p, ncols)
- out_ps.append(p)
- return out_ps
-
-
-def strip_email_quotes(text):
- """Strip leading email quotation characters ('>').
-
- Removes any combination of leading '>' interspersed with whitespace that
- appears *identically* in all lines of the input text.
-
- Parameters
- ----------
- text : str
-
- Examples
- --------
-
- Simple uses::
-
- In [2]: strip_email_quotes('> > text')
- Out[2]: 'text'
-
- In [3]: strip_email_quotes('> > text\\n> > more')
- Out[3]: 'text\\nmore'
-
- Note how only the common prefix that appears in all lines is stripped::
-
- In [4]: strip_email_quotes('> > text\\n> > more\\n> more...')
- Out[4]: '> text\\n> more\\nmore...'
-
- So if any line has no quote marks ('>'), then none are stripped from any
- of them ::
-
- In [5]: strip_email_quotes('> > text\\n> > more\\nlast different')
- Out[5]: '> > text\\n> > more\\nlast different'
- """
- lines = text.splitlines()
- strip_len = 0
-
- for characters in zip(*lines):
- # Check if all characters in this position are the same
- if len(set(characters)) > 1:
- break
- prefix_char = characters[0]
-
- if prefix_char in string.whitespace or prefix_char == ">":
- strip_len += 1
- else:
- break
-
- text = "\n".join([ln[strip_len:] for ln in lines])
- return text
-
-
-def strip_ansi(source):
- """
- Remove ansi escape codes from text.
-
- Parameters
- ----------
- source : str
- Source to remove the ansi from
- """
- return re.sub(r'\033\[(\d|;)+?m', '', source)
-
-
-class EvalFormatter(Formatter):
- """A String Formatter that allows evaluation of simple expressions.
-
- Note that this version interprets a `:` as specifying a format string (as per
- standard string formatting), so if slicing is required, you must explicitly
- create a slice.
-
- This is to be used in templating cases, such as the parallel batch
- script templates, where simple arithmetic on arguments is useful.
-
- Examples
- --------
- ::
-
- In [1]: f = EvalFormatter()
- In [2]: f.format('{n//4}', n=8)
- Out[2]: '2'
-
- In [3]: f.format("{greeting[slice(2,4)]}", greeting="Hello")
- Out[3]: 'll'
- """
- def get_field(self, name, args, kwargs):
- v = eval(name, kwargs)
- return v, name
-
-#XXX: As of Python 3.4, the format string parsing no longer splits on a colon
-# inside [], so EvalFormatter can handle slicing. Once we only support 3.4 and
-# above, it should be possible to remove FullEvalFormatter.
-
-class FullEvalFormatter(Formatter):
- """A String Formatter that allows evaluation of simple expressions.
-
- Any time a format key is not found in the kwargs,
- it will be tried as an expression in the kwargs namespace.
-
- Note that this version allows slicing using [1:2], so you cannot specify
- a format string. Use :class:`EvalFormatter` to permit format strings.
-
- Examples
- --------
- ::
-
- In [1]: f = FullEvalFormatter()
- In [2]: f.format('{n//4}', n=8)
- Out[2]: '2'
-
- In [3]: f.format('{list(range(5))[2:4]}')
- Out[3]: '[2, 3]'
-
- In [4]: f.format('{3*2}')
- Out[4]: '6'
- """
- # copied from Formatter._vformat with minor changes to allow eval
- # and replace the format_spec code with slicing
- def vformat(self, format_string:str, args, kwargs)->str:
- result = []
- for literal_text, field_name, format_spec, conversion in \
- self.parse(format_string):
-
- # output the literal text
- if literal_text:
- result.append(literal_text)
-
- # if there's a field, output it
- if field_name is not None:
- # this is some markup, find the object and do
- # the formatting
-
- if format_spec:
- # override format spec, to allow slicing:
- field_name = ':'.join([field_name, format_spec])
-
- # eval the contents of the field for the object
- # to be formatted
- obj = eval(field_name, kwargs)
-
- # do any conversion on the resulting object
- obj = self.convert_field(obj, conversion)
-
- # format the object and append to the result
- result.append(self.format_field(obj, ''))
-
- return ''.join(result)
-
-
-class DollarFormatter(FullEvalFormatter):
- """Formatter allowing Itpl style $foo replacement, for names and attribute
- access only. Standard {foo} replacement also works, and allows full
- evaluation of its arguments.
-
- Examples
- --------
- ::
-
- In [1]: f = DollarFormatter()
- In [2]: f.format('{n//4}', n=8)
- Out[2]: '2'
-
- In [3]: f.format('23 * 76 is $result', result=23*76)
- Out[3]: '23 * 76 is 1748'
-
- In [4]: f.format('$a or {b}', a=1, b=2)
- Out[4]: '1 or 2'
- """
- _dollar_pattern_ignore_single_quote = re.compile(r"(.*?)\$(\$?[\w\.]+)(?=([^']*'[^']*')*[^']*$)")
- def parse(self, fmt_string):
- for literal_txt, field_name, format_spec, conversion \
- in Formatter.parse(self, fmt_string):
-
- # Find $foo patterns in the literal text.
- continue_from = 0
- txt = ""
- for m in self._dollar_pattern_ignore_single_quote.finditer(literal_txt):
- new_txt, new_field = m.group(1,2)
- # $$foo --> $foo
- if new_field.startswith("$"):
- txt += new_txt + new_field
- else:
- yield (txt + new_txt, new_field, "", None)
- txt = ""
- continue_from = m.end()
-
- # Re-yield the {foo} style pattern
- yield (txt + literal_txt[continue_from:], field_name, format_spec, conversion)
-
- def __repr__(self):
- return ""
-
-#-----------------------------------------------------------------------------
-# Utils to columnize a list of string
-#-----------------------------------------------------------------------------
-
-def _col_chunks(l, max_rows, row_first=False):
- """Yield successive max_rows-sized column chunks from l."""
- if row_first:
- ncols = (len(l) // max_rows) + (len(l) % max_rows > 0)
- for i in range(ncols):
- yield [l[j] for j in range(i, len(l), ncols)]
- else:
- for i in range(0, len(l), max_rows):
- yield l[i:(i + max_rows)]
-
-
-def _find_optimal(rlist, row_first=False, separator_size=2, displaywidth=80):
- """Calculate optimal info to columnize a list of string"""
- for max_rows in range(1, len(rlist) + 1):
- col_widths = list(map(max, _col_chunks(rlist, max_rows, row_first)))
- sumlength = sum(col_widths)
- ncols = len(col_widths)
- if sumlength + separator_size * (ncols - 1) <= displaywidth:
- break
- return {'num_columns': ncols,
- 'optimal_separator_width': (displaywidth - sumlength) // (ncols - 1) if (ncols - 1) else 0,
- 'max_rows': max_rows,
- 'column_widths': col_widths
- }
-
-
-def _get_or_default(mylist, i, default=None):
- """return list item number, or default if don't exist"""
- if i >= len(mylist):
- return default
- else :
- return mylist[i]
-
-
-def compute_item_matrix(items, row_first=False, empty=None, *args, **kwargs) :
- """Returns a nested list, and info to columnize items
-
- Parameters
- ----------
- items
- list of strings to columize
- row_first : (default False)
- Whether to compute columns for a row-first matrix instead of
- column-first (default).
- empty : (default None)
- default value to fill list if needed
- separator_size : int (default=2)
- How much characters will be used as a separation between each columns.
- displaywidth : int (default=80)
- The width of the area onto which the columns should enter
-
- Returns
- -------
- strings_matrix
- nested list of string, the outer most list contains as many list as
- rows, the innermost lists have each as many element as columns. If the
- total number of elements in `items` does not equal the product of
- rows*columns, the last element of some lists are filled with `None`.
- dict_info
- some info to make columnize easier:
-
- num_columns
- number of columns
- max_rows
- maximum number of rows (final number may be less)
- column_widths
- list of with of each columns
- optimal_separator_width
- best separator width between columns
-
- Examples
- --------
- ::
-
- In [1]: l = ['aaa','b','cc','d','eeeee','f','g','h','i','j','k','l']
- In [2]: list, info = compute_item_matrix(l, displaywidth=12)
- In [3]: list
- Out[3]: [['aaa', 'f', 'k'], ['b', 'g', 'l'], ['cc', 'h', None], ['d', 'i', None], ['eeeee', 'j', None]]
- In [4]: ideal = {'num_columns': 3, 'column_widths': [5, 1, 1], 'optimal_separator_width': 2, 'max_rows': 5}
- In [5]: all((info[k] == ideal[k] for k in ideal.keys()))
- Out[5]: True
- """
- info = _find_optimal(list(map(len, items)), row_first, *args, **kwargs)
- nrow, ncol = info['max_rows'], info['num_columns']
- if row_first:
- return ([[_get_or_default(items, r * ncol + c, default=empty) for c in range(ncol)] for r in range(nrow)], info)
- else:
- return ([[_get_or_default(items, c * nrow + r, default=empty) for c in range(ncol)] for r in range(nrow)], info)
-
-
-def columnize(items, row_first=False, separator=" ", displaywidth=80, spread=False):
- """Transform a list of strings into a single string with columns.
-
- Parameters
- ----------
- items : sequence of strings
- The strings to process.
- row_first : (default False)
- Whether to compute columns for a row-first matrix instead of
- column-first (default).
- separator : str, optional [default is two spaces]
- The string that separates columns.
- displaywidth : int, optional [default is 80]
- Width of the display in number of characters.
-
- Returns
- -------
- The formatted string.
- """
- if not items:
- return '\n'
- matrix, info = compute_item_matrix(items, row_first=row_first, separator_size=len(separator), displaywidth=displaywidth)
- if spread:
- separator = separator.ljust(int(info['optimal_separator_width']))
- fmatrix = [filter(None, x) for x in matrix]
- sjoin = lambda x : separator.join([ y.ljust(w, ' ') for y, w in zip(x, info['column_widths'])])
- return '\n'.join(map(sjoin, fmatrix))+'\n'
-
-
-def get_text_list(list_, last_sep=' and ', sep=", ", wrap_item_with=""):
- """
- Return a string with a natural enumeration of items
-
- >>> get_text_list(['a', 'b', 'c', 'd'])
- 'a, b, c and d'
- >>> get_text_list(['a', 'b', 'c'], ' or ')
- 'a, b or c'
- >>> get_text_list(['a', 'b', 'c'], ', ')
- 'a, b, c'
- >>> get_text_list(['a', 'b'], ' or ')
- 'a or b'
- >>> get_text_list(['a'])
- 'a'
- >>> get_text_list([])
- ''
- >>> get_text_list(['a', 'b'], wrap_item_with="`")
- '`a` and `b`'
- >>> get_text_list(['a', 'b', 'c', 'd'], " = ", sep=" + ")
- 'a + b + c = d'
- """
- if len(list_) == 0:
- return ''
- if wrap_item_with:
- list_ = ['%s%s%s' % (wrap_item_with, item, wrap_item_with) for
- item in list_]
- if len(list_) == 1:
- return list_[0]
- return '%s%s%s' % (
- sep.join(i for i in list_[:-1]),
- last_sep, list_[-1])
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/dateutil/tz/win.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/dateutil/tz/win.py
deleted file mode 100644
index cde07ba792c40903f0c334839140173b39fd8124..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/dateutil/tz/win.py
+++ /dev/null
@@ -1,370 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-This module provides an interface to the native time zone data on Windows,
-including :py:class:`datetime.tzinfo` implementations.
-
-Attempting to import this module on a non-Windows platform will raise an
-:py:obj:`ImportError`.
-"""
-# This code was originally contributed by Jeffrey Harris.
-import datetime
-import struct
-
-from six.moves import winreg
-from six import text_type
-
-try:
- import ctypes
- from ctypes import wintypes
-except ValueError:
- # ValueError is raised on non-Windows systems for some horrible reason.
- raise ImportError("Running tzwin on non-Windows system")
-
-from ._common import tzrangebase
-
-__all__ = ["tzwin", "tzwinlocal", "tzres"]
-
-ONEWEEK = datetime.timedelta(7)
-
-TZKEYNAMENT = r"SOFTWARE\Microsoft\Windows NT\CurrentVersion\Time Zones"
-TZKEYNAME9X = r"SOFTWARE\Microsoft\Windows\CurrentVersion\Time Zones"
-TZLOCALKEYNAME = r"SYSTEM\CurrentControlSet\Control\TimeZoneInformation"
-
-
-def _settzkeyname():
- handle = winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE)
- try:
- winreg.OpenKey(handle, TZKEYNAMENT).Close()
- TZKEYNAME = TZKEYNAMENT
- except WindowsError:
- TZKEYNAME = TZKEYNAME9X
- handle.Close()
- return TZKEYNAME
-
-
-TZKEYNAME = _settzkeyname()
-
-
-class tzres(object):
- """
- Class for accessing ``tzres.dll``, which contains timezone name related
- resources.
-
- .. versionadded:: 2.5.0
- """
- p_wchar = ctypes.POINTER(wintypes.WCHAR) # Pointer to a wide char
-
- def __init__(self, tzres_loc='tzres.dll'):
- # Load the user32 DLL so we can load strings from tzres
- user32 = ctypes.WinDLL('user32')
-
- # Specify the LoadStringW function
- user32.LoadStringW.argtypes = (wintypes.HINSTANCE,
- wintypes.UINT,
- wintypes.LPWSTR,
- ctypes.c_int)
-
- self.LoadStringW = user32.LoadStringW
- self._tzres = ctypes.WinDLL(tzres_loc)
- self.tzres_loc = tzres_loc
-
- def load_name(self, offset):
- """
- Load a timezone name from a DLL offset (integer).
-
- >>> from dateutil.tzwin import tzres
- >>> tzr = tzres()
- >>> print(tzr.load_name(112))
- 'Eastern Standard Time'
-
- :param offset:
- A positive integer value referring to a string from the tzres dll.
-
- .. note::
-
- Offsets found in the registry are generally of the form
- ``@tzres.dll,-114``. The offset in this case is 114, not -114.
-
- """
- resource = self.p_wchar()
- lpBuffer = ctypes.cast(ctypes.byref(resource), wintypes.LPWSTR)
- nchar = self.LoadStringW(self._tzres._handle, offset, lpBuffer, 0)
- return resource[:nchar]
-
- def name_from_string(self, tzname_str):
- """
- Parse strings as returned from the Windows registry into the time zone
- name as defined in the registry.
-
- >>> from dateutil.tzwin import tzres
- >>> tzr = tzres()
- >>> print(tzr.name_from_string('@tzres.dll,-251'))
- 'Dateline Daylight Time'
- >>> print(tzr.name_from_string('Eastern Standard Time'))
- 'Eastern Standard Time'
-
- :param tzname_str:
- A timezone name string as returned from a Windows registry key.
-
- :return:
- Returns the localized timezone string from tzres.dll if the string
- is of the form `@tzres.dll,-offset`, else returns the input string.
- """
- if not tzname_str.startswith('@'):
- return tzname_str
-
- name_splt = tzname_str.split(',-')
- try:
- offset = int(name_splt[1])
- except:
- raise ValueError("Malformed timezone string.")
-
- return self.load_name(offset)
-
-
-class tzwinbase(tzrangebase):
- """tzinfo class based on win32's timezones available in the registry."""
- def __init__(self):
- raise NotImplementedError('tzwinbase is an abstract base class')
-
- def __eq__(self, other):
- # Compare on all relevant dimensions, including name.
- if not isinstance(other, tzwinbase):
- return NotImplemented
-
- return (self._std_offset == other._std_offset and
- self._dst_offset == other._dst_offset and
- self._stddayofweek == other._stddayofweek and
- self._dstdayofweek == other._dstdayofweek and
- self._stdweeknumber == other._stdweeknumber and
- self._dstweeknumber == other._dstweeknumber and
- self._stdhour == other._stdhour and
- self._dsthour == other._dsthour and
- self._stdminute == other._stdminute and
- self._dstminute == other._dstminute and
- self._std_abbr == other._std_abbr and
- self._dst_abbr == other._dst_abbr)
-
- @staticmethod
- def list():
- """Return a list of all time zones known to the system."""
- with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
- with winreg.OpenKey(handle, TZKEYNAME) as tzkey:
- result = [winreg.EnumKey(tzkey, i)
- for i in range(winreg.QueryInfoKey(tzkey)[0])]
- return result
-
- def display(self):
- """
- Return the display name of the time zone.
- """
- return self._display
-
- def transitions(self, year):
- """
- For a given year, get the DST on and off transition times, expressed
- always on the standard time side. For zones with no transitions, this
- function returns ``None``.
-
- :param year:
- The year whose transitions you would like to query.
-
- :return:
- Returns a :class:`tuple` of :class:`datetime.datetime` objects,
- ``(dston, dstoff)`` for zones with an annual DST transition, or
- ``None`` for fixed offset zones.
- """
-
- if not self.hasdst:
- return None
-
- dston = picknthweekday(year, self._dstmonth, self._dstdayofweek,
- self._dsthour, self._dstminute,
- self._dstweeknumber)
-
- dstoff = picknthweekday(year, self._stdmonth, self._stddayofweek,
- self._stdhour, self._stdminute,
- self._stdweeknumber)
-
- # Ambiguous dates default to the STD side
- dstoff -= self._dst_base_offset
-
- return dston, dstoff
-
- def _get_hasdst(self):
- return self._dstmonth != 0
-
- @property
- def _dst_base_offset(self):
- return self._dst_base_offset_
-
-
-class tzwin(tzwinbase):
- """
- Time zone object created from the zone info in the Windows registry
-
- These are similar to :py:class:`dateutil.tz.tzrange` objects in that
- the time zone data is provided in the format of a single offset rule
- for either 0 or 2 time zone transitions per year.
-
- :param: name
- The name of a Windows time zone key, e.g. "Eastern Standard Time".
- The full list of keys can be retrieved with :func:`tzwin.list`.
- """
-
- def __init__(self, name):
- self._name = name
-
- with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
- tzkeyname = text_type("{kn}\\{name}").format(kn=TZKEYNAME, name=name)
- with winreg.OpenKey(handle, tzkeyname) as tzkey:
- keydict = valuestodict(tzkey)
-
- self._std_abbr = keydict["Std"]
- self._dst_abbr = keydict["Dlt"]
-
- self._display = keydict["Display"]
-
- # See http://ww_winreg.jsiinc.com/SUBA/tip0300/rh0398.htm
- tup = struct.unpack("=3l16h", keydict["TZI"])
- stdoffset = -tup[0]-tup[1] # Bias + StandardBias * -1
- dstoffset = stdoffset-tup[2] # + DaylightBias * -1
- self._std_offset = datetime.timedelta(minutes=stdoffset)
- self._dst_offset = datetime.timedelta(minutes=dstoffset)
-
- # for the meaning see the win32 TIME_ZONE_INFORMATION structure docs
- # http://msdn.microsoft.com/en-us/library/windows/desktop/ms725481(v=vs.85).aspx
- (self._stdmonth,
- self._stddayofweek, # Sunday = 0
- self._stdweeknumber, # Last = 5
- self._stdhour,
- self._stdminute) = tup[4:9]
-
- (self._dstmonth,
- self._dstdayofweek, # Sunday = 0
- self._dstweeknumber, # Last = 5
- self._dsthour,
- self._dstminute) = tup[12:17]
-
- self._dst_base_offset_ = self._dst_offset - self._std_offset
- self.hasdst = self._get_hasdst()
-
- def __repr__(self):
- return "tzwin(%s)" % repr(self._name)
-
- def __reduce__(self):
- return (self.__class__, (self._name,))
-
-
-class tzwinlocal(tzwinbase):
- """
- Class representing the local time zone information in the Windows registry
-
- While :class:`dateutil.tz.tzlocal` makes system calls (via the :mod:`time`
- module) to retrieve time zone information, ``tzwinlocal`` retrieves the
- rules directly from the Windows registry and creates an object like
- :class:`dateutil.tz.tzwin`.
-
- Because Windows does not have an equivalent of :func:`time.tzset`, on
- Windows, :class:`dateutil.tz.tzlocal` instances will always reflect the
- time zone settings *at the time that the process was started*, meaning
- changes to the machine's time zone settings during the run of a program
- on Windows will **not** be reflected by :class:`dateutil.tz.tzlocal`.
- Because ``tzwinlocal`` reads the registry directly, it is unaffected by
- this issue.
- """
- def __init__(self):
- with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
- with winreg.OpenKey(handle, TZLOCALKEYNAME) as tzlocalkey:
- keydict = valuestodict(tzlocalkey)
-
- self._std_abbr = keydict["StandardName"]
- self._dst_abbr = keydict["DaylightName"]
-
- try:
- tzkeyname = text_type('{kn}\\{sn}').format(kn=TZKEYNAME,
- sn=self._std_abbr)
- with winreg.OpenKey(handle, tzkeyname) as tzkey:
- _keydict = valuestodict(tzkey)
- self._display = _keydict["Display"]
- except OSError:
- self._display = None
-
- stdoffset = -keydict["Bias"]-keydict["StandardBias"]
- dstoffset = stdoffset-keydict["DaylightBias"]
-
- self._std_offset = datetime.timedelta(minutes=stdoffset)
- self._dst_offset = datetime.timedelta(minutes=dstoffset)
-
- # For reasons unclear, in this particular key, the day of week has been
- # moved to the END of the SYSTEMTIME structure.
- tup = struct.unpack("=8h", keydict["StandardStart"])
-
- (self._stdmonth,
- self._stdweeknumber, # Last = 5
- self._stdhour,
- self._stdminute) = tup[1:5]
-
- self._stddayofweek = tup[7]
-
- tup = struct.unpack("=8h", keydict["DaylightStart"])
-
- (self._dstmonth,
- self._dstweeknumber, # Last = 5
- self._dsthour,
- self._dstminute) = tup[1:5]
-
- self._dstdayofweek = tup[7]
-
- self._dst_base_offset_ = self._dst_offset - self._std_offset
- self.hasdst = self._get_hasdst()
-
- def __repr__(self):
- return "tzwinlocal()"
-
- def __str__(self):
- # str will return the standard name, not the daylight name.
- return "tzwinlocal(%s)" % repr(self._std_abbr)
-
- def __reduce__(self):
- return (self.__class__, ())
-
-
-def picknthweekday(year, month, dayofweek, hour, minute, whichweek):
- """ dayofweek == 0 means Sunday, whichweek 5 means last instance """
- first = datetime.datetime(year, month, 1, hour, minute)
-
- # This will work if dayofweek is ISO weekday (1-7) or Microsoft-style (0-6),
- # Because 7 % 7 = 0
- weekdayone = first.replace(day=((dayofweek - first.isoweekday()) % 7) + 1)
- wd = weekdayone + ((whichweek - 1) * ONEWEEK)
- if (wd.month != month):
- wd -= ONEWEEK
-
- return wd
-
-
-def valuestodict(key):
- """Convert a registry key's values to a dictionary."""
- dout = {}
- size = winreg.QueryInfoKey(key)[1]
- tz_res = None
-
- for i in range(size):
- key_name, value, dtype = winreg.EnumValue(key, i)
- if dtype == winreg.REG_DWORD or dtype == winreg.REG_DWORD_LITTLE_ENDIAN:
- # If it's a DWORD (32-bit integer), it's stored as unsigned - convert
- # that to a proper signed integer
- if value & (1 << 31):
- value = value - (1 << 32)
- elif dtype == winreg.REG_SZ:
- # If it's a reference to the tzres DLL, load the actual string
- if value.startswith('@tzres'):
- tz_res = tz_res or tzres()
- value = tz_res.name_from_string(value)
-
- value = value.rstrip('\x00') # Remove trailing nulls
-
- dout[key_name] = value
-
- return dout
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydev_app_engine_debug_startup.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydev_app_engine_debug_startup.py
deleted file mode 100644
index 464f0ddf3464b5f5354ce1bbf7b7f8da0610c706..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydev_app_engine_debug_startup.py
+++ /dev/null
@@ -1,21 +0,0 @@
-if False:
- config = None
-
-
-# See: https://docs.google.com/document/d/1CCSaRiIWCLgbD3OwmuKsRoHHDfBffbROWyVWWL0ZXN4/edit
-if ':' not in config.version_id:
- # The default server version_id does not contain ':'
- import json
- import os
- import sys
-
- startup = config.python_config.startup_args
- if not startup:
- raise AssertionError('Expected --python_startup_args to be passed from the pydev debugger.')
-
- setup = json.loads(startup)
- pydevd_path = setup['pydevd']
- sys.path.append(os.path.dirname(pydevd_path))
-
- import pydevd
- pydevd.settrace(setup['client'], port=setup['port'], suspend=False, trace_only_current_thread=False)
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/add_code_to_python_process.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/add_code_to_python_process.py
deleted file mode 100644
index ed43e3706aa9d6248b7102c0f86993170821d57f..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_attach_to_process/add_code_to_python_process.py
+++ /dev/null
@@ -1,592 +0,0 @@
-r'''
-Copyright: Brainwy Software Ltda.
-
-License: EPL.
-=============
-
-Works for Windows by using an executable that'll inject a dll to a process and call a function.
-
-Note: https://github.com/fabioz/winappdbg is used just to determine if the target process is 32 or 64 bits.
-
-Works for Linux relying on gdb.
-
-Limitations:
-============
-
- Linux:
- ------
-
- 1. It possible that ptrace is disabled: /etc/sysctl.d/10-ptrace.conf
-
- Note that even enabling it in /etc/sysctl.d/10-ptrace.conf (i.e.: making the
- ptrace_scope=0), it's possible that we need to run the application that'll use ptrace (or
- gdb in this case) as root (so, we must sudo the python which'll run this module).
-
- 2. It currently doesn't work in debug builds (i.e.: python_d)
-
-
-Other implementations:
-- pyrasite.com:
- GPL
- Windows/linux (in Linux it also uses gdb to connect -- although specifics are different as we use a dll to execute
- code with other threads stopped). It's Windows approach is more limited because it doesn't seem to deal properly with
- Python 3 if threading is disabled.
-
-- https://github.com/google/pyringe:
- Apache v2.
- Only linux/Python 2.
-
-- http://pytools.codeplex.com:
- Apache V2
- Windows Only (but supports mixed mode debugging)
- Our own code relies heavily on a part of it: http://pytools.codeplex.com/SourceControl/latest#Python/Product/PyDebugAttach/PyDebugAttach.cpp
- to overcome some limitations of attaching and running code in the target python executable on Python 3.
- See: attach.cpp
-
-Linux: References if we wanted to use a pure-python debugger:
- https://bitbucket.org/haypo/python-ptrace/
- http://stackoverflow.com/questions/7841573/how-to-get-an-error-message-for-errno-value-in-python
- Jugaad:
- https://www.defcon.org/images/defcon-19/dc-19-presentations/Jakhar/DEFCON-19-Jakhar-Jugaad-Linux-Thread-Injection.pdf
- https://github.com/aseemjakhar/jugaad
-
-Something else (general and not Python related):
-- http://www.codeproject.com/Articles/4610/Three-Ways-to-Inject-Your-Code-into-Another-Proces
-
-Other references:
-- https://github.com/haypo/faulthandler
-- http://nedbatchelder.com/text/trace-function.html
-- https://github.com/python-git/python/blob/master/Python/sysmodule.c (sys_settrace)
-- https://github.com/python-git/python/blob/master/Python/ceval.c (PyEval_SetTrace)
-- https://github.com/python-git/python/blob/master/Python/thread.c (PyThread_get_key_value)
-
-
-To build the dlls needed on windows, visual studio express 13 was used (see compile_dll.bat)
-
-See: attach_pydevd.py to attach the pydev debugger to a running python process.
-'''
-
-# Note: to work with nasm compiling asm to code and decompiling to see asm with shellcode:
-# x:\nasm\nasm-2.07-win32\nasm-2.07\nasm.exe
-# nasm.asm&x:\nasm\nasm-2.07-win32\nasm-2.07\ndisasm.exe -b arch nasm
-import ctypes
-import os
-import struct
-import subprocess
-import sys
-import time
-from contextlib import contextmanager
-import platform
-import traceback
-
-try:
- TimeoutError = TimeoutError # @ReservedAssignment
-except NameError:
-
- class TimeoutError(RuntimeError): # @ReservedAssignment
- pass
-
-
-@contextmanager
-def _create_win_event(name):
- from winappdbg.win32.kernel32 import CreateEventA, WaitForSingleObject, CloseHandle
-
- manual_reset = False # i.e.: after someone waits it, automatically set to False.
- initial_state = False
- if not isinstance(name, bytes):
- name = name.encode('utf-8')
- event = CreateEventA(None, manual_reset, initial_state, name)
- if not event:
- raise ctypes.WinError()
-
- class _WinEvent(object):
-
- def wait_for_event_set(self, timeout=None):
- '''
- :param timeout: in seconds
- '''
- if timeout is None:
- timeout = 0xFFFFFFFF
- else:
- timeout = int(timeout * 1000)
- ret = WaitForSingleObject(event, timeout)
- if ret in (0, 0x80):
- return True
- elif ret == 0x102:
- # Timed out
- return False
- else:
- raise ctypes.WinError()
-
- try:
- yield _WinEvent()
- finally:
- CloseHandle(event)
-
-
-IS_WINDOWS = sys.platform == 'win32'
-IS_LINUX = sys.platform in ('linux', 'linux2')
-IS_MAC = sys.platform == 'darwin'
-
-
-def is_python_64bit():
- return (struct.calcsize('P') == 8)
-
-
-def get_target_filename(is_target_process_64=None, prefix=None, extension=None):
- # Note: we have an independent (and similar -- but not equal) version of this method in
- # `pydevd_tracing.py` which should be kept synchronized with this one (we do a copy
- # because the `pydevd_attach_to_process` is mostly independent and shouldn't be imported in the
- # debugger -- the only situation where it's imported is if the user actually does an attach to
- # process, through `attach_pydevd.py`, but this should usually be called from the IDE directly
- # and not from the debugger).
- libdir = os.path.dirname(__file__)
-
- if is_target_process_64 is None:
- if IS_WINDOWS:
- # i.e.: On windows the target process could have a different bitness (32bit is emulated on 64bit).
- raise AssertionError("On windows it's expected that the target bitness is specified.")
-
- # For other platforms, just use the the same bitness of the process we're running in.
- is_target_process_64 = is_python_64bit()
-
- arch = ''
- if IS_WINDOWS:
- # prefer not using platform.machine() when possible (it's a bit heavyweight as it may
- # spawn a subprocess).
- arch = os.environ.get("PROCESSOR_ARCHITEW6432", os.environ.get('PROCESSOR_ARCHITECTURE', ''))
-
- if not arch:
- arch = platform.machine()
- if not arch:
- print('platform.machine() did not return valid value.') # This shouldn't happen...
- return None
-
- if IS_WINDOWS:
- if not extension:
- extension = '.dll'
- suffix_64 = 'amd64'
- suffix_32 = 'x86'
-
- elif IS_LINUX:
- if not extension:
- extension = '.so'
- suffix_64 = 'amd64'
- suffix_32 = 'x86'
-
- elif IS_MAC:
- if not extension:
- extension = '.dylib'
- suffix_64 = 'x86_64'
- suffix_32 = 'x86'
-
- else:
- print('Unable to attach to process in platform: %s', sys.platform)
- return None
-
- if arch.lower() not in ('amd64', 'x86', 'x86_64', 'i386', 'x86'):
- # We don't support this processor by default. Still, let's support the case where the
- # user manually compiled it himself with some heuristics.
- #
- # Ideally the user would provide a library in the format: "attach_."
- # based on the way it's currently compiled -- see:
- # - windows/compile_windows.bat
- # - linux_and_mac/compile_linux.sh
- # - linux_and_mac/compile_mac.sh
-
- try:
- found = [name for name in os.listdir(libdir) if name.startswith('attach_') and name.endswith(extension)]
- except:
- print('Error listing dir: %s' % (libdir,))
- traceback.print_exc()
- return None
-
- if prefix:
- expected_name = prefix + arch + extension
- expected_name_linux = prefix + 'linux_' + arch + extension
- else:
- # Default is looking for the attach_ / attach_linux
- expected_name = 'attach_' + arch + extension
- expected_name_linux = 'attach_linux_' + arch + extension
-
- filename = None
- if expected_name in found: # Heuristic: user compiled with "attach_."
- filename = os.path.join(libdir, expected_name)
-
- elif IS_LINUX and expected_name_linux in found: # Heuristic: user compiled with "attach_linux_."
- filename = os.path.join(libdir, expected_name_linux)
-
- elif len(found) == 1: # Heuristic: user removed all libraries and just left his own lib.
- filename = os.path.join(libdir, found[0])
-
- else: # Heuristic: there's one additional library which doesn't seem to be our own. Find the odd one.
- filtered = [name for name in found if not name.endswith((suffix_64 + extension, suffix_32 + extension))]
- if len(filtered) == 1: # If more than one is available we can't be sure...
- filename = os.path.join(libdir, found[0])
-
- if filename is None:
- print(
- 'Unable to attach to process in arch: %s (did not find %s in %s).' % (
- arch, expected_name, libdir
- )
- )
- return None
-
- print('Using %s in arch: %s.' % (filename, arch))
-
- else:
- if is_target_process_64:
- suffix = suffix_64
- else:
- suffix = suffix_32
-
- if not prefix:
- # Default is looking for the attach_ / attach_linux
- if IS_WINDOWS or IS_MAC: # just the extension changes
- prefix = 'attach_'
- elif IS_LINUX:
- prefix = 'attach_linux_' # historically it has a different name
- else:
- print('Unable to attach to process in platform: %s' % (sys.platform,))
- return None
-
- filename = os.path.join(libdir, '%s%s%s' % (prefix, suffix, extension))
-
- if not os.path.exists(filename):
- print('Expected: %s to exist.' % (filename,))
- return None
-
- return filename
-
-
-def run_python_code_windows(pid, python_code, connect_debugger_tracing=False, show_debug_info=0):
- assert '\'' not in python_code, 'Having a single quote messes with our command.'
- from winappdbg.process import Process
- if not isinstance(python_code, bytes):
- python_code = python_code.encode('utf-8')
-
- process = Process(pid)
- bits = process.get_bits()
- is_target_process_64 = bits == 64
-
- # Note: this restriction no longer applies (we create a process with the proper bitness from
- # this process so that the attach works).
- # if is_target_process_64 != is_python_64bit():
- # raise RuntimeError("The architecture of the Python used to connect doesn't match the architecture of the target.\n"
- # "Target 64 bits: %s\n"
- # "Current Python 64 bits: %s" % (is_target_process_64, is_python_64bit()))
-
- with _acquire_mutex('_pydevd_pid_attach_mutex_%s' % (pid,), 10):
- print('--- Connecting to %s bits target (current process is: %s) ---' % (bits, 64 if is_python_64bit() else 32))
- sys.stdout.flush()
-
- with _win_write_to_shared_named_memory(python_code, pid):
-
- target_executable = get_target_filename(is_target_process_64, 'inject_dll_', '.exe')
- if not target_executable:
- raise RuntimeError('Could not find expected .exe file to inject dll in attach to process.')
-
- target_dll = get_target_filename(is_target_process_64)
- if not target_dll:
- raise RuntimeError('Could not find expected .dll file in attach to process.')
-
- print('\n--- Injecting attach dll: %s into pid: %s ---' % (os.path.basename(target_dll), pid))
- sys.stdout.flush()
- args = [target_executable, str(pid), target_dll]
- subprocess.check_call(args)
-
- # Now, if the first injection worked, go on to the second which will actually
- # run the code.
- target_dll_run_on_dllmain = get_target_filename(is_target_process_64, 'run_code_on_dllmain_', '.dll')
- if not target_dll_run_on_dllmain:
- raise RuntimeError('Could not find expected .dll in attach to process.')
-
- with _create_win_event('_pydevd_pid_event_%s' % (pid,)) as event:
- print('\n--- Injecting run code dll: %s into pid: %s ---' % (os.path.basename(target_dll_run_on_dllmain), pid))
- sys.stdout.flush()
- args = [target_executable, str(pid), target_dll_run_on_dllmain]
- subprocess.check_call(args)
-
- if not event.wait_for_event_set(15):
- print('Timeout error: the attach may not have completed.')
- sys.stdout.flush()
- print('--- Finished dll injection ---\n')
- sys.stdout.flush()
-
- return 0
-
-
-@contextmanager
-def _acquire_mutex(mutex_name, timeout):
- '''
- Only one process may be attaching to a pid, so, create a system mutex
- to make sure this holds in practice.
- '''
- from winappdbg.win32.kernel32 import CreateMutex, GetLastError, CloseHandle
- from winappdbg.win32.defines import ERROR_ALREADY_EXISTS
-
- initial_time = time.time()
- while True:
- mutex = CreateMutex(None, True, mutex_name)
- acquired = GetLastError() != ERROR_ALREADY_EXISTS
- if acquired:
- break
- if time.time() - initial_time > timeout:
- raise TimeoutError('Unable to acquire mutex to make attach before timeout.')
- time.sleep(.2)
-
- try:
- yield
- finally:
- CloseHandle(mutex)
-
-
-@contextmanager
-def _win_write_to_shared_named_memory(python_code, pid):
- # Use the definitions from winappdbg when possible.
- from winappdbg.win32 import defines
- from winappdbg.win32.kernel32 import (
- CreateFileMapping,
- MapViewOfFile,
- CloseHandle,
- UnmapViewOfFile,
- )
-
- memmove = ctypes.cdll.msvcrt.memmove
- memmove.argtypes = [
- ctypes.c_void_p,
- ctypes.c_void_p,
- defines.SIZE_T,
- ]
- memmove.restype = ctypes.c_void_p
-
- # Note: BUFSIZE must be the same from run_code_in_memory.hpp
- BUFSIZE = 2048
- assert isinstance(python_code, bytes)
- assert len(python_code) > 0, 'Python code must not be empty.'
- # Note: -1 so that we're sure we'll add a \0 to the end.
- assert len(python_code) < BUFSIZE - 1, 'Python code must have at most %s bytes (found: %s)' % (BUFSIZE - 1, len(python_code))
-
- python_code += b'\0' * (BUFSIZE - len(python_code))
- assert python_code.endswith(b'\0')
-
- INVALID_HANDLE_VALUE = -1
- PAGE_READWRITE = 0x4
- FILE_MAP_WRITE = 0x2
- filemap = CreateFileMapping(
- INVALID_HANDLE_VALUE, 0, PAGE_READWRITE, 0, BUFSIZE, u"__pydevd_pid_code_to_run__%s" % (pid,))
-
- if filemap == INVALID_HANDLE_VALUE or filemap is None:
- raise Exception("Failed to create named file mapping (ctypes: CreateFileMapping): %s" % (filemap,))
- try:
- view = MapViewOfFile(filemap, FILE_MAP_WRITE, 0, 0, 0)
- if not view:
- raise Exception("Failed to create view of named file mapping (ctypes: MapViewOfFile).")
-
- try:
- memmove(view, python_code, BUFSIZE)
- yield
- finally:
- UnmapViewOfFile(view)
- finally:
- CloseHandle(filemap)
-
-
-def run_python_code_linux(pid, python_code, connect_debugger_tracing=False, show_debug_info=0):
- assert '\'' not in python_code, 'Having a single quote messes with our command.'
-
- target_dll = get_target_filename()
- if not target_dll:
- raise RuntimeError('Could not find .so for attach to process.')
- target_dll_name = os.path.splitext(os.path.basename(target_dll))[0]
-
- # Note: we currently don't support debug builds
- is_debug = 0
- # Note that the space in the beginning of each line in the multi-line is important!
- cmd = [
- 'gdb',
- '--nw', # no gui interface
- '--nh', # no ~/.gdbinit
- '--nx', # no .gdbinit
-# '--quiet', # no version number on startup
- '--pid',
- str(pid),
- '--batch',
-# '--batch-silent',
- ]
-
- # PYDEVD_GDB_SCAN_SHARED_LIBRARIES can be a list of strings with the shared libraries
- # which should be scanned by default to make the attach to process (i.e.: libdl, libltdl, libc, libfreebl3).
- #
- # The default is scanning all shared libraries, but on some cases this can be in the 20-30
- # seconds range for some corner cases.
- # See: https://github.com/JetBrains/intellij-community/pull/1608
- #
- # By setting PYDEVD_GDB_SCAN_SHARED_LIBRARIES (to a comma-separated string), it's possible to
- # specify just a few libraries to be loaded (not many are needed for the attach,
- # but it can be tricky to pre-specify for all Linux versions as this may change
- # across different versions).
- #
- # See: https://github.com/microsoft/debugpy/issues/762#issuecomment-947103844
- # for a comment that explains the basic steps on how to discover what should be available
- # in each case (mostly trying different versions based on the output of gdb).
- #
- # The upside is that for cases when too many libraries are loaded the attach could be slower
- # and just specifying the one that is actually needed for the attach can make it much faster.
- #
- # The downside is that it may be dependent on the Linux version being attached to (which is the
- # reason why this is no longer done by default -- see: https://github.com/microsoft/debugpy/issues/882).
- gdb_load_shared_libraries = os.environ.get('PYDEVD_GDB_SCAN_SHARED_LIBRARIES', '').strip()
- if gdb_load_shared_libraries:
- print('PYDEVD_GDB_SCAN_SHARED_LIBRARIES set: %s.' % (gdb_load_shared_libraries,))
- cmd.extend(["--init-eval-command='set auto-solib-add off'"]) # Don't scan all libraries.
-
- for lib in gdb_load_shared_libraries.split(','):
- lib = lib.strip()
- cmd.extend(["--eval-command='sharedlibrary %s'" % (lib,)]) # Scan the specified library
- else:
- print('PYDEVD_GDB_SCAN_SHARED_LIBRARIES not set (scanning all libraries for needed symbols).')
-
- cmd.extend(["--eval-command='set scheduler-locking off'"]) # If on we'll deadlock.
-
- # Leave auto by default (it should do the right thing as we're attaching to a process in the
- # current host).
- cmd.extend(["--eval-command='set architecture auto'"])
-
- cmd.extend([
- "--eval-command='call (void*)dlopen(\"%s\", 2)'" % target_dll,
- "--eval-command='sharedlibrary %s'" % target_dll_name,
- "--eval-command='call (int)DoAttach(%s, \"%s\", %s)'" % (
- is_debug, python_code, show_debug_info)
- ])
-
- # print ' '.join(cmd)
-
- env = os.environ.copy()
- # Remove the PYTHONPATH (if gdb has a builtin Python it could fail if we
- # have the PYTHONPATH for a different python version or some forced encoding).
- env.pop('PYTHONIOENCODING', None)
- env.pop('PYTHONPATH', None)
- print('Running: %s' % (' '.join(cmd)))
- subprocess.check_call(' '.join(cmd), shell=True, env=env)
-
-
-def find_helper_script(filedir, script_name):
- target_filename = os.path.join(filedir, 'linux_and_mac', script_name)
- target_filename = os.path.normpath(target_filename)
- if not os.path.exists(target_filename):
- raise RuntimeError('Could not find helper script: %s' % target_filename)
-
- return target_filename
-
-
-def run_python_code_mac(pid, python_code, connect_debugger_tracing=False, show_debug_info=0):
- assert '\'' not in python_code, 'Having a single quote messes with our command.'
-
- target_dll = get_target_filename()
- if not target_dll:
- raise RuntimeError('Could not find .dylib for attach to process.')
-
- libdir = os.path.dirname(__file__)
- lldb_prepare_file = find_helper_script(libdir, 'lldb_prepare.py')
- # Note: we currently don't support debug builds
-
- is_debug = 0
- # Note that the space in the beginning of each line in the multi-line is important!
- cmd = [
- 'lldb',
- '--no-lldbinit', # Do not automatically parse any '.lldbinit' files.
- # '--attach-pid',
- # str(pid),
- # '--arch',
- # arch,
- '--script-language',
- 'Python'
- # '--batch-silent',
- ]
-
- cmd.extend([
- "-o 'process attach --pid %d'" % pid,
- "-o 'command script import \"%s\"'" % (lldb_prepare_file,),
- "-o 'load_lib_and_attach \"%s\" %s \"%s\" %s'" % (target_dll,
- is_debug, python_code, show_debug_info),
- ])
-
- cmd.extend([
- "-o 'process detach'",
- "-o 'script import os; os._exit(1)'",
- ])
-
- # print ' '.join(cmd)
-
- env = os.environ.copy()
- # Remove the PYTHONPATH (if lldb has a builtin Python it could fail if we
- # have the PYTHONPATH for a different python version or some forced encoding).
- env.pop('PYTHONIOENCODING', None)
- env.pop('PYTHONPATH', None)
- print('Running: %s' % (' '.join(cmd)))
- subprocess.check_call(' '.join(cmd), shell=True, env=env)
-
-
-if IS_WINDOWS:
- run_python_code = run_python_code_windows
-elif IS_MAC:
- run_python_code = run_python_code_mac
-elif IS_LINUX:
- run_python_code = run_python_code_linux
-else:
-
- def run_python_code(*args, **kwargs):
- print('Unable to attach to process in platform: %s', sys.platform)
-
-
-def test():
- print('Running with: %s' % (sys.executable,))
- code = '''
-import os, time, sys
-print(os.getpid())
-#from threading import Thread
-#Thread(target=str).start()
-if __name__ == '__main__':
- while True:
- time.sleep(.5)
- sys.stdout.write('.\\n')
- sys.stdout.flush()
-'''
-
- p = subprocess.Popen([sys.executable, '-u', '-c', code])
- try:
- code = 'print("It worked!")\n'
-
- # Real code will be something as:
- # code = '''import sys;sys.path.append(r'X:\winappdbg-code\examples'); import imported;'''
- run_python_code(p.pid, python_code=code)
- print('\nRun a 2nd time...\n')
- run_python_code(p.pid, python_code=code)
-
- time.sleep(3)
- finally:
- p.kill()
-
-
-def main(args):
- # Otherwise, assume the first parameter is the pid and anything else is code to be executed
- # in the target process.
- pid = int(args[0])
- del args[0]
- python_code = ';'.join(args)
-
- # Note: on Linux the python code may not have a single quote char: '
- run_python_code(pid, python_code)
-
-
-if __name__ == '__main__':
- args = sys.argv[1:]
- if not args:
- print('Expected pid and Python code to execute in target process.')
- else:
- if '--test' == args[0]:
- test()
- else:
- main(args)
-
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/requests/certs.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/requests/certs.py
deleted file mode 100644
index 38696a1fb3419dd810004d5aec9654e5224042ed..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/requests/certs.py
+++ /dev/null
@@ -1,24 +0,0 @@
-#!/usr/bin/env python
-
-"""
-requests.certs
-~~~~~~~~~~~~~~
-
-This module returns the preferred default CA certificate bundle. There is
-only one — the one from the certifi package.
-
-If you are packaging Requests, e.g., for a Linux distribution or a managed
-environment, you can change the definition of where() to return a separately
-packaged CA bundle.
-"""
-
-import os
-
-if "_PIP_STANDALONE_CERT" not in os.environ:
- from pip._vendor.certifi import where
-else:
- def where():
- return os.environ["_PIP_STANDALONE_CERT"]
-
-if __name__ == "__main__":
- print(where())
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/live.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/live.py
deleted file mode 100644
index 3ebbbc4ccbe47043eb62f8dd770f079745d3b743..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/live.py
+++ /dev/null
@@ -1,375 +0,0 @@
-import sys
-from threading import Event, RLock, Thread
-from types import TracebackType
-from typing import IO, Any, Callable, List, Optional, TextIO, Type, cast
-
-from . import get_console
-from .console import Console, ConsoleRenderable, RenderableType, RenderHook
-from .control import Control
-from .file_proxy import FileProxy
-from .jupyter import JupyterMixin
-from .live_render import LiveRender, VerticalOverflowMethod
-from .screen import Screen
-from .text import Text
-
-
-class _RefreshThread(Thread):
- """A thread that calls refresh() at regular intervals."""
-
- def __init__(self, live: "Live", refresh_per_second: float) -> None:
- self.live = live
- self.refresh_per_second = refresh_per_second
- self.done = Event()
- super().__init__(daemon=True)
-
- def stop(self) -> None:
- self.done.set()
-
- def run(self) -> None:
- while not self.done.wait(1 / self.refresh_per_second):
- with self.live._lock:
- if not self.done.is_set():
- self.live.refresh()
-
-
-class Live(JupyterMixin, RenderHook):
- """Renders an auto-updating live display of any given renderable.
-
- Args:
- renderable (RenderableType, optional): The renderable to live display. Defaults to displaying nothing.
- console (Console, optional): Optional Console instance. Default will an internal Console instance writing to stdout.
- screen (bool, optional): Enable alternate screen mode. Defaults to False.
- auto_refresh (bool, optional): Enable auto refresh. If disabled, you will need to call `refresh()` or `update()` with refresh flag. Defaults to True
- refresh_per_second (float, optional): Number of times per second to refresh the live display. Defaults to 4.
- transient (bool, optional): Clear the renderable on exit (has no effect when screen=True). Defaults to False.
- redirect_stdout (bool, optional): Enable redirection of stdout, so ``print`` may be used. Defaults to True.
- redirect_stderr (bool, optional): Enable redirection of stderr. Defaults to True.
- vertical_overflow (VerticalOverflowMethod, optional): How to handle renderable when it is too tall for the console. Defaults to "ellipsis".
- get_renderable (Callable[[], RenderableType], optional): Optional callable to get renderable. Defaults to None.
- """
-
- def __init__(
- self,
- renderable: Optional[RenderableType] = None,
- *,
- console: Optional[Console] = None,
- screen: bool = False,
- auto_refresh: bool = True,
- refresh_per_second: float = 4,
- transient: bool = False,
- redirect_stdout: bool = True,
- redirect_stderr: bool = True,
- vertical_overflow: VerticalOverflowMethod = "ellipsis",
- get_renderable: Optional[Callable[[], RenderableType]] = None,
- ) -> None:
- assert refresh_per_second > 0, "refresh_per_second must be > 0"
- self._renderable = renderable
- self.console = console if console is not None else get_console()
- self._screen = screen
- self._alt_screen = False
-
- self._redirect_stdout = redirect_stdout
- self._redirect_stderr = redirect_stderr
- self._restore_stdout: Optional[IO[str]] = None
- self._restore_stderr: Optional[IO[str]] = None
-
- self._lock = RLock()
- self.ipy_widget: Optional[Any] = None
- self.auto_refresh = auto_refresh
- self._started: bool = False
- self.transient = True if screen else transient
-
- self._refresh_thread: Optional[_RefreshThread] = None
- self.refresh_per_second = refresh_per_second
-
- self.vertical_overflow = vertical_overflow
- self._get_renderable = get_renderable
- self._live_render = LiveRender(
- self.get_renderable(), vertical_overflow=vertical_overflow
- )
-
- @property
- def is_started(self) -> bool:
- """Check if live display has been started."""
- return self._started
-
- def get_renderable(self) -> RenderableType:
- renderable = (
- self._get_renderable()
- if self._get_renderable is not None
- else self._renderable
- )
- return renderable or ""
-
- def start(self, refresh: bool = False) -> None:
- """Start live rendering display.
-
- Args:
- refresh (bool, optional): Also refresh. Defaults to False.
- """
- with self._lock:
- if self._started:
- return
- self.console.set_live(self)
- self._started = True
- if self._screen:
- self._alt_screen = self.console.set_alt_screen(True)
- self.console.show_cursor(False)
- self._enable_redirect_io()
- self.console.push_render_hook(self)
- if refresh:
- try:
- self.refresh()
- except Exception:
- # If refresh fails, we want to stop the redirection of sys.stderr,
- # so the error stacktrace is properly displayed in the terminal.
- # (or, if the code that calls Rich captures the exception and wants to display something,
- # let this be displayed in the terminal).
- self.stop()
- raise
- if self.auto_refresh:
- self._refresh_thread = _RefreshThread(self, self.refresh_per_second)
- self._refresh_thread.start()
-
- def stop(self) -> None:
- """Stop live rendering display."""
- with self._lock:
- if not self._started:
- return
- self.console.clear_live()
- self._started = False
-
- if self.auto_refresh and self._refresh_thread is not None:
- self._refresh_thread.stop()
- self._refresh_thread = None
- # allow it to fully render on the last even if overflow
- self.vertical_overflow = "visible"
- with self.console:
- try:
- if not self._alt_screen and not self.console.is_jupyter:
- self.refresh()
- finally:
- self._disable_redirect_io()
- self.console.pop_render_hook()
- if not self._alt_screen and self.console.is_terminal:
- self.console.line()
- self.console.show_cursor(True)
- if self._alt_screen:
- self.console.set_alt_screen(False)
-
- if self.transient and not self._alt_screen:
- self.console.control(self._live_render.restore_cursor())
- if self.ipy_widget is not None and self.transient:
- self.ipy_widget.close() # pragma: no cover
-
- def __enter__(self) -> "Live":
- self.start(refresh=self._renderable is not None)
- return self
-
- def __exit__(
- self,
- exc_type: Optional[Type[BaseException]],
- exc_val: Optional[BaseException],
- exc_tb: Optional[TracebackType],
- ) -> None:
- self.stop()
-
- def _enable_redirect_io(self) -> None:
- """Enable redirecting of stdout / stderr."""
- if self.console.is_terminal or self.console.is_jupyter:
- if self._redirect_stdout and not isinstance(sys.stdout, FileProxy):
- self._restore_stdout = sys.stdout
- sys.stdout = cast("TextIO", FileProxy(self.console, sys.stdout))
- if self._redirect_stderr and not isinstance(sys.stderr, FileProxy):
- self._restore_stderr = sys.stderr
- sys.stderr = cast("TextIO", FileProxy(self.console, sys.stderr))
-
- def _disable_redirect_io(self) -> None:
- """Disable redirecting of stdout / stderr."""
- if self._restore_stdout:
- sys.stdout = cast("TextIO", self._restore_stdout)
- self._restore_stdout = None
- if self._restore_stderr:
- sys.stderr = cast("TextIO", self._restore_stderr)
- self._restore_stderr = None
-
- @property
- def renderable(self) -> RenderableType:
- """Get the renderable that is being displayed
-
- Returns:
- RenderableType: Displayed renderable.
- """
- renderable = self.get_renderable()
- return Screen(renderable) if self._alt_screen else renderable
-
- def update(self, renderable: RenderableType, *, refresh: bool = False) -> None:
- """Update the renderable that is being displayed
-
- Args:
- renderable (RenderableType): New renderable to use.
- refresh (bool, optional): Refresh the display. Defaults to False.
- """
- if isinstance(renderable, str):
- renderable = self.console.render_str(renderable)
- with self._lock:
- self._renderable = renderable
- if refresh:
- self.refresh()
-
- def refresh(self) -> None:
- """Update the display of the Live Render."""
- with self._lock:
- self._live_render.set_renderable(self.renderable)
- if self.console.is_jupyter: # pragma: no cover
- try:
- from IPython.display import display
- from ipywidgets import Output
- except ImportError:
- import warnings
-
- warnings.warn('install "ipywidgets" for Jupyter support')
- else:
- if self.ipy_widget is None:
- self.ipy_widget = Output()
- display(self.ipy_widget)
-
- with self.ipy_widget:
- self.ipy_widget.clear_output(wait=True)
- self.console.print(self._live_render.renderable)
- elif self.console.is_terminal and not self.console.is_dumb_terminal:
- with self.console:
- self.console.print(Control())
- elif (
- not self._started and not self.transient
- ): # if it is finished allow files or dumb-terminals to see final result
- with self.console:
- self.console.print(Control())
-
- def process_renderables(
- self, renderables: List[ConsoleRenderable]
- ) -> List[ConsoleRenderable]:
- """Process renderables to restore cursor and display progress."""
- self._live_render.vertical_overflow = self.vertical_overflow
- if self.console.is_interactive:
- # lock needs acquiring as user can modify live_render renderable at any time unlike in Progress.
- with self._lock:
- reset = (
- Control.home()
- if self._alt_screen
- else self._live_render.position_cursor()
- )
- renderables = [reset, *renderables, self._live_render]
- elif (
- not self._started and not self.transient
- ): # if it is finished render the final output for files or dumb_terminals
- renderables = [*renderables, self._live_render]
-
- return renderables
-
-
-if __name__ == "__main__": # pragma: no cover
- import random
- import time
- from itertools import cycle
- from typing import Dict, List, Tuple
-
- from .align import Align
- from .console import Console
- from .live import Live as Live
- from .panel import Panel
- from .rule import Rule
- from .syntax import Syntax
- from .table import Table
-
- console = Console()
-
- syntax = Syntax(
- '''def loop_last(values: Iterable[T]) -> Iterable[Tuple[bool, T]]:
- """Iterate and generate a tuple with a flag for last value."""
- iter_values = iter(values)
- try:
- previous_value = next(iter_values)
- except StopIteration:
- return
- for value in iter_values:
- yield False, previous_value
- previous_value = value
- yield True, previous_value''',
- "python",
- line_numbers=True,
- )
-
- table = Table("foo", "bar", "baz")
- table.add_row("1", "2", "3")
-
- progress_renderables = [
- "You can make the terminal shorter and taller to see the live table hide"
- "Text may be printed while the progress bars are rendering.",
- Panel("In fact, [i]any[/i] renderable will work"),
- "Such as [magenta]tables[/]...",
- table,
- "Pretty printed structures...",
- {"type": "example", "text": "Pretty printed"},
- "Syntax...",
- syntax,
- Rule("Give it a try!"),
- ]
-
- examples = cycle(progress_renderables)
-
- exchanges = [
- "SGD",
- "MYR",
- "EUR",
- "USD",
- "AUD",
- "JPY",
- "CNH",
- "HKD",
- "CAD",
- "INR",
- "DKK",
- "GBP",
- "RUB",
- "NZD",
- "MXN",
- "IDR",
- "TWD",
- "THB",
- "VND",
- ]
- with Live(console=console) as live_table:
- exchange_rate_dict: Dict[Tuple[str, str], float] = {}
-
- for index in range(100):
- select_exchange = exchanges[index % len(exchanges)]
-
- for exchange in exchanges:
- if exchange == select_exchange:
- continue
- time.sleep(0.4)
- if random.randint(0, 10) < 1:
- console.log(next(examples))
- exchange_rate_dict[(select_exchange, exchange)] = 200 / (
- (random.random() * 320) + 1
- )
- if len(exchange_rate_dict) > len(exchanges) - 1:
- exchange_rate_dict.pop(list(exchange_rate_dict.keys())[0])
- table = Table(title="Exchange Rates")
-
- table.add_column("Source Currency")
- table.add_column("Destination Currency")
- table.add_column("Exchange Rate")
-
- for ((source, dest), exchange_rate) in exchange_rate_dict.items():
- table.add_row(
- source,
- dest,
- Text(
- f"{exchange_rate:.4f}",
- style="red" if exchange_rate < 1.0 else "green",
- ),
- )
-
- live_table.update(Align.center(table))
diff --git a/spaces/Terminus0501/vits-uma-genshin-honkai/Docker/Dockerfile b/spaces/Terminus0501/vits-uma-genshin-honkai/Docker/Dockerfile
deleted file mode 100644
index 4d39cdf02a2ec151686cc1d61234bf723068fed8..0000000000000000000000000000000000000000
--- a/spaces/Terminus0501/vits-uma-genshin-honkai/Docker/Dockerfile
+++ /dev/null
@@ -1,12 +0,0 @@
-FROM python:3.9-bullseye
-VOLUME ["/app"]
-WORKDIR /app
-# Set apt to Chinese mirror
-RUN sed -i 's/deb.debian.org/mirrors.ustc.edu.cn/g' /etc/apt/sources.list
-RUN apt-get update && apt-get -y install cmake git
-RUN git clone https://huggingface.co/spaces/ikechan8370/vits-uma-genshin-honkai
-WORKDIR /app/vits-uma-genshin-honkai
-RUN sed -i "s/\.launch()/\.launch(server_name=\"0.0.0.0\")/" /app/vits-uma-genshin-honkai/app.py
-ADD vits.sh /app/vits.sh
-EXPOSE 7860
-ENTRYPOINT [ "/app/vits.sh" ]
\ No newline at end of file
diff --git a/spaces/ThirdEyeData/Object-Detection-Using-FRCNN/README.md b/spaces/ThirdEyeData/Object-Detection-Using-FRCNN/README.md
deleted file mode 100644
index 30d694c35bc8feedd0c4a32d213217cea8d0dc90..0000000000000000000000000000000000000000
--- a/spaces/ThirdEyeData/Object-Detection-Using-FRCNN/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Object Detection Using FRCNN
-emoji: ⚡
-colorFrom: red
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.17.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Thunderstone/trial/Dockerfile b/spaces/Thunderstone/trial/Dockerfile
deleted file mode 100644
index 0d88044a66e9964eae9bf981ae4fe9b8b62476d6..0000000000000000000000000000000000000000
--- a/spaces/Thunderstone/trial/Dockerfile
+++ /dev/null
@@ -1,11 +0,0 @@
-FROM node:18-bullseye-slim
-RUN apt-get update && \
- apt-get install -y git
-RUN git clone https://gitgud.io/thunderstone/reason.git /app
-WORKDIR /app
-RUN npm install
-COPY Dockerfile greeting.md* .env* ./
-RUN npm run build
-EXPOSE 7860
-ENV NODE_ENV=production
-CMD [ "npm", "start" ]
diff --git a/spaces/Vicent3/ocr-wrapper/README.md b/spaces/Vicent3/ocr-wrapper/README.md
deleted file mode 100644
index 6db91191adcd218eeddd04c804ea517e21b9e282..0000000000000000000000000000000000000000
--- a/spaces/Vicent3/ocr-wrapper/README.md
+++ /dev/null
@@ -1,9 +0,0 @@
----
-title: OCR Wrapper
-emoji: 🦀
-colorFrom: red
-colorTo: gray
-sdk: static
-pinned: true
-license: agpl-3.0
----
\ No newline at end of file
diff --git a/spaces/Vision-CAIR/minigpt4/minigpt4/datasets/datasets/caption_datasets.py b/spaces/Vision-CAIR/minigpt4/minigpt4/datasets/datasets/caption_datasets.py
deleted file mode 100644
index 8c8fb2014794a2800e5bea480ba3ecd353512915..0000000000000000000000000000000000000000
--- a/spaces/Vision-CAIR/minigpt4/minigpt4/datasets/datasets/caption_datasets.py
+++ /dev/null
@@ -1,85 +0,0 @@
-"""
- Copyright (c) 2022, salesforce.com, inc.
- All rights reserved.
- SPDX-License-Identifier: BSD-3-Clause
- For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
-"""
-
-import os
-from collections import OrderedDict
-
-from minigpt4.datasets.datasets.base_dataset import BaseDataset
-from PIL import Image
-
-
-class __DisplMixin:
- def displ_item(self, index):
- sample, ann = self.__getitem__(index), self.annotation[index]
-
- return OrderedDict(
- {
- "file": ann["image"],
- "caption": ann["caption"],
- "image": sample["image"],
- }
- )
-
-
-class CaptionDataset(BaseDataset, __DisplMixin):
- def __init__(self, vis_processor, text_processor, vis_root, ann_paths):
- """
- vis_root (string): Root directory of images (e.g. coco/images/)
- ann_root (string): directory to store the annotation file
- """
- super().__init__(vis_processor, text_processor, vis_root, ann_paths)
-
- self.img_ids = {}
- n = 0
- for ann in self.annotation:
- img_id = ann["image_id"]
- if img_id not in self.img_ids.keys():
- self.img_ids[img_id] = n
- n += 1
-
- def __getitem__(self, index):
-
- # TODO this assumes image input, not general enough
- ann = self.annotation[index]
-
- img_file = '{:0>12}.jpg'.format(ann["image_id"])
- image_path = os.path.join(self.vis_root, img_file)
- image = Image.open(image_path).convert("RGB")
-
- image = self.vis_processor(image)
- caption = self.text_processor(ann["caption"])
-
- return {
- "image": image,
- "text_input": caption,
- "image_id": self.img_ids[ann["image_id"]],
- }
-
-
-class CaptionEvalDataset(BaseDataset, __DisplMixin):
- def __init__(self, vis_processor, text_processor, vis_root, ann_paths):
- """
- vis_root (string): Root directory of images (e.g. coco/images/)
- ann_root (string): directory to store the annotation file
- split (string): val or test
- """
- super().__init__(vis_processor, text_processor, vis_root, ann_paths)
-
- def __getitem__(self, index):
-
- ann = self.annotation[index]
-
- image_path = os.path.join(self.vis_root, ann["image"])
- image = Image.open(image_path).convert("RGB")
-
- image = self.vis_processor(image)
-
- return {
- "image": image,
- "image_id": ann["image_id"],
- "instance_id": ann["instance_id"],
- }
diff --git a/spaces/Wanlau/sovits-4.0_datealive/vdecoder/hifigan/nvSTFT.py b/spaces/Wanlau/sovits-4.0_datealive/vdecoder/hifigan/nvSTFT.py
deleted file mode 100644
index 88597d62a505715091f9ba62d38bf0a85a31b95a..0000000000000000000000000000000000000000
--- a/spaces/Wanlau/sovits-4.0_datealive/vdecoder/hifigan/nvSTFT.py
+++ /dev/null
@@ -1,111 +0,0 @@
-import math
-import os
-os.environ["LRU_CACHE_CAPACITY"] = "3"
-import random
-import torch
-import torch.utils.data
-import numpy as np
-import librosa
-from librosa.util import normalize
-from librosa.filters import mel as librosa_mel_fn
-from scipy.io.wavfile import read
-import soundfile as sf
-
-def load_wav_to_torch(full_path, target_sr=None, return_empty_on_exception=False):
- sampling_rate = None
- try:
- data, sampling_rate = sf.read(full_path, always_2d=True)# than soundfile.
- except Exception as ex:
- print(f"'{full_path}' failed to load.\nException:")
- print(ex)
- if return_empty_on_exception:
- return [], sampling_rate or target_sr or 32000
- else:
- raise Exception(ex)
-
- if len(data.shape) > 1:
- data = data[:, 0]
- assert len(data) > 2# check duration of audio file is > 2 samples (because otherwise the slice operation was on the wrong dimension)
-
- if np.issubdtype(data.dtype, np.integer): # if audio data is type int
- max_mag = -np.iinfo(data.dtype).min # maximum magnitude = min possible value of intXX
- else: # if audio data is type fp32
- max_mag = max(np.amax(data), -np.amin(data))
- max_mag = (2**31)+1 if max_mag > (2**15) else ((2**15)+1 if max_mag > 1.01 else 1.0) # data should be either 16-bit INT, 32-bit INT or [-1 to 1] float32
-
- data = torch.FloatTensor(data.astype(np.float32))/max_mag
-
- if (torch.isinf(data) | torch.isnan(data)).any() and return_empty_on_exception:# resample will crash with inf/NaN inputs. return_empty_on_exception will return empty arr instead of except
- return [], sampling_rate or target_sr or 32000
- if target_sr is not None and sampling_rate != target_sr:
- data = torch.from_numpy(librosa.core.resample(data.numpy(), orig_sr=sampling_rate, target_sr=target_sr))
- sampling_rate = target_sr
-
- return data, sampling_rate
-
-def dynamic_range_compression(x, C=1, clip_val=1e-5):
- return np.log(np.clip(x, a_min=clip_val, a_max=None) * C)
-
-def dynamic_range_decompression(x, C=1):
- return np.exp(x) / C
-
-def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
- return torch.log(torch.clamp(x, min=clip_val) * C)
-
-def dynamic_range_decompression_torch(x, C=1):
- return torch.exp(x) / C
-
-class STFT():
- def __init__(self, sr=22050, n_mels=80, n_fft=1024, win_size=1024, hop_length=256, fmin=20, fmax=11025, clip_val=1e-5):
- self.target_sr = sr
-
- self.n_mels = n_mels
- self.n_fft = n_fft
- self.win_size = win_size
- self.hop_length = hop_length
- self.fmin = fmin
- self.fmax = fmax
- self.clip_val = clip_val
- self.mel_basis = {}
- self.hann_window = {}
-
- def get_mel(self, y, center=False):
- sampling_rate = self.target_sr
- n_mels = self.n_mels
- n_fft = self.n_fft
- win_size = self.win_size
- hop_length = self.hop_length
- fmin = self.fmin
- fmax = self.fmax
- clip_val = self.clip_val
-
- if torch.min(y) < -1.:
- print('min value is ', torch.min(y))
- if torch.max(y) > 1.:
- print('max value is ', torch.max(y))
-
- if fmax not in self.mel_basis:
- mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax)
- self.mel_basis[str(fmax)+'_'+str(y.device)] = torch.from_numpy(mel).float().to(y.device)
- self.hann_window[str(y.device)] = torch.hann_window(self.win_size).to(y.device)
-
- y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_length)/2), int((n_fft-hop_length)/2)), mode='reflect')
- y = y.squeeze(1)
-
- spec = torch.stft(y, n_fft, hop_length=hop_length, win_length=win_size, window=self.hann_window[str(y.device)],
- center=center, pad_mode='reflect', normalized=False, onesided=True)
- # print(111,spec)
- spec = torch.sqrt(spec.pow(2).sum(-1)+(1e-9))
- # print(222,spec)
- spec = torch.matmul(self.mel_basis[str(fmax)+'_'+str(y.device)], spec)
- # print(333,spec)
- spec = dynamic_range_compression_torch(spec, clip_val=clip_val)
- # print(444,spec)
- return spec
-
- def __call__(self, audiopath):
- audio, sr = load_wav_to_torch(audiopath, target_sr=self.target_sr)
- spect = self.get_mel(audio.unsqueeze(0)).squeeze(0)
- return spect
-
-stft = STFT()
diff --git a/spaces/XAI/CHM-Corr/model/base/backbone.py b/spaces/XAI/CHM-Corr/model/base/backbone.py
deleted file mode 100644
index c20aaba40486eef005410318d511501b63622496..0000000000000000000000000000000000000000
--- a/spaces/XAI/CHM-Corr/model/base/backbone.py
+++ /dev/null
@@ -1,136 +0,0 @@
-r""" ResNet-101 backbone network """
-
-import torch.utils.model_zoo as model_zoo
-import torch.nn as nn
-import torch
-
-
-__all__ = ['Backbone', 'resnet101']
-
-
-model_urls = {
- 'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
- 'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth',
- 'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pth',
- 'resnet101': 'https://download.pytorch.org/models/resnet101-5d3b4d8f.pth',
- 'resnet152': 'https://download.pytorch.org/models/resnet152-b121ed2d.pth',
-}
-
-
-def conv3x3(in_planes, out_planes, stride=1):
- r""" 3x3 convolution with padding """
- return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
- padding=1, groups=2, bias=False)
-
-
-def conv1x1(in_planes, out_planes, stride=1):
- r""" 1x1 convolution """
- return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, groups=2, bias=False)
-
-
-class Bottleneck(nn.Module):
- expansion = 4
-
- def __init__(self, inplanes, planes, stride=1, downsample=None):
- super(Bottleneck, self).__init__()
- self.conv1 = conv1x1(inplanes, planes)
- self.bn1 = nn.BatchNorm2d(planes)
- self.conv2 = conv3x3(planes, planes, stride)
- self.bn2 = nn.BatchNorm2d(planes)
- self.conv3 = conv1x1(planes, planes * self.expansion)
- self.bn3 = nn.BatchNorm2d(planes * self.expansion)
- self.relu = nn.ReLU(inplace=True)
- self.downsample = downsample
- self.stride = stride
-
- def forward(self, x):
- identity = x
-
- out = self.conv1(x)
- out = self.bn1(out)
- out = self.relu(out)
-
- out = self.conv2(out)
- out = self.bn2(out)
- out = self.relu(out)
-
- out = self.conv3(out)
- out = self.bn3(out)
-
- if self.downsample is not None:
- identity = self.downsample(x)
-
- out += identity
- out = self.relu(out)
-
- return out
-
-
-class Backbone(nn.Module):
- def __init__(self, block, layers, zero_init_residual=False):
- super(Backbone, self).__init__()
-
- self.inplanes = 128
- self.conv1 = nn.Conv2d(6, 128, kernel_size=7, stride=2, padding=3, groups=2,
- bias=False)
- self.bn1 = nn.BatchNorm2d(128)
- self.relu = nn.ReLU(inplace=True)
- self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
- self.layer1 = self._make_layer(block, 128, layers[0])
- self.layer2 = self._make_layer(block, 256, layers[1], stride=2)
- self.layer3 = self._make_layer(block, 512, layers[2], stride=2)
- self.layer4 = self._make_layer(block, 1024, layers[3], stride=2)
- self.avgpool = nn.AdaptiveAvgPool2d((1, 1))
- self.fc = nn.Linear(512 * block.expansion, 1000)
-
- for m in self.modules():
- if isinstance(m, nn.Conv2d):
- nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
- elif isinstance(m, nn.BatchNorm2d):
- nn.init.constant_(m.weight, 1)
- nn.init.constant_(m.bias, 0)
-
- # Zero-initialize the last BN in each residual branch,
- # so that the residual branch starts with zeros, and each residual block behaves like an identity.
- # This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677
- if zero_init_residual:
- for m in self.modules():
- if isinstance(m, Bottleneck):
- nn.init.constant_(m.bn3.weight, 0)
-
- def _make_layer(self, block, planes, blocks, stride=1):
- downsample = None
- if stride != 1 or self.inplanes != planes * block.expansion:
- downsample = nn.Sequential(
- conv1x1(self.inplanes, planes * block.expansion, stride),
- nn.BatchNorm2d(planes * block.expansion),
- )
-
- layers = []
- layers.append(block(self.inplanes, planes, stride, downsample))
- self.inplanes = planes * block.expansion
- for _ in range(1, blocks):
- layers.append(block(self.inplanes, planes))
-
- return nn.Sequential(*layers)
-
-
-def resnet101(pretrained=False, **kwargs):
- """Constructs a ResNet-101 model.
-
- Args:
- pretrained (bool): If True, returns a model pre-trained on ImageNet
- """
- model = Backbone(Bottleneck, [3, 4, 23, 3], **kwargs)
- if pretrained:
- weights = model_zoo.load_url(model_urls['resnet101'])
-
- for key in weights:
- if key.split('.')[0] == 'fc':
- weights[key] = weights[key].clone()
- continue
- weights[key] = torch.cat([weights[key].clone(), weights[key].clone()], dim=0)
-
- model.load_state_dict(weights)
- return model
-
diff --git a/spaces/Xenova/next-example-app/_next/static/chunks/main-1710cefc469e610b.js b/spaces/Xenova/next-example-app/_next/static/chunks/main-1710cefc469e610b.js
deleted file mode 100644
index 271b791ef6a7009941e67f46c68e1672aa0a309e..0000000000000000000000000000000000000000
--- a/spaces/Xenova/next-example-app/_next/static/chunks/main-1710cefc469e610b.js
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/attentions.py b/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/attentions.py
deleted file mode 100644
index 86bc73b5fe98cc7b443e9078553920346c996707..0000000000000000000000000000000000000000
--- a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/attentions.py
+++ /dev/null
@@ -1,300 +0,0 @@
-import math
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import commons
-from modules import LayerNorm
-
-
-class Encoder(nn.Module):
- def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., window_size=4, **kwargs):
- super().__init__()
- self.hidden_channels = hidden_channels
- self.filter_channels = filter_channels
- self.n_heads = n_heads
- self.n_layers = n_layers
- self.kernel_size = kernel_size
- self.p_dropout = p_dropout
- self.window_size = window_size
-
- self.drop = nn.Dropout(p_dropout)
- self.attn_layers = nn.ModuleList()
- self.norm_layers_1 = nn.ModuleList()
- self.ffn_layers = nn.ModuleList()
- self.norm_layers_2 = nn.ModuleList()
- for i in range(self.n_layers):
- self.attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, window_size=window_size))
- self.norm_layers_1.append(LayerNorm(hidden_channels))
- self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout))
- self.norm_layers_2.append(LayerNorm(hidden_channels))
-
- def forward(self, x, x_mask):
- attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
- x = x * x_mask
- for i in range(self.n_layers):
- y = self.attn_layers[i](x, x, attn_mask)
- y = self.drop(y)
- x = self.norm_layers_1[i](x + y)
-
- y = self.ffn_layers[i](x, x_mask)
- y = self.drop(y)
- x = self.norm_layers_2[i](x + y)
- x = x * x_mask
- return x
-
-
-class Decoder(nn.Module):
- def __init__(self, hidden_channels, filter_channels, n_heads, n_layers, kernel_size=1, p_dropout=0., proximal_bias=False, proximal_init=True, **kwargs):
- super().__init__()
- self.hidden_channels = hidden_channels
- self.filter_channels = filter_channels
- self.n_heads = n_heads
- self.n_layers = n_layers
- self.kernel_size = kernel_size
- self.p_dropout = p_dropout
- self.proximal_bias = proximal_bias
- self.proximal_init = proximal_init
-
- self.drop = nn.Dropout(p_dropout)
- self.self_attn_layers = nn.ModuleList()
- self.norm_layers_0 = nn.ModuleList()
- self.encdec_attn_layers = nn.ModuleList()
- self.norm_layers_1 = nn.ModuleList()
- self.ffn_layers = nn.ModuleList()
- self.norm_layers_2 = nn.ModuleList()
- for i in range(self.n_layers):
- self.self_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout, proximal_bias=proximal_bias, proximal_init=proximal_init))
- self.norm_layers_0.append(LayerNorm(hidden_channels))
- self.encdec_attn_layers.append(MultiHeadAttention(hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout))
- self.norm_layers_1.append(LayerNorm(hidden_channels))
- self.ffn_layers.append(FFN(hidden_channels, hidden_channels, filter_channels, kernel_size, p_dropout=p_dropout, causal=True))
- self.norm_layers_2.append(LayerNorm(hidden_channels))
-
- def forward(self, x, x_mask, h, h_mask):
- """
- x: decoder input
- h: encoder output
- """
- self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(device=x.device, dtype=x.dtype)
- encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
- x = x * x_mask
- for i in range(self.n_layers):
- y = self.self_attn_layers[i](x, x, self_attn_mask)
- y = self.drop(y)
- x = self.norm_layers_0[i](x + y)
-
- y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
- y = self.drop(y)
- x = self.norm_layers_1[i](x + y)
-
- y = self.ffn_layers[i](x, x_mask)
- y = self.drop(y)
- x = self.norm_layers_2[i](x + y)
- x = x * x_mask
- return x
-
-
-class MultiHeadAttention(nn.Module):
- def __init__(self, channels, out_channels, n_heads, p_dropout=0., window_size=None, heads_share=True, block_length=None, proximal_bias=False, proximal_init=False):
- super().__init__()
- assert channels % n_heads == 0
-
- self.channels = channels
- self.out_channels = out_channels
- self.n_heads = n_heads
- self.p_dropout = p_dropout
- self.window_size = window_size
- self.heads_share = heads_share
- self.block_length = block_length
- self.proximal_bias = proximal_bias
- self.proximal_init = proximal_init
- self.attn = None
-
- self.k_channels = channels // n_heads
- self.conv_q = nn.Conv1d(channels, channels, 1)
- self.conv_k = nn.Conv1d(channels, channels, 1)
- self.conv_v = nn.Conv1d(channels, channels, 1)
- self.conv_o = nn.Conv1d(channels, out_channels, 1)
- self.drop = nn.Dropout(p_dropout)
-
- if window_size is not None:
- n_heads_rel = 1 if heads_share else n_heads
- rel_stddev = self.k_channels**-0.5
- self.emb_rel_k = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
- self.emb_rel_v = nn.Parameter(torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels) * rel_stddev)
-
- nn.init.xavier_uniform_(self.conv_q.weight)
- nn.init.xavier_uniform_(self.conv_k.weight)
- nn.init.xavier_uniform_(self.conv_v.weight)
- if proximal_init:
- with torch.no_grad():
- self.conv_k.weight.copy_(self.conv_q.weight)
- self.conv_k.bias.copy_(self.conv_q.bias)
-
- def forward(self, x, c, attn_mask=None):
- q = self.conv_q(x)
- k = self.conv_k(c)
- v = self.conv_v(c)
-
- x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
- x = self.conv_o(x)
- return x
-
- def attention(self, query, key, value, mask=None):
- # reshape [b, d, t] -> [b, n_h, t, d_k]
- b, d, t_s, t_t = (*key.size(), query.size(2))
- query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
- key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
- value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
- scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
- if self.window_size is not None:
- assert t_s == t_t, "Relative attention is only available for self-attention."
- key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
- rel_logits = self._matmul_with_relative_keys(query /math.sqrt(self.k_channels), key_relative_embeddings)
- scores_local = self._relative_position_to_absolute_position(rel_logits)
- scores = scores + scores_local
- if self.proximal_bias:
- assert t_s == t_t, "Proximal bias is only available for self-attention."
- scores = scores + self._attention_bias_proximal(t_s).to(device=scores.device, dtype=scores.dtype)
- if mask is not None:
- scores = scores.masked_fill(mask == 0, -1e4)
- if self.block_length is not None:
- assert t_s == t_t, "Local attention is only available for self-attention."
- block_mask = torch.ones_like(scores).triu(-self.block_length).tril(self.block_length)
- scores = scores.masked_fill(block_mask == 0, -1e4)
- p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
- p_attn = self.drop(p_attn)
- output = torch.matmul(p_attn, value)
- if self.window_size is not None:
- relative_weights = self._absolute_position_to_relative_position(p_attn)
- value_relative_embeddings = self._get_relative_embeddings(self.emb_rel_v, t_s)
- output = output + self._matmul_with_relative_values(relative_weights, value_relative_embeddings)
- output = output.transpose(2, 3).contiguous().view(b, d, t_t) # [b, n_h, t_t, d_k] -> [b, d, t_t]
- return output, p_attn
-
- def _matmul_with_relative_values(self, x, y):
- """
- x: [b, h, l, m]
- y: [h or 1, m, d]
- ret: [b, h, l, d]
- """
- ret = torch.matmul(x, y.unsqueeze(0))
- return ret
-
- def _matmul_with_relative_keys(self, x, y):
- """
- x: [b, h, l, d]
- y: [h or 1, m, d]
- ret: [b, h, l, m]
- """
- ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
- return ret
-
- def _get_relative_embeddings(self, relative_embeddings, length):
- max_relative_position = 2 * self.window_size + 1
- # Pad first before slice to avoid using cond ops.
- pad_length = max(length - (self.window_size + 1), 0)
- slice_start_position = max((self.window_size + 1) - length, 0)
- slice_end_position = slice_start_position + 2 * length - 1
- if pad_length > 0:
- padded_relative_embeddings = F.pad(
- relative_embeddings,
- commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]))
- else:
- padded_relative_embeddings = relative_embeddings
- used_relative_embeddings = padded_relative_embeddings[:,slice_start_position:slice_end_position]
- return used_relative_embeddings
-
- def _relative_position_to_absolute_position(self, x):
- """
- x: [b, h, l, 2*l-1]
- ret: [b, h, l, l]
- """
- batch, heads, length, _ = x.size()
- # Concat columns of pad to shift from relative to absolute indexing.
- x = F.pad(x, commons.convert_pad_shape([[0,0],[0,0],[0,0],[0,1]]))
-
- # Concat extra elements so to add up to shape (len+1, 2*len-1).
- x_flat = x.view([batch, heads, length * 2 * length])
- x_flat = F.pad(x_flat, commons.convert_pad_shape([[0,0],[0,0],[0,length-1]]))
-
- # Reshape and slice out the padded elements.
- x_final = x_flat.view([batch, heads, length+1, 2*length-1])[:, :, :length, length-1:]
- return x_final
-
- def _absolute_position_to_relative_position(self, x):
- """
- x: [b, h, l, l]
- ret: [b, h, l, 2*l-1]
- """
- batch, heads, length, _ = x.size()
- # padd along column
- x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length-1]]))
- x_flat = x.view([batch, heads, length**2 + length*(length -1)])
- # add 0's in the beginning that will skew the elements after reshape
- x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
- x_final = x_flat.view([batch, heads, length, 2*length])[:,:,:,1:]
- return x_final
-
- def _attention_bias_proximal(self, length):
- """Bias for self-attention to encourage attention to close positions.
- Args:
- length: an integer scalar.
- Returns:
- a Tensor with shape [1, 1, length, length]
- """
- r = torch.arange(length, dtype=torch.float32)
- diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
- return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
- def __init__(self, in_channels, out_channels, filter_channels, kernel_size, p_dropout=0., activation=None, causal=False):
- super().__init__()
- self.in_channels = in_channels
- self.out_channels = out_channels
- self.filter_channels = filter_channels
- self.kernel_size = kernel_size
- self.p_dropout = p_dropout
- self.activation = activation
- self.causal = causal
-
- if causal:
- self.padding = self._causal_padding
- else:
- self.padding = self._same_padding
-
- self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
- self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
- self.drop = nn.Dropout(p_dropout)
-
- def forward(self, x, x_mask):
- x = self.conv_1(self.padding(x * x_mask))
- if self.activation == "gelu":
- x = x * torch.sigmoid(1.702 * x)
- else:
- x = torch.relu(x)
- x = self.drop(x)
- x = self.conv_2(self.padding(x * x_mask))
- return x * x_mask
-
- def _causal_padding(self, x):
- if self.kernel_size == 1:
- return x
- pad_l = self.kernel_size - 1
- pad_r = 0
- padding = [[0, 0], [0, 0], [pad_l, pad_r]]
- x = F.pad(x, commons.convert_pad_shape(padding))
- return x
-
- def _same_padding(self, x):
- if self.kernel_size == 1:
- return x
- pad_l = (self.kernel_size - 1) // 2
- pad_r = self.kernel_size // 2
- padding = [[0, 0], [0, 0], [pad_l, pad_r]]
- x = F.pad(x, commons.convert_pad_shape(padding))
- return x
diff --git a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/mel_processing.py b/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/mel_processing.py
deleted file mode 100644
index 3e252e76320522a8a4195a60665168f22769aec2..0000000000000000000000000000000000000000
--- a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/mel_processing.py
+++ /dev/null
@@ -1,101 +0,0 @@
-import torch
-import torch.utils.data
-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, return_complex=False)
-
- 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/XyBr0/test/app.py b/spaces/XyBr0/test/app.py
deleted file mode 100644
index 7b18653059afecad08d489b6709ac27619958254..0000000000000000000000000000000000000000
--- a/spaces/XyBr0/test/app.py
+++ /dev/null
@@ -1,18 +0,0 @@
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): return x[0].isupper()
-
-learn = load_learner('model.pkl')
-
-categories = ('Dog', 'Cat')
-
-def classify_image(img):
- pred,idx,probs = learn.predict(img)
- return dict(zip(categories, map(float,probs)))
-
-image = gr.inputs.Image(shape=(192, 192))
-label = gr.outputs.Label()
-
-intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)
-intf.launch(inline=False)
\ No newline at end of file
diff --git a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py b/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
deleted file mode 100644
index 09bdca54accfb51cd12afa1a103d2f88a909215b..0000000000000000000000000000000000000000
--- a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
+++ /dev/null
@@ -1,171 +0,0 @@
-import inspect
-from typing import Optional, Tuple, Union
-
-import numpy as np
-import torch
-import torch.utils.checkpoint
-
-import PIL
-
-from ...models import UNet2DModel, VQModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-from ...schedulers import (
- DDIMScheduler,
- DPMSolverMultistepScheduler,
- EulerAncestralDiscreteScheduler,
- EulerDiscreteScheduler,
- LMSDiscreteScheduler,
- PNDMScheduler,
-)
-from ...utils import PIL_INTERPOLATION, deprecate
-
-
-def preprocess(image):
- w, h = image.size
- w, h = map(lambda x: x - x % 32, (w, h)) # resize to integer multiple of 32
- image = image.resize((w, h), resample=PIL_INTERPOLATION["lanczos"])
- image = np.array(image).astype(np.float32) / 255.0
- image = image[None].transpose(0, 3, 1, 2)
- image = torch.from_numpy(image)
- return 2.0 * image - 1.0
-
-
-class LDMSuperResolutionPipeline(DiffusionPipeline):
- r"""
- A pipeline for image super-resolution using Latent
-
- This class inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
- library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
-
- Parameters:
- vqvae ([`VQModel`]):
- Vector-quantized (VQ) VAE Model to encode and decode images to and from latent representations.
- unet ([`UNet2DModel`]): U-Net architecture to denoise the encoded image.
- scheduler ([`SchedulerMixin`]):
- A scheduler to be used in combination with `unet` to denoise the encoded image latens. Can be one of
- [`DDIMScheduler`], [`LMSDiscreteScheduler`], [`EulerDiscreteScheduler`],
- [`EulerAncestralDiscreteScheduler`], [`DPMSolverMultistepScheduler`], or [`PNDMScheduler`].
- """
-
- def __init__(
- self,
- vqvae: VQModel,
- unet: UNet2DModel,
- scheduler: Union[
- DDIMScheduler,
- PNDMScheduler,
- LMSDiscreteScheduler,
- EulerDiscreteScheduler,
- EulerAncestralDiscreteScheduler,
- DPMSolverMultistepScheduler,
- ],
- ):
- super().__init__()
- self.register_modules(vqvae=vqvae, unet=unet, scheduler=scheduler)
-
- @torch.no_grad()
- def __call__(
- self,
- image: Union[torch.Tensor, PIL.Image.Image],
- batch_size: Optional[int] = 1,
- num_inference_steps: Optional[int] = 100,
- eta: Optional[float] = 0.0,
- generator: Optional[torch.Generator] = None,
- output_type: Optional[str] = "pil",
- return_dict: bool = True,
- **kwargs,
- ) -> Union[Tuple, ImagePipelineOutput]:
- r"""
- Args:
- image (`torch.Tensor` or `PIL.Image.Image`):
- `Image`, or tensor representing an image batch, that will be used as the starting point for the
- process.
- batch_size (`int`, *optional*, defaults to 1):
- Number of images to generate.
- num_inference_steps (`int`, *optional*, defaults to 100):
- The number of denoising steps. More denoising steps usually lead to a higher quality image at the
- expense of slower inference.
- eta (`float`, *optional*, defaults to 0.0):
- Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
- [`schedulers.DDIMScheduler`], will be ignored for others.
- generator (`torch.Generator`, *optional*):
- A [torch generator](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make generation
- deterministic.
- output_type (`str`, *optional*, defaults to `"pil"`):
- The output format of the generate image. Choose between
- [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
- return_dict (`bool`, *optional*):
- Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
-
- Returns:
- [`~pipeline_utils.ImagePipelineOutput`] or `tuple`: [`~pipelines.utils.ImagePipelineOutput`] if
- `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
- generated images.
- """
- message = "Please use `image` instead of `init_image`."
- init_image = deprecate("init_image", "0.12.0", message, take_from=kwargs)
- image = init_image or image
-
- if isinstance(image, PIL.Image.Image):
- batch_size = 1
- elif isinstance(image, torch.Tensor):
- batch_size = image.shape[0]
- else:
- raise ValueError(f"`image` has to be of type `PIL.Image.Image` or `torch.Tensor` but is {type(image)}")
-
- if isinstance(image, PIL.Image.Image):
- image = preprocess(image)
-
- height, width = image.shape[-2:]
-
- # in_channels should be 6: 3 for latents, 3 for low resolution image
- latents_shape = (batch_size, self.unet.in_channels // 2, height, width)
- latents_dtype = next(self.unet.parameters()).dtype
-
- if self.device.type == "mps":
- # randn does not work reproducibly on mps
- latents = torch.randn(latents_shape, generator=generator, device="cpu", dtype=latents_dtype)
- latents = latents.to(self.device)
- else:
- latents = torch.randn(latents_shape, generator=generator, device=self.device, dtype=latents_dtype)
-
- image = image.to(device=self.device, dtype=latents_dtype)
-
- # set timesteps and move to the correct device
- self.scheduler.set_timesteps(num_inference_steps, device=self.device)
- timesteps_tensor = self.scheduler.timesteps
-
- # scale the initial noise by the standard deviation required by the scheduler
- latents = latents * self.scheduler.init_noise_sigma
-
- # prepare extra kwargs for the scheduler step, since not all schedulers have the same signature.
- # eta (η) is only used with the DDIMScheduler, it will be ignored for other schedulers.
- # eta corresponds to η in DDIM paper: https://arxiv.org/abs/2010.02502
- # and should be between [0, 1]
- accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
- extra_kwargs = {}
- if accepts_eta:
- extra_kwargs["eta"] = eta
-
- for t in self.progress_bar(timesteps_tensor):
- # concat latents and low resolution image in the channel dimension.
- latents_input = torch.cat([latents, image], dim=1)
- latents_input = self.scheduler.scale_model_input(latents_input, t)
- # predict the noise residual
- noise_pred = self.unet(latents_input, t).sample
- # compute the previous noisy sample x_t -> x_t-1
- latents = self.scheduler.step(noise_pred, t, latents, **extra_kwargs).prev_sample
-
- # decode the image latents with the VQVAE
- image = self.vqvae.decode(latents).sample
- image = torch.clamp(image, -1.0, 1.0)
- image = image / 2 + 0.5
- image = image.cpu().permute(0, 2, 3, 1).numpy()
-
- if output_type == "pil":
- image = self.numpy_to_pil(image)
-
- if not return_dict:
- return (image,)
-
- return ImagePipelineOutput(images=image)
diff --git a/spaces/YuAnthony/Audio-Caption/tools/.ipynb_checkpoints/csv_functions-checkpoint.py b/spaces/YuAnthony/Audio-Caption/tools/.ipynb_checkpoints/csv_functions-checkpoint.py
deleted file mode 100644
index 68e31b697ed33b0415d92d2037e384118e33092e..0000000000000000000000000000000000000000
--- a/spaces/YuAnthony/Audio-Caption/tools/.ipynb_checkpoints/csv_functions-checkpoint.py
+++ /dev/null
@@ -1,32 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-from typing import Optional, List, Union
-from pathlib import Path
-from collections import OrderedDict
-
-import csv
-
-__author__ = 'Konstantinos Drossos -- Tampere University'
-__docformat__ = 'reStructuredText'
-__all__ = ['read_csv_file']
-
-
-def read_csv_file(file_name: str,
- base_dir: Optional[Union[str, Path]] = 'csv_files') \
- -> List[OrderedDict]:
- """Reads a CSV file.
-
- :param file_name: The full file name of the CSV.
- :type file_name: str
- :param base_dir: The root dir of the CSV files.
- :type base_dir: str|pathlib.Path
- :return: The contents of the CSV of the task.
- :rtype: list[collections.OrderedDict]
- """
- file_path = Path().joinpath(base_dir, file_name)
- with file_path.open(mode='r') as csv_file:
- csv_reader = csv.DictReader(csv_file)
- return [csv_line for csv_line in csv_reader]
-
-# EOF
diff --git a/spaces/abbylagar/multilingual_keyword_extractor/app.py b/spaces/abbylagar/multilingual_keyword_extractor/app.py
deleted file mode 100644
index 88f39ef57014735d8d29a6a5cf0351880be5a9c2..0000000000000000000000000000000000000000
--- a/spaces/abbylagar/multilingual_keyword_extractor/app.py
+++ /dev/null
@@ -1,33 +0,0 @@
-import gradio as gr
-import yake
-from yake.highlight import TextHighlighter
-import pandas as pd
-
-def yake_func(text,slider,slider2):
- kw_extractor = yake.KeywordExtractor(top=slider)
- keywords = kw_extractor.extract_keywords(text)
- text_highlight = TextHighlighter(max_ngram_size = slider2,highlight_pre = "", highlight_post= "")
- th=text_highlight.highlight(text, keywords)
- kw = pd.DataFrame(keywords)
- kw.rename(columns={0:'keyword',1:'score'},inplace =True)
- return kw,th
-
-ex1 ="Japan official says highly radioactive water is leaking from crippled nuclear plant into ocean Japan official says highly radioactive water is leaking from crippled nuclear plant into ocean (AP) TOKYO (AP) — Japan official says highly radioactive water is leaking from crippled nuclear plant into ocean."
-ex2 = "¿Cómo empezó la Guerra Civil Española?. El mismo año 1936 se celebraron elecciones generales en España, exactamente el 16 de febrero de 1936. A estas elecciones se presentaron muchos partidos políticos tanto de izquierdas como de derechas. El Frente Popular, la coalición de izquierdas que englobaba tanto al Partido Socialista Obrero Español como al Partido Comunista, Izquierda Republicana y otros tantos, consiguió la mayoría absoluta. Pero, ¿cómo comenzó exactamente la Guerra Civil Española? Tras la victoria del bando de izquierda continuaron una serie de acciones terroristas que pretendían movilizar a la masa contra el gobierno, en el caso de los atentados de los falangistas y grupos de derecha, y para responder a los primeros en el caso de los grupos de izquierdas. Solo en el mes de febrero ya se contabilizaban por centenares los fallecidos en este tipo de acciones contra la situación política, social y económica del país. En los meses sucesivos el panorama social y militar de España fue, de todo, menos tranquilo. Varios altos mandos militares planearon durante meses una posible sublevación frente al gobierno republicano que se haría efectiva el 17 de julio de 1936 y los días sucesivos. Pero, ¿qué hizo que los militares se alzaran justo ese día? El 16 de abril de 1936 uno de los hombres de José Castillo, un instructor de las milicias de la juventud socialista, asesinó a Andrés Sáenz de Heredia, primo del mismísimo José Antonio Primo de Rivera. Como represalia el 12 de julio fue asesinado el propio José Castillo. Este hecho desencadenó la venganza de la izquierda que terminó con la vida del diputado de Renovación Española, José Calvo Sotelo, al mismo día siguiente. Este asesinato del líder de la derecha terminó por decantar la balanza de los indecisos al golpe de estado (entre los que, según Paul Preston, se encontraba el propio Franco) a llevar a cabo una acción que conllevaría un conflicto bélico en nuestro país. Así comenzaría la Guerra Civil Española que duraría hasta el 1 de abril de 1939 con la victoria del bando nacional con el general Francisco Franco a la cabeza. Él mismo tomaría las riendas de España bajo un régimen dictatorial hasta su muerte el 20 de noviembre de 1975."
-
-
-title = "Multi-lingual Keyword Extractor"
-description = "Gradio demo of YAKE!, a system for multi-lingual keyword extraction .Just paste or write your text to get the keywords (lower score means more relevant) and see the higlighted version of your text. "
-article = "' \
---header 'Content-Type: application/json' \
---data-raw '{ "query": "mutation addTerm { addTerms(input: { termUrns: [\"urn:li:glossaryTerm:CustomerAccount\"], resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)\" }) }", "variables":{}}'
-```
-
-Expected Response:
-
-```json
-{"data":{"addTerms":true},"extensions":{}}
-```
-
-
-## Add Terms With Python SDK
-
-Following codes add a glossary term named `CustomerAccount` to a column `user_name` of a hive dataset named `fct_users_created`.
-You can refer to a full code in [dataset_add_column_term.py](https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/examples/library/dataset_add_column_term.py).
-
-
-```python
-# inlined from metadata-ingestion/examples/library/dataset_add_column_term.py
-import logging
-import time
-
-from datahub.emitter.mce_builder import make_dataset_urn, make_term_urn
-from datahub.emitter.mcp import MetadataChangeProposalWrapper
-
-# read-modify-write requires access to the DataHubGraph (RestEmitter is not enough)
-from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph
-
-# Imports for metadata model classes
-from datahub.metadata.schema_classes import (
- AuditStampClass,
- EditableSchemaFieldInfoClass,
- EditableSchemaMetadataClass,
- GlossaryTermAssociationClass,
- GlossaryTermsClass,
-)
-
-log = logging.getLogger(__name__)
-logging.basicConfig(level=logging.INFO)
-
-
-def get_simple_field_path_from_v2_field_path(field_path: str) -> str:
- """A helper function to extract simple . path notation from the v2 field path"""
- if not field_path.startswith("[version=2.0]"):
- # not a v2, we assume this is a simple path
- return field_path
- # this is a v2 field path
- tokens = [
- t for t in field_path.split(".") if not (t.startswith("[") or t.endswith("]"))
- ]
-
- return ".".join(tokens)
-
-
-# Inputs -> the column, dataset and the term to set
-column = "user_name"
-dataset_urn = make_dataset_urn(platform="hive", name="fct_users_created", env="PROD")
-term_to_add = make_term_urn("User")
-
-
-# First we get the current editable schema metadata
-gms_endpoint = "http://localhost:8080"
-graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint))
-
-
-current_editable_schema_metadata = graph.get_aspect(
- entity_urn=dataset_urn, aspect_type=EditableSchemaMetadataClass
-)
-
-
-# Some pre-built objects to help all the conditional pathways
-now = int(time.time() * 1000) # milliseconds since epoch
-current_timestamp = AuditStampClass(time=now, actor="urn:li:corpuser:ingestion")
-
-term_association_to_add = GlossaryTermAssociationClass(urn=term_to_add)
-term_aspect_to_set = GlossaryTermsClass(
- terms=[term_association_to_add], auditStamp=current_timestamp
-)
-field_info_to_set = EditableSchemaFieldInfoClass(
- fieldPath=column, glossaryTerms=term_aspect_to_set
-)
-
-need_write = False
-field_match = False
-if current_editable_schema_metadata:
- for fieldInfo in current_editable_schema_metadata.editableSchemaFieldInfo:
- if get_simple_field_path_from_v2_field_path(fieldInfo.fieldPath) == column:
- # we have some editable schema metadata for this field
- field_match = True
- if fieldInfo.glossaryTerms:
- if term_to_add not in [x.urn for x in fieldInfo.glossaryTerms.terms]:
- # this term is not present
- fieldInfo.glossaryTerms.terms.append(term_association_to_add)
- need_write = True
- else:
- fieldInfo.glossaryTerms = term_aspect_to_set
- need_write = True
-
- if not field_match:
- # this field isn't present in the editable schema metadata aspect, add it
- field_info = field_info_to_set
- current_editable_schema_metadata.editableSchemaFieldInfo.append(field_info)
- need_write = True
-
-else:
- # create a brand new editable schema metadata aspect
- current_editable_schema_metadata = EditableSchemaMetadataClass(
- editableSchemaFieldInfo=[field_info_to_set],
- created=current_timestamp,
- )
- need_write = True
-
-if need_write:
- event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper(
- entityUrn=dataset_urn,
- aspect=current_editable_schema_metadata,
- )
- graph.emit(event)
- log.info(f"Term {term_to_add} added to column {column} of dataset {dataset_urn}")
-
-else:
- log.info(f"Term {term_to_add} already attached to column {column}, omitting write")
-
-```
-
-We're using the `MetdataChangeProposalWrapper` to change entities in this example.
-For more information about the `MetadataChangeProposal`, please refer to [MetadataChangeProposal & MetadataChangeLog Events](/docs/advanced/mcp-mcl.md)
-
-
-## Expected Outcomes
-You can now see the term `CustomerAccount` has been added to `user_name` column.
-
-
diff --git a/spaces/abdvl/datahub_qa_bot/docs/quick-ingestion-guides/snowflake/setup.md b/spaces/abdvl/datahub_qa_bot/docs/quick-ingestion-guides/snowflake/setup.md
deleted file mode 100644
index c3882b611db9c22e0e5a0811cc92d1f97fb16442..0000000000000000000000000000000000000000
--- a/spaces/abdvl/datahub_qa_bot/docs/quick-ingestion-guides/snowflake/setup.md
+++ /dev/null
@@ -1,70 +0,0 @@
----
-title: Setup
----
-# Snowflake Ingestion Guide: Setup & Prerequisites
-
-In order to configure ingestion from Snowflake, you'll first have to ensure you have a Snowflake user with the `ACCOUNTADMIN` role or `MANAGE GRANTS` privilege.
-
-## Snowflake Prerequisites
-
-1. Create a DataHub-specific role by executing the following queries in Snowflake. Replace `` with an existing warehouse that you wish to use for DataHub ingestion.
-
- ```sql
- create or replace role datahub_role;
- -- Grant access to a warehouse to run queries to view metadata
- grant operate, usage on warehouse "" to role datahub_role;
- ```
-
- Make note of this role and warehouse. You'll need this in the next step.
-
-2. Create a DataHub-specific user by executing the following queries. Replace `` with a strong password. Replace `` with the same warehouse used above.
-
- ```sql
- create user datahub_user display_name = 'DataHub' password='' default_role = datahub_role default_warehouse = '';
- -- Grant access to the DataHub role created above
- grant role datahub_role to user datahub_user;
- ```
-
- Make note of the user and its password. You'll need this in the next step.
-
-3. Assign privileges to read metadata about your assets by executing the following queries. Replace `` with an existing database. Repeat for all databases from your Snowflake instance that you wish to integrate with DataHub.
-
- ```sql
- set db_var = '""';
- -- Grant access to view database and schema in which your tables/views exist
- grant usage on DATABASE identifier($db_var) to role datahub_role;
- grant usage on all schemas in database identifier($db_var) to role datahub_role;
- grant usage on future schemas in database identifier($db_var) to role datahub_role;
-
- -- Grant Select acccess enable Data Profiling
- grant select on all tables in database identifier($db_var) to role datahub_role;
- grant select on future tables in database identifier($db_var) to role datahub_role;
- grant select on all external tables in database identifier($db_var) to role datahub_role;
- grant select on future external tables in database identifier($db_var) to role datahub_role;
- grant select on all views in database identifier($db_var) to role datahub_role;
- grant select on future views in database identifier($db_var) to role datahub_role;
-
- -- Grant access to view tables and views
- grant references on all tables in database identifier($db_var) to role datahub_role;
- grant references on future tables in database identifier($db_var) to role datahub_role;
- grant references on all external tables in database identifier($db_var) to role datahub_role;
- grant references on future external tables in database identifier($db_var) to role datahub_role;
- grant references on all views in database identifier($db_var) to role datahub_role;
- grant references on future views in database identifier($db_var) to role datahub_role;
-
- -- Assign privileges to extract lineage and usage statistics from Snowflake by executing the below query.
- grant imported privileges on database snowflake to role datahub_role;
-
- ```
-
- If you have imported databases in your Snowflake instance that you wish to integrate with DataHub, you'll need to use the below query for them.
-
- ```sql
- grant IMPORTED PRIVILEGES on database "" to role datahub_role;
- ```
-
-## Next Steps
-
-Once you've done all of the above in Snowflake, it's time to [move on](configuration.md) to configuring the actual ingestion source within DataHub.
-
-*Need more help? Join the conversation in [Slack](http://slack.datahubproject.io)!*
diff --git a/spaces/abdvl/datahub_qa_bot/docs/what/urn.md b/spaces/abdvl/datahub_qa_bot/docs/what/urn.md
deleted file mode 100644
index fbead110afe0ace13636f865ad6c85ceb000cee1..0000000000000000000000000000000000000000
--- a/spaces/abdvl/datahub_qa_bot/docs/what/urn.md
+++ /dev/null
@@ -1,34 +0,0 @@
-# What is URN?
-
-URN ([Uniform Resource Name](https://en.wikipedia.org/wiki/Uniform_Resource_Name)) is the chosen scheme of [URI](https://en.wikipedia.org/wiki/Uniform_Resource_Identifier) to uniquely define any resource in DataHub. It has the following form
-```
-urn:::
-```
-[Onboarding a new entity](../modeling/metadata-model.md) to [GMA](gma.md) starts with modelling an URN specific to that entity.
-You can use the existing [URN models](../../li-utils/src/main/javaPegasus/com/linkedin/common/urn) for built-in entities as a reference.
-
-## Namespace
-All URNs available in DataHub are using `li` as their namespace.
-This can be easily changed to a different namespace for your organization if you fork DataHub.
-
-## Entity Type
-Entity type for URN is different than [entity](entity.md) in GMA context. This can be thought of as the object type of
-any resource for which you need unique identifier for its each instance. While you can create URNs for GMA entities such as
-[DatasetUrn] with entity type `dataset`, you can also define URN for data platforms, [DataPlatformUrn].
-
-## ID
-ID is the unique identifier part of a URN. It's unique for a specific entity type within a specific namespace.
-ID could contain a single field, or multi fields in the case of complex URNs. A complex URN can even contain other URNs as ID fields. This type of URN is also referred to as nested URN. For non-URN ID fields, the value can be either a string, number, or [Pegasus Enum](https://linkedin.github.io/rest.li/pdl_schema#enum-type).
-
-Here are some example URNs with a single ID field:
-
-```
-urn:li:dataPlatform:kafka
-urn:li:corpuser:jdoe
-```
-
-[DatasetUrn](../../li-utils/src/main/javaPegasus/com/linkedin/common/urn/DatasetUrn.java) is an example of a complex nested URN. It contains 3 ID fields: `platform`, `name` and `fabric`, where `platform` is another [URN](../../li-utils/src/main/javaPegasus/com/linkedin/common/urn/DataPlatformUrn.java). Here are some examples
-```
-urn:li:dataset:(urn:li:dataPlatform:kafka,PageViewEvent,PROD)
-urn:li:dataset:(urn:li:dataPlatform:hdfs,PageViewEvent,EI)
-```
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/cnn/bricks/non_local.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/cnn/bricks/non_local.py
deleted file mode 100644
index 92d00155ef275c1201ea66bba30470a1785cc5d7..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/cnn/bricks/non_local.py
+++ /dev/null
@@ -1,306 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from abc import ABCMeta
-
-import torch
-import torch.nn as nn
-
-from ..utils import constant_init, normal_init
-from .conv_module import ConvModule
-from .registry import PLUGIN_LAYERS
-
-
-class _NonLocalNd(nn.Module, metaclass=ABCMeta):
- """Basic Non-local module.
-
- This module is proposed in
- "Non-local Neural Networks"
- Paper reference: https://arxiv.org/abs/1711.07971
- Code reference: https://github.com/AlexHex7/Non-local_pytorch
-
- Args:
- in_channels (int): Channels of the input feature map.
- reduction (int): Channel reduction ratio. Default: 2.
- use_scale (bool): Whether to scale pairwise_weight by
- `1/sqrt(inter_channels)` when the mode is `embedded_gaussian`.
- Default: True.
- conv_cfg (None | dict): The config dict for convolution layers.
- If not specified, it will use `nn.Conv2d` for convolution layers.
- Default: None.
- norm_cfg (None | dict): The config dict for normalization layers.
- Default: None. (This parameter is only applicable to conv_out.)
- mode (str): Options are `gaussian`, `concatenation`,
- `embedded_gaussian` and `dot_product`. Default: embedded_gaussian.
- """
-
- def __init__(self,
- in_channels,
- reduction=2,
- use_scale=True,
- conv_cfg=None,
- norm_cfg=None,
- mode='embedded_gaussian',
- **kwargs):
- super(_NonLocalNd, self).__init__()
- self.in_channels = in_channels
- self.reduction = reduction
- self.use_scale = use_scale
- self.inter_channels = max(in_channels // reduction, 1)
- self.mode = mode
-
- if mode not in [
- 'gaussian', 'embedded_gaussian', 'dot_product', 'concatenation'
- ]:
- raise ValueError("Mode should be in 'gaussian', 'concatenation', "
- f"'embedded_gaussian' or 'dot_product', but got "
- f'{mode} instead.')
-
- # g, theta, phi are defaulted as `nn.ConvNd`.
- # Here we use ConvModule for potential usage.
- self.g = ConvModule(
- self.in_channels,
- self.inter_channels,
- kernel_size=1,
- conv_cfg=conv_cfg,
- act_cfg=None)
- self.conv_out = ConvModule(
- self.inter_channels,
- self.in_channels,
- kernel_size=1,
- conv_cfg=conv_cfg,
- norm_cfg=norm_cfg,
- act_cfg=None)
-
- if self.mode != 'gaussian':
- self.theta = ConvModule(
- self.in_channels,
- self.inter_channels,
- kernel_size=1,
- conv_cfg=conv_cfg,
- act_cfg=None)
- self.phi = ConvModule(
- self.in_channels,
- self.inter_channels,
- kernel_size=1,
- conv_cfg=conv_cfg,
- act_cfg=None)
-
- if self.mode == 'concatenation':
- self.concat_project = ConvModule(
- self.inter_channels * 2,
- 1,
- kernel_size=1,
- stride=1,
- padding=0,
- bias=False,
- act_cfg=dict(type='ReLU'))
-
- self.init_weights(**kwargs)
-
- def init_weights(self, std=0.01, zeros_init=True):
- if self.mode != 'gaussian':
- for m in [self.g, self.theta, self.phi]:
- normal_init(m.conv, std=std)
- else:
- normal_init(self.g.conv, std=std)
- if zeros_init:
- if self.conv_out.norm_cfg is None:
- constant_init(self.conv_out.conv, 0)
- else:
- constant_init(self.conv_out.norm, 0)
- else:
- if self.conv_out.norm_cfg is None:
- normal_init(self.conv_out.conv, std=std)
- else:
- normal_init(self.conv_out.norm, std=std)
-
- def gaussian(self, theta_x, phi_x):
- # NonLocal1d pairwise_weight: [N, H, H]
- # NonLocal2d pairwise_weight: [N, HxW, HxW]
- # NonLocal3d pairwise_weight: [N, TxHxW, TxHxW]
- pairwise_weight = torch.matmul(theta_x, phi_x)
- pairwise_weight = pairwise_weight.softmax(dim=-1)
- return pairwise_weight
-
- def embedded_gaussian(self, theta_x, phi_x):
- # NonLocal1d pairwise_weight: [N, H, H]
- # NonLocal2d pairwise_weight: [N, HxW, HxW]
- # NonLocal3d pairwise_weight: [N, TxHxW, TxHxW]
- pairwise_weight = torch.matmul(theta_x, phi_x)
- if self.use_scale:
- # theta_x.shape[-1] is `self.inter_channels`
- pairwise_weight /= theta_x.shape[-1]**0.5
- pairwise_weight = pairwise_weight.softmax(dim=-1)
- return pairwise_weight
-
- def dot_product(self, theta_x, phi_x):
- # NonLocal1d pairwise_weight: [N, H, H]
- # NonLocal2d pairwise_weight: [N, HxW, HxW]
- # NonLocal3d pairwise_weight: [N, TxHxW, TxHxW]
- pairwise_weight = torch.matmul(theta_x, phi_x)
- pairwise_weight /= pairwise_weight.shape[-1]
- return pairwise_weight
-
- def concatenation(self, theta_x, phi_x):
- # NonLocal1d pairwise_weight: [N, H, H]
- # NonLocal2d pairwise_weight: [N, HxW, HxW]
- # NonLocal3d pairwise_weight: [N, TxHxW, TxHxW]
- h = theta_x.size(2)
- w = phi_x.size(3)
- theta_x = theta_x.repeat(1, 1, 1, w)
- phi_x = phi_x.repeat(1, 1, h, 1)
-
- concat_feature = torch.cat([theta_x, phi_x], dim=1)
- pairwise_weight = self.concat_project(concat_feature)
- n, _, h, w = pairwise_weight.size()
- pairwise_weight = pairwise_weight.view(n, h, w)
- pairwise_weight /= pairwise_weight.shape[-1]
-
- return pairwise_weight
-
- def forward(self, x):
- # Assume `reduction = 1`, then `inter_channels = C`
- # or `inter_channels = C` when `mode="gaussian"`
-
- # NonLocal1d x: [N, C, H]
- # NonLocal2d x: [N, C, H, W]
- # NonLocal3d x: [N, C, T, H, W]
- n = x.size(0)
-
- # NonLocal1d g_x: [N, H, C]
- # NonLocal2d g_x: [N, HxW, C]
- # NonLocal3d g_x: [N, TxHxW, C]
- g_x = self.g(x).view(n, self.inter_channels, -1)
- g_x = g_x.permute(0, 2, 1)
-
- # NonLocal1d theta_x: [N, H, C], phi_x: [N, C, H]
- # NonLocal2d theta_x: [N, HxW, C], phi_x: [N, C, HxW]
- # NonLocal3d theta_x: [N, TxHxW, C], phi_x: [N, C, TxHxW]
- if self.mode == 'gaussian':
- theta_x = x.view(n, self.in_channels, -1)
- theta_x = theta_x.permute(0, 2, 1)
- if self.sub_sample:
- phi_x = self.phi(x).view(n, self.in_channels, -1)
- else:
- phi_x = x.view(n, self.in_channels, -1)
- elif self.mode == 'concatenation':
- theta_x = self.theta(x).view(n, self.inter_channels, -1, 1)
- phi_x = self.phi(x).view(n, self.inter_channels, 1, -1)
- else:
- theta_x = self.theta(x).view(n, self.inter_channels, -1)
- theta_x = theta_x.permute(0, 2, 1)
- phi_x = self.phi(x).view(n, self.inter_channels, -1)
-
- pairwise_func = getattr(self, self.mode)
- # NonLocal1d pairwise_weight: [N, H, H]
- # NonLocal2d pairwise_weight: [N, HxW, HxW]
- # NonLocal3d pairwise_weight: [N, TxHxW, TxHxW]
- pairwise_weight = pairwise_func(theta_x, phi_x)
-
- # NonLocal1d y: [N, H, C]
- # NonLocal2d y: [N, HxW, C]
- # NonLocal3d y: [N, TxHxW, C]
- y = torch.matmul(pairwise_weight, g_x)
- # NonLocal1d y: [N, C, H]
- # NonLocal2d y: [N, C, H, W]
- # NonLocal3d y: [N, C, T, H, W]
- y = y.permute(0, 2, 1).contiguous().reshape(n, self.inter_channels,
- *x.size()[2:])
-
- output = x + self.conv_out(y)
-
- return output
-
-
-class NonLocal1d(_NonLocalNd):
- """1D Non-local module.
-
- Args:
- in_channels (int): Same as `NonLocalND`.
- sub_sample (bool): Whether to apply max pooling after pairwise
- function (Note that the `sub_sample` is applied on spatial only).
- Default: False.
- conv_cfg (None | dict): Same as `NonLocalND`.
- Default: dict(type='Conv1d').
- """
-
- def __init__(self,
- in_channels,
- sub_sample=False,
- conv_cfg=dict(type='Conv1d'),
- **kwargs):
- super(NonLocal1d, self).__init__(
- in_channels, conv_cfg=conv_cfg, **kwargs)
-
- self.sub_sample = sub_sample
-
- if sub_sample:
- max_pool_layer = nn.MaxPool1d(kernel_size=2)
- self.g = nn.Sequential(self.g, max_pool_layer)
- if self.mode != 'gaussian':
- self.phi = nn.Sequential(self.phi, max_pool_layer)
- else:
- self.phi = max_pool_layer
-
-
-@PLUGIN_LAYERS.register_module()
-class NonLocal2d(_NonLocalNd):
- """2D Non-local module.
-
- Args:
- in_channels (int): Same as `NonLocalND`.
- sub_sample (bool): Whether to apply max pooling after pairwise
- function (Note that the `sub_sample` is applied on spatial only).
- Default: False.
- conv_cfg (None | dict): Same as `NonLocalND`.
- Default: dict(type='Conv2d').
- """
-
- _abbr_ = 'nonlocal_block'
-
- def __init__(self,
- in_channels,
- sub_sample=False,
- conv_cfg=dict(type='Conv2d'),
- **kwargs):
- super(NonLocal2d, self).__init__(
- in_channels, conv_cfg=conv_cfg, **kwargs)
-
- self.sub_sample = sub_sample
-
- if sub_sample:
- max_pool_layer = nn.MaxPool2d(kernel_size=(2, 2))
- self.g = nn.Sequential(self.g, max_pool_layer)
- if self.mode != 'gaussian':
- self.phi = nn.Sequential(self.phi, max_pool_layer)
- else:
- self.phi = max_pool_layer
-
-
-class NonLocal3d(_NonLocalNd):
- """3D Non-local module.
-
- Args:
- in_channels (int): Same as `NonLocalND`.
- sub_sample (bool): Whether to apply max pooling after pairwise
- function (Note that the `sub_sample` is applied on spatial only).
- Default: False.
- conv_cfg (None | dict): Same as `NonLocalND`.
- Default: dict(type='Conv3d').
- """
-
- def __init__(self,
- in_channels,
- sub_sample=False,
- conv_cfg=dict(type='Conv3d'),
- **kwargs):
- super(NonLocal3d, self).__init__(
- in_channels, conv_cfg=conv_cfg, **kwargs)
- self.sub_sample = sub_sample
-
- if sub_sample:
- max_pool_layer = nn.MaxPool3d(kernel_size=(1, 2, 2))
- self.g = nn.Sequential(self.g, max_pool_layer)
- if self.mode != 'gaussian':
- self.phi = nn.Sequential(self.phi, max_pool_layer)
- else:
- self.phi = max_pool_layer
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/runner/checkpoint.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/runner/checkpoint.py
deleted file mode 100644
index b29ca320679164432f446adad893e33fb2b4b29e..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmcv/runner/checkpoint.py
+++ /dev/null
@@ -1,707 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import io
-import os
-import os.path as osp
-import pkgutil
-import re
-import time
-import warnings
-from collections import OrderedDict
-from importlib import import_module
-from tempfile import TemporaryDirectory
-
-import torch
-import torchvision
-from torch.optim import Optimizer
-from torch.utils import model_zoo
-
-import annotator.uniformer.mmcv as mmcv
-from ..fileio import FileClient
-from ..fileio import load as load_file
-from ..parallel import is_module_wrapper
-from ..utils import mkdir_or_exist
-from .dist_utils import get_dist_info
-
-ENV_MMCV_HOME = 'MMCV_HOME'
-ENV_XDG_CACHE_HOME = 'XDG_CACHE_HOME'
-DEFAULT_CACHE_DIR = '~/.cache'
-
-
-def _get_mmcv_home():
- mmcv_home = os.path.expanduser(
- os.getenv(
- ENV_MMCV_HOME,
- os.path.join(
- os.getenv(ENV_XDG_CACHE_HOME, DEFAULT_CACHE_DIR), 'mmcv')))
-
- mkdir_or_exist(mmcv_home)
- return mmcv_home
-
-
-def load_state_dict(module, state_dict, strict=False, logger=None):
- """Load state_dict to a module.
-
- This method is modified from :meth:`torch.nn.Module.load_state_dict`.
- Default value for ``strict`` is set to ``False`` and the message for
- param mismatch will be shown even if strict is False.
-
- Args:
- module (Module): Module that receives the state_dict.
- state_dict (OrderedDict): Weights.
- strict (bool): whether to strictly enforce that the keys
- in :attr:`state_dict` match the keys returned by this module's
- :meth:`~torch.nn.Module.state_dict` function. Default: ``False``.
- logger (:obj:`logging.Logger`, optional): Logger to log the error
- message. If not specified, print function will be used.
- """
- unexpected_keys = []
- all_missing_keys = []
- err_msg = []
-
- metadata = getattr(state_dict, '_metadata', None)
- state_dict = state_dict.copy()
- if metadata is not None:
- state_dict._metadata = metadata
-
- # use _load_from_state_dict to enable checkpoint version control
- def load(module, prefix=''):
- # recursively check parallel module in case that the model has a
- # complicated structure, e.g., nn.Module(nn.Module(DDP))
- if is_module_wrapper(module):
- module = module.module
- local_metadata = {} if metadata is None else metadata.get(
- prefix[:-1], {})
- module._load_from_state_dict(state_dict, prefix, local_metadata, True,
- all_missing_keys, unexpected_keys,
- err_msg)
- for name, child in module._modules.items():
- if child is not None:
- load(child, prefix + name + '.')
-
- load(module)
- load = None # break load->load reference cycle
-
- # ignore "num_batches_tracked" of BN layers
- missing_keys = [
- key for key in all_missing_keys if 'num_batches_tracked' not in key
- ]
-
- if unexpected_keys:
- err_msg.append('unexpected key in source '
- f'state_dict: {", ".join(unexpected_keys)}\n')
- if missing_keys:
- err_msg.append(
- f'missing keys in source state_dict: {", ".join(missing_keys)}\n')
-
- rank, _ = get_dist_info()
- if len(err_msg) > 0 and rank == 0:
- err_msg.insert(
- 0, 'The model and loaded state dict do not match exactly\n')
- err_msg = '\n'.join(err_msg)
- if strict:
- raise RuntimeError(err_msg)
- elif logger is not None:
- logger.warning(err_msg)
- else:
- print(err_msg)
-
-
-def get_torchvision_models():
- model_urls = dict()
- for _, name, ispkg in pkgutil.walk_packages(torchvision.models.__path__):
- if ispkg:
- continue
- _zoo = import_module(f'torchvision.models.{name}')
- if hasattr(_zoo, 'model_urls'):
- _urls = getattr(_zoo, 'model_urls')
- model_urls.update(_urls)
- return model_urls
-
-
-def get_external_models():
- mmcv_home = _get_mmcv_home()
- default_json_path = osp.join(mmcv.__path__[0], 'model_zoo/open_mmlab.json')
- default_urls = load_file(default_json_path)
- assert isinstance(default_urls, dict)
- external_json_path = osp.join(mmcv_home, 'open_mmlab.json')
- if osp.exists(external_json_path):
- external_urls = load_file(external_json_path)
- assert isinstance(external_urls, dict)
- default_urls.update(external_urls)
-
- return default_urls
-
-
-def get_mmcls_models():
- mmcls_json_path = osp.join(mmcv.__path__[0], 'model_zoo/mmcls.json')
- mmcls_urls = load_file(mmcls_json_path)
-
- return mmcls_urls
-
-
-def get_deprecated_model_names():
- deprecate_json_path = osp.join(mmcv.__path__[0],
- 'model_zoo/deprecated.json')
- deprecate_urls = load_file(deprecate_json_path)
- assert isinstance(deprecate_urls, dict)
-
- return deprecate_urls
-
-
-def _process_mmcls_checkpoint(checkpoint):
- state_dict = checkpoint['state_dict']
- new_state_dict = OrderedDict()
- for k, v in state_dict.items():
- if k.startswith('backbone.'):
- new_state_dict[k[9:]] = v
- new_checkpoint = dict(state_dict=new_state_dict)
-
- return new_checkpoint
-
-
-class CheckpointLoader:
- """A general checkpoint loader to manage all schemes."""
-
- _schemes = {}
-
- @classmethod
- def _register_scheme(cls, prefixes, loader, force=False):
- if isinstance(prefixes, str):
- prefixes = [prefixes]
- else:
- assert isinstance(prefixes, (list, tuple))
- for prefix in prefixes:
- if (prefix not in cls._schemes) or force:
- cls._schemes[prefix] = loader
- else:
- raise KeyError(
- f'{prefix} is already registered as a loader backend, '
- 'add "force=True" if you want to override it')
- # sort, longer prefixes take priority
- cls._schemes = OrderedDict(
- sorted(cls._schemes.items(), key=lambda t: t[0], reverse=True))
-
- @classmethod
- def register_scheme(cls, prefixes, loader=None, force=False):
- """Register a loader to CheckpointLoader.
-
- This method can be used as a normal class method or a decorator.
-
- Args:
- prefixes (str or list[str] or tuple[str]):
- The prefix of the registered loader.
- loader (function, optional): The loader function to be registered.
- When this method is used as a decorator, loader is None.
- Defaults to None.
- force (bool, optional): Whether to override the loader
- if the prefix has already been registered. Defaults to False.
- """
-
- if loader is not None:
- cls._register_scheme(prefixes, loader, force=force)
- return
-
- def _register(loader_cls):
- cls._register_scheme(prefixes, loader_cls, force=force)
- return loader_cls
-
- return _register
-
- @classmethod
- def _get_checkpoint_loader(cls, path):
- """Finds a loader that supports the given path. Falls back to the local
- loader if no other loader is found.
-
- Args:
- path (str): checkpoint path
-
- Returns:
- loader (function): checkpoint loader
- """
-
- for p in cls._schemes:
- if path.startswith(p):
- return cls._schemes[p]
-
- @classmethod
- def load_checkpoint(cls, filename, map_location=None, logger=None):
- """load checkpoint through URL scheme path.
-
- Args:
- filename (str): checkpoint file name with given prefix
- map_location (str, optional): Same as :func:`torch.load`.
- Default: None
- logger (:mod:`logging.Logger`, optional): The logger for message.
- Default: None
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
-
- checkpoint_loader = cls._get_checkpoint_loader(filename)
- class_name = checkpoint_loader.__name__
- mmcv.print_log(
- f'load checkpoint from {class_name[10:]} path: {filename}', logger)
- return checkpoint_loader(filename, map_location)
-
-
-@CheckpointLoader.register_scheme(prefixes='')
-def load_from_local(filename, map_location):
- """load checkpoint by local file path.
-
- Args:
- filename (str): local checkpoint file path
- map_location (str, optional): Same as :func:`torch.load`.
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
-
- if not osp.isfile(filename):
- raise IOError(f'{filename} is not a checkpoint file')
- checkpoint = torch.load(filename, map_location=map_location)
- return checkpoint
-
-
-@CheckpointLoader.register_scheme(prefixes=('http://', 'https://'))
-def load_from_http(filename, map_location=None, model_dir=None):
- """load checkpoint through HTTP or HTTPS scheme path. In distributed
- setting, this function only download checkpoint at local rank 0.
-
- Args:
- filename (str): checkpoint file path with modelzoo or
- torchvision prefix
- map_location (str, optional): Same as :func:`torch.load`.
- model_dir (string, optional): directory in which to save the object,
- Default: None
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
- rank, world_size = get_dist_info()
- rank = int(os.environ.get('LOCAL_RANK', rank))
- if rank == 0:
- checkpoint = model_zoo.load_url(
- filename, model_dir=model_dir, map_location=map_location)
- if world_size > 1:
- torch.distributed.barrier()
- if rank > 0:
- checkpoint = model_zoo.load_url(
- filename, model_dir=model_dir, map_location=map_location)
- return checkpoint
-
-
-@CheckpointLoader.register_scheme(prefixes='pavi://')
-def load_from_pavi(filename, map_location=None):
- """load checkpoint through the file path prefixed with pavi. In distributed
- setting, this function download ckpt at all ranks to different temporary
- directories.
-
- Args:
- filename (str): checkpoint file path with pavi prefix
- map_location (str, optional): Same as :func:`torch.load`.
- Default: None
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
- assert filename.startswith('pavi://'), \
- f'Expected filename startswith `pavi://`, but get {filename}'
- model_path = filename[7:]
-
- try:
- from pavi import modelcloud
- except ImportError:
- raise ImportError(
- 'Please install pavi to load checkpoint from modelcloud.')
-
- model = modelcloud.get(model_path)
- with TemporaryDirectory() as tmp_dir:
- downloaded_file = osp.join(tmp_dir, model.name)
- model.download(downloaded_file)
- checkpoint = torch.load(downloaded_file, map_location=map_location)
- return checkpoint
-
-
-@CheckpointLoader.register_scheme(prefixes='s3://')
-def load_from_ceph(filename, map_location=None, backend='petrel'):
- """load checkpoint through the file path prefixed with s3. In distributed
- setting, this function download ckpt at all ranks to different temporary
- directories.
-
- Args:
- filename (str): checkpoint file path with s3 prefix
- map_location (str, optional): Same as :func:`torch.load`.
- backend (str, optional): The storage backend type. Options are 'ceph',
- 'petrel'. Default: 'petrel'.
-
- .. warning::
- :class:`mmcv.fileio.file_client.CephBackend` will be deprecated,
- please use :class:`mmcv.fileio.file_client.PetrelBackend` instead.
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
- allowed_backends = ['ceph', 'petrel']
- if backend not in allowed_backends:
- raise ValueError(f'Load from Backend {backend} is not supported.')
-
- if backend == 'ceph':
- warnings.warn(
- 'CephBackend will be deprecated, please use PetrelBackend instead')
-
- # CephClient and PetrelBackend have the same prefix 's3://' and the latter
- # will be chosen as default. If PetrelBackend can not be instantiated
- # successfully, the CephClient will be chosen.
- try:
- file_client = FileClient(backend=backend)
- except ImportError:
- allowed_backends.remove(backend)
- file_client = FileClient(backend=allowed_backends[0])
-
- with io.BytesIO(file_client.get(filename)) as buffer:
- checkpoint = torch.load(buffer, map_location=map_location)
- return checkpoint
-
-
-@CheckpointLoader.register_scheme(prefixes=('modelzoo://', 'torchvision://'))
-def load_from_torchvision(filename, map_location=None):
- """load checkpoint through the file path prefixed with modelzoo or
- torchvision.
-
- Args:
- filename (str): checkpoint file path with modelzoo or
- torchvision prefix
- map_location (str, optional): Same as :func:`torch.load`.
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
- model_urls = get_torchvision_models()
- if filename.startswith('modelzoo://'):
- warnings.warn('The URL scheme of "modelzoo://" is deprecated, please '
- 'use "torchvision://" instead')
- model_name = filename[11:]
- else:
- model_name = filename[14:]
- return load_from_http(model_urls[model_name], map_location=map_location)
-
-
-@CheckpointLoader.register_scheme(prefixes=('open-mmlab://', 'openmmlab://'))
-def load_from_openmmlab(filename, map_location=None):
- """load checkpoint through the file path prefixed with open-mmlab or
- openmmlab.
-
- Args:
- filename (str): checkpoint file path with open-mmlab or
- openmmlab prefix
- map_location (str, optional): Same as :func:`torch.load`.
- Default: None
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
-
- model_urls = get_external_models()
- prefix_str = 'open-mmlab://'
- if filename.startswith(prefix_str):
- model_name = filename[13:]
- else:
- model_name = filename[12:]
- prefix_str = 'openmmlab://'
-
- deprecated_urls = get_deprecated_model_names()
- if model_name in deprecated_urls:
- warnings.warn(f'{prefix_str}{model_name} is deprecated in favor '
- f'of {prefix_str}{deprecated_urls[model_name]}')
- model_name = deprecated_urls[model_name]
- model_url = model_urls[model_name]
- # check if is url
- if model_url.startswith(('http://', 'https://')):
- checkpoint = load_from_http(model_url, map_location=map_location)
- else:
- filename = osp.join(_get_mmcv_home(), model_url)
- if not osp.isfile(filename):
- raise IOError(f'{filename} is not a checkpoint file')
- checkpoint = torch.load(filename, map_location=map_location)
- return checkpoint
-
-
-@CheckpointLoader.register_scheme(prefixes='mmcls://')
-def load_from_mmcls(filename, map_location=None):
- """load checkpoint through the file path prefixed with mmcls.
-
- Args:
- filename (str): checkpoint file path with mmcls prefix
- map_location (str, optional): Same as :func:`torch.load`.
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
-
- model_urls = get_mmcls_models()
- model_name = filename[8:]
- checkpoint = load_from_http(
- model_urls[model_name], map_location=map_location)
- checkpoint = _process_mmcls_checkpoint(checkpoint)
- return checkpoint
-
-
-def _load_checkpoint(filename, map_location=None, logger=None):
- """Load checkpoint from somewhere (modelzoo, file, url).
-
- Args:
- filename (str): Accept local filepath, URL, ``torchvision://xxx``,
- ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
- details.
- map_location (str, optional): Same as :func:`torch.load`.
- Default: None.
- logger (:mod:`logging.Logger`, optional): The logger for error message.
- Default: None
-
- Returns:
- dict or OrderedDict: The loaded checkpoint. It can be either an
- OrderedDict storing model weights or a dict containing other
- information, which depends on the checkpoint.
- """
- return CheckpointLoader.load_checkpoint(filename, map_location, logger)
-
-
-def _load_checkpoint_with_prefix(prefix, filename, map_location=None):
- """Load partial pretrained model with specific prefix.
-
- Args:
- prefix (str): The prefix of sub-module.
- filename (str): Accept local filepath, URL, ``torchvision://xxx``,
- ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
- details.
- map_location (str | None): Same as :func:`torch.load`. Default: None.
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
-
- checkpoint = _load_checkpoint(filename, map_location=map_location)
-
- if 'state_dict' in checkpoint:
- state_dict = checkpoint['state_dict']
- else:
- state_dict = checkpoint
- if not prefix.endswith('.'):
- prefix += '.'
- prefix_len = len(prefix)
-
- state_dict = {
- k[prefix_len:]: v
- for k, v in state_dict.items() if k.startswith(prefix)
- }
-
- assert state_dict, f'{prefix} is not in the pretrained model'
- return state_dict
-
-
-def load_checkpoint(model,
- filename,
- map_location=None,
- strict=False,
- logger=None,
- revise_keys=[(r'^module\.', '')]):
- """Load checkpoint from a file or URI.
-
- Args:
- model (Module): Module to load checkpoint.
- filename (str): Accept local filepath, URL, ``torchvision://xxx``,
- ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
- details.
- map_location (str): Same as :func:`torch.load`.
- strict (bool): Whether to allow different params for the model and
- checkpoint.
- logger (:mod:`logging.Logger` or None): The logger for error message.
- revise_keys (list): A list of customized keywords to modify the
- state_dict in checkpoint. Each item is a (pattern, replacement)
- pair of the regular expression operations. Default: strip
- the prefix 'module.' by [(r'^module\\.', '')].
-
- Returns:
- dict or OrderedDict: The loaded checkpoint.
- """
- checkpoint = _load_checkpoint(filename, map_location, logger)
- # OrderedDict is a subclass of dict
- if not isinstance(checkpoint, dict):
- raise RuntimeError(
- f'No state_dict found in checkpoint file {filename}')
- # get state_dict from checkpoint
- if 'state_dict' in checkpoint:
- state_dict = checkpoint['state_dict']
- else:
- state_dict = checkpoint
-
- # strip prefix of state_dict
- metadata = getattr(state_dict, '_metadata', OrderedDict())
- for p, r in revise_keys:
- state_dict = OrderedDict(
- {re.sub(p, r, k): v
- for k, v in state_dict.items()})
- # Keep metadata in state_dict
- state_dict._metadata = metadata
-
- # load state_dict
- load_state_dict(model, state_dict, strict, logger)
- return checkpoint
-
-
-def weights_to_cpu(state_dict):
- """Copy a model state_dict to cpu.
-
- Args:
- state_dict (OrderedDict): Model weights on GPU.
-
- Returns:
- OrderedDict: Model weights on GPU.
- """
- state_dict_cpu = OrderedDict()
- for key, val in state_dict.items():
- state_dict_cpu[key] = val.cpu()
- # Keep metadata in state_dict
- state_dict_cpu._metadata = getattr(state_dict, '_metadata', OrderedDict())
- return state_dict_cpu
-
-
-def _save_to_state_dict(module, destination, prefix, keep_vars):
- """Saves module state to `destination` dictionary.
-
- This method is modified from :meth:`torch.nn.Module._save_to_state_dict`.
-
- Args:
- module (nn.Module): The module to generate state_dict.
- destination (dict): A dict where state will be stored.
- prefix (str): The prefix for parameters and buffers used in this
- module.
- """
- for name, param in module._parameters.items():
- if param is not None:
- destination[prefix + name] = param if keep_vars else param.detach()
- for name, buf in module._buffers.items():
- # remove check of _non_persistent_buffers_set to allow nn.BatchNorm2d
- if buf is not None:
- destination[prefix + name] = buf if keep_vars else buf.detach()
-
-
-def get_state_dict(module, destination=None, prefix='', keep_vars=False):
- """Returns a dictionary containing a whole state of the module.
-
- Both parameters and persistent buffers (e.g. running averages) are
- included. Keys are corresponding parameter and buffer names.
-
- This method is modified from :meth:`torch.nn.Module.state_dict` to
- recursively check parallel module in case that the model has a complicated
- structure, e.g., nn.Module(nn.Module(DDP)).
-
- Args:
- module (nn.Module): The module to generate state_dict.
- destination (OrderedDict): Returned dict for the state of the
- module.
- prefix (str): Prefix of the key.
- keep_vars (bool): Whether to keep the variable property of the
- parameters. Default: False.
-
- Returns:
- dict: A dictionary containing a whole state of the module.
- """
- # recursively check parallel module in case that the model has a
- # complicated structure, e.g., nn.Module(nn.Module(DDP))
- if is_module_wrapper(module):
- module = module.module
-
- # below is the same as torch.nn.Module.state_dict()
- if destination is None:
- destination = OrderedDict()
- destination._metadata = OrderedDict()
- destination._metadata[prefix[:-1]] = local_metadata = dict(
- version=module._version)
- _save_to_state_dict(module, destination, prefix, keep_vars)
- for name, child in module._modules.items():
- if child is not None:
- get_state_dict(
- child, destination, prefix + name + '.', keep_vars=keep_vars)
- for hook in module._state_dict_hooks.values():
- hook_result = hook(module, destination, prefix, local_metadata)
- if hook_result is not None:
- destination = hook_result
- return destination
-
-
-def save_checkpoint(model,
- filename,
- optimizer=None,
- meta=None,
- file_client_args=None):
- """Save checkpoint to file.
-
- The checkpoint will have 3 fields: ``meta``, ``state_dict`` and
- ``optimizer``. By default ``meta`` will contain version and time info.
-
- Args:
- model (Module): Module whose params are to be saved.
- filename (str): Checkpoint filename.
- optimizer (:obj:`Optimizer`, optional): Optimizer to be saved.
- meta (dict, optional): Metadata to be saved in checkpoint.
- file_client_args (dict, optional): Arguments to instantiate a
- FileClient. See :class:`mmcv.fileio.FileClient` for details.
- Default: None.
- `New in version 1.3.16.`
- """
- if meta is None:
- meta = {}
- elif not isinstance(meta, dict):
- raise TypeError(f'meta must be a dict or None, but got {type(meta)}')
- meta.update(mmcv_version=mmcv.__version__, time=time.asctime())
-
- if is_module_wrapper(model):
- model = model.module
-
- if hasattr(model, 'CLASSES') and model.CLASSES is not None:
- # save class name to the meta
- meta.update(CLASSES=model.CLASSES)
-
- checkpoint = {
- 'meta': meta,
- 'state_dict': weights_to_cpu(get_state_dict(model))
- }
- # save optimizer state dict in the checkpoint
- if isinstance(optimizer, Optimizer):
- checkpoint['optimizer'] = optimizer.state_dict()
- elif isinstance(optimizer, dict):
- checkpoint['optimizer'] = {}
- for name, optim in optimizer.items():
- checkpoint['optimizer'][name] = optim.state_dict()
-
- if filename.startswith('pavi://'):
- if file_client_args is not None:
- raise ValueError(
- 'file_client_args should be "None" if filename starts with'
- f'"pavi://", but got {file_client_args}')
- try:
- from pavi import modelcloud
- from pavi import exception
- except ImportError:
- raise ImportError(
- 'Please install pavi to load checkpoint from modelcloud.')
- model_path = filename[7:]
- root = modelcloud.Folder()
- model_dir, model_name = osp.split(model_path)
- try:
- model = modelcloud.get(model_dir)
- except exception.NodeNotFoundError:
- model = root.create_training_model(model_dir)
- with TemporaryDirectory() as tmp_dir:
- checkpoint_file = osp.join(tmp_dir, model_name)
- with open(checkpoint_file, 'wb') as f:
- torch.save(checkpoint, f)
- f.flush()
- model.create_file(checkpoint_file, name=model_name)
- else:
- file_client = FileClient.infer_client(file_client_args, filename)
- with io.BytesIO() as f:
- torch.save(checkpoint, f)
- file_client.put(f.getvalue(), filename)
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/core/bbox/assigners/base_assigner.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/core/bbox/assigners/base_assigner.py
deleted file mode 100644
index 1ff0160dbb4bfbf53cb40d1d5cb29bcc3d197a59..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/core/bbox/assigners/base_assigner.py
+++ /dev/null
@@ -1,9 +0,0 @@
-from abc import ABCMeta, abstractmethod
-
-
-class BaseAssigner(metaclass=ABCMeta):
- """Base assigner that assigns boxes to ground truth boxes."""
-
- @abstractmethod
- def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None):
- """Assign boxes to either a ground truth boxes or a negative boxes."""
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/cascade_rcnn.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/cascade_rcnn.py
deleted file mode 100644
index d873dceb7e4efdf8d1e7d282badfe9b7118426b9..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/cascade_rcnn.py
+++ /dev/null
@@ -1,46 +0,0 @@
-from ..builder import DETECTORS
-from .two_stage import TwoStageDetector
-
-
-@DETECTORS.register_module()
-class CascadeRCNN(TwoStageDetector):
- r"""Implementation of `Cascade R-CNN: Delving into High Quality Object
- Detection `_"""
-
- def __init__(self,
- backbone,
- neck=None,
- rpn_head=None,
- roi_head=None,
- train_cfg=None,
- test_cfg=None,
- pretrained=None):
- super(CascadeRCNN, self).__init__(
- backbone=backbone,
- neck=neck,
- rpn_head=rpn_head,
- roi_head=roi_head,
- train_cfg=train_cfg,
- test_cfg=test_cfg,
- pretrained=pretrained)
-
- def show_result(self, data, result, **kwargs):
- """Show prediction results of the detector.
-
- Args:
- data (str or np.ndarray): Image filename or loaded image.
- result (Tensor or tuple): The results to draw over `img`
- bbox_result or (bbox_result, segm_result).
-
- Returns:
- np.ndarray: The image with bboxes drawn on it.
- """
- if self.with_mask:
- ms_bbox_result, ms_segm_result = result
- if isinstance(ms_bbox_result, dict):
- result = (ms_bbox_result['ensemble'],
- ms_segm_result['ensemble'])
- else:
- if isinstance(result, dict):
- result = result['ensemble']
- return super(CascadeRCNN, self).show_result(data, result, **kwargs)
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/sparse_rcnn.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/sparse_rcnn.py
deleted file mode 100644
index 0dbd0250f189e610a0bbc72b0dab2559e26857ae..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/detectors/sparse_rcnn.py
+++ /dev/null
@@ -1,110 +0,0 @@
-from ..builder import DETECTORS
-from .two_stage import TwoStageDetector
-
-
-@DETECTORS.register_module()
-class SparseRCNN(TwoStageDetector):
- r"""Implementation of `Sparse R-CNN: End-to-End Object Detection with
- Learnable Proposals `_"""
-
- def __init__(self, *args, **kwargs):
- super(SparseRCNN, self).__init__(*args, **kwargs)
- assert self.with_rpn, 'Sparse R-CNN do not support external proposals'
-
- def forward_train(self,
- img,
- img_metas,
- gt_bboxes,
- gt_labels,
- gt_bboxes_ignore=None,
- gt_masks=None,
- proposals=None,
- **kwargs):
- """Forward function of SparseR-CNN in train stage.
-
- Args:
- img (Tensor): of shape (N, C, H, W) encoding input images.
- Typically these should be mean centered and std scaled.
- img_metas (list[dict]): list of image info dict where each dict
- has: 'img_shape', 'scale_factor', 'flip', and may also contain
- 'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
- For details on the values of these keys see
- :class:`mmdet.datasets.pipelines.Collect`.
- gt_bboxes (list[Tensor]): Ground truth bboxes for each image with
- shape (num_gts, 4) in [tl_x, tl_y, br_x, br_y] format.
- gt_labels (list[Tensor]): class indices corresponding to each box
- gt_bboxes_ignore (None | list[Tensor): specify which bounding
- boxes can be ignored when computing the loss.
- gt_masks (List[Tensor], optional) : Segmentation masks for
- each box. But we don't support it in this architecture.
- proposals (List[Tensor], optional): override rpn proposals with
- custom proposals. Use when `with_rpn` is False.
-
- Returns:
- dict[str, Tensor]: a dictionary of loss components
- """
-
- assert proposals is None, 'Sparse R-CNN does not support' \
- ' external proposals'
- assert gt_masks is None, 'Sparse R-CNN does not instance segmentation'
-
- x = self.extract_feat(img)
- proposal_boxes, proposal_features, imgs_whwh = \
- self.rpn_head.forward_train(x, img_metas)
- roi_losses = self.roi_head.forward_train(
- x,
- proposal_boxes,
- proposal_features,
- img_metas,
- gt_bboxes,
- gt_labels,
- gt_bboxes_ignore=gt_bboxes_ignore,
- gt_masks=gt_masks,
- imgs_whwh=imgs_whwh)
- return roi_losses
-
- def simple_test(self, img, img_metas, rescale=False):
- """Test function without test time augmentation.
-
- Args:
- imgs (list[torch.Tensor]): List of multiple images
- img_metas (list[dict]): List of image information.
- rescale (bool): Whether to rescale the results.
- Defaults to False.
-
- Returns:
- list[list[np.ndarray]]: BBox results of each image and classes.
- The outer list corresponds to each image. The inner list
- corresponds to each class.
- """
- x = self.extract_feat(img)
- proposal_boxes, proposal_features, imgs_whwh = \
- self.rpn_head.simple_test_rpn(x, img_metas)
- bbox_results = self.roi_head.simple_test(
- x,
- proposal_boxes,
- proposal_features,
- img_metas,
- imgs_whwh=imgs_whwh,
- rescale=rescale)
- return bbox_results
-
- def forward_dummy(self, img):
- """Used for computing network flops.
-
- See `mmdetection/tools/analysis_tools/get_flops.py`
- """
- # backbone
- x = self.extract_feat(img)
- # rpn
- num_imgs = len(img)
- dummy_img_metas = [
- dict(img_shape=(800, 1333, 3)) for _ in range(num_imgs)
- ]
- proposal_boxes, proposal_features, imgs_whwh = \
- self.rpn_head.simple_test_rpn(x, dummy_img_metas)
- # roi_head
- roi_outs = self.roi_head.forward_dummy(x, proposal_boxes,
- proposal_features,
- dummy_img_metas)
- return roi_outs
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/roi_heads/point_rend_roi_head.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/roi_heads/point_rend_roi_head.py
deleted file mode 100644
index 478cdf5bff6779e9291f94c543205289036ea2c6..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet/models/roi_heads/point_rend_roi_head.py
+++ /dev/null
@@ -1,218 +0,0 @@
-# Modified from https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend # noqa
-
-import torch
-import torch.nn.functional as F
-from mmcv.ops import point_sample, rel_roi_point_to_rel_img_point
-
-from mmdet.core import bbox2roi, bbox_mapping, merge_aug_masks
-from .. import builder
-from ..builder import HEADS
-from .standard_roi_head import StandardRoIHead
-
-
-@HEADS.register_module()
-class PointRendRoIHead(StandardRoIHead):
- """`PointRend `_."""
-
- def __init__(self, point_head, *args, **kwargs):
- super().__init__(*args, **kwargs)
- assert self.with_bbox and self.with_mask
- self.init_point_head(point_head)
-
- def init_point_head(self, point_head):
- """Initialize ``point_head``"""
- self.point_head = builder.build_head(point_head)
-
- def init_weights(self, pretrained):
- """Initialize the weights in head.
-
- Args:
- pretrained (str, optional): Path to pre-trained weights.
- """
- super().init_weights(pretrained)
- self.point_head.init_weights()
-
- def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks,
- img_metas):
- """Run forward function and calculate loss for mask head and point head
- in training."""
- mask_results = super()._mask_forward_train(x, sampling_results,
- bbox_feats, gt_masks,
- img_metas)
- if mask_results['loss_mask'] is not None:
- loss_point = self._mask_point_forward_train(
- x, sampling_results, mask_results['mask_pred'], gt_masks,
- img_metas)
- mask_results['loss_mask'].update(loss_point)
-
- return mask_results
-
- def _mask_point_forward_train(self, x, sampling_results, mask_pred,
- gt_masks, img_metas):
- """Run forward function and calculate loss for point head in
- training."""
- pos_labels = torch.cat([res.pos_gt_labels for res in sampling_results])
- rel_roi_points = self.point_head.get_roi_rel_points_train(
- mask_pred, pos_labels, cfg=self.train_cfg)
- rois = bbox2roi([res.pos_bboxes for res in sampling_results])
-
- fine_grained_point_feats = self._get_fine_grained_point_feats(
- x, rois, rel_roi_points, img_metas)
- coarse_point_feats = point_sample(mask_pred, rel_roi_points)
- mask_point_pred = self.point_head(fine_grained_point_feats,
- coarse_point_feats)
- mask_point_target = self.point_head.get_targets(
- rois, rel_roi_points, sampling_results, gt_masks, self.train_cfg)
- loss_mask_point = self.point_head.loss(mask_point_pred,
- mask_point_target, pos_labels)
-
- return loss_mask_point
-
- def _get_fine_grained_point_feats(self, x, rois, rel_roi_points,
- img_metas):
- """Sample fine grained feats from each level feature map and
- concatenate them together."""
- num_imgs = len(img_metas)
- fine_grained_feats = []
- for idx in range(self.mask_roi_extractor.num_inputs):
- feats = x[idx]
- spatial_scale = 1. / float(
- self.mask_roi_extractor.featmap_strides[idx])
- point_feats = []
- for batch_ind in range(num_imgs):
- # unravel batch dim
- feat = feats[batch_ind].unsqueeze(0)
- inds = (rois[:, 0].long() == batch_ind)
- if inds.any():
- rel_img_points = rel_roi_point_to_rel_img_point(
- rois[inds], rel_roi_points[inds], feat.shape[2:],
- spatial_scale).unsqueeze(0)
- point_feat = point_sample(feat, rel_img_points)
- point_feat = point_feat.squeeze(0).transpose(0, 1)
- point_feats.append(point_feat)
- fine_grained_feats.append(torch.cat(point_feats, dim=0))
- return torch.cat(fine_grained_feats, dim=1)
-
- def _mask_point_forward_test(self, x, rois, label_pred, mask_pred,
- img_metas):
- """Mask refining process with point head in testing."""
- refined_mask_pred = mask_pred.clone()
- for subdivision_step in range(self.test_cfg.subdivision_steps):
- refined_mask_pred = F.interpolate(
- refined_mask_pred,
- scale_factor=self.test_cfg.scale_factor,
- mode='bilinear',
- align_corners=False)
- # If `subdivision_num_points` is larger or equal to the
- # resolution of the next step, then we can skip this step
- num_rois, channels, mask_height, mask_width = \
- refined_mask_pred.shape
- if (self.test_cfg.subdivision_num_points >=
- self.test_cfg.scale_factor**2 * mask_height * mask_width
- and
- subdivision_step < self.test_cfg.subdivision_steps - 1):
- continue
- point_indices, rel_roi_points = \
- self.point_head.get_roi_rel_points_test(
- refined_mask_pred, label_pred, cfg=self.test_cfg)
- fine_grained_point_feats = self._get_fine_grained_point_feats(
- x, rois, rel_roi_points, img_metas)
- coarse_point_feats = point_sample(mask_pred, rel_roi_points)
- mask_point_pred = self.point_head(fine_grained_point_feats,
- coarse_point_feats)
-
- point_indices = point_indices.unsqueeze(1).expand(-1, channels, -1)
- refined_mask_pred = refined_mask_pred.reshape(
- num_rois, channels, mask_height * mask_width)
- refined_mask_pred = refined_mask_pred.scatter_(
- 2, point_indices, mask_point_pred)
- refined_mask_pred = refined_mask_pred.view(num_rois, channels,
- mask_height, mask_width)
-
- return refined_mask_pred
-
- def simple_test_mask(self,
- x,
- img_metas,
- det_bboxes,
- det_labels,
- rescale=False):
- """Obtain mask prediction without augmentation."""
- ori_shapes = tuple(meta['ori_shape'] for meta in img_metas)
- scale_factors = tuple(meta['scale_factor'] for meta in img_metas)
- num_imgs = len(det_bboxes)
- if all(det_bbox.shape[0] == 0 for det_bbox in det_bboxes):
- segm_results = [[[] for _ in range(self.mask_head.num_classes)]
- for _ in range(num_imgs)]
- else:
- # if det_bboxes is rescaled to the original image size, we need to
- # rescale it back to the testing scale to obtain RoIs.
- if rescale and not isinstance(scale_factors[0], float):
- scale_factors = [
- torch.from_numpy(scale_factor).to(det_bboxes[0].device)
- for scale_factor in scale_factors
- ]
- _bboxes = [
- det_bboxes[i][:, :4] *
- scale_factors[i] if rescale else det_bboxes[i][:, :4]
- for i in range(len(det_bboxes))
- ]
- mask_rois = bbox2roi(_bboxes)
- mask_results = self._mask_forward(x, mask_rois)
- # split batch mask prediction back to each image
- mask_pred = mask_results['mask_pred']
- num_mask_roi_per_img = [len(det_bbox) for det_bbox in det_bboxes]
- mask_preds = mask_pred.split(num_mask_roi_per_img, 0)
- mask_rois = mask_rois.split(num_mask_roi_per_img, 0)
-
- # apply mask post-processing to each image individually
- segm_results = []
- for i in range(num_imgs):
- if det_bboxes[i].shape[0] == 0:
- segm_results.append(
- [[] for _ in range(self.mask_head.num_classes)])
- else:
- x_i = [xx[[i]] for xx in x]
- mask_rois_i = mask_rois[i]
- mask_rois_i[:, 0] = 0 # TODO: remove this hack
- mask_pred_i = self._mask_point_forward_test(
- x_i, mask_rois_i, det_labels[i], mask_preds[i],
- [img_metas])
- segm_result = self.mask_head.get_seg_masks(
- mask_pred_i, _bboxes[i], det_labels[i], self.test_cfg,
- ori_shapes[i], scale_factors[i], rescale)
- segm_results.append(segm_result)
- return segm_results
-
- def aug_test_mask(self, feats, img_metas, det_bboxes, det_labels):
- """Test for mask head with test time augmentation."""
- if det_bboxes.shape[0] == 0:
- segm_result = [[] for _ in range(self.mask_head.num_classes)]
- else:
- aug_masks = []
- for x, img_meta in zip(feats, img_metas):
- img_shape = img_meta[0]['img_shape']
- scale_factor = img_meta[0]['scale_factor']
- flip = img_meta[0]['flip']
- _bboxes = bbox_mapping(det_bboxes[:, :4], img_shape,
- scale_factor, flip)
- mask_rois = bbox2roi([_bboxes])
- mask_results = self._mask_forward(x, mask_rois)
- mask_results['mask_pred'] = self._mask_point_forward_test(
- x, mask_rois, det_labels, mask_results['mask_pred'],
- img_metas)
- # convert to numpy array to save memory
- aug_masks.append(
- mask_results['mask_pred'].sigmoid().cpu().numpy())
- merged_masks = merge_aug_masks(aug_masks, img_metas, self.test_cfg)
-
- ori_shape = img_metas[0][0]['ori_shape']
- segm_result = self.mask_head.get_seg_masks(
- merged_masks,
- det_bboxes,
- det_labels,
- self.test_cfg,
- ori_shape,
- scale_factor=1.0,
- rescale=False)
- return segm_result
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/scnet_bbox_head.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/scnet_bbox_head.py
deleted file mode 100644
index 35758f4f4e3b2bddd460edb8a7f482b3a9da2919..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/bbox_heads/scnet_bbox_head.py
+++ /dev/null
@@ -1,76 +0,0 @@
-from mmdet.models.builder import HEADS
-from .convfc_bbox_head import ConvFCBBoxHead
-
-
-@HEADS.register_module()
-class SCNetBBoxHead(ConvFCBBoxHead):
- """BBox head for `SCNet `_.
-
- This inherits ``ConvFCBBoxHead`` with modified forward() function, allow us
- to get intermediate shared feature.
- """
-
- def _forward_shared(self, x):
- """Forward function for shared part."""
- if self.num_shared_convs > 0:
- for conv in self.shared_convs:
- x = conv(x)
-
- if self.num_shared_fcs > 0:
- if self.with_avg_pool:
- x = self.avg_pool(x)
-
- x = x.flatten(1)
-
- for fc in self.shared_fcs:
- x = self.relu(fc(x))
-
- return x
-
- def _forward_cls_reg(self, x):
- """Forward function for classification and regression parts."""
- x_cls = x
- x_reg = x
-
- for conv in self.cls_convs:
- x_cls = conv(x_cls)
- if x_cls.dim() > 2:
- if self.with_avg_pool:
- x_cls = self.avg_pool(x_cls)
- x_cls = x_cls.flatten(1)
- for fc in self.cls_fcs:
- x_cls = self.relu(fc(x_cls))
-
- for conv in self.reg_convs:
- x_reg = conv(x_reg)
- if x_reg.dim() > 2:
- if self.with_avg_pool:
- x_reg = self.avg_pool(x_reg)
- x_reg = x_reg.flatten(1)
- for fc in self.reg_fcs:
- x_reg = self.relu(fc(x_reg))
-
- cls_score = self.fc_cls(x_cls) if self.with_cls else None
- bbox_pred = self.fc_reg(x_reg) if self.with_reg else None
-
- return cls_score, bbox_pred
-
- def forward(self, x, return_shared_feat=False):
- """Forward function.
-
- Args:
- x (Tensor): input features
- return_shared_feat (bool): If True, return cls-reg-shared feature.
-
- Return:
- out (tuple[Tensor]): contain ``cls_score`` and ``bbox_pred``,
- if ``return_shared_feat`` is True, append ``x_shared`` to the
- returned tuple.
- """
- x_shared = self._forward_shared(x)
- out = self._forward_cls_reg(x_shared)
-
- if return_shared_feat:
- out += (x_shared, )
-
- return out
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py
deleted file mode 100644
index 45b6f36a386cd37c50cc43666fcc516f2e14d868..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py
+++ /dev/null
@@ -1,507 +0,0 @@
-import torch
-import torch.nn as nn
-
-from mmdet.core import (bbox2result, bbox2roi, bbox_mapping, build_assigner,
- build_sampler, merge_aug_bboxes, merge_aug_masks,
- multiclass_nms)
-from ..builder import HEADS, build_head, build_roi_extractor
-from .base_roi_head import BaseRoIHead
-from .test_mixins import BBoxTestMixin, MaskTestMixin
-
-
-@HEADS.register_module()
-class CascadeRoIHead(BaseRoIHead, BBoxTestMixin, MaskTestMixin):
- """Cascade roi head including one bbox head and one mask head.
-
- https://arxiv.org/abs/1712.00726
- """
-
- def __init__(self,
- num_stages,
- stage_loss_weights,
- bbox_roi_extractor=None,
- bbox_head=None,
- mask_roi_extractor=None,
- mask_head=None,
- shared_head=None,
- train_cfg=None,
- test_cfg=None):
- assert bbox_roi_extractor is not None
- assert bbox_head is not None
- assert shared_head is None, \
- 'Shared head is not supported in Cascade RCNN anymore'
- self.num_stages = num_stages
- self.stage_loss_weights = stage_loss_weights
- super(CascadeRoIHead, self).__init__(
- bbox_roi_extractor=bbox_roi_extractor,
- bbox_head=bbox_head,
- mask_roi_extractor=mask_roi_extractor,
- mask_head=mask_head,
- shared_head=shared_head,
- train_cfg=train_cfg,
- test_cfg=test_cfg)
-
- def init_bbox_head(self, bbox_roi_extractor, bbox_head):
- """Initialize box head and box roi extractor.
-
- Args:
- bbox_roi_extractor (dict): Config of box roi extractor.
- bbox_head (dict): Config of box in box head.
- """
- self.bbox_roi_extractor = nn.ModuleList()
- self.bbox_head = nn.ModuleList()
- if not isinstance(bbox_roi_extractor, list):
- bbox_roi_extractor = [
- bbox_roi_extractor for _ in range(self.num_stages)
- ]
- if not isinstance(bbox_head, list):
- bbox_head = [bbox_head for _ in range(self.num_stages)]
- assert len(bbox_roi_extractor) == len(bbox_head) == self.num_stages
- for roi_extractor, head in zip(bbox_roi_extractor, bbox_head):
- self.bbox_roi_extractor.append(build_roi_extractor(roi_extractor))
- self.bbox_head.append(build_head(head))
-
- def init_mask_head(self, mask_roi_extractor, mask_head):
- """Initialize mask head and mask roi extractor.
-
- Args:
- mask_roi_extractor (dict): Config of mask roi extractor.
- mask_head (dict): Config of mask in mask head.
- """
- self.mask_head = nn.ModuleList()
- if not isinstance(mask_head, list):
- mask_head = [mask_head for _ in range(self.num_stages)]
- assert len(mask_head) == self.num_stages
- for head in mask_head:
- self.mask_head.append(build_head(head))
- if mask_roi_extractor is not None:
- self.share_roi_extractor = False
- self.mask_roi_extractor = nn.ModuleList()
- if not isinstance(mask_roi_extractor, list):
- mask_roi_extractor = [
- mask_roi_extractor for _ in range(self.num_stages)
- ]
- assert len(mask_roi_extractor) == self.num_stages
- for roi_extractor in mask_roi_extractor:
- self.mask_roi_extractor.append(
- build_roi_extractor(roi_extractor))
- else:
- self.share_roi_extractor = True
- self.mask_roi_extractor = self.bbox_roi_extractor
-
- def init_assigner_sampler(self):
- """Initialize assigner and sampler for each stage."""
- self.bbox_assigner = []
- self.bbox_sampler = []
- if self.train_cfg is not None:
- for idx, rcnn_train_cfg in enumerate(self.train_cfg):
- self.bbox_assigner.append(
- build_assigner(rcnn_train_cfg.assigner))
- self.current_stage = idx
- self.bbox_sampler.append(
- build_sampler(rcnn_train_cfg.sampler, context=self))
-
- def init_weights(self, pretrained):
- """Initialize the weights in head.
-
- Args:
- pretrained (str, optional): Path to pre-trained weights.
- Defaults to None.
- """
- if self.with_shared_head:
- self.shared_head.init_weights(pretrained=pretrained)
- for i in range(self.num_stages):
- if self.with_bbox:
- self.bbox_roi_extractor[i].init_weights()
- self.bbox_head[i].init_weights()
- if self.with_mask:
- if not self.share_roi_extractor:
- self.mask_roi_extractor[i].init_weights()
- self.mask_head[i].init_weights()
-
- def forward_dummy(self, x, proposals):
- """Dummy forward function."""
- # bbox head
- outs = ()
- rois = bbox2roi([proposals])
- if self.with_bbox:
- for i in range(self.num_stages):
- bbox_results = self._bbox_forward(i, x, rois)
- outs = outs + (bbox_results['cls_score'],
- bbox_results['bbox_pred'])
- # mask heads
- if self.with_mask:
- mask_rois = rois[:100]
- for i in range(self.num_stages):
- mask_results = self._mask_forward(i, x, mask_rois)
- outs = outs + (mask_results['mask_pred'], )
- return outs
-
- def _bbox_forward(self, stage, x, rois):
- """Box head forward function used in both training and testing."""
- bbox_roi_extractor = self.bbox_roi_extractor[stage]
- bbox_head = self.bbox_head[stage]
- bbox_feats = bbox_roi_extractor(x[:bbox_roi_extractor.num_inputs],
- rois)
- # do not support caffe_c4 model anymore
- cls_score, bbox_pred = bbox_head(bbox_feats)
-
- bbox_results = dict(
- cls_score=cls_score, bbox_pred=bbox_pred, bbox_feats=bbox_feats)
- return bbox_results
-
- def _bbox_forward_train(self, stage, x, sampling_results, gt_bboxes,
- gt_labels, rcnn_train_cfg):
- """Run forward function and calculate loss for box head in training."""
- rois = bbox2roi([res.bboxes for res in sampling_results])
- bbox_results = self._bbox_forward(stage, x, rois)
- bbox_targets = self.bbox_head[stage].get_targets(
- sampling_results, gt_bboxes, gt_labels, rcnn_train_cfg)
- loss_bbox = self.bbox_head[stage].loss(bbox_results['cls_score'],
- bbox_results['bbox_pred'], rois,
- *bbox_targets)
-
- bbox_results.update(
- loss_bbox=loss_bbox, rois=rois, bbox_targets=bbox_targets)
- return bbox_results
-
- def _mask_forward(self, stage, x, rois):
- """Mask head forward function used in both training and testing."""
- mask_roi_extractor = self.mask_roi_extractor[stage]
- mask_head = self.mask_head[stage]
- mask_feats = mask_roi_extractor(x[:mask_roi_extractor.num_inputs],
- rois)
- # do not support caffe_c4 model anymore
- mask_pred = mask_head(mask_feats)
-
- mask_results = dict(mask_pred=mask_pred)
- return mask_results
-
- def _mask_forward_train(self,
- stage,
- x,
- sampling_results,
- gt_masks,
- rcnn_train_cfg,
- bbox_feats=None):
- """Run forward function and calculate loss for mask head in
- training."""
- pos_rois = bbox2roi([res.pos_bboxes for res in sampling_results])
- mask_results = self._mask_forward(stage, x, pos_rois)
-
- mask_targets = self.mask_head[stage].get_targets(
- sampling_results, gt_masks, rcnn_train_cfg)
- pos_labels = torch.cat([res.pos_gt_labels for res in sampling_results])
- loss_mask = self.mask_head[stage].loss(mask_results['mask_pred'],
- mask_targets, pos_labels)
-
- mask_results.update(loss_mask=loss_mask)
- return mask_results
-
- def forward_train(self,
- x,
- img_metas,
- proposal_list,
- gt_bboxes,
- gt_labels,
- gt_bboxes_ignore=None,
- gt_masks=None):
- """
- Args:
- x (list[Tensor]): list of multi-level img features.
- img_metas (list[dict]): list of image info dict where each dict
- has: 'img_shape', 'scale_factor', 'flip', and may also contain
- 'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
- For details on the values of these keys see
- `mmdet/datasets/pipelines/formatting.py:Collect`.
- proposals (list[Tensors]): list of region proposals.
- gt_bboxes (list[Tensor]): Ground truth bboxes for each image with
- shape (num_gts, 4) in [tl_x, tl_y, br_x, br_y] format.
- gt_labels (list[Tensor]): class indices corresponding to each box
- gt_bboxes_ignore (None | list[Tensor]): specify which bounding
- boxes can be ignored when computing the loss.
- gt_masks (None | Tensor) : true segmentation masks for each box
- used if the architecture supports a segmentation task.
-
- Returns:
- dict[str, Tensor]: a dictionary of loss components
- """
- losses = dict()
- for i in range(self.num_stages):
- self.current_stage = i
- rcnn_train_cfg = self.train_cfg[i]
- lw = self.stage_loss_weights[i]
-
- # assign gts and sample proposals
- sampling_results = []
- if self.with_bbox or self.with_mask:
- bbox_assigner = self.bbox_assigner[i]
- bbox_sampler = self.bbox_sampler[i]
- num_imgs = len(img_metas)
- if gt_bboxes_ignore is None:
- gt_bboxes_ignore = [None for _ in range(num_imgs)]
-
- for j in range(num_imgs):
- assign_result = bbox_assigner.assign(
- proposal_list[j], gt_bboxes[j], gt_bboxes_ignore[j],
- gt_labels[j])
- sampling_result = bbox_sampler.sample(
- assign_result,
- proposal_list[j],
- gt_bboxes[j],
- gt_labels[j],
- feats=[lvl_feat[j][None] for lvl_feat in x])
- sampling_results.append(sampling_result)
-
- # bbox head forward and loss
- bbox_results = self._bbox_forward_train(i, x, sampling_results,
- gt_bboxes, gt_labels,
- rcnn_train_cfg)
-
- for name, value in bbox_results['loss_bbox'].items():
- losses[f's{i}.{name}'] = (
- value * lw if 'loss' in name else value)
-
- # mask head forward and loss
- if self.with_mask:
- mask_results = self._mask_forward_train(
- i, x, sampling_results, gt_masks, rcnn_train_cfg,
- bbox_results['bbox_feats'])
- for name, value in mask_results['loss_mask'].items():
- losses[f's{i}.{name}'] = (
- value * lw if 'loss' in name else value)
-
- # refine bboxes
- if i < self.num_stages - 1:
- pos_is_gts = [res.pos_is_gt for res in sampling_results]
- # bbox_targets is a tuple
- roi_labels = bbox_results['bbox_targets'][0]
- with torch.no_grad():
- roi_labels = torch.where(
- roi_labels == self.bbox_head[i].num_classes,
- bbox_results['cls_score'][:, :-1].argmax(1),
- roi_labels)
- proposal_list = self.bbox_head[i].refine_bboxes(
- bbox_results['rois'], roi_labels,
- bbox_results['bbox_pred'], pos_is_gts, img_metas)
-
- return losses
-
- def simple_test(self, x, proposal_list, img_metas, rescale=False):
- """Test without augmentation."""
- assert self.with_bbox, 'Bbox head must be implemented.'
- num_imgs = len(proposal_list)
- img_shapes = tuple(meta['img_shape'] for meta in img_metas)
- ori_shapes = tuple(meta['ori_shape'] for meta in img_metas)
- scale_factors = tuple(meta['scale_factor'] for meta in img_metas)
-
- # "ms" in variable names means multi-stage
- ms_bbox_result = {}
- ms_segm_result = {}
- ms_scores = []
- rcnn_test_cfg = self.test_cfg
-
- rois = bbox2roi(proposal_list)
- for i in range(self.num_stages):
- bbox_results = self._bbox_forward(i, x, rois)
-
- # split batch bbox prediction back to each image
- cls_score = bbox_results['cls_score']
- bbox_pred = bbox_results['bbox_pred']
- num_proposals_per_img = tuple(
- len(proposals) for proposals in proposal_list)
- rois = rois.split(num_proposals_per_img, 0)
- cls_score = cls_score.split(num_proposals_per_img, 0)
- if isinstance(bbox_pred, torch.Tensor):
- bbox_pred = bbox_pred.split(num_proposals_per_img, 0)
- else:
- bbox_pred = self.bbox_head[i].bbox_pred_split(
- bbox_pred, num_proposals_per_img)
- ms_scores.append(cls_score)
-
- if i < self.num_stages - 1:
- bbox_label = [s[:, :-1].argmax(dim=1) for s in cls_score]
- rois = torch.cat([
- self.bbox_head[i].regress_by_class(rois[j], bbox_label[j],
- bbox_pred[j],
- img_metas[j])
- for j in range(num_imgs)
- ])
-
- # average scores of each image by stages
- cls_score = [
- sum([score[i] for score in ms_scores]) / float(len(ms_scores))
- for i in range(num_imgs)
- ]
-
- # apply bbox post-processing to each image individually
- det_bboxes = []
- det_labels = []
- for i in range(num_imgs):
- det_bbox, det_label = self.bbox_head[-1].get_bboxes(
- rois[i],
- cls_score[i],
- bbox_pred[i],
- img_shapes[i],
- scale_factors[i],
- rescale=rescale,
- cfg=rcnn_test_cfg)
- det_bboxes.append(det_bbox)
- det_labels.append(det_label)
-
- if torch.onnx.is_in_onnx_export():
- return det_bboxes, det_labels
- bbox_results = [
- bbox2result(det_bboxes[i], det_labels[i],
- self.bbox_head[-1].num_classes)
- for i in range(num_imgs)
- ]
- ms_bbox_result['ensemble'] = bbox_results
-
- if self.with_mask:
- if all(det_bbox.shape[0] == 0 for det_bbox in det_bboxes):
- mask_classes = self.mask_head[-1].num_classes
- segm_results = [[[] for _ in range(mask_classes)]
- for _ in range(num_imgs)]
- else:
- if rescale and not isinstance(scale_factors[0], float):
- scale_factors = [
- torch.from_numpy(scale_factor).to(det_bboxes[0].device)
- for scale_factor in scale_factors
- ]
- _bboxes = [
- det_bboxes[i][:, :4] *
- scale_factors[i] if rescale else det_bboxes[i][:, :4]
- for i in range(len(det_bboxes))
- ]
- mask_rois = bbox2roi(_bboxes)
- num_mask_rois_per_img = tuple(
- _bbox.size(0) for _bbox in _bboxes)
- aug_masks = []
- for i in range(self.num_stages):
- mask_results = self._mask_forward(i, x, mask_rois)
- mask_pred = mask_results['mask_pred']
- # split batch mask prediction back to each image
- mask_pred = mask_pred.split(num_mask_rois_per_img, 0)
- aug_masks.append(
- [m.sigmoid().cpu().numpy() for m in mask_pred])
-
- # apply mask post-processing to each image individually
- segm_results = []
- for i in range(num_imgs):
- if det_bboxes[i].shape[0] == 0:
- segm_results.append(
- [[]
- for _ in range(self.mask_head[-1].num_classes)])
- else:
- aug_mask = [mask[i] for mask in aug_masks]
- merged_masks = merge_aug_masks(
- aug_mask, [[img_metas[i]]] * self.num_stages,
- rcnn_test_cfg)
- segm_result = self.mask_head[-1].get_seg_masks(
- merged_masks, _bboxes[i], det_labels[i],
- rcnn_test_cfg, ori_shapes[i], scale_factors[i],
- rescale)
- segm_results.append(segm_result)
- ms_segm_result['ensemble'] = segm_results
-
- if self.with_mask:
- results = list(
- zip(ms_bbox_result['ensemble'], ms_segm_result['ensemble']))
- else:
- results = ms_bbox_result['ensemble']
-
- return results
-
- def aug_test(self, features, proposal_list, img_metas, rescale=False):
- """Test with augmentations.
-
- If rescale is False, then returned bboxes and masks will fit the scale
- of imgs[0].
- """
- rcnn_test_cfg = self.test_cfg
- aug_bboxes = []
- aug_scores = []
- for x, img_meta in zip(features, img_metas):
- # only one image in the batch
- img_shape = img_meta[0]['img_shape']
- scale_factor = img_meta[0]['scale_factor']
- flip = img_meta[0]['flip']
- flip_direction = img_meta[0]['flip_direction']
-
- proposals = bbox_mapping(proposal_list[0][:, :4], img_shape,
- scale_factor, flip, flip_direction)
- # "ms" in variable names means multi-stage
- ms_scores = []
-
- rois = bbox2roi([proposals])
- for i in range(self.num_stages):
- bbox_results = self._bbox_forward(i, x, rois)
- ms_scores.append(bbox_results['cls_score'])
-
- if i < self.num_stages - 1:
- bbox_label = bbox_results['cls_score'][:, :-1].argmax(
- dim=1)
- rois = self.bbox_head[i].regress_by_class(
- rois, bbox_label, bbox_results['bbox_pred'],
- img_meta[0])
-
- cls_score = sum(ms_scores) / float(len(ms_scores))
- bboxes, scores = self.bbox_head[-1].get_bboxes(
- rois,
- cls_score,
- bbox_results['bbox_pred'],
- img_shape,
- scale_factor,
- rescale=False,
- cfg=None)
- aug_bboxes.append(bboxes)
- aug_scores.append(scores)
-
- # after merging, bboxes will be rescaled to the original image size
- merged_bboxes, merged_scores = merge_aug_bboxes(
- aug_bboxes, aug_scores, img_metas, rcnn_test_cfg)
- det_bboxes, det_labels = multiclass_nms(merged_bboxes, merged_scores,
- rcnn_test_cfg.score_thr,
- rcnn_test_cfg.nms,
- rcnn_test_cfg.max_per_img)
-
- bbox_result = bbox2result(det_bboxes, det_labels,
- self.bbox_head[-1].num_classes)
-
- if self.with_mask:
- if det_bboxes.shape[0] == 0:
- segm_result = [[[]
- for _ in range(self.mask_head[-1].num_classes)]
- ]
- else:
- aug_masks = []
- aug_img_metas = []
- for x, img_meta in zip(features, img_metas):
- img_shape = img_meta[0]['img_shape']
- scale_factor = img_meta[0]['scale_factor']
- flip = img_meta[0]['flip']
- flip_direction = img_meta[0]['flip_direction']
- _bboxes = bbox_mapping(det_bboxes[:, :4], img_shape,
- scale_factor, flip, flip_direction)
- mask_rois = bbox2roi([_bboxes])
- for i in range(self.num_stages):
- mask_results = self._mask_forward(i, x, mask_rois)
- aug_masks.append(
- mask_results['mask_pred'].sigmoid().cpu().numpy())
- aug_img_metas.append(img_meta)
- merged_masks = merge_aug_masks(aug_masks, aug_img_metas,
- self.test_cfg)
-
- ori_shape = img_metas[0][0]['ori_shape']
- segm_result = self.mask_head[-1].get_seg_masks(
- merged_masks,
- det_bboxes,
- det_labels,
- rcnn_test_cfg,
- ori_shape,
- scale_factor=1.0,
- rescale=False)
- return [(bbox_result, segm_result)]
- else:
- return [bbox_result]
diff --git a/spaces/abhishekgawade/Skin_disease_detection/app.py b/spaces/abhishekgawade/Skin_disease_detection/app.py
deleted file mode 100644
index ed75d3e088b6a5fb546214b0baf1ac8ddb4f21f4..0000000000000000000000000000000000000000
--- a/spaces/abhishekgawade/Skin_disease_detection/app.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import gradio as gr
-import tensorflow as tf
-
-path_to_model = "./skin_model_23_75.18.h5"
-
-model = tf.keras.models.load_model(path_to_model)
-
-labels = ['Acne / Rosacea',
- 'Actinic Keratosis / Basal Cell Carcinoma',
- 'Atopic Dermatitis', 'Bullous Disease',
- 'Cellulitis Impetigo (Bacterial Infections)',
- 'Eczema', 'Exanthems (Drug Eruptions)', 'Hair Loss (Alopecia)',
- 'Herpes HPV', 'Disorders of Pigmentation',
- 'Lupus ',
- 'Melanoma (Skin Cancer)', 'Nail Fungus',
- 'Poison Ivy',
- 'Psoriasis (Lichen Planus)', 'Scabies Lyme',
- 'Seborrheic Keratoses', 'Systemic Disease',
- 'Tinea Ringworm (Fungal Infections)',
- 'Urticaria Hives', 'Vascular Tumors', 'Vasculitis', 'Warts Molluscum']
-
-def classify_image(photos):
- photos = photos.reshape((-1, 224, 224, 3))
- prediction = model.predict(photos).flatten()
- confidences = {labels[i]: float(prediction[i]) for i in range(23)}
- return confidences
-
-
-title="SKIN DISEASE DETECTION"
-
-description = "An automated system is proposed for the diagnosis of #23 common skin diseases by using data from clinical images and patient information using deep learning pre-trained EfficientNetB7 model with 75% accuracy. we will implement a simple image classification model using Gradio and Tensorflow. The image classification model will classify images of various skin disease problems into labeled classes."
-
-
-article = "We used the generated Gradio UI to input an image for the trained convolutional neural network to make image classifications. The convolutional neural network was able to accurately classify the input image. Sometimes you would like to resize the image from the gradio UI for better performance"
-
-
-examples = [
- ['./123.jpg'],
- ['./acne-closed-comedo-2.jpg'],
- ['./distal-subungual-onychomycosis-86.jpg'],
- ['./cherry-angioma-16.jpg'],
- ['./malignant-melanoma-16.jpg'],
- ['./tinea-primary-lesion-15.jpg'],
- ['./congenital-nevus-35.jpg'],
- ['./tinea-body-137.jpg']
- ]
-
-
-
-
-
-gr.Interface(fn=classify_image,
- title = title,
- article = article,
- description = description,
- inputs=gr.inputs.Image(shape=(224, 224)),
- outputs=gr.outputs.Label(num_top_classes=4),
- examples=examples).launch()
-
-
-
-
diff --git a/spaces/acmyu/frame_interpolation_prototype/utils.py b/spaces/acmyu/frame_interpolation_prototype/utils.py
deleted file mode 100644
index 32e5b73654720d3b404bb38d8d75e99a9267396e..0000000000000000000000000000000000000000
--- a/spaces/acmyu/frame_interpolation_prototype/utils.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import os
-import torch
-from torch.autograd import Variable
-
-
-def make_folder(path, version):
- if not os.path.exists(os.path.join(path, version)):
- os.makedirs(os.path.join(path, version))
-
-
-def tensor2var(x, grad=False):
- if torch.cuda.is_available():
- x = x.cuda()
- return Variable(x, requires_grad=grad)
-
-def var2tensor(x):
- return x.data.cpu()
-
-def var2numpy(x):
- return x.data.cpu().numpy()
-
-def denorm(x):
- out = (x + 1) / 2
- return out.clamp_(0, 1)
-
-def getFrames(x):
- x = x[:, 0]
- x = x.to('cuda')
- return x
diff --git a/spaces/akhaliq/VQMIVC/README.md b/spaces/akhaliq/VQMIVC/README.md
deleted file mode 100644
index 79e73a2eb0181aec077e0eb62ab67ca6cc67df62..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/VQMIVC/README.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-title: VQMIVC
-emoji: 📈
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 3.0.11
-app_file: app.py
-pinned: false
----
-
-# Configuration
-
-`title`: _string_
-Display title for the Space
-
-`emoji`: _string_
-Space emoji (emoji-only character allowed)
-
-`colorFrom`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`colorTo`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`sdk`: _string_
-Can be either `gradio` or `streamlit`
-
-`sdk_version` : _string_
-Only applicable for `streamlit` SDK.
-See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
-
-`app_file`: _string_
-Path to your main application file (which contains either `gradio` or `streamlit` Python code).
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_
-Whether the Space stays on top of your list.
diff --git a/spaces/akhaliq/vox2/README.md b/spaces/akhaliq/vox2/README.md
deleted file mode 100644
index d8bc50b7e6970b8e709e8d6f2f8d1be5fb129ac3..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/vox2/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Vox2
-emoji: 🐢
-colorFrom: yellow
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.11.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/akhaliq/yolov7/models/experimental.py b/spaces/akhaliq/yolov7/models/experimental.py
deleted file mode 100644
index a14d496e69c2e6b144554342aace918857e39f15..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/yolov7/models/experimental.py
+++ /dev/null
@@ -1,106 +0,0 @@
-import numpy as np
-import torch
-import torch.nn as nn
-
-from models.common import Conv, DWConv
-from utils.google_utils import attempt_download
-
-
-class CrossConv(nn.Module):
- # Cross Convolution Downsample
- def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False):
- # ch_in, ch_out, kernel, stride, groups, expansion, shortcut
- super(CrossConv, self).__init__()
- c_ = int(c2 * e) # hidden channels
- self.cv1 = Conv(c1, c_, (1, k), (1, s))
- self.cv2 = Conv(c_, c2, (k, 1), (s, 1), g=g)
- self.add = shortcut and c1 == c2
-
- def forward(self, x):
- return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))
-
-
-class Sum(nn.Module):
- # Weighted sum of 2 or more layers https://arxiv.org/abs/1911.09070
- def __init__(self, n, weight=False): # n: number of inputs
- super(Sum, self).__init__()
- self.weight = weight # apply weights boolean
- self.iter = range(n - 1) # iter object
- if weight:
- self.w = nn.Parameter(-torch.arange(1., n) / 2, requires_grad=True) # layer weights
-
- def forward(self, x):
- y = x[0] # no weight
- if self.weight:
- w = torch.sigmoid(self.w) * 2
- for i in self.iter:
- y = y + x[i + 1] * w[i]
- else:
- for i in self.iter:
- y = y + x[i + 1]
- return y
-
-
-class MixConv2d(nn.Module):
- # Mixed Depthwise Conv https://arxiv.org/abs/1907.09595
- def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):
- super(MixConv2d, self).__init__()
- groups = len(k)
- if equal_ch: # equal c_ per group
- i = torch.linspace(0, groups - 1E-6, c2).floor() # c2 indices
- c_ = [(i == g).sum() for g in range(groups)] # intermediate channels
- else: # equal weight.numel() per group
- b = [c2] + [0] * groups
- a = np.eye(groups + 1, groups, k=-1)
- a -= np.roll(a, 1, axis=1)
- a *= np.array(k) ** 2
- a[0] = 1
- c_ = np.linalg.lstsq(a, b, rcond=None)[0].round() # solve for equal weight indices, ax = b
-
- self.m = nn.ModuleList([nn.Conv2d(c1, int(c_[g]), k[g], s, k[g] // 2, bias=False) for g in range(groups)])
- self.bn = nn.BatchNorm2d(c2)
- self.act = nn.LeakyReLU(0.1, inplace=True)
-
- def forward(self, x):
- return x + self.act(self.bn(torch.cat([m(x) for m in self.m], 1)))
-
-
-class Ensemble(nn.ModuleList):
- # Ensemble of models
- def __init__(self):
- super(Ensemble, self).__init__()
-
- def forward(self, x, augment=False):
- y = []
- for module in self:
- y.append(module(x, augment)[0])
- # y = torch.stack(y).max(0)[0] # max ensemble
- # y = torch.stack(y).mean(0) # mean ensemble
- y = torch.cat(y, 1) # nms ensemble
- return y, None # inference, train output
-
-
-def attempt_load(weights, map_location=None):
- # Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a
- model = Ensemble()
- for w in weights if isinstance(weights, list) else [weights]:
- # attempt_download(w)
- ckpt = torch.load(w, map_location=map_location) # load
- model.append(ckpt['ema' if ckpt.get('ema') else 'model'].float().fuse().eval()) # FP32 model
-
- # Compatibility updates
- for m in model.modules():
- if type(m) in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU]:
- m.inplace = True # pytorch 1.7.0 compatibility
- elif type(m) is nn.Upsample:
- m.recompute_scale_factor = None # torch 1.11.0 compatibility
- elif type(m) is Conv:
- m._non_persistent_buffers_set = set() # pytorch 1.6.0 compatibility
-
- if len(model) == 1:
- return model[-1] # return model
- else:
- print('Ensemble created with %s\n' % weights)
- for k in ['names', 'stride']:
- setattr(model, k, getattr(model[-1], k))
- return model # return ensemble
diff --git a/spaces/alamin655/websurfx/.gitpod.Dockerfile b/spaces/alamin655/websurfx/.gitpod.Dockerfile
deleted file mode 100644
index f64d7658c62998b406ad819308e5acaf687d4d26..0000000000000000000000000000000000000000
--- a/spaces/alamin655/websurfx/.gitpod.Dockerfile
+++ /dev/null
@@ -1,3 +0,0 @@
-FROM gitpod/workspace-rust
-
-RUN sudo install-packages redis-server nodejs npm liblua5.4-dev liblua5.3-dev liblua5.2-dev liblua5.1-0-dev libluajit-5.1-dev
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/rich/logging.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/rich/logging.py
deleted file mode 100644
index 002f1f7bf1c6857bdcce388f78ac1e415ef8d3f5..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/rich/logging.py
+++ /dev/null
@@ -1,268 +0,0 @@
-import logging
-from datetime import datetime
-from logging import Handler, LogRecord
-from pathlib import Path
-from typing import ClassVar, List, Optional, Type, Union
-
-from . import get_console
-from ._log_render import LogRender, FormatTimeCallable
-from .console import Console, ConsoleRenderable
-from .highlighter import Highlighter, ReprHighlighter
-from .text import Text
-from .traceback import Traceback
-
-
-class RichHandler(Handler):
- """A logging handler that renders output with Rich. The time / level / message and file are displayed in columns.
- The level is color coded, and the message is syntax highlighted.
-
- Note:
- Be careful when enabling console markup in log messages if you have configured logging for libraries not
- under your control. If a dependency writes messages containing square brackets, it may not produce the intended output.
-
- Args:
- level (Union[int, str], optional): Log level. Defaults to logging.NOTSET.
- console (:class:`~rich.console.Console`, optional): Optional console instance to write logs.
- Default will use a global console instance writing to stdout.
- show_time (bool, optional): Show a column for the time. Defaults to True.
- omit_repeated_times (bool, optional): Omit repetition of the same time. Defaults to True.
- show_level (bool, optional): Show a column for the level. Defaults to True.
- show_path (bool, optional): Show the path to the original log call. Defaults to True.
- enable_link_path (bool, optional): Enable terminal link of path column to file. Defaults to True.
- highlighter (Highlighter, optional): Highlighter to style log messages, or None to use ReprHighlighter. Defaults to None.
- markup (bool, optional): Enable console markup in log messages. Defaults to False.
- rich_tracebacks (bool, optional): Enable rich tracebacks with syntax highlighting and formatting. Defaults to False.
- tracebacks_width (Optional[int], optional): Number of characters used to render tracebacks, or None for full width. Defaults to None.
- tracebacks_extra_lines (int, optional): Additional lines of code to render tracebacks, or None for full width. Defaults to None.
- tracebacks_theme (str, optional): Override pygments theme used in traceback.
- tracebacks_word_wrap (bool, optional): Enable word wrapping of long tracebacks lines. Defaults to True.
- tracebacks_show_locals (bool, optional): Enable display of locals in tracebacks. Defaults to False.
- locals_max_length (int, optional): Maximum length of containers before abbreviating, or None for no abbreviation.
- Defaults to 10.
- locals_max_string (int, optional): Maximum length of string before truncating, or None to disable. Defaults to 80.
- log_time_format (Union[str, TimeFormatterCallable], optional): If ``log_time`` is enabled, either string for strftime or callable that formats the time. Defaults to "[%x %X] ".
- """
-
- KEYWORDS: ClassVar[Optional[List[str]]] = [
- "GET",
- "POST",
- "HEAD",
- "PUT",
- "DELETE",
- "OPTIONS",
- "TRACE",
- "PATCH",
- ]
- HIGHLIGHTER_CLASS: ClassVar[Type[Highlighter]] = ReprHighlighter
-
- def __init__(
- self,
- level: Union[int, str] = logging.NOTSET,
- console: Optional[Console] = None,
- *,
- show_time: bool = True,
- omit_repeated_times: bool = True,
- show_level: bool = True,
- show_path: bool = True,
- enable_link_path: bool = True,
- highlighter: Optional[Highlighter] = None,
- markup: bool = False,
- rich_tracebacks: bool = False,
- tracebacks_width: Optional[int] = None,
- tracebacks_extra_lines: int = 3,
- tracebacks_theme: Optional[str] = None,
- tracebacks_word_wrap: bool = True,
- tracebacks_show_locals: bool = False,
- locals_max_length: int = 10,
- locals_max_string: int = 80,
- log_time_format: Union[str, FormatTimeCallable] = "[%x %X]",
- ) -> None:
- super().__init__(level=level)
- self.console = console or get_console()
- self.highlighter = highlighter or self.HIGHLIGHTER_CLASS()
- self._log_render = LogRender(
- show_time=show_time,
- show_level=show_level,
- show_path=show_path,
- time_format=log_time_format,
- omit_repeated_times=omit_repeated_times,
- level_width=None,
- )
- self.enable_link_path = enable_link_path
- self.markup = markup
- self.rich_tracebacks = rich_tracebacks
- self.tracebacks_width = tracebacks_width
- self.tracebacks_extra_lines = tracebacks_extra_lines
- self.tracebacks_theme = tracebacks_theme
- self.tracebacks_word_wrap = tracebacks_word_wrap
- self.tracebacks_show_locals = tracebacks_show_locals
- self.locals_max_length = locals_max_length
- self.locals_max_string = locals_max_string
-
- def get_level_text(self, record: LogRecord) -> Text:
- """Get the level name from the record.
-
- Args:
- record (LogRecord): LogRecord instance.
-
- Returns:
- Text: A tuple of the style and level name.
- """
- level_name = record.levelname
- level_text = Text.styled(
- level_name.ljust(8), f"logging.level.{level_name.lower()}"
- )
- return level_text
-
- def emit(self, record: LogRecord) -> None:
- """Invoked by logging."""
- message = self.format(record)
- traceback = None
- if (
- self.rich_tracebacks
- and record.exc_info
- and record.exc_info != (None, None, None)
- ):
- exc_type, exc_value, exc_traceback = record.exc_info
- assert exc_type is not None
- assert exc_value is not None
- traceback = Traceback.from_exception(
- exc_type,
- exc_value,
- exc_traceback,
- width=self.tracebacks_width,
- extra_lines=self.tracebacks_extra_lines,
- theme=self.tracebacks_theme,
- word_wrap=self.tracebacks_word_wrap,
- show_locals=self.tracebacks_show_locals,
- locals_max_length=self.locals_max_length,
- locals_max_string=self.locals_max_string,
- )
- message = record.getMessage()
- if self.formatter:
- record.message = record.getMessage()
- formatter = self.formatter
- if hasattr(formatter, "usesTime") and formatter.usesTime():
- record.asctime = formatter.formatTime(record, formatter.datefmt)
- message = formatter.formatMessage(record)
-
- message_renderable = self.render_message(record, message)
- log_renderable = self.render(
- record=record, traceback=traceback, message_renderable=message_renderable
- )
- try:
- self.console.print(log_renderable)
- except Exception:
- self.handleError(record)
-
- def render_message(self, record: LogRecord, message: str) -> "ConsoleRenderable":
- """Render message text in to Text.
-
- record (LogRecord): logging Record.
- message (str): String containing log message.
-
- Returns:
- ConsoleRenderable: Renderable to display log message.
- """
- use_markup = getattr(record, "markup", self.markup)
- message_text = Text.from_markup(message) if use_markup else Text(message)
-
- highlighter = getattr(record, "highlighter", self.highlighter)
- if highlighter:
- message_text = highlighter(message_text)
-
- if self.KEYWORDS:
- message_text.highlight_words(self.KEYWORDS, "logging.keyword")
- return message_text
-
- def render(
- self,
- *,
- record: LogRecord,
- traceback: Optional[Traceback],
- message_renderable: "ConsoleRenderable",
- ) -> "ConsoleRenderable":
- """Render log for display.
-
- Args:
- record (LogRecord): logging Record.
- traceback (Optional[Traceback]): Traceback instance or None for no Traceback.
- message_renderable (ConsoleRenderable): Renderable (typically Text) containing log message contents.
-
- Returns:
- ConsoleRenderable: Renderable to display log.
- """
- path = Path(record.pathname).name
- level = self.get_level_text(record)
- time_format = None if self.formatter is None else self.formatter.datefmt
- log_time = datetime.fromtimestamp(record.created)
-
- log_renderable = self._log_render(
- self.console,
- [message_renderable] if not traceback else [message_renderable, traceback],
- log_time=log_time,
- time_format=time_format,
- level=level,
- path=path,
- line_no=record.lineno,
- link_path=record.pathname if self.enable_link_path else None,
- )
- return log_renderable
-
-
-if __name__ == "__main__": # pragma: no cover
- from time import sleep
-
- FORMAT = "%(message)s"
- # FORMAT = "%(asctime)-15s - %(levelname)s - %(message)s"
- logging.basicConfig(
- level="NOTSET",
- format=FORMAT,
- datefmt="[%X]",
- handlers=[RichHandler(rich_tracebacks=True, tracebacks_show_locals=True)],
- )
- log = logging.getLogger("rich")
-
- log.info("Server starting...")
- log.info("Listening on http://127.0.0.1:8080")
- sleep(1)
-
- log.info("GET /index.html 200 1298")
- log.info("GET /imgs/backgrounds/back1.jpg 200 54386")
- log.info("GET /css/styles.css 200 54386")
- log.warning("GET /favicon.ico 404 242")
- sleep(1)
-
- log.debug(
- "JSONRPC request\n--> %r\n<-- %r",
- {
- "version": "1.1",
- "method": "confirmFruitPurchase",
- "params": [["apple", "orange", "mangoes", "pomelo"], 1.123],
- "id": "194521489",
- },
- {"version": "1.1", "result": True, "error": None, "id": "194521489"},
- )
- log.debug(
- "Loading configuration file /adasd/asdasd/qeqwe/qwrqwrqwr/sdgsdgsdg/werwerwer/dfgerert/ertertert/ertetert/werwerwer"
- )
- log.error("Unable to find 'pomelo' in database!")
- log.info("POST /jsonrpc/ 200 65532")
- log.info("POST /admin/ 401 42234")
- log.warning("password was rejected for admin site.")
-
- def divide() -> None:
- number = 1
- divisor = 0
- foos = ["foo"] * 100
- log.debug("in divide")
- try:
- number / divisor
- except:
- log.exception("An error of some kind occurred!")
-
- divide()
- sleep(1)
- log.critical("Out of memory!")
- log.info("Server exited with code=-1")
- log.info("[bold]EXITING...[/bold]", extra=dict(markup=True))
diff --git a/spaces/allknowingroger/Image-Models-Test133/app.py b/spaces/allknowingroger/Image-Models-Test133/app.py
deleted file mode 100644
index 14bb23526c84b495c090472887f547fca6f8cebc..0000000000000000000000000000000000000000
--- a/spaces/allknowingroger/Image-Models-Test133/app.py
+++ /dev/null
@@ -1,144 +0,0 @@
-import gradio as gr
-# import os
-# import sys
-# from pathlib import Path
-import time
-
-models =[
- "Yacong/cloth1-lora-trained-xl",
- "ai-characters/DarkAndDarker-Style-SDXL",
- "jpull/troy",
- "moonlightnexus/wonder-anime",
- "jasvant27/my-tiger",
- "naresh1107/hitman",
- "rurulemon/lora-trained-xl-colab",
- "Yntec/ClassicEra",
- "digiplay/AM-mix1",
-]
-
-
-model_functions = {}
-model_idx = 1
-for model_path in models:
- try:
- model_functions[model_idx] = gr.Interface.load(f"models/{model_path}", live=False, preprocess=True, postprocess=False)
- except Exception as error:
- def the_fn(txt):
- return None
- model_functions[model_idx] = gr.Interface(fn=the_fn, inputs=["text"], outputs=["image"])
- model_idx+=1
-
-
-def send_it_idx(idx):
- def send_it_fn(prompt):
- output = (model_functions.get(str(idx)) or model_functions.get(str(1)))(prompt)
- return output
- return send_it_fn
-
-def get_prompts(prompt_text):
- return prompt_text
-
-def clear_it(val):
- if int(val) != 0:
- val = 0
- else:
- val = 0
- pass
- return val
-
-def all_task_end(cnt,t_stamp):
- to = t_stamp + 60
- et = time.time()
- if et > to and t_stamp != 0:
- d = gr.update(value=0)
- tog = gr.update(value=1)
- #print(f'to: {to} et: {et}')
- else:
- if cnt != 0:
- d = gr.update(value=et)
- else:
- d = gr.update(value=0)
- tog = gr.update(value=0)
- #print (f'passing: to: {to} et: {et}')
- pass
- return d, tog
-
-def all_task_start():
- print("\n\n\n\n\n\n\n")
- t = time.gmtime()
- t_stamp = time.time()
- current_time = time.strftime("%H:%M:%S", t)
- return gr.update(value=t_stamp), gr.update(value=t_stamp), gr.update(value=0)
-
-def clear_fn():
- nn = len(models)
- return tuple([None, *[None for _ in range(nn)]])
-
-
-
-with gr.Blocks(title="SD Models") as my_interface:
- with gr.Column(scale=12):
- # with gr.Row():
- # gr.Markdown("""- Primary prompt: 你想画的内容(英文单词，如 a cat, 加英文逗号效果更好；点 Improve 按钮进行完善)\n- Real prompt: 完善后的提示词，出现后再点右边的 Run 按钮开始运行""")
- with gr.Row():
- with gr.Row(scale=6):
- primary_prompt=gr.Textbox(label="Prompt", value="")
- # real_prompt=gr.Textbox(label="Real prompt")
- with gr.Row(scale=6):
- # improve_prompts_btn=gr.Button("Improve")
- with gr.Row():
- run=gr.Button("Run",variant="primary")
- clear_btn=gr.Button("Clear")
- with gr.Row():
- sd_outputs = {}
- model_idx = 1
- for model_path in models:
- with gr.Column(scale=3, min_width=320):
- with gr.Box():
- sd_outputs[model_idx] = gr.Image(label=model_path)
- pass
- model_idx += 1
- pass
- pass
-
- with gr.Row(visible=False):
- start_box=gr.Number(interactive=False)
- end_box=gr.Number(interactive=False)
- tog_box=gr.Textbox(value=0,interactive=False)
-
- start_box.change(
- all_task_end,
- [start_box, end_box],
- [start_box, tog_box],
- every=1,
- show_progress=False)
-
- primary_prompt.submit(all_task_start, None, [start_box, end_box, tog_box])
- run.click(all_task_start, None, [start_box, end_box, tog_box])
- runs_dict = {}
- model_idx = 1
- for model_path in models:
- runs_dict[model_idx] = run.click(model_functions[model_idx], inputs=[primary_prompt], outputs=[sd_outputs[model_idx]])
- model_idx += 1
- pass
- pass
-
- # improve_prompts_btn_clicked=improve_prompts_btn.click(
- # get_prompts,
- # inputs=[primary_prompt],
- # outputs=[primary_prompt],
- # cancels=list(runs_dict.values()))
- clear_btn.click(
- clear_fn,
- None,
- [primary_prompt, *list(sd_outputs.values())],
- cancels=[*list(runs_dict.values())])
- tog_box.change(
- clear_it,
- tog_box,
- tog_box,
- cancels=[*list(runs_dict.values())])
-
-my_interface.queue(concurrency_count=600, status_update_rate=1)
-my_interface.launch(inline=True, show_api=False)
-
\ No newline at end of file
diff --git a/spaces/alphunt/diffdock-alphunt-demo/esm/esm/inverse_folding/transformer_decoder.py b/spaces/alphunt/diffdock-alphunt-demo/esm/esm/inverse_folding/transformer_decoder.py
deleted file mode 100644
index fb120eeda5eaf4068459194cd78d459669ece818..0000000000000000000000000000000000000000
--- a/spaces/alphunt/diffdock-alphunt-demo/esm/esm/inverse_folding/transformer_decoder.py
+++ /dev/null
@@ -1,228 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# Contents of this file were adapted from the open source fairseq repository.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import math
-from typing import Any, Dict, List, Optional
-
-import torch
-import torch.nn as nn
-from torch import Tensor
-
-from esm.modules import SinusoidalPositionalEmbedding
-from .transformer_layer import TransformerDecoderLayer
-
-
-def fill_with_neg_inf(t):
- """FP16-compatible function that fills a tensor with -inf."""
- return t.float().fill_(float("-inf")).type_as(t)
-
-
-class TransformerDecoder(nn.Module):
- """
- Transformer decoder consisting of *args.decoder.layers* layers. Each layer
- is a :class:`TransformerDecoderLayer`.
-
- Args:
- args (argparse.Namespace): parsed command-line arguments
- dictionary (~fairseq.data.Dictionary): decoding dictionary
- embed_tokens (torch.nn.Embedding): output embedding
- no_encoder_attn (bool, optional): whether to attend to encoder outputs
- (default: False).
- """
-
- def __init__(
- self,
- args,
- dictionary,
- embed_tokens,
- ):
- super().__init__()
- self.args = args
- self.dictionary = dictionary
- self._future_mask = torch.empty(0)
-
- self.dropout_module = nn.Dropout(args.dropout)
-
- input_embed_dim = embed_tokens.embedding_dim
- embed_dim = args.decoder_embed_dim
- self.embed_dim = embed_dim
-
- self.padding_idx = embed_tokens.padding_idx
-
- self.embed_tokens = embed_tokens
- self.embed_scale = math.sqrt(embed_dim)
-
- self.project_in_dim = (
- nn.Linear(input_embed_dim, embed_dim, bias=False)
- if embed_dim != input_embed_dim
- else None
- )
- self.embed_positions = SinusoidalPositionalEmbedding(
- embed_dim,
- self.padding_idx,
- )
-
- self.layers = nn.ModuleList([])
- self.layers.extend(
- [
- self.build_decoder_layer(args)
- for _ in range(args.decoder_layers)
- ]
- )
- self.num_layers = len(self.layers)
- self.layer_norm = nn.LayerNorm(embed_dim)
-
- self.build_output_projection(args, dictionary)
-
- def build_output_projection(self, args, dictionary):
- self.output_projection = nn.Linear(
- args.decoder_embed_dim, len(dictionary), bias=False
- )
- nn.init.normal_(
- self.output_projection.weight, mean=0, std=args.decoder_embed_dim ** -0.5
- )
-
- def build_decoder_layer(self, args):
- return TransformerDecoderLayer(args)
-
- def forward(
- self,
- prev_output_tokens,
- encoder_out: Optional[Dict[str, List[Tensor]]] = None,
- incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None,
- features_only: bool = False,
- return_all_hiddens: bool = False,
- ):
- """
- Args:
- prev_output_tokens (LongTensor): previous decoder outputs of shape
- `(batch, tgt_len)`, for teacher forcing
- encoder_out (optional): output from the encoder, used for
- encoder-side attention, should be of size T x B x C
- incremental_state (dict): dictionary used for storing state during
- :ref:`Incremental decoding`
- features_only (bool, optional): only return features without
- applying output layer (default: False).
-
- Returns:
- tuple:
- - the decoder's output of shape `(batch, tgt_len, vocab)`
- - a dictionary with any model-specific outputs
- """
-
- x, extra = self.extract_features(
- prev_output_tokens,
- encoder_out=encoder_out,
- incremental_state=incremental_state,
- )
-
- if not features_only:
- x = self.output_layer(x)
- x = x.transpose(1, 2) # B x T x C -> B x C x T
- return x, extra
-
- def extract_features(
- self,
- prev_output_tokens,
- encoder_out: Optional[Dict[str, List[Tensor]]],
- incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None,
- ):
- """
- Similar to *forward* but only return features.
-
- Includes several features from "Jointly Learning to Align and
- Translate with Transformer Models" (Garg et al., EMNLP 2019).
-
- Returns:
- tuple:
- - the decoder's features of shape `(batch, tgt_len, embed_dim)`
- - a dictionary with any model-specific outputs
- """
- bs, slen = prev_output_tokens.size()
-
- enc: Optional[Tensor] = None
- padding_mask: Optional[Tensor] = None
- if encoder_out is not None and len(encoder_out["encoder_out"]) > 0:
- enc = encoder_out["encoder_out"][0]
- assert (
- enc.size()[1] == bs
- ), f"Expected enc.shape == (t, {bs}, c) got {enc.shape}"
- if encoder_out is not None and len(encoder_out["encoder_padding_mask"]) > 0:
- padding_mask = encoder_out["encoder_padding_mask"][0]
-
- # embed positions
- positions = self.embed_positions(
- prev_output_tokens
- )
-
- if incremental_state is not None:
- prev_output_tokens = prev_output_tokens[:, -1:]
- positions = positions[:, -1:]
-
- # embed tokens and positions
- x = self.embed_scale * self.embed_tokens(prev_output_tokens)
-
- if self.project_in_dim is not None:
- x = self.project_in_dim(x)
-
- x += positions
-
- x = self.dropout_module(x)
-
- # B x T x C -> T x B x C
- x = x.transpose(0, 1)
-
- self_attn_padding_mask: Optional[Tensor] = None
- if prev_output_tokens.eq(self.padding_idx).any():
- self_attn_padding_mask = prev_output_tokens.eq(self.padding_idx)
-
- # decoder layers
- attn: Optional[Tensor] = None
- inner_states: List[Optional[Tensor]] = [x]
- for idx, layer in enumerate(self.layers):
- if incremental_state is None:
- self_attn_mask = self.buffered_future_mask(x)
- else:
- self_attn_mask = None
-
- x, layer_attn, _ = layer(
- x,
- enc,
- padding_mask,
- incremental_state,
- self_attn_mask=self_attn_mask,
- self_attn_padding_mask=self_attn_padding_mask,
- need_attn=False,
- need_head_weights=False,
- )
- inner_states.append(x)
-
- if self.layer_norm is not None:
- x = self.layer_norm(x)
-
- # T x B x C -> B x C x T
- x = x.transpose(0, 1)
-
- return x, {"inner_states": inner_states}
-
- def output_layer(self, features):
- """Project features to the vocabulary size."""
- return self.output_projection(features)
-
- def buffered_future_mask(self, tensor):
- dim = tensor.size(0)
- # self._future_mask.device != tensor.device is not working in TorchScript. This is a workaround.
- if (
- self._future_mask.size(0) == 0
- or (not self._future_mask.device == tensor.device)
- or self._future_mask.size(0) < dim
- ):
- self._future_mask = torch.triu(
- fill_with_neg_inf(torch.zeros([dim, dim])), 1
- )
- self._future_mask = self._future_mask.to(tensor)
- return self._future_mask[:dim, :dim]
diff --git a/spaces/altryne/vidtranslator/static/css/main.css b/spaces/altryne/vidtranslator/static/css/main.css
deleted file mode 100644
index a397bedd49dfd92166159c791aa796917d35bdea..0000000000000000000000000000000000000000
--- a/spaces/altryne/vidtranslator/static/css/main.css
+++ /dev/null
@@ -1,97 +0,0 @@
-@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@700&display=swap');
-
-#download_status input[type=checkbox] {
- display: none;
-}
-#download_status label{
- height: 100%;
-}
-.main-title{
- color: #FF7A7A;
- font-family: 'Poppins', sans-serif;
- font-size: 4.5em;
- line-height: 1.25;
- font-weight: 700;
- background-image: linear-gradient(45deg, #695EE6 0%, #FF7A7A 85%);
- -webkit-background-clip: text;
- -webkit-text-fill-color: transparent;
-}
-.secondary{
- color: #FF7A7A;
- font-family: 'Poppins', sans-serif;
- font-size: 2em;
- line-height: 1.25;
- font-weight: 700;
- background-image: linear-gradient(45deg, #695EE6 0%, #FF7A7A 85%);
- -webkit-background-clip: text;
- -webkit-text-fill-color: transparent;
-}
-#submit{
- position: absolute;
- flex:0 !important;
- width: 120px;
- right: 13px;
- top: 40px;
- border-radius: 0 5px 5px 5px !important;
-}
-#url_input{
- font-size: 20px !important;
-}
-#download_status label{
- font-size: 18px !important;
-}
-#second_row>.gr-form{
- border-top-left-radius: 0px !important;
- border-top-right-radius: 0px !important;
-}
-
-#input_row{
- position: relative;
-}
-#url_input_group .gr-form:nth-child(2){
- position:relative
-}
-#url_input textarea{
- font-size: 20px !important;
- }
-
-#source_language{
-flex-grow: revert
-}
-
-#translate_toggle{
-flex-grow: revert;
-min-width: 200px;
-}
-#translate_toggle label{
- height: 100%;
-}
-
-/*
-#translate_toggle{
-position: absolute;
-right: 0;
-width: auto;
-flex: none;
-background: transparent
-}
-*/
-.wrap.absolute{
- position: relative !important;
- opacity: 100% !important;
-}
-
-#fake_ass_group{
- display:none;
- visibility: hidden;
- position:absolute;
- pointer-events: none;
-}
-#output_text label{
- font-size: 20px !important;
- white-space: pre-wrap;
-}
-
-footer{
- /*display: none !important;*/
-}
\ No newline at end of file
diff --git a/spaces/altryne/vidtranslator/utils/apis.py b/spaces/altryne/vidtranslator/utils/apis.py
deleted file mode 100644
index eb3b777de13e49ad8a8ac89c9fb316ee50ffa809..0000000000000000000000000000000000000000
--- a/spaces/altryne/vidtranslator/utils/apis.py
+++ /dev/null
@@ -1,151 +0,0 @@
-import json
-import os
-import pathlib
-import time
-
-from pathlib import Path
-from shutil import rmtree
-
-import anvil.server
-import anvil.media
-import dotenv
-import gradio as gr
-import requests
-from download import download_generator, caption_generator
-
-dotenv.load_dotenv()
-
-@anvil.server.background_task
-@anvil.server.callable
-def call_gradio_api(api_name='test_api', data=()):
- port = os.environ.get('SERVER_PORT', 8111)
- gradio_base_url = os.environ.get('GRADIO_URL', f'http://127.0.0.1:{port}/api/')
- gradio_url = f"{gradio_base_url}{api_name}"
- payload = json.dumps({"data": data})
- headers = {
- 'accept': 'application/json',
- 'Content-Type': 'application/json'
- }
- print(f"Calling {gradio_url} with {payload}")
- resp = requests.request("POST", gradio_url, headers=headers, data=payload)
- print(f"Finished calling gradio API with result")
- print(resp.text)
- if api_name == 'caption':
- return json.loads(resp.text)
- if api_name == 'transcribe_translate':
- return json.loads(resp.text)
- # data = resp.json()['data'][0]
- # data = json.loads(data)
- # return {"status": data['status'], "captions": data['captions'], "language": data['language']}
-
- data = resp.json()['data'][0]
- if data:
- video_path = data[0]
- translated_video = anvil.media.from_file(video_path)
- return {'translated_video': translated_video,
- 'log': data[1],
- 'text': data[2],
- 'language': data[3],
- 'duration': resp.json()['duration']}
-
-def remote_download(url):
- print(f"remote_download: Downloading {url}")
- final_response = ''
- subbed_video_media = None
- whisper_result = None
- for response in download_generator(url):
- if 'whisper_result' in response:
- whisper_result = response.get('whisper_result')
- final_response = response['message']
- print(final_response)
- if 'sub_video' in response:
- subbed_video_media = response['sub_video']
- return subbed_video_media, final_response, whisper_result["text"], whisper_result["language"]
-
-def test_api(url=''):
- print(f'Request from Anvil with URL {url}, faking a long ass request that takes 15 seconds')
- time.sleep(15)
- # fake a long ass request that takes 15 seconds
- # TODO: add a video output here to test how events are done
- # TODO: add an anvil server pingback to show we completed the queue operation
- return f"I've slept for 15 seconds and now I'm done. "
-
-
-def caption(downloadable_url="", uid="", language="Autodetect", override_model_size=""):
- """
- :param media_id: The twitter media ID object
- :param user_id_str: The twitter user ID string
- :param tweet_url: tweet URL can potentially not exist in the future, so we can upload on behalf of the user
- :return:
- """
- status, whisper_result_captions, detected_language = caption_generator(downloadable_url, uid, language, override_model_size)
- anvil.server.launch_background_task('add_captions_to_video', uid, whisper_result_captions)
- return {'status': status, 'message': 'started a background process to upload subtitles to {uid}' }
-
-
-def transcribe_translate(downloadable_url="", uid="", language="Autodetect", override_model_size=""):
- """
- :param media_id: The twitter media ID object
- :param user_id_str: The twitter user ID string
- :param tweet_url: tweet URL can potentially not exist in the future, so we can upload on behalf of the user
- :return:
- """
- status, whisper_result_captions, detected_language = caption_generator(downloadable_url, uid, language, override_model_size)
- return json.dumps({"status": status, "captions": whisper_result_captions, "language": detected_language})
-
-def render_api_elements(url_input, download_status, output_text, sub_video, output_file):
- with gr.Group(elem_id='fake_ass_group') as api_buttons:
- # This is a hack to get APIs registered with the blocks interface
- translate_result = gr.Textbox(visible=False)
- translate_language = gr.Textbox(visible=False)
- gr.Button("API", visible=False)\
- .click(api_name='cleanup_output_dir',
- fn=cleanup_output_dir, queue=True, inputs=[], outputs=[])
- gr.Button("API", visible=False)\
- .click(api_name='test_api', queue=True, fn=test_api, inputs=[url_input], outputs=[])
-
- gr.Button("remote_download", visible=False)\
- .click(api_name='remote_download', queue=True, fn=remote_download, inputs=[url_input], outputs=[download_status, output_text, translate_result, translate_language])
-
- # creating fake elements just make gradio, cause I can't define an API signature like a sane person
-
- gr.Button("caption", visible=False)\
- .click(api_name='caption',
- queue=True,
- fn=caption,
- inputs=[
- gr.Text(label='tweet_url'),
- gr.Text(label='media_uid'),
- gr.Text(label='language (optional)'),
- gr.Dropdown(label='Model Size', choices=['base', 'tiny', 'small', 'medium', 'large']),
- ],
- outputs=[
- gr.Text(label='response_json')
- ])
-
- gr.Button("transcribe_translate", visible=False)\
- .click(api_name='transcribe_translate',
- queue=True,
- fn=transcribe_translate,
- inputs=[
- gr.Text(label='tweet_url'),
- gr.Text(label='media_uid'),
- gr.Text(label='language (optional)'),
- gr.Dropdown(label='Model Size', choices=['base', 'tiny', 'small', 'medium', 'large']),
- ],
- outputs=[
- gr.Text(label='response_json')
- ])
- return api_buttons
-
-
-@anvil.server.callable
-def cleanup_output_dir():
- #make sure we're in the main directory
- os.chdir(pathlib.Path(__file__).parent.parent.absolute())
- #delete the output directory contents
- for path in Path("output").glob("**/*"):
- if path.is_file():
- path.unlink()
- elif path.is_dir():
- rmtree(path)
\ No newline at end of file
diff --git a/spaces/amagastya/SPARK/README.md b/spaces/amagastya/SPARK/README.md
deleted file mode 100644
index b8cf7be9878faf5c768e21a92a2e5cadb9f1f84b..0000000000000000000000000000000000000000
--- a/spaces/amagastya/SPARK/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: SPARK Prompt Assistant
-emoji: ⚡
-colorFrom: blue
-colorTo: yellow
-sdk: docker
-pinned: false
-license: cc-by-nc-nd-4.0
-app_port: 8000
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/annt/mrc_uit_squadv2/retro_reader/models/modeling_electra.py b/spaces/annt/mrc_uit_squadv2/retro_reader/models/modeling_electra.py
deleted file mode 100644
index 68490be9beb873418331bd8ff7efb4507cead26a..0000000000000000000000000000000000000000
--- a/spaces/annt/mrc_uit_squadv2/retro_reader/models/modeling_electra.py
+++ /dev/null
@@ -1,124 +0,0 @@
-import torch
-from torch import nn
-from torch.nn import CrossEntropyLoss
-
-from transformers import (
- ElectraForSequenceClassification as SeqClassification,
- ElectraPreTrainedModel,
- ElectraModel,
- ElectraConfig,
-)
-
-from .modeling_outputs import (
- QuestionAnsweringModelOutput,
- QuestionAnsweringNaModelOutput,
-)
-
-
-class ElectraForSequenceClassification(SeqClassification):
- model_type = "electra"
-
-
-class ElectraForQuestionAnsweringAVPool(ElectraPreTrainedModel):
- config_class = ElectraConfig
- base_model_prefix = "electra"
- model_type = "electra"
-
- def __init__(self, config):
- super(ElectraForQuestionAnsweringAVPool, self).__init__(config)
- self.num_labels = config.num_labels
-
- self.electra = ElectraModel(config)
- self.qa_outputs = nn.Linear(config.hidden_size, config.num_labels)
- self.has_ans = nn.Sequential(
- nn.Dropout(p=config.hidden_dropout_prob),
- nn.Linear(config.hidden_size, 2)
- )
-
- # Initialize weights and apply final processing
- self.post_init()
-
- def forward(
- self,
- input_ids=None,
- attention_mask=None,
- token_type_ids=None,
- position_ids=None,
- head_mask=None,
- inputs_embeds=None,
- start_positions=None,
- end_positions=None,
- is_impossibles=None,
- output_attentions=None,
- output_hidden_states=None,
- return_dict=None,
- ):
- return_dict = return_dict if return_dict is not None else self.config.use_return_dict
-
- discriminator_hidden_states = self.electra(
- input_ids=input_ids,
- attention_mask=attention_mask,
- token_type_ids=token_type_ids,
- position_ids=position_ids,
- head_mask=head_mask,
- inputs_embeds=inputs_embeds,
- output_attentions=output_attentions,
- output_hidden_states=output_hidden_states,
- )
-
- sequence_output = discriminator_hidden_states[0]
-
- logits = self.qa_outputs(sequence_output)
- start_logits, end_logits = logits.split(1, dim=-1)
- start_logits = start_logits.squeeze(-1).contiguous()
- end_logits = end_logits.squeeze(-1).contiguous()
-
- first_word = sequence_output[:, 0, :]
-
- has_logits = self.has_ans(first_word)
-
- total_loss = None
- if (
- start_positions is not None and
- end_positions is not None and
- is_impossibles is not None
- ):
- # If we are on multi-GPU, split add a dimension
- if len(start_positions.size()) > 1:
- start_positions = start_positions.squeeze(-1)
- if len(end_positions.size()) > 1:
- end_positions = end_positions.squeeze(-1)
- if len(is_impossibles.size()) > 1:
- is_impossibles = is_impossibles.squeeze(-1)
- # sometimes the start/end positions are outside our model inputs, we ignore these terms
- ignored_index = start_logits.size(1)
- start_positions.clamp_(0, ignored_index)
- end_positions.clamp_(0, ignored_index)
- is_impossibles.clamp_(0, ignored_index)
-
- loss_fct = CrossEntropyLoss(ignore_index=ignored_index)
- start_loss = loss_fct(start_logits, start_positions)
- end_loss = loss_fct(end_logits, end_positions)
- span_loss = start_loss + end_loss
-
- # Internal Front Verification (I-FV)
- # alpha1 == 1.0, alpha2 == 0.5
- choice_loss = loss_fct(has_logits, is_impossibles.long())
- total_loss = 1.0 * span_loss + 0.5 * choice_loss
-
- if not return_dict:
- output = (
- start_logits,
- end_logits,
- has_logits,
- ) + discriminator_hidden_states[2:] # hidden_states, attentions
- return ((total_loss,) + output) if total_loss is not None else output
-
- return QuestionAnsweringNaModelOutput(
- loss=total_loss,
- start_logits=start_logits,
- end_logits=end_logits,
- has_logits=has_logits,
- hidden_states=discriminator_hidden_states.hidden_states,
- attentions=discriminator_hidden_states.attentions,
- )
\ No newline at end of file
diff --git a/spaces/artificialguybr/video-dubbing/TTS/TTS/utils/samplers.py b/spaces/artificialguybr/video-dubbing/TTS/TTS/utils/samplers.py
deleted file mode 100644
index b08a763a33e40d00a32577e31ffc12b8e228bc46..0000000000000000000000000000000000000000
--- a/spaces/artificialguybr/video-dubbing/TTS/TTS/utils/samplers.py
+++ /dev/null
@@ -1,201 +0,0 @@
-import math
-import random
-from typing import Callable, List, Union
-
-from torch.utils.data.sampler import BatchSampler, Sampler, SubsetRandomSampler
-
-
-class SubsetSampler(Sampler):
- """
- Samples elements sequentially from a given list of indices.
-
- Args:
- indices (list): a sequence of indices
- """
-
- def __init__(self, indices):
- super().__init__(indices)
- self.indices = indices
-
- def __iter__(self):
- return (self.indices[i] for i in range(len(self.indices)))
-
- def __len__(self):
- return len(self.indices)
-
-
-class PerfectBatchSampler(Sampler):
- """
- Samples a mini-batch of indices for a balanced class batching
-
- Args:
- dataset_items(list): dataset items to sample from.
- classes (list): list of classes of dataset_items to sample from.
- batch_size (int): total number of samples to be sampled in a mini-batch.
- num_gpus (int): number of GPU in the data parallel mode.
- shuffle (bool): if True, samples randomly, otherwise samples sequentially.
- drop_last (bool): if True, drops last incomplete batch.
- """
-
- def __init__(
- self,
- dataset_items,
- classes,
- batch_size,
- num_classes_in_batch,
- num_gpus=1,
- shuffle=True,
- drop_last=False,
- label_key="class_name",
- ):
- super().__init__(dataset_items)
- assert (
- batch_size % (num_classes_in_batch * num_gpus) == 0
- ), "Batch size must be divisible by number of classes times the number of data parallel devices (if enabled)."
-
- label_indices = {}
- for idx, item in enumerate(dataset_items):
- label = item[label_key]
- if label not in label_indices.keys():
- label_indices[label] = [idx]
- else:
- label_indices[label].append(idx)
-
- if shuffle:
- self._samplers = [SubsetRandomSampler(label_indices[key]) for key in classes]
- else:
- self._samplers = [SubsetSampler(label_indices[key]) for key in classes]
-
- self._batch_size = batch_size
- self._drop_last = drop_last
- self._dp_devices = num_gpus
- self._num_classes_in_batch = num_classes_in_batch
-
- def __iter__(self):
- batch = []
- if self._num_classes_in_batch != len(self._samplers):
- valid_samplers_idx = random.sample(range(len(self._samplers)), self._num_classes_in_batch)
- else:
- valid_samplers_idx = None
-
- iters = [iter(s) for s in self._samplers]
- done = False
-
- while True:
- b = []
- for i, it in enumerate(iters):
- if valid_samplers_idx is not None and i not in valid_samplers_idx:
- continue
- idx = next(it, None)
- if idx is None:
- done = True
- break
- b.append(idx)
- if done:
- break
- batch += b
- if len(batch) == self._batch_size:
- yield batch
- batch = []
- if valid_samplers_idx is not None:
- valid_samplers_idx = random.sample(range(len(self._samplers)), self._num_classes_in_batch)
-
- if not self._drop_last:
- if len(batch) > 0:
- groups = len(batch) // self._num_classes_in_batch
- if groups % self._dp_devices == 0:
- yield batch
- else:
- batch = batch[: (groups // self._dp_devices) * self._dp_devices * self._num_classes_in_batch]
- if len(batch) > 0:
- yield batch
-
- def __len__(self):
- class_batch_size = self._batch_size // self._num_classes_in_batch
- return min(((len(s) + class_batch_size - 1) // class_batch_size) for s in self._samplers)
-
-
-def identity(x):
- return x
-
-
-class SortedSampler(Sampler):
- """Samples elements sequentially, always in the same order.
-
- Taken from https://github.com/PetrochukM/PyTorch-NLP
-
- Args:
- data (iterable): Iterable data.
- sort_key (callable): Specifies a function of one argument that is used to extract a
- numerical comparison key from each list element.
-
- Example:
- >>> list(SortedSampler(range(10), sort_key=lambda i: -i))
- [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
-
- """
-
- def __init__(self, data, sort_key: Callable = identity):
- super().__init__(data)
- self.data = data
- self.sort_key = sort_key
- zip_ = [(i, self.sort_key(row)) for i, row in enumerate(self.data)]
- zip_ = sorted(zip_, key=lambda r: r[1])
- self.sorted_indexes = [item[0] for item in zip_]
-
- def __iter__(self):
- return iter(self.sorted_indexes)
-
- def __len__(self):
- return len(self.data)
-
-
-class BucketBatchSampler(BatchSampler):
- """Bucket batch sampler
-
- Adapted from https://github.com/PetrochukM/PyTorch-NLP
-
- Args:
- sampler (torch.data.utils.sampler.Sampler):
- batch_size (int): Size of mini-batch.
- drop_last (bool): If `True` the sampler will drop the last batch if its size would be less
- than `batch_size`.
- data (list): List of data samples.
- sort_key (callable, optional): Callable to specify a comparison key for sorting.
- bucket_size_multiplier (int, optional): Buckets are of size
- `batch_size * bucket_size_multiplier`.
-
- Example:
- >>> sampler = WeightedRandomSampler(weights, len(weights))
- >>> sampler = BucketBatchSampler(sampler, data=data_items, batch_size=32, drop_last=True)
- """
-
- def __init__(
- self,
- sampler,
- data,
- batch_size,
- drop_last,
- sort_key: Union[Callable, List] = identity,
- bucket_size_multiplier=100,
- ):
- super().__init__(sampler, batch_size, drop_last)
- self.data = data
- self.sort_key = sort_key
- _bucket_size = batch_size * bucket_size_multiplier
- if hasattr(sampler, "__len__"):
- _bucket_size = min(_bucket_size, len(sampler))
- self.bucket_sampler = BatchSampler(sampler, _bucket_size, False)
-
- def __iter__(self):
- for idxs in self.bucket_sampler:
- bucket_data = [self.data[idx] for idx in idxs]
- sorted_sampler = SortedSampler(bucket_data, self.sort_key)
- for batch_idx in SubsetRandomSampler(list(BatchSampler(sorted_sampler, self.batch_size, self.drop_last))):
- sorted_idxs = [idxs[i] for i in batch_idx]
- yield sorted_idxs
-
- def __len__(self):
- if self.drop_last:
- return len(self.sampler) // self.batch_size
- return math.ceil(len(self.sampler) / self.batch_size)
diff --git a/spaces/artificialguybr/video-dubbing/TTS/recipes/ljspeech/glow_tts/train_glowtts.py b/spaces/artificialguybr/video-dubbing/TTS/recipes/ljspeech/glow_tts/train_glowtts.py
deleted file mode 100644
index 9eb188f8a4db42c6868bdf2e2cf8bbbeedb97cdd..0000000000000000000000000000000000000000
--- a/spaces/artificialguybr/video-dubbing/TTS/recipes/ljspeech/glow_tts/train_glowtts.py
+++ /dev/null
@@ -1,84 +0,0 @@
-import os
-
-# Trainer: Where the ✨️ happens.
-# TrainingArgs: Defines the set of arguments of the Trainer.
-from trainer import Trainer, TrainerArgs
-
-# GlowTTSConfig: all model related values for training, validating and testing.
-from TTS.tts.configs.glow_tts_config import GlowTTSConfig
-
-# BaseDatasetConfig: defines name, formatter and path of the dataset.
-from TTS.tts.configs.shared_configs import BaseDatasetConfig
-from TTS.tts.datasets import load_tts_samples
-from TTS.tts.models.glow_tts import GlowTTS
-from TTS.tts.utils.text.tokenizer import TTSTokenizer
-from TTS.utils.audio import AudioProcessor
-
-# we use the same path as this script as our training folder.
-output_path = os.path.dirname(os.path.abspath(__file__))
-
-# DEFINE DATASET CONFIG
-# Set LJSpeech as our target dataset and define its path.
-# You can also use a simple Dict to define the dataset and pass it to your custom formatter.
-dataset_config = BaseDatasetConfig(
- formatter="ljspeech", meta_file_train="metadata.csv", path=os.path.join(output_path, "../LJSpeech-1.1/")
-)
-
-# INITIALIZE THE TRAINING CONFIGURATION
-# Configure the model. Every config class inherits the BaseTTSConfig.
-config = GlowTTSConfig(
- batch_size=32,
- eval_batch_size=16,
- num_loader_workers=4,
- num_eval_loader_workers=4,
- run_eval=True,
- test_delay_epochs=-1,
- epochs=1000,
- text_cleaner="phoneme_cleaners",
- use_phonemes=True,
- phoneme_language="en-us",
- phoneme_cache_path=os.path.join(output_path, "phoneme_cache"),
- print_step=25,
- print_eval=False,
- mixed_precision=True,
- output_path=output_path,
- datasets=[dataset_config],
-)
-
-# INITIALIZE THE AUDIO PROCESSOR
-# Audio processor is used for feature extraction and audio I/O.
-# It mainly serves to the dataloader and the training loggers.
-ap = AudioProcessor.init_from_config(config)
-
-# INITIALIZE THE TOKENIZER
-# Tokenizer is used to convert text to sequences of token IDs.
-# If characters are not defined in the config, default characters are passed to the config
-tokenizer, config = TTSTokenizer.init_from_config(config)
-
-# LOAD DATA SAMPLES
-# Each sample is a list of ```[text, audio_file_path, speaker_name]```
-# You can define your custom sample loader returning the list of samples.
-# Or define your custom formatter and pass it to the `load_tts_samples`.
-# Check `TTS.tts.datasets.load_tts_samples` for more details.
-train_samples, eval_samples = load_tts_samples(
- dataset_config,
- eval_split=True,
- eval_split_max_size=config.eval_split_max_size,
- eval_split_size=config.eval_split_size,
-)
-
-# INITIALIZE THE MODEL
-# Models take a config object and a speaker manager as input
-# Config defines the details of the model like the number of layers, the size of the embedding, etc.
-# Speaker manager is used by multi-speaker models.
-model = GlowTTS(config, ap, tokenizer, speaker_manager=None)
-
-# INITIALIZE THE TRAINER
-# Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
-# distributed training, etc.
-trainer = Trainer(
- TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
-)
-
-# AND... 3,2,1... 🚀
-trainer.fit()
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ocb.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ocb.py
deleted file mode 100644
index 27758b1198eeeaaafc5c2cbe421e87d767056011..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/Cipher/_mode_ocb.py
+++ /dev/null
@@ -1,525 +0,0 @@
-# ===================================================================
-#
-# Copyright (c) 2014, Legrandin
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-# 1. Redistributions of source code must retain the above copyright
-# notice, this list of conditions and the following disclaimer.
-# 2. 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.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-# ===================================================================
-
-"""
-Offset Codebook (OCB) mode.
-
-OCB is Authenticated Encryption with Associated Data (AEAD) cipher mode
-designed by Prof. Phillip Rogaway and specified in `RFC7253`_.
-
-The algorithm provides both authenticity and privacy, it is very efficient,
-it uses only one key and it can be used in online mode (so that encryption
-or decryption can start before the end of the message is available).
-
-This module implements the third and last variant of OCB (OCB3) and it only
-works in combination with a 128-bit block symmetric cipher, like AES.
-
-OCB is patented in US but `free licenses`_ exist for software implementations
-meant for non-military purposes.
-
-Example:
- >>> from Crypto.Cipher import AES
- >>> from Crypto.Random import get_random_bytes
- >>>
- >>> key = get_random_bytes(32)
- >>> cipher = AES.new(key, AES.MODE_OCB)
- >>> plaintext = b"Attack at dawn"
- >>> ciphertext, mac = cipher.encrypt_and_digest(plaintext)
- >>> # Deliver cipher.nonce, ciphertext and mac
- ...
- >>> cipher = AES.new(key, AES.MODE_OCB, nonce=nonce)
- >>> try:
- >>> plaintext = cipher.decrypt_and_verify(ciphertext, mac)
- >>> except ValueError:
- >>> print "Invalid message"
- >>> else:
- >>> print plaintext
-
-:undocumented: __package__
-
-.. _RFC7253: http://www.rfc-editor.org/info/rfc7253
-.. _free licenses: http://web.cs.ucdavis.edu/~rogaway/ocb/license.htm
-"""
-
-import struct
-from binascii import unhexlify
-
-from Crypto.Util.py3compat import bord, _copy_bytes
-from Crypto.Util.number import long_to_bytes, bytes_to_long
-from Crypto.Util.strxor import strxor
-
-from Crypto.Hash import BLAKE2s
-from Crypto.Random import get_random_bytes
-
-from Crypto.Util._raw_api import (load_pycryptodome_raw_lib, VoidPointer,
- create_string_buffer, get_raw_buffer,
- SmartPointer, c_size_t, c_uint8_ptr,
- is_buffer)
-
-_raw_ocb_lib = load_pycryptodome_raw_lib("Crypto.Cipher._raw_ocb", """
- int OCB_start_operation(void *cipher,
- const uint8_t *offset_0,
- size_t offset_0_len,
- void **pState);
- int OCB_encrypt(void *state,
- const uint8_t *in,
- uint8_t *out,
- size_t data_len);
- int OCB_decrypt(void *state,
- const uint8_t *in,
- uint8_t *out,
- size_t data_len);
- int OCB_update(void *state,
- const uint8_t *in,
- size_t data_len);
- int OCB_digest(void *state,
- uint8_t *tag,
- size_t tag_len);
- int OCB_stop_operation(void *state);
- """)
-
-
-class OcbMode(object):
- """Offset Codebook (OCB) mode.
-
- :undocumented: __init__
- """
-
- def __init__(self, factory, nonce, mac_len, cipher_params):
-
- if factory.block_size != 16:
- raise ValueError("OCB mode is only available for ciphers"
- " that operate on 128 bits blocks")
-
- self.block_size = 16
- """The block size of the underlying cipher, in bytes."""
-
- self.nonce = _copy_bytes(None, None, nonce)
- """Nonce used for this session."""
- if len(nonce) not in range(1, 16):
- raise ValueError("Nonce must be at most 15 bytes long")
- if not is_buffer(nonce):
- raise TypeError("Nonce must be bytes, bytearray or memoryview")
-
- self._mac_len = mac_len
- if not 8 <= mac_len <= 16:
- raise ValueError("MAC tag must be between 8 and 16 bytes long")
-
- # Cache for MAC tag
- self._mac_tag = None
-
- # Cache for unaligned associated data
- self._cache_A = b""
-
- # Cache for unaligned ciphertext/plaintext
- self._cache_P = b""
-
- # Allowed transitions after initialization
- self._next = [self.update, self.encrypt, self.decrypt,
- self.digest, self.verify]
-
- # Compute Offset_0
- params_without_key = dict(cipher_params)
- key = params_without_key.pop("key")
- nonce = (struct.pack('B', self._mac_len << 4 & 0xFF) +
- b'\x00' * (14 - len(nonce)) +
- b'\x01' + self.nonce)
-
- bottom_bits = bord(nonce[15]) & 0x3F # 6 bits, 0..63
- top_bits = bord(nonce[15]) & 0xC0 # 2 bits
-
- ktop_cipher = factory.new(key,
- factory.MODE_ECB,
- **params_without_key)
- ktop = ktop_cipher.encrypt(struct.pack('15sB',
- nonce[:15],
- top_bits))
-
- stretch = ktop + strxor(ktop[:8], ktop[1:9]) # 192 bits
- offset_0 = long_to_bytes(bytes_to_long(stretch) >>
- (64 - bottom_bits), 24)[8:]
-
- # Create low-level cipher instance
- raw_cipher = factory._create_base_cipher(cipher_params)
- if cipher_params:
- raise TypeError("Unknown keywords: " + str(cipher_params))
-
- self._state = VoidPointer()
- result = _raw_ocb_lib.OCB_start_operation(raw_cipher.get(),
- offset_0,
- c_size_t(len(offset_0)),
- self._state.address_of())
- if result:
- raise ValueError("Error %d while instantiating the OCB mode"
- % result)
-
- # Ensure that object disposal of this Python object will (eventually)
- # free the memory allocated by the raw library for the cipher mode
- self._state = SmartPointer(self._state.get(),
- _raw_ocb_lib.OCB_stop_operation)
-
- # Memory allocated for the underlying block cipher is now owed
- # by the cipher mode
- raw_cipher.release()
-
- def _update(self, assoc_data, assoc_data_len):
- result = _raw_ocb_lib.OCB_update(self._state.get(),
- c_uint8_ptr(assoc_data),
- c_size_t(assoc_data_len))
- if result:
- raise ValueError("Error %d while computing MAC in OCB mode" % result)
-
- def update(self, assoc_data):
- """Process the associated data.
-
- If there is any associated data, the caller has to invoke
- this method one or more times, before using
- ``decrypt`` or ``encrypt``.
-
- By *associated data* it is meant any data (e.g. packet headers) that
- will not be encrypted and will be transmitted in the clear.
- However, the receiver shall still able to detect modifications.
-
- If there is no associated data, this method must not be called.
-
- The caller may split associated data in segments of any size, and
- invoke this method multiple times, each time with the next segment.
-
- :Parameters:
- assoc_data : bytes/bytearray/memoryview
- A piece of associated data.
- """
-
- if self.update not in self._next:
- raise TypeError("update() can only be called"
- " immediately after initialization")
-
- self._next = [self.encrypt, self.decrypt, self.digest,
- self.verify, self.update]
-
- if len(self._cache_A) > 0:
- filler = min(16 - len(self._cache_A), len(assoc_data))
- self._cache_A += _copy_bytes(None, filler, assoc_data)
- assoc_data = assoc_data[filler:]
-
- if len(self._cache_A) < 16:
- return self
-
- # Clear the cache, and proceeding with any other aligned data
- self._cache_A, seg = b"", self._cache_A
- self.update(seg)
-
- update_len = len(assoc_data) // 16 * 16
- self._cache_A = _copy_bytes(update_len, None, assoc_data)
- self._update(assoc_data, update_len)
- return self
-
- def _transcrypt_aligned(self, in_data, in_data_len,
- trans_func, trans_desc):
-
- out_data = create_string_buffer(in_data_len)
- result = trans_func(self._state.get(),
- in_data,
- out_data,
- c_size_t(in_data_len))
- if result:
- raise ValueError("Error %d while %sing in OCB mode"
- % (result, trans_desc))
- return get_raw_buffer(out_data)
-
- def _transcrypt(self, in_data, trans_func, trans_desc):
- # Last piece to encrypt/decrypt
- if in_data is None:
- out_data = self._transcrypt_aligned(self._cache_P,
- len(self._cache_P),
- trans_func,
- trans_desc)
- self._cache_P = b""
- return out_data
-
- # Try to fill up the cache, if it already contains something
- prefix = b""
- if len(self._cache_P) > 0:
- filler = min(16 - len(self._cache_P), len(in_data))
- self._cache_P += _copy_bytes(None, filler, in_data)
- in_data = in_data[filler:]
-
- if len(self._cache_P) < 16:
- # We could not manage to fill the cache, so there is certainly
- # no output yet.
- return b""
-
- # Clear the cache, and proceeding with any other aligned data
- prefix = self._transcrypt_aligned(self._cache_P,
- len(self._cache_P),
- trans_func,
- trans_desc)
- self._cache_P = b""
-
- # Process data in multiples of the block size
- trans_len = len(in_data) // 16 * 16
- result = self._transcrypt_aligned(c_uint8_ptr(in_data),
- trans_len,
- trans_func,
- trans_desc)
- if prefix:
- result = prefix + result
-
- # Left-over
- self._cache_P = _copy_bytes(trans_len, None, in_data)
-
- return result
-
- def encrypt(self, plaintext=None):
- """Encrypt the next piece of plaintext.
-
- After the entire plaintext has been passed (but before `digest`),
- you **must** call this method one last time with no arguments to collect
- the final piece of ciphertext.
-
- If possible, use the method `encrypt_and_digest` instead.
-
- :Parameters:
- plaintext : bytes/bytearray/memoryview
- The next piece of data to encrypt or ``None`` to signify
- that encryption has finished and that any remaining ciphertext
- has to be produced.
- :Return:
- the ciphertext, as a byte string.
- Its length may not match the length of the *plaintext*.
- """
-
- if self.encrypt not in self._next:
- raise TypeError("encrypt() can only be called after"
- " initialization or an update()")
-
- if plaintext is None:
- self._next = [self.digest]
- else:
- self._next = [self.encrypt]
- return self._transcrypt(plaintext, _raw_ocb_lib.OCB_encrypt, "encrypt")
-
- def decrypt(self, ciphertext=None):
- """Decrypt the next piece of ciphertext.
-
- After the entire ciphertext has been passed (but before `verify`),
- you **must** call this method one last time with no arguments to collect
- the remaining piece of plaintext.
-
- If possible, use the method `decrypt_and_verify` instead.
-
- :Parameters:
- ciphertext : bytes/bytearray/memoryview
- The next piece of data to decrypt or ``None`` to signify
- that decryption has finished and that any remaining plaintext
- has to be produced.
- :Return:
- the plaintext, as a byte string.
- Its length may not match the length of the *ciphertext*.
- """
-
- if self.decrypt not in self._next:
- raise TypeError("decrypt() can only be called after"
- " initialization or an update()")
-
- if ciphertext is None:
- self._next = [self.verify]
- else:
- self._next = [self.decrypt]
- return self._transcrypt(ciphertext,
- _raw_ocb_lib.OCB_decrypt,
- "decrypt")
-
- def _compute_mac_tag(self):
-
- if self._mac_tag is not None:
- return
-
- if self._cache_A:
- self._update(self._cache_A, len(self._cache_A))
- self._cache_A = b""
-
- mac_tag = create_string_buffer(16)
- result = _raw_ocb_lib.OCB_digest(self._state.get(),
- mac_tag,
- c_size_t(len(mac_tag))
- )
- if result:
- raise ValueError("Error %d while computing digest in OCB mode"
- % result)
- self._mac_tag = get_raw_buffer(mac_tag)[:self._mac_len]
-
- def digest(self):
- """Compute the *binary* MAC tag.
-
- Call this method after the final `encrypt` (the one with no arguments)
- to obtain the MAC tag.
-
- The MAC tag is needed by the receiver to determine authenticity
- of the message.
-
- :Return: the MAC, as a byte string.
- """
-
- if self.digest not in self._next:
- raise TypeError("digest() cannot be called now for this cipher")
-
- assert(len(self._cache_P) == 0)
-
- self._next = [self.digest]
-
- if self._mac_tag is None:
- self._compute_mac_tag()
-
- return self._mac_tag
-
- def hexdigest(self):
- """Compute the *printable* MAC tag.
-
- This method is like `digest`.
-
- :Return: the MAC, as a hexadecimal string.
- """
- return "".join(["%02x" % bord(x) for x in self.digest()])
-
- def verify(self, received_mac_tag):
- """Validate the *binary* MAC tag.
-
- Call this method after the final `decrypt` (the one with no arguments)
- to check if the message is authentic and valid.
-
- :Parameters:
- received_mac_tag : bytes/bytearray/memoryview
- This is the *binary* MAC, as received from the sender.
- :Raises ValueError:
- if the MAC does not match. The message has been tampered with
- or the key is incorrect.
- """
-
- if self.verify not in self._next:
- raise TypeError("verify() cannot be called now for this cipher")
-
- assert(len(self._cache_P) == 0)
-
- self._next = [self.verify]
-
- if self._mac_tag is None:
- self._compute_mac_tag()
-
- secret = get_random_bytes(16)
- mac1 = BLAKE2s.new(digest_bits=160, key=secret, data=self._mac_tag)
- mac2 = BLAKE2s.new(digest_bits=160, key=secret, data=received_mac_tag)
-
- if mac1.digest() != mac2.digest():
- raise ValueError("MAC check failed")
-
- def hexverify(self, hex_mac_tag):
- """Validate the *printable* MAC tag.
-
- This method is like `verify`.
-
- :Parameters:
- hex_mac_tag : string
- This is the *printable* MAC, as received from the sender.
- :Raises ValueError:
- if the MAC does not match. The message has been tampered with
- or the key is incorrect.
- """
-
- self.verify(unhexlify(hex_mac_tag))
-
- def encrypt_and_digest(self, plaintext):
- """Encrypt the message and create the MAC tag in one step.
-
- :Parameters:
- plaintext : bytes/bytearray/memoryview
- The entire message to encrypt.
- :Return:
- a tuple with two byte strings:
-
- - the encrypted data
- - the MAC
- """
-
- return self.encrypt(plaintext) + self.encrypt(), self.digest()
-
- def decrypt_and_verify(self, ciphertext, received_mac_tag):
- """Decrypted the message and verify its authenticity in one step.
-
- :Parameters:
- ciphertext : bytes/bytearray/memoryview
- The entire message to decrypt.
- received_mac_tag : byte string
- This is the *binary* MAC, as received from the sender.
-
- :Return: the decrypted data (byte string).
- :Raises ValueError:
- if the MAC does not match. The message has been tampered with
- or the key is incorrect.
- """
-
- plaintext = self.decrypt(ciphertext) + self.decrypt()
- self.verify(received_mac_tag)
- return plaintext
-
-
-def _create_ocb_cipher(factory, **kwargs):
- """Create a new block cipher, configured in OCB mode.
-
- :Parameters:
- factory : module
- A symmetric cipher module from `Crypto.Cipher`
- (like `Crypto.Cipher.AES`).
-
- :Keywords:
- nonce : bytes/bytearray/memoryview
- A value that must never be reused for any other encryption.
- Its length can vary from 1 to 15 bytes.
- If not specified, a random 15 bytes long nonce is generated.
-
- mac_len : integer
- Length of the MAC, in bytes.
- It must be in the range ``[8..16]``.
- The default is 16 (128 bits).
-
- Any other keyword will be passed to the underlying block cipher.
- See the relevant documentation for details (at least ``key`` will need
- to be present).
- """
-
- try:
- nonce = kwargs.pop("nonce", None)
- if nonce is None:
- nonce = get_random_bytes(15)
- mac_len = kwargs.pop("mac_len", 16)
- except KeyError as e:
- raise TypeError("Keyword missing: " + str(e))
-
- return OcbMode(factory, nonce, mac_len, kwargs)
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/SelfTest/loader.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/SelfTest/loader.py
deleted file mode 100644
index 18be270d1a6e7d52494741af40a30cf25f92b5bf..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Crypto/SelfTest/loader.py
+++ /dev/null
@@ -1,206 +0,0 @@
-# ===================================================================
-#
-# Copyright (c) 2016, Legrandin
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-# 1. Redistributions of source code must retain the above copyright
-# notice, this list of conditions and the following disclaimer.
-# 2. 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.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-# ===================================================================
-
-import os
-import re
-import json
-import errno
-import binascii
-import warnings
-from binascii import unhexlify
-from Crypto.Util.py3compat import FileNotFoundError
-
-
-try:
- import pycryptodome_test_vectors # type: ignore
- test_vectors_available = True
-except ImportError:
- test_vectors_available = False
-
-
-def _load_tests(dir_comps, file_in, description, conversions):
- """Load and parse a test vector file
-
- Return a list of objects, one per group of adjacent
- KV lines or for a single line in the form "[.*]".
-
- For a group of lines, the object has one attribute per line.
- """
-
- line_number = 0
- results = []
-
- class TestVector(object):
- def __init__(self, description, count):
- self.desc = description
- self.count = count
- self.others = []
-
- test_vector = None
- count = 0
- new_group = True
-
- while True:
- line_number += 1
- line = file_in.readline()
- if not line:
- if test_vector is not None:
- results.append(test_vector)
- break
- line = line.strip()
-
- # Skip comments and empty lines
- if line.startswith('#') or not line:
- new_group = True
- continue
-
- if line.startswith("["):
- if test_vector is not None:
- results.append(test_vector)
- test_vector = None
- results.append(line)
- continue
-
- if new_group:
- count += 1
- new_group = False
- if test_vector is not None:
- results.append(test_vector)
- test_vector = TestVector("%s (#%d)" % (description, count), count)
-
- res = re.match("([A-Za-z0-9]+) = ?(.*)", line)
- if not res:
- test_vector.others += [line]
- else:
- token = res.group(1).lower()
- data = res.group(2).lower()
-
- conversion = conversions.get(token, None)
- if conversion is None:
- if len(data) % 2 != 0:
- data = "0" + data
- setattr(test_vector, token, binascii.unhexlify(data))
- else:
- setattr(test_vector, token, conversion(data))
-
- # This line is ignored
- return results
-
-
-def load_test_vectors(dir_comps, file_name, description, conversions):
- """Load and parse a test vector file
-
- This function returns a list of objects, one per group of adjacent
- KV lines or for a single line in the form "[.*]".
-
- For a group of lines, the object has one attribute per line.
- """
-
- results = None
-
- try:
- if not test_vectors_available:
- raise FileNotFoundError(errno.ENOENT,
- os.strerror(errno.ENOENT),
- file_name)
-
- description = "%s test (%s)" % (description, file_name)
-
- init_dir = os.path.dirname(pycryptodome_test_vectors.__file__)
- full_file_name = os.path.join(os.path.join(init_dir, *dir_comps), file_name)
- with open(full_file_name) as file_in:
- results = _load_tests(dir_comps, file_in, description, conversions)
-
- except FileNotFoundError:
- warnings.warn("Warning: skipping extended tests for " + description,
- UserWarning,
- stacklevel=2)
-
- return results
-
-
-def load_test_vectors_wycheproof(dir_comps, file_name, description,
- root_tag={}, group_tag={}, unit_tag={}):
-
- result = []
- try:
- if not test_vectors_available:
- raise FileNotFoundError(errno.ENOENT,
- os.strerror(errno.ENOENT),
- file_name)
-
- init_dir = os.path.dirname(pycryptodome_test_vectors.__file__)
- full_file_name = os.path.join(os.path.join(init_dir, *dir_comps), file_name)
- with open(full_file_name) as file_in:
- tv_tree = json.load(file_in)
-
- except FileNotFoundError:
- warnings.warn("Warning: skipping extended tests for " + description,
- UserWarning,
- stacklevel=2)
- return result
-
- class TestVector(object):
- pass
-
- common_root = {}
- for k, v in root_tag.items():
- common_root[k] = v(tv_tree)
-
- for group in tv_tree['testGroups']:
-
- common_group = {}
- for k, v in group_tag.items():
- common_group[k] = v(group)
-
- for test in group['tests']:
- tv = TestVector()
-
- for k, v in common_root.items():
- setattr(tv, k, v)
- for k, v in common_group.items():
- setattr(tv, k, v)
-
- tv.id = test['tcId']
- tv.comment = test['comment']
- for attr in 'key', 'iv', 'aad', 'msg', 'ct', 'tag', 'label', 'ikm', 'salt', 'info', 'okm', 'sig':
- if attr in test:
- setattr(tv, attr, unhexlify(test[attr]))
- tv.filename = file_name
-
- for k, v in unit_tag.items():
- setattr(tv, k, v(test))
-
- tv.valid = test['result'] != "invalid"
- tv.warning = test['result'] == "acceptable"
- result.append(tv)
-
- return result
-
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/line_chart_with_generator.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/line_chart_with_generator.py
deleted file mode 100644
index 096c2489c7074f3fb08f32a4f12efd148cc96616..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/line_chart_with_generator.py
+++ /dev/null
@@ -1,21 +0,0 @@
-"""
-Line Chart with Sequence Generator
-----------------------------------
-This examples shows how to create multiple lines using the sequence generator.
-"""
-# category: line charts
-
-import altair as alt
-
-source = alt.sequence(start=0, stop=12.7, step=0.1, as_='x')
-
-alt.Chart(source).mark_line().transform_calculate(
- sin='sin(datum.x)',
- cos='cos(datum.x)'
-).transform_fold(
- ['sin', 'cos']
-).encode(
- x='x:Q',
- y='value:Q',
- color='key:N'
-)
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/anyio/_core/_tasks.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/anyio/_core/_tasks.py
deleted file mode 100644
index f24764cfe6be0071eed8655a657d9f6a5ab75803..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/anyio/_core/_tasks.py
+++ /dev/null
@@ -1,178 +0,0 @@
-import math
-from types import TracebackType
-from typing import Optional, Type
-from warnings import warn
-
-from ..abc._tasks import TaskGroup, TaskStatus
-from ._compat import (
- DeprecatedAsyncContextManager,
- DeprecatedAwaitable,
- DeprecatedAwaitableFloat,
-)
-from ._eventloop import get_asynclib
-
-
-class _IgnoredTaskStatus(TaskStatus):
- def started(self, value: object = None) -> None:
- pass
-
-
-TASK_STATUS_IGNORED = _IgnoredTaskStatus()
-
-
-class CancelScope(DeprecatedAsyncContextManager["CancelScope"]):
- """
- Wraps a unit of work that can be made separately cancellable.
-
- :param deadline: The time (clock value) when this scope is cancelled automatically
- :param shield: ``True`` to shield the cancel scope from external cancellation
- """
-
- def __new__(
- cls, *, deadline: float = math.inf, shield: bool = False
- ) -> "CancelScope":
- return get_asynclib().CancelScope(shield=shield, deadline=deadline)
-
- def cancel(self) -> DeprecatedAwaitable:
- """Cancel this scope immediately."""
- raise NotImplementedError
-
- @property
- def deadline(self) -> float:
- """
- The time (clock value) when this scope is cancelled automatically.
-
- Will be ``float('inf')`` if no timeout has been set.
-
- """
- raise NotImplementedError
-
- @deadline.setter
- def deadline(self, value: float) -> None:
- raise NotImplementedError
-
- @property
- def cancel_called(self) -> bool:
- """``True`` if :meth:`cancel` has been called."""
- raise NotImplementedError
-
- @property
- def shield(self) -> bool:
- """
- ``True`` if this scope is shielded from external cancellation.
-
- While a scope is shielded, it will not receive cancellations from outside.
-
- """
- raise NotImplementedError
-
- @shield.setter
- def shield(self, value: bool) -> None:
- raise NotImplementedError
-
- def __enter__(self) -> "CancelScope":
- raise NotImplementedError
-
- def __exit__(
- self,
- exc_type: Optional[Type[BaseException]],
- exc_val: Optional[BaseException],
- exc_tb: Optional[TracebackType],
- ) -> Optional[bool]:
- raise NotImplementedError
-
-
-def open_cancel_scope(*, shield: bool = False) -> CancelScope:
- """
- Open a cancel scope.
-
- :param shield: ``True`` to shield the cancel scope from external cancellation
- :return: a cancel scope
-
- .. deprecated:: 3.0
- Use :class:`~CancelScope` directly.
-
- """
- warn(
- "open_cancel_scope() is deprecated -- use CancelScope() directly",
- DeprecationWarning,
- )
- return get_asynclib().CancelScope(shield=shield)
-
-
-class FailAfterContextManager(DeprecatedAsyncContextManager[CancelScope]):
- def __init__(self, cancel_scope: CancelScope):
- self._cancel_scope = cancel_scope
-
- def __enter__(self) -> CancelScope:
- return self._cancel_scope.__enter__()
-
- def __exit__(
- self,
- exc_type: Optional[Type[BaseException]],
- exc_val: Optional[BaseException],
- exc_tb: Optional[TracebackType],
- ) -> Optional[bool]:
- retval = self._cancel_scope.__exit__(exc_type, exc_val, exc_tb)
- if self._cancel_scope.cancel_called:
- raise TimeoutError
-
- return retval
-
-
-def fail_after(delay: Optional[float], shield: bool = False) -> FailAfterContextManager:
- """
- Create a context manager which raises a :class:`TimeoutError` if does not finish in time.
-
- :param delay: maximum allowed time (in seconds) before raising the exception, or ``None`` to
- disable the timeout
- :param shield: ``True`` to shield the cancel scope from external cancellation
- :return: a context manager that yields a cancel scope
- :rtype: :class:`~typing.ContextManager`\\[:class:`~anyio.abc.CancelScope`\\]
-
- """
- deadline = (
- (get_asynclib().current_time() + delay) if delay is not None else math.inf
- )
- cancel_scope = get_asynclib().CancelScope(deadline=deadline, shield=shield)
- return FailAfterContextManager(cancel_scope)
-
-
-def move_on_after(delay: Optional[float], shield: bool = False) -> CancelScope:
- """
- Create a cancel scope with a deadline that expires after the given delay.
-
- :param delay: maximum allowed time (in seconds) before exiting the context block, or ``None``
- to disable the timeout
- :param shield: ``True`` to shield the cancel scope from external cancellation
- :return: a cancel scope
-
- """
- deadline = (
- (get_asynclib().current_time() + delay) if delay is not None else math.inf
- )
- return get_asynclib().CancelScope(deadline=deadline, shield=shield)
-
-
-def current_effective_deadline() -> DeprecatedAwaitableFloat:
- """
- Return the nearest deadline among all the cancel scopes effective for the current task.
-
- :return: a clock value from the event loop's internal clock (``float('inf')`` if there is no
- deadline in effect)
- :rtype: float
-
- """
- return DeprecatedAwaitableFloat(
- get_asynclib().current_effective_deadline(), current_effective_deadline
- )
-
-
-def create_task_group() -> "TaskGroup":
- """
- Create a task group.
-
- :return: a task group
-
- """
- return get_asynclib().TaskGroup()
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/dictionary.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/dictionary.py
deleted file mode 100644
index d6495389f0102156f0b2dc6f892946d572911bbe..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/dictionary.py
+++ /dev/null
@@ -1,401 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import os
-from collections import Counter
-from multiprocessing import Pool
-
-import torch
-from fairseq import utils
-from fairseq.data import data_utils
-from fairseq.file_chunker_utils import Chunker, find_offsets
-from fairseq.file_io import PathManager
-from fairseq.tokenizer import tokenize_line
-
-
-class Dictionary:
- """A mapping from symbols to consecutive integers"""
-
- def __init__(
- self,
- *, # begin keyword-only arguments
- bos="",
- pad="",
- eos=" ",
- unk="",
- extra_special_symbols=None,
- ):
- self.bos_word, self.unk_word, self.pad_word, self.eos_word = bos, unk, pad, eos
- self.symbols = []
- self.count = []
- self.indices = {}
- self.bos_index = self.add_symbol(bos)
- self.pad_index = self.add_symbol(pad)
- self.eos_index = self.add_symbol(eos)
- self.unk_index = self.add_symbol(unk)
- if extra_special_symbols:
- for s in extra_special_symbols:
- self.add_symbol(s)
- self.nspecial = len(self.symbols)
-
- def __eq__(self, other):
- return self.indices == other.indices
-
- def __getitem__(self, idx):
- if idx < len(self.symbols):
- return self.symbols[idx]
- return self.unk_word
-
- def get_count(self, idx):
- return self.count[idx]
-
- def __len__(self):
- """Returns the number of symbols in the dictionary"""
- return len(self.symbols)
-
- def __contains__(self, sym):
- return sym in self.indices
-
- def index(self, sym):
- """Returns the index of the specified symbol"""
- assert isinstance(sym, str)
- if sym in self.indices:
- return self.indices[sym]
- return self.unk_index
-
- def string(
- self,
- tensor,
- bpe_symbol=None,
- escape_unk=False,
- extra_symbols_to_ignore=None,
- unk_string=None,
- include_eos=False,
- separator=" ",
- ):
- """Helper for converting a tensor of token indices to a string.
-
- Can optionally remove BPE symbols or escape words.
- """
- if torch.is_tensor(tensor) and tensor.dim() == 2:
- return "\n".join(
- self.string(
- t,
- bpe_symbol,
- escape_unk,
- extra_symbols_to_ignore,
- include_eos=include_eos,
- )
- for t in tensor
- )
-
- extra_symbols_to_ignore = set(extra_symbols_to_ignore or [])
- if not include_eos:
- extra_symbols_to_ignore.add(self.eos())
-
- def token_string(i):
- if i == self.unk():
- if unk_string is not None:
- return unk_string
- else:
- return self.unk_string(escape_unk)
- else:
- return self[i]
-
- if hasattr(self, "bos_index"):
- extra_symbols_to_ignore.add(self.bos())
-
- sent = separator.join(
- token_string(i)
- for i in tensor
- if utils.item(i) not in extra_symbols_to_ignore
- )
-
- return data_utils.post_process(sent, bpe_symbol)
-
- def unk_string(self, escape=False):
- """Return unknown string, optionally escaped as: <>"""
- if escape:
- return "<{}>".format(self.unk_word)
- else:
- return self.unk_word
-
- def add_symbol(self, word, n=1, overwrite=False):
- """Adds a word to the dictionary"""
- if word in self.indices and not overwrite:
- idx = self.indices[word]
- self.count[idx] = self.count[idx] + n
- return idx
- else:
- idx = len(self.symbols)
- self.indices[word] = idx
- self.symbols.append(word)
- self.count.append(n)
- return idx
-
- def update(self, new_dict):
- """Updates counts from new dictionary."""
- for word in new_dict.symbols:
- idx2 = new_dict.indices[word]
- if word in self.indices:
- idx = self.indices[word]
- self.count[idx] = self.count[idx] + new_dict.count[idx2]
- else:
- idx = len(self.symbols)
- self.indices[word] = idx
- self.symbols.append(word)
- self.count.append(new_dict.count[idx2])
-
- def finalize(self, threshold=-1, nwords=-1, padding_factor=8):
- """Sort symbols by frequency in descending order, ignoring special ones.
-
- Args:
- - threshold defines the minimum word count
- - nwords defines the total number of words in the final dictionary,
- including special symbols
- - padding_factor can be used to pad the dictionary size to be a
- multiple of 8, which is important on some hardware (e.g., Nvidia
- Tensor Cores).
- """
- if nwords <= 0:
- nwords = len(self)
-
- new_indices = dict(zip(self.symbols[: self.nspecial], range(self.nspecial)))
- new_symbols = self.symbols[: self.nspecial]
- new_count = self.count[: self.nspecial]
-
- c = Counter(
- dict(
- sorted(zip(self.symbols[self.nspecial :], self.count[self.nspecial :]))
- )
- )
- for symbol, count in c.most_common(nwords - self.nspecial):
- if count >= threshold:
- new_indices[symbol] = len(new_symbols)
- new_symbols.append(symbol)
- new_count.append(count)
- else:
- break
-
- assert len(new_symbols) == len(new_indices)
-
- self.count = list(new_count)
- self.symbols = list(new_symbols)
- self.indices = new_indices
-
- self.pad_to_multiple_(padding_factor)
-
- def pad_to_multiple_(self, padding_factor):
- """Pad Dictionary size to be a multiple of *padding_factor*."""
- if padding_factor > 1:
- i = 0
- while len(self) % padding_factor != 0:
- symbol = "madeupword{:04d}".format(i)
- self.add_symbol(symbol, n=0)
- i += 1
-
- def bos(self):
- """Helper to get index of beginning-of-sentence symbol"""
- return self.bos_index
-
- def pad(self):
- """Helper to get index of pad symbol"""
- return self.pad_index
-
- def eos(self):
- """Helper to get index of end-of-sentence symbol"""
- return self.eos_index
-
- def unk(self):
- """Helper to get index of unk symbol"""
- return self.unk_index
-
- @classmethod
- def load(cls, f):
- """Loads the dictionary from a text file with the format:
-
- ```
-
-
- ...
- ```
- """
- d = cls()
- d.add_from_file(f)
- return d
-
- def add_from_file(self, f):
- """
- Loads a pre-existing dictionary from a text file and adds its symbols
- to this instance.
- """
- if isinstance(f, str):
- try:
- with open(PathManager.get_local_path(f), "r", encoding="utf-8") as fd:
- self.add_from_file(fd)
- except FileNotFoundError as fnfe:
- raise fnfe
- except UnicodeError:
- raise Exception(
- "Incorrect encoding detected in {}, please "
- "rebuild the dataset".format(f)
- )
- return
-
- lines = f.readlines()
- indices_start_line = self._load_meta(lines)
-
- for line in lines[indices_start_line:]:
- try:
- line, field = line.rstrip().rsplit(" ", 1)
- if field == "#fairseq:overwrite":
- overwrite = True
- line, field = line.rsplit(" ", 1)
- else:
- overwrite = False
- count = int(field)
- word = line
- if word in self and not overwrite:
- raise RuntimeError(
- "Duplicate word found when loading Dictionary: '{}'. "
- "Duplicate words can overwrite earlier ones by adding the "
- "#fairseq:overwrite flag at the end of the corresponding row "
- "in the dictionary file. If using the Camembert model, please "
- "download an updated copy of the model file.".format(word)
- )
- self.add_symbol(word, n=count, overwrite=overwrite)
- except ValueError:
- raise ValueError(
- f"Incorrect dictionary format, expected ' [flags]': \"{line}\""
- )
-
- def _save(self, f, kv_iterator):
- if isinstance(f, str):
- PathManager.mkdirs(os.path.dirname(f))
- with PathManager.open(f, "w", encoding="utf-8") as fd:
- return self.save(fd)
- for k, v in kv_iterator:
- print("{} {}".format(k, v), file=f)
-
- def _get_meta(self):
- return [], []
-
- def _load_meta(self, lines):
- return 0
-
- def save(self, f):
- """Stores dictionary into a text file"""
- ex_keys, ex_vals = self._get_meta()
- self._save(
- f,
- zip(
- ex_keys + self.symbols[self.nspecial :],
- ex_vals + self.count[self.nspecial :],
- ),
- )
-
- def dummy_sentence(self, length):
- t = torch.Tensor(length).uniform_(self.nspecial + 1, len(self)).long()
- t[-1] = self.eos()
- return t
-
- def encode_line(
- self,
- line,
- line_tokenizer=tokenize_line,
- add_if_not_exist=True,
- consumer=None,
- append_eos=True,
- reverse_order=False,
- ) -> torch.IntTensor:
- words = line_tokenizer(line)
- if reverse_order:
- words = list(reversed(words))
- nwords = len(words)
- ids = torch.IntTensor(nwords + 1 if append_eos else nwords)
-
- for i, word in enumerate(words):
- if add_if_not_exist:
- idx = self.add_symbol(word)
- else:
- idx = self.index(word)
- if consumer is not None:
- consumer(word, idx)
- ids[i] = idx
- if append_eos:
- ids[nwords] = self.eos_index
- return ids
-
- @staticmethod
- def _add_file_to_dictionary_single_worker(
- filename,
- tokenize,
- eos_word,
- start_offset,
- end_offset,
- ):
- counter = Counter()
- with Chunker(filename, start_offset, end_offset) as line_iterator:
- for line in line_iterator:
- for word in tokenize(line):
- counter.update([word])
- counter.update([eos_word])
- return counter
-
- @staticmethod
- def add_file_to_dictionary(filename, dict, tokenize, num_workers):
- def merge_result(counter):
- for w, c in sorted(counter.items()):
- dict.add_symbol(w, c)
-
- local_file = PathManager.get_local_path(filename)
- offsets = find_offsets(local_file, num_workers)
- if num_workers > 1:
- chunks = zip(offsets, offsets[1:])
- pool = Pool(processes=num_workers)
- results = []
- for (start_offset, end_offset) in chunks:
- results.append(
- pool.apply_async(
- Dictionary._add_file_to_dictionary_single_worker,
- (
- local_file,
- tokenize,
- dict.eos_word,
- start_offset,
- end_offset,
- ),
- )
- )
- pool.close()
- pool.join()
- for r in results:
- merge_result(r.get())
- else:
- merge_result(
- Dictionary._add_file_to_dictionary_single_worker(
- local_file, tokenize, dict.eos_word, offsets[0], offsets[1]
- )
- )
-
-
-class TruncatedDictionary(object):
- def __init__(self, wrapped_dict, length):
- self.__class__ = type(
- wrapped_dict.__class__.__name__,
- (self.__class__, wrapped_dict.__class__),
- {},
- )
- self.__dict__ = wrapped_dict.__dict__
- self.wrapped_dict = wrapped_dict
- self.length = min(len(self.wrapped_dict), length)
-
- def __len__(self):
- return self.length
-
- def __getitem__(self, i):
- if i < self.length:
- return self.wrapped_dict[i]
- return self.wrapped_dict.unk()
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/subsample_dataset.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/subsample_dataset.py
deleted file mode 100644
index 48feaf883f87dc95f8637c24d3c96f3f9fd8bd1d..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/subsample_dataset.py
+++ /dev/null
@@ -1,72 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import logging
-
-import numpy as np
-
-from . import BaseWrapperDataset
-
-
-logger = logging.getLogger(__name__)
-
-
-class SubsampleDataset(BaseWrapperDataset):
- """Subsamples a given dataset by a specified ratio. Subsampling is done on the number of examples
-
- Args:
- dataset (~torch.utils.data.Dataset): dataset to subsample
- size_ratio(float): the ratio to subsample to. must be between 0 and 1 (exclusive)
- """
-
- def __init__(self, dataset, size_ratio, shuffle=False):
- super().__init__(dataset)
- assert size_ratio < 1
- self.actual_size = np.ceil(len(dataset) * size_ratio).astype(int)
- self.indices = np.random.choice(
- list(range(len(self.dataset))), self.actual_size, replace=False
- )
- self.shuffle = shuffle
- logger.info(
- "subsampled dataset from {} to {} (ratio={})".format(
- len(self.dataset), self.actual_size, size_ratio
- )
- )
-
- def __getitem__(self, index):
- return self.dataset[self.indices[index]]
-
- def __len__(self):
- return self.actual_size
-
- def collater(self, samples):
- return self.dataset.collater(samples)
-
- @property
- def sizes(self):
- return self.dataset.sizes[self.indices]
-
- @property
- def name(self):
- return self.dataset.name
-
- def num_tokens(self, index):
- return self.dataset.num_tokens(self.indices[index])
-
- def size(self, index):
- return self.dataset.size(self.indices[index])
-
- def ordered_indices(self):
- """Return an ordered list of indices. Batches will be constructed based
- on this order."""
- if self.shuffle:
- order = [np.random.permutation(len(self))]
- else:
- order = [np.arange(len(self))]
- order.append(self.sizes)
- return np.lexsort(order)
-
- def prefetch(self, indices):
- self.dataset.prefetch(self.indices[indices])
diff --git a/spaces/asafAdge/Detic/detic/data/datasets/lvis_22k_categories.py b/spaces/asafAdge/Detic/detic/data/datasets/lvis_22k_categories.py
deleted file mode 100644
index 9525f0873d68d84dd691979c32eaadd7860f59fe..0000000000000000000000000000000000000000
--- a/spaces/asafAdge/Detic/detic/data/datasets/lvis_22k_categories.py
+++ /dev/null
@@ -1 +0,0 @@
-CATEGORIES = [{'name': 'aerosol_can', 'id': 1, 'frequency': 'c', 'synset': 'aerosol.n.02'}, {'name': 'air_conditioner', 'id': 2, 'frequency': 'f', 'synset': 'air_conditioner.n.01'}, {'name': 'airplane', 'id': 3, 'frequency': 'f', 'synset': 'airplane.n.01'}, {'name': 'alarm_clock', 'id': 4, 'frequency': 'f', 'synset': 'alarm_clock.n.01'}, {'name': 'alcohol', 'id': 5, 'frequency': 'c', 'synset': 'alcohol.n.01'}, {'name': 'alligator', 'id': 6, 'frequency': 'c', 'synset': 'alligator.n.02'}, {'name': 'almond', 'id': 7, 'frequency': 'c', 'synset': 'almond.n.02'}, {'name': 'ambulance', 'id': 8, 'frequency': 'c', 'synset': 'ambulance.n.01'}, {'name': 'amplifier', 'id': 9, 'frequency': 'c', 'synset': 'amplifier.n.01'}, {'name': 'anklet', 'id': 10, 'frequency': 'c', 'synset': 'anklet.n.03'}, {'name': 'antenna', 'id': 11, 'frequency': 'f', 'synset': 'antenna.n.01'}, {'name': 'apple', 'id': 12, 'frequency': 'f', 'synset': 'apple.n.01'}, {'name': 'applesauce', 'id': 13, 'frequency': 'r', 'synset': 'applesauce.n.01'}, {'name': 'apricot', 'id': 14, 'frequency': 'r', 'synset': 'apricot.n.02'}, {'name': 'apron', 'id': 15, 'frequency': 'f', 'synset': 'apron.n.01'}, {'name': 'aquarium', 'id': 16, 'frequency': 'c', 'synset': 'aquarium.n.01'}, {'name': 'arctic_(type_of_shoe)', 'id': 17, 'frequency': 'r', 'synset': 'arctic.n.02'}, {'name': 'armband', 'id': 18, 'frequency': 'c', 'synset': 'armband.n.02'}, {'name': 'armchair', 'id': 19, 'frequency': 'f', 'synset': 'armchair.n.01'}, {'name': 'armoire', 'id': 20, 'frequency': 'r', 'synset': 'armoire.n.01'}, {'name': 'armor', 'id': 21, 'frequency': 'r', 'synset': 'armor.n.01'}, {'name': 'artichoke', 'id': 22, 'frequency': 'c', 'synset': 'artichoke.n.02'}, {'name': 'trash_can', 'id': 23, 'frequency': 'f', 'synset': 'ashcan.n.01'}, {'name': 'ashtray', 'id': 24, 'frequency': 'c', 'synset': 'ashtray.n.01'}, {'name': 'asparagus', 'id': 25, 'frequency': 'c', 'synset': 'asparagus.n.02'}, {'name': 'atomizer', 'id': 26, 'frequency': 'c', 'synset': 'atomizer.n.01'}, {'name': 'avocado', 'id': 27, 'frequency': 'f', 'synset': 'avocado.n.01'}, {'name': 'award', 'id': 28, 'frequency': 'c', 'synset': 'award.n.02'}, {'name': 'awning', 'id': 29, 'frequency': 'f', 'synset': 'awning.n.01'}, {'name': 'ax', 'id': 30, 'frequency': 'r', 'synset': 'ax.n.01'}, {'name': 'baboon', 'id': 31, 'frequency': 'r', 'synset': 'baboon.n.01'}, {'name': 'baby_buggy', 'id': 32, 'frequency': 'f', 'synset': 'baby_buggy.n.01'}, {'name': 'basketball_backboard', 'id': 33, 'frequency': 'c', 'synset': 'backboard.n.01'}, {'name': 'backpack', 'id': 34, 'frequency': 'f', 'synset': 'backpack.n.01'}, {'name': 'handbag', 'id': 35, 'frequency': 'f', 'synset': 'bag.n.04'}, {'name': 'suitcase', 'id': 36, 'frequency': 'f', 'synset': 'bag.n.06'}, {'name': 'bagel', 'id': 37, 'frequency': 'c', 'synset': 'bagel.n.01'}, {'name': 'bagpipe', 'id': 38, 'frequency': 'r', 'synset': 'bagpipe.n.01'}, {'name': 'baguet', 'id': 39, 'frequency': 'r', 'synset': 'baguet.n.01'}, {'name': 'bait', 'id': 40, 'frequency': 'r', 'synset': 'bait.n.02'}, {'name': 'ball', 'id': 41, 'frequency': 'f', 'synset': 'ball.n.06'}, {'name': 'ballet_skirt', 'id': 42, 'frequency': 'r', 'synset': 'ballet_skirt.n.01'}, {'name': 'balloon', 'id': 43, 'frequency': 'f', 'synset': 'balloon.n.01'}, {'name': 'bamboo', 'id': 44, 'frequency': 'c', 'synset': 'bamboo.n.02'}, {'name': 'banana', 'id': 45, 'frequency': 'f', 'synset': 'banana.n.02'}, {'name': 'Band_Aid', 'id': 46, 'frequency': 'c', 'synset': 'band_aid.n.01'}, {'name': 'bandage', 'id': 47, 'frequency': 'c', 'synset': 'bandage.n.01'}, {'name': 'bandanna', 'id': 48, 'frequency': 'f', 'synset': 'bandanna.n.01'}, {'name': 'banjo', 'id': 49, 'frequency': 'r', 'synset': 'banjo.n.01'}, {'name': 'banner', 'id': 50, 'frequency': 'f', 'synset': 'banner.n.01'}, {'name': 'barbell', 'id': 51, 'frequency': 'r', 'synset': 'barbell.n.01'}, {'name': 'barge', 'id': 52, 'frequency': 'r', 'synset': 'barge.n.01'}, {'name': 'barrel', 'id': 53, 'frequency': 'f', 'synset': 'barrel.n.02'}, {'name': 'barrette', 'id': 54, 'frequency': 'c', 'synset': 'barrette.n.01'}, {'name': 'barrow', 'id': 55, 'frequency': 'c', 'synset': 'barrow.n.03'}, {'name': 'baseball_base', 'id': 56, 'frequency': 'f', 'synset': 'base.n.03'}, {'name': 'baseball', 'id': 57, 'frequency': 'f', 'synset': 'baseball.n.02'}, {'name': 'baseball_bat', 'id': 58, 'frequency': 'f', 'synset': 'baseball_bat.n.01'}, {'name': 'baseball_cap', 'id': 59, 'frequency': 'f', 'synset': 'baseball_cap.n.01'}, {'name': 'baseball_glove', 'id': 60, 'frequency': 'f', 'synset': 'baseball_glove.n.01'}, {'name': 'basket', 'id': 61, 'frequency': 'f', 'synset': 'basket.n.01'}, {'name': 'basketball', 'id': 62, 'frequency': 'c', 'synset': 'basketball.n.02'}, {'name': 'bass_horn', 'id': 63, 'frequency': 'r', 'synset': 'bass_horn.n.01'}, {'name': 'bat_(animal)', 'id': 64, 'frequency': 'c', 'synset': 'bat.n.01'}, {'name': 'bath_mat', 'id': 65, 'frequency': 'f', 'synset': 'bath_mat.n.01'}, {'name': 'bath_towel', 'id': 66, 'frequency': 'f', 'synset': 'bath_towel.n.01'}, {'name': 'bathrobe', 'id': 67, 'frequency': 'c', 'synset': 'bathrobe.n.01'}, {'name': 'bathtub', 'id': 68, 'frequency': 'f', 'synset': 'bathtub.n.01'}, {'name': 'batter_(food)', 'id': 69, 'frequency': 'r', 'synset': 'batter.n.02'}, {'name': 'battery', 'id': 70, 'frequency': 'c', 'synset': 'battery.n.02'}, {'name': 'beachball', 'id': 71, 'frequency': 'r', 'synset': 'beach_ball.n.01'}, {'name': 'bead', 'id': 72, 'frequency': 'c', 'synset': 'bead.n.01'}, {'name': 'bean_curd', 'id': 73, 'frequency': 'c', 'synset': 'bean_curd.n.01'}, {'name': 'beanbag', 'id': 74, 'frequency': 'c', 'synset': 'beanbag.n.01'}, {'name': 'beanie', 'id': 75, 'frequency': 'f', 'synset': 'beanie.n.01'}, {'name': 'bear', 'id': 76, 'frequency': 'f', 'synset': 'bear.n.01'}, {'name': 'bed', 'id': 77, 'frequency': 'f', 'synset': 'bed.n.01'}, {'name': 'bedpan', 'id': 78, 'frequency': 'r', 'synset': 'bedpan.n.01'}, {'name': 'bedspread', 'id': 79, 'frequency': 'f', 'synset': 'bedspread.n.01'}, {'name': 'cow', 'id': 80, 'frequency': 'f', 'synset': 'beef.n.01'}, {'name': 'beef_(food)', 'id': 81, 'frequency': 'f', 'synset': 'beef.n.02'}, {'name': 'beeper', 'id': 82, 'frequency': 'r', 'synset': 'beeper.n.01'}, {'name': 'beer_bottle', 'id': 83, 'frequency': 'f', 'synset': 'beer_bottle.n.01'}, {'name': 'beer_can', 'id': 84, 'frequency': 'c', 'synset': 'beer_can.n.01'}, {'name': 'beetle', 'id': 85, 'frequency': 'r', 'synset': 'beetle.n.01'}, {'name': 'bell', 'id': 86, 'frequency': 'f', 'synset': 'bell.n.01'}, {'name': 'bell_pepper', 'id': 87, 'frequency': 'f', 'synset': 'bell_pepper.n.02'}, {'name': 'belt', 'id': 88, 'frequency': 'f', 'synset': 'belt.n.02'}, {'name': 'belt_buckle', 'id': 89, 'frequency': 'f', 'synset': 'belt_buckle.n.01'}, {'name': 'bench', 'id': 90, 'frequency': 'f', 'synset': 'bench.n.01'}, {'name': 'beret', 'id': 91, 'frequency': 'c', 'synset': 'beret.n.01'}, {'name': 'bib', 'id': 92, 'frequency': 'c', 'synset': 'bib.n.02'}, {'name': 'Bible', 'id': 93, 'frequency': 'r', 'synset': 'bible.n.01'}, {'name': 'bicycle', 'id': 94, 'frequency': 'f', 'synset': 'bicycle.n.01'}, {'name': 'visor', 'id': 95, 'frequency': 'f', 'synset': 'bill.n.09'}, {'name': 'billboard', 'id': 96, 'frequency': 'f', 'synset': 'billboard.n.01'}, {'name': 'binder', 'id': 97, 'frequency': 'c', 'synset': 'binder.n.03'}, {'name': 'binoculars', 'id': 98, 'frequency': 'c', 'synset': 'binoculars.n.01'}, {'name': 'bird', 'id': 99, 'frequency': 'f', 'synset': 'bird.n.01'}, {'name': 'birdfeeder', 'id': 100, 'frequency': 'c', 'synset': 'bird_feeder.n.01'}, {'name': 'birdbath', 'id': 101, 'frequency': 'c', 'synset': 'birdbath.n.01'}, {'name': 'birdcage', 'id': 102, 'frequency': 'c', 'synset': 'birdcage.n.01'}, {'name': 'birdhouse', 'id': 103, 'frequency': 'c', 'synset': 'birdhouse.n.01'}, {'name': 'birthday_cake', 'id': 104, 'frequency': 'f', 'synset': 'birthday_cake.n.01'}, {'name': 'birthday_card', 'id': 105, 'frequency': 'r', 'synset': 'birthday_card.n.01'}, {'name': 'pirate_flag', 'id': 106, 'frequency': 'r', 'synset': 'black_flag.n.01'}, {'name': 'black_sheep', 'id': 107, 'frequency': 'c', 'synset': 'black_sheep.n.02'}, {'name': 'blackberry', 'id': 108, 'frequency': 'c', 'synset': 'blackberry.n.01'}, {'name': 'blackboard', 'id': 109, 'frequency': 'f', 'synset': 'blackboard.n.01'}, {'name': 'blanket', 'id': 110, 'frequency': 'f', 'synset': 'blanket.n.01'}, {'name': 'blazer', 'id': 111, 'frequency': 'c', 'synset': 'blazer.n.01'}, {'name': 'blender', 'id': 112, 'frequency': 'f', 'synset': 'blender.n.01'}, {'name': 'blimp', 'id': 113, 'frequency': 'r', 'synset': 'blimp.n.02'}, {'name': 'blinker', 'id': 114, 'frequency': 'f', 'synset': 'blinker.n.01'}, {'name': 'blouse', 'id': 115, 'frequency': 'f', 'synset': 'blouse.n.01'}, {'name': 'blueberry', 'id': 116, 'frequency': 'f', 'synset': 'blueberry.n.02'}, {'name': 'gameboard', 'id': 117, 'frequency': 'r', 'synset': 'board.n.09'}, {'name': 'boat', 'id': 118, 'frequency': 'f', 'synset': 'boat.n.01'}, {'name': 'bob', 'id': 119, 'frequency': 'r', 'synset': 'bob.n.05'}, {'name': 'bobbin', 'id': 120, 'frequency': 'c', 'synset': 'bobbin.n.01'}, {'name': 'bobby_pin', 'id': 121, 'frequency': 'c', 'synset': 'bobby_pin.n.01'}, {'name': 'boiled_egg', 'id': 122, 'frequency': 'c', 'synset': 'boiled_egg.n.01'}, {'name': 'bolo_tie', 'id': 123, 'frequency': 'r', 'synset': 'bolo_tie.n.01'}, {'name': 'deadbolt', 'id': 124, 'frequency': 'c', 'synset': 'bolt.n.03'}, {'name': 'bolt', 'id': 125, 'frequency': 'f', 'synset': 'bolt.n.06'}, {'name': 'bonnet', 'id': 126, 'frequency': 'r', 'synset': 'bonnet.n.01'}, {'name': 'book', 'id': 127, 'frequency': 'f', 'synset': 'book.n.01'}, {'name': 'bookcase', 'id': 128, 'frequency': 'c', 'synset': 'bookcase.n.01'}, {'name': 'booklet', 'id': 129, 'frequency': 'c', 'synset': 'booklet.n.01'}, {'name': 'bookmark', 'id': 130, 'frequency': 'r', 'synset': 'bookmark.n.01'}, {'name': 'boom_microphone', 'id': 131, 'frequency': 'r', 'synset': 'boom.n.04'}, {'name': 'boot', 'id': 132, 'frequency': 'f', 'synset': 'boot.n.01'}, {'name': 'bottle', 'id': 133, 'frequency': 'f', 'synset': 'bottle.n.01'}, {'name': 'bottle_opener', 'id': 134, 'frequency': 'c', 'synset': 'bottle_opener.n.01'}, {'name': 'bouquet', 'id': 135, 'frequency': 'c', 'synset': 'bouquet.n.01'}, {'name': 'bow_(weapon)', 'id': 136, 'frequency': 'r', 'synset': 'bow.n.04'}, {'name': 'bow_(decorative_ribbons)', 'id': 137, 'frequency': 'f', 'synset': 'bow.n.08'}, {'name': 'bow-tie', 'id': 138, 'frequency': 'f', 'synset': 'bow_tie.n.01'}, {'name': 'bowl', 'id': 139, 'frequency': 'f', 'synset': 'bowl.n.03'}, {'name': 'pipe_bowl', 'id': 140, 'frequency': 'r', 'synset': 'bowl.n.08'}, {'name': 'bowler_hat', 'id': 141, 'frequency': 'c', 'synset': 'bowler_hat.n.01'}, {'name': 'bowling_ball', 'id': 142, 'frequency': 'r', 'synset': 'bowling_ball.n.01'}, {'name': 'box', 'id': 143, 'frequency': 'f', 'synset': 'box.n.01'}, {'name': 'boxing_glove', 'id': 144, 'frequency': 'r', 'synset': 'boxing_glove.n.01'}, {'name': 'suspenders', 'id': 145, 'frequency': 'c', 'synset': 'brace.n.06'}, {'name': 'bracelet', 'id': 146, 'frequency': 'f', 'synset': 'bracelet.n.02'}, {'name': 'brass_plaque', 'id': 147, 'frequency': 'r', 'synset': 'brass.n.07'}, {'name': 'brassiere', 'id': 148, 'frequency': 'c', 'synset': 'brassiere.n.01'}, {'name': 'bread-bin', 'id': 149, 'frequency': 'c', 'synset': 'bread-bin.n.01'}, {'name': 'bread', 'id': 150, 'frequency': 'f', 'synset': 'bread.n.01'}, {'name': 'breechcloth', 'id': 151, 'frequency': 'r', 'synset': 'breechcloth.n.01'}, {'name': 'bridal_gown', 'id': 152, 'frequency': 'f', 'synset': 'bridal_gown.n.01'}, {'name': 'briefcase', 'id': 153, 'frequency': 'c', 'synset': 'briefcase.n.01'}, {'name': 'broccoli', 'id': 154, 'frequency': 'f', 'synset': 'broccoli.n.01'}, {'name': 'broach', 'id': 155, 'frequency': 'r', 'synset': 'brooch.n.01'}, {'name': 'broom', 'id': 156, 'frequency': 'c', 'synset': 'broom.n.01'}, {'name': 'brownie', 'id': 157, 'frequency': 'c', 'synset': 'brownie.n.03'}, {'name': 'brussels_sprouts', 'id': 158, 'frequency': 'c', 'synset': 'brussels_sprouts.n.01'}, {'name': 'bubble_gum', 'id': 159, 'frequency': 'r', 'synset': 'bubble_gum.n.01'}, {'name': 'bucket', 'id': 160, 'frequency': 'f', 'synset': 'bucket.n.01'}, {'name': 'horse_buggy', 'id': 161, 'frequency': 'r', 'synset': 'buggy.n.01'}, {'name': 'bull', 'id': 162, 'frequency': 'c', 'synset': 'bull.n.11'}, {'name': 'bulldog', 'id': 163, 'frequency': 'c', 'synset': 'bulldog.n.01'}, {'name': 'bulldozer', 'id': 164, 'frequency': 'r', 'synset': 'bulldozer.n.01'}, {'name': 'bullet_train', 'id': 165, 'frequency': 'c', 'synset': 'bullet_train.n.01'}, {'name': 'bulletin_board', 'id': 166, 'frequency': 'c', 'synset': 'bulletin_board.n.02'}, {'name': 'bulletproof_vest', 'id': 167, 'frequency': 'r', 'synset': 'bulletproof_vest.n.01'}, {'name': 'bullhorn', 'id': 168, 'frequency': 'c', 'synset': 'bullhorn.n.01'}, {'name': 'bun', 'id': 169, 'frequency': 'f', 'synset': 'bun.n.01'}, {'name': 'bunk_bed', 'id': 170, 'frequency': 'c', 'synset': 'bunk_bed.n.01'}, {'name': 'buoy', 'id': 171, 'frequency': 'f', 'synset': 'buoy.n.01'}, {'name': 'burrito', 'id': 172, 'frequency': 'r', 'synset': 'burrito.n.01'}, {'name': 'bus_(vehicle)', 'id': 173, 'frequency': 'f', 'synset': 'bus.n.01'}, {'name': 'business_card', 'id': 174, 'frequency': 'c', 'synset': 'business_card.n.01'}, {'name': 'butter', 'id': 175, 'frequency': 'f', 'synset': 'butter.n.01'}, {'name': 'butterfly', 'id': 176, 'frequency': 'c', 'synset': 'butterfly.n.01'}, {'name': 'button', 'id': 177, 'frequency': 'f', 'synset': 'button.n.01'}, {'name': 'cab_(taxi)', 'id': 178, 'frequency': 'f', 'synset': 'cab.n.03'}, {'name': 'cabana', 'id': 179, 'frequency': 'r', 'synset': 'cabana.n.01'}, {'name': 'cabin_car', 'id': 180, 'frequency': 'c', 'synset': 'cabin_car.n.01'}, {'name': 'cabinet', 'id': 181, 'frequency': 'f', 'synset': 'cabinet.n.01'}, {'name': 'locker', 'id': 182, 'frequency': 'r', 'synset': 'cabinet.n.03'}, {'name': 'cake', 'id': 183, 'frequency': 'f', 'synset': 'cake.n.03'}, {'name': 'calculator', 'id': 184, 'frequency': 'c', 'synset': 'calculator.n.02'}, {'name': 'calendar', 'id': 185, 'frequency': 'f', 'synset': 'calendar.n.02'}, {'name': 'calf', 'id': 186, 'frequency': 'c', 'synset': 'calf.n.01'}, {'name': 'camcorder', 'id': 187, 'frequency': 'c', 'synset': 'camcorder.n.01'}, {'name': 'camel', 'id': 188, 'frequency': 'c', 'synset': 'camel.n.01'}, {'name': 'camera', 'id': 189, 'frequency': 'f', 'synset': 'camera.n.01'}, {'name': 'camera_lens', 'id': 190, 'frequency': 'c', 'synset': 'camera_lens.n.01'}, {'name': 'camper_(vehicle)', 'id': 191, 'frequency': 'c', 'synset': 'camper.n.02'}, {'name': 'can', 'id': 192, 'frequency': 'f', 'synset': 'can.n.01'}, {'name': 'can_opener', 'id': 193, 'frequency': 'c', 'synset': 'can_opener.n.01'}, {'name': 'candle', 'id': 194, 'frequency': 'f', 'synset': 'candle.n.01'}, {'name': 'candle_holder', 'id': 195, 'frequency': 'f', 'synset': 'candlestick.n.01'}, {'name': 'candy_bar', 'id': 196, 'frequency': 'r', 'synset': 'candy_bar.n.01'}, {'name': 'candy_cane', 'id': 197, 'frequency': 'c', 'synset': 'candy_cane.n.01'}, {'name': 'walking_cane', 'id': 198, 'frequency': 'c', 'synset': 'cane.n.01'}, {'name': 'canister', 'id': 199, 'frequency': 'c', 'synset': 'canister.n.02'}, {'name': 'canoe', 'id': 200, 'frequency': 'c', 'synset': 'canoe.n.01'}, {'name': 'cantaloup', 'id': 201, 'frequency': 'c', 'synset': 'cantaloup.n.02'}, {'name': 'canteen', 'id': 202, 'frequency': 'r', 'synset': 'canteen.n.01'}, {'name': 'cap_(headwear)', 'id': 203, 'frequency': 'f', 'synset': 'cap.n.01'}, {'name': 'bottle_cap', 'id': 204, 'frequency': 'f', 'synset': 'cap.n.02'}, {'name': 'cape', 'id': 205, 'frequency': 'c', 'synset': 'cape.n.02'}, {'name': 'cappuccino', 'id': 206, 'frequency': 'c', 'synset': 'cappuccino.n.01'}, {'name': 'car_(automobile)', 'id': 207, 'frequency': 'f', 'synset': 'car.n.01'}, {'name': 'railcar_(part_of_a_train)', 'id': 208, 'frequency': 'f', 'synset': 'car.n.02'}, {'name': 'elevator_car', 'id': 209, 'frequency': 'r', 'synset': 'car.n.04'}, {'name': 'car_battery', 'id': 210, 'frequency': 'r', 'synset': 'car_battery.n.01'}, {'name': 'identity_card', 'id': 211, 'frequency': 'c', 'synset': 'card.n.02'}, {'name': 'card', 'id': 212, 'frequency': 'c', 'synset': 'card.n.03'}, {'name': 'cardigan', 'id': 213, 'frequency': 'c', 'synset': 'cardigan.n.01'}, {'name': 'cargo_ship', 'id': 214, 'frequency': 'r', 'synset': 'cargo_ship.n.01'}, {'name': 'carnation', 'id': 215, 'frequency': 'r', 'synset': 'carnation.n.01'}, {'name': 'horse_carriage', 'id': 216, 'frequency': 'c', 'synset': 'carriage.n.02'}, {'name': 'carrot', 'id': 217, 'frequency': 'f', 'synset': 'carrot.n.01'}, {'name': 'tote_bag', 'id': 218, 'frequency': 'f', 'synset': 'carryall.n.01'}, {'name': 'cart', 'id': 219, 'frequency': 'c', 'synset': 'cart.n.01'}, {'name': 'carton', 'id': 220, 'frequency': 'c', 'synset': 'carton.n.02'}, {'name': 'cash_register', 'id': 221, 'frequency': 'c', 'synset': 'cash_register.n.01'}, {'name': 'casserole', 'id': 222, 'frequency': 'r', 'synset': 'casserole.n.01'}, {'name': 'cassette', 'id': 223, 'frequency': 'r', 'synset': 'cassette.n.01'}, {'name': 'cast', 'id': 224, 'frequency': 'c', 'synset': 'cast.n.05'}, {'name': 'cat', 'id': 225, 'frequency': 'f', 'synset': 'cat.n.01'}, {'name': 'cauliflower', 'id': 226, 'frequency': 'f', 'synset': 'cauliflower.n.02'}, {'name': 'cayenne_(spice)', 'id': 227, 'frequency': 'c', 'synset': 'cayenne.n.02'}, {'name': 'CD_player', 'id': 228, 'frequency': 'c', 'synset': 'cd_player.n.01'}, {'name': 'celery', 'id': 229, 'frequency': 'f', 'synset': 'celery.n.01'}, {'name': 'cellular_telephone', 'id': 230, 'frequency': 'f', 'synset': 'cellular_telephone.n.01'}, {'name': 'chain_mail', 'id': 231, 'frequency': 'r', 'synset': 'chain_mail.n.01'}, {'name': 'chair', 'id': 232, 'frequency': 'f', 'synset': 'chair.n.01'}, {'name': 'chaise_longue', 'id': 233, 'frequency': 'r', 'synset': 'chaise_longue.n.01'}, {'name': 'chalice', 'id': 234, 'frequency': 'r', 'synset': 'chalice.n.01'}, {'name': 'chandelier', 'id': 235, 'frequency': 'f', 'synset': 'chandelier.n.01'}, {'name': 'chap', 'id': 236, 'frequency': 'r', 'synset': 'chap.n.04'}, {'name': 'checkbook', 'id': 237, 'frequency': 'r', 'synset': 'checkbook.n.01'}, {'name': 'checkerboard', 'id': 238, 'frequency': 'r', 'synset': 'checkerboard.n.01'}, {'name': 'cherry', 'id': 239, 'frequency': 'c', 'synset': 'cherry.n.03'}, {'name': 'chessboard', 'id': 240, 'frequency': 'r', 'synset': 'chessboard.n.01'}, {'name': 'chicken_(animal)', 'id': 241, 'frequency': 'c', 'synset': 'chicken.n.02'}, {'name': 'chickpea', 'id': 242, 'frequency': 'c', 'synset': 'chickpea.n.01'}, {'name': 'chili_(vegetable)', 'id': 243, 'frequency': 'c', 'synset': 'chili.n.02'}, {'name': 'chime', 'id': 244, 'frequency': 'r', 'synset': 'chime.n.01'}, {'name': 'chinaware', 'id': 245, 'frequency': 'r', 'synset': 'chinaware.n.01'}, {'name': 'crisp_(potato_chip)', 'id': 246, 'frequency': 'c', 'synset': 'chip.n.04'}, {'name': 'poker_chip', 'id': 247, 'frequency': 'r', 'synset': 'chip.n.06'}, {'name': 'chocolate_bar', 'id': 248, 'frequency': 'c', 'synset': 'chocolate_bar.n.01'}, {'name': 'chocolate_cake', 'id': 249, 'frequency': 'c', 'synset': 'chocolate_cake.n.01'}, {'name': 'chocolate_milk', 'id': 250, 'frequency': 'r', 'synset': 'chocolate_milk.n.01'}, {'name': 'chocolate_mousse', 'id': 251, 'frequency': 'r', 'synset': 'chocolate_mousse.n.01'}, {'name': 'choker', 'id': 252, 'frequency': 'f', 'synset': 'choker.n.03'}, {'name': 'chopping_board', 'id': 253, 'frequency': 'f', 'synset': 'chopping_board.n.01'}, {'name': 'chopstick', 'id': 254, 'frequency': 'f', 'synset': 'chopstick.n.01'}, {'name': 'Christmas_tree', 'id': 255, 'frequency': 'f', 'synset': 'christmas_tree.n.05'}, {'name': 'slide', 'id': 256, 'frequency': 'c', 'synset': 'chute.n.02'}, {'name': 'cider', 'id': 257, 'frequency': 'r', 'synset': 'cider.n.01'}, {'name': 'cigar_box', 'id': 258, 'frequency': 'r', 'synset': 'cigar_box.n.01'}, {'name': 'cigarette', 'id': 259, 'frequency': 'f', 'synset': 'cigarette.n.01'}, {'name': 'cigarette_case', 'id': 260, 'frequency': 'c', 'synset': 'cigarette_case.n.01'}, {'name': 'cistern', 'id': 261, 'frequency': 'f', 'synset': 'cistern.n.02'}, {'name': 'clarinet', 'id': 262, 'frequency': 'r', 'synset': 'clarinet.n.01'}, {'name': 'clasp', 'id': 263, 'frequency': 'c', 'synset': 'clasp.n.01'}, {'name': 'cleansing_agent', 'id': 264, 'frequency': 'c', 'synset': 'cleansing_agent.n.01'}, {'name': 'cleat_(for_securing_rope)', 'id': 265, 'frequency': 'r', 'synset': 'cleat.n.02'}, {'name': 'clementine', 'id': 266, 'frequency': 'r', 'synset': 'clementine.n.01'}, {'name': 'clip', 'id': 267, 'frequency': 'c', 'synset': 'clip.n.03'}, {'name': 'clipboard', 'id': 268, 'frequency': 'c', 'synset': 'clipboard.n.01'}, {'name': 'clippers_(for_plants)', 'id': 269, 'frequency': 'r', 'synset': 'clipper.n.03'}, {'name': 'cloak', 'id': 270, 'frequency': 'r', 'synset': 'cloak.n.02'}, {'name': 'clock', 'id': 271, 'frequency': 'f', 'synset': 'clock.n.01'}, {'name': 'clock_tower', 'id': 272, 'frequency': 'f', 'synset': 'clock_tower.n.01'}, {'name': 'clothes_hamper', 'id': 273, 'frequency': 'c', 'synset': 'clothes_hamper.n.01'}, {'name': 'clothespin', 'id': 274, 'frequency': 'c', 'synset': 'clothespin.n.01'}, {'name': 'clutch_bag', 'id': 275, 'frequency': 'r', 'synset': 'clutch_bag.n.01'}, {'name': 'coaster', 'id': 276, 'frequency': 'f', 'synset': 'coaster.n.03'}, {'name': 'coat', 'id': 277, 'frequency': 'f', 'synset': 'coat.n.01'}, {'name': 'coat_hanger', 'id': 278, 'frequency': 'c', 'synset': 'coat_hanger.n.01'}, {'name': 'coatrack', 'id': 279, 'frequency': 'c', 'synset': 'coatrack.n.01'}, {'name': 'cock', 'id': 280, 'frequency': 'c', 'synset': 'cock.n.04'}, {'name': 'cockroach', 'id': 281, 'frequency': 'r', 'synset': 'cockroach.n.01'}, {'name': 'cocoa_(beverage)', 'id': 282, 'frequency': 'r', 'synset': 'cocoa.n.01'}, {'name': 'coconut', 'id': 283, 'frequency': 'c', 'synset': 'coconut.n.02'}, {'name': 'coffee_maker', 'id': 284, 'frequency': 'f', 'synset': 'coffee_maker.n.01'}, {'name': 'coffee_table', 'id': 285, 'frequency': 'f', 'synset': 'coffee_table.n.01'}, {'name': 'coffeepot', 'id': 286, 'frequency': 'c', 'synset': 'coffeepot.n.01'}, {'name': 'coil', 'id': 287, 'frequency': 'r', 'synset': 'coil.n.05'}, {'name': 'coin', 'id': 288, 'frequency': 'c', 'synset': 'coin.n.01'}, {'name': 'colander', 'id': 289, 'frequency': 'c', 'synset': 'colander.n.01'}, {'name': 'coleslaw', 'id': 290, 'frequency': 'c', 'synset': 'coleslaw.n.01'}, {'name': 'coloring_material', 'id': 291, 'frequency': 'r', 'synset': 'coloring_material.n.01'}, {'name': 'combination_lock', 'id': 292, 'frequency': 'r', 'synset': 'combination_lock.n.01'}, {'name': 'pacifier', 'id': 293, 'frequency': 'c', 'synset': 'comforter.n.04'}, {'name': 'comic_book', 'id': 294, 'frequency': 'r', 'synset': 'comic_book.n.01'}, {'name': 'compass', 'id': 295, 'frequency': 'r', 'synset': 'compass.n.01'}, {'name': 'computer_keyboard', 'id': 296, 'frequency': 'f', 'synset': 'computer_keyboard.n.01'}, {'name': 'condiment', 'id': 297, 'frequency': 'f', 'synset': 'condiment.n.01'}, {'name': 'cone', 'id': 298, 'frequency': 'f', 'synset': 'cone.n.01'}, {'name': 'control', 'id': 299, 'frequency': 'f', 'synset': 'control.n.09'}, {'name': 'convertible_(automobile)', 'id': 300, 'frequency': 'r', 'synset': 'convertible.n.01'}, {'name': 'sofa_bed', 'id': 301, 'frequency': 'r', 'synset': 'convertible.n.03'}, {'name': 'cooker', 'id': 302, 'frequency': 'r', 'synset': 'cooker.n.01'}, {'name': 'cookie', 'id': 303, 'frequency': 'f', 'synset': 'cookie.n.01'}, {'name': 'cooking_utensil', 'id': 304, 'frequency': 'r', 'synset': 'cooking_utensil.n.01'}, {'name': 'cooler_(for_food)', 'id': 305, 'frequency': 'f', 'synset': 'cooler.n.01'}, {'name': 'cork_(bottle_plug)', 'id': 306, 'frequency': 'f', 'synset': 'cork.n.04'}, {'name': 'corkboard', 'id': 307, 'frequency': 'r', 'synset': 'corkboard.n.01'}, {'name': 'corkscrew', 'id': 308, 'frequency': 'c', 'synset': 'corkscrew.n.01'}, {'name': 'edible_corn', 'id': 309, 'frequency': 'f', 'synset': 'corn.n.03'}, {'name': 'cornbread', 'id': 310, 'frequency': 'r', 'synset': 'cornbread.n.01'}, {'name': 'cornet', 'id': 311, 'frequency': 'c', 'synset': 'cornet.n.01'}, {'name': 'cornice', 'id': 312, 'frequency': 'c', 'synset': 'cornice.n.01'}, {'name': 'cornmeal', 'id': 313, 'frequency': 'r', 'synset': 'cornmeal.n.01'}, {'name': 'corset', 'id': 314, 'frequency': 'c', 'synset': 'corset.n.01'}, {'name': 'costume', 'id': 315, 'frequency': 'c', 'synset': 'costume.n.04'}, {'name': 'cougar', 'id': 316, 'frequency': 'r', 'synset': 'cougar.n.01'}, {'name': 'coverall', 'id': 317, 'frequency': 'r', 'synset': 'coverall.n.01'}, {'name': 'cowbell', 'id': 318, 'frequency': 'c', 'synset': 'cowbell.n.01'}, {'name': 'cowboy_hat', 'id': 319, 'frequency': 'f', 'synset': 'cowboy_hat.n.01'}, {'name': 'crab_(animal)', 'id': 320, 'frequency': 'c', 'synset': 'crab.n.01'}, {'name': 'crabmeat', 'id': 321, 'frequency': 'r', 'synset': 'crab.n.05'}, {'name': 'cracker', 'id': 322, 'frequency': 'c', 'synset': 'cracker.n.01'}, {'name': 'crape', 'id': 323, 'frequency': 'r', 'synset': 'crape.n.01'}, {'name': 'crate', 'id': 324, 'frequency': 'f', 'synset': 'crate.n.01'}, {'name': 'crayon', 'id': 325, 'frequency': 'c', 'synset': 'crayon.n.01'}, {'name': 'cream_pitcher', 'id': 326, 'frequency': 'r', 'synset': 'cream_pitcher.n.01'}, {'name': 'crescent_roll', 'id': 327, 'frequency': 'c', 'synset': 'crescent_roll.n.01'}, {'name': 'crib', 'id': 328, 'frequency': 'c', 'synset': 'crib.n.01'}, {'name': 'crock_pot', 'id': 329, 'frequency': 'c', 'synset': 'crock.n.03'}, {'name': 'crossbar', 'id': 330, 'frequency': 'f', 'synset': 'crossbar.n.01'}, {'name': 'crouton', 'id': 331, 'frequency': 'r', 'synset': 'crouton.n.01'}, {'name': 'crow', 'id': 332, 'frequency': 'c', 'synset': 'crow.n.01'}, {'name': 'crowbar', 'id': 333, 'frequency': 'r', 'synset': 'crowbar.n.01'}, {'name': 'crown', 'id': 334, 'frequency': 'c', 'synset': 'crown.n.04'}, {'name': 'crucifix', 'id': 335, 'frequency': 'c', 'synset': 'crucifix.n.01'}, {'name': 'cruise_ship', 'id': 336, 'frequency': 'c', 'synset': 'cruise_ship.n.01'}, {'name': 'police_cruiser', 'id': 337, 'frequency': 'c', 'synset': 'cruiser.n.01'}, {'name': 'crumb', 'id': 338, 'frequency': 'f', 'synset': 'crumb.n.03'}, {'name': 'crutch', 'id': 339, 'frequency': 'c', 'synset': 'crutch.n.01'}, {'name': 'cub_(animal)', 'id': 340, 'frequency': 'c', 'synset': 'cub.n.03'}, {'name': 'cube', 'id': 341, 'frequency': 'c', 'synset': 'cube.n.05'}, {'name': 'cucumber', 'id': 342, 'frequency': 'f', 'synset': 'cucumber.n.02'}, {'name': 'cufflink', 'id': 343, 'frequency': 'c', 'synset': 'cufflink.n.01'}, {'name': 'cup', 'id': 344, 'frequency': 'f', 'synset': 'cup.n.01'}, {'name': 'trophy_cup', 'id': 345, 'frequency': 'c', 'synset': 'cup.n.08'}, {'name': 'cupboard', 'id': 346, 'frequency': 'f', 'synset': 'cupboard.n.01'}, {'name': 'cupcake', 'id': 347, 'frequency': 'f', 'synset': 'cupcake.n.01'}, {'name': 'hair_curler', 'id': 348, 'frequency': 'r', 'synset': 'curler.n.01'}, {'name': 'curling_iron', 'id': 349, 'frequency': 'r', 'synset': 'curling_iron.n.01'}, {'name': 'curtain', 'id': 350, 'frequency': 'f', 'synset': 'curtain.n.01'}, {'name': 'cushion', 'id': 351, 'frequency': 'f', 'synset': 'cushion.n.03'}, {'name': 'cylinder', 'id': 352, 'frequency': 'r', 'synset': 'cylinder.n.04'}, {'name': 'cymbal', 'id': 353, 'frequency': 'r', 'synset': 'cymbal.n.01'}, {'name': 'dagger', 'id': 354, 'frequency': 'r', 'synset': 'dagger.n.01'}, {'name': 'dalmatian', 'id': 355, 'frequency': 'r', 'synset': 'dalmatian.n.02'}, {'name': 'dartboard', 'id': 356, 'frequency': 'c', 'synset': 'dartboard.n.01'}, {'name': 'date_(fruit)', 'id': 357, 'frequency': 'r', 'synset': 'date.n.08'}, {'name': 'deck_chair', 'id': 358, 'frequency': 'f', 'synset': 'deck_chair.n.01'}, {'name': 'deer', 'id': 359, 'frequency': 'c', 'synset': 'deer.n.01'}, {'name': 'dental_floss', 'id': 360, 'frequency': 'c', 'synset': 'dental_floss.n.01'}, {'name': 'desk', 'id': 361, 'frequency': 'f', 'synset': 'desk.n.01'}, {'name': 'detergent', 'id': 362, 'frequency': 'r', 'synset': 'detergent.n.01'}, {'name': 'diaper', 'id': 363, 'frequency': 'c', 'synset': 'diaper.n.01'}, {'name': 'diary', 'id': 364, 'frequency': 'r', 'synset': 'diary.n.01'}, {'name': 'die', 'id': 365, 'frequency': 'r', 'synset': 'die.n.01'}, {'name': 'dinghy', 'id': 366, 'frequency': 'r', 'synset': 'dinghy.n.01'}, {'name': 'dining_table', 'id': 367, 'frequency': 'f', 'synset': 'dining_table.n.01'}, {'name': 'tux', 'id': 368, 'frequency': 'r', 'synset': 'dinner_jacket.n.01'}, {'name': 'dish', 'id': 369, 'frequency': 'f', 'synset': 'dish.n.01'}, {'name': 'dish_antenna', 'id': 370, 'frequency': 'c', 'synset': 'dish.n.05'}, {'name': 'dishrag', 'id': 371, 'frequency': 'c', 'synset': 'dishrag.n.01'}, {'name': 'dishtowel', 'id': 372, 'frequency': 'f', 'synset': 'dishtowel.n.01'}, {'name': 'dishwasher', 'id': 373, 'frequency': 'f', 'synset': 'dishwasher.n.01'}, {'name': 'dishwasher_detergent', 'id': 374, 'frequency': 'r', 'synset': 'dishwasher_detergent.n.01'}, {'name': 'dispenser', 'id': 375, 'frequency': 'f', 'synset': 'dispenser.n.01'}, {'name': 'diving_board', 'id': 376, 'frequency': 'r', 'synset': 'diving_board.n.01'}, {'name': 'Dixie_cup', 'id': 377, 'frequency': 'f', 'synset': 'dixie_cup.n.01'}, {'name': 'dog', 'id': 378, 'frequency': 'f', 'synset': 'dog.n.01'}, {'name': 'dog_collar', 'id': 379, 'frequency': 'f', 'synset': 'dog_collar.n.01'}, {'name': 'doll', 'id': 380, 'frequency': 'f', 'synset': 'doll.n.01'}, {'name': 'dollar', 'id': 381, 'frequency': 'r', 'synset': 'dollar.n.02'}, {'name': 'dollhouse', 'id': 382, 'frequency': 'r', 'synset': 'dollhouse.n.01'}, {'name': 'dolphin', 'id': 383, 'frequency': 'c', 'synset': 'dolphin.n.02'}, {'name': 'domestic_ass', 'id': 384, 'frequency': 'c', 'synset': 'domestic_ass.n.01'}, {'name': 'doorknob', 'id': 385, 'frequency': 'f', 'synset': 'doorknob.n.01'}, {'name': 'doormat', 'id': 386, 'frequency': 'c', 'synset': 'doormat.n.02'}, {'name': 'doughnut', 'id': 387, 'frequency': 'f', 'synset': 'doughnut.n.02'}, {'name': 'dove', 'id': 388, 'frequency': 'r', 'synset': 'dove.n.01'}, {'name': 'dragonfly', 'id': 389, 'frequency': 'r', 'synset': 'dragonfly.n.01'}, {'name': 'drawer', 'id': 390, 'frequency': 'f', 'synset': 'drawer.n.01'}, {'name': 'underdrawers', 'id': 391, 'frequency': 'c', 'synset': 'drawers.n.01'}, {'name': 'dress', 'id': 392, 'frequency': 'f', 'synset': 'dress.n.01'}, {'name': 'dress_hat', 'id': 393, 'frequency': 'c', 'synset': 'dress_hat.n.01'}, {'name': 'dress_suit', 'id': 394, 'frequency': 'f', 'synset': 'dress_suit.n.01'}, {'name': 'dresser', 'id': 395, 'frequency': 'f', 'synset': 'dresser.n.05'}, {'name': 'drill', 'id': 396, 'frequency': 'c', 'synset': 'drill.n.01'}, {'name': 'drone', 'id': 397, 'frequency': 'r', 'synset': 'drone.n.04'}, {'name': 'dropper', 'id': 398, 'frequency': 'r', 'synset': 'dropper.n.01'}, {'name': 'drum_(musical_instrument)', 'id': 399, 'frequency': 'c', 'synset': 'drum.n.01'}, {'name': 'drumstick', 'id': 400, 'frequency': 'r', 'synset': 'drumstick.n.02'}, {'name': 'duck', 'id': 401, 'frequency': 'f', 'synset': 'duck.n.01'}, {'name': 'duckling', 'id': 402, 'frequency': 'c', 'synset': 'duckling.n.02'}, {'name': 'duct_tape', 'id': 403, 'frequency': 'c', 'synset': 'duct_tape.n.01'}, {'name': 'duffel_bag', 'id': 404, 'frequency': 'f', 'synset': 'duffel_bag.n.01'}, {'name': 'dumbbell', 'id': 405, 'frequency': 'r', 'synset': 'dumbbell.n.01'}, {'name': 'dumpster', 'id': 406, 'frequency': 'c', 'synset': 'dumpster.n.01'}, {'name': 'dustpan', 'id': 407, 'frequency': 'r', 'synset': 'dustpan.n.02'}, {'name': 'eagle', 'id': 408, 'frequency': 'c', 'synset': 'eagle.n.01'}, {'name': 'earphone', 'id': 409, 'frequency': 'f', 'synset': 'earphone.n.01'}, {'name': 'earplug', 'id': 410, 'frequency': 'r', 'synset': 'earplug.n.01'}, {'name': 'earring', 'id': 411, 'frequency': 'f', 'synset': 'earring.n.01'}, {'name': 'easel', 'id': 412, 'frequency': 'c', 'synset': 'easel.n.01'}, {'name': 'eclair', 'id': 413, 'frequency': 'r', 'synset': 'eclair.n.01'}, {'name': 'eel', 'id': 414, 'frequency': 'r', 'synset': 'eel.n.01'}, {'name': 'egg', 'id': 415, 'frequency': 'f', 'synset': 'egg.n.02'}, {'name': 'egg_roll', 'id': 416, 'frequency': 'r', 'synset': 'egg_roll.n.01'}, {'name': 'egg_yolk', 'id': 417, 'frequency': 'c', 'synset': 'egg_yolk.n.01'}, {'name': 'eggbeater', 'id': 418, 'frequency': 'c', 'synset': 'eggbeater.n.02'}, {'name': 'eggplant', 'id': 419, 'frequency': 'c', 'synset': 'eggplant.n.01'}, {'name': 'electric_chair', 'id': 420, 'frequency': 'r', 'synset': 'electric_chair.n.01'}, {'name': 'refrigerator', 'id': 421, 'frequency': 'f', 'synset': 'electric_refrigerator.n.01'}, {'name': 'elephant', 'id': 422, 'frequency': 'f', 'synset': 'elephant.n.01'}, {'name': 'elk', 'id': 423, 'frequency': 'c', 'synset': 'elk.n.01'}, {'name': 'envelope', 'id': 424, 'frequency': 'c', 'synset': 'envelope.n.01'}, {'name': 'eraser', 'id': 425, 'frequency': 'c', 'synset': 'eraser.n.01'}, {'name': 'escargot', 'id': 426, 'frequency': 'r', 'synset': 'escargot.n.01'}, {'name': 'eyepatch', 'id': 427, 'frequency': 'r', 'synset': 'eyepatch.n.01'}, {'name': 'falcon', 'id': 428, 'frequency': 'r', 'synset': 'falcon.n.01'}, {'name': 'fan', 'id': 429, 'frequency': 'f', 'synset': 'fan.n.01'}, {'name': 'faucet', 'id': 430, 'frequency': 'f', 'synset': 'faucet.n.01'}, {'name': 'fedora', 'id': 431, 'frequency': 'r', 'synset': 'fedora.n.01'}, {'name': 'ferret', 'id': 432, 'frequency': 'r', 'synset': 'ferret.n.02'}, {'name': 'Ferris_wheel', 'id': 433, 'frequency': 'c', 'synset': 'ferris_wheel.n.01'}, {'name': 'ferry', 'id': 434, 'frequency': 'c', 'synset': 'ferry.n.01'}, {'name': 'fig_(fruit)', 'id': 435, 'frequency': 'r', 'synset': 'fig.n.04'}, {'name': 'fighter_jet', 'id': 436, 'frequency': 'c', 'synset': 'fighter.n.02'}, {'name': 'figurine', 'id': 437, 'frequency': 'f', 'synset': 'figurine.n.01'}, {'name': 'file_cabinet', 'id': 438, 'frequency': 'c', 'synset': 'file.n.03'}, {'name': 'file_(tool)', 'id': 439, 'frequency': 'r', 'synset': 'file.n.04'}, {'name': 'fire_alarm', 'id': 440, 'frequency': 'f', 'synset': 'fire_alarm.n.02'}, {'name': 'fire_engine', 'id': 441, 'frequency': 'f', 'synset': 'fire_engine.n.01'}, {'name': 'fire_extinguisher', 'id': 442, 'frequency': 'f', 'synset': 'fire_extinguisher.n.01'}, {'name': 'fire_hose', 'id': 443, 'frequency': 'c', 'synset': 'fire_hose.n.01'}, {'name': 'fireplace', 'id': 444, 'frequency': 'f', 'synset': 'fireplace.n.01'}, {'name': 'fireplug', 'id': 445, 'frequency': 'f', 'synset': 'fireplug.n.01'}, {'name': 'first-aid_kit', 'id': 446, 'frequency': 'r', 'synset': 'first-aid_kit.n.01'}, {'name': 'fish', 'id': 447, 'frequency': 'f', 'synset': 'fish.n.01'}, {'name': 'fish_(food)', 'id': 448, 'frequency': 'c', 'synset': 'fish.n.02'}, {'name': 'fishbowl', 'id': 449, 'frequency': 'r', 'synset': 'fishbowl.n.02'}, {'name': 'fishing_rod', 'id': 450, 'frequency': 'c', 'synset': 'fishing_rod.n.01'}, {'name': 'flag', 'id': 451, 'frequency': 'f', 'synset': 'flag.n.01'}, {'name': 'flagpole', 'id': 452, 'frequency': 'f', 'synset': 'flagpole.n.02'}, {'name': 'flamingo', 'id': 453, 'frequency': 'c', 'synset': 'flamingo.n.01'}, {'name': 'flannel', 'id': 454, 'frequency': 'c', 'synset': 'flannel.n.01'}, {'name': 'flap', 'id': 455, 'frequency': 'c', 'synset': 'flap.n.01'}, {'name': 'flash', 'id': 456, 'frequency': 'r', 'synset': 'flash.n.10'}, {'name': 'flashlight', 'id': 457, 'frequency': 'c', 'synset': 'flashlight.n.01'}, {'name': 'fleece', 'id': 458, 'frequency': 'r', 'synset': 'fleece.n.03'}, {'name': 'flip-flop_(sandal)', 'id': 459, 'frequency': 'f', 'synset': 'flip-flop.n.02'}, {'name': 'flipper_(footwear)', 'id': 460, 'frequency': 'c', 'synset': 'flipper.n.01'}, {'name': 'flower_arrangement', 'id': 461, 'frequency': 'f', 'synset': 'flower_arrangement.n.01'}, {'name': 'flute_glass', 'id': 462, 'frequency': 'c', 'synset': 'flute.n.02'}, {'name': 'foal', 'id': 463, 'frequency': 'c', 'synset': 'foal.n.01'}, {'name': 'folding_chair', 'id': 464, 'frequency': 'c', 'synset': 'folding_chair.n.01'}, {'name': 'food_processor', 'id': 465, 'frequency': 'c', 'synset': 'food_processor.n.01'}, {'name': 'football_(American)', 'id': 466, 'frequency': 'c', 'synset': 'football.n.02'}, {'name': 'football_helmet', 'id': 467, 'frequency': 'r', 'synset': 'football_helmet.n.01'}, {'name': 'footstool', 'id': 468, 'frequency': 'c', 'synset': 'footstool.n.01'}, {'name': 'fork', 'id': 469, 'frequency': 'f', 'synset': 'fork.n.01'}, {'name': 'forklift', 'id': 470, 'frequency': 'c', 'synset': 'forklift.n.01'}, {'name': 'freight_car', 'id': 471, 'frequency': 'c', 'synset': 'freight_car.n.01'}, {'name': 'French_toast', 'id': 472, 'frequency': 'c', 'synset': 'french_toast.n.01'}, {'name': 'freshener', 'id': 473, 'frequency': 'c', 'synset': 'freshener.n.01'}, {'name': 'frisbee', 'id': 474, 'frequency': 'f', 'synset': 'frisbee.n.01'}, {'name': 'frog', 'id': 475, 'frequency': 'c', 'synset': 'frog.n.01'}, {'name': 'fruit_juice', 'id': 476, 'frequency': 'c', 'synset': 'fruit_juice.n.01'}, {'name': 'frying_pan', 'id': 477, 'frequency': 'f', 'synset': 'frying_pan.n.01'}, {'name': 'fudge', 'id': 478, 'frequency': 'r', 'synset': 'fudge.n.01'}, {'name': 'funnel', 'id': 479, 'frequency': 'r', 'synset': 'funnel.n.02'}, {'name': 'futon', 'id': 480, 'frequency': 'r', 'synset': 'futon.n.01'}, {'name': 'gag', 'id': 481, 'frequency': 'r', 'synset': 'gag.n.02'}, {'name': 'garbage', 'id': 482, 'frequency': 'r', 'synset': 'garbage.n.03'}, {'name': 'garbage_truck', 'id': 483, 'frequency': 'c', 'synset': 'garbage_truck.n.01'}, {'name': 'garden_hose', 'id': 484, 'frequency': 'c', 'synset': 'garden_hose.n.01'}, {'name': 'gargle', 'id': 485, 'frequency': 'c', 'synset': 'gargle.n.01'}, {'name': 'gargoyle', 'id': 486, 'frequency': 'r', 'synset': 'gargoyle.n.02'}, {'name': 'garlic', 'id': 487, 'frequency': 'c', 'synset': 'garlic.n.02'}, {'name': 'gasmask', 'id': 488, 'frequency': 'r', 'synset': 'gasmask.n.01'}, {'name': 'gazelle', 'id': 489, 'frequency': 'c', 'synset': 'gazelle.n.01'}, {'name': 'gelatin', 'id': 490, 'frequency': 'c', 'synset': 'gelatin.n.02'}, {'name': 'gemstone', 'id': 491, 'frequency': 'r', 'synset': 'gem.n.02'}, {'name': 'generator', 'id': 492, 'frequency': 'r', 'synset': 'generator.n.02'}, {'name': 'giant_panda', 'id': 493, 'frequency': 'c', 'synset': 'giant_panda.n.01'}, {'name': 'gift_wrap', 'id': 494, 'frequency': 'c', 'synset': 'gift_wrap.n.01'}, {'name': 'ginger', 'id': 495, 'frequency': 'c', 'synset': 'ginger.n.03'}, {'name': 'giraffe', 'id': 496, 'frequency': 'f', 'synset': 'giraffe.n.01'}, {'name': 'cincture', 'id': 497, 'frequency': 'c', 'synset': 'girdle.n.02'}, {'name': 'glass_(drink_container)', 'id': 498, 'frequency': 'f', 'synset': 'glass.n.02'}, {'name': 'globe', 'id': 499, 'frequency': 'c', 'synset': 'globe.n.03'}, {'name': 'glove', 'id': 500, 'frequency': 'f', 'synset': 'glove.n.02'}, {'name': 'goat', 'id': 501, 'frequency': 'c', 'synset': 'goat.n.01'}, {'name': 'goggles', 'id': 502, 'frequency': 'f', 'synset': 'goggles.n.01'}, {'name': 'goldfish', 'id': 503, 'frequency': 'r', 'synset': 'goldfish.n.01'}, {'name': 'golf_club', 'id': 504, 'frequency': 'c', 'synset': 'golf_club.n.02'}, {'name': 'golfcart', 'id': 505, 'frequency': 'c', 'synset': 'golfcart.n.01'}, {'name': 'gondola_(boat)', 'id': 506, 'frequency': 'r', 'synset': 'gondola.n.02'}, {'name': 'goose', 'id': 507, 'frequency': 'c', 'synset': 'goose.n.01'}, {'name': 'gorilla', 'id': 508, 'frequency': 'r', 'synset': 'gorilla.n.01'}, {'name': 'gourd', 'id': 509, 'frequency': 'r', 'synset': 'gourd.n.02'}, {'name': 'grape', 'id': 510, 'frequency': 'f', 'synset': 'grape.n.01'}, {'name': 'grater', 'id': 511, 'frequency': 'c', 'synset': 'grater.n.01'}, {'name': 'gravestone', 'id': 512, 'frequency': 'c', 'synset': 'gravestone.n.01'}, {'name': 'gravy_boat', 'id': 513, 'frequency': 'r', 'synset': 'gravy_boat.n.01'}, {'name': 'green_bean', 'id': 514, 'frequency': 'f', 'synset': 'green_bean.n.02'}, {'name': 'green_onion', 'id': 515, 'frequency': 'f', 'synset': 'green_onion.n.01'}, {'name': 'griddle', 'id': 516, 'frequency': 'r', 'synset': 'griddle.n.01'}, {'name': 'grill', 'id': 517, 'frequency': 'f', 'synset': 'grill.n.02'}, {'name': 'grits', 'id': 518, 'frequency': 'r', 'synset': 'grits.n.01'}, {'name': 'grizzly', 'id': 519, 'frequency': 'c', 'synset': 'grizzly.n.01'}, {'name': 'grocery_bag', 'id': 520, 'frequency': 'c', 'synset': 'grocery_bag.n.01'}, {'name': 'guitar', 'id': 521, 'frequency': 'f', 'synset': 'guitar.n.01'}, {'name': 'gull', 'id': 522, 'frequency': 'c', 'synset': 'gull.n.02'}, {'name': 'gun', 'id': 523, 'frequency': 'c', 'synset': 'gun.n.01'}, {'name': 'hairbrush', 'id': 524, 'frequency': 'f', 'synset': 'hairbrush.n.01'}, {'name': 'hairnet', 'id': 525, 'frequency': 'c', 'synset': 'hairnet.n.01'}, {'name': 'hairpin', 'id': 526, 'frequency': 'c', 'synset': 'hairpin.n.01'}, {'name': 'halter_top', 'id': 527, 'frequency': 'r', 'synset': 'halter.n.03'}, {'name': 'ham', 'id': 528, 'frequency': 'f', 'synset': 'ham.n.01'}, {'name': 'hamburger', 'id': 529, 'frequency': 'c', 'synset': 'hamburger.n.01'}, {'name': 'hammer', 'id': 530, 'frequency': 'c', 'synset': 'hammer.n.02'}, {'name': 'hammock', 'id': 531, 'frequency': 'c', 'synset': 'hammock.n.02'}, {'name': 'hamper', 'id': 532, 'frequency': 'r', 'synset': 'hamper.n.02'}, {'name': 'hamster', 'id': 533, 'frequency': 'c', 'synset': 'hamster.n.01'}, {'name': 'hair_dryer', 'id': 534, 'frequency': 'f', 'synset': 'hand_blower.n.01'}, {'name': 'hand_glass', 'id': 535, 'frequency': 'r', 'synset': 'hand_glass.n.01'}, {'name': 'hand_towel', 'id': 536, 'frequency': 'f', 'synset': 'hand_towel.n.01'}, {'name': 'handcart', 'id': 537, 'frequency': 'c', 'synset': 'handcart.n.01'}, {'name': 'handcuff', 'id': 538, 'frequency': 'r', 'synset': 'handcuff.n.01'}, {'name': 'handkerchief', 'id': 539, 'frequency': 'c', 'synset': 'handkerchief.n.01'}, {'name': 'handle', 'id': 540, 'frequency': 'f', 'synset': 'handle.n.01'}, {'name': 'handsaw', 'id': 541, 'frequency': 'r', 'synset': 'handsaw.n.01'}, {'name': 'hardback_book', 'id': 542, 'frequency': 'r', 'synset': 'hardback.n.01'}, {'name': 'harmonium', 'id': 543, 'frequency': 'r', 'synset': 'harmonium.n.01'}, {'name': 'hat', 'id': 544, 'frequency': 'f', 'synset': 'hat.n.01'}, {'name': 'hatbox', 'id': 545, 'frequency': 'r', 'synset': 'hatbox.n.01'}, {'name': 'veil', 'id': 546, 'frequency': 'c', 'synset': 'head_covering.n.01'}, {'name': 'headband', 'id': 547, 'frequency': 'f', 'synset': 'headband.n.01'}, {'name': 'headboard', 'id': 548, 'frequency': 'f', 'synset': 'headboard.n.01'}, {'name': 'headlight', 'id': 549, 'frequency': 'f', 'synset': 'headlight.n.01'}, {'name': 'headscarf', 'id': 550, 'frequency': 'c', 'synset': 'headscarf.n.01'}, {'name': 'headset', 'id': 551, 'frequency': 'r', 'synset': 'headset.n.01'}, {'name': 'headstall_(for_horses)', 'id': 552, 'frequency': 'c', 'synset': 'headstall.n.01'}, {'name': 'heart', 'id': 553, 'frequency': 'c', 'synset': 'heart.n.02'}, {'name': 'heater', 'id': 554, 'frequency': 'c', 'synset': 'heater.n.01'}, {'name': 'helicopter', 'id': 555, 'frequency': 'c', 'synset': 'helicopter.n.01'}, {'name': 'helmet', 'id': 556, 'frequency': 'f', 'synset': 'helmet.n.02'}, {'name': 'heron', 'id': 557, 'frequency': 'r', 'synset': 'heron.n.02'}, {'name': 'highchair', 'id': 558, 'frequency': 'c', 'synset': 'highchair.n.01'}, {'name': 'hinge', 'id': 559, 'frequency': 'f', 'synset': 'hinge.n.01'}, {'name': 'hippopotamus', 'id': 560, 'frequency': 'r', 'synset': 'hippopotamus.n.01'}, {'name': 'hockey_stick', 'id': 561, 'frequency': 'r', 'synset': 'hockey_stick.n.01'}, {'name': 'hog', 'id': 562, 'frequency': 'c', 'synset': 'hog.n.03'}, {'name': 'home_plate_(baseball)', 'id': 563, 'frequency': 'f', 'synset': 'home_plate.n.01'}, {'name': 'honey', 'id': 564, 'frequency': 'c', 'synset': 'honey.n.01'}, {'name': 'fume_hood', 'id': 565, 'frequency': 'f', 'synset': 'hood.n.06'}, {'name': 'hook', 'id': 566, 'frequency': 'f', 'synset': 'hook.n.05'}, {'name': 'hookah', 'id': 567, 'frequency': 'r', 'synset': 'hookah.n.01'}, {'name': 'hornet', 'id': 568, 'frequency': 'r', 'synset': 'hornet.n.01'}, {'name': 'horse', 'id': 569, 'frequency': 'f', 'synset': 'horse.n.01'}, {'name': 'hose', 'id': 570, 'frequency': 'f', 'synset': 'hose.n.03'}, {'name': 'hot-air_balloon', 'id': 571, 'frequency': 'r', 'synset': 'hot-air_balloon.n.01'}, {'name': 'hotplate', 'id': 572, 'frequency': 'r', 'synset': 'hot_plate.n.01'}, {'name': 'hot_sauce', 'id': 573, 'frequency': 'c', 'synset': 'hot_sauce.n.01'}, {'name': 'hourglass', 'id': 574, 'frequency': 'r', 'synset': 'hourglass.n.01'}, {'name': 'houseboat', 'id': 575, 'frequency': 'r', 'synset': 'houseboat.n.01'}, {'name': 'hummingbird', 'id': 576, 'frequency': 'c', 'synset': 'hummingbird.n.01'}, {'name': 'hummus', 'id': 577, 'frequency': 'r', 'synset': 'hummus.n.01'}, {'name': 'polar_bear', 'id': 578, 'frequency': 'f', 'synset': 'ice_bear.n.01'}, {'name': 'icecream', 'id': 579, 'frequency': 'c', 'synset': 'ice_cream.n.01'}, {'name': 'popsicle', 'id': 580, 'frequency': 'r', 'synset': 'ice_lolly.n.01'}, {'name': 'ice_maker', 'id': 581, 'frequency': 'c', 'synset': 'ice_maker.n.01'}, {'name': 'ice_pack', 'id': 582, 'frequency': 'r', 'synset': 'ice_pack.n.01'}, {'name': 'ice_skate', 'id': 583, 'frequency': 'r', 'synset': 'ice_skate.n.01'}, {'name': 'igniter', 'id': 584, 'frequency': 'c', 'synset': 'igniter.n.01'}, {'name': 'inhaler', 'id': 585, 'frequency': 'r', 'synset': 'inhaler.n.01'}, {'name': 'iPod', 'id': 586, 'frequency': 'f', 'synset': 'ipod.n.01'}, {'name': 'iron_(for_clothing)', 'id': 587, 'frequency': 'c', 'synset': 'iron.n.04'}, {'name': 'ironing_board', 'id': 588, 'frequency': 'c', 'synset': 'ironing_board.n.01'}, {'name': 'jacket', 'id': 589, 'frequency': 'f', 'synset': 'jacket.n.01'}, {'name': 'jam', 'id': 590, 'frequency': 'c', 'synset': 'jam.n.01'}, {'name': 'jar', 'id': 591, 'frequency': 'f', 'synset': 'jar.n.01'}, {'name': 'jean', 'id': 592, 'frequency': 'f', 'synset': 'jean.n.01'}, {'name': 'jeep', 'id': 593, 'frequency': 'c', 'synset': 'jeep.n.01'}, {'name': 'jelly_bean', 'id': 594, 'frequency': 'r', 'synset': 'jelly_bean.n.01'}, {'name': 'jersey', 'id': 595, 'frequency': 'f', 'synset': 'jersey.n.03'}, {'name': 'jet_plane', 'id': 596, 'frequency': 'c', 'synset': 'jet.n.01'}, {'name': 'jewel', 'id': 597, 'frequency': 'r', 'synset': 'jewel.n.01'}, {'name': 'jewelry', 'id': 598, 'frequency': 'c', 'synset': 'jewelry.n.01'}, {'name': 'joystick', 'id': 599, 'frequency': 'r', 'synset': 'joystick.n.02'}, {'name': 'jumpsuit', 'id': 600, 'frequency': 'c', 'synset': 'jump_suit.n.01'}, {'name': 'kayak', 'id': 601, 'frequency': 'c', 'synset': 'kayak.n.01'}, {'name': 'keg', 'id': 602, 'frequency': 'r', 'synset': 'keg.n.02'}, {'name': 'kennel', 'id': 603, 'frequency': 'r', 'synset': 'kennel.n.01'}, {'name': 'kettle', 'id': 604, 'frequency': 'c', 'synset': 'kettle.n.01'}, {'name': 'key', 'id': 605, 'frequency': 'f', 'synset': 'key.n.01'}, {'name': 'keycard', 'id': 606, 'frequency': 'r', 'synset': 'keycard.n.01'}, {'name': 'kilt', 'id': 607, 'frequency': 'c', 'synset': 'kilt.n.01'}, {'name': 'kimono', 'id': 608, 'frequency': 'c', 'synset': 'kimono.n.01'}, {'name': 'kitchen_sink', 'id': 609, 'frequency': 'f', 'synset': 'kitchen_sink.n.01'}, {'name': 'kitchen_table', 'id': 610, 'frequency': 'r', 'synset': 'kitchen_table.n.01'}, {'name': 'kite', 'id': 611, 'frequency': 'f', 'synset': 'kite.n.03'}, {'name': 'kitten', 'id': 612, 'frequency': 'c', 'synset': 'kitten.n.01'}, {'name': 'kiwi_fruit', 'id': 613, 'frequency': 'c', 'synset': 'kiwi.n.03'}, {'name': 'knee_pad', 'id': 614, 'frequency': 'f', 'synset': 'knee_pad.n.01'}, {'name': 'knife', 'id': 615, 'frequency': 'f', 'synset': 'knife.n.01'}, {'name': 'knitting_needle', 'id': 616, 'frequency': 'r', 'synset': 'knitting_needle.n.01'}, {'name': 'knob', 'id': 617, 'frequency': 'f', 'synset': 'knob.n.02'}, {'name': 'knocker_(on_a_door)', 'id': 618, 'frequency': 'r', 'synset': 'knocker.n.05'}, {'name': 'koala', 'id': 619, 'frequency': 'r', 'synset': 'koala.n.01'}, {'name': 'lab_coat', 'id': 620, 'frequency': 'r', 'synset': 'lab_coat.n.01'}, {'name': 'ladder', 'id': 621, 'frequency': 'f', 'synset': 'ladder.n.01'}, {'name': 'ladle', 'id': 622, 'frequency': 'c', 'synset': 'ladle.n.01'}, {'name': 'ladybug', 'id': 623, 'frequency': 'c', 'synset': 'ladybug.n.01'}, {'name': 'lamb_(animal)', 'id': 624, 'frequency': 'f', 'synset': 'lamb.n.01'}, {'name': 'lamb-chop', 'id': 625, 'frequency': 'r', 'synset': 'lamb_chop.n.01'}, {'name': 'lamp', 'id': 626, 'frequency': 'f', 'synset': 'lamp.n.02'}, {'name': 'lamppost', 'id': 627, 'frequency': 'f', 'synset': 'lamppost.n.01'}, {'name': 'lampshade', 'id': 628, 'frequency': 'f', 'synset': 'lampshade.n.01'}, {'name': 'lantern', 'id': 629, 'frequency': 'c', 'synset': 'lantern.n.01'}, {'name': 'lanyard', 'id': 630, 'frequency': 'f', 'synset': 'lanyard.n.02'}, {'name': 'laptop_computer', 'id': 631, 'frequency': 'f', 'synset': 'laptop.n.01'}, {'name': 'lasagna', 'id': 632, 'frequency': 'r', 'synset': 'lasagna.n.01'}, {'name': 'latch', 'id': 633, 'frequency': 'f', 'synset': 'latch.n.02'}, {'name': 'lawn_mower', 'id': 634, 'frequency': 'r', 'synset': 'lawn_mower.n.01'}, {'name': 'leather', 'id': 635, 'frequency': 'r', 'synset': 'leather.n.01'}, {'name': 'legging_(clothing)', 'id': 636, 'frequency': 'c', 'synset': 'legging.n.01'}, {'name': 'Lego', 'id': 637, 'frequency': 'c', 'synset': 'lego.n.01'}, {'name': 'legume', 'id': 638, 'frequency': 'r', 'synset': 'legume.n.02'}, {'name': 'lemon', 'id': 639, 'frequency': 'f', 'synset': 'lemon.n.01'}, {'name': 'lemonade', 'id': 640, 'frequency': 'r', 'synset': 'lemonade.n.01'}, {'name': 'lettuce', 'id': 641, 'frequency': 'f', 'synset': 'lettuce.n.02'}, {'name': 'license_plate', 'id': 642, 'frequency': 'f', 'synset': 'license_plate.n.01'}, {'name': 'life_buoy', 'id': 643, 'frequency': 'f', 'synset': 'life_buoy.n.01'}, {'name': 'life_jacket', 'id': 644, 'frequency': 'f', 'synset': 'life_jacket.n.01'}, {'name': 'lightbulb', 'id': 645, 'frequency': 'f', 'synset': 'light_bulb.n.01'}, {'name': 'lightning_rod', 'id': 646, 'frequency': 'r', 'synset': 'lightning_rod.n.02'}, {'name': 'lime', 'id': 647, 'frequency': 'f', 'synset': 'lime.n.06'}, {'name': 'limousine', 'id': 648, 'frequency': 'r', 'synset': 'limousine.n.01'}, {'name': 'lion', 'id': 649, 'frequency': 'c', 'synset': 'lion.n.01'}, {'name': 'lip_balm', 'id': 650, 'frequency': 'c', 'synset': 'lip_balm.n.01'}, {'name': 'liquor', 'id': 651, 'frequency': 'r', 'synset': 'liquor.n.01'}, {'name': 'lizard', 'id': 652, 'frequency': 'c', 'synset': 'lizard.n.01'}, {'name': 'log', 'id': 653, 'frequency': 'f', 'synset': 'log.n.01'}, {'name': 'lollipop', 'id': 654, 'frequency': 'c', 'synset': 'lollipop.n.02'}, {'name': 'speaker_(stero_equipment)', 'id': 655, 'frequency': 'f', 'synset': 'loudspeaker.n.01'}, {'name': 'loveseat', 'id': 656, 'frequency': 'c', 'synset': 'love_seat.n.01'}, {'name': 'machine_gun', 'id': 657, 'frequency': 'r', 'synset': 'machine_gun.n.01'}, {'name': 'magazine', 'id': 658, 'frequency': 'f', 'synset': 'magazine.n.02'}, {'name': 'magnet', 'id': 659, 'frequency': 'f', 'synset': 'magnet.n.01'}, {'name': 'mail_slot', 'id': 660, 'frequency': 'c', 'synset': 'mail_slot.n.01'}, {'name': 'mailbox_(at_home)', 'id': 661, 'frequency': 'f', 'synset': 'mailbox.n.01'}, {'name': 'mallard', 'id': 662, 'frequency': 'r', 'synset': 'mallard.n.01'}, {'name': 'mallet', 'id': 663, 'frequency': 'r', 'synset': 'mallet.n.01'}, {'name': 'mammoth', 'id': 664, 'frequency': 'r', 'synset': 'mammoth.n.01'}, {'name': 'manatee', 'id': 665, 'frequency': 'r', 'synset': 'manatee.n.01'}, {'name': 'mandarin_orange', 'id': 666, 'frequency': 'c', 'synset': 'mandarin.n.05'}, {'name': 'manger', 'id': 667, 'frequency': 'c', 'synset': 'manger.n.01'}, {'name': 'manhole', 'id': 668, 'frequency': 'f', 'synset': 'manhole.n.01'}, {'name': 'map', 'id': 669, 'frequency': 'f', 'synset': 'map.n.01'}, {'name': 'marker', 'id': 670, 'frequency': 'f', 'synset': 'marker.n.03'}, {'name': 'martini', 'id': 671, 'frequency': 'r', 'synset': 'martini.n.01'}, {'name': 'mascot', 'id': 672, 'frequency': 'r', 'synset': 'mascot.n.01'}, {'name': 'mashed_potato', 'id': 673, 'frequency': 'c', 'synset': 'mashed_potato.n.01'}, {'name': 'masher', 'id': 674, 'frequency': 'r', 'synset': 'masher.n.02'}, {'name': 'mask', 'id': 675, 'frequency': 'f', 'synset': 'mask.n.04'}, {'name': 'mast', 'id': 676, 'frequency': 'f', 'synset': 'mast.n.01'}, {'name': 'mat_(gym_equipment)', 'id': 677, 'frequency': 'c', 'synset': 'mat.n.03'}, {'name': 'matchbox', 'id': 678, 'frequency': 'r', 'synset': 'matchbox.n.01'}, {'name': 'mattress', 'id': 679, 'frequency': 'f', 'synset': 'mattress.n.01'}, {'name': 'measuring_cup', 'id': 680, 'frequency': 'c', 'synset': 'measuring_cup.n.01'}, {'name': 'measuring_stick', 'id': 681, 'frequency': 'c', 'synset': 'measuring_stick.n.01'}, {'name': 'meatball', 'id': 682, 'frequency': 'c', 'synset': 'meatball.n.01'}, {'name': 'medicine', 'id': 683, 'frequency': 'c', 'synset': 'medicine.n.02'}, {'name': 'melon', 'id': 684, 'frequency': 'c', 'synset': 'melon.n.01'}, {'name': 'microphone', 'id': 685, 'frequency': 'f', 'synset': 'microphone.n.01'}, {'name': 'microscope', 'id': 686, 'frequency': 'r', 'synset': 'microscope.n.01'}, {'name': 'microwave_oven', 'id': 687, 'frequency': 'f', 'synset': 'microwave.n.02'}, {'name': 'milestone', 'id': 688, 'frequency': 'r', 'synset': 'milestone.n.01'}, {'name': 'milk', 'id': 689, 'frequency': 'f', 'synset': 'milk.n.01'}, {'name': 'milk_can', 'id': 690, 'frequency': 'r', 'synset': 'milk_can.n.01'}, {'name': 'milkshake', 'id': 691, 'frequency': 'r', 'synset': 'milkshake.n.01'}, {'name': 'minivan', 'id': 692, 'frequency': 'f', 'synset': 'minivan.n.01'}, {'name': 'mint_candy', 'id': 693, 'frequency': 'r', 'synset': 'mint.n.05'}, {'name': 'mirror', 'id': 694, 'frequency': 'f', 'synset': 'mirror.n.01'}, {'name': 'mitten', 'id': 695, 'frequency': 'c', 'synset': 'mitten.n.01'}, {'name': 'mixer_(kitchen_tool)', 'id': 696, 'frequency': 'c', 'synset': 'mixer.n.04'}, {'name': 'money', 'id': 697, 'frequency': 'c', 'synset': 'money.n.03'}, {'name': 'monitor_(computer_equipment) computer_monitor', 'id': 698, 'frequency': 'f', 'synset': 'monitor.n.04'}, {'name': 'monkey', 'id': 699, 'frequency': 'c', 'synset': 'monkey.n.01'}, {'name': 'motor', 'id': 700, 'frequency': 'f', 'synset': 'motor.n.01'}, {'name': 'motor_scooter', 'id': 701, 'frequency': 'f', 'synset': 'motor_scooter.n.01'}, {'name': 'motor_vehicle', 'id': 702, 'frequency': 'r', 'synset': 'motor_vehicle.n.01'}, {'name': 'motorcycle', 'id': 703, 'frequency': 'f', 'synset': 'motorcycle.n.01'}, {'name': 'mound_(baseball)', 'id': 704, 'frequency': 'f', 'synset': 'mound.n.01'}, {'name': 'mouse_(computer_equipment)', 'id': 705, 'frequency': 'f', 'synset': 'mouse.n.04'}, {'name': 'mousepad', 'id': 706, 'frequency': 'f', 'synset': 'mousepad.n.01'}, {'name': 'muffin', 'id': 707, 'frequency': 'c', 'synset': 'muffin.n.01'}, {'name': 'mug', 'id': 708, 'frequency': 'f', 'synset': 'mug.n.04'}, {'name': 'mushroom', 'id': 709, 'frequency': 'f', 'synset': 'mushroom.n.02'}, {'name': 'music_stool', 'id': 710, 'frequency': 'r', 'synset': 'music_stool.n.01'}, {'name': 'musical_instrument', 'id': 711, 'frequency': 'c', 'synset': 'musical_instrument.n.01'}, {'name': 'nailfile', 'id': 712, 'frequency': 'r', 'synset': 'nailfile.n.01'}, {'name': 'napkin', 'id': 713, 'frequency': 'f', 'synset': 'napkin.n.01'}, {'name': 'neckerchief', 'id': 714, 'frequency': 'r', 'synset': 'neckerchief.n.01'}, {'name': 'necklace', 'id': 715, 'frequency': 'f', 'synset': 'necklace.n.01'}, {'name': 'necktie', 'id': 716, 'frequency': 'f', 'synset': 'necktie.n.01'}, {'name': 'needle', 'id': 717, 'frequency': 'c', 'synset': 'needle.n.03'}, {'name': 'nest', 'id': 718, 'frequency': 'c', 'synset': 'nest.n.01'}, {'name': 'newspaper', 'id': 719, 'frequency': 'f', 'synset': 'newspaper.n.01'}, {'name': 'newsstand', 'id': 720, 'frequency': 'c', 'synset': 'newsstand.n.01'}, {'name': 'nightshirt', 'id': 721, 'frequency': 'c', 'synset': 'nightwear.n.01'}, {'name': 'nosebag_(for_animals)', 'id': 722, 'frequency': 'r', 'synset': 'nosebag.n.01'}, {'name': 'noseband_(for_animals)', 'id': 723, 'frequency': 'c', 'synset': 'noseband.n.01'}, {'name': 'notebook', 'id': 724, 'frequency': 'f', 'synset': 'notebook.n.01'}, {'name': 'notepad', 'id': 725, 'frequency': 'c', 'synset': 'notepad.n.01'}, {'name': 'nut', 'id': 726, 'frequency': 'f', 'synset': 'nut.n.03'}, {'name': 'nutcracker', 'id': 727, 'frequency': 'r', 'synset': 'nutcracker.n.01'}, {'name': 'oar', 'id': 728, 'frequency': 'f', 'synset': 'oar.n.01'}, {'name': 'octopus_(food)', 'id': 729, 'frequency': 'r', 'synset': 'octopus.n.01'}, {'name': 'octopus_(animal)', 'id': 730, 'frequency': 'r', 'synset': 'octopus.n.02'}, {'name': 'oil_lamp', 'id': 731, 'frequency': 'c', 'synset': 'oil_lamp.n.01'}, {'name': 'olive_oil', 'id': 732, 'frequency': 'c', 'synset': 'olive_oil.n.01'}, {'name': 'omelet', 'id': 733, 'frequency': 'r', 'synset': 'omelet.n.01'}, {'name': 'onion', 'id': 734, 'frequency': 'f', 'synset': 'onion.n.01'}, {'name': 'orange_(fruit)', 'id': 735, 'frequency': 'f', 'synset': 'orange.n.01'}, {'name': 'orange_juice', 'id': 736, 'frequency': 'c', 'synset': 'orange_juice.n.01'}, {'name': 'ostrich', 'id': 737, 'frequency': 'c', 'synset': 'ostrich.n.02'}, {'name': 'ottoman', 'id': 738, 'frequency': 'f', 'synset': 'ottoman.n.03'}, {'name': 'oven', 'id': 739, 'frequency': 'f', 'synset': 'oven.n.01'}, {'name': 'overalls_(clothing)', 'id': 740, 'frequency': 'c', 'synset': 'overall.n.01'}, {'name': 'owl', 'id': 741, 'frequency': 'c', 'synset': 'owl.n.01'}, {'name': 'packet', 'id': 742, 'frequency': 'c', 'synset': 'packet.n.03'}, {'name': 'inkpad', 'id': 743, 'frequency': 'r', 'synset': 'pad.n.03'}, {'name': 'pad', 'id': 744, 'frequency': 'c', 'synset': 'pad.n.04'}, {'name': 'paddle', 'id': 745, 'frequency': 'f', 'synset': 'paddle.n.04'}, {'name': 'padlock', 'id': 746, 'frequency': 'c', 'synset': 'padlock.n.01'}, {'name': 'paintbrush', 'id': 747, 'frequency': 'c', 'synset': 'paintbrush.n.01'}, {'name': 'painting', 'id': 748, 'frequency': 'f', 'synset': 'painting.n.01'}, {'name': 'pajamas', 'id': 749, 'frequency': 'f', 'synset': 'pajama.n.02'}, {'name': 'palette', 'id': 750, 'frequency': 'c', 'synset': 'palette.n.02'}, {'name': 'pan_(for_cooking)', 'id': 751, 'frequency': 'f', 'synset': 'pan.n.01'}, {'name': 'pan_(metal_container)', 'id': 752, 'frequency': 'r', 'synset': 'pan.n.03'}, {'name': 'pancake', 'id': 753, 'frequency': 'c', 'synset': 'pancake.n.01'}, {'name': 'pantyhose', 'id': 754, 'frequency': 'r', 'synset': 'pantyhose.n.01'}, {'name': 'papaya', 'id': 755, 'frequency': 'r', 'synset': 'papaya.n.02'}, {'name': 'paper_plate', 'id': 756, 'frequency': 'f', 'synset': 'paper_plate.n.01'}, {'name': 'paper_towel', 'id': 757, 'frequency': 'f', 'synset': 'paper_towel.n.01'}, {'name': 'paperback_book', 'id': 758, 'frequency': 'r', 'synset': 'paperback_book.n.01'}, {'name': 'paperweight', 'id': 759, 'frequency': 'r', 'synset': 'paperweight.n.01'}, {'name': 'parachute', 'id': 760, 'frequency': 'c', 'synset': 'parachute.n.01'}, {'name': 'parakeet', 'id': 761, 'frequency': 'c', 'synset': 'parakeet.n.01'}, {'name': 'parasail_(sports)', 'id': 762, 'frequency': 'c', 'synset': 'parasail.n.01'}, {'name': 'parasol', 'id': 763, 'frequency': 'c', 'synset': 'parasol.n.01'}, {'name': 'parchment', 'id': 764, 'frequency': 'r', 'synset': 'parchment.n.01'}, {'name': 'parka', 'id': 765, 'frequency': 'c', 'synset': 'parka.n.01'}, {'name': 'parking_meter', 'id': 766, 'frequency': 'f', 'synset': 'parking_meter.n.01'}, {'name': 'parrot', 'id': 767, 'frequency': 'c', 'synset': 'parrot.n.01'}, {'name': 'passenger_car_(part_of_a_train)', 'id': 768, 'frequency': 'c', 'synset': 'passenger_car.n.01'}, {'name': 'passenger_ship', 'id': 769, 'frequency': 'r', 'synset': 'passenger_ship.n.01'}, {'name': 'passport', 'id': 770, 'frequency': 'c', 'synset': 'passport.n.02'}, {'name': 'pastry', 'id': 771, 'frequency': 'f', 'synset': 'pastry.n.02'}, {'name': 'patty_(food)', 'id': 772, 'frequency': 'r', 'synset': 'patty.n.01'}, {'name': 'pea_(food)', 'id': 773, 'frequency': 'c', 'synset': 'pea.n.01'}, {'name': 'peach', 'id': 774, 'frequency': 'c', 'synset': 'peach.n.03'}, {'name': 'peanut_butter', 'id': 775, 'frequency': 'c', 'synset': 'peanut_butter.n.01'}, {'name': 'pear', 'id': 776, 'frequency': 'f', 'synset': 'pear.n.01'}, {'name': 'peeler_(tool_for_fruit_and_vegetables)', 'id': 777, 'frequency': 'c', 'synset': 'peeler.n.03'}, {'name': 'wooden_leg', 'id': 778, 'frequency': 'r', 'synset': 'peg.n.04'}, {'name': 'pegboard', 'id': 779, 'frequency': 'r', 'synset': 'pegboard.n.01'}, {'name': 'pelican', 'id': 780, 'frequency': 'c', 'synset': 'pelican.n.01'}, {'name': 'pen', 'id': 781, 'frequency': 'f', 'synset': 'pen.n.01'}, {'name': 'pencil', 'id': 782, 'frequency': 'f', 'synset': 'pencil.n.01'}, {'name': 'pencil_box', 'id': 783, 'frequency': 'r', 'synset': 'pencil_box.n.01'}, {'name': 'pencil_sharpener', 'id': 784, 'frequency': 'r', 'synset': 'pencil_sharpener.n.01'}, {'name': 'pendulum', 'id': 785, 'frequency': 'r', 'synset': 'pendulum.n.01'}, {'name': 'penguin', 'id': 786, 'frequency': 'c', 'synset': 'penguin.n.01'}, {'name': 'pennant', 'id': 787, 'frequency': 'r', 'synset': 'pennant.n.02'}, {'name': 'penny_(coin)', 'id': 788, 'frequency': 'r', 'synset': 'penny.n.02'}, {'name': 'pepper', 'id': 789, 'frequency': 'f', 'synset': 'pepper.n.03'}, {'name': 'pepper_mill', 'id': 790, 'frequency': 'c', 'synset': 'pepper_mill.n.01'}, {'name': 'perfume', 'id': 791, 'frequency': 'c', 'synset': 'perfume.n.02'}, {'name': 'persimmon', 'id': 792, 'frequency': 'r', 'synset': 'persimmon.n.02'}, {'name': 'person', 'id': 793, 'frequency': 'f', 'synset': 'person.n.01'}, {'name': 'pet', 'id': 794, 'frequency': 'c', 'synset': 'pet.n.01'}, {'name': 'pew_(church_bench)', 'id': 795, 'frequency': 'c', 'synset': 'pew.n.01'}, {'name': 'phonebook', 'id': 796, 'frequency': 'r', 'synset': 'phonebook.n.01'}, {'name': 'phonograph_record', 'id': 797, 'frequency': 'c', 'synset': 'phonograph_record.n.01'}, {'name': 'piano', 'id': 798, 'frequency': 'f', 'synset': 'piano.n.01'}, {'name': 'pickle', 'id': 799, 'frequency': 'f', 'synset': 'pickle.n.01'}, {'name': 'pickup_truck', 'id': 800, 'frequency': 'f', 'synset': 'pickup.n.01'}, {'name': 'pie', 'id': 801, 'frequency': 'c', 'synset': 'pie.n.01'}, {'name': 'pigeon', 'id': 802, 'frequency': 'c', 'synset': 'pigeon.n.01'}, {'name': 'piggy_bank', 'id': 803, 'frequency': 'r', 'synset': 'piggy_bank.n.01'}, {'name': 'pillow', 'id': 804, 'frequency': 'f', 'synset': 'pillow.n.01'}, {'name': 'pin_(non_jewelry)', 'id': 805, 'frequency': 'r', 'synset': 'pin.n.09'}, {'name': 'pineapple', 'id': 806, 'frequency': 'f', 'synset': 'pineapple.n.02'}, {'name': 'pinecone', 'id': 807, 'frequency': 'c', 'synset': 'pinecone.n.01'}, {'name': 'ping-pong_ball', 'id': 808, 'frequency': 'r', 'synset': 'ping-pong_ball.n.01'}, {'name': 'pinwheel', 'id': 809, 'frequency': 'r', 'synset': 'pinwheel.n.03'}, {'name': 'tobacco_pipe', 'id': 810, 'frequency': 'r', 'synset': 'pipe.n.01'}, {'name': 'pipe', 'id': 811, 'frequency': 'f', 'synset': 'pipe.n.02'}, {'name': 'pistol', 'id': 812, 'frequency': 'r', 'synset': 'pistol.n.01'}, {'name': 'pita_(bread)', 'id': 813, 'frequency': 'c', 'synset': 'pita.n.01'}, {'name': 'pitcher_(vessel_for_liquid)', 'id': 814, 'frequency': 'f', 'synset': 'pitcher.n.02'}, {'name': 'pitchfork', 'id': 815, 'frequency': 'r', 'synset': 'pitchfork.n.01'}, {'name': 'pizza', 'id': 816, 'frequency': 'f', 'synset': 'pizza.n.01'}, {'name': 'place_mat', 'id': 817, 'frequency': 'f', 'synset': 'place_mat.n.01'}, {'name': 'plate', 'id': 818, 'frequency': 'f', 'synset': 'plate.n.04'}, {'name': 'platter', 'id': 819, 'frequency': 'c', 'synset': 'platter.n.01'}, {'name': 'playpen', 'id': 820, 'frequency': 'r', 'synset': 'playpen.n.01'}, {'name': 'pliers', 'id': 821, 'frequency': 'c', 'synset': 'pliers.n.01'}, {'name': 'plow_(farm_equipment)', 'id': 822, 'frequency': 'r', 'synset': 'plow.n.01'}, {'name': 'plume', 'id': 823, 'frequency': 'r', 'synset': 'plume.n.02'}, {'name': 'pocket_watch', 'id': 824, 'frequency': 'r', 'synset': 'pocket_watch.n.01'}, {'name': 'pocketknife', 'id': 825, 'frequency': 'c', 'synset': 'pocketknife.n.01'}, {'name': 'poker_(fire_stirring_tool)', 'id': 826, 'frequency': 'c', 'synset': 'poker.n.01'}, {'name': 'pole', 'id': 827, 'frequency': 'f', 'synset': 'pole.n.01'}, {'name': 'polo_shirt', 'id': 828, 'frequency': 'f', 'synset': 'polo_shirt.n.01'}, {'name': 'poncho', 'id': 829, 'frequency': 'r', 'synset': 'poncho.n.01'}, {'name': 'pony', 'id': 830, 'frequency': 'c', 'synset': 'pony.n.05'}, {'name': 'pool_table', 'id': 831, 'frequency': 'r', 'synset': 'pool_table.n.01'}, {'name': 'pop_(soda)', 'id': 832, 'frequency': 'f', 'synset': 'pop.n.02'}, {'name': 'postbox_(public)', 'id': 833, 'frequency': 'c', 'synset': 'postbox.n.01'}, {'name': 'postcard', 'id': 834, 'frequency': 'c', 'synset': 'postcard.n.01'}, {'name': 'poster', 'id': 835, 'frequency': 'f', 'synset': 'poster.n.01'}, {'name': 'pot', 'id': 836, 'frequency': 'f', 'synset': 'pot.n.01'}, {'name': 'flowerpot', 'id': 837, 'frequency': 'f', 'synset': 'pot.n.04'}, {'name': 'potato', 'id': 838, 'frequency': 'f', 'synset': 'potato.n.01'}, {'name': 'potholder', 'id': 839, 'frequency': 'c', 'synset': 'potholder.n.01'}, {'name': 'pottery', 'id': 840, 'frequency': 'c', 'synset': 'pottery.n.01'}, {'name': 'pouch', 'id': 841, 'frequency': 'c', 'synset': 'pouch.n.01'}, {'name': 'power_shovel', 'id': 842, 'frequency': 'c', 'synset': 'power_shovel.n.01'}, {'name': 'prawn', 'id': 843, 'frequency': 'c', 'synset': 'prawn.n.01'}, {'name': 'pretzel', 'id': 844, 'frequency': 'c', 'synset': 'pretzel.n.01'}, {'name': 'printer', 'id': 845, 'frequency': 'f', 'synset': 'printer.n.03'}, {'name': 'projectile_(weapon)', 'id': 846, 'frequency': 'c', 'synset': 'projectile.n.01'}, {'name': 'projector', 'id': 847, 'frequency': 'c', 'synset': 'projector.n.02'}, {'name': 'propeller', 'id': 848, 'frequency': 'f', 'synset': 'propeller.n.01'}, {'name': 'prune', 'id': 849, 'frequency': 'r', 'synset': 'prune.n.01'}, {'name': 'pudding', 'id': 850, 'frequency': 'r', 'synset': 'pudding.n.01'}, {'name': 'puffer_(fish)', 'id': 851, 'frequency': 'r', 'synset': 'puffer.n.02'}, {'name': 'puffin', 'id': 852, 'frequency': 'r', 'synset': 'puffin.n.01'}, {'name': 'pug-dog', 'id': 853, 'frequency': 'r', 'synset': 'pug.n.01'}, {'name': 'pumpkin', 'id': 854, 'frequency': 'c', 'synset': 'pumpkin.n.02'}, {'name': 'puncher', 'id': 855, 'frequency': 'r', 'synset': 'punch.n.03'}, {'name': 'puppet', 'id': 856, 'frequency': 'r', 'synset': 'puppet.n.01'}, {'name': 'puppy', 'id': 857, 'frequency': 'c', 'synset': 'puppy.n.01'}, {'name': 'quesadilla', 'id': 858, 'frequency': 'r', 'synset': 'quesadilla.n.01'}, {'name': 'quiche', 'id': 859, 'frequency': 'r', 'synset': 'quiche.n.02'}, {'name': 'quilt', 'id': 860, 'frequency': 'f', 'synset': 'quilt.n.01'}, {'name': 'rabbit', 'id': 861, 'frequency': 'c', 'synset': 'rabbit.n.01'}, {'name': 'race_car', 'id': 862, 'frequency': 'r', 'synset': 'racer.n.02'}, {'name': 'racket', 'id': 863, 'frequency': 'c', 'synset': 'racket.n.04'}, {'name': 'radar', 'id': 864, 'frequency': 'r', 'synset': 'radar.n.01'}, {'name': 'radiator', 'id': 865, 'frequency': 'f', 'synset': 'radiator.n.03'}, {'name': 'radio_receiver', 'id': 866, 'frequency': 'c', 'synset': 'radio_receiver.n.01'}, {'name': 'radish', 'id': 867, 'frequency': 'c', 'synset': 'radish.n.03'}, {'name': 'raft', 'id': 868, 'frequency': 'c', 'synset': 'raft.n.01'}, {'name': 'rag_doll', 'id': 869, 'frequency': 'r', 'synset': 'rag_doll.n.01'}, {'name': 'raincoat', 'id': 870, 'frequency': 'c', 'synset': 'raincoat.n.01'}, {'name': 'ram_(animal)', 'id': 871, 'frequency': 'c', 'synset': 'ram.n.05'}, {'name': 'raspberry', 'id': 872, 'frequency': 'c', 'synset': 'raspberry.n.02'}, {'name': 'rat', 'id': 873, 'frequency': 'r', 'synset': 'rat.n.01'}, {'name': 'razorblade', 'id': 874, 'frequency': 'c', 'synset': 'razorblade.n.01'}, {'name': 'reamer_(juicer)', 'id': 875, 'frequency': 'c', 'synset': 'reamer.n.01'}, {'name': 'rearview_mirror', 'id': 876, 'frequency': 'f', 'synset': 'rearview_mirror.n.01'}, {'name': 'receipt', 'id': 877, 'frequency': 'c', 'synset': 'receipt.n.02'}, {'name': 'recliner', 'id': 878, 'frequency': 'c', 'synset': 'recliner.n.01'}, {'name': 'record_player', 'id': 879, 'frequency': 'c', 'synset': 'record_player.n.01'}, {'name': 'reflector', 'id': 880, 'frequency': 'f', 'synset': 'reflector.n.01'}, {'name': 'remote_control', 'id': 881, 'frequency': 'f', 'synset': 'remote_control.n.01'}, {'name': 'rhinoceros', 'id': 882, 'frequency': 'c', 'synset': 'rhinoceros.n.01'}, {'name': 'rib_(food)', 'id': 883, 'frequency': 'r', 'synset': 'rib.n.03'}, {'name': 'rifle', 'id': 884, 'frequency': 'c', 'synset': 'rifle.n.01'}, {'name': 'ring', 'id': 885, 'frequency': 'f', 'synset': 'ring.n.08'}, {'name': 'river_boat', 'id': 886, 'frequency': 'r', 'synset': 'river_boat.n.01'}, {'name': 'road_map', 'id': 887, 'frequency': 'r', 'synset': 'road_map.n.02'}, {'name': 'robe', 'id': 888, 'frequency': 'c', 'synset': 'robe.n.01'}, {'name': 'rocking_chair', 'id': 889, 'frequency': 'c', 'synset': 'rocking_chair.n.01'}, {'name': 'rodent', 'id': 890, 'frequency': 'r', 'synset': 'rodent.n.01'}, {'name': 'roller_skate', 'id': 891, 'frequency': 'r', 'synset': 'roller_skate.n.01'}, {'name': 'Rollerblade', 'id': 892, 'frequency': 'r', 'synset': 'rollerblade.n.01'}, {'name': 'rolling_pin', 'id': 893, 'frequency': 'c', 'synset': 'rolling_pin.n.01'}, {'name': 'root_beer', 'id': 894, 'frequency': 'r', 'synset': 'root_beer.n.01'}, {'name': 'router_(computer_equipment)', 'id': 895, 'frequency': 'c', 'synset': 'router.n.02'}, {'name': 'rubber_band', 'id': 896, 'frequency': 'f', 'synset': 'rubber_band.n.01'}, {'name': 'runner_(carpet)', 'id': 897, 'frequency': 'c', 'synset': 'runner.n.08'}, {'name': 'plastic_bag', 'id': 898, 'frequency': 'f', 'synset': 'sack.n.01'}, {'name': 'saddle_(on_an_animal)', 'id': 899, 'frequency': 'f', 'synset': 'saddle.n.01'}, {'name': 'saddle_blanket', 'id': 900, 'frequency': 'f', 'synset': 'saddle_blanket.n.01'}, {'name': 'saddlebag', 'id': 901, 'frequency': 'c', 'synset': 'saddlebag.n.01'}, {'name': 'safety_pin', 'id': 902, 'frequency': 'r', 'synset': 'safety_pin.n.01'}, {'name': 'sail', 'id': 903, 'frequency': 'f', 'synset': 'sail.n.01'}, {'name': 'salad', 'id': 904, 'frequency': 'f', 'synset': 'salad.n.01'}, {'name': 'salad_plate', 'id': 905, 'frequency': 'r', 'synset': 'salad_plate.n.01'}, {'name': 'salami', 'id': 906, 'frequency': 'c', 'synset': 'salami.n.01'}, {'name': 'salmon_(fish)', 'id': 907, 'frequency': 'c', 'synset': 'salmon.n.01'}, {'name': 'salmon_(food)', 'id': 908, 'frequency': 'r', 'synset': 'salmon.n.03'}, {'name': 'salsa', 'id': 909, 'frequency': 'c', 'synset': 'salsa.n.01'}, {'name': 'saltshaker', 'id': 910, 'frequency': 'f', 'synset': 'saltshaker.n.01'}, {'name': 'sandal_(type_of_shoe)', 'id': 911, 'frequency': 'f', 'synset': 'sandal.n.01'}, {'name': 'sandwich', 'id': 912, 'frequency': 'f', 'synset': 'sandwich.n.01'}, {'name': 'satchel', 'id': 913, 'frequency': 'r', 'synset': 'satchel.n.01'}, {'name': 'saucepan', 'id': 914, 'frequency': 'r', 'synset': 'saucepan.n.01'}, {'name': 'saucer', 'id': 915, 'frequency': 'f', 'synset': 'saucer.n.02'}, {'name': 'sausage', 'id': 916, 'frequency': 'f', 'synset': 'sausage.n.01'}, {'name': 'sawhorse', 'id': 917, 'frequency': 'r', 'synset': 'sawhorse.n.01'}, {'name': 'saxophone', 'id': 918, 'frequency': 'r', 'synset': 'sax.n.02'}, {'name': 'scale_(measuring_instrument)', 'id': 919, 'frequency': 'f', 'synset': 'scale.n.07'}, {'name': 'scarecrow', 'id': 920, 'frequency': 'r', 'synset': 'scarecrow.n.01'}, {'name': 'scarf', 'id': 921, 'frequency': 'f', 'synset': 'scarf.n.01'}, {'name': 'school_bus', 'id': 922, 'frequency': 'c', 'synset': 'school_bus.n.01'}, {'name': 'scissors', 'id': 923, 'frequency': 'f', 'synset': 'scissors.n.01'}, {'name': 'scoreboard', 'id': 924, 'frequency': 'f', 'synset': 'scoreboard.n.01'}, {'name': 'scraper', 'id': 925, 'frequency': 'r', 'synset': 'scraper.n.01'}, {'name': 'screwdriver', 'id': 926, 'frequency': 'c', 'synset': 'screwdriver.n.01'}, {'name': 'scrubbing_brush', 'id': 927, 'frequency': 'f', 'synset': 'scrub_brush.n.01'}, {'name': 'sculpture', 'id': 928, 'frequency': 'c', 'synset': 'sculpture.n.01'}, {'name': 'seabird', 'id': 929, 'frequency': 'c', 'synset': 'seabird.n.01'}, {'name': 'seahorse', 'id': 930, 'frequency': 'c', 'synset': 'seahorse.n.02'}, {'name': 'seaplane', 'id': 931, 'frequency': 'r', 'synset': 'seaplane.n.01'}, {'name': 'seashell', 'id': 932, 'frequency': 'c', 'synset': 'seashell.n.01'}, {'name': 'sewing_machine', 'id': 933, 'frequency': 'c', 'synset': 'sewing_machine.n.01'}, {'name': 'shaker', 'id': 934, 'frequency': 'c', 'synset': 'shaker.n.03'}, {'name': 'shampoo', 'id': 935, 'frequency': 'c', 'synset': 'shampoo.n.01'}, {'name': 'shark', 'id': 936, 'frequency': 'c', 'synset': 'shark.n.01'}, {'name': 'sharpener', 'id': 937, 'frequency': 'r', 'synset': 'sharpener.n.01'}, {'name': 'Sharpie', 'id': 938, 'frequency': 'r', 'synset': 'sharpie.n.03'}, {'name': 'shaver_(electric)', 'id': 939, 'frequency': 'r', 'synset': 'shaver.n.03'}, {'name': 'shaving_cream', 'id': 940, 'frequency': 'c', 'synset': 'shaving_cream.n.01'}, {'name': 'shawl', 'id': 941, 'frequency': 'r', 'synset': 'shawl.n.01'}, {'name': 'shears', 'id': 942, 'frequency': 'r', 'synset': 'shears.n.01'}, {'name': 'sheep', 'id': 943, 'frequency': 'f', 'synset': 'sheep.n.01'}, {'name': 'shepherd_dog', 'id': 944, 'frequency': 'r', 'synset': 'shepherd_dog.n.01'}, {'name': 'sherbert', 'id': 945, 'frequency': 'r', 'synset': 'sherbert.n.01'}, {'name': 'shield', 'id': 946, 'frequency': 'c', 'synset': 'shield.n.02'}, {'name': 'shirt', 'id': 947, 'frequency': 'f', 'synset': 'shirt.n.01'}, {'name': 'shoe', 'id': 948, 'frequency': 'f', 'synset': 'shoe.n.01'}, {'name': 'shopping_bag', 'id': 949, 'frequency': 'f', 'synset': 'shopping_bag.n.01'}, {'name': 'shopping_cart', 'id': 950, 'frequency': 'c', 'synset': 'shopping_cart.n.01'}, {'name': 'short_pants', 'id': 951, 'frequency': 'f', 'synset': 'short_pants.n.01'}, {'name': 'shot_glass', 'id': 952, 'frequency': 'r', 'synset': 'shot_glass.n.01'}, {'name': 'shoulder_bag', 'id': 953, 'frequency': 'f', 'synset': 'shoulder_bag.n.01'}, {'name': 'shovel', 'id': 954, 'frequency': 'c', 'synset': 'shovel.n.01'}, {'name': 'shower_head', 'id': 955, 'frequency': 'f', 'synset': 'shower.n.01'}, {'name': 'shower_cap', 'id': 956, 'frequency': 'r', 'synset': 'shower_cap.n.01'}, {'name': 'shower_curtain', 'id': 957, 'frequency': 'f', 'synset': 'shower_curtain.n.01'}, {'name': 'shredder_(for_paper)', 'id': 958, 'frequency': 'r', 'synset': 'shredder.n.01'}, {'name': 'signboard', 'id': 959, 'frequency': 'f', 'synset': 'signboard.n.01'}, {'name': 'silo', 'id': 960, 'frequency': 'c', 'synset': 'silo.n.01'}, {'name': 'sink', 'id': 961, 'frequency': 'f', 'synset': 'sink.n.01'}, {'name': 'skateboard', 'id': 962, 'frequency': 'f', 'synset': 'skateboard.n.01'}, {'name': 'skewer', 'id': 963, 'frequency': 'c', 'synset': 'skewer.n.01'}, {'name': 'ski', 'id': 964, 'frequency': 'f', 'synset': 'ski.n.01'}, {'name': 'ski_boot', 'id': 965, 'frequency': 'f', 'synset': 'ski_boot.n.01'}, {'name': 'ski_parka', 'id': 966, 'frequency': 'f', 'synset': 'ski_parka.n.01'}, {'name': 'ski_pole', 'id': 967, 'frequency': 'f', 'synset': 'ski_pole.n.01'}, {'name': 'skirt', 'id': 968, 'frequency': 'f', 'synset': 'skirt.n.02'}, {'name': 'skullcap', 'id': 969, 'frequency': 'r', 'synset': 'skullcap.n.01'}, {'name': 'sled', 'id': 970, 'frequency': 'c', 'synset': 'sled.n.01'}, {'name': 'sleeping_bag', 'id': 971, 'frequency': 'c', 'synset': 'sleeping_bag.n.01'}, {'name': 'sling_(bandage)', 'id': 972, 'frequency': 'r', 'synset': 'sling.n.05'}, {'name': 'slipper_(footwear)', 'id': 973, 'frequency': 'c', 'synset': 'slipper.n.01'}, {'name': 'smoothie', 'id': 974, 'frequency': 'r', 'synset': 'smoothie.n.02'}, {'name': 'snake', 'id': 975, 'frequency': 'r', 'synset': 'snake.n.01'}, {'name': 'snowboard', 'id': 976, 'frequency': 'f', 'synset': 'snowboard.n.01'}, {'name': 'snowman', 'id': 977, 'frequency': 'c', 'synset': 'snowman.n.01'}, {'name': 'snowmobile', 'id': 978, 'frequency': 'c', 'synset': 'snowmobile.n.01'}, {'name': 'soap', 'id': 979, 'frequency': 'f', 'synset': 'soap.n.01'}, {'name': 'soccer_ball', 'id': 980, 'frequency': 'f', 'synset': 'soccer_ball.n.01'}, {'name': 'sock', 'id': 981, 'frequency': 'f', 'synset': 'sock.n.01'}, {'name': 'sofa', 'id': 982, 'frequency': 'f', 'synset': 'sofa.n.01'}, {'name': 'softball', 'id': 983, 'frequency': 'r', 'synset': 'softball.n.01'}, {'name': 'solar_array', 'id': 984, 'frequency': 'c', 'synset': 'solar_array.n.01'}, {'name': 'sombrero', 'id': 985, 'frequency': 'r', 'synset': 'sombrero.n.02'}, {'name': 'soup', 'id': 986, 'frequency': 'f', 'synset': 'soup.n.01'}, {'name': 'soup_bowl', 'id': 987, 'frequency': 'r', 'synset': 'soup_bowl.n.01'}, {'name': 'soupspoon', 'id': 988, 'frequency': 'c', 'synset': 'soupspoon.n.01'}, {'name': 'sour_cream', 'id': 989, 'frequency': 'c', 'synset': 'sour_cream.n.01'}, {'name': 'soya_milk', 'id': 990, 'frequency': 'r', 'synset': 'soya_milk.n.01'}, {'name': 'space_shuttle', 'id': 991, 'frequency': 'r', 'synset': 'space_shuttle.n.01'}, {'name': 'sparkler_(fireworks)', 'id': 992, 'frequency': 'r', 'synset': 'sparkler.n.02'}, {'name': 'spatula', 'id': 993, 'frequency': 'f', 'synset': 'spatula.n.02'}, {'name': 'spear', 'id': 994, 'frequency': 'r', 'synset': 'spear.n.01'}, {'name': 'spectacles', 'id': 995, 'frequency': 'f', 'synset': 'spectacles.n.01'}, {'name': 'spice_rack', 'id': 996, 'frequency': 'c', 'synset': 'spice_rack.n.01'}, {'name': 'spider', 'id': 997, 'frequency': 'c', 'synset': 'spider.n.01'}, {'name': 'crawfish', 'id': 998, 'frequency': 'r', 'synset': 'spiny_lobster.n.02'}, {'name': 'sponge', 'id': 999, 'frequency': 'c', 'synset': 'sponge.n.01'}, {'name': 'spoon', 'id': 1000, 'frequency': 'f', 'synset': 'spoon.n.01'}, {'name': 'sportswear', 'id': 1001, 'frequency': 'c', 'synset': 'sportswear.n.01'}, {'name': 'spotlight', 'id': 1002, 'frequency': 'c', 'synset': 'spotlight.n.02'}, {'name': 'squid_(food)', 'id': 1003, 'frequency': 'r', 'synset': 'squid.n.01'}, {'name': 'squirrel', 'id': 1004, 'frequency': 'c', 'synset': 'squirrel.n.01'}, {'name': 'stagecoach', 'id': 1005, 'frequency': 'r', 'synset': 'stagecoach.n.01'}, {'name': 'stapler_(stapling_machine)', 'id': 1006, 'frequency': 'c', 'synset': 'stapler.n.01'}, {'name': 'starfish', 'id': 1007, 'frequency': 'c', 'synset': 'starfish.n.01'}, {'name': 'statue_(sculpture)', 'id': 1008, 'frequency': 'f', 'synset': 'statue.n.01'}, {'name': 'steak_(food)', 'id': 1009, 'frequency': 'c', 'synset': 'steak.n.01'}, {'name': 'steak_knife', 'id': 1010, 'frequency': 'r', 'synset': 'steak_knife.n.01'}, {'name': 'steering_wheel', 'id': 1011, 'frequency': 'f', 'synset': 'steering_wheel.n.01'}, {'name': 'stepladder', 'id': 1012, 'frequency': 'r', 'synset': 'step_ladder.n.01'}, {'name': 'step_stool', 'id': 1013, 'frequency': 'c', 'synset': 'step_stool.n.01'}, {'name': 'stereo_(sound_system)', 'id': 1014, 'frequency': 'c', 'synset': 'stereo.n.01'}, {'name': 'stew', 'id': 1015, 'frequency': 'r', 'synset': 'stew.n.02'}, {'name': 'stirrer', 'id': 1016, 'frequency': 'r', 'synset': 'stirrer.n.02'}, {'name': 'stirrup', 'id': 1017, 'frequency': 'f', 'synset': 'stirrup.n.01'}, {'name': 'stool', 'id': 1018, 'frequency': 'f', 'synset': 'stool.n.01'}, {'name': 'stop_sign', 'id': 1019, 'frequency': 'f', 'synset': 'stop_sign.n.01'}, {'name': 'brake_light', 'id': 1020, 'frequency': 'f', 'synset': 'stoplight.n.01'}, {'name': 'stove', 'id': 1021, 'frequency': 'f', 'synset': 'stove.n.01'}, {'name': 'strainer', 'id': 1022, 'frequency': 'c', 'synset': 'strainer.n.01'}, {'name': 'strap', 'id': 1023, 'frequency': 'f', 'synset': 'strap.n.01'}, {'name': 'straw_(for_drinking)', 'id': 1024, 'frequency': 'f', 'synset': 'straw.n.04'}, {'name': 'strawberry', 'id': 1025, 'frequency': 'f', 'synset': 'strawberry.n.01'}, {'name': 'street_sign', 'id': 1026, 'frequency': 'f', 'synset': 'street_sign.n.01'}, {'name': 'streetlight', 'id': 1027, 'frequency': 'f', 'synset': 'streetlight.n.01'}, {'name': 'string_cheese', 'id': 1028, 'frequency': 'r', 'synset': 'string_cheese.n.01'}, {'name': 'stylus', 'id': 1029, 'frequency': 'r', 'synset': 'stylus.n.02'}, {'name': 'subwoofer', 'id': 1030, 'frequency': 'r', 'synset': 'subwoofer.n.01'}, {'name': 'sugar_bowl', 'id': 1031, 'frequency': 'r', 'synset': 'sugar_bowl.n.01'}, {'name': 'sugarcane_(plant)', 'id': 1032, 'frequency': 'r', 'synset': 'sugarcane.n.01'}, {'name': 'suit_(clothing)', 'id': 1033, 'frequency': 'f', 'synset': 'suit.n.01'}, {'name': 'sunflower', 'id': 1034, 'frequency': 'c', 'synset': 'sunflower.n.01'}, {'name': 'sunglasses', 'id': 1035, 'frequency': 'f', 'synset': 'sunglasses.n.01'}, {'name': 'sunhat', 'id': 1036, 'frequency': 'c', 'synset': 'sunhat.n.01'}, {'name': 'surfboard', 'id': 1037, 'frequency': 'f', 'synset': 'surfboard.n.01'}, {'name': 'sushi', 'id': 1038, 'frequency': 'c', 'synset': 'sushi.n.01'}, {'name': 'mop', 'id': 1039, 'frequency': 'c', 'synset': 'swab.n.02'}, {'name': 'sweat_pants', 'id': 1040, 'frequency': 'c', 'synset': 'sweat_pants.n.01'}, {'name': 'sweatband', 'id': 1041, 'frequency': 'c', 'synset': 'sweatband.n.02'}, {'name': 'sweater', 'id': 1042, 'frequency': 'f', 'synset': 'sweater.n.01'}, {'name': 'sweatshirt', 'id': 1043, 'frequency': 'f', 'synset': 'sweatshirt.n.01'}, {'name': 'sweet_potato', 'id': 1044, 'frequency': 'c', 'synset': 'sweet_potato.n.02'}, {'name': 'swimsuit', 'id': 1045, 'frequency': 'f', 'synset': 'swimsuit.n.01'}, {'name': 'sword', 'id': 1046, 'frequency': 'c', 'synset': 'sword.n.01'}, {'name': 'syringe', 'id': 1047, 'frequency': 'r', 'synset': 'syringe.n.01'}, {'name': 'Tabasco_sauce', 'id': 1048, 'frequency': 'r', 'synset': 'tabasco.n.02'}, {'name': 'table-tennis_table', 'id': 1049, 'frequency': 'r', 'synset': 'table-tennis_table.n.01'}, {'name': 'table', 'id': 1050, 'frequency': 'f', 'synset': 'table.n.02'}, {'name': 'table_lamp', 'id': 1051, 'frequency': 'c', 'synset': 'table_lamp.n.01'}, {'name': 'tablecloth', 'id': 1052, 'frequency': 'f', 'synset': 'tablecloth.n.01'}, {'name': 'tachometer', 'id': 1053, 'frequency': 'r', 'synset': 'tachometer.n.01'}, {'name': 'taco', 'id': 1054, 'frequency': 'r', 'synset': 'taco.n.02'}, {'name': 'tag', 'id': 1055, 'frequency': 'f', 'synset': 'tag.n.02'}, {'name': 'taillight', 'id': 1056, 'frequency': 'f', 'synset': 'taillight.n.01'}, {'name': 'tambourine', 'id': 1057, 'frequency': 'r', 'synset': 'tambourine.n.01'}, {'name': 'army_tank', 'id': 1058, 'frequency': 'r', 'synset': 'tank.n.01'}, {'name': 'tank_(storage_vessel)', 'id': 1059, 'frequency': 'f', 'synset': 'tank.n.02'}, {'name': 'tank_top_(clothing)', 'id': 1060, 'frequency': 'f', 'synset': 'tank_top.n.01'}, {'name': 'tape_(sticky_cloth_or_paper)', 'id': 1061, 'frequency': 'f', 'synset': 'tape.n.01'}, {'name': 'tape_measure', 'id': 1062, 'frequency': 'c', 'synset': 'tape.n.04'}, {'name': 'tapestry', 'id': 1063, 'frequency': 'c', 'synset': 'tapestry.n.02'}, {'name': 'tarp', 'id': 1064, 'frequency': 'f', 'synset': 'tarpaulin.n.01'}, {'name': 'tartan', 'id': 1065, 'frequency': 'c', 'synset': 'tartan.n.01'}, {'name': 'tassel', 'id': 1066, 'frequency': 'c', 'synset': 'tassel.n.01'}, {'name': 'tea_bag', 'id': 1067, 'frequency': 'c', 'synset': 'tea_bag.n.01'}, {'name': 'teacup', 'id': 1068, 'frequency': 'c', 'synset': 'teacup.n.02'}, {'name': 'teakettle', 'id': 1069, 'frequency': 'c', 'synset': 'teakettle.n.01'}, {'name': 'teapot', 'id': 1070, 'frequency': 'f', 'synset': 'teapot.n.01'}, {'name': 'teddy_bear', 'id': 1071, 'frequency': 'f', 'synset': 'teddy.n.01'}, {'name': 'telephone', 'id': 1072, 'frequency': 'f', 'synset': 'telephone.n.01'}, {'name': 'telephone_booth', 'id': 1073, 'frequency': 'c', 'synset': 'telephone_booth.n.01'}, {'name': 'telephone_pole', 'id': 1074, 'frequency': 'f', 'synset': 'telephone_pole.n.01'}, {'name': 'telephoto_lens', 'id': 1075, 'frequency': 'r', 'synset': 'telephoto_lens.n.01'}, {'name': 'television_camera', 'id': 1076, 'frequency': 'c', 'synset': 'television_camera.n.01'}, {'name': 'television_set', 'id': 1077, 'frequency': 'f', 'synset': 'television_receiver.n.01'}, {'name': 'tennis_ball', 'id': 1078, 'frequency': 'f', 'synset': 'tennis_ball.n.01'}, {'name': 'tennis_racket', 'id': 1079, 'frequency': 'f', 'synset': 'tennis_racket.n.01'}, {'name': 'tequila', 'id': 1080, 'frequency': 'r', 'synset': 'tequila.n.01'}, {'name': 'thermometer', 'id': 1081, 'frequency': 'c', 'synset': 'thermometer.n.01'}, {'name': 'thermos_bottle', 'id': 1082, 'frequency': 'c', 'synset': 'thermos.n.01'}, {'name': 'thermostat', 'id': 1083, 'frequency': 'f', 'synset': 'thermostat.n.01'}, {'name': 'thimble', 'id': 1084, 'frequency': 'r', 'synset': 'thimble.n.02'}, {'name': 'thread', 'id': 1085, 'frequency': 'c', 'synset': 'thread.n.01'}, {'name': 'thumbtack', 'id': 1086, 'frequency': 'c', 'synset': 'thumbtack.n.01'}, {'name': 'tiara', 'id': 1087, 'frequency': 'c', 'synset': 'tiara.n.01'}, {'name': 'tiger', 'id': 1088, 'frequency': 'c', 'synset': 'tiger.n.02'}, {'name': 'tights_(clothing)', 'id': 1089, 'frequency': 'c', 'synset': 'tights.n.01'}, {'name': 'timer', 'id': 1090, 'frequency': 'c', 'synset': 'timer.n.01'}, {'name': 'tinfoil', 'id': 1091, 'frequency': 'f', 'synset': 'tinfoil.n.01'}, {'name': 'tinsel', 'id': 1092, 'frequency': 'c', 'synset': 'tinsel.n.01'}, {'name': 'tissue_paper', 'id': 1093, 'frequency': 'f', 'synset': 'tissue.n.02'}, {'name': 'toast_(food)', 'id': 1094, 'frequency': 'c', 'synset': 'toast.n.01'}, {'name': 'toaster', 'id': 1095, 'frequency': 'f', 'synset': 'toaster.n.02'}, {'name': 'toaster_oven', 'id': 1096, 'frequency': 'f', 'synset': 'toaster_oven.n.01'}, {'name': 'toilet', 'id': 1097, 'frequency': 'f', 'synset': 'toilet.n.02'}, {'name': 'toilet_tissue', 'id': 1098, 'frequency': 'f', 'synset': 'toilet_tissue.n.01'}, {'name': 'tomato', 'id': 1099, 'frequency': 'f', 'synset': 'tomato.n.01'}, {'name': 'tongs', 'id': 1100, 'frequency': 'f', 'synset': 'tongs.n.01'}, {'name': 'toolbox', 'id': 1101, 'frequency': 'c', 'synset': 'toolbox.n.01'}, {'name': 'toothbrush', 'id': 1102, 'frequency': 'f', 'synset': 'toothbrush.n.01'}, {'name': 'toothpaste', 'id': 1103, 'frequency': 'f', 'synset': 'toothpaste.n.01'}, {'name': 'toothpick', 'id': 1104, 'frequency': 'f', 'synset': 'toothpick.n.01'}, {'name': 'cover', 'id': 1105, 'frequency': 'f', 'synset': 'top.n.09'}, {'name': 'tortilla', 'id': 1106, 'frequency': 'c', 'synset': 'tortilla.n.01'}, {'name': 'tow_truck', 'id': 1107, 'frequency': 'c', 'synset': 'tow_truck.n.01'}, {'name': 'towel', 'id': 1108, 'frequency': 'f', 'synset': 'towel.n.01'}, {'name': 'towel_rack', 'id': 1109, 'frequency': 'f', 'synset': 'towel_rack.n.01'}, {'name': 'toy', 'id': 1110, 'frequency': 'f', 'synset': 'toy.n.03'}, {'name': 'tractor_(farm_equipment)', 'id': 1111, 'frequency': 'c', 'synset': 'tractor.n.01'}, {'name': 'traffic_light', 'id': 1112, 'frequency': 'f', 'synset': 'traffic_light.n.01'}, {'name': 'dirt_bike', 'id': 1113, 'frequency': 'c', 'synset': 'trail_bike.n.01'}, {'name': 'trailer_truck', 'id': 1114, 'frequency': 'f', 'synset': 'trailer_truck.n.01'}, {'name': 'train_(railroad_vehicle)', 'id': 1115, 'frequency': 'f', 'synset': 'train.n.01'}, {'name': 'trampoline', 'id': 1116, 'frequency': 'r', 'synset': 'trampoline.n.01'}, {'name': 'tray', 'id': 1117, 'frequency': 'f', 'synset': 'tray.n.01'}, {'name': 'trench_coat', 'id': 1118, 'frequency': 'r', 'synset': 'trench_coat.n.01'}, {'name': 'triangle_(musical_instrument)', 'id': 1119, 'frequency': 'r', 'synset': 'triangle.n.05'}, {'name': 'tricycle', 'id': 1120, 'frequency': 'c', 'synset': 'tricycle.n.01'}, {'name': 'tripod', 'id': 1121, 'frequency': 'f', 'synset': 'tripod.n.01'}, {'name': 'trousers', 'id': 1122, 'frequency': 'f', 'synset': 'trouser.n.01'}, {'name': 'truck', 'id': 1123, 'frequency': 'f', 'synset': 'truck.n.01'}, {'name': 'truffle_(chocolate)', 'id': 1124, 'frequency': 'r', 'synset': 'truffle.n.03'}, {'name': 'trunk', 'id': 1125, 'frequency': 'c', 'synset': 'trunk.n.02'}, {'name': 'vat', 'id': 1126, 'frequency': 'r', 'synset': 'tub.n.02'}, {'name': 'turban', 'id': 1127, 'frequency': 'c', 'synset': 'turban.n.01'}, {'name': 'turkey_(food)', 'id': 1128, 'frequency': 'c', 'synset': 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1141, 'frequency': 'f', 'synset': 'vent.n.01'}, {'name': 'vest', 'id': 1142, 'frequency': 'f', 'synset': 'vest.n.01'}, {'name': 'videotape', 'id': 1143, 'frequency': 'c', 'synset': 'videotape.n.01'}, {'name': 'vinegar', 'id': 1144, 'frequency': 'r', 'synset': 'vinegar.n.01'}, {'name': 'violin', 'id': 1145, 'frequency': 'r', 'synset': 'violin.n.01'}, {'name': 'vodka', 'id': 1146, 'frequency': 'r', 'synset': 'vodka.n.01'}, {'name': 'volleyball', 'id': 1147, 'frequency': 'c', 'synset': 'volleyball.n.02'}, {'name': 'vulture', 'id': 1148, 'frequency': 'r', 'synset': 'vulture.n.01'}, {'name': 'waffle', 'id': 1149, 'frequency': 'c', 'synset': 'waffle.n.01'}, {'name': 'waffle_iron', 'id': 1150, 'frequency': 'r', 'synset': 'waffle_iron.n.01'}, {'name': 'wagon', 'id': 1151, 'frequency': 'c', 'synset': 'wagon.n.01'}, {'name': 'wagon_wheel', 'id': 1152, 'frequency': 'c', 'synset': 'wagon_wheel.n.01'}, {'name': 'walking_stick', 'id': 1153, 'frequency': 'c', 'synset': 'walking_stick.n.01'}, {'name': 'wall_clock', 'id': 1154, 'frequency': 'c', 'synset': 'wall_clock.n.01'}, {'name': 'wall_socket', 'id': 1155, 'frequency': 'f', 'synset': 'wall_socket.n.01'}, {'name': 'wallet', 'id': 1156, 'frequency': 'f', 'synset': 'wallet.n.01'}, {'name': 'walrus', 'id': 1157, 'frequency': 'r', 'synset': 'walrus.n.01'}, {'name': 'wardrobe', 'id': 1158, 'frequency': 'r', 'synset': 'wardrobe.n.01'}, {'name': 'washbasin', 'id': 1159, 'frequency': 'r', 'synset': 'washbasin.n.01'}, {'name': 'automatic_washer', 'id': 1160, 'frequency': 'c', 'synset': 'washer.n.03'}, {'name': 'watch', 'id': 1161, 'frequency': 'f', 'synset': 'watch.n.01'}, {'name': 'water_bottle', 'id': 1162, 'frequency': 'f', 'synset': 'water_bottle.n.01'}, {'name': 'water_cooler', 'id': 1163, 'frequency': 'c', 'synset': 'water_cooler.n.01'}, {'name': 'water_faucet', 'id': 1164, 'frequency': 'c', 'synset': 'water_faucet.n.01'}, {'name': 'water_heater', 'id': 1165, 'frequency': 'r', 'synset': 'water_heater.n.01'}, {'name': 'water_jug', 'id': 1166, 'frequency': 'c', 'synset': 'water_jug.n.01'}, {'name': 'water_gun', 'id': 1167, 'frequency': 'r', 'synset': 'water_pistol.n.01'}, {'name': 'water_scooter', 'id': 1168, 'frequency': 'c', 'synset': 'water_scooter.n.01'}, {'name': 'water_ski', 'id': 1169, 'frequency': 'c', 'synset': 'water_ski.n.01'}, {'name': 'water_tower', 'id': 1170, 'frequency': 'c', 'synset': 'water_tower.n.01'}, {'name': 'watering_can', 'id': 1171, 'frequency': 'c', 'synset': 'watering_can.n.01'}, {'name': 'watermelon', 'id': 1172, 'frequency': 'f', 'synset': 'watermelon.n.02'}, {'name': 'weathervane', 'id': 1173, 'frequency': 'f', 'synset': 'weathervane.n.01'}, {'name': 'webcam', 'id': 1174, 'frequency': 'c', 'synset': 'webcam.n.01'}, {'name': 'wedding_cake', 'id': 1175, 'frequency': 'c', 'synset': 'wedding_cake.n.01'}, {'name': 'wedding_ring', 'id': 1176, 'frequency': 'c', 'synset': 'wedding_ring.n.01'}, {'name': 'wet_suit', 'id': 1177, 'frequency': 'f', 'synset': 'wet_suit.n.01'}, {'name': 'wheel', 'id': 1178, 'frequency': 'f', 'synset': 'wheel.n.01'}, {'name': 'wheelchair', 'id': 1179, 'frequency': 'c', 'synset': 'wheelchair.n.01'}, {'name': 'whipped_cream', 'id': 1180, 'frequency': 'c', 'synset': 'whipped_cream.n.01'}, {'name': 'whistle', 'id': 1181, 'frequency': 'c', 'synset': 'whistle.n.03'}, {'name': 'wig', 'id': 1182, 'frequency': 'c', 'synset': 'wig.n.01'}, {'name': 'wind_chime', 'id': 1183, 'frequency': 'c', 'synset': 'wind_chime.n.01'}, {'name': 'windmill', 'id': 1184, 'frequency': 'c', 'synset': 'windmill.n.01'}, {'name': 'window_box_(for_plants)', 'id': 1185, 'frequency': 'c', 'synset': 'window_box.n.01'}, {'name': 'windshield_wiper', 'id': 1186, 'frequency': 'f', 'synset': 'windshield_wiper.n.01'}, {'name': 'windsock', 'id': 1187, 'frequency': 'c', 'synset': 'windsock.n.01'}, {'name': 'wine_bottle', 'id': 1188, 'frequency': 'f', 'synset': 'wine_bottle.n.01'}, {'name': 'wine_bucket', 'id': 1189, 'frequency': 'c', 'synset': 'wine_bucket.n.01'}, {'name': 'wineglass', 'id': 1190, 'frequency': 'f', 'synset': 'wineglass.n.01'}, {'name': 'blinder_(for_horses)', 'id': 1191, 'frequency': 'f', 'synset': 'winker.n.02'}, {'name': 'wok', 'id': 1192, 'frequency': 'c', 'synset': 'wok.n.01'}, {'name': 'wolf', 'id': 1193, 'frequency': 'r', 'synset': 'wolf.n.01'}, {'name': 'wooden_spoon', 'id': 1194, 'frequency': 'c', 'synset': 'wooden_spoon.n.02'}, {'name': 'wreath', 'id': 1195, 'frequency': 'c', 'synset': 'wreath.n.01'}, {'name': 'wrench', 'id': 1196, 'frequency': 'c', 'synset': 'wrench.n.03'}, {'name': 'wristband', 'id': 1197, 'frequency': 'f', 'synset': 'wristband.n.01'}, {'name': 'wristlet', 'id': 1198, 'frequency': 'f', 'synset': 'wristlet.n.01'}, {'name': 'yacht', 'id': 1199, 'frequency': 'c', 'synset': 'yacht.n.01'}, {'name': 'yogurt', 'id': 1200, 'frequency': 'c', 'synset': 'yogurt.n.01'}, {'name': 'yoke_(animal_equipment)', 'id': 1201, 'frequency': 'c', 'synset': 'yoke.n.07'}, {'name': 'zebra', 'id': 1202, 'frequency': 'f', 'synset': 'zebra.n.01'}, {'name': 'zucchini', 'id': 1203, 'frequency': 'c', 'synset': 'zucchini.n.02'}, {'id': 1204, 'synset': 'organism.n.01', 'name': 'organism'}, {'id': 1205, 'synset': 'benthos.n.02', 'name': 'benthos'}, {'id': 1206, 'synset': 'heterotroph.n.01', 'name': 'heterotroph'}, {'id': 1207, 'synset': 'cell.n.02', 'name': 'cell'}, {'id': 1208, 'synset': 'animal.n.01', 'name': 'animal'}, {'id': 1209, 'synset': 'plant.n.02', 'name': 'plant'}, {'id': 1210, 'synset': 'food.n.01', 'name': 'food'}, {'id': 1211, 'synset': 'artifact.n.01', 'name': 'artifact'}, {'id': 1212, 'synset': 'hop.n.01', 'name': 'hop'}, {'id': 1213, 'synset': 'check-in.n.01', 'name': 'check-in'}, {'id': 1214, 'synset': 'dressage.n.01', 'name': 'dressage'}, {'id': 1215, 'synset': 'curvet.n.01', 'name': 'curvet'}, {'id': 1216, 'synset': 'piaffe.n.01', 'name': 'piaffe'}, {'id': 1217, 'synset': 'funambulism.n.01', 'name': 'funambulism'}, {'id': 1218, 'synset': 'rock_climbing.n.01', 'name': 'rock_climbing'}, {'id': 1219, 'synset': 'contact_sport.n.01', 'name': 'contact_sport'}, {'id': 1220, 'synset': 'outdoor_sport.n.01', 'name': 'outdoor_sport'}, {'id': 1221, 'synset': 'gymnastics.n.01', 'name': 'gymnastics'}, {'id': 1222, 'synset': 'acrobatics.n.01', 'name': 'acrobatics'}, {'id': 1223, 'synset': 'track_and_field.n.01', 'name': 'track_and_field'}, {'id': 1224, 'synset': 'track.n.11', 'name': 'track'}, {'id': 1225, 'synset': 'jumping.n.01', 'name': 'jumping'}, {'id': 1226, 'synset': 'broad_jump.n.02', 'name': 'broad_jump'}, {'id': 1227, 'synset': 'high_jump.n.02', 'name': 'high_jump'}, {'id': 1228, 'synset': 'fosbury_flop.n.01', 'name': 'Fosbury_flop'}, {'id': 1229, 'synset': 'skiing.n.01', 'name': 'skiing'}, {'id': 1230, 'synset': 'cross-country_skiing.n.01', 'name': 'cross-country_skiing'}, {'id': 1231, 'synset': 'ski_jumping.n.01', 'name': 'ski_jumping'}, {'id': 1232, 'synset': 'water_sport.n.01', 'name': 'water_sport'}, {'id': 1233, 'synset': 'swimming.n.01', 'name': 'swimming'}, {'id': 1234, 'synset': 'bathe.n.01', 'name': 'bathe'}, {'id': 1235, 'synset': 'dip.n.08', 'name': 'dip'}, {'id': 1236, 'synset': 'dive.n.02', 'name': 'dive'}, {'id': 1237, 'synset': 'floating.n.01', 'name': 'floating'}, {'id': 1238, 'synset': "dead-man's_float.n.01", 'name': "dead-man's_float"}, {'id': 1239, 'synset': 'belly_flop.n.01', 'name': 'belly_flop'}, {'id': 1240, 'synset': 'cliff_diving.n.01', 'name': 'cliff_diving'}, {'id': 1241, 'synset': 'flip.n.05', 'name': 'flip'}, {'id': 1242, 'synset': 'gainer.n.03', 'name': 'gainer'}, {'id': 1243, 'synset': 'half_gainer.n.01', 'name': 'half_gainer'}, {'id': 1244, 'synset': 'jackknife.n.02', 'name': 'jackknife'}, {'id': 1245, 'synset': 'swan_dive.n.01', 'name': 'swan_dive'}, {'id': 1246, 'synset': 'skin_diving.n.01', 'name': 'skin_diving'}, {'id': 1247, 'synset': 'scuba_diving.n.01', 'name': 'scuba_diving'}, {'id': 1248, 'synset': 'snorkeling.n.01', 'name': 'snorkeling'}, {'id': 1249, 'synset': 'surfing.n.01', 'name': 'surfing'}, {'id': 1250, 'synset': 'water-skiing.n.01', 'name': 'water-skiing'}, {'id': 1251, 'synset': 'rowing.n.01', 'name': 'rowing'}, {'id': 1252, 'synset': 'sculling.n.01', 'name': 'sculling'}, {'id': 1253, 'synset': 'boxing.n.01', 'name': 'boxing'}, {'id': 1254, 'synset': 'professional_boxing.n.01', 'name': 'professional_boxing'}, {'id': 1255, 'synset': 'in-fighting.n.02', 'name': 'in-fighting'}, {'id': 1256, 'synset': 'fight.n.05', 'name': 'fight'}, {'id': 1257, 'synset': 'rope-a-dope.n.01', 'name': 'rope-a-dope'}, {'id': 1258, 'synset': 'spar.n.03', 'name': 'spar'}, {'id': 1259, 'synset': 'archery.n.01', 'name': 'archery'}, {'id': 1260, 'synset': 'sledding.n.01', 'name': 'sledding'}, {'id': 1261, 'synset': 'tobogganing.n.01', 'name': 'tobogganing'}, {'id': 1262, 'synset': 'luging.n.01', 'name': 'luging'}, {'id': 1263, 'synset': 'bobsledding.n.01', 'name': 'bobsledding'}, {'id': 1264, 'synset': 'wrestling.n.02', 'name': 'wrestling'}, {'id': 1265, 'synset': 'greco-roman_wrestling.n.01', 'name': 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1280, 'synset': 'greyhound_racing.n.01', 'name': 'greyhound_racing'}, {'id': 1281, 'synset': 'horse_racing.n.01', 'name': 'horse_racing'}, {'id': 1282, 'synset': 'riding.n.01', 'name': 'riding'}, {'id': 1283, 'synset': 'equestrian_sport.n.01', 'name': 'equestrian_sport'}, {'id': 1284, 'synset': 'pony-trekking.n.01', 'name': 'pony-trekking'}, {'id': 1285, 'synset': 'showjumping.n.01', 'name': 'showjumping'}, {'id': 1286, 'synset': 'cross-country_riding.n.01', 'name': 'cross-country_riding'}, {'id': 1287, 'synset': 'cycling.n.01', 'name': 'cycling'}, {'id': 1288, 'synset': 'bicycling.n.01', 'name': 'bicycling'}, {'id': 1289, 'synset': 'motorcycling.n.01', 'name': 'motorcycling'}, {'id': 1290, 'synset': 'dune_cycling.n.01', 'name': 'dune_cycling'}, {'id': 1291, 'synset': 'blood_sport.n.01', 'name': 'blood_sport'}, {'id': 1292, 'synset': 'bullfighting.n.01', 'name': 'bullfighting'}, {'id': 1293, 'synset': 'cockfighting.n.01', 'name': 'cockfighting'}, {'id': 1294, 'synset': 'hunt.n.08', 'name': 'hunt'}, {'id': 1295, 'synset': 'battue.n.01', 'name': 'battue'}, {'id': 1296, 'synset': 'beagling.n.01', 'name': 'beagling'}, {'id': 1297, 'synset': 'coursing.n.01', 'name': 'coursing'}, {'id': 1298, 'synset': 'deer_hunting.n.01', 'name': 'deer_hunting'}, {'id': 1299, 'synset': 'ducking.n.01', 'name': 'ducking'}, {'id': 1300, 'synset': 'fox_hunting.n.01', 'name': 'fox_hunting'}, {'id': 1301, 'synset': 'pigsticking.n.01', 'name': 'pigsticking'}, {'id': 1302, 'synset': 'fishing.n.01', 'name': 'fishing'}, {'id': 1303, 'synset': 'angling.n.01', 'name': 'angling'}, {'id': 1304, 'synset': 'fly-fishing.n.01', 'name': 'fly-fishing'}, {'id': 1305, 'synset': 'troll.n.04', 'name': 'troll'}, {'id': 1306, 'synset': 'casting.n.03', 'name': 'casting'}, {'id': 1307, 'synset': 'bait_casting.n.01', 'name': 'bait_casting'}, {'id': 1308, 'synset': 'fly_casting.n.01', 'name': 'fly_casting'}, {'id': 1309, 'synset': 'overcast.n.04', 'name': 'overcast'}, {'id': 1310, 'synset': 'surf_casting.n.01', 'name': 'surf_casting'}, {'id': 1311, 'synset': 'day_game.n.01', 'name': 'day_game'}, {'id': 1312, 'synset': 'athletic_game.n.01', 'name': 'athletic_game'}, {'id': 1313, 'synset': 'ice_hockey.n.01', 'name': 'ice_hockey'}, {'id': 1314, 'synset': 'tetherball.n.01', 'name': 'tetherball'}, {'id': 1315, 'synset': 'water_polo.n.01', 'name': 'water_polo'}, {'id': 1316, 'synset': 'outdoor_game.n.01', 'name': 'outdoor_game'}, {'id': 1317, 'synset': 'golf.n.01', 'name': 'golf'}, {'id': 1318, 'synset': 'professional_golf.n.01', 'name': 'professional_golf'}, {'id': 1319, 'synset': 'round_of_golf.n.01', 'name': 'round_of_golf'}, {'id': 1320, 'synset': 'medal_play.n.01', 'name': 'medal_play'}, {'id': 1321, 'synset': 'match_play.n.01', 'name': 'match_play'}, {'id': 1322, 'synset': 'miniature_golf.n.01', 'name': 'miniature_golf'}, {'id': 1323, 'synset': 'croquet.n.01', 'name': 'croquet'}, {'id': 1324, 'synset': 'quoits.n.01', 'name': 'quoits'}, {'id': 1325, 'synset': 'shuffleboard.n.01', 'name': 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'perfect_game'}, {'id': 1341, 'synset': 'no-hit_game.n.01', 'name': 'no-hit_game'}, {'id': 1342, 'synset': 'one-hitter.n.01', 'name': 'one-hitter'}, {'id': 1343, 'synset': 'two-hitter.n.01', 'name': 'two-hitter'}, {'id': 1344, 'synset': 'three-hitter.n.01', 'name': 'three-hitter'}, {'id': 1345, 'synset': 'four-hitter.n.01', 'name': 'four-hitter'}, {'id': 1346, 'synset': 'five-hitter.n.01', 'name': 'five-hitter'}, {'id': 1347, 'synset': 'softball.n.02', 'name': 'softball'}, {'id': 1348, 'synset': 'rounders.n.01', 'name': 'rounders'}, {'id': 1349, 'synset': 'stickball.n.01', 'name': 'stickball'}, {'id': 1350, 'synset': 'cricket.n.02', 'name': 'cricket'}, {'id': 1351, 'synset': 'lacrosse.n.01', 'name': 'lacrosse'}, {'id': 1352, 'synset': 'polo.n.02', 'name': 'polo'}, {'id': 1353, 'synset': 'pushball.n.01', 'name': 'pushball'}, {'id': 1354, 'synset': 'soccer.n.01', 'name': 'soccer'}, {'id': 1355, 'synset': 'court_game.n.01', 'name': 'court_game'}, {'id': 1356, 'synset': 'handball.n.02', 'name': 'handball'}, {'id': 1357, 'synset': 'racquetball.n.02', 'name': 'racquetball'}, {'id': 1358, 'synset': 'fives.n.01', 'name': 'fives'}, {'id': 1359, 'synset': 'squash.n.03', 'name': 'squash'}, {'id': 1360, 'synset': 'volleyball.n.01', 'name': 'volleyball'}, {'id': 1361, 'synset': 'jai_alai.n.01', 'name': 'jai_alai'}, {'id': 1362, 'synset': 'badminton.n.01', 'name': 'badminton'}, {'id': 1363, 'synset': 'battledore.n.02', 'name': 'battledore'}, {'id': 1364, 'synset': 'basketball.n.01', 'name': 'basketball'}, {'id': 1365, 'synset': 'professional_basketball.n.01', 'name': 'professional_basketball'}, {'id': 1366, 'synset': 'deck_tennis.n.01', 'name': 'deck_tennis'}, {'id': 1367, 'synset': 'netball.n.01', 'name': 'netball'}, {'id': 1368, 'synset': 'tennis.n.01', 'name': 'tennis'}, {'id': 1369, 'synset': 'professional_tennis.n.01', 'name': 'professional_tennis'}, {'id': 1370, 'synset': 'singles.n.02', 'name': 'singles'}, {'id': 1371, 'synset': 'singles.n.01', 'name': 'singles'}, {'id': 1372, 'synset': 'doubles.n.02', 'name': 'doubles'}, {'id': 1373, 'synset': 'doubles.n.01', 'name': 'doubles'}, {'id': 1374, 'synset': 'royal_tennis.n.01', 'name': 'royal_tennis'}, {'id': 1375, 'synset': 'pallone.n.01', 'name': 'pallone'}, {'id': 1376, 'synset': 'sport.n.01', 'name': 'sport'}, {'id': 1377, 'synset': 'clasp.n.02', 'name': 'clasp'}, {'id': 1378, 'synset': 'judo.n.01', 'name': 'judo'}, {'id': 1379, 'synset': 'team_sport.n.01', 'name': 'team_sport'}, {'id': 1380, 'synset': 'last_supper.n.01', 'name': 'Last_Supper'}, {'id': 1381, 'synset': 'seder.n.01', 'name': 'Seder'}, {'id': 1382, 'synset': 'camping.n.01', 'name': 'camping'}, {'id': 1383, 'synset': 'pest.n.04', 'name': 'pest'}, {'id': 1384, 'synset': 'critter.n.01', 'name': 'critter'}, {'id': 1385, 'synset': 'creepy-crawly.n.01', 'name': 'creepy-crawly'}, {'id': 1386, 'synset': 'darter.n.02', 'name': 'darter'}, {'id': 1387, 'synset': 'peeper.n.03', 'name': 'peeper'}, {'id': 1388, 'synset': 'homeotherm.n.01', 'name': 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{'id': 1404, 'synset': 'migrator.n.02', 'name': 'migrator'}, {'id': 1405, 'synset': 'molter.n.01', 'name': 'molter'}, {'id': 1406, 'synset': 'stayer.n.01', 'name': 'stayer'}, {'id': 1407, 'synset': 'stunt.n.02', 'name': 'stunt'}, {'id': 1408, 'synset': 'marine_animal.n.01', 'name': 'marine_animal'}, {'id': 1409, 'synset': 'by-catch.n.01', 'name': 'by-catch'}, {'id': 1410, 'synset': 'female.n.01', 'name': 'female'}, {'id': 1411, 'synset': 'hen.n.04', 'name': 'hen'}, {'id': 1412, 'synset': 'male.n.01', 'name': 'male'}, {'id': 1413, 'synset': 'adult.n.02', 'name': 'adult'}, {'id': 1414, 'synset': 'young.n.01', 'name': 'young'}, {'id': 1415, 'synset': 'orphan.n.04', 'name': 'orphan'}, {'id': 1416, 'synset': 'young_mammal.n.01', 'name': 'young_mammal'}, {'id': 1417, 'synset': 'baby.n.06', 'name': 'baby'}, {'id': 1418, 'synset': 'pup.n.01', 'name': 'pup'}, {'id': 1419, 'synset': 'wolf_pup.n.01', 'name': 'wolf_pup'}, {'id': 1420, 'synset': 'lion_cub.n.01', 'name': 'lion_cub'}, {'id': 1421, 'synset': 'bear_cub.n.01', 'name': 'bear_cub'}, {'id': 1422, 'synset': 'tiger_cub.n.01', 'name': 'tiger_cub'}, {'id': 1423, 'synset': 'kit.n.03', 'name': 'kit'}, {'id': 1424, 'synset': 'suckling.n.03', 'name': 'suckling'}, {'id': 1425, 'synset': 'sire.n.03', 'name': 'sire'}, {'id': 1426, 'synset': 'dam.n.03', 'name': 'dam'}, {'id': 1427, 'synset': 'thoroughbred.n.03', 'name': 'thoroughbred'}, {'id': 1428, 'synset': 'giant.n.01', 'name': 'giant'}, {'id': 1429, 'synset': 'mutant.n.02', 'name': 'mutant'}, {'id': 1430, 'synset': 'carnivore.n.02', 'name': 'carnivore'}, {'id': 1431, 'synset': 'herbivore.n.01', 'name': 'herbivore'}, {'id': 1432, 'synset': 'insectivore.n.02', 'name': 'insectivore'}, {'id': 1433, 'synset': 'acrodont.n.01', 'name': 'acrodont'}, {'id': 1434, 'synset': 'pleurodont.n.01', 'name': 'pleurodont'}, {'id': 1435, 'synset': 'microorganism.n.01', 'name': 'microorganism'}, {'id': 1436, 'synset': 'monohybrid.n.01', 'name': 'monohybrid'}, {'id': 1437, 'synset': 'arbovirus.n.01', 'name': 'arbovirus'}, {'id': 1438, 'synset': 'adenovirus.n.01', 'name': 'adenovirus'}, {'id': 1439, 'synset': 'arenavirus.n.01', 'name': 'arenavirus'}, {'id': 1440, 'synset': 'marburg_virus.n.01', 'name': 'Marburg_virus'}, {'id': 1441, 'synset': 'arenaviridae.n.01', 'name': 'Arenaviridae'}, {'id': 1442, 'synset': 'vesiculovirus.n.01', 'name': 'vesiculovirus'}, {'id': 1443, 'synset': 'reoviridae.n.01', 'name': 'Reoviridae'}, {'id': 1444, 'synset': 'variola_major.n.02', 'name': 'variola_major'}, {'id': 1445, 'synset': 'viroid.n.01', 'name': 'viroid'}, {'id': 1446, 'synset': 'coliphage.n.01', 'name': 'coliphage'}, {'id': 1447, 'synset': 'paramyxovirus.n.01', 'name': 'paramyxovirus'}, {'id': 1448, 'synset': 'poliovirus.n.01', 'name': 'poliovirus'}, {'id': 1449, 'synset': 'herpes.n.02', 'name': 'herpes'}, {'id': 1450, 'synset': 'herpes_simplex_1.n.01', 'name': 'herpes_simplex_1'}, {'id': 1451, 'synset': 'herpes_zoster.n.02', 'name': 'herpes_zoster'}, {'id': 1452, 'synset': 'herpes_varicella_zoster.n.01', 'name': 'herpes_varicella_zoster'}, {'id': 1453, 'synset': 'cytomegalovirus.n.01', 'name': 'cytomegalovirus'}, {'id': 1454, 'synset': 'varicella_zoster_virus.n.01', 'name': 'varicella_zoster_virus'}, {'id': 1455, 'synset': 'polyoma.n.01', 'name': 'polyoma'}, {'id': 1456, 'synset': 'lyssavirus.n.01', 'name': 'lyssavirus'}, {'id': 1457, 'synset': 'reovirus.n.01', 'name': 'reovirus'}, {'id': 1458, 'synset': 'rotavirus.n.01', 'name': 'rotavirus'}, {'id': 1459, 'synset': 'moneran.n.01', 'name': 'moneran'}, {'id': 1460, 'synset': 'archaebacteria.n.01', 'name': 'archaebacteria'}, {'id': 1461, 'synset': 'bacteroid.n.01', 'name': 'bacteroid'}, {'id': 1462, 'synset': 'bacillus_anthracis.n.01', 'name': 'Bacillus_anthracis'}, {'id': 1463, 'synset': 'yersinia_pestis.n.01', 'name': 'Yersinia_pestis'}, {'id': 1464, 'synset': 'brucella.n.01', 'name': 'Brucella'}, {'id': 1465, 'synset': 'spirillum.n.02', 'name': 'spirillum'}, {'id': 1466, 'synset': 'botulinus.n.01', 'name': 'botulinus'}, {'id': 1467, 'synset': 'clostridium_perfringens.n.01', 'name': 'clostridium_perfringens'}, {'id': 1468, 'synset': 'cyanobacteria.n.01', 'name': 'cyanobacteria'}, {'id': 1469, 'synset': 'trichodesmium.n.01', 'name': 'trichodesmium'}, {'id': 1470, 'synset': 'nitric_bacteria.n.01', 'name': 'nitric_bacteria'}, {'id': 1471, 'synset': 'spirillum.n.01', 'name': 'spirillum'}, {'id': 1472, 'synset': 'francisella.n.01', 'name': 'Francisella'}, {'id': 1473, 'synset': 'gonococcus.n.01', 'name': 'gonococcus'}, {'id': 1474, 'synset': 'corynebacterium_diphtheriae.n.01', 'name': 'Corynebacterium_diphtheriae'}, {'id': 1475, 'synset': 'enteric_bacteria.n.01', 'name': 'enteric_bacteria'}, {'id': 1476, 'synset': 'klebsiella.n.01', 'name': 'klebsiella'}, {'id': 1477, 'synset': 'salmonella_typhimurium.n.01', 'name': 'Salmonella_typhimurium'}, {'id': 1478, 'synset': 'typhoid_bacillus.n.01', 'name': 'typhoid_bacillus'}, {'id': 1479, 'synset': 'nitrate_bacterium.n.01', 'name': 'nitrate_bacterium'}, {'id': 1480, 'synset': 'nitrite_bacterium.n.01', 'name': 'nitrite_bacterium'}, {'id': 1481, 'synset': 'actinomycete.n.01', 'name': 'actinomycete'}, {'id': 1482, 'synset': 'streptomyces.n.01', 'name': 'streptomyces'}, {'id': 1483, 'synset': 'streptomyces_erythreus.n.01', 'name': 'Streptomyces_erythreus'}, {'id': 1484, 'synset': 'streptomyces_griseus.n.01', 'name': 'Streptomyces_griseus'}, {'id': 1485, 'synset': 'tubercle_bacillus.n.01', 'name': 'tubercle_bacillus'}, {'id': 1486, 'synset': 'pus-forming_bacteria.n.01', 'name': 'pus-forming_bacteria'}, {'id': 1487, 'synset': 'streptobacillus.n.01', 'name': 'streptobacillus'}, {'id': 1488, 'synset': 'myxobacteria.n.01', 'name': 'myxobacteria'}, {'id': 1489, 'synset': 'staphylococcus.n.01', 'name': 'staphylococcus'}, {'id': 1490, 'synset': 'diplococcus.n.01', 'name': 'diplococcus'}, {'id': 1491, 'synset': 'pneumococcus.n.01', 'name': 'pneumococcus'}, {'id': 1492, 'synset': 'streptococcus.n.01', 'name': 'streptococcus'}, {'id': 1493, 'synset': 'spirochete.n.01', 'name': 'spirochete'}, {'id': 1494, 'synset': 'planktonic_algae.n.01', 'name': 'planktonic_algae'}, {'id': 1495, 'synset': 'zooplankton.n.01', 'name': 'zooplankton'}, {'id': 1496, 'synset': 'parasite.n.01', 'name': 'parasite'}, {'id': 1497, 'synset': 'endoparasite.n.01', 'name': 'endoparasite'}, {'id': 1498, 'synset': 'ectoparasite.n.01', 'name': 'ectoparasite'}, {'id': 1499, 'synset': 'pathogen.n.01', 'name': 'pathogen'}, {'id': 1500, 'synset': 'commensal.n.01', 'name': 'commensal'}, {'id': 1501, 'synset': 'myrmecophile.n.01', 'name': 'myrmecophile'}, {'id': 1502, 'synset': 'protoctist.n.01', 'name': 'protoctist'}, {'id': 1503, 'synset': 'protozoan.n.01', 'name': 'protozoan'}, {'id': 1504, 'synset': 'sarcodinian.n.01', 'name': 'sarcodinian'}, {'id': 1505, 'synset': 'heliozoan.n.01', 'name': 'heliozoan'}, {'id': 1506, 'synset': 'endameba.n.01', 'name': 'endameba'}, {'id': 1507, 'synset': 'ameba.n.01', 'name': 'ameba'}, {'id': 1508, 'synset': 'globigerina.n.01', 'name': 'globigerina'}, {'id': 1509, 'synset': 'testacean.n.01', 'name': 'testacean'}, {'id': 1510, 'synset': 'arcella.n.01', 'name': 'arcella'}, {'id': 1511, 'synset': 'difflugia.n.01', 'name': 'difflugia'}, {'id': 1512, 'synset': 'ciliate.n.01', 'name': 'ciliate'}, {'id': 1513, 'synset': 'paramecium.n.01', 'name': 'paramecium'}, {'id': 1514, 'synset': 'stentor.n.03', 'name': 'stentor'}, {'id': 1515, 'synset': 'alga.n.01', 'name': 'alga'}, {'id': 1516, 'synset': 'arame.n.01', 'name': 'arame'}, {'id': 1517, 'synset': 'seagrass.n.01', 'name': 'seagrass'}, {'id': 1518, 'synset': 'golden_algae.n.01', 'name': 'golden_algae'}, {'id': 1519, 'synset': 'yellow-green_algae.n.01', 'name': 'yellow-green_algae'}, {'id': 1520, 'synset': 'brown_algae.n.01', 'name': 'brown_algae'}, {'id': 1521, 'synset': 'kelp.n.01', 'name': 'kelp'}, {'id': 1522, 'synset': 'fucoid.n.02', 'name': 'fucoid'}, {'id': 1523, 'synset': 'fucoid.n.01', 'name': 'fucoid'}, {'id': 1524, 'synset': 'fucus.n.01', 'name': 'fucus'}, {'id': 1525, 'synset': 'bladderwrack.n.01', 'name': 'bladderwrack'}, {'id': 1526, 'synset': 'green_algae.n.01', 'name': 'green_algae'}, {'id': 1527, 'synset': 'pond_scum.n.01', 'name': 'pond_scum'}, {'id': 1528, 'synset': 'chlorella.n.01', 'name': 'chlorella'}, {'id': 1529, 'synset': 'stonewort.n.01', 'name': 'stonewort'}, {'id': 1530, 'synset': 'desmid.n.01', 'name': 'desmid'}, {'id': 1531, 'synset': 'sea_moss.n.02', 'name': 'sea_moss'}, {'id': 1532, 'synset': 'eukaryote.n.01', 'name': 'eukaryote'}, {'id': 1533, 'synset': 'prokaryote.n.01', 'name': 'prokaryote'}, {'id': 1534, 'synset': 'zooid.n.01', 'name': 'zooid'}, {'id': 1535, 'synset': 'leishmania.n.01', 'name': 'Leishmania'}, {'id': 1536, 'synset': 'zoomastigote.n.01', 'name': 'zoomastigote'}, {'id': 1537, 'synset': 'polymastigote.n.01', 'name': 'polymastigote'}, {'id': 1538, 'synset': 'costia.n.01', 'name': 'costia'}, {'id': 1539, 'synset': 'giardia.n.01', 'name': 'giardia'}, {'id': 1540, 'synset': 'cryptomonad.n.01', 'name': 'cryptomonad'}, {'id': 1541, 'synset': 'sporozoan.n.01', 'name': 'sporozoan'}, {'id': 1542, 'synset': 'sporozoite.n.01', 'name': 'sporozoite'}, {'id': 1543, 'synset': 'trophozoite.n.01', 'name': 'trophozoite'}, {'id': 1544, 'synset': 'merozoite.n.01', 'name': 'merozoite'}, {'id': 1545, 'synset': 'coccidium.n.01', 'name': 'coccidium'}, {'id': 1546, 'synset': 'gregarine.n.01', 'name': 'gregarine'}, {'id': 1547, 'synset': 'plasmodium.n.02', 'name': 'plasmodium'}, {'id': 1548, 'synset': 'leucocytozoan.n.01', 'name': 'leucocytozoan'}, {'id': 1549, 'synset': 'microsporidian.n.01', 'name': 'microsporidian'}, {'id': 1550, 'synset': 'ostariophysi.n.01', 'name': 'Ostariophysi'}, {'id': 1551, 'synset': 'cypriniform_fish.n.01', 'name': 'cypriniform_fish'}, {'id': 1552, 'synset': 'loach.n.01', 'name': 'loach'}, {'id': 1553, 'synset': 'cyprinid.n.01', 'name': 'cyprinid'}, {'id': 1554, 'synset': 'carp.n.02', 'name': 'carp'}, {'id': 1555, 'synset': 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'buffalo_fish.n.01', 'name': 'buffalo_fish'}, {'id': 1572, 'synset': 'black_buffalo.n.01', 'name': 'black_buffalo'}, {'id': 1573, 'synset': 'hog_sucker.n.01', 'name': 'hog_sucker'}, {'id': 1574, 'synset': 'redhorse.n.01', 'name': 'redhorse'}, {'id': 1575, 'synset': 'cyprinodont.n.01', 'name': 'cyprinodont'}, {'id': 1576, 'synset': 'killifish.n.01', 'name': 'killifish'}, {'id': 1577, 'synset': 'mummichog.n.01', 'name': 'mummichog'}, {'id': 1578, 'synset': 'striped_killifish.n.01', 'name': 'striped_killifish'}, {'id': 1579, 'synset': 'rivulus.n.01', 'name': 'rivulus'}, {'id': 1580, 'synset': 'flagfish.n.01', 'name': 'flagfish'}, {'id': 1581, 'synset': 'swordtail.n.01', 'name': 'swordtail'}, {'id': 1582, 'synset': 'guppy.n.01', 'name': 'guppy'}, {'id': 1583, 'synset': 'topminnow.n.01', 'name': 'topminnow'}, {'id': 1584, 'synset': 'mosquitofish.n.01', 'name': 'mosquitofish'}, {'id': 1585, 'synset': 'platy.n.01', 'name': 'platy'}, {'id': 1586, 'synset': 'mollie.n.01', 'name': 'mollie'}, {'id': 1587, 'synset': 'squirrelfish.n.02', 'name': 'squirrelfish'}, {'id': 1588, 'synset': 'reef_squirrelfish.n.01', 'name': 'reef_squirrelfish'}, {'id': 1589, 'synset': 'deepwater_squirrelfish.n.01', 'name': 'deepwater_squirrelfish'}, {'id': 1590, 'synset': 'holocentrus_ascensionis.n.01', 'name': 'Holocentrus_ascensionis'}, {'id': 1591, 'synset': 'soldierfish.n.01', 'name': 'soldierfish'}, {'id': 1592, 'synset': 'anomalops.n.01', 'name': 'anomalops'}, {'id': 1593, 'synset': 'flashlight_fish.n.01', 'name': 'flashlight_fish'}, {'id': 1594, 'synset': 'john_dory.n.01', 'name': 'John_Dory'}, {'id': 1595, 'synset': 'boarfish.n.02', 'name': 'boarfish'}, {'id': 1596, 'synset': 'boarfish.n.01', 'name': 'boarfish'}, {'id': 1597, 'synset': 'cornetfish.n.01', 'name': 'cornetfish'}, {'id': 1598, 'synset': 'stickleback.n.01', 'name': 'stickleback'}, {'id': 1599, 'synset': 'three-spined_stickleback.n.01', 'name': 'three-spined_stickleback'}, {'id': 1600, 'synset': 'ten-spined_stickleback.n.01', 'name': 'ten-spined_stickleback'}, {'id': 1601, 'synset': 'pipefish.n.01', 'name': 'pipefish'}, {'id': 1602, 'synset': 'dwarf_pipefish.n.01', 'name': 'dwarf_pipefish'}, {'id': 1603, 'synset': 'deepwater_pipefish.n.01', 'name': 'deepwater_pipefish'}, {'id': 1604, 'synset': 'snipefish.n.01', 'name': 'snipefish'}, {'id': 1605, 'synset': 'shrimpfish.n.01', 'name': 'shrimpfish'}, {'id': 1606, 'synset': 'trumpetfish.n.01', 'name': 'trumpetfish'}, {'id': 1607, 'synset': 'pellicle.n.01', 'name': 'pellicle'}, {'id': 1608, 'synset': 'embryo.n.02', 'name': 'embryo'}, {'id': 1609, 'synset': 'fetus.n.01', 'name': 'fetus'}, {'id': 1610, 'synset': 'abortus.n.01', 'name': 'abortus'}, {'id': 1611, 'synset': 'spawn.n.01', 'name': 'spawn'}, {'id': 1612, 'synset': 'blastula.n.01', 'name': 'blastula'}, {'id': 1613, 'synset': 'blastocyst.n.01', 'name': 'blastocyst'}, {'id': 1614, 'synset': 'gastrula.n.01', 'name': 'gastrula'}, {'id': 1615, 'synset': 'morula.n.01', 'name': 'morula'}, {'id': 1616, 'synset': 'yolk.n.02', 'name': 'yolk'}, {'id': 1617, 'synset': 'chordate.n.01', 'name': 'chordate'}, {'id': 1618, 'synset': 'cephalochordate.n.01', 'name': 'cephalochordate'}, {'id': 1619, 'synset': 'lancelet.n.01', 'name': 'lancelet'}, {'id': 1620, 'synset': 'tunicate.n.01', 'name': 'tunicate'}, {'id': 1621, 'synset': 'ascidian.n.01', 'name': 'ascidian'}, {'id': 1622, 'synset': 'sea_squirt.n.01', 'name': 'sea_squirt'}, {'id': 1623, 'synset': 'salp.n.01', 'name': 'salp'}, {'id': 1624, 'synset': 'doliolum.n.01', 'name': 'doliolum'}, {'id': 1625, 'synset': 'larvacean.n.01', 'name': 'larvacean'}, {'id': 1626, 'synset': 'appendicularia.n.01', 'name': 'appendicularia'}, {'id': 1627, 'synset': 'ascidian_tadpole.n.01', 'name': 'ascidian_tadpole'}, {'id': 1628, 'synset': 'vertebrate.n.01', 'name': 'vertebrate'}, {'id': 1629, 'synset': 'amniota.n.01', 'name': 'Amniota'}, {'id': 1630, 'synset': 'amniote.n.01', 'name': 'amniote'}, {'id': 1631, 'synset': 'aquatic_vertebrate.n.01', 'name': 'aquatic_vertebrate'}, {'id': 1632, 'synset': 'jawless_vertebrate.n.01', 'name': 'jawless_vertebrate'}, {'id': 1633, 'synset': 'ostracoderm.n.01', 'name': 'ostracoderm'}, {'id': 1634, 'synset': 'heterostracan.n.01', 'name': 'heterostracan'}, {'id': 1635, 'synset': 'anaspid.n.01', 'name': 'anaspid'}, {'id': 1636, 'synset': 'conodont.n.02', 'name': 'conodont'}, {'id': 1637, 'synset': 'cyclostome.n.01', 'name': 'cyclostome'}, {'id': 1638, 'synset': 'lamprey.n.01', 'name': 'lamprey'}, {'id': 1639, 'synset': 'sea_lamprey.n.01', 'name': 'sea_lamprey'}, {'id': 1640, 'synset': 'hagfish.n.01', 'name': 'hagfish'}, {'id': 1641, 'synset': 'myxine_glutinosa.n.01', 'name': 'Myxine_glutinosa'}, {'id': 1642, 'synset': 'eptatretus.n.01', 'name': 'eptatretus'}, {'id': 1643, 'synset': 'gnathostome.n.01', 'name': 'gnathostome'}, {'id': 1644, 'synset': 'placoderm.n.01', 'name': 'placoderm'}, {'id': 1645, 'synset': 'cartilaginous_fish.n.01', 'name': 'cartilaginous_fish'}, {'id': 1646, 'synset': 'holocephalan.n.01', 'name': 'holocephalan'}, {'id': 1647, 'synset': 'chimaera.n.03', 'name': 'chimaera'}, {'id': 1648, 'synset': 'rabbitfish.n.01', 'name': 'rabbitfish'}, {'id': 1649, 'synset': 'elasmobranch.n.01', 'name': 'elasmobranch'}, {'id': 1650, 'synset': 'cow_shark.n.01', 'name': 'cow_shark'}, {'id': 1651, 'synset': 'mackerel_shark.n.01', 'name': 'mackerel_shark'}, {'id': 1652, 'synset': 'porbeagle.n.01', 'name': 'porbeagle'}, {'id': 1653, 'synset': 'mako.n.01', 'name': 'mako'}, {'id': 1654, 'synset': 'shortfin_mako.n.01', 'name': 'shortfin_mako'}, {'id': 1655, 'synset': 'longfin_mako.n.01', 'name': 'longfin_mako'}, {'id': 1656, 'synset': 'bonito_shark.n.01', 'name': 'bonito_shark'}, {'id': 1657, 'synset': 'great_white_shark.n.01', 'name': 'great_white_shark'}, {'id': 1658, 'synset': 'basking_shark.n.01', 'name': 'basking_shark'}, {'id': 1659, 'synset': 'thresher.n.02', 'name': 'thresher'}, {'id': 1660, 'synset': 'carpet_shark.n.01', 'name': 'carpet_shark'}, {'id': 1661, 'synset': 'nurse_shark.n.01', 'name': 'nurse_shark'}, {'id': 1662, 'synset': 'sand_tiger.n.01', 'name': 'sand_tiger'}, {'id': 1663, 'synset': 'whale_shark.n.01', 'name': 'whale_shark'}, {'id': 1664, 'synset': 'requiem_shark.n.01', 'name': 'requiem_shark'}, {'id': 1665, 'synset': 'bull_shark.n.01', 'name': 'bull_shark'}, {'id': 1666, 'synset': 'sandbar_shark.n.02', 'name': 'sandbar_shark'}, {'id': 1667, 'synset': 'blacktip_shark.n.01', 'name': 'blacktip_shark'}, {'id': 1668, 'synset': 'whitetip_shark.n.02', 'name': 'whitetip_shark'}, {'id': 1669, 'synset': 'dusky_shark.n.01', 'name': 'dusky_shark'}, {'id': 1670, 'synset': 'lemon_shark.n.01', 'name': 'lemon_shark'}, {'id': 1671, 'synset': 'blue_shark.n.01', 'name': 'blue_shark'}, {'id': 1672, 'synset': 'tiger_shark.n.01', 'name': 'tiger_shark'}, {'id': 1673, 'synset': 'soupfin_shark.n.01', 'name': 'soupfin_shark'}, {'id': 1674, 'synset': 'dogfish.n.02', 'name': 'dogfish'}, {'id': 1675, 'synset': 'smooth_dogfish.n.01', 'name': 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1689, 'synset': 'electric_ray.n.01', 'name': 'electric_ray'}, {'id': 1690, 'synset': 'sawfish.n.01', 'name': 'sawfish'}, {'id': 1691, 'synset': 'smalltooth_sawfish.n.01', 'name': 'smalltooth_sawfish'}, {'id': 1692, 'synset': 'guitarfish.n.01', 'name': 'guitarfish'}, {'id': 1693, 'synset': 'stingray.n.01', 'name': 'stingray'}, {'id': 1694, 'synset': 'roughtail_stingray.n.01', 'name': 'roughtail_stingray'}, {'id': 1695, 'synset': 'butterfly_ray.n.01', 'name': 'butterfly_ray'}, {'id': 1696, 'synset': 'eagle_ray.n.01', 'name': 'eagle_ray'}, {'id': 1697, 'synset': 'spotted_eagle_ray.n.01', 'name': 'spotted_eagle_ray'}, {'id': 1698, 'synset': 'cownose_ray.n.01', 'name': 'cownose_ray'}, {'id': 1699, 'synset': 'manta.n.02', 'name': 'manta'}, {'id': 1700, 'synset': 'atlantic_manta.n.01', 'name': 'Atlantic_manta'}, {'id': 1701, 'synset': 'devil_ray.n.01', 'name': 'devil_ray'}, {'id': 1702, 'synset': 'skate.n.02', 'name': 'skate'}, {'id': 1703, 'synset': 'grey_skate.n.01', 'name': 'grey_skate'}, {'id': 1704, 'synset': 'little_skate.n.01', 'name': 'little_skate'}, {'id': 1705, 'synset': 'thorny_skate.n.01', 'name': 'thorny_skate'}, {'id': 1706, 'synset': 'barndoor_skate.n.01', 'name': 'barndoor_skate'}, {'id': 1707, 'synset': 'dickeybird.n.01', 'name': 'dickeybird'}, {'id': 1708, 'synset': 'fledgling.n.02', 'name': 'fledgling'}, {'id': 1709, 'synset': 'nestling.n.01', 'name': 'nestling'}, {'id': 1710, 'synset': 'cock.n.05', 'name': 'cock'}, {'id': 1711, 'synset': 'gamecock.n.01', 'name': 'gamecock'}, {'id': 1712, 'synset': 'hen.n.02', 'name': 'hen'}, {'id': 1713, 'synset': 'nester.n.02', 'name': 'nester'}, {'id': 1714, 'synset': 'night_bird.n.01', 'name': 'night_bird'}, {'id': 1715, 'synset': 'night_raven.n.02', 'name': 'night_raven'}, {'id': 1716, 'synset': 'bird_of_passage.n.02', 'name': 'bird_of_passage'}, {'id': 1717, 'synset': 'archaeopteryx.n.01', 'name': 'archaeopteryx'}, {'id': 1718, 'synset': 'archaeornis.n.01', 'name': 'archaeornis'}, {'id': 1719, 'synset': 'ratite.n.01', 'name': 'ratite'}, {'id': 1720, 'synset': 'carinate.n.01', 'name': 'carinate'}, {'id': 1721, 'synset': 'cassowary.n.01', 'name': 'cassowary'}, {'id': 1722, 'synset': 'emu.n.02', 'name': 'emu'}, {'id': 1723, 'synset': 'kiwi.n.04', 'name': 'kiwi'}, {'id': 1724, 'synset': 'rhea.n.03', 'name': 'rhea'}, {'id': 1725, 'synset': 'rhea.n.02', 'name': 'rhea'}, {'id': 1726, 'synset': 'elephant_bird.n.01', 'name': 'elephant_bird'}, {'id': 1727, 'synset': 'moa.n.01', 'name': 'moa'}, {'id': 1728, 'synset': 'passerine.n.01', 'name': 'passerine'}, {'id': 1729, 'synset': 'nonpasserine_bird.n.01', 'name': 'nonpasserine_bird'}, {'id': 1730, 'synset': 'oscine.n.01', 'name': 'oscine'}, {'id': 1731, 'synset': 'songbird.n.01', 'name': 'songbird'}, {'id': 1732, 'synset': 'honey_eater.n.01', 'name': 'honey_eater'}, {'id': 1733, 'synset': 'accentor.n.01', 'name': 'accentor'}, {'id': 1734, 'synset': 'hedge_sparrow.n.01', 'name': 'hedge_sparrow'}, {'id': 1735, 'synset': 'lark.n.03', 'name': 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'house_finch'}, {'id': 1752, 'synset': 'purple_finch.n.01', 'name': 'purple_finch'}, {'id': 1753, 'synset': 'canary.n.04', 'name': 'canary'}, {'id': 1754, 'synset': 'common_canary.n.01', 'name': 'common_canary'}, {'id': 1755, 'synset': 'serin.n.01', 'name': 'serin'}, {'id': 1756, 'synset': 'crossbill.n.01', 'name': 'crossbill'}, {'id': 1757, 'synset': 'bullfinch.n.02', 'name': 'bullfinch'}, {'id': 1758, 'synset': 'junco.n.01', 'name': 'junco'}, {'id': 1759, 'synset': 'dark-eyed_junco.n.01', 'name': 'dark-eyed_junco'}, {'id': 1760, 'synset': 'new_world_sparrow.n.01', 'name': 'New_World_sparrow'}, {'id': 1761, 'synset': 'vesper_sparrow.n.01', 'name': 'vesper_sparrow'}, {'id': 1762, 'synset': 'white-throated_sparrow.n.01', 'name': 'white-throated_sparrow'}, {'id': 1763, 'synset': 'white-crowned_sparrow.n.01', 'name': 'white-crowned_sparrow'}, {'id': 1764, 'synset': 'chipping_sparrow.n.01', 'name': 'chipping_sparrow'}, {'id': 1765, 'synset': 'field_sparrow.n.01', 'name': 'field_sparrow'}, {'id': 1766, 'synset': 'tree_sparrow.n.02', 'name': 'tree_sparrow'}, {'id': 1767, 'synset': 'song_sparrow.n.01', 'name': 'song_sparrow'}, {'id': 1768, 'synset': 'swamp_sparrow.n.01', 'name': 'swamp_sparrow'}, {'id': 1769, 'synset': 'bunting.n.02', 'name': 'bunting'}, {'id': 1770, 'synset': 'indigo_bunting.n.01', 'name': 'indigo_bunting'}, {'id': 1771, 'synset': 'ortolan.n.01', 'name': 'ortolan'}, {'id': 1772, 'synset': 'reed_bunting.n.01', 'name': 'reed_bunting'}, {'id': 1773, 'synset': 'yellowhammer.n.02', 'name': 'yellowhammer'}, {'id': 1774, 'synset': 'yellow-breasted_bunting.n.01', 'name': 'yellow-breasted_bunting'}, {'id': 1775, 'synset': 'snow_bunting.n.01', 'name': 'snow_bunting'}, {'id': 1776, 'synset': 'honeycreeper.n.02', 'name': 'honeycreeper'}, {'id': 1777, 'synset': 'banana_quit.n.01', 'name': 'banana_quit'}, {'id': 1778, 'synset': 'sparrow.n.01', 'name': 'sparrow'}, {'id': 1779, 'synset': 'english_sparrow.n.01', 'name': 'English_sparrow'}, {'id': 1780, 'synset': 'tree_sparrow.n.01', 'name': 'tree_sparrow'}, {'id': 1781, 'synset': 'grosbeak.n.01', 'name': 'grosbeak'}, {'id': 1782, 'synset': 'evening_grosbeak.n.01', 'name': 'evening_grosbeak'}, {'id': 1783, 'synset': 'hawfinch.n.01', 'name': 'hawfinch'}, {'id': 1784, 'synset': 'pine_grosbeak.n.01', 'name': 'pine_grosbeak'}, {'id': 1785, 'synset': 'cardinal.n.04', 'name': 'cardinal'}, {'id': 1786, 'synset': 'pyrrhuloxia.n.01', 'name': 'pyrrhuloxia'}, {'id': 1787, 'synset': 'towhee.n.01', 'name': 'towhee'}, {'id': 1788, 'synset': 'chewink.n.01', 'name': 'chewink'}, {'id': 1789, 'synset': 'green-tailed_towhee.n.01', 'name': 'green-tailed_towhee'}, {'id': 1790, 'synset': 'weaver.n.02', 'name': 'weaver'}, {'id': 1791, 'synset': 'baya.n.01', 'name': 'baya'}, {'id': 1792, 'synset': 'whydah.n.01', 'name': 'whydah'}, {'id': 1793, 'synset': 'java_sparrow.n.01', 'name': 'Java_sparrow'}, {'id': 1794, 'synset': 'avadavat.n.01', 'name': 'avadavat'}, {'id': 1795, 'synset': 'grassfinch.n.01', 'name': 'grassfinch'}, {'id': 1796, 'synset': 'zebra_finch.n.01', 'name': 'zebra_finch'}, {'id': 1797, 'synset': 'honeycreeper.n.01', 'name': 'honeycreeper'}, {'id': 1798, 'synset': 'lyrebird.n.01', 'name': 'lyrebird'}, {'id': 1799, 'synset': 'scrubbird.n.01', 'name': 'scrubbird'}, {'id': 1800, 'synset': 'broadbill.n.04', 'name': 'broadbill'}, {'id': 1801, 'synset': 'tyrannid.n.01', 'name': 'tyrannid'}, {'id': 1802, 'synset': 'new_world_flycatcher.n.01', 'name': 'New_World_flycatcher'}, {'id': 1803, 'synset': 'kingbird.n.01', 'name': 'kingbird'}, {'id': 1804, 'synset': 'arkansas_kingbird.n.01', 'name': 'Arkansas_kingbird'}, {'id': 1805, 'synset': "cassin's_kingbird.n.01", 'name': "Cassin's_kingbird"}, {'id': 1806, 'synset': 'eastern_kingbird.n.01', 'name': 'eastern_kingbird'}, {'id': 1807, 'synset': 'grey_kingbird.n.01', 'name': 'grey_kingbird'}, {'id': 1808, 'synset': 'pewee.n.01', 'name': 'pewee'}, {'id': 1809, 'synset': 'western_wood_pewee.n.01', 'name': 'western_wood_pewee'}, {'id': 1810, 'synset': 'phoebe.n.03', 'name': 'phoebe'}, {'id': 1811, 'synset': 'vermillion_flycatcher.n.01', 'name': 'vermillion_flycatcher'}, {'id': 1812, 'synset': 'cotinga.n.01', 'name': 'cotinga'}, {'id': 1813, 'synset': 'cock_of_the_rock.n.02', 'name': 'cock_of_the_rock'}, {'id': 1814, 'synset': 'cock_of_the_rock.n.01', 'name': 'cock_of_the_rock'}, {'id': 1815, 'synset': 'manakin.n.03', 'name': 'manakin'}, {'id': 1816, 'synset': 'bellbird.n.01', 'name': 'bellbird'}, {'id': 1817, 'synset': 'umbrella_bird.n.01', 'name': 'umbrella_bird'}, {'id': 1818, 'synset': 'ovenbird.n.02', 'name': 'ovenbird'}, {'id': 1819, 'synset': 'antbird.n.01', 'name': 'antbird'}, {'id': 1820, 'synset': 'ant_thrush.n.01', 'name': 'ant_thrush'}, {'id': 1821, 'synset': 'ant_shrike.n.01', 'name': 'ant_shrike'}, {'id': 1822, 'synset': 'spotted_antbird.n.01', 'name': 'spotted_antbird'}, {'id': 1823, 'synset': 'woodhewer.n.01', 'name': 'woodhewer'}, {'id': 1824, 'synset': 'pitta.n.01', 'name': 'pitta'}, {'id': 1825, 'synset': 'scissortail.n.01', 'name': 'scissortail'}, {'id': 1826, 'synset': 'old_world_flycatcher.n.01', 'name': 'Old_World_flycatcher'}, {'id': 1827, 'synset': 'spotted_flycatcher.n.01', 'name': 'spotted_flycatcher'}, {'id': 1828, 'synset': 'thickhead.n.01', 'name': 'thickhead'}, {'id': 1829, 'synset': 'thrush.n.03', 'name': 'thrush'}, {'id': 1830, 'synset': 'missel_thrush.n.01', 'name': 'missel_thrush'}, {'id': 1831, 'synset': 'song_thrush.n.01', 'name': 'song_thrush'}, {'id': 1832, 'synset': 'fieldfare.n.01', 'name': 'fieldfare'}, {'id': 1833, 'synset': 'redwing.n.02', 'name': 'redwing'}, {'id': 1834, 'synset': 'blackbird.n.02', 'name': 'blackbird'}, {'id': 1835, 'synset': 'ring_ouzel.n.01', 'name': 'ring_ouzel'}, {'id': 1836, 'synset': 'robin.n.02', 'name': 'robin'}, {'id': 1837, 'synset': 'clay-colored_robin.n.01', 'name': 'clay-colored_robin'}, {'id': 1838, 'synset': 'hermit_thrush.n.01', 'name': 'hermit_thrush'}, {'id': 1839, 'synset': 'veery.n.01', 'name': 'veery'}, {'id': 1840, 'synset': 'wood_thrush.n.01', 'name': 'wood_thrush'}, {'id': 1841, 'synset': 'nightingale.n.01', 'name': 'nightingale'}, {'id': 1842, 'synset': 'thrush_nightingale.n.01', 'name': 'thrush_nightingale'}, {'id': 1843, 'synset': 'bulbul.n.01', 'name': 'bulbul'}, {'id': 1844, 'synset': 'old_world_chat.n.01', 'name': 'Old_World_chat'}, {'id': 1845, 'synset': 'stonechat.n.01', 'name': 'stonechat'}, {'id': 1846, 'synset': 'whinchat.n.01', 'name': 'whinchat'}, {'id': 1847, 'synset': 'solitaire.n.03', 'name': 'solitaire'}, {'id': 1848, 'synset': 'redstart.n.02', 'name': 'redstart'}, {'id': 1849, 'synset': 'wheatear.n.01', 'name': 'wheatear'}, {'id': 1850, 'synset': 'bluebird.n.02', 'name': 'bluebird'}, {'id': 1851, 'synset': 'robin.n.01', 'name': 'robin'}, {'id': 1852, 'synset': 'bluethroat.n.01', 'name': 'bluethroat'}, {'id': 1853, 'synset': 'warbler.n.02', 'name': 'warbler'}, {'id': 1854, 'synset': 'gnatcatcher.n.01', 'name': 'gnatcatcher'}, {'id': 1855, 'synset': 'kinglet.n.01', 'name': 'kinglet'}, {'id': 1856, 'synset': 'goldcrest.n.01', 'name': 'goldcrest'}, {'id': 1857, 'synset': 'gold-crowned_kinglet.n.01', 'name': 'gold-crowned_kinglet'}, {'id': 1858, 'synset': 'ruby-crowned_kinglet.n.01', 'name': 'ruby-crowned_kinglet'}, {'id': 1859, 'synset': 'old_world_warbler.n.01', 'name': 'Old_World_warbler'}, {'id': 1860, 'synset': 'blackcap.n.04', 'name': 'blackcap'}, {'id': 1861, 'synset': 'greater_whitethroat.n.01', 'name': 'greater_whitethroat'}, {'id': 1862, 'synset': 'lesser_whitethroat.n.01', 'name': 'lesser_whitethroat'}, {'id': 1863, 'synset': 'wood_warbler.n.02', 'name': 'wood_warbler'}, {'id': 1864, 'synset': 'sedge_warbler.n.01', 'name': 'sedge_warbler'}, {'id': 1865, 'synset': 'wren_warbler.n.01', 'name': 'wren_warbler'}, {'id': 1866, 'synset': 'tailorbird.n.01', 'name': 'tailorbird'}, {'id': 1867, 'synset': 'babbler.n.02', 'name': 'babbler'}, {'id': 1868, 'synset': 'new_world_warbler.n.01', 'name': 'New_World_warbler'}, {'id': 1869, 'synset': 'parula_warbler.n.01', 'name': 'parula_warbler'}, {'id': 1870, 'synset': "wilson's_warbler.n.01", 'name': "Wilson's_warbler"}, {'id': 1871, 'synset': 'flycatching_warbler.n.01', 'name': 'flycatching_warbler'}, {'id': 1872, 'synset': 'american_redstart.n.01', 'name': 'American_redstart'}, {'id': 1873, 'synset': 'cape_may_warbler.n.01', 'name': 'Cape_May_warbler'}, {'id': 1874, 'synset': 'yellow_warbler.n.01', 'name': 'yellow_warbler'}, {'id': 1875, 'synset': 'blackburn.n.01', 'name': 'Blackburn'}, {'id': 1876, 'synset': "audubon's_warbler.n.01", 'name': "Audubon's_warbler"}, {'id': 1877, 'synset': 'myrtle_warbler.n.01', 'name': 'myrtle_warbler'}, {'id': 1878, 'synset': 'blackpoll.n.01', 'name': 'blackpoll'}, {'id': 1879, 'synset': 'new_world_chat.n.01', 'name': 'New_World_chat'}, {'id': 1880, 'synset': 'yellow-breasted_chat.n.01', 'name': 'yellow-breasted_chat'}, {'id': 1881, 'synset': 'ovenbird.n.01', 'name': 'ovenbird'}, {'id': 1882, 'synset': 'water_thrush.n.01', 'name': 'water_thrush'}, {'id': 1883, 'synset': 'yellowthroat.n.01', 'name': 'yellowthroat'}, {'id': 1884, 'synset': 'common_yellowthroat.n.01', 'name': 'common_yellowthroat'}, {'id': 1885, 'synset': 'riflebird.n.01', 'name': 'riflebird'}, {'id': 1886, 'synset': 'new_world_oriole.n.01', 'name': 'New_World_oriole'}, {'id': 1887, 'synset': 'northern_oriole.n.01', 'name': 'northern_oriole'}, {'id': 1888, 'synset': 'baltimore_oriole.n.01', 'name': 'Baltimore_oriole'}, {'id': 1889, 'synset': "bullock's_oriole.n.01", 'name': "Bullock's_oriole"}, {'id': 1890, 'synset': 'orchard_oriole.n.01', 'name': 'orchard_oriole'}, {'id': 1891, 'synset': 'meadowlark.n.01', 'name': 'meadowlark'}, {'id': 1892, 'synset': 'eastern_meadowlark.n.01', 'name': 'eastern_meadowlark'}, {'id': 1893, 'synset': 'western_meadowlark.n.01', 'name': 'western_meadowlark'}, {'id': 1894, 'synset': 'cacique.n.01', 'name': 'cacique'}, {'id': 1895, 'synset': 'bobolink.n.01', 'name': 'bobolink'}, {'id': 1896, 'synset': 'new_world_blackbird.n.01', 'name': 'New_World_blackbird'}, {'id': 1897, 'synset': 'grackle.n.02', 'name': 'grackle'}, {'id': 1898, 'synset': 'purple_grackle.n.01', 'name': 'purple_grackle'}, {'id': 1899, 'synset': 'rusty_blackbird.n.01', 'name': 'rusty_blackbird'}, {'id': 1900, 'synset': 'cowbird.n.01', 'name': 'cowbird'}, {'id': 1901, 'synset': 'red-winged_blackbird.n.01', 'name': 'red-winged_blackbird'}, {'id': 1902, 'synset': 'old_world_oriole.n.01', 'name': 'Old_World_oriole'}, {'id': 1903, 'synset': 'golden_oriole.n.01', 'name': 'golden_oriole'}, {'id': 1904, 'synset': 'fig-bird.n.01', 'name': 'fig-bird'}, {'id': 1905, 'synset': 'starling.n.01', 'name': 'starling'}, {'id': 1906, 'synset': 'common_starling.n.01', 'name': 'common_starling'}, {'id': 1907, 'synset': 'rose-colored_starling.n.01', 'name': 'rose-colored_starling'}, {'id': 1908, 'synset': 'myna.n.01', 'name': 'myna'}, {'id': 1909, 'synset': 'crested_myna.n.01', 'name': 'crested_myna'}, {'id': 1910, 'synset': 'hill_myna.n.01', 'name': 'hill_myna'}, {'id': 1911, 'synset': 'corvine_bird.n.01', 'name': 'corvine_bird'}, {'id': 1912, 'synset': 'american_crow.n.01', 'name': 'American_crow'}, {'id': 1913, 'synset': 'raven.n.01', 'name': 'raven'}, {'id': 1914, 'synset': 'rook.n.02', 'name': 'rook'}, {'id': 1915, 'synset': 'jackdaw.n.01', 'name': 'jackdaw'}, {'id': 1916, 'synset': 'chough.n.01', 'name': 'chough'}, {'id': 1917, 'synset': 'jay.n.02', 'name': 'jay'}, {'id': 1918, 'synset': 'old_world_jay.n.01', 'name': 'Old_World_jay'}, {'id': 1919, 'synset': 'common_european_jay.n.01', 'name': 'common_European_jay'}, {'id': 1920, 'synset': 'new_world_jay.n.01', 'name': 'New_World_jay'}, {'id': 1921, 'synset': 'blue_jay.n.01', 'name': 'blue_jay'}, {'id': 1922, 'synset': 'canada_jay.n.01', 'name': 'Canada_jay'}, {'id': 1923, 'synset': 'rocky_mountain_jay.n.01', 'name': 'Rocky_Mountain_jay'}, {'id': 1924, 'synset': 'nutcracker.n.03', 'name': 'nutcracker'}, {'id': 1925, 'synset': 'common_nutcracker.n.01', 'name': 'common_nutcracker'}, {'id': 1926, 'synset': "clark's_nutcracker.n.01", 'name': "Clark's_nutcracker"}, {'id': 1927, 'synset': 'magpie.n.01', 'name': 'magpie'}, {'id': 1928, 'synset': 'european_magpie.n.01', 'name': 'European_magpie'}, {'id': 1929, 'synset': 'american_magpie.n.01', 'name': 'American_magpie'}, {'id': 1930, 'synset': 'australian_magpie.n.01', 'name': 'Australian_magpie'}, {'id': 1931, 'synset': 'butcherbird.n.02', 'name': 'butcherbird'}, {'id': 1932, 'synset': 'currawong.n.01', 'name': 'currawong'}, {'id': 1933, 'synset': 'piping_crow.n.01', 'name': 'piping_crow'}, {'id': 1934, 'synset': 'wren.n.02', 'name': 'wren'}, {'id': 1935, 'synset': 'winter_wren.n.01', 'name': 'winter_wren'}, {'id': 1936, 'synset': 'house_wren.n.01', 'name': 'house_wren'}, {'id': 1937, 'synset': 'marsh_wren.n.01', 'name': 'marsh_wren'}, {'id': 1938, 'synset': 'long-billed_marsh_wren.n.01', 'name': 'long-billed_marsh_wren'}, {'id': 1939, 'synset': 'sedge_wren.n.01', 'name': 'sedge_wren'}, {'id': 1940, 'synset': 'rock_wren.n.02', 'name': 'rock_wren'}, {'id': 1941, 'synset': 'carolina_wren.n.01', 'name': 'Carolina_wren'}, {'id': 1942, 'synset': 'cactus_wren.n.01', 'name': 'cactus_wren'}, {'id': 1943, 'synset': 'mockingbird.n.01', 'name': 'mockingbird'}, {'id': 1944, 'synset': 'blue_mockingbird.n.01', 'name': 'blue_mockingbird'}, {'id': 1945, 'synset': 'catbird.n.02', 'name': 'catbird'}, {'id': 1946, 'synset': 'thrasher.n.02', 'name': 'thrasher'}, {'id': 1947, 'synset': 'brown_thrasher.n.01', 'name': 'brown_thrasher'}, {'id': 1948, 'synset': 'new_zealand_wren.n.01', 'name': 'New_Zealand_wren'}, {'id': 1949, 'synset': 'rock_wren.n.01', 'name': 'rock_wren'}, {'id': 1950, 'synset': 'rifleman_bird.n.01', 'name': 'rifleman_bird'}, {'id': 1951, 'synset': 'creeper.n.03', 'name': 'creeper'}, {'id': 1952, 'synset': 'brown_creeper.n.01', 'name': 'brown_creeper'}, {'id': 1953, 'synset': 'european_creeper.n.01', 'name': 'European_creeper'}, {'id': 1954, 'synset': 'wall_creeper.n.01', 'name': 'wall_creeper'}, {'id': 1955, 'synset': 'european_nuthatch.n.01', 'name': 'European_nuthatch'}, {'id': 1956, 'synset': 'red-breasted_nuthatch.n.01', 'name': 'red-breasted_nuthatch'}, {'id': 1957, 'synset': 'white-breasted_nuthatch.n.01', 'name': 'white-breasted_nuthatch'}, {'id': 1958, 'synset': 'titmouse.n.01', 'name': 'titmouse'}, {'id': 1959, 'synset': 'chickadee.n.01', 'name': 'chickadee'}, {'id': 1960, 'synset': 'black-capped_chickadee.n.01', 'name': 'black-capped_chickadee'}, {'id': 1961, 'synset': 'tufted_titmouse.n.01', 'name': 'tufted_titmouse'}, {'id': 1962, 'synset': 'carolina_chickadee.n.01', 'name': 'Carolina_chickadee'}, {'id': 1963, 'synset': 'blue_tit.n.01', 'name': 'blue_tit'}, {'id': 1964, 'synset': 'bushtit.n.01', 'name': 'bushtit'}, {'id': 1965, 'synset': 'wren-tit.n.01', 'name': 'wren-tit'}, {'id': 1966, 'synset': 'verdin.n.01', 'name': 'verdin'}, {'id': 1967, 'synset': 'fairy_bluebird.n.01', 'name': 'fairy_bluebird'}, {'id': 1968, 'synset': 'swallow.n.03', 'name': 'swallow'}, {'id': 1969, 'synset': 'barn_swallow.n.01', 'name': 'barn_swallow'}, {'id': 1970, 'synset': 'cliff_swallow.n.01', 'name': 'cliff_swallow'}, {'id': 1971, 'synset': 'tree_swallow.n.02', 'name': 'tree_swallow'}, {'id': 1972, 'synset': 'white-bellied_swallow.n.01', 'name': 'white-bellied_swallow'}, {'id': 1973, 'synset': 'martin.n.05', 'name': 'martin'}, {'id': 1974, 'synset': 'house_martin.n.01', 'name': 'house_martin'}, {'id': 1975, 'synset': 'bank_martin.n.01', 'name': 'bank_martin'}, {'id': 1976, 'synset': 'purple_martin.n.01', 'name': 'purple_martin'}, {'id': 1977, 'synset': 'wood_swallow.n.01', 'name': 'wood_swallow'}, {'id': 1978, 'synset': 'tanager.n.01', 'name': 'tanager'}, {'id': 1979, 'synset': 'scarlet_tanager.n.01', 'name': 'scarlet_tanager'}, {'id': 1980, 'synset': 'western_tanager.n.01', 'name': 'western_tanager'}, {'id': 1981, 'synset': 'summer_tanager.n.01', 'name': 'summer_tanager'}, {'id': 1982, 'synset': 'hepatic_tanager.n.01', 'name': 'hepatic_tanager'}, {'id': 1983, 'synset': 'shrike.n.01', 'name': 'shrike'}, {'id': 1984, 'synset': 'butcherbird.n.01', 'name': 'butcherbird'}, {'id': 1985, 'synset': 'european_shrike.n.01', 'name': 'European_shrike'}, {'id': 1986, 'synset': 'northern_shrike.n.01', 'name': 'northern_shrike'}, {'id': 1987, 'synset': 'white-rumped_shrike.n.01', 'name': 'white-rumped_shrike'}, {'id': 1988, 'synset': 'loggerhead_shrike.n.01', 'name': 'loggerhead_shrike'}, {'id': 1989, 'synset': 'migrant_shrike.n.01', 'name': 'migrant_shrike'}, {'id': 1990, 'synset': 'bush_shrike.n.01', 'name': 'bush_shrike'}, {'id': 1991, 'synset': 'black-fronted_bush_shrike.n.01', 'name': 'black-fronted_bush_shrike'}, {'id': 1992, 'synset': 'bowerbird.n.01', 'name': 'bowerbird'}, {'id': 1993, 'synset': 'satin_bowerbird.n.01', 'name': 'satin_bowerbird'}, {'id': 1994, 'synset': 'great_bowerbird.n.01', 'name': 'great_bowerbird'}, {'id': 1995, 'synset': 'water_ouzel.n.01', 'name': 'water_ouzel'}, {'id': 1996, 'synset': 'european_water_ouzel.n.01', 'name': 'European_water_ouzel'}, {'id': 1997, 'synset': 'american_water_ouzel.n.01', 'name': 'American_water_ouzel'}, {'id': 1998, 'synset': 'vireo.n.01', 'name': 'vireo'}, {'id': 1999, 'synset': 'red-eyed_vireo.n.01', 'name': 'red-eyed_vireo'}, {'id': 2000, 'synset': 'solitary_vireo.n.01', 'name': 'solitary_vireo'}, {'id': 2001, 'synset': 'blue-headed_vireo.n.01', 'name': 'blue-headed_vireo'}, {'id': 2002, 'synset': 'waxwing.n.01', 'name': 'waxwing'}, {'id': 2003, 'synset': 'cedar_waxwing.n.01', 'name': 'cedar_waxwing'}, {'id': 2004, 'synset': 'bohemian_waxwing.n.01', 'name': 'Bohemian_waxwing'}, {'id': 2005, 'synset': 'bird_of_prey.n.01', 'name': 'bird_of_prey'}, {'id': 2006, 'synset': 'accipitriformes.n.01', 'name': 'Accipitriformes'}, {'id': 2007, 'synset': 'hawk.n.01', 'name': 'hawk'}, {'id': 2008, 'synset': 'eyas.n.01', 'name': 'eyas'}, {'id': 2009, 'synset': 'tiercel.n.01', 'name': 'tiercel'}, {'id': 2010, 'synset': 'goshawk.n.01', 'name': 'goshawk'}, {'id': 2011, 'synset': 'sparrow_hawk.n.02', 'name': 'sparrow_hawk'}, {'id': 2012, 'synset': "cooper's_hawk.n.01", 'name': "Cooper's_hawk"}, {'id': 2013, 'synset': 'chicken_hawk.n.01', 'name': 'chicken_hawk'}, {'id': 2014, 'synset': 'buteonine.n.01', 'name': 'buteonine'}, {'id': 2015, 'synset': 'redtail.n.01', 'name': 'redtail'}, {'id': 2016, 'synset': 'rough-legged_hawk.n.01', 'name': 'rough-legged_hawk'}, {'id': 2017, 'synset': 'red-shouldered_hawk.n.01', 'name': 'red-shouldered_hawk'}, {'id': 2018, 'synset': 'buzzard.n.02', 'name': 'buzzard'}, {'id': 2019, 'synset': 'honey_buzzard.n.01', 'name': 'honey_buzzard'}, {'id': 2020, 'synset': 'kite.n.04', 'name': 'kite'}, {'id': 2021, 'synset': 'black_kite.n.01', 'name': 'black_kite'}, {'id': 2022, 'synset': 'swallow-tailed_kite.n.01', 'name': 'swallow-tailed_kite'}, {'id': 2023, 'synset': 'white-tailed_kite.n.01', 'name': 'white-tailed_kite'}, {'id': 2024, 'synset': 'harrier.n.03', 'name': 'harrier'}, {'id': 2025, 'synset': 'marsh_harrier.n.01', 'name': 'marsh_harrier'}, {'id': 2026, 'synset': "montagu's_harrier.n.01", 'name': "Montagu's_harrier"}, {'id': 2027, 'synset': 'marsh_hawk.n.01', 'name': 'marsh_hawk'}, {'id': 2028, 'synset': 'harrier_eagle.n.01', 'name': 'harrier_eagle'}, {'id': 2029, 'synset': 'peregrine.n.01', 'name': 'peregrine'}, {'id': 2030, 'synset': 'falcon-gentle.n.01', 'name': 'falcon-gentle'}, {'id': 2031, 'synset': 'gyrfalcon.n.01', 'name': 'gyrfalcon'}, {'id': 2032, 'synset': 'kestrel.n.02', 'name': 'kestrel'}, {'id': 2033, 'synset': 'sparrow_hawk.n.01', 'name': 'sparrow_hawk'}, {'id': 2034, 'synset': 'pigeon_hawk.n.01', 'name': 'pigeon_hawk'}, {'id': 2035, 'synset': 'hobby.n.03', 'name': 'hobby'}, {'id': 2036, 'synset': 'caracara.n.01', 'name': 'caracara'}, {'id': 2037, 'synset': "audubon's_caracara.n.01", 'name': "Audubon's_caracara"}, {'id': 2038, 'synset': 'carancha.n.01', 'name': 'carancha'}, {'id': 2039, 'synset': 'young_bird.n.01', 'name': 'young_bird'}, {'id': 2040, 'synset': 'eaglet.n.01', 'name': 'eaglet'}, {'id': 2041, 'synset': 'harpy.n.04', 'name': 'harpy'}, {'id': 2042, 'synset': 'golden_eagle.n.01', 'name': 'golden_eagle'}, {'id': 2043, 'synset': 'tawny_eagle.n.01', 'name': 'tawny_eagle'}, {'id': 2044, 'synset': 'bald_eagle.n.01', 'name': 'bald_eagle'}, {'id': 2045, 'synset': 'sea_eagle.n.02', 'name': 'sea_eagle'}, {'id': 2046, 'synset': 'kamchatkan_sea_eagle.n.01', 'name': 'Kamchatkan_sea_eagle'}, {'id': 2047, 'synset': 'ern.n.01', 'name': 'ern'}, {'id': 2048, 'synset': 'fishing_eagle.n.01', 'name': 'fishing_eagle'}, {'id': 2049, 'synset': 'osprey.n.01', 'name': 'osprey'}, {'id': 2050, 'synset': 'aegypiidae.n.01', 'name': 'Aegypiidae'}, {'id': 2051, 'synset': 'old_world_vulture.n.01', 'name': 'Old_World_vulture'}, {'id': 2052, 'synset': 'griffon_vulture.n.01', 'name': 'griffon_vulture'}, {'id': 2053, 'synset': 'bearded_vulture.n.01', 'name': 'bearded_vulture'}, {'id': 2054, 'synset': 'egyptian_vulture.n.01', 'name': 'Egyptian_vulture'}, {'id': 2055, 'synset': 'black_vulture.n.02', 'name': 'black_vulture'}, {'id': 2056, 'synset': 'secretary_bird.n.01', 'name': 'secretary_bird'}, {'id': 2057, 'synset': 'new_world_vulture.n.01', 'name': 'New_World_vulture'}, {'id': 2058, 'synset': 'buzzard.n.01', 'name': 'buzzard'}, {'id': 2059, 'synset': 'condor.n.01', 'name': 'condor'}, {'id': 2060, 'synset': 'andean_condor.n.01', 'name': 'Andean_condor'}, {'id': 2061, 'synset': 'california_condor.n.01', 'name': 'California_condor'}, {'id': 2062, 'synset': 'black_vulture.n.01', 'name': 'black_vulture'}, {'id': 2063, 'synset': 'king_vulture.n.01', 'name': 'king_vulture'}, {'id': 2064, 'synset': 'owlet.n.01', 'name': 'owlet'}, {'id': 2065, 'synset': 'little_owl.n.01', 'name': 'little_owl'}, {'id': 2066, 'synset': 'horned_owl.n.01', 'name': 'horned_owl'}, {'id': 2067, 'synset': 'great_horned_owl.n.01', 'name': 'great_horned_owl'}, {'id': 2068, 'synset': 'great_grey_owl.n.01', 'name': 'great_grey_owl'}, {'id': 2069, 'synset': 'tawny_owl.n.01', 'name': 'tawny_owl'}, {'id': 2070, 'synset': 'barred_owl.n.01', 'name': 'barred_owl'}, {'id': 2071, 'synset': 'screech_owl.n.02', 'name': 'screech_owl'}, {'id': 2072, 'synset': 'screech_owl.n.01', 'name': 'screech_owl'}, {'id': 2073, 'synset': 'scops_owl.n.01', 'name': 'scops_owl'}, {'id': 2074, 'synset': 'spotted_owl.n.01', 'name': 'spotted_owl'}, {'id': 2075, 'synset': 'old_world_scops_owl.n.01', 'name': 'Old_World_scops_owl'}, {'id': 2076, 'synset': 'oriental_scops_owl.n.01', 'name': 'Oriental_scops_owl'}, {'id': 2077, 'synset': 'hoot_owl.n.01', 'name': 'hoot_owl'}, {'id': 2078, 'synset': 'hawk_owl.n.01', 'name': 'hawk_owl'}, {'id': 2079, 'synset': 'long-eared_owl.n.01', 'name': 'long-eared_owl'}, {'id': 2080, 'synset': 'laughing_owl.n.01', 'name': 'laughing_owl'}, {'id': 2081, 'synset': 'barn_owl.n.01', 'name': 'barn_owl'}, {'id': 2082, 'synset': 'amphibian.n.03', 'name': 'amphibian'}, {'id': 2083, 'synset': 'ichyostega.n.01', 'name': 'Ichyostega'}, {'id': 2084, 'synset': 'urodele.n.01', 'name': 'urodele'}, {'id': 2085, 'synset': 'salamander.n.01', 'name': 'salamander'}, {'id': 2086, 'synset': 'european_fire_salamander.n.01', 'name': 'European_fire_salamander'}, {'id': 2087, 'synset': 'spotted_salamander.n.02', 'name': 'spotted_salamander'}, {'id': 2088, 'synset': 'alpine_salamander.n.01', 'name': 'alpine_salamander'}, {'id': 2089, 'synset': 'newt.n.01', 'name': 'newt'}, {'id': 2090, 'synset': 'common_newt.n.01', 'name': 'common_newt'}, {'id': 2091, 'synset': 'red_eft.n.01', 'name': 'red_eft'}, {'id': 2092, 'synset': 'pacific_newt.n.01', 'name': 'Pacific_newt'}, {'id': 2093, 'synset': 'rough-skinned_newt.n.01', 'name': 'rough-skinned_newt'}, {'id': 2094, 'synset': 'california_newt.n.01', 'name': 'California_newt'}, {'id': 2095, 'synset': 'eft.n.01', 'name': 'eft'}, {'id': 2096, 'synset': 'ambystomid.n.01', 'name': 'ambystomid'}, {'id': 2097, 'synset': 'mole_salamander.n.01', 'name': 'mole_salamander'}, {'id': 2098, 'synset': 'spotted_salamander.n.01', 'name': 'spotted_salamander'}, {'id': 2099, 'synset': 'tiger_salamander.n.01', 'name': 'tiger_salamander'}, {'id': 2100, 'synset': 'axolotl.n.01', 'name': 'axolotl'}, {'id': 2101, 'synset': 'waterdog.n.01', 'name': 'waterdog'}, {'id': 2102, 'synset': 'hellbender.n.01', 'name': 'hellbender'}, {'id': 2103, 'synset': 'giant_salamander.n.01', 'name': 'giant_salamander'}, {'id': 2104, 'synset': 'olm.n.01', 'name': 'olm'}, {'id': 2105, 'synset': 'mud_puppy.n.01', 'name': 'mud_puppy'}, {'id': 2106, 'synset': 'dicamptodon.n.01', 'name': 'dicamptodon'}, {'id': 2107, 'synset': 'pacific_giant_salamander.n.01', 'name': 'Pacific_giant_salamander'}, {'id': 2108, 'synset': 'olympic_salamander.n.01', 'name': 'olympic_salamander'}, {'id': 2109, 'synset': 'lungless_salamander.n.01', 'name': 'lungless_salamander'}, {'id': 2110, 'synset': 'eastern_red-backed_salamander.n.01', 'name': 'eastern_red-backed_salamander'}, {'id': 2111, 'synset': 'western_red-backed_salamander.n.01', 'name': 'western_red-backed_salamander'}, {'id': 2112, 'synset': 'dusky_salamander.n.01', 'name': 'dusky_salamander'}, {'id': 2113, 'synset': 'climbing_salamander.n.01', 'name': 'climbing_salamander'}, {'id': 2114, 'synset': 'arboreal_salamander.n.01', 'name': 'arboreal_salamander'}, {'id': 2115, 'synset': 'slender_salamander.n.01', 'name': 'slender_salamander'}, {'id': 2116, 'synset': 'web-toed_salamander.n.01', 'name': 'web-toed_salamander'}, {'id': 2117, 'synset': 'shasta_salamander.n.01', 'name': 'Shasta_salamander'}, {'id': 2118, 'synset': 'limestone_salamander.n.01', 'name': 'limestone_salamander'}, {'id': 2119, 'synset': 'amphiuma.n.01', 'name': 'amphiuma'}, {'id': 2120, 'synset': 'siren.n.05', 'name': 'siren'}, {'id': 2121, 'synset': 'true_frog.n.01', 'name': 'true_frog'}, {'id': 2122, 'synset': 'wood-frog.n.01', 'name': 'wood-frog'}, {'id': 2123, 'synset': 'leopard_frog.n.01', 'name': 'leopard_frog'}, {'id': 2124, 'synset': 'bullfrog.n.01', 'name': 'bullfrog'}, {'id': 2125, 'synset': 'green_frog.n.01', 'name': 'green_frog'}, {'id': 2126, 'synset': 'cascades_frog.n.01', 'name': 'cascades_frog'}, {'id': 2127, 'synset': 'goliath_frog.n.01', 'name': 'goliath_frog'}, {'id': 2128, 'synset': 'pickerel_frog.n.01', 'name': 'pickerel_frog'}, {'id': 2129, 'synset': 'tarahumara_frog.n.01', 'name': 'tarahumara_frog'}, {'id': 2130, 'synset': 'grass_frog.n.01', 'name': 'grass_frog'}, {'id': 2131, 'synset': 'leptodactylid_frog.n.01', 'name': 'leptodactylid_frog'}, {'id': 2132, 'synset': 'robber_frog.n.02', 'name': 'robber_frog'}, {'id': 2133, 'synset': 'barking_frog.n.01', 'name': 'barking_frog'}, {'id': 2134, 'synset': 'crapaud.n.01', 'name': 'crapaud'}, {'id': 2135, 'synset': 'tree_frog.n.02', 'name': 'tree_frog'}, {'id': 2136, 'synset': 'tailed_frog.n.01', 'name': 'tailed_frog'}, {'id': 2137, 'synset': 'liopelma_hamiltoni.n.01', 'name': 'Liopelma_hamiltoni'}, {'id': 2138, 'synset': 'true_toad.n.01', 'name': 'true_toad'}, {'id': 2139, 'synset': 'bufo.n.01', 'name': 'bufo'}, {'id': 2140, 'synset': 'agua.n.01', 'name': 'agua'}, {'id': 2141, 'synset': 'european_toad.n.01', 'name': 'European_toad'}, {'id': 2142, 'synset': 'natterjack.n.01', 'name': 'natterjack'}, {'id': 2143, 'synset': 'american_toad.n.01', 'name': 'American_toad'}, {'id': 2144, 'synset': 'eurasian_green_toad.n.01', 'name': 'Eurasian_green_toad'}, {'id': 2145, 'synset': 'american_green_toad.n.01', 'name': 'American_green_toad'}, {'id': 2146, 'synset': 'yosemite_toad.n.01', 'name': 'Yosemite_toad'}, {'id': 2147, 'synset': 'texas_toad.n.01', 'name': 'Texas_toad'}, {'id': 2148, 'synset': 'southwestern_toad.n.01', 'name': 'southwestern_toad'}, {'id': 2149, 'synset': 'western_toad.n.01', 'name': 'western_toad'}, {'id': 2150, 'synset': 'obstetrical_toad.n.01', 'name': 'obstetrical_toad'}, {'id': 2151, 'synset': 'midwife_toad.n.01', 'name': 'midwife_toad'}, {'id': 2152, 'synset': 'fire-bellied_toad.n.01', 'name': 'fire-bellied_toad'}, {'id': 2153, 'synset': 'spadefoot.n.01', 'name': 'spadefoot'}, {'id': 2154, 'synset': 'western_spadefoot.n.01', 'name': 'western_spadefoot'}, {'id': 2155, 'synset': 'southern_spadefoot.n.01', 'name': 'southern_spadefoot'}, {'id': 2156, 'synset': 'plains_spadefoot.n.01', 'name': 'plains_spadefoot'}, {'id': 2157, 'synset': 'tree_toad.n.01', 'name': 'tree_toad'}, {'id': 2158, 'synset': 'spring_peeper.n.01', 'name': 'spring_peeper'}, {'id': 2159, 'synset': 'pacific_tree_toad.n.01', 'name': 'Pacific_tree_toad'}, {'id': 2160, 'synset': 'canyon_treefrog.n.01', 'name': 'canyon_treefrog'}, {'id': 2161, 'synset': 'chameleon_tree_frog.n.01', 'name': 'chameleon_tree_frog'}, {'id': 2162, 'synset': 'cricket_frog.n.01', 'name': 'cricket_frog'}, {'id': 2163, 'synset': 'northern_cricket_frog.n.01', 'name': 'northern_cricket_frog'}, {'id': 2164, 'synset': 'eastern_cricket_frog.n.01', 'name': 'eastern_cricket_frog'}, {'id': 2165, 'synset': 'chorus_frog.n.01', 'name': 'chorus_frog'}, {'id': 2166, 'synset': 'lowland_burrowing_treefrog.n.01', 'name': 'lowland_burrowing_treefrog'}, {'id': 2167, 'synset': 'western_narrow-mouthed_toad.n.01', 'name': 'western_narrow-mouthed_toad'}, {'id': 2168, 'synset': 'eastern_narrow-mouthed_toad.n.01', 'name': 'eastern_narrow-mouthed_toad'}, {'id': 2169, 'synset': 'sheep_frog.n.01', 'name': 'sheep_frog'}, {'id': 2170, 'synset': 'tongueless_frog.n.01', 'name': 'tongueless_frog'}, {'id': 2171, 'synset': 'surinam_toad.n.01', 'name': 'Surinam_toad'}, {'id': 2172, 'synset': 'african_clawed_frog.n.01', 'name': 'African_clawed_frog'}, {'id': 2173, 'synset': 'south_american_poison_toad.n.01', 'name': 'South_American_poison_toad'}, {'id': 2174, 'synset': 'caecilian.n.01', 'name': 'caecilian'}, {'id': 2175, 'synset': 'reptile.n.01', 'name': 'reptile'}, {'id': 2176, 'synset': 'anapsid.n.01', 'name': 'anapsid'}, {'id': 2177, 'synset': 'diapsid.n.01', 'name': 'diapsid'}, {'id': 2178, 'synset': 'diapsida.n.01', 'name': 'Diapsida'}, {'id': 2179, 'synset': 'chelonian.n.01', 'name': 'chelonian'}, {'id': 2180, 'synset': 'sea_turtle.n.01', 'name': 'sea_turtle'}, {'id': 2181, 'synset': 'green_turtle.n.01', 'name': 'green_turtle'}, {'id': 2182, 'synset': 'loggerhead.n.02', 'name': 'loggerhead'}, {'id': 2183, 'synset': 'ridley.n.01', 'name': 'ridley'}, {'id': 2184, 'synset': 'atlantic_ridley.n.01', 'name': 'Atlantic_ridley'}, {'id': 2185, 'synset': 'pacific_ridley.n.01', 'name': 'Pacific_ridley'}, {'id': 2186, 'synset': 'hawksbill_turtle.n.01', 'name': 'hawksbill_turtle'}, {'id': 2187, 'synset': 'leatherback_turtle.n.01', 'name': 'leatherback_turtle'}, {'id': 2188, 'synset': 'snapping_turtle.n.01', 'name': 'snapping_turtle'}, {'id': 2189, 'synset': 'common_snapping_turtle.n.01', 'name': 'common_snapping_turtle'}, {'id': 2190, 'synset': 'alligator_snapping_turtle.n.01', 'name': 'alligator_snapping_turtle'}, {'id': 2191, 'synset': 'mud_turtle.n.01', 'name': 'mud_turtle'}, {'id': 2192, 'synset': 'musk_turtle.n.01', 'name': 'musk_turtle'}, {'id': 2193, 'synset': 'terrapin.n.01', 'name': 'terrapin'}, {'id': 2194, 'synset': 'diamondback_terrapin.n.01', 'name': 'diamondback_terrapin'}, {'id': 2195, 'synset': 'red-bellied_terrapin.n.01', 'name': 'red-bellied_terrapin'}, {'id': 2196, 'synset': 'slider.n.03', 'name': 'slider'}, {'id': 2197, 'synset': 'cooter.n.01', 'name': 'cooter'}, {'id': 2198, 'synset': 'box_turtle.n.01', 'name': 'box_turtle'}, {'id': 2199, 'synset': 'western_box_turtle.n.01', 'name': 'Western_box_turtle'}, {'id': 2200, 'synset': 'painted_turtle.n.01', 'name': 'painted_turtle'}, {'id': 2201, 'synset': 'tortoise.n.01', 'name': 'tortoise'}, {'id': 2202, 'synset': 'european_tortoise.n.01', 'name': 'European_tortoise'}, {'id': 2203, 'synset': 'giant_tortoise.n.01', 'name': 'giant_tortoise'}, {'id': 2204, 'synset': 'gopher_tortoise.n.01', 'name': 'gopher_tortoise'}, {'id': 2205, 'synset': 'desert_tortoise.n.01', 'name': 'desert_tortoise'}, {'id': 2206, 'synset': 'texas_tortoise.n.01', 'name': 'Texas_tortoise'}, {'id': 2207, 'synset': 'soft-shelled_turtle.n.01', 'name': 'soft-shelled_turtle'}, {'id': 2208, 'synset': 'spiny_softshell.n.01', 'name': 'spiny_softshell'}, {'id': 2209, 'synset': 'smooth_softshell.n.01', 'name': 'smooth_softshell'}, {'id': 2210, 'synset': 'tuatara.n.01', 'name': 'tuatara'}, {'id': 2211, 'synset': 'saurian.n.01', 'name': 'saurian'}, {'id': 2212, 'synset': 'gecko.n.01', 'name': 'gecko'}, {'id': 2213, 'synset': 'flying_gecko.n.01', 'name': 'flying_gecko'}, {'id': 2214, 'synset': 'banded_gecko.n.01', 'name': 'banded_gecko'}, {'id': 2215, 'synset': 'iguanid.n.01', 'name': 'iguanid'}, {'id': 2216, 'synset': 'common_iguana.n.01', 'name': 'common_iguana'}, {'id': 2217, 'synset': 'marine_iguana.n.01', 'name': 'marine_iguana'}, {'id': 2218, 'synset': 'desert_iguana.n.01', 'name': 'desert_iguana'}, {'id': 2219, 'synset': 'chuckwalla.n.01', 'name': 'chuckwalla'}, {'id': 2220, 'synset': 'zebra-tailed_lizard.n.01', 'name': 'zebra-tailed_lizard'}, {'id': 2221, 'synset': 'fringe-toed_lizard.n.01', 'name': 'fringe-toed_lizard'}, {'id': 2222, 'synset': 'earless_lizard.n.01', 'name': 'earless_lizard'}, {'id': 2223, 'synset': 'collared_lizard.n.01', 'name': 'collared_lizard'}, {'id': 2224, 'synset': 'leopard_lizard.n.01', 'name': 'leopard_lizard'}, {'id': 2225, 'synset': 'spiny_lizard.n.02', 'name': 'spiny_lizard'}, {'id': 2226, 'synset': 'fence_lizard.n.01', 'name': 'fence_lizard'}, {'id': 2227, 'synset': 'western_fence_lizard.n.01', 'name': 'western_fence_lizard'}, {'id': 2228, 'synset': 'eastern_fence_lizard.n.01', 'name': 'eastern_fence_lizard'}, {'id': 2229, 'synset': 'sagebrush_lizard.n.01', 'name': 'sagebrush_lizard'}, {'id': 2230, 'synset': 'side-blotched_lizard.n.01', 'name': 'side-blotched_lizard'}, {'id': 2231, 'synset': 'tree_lizard.n.01', 'name': 'tree_lizard'}, {'id': 2232, 'synset': 'horned_lizard.n.01', 'name': 'horned_lizard'}, {'id': 2233, 'synset': 'texas_horned_lizard.n.01', 'name': 'Texas_horned_lizard'}, {'id': 2234, 'synset': 'basilisk.n.03', 'name': 'basilisk'}, {'id': 2235, 'synset': 'american_chameleon.n.01', 'name': 'American_chameleon'}, {'id': 2236, 'synset': 'worm_lizard.n.01', 'name': 'worm_lizard'}, {'id': 2237, 'synset': 'night_lizard.n.01', 'name': 'night_lizard'}, {'id': 2238, 'synset': 'skink.n.01', 'name': 'skink'}, {'id': 2239, 'synset': 'western_skink.n.01', 'name': 'western_skink'}, {'id': 2240, 'synset': 'mountain_skink.n.01', 'name': 'mountain_skink'}, {'id': 2241, 'synset': 'teiid_lizard.n.01', 'name': 'teiid_lizard'}, {'id': 2242, 'synset': 'whiptail.n.01', 'name': 'whiptail'}, {'id': 2243, 'synset': 'racerunner.n.01', 'name': 'racerunner'}, {'id': 2244, 'synset': 'plateau_striped_whiptail.n.01', 'name': 'plateau_striped_whiptail'}, {'id': 2245, 'synset': 'chihuahuan_spotted_whiptail.n.01', 'name': 'Chihuahuan_spotted_whiptail'}, {'id': 2246, 'synset': 'western_whiptail.n.01', 'name': 'western_whiptail'}, {'id': 2247, 'synset': 'checkered_whiptail.n.01', 'name': 'checkered_whiptail'}, {'id': 2248, 'synset': 'teju.n.01', 'name': 'teju'}, {'id': 2249, 'synset': 'caiman_lizard.n.01', 'name': 'caiman_lizard'}, {'id': 2250, 'synset': 'agamid.n.01', 'name': 'agamid'}, {'id': 2251, 'synset': 'agama.n.01', 'name': 'agama'}, {'id': 2252, 'synset': 'frilled_lizard.n.01', 'name': 'frilled_lizard'}, {'id': 2253, 'synset': 'moloch.n.03', 'name': 'moloch'}, {'id': 2254, 'synset': 'mountain_devil.n.02', 'name': 'mountain_devil'}, {'id': 2255, 'synset': 'anguid_lizard.n.01', 'name': 'anguid_lizard'}, {'id': 2256, 'synset': 'alligator_lizard.n.01', 'name': 'alligator_lizard'}, {'id': 2257, 'synset': 'blindworm.n.01', 'name': 'blindworm'}, {'id': 2258, 'synset': 'glass_lizard.n.01', 'name': 'glass_lizard'}, {'id': 2259, 'synset': 'legless_lizard.n.01', 'name': 'legless_lizard'}, {'id': 2260, 'synset': 'lanthanotus_borneensis.n.01', 'name': 'Lanthanotus_borneensis'}, {'id': 2261, 'synset': 'venomous_lizard.n.01', 'name': 'venomous_lizard'}, {'id': 2262, 'synset': 'gila_monster.n.01', 'name': 'Gila_monster'}, {'id': 2263, 'synset': 'beaded_lizard.n.01', 'name': 'beaded_lizard'}, {'id': 2264, 'synset': 'lacertid_lizard.n.01', 'name': 'lacertid_lizard'}, {'id': 2265, 'synset': 'sand_lizard.n.01', 'name': 'sand_lizard'}, {'id': 2266, 'synset': 'green_lizard.n.01', 'name': 'green_lizard'}, {'id': 2267, 'synset': 'chameleon.n.03', 'name': 'chameleon'}, {'id': 2268, 'synset': 'african_chameleon.n.01', 'name': 'African_chameleon'}, {'id': 2269, 'synset': 'horned_chameleon.n.01', 'name': 'horned_chameleon'}, {'id': 2270, 'synset': 'monitor.n.07', 'name': 'monitor'}, {'id': 2271, 'synset': 'african_monitor.n.01', 'name': 'African_monitor'}, {'id': 2272, 'synset': 'komodo_dragon.n.01', 'name': 'Komodo_dragon'}, {'id': 2273, 'synset': 'crocodilian_reptile.n.01', 'name': 'crocodilian_reptile'}, {'id': 2274, 'synset': 'crocodile.n.01', 'name': 'crocodile'}, {'id': 2275, 'synset': 'african_crocodile.n.01', 'name': 'African_crocodile'}, {'id': 2276, 'synset': 'asian_crocodile.n.01', 'name': 'Asian_crocodile'}, {'id': 2277, 'synset': "morlett's_crocodile.n.01", 'name': "Morlett's_crocodile"}, {'id': 2278, 'synset': 'false_gavial.n.01', 'name': 'false_gavial'}, {'id': 2279, 'synset': 'american_alligator.n.01', 'name': 'American_alligator'}, {'id': 2280, 'synset': 'chinese_alligator.n.01', 'name': 'Chinese_alligator'}, {'id': 2281, 'synset': 'caiman.n.01', 'name': 'caiman'}, {'id': 2282, 'synset': 'spectacled_caiman.n.01', 'name': 'spectacled_caiman'}, {'id': 2283, 'synset': 'gavial.n.01', 'name': 'gavial'}, {'id': 2284, 'synset': 'armored_dinosaur.n.01', 'name': 'armored_dinosaur'}, {'id': 2285, 'synset': 'stegosaur.n.01', 'name': 'stegosaur'}, {'id': 2286, 'synset': 'ankylosaur.n.01', 'name': 'ankylosaur'}, {'id': 2287, 'synset': 'edmontonia.n.01', 'name': 'Edmontonia'}, {'id': 2288, 'synset': 'bone-headed_dinosaur.n.01', 'name': 'bone-headed_dinosaur'}, {'id': 2289, 'synset': 'pachycephalosaur.n.01', 'name': 'pachycephalosaur'}, {'id': 2290, 'synset': 'ceratopsian.n.01', 'name': 'ceratopsian'}, {'id': 2291, 'synset': 'protoceratops.n.01', 'name': 'protoceratops'}, {'id': 2292, 'synset': 'triceratops.n.01', 'name': 'triceratops'}, {'id': 2293, 'synset': 'styracosaur.n.01', 'name': 'styracosaur'}, {'id': 2294, 'synset': 'psittacosaur.n.01', 'name': 'psittacosaur'}, {'id': 2295, 'synset': 'ornithopod.n.01', 'name': 'ornithopod'}, {'id': 2296, 'synset': 'hadrosaur.n.01', 'name': 'hadrosaur'}, {'id': 2297, 'synset': 'trachodon.n.01', 'name': 'trachodon'}, {'id': 2298, 'synset': 'saurischian.n.01', 'name': 'saurischian'}, {'id': 2299, 'synset': 'sauropod.n.01', 'name': 'sauropod'}, {'id': 2300, 'synset': 'apatosaur.n.01', 'name': 'apatosaur'}, {'id': 2301, 'synset': 'barosaur.n.01', 'name': 'barosaur'}, {'id': 2302, 'synset': 'diplodocus.n.01', 'name': 'diplodocus'}, {'id': 2303, 'synset': 'argentinosaur.n.01', 'name': 'argentinosaur'}, {'id': 2304, 'synset': 'theropod.n.01', 'name': 'theropod'}, {'id': 2305, 'synset': 'ceratosaur.n.01', 'name': 'ceratosaur'}, {'id': 2306, 'synset': 'coelophysis.n.01', 'name': 'coelophysis'}, {'id': 2307, 'synset': 'tyrannosaur.n.01', 'name': 'tyrannosaur'}, {'id': 2308, 'synset': 'allosaur.n.01', 'name': 'allosaur'}, {'id': 2309, 'synset': 'ornithomimid.n.01', 'name': 'ornithomimid'}, {'id': 2310, 'synset': 'maniraptor.n.01', 'name': 'maniraptor'}, {'id': 2311, 'synset': 'oviraptorid.n.01', 'name': 'oviraptorid'}, {'id': 2312, 'synset': 'velociraptor.n.01', 'name': 'velociraptor'}, {'id': 2313, 'synset': 'deinonychus.n.01', 'name': 'deinonychus'}, {'id': 2314, 'synset': 'utahraptor.n.01', 'name': 'utahraptor'}, {'id': 2315, 'synset': 'synapsid.n.01', 'name': 'synapsid'}, {'id': 2316, 'synset': 'dicynodont.n.01', 'name': 'dicynodont'}, {'id': 2317, 'synset': 'pelycosaur.n.01', 'name': 'pelycosaur'}, {'id': 2318, 'synset': 'dimetrodon.n.01', 'name': 'dimetrodon'}, {'id': 2319, 'synset': 'pterosaur.n.01', 'name': 'pterosaur'}, {'id': 2320, 'synset': 'pterodactyl.n.01', 'name': 'pterodactyl'}, {'id': 2321, 'synset': 'ichthyosaur.n.01', 'name': 'ichthyosaur'}, {'id': 2322, 'synset': 'ichthyosaurus.n.01', 'name': 'ichthyosaurus'}, {'id': 2323, 'synset': 'stenopterygius.n.01', 'name': 'stenopterygius'}, {'id': 2324, 'synset': 'plesiosaur.n.01', 'name': 'plesiosaur'}, {'id': 2325, 'synset': 'nothosaur.n.01', 'name': 'nothosaur'}, {'id': 2326, 'synset': 'colubrid_snake.n.01', 'name': 'colubrid_snake'}, {'id': 2327, 'synset': 'hoop_snake.n.01', 'name': 'hoop_snake'}, {'id': 2328, 'synset': 'thunder_snake.n.01', 'name': 'thunder_snake'}, {'id': 2329, 'synset': 'ringneck_snake.n.01', 'name': 'ringneck_snake'}, {'id': 2330, 'synset': 'hognose_snake.n.01', 'name': 'hognose_snake'}, {'id': 2331, 'synset': 'leaf-nosed_snake.n.01', 'name': 'leaf-nosed_snake'}, {'id': 2332, 'synset': 'green_snake.n.02', 'name': 'green_snake'}, {'id': 2333, 'synset': 'smooth_green_snake.n.01', 'name': 'smooth_green_snake'}, {'id': 2334, 'synset': 'rough_green_snake.n.01', 'name': 'rough_green_snake'}, {'id': 2335, 'synset': 'green_snake.n.01', 'name': 'green_snake'}, {'id': 2336, 'synset': 'racer.n.04', 'name': 'racer'}, {'id': 2337, 'synset': 'blacksnake.n.02', 'name': 'blacksnake'}, {'id': 2338, 'synset': 'blue_racer.n.01', 'name': 'blue_racer'}, {'id': 2339, 'synset': 'horseshoe_whipsnake.n.01', 'name': 'horseshoe_whipsnake'}, {'id': 2340, 'synset': 'whip-snake.n.01', 'name': 'whip-snake'}, {'id': 2341, 'synset': 'coachwhip.n.02', 'name': 'coachwhip'}, {'id': 2342, 'synset': 'california_whipsnake.n.01', 'name': 'California_whipsnake'}, {'id': 2343, 'synset': 'sonoran_whipsnake.n.01', 'name': 'Sonoran_whipsnake'}, {'id': 2344, 'synset': 'rat_snake.n.01', 'name': 'rat_snake'}, {'id': 2345, 'synset': 'corn_snake.n.01', 'name': 'corn_snake'}, {'id': 2346, 'synset': 'black_rat_snake.n.01', 'name': 'black_rat_snake'}, {'id': 2347, 'synset': 'chicken_snake.n.01', 'name': 'chicken_snake'}, {'id': 2348, 'synset': 'indian_rat_snake.n.01', 'name': 'Indian_rat_snake'}, {'id': 2349, 'synset': 'glossy_snake.n.01', 'name': 'glossy_snake'}, {'id': 2350, 'synset': 'bull_snake.n.01', 'name': 'bull_snake'}, {'id': 2351, 'synset': 'gopher_snake.n.02', 'name': 'gopher_snake'}, {'id': 2352, 'synset': 'pine_snake.n.01', 'name': 'pine_snake'}, {'id': 2353, 'synset': 'king_snake.n.01', 'name': 'king_snake'}, {'id': 2354, 'synset': 'common_kingsnake.n.01', 'name': 'common_kingsnake'}, {'id': 2355, 'synset': 'milk_snake.n.01', 'name': 'milk_snake'}, {'id': 2356, 'synset': 'garter_snake.n.01', 'name': 'garter_snake'}, {'id': 2357, 'synset': 'common_garter_snake.n.01', 'name': 'common_garter_snake'}, {'id': 2358, 'synset': 'ribbon_snake.n.01', 'name': 'ribbon_snake'}, {'id': 2359, 'synset': 'western_ribbon_snake.n.01', 'name': 'Western_ribbon_snake'}, {'id': 2360, 'synset': 'lined_snake.n.01', 'name': 'lined_snake'}, {'id': 2361, 'synset': 'ground_snake.n.01', 'name': 'ground_snake'}, {'id': 2362, 'synset': 'eastern_ground_snake.n.01', 'name': 'eastern_ground_snake'}, {'id': 2363, 'synset': 'water_snake.n.01', 'name': 'water_snake'}, {'id': 2364, 'synset': 'common_water_snake.n.01', 'name': 'common_water_snake'}, {'id': 2365, 'synset': 'water_moccasin.n.02', 'name': 'water_moccasin'}, {'id': 2366, 'synset': 'grass_snake.n.01', 'name': 'grass_snake'}, {'id': 2367, 'synset': 'viperine_grass_snake.n.01', 'name': 'viperine_grass_snake'}, {'id': 2368, 'synset': 'red-bellied_snake.n.01', 'name': 'red-bellied_snake'}, {'id': 2369, 'synset': 'sand_snake.n.01', 'name': 'sand_snake'}, {'id': 2370, 'synset': 'banded_sand_snake.n.01', 'name': 'banded_sand_snake'}, {'id': 2371, 'synset': 'black-headed_snake.n.01', 'name': 'black-headed_snake'}, {'id': 2372, 'synset': 'vine_snake.n.01', 'name': 'vine_snake'}, {'id': 2373, 'synset': 'lyre_snake.n.01', 'name': 'lyre_snake'}, {'id': 2374, 'synset': 'sonoran_lyre_snake.n.01', 'name': 'Sonoran_lyre_snake'}, {'id': 2375, 'synset': 'night_snake.n.01', 'name': 'night_snake'}, {'id': 2376, 'synset': 'blind_snake.n.01', 'name': 'blind_snake'}, {'id': 2377, 'synset': 'western_blind_snake.n.01', 'name': 'western_blind_snake'}, {'id': 2378, 'synset': 'indigo_snake.n.01', 'name': 'indigo_snake'}, {'id': 2379, 'synset': 'eastern_indigo_snake.n.01', 'name': 'eastern_indigo_snake'}, {'id': 2380, 'synset': 'constrictor.n.01', 'name': 'constrictor'}, {'id': 2381, 'synset': 'boa.n.02', 'name': 'boa'}, {'id': 2382, 'synset': 'boa_constrictor.n.01', 'name': 'boa_constrictor'}, {'id': 2383, 'synset': 'rubber_boa.n.01', 'name': 'rubber_boa'}, {'id': 2384, 'synset': 'rosy_boa.n.01', 'name': 'rosy_boa'}, {'id': 2385, 'synset': 'anaconda.n.01', 'name': 'anaconda'}, {'id': 2386, 'synset': 'python.n.01', 'name': 'python'}, {'id': 2387, 'synset': 'carpet_snake.n.01', 'name': 'carpet_snake'}, {'id': 2388, 'synset': 'reticulated_python.n.01', 'name': 'reticulated_python'}, {'id': 2389, 'synset': 'indian_python.n.01', 'name': 'Indian_python'}, {'id': 2390, 'synset': 'rock_python.n.01', 'name': 'rock_python'}, {'id': 2391, 'synset': 'amethystine_python.n.01', 'name': 'amethystine_python'}, {'id': 2392, 'synset': 'elapid.n.01', 'name': 'elapid'}, {'id': 2393, 'synset': 'coral_snake.n.02', 'name': 'coral_snake'}, {'id': 2394, 'synset': 'eastern_coral_snake.n.01', 'name': 'eastern_coral_snake'}, {'id': 2395, 'synset': 'western_coral_snake.n.01', 'name': 'western_coral_snake'}, {'id': 2396, 'synset': 'coral_snake.n.01', 'name': 'coral_snake'}, {'id': 2397, 'synset': 'african_coral_snake.n.01', 'name': 'African_coral_snake'}, {'id': 2398, 'synset': 'australian_coral_snake.n.01', 'name': 'Australian_coral_snake'}, {'id': 2399, 'synset': 'copperhead.n.02', 'name': 'copperhead'}, {'id': 2400, 'synset': 'cobra.n.01', 'name': 'cobra'}, {'id': 2401, 'synset': 'indian_cobra.n.01', 'name': 'Indian_cobra'}, {'id': 2402, 'synset': 'asp.n.02', 'name': 'asp'}, {'id': 2403, 'synset': 'black-necked_cobra.n.01', 'name': 'black-necked_cobra'}, {'id': 2404, 'synset': 'hamadryad.n.02', 'name': 'hamadryad'}, {'id': 2405, 'synset': 'ringhals.n.01', 'name': 'ringhals'}, {'id': 2406, 'synset': 'mamba.n.01', 'name': 'mamba'}, {'id': 2407, 'synset': 'black_mamba.n.01', 'name': 'black_mamba'}, {'id': 2408, 'synset': 'green_mamba.n.01', 'name': 'green_mamba'}, {'id': 2409, 'synset': 'death_adder.n.01', 'name': 'death_adder'}, {'id': 2410, 'synset': 'tiger_snake.n.01', 'name': 'tiger_snake'}, {'id': 2411, 'synset': 'australian_blacksnake.n.01', 'name': 'Australian_blacksnake'}, {'id': 2412, 'synset': 'krait.n.01', 'name': 'krait'}, {'id': 2413, 'synset': 'banded_krait.n.01', 'name': 'banded_krait'}, {'id': 2414, 'synset': 'taipan.n.01', 'name': 'taipan'}, {'id': 2415, 'synset': 'sea_snake.n.01', 'name': 'sea_snake'}, {'id': 2416, 'synset': 'viper.n.01', 'name': 'viper'}, {'id': 2417, 'synset': 'adder.n.03', 'name': 'adder'}, {'id': 2418, 'synset': 'asp.n.01', 'name': 'asp'}, {'id': 2419, 'synset': 'puff_adder.n.01', 'name': 'puff_adder'}, {'id': 2420, 'synset': 'gaboon_viper.n.01', 'name': 'gaboon_viper'}, {'id': 2421, 'synset': 'horned_viper.n.01', 'name': 'horned_viper'}, {'id': 2422, 'synset': 'pit_viper.n.01', 'name': 'pit_viper'}, {'id': 2423, 'synset': 'copperhead.n.01', 'name': 'copperhead'}, {'id': 2424, 'synset': 'water_moccasin.n.01', 'name': 'water_moccasin'}, {'id': 2425, 'synset': 'rattlesnake.n.01', 'name': 'rattlesnake'}, {'id': 2426, 'synset': 'diamondback.n.01', 'name': 'diamondback'}, {'id': 2427, 'synset': 'timber_rattlesnake.n.01', 'name': 'timber_rattlesnake'}, {'id': 2428, 'synset': 'canebrake_rattlesnake.n.01', 'name': 'canebrake_rattlesnake'}, {'id': 2429, 'synset': 'prairie_rattlesnake.n.01', 'name': 'prairie_rattlesnake'}, {'id': 2430, 'synset': 'sidewinder.n.01', 'name': 'sidewinder'}, {'id': 2431, 'synset': 'western_diamondback.n.01', 'name': 'Western_diamondback'}, {'id': 2432, 'synset': 'rock_rattlesnake.n.01', 'name': 'rock_rattlesnake'}, {'id': 2433, 'synset': 'tiger_rattlesnake.n.01', 'name': 'tiger_rattlesnake'}, {'id': 2434, 'synset': 'mojave_rattlesnake.n.01', 'name': 'Mojave_rattlesnake'}, {'id': 2435, 'synset': 'speckled_rattlesnake.n.01', 'name': 'speckled_rattlesnake'}, {'id': 2436, 'synset': 'massasauga.n.02', 'name': 'massasauga'}, {'id': 2437, 'synset': 'ground_rattler.n.01', 'name': 'ground_rattler'}, {'id': 2438, 'synset': 'fer-de-lance.n.01', 'name': 'fer-de-lance'}, {'id': 2439, 'synset': 'carcase.n.01', 'name': 'carcase'}, {'id': 2440, 'synset': 'carrion.n.01', 'name': 'carrion'}, {'id': 2441, 'synset': 'arthropod.n.01', 'name': 'arthropod'}, {'id': 2442, 'synset': 'trilobite.n.01', 'name': 'trilobite'}, {'id': 2443, 'synset': 'arachnid.n.01', 'name': 'arachnid'}, {'id': 2444, 'synset': 'harvestman.n.01', 'name': 'harvestman'}, {'id': 2445, 'synset': 'scorpion.n.03', 'name': 'scorpion'}, {'id': 2446, 'synset': 'false_scorpion.n.01', 'name': 'false_scorpion'}, {'id': 2447, 'synset': 'book_scorpion.n.01', 'name': 'book_scorpion'}, {'id': 2448, 'synset': 'whip-scorpion.n.01', 'name': 'whip-scorpion'}, {'id': 2449, 'synset': 'vinegarroon.n.01', 'name': 'vinegarroon'}, {'id': 2450, 'synset': 'orb-weaving_spider.n.01', 'name': 'orb-weaving_spider'}, {'id': 2451, 'synset': 'black_and_gold_garden_spider.n.01', 'name': 'black_and_gold_garden_spider'}, {'id': 2452, 'synset': 'barn_spider.n.01', 'name': 'barn_spider'}, {'id': 2453, 'synset': 'garden_spider.n.01', 'name': 'garden_spider'}, {'id': 2454, 'synset': 'comb-footed_spider.n.01', 'name': 'comb-footed_spider'}, {'id': 2455, 'synset': 'black_widow.n.01', 'name': 'black_widow'}, {'id': 2456, 'synset': 'tarantula.n.02', 'name': 'tarantula'}, {'id': 2457, 'synset': 'wolf_spider.n.01', 'name': 'wolf_spider'}, {'id': 2458, 'synset': 'european_wolf_spider.n.01', 'name': 'European_wolf_spider'}, {'id': 2459, 'synset': 'trap-door_spider.n.01', 'name': 'trap-door_spider'}, {'id': 2460, 'synset': 'acarine.n.01', 'name': 'acarine'}, {'id': 2461, 'synset': 'tick.n.02', 'name': 'tick'}, {'id': 2462, 'synset': 'hard_tick.n.01', 'name': 'hard_tick'}, {'id': 2463, 'synset': 'ixodes_dammini.n.01', 'name': 'Ixodes_dammini'}, {'id': 2464, 'synset': 'ixodes_neotomae.n.01', 'name': 'Ixodes_neotomae'}, {'id': 2465, 'synset': 'ixodes_pacificus.n.01', 'name': 'Ixodes_pacificus'}, {'id': 2466, 'synset': 'ixodes_scapularis.n.01', 'name': 'Ixodes_scapularis'}, {'id': 2467, 'synset': 'sheep-tick.n.02', 'name': 'sheep-tick'}, {'id': 2468, 'synset': 'ixodes_persulcatus.n.01', 'name': 'Ixodes_persulcatus'}, {'id': 2469, 'synset': 'ixodes_dentatus.n.01', 'name': 'Ixodes_dentatus'}, {'id': 2470, 'synset': 'ixodes_spinipalpis.n.01', 'name': 'Ixodes_spinipalpis'}, {'id': 2471, 'synset': 'wood_tick.n.01', 'name': 'wood_tick'}, {'id': 2472, 'synset': 'soft_tick.n.01', 'name': 'soft_tick'}, {'id': 2473, 'synset': 'mite.n.02', 'name': 'mite'}, {'id': 2474, 'synset': 'web-spinning_mite.n.01', 'name': 'web-spinning_mite'}, {'id': 2475, 'synset': 'acarid.n.01', 'name': 'acarid'}, {'id': 2476, 'synset': 'trombidiid.n.01', 'name': 'trombidiid'}, {'id': 2477, 'synset': 'trombiculid.n.01', 'name': 'trombiculid'}, {'id': 2478, 'synset': 'harvest_mite.n.01', 'name': 'harvest_mite'}, {'id': 2479, 'synset': 'acarus.n.01', 'name': 'acarus'}, {'id': 2480, 'synset': 'itch_mite.n.01', 'name': 'itch_mite'}, {'id': 2481, 'synset': 'rust_mite.n.01', 'name': 'rust_mite'}, {'id': 2482, 'synset': 'spider_mite.n.01', 'name': 'spider_mite'}, {'id': 2483, 'synset': 'red_spider.n.01', 'name': 'red_spider'}, {'id': 2484, 'synset': 'myriapod.n.01', 'name': 'myriapod'}, {'id': 2485, 'synset': 'garden_centipede.n.01', 'name': 'garden_centipede'}, {'id': 2486, 'synset': 'tardigrade.n.01', 'name': 'tardigrade'}, {'id': 2487, 'synset': 'centipede.n.01', 'name': 'centipede'}, {'id': 2488, 'synset': 'house_centipede.n.01', 'name': 'house_centipede'}, {'id': 2489, 'synset': 'millipede.n.01', 'name': 'millipede'}, {'id': 2490, 'synset': 'sea_spider.n.01', 'name': 'sea_spider'}, {'id': 2491, 'synset': 'merostomata.n.01', 'name': 'Merostomata'}, {'id': 2492, 'synset': 'horseshoe_crab.n.01', 'name': 'horseshoe_crab'}, {'id': 2493, 'synset': 'asian_horseshoe_crab.n.01', 'name': 'Asian_horseshoe_crab'}, {'id': 2494, 'synset': 'eurypterid.n.01', 'name': 'eurypterid'}, {'id': 2495, 'synset': 'tongue_worm.n.01', 'name': 'tongue_worm'}, {'id': 2496, 'synset': 'gallinaceous_bird.n.01', 'name': 'gallinaceous_bird'}, {'id': 2497, 'synset': 'domestic_fowl.n.01', 'name': 'domestic_fowl'}, {'id': 2498, 'synset': 'dorking.n.01', 'name': 'Dorking'}, {'id': 2499, 'synset': 'plymouth_rock.n.02', 'name': 'Plymouth_Rock'}, {'id': 2500, 'synset': 'cornish.n.02', 'name': 'Cornish'}, {'id': 2501, 'synset': 'rock_cornish.n.01', 'name': 'Rock_Cornish'}, {'id': 2502, 'synset': 'game_fowl.n.01', 'name': 'game_fowl'}, {'id': 2503, 'synset': 'cochin.n.01', 'name': 'cochin'}, {'id': 2504, 'synset': 'jungle_fowl.n.01', 'name': 'jungle_fowl'}, {'id': 2505, 'synset': 'jungle_cock.n.01', 'name': 'jungle_cock'}, {'id': 2506, 'synset': 'jungle_hen.n.01', 'name': 'jungle_hen'}, {'id': 2507, 'synset': 'red_jungle_fowl.n.01', 'name': 'red_jungle_fowl'}, {'id': 2508, 'synset': 'bantam.n.01', 'name': 'bantam'}, {'id': 2509, 'synset': 'chick.n.01', 'name': 'chick'}, {'id': 2510, 'synset': 'cockerel.n.01', 'name': 'cockerel'}, {'id': 2511, 'synset': 'capon.n.02', 'name': 'capon'}, {'id': 2512, 'synset': 'hen.n.01', 'name': 'hen'}, {'id': 2513, 'synset': 'cackler.n.01', 'name': 'cackler'}, {'id': 2514, 'synset': 'brood_hen.n.01', 'name': 'brood_hen'}, {'id': 2515, 'synset': 'mother_hen.n.02', 'name': 'mother_hen'}, {'id': 2516, 'synset': 'layer.n.04', 'name': 'layer'}, {'id': 2517, 'synset': 'pullet.n.02', 'name': 'pullet'}, {'id': 2518, 'synset': 'spring_chicken.n.02', 'name': 'spring_chicken'}, {'id': 2519, 'synset': 'rhode_island_red.n.01', 'name': 'Rhode_Island_red'}, {'id': 2520, 'synset': 'dominique.n.01', 'name': 'Dominique'}, {'id': 2521, 'synset': 'orpington.n.01', 'name': 'Orpington'}, {'id': 2522, 'synset': 'turkey.n.01', 'name': 'turkey'}, {'id': 2523, 'synset': 'turkey_cock.n.01', 'name': 'turkey_cock'}, {'id': 2524, 'synset': 'ocellated_turkey.n.01', 'name': 'ocellated_turkey'}, {'id': 2525, 'synset': 'grouse.n.02', 'name': 'grouse'}, {'id': 2526, 'synset': 'black_grouse.n.01', 'name': 'black_grouse'}, {'id': 2527, 'synset': 'european_black_grouse.n.01', 'name': 'European_black_grouse'}, {'id': 2528, 'synset': 'asian_black_grouse.n.01', 'name': 'Asian_black_grouse'}, {'id': 2529, 'synset': 'blackcock.n.01', 'name': 'blackcock'}, {'id': 2530, 'synset': 'greyhen.n.01', 'name': 'greyhen'}, {'id': 2531, 'synset': 'ptarmigan.n.01', 'name': 'ptarmigan'}, {'id': 2532, 'synset': 'red_grouse.n.01', 'name': 'red_grouse'}, {'id': 2533, 'synset': 'moorhen.n.02', 'name': 'moorhen'}, {'id': 2534, 'synset': 'capercaillie.n.01', 'name': 'capercaillie'}, {'id': 2535, 'synset': 'spruce_grouse.n.01', 'name': 'spruce_grouse'}, {'id': 2536, 'synset': 'sage_grouse.n.01', 'name': 'sage_grouse'}, {'id': 2537, 'synset': 'ruffed_grouse.n.01', 'name': 'ruffed_grouse'}, {'id': 2538, 'synset': 'sharp-tailed_grouse.n.01', 'name': 'sharp-tailed_grouse'}, {'id': 2539, 'synset': 'prairie_chicken.n.01', 'name': 'prairie_chicken'}, {'id': 2540, 'synset': 'greater_prairie_chicken.n.01', 'name': 'greater_prairie_chicken'}, {'id': 2541, 'synset': 'lesser_prairie_chicken.n.01', 'name': 'lesser_prairie_chicken'}, {'id': 2542, 'synset': 'heath_hen.n.01', 'name': 'heath_hen'}, {'id': 2543, 'synset': 'guan.n.01', 'name': 'guan'}, {'id': 2544, 'synset': 'curassow.n.01', 'name': 'curassow'}, {'id': 2545, 'synset': 'piping_guan.n.01', 'name': 'piping_guan'}, {'id': 2546, 'synset': 'chachalaca.n.01', 'name': 'chachalaca'}, {'id': 2547, 'synset': 'texas_chachalaca.n.01', 'name': 'Texas_chachalaca'}, {'id': 2548, 'synset': 'megapode.n.01', 'name': 'megapode'}, {'id': 2549, 'synset': 'mallee_fowl.n.01', 'name': 'mallee_fowl'}, {'id': 2550, 'synset': 'mallee_hen.n.01', 'name': 'mallee_hen'}, {'id': 2551, 'synset': 'brush_turkey.n.01', 'name': 'brush_turkey'}, {'id': 2552, 'synset': 'maleo.n.01', 'name': 'maleo'}, {'id': 2553, 'synset': 'phasianid.n.01', 'name': 'phasianid'}, {'id': 2554, 'synset': 'pheasant.n.01', 'name': 'pheasant'}, {'id': 2555, 'synset': 'ring-necked_pheasant.n.01', 'name': 'ring-necked_pheasant'}, {'id': 2556, 'synset': 'afropavo.n.01', 'name': 'afropavo'}, {'id': 2557, 'synset': 'argus.n.02', 'name': 'argus'}, {'id': 2558, 'synset': 'golden_pheasant.n.01', 'name': 'golden_pheasant'}, {'id': 2559, 'synset': 'bobwhite.n.01', 'name': 'bobwhite'}, {'id': 2560, 'synset': 'northern_bobwhite.n.01', 'name': 'northern_bobwhite'}, {'id': 2561, 'synset': 'old_world_quail.n.01', 'name': 'Old_World_quail'}, {'id': 2562, 'synset': 'migratory_quail.n.01', 'name': 'migratory_quail'}, {'id': 2563, 'synset': 'monal.n.01', 'name': 'monal'}, {'id': 2564, 'synset': 'peafowl.n.01', 'name': 'peafowl'}, {'id': 2565, 'synset': 'peachick.n.01', 'name': 'peachick'}, {'id': 2566, 'synset': 'peacock.n.02', 'name': 'peacock'}, {'id': 2567, 'synset': 'peahen.n.01', 'name': 'peahen'}, {'id': 2568, 'synset': 'blue_peafowl.n.01', 'name': 'blue_peafowl'}, {'id': 2569, 'synset': 'green_peafowl.n.01', 'name': 'green_peafowl'}, {'id': 2570, 'synset': 'quail.n.02', 'name': 'quail'}, {'id': 2571, 'synset': 'california_quail.n.01', 'name': 'California_quail'}, {'id': 2572, 'synset': 'tragopan.n.01', 'name': 'tragopan'}, {'id': 2573, 'synset': 'partridge.n.03', 'name': 'partridge'}, {'id': 2574, 'synset': 'hungarian_partridge.n.01', 'name': 'Hungarian_partridge'}, {'id': 2575, 'synset': 'red-legged_partridge.n.01', 'name': 'red-legged_partridge'}, {'id': 2576, 'synset': 'greek_partridge.n.01', 'name': 'Greek_partridge'}, {'id': 2577, 'synset': 'mountain_quail.n.01', 'name': 'mountain_quail'}, {'id': 2578, 'synset': 'guinea_fowl.n.01', 'name': 'guinea_fowl'}, {'id': 2579, 'synset': 'guinea_hen.n.02', 'name': 'guinea_hen'}, {'id': 2580, 'synset': 'hoatzin.n.01', 'name': 'hoatzin'}, {'id': 2581, 'synset': 'tinamou.n.01', 'name': 'tinamou'}, {'id': 2582, 'synset': 'columbiform_bird.n.01', 'name': 'columbiform_bird'}, {'id': 2583, 'synset': 'dodo.n.02', 'name': 'dodo'}, {'id': 2584, 'synset': 'pouter_pigeon.n.01', 'name': 'pouter_pigeon'}, {'id': 2585, 'synset': 'rock_dove.n.01', 'name': 'rock_dove'}, {'id': 2586, 'synset': 'band-tailed_pigeon.n.01', 'name': 'band-tailed_pigeon'}, {'id': 2587, 'synset': 'wood_pigeon.n.01', 'name': 'wood_pigeon'}, {'id': 2588, 'synset': 'turtledove.n.02', 'name': 'turtledove'}, {'id': 2589, 'synset': 'streptopelia_turtur.n.01', 'name': 'Streptopelia_turtur'}, {'id': 2590, 'synset': 'ringdove.n.01', 'name': 'ringdove'}, {'id': 2591, 'synset': 'australian_turtledove.n.01', 'name': 'Australian_turtledove'}, {'id': 2592, 'synset': 'mourning_dove.n.01', 'name': 'mourning_dove'}, {'id': 2593, 'synset': 'domestic_pigeon.n.01', 'name': 'domestic_pigeon'}, {'id': 2594, 'synset': 'squab.n.03', 'name': 'squab'}, {'id': 2595, 'synset': 'fairy_swallow.n.01', 'name': 'fairy_swallow'}, {'id': 2596, 'synset': 'roller.n.07', 'name': 'roller'}, {'id': 2597, 'synset': 'homing_pigeon.n.01', 'name': 'homing_pigeon'}, {'id': 2598, 'synset': 'carrier_pigeon.n.01', 'name': 'carrier_pigeon'}, {'id': 2599, 'synset': 'passenger_pigeon.n.01', 'name': 'passenger_pigeon'}, {'id': 2600, 'synset': 'sandgrouse.n.01', 'name': 'sandgrouse'}, {'id': 2601, 'synset': 'painted_sandgrouse.n.01', 'name': 'painted_sandgrouse'}, {'id': 2602, 'synset': 'pin-tailed_sandgrouse.n.01', 'name': 'pin-tailed_sandgrouse'}, {'id': 2603, 'synset': "pallas's_sandgrouse.n.01", 'name': "pallas's_sandgrouse"}, {'id': 2604, 'synset': 'popinjay.n.02', 'name': 'popinjay'}, {'id': 2605, 'synset': 'poll.n.04', 'name': 'poll'}, {'id': 2606, 'synset': 'african_grey.n.01', 'name': 'African_grey'}, {'id': 2607, 'synset': 'amazon.n.04', 'name': 'amazon'}, {'id': 2608, 'synset': 'macaw.n.01', 'name': 'macaw'}, {'id': 2609, 'synset': 'kea.n.01', 'name': 'kea'}, {'id': 2610, 'synset': 'cockatoo.n.01', 'name': 'cockatoo'}, {'id': 2611, 'synset': 'sulphur-crested_cockatoo.n.01', 'name': 'sulphur-crested_cockatoo'}, {'id': 2612, 'synset': 'pink_cockatoo.n.01', 'name': 'pink_cockatoo'}, {'id': 2613, 'synset': 'cockateel.n.01', 'name': 'cockateel'}, {'id': 2614, 'synset': 'lovebird.n.02', 'name': 'lovebird'}, {'id': 2615, 'synset': 'lory.n.01', 'name': 'lory'}, {'id': 2616, 'synset': 'lorikeet.n.01', 'name': 'lorikeet'}, {'id': 2617, 'synset': 'varied_lorikeet.n.01', 'name': 'varied_Lorikeet'}, {'id': 2618, 'synset': 'rainbow_lorikeet.n.01', 'name': 'rainbow_lorikeet'}, {'id': 2619, 'synset': 'carolina_parakeet.n.01', 'name': 'Carolina_parakeet'}, {'id': 2620, 'synset': 'budgerigar.n.01', 'name': 'budgerigar'}, {'id': 2621, 'synset': 'ring-necked_parakeet.n.01', 'name': 'ring-necked_parakeet'}, {'id': 2622, 'synset': 'cuculiform_bird.n.01', 'name': 'cuculiform_bird'}, {'id': 2623, 'synset': 'cuckoo.n.02', 'name': 'cuckoo'}, {'id': 2624, 'synset': 'european_cuckoo.n.01', 'name': 'European_cuckoo'}, {'id': 2625, 'synset': 'black-billed_cuckoo.n.01', 'name': 'black-billed_cuckoo'}, {'id': 2626, 'synset': 'roadrunner.n.01', 'name': 'roadrunner'}, {'id': 2627, 'synset': 'ani.n.01', 'name': 'ani'}, {'id': 2628, 'synset': 'coucal.n.01', 'name': 'coucal'}, {'id': 2629, 'synset': 'crow_pheasant.n.01', 'name': 'crow_pheasant'}, {'id': 2630, 'synset': 'touraco.n.01', 'name': 'touraco'}, {'id': 2631, 'synset': 'coraciiform_bird.n.01', 'name': 'coraciiform_bird'}, {'id': 2632, 'synset': 'roller.n.06', 'name': 'roller'}, {'id': 2633, 'synset': 'european_roller.n.01', 'name': 'European_roller'}, {'id': 2634, 'synset': 'ground_roller.n.01', 'name': 'ground_roller'}, {'id': 2635, 'synset': 'kingfisher.n.01', 'name': 'kingfisher'}, {'id': 2636, 'synset': 'eurasian_kingfisher.n.01', 'name': 'Eurasian_kingfisher'}, {'id': 2637, 'synset': 'belted_kingfisher.n.01', 'name': 'belted_kingfisher'}, {'id': 2638, 'synset': 'kookaburra.n.01', 'name': 'kookaburra'}, {'id': 2639, 'synset': 'bee_eater.n.01', 'name': 'bee_eater'}, {'id': 2640, 'synset': 'hornbill.n.01', 'name': 'hornbill'}, {'id': 2641, 'synset': 'hoopoe.n.01', 'name': 'hoopoe'}, {'id': 2642, 'synset': 'euopean_hoopoe.n.01', 'name': 'Euopean_hoopoe'}, {'id': 2643, 'synset': 'wood_hoopoe.n.01', 'name': 'wood_hoopoe'}, {'id': 2644, 'synset': 'motmot.n.01', 'name': 'motmot'}, {'id': 2645, 'synset': 'tody.n.01', 'name': 'tody'}, {'id': 2646, 'synset': 'apodiform_bird.n.01', 'name': 'apodiform_bird'}, {'id': 2647, 'synset': 'swift.n.03', 'name': 'swift'}, {'id': 2648, 'synset': 'european_swift.n.01', 'name': 'European_swift'}, {'id': 2649, 'synset': 'chimney_swift.n.01', 'name': 'chimney_swift'}, {'id': 2650, 'synset': 'swiftlet.n.01', 'name': 'swiftlet'}, {'id': 2651, 'synset': 'tree_swift.n.01', 'name': 'tree_swift'}, {'id': 2652, 'synset': 'archilochus_colubris.n.01', 'name': 'Archilochus_colubris'}, {'id': 2653, 'synset': 'thornbill.n.01', 'name': 'thornbill'}, {'id': 2654, 'synset': 'goatsucker.n.01', 'name': 'goatsucker'}, {'id': 2655, 'synset': 'european_goatsucker.n.01', 'name': 'European_goatsucker'}, {'id': 2656, 'synset': "chuck-will's-widow.n.01", 'name': "chuck-will's-widow"}, {'id': 2657, 'synset': 'whippoorwill.n.01', 'name': 'whippoorwill'}, {'id': 2658, 'synset': 'poorwill.n.01', 'name': 'poorwill'}, {'id': 2659, 'synset': 'frogmouth.n.01', 'name': 'frogmouth'}, {'id': 2660, 'synset': 'oilbird.n.01', 'name': 'oilbird'}, {'id': 2661, 'synset': 'piciform_bird.n.01', 'name': 'piciform_bird'}, {'id': 2662, 'synset': 'woodpecker.n.01', 'name': 'woodpecker'}, {'id': 2663, 'synset': 'green_woodpecker.n.01', 'name': 'green_woodpecker'}, {'id': 2664, 'synset': 'downy_woodpecker.n.01', 'name': 'downy_woodpecker'}, {'id': 2665, 'synset': 'flicker.n.02', 'name': 'flicker'}, {'id': 2666, 'synset': 'yellow-shafted_flicker.n.01', 'name': 'yellow-shafted_flicker'}, {'id': 2667, 'synset': 'gilded_flicker.n.01', 'name': 'gilded_flicker'}, {'id': 2668, 'synset': 'red-shafted_flicker.n.01', 'name': 'red-shafted_flicker'}, {'id': 2669, 'synset': 'ivorybill.n.01', 'name': 'ivorybill'}, {'id': 2670, 'synset': 'redheaded_woodpecker.n.01', 'name': 'redheaded_woodpecker'}, {'id': 2671, 'synset': 'sapsucker.n.01', 'name': 'sapsucker'}, {'id': 2672, 'synset': 'yellow-bellied_sapsucker.n.01', 'name': 'yellow-bellied_sapsucker'}, {'id': 2673, 'synset': 'red-breasted_sapsucker.n.01', 'name': 'red-breasted_sapsucker'}, {'id': 2674, 'synset': 'wryneck.n.02', 'name': 'wryneck'}, {'id': 2675, 'synset': 'piculet.n.01', 'name': 'piculet'}, {'id': 2676, 'synset': 'barbet.n.01', 'name': 'barbet'}, {'id': 2677, 'synset': 'puffbird.n.01', 'name': 'puffbird'}, {'id': 2678, 'synset': 'honey_guide.n.01', 'name': 'honey_guide'}, {'id': 2679, 'synset': 'jacamar.n.01', 'name': 'jacamar'}, {'id': 2680, 'synset': 'toucan.n.01', 'name': 'toucan'}, {'id': 2681, 'synset': 'toucanet.n.01', 'name': 'toucanet'}, {'id': 2682, 'synset': 'trogon.n.01', 'name': 'trogon'}, {'id': 2683, 'synset': 'quetzal.n.02', 'name': 'quetzal'}, {'id': 2684, 'synset': 'resplendent_quetzel.n.01', 'name': 'resplendent_quetzel'}, {'id': 2685, 'synset': 'aquatic_bird.n.01', 'name': 'aquatic_bird'}, {'id': 2686, 'synset': 'waterfowl.n.01', 'name': 'waterfowl'}, {'id': 2687, 'synset': 'anseriform_bird.n.01', 'name': 'anseriform_bird'}, {'id': 2688, 'synset': 'drake.n.02', 'name': 'drake'}, {'id': 2689, 'synset': 'quack-quack.n.01', 'name': 'quack-quack'}, {'id': 2690, 'synset': 'diving_duck.n.01', 'name': 'diving_duck'}, {'id': 2691, 'synset': 'dabbling_duck.n.01', 'name': 'dabbling_duck'}, {'id': 2692, 'synset': 'black_duck.n.01', 'name': 'black_duck'}, {'id': 2693, 'synset': 'teal.n.02', 'name': 'teal'}, {'id': 2694, 'synset': 'greenwing.n.01', 'name': 'greenwing'}, {'id': 2695, 'synset': 'bluewing.n.01', 'name': 'bluewing'}, {'id': 2696, 'synset': 'garganey.n.01', 'name': 'garganey'}, {'id': 2697, 'synset': 'widgeon.n.01', 'name': 'widgeon'}, {'id': 2698, 'synset': 'american_widgeon.n.01', 'name': 'American_widgeon'}, {'id': 2699, 'synset': 'shoveler.n.02', 'name': 'shoveler'}, {'id': 2700, 'synset': 'pintail.n.01', 'name': 'pintail'}, {'id': 2701, 'synset': 'sheldrake.n.02', 'name': 'sheldrake'}, {'id': 2702, 'synset': 'shelduck.n.01', 'name': 'shelduck'}, {'id': 2703, 'synset': 'ruddy_duck.n.01', 'name': 'ruddy_duck'}, {'id': 2704, 'synset': 'bufflehead.n.01', 'name': 'bufflehead'}, {'id': 2705, 'synset': 'goldeneye.n.02', 'name': 'goldeneye'}, {'id': 2706, 'synset': "barrow's_goldeneye.n.01", 'name': "Barrow's_goldeneye"}, {'id': 2707, 'synset': 'canvasback.n.01', 'name': 'canvasback'}, {'id': 2708, 'synset': 'pochard.n.01', 'name': 'pochard'}, {'id': 2709, 'synset': 'redhead.n.02', 'name': 'redhead'}, {'id': 2710, 'synset': 'scaup.n.01', 'name': 'scaup'}, {'id': 2711, 'synset': 'greater_scaup.n.01', 'name': 'greater_scaup'}, {'id': 2712, 'synset': 'lesser_scaup.n.01', 'name': 'lesser_scaup'}, {'id': 2713, 'synset': 'wild_duck.n.01', 'name': 'wild_duck'}, {'id': 2714, 'synset': 'wood_duck.n.01', 'name': 'wood_duck'}, {'id': 2715, 'synset': 'wood_drake.n.01', 'name': 'wood_drake'}, {'id': 2716, 'synset': 'mandarin_duck.n.01', 'name': 'mandarin_duck'}, {'id': 2717, 'synset': 'muscovy_duck.n.01', 'name': 'muscovy_duck'}, {'id': 2718, 'synset': 'sea_duck.n.01', 'name': 'sea_duck'}, {'id': 2719, 'synset': 'eider.n.01', 'name': 'eider'}, {'id': 2720, 'synset': 'scoter.n.01', 'name': 'scoter'}, {'id': 2721, 'synset': 'common_scoter.n.01', 'name': 'common_scoter'}, {'id': 2722, 'synset': 'old_squaw.n.01', 'name': 'old_squaw'}, {'id': 2723, 'synset': 'merganser.n.01', 'name': 'merganser'}, {'id': 2724, 'synset': 'goosander.n.01', 'name': 'goosander'}, {'id': 2725, 'synset': 'american_merganser.n.01', 'name': 'American_merganser'}, {'id': 2726, 'synset': 'red-breasted_merganser.n.01', 'name': 'red-breasted_merganser'}, {'id': 2727, 'synset': 'smew.n.01', 'name': 'smew'}, {'id': 2728, 'synset': 'hooded_merganser.n.01', 'name': 'hooded_merganser'}, {'id': 2729, 'synset': 'gosling.n.01', 'name': 'gosling'}, {'id': 2730, 'synset': 'gander.n.01', 'name': 'gander'}, {'id': 2731, 'synset': 'chinese_goose.n.01', 'name': 'Chinese_goose'}, {'id': 2732, 'synset': 'greylag.n.01', 'name': 'greylag'}, {'id': 2733, 'synset': 'blue_goose.n.01', 'name': 'blue_goose'}, {'id': 2734, 'synset': 'snow_goose.n.01', 'name': 'snow_goose'}, {'id': 2735, 'synset': 'brant.n.01', 'name': 'brant'}, {'id': 2736, 'synset': 'common_brant_goose.n.01', 'name': 'common_brant_goose'}, {'id': 2737, 'synset': 'honker.n.03', 'name': 'honker'}, {'id': 2738, 'synset': 'barnacle_goose.n.01', 'name': 'barnacle_goose'}, {'id': 2739, 'synset': 'coscoroba.n.01', 'name': 'coscoroba'}, {'id': 2740, 'synset': 'swan.n.01', 'name': 'swan'}, {'id': 2741, 'synset': 'cob.n.04', 'name': 'cob'}, {'id': 2742, 'synset': 'pen.n.05', 'name': 'pen'}, {'id': 2743, 'synset': 'cygnet.n.01', 'name': 'cygnet'}, {'id': 2744, 'synset': 'mute_swan.n.01', 'name': 'mute_swan'}, {'id': 2745, 'synset': 'whooper.n.02', 'name': 'whooper'}, {'id': 2746, 'synset': 'tundra_swan.n.01', 'name': 'tundra_swan'}, {'id': 2747, 'synset': 'whistling_swan.n.01', 'name': 'whistling_swan'}, {'id': 2748, 'synset': "bewick's_swan.n.01", 'name': "Bewick's_swan"}, {'id': 2749, 'synset': 'trumpeter.n.04', 'name': 'trumpeter'}, {'id': 2750, 'synset': 'black_swan.n.01', 'name': 'black_swan'}, {'id': 2751, 'synset': 'screamer.n.03', 'name': 'screamer'}, {'id': 2752, 'synset': 'horned_screamer.n.01', 'name': 'horned_screamer'}, {'id': 2753, 'synset': 'crested_screamer.n.01', 'name': 'crested_screamer'}, {'id': 2754, 'synset': 'chaja.n.01', 'name': 'chaja'}, {'id': 2755, 'synset': 'mammal.n.01', 'name': 'mammal'}, {'id': 2756, 'synset': 'female_mammal.n.01', 'name': 'female_mammal'}, {'id': 2757, 'synset': 'tusker.n.01', 'name': 'tusker'}, {'id': 2758, 'synset': 'prototherian.n.01', 'name': 'prototherian'}, {'id': 2759, 'synset': 'monotreme.n.01', 'name': 'monotreme'}, {'id': 2760, 'synset': 'echidna.n.02', 'name': 'echidna'}, {'id': 2761, 'synset': 'echidna.n.01', 'name': 'echidna'}, {'id': 2762, 'synset': 'platypus.n.01', 'name': 'platypus'}, {'id': 2763, 'synset': 'marsupial.n.01', 'name': 'marsupial'}, {'id': 2764, 'synset': 'opossum.n.02', 'name': 'opossum'}, {'id': 2765, 'synset': 'common_opossum.n.01', 'name': 'common_opossum'}, {'id': 2766, 'synset': 'crab-eating_opossum.n.01', 'name': 'crab-eating_opossum'}, {'id': 2767, 'synset': 'opossum_rat.n.01', 'name': 'opossum_rat'}, {'id': 2768, 'synset': 'bandicoot.n.01', 'name': 'bandicoot'}, {'id': 2769, 'synset': 'rabbit-eared_bandicoot.n.01', 'name': 'rabbit-eared_bandicoot'}, {'id': 2770, 'synset': 'kangaroo.n.01', 'name': 'kangaroo'}, {'id': 2771, 'synset': 'giant_kangaroo.n.01', 'name': 'giant_kangaroo'}, {'id': 2772, 'synset': 'wallaby.n.01', 'name': 'wallaby'}, {'id': 2773, 'synset': 'common_wallaby.n.01', 'name': 'common_wallaby'}, {'id': 2774, 'synset': 'hare_wallaby.n.01', 'name': 'hare_wallaby'}, {'id': 2775, 'synset': 'nail-tailed_wallaby.n.01', 'name': 'nail-tailed_wallaby'}, {'id': 2776, 'synset': 'rock_wallaby.n.01', 'name': 'rock_wallaby'}, {'id': 2777, 'synset': 'pademelon.n.01', 'name': 'pademelon'}, {'id': 2778, 'synset': 'tree_wallaby.n.01', 'name': 'tree_wallaby'}, {'id': 2779, 'synset': 'musk_kangaroo.n.01', 'name': 'musk_kangaroo'}, {'id': 2780, 'synset': 'rat_kangaroo.n.01', 'name': 'rat_kangaroo'}, {'id': 2781, 'synset': 'potoroo.n.01', 'name': 'potoroo'}, {'id': 2782, 'synset': 'bettong.n.01', 'name': 'bettong'}, {'id': 2783, 'synset': 'jerboa_kangaroo.n.01', 'name': 'jerboa_kangaroo'}, {'id': 2784, 'synset': 'phalanger.n.01', 'name': 'phalanger'}, {'id': 2785, 'synset': 'cuscus.n.01', 'name': 'cuscus'}, {'id': 2786, 'synset': 'brush-tailed_phalanger.n.01', 'name': 'brush-tailed_phalanger'}, {'id': 2787, 'synset': 'flying_phalanger.n.01', 'name': 'flying_phalanger'}, {'id': 2788, 'synset': 'wombat.n.01', 'name': 'wombat'}, {'id': 2789, 'synset': 'dasyurid_marsupial.n.01', 'name': 'dasyurid_marsupial'}, {'id': 2790, 'synset': 'dasyure.n.01', 'name': 'dasyure'}, {'id': 2791, 'synset': 'eastern_dasyure.n.01', 'name': 'eastern_dasyure'}, {'id': 2792, 'synset': 'native_cat.n.01', 'name': 'native_cat'}, {'id': 2793, 'synset': 'thylacine.n.01', 'name': 'thylacine'}, {'id': 2794, 'synset': 'tasmanian_devil.n.01', 'name': 'Tasmanian_devil'}, {'id': 2795, 'synset': 'pouched_mouse.n.01', 'name': 'pouched_mouse'}, {'id': 2796, 'synset': 'numbat.n.01', 'name': 'numbat'}, {'id': 2797, 'synset': 'pouched_mole.n.01', 'name': 'pouched_mole'}, {'id': 2798, 'synset': 'placental.n.01', 'name': 'placental'}, {'id': 2799, 'synset': 'livestock.n.01', 'name': 'livestock'}, {'id': 2800, 'synset': 'cow.n.02', 'name': 'cow'}, {'id': 2801, 'synset': 'calf.n.04', 'name': 'calf'}, {'id': 2802, 'synset': 'yearling.n.03', 'name': 'yearling'}, {'id': 2803, 'synset': 'buck.n.05', 'name': 'buck'}, {'id': 2804, 'synset': 'doe.n.02', 'name': 'doe'}, {'id': 2805, 'synset': 'insectivore.n.01', 'name': 'insectivore'}, {'id': 2806, 'synset': 'mole.n.06', 'name': 'mole'}, {'id': 2807, 'synset': 'starnose_mole.n.01', 'name': 'starnose_mole'}, {'id': 2808, 'synset': "brewer's_mole.n.01", 'name': "brewer's_mole"}, {'id': 2809, 'synset': 'golden_mole.n.01', 'name': 'golden_mole'}, {'id': 2810, 'synset': 'shrew_mole.n.01', 'name': 'shrew_mole'}, {'id': 2811, 'synset': 'asiatic_shrew_mole.n.01', 'name': 'Asiatic_shrew_mole'}, {'id': 2812, 'synset': 'american_shrew_mole.n.01', 'name': 'American_shrew_mole'}, {'id': 2813, 'synset': 'shrew.n.02', 'name': 'shrew'}, {'id': 2814, 'synset': 'common_shrew.n.01', 'name': 'common_shrew'}, {'id': 2815, 'synset': 'masked_shrew.n.01', 'name': 'masked_shrew'}, {'id': 2816, 'synset': 'short-tailed_shrew.n.01', 'name': 'short-tailed_shrew'}, {'id': 2817, 'synset': 'water_shrew.n.01', 'name': 'water_shrew'}, {'id': 2818, 'synset': 'american_water_shrew.n.01', 'name': 'American_water_shrew'}, {'id': 2819, 'synset': 'european_water_shrew.n.01', 'name': 'European_water_shrew'}, {'id': 2820, 'synset': 'mediterranean_water_shrew.n.01', 'name': 'Mediterranean_water_shrew'}, {'id': 2821, 'synset': 'least_shrew.n.01', 'name': 'least_shrew'}, {'id': 2822, 'synset': 'hedgehog.n.02', 'name': 'hedgehog'}, {'id': 2823, 'synset': 'tenrec.n.01', 'name': 'tenrec'}, {'id': 2824, 'synset': 'tailless_tenrec.n.01', 'name': 'tailless_tenrec'}, {'id': 2825, 'synset': 'otter_shrew.n.01', 'name': 'otter_shrew'}, {'id': 2826, 'synset': 'eiderdown.n.02', 'name': 'eiderdown'}, {'id': 2827, 'synset': 'aftershaft.n.01', 'name': 'aftershaft'}, {'id': 2828, 'synset': 'sickle_feather.n.01', 'name': 'sickle_feather'}, {'id': 2829, 'synset': 'contour_feather.n.01', 'name': 'contour_feather'}, {'id': 2830, 'synset': 'bastard_wing.n.01', 'name': 'bastard_wing'}, {'id': 2831, 'synset': 'saddle_hackle.n.01', 'name': 'saddle_hackle'}, {'id': 2832, 'synset': 'encolure.n.01', 'name': 'encolure'}, {'id': 2833, 'synset': 'hair.n.06', 'name': 'hair'}, {'id': 2834, 'synset': 'squama.n.01', 'name': 'squama'}, {'id': 2835, 'synset': 'scute.n.01', 'name': 'scute'}, {'id': 2836, 'synset': 'sclerite.n.01', 'name': 'sclerite'}, {'id': 2837, 'synset': 'plastron.n.05', 'name': 'plastron'}, {'id': 2838, 'synset': 'scallop_shell.n.01', 'name': 'scallop_shell'}, {'id': 2839, 'synset': 'oyster_shell.n.01', 'name': 'oyster_shell'}, {'id': 2840, 'synset': 'theca.n.02', 'name': 'theca'}, {'id': 2841, 'synset': 'invertebrate.n.01', 'name': 'invertebrate'}, {'id': 2842, 'synset': 'sponge.n.04', 'name': 'sponge'}, {'id': 2843, 'synset': 'choanocyte.n.01', 'name': 'choanocyte'}, {'id': 2844, 'synset': 'glass_sponge.n.01', 'name': 'glass_sponge'}, {'id': 2845, 'synset': "venus's_flower_basket.n.01", 'name': "Venus's_flower_basket"}, {'id': 2846, 'synset': 'metazoan.n.01', 'name': 'metazoan'}, {'id': 2847, 'synset': 'coelenterate.n.01', 'name': 'coelenterate'}, {'id': 2848, 'synset': 'planula.n.01', 'name': 'planula'}, {'id': 2849, 'synset': 'polyp.n.02', 'name': 'polyp'}, {'id': 2850, 'synset': 'medusa.n.02', 'name': 'medusa'}, {'id': 2851, 'synset': 'jellyfish.n.02', 'name': 'jellyfish'}, {'id': 2852, 'synset': 'scyphozoan.n.01', 'name': 'scyphozoan'}, {'id': 2853, 'synset': 'chrysaora_quinquecirrha.n.01', 'name': 'Chrysaora_quinquecirrha'}, {'id': 2854, 'synset': 'hydrozoan.n.01', 'name': 'hydrozoan'}, {'id': 2855, 'synset': 'hydra.n.04', 'name': 'hydra'}, {'id': 2856, 'synset': 'siphonophore.n.01', 'name': 'siphonophore'}, {'id': 2857, 'synset': 'nanomia.n.01', 'name': 'nanomia'}, {'id': 2858, 'synset': 'portuguese_man-of-war.n.01', 'name': 'Portuguese_man-of-war'}, {'id': 2859, 'synset': 'praya.n.01', 'name': 'praya'}, {'id': 2860, 'synset': 'apolemia.n.01', 'name': 'apolemia'}, {'id': 2861, 'synset': 'anthozoan.n.01', 'name': 'anthozoan'}, {'id': 2862, 'synset': 'sea_anemone.n.01', 'name': 'sea_anemone'}, {'id': 2863, 'synset': 'actinia.n.02', 'name': 'actinia'}, {'id': 2864, 'synset': 'sea_pen.n.01', 'name': 'sea_pen'}, {'id': 2865, 'synset': 'coral.n.04', 'name': 'coral'}, {'id': 2866, 'synset': 'gorgonian.n.01', 'name': 'gorgonian'}, {'id': 2867, 'synset': 'sea_feather.n.01', 'name': 'sea_feather'}, {'id': 2868, 'synset': 'sea_fan.n.01', 'name': 'sea_fan'}, {'id': 2869, 'synset': 'red_coral.n.02', 'name': 'red_coral'}, {'id': 2870, 'synset': 'stony_coral.n.01', 'name': 'stony_coral'}, {'id': 2871, 'synset': 'brain_coral.n.01', 'name': 'brain_coral'}, {'id': 2872, 'synset': 'staghorn_coral.n.01', 'name': 'staghorn_coral'}, {'id': 2873, 'synset': 'mushroom_coral.n.01', 'name': 'mushroom_coral'}, {'id': 2874, 'synset': 'ctenophore.n.01', 'name': 'ctenophore'}, {'id': 2875, 'synset': 'beroe.n.01', 'name': 'beroe'}, {'id': 2876, 'synset': 'platyctenean.n.01', 'name': 'platyctenean'}, {'id': 2877, 'synset': 'sea_gooseberry.n.01', 'name': 'sea_gooseberry'}, {'id': 2878, 'synset': "venus's_girdle.n.01", 'name': "Venus's_girdle"}, {'id': 2879, 'synset': 'worm.n.01', 'name': 'worm'}, {'id': 2880, 'synset': 'helminth.n.01', 'name': 'helminth'}, {'id': 2881, 'synset': 'woodworm.n.01', 'name': 'woodworm'}, {'id': 2882, 'synset': 'woodborer.n.01', 'name': 'woodborer'}, {'id': 2883, 'synset': 'acanthocephalan.n.01', 'name': 'acanthocephalan'}, {'id': 2884, 'synset': 'arrowworm.n.01', 'name': 'arrowworm'}, {'id': 2885, 'synset': 'bladder_worm.n.01', 'name': 'bladder_worm'}, {'id': 2886, 'synset': 'flatworm.n.01', 'name': 'flatworm'}, {'id': 2887, 'synset': 'planarian.n.01', 'name': 'planarian'}, {'id': 2888, 'synset': 'fluke.n.05', 'name': 'fluke'}, {'id': 2889, 'synset': 'cercaria.n.01', 'name': 'cercaria'}, {'id': 2890, 'synset': 'liver_fluke.n.01', 'name': 'liver_fluke'}, {'id': 2891, 'synset': 'fasciolopsis_buski.n.01', 'name': 'Fasciolopsis_buski'}, {'id': 2892, 'synset': 'schistosome.n.01', 'name': 'schistosome'}, {'id': 2893, 'synset': 'tapeworm.n.01', 'name': 'tapeworm'}, {'id': 2894, 'synset': 'echinococcus.n.01', 'name': 'echinococcus'}, {'id': 2895, 'synset': 'taenia.n.02', 'name': 'taenia'}, {'id': 2896, 'synset': 'ribbon_worm.n.01', 'name': 'ribbon_worm'}, {'id': 2897, 'synset': 'beard_worm.n.01', 'name': 'beard_worm'}, {'id': 2898, 'synset': 'rotifer.n.01', 'name': 'rotifer'}, {'id': 2899, 'synset': 'nematode.n.01', 'name': 'nematode'}, {'id': 2900, 'synset': 'common_roundworm.n.01', 'name': 'common_roundworm'}, {'id': 2901, 'synset': 'chicken_roundworm.n.01', 'name': 'chicken_roundworm'}, {'id': 2902, 'synset': 'pinworm.n.01', 'name': 'pinworm'}, {'id': 2903, 'synset': 'eelworm.n.01', 'name': 'eelworm'}, {'id': 2904, 'synset': 'vinegar_eel.n.01', 'name': 'vinegar_eel'}, {'id': 2905, 'synset': 'trichina.n.01', 'name': 'trichina'}, {'id': 2906, 'synset': 'hookworm.n.01', 'name': 'hookworm'}, {'id': 2907, 'synset': 'filaria.n.02', 'name': 'filaria'}, {'id': 2908, 'synset': 'guinea_worm.n.02', 'name': 'Guinea_worm'}, {'id': 2909, 'synset': 'annelid.n.01', 'name': 'annelid'}, {'id': 2910, 'synset': 'archiannelid.n.01', 'name': 'archiannelid'}, {'id': 2911, 'synset': 'oligochaete.n.01', 'name': 'oligochaete'}, {'id': 2912, 'synset': 'earthworm.n.01', 'name': 'earthworm'}, {'id': 2913, 'synset': 'polychaete.n.01', 'name': 'polychaete'}, {'id': 2914, 'synset': 'lugworm.n.01', 'name': 'lugworm'}, {'id': 2915, 'synset': 'sea_mouse.n.01', 'name': 'sea_mouse'}, {'id': 2916, 'synset': 'bloodworm.n.01', 'name': 'bloodworm'}, {'id': 2917, 'synset': 'leech.n.01', 'name': 'leech'}, {'id': 2918, 'synset': 'medicinal_leech.n.01', 'name': 'medicinal_leech'}, {'id': 2919, 'synset': 'horseleech.n.01', 'name': 'horseleech'}, {'id': 2920, 'synset': 'mollusk.n.01', 'name': 'mollusk'}, {'id': 2921, 'synset': 'scaphopod.n.01', 'name': 'scaphopod'}, {'id': 2922, 'synset': 'tooth_shell.n.01', 'name': 'tooth_shell'}, {'id': 2923, 'synset': 'gastropod.n.01', 'name': 'gastropod'}, {'id': 2924, 'synset': 'abalone.n.01', 'name': 'abalone'}, {'id': 2925, 'synset': 'ormer.n.01', 'name': 'ormer'}, {'id': 2926, 'synset': 'scorpion_shell.n.01', 'name': 'scorpion_shell'}, {'id': 2927, 'synset': 'conch.n.01', 'name': 'conch'}, {'id': 2928, 'synset': 'giant_conch.n.01', 'name': 'giant_conch'}, {'id': 2929, 'synset': 'snail.n.01', 'name': 'snail'}, {'id': 2930, 'synset': 'edible_snail.n.01', 'name': 'edible_snail'}, {'id': 2931, 'synset': 'garden_snail.n.01', 'name': 'garden_snail'}, {'id': 2932, 'synset': 'brown_snail.n.01', 'name': 'brown_snail'}, {'id': 2933, 'synset': 'helix_hortensis.n.01', 'name': 'Helix_hortensis'}, {'id': 2934, 'synset': 'slug.n.07', 'name': 'slug'}, {'id': 2935, 'synset': 'seasnail.n.02', 'name': 'seasnail'}, {'id': 2936, 'synset': 'neritid.n.01', 'name': 'neritid'}, {'id': 2937, 'synset': 'nerita.n.01', 'name': 'nerita'}, {'id': 2938, 'synset': 'bleeding_tooth.n.01', 'name': 'bleeding_tooth'}, {'id': 2939, 'synset': 'neritina.n.01', 'name': 'neritina'}, {'id': 2940, 'synset': 'whelk.n.02', 'name': 'whelk'}, {'id': 2941, 'synset': 'moon_shell.n.01', 'name': 'moon_shell'}, {'id': 2942, 'synset': 'periwinkle.n.04', 'name': 'periwinkle'}, {'id': 2943, 'synset': 'limpet.n.02', 'name': 'limpet'}, {'id': 2944, 'synset': 'common_limpet.n.01', 'name': 'common_limpet'}, {'id': 2945, 'synset': 'keyhole_limpet.n.01', 'name': 'keyhole_limpet'}, {'id': 2946, 'synset': 'river_limpet.n.01', 'name': 'river_limpet'}, {'id': 2947, 'synset': 'sea_slug.n.01', 'name': 'sea_slug'}, {'id': 2948, 'synset': 'sea_hare.n.01', 'name': 'sea_hare'}, {'id': 2949, 'synset': 'hermissenda_crassicornis.n.01', 'name': 'Hermissenda_crassicornis'}, {'id': 2950, 'synset': 'bubble_shell.n.01', 'name': 'bubble_shell'}, {'id': 2951, 'synset': 'physa.n.01', 'name': 'physa'}, {'id': 2952, 'synset': 'cowrie.n.01', 'name': 'cowrie'}, {'id': 2953, 'synset': 'money_cowrie.n.01', 'name': 'money_cowrie'}, {'id': 2954, 'synset': 'tiger_cowrie.n.01', 'name': 'tiger_cowrie'}, {'id': 2955, 'synset': 'solenogaster.n.01', 'name': 'solenogaster'}, {'id': 2956, 'synset': 'chiton.n.02', 'name': 'chiton'}, {'id': 2957, 'synset': 'bivalve.n.01', 'name': 'bivalve'}, {'id': 2958, 'synset': 'spat.n.03', 'name': 'spat'}, {'id': 2959, 'synset': 'clam.n.01', 'name': 'clam'}, {'id': 2960, 'synset': 'soft-shell_clam.n.02', 'name': 'soft-shell_clam'}, {'id': 2961, 'synset': 'quahog.n.02', 'name': 'quahog'}, {'id': 2962, 'synset': 'littleneck.n.02', 'name': 'littleneck'}, {'id': 2963, 'synset': 'cherrystone.n.02', 'name': 'cherrystone'}, {'id': 2964, 'synset': 'geoduck.n.01', 'name': 'geoduck'}, {'id': 2965, 'synset': 'razor_clam.n.01', 'name': 'razor_clam'}, {'id': 2966, 'synset': 'giant_clam.n.01', 'name': 'giant_clam'}, {'id': 2967, 'synset': 'cockle.n.02', 'name': 'cockle'}, {'id': 2968, 'synset': 'edible_cockle.n.01', 'name': 'edible_cockle'}, {'id': 2969, 'synset': 'oyster.n.01', 'name': 'oyster'}, {'id': 2970, 'synset': 'japanese_oyster.n.01', 'name': 'Japanese_oyster'}, {'id': 2971, 'synset': 'virginia_oyster.n.01', 'name': 'Virginia_oyster'}, {'id': 2972, 'synset': 'pearl_oyster.n.01', 'name': 'pearl_oyster'}, {'id': 2973, 'synset': 'saddle_oyster.n.01', 'name': 'saddle_oyster'}, {'id': 2974, 'synset': 'window_oyster.n.01', 'name': 'window_oyster'}, {'id': 2975, 'synset': 'ark_shell.n.01', 'name': 'ark_shell'}, {'id': 2976, 'synset': 'blood_clam.n.01', 'name': 'blood_clam'}, {'id': 2977, 'synset': 'mussel.n.02', 'name': 'mussel'}, {'id': 2978, 'synset': 'marine_mussel.n.01', 'name': 'marine_mussel'}, {'id': 2979, 'synset': 'edible_mussel.n.01', 'name': 'edible_mussel'}, {'id': 2980, 'synset': 'freshwater_mussel.n.01', 'name': 'freshwater_mussel'}, {'id': 2981, 'synset': 'pearly-shelled_mussel.n.01', 'name': 'pearly-shelled_mussel'}, {'id': 2982, 'synset': 'thin-shelled_mussel.n.01', 'name': 'thin-shelled_mussel'}, {'id': 2983, 'synset': 'zebra_mussel.n.01', 'name': 'zebra_mussel'}, {'id': 2984, 'synset': 'scallop.n.04', 'name': 'scallop'}, {'id': 2985, 'synset': 'bay_scallop.n.02', 'name': 'bay_scallop'}, {'id': 2986, 'synset': 'sea_scallop.n.02', 'name': 'sea_scallop'}, {'id': 2987, 'synset': 'shipworm.n.01', 'name': 'shipworm'}, {'id': 2988, 'synset': 'teredo.n.01', 'name': 'teredo'}, {'id': 2989, 'synset': 'piddock.n.01', 'name': 'piddock'}, {'id': 2990, 'synset': 'cephalopod.n.01', 'name': 'cephalopod'}, {'id': 2991, 'synset': 'chambered_nautilus.n.01', 'name': 'chambered_nautilus'}, {'id': 2992, 'synset': 'octopod.n.01', 'name': 'octopod'}, {'id': 2993, 'synset': 'paper_nautilus.n.01', 'name': 'paper_nautilus'}, {'id': 2994, 'synset': 'decapod.n.02', 'name': 'decapod'}, {'id': 2995, 'synset': 'squid.n.02', 'name': 'squid'}, {'id': 2996, 'synset': 'loligo.n.01', 'name': 'loligo'}, {'id': 2997, 'synset': 'ommastrephes.n.01', 'name': 'ommastrephes'}, {'id': 2998, 'synset': 'architeuthis.n.01', 'name': 'architeuthis'}, {'id': 2999, 'synset': 'cuttlefish.n.01', 'name': 'cuttlefish'}, {'id': 3000, 'synset': 'spirula.n.01', 'name': 'spirula'}, {'id': 3001, 'synset': 'crustacean.n.01', 'name': 'crustacean'}, {'id': 3002, 'synset': 'malacostracan_crustacean.n.01', 'name': 'malacostracan_crustacean'}, {'id': 3003, 'synset': 'decapod_crustacean.n.01', 'name': 'decapod_crustacean'}, {'id': 3004, 'synset': 'brachyuran.n.01', 'name': 'brachyuran'}, {'id': 3005, 'synset': 'stone_crab.n.02', 'name': 'stone_crab'}, {'id': 3006, 'synset': 'hard-shell_crab.n.01', 'name': 'hard-shell_crab'}, {'id': 3007, 'synset': 'soft-shell_crab.n.02', 'name': 'soft-shell_crab'}, {'id': 3008, 'synset': 'dungeness_crab.n.02', 'name': 'Dungeness_crab'}, {'id': 3009, 'synset': 'rock_crab.n.01', 'name': 'rock_crab'}, {'id': 3010, 'synset': 'jonah_crab.n.01', 'name': 'Jonah_crab'}, {'id': 3011, 'synset': 'swimming_crab.n.01', 'name': 'swimming_crab'}, {'id': 3012, 'synset': 'english_lady_crab.n.01', 'name': 'English_lady_crab'}, {'id': 3013, 'synset': 'american_lady_crab.n.01', 'name': 'American_lady_crab'}, {'id': 3014, 'synset': 'blue_crab.n.02', 'name': 'blue_crab'}, {'id': 3015, 'synset': 'fiddler_crab.n.01', 'name': 'fiddler_crab'}, {'id': 3016, 'synset': 'pea_crab.n.01', 'name': 'pea_crab'}, {'id': 3017, 'synset': 'king_crab.n.03', 'name': 'king_crab'}, {'id': 3018, 'synset': 'spider_crab.n.01', 'name': 'spider_crab'}, {'id': 3019, 'synset': 'european_spider_crab.n.01', 'name': 'European_spider_crab'}, {'id': 3020, 'synset': 'giant_crab.n.01', 'name': 'giant_crab'}, {'id': 3021, 'synset': 'lobster.n.02', 'name': 'lobster'}, {'id': 3022, 'synset': 'true_lobster.n.01', 'name': 'true_lobster'}, {'id': 3023, 'synset': 'american_lobster.n.02', 'name': 'American_lobster'}, {'id': 3024, 'synset': 'european_lobster.n.02', 'name': 'European_lobster'}, {'id': 3025, 'synset': 'cape_lobster.n.01', 'name': 'Cape_lobster'}, {'id': 3026, 'synset': 'norway_lobster.n.01', 'name': 'Norway_lobster'}, {'id': 3027, 'synset': 'crayfish.n.03', 'name': 'crayfish'}, {'id': 3028, 'synset': 'old_world_crayfish.n.01', 'name': 'Old_World_crayfish'}, {'id': 3029, 'synset': 'american_crayfish.n.01', 'name': 'American_crayfish'}, {'id': 3030, 'synset': 'hermit_crab.n.01', 'name': 'hermit_crab'}, {'id': 3031, 'synset': 'shrimp.n.03', 'name': 'shrimp'}, {'id': 3032, 'synset': 'snapping_shrimp.n.01', 'name': 'snapping_shrimp'}, {'id': 3033, 'synset': 'prawn.n.02', 'name': 'prawn'}, {'id': 3034, 'synset': 'long-clawed_prawn.n.01', 'name': 'long-clawed_prawn'}, {'id': 3035, 'synset': 'tropical_prawn.n.01', 'name': 'tropical_prawn'}, {'id': 3036, 'synset': 'krill.n.01', 'name': 'krill'}, {'id': 3037, 'synset': 'euphausia_pacifica.n.01', 'name': 'Euphausia_pacifica'}, {'id': 3038, 'synset': 'opossum_shrimp.n.01', 'name': 'opossum_shrimp'}, {'id': 3039, 'synset': 'stomatopod.n.01', 'name': 'stomatopod'}, {'id': 3040, 'synset': 'mantis_shrimp.n.01', 'name': 'mantis_shrimp'}, {'id': 3041, 'synset': 'squilla.n.01', 'name': 'squilla'}, {'id': 3042, 'synset': 'isopod.n.01', 'name': 'isopod'}, {'id': 3043, 'synset': 'woodlouse.n.01', 'name': 'woodlouse'}, {'id': 3044, 'synset': 'pill_bug.n.01', 'name': 'pill_bug'}, {'id': 3045, 'synset': 'sow_bug.n.01', 'name': 'sow_bug'}, {'id': 3046, 'synset': 'sea_louse.n.01', 'name': 'sea_louse'}, {'id': 3047, 'synset': 'amphipod.n.01', 'name': 'amphipod'}, {'id': 3048, 'synset': 'skeleton_shrimp.n.01', 'name': 'skeleton_shrimp'}, {'id': 3049, 'synset': 'whale_louse.n.01', 'name': 'whale_louse'}, {'id': 3050, 'synset': 'daphnia.n.01', 'name': 'daphnia'}, {'id': 3051, 'synset': 'fairy_shrimp.n.01', 'name': 'fairy_shrimp'}, {'id': 3052, 'synset': 'brine_shrimp.n.01', 'name': 'brine_shrimp'}, {'id': 3053, 'synset': 'tadpole_shrimp.n.01', 'name': 'tadpole_shrimp'}, {'id': 3054, 'synset': 'copepod.n.01', 'name': 'copepod'}, {'id': 3055, 'synset': 'cyclops.n.02', 'name': 'cyclops'}, {'id': 3056, 'synset': 'seed_shrimp.n.01', 'name': 'seed_shrimp'}, {'id': 3057, 'synset': 'barnacle.n.01', 'name': 'barnacle'}, {'id': 3058, 'synset': 'acorn_barnacle.n.01', 'name': 'acorn_barnacle'}, {'id': 3059, 'synset': 'goose_barnacle.n.01', 'name': 'goose_barnacle'}, {'id': 3060, 'synset': 'onychophoran.n.01', 'name': 'onychophoran'}, {'id': 3061, 'synset': 'wading_bird.n.01', 'name': 'wading_bird'}, {'id': 3062, 'synset': 'stork.n.01', 'name': 'stork'}, {'id': 3063, 'synset': 'white_stork.n.01', 'name': 'white_stork'}, {'id': 3064, 'synset': 'black_stork.n.01', 'name': 'black_stork'}, {'id': 3065, 'synset': 'adjutant_bird.n.01', 'name': 'adjutant_bird'}, {'id': 3066, 'synset': 'marabou.n.01', 'name': 'marabou'}, {'id': 3067, 'synset': 'openbill.n.01', 'name': 'openbill'}, {'id': 3068, 'synset': 'jabiru.n.03', 'name': 'jabiru'}, {'id': 3069, 'synset': 'saddlebill.n.01', 'name': 'saddlebill'}, {'id': 3070, 'synset': 'policeman_bird.n.01', 'name': 'policeman_bird'}, {'id': 3071, 'synset': 'wood_ibis.n.02', 'name': 'wood_ibis'}, {'id': 3072, 'synset': 'shoebill.n.01', 'name': 'shoebill'}, {'id': 3073, 'synset': 'ibis.n.01', 'name': 'ibis'}, {'id': 3074, 'synset': 'wood_ibis.n.01', 'name': 'wood_ibis'}, {'id': 3075, 'synset': 'sacred_ibis.n.01', 'name': 'sacred_ibis'}, {'id': 3076, 'synset': 'spoonbill.n.01', 'name': 'spoonbill'}, {'id': 3077, 'synset': 'common_spoonbill.n.01', 'name': 'common_spoonbill'}, {'id': 3078, 'synset': 'roseate_spoonbill.n.01', 'name': 'roseate_spoonbill'}, {'id': 3079, 'synset': 'great_blue_heron.n.01', 'name': 'great_blue_heron'}, {'id': 3080, 'synset': 'great_white_heron.n.03', 'name': 'great_white_heron'}, {'id': 3081, 'synset': 'egret.n.01', 'name': 'egret'}, {'id': 3082, 'synset': 'little_blue_heron.n.01', 'name': 'little_blue_heron'}, {'id': 3083, 'synset': 'snowy_egret.n.01', 'name': 'snowy_egret'}, {'id': 3084, 'synset': 'little_egret.n.01', 'name': 'little_egret'}, {'id': 3085, 'synset': 'great_white_heron.n.02', 'name': 'great_white_heron'}, {'id': 3086, 'synset': 'american_egret.n.01', 'name': 'American_egret'}, {'id': 3087, 'synset': 'cattle_egret.n.01', 'name': 'cattle_egret'}, {'id': 3088, 'synset': 'night_heron.n.01', 'name': 'night_heron'}, {'id': 3089, 'synset': 'black-crowned_night_heron.n.01', 'name': 'black-crowned_night_heron'}, {'id': 3090, 'synset': 'yellow-crowned_night_heron.n.01', 'name': 'yellow-crowned_night_heron'}, {'id': 3091, 'synset': 'boatbill.n.01', 'name': 'boatbill'}, {'id': 3092, 'synset': 'bittern.n.01', 'name': 'bittern'}, {'id': 3093, 'synset': 'american_bittern.n.01', 'name': 'American_bittern'}, {'id': 3094, 'synset': 'european_bittern.n.01', 'name': 'European_bittern'}, {'id': 3095, 'synset': 'least_bittern.n.01', 'name': 'least_bittern'}, {'id': 3096, 'synset': 'crane.n.05', 'name': 'crane'}, {'id': 3097, 'synset': 'whooping_crane.n.01', 'name': 'whooping_crane'}, {'id': 3098, 'synset': 'courlan.n.01', 'name': 'courlan'}, {'id': 3099, 'synset': 'limpkin.n.01', 'name': 'limpkin'}, {'id': 3100, 'synset': 'crested_cariama.n.01', 'name': 'crested_cariama'}, {'id': 3101, 'synset': 'chunga.n.01', 'name': 'chunga'}, {'id': 3102, 'synset': 'rail.n.05', 'name': 'rail'}, {'id': 3103, 'synset': 'weka.n.01', 'name': 'weka'}, {'id': 3104, 'synset': 'crake.n.01', 'name': 'crake'}, {'id': 3105, 'synset': 'corncrake.n.01', 'name': 'corncrake'}, {'id': 3106, 'synset': 'spotted_crake.n.01', 'name': 'spotted_crake'}, {'id': 3107, 'synset': 'gallinule.n.01', 'name': 'gallinule'}, {'id': 3108, 'synset': 'florida_gallinule.n.01', 'name': 'Florida_gallinule'}, {'id': 3109, 'synset': 'moorhen.n.01', 'name': 'moorhen'}, {'id': 3110, 'synset': 'purple_gallinule.n.01', 'name': 'purple_gallinule'}, {'id': 3111, 'synset': 'european_gallinule.n.01', 'name': 'European_gallinule'}, {'id': 3112, 'synset': 'american_gallinule.n.01', 'name': 'American_gallinule'}, {'id': 3113, 'synset': 'notornis.n.01', 'name': 'notornis'}, {'id': 3114, 'synset': 'coot.n.01', 'name': 'coot'}, {'id': 3115, 'synset': 'american_coot.n.01', 'name': 'American_coot'}, {'id': 3116, 'synset': 'old_world_coot.n.01', 'name': 'Old_World_coot'}, {'id': 3117, 'synset': 'bustard.n.01', 'name': 'bustard'}, {'id': 3118, 'synset': 'great_bustard.n.01', 'name': 'great_bustard'}, {'id': 3119, 'synset': 'plain_turkey.n.01', 'name': 'plain_turkey'}, {'id': 3120, 'synset': 'button_quail.n.01', 'name': 'button_quail'}, {'id': 3121, 'synset': 'striped_button_quail.n.01', 'name': 'striped_button_quail'}, {'id': 3122, 'synset': 'plain_wanderer.n.01', 'name': 'plain_wanderer'}, {'id': 3123, 'synset': 'trumpeter.n.03', 'name': 'trumpeter'}, {'id': 3124, 'synset': 'brazilian_trumpeter.n.01', 'name': 'Brazilian_trumpeter'}, {'id': 3125, 'synset': 'shorebird.n.01', 'name': 'shorebird'}, {'id': 3126, 'synset': 'plover.n.01', 'name': 'plover'}, {'id': 3127, 'synset': 'piping_plover.n.01', 'name': 'piping_plover'}, {'id': 3128, 'synset': 'killdeer.n.01', 'name': 'killdeer'}, {'id': 3129, 'synset': 'dotterel.n.01', 'name': 'dotterel'}, {'id': 3130, 'synset': 'golden_plover.n.01', 'name': 'golden_plover'}, {'id': 3131, 'synset': 'lapwing.n.01', 'name': 'lapwing'}, {'id': 3132, 'synset': 'turnstone.n.01', 'name': 'turnstone'}, {'id': 3133, 'synset': 'ruddy_turnstone.n.01', 'name': 'ruddy_turnstone'}, {'id': 3134, 'synset': 'black_turnstone.n.01', 'name': 'black_turnstone'}, {'id': 3135, 'synset': 'sandpiper.n.01', 'name': 'sandpiper'}, {'id': 3136, 'synset': 'surfbird.n.01', 'name': 'surfbird'}, {'id': 3137, 'synset': 'european_sandpiper.n.01', 'name': 'European_sandpiper'}, {'id': 3138, 'synset': 'spotted_sandpiper.n.01', 'name': 'spotted_sandpiper'}, {'id': 3139, 'synset': 'least_sandpiper.n.01', 'name': 'least_sandpiper'}, {'id': 3140, 'synset': 'red-backed_sandpiper.n.01', 'name': 'red-backed_sandpiper'}, {'id': 3141, 'synset': 'greenshank.n.01', 'name': 'greenshank'}, {'id': 3142, 'synset': 'redshank.n.01', 'name': 'redshank'}, {'id': 3143, 'synset': 'yellowlegs.n.01', 'name': 'yellowlegs'}, {'id': 3144, 'synset': 'greater_yellowlegs.n.01', 'name': 'greater_yellowlegs'}, {'id': 3145, 'synset': 'lesser_yellowlegs.n.01', 'name': 'lesser_yellowlegs'}, {'id': 3146, 'synset': 'pectoral_sandpiper.n.01', 'name': 'pectoral_sandpiper'}, {'id': 3147, 'synset': 'knot.n.07', 'name': 'knot'}, {'id': 3148, 'synset': 'curlew_sandpiper.n.01', 'name': 'curlew_sandpiper'}, {'id': 3149, 'synset': 'sanderling.n.01', 'name': 'sanderling'}, {'id': 3150, 'synset': 'upland_sandpiper.n.01', 'name': 'upland_sandpiper'}, {'id': 3151, 'synset': 'ruff.n.03', 'name': 'ruff'}, {'id': 3152, 'synset': 'reeve.n.01', 'name': 'reeve'}, {'id': 3153, 'synset': 'tattler.n.02', 'name': 'tattler'}, {'id': 3154, 'synset': 'polynesian_tattler.n.01', 'name': 'Polynesian_tattler'}, {'id': 3155, 'synset': 'willet.n.01', 'name': 'willet'}, {'id': 3156, 'synset': 'woodcock.n.01', 'name': 'woodcock'}, {'id': 3157, 'synset': 'eurasian_woodcock.n.01', 'name': 'Eurasian_woodcock'}, {'id': 3158, 'synset': 'american_woodcock.n.01', 'name': 'American_woodcock'}, {'id': 3159, 'synset': 'snipe.n.01', 'name': 'snipe'}, {'id': 3160, 'synset': 'whole_snipe.n.01', 'name': 'whole_snipe'}, {'id': 3161, 'synset': "wilson's_snipe.n.01", 'name': "Wilson's_snipe"}, {'id': 3162, 'synset': 'great_snipe.n.01', 'name': 'great_snipe'}, {'id': 3163, 'synset': 'jacksnipe.n.01', 'name': 'jacksnipe'}, {'id': 3164, 'synset': 'dowitcher.n.01', 'name': 'dowitcher'}, {'id': 3165, 'synset': 'greyback.n.02', 'name': 'greyback'}, {'id': 3166, 'synset': 'red-breasted_snipe.n.01', 'name': 'red-breasted_snipe'}, {'id': 3167, 'synset': 'curlew.n.01', 'name': 'curlew'}, {'id': 3168, 'synset': 'european_curlew.n.01', 'name': 'European_curlew'}, {'id': 3169, 'synset': 'eskimo_curlew.n.01', 'name': 'Eskimo_curlew'}, {'id': 3170, 'synset': 'godwit.n.01', 'name': 'godwit'}, {'id': 3171, 'synset': 'hudsonian_godwit.n.01', 'name': 'Hudsonian_godwit'}, {'id': 3172, 'synset': 'stilt.n.04', 'name': 'stilt'}, {'id': 3173, 'synset': 'black-necked_stilt.n.01', 'name': 'black-necked_stilt'}, {'id': 3174, 'synset': 'black-winged_stilt.n.01', 'name': 'black-winged_stilt'}, {'id': 3175, 'synset': 'white-headed_stilt.n.01', 'name': 'white-headed_stilt'}, {'id': 3176, 'synset': 'kaki.n.02', 'name': 'kaki'}, {'id': 3177, 'synset': 'stilt.n.03', 'name': 'stilt'}, {'id': 3178, 'synset': 'banded_stilt.n.01', 'name': 'banded_stilt'}, {'id': 3179, 'synset': 'avocet.n.01', 'name': 'avocet'}, {'id': 3180, 'synset': 'oystercatcher.n.01', 'name': 'oystercatcher'}, {'id': 3181, 'synset': 'phalarope.n.01', 'name': 'phalarope'}, {'id': 3182, 'synset': 'red_phalarope.n.01', 'name': 'red_phalarope'}, {'id': 3183, 'synset': 'northern_phalarope.n.01', 'name': 'northern_phalarope'}, {'id': 3184, 'synset': "wilson's_phalarope.n.01", 'name': "Wilson's_phalarope"}, {'id': 3185, 'synset': 'pratincole.n.01', 'name': 'pratincole'}, {'id': 3186, 'synset': 'courser.n.04', 'name': 'courser'}, {'id': 3187, 'synset': 'cream-colored_courser.n.01', 'name': 'cream-colored_courser'}, {'id': 3188, 'synset': 'crocodile_bird.n.01', 'name': 'crocodile_bird'}, {'id': 3189, 'synset': 'stone_curlew.n.01', 'name': 'stone_curlew'}, {'id': 3190, 'synset': 'coastal_diving_bird.n.01', 'name': 'coastal_diving_bird'}, {'id': 3191, 'synset': 'larid.n.01', 'name': 'larid'}, {'id': 3192, 'synset': 'mew.n.02', 'name': 'mew'}, {'id': 3193, 'synset': 'black-backed_gull.n.01', 'name': 'black-backed_gull'}, {'id': 3194, 'synset': 'herring_gull.n.01', 'name': 'herring_gull'}, {'id': 3195, 'synset': 'laughing_gull.n.01', 'name': 'laughing_gull'}, {'id': 3196, 'synset': 'ivory_gull.n.01', 'name': 'ivory_gull'}, {'id': 3197, 'synset': 'kittiwake.n.01', 'name': 'kittiwake'}, {'id': 3198, 'synset': 'tern.n.01', 'name': 'tern'}, {'id': 3199, 'synset': 'sea_swallow.n.01', 'name': 'sea_swallow'}, {'id': 3200, 'synset': 'skimmer.n.04', 'name': 'skimmer'}, {'id': 3201, 'synset': 'jaeger.n.01', 'name': 'jaeger'}, {'id': 3202, 'synset': 'parasitic_jaeger.n.01', 'name': 'parasitic_jaeger'}, {'id': 3203, 'synset': 'skua.n.01', 'name': 'skua'}, {'id': 3204, 'synset': 'great_skua.n.01', 'name': 'great_skua'}, {'id': 3205, 'synset': 'auk.n.01', 'name': 'auk'}, {'id': 3206, 'synset': 'auklet.n.01', 'name': 'auklet'}, {'id': 3207, 'synset': 'razorbill.n.01', 'name': 'razorbill'}, {'id': 3208, 'synset': 'little_auk.n.01', 'name': 'little_auk'}, {'id': 3209, 'synset': 'guillemot.n.01', 'name': 'guillemot'}, {'id': 3210, 'synset': 'black_guillemot.n.01', 'name': 'black_guillemot'}, {'id': 3211, 'synset': 'pigeon_guillemot.n.01', 'name': 'pigeon_guillemot'}, {'id': 3212, 'synset': 'murre.n.01', 'name': 'murre'}, {'id': 3213, 'synset': 'common_murre.n.01', 'name': 'common_murre'}, {'id': 3214, 'synset': 'thick-billed_murre.n.01', 'name': 'thick-billed_murre'}, {'id': 3215, 'synset': 'atlantic_puffin.n.01', 'name': 'Atlantic_puffin'}, {'id': 3216, 'synset': 'horned_puffin.n.01', 'name': 'horned_puffin'}, {'id': 3217, 'synset': 'tufted_puffin.n.01', 'name': 'tufted_puffin'}, {'id': 3218, 'synset': 'gaviiform_seabird.n.01', 'name': 'gaviiform_seabird'}, {'id': 3219, 'synset': 'loon.n.02', 'name': 'loon'}, {'id': 3220, 'synset': 'podicipitiform_seabird.n.01', 'name': 'podicipitiform_seabird'}, {'id': 3221, 'synset': 'grebe.n.01', 'name': 'grebe'}, {'id': 3222, 'synset': 'great_crested_grebe.n.01', 'name': 'great_crested_grebe'}, {'id': 3223, 'synset': 'red-necked_grebe.n.01', 'name': 'red-necked_grebe'}, {'id': 3224, 'synset': 'black-necked_grebe.n.01', 'name': 'black-necked_grebe'}, {'id': 3225, 'synset': 'dabchick.n.01', 'name': 'dabchick'}, {'id': 3226, 'synset': 'pied-billed_grebe.n.01', 'name': 'pied-billed_grebe'}, {'id': 3227, 'synset': 'pelecaniform_seabird.n.01', 'name': 'pelecaniform_seabird'}, {'id': 3228, 'synset': 'white_pelican.n.01', 'name': 'white_pelican'}, {'id': 3229, 'synset': 'old_world_white_pelican.n.01', 'name': 'Old_world_white_pelican'}, {'id': 3230, 'synset': 'frigate_bird.n.01', 'name': 'frigate_bird'}, {'id': 3231, 'synset': 'gannet.n.01', 'name': 'gannet'}, {'id': 3232, 'synset': 'solan.n.01', 'name': 'solan'}, {'id': 3233, 'synset': 'booby.n.02', 'name': 'booby'}, {'id': 3234, 'synset': 'cormorant.n.01', 'name': 'cormorant'}, {'id': 3235, 'synset': 'snakebird.n.01', 'name': 'snakebird'}, {'id': 3236, 'synset': 'water_turkey.n.01', 'name': 'water_turkey'}, {'id': 3237, 'synset': 'tropic_bird.n.01', 'name': 'tropic_bird'}, {'id': 3238, 'synset': 'sphenisciform_seabird.n.01', 'name': 'sphenisciform_seabird'}, {'id': 3239, 'synset': 'adelie.n.01', 'name': 'Adelie'}, {'id': 3240, 'synset': 'king_penguin.n.01', 'name': 'king_penguin'}, {'id': 3241, 'synset': 'emperor_penguin.n.01', 'name': 'emperor_penguin'}, {'id': 3242, 'synset': 'jackass_penguin.n.01', 'name': 'jackass_penguin'}, {'id': 3243, 'synset': 'rock_hopper.n.01', 'name': 'rock_hopper'}, {'id': 3244, 'synset': 'pelagic_bird.n.01', 'name': 'pelagic_bird'}, {'id': 3245, 'synset': 'procellariiform_seabird.n.01', 'name': 'procellariiform_seabird'}, {'id': 3246, 'synset': 'albatross.n.02', 'name': 'albatross'}, {'id': 3247, 'synset': 'wandering_albatross.n.01', 'name': 'wandering_albatross'}, {'id': 3248, 'synset': 'black-footed_albatross.n.01', 'name': 'black-footed_albatross'}, {'id': 3249, 'synset': 'petrel.n.01', 'name': 'petrel'}, {'id': 3250, 'synset': 'white-chinned_petrel.n.01', 'name': 'white-chinned_petrel'}, {'id': 3251, 'synset': 'giant_petrel.n.01', 'name': 'giant_petrel'}, {'id': 3252, 'synset': 'fulmar.n.01', 'name': 'fulmar'}, {'id': 3253, 'synset': 'shearwater.n.01', 'name': 'shearwater'}, {'id': 3254, 'synset': 'manx_shearwater.n.01', 'name': 'Manx_shearwater'}, {'id': 3255, 'synset': 'storm_petrel.n.01', 'name': 'storm_petrel'}, {'id': 3256, 'synset': 'stormy_petrel.n.01', 'name': 'stormy_petrel'}, {'id': 3257, 'synset': "mother_carey's_chicken.n.01", 'name': "Mother_Carey's_chicken"}, {'id': 3258, 'synset': 'diving_petrel.n.01', 'name': 'diving_petrel'}, {'id': 3259, 'synset': 'aquatic_mammal.n.01', 'name': 'aquatic_mammal'}, {'id': 3260, 'synset': 'cetacean.n.01', 'name': 'cetacean'}, {'id': 3261, 'synset': 'whale.n.02', 'name': 'whale'}, {'id': 3262, 'synset': 'baleen_whale.n.01', 'name': 'baleen_whale'}, {'id': 3263, 'synset': 'right_whale.n.01', 'name': 'right_whale'}, {'id': 3264, 'synset': 'bowhead.n.01', 'name': 'bowhead'}, {'id': 3265, 'synset': 'rorqual.n.01', 'name': 'rorqual'}, {'id': 3266, 'synset': 'blue_whale.n.01', 'name': 'blue_whale'}, {'id': 3267, 'synset': 'finback.n.01', 'name': 'finback'}, {'id': 3268, 'synset': 'sei_whale.n.01', 'name': 'sei_whale'}, {'id': 3269, 'synset': 'lesser_rorqual.n.01', 'name': 'lesser_rorqual'}, {'id': 3270, 'synset': 'humpback.n.03', 'name': 'humpback'}, {'id': 3271, 'synset': 'grey_whale.n.01', 'name': 'grey_whale'}, {'id': 3272, 'synset': 'toothed_whale.n.01', 'name': 'toothed_whale'}, {'id': 3273, 'synset': 'sperm_whale.n.01', 'name': 'sperm_whale'}, {'id': 3274, 'synset': 'pygmy_sperm_whale.n.01', 'name': 'pygmy_sperm_whale'}, {'id': 3275, 'synset': 'dwarf_sperm_whale.n.01', 'name': 'dwarf_sperm_whale'}, {'id': 3276, 'synset': 'beaked_whale.n.01', 'name': 'beaked_whale'}, {'id': 3277, 'synset': 'bottle-nosed_whale.n.01', 'name': 'bottle-nosed_whale'}, {'id': 3278, 'synset': 'common_dolphin.n.01', 'name': 'common_dolphin'}, {'id': 3279, 'synset': 'bottlenose_dolphin.n.01', 'name': 'bottlenose_dolphin'}, {'id': 3280, 'synset': 'atlantic_bottlenose_dolphin.n.01', 'name': 'Atlantic_bottlenose_dolphin'}, {'id': 3281, 'synset': 'pacific_bottlenose_dolphin.n.01', 'name': 'Pacific_bottlenose_dolphin'}, {'id': 3282, 'synset': 'porpoise.n.01', 'name': 'porpoise'}, {'id': 3283, 'synset': 'harbor_porpoise.n.01', 'name': 'harbor_porpoise'}, {'id': 3284, 'synset': 'vaquita.n.01', 'name': 'vaquita'}, {'id': 3285, 'synset': 'grampus.n.02', 'name': 'grampus'}, {'id': 3286, 'synset': 'killer_whale.n.01', 'name': 'killer_whale'}, {'id': 3287, 'synset': 'pilot_whale.n.01', 'name': 'pilot_whale'}, {'id': 3288, 'synset': 'river_dolphin.n.01', 'name': 'river_dolphin'}, {'id': 3289, 'synset': 'narwhal.n.01', 'name': 'narwhal'}, {'id': 3290, 'synset': 'white_whale.n.01', 'name': 'white_whale'}, {'id': 3291, 'synset': 'sea_cow.n.01', 'name': 'sea_cow'}, {'id': 3292, 'synset': 'dugong.n.01', 'name': 'dugong'}, {'id': 3293, 'synset': "steller's_sea_cow.n.01", 'name': "Steller's_sea_cow"}, {'id': 3294, 'synset': 'carnivore.n.01', 'name': 'carnivore'}, {'id': 3295, 'synset': 'omnivore.n.02', 'name': 'omnivore'}, {'id': 3296, 'synset': 'pinniped_mammal.n.01', 'name': 'pinniped_mammal'}, {'id': 3297, 'synset': 'seal.n.09', 'name': 'seal'}, {'id': 3298, 'synset': 'crabeater_seal.n.01', 'name': 'crabeater_seal'}, {'id': 3299, 'synset': 'eared_seal.n.01', 'name': 'eared_seal'}, {'id': 3300, 'synset': 'fur_seal.n.02', 'name': 'fur_seal'}, {'id': 3301, 'synset': 'guadalupe_fur_seal.n.01', 'name': 'guadalupe_fur_seal'}, {'id': 3302, 'synset': 'fur_seal.n.01', 'name': 'fur_seal'}, {'id': 3303, 'synset': 'alaska_fur_seal.n.01', 'name': 'Alaska_fur_seal'}, {'id': 3304, 'synset': 'sea_lion.n.01', 'name': 'sea_lion'}, {'id': 3305, 'synset': 'south_american_sea_lion.n.01', 'name': 'South_American_sea_lion'}, {'id': 3306, 'synset': 'california_sea_lion.n.01', 'name': 'California_sea_lion'}, {'id': 3307, 'synset': 'australian_sea_lion.n.01', 'name': 'Australian_sea_lion'}, {'id': 3308, 'synset': 'steller_sea_lion.n.01', 'name': 'Steller_sea_lion'}, {'id': 3309, 'synset': 'earless_seal.n.01', 'name': 'earless_seal'}, {'id': 3310, 'synset': 'harbor_seal.n.01', 'name': 'harbor_seal'}, {'id': 3311, 'synset': 'harp_seal.n.01', 'name': 'harp_seal'}, {'id': 3312, 'synset': 'elephant_seal.n.01', 'name': 'elephant_seal'}, {'id': 3313, 'synset': 'bearded_seal.n.01', 'name': 'bearded_seal'}, {'id': 3314, 'synset': 'hooded_seal.n.01', 'name': 'hooded_seal'}, {'id': 3315, 'synset': 'atlantic_walrus.n.01', 'name': 'Atlantic_walrus'}, {'id': 3316, 'synset': 'pacific_walrus.n.01', 'name': 'Pacific_walrus'}, {'id': 3317, 'synset': 'fissipedia.n.01', 'name': 'Fissipedia'}, {'id': 3318, 'synset': 'fissiped_mammal.n.01', 'name': 'fissiped_mammal'}, {'id': 3319, 'synset': 'aardvark.n.01', 'name': 'aardvark'}, {'id': 3320, 'synset': 'canine.n.02', 'name': 'canine'}, {'id': 3321, 'synset': 'bitch.n.04', 'name': 'bitch'}, {'id': 3322, 'synset': 'brood_bitch.n.01', 'name': 'brood_bitch'}, {'id': 3323, 'synset': 'pooch.n.01', 'name': 'pooch'}, {'id': 3324, 'synset': 'cur.n.01', 'name': 'cur'}, {'id': 3325, 'synset': 'feist.n.01', 'name': 'feist'}, {'id': 3326, 'synset': 'pariah_dog.n.01', 'name': 'pariah_dog'}, {'id': 3327, 'synset': 'lapdog.n.01', 'name': 'lapdog'}, {'id': 3328, 'synset': 'toy_dog.n.01', 'name': 'toy_dog'}, {'id': 3329, 'synset': 'chihuahua.n.03', 'name': 'Chihuahua'}, {'id': 3330, 'synset': 'japanese_spaniel.n.01', 'name': 'Japanese_spaniel'}, {'id': 3331, 'synset': 'maltese_dog.n.01', 'name': 'Maltese_dog'}, {'id': 3332, 'synset': 'pekinese.n.01', 'name': 'Pekinese'}, {'id': 3333, 'synset': 'shih-tzu.n.01', 'name': 'Shih-Tzu'}, {'id': 3334, 'synset': 'toy_spaniel.n.01', 'name': 'toy_spaniel'}, {'id': 3335, 'synset': 'english_toy_spaniel.n.01', 'name': 'English_toy_spaniel'}, {'id': 3336, 'synset': 'blenheim_spaniel.n.01', 'name': 'Blenheim_spaniel'}, {'id': 3337, 'synset': 'king_charles_spaniel.n.01', 'name': 'King_Charles_spaniel'}, {'id': 3338, 'synset': 'papillon.n.01', 'name': 'papillon'}, {'id': 3339, 'synset': 'toy_terrier.n.01', 'name': 'toy_terrier'}, {'id': 3340, 'synset': 'hunting_dog.n.01', 'name': 'hunting_dog'}, {'id': 3341, 'synset': 'courser.n.03', 'name': 'courser'}, {'id': 3342, 'synset': 'rhodesian_ridgeback.n.01', 'name': 'Rhodesian_ridgeback'}, {'id': 3343, 'synset': 'hound.n.01', 'name': 'hound'}, {'id': 3344, 'synset': 'afghan_hound.n.01', 'name': 'Afghan_hound'}, {'id': 3345, 'synset': 'basset.n.01', 'name': 'basset'}, {'id': 3346, 'synset': 'beagle.n.01', 'name': 'beagle'}, {'id': 3347, 'synset': 'bloodhound.n.01', 'name': 'bloodhound'}, {'id': 3348, 'synset': 'bluetick.n.01', 'name': 'bluetick'}, {'id': 3349, 'synset': 'boarhound.n.01', 'name': 'boarhound'}, {'id': 3350, 'synset': 'coonhound.n.01', 'name': 'coonhound'}, {'id': 3351, 'synset': 'coondog.n.01', 'name': 'coondog'}, {'id': 3352, 'synset': 'black-and-tan_coonhound.n.01', 'name': 'black-and-tan_coonhound'}, {'id': 3353, 'synset': 'dachshund.n.01', 'name': 'dachshund'}, {'id': 3354, 'synset': 'sausage_dog.n.01', 'name': 'sausage_dog'}, {'id': 3355, 'synset': 'foxhound.n.01', 'name': 'foxhound'}, {'id': 3356, 'synset': 'american_foxhound.n.01', 'name': 'American_foxhound'}, {'id': 3357, 'synset': 'walker_hound.n.01', 'name': 'Walker_hound'}, {'id': 3358, 'synset': 'english_foxhound.n.01', 'name': 'English_foxhound'}, {'id': 3359, 'synset': 'harrier.n.02', 'name': 'harrier'}, {'id': 3360, 'synset': 'plott_hound.n.01', 'name': 'Plott_hound'}, {'id': 3361, 'synset': 'redbone.n.01', 'name': 'redbone'}, {'id': 3362, 'synset': 'wolfhound.n.01', 'name': 'wolfhound'}, {'id': 3363, 'synset': 'borzoi.n.01', 'name': 'borzoi'}, {'id': 3364, 'synset': 'irish_wolfhound.n.01', 'name': 'Irish_wolfhound'}, {'id': 3365, 'synset': 'greyhound.n.01', 'name': 'greyhound'}, {'id': 3366, 'synset': 'italian_greyhound.n.01', 'name': 'Italian_greyhound'}, {'id': 3367, 'synset': 'whippet.n.01', 'name': 'whippet'}, {'id': 3368, 'synset': 'ibizan_hound.n.01', 'name': 'Ibizan_hound'}, {'id': 3369, 'synset': 'norwegian_elkhound.n.01', 'name': 'Norwegian_elkhound'}, {'id': 3370, 'synset': 'otterhound.n.01', 'name': 'otterhound'}, {'id': 3371, 'synset': 'saluki.n.01', 'name': 'Saluki'}, {'id': 3372, 'synset': 'scottish_deerhound.n.01', 'name': 'Scottish_deerhound'}, {'id': 3373, 'synset': 'staghound.n.01', 'name': 'staghound'}, {'id': 3374, 'synset': 'weimaraner.n.01', 'name': 'Weimaraner'}, {'id': 3375, 'synset': 'terrier.n.01', 'name': 'terrier'}, {'id': 3376, 'synset': 'bullterrier.n.01', 'name': 'bullterrier'}, {'id': 3377, 'synset': 'staffordshire_bullterrier.n.01', 'name': 'Staffordshire_bullterrier'}, {'id': 3378, 'synset': 'american_staffordshire_terrier.n.01', 'name': 'American_Staffordshire_terrier'}, {'id': 3379, 'synset': 'bedlington_terrier.n.01', 'name': 'Bedlington_terrier'}, {'id': 3380, 'synset': 'border_terrier.n.01', 'name': 'Border_terrier'}, {'id': 3381, 'synset': 'kerry_blue_terrier.n.01', 'name': 'Kerry_blue_terrier'}, {'id': 3382, 'synset': 'irish_terrier.n.01', 'name': 'Irish_terrier'}, {'id': 3383, 'synset': 'norfolk_terrier.n.01', 'name': 'Norfolk_terrier'}, {'id': 3384, 'synset': 'norwich_terrier.n.01', 'name': 'Norwich_terrier'}, {'id': 3385, 'synset': 'yorkshire_terrier.n.01', 'name': 'Yorkshire_terrier'}, {'id': 3386, 'synset': 'rat_terrier.n.01', 'name': 'rat_terrier'}, {'id': 3387, 'synset': 'manchester_terrier.n.01', 'name': 'Manchester_terrier'}, {'id': 3388, 'synset': 'toy_manchester.n.01', 'name': 'toy_Manchester'}, {'id': 3389, 'synset': 'fox_terrier.n.01', 'name': 'fox_terrier'}, {'id': 3390, 'synset': 'smooth-haired_fox_terrier.n.01', 'name': 'smooth-haired_fox_terrier'}, {'id': 3391, 'synset': 'wire-haired_fox_terrier.n.01', 'name': 'wire-haired_fox_terrier'}, {'id': 3392, 'synset': 'wirehair.n.01', 'name': 'wirehair'}, {'id': 3393, 'synset': 'lakeland_terrier.n.01', 'name': 'Lakeland_terrier'}, {'id': 3394, 'synset': 'welsh_terrier.n.01', 'name': 'Welsh_terrier'}, {'id': 3395, 'synset': 'sealyham_terrier.n.01', 'name': 'Sealyham_terrier'}, {'id': 3396, 'synset': 'airedale.n.01', 'name': 'Airedale'}, {'id': 3397, 'synset': 'cairn.n.02', 'name': 'cairn'}, {'id': 3398, 'synset': 'australian_terrier.n.01', 'name': 'Australian_terrier'}, {'id': 3399, 'synset': 'dandie_dinmont.n.01', 'name': 'Dandie_Dinmont'}, {'id': 3400, 'synset': 'boston_bull.n.01', 'name': 'Boston_bull'}, {'id': 3401, 'synset': 'schnauzer.n.01', 'name': 'schnauzer'}, {'id': 3402, 'synset': 'miniature_schnauzer.n.01', 'name': 'miniature_schnauzer'}, {'id': 3403, 'synset': 'giant_schnauzer.n.01', 'name': 'giant_schnauzer'}, {'id': 3404, 'synset': 'standard_schnauzer.n.01', 'name': 'standard_schnauzer'}, {'id': 3405, 'synset': 'scotch_terrier.n.01', 'name': 'Scotch_terrier'}, {'id': 3406, 'synset': 'tibetan_terrier.n.01', 'name': 'Tibetan_terrier'}, {'id': 3407, 'synset': 'silky_terrier.n.01', 'name': 'silky_terrier'}, {'id': 3408, 'synset': 'skye_terrier.n.01', 'name': 'Skye_terrier'}, {'id': 3409, 'synset': 'clydesdale_terrier.n.01', 'name': 'Clydesdale_terrier'}, {'id': 3410, 'synset': 'soft-coated_wheaten_terrier.n.01', 'name': 'soft-coated_wheaten_terrier'}, {'id': 3411, 'synset': 'west_highland_white_terrier.n.01', 'name': 'West_Highland_white_terrier'}, {'id': 3412, 'synset': 'lhasa.n.02', 'name': 'Lhasa'}, {'id': 3413, 'synset': 'sporting_dog.n.01', 'name': 'sporting_dog'}, {'id': 3414, 'synset': 'bird_dog.n.01', 'name': 'bird_dog'}, {'id': 3415, 'synset': 'water_dog.n.02', 'name': 'water_dog'}, {'id': 3416, 'synset': 'retriever.n.01', 'name': 'retriever'}, {'id': 3417, 'synset': 'flat-coated_retriever.n.01', 'name': 'flat-coated_retriever'}, {'id': 3418, 'synset': 'curly-coated_retriever.n.01', 'name': 'curly-coated_retriever'}, {'id': 3419, 'synset': 'golden_retriever.n.01', 'name': 'golden_retriever'}, {'id': 3420, 'synset': 'labrador_retriever.n.01', 'name': 'Labrador_retriever'}, {'id': 3421, 'synset': 'chesapeake_bay_retriever.n.01', 'name': 'Chesapeake_Bay_retriever'}, {'id': 3422, 'synset': 'pointer.n.04', 'name': 'pointer'}, {'id': 3423, 'synset': 'german_short-haired_pointer.n.01', 'name': 'German_short-haired_pointer'}, {'id': 3424, 'synset': 'setter.n.02', 'name': 'setter'}, {'id': 3425, 'synset': 'vizsla.n.01', 'name': 'vizsla'}, {'id': 3426, 'synset': 'english_setter.n.01', 'name': 'English_setter'}, {'id': 3427, 'synset': 'irish_setter.n.01', 'name': 'Irish_setter'}, {'id': 3428, 'synset': 'gordon_setter.n.01', 'name': 'Gordon_setter'}, {'id': 3429, 'synset': 'spaniel.n.01', 'name': 'spaniel'}, {'id': 3430, 'synset': 'brittany_spaniel.n.01', 'name': 'Brittany_spaniel'}, {'id': 3431, 'synset': 'clumber.n.01', 'name': 'clumber'}, {'id': 3432, 'synset': 'field_spaniel.n.01', 'name': 'field_spaniel'}, {'id': 3433, 'synset': 'springer_spaniel.n.01', 'name': 'springer_spaniel'}, {'id': 3434, 'synset': 'english_springer.n.01', 'name': 'English_springer'}, {'id': 3435, 'synset': 'welsh_springer_spaniel.n.01', 'name': 'Welsh_springer_spaniel'}, {'id': 3436, 'synset': 'cocker_spaniel.n.01', 'name': 'cocker_spaniel'}, {'id': 3437, 'synset': 'sussex_spaniel.n.01', 'name': 'Sussex_spaniel'}, {'id': 3438, 'synset': 'water_spaniel.n.01', 'name': 'water_spaniel'}, {'id': 3439, 'synset': 'american_water_spaniel.n.01', 'name': 'American_water_spaniel'}, {'id': 3440, 'synset': 'irish_water_spaniel.n.01', 'name': 'Irish_water_spaniel'}, {'id': 3441, 'synset': 'griffon.n.03', 'name': 'griffon'}, {'id': 3442, 'synset': 'working_dog.n.01', 'name': 'working_dog'}, {'id': 3443, 'synset': 'watchdog.n.02', 'name': 'watchdog'}, {'id': 3444, 'synset': 'kuvasz.n.01', 'name': 'kuvasz'}, {'id': 3445, 'synset': 'attack_dog.n.01', 'name': 'attack_dog'}, {'id': 3446, 'synset': 'housedog.n.01', 'name': 'housedog'}, {'id': 3447, 'synset': 'schipperke.n.01', 'name': 'schipperke'}, {'id': 3448, 'synset': 'belgian_sheepdog.n.01', 'name': 'Belgian_sheepdog'}, {'id': 3449, 'synset': 'groenendael.n.01', 'name': 'groenendael'}, {'id': 3450, 'synset': 'malinois.n.01', 'name': 'malinois'}, {'id': 3451, 'synset': 'briard.n.01', 'name': 'briard'}, {'id': 3452, 'synset': 'kelpie.n.02', 'name': 'kelpie'}, {'id': 3453, 'synset': 'komondor.n.01', 'name': 'komondor'}, {'id': 3454, 'synset': 'old_english_sheepdog.n.01', 'name': 'Old_English_sheepdog'}, {'id': 3455, 'synset': 'shetland_sheepdog.n.01', 'name': 'Shetland_sheepdog'}, {'id': 3456, 'synset': 'collie.n.01', 'name': 'collie'}, {'id': 3457, 'synset': 'border_collie.n.01', 'name': 'Border_collie'}, {'id': 3458, 'synset': 'bouvier_des_flandres.n.01', 'name': 'Bouvier_des_Flandres'}, {'id': 3459, 'synset': 'rottweiler.n.01', 'name': 'Rottweiler'}, {'id': 3460, 'synset': 'german_shepherd.n.01', 'name': 'German_shepherd'}, {'id': 3461, 'synset': 'police_dog.n.01', 'name': 'police_dog'}, {'id': 3462, 'synset': 'pinscher.n.01', 'name': 'pinscher'}, {'id': 3463, 'synset': 'doberman.n.01', 'name': 'Doberman'}, {'id': 3464, 'synset': 'miniature_pinscher.n.01', 'name': 'miniature_pinscher'}, {'id': 3465, 'synset': 'sennenhunde.n.01', 'name': 'Sennenhunde'}, {'id': 3466, 'synset': 'greater_swiss_mountain_dog.n.01', 'name': 'Greater_Swiss_Mountain_dog'}, {'id': 3467, 'synset': 'bernese_mountain_dog.n.01', 'name': 'Bernese_mountain_dog'}, {'id': 3468, 'synset': 'appenzeller.n.01', 'name': 'Appenzeller'}, {'id': 3469, 'synset': 'entlebucher.n.01', 'name': 'EntleBucher'}, {'id': 3470, 'synset': 'boxer.n.04', 'name': 'boxer'}, {'id': 3471, 'synset': 'mastiff.n.01', 'name': 'mastiff'}, {'id': 3472, 'synset': 'bull_mastiff.n.01', 'name': 'bull_mastiff'}, {'id': 3473, 'synset': 'tibetan_mastiff.n.01', 'name': 'Tibetan_mastiff'}, {'id': 3474, 'synset': 'french_bulldog.n.01', 'name': 'French_bulldog'}, {'id': 3475, 'synset': 'great_dane.n.01', 'name': 'Great_Dane'}, {'id': 3476, 'synset': 'guide_dog.n.01', 'name': 'guide_dog'}, {'id': 3477, 'synset': 'seeing_eye_dog.n.01', 'name': 'Seeing_Eye_dog'}, {'id': 3478, 'synset': 'hearing_dog.n.01', 'name': 'hearing_dog'}, {'id': 3479, 'synset': 'saint_bernard.n.01', 'name': 'Saint_Bernard'}, {'id': 3480, 'synset': 'seizure-alert_dog.n.01', 'name': 'seizure-alert_dog'}, {'id': 3481, 'synset': 'sled_dog.n.01', 'name': 'sled_dog'}, {'id': 3482, 'synset': 'eskimo_dog.n.01', 'name': 'Eskimo_dog'}, {'id': 3483, 'synset': 'malamute.n.01', 'name': 'malamute'}, {'id': 3484, 'synset': 'siberian_husky.n.01', 'name': 'Siberian_husky'}, {'id': 3485, 'synset': 'liver-spotted_dalmatian.n.01', 'name': 'liver-spotted_dalmatian'}, {'id': 3486, 'synset': 'affenpinscher.n.01', 'name': 'affenpinscher'}, {'id': 3487, 'synset': 'basenji.n.01', 'name': 'basenji'}, {'id': 3488, 'synset': 'leonberg.n.01', 'name': 'Leonberg'}, {'id': 3489, 'synset': 'newfoundland.n.01', 'name': 'Newfoundland'}, {'id': 3490, 'synset': 'great_pyrenees.n.01', 'name': 'Great_Pyrenees'}, {'id': 3491, 'synset': 'spitz.n.01', 'name': 'spitz'}, {'id': 3492, 'synset': 'samoyed.n.03', 'name': 'Samoyed'}, {'id': 3493, 'synset': 'pomeranian.n.01', 'name': 'Pomeranian'}, {'id': 3494, 'synset': 'chow.n.03', 'name': 'chow'}, {'id': 3495, 'synset': 'keeshond.n.01', 'name': 'keeshond'}, {'id': 3496, 'synset': 'griffon.n.02', 'name': 'griffon'}, {'id': 3497, 'synset': 'brabancon_griffon.n.01', 'name': 'Brabancon_griffon'}, {'id': 3498, 'synset': 'corgi.n.01', 'name': 'corgi'}, {'id': 3499, 'synset': 'pembroke.n.01', 'name': 'Pembroke'}, {'id': 3500, 'synset': 'cardigan.n.02', 'name': 'Cardigan'}, {'id': 3501, 'synset': 'poodle.n.01', 'name': 'poodle'}, {'id': 3502, 'synset': 'toy_poodle.n.01', 'name': 'toy_poodle'}, {'id': 3503, 'synset': 'miniature_poodle.n.01', 'name': 'miniature_poodle'}, {'id': 3504, 'synset': 'standard_poodle.n.01', 'name': 'standard_poodle'}, {'id': 3505, 'synset': 'large_poodle.n.01', 'name': 'large_poodle'}, {'id': 3506, 'synset': 'mexican_hairless.n.01', 'name': 'Mexican_hairless'}, {'id': 3507, 'synset': 'timber_wolf.n.01', 'name': 'timber_wolf'}, {'id': 3508, 'synset': 'white_wolf.n.01', 'name': 'white_wolf'}, {'id': 3509, 'synset': 'red_wolf.n.01', 'name': 'red_wolf'}, {'id': 3510, 'synset': 'coyote.n.01', 'name': 'coyote'}, {'id': 3511, 'synset': 'coydog.n.01', 'name': 'coydog'}, {'id': 3512, 'synset': 'jackal.n.01', 'name': 'jackal'}, {'id': 3513, 'synset': 'wild_dog.n.01', 'name': 'wild_dog'}, {'id': 3514, 'synset': 'dingo.n.01', 'name': 'dingo'}, {'id': 3515, 'synset': 'dhole.n.01', 'name': 'dhole'}, {'id': 3516, 'synset': 'crab-eating_dog.n.01', 'name': 'crab-eating_dog'}, {'id': 3517, 'synset': 'raccoon_dog.n.01', 'name': 'raccoon_dog'}, {'id': 3518, 'synset': 'african_hunting_dog.n.01', 'name': 'African_hunting_dog'}, {'id': 3519, 'synset': 'hyena.n.01', 'name': 'hyena'}, {'id': 3520, 'synset': 'striped_hyena.n.01', 'name': 'striped_hyena'}, {'id': 3521, 'synset': 'brown_hyena.n.01', 'name': 'brown_hyena'}, {'id': 3522, 'synset': 'spotted_hyena.n.01', 'name': 'spotted_hyena'}, {'id': 3523, 'synset': 'aardwolf.n.01', 'name': 'aardwolf'}, {'id': 3524, 'synset': 'fox.n.01', 'name': 'fox'}, {'id': 3525, 'synset': 'vixen.n.02', 'name': 'vixen'}, {'id': 3526, 'synset': 'reynard.n.01', 'name': 'Reynard'}, {'id': 3527, 'synset': 'red_fox.n.03', 'name': 'red_fox'}, {'id': 3528, 'synset': 'black_fox.n.01', 'name': 'black_fox'}, {'id': 3529, 'synset': 'silver_fox.n.01', 'name': 'silver_fox'}, {'id': 3530, 'synset': 'red_fox.n.02', 'name': 'red_fox'}, {'id': 3531, 'synset': 'kit_fox.n.02', 'name': 'kit_fox'}, {'id': 3532, 'synset': 'kit_fox.n.01', 'name': 'kit_fox'}, {'id': 3533, 'synset': 'arctic_fox.n.01', 'name': 'Arctic_fox'}, {'id': 3534, 'synset': 'blue_fox.n.01', 'name': 'blue_fox'}, {'id': 3535, 'synset': 'grey_fox.n.01', 'name': 'grey_fox'}, {'id': 3536, 'synset': 'feline.n.01', 'name': 'feline'}, {'id': 3537, 'synset': 'domestic_cat.n.01', 'name': 'domestic_cat'}, {'id': 3538, 'synset': 'kitty.n.04', 'name': 'kitty'}, {'id': 3539, 'synset': 'mouser.n.01', 'name': 'mouser'}, {'id': 3540, 'synset': 'alley_cat.n.01', 'name': 'alley_cat'}, {'id': 3541, 'synset': 'stray.n.01', 'name': 'stray'}, {'id': 3542, 'synset': 'tom.n.02', 'name': 'tom'}, {'id': 3543, 'synset': 'gib.n.02', 'name': 'gib'}, {'id': 3544, 'synset': 'tabby.n.02', 'name': 'tabby'}, {'id': 3545, 'synset': 'tabby.n.01', 'name': 'tabby'}, {'id': 3546, 'synset': 'tiger_cat.n.02', 'name': 'tiger_cat'}, {'id': 3547, 'synset': 'tortoiseshell.n.03', 'name': 'tortoiseshell'}, {'id': 3548, 'synset': 'persian_cat.n.01', 'name': 'Persian_cat'}, {'id': 3549, 'synset': 'angora.n.04', 'name': 'Angora'}, {'id': 3550, 'synset': 'siamese_cat.n.01', 'name': 'Siamese_cat'}, {'id': 3551, 'synset': 'blue_point_siamese.n.01', 'name': 'blue_point_Siamese'}, {'id': 3552, 'synset': 'burmese_cat.n.01', 'name': 'Burmese_cat'}, {'id': 3553, 'synset': 'egyptian_cat.n.01', 'name': 'Egyptian_cat'}, {'id': 3554, 'synset': 'maltese.n.03', 'name': 'Maltese'}, {'id': 3555, 'synset': 'abyssinian.n.01', 'name': 'Abyssinian'}, {'id': 3556, 'synset': 'manx.n.02', 'name': 'Manx'}, {'id': 3557, 'synset': 'wildcat.n.03', 'name': 'wildcat'}, {'id': 3558, 'synset': 'sand_cat.n.01', 'name': 'sand_cat'}, {'id': 3559, 'synset': 'european_wildcat.n.01', 'name': 'European_wildcat'}, {'id': 3560, 'synset': 'ocelot.n.01', 'name': 'ocelot'}, {'id': 3561, 'synset': 'jaguarundi.n.01', 'name': 'jaguarundi'}, {'id': 3562, 'synset': 'kaffir_cat.n.01', 'name': 'kaffir_cat'}, {'id': 3563, 'synset': 'jungle_cat.n.01', 'name': 'jungle_cat'}, {'id': 3564, 'synset': 'serval.n.01', 'name': 'serval'}, {'id': 3565, 'synset': 'leopard_cat.n.01', 'name': 'leopard_cat'}, {'id': 3566, 'synset': 'margay.n.01', 'name': 'margay'}, {'id': 3567, 'synset': 'manul.n.01', 'name': 'manul'}, {'id': 3568, 'synset': 'lynx.n.02', 'name': 'lynx'}, {'id': 3569, 'synset': 'common_lynx.n.01', 'name': 'common_lynx'}, {'id': 3570, 'synset': 'canada_lynx.n.01', 'name': 'Canada_lynx'}, {'id': 3571, 'synset': 'bobcat.n.01', 'name': 'bobcat'}, {'id': 3572, 'synset': 'spotted_lynx.n.01', 'name': 'spotted_lynx'}, {'id': 3573, 'synset': 'caracal.n.01', 'name': 'caracal'}, {'id': 3574, 'synset': 'big_cat.n.01', 'name': 'big_cat'}, {'id': 3575, 'synset': 'leopard.n.02', 'name': 'leopard'}, {'id': 3576, 'synset': 'leopardess.n.01', 'name': 'leopardess'}, {'id': 3577, 'synset': 'panther.n.02', 'name': 'panther'}, {'id': 3578, 'synset': 'snow_leopard.n.01', 'name': 'snow_leopard'}, {'id': 3579, 'synset': 'jaguar.n.01', 'name': 'jaguar'}, {'id': 3580, 'synset': 'lioness.n.01', 'name': 'lioness'}, {'id': 3581, 'synset': 'lionet.n.01', 'name': 'lionet'}, {'id': 3582, 'synset': 'bengal_tiger.n.01', 'name': 'Bengal_tiger'}, {'id': 3583, 'synset': 'tigress.n.01', 'name': 'tigress'}, {'id': 3584, 'synset': 'liger.n.01', 'name': 'liger'}, {'id': 3585, 'synset': 'tiglon.n.01', 'name': 'tiglon'}, {'id': 3586, 'synset': 'cheetah.n.01', 'name': 'cheetah'}, {'id': 3587, 'synset': 'saber-toothed_tiger.n.01', 'name': 'saber-toothed_tiger'}, {'id': 3588, 'synset': 'smiledon_californicus.n.01', 'name': 'Smiledon_californicus'}, {'id': 3589, 'synset': 'brown_bear.n.01', 'name': 'brown_bear'}, {'id': 3590, 'synset': 'bruin.n.01', 'name': 'bruin'}, {'id': 3591, 'synset': 'syrian_bear.n.01', 'name': 'Syrian_bear'}, {'id': 3592, 'synset': 'alaskan_brown_bear.n.01', 'name': 'Alaskan_brown_bear'}, {'id': 3593, 'synset': 'american_black_bear.n.01', 'name': 'American_black_bear'}, {'id': 3594, 'synset': 'cinnamon_bear.n.01', 'name': 'cinnamon_bear'}, {'id': 3595, 'synset': 'asiatic_black_bear.n.01', 'name': 'Asiatic_black_bear'}, {'id': 3596, 'synset': 'sloth_bear.n.01', 'name': 'sloth_bear'}, {'id': 3597, 'synset': 'viverrine.n.01', 'name': 'viverrine'}, {'id': 3598, 'synset': 'civet.n.01', 'name': 'civet'}, {'id': 3599, 'synset': 'large_civet.n.01', 'name': 'large_civet'}, {'id': 3600, 'synset': 'small_civet.n.01', 'name': 'small_civet'}, {'id': 3601, 'synset': 'binturong.n.01', 'name': 'binturong'}, {'id': 3602, 'synset': 'cryptoprocta.n.01', 'name': 'Cryptoprocta'}, {'id': 3603, 'synset': 'fossa.n.03', 'name': 'fossa'}, {'id': 3604, 'synset': 'fanaloka.n.01', 'name': 'fanaloka'}, {'id': 3605, 'synset': 'genet.n.03', 'name': 'genet'}, {'id': 3606, 'synset': 'banded_palm_civet.n.01', 'name': 'banded_palm_civet'}, {'id': 3607, 'synset': 'mongoose.n.01', 'name': 'mongoose'}, {'id': 3608, 'synset': 'indian_mongoose.n.01', 'name': 'Indian_mongoose'}, {'id': 3609, 'synset': 'ichneumon.n.01', 'name': 'ichneumon'}, {'id': 3610, 'synset': 'palm_cat.n.01', 'name': 'palm_cat'}, {'id': 3611, 'synset': 'meerkat.n.01', 'name': 'meerkat'}, {'id': 3612, 'synset': 'slender-tailed_meerkat.n.01', 'name': 'slender-tailed_meerkat'}, {'id': 3613, 'synset': 'suricate.n.01', 'name': 'suricate'}, {'id': 3614, 'synset': 'fruit_bat.n.01', 'name': 'fruit_bat'}, {'id': 3615, 'synset': 'flying_fox.n.01', 'name': 'flying_fox'}, {'id': 3616, 'synset': 'pteropus_capestratus.n.01', 'name': 'Pteropus_capestratus'}, {'id': 3617, 'synset': 'pteropus_hypomelanus.n.01', 'name': 'Pteropus_hypomelanus'}, {'id': 3618, 'synset': 'harpy.n.03', 'name': 'harpy'}, {'id': 3619, 'synset': 'cynopterus_sphinx.n.01', 'name': 'Cynopterus_sphinx'}, {'id': 3620, 'synset': 'carnivorous_bat.n.01', 'name': 'carnivorous_bat'}, {'id': 3621, 'synset': 'mouse-eared_bat.n.01', 'name': 'mouse-eared_bat'}, {'id': 3622, 'synset': 'leafnose_bat.n.01', 'name': 'leafnose_bat'}, {'id': 3623, 'synset': 'macrotus.n.01', 'name': 'macrotus'}, {'id': 3624, 'synset': 'spearnose_bat.n.01', 'name': 'spearnose_bat'}, {'id': 3625, 'synset': 'phyllostomus_hastatus.n.01', 'name': 'Phyllostomus_hastatus'}, {'id': 3626, 'synset': 'hognose_bat.n.01', 'name': 'hognose_bat'}, {'id': 3627, 'synset': 'horseshoe_bat.n.02', 'name': 'horseshoe_bat'}, {'id': 3628, 'synset': 'horseshoe_bat.n.01', 'name': 'horseshoe_bat'}, {'id': 3629, 'synset': 'orange_bat.n.01', 'name': 'orange_bat'}, {'id': 3630, 'synset': 'false_vampire.n.01', 'name': 'false_vampire'}, {'id': 3631, 'synset': 'big-eared_bat.n.01', 'name': 'big-eared_bat'}, {'id': 3632, 'synset': 'vespertilian_bat.n.01', 'name': 'vespertilian_bat'}, {'id': 3633, 'synset': 'frosted_bat.n.01', 'name': 'frosted_bat'}, {'id': 3634, 'synset': 'red_bat.n.01', 'name': 'red_bat'}, {'id': 3635, 'synset': 'brown_bat.n.01', 'name': 'brown_bat'}, {'id': 3636, 'synset': 'little_brown_bat.n.01', 'name': 'little_brown_bat'}, {'id': 3637, 'synset': 'cave_myotis.n.01', 'name': 'cave_myotis'}, {'id': 3638, 'synset': 'big_brown_bat.n.01', 'name': 'big_brown_bat'}, {'id': 3639, 'synset': 'serotine.n.01', 'name': 'serotine'}, {'id': 3640, 'synset': 'pallid_bat.n.01', 'name': 'pallid_bat'}, {'id': 3641, 'synset': 'pipistrelle.n.01', 'name': 'pipistrelle'}, {'id': 3642, 'synset': 'eastern_pipistrel.n.01', 'name': 'eastern_pipistrel'}, {'id': 3643, 'synset': 'jackass_bat.n.01', 'name': 'jackass_bat'}, {'id': 3644, 'synset': 'long-eared_bat.n.01', 'name': 'long-eared_bat'}, {'id': 3645, 'synset': 'western_big-eared_bat.n.01', 'name': 'western_big-eared_bat'}, {'id': 3646, 'synset': 'freetail.n.01', 'name': 'freetail'}, {'id': 3647, 'synset': 'guano_bat.n.01', 'name': 'guano_bat'}, {'id': 3648, 'synset': 'pocketed_bat.n.01', 'name': 'pocketed_bat'}, {'id': 3649, 'synset': 'mastiff_bat.n.01', 'name': 'mastiff_bat'}, {'id': 3650, 'synset': 'vampire_bat.n.01', 'name': 'vampire_bat'}, {'id': 3651, 'synset': 'desmodus_rotundus.n.01', 'name': 'Desmodus_rotundus'}, {'id': 3652, 'synset': 'hairy-legged_vampire_bat.n.01', 'name': 'hairy-legged_vampire_bat'}, {'id': 3653, 'synset': 'predator.n.02', 'name': 'predator'}, {'id': 3654, 'synset': 'prey.n.02', 'name': 'prey'}, {'id': 3655, 'synset': 'game.n.04', 'name': 'game'}, {'id': 3656, 'synset': 'big_game.n.01', 'name': 'big_game'}, {'id': 3657, 'synset': 'game_bird.n.01', 'name': 'game_bird'}, {'id': 3658, 'synset': 'fossorial_mammal.n.01', 'name': 'fossorial_mammal'}, {'id': 3659, 'synset': 'tetrapod.n.01', 'name': 'tetrapod'}, {'id': 3660, 'synset': 'quadruped.n.01', 'name': 'quadruped'}, {'id': 3661, 'synset': 'hexapod.n.01', 'name': 'hexapod'}, {'id': 3662, 'synset': 'biped.n.01', 'name': 'biped'}, {'id': 3663, 'synset': 'insect.n.01', 'name': 'insect'}, {'id': 3664, 'synset': 'social_insect.n.01', 'name': 'social_insect'}, {'id': 3665, 'synset': 'holometabola.n.01', 'name': 'holometabola'}, {'id': 3666, 'synset': 'defoliator.n.01', 'name': 'defoliator'}, {'id': 3667, 'synset': 'pollinator.n.01', 'name': 'pollinator'}, {'id': 3668, 'synset': 'gallfly.n.03', 'name': 'gallfly'}, {'id': 3669, 'synset': 'scorpion_fly.n.01', 'name': 'scorpion_fly'}, {'id': 3670, 'synset': 'hanging_fly.n.01', 'name': 'hanging_fly'}, {'id': 3671, 'synset': 'collembolan.n.01', 'name': 'collembolan'}, {'id': 3672, 'synset': 'tiger_beetle.n.01', 'name': 'tiger_beetle'}, {'id': 3673, 'synset': 'two-spotted_ladybug.n.01', 'name': 'two-spotted_ladybug'}, {'id': 3674, 'synset': 'mexican_bean_beetle.n.01', 'name': 'Mexican_bean_beetle'}, {'id': 3675, 'synset': 'hippodamia_convergens.n.01', 'name': 'Hippodamia_convergens'}, {'id': 3676, 'synset': 'vedalia.n.01', 'name': 'vedalia'}, {'id': 3677, 'synset': 'ground_beetle.n.01', 'name': 'ground_beetle'}, {'id': 3678, 'synset': 'bombardier_beetle.n.01', 'name': 'bombardier_beetle'}, {'id': 3679, 'synset': 'calosoma.n.01', 'name': 'calosoma'}, {'id': 3680, 'synset': 'searcher.n.03', 'name': 'searcher'}, {'id': 3681, 'synset': 'firefly.n.02', 'name': 'firefly'}, {'id': 3682, 'synset': 'glowworm.n.01', 'name': 'glowworm'}, {'id': 3683, 'synset': 'long-horned_beetle.n.01', 'name': 'long-horned_beetle'}, {'id': 3684, 'synset': 'sawyer.n.02', 'name': 'sawyer'}, {'id': 3685, 'synset': 'pine_sawyer.n.01', 'name': 'pine_sawyer'}, {'id': 3686, 'synset': 'leaf_beetle.n.01', 'name': 'leaf_beetle'}, {'id': 3687, 'synset': 'flea_beetle.n.01', 'name': 'flea_beetle'}, {'id': 3688, 'synset': 'colorado_potato_beetle.n.01', 'name': 'Colorado_potato_beetle'}, {'id': 3689, 'synset': 'carpet_beetle.n.01', 'name': 'carpet_beetle'}, {'id': 3690, 'synset': 'buffalo_carpet_beetle.n.01', 'name': 'buffalo_carpet_beetle'}, {'id': 3691, 'synset': 'black_carpet_beetle.n.01', 'name': 'black_carpet_beetle'}, {'id': 3692, 'synset': 'clerid_beetle.n.01', 'name': 'clerid_beetle'}, {'id': 3693, 'synset': 'bee_beetle.n.01', 'name': 'bee_beetle'}, {'id': 3694, 'synset': 'lamellicorn_beetle.n.01', 'name': 'lamellicorn_beetle'}, {'id': 3695, 'synset': 'scarabaeid_beetle.n.01', 'name': 'scarabaeid_beetle'}, {'id': 3696, 'synset': 'dung_beetle.n.01', 'name': 'dung_beetle'}, {'id': 3697, 'synset': 'scarab.n.01', 'name': 'scarab'}, {'id': 3698, 'synset': 'tumblebug.n.01', 'name': 'tumblebug'}, {'id': 3699, 'synset': 'dorbeetle.n.01', 'name': 'dorbeetle'}, {'id': 3700, 'synset': 'june_beetle.n.01', 'name': 'June_beetle'}, {'id': 3701, 'synset': 'green_june_beetle.n.01', 'name': 'green_June_beetle'}, {'id': 3702, 'synset': 'japanese_beetle.n.01', 'name': 'Japanese_beetle'}, {'id': 3703, 'synset': 'oriental_beetle.n.01', 'name': 'Oriental_beetle'}, {'id': 3704, 'synset': 'rhinoceros_beetle.n.01', 'name': 'rhinoceros_beetle'}, {'id': 3705, 'synset': 'melolonthid_beetle.n.01', 'name': 'melolonthid_beetle'}, {'id': 3706, 'synset': 'cockchafer.n.01', 'name': 'cockchafer'}, {'id': 3707, 'synset': 'rose_chafer.n.02', 'name': 'rose_chafer'}, {'id': 3708, 'synset': 'rose_chafer.n.01', 'name': 'rose_chafer'}, {'id': 3709, 'synset': 'stag_beetle.n.01', 'name': 'stag_beetle'}, {'id': 3710, 'synset': 'elaterid_beetle.n.01', 'name': 'elaterid_beetle'}, {'id': 3711, 'synset': 'click_beetle.n.01', 'name': 'click_beetle'}, {'id': 3712, 'synset': 'firefly.n.01', 'name': 'firefly'}, {'id': 3713, 'synset': 'wireworm.n.01', 'name': 'wireworm'}, {'id': 3714, 'synset': 'water_beetle.n.01', 'name': 'water_beetle'}, {'id': 3715, 'synset': 'whirligig_beetle.n.01', 'name': 'whirligig_beetle'}, {'id': 3716, 'synset': 'deathwatch_beetle.n.01', 'name': 'deathwatch_beetle'}, {'id': 3717, 'synset': 'weevil.n.01', 'name': 'weevil'}, {'id': 3718, 'synset': 'snout_beetle.n.01', 'name': 'snout_beetle'}, {'id': 3719, 'synset': 'boll_weevil.n.01', 'name': 'boll_weevil'}, {'id': 3720, 'synset': 'blister_beetle.n.01', 'name': 'blister_beetle'}, {'id': 3721, 'synset': 'oil_beetle.n.01', 'name': 'oil_beetle'}, {'id': 3722, 'synset': 'spanish_fly.n.01', 'name': 'Spanish_fly'}, {'id': 3723, 'synset': 'dutch-elm_beetle.n.01', 'name': 'Dutch-elm_beetle'}, {'id': 3724, 'synset': 'bark_beetle.n.01', 'name': 'bark_beetle'}, {'id': 3725, 'synset': 'spruce_bark_beetle.n.01', 'name': 'spruce_bark_beetle'}, {'id': 3726, 'synset': 'rove_beetle.n.01', 'name': 'rove_beetle'}, {'id': 3727, 'synset': 'darkling_beetle.n.01', 'name': 'darkling_beetle'}, {'id': 3728, 'synset': 'mealworm.n.01', 'name': 'mealworm'}, {'id': 3729, 'synset': 'flour_beetle.n.01', 'name': 'flour_beetle'}, {'id': 3730, 'synset': 'seed_beetle.n.01', 'name': 'seed_beetle'}, {'id': 3731, 'synset': 'pea_weevil.n.01', 'name': 'pea_weevil'}, {'id': 3732, 'synset': 'bean_weevil.n.01', 'name': 'bean_weevil'}, {'id': 3733, 'synset': 'rice_weevil.n.01', 'name': 'rice_weevil'}, {'id': 3734, 'synset': 'asian_longhorned_beetle.n.01', 'name': 'Asian_longhorned_beetle'}, {'id': 3735, 'synset': 'web_spinner.n.01', 'name': 'web_spinner'}, {'id': 3736, 'synset': 'louse.n.01', 'name': 'louse'}, {'id': 3737, 'synset': 'common_louse.n.01', 'name': 'common_louse'}, {'id': 3738, 'synset': 'head_louse.n.01', 'name': 'head_louse'}, {'id': 3739, 'synset': 'body_louse.n.01', 'name': 'body_louse'}, {'id': 3740, 'synset': 'crab_louse.n.01', 'name': 'crab_louse'}, {'id': 3741, 'synset': 'bird_louse.n.01', 'name': 'bird_louse'}, {'id': 3742, 'synset': 'flea.n.01', 'name': 'flea'}, {'id': 3743, 'synset': 'pulex_irritans.n.01', 'name': 'Pulex_irritans'}, {'id': 3744, 'synset': 'dog_flea.n.01', 'name': 'dog_flea'}, {'id': 3745, 'synset': 'cat_flea.n.01', 'name': 'cat_flea'}, {'id': 3746, 'synset': 'chigoe.n.01', 'name': 'chigoe'}, {'id': 3747, 'synset': 'sticktight.n.02', 'name': 'sticktight'}, {'id': 3748, 'synset': 'dipterous_insect.n.01', 'name': 'dipterous_insect'}, {'id': 3749, 'synset': 'gall_midge.n.01', 'name': 'gall_midge'}, {'id': 3750, 'synset': 'hessian_fly.n.01', 'name': 'Hessian_fly'}, {'id': 3751, 'synset': 'fly.n.01', 'name': 'fly'}, {'id': 3752, 'synset': 'housefly.n.01', 'name': 'housefly'}, {'id': 3753, 'synset': 'tsetse_fly.n.01', 'name': 'tsetse_fly'}, {'id': 3754, 'synset': 'blowfly.n.01', 'name': 'blowfly'}, {'id': 3755, 'synset': 'bluebottle.n.02', 'name': 'bluebottle'}, {'id': 3756, 'synset': 'greenbottle.n.01', 'name': 'greenbottle'}, {'id': 3757, 'synset': 'flesh_fly.n.01', 'name': 'flesh_fly'}, {'id': 3758, 'synset': 'tachina_fly.n.01', 'name': 'tachina_fly'}, {'id': 3759, 'synset': 'gadfly.n.02', 'name': 'gadfly'}, {'id': 3760, 'synset': 'botfly.n.01', 'name': 'botfly'}, {'id': 3761, 'synset': 'human_botfly.n.01', 'name': 'human_botfly'}, {'id': 3762, 'synset': 'sheep_botfly.n.01', 'name': 'sheep_botfly'}, {'id': 3763, 'synset': 'warble_fly.n.01', 'name': 'warble_fly'}, {'id': 3764, 'synset': 'horsefly.n.02', 'name': 'horsefly'}, {'id': 3765, 'synset': 'bee_fly.n.01', 'name': 'bee_fly'}, {'id': 3766, 'synset': 'robber_fly.n.01', 'name': 'robber_fly'}, {'id': 3767, 'synset': 'fruit_fly.n.01', 'name': 'fruit_fly'}, {'id': 3768, 'synset': 'apple_maggot.n.01', 'name': 'apple_maggot'}, {'id': 3769, 'synset': 'mediterranean_fruit_fly.n.01', 'name': 'Mediterranean_fruit_fly'}, {'id': 3770, 'synset': 'drosophila.n.01', 'name': 'drosophila'}, {'id': 3771, 'synset': 'vinegar_fly.n.01', 'name': 'vinegar_fly'}, {'id': 3772, 'synset': 'leaf_miner.n.01', 'name': 'leaf_miner'}, {'id': 3773, 'synset': 'louse_fly.n.01', 'name': 'louse_fly'}, {'id': 3774, 'synset': 'horse_tick.n.01', 'name': 'horse_tick'}, {'id': 3775, 'synset': 'sheep_ked.n.01', 'name': 'sheep_ked'}, {'id': 3776, 'synset': 'horn_fly.n.01', 'name': 'horn_fly'}, {'id': 3777, 'synset': 'mosquito.n.01', 'name': 'mosquito'}, {'id': 3778, 'synset': 'wiggler.n.02', 'name': 'wiggler'}, {'id': 3779, 'synset': 'gnat.n.02', 'name': 'gnat'}, {'id': 3780, 'synset': 'yellow-fever_mosquito.n.01', 'name': 'yellow-fever_mosquito'}, {'id': 3781, 'synset': 'asian_tiger_mosquito.n.01', 'name': 'Asian_tiger_mosquito'}, {'id': 3782, 'synset': 'anopheline.n.01', 'name': 'anopheline'}, {'id': 3783, 'synset': 'malarial_mosquito.n.01', 'name': 'malarial_mosquito'}, {'id': 3784, 'synset': 'common_mosquito.n.01', 'name': 'common_mosquito'}, {'id': 3785, 'synset': 'culex_quinquefasciatus.n.01', 'name': 'Culex_quinquefasciatus'}, {'id': 3786, 'synset': 'gnat.n.01', 'name': 'gnat'}, {'id': 3787, 'synset': 'punkie.n.01', 'name': 'punkie'}, {'id': 3788, 'synset': 'midge.n.01', 'name': 'midge'}, {'id': 3789, 'synset': 'fungus_gnat.n.02', 'name': 'fungus_gnat'}, {'id': 3790, 'synset': 'psychodid.n.01', 'name': 'psychodid'}, {'id': 3791, 'synset': 'sand_fly.n.01', 'name': 'sand_fly'}, {'id': 3792, 'synset': 'fungus_gnat.n.01', 'name': 'fungus_gnat'}, {'id': 3793, 'synset': 'armyworm.n.03', 'name': 'armyworm'}, {'id': 3794, 'synset': 'crane_fly.n.01', 'name': 'crane_fly'}, {'id': 3795, 'synset': 'blackfly.n.02', 'name': 'blackfly'}, {'id': 3796, 'synset': 'hymenopterous_insect.n.01', 'name': 'hymenopterous_insect'}, {'id': 3797, 'synset': 'bee.n.01', 'name': 'bee'}, {'id': 3798, 'synset': 'drone.n.01', 'name': 'drone'}, {'id': 3799, 'synset': 'queen_bee.n.01', 'name': 'queen_bee'}, {'id': 3800, 'synset': 'worker.n.03', 'name': 'worker'}, {'id': 3801, 'synset': 'soldier.n.02', 'name': 'soldier'}, {'id': 3802, 'synset': 'worker_bee.n.01', 'name': 'worker_bee'}, {'id': 3803, 'synset': 'honeybee.n.01', 'name': 'honeybee'}, {'id': 3804, 'synset': 'africanized_bee.n.01', 'name': 'Africanized_bee'}, {'id': 3805, 'synset': 'black_bee.n.01', 'name': 'black_bee'}, {'id': 3806, 'synset': 'carniolan_bee.n.01', 'name': 'Carniolan_bee'}, {'id': 3807, 'synset': 'italian_bee.n.01', 'name': 'Italian_bee'}, {'id': 3808, 'synset': 'carpenter_bee.n.01', 'name': 'carpenter_bee'}, {'id': 3809, 'synset': 'bumblebee.n.01', 'name': 'bumblebee'}, {'id': 3810, 'synset': 'cuckoo-bumblebee.n.01', 'name': 'cuckoo-bumblebee'}, {'id': 3811, 'synset': 'andrena.n.01', 'name': 'andrena'}, {'id': 3812, 'synset': 'nomia_melanderi.n.01', 'name': 'Nomia_melanderi'}, {'id': 3813, 'synset': 'leaf-cutting_bee.n.01', 'name': 'leaf-cutting_bee'}, {'id': 3814, 'synset': 'mason_bee.n.01', 'name': 'mason_bee'}, {'id': 3815, 'synset': 'potter_bee.n.01', 'name': 'potter_bee'}, {'id': 3816, 'synset': 'wasp.n.02', 'name': 'wasp'}, {'id': 3817, 'synset': 'vespid.n.01', 'name': 'vespid'}, {'id': 3818, 'synset': 'paper_wasp.n.01', 'name': 'paper_wasp'}, {'id': 3819, 'synset': 'giant_hornet.n.01', 'name': 'giant_hornet'}, {'id': 3820, 'synset': 'common_wasp.n.01', 'name': 'common_wasp'}, {'id': 3821, 'synset': 'bald-faced_hornet.n.01', 'name': 'bald-faced_hornet'}, {'id': 3822, 'synset': 'yellow_jacket.n.02', 'name': 'yellow_jacket'}, {'id': 3823, 'synset': 'polistes_annularis.n.01', 'name': 'Polistes_annularis'}, {'id': 3824, 'synset': 'mason_wasp.n.02', 'name': 'mason_wasp'}, {'id': 3825, 'synset': 'potter_wasp.n.01', 'name': 'potter_wasp'}, {'id': 3826, 'synset': 'mutillidae.n.01', 'name': 'Mutillidae'}, {'id': 3827, 'synset': 'velvet_ant.n.01', 'name': 'velvet_ant'}, {'id': 3828, 'synset': 'sphecoid_wasp.n.01', 'name': 'sphecoid_wasp'}, {'id': 3829, 'synset': 'mason_wasp.n.01', 'name': 'mason_wasp'}, {'id': 3830, 'synset': 'digger_wasp.n.01', 'name': 'digger_wasp'}, {'id': 3831, 'synset': 'cicada_killer.n.01', 'name': 'cicada_killer'}, {'id': 3832, 'synset': 'mud_dauber.n.01', 'name': 'mud_dauber'}, {'id': 3833, 'synset': 'gall_wasp.n.01', 'name': 'gall_wasp'}, {'id': 3834, 'synset': 'chalcid_fly.n.01', 'name': 'chalcid_fly'}, {'id': 3835, 'synset': 'strawworm.n.02', 'name': 'strawworm'}, {'id': 3836, 'synset': 'chalcis_fly.n.01', 'name': 'chalcis_fly'}, {'id': 3837, 'synset': 'ichneumon_fly.n.01', 'name': 'ichneumon_fly'}, {'id': 3838, 'synset': 'sawfly.n.01', 'name': 'sawfly'}, {'id': 3839, 'synset': 'birch_leaf_miner.n.01', 'name': 'birch_leaf_miner'}, {'id': 3840, 'synset': 'ant.n.01', 'name': 'ant'}, {'id': 3841, 'synset': 'pharaoh_ant.n.01', 'name': 'pharaoh_ant'}, {'id': 3842, 'synset': 'little_black_ant.n.01', 'name': 'little_black_ant'}, {'id': 3843, 'synset': 'army_ant.n.01', 'name': 'army_ant'}, {'id': 3844, 'synset': 'carpenter_ant.n.01', 'name': 'carpenter_ant'}, {'id': 3845, 'synset': 'fire_ant.n.01', 'name': 'fire_ant'}, {'id': 3846, 'synset': 'wood_ant.n.01', 'name': 'wood_ant'}, {'id': 3847, 'synset': 'slave_ant.n.01', 'name': 'slave_ant'}, {'id': 3848, 'synset': 'formica_fusca.n.01', 'name': 'Formica_fusca'}, {'id': 3849, 'synset': 'slave-making_ant.n.01', 'name': 'slave-making_ant'}, {'id': 3850, 'synset': 'sanguinary_ant.n.01', 'name': 'sanguinary_ant'}, {'id': 3851, 'synset': 'bulldog_ant.n.01', 'name': 'bulldog_ant'}, {'id': 3852, 'synset': 'amazon_ant.n.01', 'name': 'Amazon_ant'}, {'id': 3853, 'synset': 'termite.n.01', 'name': 'termite'}, {'id': 3854, 'synset': 'dry-wood_termite.n.01', 'name': 'dry-wood_termite'}, {'id': 3855, 'synset': 'reticulitermes_lucifugus.n.01', 'name': 'Reticulitermes_lucifugus'}, {'id': 3856, 'synset': 'mastotermes_darwiniensis.n.01', 'name': 'Mastotermes_darwiniensis'}, {'id': 3857, 'synset': 'mastotermes_electrodominicus.n.01', 'name': 'Mastotermes_electrodominicus'}, {'id': 3858, 'synset': 'powder-post_termite.n.01', 'name': 'powder-post_termite'}, {'id': 3859, 'synset': 'orthopterous_insect.n.01', 'name': 'orthopterous_insect'}, {'id': 3860, 'synset': 'grasshopper.n.01', 'name': 'grasshopper'}, {'id': 3861, 'synset': 'short-horned_grasshopper.n.01', 'name': 'short-horned_grasshopper'}, {'id': 3862, 'synset': 'locust.n.01', 'name': 'locust'}, {'id': 3863, 'synset': 'migratory_locust.n.01', 'name': 'migratory_locust'}, {'id': 3864, 'synset': 'migratory_grasshopper.n.01', 'name': 'migratory_grasshopper'}, {'id': 3865, 'synset': 'long-horned_grasshopper.n.01', 'name': 'long-horned_grasshopper'}, {'id': 3866, 'synset': 'katydid.n.01', 'name': 'katydid'}, {'id': 3867, 'synset': 'mormon_cricket.n.01', 'name': 'mormon_cricket'}, {'id': 3868, 'synset': 'sand_cricket.n.01', 'name': 'sand_cricket'}, {'id': 3869, 'synset': 'cricket.n.01', 'name': 'cricket'}, {'id': 3870, 'synset': 'mole_cricket.n.01', 'name': 'mole_cricket'}, {'id': 3871, 'synset': 'european_house_cricket.n.01', 'name': 'European_house_cricket'}, {'id': 3872, 'synset': 'field_cricket.n.01', 'name': 'field_cricket'}, {'id': 3873, 'synset': 'tree_cricket.n.01', 'name': 'tree_cricket'}, {'id': 3874, 'synset': 'snowy_tree_cricket.n.01', 'name': 'snowy_tree_cricket'}, {'id': 3875, 'synset': 'phasmid.n.01', 'name': 'phasmid'}, {'id': 3876, 'synset': 'walking_stick.n.02', 'name': 'walking_stick'}, {'id': 3877, 'synset': 'diapheromera.n.01', 'name': 'diapheromera'}, {'id': 3878, 'synset': 'walking_leaf.n.02', 'name': 'walking_leaf'}, {'id': 3879, 'synset': 'oriental_cockroach.n.01', 'name': 'oriental_cockroach'}, {'id': 3880, 'synset': 'american_cockroach.n.01', 'name': 'American_cockroach'}, {'id': 3881, 'synset': 'australian_cockroach.n.01', 'name': 'Australian_cockroach'}, {'id': 3882, 'synset': 'german_cockroach.n.01', 'name': 'German_cockroach'}, {'id': 3883, 'synset': 'giant_cockroach.n.01', 'name': 'giant_cockroach'}, {'id': 3884, 'synset': 'mantis.n.01', 'name': 'mantis'}, {'id': 3885, 'synset': 'praying_mantis.n.01', 'name': 'praying_mantis'}, {'id': 3886, 'synset': 'bug.n.01', 'name': 'bug'}, {'id': 3887, 'synset': 'hemipterous_insect.n.01', 'name': 'hemipterous_insect'}, {'id': 3888, 'synset': 'leaf_bug.n.01', 'name': 'leaf_bug'}, {'id': 3889, 'synset': 'mirid_bug.n.01', 'name': 'mirid_bug'}, {'id': 3890, 'synset': 'four-lined_plant_bug.n.01', 'name': 'four-lined_plant_bug'}, {'id': 3891, 'synset': 'lygus_bug.n.01', 'name': 'lygus_bug'}, {'id': 3892, 'synset': 'tarnished_plant_bug.n.01', 'name': 'tarnished_plant_bug'}, {'id': 3893, 'synset': 'lace_bug.n.01', 'name': 'lace_bug'}, {'id': 3894, 'synset': 'lygaeid.n.01', 'name': 'lygaeid'}, {'id': 3895, 'synset': 'chinch_bug.n.01', 'name': 'chinch_bug'}, {'id': 3896, 'synset': 'coreid_bug.n.01', 'name': 'coreid_bug'}, {'id': 3897, 'synset': 'squash_bug.n.01', 'name': 'squash_bug'}, {'id': 3898, 'synset': 'leaf-footed_bug.n.01', 'name': 'leaf-footed_bug'}, {'id': 3899, 'synset': 'bedbug.n.01', 'name': 'bedbug'}, {'id': 3900, 'synset': 'backswimmer.n.01', 'name': 'backswimmer'}, {'id': 3901, 'synset': 'true_bug.n.01', 'name': 'true_bug'}, {'id': 3902, 'synset': 'heteropterous_insect.n.01', 'name': 'heteropterous_insect'}, {'id': 3903, 'synset': 'water_bug.n.01', 'name': 'water_bug'}, {'id': 3904, 'synset': 'giant_water_bug.n.01', 'name': 'giant_water_bug'}, {'id': 3905, 'synset': 'water_scorpion.n.01', 'name': 'water_scorpion'}, {'id': 3906, 'synset': 'water_boatman.n.01', 'name': 'water_boatman'}, {'id': 3907, 'synset': 'water_strider.n.01', 'name': 'water_strider'}, {'id': 3908, 'synset': 'common_pond-skater.n.01', 'name': 'common_pond-skater'}, {'id': 3909, 'synset': 'assassin_bug.n.01', 'name': 'assassin_bug'}, {'id': 3910, 'synset': 'conenose.n.01', 'name': 'conenose'}, {'id': 3911, 'synset': 'wheel_bug.n.01', 'name': 'wheel_bug'}, {'id': 3912, 'synset': 'firebug.n.02', 'name': 'firebug'}, {'id': 3913, 'synset': 'cotton_stainer.n.01', 'name': 'cotton_stainer'}, {'id': 3914, 'synset': 'homopterous_insect.n.01', 'name': 'homopterous_insect'}, {'id': 3915, 'synset': 'whitefly.n.01', 'name': 'whitefly'}, {'id': 3916, 'synset': 'citrus_whitefly.n.01', 'name': 'citrus_whitefly'}, {'id': 3917, 'synset': 'greenhouse_whitefly.n.01', 'name': 'greenhouse_whitefly'}, {'id': 3918, 'synset': 'sweet-potato_whitefly.n.01', 'name': 'sweet-potato_whitefly'}, {'id': 3919, 'synset': 'superbug.n.02', 'name': 'superbug'}, {'id': 3920, 'synset': 'cotton_strain.n.01', 'name': 'cotton_strain'}, {'id': 3921, 'synset': 'coccid_insect.n.01', 'name': 'coccid_insect'}, {'id': 3922, 'synset': 'scale_insect.n.01', 'name': 'scale_insect'}, {'id': 3923, 'synset': 'soft_scale.n.01', 'name': 'soft_scale'}, {'id': 3924, 'synset': 'brown_soft_scale.n.01', 'name': 'brown_soft_scale'}, {'id': 3925, 'synset': 'armored_scale.n.01', 'name': 'armored_scale'}, {'id': 3926, 'synset': 'san_jose_scale.n.01', 'name': 'San_Jose_scale'}, {'id': 3927, 'synset': 'cochineal_insect.n.01', 'name': 'cochineal_insect'}, {'id': 3928, 'synset': 'mealybug.n.01', 'name': 'mealybug'}, {'id': 3929, 'synset': 'citrophilous_mealybug.n.01', 'name': 'citrophilous_mealybug'}, {'id': 3930, 'synset': 'comstock_mealybug.n.01', 'name': 'Comstock_mealybug'}, {'id': 3931, 'synset': 'citrus_mealybug.n.01', 'name': 'citrus_mealybug'}, {'id': 3932, 'synset': 'plant_louse.n.01', 'name': 'plant_louse'}, {'id': 3933, 'synset': 'aphid.n.01', 'name': 'aphid'}, {'id': 3934, 'synset': 'apple_aphid.n.01', 'name': 'apple_aphid'}, {'id': 3935, 'synset': 'blackfly.n.01', 'name': 'blackfly'}, {'id': 3936, 'synset': 'greenfly.n.01', 'name': 'greenfly'}, {'id': 3937, 'synset': 'green_peach_aphid.n.01', 'name': 'green_peach_aphid'}, {'id': 3938, 'synset': 'ant_cow.n.01', 'name': 'ant_cow'}, {'id': 3939, 'synset': 'woolly_aphid.n.01', 'name': 'woolly_aphid'}, {'id': 3940, 'synset': 'woolly_apple_aphid.n.01', 'name': 'woolly_apple_aphid'}, {'id': 3941, 'synset': 'woolly_alder_aphid.n.01', 'name': 'woolly_alder_aphid'}, {'id': 3942, 'synset': 'adelgid.n.01', 'name': 'adelgid'}, {'id': 3943, 'synset': 'balsam_woolly_aphid.n.01', 'name': 'balsam_woolly_aphid'}, {'id': 3944, 'synset': 'spruce_gall_aphid.n.01', 'name': 'spruce_gall_aphid'}, {'id': 3945, 'synset': 'woolly_adelgid.n.01', 'name': 'woolly_adelgid'}, {'id': 3946, 'synset': 'jumping_plant_louse.n.01', 'name': 'jumping_plant_louse'}, {'id': 3947, 'synset': 'cicada.n.01', 'name': 'cicada'}, {'id': 3948, 'synset': 'dog-day_cicada.n.01', 'name': 'dog-day_cicada'}, {'id': 3949, 'synset': 'seventeen-year_locust.n.01', 'name': 'seventeen-year_locust'}, {'id': 3950, 'synset': 'spittle_insect.n.01', 'name': 'spittle_insect'}, {'id': 3951, 'synset': 'froghopper.n.01', 'name': 'froghopper'}, {'id': 3952, 'synset': 'meadow_spittlebug.n.01', 'name': 'meadow_spittlebug'}, {'id': 3953, 'synset': 'pine_spittlebug.n.01', 'name': 'pine_spittlebug'}, {'id': 3954, 'synset': 'saratoga_spittlebug.n.01', 'name': 'Saratoga_spittlebug'}, {'id': 3955, 'synset': 'leafhopper.n.01', 'name': 'leafhopper'}, {'id': 3956, 'synset': 'plant_hopper.n.01', 'name': 'plant_hopper'}, {'id': 3957, 'synset': 'treehopper.n.01', 'name': 'treehopper'}, {'id': 3958, 'synset': 'lantern_fly.n.01', 'name': 'lantern_fly'}, {'id': 3959, 'synset': 'psocopterous_insect.n.01', 'name': 'psocopterous_insect'}, {'id': 3960, 'synset': 'psocid.n.01', 'name': 'psocid'}, {'id': 3961, 'synset': 'bark-louse.n.01', 'name': 'bark-louse'}, {'id': 3962, 'synset': 'booklouse.n.01', 'name': 'booklouse'}, {'id': 3963, 'synset': 'common_booklouse.n.01', 'name': 'common_booklouse'}, {'id': 3964, 'synset': 'ephemerid.n.01', 'name': 'ephemerid'}, {'id': 3965, 'synset': 'mayfly.n.01', 'name': 'mayfly'}, {'id': 3966, 'synset': 'stonefly.n.01', 'name': 'stonefly'}, {'id': 3967, 'synset': 'neuropteron.n.01', 'name': 'neuropteron'}, {'id': 3968, 'synset': 'ant_lion.n.02', 'name': 'ant_lion'}, {'id': 3969, 'synset': 'doodlebug.n.03', 'name': 'doodlebug'}, {'id': 3970, 'synset': 'lacewing.n.01', 'name': 'lacewing'}, {'id': 3971, 'synset': 'aphid_lion.n.01', 'name': 'aphid_lion'}, {'id': 3972, 'synset': 'green_lacewing.n.01', 'name': 'green_lacewing'}, {'id': 3973, 'synset': 'brown_lacewing.n.01', 'name': 'brown_lacewing'}, {'id': 3974, 'synset': 'dobson.n.02', 'name': 'dobson'}, {'id': 3975, 'synset': 'hellgrammiate.n.01', 'name': 'hellgrammiate'}, {'id': 3976, 'synset': 'fish_fly.n.01', 'name': 'fish_fly'}, {'id': 3977, 'synset': 'alderfly.n.01', 'name': 'alderfly'}, {'id': 3978, 'synset': 'snakefly.n.01', 'name': 'snakefly'}, {'id': 3979, 'synset': 'mantispid.n.01', 'name': 'mantispid'}, {'id': 3980, 'synset': 'odonate.n.01', 'name': 'odonate'}, {'id': 3981, 'synset': 'damselfly.n.01', 'name': 'damselfly'}, {'id': 3982, 'synset': 'trichopterous_insect.n.01', 'name': 'trichopterous_insect'}, {'id': 3983, 'synset': 'caddis_fly.n.01', 'name': 'caddis_fly'}, {'id': 3984, 'synset': 'caseworm.n.01', 'name': 'caseworm'}, {'id': 3985, 'synset': 'caddisworm.n.01', 'name': 'caddisworm'}, {'id': 3986, 'synset': 'thysanuran_insect.n.01', 'name': 'thysanuran_insect'}, {'id': 3987, 'synset': 'bristletail.n.01', 'name': 'bristletail'}, {'id': 3988, 'synset': 'silverfish.n.01', 'name': 'silverfish'}, {'id': 3989, 'synset': 'firebrat.n.01', 'name': 'firebrat'}, {'id': 3990, 'synset': 'jumping_bristletail.n.01', 'name': 'jumping_bristletail'}, {'id': 3991, 'synset': 'thysanopter.n.01', 'name': 'thysanopter'}, {'id': 3992, 'synset': 'thrips.n.01', 'name': 'thrips'}, {'id': 3993, 'synset': 'tobacco_thrips.n.01', 'name': 'tobacco_thrips'}, {'id': 3994, 'synset': 'onion_thrips.n.01', 'name': 'onion_thrips'}, {'id': 3995, 'synset': 'earwig.n.01', 'name': 'earwig'}, {'id': 3996, 'synset': 'common_european_earwig.n.01', 'name': 'common_European_earwig'}, {'id': 3997, 'synset': 'lepidopterous_insect.n.01', 'name': 'lepidopterous_insect'}, {'id': 3998, 'synset': 'nymphalid.n.01', 'name': 'nymphalid'}, {'id': 3999, 'synset': 'mourning_cloak.n.01', 'name': 'mourning_cloak'}, {'id': 4000, 'synset': 'tortoiseshell.n.02', 'name': 'tortoiseshell'}, {'id': 4001, 'synset': 'painted_beauty.n.01', 'name': 'painted_beauty'}, {'id': 4002, 'synset': 'admiral.n.02', 'name': 'admiral'}, {'id': 4003, 'synset': 'red_admiral.n.01', 'name': 'red_admiral'}, {'id': 4004, 'synset': 'white_admiral.n.02', 'name': 'white_admiral'}, {'id': 4005, 'synset': 'banded_purple.n.01', 'name': 'banded_purple'}, {'id': 4006, 'synset': 'red-spotted_purple.n.01', 'name': 'red-spotted_purple'}, {'id': 4007, 'synset': 'viceroy.n.02', 'name': 'viceroy'}, {'id': 4008, 'synset': 'anglewing.n.01', 'name': 'anglewing'}, {'id': 4009, 'synset': 'ringlet.n.04', 'name': 'ringlet'}, {'id': 4010, 'synset': 'comma.n.02', 'name': 'comma'}, {'id': 4011, 'synset': 'fritillary.n.02', 'name': 'fritillary'}, {'id': 4012, 'synset': 'silverspot.n.01', 'name': 'silverspot'}, {'id': 4013, 'synset': 'emperor_butterfly.n.01', 'name': 'emperor_butterfly'}, {'id': 4014, 'synset': 'purple_emperor.n.01', 'name': 'purple_emperor'}, {'id': 4015, 'synset': 'peacock.n.01', 'name': 'peacock'}, {'id': 4016, 'synset': 'danaid.n.01', 'name': 'danaid'}, {'id': 4017, 'synset': 'monarch.n.02', 'name': 'monarch'}, {'id': 4018, 'synset': 'pierid.n.01', 'name': 'pierid'}, {'id': 4019, 'synset': 'cabbage_butterfly.n.01', 'name': 'cabbage_butterfly'}, {'id': 4020, 'synset': 'small_white.n.01', 'name': 'small_white'}, {'id': 4021, 'synset': 'large_white.n.01', 'name': 'large_white'}, {'id': 4022, 'synset': 'southern_cabbage_butterfly.n.01', 'name': 'southern_cabbage_butterfly'}, {'id': 4023, 'synset': 'sulphur_butterfly.n.01', 'name': 'sulphur_butterfly'}, {'id': 4024, 'synset': 'lycaenid.n.01', 'name': 'lycaenid'}, {'id': 4025, 'synset': 'blue.n.07', 'name': 'blue'}, {'id': 4026, 'synset': 'copper.n.05', 'name': 'copper'}, {'id': 4027, 'synset': 'american_copper.n.01', 'name': 'American_copper'}, {'id': 4028, 'synset': 'hairstreak.n.01', 'name': 'hairstreak'}, {'id': 4029, 'synset': 'strymon_melinus.n.01', 'name': 'Strymon_melinus'}, {'id': 4030, 'synset': 'moth.n.01', 'name': 'moth'}, {'id': 4031, 'synset': 'moth_miller.n.01', 'name': 'moth_miller'}, {'id': 4032, 'synset': 'tortricid.n.01', 'name': 'tortricid'}, {'id': 4033, 'synset': 'leaf_roller.n.01', 'name': 'leaf_roller'}, {'id': 4034, 'synset': 'tea_tortrix.n.01', 'name': 'tea_tortrix'}, {'id': 4035, 'synset': 'orange_tortrix.n.01', 'name': 'orange_tortrix'}, {'id': 4036, 'synset': 'codling_moth.n.01', 'name': 'codling_moth'}, {'id': 4037, 'synset': 'lymantriid.n.01', 'name': 'lymantriid'}, {'id': 4038, 'synset': 'tussock_caterpillar.n.01', 'name': 'tussock_caterpillar'}, {'id': 4039, 'synset': 'gypsy_moth.n.01', 'name': 'gypsy_moth'}, {'id': 4040, 'synset': 'browntail.n.01', 'name': 'browntail'}, {'id': 4041, 'synset': 'gold-tail_moth.n.01', 'name': 'gold-tail_moth'}, {'id': 4042, 'synset': 'geometrid.n.01', 'name': 'geometrid'}, {'id': 4043, 'synset': 'paleacrita_vernata.n.01', 'name': 'Paleacrita_vernata'}, {'id': 4044, 'synset': 'alsophila_pometaria.n.01', 'name': 'Alsophila_pometaria'}, {'id': 4045, 'synset': 'cankerworm.n.01', 'name': 'cankerworm'}, {'id': 4046, 'synset': 'spring_cankerworm.n.01', 'name': 'spring_cankerworm'}, {'id': 4047, 'synset': 'fall_cankerworm.n.01', 'name': 'fall_cankerworm'}, {'id': 4048, 'synset': 'measuring_worm.n.01', 'name': 'measuring_worm'}, {'id': 4049, 'synset': 'pyralid.n.01', 'name': 'pyralid'}, {'id': 4050, 'synset': 'bee_moth.n.01', 'name': 'bee_moth'}, {'id': 4051, 'synset': 'corn_borer.n.02', 'name': 'corn_borer'}, {'id': 4052, 'synset': 'mediterranean_flour_moth.n.01', 'name': 'Mediterranean_flour_moth'}, {'id': 4053, 'synset': 'tobacco_moth.n.01', 'name': 'tobacco_moth'}, {'id': 4054, 'synset': 'almond_moth.n.01', 'name': 'almond_moth'}, {'id': 4055, 'synset': 'raisin_moth.n.01', 'name': 'raisin_moth'}, {'id': 4056, 'synset': 'tineoid.n.01', 'name': 'tineoid'}, {'id': 4057, 'synset': 'tineid.n.01', 'name': 'tineid'}, {'id': 4058, 'synset': 'clothes_moth.n.01', 'name': 'clothes_moth'}, {'id': 4059, 'synset': 'casemaking_clothes_moth.n.01', 'name': 'casemaking_clothes_moth'}, {'id': 4060, 'synset': 'webbing_clothes_moth.n.01', 'name': 'webbing_clothes_moth'}, {'id': 4061, 'synset': 'carpet_moth.n.01', 'name': 'carpet_moth'}, {'id': 4062, 'synset': 'gelechiid.n.01', 'name': 'gelechiid'}, {'id': 4063, 'synset': 'grain_moth.n.01', 'name': 'grain_moth'}, {'id': 4064, 'synset': 'angoumois_moth.n.01', 'name': 'angoumois_moth'}, {'id': 4065, 'synset': 'potato_moth.n.01', 'name': 'potato_moth'}, {'id': 4066, 'synset': 'potato_tuberworm.n.01', 'name': 'potato_tuberworm'}, {'id': 4067, 'synset': 'noctuid_moth.n.01', 'name': 'noctuid_moth'}, {'id': 4068, 'synset': 'cutworm.n.01', 'name': 'cutworm'}, {'id': 4069, 'synset': 'underwing.n.01', 'name': 'underwing'}, {'id': 4070, 'synset': 'red_underwing.n.01', 'name': 'red_underwing'}, {'id': 4071, 'synset': 'antler_moth.n.01', 'name': 'antler_moth'}, {'id': 4072, 'synset': 'heliothis_moth.n.01', 'name': 'heliothis_moth'}, {'id': 4073, 'synset': 'army_cutworm.n.01', 'name': 'army_cutworm'}, {'id': 4074, 'synset': 'armyworm.n.02', 'name': 'armyworm'}, {'id': 4075, 'synset': 'armyworm.n.01', 'name': 'armyworm'}, {'id': 4076, 'synset': 'spodoptera_exigua.n.02', 'name': 'Spodoptera_exigua'}, {'id': 4077, 'synset': 'beet_armyworm.n.01', 'name': 'beet_armyworm'}, {'id': 4078, 'synset': 'spodoptera_frugiperda.n.02', 'name': 'Spodoptera_frugiperda'}, {'id': 4079, 'synset': 'fall_armyworm.n.01', 'name': 'fall_armyworm'}, {'id': 4080, 'synset': 'hawkmoth.n.01', 'name': 'hawkmoth'}, {'id': 4081, 'synset': 'manduca_sexta.n.02', 'name': 'Manduca_sexta'}, {'id': 4082, 'synset': 'tobacco_hornworm.n.01', 'name': 'tobacco_hornworm'}, {'id': 4083, 'synset': 'manduca_quinquemaculata.n.02', 'name': 'Manduca_quinquemaculata'}, {'id': 4084, 'synset': 'tomato_hornworm.n.01', 'name': 'tomato_hornworm'}, {'id': 4085, 'synset': "death's-head_moth.n.01", 'name': "death's-head_moth"}, {'id': 4086, 'synset': 'bombycid.n.01', 'name': 'bombycid'}, {'id': 4087, 'synset': 'domestic_silkworm_moth.n.01', 'name': 'domestic_silkworm_moth'}, {'id': 4088, 'synset': 'silkworm.n.01', 'name': 'silkworm'}, {'id': 4089, 'synset': 'saturniid.n.01', 'name': 'saturniid'}, {'id': 4090, 'synset': 'emperor.n.03', 'name': 'emperor'}, {'id': 4091, 'synset': 'imperial_moth.n.01', 'name': 'imperial_moth'}, {'id': 4092, 'synset': 'giant_silkworm_moth.n.01', 'name': 'giant_silkworm_moth'}, {'id': 4093, 'synset': 'silkworm.n.02', 'name': 'silkworm'}, {'id': 4094, 'synset': 'luna_moth.n.01', 'name': 'luna_moth'}, {'id': 4095, 'synset': 'cecropia.n.02', 'name': 'cecropia'}, {'id': 4096, 'synset': 'cynthia_moth.n.01', 'name': 'cynthia_moth'}, {'id': 4097, 'synset': 'ailanthus_silkworm.n.01', 'name': 'ailanthus_silkworm'}, {'id': 4098, 'synset': 'io_moth.n.01', 'name': 'io_moth'}, {'id': 4099, 'synset': 'polyphemus_moth.n.01', 'name': 'polyphemus_moth'}, {'id': 4100, 'synset': 'pernyi_moth.n.01', 'name': 'pernyi_moth'}, {'id': 4101, 'synset': 'tussah.n.01', 'name': 'tussah'}, {'id': 4102, 'synset': 'atlas_moth.n.01', 'name': 'atlas_moth'}, {'id': 4103, 'synset': 'arctiid.n.01', 'name': 'arctiid'}, {'id': 4104, 'synset': 'tiger_moth.n.01', 'name': 'tiger_moth'}, {'id': 4105, 'synset': 'cinnabar.n.02', 'name': 'cinnabar'}, {'id': 4106, 'synset': 'lasiocampid.n.01', 'name': 'lasiocampid'}, {'id': 4107, 'synset': 'eggar.n.01', 'name': 'eggar'}, {'id': 4108, 'synset': 'tent-caterpillar_moth.n.02', 'name': 'tent-caterpillar_moth'}, {'id': 4109, 'synset': 'tent_caterpillar.n.01', 'name': 'tent_caterpillar'}, {'id': 4110, 'synset': 'tent-caterpillar_moth.n.01', 'name': 'tent-caterpillar_moth'}, {'id': 4111, 'synset': 'forest_tent_caterpillar.n.01', 'name': 'forest_tent_caterpillar'}, {'id': 4112, 'synset': 'lappet.n.03', 'name': 'lappet'}, {'id': 4113, 'synset': 'lappet_caterpillar.n.01', 'name': 'lappet_caterpillar'}, {'id': 4114, 'synset': 'webworm.n.01', 'name': 'webworm'}, {'id': 4115, 'synset': 'webworm_moth.n.01', 'name': 'webworm_moth'}, {'id': 4116, 'synset': 'hyphantria_cunea.n.02', 'name': 'Hyphantria_cunea'}, {'id': 4117, 'synset': 'fall_webworm.n.01', 'name': 'fall_webworm'}, {'id': 4118, 'synset': 'garden_webworm.n.01', 'name': 'garden_webworm'}, {'id': 4119, 'synset': 'instar.n.01', 'name': 'instar'}, {'id': 4120, 'synset': 'caterpillar.n.01', 'name': 'caterpillar'}, {'id': 4121, 'synset': 'corn_borer.n.01', 'name': 'corn_borer'}, {'id': 4122, 'synset': 'bollworm.n.01', 'name': 'bollworm'}, {'id': 4123, 'synset': 'pink_bollworm.n.01', 'name': 'pink_bollworm'}, {'id': 4124, 'synset': 'corn_earworm.n.01', 'name': 'corn_earworm'}, {'id': 4125, 'synset': 'cabbageworm.n.01', 'name': 'cabbageworm'}, {'id': 4126, 'synset': 'woolly_bear.n.01', 'name': 'woolly_bear'}, {'id': 4127, 'synset': 'woolly_bear_moth.n.01', 'name': 'woolly_bear_moth'}, {'id': 4128, 'synset': 'larva.n.01', 'name': 'larva'}, {'id': 4129, 'synset': 'nymph.n.02', 'name': 'nymph'}, {'id': 4130, 'synset': 'leptocephalus.n.01', 'name': 'leptocephalus'}, {'id': 4131, 'synset': 'grub.n.02', 'name': 'grub'}, {'id': 4132, 'synset': 'maggot.n.01', 'name': 'maggot'}, {'id': 4133, 'synset': 'leatherjacket.n.03', 'name': 'leatherjacket'}, {'id': 4134, 'synset': 'pupa.n.01', 'name': 'pupa'}, {'id': 4135, 'synset': 'chrysalis.n.01', 'name': 'chrysalis'}, {'id': 4136, 'synset': 'imago.n.02', 'name': 'imago'}, {'id': 4137, 'synset': 'queen.n.01', 'name': 'queen'}, {'id': 4138, 'synset': 'phoronid.n.01', 'name': 'phoronid'}, {'id': 4139, 'synset': 'bryozoan.n.01', 'name': 'bryozoan'}, {'id': 4140, 'synset': 'brachiopod.n.01', 'name': 'brachiopod'}, {'id': 4141, 'synset': 'peanut_worm.n.01', 'name': 'peanut_worm'}, {'id': 4142, 'synset': 'echinoderm.n.01', 'name': 'echinoderm'}, {'id': 4143, 'synset': 'brittle_star.n.01', 'name': 'brittle_star'}, {'id': 4144, 'synset': 'basket_star.n.01', 'name': 'basket_star'}, {'id': 4145, 'synset': 'astrophyton_muricatum.n.01', 'name': 'Astrophyton_muricatum'}, {'id': 4146, 'synset': 'sea_urchin.n.01', 'name': 'sea_urchin'}, {'id': 4147, 'synset': 'edible_sea_urchin.n.01', 'name': 'edible_sea_urchin'}, {'id': 4148, 'synset': 'sand_dollar.n.01', 'name': 'sand_dollar'}, {'id': 4149, 'synset': 'heart_urchin.n.01', 'name': 'heart_urchin'}, {'id': 4150, 'synset': 'crinoid.n.01', 'name': 'crinoid'}, {'id': 4151, 'synset': 'sea_lily.n.01', 'name': 'sea_lily'}, {'id': 4152, 'synset': 'feather_star.n.01', 'name': 'feather_star'}, {'id': 4153, 'synset': 'sea_cucumber.n.01', 'name': 'sea_cucumber'}, {'id': 4154, 'synset': 'trepang.n.01', 'name': 'trepang'}, {'id': 4155, 'synset': 'duplicidentata.n.01', 'name': 'Duplicidentata'}, {'id': 4156, 'synset': 'lagomorph.n.01', 'name': 'lagomorph'}, {'id': 4157, 'synset': 'leporid.n.01', 'name': 'leporid'}, {'id': 4158, 'synset': 'rabbit_ears.n.02', 'name': 'rabbit_ears'}, {'id': 4159, 'synset': 'lapin.n.02', 'name': 'lapin'}, {'id': 4160, 'synset': 'bunny.n.02', 'name': 'bunny'}, {'id': 4161, 'synset': 'european_rabbit.n.01', 'name': 'European_rabbit'}, {'id': 4162, 'synset': 'wood_rabbit.n.01', 'name': 'wood_rabbit'}, {'id': 4163, 'synset': 'eastern_cottontail.n.01', 'name': 'eastern_cottontail'}, {'id': 4164, 'synset': 'swamp_rabbit.n.02', 'name': 'swamp_rabbit'}, {'id': 4165, 'synset': 'marsh_hare.n.01', 'name': 'marsh_hare'}, {'id': 4166, 'synset': 'hare.n.01', 'name': 'hare'}, {'id': 4167, 'synset': 'leveret.n.01', 'name': 'leveret'}, {'id': 4168, 'synset': 'european_hare.n.01', 'name': 'European_hare'}, {'id': 4169, 'synset': 'jackrabbit.n.01', 'name': 'jackrabbit'}, {'id': 4170, 'synset': 'white-tailed_jackrabbit.n.01', 'name': 'white-tailed_jackrabbit'}, {'id': 4171, 'synset': 'blacktail_jackrabbit.n.01', 'name': 'blacktail_jackrabbit'}, {'id': 4172, 'synset': 'polar_hare.n.01', 'name': 'polar_hare'}, {'id': 4173, 'synset': 'snowshoe_hare.n.01', 'name': 'snowshoe_hare'}, {'id': 4174, 'synset': 'belgian_hare.n.01', 'name': 'Belgian_hare'}, {'id': 4175, 'synset': 'angora.n.03', 'name': 'Angora'}, {'id': 4176, 'synset': 'pika.n.01', 'name': 'pika'}, {'id': 4177, 'synset': 'little_chief_hare.n.01', 'name': 'little_chief_hare'}, {'id': 4178, 'synset': 'collared_pika.n.01', 'name': 'collared_pika'}, {'id': 4179, 'synset': 'mouse.n.01', 'name': 'mouse'}, {'id': 4180, 'synset': 'pocket_rat.n.01', 'name': 'pocket_rat'}, {'id': 4181, 'synset': 'murine.n.01', 'name': 'murine'}, {'id': 4182, 'synset': 'house_mouse.n.01', 'name': 'house_mouse'}, {'id': 4183, 'synset': 'harvest_mouse.n.02', 'name': 'harvest_mouse'}, {'id': 4184, 'synset': 'field_mouse.n.02', 'name': 'field_mouse'}, {'id': 4185, 'synset': 'nude_mouse.n.01', 'name': 'nude_mouse'}, {'id': 4186, 'synset': 'european_wood_mouse.n.01', 'name': 'European_wood_mouse'}, {'id': 4187, 'synset': 'brown_rat.n.01', 'name': 'brown_rat'}, {'id': 4188, 'synset': 'wharf_rat.n.02', 'name': 'wharf_rat'}, {'id': 4189, 'synset': 'sewer_rat.n.01', 'name': 'sewer_rat'}, {'id': 4190, 'synset': 'black_rat.n.01', 'name': 'black_rat'}, {'id': 4191, 'synset': 'bandicoot_rat.n.01', 'name': 'bandicoot_rat'}, {'id': 4192, 'synset': 'jerboa_rat.n.01', 'name': 'jerboa_rat'}, {'id': 4193, 'synset': 'kangaroo_mouse.n.02', 'name': 'kangaroo_mouse'}, {'id': 4194, 'synset': 'water_rat.n.03', 'name': 'water_rat'}, {'id': 4195, 'synset': 'beaver_rat.n.01', 'name': 'beaver_rat'}, {'id': 4196, 'synset': 'new_world_mouse.n.01', 'name': 'New_World_mouse'}, {'id': 4197, 'synset': 'american_harvest_mouse.n.01', 'name': 'American_harvest_mouse'}, {'id': 4198, 'synset': 'wood_mouse.n.01', 'name': 'wood_mouse'}, {'id': 4199, 'synset': 'white-footed_mouse.n.01', 'name': 'white-footed_mouse'}, {'id': 4200, 'synset': 'deer_mouse.n.01', 'name': 'deer_mouse'}, {'id': 4201, 'synset': 'cactus_mouse.n.01', 'name': 'cactus_mouse'}, {'id': 4202, 'synset': 'cotton_mouse.n.01', 'name': 'cotton_mouse'}, {'id': 4203, 'synset': 'pygmy_mouse.n.01', 'name': 'pygmy_mouse'}, {'id': 4204, 'synset': 'grasshopper_mouse.n.01', 'name': 'grasshopper_mouse'}, {'id': 4205, 'synset': 'muskrat.n.02', 'name': 'muskrat'}, {'id': 4206, 'synset': 'round-tailed_muskrat.n.01', 'name': 'round-tailed_muskrat'}, {'id': 4207, 'synset': 'cotton_rat.n.01', 'name': 'cotton_rat'}, {'id': 4208, 'synset': 'wood_rat.n.01', 'name': 'wood_rat'}, {'id': 4209, 'synset': 'dusky-footed_wood_rat.n.01', 'name': 'dusky-footed_wood_rat'}, {'id': 4210, 'synset': 'vole.n.01', 'name': 'vole'}, {'id': 4211, 'synset': 'packrat.n.02', 'name': 'packrat'}, {'id': 4212, 'synset': 'dusky-footed_woodrat.n.01', 'name': 'dusky-footed_woodrat'}, {'id': 4213, 'synset': 'eastern_woodrat.n.01', 'name': 'eastern_woodrat'}, {'id': 4214, 'synset': 'rice_rat.n.01', 'name': 'rice_rat'}, {'id': 4215, 'synset': 'pine_vole.n.01', 'name': 'pine_vole'}, {'id': 4216, 'synset': 'meadow_vole.n.01', 'name': 'meadow_vole'}, {'id': 4217, 'synset': 'water_vole.n.02', 'name': 'water_vole'}, {'id': 4218, 'synset': 'prairie_vole.n.01', 'name': 'prairie_vole'}, {'id': 4219, 'synset': 'water_vole.n.01', 'name': 'water_vole'}, {'id': 4220, 'synset': 'red-backed_mouse.n.01', 'name': 'red-backed_mouse'}, {'id': 4221, 'synset': 'phenacomys.n.01', 'name': 'phenacomys'}, {'id': 4222, 'synset': 'eurasian_hamster.n.01', 'name': 'Eurasian_hamster'}, {'id': 4223, 'synset': 'golden_hamster.n.01', 'name': 'golden_hamster'}, {'id': 4224, 'synset': 'gerbil.n.01', 'name': 'gerbil'}, {'id': 4225, 'synset': 'jird.n.01', 'name': 'jird'}, {'id': 4226, 'synset': 'tamarisk_gerbil.n.01', 'name': 'tamarisk_gerbil'}, {'id': 4227, 'synset': 'sand_rat.n.02', 'name': 'sand_rat'}, {'id': 4228, 'synset': 'lemming.n.01', 'name': 'lemming'}, {'id': 4229, 'synset': 'european_lemming.n.01', 'name': 'European_lemming'}, {'id': 4230, 'synset': 'brown_lemming.n.01', 'name': 'brown_lemming'}, {'id': 4231, 'synset': 'grey_lemming.n.01', 'name': 'grey_lemming'}, {'id': 4232, 'synset': 'pied_lemming.n.01', 'name': 'pied_lemming'}, {'id': 4233, 'synset': 'hudson_bay_collared_lemming.n.01', 'name': 'Hudson_bay_collared_lemming'}, {'id': 4234, 'synset': 'southern_bog_lemming.n.01', 'name': 'southern_bog_lemming'}, {'id': 4235, 'synset': 'northern_bog_lemming.n.01', 'name': 'northern_bog_lemming'}, {'id': 4236, 'synset': 'porcupine.n.01', 'name': 'porcupine'}, {'id': 4237, 'synset': 'old_world_porcupine.n.01', 'name': 'Old_World_porcupine'}, {'id': 4238, 'synset': 'brush-tailed_porcupine.n.01', 'name': 'brush-tailed_porcupine'}, {'id': 4239, 'synset': 'long-tailed_porcupine.n.01', 'name': 'long-tailed_porcupine'}, {'id': 4240, 'synset': 'new_world_porcupine.n.01', 'name': 'New_World_porcupine'}, {'id': 4241, 'synset': 'canada_porcupine.n.01', 'name': 'Canada_porcupine'}, {'id': 4242, 'synset': 'pocket_mouse.n.01', 'name': 'pocket_mouse'}, {'id': 4243, 'synset': 'silky_pocket_mouse.n.01', 'name': 'silky_pocket_mouse'}, {'id': 4244, 'synset': 'plains_pocket_mouse.n.01', 'name': 'plains_pocket_mouse'}, {'id': 4245, 'synset': 'hispid_pocket_mouse.n.01', 'name': 'hispid_pocket_mouse'}, {'id': 4246, 'synset': 'mexican_pocket_mouse.n.01', 'name': 'Mexican_pocket_mouse'}, {'id': 4247, 'synset': 'kangaroo_rat.n.01', 'name': 'kangaroo_rat'}, {'id': 4248, 'synset': 'ord_kangaroo_rat.n.01', 'name': 'Ord_kangaroo_rat'}, {'id': 4249, 'synset': 'kangaroo_mouse.n.01', 'name': 'kangaroo_mouse'}, {'id': 4250, 'synset': 'jumping_mouse.n.01', 'name': 'jumping_mouse'}, {'id': 4251, 'synset': 'meadow_jumping_mouse.n.01', 'name': 'meadow_jumping_mouse'}, {'id': 4252, 'synset': 'jerboa.n.01', 'name': 'jerboa'}, {'id': 4253, 'synset': 'typical_jerboa.n.01', 'name': 'typical_jerboa'}, {'id': 4254, 'synset': 'jaculus_jaculus.n.01', 'name': 'Jaculus_jaculus'}, {'id': 4255, 'synset': 'dormouse.n.01', 'name': 'dormouse'}, {'id': 4256, 'synset': 'loir.n.01', 'name': 'loir'}, {'id': 4257, 'synset': 'hazel_mouse.n.01', 'name': 'hazel_mouse'}, {'id': 4258, 'synset': 'lerot.n.01', 'name': 'lerot'}, {'id': 4259, 'synset': 'gopher.n.04', 'name': 'gopher'}, {'id': 4260, 'synset': 'plains_pocket_gopher.n.01', 'name': 'plains_pocket_gopher'}, {'id': 4261, 'synset': 'southeastern_pocket_gopher.n.01', 'name': 'southeastern_pocket_gopher'}, {'id': 4262, 'synset': 'valley_pocket_gopher.n.01', 'name': 'valley_pocket_gopher'}, {'id': 4263, 'synset': 'northern_pocket_gopher.n.01', 'name': 'northern_pocket_gopher'}, {'id': 4264, 'synset': 'tree_squirrel.n.01', 'name': 'tree_squirrel'}, {'id': 4265, 'synset': 'eastern_grey_squirrel.n.01', 'name': 'eastern_grey_squirrel'}, {'id': 4266, 'synset': 'western_grey_squirrel.n.01', 'name': 'western_grey_squirrel'}, {'id': 4267, 'synset': 'fox_squirrel.n.01', 'name': 'fox_squirrel'}, {'id': 4268, 'synset': 'black_squirrel.n.01', 'name': 'black_squirrel'}, {'id': 4269, 'synset': 'red_squirrel.n.02', 'name': 'red_squirrel'}, {'id': 4270, 'synset': 'american_red_squirrel.n.01', 'name': 'American_red_squirrel'}, {'id': 4271, 'synset': 'chickeree.n.01', 'name': 'chickeree'}, {'id': 4272, 'synset': 'antelope_squirrel.n.01', 'name': 'antelope_squirrel'}, {'id': 4273, 'synset': 'ground_squirrel.n.02', 'name': 'ground_squirrel'}, {'id': 4274, 'synset': 'mantled_ground_squirrel.n.01', 'name': 'mantled_ground_squirrel'}, {'id': 4275, 'synset': 'suslik.n.01', 'name': 'suslik'}, {'id': 4276, 'synset': 'flickertail.n.01', 'name': 'flickertail'}, {'id': 4277, 'synset': 'rock_squirrel.n.01', 'name': 'rock_squirrel'}, {'id': 4278, 'synset': 'arctic_ground_squirrel.n.01', 'name': 'Arctic_ground_squirrel'}, {'id': 4279, 'synset': 'prairie_dog.n.01', 'name': 'prairie_dog'}, {'id': 4280, 'synset': 'blacktail_prairie_dog.n.01', 'name': 'blacktail_prairie_dog'}, {'id': 4281, 'synset': 'whitetail_prairie_dog.n.01', 'name': 'whitetail_prairie_dog'}, {'id': 4282, 'synset': 'eastern_chipmunk.n.01', 'name': 'eastern_chipmunk'}, {'id': 4283, 'synset': 'chipmunk.n.01', 'name': 'chipmunk'}, {'id': 4284, 'synset': 'baronduki.n.01', 'name': 'baronduki'}, {'id': 4285, 'synset': 'american_flying_squirrel.n.01', 'name': 'American_flying_squirrel'}, {'id': 4286, 'synset': 'southern_flying_squirrel.n.01', 'name': 'southern_flying_squirrel'}, {'id': 4287, 'synset': 'northern_flying_squirrel.n.01', 'name': 'northern_flying_squirrel'}, {'id': 4288, 'synset': 'marmot.n.01', 'name': 'marmot'}, {'id': 4289, 'synset': 'groundhog.n.01', 'name': 'groundhog'}, {'id': 4290, 'synset': 'hoary_marmot.n.01', 'name': 'hoary_marmot'}, {'id': 4291, 'synset': 'yellowbelly_marmot.n.01', 'name': 'yellowbelly_marmot'}, {'id': 4292, 'synset': 'asiatic_flying_squirrel.n.01', 'name': 'Asiatic_flying_squirrel'}, {'id': 4293, 'synset': 'beaver.n.07', 'name': 'beaver'}, {'id': 4294, 'synset': 'old_world_beaver.n.01', 'name': 'Old_World_beaver'}, {'id': 4295, 'synset': 'new_world_beaver.n.01', 'name': 'New_World_beaver'}, {'id': 4296, 'synset': 'mountain_beaver.n.01', 'name': 'mountain_beaver'}, {'id': 4297, 'synset': 'cavy.n.01', 'name': 'cavy'}, {'id': 4298, 'synset': 'guinea_pig.n.02', 'name': 'guinea_pig'}, {'id': 4299, 'synset': 'aperea.n.01', 'name': 'aperea'}, {'id': 4300, 'synset': 'mara.n.02', 'name': 'mara'}, {'id': 4301, 'synset': 'capybara.n.01', 'name': 'capybara'}, {'id': 4302, 'synset': 'agouti.n.01', 'name': 'agouti'}, {'id': 4303, 'synset': 'paca.n.01', 'name': 'paca'}, {'id': 4304, 'synset': 'mountain_paca.n.01', 'name': 'mountain_paca'}, {'id': 4305, 'synset': 'coypu.n.01', 'name': 'coypu'}, {'id': 4306, 'synset': 'chinchilla.n.03', 'name': 'chinchilla'}, {'id': 4307, 'synset': 'mountain_chinchilla.n.01', 'name': 'mountain_chinchilla'}, {'id': 4308, 'synset': 'viscacha.n.01', 'name': 'viscacha'}, {'id': 4309, 'synset': 'abrocome.n.01', 'name': 'abrocome'}, {'id': 4310, 'synset': 'mole_rat.n.02', 'name': 'mole_rat'}, {'id': 4311, 'synset': 'mole_rat.n.01', 'name': 'mole_rat'}, {'id': 4312, 'synset': 'sand_rat.n.01', 'name': 'sand_rat'}, {'id': 4313, 'synset': 'naked_mole_rat.n.01', 'name': 'naked_mole_rat'}, {'id': 4314, 'synset': 'queen.n.09', 'name': 'queen'}, {'id': 4315, 'synset': 'damaraland_mole_rat.n.01', 'name': 'Damaraland_mole_rat'}, {'id': 4316, 'synset': 'ungulata.n.01', 'name': 'Ungulata'}, {'id': 4317, 'synset': 'ungulate.n.01', 'name': 'ungulate'}, {'id': 4318, 'synset': 'unguiculate.n.01', 'name': 'unguiculate'}, {'id': 4319, 'synset': 'dinoceras.n.01', 'name': 'dinoceras'}, {'id': 4320, 'synset': 'hyrax.n.01', 'name': 'hyrax'}, {'id': 4321, 'synset': 'rock_hyrax.n.01', 'name': 'rock_hyrax'}, {'id': 4322, 'synset': 'odd-toed_ungulate.n.01', 'name': 'odd-toed_ungulate'}, {'id': 4323, 'synset': 'equine.n.01', 'name': 'equine'}, {'id': 4324, 'synset': 'roan.n.02', 'name': 'roan'}, {'id': 4325, 'synset': 'stablemate.n.01', 'name': 'stablemate'}, {'id': 4326, 'synset': 'gee-gee.n.01', 'name': 'gee-gee'}, {'id': 4327, 'synset': 'eohippus.n.01', 'name': 'eohippus'}, {'id': 4328, 'synset': 'filly.n.01', 'name': 'filly'}, {'id': 4329, 'synset': 'colt.n.01', 'name': 'colt'}, {'id': 4330, 'synset': 'male_horse.n.01', 'name': 'male_horse'}, {'id': 4331, 'synset': 'ridgeling.n.01', 'name': 'ridgeling'}, {'id': 4332, 'synset': 'stallion.n.01', 'name': 'stallion'}, {'id': 4333, 'synset': 'stud.n.04', 'name': 'stud'}, {'id': 4334, 'synset': 'gelding.n.01', 'name': 'gelding'}, {'id': 4335, 'synset': 'mare.n.01', 'name': 'mare'}, {'id': 4336, 'synset': 'broodmare.n.01', 'name': 'broodmare'}, {'id': 4337, 'synset': 'saddle_horse.n.01', 'name': 'saddle_horse'}, {'id': 4338, 'synset': 'remount.n.01', 'name': 'remount'}, {'id': 4339, 'synset': 'palfrey.n.01', 'name': 'palfrey'}, {'id': 4340, 'synset': 'warhorse.n.03', 'name': 'warhorse'}, {'id': 4341, 'synset': 'cavalry_horse.n.01', 'name': 'cavalry_horse'}, {'id': 4342, 'synset': 'charger.n.01', 'name': 'charger'}, {'id': 4343, 'synset': 'steed.n.01', 'name': 'steed'}, {'id': 4344, 'synset': 'prancer.n.01', 'name': 'prancer'}, {'id': 4345, 'synset': 'hack.n.08', 'name': 'hack'}, {'id': 4346, 'synset': 'cow_pony.n.01', 'name': 'cow_pony'}, {'id': 4347, 'synset': 'quarter_horse.n.01', 'name': 'quarter_horse'}, {'id': 4348, 'synset': 'morgan.n.06', 'name': 'Morgan'}, {'id': 4349, 'synset': 'tennessee_walker.n.01', 'name': 'Tennessee_walker'}, {'id': 4350, 'synset': 'american_saddle_horse.n.01', 'name': 'American_saddle_horse'}, {'id': 4351, 'synset': 'appaloosa.n.01', 'name': 'Appaloosa'}, {'id': 4352, 'synset': 'arabian.n.02', 'name': 'Arabian'}, {'id': 4353, 'synset': 'lippizan.n.01', 'name': 'Lippizan'}, {'id': 4354, 'synset': 'pony.n.01', 'name': 'pony'}, {'id': 4355, 'synset': 'polo_pony.n.01', 'name': 'polo_pony'}, {'id': 4356, 'synset': 'mustang.n.01', 'name': 'mustang'}, {'id': 4357, 'synset': 'bronco.n.01', 'name': 'bronco'}, {'id': 4358, 'synset': 'bucking_bronco.n.01', 'name': 'bucking_bronco'}, {'id': 4359, 'synset': 'buckskin.n.01', 'name': 'buckskin'}, {'id': 4360, 'synset': 'crowbait.n.01', 'name': 'crowbait'}, {'id': 4361, 'synset': 'dun.n.01', 'name': 'dun'}, {'id': 4362, 'synset': 'grey.n.07', 'name': 'grey'}, {'id': 4363, 'synset': 'wild_horse.n.01', 'name': 'wild_horse'}, {'id': 4364, 'synset': 'tarpan.n.01', 'name': 'tarpan'}, {'id': 4365, 'synset': "przewalski's_horse.n.01", 'name': "Przewalski's_horse"}, {'id': 4366, 'synset': 'cayuse.n.01', 'name': 'cayuse'}, {'id': 4367, 'synset': 'hack.n.07', 'name': 'hack'}, {'id': 4368, 'synset': 'hack.n.06', 'name': 'hack'}, {'id': 4369, 'synset': 'plow_horse.n.01', 'name': 'plow_horse'}, {'id': 4370, 'synset': 'shetland_pony.n.01', 'name': 'Shetland_pony'}, {'id': 4371, 'synset': 'welsh_pony.n.01', 'name': 'Welsh_pony'}, {'id': 4372, 'synset': 'exmoor.n.02', 'name': 'Exmoor'}, {'id': 4373, 'synset': 'racehorse.n.01', 'name': 'racehorse'}, {'id': 4374, 'synset': 'thoroughbred.n.02', 'name': 'thoroughbred'}, {'id': 4375, 'synset': 'steeplechaser.n.01', 'name': 'steeplechaser'}, {'id': 4376, 'synset': 'racer.n.03', 'name': 'racer'}, {'id': 4377, 'synset': 'finisher.n.06', 'name': 'finisher'}, {'id': 4378, 'synset': 'pony.n.02', 'name': 'pony'}, {'id': 4379, 'synset': 'yearling.n.02', 'name': 'yearling'}, {'id': 4380, 'synset': 'dark_horse.n.02', 'name': 'dark_horse'}, {'id': 4381, 'synset': 'mudder.n.01', 'name': 'mudder'}, {'id': 4382, 'synset': 'nonstarter.n.02', 'name': 'nonstarter'}, {'id': 4383, 'synset': 'stalking-horse.n.04', 'name': 'stalking-horse'}, {'id': 4384, 'synset': 'harness_horse.n.01', 'name': 'harness_horse'}, {'id': 4385, 'synset': 'cob.n.02', 'name': 'cob'}, {'id': 4386, 'synset': 'hackney.n.02', 'name': 'hackney'}, {'id': 4387, 'synset': 'workhorse.n.02', 'name': 'workhorse'}, {'id': 4388, 'synset': 'draft_horse.n.01', 'name': 'draft_horse'}, {'id': 4389, 'synset': 'packhorse.n.01', 'name': 'packhorse'}, {'id': 4390, 'synset': 'carthorse.n.01', 'name': 'carthorse'}, {'id': 4391, 'synset': 'clydesdale.n.01', 'name': 'Clydesdale'}, {'id': 4392, 'synset': 'percheron.n.01', 'name': 'Percheron'}, {'id': 4393, 'synset': 'farm_horse.n.01', 'name': 'farm_horse'}, {'id': 4394, 'synset': 'shire.n.02', 'name': 'shire'}, {'id': 4395, 'synset': 'pole_horse.n.02', 'name': 'pole_horse'}, {'id': 4396, 'synset': 'post_horse.n.01', 'name': 'post_horse'}, {'id': 4397, 'synset': 'coach_horse.n.01', 'name': 'coach_horse'}, {'id': 4398, 'synset': 'pacer.n.02', 'name': 'pacer'}, {'id': 4399, 'synset': 'pacer.n.01', 'name': 'pacer'}, {'id': 4400, 'synset': 'trotting_horse.n.01', 'name': 'trotting_horse'}, {'id': 4401, 'synset': 'pole_horse.n.01', 'name': 'pole_horse'}, {'id': 4402, 'synset': 'stepper.n.03', 'name': 'stepper'}, {'id': 4403, 'synset': 'chestnut.n.06', 'name': 'chestnut'}, {'id': 4404, 'synset': 'liver_chestnut.n.01', 'name': 'liver_chestnut'}, {'id': 4405, 'synset': 'bay.n.07', 'name': 'bay'}, {'id': 4406, 'synset': 'sorrel.n.05', 'name': 'sorrel'}, {'id': 4407, 'synset': 'palomino.n.01', 'name': 'palomino'}, {'id': 4408, 'synset': 'pinto.n.01', 'name': 'pinto'}, {'id': 4409, 'synset': 'ass.n.03', 'name': 'ass'}, {'id': 4410, 'synset': 'burro.n.01', 'name': 'burro'}, {'id': 4411, 'synset': 'moke.n.01', 'name': 'moke'}, {'id': 4412, 'synset': 'jack.n.12', 'name': 'jack'}, {'id': 4413, 'synset': 'jennet.n.01', 'name': 'jennet'}, {'id': 4414, 'synset': 'mule.n.01', 'name': 'mule'}, {'id': 4415, 'synset': 'hinny.n.01', 'name': 'hinny'}, {'id': 4416, 'synset': 'wild_ass.n.01', 'name': 'wild_ass'}, {'id': 4417, 'synset': 'african_wild_ass.n.01', 'name': 'African_wild_ass'}, {'id': 4418, 'synset': 'kiang.n.01', 'name': 'kiang'}, {'id': 4419, 'synset': 'onager.n.02', 'name': 'onager'}, {'id': 4420, 'synset': 'chigetai.n.01', 'name': 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4435, 'synset': 'sucking_pig.n.01', 'name': 'sucking_pig'}, {'id': 4436, 'synset': 'porker.n.01', 'name': 'porker'}, {'id': 4437, 'synset': 'boar.n.02', 'name': 'boar'}, {'id': 4438, 'synset': 'sow.n.01', 'name': 'sow'}, {'id': 4439, 'synset': 'razorback.n.01', 'name': 'razorback'}, {'id': 4440, 'synset': 'wild_boar.n.01', 'name': 'wild_boar'}, {'id': 4441, 'synset': 'babirusa.n.01', 'name': 'babirusa'}, {'id': 4442, 'synset': 'warthog.n.01', 'name': 'warthog'}, {'id': 4443, 'synset': 'peccary.n.01', 'name': 'peccary'}, {'id': 4444, 'synset': 'collared_peccary.n.01', 'name': 'collared_peccary'}, {'id': 4445, 'synset': 'white-lipped_peccary.n.01', 'name': 'white-lipped_peccary'}, {'id': 4446, 'synset': 'ruminant.n.01', 'name': 'ruminant'}, {'id': 4447, 'synset': 'bovid.n.01', 'name': 'bovid'}, {'id': 4448, 'synset': 'bovine.n.01', 'name': 'bovine'}, {'id': 4449, 'synset': 'ox.n.02', 'name': 'ox'}, {'id': 4450, 'synset': 'cattle.n.01', 'name': 'cattle'}, {'id': 4451, 'synset': 'ox.n.01', 'name': 'ox'}, {'id': 4452, 'synset': 'stirk.n.01', 'name': 'stirk'}, {'id': 4453, 'synset': 'bullock.n.02', 'name': 'bullock'}, {'id': 4454, 'synset': 'bull.n.01', 'name': 'bull'}, {'id': 4455, 'synset': 'cow.n.01', 'name': 'cow'}, {'id': 4456, 'synset': 'heifer.n.01', 'name': 'heifer'}, {'id': 4457, 'synset': 'bullock.n.01', 'name': 'bullock'}, {'id': 4458, 'synset': 'dogie.n.01', 'name': 'dogie'}, {'id': 4459, 'synset': 'maverick.n.02', 'name': 'maverick'}, {'id': 4460, 'synset': 'longhorn.n.01', 'name': 'longhorn'}, {'id': 4461, 'synset': 'brahman.n.04', 'name': 'Brahman'}, {'id': 4462, 'synset': 'zebu.n.01', 'name': 'zebu'}, {'id': 4463, 'synset': 'aurochs.n.02', 'name': 'aurochs'}, {'id': 4464, 'synset': 'yak.n.02', 'name': 'yak'}, {'id': 4465, 'synset': 'banteng.n.01', 'name': 'banteng'}, {'id': 4466, 'synset': 'welsh.n.03', 'name': 'Welsh'}, {'id': 4467, 'synset': 'red_poll.n.01', 'name': 'red_poll'}, {'id': 4468, 'synset': 'santa_gertrudis.n.01', 'name': 'Santa_Gertrudis'}, {'id': 4469, 'synset': 'aberdeen_angus.n.01', 'name': 'Aberdeen_Angus'}, {'id': 4470, 'synset': 'africander.n.01', 'name': 'Africander'}, {'id': 4471, 'synset': 'dairy_cattle.n.01', 'name': 'dairy_cattle'}, {'id': 4472, 'synset': 'ayrshire.n.01', 'name': 'Ayrshire'}, {'id': 4473, 'synset': 'brown_swiss.n.01', 'name': 'Brown_Swiss'}, {'id': 4474, 'synset': 'charolais.n.01', 'name': 'Charolais'}, {'id': 4475, 'synset': 'jersey.n.05', 'name': 'Jersey'}, {'id': 4476, 'synset': 'devon.n.02', 'name': 'Devon'}, {'id': 4477, 'synset': 'grade.n.09', 'name': 'grade'}, {'id': 4478, 'synset': 'durham.n.02', 'name': 'Durham'}, {'id': 4479, 'synset': 'milking_shorthorn.n.01', 'name': 'milking_shorthorn'}, {'id': 4480, 'synset': 'galloway.n.02', 'name': 'Galloway'}, {'id': 4481, 'synset': 'friesian.n.01', 'name': 'Friesian'}, {'id': 4482, 'synset': 'guernsey.n.02', 'name': 'Guernsey'}, {'id': 4483, 'synset': 'hereford.n.01', 'name': 'Hereford'}, {'id': 4484, 'synset': 'cattalo.n.01', 'name': 'cattalo'}, {'id': 4485, 'synset': 'old_world_buffalo.n.01', 'name': 'Old_World_buffalo'}, {'id': 4486, 'synset': 'water_buffalo.n.01', 'name': 'water_buffalo'}, {'id': 4487, 'synset': 'indian_buffalo.n.01', 'name': 'Indian_buffalo'}, {'id': 4488, 'synset': 'carabao.n.01', 'name': 'carabao'}, {'id': 4489, 'synset': 'anoa.n.01', 'name': 'anoa'}, {'id': 4490, 'synset': 'tamarau.n.01', 'name': 'tamarau'}, {'id': 4491, 'synset': 'cape_buffalo.n.01', 'name': 'Cape_buffalo'}, {'id': 4492, 'synset': 'asian_wild_ox.n.01', 'name': 'Asian_wild_ox'}, {'id': 4493, 'synset': 'gaur.n.01', 'name': 'gaur'}, {'id': 4494, 'synset': 'gayal.n.01', 'name': 'gayal'}, {'id': 4495, 'synset': 'bison.n.01', 'name': 'bison'}, {'id': 4496, 'synset': 'american_bison.n.01', 'name': 'American_bison'}, {'id': 4497, 'synset': 'wisent.n.01', 'name': 'wisent'}, {'id': 4498, 'synset': 'musk_ox.n.01', 'name': 'musk_ox'}, {'id': 4499, 'synset': 'ewe.n.03', 'name': 'ewe'}, {'id': 4500, 'synset': 'wether.n.01', 'name': 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'synset': 'argali.n.01', 'name': 'argali'}, {'id': 4518, 'synset': 'marco_polo_sheep.n.01', 'name': 'Marco_Polo_sheep'}, {'id': 4519, 'synset': 'urial.n.01', 'name': 'urial'}, {'id': 4520, 'synset': 'dall_sheep.n.01', 'name': 'Dall_sheep'}, {'id': 4521, 'synset': 'mountain_sheep.n.01', 'name': 'mountain_sheep'}, {'id': 4522, 'synset': 'bighorn.n.02', 'name': 'bighorn'}, {'id': 4523, 'synset': 'mouflon.n.01', 'name': 'mouflon'}, {'id': 4524, 'synset': 'aoudad.n.01', 'name': 'aoudad'}, {'id': 4525, 'synset': 'kid.n.05', 'name': 'kid'}, {'id': 4526, 'synset': 'billy.n.02', 'name': 'billy'}, {'id': 4527, 'synset': 'nanny.n.02', 'name': 'nanny'}, {'id': 4528, 'synset': 'domestic_goat.n.01', 'name': 'domestic_goat'}, {'id': 4529, 'synset': 'cashmere_goat.n.01', 'name': 'Cashmere_goat'}, {'id': 4530, 'synset': 'angora.n.02', 'name': 'Angora'}, {'id': 4531, 'synset': 'wild_goat.n.01', 'name': 'wild_goat'}, {'id': 4532, 'synset': 'bezoar_goat.n.01', 'name': 'bezoar_goat'}, {'id': 4533, 'synset': 'markhor.n.01', 'name': 'markhor'}, {'id': 4534, 'synset': 'ibex.n.01', 'name': 'ibex'}, {'id': 4535, 'synset': 'goat_antelope.n.01', 'name': 'goat_antelope'}, {'id': 4536, 'synset': 'mountain_goat.n.01', 'name': 'mountain_goat'}, {'id': 4537, 'synset': 'goral.n.01', 'name': 'goral'}, {'id': 4538, 'synset': 'serow.n.01', 'name': 'serow'}, {'id': 4539, 'synset': 'chamois.n.02', 'name': 'chamois'}, {'id': 4540, 'synset': 'takin.n.01', 'name': 'takin'}, {'id': 4541, 'synset': 'antelope.n.01', 'name': 'antelope'}, {'id': 4542, 'synset': 'blackbuck.n.01', 'name': 'blackbuck'}, {'id': 4543, 'synset': 'gerenuk.n.01', 'name': 'gerenuk'}, {'id': 4544, 'synset': 'addax.n.01', 'name': 'addax'}, {'id': 4545, 'synset': 'gnu.n.01', 'name': 'gnu'}, {'id': 4546, 'synset': 'dik-dik.n.01', 'name': 'dik-dik'}, {'id': 4547, 'synset': 'hartebeest.n.01', 'name': 'hartebeest'}, {'id': 4548, 'synset': 'sassaby.n.01', 'name': 'sassaby'}, {'id': 4549, 'synset': 'impala.n.01', 'name': 'impala'}, {'id': 4550, 'synset': "thomson's_gazelle.n.01", 'name': "Thomson's_gazelle"}, {'id': 4551, 'synset': 'gazella_subgutturosa.n.01', 'name': 'Gazella_subgutturosa'}, {'id': 4552, 'synset': 'springbok.n.01', 'name': 'springbok'}, {'id': 4553, 'synset': 'bongo.n.02', 'name': 'bongo'}, {'id': 4554, 'synset': 'kudu.n.01', 'name': 'kudu'}, {'id': 4555, 'synset': 'greater_kudu.n.01', 'name': 'greater_kudu'}, {'id': 4556, 'synset': 'lesser_kudu.n.01', 'name': 'lesser_kudu'}, {'id': 4557, 'synset': 'harnessed_antelope.n.01', 'name': 'harnessed_antelope'}, {'id': 4558, 'synset': 'nyala.n.02', 'name': 'nyala'}, {'id': 4559, 'synset': 'mountain_nyala.n.01', 'name': 'mountain_nyala'}, {'id': 4560, 'synset': 'bushbuck.n.01', 'name': 'bushbuck'}, {'id': 4561, 'synset': 'nilgai.n.01', 'name': 'nilgai'}, {'id': 4562, 'synset': 'sable_antelope.n.01', 'name': 'sable_antelope'}, {'id': 4563, 'synset': 'saiga.n.01', 'name': 'saiga'}, {'id': 4564, 'synset': 'steenbok.n.01', 'name': 'steenbok'}, {'id': 4565, 'synset': 'eland.n.01', 'name': 'eland'}, {'id': 4566, 'synset': 'common_eland.n.01', 'name': 'common_eland'}, {'id': 4567, 'synset': 'giant_eland.n.01', 'name': 'giant_eland'}, {'id': 4568, 'synset': 'kob.n.01', 'name': 'kob'}, {'id': 4569, 'synset': 'lechwe.n.01', 'name': 'lechwe'}, {'id': 4570, 'synset': 'waterbuck.n.01', 'name': 'waterbuck'}, {'id': 4571, 'synset': 'puku.n.01', 'name': 'puku'}, {'id': 4572, 'synset': 'oryx.n.01', 'name': 'oryx'}, {'id': 4573, 'synset': 'gemsbok.n.01', 'name': 'gemsbok'}, {'id': 4574, 'synset': 'forest_goat.n.01', 'name': 'forest_goat'}, {'id': 4575, 'synset': 'pronghorn.n.01', 'name': 'pronghorn'}, {'id': 4576, 'synset': 'stag.n.02', 'name': 'stag'}, {'id': 4577, 'synset': 'royal.n.02', 'name': 'royal'}, {'id': 4578, 'synset': 'pricket.n.02', 'name': 'pricket'}, {'id': 4579, 'synset': 'fawn.n.02', 'name': 'fawn'}, {'id': 4580, 'synset': 'red_deer.n.01', 'name': 'red_deer'}, {'id': 4581, 'synset': 'hart.n.03', 'name': 'hart'}, {'id': 4582, 'synset': 'hind.n.02', 'name': 'hind'}, {'id': 4583, 'synset': 'brocket.n.02', 'name': 'brocket'}, {'id': 4584, 'synset': 'sambar.n.01', 'name': 'sambar'}, {'id': 4585, 'synset': 'wapiti.n.01', 'name': 'wapiti'}, {'id': 4586, 'synset': 'japanese_deer.n.01', 'name': 'Japanese_deer'}, {'id': 4587, 'synset': 'virginia_deer.n.01', 'name': 'Virginia_deer'}, {'id': 4588, 'synset': 'mule_deer.n.01', 'name': 'mule_deer'}, {'id': 4589, 'synset': 'black-tailed_deer.n.01', 'name': 'black-tailed_deer'}, {'id': 4590, 'synset': 'fallow_deer.n.01', 'name': 'fallow_deer'}, {'id': 4591, 'synset': 'roe_deer.n.01', 'name': 'roe_deer'}, {'id': 4592, 'synset': 'roebuck.n.01', 'name': 'roebuck'}, {'id': 4593, 'synset': 'caribou.n.01', 'name': 'caribou'}, {'id': 4594, 'synset': 'woodland_caribou.n.01', 'name': 'woodland_caribou'}, {'id': 4595, 'synset': 'barren_ground_caribou.n.01', 'name': 'barren_ground_caribou'}, {'id': 4596, 'synset': 'brocket.n.01', 'name': 'brocket'}, {'id': 4597, 'synset': 'muntjac.n.01', 'name': 'muntjac'}, {'id': 4598, 'synset': 'musk_deer.n.01', 'name': 'musk_deer'}, {'id': 4599, 'synset': "pere_david's_deer.n.01", 'name': "pere_david's_deer"}, {'id': 4600, 'synset': 'chevrotain.n.01', 'name': 'chevrotain'}, {'id': 4601, 'synset': 'kanchil.n.01', 'name': 'kanchil'}, {'id': 4602, 'synset': 'napu.n.01', 'name': 'napu'}, {'id': 4603, 'synset': 'water_chevrotain.n.01', 'name': 'water_chevrotain'}, {'id': 4604, 'synset': 'arabian_camel.n.01', 'name': 'Arabian_camel'}, {'id': 4605, 'synset': 'bactrian_camel.n.01', 'name': 'Bactrian_camel'}, {'id': 4606, 'synset': 'llama.n.01', 'name': 'llama'}, {'id': 4607, 'synset': 'domestic_llama.n.01', 'name': 'domestic_llama'}, {'id': 4608, 'synset': 'guanaco.n.01', 'name': 'guanaco'}, {'id': 4609, 'synset': 'alpaca.n.03', 'name': 'alpaca'}, {'id': 4610, 'synset': 'vicuna.n.03', 'name': 'vicuna'}, {'id': 4611, 'synset': 'okapi.n.01', 'name': 'okapi'}, {'id': 4612, 'synset': 'musteline_mammal.n.01', 'name': 'musteline_mammal'}, {'id': 4613, 'synset': 'weasel.n.02', 'name': 'weasel'}, {'id': 4614, 'synset': 'ermine.n.02', 'name': 'ermine'}, {'id': 4615, 'synset': 'stoat.n.01', 'name': 'stoat'}, {'id': 4616, 'synset': 'new_world_least_weasel.n.01', 'name': 'New_World_least_weasel'}, {'id': 4617, 'synset': 'old_world_least_weasel.n.01', 'name': 'Old_World_least_weasel'}, {'id': 4618, 'synset': 'longtail_weasel.n.01', 'name': 'longtail_weasel'}, {'id': 4619, 'synset': 'mink.n.03', 'name': 'mink'}, {'id': 4620, 'synset': 'american_mink.n.01', 'name': 'American_mink'}, {'id': 4621, 'synset': 'polecat.n.02', 'name': 'polecat'}, {'id': 4622, 'synset': 'black-footed_ferret.n.01', 'name': 'black-footed_ferret'}, {'id': 4623, 'synset': 'muishond.n.01', 'name': 'muishond'}, {'id': 4624, 'synset': 'snake_muishond.n.01', 'name': 'snake_muishond'}, {'id': 4625, 'synset': 'striped_muishond.n.01', 'name': 'striped_muishond'}, {'id': 4626, 'synset': 'otter.n.02', 'name': 'otter'}, {'id': 4627, 'synset': 'river_otter.n.01', 'name': 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'toadfish.n.01', 'name': 'toadfish'}, {'id': 4901, 'synset': 'oyster_fish.n.01', 'name': 'oyster_fish'}, {'id': 4902, 'synset': 'frogfish.n.01', 'name': 'frogfish'}, {'id': 4903, 'synset': 'sargassum_fish.n.01', 'name': 'sargassum_fish'}, {'id': 4904, 'synset': 'needlefish.n.01', 'name': 'needlefish'}, {'id': 4905, 'synset': 'timucu.n.01', 'name': 'timucu'}, {'id': 4906, 'synset': 'flying_fish.n.01', 'name': 'flying_fish'}, {'id': 4907, 'synset': 'monoplane_flying_fish.n.01', 'name': 'monoplane_flying_fish'}, {'id': 4908, 'synset': 'halfbeak.n.01', 'name': 'halfbeak'}, {'id': 4909, 'synset': 'saury.n.01', 'name': 'saury'}, {'id': 4910, 'synset': 'spiny-finned_fish.n.01', 'name': 'spiny-finned_fish'}, {'id': 4911, 'synset': 'lingcod.n.02', 'name': 'lingcod'}, {'id': 4912, 'synset': 'percoid_fish.n.01', 'name': 'percoid_fish'}, {'id': 4913, 'synset': 'perch.n.07', 'name': 'perch'}, {'id': 4914, 'synset': 'climbing_perch.n.01', 'name': 'climbing_perch'}, {'id': 4915, 'synset': 'perch.n.06', 'name': 'perch'}, {'id': 4916, 'synset': 'yellow_perch.n.01', 'name': 'yellow_perch'}, {'id': 4917, 'synset': 'european_perch.n.01', 'name': 'European_perch'}, {'id': 4918, 'synset': 'pike-perch.n.01', 'name': 'pike-perch'}, {'id': 4919, 'synset': 'walleye.n.02', 'name': 'walleye'}, {'id': 4920, 'synset': 'blue_pike.n.01', 'name': 'blue_pike'}, {'id': 4921, 'synset': 'snail_darter.n.01', 'name': 'snail_darter'}, {'id': 4922, 'synset': 'cusk-eel.n.01', 'name': 'cusk-eel'}, {'id': 4923, 'synset': 'brotula.n.01', 'name': 'brotula'}, {'id': 4924, 'synset': 'pearlfish.n.01', 'name': 'pearlfish'}, {'id': 4925, 'synset': 'robalo.n.01', 'name': 'robalo'}, {'id': 4926, 'synset': 'snook.n.01', 'name': 'snook'}, {'id': 4927, 'synset': 'pike.n.05', 'name': 'pike'}, {'id': 4928, 'synset': 'northern_pike.n.01', 'name': 'northern_pike'}, {'id': 4929, 'synset': 'muskellunge.n.02', 'name': 'muskellunge'}, {'id': 4930, 'synset': 'pickerel.n.02', 'name': 'pickerel'}, {'id': 4931, 'synset': 'chain_pickerel.n.01', 'name': 'chain_pickerel'}, {'id': 4932, 'synset': 'redfin_pickerel.n.01', 'name': 'redfin_pickerel'}, {'id': 4933, 'synset': 'sunfish.n.03', 'name': 'sunfish'}, {'id': 4934, 'synset': 'crappie.n.02', 'name': 'crappie'}, {'id': 4935, 'synset': 'black_crappie.n.01', 'name': 'black_crappie'}, {'id': 4936, 'synset': 'white_crappie.n.01', 'name': 'white_crappie'}, {'id': 4937, 'synset': 'freshwater_bream.n.02', 'name': 'freshwater_bream'}, {'id': 4938, 'synset': 'pumpkinseed.n.01', 'name': 'pumpkinseed'}, {'id': 4939, 'synset': 'bluegill.n.01', 'name': 'bluegill'}, {'id': 4940, 'synset': 'spotted_sunfish.n.01', 'name': 'spotted_sunfish'}, {'id': 4941, 'synset': 'freshwater_bass.n.02', 'name': 'freshwater_bass'}, {'id': 4942, 'synset': 'rock_bass.n.02', 'name': 'rock_bass'}, {'id': 4943, 'synset': 'black_bass.n.02', 'name': 'black_bass'}, {'id': 4944, 'synset': 'kentucky_black_bass.n.01', 'name': 'Kentucky_black_bass'}, {'id': 4945, 'synset': 'smallmouth.n.01', 'name': 'smallmouth'}, {'id': 4946, 'synset': 'largemouth.n.01', 'name': 'largemouth'}, {'id': 4947, 'synset': 'bass.n.08', 'name': 'bass'}, {'id': 4948, 'synset': 'serranid_fish.n.01', 'name': 'serranid_fish'}, {'id': 4949, 'synset': 'white_perch.n.01', 'name': 'white_perch'}, {'id': 4950, 'synset': 'yellow_bass.n.01', 'name': 'yellow_bass'}, {'id': 4951, 'synset': 'blackmouth_bass.n.01', 'name': 'blackmouth_bass'}, {'id': 4952, 'synset': 'rock_sea_bass.n.01', 'name': 'rock_sea_bass'}, {'id': 4953, 'synset': 'striped_bass.n.02', 'name': 'striped_bass'}, {'id': 4954, 'synset': 'stone_bass.n.01', 'name': 'stone_bass'}, {'id': 4955, 'synset': 'grouper.n.02', 'name': 'grouper'}, {'id': 4956, 'synset': 'hind.n.01', 'name': 'hind'}, {'id': 4957, 'synset': 'rock_hind.n.01', 'name': 'rock_hind'}, {'id': 4958, 'synset': 'creole-fish.n.01', 'name': 'creole-fish'}, {'id': 4959, 'synset': 'jewfish.n.02', 'name': 'jewfish'}, {'id': 4960, 'synset': 'soapfish.n.01', 'name': 'soapfish'}, {'id': 4961, 'synset': 'surfperch.n.01', 'name': 'surfperch'}, {'id': 4962, 'synset': 'rainbow_seaperch.n.01', 'name': 'rainbow_seaperch'}, {'id': 4963, 'synset': 'bigeye.n.01', 'name': 'bigeye'}, {'id': 4964, 'synset': 'catalufa.n.01', 'name': 'catalufa'}, {'id': 4965, 'synset': 'cardinalfish.n.01', 'name': 'cardinalfish'}, {'id': 4966, 'synset': 'flame_fish.n.01', 'name': 'flame_fish'}, {'id': 4967, 'synset': 'tilefish.n.02', 'name': 'tilefish'}, {'id': 4968, 'synset': 'bluefish.n.01', 'name': 'bluefish'}, {'id': 4969, 'synset': 'cobia.n.01', 'name': 'cobia'}, {'id': 4970, 'synset': 'remora.n.01', 'name': 'remora'}, {'id': 4971, 'synset': 'sharksucker.n.01', 'name': 'sharksucker'}, {'id': 4972, 'synset': 'whale_sucker.n.01', 'name': 'whale_sucker'}, {'id': 4973, 'synset': 'carangid_fish.n.01', 'name': 'carangid_fish'}, {'id': 4974, 'synset': 'jack.n.11', 'name': 'jack'}, {'id': 4975, 'synset': 'crevalle_jack.n.01', 'name': 'crevalle_jack'}, {'id': 4976, 'synset': 'yellow_jack.n.03', 'name': 'yellow_jack'}, {'id': 4977, 'synset': 'runner.n.10', 'name': 'runner'}, {'id': 4978, 'synset': 'rainbow_runner.n.01', 'name': 'rainbow_runner'}, {'id': 4979, 'synset': 'leatherjacket.n.02', 'name': 'leatherjacket'}, {'id': 4980, 'synset': 'threadfish.n.01', 'name': 'threadfish'}, {'id': 4981, 'synset': 'moonfish.n.01', 'name': 'moonfish'}, {'id': 4982, 'synset': 'lookdown.n.01', 'name': 'lookdown'}, {'id': 4983, 'synset': 'amberjack.n.01', 'name': 'amberjack'}, {'id': 4984, 'synset': 'yellowtail.n.02', 'name': 'yellowtail'}, {'id': 4985, 'synset': 'kingfish.n.05', 'name': 'kingfish'}, {'id': 4986, 'synset': 'pompano.n.02', 'name': 'pompano'}, {'id': 4987, 'synset': 'florida_pompano.n.01', 'name': 'Florida_pompano'}, {'id': 4988, 'synset': 'permit.n.03', 'name': 'permit'}, {'id': 4989, 'synset': 'scad.n.01', 'name': 'scad'}, {'id': 4990, 'synset': 'horse_mackerel.n.03', 'name': 'horse_mackerel'}, {'id': 4991, 'synset': 'horse_mackerel.n.02', 'name': 'horse_mackerel'}, {'id': 4992, 'synset': 'bigeye_scad.n.01', 'name': 'bigeye_scad'}, {'id': 4993, 'synset': 'mackerel_scad.n.01', 'name': 'mackerel_scad'}, {'id': 4994, 'synset': 'round_scad.n.01', 'name': 'round_scad'}, {'id': 4995, 'synset': 'dolphinfish.n.02', 'name': 'dolphinfish'}, {'id': 4996, 'synset': 'coryphaena_hippurus.n.01', 'name': 'Coryphaena_hippurus'}, {'id': 4997, 'synset': 'coryphaena_equisetis.n.01', 'name': 'Coryphaena_equisetis'}, {'id': 4998, 'synset': 'pomfret.n.01', 'name': 'pomfret'}, {'id': 4999, 'synset': 'characin.n.01', 'name': 'characin'}, {'id': 5000, 'synset': 'tetra.n.01', 'name': 'tetra'}, {'id': 5001, 'synset': 'cardinal_tetra.n.01', 'name': 'cardinal_tetra'}, {'id': 5002, 'synset': 'piranha.n.02', 'name': 'piranha'}, {'id': 5003, 'synset': 'cichlid.n.01', 'name': 'cichlid'}, {'id': 5004, 'synset': 'bolti.n.01', 'name': 'bolti'}, {'id': 5005, 'synset': 'snapper.n.05', 'name': 'snapper'}, {'id': 5006, 'synset': 'red_snapper.n.02', 'name': 'red_snapper'}, {'id': 5007, 'synset': 'grey_snapper.n.01', 'name': 'grey_snapper'}, {'id': 5008, 'synset': 'mutton_snapper.n.01', 'name': 'mutton_snapper'}, {'id': 5009, 'synset': 'schoolmaster.n.03', 'name': 'schoolmaster'}, {'id': 5010, 'synset': 'yellowtail.n.01', 'name': 'yellowtail'}, {'id': 5011, 'synset': 'grunt.n.03', 'name': 'grunt'}, {'id': 5012, 'synset': 'margate.n.01', 'name': 'margate'}, {'id': 5013, 'synset': 'spanish_grunt.n.01', 'name': 'Spanish_grunt'}, {'id': 5014, 'synset': 'tomtate.n.01', 'name': 'tomtate'}, {'id': 5015, 'synset': 'cottonwick.n.01', 'name': 'cottonwick'}, {'id': 5016, 'synset': "sailor's-choice.n.02", 'name': "sailor's-choice"}, {'id': 5017, 'synset': 'porkfish.n.01', 'name': 'porkfish'}, {'id': 5018, 'synset': 'pompon.n.02', 'name': 'pompon'}, {'id': 5019, 'synset': 'pigfish.n.02', 'name': 'pigfish'}, {'id': 5020, 'synset': 'sparid.n.01', 'name': 'sparid'}, {'id': 5021, 'synset': 'sea_bream.n.02', 'name': 'sea_bream'}, {'id': 5022, 'synset': 'porgy.n.02', 'name': 'porgy'}, {'id': 5023, 'synset': 'red_porgy.n.01', 'name': 'red_porgy'}, {'id': 5024, 'synset': 'european_sea_bream.n.01', 'name': 'European_sea_bream'}, {'id': 5025, 'synset': 'atlantic_sea_bream.n.01', 'name': 'Atlantic_sea_bream'}, {'id': 5026, 'synset': 'sheepshead.n.01', 'name': 'sheepshead'}, {'id': 5027, 'synset': 'pinfish.n.01', 'name': 'pinfish'}, {'id': 5028, 'synset': 'sheepshead_porgy.n.01', 'name': 'sheepshead_porgy'}, {'id': 5029, 'synset': 'snapper.n.04', 'name': 'snapper'}, {'id': 5030, 'synset': 'black_bream.n.01', 'name': 'black_bream'}, {'id': 5031, 'synset': 'scup.n.04', 'name': 'scup'}, {'id': 5032, 'synset': 'scup.n.03', 'name': 'scup'}, {'id': 5033, 'synset': 'sciaenid_fish.n.01', 'name': 'sciaenid_fish'}, {'id': 5034, 'synset': 'striped_drum.n.01', 'name': 'striped_drum'}, {'id': 5035, 'synset': 'jackknife-fish.n.01', 'name': 'jackknife-fish'}, {'id': 5036, 'synset': 'silver_perch.n.01', 'name': 'silver_perch'}, {'id': 5037, 'synset': 'red_drum.n.01', 'name': 'red_drum'}, {'id': 5038, 'synset': 'mulloway.n.01', 'name': 'mulloway'}, {'id': 5039, 'synset': 'maigre.n.01', 'name': 'maigre'}, {'id': 5040, 'synset': 'croaker.n.02', 'name': 'croaker'}, {'id': 5041, 'synset': 'atlantic_croaker.n.01', 'name': 'Atlantic_croaker'}, {'id': 5042, 'synset': 'yellowfin_croaker.n.01', 'name': 'yellowfin_croaker'}, {'id': 5043, 'synset': 'whiting.n.04', 'name': 'whiting'}, {'id': 5044, 'synset': 'kingfish.n.04', 'name': 'kingfish'}, {'id': 5045, 'synset': 'king_whiting.n.01', 'name': 'king_whiting'}, {'id': 5046, 'synset': 'northern_whiting.n.01', 'name': 'northern_whiting'}, {'id': 5047, 'synset': 'corbina.n.01', 'name': 'corbina'}, {'id': 5048, 'synset': 'white_croaker.n.02', 'name': 'white_croaker'}, {'id': 5049, 'synset': 'white_croaker.n.01', 'name': 'white_croaker'}, {'id': 5050, 'synset': 'sea_trout.n.02', 'name': 'sea_trout'}, {'id': 5051, 'synset': 'weakfish.n.02', 'name': 'weakfish'}, {'id': 5052, 'synset': 'spotted_weakfish.n.01', 'name': 'spotted_weakfish'}, {'id': 5053, 'synset': 'mullet.n.03', 'name': 'mullet'}, {'id': 5054, 'synset': 'goatfish.n.01', 'name': 'goatfish'}, {'id': 5055, 'synset': 'red_goatfish.n.01', 'name': 'red_goatfish'}, {'id': 5056, 'synset': 'yellow_goatfish.n.01', 'name': 'yellow_goatfish'}, {'id': 5057, 'synset': 'mullet.n.02', 'name': 'mullet'}, {'id': 5058, 'synset': 'striped_mullet.n.01', 'name': 'striped_mullet'}, {'id': 5059, 'synset': 'white_mullet.n.01', 'name': 'white_mullet'}, {'id': 5060, 'synset': 'liza.n.01', 'name': 'liza'}, {'id': 5061, 'synset': 'silversides.n.01', 'name': 'silversides'}, {'id': 5062, 'synset': 'jacksmelt.n.01', 'name': 'jacksmelt'}, {'id': 5063, 'synset': 'barracuda.n.01', 'name': 'barracuda'}, {'id': 5064, 'synset': 'great_barracuda.n.01', 'name': 'great_barracuda'}, {'id': 5065, 'synset': 'sweeper.n.03', 'name': 'sweeper'}, {'id': 5066, 'synset': 'sea_chub.n.01', 'name': 'sea_chub'}, {'id': 5067, 'synset': 'bermuda_chub.n.01', 'name': 'Bermuda_chub'}, {'id': 5068, 'synset': 'spadefish.n.01', 'name': 'spadefish'}, {'id': 5069, 'synset': 'butterfly_fish.n.01', 'name': 'butterfly_fish'}, {'id': 5070, 'synset': 'chaetodon.n.01', 'name': 'chaetodon'}, {'id': 5071, 'synset': 'angelfish.n.01', 'name': 'angelfish'}, {'id': 5072, 'synset': 'rock_beauty.n.01', 'name': 'rock_beauty'}, {'id': 5073, 'synset': 'damselfish.n.01', 'name': 'damselfish'}, {'id': 5074, 'synset': 'beaugregory.n.01', 'name': 'beaugregory'}, {'id': 5075, 'synset': 'anemone_fish.n.01', 'name': 'anemone_fish'}, {'id': 5076, 'synset': 'clown_anemone_fish.n.01', 'name': 'clown_anemone_fish'}, {'id': 5077, 'synset': 'sergeant_major.n.02', 'name': 'sergeant_major'}, {'id': 5078, 'synset': 'wrasse.n.01', 'name': 'wrasse'}, {'id': 5079, 'synset': 'pigfish.n.01', 'name': 'pigfish'}, {'id': 5080, 'synset': 'hogfish.n.01', 'name': 'hogfish'}, {'id': 5081, 'synset': 'slippery_dick.n.01', 'name': 'slippery_dick'}, {'id': 5082, 'synset': 'puddingwife.n.01', 'name': 'puddingwife'}, {'id': 5083, 'synset': 'bluehead.n.01', 'name': 'bluehead'}, {'id': 5084, 'synset': 'pearly_razorfish.n.01', 'name': 'pearly_razorfish'}, {'id': 5085, 'synset': 'tautog.n.01', 'name': 'tautog'}, {'id': 5086, 'synset': 'cunner.n.01', 'name': 'cunner'}, {'id': 5087, 'synset': 'parrotfish.n.01', 'name': 'parrotfish'}, {'id': 5088, 'synset': 'threadfin.n.01', 'name': 'threadfin'}, {'id': 5089, 'synset': 'jawfish.n.01', 'name': 'jawfish'}, {'id': 5090, 'synset': 'stargazer.n.03', 'name': 'stargazer'}, {'id': 5091, 'synset': 'sand_stargazer.n.01', 'name': 'sand_stargazer'}, {'id': 5092, 'synset': 'blenny.n.01', 'name': 'blenny'}, {'id': 5093, 'synset': 'shanny.n.01', 'name': 'shanny'}, {'id': 5094, 'synset': 'molly_miller.n.01', 'name': 'Molly_Miller'}, {'id': 5095, 'synset': 'clinid.n.01', 'name': 'clinid'}, {'id': 5096, 'synset': 'pikeblenny.n.01', 'name': 'pikeblenny'}, {'id': 5097, 'synset': 'bluethroat_pikeblenny.n.01', 'name': 'bluethroat_pikeblenny'}, {'id': 5098, 'synset': 'gunnel.n.02', 'name': 'gunnel'}, {'id': 5099, 'synset': 'rock_gunnel.n.01', 'name': 'rock_gunnel'}, {'id': 5100, 'synset': 'eelblenny.n.01', 'name': 'eelblenny'}, {'id': 5101, 'synset': 'wrymouth.n.01', 'name': 'wrymouth'}, {'id': 5102, 'synset': 'wolffish.n.01', 'name': 'wolffish'}, {'id': 5103, 'synset': 'viviparous_eelpout.n.01', 'name': 'viviparous_eelpout'}, {'id': 5104, 'synset': 'ocean_pout.n.01', 'name': 'ocean_pout'}, {'id': 5105, 'synset': 'sand_lance.n.01', 'name': 'sand_lance'}, {'id': 5106, 'synset': 'dragonet.n.01', 'name': 'dragonet'}, {'id': 5107, 'synset': 'goby.n.01', 'name': 'goby'}, {'id': 5108, 'synset': 'mudskipper.n.01', 'name': 'mudskipper'}, {'id': 5109, 'synset': 'sleeper.n.08', 'name': 'sleeper'}, {'id': 5110, 'synset': 'flathead.n.02', 'name': 'flathead'}, {'id': 5111, 'synset': 'archerfish.n.01', 'name': 'archerfish'}, {'id': 5112, 'synset': 'surgeonfish.n.01', 'name': 'surgeonfish'}, {'id': 5113, 'synset': 'gempylid.n.01', 'name': 'gempylid'}, {'id': 5114, 'synset': 'snake_mackerel.n.01', 'name': 'snake_mackerel'}, {'id': 5115, 'synset': 'escolar.n.01', 'name': 'escolar'}, {'id': 5116, 'synset': 'oilfish.n.01', 'name': 'oilfish'}, {'id': 5117, 'synset': 'cutlassfish.n.01', 'name': 'cutlassfish'}, {'id': 5118, 'synset': 'scombroid.n.01', 'name': 'scombroid'}, {'id': 5119, 'synset': 'mackerel.n.02', 'name': 'mackerel'}, {'id': 5120, 'synset': 'common_mackerel.n.01', 'name': 'common_mackerel'}, {'id': 5121, 'synset': 'spanish_mackerel.n.03', 'name': 'Spanish_mackerel'}, {'id': 5122, 'synset': 'chub_mackerel.n.01', 'name': 'chub_mackerel'}, {'id': 5123, 'synset': 'wahoo.n.03', 'name': 'wahoo'}, {'id': 5124, 'synset': 'spanish_mackerel.n.02', 'name': 'Spanish_mackerel'}, {'id': 5125, 'synset': 'king_mackerel.n.01', 'name': 'king_mackerel'}, {'id': 5126, 'synset': 'scomberomorus_maculatus.n.01', 'name': 'Scomberomorus_maculatus'}, {'id': 5127, 'synset': 'cero.n.01', 'name': 'cero'}, {'id': 5128, 'synset': 'sierra.n.02', 'name': 'sierra'}, {'id': 5129, 'synset': 'tuna.n.03', 'name': 'tuna'}, {'id': 5130, 'synset': 'albacore.n.02', 'name': 'albacore'}, {'id': 5131, 'synset': 'bluefin.n.02', 'name': 'bluefin'}, {'id': 5132, 'synset': 'yellowfin.n.01', 'name': 'yellowfin'}, {'id': 5133, 'synset': 'bonito.n.03', 'name': 'bonito'}, {'id': 5134, 'synset': 'skipjack.n.02', 'name': 'skipjack'}, {'id': 5135, 'synset': 'chile_bonito.n.01', 'name': 'Chile_bonito'}, {'id': 5136, 'synset': 'skipjack.n.01', 'name': 'skipjack'}, {'id': 5137, 'synset': 'bonito.n.02', 'name': 'bonito'}, {'id': 5138, 'synset': 'swordfish.n.02', 'name': 'swordfish'}, {'id': 5139, 'synset': 'sailfish.n.02', 'name': 'sailfish'}, {'id': 5140, 'synset': 'atlantic_sailfish.n.01', 'name': 'Atlantic_sailfish'}, {'id': 5141, 'synset': 'billfish.n.02', 'name': 'billfish'}, {'id': 5142, 'synset': 'marlin.n.01', 'name': 'marlin'}, {'id': 5143, 'synset': 'blue_marlin.n.01', 'name': 'blue_marlin'}, {'id': 5144, 'synset': 'black_marlin.n.01', 'name': 'black_marlin'}, {'id': 5145, 'synset': 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5160, 'synset': 'silver_jenny.n.01', 'name': 'silver_jenny'}, {'id': 5161, 'synset': 'whiting.n.03', 'name': 'whiting'}, {'id': 5162, 'synset': 'ganoid.n.01', 'name': 'ganoid'}, {'id': 5163, 'synset': 'bowfin.n.01', 'name': 'bowfin'}, {'id': 5164, 'synset': 'paddlefish.n.01', 'name': 'paddlefish'}, {'id': 5165, 'synset': 'chinese_paddlefish.n.01', 'name': 'Chinese_paddlefish'}, {'id': 5166, 'synset': 'sturgeon.n.01', 'name': 'sturgeon'}, {'id': 5167, 'synset': 'pacific_sturgeon.n.01', 'name': 'Pacific_sturgeon'}, {'id': 5168, 'synset': 'beluga.n.01', 'name': 'beluga'}, {'id': 5169, 'synset': 'gar.n.01', 'name': 'gar'}, {'id': 5170, 'synset': 'scorpaenoid.n.01', 'name': 'scorpaenoid'}, {'id': 5171, 'synset': 'scorpaenid.n.01', 'name': 'scorpaenid'}, {'id': 5172, 'synset': 'scorpionfish.n.01', 'name': 'scorpionfish'}, {'id': 5173, 'synset': 'plumed_scorpionfish.n.01', 'name': 'plumed_scorpionfish'}, {'id': 5174, 'synset': 'lionfish.n.01', 'name': 'lionfish'}, {'id': 5175, 'synset': 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5205, 'synset': 'balloonfish.n.01', 'name': 'balloonfish'}, {'id': 5206, 'synset': 'burrfish.n.01', 'name': 'burrfish'}, {'id': 5207, 'synset': 'ocean_sunfish.n.01', 'name': 'ocean_sunfish'}, {'id': 5208, 'synset': 'sharptail_mola.n.01', 'name': 'sharptail_mola'}, {'id': 5209, 'synset': 'flatfish.n.02', 'name': 'flatfish'}, {'id': 5210, 'synset': 'flounder.n.02', 'name': 'flounder'}, {'id': 5211, 'synset': 'righteye_flounder.n.01', 'name': 'righteye_flounder'}, {'id': 5212, 'synset': 'plaice.n.02', 'name': 'plaice'}, {'id': 5213, 'synset': 'european_flatfish.n.01', 'name': 'European_flatfish'}, {'id': 5214, 'synset': 'yellowtail_flounder.n.02', 'name': 'yellowtail_flounder'}, {'id': 5215, 'synset': 'winter_flounder.n.02', 'name': 'winter_flounder'}, {'id': 5216, 'synset': 'lemon_sole.n.05', 'name': 'lemon_sole'}, {'id': 5217, 'synset': 'american_plaice.n.01', 'name': 'American_plaice'}, {'id': 5218, 'synset': 'halibut.n.02', 'name': 'halibut'}, {'id': 5219, 'synset': 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'synset': 'hogchoker.n.01', 'name': 'hogchoker'}, {'id': 5235, 'synset': 'aba.n.02', 'name': 'aba'}, {'id': 5236, 'synset': 'abacus.n.02', 'name': 'abacus'}, {'id': 5237, 'synset': 'abandoned_ship.n.01', 'name': 'abandoned_ship'}, {'id': 5238, 'synset': 'a_battery.n.01', 'name': 'A_battery'}, {'id': 5239, 'synset': 'abattoir.n.01', 'name': 'abattoir'}, {'id': 5240, 'synset': 'abaya.n.01', 'name': 'abaya'}, {'id': 5241, 'synset': 'abbe_condenser.n.01', 'name': 'Abbe_condenser'}, {'id': 5242, 'synset': 'abbey.n.03', 'name': 'abbey'}, {'id': 5243, 'synset': 'abbey.n.02', 'name': 'abbey'}, {'id': 5244, 'synset': 'abbey.n.01', 'name': 'abbey'}, {'id': 5245, 'synset': 'abney_level.n.01', 'name': 'Abney_level'}, {'id': 5246, 'synset': 'abrader.n.01', 'name': 'abrader'}, {'id': 5247, 'synset': 'abrading_stone.n.01', 'name': 'abrading_stone'}, {'id': 5248, 'synset': 'abutment.n.02', 'name': 'abutment'}, {'id': 5249, 'synset': 'abutment_arch.n.01', 'name': 'abutment_arch'}, {'id': 5250, 'synset': 'academic_costume.n.01', 'name': 'academic_costume'}, {'id': 5251, 'synset': 'academic_gown.n.01', 'name': 'academic_gown'}, {'id': 5252, 'synset': 'accelerator.n.02', 'name': 'accelerator'}, {'id': 5253, 'synset': 'accelerator.n.04', 'name': 'accelerator'}, {'id': 5254, 'synset': 'accelerator.n.01', 'name': 'accelerator'}, {'id': 5255, 'synset': 'accelerometer.n.01', 'name': 'accelerometer'}, {'id': 5256, 'synset': 'accessory.n.01', 'name': 'accessory'}, {'id': 5257, 'synset': 'accommodating_lens_implant.n.01', 'name': 'accommodating_lens_implant'}, {'id': 5258, 'synset': 'accommodation.n.04', 'name': 'accommodation'}, {'id': 5259, 'synset': 'accordion.n.01', 'name': 'accordion'}, {'id': 5260, 'synset': 'acetate_disk.n.01', 'name': 'acetate_disk'}, {'id': 5261, 'synset': 'acetate_rayon.n.01', 'name': 'acetate_rayon'}, {'id': 5262, 'synset': 'achromatic_lens.n.01', 'name': 'achromatic_lens'}, {'id': 5263, 'synset': 'acoustic_delay_line.n.01', 'name': 'acoustic_delay_line'}, {'id': 5264, 'synset': 'acoustic_device.n.01', 'name': 'acoustic_device'}, {'id': 5265, 'synset': 'acoustic_guitar.n.01', 'name': 'acoustic_guitar'}, {'id': 5266, 'synset': 'acoustic_modem.n.01', 'name': 'acoustic_modem'}, {'id': 5267, 'synset': 'acropolis.n.01', 'name': 'acropolis'}, {'id': 5268, 'synset': 'acrylic.n.04', 'name': 'acrylic'}, {'id': 5269, 'synset': 'acrylic.n.03', 'name': 'acrylic'}, {'id': 5270, 'synset': 'actinometer.n.01', 'name': 'actinometer'}, {'id': 5271, 'synset': 'action.n.07', 'name': 'action'}, {'id': 5272, 'synset': 'active_matrix_screen.n.01', 'name': 'active_matrix_screen'}, {'id': 5273, 'synset': 'actuator.n.01', 'name': 'actuator'}, {'id': 5274, 'synset': 'adapter.n.02', 'name': 'adapter'}, {'id': 5275, 'synset': 'adder.n.02', 'name': 'adder'}, {'id': 5276, 'synset': 'adding_machine.n.01', 'name': 'adding_machine'}, {'id': 5277, 'synset': 'addressing_machine.n.01', 'name': 'addressing_machine'}, {'id': 5278, 'synset': 'adhesive_bandage.n.01', 'name': 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'air-to-air_missile.n.01', 'name': 'air-to-air_missile'}, {'id': 5326, 'synset': 'air-to-ground_missile.n.01', 'name': 'air-to-ground_missile'}, {'id': 5327, 'synset': 'aisle.n.03', 'name': 'aisle'}, {'id': 5328, 'synset': "aladdin's_lamp.n.01", 'name': "Aladdin's_lamp"}, {'id': 5329, 'synset': 'alarm.n.02', 'name': 'alarm'}, {'id': 5330, 'synset': 'alb.n.01', 'name': 'alb'}, {'id': 5331, 'synset': 'alcazar.n.01', 'name': 'alcazar'}, {'id': 5332, 'synset': 'alcohol_thermometer.n.01', 'name': 'alcohol_thermometer'}, {'id': 5333, 'synset': 'alehouse.n.01', 'name': 'alehouse'}, {'id': 5334, 'synset': 'alembic.n.01', 'name': 'alembic'}, {'id': 5335, 'synset': 'algometer.n.01', 'name': 'algometer'}, {'id': 5336, 'synset': 'alidade.n.02', 'name': 'alidade'}, {'id': 5337, 'synset': 'alidade.n.01', 'name': 'alidade'}, {'id': 5338, 'synset': 'a-line.n.01', 'name': 'A-line'}, {'id': 5339, 'synset': 'allen_screw.n.01', 'name': 'Allen_screw'}, {'id': 5340, 'synset': 'allen_wrench.n.01', 'name': 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5661, 'synset': 'barrel_organ.n.01', 'name': 'barrel_organ'}, {'id': 5662, 'synset': 'barrel_vault.n.01', 'name': 'barrel_vault'}, {'id': 5663, 'synset': 'barricade.n.02', 'name': 'barricade'}, {'id': 5664, 'synset': 'barrier.n.01', 'name': 'barrier'}, {'id': 5665, 'synset': 'barroom.n.01', 'name': 'barroom'}, {'id': 5666, 'synset': 'bascule.n.01', 'name': 'bascule'}, {'id': 5667, 'synset': 'base.n.08', 'name': 'base'}, {'id': 5668, 'synset': 'baseball_equipment.n.01', 'name': 'baseball_equipment'}, {'id': 5669, 'synset': 'basement.n.01', 'name': 'basement'}, {'id': 5670, 'synset': 'basement.n.02', 'name': 'basement'}, {'id': 5671, 'synset': 'basic_point_defense_missile_system.n.01', 'name': 'basic_point_defense_missile_system'}, {'id': 5672, 'synset': 'basilica.n.02', 'name': 'basilica'}, {'id': 5673, 'synset': 'basilica.n.01', 'name': 'basilica'}, {'id': 5674, 'synset': 'basilisk.n.02', 'name': 'basilisk'}, {'id': 5675, 'synset': 'basin.n.01', 'name': 'basin'}, {'id': 5676, 'synset': 'basinet.n.01', 'name': 'basinet'}, {'id': 5677, 'synset': 'basket.n.03', 'name': 'basket'}, {'id': 5678, 'synset': 'basketball_court.n.01', 'name': 'basketball_court'}, {'id': 5679, 'synset': 'basketball_equipment.n.01', 'name': 'basketball_equipment'}, {'id': 5680, 'synset': 'basket_weave.n.01', 'name': 'basket_weave'}, {'id': 5681, 'synset': 'bass.n.07', 'name': 'bass'}, {'id': 5682, 'synset': 'bass_clarinet.n.01', 'name': 'bass_clarinet'}, {'id': 5683, 'synset': 'bass_drum.n.01', 'name': 'bass_drum'}, {'id': 5684, 'synset': 'basset_horn.n.01', 'name': 'basset_horn'}, {'id': 5685, 'synset': 'bass_fiddle.n.01', 'name': 'bass_fiddle'}, {'id': 5686, 'synset': 'bass_guitar.n.01', 'name': 'bass_guitar'}, {'id': 5687, 'synset': 'bassinet.n.01', 'name': 'bassinet'}, {'id': 5688, 'synset': 'bassinet.n.02', 'name': 'bassinet'}, {'id': 5689, 'synset': 'bassoon.n.01', 'name': 'bassoon'}, {'id': 5690, 'synset': 'baster.n.03', 'name': 'baster'}, {'id': 5691, 'synset': 'bastinado.n.01', 'name': 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'synset': 'bedford_cord.n.01', 'name': 'Bedford_cord'}, {'id': 5756, 'synset': 'bed_jacket.n.01', 'name': 'bed_jacket'}, {'id': 5757, 'synset': 'bedpost.n.01', 'name': 'bedpost'}, {'id': 5758, 'synset': 'bedroll.n.01', 'name': 'bedroll'}, {'id': 5759, 'synset': 'bedroom.n.01', 'name': 'bedroom'}, {'id': 5760, 'synset': 'bedroom_furniture.n.01', 'name': 'bedroom_furniture'}, {'id': 5761, 'synset': 'bedsitting_room.n.01', 'name': 'bedsitting_room'}, {'id': 5762, 'synset': 'bedspring.n.01', 'name': 'bedspring'}, {'id': 5763, 'synset': 'bedstead.n.01', 'name': 'bedstead'}, {'id': 5764, 'synset': 'beefcake.n.01', 'name': 'beefcake'}, {'id': 5765, 'synset': 'beehive.n.04', 'name': 'beehive'}, {'id': 5766, 'synset': 'beer_barrel.n.01', 'name': 'beer_barrel'}, {'id': 5767, 'synset': 'beer_garden.n.01', 'name': 'beer_garden'}, {'id': 5768, 'synset': 'beer_glass.n.01', 'name': 'beer_glass'}, {'id': 5769, 'synset': 'beer_hall.n.01', 'name': 'beer_hall'}, {'id': 5770, 'synset': 'beer_mat.n.01', 'name': 'beer_mat'}, {'id': 5771, 'synset': 'beer_mug.n.01', 'name': 'beer_mug'}, {'id': 5772, 'synset': 'belaying_pin.n.01', 'name': 'belaying_pin'}, {'id': 5773, 'synset': 'belfry.n.02', 'name': 'belfry'}, {'id': 5774, 'synset': 'bell_arch.n.01', 'name': 'bell_arch'}, {'id': 5775, 'synset': 'bellarmine.n.02', 'name': 'bellarmine'}, {'id': 5776, 'synset': 'bellbottom_trousers.n.01', 'name': 'bellbottom_trousers'}, {'id': 5777, 'synset': 'bell_cote.n.01', 'name': 'bell_cote'}, {'id': 5778, 'synset': 'bell_foundry.n.01', 'name': 'bell_foundry'}, {'id': 5779, 'synset': 'bell_gable.n.01', 'name': 'bell_gable'}, {'id': 5780, 'synset': 'bell_jar.n.01', 'name': 'bell_jar'}, {'id': 5781, 'synset': 'bellows.n.01', 'name': 'bellows'}, {'id': 5782, 'synset': 'bellpull.n.01', 'name': 'bellpull'}, {'id': 5783, 'synset': 'bell_push.n.01', 'name': 'bell_push'}, {'id': 5784, 'synset': 'bell_seat.n.01', 'name': 'bell_seat'}, {'id': 5785, 'synset': 'bell_tent.n.01', 'name': 'bell_tent'}, {'id': 5786, 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{'id': 5802, 'synset': 'bevatron.n.01', 'name': 'bevatron'}, {'id': 5803, 'synset': 'bevel.n.02', 'name': 'bevel'}, {'id': 5804, 'synset': 'bevel_gear.n.01', 'name': 'bevel_gear'}, {'id': 5805, 'synset': 'b-flat_clarinet.n.01', 'name': 'B-flat_clarinet'}, {'id': 5806, 'synset': 'bib.n.01', 'name': 'bib'}, {'id': 5807, 'synset': 'bib-and-tucker.n.01', 'name': 'bib-and-tucker'}, {'id': 5808, 'synset': 'bicorn.n.01', 'name': 'bicorn'}, {'id': 5809, 'synset': 'bicycle-built-for-two.n.01', 'name': 'bicycle-built-for-two'}, {'id': 5810, 'synset': 'bicycle_chain.n.01', 'name': 'bicycle_chain'}, {'id': 5811, 'synset': 'bicycle_clip.n.01', 'name': 'bicycle_clip'}, {'id': 5812, 'synset': 'bicycle_pump.n.01', 'name': 'bicycle_pump'}, {'id': 5813, 'synset': 'bicycle_rack.n.01', 'name': 'bicycle_rack'}, {'id': 5814, 'synset': 'bicycle_seat.n.01', 'name': 'bicycle_seat'}, {'id': 5815, 'synset': 'bicycle_wheel.n.01', 'name': 'bicycle_wheel'}, {'id': 5816, 'synset': 'bidet.n.01', 'name': 'bidet'}, {'id': 5817, 'synset': 'bier.n.02', 'name': 'bier'}, {'id': 5818, 'synset': 'bier.n.01', 'name': 'bier'}, {'id': 5819, 'synset': 'bi-fold_door.n.01', 'name': 'bi-fold_door'}, {'id': 5820, 'synset': 'bifocals.n.01', 'name': 'bifocals'}, {'id': 5821, 'synset': 'big_blue.n.01', 'name': 'Big_Blue'}, {'id': 5822, 'synset': 'big_board.n.02', 'name': 'big_board'}, {'id': 5823, 'synset': 'bight.n.04', 'name': 'bight'}, {'id': 5824, 'synset': 'bikini.n.02', 'name': 'bikini'}, {'id': 5825, 'synset': 'bikini_pants.n.01', 'name': 'bikini_pants'}, {'id': 5826, 'synset': 'bilge.n.02', 'name': 'bilge'}, {'id': 5827, 'synset': 'bilge_keel.n.01', 'name': 'bilge_keel'}, {'id': 5828, 'synset': 'bilge_pump.n.01', 'name': 'bilge_pump'}, {'id': 5829, 'synset': 'bilge_well.n.01', 'name': 'bilge_well'}, {'id': 5830, 'synset': 'bill.n.08', 'name': 'bill'}, {'id': 5831, 'synset': 'billiard_ball.n.01', 'name': 'billiard_ball'}, {'id': 5832, 'synset': 'billiard_room.n.01', 'name': 'billiard_room'}, {'id': 5833, 'synset': 'bin.n.01', 'name': 'bin'}, {'id': 5834, 'synset': 'binder.n.04', 'name': 'binder'}, {'id': 5835, 'synset': 'bindery.n.01', 'name': 'bindery'}, {'id': 5836, 'synset': 'binding.n.05', 'name': 'binding'}, {'id': 5837, 'synset': 'bin_liner.n.01', 'name': 'bin_liner'}, {'id': 5838, 'synset': 'binnacle.n.01', 'name': 'binnacle'}, {'id': 5839, 'synset': 'binocular_microscope.n.01', 'name': 'binocular_microscope'}, {'id': 5840, 'synset': 'biochip.n.01', 'name': 'biochip'}, {'id': 5841, 'synset': 'biohazard_suit.n.01', 'name': 'biohazard_suit'}, {'id': 5842, 'synset': 'bioscope.n.02', 'name': 'bioscope'}, {'id': 5843, 'synset': 'biplane.n.01', 'name': 'biplane'}, {'id': 5844, 'synset': 'birch.n.03', 'name': 'birch'}, {'id': 5845, 'synset': 'birchbark_canoe.n.01', 'name': 'birchbark_canoe'}, {'id': 5846, 'synset': 'birdcall.n.02', 'name': 'birdcall'}, {'id': 5847, 'synset': 'bird_shot.n.01', 'name': 'bird_shot'}, {'id': 5848, 'synset': 'biretta.n.01', 'name': 'biretta'}, {'id': 5849, 'synset': 'bishop.n.03', 'name': 'bishop'}, {'id': 5850, 'synset': 'bistro.n.01', 'name': 'bistro'}, {'id': 5851, 'synset': 'bit.n.11', 'name': 'bit'}, {'id': 5852, 'synset': 'bit.n.05', 'name': 'bit'}, {'id': 5853, 'synset': 'bite_plate.n.01', 'name': 'bite_plate'}, {'id': 5854, 'synset': 'bitewing.n.01', 'name': 'bitewing'}, {'id': 5855, 'synset': 'bitumastic.n.01', 'name': 'bitumastic'}, {'id': 5856, 'synset': 'black.n.07', 'name': 'black'}, {'id': 5857, 'synset': 'black.n.06', 'name': 'black'}, {'id': 5858, 'synset': 'blackboard_eraser.n.01', 'name': 'blackboard_eraser'}, {'id': 5859, 'synset': 'black_box.n.01', 'name': 'black_box'}, {'id': 5860, 'synset': 'blackface.n.01', 'name': 'blackface'}, {'id': 5861, 'synset': 'blackjack.n.02', 'name': 'blackjack'}, {'id': 5862, 'synset': 'black_tie.n.02', 'name': 'black_tie'}, {'id': 5863, 'synset': 'blackwash.n.03', 'name': 'blackwash'}, {'id': 5864, 'synset': 'bladder.n.02', 'name': 'bladder'}, {'id': 5865, 'synset': 'blade.n.09', 'name': 'blade'}, {'id': 5866, 'synset': 'blade.n.08', 'name': 'blade'}, {'id': 5867, 'synset': 'blade.n.07', 'name': 'blade'}, {'id': 5868, 'synset': 'blank.n.04', 'name': 'blank'}, {'id': 5869, 'synset': 'blast_furnace.n.01', 'name': 'blast_furnace'}, {'id': 5870, 'synset': 'blasting_cap.n.01', 'name': 'blasting_cap'}, {'id': 5871, 'synset': 'blind.n.03', 'name': 'blind'}, {'id': 5872, 'synset': 'blind_curve.n.01', 'name': 'blind_curve'}, {'id': 5873, 'synset': 'blindfold.n.01', 'name': 'blindfold'}, {'id': 5874, 'synset': 'bling.n.01', 'name': 'bling'}, {'id': 5875, 'synset': 'blister_pack.n.01', 'name': 'blister_pack'}, {'id': 5876, 'synset': 'block.n.05', 'name': 'block'}, {'id': 5877, 'synset': 'blockade.n.02', 'name': 'blockade'}, {'id': 5878, 'synset': 'blockade-runner.n.01', 'name': 'blockade-runner'}, {'id': 5879, 'synset': 'block_and_tackle.n.01', 'name': 'block_and_tackle'}, {'id': 5880, 'synset': 'blockbuster.n.01', 'name': 'blockbuster'}, {'id': 5881, 'synset': 'blockhouse.n.01', 'name': 'blockhouse'}, {'id': 5882, 'synset': 'block_plane.n.01', 'name': 'block_plane'}, {'id': 5883, 'synset': 'bloodmobile.n.01', 'name': 'bloodmobile'}, {'id': 5884, 'synset': 'bloomers.n.01', 'name': 'bloomers'}, {'id': 5885, 'synset': 'blower.n.01', 'name': 'blower'}, {'id': 5886, 'synset': 'blowtorch.n.01', 'name': 'blowtorch'}, {'id': 5887, 'synset': 'blucher.n.02', 'name': 'blucher'}, {'id': 5888, 'synset': 'bludgeon.n.01', 'name': 'bludgeon'}, {'id': 5889, 'synset': 'blue.n.02', 'name': 'blue'}, {'id': 5890, 'synset': 'blue_chip.n.02', 'name': 'blue_chip'}, {'id': 5891, 'synset': 'blunderbuss.n.01', 'name': 'blunderbuss'}, {'id': 5892, 'synset': 'blunt_file.n.01', 'name': 'blunt_file'}, {'id': 5893, 'synset': 'boarding.n.02', 'name': 'boarding'}, {'id': 5894, 'synset': 'boarding_house.n.01', 'name': 'boarding_house'}, {'id': 5895, 'synset': 'boardroom.n.01', 'name': 'boardroom'}, {'id': 5896, 'synset': 'boards.n.02', 'name': 'boards'}, {'id': 5897, 'synset': 'boater.n.01', 'name': 'boater'}, {'id': 5898, 'synset': 'boat_hook.n.01', 'name': 'boat_hook'}, {'id': 5899, 'synset': 'boathouse.n.01', 'name': 'boathouse'}, {'id': 5900, 'synset': "boatswain's_chair.n.01", 'name': "boatswain's_chair"}, {'id': 5901, 'synset': 'boat_train.n.01', 'name': 'boat_train'}, {'id': 5902, 'synset': 'boatyard.n.01', 'name': 'boatyard'}, {'id': 5903, 'synset': 'bobsled.n.02', 'name': 'bobsled'}, {'id': 5904, 'synset': 'bobsled.n.01', 'name': 'bobsled'}, {'id': 5905, 'synset': 'bocce_ball.n.01', 'name': 'bocce_ball'}, {'id': 5906, 'synset': 'bodega.n.01', 'name': 'bodega'}, {'id': 5907, 'synset': 'bodice.n.01', 'name': 'bodice'}, {'id': 5908, 'synset': 'bodkin.n.04', 'name': 'bodkin'}, {'id': 5909, 'synset': 'bodkin.n.03', 'name': 'bodkin'}, {'id': 5910, 'synset': 'bodkin.n.02', 'name': 'bodkin'}, {'id': 5911, 'synset': 'body.n.11', 'name': 'body'}, {'id': 5912, 'synset': 'body_armor.n.01', 'name': 'body_armor'}, {'id': 5913, 'synset': 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{'id': 5945, 'synset': 'bookmobile.n.01', 'name': 'bookmobile'}, {'id': 5946, 'synset': 'bookshelf.n.01', 'name': 'bookshelf'}, {'id': 5947, 'synset': 'bookshop.n.01', 'name': 'bookshop'}, {'id': 5948, 'synset': 'boom.n.05', 'name': 'boom'}, {'id': 5949, 'synset': 'boomerang.n.01', 'name': 'boomerang'}, {'id': 5950, 'synset': 'booster.n.05', 'name': 'booster'}, {'id': 5951, 'synset': 'booster.n.04', 'name': 'booster'}, {'id': 5952, 'synset': 'boot.n.04', 'name': 'boot'}, {'id': 5953, 'synset': 'boot_camp.n.01', 'name': 'boot_camp'}, {'id': 5954, 'synset': 'bootee.n.01', 'name': 'bootee'}, {'id': 5955, 'synset': 'booth.n.02', 'name': 'booth'}, {'id': 5956, 'synset': 'booth.n.04', 'name': 'booth'}, {'id': 5957, 'synset': 'booth.n.01', 'name': 'booth'}, {'id': 5958, 'synset': 'boothose.n.01', 'name': 'boothose'}, {'id': 5959, 'synset': 'bootjack.n.01', 'name': 'bootjack'}, {'id': 5960, 'synset': 'bootlace.n.01', 'name': 'bootlace'}, {'id': 5961, 'synset': 'bootleg.n.02', 'name': 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{'id': 5993, 'synset': 'bowsprit.n.01', 'name': 'bowsprit'}, {'id': 5994, 'synset': 'bowstring.n.01', 'name': 'bowstring'}, {'id': 5995, 'synset': 'box.n.02', 'name': 'box'}, {'id': 5996, 'synset': 'box.n.08', 'name': 'box'}, {'id': 5997, 'synset': 'box_beam.n.01', 'name': 'box_beam'}, {'id': 5998, 'synset': 'box_camera.n.01', 'name': 'box_camera'}, {'id': 5999, 'synset': 'boxcar.n.01', 'name': 'boxcar'}, {'id': 6000, 'synset': 'box_coat.n.01', 'name': 'box_coat'}, {'id': 6001, 'synset': 'boxing_equipment.n.01', 'name': 'boxing_equipment'}, {'id': 6002, 'synset': 'box_office.n.02', 'name': 'box_office'}, {'id': 6003, 'synset': 'box_spring.n.01', 'name': 'box_spring'}, {'id': 6004, 'synset': 'box_wrench.n.01', 'name': 'box_wrench'}, {'id': 6005, 'synset': 'brace.n.09', 'name': 'brace'}, {'id': 6006, 'synset': 'brace.n.07', 'name': 'brace'}, {'id': 6007, 'synset': 'brace.n.01', 'name': 'brace'}, {'id': 6008, 'synset': 'brace_and_bit.n.01', 'name': 'brace_and_bit'}, {'id': 6009, 'synset': 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6071, 'synset': 'britches.n.01', 'name': 'britches'}, {'id': 6072, 'synset': 'broad_arrow.n.03', 'name': 'broad_arrow'}, {'id': 6073, 'synset': 'broadax.n.01', 'name': 'broadax'}, {'id': 6074, 'synset': 'brochette.n.01', 'name': 'brochette'}, {'id': 6075, 'synset': 'broadcaster.n.02', 'name': 'broadcaster'}, {'id': 6076, 'synset': 'broadcloth.n.02', 'name': 'broadcloth'}, {'id': 6077, 'synset': 'broadcloth.n.01', 'name': 'broadcloth'}, {'id': 6078, 'synset': 'broad_hatchet.n.01', 'name': 'broad_hatchet'}, {'id': 6079, 'synset': 'broadloom.n.01', 'name': 'broadloom'}, {'id': 6080, 'synset': 'broadside.n.03', 'name': 'broadside'}, {'id': 6081, 'synset': 'broadsword.n.01', 'name': 'broadsword'}, {'id': 6082, 'synset': 'brocade.n.01', 'name': 'brocade'}, {'id': 6083, 'synset': 'brogan.n.01', 'name': 'brogan'}, {'id': 6084, 'synset': 'broiler.n.01', 'name': 'broiler'}, {'id': 6085, 'synset': 'broken_arch.n.01', 'name': 'broken_arch'}, {'id': 6086, 'synset': 'bronchoscope.n.01', 'name': 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{'id': 6101, 'synset': 'bucket_seat.n.01', 'name': 'bucket_seat'}, {'id': 6102, 'synset': 'bucket_shop.n.02', 'name': 'bucket_shop'}, {'id': 6103, 'synset': 'buckle.n.01', 'name': 'buckle'}, {'id': 6104, 'synset': 'buckram.n.01', 'name': 'buckram'}, {'id': 6105, 'synset': 'bucksaw.n.01', 'name': 'bucksaw'}, {'id': 6106, 'synset': 'buckskins.n.01', 'name': 'buckskins'}, {'id': 6107, 'synset': 'buff.n.05', 'name': 'buff'}, {'id': 6108, 'synset': 'buffer.n.05', 'name': 'buffer'}, {'id': 6109, 'synset': 'buffer.n.04', 'name': 'buffer'}, {'id': 6110, 'synset': 'buffet.n.01', 'name': 'buffet'}, {'id': 6111, 'synset': 'buffing_wheel.n.01', 'name': 'buffing_wheel'}, {'id': 6112, 'synset': 'bugle.n.01', 'name': 'bugle'}, {'id': 6113, 'synset': 'building.n.01', 'name': 'building'}, {'id': 6114, 'synset': 'building_complex.n.01', 'name': 'building_complex'}, {'id': 6115, 'synset': 'bulldog_clip.n.01', 'name': 'bulldog_clip'}, {'id': 6116, 'synset': 'bulldog_wrench.n.01', 'name': 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'butcher_shop'}, {'id': 6166, 'synset': 'butter_dish.n.01', 'name': 'butter_dish'}, {'id': 6167, 'synset': 'butterfly_valve.n.01', 'name': 'butterfly_valve'}, {'id': 6168, 'synset': 'butter_knife.n.01', 'name': 'butter_knife'}, {'id': 6169, 'synset': 'butt_hinge.n.01', 'name': 'butt_hinge'}, {'id': 6170, 'synset': 'butt_joint.n.01', 'name': 'butt_joint'}, {'id': 6171, 'synset': 'buttonhook.n.01', 'name': 'buttonhook'}, {'id': 6172, 'synset': 'buttress.n.01', 'name': 'buttress'}, {'id': 6173, 'synset': 'butt_shaft.n.01', 'name': 'butt_shaft'}, {'id': 6174, 'synset': 'butt_weld.n.01', 'name': 'butt_weld'}, {'id': 6175, 'synset': 'buzz_bomb.n.01', 'name': 'buzz_bomb'}, {'id': 6176, 'synset': 'buzzer.n.02', 'name': 'buzzer'}, {'id': 6177, 'synset': 'bvd.n.01', 'name': 'BVD'}, {'id': 6178, 'synset': 'bypass_condenser.n.01', 'name': 'bypass_condenser'}, {'id': 6179, 'synset': 'byway.n.01', 'name': 'byway'}, {'id': 6180, 'synset': 'cab.n.02', 'name': 'cab'}, {'id': 6181, 'synset': 'cab.n.01', 'name': 'cab'}, {'id': 6182, 'synset': 'cabaret.n.01', 'name': 'cabaret'}, {'id': 6183, 'synset': 'caber.n.01', 'name': 'caber'}, {'id': 6184, 'synset': 'cabin.n.03', 'name': 'cabin'}, {'id': 6185, 'synset': 'cabin.n.02', 'name': 'cabin'}, {'id': 6186, 'synset': 'cabin_class.n.01', 'name': 'cabin_class'}, {'id': 6187, 'synset': 'cabin_cruiser.n.01', 'name': 'cabin_cruiser'}, {'id': 6188, 'synset': 'cabinet.n.04', 'name': 'cabinet'}, {'id': 6189, 'synset': 'cabinetwork.n.01', 'name': 'cabinetwork'}, {'id': 6190, 'synset': 'cabin_liner.n.01', 'name': 'cabin_liner'}, {'id': 6191, 'synset': 'cable.n.06', 'name': 'cable'}, {'id': 6192, 'synset': 'cable.n.02', 'name': 'cable'}, {'id': 6193, 'synset': 'cable_car.n.01', 'name': 'cable_car'}, {'id': 6194, 'synset': 'cache.n.03', 'name': 'cache'}, {'id': 6195, 'synset': 'caddy.n.01', 'name': 'caddy'}, {'id': 6196, 'synset': 'caesium_clock.n.01', 'name': 'caesium_clock'}, {'id': 6197, 'synset': 'cafe.n.01', 'name': 'cafe'}, {'id': 6198, 'synset': 'cafeteria.n.01', 'name': 'cafeteria'}, {'id': 6199, 'synset': 'cafeteria_tray.n.01', 'name': 'cafeteria_tray'}, {'id': 6200, 'synset': 'caff.n.01', 'name': 'caff'}, {'id': 6201, 'synset': 'caftan.n.02', 'name': 'caftan'}, {'id': 6202, 'synset': 'caftan.n.01', 'name': 'caftan'}, {'id': 6203, 'synset': 'cage.n.01', 'name': 'cage'}, {'id': 6204, 'synset': 'cage.n.04', 'name': 'cage'}, {'id': 6205, 'synset': 'cagoule.n.01', 'name': 'cagoule'}, {'id': 6206, 'synset': 'caisson.n.02', 'name': 'caisson'}, {'id': 6207, 'synset': 'calash.n.02', 'name': 'calash'}, {'id': 6208, 'synset': 'calceus.n.01', 'name': 'calceus'}, {'id': 6209, 'synset': 'calcimine.n.01', 'name': 'calcimine'}, {'id': 6210, 'synset': 'caldron.n.01', 'name': 'caldron'}, {'id': 6211, 'synset': 'calico.n.01', 'name': 'calico'}, {'id': 6212, 'synset': 'caliper.n.01', 'name': 'caliper'}, {'id': 6213, 'synset': 'call-board.n.01', 'name': 'call-board'}, {'id': 6214, 'synset': 'call_center.n.01', 'name': 'call_center'}, {'id': 6215, 'synset': 'caller_id.n.01', 'name': 'caller_ID'}, {'id': 6216, 'synset': 'calliope.n.02', 'name': 'calliope'}, {'id': 6217, 'synset': 'calorimeter.n.01', 'name': 'calorimeter'}, {'id': 6218, 'synset': 'calpac.n.01', 'name': 'calpac'}, {'id': 6219, 'synset': 'camail.n.01', 'name': 'camail'}, {'id': 6220, 'synset': 'camber_arch.n.01', 'name': 'camber_arch'}, {'id': 6221, 'synset': 'cambric.n.01', 'name': 'cambric'}, {'id': 6222, 'synset': "camel's_hair.n.01", 'name': "camel's_hair"}, {'id': 6223, 'synset': 'camera_lucida.n.01', 'name': 'camera_lucida'}, {'id': 6224, 'synset': 'camera_obscura.n.01', 'name': 'camera_obscura'}, {'id': 6225, 'synset': 'camera_tripod.n.01', 'name': 'camera_tripod'}, {'id': 6226, 'synset': 'camise.n.01', 'name': 'camise'}, {'id': 6227, 'synset': 'camisole.n.02', 'name': 'camisole'}, {'id': 6228, 'synset': 'camisole.n.01', 'name': 'camisole'}, {'id': 6229, 'synset': 'camlet.n.02', 'name': 'camlet'}, {'id': 6230, 'synset': 'camouflage.n.03', 'name': 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'name': 'candlesnuffer'}, {'id': 6247, 'synset': 'candlewick.n.02', 'name': 'candlewick'}, {'id': 6248, 'synset': 'candy_thermometer.n.01', 'name': 'candy_thermometer'}, {'id': 6249, 'synset': 'cane.n.03', 'name': 'cane'}, {'id': 6250, 'synset': 'cangue.n.01', 'name': 'cangue'}, {'id': 6251, 'synset': 'cannery.n.01', 'name': 'cannery'}, {'id': 6252, 'synset': 'cannikin.n.02', 'name': 'cannikin'}, {'id': 6253, 'synset': 'cannikin.n.01', 'name': 'cannikin'}, {'id': 6254, 'synset': 'cannon.n.01', 'name': 'cannon'}, {'id': 6255, 'synset': 'cannon.n.04', 'name': 'cannon'}, {'id': 6256, 'synset': 'cannon.n.03', 'name': 'cannon'}, {'id': 6257, 'synset': 'cannon.n.02', 'name': 'cannon'}, {'id': 6258, 'synset': 'cannonball.n.01', 'name': 'cannonball'}, {'id': 6259, 'synset': 'canopic_jar.n.01', 'name': 'canopic_jar'}, {'id': 6260, 'synset': 'canopy.n.03', 'name': 'canopy'}, {'id': 6261, 'synset': 'canopy.n.02', 'name': 'canopy'}, {'id': 6262, 'synset': 'canopy.n.01', 'name': 'canopy'}, {'id': 6263, 'synset': 'canteen.n.05', 'name': 'canteen'}, {'id': 6264, 'synset': 'canteen.n.04', 'name': 'canteen'}, {'id': 6265, 'synset': 'canteen.n.03', 'name': 'canteen'}, {'id': 6266, 'synset': 'canteen.n.02', 'name': 'canteen'}, {'id': 6267, 'synset': 'cant_hook.n.01', 'name': 'cant_hook'}, {'id': 6268, 'synset': 'cantilever.n.01', 'name': 'cantilever'}, {'id': 6269, 'synset': 'cantilever_bridge.n.01', 'name': 'cantilever_bridge'}, {'id': 6270, 'synset': 'cantle.n.01', 'name': 'cantle'}, {'id': 6271, 'synset': 'canton_crepe.n.01', 'name': 'Canton_crepe'}, {'id': 6272, 'synset': 'canvas.n.01', 'name': 'canvas'}, {'id': 6273, 'synset': 'canvas.n.06', 'name': 'canvas'}, {'id': 6274, 'synset': 'canvas_tent.n.01', 'name': 'canvas_tent'}, {'id': 6275, 'synset': 'cap.n.04', 'name': 'cap'}, {'id': 6276, 'synset': 'capacitor.n.01', 'name': 'capacitor'}, {'id': 6277, 'synset': 'caparison.n.01', 'name': 'caparison'}, {'id': 6278, 'synset': 'capital_ship.n.01', 'name': 'capital_ship'}, {'id': 6279, 'synset': 'capitol.n.01', 'name': 'capitol'}, {'id': 6280, 'synset': 'cap_opener.n.01', 'name': 'cap_opener'}, {'id': 6281, 'synset': 'capote.n.02', 'name': 'capote'}, {'id': 6282, 'synset': 'capote.n.01', 'name': 'capote'}, {'id': 6283, 'synset': 'cap_screw.n.01', 'name': 'cap_screw'}, {'id': 6284, 'synset': 'capstan.n.01', 'name': 'capstan'}, {'id': 6285, 'synset': 'capstone.n.02', 'name': 'capstone'}, {'id': 6286, 'synset': 'capsule.n.01', 'name': 'capsule'}, {'id': 6287, 'synset': "captain's_chair.n.01", 'name': "captain's_chair"}, {'id': 6288, 'synset': 'carabiner.n.01', 'name': 'carabiner'}, {'id': 6289, 'synset': 'carafe.n.01', 'name': 'carafe'}, {'id': 6290, 'synset': 'caravansary.n.01', 'name': 'caravansary'}, {'id': 6291, 'synset': 'carbine.n.01', 'name': 'carbine'}, {'id': 6292, 'synset': 'car_bomb.n.01', 'name': 'car_bomb'}, {'id': 6293, 'synset': 'carbon_arc_lamp.n.01', 'name': 'carbon_arc_lamp'}, {'id': 6294, 'synset': 'carboy.n.01', 'name': 'carboy'}, {'id': 6295, 'synset': 'carburetor.n.01', 'name': 'carburetor'}, {'id': 6296, 'synset': 'car_carrier.n.01', 'name': 'car_carrier'}, {'id': 6297, 'synset': 'cardcase.n.01', 'name': 'cardcase'}, {'id': 6298, 'synset': 'cardiac_monitor.n.01', 'name': 'cardiac_monitor'}, {'id': 6299, 'synset': 'card_index.n.01', 'name': 'card_index'}, {'id': 6300, 'synset': 'cardiograph.n.01', 'name': 'cardiograph'}, {'id': 6301, 'synset': 'cardioid_microphone.n.01', 'name': 'cardioid_microphone'}, {'id': 6302, 'synset': 'car_door.n.01', 'name': 'car_door'}, {'id': 6303, 'synset': 'cardroom.n.01', 'name': 'cardroom'}, {'id': 6304, 'synset': 'card_table.n.02', 'name': 'card_table'}, {'id': 6305, 'synset': 'card_table.n.01', 'name': 'card_table'}, {'id': 6306, 'synset': 'car-ferry.n.01', 'name': 'car-ferry'}, {'id': 6307, 'synset': 'cargo_area.n.01', 'name': 'cargo_area'}, {'id': 6308, 'synset': 'cargo_container.n.01', 'name': 'cargo_container'}, {'id': 6309, 'synset': 'cargo_door.n.01', 'name': 'cargo_door'}, {'id': 6310, 'synset': 'cargo_hatch.n.01', 'name': 'cargo_hatch'}, {'id': 6311, 'synset': 'cargo_helicopter.n.01', 'name': 'cargo_helicopter'}, {'id': 6312, 'synset': 'cargo_liner.n.01', 'name': 'cargo_liner'}, {'id': 6313, 'synset': 'carillon.n.01', 'name': 'carillon'}, {'id': 6314, 'synset': 'car_mirror.n.01', 'name': 'car_mirror'}, {'id': 6315, 'synset': 'caroche.n.01', 'name': 'caroche'}, {'id': 6316, 'synset': 'carousel.n.02', 'name': 'carousel'}, {'id': 6317, 'synset': "carpenter's_hammer.n.01", 'name': "carpenter's_hammer"}, {'id': 6318, 'synset': "carpenter's_kit.n.01", 'name': "carpenter's_kit"}, {'id': 6319, 'synset': "carpenter's_level.n.01", 'name': "carpenter's_level"}, {'id': 6320, 'synset': "carpenter's_mallet.n.01", 'name': "carpenter's_mallet"}, {'id': 6321, 'synset': "carpenter's_rule.n.01", 'name': "carpenter's_rule"}, {'id': 6322, 'synset': "carpenter's_square.n.01", 'name': "carpenter's_square"}, {'id': 6323, 'synset': 'carpetbag.n.01', 'name': 'carpetbag'}, {'id': 6324, 'synset': 'carpet_beater.n.01', 'name': 'carpet_beater'}, {'id': 6325, 'synset': 'carpet_loom.n.01', 'name': 'carpet_loom'}, {'id': 6326, 'synset': 'carpet_pad.n.01', 'name': 'carpet_pad'}, {'id': 6327, 'synset': 'carpet_sweeper.n.01', 'name': 'carpet_sweeper'}, {'id': 6328, 'synset': 'carpet_tack.n.01', 'name': 'carpet_tack'}, {'id': 6329, 'synset': 'carport.n.01', 'name': 'carport'}, {'id': 6330, 'synset': 'carrack.n.01', 'name': 'carrack'}, {'id': 6331, 'synset': 'carrel.n.02', 'name': 'carrel'}, {'id': 6332, 'synset': 'carriage.n.04', 'name': 'carriage'}, {'id': 6333, 'synset': 'carriage_bolt.n.01', 'name': 'carriage_bolt'}, {'id': 6334, 'synset': 'carriageway.n.01', 'name': 'carriageway'}, {'id': 6335, 'synset': 'carriage_wrench.n.01', 'name': 'carriage_wrench'}, {'id': 6336, 'synset': 'carrick_bend.n.01', 'name': 'carrick_bend'}, {'id': 6337, 'synset': 'carrier.n.10', 'name': 'carrier'}, {'id': 6338, 'synset': 'carrycot.n.01', 'name': 'carrycot'}, {'id': 6339, 'synset': 'car_seat.n.01', 'name': 'car_seat'}, {'id': 6340, 'synset': 'car_tire.n.01', 'name': 'car_tire'}, {'id': 6341, 'synset': 'cartouche.n.01', 'name': 'cartouche'}, {'id': 6342, 'synset': 'car_train.n.01', 'name': 'car_train'}, {'id': 6343, 'synset': 'cartridge.n.01', 'name': 'cartridge'}, {'id': 6344, 'synset': 'cartridge.n.04', 'name': 'cartridge'}, {'id': 6345, 'synset': 'cartridge_belt.n.01', 'name': 'cartridge_belt'}, {'id': 6346, 'synset': 'cartridge_extractor.n.01', 'name': 'cartridge_extractor'}, {'id': 6347, 'synset': 'cartridge_fuse.n.01', 'name': 'cartridge_fuse'}, {'id': 6348, 'synset': 'cartridge_holder.n.01', 'name': 'cartridge_holder'}, {'id': 6349, 'synset': 'cartwheel.n.01', 'name': 'cartwheel'}, {'id': 6350, 'synset': 'carving_fork.n.01', 'name': 'carving_fork'}, {'id': 6351, 'synset': 'carving_knife.n.01', 'name': 'carving_knife'}, {'id': 6352, 'synset': 'car_wheel.n.01', 'name': 'car_wheel'}, {'id': 6353, 'synset': 'caryatid.n.01', 'name': 'caryatid'}, {'id': 6354, 'synset': 'cascade_liquefier.n.01', 'name': 'cascade_liquefier'}, {'id': 6355, 'synset': 'cascade_transformer.n.01', 'name': 'cascade_transformer'}, {'id': 6356, 'synset': 'case.n.05', 'name': 'case'}, {'id': 6357, 'synset': 'case.n.20', 'name': 'case'}, {'id': 6358, 'synset': 'case.n.18', 'name': 'case'}, {'id': 6359, 'synset': 'casein_paint.n.01', 'name': 'casein_paint'}, {'id': 6360, 'synset': 'case_knife.n.02', 'name': 'case_knife'}, {'id': 6361, 'synset': 'case_knife.n.01', 'name': 'case_knife'}, {'id': 6362, 'synset': 'casement.n.01', 'name': 'casement'}, {'id': 6363, 'synset': 'casement_window.n.01', 'name': 'casement_window'}, {'id': 6364, 'synset': 'casern.n.01', 'name': 'casern'}, {'id': 6365, 'synset': 'case_shot.n.01', 'name': 'case_shot'}, {'id': 6366, 'synset': 'cash_bar.n.01', 'name': 'cash_bar'}, {'id': 6367, 'synset': 'cashbox.n.01', 'name': 'cashbox'}, {'id': 6368, 'synset': 'cash_machine.n.01', 'name': 'cash_machine'}, {'id': 6369, 'synset': 'cashmere.n.01', 'name': 'cashmere'}, {'id': 6370, 'synset': 'casing.n.03', 'name': 'casing'}, {'id': 6371, 'synset': 'casino.n.01', 'name': 'casino'}, {'id': 6372, 'synset': 'casket.n.02', 'name': 'casket'}, {'id': 6373, 'synset': 'casque.n.01', 'name': 'casque'}, {'id': 6374, 'synset': 'casquet.n.01', 'name': 'casquet'}, {'id': 6375, 'synset': 'cassegrainian_telescope.n.01', 'name': 'Cassegrainian_telescope'}, {'id': 6376, 'synset': 'casserole.n.02', 'name': 'casserole'}, {'id': 6377, 'synset': 'cassette_deck.n.01', 'name': 'cassette_deck'}, {'id': 6378, 'synset': 'cassette_player.n.01', 'name': 'cassette_player'}, {'id': 6379, 'synset': 'cassette_recorder.n.01', 'name': 'cassette_recorder'}, {'id': 6380, 'synset': 'cassette_tape.n.01', 'name': 'cassette_tape'}, {'id': 6381, 'synset': 'cassock.n.01', 'name': 'cassock'}, {'id': 6382, 'synset': 'caster.n.03', 'name': 'caster'}, {'id': 6383, 'synset': 'caster.n.02', 'name': 'caster'}, {'id': 6384, 'synset': 'castle.n.02', 'name': 'castle'}, {'id': 6385, 'synset': 'castle.n.03', 'name': 'castle'}, {'id': 6386, 'synset': 'catacomb.n.01', 'name': 'catacomb'}, {'id': 6387, 'synset': 'catafalque.n.01', 'name': 'catafalque'}, {'id': 6388, 'synset': 'catalytic_converter.n.01', 'name': 'catalytic_converter'}, {'id': 6389, 'synset': 'catalytic_cracker.n.01', 'name': 'catalytic_cracker'}, {'id': 6390, 'synset': 'catamaran.n.01', 'name': 'catamaran'}, {'id': 6391, 'synset': 'catapult.n.03', 'name': 'catapult'}, {'id': 6392, 'synset': 'catapult.n.02', 'name': 'catapult'}, {'id': 6393, 'synset': 'catboat.n.01', 'name': 'catboat'}, {'id': 6394, 'synset': 'cat_box.n.01', 'name': 'cat_box'}, {'id': 6395, 'synset': 'catch.n.07', 'name': 'catch'}, {'id': 6396, 'synset': 'catchall.n.01', 'name': 'catchall'}, {'id': 6397, 'synset': "catcher's_mask.n.01", 'name': "catcher's_mask"}, {'id': 6398, 'synset': 'catchment.n.01', 'name': 'catchment'}, {'id': 6399, 'synset': 'caterpillar.n.02', 'name': 'Caterpillar'}, {'id': 6400, 'synset': 'cathedra.n.01', 'name': 'cathedra'}, {'id': 6401, 'synset': 'cathedral.n.01', 'name': 'cathedral'}, {'id': 6402, 'synset': 'cathedral.n.02', 'name': 'cathedral'}, {'id': 6403, 'synset': 'catheter.n.01', 'name': 'catheter'}, {'id': 6404, 'synset': 'cathode.n.01', 'name': 'cathode'}, {'id': 6405, 'synset': 'cathode-ray_tube.n.01', 'name': 'cathode-ray_tube'}, {'id': 6406, 'synset': "cat-o'-nine-tails.n.01", 'name': "cat-o'-nine-tails"}, {'id': 6407, 'synset': "cat's-paw.n.02", 'name': "cat's-paw"}, {'id': 6408, 'synset': 'catsup_bottle.n.01', 'name': 'catsup_bottle'}, {'id': 6409, 'synset': 'cattle_car.n.01', 'name': 'cattle_car'}, {'id': 6410, 'synset': 'cattle_guard.n.01', 'name': 'cattle_guard'}, {'id': 6411, 'synset': 'cattleship.n.01', 'name': 'cattleship'}, {'id': 6412, 'synset': 'cautery.n.01', 'name': 'cautery'}, {'id': 6413, 'synset': 'cavalier_hat.n.01', 'name': 'cavalier_hat'}, {'id': 6414, 'synset': 'cavalry_sword.n.01', 'name': 'cavalry_sword'}, {'id': 6415, 'synset': 'cavetto.n.01', 'name': 'cavetto'}, {'id': 6416, 'synset': 'cavity_wall.n.01', 'name': 'cavity_wall'}, {'id': 6417, 'synset': 'c_battery.n.01', 'name': 'C_battery'}, {'id': 6418, 'synset': 'c-clamp.n.01', 'name': 'C-clamp'}, {'id': 6419, 'synset': 'cd_drive.n.01', 'name': 'CD_drive'}, {'id': 6420, 'synset': 'cd-r.n.01', 'name': 'CD-R'}, {'id': 6421, 'synset': 'cd-rom.n.01', 'name': 'CD-ROM'}, {'id': 6422, 'synset': 'cd-rom_drive.n.01', 'name': 'CD-ROM_drive'}, {'id': 6423, 'synset': 'cedar_chest.n.01', 'name': 'cedar_chest'}, {'id': 6424, 'synset': 'ceiling.n.01', 'name': 'ceiling'}, {'id': 6425, 'synset': 'celesta.n.01', 'name': 'celesta'}, {'id': 6426, 'synset': 'cell.n.03', 'name': 'cell'}, {'id': 6427, 'synset': 'cell.n.07', 'name': 'cell'}, {'id': 6428, 'synset': 'cellar.n.03', 'name': 'cellar'}, {'id': 6429, 'synset': 'cellblock.n.01', 'name': 'cellblock'}, {'id': 6430, 'synset': 'cello.n.01', 'name': 'cello'}, {'id': 6431, 'synset': 'cellophane.n.01', 'name': 'cellophane'}, {'id': 6432, 'synset': 'cellulose_tape.n.01', 'name': 'cellulose_tape'}, {'id': 6433, 'synset': 'cenotaph.n.01', 'name': 'cenotaph'}, {'id': 6434, 'synset': 'censer.n.01', 'name': 'censer'}, {'id': 6435, 'synset': 'center.n.03', 'name': 'center'}, {'id': 6436, 'synset': 'center_punch.n.01', 'name': 'center_punch'}, {'id': 6437, 'synset': 'centigrade_thermometer.n.01', 'name': 'Centigrade_thermometer'}, {'id': 6438, 'synset': 'central_processing_unit.n.01', 'name': 'central_processing_unit'}, {'id': 6439, 'synset': 'centrifugal_pump.n.01', 'name': 'centrifugal_pump'}, {'id': 6440, 'synset': 'centrifuge.n.01', 'name': 'centrifuge'}, {'id': 6441, 'synset': 'ceramic.n.01', 'name': 'ceramic'}, {'id': 6442, 'synset': 'ceramic_ware.n.01', 'name': 'ceramic_ware'}, {'id': 6443, 'synset': 'cereal_bowl.n.01', 'name': 'cereal_bowl'}, {'id': 6444, 'synset': 'cereal_box.n.01', 'name': 'cereal_box'}, {'id': 6445, 'synset': 'cerecloth.n.01', 'name': 'cerecloth'}, {'id': 6446, 'synset': 'cesspool.n.01', 'name': 'cesspool'}, {'id': 6447, 'synset': 'chachka.n.02', 'name': 'chachka'}, {'id': 6448, 'synset': 'chador.n.01', 'name': 'chador'}, {'id': 6449, 'synset': 'chafing_dish.n.01', 'name': 'chafing_dish'}, {'id': 6450, 'synset': 'chain.n.03', 'name': 'chain'}, {'id': 6451, 'synset': 'chain.n.05', 'name': 'chain'}, {'id': 6452, 'synset': 'chainlink_fence.n.01', 'name': 'chainlink_fence'}, {'id': 6453, 'synset': 'chain_printer.n.01', 'name': 'chain_printer'}, {'id': 6454, 'synset': 'chain_saw.n.01', 'name': 'chain_saw'}, {'id': 6455, 'synset': 'chain_store.n.01', 'name': 'chain_store'}, {'id': 6456, 'synset': 'chain_tongs.n.01', 'name': 'chain_tongs'}, {'id': 6457, 'synset': 'chain_wrench.n.01', 'name': 'chain_wrench'}, {'id': 6458, 'synset': 'chair.n.05', 'name': 'chair'}, {'id': 6459, 'synset': 'chair_of_state.n.01', 'name': 'chair_of_state'}, {'id': 6460, 'synset': 'chairlift.n.01', 'name': 'chairlift'}, {'id': 6461, 'synset': 'chaise.n.02', 'name': 'chaise'}, {'id': 6462, 'synset': 'chalet.n.01', 'name': 'chalet'}, {'id': 6463, 'synset': 'chalk.n.04', 'name': 'chalk'}, {'id': 6464, 'synset': 'challis.n.01', 'name': 'challis'}, {'id': 6465, 'synset': 'chamberpot.n.01', 'name': 'chamberpot'}, {'id': 6466, 'synset': 'chambray.n.01', 'name': 'chambray'}, {'id': 6467, 'synset': 'chamfer_bit.n.01', 'name': 'chamfer_bit'}, {'id': 6468, 'synset': 'chamfer_plane.n.01', 'name': 'chamfer_plane'}, {'id': 6469, 'synset': 'chamois_cloth.n.01', 'name': 'chamois_cloth'}, {'id': 6470, 'synset': 'chancel.n.01', 'name': 'chancel'}, {'id': 6471, 'synset': 'chancellery.n.01', 'name': 'chancellery'}, {'id': 6472, 'synset': 'chancery.n.02', 'name': 'chancery'}, {'id': 6473, 'synset': 'chandlery.n.01', 'name': 'chandlery'}, {'id': 6474, 'synset': 'chanfron.n.01', 'name': 'chanfron'}, {'id': 6475, 'synset': 'chanter.n.01', 'name': 'chanter'}, {'id': 6476, 'synset': 'chantry.n.02', 'name': 'chantry'}, {'id': 6477, 'synset': 'chapel.n.01', 'name': 'chapel'}, {'id': 6478, 'synset': 'chapterhouse.n.02', 'name': 'chapterhouse'}, {'id': 6479, 'synset': 'chapterhouse.n.01', 'name': 'chapterhouse'}, {'id': 6480, 'synset': 'character_printer.n.01', 'name': 'character_printer'}, {'id': 6481, 'synset': 'charcuterie.n.01', 'name': 'charcuterie'}, {'id': 6482, 'synset': 'charge-exchange_accelerator.n.01', 'name': 'charge-exchange_accelerator'}, {'id': 6483, 'synset': 'charger.n.02', 'name': 'charger'}, {'id': 6484, 'synset': 'chariot.n.01', 'name': 'chariot'}, {'id': 6485, 'synset': 'chariot.n.02', 'name': 'chariot'}, {'id': 6486, 'synset': 'charnel_house.n.01', 'name': 'charnel_house'}, {'id': 6487, 'synset': 'chassis.n.03', 'name': 'chassis'}, {'id': 6488, 'synset': 'chassis.n.02', 'name': 'chassis'}, {'id': 6489, 'synset': 'chasuble.n.01', 'name': 'chasuble'}, {'id': 6490, 'synset': 'chateau.n.01', 'name': 'chateau'}, {'id': 6491, 'synset': 'chatelaine.n.02', 'name': 'chatelaine'}, {'id': 6492, 'synset': 'checker.n.03', 'name': 'checker'}, {'id': 6493, 'synset': 'checkout.n.03', 'name': 'checkout'}, {'id': 6494, 'synset': 'cheekpiece.n.01', 'name': 'cheekpiece'}, {'id': 6495, 'synset': 'cheeseboard.n.01', 'name': 'cheeseboard'}, {'id': 6496, 'synset': 'cheesecloth.n.01', 'name': 'cheesecloth'}, {'id': 6497, 'synset': 'cheese_cutter.n.01', 'name': 'cheese_cutter'}, {'id': 6498, 'synset': 'cheese_press.n.01', 'name': 'cheese_press'}, {'id': 6499, 'synset': 'chemical_bomb.n.01', 'name': 'chemical_bomb'}, {'id': 6500, 'synset': 'chemical_plant.n.01', 'name': 'chemical_plant'}, {'id': 6501, 'synset': 'chemical_reactor.n.01', 'name': 'chemical_reactor'}, {'id': 6502, 'synset': 'chemise.n.02', 'name': 'chemise'}, {'id': 6503, 'synset': 'chemise.n.01', 'name': 'chemise'}, {'id': 6504, 'synset': 'chenille.n.02', 'name': 'chenille'}, {'id': 6505, 'synset': 'chessman.n.01', 'name': 'chessman'}, {'id': 6506, 'synset': 'chest.n.02', 'name': 'chest'}, {'id': 6507, 'synset': 'chesterfield.n.02', 'name': 'chesterfield'}, {'id': 6508, 'synset': 'chest_of_drawers.n.01', 'name': 'chest_of_drawers'}, {'id': 6509, 'synset': 'chest_protector.n.01', 'name': 'chest_protector'}, {'id': 6510, 'synset': 'cheval-de-frise.n.01', 'name': 'cheval-de-frise'}, {'id': 6511, 'synset': 'cheval_glass.n.01', 'name': 'cheval_glass'}, {'id': 6512, 'synset': 'chicane.n.02', 'name': 'chicane'}, {'id': 6513, 'synset': 'chicken_coop.n.01', 'name': 'chicken_coop'}, {'id': 6514, 'synset': 'chicken_wire.n.01', 'name': 'chicken_wire'}, {'id': 6515, 'synset': 'chicken_yard.n.01', 'name': 'chicken_yard'}, {'id': 6516, 'synset': 'chiffon.n.01', 'name': 'chiffon'}, {'id': 6517, 'synset': 'chiffonier.n.01', 'name': 'chiffonier'}, {'id': 6518, 'synset': "child's_room.n.01", 'name': "child's_room"}, {'id': 6519, 'synset': 'chimney_breast.n.01', 'name': 'chimney_breast'}, {'id': 6520, 'synset': 'chimney_corner.n.01', 'name': 'chimney_corner'}, {'id': 6521, 'synset': 'china.n.02', 'name': 'china'}, {'id': 6522, 'synset': 'china_cabinet.n.01', 'name': 'china_cabinet'}, {'id': 6523, 'synset': 'chinchilla.n.02', 'name': 'chinchilla'}, {'id': 6524, 'synset': 'chinese_lantern.n.01', 'name': 'Chinese_lantern'}, {'id': 6525, 'synset': 'chinese_puzzle.n.01', 'name': 'Chinese_puzzle'}, {'id': 6526, 'synset': 'chinning_bar.n.01', 'name': 'chinning_bar'}, {'id': 6527, 'synset': 'chino.n.02', 'name': 'chino'}, {'id': 6528, 'synset': 'chino.n.01', 'name': 'chino'}, {'id': 6529, 'synset': 'chin_rest.n.01', 'name': 'chin_rest'}, {'id': 6530, 'synset': 'chin_strap.n.01', 'name': 'chin_strap'}, {'id': 6531, 'synset': 'chintz.n.01', 'name': 'chintz'}, {'id': 6532, 'synset': 'chip.n.07', 'name': 'chip'}, {'id': 6533, 'synset': 'chisel.n.01', 'name': 'chisel'}, {'id': 6534, 'synset': 'chlamys.n.02', 'name': 'chlamys'}, {'id': 6535, 'synset': 'choir.n.03', 'name': 'choir'}, {'id': 6536, 'synset': 'choir_loft.n.01', 'name': 'choir_loft'}, {'id': 6537, 'synset': 'choke.n.02', 'name': 'choke'}, {'id': 6538, 'synset': 'choke.n.01', 'name': 'choke'}, {'id': 6539, 'synset': 'chokey.n.01', 'name': 'chokey'}, {'id': 6540, 'synset': 'choo-choo.n.01', 'name': 'choo-choo'}, {'id': 6541, 'synset': 'chopine.n.01', 'name': 'chopine'}, {'id': 6542, 'synset': 'chordophone.n.01', 'name': 'chordophone'}, {'id': 6543, 'synset': 'christmas_stocking.n.01', 'name': 'Christmas_stocking'}, {'id': 6544, 'synset': 'chronograph.n.01', 'name': 'chronograph'}, {'id': 6545, 'synset': 'chronometer.n.01', 'name': 'chronometer'}, {'id': 6546, 'synset': 'chronoscope.n.01', 'name': 'chronoscope'}, {'id': 6547, 'synset': 'chuck.n.03', 'name': 'chuck'}, {'id': 6548, 'synset': 'chuck_wagon.n.01', 'name': 'chuck_wagon'}, {'id': 6549, 'synset': 'chukka.n.02', 'name': 'chukka'}, {'id': 6550, 'synset': 'church.n.02', 'name': 'church'}, {'id': 6551, 'synset': 'church_bell.n.01', 'name': 'church_bell'}, {'id': 6552, 'synset': 'church_hat.n.01', 'name': 'church_hat'}, {'id': 6553, 'synset': 'church_key.n.01', 'name': 'church_key'}, {'id': 6554, 'synset': 'church_tower.n.01', 'name': 'church_tower'}, {'id': 6555, 'synset': 'churidars.n.01', 'name': 'churidars'}, {'id': 6556, 'synset': 'churn.n.01', 'name': 'churn'}, {'id': 6557, 'synset': 'ciderpress.n.01', 'name': 'ciderpress'}, {'id': 6558, 'synset': 'cigar_band.n.01', 'name': 'cigar_band'}, {'id': 6559, 'synset': 'cigar_cutter.n.01', 'name': 'cigar_cutter'}, {'id': 6560, 'synset': 'cigarette_butt.n.01', 'name': 'cigarette_butt'}, {'id': 6561, 'synset': 'cigarette_holder.n.01', 'name': 'cigarette_holder'}, {'id': 6562, 'synset': 'cigar_lighter.n.01', 'name': 'cigar_lighter'}, {'id': 6563, 'synset': 'cinch.n.02', 'name': 'cinch'}, {'id': 6564, 'synset': 'cinema.n.02', 'name': 'cinema'}, {'id': 6565, 'synset': 'cinquefoil.n.02', 'name': 'cinquefoil'}, {'id': 6566, 'synset': 'circle.n.08', 'name': 'circle'}, {'id': 6567, 'synset': 'circlet.n.02', 'name': 'circlet'}, {'id': 6568, 'synset': 'circuit.n.01', 'name': 'circuit'}, {'id': 6569, 'synset': 'circuit_board.n.01', 'name': 'circuit_board'}, {'id': 6570, 'synset': 'circuit_breaker.n.01', 'name': 'circuit_breaker'}, {'id': 6571, 'synset': 'circuitry.n.01', 'name': 'circuitry'}, {'id': 6572, 'synset': 'circular_plane.n.01', 'name': 'circular_plane'}, {'id': 6573, 'synset': 'circular_saw.n.01', 'name': 'circular_saw'}, {'id': 6574, 'synset': 'circus_tent.n.01', 'name': 'circus_tent'}, {'id': 6575, 'synset': 'cistern.n.03', 'name': 'cistern'}, {'id': 6576, 'synset': 'cittern.n.01', 'name': 'cittern'}, {'id': 6577, 'synset': 'city_hall.n.01', 'name': 'city_hall'}, {'id': 6578, 'synset': 'cityscape.n.02', 'name': 'cityscape'}, {'id': 6579, 'synset': 'city_university.n.01', 'name': 'city_university'}, {'id': 6580, 'synset': 'civies.n.01', 'name': 'civies'}, {'id': 6581, 'synset': 'civilian_clothing.n.01', 'name': 'civilian_clothing'}, {'id': 6582, 'synset': 'clack_valve.n.01', 'name': 'clack_valve'}, {'id': 6583, 'synset': 'clamp.n.01', 'name': 'clamp'}, {'id': 6584, 'synset': 'clamshell.n.02', 'name': 'clamshell'}, {'id': 6585, 'synset': 'clapper.n.03', 'name': 'clapper'}, {'id': 6586, 'synset': 'clapperboard.n.01', 'name': 'clapperboard'}, {'id': 6587, 'synset': 'clarence.n.01', 'name': 'clarence'}, {'id': 6588, 'synset': 'clark_cell.n.01', 'name': 'Clark_cell'}, {'id': 6589, 'synset': 'clasp_knife.n.01', 'name': 'clasp_knife'}, {'id': 6590, 'synset': 'classroom.n.01', 'name': 'classroom'}, {'id': 6591, 'synset': 'clavichord.n.01', 'name': 'clavichord'}, {'id': 6592, 'synset': 'clavier.n.02', 'name': 'clavier'}, {'id': 6593, 'synset': 'clay_pigeon.n.01', 'name': 'clay_pigeon'}, {'id': 6594, 'synset': 'claymore_mine.n.01', 'name': 'claymore_mine'}, {'id': 6595, 'synset': 'claymore.n.01', 'name': 'claymore'}, {'id': 6596, 'synset': 'cleaners.n.01', 'name': 'cleaners'}, {'id': 6597, 'synset': 'cleaning_implement.n.01', 'name': 'cleaning_implement'}, {'id': 6598, 'synset': 'cleaning_pad.n.01', 'name': 'cleaning_pad'}, {'id': 6599, 'synset': 'clean_room.n.01', 'name': 'clean_room'}, {'id': 6600, 'synset': 'clearway.n.01', 'name': 'clearway'}, {'id': 6601, 'synset': 'cleat.n.01', 'name': 'cleat'}, {'id': 6602, 'synset': 'cleats.n.01', 'name': 'cleats'}, {'id': 6603, 'synset': 'cleaver.n.01', 'name': 'cleaver'}, {'id': 6604, 'synset': 'clerestory.n.01', 'name': 'clerestory'}, {'id': 6605, 'synset': 'clevis.n.01', 'name': 'clevis'}, {'id': 6606, 'synset': 'clews.n.01', 'name': 'clews'}, {'id': 6607, 'synset': 'cliff_dwelling.n.01', 'name': 'cliff_dwelling'}, {'id': 6608, 'synset': 'climbing_frame.n.01', 'name': 'climbing_frame'}, {'id': 6609, 'synset': 'clinch.n.03', 'name': 'clinch'}, {'id': 6610, 'synset': 'clinch.n.02', 'name': 'clinch'}, {'id': 6611, 'synset': 'clincher.n.03', 'name': 'clincher'}, {'id': 6612, 'synset': 'clinic.n.03', 'name': 'clinic'}, {'id': 6613, 'synset': 'clinical_thermometer.n.01', 'name': 'clinical_thermometer'}, {'id': 6614, 'synset': 'clinker.n.02', 'name': 'clinker'}, {'id': 6615, 'synset': 'clinometer.n.01', 'name': 'clinometer'}, {'id': 6616, 'synset': 'clip_lead.n.01', 'name': 'clip_lead'}, {'id': 6617, 'synset': 'clip-on.n.01', 'name': 'clip-on'}, {'id': 6618, 'synset': 'clipper.n.04', 'name': 'clipper'}, {'id': 6619, 'synset': 'clipper.n.02', 'name': 'clipper'}, {'id': 6620, 'synset': 'cloak.n.01', 'name': 'cloak'}, {'id': 6621, 'synset': 'cloakroom.n.02', 'name': 'cloakroom'}, {'id': 6622, 'synset': 'cloche.n.02', 'name': 'cloche'}, {'id': 6623, 'synset': 'cloche.n.01', 'name': 'cloche'}, {'id': 6624, 'synset': 'clock_pendulum.n.01', 'name': 'clock_pendulum'}, {'id': 6625, 'synset': 'clock_radio.n.01', 'name': 'clock_radio'}, {'id': 6626, 'synset': 'clockwork.n.01', 'name': 'clockwork'}, {'id': 6627, 'synset': 'clog.n.01', 'name': 'clog'}, {'id': 6628, 'synset': 'cloisonne.n.01', 'name': 'cloisonne'}, {'id': 6629, 'synset': 'cloister.n.02', 'name': 'cloister'}, {'id': 6630, 'synset': 'closed_circuit.n.01', 'name': 'closed_circuit'}, {'id': 6631, 'synset': 'closed-circuit_television.n.01', 'name': 'closed-circuit_television'}, {'id': 6632, 'synset': 'closed_loop.n.01', 'name': 'closed_loop'}, {'id': 6633, 'synset': 'closet.n.04', 'name': 'closet'}, {'id': 6634, 'synset': 'closeup_lens.n.01', 'name': 'closeup_lens'}, {'id': 6635, 'synset': 'cloth_cap.n.01', 'name': 'cloth_cap'}, {'id': 6636, 'synset': 'cloth_covering.n.01', 'name': 'cloth_covering'}, {'id': 6637, 'synset': 'clothesbrush.n.01', 'name': 'clothesbrush'}, {'id': 6638, 'synset': 'clothes_closet.n.01', 'name': 'clothes_closet'}, {'id': 6639, 'synset': 'clothes_dryer.n.01', 'name': 'clothes_dryer'}, {'id': 6640, 'synset': 'clotheshorse.n.01', 'name': 'clotheshorse'}, {'id': 6641, 'synset': 'clothes_tree.n.01', 'name': 'clothes_tree'}, {'id': 6642, 'synset': 'clothing.n.01', 'name': 'clothing'}, {'id': 6643, 'synset': 'clothing_store.n.01', 'name': 'clothing_store'}, {'id': 6644, 'synset': 'clout_nail.n.01', 'name': 'clout_nail'}, {'id': 6645, 'synset': 'clove_hitch.n.01', 'name': 'clove_hitch'}, {'id': 6646, 'synset': 'club_car.n.01', 'name': 'club_car'}, {'id': 6647, 'synset': 'clubroom.n.01', 'name': 'clubroom'}, {'id': 6648, 'synset': 'cluster_bomb.n.01', 'name': 'cluster_bomb'}, {'id': 6649, 'synset': 'clutch.n.07', 'name': 'clutch'}, {'id': 6650, 'synset': 'clutch.n.06', 'name': 'clutch'}, {'id': 6651, 'synset': 'coach.n.04', 'name': 'coach'}, {'id': 6652, 'synset': 'coach_house.n.01', 'name': 'coach_house'}, {'id': 6653, 'synset': 'coal_car.n.01', 'name': 'coal_car'}, {'id': 6654, 'synset': 'coal_chute.n.01', 'name': 'coal_chute'}, {'id': 6655, 'synset': 'coal_house.n.01', 'name': 'coal_house'}, {'id': 6656, 'synset': 'coal_shovel.n.01', 'name': 'coal_shovel'}, {'id': 6657, 'synset': 'coaming.n.01', 'name': 'coaming'}, {'id': 6658, 'synset': 'coaster_brake.n.01', 'name': 'coaster_brake'}, {'id': 6659, 'synset': 'coat_button.n.01', 'name': 'coat_button'}, {'id': 6660, 'synset': 'coat_closet.n.01', 'name': 'coat_closet'}, {'id': 6661, 'synset': 'coatdress.n.01', 'name': 'coatdress'}, {'id': 6662, 'synset': 'coatee.n.01', 'name': 'coatee'}, {'id': 6663, 'synset': 'coating.n.01', 'name': 'coating'}, {'id': 6664, 'synset': 'coating.n.03', 'name': 'coating'}, {'id': 6665, 'synset': 'coat_of_paint.n.01', 'name': 'coat_of_paint'}, {'id': 6666, 'synset': 'coattail.n.01', 'name': 'coattail'}, {'id': 6667, 'synset': 'coaxial_cable.n.01', 'name': 'coaxial_cable'}, {'id': 6668, 'synset': 'cobweb.n.03', 'name': 'cobweb'}, {'id': 6669, 'synset': 'cobweb.n.01', 'name': 'cobweb'}, {'id': 6670, 'synset': 'cockcroft_and_walton_accelerator.n.01', 'name': 'Cockcroft_and_Walton_accelerator'}, {'id': 6671, 'synset': 'cocked_hat.n.01', 'name': 'cocked_hat'}, {'id': 6672, 'synset': 'cockhorse.n.01', 'name': 'cockhorse'}, {'id': 6673, 'synset': 'cockleshell.n.01', 'name': 'cockleshell'}, {'id': 6674, 'synset': 'cockpit.n.01', 'name': 'cockpit'}, {'id': 6675, 'synset': 'cockpit.n.03', 'name': 'cockpit'}, {'id': 6676, 'synset': 'cockpit.n.02', 'name': 'cockpit'}, {'id': 6677, 'synset': 'cockscomb.n.03', 'name': 'cockscomb'}, {'id': 6678, 'synset': 'cocktail_dress.n.01', 'name': 'cocktail_dress'}, {'id': 6679, 'synset': 'cocktail_lounge.n.01', 'name': 'cocktail_lounge'}, {'id': 6680, 'synset': 'cocktail_shaker.n.01', 'name': 'cocktail_shaker'}, {'id': 6681, 'synset': 'cocotte.n.02', 'name': 'cocotte'}, {'id': 6682, 'synset': 'codpiece.n.01', 'name': 'codpiece'}, {'id': 6683, 'synset': 'coelostat.n.01', 'name': 'coelostat'}, {'id': 6684, 'synset': 'coffee_can.n.01', 'name': 'coffee_can'}, {'id': 6685, 'synset': 'coffee_cup.n.01', 'name': 'coffee_cup'}, {'id': 6686, 'synset': 'coffee_filter.n.01', 'name': 'coffee_filter'}, {'id': 6687, 'synset': 'coffee_mill.n.01', 'name': 'coffee_mill'}, {'id': 6688, 'synset': 'coffee_mug.n.01', 'name': 'coffee_mug'}, {'id': 6689, 'synset': 'coffee_stall.n.01', 'name': 'coffee_stall'}, {'id': 6690, 'synset': 'coffee_urn.n.01', 'name': 'coffee_urn'}, {'id': 6691, 'synset': 'coffer.n.02', 'name': 'coffer'}, {'id': 6692, 'synset': 'coffey_still.n.01', 'name': 'Coffey_still'}, {'id': 6693, 'synset': 'coffin.n.01', 'name': 'coffin'}, {'id': 6694, 'synset': 'cog.n.02', 'name': 'cog'}, {'id': 6695, 'synset': 'coif.n.02', 'name': 'coif'}, {'id': 6696, 'synset': 'coil.n.01', 'name': 'coil'}, {'id': 6697, 'synset': 'coil.n.06', 'name': 'coil'}, {'id': 6698, 'synset': 'coil.n.03', 'name': 'coil'}, {'id': 6699, 'synset': 'coil_spring.n.01', 'name': 'coil_spring'}, {'id': 6700, 'synset': 'coin_box.n.01', 'name': 'coin_box'}, {'id': 6701, 'synset': 'cold_cathode.n.01', 'name': 'cold_cathode'}, {'id': 6702, 'synset': 'cold_chisel.n.01', 'name': 'cold_chisel'}, {'id': 6703, 'synset': 'cold_cream.n.01', 'name': 'cold_cream'}, {'id': 6704, 'synset': 'cold_frame.n.01', 'name': 'cold_frame'}, {'id': 6705, 'synset': 'collar.n.01', 'name': 'collar'}, {'id': 6706, 'synset': 'collar.n.03', 'name': 'collar'}, {'id': 6707, 'synset': 'college.n.03', 'name': 'college'}, {'id': 6708, 'synset': 'collet.n.02', 'name': 'collet'}, {'id': 6709, 'synset': 'collider.n.01', 'name': 'collider'}, {'id': 6710, 'synset': 'colliery.n.01', 'name': 'colliery'}, {'id': 6711, 'synset': 'collimator.n.02', 'name': 'collimator'}, {'id': 6712, 'synset': 'collimator.n.01', 'name': 'collimator'}, {'id': 6713, 'synset': 'cologne.n.02', 'name': 'cologne'}, {'id': 6714, 'synset': 'colonnade.n.01', 'name': 'colonnade'}, {'id': 6715, 'synset': 'colonoscope.n.01', 'name': 'colonoscope'}, {'id': 6716, 'synset': 'colorimeter.n.01', 'name': 'colorimeter'}, {'id': 6717, 'synset': 'colors.n.02', 'name': 'colors'}, {'id': 6718, 'synset': 'color_television.n.01', 'name': 'color_television'}, {'id': 6719, 'synset': 'color_tube.n.01', 'name': 'color_tube'}, {'id': 6720, 'synset': 'color_wash.n.01', 'name': 'color_wash'}, {'id': 6721, 'synset': 'colt.n.02', 'name': 'Colt'}, {'id': 6722, 'synset': 'colter.n.01', 'name': 'colter'}, {'id': 6723, 'synset': 'columbarium.n.03', 'name': 'columbarium'}, {'id': 6724, 'synset': 'columbarium.n.02', 'name': 'columbarium'}, {'id': 6725, 'synset': 'column.n.07', 'name': 'column'}, {'id': 6726, 'synset': 'column.n.06', 'name': 'column'}, {'id': 6727, 'synset': 'comb.n.01', 'name': 'comb'}, {'id': 6728, 'synset': 'comb.n.03', 'name': 'comb'}, {'id': 6729, 'synset': 'comber.n.03', 'name': 'comber'}, {'id': 6730, 'synset': 'combination_plane.n.01', 'name': 'combination_plane'}, {'id': 6731, 'synset': 'combine.n.01', 'name': 'combine'}, {'id': 6732, 'synset': 'command_module.n.01', 'name': 'command_module'}, {'id': 6733, 'synset': 'commissary.n.01', 'name': 'commissary'}, {'id': 6734, 'synset': 'commissary.n.02', 'name': 'commissary'}, {'id': 6735, 'synset': 'commodity.n.01', 'name': 'commodity'}, {'id': 6736, 'synset': 'common_ax.n.01', 'name': 'common_ax'}, {'id': 6737, 'synset': 'common_room.n.01', 'name': 'common_room'}, {'id': 6738, 'synset': 'communications_satellite.n.01', 'name': 'communications_satellite'}, {'id': 6739, 'synset': 'communication_system.n.01', 'name': 'communication_system'}, {'id': 6740, 'synset': 'community_center.n.01', 'name': 'community_center'}, {'id': 6741, 'synset': 'commutator.n.01', 'name': 'commutator'}, {'id': 6742, 'synset': 'commuter.n.01', 'name': 'commuter'}, {'id': 6743, 'synset': 'compact.n.01', 'name': 'compact'}, {'id': 6744, 'synset': 'compact.n.03', 'name': 'compact'}, {'id': 6745, 'synset': 'compact_disk.n.01', 'name': 'compact_disk'}, {'id': 6746, 'synset': 'compact-disk_burner.n.01', 'name': 'compact-disk_burner'}, {'id': 6747, 'synset': 'companionway.n.01', 'name': 'companionway'}, {'id': 6748, 'synset': 'compartment.n.02', 'name': 'compartment'}, {'id': 6749, 'synset': 'compartment.n.01', 'name': 'compartment'}, {'id': 6750, 'synset': 'compass.n.04', 'name': 'compass'}, {'id': 6751, 'synset': 'compass_card.n.01', 'name': 'compass_card'}, {'id': 6752, 'synset': 'compass_saw.n.01', 'name': 'compass_saw'}, {'id': 6753, 'synset': 'compound.n.03', 'name': 'compound'}, {'id': 6754, 'synset': 'compound_lens.n.01', 'name': 'compound_lens'}, {'id': 6755, 'synset': 'compound_lever.n.01', 'name': 'compound_lever'}, {'id': 6756, 'synset': 'compound_microscope.n.01', 'name': 'compound_microscope'}, {'id': 6757, 'synset': 'compress.n.01', 'name': 'compress'}, {'id': 6758, 'synset': 'compression_bandage.n.01', 'name': 'compression_bandage'}, {'id': 6759, 'synset': 'compressor.n.01', 'name': 'compressor'}, {'id': 6760, 'synset': 'computer.n.01', 'name': 'computer'}, {'id': 6761, 'synset': 'computer_circuit.n.01', 'name': 'computer_circuit'}, {'id': 6762, 'synset': 'computerized_axial_tomography_scanner.n.01', 'name': 'computerized_axial_tomography_scanner'}, {'id': 6763, 'synset': 'computer_monitor.n.01', 'name': 'computer_monitor'}, {'id': 6764, 'synset': 'computer_network.n.01', 'name': 'computer_network'}, {'id': 6765, 'synset': 'computer_screen.n.01', 'name': 'computer_screen'}, {'id': 6766, 'synset': 'computer_store.n.01', 'name': 'computer_store'}, {'id': 6767, 'synset': 'computer_system.n.01', 'name': 'computer_system'}, {'id': 6768, 'synset': 'concentration_camp.n.01', 'name': 'concentration_camp'}, {'id': 6769, 'synset': 'concert_grand.n.01', 'name': 'concert_grand'}, {'id': 6770, 'synset': 'concert_hall.n.01', 'name': 'concert_hall'}, {'id': 6771, 'synset': 'concertina.n.02', 'name': 'concertina'}, {'id': 6772, 'synset': 'concertina.n.01', 'name': 'concertina'}, {'id': 6773, 'synset': 'concrete_mixer.n.01', 'name': 'concrete_mixer'}, {'id': 6774, 'synset': 'condensation_pump.n.01', 'name': 'condensation_pump'}, {'id': 6775, 'synset': 'condenser.n.04', 'name': 'condenser'}, {'id': 6776, 'synset': 'condenser.n.03', 'name': 'condenser'}, {'id': 6777, 'synset': 'condenser.n.02', 'name': 'condenser'}, {'id': 6778, 'synset': 'condenser_microphone.n.01', 'name': 'condenser_microphone'}, {'id': 6779, 'synset': 'condominium.n.02', 'name': 'condominium'}, {'id': 6780, 'synset': 'condominium.n.01', 'name': 'condominium'}, {'id': 6781, 'synset': 'conductor.n.04', 'name': 'conductor'}, {'id': 6782, 'synset': 'cone_clutch.n.01', 'name': 'cone_clutch'}, {'id': 6783, 'synset': 'confectionery.n.02', 'name': 'confectionery'}, {'id': 6784, 'synset': 'conference_center.n.01', 'name': 'conference_center'}, {'id': 6785, 'synset': 'conference_room.n.01', 'name': 'conference_room'}, {'id': 6786, 'synset': 'conference_table.n.01', 'name': 'conference_table'}, {'id': 6787, 'synset': 'confessional.n.01', 'name': 'confessional'}, {'id': 6788, 'synset': 'conformal_projection.n.01', 'name': 'conformal_projection'}, {'id': 6789, 'synset': 'congress_boot.n.01', 'name': 'congress_boot'}, {'id': 6790, 'synset': 'conic_projection.n.01', 'name': 'conic_projection'}, {'id': 6791, 'synset': 'connecting_rod.n.01', 'name': 'connecting_rod'}, {'id': 6792, 'synset': 'connecting_room.n.01', 'name': 'connecting_room'}, {'id': 6793, 'synset': 'connection.n.03', 'name': 'connection'}, {'id': 6794, 'synset': 'conning_tower.n.02', 'name': 'conning_tower'}, {'id': 6795, 'synset': 'conning_tower.n.01', 'name': 'conning_tower'}, {'id': 6796, 'synset': 'conservatory.n.03', 'name': 'conservatory'}, {'id': 6797, 'synset': 'conservatory.n.02', 'name': 'conservatory'}, {'id': 6798, 'synset': 'console.n.03', 'name': 'console'}, {'id': 6799, 'synset': 'console.n.02', 'name': 'console'}, {'id': 6800, 'synset': 'console_table.n.01', 'name': 'console_table'}, {'id': 6801, 'synset': 'consulate.n.01', 'name': 'consulate'}, {'id': 6802, 'synset': 'contact.n.07', 'name': 'contact'}, {'id': 6803, 'synset': 'contact.n.09', 'name': 'contact'}, {'id': 6804, 'synset': 'container.n.01', 'name': 'container'}, {'id': 6805, 'synset': 'container_ship.n.01', 'name': 'container_ship'}, {'id': 6806, 'synset': 'containment.n.02', 'name': 'containment'}, {'id': 6807, 'synset': 'contrabassoon.n.01', 'name': 'contrabassoon'}, {'id': 6808, 'synset': 'control_center.n.01', 'name': 'control_center'}, {'id': 6809, 'synset': 'control_circuit.n.01', 'name': 'control_circuit'}, {'id': 6810, 'synset': 'control_key.n.01', 'name': 'control_key'}, {'id': 6811, 'synset': 'control_panel.n.01', 'name': 'control_panel'}, {'id': 6812, 'synset': 'control_rod.n.01', 'name': 'control_rod'}, {'id': 6813, 'synset': 'control_room.n.01', 'name': 'control_room'}, {'id': 6814, 'synset': 'control_system.n.01', 'name': 'control_system'}, {'id': 6815, 'synset': 'control_tower.n.01', 'name': 'control_tower'}, {'id': 6816, 'synset': 'convector.n.01', 'name': 'convector'}, {'id': 6817, 'synset': 'convenience_store.n.01', 'name': 'convenience_store'}, {'id': 6818, 'synset': 'convent.n.01', 'name': 'convent'}, {'id': 6819, 'synset': 'conventicle.n.02', 'name': 'conventicle'}, {'id': 6820, 'synset': 'converging_lens.n.01', 'name': 'converging_lens'}, {'id': 6821, 'synset': 'converter.n.01', 'name': 'converter'}, {'id': 6822, 'synset': 'conveyance.n.03', 'name': 'conveyance'}, {'id': 6823, 'synset': 'conveyer_belt.n.01', 'name': 'conveyer_belt'}, {'id': 6824, 'synset': 'cookfire.n.01', 'name': 'cookfire'}, {'id': 6825, 'synset': 'cookhouse.n.02', 'name': 'cookhouse'}, {'id': 6826, 'synset': 'cookie_cutter.n.01', 'name': 'cookie_cutter'}, {'id': 6827, 'synset': 'cookie_jar.n.01', 'name': 'cookie_jar'}, {'id': 6828, 'synset': 'cookie_sheet.n.01', 'name': 'cookie_sheet'}, {'id': 6829, 'synset': 'cookstove.n.01', 'name': 'cookstove'}, {'id': 6830, 'synset': 'coolant_system.n.01', 'name': 'coolant_system'}, {'id': 6831, 'synset': 'cooling_system.n.02', 'name': 'cooling_system'}, {'id': 6832, 'synset': 'cooling_system.n.01', 'name': 'cooling_system'}, {'id': 6833, 'synset': 'cooling_tower.n.01', 'name': 'cooling_tower'}, {'id': 6834, 'synset': 'coonskin_cap.n.01', 'name': 'coonskin_cap'}, {'id': 6835, 'synset': 'cope.n.02', 'name': 'cope'}, {'id': 6836, 'synset': 'coping_saw.n.01', 'name': 'coping_saw'}, {'id': 6837, 'synset': 'copperware.n.01', 'name': 'copperware'}, {'id': 6838, 'synset': 'copyholder.n.01', 'name': 'copyholder'}, {'id': 6839, 'synset': 'coquille.n.02', 'name': 'coquille'}, {'id': 6840, 'synset': 'coracle.n.01', 'name': 'coracle'}, {'id': 6841, 'synset': 'corbel.n.01', 'name': 'corbel'}, {'id': 6842, 'synset': 'corbel_arch.n.01', 'name': 'corbel_arch'}, {'id': 6843, 'synset': 'corbel_step.n.01', 'name': 'corbel_step'}, {'id': 6844, 'synset': 'corbie_gable.n.01', 'name': 'corbie_gable'}, {'id': 6845, 'synset': 'cord.n.04', 'name': 'cord'}, {'id': 6846, 'synset': 'cord.n.03', 'name': 'cord'}, {'id': 6847, 'synset': 'cordage.n.02', 'name': 'cordage'}, {'id': 6848, 'synset': 'cords.n.01', 'name': 'cords'}, {'id': 6849, 'synset': 'core.n.10', 'name': 'core'}, {'id': 6850, 'synset': 'core_bit.n.01', 'name': 'core_bit'}, {'id': 6851, 'synset': 'core_drill.n.01', 'name': 'core_drill'}, {'id': 6852, 'synset': 'corer.n.01', 'name': 'corer'}, {'id': 6853, 'synset': 'corker.n.02', 'name': 'corker'}, {'id': 6854, 'synset': 'corncrib.n.01', 'name': 'corncrib'}, {'id': 6855, 'synset': 'corner.n.11', 'name': 'corner'}, {'id': 6856, 'synset': 'corner.n.03', 'name': 'corner'}, {'id': 6857, 'synset': 'corner_post.n.01', 'name': 'corner_post'}, {'id': 6858, 'synset': 'cornice.n.03', 'name': 'cornice'}, {'id': 6859, 'synset': 'cornice.n.02', 'name': 'cornice'}, {'id': 6860, 'synset': 'correctional_institution.n.01', 'name': 'correctional_institution'}, {'id': 6861, 'synset': 'corrugated_fastener.n.01', 'name': 'corrugated_fastener'}, {'id': 6862, 'synset': 'corselet.n.01', 'name': 'corselet'}, {'id': 6863, 'synset': 'cosmetic.n.01', 'name': 'cosmetic'}, {'id': 6864, 'synset': 'cosmotron.n.01', 'name': 'cosmotron'}, {'id': 6865, 'synset': 'costume.n.01', 'name': 'costume'}, {'id': 6866, 'synset': 'costume.n.02', 'name': 'costume'}, {'id': 6867, 'synset': 'costume.n.03', 'name': 'costume'}, {'id': 6868, 'synset': 'cosy.n.01', 'name': 'cosy'}, {'id': 6869, 'synset': 'cot.n.03', 'name': 'cot'}, {'id': 6870, 'synset': 'cottage_tent.n.01', 'name': 'cottage_tent'}, {'id': 6871, 'synset': 'cotter.n.03', 'name': 'cotter'}, {'id': 6872, 'synset': 'cotter_pin.n.01', 'name': 'cotter_pin'}, {'id': 6873, 'synset': 'cotton.n.02', 'name': 'cotton'}, {'id': 6874, 'synset': 'cotton_flannel.n.01', 'name': 'cotton_flannel'}, {'id': 6875, 'synset': 'cotton_mill.n.01', 'name': 'cotton_mill'}, {'id': 6876, 'synset': 'couch.n.03', 'name': 'couch'}, {'id': 6877, 'synset': 'couch.n.02', 'name': 'couch'}, {'id': 6878, 'synset': 'couchette.n.01', 'name': 'couchette'}, {'id': 6879, 'synset': 'coude_telescope.n.01', 'name': 'coude_telescope'}, {'id': 6880, 'synset': 'counter.n.01', 'name': 'counter'}, {'id': 6881, 'synset': 'counter.n.03', 'name': 'counter'}, {'id': 6882, 'synset': 'counter.n.02', 'name': 'counter'}, {'id': 6883, 'synset': 'counterbore.n.01', 'name': 'counterbore'}, {'id': 6884, 'synset': 'counter_tube.n.01', 'name': 'counter_tube'}, {'id': 6885, 'synset': 'country_house.n.01', 'name': 'country_house'}, {'id': 6886, 'synset': 'country_store.n.01', 'name': 'country_store'}, {'id': 6887, 'synset': 'coupe.n.01', 'name': 'coupe'}, {'id': 6888, 'synset': 'coupling.n.02', 'name': 'coupling'}, {'id': 6889, 'synset': 'court.n.10', 'name': 'court'}, {'id': 6890, 'synset': 'court.n.04', 'name': 'court'}, {'id': 6891, 'synset': 'court.n.02', 'name': 'court'}, {'id': 6892, 'synset': 'court.n.09', 'name': 'court'}, {'id': 6893, 'synset': 'courtelle.n.01', 'name': 'Courtelle'}, {'id': 6894, 'synset': 'courthouse.n.02', 'name': 'courthouse'}, {'id': 6895, 'synset': 'courthouse.n.01', 'name': 'courthouse'}, {'id': 6896, 'synset': 'covered_bridge.n.01', 'name': 'covered_bridge'}, {'id': 6897, 'synset': 'covered_couch.n.01', 'name': 'covered_couch'}, {'id': 6898, 'synset': 'covered_wagon.n.01', 'name': 'covered_wagon'}, {'id': 6899, 'synset': 'covering.n.02', 'name': 'covering'}, {'id': 6900, 'synset': 'coverlet.n.01', 'name': 'coverlet'}, {'id': 6901, 'synset': 'cover_plate.n.01', 'name': 'cover_plate'}, {'id': 6902, 'synset': 'cowbarn.n.01', 'name': 'cowbarn'}, {'id': 6903, 'synset': 'cowboy_boot.n.01', 'name': 'cowboy_boot'}, {'id': 6904, 'synset': 'cowhide.n.03', 'name': 'cowhide'}, {'id': 6905, 'synset': 'cowl.n.02', 'name': 'cowl'}, {'id': 6906, 'synset': 'cow_pen.n.01', 'name': 'cow_pen'}, {'id': 6907, 'synset': 'cpu_board.n.01', 'name': 'CPU_board'}, {'id': 6908, 'synset': 'crackle.n.02', 'name': 'crackle'}, {'id': 6909, 'synset': 'cradle.n.01', 'name': 'cradle'}, {'id': 6910, 'synset': 'craft.n.02', 'name': 'craft'}, {'id': 6911, 'synset': 'cramp.n.03', 'name': 'cramp'}, {'id': 6912, 'synset': 'crampon.n.02', 'name': 'crampon'}, {'id': 6913, 'synset': 'crampon.n.01', 'name': 'crampon'}, {'id': 6914, 'synset': 'crane.n.04', 'name': 'crane'}, {'id': 6915, 'synset': 'craniometer.n.01', 'name': 'craniometer'}, {'id': 6916, 'synset': 'crank.n.04', 'name': 'crank'}, {'id': 6917, 'synset': 'crankcase.n.01', 'name': 'crankcase'}, {'id': 6918, 'synset': 'crankshaft.n.01', 'name': 'crankshaft'}, {'id': 6919, 'synset': 'crash_barrier.n.01', 'name': 'crash_barrier'}, {'id': 6920, 'synset': 'crash_helmet.n.01', 'name': 'crash_helmet'}, {'id': 6921, 'synset': 'cravat.n.01', 'name': 'cravat'}, {'id': 6922, 'synset': 'crazy_quilt.n.01', 'name': 'crazy_quilt'}, {'id': 6923, 'synset': 'cream.n.03', 'name': 'cream'}, {'id': 6924, 'synset': 'creche.n.01', 'name': 'creche'}, {'id': 6925, 'synset': 'creche.n.02', 'name': 'creche'}, {'id': 6926, 'synset': 'credenza.n.01', 'name': 'credenza'}, {'id': 6927, 'synset': 'creel.n.01', 'name': 'creel'}, {'id': 6928, 'synset': 'crematory.n.02', 'name': 'crematory'}, {'id': 6929, 'synset': 'crematory.n.01', 'name': 'crematory'}, {'id': 6930, 'synset': 'crepe.n.03', 'name': 'crepe'}, {'id': 6931, 'synset': 'crepe_de_chine.n.01', 'name': 'crepe_de_Chine'}, {'id': 6932, 'synset': 'crescent_wrench.n.01', 'name': 'crescent_wrench'}, {'id': 6933, 'synset': 'cretonne.n.01', 'name': 'cretonne'}, {'id': 6934, 'synset': 'crib.n.03', 'name': 'crib'}, {'id': 6935, 'synset': 'cricket_ball.n.01', 'name': 'cricket_ball'}, {'id': 6936, 'synset': 'cricket_bat.n.01', 'name': 'cricket_bat'}, {'id': 6937, 'synset': 'cricket_equipment.n.01', 'name': 'cricket_equipment'}, {'id': 6938, 'synset': 'cringle.n.01', 'name': 'cringle'}, {'id': 6939, 'synset': 'crinoline.n.03', 'name': 'crinoline'}, {'id': 6940, 'synset': 'crinoline.n.02', 'name': 'crinoline'}, {'id': 6941, 'synset': 'crochet_needle.n.01', 'name': 'crochet_needle'}, {'id': 6942, 'synset': 'crock_pot.n.01', 'name': 'Crock_Pot'}, {'id': 6943, 'synset': 'crook.n.03', 'name': 'crook'}, {'id': 6944, 'synset': 'crookes_radiometer.n.01', 'name': 'Crookes_radiometer'}, {'id': 6945, 'synset': 'crookes_tube.n.01', 'name': 'Crookes_tube'}, {'id': 6946, 'synset': 'croquet_ball.n.01', 'name': 'croquet_ball'}, {'id': 6947, 'synset': 'croquet_equipment.n.01', 'name': 'croquet_equipment'}, {'id': 6948, 'synset': 'croquet_mallet.n.01', 'name': 'croquet_mallet'}, {'id': 6949, 'synset': 'cross.n.01', 'name': 'cross'}, {'id': 6950, 'synset': 'crossbar.n.03', 'name': 'crossbar'}, {'id': 6951, 'synset': 'crossbar.n.02', 'name': 'crossbar'}, {'id': 6952, 'synset': 'crossbench.n.01', 'name': 'crossbench'}, {'id': 6953, 'synset': 'cross_bit.n.01', 'name': 'cross_bit'}, {'id': 6954, 'synset': 'crossbow.n.01', 'name': 'crossbow'}, {'id': 6955, 'synset': 'crosscut_saw.n.01', 'name': 'crosscut_saw'}, {'id': 6956, 'synset': 'crossjack.n.01', 'name': 'crossjack'}, {'id': 6957, 'synset': 'crosspiece.n.02', 'name': 'crosspiece'}, {'id': 6958, 'synset': 'crotchet.n.04', 'name': 'crotchet'}, {'id': 6959, 'synset': "croupier's_rake.n.01", 'name': "croupier's_rake"}, {'id': 6960, 'synset': 'crown.n.11', 'name': 'crown'}, {'id': 6961, 'synset': 'crown_jewels.n.01', 'name': 'crown_jewels'}, {'id': 6962, 'synset': 'crown_lens.n.01', 'name': 'crown_lens'}, {'id': 6963, 'synset': "crow's_nest.n.01", 'name': "crow's_nest"}, {'id': 6964, 'synset': 'crucible.n.01', 'name': 'crucible'}, {'id': 6965, 'synset': 'cruet.n.01', 'name': 'cruet'}, {'id': 6966, 'synset': 'cruet-stand.n.01', 'name': 'cruet-stand'}, {'id': 6967, 'synset': 'cruise_control.n.01', 'name': 'cruise_control'}, {'id': 6968, 'synset': 'cruise_missile.n.01', 'name': 'cruise_missile'}, {'id': 6969, 'synset': 'cruiser.n.02', 'name': 'cruiser'}, {'id': 6970, 'synset': 'crupper.n.01', 'name': 'crupper'}, {'id': 6971, 'synset': 'cruse.n.01', 'name': 'cruse'}, {'id': 6972, 'synset': 'crusher.n.01', 'name': 'crusher'}, {'id': 6973, 'synset': 'cryometer.n.01', 'name': 'cryometer'}, {'id': 6974, 'synset': 'cryoscope.n.01', 'name': 'cryoscope'}, {'id': 6975, 'synset': 'cryostat.n.01', 'name': 'cryostat'}, {'id': 6976, 'synset': 'crypt.n.01', 'name': 'crypt'}, {'id': 6977, 'synset': 'crystal.n.06', 'name': 'crystal'}, {'id': 6978, 'synset': 'crystal_detector.n.01', 'name': 'crystal_detector'}, {'id': 6979, 'synset': 'crystal_microphone.n.01', 'name': 'crystal_microphone'}, {'id': 6980, 'synset': 'crystal_oscillator.n.01', 'name': 'crystal_oscillator'}, {'id': 6981, 'synset': 'crystal_set.n.01', 'name': 'crystal_set'}, {'id': 6982, 'synset': 'cubitiere.n.01', 'name': 'cubitiere'}, {'id': 6983, 'synset': 'cucking_stool.n.01', 'name': 'cucking_stool'}, {'id': 6984, 'synset': 'cuckoo_clock.n.01', 'name': 'cuckoo_clock'}, {'id': 6985, 'synset': 'cuddy.n.01', 'name': 'cuddy'}, {'id': 6986, 'synset': 'cudgel.n.01', 'name': 'cudgel'}, {'id': 6987, 'synset': 'cue.n.04', 'name': 'cue'}, {'id': 6988, 'synset': 'cue_ball.n.01', 'name': 'cue_ball'}, {'id': 6989, 'synset': 'cuff.n.01', 'name': 'cuff'}, {'id': 6990, 'synset': 'cuirass.n.01', 'name': 'cuirass'}, {'id': 6991, 'synset': 'cuisse.n.01', 'name': 'cuisse'}, {'id': 6992, 'synset': 'cul.n.01', 'name': 'cul'}, {'id': 6993, 'synset': 'culdoscope.n.01', 'name': 'culdoscope'}, {'id': 6994, 'synset': 'cullis.n.01', 'name': 'cullis'}, {'id': 6995, 'synset': 'culotte.n.01', 'name': 'culotte'}, {'id': 6996, 'synset': 'cultivator.n.02', 'name': 'cultivator'}, {'id': 6997, 'synset': 'culverin.n.02', 'name': 'culverin'}, {'id': 6998, 'synset': 'culverin.n.01', 'name': 'culverin'}, {'id': 6999, 'synset': 'culvert.n.01', 'name': 'culvert'}, {'id': 7000, 'synset': 'cup_hook.n.01', 'name': 'cup_hook'}, {'id': 7001, 'synset': 'cupola.n.02', 'name': 'cupola'}, {'id': 7002, 'synset': 'cupola.n.01', 'name': 'cupola'}, {'id': 7003, 'synset': 'curb.n.02', 'name': 'curb'}, {'id': 7004, 'synset': 'curb_roof.n.01', 'name': 'curb_roof'}, {'id': 7005, 'synset': 'curbstone.n.01', 'name': 'curbstone'}, {'id': 7006, 'synset': 'curette.n.01', 'name': 'curette'}, {'id': 7007, 'synset': 'currycomb.n.01', 'name': 'currycomb'}, {'id': 7008, 'synset': 'cursor.n.01', 'name': 'cursor'}, {'id': 7009, 'synset': 'customhouse.n.01', 'name': 'customhouse'}, {'id': 7010, 'synset': 'cutaway.n.01', 'name': 'cutaway'}, {'id': 7011, 'synset': 'cutlas.n.01', 'name': 'cutlas'}, {'id': 7012, 'synset': 'cutoff.n.03', 'name': 'cutoff'}, {'id': 7013, 'synset': 'cutout.n.01', 'name': 'cutout'}, {'id': 7014, 'synset': 'cutter.n.06', 'name': 'cutter'}, {'id': 7015, 'synset': 'cutter.n.05', 'name': 'cutter'}, {'id': 7016, 'synset': 'cutting_implement.n.01', 'name': 'cutting_implement'}, {'id': 7017, 'synset': 'cutting_room.n.01', 'name': 'cutting_room'}, {'id': 7018, 'synset': 'cutty_stool.n.01', 'name': 'cutty_stool'}, {'id': 7019, 'synset': 'cutwork.n.01', 'name': 'cutwork'}, {'id': 7020, 'synset': 'cybercafe.n.01', 'name': 'cybercafe'}, {'id': 7021, 'synset': 'cyclopean_masonry.n.01', 'name': 'cyclopean_masonry'}, {'id': 7022, 'synset': 'cyclostyle.n.01', 'name': 'cyclostyle'}, {'id': 7023, 'synset': 'cyclotron.n.01', 'name': 'cyclotron'}, {'id': 7024, 'synset': 'cylinder.n.03', 'name': 'cylinder'}, {'id': 7025, 'synset': 'cylinder_lock.n.01', 'name': 'cylinder_lock'}, {'id': 7026, 'synset': 'dacha.n.01', 'name': 'dacha'}, {'id': 7027, 'synset': 'dacron.n.01', 'name': 'Dacron'}, {'id': 7028, 'synset': 'dado.n.02', 'name': 'dado'}, {'id': 7029, 'synset': 'dado_plane.n.01', 'name': 'dado_plane'}, {'id': 7030, 'synset': 'dairy.n.01', 'name': 'dairy'}, {'id': 7031, 'synset': 'dais.n.01', 'name': 'dais'}, {'id': 7032, 'synset': 'daisy_print_wheel.n.01', 'name': 'daisy_print_wheel'}, {'id': 7033, 'synset': 'daisywheel_printer.n.01', 'name': 'daisywheel_printer'}, {'id': 7034, 'synset': 'dam.n.01', 'name': 'dam'}, {'id': 7035, 'synset': 'damask.n.02', 'name': 'damask'}, {'id': 7036, 'synset': 'dampener.n.01', 'name': 'dampener'}, {'id': 7037, 'synset': 'damper.n.02', 'name': 'damper'}, {'id': 7038, 'synset': 'damper_block.n.01', 'name': 'damper_block'}, {'id': 7039, 'synset': 'dark_lantern.n.01', 'name': 'dark_lantern'}, {'id': 7040, 'synset': 'darkroom.n.01', 'name': 'darkroom'}, {'id': 7041, 'synset': 'darning_needle.n.01', 'name': 'darning_needle'}, {'id': 7042, 'synset': 'dart.n.02', 'name': 'dart'}, {'id': 7043, 'synset': 'dart.n.01', 'name': 'dart'}, {'id': 7044, 'synset': 'dashboard.n.02', 'name': 'dashboard'}, {'id': 7045, 'synset': 'dashiki.n.01', 'name': 'dashiki'}, {'id': 7046, 'synset': 'dash-pot.n.01', 'name': 'dash-pot'}, {'id': 7047, 'synset': 'data_converter.n.01', 'name': 'data_converter'}, {'id': 7048, 'synset': 'data_input_device.n.01', 'name': 'data_input_device'}, {'id': 7049, 'synset': 'data_multiplexer.n.01', 'name': 'data_multiplexer'}, {'id': 7050, 'synset': 'data_system.n.01', 'name': 'data_system'}, {'id': 7051, 'synset': 'davenport.n.03', 'name': 'davenport'}, {'id': 7052, 'synset': 'davenport.n.02', 'name': 'davenport'}, {'id': 7053, 'synset': 'davit.n.01', 'name': 'davit'}, {'id': 7054, 'synset': 'daybed.n.01', 'name': 'daybed'}, {'id': 7055, 'synset': 'daybook.n.02', 'name': 'daybook'}, {'id': 7056, 'synset': 'day_nursery.n.01', 'name': 'day_nursery'}, {'id': 7057, 'synset': 'day_school.n.03', 'name': 'day_school'}, {'id': 7058, 'synset': 'dead_axle.n.01', 'name': 'dead_axle'}, {'id': 7059, 'synset': 'deadeye.n.02', 'name': 'deadeye'}, {'id': 7060, 'synset': 'deadhead.n.02', 'name': 'deadhead'}, {'id': 7061, 'synset': 'deanery.n.01', 'name': 'deanery'}, {'id': 7062, 'synset': 'deathbed.n.02', 'name': 'deathbed'}, {'id': 7063, 'synset': 'death_camp.n.01', 'name': 'death_camp'}, {'id': 7064, 'synset': 'death_house.n.01', 'name': 'death_house'}, {'id': 7065, 'synset': 'death_knell.n.02', 'name': 'death_knell'}, {'id': 7066, 'synset': 'death_seat.n.01', 'name': 'death_seat'}, {'id': 7067, 'synset': 'deck.n.02', 'name': 'deck'}, {'id': 7068, 'synset': 'deck.n.04', 'name': 'deck'}, {'id': 7069, 'synset': 'deck-house.n.01', 'name': 'deck-house'}, {'id': 7070, 'synset': 'deckle.n.02', 'name': 'deckle'}, {'id': 7071, 'synset': 'deckle_edge.n.01', 'name': 'deckle_edge'}, {'id': 7072, 'synset': 'declinometer.n.01', 'name': 'declinometer'}, {'id': 7073, 'synset': 'decoder.n.02', 'name': 'decoder'}, {'id': 7074, 'synset': 'decolletage.n.01', 'name': 'decolletage'}, {'id': 7075, 'synset': 'decoupage.n.01', 'name': 'decoupage'}, {'id': 7076, 'synset': 'dedicated_file_server.n.01', 'name': 'dedicated_file_server'}, {'id': 7077, 'synset': 'deep-freeze.n.01', 'name': 'deep-freeze'}, {'id': 7078, 'synset': 'deerstalker.n.01', 'name': 'deerstalker'}, {'id': 7079, 'synset': 'defense_system.n.01', 'name': 'defense_system'}, {'id': 7080, 'synset': 'defensive_structure.n.01', 'name': 'defensive_structure'}, {'id': 7081, 'synset': 'defibrillator.n.01', 'name': 'defibrillator'}, {'id': 7082, 'synset': 'defilade.n.01', 'name': 'defilade'}, {'id': 7083, 'synset': 'deflector.n.01', 'name': 'deflector'}, {'id': 7084, 'synset': 'delayed_action.n.01', 'name': 'delayed_action'}, {'id': 7085, 'synset': 'delay_line.n.01', 'name': 'delay_line'}, {'id': 7086, 'synset': 'delft.n.01', 'name': 'delft'}, {'id': 7087, 'synset': 'delicatessen.n.02', 'name': 'delicatessen'}, {'id': 7088, 'synset': 'delivery_truck.n.01', 'name': 'delivery_truck'}, {'id': 7089, 'synset': 'delta_wing.n.01', 'name': 'delta_wing'}, {'id': 7090, 'synset': 'demijohn.n.01', 'name': 'demijohn'}, {'id': 7091, 'synset': 'demitasse.n.02', 'name': 'demitasse'}, {'id': 7092, 'synset': 'den.n.04', 'name': 'den'}, {'id': 7093, 'synset': 'denim.n.02', 'name': 'denim'}, {'id': 7094, 'synset': 'densimeter.n.01', 'name': 'densimeter'}, {'id': 7095, 'synset': 'densitometer.n.01', 'name': 'densitometer'}, {'id': 7096, 'synset': 'dental_appliance.n.01', 'name': 'dental_appliance'}, {'id': 7097, 'synset': 'dental_implant.n.01', 'name': 'dental_implant'}, {'id': 7098, 'synset': "dentist's_drill.n.01", 'name': "dentist's_drill"}, {'id': 7099, 'synset': 'denture.n.01', 'name': 'denture'}, {'id': 7100, 'synset': 'deodorant.n.01', 'name': 'deodorant'}, {'id': 7101, 'synset': 'department_store.n.01', 'name': 'department_store'}, {'id': 7102, 'synset': 'departure_lounge.n.01', 'name': 'departure_lounge'}, {'id': 7103, 'synset': 'depilatory.n.02', 'name': 'depilatory'}, {'id': 7104, 'synset': 'depressor.n.03', 'name': 'depressor'}, {'id': 7105, 'synset': 'depth_finder.n.01', 'name': 'depth_finder'}, {'id': 7106, 'synset': 'depth_gauge.n.01', 'name': 'depth_gauge'}, {'id': 7107, 'synset': 'derrick.n.02', 'name': 'derrick'}, {'id': 7108, 'synset': 'derrick.n.01', 'name': 'derrick'}, {'id': 7109, 'synset': 'derringer.n.01', 'name': 'derringer'}, {'id': 7110, 'synset': 'desk_phone.n.01', 'name': 'desk_phone'}, {'id': 7111, 'synset': 'desktop_computer.n.01', 'name': 'desktop_computer'}, {'id': 7112, 'synset': 'dessert_spoon.n.01', 'name': 'dessert_spoon'}, {'id': 7113, 'synset': 'destroyer.n.01', 'name': 'destroyer'}, {'id': 7114, 'synset': 'destroyer_escort.n.01', 'name': 'destroyer_escort'}, {'id': 7115, 'synset': 'detached_house.n.01', 'name': 'detached_house'}, {'id': 7116, 'synset': 'detector.n.01', 'name': 'detector'}, {'id': 7117, 'synset': 'detector.n.03', 'name': 'detector'}, {'id': 7118, 'synset': 'detention_home.n.01', 'name': 'detention_home'}, {'id': 7119, 'synset': 'detonating_fuse.n.01', 'name': 'detonating_fuse'}, {'id': 7120, 'synset': 'detonator.n.01', 'name': 'detonator'}, {'id': 7121, 'synset': 'developer.n.02', 'name': 'developer'}, {'id': 7122, 'synset': 'device.n.01', 'name': 'device'}, {'id': 7123, 'synset': 'dewar_flask.n.01', 'name': 'Dewar_flask'}, {'id': 7124, 'synset': 'dhoti.n.01', 'name': 'dhoti'}, {'id': 7125, 'synset': 'dhow.n.01', 'name': 'dhow'}, {'id': 7126, 'synset': 'dial.n.04', 'name': 'dial'}, {'id': 7127, 'synset': 'dial.n.03', 'name': 'dial'}, {'id': 7128, 'synset': 'dial.n.02', 'name': 'dial'}, {'id': 7129, 'synset': 'dialog_box.n.01', 'name': 'dialog_box'}, {'id': 7130, 'synset': 'dial_telephone.n.01', 'name': 'dial_telephone'}, {'id': 7131, 'synset': 'dialyzer.n.01', 'name': 'dialyzer'}, {'id': 7132, 'synset': 'diamante.n.02', 'name': 'diamante'}, {'id': 7133, 'synset': 'diaper.n.02', 'name': 'diaper'}, {'id': 7134, 'synset': 'diaphone.n.01', 'name': 'diaphone'}, {'id': 7135, 'synset': 'diaphragm.n.01', 'name': 'diaphragm'}, {'id': 7136, 'synset': 'diaphragm.n.04', 'name': 'diaphragm'}, {'id': 7137, 'synset': 'diathermy_machine.n.01', 'name': 'diathermy_machine'}, {'id': 7138, 'synset': 'dibble.n.01', 'name': 'dibble'}, {'id': 7139, 'synset': 'dice_cup.n.01', 'name': 'dice_cup'}, {'id': 7140, 'synset': 'dicer.n.01', 'name': 'dicer'}, {'id': 7141, 'synset': 'dickey.n.02', 'name': 'dickey'}, {'id': 7142, 'synset': 'dickey.n.01', 'name': 'dickey'}, {'id': 7143, 'synset': 'dictaphone.n.01', 'name': 'Dictaphone'}, {'id': 7144, 'synset': 'die.n.03', 'name': 'die'}, {'id': 7145, 'synset': 'diesel.n.02', 'name': 'diesel'}, {'id': 7146, 'synset': 'diesel-electric_locomotive.n.01', 'name': 'diesel-electric_locomotive'}, {'id': 7147, 'synset': 'diesel-hydraulic_locomotive.n.01', 'name': 'diesel-hydraulic_locomotive'}, {'id': 7148, 'synset': 'diesel_locomotive.n.01', 'name': 'diesel_locomotive'}, {'id': 7149, 'synset': 'diestock.n.01', 'name': 'diestock'}, {'id': 7150, 'synset': 'differential_analyzer.n.01', 'name': 'differential_analyzer'}, {'id': 7151, 'synset': 'differential_gear.n.01', 'name': 'differential_gear'}, {'id': 7152, 'synset': 'diffuser.n.02', 'name': 'diffuser'}, {'id': 7153, 'synset': 'diffuser.n.01', 'name': 'diffuser'}, {'id': 7154, 'synset': 'digester.n.01', 'name': 'digester'}, {'id': 7155, 'synset': 'diggings.n.02', 'name': 'diggings'}, {'id': 7156, 'synset': 'digital-analog_converter.n.01', 'name': 'digital-analog_converter'}, {'id': 7157, 'synset': 'digital_audiotape.n.01', 'name': 'digital_audiotape'}, {'id': 7158, 'synset': 'digital_camera.n.01', 'name': 'digital_camera'}, {'id': 7159, 'synset': 'digital_clock.n.01', 'name': 'digital_clock'}, {'id': 7160, 'synset': 'digital_computer.n.01', 'name': 'digital_computer'}, {'id': 7161, 'synset': 'digital_display.n.01', 'name': 'digital_display'}, {'id': 7162, 'synset': 'digital_subscriber_line.n.01', 'name': 'digital_subscriber_line'}, {'id': 7163, 'synset': 'digital_voltmeter.n.01', 'name': 'digital_voltmeter'}, {'id': 7164, 'synset': 'digital_watch.n.01', 'name': 'digital_watch'}, {'id': 7165, 'synset': 'digitizer.n.01', 'name': 'digitizer'}, {'id': 7166, 'synset': 'dilator.n.03', 'name': 'dilator'}, {'id': 7167, 'synset': 'dildo.n.01', 'name': 'dildo'}, {'id': 7168, 'synset': 'dimity.n.01', 'name': 'dimity'}, {'id': 7169, 'synset': 'dimmer.n.01', 'name': 'dimmer'}, {'id': 7170, 'synset': 'diner.n.03', 'name': 'diner'}, {'id': 7171, 'synset': 'dinette.n.01', 'name': 'dinette'}, {'id': 7172, 'synset': 'dining_area.n.01', 'name': 'dining_area'}, {'id': 7173, 'synset': 'dining_car.n.01', 'name': 'dining_car'}, {'id': 7174, 'synset': 'dining-hall.n.01', 'name': 'dining-hall'}, {'id': 7175, 'synset': 'dining_room.n.01', 'name': 'dining_room'}, {'id': 7176, 'synset': 'dining-room_furniture.n.01', 'name': 'dining-room_furniture'}, {'id': 7177, 'synset': 'dining-room_table.n.01', 'name': 'dining-room_table'}, {'id': 7178, 'synset': 'dinner_bell.n.01', 'name': 'dinner_bell'}, {'id': 7179, 'synset': 'dinner_dress.n.01', 'name': 'dinner_dress'}, {'id': 7180, 'synset': 'dinner_napkin.n.01', 'name': 'dinner_napkin'}, {'id': 7181, 'synset': 'dinner_pail.n.01', 'name': 'dinner_pail'}, {'id': 7182, 'synset': 'dinner_table.n.01', 'name': 'dinner_table'}, {'id': 7183, 'synset': 'dinner_theater.n.01', 'name': 'dinner_theater'}, {'id': 7184, 'synset': 'diode.n.02', 'name': 'diode'}, {'id': 7185, 'synset': 'diode.n.01', 'name': 'diode'}, {'id': 7186, 'synset': 'dip.n.07', 'name': 'dip'}, {'id': 7187, 'synset': 'diplomatic_building.n.01', 'name': 'diplomatic_building'}, {'id': 7188, 'synset': 'dipole.n.02', 'name': 'dipole'}, {'id': 7189, 'synset': 'dipper.n.01', 'name': 'dipper'}, {'id': 7190, 'synset': 'dipstick.n.01', 'name': 'dipstick'}, {'id': 7191, 'synset': 'dip_switch.n.01', 'name': 'DIP_switch'}, {'id': 7192, 'synset': 'directional_antenna.n.01', 'name': 'directional_antenna'}, {'id': 7193, 'synset': 'directional_microphone.n.01', 'name': 'directional_microphone'}, {'id': 7194, 'synset': 'direction_finder.n.01', 'name': 'direction_finder'}, {'id': 7195, 'synset': 'dirk.n.01', 'name': 'dirk'}, {'id': 7196, 'synset': 'dirndl.n.02', 'name': 'dirndl'}, {'id': 7197, 'synset': 'dirndl.n.01', 'name': 'dirndl'}, {'id': 7198, 'synset': 'dirty_bomb.n.01', 'name': 'dirty_bomb'}, {'id': 7199, 'synset': 'discharge_lamp.n.01', 'name': 'discharge_lamp'}, {'id': 7200, 'synset': 'discharge_pipe.n.01', 'name': 'discharge_pipe'}, {'id': 7201, 'synset': 'disco.n.02', 'name': 'disco'}, {'id': 7202, 'synset': 'discount_house.n.01', 'name': 'discount_house'}, {'id': 7203, 'synset': 'discus.n.02', 'name': 'discus'}, {'id': 7204, 'synset': 'disguise.n.02', 'name': 'disguise'}, {'id': 7205, 'synset': 'dishpan.n.01', 'name': 'dishpan'}, {'id': 7206, 'synset': 'dish_rack.n.01', 'name': 'dish_rack'}, {'id': 7207, 'synset': 'disk.n.02', 'name': 'disk'}, {'id': 7208, 'synset': 'disk_brake.n.01', 'name': 'disk_brake'}, {'id': 7209, 'synset': 'disk_clutch.n.01', 'name': 'disk_clutch'}, {'id': 7210, 'synset': 'disk_controller.n.01', 'name': 'disk_controller'}, {'id': 7211, 'synset': 'disk_drive.n.01', 'name': 'disk_drive'}, {'id': 7212, 'synset': 'diskette.n.01', 'name': 'diskette'}, {'id': 7213, 'synset': 'disk_harrow.n.01', 'name': 'disk_harrow'}, {'id': 7214, 'synset': 'dispatch_case.n.01', 'name': 'dispatch_case'}, {'id': 7215, 'synset': 'dispensary.n.01', 'name': 'dispensary'}, {'id': 7216, 'synset': 'display.n.06', 'name': 'display'}, {'id': 7217, 'synset': 'display_adapter.n.01', 'name': 'display_adapter'}, {'id': 7218, 'synset': 'display_panel.n.01', 'name': 'display_panel'}, {'id': 7219, 'synset': 'display_window.n.01', 'name': 'display_window'}, {'id': 7220, 'synset': 'disposal.n.04', 'name': 'disposal'}, {'id': 7221, 'synset': 'disrupting_explosive.n.01', 'name': 'disrupting_explosive'}, {'id': 7222, 'synset': 'distaff.n.02', 'name': 'distaff'}, {'id': 7223, 'synset': 'distillery.n.01', 'name': 'distillery'}, {'id': 7224, 'synset': 'distributor.n.04', 'name': 'distributor'}, {'id': 7225, 'synset': 'distributor_cam.n.01', 'name': 'distributor_cam'}, {'id': 7226, 'synset': 'distributor_cap.n.01', 'name': 'distributor_cap'}, {'id': 7227, 'synset': 'distributor_housing.n.01', 'name': 'distributor_housing'}, {'id': 7228, 'synset': 'distributor_point.n.01', 'name': 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'name': 'dogcart'}, {'id': 7245, 'synset': 'doggie_bag.n.01', 'name': 'doggie_bag'}, {'id': 7246, 'synset': 'dogsled.n.01', 'name': 'dogsled'}, {'id': 7247, 'synset': 'dog_wrench.n.01', 'name': 'dog_wrench'}, {'id': 7248, 'synset': 'doily.n.01', 'name': 'doily'}, {'id': 7249, 'synset': 'dolly.n.02', 'name': 'dolly'}, {'id': 7250, 'synset': 'dolman.n.02', 'name': 'dolman'}, {'id': 7251, 'synset': 'dolman.n.01', 'name': 'dolman'}, {'id': 7252, 'synset': 'dolman_sleeve.n.01', 'name': 'dolman_sleeve'}, {'id': 7253, 'synset': 'dolmen.n.01', 'name': 'dolmen'}, {'id': 7254, 'synset': 'dome.n.04', 'name': 'dome'}, {'id': 7255, 'synset': 'dome.n.03', 'name': 'dome'}, {'id': 7256, 'synset': 'domino.n.03', 'name': 'domino'}, {'id': 7257, 'synset': 'dongle.n.01', 'name': 'dongle'}, {'id': 7258, 'synset': 'donkey_jacket.n.01', 'name': 'donkey_jacket'}, {'id': 7259, 'synset': 'door.n.01', 'name': 'door'}, {'id': 7260, 'synset': 'door.n.05', 'name': 'door'}, {'id': 7261, 'synset': 'door.n.04', 'name': 'door'}, {'id': 7262, 'synset': 'doorbell.n.01', 'name': 'doorbell'}, {'id': 7263, 'synset': 'doorframe.n.01', 'name': 'doorframe'}, {'id': 7264, 'synset': 'doorjamb.n.01', 'name': 'doorjamb'}, {'id': 7265, 'synset': 'doorlock.n.01', 'name': 'doorlock'}, {'id': 7266, 'synset': 'doornail.n.01', 'name': 'doornail'}, {'id': 7267, 'synset': 'doorplate.n.01', 'name': 'doorplate'}, {'id': 7268, 'synset': 'doorsill.n.01', 'name': 'doorsill'}, {'id': 7269, 'synset': 'doorstop.n.01', 'name': 'doorstop'}, {'id': 7270, 'synset': 'doppler_radar.n.01', 'name': 'Doppler_radar'}, {'id': 7271, 'synset': 'dormer.n.01', 'name': 'dormer'}, {'id': 7272, 'synset': 'dormer_window.n.01', 'name': 'dormer_window'}, {'id': 7273, 'synset': 'dormitory.n.01', 'name': 'dormitory'}, {'id': 7274, 'synset': 'dormitory.n.02', 'name': 'dormitory'}, {'id': 7275, 'synset': 'dosemeter.n.01', 'name': 'dosemeter'}, {'id': 7276, 'synset': 'dossal.n.01', 'name': 'dossal'}, {'id': 7277, 'synset': 'dot_matrix_printer.n.01', 'name': 'dot_matrix_printer'}, {'id': 7278, 'synset': 'double_bed.n.01', 'name': 'double_bed'}, {'id': 7279, 'synset': 'double-bitted_ax.n.01', 'name': 'double-bitted_ax'}, {'id': 7280, 'synset': 'double_boiler.n.01', 'name': 'double_boiler'}, {'id': 7281, 'synset': 'double-breasted_jacket.n.01', 'name': 'double-breasted_jacket'}, {'id': 7282, 'synset': 'double-breasted_suit.n.01', 'name': 'double-breasted_suit'}, {'id': 7283, 'synset': 'double_door.n.01', 'name': 'double_door'}, {'id': 7284, 'synset': 'double_glazing.n.01', 'name': 'double_glazing'}, {'id': 7285, 'synset': 'double-hung_window.n.01', 'name': 'double-hung_window'}, {'id': 7286, 'synset': 'double_knit.n.01', 'name': 'double_knit'}, {'id': 7287, 'synset': 'doubler.n.01', 'name': 'doubler'}, {'id': 7288, 'synset': 'double_reed.n.02', 'name': 'double_reed'}, {'id': 7289, 'synset': 'double-reed_instrument.n.01', 'name': 'double-reed_instrument'}, {'id': 7290, 'synset': 'doublet.n.01', 'name': 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'name': 'drainplug'}, {'id': 7306, 'synset': 'drape.n.03', 'name': 'drape'}, {'id': 7307, 'synset': 'drapery.n.02', 'name': 'drapery'}, {'id': 7308, 'synset': 'drawbar.n.01', 'name': 'drawbar'}, {'id': 7309, 'synset': 'drawbridge.n.01', 'name': 'drawbridge'}, {'id': 7310, 'synset': 'drawing_chalk.n.01', 'name': 'drawing_chalk'}, {'id': 7311, 'synset': 'drawing_room.n.01', 'name': 'drawing_room'}, {'id': 7312, 'synset': 'drawing_room.n.02', 'name': 'drawing_room'}, {'id': 7313, 'synset': 'drawknife.n.01', 'name': 'drawknife'}, {'id': 7314, 'synset': 'drawstring_bag.n.01', 'name': 'drawstring_bag'}, {'id': 7315, 'synset': 'dray.n.01', 'name': 'dray'}, {'id': 7316, 'synset': 'dreadnought.n.01', 'name': 'dreadnought'}, {'id': 7317, 'synset': 'dredge.n.01', 'name': 'dredge'}, {'id': 7318, 'synset': 'dredger.n.01', 'name': 'dredger'}, {'id': 7319, 'synset': 'dredging_bucket.n.01', 'name': 'dredging_bucket'}, {'id': 7320, 'synset': 'dress_blues.n.01', 'name': 'dress_blues'}, {'id': 7321, 'synset': 'dressing.n.04', 'name': 'dressing'}, {'id': 7322, 'synset': 'dressing_case.n.01', 'name': 'dressing_case'}, {'id': 7323, 'synset': 'dressing_gown.n.01', 'name': 'dressing_gown'}, {'id': 7324, 'synset': 'dressing_room.n.01', 'name': 'dressing_room'}, {'id': 7325, 'synset': 'dressing_sack.n.01', 'name': 'dressing_sack'}, {'id': 7326, 'synset': 'dressing_table.n.01', 'name': 'dressing_table'}, {'id': 7327, 'synset': 'dress_rack.n.01', 'name': 'dress_rack'}, {'id': 7328, 'synset': 'dress_shirt.n.01', 'name': 'dress_shirt'}, {'id': 7329, 'synset': 'dress_uniform.n.01', 'name': 'dress_uniform'}, {'id': 7330, 'synset': 'drift_net.n.01', 'name': 'drift_net'}, {'id': 7331, 'synset': 'electric_drill.n.01', 'name': 'electric_drill'}, {'id': 7332, 'synset': 'drilling_platform.n.01', 'name': 'drilling_platform'}, {'id': 7333, 'synset': 'drill_press.n.01', 'name': 'drill_press'}, {'id': 7334, 'synset': 'drill_rig.n.01', 'name': 'drill_rig'}, {'id': 7335, 'synset': 'drinking_fountain.n.01', 'name': 'drinking_fountain'}, {'id': 7336, 'synset': 'drinking_vessel.n.01', 'name': 'drinking_vessel'}, {'id': 7337, 'synset': 'drip_loop.n.01', 'name': 'drip_loop'}, {'id': 7338, 'synset': 'drip_mat.n.01', 'name': 'drip_mat'}, {'id': 7339, 'synset': 'drip_pan.n.02', 'name': 'drip_pan'}, {'id': 7340, 'synset': 'dripping_pan.n.01', 'name': 'dripping_pan'}, {'id': 7341, 'synset': 'drip_pot.n.01', 'name': 'drip_pot'}, {'id': 7342, 'synset': 'drive.n.02', 'name': 'drive'}, {'id': 7343, 'synset': 'drive.n.10', 'name': 'drive'}, {'id': 7344, 'synset': 'drive_line.n.01', 'name': 'drive_line'}, {'id': 7345, 'synset': 'driver.n.05', 'name': 'driver'}, {'id': 7346, 'synset': 'driveshaft.n.01', 'name': 'driveshaft'}, {'id': 7347, 'synset': 'driveway.n.01', 'name': 'driveway'}, {'id': 7348, 'synset': 'driving_iron.n.01', 'name': 'driving_iron'}, {'id': 7349, 'synset': 'driving_wheel.n.01', 'name': 'driving_wheel'}, {'id': 7350, 'synset': 'drogue.n.04', 'name': 'drogue'}, {'id': 7351, 'synset': 'drogue_parachute.n.01', 'name': 'drogue_parachute'}, {'id': 7352, 'synset': 'drone.n.05', 'name': 'drone'}, {'id': 7353, 'synset': 'drop_arch.n.01', 'name': 'drop_arch'}, {'id': 7354, 'synset': 'drop_cloth.n.02', 'name': 'drop_cloth'}, {'id': 7355, 'synset': 'drop_curtain.n.01', 'name': 'drop_curtain'}, {'id': 7356, 'synset': 'drop_forge.n.01', 'name': 'drop_forge'}, {'id': 7357, 'synset': 'drop-leaf_table.n.01', 'name': 'drop-leaf_table'}, {'id': 7358, 'synset': 'droshky.n.01', 'name': 'droshky'}, {'id': 7359, 'synset': 'drove.n.03', 'name': 'drove'}, {'id': 7360, 'synset': 'drugget.n.01', 'name': 'drugget'}, {'id': 7361, 'synset': 'drugstore.n.01', 'name': 'drugstore'}, {'id': 7362, 'synset': 'drum.n.04', 'name': 'drum'}, {'id': 7363, 'synset': 'drum_brake.n.01', 'name': 'drum_brake'}, {'id': 7364, 'synset': 'drumhead.n.01', 'name': 'drumhead'}, {'id': 7365, 'synset': 'drum_printer.n.01', 'name': 'drum_printer'}, {'id': 7366, 'synset': 'drum_sander.n.01', 'name': 'drum_sander'}, {'id': 7367, 'synset': 'dry_battery.n.01', 'name': 'dry_battery'}, {'id': 7368, 'synset': 'dry-bulb_thermometer.n.01', 'name': 'dry-bulb_thermometer'}, {'id': 7369, 'synset': 'dry_cell.n.01', 'name': 'dry_cell'}, {'id': 7370, 'synset': 'dry_dock.n.01', 'name': 'dry_dock'}, {'id': 7371, 'synset': 'dryer.n.01', 'name': 'dryer'}, {'id': 7372, 'synset': 'dry_fly.n.01', 'name': 'dry_fly'}, {'id': 7373, 'synset': 'dry_kiln.n.01', 'name': 'dry_kiln'}, {'id': 7374, 'synset': 'dry_masonry.n.01', 'name': 'dry_masonry'}, {'id': 7375, 'synset': 'dry_point.n.02', 'name': 'dry_point'}, {'id': 7376, 'synset': 'dry_wall.n.02', 'name': 'dry_wall'}, {'id': 7377, 'synset': 'dual_scan_display.n.01', 'name': 'dual_scan_display'}, {'id': 7378, 'synset': 'duck.n.04', 'name': 'duck'}, {'id': 7379, 'synset': 'duckboard.n.01', 'name': 'duckboard'}, {'id': 7380, 'synset': 'duckpin.n.01', 'name': 'duckpin'}, {'id': 7381, 'synset': 'dudeen.n.01', 'name': 'dudeen'}, {'id': 7382, 'synset': 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'duplex_apartment.n.01', 'name': 'duplex_apartment'}, {'id': 7399, 'synset': 'duplex_house.n.01', 'name': 'duplex_house'}, {'id': 7400, 'synset': 'duplicator.n.01', 'name': 'duplicator'}, {'id': 7401, 'synset': 'dust_bag.n.01', 'name': 'dust_bag'}, {'id': 7402, 'synset': 'dustcloth.n.01', 'name': 'dustcloth'}, {'id': 7403, 'synset': 'dust_cover.n.03', 'name': 'dust_cover'}, {'id': 7404, 'synset': 'dust_cover.n.02', 'name': 'dust_cover'}, {'id': 7405, 'synset': 'dustmop.n.01', 'name': 'dustmop'}, {'id': 7406, 'synset': 'dutch_oven.n.01', 'name': 'Dutch_oven'}, {'id': 7407, 'synset': 'dutch_oven.n.02', 'name': 'Dutch_oven'}, {'id': 7408, 'synset': 'dwelling.n.01', 'name': 'dwelling'}, {'id': 7409, 'synset': 'dye-works.n.01', 'name': 'dye-works'}, {'id': 7410, 'synset': 'dynamo.n.01', 'name': 'dynamo'}, {'id': 7411, 'synset': 'dynamometer.n.01', 'name': 'dynamometer'}, {'id': 7412, 'synset': 'eames_chair.n.01', 'name': 'Eames_chair'}, {'id': 7413, 'synset': 'earflap.n.01', 'name': 'earflap'}, {'id': 7414, 'synset': 'early_warning_radar.n.01', 'name': 'early_warning_radar'}, {'id': 7415, 'synset': 'early_warning_system.n.01', 'name': 'early_warning_system'}, {'id': 7416, 'synset': 'earmuff.n.01', 'name': 'earmuff'}, {'id': 7417, 'synset': 'earplug.n.02', 'name': 'earplug'}, {'id': 7418, 'synset': 'earthenware.n.01', 'name': 'earthenware'}, {'id': 7419, 'synset': 'earthwork.n.01', 'name': 'earthwork'}, {'id': 7420, 'synset': 'easy_chair.n.01', 'name': 'easy_chair'}, {'id': 7421, 'synset': 'eaves.n.01', 'name': 'eaves'}, {'id': 7422, 'synset': 'ecclesiastical_attire.n.01', 'name': 'ecclesiastical_attire'}, {'id': 7423, 'synset': 'echinus.n.01', 'name': 'echinus'}, {'id': 7424, 'synset': 'echocardiograph.n.01', 'name': 'echocardiograph'}, {'id': 7425, 'synset': 'edger.n.02', 'name': 'edger'}, {'id': 7426, 'synset': 'edge_tool.n.01', 'name': 'edge_tool'}, {'id': 7427, 'synset': 'efficiency_apartment.n.01', 'name': 'efficiency_apartment'}, {'id': 7428, 'synset': 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7540, 'synset': 'escutcheon.n.03', 'name': 'escutcheon'}, {'id': 7541, 'synset': 'esophagoscope.n.01', 'name': 'esophagoscope'}, {'id': 7542, 'synset': 'espadrille.n.01', 'name': 'espadrille'}, {'id': 7543, 'synset': 'espalier.n.01', 'name': 'espalier'}, {'id': 7544, 'synset': 'espresso_maker.n.01', 'name': 'espresso_maker'}, {'id': 7545, 'synset': 'espresso_shop.n.01', 'name': 'espresso_shop'}, {'id': 7546, 'synset': 'establishment.n.04', 'name': 'establishment'}, {'id': 7547, 'synset': 'estaminet.n.01', 'name': 'estaminet'}, {'id': 7548, 'synset': 'estradiol_patch.n.01', 'name': 'estradiol_patch'}, {'id': 7549, 'synset': 'etagere.n.01', 'name': 'etagere'}, {'id': 7550, 'synset': 'etamine.n.01', 'name': 'etamine'}, {'id': 7551, 'synset': 'etching.n.02', 'name': 'etching'}, {'id': 7552, 'synset': 'ethernet.n.01', 'name': 'ethernet'}, {'id': 7553, 'synset': 'ethernet_cable.n.01', 'name': 'ethernet_cable'}, {'id': 7554, 'synset': 'eton_jacket.n.01', 'name': 'Eton_jacket'}, {'id': 7555, 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'firmer_chisel'}, {'id': 7722, 'synset': 'first-aid_station.n.01', 'name': 'first-aid_station'}, {'id': 7723, 'synset': 'first_base.n.01', 'name': 'first_base'}, {'id': 7724, 'synset': 'first_class.n.03', 'name': 'first_class'}, {'id': 7725, 'synset': "fisherman's_bend.n.01", 'name': "fisherman's_bend"}, {'id': 7726, 'synset': "fisherman's_knot.n.01", 'name': "fisherman's_knot"}, {'id': 7727, 'synset': "fisherman's_lure.n.01", 'name': "fisherman's_lure"}, {'id': 7728, 'synset': 'fishhook.n.01', 'name': 'fishhook'}, {'id': 7729, 'synset': 'fishing_boat.n.01', 'name': 'fishing_boat'}, {'id': 7730, 'synset': 'fishing_gear.n.01', 'name': 'fishing_gear'}, {'id': 7731, 'synset': 'fish_joint.n.01', 'name': 'fish_joint'}, {'id': 7732, 'synset': 'fish_knife.n.01', 'name': 'fish_knife'}, {'id': 7733, 'synset': 'fishnet.n.01', 'name': 'fishnet'}, {'id': 7734, 'synset': 'fish_slice.n.01', 'name': 'fish_slice'}, {'id': 7735, 'synset': 'fitment.n.01', 'name': 'fitment'}, {'id': 7736, 'synset': 'fixative.n.02', 'name': 'fixative'}, {'id': 7737, 'synset': 'fixer-upper.n.01', 'name': 'fixer-upper'}, {'id': 7738, 'synset': 'flageolet.n.02', 'name': 'flageolet'}, {'id': 7739, 'synset': 'flagon.n.01', 'name': 'flagon'}, {'id': 7740, 'synset': 'flagship.n.02', 'name': 'flagship'}, {'id': 7741, 'synset': 'flail.n.01', 'name': 'flail'}, {'id': 7742, 'synset': 'flambeau.n.01', 'name': 'flambeau'}, {'id': 7743, 'synset': 'flamethrower.n.01', 'name': 'flamethrower'}, {'id': 7744, 'synset': 'flange.n.01', 'name': 'flange'}, {'id': 7745, 'synset': 'flannel.n.03', 'name': 'flannel'}, {'id': 7746, 'synset': 'flannelette.n.01', 'name': 'flannelette'}, {'id': 7747, 'synset': 'flap.n.05', 'name': 'flap'}, {'id': 7748, 'synset': 'flash.n.09', 'name': 'flash'}, {'id': 7749, 'synset': 'flash_camera.n.01', 'name': 'flash_camera'}, {'id': 7750, 'synset': 'flasher.n.02', 'name': 'flasher'}, {'id': 7751, 'synset': 'flashlight_battery.n.01', 'name': 'flashlight_battery'}, {'id': 7752, 'synset': 'flash_memory.n.01', 'name': 'flash_memory'}, {'id': 7753, 'synset': 'flask.n.01', 'name': 'flask'}, {'id': 7754, 'synset': 'flat_arch.n.01', 'name': 'flat_arch'}, {'id': 7755, 'synset': 'flatbed.n.02', 'name': 'flatbed'}, {'id': 7756, 'synset': 'flatbed_press.n.01', 'name': 'flatbed_press'}, {'id': 7757, 'synset': 'flat_bench.n.01', 'name': 'flat_bench'}, {'id': 7758, 'synset': 'flatcar.n.01', 'name': 'flatcar'}, {'id': 7759, 'synset': 'flat_file.n.01', 'name': 'flat_file'}, {'id': 7760, 'synset': 'flatlet.n.01', 'name': 'flatlet'}, {'id': 7761, 'synset': 'flat_panel_display.n.01', 'name': 'flat_panel_display'}, {'id': 7762, 'synset': 'flats.n.01', 'name': 'flats'}, {'id': 7763, 'synset': 'flat_tip_screwdriver.n.01', 'name': 'flat_tip_screwdriver'}, {'id': 7764, 'synset': 'fleet_ballistic_missile_submarine.n.01', 'name': 'fleet_ballistic_missile_submarine'}, {'id': 7765, 'synset': 'fleur-de-lis.n.02', 'name': 'fleur-de-lis'}, {'id': 7766, 'synset': 'flight_simulator.n.01', 'name': 'flight_simulator'}, {'id': 7767, 'synset': 'flintlock.n.02', 'name': 'flintlock'}, {'id': 7768, 'synset': 'flintlock.n.01', 'name': 'flintlock'}, {'id': 7769, 'synset': 'float.n.05', 'name': 'float'}, {'id': 7770, 'synset': 'floating_dock.n.01', 'name': 'floating_dock'}, {'id': 7771, 'synset': 'floatplane.n.01', 'name': 'floatplane'}, {'id': 7772, 'synset': 'flood.n.03', 'name': 'flood'}, {'id': 7773, 'synset': 'floor.n.01', 'name': 'floor'}, {'id': 7774, 'synset': 'floor.n.02', 'name': 'floor'}, {'id': 7775, 'synset': 'floor.n.09', 'name': 'floor'}, {'id': 7776, 'synset': 'floorboard.n.02', 'name': 'floorboard'}, {'id': 7777, 'synset': 'floor_cover.n.01', 'name': 'floor_cover'}, {'id': 7778, 'synset': 'floor_joist.n.01', 'name': 'floor_joist'}, {'id': 7779, 'synset': 'floor_lamp.n.01', 'name': 'floor_lamp'}, {'id': 7780, 'synset': 'flophouse.n.01', 'name': 'flophouse'}, {'id': 7781, 'synset': 'florist.n.02', 'name': 'florist'}, {'id': 7782, 'synset': 'floss.n.01', 'name': 'floss'}, {'id': 7783, 'synset': 'flotsam.n.01', 'name': 'flotsam'}, {'id': 7784, 'synset': 'flour_bin.n.01', 'name': 'flour_bin'}, {'id': 7785, 'synset': 'flour_mill.n.01', 'name': 'flour_mill'}, {'id': 7786, 'synset': 'flowerbed.n.01', 'name': 'flowerbed'}, {'id': 7787, 'synset': 'flugelhorn.n.01', 'name': 'flugelhorn'}, {'id': 7788, 'synset': 'fluid_drive.n.01', 'name': 'fluid_drive'}, {'id': 7789, 'synset': 'fluid_flywheel.n.01', 'name': 'fluid_flywheel'}, {'id': 7790, 'synset': 'flume.n.02', 'name': 'flume'}, {'id': 7791, 'synset': 'fluorescent_lamp.n.01', 'name': 'fluorescent_lamp'}, {'id': 7792, 'synset': 'fluoroscope.n.01', 'name': 'fluoroscope'}, {'id': 7793, 'synset': 'flush_toilet.n.01', 'name': 'flush_toilet'}, {'id': 7794, 'synset': 'flute.n.01', 'name': 'flute'}, {'id': 7795, 'synset': 'flux_applicator.n.01', 'name': 'flux_applicator'}, {'id': 7796, 'synset': 'fluxmeter.n.01', 'name': 'fluxmeter'}, {'id': 7797, 'synset': 'fly.n.05', 'name': 'fly'}, {'id': 7798, 'synset': 'flying_boat.n.01', 'name': 'flying_boat'}, {'id': 7799, 'synset': 'flying_buttress.n.01', 'name': 'flying_buttress'}, {'id': 7800, 'synset': 'flying_carpet.n.01', 'name': 'flying_carpet'}, {'id': 7801, 'synset': 'flying_jib.n.01', 'name': 'flying_jib'}, {'id': 7802, 'synset': 'fly_rod.n.01', 'name': 'fly_rod'}, {'id': 7803, 'synset': 'fly_tent.n.01', 'name': 'fly_tent'}, {'id': 7804, 'synset': 'flytrap.n.01', 'name': 'flytrap'}, {'id': 7805, 'synset': 'flywheel.n.01', 'name': 'flywheel'}, {'id': 7806, 'synset': 'fob.n.03', 'name': 'fob'}, {'id': 7807, 'synset': 'foghorn.n.02', 'name': 'foghorn'}, {'id': 7808, 'synset': 'foglamp.n.01', 'name': 'foglamp'}, {'id': 7809, 'synset': 'foil.n.05', 'name': 'foil'}, {'id': 7810, 'synset': 'fold.n.06', 'name': 'fold'}, {'id': 7811, 'synset': 'folder.n.02', 'name': 'folder'}, {'id': 7812, 'synset': 'folding_door.n.01', 'name': 'folding_door'}, {'id': 7813, 'synset': 'folding_saw.n.01', 'name': 'folding_saw'}, {'id': 7814, 'synset': 'food_court.n.01', 'name': 'food_court'}, {'id': 7815, 'synset': 'food_hamper.n.01', 'name': 'food_hamper'}, {'id': 7816, 'synset': 'foot.n.11', 'name': 'foot'}, {'id': 7817, 'synset': 'footage.n.01', 'name': 'footage'}, {'id': 7818, 'synset': 'football_stadium.n.01', 'name': 'football_stadium'}, {'id': 7819, 'synset': 'footbath.n.01', 'name': 'footbath'}, {'id': 7820, 'synset': 'foot_brake.n.01', 'name': 'foot_brake'}, {'id': 7821, 'synset': 'footbridge.n.01', 'name': 'footbridge'}, {'id': 7822, 'synset': 'foothold.n.02', 'name': 'foothold'}, {'id': 7823, 'synset': 'footlocker.n.01', 'name': 'footlocker'}, {'id': 7824, 'synset': 'foot_rule.n.01', 'name': 'foot_rule'}, {'id': 7825, 'synset': 'footwear.n.02', 'name': 'footwear'}, {'id': 7826, 'synset': 'footwear.n.01', 'name': 'footwear'}, {'id': 7827, 'synset': 'forceps.n.01', 'name': 'forceps'}, {'id': 7828, 'synset': 'force_pump.n.01', 'name': 'force_pump'}, {'id': 7829, 'synset': 'fore-and-after.n.01', 'name': 'fore-and-after'}, {'id': 7830, 'synset': 'fore-and-aft_sail.n.01', 'name': 'fore-and-aft_sail'}, {'id': 7831, 'synset': 'forecastle.n.01', 'name': 'forecastle'}, {'id': 7832, 'synset': 'forecourt.n.01', 'name': 'forecourt'}, {'id': 7833, 'synset': 'foredeck.n.01', 'name': 'foredeck'}, {'id': 7834, 'synset': 'fore_edge.n.01', 'name': 'fore_edge'}, {'id': 7835, 'synset': 'foreground.n.02', 'name': 'foreground'}, {'id': 7836, 'synset': 'foremast.n.01', 'name': 'foremast'}, {'id': 7837, 'synset': 'fore_plane.n.01', 'name': 'fore_plane'}, {'id': 7838, 'synset': 'foresail.n.01', 'name': 'foresail'}, {'id': 7839, 'synset': 'forestay.n.01', 'name': 'forestay'}, {'id': 7840, 'synset': 'foretop.n.01', 'name': 'foretop'}, {'id': 7841, 'synset': 'fore-topmast.n.01', 'name': 'fore-topmast'}, {'id': 7842, 'synset': 'fore-topsail.n.01', 'name': 'fore-topsail'}, {'id': 7843, 'synset': 'forge.n.01', 'name': 'forge'}, {'id': 7844, 'synset': 'fork.n.04', 'name': 'fork'}, {'id': 7845, 'synset': 'formalwear.n.01', 'name': 'formalwear'}, {'id': 7846, 'synset': 'formica.n.01', 'name': 'Formica'}, {'id': 7847, 'synset': 'fortification.n.01', 'name': 'fortification'}, {'id': 7848, 'synset': 'fortress.n.01', 'name': 'fortress'}, {'id': 7849, 'synset': 'forty-five.n.01', 'name': 'forty-five'}, {'id': 7850, 'synset': 'foucault_pendulum.n.01', 'name': 'Foucault_pendulum'}, {'id': 7851, 'synset': 'foulard.n.01', 'name': 'foulard'}, {'id': 7852, 'synset': 'foul-weather_gear.n.01', 'name': 'foul-weather_gear'}, {'id': 7853, 'synset': 'foundation_garment.n.01', 'name': 'foundation_garment'}, {'id': 7854, 'synset': 'foundry.n.01', 'name': 'foundry'}, {'id': 7855, 'synset': 'fountain.n.01', 'name': 'fountain'}, {'id': 7856, 'synset': 'fountain_pen.n.01', 'name': 'fountain_pen'}, {'id': 7857, 'synset': 'four-in-hand.n.01', 'name': 'four-in-hand'}, {'id': 7858, 'synset': 'four-poster.n.01', 'name': 'four-poster'}, {'id': 7859, 'synset': 'four-pounder.n.01', 'name': 'four-pounder'}, {'id': 7860, 'synset': 'four-stroke_engine.n.01', 'name': 'four-stroke_engine'}, {'id': 7861, 'synset': 'four-wheel_drive.n.02', 'name': 'four-wheel_drive'}, {'id': 7862, 'synset': 'four-wheel_drive.n.01', 'name': 'four-wheel_drive'}, {'id': 7863, 'synset': 'four-wheeler.n.01', 'name': 'four-wheeler'}, {'id': 7864, 'synset': 'fowling_piece.n.01', 'name': 'fowling_piece'}, {'id': 7865, 'synset': 'foxhole.n.01', 'name': 'foxhole'}, {'id': 7866, 'synset': 'fragmentation_bomb.n.01', 'name': 'fragmentation_bomb'}, {'id': 7867, 'synset': 'frail.n.02', 'name': 'frail'}, {'id': 7868, 'synset': 'fraise.n.02', 'name': 'fraise'}, {'id': 7869, 'synset': 'frame.n.10', 'name': 'frame'}, {'id': 7870, 'synset': 'frame.n.01', 'name': 'frame'}, {'id': 7871, 'synset': 'frame_buffer.n.01', 'name': 'frame_buffer'}, {'id': 7872, 'synset': 'framework.n.03', 'name': 'framework'}, {'id': 7873, 'synset': 'francis_turbine.n.01', 'name': 'Francis_turbine'}, {'id': 7874, 'synset': 'franking_machine.n.01', 'name': 'franking_machine'}, {'id': 7875, 'synset': 'free_house.n.01', 'name': 'free_house'}, {'id': 7876, 'synset': 'free-reed.n.01', 'name': 'free-reed'}, {'id': 7877, 'synset': 'free-reed_instrument.n.01', 'name': 'free-reed_instrument'}, {'id': 7878, 'synset': 'freewheel.n.01', 'name': 'freewheel'}, {'id': 7879, 'synset': 'freight_elevator.n.01', 'name': 'freight_elevator'}, {'id': 7880, 'synset': 'freight_liner.n.01', 'name': 'freight_liner'}, {'id': 7881, 'synset': 'freight_train.n.01', 'name': 'freight_train'}, {'id': 7882, 'synset': 'french_door.n.01', 'name': 'French_door'}, {'id': 7883, 'synset': 'french_horn.n.01', 'name': 'French_horn'}, {'id': 7884, 'synset': 'french_polish.n.02', 'name': 'French_polish'}, {'id': 7885, 'synset': 'french_roof.n.01', 'name': 'French_roof'}, {'id': 7886, 'synset': 'french_window.n.01', 'name': 'French_window'}, {'id': 7887, 'synset': 'fresnel_lens.n.01', 'name': 'Fresnel_lens'}, {'id': 7888, 'synset': 'fret.n.04', 'name': 'fret'}, {'id': 7889, 'synset': 'friary.n.01', 'name': 'friary'}, {'id': 7890, 'synset': 'friction_clutch.n.01', 'name': 'friction_clutch'}, {'id': 7891, 'synset': 'frieze.n.02', 'name': 'frieze'}, {'id': 7892, 'synset': 'frieze.n.01', 'name': 'frieze'}, {'id': 7893, 'synset': 'frigate.n.02', 'name': 'frigate'}, {'id': 7894, 'synset': 'frigate.n.01', 'name': 'frigate'}, {'id': 7895, 'synset': 'frill.n.03', 'name': 'frill'}, {'id': 7896, 'synset': 'frock.n.01', 'name': 'frock'}, {'id': 7897, 'synset': 'frock_coat.n.01', 'name': 'frock_coat'}, {'id': 7898, 'synset': 'frontlet.n.01', 'name': 'frontlet'}, {'id': 7899, 'synset': 'front_porch.n.01', 'name': 'front_porch'}, {'id': 7900, 'synset': 'front_projector.n.01', 'name': 'front_projector'}, {'id': 7901, 'synset': 'fruit_machine.n.01', 'name': 'fruit_machine'}, {'id': 7902, 'synset': 'fuel_filter.n.01', 'name': 'fuel_filter'}, {'id': 7903, 'synset': 'fuel_gauge.n.01', 'name': 'fuel_gauge'}, {'id': 7904, 'synset': 'fuel_injection.n.01', 'name': 'fuel_injection'}, {'id': 7905, 'synset': 'fuel_system.n.01', 'name': 'fuel_system'}, {'id': 7906, 'synset': 'full-dress_uniform.n.01', 'name': 'full-dress_uniform'}, {'id': 7907, 'synset': 'full_metal_jacket.n.01', 'name': 'full_metal_jacket'}, {'id': 7908, 'synset': 'full_skirt.n.01', 'name': 'full_skirt'}, {'id': 7909, 'synset': 'fumigator.n.02', 'name': 'fumigator'}, {'id': 7910, 'synset': 'funeral_home.n.01', 'name': 'funeral_home'}, {'id': 7911, 'synset': 'funny_wagon.n.01', 'name': 'funny_wagon'}, {'id': 7912, 'synset': 'fur.n.03', 'name': 'fur'}, {'id': 7913, 'synset': 'fur_coat.n.01', 'name': 'fur_coat'}, {'id': 7914, 'synset': 'fur_hat.n.01', 'name': 'fur_hat'}, {'id': 7915, 'synset': 'furnace.n.01', 'name': 'furnace'}, {'id': 7916, 'synset': 'furnace_lining.n.01', 'name': 'furnace_lining'}, {'id': 7917, 'synset': 'furnace_room.n.01', 'name': 'furnace_room'}, {'id': 7918, 'synset': 'furnishing.n.02', 'name': 'furnishing'}, {'id': 7919, 'synset': 'furnishing.n.01', 'name': 'furnishing'}, {'id': 7920, 'synset': 'furniture.n.01', 'name': 'furniture'}, {'id': 7921, 'synset': 'fur-piece.n.01', 'name': 'fur-piece'}, {'id': 7922, 'synset': 'furrow.n.01', 'name': 'furrow'}, {'id': 7923, 'synset': 'fuse.n.01', 'name': 'fuse'}, {'id': 7924, 'synset': 'fusee_drive.n.01', 'name': 'fusee_drive'}, {'id': 7925, 'synset': 'fuselage.n.01', 'name': 'fuselage'}, {'id': 7926, 'synset': 'fusil.n.01', 'name': 'fusil'}, {'id': 7927, 'synset': 'fustian.n.02', 'name': 'fustian'}, {'id': 7928, 'synset': 'gabardine.n.01', 'name': 'gabardine'}, {'id': 7929, 'synset': 'gable.n.01', 'name': 'gable'}, {'id': 7930, 'synset': 'gable_roof.n.01', 'name': 'gable_roof'}, {'id': 7931, 'synset': 'gadgetry.n.01', 'name': 'gadgetry'}, {'id': 7932, 'synset': 'gaff.n.03', 'name': 'gaff'}, {'id': 7933, 'synset': 'gaff.n.02', 'name': 'gaff'}, {'id': 7934, 'synset': 'gaff.n.01', 'name': 'gaff'}, {'id': 7935, 'synset': 'gaffsail.n.01', 'name': 'gaffsail'}, {'id': 7936, 'synset': 'gaff_topsail.n.01', 'name': 'gaff_topsail'}, {'id': 7937, 'synset': 'gaiter.n.03', 'name': 'gaiter'}, {'id': 7938, 'synset': 'gaiter.n.02', 'name': 'gaiter'}, {'id': 7939, 'synset': 'galilean_telescope.n.01', 'name': 'Galilean_telescope'}, {'id': 7940, 'synset': 'galleon.n.01', 'name': 'galleon'}, {'id': 7941, 'synset': 'gallery.n.04', 'name': 'gallery'}, {'id': 7942, 'synset': 'gallery.n.03', 'name': 'gallery'}, {'id': 7943, 'synset': 'galley.n.04', 'name': 'galley'}, {'id': 7944, 'synset': 'galley.n.03', 'name': 'galley'}, {'id': 7945, 'synset': 'galley.n.02', 'name': 'galley'}, {'id': 7946, 'synset': 'gallows.n.01', 'name': 'gallows'}, {'id': 7947, 'synset': 'gallows_tree.n.01', 'name': 'gallows_tree'}, {'id': 7948, 'synset': 'galvanometer.n.01', 'name': 'galvanometer'}, {'id': 7949, 'synset': 'gambling_house.n.01', 'name': 'gambling_house'}, {'id': 7950, 'synset': 'gambrel.n.01', 'name': 'gambrel'}, {'id': 7951, 'synset': 'game.n.09', 'name': 'game'}, {'id': 7952, 'synset': 'gamebag.n.01', 'name': 'gamebag'}, {'id': 7953, 'synset': 'game_equipment.n.01', 'name': 'game_equipment'}, {'id': 7954, 'synset': 'gaming_table.n.01', 'name': 'gaming_table'}, {'id': 7955, 'synset': 'gamp.n.01', 'name': 'gamp'}, {'id': 7956, 'synset': 'gangplank.n.01', 'name': 'gangplank'}, {'id': 7957, 'synset': 'gangsaw.n.01', 'name': 'gangsaw'}, {'id': 7958, 'synset': 'gangway.n.01', 'name': 'gangway'}, {'id': 7959, 'synset': 'gantlet.n.04', 'name': 'gantlet'}, {'id': 7960, 'synset': 'gantry.n.01', 'name': 'gantry'}, {'id': 7961, 'synset': 'garage.n.01', 'name': 'garage'}, {'id': 7962, 'synset': 'garage.n.02', 'name': 'garage'}, {'id': 7963, 'synset': 'garand_rifle.n.01', 'name': 'Garand_rifle'}, {'id': 7964, 'synset': 'garboard.n.01', 'name': 'garboard'}, {'id': 7965, 'synset': 'garden.n.01', 'name': 'garden'}, {'id': 7966, 'synset': 'garden.n.03', 'name': 'garden'}, {'id': 7967, 'synset': 'garden_rake.n.01', 'name': 'garden_rake'}, {'id': 7968, 'synset': 'garden_spade.n.01', 'name': 'garden_spade'}, {'id': 7969, 'synset': 'garden_tool.n.01', 'name': 'garden_tool'}, {'id': 7970, 'synset': 'garden_trowel.n.01', 'name': 'garden_trowel'}, {'id': 7971, 'synset': 'gargoyle.n.01', 'name': 'gargoyle'}, {'id': 7972, 'synset': 'garibaldi.n.02', 'name': 'garibaldi'}, {'id': 7973, 'synset': 'garlic_press.n.01', 'name': 'garlic_press'}, {'id': 7974, 'synset': 'garment.n.01', 'name': 'garment'}, {'id': 7975, 'synset': 'garment_bag.n.01', 'name': 'garment_bag'}, {'id': 7976, 'synset': 'garrison_cap.n.01', 'name': 'garrison_cap'}, {'id': 7977, 'synset': 'garrote.n.01', 'name': 'garrote'}, {'id': 7978, 'synset': 'garter.n.01', 'name': 'garter'}, {'id': 7979, 'synset': 'garter_belt.n.01', 'name': 'garter_belt'}, {'id': 7980, 'synset': 'garter_stitch.n.01', 'name': 'garter_stitch'}, {'id': 7981, 'synset': 'gas_guzzler.n.01', 'name': 'gas_guzzler'}, {'id': 7982, 'synset': 'gas_shell.n.01', 'name': 'gas_shell'}, {'id': 7983, 'synset': 'gas_bracket.n.01', 'name': 'gas_bracket'}, {'id': 7984, 'synset': 'gas_burner.n.01', 'name': 'gas_burner'}, {'id': 7985, 'synset': 'gas-cooled_reactor.n.01', 'name': 'gas-cooled_reactor'}, {'id': 7986, 'synset': 'gas-discharge_tube.n.01', 'name': 'gas-discharge_tube'}, {'id': 7987, 'synset': 'gas_engine.n.01', 'name': 'gas_engine'}, {'id': 7988, 'synset': 'gas_fixture.n.01', 'name': 'gas_fixture'}, {'id': 7989, 'synset': 'gas_furnace.n.01', 'name': 'gas_furnace'}, {'id': 7990, 'synset': 'gas_gun.n.01', 'name': 'gas_gun'}, {'id': 7991, 'synset': 'gas_heater.n.01', 'name': 'gas_heater'}, {'id': 7992, 'synset': 'gas_holder.n.01', 'name': 'gas_holder'}, {'id': 7993, 'synset': 'gasket.n.01', 'name': 'gasket'}, {'id': 7994, 'synset': 'gas_lamp.n.01', 'name': 'gas_lamp'}, {'id': 7995, 'synset': 'gas_maser.n.01', 'name': 'gas_maser'}, {'id': 7996, 'synset': 'gas_meter.n.01', 'name': 'gas_meter'}, {'id': 7997, 'synset': 'gasoline_engine.n.01', 'name': 'gasoline_engine'}, {'id': 7998, 'synset': 'gasoline_gauge.n.01', 'name': 'gasoline_gauge'}, {'id': 7999, 'synset': 'gas_oven.n.02', 'name': 'gas_oven'}, {'id': 8000, 'synset': 'gas_oven.n.01', 'name': 'gas_oven'}, {'id': 8001, 'synset': 'gas_pump.n.01', 'name': 'gas_pump'}, {'id': 8002, 'synset': 'gas_range.n.01', 'name': 'gas_range'}, {'id': 8003, 'synset': 'gas_ring.n.01', 'name': 'gas_ring'}, {'id': 8004, 'synset': 'gas_tank.n.01', 'name': 'gas_tank'}, {'id': 8005, 'synset': 'gas_thermometer.n.01', 'name': 'gas_thermometer'}, {'id': 8006, 'synset': 'gastroscope.n.01', 'name': 'gastroscope'}, {'id': 8007, 'synset': 'gas_turbine.n.01', 'name': 'gas_turbine'}, {'id': 8008, 'synset': 'gas-turbine_ship.n.01', 'name': 'gas-turbine_ship'}, {'id': 8009, 'synset': 'gat.n.01', 'name': 'gat'}, {'id': 8010, 'synset': 'gate.n.01', 'name': 'gate'}, {'id': 8011, 'synset': 'gatehouse.n.01', 'name': 'gatehouse'}, {'id': 8012, 'synset': 'gateleg_table.n.01', 'name': 'gateleg_table'}, {'id': 8013, 'synset': 'gatepost.n.01', 'name': 'gatepost'}, {'id': 8014, 'synset': 'gathered_skirt.n.01', 'name': 'gathered_skirt'}, {'id': 8015, 'synset': 'gatling_gun.n.01', 'name': 'Gatling_gun'}, {'id': 8016, 'synset': 'gauge.n.01', 'name': 'gauge'}, {'id': 8017, 'synset': 'gauntlet.n.03', 'name': 'gauntlet'}, {'id': 8018, 'synset': 'gauntlet.n.02', 'name': 'gauntlet'}, {'id': 8019, 'synset': 'gauze.n.02', 'name': 'gauze'}, {'id': 8020, 'synset': 'gauze.n.01', 'name': 'gauze'}, {'id': 8021, 'synset': 'gavel.n.01', 'name': 'gavel'}, {'id': 8022, 'synset': 'gazebo.n.01', 'name': 'gazebo'}, {'id': 8023, 'synset': 'gear.n.01', 'name': 'gear'}, {'id': 8024, 'synset': 'gear.n.04', 'name': 'gear'}, {'id': 8025, 'synset': 'gear.n.03', 'name': 'gear'}, {'id': 8026, 'synset': 'gearbox.n.01', 'name': 'gearbox'}, {'id': 8027, 'synset': 'gearing.n.01', 'name': 'gearing'}, {'id': 8028, 'synset': 'gearset.n.01', 'name': 'gearset'}, {'id': 8029, 'synset': 'gearshift.n.01', 'name': 'gearshift'}, {'id': 8030, 'synset': 'geiger_counter.n.01', 'name': 'Geiger_counter'}, {'id': 8031, 'synset': 'geiger_tube.n.01', 'name': 'Geiger_tube'}, {'id': 8032, 'synset': 'gene_chip.n.01', 'name': 'gene_chip'}, {'id': 8033, 'synset': 'general-purpose_bomb.n.01', 'name': 'general-purpose_bomb'}, {'id': 8034, 'synset': 'generator.n.01', 'name': 'generator'}, {'id': 8035, 'synset': 'generator.n.04', 'name': 'generator'}, {'id': 8036, 'synset': 'geneva_gown.n.01', 'name': 'Geneva_gown'}, {'id': 8037, 'synset': 'geodesic_dome.n.01', 'name': 'geodesic_dome'}, {'id': 8038, 'synset': 'georgette.n.01', 'name': 'georgette'}, {'id': 8039, 'synset': 'gharry.n.01', 'name': 'gharry'}, {'id': 8040, 'synset': 'ghat.n.01', 'name': 'ghat'}, {'id': 8041, 'synset': 'ghetto_blaster.n.01', 'name': 'ghetto_blaster'}, {'id': 8042, 'synset': 'gift_shop.n.01', 'name': 'gift_shop'}, {'id': 8043, 'synset': 'gift_wrapping.n.01', 'name': 'gift_wrapping'}, {'id': 8044, 'synset': 'gig.n.05', 'name': 'gig'}, {'id': 8045, 'synset': 'gig.n.04', 'name': 'gig'}, {'id': 8046, 'synset': 'gig.n.01', 'name': 'gig'}, {'id': 8047, 'synset': 'gig.n.03', 'name': 'gig'}, {'id': 8048, 'synset': 'gildhall.n.01', 'name': 'gildhall'}, {'id': 8049, 'synset': 'gill_net.n.01', 'name': 'gill_net'}, {'id': 8050, 'synset': 'gilt.n.01', 'name': 'gilt'}, {'id': 8051, 'synset': 'gimbal.n.01', 'name': 'gimbal'}, {'id': 8052, 'synset': 'gingham.n.01', 'name': 'gingham'}, {'id': 8053, 'synset': 'girandole.n.01', 'name': 'girandole'}, {'id': 8054, 'synset': 'girder.n.01', 'name': 'girder'}, {'id': 8055, 'synset': 'glass.n.07', 'name': 'glass'}, {'id': 8056, 'synset': 'glass_cutter.n.03', 'name': 'glass_cutter'}, {'id': 8057, 'synset': 'glasses_case.n.01', 'name': 'glasses_case'}, {'id': 8058, 'synset': 'glebe_house.n.01', 'name': 'glebe_house'}, {'id': 8059, 'synset': 'glengarry.n.01', 'name': 'Glengarry'}, {'id': 8060, 'synset': 'glider.n.01', 'name': 'glider'}, {'id': 8061, 'synset': 'global_positioning_system.n.01', 'name': 'Global_Positioning_System'}, {'id': 8062, 'synset': 'glockenspiel.n.01', 'name': 'glockenspiel'}, {'id': 8063, 'synset': 'glory_hole.n.01', 'name': 'glory_hole'}, {'id': 8064, 'synset': 'glove_compartment.n.01', 'name': 'glove_compartment'}, {'id': 8065, 'synset': 'glow_lamp.n.01', 'name': 'glow_lamp'}, {'id': 8066, 'synset': 'glow_tube.n.01', 'name': 'glow_tube'}, {'id': 8067, 'synset': 'glyptic_art.n.01', 'name': 'glyptic_art'}, {'id': 8068, 'synset': 'glyptics.n.01', 'name': 'glyptics'}, {'id': 8069, 'synset': 'gnomon.n.01', 'name': 'gnomon'}, {'id': 8070, 'synset': 'goal.n.03', 'name': 'goal'}, {'id': 8071, 'synset': 'goalmouth.n.01', 'name': 'goalmouth'}, {'id': 8072, 'synset': 'goalpost.n.01', 'name': 'goalpost'}, {'id': 8073, 'synset': 'goblet.n.01', 'name': 'goblet'}, {'id': 8074, 'synset': 'godown.n.01', 'name': 'godown'}, {'id': 8075, 'synset': 'go-kart.n.01', 'name': 'go-kart'}, {'id': 8076, 'synset': 'gold_plate.n.02', 'name': 'gold_plate'}, {'id': 8077, 'synset': 'golf_bag.n.01', 'name': 'golf_bag'}, {'id': 8078, 'synset': 'golf_ball.n.01', 'name': 'golf_ball'}, {'id': 8079, 'synset': 'golf-club_head.n.01', 'name': 'golf-club_head'}, {'id': 8080, 'synset': 'golf_equipment.n.01', 'name': 'golf_equipment'}, {'id': 8081, 'synset': 'golf_glove.n.01', 'name': 'golf_glove'}, {'id': 8082, 'synset': 'golliwog.n.01', 'name': 'golliwog'}, {'id': 8083, 'synset': 'gong.n.01', 'name': 'gong'}, {'id': 8084, 'synset': 'goniometer.n.01', 'name': 'goniometer'}, {'id': 8085, 'synset': 'gordian_knot.n.02', 'name': 'Gordian_knot'}, {'id': 8086, 'synset': 'gorget.n.01', 'name': 'gorget'}, {'id': 8087, 'synset': 'gossamer.n.01', 'name': 'gossamer'}, {'id': 8088, 'synset': 'gothic_arch.n.01', 'name': 'Gothic_arch'}, {'id': 8089, 'synset': 'gouache.n.01', 'name': 'gouache'}, {'id': 8090, 'synset': 'gouge.n.02', 'name': 'gouge'}, {'id': 8091, 'synset': 'gourd.n.01', 'name': 'gourd'}, {'id': 8092, 'synset': 'government_building.n.01', 'name': 'government_building'}, {'id': 8093, 'synset': 'government_office.n.01', 'name': 'government_office'}, {'id': 8094, 'synset': 'gown.n.01', 'name': 'gown'}, {'id': 8095, 'synset': 'gown.n.05', 'name': 'gown'}, {'id': 8096, 'synset': 'gown.n.04', 'name': 'gown'}, {'id': 8097, 'synset': 'grab.n.01', 'name': 'grab'}, {'id': 8098, 'synset': 'grab_bag.n.02', 'name': 'grab_bag'}, {'id': 8099, 'synset': 'grab_bar.n.01', 'name': 'grab_bar'}, {'id': 8100, 'synset': 'grace_cup.n.01', 'name': 'grace_cup'}, {'id': 8101, 'synset': 'grade_separation.n.01', 'name': 'grade_separation'}, {'id': 8102, 'synset': 'graduated_cylinder.n.01', 'name': 'graduated_cylinder'}, {'id': 8103, 'synset': 'graffito.n.01', 'name': 'graffito'}, {'id': 8104, 'synset': 'gramophone.n.01', 'name': 'gramophone'}, {'id': 8105, 'synset': 'granary.n.01', 'name': 'granary'}, {'id': 8106, 'synset': 'grandfather_clock.n.01', 'name': 'grandfather_clock'}, {'id': 8107, 'synset': 'grand_piano.n.01', 'name': 'grand_piano'}, {'id': 8108, 'synset': 'graniteware.n.01', 'name': 'graniteware'}, {'id': 8109, 'synset': 'granny_knot.n.01', 'name': 'granny_knot'}, {'id': 8110, 'synset': 'grape_arbor.n.01', 'name': 'grape_arbor'}, {'id': 8111, 'synset': 'grapnel.n.02', 'name': 'grapnel'}, {'id': 8112, 'synset': 'grapnel.n.01', 'name': 'grapnel'}, {'id': 8113, 'synset': 'grass_skirt.n.01', 'name': 'grass_skirt'}, {'id': 8114, 'synset': 'grate.n.01', 'name': 'grate'}, {'id': 8115, 'synset': 'grate.n.03', 'name': 'grate'}, {'id': 8116, 'synset': 'graver.n.01', 'name': 'graver'}, {'id': 8117, 'synset': 'gravimeter.n.02', 'name': 'gravimeter'}, {'id': 8118, 'synset': 'gravure.n.03', 'name': 'gravure'}, {'id': 8119, 'synset': 'grey.n.06', 'name': 'grey'}, {'id': 8120, 'synset': 'grease-gun.n.01', 'name': 'grease-gun'}, {'id': 8121, 'synset': 'greasepaint.n.01', 'name': 'greasepaint'}, {'id': 8122, 'synset': 'greasy_spoon.n.01', 'name': 'greasy_spoon'}, {'id': 8123, 'synset': 'greatcoat.n.01', 'name': 'greatcoat'}, {'id': 8124, 'synset': 'great_hall.n.01', 'name': 'great_hall'}, {'id': 8125, 'synset': 'greave.n.01', 'name': 'greave'}, {'id': 8126, 'synset': 'greengrocery.n.02', 'name': 'greengrocery'}, {'id': 8127, 'synset': 'greenhouse.n.01', 'name': 'greenhouse'}, {'id': 8128, 'synset': 'grenade.n.01', 'name': 'grenade'}, {'id': 8129, 'synset': 'grid.n.05', 'name': 'grid'}, {'id': 8130, 'synset': 'grille.n.02', 'name': 'grille'}, {'id': 8131, 'synset': 'grillroom.n.01', 'name': 'grillroom'}, {'id': 8132, 'synset': 'grinder.n.04', 'name': 'grinder'}, {'id': 8133, 'synset': 'grinding_wheel.n.01', 'name': 'grinding_wheel'}, {'id': 8134, 'synset': 'grindstone.n.01', 'name': 'grindstone'}, {'id': 8135, 'synset': 'gripsack.n.01', 'name': 'gripsack'}, {'id': 8136, 'synset': 'gristmill.n.01', 'name': 'gristmill'}, {'id': 8137, 'synset': 'grocery_store.n.01', 'name': 'grocery_store'}, {'id': 8138, 'synset': 'grogram.n.01', 'name': 'grogram'}, {'id': 8139, 'synset': 'groined_vault.n.01', 'name': 'groined_vault'}, {'id': 8140, 'synset': 'groover.n.01', 'name': 'groover'}, {'id': 8141, 'synset': 'grosgrain.n.01', 'name': 'grosgrain'}, {'id': 8142, 'synset': 'gros_point.n.01', 'name': 'gros_point'}, {'id': 8143, 'synset': 'ground.n.09', 'name': 'ground'}, {'id': 8144, 'synset': 'ground_bait.n.01', 'name': 'ground_bait'}, {'id': 8145, 'synset': 'ground_control.n.01', 'name': 'ground_control'}, {'id': 8146, 'synset': 'ground_floor.n.01', 'name': 'ground_floor'}, {'id': 8147, 'synset': 'groundsheet.n.01', 'name': 'groundsheet'}, {'id': 8148, 'synset': 'g-string.n.01', 'name': 'G-string'}, {'id': 8149, 'synset': 'guard.n.03', 'name': 'guard'}, {'id': 8150, 'synset': 'guard_boat.n.01', 'name': 'guard_boat'}, {'id': 8151, 'synset': 'guardroom.n.02', 'name': 'guardroom'}, {'id': 8152, 'synset': 'guardroom.n.01', 'name': 'guardroom'}, {'id': 8153, 'synset': 'guard_ship.n.01', 'name': 'guard_ship'}, {'id': 8154, 'synset': "guard's_van.n.01", 'name': "guard's_van"}, {'id': 8155, 'synset': 'gueridon.n.01', 'name': 'gueridon'}, {'id': 8156, 'synset': 'guarnerius.n.03', 'name': 'Guarnerius'}, {'id': 8157, 'synset': 'guesthouse.n.01', 'name': 'guesthouse'}, {'id': 8158, 'synset': 'guestroom.n.01', 'name': 'guestroom'}, {'id': 8159, 'synset': 'guidance_system.n.01', 'name': 'guidance_system'}, {'id': 8160, 'synset': 'guided_missile.n.01', 'name': 'guided_missile'}, {'id': 8161, 'synset': 'guided_missile_cruiser.n.01', 'name': 'guided_missile_cruiser'}, {'id': 8162, 'synset': 'guided_missile_frigate.n.01', 'name': 'guided_missile_frigate'}, {'id': 8163, 'synset': 'guildhall.n.01', 'name': 'guildhall'}, {'id': 8164, 'synset': 'guilloche.n.01', 'name': 'guilloche'}, {'id': 8165, 'synset': 'guillotine.n.02', 'name': 'guillotine'}, {'id': 8166, 'synset': 'guimpe.n.02', 'name': 'guimpe'}, {'id': 8167, 'synset': 'guimpe.n.01', 'name': 'guimpe'}, {'id': 8168, 'synset': 'guitar_pick.n.01', 'name': 'guitar_pick'}, {'id': 8169, 'synset': 'gulag.n.01', 'name': 'gulag'}, {'id': 8170, 'synset': 'gunboat.n.01', 'name': 'gunboat'}, {'id': 8171, 'synset': 'gun_carriage.n.01', 'name': 'gun_carriage'}, {'id': 8172, 'synset': 'gun_case.n.01', 'name': 'gun_case'}, {'id': 8173, 'synset': 'gun_emplacement.n.01', 'name': 'gun_emplacement'}, {'id': 8174, 'synset': 'gun_enclosure.n.01', 'name': 'gun_enclosure'}, {'id': 8175, 'synset': 'gunlock.n.01', 'name': 'gunlock'}, {'id': 8176, 'synset': 'gunnery.n.01', 'name': 'gunnery'}, {'id': 8177, 'synset': 'gunnysack.n.01', 'name': 'gunnysack'}, {'id': 8178, 'synset': 'gun_pendulum.n.01', 'name': 'gun_pendulum'}, {'id': 8179, 'synset': 'gun_room.n.01', 'name': 'gun_room'}, {'id': 8180, 'synset': 'gunsight.n.01', 'name': 'gunsight'}, {'id': 8181, 'synset': 'gun_trigger.n.01', 'name': 'gun_trigger'}, {'id': 8182, 'synset': 'gurney.n.01', 'name': 'gurney'}, {'id': 8183, 'synset': 'gusher.n.01', 'name': 'gusher'}, {'id': 8184, 'synset': 'gusset.n.03', 'name': 'gusset'}, {'id': 8185, 'synset': 'gusset.n.02', 'name': 'gusset'}, {'id': 8186, 'synset': 'guy.n.03', 'name': 'guy'}, {'id': 8187, 'synset': 'gymnastic_apparatus.n.01', 'name': 'gymnastic_apparatus'}, {'id': 8188, 'synset': 'gym_shoe.n.01', 'name': 'gym_shoe'}, {'id': 8189, 'synset': 'gym_suit.n.01', 'name': 'gym_suit'}, {'id': 8190, 'synset': 'gymslip.n.01', 'name': 'gymslip'}, {'id': 8191, 'synset': 'gypsy_cab.n.01', 'name': 'gypsy_cab'}, {'id': 8192, 'synset': 'gyrocompass.n.01', 'name': 'gyrocompass'}, {'id': 8193, 'synset': 'gyroscope.n.01', 'name': 'gyroscope'}, {'id': 8194, 'synset': 'gyrostabilizer.n.01', 'name': 'gyrostabilizer'}, {'id': 8195, 'synset': 'habergeon.n.01', 'name': 'habergeon'}, {'id': 8196, 'synset': 'habit.n.03', 'name': 'habit'}, {'id': 8197, 'synset': 'habit.n.05', 'name': 'habit'}, {'id': 8198, 'synset': 'hacienda.n.02', 'name': 'hacienda'}, {'id': 8199, 'synset': 'hacksaw.n.01', 'name': 'hacksaw'}, {'id': 8200, 'synset': 'haft.n.01', 'name': 'haft'}, {'id': 8201, 'synset': 'haircloth.n.01', 'name': 'haircloth'}, {'id': 8202, 'synset': 'hairdressing.n.01', 'name': 'hairdressing'}, {'id': 8203, 'synset': 'hairpiece.n.01', 'name': 'hairpiece'}, {'id': 8204, 'synset': 'hair_shirt.n.01', 'name': 'hair_shirt'}, {'id': 8205, 'synset': 'hair_slide.n.01', 'name': 'hair_slide'}, {'id': 8206, 'synset': 'hair_spray.n.01', 'name': 'hair_spray'}, {'id': 8207, 'synset': 'hairspring.n.01', 'name': 'hairspring'}, {'id': 8208, 'synset': 'hair_trigger.n.01', 'name': 'hair_trigger'}, {'id': 8209, 'synset': 'halberd.n.01', 'name': 'halberd'}, {'id': 8210, 'synset': 'half_binding.n.01', 'name': 'half_binding'}, {'id': 8211, 'synset': 'half_hatchet.n.01', 'name': 'half_hatchet'}, {'id': 8212, 'synset': 'half_hitch.n.01', 'name': 'half_hitch'}, {'id': 8213, 'synset': 'half_track.n.01', 'name': 'half_track'}, {'id': 8214, 'synset': 'hall.n.13', 'name': 'hall'}, {'id': 8215, 'synset': 'hall.n.03', 'name': 'hall'}, {'id': 8216, 'synset': 'hall.n.12', 'name': 'hall'}, {'id': 8217, 'synset': 'hall_of_fame.n.01', 'name': 'Hall_of_Fame'}, {'id': 8218, 'synset': 'hall_of_residence.n.01', 'name': 'hall_of_residence'}, {'id': 8219, 'synset': 'hallstand.n.01', 'name': 'hallstand'}, {'id': 8220, 'synset': 'halter.n.01', 'name': 'halter'}, {'id': 8221, 'synset': 'hame.n.01', 'name': 'hame'}, {'id': 8222, 'synset': 'hammer.n.07', 'name': 'hammer'}, {'id': 8223, 'synset': 'hammer.n.05', 'name': 'hammer'}, {'id': 8224, 'synset': 'hammerhead.n.02', 'name': 'hammerhead'}, {'id': 8225, 'synset': 'hand.n.08', 'name': 'hand'}, {'id': 8226, 'synset': 'handball.n.01', 'name': 'handball'}, {'id': 8227, 'synset': 'handbarrow.n.01', 'name': 'handbarrow'}, {'id': 8228, 'synset': 'handbell.n.01', 'name': 'handbell'}, {'id': 8229, 'synset': 'handbow.n.01', 'name': 'handbow'}, {'id': 8230, 'synset': 'hand_brake.n.01', 'name': 'hand_brake'}, {'id': 8231, 'synset': 'hand_calculator.n.01', 'name': 'hand_calculator'}, {'id': 8232, 'synset': 'handcar.n.01', 'name': 'handcar'}, {'id': 8233, 'synset': 'hand_cream.n.01', 'name': 'hand_cream'}, {'id': 8234, 'synset': 'hand_drill.n.01', 'name': 'hand_drill'}, {'id': 8235, 'synset': 'hand_glass.n.02', 'name': 'hand_glass'}, {'id': 8236, 'synset': 'hand_grenade.n.01', 'name': 'hand_grenade'}, {'id': 8237, 'synset': 'hand-held_computer.n.01', 'name': 'hand-held_computer'}, {'id': 8238, 'synset': 'handhold.n.01', 'name': 'handhold'}, {'id': 8239, 'synset': 'handlebar.n.01', 'name': 'handlebar'}, {'id': 8240, 'synset': 'handloom.n.01', 'name': 'handloom'}, {'id': 8241, 'synset': 'hand_lotion.n.01', 'name': 'hand_lotion'}, {'id': 8242, 'synset': 'hand_luggage.n.01', 'name': 'hand_luggage'}, {'id': 8243, 'synset': 'hand-me-down.n.01', 'name': 'hand-me-down'}, {'id': 8244, 'synset': 'hand_mower.n.01', 'name': 'hand_mower'}, {'id': 8245, 'synset': 'hand_pump.n.01', 'name': 'hand_pump'}, {'id': 8246, 'synset': 'handrest.n.01', 'name': 'handrest'}, {'id': 8247, 'synset': 'handset.n.01', 'name': 'handset'}, {'id': 8248, 'synset': 'hand_shovel.n.01', 'name': 'hand_shovel'}, {'id': 8249, 'synset': 'handspike.n.01', 'name': 'handspike'}, {'id': 8250, 'synset': 'handstamp.n.01', 'name': 'handstamp'}, {'id': 8251, 'synset': 'hand_throttle.n.01', 'name': 'hand_throttle'}, {'id': 8252, 'synset': 'hand_tool.n.01', 'name': 'hand_tool'}, {'id': 8253, 'synset': 'hand_truck.n.01', 'name': 'hand_truck'}, {'id': 8254, 'synset': 'handwear.n.01', 'name': 'handwear'}, {'id': 8255, 'synset': 'handwheel.n.02', 'name': 'handwheel'}, {'id': 8256, 'synset': 'handwheel.n.01', 'name': 'handwheel'}, {'id': 8257, 'synset': 'hangar_queen.n.01', 'name': 'hangar_queen'}, {'id': 8258, 'synset': 'hanger.n.02', 'name': 'hanger'}, {'id': 8259, 'synset': 'hang_glider.n.02', 'name': 'hang_glider'}, {'id': 8260, 'synset': "hangman's_rope.n.01", 'name': "hangman's_rope"}, {'id': 8261, 'synset': 'hank.n.01', 'name': 'hank'}, {'id': 8262, 'synset': 'hansom.n.01', 'name': 'hansom'}, {'id': 8263, 'synset': 'harbor.n.02', 'name': 'harbor'}, {'id': 8264, 'synset': 'hard_disc.n.01', 'name': 'hard_disc'}, {'id': 8265, 'synset': 'hard_hat.n.02', 'name': 'hard_hat'}, {'id': 8266, 'synset': 'hardtop.n.01', 'name': 'hardtop'}, {'id': 8267, 'synset': 'hardware.n.02', 'name': 'hardware'}, {'id': 8268, 'synset': 'hardware_store.n.01', 'name': 'hardware_store'}, {'id': 8269, 'synset': 'harmonica.n.01', 'name': 'harmonica'}, {'id': 8270, 'synset': 'harness.n.02', 'name': 'harness'}, {'id': 8271, 'synset': 'harness.n.01', 'name': 'harness'}, {'id': 8272, 'synset': 'harp.n.01', 'name': 'harp'}, {'id': 8273, 'synset': 'harp.n.02', 'name': 'harp'}, {'id': 8274, 'synset': 'harpoon.n.01', 'name': 'harpoon'}, {'id': 8275, 'synset': 'harpoon_gun.n.01', 'name': 'harpoon_gun'}, {'id': 8276, 'synset': 'harpoon_log.n.01', 'name': 'harpoon_log'}, {'id': 8277, 'synset': 'harpsichord.n.01', 'name': 'harpsichord'}, {'id': 8278, 'synset': 'harris_tweed.n.01', 'name': 'Harris_Tweed'}, {'id': 8279, 'synset': 'harrow.n.01', 'name': 'harrow'}, {'id': 8280, 'synset': 'harvester.n.02', 'name': 'harvester'}, {'id': 8281, 'synset': 'hash_house.n.01', 'name': 'hash_house'}, {'id': 8282, 'synset': 'hasp.n.01', 'name': 'hasp'}, {'id': 8283, 'synset': 'hatch.n.03', 'name': 'hatch'}, {'id': 8284, 'synset': 'hatchback.n.02', 'name': 'hatchback'}, {'id': 8285, 'synset': 'hatchback.n.01', 'name': 'hatchback'}, {'id': 8286, 'synset': 'hatchel.n.01', 'name': 'hatchel'}, {'id': 8287, 'synset': 'hatchet.n.02', 'name': 'hatchet'}, {'id': 8288, 'synset': 'hatpin.n.01', 'name': 'hatpin'}, {'id': 8289, 'synset': 'hauberk.n.01', 'name': 'hauberk'}, {'id': 8290, 'synset': 'hawaiian_guitar.n.01', 'name': 'Hawaiian_guitar'}, {'id': 8291, 'synset': 'hawse.n.01', 'name': 'hawse'}, {'id': 8292, 'synset': 'hawser.n.01', 'name': 'hawser'}, {'id': 8293, 'synset': 'hawser_bend.n.01', 'name': 'hawser_bend'}, {'id': 8294, 'synset': 'hay_bale.n.01', 'name': 'hay_bale'}, {'id': 8295, 'synset': 'hayfork.n.01', 'name': 'hayfork'}, {'id': 8296, 'synset': 'hayloft.n.01', 'name': 'hayloft'}, {'id': 8297, 'synset': 'haymaker.n.01', 'name': 'haymaker'}, {'id': 8298, 'synset': 'hayrack.n.02', 'name': 'hayrack'}, {'id': 8299, 'synset': 'hayrack.n.01', 'name': 'hayrack'}, {'id': 8300, 'synset': 'hazard.n.03', 'name': 'hazard'}, {'id': 8301, 'synset': 'head.n.31', 'name': 'head'}, {'id': 8302, 'synset': 'head.n.30', 'name': 'head'}, {'id': 8303, 'synset': 'head.n.29', 'name': 'head'}, {'id': 8304, 'synset': 'headdress.n.01', 'name': 'headdress'}, {'id': 8305, 'synset': 'header.n.05', 'name': 'header'}, {'id': 8306, 'synset': 'header.n.04', 'name': 'header'}, {'id': 8307, 'synset': 'header.n.03', 'name': 'header'}, {'id': 8308, 'synset': 'header.n.02', 'name': 'header'}, {'id': 8309, 'synset': 'headfast.n.01', 'name': 'headfast'}, {'id': 8310, 'synset': 'head_gasket.n.01', 'name': 'head_gasket'}, {'id': 8311, 'synset': 'head_gate.n.02', 'name': 'head_gate'}, {'id': 8312, 'synset': 'headgear.n.03', 'name': 'headgear'}, {'id': 8313, 'synset': 'headpiece.n.02', 'name': 'headpiece'}, {'id': 8314, 'synset': 'headpin.n.01', 'name': 'headpin'}, {'id': 8315, 'synset': 'headquarters.n.01', 'name': 'headquarters'}, {'id': 8316, 'synset': 'headrace.n.01', 'name': 'headrace'}, {'id': 8317, 'synset': 'headrest.n.02', 'name': 'headrest'}, {'id': 8318, 'synset': 'headsail.n.01', 'name': 'headsail'}, {'id': 8319, 'synset': 'head_shop.n.01', 'name': 'head_shop'}, {'id': 8320, 'synset': 'headstock.n.01', 'name': 'headstock'}, {'id': 8321, 'synset': 'health_spa.n.01', 'name': 'health_spa'}, {'id': 8322, 'synset': 'hearing_aid.n.02', 'name': 'hearing_aid'}, {'id': 8323, 'synset': 'hearing_aid.n.01', 'name': 'hearing_aid'}, {'id': 8324, 'synset': 'hearse.n.01', 'name': 'hearse'}, {'id': 8325, 'synset': 'hearth.n.02', 'name': 'hearth'}, {'id': 8326, 'synset': 'hearthrug.n.01', 'name': 'hearthrug'}, {'id': 8327, 'synset': 'heart-lung_machine.n.01', 'name': 'heart-lung_machine'}, {'id': 8328, 'synset': 'heat_engine.n.01', 'name': 'heat_engine'}, {'id': 8329, 'synset': 'heat_exchanger.n.01', 'name': 'heat_exchanger'}, {'id': 8330, 'synset': 'heating_pad.n.01', 'name': 'heating_pad'}, {'id': 8331, 'synset': 'heat_lamp.n.01', 'name': 'heat_lamp'}, {'id': 8332, 'synset': 'heat_pump.n.01', 'name': 'heat_pump'}, {'id': 8333, 'synset': 'heat-seeking_missile.n.01', 'name': 'heat-seeking_missile'}, {'id': 8334, 'synset': 'heat_shield.n.01', 'name': 'heat_shield'}, {'id': 8335, 'synset': 'heat_sink.n.01', 'name': 'heat_sink'}, {'id': 8336, 'synset': 'heaume.n.01', 'name': 'heaume'}, {'id': 8337, 'synset': 'heaver.n.01', 'name': 'heaver'}, {'id': 8338, 'synset': 'heavier-than-air_craft.n.01', 'name': 'heavier-than-air_craft'}, {'id': 8339, 'synset': 'heckelphone.n.01', 'name': 'heckelphone'}, {'id': 8340, 'synset': 'hectograph.n.01', 'name': 'hectograph'}, {'id': 8341, 'synset': 'hedge.n.01', 'name': 'hedge'}, {'id': 8342, 'synset': 'hedge_trimmer.n.01', 'name': 'hedge_trimmer'}, {'id': 8343, 'synset': 'helicon.n.01', 'name': 'helicon'}, {'id': 8344, 'synset': 'heliograph.n.01', 'name': 'heliograph'}, {'id': 8345, 'synset': 'heliometer.n.01', 'name': 'heliometer'}, {'id': 8346, 'synset': 'helm.n.01', 'name': 'helm'}, {'id': 8347, 'synset': 'helmet.n.01', 'name': 'helmet'}, {'id': 8348, 'synset': 'hematocrit.n.02', 'name': 'hematocrit'}, {'id': 8349, 'synset': 'hemming-stitch.n.01', 'name': 'hemming-stitch'}, {'id': 8350, 'synset': 'hemostat.n.01', 'name': 'hemostat'}, {'id': 8351, 'synset': 'hemstitch.n.01', 'name': 'hemstitch'}, {'id': 8352, 'synset': 'henroost.n.01', 'name': 'henroost'}, {'id': 8353, 'synset': 'heraldry.n.02', 'name': 'heraldry'}, {'id': 8354, 'synset': 'hermitage.n.01', 'name': 'hermitage'}, {'id': 8355, 'synset': 'herringbone.n.01', 'name': 'herringbone'}, {'id': 8356, 'synset': 'herringbone.n.02', 'name': 'herringbone'}, {'id': 8357, 'synset': 'herschelian_telescope.n.01', 'name': 'Herschelian_telescope'}, {'id': 8358, 'synset': 'hessian_boot.n.01', 'name': 'Hessian_boot'}, {'id': 8359, 'synset': 'heterodyne_receiver.n.01', 'name': 'heterodyne_receiver'}, {'id': 8360, 'synset': 'hibachi.n.01', 'name': 'hibachi'}, {'id': 8361, 'synset': 'hideaway.n.02', 'name': 'hideaway'}, {'id': 8362, 'synset': 'hi-fi.n.01', 'name': 'hi-fi'}, {'id': 8363, 'synset': 'high_altar.n.01', 'name': 'high_altar'}, {'id': 8364, 'synset': 'high-angle_gun.n.01', 'name': 'high-angle_gun'}, {'id': 8365, 'synset': 'highball_glass.n.01', 'name': 'highball_glass'}, {'id': 8366, 'synset': 'highboard.n.01', 'name': 'highboard'}, {'id': 8367, 'synset': 'highboy.n.01', 'name': 'highboy'}, {'id': 8368, 'synset': 'high_gear.n.01', 'name': 'high_gear'}, {'id': 8369, 'synset': 'high-hat_cymbal.n.01', 'name': 'high-hat_cymbal'}, {'id': 8370, 'synset': 'highlighter.n.02', 'name': 'highlighter'}, {'id': 8371, 'synset': 'highlighter.n.01', 'name': 'highlighter'}, {'id': 8372, 'synset': 'high-pass_filter.n.01', 'name': 'high-pass_filter'}, {'id': 8373, 'synset': 'high-rise.n.01', 'name': 'high-rise'}, {'id': 8374, 'synset': 'high_table.n.01', 'name': 'high_table'}, {'id': 8375, 'synset': 'high-warp_loom.n.01', 'name': 'high-warp_loom'}, {'id': 8376, 'synset': 'hijab.n.01', 'name': 'hijab'}, {'id': 8377, 'synset': 'hinging_post.n.01', 'name': 'hinging_post'}, {'id': 8378, 'synset': 'hip_boot.n.01', 'name': 'hip_boot'}, {'id': 8379, 'synset': 'hipflask.n.01', 'name': 'hipflask'}, {'id': 8380, 'synset': 'hip_pad.n.01', 'name': 'hip_pad'}, {'id': 8381, 'synset': 'hip_pocket.n.01', 'name': 'hip_pocket'}, {'id': 8382, 'synset': 'hippodrome.n.01', 'name': 'hippodrome'}, {'id': 8383, 'synset': 'hip_roof.n.01', 'name': 'hip_roof'}, {'id': 8384, 'synset': 'hitch.n.05', 'name': 'hitch'}, {'id': 8385, 'synset': 'hitch.n.04', 'name': 'hitch'}, {'id': 8386, 'synset': 'hitching_post.n.01', 'name': 'hitching_post'}, {'id': 8387, 'synset': 'hitchrack.n.01', 'name': 'hitchrack'}, {'id': 8388, 'synset': 'hob.n.03', 'name': 'hob'}, {'id': 8389, 'synset': 'hobble_skirt.n.01', 'name': 'hobble_skirt'}, {'id': 8390, 'synset': 'hockey_skate.n.01', 'name': 'hockey_skate'}, {'id': 8391, 'synset': 'hod.n.01', 'name': 'hod'}, {'id': 8392, 'synset': 'hodoscope.n.01', 'name': 'hodoscope'}, {'id': 8393, 'synset': 'hoe.n.01', 'name': 'hoe'}, {'id': 8394, 'synset': 'hoe_handle.n.01', 'name': 'hoe_handle'}, {'id': 8395, 'synset': 'hogshead.n.02', 'name': 'hogshead'}, {'id': 8396, 'synset': 'hoist.n.01', 'name': 'hoist'}, {'id': 8397, 'synset': 'hold.n.07', 'name': 'hold'}, {'id': 8398, 'synset': 'holder.n.01', 'name': 'holder'}, {'id': 8399, 'synset': 'holding_cell.n.01', 'name': 'holding_cell'}, {'id': 8400, 'synset': 'holding_device.n.01', 'name': 'holding_device'}, {'id': 8401, 'synset': 'holding_pen.n.01', 'name': 'holding_pen'}, {'id': 8402, 'synset': 'hollowware.n.01', 'name': 'hollowware'}, {'id': 8403, 'synset': 'holster.n.01', 'name': 'holster'}, {'id': 8404, 'synset': 'holster.n.02', 'name': 'holster'}, {'id': 8405, 'synset': 'holy_of_holies.n.02', 'name': 'holy_of_holies'}, {'id': 8406, 'synset': 'home.n.09', 'name': 'home'}, {'id': 8407, 'synset': 'home_appliance.n.01', 'name': 'home_appliance'}, {'id': 8408, 'synset': 'home_computer.n.01', 'name': 'home_computer'}, {'id': 8409, 'synset': 'home_room.n.01', 'name': 'home_room'}, {'id': 8410, 'synset': 'homespun.n.01', 'name': 'homespun'}, {'id': 8411, 'synset': 'homestead.n.03', 'name': 'homestead'}, {'id': 8412, 'synset': 'home_theater.n.01', 'name': 'home_theater'}, {'id': 8413, 'synset': 'homing_torpedo.n.01', 'name': 'homing_torpedo'}, {'id': 8414, 'synset': 'hone.n.01', 'name': 'hone'}, {'id': 8415, 'synset': 'honeycomb.n.02', 'name': 'honeycomb'}, {'id': 8416, 'synset': 'hood.n.09', 'name': 'hood'}, {'id': 8417, 'synset': 'hood.n.08', 'name': 'hood'}, {'id': 8418, 'synset': 'hood.n.07', 'name': 'hood'}, {'id': 8419, 'synset': 'hood.n.05', 'name': 'hood'}, {'id': 8420, 'synset': 'hood_latch.n.01', 'name': 'hood_latch'}, {'id': 8421, 'synset': 'hook.n.04', 'name': 'hook'}, {'id': 8422, 'synset': 'hook.n.01', 'name': 'hook'}, {'id': 8423, 'synset': 'hook_and_eye.n.01', 'name': 'hook_and_eye'}, {'id': 8424, 'synset': 'hookup.n.02', 'name': 'hookup'}, {'id': 8425, 'synset': 'hookup.n.01', 'name': 'hookup'}, {'id': 8426, 'synset': 'hook_wrench.n.01', 'name': 'hook_wrench'}, {'id': 8427, 'synset': 'hoopskirt.n.01', 'name': 'hoopskirt'}, {'id': 8428, 'synset': 'hoosegow.n.01', 'name': 'hoosegow'}, {'id': 8429, 'synset': 'hoover.n.04', 'name': 'Hoover'}, {'id': 8430, 'synset': 'hope_chest.n.01', 'name': 'hope_chest'}, {'id': 8431, 'synset': 'hopper.n.01', 'name': 'hopper'}, {'id': 8432, 'synset': 'hopsacking.n.01', 'name': 'hopsacking'}, {'id': 8433, 'synset': 'horizontal_bar.n.01', 'name': 'horizontal_bar'}, {'id': 8434, 'synset': 'horizontal_stabilizer.n.01', 'name': 'horizontal_stabilizer'}, {'id': 8435, 'synset': 'horizontal_tail.n.01', 'name': 'horizontal_tail'}, {'id': 8436, 'synset': 'horn.n.09', 'name': 'horn'}, {'id': 8437, 'synset': 'horn.n.01', 'name': 'horn'}, {'id': 8438, 'synset': 'horn.n.08', 'name': 'horn'}, {'id': 8439, 'synset': 'horn_button.n.01', 'name': 'horn_button'}, {'id': 8440, 'synset': 'hornpipe.n.03', 'name': 'hornpipe'}, {'id': 8441, 'synset': 'horse.n.02', 'name': 'horse'}, {'id': 8442, 'synset': 'horsebox.n.01', 'name': 'horsebox'}, {'id': 8443, 'synset': 'horsecar.n.01', 'name': 'horsecar'}, {'id': 8444, 'synset': 'horse_cart.n.01', 'name': 'horse_cart'}, {'id': 8445, 'synset': 'horsecloth.n.01', 'name': 'horsecloth'}, {'id': 8446, 'synset': 'horse-drawn_vehicle.n.01', 'name': 'horse-drawn_vehicle'}, {'id': 8447, 'synset': 'horsehair.n.02', 'name': 'horsehair'}, {'id': 8448, 'synset': 'horsehair_wig.n.01', 'name': 'horsehair_wig'}, {'id': 8449, 'synset': 'horseless_carriage.n.01', 'name': 'horseless_carriage'}, {'id': 8450, 'synset': 'horse_pistol.n.01', 'name': 'horse_pistol'}, {'id': 8451, 'synset': 'horseshoe.n.02', 'name': 'horseshoe'}, {'id': 8452, 'synset': 'horseshoe.n.01', 'name': 'horseshoe'}, {'id': 8453, 'synset': 'horse-trail.n.01', 'name': 'horse-trail'}, {'id': 8454, 'synset': 'horsewhip.n.01', 'name': 'horsewhip'}, {'id': 8455, 'synset': 'hose.n.02', 'name': 'hose'}, {'id': 8456, 'synset': 'hosiery.n.01', 'name': 'hosiery'}, {'id': 8457, 'synset': 'hospice.n.01', 'name': 'hospice'}, {'id': 8458, 'synset': 'hospital.n.01', 'name': 'hospital'}, {'id': 8459, 'synset': 'hospital_bed.n.01', 'name': 'hospital_bed'}, {'id': 8460, 'synset': 'hospital_room.n.01', 'name': 'hospital_room'}, {'id': 8461, 'synset': 'hospital_ship.n.01', 'name': 'hospital_ship'}, {'id': 8462, 'synset': 'hospital_train.n.01', 'name': 'hospital_train'}, {'id': 8463, 'synset': 'hostel.n.02', 'name': 'hostel'}, {'id': 8464, 'synset': 'hostel.n.01', 'name': 'hostel'}, {'id': 8465, 'synset': 'hotel.n.01', 'name': 'hotel'}, {'id': 8466, 'synset': 'hotel-casino.n.02', 'name': 'hotel-casino'}, {'id': 8467, 'synset': 'hotel-casino.n.01', 'name': 'hotel-casino'}, {'id': 8468, 'synset': 'hotel_room.n.01', 'name': 'hotel_room'}, {'id': 8469, 'synset': 'hot_line.n.01', 'name': 'hot_line'}, {'id': 8470, 'synset': 'hot_pants.n.02', 'name': 'hot_pants'}, {'id': 8471, 'synset': 'hot_rod.n.01', 'name': 'hot_rod'}, {'id': 8472, 'synset': 'hot_spot.n.03', 'name': 'hot_spot'}, {'id': 8473, 'synset': 'hot_tub.n.01', 'name': 'hot_tub'}, {'id': 8474, 'synset': 'hot-water_bottle.n.01', 'name': 'hot-water_bottle'}, {'id': 8475, 'synset': 'houndstooth_check.n.01', 'name': 'houndstooth_check'}, {'id': 8476, 'synset': 'hour_hand.n.01', 'name': 'hour_hand'}, {'id': 8477, 'synset': 'house.n.01', 'name': 'house'}, {'id': 8478, 'synset': 'house.n.12', 'name': 'house'}, {'id': 8479, 'synset': 'houselights.n.01', 'name': 'houselights'}, {'id': 8480, 'synset': 'house_of_cards.n.02', 'name': 'house_of_cards'}, {'id': 8481, 'synset': 'house_of_correction.n.01', 'name': 'house_of_correction'}, {'id': 8482, 'synset': 'house_paint.n.01', 'name': 'house_paint'}, {'id': 8483, 'synset': 'housetop.n.01', 'name': 'housetop'}, {'id': 8484, 'synset': 'housing.n.01', 'name': 'housing'}, {'id': 8485, 'synset': 'hovel.n.01', 'name': 'hovel'}, {'id': 8486, 'synset': 'hovercraft.n.01', 'name': 'hovercraft'}, {'id': 8487, 'synset': 'howdah.n.01', 'name': 'howdah'}, {'id': 8488, 'synset': 'huarache.n.01', 'name': 'huarache'}, {'id': 8489, 'synset': 'hub-and-spoke.n.01', 'name': 'hub-and-spoke'}, {'id': 8490, 'synset': 'hubcap.n.01', 'name': 'hubcap'}, {'id': 8491, 'synset': 'huck.n.01', 'name': 'huck'}, {'id': 8492, 'synset': 'hug-me-tight.n.01', 'name': 'hug-me-tight'}, {'id': 8493, 'synset': 'hula-hoop.n.01', 'name': 'hula-hoop'}, {'id': 8494, 'synset': 'hulk.n.02', 'name': 'hulk'}, {'id': 8495, 'synset': 'hull.n.06', 'name': 'hull'}, {'id': 8496, 'synset': 'humeral_veil.n.01', 'name': 'humeral_veil'}, {'id': 8497, 'synset': 'humvee.n.01', 'name': 'Humvee'}, {'id': 8498, 'synset': 'hunter.n.04', 'name': 'hunter'}, {'id': 8499, 'synset': 'hunting_knife.n.01', 'name': 'hunting_knife'}, {'id': 8500, 'synset': 'hurdle.n.01', 'name': 'hurdle'}, {'id': 8501, 'synset': 'hurricane_deck.n.01', 'name': 'hurricane_deck'}, {'id': 8502, 'synset': 'hurricane_lamp.n.01', 'name': 'hurricane_lamp'}, {'id': 8503, 'synset': 'hut.n.01', 'name': 'hut'}, {'id': 8504, 'synset': 'hutch.n.01', 'name': 'hutch'}, {'id': 8505, 'synset': 'hutment.n.01', 'name': 'hutment'}, {'id': 8506, 'synset': 'hydraulic_brake.n.01', 'name': 'hydraulic_brake'}, {'id': 8507, 'synset': 'hydraulic_press.n.01', 'name': 'hydraulic_press'}, {'id': 8508, 'synset': 'hydraulic_pump.n.01', 'name': 'hydraulic_pump'}, {'id': 8509, 'synset': 'hydraulic_system.n.01', 'name': 'hydraulic_system'}, {'id': 8510, 'synset': 'hydraulic_transmission.n.01', 'name': 'hydraulic_transmission'}, {'id': 8511, 'synset': 'hydroelectric_turbine.n.01', 'name': 'hydroelectric_turbine'}, {'id': 8512, 'synset': 'hydrofoil.n.02', 'name': 'hydrofoil'}, {'id': 8513, 'synset': 'hydrofoil.n.01', 'name': 'hydrofoil'}, {'id': 8514, 'synset': 'hydrogen_bomb.n.01', 'name': 'hydrogen_bomb'}, {'id': 8515, 'synset': 'hydrometer.n.01', 'name': 'hydrometer'}, {'id': 8516, 'synset': 'hygrodeik.n.01', 'name': 'hygrodeik'}, {'id': 8517, 'synset': 'hygrometer.n.01', 'name': 'hygrometer'}, {'id': 8518, 'synset': 'hygroscope.n.01', 'name': 'hygroscope'}, {'id': 8519, 'synset': 'hyperbaric_chamber.n.01', 'name': 'hyperbaric_chamber'}, {'id': 8520, 'synset': 'hypercoaster.n.01', 'name': 'hypercoaster'}, {'id': 8521, 'synset': 'hypermarket.n.01', 'name': 'hypermarket'}, {'id': 8522, 'synset': 'hypodermic_needle.n.01', 'name': 'hypodermic_needle'}, {'id': 8523, 'synset': 'hypodermic_syringe.n.01', 'name': 'hypodermic_syringe'}, {'id': 8524, 'synset': 'hypsometer.n.01', 'name': 'hypsometer'}, {'id': 8525, 'synset': 'hysterosalpingogram.n.01', 'name': 'hysterosalpingogram'}, {'id': 8526, 'synset': 'i-beam.n.01', 'name': 'I-beam'}, {'id': 8527, 'synset': 'ice_ax.n.01', 'name': 'ice_ax'}, {'id': 8528, 'synset': 'iceboat.n.02', 'name': 'iceboat'}, {'id': 8529, 'synset': 'icebreaker.n.01', 'name': 'icebreaker'}, {'id': 8530, 'synset': 'iced-tea_spoon.n.01', 'name': 'iced-tea_spoon'}, {'id': 8531, 'synset': 'ice_hockey_rink.n.01', 'name': 'ice_hockey_rink'}, {'id': 8532, 'synset': 'ice_machine.n.01', 'name': 'ice_machine'}, {'id': 8533, 'synset': 'icepick.n.01', 'name': 'icepick'}, {'id': 8534, 'synset': 'ice_rink.n.01', 'name': 'ice_rink'}, {'id': 8535, 'synset': 'ice_tongs.n.01', 'name': 'ice_tongs'}, {'id': 8536, 'synset': 'icetray.n.01', 'name': 'icetray'}, {'id': 8537, 'synset': 'iconoscope.n.01', 'name': 'iconoscope'}, {'id': 8538, 'synset': 'identikit.n.01', 'name': 'Identikit'}, {'id': 8539, 'synset': 'idle_pulley.n.01', 'name': 'idle_pulley'}, {'id': 8540, 'synset': 'igloo.n.01', 'name': 'igloo'}, {'id': 8541, 'synset': 'ignition_coil.n.01', 'name': 'ignition_coil'}, {'id': 8542, 'synset': 'ignition_key.n.01', 'name': 'ignition_key'}, {'id': 8543, 'synset': 'ignition_switch.n.01', 'name': 'ignition_switch'}, {'id': 8544, 'synset': 'imaret.n.01', 'name': 'imaret'}, {'id': 8545, 'synset': 'immovable_bandage.n.01', 'name': 'immovable_bandage'}, {'id': 8546, 'synset': 'impact_printer.n.01', 'name': 'impact_printer'}, {'id': 8547, 'synset': 'impeller.n.01', 'name': 'impeller'}, {'id': 8548, 'synset': 'implant.n.01', 'name': 'implant'}, {'id': 8549, 'synset': 'implement.n.01', 'name': 'implement'}, {'id': 8550, 'synset': 'impression.n.07', 'name': 'impression'}, {'id': 8551, 'synset': 'imprint.n.05', 'name': 'imprint'}, {'id': 8552, 'synset': 'improvised_explosive_device.n.01', 'name': 'improvised_explosive_device'}, {'id': 8553, 'synset': 'impulse_turbine.n.01', 'name': 'impulse_turbine'}, {'id': 8554, 'synset': 'in-basket.n.01', 'name': 'in-basket'}, {'id': 8555, 'synset': 'incendiary_bomb.n.01', 'name': 'incendiary_bomb'}, {'id': 8556, 'synset': 'incinerator.n.01', 'name': 'incinerator'}, {'id': 8557, 'synset': 'inclined_plane.n.01', 'name': 'inclined_plane'}, {'id': 8558, 'synset': 'inclinometer.n.02', 'name': 'inclinometer'}, {'id': 8559, 'synset': 'inclinometer.n.01', 'name': 'inclinometer'}, {'id': 8560, 'synset': 'incrustation.n.03', 'name': 'incrustation'}, {'id': 8561, 'synset': 'incubator.n.01', 'name': 'incubator'}, {'id': 8562, 'synset': 'index_register.n.01', 'name': 'index_register'}, {'id': 8563, 'synset': 'indiaman.n.01', 'name': 'Indiaman'}, {'id': 8564, 'synset': 'indian_club.n.01', 'name': 'Indian_club'}, {'id': 8565, 'synset': 'indicator.n.03', 'name': 'indicator'}, {'id': 8566, 'synset': 'induction_coil.n.01', 'name': 'induction_coil'}, {'id': 8567, 'synset': 'inductor.n.01', 'name': 'inductor'}, {'id': 8568, 'synset': 'industrial_watercourse.n.01', 'name': 'industrial_watercourse'}, {'id': 8569, 'synset': 'inertial_guidance_system.n.01', 'name': 'inertial_guidance_system'}, {'id': 8570, 'synset': 'inflater.n.01', 'name': 'inflater'}, {'id': 8571, 'synset': 'injector.n.01', 'name': 'injector'}, {'id': 8572, 'synset': 'ink_bottle.n.01', 'name': 'ink_bottle'}, {'id': 8573, 'synset': 'ink_eraser.n.01', 'name': 'ink_eraser'}, {'id': 8574, 'synset': 'ink-jet_printer.n.01', 'name': 'ink-jet_printer'}, {'id': 8575, 'synset': 'inkle.n.01', 'name': 'inkle'}, {'id': 8576, 'synset': 'inkstand.n.02', 'name': 'inkstand'}, {'id': 8577, 'synset': 'inkwell.n.01', 'name': 'inkwell'}, {'id': 8578, 'synset': 'inlay.n.01', 'name': 'inlay'}, {'id': 8579, 'synset': 'inside_caliper.n.01', 'name': 'inside_caliper'}, {'id': 8580, 'synset': 'insole.n.01', 'name': 'insole'}, {'id': 8581, 'synset': 'instep.n.02', 'name': 'instep'}, {'id': 8582, 'synset': 'instillator.n.01', 'name': 'instillator'}, {'id': 8583, 'synset': 'institution.n.02', 'name': 'institution'}, {'id': 8584, 'synset': 'instrument.n.01', 'name': 'instrument'}, {'id': 8585, 'synset': 'instrument_of_punishment.n.01', 'name': 'instrument_of_punishment'}, {'id': 8586, 'synset': 'instrument_of_torture.n.01', 'name': 'instrument_of_torture'}, {'id': 8587, 'synset': 'intaglio.n.02', 'name': 'intaglio'}, {'id': 8588, 'synset': 'intake_valve.n.01', 'name': 'intake_valve'}, {'id': 8589, 'synset': 'integrated_circuit.n.01', 'name': 'integrated_circuit'}, {'id': 8590, 'synset': 'integrator.n.01', 'name': 'integrator'}, {'id': 8591, 'synset': 'intelnet.n.01', 'name': 'Intelnet'}, {'id': 8592, 'synset': 'interceptor.n.01', 'name': 'interceptor'}, {'id': 8593, 'synset': 'interchange.n.01', 'name': 'interchange'}, {'id': 8594, 'synset': 'intercommunication_system.n.01', 'name': 'intercommunication_system'}, {'id': 8595, 'synset': 'intercontinental_ballistic_missile.n.01', 'name': 'intercontinental_ballistic_missile'}, {'id': 8596, 'synset': 'interface.n.04', 'name': 'interface'}, {'id': 8597, 'synset': 'interferometer.n.01', 'name': 'interferometer'}, {'id': 8598, 'synset': 'interior_door.n.01', 'name': 'interior_door'}, {'id': 8599, 'synset': 'internal-combustion_engine.n.01', 'name': 'internal-combustion_engine'}, {'id': 8600, 'synset': 'internal_drive.n.01', 'name': 'internal_drive'}, {'id': 8601, 'synset': 'internet.n.01', 'name': 'internet'}, {'id': 8602, 'synset': 'interphone.n.01', 'name': 'interphone'}, {'id': 8603, 'synset': 'interrupter.n.01', 'name': 'interrupter'}, {'id': 8604, 'synset': 'intersection.n.02', 'name': 'intersection'}, {'id': 8605, 'synset': 'interstice.n.02', 'name': 'interstice'}, {'id': 8606, 'synset': 'intraocular_lens.n.01', 'name': 'intraocular_lens'}, {'id': 8607, 'synset': 'intravenous_pyelogram.n.01', 'name': 'intravenous_pyelogram'}, {'id': 8608, 'synset': 'inverter.n.01', 'name': 'inverter'}, {'id': 8609, 'synset': 'ion_engine.n.01', 'name': 'ion_engine'}, {'id': 8610, 'synset': 'ionization_chamber.n.01', 'name': 'ionization_chamber'}, {'id': 8611, 'synset': 'video_ipod.n.01', 'name': 'video_iPod'}, {'id': 8612, 'synset': 'iron.n.02', 'name': 'iron'}, {'id': 8613, 'synset': 'iron.n.03', 'name': 'iron'}, {'id': 8614, 'synset': 'irons.n.01', 'name': 'irons'}, {'id': 8615, 'synset': 'ironclad.n.01', 'name': 'ironclad'}, {'id': 8616, 'synset': 'iron_foundry.n.01', 'name': 'iron_foundry'}, {'id': 8617, 'synset': 'iron_horse.n.01', 'name': 'iron_horse'}, {'id': 8618, 'synset': 'ironing.n.01', 'name': 'ironing'}, {'id': 8619, 'synset': 'iron_lung.n.01', 'name': 'iron_lung'}, {'id': 8620, 'synset': 'ironmongery.n.01', 'name': 'ironmongery'}, {'id': 8621, 'synset': 'ironworks.n.01', 'name': 'ironworks'}, {'id': 8622, 'synset': 'irrigation_ditch.n.01', 'name': 'irrigation_ditch'}, {'id': 8623, 'synset': 'izar.n.01', 'name': 'izar'}, {'id': 8624, 'synset': 'jabot.n.01', 'name': 'jabot'}, {'id': 8625, 'synset': 'jack.n.10', 'name': 'jack'}, {'id': 8626, 'synset': 'jack.n.07', 'name': 'jack'}, {'id': 8627, 'synset': 'jack.n.06', 'name': 'jack'}, {'id': 8628, 'synset': 'jack.n.05', 'name': 'jack'}, {'id': 8629, 'synset': 'jacket.n.02', 'name': 'jacket'}, {'id': 8630, 'synset': 'jacket.n.05', 'name': 'jacket'}, {'id': 8631, 'synset': 'jack-in-the-box.n.01', 'name': 'jack-in-the-box'}, {'id': 8632, 'synset': "jack-o'-lantern.n.02", 'name': "jack-o'-lantern"}, {'id': 8633, 'synset': 'jack_plane.n.01', 'name': 'jack_plane'}, {'id': 8634, 'synset': "jacob's_ladder.n.02", 'name': "Jacob's_ladder"}, {'id': 8635, 'synset': 'jaconet.n.01', 'name': 'jaconet'}, {'id': 8636, 'synset': 'jacquard_loom.n.01', 'name': 'Jacquard_loom'}, {'id': 8637, 'synset': 'jacquard.n.02', 'name': 'jacquard'}, {'id': 8638, 'synset': 'jag.n.03', 'name': 'jag'}, {'id': 8639, 'synset': 'jail.n.01', 'name': 'jail'}, {'id': 8640, 'synset': 'jalousie.n.02', 'name': 'jalousie'}, {'id': 8641, 'synset': 'jamb.n.01', 'name': 'jamb'}, {'id': 8642, 'synset': 'jammer.n.01', 'name': 'jammer'}, {'id': 8643, 'synset': 'jampot.n.01', 'name': 'jampot'}, {'id': 8644, 'synset': 'japan.n.04', 'name': 'japan'}, {'id': 8645, 'synset': 'jarvik_heart.n.01', 'name': 'Jarvik_heart'}, {'id': 8646, 'synset': 'jaunting_car.n.01', 'name': 'jaunting_car'}, {'id': 8647, 'synset': 'javelin.n.02', 'name': 'javelin'}, {'id': 8648, 'synset': 'jaw.n.03', 'name': 'jaw'}, {'id': 8649, 'synset': 'jaws_of_life.n.01', 'name': 'Jaws_of_Life'}, {'id': 8650, 'synset': 'jellaba.n.01', 'name': 'jellaba'}, {'id': 8651, 'synset': 'jerkin.n.01', 'name': 'jerkin'}, {'id': 8652, 'synset': 'jeroboam.n.02', 'name': 'jeroboam'}, {'id': 8653, 'synset': 'jersey.n.04', 'name': 'jersey'}, {'id': 8654, 'synset': 'jet_bridge.n.01', 'name': 'jet_bridge'}, {'id': 8655, 'synset': 'jet_engine.n.01', 'name': 'jet_engine'}, {'id': 8656, 'synset': 'jetliner.n.01', 'name': 'jetliner'}, {'id': 8657, 'synset': "jeweler's_glass.n.01", 'name': "jeweler's_glass"}, {'id': 8658, 'synset': 'jewelled_headdress.n.01', 'name': 'jewelled_headdress'}, {'id': 8659, 'synset': "jew's_harp.n.01", 'name': "jew's_harp"}, {'id': 8660, 'synset': 'jib.n.01', 'name': 'jib'}, {'id': 8661, 'synset': 'jibboom.n.01', 'name': 'jibboom'}, {'id': 8662, 'synset': 'jig.n.03', 'name': 'jig'}, {'id': 8663, 'synset': 'jig.n.02', 'name': 'jig'}, {'id': 8664, 'synset': 'jiggermast.n.01', 'name': 'jiggermast'}, {'id': 8665, 'synset': 'jigsaw.n.02', 'name': 'jigsaw'}, {'id': 8666, 'synset': 'jigsaw_puzzle.n.01', 'name': 'jigsaw_puzzle'}, {'id': 8667, 'synset': 'jinrikisha.n.01', 'name': 'jinrikisha'}, {'id': 8668, 'synset': 'jobcentre.n.01', 'name': 'jobcentre'}, {'id': 8669, 'synset': 'jodhpurs.n.01', 'name': 'jodhpurs'}, {'id': 8670, 'synset': 'jodhpur.n.01', 'name': 'jodhpur'}, {'id': 8671, 'synset': 'joinery.n.01', 'name': 'joinery'}, {'id': 8672, 'synset': 'joint.n.05', 'name': 'joint'}, {'id': 8673, 'synset': 'joint_direct_attack_munition.n.01', 'name': 'Joint_Direct_Attack_Munition'}, {'id': 8674, 'synset': 'jointer.n.01', 'name': 'jointer'}, {'id': 8675, 'synset': 'joist.n.01', 'name': 'joist'}, {'id': 8676, 'synset': 'jolly_boat.n.01', 'name': 'jolly_boat'}, {'id': 8677, 'synset': 'jorum.n.01', 'name': 'jorum'}, {'id': 8678, 'synset': 'joss_house.n.01', 'name': 'joss_house'}, {'id': 8679, 'synset': 'journal_bearing.n.01', 'name': 'journal_bearing'}, {'id': 8680, 'synset': 'journal_box.n.01', 'name': 'journal_box'}, {'id': 8681, 'synset': 'jungle_gym.n.01', 'name': 'jungle_gym'}, {'id': 8682, 'synset': 'junk.n.02', 'name': 'junk'}, {'id': 8683, 'synset': 'jug.n.01', 'name': 'jug'}, {'id': 8684, 'synset': 'jukebox.n.01', 'name': 'jukebox'}, {'id': 8685, 'synset': 'jumbojet.n.01', 'name': 'jumbojet'}, {'id': 8686, 'synset': 'jumper.n.07', 'name': 'jumper'}, {'id': 8687, 'synset': 'jumper.n.06', 'name': 'jumper'}, {'id': 8688, 'synset': 'jumper.n.05', 'name': 'jumper'}, {'id': 8689, 'synset': 'jumper.n.04', 'name': 'jumper'}, {'id': 8690, 'synset': 'jumper_cable.n.01', 'name': 'jumper_cable'}, {'id': 8691, 'synset': 'jump_seat.n.01', 'name': 'jump_seat'}, {'id': 8692, 'synset': 'jump_suit.n.02', 'name': 'jump_suit'}, {'id': 8693, 'synset': 'junction.n.01', 'name': 'junction'}, {'id': 8694, 'synset': 'junction.n.04', 'name': 'junction'}, {'id': 8695, 'synset': 'junction_barrier.n.01', 'name': 'junction_barrier'}, {'id': 8696, 'synset': 'junk_shop.n.01', 'name': 'junk_shop'}, {'id': 8697, 'synset': 'jury_box.n.01', 'name': 'jury_box'}, {'id': 8698, 'synset': 'jury_mast.n.01', 'name': 'jury_mast'}, {'id': 8699, 'synset': 'kachina.n.03', 'name': 'kachina'}, {'id': 8700, 'synset': 'kaffiyeh.n.01', 'name': 'kaffiyeh'}, {'id': 8701, 'synset': 'kalansuwa.n.01', 'name': 'kalansuwa'}, {'id': 8702, 'synset': 'kalashnikov.n.01', 'name': 'Kalashnikov'}, {'id': 8703, 'synset': 'kameez.n.01', 'name': 'kameez'}, {'id': 8704, 'synset': 'kanzu.n.01', 'name': 'kanzu'}, {'id': 8705, 'synset': 'katharometer.n.01', 'name': 'katharometer'}, {'id': 8706, 'synset': 'kazoo.n.01', 'name': 'kazoo'}, {'id': 8707, 'synset': 'keel.n.03', 'name': 'keel'}, {'id': 8708, 'synset': 'keelboat.n.01', 'name': 'keelboat'}, {'id': 8709, 'synset': 'keelson.n.01', 'name': 'keelson'}, {'id': 8710, 'synset': 'keep.n.02', 'name': 'keep'}, {'id': 8711, 'synset': 'kepi.n.01', 'name': 'kepi'}, {'id': 8712, 'synset': 'keratoscope.n.01', 'name': 'keratoscope'}, {'id': 8713, 'synset': 'kerchief.n.01', 'name': 'kerchief'}, {'id': 8714, 'synset': 'ketch.n.01', 'name': 'ketch'}, {'id': 8715, 'synset': 'kettle.n.04', 'name': 'kettle'}, {'id': 8716, 'synset': 'key.n.15', 'name': 'key'}, {'id': 8717, 'synset': 'keyboard.n.01', 'name': 'keyboard'}, {'id': 8718, 'synset': 'keyboard_buffer.n.01', 'name': 'keyboard_buffer'}, {'id': 8719, 'synset': 'keyboard_instrument.n.01', 'name': 'keyboard_instrument'}, {'id': 8720, 'synset': 'keyhole.n.01', 'name': 'keyhole'}, {'id': 8721, 'synset': 'keyhole_saw.n.01', 'name': 'keyhole_saw'}, {'id': 8722, 'synset': 'khadi.n.01', 'name': 'khadi'}, {'id': 8723, 'synset': 'khaki.n.01', 'name': 'khaki'}, {'id': 8724, 'synset': 'khakis.n.01', 'name': 'khakis'}, {'id': 8725, 'synset': 'khimar.n.01', 'name': 'khimar'}, {'id': 8726, 'synset': 'khukuri.n.01', 'name': 'khukuri'}, {'id': 8727, 'synset': 'kick_pleat.n.01', 'name': 'kick_pleat'}, {'id': 8728, 'synset': 'kicksorter.n.01', 'name': 'kicksorter'}, {'id': 8729, 'synset': 'kickstand.n.01', 'name': 'kickstand'}, {'id': 8730, 'synset': 'kick_starter.n.01', 'name': 'kick_starter'}, {'id': 8731, 'synset': 'kid_glove.n.01', 'name': 'kid_glove'}, {'id': 8732, 'synset': 'kiln.n.01', 'name': 'kiln'}, {'id': 8733, 'synset': 'kinescope.n.01', 'name': 'kinescope'}, {'id': 8734, 'synset': 'kinetoscope.n.01', 'name': 'Kinetoscope'}, {'id': 8735, 'synset': 'king.n.10', 'name': 'king'}, {'id': 8736, 'synset': 'king.n.08', 'name': 'king'}, {'id': 8737, 'synset': 'kingbolt.n.01', 'name': 'kingbolt'}, {'id': 8738, 'synset': 'king_post.n.01', 'name': 'king_post'}, {'id': 8739, 'synset': "kipp's_apparatus.n.01", 'name': "Kipp's_apparatus"}, {'id': 8740, 'synset': 'kirk.n.01', 'name': 'kirk'}, {'id': 8741, 'synset': 'kirpan.n.01', 'name': 'kirpan'}, {'id': 8742, 'synset': 'kirtle.n.02', 'name': 'kirtle'}, {'id': 8743, 'synset': 'kirtle.n.01', 'name': 'kirtle'}, {'id': 8744, 'synset': 'kit.n.02', 'name': 'kit'}, {'id': 8745, 'synset': 'kit.n.01', 'name': 'kit'}, {'id': 8746, 'synset': 'kitbag.n.01', 'name': 'kitbag'}, {'id': 8747, 'synset': 'kitchen.n.01', 'name': 'kitchen'}, {'id': 8748, 'synset': 'kitchen_appliance.n.01', 'name': 'kitchen_appliance'}, {'id': 8749, 'synset': 'kitchenette.n.01', 'name': 'kitchenette'}, {'id': 8750, 'synset': 'kitchen_utensil.n.01', 'name': 'kitchen_utensil'}, {'id': 8751, 'synset': 'kitchenware.n.01', 'name': 'kitchenware'}, {'id': 8752, 'synset': 'kite_balloon.n.01', 'name': 'kite_balloon'}, {'id': 8753, 'synset': 'klaxon.n.01', 'name': 'klaxon'}, {'id': 8754, 'synset': 'klieg_light.n.01', 'name': 'klieg_light'}, {'id': 8755, 'synset': 'klystron.n.01', 'name': 'klystron'}, {'id': 8756, 'synset': 'knee_brace.n.01', 'name': 'knee_brace'}, {'id': 8757, 'synset': 'knee-high.n.01', 'name': 'knee-high'}, {'id': 8758, 'synset': 'knee_piece.n.01', 'name': 'knee_piece'}, {'id': 8759, 'synset': 'knife.n.02', 'name': 'knife'}, {'id': 8760, 'synset': 'knife_blade.n.01', 'name': 'knife_blade'}, {'id': 8761, 'synset': 'knight.n.02', 'name': 'knight'}, {'id': 8762, 'synset': 'knit.n.01', 'name': 'knit'}, {'id': 8763, 'synset': 'knitting_machine.n.01', 'name': 'knitting_machine'}, {'id': 8764, 'synset': 'knitwear.n.01', 'name': 'knitwear'}, {'id': 8765, 'synset': 'knob.n.01', 'name': 'knob'}, {'id': 8766, 'synset': 'knob.n.04', 'name': 'knob'}, {'id': 8767, 'synset': 'knobble.n.01', 'name': 'knobble'}, {'id': 8768, 'synset': 'knobkerrie.n.01', 'name': 'knobkerrie'}, {'id': 8769, 'synset': 'knot.n.02', 'name': 'knot'}, {'id': 8770, 'synset': 'knuckle_joint.n.02', 'name': 'knuckle_joint'}, {'id': 8771, 'synset': 'kohl.n.01', 'name': 'kohl'}, {'id': 8772, 'synset': 'koto.n.01', 'name': 'koto'}, {'id': 8773, 'synset': 'kraal.n.02', 'name': 'kraal'}, {'id': 8774, 'synset': 'kremlin.n.02', 'name': 'kremlin'}, {'id': 8775, 'synset': 'kris.n.01', 'name': 'kris'}, {'id': 8776, 'synset': 'krummhorn.n.01', 'name': 'krummhorn'}, {'id': 8777, 'synset': "kundt's_tube.n.01", 'name': "Kundt's_tube"}, {'id': 8778, 'synset': 'kurdistan.n.02', 'name': 'Kurdistan'}, {'id': 8779, 'synset': 'kurta.n.01', 'name': 'kurta'}, {'id': 8780, 'synset': 'kylix.n.01', 'name': 'kylix'}, {'id': 8781, 'synset': 'kymograph.n.01', 'name': 'kymograph'}, {'id': 8782, 'synset': 'lab_bench.n.01', 'name': 'lab_bench'}, {'id': 8783, 'synset': 'lace.n.02', 'name': 'lace'}, {'id': 8784, 'synset': 'lacquer.n.02', 'name': 'lacquer'}, {'id': 8785, 'synset': 'lacquerware.n.01', 'name': 'lacquerware'}, {'id': 8786, 'synset': 'lacrosse_ball.n.01', 'name': 'lacrosse_ball'}, {'id': 8787, 'synset': 'ladder-back.n.02', 'name': 'ladder-back'}, {'id': 8788, 'synset': 'ladder-back.n.01', 'name': 'ladder-back'}, {'id': 8789, 'synset': 'ladder_truck.n.01', 'name': 'ladder_truck'}, {'id': 8790, 'synset': "ladies'_room.n.01", 'name': "ladies'_room"}, {'id': 8791, 'synset': 'lady_chapel.n.01', 'name': 'lady_chapel'}, {'id': 8792, 'synset': 'lagerphone.n.01', 'name': 'lagerphone'}, {'id': 8793, 'synset': 'lag_screw.n.01', 'name': 'lag_screw'}, {'id': 8794, 'synset': 'lake_dwelling.n.01', 'name': 'lake_dwelling'}, {'id': 8795, 'synset': 'lally.n.01', 'name': 'lally'}, {'id': 8796, 'synset': 'lamasery.n.01', 'name': 'lamasery'}, {'id': 8797, 'synset': 'lambrequin.n.02', 'name': 'lambrequin'}, {'id': 8798, 'synset': 'lame.n.02', 'name': 'lame'}, {'id': 8799, 'synset': 'laminar_flow_clean_room.n.01', 'name': 'laminar_flow_clean_room'}, {'id': 8800, 'synset': 'laminate.n.01', 'name': 'laminate'}, {'id': 8801, 'synset': 'lamination.n.01', 'name': 'lamination'}, {'id': 8802, 'synset': 'lamp.n.01', 'name': 'lamp'}, {'id': 8803, 'synset': 'lamp_house.n.01', 'name': 'lamp_house'}, {'id': 8804, 'synset': 'lanai.n.02', 'name': 'lanai'}, {'id': 8805, 'synset': 'lancet_arch.n.01', 'name': 'lancet_arch'}, {'id': 8806, 'synset': 'lancet_window.n.01', 'name': 'lancet_window'}, {'id': 8807, 'synset': 'landau.n.02', 'name': 'landau'}, {'id': 8808, 'synset': 'lander.n.02', 'name': 'lander'}, {'id': 8809, 'synset': 'landing_craft.n.01', 'name': 'landing_craft'}, {'id': 8810, 'synset': 'landing_flap.n.01', 'name': 'landing_flap'}, {'id': 8811, 'synset': 'landing_gear.n.01', 'name': 'landing_gear'}, {'id': 8812, 'synset': 'landing_net.n.01', 'name': 'landing_net'}, {'id': 8813, 'synset': 'landing_skid.n.01', 'name': 'landing_skid'}, {'id': 8814, 'synset': 'land_line.n.01', 'name': 'land_line'}, {'id': 8815, 'synset': 'land_mine.n.01', 'name': 'land_mine'}, {'id': 8816, 'synset': 'land_office.n.01', 'name': 'land_office'}, {'id': 8817, 'synset': 'lanolin.n.02', 'name': 'lanolin'}, {'id': 8818, 'synset': 'lanyard.n.01', 'name': 'lanyard'}, {'id': 8819, 'synset': 'lap.n.03', 'name': 'lap'}, {'id': 8820, 'synset': 'laparoscope.n.01', 'name': 'laparoscope'}, {'id': 8821, 'synset': 'lapboard.n.01', 'name': 'lapboard'}, {'id': 8822, 'synset': 'lapel.n.01', 'name': 'lapel'}, {'id': 8823, 'synset': 'lap_joint.n.01', 'name': 'lap_joint'}, {'id': 8824, 'synset': 'laryngoscope.n.01', 'name': 'laryngoscope'}, {'id': 8825, 'synset': 'laser.n.01', 'name': 'laser'}, {'id': 8826, 'synset': 'laser-guided_bomb.n.01', 'name': 'laser-guided_bomb'}, {'id': 8827, 'synset': 'laser_printer.n.01', 'name': 'laser_printer'}, {'id': 8828, 'synset': 'lash.n.02', 'name': 'lash'}, {'id': 8829, 'synset': 'lashing.n.02', 'name': 'lashing'}, {'id': 8830, 'synset': 'lasso.n.02', 'name': 'lasso'}, {'id': 8831, 'synset': 'latch.n.01', 'name': 'latch'}, {'id': 8832, 'synset': 'latchet.n.01', 'name': 'latchet'}, {'id': 8833, 'synset': 'latchkey.n.01', 'name': 'latchkey'}, {'id': 8834, 'synset': 'lateen.n.01', 'name': 'lateen'}, {'id': 8835, 'synset': 'latex_paint.n.01', 'name': 'latex_paint'}, {'id': 8836, 'synset': 'lath.n.01', 'name': 'lath'}, {'id': 8837, 'synset': 'lathe.n.01', 'name': 'lathe'}, {'id': 8838, 'synset': 'latrine.n.01', 'name': 'latrine'}, {'id': 8839, 'synset': 'lattice.n.03', 'name': 'lattice'}, {'id': 8840, 'synset': 'launch.n.01', 'name': 'launch'}, {'id': 8841, 'synset': 'launcher.n.01', 'name': 'launcher'}, {'id': 8842, 'synset': 'laundry.n.01', 'name': 'laundry'}, {'id': 8843, 'synset': 'laundry_cart.n.01', 'name': 'laundry_cart'}, {'id': 8844, 'synset': 'laundry_truck.n.01', 'name': 'laundry_truck'}, {'id': 8845, 'synset': 'lavalava.n.01', 'name': 'lavalava'}, {'id': 8846, 'synset': 'lavaliere.n.01', 'name': 'lavaliere'}, {'id': 8847, 'synset': 'laver.n.02', 'name': 'laver'}, {'id': 8848, 'synset': 'lawn_chair.n.01', 'name': 'lawn_chair'}, {'id': 8849, 'synset': 'lawn_furniture.n.01', 'name': 'lawn_furniture'}, {'id': 8850, 'synset': 'layette.n.01', 'name': 'layette'}, {'id': 8851, 'synset': 'lead-acid_battery.n.01', 'name': 'lead-acid_battery'}, {'id': 8852, 'synset': 'lead-in.n.02', 'name': 'lead-in'}, {'id': 8853, 'synset': 'leading_rein.n.01', 'name': 'leading_rein'}, {'id': 8854, 'synset': 'lead_pencil.n.01', 'name': 'lead_pencil'}, {'id': 8855, 'synset': 'leaf_spring.n.01', 'name': 'leaf_spring'}, {'id': 8856, 'synset': 'lean-to.n.01', 'name': 'lean-to'}, {'id': 8857, 'synset': 'lean-to_tent.n.01', 'name': 'lean-to_tent'}, {'id': 8858, 'synset': 'leash.n.01', 'name': 'leash'}, {'id': 8859, 'synset': 'leatherette.n.01', 'name': 'leatherette'}, {'id': 8860, 'synset': 'leather_strip.n.01', 'name': 'leather_strip'}, {'id': 8861, 'synset': 'leclanche_cell.n.01', 'name': 'Leclanche_cell'}, {'id': 8862, 'synset': 'lectern.n.01', 'name': 'lectern'}, {'id': 8863, 'synset': 'lecture_room.n.01', 'name': 'lecture_room'}, {'id': 8864, 'synset': 'lederhosen.n.01', 'name': 'lederhosen'}, {'id': 8865, 'synset': 'ledger_board.n.01', 'name': 'ledger_board'}, {'id': 8866, 'synset': 'leg.n.07', 'name': 'leg'}, {'id': 8867, 'synset': 'leg.n.03', 'name': 'leg'}, {'id': 8868, 'synset': 'leiden_jar.n.01', 'name': 'Leiden_jar'}, {'id': 8869, 'synset': 'leisure_wear.n.01', 'name': 'leisure_wear'}, {'id': 8870, 'synset': 'lens.n.01', 'name': 'lens'}, {'id': 8871, 'synset': 'lens.n.05', 'name': 'lens'}, {'id': 8872, 'synset': 'lens_cap.n.01', 'name': 'lens_cap'}, {'id': 8873, 'synset': 'lens_implant.n.01', 'name': 'lens_implant'}, {'id': 8874, 'synset': 'leotard.n.01', 'name': 'leotard'}, {'id': 8875, 'synset': 'letter_case.n.01', 'name': 'letter_case'}, {'id': 8876, 'synset': 'letter_opener.n.01', 'name': 'letter_opener'}, {'id': 8877, 'synset': 'levee.n.03', 'name': 'levee'}, {'id': 8878, 'synset': 'level.n.05', 'name': 'level'}, {'id': 8879, 'synset': 'lever.n.01', 'name': 'lever'}, {'id': 8880, 'synset': 'lever.n.03', 'name': 'lever'}, {'id': 8881, 'synset': 'lever.n.02', 'name': 'lever'}, {'id': 8882, 'synset': 'lever_lock.n.01', 'name': 'lever_lock'}, {'id': 8883, 'synset': "levi's.n.01", 'name': "Levi's"}, {'id': 8884, 'synset': 'liberty_ship.n.01', 'name': 'Liberty_ship'}, {'id': 8885, 'synset': 'library.n.01', 'name': 'library'}, {'id': 8886, 'synset': 'library.n.05', 'name': 'library'}, {'id': 8887, 'synset': 'lid.n.02', 'name': 'lid'}, {'id': 8888, 'synset': 'liebig_condenser.n.01', 'name': 'Liebig_condenser'}, {'id': 8889, 'synset': 'lie_detector.n.01', 'name': 'lie_detector'}, {'id': 8890, 'synset': 'lifeboat.n.01', 'name': 'lifeboat'}, {'id': 8891, 'synset': 'life_office.n.01', 'name': 'life_office'}, {'id': 8892, 'synset': 'life_preserver.n.01', 'name': 'life_preserver'}, {'id': 8893, 'synset': 'life-support_system.n.02', 'name': 'life-support_system'}, {'id': 8894, 'synset': 'life-support_system.n.01', 'name': 'life-support_system'}, {'id': 8895, 'synset': 'lifting_device.n.01', 'name': 'lifting_device'}, {'id': 8896, 'synset': 'lift_pump.n.01', 'name': 'lift_pump'}, {'id': 8897, 'synset': 'ligament.n.02', 'name': 'ligament'}, {'id': 8898, 'synset': 'ligature.n.03', 'name': 'ligature'}, {'id': 8899, 'synset': 'light.n.02', 'name': 'light'}, {'id': 8900, 'synset': 'light_arm.n.01', 'name': 'light_arm'}, {'id': 8901, 'synset': 'light_circuit.n.01', 'name': 'light_circuit'}, {'id': 8902, 'synset': 'light-emitting_diode.n.01', 'name': 'light-emitting_diode'}, {'id': 8903, 'synset': 'lighter.n.02', 'name': 'lighter'}, {'id': 8904, 'synset': 'lighter-than-air_craft.n.01', 'name': 'lighter-than-air_craft'}, {'id': 8905, 'synset': 'light_filter.n.01', 'name': 'light_filter'}, {'id': 8906, 'synset': 'lighting.n.02', 'name': 'lighting'}, {'id': 8907, 'synset': 'light_machine_gun.n.01', 'name': 'light_machine_gun'}, {'id': 8908, 'synset': 'light_meter.n.01', 'name': 'light_meter'}, {'id': 8909, 'synset': 'light_microscope.n.01', 'name': 'light_microscope'}, {'id': 8910, 'synset': 'light_pen.n.01', 'name': 'light_pen'}, {'id': 8911, 'synset': 'lightship.n.01', 'name': 'lightship'}, {'id': 8912, 'synset': 'lilo.n.01', 'name': 'Lilo'}, {'id': 8913, 'synset': 'limber.n.01', 'name': 'limber'}, {'id': 8914, 'synset': 'limekiln.n.01', 'name': 'limekiln'}, {'id': 8915, 'synset': 'limiter.n.01', 'name': 'limiter'}, {'id': 8916, 'synset': 'linear_accelerator.n.01', 'name': 'linear_accelerator'}, {'id': 8917, 'synset': 'linen.n.01', 'name': 'linen'}, {'id': 8918, 'synset': 'line_printer.n.01', 'name': 'line_printer'}, {'id': 8919, 'synset': 'liner.n.04', 'name': 'liner'}, {'id': 8920, 'synset': 'liner.n.03', 'name': 'liner'}, {'id': 8921, 'synset': 'lingerie.n.01', 'name': 'lingerie'}, {'id': 8922, 'synset': 'lining.n.01', 'name': 'lining'}, {'id': 8923, 'synset': 'link.n.09', 'name': 'link'}, {'id': 8924, 'synset': 'linkage.n.03', 'name': 'linkage'}, {'id': 8925, 'synset': 'link_trainer.n.01', 'name': 'Link_trainer'}, {'id': 8926, 'synset': 'linocut.n.02', 'name': 'linocut'}, {'id': 8927, 'synset': 'linoleum_knife.n.01', 'name': 'linoleum_knife'}, {'id': 8928, 'synset': 'linotype.n.01', 'name': 'Linotype'}, {'id': 8929, 'synset': 'linsey-woolsey.n.01', 'name': 'linsey-woolsey'}, {'id': 8930, 'synset': 'linstock.n.01', 'name': 'linstock'}, {'id': 8931, 'synset': 'lion-jaw_forceps.n.01', 'name': 'lion-jaw_forceps'}, {'id': 8932, 'synset': 'lip-gloss.n.01', 'name': 'lip-gloss'}, {'id': 8933, 'synset': 'lipstick.n.01', 'name': 'lipstick'}, {'id': 8934, 'synset': 'liqueur_glass.n.01', 'name': 'liqueur_glass'}, {'id': 8935, 'synset': 'liquid_crystal_display.n.01', 'name': 'liquid_crystal_display'}, {'id': 8936, 'synset': 'liquid_metal_reactor.n.01', 'name': 'liquid_metal_reactor'}, {'id': 8937, 'synset': 'lisle.n.01', 'name': 'lisle'}, {'id': 8938, 'synset': 'lister.n.03', 'name': 'lister'}, {'id': 8939, 'synset': 'litterbin.n.01', 'name': 'litterbin'}, {'id': 8940, 'synset': 'little_theater.n.01', 'name': 'little_theater'}, {'id': 8941, 'synset': 'live_axle.n.01', 'name': 'live_axle'}, {'id': 8942, 'synset': 'living_quarters.n.01', 'name': 'living_quarters'}, {'id': 8943, 'synset': 'living_room.n.01', 'name': 'living_room'}, {'id': 8944, 'synset': 'load.n.09', 'name': 'load'}, {'id': 8945, 'synset': 'loafer.n.02', 'name': 'Loafer'}, {'id': 8946, 'synset': 'loaner.n.02', 'name': 'loaner'}, {'id': 8947, 'synset': 'lobe.n.04', 'name': 'lobe'}, {'id': 8948, 'synset': 'lobster_pot.n.01', 'name': 'lobster_pot'}, {'id': 8949, 'synset': 'local.n.01', 'name': 'local'}, {'id': 8950, 'synset': 'local_area_network.n.01', 'name': 'local_area_network'}, {'id': 8951, 'synset': 'local_oscillator.n.01', 'name': 'local_oscillator'}, {'id': 8952, 'synset': 'lochaber_ax.n.01', 'name': 'Lochaber_ax'}, {'id': 8953, 'synset': 'lock.n.01', 'name': 'lock'}, {'id': 8954, 'synset': 'lock.n.05', 'name': 'lock'}, {'id': 8955, 'synset': 'lock.n.04', 'name': 'lock'}, {'id': 8956, 'synset': 'lock.n.03', 'name': 'lock'}, {'id': 8957, 'synset': 'lockage.n.02', 'name': 'lockage'}, {'id': 8958, 'synset': 'locker.n.02', 'name': 'locker'}, {'id': 8959, 'synset': 'locker_room.n.01', 'name': 'locker_room'}, {'id': 8960, 'synset': 'locket.n.01', 'name': 'locket'}, {'id': 8961, 'synset': 'lock-gate.n.01', 'name': 'lock-gate'}, {'id': 8962, 'synset': 'locking_pliers.n.01', 'name': 'locking_pliers'}, {'id': 8963, 'synset': 'lockring.n.01', 'name': 'lockring'}, {'id': 8964, 'synset': 'lockstitch.n.01', 'name': 'lockstitch'}, {'id': 8965, 'synset': 'lockup.n.01', 'name': 'lockup'}, {'id': 8966, 'synset': 'locomotive.n.01', 'name': 'locomotive'}, {'id': 8967, 'synset': 'lodge.n.05', 'name': 'lodge'}, {'id': 8968, 'synset': 'lodge.n.04', 'name': 'lodge'}, {'id': 8969, 'synset': 'lodge.n.03', 'name': 'lodge'}, {'id': 8970, 'synset': 'lodging_house.n.01', 'name': 'lodging_house'}, {'id': 8971, 'synset': 'loft.n.02', 'name': 'loft'}, {'id': 8972, 'synset': 'loft.n.04', 'name': 'loft'}, {'id': 8973, 'synset': 'loft.n.01', 'name': 'loft'}, {'id': 8974, 'synset': 'log_cabin.n.01', 'name': 'log_cabin'}, {'id': 8975, 'synset': 'loggia.n.01', 'name': 'loggia'}, {'id': 8976, 'synset': 'longbow.n.01', 'name': 'longbow'}, {'id': 8977, 'synset': 'long_iron.n.01', 'name': 'long_iron'}, {'id': 8978, 'synset': 'long_johns.n.01', 'name': 'long_johns'}, {'id': 8979, 'synset': 'long_sleeve.n.01', 'name': 'long_sleeve'}, {'id': 8980, 'synset': 'long_tom.n.01', 'name': 'long_tom'}, {'id': 8981, 'synset': 'long_trousers.n.01', 'name': 'long_trousers'}, {'id': 8982, 'synset': 'long_underwear.n.01', 'name': 'long_underwear'}, {'id': 8983, 'synset': 'looking_glass.n.01', 'name': 'looking_glass'}, {'id': 8984, 'synset': 'lookout.n.03', 'name': 'lookout'}, {'id': 8985, 'synset': 'loom.n.01', 'name': 'loom'}, {'id': 8986, 'synset': 'loop_knot.n.01', 'name': 'loop_knot'}, {'id': 8987, 'synset': 'lorgnette.n.01', 'name': 'lorgnette'}, {'id': 8988, 'synset': 'lorraine_cross.n.01', 'name': 'Lorraine_cross'}, {'id': 8989, 'synset': 'lorry.n.02', 'name': 'lorry'}, {'id': 8990, 'synset': 'lota.n.01', 'name': 'lota'}, {'id': 8991, 'synset': 'lotion.n.01', 'name': 'lotion'}, {'id': 8992, 'synset': 'lounge.n.02', 'name': 'lounge'}, {'id': 8993, 'synset': 'lounger.n.03', 'name': 'lounger'}, {'id': 8994, 'synset': 'lounging_jacket.n.01', 'name': 'lounging_jacket'}, {'id': 8995, 'synset': 'lounging_pajama.n.01', 'name': 'lounging_pajama'}, {'id': 8996, 'synset': 'loungewear.n.01', 'name': 'loungewear'}, {'id': 8997, 'synset': 'loupe.n.01', 'name': 'loupe'}, {'id': 8998, 'synset': 'louvered_window.n.01', 'name': 'louvered_window'}, {'id': 8999, 'synset': 'love_knot.n.01', 'name': 'love_knot'}, {'id': 9000, 'synset': 'loving_cup.n.01', 'name': 'loving_cup'}, {'id': 9001, 'synset': 'lowboy.n.01', 'name': 'lowboy'}, {'id': 9002, 'synset': 'low-pass_filter.n.01', 'name': 'low-pass_filter'}, {'id': 9003, 'synset': 'low-warp-loom.n.01', 'name': 'low-warp-loom'}, {'id': 9004, 'synset': 'lp.n.01', 'name': 'LP'}, {'id': 9005, 'synset': 'l-plate.n.01', 'name': 'L-plate'}, {'id': 9006, 'synset': "lubber's_hole.n.01", 'name': "lubber's_hole"}, {'id': 9007, 'synset': 'lubricating_system.n.01', 'name': 'lubricating_system'}, {'id': 9008, 'synset': 'luff.n.01', 'name': 'luff'}, {'id': 9009, 'synset': 'lug.n.03', 'name': 'lug'}, {'id': 9010, 'synset': 'luge.n.01', 'name': 'luge'}, {'id': 9011, 'synset': 'luger.n.01', 'name': 'Luger'}, {'id': 9012, 'synset': 'luggage_carrier.n.01', 'name': 'luggage_carrier'}, {'id': 9013, 'synset': 'luggage_compartment.n.01', 'name': 'luggage_compartment'}, {'id': 9014, 'synset': 'luggage_rack.n.01', 'name': 'luggage_rack'}, {'id': 9015, 'synset': 'lugger.n.01', 'name': 'lugger'}, {'id': 9016, 'synset': 'lugsail.n.01', 'name': 'lugsail'}, {'id': 9017, 'synset': 'lug_wrench.n.01', 'name': 'lug_wrench'}, {'id': 9018, 'synset': 'lumberjack.n.02', 'name': 'lumberjack'}, {'id': 9019, 'synset': 'lumbermill.n.01', 'name': 'lumbermill'}, {'id': 9020, 'synset': 'lunar_excursion_module.n.01', 'name': 'lunar_excursion_module'}, {'id': 9021, 'synset': 'lunchroom.n.01', 'name': 'lunchroom'}, {'id': 9022, 'synset': 'lunette.n.01', 'name': 'lunette'}, {'id': 9023, 'synset': 'lungi.n.01', 'name': 'lungi'}, {'id': 9024, 'synset': 'lunula.n.02', 'name': 'lunula'}, {'id': 9025, 'synset': 'lusterware.n.01', 'name': 'lusterware'}, {'id': 9026, 'synset': 'lute.n.02', 'name': 'lute'}, {'id': 9027, 'synset': 'luxury_liner.n.01', 'name': 'luxury_liner'}, {'id': 9028, 'synset': 'lyceum.n.02', 'name': 'lyceum'}, {'id': 9029, 'synset': 'lychgate.n.01', 'name': 'lychgate'}, {'id': 9030, 'synset': 'lyre.n.01', 'name': 'lyre'}, {'id': 9031, 'synset': 'machete.n.01', 'name': 'machete'}, {'id': 9032, 'synset': 'machicolation.n.01', 'name': 'machicolation'}, {'id': 9033, 'synset': 'machine.n.01', 'name': 'machine'}, {'id': 9034, 'synset': 'machine.n.04', 'name': 'machine'}, {'id': 9035, 'synset': 'machine_bolt.n.01', 'name': 'machine_bolt'}, {'id': 9036, 'synset': 'machinery.n.01', 'name': 'machinery'}, {'id': 9037, 'synset': 'machine_screw.n.01', 'name': 'machine_screw'}, {'id': 9038, 'synset': 'machine_tool.n.01', 'name': 'machine_tool'}, {'id': 9039, 'synset': "machinist's_vise.n.01", 'name': "machinist's_vise"}, {'id': 9040, 'synset': 'machmeter.n.01', 'name': 'machmeter'}, {'id': 9041, 'synset': 'mackinaw.n.04', 'name': 'mackinaw'}, {'id': 9042, 'synset': 'mackinaw.n.03', 'name': 'mackinaw'}, {'id': 9043, 'synset': 'mackinaw.n.01', 'name': 'mackinaw'}, {'id': 9044, 'synset': 'mackintosh.n.01', 'name': 'mackintosh'}, {'id': 9045, 'synset': 'macrame.n.01', 'name': 'macrame'}, {'id': 9046, 'synset': 'madras.n.03', 'name': 'madras'}, {'id': 9047, 'synset': 'mae_west.n.02', 'name': 'Mae_West'}, {'id': 9048, 'synset': 'magazine_rack.n.01', 'name': 'magazine_rack'}, {'id': 9049, 'synset': 'magic_lantern.n.01', 'name': 'magic_lantern'}, {'id': 9050, 'synset': 'magnetic_bottle.n.01', 'name': 'magnetic_bottle'}, {'id': 9051, 'synset': 'magnetic_compass.n.01', 'name': 'magnetic_compass'}, {'id': 9052, 'synset': 'magnetic_core_memory.n.01', 'name': 'magnetic_core_memory'}, {'id': 9053, 'synset': 'magnetic_disk.n.01', 'name': 'magnetic_disk'}, {'id': 9054, 'synset': 'magnetic_head.n.01', 'name': 'magnetic_head'}, {'id': 9055, 'synset': 'magnetic_mine.n.01', 'name': 'magnetic_mine'}, {'id': 9056, 'synset': 'magnetic_needle.n.01', 'name': 'magnetic_needle'}, {'id': 9057, 'synset': 'magnetic_recorder.n.01', 'name': 'magnetic_recorder'}, {'id': 9058, 'synset': 'magnetic_stripe.n.01', 'name': 'magnetic_stripe'}, {'id': 9059, 'synset': 'magnetic_tape.n.01', 'name': 'magnetic_tape'}, {'id': 9060, 'synset': 'magneto.n.01', 'name': 'magneto'}, {'id': 9061, 'synset': 'magnetometer.n.01', 'name': 'magnetometer'}, {'id': 9062, 'synset': 'magnetron.n.01', 'name': 'magnetron'}, {'id': 9063, 'synset': 'magnifier.n.01', 'name': 'magnifier'}, {'id': 9064, 'synset': 'magnum.n.01', 'name': 'magnum'}, {'id': 9065, 'synset': 'magnus_hitch.n.01', 'name': 'magnus_hitch'}, {'id': 9066, 'synset': 'mail.n.03', 'name': 'mail'}, {'id': 9067, 'synset': 'mailbag.n.02', 'name': 'mailbag'}, {'id': 9068, 'synset': 'mailbag.n.01', 'name': 'mailbag'}, {'id': 9069, 'synset': 'mailboat.n.01', 'name': 'mailboat'}, {'id': 9070, 'synset': 'mail_car.n.01', 'name': 'mail_car'}, {'id': 9071, 'synset': 'maildrop.n.01', 'name': 'maildrop'}, {'id': 9072, 'synset': 'mailer.n.04', 'name': 'mailer'}, {'id': 9073, 'synset': 'maillot.n.02', 'name': 'maillot'}, {'id': 9074, 'synset': 'maillot.n.01', 'name': 'maillot'}, {'id': 9075, 'synset': 'mailsorter.n.01', 'name': 'mailsorter'}, {'id': 9076, 'synset': 'mail_train.n.01', 'name': 'mail_train'}, {'id': 9077, 'synset': 'mainframe.n.01', 'name': 'mainframe'}, {'id': 9078, 'synset': 'mainmast.n.01', 'name': 'mainmast'}, {'id': 9079, 'synset': 'main_rotor.n.01', 'name': 'main_rotor'}, {'id': 9080, 'synset': 'mainsail.n.01', 'name': 'mainsail'}, {'id': 9081, 'synset': 'mainspring.n.01', 'name': 'mainspring'}, {'id': 9082, 'synset': 'main-topmast.n.01', 'name': 'main-topmast'}, {'id': 9083, 'synset': 'main-topsail.n.01', 'name': 'main-topsail'}, {'id': 9084, 'synset': 'main_yard.n.01', 'name': 'main_yard'}, {'id': 9085, 'synset': 'maisonette.n.02', 'name': 'maisonette'}, {'id': 9086, 'synset': 'majolica.n.01', 'name': 'majolica'}, {'id': 9087, 'synset': 'makeup.n.01', 'name': 'makeup'}, {'id': 9088, 'synset': 'maksutov_telescope.n.01', 'name': 'Maksutov_telescope'}, {'id': 9089, 'synset': 'malacca.n.02', 'name': 'malacca'}, {'id': 9090, 'synset': 'mallet.n.03', 'name': 'mallet'}, {'id': 9091, 'synset': 'mallet.n.02', 'name': 'mallet'}, {'id': 9092, 'synset': 'mammogram.n.01', 'name': 'mammogram'}, {'id': 9093, 'synset': 'mandola.n.01', 'name': 'mandola'}, {'id': 9094, 'synset': 'mandolin.n.01', 'name': 'mandolin'}, {'id': 9095, 'synset': 'mangle.n.01', 'name': 'mangle'}, {'id': 9096, 'synset': 'manhole_cover.n.01', 'name': 'manhole_cover'}, {'id': 9097, 'synset': 'man-of-war.n.01', 'name': 'man-of-war'}, {'id': 9098, 'synset': 'manometer.n.01', 'name': 'manometer'}, {'id': 9099, 'synset': 'manor.n.01', 'name': 'manor'}, {'id': 9100, 'synset': 'manor_hall.n.01', 'name': 'manor_hall'}, {'id': 9101, 'synset': 'manpad.n.01', 'name': 'MANPAD'}, {'id': 9102, 'synset': 'mansard.n.01', 'name': 'mansard'}, {'id': 9103, 'synset': 'manse.n.02', 'name': 'manse'}, {'id': 9104, 'synset': 'mansion.n.02', 'name': 'mansion'}, {'id': 9105, 'synset': 'mantel.n.01', 'name': 'mantel'}, {'id': 9106, 'synset': 'mantelet.n.02', 'name': 'mantelet'}, {'id': 9107, 'synset': 'mantilla.n.01', 'name': 'mantilla'}, {'id': 9108, 'synset': 'mao_jacket.n.01', 'name': 'Mao_jacket'}, {'id': 9109, 'synset': 'maquiladora.n.01', 'name': 'maquiladora'}, {'id': 9110, 'synset': 'maraca.n.01', 'name': 'maraca'}, {'id': 9111, 'synset': 'marble.n.02', 'name': 'marble'}, {'id': 9112, 'synset': 'marching_order.n.01', 'name': 'marching_order'}, {'id': 9113, 'synset': 'marimba.n.01', 'name': 'marimba'}, {'id': 9114, 'synset': 'marina.n.01', 'name': 'marina'}, {'id': 9115, 'synset': 'marketplace.n.02', 'name': 'marketplace'}, {'id': 9116, 'synset': 'marlinespike.n.01', 'name': 'marlinespike'}, {'id': 9117, 'synset': 'marocain.n.01', 'name': 'marocain'}, {'id': 9118, 'synset': 'marquee.n.02', 'name': 'marquee'}, {'id': 9119, 'synset': 'marquetry.n.01', 'name': 'marquetry'}, {'id': 9120, 'synset': 'marriage_bed.n.01', 'name': 'marriage_bed'}, {'id': 9121, 'synset': 'martello_tower.n.01', 'name': 'martello_tower'}, {'id': 9122, 'synset': 'martingale.n.01', 'name': 'martingale'}, {'id': 9123, 'synset': 'mascara.n.01', 'name': 'mascara'}, {'id': 9124, 'synset': 'maser.n.01', 'name': 'maser'}, {'id': 9125, 'synset': 'mashie.n.01', 'name': 'mashie'}, {'id': 9126, 'synset': 'mashie_niblick.n.01', 'name': 'mashie_niblick'}, {'id': 9127, 'synset': 'masjid.n.01', 'name': 'masjid'}, {'id': 9128, 'synset': 'mask.n.01', 'name': 'mask'}, {'id': 9129, 'synset': 'masonite.n.01', 'name': 'Masonite'}, {'id': 9130, 'synset': 'mason_jar.n.01', 'name': 'Mason_jar'}, {'id': 9131, 'synset': 'masonry.n.01', 'name': 'masonry'}, {'id': 9132, 'synset': "mason's_level.n.01", 'name': "mason's_level"}, {'id': 9133, 'synset': 'massage_parlor.n.02', 'name': 'massage_parlor'}, {'id': 9134, 'synset': 'massage_parlor.n.01', 'name': 'massage_parlor'}, {'id': 9135, 'synset': 'mass_spectrograph.n.01', 'name': 'mass_spectrograph'}, {'id': 9136, 'synset': 'mass_spectrometer.n.01', 'name': 'mass_spectrometer'}, {'id': 9137, 'synset': 'mast.n.04', 'name': 'mast'}, {'id': 9138, 'synset': 'mastaba.n.01', 'name': 'mastaba'}, {'id': 9139, 'synset': 'master_bedroom.n.01', 'name': 'master_bedroom'}, {'id': 9140, 'synset': 'masterpiece.n.01', 'name': 'masterpiece'}, {'id': 9141, 'synset': 'mat.n.01', 'name': 'mat'}, {'id': 9142, 'synset': 'match.n.01', 'name': 'match'}, {'id': 9143, 'synset': 'match.n.03', 'name': 'match'}, {'id': 9144, 'synset': 'matchboard.n.01', 'name': 'matchboard'}, {'id': 9145, 'synset': 'matchbook.n.01', 'name': 'matchbook'}, {'id': 9146, 'synset': 'matchlock.n.01', 'name': 'matchlock'}, {'id': 9147, 'synset': 'match_plane.n.01', 'name': 'match_plane'}, {'id': 9148, 'synset': 'matchstick.n.01', 'name': 'matchstick'}, {'id': 9149, 'synset': 'material.n.04', 'name': 'material'}, {'id': 9150, 'synset': 'materiel.n.01', 'name': 'materiel'}, {'id': 9151, 'synset': 'maternity_hospital.n.01', 'name': 'maternity_hospital'}, {'id': 9152, 'synset': 'maternity_ward.n.01', 'name': 'maternity_ward'}, {'id': 9153, 'synset': 'matrix.n.06', 'name': 'matrix'}, {'id': 9154, 'synset': 'matthew_walker.n.01', 'name': 'Matthew_Walker'}, {'id': 9155, 'synset': 'matting.n.01', 'name': 'matting'}, {'id': 9156, 'synset': 'mattock.n.01', 'name': 'mattock'}, {'id': 9157, 'synset': 'mattress_cover.n.01', 'name': 'mattress_cover'}, {'id': 9158, 'synset': 'maul.n.01', 'name': 'maul'}, {'id': 9159, 'synset': 'maulstick.n.01', 'name': 'maulstick'}, {'id': 9160, 'synset': 'mauser.n.02', 'name': 'Mauser'}, {'id': 9161, 'synset': 'mausoleum.n.01', 'name': 'mausoleum'}, {'id': 9162, 'synset': 'maxi.n.01', 'name': 'maxi'}, {'id': 9163, 'synset': 'maxim_gun.n.01', 'name': 'Maxim_gun'}, {'id': 9164, 'synset': 'maximum_and_minimum_thermometer.n.01', 'name': 'maximum_and_minimum_thermometer'}, {'id': 9165, 'synset': 'maypole.n.01', 'name': 'maypole'}, {'id': 9166, 'synset': 'maze.n.01', 'name': 'maze'}, {'id': 9167, 'synset': 'mazer.n.01', 'name': 'mazer'}, {'id': 9168, 'synset': 'means.n.02', 'name': 'means'}, {'id': 9169, 'synset': 'measure.n.09', 'name': 'measure'}, {'id': 9170, 'synset': 'measuring_instrument.n.01', 'name': 'measuring_instrument'}, {'id': 9171, 'synset': 'meat_counter.n.01', 'name': 'meat_counter'}, {'id': 9172, 'synset': 'meat_grinder.n.01', 'name': 'meat_grinder'}, {'id': 9173, 'synset': 'meat_hook.n.01', 'name': 'meat_hook'}, {'id': 9174, 'synset': 'meat_house.n.02', 'name': 'meat_house'}, {'id': 9175, 'synset': 'meat_safe.n.01', 'name': 'meat_safe'}, {'id': 9176, 'synset': 'meat_thermometer.n.01', 'name': 'meat_thermometer'}, {'id': 9177, 'synset': 'mechanical_device.n.01', 'name': 'mechanical_device'}, {'id': 9178, 'synset': 'mechanical_piano.n.01', 'name': 'mechanical_piano'}, {'id': 9179, 'synset': 'mechanical_system.n.01', 'name': 'mechanical_system'}, {'id': 9180, 'synset': 'mechanism.n.05', 'name': 'mechanism'}, {'id': 9181, 'synset': 'medical_building.n.01', 'name': 'medical_building'}, {'id': 9182, 'synset': 'medical_instrument.n.01', 'name': 'medical_instrument'}, {'id': 9183, 'synset': 'medicine_ball.n.01', 'name': 'medicine_ball'}, {'id': 9184, 'synset': 'medicine_chest.n.01', 'name': 'medicine_chest'}, {'id': 9185, 'synset': 'medline.n.01', 'name': 'MEDLINE'}, {'id': 9186, 'synset': 'megalith.n.01', 'name': 'megalith'}, {'id': 9187, 'synset': 'megaphone.n.01', 'name': 'megaphone'}, {'id': 9188, 'synset': 'memorial.n.03', 'name': 'memorial'}, {'id': 9189, 'synset': 'memory.n.04', 'name': 'memory'}, {'id': 9190, 'synset': 'memory_chip.n.01', 'name': 'memory_chip'}, {'id': 9191, 'synset': 'memory_device.n.01', 'name': 'memory_device'}, {'id': 9192, 'synset': 'menagerie.n.02', 'name': 'menagerie'}, {'id': 9193, 'synset': 'mending.n.01', 'name': 'mending'}, {'id': 9194, 'synset': 'menhir.n.01', 'name': 'menhir'}, {'id': 9195, 'synset': 'menorah.n.02', 'name': 'menorah'}, {'id': 9196, 'synset': 'menorah.n.01', 'name': 'Menorah'}, {'id': 9197, 'synset': "man's_clothing.n.01", 'name': "man's_clothing"}, {'id': 9198, 'synset': "men's_room.n.01", 'name': "men's_room"}, {'id': 9199, 'synset': 'mercantile_establishment.n.01', 'name': 'mercantile_establishment'}, {'id': 9200, 'synset': 'mercury_barometer.n.01', 'name': 'mercury_barometer'}, {'id': 9201, 'synset': 'mercury_cell.n.01', 'name': 'mercury_cell'}, {'id': 9202, 'synset': 'mercury_thermometer.n.01', 'name': 'mercury_thermometer'}, {'id': 9203, 'synset': 'mercury-vapor_lamp.n.01', 'name': 'mercury-vapor_lamp'}, {'id': 9204, 'synset': 'mercy_seat.n.02', 'name': 'mercy_seat'}, {'id': 9205, 'synset': 'merlon.n.01', 'name': 'merlon'}, {'id': 9206, 'synset': 'mess.n.05', 'name': 'mess'}, {'id': 9207, 'synset': 'mess_jacket.n.01', 'name': 'mess_jacket'}, {'id': 9208, 'synset': 'mess_kit.n.01', 'name': 'mess_kit'}, {'id': 9209, 'synset': 'messuage.n.01', 'name': 'messuage'}, {'id': 9210, 'synset': 'metal_detector.n.01', 'name': 'metal_detector'}, {'id': 9211, 'synset': 'metallic.n.01', 'name': 'metallic'}, {'id': 9212, 'synset': 'metal_screw.n.01', 'name': 'metal_screw'}, {'id': 9213, 'synset': 'metal_wood.n.01', 'name': 'metal_wood'}, {'id': 9214, 'synset': 'meteorological_balloon.n.01', 'name': 'meteorological_balloon'}, {'id': 9215, 'synset': 'meter.n.02', 'name': 'meter'}, {'id': 9216, 'synset': 'meterstick.n.01', 'name': 'meterstick'}, {'id': 9217, 'synset': 'metronome.n.01', 'name': 'metronome'}, {'id': 9218, 'synset': 'mezzanine.n.02', 'name': 'mezzanine'}, {'id': 9219, 'synset': 'mezzanine.n.01', 'name': 'mezzanine'}, {'id': 9220, 'synset': 'microbalance.n.01', 'name': 'microbalance'}, {'id': 9221, 'synset': 'microbrewery.n.01', 'name': 'microbrewery'}, {'id': 9222, 'synset': 'microfiche.n.01', 'name': 'microfiche'}, {'id': 9223, 'synset': 'microfilm.n.01', 'name': 'microfilm'}, {'id': 9224, 'synset': 'micrometer.n.02', 'name': 'micrometer'}, {'id': 9225, 'synset': 'microprocessor.n.01', 'name': 'microprocessor'}, {'id': 9226, 'synset': 'microtome.n.01', 'name': 'microtome'}, {'id': 9227, 'synset': 'microwave_diathermy_machine.n.01', 'name': 'microwave_diathermy_machine'}, {'id': 9228, 'synset': 'microwave_linear_accelerator.n.01', 'name': 'microwave_linear_accelerator'}, {'id': 9229, 'synset': 'middy.n.01', 'name': 'middy'}, {'id': 9230, 'synset': 'midiron.n.01', 'name': 'midiron'}, {'id': 9231, 'synset': 'mihrab.n.02', 'name': 'mihrab'}, {'id': 9232, 'synset': 'mihrab.n.01', 'name': 'mihrab'}, {'id': 9233, 'synset': 'military_hospital.n.01', 'name': 'military_hospital'}, {'id': 9234, 'synset': 'military_quarters.n.01', 'name': 'military_quarters'}, {'id': 9235, 'synset': 'military_uniform.n.01', 'name': 'military_uniform'}, {'id': 9236, 'synset': 'military_vehicle.n.01', 'name': 'military_vehicle'}, {'id': 9237, 'synset': 'milk_bar.n.01', 'name': 'milk_bar'}, {'id': 9238, 'synset': 'milk_float.n.01', 'name': 'milk_float'}, {'id': 9239, 'synset': 'milking_machine.n.01', 'name': 'milking_machine'}, {'id': 9240, 'synset': 'milking_stool.n.01', 'name': 'milking_stool'}, {'id': 9241, 'synset': 'milk_wagon.n.01', 'name': 'milk_wagon'}, {'id': 9242, 'synset': 'mill.n.04', 'name': 'mill'}, {'id': 9243, 'synset': 'milldam.n.01', 'name': 'milldam'}, {'id': 9244, 'synset': 'miller.n.05', 'name': 'miller'}, {'id': 9245, 'synset': 'milliammeter.n.01', 'name': 'milliammeter'}, {'id': 9246, 'synset': 'millinery.n.02', 'name': 'millinery'}, {'id': 9247, 'synset': 'millinery.n.01', 'name': 'millinery'}, {'id': 9248, 'synset': 'milling.n.01', 'name': 'milling'}, {'id': 9249, 'synset': 'millivoltmeter.n.01', 'name': 'millivoltmeter'}, {'id': 9250, 'synset': 'millstone.n.03', 'name': 'millstone'}, {'id': 9251, 'synset': 'millstone.n.02', 'name': 'millstone'}, {'id': 9252, 'synset': 'millwheel.n.01', 'name': 'millwheel'}, {'id': 9253, 'synset': 'mimeograph.n.01', 'name': 'mimeograph'}, {'id': 9254, 'synset': 'minaret.n.01', 'name': 'minaret'}, {'id': 9255, 'synset': 'mincer.n.01', 'name': 'mincer'}, {'id': 9256, 'synset': 'mine.n.02', 'name': 'mine'}, {'id': 9257, 'synset': 'mine_detector.n.01', 'name': 'mine_detector'}, {'id': 9258, 'synset': 'minelayer.n.01', 'name': 'minelayer'}, {'id': 9259, 'synset': 'mineshaft.n.01', 'name': 'mineshaft'}, {'id': 9260, 'synset': 'minibar.n.01', 'name': 'minibar'}, {'id': 9261, 'synset': 'minibike.n.01', 'name': 'minibike'}, {'id': 9262, 'synset': 'minibus.n.01', 'name': 'minibus'}, {'id': 9263, 'synset': 'minicar.n.01', 'name': 'minicar'}, {'id': 9264, 'synset': 'minicomputer.n.01', 'name': 'minicomputer'}, {'id': 9265, 'synset': 'ministry.n.02', 'name': 'ministry'}, {'id': 9266, 'synset': 'miniskirt.n.01', 'name': 'miniskirt'}, {'id': 9267, 'synset': 'minisub.n.01', 'name': 'minisub'}, {'id': 9268, 'synset': 'miniver.n.01', 'name': 'miniver'}, {'id': 9269, 'synset': 'mink.n.02', 'name': 'mink'}, {'id': 9270, 'synset': 'minster.n.01', 'name': 'minster'}, {'id': 9271, 'synset': 'mint.n.06', 'name': 'mint'}, {'id': 9272, 'synset': 'minute_hand.n.01', 'name': 'minute_hand'}, {'id': 9273, 'synset': 'minuteman.n.02', 'name': 'Minuteman'}, {'id': 9274, 'synset': 'missile.n.01', 'name': 'missile'}, {'id': 9275, 'synset': 'missile_defense_system.n.01', 'name': 'missile_defense_system'}, {'id': 9276, 'synset': 'miter_box.n.01', 'name': 'miter_box'}, {'id': 9277, 'synset': 'miter_joint.n.01', 'name': 'miter_joint'}, {'id': 9278, 'synset': 'mixer.n.03', 'name': 'mixer'}, {'id': 9279, 'synset': 'mixing_bowl.n.01', 'name': 'mixing_bowl'}, {'id': 9280, 'synset': 'mixing_faucet.n.01', 'name': 'mixing_faucet'}, {'id': 9281, 'synset': 'mizzen.n.02', 'name': 'mizzen'}, {'id': 9282, 'synset': 'mizzenmast.n.01', 'name': 'mizzenmast'}, {'id': 9283, 'synset': 'mobcap.n.01', 'name': 'mobcap'}, {'id': 9284, 'synset': 'mobile_home.n.01', 'name': 'mobile_home'}, {'id': 9285, 'synset': 'moccasin.n.01', 'name': 'moccasin'}, {'id': 9286, 'synset': 'mock-up.n.01', 'name': 'mock-up'}, {'id': 9287, 'synset': 'mod_con.n.01', 'name': 'mod_con'}, {'id': 9288, 'synset': 'model_t.n.01', 'name': 'Model_T'}, {'id': 9289, 'synset': 'modem.n.01', 'name': 'modem'}, {'id': 9290, 'synset': 'modillion.n.01', 'name': 'modillion'}, {'id': 9291, 'synset': 'module.n.03', 'name': 'module'}, {'id': 9292, 'synset': 'module.n.02', 'name': 'module'}, {'id': 9293, 'synset': 'mohair.n.01', 'name': 'mohair'}, {'id': 9294, 'synset': 'moire.n.01', 'name': 'moire'}, {'id': 9295, 'synset': 'mold.n.02', 'name': 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'monofocal_lens_implant'}, {'id': 9311, 'synset': 'monoplane.n.01', 'name': 'monoplane'}, {'id': 9312, 'synset': 'monotype.n.02', 'name': 'monotype'}, {'id': 9313, 'synset': 'monstrance.n.02', 'name': 'monstrance'}, {'id': 9314, 'synset': 'mooring_tower.n.01', 'name': 'mooring_tower'}, {'id': 9315, 'synset': 'moorish_arch.n.01', 'name': 'Moorish_arch'}, {'id': 9316, 'synset': 'moped.n.01', 'name': 'moped'}, {'id': 9317, 'synset': 'mop_handle.n.01', 'name': 'mop_handle'}, {'id': 9318, 'synset': 'moquette.n.01', 'name': 'moquette'}, {'id': 9319, 'synset': 'morgue.n.01', 'name': 'morgue'}, {'id': 9320, 'synset': 'morion.n.01', 'name': 'morion'}, {'id': 9321, 'synset': 'morning_dress.n.02', 'name': 'morning_dress'}, {'id': 9322, 'synset': 'morning_dress.n.01', 'name': 'morning_dress'}, {'id': 9323, 'synset': 'morning_room.n.01', 'name': 'morning_room'}, {'id': 9324, 'synset': 'morris_chair.n.01', 'name': 'Morris_chair'}, {'id': 9325, 'synset': 'mortar.n.01', 'name': 'mortar'}, {'id': 9326, 'synset': 'mortar.n.03', 'name': 'mortar'}, {'id': 9327, 'synset': 'mortarboard.n.02', 'name': 'mortarboard'}, {'id': 9328, 'synset': 'mortise_joint.n.02', 'name': 'mortise_joint'}, {'id': 9329, 'synset': 'mosaic.n.05', 'name': 'mosaic'}, {'id': 9330, 'synset': 'mosque.n.01', 'name': 'mosque'}, {'id': 9331, 'synset': 'mosquito_net.n.01', 'name': 'mosquito_net'}, {'id': 9332, 'synset': 'motel.n.01', 'name': 'motel'}, {'id': 9333, 'synset': 'motel_room.n.01', 'name': 'motel_room'}, {'id': 9334, 'synset': 'mother_hubbard.n.01', 'name': 'Mother_Hubbard'}, {'id': 9335, 'synset': 'motion-picture_camera.n.01', 'name': 'motion-picture_camera'}, {'id': 9336, 'synset': 'motion-picture_film.n.01', 'name': 'motion-picture_film'}, {'id': 9337, 'synset': 'motley.n.03', 'name': 'motley'}, {'id': 9338, 'synset': 'motley.n.02', 'name': 'motley'}, {'id': 9339, 'synset': 'motorboat.n.01', 'name': 'motorboat'}, {'id': 9340, 'synset': 'motor_hotel.n.01', 'name': 'motor_hotel'}, {'id': 9341, 'synset': 'motorized_wheelchair.n.01', 'name': 'motorized_wheelchair'}, {'id': 9342, 'synset': 'mound.n.04', 'name': 'mound'}, {'id': 9343, 'synset': 'mount.n.04', 'name': 'mount'}, {'id': 9344, 'synset': 'mountain_bike.n.01', 'name': 'mountain_bike'}, {'id': 9345, 'synset': 'mountain_tent.n.01', 'name': 'mountain_tent'}, {'id': 9346, 'synset': 'mouse_button.n.01', 'name': 'mouse_button'}, {'id': 9347, 'synset': 'mousetrap.n.01', 'name': 'mousetrap'}, {'id': 9348, 'synset': 'mousse.n.03', 'name': 'mousse'}, {'id': 9349, 'synset': 'mouthpiece.n.06', 'name': 'mouthpiece'}, {'id': 9350, 'synset': 'mouthpiece.n.02', 'name': 'mouthpiece'}, {'id': 9351, 'synset': 'mouthpiece.n.04', 'name': 'mouthpiece'}, {'id': 9352, 'synset': 'movement.n.10', 'name': 'movement'}, {'id': 9353, 'synset': 'movie_projector.n.01', 'name': 'movie_projector'}, {'id': 9354, 'synset': 'moving-coil_galvanometer.n.01', 'name': 'moving-coil_galvanometer'}, {'id': 9355, 'synset': 'moving_van.n.01', 'name': 'moving_van'}, {'id': 9356, 'synset': 'mud_brick.n.01', 'name': 'mud_brick'}, {'id': 9357, 'synset': 'mudguard.n.01', 'name': 'mudguard'}, {'id': 9358, 'synset': 'mudhif.n.01', 'name': 'mudhif'}, {'id': 9359, 'synset': 'muff.n.01', 'name': 'muff'}, {'id': 9360, 'synset': 'muffle.n.01', 'name': 'muffle'}, {'id': 9361, 'synset': 'muffler.n.02', 'name': 'muffler'}, {'id': 9362, 'synset': 'mufti.n.02', 'name': 'mufti'}, {'id': 9363, 'synset': 'mulch.n.01', 'name': 'mulch'}, {'id': 9364, 'synset': 'mule.n.02', 'name': 'mule'}, {'id': 9365, 'synset': 'multichannel_recorder.n.01', 'name': 'multichannel_recorder'}, {'id': 9366, 'synset': 'multiengine_airplane.n.01', 'name': 'multiengine_airplane'}, {'id': 9367, 'synset': 'multiplex.n.02', 'name': 'multiplex'}, {'id': 9368, 'synset': 'multiplexer.n.01', 'name': 'multiplexer'}, {'id': 9369, 'synset': 'multiprocessor.n.01', 'name': 'multiprocessor'}, {'id': 9370, 'synset': 'multistage_rocket.n.01', 'name': 'multistage_rocket'}, {'id': 9371, 'synset': 'munition.n.02', 'name': 'munition'}, {'id': 9372, 'synset': 'murphy_bed.n.01', 'name': 'Murphy_bed'}, {'id': 9373, 'synset': 'musette.n.01', 'name': 'musette'}, {'id': 9374, 'synset': 'musette_pipe.n.01', 'name': 'musette_pipe'}, {'id': 9375, 'synset': 'museum.n.01', 'name': 'museum'}, {'id': 9376, 'synset': 'mushroom_anchor.n.01', 'name': 'mushroom_anchor'}, {'id': 9377, 'synset': 'music_box.n.01', 'name': 'music_box'}, {'id': 9378, 'synset': 'music_hall.n.01', 'name': 'music_hall'}, {'id': 9379, 'synset': 'music_school.n.02', 'name': 'music_school'}, {'id': 9380, 'synset': 'music_stand.n.01', 'name': 'music_stand'}, {'id': 9381, 'synset': 'musket.n.01', 'name': 'musket'}, {'id': 9382, 'synset': 'musket_ball.n.01', 'name': 'musket_ball'}, {'id': 9383, 'synset': 'muslin.n.01', 'name': 'muslin'}, {'id': 9384, 'synset': 'mustache_cup.n.01', 'name': 'mustache_cup'}, {'id': 9385, 'synset': 'mustard_plaster.n.01', 'name': 'mustard_plaster'}, {'id': 9386, 'synset': 'mute.n.02', 'name': 'mute'}, {'id': 9387, 'synset': 'muzzle_loader.n.01', 'name': 'muzzle_loader'}, {'id': 9388, 'synset': 'muzzle.n.03', 'name': 'muzzle'}, {'id': 9389, 'synset': 'myelogram.n.01', 'name': 'myelogram'}, {'id': 9390, 'synset': 'nacelle.n.01', 'name': 'nacelle'}, {'id': 9391, 'synset': 'nail.n.02', 'name': 'nail'}, {'id': 9392, 'synset': 'nailbrush.n.01', 'name': 'nailbrush'}, {'id': 9393, 'synset': 'nailhead.n.02', 'name': 'nailhead'}, {'id': 9394, 'synset': 'nailhead.n.01', 'name': 'nailhead'}, {'id': 9395, 'synset': 'nail_polish.n.01', 'name': 'nail_polish'}, {'id': 9396, 'synset': 'nainsook.n.01', 'name': 'nainsook'}, {'id': 9397, 'synset': "napier's_bones.n.01", 'name': "Napier's_bones"}, {'id': 9398, 'synset': 'nard.n.01', 'name': 'nard'}, {'id': 9399, 'synset': 'narrowbody_aircraft.n.01', 'name': 'narrowbody_aircraft'}, {'id': 9400, 'synset': 'narrow_wale.n.01', 'name': 'narrow_wale'}, {'id': 9401, 'synset': 'narthex.n.02', 'name': 'narthex'}, {'id': 9402, 'synset': 'narthex.n.01', 'name': 'narthex'}, {'id': 9403, 'synset': 'nasotracheal_tube.n.01', 'name': 'nasotracheal_tube'}, {'id': 9404, 'synset': 'national_monument.n.01', 'name': 'national_monument'}, {'id': 9405, 'synset': 'nautilus.n.01', 'name': 'nautilus'}, {'id': 9406, 'synset': 'navigational_system.n.01', 'name': 'navigational_system'}, {'id': 9407, 'synset': 'naval_equipment.n.01', 'name': 'naval_equipment'}, {'id': 9408, 'synset': 'naval_gun.n.01', 'name': 'naval_gun'}, {'id': 9409, 'synset': 'naval_missile.n.01', 'name': 'naval_missile'}, {'id': 9410, 'synset': 'naval_radar.n.01', 'name': 'naval_radar'}, {'id': 9411, 'synset': 'naval_tactical_data_system.n.01', 'name': 'naval_tactical_data_system'}, {'id': 9412, 'synset': 'naval_weaponry.n.01', 'name': 'naval_weaponry'}, {'id': 9413, 'synset': 'nave.n.01', 'name': 'nave'}, {'id': 9414, 'synset': 'navigational_instrument.n.01', 'name': 'navigational_instrument'}, {'id': 9415, 'synset': 'nebuchadnezzar.n.02', 'name': 'nebuchadnezzar'}, {'id': 9416, 'synset': 'neckband.n.01', 'name': 'neckband'}, {'id': 9417, 'synset': 'neck_brace.n.01', 'name': 'neck_brace'}, {'id': 9418, 'synset': 'neckcloth.n.01', 'name': 'neckcloth'}, {'id': 9419, 'synset': 'necklet.n.01', 'name': 'necklet'}, {'id': 9420, 'synset': 'neckline.n.01', 'name': 'neckline'}, {'id': 9421, 'synset': 'neckpiece.n.01', 'name': 'neckpiece'}, {'id': 9422, 'synset': 'neckwear.n.01', 'name': 'neckwear'}, {'id': 9423, 'synset': 'needle.n.02', 'name': 'needle'}, {'id': 9424, 'synset': 'needlenose_pliers.n.01', 'name': 'needlenose_pliers'}, {'id': 9425, 'synset': 'needlework.n.01', 'name': 'needlework'}, {'id': 9426, 'synset': 'negative.n.02', 'name': 'negative'}, {'id': 9427, 'synset': 'negative_magnetic_pole.n.01', 'name': 'negative_magnetic_pole'}, {'id': 9428, 'synset': 'negative_pole.n.01', 'name': 'negative_pole'}, {'id': 9429, 'synset': 'negligee.n.01', 'name': 'negligee'}, {'id': 9430, 'synset': 'neolith.n.01', 'name': 'neolith'}, {'id': 9431, 'synset': 'neon_lamp.n.01', 'name': 'neon_lamp'}, {'id': 9432, 'synset': 'nephoscope.n.01', 'name': 'nephoscope'}, {'id': 9433, 'synset': 'nest.n.05', 'name': 'nest'}, {'id': 9434, 'synset': 'nest_egg.n.02', 'name': 'nest_egg'}, {'id': 9435, 'synset': 'net.n.06', 'name': 'net'}, {'id': 9436, 'synset': 'net.n.02', 'name': 'net'}, {'id': 9437, 'synset': 'net.n.05', 'name': 'net'}, {'id': 9438, 'synset': 'net.n.04', 'name': 'net'}, {'id': 9439, 'synset': 'network.n.05', 'name': 'network'}, {'id': 9440, 'synset': 'network.n.04', 'name': 'network'}, {'id': 9441, 'synset': 'neutron_bomb.n.01', 'name': 'neutron_bomb'}, {'id': 9442, 'synset': 'newel.n.02', 'name': 'newel'}, {'id': 9443, 'synset': 'newel_post.n.01', 'name': 'newel_post'}, {'id': 9444, 'synset': 'newspaper.n.03', 'name': 'newspaper'}, {'id': 9445, 'synset': 'newsroom.n.03', 'name': 'newsroom'}, {'id': 9446, 'synset': 'newsroom.n.02', 'name': 'newsroom'}, {'id': 9447, 'synset': 'newtonian_telescope.n.01', 'name': 'Newtonian_telescope'}, {'id': 9448, 'synset': 'nib.n.01', 'name': 'nib'}, {'id': 9449, 'synset': 'niblick.n.01', 'name': 'niblick'}, {'id': 9450, 'synset': 'nicad.n.01', 'name': 'nicad'}, {'id': 9451, 'synset': 'nickel-iron_battery.n.01', 'name': 'nickel-iron_battery'}, {'id': 9452, 'synset': 'nicol_prism.n.01', 'name': 'Nicol_prism'}, {'id': 9453, 'synset': 'night_bell.n.01', 'name': 'night_bell'}, {'id': 9454, 'synset': 'nightcap.n.02', 'name': 'nightcap'}, {'id': 9455, 'synset': 'nightgown.n.01', 'name': 'nightgown'}, {'id': 9456, 'synset': 'night_latch.n.01', 'name': 'night_latch'}, {'id': 9457, 'synset': 'night-light.n.01', 'name': 'night-light'}, {'id': 9458, 'synset': 'nightshirt.n.01', 'name': 'nightshirt'}, {'id': 9459, 'synset': 'ninepin.n.01', 'name': 'ninepin'}, {'id': 9460, 'synset': 'ninepin_ball.n.01', 'name': 'ninepin_ball'}, {'id': 9461, 'synset': 'ninon.n.01', 'name': 'ninon'}, {'id': 9462, 'synset': 'nipple.n.02', 'name': 'nipple'}, {'id': 9463, 'synset': 'nipple_shield.n.01', 'name': 'nipple_shield'}, {'id': 9464, 'synset': 'niqab.n.01', 'name': 'niqab'}, {'id': 9465, 'synset': 'nissen_hut.n.01', 'name': 'Nissen_hut'}, {'id': 9466, 'synset': 'nogging.n.01', 'name': 'nogging'}, {'id': 9467, 'synset': 'noisemaker.n.01', 'name': 'noisemaker'}, {'id': 9468, 'synset': 'nonsmoker.n.02', 'name': 'nonsmoker'}, {'id': 9469, 'synset': 'non-volatile_storage.n.01', 'name': 'non-volatile_storage'}, {'id': 9470, 'synset': 'norfolk_jacket.n.01', 'name': 'Norfolk_jacket'}, {'id': 9471, 'synset': 'noria.n.01', 'name': 'noria'}, {'id': 9472, 'synset': 'nose_flute.n.01', 'name': 'nose_flute'}, {'id': 9473, 'synset': 'nosewheel.n.01', 'name': 'nosewheel'}, {'id': 9474, 'synset': 'notebook.n.02', 'name': 'notebook'}, {'id': 9475, 'synset': 'nuclear-powered_ship.n.01', 'name': 'nuclear-powered_ship'}, {'id': 9476, 'synset': 'nuclear_reactor.n.01', 'name': 'nuclear_reactor'}, {'id': 9477, 'synset': 'nuclear_rocket.n.01', 'name': 'nuclear_rocket'}, {'id': 9478, 'synset': 'nuclear_weapon.n.01', 'name': 'nuclear_weapon'}, {'id': 9479, 'synset': 'nude.n.01', 'name': 'nude'}, {'id': 9480, 'synset': 'numdah.n.01', 'name': 'numdah'}, {'id': 9481, 'synset': "nun's_habit.n.01", 'name': "nun's_habit"}, {'id': 9482, 'synset': 'nursery.n.01', 'name': 'nursery'}, {'id': 9483, 'synset': 'nut_and_bolt.n.01', 'name': 'nut_and_bolt'}, {'id': 9484, 'synset': 'nylon.n.02', 'name': 'nylon'}, {'id': 9485, 'synset': 'nylons.n.01', 'name': 'nylons'}, {'id': 9486, 'synset': 'oast.n.01', 'name': 'oast'}, {'id': 9487, 'synset': 'oast_house.n.01', 'name': 'oast_house'}, {'id': 9488, 'synset': 'obelisk.n.01', 'name': 'obelisk'}, {'id': 9489, 'synset': 'object_ball.n.01', 'name': 'object_ball'}, {'id': 9490, 'synset': 'objective.n.02', 'name': 'objective'}, {'id': 9491, 'synset': 'oblique_bandage.n.01', 'name': 'oblique_bandage'}, {'id': 9492, 'synset': 'oboe.n.01', 'name': 'oboe'}, {'id': 9493, 'synset': 'oboe_da_caccia.n.01', 'name': 'oboe_da_caccia'}, {'id': 9494, 'synset': "oboe_d'amore.n.01", 'name': "oboe_d'amore"}, {'id': 9495, 'synset': 'observation_dome.n.01', 'name': 'observation_dome'}, {'id': 9496, 'synset': 'observatory.n.01', 'name': 'observatory'}, {'id': 9497, 'synset': 'obstacle.n.02', 'name': 'obstacle'}, {'id': 9498, 'synset': 'obturator.n.01', 'name': 'obturator'}, {'id': 9499, 'synset': 'ocarina.n.01', 'name': 'ocarina'}, {'id': 9500, 'synset': 'octant.n.01', 'name': 'octant'}, {'id': 9501, 'synset': 'odd-leg_caliper.n.01', 'name': 'odd-leg_caliper'}, {'id': 9502, 'synset': 'odometer.n.01', 'name': 'odometer'}, {'id': 9503, 'synset': 'oeil_de_boeuf.n.01', 'name': 'oeil_de_boeuf'}, {'id': 9504, 'synset': 'office.n.01', 'name': 'office'}, {'id': 9505, 'synset': 'office_building.n.01', 'name': 'office_building'}, {'id': 9506, 'synset': 'office_furniture.n.01', 'name': 'office_furniture'}, {'id': 9507, 'synset': "officer's_mess.n.01", 'name': "officer's_mess"}, {'id': 9508, 'synset': 'off-line_equipment.n.01', 'name': 'off-line_equipment'}, {'id': 9509, 'synset': 'ogee.n.01', 'name': 'ogee'}, {'id': 9510, 'synset': 'ogee_arch.n.01', 'name': 'ogee_arch'}, {'id': 9511, 'synset': 'ohmmeter.n.01', 'name': 'ohmmeter'}, {'id': 9512, 'synset': 'oil.n.02', 'name': 'oil'}, {'id': 9513, 'synset': 'oilcan.n.01', 'name': 'oilcan'}, {'id': 9514, 'synset': 'oilcloth.n.01', 'name': 'oilcloth'}, {'id': 9515, 'synset': 'oil_filter.n.01', 'name': 'oil_filter'}, {'id': 9516, 'synset': 'oil_heater.n.01', 'name': 'oil_heater'}, {'id': 9517, 'synset': 'oil_paint.n.01', 'name': 'oil_paint'}, {'id': 9518, 'synset': 'oil_pump.n.01', 'name': 'oil_pump'}, {'id': 9519, 'synset': 'oil_refinery.n.01', 'name': 'oil_refinery'}, {'id': 9520, 'synset': 'oilskin.n.01', 'name': 'oilskin'}, {'id': 9521, 'synset': 'oil_slick.n.01', 'name': 'oil_slick'}, {'id': 9522, 'synset': 'oilstone.n.01', 'name': 'oilstone'}, {'id': 9523, 'synset': 'oil_tanker.n.01', 'name': 'oil_tanker'}, {'id': 9524, 'synset': 'old_school_tie.n.01', 'name': 'old_school_tie'}, {'id': 9525, 'synset': 'olive_drab.n.03', 'name': 'olive_drab'}, {'id': 9526, 'synset': 'olive_drab.n.02', 'name': 'olive_drab'}, {'id': 9527, 'synset': 'olympian_zeus.n.01', 'name': 'Olympian_Zeus'}, {'id': 9528, 'synset': 'omelet_pan.n.01', 'name': 'omelet_pan'}, {'id': 9529, 'synset': 'omnidirectional_antenna.n.01', 'name': 'omnidirectional_antenna'}, {'id': 9530, 'synset': 'omnirange.n.01', 'name': 'omnirange'}, {'id': 9531, 'synset': 'onion_dome.n.01', 'name': 'onion_dome'}, {'id': 9532, 'synset': 'open-air_market.n.01', 'name': 'open-air_market'}, {'id': 9533, 'synset': 'open_circuit.n.01', 'name': 'open_circuit'}, {'id': 9534, 'synset': 'open-end_wrench.n.01', 'name': 'open-end_wrench'}, {'id': 9535, 'synset': 'opener.n.03', 'name': 'opener'}, {'id': 9536, 'synset': 'open-hearth_furnace.n.01', 'name': 'open-hearth_furnace'}, {'id': 9537, 'synset': 'openside_plane.n.01', 'name': 'openside_plane'}, {'id': 9538, 'synset': 'open_sight.n.01', 'name': 'open_sight'}, {'id': 9539, 'synset': 'openwork.n.01', 'name': 'openwork'}, {'id': 9540, 'synset': 'opera.n.03', 'name': 'opera'}, {'id': 9541, 'synset': 'opera_cloak.n.01', 'name': 'opera_cloak'}, {'id': 9542, 'synset': 'operating_microscope.n.01', 'name': 'operating_microscope'}, {'id': 9543, 'synset': 'operating_room.n.01', 'name': 'operating_room'}, {'id': 9544, 'synset': 'operating_table.n.01', 'name': 'operating_table'}, {'id': 9545, 'synset': 'ophthalmoscope.n.01', 'name': 'ophthalmoscope'}, {'id': 9546, 'synset': 'optical_device.n.01', 'name': 'optical_device'}, {'id': 9547, 'synset': 'optical_disk.n.01', 'name': 'optical_disk'}, {'id': 9548, 'synset': 'optical_instrument.n.01', 'name': 'optical_instrument'}, {'id': 9549, 'synset': 'optical_pyrometer.n.01', 'name': 'optical_pyrometer'}, {'id': 9550, 'synset': 'optical_telescope.n.01', 'name': 'optical_telescope'}, {'id': 9551, 'synset': 'orchestra_pit.n.01', 'name': 'orchestra_pit'}, {'id': 9552, 'synset': 'ordinary.n.04', 'name': 'ordinary'}, {'id': 9553, 'synset': 'organ.n.05', 'name': 'organ'}, {'id': 9554, 'synset': 'organdy.n.01', 'name': 'organdy'}, {'id': 9555, 'synset': 'organic_light-emitting_diode.n.01', 'name': 'organic_light-emitting_diode'}, {'id': 9556, 'synset': 'organ_loft.n.01', 'name': 'organ_loft'}, {'id': 9557, 'synset': 'organ_pipe.n.01', 'name': 'organ_pipe'}, {'id': 9558, 'synset': 'organza.n.01', 'name': 'organza'}, {'id': 9559, 'synset': 'oriel.n.01', 'name': 'oriel'}, {'id': 9560, 'synset': 'oriflamme.n.02', 'name': 'oriflamme'}, {'id': 9561, 'synset': 'o_ring.n.01', 'name': 'O_ring'}, {'id': 9562, 'synset': 'orlon.n.01', 'name': 'Orlon'}, {'id': 9563, 'synset': 'orlop_deck.n.01', 'name': 'orlop_deck'}, {'id': 9564, 'synset': 'orphanage.n.02', 'name': 'orphanage'}, {'id': 9565, 'synset': 'orphrey.n.01', 'name': 'orphrey'}, {'id': 9566, 'synset': 'orrery.n.01', 'name': 'orrery'}, {'id': 9567, 'synset': 'orthicon.n.01', 'name': 'orthicon'}, {'id': 9568, 'synset': 'orthochromatic_film.n.01', 'name': 'orthochromatic_film'}, {'id': 9569, 'synset': 'orthopter.n.01', 'name': 'orthopter'}, {'id': 9570, 'synset': 'orthoscope.n.01', 'name': 'orthoscope'}, {'id': 9571, 'synset': 'oscillograph.n.01', 'name': 'oscillograph'}, {'id': 9572, 'synset': 'oscilloscope.n.01', 'name': 'oscilloscope'}, {'id': 9573, 'synset': 'ossuary.n.01', 'name': 'ossuary'}, {'id': 9574, 'synset': 'otoscope.n.01', 'name': 'otoscope'}, {'id': 9575, 'synset': 'oubliette.n.01', 'name': 'oubliette'}, {'id': 9576, 'synset': 'out-basket.n.01', 'name': 'out-basket'}, {'id': 9577, 'synset': 'outboard_motor.n.01', 'name': 'outboard_motor'}, {'id': 9578, 'synset': 'outboard_motorboat.n.01', 'name': 'outboard_motorboat'}, {'id': 9579, 'synset': 'outbuilding.n.01', 'name': 'outbuilding'}, {'id': 9580, 'synset': 'outerwear.n.01', 'name': 'outerwear'}, {'id': 9581, 'synset': 'outfall.n.01', 'name': 'outfall'}, {'id': 9582, 'synset': 'outfit.n.02', 'name': 'outfit'}, {'id': 9583, 'synset': 'outfitter.n.02', 'name': 'outfitter'}, {'id': 9584, 'synset': 'outhouse.n.01', 'name': 'outhouse'}, {'id': 9585, 'synset': 'output_device.n.01', 'name': 'output_device'}, {'id': 9586, 'synset': 'outrigger.n.01', 'name': 'outrigger'}, {'id': 9587, 'synset': 'outrigger_canoe.n.01', 'name': 'outrigger_canoe'}, {'id': 9588, 'synset': 'outside_caliper.n.01', 'name': 'outside_caliper'}, {'id': 9589, 'synset': 'outside_mirror.n.01', 'name': 'outside_mirror'}, {'id': 9590, 'synset': 'outwork.n.01', 'name': 'outwork'}, {'id': 9591, 'synset': 'oven_thermometer.n.01', 'name': 'oven_thermometer'}, {'id': 9592, 'synset': 'overall.n.02', 'name': 'overall'}, {'id': 9593, 'synset': 'overcoat.n.02', 'name': 'overcoat'}, {'id': 9594, 'synset': 'overdrive.n.02', 'name': 'overdrive'}, {'id': 9595, 'synset': 'overgarment.n.01', 'name': 'overgarment'}, {'id': 9596, 'synset': 'overhand_knot.n.01', 'name': 'overhand_knot'}, {'id': 9597, 'synset': 'overhang.n.01', 'name': 'overhang'}, {'id': 9598, 'synset': 'overhead_projector.n.01', 'name': 'overhead_projector'}, {'id': 9599, 'synset': 'overmantel.n.01', 'name': 'overmantel'}, {'id': 9600, 'synset': 'overnighter.n.02', 'name': 'overnighter'}, {'id': 9601, 'synset': 'overpass.n.01', 'name': 'overpass'}, {'id': 9602, 'synset': 'override.n.01', 'name': 'override'}, {'id': 9603, 'synset': 'overshoe.n.01', 'name': 'overshoe'}, {'id': 9604, 'synset': 'overskirt.n.01', 'name': 'overskirt'}, {'id': 9605, 'synset': 'oxbow.n.03', 'name': 'oxbow'}, {'id': 9606, 'synset': 'oxbridge.n.01', 'name': 'Oxbridge'}, {'id': 9607, 'synset': 'oxcart.n.01', 'name': 'oxcart'}, {'id': 9608, 'synset': 'oxeye.n.03', 'name': 'oxeye'}, {'id': 9609, 'synset': 'oxford.n.04', 'name': 'oxford'}, {'id': 9610, 'synset': 'oximeter.n.01', 'name': 'oximeter'}, {'id': 9611, 'synset': 'oxyacetylene_torch.n.01', 'name': 'oxyacetylene_torch'}, {'id': 9612, 'synset': 'oxygen_mask.n.01', 'name': 'oxygen_mask'}, {'id': 9613, 'synset': 'oyster_bar.n.01', 'name': 'oyster_bar'}, {'id': 9614, 'synset': 'oyster_bed.n.01', 'name': 'oyster_bed'}, {'id': 9615, 'synset': 'pace_car.n.01', 'name': 'pace_car'}, {'id': 9616, 'synset': 'pacemaker.n.03', 'name': 'pacemaker'}, {'id': 9617, 'synset': 'pack.n.03', 'name': 'pack'}, {'id': 9618, 'synset': 'pack.n.09', 'name': 'pack'}, {'id': 9619, 'synset': 'pack.n.07', 'name': 'pack'}, {'id': 9620, 'synset': 'package.n.02', 'name': 'package'}, {'id': 9621, 'synset': 'package_store.n.01', 'name': 'package_store'}, {'id': 9622, 'synset': 'packaging.n.03', 'name': 'packaging'}, {'id': 9623, 'synset': 'packing_box.n.02', 'name': 'packing_box'}, {'id': 9624, 'synset': 'packinghouse.n.02', 'name': 'packinghouse'}, {'id': 9625, 'synset': 'packinghouse.n.01', 'name': 'packinghouse'}, {'id': 9626, 'synset': 'packing_needle.n.01', 'name': 'packing_needle'}, {'id': 9627, 'synset': 'packsaddle.n.01', 'name': 'packsaddle'}, {'id': 9628, 'synset': 'paddle.n.02', 'name': 'paddle'}, {'id': 9629, 'synset': 'paddle.n.01', 'name': 'paddle'}, {'id': 9630, 'synset': 'paddle_box.n.01', 'name': 'paddle_box'}, {'id': 9631, 'synset': 'paddle_steamer.n.01', 'name': 'paddle_steamer'}, {'id': 9632, 'synset': 'paddlewheel.n.01', 'name': 'paddlewheel'}, {'id': 9633, 'synset': 'paddock.n.01', 'name': 'paddock'}, {'id': 9634, 'synset': 'page_printer.n.01', 'name': 'page_printer'}, {'id': 9635, 'synset': 'paint.n.01', 'name': 'paint'}, {'id': 9636, 'synset': 'paintball.n.01', 'name': 'paintball'}, {'id': 9637, 'synset': 'paintball_gun.n.01', 'name': 'paintball_gun'}, {'id': 9638, 'synset': 'paintbox.n.01', 'name': 'paintbox'}, {'id': 9639, 'synset': 'paisley.n.01', 'name': 'paisley'}, {'id': 9640, 'synset': 'pajama.n.01', 'name': 'pajama'}, {'id': 9641, 'synset': 'palace.n.04', 'name': 'palace'}, {'id': 9642, 'synset': 'palace.n.01', 'name': 'palace'}, {'id': 9643, 'synset': 'palace.n.03', 'name': 'palace'}, {'id': 9644, 'synset': 'palanquin.n.01', 'name': 'palanquin'}, {'id': 9645, 'synset': 'paleolith.n.01', 'name': 'paleolith'}, {'id': 9646, 'synset': 'palestra.n.01', 'name': 'palestra'}, {'id': 9647, 'synset': 'palette_knife.n.01', 'name': 'palette_knife'}, {'id': 9648, 'synset': 'palisade.n.01', 'name': 'palisade'}, {'id': 9649, 'synset': 'pallet.n.03', 'name': 'pallet'}, {'id': 9650, 'synset': 'pallette.n.01', 'name': 'pallette'}, {'id': 9651, 'synset': 'pallium.n.04', 'name': 'pallium'}, {'id': 9652, 'synset': 'pallium.n.03', 'name': 'pallium'}, {'id': 9653, 'synset': 'pancake_turner.n.01', 'name': 'pancake_turner'}, {'id': 9654, 'synset': 'panchromatic_film.n.01', 'name': 'panchromatic_film'}, {'id': 9655, 'synset': 'panda_car.n.01', 'name': 'panda_car'}, {'id': 9656, 'synset': 'paneling.n.01', 'name': 'paneling'}, {'id': 9657, 'synset': 'panhandle.n.02', 'name': 'panhandle'}, {'id': 9658, 'synset': 'panic_button.n.01', 'name': 'panic_button'}, {'id': 9659, 'synset': 'pannier.n.02', 'name': 'pannier'}, {'id': 9660, 'synset': 'pannier.n.01', 'name': 'pannier'}, {'id': 9661, 'synset': 'pannikin.n.01', 'name': 'pannikin'}, {'id': 9662, 'synset': 'panopticon.n.02', 'name': 'panopticon'}, {'id': 9663, 'synset': 'panopticon.n.01', 'name': 'panopticon'}, {'id': 9664, 'synset': 'panpipe.n.01', 'name': 'panpipe'}, {'id': 9665, 'synset': 'pantaloon.n.03', 'name': 'pantaloon'}, {'id': 9666, 'synset': 'pantechnicon.n.01', 'name': 'pantechnicon'}, {'id': 9667, 'synset': 'pantheon.n.03', 'name': 'pantheon'}, {'id': 9668, 'synset': 'pantheon.n.02', 'name': 'pantheon'}, {'id': 9669, 'synset': 'pantie.n.01', 'name': 'pantie'}, {'id': 9670, 'synset': 'panting.n.02', 'name': 'panting'}, {'id': 9671, 'synset': 'pant_leg.n.01', 'name': 'pant_leg'}, {'id': 9672, 'synset': 'pantograph.n.01', 'name': 'pantograph'}, {'id': 9673, 'synset': 'pantry.n.01', 'name': 'pantry'}, {'id': 9674, 'synset': 'pants_suit.n.01', 'name': 'pants_suit'}, {'id': 9675, 'synset': 'panty_girdle.n.01', 'name': 'panty_girdle'}, {'id': 9676, 'synset': 'panzer.n.01', 'name': 'panzer'}, {'id': 9677, 'synset': 'paper_chain.n.01', 'name': 'paper_chain'}, {'id': 9678, 'synset': 'paper_clip.n.01', 'name': 'paper_clip'}, {'id': 9679, 'synset': 'paper_cutter.n.01', 'name': 'paper_cutter'}, {'id': 9680, 'synset': 'paper_fastener.n.01', 'name': 'paper_fastener'}, {'id': 9681, 'synset': 'paper_feed.n.01', 'name': 'paper_feed'}, {'id': 9682, 'synset': 'paper_mill.n.01', 'name': 'paper_mill'}, {'id': 9683, 'synset': 'parabolic_mirror.n.01', 'name': 'parabolic_mirror'}, {'id': 9684, 'synset': 'parabolic_reflector.n.01', 'name': 'parabolic_reflector'}, {'id': 9685, 'synset': 'parallel_bars.n.01', 'name': 'parallel_bars'}, {'id': 9686, 'synset': 'parallel_circuit.n.01', 'name': 'parallel_circuit'}, {'id': 9687, 'synset': 'parallel_interface.n.01', 'name': 'parallel_interface'}, {'id': 9688, 'synset': 'parang.n.01', 'name': 'parang'}, {'id': 9689, 'synset': 'parapet.n.02', 'name': 'parapet'}, {'id': 9690, 'synset': 'parapet.n.01', 'name': 'parapet'}, {'id': 9691, 'synset': 'parer.n.02', 'name': 'parer'}, {'id': 9692, 'synset': 'parfait_glass.n.01', 'name': 'parfait_glass'}, {'id': 9693, 'synset': 'pargeting.n.02', 'name': 'pargeting'}, {'id': 9694, 'synset': 'pari-mutuel_machine.n.01', 'name': 'pari-mutuel_machine'}, {'id': 9695, 'synset': 'park_bench.n.01', 'name': 'park_bench'}, {'id': 9696, 'synset': 'parlor.n.01', 'name': 'parlor'}, {'id': 9697, 'synset': 'parquet.n.01', 'name': 'parquet'}, {'id': 9698, 'synset': 'parquetry.n.01', 'name': 'parquetry'}, {'id': 9699, 'synset': 'parsonage.n.01', 'name': 'parsonage'}, {'id': 9700, 'synset': 'parsons_table.n.01', 'name': 'Parsons_table'}, {'id': 9701, 'synset': 'partial_denture.n.01', 'name': 'partial_denture'}, {'id': 9702, 'synset': 'particle_detector.n.01', 'name': 'particle_detector'}, {'id': 9703, 'synset': 'partition.n.01', 'name': 'partition'}, {'id': 9704, 'synset': 'parts_bin.n.01', 'name': 'parts_bin'}, {'id': 9705, 'synset': 'party_line.n.02', 'name': 'party_line'}, {'id': 9706, 'synset': 'party_wall.n.01', 'name': 'party_wall'}, {'id': 9707, 'synset': 'parvis.n.01', 'name': 'parvis'}, {'id': 9708, 'synset': 'passenger_train.n.01', 'name': 'passenger_train'}, {'id': 9709, 'synset': 'passenger_van.n.01', 'name': 'passenger_van'}, {'id': 9710, 'synset': 'passe-partout.n.02', 'name': 'passe-partout'}, {'id': 9711, 'synset': 'passive_matrix_display.n.01', 'name': 'passive_matrix_display'}, {'id': 9712, 'synset': 'passkey.n.01', 'name': 'passkey'}, {'id': 9713, 'synset': 'pass-through.n.01', 'name': 'pass-through'}, {'id': 9714, 'synset': 'pastry_cart.n.01', 'name': 'pastry_cart'}, {'id': 9715, 'synset': 'patch.n.03', 'name': 'patch'}, {'id': 9716, 'synset': 'patchcord.n.01', 'name': 'patchcord'}, {'id': 9717, 'synset': 'patchouli.n.02', 'name': 'patchouli'}, {'id': 9718, 'synset': 'patch_pocket.n.01', 'name': 'patch_pocket'}, {'id': 9719, 'synset': 'patchwork.n.02', 'name': 'patchwork'}, {'id': 9720, 'synset': 'patent_log.n.01', 'name': 'patent_log'}, {'id': 9721, 'synset': 'paternoster.n.02', 'name': 'paternoster'}, {'id': 9722, 'synset': 'patina.n.01', 'name': 'patina'}, {'id': 9723, 'synset': 'patio.n.01', 'name': 'patio'}, {'id': 9724, 'synset': 'patisserie.n.01', 'name': 'patisserie'}, {'id': 9725, 'synset': 'patka.n.01', 'name': 'patka'}, {'id': 9726, 'synset': 'patrol_boat.n.01', 'name': 'patrol_boat'}, {'id': 9727, 'synset': 'patty-pan.n.01', 'name': 'patty-pan'}, {'id': 9728, 'synset': 'pave.n.01', 'name': 'pave'}, {'id': 9729, 'synset': 'pavilion.n.01', 'name': 'pavilion'}, {'id': 9730, 'synset': 'pavior.n.01', 'name': 'pavior'}, {'id': 9731, 'synset': 'pavis.n.01', 'name': 'pavis'}, {'id': 9732, 'synset': 'pawn.n.03', 'name': 'pawn'}, {'id': 9733, 'synset': "pawnbroker's_shop.n.01", 'name': "pawnbroker's_shop"}, {'id': 9734, 'synset': 'pay-phone.n.01', 'name': 'pay-phone'}, {'id': 9735, 'synset': 'pc_board.n.01', 'name': 'PC_board'}, {'id': 9736, 'synset': 'peach_orchard.n.01', 'name': 'peach_orchard'}, {'id': 9737, 'synset': 'pea_jacket.n.01', 'name': 'pea_jacket'}, {'id': 9738, 'synset': 'peavey.n.01', 'name': 'peavey'}, {'id': 9739, 'synset': 'pectoral.n.02', 'name': 'pectoral'}, {'id': 9740, 'synset': 'pedal.n.02', 'name': 'pedal'}, {'id': 9741, 'synset': 'pedal_pusher.n.01', 'name': 'pedal_pusher'}, {'id': 9742, 'synset': 'pedestal.n.03', 'name': 'pedestal'}, {'id': 9743, 'synset': 'pedestal_table.n.01', 'name': 'pedestal_table'}, {'id': 9744, 'synset': 'pedestrian_crossing.n.01', 'name': 'pedestrian_crossing'}, {'id': 9745, 'synset': 'pedicab.n.01', 'name': 'pedicab'}, {'id': 9746, 'synset': 'pediment.n.01', 'name': 'pediment'}, {'id': 9747, 'synset': 'pedometer.n.01', 'name': 'pedometer'}, {'id': 9748, 'synset': 'peep_sight.n.01', 'name': 'peep_sight'}, {'id': 9749, 'synset': 'peg.n.01', 'name': 'peg'}, {'id': 9750, 'synset': 'peg.n.06', 'name': 'peg'}, {'id': 9751, 'synset': 'peg.n.05', 'name': 'peg'}, {'id': 9752, 'synset': 'pelham.n.01', 'name': 'Pelham'}, {'id': 9753, 'synset': 'pelican_crossing.n.01', 'name': 'pelican_crossing'}, {'id': 9754, 'synset': 'pelisse.n.01', 'name': 'pelisse'}, {'id': 9755, 'synset': 'pelvimeter.n.01', 'name': 'pelvimeter'}, {'id': 9756, 'synset': 'penal_colony.n.01', 'name': 'penal_colony'}, {'id': 9757, 'synset': 'penal_institution.n.01', 'name': 'penal_institution'}, {'id': 9758, 'synset': 'penalty_box.n.01', 'name': 'penalty_box'}, {'id': 9759, 'synset': 'pen-and-ink.n.01', 'name': 'pen-and-ink'}, {'id': 9760, 'synset': 'pencil.n.04', 'name': 'pencil'}, {'id': 9761, 'synset': 'pendant_earring.n.01', 'name': 'pendant_earring'}, {'id': 9762, 'synset': 'pendulum_clock.n.01', 'name': 'pendulum_clock'}, {'id': 9763, 'synset': 'pendulum_watch.n.01', 'name': 'pendulum_watch'}, {'id': 9764, 'synset': 'penetration_bomb.n.01', 'name': 'penetration_bomb'}, {'id': 9765, 'synset': 'penile_implant.n.01', 'name': 'penile_implant'}, {'id': 9766, 'synset': 'penitentiary.n.01', 'name': 'penitentiary'}, {'id': 9767, 'synset': 'penknife.n.01', 'name': 'penknife'}, {'id': 9768, 'synset': 'penlight.n.01', 'name': 'penlight'}, {'id': 9769, 'synset': 'pennant.n.03', 'name': 'pennant'}, {'id': 9770, 'synset': 'pennywhistle.n.01', 'name': 'pennywhistle'}, {'id': 9771, 'synset': 'penthouse.n.01', 'name': 'penthouse'}, {'id': 9772, 'synset': 'pentode.n.01', 'name': 'pentode'}, {'id': 9773, 'synset': 'peplos.n.01', 'name': 'peplos'}, {'id': 9774, 'synset': 'peplum.n.01', 'name': 'peplum'}, {'id': 9775, 'synset': 'pepper_shaker.n.01', 'name': 'pepper_shaker'}, {'id': 9776, 'synset': 'pepper_spray.n.01', 'name': 'pepper_spray'}, {'id': 9777, 'synset': 'percale.n.01', 'name': 'percale'}, {'id': 9778, 'synset': 'percolator.n.01', 'name': 'percolator'}, {'id': 9779, 'synset': 'percussion_cap.n.01', 'name': 'percussion_cap'}, {'id': 9780, 'synset': 'percussion_instrument.n.01', 'name': 'percussion_instrument'}, {'id': 9781, 'synset': 'perforation.n.01', 'name': 'perforation'}, {'id': 9782, 'synset': 'perfumery.n.03', 'name': 'perfumery'}, {'id': 9783, 'synset': 'perfumery.n.02', 'name': 'perfumery'}, {'id': 9784, 'synset': 'perfumery.n.01', 'name': 'perfumery'}, {'id': 9785, 'synset': 'peripheral.n.01', 'name': 'peripheral'}, {'id': 9786, 'synset': 'periscope.n.01', 'name': 'periscope'}, {'id': 9787, 'synset': 'peristyle.n.01', 'name': 'peristyle'}, {'id': 9788, 'synset': 'periwig.n.01', 'name': 'periwig'}, {'id': 9789, 'synset': 'permanent_press.n.01', 'name': 'permanent_press'}, {'id': 9790, 'synset': 'perpetual_motion_machine.n.01', 'name': 'perpetual_motion_machine'}, {'id': 9791, 'synset': 'personal_computer.n.01', 'name': 'personal_computer'}, {'id': 9792, 'synset': 'personal_digital_assistant.n.01', 'name': 'personal_digital_assistant'}, {'id': 9793, 'synset': 'personnel_carrier.n.01', 'name': 'personnel_carrier'}, {'id': 9794, 'synset': 'pestle.n.03', 'name': 'pestle'}, {'id': 9795, 'synset': 'pestle.n.02', 'name': 'pestle'}, {'id': 9796, 'synset': 'petcock.n.01', 'name': 'petcock'}, {'id': 9797, 'synset': 'petri_dish.n.01', 'name': 'Petri_dish'}, {'id': 9798, 'synset': 'petrolatum_gauze.n.01', 'name': 'petrolatum_gauze'}, {'id': 9799, 'synset': 'pet_shop.n.01', 'name': 'pet_shop'}, {'id': 9800, 'synset': 'petticoat.n.01', 'name': 'petticoat'}, {'id': 9801, 'synset': 'phial.n.01', 'name': 'phial'}, {'id': 9802, 'synset': 'phillips_screw.n.01', 'name': 'Phillips_screw'}, {'id': 9803, 'synset': 'phillips_screwdriver.n.01', 'name': 'Phillips_screwdriver'}, {'id': 9804, 'synset': 'phonograph_needle.n.01', 'name': 'phonograph_needle'}, {'id': 9805, 'synset': 'photocathode.n.01', 'name': 'photocathode'}, {'id': 9806, 'synset': 'photocoagulator.n.01', 'name': 'photocoagulator'}, {'id': 9807, 'synset': 'photocopier.n.01', 'name': 'photocopier'}, {'id': 9808, 'synset': 'photographic_equipment.n.01', 'name': 'photographic_equipment'}, {'id': 9809, 'synset': 'photographic_paper.n.01', 'name': 'photographic_paper'}, {'id': 9810, 'synset': 'photometer.n.01', 'name': 'photometer'}, {'id': 9811, 'synset': 'photomicrograph.n.01', 'name': 'photomicrograph'}, {'id': 9812, 'synset': 'photostat.n.02', 'name': 'Photostat'}, {'id': 9813, 'synset': 'photostat.n.01', 'name': 'photostat'}, {'id': 9814, 'synset': 'physical_pendulum.n.01', 'name': 'physical_pendulum'}, {'id': 9815, 'synset': 'piano_action.n.01', 'name': 'piano_action'}, {'id': 9816, 'synset': 'piano_keyboard.n.01', 'name': 'piano_keyboard'}, {'id': 9817, 'synset': 'piano_wire.n.01', 'name': 'piano_wire'}, {'id': 9818, 'synset': 'piccolo.n.01', 'name': 'piccolo'}, {'id': 9819, 'synset': 'pick.n.07', 'name': 'pick'}, {'id': 9820, 'synset': 'pick.n.06', 'name': 'pick'}, {'id': 9821, 'synset': 'pick.n.05', 'name': 'pick'}, {'id': 9822, 'synset': 'pickelhaube.n.01', 'name': 'pickelhaube'}, {'id': 9823, 'synset': 'picket_boat.n.01', 'name': 'picket_boat'}, {'id': 9824, 'synset': 'picket_fence.n.01', 'name': 'picket_fence'}, {'id': 9825, 'synset': 'picket_ship.n.01', 'name': 'picket_ship'}, {'id': 9826, 'synset': 'pickle_barrel.n.01', 'name': 'pickle_barrel'}, {'id': 9827, 'synset': 'picture_frame.n.01', 'name': 'picture_frame'}, {'id': 9828, 'synset': 'picture_hat.n.01', 'name': 'picture_hat'}, {'id': 9829, 'synset': 'picture_rail.n.01', 'name': 'picture_rail'}, {'id': 9830, 'synset': 'picture_window.n.01', 'name': 'picture_window'}, {'id': 9831, 'synset': 'piece_of_cloth.n.01', 'name': 'piece_of_cloth'}, {'id': 9832, 'synset': 'pied-a-terre.n.01', 'name': 'pied-a-terre'}, {'id': 9833, 'synset': 'pier.n.03', 'name': 'pier'}, {'id': 9834, 'synset': 'pier.n.02', 'name': 'pier'}, {'id': 9835, 'synset': 'pier_arch.n.01', 'name': 'pier_arch'}, {'id': 9836, 'synset': 'pier_glass.n.01', 'name': 'pier_glass'}, {'id': 9837, 'synset': 'pier_table.n.01', 'name': 'pier_table'}, {'id': 9838, 'synset': 'pieta.n.01', 'name': 'pieta'}, {'id': 9839, 'synset': 'piezometer.n.01', 'name': 'piezometer'}, {'id': 9840, 'synset': 'pig_bed.n.01', 'name': 'pig_bed'}, {'id': 9841, 'synset': 'piggery.n.01', 'name': 'piggery'}, {'id': 9842, 'synset': 'pilaster.n.01', 'name': 'pilaster'}, {'id': 9843, 'synset': 'pile.n.06', 'name': 'pile'}, {'id': 9844, 'synset': 'pile_driver.n.01', 'name': 'pile_driver'}, {'id': 9845, 'synset': 'pill_bottle.n.01', 'name': 'pill_bottle'}, {'id': 9846, 'synset': 'pillbox.n.01', 'name': 'pillbox'}, {'id': 9847, 'synset': 'pillion.n.01', 'name': 'pillion'}, {'id': 9848, 'synset': 'pillory.n.01', 'name': 'pillory'}, {'id': 9849, 'synset': 'pillow_block.n.01', 'name': 'pillow_block'}, {'id': 9850, 'synset': 'pillow_lace.n.01', 'name': 'pillow_lace'}, {'id': 9851, 'synset': 'pillow_sham.n.01', 'name': 'pillow_sham'}, {'id': 9852, 'synset': 'pilot_bit.n.01', 'name': 'pilot_bit'}, {'id': 9853, 'synset': 'pilot_boat.n.01', 'name': 'pilot_boat'}, {'id': 9854, 'synset': 'pilot_burner.n.01', 'name': 'pilot_burner'}, {'id': 9855, 'synset': 'pilot_cloth.n.01', 'name': 'pilot_cloth'}, {'id': 9856, 'synset': 'pilot_engine.n.01', 'name': 'pilot_engine'}, {'id': 9857, 'synset': 'pilothouse.n.01', 'name': 'pilothouse'}, {'id': 9858, 'synset': 'pilot_light.n.02', 'name': 'pilot_light'}, {'id': 9859, 'synset': 'pin.n.08', 'name': 'pin'}, {'id': 9860, 'synset': 'pin.n.07', 'name': 'pin'}, {'id': 9861, 'synset': 'pinata.n.01', 'name': 'pinata'}, {'id': 9862, 'synset': 'pinball_machine.n.01', 'name': 'pinball_machine'}, {'id': 9863, 'synset': 'pince-nez.n.01', 'name': 'pince-nez'}, {'id': 9864, 'synset': 'pincer.n.01', 'name': 'pincer'}, {'id': 9865, 'synset': 'pinch_bar.n.01', 'name': 'pinch_bar'}, {'id': 9866, 'synset': 'pincurl_clip.n.01', 'name': 'pincurl_clip'}, {'id': 9867, 'synset': 'pinfold.n.01', 'name': 'pinfold'}, {'id': 9868, 'synset': 'pinhead.n.02', 'name': 'pinhead'}, {'id': 9869, 'synset': 'pinion.n.01', 'name': 'pinion'}, {'id': 9870, 'synset': 'pinnacle.n.01', 'name': 'pinnacle'}, {'id': 9871, 'synset': 'pinprick.n.02', 'name': 'pinprick'}, {'id': 9872, 'synset': 'pinstripe.n.03', 'name': 'pinstripe'}, {'id': 9873, 'synset': 'pinstripe.n.02', 'name': 'pinstripe'}, {'id': 9874, 'synset': 'pinstripe.n.01', 'name': 'pinstripe'}, {'id': 9875, 'synset': 'pintle.n.01', 'name': 'pintle'}, {'id': 9876, 'synset': 'pinwheel.n.02', 'name': 'pinwheel'}, {'id': 9877, 'synset': 'tabor_pipe.n.01', 'name': 'tabor_pipe'}, {'id': 9878, 'synset': 'pipe.n.04', 'name': 'pipe'}, {'id': 9879, 'synset': 'pipe_bomb.n.01', 'name': 'pipe_bomb'}, {'id': 9880, 'synset': 'pipe_cleaner.n.01', 'name': 'pipe_cleaner'}, {'id': 9881, 'synset': 'pipe_cutter.n.01', 'name': 'pipe_cutter'}, {'id': 9882, 'synset': 'pipefitting.n.01', 'name': 'pipefitting'}, {'id': 9883, 'synset': 'pipet.n.01', 'name': 'pipet'}, {'id': 9884, 'synset': 'pipe_vise.n.01', 'name': 'pipe_vise'}, {'id': 9885, 'synset': 'pipe_wrench.n.01', 'name': 'pipe_wrench'}, {'id': 9886, 'synset': 'pique.n.01', 'name': 'pique'}, {'id': 9887, 'synset': 'pirate.n.03', 'name': 'pirate'}, {'id': 9888, 'synset': 'piste.n.02', 'name': 'piste'}, {'id': 9889, 'synset': 'pistol_grip.n.01', 'name': 'pistol_grip'}, {'id': 9890, 'synset': 'piston.n.02', 'name': 'piston'}, {'id': 9891, 'synset': 'piston_ring.n.01', 'name': 'piston_ring'}, {'id': 9892, 'synset': 'piston_rod.n.01', 'name': 'piston_rod'}, {'id': 9893, 'synset': 'pit.n.07', 'name': 'pit'}, {'id': 9894, 'synset': 'pitching_wedge.n.01', 'name': 'pitching_wedge'}, {'id': 9895, 'synset': 'pitch_pipe.n.01', 'name': 'pitch_pipe'}, {'id': 9896, 'synset': 'pith_hat.n.01', 'name': 'pith_hat'}, {'id': 9897, 'synset': 'piton.n.01', 'name': 'piton'}, {'id': 9898, 'synset': 'pitot-static_tube.n.01', 'name': 'Pitot-static_tube'}, {'id': 9899, 'synset': 'pitot_tube.n.01', 'name': 'Pitot_tube'}, {'id': 9900, 'synset': 'pitsaw.n.01', 'name': 'pitsaw'}, {'id': 9901, 'synset': 'pivot.n.02', 'name': 'pivot'}, {'id': 9902, 'synset': 'pivoting_window.n.01', 'name': 'pivoting_window'}, {'id': 9903, 'synset': 'pizzeria.n.01', 'name': 'pizzeria'}, {'id': 9904, 'synset': 'place_of_business.n.01', 'name': 'place_of_business'}, {'id': 9905, 'synset': 'place_of_worship.n.01', 'name': 'place_of_worship'}, {'id': 9906, 'synset': 'placket.n.01', 'name': 'placket'}, {'id': 9907, 'synset': 'planchet.n.01', 'name': 'planchet'}, {'id': 9908, 'synset': 'plane.n.05', 'name': 'plane'}, {'id': 9909, 'synset': 'plane.n.04', 'name': 'plane'}, {'id': 9910, 'synset': 'plane_seat.n.01', 'name': 'plane_seat'}, {'id': 9911, 'synset': 'planetarium.n.03', 'name': 'planetarium'}, {'id': 9912, 'synset': 'planetarium.n.02', 'name': 'planetarium'}, {'id': 9913, 'synset': 'planetarium.n.01', 'name': 'planetarium'}, {'id': 9914, 'synset': 'planetary_gear.n.01', 'name': 'planetary_gear'}, {'id': 9915, 'synset': 'plank-bed.n.01', 'name': 'plank-bed'}, {'id': 9916, 'synset': 'planking.n.02', 'name': 'planking'}, {'id': 9917, 'synset': 'planner.n.02', 'name': 'planner'}, {'id': 9918, 'synset': 'plant.n.01', 'name': 'plant'}, {'id': 9919, 'synset': 'planter.n.03', 'name': 'planter'}, {'id': 9920, 'synset': 'plaster.n.05', 'name': 'plaster'}, {'id': 9921, 'synset': 'plasterboard.n.01', 'name': 'plasterboard'}, {'id': 9922, 'synset': 'plastering_trowel.n.01', 'name': 'plastering_trowel'}, {'id': 9923, 'synset': 'plastic_bag.n.01', 'name': 'plastic_bag'}, {'id': 9924, 'synset': 'plastic_bomb.n.01', 'name': 'plastic_bomb'}, {'id': 9925, 'synset': 'plastic_laminate.n.01', 'name': 'plastic_laminate'}, {'id': 9926, 'synset': 'plastic_wrap.n.01', 'name': 'plastic_wrap'}, {'id': 9927, 'synset': 'plastron.n.03', 'name': 'plastron'}, {'id': 9928, 'synset': 'plastron.n.02', 'name': 'plastron'}, {'id': 9929, 'synset': 'plastron.n.01', 'name': 'plastron'}, {'id': 9930, 'synset': 'plate.n.14', 'name': 'plate'}, {'id': 9931, 'synset': 'plate.n.13', 'name': 'plate'}, {'id': 9932, 'synset': 'plate.n.12', 'name': 'plate'}, {'id': 9933, 'synset': 'platen.n.03', 'name': 'platen'}, {'id': 9934, 'synset': 'platen.n.01', 'name': 'platen'}, {'id': 9935, 'synset': 'plate_rack.n.01', 'name': 'plate_rack'}, {'id': 9936, 'synset': 'plate_rail.n.01', 'name': 'plate_rail'}, {'id': 9937, 'synset': 'platform.n.01', 'name': 'platform'}, {'id': 9938, 'synset': 'platform.n.04', 'name': 'platform'}, {'id': 9939, 'synset': 'platform.n.03', 'name': 'platform'}, {'id': 9940, 'synset': 'platform_bed.n.01', 'name': 'platform_bed'}, {'id': 9941, 'synset': 'platform_rocker.n.01', 'name': 'platform_rocker'}, {'id': 9942, 'synset': 'plating.n.01', 'name': 'plating'}, {'id': 9943, 'synset': 'playback.n.02', 'name': 'playback'}, {'id': 9944, 'synset': 'playbox.n.01', 'name': 'playbox'}, {'id': 9945, 'synset': 'playground.n.02', 'name': 'playground'}, {'id': 9946, 'synset': 'playsuit.n.01', 'name': 'playsuit'}, {'id': 9947, 'synset': 'plaza.n.02', 'name': 'plaza'}, {'id': 9948, 'synset': 'pleat.n.01', 'name': 'pleat'}, {'id': 9949, 'synset': 'plenum.n.02', 'name': 'plenum'}, {'id': 9950, 'synset': 'plethysmograph.n.01', 'name': 'plethysmograph'}, {'id': 9951, 'synset': 'pleximeter.n.01', 'name': 'pleximeter'}, {'id': 9952, 'synset': 'plexor.n.01', 'name': 'plexor'}, {'id': 9953, 'synset': 'plimsoll.n.02', 'name': 'plimsoll'}, {'id': 9954, 'synset': 'plotter.n.04', 'name': 'plotter'}, {'id': 9955, 'synset': 'plug.n.01', 'name': 'plug'}, {'id': 9956, 'synset': 'plug.n.05', 'name': 'plug'}, {'id': 9957, 'synset': 'plug_fuse.n.01', 'name': 'plug_fuse'}, {'id': 9958, 'synset': 'plughole.n.01', 'name': 'plughole'}, {'id': 9959, 'synset': 'plumb_bob.n.01', 'name': 'plumb_bob'}, {'id': 9960, 'synset': 'plumb_level.n.01', 'name': 'plumb_level'}, {'id': 9961, 'synset': 'plunger.n.03', 'name': 'plunger'}, {'id': 9962, 'synset': 'plus_fours.n.01', 'name': 'plus_fours'}, {'id': 9963, 'synset': 'plush.n.01', 'name': 'plush'}, {'id': 9964, 'synset': 'plywood.n.01', 'name': 'plywood'}, {'id': 9965, 'synset': 'pneumatic_drill.n.01', 'name': 'pneumatic_drill'}, {'id': 9966, 'synset': 'p-n_junction.n.01', 'name': 'p-n_junction'}, {'id': 9967, 'synset': 'p-n-p_transistor.n.01', 'name': 'p-n-p_transistor'}, {'id': 9968, 'synset': 'poacher.n.02', 'name': 'poacher'}, {'id': 9969, 'synset': 'pocket.n.01', 'name': 'pocket'}, {'id': 9970, 'synset': 'pocket_battleship.n.01', 'name': 'pocket_battleship'}, {'id': 9971, 'synset': 'pocketcomb.n.01', 'name': 'pocketcomb'}, {'id': 9972, 'synset': 'pocket_flap.n.01', 'name': 'pocket_flap'}, {'id': 9973, 'synset': 'pocket-handkerchief.n.01', 'name': 'pocket-handkerchief'}, {'id': 9974, 'synset': 'pod.n.04', 'name': 'pod'}, {'id': 9975, 'synset': 'pogo_stick.n.01', 'name': 'pogo_stick'}, {'id': 9976, 'synset': 'point-and-shoot_camera.n.01', 'name': 'point-and-shoot_camera'}, {'id': 9977, 'synset': 'pointed_arch.n.01', 'name': 'pointed_arch'}, {'id': 9978, 'synset': 'pointing_trowel.n.01', 'name': 'pointing_trowel'}, {'id': 9979, 'synset': 'point_lace.n.01', 'name': 'point_lace'}, {'id': 9980, 'synset': 'polarimeter.n.01', 'name': 'polarimeter'}, {'id': 9981, 'synset': 'polaroid.n.01', 'name': 'Polaroid'}, {'id': 9982, 'synset': 'polaroid_camera.n.01', 'name': 'Polaroid_camera'}, {'id': 9983, 'synset': 'pole.n.09', 'name': 'pole'}, {'id': 9984, 'synset': 'poleax.n.02', 'name': 'poleax'}, {'id': 9985, 'synset': 'poleax.n.01', 'name': 'poleax'}, {'id': 9986, 'synset': 'police_boat.n.01', 'name': 'police_boat'}, {'id': 9987, 'synset': 'police_van.n.01', 'name': 'police_van'}, {'id': 9988, 'synset': 'polling_booth.n.01', 'name': 'polling_booth'}, {'id': 9989, 'synset': 'polo_ball.n.01', 'name': 'polo_ball'}, {'id': 9990, 'synset': 'polo_mallet.n.01', 'name': 'polo_mallet'}, {'id': 9991, 'synset': 'polonaise.n.01', 'name': 'polonaise'}, {'id': 9992, 'synset': 'polyester.n.03', 'name': 'polyester'}, {'id': 9993, 'synset': 'polygraph.n.01', 'name': 'polygraph'}, {'id': 9994, 'synset': 'pomade.n.01', 'name': 'pomade'}, {'id': 9995, 'synset': 'pommel_horse.n.01', 'name': 'pommel_horse'}, {'id': 9996, 'synset': 'pongee.n.01', 'name': 'pongee'}, {'id': 9997, 'synset': 'poniard.n.01', 'name': 'poniard'}, {'id': 9998, 'synset': 'pontifical.n.01', 'name': 'pontifical'}, {'id': 9999, 'synset': 'pontoon.n.01', 'name': 'pontoon'}, {'id': 10000, 'synset': 'pontoon_bridge.n.01', 'name': 'pontoon_bridge'}, {'id': 10001, 'synset': 'pony_cart.n.01', 'name': 'pony_cart'}, {'id': 10002, 'synset': 'pool_ball.n.01', 'name': 'pool_ball'}, {'id': 10003, 'synset': 'poolroom.n.01', 'name': 'poolroom'}, {'id': 10004, 'synset': 'poop_deck.n.01', 'name': 'poop_deck'}, {'id': 10005, 'synset': 'poor_box.n.01', 'name': 'poor_box'}, {'id': 10006, 'synset': 'poorhouse.n.01', 'name': 'poorhouse'}, {'id': 10007, 'synset': 'pop_bottle.n.01', 'name': 'pop_bottle'}, {'id': 10008, 'synset': 'popgun.n.01', 'name': 'popgun'}, {'id': 10009, 'synset': 'poplin.n.01', 'name': 'poplin'}, {'id': 10010, 'synset': 'popper.n.03', 'name': 'popper'}, {'id': 10011, 'synset': 'poppet.n.01', 'name': 'poppet'}, {'id': 10012, 'synset': 'pop_tent.n.01', 'name': 'pop_tent'}, {'id': 10013, 'synset': 'porcelain.n.01', 'name': 'porcelain'}, {'id': 10014, 'synset': 'porch.n.01', 'name': 'porch'}, {'id': 10015, 'synset': 'porkpie.n.01', 'name': 'porkpie'}, {'id': 10016, 'synset': 'porringer.n.01', 'name': 'porringer'}, {'id': 10017, 'synset': 'portable.n.01', 'name': 'portable'}, {'id': 10018, 'synset': 'portable_computer.n.01', 'name': 'portable_computer'}, {'id': 10019, 'synset': 'portable_circular_saw.n.01', 'name': 'portable_circular_saw'}, {'id': 10020, 'synset': 'portcullis.n.01', 'name': 'portcullis'}, {'id': 10021, 'synset': 'porte-cochere.n.02', 'name': 'porte-cochere'}, {'id': 10022, 'synset': 'porte-cochere.n.01', 'name': 'porte-cochere'}, {'id': 10023, 'synset': 'portfolio.n.01', 'name': 'portfolio'}, {'id': 10024, 'synset': 'porthole.n.01', 'name': 'porthole'}, {'id': 10025, 'synset': 'portico.n.01', 'name': 'portico'}, {'id': 10026, 'synset': 'portiere.n.01', 'name': 'portiere'}, {'id': 10027, 'synset': 'portmanteau.n.02', 'name': 'portmanteau'}, {'id': 10028, 'synset': 'portrait_camera.n.01', 'name': 'portrait_camera'}, {'id': 10029, 'synset': 'portrait_lens.n.01', 'name': 'portrait_lens'}, {'id': 10030, 'synset': 'positive_pole.n.02', 'name': 'positive_pole'}, {'id': 10031, 'synset': 'positive_pole.n.01', 'name': 'positive_pole'}, {'id': 10032, 'synset': 'positron_emission_tomography_scanner.n.01', 'name': 'positron_emission_tomography_scanner'}, {'id': 10033, 'synset': 'post.n.04', 'name': 'post'}, {'id': 10034, 'synset': 'postage_meter.n.01', 'name': 'postage_meter'}, {'id': 10035, 'synset': 'post_and_lintel.n.01', 'name': 'post_and_lintel'}, {'id': 10036, 'synset': 'post_chaise.n.01', 'name': 'post_chaise'}, {'id': 10037, 'synset': 'postern.n.01', 'name': 'postern'}, {'id': 10038, 'synset': 'post_exchange.n.01', 'name': 'post_exchange'}, {'id': 10039, 'synset': 'posthole_digger.n.01', 'name': 'posthole_digger'}, {'id': 10040, 'synset': 'post_horn.n.01', 'name': 'post_horn'}, {'id': 10041, 'synset': 'posthouse.n.01', 'name': 'posthouse'}, {'id': 10042, 'synset': 'potbelly.n.02', 'name': 'potbelly'}, {'id': 10043, 'synset': 'potemkin_village.n.01', 'name': 'Potemkin_village'}, {'id': 10044, 'synset': 'potential_divider.n.01', 'name': 'potential_divider'}, {'id': 10045, 'synset': 'potentiometer.n.02', 'name': 'potentiometer'}, {'id': 10046, 'synset': 'potentiometer.n.01', 'name': 'potentiometer'}, {'id': 10047, 'synset': 'potpourri.n.03', 'name': 'potpourri'}, {'id': 10048, 'synset': 'potsherd.n.01', 'name': 'potsherd'}, {'id': 10049, 'synset': "potter's_wheel.n.01", 'name': "potter's_wheel"}, {'id': 10050, 'synset': 'pottle.n.01', 'name': 'pottle'}, {'id': 10051, 'synset': 'potty_seat.n.01', 'name': 'potty_seat'}, {'id': 10052, 'synset': 'poultice.n.01', 'name': 'poultice'}, {'id': 10053, 'synset': 'pound.n.13', 'name': 'pound'}, {'id': 10054, 'synset': 'pound_net.n.01', 'name': 'pound_net'}, {'id': 10055, 'synset': 'powder.n.03', 'name': 'powder'}, {'id': 10056, 'synset': 'powder_and_shot.n.01', 'name': 'powder_and_shot'}, {'id': 10057, 'synset': 'powdered_mustard.n.01', 'name': 'powdered_mustard'}, {'id': 10058, 'synset': 'powder_horn.n.01', 'name': 'powder_horn'}, {'id': 10059, 'synset': 'powder_keg.n.02', 'name': 'powder_keg'}, {'id': 10060, 'synset': 'power_brake.n.01', 'name': 'power_brake'}, {'id': 10061, 'synset': 'power_cord.n.01', 'name': 'power_cord'}, {'id': 10062, 'synset': 'power_drill.n.01', 'name': 'power_drill'}, {'id': 10063, 'synset': 'power_line.n.01', 'name': 'power_line'}, {'id': 10064, 'synset': 'power_loom.n.01', 'name': 'power_loom'}, {'id': 10065, 'synset': 'power_mower.n.01', 'name': 'power_mower'}, {'id': 10066, 'synset': 'power_pack.n.01', 'name': 'power_pack'}, {'id': 10067, 'synset': 'power_saw.n.01', 'name': 'power_saw'}, {'id': 10068, 'synset': 'power_steering.n.01', 'name': 'power_steering'}, {'id': 10069, 'synset': 'power_takeoff.n.01', 'name': 'power_takeoff'}, {'id': 10070, 'synset': 'power_tool.n.01', 'name': 'power_tool'}, {'id': 10071, 'synset': 'praetorium.n.01', 'name': 'praetorium'}, {'id': 10072, 'synset': 'prayer_rug.n.01', 'name': 'prayer_rug'}, {'id': 10073, 'synset': 'prayer_shawl.n.01', 'name': 'prayer_shawl'}, {'id': 10074, 'synset': 'precipitator.n.01', 'name': 'precipitator'}, {'id': 10075, 'synset': 'prefab.n.01', 'name': 'prefab'}, {'id': 10076, 'synset': 'presbytery.n.01', 'name': 'presbytery'}, {'id': 10077, 'synset': 'presence_chamber.n.01', 'name': 'presence_chamber'}, {'id': 10078, 'synset': 'press.n.07', 'name': 'press'}, {'id': 10079, 'synset': 'press.n.03', 'name': 'press'}, {'id': 10080, 'synset': 'press.n.06', 'name': 'press'}, {'id': 10081, 'synset': 'press_box.n.01', 'name': 'press_box'}, {'id': 10082, 'synset': 'press_gallery.n.01', 'name': 'press_gallery'}, {'id': 10083, 'synset': 'press_of_sail.n.01', 'name': 'press_of_sail'}, {'id': 10084, 'synset': 'pressure_cabin.n.01', 'name': 'pressure_cabin'}, {'id': 10085, 'synset': 'pressure_cooker.n.01', 'name': 'pressure_cooker'}, {'id': 10086, 'synset': 'pressure_dome.n.01', 'name': 'pressure_dome'}, {'id': 10087, 'synset': 'pressure_gauge.n.01', 'name': 'pressure_gauge'}, {'id': 10088, 'synset': 'pressurized_water_reactor.n.01', 'name': 'pressurized_water_reactor'}, {'id': 10089, 'synset': 'pressure_suit.n.01', 'name': 'pressure_suit'}, {'id': 10090, 'synset': 'pricket.n.01', 'name': 'pricket'}, {'id': 10091, 'synset': 'prie-dieu.n.01', 'name': 'prie-dieu'}, {'id': 10092, 'synset': 'primary_coil.n.01', 'name': 'primary_coil'}, {'id': 10093, 'synset': 'primus_stove.n.01', 'name': 'Primus_stove'}, {'id': 10094, 'synset': 'prince_albert.n.02', 'name': 'Prince_Albert'}, {'id': 10095, 'synset': 'print.n.06', 'name': 'print'}, {'id': 10096, 'synset': 'print_buffer.n.01', 'name': 'print_buffer'}, {'id': 10097, 'synset': 'printed_circuit.n.01', 'name': 'printed_circuit'}, {'id': 10098, 'synset': 'printer.n.02', 'name': 'printer'}, {'id': 10099, 'synset': 'printer_cable.n.01', 'name': 'printer_cable'}, {'id': 10100, 'synset': 'priory.n.01', 'name': 'priory'}, {'id': 10101, 'synset': 'prison.n.01', 'name': 'prison'}, {'id': 10102, 'synset': 'prison_camp.n.01', 'name': 'prison_camp'}, {'id': 10103, 'synset': 'privateer.n.02', 'name': 'privateer'}, {'id': 10104, 'synset': 'private_line.n.01', 'name': 'private_line'}, {'id': 10105, 'synset': 'privet_hedge.n.01', 'name': 'privet_hedge'}, {'id': 10106, 'synset': 'probe.n.02', 'name': 'probe'}, {'id': 10107, 'synset': 'proctoscope.n.01', 'name': 'proctoscope'}, {'id': 10108, 'synset': 'prod.n.02', 'name': 'prod'}, {'id': 10109, 'synset': 'production_line.n.01', 'name': 'production_line'}, {'id': 10110, 'synset': 'projector.n.01', 'name': 'projector'}, {'id': 10111, 'synset': 'prolonge.n.01', 'name': 'prolonge'}, {'id': 10112, 'synset': 'prolonge_knot.n.01', 'name': 'prolonge_knot'}, {'id': 10113, 'synset': 'prompter.n.02', 'name': 'prompter'}, {'id': 10114, 'synset': 'prong.n.01', 'name': 'prong'}, {'id': 10115, 'synset': 'propeller_plane.n.01', 'name': 'propeller_plane'}, {'id': 10116, 'synset': 'propjet.n.01', 'name': 'propjet'}, {'id': 10117, 'synset': 'proportional_counter_tube.n.01', 'name': 'proportional_counter_tube'}, {'id': 10118, 'synset': 'propulsion_system.n.01', 'name': 'propulsion_system'}, {'id': 10119, 'synset': 'proscenium.n.02', 'name': 'proscenium'}, {'id': 10120, 'synset': 'proscenium_arch.n.01', 'name': 'proscenium_arch'}, {'id': 10121, 'synset': 'prosthesis.n.01', 'name': 'prosthesis'}, {'id': 10122, 'synset': 'protective_covering.n.01', 'name': 'protective_covering'}, {'id': 10123, 'synset': 'protective_garment.n.01', 'name': 'protective_garment'}, {'id': 10124, 'synset': 'proton_accelerator.n.01', 'name': 'proton_accelerator'}, {'id': 10125, 'synset': 'protractor.n.01', 'name': 'protractor'}, {'id': 10126, 'synset': 'pruner.n.02', 'name': 'pruner'}, {'id': 10127, 'synset': 'pruning_knife.n.01', 'name': 'pruning_knife'}, {'id': 10128, 'synset': 'pruning_saw.n.01', 'name': 'pruning_saw'}, {'id': 10129, 'synset': 'pruning_shears.n.01', 'name': 'pruning_shears'}, {'id': 10130, 'synset': 'psaltery.n.01', 'name': 'psaltery'}, {'id': 10131, 'synset': 'psychrometer.n.01', 'name': 'psychrometer'}, {'id': 10132, 'synset': 'pt_boat.n.01', 'name': 'PT_boat'}, {'id': 10133, 'synset': 'public_address_system.n.01', 'name': 'public_address_system'}, {'id': 10134, 'synset': 'public_house.n.01', 'name': 'public_house'}, {'id': 10135, 'synset': 'public_toilet.n.01', 'name': 'public_toilet'}, {'id': 10136, 'synset': 'public_transport.n.01', 'name': 'public_transport'}, {'id': 10137, 'synset': 'public_works.n.01', 'name': 'public_works'}, {'id': 10138, 'synset': 'puck.n.02', 'name': 'puck'}, {'id': 10139, 'synset': 'pull.n.04', 'name': 'pull'}, {'id': 10140, 'synset': 'pullback.n.01', 'name': 'pullback'}, {'id': 10141, 'synset': 'pull_chain.n.01', 'name': 'pull_chain'}, {'id': 10142, 'synset': 'pulley.n.01', 'name': 'pulley'}, {'id': 10143, 'synset': 'pull-off.n.01', 'name': 'pull-off'}, {'id': 10144, 'synset': 'pullman.n.01', 'name': 'Pullman'}, {'id': 10145, 'synset': 'pullover.n.01', 'name': 'pullover'}, {'id': 10146, 'synset': 'pull-through.n.01', 'name': 'pull-through'}, {'id': 10147, 'synset': 'pulse_counter.n.01', 'name': 'pulse_counter'}, {'id': 10148, 'synset': 'pulse_generator.n.01', 'name': 'pulse_generator'}, {'id': 10149, 'synset': 'pulse_timing_circuit.n.01', 'name': 'pulse_timing_circuit'}, {'id': 10150, 'synset': 'pump.n.01', 'name': 'pump'}, {'id': 10151, 'synset': 'pump.n.03', 'name': 'pump'}, {'id': 10152, 'synset': 'pump_action.n.01', 'name': 'pump_action'}, {'id': 10153, 'synset': 'pump_house.n.01', 'name': 'pump_house'}, {'id': 10154, 'synset': 'pump_room.n.01', 'name': 'pump_room'}, {'id': 10155, 'synset': 'pump-type_pliers.n.01', 'name': 'pump-type_pliers'}, {'id': 10156, 'synset': 'pump_well.n.01', 'name': 'pump_well'}, {'id': 10157, 'synset': 'punchboard.n.01', 'name': 'punchboard'}, {'id': 10158, 'synset': 'punch_bowl.n.01', 'name': 'punch_bowl'}, {'id': 10159, 'synset': 'punching_bag.n.02', 'name': 'punching_bag'}, {'id': 10160, 'synset': 'punch_pliers.n.01', 'name': 'punch_pliers'}, {'id': 10161, 'synset': 'punch_press.n.01', 'name': 'punch_press'}, {'id': 10162, 'synset': 'punnet.n.01', 'name': 'punnet'}, {'id': 10163, 'synset': 'punt.n.02', 'name': 'punt'}, {'id': 10164, 'synset': 'pup_tent.n.01', 'name': 'pup_tent'}, {'id': 10165, 'synset': 'purdah.n.03', 'name': 'purdah'}, {'id': 10166, 'synset': 'purifier.n.01', 'name': 'purifier'}, {'id': 10167, 'synset': 'purl.n.02', 'name': 'purl'}, {'id': 10168, 'synset': 'purse.n.03', 'name': 'purse'}, {'id': 10169, 'synset': 'push-bike.n.01', 'name': 'push-bike'}, {'id': 10170, 'synset': 'push_broom.n.01', 'name': 'push_broom'}, {'id': 10171, 'synset': 'push_button.n.01', 'name': 'push_button'}, {'id': 10172, 'synset': 'push-button_radio.n.01', 'name': 'push-button_radio'}, {'id': 10173, 'synset': 'pusher.n.04', 'name': 'pusher'}, {'id': 10174, 'synset': 'put-put.n.01', 'name': 'put-put'}, {'id': 10175, 'synset': 'puttee.n.01', 'name': 'puttee'}, {'id': 10176, 'synset': 'putter.n.02', 'name': 'putter'}, {'id': 10177, 'synset': 'putty_knife.n.01', 'name': 'putty_knife'}, {'id': 10178, 'synset': 'puzzle.n.02', 'name': 'puzzle'}, {'id': 10179, 'synset': 'pylon.n.02', 'name': 'pylon'}, {'id': 10180, 'synset': 'pylon.n.01', 'name': 'pylon'}, {'id': 10181, 'synset': 'pyramidal_tent.n.01', 'name': 'pyramidal_tent'}, {'id': 10182, 'synset': 'pyrograph.n.01', 'name': 'pyrograph'}, {'id': 10183, 'synset': 'pyrometer.n.01', 'name': 'pyrometer'}, {'id': 10184, 'synset': 'pyrometric_cone.n.01', 'name': 'pyrometric_cone'}, {'id': 10185, 'synset': 'pyrostat.n.01', 'name': 'pyrostat'}, {'id': 10186, 'synset': 'pyx.n.02', 'name': 'pyx'}, {'id': 10187, 'synset': 'pyx.n.01', 'name': 'pyx'}, {'id': 10188, 'synset': 'pyxis.n.03', 'name': 'pyxis'}, {'id': 10189, 'synset': 'quad.n.04', 'name': 'quad'}, {'id': 10190, 'synset': 'quadrant.n.04', 'name': 'quadrant'}, {'id': 10191, 'synset': 'quadraphony.n.01', 'name': 'quadraphony'}, {'id': 10192, 'synset': 'quartering.n.02', 'name': 'quartering'}, {'id': 10193, 'synset': 'quarterstaff.n.01', 'name': 'quarterstaff'}, {'id': 10194, 'synset': 'quartz_battery.n.01', 'name': 'quartz_battery'}, {'id': 10195, 'synset': 'quartz_lamp.n.01', 'name': 'quartz_lamp'}, {'id': 10196, 'synset': 'queen.n.08', 'name': 'queen'}, {'id': 10197, 'synset': 'queen.n.07', 'name': 'queen'}, {'id': 10198, 'synset': 'queen_post.n.01', 'name': 'queen_post'}, {'id': 10199, 'synset': 'quern.n.01', 'name': 'quern'}, {'id': 10200, 'synset': 'quill.n.01', 'name': 'quill'}, {'id': 10201, 'synset': 'quilted_bedspread.n.01', 'name': 'quilted_bedspread'}, {'id': 10202, 'synset': 'quilting.n.02', 'name': 'quilting'}, {'id': 10203, 'synset': 'quipu.n.01', 'name': 'quipu'}, {'id': 10204, 'synset': 'quirk_molding.n.01', 'name': 'quirk_molding'}, {'id': 10205, 'synset': 'quirt.n.01', 'name': 'quirt'}, {'id': 10206, 'synset': 'quiver.n.03', 'name': 'quiver'}, {'id': 10207, 'synset': 'quoin.n.02', 'name': 'quoin'}, {'id': 10208, 'synset': 'quoit.n.01', 'name': 'quoit'}, {'id': 10209, 'synset': 'qwerty_keyboard.n.01', 'name': 'QWERTY_keyboard'}, {'id': 10210, 'synset': 'rabbet.n.01', 'name': 'rabbet'}, {'id': 10211, 'synset': 'rabbet_joint.n.01', 'name': 'rabbet_joint'}, {'id': 10212, 'synset': 'rabbit_ears.n.01', 'name': 'rabbit_ears'}, {'id': 10213, 'synset': 'rabbit_hutch.n.01', 'name': 'rabbit_hutch'}, {'id': 10214, 'synset': 'raceabout.n.01', 'name': 'raceabout'}, {'id': 10215, 'synset': 'raceway.n.01', 'name': 'raceway'}, {'id': 10216, 'synset': 'racing_boat.n.01', 'name': 'racing_boat'}, {'id': 10217, 'synset': 'racing_gig.n.01', 'name': 'racing_gig'}, {'id': 10218, 'synset': 'racing_skiff.n.01', 'name': 'racing_skiff'}, {'id': 10219, 'synset': 'rack.n.05', 'name': 'rack'}, {'id': 10220, 'synset': 'rack.n.01', 'name': 'rack'}, {'id': 10221, 'synset': 'rack.n.04', 'name': 'rack'}, {'id': 10222, 'synset': 'rack_and_pinion.n.01', 'name': 'rack_and_pinion'}, {'id': 10223, 'synset': 'racquetball.n.01', 'name': 'racquetball'}, {'id': 10224, 'synset': 'radial.n.01', 'name': 'radial'}, {'id': 10225, 'synset': 'radial_engine.n.01', 'name': 'radial_engine'}, {'id': 10226, 'synset': 'radiation_pyrometer.n.01', 'name': 'radiation_pyrometer'}, {'id': 10227, 'synset': 'radiator.n.02', 'name': 'radiator'}, {'id': 10228, 'synset': 'radiator_cap.n.01', 'name': 'radiator_cap'}, {'id': 10229, 'synset': 'radiator_hose.n.01', 'name': 'radiator_hose'}, {'id': 10230, 'synset': 'radio.n.03', 'name': 'radio'}, {'id': 10231, 'synset': 'radio_antenna.n.01', 'name': 'radio_antenna'}, {'id': 10232, 'synset': 'radio_chassis.n.01', 'name': 'radio_chassis'}, {'id': 10233, 'synset': 'radio_compass.n.01', 'name': 'radio_compass'}, {'id': 10234, 'synset': 'radiogram.n.02', 'name': 'radiogram'}, {'id': 10235, 'synset': 'radio_interferometer.n.01', 'name': 'radio_interferometer'}, {'id': 10236, 'synset': 'radio_link.n.01', 'name': 'radio_link'}, {'id': 10237, 'synset': 'radiometer.n.01', 'name': 'radiometer'}, {'id': 10238, 'synset': 'radiomicrometer.n.01', 'name': 'radiomicrometer'}, {'id': 10239, 'synset': 'radio-phonograph.n.01', 'name': 'radio-phonograph'}, {'id': 10240, 'synset': 'radiotelegraph.n.02', 'name': 'radiotelegraph'}, {'id': 10241, 'synset': 'radiotelephone.n.02', 'name': 'radiotelephone'}, {'id': 10242, 'synset': 'radio_telescope.n.01', 'name': 'radio_telescope'}, {'id': 10243, 'synset': 'radiotherapy_equipment.n.01', 'name': 'radiotherapy_equipment'}, {'id': 10244, 'synset': 'radio_transmitter.n.01', 'name': 'radio_transmitter'}, {'id': 10245, 'synset': 'radome.n.01', 'name': 'radome'}, {'id': 10246, 'synset': 'rafter.n.01', 'name': 'rafter'}, {'id': 10247, 'synset': 'raft_foundation.n.01', 'name': 'raft_foundation'}, {'id': 10248, 'synset': 'rag.n.01', 'name': 'rag'}, {'id': 10249, 'synset': 'ragbag.n.02', 'name': 'ragbag'}, {'id': 10250, 'synset': 'raglan.n.01', 'name': 'raglan'}, {'id': 10251, 'synset': 'raglan_sleeve.n.01', 'name': 'raglan_sleeve'}, {'id': 10252, 'synset': 'rail.n.04', 'name': 'rail'}, {'id': 10253, 'synset': 'rail_fence.n.01', 'name': 'rail_fence'}, {'id': 10254, 'synset': 'railhead.n.01', 'name': 'railhead'}, {'id': 10255, 'synset': 'railing.n.01', 'name': 'railing'}, {'id': 10256, 'synset': 'railing.n.02', 'name': 'railing'}, {'id': 10257, 'synset': 'railroad_bed.n.01', 'name': 'railroad_bed'}, {'id': 10258, 'synset': 'railroad_tunnel.n.01', 'name': 'railroad_tunnel'}, {'id': 10259, 'synset': 'rain_barrel.n.01', 'name': 'rain_barrel'}, {'id': 10260, 'synset': 'rain_gauge.n.01', 'name': 'rain_gauge'}, {'id': 10261, 'synset': 'rain_stick.n.01', 'name': 'rain_stick'}, {'id': 10262, 'synset': 'rake.n.03', 'name': 'rake'}, {'id': 10263, 'synset': 'rake_handle.n.01', 'name': 'rake_handle'}, {'id': 10264, 'synset': 'ram_disk.n.01', 'name': 'RAM_disk'}, {'id': 10265, 'synset': 'ramekin.n.02', 'name': 'ramekin'}, {'id': 10266, 'synset': 'ramjet.n.01', 'name': 'ramjet'}, {'id': 10267, 'synset': 'rammer.n.01', 'name': 'rammer'}, {'id': 10268, 'synset': 'ramp.n.01', 'name': 'ramp'}, {'id': 10269, 'synset': 'rampant_arch.n.01', 'name': 'rampant_arch'}, {'id': 10270, 'synset': 'rampart.n.01', 'name': 'rampart'}, {'id': 10271, 'synset': 'ramrod.n.01', 'name': 'ramrod'}, {'id': 10272, 'synset': 'ramrod.n.03', 'name': 'ramrod'}, {'id': 10273, 'synset': 'ranch.n.01', 'name': 'ranch'}, {'id': 10274, 'synset': 'ranch_house.n.01', 'name': 'ranch_house'}, {'id': 10275, 'synset': 'random-access_memory.n.01', 'name': 'random-access_memory'}, {'id': 10276, 'synset': 'rangefinder.n.01', 'name': 'rangefinder'}, {'id': 10277, 'synset': 'range_hood.n.01', 'name': 'range_hood'}, {'id': 10278, 'synset': 'range_pole.n.01', 'name': 'range_pole'}, {'id': 10279, 'synset': 'rapier.n.01', 'name': 'rapier'}, {'id': 10280, 'synset': 'rariora.n.01', 'name': 'rariora'}, {'id': 10281, 'synset': 'rasp.n.02', 'name': 'rasp'}, {'id': 10282, 'synset': 'ratchet.n.01', 'name': 'ratchet'}, {'id': 10283, 'synset': 'ratchet_wheel.n.01', 'name': 'ratchet_wheel'}, {'id': 10284, 'synset': 'rathskeller.n.01', 'name': 'rathskeller'}, {'id': 10285, 'synset': 'ratline.n.01', 'name': 'ratline'}, {'id': 10286, 'synset': 'rat-tail_file.n.01', 'name': 'rat-tail_file'}, {'id': 10287, 'synset': 'rattan.n.03', 'name': 'rattan'}, {'id': 10288, 'synset': 'rattrap.n.03', 'name': 'rattrap'}, {'id': 10289, 'synset': 'rayon.n.01', 'name': 'rayon'}, {'id': 10290, 'synset': 'razor.n.01', 'name': 'razor'}, {'id': 10291, 'synset': 'reaction-propulsion_engine.n.01', 'name': 'reaction-propulsion_engine'}, {'id': 10292, 'synset': 'reaction_turbine.n.01', 'name': 'reaction_turbine'}, {'id': 10293, 'synset': 'reactor.n.01', 'name': 'reactor'}, {'id': 10294, 'synset': 'reading_lamp.n.01', 'name': 'reading_lamp'}, {'id': 10295, 'synset': 'reading_room.n.01', 'name': 'reading_room'}, {'id': 10296, 'synset': 'read-only_memory.n.01', 'name': 'read-only_memory'}, {'id': 10297, 'synset': 'read-only_memory_chip.n.01', 'name': 'read-only_memory_chip'}, {'id': 10298, 'synset': 'readout.n.03', 'name': 'readout'}, {'id': 10299, 'synset': 'read/write_head.n.01', 'name': 'read/write_head'}, {'id': 10300, 'synset': 'ready-to-wear.n.01', 'name': 'ready-to-wear'}, {'id': 10301, 'synset': 'real_storage.n.01', 'name': 'real_storage'}, {'id': 10302, 'synset': 'reamer.n.02', 'name': 'reamer'}, {'id': 10303, 'synset': 'reaumur_thermometer.n.01', 'name': 'Reaumur_thermometer'}, {'id': 10304, 'synset': 'rebozo.n.01', 'name': 'rebozo'}, {'id': 10305, 'synset': 'receiver.n.01', 'name': 'receiver'}, {'id': 10306, 'synset': 'receptacle.n.01', 'name': 'receptacle'}, {'id': 10307, 'synset': 'reception_desk.n.01', 'name': 'reception_desk'}, {'id': 10308, 'synset': 'reception_room.n.01', 'name': 'reception_room'}, {'id': 10309, 'synset': 'recess.n.04', 'name': 'recess'}, {'id': 10310, 'synset': 'reciprocating_engine.n.01', 'name': 'reciprocating_engine'}, {'id': 10311, 'synset': 'reconnaissance_plane.n.01', 'name': 'reconnaissance_plane'}, {'id': 10312, 'synset': 'reconnaissance_vehicle.n.01', 'name': 'reconnaissance_vehicle'}, {'id': 10313, 'synset': 'record_changer.n.01', 'name': 'record_changer'}, {'id': 10314, 'synset': 'recorder.n.01', 'name': 'recorder'}, {'id': 10315, 'synset': 'recording.n.03', 'name': 'recording'}, {'id': 10316, 'synset': 'recording_system.n.01', 'name': 'recording_system'}, {'id': 10317, 'synset': 'record_sleeve.n.01', 'name': 'record_sleeve'}, {'id': 10318, 'synset': 'recovery_room.n.01', 'name': 'recovery_room'}, {'id': 10319, 'synset': 'recreational_vehicle.n.01', 'name': 'recreational_vehicle'}, {'id': 10320, 'synset': 'recreation_room.n.01', 'name': 'recreation_room'}, {'id': 10321, 'synset': 'recycling_bin.n.01', 'name': 'recycling_bin'}, {'id': 10322, 'synset': 'recycling_plant.n.01', 'name': 'recycling_plant'}, {'id': 10323, 'synset': 'redbrick_university.n.01', 'name': 'redbrick_university'}, {'id': 10324, 'synset': 'red_carpet.n.01', 'name': 'red_carpet'}, {'id': 10325, 'synset': 'redoubt.n.02', 'name': 'redoubt'}, {'id': 10326, 'synset': 'redoubt.n.01', 'name': 'redoubt'}, {'id': 10327, 'synset': 'reduction_gear.n.01', 'name': 'reduction_gear'}, {'id': 10328, 'synset': 'reed_pipe.n.01', 'name': 'reed_pipe'}, {'id': 10329, 'synset': 'reed_stop.n.01', 'name': 'reed_stop'}, {'id': 10330, 'synset': 'reef_knot.n.01', 'name': 'reef_knot'}, {'id': 10331, 'synset': 'reel.n.03', 'name': 'reel'}, {'id': 10332, 'synset': 'reel.n.01', 'name': 'reel'}, {'id': 10333, 'synset': 'refectory.n.01', 'name': 'refectory'}, {'id': 10334, 'synset': 'refectory_table.n.01', 'name': 'refectory_table'}, {'id': 10335, 'synset': 'refinery.n.01', 'name': 'refinery'}, {'id': 10336, 'synset': 'reflecting_telescope.n.01', 'name': 'reflecting_telescope'}, {'id': 10337, 'synset': 'reflectometer.n.01', 'name': 'reflectometer'}, {'id': 10338, 'synset': 'reflex_camera.n.01', 'name': 'reflex_camera'}, {'id': 10339, 'synset': 'reflux_condenser.n.01', 'name': 'reflux_condenser'}, {'id': 10340, 'synset': 'reformatory.n.01', 'name': 'reformatory'}, {'id': 10341, 'synset': 'reformer.n.02', 'name': 'reformer'}, {'id': 10342, 'synset': 'refracting_telescope.n.01', 'name': 'refracting_telescope'}, {'id': 10343, 'synset': 'refractometer.n.01', 'name': 'refractometer'}, {'id': 10344, 'synset': 'refrigeration_system.n.01', 'name': 'refrigeration_system'}, {'id': 10345, 'synset': 'refrigerator.n.01', 'name': 'refrigerator'}, {'id': 10346, 'synset': 'refrigerator_car.n.01', 'name': 'refrigerator_car'}, {'id': 10347, 'synset': 'refuge.n.03', 'name': 'refuge'}, {'id': 10348, 'synset': 'regalia.n.01', 'name': 'regalia'}, {'id': 10349, 'synset': 'regimentals.n.01', 'name': 'regimentals'}, {'id': 10350, 'synset': 'regulator.n.01', 'name': 'regulator'}, {'id': 10351, 'synset': 'rein.n.01', 'name': 'rein'}, {'id': 10352, 'synset': 'relay.n.05', 'name': 'relay'}, {'id': 10353, 'synset': 'release.n.08', 'name': 'release'}, {'id': 10354, 'synset': 'religious_residence.n.01', 'name': 'religious_residence'}, {'id': 10355, 'synset': 'reliquary.n.01', 'name': 'reliquary'}, {'id': 10356, 'synset': 'remote_terminal.n.01', 'name': 'remote_terminal'}, {'id': 10357, 'synset': 'removable_disk.n.01', 'name': 'removable_disk'}, {'id': 10358, 'synset': 'rendering.n.05', 'name': 'rendering'}, {'id': 10359, 'synset': 'rep.n.02', 'name': 'rep'}, {'id': 10360, 'synset': 'repair_shop.n.01', 'name': 'repair_shop'}, {'id': 10361, 'synset': 'repeater.n.04', 'name': 'repeater'}, {'id': 10362, 'synset': 'repeating_firearm.n.01', 'name': 'repeating_firearm'}, {'id': 10363, 'synset': 'repository.n.03', 'name': 'repository'}, {'id': 10364, 'synset': 'reproducer.n.01', 'name': 'reproducer'}, {'id': 10365, 'synset': 'rerebrace.n.01', 'name': 'rerebrace'}, {'id': 10366, 'synset': 'rescue_equipment.n.01', 'name': 'rescue_equipment'}, {'id': 10367, 'synset': 'research_center.n.01', 'name': 'research_center'}, {'id': 10368, 'synset': 'reseau.n.02', 'name': 'reseau'}, {'id': 10369, 'synset': 'reservoir.n.03', 'name': 'reservoir'}, {'id': 10370, 'synset': 'reset.n.01', 'name': 'reset'}, {'id': 10371, 'synset': 'reset_button.n.01', 'name': 'reset_button'}, {'id': 10372, 'synset': 'residence.n.02', 'name': 'residence'}, {'id': 10373, 'synset': 'resistance_pyrometer.n.01', 'name': 'resistance_pyrometer'}, {'id': 10374, 'synset': 'resistor.n.01', 'name': 'resistor'}, {'id': 10375, 'synset': 'resonator.n.03', 'name': 'resonator'}, {'id': 10376, 'synset': 'resonator.n.01', 'name': 'resonator'}, {'id': 10377, 'synset': 'resort_hotel.n.02', 'name': 'resort_hotel'}, {'id': 10378, 'synset': 'respirator.n.01', 'name': 'respirator'}, {'id': 10379, 'synset': 'restaurant.n.01', 'name': 'restaurant'}, {'id': 10380, 'synset': 'rest_house.n.01', 'name': 'rest_house'}, {'id': 10381, 'synset': 'restraint.n.06', 'name': 'restraint'}, {'id': 10382, 'synset': 'resuscitator.n.01', 'name': 'resuscitator'}, {'id': 10383, 'synset': 'retainer.n.03', 'name': 'retainer'}, {'id': 10384, 'synset': 'retaining_wall.n.01', 'name': 'retaining_wall'}, {'id': 10385, 'synset': 'reticle.n.01', 'name': 'reticle'}, {'id': 10386, 'synset': 'reticulation.n.02', 'name': 'reticulation'}, {'id': 10387, 'synset': 'reticule.n.01', 'name': 'reticule'}, {'id': 10388, 'synset': 'retort.n.02', 'name': 'retort'}, {'id': 10389, 'synset': 'retractor.n.01', 'name': 'retractor'}, {'id': 10390, 'synset': 'return_key.n.01', 'name': 'return_key'}, {'id': 10391, 'synset': 'reverberatory_furnace.n.01', 'name': 'reverberatory_furnace'}, {'id': 10392, 'synset': 'revers.n.01', 'name': 'revers'}, {'id': 10393, 'synset': 'reverse.n.02', 'name': 'reverse'}, {'id': 10394, 'synset': 'reversible.n.01', 'name': 'reversible'}, {'id': 10395, 'synset': 'revetment.n.02', 'name': 'revetment'}, {'id': 10396, 'synset': 'revetment.n.01', 'name': 'revetment'}, {'id': 10397, 'synset': 'revolver.n.01', 'name': 'revolver'}, {'id': 10398, 'synset': 'revolving_door.n.02', 'name': 'revolving_door'}, {'id': 10399, 'synset': 'rheometer.n.01', 'name': 'rheometer'}, {'id': 10400, 'synset': 'rheostat.n.01', 'name': 'rheostat'}, {'id': 10401, 'synset': 'rhinoscope.n.01', 'name': 'rhinoscope'}, {'id': 10402, 'synset': 'rib.n.01', 'name': 'rib'}, {'id': 10403, 'synset': 'riband.n.01', 'name': 'riband'}, {'id': 10404, 'synset': 'ribbed_vault.n.01', 'name': 'ribbed_vault'}, {'id': 10405, 'synset': 'ribbing.n.01', 'name': 'ribbing'}, {'id': 10406, 'synset': 'ribbon_development.n.01', 'name': 'ribbon_development'}, {'id': 10407, 'synset': 'rib_joint_pliers.n.01', 'name': 'rib_joint_pliers'}, {'id': 10408, 'synset': 'ricer.n.01', 'name': 'ricer'}, {'id': 10409, 'synset': 'riddle.n.02', 'name': 'riddle'}, {'id': 10410, 'synset': 'ride.n.02', 'name': 'ride'}, {'id': 10411, 'synset': 'ridge.n.06', 'name': 'ridge'}, {'id': 10412, 'synset': 'ridge_rope.n.01', 'name': 'ridge_rope'}, {'id': 10413, 'synset': 'riding_boot.n.01', 'name': 'riding_boot'}, {'id': 10414, 'synset': 'riding_crop.n.01', 'name': 'riding_crop'}, {'id': 10415, 'synset': 'riding_mower.n.01', 'name': 'riding_mower'}, {'id': 10416, 'synset': 'rifle_ball.n.01', 'name': 'rifle_ball'}, {'id': 10417, 'synset': 'rifle_grenade.n.01', 'name': 'rifle_grenade'}, {'id': 10418, 'synset': 'rig.n.01', 'name': 'rig'}, {'id': 10419, 'synset': 'rigger.n.02', 'name': 'rigger'}, {'id': 10420, 'synset': 'rigger.n.04', 'name': 'rigger'}, {'id': 10421, 'synset': 'rigging.n.01', 'name': 'rigging'}, {'id': 10422, 'synset': 'rigout.n.01', 'name': 'rigout'}, {'id': 10423, 'synset': 'ringlet.n.03', 'name': 'ringlet'}, {'id': 10424, 'synset': 'rings.n.01', 'name': 'rings'}, {'id': 10425, 'synset': 'rink.n.01', 'name': 'rink'}, {'id': 10426, 'synset': 'riot_gun.n.01', 'name': 'riot_gun'}, {'id': 10427, 'synset': 'ripcord.n.02', 'name': 'ripcord'}, {'id': 10428, 'synset': 'ripcord.n.01', 'name': 'ripcord'}, {'id': 10429, 'synset': 'ripping_bar.n.01', 'name': 'ripping_bar'}, {'id': 10430, 'synset': 'ripping_chisel.n.01', 'name': 'ripping_chisel'}, {'id': 10431, 'synset': 'ripsaw.n.01', 'name': 'ripsaw'}, {'id': 10432, 'synset': 'riser.n.03', 'name': 'riser'}, {'id': 10433, 'synset': 'riser.n.02', 'name': 'riser'}, {'id': 10434, 'synset': 'ritz.n.03', 'name': 'Ritz'}, {'id': 10435, 'synset': 'rivet.n.02', 'name': 'rivet'}, {'id': 10436, 'synset': 'riveting_machine.n.01', 'name': 'riveting_machine'}, {'id': 10437, 'synset': 'roach_clip.n.01', 'name': 'roach_clip'}, {'id': 10438, 'synset': 'road.n.01', 'name': 'road'}, {'id': 10439, 'synset': 'roadbed.n.01', 'name': 'roadbed'}, {'id': 10440, 'synset': 'roadblock.n.02', 'name': 'roadblock'}, {'id': 10441, 'synset': 'roadhouse.n.01', 'name': 'roadhouse'}, {'id': 10442, 'synset': 'roadster.n.01', 'name': 'roadster'}, {'id': 10443, 'synset': 'roadway.n.01', 'name': 'roadway'}, {'id': 10444, 'synset': 'roaster.n.04', 'name': 'roaster'}, {'id': 10445, 'synset': 'robotics_equipment.n.01', 'name': 'robotics_equipment'}, {'id': 10446, 'synset': 'rochon_prism.n.01', 'name': 'Rochon_prism'}, {'id': 10447, 'synset': 'rock_bit.n.01', 'name': 'rock_bit'}, {'id': 10448, 'synset': 'rocker.n.07', 'name': 'rocker'}, {'id': 10449, 'synset': 'rocker.n.05', 'name': 'rocker'}, {'id': 10450, 'synset': 'rocker_arm.n.01', 'name': 'rocker_arm'}, {'id': 10451, 'synset': 'rocket.n.02', 'name': 'rocket'}, {'id': 10452, 'synset': 'rocket.n.01', 'name': 'rocket'}, {'id': 10453, 'synset': 'rod.n.01', 'name': 'rod'}, {'id': 10454, 'synset': 'rodeo.n.02', 'name': 'rodeo'}, {'id': 10455, 'synset': 'roll.n.04', 'name': 'roll'}, {'id': 10456, 'synset': 'roller.n.04', 'name': 'roller'}, {'id': 10457, 'synset': 'roller.n.03', 'name': 'roller'}, {'id': 10458, 'synset': 'roller_bandage.n.01', 'name': 'roller_bandage'}, {'id': 10459, 'synset': 'in-line_skate.n.01', 'name': 'in-line_skate'}, {'id': 10460, 'synset': 'roller_blind.n.01', 'name': 'roller_blind'}, {'id': 10461, 'synset': 'roller_coaster.n.02', 'name': 'roller_coaster'}, {'id': 10462, 'synset': 'roller_towel.n.01', 'name': 'roller_towel'}, {'id': 10463, 'synset': 'roll_film.n.01', 'name': 'roll_film'}, {'id': 10464, 'synset': 'rolling_hitch.n.01', 'name': 'rolling_hitch'}, {'id': 10465, 'synset': 'rolling_mill.n.01', 'name': 'rolling_mill'}, {'id': 10466, 'synset': 'rolling_stock.n.01', 'name': 'rolling_stock'}, {'id': 10467, 'synset': 'roll-on.n.02', 'name': 'roll-on'}, {'id': 10468, 'synset': 'roll-on.n.01', 'name': 'roll-on'}, {'id': 10469, 'synset': 'roll-on_roll-off.n.01', 'name': 'roll-on_roll-off'}, {'id': 10470, 'synset': 'rolodex.n.01', 'name': 'Rolodex'}, {'id': 10471, 'synset': 'roman_arch.n.01', 'name': 'Roman_arch'}, {'id': 10472, 'synset': 'roman_building.n.01', 'name': 'Roman_building'}, {'id': 10473, 'synset': 'romper.n.02', 'name': 'romper'}, {'id': 10474, 'synset': 'rood_screen.n.01', 'name': 'rood_screen'}, {'id': 10475, 'synset': 'roof.n.01', 'name': 'roof'}, {'id': 10476, 'synset': 'roof.n.02', 'name': 'roof'}, {'id': 10477, 'synset': 'roofing.n.01', 'name': 'roofing'}, {'id': 10478, 'synset': 'room.n.01', 'name': 'room'}, {'id': 10479, 'synset': 'roomette.n.01', 'name': 'roomette'}, {'id': 10480, 'synset': 'room_light.n.01', 'name': 'room_light'}, {'id': 10481, 'synset': 'roost.n.01', 'name': 'roost'}, {'id': 10482, 'synset': 'rope.n.01', 'name': 'rope'}, {'id': 10483, 'synset': 'rope_bridge.n.01', 'name': 'rope_bridge'}, {'id': 10484, 'synset': 'rope_tow.n.01', 'name': 'rope_tow'}, {'id': 10485, 'synset': 'rose_water.n.01', 'name': 'rose_water'}, {'id': 10486, 'synset': 'rose_window.n.01', 'name': 'rose_window'}, {'id': 10487, 'synset': 'rosin_bag.n.01', 'name': 'rosin_bag'}, {'id': 10488, 'synset': 'rotary_actuator.n.01', 'name': 'rotary_actuator'}, {'id': 10489, 'synset': 'rotary_engine.n.01', 'name': 'rotary_engine'}, {'id': 10490, 'synset': 'rotary_press.n.01', 'name': 'rotary_press'}, {'id': 10491, 'synset': 'rotating_mechanism.n.01', 'name': 'rotating_mechanism'}, {'id': 10492, 'synset': 'rotating_shaft.n.01', 'name': 'rotating_shaft'}, {'id': 10493, 'synset': 'rotisserie.n.02', 'name': 'rotisserie'}, {'id': 10494, 'synset': 'rotisserie.n.01', 'name': 'rotisserie'}, {'id': 10495, 'synset': 'rotor.n.03', 'name': 'rotor'}, {'id': 10496, 'synset': 'rotor.n.01', 'name': 'rotor'}, {'id': 10497, 'synset': 'rotor.n.02', 'name': 'rotor'}, {'id': 10498, 'synset': 'rotor_blade.n.01', 'name': 'rotor_blade'}, {'id': 10499, 'synset': 'rotor_head.n.01', 'name': 'rotor_head'}, {'id': 10500, 'synset': 'rotunda.n.02', 'name': 'rotunda'}, {'id': 10501, 'synset': 'rotunda.n.01', 'name': 'rotunda'}, {'id': 10502, 'synset': 'rouge.n.01', 'name': 'rouge'}, {'id': 10503, 'synset': 'roughcast.n.02', 'name': 'roughcast'}, {'id': 10504, 'synset': 'rouleau.n.02', 'name': 'rouleau'}, {'id': 10505, 'synset': 'roulette.n.02', 'name': 'roulette'}, {'id': 10506, 'synset': 'roulette_ball.n.01', 'name': 'roulette_ball'}, {'id': 10507, 'synset': 'roulette_wheel.n.01', 'name': 'roulette_wheel'}, {'id': 10508, 'synset': 'round.n.01', 'name': 'round'}, {'id': 10509, 'synset': 'round_arch.n.01', 'name': 'round_arch'}, {'id': 10510, 'synset': 'round-bottom_flask.n.01', 'name': 'round-bottom_flask'}, {'id': 10511, 'synset': 'roundel.n.02', 'name': 'roundel'}, {'id': 10512, 'synset': 'round_file.n.01', 'name': 'round_file'}, {'id': 10513, 'synset': 'roundhouse.n.01', 'name': 'roundhouse'}, {'id': 10514, 'synset': 'router.n.03', 'name': 'router'}, {'id': 10515, 'synset': 'router_plane.n.01', 'name': 'router_plane'}, {'id': 10516, 'synset': 'rowel.n.01', 'name': 'rowel'}, {'id': 10517, 'synset': 'row_house.n.01', 'name': 'row_house'}, {'id': 10518, 'synset': 'rowing_boat.n.01', 'name': 'rowing_boat'}, {'id': 10519, 'synset': 'rowlock_arch.n.01', 'name': 'rowlock_arch'}, {'id': 10520, 'synset': 'royal.n.01', 'name': 'royal'}, {'id': 10521, 'synset': 'royal_mast.n.01', 'name': 'royal_mast'}, {'id': 10522, 'synset': 'rubber_boot.n.01', 'name': 'rubber_boot'}, {'id': 10523, 'synset': 'rubber_bullet.n.01', 'name': 'rubber_bullet'}, {'id': 10524, 'synset': 'rubber_eraser.n.01', 'name': 'rubber_eraser'}, {'id': 10525, 'synset': 'rudder.n.02', 'name': 'rudder'}, {'id': 10526, 'synset': 'rudder.n.01', 'name': 'rudder'}, {'id': 10527, 'synset': 'rudder_blade.n.01', 'name': 'rudder_blade'}, {'id': 10528, 'synset': 'rug.n.01', 'name': 'rug'}, {'id': 10529, 'synset': 'rugby_ball.n.01', 'name': 'rugby_ball'}, {'id': 10530, 'synset': 'ruin.n.02', 'name': 'ruin'}, {'id': 10531, 'synset': 'rule.n.12', 'name': 'rule'}, {'id': 10532, 'synset': 'rumble.n.02', 'name': 'rumble'}, {'id': 10533, 'synset': 'rumble_seat.n.01', 'name': 'rumble_seat'}, {'id': 10534, 'synset': 'rummer.n.01', 'name': 'rummer'}, {'id': 10535, 'synset': 'rumpus_room.n.01', 'name': 'rumpus_room'}, {'id': 10536, 'synset': 'runcible_spoon.n.01', 'name': 'runcible_spoon'}, {'id': 10537, 'synset': 'rundle.n.01', 'name': 'rundle'}, {'id': 10538, 'synset': 'running_shoe.n.01', 'name': 'running_shoe'}, {'id': 10539, 'synset': 'running_suit.n.01', 'name': 'running_suit'}, {'id': 10540, 'synset': 'runway.n.04', 'name': 'runway'}, {'id': 10541, 'synset': 'rushlight.n.01', 'name': 'rushlight'}, {'id': 10542, 'synset': 'russet.n.01', 'name': 'russet'}, {'id': 10543, 'synset': 'rya.n.01', 'name': 'rya'}, {'id': 10544, 'synset': 'saber.n.01', 'name': 'saber'}, {'id': 10545, 'synset': 'saber_saw.n.01', 'name': 'saber_saw'}, {'id': 10546, 'synset': 'sable.n.04', 'name': 'sable'}, {'id': 10547, 'synset': 'sable.n.01', 'name': 'sable'}, {'id': 10548, 'synset': 'sable_coat.n.01', 'name': 'sable_coat'}, {'id': 10549, 'synset': 'sabot.n.01', 'name': 'sabot'}, {'id': 10550, 'synset': 'sachet.n.01', 'name': 'sachet'}, {'id': 10551, 'synset': 'sack.n.05', 'name': 'sack'}, {'id': 10552, 'synset': 'sackbut.n.01', 'name': 'sackbut'}, {'id': 10553, 'synset': 'sackcloth.n.02', 'name': 'sackcloth'}, {'id': 10554, 'synset': 'sackcloth.n.01', 'name': 'sackcloth'}, {'id': 10555, 'synset': 'sack_coat.n.01', 'name': 'sack_coat'}, {'id': 10556, 'synset': 'sacking.n.01', 'name': 'sacking'}, {'id': 10557, 'synset': 'saddle_oxford.n.01', 'name': 'saddle_oxford'}, {'id': 10558, 'synset': 'saddlery.n.02', 'name': 'saddlery'}, {'id': 10559, 'synset': 'saddle_seat.n.01', 'name': 'saddle_seat'}, {'id': 10560, 'synset': 'saddle_stitch.n.01', 'name': 'saddle_stitch'}, {'id': 10561, 'synset': 'safe.n.01', 'name': 'safe'}, {'id': 10562, 'synset': 'safe.n.02', 'name': 'safe'}, {'id': 10563, 'synset': 'safe-deposit.n.01', 'name': 'safe-deposit'}, {'id': 10564, 'synset': 'safe_house.n.01', 'name': 'safe_house'}, {'id': 10565, 'synset': 'safety_arch.n.01', 'name': 'safety_arch'}, {'id': 10566, 'synset': 'safety_belt.n.01', 'name': 'safety_belt'}, {'id': 10567, 'synset': 'safety_bicycle.n.01', 'name': 'safety_bicycle'}, {'id': 10568, 'synset': 'safety_bolt.n.01', 'name': 'safety_bolt'}, {'id': 10569, 'synset': 'safety_curtain.n.01', 'name': 'safety_curtain'}, {'id': 10570, 'synset': 'safety_fuse.n.01', 'name': 'safety_fuse'}, {'id': 10571, 'synset': 'safety_lamp.n.01', 'name': 'safety_lamp'}, {'id': 10572, 'synset': 'safety_match.n.01', 'name': 'safety_match'}, {'id': 10573, 'synset': 'safety_net.n.02', 'name': 'safety_net'}, {'id': 10574, 'synset': 'safety_rail.n.01', 'name': 'safety_rail'}, {'id': 10575, 'synset': 'safety_razor.n.01', 'name': 'safety_razor'}, {'id': 10576, 'synset': 'safety_valve.n.01', 'name': 'safety_valve'}, {'id': 10577, 'synset': 'sail.n.03', 'name': 'sail'}, {'id': 10578, 'synset': 'sailboat.n.01', 'name': 'sailboat'}, {'id': 10579, 'synset': 'sailcloth.n.01', 'name': 'sailcloth'}, {'id': 10580, 'synset': 'sailing_vessel.n.01', 'name': 'sailing_vessel'}, {'id': 10581, 'synset': 'sailing_warship.n.01', 'name': 'sailing_warship'}, {'id': 10582, 'synset': 'sailor_cap.n.01', 'name': 'sailor_cap'}, {'id': 10583, 'synset': 'sailor_suit.n.01', 'name': 'sailor_suit'}, {'id': 10584, 'synset': 'salad_bar.n.01', 'name': 'salad_bar'}, {'id': 10585, 'synset': 'salad_bowl.n.02', 'name': 'salad_bowl'}, {'id': 10586, 'synset': 'salinometer.n.01', 'name': 'salinometer'}, {'id': 10587, 'synset': 'sallet.n.01', 'name': 'sallet'}, {'id': 10588, 'synset': 'salon.n.03', 'name': 'salon'}, {'id': 10589, 'synset': 'salon.n.01', 'name': 'salon'}, {'id': 10590, 'synset': 'salon.n.02', 'name': 'salon'}, {'id': 10591, 'synset': 'saltbox.n.01', 'name': 'saltbox'}, {'id': 10592, 'synset': 'saltcellar.n.01', 'name': 'saltcellar'}, {'id': 10593, 'synset': 'saltworks.n.01', 'name': 'saltworks'}, {'id': 10594, 'synset': 'salver.n.01', 'name': 'salver'}, {'id': 10595, 'synset': 'salwar.n.01', 'name': 'salwar'}, {'id': 10596, 'synset': 'sam_browne_belt.n.01', 'name': 'Sam_Browne_belt'}, {'id': 10597, 'synset': 'samisen.n.01', 'name': 'samisen'}, {'id': 10598, 'synset': 'samite.n.01', 'name': 'samite'}, {'id': 10599, 'synset': 'samovar.n.01', 'name': 'samovar'}, {'id': 10600, 'synset': 'sampan.n.01', 'name': 'sampan'}, {'id': 10601, 'synset': 'sandbag.n.01', 'name': 'sandbag'}, {'id': 10602, 'synset': 'sandblaster.n.01', 'name': 'sandblaster'}, {'id': 10603, 'synset': 'sandbox.n.01', 'name': 'sandbox'}, {'id': 10604, 'synset': 'sandglass.n.01', 'name': 'sandglass'}, {'id': 10605, 'synset': 'sand_wedge.n.01', 'name': 'sand_wedge'}, {'id': 10606, 'synset': 'sandwich_board.n.01', 'name': 'sandwich_board'}, {'id': 10607, 'synset': 'sanitary_napkin.n.01', 'name': 'sanitary_napkin'}, {'id': 10608, 'synset': 'cling_film.n.01', 'name': 'cling_film'}, {'id': 10609, 'synset': 'sarcenet.n.01', 'name': 'sarcenet'}, {'id': 10610, 'synset': 'sarcophagus.n.01', 'name': 'sarcophagus'}, {'id': 10611, 'synset': 'sari.n.01', 'name': 'sari'}, {'id': 10612, 'synset': 'sarong.n.01', 'name': 'sarong'}, {'id': 10613, 'synset': 'sash.n.01', 'name': 'sash'}, {'id': 10614, 'synset': 'sash_fastener.n.01', 'name': 'sash_fastener'}, {'id': 10615, 'synset': 'sash_window.n.01', 'name': 'sash_window'}, {'id': 10616, 'synset': 'sateen.n.01', 'name': 'sateen'}, {'id': 10617, 'synset': 'satellite.n.01', 'name': 'satellite'}, {'id': 10618, 'synset': 'satellite_receiver.n.01', 'name': 'satellite_receiver'}, {'id': 10619, 'synset': 'satellite_television.n.01', 'name': 'satellite_television'}, {'id': 10620, 'synset': 'satellite_transmitter.n.01', 'name': 'satellite_transmitter'}, {'id': 10621, 'synset': 'satin.n.01', 'name': 'satin'}, {'id': 10622, 'synset': 'saturday_night_special.n.01', 'name': 'Saturday_night_special'}, {'id': 10623, 'synset': 'saucepot.n.01', 'name': 'saucepot'}, {'id': 10624, 'synset': 'sauna.n.01', 'name': 'sauna'}, {'id': 10625, 'synset': 'savings_bank.n.02', 'name': 'savings_bank'}, {'id': 10626, 'synset': 'saw.n.02', 'name': 'saw'}, {'id': 10627, 'synset': 'sawed-off_shotgun.n.01', 'name': 'sawed-off_shotgun'}, {'id': 10628, 'synset': 'sawmill.n.01', 'name': 'sawmill'}, {'id': 10629, 'synset': 'saw_set.n.01', 'name': 'saw_set'}, {'id': 10630, 'synset': 'saxhorn.n.01', 'name': 'saxhorn'}, {'id': 10631, 'synset': 'scabbard.n.01', 'name': 'scabbard'}, {'id': 10632, 'synset': 'scaffolding.n.01', 'name': 'scaffolding'}, {'id': 10633, 'synset': 'scale.n.08', 'name': 'scale'}, {'id': 10634, 'synset': 'scaler.n.01', 'name': 'scaler'}, {'id': 10635, 'synset': 'scaling_ladder.n.01', 'name': 'scaling_ladder'}, {'id': 10636, 'synset': 'scalpel.n.01', 'name': 'scalpel'}, {'id': 10637, 'synset': 'scanner.n.04', 'name': 'scanner'}, {'id': 10638, 'synset': 'scanner.n.03', 'name': 'scanner'}, {'id': 10639, 'synset': 'scanner.n.02', 'name': 'scanner'}, {'id': 10640, 'synset': 'scantling.n.01', 'name': 'scantling'}, {'id': 10641, 'synset': 'scarf_joint.n.01', 'name': 'scarf_joint'}, {'id': 10642, 'synset': 'scatter_rug.n.01', 'name': 'scatter_rug'}, {'id': 10643, 'synset': 'scauper.n.01', 'name': 'scauper'}, {'id': 10644, 'synset': 'schmidt_telescope.n.01', 'name': 'Schmidt_telescope'}, {'id': 10645, 'synset': 'school.n.02', 'name': 'school'}, {'id': 10646, 'synset': 'schoolbag.n.01', 'name': 'schoolbag'}, {'id': 10647, 'synset': 'school_bell.n.01', 'name': 'school_bell'}, {'id': 10648, 'synset': 'school_ship.n.01', 'name': 'school_ship'}, {'id': 10649, 'synset': 'school_system.n.01', 'name': 'school_system'}, {'id': 10650, 'synset': 'schooner.n.02', 'name': 'schooner'}, {'id': 10651, 'synset': 'schooner.n.01', 'name': 'schooner'}, {'id': 10652, 'synset': 'scientific_instrument.n.01', 'name': 'scientific_instrument'}, {'id': 10653, 'synset': 'scimitar.n.01', 'name': 'scimitar'}, {'id': 10654, 'synset': 'scintillation_counter.n.01', 'name': 'scintillation_counter'}, {'id': 10655, 'synset': 'sclerometer.n.01', 'name': 'sclerometer'}, {'id': 10656, 'synset': 'scoinson_arch.n.01', 'name': 'scoinson_arch'}, {'id': 10657, 'synset': 'sconce.n.04', 'name': 'sconce'}, {'id': 10658, 'synset': 'sconce.n.03', 'name': 'sconce'}, {'id': 10659, 'synset': 'scoop.n.06', 'name': 'scoop'}, {'id': 10660, 'synset': 'scooter.n.02', 'name': 'scooter'}, {'id': 10661, 'synset': 'scouring_pad.n.01', 'name': 'scouring_pad'}, {'id': 10662, 'synset': 'scow.n.02', 'name': 'scow'}, {'id': 10663, 'synset': 'scow.n.01', 'name': 'scow'}, {'id': 10664, 'synset': 'scratcher.n.03', 'name': 'scratcher'}, {'id': 10665, 'synset': 'screen.n.05', 'name': 'screen'}, {'id': 10666, 'synset': 'screen.n.04', 'name': 'screen'}, {'id': 10667, 'synset': 'screen.n.09', 'name': 'screen'}, {'id': 10668, 'synset': 'screen.n.03', 'name': 'screen'}, {'id': 10669, 'synset': 'screen_door.n.01', 'name': 'screen_door'}, {'id': 10670, 'synset': 'screening.n.02', 'name': 'screening'}, {'id': 10671, 'synset': 'screw.n.04', 'name': 'screw'}, {'id': 10672, 'synset': 'screw.n.03', 'name': 'screw'}, {'id': 10673, 'synset': 'screw.n.02', 'name': 'screw'}, {'id': 10674, 'synset': 'screw_eye.n.01', 'name': 'screw_eye'}, {'id': 10675, 'synset': 'screw_key.n.01', 'name': 'screw_key'}, {'id': 10676, 'synset': 'screw_thread.n.01', 'name': 'screw_thread'}, {'id': 10677, 'synset': 'screwtop.n.01', 'name': 'screwtop'}, {'id': 10678, 'synset': 'screw_wrench.n.01', 'name': 'screw_wrench'}, {'id': 10679, 'synset': 'scriber.n.01', 'name': 'scriber'}, {'id': 10680, 'synset': 'scrim.n.01', 'name': 'scrim'}, {'id': 10681, 'synset': 'scrimshaw.n.01', 'name': 'scrimshaw'}, {'id': 10682, 'synset': 'scriptorium.n.01', 'name': 'scriptorium'}, {'id': 10683, 'synset': 'scrubber.n.03', 'name': 'scrubber'}, {'id': 10684, 'synset': 'scrub_plane.n.01', 'name': 'scrub_plane'}, {'id': 10685, 'synset': 'scuffer.n.01', 'name': 'scuffer'}, {'id': 10686, 'synset': 'scuffle.n.02', 'name': 'scuffle'}, {'id': 10687, 'synset': 'scull.n.02', 'name': 'scull'}, {'id': 10688, 'synset': 'scull.n.01', 'name': 'scull'}, {'id': 10689, 'synset': 'scullery.n.01', 'name': 'scullery'}, {'id': 10690, 'synset': 'scuttle.n.01', 'name': 'scuttle'}, {'id': 10691, 'synset': 'scyphus.n.01', 'name': 'scyphus'}, {'id': 10692, 'synset': 'scythe.n.01', 'name': 'scythe'}, {'id': 10693, 'synset': 'seabag.n.01', 'name': 'seabag'}, {'id': 10694, 'synset': 'sea_boat.n.01', 'name': 'sea_boat'}, {'id': 10695, 'synset': 'sea_chest.n.01', 'name': 'sea_chest'}, {'id': 10696, 'synset': 'sealing_wax.n.01', 'name': 'sealing_wax'}, {'id': 10697, 'synset': 'sealskin.n.02', 'name': 'sealskin'}, {'id': 10698, 'synset': 'seam.n.01', 'name': 'seam'}, {'id': 10699, 'synset': 'searchlight.n.01', 'name': 'searchlight'}, {'id': 10700, 'synset': 'searing_iron.n.01', 'name': 'searing_iron'}, {'id': 10701, 'synset': 'seat.n.04', 'name': 'seat'}, {'id': 10702, 'synset': 'seat.n.03', 'name': 'seat'}, {'id': 10703, 'synset': 'seat.n.09', 'name': 'seat'}, {'id': 10704, 'synset': 'seat_belt.n.01', 'name': 'seat_belt'}, {'id': 10705, 'synset': 'secateurs.n.01', 'name': 'secateurs'}, {'id': 10706, 'synset': 'secondary_coil.n.01', 'name': 'secondary_coil'}, {'id': 10707, 'synset': 'second_balcony.n.01', 'name': 'second_balcony'}, {'id': 10708, 'synset': 'second_base.n.01', 'name': 'second_base'}, {'id': 10709, 'synset': 'second_hand.n.02', 'name': 'second_hand'}, {'id': 10710, 'synset': 'secretary.n.04', 'name': 'secretary'}, {'id': 10711, 'synset': 'sectional.n.01', 'name': 'sectional'}, {'id': 10712, 'synset': 'security_blanket.n.02', 'name': 'security_blanket'}, {'id': 10713, 'synset': 'security_system.n.02', 'name': 'security_system'}, {'id': 10714, 'synset': 'security_system.n.01', 'name': 'security_system'}, {'id': 10715, 'synset': 'sedan.n.01', 'name': 'sedan'}, {'id': 10716, 'synset': 'sedan.n.02', 'name': 'sedan'}, {'id': 10717, 'synset': 'seeder.n.02', 'name': 'seeder'}, {'id': 10718, 'synset': 'seeker.n.02', 'name': 'seeker'}, {'id': 10719, 'synset': 'seersucker.n.01', 'name': 'seersucker'}, {'id': 10720, 'synset': 'segmental_arch.n.01', 'name': 'segmental_arch'}, {'id': 10721, 'synset': 'segway.n.01', 'name': 'Segway'}, {'id': 10722, 'synset': 'seidel.n.01', 'name': 'seidel'}, {'id': 10723, 'synset': 'seine.n.02', 'name': 'seine'}, {'id': 10724, 'synset': 'seismograph.n.01', 'name': 'seismograph'}, {'id': 10725, 'synset': 'selector.n.02', 'name': 'selector'}, {'id': 10726, 'synset': 'selenium_cell.n.01', 'name': 'selenium_cell'}, {'id': 10727, 'synset': 'self-propelled_vehicle.n.01', 'name': 'self-propelled_vehicle'}, {'id': 10728, 'synset': 'self-registering_thermometer.n.01', 'name': 'self-registering_thermometer'}, {'id': 10729, 'synset': 'self-starter.n.02', 'name': 'self-starter'}, {'id': 10730, 'synset': 'selsyn.n.01', 'name': 'selsyn'}, {'id': 10731, 'synset': 'selvage.n.02', 'name': 'selvage'}, {'id': 10732, 'synset': 'semaphore.n.01', 'name': 'semaphore'}, {'id': 10733, 'synset': 'semiautomatic_firearm.n.01', 'name': 'semiautomatic_firearm'}, {'id': 10734, 'synset': 'semiautomatic_pistol.n.01', 'name': 'semiautomatic_pistol'}, {'id': 10735, 'synset': 'semiconductor_device.n.01', 'name': 'semiconductor_device'}, {'id': 10736, 'synset': 'semi-detached_house.n.01', 'name': 'semi-detached_house'}, {'id': 10737, 'synset': 'semigloss.n.01', 'name': 'semigloss'}, {'id': 10738, 'synset': 'semitrailer.n.01', 'name': 'semitrailer'}, {'id': 10739, 'synset': 'sennit.n.01', 'name': 'sennit'}, {'id': 10740, 'synset': 'sensitometer.n.01', 'name': 'sensitometer'}, {'id': 10741, 'synset': 'sentry_box.n.01', 'name': 'sentry_box'}, {'id': 10742, 'synset': 'separate.n.02', 'name': 'separate'}, {'id': 10743, 'synset': 'septic_tank.n.01', 'name': 'septic_tank'}, {'id': 10744, 'synset': 'sequence.n.03', 'name': 'sequence'}, {'id': 10745, 'synset': 'sequencer.n.01', 'name': 'sequencer'}, {'id': 10746, 'synset': 'serape.n.01', 'name': 'serape'}, {'id': 10747, 'synset': 'serge.n.01', 'name': 'serge'}, {'id': 10748, 'synset': 'serger.n.01', 'name': 'serger'}, {'id': 10749, 'synset': 'serial_port.n.01', 'name': 'serial_port'}, {'id': 10750, 'synset': 'serpent.n.03', 'name': 'serpent'}, {'id': 10751, 'synset': 'serration.n.03', 'name': 'serration'}, {'id': 10752, 'synset': 'server.n.04', 'name': 'server'}, {'id': 10753, 'synset': 'server.n.03', 'name': 'server'}, {'id': 10754, 'synset': 'service_club.n.02', 'name': 'service_club'}, {'id': 10755, 'synset': 'serving_cart.n.01', 'name': 'serving_cart'}, {'id': 10756, 'synset': 'serving_dish.n.01', 'name': 'serving_dish'}, {'id': 10757, 'synset': 'servo.n.01', 'name': 'servo'}, {'id': 10758, 'synset': 'set.n.13', 'name': 'set'}, {'id': 10759, 'synset': 'set_gun.n.01', 'name': 'set_gun'}, {'id': 10760, 'synset': 'setscrew.n.02', 'name': 'setscrew'}, {'id': 10761, 'synset': 'setscrew.n.01', 'name': 'setscrew'}, {'id': 10762, 'synset': 'set_square.n.01', 'name': 'set_square'}, {'id': 10763, 'synset': 'settee.n.02', 'name': 'settee'}, {'id': 10764, 'synset': 'settle.n.01', 'name': 'settle'}, {'id': 10765, 'synset': 'settlement_house.n.01', 'name': 'settlement_house'}, {'id': 10766, 'synset': 'seventy-eight.n.02', 'name': 'seventy-eight'}, {'id': 10767, 'synset': 'seven_wonders_of_the_ancient_world.n.01', 'name': 'Seven_Wonders_of_the_Ancient_World'}, {'id': 10768, 'synset': 'sewage_disposal_plant.n.01', 'name': 'sewage_disposal_plant'}, {'id': 10769, 'synset': 'sewer.n.01', 'name': 'sewer'}, {'id': 10770, 'synset': 'sewing_basket.n.01', 'name': 'sewing_basket'}, {'id': 10771, 'synset': 'sewing_kit.n.01', 'name': 'sewing_kit'}, {'id': 10772, 'synset': 'sewing_needle.n.01', 'name': 'sewing_needle'}, {'id': 10773, 'synset': 'sewing_room.n.01', 'name': 'sewing_room'}, {'id': 10774, 'synset': 'sextant.n.02', 'name': 'sextant'}, {'id': 10775, 'synset': 'sgraffito.n.01', 'name': 'sgraffito'}, {'id': 10776, 'synset': 'shackle.n.01', 'name': 'shackle'}, {'id': 10777, 'synset': 'shackle.n.02', 'name': 'shackle'}, {'id': 10778, 'synset': 'shade.n.03', 'name': 'shade'}, {'id': 10779, 'synset': 'shadow_box.n.01', 'name': 'shadow_box'}, {'id': 10780, 'synset': 'shaft.n.03', 'name': 'shaft'}, {'id': 10781, 'synset': 'shag_rug.n.01', 'name': 'shag_rug'}, {'id': 10782, 'synset': 'shank.n.04', 'name': 'shank'}, {'id': 10783, 'synset': 'shank.n.03', 'name': 'shank'}, {'id': 10784, 'synset': 'shantung.n.01', 'name': 'shantung'}, {'id': 10785, 'synset': 'shaper.n.02', 'name': 'shaper'}, {'id': 10786, 'synset': 'shaping_tool.n.01', 'name': 'shaping_tool'}, {'id': 10787, 'synset': 'sharkskin.n.01', 'name': 'sharkskin'}, {'id': 10788, 'synset': 'shaving_brush.n.01', 'name': 'shaving_brush'}, {'id': 10789, 'synset': 'shaving_foam.n.01', 'name': 'shaving_foam'}, {'id': 10790, 'synset': 'shawm.n.01', 'name': 'shawm'}, {'id': 10791, 'synset': 'sheath.n.01', 'name': 'sheath'}, {'id': 10792, 'synset': 'sheathing.n.01', 'name': 'sheathing'}, {'id': 10793, 'synset': 'shed.n.01', 'name': 'shed'}, {'id': 10794, 'synset': 'sheep_bell.n.01', 'name': 'sheep_bell'}, {'id': 10795, 'synset': 'sheepshank.n.01', 'name': 'sheepshank'}, {'id': 10796, 'synset': 'sheepskin_coat.n.01', 'name': 'sheepskin_coat'}, {'id': 10797, 'synset': 'sheepwalk.n.01', 'name': 'sheepwalk'}, {'id': 10798, 'synset': 'sheet.n.03', 'name': 'sheet'}, {'id': 10799, 'synset': 'sheet_bend.n.01', 'name': 'sheet_bend'}, {'id': 10800, 'synset': 'sheeting.n.01', 'name': 'sheeting'}, {'id': 10801, 'synset': 'sheet_pile.n.01', 'name': 'sheet_pile'}, {'id': 10802, 'synset': 'sheetrock.n.01', 'name': 'Sheetrock'}, {'id': 10803, 'synset': 'shelf.n.01', 'name': 'shelf'}, {'id': 10804, 'synset': 'shelf_bracket.n.01', 'name': 'shelf_bracket'}, {'id': 10805, 'synset': 'shell.n.01', 'name': 'shell'}, {'id': 10806, 'synset': 'shell.n.08', 'name': 'shell'}, {'id': 10807, 'synset': 'shell.n.07', 'name': 'shell'}, {'id': 10808, 'synset': 'shellac.n.02', 'name': 'shellac'}, {'id': 10809, 'synset': 'shelter.n.01', 'name': 'shelter'}, {'id': 10810, 'synset': 'shelter.n.02', 'name': 'shelter'}, {'id': 10811, 'synset': 'shelter.n.05', 'name': 'shelter'}, {'id': 10812, 'synset': 'sheltered_workshop.n.01', 'name': 'sheltered_workshop'}, {'id': 10813, 'synset': 'sheraton.n.01', 'name': 'Sheraton'}, {'id': 10814, 'synset': 'shield.n.01', 'name': 'shield'}, {'id': 10815, 'synset': 'shielding.n.03', 'name': 'shielding'}, {'id': 10816, 'synset': 'shift_key.n.01', 'name': 'shift_key'}, {'id': 10817, 'synset': 'shillelagh.n.01', 'name': 'shillelagh'}, {'id': 10818, 'synset': 'shim.n.01', 'name': 'shim'}, {'id': 10819, 'synset': 'shingle.n.03', 'name': 'shingle'}, {'id': 10820, 'synset': 'shin_guard.n.01', 'name': 'shin_guard'}, {'id': 10821, 'synset': 'ship.n.01', 'name': 'ship'}, {'id': 10822, 'synset': 'shipboard_system.n.01', 'name': 'shipboard_system'}, {'id': 10823, 'synset': 'shipping.n.02', 'name': 'shipping'}, {'id': 10824, 'synset': 'shipping_room.n.01', 'name': 'shipping_room'}, {'id': 10825, 'synset': 'ship-towed_long-range_acoustic_detection_system.n.01', 'name': 'ship-towed_long-range_acoustic_detection_system'}, {'id': 10826, 'synset': 'shipwreck.n.01', 'name': 'shipwreck'}, {'id': 10827, 'synset': 'shirt_button.n.01', 'name': 'shirt_button'}, {'id': 10828, 'synset': 'shirtdress.n.01', 'name': 'shirtdress'}, {'id': 10829, 'synset': 'shirtfront.n.01', 'name': 'shirtfront'}, {'id': 10830, 'synset': 'shirting.n.01', 'name': 'shirting'}, {'id': 10831, 'synset': 'shirtsleeve.n.01', 'name': 'shirtsleeve'}, {'id': 10832, 'synset': 'shirttail.n.02', 'name': 'shirttail'}, {'id': 10833, 'synset': 'shirtwaist.n.01', 'name': 'shirtwaist'}, {'id': 10834, 'synset': 'shiv.n.01', 'name': 'shiv'}, {'id': 10835, 'synset': 'shock_absorber.n.01', 'name': 'shock_absorber'}, {'id': 10836, 'synset': 'shoe.n.02', 'name': 'shoe'}, {'id': 10837, 'synset': 'shoebox.n.02', 'name': 'shoebox'}, {'id': 10838, 'synset': 'shoehorn.n.01', 'name': 'shoehorn'}, {'id': 10839, 'synset': 'shoe_shop.n.01', 'name': 'shoe_shop'}, {'id': 10840, 'synset': 'shoetree.n.01', 'name': 'shoetree'}, {'id': 10841, 'synset': 'shofar.n.01', 'name': 'shofar'}, {'id': 10842, 'synset': 'shoji.n.01', 'name': 'shoji'}, {'id': 10843, 'synset': 'shooting_brake.n.01', 'name': 'shooting_brake'}, {'id': 10844, 'synset': 'shooting_lodge.n.01', 'name': 'shooting_lodge'}, {'id': 10845, 'synset': 'shooting_stick.n.01', 'name': 'shooting_stick'}, {'id': 10846, 'synset': 'shop.n.01', 'name': 'shop'}, {'id': 10847, 'synset': 'shop_bell.n.01', 'name': 'shop_bell'}, {'id': 10848, 'synset': 'shopping_basket.n.01', 'name': 'shopping_basket'}, {'id': 10849, 'synset': 'short_circuit.n.01', 'name': 'short_circuit'}, {'id': 10850, 'synset': 'short_iron.n.01', 'name': 'short_iron'}, {'id': 10851, 'synset': 'short_sleeve.n.01', 'name': 'short_sleeve'}, {'id': 10852, 'synset': 'shortwave_diathermy_machine.n.01', 'name': 'shortwave_diathermy_machine'}, {'id': 10853, 'synset': 'shot.n.12', 'name': 'shot'}, {'id': 10854, 'synset': 'shotgun.n.01', 'name': 'shotgun'}, {'id': 10855, 'synset': 'shotgun_shell.n.01', 'name': 'shotgun_shell'}, {'id': 10856, 'synset': 'shot_tower.n.01', 'name': 'shot_tower'}, {'id': 10857, 'synset': 'shoulder.n.04', 'name': 'shoulder'}, {'id': 10858, 'synset': 'shouldered_arch.n.01', 'name': 'shouldered_arch'}, {'id': 10859, 'synset': 'shoulder_holster.n.01', 'name': 'shoulder_holster'}, {'id': 10860, 'synset': 'shoulder_pad.n.01', 'name': 'shoulder_pad'}, {'id': 10861, 'synset': 'shoulder_patch.n.01', 'name': 'shoulder_patch'}, {'id': 10862, 'synset': 'shovel.n.03', 'name': 'shovel'}, {'id': 10863, 'synset': 'shovel_hat.n.01', 'name': 'shovel_hat'}, {'id': 10864, 'synset': 'showboat.n.01', 'name': 'showboat'}, {'id': 10865, 'synset': 'shower_room.n.01', 'name': 'shower_room'}, {'id': 10866, 'synset': 'shower_stall.n.01', 'name': 'shower_stall'}, {'id': 10867, 'synset': 'showroom.n.01', 'name': 'showroom'}, {'id': 10868, 'synset': 'shrapnel.n.01', 'name': 'shrapnel'}, {'id': 10869, 'synset': 'shrimper.n.01', 'name': 'shrimper'}, {'id': 10870, 'synset': 'shrine.n.01', 'name': 'shrine'}, {'id': 10871, 'synset': 'shrink-wrap.n.01', 'name': 'shrink-wrap'}, {'id': 10872, 'synset': 'shunt.n.03', 'name': 'shunt'}, {'id': 10873, 'synset': 'shunt.n.02', 'name': 'shunt'}, {'id': 10874, 'synset': 'shunter.n.01', 'name': 'shunter'}, {'id': 10875, 'synset': 'shutter.n.02', 'name': 'shutter'}, {'id': 10876, 'synset': 'shutter.n.01', 'name': 'shutter'}, {'id': 10877, 'synset': 'shuttle.n.03', 'name': 'shuttle'}, {'id': 10878, 'synset': 'shuttle.n.02', 'name': 'shuttle'}, {'id': 10879, 'synset': 'shuttle_bus.n.01', 'name': 'shuttle_bus'}, {'id': 10880, 'synset': 'shuttlecock.n.01', 'name': 'shuttlecock'}, {'id': 10881, 'synset': 'shuttle_helicopter.n.01', 'name': 'shuttle_helicopter'}, {'id': 10882, 'synset': 'sibley_tent.n.01', 'name': 'Sibley_tent'}, {'id': 10883, 'synset': 'sickbay.n.01', 'name': 'sickbay'}, {'id': 10884, 'synset': 'sickbed.n.01', 'name': 'sickbed'}, {'id': 10885, 'synset': 'sickle.n.01', 'name': 'sickle'}, {'id': 10886, 'synset': 'sickroom.n.01', 'name': 'sickroom'}, {'id': 10887, 'synset': 'sideboard.n.02', 'name': 'sideboard'}, {'id': 10888, 'synset': 'sidecar.n.02', 'name': 'sidecar'}, {'id': 10889, 'synset': 'side_chapel.n.01', 'name': 'side_chapel'}, {'id': 10890, 'synset': 'sidelight.n.01', 'name': 'sidelight'}, {'id': 10891, 'synset': 'sidesaddle.n.01', 'name': 'sidesaddle'}, {'id': 10892, 'synset': 'sidewalk.n.01', 'name': 'sidewalk'}, {'id': 10893, 'synset': 'sidewall.n.02', 'name': 'sidewall'}, {'id': 10894, 'synset': 'side-wheeler.n.01', 'name': 'side-wheeler'}, {'id': 10895, 'synset': 'sidewinder.n.02', 'name': 'sidewinder'}, {'id': 10896, 'synset': 'sieve.n.01', 'name': 'sieve'}, {'id': 10897, 'synset': 'sifter.n.01', 'name': 'sifter'}, {'id': 10898, 'synset': 'sights.n.01', 'name': 'sights'}, {'id': 10899, 'synset': 'sigmoidoscope.n.01', 'name': 'sigmoidoscope'}, {'id': 10900, 'synset': 'signal_box.n.01', 'name': 'signal_box'}, {'id': 10901, 'synset': 'signaling_device.n.01', 'name': 'signaling_device'}, {'id': 10902, 'synset': 'silencer.n.02', 'name': 'silencer'}, {'id': 10903, 'synset': 'silent_butler.n.01', 'name': 'silent_butler'}, {'id': 10904, 'synset': 'silex.n.02', 'name': 'Silex'}, {'id': 10905, 'synset': 'silk.n.01', 'name': 'silk'}, {'id': 10906, 'synset': 'silks.n.01', 'name': 'silks'}, {'id': 10907, 'synset': 'silver_plate.n.02', 'name': 'silver_plate'}, {'id': 10908, 'synset': 'silverpoint.n.01', 'name': 'silverpoint'}, {'id': 10909, 'synset': 'simple_pendulum.n.01', 'name': 'simple_pendulum'}, {'id': 10910, 'synset': 'simulator.n.01', 'name': 'simulator'}, {'id': 10911, 'synset': 'single_bed.n.01', 'name': 'single_bed'}, {'id': 10912, 'synset': 'single-breasted_jacket.n.01', 'name': 'single-breasted_jacket'}, {'id': 10913, 'synset': 'single-breasted_suit.n.01', 'name': 'single-breasted_suit'}, {'id': 10914, 'synset': 'single_prop.n.01', 'name': 'single_prop'}, {'id': 10915, 'synset': 'single-reed_instrument.n.01', 'name': 'single-reed_instrument'}, {'id': 10916, 'synset': 'single-rotor_helicopter.n.01', 'name': 'single-rotor_helicopter'}, {'id': 10917, 'synset': 'singlestick.n.01', 'name': 'singlestick'}, {'id': 10918, 'synset': 'singlet.n.01', 'name': 'singlet'}, {'id': 10919, 'synset': 'siren.n.04', 'name': 'siren'}, {'id': 10920, 'synset': 'sister_ship.n.01', 'name': 'sister_ship'}, {'id': 10921, 'synset': 'sitar.n.01', 'name': 'sitar'}, {'id': 10922, 'synset': 'sitz_bath.n.01', 'name': 'sitz_bath'}, {'id': 10923, 'synset': 'six-pack.n.01', 'name': 'six-pack'}, {'id': 10924, 'synset': 'skate.n.01', 'name': 'skate'}, {'id': 10925, 'synset': 'skeg.n.01', 'name': 'skeg'}, {'id': 10926, 'synset': 'skein.n.01', 'name': 'skein'}, {'id': 10927, 'synset': 'skeleton.n.04', 'name': 'skeleton'}, {'id': 10928, 'synset': 'skeleton_key.n.01', 'name': 'skeleton_key'}, {'id': 10929, 'synset': 'skep.n.02', 'name': 'skep'}, {'id': 10930, 'synset': 'skep.n.01', 'name': 'skep'}, {'id': 10931, 'synset': 'sketch.n.01', 'name': 'sketch'}, {'id': 10932, 'synset': 'sketcher.n.02', 'name': 'sketcher'}, {'id': 10933, 'synset': 'skew_arch.n.01', 'name': 'skew_arch'}, {'id': 10934, 'synset': 'ski_binding.n.01', 'name': 'ski_binding'}, {'id': 10935, 'synset': 'skibob.n.01', 'name': 'skibob'}, {'id': 10936, 'synset': 'ski_cap.n.01', 'name': 'ski_cap'}, {'id': 10937, 'synset': 'skidder.n.03', 'name': 'skidder'}, {'id': 10938, 'synset': 'skid_lid.n.01', 'name': 'skid_lid'}, {'id': 10939, 'synset': 'skiff.n.01', 'name': 'skiff'}, {'id': 10940, 'synset': 'ski_jump.n.01', 'name': 'ski_jump'}, {'id': 10941, 'synset': 'ski_lodge.n.01', 'name': 'ski_lodge'}, {'id': 10942, 'synset': 'ski_mask.n.01', 'name': 'ski_mask'}, {'id': 10943, 'synset': 'skimmer.n.02', 'name': 'skimmer'}, {'id': 10944, 'synset': 'ski-plane.n.01', 'name': 'ski-plane'}, {'id': 10945, 'synset': 'ski_rack.n.01', 'name': 'ski_rack'}, {'id': 10946, 'synset': 'skirt.n.01', 'name': 'skirt'}, {'id': 10947, 'synset': 'ski_tow.n.01', 'name': 'ski_tow'}, {'id': 10948, 'synset': 'skivvies.n.01', 'name': 'Skivvies'}, {'id': 10949, 'synset': 'skybox.n.01', 'name': 'skybox'}, {'id': 10950, 'synset': 'skyhook.n.02', 'name': 'skyhook'}, {'id': 10951, 'synset': 'skylight.n.01', 'name': 'skylight'}, {'id': 10952, 'synset': 'skysail.n.01', 'name': 'skysail'}, {'id': 10953, 'synset': 'skyscraper.n.01', 'name': 'skyscraper'}, {'id': 10954, 'synset': 'skywalk.n.01', 'name': 'skywalk'}, {'id': 10955, 'synset': 'slacks.n.01', 'name': 'slacks'}, {'id': 10956, 'synset': 'slack_suit.n.01', 'name': 'slack_suit'}, {'id': 10957, 'synset': 'slasher.n.02', 'name': 'slasher'}, {'id': 10958, 'synset': 'slash_pocket.n.01', 'name': 'slash_pocket'}, {'id': 10959, 'synset': 'slat.n.01', 'name': 'slat'}, {'id': 10960, 'synset': 'slate.n.01', 'name': 'slate'}, {'id': 10961, 'synset': 'slate_pencil.n.01', 'name': 'slate_pencil'}, {'id': 10962, 'synset': 'slate_roof.n.01', 'name': 'slate_roof'}, {'id': 10963, 'synset': 'sleeper.n.07', 'name': 'sleeper'}, {'id': 10964, 'synset': 'sleeper.n.06', 'name': 'sleeper'}, {'id': 10965, 'synset': 'sleeping_car.n.01', 'name': 'sleeping_car'}, {'id': 10966, 'synset': 'sleeve.n.01', 'name': 'sleeve'}, {'id': 10967, 'synset': 'sleeve.n.02', 'name': 'sleeve'}, {'id': 10968, 'synset': 'sleigh_bed.n.01', 'name': 'sleigh_bed'}, {'id': 10969, 'synset': 'sleigh_bell.n.01', 'name': 'sleigh_bell'}, {'id': 10970, 'synset': 'slice_bar.n.01', 'name': 'slice_bar'}, {'id': 10971, 'synset': 'slicer.n.03', 'name': 'slicer'}, {'id': 10972, 'synset': 'slicer.n.02', 'name': 'slicer'}, {'id': 10973, 'synset': 'slide.n.04', 'name': 'slide'}, {'id': 10974, 'synset': 'slide_fastener.n.01', 'name': 'slide_fastener'}, {'id': 10975, 'synset': 'slide_projector.n.01', 'name': 'slide_projector'}, {'id': 10976, 'synset': 'slide_rule.n.01', 'name': 'slide_rule'}, {'id': 10977, 'synset': 'slide_valve.n.01', 'name': 'slide_valve'}, {'id': 10978, 'synset': 'sliding_door.n.01', 'name': 'sliding_door'}, {'id': 10979, 'synset': 'sliding_seat.n.01', 'name': 'sliding_seat'}, {'id': 10980, 'synset': 'sliding_window.n.01', 'name': 'sliding_window'}, {'id': 10981, 'synset': 'sling.n.04', 'name': 'sling'}, {'id': 10982, 'synset': 'slingback.n.01', 'name': 'slingback'}, {'id': 10983, 'synset': 'slinger_ring.n.01', 'name': 'slinger_ring'}, {'id': 10984, 'synset': 'slip_clutch.n.01', 'name': 'slip_clutch'}, {'id': 10985, 'synset': 'slipcover.n.01', 'name': 'slipcover'}, {'id': 10986, 'synset': 'slip-joint_pliers.n.01', 'name': 'slip-joint_pliers'}, {'id': 10987, 'synset': 'slipknot.n.01', 'name': 'slipknot'}, {'id': 10988, 'synset': 'slip-on.n.01', 'name': 'slip-on'}, {'id': 10989, 'synset': 'slip_ring.n.01', 'name': 'slip_ring'}, {'id': 10990, 'synset': 'slit_lamp.n.01', 'name': 'slit_lamp'}, {'id': 10991, 'synset': 'slit_trench.n.01', 'name': 'slit_trench'}, {'id': 10992, 'synset': 'sloop.n.01', 'name': 'sloop'}, {'id': 10993, 'synset': 'sloop_of_war.n.01', 'name': 'sloop_of_war'}, {'id': 10994, 'synset': 'slop_basin.n.01', 'name': 'slop_basin'}, {'id': 10995, 'synset': 'slop_pail.n.01', 'name': 'slop_pail'}, {'id': 10996, 'synset': 'slops.n.02', 'name': 'slops'}, {'id': 10997, 'synset': 'slopshop.n.01', 'name': 'slopshop'}, {'id': 10998, 'synset': 'slot.n.07', 'name': 'slot'}, {'id': 10999, 'synset': 'slot_machine.n.01', 'name': 'slot_machine'}, {'id': 11000, 'synset': 'sluice.n.01', 'name': 'sluice'}, {'id': 11001, 'synset': 'smack.n.03', 'name': 'smack'}, {'id': 11002, 'synset': 'small_boat.n.01', 'name': 'small_boat'}, {'id': 11003, 'synset': 'small_computer_system_interface.n.01', 'name': 'small_computer_system_interface'}, {'id': 11004, 'synset': 'small_ship.n.01', 'name': 'small_ship'}, {'id': 11005, 'synset': 'small_stores.n.01', 'name': 'small_stores'}, {'id': 11006, 'synset': 'smart_bomb.n.01', 'name': 'smart_bomb'}, {'id': 11007, 'synset': 'smelling_bottle.n.01', 'name': 'smelling_bottle'}, {'id': 11008, 'synset': 'smocking.n.01', 'name': 'smocking'}, {'id': 11009, 'synset': 'smoke_bomb.n.01', 'name': 'smoke_bomb'}, {'id': 11010, 'synset': 'smokehouse.n.01', 'name': 'smokehouse'}, {'id': 11011, 'synset': 'smoker.n.03', 'name': 'smoker'}, {'id': 11012, 'synset': 'smoke_screen.n.01', 'name': 'smoke_screen'}, {'id': 11013, 'synset': 'smoking_room.n.01', 'name': 'smoking_room'}, {'id': 11014, 'synset': 'smoothbore.n.01', 'name': 'smoothbore'}, {'id': 11015, 'synset': 'smooth_plane.n.01', 'name': 'smooth_plane'}, {'id': 11016, 'synset': 'snack_bar.n.01', 'name': 'snack_bar'}, {'id': 11017, 'synset': 'snaffle.n.01', 'name': 'snaffle'}, {'id': 11018, 'synset': 'snap.n.10', 'name': 'snap'}, {'id': 11019, 'synset': 'snap_brim.n.01', 'name': 'snap_brim'}, {'id': 11020, 'synset': 'snap-brim_hat.n.01', 'name': 'snap-brim_hat'}, {'id': 11021, 'synset': 'snare.n.05', 'name': 'snare'}, {'id': 11022, 'synset': 'snare_drum.n.01', 'name': 'snare_drum'}, {'id': 11023, 'synset': 'snatch_block.n.01', 'name': 'snatch_block'}, {'id': 11024, 'synset': 'snifter.n.01', 'name': 'snifter'}, {'id': 11025, 'synset': 'sniper_rifle.n.01', 'name': 'sniper_rifle'}, {'id': 11026, 'synset': 'snips.n.01', 'name': 'snips'}, {'id': 11027, 'synset': 'sno-cat.n.01', 'name': 'Sno-cat'}, {'id': 11028, 'synset': 'snood.n.01', 'name': 'snood'}, {'id': 11029, 'synset': 'snorkel.n.02', 'name': 'snorkel'}, {'id': 11030, 'synset': 'snorkel.n.01', 'name': 'snorkel'}, {'id': 11031, 'synset': 'snowbank.n.01', 'name': 'snowbank'}, {'id': 11032, 'synset': 'snowplow.n.01', 'name': 'snowplow'}, {'id': 11033, 'synset': 'snowshoe.n.01', 'name': 'snowshoe'}, {'id': 11034, 'synset': 'snowsuit.n.01', 'name': 'snowsuit'}, {'id': 11035, 'synset': 'snow_thrower.n.01', 'name': 'snow_thrower'}, {'id': 11036, 'synset': 'snuffbox.n.01', 'name': 'snuffbox'}, {'id': 11037, 'synset': 'snuffer.n.01', 'name': 'snuffer'}, {'id': 11038, 'synset': 'snuffers.n.01', 'name': 'snuffers'}, {'id': 11039, 'synset': 'soapbox.n.01', 'name': 'soapbox'}, {'id': 11040, 'synset': 'soap_dish.n.01', 'name': 'soap_dish'}, {'id': 11041, 'synset': 'soap_dispenser.n.01', 'name': 'soap_dispenser'}, {'id': 11042, 'synset': 'soap_pad.n.01', 'name': 'soap_pad'}, {'id': 11043, 'synset': 'socket.n.02', 'name': 'socket'}, {'id': 11044, 'synset': 'socket_wrench.n.01', 'name': 'socket_wrench'}, {'id': 11045, 'synset': 'socle.n.01', 'name': 'socle'}, {'id': 11046, 'synset': 'soda_can.n.01', 'name': 'soda_can'}, {'id': 11047, 'synset': 'soda_fountain.n.02', 'name': 'soda_fountain'}, {'id': 11048, 'synset': 'soda_fountain.n.01', 'name': 'soda_fountain'}, {'id': 11049, 'synset': 'sod_house.n.01', 'name': 'sod_house'}, {'id': 11050, 'synset': 'sodium-vapor_lamp.n.01', 'name': 'sodium-vapor_lamp'}, {'id': 11051, 'synset': 'soffit.n.01', 'name': 'soffit'}, {'id': 11052, 'synset': 'soft_pedal.n.01', 'name': 'soft_pedal'}, {'id': 11053, 'synset': 'soil_pipe.n.01', 'name': 'soil_pipe'}, {'id': 11054, 'synset': 'solar_cell.n.01', 'name': 'solar_cell'}, {'id': 11055, 'synset': 'solar_dish.n.01', 'name': 'solar_dish'}, {'id': 11056, 'synset': 'solar_heater.n.01', 'name': 'solar_heater'}, {'id': 11057, 'synset': 'solar_house.n.01', 'name': 'solar_house'}, {'id': 11058, 'synset': 'solar_telescope.n.01', 'name': 'solar_telescope'}, {'id': 11059, 'synset': 'solar_thermal_system.n.01', 'name': 'solar_thermal_system'}, {'id': 11060, 'synset': 'soldering_iron.n.01', 'name': 'soldering_iron'}, {'id': 11061, 'synset': 'solenoid.n.01', 'name': 'solenoid'}, {'id': 11062, 'synset': 'solleret.n.01', 'name': 'solleret'}, {'id': 11063, 'synset': 'sonic_depth_finder.n.01', 'name': 'sonic_depth_finder'}, {'id': 11064, 'synset': 'sonogram.n.01', 'name': 'sonogram'}, {'id': 11065, 'synset': 'sonograph.n.01', 'name': 'sonograph'}, {'id': 11066, 'synset': 'sorter.n.02', 'name': 'sorter'}, {'id': 11067, 'synset': 'souk.n.01', 'name': 'souk'}, {'id': 11068, 'synset': 'sound_bow.n.01', 'name': 'sound_bow'}, {'id': 11069, 'synset': 'soundbox.n.01', 'name': 'soundbox'}, {'id': 11070, 'synset': 'sound_camera.n.01', 'name': 'sound_camera'}, {'id': 11071, 'synset': 'sounder.n.01', 'name': 'sounder'}, {'id': 11072, 'synset': 'sound_film.n.01', 'name': 'sound_film'}, {'id': 11073, 'synset': 'sounding_board.n.02', 'name': 'sounding_board'}, {'id': 11074, 'synset': 'sounding_rocket.n.01', 'name': 'sounding_rocket'}, {'id': 11075, 'synset': 'sound_recording.n.01', 'name': 'sound_recording'}, {'id': 11076, 'synset': 'sound_spectrograph.n.01', 'name': 'sound_spectrograph'}, {'id': 11077, 'synset': 'soup_ladle.n.01', 'name': 'soup_ladle'}, {'id': 11078, 'synset': 'source_of_illumination.n.01', 'name': 'source_of_illumination'}, {'id': 11079, 'synset': 'sourdine.n.02', 'name': 'sourdine'}, {'id': 11080, 'synset': 'soutache.n.01', 'name': 'soutache'}, {'id': 11081, 'synset': 'soutane.n.01', 'name': 'soutane'}, {'id': 11082, 'synset': "sou'wester.n.02", 'name': "sou'wester"}, {'id': 11083, 'synset': 'soybean_future.n.01', 'name': 'soybean_future'}, {'id': 11084, 'synset': 'space_bar.n.01', 'name': 'space_bar'}, {'id': 11085, 'synset': 'space_capsule.n.01', 'name': 'space_capsule'}, {'id': 11086, 'synset': 'spacecraft.n.01', 'name': 'spacecraft'}, {'id': 11087, 'synset': 'space_heater.n.01', 'name': 'space_heater'}, {'id': 11088, 'synset': 'space_helmet.n.01', 'name': 'space_helmet'}, {'id': 11089, 'synset': 'space_rocket.n.01', 'name': 'space_rocket'}, {'id': 11090, 'synset': 'space_station.n.01', 'name': 'space_station'}, {'id': 11091, 'synset': 'spacesuit.n.01', 'name': 'spacesuit'}, {'id': 11092, 'synset': 'spade.n.02', 'name': 'spade'}, {'id': 11093, 'synset': 'spade_bit.n.01', 'name': 'spade_bit'}, {'id': 11094, 'synset': 'spaghetti_junction.n.01', 'name': 'spaghetti_junction'}, {'id': 11095, 'synset': 'spandau.n.01', 'name': 'Spandau'}, {'id': 11096, 'synset': 'spandex.n.01', 'name': 'spandex'}, {'id': 11097, 'synset': 'spandrel.n.01', 'name': 'spandrel'}, {'id': 11098, 'synset': 'spanker.n.02', 'name': 'spanker'}, {'id': 11099, 'synset': 'spar.n.02', 'name': 'spar'}, {'id': 11100, 'synset': 'sparge_pipe.n.01', 'name': 'sparge_pipe'}, {'id': 11101, 'synset': 'spark_arrester.n.02', 'name': 'spark_arrester'}, {'id': 11102, 'synset': 'spark_arrester.n.01', 'name': 'spark_arrester'}, {'id': 11103, 'synset': 'spark_chamber.n.01', 'name': 'spark_chamber'}, {'id': 11104, 'synset': 'spark_coil.n.01', 'name': 'spark_coil'}, {'id': 11105, 'synset': 'spark_gap.n.01', 'name': 'spark_gap'}, {'id': 11106, 'synset': 'spark_lever.n.01', 'name': 'spark_lever'}, {'id': 11107, 'synset': 'spark_plug.n.01', 'name': 'spark_plug'}, {'id': 11108, 'synset': 'sparkplug_wrench.n.01', 'name': 'sparkplug_wrench'}, {'id': 11109, 'synset': 'spark_transmitter.n.01', 'name': 'spark_transmitter'}, {'id': 11110, 'synset': 'spat.n.02', 'name': 'spat'}, {'id': 11111, 'synset': 'spatula.n.01', 'name': 'spatula'}, {'id': 11112, 'synset': 'speakerphone.n.01', 'name': 'speakerphone'}, {'id': 11113, 'synset': 'speaking_trumpet.n.01', 'name': 'speaking_trumpet'}, {'id': 11114, 'synset': 'spear.n.02', 'name': 'spear'}, {'id': 11115, 'synset': 'specialty_store.n.01', 'name': 'specialty_store'}, {'id': 11116, 'synset': 'specimen_bottle.n.01', 'name': 'specimen_bottle'}, {'id': 11117, 'synset': 'spectacle.n.02', 'name': 'spectacle'}, {'id': 11118, 'synset': 'spectator_pump.n.01', 'name': 'spectator_pump'}, {'id': 11119, 'synset': 'spectrograph.n.01', 'name': 'spectrograph'}, {'id': 11120, 'synset': 'spectrophotometer.n.01', 'name': 'spectrophotometer'}, {'id': 11121, 'synset': 'spectroscope.n.01', 'name': 'spectroscope'}, {'id': 11122, 'synset': 'speculum.n.02', 'name': 'speculum'}, {'id': 11123, 'synset': 'speedboat.n.01', 'name': 'speedboat'}, {'id': 11124, 'synset': 'speed_bump.n.01', 'name': 'speed_bump'}, {'id': 11125, 'synset': 'speedometer.n.01', 'name': 'speedometer'}, {'id': 11126, 'synset': 'speed_skate.n.01', 'name': 'speed_skate'}, {'id': 11127, 'synset': 'spherometer.n.01', 'name': 'spherometer'}, {'id': 11128, 'synset': 'sphygmomanometer.n.01', 'name': 'sphygmomanometer'}, {'id': 11129, 'synset': 'spicemill.n.01', 'name': 'spicemill'}, {'id': 11130, 'synset': 'spider.n.03', 'name': 'spider'}, {'id': 11131, 'synset': 'spider_web.n.01', 'name': 'spider_web'}, {'id': 11132, 'synset': 'spike.n.02', 'name': 'spike'}, {'id': 11133, 'synset': 'spike.n.11', 'name': 'spike'}, {'id': 11134, 'synset': 'spindle.n.04', 'name': 'spindle'}, {'id': 11135, 'synset': 'spindle.n.03', 'name': 'spindle'}, {'id': 11136, 'synset': 'spindle.n.02', 'name': 'spindle'}, {'id': 11137, 'synset': 'spin_dryer.n.01', 'name': 'spin_dryer'}, {'id': 11138, 'synset': 'spinet.n.02', 'name': 'spinet'}, {'id': 11139, 'synset': 'spinet.n.01', 'name': 'spinet'}, {'id': 11140, 'synset': 'spinnaker.n.01', 'name': 'spinnaker'}, {'id': 11141, 'synset': 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'name': 'sport_kite'}, {'id': 11172, 'synset': 'sports_car.n.01', 'name': 'sports_car'}, {'id': 11173, 'synset': 'sports_equipment.n.01', 'name': 'sports_equipment'}, {'id': 11174, 'synset': 'sports_implement.n.01', 'name': 'sports_implement'}, {'id': 11175, 'synset': 'sport_utility.n.01', 'name': 'sport_utility'}, {'id': 11176, 'synset': 'spot.n.07', 'name': 'spot'}, {'id': 11177, 'synset': 'spot_weld.n.01', 'name': 'spot_weld'}, {'id': 11178, 'synset': 'spouter.n.02', 'name': 'spouter'}, {'id': 11179, 'synset': 'sprag.n.01', 'name': 'sprag'}, {'id': 11180, 'synset': 'spray_gun.n.01', 'name': 'spray_gun'}, {'id': 11181, 'synset': 'spray_paint.n.01', 'name': 'spray_paint'}, {'id': 11182, 'synset': 'spreader.n.01', 'name': 'spreader'}, {'id': 11183, 'synset': 'sprig.n.02', 'name': 'sprig'}, {'id': 11184, 'synset': 'spring.n.02', 'name': 'spring'}, {'id': 11185, 'synset': 'spring_balance.n.01', 'name': 'spring_balance'}, {'id': 11186, 'synset': 'springboard.n.01', 'name': 'springboard'}, {'id': 11187, 'synset': 'sprinkler.n.01', 'name': 'sprinkler'}, {'id': 11188, 'synset': 'sprinkler_system.n.01', 'name': 'sprinkler_system'}, {'id': 11189, 'synset': 'sprit.n.01', 'name': 'sprit'}, {'id': 11190, 'synset': 'spritsail.n.01', 'name': 'spritsail'}, {'id': 11191, 'synset': 'sprocket.n.02', 'name': 'sprocket'}, {'id': 11192, 'synset': 'sprocket.n.01', 'name': 'sprocket'}, {'id': 11193, 'synset': 'spun_yarn.n.01', 'name': 'spun_yarn'}, {'id': 11194, 'synset': 'spur.n.04', 'name': 'spur'}, {'id': 11195, 'synset': 'spur_gear.n.01', 'name': 'spur_gear'}, {'id': 11196, 'synset': 'sputnik.n.01', 'name': 'sputnik'}, {'id': 11197, 'synset': 'spy_satellite.n.01', 'name': 'spy_satellite'}, {'id': 11198, 'synset': 'squad_room.n.01', 'name': 'squad_room'}, {'id': 11199, 'synset': 'square.n.08', 'name': 'square'}, {'id': 11200, 'synset': 'square_knot.n.01', 'name': 'square_knot'}, {'id': 11201, 'synset': 'square-rigger.n.01', 'name': 'square-rigger'}, {'id': 11202, 'synset': 'square_sail.n.01', 'name': 'square_sail'}, {'id': 11203, 'synset': 'squash_ball.n.01', 'name': 'squash_ball'}, {'id': 11204, 'synset': 'squash_racket.n.01', 'name': 'squash_racket'}, {'id': 11205, 'synset': 'squawk_box.n.01', 'name': 'squawk_box'}, {'id': 11206, 'synset': 'squeegee.n.01', 'name': 'squeegee'}, {'id': 11207, 'synset': 'squeezer.n.01', 'name': 'squeezer'}, {'id': 11208, 'synset': 'squelch_circuit.n.01', 'name': 'squelch_circuit'}, {'id': 11209, 'synset': 'squinch.n.01', 'name': 'squinch'}, {'id': 11210, 'synset': 'stabilizer.n.03', 'name': 'stabilizer'}, {'id': 11211, 'synset': 'stabilizer.n.02', 'name': 'stabilizer'}, {'id': 11212, 'synset': 'stabilizer_bar.n.01', 'name': 'stabilizer_bar'}, {'id': 11213, 'synset': 'stable.n.01', 'name': 'stable'}, {'id': 11214, 'synset': 'stable_gear.n.01', 'name': 'stable_gear'}, {'id': 11215, 'synset': 'stabling.n.01', 'name': 'stabling'}, {'id': 11216, 'synset': 'stacks.n.02', 'name': 'stacks'}, {'id': 11217, 'synset': 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'synset': 'standard_cell.n.01', 'name': 'standard_cell'}, {'id': 11234, 'synset': 'standard_transmission.n.01', 'name': 'standard_transmission'}, {'id': 11235, 'synset': 'standing_press.n.01', 'name': 'standing_press'}, {'id': 11236, 'synset': 'stanhope.n.01', 'name': 'stanhope'}, {'id': 11237, 'synset': 'stanley_steamer.n.01', 'name': 'Stanley_Steamer'}, {'id': 11238, 'synset': 'staple.n.05', 'name': 'staple'}, {'id': 11239, 'synset': 'staple.n.04', 'name': 'staple'}, {'id': 11240, 'synset': 'staple_gun.n.01', 'name': 'staple_gun'}, {'id': 11241, 'synset': 'starship.n.01', 'name': 'starship'}, {'id': 11242, 'synset': 'starter.n.01', 'name': 'starter'}, {'id': 11243, 'synset': 'starting_gate.n.01', 'name': 'starting_gate'}, {'id': 11244, 'synset': 'stassano_furnace.n.01', 'name': 'Stassano_furnace'}, {'id': 11245, 'synset': 'statehouse.n.01', 'name': 'Statehouse'}, {'id': 11246, 'synset': 'stately_home.n.01', 'name': 'stately_home'}, {'id': 11247, 'synset': 'state_prison.n.01', 'name': 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'steerage.n.01', 'name': 'steerage'}, {'id': 11278, 'synset': 'steering_gear.n.01', 'name': 'steering_gear'}, {'id': 11279, 'synset': 'steering_linkage.n.01', 'name': 'steering_linkage'}, {'id': 11280, 'synset': 'steering_system.n.01', 'name': 'steering_system'}, {'id': 11281, 'synset': 'stele.n.02', 'name': 'stele'}, {'id': 11282, 'synset': 'stem-winder.n.01', 'name': 'stem-winder'}, {'id': 11283, 'synset': 'stencil.n.01', 'name': 'stencil'}, {'id': 11284, 'synset': 'sten_gun.n.01', 'name': 'Sten_gun'}, {'id': 11285, 'synset': 'stenograph.n.02', 'name': 'stenograph'}, {'id': 11286, 'synset': 'step.n.04', 'name': 'step'}, {'id': 11287, 'synset': 'step-down_transformer.n.01', 'name': 'step-down_transformer'}, {'id': 11288, 'synset': 'step-up_transformer.n.01', 'name': 'step-up_transformer'}, {'id': 11289, 'synset': 'stereoscope.n.01', 'name': 'stereoscope'}, {'id': 11290, 'synset': 'stern_chaser.n.01', 'name': 'stern_chaser'}, {'id': 11291, 'synset': 'sternpost.n.01', 'name': 'sternpost'}, {'id': 11292, 'synset': 'sternwheeler.n.01', 'name': 'sternwheeler'}, {'id': 11293, 'synset': 'stethoscope.n.01', 'name': 'stethoscope'}, {'id': 11294, 'synset': 'stewing_pan.n.01', 'name': 'stewing_pan'}, {'id': 11295, 'synset': 'stick.n.01', 'name': 'stick'}, {'id': 11296, 'synset': 'stick.n.07', 'name': 'stick'}, {'id': 11297, 'synset': 'stick.n.03', 'name': 'stick'}, {'id': 11298, 'synset': 'stick.n.06', 'name': 'stick'}, {'id': 11299, 'synset': 'stile.n.01', 'name': 'stile'}, {'id': 11300, 'synset': 'stiletto.n.01', 'name': 'stiletto'}, {'id': 11301, 'synset': 'still.n.03', 'name': 'still'}, {'id': 11302, 'synset': 'stillroom.n.01', 'name': 'stillroom'}, {'id': 11303, 'synset': 'stillson_wrench.n.01', 'name': 'Stillson_wrench'}, {'id': 11304, 'synset': 'stilt.n.02', 'name': 'stilt'}, {'id': 11305, 'synset': 'stinger.n.03', 'name': 'Stinger'}, {'id': 11306, 'synset': 'stink_bomb.n.01', 'name': 'stink_bomb'}, {'id': 11307, 'synset': 'stirrup_pump.n.01', 'name': 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'name': 'stomach_pump'}, {'id': 11324, 'synset': 'stone_wall.n.01', 'name': 'stone_wall'}, {'id': 11325, 'synset': 'stoneware.n.01', 'name': 'stoneware'}, {'id': 11326, 'synset': 'stonework.n.01', 'name': 'stonework'}, {'id': 11327, 'synset': 'stoop.n.03', 'name': 'stoop'}, {'id': 11328, 'synset': 'stop_bath.n.01', 'name': 'stop_bath'}, {'id': 11329, 'synset': 'stopcock.n.01', 'name': 'stopcock'}, {'id': 11330, 'synset': 'stopper_knot.n.01', 'name': 'stopper_knot'}, {'id': 11331, 'synset': 'stopwatch.n.01', 'name': 'stopwatch'}, {'id': 11332, 'synset': 'storage_battery.n.01', 'name': 'storage_battery'}, {'id': 11333, 'synset': 'storage_cell.n.01', 'name': 'storage_cell'}, {'id': 11334, 'synset': 'storage_ring.n.01', 'name': 'storage_ring'}, {'id': 11335, 'synset': 'storage_space.n.01', 'name': 'storage_space'}, {'id': 11336, 'synset': 'storeroom.n.01', 'name': 'storeroom'}, {'id': 11337, 'synset': 'storm_cellar.n.01', 'name': 'storm_cellar'}, {'id': 11338, 'synset': 'storm_door.n.01', 'name': 'storm_door'}, {'id': 11339, 'synset': 'storm_window.n.01', 'name': 'storm_window'}, {'id': 11340, 'synset': 'stoup.n.02', 'name': 'stoup'}, {'id': 11341, 'synset': 'stoup.n.01', 'name': 'stoup'}, {'id': 11342, 'synset': 'stove.n.02', 'name': 'stove'}, {'id': 11343, 'synset': 'stove_bolt.n.01', 'name': 'stove_bolt'}, {'id': 11344, 'synset': 'stovepipe.n.01', 'name': 'stovepipe'}, {'id': 11345, 'synset': 'stovepipe_iron.n.01', 'name': 'stovepipe_iron'}, {'id': 11346, 'synset': 'stradavarius.n.01', 'name': 'Stradavarius'}, {'id': 11347, 'synset': 'straight_chair.n.01', 'name': 'straight_chair'}, {'id': 11348, 'synset': 'straightedge.n.01', 'name': 'straightedge'}, {'id': 11349, 'synset': 'straightener.n.01', 'name': 'straightener'}, {'id': 11350, 'synset': 'straight_flute.n.01', 'name': 'straight_flute'}, {'id': 11351, 'synset': 'straight_pin.n.01', 'name': 'straight_pin'}, {'id': 11352, 'synset': 'straight_razor.n.01', 'name': 'straight_razor'}, {'id': 11353, 'synset': 'straitjacket.n.02', 'name': 'straitjacket'}, {'id': 11354, 'synset': 'strap.n.04', 'name': 'strap'}, {'id': 11355, 'synset': 'strap_hinge.n.01', 'name': 'strap_hinge'}, {'id': 11356, 'synset': 'strapless.n.01', 'name': 'strapless'}, {'id': 11357, 'synset': 'streamer_fly.n.01', 'name': 'streamer_fly'}, {'id': 11358, 'synset': 'streamliner.n.01', 'name': 'streamliner'}, {'id': 11359, 'synset': 'street.n.01', 'name': 'street'}, {'id': 11360, 'synset': 'street.n.02', 'name': 'street'}, {'id': 11361, 'synset': 'streetcar.n.01', 'name': 'streetcar'}, {'id': 11362, 'synset': 'street_clothes.n.01', 'name': 'street_clothes'}, {'id': 11363, 'synset': 'stretcher.n.03', 'name': 'stretcher'}, {'id': 11364, 'synset': 'stretcher.n.01', 'name': 'stretcher'}, {'id': 11365, 'synset': 'stretch_pants.n.01', 'name': 'stretch_pants'}, {'id': 11366, 'synset': 'strickle.n.02', 'name': 'strickle'}, {'id': 11367, 'synset': 'strickle.n.01', 'name': 'strickle'}, {'id': 11368, 'synset': 'stringed_instrument.n.01', 'name': 'stringed_instrument'}, {'id': 11369, 'synset': 'stringer.n.04', 'name': 'stringer'}, {'id': 11370, 'synset': 'stringer.n.03', 'name': 'stringer'}, {'id': 11371, 'synset': 'string_tie.n.01', 'name': 'string_tie'}, {'id': 11372, 'synset': 'strip.n.05', 'name': 'strip'}, {'id': 11373, 'synset': 'strip_lighting.n.01', 'name': 'strip_lighting'}, {'id': 11374, 'synset': 'strip_mall.n.01', 'name': 'strip_mall'}, {'id': 11375, 'synset': 'stroboscope.n.01', 'name': 'stroboscope'}, {'id': 11376, 'synset': 'strongbox.n.01', 'name': 'strongbox'}, {'id': 11377, 'synset': 'stronghold.n.01', 'name': 'stronghold'}, {'id': 11378, 'synset': 'strongroom.n.01', 'name': 'strongroom'}, {'id': 11379, 'synset': 'strop.n.01', 'name': 'strop'}, {'id': 11380, 'synset': 'structural_member.n.01', 'name': 'structural_member'}, {'id': 11381, 'synset': 'structure.n.01', 'name': 'structure'}, {'id': 11382, 'synset': 'student_center.n.01', 'name': 'student_center'}, {'id': 11383, 'synset': 'student_lamp.n.01', 'name': 'student_lamp'}, {'id': 11384, 'synset': 'student_union.n.01', 'name': 'student_union'}, {'id': 11385, 'synset': 'stud_finder.n.01', 'name': 'stud_finder'}, {'id': 11386, 'synset': 'studio_apartment.n.01', 'name': 'studio_apartment'}, {'id': 11387, 'synset': 'studio_couch.n.01', 'name': 'studio_couch'}, {'id': 11388, 'synset': 'study.n.05', 'name': 'study'}, {'id': 11389, 'synset': 'study_hall.n.02', 'name': 'study_hall'}, {'id': 11390, 'synset': 'stuffing_nut.n.01', 'name': 'stuffing_nut'}, {'id': 11391, 'synset': 'stump.n.03', 'name': 'stump'}, {'id': 11392, 'synset': 'stun_gun.n.01', 'name': 'stun_gun'}, {'id': 11393, 'synset': 'stupa.n.01', 'name': 'stupa'}, {'id': 11394, 'synset': 'sty.n.02', 'name': 'sty'}, {'id': 11395, 'synset': 'stylus.n.01', 'name': 'stylus'}, {'id': 11396, 'synset': 'sub-assembly.n.01', 'name': 'sub-assembly'}, {'id': 11397, 'synset': 'subcompact.n.01', 'name': 'subcompact'}, {'id': 11398, 'synset': 'submachine_gun.n.01', 'name': 'submachine_gun'}, {'id': 11399, 'synset': 'submarine.n.01', 'name': 'submarine'}, {'id': 11400, 'synset': 'submarine_torpedo.n.01', 'name': 'submarine_torpedo'}, {'id': 11401, 'synset': 'submersible.n.02', 'name': 'submersible'}, {'id': 11402, 'synset': 'submersible.n.01', 'name': 'submersible'}, {'id': 11403, 'synset': 'subtracter.n.02', 'name': 'subtracter'}, {'id': 11404, 'synset': 'subway_token.n.01', 'name': 'subway_token'}, {'id': 11405, 'synset': 'subway_train.n.01', 'name': 'subway_train'}, {'id': 11406, 'synset': 'suction_cup.n.01', 'name': 'suction_cup'}, {'id': 11407, 'synset': 'suction_pump.n.01', 'name': 'suction_pump'}, {'id': 11408, 'synset': 'sudatorium.n.01', 'name': 'sudatorium'}, {'id': 11409, 'synset': 'suede_cloth.n.01', 'name': 'suede_cloth'}, {'id': 11410, 'synset': 'sugar_refinery.n.01', 'name': 'sugar_refinery'}, {'id': 11411, 'synset': 'sugar_spoon.n.01', 'name': 'sugar_spoon'}, {'id': 11412, 'synset': 'suite.n.02', 'name': 'suite'}, {'id': 11413, 'synset': 'suiting.n.01', 'name': 'suiting'}, {'id': 11414, 'synset': 'sulky.n.01', 'name': 'sulky'}, {'id': 11415, 'synset': 'summer_house.n.01', 'name': 'summer_house'}, {'id': 11416, 'synset': 'sumo_ring.n.01', 'name': 'sumo_ring'}, {'id': 11417, 'synset': 'sump.n.01', 'name': 'sump'}, {'id': 11418, 'synset': 'sump_pump.n.01', 'name': 'sump_pump'}, {'id': 11419, 'synset': 'sunbonnet.n.01', 'name': 'sunbonnet'}, {'id': 11420, 'synset': 'sunday_best.n.01', 'name': 'Sunday_best'}, {'id': 11421, 'synset': 'sun_deck.n.01', 'name': 'sun_deck'}, {'id': 11422, 'synset': 'sundial.n.01', 'name': 'sundial'}, {'id': 11423, 'synset': 'sundress.n.01', 'name': 'sundress'}, {'id': 11424, 'synset': 'sundries.n.01', 'name': 'sundries'}, {'id': 11425, 'synset': 'sun_gear.n.01', 'name': 'sun_gear'}, {'id': 11426, 'synset': 'sunglass.n.01', 'name': 'sunglass'}, {'id': 11427, 'synset': 'sunlamp.n.01', 'name': 'sunlamp'}, {'id': 11428, 'synset': 'sun_parlor.n.01', 'name': 'sun_parlor'}, {'id': 11429, 'synset': 'sunroof.n.01', 'name': 'sunroof'}, {'id': 11430, 'synset': 'sunscreen.n.01', 'name': 'sunscreen'}, {'id': 11431, 'synset': 'sunsuit.n.01', 'name': 'sunsuit'}, {'id': 11432, 'synset': 'supercharger.n.01', 'name': 'supercharger'}, {'id': 11433, 'synset': 'supercomputer.n.01', 'name': 'supercomputer'}, {'id': 11434, 'synset': 'superconducting_supercollider.n.01', 'name': 'superconducting_supercollider'}, {'id': 11435, 'synset': 'superhighway.n.02', 'name': 'superhighway'}, {'id': 11436, 'synset': 'supermarket.n.01', 'name': 'supermarket'}, {'id': 11437, 'synset': 'superstructure.n.01', 'name': 'superstructure'}, {'id': 11438, 'synset': 'supertanker.n.01', 'name': 'supertanker'}, {'id': 11439, 'synset': 'supper_club.n.01', 'name': 'supper_club'}, {'id': 11440, 'synset': 'supplejack.n.01', 'name': 'supplejack'}, {'id': 11441, 'synset': 'supply_chamber.n.01', 'name': 'supply_chamber'}, {'id': 11442, 'synset': 'supply_closet.n.01', 'name': 'supply_closet'}, {'id': 11443, 'synset': 'support.n.10', 'name': 'support'}, {'id': 11444, 'synset': 'support.n.07', 'name': 'support'}, {'id': 11445, 'synset': 'support_column.n.01', 'name': 'support_column'}, {'id': 11446, 'synset': 'support_hose.n.01', 'name': 'support_hose'}, {'id': 11447, 'synset': 'supporting_structure.n.01', 'name': 'supporting_structure'}, {'id': 11448, 'synset': 'supporting_tower.n.01', 'name': 'supporting_tower'}, {'id': 11449, 'synset': 'surcoat.n.02', 'name': 'surcoat'}, {'id': 11450, 'synset': 'surface_gauge.n.01', 'name': 'surface_gauge'}, {'id': 11451, 'synset': 'surface_lift.n.01', 'name': 'surface_lift'}, {'id': 11452, 'synset': 'surface_search_radar.n.01', 'name': 'surface_search_radar'}, {'id': 11453, 'synset': 'surface_ship.n.01', 'name': 'surface_ship'}, {'id': 11454, 'synset': 'surface-to-air_missile.n.01', 'name': 'surface-to-air_missile'}, {'id': 11455, 'synset': 'surface-to-air_missile_system.n.01', 'name': 'surface-to-air_missile_system'}, {'id': 11456, 'synset': 'surfboat.n.01', 'name': 'surfboat'}, {'id': 11457, 'synset': 'surcoat.n.01', 'name': 'surcoat'}, {'id': 11458, 'synset': "surgeon's_knot.n.01", 'name': "surgeon's_knot"}, {'id': 11459, 'synset': 'surgery.n.02', 'name': 'surgery'}, {'id': 11460, 'synset': 'surge_suppressor.n.01', 'name': 'surge_suppressor'}, {'id': 11461, 'synset': 'surgical_dressing.n.01', 'name': 'surgical_dressing'}, {'id': 11462, 'synset': 'surgical_instrument.n.01', 'name': 'surgical_instrument'}, {'id': 11463, 'synset': 'surgical_knife.n.01', 'name': 'surgical_knife'}, {'id': 11464, 'synset': 'surplice.n.01', 'name': 'surplice'}, {'id': 11465, 'synset': 'surrey.n.02', 'name': 'surrey'}, {'id': 11466, 'synset': 'surtout.n.01', 'name': 'surtout'}, {'id': 11467, 'synset': 'surveillance_system.n.01', 'name': 'surveillance_system'}, {'id': 11468, 'synset': 'surveying_instrument.n.01', 'name': 'surveying_instrument'}, {'id': 11469, 'synset': "surveyor's_level.n.01", 'name': "surveyor's_level"}, {'id': 11470, 'synset': 'sushi_bar.n.01', 'name': 'sushi_bar'}, {'id': 11471, 'synset': 'suspension.n.05', 'name': 'suspension'}, {'id': 11472, 'synset': 'suspension_bridge.n.01', 'name': 'suspension_bridge'}, {'id': 11473, 'synset': 'suspensory.n.01', 'name': 'suspensory'}, {'id': 11474, 'synset': 'sustaining_pedal.n.01', 'name': 'sustaining_pedal'}, {'id': 11475, 'synset': 'suture.n.02', 'name': 'suture'}, {'id': 11476, 'synset': 'swab.n.01', 'name': 'swab'}, {'id': 11477, 'synset': 'swaddling_clothes.n.01', 'name': 'swaddling_clothes'}, {'id': 11478, 'synset': 'swag.n.03', 'name': 'swag'}, {'id': 11479, 'synset': 'swage_block.n.01', 'name': 'swage_block'}, {'id': 11480, 'synset': 'swagger_stick.n.01', 'name': 'swagger_stick'}, {'id': 11481, 'synset': 'swallow-tailed_coat.n.01', 'name': 'swallow-tailed_coat'}, {'id': 11482, 'synset': 'swamp_buggy.n.01', 'name': 'swamp_buggy'}, {'id': 11483, 'synset': "swan's_down.n.01", 'name': "swan's_down"}, {'id': 11484, 'synset': 'swathe.n.01', 'name': 'swathe'}, {'id': 11485, 'synset': 'swatter.n.01', 'name': 'swatter'}, {'id': 11486, 'synset': 'sweat_bag.n.01', 'name': 'sweat_bag'}, {'id': 11487, 'synset': 'sweatband.n.01', 'name': 'sweatband'}, {'id': 11488, 'synset': 'sweatshop.n.01', 'name': 'sweatshop'}, {'id': 11489, 'synset': 'sweat_suit.n.01', 'name': 'sweat_suit'}, {'id': 11490, 'synset': 'sweep.n.04', 'name': 'sweep'}, {'id': 11491, 'synset': 'sweep_hand.n.01', 'name': 'sweep_hand'}, {'id': 11492, 'synset': 'swimming_trunks.n.01', 'name': 'swimming_trunks'}, {'id': 11493, 'synset': 'swing.n.02', 'name': 'swing'}, {'id': 11494, 'synset': 'swing_door.n.01', 'name': 'swing_door'}, {'id': 11495, 'synset': 'switch.n.01', 'name': 'switch'}, {'id': 11496, 'synset': 'switchblade.n.01', 'name': 'switchblade'}, {'id': 11497, 'synset': 'switch_engine.n.01', 'name': 'switch_engine'}, {'id': 11498, 'synset': 'swivel.n.01', 'name': 'swivel'}, {'id': 11499, 'synset': 'swivel_chair.n.01', 'name': 'swivel_chair'}, {'id': 11500, 'synset': 'swizzle_stick.n.01', 'name': 'swizzle_stick'}, {'id': 11501, 'synset': 'sword_cane.n.01', 'name': 'sword_cane'}, {'id': 11502, 'synset': 's_wrench.n.01', 'name': 'S_wrench'}, {'id': 11503, 'synset': 'synagogue.n.01', 'name': 'synagogue'}, {'id': 11504, 'synset': 'synchrocyclotron.n.01', 'name': 'synchrocyclotron'}, {'id': 11505, 'synset': 'synchroflash.n.01', 'name': 'synchroflash'}, {'id': 11506, 'synset': 'synchromesh.n.01', 'name': 'synchromesh'}, {'id': 11507, 'synset': 'synchronous_converter.n.01', 'name': 'synchronous_converter'}, {'id': 11508, 'synset': 'synchronous_motor.n.01', 'name': 'synchronous_motor'}, {'id': 11509, 'synset': 'synchrotron.n.01', 'name': 'synchrotron'}, {'id': 11510, 'synset': 'synchroscope.n.01', 'name': 'synchroscope'}, {'id': 11511, 'synset': 'synthesizer.n.02', 'name': 'synthesizer'}, {'id': 11512, 'synset': 'system.n.01', 'name': 'system'}, {'id': 11513, 'synset': 'tabard.n.01', 'name': 'tabard'}, {'id': 11514, 'synset': 'tabernacle.n.02', 'name': 'Tabernacle'}, {'id': 11515, 'synset': 'tabi.n.01', 'name': 'tabi'}, {'id': 11516, 'synset': 'tab_key.n.01', 'name': 'tab_key'}, {'id': 11517, 'synset': 'table.n.03', 'name': 'table'}, {'id': 11518, 'synset': 'tablefork.n.01', 'name': 'tablefork'}, {'id': 11519, 'synset': 'table_knife.n.01', 'name': 'table_knife'}, {'id': 11520, 'synset': 'table_saw.n.01', 'name': 'table_saw'}, {'id': 11521, 'synset': 'tablespoon.n.02', 'name': 'tablespoon'}, {'id': 11522, 'synset': 'tablet-armed_chair.n.01', 'name': 'tablet-armed_chair'}, {'id': 11523, 'synset': 'table-tennis_racquet.n.01', 'name': 'table-tennis_racquet'}, {'id': 11524, 'synset': 'tabletop.n.01', 'name': 'tabletop'}, {'id': 11525, 'synset': 'tableware.n.01', 'name': 'tableware'}, {'id': 11526, 'synset': 'tabor.n.01', 'name': 'tabor'}, {'id': 11527, 'synset': 'taboret.n.01', 'name': 'taboret'}, {'id': 11528, 'synset': 'tachistoscope.n.01', 'name': 'tachistoscope'}, {'id': 11529, 'synset': 'tachograph.n.01', 'name': 'tachograph'}, {'id': 11530, 'synset': 'tachymeter.n.01', 'name': 'tachymeter'}, {'id': 11531, 'synset': 'tack.n.02', 'name': 'tack'}, {'id': 11532, 'synset': 'tack_hammer.n.01', 'name': 'tack_hammer'}, {'id': 11533, 'synset': 'taffeta.n.01', 'name': 'taffeta'}, {'id': 11534, 'synset': 'taffrail.n.01', 'name': 'taffrail'}, {'id': 11535, 'synset': 'tailgate.n.01', 'name': 'tailgate'}, {'id': 11536, 'synset': 'tailor-made.n.01', 'name': 'tailor-made'}, {'id': 11537, 'synset': "tailor's_chalk.n.01", 'name': "tailor's_chalk"}, {'id': 11538, 'synset': 'tailpipe.n.01', 'name': 'tailpipe'}, {'id': 11539, 'synset': 'tail_rotor.n.01', 'name': 'tail_rotor'}, {'id': 11540, 'synset': 'tailstock.n.01', 'name': 'tailstock'}, {'id': 11541, 'synset': 'take-up.n.01', 'name': 'take-up'}, {'id': 11542, 'synset': 'talaria.n.01', 'name': 'talaria'}, {'id': 11543, 'synset': 'talcum.n.02', 'name': 'talcum'}, {'id': 11544, 'synset': 'tam.n.01', 'name': 'tam'}, {'id': 11545, 'synset': 'tambour.n.02', 'name': 'tambour'}, {'id': 11546, 'synset': 'tambour.n.01', 'name': 'tambour'}, {'id': 11547, 'synset': 'tammy.n.01', 'name': 'tammy'}, {'id': 11548, 'synset': 'tamp.n.01', 'name': 'tamp'}, {'id': 11549, 'synset': 'tampax.n.01', 'name': 'Tampax'}, {'id': 11550, 'synset': 'tampion.n.01', 'name': 'tampion'}, {'id': 11551, 'synset': 'tampon.n.01', 'name': 'tampon'}, {'id': 11552, 'synset': 'tandoor.n.01', 'name': 'tandoor'}, {'id': 11553, 'synset': 'tangram.n.01', 'name': 'tangram'}, {'id': 11554, 'synset': 'tankard.n.01', 'name': 'tankard'}, {'id': 11555, 'synset': 'tank_car.n.01', 'name': 'tank_car'}, {'id': 11556, 'synset': 'tank_destroyer.n.01', 'name': 'tank_destroyer'}, {'id': 11557, 'synset': 'tank_engine.n.01', 'name': 'tank_engine'}, {'id': 11558, 'synset': 'tanker_plane.n.01', 'name': 'tanker_plane'}, {'id': 11559, 'synset': 'tank_shell.n.01', 'name': 'tank_shell'}, {'id': 11560, 'synset': 'tannoy.n.01', 'name': 'tannoy'}, {'id': 11561, 'synset': 'tap.n.06', 'name': 'tap'}, {'id': 11562, 'synset': 'tapa.n.02', 'name': 'tapa'}, {'id': 11563, 'synset': 'tape.n.02', 'name': 'tape'}, {'id': 11564, 'synset': 'tape_deck.n.01', 'name': 'tape_deck'}, {'id': 11565, 'synset': 'tape_drive.n.01', 'name': 'tape_drive'}, {'id': 11566, 'synset': 'tape_player.n.01', 'name': 'tape_player'}, {'id': 11567, 'synset': 'tape_recorder.n.01', 'name': 'tape_recorder'}, {'id': 11568, 'synset': 'taper_file.n.01', 'name': 'taper_file'}, {'id': 11569, 'synset': 'tappet.n.01', 'name': 'tappet'}, {'id': 11570, 'synset': 'tap_wrench.n.01', 'name': 'tap_wrench'}, {'id': 11571, 'synset': 'tare.n.05', 'name': 'tare'}, {'id': 11572, 'synset': 'target.n.04', 'name': 'target'}, {'id': 11573, 'synset': 'target_acquisition_system.n.01', 'name': 'target_acquisition_system'}, {'id': 11574, 'synset': 'tarmacadam.n.02', 'name': 'tarmacadam'}, {'id': 11575, 'synset': 'tasset.n.01', 'name': 'tasset'}, {'id': 11576, 'synset': 'tattoo.n.02', 'name': 'tattoo'}, {'id': 11577, 'synset': 'tavern.n.01', 'name': 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'name': 'tea_urn'}, {'id': 11594, 'synset': 'tee.n.03', 'name': 'tee'}, {'id': 11595, 'synset': 'tee_hinge.n.01', 'name': 'tee_hinge'}, {'id': 11596, 'synset': 'telecom_hotel.n.01', 'name': 'telecom_hotel'}, {'id': 11597, 'synset': 'telecommunication_system.n.01', 'name': 'telecommunication_system'}, {'id': 11598, 'synset': 'telegraph.n.01', 'name': 'telegraph'}, {'id': 11599, 'synset': 'telegraph_key.n.01', 'name': 'telegraph_key'}, {'id': 11600, 'synset': 'telemeter.n.01', 'name': 'telemeter'}, {'id': 11601, 'synset': 'telephone_bell.n.01', 'name': 'telephone_bell'}, {'id': 11602, 'synset': 'telephone_cord.n.01', 'name': 'telephone_cord'}, {'id': 11603, 'synset': 'telephone_jack.n.01', 'name': 'telephone_jack'}, {'id': 11604, 'synset': 'telephone_line.n.02', 'name': 'telephone_line'}, {'id': 11605, 'synset': 'telephone_plug.n.01', 'name': 'telephone_plug'}, {'id': 11606, 'synset': 'telephone_receiver.n.01', 'name': 'telephone_receiver'}, {'id': 11607, 'synset': 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'tensimeter.n.01', 'name': 'tensimeter'}, {'id': 11637, 'synset': 'tensiometer.n.03', 'name': 'tensiometer'}, {'id': 11638, 'synset': 'tensiometer.n.02', 'name': 'tensiometer'}, {'id': 11639, 'synset': 'tensiometer.n.01', 'name': 'tensiometer'}, {'id': 11640, 'synset': 'tent.n.01', 'name': 'tent'}, {'id': 11641, 'synset': 'tenter.n.01', 'name': 'tenter'}, {'id': 11642, 'synset': 'tenterhook.n.01', 'name': 'tenterhook'}, {'id': 11643, 'synset': 'tent-fly.n.01', 'name': 'tent-fly'}, {'id': 11644, 'synset': 'tent_peg.n.01', 'name': 'tent_peg'}, {'id': 11645, 'synset': 'tepee.n.01', 'name': 'tepee'}, {'id': 11646, 'synset': 'terminal.n.02', 'name': 'terminal'}, {'id': 11647, 'synset': 'terminal.n.04', 'name': 'terminal'}, {'id': 11648, 'synset': 'terraced_house.n.01', 'name': 'terraced_house'}, {'id': 11649, 'synset': 'terra_cotta.n.01', 'name': 'terra_cotta'}, {'id': 11650, 'synset': 'terrarium.n.01', 'name': 'terrarium'}, {'id': 11651, 'synset': 'terra_sigillata.n.01', 'name': 'terra_sigillata'}, {'id': 11652, 'synset': 'terry.n.02', 'name': 'terry'}, {'id': 11653, 'synset': 'tesla_coil.n.01', 'name': 'Tesla_coil'}, {'id': 11654, 'synset': 'tessera.n.01', 'name': 'tessera'}, {'id': 11655, 'synset': 'test_equipment.n.01', 'name': 'test_equipment'}, {'id': 11656, 'synset': 'test_rocket.n.01', 'name': 'test_rocket'}, {'id': 11657, 'synset': 'test_room.n.01', 'name': 'test_room'}, {'id': 11658, 'synset': 'testudo.n.01', 'name': 'testudo'}, {'id': 11659, 'synset': 'tetraskelion.n.01', 'name': 'tetraskelion'}, {'id': 11660, 'synset': 'tetrode.n.01', 'name': 'tetrode'}, {'id': 11661, 'synset': 'textile_machine.n.01', 'name': 'textile_machine'}, {'id': 11662, 'synset': 'textile_mill.n.01', 'name': 'textile_mill'}, {'id': 11663, 'synset': 'thatch.n.04', 'name': 'thatch'}, {'id': 11664, 'synset': 'theater.n.01', 'name': 'theater'}, {'id': 11665, 'synset': 'theater_curtain.n.01', 'name': 'theater_curtain'}, {'id': 11666, 'synset': 'theater_light.n.01', 'name': 'theater_light'}, {'id': 11667, 'synset': 'theodolite.n.01', 'name': 'theodolite'}, {'id': 11668, 'synset': 'theremin.n.01', 'name': 'theremin'}, {'id': 11669, 'synset': 'thermal_printer.n.01', 'name': 'thermal_printer'}, {'id': 11670, 'synset': 'thermal_reactor.n.01', 'name': 'thermal_reactor'}, {'id': 11671, 'synset': 'thermocouple.n.01', 'name': 'thermocouple'}, {'id': 11672, 'synset': 'thermoelectric_thermometer.n.01', 'name': 'thermoelectric_thermometer'}, {'id': 11673, 'synset': 'thermograph.n.02', 'name': 'thermograph'}, {'id': 11674, 'synset': 'thermograph.n.01', 'name': 'thermograph'}, {'id': 11675, 'synset': 'thermohydrometer.n.01', 'name': 'thermohydrometer'}, {'id': 11676, 'synset': 'thermojunction.n.01', 'name': 'thermojunction'}, {'id': 11677, 'synset': 'thermonuclear_reactor.n.01', 'name': 'thermonuclear_reactor'}, {'id': 11678, 'synset': 'thermopile.n.01', 'name': 'thermopile'}, {'id': 11679, 'synset': 'thigh_pad.n.01', 'name': 'thigh_pad'}, {'id': 11680, 'synset': 'thill.n.01', 'name': 'thill'}, {'id': 11681, 'synset': 'thinning_shears.n.01', 'name': 'thinning_shears'}, {'id': 11682, 'synset': 'third_base.n.01', 'name': 'third_base'}, {'id': 11683, 'synset': 'third_gear.n.01', 'name': 'third_gear'}, {'id': 11684, 'synset': 'third_rail.n.01', 'name': 'third_rail'}, {'id': 11685, 'synset': 'thong.n.03', 'name': 'thong'}, {'id': 11686, 'synset': 'thong.n.02', 'name': 'thong'}, {'id': 11687, 'synset': 'three-centered_arch.n.01', 'name': 'three-centered_arch'}, {'id': 11688, 'synset': 'three-decker.n.02', 'name': 'three-decker'}, {'id': 11689, 'synset': 'three-dimensional_radar.n.01', 'name': 'three-dimensional_radar'}, {'id': 11690, 'synset': 'three-piece_suit.n.01', 'name': 'three-piece_suit'}, {'id': 11691, 'synset': 'three-quarter_binding.n.01', 'name': 'three-quarter_binding'}, {'id': 11692, 'synset': 'three-way_switch.n.01', 'name': 'three-way_switch'}, {'id': 11693, 'synset': 'thresher.n.01', 'name': 'thresher'}, {'id': 11694, 'synset': 'threshing_floor.n.01', 'name': 'threshing_floor'}, {'id': 11695, 'synset': 'thriftshop.n.01', 'name': 'thriftshop'}, {'id': 11696, 'synset': 'throat_protector.n.01', 'name': 'throat_protector'}, {'id': 11697, 'synset': 'throne.n.01', 'name': 'throne'}, {'id': 11698, 'synset': 'thrust_bearing.n.01', 'name': 'thrust_bearing'}, {'id': 11699, 'synset': 'thruster.n.02', 'name': 'thruster'}, {'id': 11700, 'synset': 'thumb.n.02', 'name': 'thumb'}, {'id': 11701, 'synset': 'thumbhole.n.02', 'name': 'thumbhole'}, {'id': 11702, 'synset': 'thumbscrew.n.02', 'name': 'thumbscrew'}, {'id': 11703, 'synset': 'thumbstall.n.01', 'name': 'thumbstall'}, {'id': 11704, 'synset': 'thunderer.n.02', 'name': 'thunderer'}, {'id': 11705, 'synset': 'thwart.n.01', 'name': 'thwart'}, {'id': 11706, 'synset': 'ticking.n.02', 'name': 'ticking'}, {'id': 11707, 'synset': 'tickler_coil.n.01', 'name': 'tickler_coil'}, {'id': 11708, 'synset': 'tie.n.04', 'name': 'tie'}, {'id': 11709, 'synset': 'tie.n.08', 'name': 'tie'}, {'id': 11710, 'synset': 'tie_rack.n.01', 'name': 'tie_rack'}, {'id': 11711, 'synset': 'tie_rod.n.01', 'name': 'tie_rod'}, {'id': 11712, 'synset': 'tile.n.01', 'name': 'tile'}, {'id': 11713, 'synset': 'tile_cutter.n.01', 'name': 'tile_cutter'}, {'id': 11714, 'synset': 'tile_roof.n.01', 'name': 'tile_roof'}, {'id': 11715, 'synset': 'tiller.n.03', 'name': 'tiller'}, {'id': 11716, 'synset': 'tilter.n.02', 'name': 'tilter'}, {'id': 11717, 'synset': 'tilt-top_table.n.01', 'name': 'tilt-top_table'}, {'id': 11718, 'synset': 'timber.n.02', 'name': 'timber'}, {'id': 11719, 'synset': 'timber.n.03', 'name': 'timber'}, {'id': 11720, 'synset': 'timber_hitch.n.01', 'name': 'timber_hitch'}, {'id': 11721, 'synset': 'timbrel.n.01', 'name': 'timbrel'}, {'id': 11722, 'synset': 'time_bomb.n.02', 'name': 'time_bomb'}, {'id': 11723, 'synset': 'time_capsule.n.01', 'name': 'time_capsule'}, {'id': 11724, 'synset': 'time_clock.n.01', 'name': 'time_clock'}, {'id': 11725, 'synset': 'time-delay_measuring_instrument.n.01', 'name': 'time-delay_measuring_instrument'}, {'id': 11726, 'synset': 'time-fuse.n.01', 'name': 'time-fuse'}, {'id': 11727, 'synset': 'timepiece.n.01', 'name': 'timepiece'}, {'id': 11728, 'synset': 'timer.n.03', 'name': 'timer'}, {'id': 11729, 'synset': 'time-switch.n.01', 'name': 'time-switch'}, {'id': 11730, 'synset': 'tin.n.02', 'name': 'tin'}, {'id': 11731, 'synset': 'tinderbox.n.02', 'name': 'tinderbox'}, {'id': 11732, 'synset': 'tine.n.01', 'name': 'tine'}, {'id': 11733, 'synset': 'tippet.n.01', 'name': 'tippet'}, {'id': 11734, 'synset': 'tire_chain.n.01', 'name': 'tire_chain'}, {'id': 11735, 'synset': 'tire_iron.n.01', 'name': 'tire_iron'}, {'id': 11736, 'synset': 'titfer.n.01', 'name': 'titfer'}, {'id': 11737, 'synset': 'tithe_barn.n.01', 'name': 'tithe_barn'}, {'id': 11738, 'synset': 'titrator.n.01', 'name': 'titrator'}, {'id': 11739, 'synset': 'toasting_fork.n.01', 'name': 'toasting_fork'}, {'id': 11740, 'synset': 'toastrack.n.01', 'name': 'toastrack'}, {'id': 11741, 'synset': 'tobacco_pouch.n.01', 'name': 'tobacco_pouch'}, {'id': 11742, 'synset': 'tobacco_shop.n.01', 'name': 'tobacco_shop'}, {'id': 11743, 'synset': 'toboggan.n.01', 'name': 'toboggan'}, {'id': 11744, 'synset': 'toby.n.01', 'name': 'toby'}, {'id': 11745, 'synset': 'tocsin.n.02', 'name': 'tocsin'}, {'id': 11746, 'synset': 'toe.n.02', 'name': 'toe'}, {'id': 11747, 'synset': 'toecap.n.01', 'name': 'toecap'}, {'id': 11748, 'synset': 'toehold.n.02', 'name': 'toehold'}, {'id': 11749, 'synset': 'toga.n.01', 'name': 'toga'}, {'id': 11750, 'synset': 'toga_virilis.n.01', 'name': 'toga_virilis'}, {'id': 11751, 'synset': 'toggle.n.03', 'name': 'toggle'}, {'id': 11752, 'synset': 'toggle_bolt.n.01', 'name': 'toggle_bolt'}, {'id': 11753, 'synset': 'toggle_joint.n.01', 'name': 'toggle_joint'}, {'id': 11754, 'synset': 'toggle_switch.n.01', 'name': 'toggle_switch'}, {'id': 11755, 'synset': 'togs.n.01', 'name': 'togs'}, {'id': 11756, 'synset': 'toilet.n.01', 'name': 'toilet'}, {'id': 11757, 'synset': 'toilet_bag.n.01', 'name': 'toilet_bag'}, {'id': 11758, 'synset': 'toilet_bowl.n.01', 'name': 'toilet_bowl'}, {'id': 11759, 'synset': 'toilet_kit.n.01', 'name': 'toilet_kit'}, {'id': 11760, 'synset': 'toilet_powder.n.01', 'name': 'toilet_powder'}, {'id': 11761, 'synset': 'toiletry.n.01', 'name': 'toiletry'}, {'id': 11762, 'synset': 'toilet_seat.n.01', 'name': 'toilet_seat'}, {'id': 11763, 'synset': 'toilet_water.n.01', 'name': 'toilet_water'}, {'id': 11764, 'synset': 'tokamak.n.01', 'name': 'tokamak'}, {'id': 11765, 'synset': 'token.n.03', 'name': 'token'}, {'id': 11766, 'synset': 'tollbooth.n.01', 'name': 'tollbooth'}, {'id': 11767, 'synset': 'toll_bridge.n.01', 'name': 'toll_bridge'}, {'id': 11768, 'synset': 'tollgate.n.01', 'name': 'tollgate'}, {'id': 11769, 'synset': 'toll_line.n.01', 'name': 'toll_line'}, {'id': 11770, 'synset': 'tomahawk.n.01', 'name': 'tomahawk'}, {'id': 11771, 'synset': 'tommy_gun.n.01', 'name': 'Tommy_gun'}, {'id': 11772, 'synset': 'tomograph.n.01', 'name': 'tomograph'}, {'id': 11773, 'synset': 'tone_arm.n.01', 'name': 'tone_arm'}, {'id': 11774, 'synset': 'toner.n.03', 'name': 'toner'}, {'id': 11775, 'synset': 'tongue.n.07', 'name': 'tongue'}, {'id': 11776, 'synset': 'tongue_and_groove_joint.n.01', 'name': 'tongue_and_groove_joint'}, {'id': 11777, 'synset': 'tongue_depressor.n.01', 'name': 'tongue_depressor'}, {'id': 11778, 'synset': 'tonometer.n.01', 'name': 'tonometer'}, {'id': 11779, 'synset': 'tool.n.01', 'name': 'tool'}, {'id': 11780, 'synset': 'tool_bag.n.01', 'name': 'tool_bag'}, {'id': 11781, 'synset': 'toolshed.n.01', 'name': 'toolshed'}, {'id': 11782, 'synset': 'tooth.n.02', 'name': 'tooth'}, {'id': 11783, 'synset': 'tooth.n.05', 'name': 'tooth'}, {'id': 11784, 'synset': 'top.n.10', 'name': 'top'}, {'id': 11785, 'synset': 'topgallant.n.02', 'name': 'topgallant'}, {'id': 11786, 'synset': 'topgallant.n.01', 'name': 'topgallant'}, {'id': 11787, 'synset': 'topiary.n.01', 'name': 'topiary'}, {'id': 11788, 'synset': 'topknot.n.01', 'name': 'topknot'}, {'id': 11789, 'synset': 'topmast.n.01', 'name': 'topmast'}, {'id': 11790, 'synset': 'topper.n.05', 'name': 'topper'}, {'id': 11791, 'synset': 'topsail.n.01', 'name': 'topsail'}, {'id': 11792, 'synset': 'toque.n.01', 'name': 'toque'}, {'id': 11793, 'synset': 'torch.n.01', 'name': 'torch'}, {'id': 11794, 'synset': 'torpedo.n.06', 'name': 'torpedo'}, {'id': 11795, 'synset': 'torpedo.n.05', 'name': 'torpedo'}, {'id': 11796, 'synset': 'torpedo.n.03', 'name': 'torpedo'}, {'id': 11797, 'synset': 'torpedo_boat.n.01', 'name': 'torpedo_boat'}, {'id': 11798, 'synset': 'torpedo-boat_destroyer.n.01', 'name': 'torpedo-boat_destroyer'}, {'id': 11799, 'synset': 'torpedo_tube.n.01', 'name': 'torpedo_tube'}, {'id': 11800, 'synset': 'torque_converter.n.01', 'name': 'torque_converter'}, {'id': 11801, 'synset': 'torque_wrench.n.01', 'name': 'torque_wrench'}, {'id': 11802, 'synset': 'torture_chamber.n.01', 'name': 'torture_chamber'}, {'id': 11803, 'synset': 'totem_pole.n.01', 'name': 'totem_pole'}, {'id': 11804, 'synset': 'touch_screen.n.01', 'name': 'touch_screen'}, {'id': 11805, 'synset': 'toupee.n.01', 'name': 'toupee'}, {'id': 11806, 'synset': 'touring_car.n.01', 'name': 'touring_car'}, {'id': 11807, 'synset': 'tourist_class.n.01', 'name': 'tourist_class'}, {'id': 11808, 'synset': 'toweling.n.01', 'name': 'toweling'}, {'id': 11809, 'synset': 'towel_rail.n.01', 'name': 'towel_rail'}, {'id': 11810, 'synset': 'tower.n.01', 'name': 'tower'}, {'id': 11811, 'synset': 'town_hall.n.01', 'name': 'town_hall'}, {'id': 11812, 'synset': 'towpath.n.01', 'name': 'towpath'}, {'id': 11813, 'synset': 'toy_box.n.01', 'name': 'toy_box'}, {'id': 11814, 'synset': 'toyshop.n.01', 'name': 'toyshop'}, {'id': 11815, 'synset': 'trace_detector.n.01', 'name': 'trace_detector'}, {'id': 11816, 'synset': 'track.n.09', 'name': 'track'}, {'id': 11817, 'synset': 'track.n.08', 'name': 'track'}, {'id': 11818, 'synset': 'trackball.n.01', 'name': 'trackball'}, {'id': 11819, 'synset': 'tracked_vehicle.n.01', 'name': 'tracked_vehicle'}, {'id': 11820, 'synset': 'tract_house.n.01', 'name': 'tract_house'}, {'id': 11821, 'synset': 'tract_housing.n.01', 'name': 'tract_housing'}, {'id': 11822, 'synset': 'traction_engine.n.01', 'name': 'traction_engine'}, {'id': 11823, 'synset': 'tractor.n.02', 'name': 'tractor'}, {'id': 11824, 'synset': 'trailer.n.04', 'name': 'trailer'}, {'id': 11825, 'synset': 'trailer.n.03', 'name': 'trailer'}, {'id': 11826, 'synset': 'trailer_camp.n.01', 'name': 'trailer_camp'}, {'id': 11827, 'synset': 'trailing_edge.n.01', 'name': 'trailing_edge'}, {'id': 11828, 'synset': 'tramline.n.01', 'name': 'tramline'}, {'id': 11829, 'synset': 'trammel.n.02', 'name': 'trammel'}, {'id': 11830, 'synset': 'tramp_steamer.n.01', 'name': 'tramp_steamer'}, {'id': 11831, 'synset': 'tramway.n.01', 'name': 'tramway'}, {'id': 11832, 'synset': 'transdermal_patch.n.01', 'name': 'transdermal_patch'}, {'id': 11833, 'synset': 'transept.n.01', 'name': 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'trapeze.n.01', 'name': 'trapeze'}, {'id': 11849, 'synset': 'trave.n.01', 'name': 'trave'}, {'id': 11850, 'synset': 'travel_iron.n.01', 'name': 'travel_iron'}, {'id': 11851, 'synset': 'trawl.n.02', 'name': 'trawl'}, {'id': 11852, 'synset': 'trawl.n.01', 'name': 'trawl'}, {'id': 11853, 'synset': 'trawler.n.02', 'name': 'trawler'}, {'id': 11854, 'synset': 'tray_cloth.n.01', 'name': 'tray_cloth'}, {'id': 11855, 'synset': 'tread.n.04', 'name': 'tread'}, {'id': 11856, 'synset': 'tread.n.03', 'name': 'tread'}, {'id': 11857, 'synset': 'treadmill.n.02', 'name': 'treadmill'}, {'id': 11858, 'synset': 'treadmill.n.01', 'name': 'treadmill'}, {'id': 11859, 'synset': 'treasure_chest.n.01', 'name': 'treasure_chest'}, {'id': 11860, 'synset': 'treasure_ship.n.01', 'name': 'treasure_ship'}, {'id': 11861, 'synset': 'treenail.n.01', 'name': 'treenail'}, {'id': 11862, 'synset': 'trefoil_arch.n.01', 'name': 'trefoil_arch'}, {'id': 11863, 'synset': 'trellis.n.01', 'name': 'trellis'}, {'id': 11864, 'synset': 'trench.n.01', 'name': 'trench'}, {'id': 11865, 'synset': 'trench_knife.n.01', 'name': 'trench_knife'}, {'id': 11866, 'synset': 'trepan.n.02', 'name': 'trepan'}, {'id': 11867, 'synset': 'trepan.n.01', 'name': 'trepan'}, {'id': 11868, 'synset': 'trestle.n.02', 'name': 'trestle'}, {'id': 11869, 'synset': 'trestle.n.01', 'name': 'trestle'}, {'id': 11870, 'synset': 'trestle_bridge.n.01', 'name': 'trestle_bridge'}, {'id': 11871, 'synset': 'trestle_table.n.01', 'name': 'trestle_table'}, {'id': 11872, 'synset': 'trestlework.n.01', 'name': 'trestlework'}, {'id': 11873, 'synset': 'trews.n.01', 'name': 'trews'}, {'id': 11874, 'synset': 'trial_balloon.n.02', 'name': 'trial_balloon'}, {'id': 11875, 'synset': 'triangle.n.04', 'name': 'triangle'}, {'id': 11876, 'synset': 'triclinium.n.02', 'name': 'triclinium'}, {'id': 11877, 'synset': 'triclinium.n.01', 'name': 'triclinium'}, {'id': 11878, 'synset': 'tricorn.n.01', 'name': 'tricorn'}, {'id': 11879, 'synset': 'tricot.n.01', 'name': 'tricot'}, {'id': 11880, 'synset': 'trident.n.01', 'name': 'trident'}, {'id': 11881, 'synset': 'trigger.n.02', 'name': 'trigger'}, {'id': 11882, 'synset': 'trimaran.n.01', 'name': 'trimaran'}, {'id': 11883, 'synset': 'trimmer.n.02', 'name': 'trimmer'}, {'id': 11884, 'synset': 'trimmer_arch.n.01', 'name': 'trimmer_arch'}, {'id': 11885, 'synset': 'triode.n.01', 'name': 'triode'}, {'id': 11886, 'synset': 'triptych.n.01', 'name': 'triptych'}, {'id': 11887, 'synset': 'trip_wire.n.02', 'name': 'trip_wire'}, {'id': 11888, 'synset': 'trireme.n.01', 'name': 'trireme'}, {'id': 11889, 'synset': 'triskelion.n.01', 'name': 'triskelion'}, {'id': 11890, 'synset': 'triumphal_arch.n.01', 'name': 'triumphal_arch'}, {'id': 11891, 'synset': 'trivet.n.02', 'name': 'trivet'}, {'id': 11892, 'synset': 'trivet.n.01', 'name': 'trivet'}, {'id': 11893, 'synset': 'troika.n.01', 'name': 'troika'}, {'id': 11894, 'synset': 'troll.n.03', 'name': 'troll'}, {'id': 11895, 'synset': 'trolleybus.n.01', 'name': 'trolleybus'}, {'id': 11896, 'synset': 'trombone.n.01', 'name': 'trombone'}, {'id': 11897, 'synset': 'troop_carrier.n.01', 'name': 'troop_carrier'}, {'id': 11898, 'synset': 'troopship.n.01', 'name': 'troopship'}, {'id': 11899, 'synset': 'trophy_case.n.01', 'name': 'trophy_case'}, {'id': 11900, 'synset': 'trough.n.05', 'name': 'trough'}, {'id': 11901, 'synset': 'trouser.n.02', 'name': 'trouser'}, {'id': 11902, 'synset': 'trouser_cuff.n.01', 'name': 'trouser_cuff'}, {'id': 11903, 'synset': 'trouser_press.n.01', 'name': 'trouser_press'}, {'id': 11904, 'synset': 'trousseau.n.01', 'name': 'trousseau'}, {'id': 11905, 'synset': 'trowel.n.01', 'name': 'trowel'}, {'id': 11906, 'synset': 'trumpet_arch.n.01', 'name': 'trumpet_arch'}, {'id': 11907, 'synset': 'truncheon.n.01', 'name': 'truncheon'}, {'id': 11908, 'synset': 'trundle_bed.n.01', 'name': 'trundle_bed'}, {'id': 11909, 'synset': 'trunk_hose.n.01', 'name': 'trunk_hose'}, {'id': 11910, 'synset': 'trunk_lid.n.01', 'name': 'trunk_lid'}, {'id': 11911, 'synset': 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'synset': 'turnstile.n.01', 'name': 'turnstile'}, {'id': 11944, 'synset': 'turntable.n.01', 'name': 'turntable'}, {'id': 11945, 'synset': 'turntable.n.02', 'name': 'turntable'}, {'id': 11946, 'synset': 'turret.n.01', 'name': 'turret'}, {'id': 11947, 'synset': 'turret_clock.n.01', 'name': 'turret_clock'}, {'id': 11948, 'synset': 'tweed.n.01', 'name': 'tweed'}, {'id': 11949, 'synset': 'tweeter.n.01', 'name': 'tweeter'}, {'id': 11950, 'synset': 'twenty-two.n.02', 'name': 'twenty-two'}, {'id': 11951, 'synset': 'twenty-two_pistol.n.01', 'name': 'twenty-two_pistol'}, {'id': 11952, 'synset': 'twenty-two_rifle.n.01', 'name': 'twenty-two_rifle'}, {'id': 11953, 'synset': 'twill.n.02', 'name': 'twill'}, {'id': 11954, 'synset': 'twill.n.01', 'name': 'twill'}, {'id': 11955, 'synset': 'twin_bed.n.01', 'name': 'twin_bed'}, {'id': 11956, 'synset': 'twinjet.n.01', 'name': 'twinjet'}, {'id': 11957, 'synset': 'twist_bit.n.01', 'name': 'twist_bit'}, {'id': 11958, 'synset': 'two-by-four.n.01', 'name': 'two-by-four'}, {'id': 11959, 'synset': 'two-man_tent.n.01', 'name': 'two-man_tent'}, {'id': 11960, 'synset': 'two-piece.n.01', 'name': 'two-piece'}, {'id': 11961, 'synset': 'typesetting_machine.n.01', 'name': 'typesetting_machine'}, {'id': 11962, 'synset': 'typewriter_carriage.n.01', 'name': 'typewriter_carriage'}, {'id': 11963, 'synset': 'typewriter_keyboard.n.01', 'name': 'typewriter_keyboard'}, {'id': 11964, 'synset': 'tyrolean.n.02', 'name': 'tyrolean'}, {'id': 11965, 'synset': 'uke.n.01', 'name': 'uke'}, {'id': 11966, 'synset': 'ulster.n.02', 'name': 'ulster'}, {'id': 11967, 'synset': 'ultracentrifuge.n.01', 'name': 'ultracentrifuge'}, {'id': 11968, 'synset': 'ultramicroscope.n.01', 'name': 'ultramicroscope'}, {'id': 11969, 'synset': 'ultrasuede.n.01', 'name': 'Ultrasuede'}, {'id': 11970, 'synset': 'ultraviolet_lamp.n.01', 'name': 'ultraviolet_lamp'}, {'id': 11971, 'synset': 'umbrella_tent.n.01', 'name': 'umbrella_tent'}, {'id': 11972, 'synset': 'undercarriage.n.01', 'name': 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'synset': 'upset.n.04', 'name': 'upset'}, {'id': 11988, 'synset': 'upstairs.n.01', 'name': 'upstairs'}, {'id': 11989, 'synset': 'urceole.n.01', 'name': 'urceole'}, {'id': 11990, 'synset': 'urn.n.02', 'name': 'urn'}, {'id': 11991, 'synset': 'used-car.n.01', 'name': 'used-car'}, {'id': 11992, 'synset': 'utensil.n.01', 'name': 'utensil'}, {'id': 11993, 'synset': 'uzi.n.01', 'name': 'Uzi'}, {'id': 11994, 'synset': 'vacation_home.n.01', 'name': 'vacation_home'}, {'id': 11995, 'synset': 'vacuum_chamber.n.01', 'name': 'vacuum_chamber'}, {'id': 11996, 'synset': 'vacuum_flask.n.01', 'name': 'vacuum_flask'}, {'id': 11997, 'synset': 'vacuum_gauge.n.01', 'name': 'vacuum_gauge'}, {'id': 11998, 'synset': 'valenciennes.n.02', 'name': 'Valenciennes'}, {'id': 11999, 'synset': 'valise.n.01', 'name': 'valise'}, {'id': 12000, 'synset': 'valve.n.03', 'name': 'valve'}, {'id': 12001, 'synset': 'valve.n.02', 'name': 'valve'}, {'id': 12002, 'synset': 'valve-in-head_engine.n.01', 'name': 'valve-in-head_engine'}, {'id': 12003, 'synset': 'vambrace.n.01', 'name': 'vambrace'}, {'id': 12004, 'synset': 'van.n.05', 'name': 'van'}, {'id': 12005, 'synset': 'van.n.04', 'name': 'van'}, {'id': 12006, 'synset': 'vane.n.02', 'name': 'vane'}, {'id': 12007, 'synset': 'vaporizer.n.01', 'name': 'vaporizer'}, {'id': 12008, 'synset': 'variable-pitch_propeller.n.01', 'name': 'variable-pitch_propeller'}, {'id': 12009, 'synset': 'variometer.n.01', 'name': 'variometer'}, {'id': 12010, 'synset': 'varnish.n.01', 'name': 'varnish'}, {'id': 12011, 'synset': 'vault.n.03', 'name': 'vault'}, {'id': 12012, 'synset': 'vault.n.02', 'name': 'vault'}, {'id': 12013, 'synset': 'vaulting_horse.n.01', 'name': 'vaulting_horse'}, {'id': 12014, 'synset': 'vehicle.n.01', 'name': 'vehicle'}, {'id': 12015, 'synset': 'velcro.n.01', 'name': 'Velcro'}, {'id': 12016, 'synset': 'velocipede.n.01', 'name': 'velocipede'}, {'id': 12017, 'synset': 'velour.n.01', 'name': 'velour'}, {'id': 12018, 'synset': 'velvet.n.01', 'name': 'velvet'}, {'id': 12019, 'synset': 'velveteen.n.01', 'name': 'velveteen'}, {'id': 12020, 'synset': 'veneer.n.01', 'name': 'veneer'}, {'id': 12021, 'synset': 'venetian_blind.n.01', 'name': 'Venetian_blind'}, {'id': 12022, 'synset': 'venn_diagram.n.01', 'name': 'Venn_diagram'}, {'id': 12023, 'synset': 'ventilation.n.02', 'name': 'ventilation'}, {'id': 12024, 'synset': 'ventilation_shaft.n.01', 'name': 'ventilation_shaft'}, {'id': 12025, 'synset': 'ventilator.n.01', 'name': 'ventilator'}, {'id': 12026, 'synset': 'veranda.n.01', 'name': 'veranda'}, {'id': 12027, 'synset': 'verdigris.n.02', 'name': 'verdigris'}, {'id': 12028, 'synset': 'vernier_caliper.n.01', 'name': 'vernier_caliper'}, {'id': 12029, 'synset': 'vernier_scale.n.01', 'name': 'vernier_scale'}, {'id': 12030, 'synset': 'vertical_file.n.01', 'name': 'vertical_file'}, {'id': 12031, 'synset': 'vertical_stabilizer.n.01', 'name': 'vertical_stabilizer'}, {'id': 12032, 'synset': 'vertical_tail.n.01', 'name': 'vertical_tail'}, {'id': 12033, 'synset': 'very_pistol.n.01', 'name': 'Very_pistol'}, {'id': 12034, 'synset': 'vessel.n.02', 'name': 'vessel'}, {'id': 12035, 'synset': 'vessel.n.03', 'name': 'vessel'}, {'id': 12036, 'synset': 'vestiture.n.01', 'name': 'vestiture'}, {'id': 12037, 'synset': 'vestment.n.01', 'name': 'vestment'}, {'id': 12038, 'synset': 'vest_pocket.n.01', 'name': 'vest_pocket'}, {'id': 12039, 'synset': 'vestry.n.02', 'name': 'vestry'}, {'id': 12040, 'synset': 'viaduct.n.01', 'name': 'viaduct'}, {'id': 12041, 'synset': 'vibraphone.n.01', 'name': 'vibraphone'}, {'id': 12042, 'synset': 'vibrator.n.02', 'name': 'vibrator'}, {'id': 12043, 'synset': 'vibrator.n.01', 'name': 'vibrator'}, {'id': 12044, 'synset': 'victrola.n.01', 'name': 'Victrola'}, {'id': 12045, 'synset': 'vicuna.n.02', 'name': 'vicuna'}, {'id': 12046, 'synset': 'videocassette.n.01', 'name': 'videocassette'}, {'id': 12047, 'synset': 'videocassette_recorder.n.01', 'name': 'videocassette_recorder'}, {'id': 12048, 'synset': 'videodisk.n.01', 'name': 'videodisk'}, {'id': 12049, 'synset': 'video_recording.n.01', 'name': 'video_recording'}, {'id': 12050, 'synset': 'videotape.n.02', 'name': 'videotape'}, {'id': 12051, 'synset': 'vigil_light.n.01', 'name': 'vigil_light'}, {'id': 12052, 'synset': 'villa.n.04', 'name': 'villa'}, {'id': 12053, 'synset': 'villa.n.03', 'name': 'villa'}, {'id': 12054, 'synset': 'villa.n.02', 'name': 'villa'}, {'id': 12055, 'synset': 'viol.n.01', 'name': 'viol'}, {'id': 12056, 'synset': 'viola.n.03', 'name': 'viola'}, {'id': 12057, 'synset': 'viola_da_braccio.n.01', 'name': 'viola_da_braccio'}, {'id': 12058, 'synset': 'viola_da_gamba.n.01', 'name': 'viola_da_gamba'}, {'id': 12059, 'synset': "viola_d'amore.n.01", 'name': "viola_d'amore"}, {'id': 12060, 'synset': 'virginal.n.01', 'name': 'virginal'}, {'id': 12061, 'synset': 'viscometer.n.01', 'name': 'viscometer'}, {'id': 12062, 'synset': 'viscose_rayon.n.01', 'name': 'viscose_rayon'}, {'id': 12063, 'synset': 'vise.n.01', 'name': 'vise'}, {'id': 12064, 'synset': 'visor.n.01', 'name': 'visor'}, {'id': 12065, 'synset': 'visual_display_unit.n.01', 'name': 'visual_display_unit'}, {'id': 12066, 'synset': 'vivarium.n.01', 'name': 'vivarium'}, {'id': 12067, 'synset': 'viyella.n.01', 'name': 'Viyella'}, {'id': 12068, 'synset': 'voile.n.01', 'name': 'voile'}, {'id': 12069, 'synset': 'volleyball_net.n.01', 'name': 'volleyball_net'}, {'id': 12070, 'synset': 'voltage_regulator.n.01', 'name': 'voltage_regulator'}, {'id': 12071, 'synset': 'voltaic_cell.n.01', 'name': 'voltaic_cell'}, {'id': 12072, 'synset': 'voltaic_pile.n.01', 'name': 'voltaic_pile'}, {'id': 12073, 'synset': 'voltmeter.n.01', 'name': 'voltmeter'}, {'id': 12074, 'synset': 'vomitory.n.01', 'name': 'vomitory'}, {'id': 12075, 'synset': 'von_neumann_machine.n.01', 'name': 'von_Neumann_machine'}, {'id': 12076, 'synset': 'voting_booth.n.01', 'name': 'voting_booth'}, {'id': 12077, 'synset': 'voting_machine.n.01', 'name': 'voting_machine'}, {'id': 12078, 'synset': 'voussoir.n.01', 'name': 'voussoir'}, {'id': 12079, 'synset': 'vox_angelica.n.01', 'name': 'vox_angelica'}, {'id': 12080, 'synset': 'vox_humana.n.01', 'name': 'vox_humana'}, {'id': 12081, 'synset': 'waders.n.01', 'name': 'waders'}, {'id': 12082, 'synset': 'wading_pool.n.01', 'name': 'wading_pool'}, {'id': 12083, 'synset': 'wagon.n.04', 'name': 'wagon'}, {'id': 12084, 'synset': 'wagon_tire.n.01', 'name': 'wagon_tire'}, {'id': 12085, 'synset': 'wain.n.03', 'name': 'wain'}, {'id': 12086, 'synset': 'wainscot.n.02', 'name': 'wainscot'}, {'id': 12087, 'synset': 'wainscoting.n.01', 'name': 'wainscoting'}, {'id': 12088, 'synset': 'waist_pack.n.01', 'name': 'waist_pack'}, {'id': 12089, 'synset': 'walker.n.06', 'name': 'walker'}, {'id': 12090, 'synset': 'walker.n.05', 'name': 'walker'}, {'id': 12091, 'synset': 'walker.n.04', 'name': 'walker'}, {'id': 12092, 'synset': 'walkie-talkie.n.01', 'name': 'walkie-talkie'}, {'id': 12093, 'synset': 'walk-in.n.04', 'name': 'walk-in'}, {'id': 12094, 'synset': 'walking_shoe.n.01', 'name': 'walking_shoe'}, {'id': 12095, 'synset': 'walkman.n.01', 'name': 'Walkman'}, {'id': 12096, 'synset': 'walk-up_apartment.n.01', 'name': 'walk-up_apartment'}, {'id': 12097, 'synset': 'wall.n.01', 'name': 'wall'}, {'id': 12098, 'synset': 'wall.n.07', 'name': 'wall'}, {'id': 12099, 'synset': 'wall_tent.n.01', 'name': 'wall_tent'}, {'id': 12100, 'synset': 'wall_unit.n.01', 'name': 'wall_unit'}, {'id': 12101, 'synset': 'wand.n.01', 'name': 'wand'}, {'id': 12102, 'synset': 'wankel_engine.n.01', 'name': 'Wankel_engine'}, {'id': 12103, 'synset': 'ward.n.03', 'name': 'ward'}, {'id': 12104, 'synset': 'wardroom.n.01', 'name': 'wardroom'}, {'id': 12105, 'synset': 'warehouse.n.01', 'name': 'warehouse'}, {'id': 12106, 'synset': 'warming_pan.n.01', 'name': 'warming_pan'}, {'id': 12107, 'synset': 'war_paint.n.02', 'name': 'war_paint'}, {'id': 12108, 'synset': 'warplane.n.01', 'name': 'warplane'}, {'id': 12109, 'synset': 'war_room.n.01', 'name': 'war_room'}, {'id': 12110, 'synset': 'warship.n.01', 'name': 'warship'}, {'id': 12111, 'synset': 'wash.n.01', 'name': 'wash'}, {'id': 12112, 'synset': 'wash-and-wear.n.01', 'name': 'wash-and-wear'}, {'id': 12113, 'synset': 'washbasin.n.02', 'name': 'washbasin'}, {'id': 12114, 'synset': 'washboard.n.02', 'name': 'washboard'}, {'id': 12115, 'synset': 'washboard.n.01', 'name': 'washboard'}, {'id': 12116, 'synset': 'washer.n.02', 'name': 'washer'}, {'id': 12117, 'synset': 'washhouse.n.01', 'name': 'washhouse'}, {'id': 12118, 'synset': 'washroom.n.01', 'name': 'washroom'}, {'id': 12119, 'synset': 'washstand.n.01', 'name': 'washstand'}, {'id': 12120, 'synset': 'washtub.n.01', 'name': 'washtub'}, {'id': 12121, 'synset': 'wastepaper_basket.n.01', 'name': 'wastepaper_basket'}, {'id': 12122, 'synset': 'watch_cap.n.01', 'name': 'watch_cap'}, {'id': 12123, 'synset': 'watch_case.n.01', 'name': 'watch_case'}, {'id': 12124, 'synset': 'watch_glass.n.01', 'name': 'watch_glass'}, {'id': 12125, 'synset': 'watchtower.n.01', 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'whipping_post.n.01', 'name': 'whipping_post'}, {'id': 12203, 'synset': 'whipstitch.n.01', 'name': 'whipstitch'}, {'id': 12204, 'synset': 'whirler.n.02', 'name': 'whirler'}, {'id': 12205, 'synset': 'whisk.n.02', 'name': 'whisk'}, {'id': 12206, 'synset': 'whisk.n.01', 'name': 'whisk'}, {'id': 12207, 'synset': 'whiskey_bottle.n.01', 'name': 'whiskey_bottle'}, {'id': 12208, 'synset': 'whiskey_jug.n.01', 'name': 'whiskey_jug'}, {'id': 12209, 'synset': 'whispering_gallery.n.01', 'name': 'whispering_gallery'}, {'id': 12210, 'synset': 'whistle.n.04', 'name': 'whistle'}, {'id': 12211, 'synset': 'white.n.11', 'name': 'white'}, {'id': 12212, 'synset': 'white_goods.n.01', 'name': 'white_goods'}, {'id': 12213, 'synset': 'whitewash.n.02', 'name': 'whitewash'}, {'id': 12214, 'synset': 'whorehouse.n.01', 'name': 'whorehouse'}, {'id': 12215, 'synset': 'wick.n.02', 'name': 'wick'}, {'id': 12216, 'synset': 'wicker.n.02', 'name': 'wicker'}, {'id': 12217, 'synset': 'wicker_basket.n.01', 'name': 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'windbreak.n.01', 'name': 'windbreak'}, {'id': 12234, 'synset': 'winder.n.02', 'name': 'winder'}, {'id': 12235, 'synset': 'wind_instrument.n.01', 'name': 'wind_instrument'}, {'id': 12236, 'synset': 'windjammer.n.01', 'name': 'windjammer'}, {'id': 12237, 'synset': 'windmill.n.02', 'name': 'windmill'}, {'id': 12238, 'synset': 'window.n.01', 'name': 'window'}, {'id': 12239, 'synset': 'window.n.08', 'name': 'window'}, {'id': 12240, 'synset': 'window_blind.n.01', 'name': 'window_blind'}, {'id': 12241, 'synset': 'window_envelope.n.01', 'name': 'window_envelope'}, {'id': 12242, 'synset': 'window_frame.n.01', 'name': 'window_frame'}, {'id': 12243, 'synset': 'window_screen.n.01', 'name': 'window_screen'}, {'id': 12244, 'synset': 'window_seat.n.01', 'name': 'window_seat'}, {'id': 12245, 'synset': 'window_shade.n.01', 'name': 'window_shade'}, {'id': 12246, 'synset': 'windowsill.n.01', 'name': 'windowsill'}, {'id': 12247, 'synset': 'windshield.n.01', 'name': 'windshield'}, {'id': 12248, 'synset': 'windsor_chair.n.01', 'name': 'Windsor_chair'}, {'id': 12249, 'synset': 'windsor_knot.n.01', 'name': 'Windsor_knot'}, {'id': 12250, 'synset': 'windsor_tie.n.01', 'name': 'Windsor_tie'}, {'id': 12251, 'synset': 'wind_tee.n.01', 'name': 'wind_tee'}, {'id': 12252, 'synset': 'wind_tunnel.n.01', 'name': 'wind_tunnel'}, {'id': 12253, 'synset': 'wind_turbine.n.01', 'name': 'wind_turbine'}, {'id': 12254, 'synset': 'wine_bar.n.01', 'name': 'wine_bar'}, {'id': 12255, 'synset': 'wine_cask.n.01', 'name': 'wine_cask'}, {'id': 12256, 'synset': 'winepress.n.01', 'name': 'winepress'}, {'id': 12257, 'synset': 'winery.n.01', 'name': 'winery'}, {'id': 12258, 'synset': 'wineskin.n.01', 'name': 'wineskin'}, {'id': 12259, 'synset': 'wing.n.02', 'name': 'wing'}, {'id': 12260, 'synset': 'wing_chair.n.01', 'name': 'wing_chair'}, {'id': 12261, 'synset': 'wing_nut.n.02', 'name': 'wing_nut'}, {'id': 12262, 'synset': 'wing_tip.n.02', 'name': 'wing_tip'}, {'id': 12263, 'synset': 'wing_tip.n.01', 'name': 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{'id': 12294, 'synset': 'workhouse.n.02', 'name': 'workhouse'}, {'id': 12295, 'synset': 'workhouse.n.01', 'name': 'workhouse'}, {'id': 12296, 'synset': 'workpiece.n.01', 'name': 'workpiece'}, {'id': 12297, 'synset': 'workroom.n.01', 'name': 'workroom'}, {'id': 12298, 'synset': 'works.n.04', 'name': 'works'}, {'id': 12299, 'synset': 'work-shirt.n.01', 'name': 'work-shirt'}, {'id': 12300, 'synset': 'workstation.n.01', 'name': 'workstation'}, {'id': 12301, 'synset': 'worktable.n.01', 'name': 'worktable'}, {'id': 12302, 'synset': 'workwear.n.01', 'name': 'workwear'}, {'id': 12303, 'synset': 'world_wide_web.n.01', 'name': 'World_Wide_Web'}, {'id': 12304, 'synset': 'worm_fence.n.01', 'name': 'worm_fence'}, {'id': 12305, 'synset': 'worm_gear.n.01', 'name': 'worm_gear'}, {'id': 12306, 'synset': 'worm_wheel.n.01', 'name': 'worm_wheel'}, {'id': 12307, 'synset': 'worsted.n.01', 'name': 'worsted'}, {'id': 12308, 'synset': 'worsted.n.02', 'name': 'worsted'}, {'id': 12309, 'synset': 'wrap.n.01', 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'name': 'X-ray_film'}, {'id': 12325, 'synset': 'x-ray_machine.n.01', 'name': 'X-ray_machine'}, {'id': 12326, 'synset': 'x-ray_tube.n.01', 'name': 'X-ray_tube'}, {'id': 12327, 'synset': 'yacht_chair.n.01', 'name': 'yacht_chair'}, {'id': 12328, 'synset': 'yagi.n.01', 'name': 'yagi'}, {'id': 12329, 'synset': 'yard.n.09', 'name': 'yard'}, {'id': 12330, 'synset': 'yard.n.08', 'name': 'yard'}, {'id': 12331, 'synset': 'yardarm.n.01', 'name': 'yardarm'}, {'id': 12332, 'synset': 'yard_marker.n.01', 'name': 'yard_marker'}, {'id': 12333, 'synset': 'yardstick.n.02', 'name': 'yardstick'}, {'id': 12334, 'synset': 'yarmulke.n.01', 'name': 'yarmulke'}, {'id': 12335, 'synset': 'yashmak.n.01', 'name': 'yashmak'}, {'id': 12336, 'synset': 'yataghan.n.01', 'name': 'yataghan'}, {'id': 12337, 'synset': 'yawl.n.02', 'name': 'yawl'}, {'id': 12338, 'synset': 'yawl.n.01', 'name': 'yawl'}, {'id': 12339, 'synset': 'yoke.n.01', 'name': 'yoke'}, {'id': 12340, 'synset': 'yoke.n.06', 'name': 'yoke'}, {'id': 12341, 'synset': 'yurt.n.01', 'name': 'yurt'}, {'id': 12342, 'synset': 'zamboni.n.01', 'name': 'Zamboni'}, {'id': 12343, 'synset': 'zero.n.04', 'name': 'zero'}, {'id': 12344, 'synset': 'ziggurat.n.01', 'name': 'ziggurat'}, {'id': 12345, 'synset': 'zill.n.01', 'name': 'zill'}, {'id': 12346, 'synset': 'zip_gun.n.01', 'name': 'zip_gun'}, {'id': 12347, 'synset': 'zither.n.01', 'name': 'zither'}, {'id': 12348, 'synset': 'zoot_suit.n.01', 'name': 'zoot_suit'}, {'id': 12349, 'synset': 'shading.n.01', 'name': 'shading'}, {'id': 12350, 'synset': 'grain.n.10', 'name': 'grain'}, {'id': 12351, 'synset': 'wood_grain.n.01', 'name': 'wood_grain'}, {'id': 12352, 'synset': 'graining.n.01', 'name': 'graining'}, {'id': 12353, 'synset': 'marbleization.n.01', 'name': 'marbleization'}, {'id': 12354, 'synset': 'light.n.07', 'name': 'light'}, {'id': 12355, 'synset': 'aura.n.02', 'name': 'aura'}, {'id': 12356, 'synset': 'sunniness.n.01', 'name': 'sunniness'}, {'id': 12357, 'synset': 'glint.n.02', 'name': 'glint'}, 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{'id': 12373, 'synset': 'charcoal.n.03', 'name': 'charcoal'}, {'id': 12374, 'synset': 'sanguine.n.01', 'name': 'sanguine'}, {'id': 12375, 'synset': 'turkey_red.n.01', 'name': 'Turkey_red'}, {'id': 12376, 'synset': 'crimson.n.01', 'name': 'crimson'}, {'id': 12377, 'synset': 'dark_red.n.01', 'name': 'dark_red'}, {'id': 12378, 'synset': 'claret.n.01', 'name': 'claret'}, {'id': 12379, 'synset': 'fuschia.n.01', 'name': 'fuschia'}, {'id': 12380, 'synset': 'maroon.n.02', 'name': 'maroon'}, {'id': 12381, 'synset': 'orange.n.02', 'name': 'orange'}, {'id': 12382, 'synset': 'reddish_orange.n.01', 'name': 'reddish_orange'}, {'id': 12383, 'synset': 'yellow.n.01', 'name': 'yellow'}, {'id': 12384, 'synset': 'gamboge.n.02', 'name': 'gamboge'}, {'id': 12385, 'synset': 'pale_yellow.n.01', 'name': 'pale_yellow'}, {'id': 12386, 'synset': 'green.n.01', 'name': 'green'}, {'id': 12387, 'synset': 'greenishness.n.01', 'name': 'greenishness'}, {'id': 12388, 'synset': 'sea_green.n.01', 'name': 'sea_green'}, {'id': 12389, 'synset': 'sage_green.n.01', 'name': 'sage_green'}, {'id': 12390, 'synset': 'bottle_green.n.01', 'name': 'bottle_green'}, {'id': 12391, 'synset': 'emerald.n.03', 'name': 'emerald'}, {'id': 12392, 'synset': 'olive_green.n.01', 'name': 'olive_green'}, {'id': 12393, 'synset': 'jade_green.n.01', 'name': 'jade_green'}, {'id': 12394, 'synset': 'blue.n.01', 'name': 'blue'}, {'id': 12395, 'synset': 'azure.n.01', 'name': 'azure'}, {'id': 12396, 'synset': 'steel_blue.n.01', 'name': 'steel_blue'}, {'id': 12397, 'synset': 'greenish_blue.n.01', 'name': 'greenish_blue'}, {'id': 12398, 'synset': 'purplish_blue.n.01', 'name': 'purplish_blue'}, {'id': 12399, 'synset': 'purple.n.01', 'name': 'purple'}, {'id': 12400, 'synset': 'tyrian_purple.n.02', 'name': 'Tyrian_purple'}, {'id': 12401, 'synset': 'indigo.n.03', 'name': 'indigo'}, {'id': 12402, 'synset': 'lavender.n.02', 'name': 'lavender'}, {'id': 12403, 'synset': 'reddish_purple.n.01', 'name': 'reddish_purple'}, {'id': 12404, 'synset': 'pink.n.01', 'name': 'pink'}, {'id': 12405, 'synset': 'carnation.n.02', 'name': 'carnation'}, {'id': 12406, 'synset': 'rose.n.03', 'name': 'rose'}, {'id': 12407, 'synset': 'chestnut.n.04', 'name': 'chestnut'}, {'id': 12408, 'synset': 'chocolate.n.03', 'name': 'chocolate'}, {'id': 12409, 'synset': 'light_brown.n.01', 'name': 'light_brown'}, {'id': 12410, 'synset': 'tan.n.02', 'name': 'tan'}, {'id': 12411, 'synset': 'beige.n.01', 'name': 'beige'}, {'id': 12412, 'synset': 'reddish_brown.n.01', 'name': 'reddish_brown'}, {'id': 12413, 'synset': 'brick_red.n.01', 'name': 'brick_red'}, {'id': 12414, 'synset': 'copper.n.04', 'name': 'copper'}, {'id': 12415, 'synset': 'indian_red.n.03', 'name': 'Indian_red'}, {'id': 12416, 'synset': 'puce.n.01', 'name': 'puce'}, {'id': 12417, 'synset': 'olive.n.05', 'name': 'olive'}, {'id': 12418, 'synset': 'ultramarine.n.02', 'name': 'ultramarine'}, {'id': 12419, 'synset': 'complementary_color.n.01', 'name': 'complementary_color'}, {'id': 12420, 'synset': 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'name': 'mouth'}, {'id': 12465, 'synset': 'canthus.n.01', 'name': 'canthus'}, {'id': 12466, 'synset': 'milk.n.02', 'name': 'milk'}, {'id': 12467, 'synset': "mother's_milk.n.01", 'name': "mother's_milk"}, {'id': 12468, 'synset': 'colostrum.n.01', 'name': 'colostrum'}, {'id': 12469, 'synset': 'vein.n.01', 'name': 'vein'}, {'id': 12470, 'synset': 'ganglion_cell.n.01', 'name': 'ganglion_cell'}, {'id': 12471, 'synset': 'x_chromosome.n.01', 'name': 'X_chromosome'}, {'id': 12472, 'synset': 'embryonic_cell.n.01', 'name': 'embryonic_cell'}, {'id': 12473, 'synset': 'myeloblast.n.01', 'name': 'myeloblast'}, {'id': 12474, 'synset': 'sideroblast.n.01', 'name': 'sideroblast'}, {'id': 12475, 'synset': 'osteocyte.n.01', 'name': 'osteocyte'}, {'id': 12476, 'synset': 'megalocyte.n.01', 'name': 'megalocyte'}, {'id': 12477, 'synset': 'leukocyte.n.01', 'name': 'leukocyte'}, {'id': 12478, 'synset': 'histiocyte.n.01', 'name': 'histiocyte'}, {'id': 12479, 'synset': 'fixed_phagocyte.n.01', 'name': 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'synset': 'silver_screen.n.01', 'name': 'silver_screen'}, {'id': 12525, 'synset': 'free_press.n.01', 'name': 'free_press'}, {'id': 12526, 'synset': 'press.n.02', 'name': 'press'}, {'id': 12527, 'synset': 'print_media.n.01', 'name': 'print_media'}, {'id': 12528, 'synset': 'storage_medium.n.01', 'name': 'storage_medium'}, {'id': 12529, 'synset': 'magnetic_storage_medium.n.01', 'name': 'magnetic_storage_medium'}, {'id': 12530, 'synset': 'journalism.n.01', 'name': 'journalism'}, {'id': 12531, 'synset': 'fleet_street.n.02', 'name': 'Fleet_Street'}, {'id': 12532, 'synset': 'photojournalism.n.01', 'name': 'photojournalism'}, {'id': 12533, 'synset': 'news_photography.n.01', 'name': 'news_photography'}, {'id': 12534, 'synset': 'rotogravure.n.02', 'name': 'rotogravure'}, {'id': 12535, 'synset': 'daily.n.01', 'name': 'daily'}, {'id': 12536, 'synset': 'gazette.n.01', 'name': 'gazette'}, {'id': 12537, 'synset': 'school_newspaper.n.01', 'name': 'school_newspaper'}, {'id': 12538, 'synset': 'tabloid.n.02', 'name': 'tabloid'}, {'id': 12539, 'synset': 'yellow_journalism.n.01', 'name': 'yellow_journalism'}, {'id': 12540, 'synset': 'telecommunication.n.01', 'name': 'telecommunication'}, {'id': 12541, 'synset': 'telephone.n.02', 'name': 'telephone'}, {'id': 12542, 'synset': 'voice_mail.n.01', 'name': 'voice_mail'}, {'id': 12543, 'synset': 'call.n.01', 'name': 'call'}, {'id': 12544, 'synset': 'call-back.n.01', 'name': 'call-back'}, {'id': 12545, 'synset': 'collect_call.n.01', 'name': 'collect_call'}, {'id': 12546, 'synset': 'call_forwarding.n.01', 'name': 'call_forwarding'}, {'id': 12547, 'synset': 'call-in.n.01', 'name': 'call-in'}, {'id': 12548, 'synset': 'call_waiting.n.01', 'name': 'call_waiting'}, {'id': 12549, 'synset': 'crank_call.n.01', 'name': 'crank_call'}, {'id': 12550, 'synset': 'local_call.n.01', 'name': 'local_call'}, {'id': 12551, 'synset': 'long_distance.n.01', 'name': 'long_distance'}, {'id': 12552, 'synset': 'toll_call.n.01', 'name': 'toll_call'}, {'id': 12553, 'synset': 'wake-up_call.n.02', 'name': 'wake-up_call'}, {'id': 12554, 'synset': 'three-way_calling.n.01', 'name': 'three-way_calling'}, {'id': 12555, 'synset': 'telegraphy.n.01', 'name': 'telegraphy'}, {'id': 12556, 'synset': 'cable.n.01', 'name': 'cable'}, {'id': 12557, 'synset': 'wireless.n.02', 'name': 'wireless'}, {'id': 12558, 'synset': 'radiotelegraph.n.01', 'name': 'radiotelegraph'}, {'id': 12559, 'synset': 'radiotelephone.n.01', 'name': 'radiotelephone'}, {'id': 12560, 'synset': 'broadcasting.n.02', 'name': 'broadcasting'}, {'id': 12561, 'synset': 'rediffusion.n.01', 'name': 'Rediffusion'}, {'id': 12562, 'synset': 'multiplex.n.01', 'name': 'multiplex'}, {'id': 12563, 'synset': 'radio.n.01', 'name': 'radio'}, {'id': 12564, 'synset': 'television.n.01', 'name': 'television'}, {'id': 12565, 'synset': 'cable_television.n.01', 'name': 'cable_television'}, {'id': 12566, 'synset': 'high-definition_television.n.01', 'name': 'high-definition_television'}, {'id': 12567, 'synset': 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{'id': 12674, 'synset': 'meal.n.01', 'name': 'meal'}, {'id': 12675, 'synset': 'potluck.n.01', 'name': 'potluck'}, {'id': 12676, 'synset': 'refection.n.01', 'name': 'refection'}, {'id': 12677, 'synset': 'refreshment.n.01', 'name': 'refreshment'}, {'id': 12678, 'synset': 'breakfast.n.01', 'name': 'breakfast'}, {'id': 12679, 'synset': 'continental_breakfast.n.01', 'name': 'continental_breakfast'}, {'id': 12680, 'synset': 'brunch.n.01', 'name': 'brunch'}, {'id': 12681, 'synset': 'lunch.n.01', 'name': 'lunch'}, {'id': 12682, 'synset': 'business_lunch.n.01', 'name': 'business_lunch'}, {'id': 12683, 'synset': 'high_tea.n.01', 'name': 'high_tea'}, {'id': 12684, 'synset': 'tea.n.02', 'name': 'tea'}, {'id': 12685, 'synset': 'dinner.n.01', 'name': 'dinner'}, {'id': 12686, 'synset': 'supper.n.01', 'name': 'supper'}, {'id': 12687, 'synset': 'buffet.n.02', 'name': 'buffet'}, {'id': 12688, 'synset': 'picnic.n.03', 'name': 'picnic'}, {'id': 12689, 'synset': 'cookout.n.01', 'name': 'cookout'}, {'id': 12690, 'synset': 'barbecue.n.02', 'name': 'barbecue'}, {'id': 12691, 'synset': 'clambake.n.01', 'name': 'clambake'}, {'id': 12692, 'synset': 'fish_fry.n.01', 'name': 'fish_fry'}, {'id': 12693, 'synset': 'bite.n.04', 'name': 'bite'}, {'id': 12694, 'synset': 'nosh.n.01', 'name': 'nosh'}, {'id': 12695, 'synset': 'nosh-up.n.01', 'name': 'nosh-up'}, {'id': 12696, 'synset': "ploughman's_lunch.n.01", 'name': "ploughman's_lunch"}, {'id': 12697, 'synset': 'coffee_break.n.01', 'name': 'coffee_break'}, {'id': 12698, 'synset': 'banquet.n.02', 'name': 'banquet'}, {'id': 12699, 'synset': 'entree.n.01', 'name': 'entree'}, {'id': 12700, 'synset': 'piece_de_resistance.n.02', 'name': 'piece_de_resistance'}, {'id': 12701, 'synset': 'plate.n.08', 'name': 'plate'}, {'id': 12702, 'synset': 'adobo.n.01', 'name': 'adobo'}, {'id': 12703, 'synset': 'side_dish.n.01', 'name': 'side_dish'}, {'id': 12704, 'synset': 'special.n.02', 'name': 'special'}, {'id': 12705, 'synset': 'chicken_casserole.n.01', 'name': 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12736, 'synset': 'gazpacho.n.01', 'name': 'gazpacho'}, {'id': 12737, 'synset': 'gumbo.n.04', 'name': 'gumbo'}, {'id': 12738, 'synset': 'julienne.n.02', 'name': 'julienne'}, {'id': 12739, 'synset': 'marmite.n.01', 'name': 'marmite'}, {'id': 12740, 'synset': 'mock_turtle_soup.n.01', 'name': 'mock_turtle_soup'}, {'id': 12741, 'synset': 'mulligatawny.n.01', 'name': 'mulligatawny'}, {'id': 12742, 'synset': 'oxtail_soup.n.01', 'name': 'oxtail_soup'}, {'id': 12743, 'synset': 'pea_soup.n.01', 'name': 'pea_soup'}, {'id': 12744, 'synset': 'pepper_pot.n.01', 'name': 'pepper_pot'}, {'id': 12745, 'synset': 'petite_marmite.n.01', 'name': 'petite_marmite'}, {'id': 12746, 'synset': 'potage.n.01', 'name': 'potage'}, {'id': 12747, 'synset': 'pottage.n.01', 'name': 'pottage'}, {'id': 12748, 'synset': 'turtle_soup.n.01', 'name': 'turtle_soup'}, {'id': 12749, 'synset': 'eggdrop_soup.n.01', 'name': 'eggdrop_soup'}, {'id': 12750, 'synset': 'chowder.n.01', 'name': 'chowder'}, {'id': 12751, 'synset': 'corn_chowder.n.01', 'name': 'corn_chowder'}, {'id': 12752, 'synset': 'clam_chowder.n.01', 'name': 'clam_chowder'}, {'id': 12753, 'synset': 'manhattan_clam_chowder.n.01', 'name': 'Manhattan_clam_chowder'}, {'id': 12754, 'synset': 'new_england_clam_chowder.n.01', 'name': 'New_England_clam_chowder'}, {'id': 12755, 'synset': 'fish_chowder.n.01', 'name': 'fish_chowder'}, {'id': 12756, 'synset': 'won_ton.n.02', 'name': 'won_ton'}, {'id': 12757, 'synset': 'split-pea_soup.n.01', 'name': 'split-pea_soup'}, {'id': 12758, 'synset': 'green_pea_soup.n.01', 'name': 'green_pea_soup'}, {'id': 12759, 'synset': 'lentil_soup.n.01', 'name': 'lentil_soup'}, {'id': 12760, 'synset': 'scotch_broth.n.01', 'name': 'Scotch_broth'}, {'id': 12761, 'synset': 'vichyssoise.n.01', 'name': 'vichyssoise'}, {'id': 12762, 'synset': 'bigos.n.01', 'name': 'bigos'}, {'id': 12763, 'synset': 'brunswick_stew.n.01', 'name': 'Brunswick_stew'}, {'id': 12764, 'synset': 'burgoo.n.03', 'name': 'burgoo'}, {'id': 12765, 'synset': 'burgoo.n.02', 'name': 'burgoo'}, {'id': 12766, 'synset': 'olla_podrida.n.01', 'name': 'olla_podrida'}, {'id': 12767, 'synset': 'mulligan_stew.n.01', 'name': 'mulligan_stew'}, {'id': 12768, 'synset': 'purloo.n.01', 'name': 'purloo'}, {'id': 12769, 'synset': 'goulash.n.01', 'name': 'goulash'}, {'id': 12770, 'synset': 'hotchpotch.n.02', 'name': 'hotchpotch'}, {'id': 12771, 'synset': 'hot_pot.n.01', 'name': 'hot_pot'}, {'id': 12772, 'synset': 'beef_goulash.n.01', 'name': 'beef_goulash'}, {'id': 12773, 'synset': 'pork-and-veal_goulash.n.01', 'name': 'pork-and-veal_goulash'}, {'id': 12774, 'synset': 'porkholt.n.01', 'name': 'porkholt'}, {'id': 12775, 'synset': 'irish_stew.n.01', 'name': 'Irish_stew'}, {'id': 12776, 'synset': 'oyster_stew.n.01', 'name': 'oyster_stew'}, {'id': 12777, 'synset': 'lobster_stew.n.01', 'name': 'lobster_stew'}, {'id': 12778, 'synset': 'lobscouse.n.01', 'name': 'lobscouse'}, {'id': 12779, 'synset': 'fish_stew.n.01', 'name': 'fish_stew'}, {'id': 12780, 'synset': 'bouillabaisse.n.01', 'name': 'bouillabaisse'}, {'id': 12781, 'synset': 'matelote.n.01', 'name': 'matelote'}, {'id': 12782, 'synset': 'paella.n.01', 'name': 'paella'}, {'id': 12783, 'synset': 'fricassee.n.01', 'name': 'fricassee'}, {'id': 12784, 'synset': 'chicken_stew.n.01', 'name': 'chicken_stew'}, {'id': 12785, 'synset': 'turkey_stew.n.01', 'name': 'turkey_stew'}, {'id': 12786, 'synset': 'beef_stew.n.01', 'name': 'beef_stew'}, {'id': 12787, 'synset': 'ragout.n.01', 'name': 'ragout'}, {'id': 12788, 'synset': 'ratatouille.n.01', 'name': 'ratatouille'}, {'id': 12789, 'synset': 'salmi.n.01', 'name': 'salmi'}, {'id': 12790, 'synset': 'pot-au-feu.n.01', 'name': 'pot-au-feu'}, {'id': 12791, 'synset': 'slumgullion.n.01', 'name': 'slumgullion'}, {'id': 12792, 'synset': 'smorgasbord.n.02', 'name': 'smorgasbord'}, {'id': 12793, 'synset': 'viand.n.01', 'name': 'viand'}, {'id': 12794, 'synset': 'ready-mix.n.01', 'name': 'ready-mix'}, {'id': 12795, 'synset': 'brownie_mix.n.01', 'name': 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'synset': 'brown_sugar.n.01', 'name': 'brown_sugar'}, {'id': 12811, 'synset': 'demerara.n.05', 'name': 'demerara'}, {'id': 12812, 'synset': 'sweet.n.03', 'name': 'sweet'}, {'id': 12813, 'synset': 'confectionery.n.01', 'name': 'confectionery'}, {'id': 12814, 'synset': 'confiture.n.01', 'name': 'confiture'}, {'id': 12815, 'synset': 'sweetmeat.n.01', 'name': 'sweetmeat'}, {'id': 12816, 'synset': 'candy.n.01', 'name': 'candy'}, {'id': 12817, 'synset': 'carob_bar.n.01', 'name': 'carob_bar'}, {'id': 12818, 'synset': 'hardbake.n.01', 'name': 'hardbake'}, {'id': 12819, 'synset': 'hard_candy.n.01', 'name': 'hard_candy'}, {'id': 12820, 'synset': 'barley-sugar.n.01', 'name': 'barley-sugar'}, {'id': 12821, 'synset': 'brandyball.n.01', 'name': 'brandyball'}, {'id': 12822, 'synset': 'jawbreaker.n.01', 'name': 'jawbreaker'}, {'id': 12823, 'synset': 'lemon_drop.n.01', 'name': 'lemon_drop'}, {'id': 12824, 'synset': 'sourball.n.01', 'name': 'sourball'}, {'id': 12825, 'synset': 'patty.n.03', 'name': 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'peppermint.n.03', 'name': 'peppermint'}, {'id': 12856, 'synset': 'kiss.n.03', 'name': 'kiss'}, {'id': 12857, 'synset': 'molasses_kiss.n.01', 'name': 'molasses_kiss'}, {'id': 12858, 'synset': 'meringue_kiss.n.01', 'name': 'meringue_kiss'}, {'id': 12859, 'synset': 'chocolate_kiss.n.01', 'name': 'chocolate_kiss'}, {'id': 12860, 'synset': 'licorice.n.02', 'name': 'licorice'}, {'id': 12861, 'synset': 'life_saver.n.01', 'name': 'Life_Saver'}, {'id': 12862, 'synset': 'lozenge.n.01', 'name': 'lozenge'}, {'id': 12863, 'synset': 'cachou.n.01', 'name': 'cachou'}, {'id': 12864, 'synset': 'cough_drop.n.01', 'name': 'cough_drop'}, {'id': 12865, 'synset': 'marshmallow.n.01', 'name': 'marshmallow'}, {'id': 12866, 'synset': 'marzipan.n.01', 'name': 'marzipan'}, {'id': 12867, 'synset': 'nougat.n.01', 'name': 'nougat'}, {'id': 12868, 'synset': 'nougat_bar.n.01', 'name': 'nougat_bar'}, {'id': 12869, 'synset': 'nut_bar.n.01', 'name': 'nut_bar'}, {'id': 12870, 'synset': 'peanut_bar.n.01', 'name': 'peanut_bar'}, {'id': 12871, 'synset': 'popcorn_ball.n.01', 'name': 'popcorn_ball'}, {'id': 12872, 'synset': 'praline.n.01', 'name': 'praline'}, {'id': 12873, 'synset': 'rock_candy.n.02', 'name': 'rock_candy'}, {'id': 12874, 'synset': 'rock_candy.n.01', 'name': 'rock_candy'}, {'id': 12875, 'synset': 'sugar_candy.n.01', 'name': 'sugar_candy'}, {'id': 12876, 'synset': 'sugarplum.n.01', 'name': 'sugarplum'}, {'id': 12877, 'synset': 'taffy.n.01', 'name': 'taffy'}, {'id': 12878, 'synset': 'molasses_taffy.n.01', 'name': 'molasses_taffy'}, {'id': 12879, 'synset': 'turkish_delight.n.01', 'name': 'Turkish_Delight'}, {'id': 12880, 'synset': 'dessert.n.01', 'name': 'dessert'}, {'id': 12881, 'synset': 'ambrosia.n.04', 'name': 'ambrosia'}, {'id': 12882, 'synset': 'ambrosia.n.03', 'name': 'ambrosia'}, {'id': 12883, 'synset': 'baked_alaska.n.01', 'name': 'baked_Alaska'}, {'id': 12884, 'synset': 'blancmange.n.01', 'name': 'blancmange'}, {'id': 12885, 'synset': 'charlotte.n.02', 'name': 'charlotte'}, {'id': 12886, 'synset': 'compote.n.01', 'name': 'compote'}, {'id': 12887, 'synset': 'dumpling.n.02', 'name': 'dumpling'}, {'id': 12888, 'synset': 'flan.n.01', 'name': 'flan'}, {'id': 12889, 'synset': 'frozen_dessert.n.01', 'name': 'frozen_dessert'}, {'id': 12890, 'synset': 'junket.n.01', 'name': 'junket'}, {'id': 12891, 'synset': 'mousse.n.02', 'name': 'mousse'}, {'id': 12892, 'synset': 'mousse.n.01', 'name': 'mousse'}, {'id': 12893, 'synset': 'pavlova.n.02', 'name': 'pavlova'}, {'id': 12894, 'synset': 'peach_melba.n.01', 'name': 'peach_melba'}, {'id': 12895, 'synset': 'whip.n.03', 'name': 'whip'}, {'id': 12896, 'synset': 'prune_whip.n.01', 'name': 'prune_whip'}, {'id': 12897, 'synset': 'pudding.n.03', 'name': 'pudding'}, {'id': 12898, 'synset': 'pudding.n.02', 'name': 'pudding'}, {'id': 12899, 'synset': 'syllabub.n.02', 'name': 'syllabub'}, {'id': 12900, 'synset': 'tiramisu.n.01', 'name': 'tiramisu'}, {'id': 12901, 'synset': 'trifle.n.01', 'name': 'trifle'}, {'id': 12902, 'synset': 'tipsy_cake.n.01', 'name': 'tipsy_cake'}, {'id': 12903, 'synset': 'jello.n.01', 'name': 'jello'}, {'id': 12904, 'synset': 'apple_dumpling.n.01', 'name': 'apple_dumpling'}, {'id': 12905, 'synset': 'ice.n.05', 'name': 'ice'}, {'id': 12906, 'synset': 'water_ice.n.02', 'name': 'water_ice'}, {'id': 12907, 'synset': 'ice-cream_cone.n.01', 'name': 'ice-cream_cone'}, {'id': 12908, 'synset': 'chocolate_ice_cream.n.01', 'name': 'chocolate_ice_cream'}, {'id': 12909, 'synset': 'neapolitan_ice_cream.n.01', 'name': 'Neapolitan_ice_cream'}, {'id': 12910, 'synset': 'peach_ice_cream.n.01', 'name': 'peach_ice_cream'}, {'id': 12911, 'synset': 'strawberry_ice_cream.n.01', 'name': 'strawberry_ice_cream'}, {'id': 12912, 'synset': 'tutti-frutti.n.01', 'name': 'tutti-frutti'}, {'id': 12913, 'synset': 'vanilla_ice_cream.n.01', 'name': 'vanilla_ice_cream'}, {'id': 12914, 'synset': 'ice_milk.n.01', 'name': 'ice_milk'}, {'id': 12915, 'synset': 'frozen_yogurt.n.01', 'name': 'frozen_yogurt'}, {'id': 12916, 'synset': 'snowball.n.03', 'name': 'snowball'}, {'id': 12917, 'synset': 'snowball.n.02', 'name': 'snowball'}, {'id': 12918, 'synset': 'parfait.n.01', 'name': 'parfait'}, {'id': 12919, 'synset': 'ice-cream_sundae.n.01', 'name': 'ice-cream_sundae'}, {'id': 12920, 'synset': 'split.n.07', 'name': 'split'}, {'id': 12921, 'synset': 'banana_split.n.01', 'name': 'banana_split'}, {'id': 12922, 'synset': 'frozen_pudding.n.01', 'name': 'frozen_pudding'}, {'id': 12923, 'synset': 'frozen_custard.n.01', 'name': 'frozen_custard'}, {'id': 12924, 'synset': 'flummery.n.01', 'name': 'flummery'}, {'id': 12925, 'synset': 'fish_mousse.n.01', 'name': 'fish_mousse'}, {'id': 12926, 'synset': 'chicken_mousse.n.01', 'name': 'chicken_mousse'}, {'id': 12927, 'synset': 'plum_pudding.n.01', 'name': 'plum_pudding'}, {'id': 12928, 'synset': 'carrot_pudding.n.01', 'name': 'carrot_pudding'}, {'id': 12929, 'synset': 'corn_pudding.n.01', 'name': 'corn_pudding'}, {'id': 12930, 'synset': 'steamed_pudding.n.01', 'name': 'steamed_pudding'}, {'id': 12931, 'synset': 'duff.n.01', 'name': 'duff'}, {'id': 12932, 'synset': 'vanilla_pudding.n.01', 'name': 'vanilla_pudding'}, {'id': 12933, 'synset': 'chocolate_pudding.n.01', 'name': 'chocolate_pudding'}, {'id': 12934, 'synset': 'brown_betty.n.01', 'name': 'brown_Betty'}, {'id': 12935, 'synset': 'nesselrode.n.01', 'name': 'Nesselrode'}, {'id': 12936, 'synset': 'pease_pudding.n.01', 'name': 'pease_pudding'}, {'id': 12937, 'synset': 'custard.n.01', 'name': 'custard'}, {'id': 12938, 'synset': 'creme_caramel.n.01', 'name': 'creme_caramel'}, {'id': 12939, 'synset': 'creme_anglais.n.01', 'name': 'creme_anglais'}, {'id': 12940, 'synset': 'creme_brulee.n.01', 'name': 'creme_brulee'}, {'id': 12941, 'synset': 'fruit_custard.n.01', 'name': 'fruit_custard'}, {'id': 12942, 'synset': 'tapioca.n.01', 'name': 'tapioca'}, {'id': 12943, 'synset': 'tapioca_pudding.n.01', 'name': 'tapioca_pudding'}, {'id': 12944, 'synset': 'roly-poly.n.02', 'name': 'roly-poly'}, {'id': 12945, 'synset': 'suet_pudding.n.01', 'name': 'suet_pudding'}, {'id': 12946, 'synset': 'bavarian_cream.n.01', 'name': 'Bavarian_cream'}, {'id': 12947, 'synset': 'maraschino.n.02', 'name': 'maraschino'}, {'id': 12948, 'synset': 'nonpareil.n.02', 'name': 'nonpareil'}, {'id': 12949, 'synset': 'zabaglione.n.01', 'name': 'zabaglione'}, {'id': 12950, 'synset': 'garnish.n.01', 'name': 'garnish'}, {'id': 12951, 'synset': 'pastry.n.01', 'name': 'pastry'}, {'id': 12952, 'synset': 'turnover.n.02', 'name': 'turnover'}, {'id': 12953, 'synset': 'apple_turnover.n.01', 'name': 'apple_turnover'}, {'id': 12954, 'synset': 'knish.n.01', 'name': 'knish'}, {'id': 12955, 'synset': 'pirogi.n.01', 'name': 'pirogi'}, {'id': 12956, 'synset': 'samosa.n.01', 'name': 'samosa'}, {'id': 12957, 'synset': 'timbale.n.01', 'name': 'timbale'}, {'id': 12958, 'synset': 'puff_paste.n.01', 'name': 'puff_paste'}, {'id': 12959, 'synset': 'phyllo.n.01', 'name': 'phyllo'}, {'id': 12960, 'synset': 'puff_batter.n.01', 'name': 'puff_batter'}, {'id': 12961, 'synset': 'ice-cream_cake.n.01', 'name': 'ice-cream_cake'}, {'id': 12962, 'synset': 'fish_cake.n.01', 'name': 'fish_cake'}, {'id': 12963, 'synset': 'fish_stick.n.01', 'name': 'fish_stick'}, {'id': 12964, 'synset': 'conserve.n.01', 'name': 'conserve'}, {'id': 12965, 'synset': 'apple_butter.n.01', 'name': 'apple_butter'}, {'id': 12966, 'synset': 'chowchow.n.02', 'name': 'chowchow'}, {'id': 12967, 'synset': 'lemon_curd.n.01', 'name': 'lemon_curd'}, {'id': 12968, 'synset': 'strawberry_jam.n.01', 'name': 'strawberry_jam'}, {'id': 12969, 'synset': 'jelly.n.02', 'name': 'jelly'}, {'id': 12970, 'synset': 'apple_jelly.n.01', 'name': 'apple_jelly'}, {'id': 12971, 'synset': 'crabapple_jelly.n.01', 'name': 'crabapple_jelly'}, {'id': 12972, 'synset': 'grape_jelly.n.01', 'name': 'grape_jelly'}, {'id': 12973, 'synset': 'marmalade.n.01', 'name': 'marmalade'}, {'id': 12974, 'synset': 'orange_marmalade.n.01', 'name': 'orange_marmalade'}, {'id': 12975, 'synset': 'gelatin_dessert.n.01', 'name': 'gelatin_dessert'}, {'id': 12976, 'synset': 'buffalo_wing.n.01', 'name': 'buffalo_wing'}, {'id': 12977, 'synset': 'barbecued_wing.n.01', 'name': 'barbecued_wing'}, {'id': 12978, 'synset': 'mess.n.03', 'name': 'mess'}, {'id': 12979, 'synset': 'mince.n.01', 'name': 'mince'}, {'id': 12980, 'synset': 'puree.n.01', 'name': 'puree'}, {'id': 12981, 'synset': 'barbecue.n.01', 'name': 'barbecue'}, {'id': 12982, 'synset': 'biryani.n.01', 'name': 'biryani'}, {'id': 12983, 'synset': 'escalope_de_veau_orloff.n.01', 'name': 'escalope_de_veau_Orloff'}, {'id': 12984, 'synset': 'saute.n.01', 'name': 'saute'}, {'id': 12985, 'synset': 'veal_parmesan.n.01', 'name': 'veal_parmesan'}, {'id': 12986, 'synset': 'veal_cordon_bleu.n.01', 'name': 'veal_cordon_bleu'}, {'id': 12987, 'synset': 'margarine.n.01', 'name': 'margarine'}, {'id': 12988, 'synset': 'mincemeat.n.01', 'name': 'mincemeat'}, {'id': 12989, 'synset': 'stuffing.n.01', 'name': 'stuffing'}, {'id': 12990, 'synset': 'turkey_stuffing.n.01', 'name': 'turkey_stuffing'}, {'id': 12991, 'synset': 'oyster_stuffing.n.01', 'name': 'oyster_stuffing'}, {'id': 12992, 'synset': 'forcemeat.n.01', 'name': 'forcemeat'}, {'id': 12993, 'synset': 'anadama_bread.n.01', 'name': 'anadama_bread'}, {'id': 12994, 'synset': 'bap.n.01', 'name': 'bap'}, {'id': 12995, 'synset': 'barmbrack.n.01', 'name': 'barmbrack'}, {'id': 12996, 'synset': 'breadstick.n.01', 'name': 'breadstick'}, {'id': 12997, 'synset': 'grissino.n.01', 'name': 'grissino'}, {'id': 12998, 'synset': 'brown_bread.n.02', 'name': 'brown_bread'}, {'id': 12999, 'synset': 'tea_bread.n.01', 'name': 'tea_bread'}, {'id': 13000, 'synset': 'caraway_seed_bread.n.01', 'name': 'caraway_seed_bread'}, {'id': 13001, 'synset': 'challah.n.01', 'name': 'challah'}, {'id': 13002, 'synset': 'cinnamon_bread.n.01', 'name': 'cinnamon_bread'}, {'id': 13003, 'synset': 'cracked-wheat_bread.n.01', 'name': 'cracked-wheat_bread'}, {'id': 13004, 'synset': 'dark_bread.n.01', 'name': 'dark_bread'}, {'id': 13005, 'synset': 'english_muffin.n.01', 'name': 'English_muffin'}, {'id': 13006, 'synset': 'flatbread.n.01', 'name': 'flatbread'}, {'id': 13007, 'synset': 'garlic_bread.n.01', 'name': 'garlic_bread'}, {'id': 13008, 'synset': 'gluten_bread.n.01', 'name': 'gluten_bread'}, {'id': 13009, 'synset': 'graham_bread.n.01', 'name': 'graham_bread'}, {'id': 13010, 'synset': 'host.n.09', 'name': 'Host'}, {'id': 13011, 'synset': 'flatbrod.n.01', 'name': 'flatbrod'}, {'id': 13012, 'synset': 'bannock.n.01', 'name': 'bannock'}, {'id': 13013, 'synset': 'chapatti.n.01', 'name': 'chapatti'}, {'id': 13014, 'synset': 'loaf_of_bread.n.01', 'name': 'loaf_of_bread'}, {'id': 13015, 'synset': 'french_loaf.n.01', 'name': 'French_loaf'}, {'id': 13016, 'synset': 'matzo.n.01', 'name': 'matzo'}, {'id': 13017, 'synset': 'nan.n.04', 'name': 'nan'}, {'id': 13018, 'synset': 'onion_bread.n.01', 'name': 'onion_bread'}, {'id': 13019, 'synset': 'raisin_bread.n.01', 'name': 'raisin_bread'}, {'id': 13020, 'synset': 'quick_bread.n.01', 'name': 'quick_bread'}, {'id': 13021, 'synset': 'banana_bread.n.01', 'name': 'banana_bread'}, {'id': 13022, 'synset': 'date_bread.n.01', 'name': 'date_bread'}, {'id': 13023, 'synset': 'date-nut_bread.n.01', 'name': 'date-nut_bread'}, {'id': 13024, 'synset': 'nut_bread.n.01', 'name': 'nut_bread'}, {'id': 13025, 'synset': 'oatcake.n.01', 'name': 'oatcake'}, {'id': 13026, 'synset': 'irish_soda_bread.n.01', 'name': 'Irish_soda_bread'}, {'id': 13027, 'synset': 'skillet_bread.n.01', 'name': 'skillet_bread'}, {'id': 13028, 'synset': 'rye_bread.n.01', 'name': 'rye_bread'}, {'id': 13029, 'synset': 'black_bread.n.01', 'name': 'black_bread'}, {'id': 13030, 'synset': 'jewish_rye_bread.n.01', 'name': 'Jewish_rye_bread'}, {'id': 13031, 'synset': 'limpa.n.01', 'name': 'limpa'}, {'id': 13032, 'synset': 'swedish_rye_bread.n.01', 'name': 'Swedish_rye_bread'}, {'id': 13033, 'synset': 'salt-rising_bread.n.01', 'name': 'salt-rising_bread'}, {'id': 13034, 'synset': 'simnel.n.01', 'name': 'simnel'}, {'id': 13035, 'synset': 'sour_bread.n.01', 'name': 'sour_bread'}, {'id': 13036, 'synset': 'wafer.n.03', 'name': 'wafer'}, {'id': 13037, 'synset': 'white_bread.n.01', 'name': 'white_bread'}, {'id': 13038, 'synset': 'french_bread.n.01', 'name': 'French_bread'}, {'id': 13039, 'synset': 'italian_bread.n.01', 'name': 'Italian_bread'}, {'id': 13040, 'synset': 'corn_cake.n.01', 'name': 'corn_cake'}, {'id': 13041, 'synset': 'skillet_corn_bread.n.01', 'name': 'skillet_corn_bread'}, {'id': 13042, 'synset': 'ashcake.n.01', 'name': 'ashcake'}, {'id': 13043, 'synset': 'hoecake.n.01', 'name': 'hoecake'}, {'id': 13044, 'synset': 'cornpone.n.01', 'name': 'cornpone'}, {'id': 13045, 'synset': 'corn_dab.n.01', 'name': 'corn_dab'}, {'id': 13046, 'synset': 'hush_puppy.n.01', 'name': 'hush_puppy'}, {'id': 13047, 'synset': 'johnnycake.n.01', 'name': 'johnnycake'}, {'id': 13048, 'synset': 'shawnee_cake.n.01', 'name': 'Shawnee_cake'}, {'id': 13049, 'synset': 'spoon_bread.n.01', 'name': 'spoon_bread'}, {'id': 13050, 'synset': 'cinnamon_toast.n.01', 'name': 'cinnamon_toast'}, {'id': 13051, 'synset': 'orange_toast.n.01', 'name': 'orange_toast'}, {'id': 13052, 'synset': 'melba_toast.n.01', 'name': 'Melba_toast'}, {'id': 13053, 'synset': 'zwieback.n.01', 'name': 'zwieback'}, {'id': 13054, 'synset': 'frankfurter_bun.n.01', 'name': 'frankfurter_bun'}, {'id': 13055, 'synset': 'hamburger_bun.n.01', 'name': 'hamburger_bun'}, {'id': 13056, 'synset': 'bran_muffin.n.01', 'name': 'bran_muffin'}, {'id': 13057, 'synset': 'corn_muffin.n.01', 'name': 'corn_muffin'}, {'id': 13058, 'synset': 'yorkshire_pudding.n.01', 'name': 'Yorkshire_pudding'}, {'id': 13059, 'synset': 'popover.n.01', 'name': 'popover'}, {'id': 13060, 'synset': 'scone.n.01', 'name': 'scone'}, {'id': 13061, 'synset': 'drop_scone.n.01', 'name': 'drop_scone'}, {'id': 13062, 'synset': 'cross_bun.n.01', 'name': 'cross_bun'}, {'id': 13063, 'synset': 'brioche.n.01', 'name': 'brioche'}, {'id': 13064, 'synset': 'hard_roll.n.01', 'name': 'hard_roll'}, {'id': 13065, 'synset': 'soft_roll.n.01', 'name': 'soft_roll'}, {'id': 13066, 'synset': 'kaiser_roll.n.01', 'name': 'kaiser_roll'}, {'id': 13067, 'synset': 'parker_house_roll.n.01', 'name': 'Parker_House_roll'}, {'id': 13068, 'synset': 'clover-leaf_roll.n.01', 'name': 'clover-leaf_roll'}, {'id': 13069, 'synset': 'onion_roll.n.01', 'name': 'onion_roll'}, {'id': 13070, 'synset': 'bialy.n.01', 'name': 'bialy'}, {'id': 13071, 'synset': 'sweet_roll.n.01', 'name': 'sweet_roll'}, {'id': 13072, 'synset': 'bear_claw.n.01', 'name': 'bear_claw'}, {'id': 13073, 'synset': 'cinnamon_roll.n.01', 'name': 'cinnamon_roll'}, {'id': 13074, 'synset': 'honey_bun.n.01', 'name': 'honey_bun'}, {'id': 13075, 'synset': 'pinwheel_roll.n.01', 'name': 'pinwheel_roll'}, {'id': 13076, 'synset': 'danish.n.02', 'name': 'danish'}, {'id': 13077, 'synset': 'onion_bagel.n.01', 'name': 'onion_bagel'}, {'id': 13078, 'synset': 'biscuit.n.01', 'name': 'biscuit'}, {'id': 13079, 'synset': 'rolled_biscuit.n.01', 'name': 'rolled_biscuit'}, {'id': 13080, 'synset': 'baking-powder_biscuit.n.01', 'name': 'baking-powder_biscuit'}, {'id': 13081, 'synset': 'buttermilk_biscuit.n.01', 'name': 'buttermilk_biscuit'}, {'id': 13082, 'synset': 'shortcake.n.01', 'name': 'shortcake'}, {'id': 13083, 'synset': 'hardtack.n.01', 'name': 'hardtack'}, {'id': 13084, 'synset': 'saltine.n.01', 'name': 'saltine'}, {'id': 13085, 'synset': 'soda_cracker.n.01', 'name': 'soda_cracker'}, {'id': 13086, 'synset': 'oyster_cracker.n.01', 'name': 'oyster_cracker'}, {'id': 13087, 'synset': 'water_biscuit.n.01', 'name': 'water_biscuit'}, {'id': 13088, 'synset': 'graham_cracker.n.01', 'name': 'graham_cracker'}, {'id': 13089, 'synset': 'soft_pretzel.n.01', 'name': 'soft_pretzel'}, {'id': 13090, 'synset': 'sandwich_plate.n.01', 'name': 'sandwich_plate'}, {'id': 13091, 'synset': 'butty.n.01', 'name': 'butty'}, {'id': 13092, 'synset': 'ham_sandwich.n.01', 'name': 'ham_sandwich'}, {'id': 13093, 'synset': 'chicken_sandwich.n.01', 'name': 'chicken_sandwich'}, {'id': 13094, 'synset': 'club_sandwich.n.01', 'name': 'club_sandwich'}, {'id': 13095, 'synset': 'open-face_sandwich.n.01', 'name': 'open-face_sandwich'}, {'id': 13096, 'synset': 'cheeseburger.n.01', 'name': 'cheeseburger'}, {'id': 13097, 'synset': 'tunaburger.n.01', 'name': 'tunaburger'}, {'id': 13098, 'synset': 'hotdog.n.02', 'name': 'hotdog'}, {'id': 13099, 'synset': 'sloppy_joe.n.01', 'name': 'Sloppy_Joe'}, {'id': 13100, 'synset': 'bomber.n.03', 'name': 'bomber'}, {'id': 13101, 'synset': 'gyro.n.01', 'name': 'gyro'}, {'id': 13102, 'synset': 'bacon-lettuce-tomato_sandwich.n.01', 'name': 'bacon-lettuce-tomato_sandwich'}, {'id': 13103, 'synset': 'reuben.n.02', 'name': 'Reuben'}, {'id': 13104, 'synset': 'western.n.02', 'name': 'western'}, {'id': 13105, 'synset': 'wrap.n.02', 'name': 'wrap'}, {'id': 13106, 'synset': 'spaghetti.n.01', 'name': 'spaghetti'}, {'id': 13107, 'synset': 'hasty_pudding.n.01', 'name': 'hasty_pudding'}, {'id': 13108, 'synset': 'gruel.n.01', 'name': 'gruel'}, {'id': 13109, 'synset': 'congee.n.01', 'name': 'congee'}, {'id': 13110, 'synset': 'skilly.n.01', 'name': 'skilly'}, {'id': 13111, 'synset': 'edible_fruit.n.01', 'name': 'edible_fruit'}, {'id': 13112, 'synset': 'vegetable.n.01', 'name': 'vegetable'}, {'id': 13113, 'synset': 'julienne.n.01', 'name': 'julienne'}, {'id': 13114, 'synset': 'raw_vegetable.n.01', 'name': 'raw_vegetable'}, {'id': 13115, 'synset': 'crudites.n.01', 'name': 'crudites'}, {'id': 13116, 'synset': 'celery_stick.n.01', 'name': 'celery_stick'}, {'id': 13117, 'synset': 'legume.n.03', 'name': 'legume'}, {'id': 13118, 'synset': 'pulse.n.04', 'name': 'pulse'}, {'id': 13119, 'synset': 'potherb.n.01', 'name': 'potherb'}, {'id': 13120, 'synset': 'greens.n.01', 'name': 'greens'}, {'id': 13121, 'synset': 'chop-suey_greens.n.02', 'name': 'chop-suey_greens'}, {'id': 13122, 'synset': 'solanaceous_vegetable.n.01', 'name': 'solanaceous_vegetable'}, {'id': 13123, 'synset': 'root_vegetable.n.01', 'name': 'root_vegetable'}, {'id': 13124, 'synset': 'baked_potato.n.01', 'name': 'baked_potato'}, {'id': 13125, 'synset': 'french_fries.n.01', 'name': 'french_fries'}, {'id': 13126, 'synset': 'home_fries.n.01', 'name': 'home_fries'}, {'id': 13127, 'synset': 'jacket_potato.n.01', 'name': 'jacket_potato'}, {'id': 13128, 'synset': 'potato_skin.n.01', 'name': 'potato_skin'}, {'id': 13129, 'synset': 'uruguay_potato.n.02', 'name': 'Uruguay_potato'}, {'id': 13130, 'synset': 'yam.n.04', 'name': 'yam'}, {'id': 13131, 'synset': 'yam.n.03', 'name': 'yam'}, {'id': 13132, 'synset': 'snack_food.n.01', 'name': 'snack_food'}, {'id': 13133, 'synset': 'corn_chip.n.01', 'name': 'corn_chip'}, {'id': 13134, 'synset': 'tortilla_chip.n.01', 'name': 'tortilla_chip'}, {'id': 13135, 'synset': 'nacho.n.01', 'name': 'nacho'}, {'id': 13136, 'synset': 'pieplant.n.01', 'name': 'pieplant'}, {'id': 13137, 'synset': 'cruciferous_vegetable.n.01', 'name': 'cruciferous_vegetable'}, {'id': 13138, 'synset': 'mustard.n.03', 'name': 'mustard'}, {'id': 13139, 'synset': 'cabbage.n.01', 'name': 'cabbage'}, {'id': 13140, 'synset': 'kale.n.03', 'name': 'kale'}, {'id': 13141, 'synset': 'collards.n.01', 'name': 'collards'}, {'id': 13142, 'synset': 'chinese_cabbage.n.02', 'name': 'Chinese_cabbage'}, {'id': 13143, 'synset': 'bok_choy.n.02', 'name': 'bok_choy'}, {'id': 13144, 'synset': 'head_cabbage.n.02', 'name': 'head_cabbage'}, {'id': 13145, 'synset': 'red_cabbage.n.02', 'name': 'red_cabbage'}, {'id': 13146, 'synset': 'savoy_cabbage.n.02', 'name': 'savoy_cabbage'}, {'id': 13147, 'synset': 'broccoli.n.02', 'name': 'broccoli'}, {'id': 13148, 'synset': 'broccoli_rabe.n.02', 'name': 'broccoli_rabe'}, {'id': 13149, 'synset': 'squash.n.02', 'name': 'squash'}, {'id': 13150, 'synset': 'summer_squash.n.02', 'name': 'summer_squash'}, {'id': 13151, 'synset': 'yellow_squash.n.02', 'name': 'yellow_squash'}, {'id': 13152, 'synset': 'crookneck.n.01', 'name': 'crookneck'}, {'id': 13153, 'synset': 'marrow.n.04', 'name': 'marrow'}, {'id': 13154, 'synset': 'cocozelle.n.02', 'name': 'cocozelle'}, {'id': 13155, 'synset': 'pattypan_squash.n.02', 'name': 'pattypan_squash'}, {'id': 13156, 'synset': 'spaghetti_squash.n.02', 'name': 'spaghetti_squash'}, {'id': 13157, 'synset': 'winter_squash.n.02', 'name': 'winter_squash'}, {'id': 13158, 'synset': 'acorn_squash.n.02', 'name': 'acorn_squash'}, {'id': 13159, 'synset': 'butternut_squash.n.02', 'name': 'butternut_squash'}, {'id': 13160, 'synset': 'hubbard_squash.n.02', 'name': 'hubbard_squash'}, {'id': 13161, 'synset': 'turban_squash.n.02', 'name': 'turban_squash'}, {'id': 13162, 'synset': 'buttercup_squash.n.02', 'name': 'buttercup_squash'}, {'id': 13163, 'synset': 'cushaw.n.02', 'name': 'cushaw'}, {'id': 13164, 'synset': 'winter_crookneck_squash.n.02', 'name': 'winter_crookneck_squash'}, {'id': 13165, 'synset': 'gherkin.n.02', 'name': 'gherkin'}, {'id': 13166, 'synset': 'artichoke_heart.n.01', 'name': 'artichoke_heart'}, {'id': 13167, 'synset': 'jerusalem_artichoke.n.03', 'name': 'Jerusalem_artichoke'}, {'id': 13168, 'synset': 'bamboo_shoot.n.01', 'name': 'bamboo_shoot'}, {'id': 13169, 'synset': 'sprout.n.02', 'name': 'sprout'}, {'id': 13170, 'synset': 'bean_sprout.n.01', 'name': 'bean_sprout'}, {'id': 13171, 'synset': 'alfalfa_sprout.n.01', 'name': 'alfalfa_sprout'}, {'id': 13172, 'synset': 'beet.n.02', 'name': 'beet'}, {'id': 13173, 'synset': 'beet_green.n.01', 'name': 'beet_green'}, {'id': 13174, 'synset': 'sugar_beet.n.02', 'name': 'sugar_beet'}, {'id': 13175, 'synset': 'mangel-wurzel.n.02', 'name': 'mangel-wurzel'}, {'id': 13176, 'synset': 'chard.n.02', 'name': 'chard'}, {'id': 13177, 'synset': 'pepper.n.04', 'name': 'pepper'}, {'id': 13178, 'synset': 'sweet_pepper.n.02', 'name': 'sweet_pepper'}, {'id': 13179, 'synset': 'green_pepper.n.01', 'name': 'green_pepper'}, {'id': 13180, 'synset': 'globe_pepper.n.01', 'name': 'globe_pepper'}, {'id': 13181, 'synset': 'pimento.n.02', 'name': 'pimento'}, {'id': 13182, 'synset': 'hot_pepper.n.02', 'name': 'hot_pepper'}, {'id': 13183, 'synset': 'jalapeno.n.02', 'name': 'jalapeno'}, {'id': 13184, 'synset': 'chipotle.n.01', 'name': 'chipotle'}, {'id': 13185, 'synset': 'cayenne.n.03', 'name': 'cayenne'}, {'id': 13186, 'synset': 'tabasco.n.03', 'name': 'tabasco'}, {'id': 13187, 'synset': 'onion.n.03', 'name': 'onion'}, {'id': 13188, 'synset': 'bermuda_onion.n.01', 'name': 'Bermuda_onion'}, {'id': 13189, 'synset': 'vidalia_onion.n.01', 'name': 'Vidalia_onion'}, {'id': 13190, 'synset': 'spanish_onion.n.01', 'name': 'Spanish_onion'}, {'id': 13191, 'synset': 'purple_onion.n.01', 'name': 'purple_onion'}, {'id': 13192, 'synset': 'leek.n.02', 'name': 'leek'}, {'id': 13193, 'synset': 'shallot.n.03', 'name': 'shallot'}, {'id': 13194, 'synset': 'salad_green.n.01', 'name': 'salad_green'}, {'id': 13195, 'synset': 'lettuce.n.03', 'name': 'lettuce'}, {'id': 13196, 'synset': 'butterhead_lettuce.n.01', 'name': 'butterhead_lettuce'}, {'id': 13197, 'synset': 'buttercrunch.n.01', 'name': 'buttercrunch'}, {'id': 13198, 'synset': 'bibb_lettuce.n.01', 'name': 'Bibb_lettuce'}, {'id': 13199, 'synset': 'boston_lettuce.n.01', 'name': 'Boston_lettuce'}, {'id': 13200, 'synset': 'crisphead_lettuce.n.01', 'name': 'crisphead_lettuce'}, {'id': 13201, 'synset': 'cos.n.02', 'name': 'cos'}, {'id': 13202, 'synset': 'leaf_lettuce.n.02', 'name': 'leaf_lettuce'}, {'id': 13203, 'synset': 'celtuce.n.02', 'name': 'celtuce'}, {'id': 13204, 'synset': 'bean.n.01', 'name': 'bean'}, {'id': 13205, 'synset': 'goa_bean.n.02', 'name': 'goa_bean'}, {'id': 13206, 'synset': 'lentil.n.01', 'name': 'lentil'}, {'id': 13207, 'synset': 'green_pea.n.01', 'name': 'green_pea'}, {'id': 13208, 'synset': 'marrowfat_pea.n.01', 'name': 'marrowfat_pea'}, {'id': 13209, 'synset': 'snow_pea.n.02', 'name': 'snow_pea'}, {'id': 13210, 'synset': 'sugar_snap_pea.n.02', 'name': 'sugar_snap_pea'}, {'id': 13211, 'synset': 'split-pea.n.01', 'name': 'split-pea'}, {'id': 13212, 'synset': 'chickpea.n.03', 'name': 'chickpea'}, {'id': 13213, 'synset': 'cajan_pea.n.02', 'name': 'cajan_pea'}, {'id': 13214, 'synset': 'field_pea.n.03', 'name': 'field_pea'}, {'id': 13215, 'synset': 'mushy_peas.n.01', 'name': 'mushy_peas'}, {'id': 13216, 'synset': 'black-eyed_pea.n.03', 'name': 'black-eyed_pea'}, {'id': 13217, 'synset': 'common_bean.n.02', 'name': 'common_bean'}, {'id': 13218, 'synset': 'kidney_bean.n.02', 'name': 'kidney_bean'}, {'id': 13219, 'synset': 'navy_bean.n.01', 'name': 'navy_bean'}, {'id': 13220, 'synset': 'pinto_bean.n.01', 'name': 'pinto_bean'}, {'id': 13221, 'synset': 'frijole.n.02', 'name': 'frijole'}, {'id': 13222, 'synset': 'black_bean.n.01', 'name': 'black_bean'}, {'id': 13223, 'synset': 'fresh_bean.n.01', 'name': 'fresh_bean'}, {'id': 13224, 'synset': 'flageolet.n.01', 'name': 'flageolet'}, {'id': 13225, 'synset': 'green_bean.n.01', 'name': 'green_bean'}, {'id': 13226, 'synset': 'snap_bean.n.01', 'name': 'snap_bean'}, {'id': 13227, 'synset': 'string_bean.n.01', 'name': 'string_bean'}, {'id': 13228, 'synset': 'kentucky_wonder.n.01', 'name': 'Kentucky_wonder'}, {'id': 13229, 'synset': 'scarlet_runner.n.03', 'name': 'scarlet_runner'}, {'id': 13230, 'synset': 'haricot_vert.n.01', 'name': 'haricot_vert'}, {'id': 13231, 'synset': 'wax_bean.n.02', 'name': 'wax_bean'}, {'id': 13232, 'synset': 'shell_bean.n.02', 'name': 'shell_bean'}, {'id': 13233, 'synset': 'lima_bean.n.03', 'name': 'lima_bean'}, {'id': 13234, 'synset': 'fordhooks.n.01', 'name': 'Fordhooks'}, {'id': 13235, 'synset': 'sieva_bean.n.02', 'name': 'sieva_bean'}, {'id': 13236, 'synset': 'fava_bean.n.02', 'name': 'fava_bean'}, {'id': 13237, 'synset': 'soy.n.04', 'name': 'soy'}, {'id': 13238, 'synset': 'green_soybean.n.01', 'name': 'green_soybean'}, {'id': 13239, 'synset': 'field_soybean.n.01', 'name': 'field_soybean'}, {'id': 13240, 'synset': 'cardoon.n.02', 'name': 'cardoon'}, {'id': 13241, 'synset': 'carrot.n.03', 'name': 'carrot'}, {'id': 13242, 'synset': 'carrot_stick.n.01', 'name': 'carrot_stick'}, {'id': 13243, 'synset': 'celery.n.02', 'name': 'celery'}, {'id': 13244, 'synset': 'pascal_celery.n.01', 'name': 'pascal_celery'}, {'id': 13245, 'synset': 'celeriac.n.02', 'name': 'celeriac'}, {'id': 13246, 'synset': 'chicory.n.04', 'name': 'chicory'}, {'id': 13247, 'synset': 'radicchio.n.01', 'name': 'radicchio'}, {'id': 13248, 'synset': 'coffee_substitute.n.01', 'name': 'coffee_substitute'}, {'id': 13249, 'synset': 'chicory.n.03', 'name': 'chicory'}, {'id': 13250, 'synset': 'postum.n.01', 'name': 'Postum'}, {'id': 13251, 'synset': 'chicory_escarole.n.01', 'name': 'chicory_escarole'}, {'id': 13252, 'synset': 'belgian_endive.n.01', 'name': 'Belgian_endive'}, {'id': 13253, 'synset': 'sweet_corn.n.02', 'name': 'sweet_corn'}, {'id': 13254, 'synset': 'hominy.n.01', 'name': 'hominy'}, {'id': 13255, 'synset': 'lye_hominy.n.01', 'name': 'lye_hominy'}, {'id': 13256, 'synset': 'pearl_hominy.n.01', 'name': 'pearl_hominy'}, {'id': 13257, 'synset': 'popcorn.n.02', 'name': 'popcorn'}, {'id': 13258, 'synset': 'cress.n.02', 'name': 'cress'}, {'id': 13259, 'synset': 'watercress.n.02', 'name': 'watercress'}, {'id': 13260, 'synset': 'garden_cress.n.01', 'name': 'garden_cress'}, {'id': 13261, 'synset': 'winter_cress.n.02', 'name': 'winter_cress'}, {'id': 13262, 'synset': 'dandelion_green.n.02', 'name': 'dandelion_green'}, {'id': 13263, 'synset': 'gumbo.n.03', 'name': 'gumbo'}, {'id': 13264, 'synset': 'kohlrabi.n.02', 'name': 'kohlrabi'}, {'id': 13265, 'synset': "lamb's-quarter.n.01", 'name': "lamb's-quarter"}, {'id': 13266, 'synset': 'wild_spinach.n.03', 'name': 'wild_spinach'}, {'id': 13267, 'synset': 'beefsteak_tomato.n.01', 'name': 'beefsteak_tomato'}, {'id': 13268, 'synset': 'cherry_tomato.n.02', 'name': 'cherry_tomato'}, {'id': 13269, 'synset': 'plum_tomato.n.02', 'name': 'plum_tomato'}, {'id': 13270, 'synset': 'tomatillo.n.03', 'name': 'tomatillo'}, {'id': 13271, 'synset': 'mushroom.n.05', 'name': 'mushroom'}, {'id': 13272, 'synset': 'stuffed_mushroom.n.01', 'name': 'stuffed_mushroom'}, {'id': 13273, 'synset': 'salsify.n.03', 'name': 'salsify'}, {'id': 13274, 'synset': 'oyster_plant.n.03', 'name': 'oyster_plant'}, {'id': 13275, 'synset': 'scorzonera.n.02', 'name': 'scorzonera'}, {'id': 13276, 'synset': 'parsnip.n.03', 'name': 'parsnip'}, {'id': 13277, 'synset': 'radish.n.01', 'name': 'radish'}, {'id': 13278, 'synset': 'turnip.n.02', 'name': 'turnip'}, {'id': 13279, 'synset': 'white_turnip.n.02', 'name': 'white_turnip'}, {'id': 13280, 'synset': 'rutabaga.n.01', 'name': 'rutabaga'}, {'id': 13281, 'synset': 'turnip_greens.n.01', 'name': 'turnip_greens'}, {'id': 13282, 'synset': 'sorrel.n.04', 'name': 'sorrel'}, {'id': 13283, 'synset': 'french_sorrel.n.02', 'name': 'French_sorrel'}, {'id': 13284, 'synset': 'spinach.n.02', 'name': 'spinach'}, {'id': 13285, 'synset': 'taro.n.03', 'name': 'taro'}, {'id': 13286, 'synset': 'truffle.n.02', 'name': 'truffle'}, {'id': 13287, 'synset': 'edible_nut.n.01', 'name': 'edible_nut'}, {'id': 13288, 'synset': 'bunya_bunya.n.02', 'name': 'bunya_bunya'}, {'id': 13289, 'synset': 'peanut.n.04', 'name': 'peanut'}, {'id': 13290, 'synset': 'freestone.n.01', 'name': 'freestone'}, {'id': 13291, 'synset': 'cling.n.01', 'name': 'cling'}, {'id': 13292, 'synset': 'windfall.n.01', 'name': 'windfall'}, {'id': 13293, 'synset': 'crab_apple.n.03', 'name': 'crab_apple'}, {'id': 13294, 'synset': 'eating_apple.n.01', 'name': 'eating_apple'}, {'id': 13295, 'synset': 'baldwin.n.03', 'name': 'Baldwin'}, {'id': 13296, 'synset': 'cortland.n.01', 'name': 'Cortland'}, {'id': 13297, 'synset': "cox's_orange_pippin.n.01", 'name': "Cox's_Orange_Pippin"}, {'id': 13298, 'synset': 'delicious.n.01', 'name': 'Delicious'}, {'id': 13299, 'synset': 'golden_delicious.n.01', 'name': 'Golden_Delicious'}, {'id': 13300, 'synset': 'red_delicious.n.01', 'name': 'Red_Delicious'}, {'id': 13301, 'synset': 'empire.n.05', 'name': 'Empire'}, {'id': 13302, 'synset': "grimes'_golden.n.01", 'name': "Grimes'_golden"}, {'id': 13303, 'synset': 'jonathan.n.01', 'name': 'Jonathan'}, {'id': 13304, 'synset': 'mcintosh.n.01', 'name': 'McIntosh'}, {'id': 13305, 'synset': 'macoun.n.01', 'name': 'Macoun'}, {'id': 13306, 'synset': 'northern_spy.n.01', 'name': 'Northern_Spy'}, {'id': 13307, 'synset': 'pearmain.n.01', 'name': 'Pearmain'}, {'id': 13308, 'synset': 'pippin.n.01', 'name': 'Pippin'}, {'id': 13309, 'synset': 'prima.n.01', 'name': 'Prima'}, {'id': 13310, 'synset': 'stayman.n.01', 'name': 'Stayman'}, {'id': 13311, 'synset': 'winesap.n.01', 'name': 'Winesap'}, {'id': 13312, 'synset': 'stayman_winesap.n.01', 'name': 'Stayman_Winesap'}, {'id': 13313, 'synset': 'cooking_apple.n.01', 'name': 'cooking_apple'}, {'id': 13314, 'synset': "bramley's_seedling.n.01", 'name': "Bramley's_Seedling"}, {'id': 13315, 'synset': 'granny_smith.n.01', 'name': 'Granny_Smith'}, {'id': 13316, 'synset': "lane's_prince_albert.n.01", 'name': "Lane's_Prince_Albert"}, {'id': 13317, 'synset': 'newtown_wonder.n.01', 'name': 'Newtown_Wonder'}, {'id': 13318, 'synset': 'rome_beauty.n.01', 'name': 'Rome_Beauty'}, {'id': 13319, 'synset': 'berry.n.01', 'name': 'berry'}, {'id': 13320, 'synset': 'bilberry.n.03', 'name': 'bilberry'}, {'id': 13321, 'synset': 'huckleberry.n.03', 'name': 'huckleberry'}, {'id': 13322, 'synset': 'wintergreen.n.03', 'name': 'wintergreen'}, {'id': 13323, 'synset': 'cranberry.n.02', 'name': 'cranberry'}, {'id': 13324, 'synset': 'lingonberry.n.02', 'name': 'lingonberry'}, {'id': 13325, 'synset': 'currant.n.01', 'name': 'currant'}, {'id': 13326, 'synset': 'gooseberry.n.02', 'name': 'gooseberry'}, {'id': 13327, 'synset': 'black_currant.n.02', 'name': 'black_currant'}, {'id': 13328, 'synset': 'red_currant.n.02', 'name': 'red_currant'}, {'id': 13329, 'synset': 'boysenberry.n.02', 'name': 'boysenberry'}, {'id': 13330, 'synset': 'dewberry.n.02', 'name': 'dewberry'}, {'id': 13331, 'synset': 'loganberry.n.02', 'name': 'loganberry'}, {'id': 13332, 'synset': 'saskatoon.n.02', 'name': 'saskatoon'}, {'id': 13333, 'synset': 'sugarberry.n.02', 'name': 'sugarberry'}, {'id': 13334, 'synset': 'acerola.n.02', 'name': 'acerola'}, {'id': 13335, 'synset': 'carambola.n.02', 'name': 'carambola'}, {'id': 13336, 'synset': 'ceriman.n.02', 'name': 'ceriman'}, {'id': 13337, 'synset': 'carissa_plum.n.01', 'name': 'carissa_plum'}, {'id': 13338, 'synset': 'citrus.n.01', 'name': 'citrus'}, {'id': 13339, 'synset': 'temple_orange.n.02', 'name': 'temple_orange'}, {'id': 13340, 'synset': 'clementine.n.02', 'name': 'clementine'}, {'id': 13341, 'synset': 'satsuma.n.02', 'name': 'satsuma'}, {'id': 13342, 'synset': 'tangerine.n.02', 'name': 'tangerine'}, {'id': 13343, 'synset': 'tangelo.n.02', 'name': 'tangelo'}, {'id': 13344, 'synset': 'bitter_orange.n.02', 'name': 'bitter_orange'}, {'id': 13345, 'synset': 'sweet_orange.n.01', 'name': 'sweet_orange'}, {'id': 13346, 'synset': 'jaffa_orange.n.01', 'name': 'Jaffa_orange'}, {'id': 13347, 'synset': 'navel_orange.n.01', 'name': 'navel_orange'}, {'id': 13348, 'synset': 'valencia_orange.n.01', 'name': 'Valencia_orange'}, {'id': 13349, 'synset': 'kumquat.n.02', 'name': 'kumquat'}, {'id': 13350, 'synset': 'key_lime.n.01', 'name': 'key_lime'}, {'id': 13351, 'synset': 'grapefruit.n.02', 'name': 'grapefruit'}, {'id': 13352, 'synset': 'pomelo.n.02', 'name': 'pomelo'}, {'id': 13353, 'synset': 'citrange.n.02', 'name': 'citrange'}, {'id': 13354, 'synset': 'citron.n.01', 'name': 'citron'}, {'id': 13355, 'synset': 'jordan_almond.n.02', 'name': 'Jordan_almond'}, {'id': 13356, 'synset': 'nectarine.n.02', 'name': 'nectarine'}, {'id': 13357, 'synset': 'pitahaya.n.02', 'name': 'pitahaya'}, {'id': 13358, 'synset': 'plum.n.02', 'name': 'plum'}, {'id': 13359, 'synset': 'damson.n.01', 'name': 'damson'}, {'id': 13360, 'synset': 'greengage.n.01', 'name': 'greengage'}, {'id': 13361, 'synset': 'beach_plum.n.02', 'name': 'beach_plum'}, {'id': 13362, 'synset': 'sloe.n.03', 'name': 'sloe'}, {'id': 13363, 'synset': 'victoria_plum.n.01', 'name': 'Victoria_plum'}, {'id': 13364, 'synset': 'dried_fruit.n.01', 'name': 'dried_fruit'}, {'id': 13365, 'synset': 'dried_apricot.n.01', 'name': 'dried_apricot'}, {'id': 13366, 'synset': 'raisin.n.01', 'name': 'raisin'}, {'id': 13367, 'synset': 'seedless_raisin.n.01', 'name': 'seedless_raisin'}, {'id': 13368, 'synset': 'seeded_raisin.n.01', 'name': 'seeded_raisin'}, {'id': 13369, 'synset': 'currant.n.03', 'name': 'currant'}, {'id': 13370, 'synset': 'anchovy_pear.n.02', 'name': 'anchovy_pear'}, {'id': 13371, 'synset': 'passion_fruit.n.01', 'name': 'passion_fruit'}, {'id': 13372, 'synset': 'granadilla.n.04', 'name': 'granadilla'}, {'id': 13373, 'synset': 'sweet_calabash.n.02', 'name': 'sweet_calabash'}, {'id': 13374, 'synset': 'bell_apple.n.01', 'name': 'bell_apple'}, {'id': 13375, 'synset': 'breadfruit.n.02', 'name': 'breadfruit'}, {'id': 13376, 'synset': 'jackfruit.n.02', 'name': 'jackfruit'}, {'id': 13377, 'synset': 'cacao_bean.n.01', 'name': 'cacao_bean'}, {'id': 13378, 'synset': 'cocoa.n.02', 'name': 'cocoa'}, {'id': 13379, 'synset': 'canistel.n.02', 'name': 'canistel'}, {'id': 13380, 'synset': 'melon_ball.n.01', 'name': 'melon_ball'}, {'id': 13381, 'synset': 'muskmelon.n.02', 'name': 'muskmelon'}, {'id': 13382, 'synset': 'winter_melon.n.02', 'name': 'winter_melon'}, {'id': 13383, 'synset': 'honeydew.n.01', 'name': 'honeydew'}, {'id': 13384, 'synset': 'persian_melon.n.02', 'name': 'Persian_melon'}, {'id': 13385, 'synset': 'net_melon.n.02', 'name': 'net_melon'}, {'id': 13386, 'synset': 'casaba.n.01', 'name': 'casaba'}, {'id': 13387, 'synset': 'sweet_cherry.n.02', 'name': 'sweet_cherry'}, {'id': 13388, 'synset': 'bing_cherry.n.01', 'name': 'bing_cherry'}, {'id': 13389, 'synset': 'heart_cherry.n.02', 'name': 'heart_cherry'}, {'id': 13390, 'synset': 'blackheart.n.02', 'name': 'blackheart'}, {'id': 13391, 'synset': 'capulin.n.02', 'name': 'capulin'}, {'id': 13392, 'synset': 'sour_cherry.n.03', 'name': 'sour_cherry'}, {'id': 13393, 'synset': 'amarelle.n.02', 'name': 'amarelle'}, {'id': 13394, 'synset': 'morello.n.02', 'name': 'morello'}, {'id': 13395, 'synset': 'cocoa_plum.n.02', 'name': 'cocoa_plum'}, {'id': 13396, 'synset': 'gherkin.n.01', 'name': 'gherkin'}, {'id': 13397, 'synset': 'fox_grape.n.02', 'name': 'fox_grape'}, {'id': 13398, 'synset': 'concord_grape.n.01', 'name': 'Concord_grape'}, {'id': 13399, 'synset': 'catawba.n.02', 'name': 'Catawba'}, {'id': 13400, 'synset': 'muscadine.n.02', 'name': 'muscadine'}, {'id': 13401, 'synset': 'scuppernong.n.01', 'name': 'scuppernong'}, {'id': 13402, 'synset': 'slipskin_grape.n.01', 'name': 'slipskin_grape'}, {'id': 13403, 'synset': 'vinifera_grape.n.02', 'name': 'vinifera_grape'}, {'id': 13404, 'synset': 'emperor.n.02', 'name': 'emperor'}, {'id': 13405, 'synset': 'muscat.n.04', 'name': 'muscat'}, {'id': 13406, 'synset': 'ribier.n.01', 'name': 'ribier'}, {'id': 13407, 'synset': 'sultana.n.01', 'name': 'sultana'}, {'id': 13408, 'synset': 'tokay.n.02', 'name': 'Tokay'}, {'id': 13409, 'synset': 'flame_tokay.n.01', 'name': 'flame_tokay'}, {'id': 13410, 'synset': 'thompson_seedless.n.01', 'name': 'Thompson_Seedless'}, {'id': 13411, 'synset': 'custard_apple.n.02', 'name': 'custard_apple'}, {'id': 13412, 'synset': 'cherimoya.n.02', 'name': 'cherimoya'}, {'id': 13413, 'synset': 'soursop.n.02', 'name': 'soursop'}, {'id': 13414, 'synset': 'sweetsop.n.02', 'name': 'sweetsop'}, {'id': 13415, 'synset': 'ilama.n.02', 'name': 'ilama'}, {'id': 13416, 'synset': 'pond_apple.n.02', 'name': 'pond_apple'}, {'id': 13417, 'synset': 'papaw.n.02', 'name': 'papaw'}, {'id': 13418, 'synset': 'kai_apple.n.01', 'name': 'kai_apple'}, {'id': 13419, 'synset': 'ketembilla.n.02', 'name': 'ketembilla'}, {'id': 13420, 'synset': 'ackee.n.01', 'name': 'ackee'}, {'id': 13421, 'synset': 'durian.n.02', 'name': 'durian'}, {'id': 13422, 'synset': 'feijoa.n.02', 'name': 'feijoa'}, {'id': 13423, 'synset': 'genip.n.02', 'name': 'genip'}, {'id': 13424, 'synset': 'genipap.n.01', 'name': 'genipap'}, {'id': 13425, 'synset': 'loquat.n.02', 'name': 'loquat'}, {'id': 13426, 'synset': 'mangosteen.n.02', 'name': 'mangosteen'}, {'id': 13427, 'synset': 'mango.n.02', 'name': 'mango'}, {'id': 13428, 'synset': 'sapodilla.n.02', 'name': 'sapodilla'}, {'id': 13429, 'synset': 'sapote.n.02', 'name': 'sapote'}, {'id': 13430, 'synset': 'tamarind.n.02', 'name': 'tamarind'}, {'id': 13431, 'synset': 'elderberry.n.02', 'name': 'elderberry'}, {'id': 13432, 'synset': 'guava.n.03', 'name': 'guava'}, {'id': 13433, 'synset': 'mombin.n.02', 'name': 'mombin'}, {'id': 13434, 'synset': 'hog_plum.n.04', 'name': 'hog_plum'}, {'id': 13435, 'synset': 'hog_plum.n.03', 'name': 'hog_plum'}, {'id': 13436, 'synset': 'jaboticaba.n.02', 'name': 'jaboticaba'}, {'id': 13437, 'synset': 'jujube.n.02', 'name': 'jujube'}, {'id': 13438, 'synset': 'litchi.n.02', 'name': 'litchi'}, {'id': 13439, 'synset': 'longanberry.n.02', 'name': 'longanberry'}, {'id': 13440, 'synset': 'mamey.n.02', 'name': 'mamey'}, {'id': 13441, 'synset': 'marang.n.02', 'name': 'marang'}, {'id': 13442, 'synset': 'medlar.n.04', 'name': 'medlar'}, {'id': 13443, 'synset': 'medlar.n.03', 'name': 'medlar'}, {'id': 13444, 'synset': 'mulberry.n.02', 'name': 'mulberry'}, {'id': 13445, 'synset': 'olive.n.04', 'name': 'olive'}, {'id': 13446, 'synset': 'black_olive.n.01', 'name': 'black_olive'}, {'id': 13447, 'synset': 'green_olive.n.01', 'name': 'green_olive'}, {'id': 13448, 'synset': 'bosc.n.01', 'name': 'bosc'}, {'id': 13449, 'synset': 'anjou.n.02', 'name': 'anjou'}, {'id': 13450, 'synset': 'bartlett.n.03', 'name': 'bartlett'}, {'id': 13451, 'synset': 'seckel.n.01', 'name': 'seckel'}, {'id': 13452, 'synset': 'plantain.n.03', 'name': 'plantain'}, {'id': 13453, 'synset': 'plumcot.n.02', 'name': 'plumcot'}, {'id': 13454, 'synset': 'pomegranate.n.02', 'name': 'pomegranate'}, {'id': 13455, 'synset': 'prickly_pear.n.02', 'name': 'prickly_pear'}, {'id': 13456, 'synset': 'barbados_gooseberry.n.02', 'name': 'Barbados_gooseberry'}, {'id': 13457, 'synset': 'quandong.n.04', 'name': 'quandong'}, {'id': 13458, 'synset': 'quandong_nut.n.01', 'name': 'quandong_nut'}, {'id': 13459, 'synset': 'quince.n.02', 'name': 'quince'}, {'id': 13460, 'synset': 'rambutan.n.02', 'name': 'rambutan'}, {'id': 13461, 'synset': 'pulasan.n.02', 'name': 'pulasan'}, {'id': 13462, 'synset': 'rose_apple.n.02', 'name': 'rose_apple'}, {'id': 13463, 'synset': 'sorb.n.01', 'name': 'sorb'}, {'id': 13464, 'synset': 'sour_gourd.n.02', 'name': 'sour_gourd'}, {'id': 13465, 'synset': 'edible_seed.n.01', 'name': 'edible_seed'}, {'id': 13466, 'synset': 'pumpkin_seed.n.01', 'name': 'pumpkin_seed'}, {'id': 13467, 'synset': 'betel_nut.n.01', 'name': 'betel_nut'}, {'id': 13468, 'synset': 'beechnut.n.01', 'name': 'beechnut'}, {'id': 13469, 'synset': 'walnut.n.01', 'name': 'walnut'}, {'id': 13470, 'synset': 'black_walnut.n.02', 'name': 'black_walnut'}, {'id': 13471, 'synset': 'english_walnut.n.02', 'name': 'English_walnut'}, {'id': 13472, 'synset': 'brazil_nut.n.02', 'name': 'brazil_nut'}, {'id': 13473, 'synset': 'butternut.n.02', 'name': 'butternut'}, {'id': 13474, 'synset': 'souari_nut.n.02', 'name': 'souari_nut'}, {'id': 13475, 'synset': 'cashew.n.02', 'name': 'cashew'}, {'id': 13476, 'synset': 'chestnut.n.03', 'name': 'chestnut'}, {'id': 13477, 'synset': 'chincapin.n.01', 'name': 'chincapin'}, {'id': 13478, 'synset': 'hazelnut.n.02', 'name': 'hazelnut'}, {'id': 13479, 'synset': 'coconut_milk.n.02', 'name': 'coconut_milk'}, {'id': 13480, 'synset': 'grugru_nut.n.01', 'name': 'grugru_nut'}, {'id': 13481, 'synset': 'hickory_nut.n.01', 'name': 'hickory_nut'}, {'id': 13482, 'synset': 'cola_extract.n.01', 'name': 'cola_extract'}, {'id': 13483, 'synset': 'macadamia_nut.n.02', 'name': 'macadamia_nut'}, {'id': 13484, 'synset': 'pecan.n.03', 'name': 'pecan'}, {'id': 13485, 'synset': 'pine_nut.n.01', 'name': 'pine_nut'}, {'id': 13486, 'synset': 'pistachio.n.02', 'name': 'pistachio'}, {'id': 13487, 'synset': 'sunflower_seed.n.01', 'name': 'sunflower_seed'}, {'id': 13488, 'synset': 'anchovy_paste.n.01', 'name': 'anchovy_paste'}, {'id': 13489, 'synset': 'rollmops.n.01', 'name': 'rollmops'}, {'id': 13490, 'synset': 'feed.n.01', 'name': 'feed'}, {'id': 13491, 'synset': 'cattle_cake.n.01', 'name': 'cattle_cake'}, {'id': 13492, 'synset': 'creep_feed.n.01', 'name': 'creep_feed'}, {'id': 13493, 'synset': 'fodder.n.02', 'name': 'fodder'}, {'id': 13494, 'synset': 'feed_grain.n.01', 'name': 'feed_grain'}, {'id': 13495, 'synset': 'eatage.n.01', 'name': 'eatage'}, {'id': 13496, 'synset': 'silage.n.01', 'name': 'silage'}, {'id': 13497, 'synset': 'oil_cake.n.01', 'name': 'oil_cake'}, {'id': 13498, 'synset': 'oil_meal.n.01', 'name': 'oil_meal'}, {'id': 13499, 'synset': 'alfalfa.n.02', 'name': 'alfalfa'}, {'id': 13500, 'synset': 'broad_bean.n.03', 'name': 'broad_bean'}, {'id': 13501, 'synset': 'hay.n.01', 'name': 'hay'}, {'id': 13502, 'synset': 'timothy.n.03', 'name': 'timothy'}, {'id': 13503, 'synset': 'stover.n.01', 'name': 'stover'}, {'id': 13504, 'synset': 'grain.n.02', 'name': 'grain'}, {'id': 13505, 'synset': 'grist.n.01', 'name': 'grist'}, {'id': 13506, 'synset': 'groats.n.01', 'name': 'groats'}, {'id': 13507, 'synset': 'millet.n.03', 'name': 'millet'}, {'id': 13508, 'synset': 'barley.n.01', 'name': 'barley'}, {'id': 13509, 'synset': 'pearl_barley.n.01', 'name': 'pearl_barley'}, {'id': 13510, 'synset': 'buckwheat.n.02', 'name': 'buckwheat'}, {'id': 13511, 'synset': 'bulgur.n.01', 'name': 'bulgur'}, {'id': 13512, 'synset': 'wheat.n.02', 'name': 'wheat'}, {'id': 13513, 'synset': 'cracked_wheat.n.01', 'name': 'cracked_wheat'}, {'id': 13514, 'synset': 'stodge.n.01', 'name': 'stodge'}, {'id': 13515, 'synset': 'wheat_germ.n.01', 'name': 'wheat_germ'}, {'id': 13516, 'synset': 'oat.n.02', 'name': 'oat'}, {'id': 13517, 'synset': 'rice.n.01', 'name': 'rice'}, {'id': 13518, 'synset': 'brown_rice.n.01', 'name': 'brown_rice'}, {'id': 13519, 'synset': 'white_rice.n.01', 'name': 'white_rice'}, {'id': 13520, 'synset': 'wild_rice.n.02', 'name': 'wild_rice'}, {'id': 13521, 'synset': 'paddy.n.03', 'name': 'paddy'}, {'id': 13522, 'synset': 'slop.n.01', 'name': 'slop'}, {'id': 13523, 'synset': 'mash.n.02', 'name': 'mash'}, {'id': 13524, 'synset': 'chicken_feed.n.01', 'name': 'chicken_feed'}, {'id': 13525, 'synset': 'cud.n.01', 'name': 'cud'}, {'id': 13526, 'synset': 'bird_feed.n.01', 'name': 'bird_feed'}, {'id': 13527, 'synset': 'petfood.n.01', 'name': 'petfood'}, {'id': 13528, 'synset': 'dog_food.n.01', 'name': 'dog_food'}, {'id': 13529, 'synset': 'cat_food.n.01', 'name': 'cat_food'}, {'id': 13530, 'synset': 'canary_seed.n.01', 'name': 'canary_seed'}, {'id': 13531, 'synset': 'tossed_salad.n.01', 'name': 'tossed_salad'}, {'id': 13532, 'synset': 'green_salad.n.01', 'name': 'green_salad'}, {'id': 13533, 'synset': 'caesar_salad.n.01', 'name': 'Caesar_salad'}, {'id': 13534, 'synset': 'salmagundi.n.02', 'name': 'salmagundi'}, {'id': 13535, 'synset': 'salad_nicoise.n.01', 'name': 'salad_nicoise'}, {'id': 13536, 'synset': 'combination_salad.n.01', 'name': 'combination_salad'}, {'id': 13537, 'synset': "chef's_salad.n.01", 'name': "chef's_salad"}, {'id': 13538, 'synset': 'potato_salad.n.01', 'name': 'potato_salad'}, {'id': 13539, 'synset': 'pasta_salad.n.01', 'name': 'pasta_salad'}, {'id': 13540, 'synset': 'macaroni_salad.n.01', 'name': 'macaroni_salad'}, {'id': 13541, 'synset': 'fruit_salad.n.01', 'name': 'fruit_salad'}, {'id': 13542, 'synset': 'waldorf_salad.n.01', 'name': 'Waldorf_salad'}, {'id': 13543, 'synset': 'crab_louis.n.01', 'name': 'crab_Louis'}, {'id': 13544, 'synset': 'herring_salad.n.01', 'name': 'herring_salad'}, {'id': 13545, 'synset': 'tuna_fish_salad.n.01', 'name': 'tuna_fish_salad'}, {'id': 13546, 'synset': 'chicken_salad.n.01', 'name': 'chicken_salad'}, {'id': 13547, 'synset': 'aspic.n.01', 'name': 'aspic'}, {'id': 13548, 'synset': 'molded_salad.n.01', 'name': 'molded_salad'}, {'id': 13549, 'synset': 'tabbouleh.n.01', 'name': 'tabbouleh'}, {'id': 13550, 'synset': 'ingredient.n.03', 'name': 'ingredient'}, {'id': 13551, 'synset': 'flavorer.n.01', 'name': 'flavorer'}, {'id': 13552, 'synset': 'bouillon_cube.n.01', 'name': 'bouillon_cube'}, {'id': 13553, 'synset': 'herb.n.02', 'name': 'herb'}, {'id': 13554, 'synset': 'fines_herbes.n.01', 'name': 'fines_herbes'}, {'id': 13555, 'synset': 'spice.n.02', 'name': 'spice'}, {'id': 13556, 'synset': 'spearmint_oil.n.01', 'name': 'spearmint_oil'}, {'id': 13557, 'synset': 'lemon_oil.n.01', 'name': 'lemon_oil'}, {'id': 13558, 'synset': 'wintergreen_oil.n.01', 'name': 'wintergreen_oil'}, {'id': 13559, 'synset': 'salt.n.02', 'name': 'salt'}, {'id': 13560, 'synset': 'celery_salt.n.01', 'name': 'celery_salt'}, {'id': 13561, 'synset': 'onion_salt.n.01', 'name': 'onion_salt'}, {'id': 13562, 'synset': 'seasoned_salt.n.01', 'name': 'seasoned_salt'}, {'id': 13563, 'synset': 'sour_salt.n.01', 'name': 'sour_salt'}, {'id': 13564, 'synset': 'five_spice_powder.n.01', 'name': 'five_spice_powder'}, {'id': 13565, 'synset': 'allspice.n.03', 'name': 'allspice'}, {'id': 13566, 'synset': 'cinnamon.n.03', 'name': 'cinnamon'}, {'id': 13567, 'synset': 'stick_cinnamon.n.01', 'name': 'stick_cinnamon'}, {'id': 13568, 'synset': 'clove.n.04', 'name': 'clove'}, {'id': 13569, 'synset': 'cumin.n.02', 'name': 'cumin'}, {'id': 13570, 'synset': 'fennel.n.04', 'name': 'fennel'}, {'id': 13571, 'synset': 'ginger.n.02', 'name': 'ginger'}, {'id': 13572, 'synset': 'mace.n.03', 'name': 'mace'}, {'id': 13573, 'synset': 'nutmeg.n.02', 'name': 'nutmeg'}, {'id': 13574, 'synset': 'black_pepper.n.02', 'name': 'black_pepper'}, {'id': 13575, 'synset': 'white_pepper.n.02', 'name': 'white_pepper'}, {'id': 13576, 'synset': 'sassafras.n.02', 'name': 'sassafras'}, {'id': 13577, 'synset': 'basil.n.03', 'name': 'basil'}, {'id': 13578, 'synset': 'bay_leaf.n.01', 'name': 'bay_leaf'}, {'id': 13579, 'synset': 'borage.n.02', 'name': 'borage'}, {'id': 13580, 'synset': 'hyssop.n.02', 'name': 'hyssop'}, {'id': 13581, 'synset': 'caraway.n.02', 'name': 'caraway'}, {'id': 13582, 'synset': 'chervil.n.02', 'name': 'chervil'}, {'id': 13583, 'synset': 'chives.n.02', 'name': 'chives'}, {'id': 13584, 'synset': 'comfrey.n.02', 'name': 'comfrey'}, {'id': 13585, 'synset': 'coriander.n.03', 'name': 'coriander'}, {'id': 13586, 'synset': 'coriander.n.02', 'name': 'coriander'}, {'id': 13587, 'synset': 'costmary.n.02', 'name': 'costmary'}, {'id': 13588, 'synset': 'fennel.n.03', 'name': 'fennel'}, {'id': 13589, 'synset': 'fennel.n.02', 'name': 'fennel'}, {'id': 13590, 'synset': 'fennel_seed.n.01', 'name': 'fennel_seed'}, {'id': 13591, 'synset': 'fenugreek.n.02', 'name': 'fenugreek'}, {'id': 13592, 'synset': 'clove.n.03', 'name': 'clove'}, {'id': 13593, 'synset': 'garlic_chive.n.02', 'name': 'garlic_chive'}, {'id': 13594, 'synset': 'lemon_balm.n.02', 'name': 'lemon_balm'}, {'id': 13595, 'synset': 'lovage.n.02', 'name': 'lovage'}, {'id': 13596, 'synset': 'marjoram.n.02', 'name': 'marjoram'}, {'id': 13597, 'synset': 'mint.n.04', 'name': 'mint'}, {'id': 13598, 'synset': 'mustard_seed.n.01', 'name': 'mustard_seed'}, {'id': 13599, 'synset': 'mustard.n.02', 'name': 'mustard'}, {'id': 13600, 'synset': 'chinese_mustard.n.02', 'name': 'Chinese_mustard'}, {'id': 13601, 'synset': 'nasturtium.n.03', 'name': 'nasturtium'}, {'id': 13602, 'synset': 'parsley.n.02', 'name': 'parsley'}, {'id': 13603, 'synset': 'salad_burnet.n.02', 'name': 'salad_burnet'}, {'id': 13604, 'synset': 'rosemary.n.02', 'name': 'rosemary'}, {'id': 13605, 'synset': 'rue.n.02', 'name': 'rue'}, {'id': 13606, 'synset': 'sage.n.02', 'name': 'sage'}, {'id': 13607, 'synset': 'clary_sage.n.02', 'name': 'clary_sage'}, {'id': 13608, 'synset': 'savory.n.03', 'name': 'savory'}, {'id': 13609, 'synset': 'summer_savory.n.02', 'name': 'summer_savory'}, {'id': 13610, 'synset': 'winter_savory.n.02', 'name': 'winter_savory'}, {'id': 13611, 'synset': 'sweet_woodruff.n.02', 'name': 'sweet_woodruff'}, {'id': 13612, 'synset': 'sweet_cicely.n.03', 'name': 'sweet_cicely'}, {'id': 13613, 'synset': 'tarragon.n.02', 'name': 'tarragon'}, {'id': 13614, 'synset': 'thyme.n.02', 'name': 'thyme'}, {'id': 13615, 'synset': 'turmeric.n.02', 'name': 'turmeric'}, {'id': 13616, 'synset': 'caper.n.02', 'name': 'caper'}, {'id': 13617, 'synset': 'catsup.n.01', 'name': 'catsup'}, {'id': 13618, 'synset': 'cardamom.n.02', 'name': 'cardamom'}, {'id': 13619, 'synset': 'chili_powder.n.01', 'name': 'chili_powder'}, {'id': 13620, 'synset': 'chili_sauce.n.01', 'name': 'chili_sauce'}, {'id': 13621, 'synset': 'chutney.n.01', 'name': 'chutney'}, {'id': 13622, 'synset': 'steak_sauce.n.01', 'name': 'steak_sauce'}, {'id': 13623, 'synset': 'taco_sauce.n.01', 'name': 'taco_sauce'}, {'id': 13624, 'synset': 'mint_sauce.n.01', 'name': 'mint_sauce'}, {'id': 13625, 'synset': 'cranberry_sauce.n.01', 'name': 'cranberry_sauce'}, {'id': 13626, 'synset': 'curry_powder.n.01', 'name': 'curry_powder'}, {'id': 13627, 'synset': 'curry.n.01', 'name': 'curry'}, {'id': 13628, 'synset': 'lamb_curry.n.01', 'name': 'lamb_curry'}, {'id': 13629, 'synset': 'duck_sauce.n.01', 'name': 'duck_sauce'}, {'id': 13630, 'synset': 'horseradish.n.03', 'name': 'horseradish'}, {'id': 13631, 'synset': 'marinade.n.01', 'name': 'marinade'}, {'id': 13632, 'synset': 'paprika.n.02', 'name': 'paprika'}, {'id': 13633, 'synset': 'spanish_paprika.n.01', 'name': 'Spanish_paprika'}, {'id': 13634, 'synset': 'dill_pickle.n.01', 'name': 'dill_pickle'}, {'id': 13635, 'synset': 'bread_and_butter_pickle.n.01', 'name': 'bread_and_butter_pickle'}, {'id': 13636, 'synset': 'pickle_relish.n.01', 'name': 'pickle_relish'}, {'id': 13637, 'synset': 'piccalilli.n.01', 'name': 'piccalilli'}, {'id': 13638, 'synset': 'sweet_pickle.n.01', 'name': 'sweet_pickle'}, {'id': 13639, 'synset': 'soy_sauce.n.01', 'name': 'soy_sauce'}, {'id': 13640, 'synset': 'tomato_paste.n.01', 'name': 'tomato_paste'}, {'id': 13641, 'synset': 'angelica.n.03', 'name': 'angelica'}, {'id': 13642, 'synset': 'angelica.n.02', 'name': 'angelica'}, {'id': 13643, 'synset': 'almond_extract.n.01', 'name': 'almond_extract'}, {'id': 13644, 'synset': 'anise.n.02', 'name': 'anise'}, {'id': 13645, 'synset': 'chinese_anise.n.02', 'name': 'Chinese_anise'}, {'id': 13646, 'synset': 'juniper_berries.n.01', 'name': 'juniper_berries'}, {'id': 13647, 'synset': 'saffron.n.02', 'name': 'saffron'}, {'id': 13648, 'synset': 'sesame_seed.n.01', 'name': 'sesame_seed'}, {'id': 13649, 'synset': 'caraway_seed.n.01', 'name': 'caraway_seed'}, {'id': 13650, 'synset': 'poppy_seed.n.01', 'name': 'poppy_seed'}, {'id': 13651, 'synset': 'dill.n.02', 'name': 'dill'}, {'id': 13652, 'synset': 'dill_seed.n.01', 'name': 'dill_seed'}, {'id': 13653, 'synset': 'celery_seed.n.01', 'name': 'celery_seed'}, {'id': 13654, 'synset': 'lemon_extract.n.01', 'name': 'lemon_extract'}, {'id': 13655, 'synset': 'monosodium_glutamate.n.01', 'name': 'monosodium_glutamate'}, {'id': 13656, 'synset': 'vanilla_bean.n.01', 'name': 'vanilla_bean'}, {'id': 13657, 'synset': 'cider_vinegar.n.01', 'name': 'cider_vinegar'}, {'id': 13658, 'synset': 'wine_vinegar.n.01', 'name': 'wine_vinegar'}, {'id': 13659, 'synset': 'sauce.n.01', 'name': 'sauce'}, {'id': 13660, 'synset': 'anchovy_sauce.n.01', 'name': 'anchovy_sauce'}, {'id': 13661, 'synset': 'hard_sauce.n.01', 'name': 'hard_sauce'}, {'id': 13662, 'synset': 'horseradish_sauce.n.01', 'name': 'horseradish_sauce'}, {'id': 13663, 'synset': 'bolognese_pasta_sauce.n.01', 'name': 'bolognese_pasta_sauce'}, {'id': 13664, 'synset': 'carbonara.n.01', 'name': 'carbonara'}, {'id': 13665, 'synset': 'tomato_sauce.n.01', 'name': 'tomato_sauce'}, {'id': 13666, 'synset': 'tartare_sauce.n.01', 'name': 'tartare_sauce'}, {'id': 13667, 'synset': 'wine_sauce.n.01', 'name': 'wine_sauce'}, {'id': 13668, 'synset': 'marchand_de_vin.n.01', 'name': 'marchand_de_vin'}, {'id': 13669, 'synset': 'bread_sauce.n.01', 'name': 'bread_sauce'}, {'id': 13670, 'synset': 'plum_sauce.n.01', 'name': 'plum_sauce'}, {'id': 13671, 'synset': 'peach_sauce.n.01', 'name': 'peach_sauce'}, {'id': 13672, 'synset': 'apricot_sauce.n.01', 'name': 'apricot_sauce'}, {'id': 13673, 'synset': 'pesto.n.01', 'name': 'pesto'}, {'id': 13674, 'synset': 'ravigote.n.01', 'name': 'ravigote'}, {'id': 13675, 'synset': 'remoulade_sauce.n.01', 'name': 'remoulade_sauce'}, {'id': 13676, 'synset': 'dressing.n.01', 'name': 'dressing'}, {'id': 13677, 'synset': 'sauce_louis.n.01', 'name': 'sauce_Louis'}, {'id': 13678, 'synset': 'bleu_cheese_dressing.n.01', 'name': 'bleu_cheese_dressing'}, {'id': 13679, 'synset': 'blue_cheese_dressing.n.01', 'name': 'blue_cheese_dressing'}, {'id': 13680, 'synset': 'french_dressing.n.01', 'name': 'French_dressing'}, {'id': 13681, 'synset': 'lorenzo_dressing.n.01', 'name': 'Lorenzo_dressing'}, {'id': 13682, 'synset': 'anchovy_dressing.n.01', 'name': 'anchovy_dressing'}, {'id': 13683, 'synset': 'italian_dressing.n.01', 'name': 'Italian_dressing'}, {'id': 13684, 'synset': 'half-and-half_dressing.n.01', 'name': 'half-and-half_dressing'}, {'id': 13685, 'synset': 'mayonnaise.n.01', 'name': 'mayonnaise'}, {'id': 13686, 'synset': 'green_mayonnaise.n.01', 'name': 'green_mayonnaise'}, {'id': 13687, 'synset': 'aioli.n.01', 'name': 'aioli'}, {'id': 13688, 'synset': 'russian_dressing.n.01', 'name': 'Russian_dressing'}, {'id': 13689, 'synset': 'salad_cream.n.01', 'name': 'salad_cream'}, {'id': 13690, 'synset': 'thousand_island_dressing.n.01', 'name': 'Thousand_Island_dressing'}, {'id': 13691, 'synset': 'barbecue_sauce.n.01', 'name': 'barbecue_sauce'}, {'id': 13692, 'synset': 'hollandaise.n.01', 'name': 'hollandaise'}, {'id': 13693, 'synset': 'bearnaise.n.01', 'name': 'bearnaise'}, {'id': 13694, 'synset': 'bercy.n.01', 'name': 'Bercy'}, {'id': 13695, 'synset': 'bordelaise.n.01', 'name': 'bordelaise'}, {'id': 13696, 'synset': 'bourguignon.n.01', 'name': 'bourguignon'}, {'id': 13697, 'synset': 'brown_sauce.n.02', 'name': 'brown_sauce'}, {'id': 13698, 'synset': 'espagnole.n.01', 'name': 'Espagnole'}, {'id': 13699, 'synset': 'chinese_brown_sauce.n.01', 'name': 'Chinese_brown_sauce'}, {'id': 13700, 'synset': 'blanc.n.01', 'name': 'blanc'}, {'id': 13701, 'synset': 'cheese_sauce.n.01', 'name': 'cheese_sauce'}, {'id': 13702, 'synset': 'chocolate_sauce.n.01', 'name': 'chocolate_sauce'}, {'id': 13703, 'synset': 'hot-fudge_sauce.n.01', 'name': 'hot-fudge_sauce'}, {'id': 13704, 'synset': 'cocktail_sauce.n.01', 'name': 'cocktail_sauce'}, {'id': 13705, 'synset': 'colbert.n.01', 'name': 'Colbert'}, {'id': 13706, 'synset': 'white_sauce.n.01', 'name': 'white_sauce'}, {'id': 13707, 'synset': 'cream_sauce.n.01', 'name': 'cream_sauce'}, {'id': 13708, 'synset': 'mornay_sauce.n.01', 'name': 'Mornay_sauce'}, {'id': 13709, 'synset': 'demiglace.n.01', 'name': 'demiglace'}, {'id': 13710, 'synset': 'gravy.n.02', 'name': 'gravy'}, {'id': 13711, 'synset': 'gravy.n.01', 'name': 'gravy'}, {'id': 13712, 'synset': 'spaghetti_sauce.n.01', 'name': 'spaghetti_sauce'}, {'id': 13713, 'synset': 'marinara.n.01', 'name': 'marinara'}, {'id': 13714, 'synset': 'mole.n.03', 'name': 'mole'}, {'id': 13715, 'synset': "hunter's_sauce.n.01", 'name': "hunter's_sauce"}, {'id': 13716, 'synset': 'mushroom_sauce.n.01', 'name': 'mushroom_sauce'}, {'id': 13717, 'synset': 'mustard_sauce.n.01', 'name': 'mustard_sauce'}, {'id': 13718, 'synset': 'nantua.n.01', 'name': 'Nantua'}, {'id': 13719, 'synset': 'hungarian_sauce.n.01', 'name': 'Hungarian_sauce'}, {'id': 13720, 'synset': 'pepper_sauce.n.01', 'name': 'pepper_sauce'}, {'id': 13721, 'synset': 'roux.n.01', 'name': 'roux'}, {'id': 13722, 'synset': 'smitane.n.01', 'name': 'Smitane'}, {'id': 13723, 'synset': 'soubise.n.01', 'name': 'Soubise'}, {'id': 13724, 'synset': 'lyonnaise_sauce.n.01', 'name': 'Lyonnaise_sauce'}, {'id': 13725, 'synset': 'veloute.n.01', 'name': 'veloute'}, {'id': 13726, 'synset': 'allemande.n.01', 'name': 'allemande'}, {'id': 13727, 'synset': 'caper_sauce.n.01', 'name': 'caper_sauce'}, {'id': 13728, 'synset': 'poulette.n.01', 'name': 'poulette'}, {'id': 13729, 'synset': 'curry_sauce.n.01', 'name': 'curry_sauce'}, {'id': 13730, 'synset': 'worcester_sauce.n.01', 'name': 'Worcester_sauce'}, {'id': 13731, 'synset': 'coconut_milk.n.01', 'name': 'coconut_milk'}, {'id': 13732, 'synset': 'egg_white.n.01', 'name': 'egg_white'}, {'id': 13733, 'synset': 'hard-boiled_egg.n.01', 'name': 'hard-boiled_egg'}, {'id': 13734, 'synset': 'easter_egg.n.02', 'name': 'Easter_egg'}, {'id': 13735, 'synset': 'easter_egg.n.01', 'name': 'Easter_egg'}, {'id': 13736, 'synset': 'chocolate_egg.n.01', 'name': 'chocolate_egg'}, {'id': 13737, 'synset': 'candy_egg.n.01', 'name': 'candy_egg'}, {'id': 13738, 'synset': 'poached_egg.n.01', 'name': 'poached_egg'}, {'id': 13739, 'synset': 'scrambled_eggs.n.01', 'name': 'scrambled_eggs'}, {'id': 13740, 'synset': 'deviled_egg.n.01', 'name': 'deviled_egg'}, {'id': 13741, 'synset': 'shirred_egg.n.01', 'name': 'shirred_egg'}, {'id': 13742, 'synset': 'firm_omelet.n.01', 'name': 'firm_omelet'}, {'id': 13743, 'synset': 'french_omelet.n.01', 'name': 'French_omelet'}, {'id': 13744, 'synset': 'fluffy_omelet.n.01', 'name': 'fluffy_omelet'}, {'id': 13745, 'synset': 'western_omelet.n.01', 'name': 'western_omelet'}, {'id': 13746, 'synset': 'souffle.n.01', 'name': 'souffle'}, {'id': 13747, 'synset': 'fried_egg.n.01', 'name': 'fried_egg'}, {'id': 13748, 'synset': 'dairy_product.n.01', 'name': 'dairy_product'}, {'id': 13749, 'synset': 'milk.n.04', 'name': 'milk'}, {'id': 13750, 'synset': 'sour_milk.n.01', 'name': 'sour_milk'}, {'id': 13751, 'synset': 'formula.n.06', 'name': 'formula'}, {'id': 13752, 'synset': 'pasteurized_milk.n.01', 'name': 'pasteurized_milk'}, {'id': 13753, 'synset': "cows'_milk.n.01", 'name': "cows'_milk"}, {'id': 13754, 'synset': "yak's_milk.n.01", 'name': "yak's_milk"}, {'id': 13755, 'synset': "goats'_milk.n.01", 'name': "goats'_milk"}, {'id': 13756, 'synset': 'acidophilus_milk.n.01', 'name': 'acidophilus_milk'}, {'id': 13757, 'synset': 'raw_milk.n.01', 'name': 'raw_milk'}, {'id': 13758, 'synset': 'scalded_milk.n.01', 'name': 'scalded_milk'}, {'id': 13759, 'synset': 'homogenized_milk.n.01', 'name': 'homogenized_milk'}, {'id': 13760, 'synset': 'certified_milk.n.01', 'name': 'certified_milk'}, {'id': 13761, 'synset': 'powdered_milk.n.01', 'name': 'powdered_milk'}, {'id': 13762, 'synset': 'nonfat_dry_milk.n.01', 'name': 'nonfat_dry_milk'}, {'id': 13763, 'synset': 'evaporated_milk.n.01', 'name': 'evaporated_milk'}, {'id': 13764, 'synset': 'condensed_milk.n.01', 'name': 'condensed_milk'}, {'id': 13765, 'synset': 'skim_milk.n.01', 'name': 'skim_milk'}, {'id': 13766, 'synset': 'semi-skimmed_milk.n.01', 'name': 'semi-skimmed_milk'}, {'id': 13767, 'synset': 'whole_milk.n.01', 'name': 'whole_milk'}, {'id': 13768, 'synset': 'low-fat_milk.n.01', 'name': 'low-fat_milk'}, {'id': 13769, 'synset': 'buttermilk.n.01', 'name': 'buttermilk'}, {'id': 13770, 'synset': 'cream.n.02', 'name': 'cream'}, {'id': 13771, 'synset': 'clotted_cream.n.01', 'name': 'clotted_cream'}, {'id': 13772, 'synset': 'double_creme.n.01', 'name': 'double_creme'}, {'id': 13773, 'synset': 'half-and-half.n.01', 'name': 'half-and-half'}, {'id': 13774, 'synset': 'heavy_cream.n.01', 'name': 'heavy_cream'}, {'id': 13775, 'synset': 'light_cream.n.01', 'name': 'light_cream'}, {'id': 13776, 'synset': 'whipping_cream.n.01', 'name': 'whipping_cream'}, {'id': 13777, 'synset': 'clarified_butter.n.01', 'name': 'clarified_butter'}, {'id': 13778, 'synset': 'ghee.n.01', 'name': 'ghee'}, {'id': 13779, 'synset': 'brown_butter.n.01', 'name': 'brown_butter'}, {'id': 13780, 'synset': 'meuniere_butter.n.01', 'name': 'Meuniere_butter'}, {'id': 13781, 'synset': 'blueberry_yogurt.n.01', 'name': 'blueberry_yogurt'}, {'id': 13782, 'synset': 'raita.n.01', 'name': 'raita'}, {'id': 13783, 'synset': 'whey.n.02', 'name': 'whey'}, {'id': 13784, 'synset': 'curd.n.02', 'name': 'curd'}, {'id': 13785, 'synset': 'curd.n.01', 'name': 'curd'}, {'id': 13786, 'synset': 'clabber.n.01', 'name': 'clabber'}, {'id': 13787, 'synset': 'cheese.n.01', 'name': 'cheese'}, {'id': 13788, 'synset': 'paring.n.02', 'name': 'paring'}, {'id': 13789, 'synset': 'cream_cheese.n.01', 'name': 'cream_cheese'}, {'id': 13790, 'synset': 'double_cream.n.01', 'name': 'double_cream'}, {'id': 13791, 'synset': 'mascarpone.n.01', 'name': 'mascarpone'}, {'id': 13792, 'synset': 'triple_cream.n.01', 'name': 'triple_cream'}, {'id': 13793, 'synset': 'cottage_cheese.n.01', 'name': 'cottage_cheese'}, {'id': 13794, 'synset': 'process_cheese.n.01', 'name': 'process_cheese'}, {'id': 13795, 'synset': 'bleu.n.01', 'name': 'bleu'}, {'id': 13796, 'synset': 'stilton.n.01', 'name': 'Stilton'}, {'id': 13797, 'synset': 'roquefort.n.01', 'name': 'Roquefort'}, {'id': 13798, 'synset': 'gorgonzola.n.01', 'name': 'gorgonzola'}, {'id': 13799, 'synset': 'danish_blue.n.01', 'name': 'Danish_blue'}, {'id': 13800, 'synset': 'bavarian_blue.n.01', 'name': 'Bavarian_blue'}, {'id': 13801, 'synset': 'brie.n.01', 'name': 'Brie'}, {'id': 13802, 'synset': 'brick_cheese.n.01', 'name': 'brick_cheese'}, {'id': 13803, 'synset': 'camembert.n.01', 'name': 'Camembert'}, {'id': 13804, 'synset': 'cheddar.n.02', 'name': 'cheddar'}, {'id': 13805, 'synset': 'rat_cheese.n.01', 'name': 'rat_cheese'}, {'id': 13806, 'synset': 'cheshire_cheese.n.01', 'name': 'Cheshire_cheese'}, {'id': 13807, 'synset': 'double_gloucester.n.01', 'name': 'double_Gloucester'}, {'id': 13808, 'synset': 'edam.n.01', 'name': 'Edam'}, {'id': 13809, 'synset': 'goat_cheese.n.01', 'name': 'goat_cheese'}, {'id': 13810, 'synset': 'gouda.n.01', 'name': 'Gouda'}, {'id': 13811, 'synset': 'grated_cheese.n.01', 'name': 'grated_cheese'}, {'id': 13812, 'synset': 'hand_cheese.n.01', 'name': 'hand_cheese'}, {'id': 13813, 'synset': 'liederkranz.n.01', 'name': 'Liederkranz'}, {'id': 13814, 'synset': 'limburger.n.01', 'name': 'Limburger'}, {'id': 13815, 'synset': 'mozzarella.n.01', 'name': 'mozzarella'}, {'id': 13816, 'synset': 'muenster.n.01', 'name': 'Muenster'}, {'id': 13817, 'synset': 'parmesan.n.01', 'name': 'Parmesan'}, {'id': 13818, 'synset': 'quark_cheese.n.01', 'name': 'quark_cheese'}, {'id': 13819, 'synset': 'ricotta.n.01', 'name': 'ricotta'}, {'id': 13820, 'synset': 'swiss_cheese.n.01', 'name': 'Swiss_cheese'}, {'id': 13821, 'synset': 'emmenthal.n.01', 'name': 'Emmenthal'}, {'id': 13822, 'synset': 'gruyere.n.01', 'name': 'Gruyere'}, {'id': 13823, 'synset': 'sapsago.n.01', 'name': 'sapsago'}, {'id': 13824, 'synset': 'velveeta.n.01', 'name': 'Velveeta'}, {'id': 13825, 'synset': 'nut_butter.n.01', 'name': 'nut_butter'}, {'id': 13826, 'synset': 'marshmallow_fluff.n.01', 'name': 'marshmallow_fluff'}, {'id': 13827, 'synset': 'onion_butter.n.01', 'name': 'onion_butter'}, {'id': 13828, 'synset': 'pimento_butter.n.01', 'name': 'pimento_butter'}, {'id': 13829, 'synset': 'shrimp_butter.n.01', 'name': 'shrimp_butter'}, {'id': 13830, 'synset': 'lobster_butter.n.01', 'name': 'lobster_butter'}, {'id': 13831, 'synset': 'yak_butter.n.01', 'name': 'yak_butter'}, {'id': 13832, 'synset': 'spread.n.05', 'name': 'spread'}, {'id': 13833, 'synset': 'cheese_spread.n.01', 'name': 'cheese_spread'}, {'id': 13834, 'synset': 'anchovy_butter.n.01', 'name': 'anchovy_butter'}, {'id': 13835, 'synset': 'fishpaste.n.01', 'name': 'fishpaste'}, {'id': 13836, 'synset': 'garlic_butter.n.01', 'name': 'garlic_butter'}, {'id': 13837, 'synset': 'miso.n.01', 'name': 'miso'}, {'id': 13838, 'synset': 'wasabi.n.02', 'name': 'wasabi'}, {'id': 13839, 'synset': 'snail_butter.n.01', 'name': 'snail_butter'}, {'id': 13840, 'synset': 'pate.n.01', 'name': 'pate'}, {'id': 13841, 'synset': 'duck_pate.n.01', 'name': 'duck_pate'}, {'id': 13842, 'synset': 'foie_gras.n.01', 'name': 'foie_gras'}, {'id': 13843, 'synset': 'tapenade.n.01', 'name': 'tapenade'}, {'id': 13844, 'synset': 'tahini.n.01', 'name': 'tahini'}, {'id': 13845, 'synset': 'sweetening.n.01', 'name': 'sweetening'}, {'id': 13846, 'synset': 'aspartame.n.01', 'name': 'aspartame'}, {'id': 13847, 'synset': 'saccharin.n.01', 'name': 'saccharin'}, {'id': 13848, 'synset': 'sugar.n.01', 'name': 'sugar'}, {'id': 13849, 'synset': 'syrup.n.01', 'name': 'syrup'}, {'id': 13850, 'synset': 'sugar_syrup.n.01', 'name': 'sugar_syrup'}, {'id': 13851, 'synset': 'molasses.n.01', 'name': 'molasses'}, {'id': 13852, 'synset': 'sorghum.n.03', 'name': 'sorghum'}, {'id': 13853, 'synset': 'treacle.n.01', 'name': 'treacle'}, {'id': 13854, 'synset': 'grenadine.n.01', 'name': 'grenadine'}, {'id': 13855, 'synset': 'maple_syrup.n.01', 'name': 'maple_syrup'}, {'id': 13856, 'synset': 'corn_syrup.n.01', 'name': 'corn_syrup'}, {'id': 13857, 'synset': 'miraculous_food.n.01', 'name': 'miraculous_food'}, {'id': 13858, 'synset': 'dough.n.01', 'name': 'dough'}, {'id': 13859, 'synset': 'bread_dough.n.01', 'name': 'bread_dough'}, {'id': 13860, 'synset': 'pancake_batter.n.01', 'name': 'pancake_batter'}, {'id': 13861, 'synset': 'fritter_batter.n.01', 'name': 'fritter_batter'}, {'id': 13862, 'synset': 'coq_au_vin.n.01', 'name': 'coq_au_vin'}, {'id': 13863, 'synset': 'chicken_provencale.n.01', 'name': 'chicken_provencale'}, {'id': 13864, 'synset': 'chicken_and_rice.n.01', 'name': 'chicken_and_rice'}, {'id': 13865, 'synset': 'moo_goo_gai_pan.n.01', 'name': 'moo_goo_gai_pan'}, {'id': 13866, 'synset': 'arroz_con_pollo.n.01', 'name': 'arroz_con_pollo'}, {'id': 13867, 'synset': 'bacon_and_eggs.n.02', 'name': 'bacon_and_eggs'}, {'id': 13868, 'synset': 'barbecued_spareribs.n.01', 'name': 'barbecued_spareribs'}, {'id': 13869, 'synset': 'beef_bourguignonne.n.01', 'name': 'beef_Bourguignonne'}, {'id': 13870, 'synset': 'beef_wellington.n.01', 'name': 'beef_Wellington'}, {'id': 13871, 'synset': 'bitok.n.01', 'name': 'bitok'}, {'id': 13872, 'synset': 'boiled_dinner.n.01', 'name': 'boiled_dinner'}, {'id': 13873, 'synset': 'boston_baked_beans.n.01', 'name': 'Boston_baked_beans'}, {'id': 13874, 'synset': 'bubble_and_squeak.n.01', 'name': 'bubble_and_squeak'}, {'id': 13875, 'synset': 'pasta.n.01', 'name': 'pasta'}, {'id': 13876, 'synset': 'cannelloni.n.01', 'name': 'cannelloni'}, {'id': 13877, 'synset': 'carbonnade_flamande.n.01', 'name': 'carbonnade_flamande'}, {'id': 13878, 'synset': 'cheese_souffle.n.01', 'name': 'cheese_souffle'}, {'id': 13879, 'synset': 'chicken_marengo.n.01', 'name': 'chicken_Marengo'}, {'id': 13880, 'synset': 'chicken_cordon_bleu.n.01', 'name': 'chicken_cordon_bleu'}, {'id': 13881, 'synset': 'maryland_chicken.n.01', 'name': 'Maryland_chicken'}, {'id': 13882, 'synset': 'chicken_paprika.n.01', 'name': 'chicken_paprika'}, {'id': 13883, 'synset': 'chicken_tetrazzini.n.01', 'name': 'chicken_Tetrazzini'}, {'id': 13884, 'synset': 'tetrazzini.n.01', 'name': 'Tetrazzini'}, {'id': 13885, 'synset': 'chicken_kiev.n.01', 'name': 'chicken_Kiev'}, {'id': 13886, 'synset': 'chili.n.01', 'name': 'chili'}, {'id': 13887, 'synset': 'chili_dog.n.01', 'name': 'chili_dog'}, {'id': 13888, 'synset': 'chop_suey.n.01', 'name': 'chop_suey'}, {'id': 13889, 'synset': 'chow_mein.n.01', 'name': 'chow_mein'}, {'id': 13890, 'synset': 'codfish_ball.n.01', 'name': 'codfish_ball'}, {'id': 13891, 'synset': 'coquille.n.01', 'name': 'coquille'}, {'id': 13892, 'synset': 'coquilles_saint-jacques.n.01', 'name': 'coquilles_Saint-Jacques'}, {'id': 13893, 'synset': 'croquette.n.01', 'name': 'croquette'}, {'id': 13894, 'synset': 'cottage_pie.n.01', 'name': 'cottage_pie'}, {'id': 13895, 'synset': 'rissole.n.01', 'name': 'rissole'}, {'id': 13896, 'synset': 'dolmas.n.01', 'name': 'dolmas'}, {'id': 13897, 'synset': 'egg_foo_yong.n.01', 'name': 'egg_foo_yong'}, {'id': 13898, 'synset': 'eggs_benedict.n.01', 'name': 'eggs_Benedict'}, {'id': 13899, 'synset': 'enchilada.n.01', 'name': 'enchilada'}, {'id': 13900, 'synset': 'falafel.n.01', 'name': 'falafel'}, {'id': 13901, 'synset': 'fish_and_chips.n.01', 'name': 'fish_and_chips'}, {'id': 13902, 'synset': 'fondue.n.02', 'name': 'fondue'}, {'id': 13903, 'synset': 'cheese_fondue.n.01', 'name': 'cheese_fondue'}, {'id': 13904, 'synset': 'chocolate_fondue.n.01', 'name': 'chocolate_fondue'}, {'id': 13905, 'synset': 'fondue.n.01', 'name': 'fondue'}, {'id': 13906, 'synset': 'beef_fondue.n.01', 'name': 'beef_fondue'}, {'id': 13907, 'synset': 'fried_rice.n.01', 'name': 'fried_rice'}, {'id': 13908, 'synset': 'frittata.n.01', 'name': 'frittata'}, {'id': 13909, 'synset': 'frog_legs.n.01', 'name': 'frog_legs'}, {'id': 13910, 'synset': 'galantine.n.01', 'name': 'galantine'}, {'id': 13911, 'synset': 'gefilte_fish.n.01', 'name': 'gefilte_fish'}, {'id': 13912, 'synset': 'haggis.n.01', 'name': 'haggis'}, {'id': 13913, 'synset': 'ham_and_eggs.n.01', 'name': 'ham_and_eggs'}, {'id': 13914, 'synset': 'hash.n.01', 'name': 'hash'}, {'id': 13915, 'synset': 'corned_beef_hash.n.01', 'name': 'corned_beef_hash'}, {'id': 13916, 'synset': 'jambalaya.n.01', 'name': 'jambalaya'}, {'id': 13917, 'synset': 'kabob.n.01', 'name': 'kabob'}, {'id': 13918, 'synset': 'kedgeree.n.01', 'name': 'kedgeree'}, {'id': 13919, 'synset': 'souvlaki.n.01', 'name': 'souvlaki'}, {'id': 13920, 'synset': 'seafood_newburg.n.01', 'name': 'seafood_Newburg'}, {'id': 13921, 'synset': 'lobster_newburg.n.01', 'name': 'lobster_Newburg'}, {'id': 13922, 'synset': 'shrimp_newburg.n.01', 'name': 'shrimp_Newburg'}, {'id': 13923, 'synset': 'newburg_sauce.n.01', 'name': 'Newburg_sauce'}, {'id': 13924, 'synset': 'lobster_thermidor.n.01', 'name': 'lobster_thermidor'}, {'id': 13925, 'synset': 'lutefisk.n.01', 'name': 'lutefisk'}, {'id': 13926, 'synset': 'macaroni_and_cheese.n.01', 'name': 'macaroni_and_cheese'}, {'id': 13927, 'synset': 'macedoine.n.01', 'name': 'macedoine'}, {'id': 13928, 'synset': 'porcupine_ball.n.01', 'name': 'porcupine_ball'}, {'id': 13929, 'synset': 'swedish_meatball.n.01', 'name': 'Swedish_meatball'}, {'id': 13930, 'synset': 'meat_loaf.n.01', 'name': 'meat_loaf'}, {'id': 13931, 'synset': 'moussaka.n.01', 'name': 'moussaka'}, {'id': 13932, 'synset': 'osso_buco.n.01', 'name': 'osso_buco'}, {'id': 13933, 'synset': 'marrow.n.03', 'name': 'marrow'}, {'id': 13934, 'synset': 'pheasant_under_glass.n.01', 'name': 'pheasant_under_glass'}, {'id': 13935, 'synset': 'pigs_in_blankets.n.01', 'name': 'pigs_in_blankets'}, {'id': 13936, 'synset': 'pilaf.n.01', 'name': 'pilaf'}, {'id': 13937, 'synset': 'bulgur_pilaf.n.01', 'name': 'bulgur_pilaf'}, {'id': 13938, 'synset': 'sausage_pizza.n.01', 'name': 'sausage_pizza'}, {'id': 13939, 'synset': 'pepperoni_pizza.n.01', 'name': 'pepperoni_pizza'}, {'id': 13940, 'synset': 'cheese_pizza.n.01', 'name': 'cheese_pizza'}, {'id': 13941, 'synset': 'anchovy_pizza.n.01', 'name': 'anchovy_pizza'}, {'id': 13942, 'synset': 'sicilian_pizza.n.01', 'name': 'Sicilian_pizza'}, {'id': 13943, 'synset': 'poi.n.01', 'name': 'poi'}, {'id': 13944, 'synset': 'pork_and_beans.n.01', 'name': 'pork_and_beans'}, {'id': 13945, 'synset': 'porridge.n.01', 'name': 'porridge'}, {'id': 13946, 'synset': 'oatmeal.n.01', 'name': 'oatmeal'}, {'id': 13947, 'synset': 'loblolly.n.01', 'name': 'loblolly'}, {'id': 13948, 'synset': 'potpie.n.01', 'name': 'potpie'}, {'id': 13949, 'synset': 'rijsttaffel.n.01', 'name': 'rijsttaffel'}, {'id': 13950, 'synset': 'risotto.n.01', 'name': 'risotto'}, {'id': 13951, 'synset': 'roulade.n.01', 'name': 'roulade'}, {'id': 13952, 'synset': 'fish_loaf.n.01', 'name': 'fish_loaf'}, {'id': 13953, 'synset': 'salmon_loaf.n.01', 'name': 'salmon_loaf'}, {'id': 13954, 'synset': 'salisbury_steak.n.01', 'name': 'Salisbury_steak'}, {'id': 13955, 'synset': 'sauerbraten.n.01', 'name': 'sauerbraten'}, {'id': 13956, 'synset': 'sauerkraut.n.01', 'name': 'sauerkraut'}, {'id': 13957, 'synset': 'scallopine.n.01', 'name': 'scallopine'}, {'id': 13958, 'synset': 'veal_scallopini.n.01', 'name': 'veal_scallopini'}, {'id': 13959, 'synset': 'scampi.n.01', 'name': 'scampi'}, {'id': 13960, 'synset': 'scotch_egg.n.01', 'name': 'Scotch_egg'}, {'id': 13961, 'synset': 'scotch_woodcock.n.01', 'name': 'Scotch_woodcock'}, {'id': 13962, 'synset': 'scrapple.n.01', 'name': 'scrapple'}, {'id': 13963, 'synset': 'spaghetti_and_meatballs.n.01', 'name': 'spaghetti_and_meatballs'}, {'id': 13964, 'synset': 'spanish_rice.n.01', 'name': 'Spanish_rice'}, {'id': 13965, 'synset': 'steak_tartare.n.01', 'name': 'steak_tartare'}, {'id': 13966, 'synset': 'pepper_steak.n.02', 'name': 'pepper_steak'}, {'id': 13967, 'synset': 'steak_au_poivre.n.01', 'name': 'steak_au_poivre'}, {'id': 13968, 'synset': 'beef_stroganoff.n.01', 'name': 'beef_Stroganoff'}, {'id': 13969, 'synset': 'stuffed_cabbage.n.01', 'name': 'stuffed_cabbage'}, {'id': 13970, 'synset': 'kishke.n.01', 'name': 'kishke'}, {'id': 13971, 'synset': 'stuffed_peppers.n.01', 'name': 'stuffed_peppers'}, {'id': 13972, 'synset': 'stuffed_tomato.n.02', 'name': 'stuffed_tomato'}, {'id': 13973, 'synset': 'stuffed_tomato.n.01', 'name': 'stuffed_tomato'}, {'id': 13974, 'synset': 'succotash.n.01', 'name': 'succotash'}, {'id': 13975, 'synset': 'sukiyaki.n.01', 'name': 'sukiyaki'}, {'id': 13976, 'synset': 'sashimi.n.01', 'name': 'sashimi'}, {'id': 13977, 'synset': 'swiss_steak.n.01', 'name': 'Swiss_steak'}, {'id': 13978, 'synset': 'tamale.n.02', 'name': 'tamale'}, {'id': 13979, 'synset': 'tamale_pie.n.01', 'name': 'tamale_pie'}, {'id': 13980, 'synset': 'tempura.n.01', 'name': 'tempura'}, {'id': 13981, 'synset': 'teriyaki.n.01', 'name': 'teriyaki'}, {'id': 13982, 'synset': 'terrine.n.01', 'name': 'terrine'}, {'id': 13983, 'synset': 'welsh_rarebit.n.01', 'name': 'Welsh_rarebit'}, {'id': 13984, 'synset': 'schnitzel.n.01', 'name': 'schnitzel'}, {'id': 13985, 'synset': 'chicken_taco.n.01', 'name': 'chicken_taco'}, {'id': 13986, 'synset': 'beef_burrito.n.01', 'name': 'beef_burrito'}, {'id': 13987, 'synset': 'tostada.n.01', 'name': 'tostada'}, {'id': 13988, 'synset': 'bean_tostada.n.01', 'name': 'bean_tostada'}, {'id': 13989, 'synset': 'refried_beans.n.01', 'name': 'refried_beans'}, {'id': 13990, 'synset': 'beverage.n.01', 'name': 'beverage'}, {'id': 13991, 'synset': 'wish-wash.n.01', 'name': 'wish-wash'}, {'id': 13992, 'synset': 'concoction.n.01', 'name': 'concoction'}, {'id': 13993, 'synset': 'mix.n.01', 'name': 'mix'}, {'id': 13994, 'synset': 'filling.n.03', 'name': 'filling'}, {'id': 13995, 'synset': 'lekvar.n.01', 'name': 'lekvar'}, {'id': 13996, 'synset': 'potion.n.01', 'name': 'potion'}, {'id': 13997, 'synset': 'elixir.n.03', 'name': 'elixir'}, {'id': 13998, 'synset': 'elixir_of_life.n.01', 'name': 'elixir_of_life'}, {'id': 13999, 'synset': 'philter.n.01', 'name': 'philter'}, {'id': 14000, 'synset': 'proof_spirit.n.01', 'name': 'proof_spirit'}, {'id': 14001, 'synset': 'home_brew.n.01', 'name': 'home_brew'}, {'id': 14002, 'synset': 'hooch.n.01', 'name': 'hooch'}, {'id': 14003, 'synset': 'kava.n.01', 'name': 'kava'}, {'id': 14004, 'synset': 'aperitif.n.01', 'name': 'aperitif'}, {'id': 14005, 'synset': 'brew.n.01', 'name': 'brew'}, {'id': 14006, 'synset': 'beer.n.01', 'name': 'beer'}, {'id': 14007, 'synset': 'draft_beer.n.01', 'name': 'draft_beer'}, {'id': 14008, 'synset': 'suds.n.02', 'name': 'suds'}, {'id': 14009, 'synset': 'munich_beer.n.01', 'name': 'Munich_beer'}, {'id': 14010, 'synset': 'bock.n.01', 'name': 'bock'}, {'id': 14011, 'synset': 'lager.n.02', 'name': 'lager'}, {'id': 14012, 'synset': 'light_beer.n.01', 'name': 'light_beer'}, {'id': 14013, 'synset': 'oktoberfest.n.01', 'name': 'Oktoberfest'}, {'id': 14014, 'synset': 'pilsner.n.01', 'name': 'Pilsner'}, {'id': 14015, 'synset': 'shebeen.n.01', 'name': 'shebeen'}, {'id': 14016, 'synset': 'weissbier.n.01', 'name': 'Weissbier'}, {'id': 14017, 'synset': 'weizenbock.n.01', 'name': 'Weizenbock'}, {'id': 14018, 'synset': 'malt.n.03', 'name': 'malt'}, {'id': 14019, 'synset': 'wort.n.02', 'name': 'wort'}, {'id': 14020, 'synset': 'malt.n.02', 'name': 'malt'}, {'id': 14021, 'synset': 'ale.n.01', 'name': 'ale'}, {'id': 14022, 'synset': 'bitter.n.01', 'name': 'bitter'}, {'id': 14023, 'synset': 'burton.n.03', 'name': 'Burton'}, {'id': 14024, 'synset': 'pale_ale.n.01', 'name': 'pale_ale'}, {'id': 14025, 'synset': 'porter.n.07', 'name': 'porter'}, {'id': 14026, 'synset': 'stout.n.01', 'name': 'stout'}, {'id': 14027, 'synset': 'guinness.n.02', 'name': 'Guinness'}, {'id': 14028, 'synset': 'kvass.n.01', 'name': 'kvass'}, {'id': 14029, 'synset': 'mead.n.03', 'name': 'mead'}, {'id': 14030, 'synset': 'metheglin.n.01', 'name': 'metheglin'}, {'id': 14031, 'synset': 'hydromel.n.01', 'name': 'hydromel'}, {'id': 14032, 'synset': 'oenomel.n.01', 'name': 'oenomel'}, {'id': 14033, 'synset': 'near_beer.n.01', 'name': 'near_beer'}, {'id': 14034, 'synset': 'ginger_beer.n.01', 'name': 'ginger_beer'}, {'id': 14035, 'synset': 'sake.n.02', 'name': 'sake'}, {'id': 14036, 'synset': 'wine.n.01', 'name': 'wine'}, {'id': 14037, 'synset': 'vintage.n.01', 'name': 'vintage'}, {'id': 14038, 'synset': 'red_wine.n.01', 'name': 'red_wine'}, {'id': 14039, 'synset': 'white_wine.n.01', 'name': 'white_wine'}, {'id': 14040, 'synset': 'blush_wine.n.01', 'name': 'blush_wine'}, {'id': 14041, 'synset': 'altar_wine.n.01', 'name': 'altar_wine'}, {'id': 14042, 'synset': 'sparkling_wine.n.01', 'name': 'sparkling_wine'}, {'id': 14043, 'synset': 'champagne.n.01', 'name': 'champagne'}, {'id': 14044, 'synset': 'cold_duck.n.01', 'name': 'cold_duck'}, {'id': 14045, 'synset': 'burgundy.n.02', 'name': 'Burgundy'}, {'id': 14046, 'synset': 'beaujolais.n.01', 'name': 'Beaujolais'}, {'id': 14047, 'synset': 'medoc.n.01', 'name': 'Medoc'}, {'id': 14048, 'synset': 'canary_wine.n.01', 'name': 'Canary_wine'}, {'id': 14049, 'synset': 'chablis.n.02', 'name': 'Chablis'}, {'id': 14050, 'synset': 'montrachet.n.01', 'name': 'Montrachet'}, {'id': 14051, 'synset': 'chardonnay.n.02', 'name': 'Chardonnay'}, {'id': 14052, 'synset': 'pinot_noir.n.02', 'name': 'Pinot_noir'}, {'id': 14053, 'synset': 'pinot_blanc.n.02', 'name': 'Pinot_blanc'}, {'id': 14054, 'synset': 'bordeaux.n.02', 'name': 'Bordeaux'}, {'id': 14055, 'synset': 'claret.n.02', 'name': 'claret'}, {'id': 14056, 'synset': 'chianti.n.01', 'name': 'Chianti'}, {'id': 14057, 'synset': 'cabernet.n.01', 'name': 'Cabernet'}, {'id': 14058, 'synset': 'merlot.n.02', 'name': 'Merlot'}, {'id': 14059, 'synset': 'sauvignon_blanc.n.02', 'name': 'Sauvignon_blanc'}, {'id': 14060, 'synset': 'california_wine.n.01', 'name': 'California_wine'}, {'id': 14061, 'synset': 'cotes_de_provence.n.01', 'name': 'Cotes_de_Provence'}, {'id': 14062, 'synset': 'dessert_wine.n.01', 'name': 'dessert_wine'}, {'id': 14063, 'synset': 'dubonnet.n.01', 'name': 'Dubonnet'}, {'id': 14064, 'synset': 'jug_wine.n.01', 'name': 'jug_wine'}, {'id': 14065, 'synset': 'macon.n.02', 'name': 'macon'}, {'id': 14066, 'synset': 'moselle.n.01', 'name': 'Moselle'}, {'id': 14067, 'synset': 'muscadet.n.02', 'name': 'Muscadet'}, {'id': 14068, 'synset': 'plonk.n.01', 'name': 'plonk'}, {'id': 14069, 'synset': 'retsina.n.01', 'name': 'retsina'}, {'id': 14070, 'synset': 'rhine_wine.n.01', 'name': 'Rhine_wine'}, {'id': 14071, 'synset': 'riesling.n.02', 'name': 'Riesling'}, {'id': 14072, 'synset': 'liebfraumilch.n.01', 'name': 'liebfraumilch'}, {'id': 14073, 'synset': 'rhone_wine.n.01', 'name': 'Rhone_wine'}, {'id': 14074, 'synset': 'rioja.n.01', 'name': 'Rioja'}, {'id': 14075, 'synset': 'sack.n.04', 'name': 'sack'}, {'id': 14076, 'synset': 'saint_emilion.n.01', 'name': 'Saint_Emilion'}, {'id': 14077, 'synset': 'soave.n.01', 'name': 'Soave'}, {'id': 14078, 'synset': 'zinfandel.n.02', 'name': 'zinfandel'}, {'id': 14079, 'synset': 'sauterne.n.01', 'name': 'Sauterne'}, {'id': 14080, 'synset': 'straw_wine.n.01', 'name': 'straw_wine'}, {'id': 14081, 'synset': 'table_wine.n.01', 'name': 'table_wine'}, {'id': 14082, 'synset': 'tokay.n.01', 'name': 'Tokay'}, {'id': 14083, 'synset': 'vin_ordinaire.n.01', 'name': 'vin_ordinaire'}, {'id': 14084, 'synset': 'vermouth.n.01', 'name': 'vermouth'}, {'id': 14085, 'synset': 'sweet_vermouth.n.01', 'name': 'sweet_vermouth'}, {'id': 14086, 'synset': 'dry_vermouth.n.01', 'name': 'dry_vermouth'}, {'id': 14087, 'synset': 'chenin_blanc.n.02', 'name': 'Chenin_blanc'}, {'id': 14088, 'synset': 'verdicchio.n.02', 'name': 'Verdicchio'}, {'id': 14089, 'synset': 'vouvray.n.01', 'name': 'Vouvray'}, {'id': 14090, 'synset': 'yquem.n.01', 'name': 'Yquem'}, {'id': 14091, 'synset': 'generic.n.01', 'name': 'generic'}, {'id': 14092, 'synset': 'varietal.n.01', 'name': 'varietal'}, {'id': 14093, 'synset': 'fortified_wine.n.01', 'name': 'fortified_wine'}, {'id': 14094, 'synset': 'madeira.n.03', 'name': 'Madeira'}, {'id': 14095, 'synset': 'malmsey.n.01', 'name': 'malmsey'}, {'id': 14096, 'synset': 'port.n.02', 'name': 'port'}, {'id': 14097, 'synset': 'sherry.n.01', 'name': 'sherry'}, {'id': 14098, 'synset': 'marsala.n.01', 'name': 'Marsala'}, {'id': 14099, 'synset': 'muscat.n.03', 'name': 'muscat'}, {'id': 14100, 'synset': 'neutral_spirits.n.01', 'name': 'neutral_spirits'}, {'id': 14101, 'synset': 'aqua_vitae.n.01', 'name': 'aqua_vitae'}, {'id': 14102, 'synset': 'eau_de_vie.n.01', 'name': 'eau_de_vie'}, {'id': 14103, 'synset': 'moonshine.n.02', 'name': 'moonshine'}, {'id': 14104, 'synset': 'bathtub_gin.n.01', 'name': 'bathtub_gin'}, {'id': 14105, 'synset': 'aquavit.n.01', 'name': 'aquavit'}, {'id': 14106, 'synset': 'arrack.n.01', 'name': 'arrack'}, {'id': 14107, 'synset': 'bitters.n.01', 'name': 'bitters'}, {'id': 14108, 'synset': 'brandy.n.01', 'name': 'brandy'}, {'id': 14109, 'synset': 'applejack.n.01', 'name': 'applejack'}, {'id': 14110, 'synset': 'calvados.n.01', 'name': 'Calvados'}, {'id': 14111, 'synset': 'armagnac.n.01', 'name': 'Armagnac'}, {'id': 14112, 'synset': 'cognac.n.01', 'name': 'Cognac'}, {'id': 14113, 'synset': 'grappa.n.01', 'name': 'grappa'}, {'id': 14114, 'synset': 'kirsch.n.01', 'name': 'kirsch'}, {'id': 14115, 'synset': 'slivovitz.n.01', 'name': 'slivovitz'}, {'id': 14116, 'synset': 'gin.n.01', 'name': 'gin'}, {'id': 14117, 'synset': 'sloe_gin.n.01', 'name': 'sloe_gin'}, {'id': 14118, 'synset': 'geneva.n.02', 'name': 'geneva'}, {'id': 14119, 'synset': 'grog.n.01', 'name': 'grog'}, {'id': 14120, 'synset': 'ouzo.n.01', 'name': 'ouzo'}, {'id': 14121, 'synset': 'rum.n.01', 'name': 'rum'}, {'id': 14122, 'synset': 'demerara.n.04', 'name': 'demerara'}, {'id': 14123, 'synset': 'jamaica_rum.n.01', 'name': 'Jamaica_rum'}, {'id': 14124, 'synset': 'schnapps.n.01', 'name': 'schnapps'}, {'id': 14125, 'synset': 'pulque.n.01', 'name': 'pulque'}, {'id': 14126, 'synset': 'mescal.n.02', 'name': 'mescal'}, {'id': 14127, 'synset': 'whiskey.n.01', 'name': 'whiskey'}, {'id': 14128, 'synset': 'blended_whiskey.n.01', 'name': 'blended_whiskey'}, {'id': 14129, 'synset': 'bourbon.n.02', 'name': 'bourbon'}, {'id': 14130, 'synset': 'corn_whiskey.n.01', 'name': 'corn_whiskey'}, {'id': 14131, 'synset': 'firewater.n.01', 'name': 'firewater'}, {'id': 14132, 'synset': 'irish.n.02', 'name': 'Irish'}, {'id': 14133, 'synset': 'poteen.n.01', 'name': 'poteen'}, {'id': 14134, 'synset': 'rye.n.03', 'name': 'rye'}, {'id': 14135, 'synset': 'scotch.n.02', 'name': 'Scotch'}, {'id': 14136, 'synset': 'sour_mash.n.02', 'name': 'sour_mash'}, {'id': 14137, 'synset': 'liqueur.n.01', 'name': 'liqueur'}, {'id': 14138, 'synset': 'absinth.n.01', 'name': 'absinth'}, {'id': 14139, 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{'id': 14154, 'synset': 'maraschino.n.01', 'name': 'maraschino'}, {'id': 14155, 'synset': 'pastis.n.01', 'name': 'pastis'}, {'id': 14156, 'synset': 'pernod.n.01', 'name': 'Pernod'}, {'id': 14157, 'synset': 'pousse-cafe.n.01', 'name': 'pousse-cafe'}, {'id': 14158, 'synset': 'kahlua.n.01', 'name': 'Kahlua'}, {'id': 14159, 'synset': 'ratafia.n.01', 'name': 'ratafia'}, {'id': 14160, 'synset': 'sambuca.n.01', 'name': 'sambuca'}, {'id': 14161, 'synset': 'mixed_drink.n.01', 'name': 'mixed_drink'}, {'id': 14162, 'synset': 'cocktail.n.01', 'name': 'cocktail'}, {'id': 14163, 'synset': 'dom_pedro.n.01', 'name': 'Dom_Pedro'}, {'id': 14164, 'synset': 'highball.n.01', 'name': 'highball'}, {'id': 14165, 'synset': 'mixer.n.02', 'name': 'mixer'}, {'id': 14166, 'synset': 'bishop.n.02', 'name': 'bishop'}, {'id': 14167, 'synset': 'bloody_mary.n.02', 'name': 'Bloody_Mary'}, {'id': 14168, 'synset': 'virgin_mary.n.02', 'name': 'Virgin_Mary'}, {'id': 14169, 'synset': 'bullshot.n.01', 'name': 'bullshot'}, {'id': 14170, 'synset': 'cobbler.n.02', 'name': 'cobbler'}, {'id': 14171, 'synset': 'collins.n.02', 'name': 'collins'}, {'id': 14172, 'synset': 'cooler.n.02', 'name': 'cooler'}, {'id': 14173, 'synset': 'refresher.n.02', 'name': 'refresher'}, {'id': 14174, 'synset': 'daiquiri.n.01', 'name': 'daiquiri'}, {'id': 14175, 'synset': 'strawberry_daiquiri.n.01', 'name': 'strawberry_daiquiri'}, {'id': 14176, 'synset': 'nada_daiquiri.n.01', 'name': 'NADA_daiquiri'}, {'id': 14177, 'synset': 'spritzer.n.01', 'name': 'spritzer'}, {'id': 14178, 'synset': 'flip.n.02', 'name': 'flip'}, {'id': 14179, 'synset': 'gimlet.n.01', 'name': 'gimlet'}, {'id': 14180, 'synset': 'gin_and_tonic.n.01', 'name': 'gin_and_tonic'}, {'id': 14181, 'synset': 'grasshopper.n.02', 'name': 'grasshopper'}, {'id': 14182, 'synset': 'harvey_wallbanger.n.01', 'name': 'Harvey_Wallbanger'}, {'id': 14183, 'synset': 'julep.n.01', 'name': 'julep'}, {'id': 14184, 'synset': 'manhattan.n.02', 'name': 'manhattan'}, {'id': 14185, 'synset': 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{'id': 14216, 'synset': 'mocha.n.02', 'name': 'mocha'}, {'id': 14217, 'synset': 'cassareep.n.01', 'name': 'cassareep'}, {'id': 14218, 'synset': 'turkish_coffee.n.01', 'name': 'Turkish_coffee'}, {'id': 14219, 'synset': 'hard_cider.n.01', 'name': 'hard_cider'}, {'id': 14220, 'synset': 'scrumpy.n.01', 'name': 'scrumpy'}, {'id': 14221, 'synset': 'sweet_cider.n.01', 'name': 'sweet_cider'}, {'id': 14222, 'synset': 'mulled_cider.n.01', 'name': 'mulled_cider'}, {'id': 14223, 'synset': 'perry.n.04', 'name': 'perry'}, {'id': 14224, 'synset': 'rotgut.n.01', 'name': 'rotgut'}, {'id': 14225, 'synset': 'slug.n.05', 'name': 'slug'}, {'id': 14226, 'synset': 'criollo.n.02', 'name': 'criollo'}, {'id': 14227, 'synset': 'juice.n.01', 'name': 'juice'}, {'id': 14228, 'synset': 'nectar.n.02', 'name': 'nectar'}, {'id': 14229, 'synset': 'apple_juice.n.01', 'name': 'apple_juice'}, {'id': 14230, 'synset': 'cranberry_juice.n.01', 'name': 'cranberry_juice'}, {'id': 14231, 'synset': 'grape_juice.n.01', 'name': 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{'id': 14262, 'synset': 'tonic.n.01', 'name': 'tonic'}, {'id': 14263, 'synset': 'coffee_bean.n.01', 'name': 'coffee_bean'}, {'id': 14264, 'synset': 'coffee.n.01', 'name': 'coffee'}, {'id': 14265, 'synset': 'cafe_royale.n.01', 'name': 'cafe_royale'}, {'id': 14266, 'synset': 'fruit_punch.n.01', 'name': 'fruit_punch'}, {'id': 14267, 'synset': 'milk_punch.n.01', 'name': 'milk_punch'}, {'id': 14268, 'synset': 'mimosa.n.03', 'name': 'mimosa'}, {'id': 14269, 'synset': 'pina_colada.n.01', 'name': 'pina_colada'}, {'id': 14270, 'synset': 'punch.n.02', 'name': 'punch'}, {'id': 14271, 'synset': 'cup.n.06', 'name': 'cup'}, {'id': 14272, 'synset': 'champagne_cup.n.01', 'name': 'champagne_cup'}, {'id': 14273, 'synset': 'claret_cup.n.01', 'name': 'claret_cup'}, {'id': 14274, 'synset': 'wassail.n.01', 'name': 'wassail'}, {'id': 14275, 'synset': "planter's_punch.n.01", 'name': "planter's_punch"}, {'id': 14276, 'synset': 'white_russian.n.02', 'name': 'White_Russian'}, {'id': 14277, 'synset': 'fish_house_punch.n.01', 'name': 'fish_house_punch'}, {'id': 14278, 'synset': 'may_wine.n.01', 'name': 'May_wine'}, {'id': 14279, 'synset': 'eggnog.n.01', 'name': 'eggnog'}, {'id': 14280, 'synset': 'cassiri.n.01', 'name': 'cassiri'}, {'id': 14281, 'synset': 'spruce_beer.n.01', 'name': 'spruce_beer'}, {'id': 14282, 'synset': 'rickey.n.01', 'name': 'rickey'}, {'id': 14283, 'synset': 'gin_rickey.n.01', 'name': 'gin_rickey'}, {'id': 14284, 'synset': 'tea.n.05', 'name': 'tea'}, {'id': 14285, 'synset': 'tea.n.01', 'name': 'tea'}, {'id': 14286, 'synset': 'tea-like_drink.n.01', 'name': 'tea-like_drink'}, {'id': 14287, 'synset': 'cambric_tea.n.01', 'name': 'cambric_tea'}, {'id': 14288, 'synset': 'cuppa.n.01', 'name': 'cuppa'}, {'id': 14289, 'synset': 'herb_tea.n.01', 'name': 'herb_tea'}, {'id': 14290, 'synset': 'tisane.n.01', 'name': 'tisane'}, {'id': 14291, 'synset': 'camomile_tea.n.01', 'name': 'camomile_tea'}, {'id': 14292, 'synset': 'ice_tea.n.01', 'name': 'ice_tea'}, {'id': 14293, 'synset': 'sun_tea.n.01', 'name': 'sun_tea'}, {'id': 14294, 'synset': 'black_tea.n.01', 'name': 'black_tea'}, {'id': 14295, 'synset': 'congou.n.01', 'name': 'congou'}, {'id': 14296, 'synset': 'darjeeling.n.01', 'name': 'Darjeeling'}, {'id': 14297, 'synset': 'orange_pekoe.n.01', 'name': 'orange_pekoe'}, {'id': 14298, 'synset': 'souchong.n.01', 'name': 'souchong'}, {'id': 14299, 'synset': 'green_tea.n.01', 'name': 'green_tea'}, {'id': 14300, 'synset': 'hyson.n.01', 'name': 'hyson'}, {'id': 14301, 'synset': 'oolong.n.01', 'name': 'oolong'}, {'id': 14302, 'synset': 'water.n.06', 'name': 'water'}, {'id': 14303, 'synset': 'bottled_water.n.01', 'name': 'bottled_water'}, {'id': 14304, 'synset': 'branch_water.n.01', 'name': 'branch_water'}, {'id': 14305, 'synset': 'spring_water.n.02', 'name': 'spring_water'}, {'id': 14306, 'synset': 'sugar_water.n.01', 'name': 'sugar_water'}, {'id': 14307, 'synset': 'drinking_water.n.01', 'name': 'drinking_water'}, {'id': 14308, 'synset': 'ice_water.n.01', 'name': 'ice_water'}, {'id': 14309, 'synset': 'soda_water.n.01', 'name': 'soda_water'}, {'id': 14310, 'synset': 'mineral_water.n.01', 'name': 'mineral_water'}, {'id': 14311, 'synset': 'seltzer.n.01', 'name': 'seltzer'}, {'id': 14312, 'synset': 'vichy_water.n.01', 'name': 'Vichy_water'}, {'id': 14313, 'synset': 'perishable.n.01', 'name': 'perishable'}, {'id': 14314, 'synset': 'couscous.n.01', 'name': 'couscous'}, {'id': 14315, 'synset': 'ramekin.n.01', 'name': 'ramekin'}, {'id': 14316, 'synset': 'multivitamin.n.01', 'name': 'multivitamin'}, {'id': 14317, 'synset': 'vitamin_pill.n.01', 'name': 'vitamin_pill'}, {'id': 14318, 'synset': 'soul_food.n.01', 'name': 'soul_food'}, {'id': 14319, 'synset': 'mold.n.06', 'name': 'mold'}, {'id': 14320, 'synset': 'people.n.01', 'name': 'people'}, {'id': 14321, 'synset': 'collection.n.01', 'name': 'collection'}, {'id': 14322, 'synset': 'book.n.07', 'name': 'book'}, {'id': 14323, 'synset': 'library.n.02', 'name': 'library'}, {'id': 14324, 'synset': 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'synset': 'benthos.n.01', 'name': 'benthos'}, {'id': 14371, 'synset': 'goldfield.n.01', 'name': 'goldfield'}, {'id': 14372, 'synset': 'grainfield.n.01', 'name': 'grainfield'}, {'id': 14373, 'synset': 'half-mast.n.01', 'name': 'half-mast'}, {'id': 14374, 'synset': 'hemline.n.01', 'name': 'hemline'}, {'id': 14375, 'synset': 'heronry.n.01', 'name': 'heronry'}, {'id': 14376, 'synset': 'hipline.n.02', 'name': 'hipline'}, {'id': 14377, 'synset': 'hipline.n.01', 'name': 'hipline'}, {'id': 14378, 'synset': 'hole-in-the-wall.n.01', 'name': 'hole-in-the-wall'}, {'id': 14379, 'synset': 'junkyard.n.01', 'name': 'junkyard'}, {'id': 14380, 'synset': 'isoclinic_line.n.01', 'name': 'isoclinic_line'}, {'id': 14381, 'synset': 'littoral.n.01', 'name': 'littoral'}, {'id': 14382, 'synset': 'magnetic_pole.n.01', 'name': 'magnetic_pole'}, {'id': 14383, 'synset': 'grassland.n.01', 'name': 'grassland'}, {'id': 14384, 'synset': 'mecca.n.02', 'name': 'mecca'}, {'id': 14385, 'synset': "observer's_meridian.n.01", 'name': "observer's_meridian"}, {'id': 14386, 'synset': 'prime_meridian.n.01', 'name': 'prime_meridian'}, {'id': 14387, 'synset': 'nombril.n.01', 'name': 'nombril'}, {'id': 14388, 'synset': 'no-parking_zone.n.01', 'name': 'no-parking_zone'}, {'id': 14389, 'synset': 'outdoors.n.01', 'name': 'outdoors'}, {'id': 14390, 'synset': 'fairground.n.01', 'name': 'fairground'}, {'id': 14391, 'synset': 'pasture.n.01', 'name': 'pasture'}, {'id': 14392, 'synset': 'perihelion.n.01', 'name': 'perihelion'}, {'id': 14393, 'synset': 'periselene.n.01', 'name': 'periselene'}, {'id': 14394, 'synset': 'locus_of_infection.n.01', 'name': 'locus_of_infection'}, {'id': 14395, 'synset': 'kasbah.n.01', 'name': 'kasbah'}, {'id': 14396, 'synset': 'waterfront.n.01', 'name': 'waterfront'}, {'id': 14397, 'synset': 'resort.n.01', 'name': 'resort'}, {'id': 14398, 'synset': 'resort_area.n.01', 'name': 'resort_area'}, {'id': 14399, 'synset': 'rough.n.01', 'name': 'rough'}, {'id': 14400, 'synset': 'ashram.n.02', 'name': 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'aegean_island.n.01', 'name': 'Aegean_island'}, {'id': 14432, 'synset': 'sultanate.n.01', 'name': 'sultanate'}, {'id': 14433, 'synset': 'swiss_canton.n.01', 'name': 'Swiss_canton'}, {'id': 14434, 'synset': 'abyssal_zone.n.01', 'name': 'abyssal_zone'}, {'id': 14435, 'synset': 'aerie.n.01', 'name': 'aerie'}, {'id': 14436, 'synset': 'air_bubble.n.01', 'name': 'air_bubble'}, {'id': 14437, 'synset': 'alluvial_flat.n.01', 'name': 'alluvial_flat'}, {'id': 14438, 'synset': 'alp.n.01', 'name': 'alp'}, {'id': 14439, 'synset': 'alpine_glacier.n.01', 'name': 'Alpine_glacier'}, {'id': 14440, 'synset': 'anthill.n.01', 'name': 'anthill'}, {'id': 14441, 'synset': 'aquifer.n.01', 'name': 'aquifer'}, {'id': 14442, 'synset': 'archipelago.n.01', 'name': 'archipelago'}, {'id': 14443, 'synset': 'arete.n.01', 'name': 'arete'}, {'id': 14444, 'synset': 'arroyo.n.01', 'name': 'arroyo'}, {'id': 14445, 'synset': 'ascent.n.01', 'name': 'ascent'}, {'id': 14446, 'synset': 'asterism.n.02', 'name': 'asterism'}, {'id': 14447, 'synset': 'asthenosphere.n.01', 'name': 'asthenosphere'}, {'id': 14448, 'synset': 'atoll.n.01', 'name': 'atoll'}, {'id': 14449, 'synset': 'bank.n.03', 'name': 'bank'}, {'id': 14450, 'synset': 'bank.n.01', 'name': 'bank'}, {'id': 14451, 'synset': 'bar.n.08', 'name': 'bar'}, {'id': 14452, 'synset': 'barbecue_pit.n.01', 'name': 'barbecue_pit'}, {'id': 14453, 'synset': 'barrier_reef.n.01', 'name': 'barrier_reef'}, {'id': 14454, 'synset': 'baryon.n.01', 'name': 'baryon'}, {'id': 14455, 'synset': 'basin.n.03', 'name': 'basin'}, {'id': 14456, 'synset': 'beach.n.01', 'name': 'beach'}, {'id': 14457, 'synset': 'honeycomb.n.01', 'name': 'honeycomb'}, {'id': 14458, 'synset': 'belay.n.01', 'name': 'belay'}, {'id': 14459, 'synset': 'ben.n.01', 'name': 'ben'}, {'id': 14460, 'synset': 'berm.n.01', 'name': 'berm'}, {'id': 14461, 'synset': 'bladder_stone.n.01', 'name': 'bladder_stone'}, {'id': 14462, 'synset': 'bluff.n.01', 'name': 'bluff'}, {'id': 14463, 'synset': 'borrow_pit.n.01', 'name': 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{'id': 14481, 'synset': 'comet.n.01', 'name': 'comet'}, {'id': 14482, 'synset': 'continental_glacier.n.01', 'name': 'continental_glacier'}, {'id': 14483, 'synset': 'coral_reef.n.01', 'name': 'coral_reef'}, {'id': 14484, 'synset': 'cove.n.02', 'name': 'cove'}, {'id': 14485, 'synset': 'crag.n.01', 'name': 'crag'}, {'id': 14486, 'synset': 'crater.n.03', 'name': 'crater'}, {'id': 14487, 'synset': 'cultivated_land.n.01', 'name': 'cultivated_land'}, {'id': 14488, 'synset': 'dale.n.01', 'name': 'dale'}, {'id': 14489, 'synset': 'defile.n.01', 'name': 'defile'}, {'id': 14490, 'synset': 'delta.n.01', 'name': 'delta'}, {'id': 14491, 'synset': 'descent.n.05', 'name': 'descent'}, {'id': 14492, 'synset': 'diapir.n.01', 'name': 'diapir'}, {'id': 14493, 'synset': 'divot.n.02', 'name': 'divot'}, {'id': 14494, 'synset': 'divot.n.01', 'name': 'divot'}, {'id': 14495, 'synset': 'down.n.04', 'name': 'down'}, {'id': 14496, 'synset': 'downhill.n.01', 'name': 'downhill'}, {'id': 14497, 'synset': 'draw.n.01', 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14660, 'synset': 'volcanic_crater.n.01', 'name': 'volcanic_crater'}, {'id': 14661, 'synset': 'volcano.n.02', 'name': 'volcano'}, {'id': 14662, 'synset': 'wadi.n.01', 'name': 'wadi'}, {'id': 14663, 'synset': 'wall.n.05', 'name': 'wall'}, {'id': 14664, 'synset': 'warren.n.03', 'name': 'warren'}, {'id': 14665, 'synset': "wasp's_nest.n.01", 'name': "wasp's_nest"}, {'id': 14666, 'synset': 'watercourse.n.01', 'name': 'watercourse'}, {'id': 14667, 'synset': 'waterside.n.01', 'name': 'waterside'}, {'id': 14668, 'synset': 'water_table.n.01', 'name': 'water_table'}, {'id': 14669, 'synset': 'whinstone.n.01', 'name': 'whinstone'}, {'id': 14670, 'synset': 'wormcast.n.02', 'name': 'wormcast'}, {'id': 14671, 'synset': 'xenolith.n.01', 'name': 'xenolith'}, {'id': 14672, 'synset': 'circe.n.01', 'name': 'Circe'}, {'id': 14673, 'synset': 'gryphon.n.01', 'name': 'gryphon'}, {'id': 14674, 'synset': 'spiritual_leader.n.01', 'name': 'spiritual_leader'}, {'id': 14675, 'synset': 'messiah.n.01', 'name': 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14788, 'synset': 'tutelo.n.01', 'name': 'Tutelo'}, {'id': 14789, 'synset': 'yana.n.01', 'name': 'Yana'}, {'id': 14790, 'synset': 'yavapai.n.01', 'name': 'Yavapai'}, {'id': 14791, 'synset': 'yokuts.n.02', 'name': 'Yokuts'}, {'id': 14792, 'synset': 'yuma.n.01', 'name': 'Yuma'}, {'id': 14793, 'synset': 'gadaba.n.01', 'name': 'Gadaba'}, {'id': 14794, 'synset': 'kolam.n.01', 'name': 'Kolam'}, {'id': 14795, 'synset': 'kui.n.01', 'name': 'Kui'}, {'id': 14796, 'synset': 'toda.n.01', 'name': 'Toda'}, {'id': 14797, 'synset': 'tulu.n.01', 'name': 'Tulu'}, {'id': 14798, 'synset': 'gujarati.n.01', 'name': 'Gujarati'}, {'id': 14799, 'synset': 'kashmiri.n.01', 'name': 'Kashmiri'}, {'id': 14800, 'synset': 'punjabi.n.01', 'name': 'Punjabi'}, {'id': 14801, 'synset': 'slav.n.01', 'name': 'Slav'}, {'id': 14802, 'synset': 'anabaptist.n.01', 'name': 'Anabaptist'}, {'id': 14803, 'synset': 'adventist.n.01', 'name': 'Adventist'}, {'id': 14804, 'synset': 'gentile.n.03', 'name': 'gentile'}, {'id': 14805, 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14902, 'synset': 'lapp.n.01', 'name': 'Lapp'}, {'id': 14903, 'synset': 'latin_american.n.01', 'name': 'Latin_American'}, {'id': 14904, 'synset': 'lebanese.n.01', 'name': 'Lebanese'}, {'id': 14905, 'synset': 'levantine.n.01', 'name': 'Levantine'}, {'id': 14906, 'synset': 'liberian.n.01', 'name': 'Liberian'}, {'id': 14907, 'synset': 'luxemburger.n.01', 'name': 'Luxemburger'}, {'id': 14908, 'synset': 'macedonian.n.01', 'name': 'Macedonian'}, {'id': 14909, 'synset': 'sabahan.n.01', 'name': 'Sabahan'}, {'id': 14910, 'synset': 'mexican.n.01', 'name': 'Mexican'}, {'id': 14911, 'synset': 'chicano.n.01', 'name': 'Chicano'}, {'id': 14912, 'synset': 'mexican-american.n.01', 'name': 'Mexican-American'}, {'id': 14913, 'synset': 'namibian.n.01', 'name': 'Namibian'}, {'id': 14914, 'synset': 'nauruan.n.01', 'name': 'Nauruan'}, {'id': 14915, 'synset': 'gurkha.n.02', 'name': 'Gurkha'}, {'id': 14916, 'synset': 'new_zealander.n.01', 'name': 'New_Zealander'}, {'id': 14917, 'synset': 'nicaraguan.n.01', 'name': 'Nicaraguan'}, {'id': 14918, 'synset': 'nigerian.n.01', 'name': 'Nigerian'}, {'id': 14919, 'synset': 'hausa.n.01', 'name': 'Hausa'}, {'id': 14920, 'synset': 'north_american.n.01', 'name': 'North_American'}, {'id': 14921, 'synset': 'nova_scotian.n.01', 'name': 'Nova_Scotian'}, {'id': 14922, 'synset': 'omani.n.01', 'name': 'Omani'}, {'id': 14923, 'synset': 'pakistani.n.01', 'name': 'Pakistani'}, {'id': 14924, 'synset': 'brahui.n.01', 'name': 'Brahui'}, {'id': 14925, 'synset': 'south_american_indian.n.01', 'name': 'South_American_Indian'}, {'id': 14926, 'synset': 'carib.n.01', 'name': 'Carib'}, {'id': 14927, 'synset': 'filipino.n.01', 'name': 'Filipino'}, {'id': 14928, 'synset': 'polynesian.n.01', 'name': 'Polynesian'}, {'id': 14929, 'synset': 'qatari.n.01', 'name': 'Qatari'}, {'id': 14930, 'synset': 'romanian.n.01', 'name': 'Romanian'}, {'id': 14931, 'synset': 'muscovite.n.02', 'name': 'Muscovite'}, {'id': 14932, 'synset': 'georgian.n.02', 'name': 'Georgian'}, {'id': 14933, 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'name': 'German_American'}, {'id': 14965, 'synset': 'illinoisan.n.01', 'name': 'Illinoisan'}, {'id': 14966, 'synset': 'mainer.n.01', 'name': 'Mainer'}, {'id': 14967, 'synset': 'marylander.n.01', 'name': 'Marylander'}, {'id': 14968, 'synset': 'minnesotan.n.01', 'name': 'Minnesotan'}, {'id': 14969, 'synset': 'nebraskan.n.01', 'name': 'Nebraskan'}, {'id': 14970, 'synset': 'new_hampshirite.n.01', 'name': 'New_Hampshirite'}, {'id': 14971, 'synset': 'new_jerseyan.n.01', 'name': 'New_Jerseyan'}, {'id': 14972, 'synset': 'new_yorker.n.01', 'name': 'New_Yorker'}, {'id': 14973, 'synset': 'north_carolinian.n.01', 'name': 'North_Carolinian'}, {'id': 14974, 'synset': 'oregonian.n.01', 'name': 'Oregonian'}, {'id': 14975, 'synset': 'pennsylvanian.n.02', 'name': 'Pennsylvanian'}, {'id': 14976, 'synset': 'texan.n.01', 'name': 'Texan'}, {'id': 14977, 'synset': 'utahan.n.01', 'name': 'Utahan'}, {'id': 14978, 'synset': 'uruguayan.n.01', 'name': 'Uruguayan'}, {'id': 14979, 'synset': 'vietnamese.n.01', 'name': 'Vietnamese'}, {'id': 14980, 'synset': 'gambian.n.01', 'name': 'Gambian'}, {'id': 14981, 'synset': 'east_german.n.01', 'name': 'East_German'}, {'id': 14982, 'synset': 'berliner.n.01', 'name': 'Berliner'}, {'id': 14983, 'synset': 'prussian.n.01', 'name': 'Prussian'}, {'id': 14984, 'synset': 'ghanian.n.01', 'name': 'Ghanian'}, {'id': 14985, 'synset': 'guinean.n.01', 'name': 'Guinean'}, {'id': 14986, 'synset': 'papuan.n.01', 'name': 'Papuan'}, {'id': 14987, 'synset': 'walloon.n.01', 'name': 'Walloon'}, {'id': 14988, 'synset': 'yemeni.n.01', 'name': 'Yemeni'}, {'id': 14989, 'synset': 'yugoslav.n.01', 'name': 'Yugoslav'}, {'id': 14990, 'synset': 'serbian.n.01', 'name': 'Serbian'}, {'id': 14991, 'synset': 'xhosa.n.01', 'name': 'Xhosa'}, {'id': 14992, 'synset': 'zairese.n.01', 'name': 'Zairese'}, {'id': 14993, 'synset': 'zimbabwean.n.01', 'name': 'Zimbabwean'}, {'id': 14994, 'synset': 'zulu.n.01', 'name': 'Zulu'}, {'id': 14995, 'synset': 'gemini.n.01', 'name': 'Gemini'}, {'id': 14996, 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15012, 'synset': 'academic_administrator.n.01', 'name': 'academic_administrator'}, {'id': 15013, 'synset': 'academician.n.01', 'name': 'academician'}, {'id': 15014, 'synset': 'accessory_before_the_fact.n.01', 'name': 'accessory_before_the_fact'}, {'id': 15015, 'synset': 'companion.n.03', 'name': 'companion'}, {'id': 15016, 'synset': 'accompanist.n.01', 'name': 'accompanist'}, {'id': 15017, 'synset': 'accomplice.n.01', 'name': 'accomplice'}, {'id': 15018, 'synset': 'account_executive.n.01', 'name': 'account_executive'}, {'id': 15019, 'synset': 'accused.n.01', 'name': 'accused'}, {'id': 15020, 'synset': 'accuser.n.01', 'name': 'accuser'}, {'id': 15021, 'synset': 'acid_head.n.01', 'name': 'acid_head'}, {'id': 15022, 'synset': 'acquaintance.n.03', 'name': 'acquaintance'}, {'id': 15023, 'synset': 'acquirer.n.01', 'name': 'acquirer'}, {'id': 15024, 'synset': 'aerialist.n.01', 'name': 'aerialist'}, {'id': 15025, 'synset': 'action_officer.n.01', 'name': 'action_officer'}, {'id': 15026, 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{'id': 16789, 'synset': 'puritan.n.01', 'name': 'Puritan'}, {'id': 16790, 'synset': 'pursuer.n.02', 'name': 'pursuer'}, {'id': 16791, 'synset': 'pusher.n.03', 'name': 'pusher'}, {'id': 16792, 'synset': 'pusher.n.02', 'name': 'pusher'}, {'id': 16793, 'synset': 'pusher.n.01', 'name': 'pusher'}, {'id': 16794, 'synset': 'putz.n.01', 'name': 'putz'}, {'id': 16795, 'synset': 'pygmy.n.02', 'name': 'Pygmy'}, {'id': 16796, 'synset': 'qadi.n.01', 'name': 'qadi'}, {'id': 16797, 'synset': 'quadriplegic.n.01', 'name': 'quadriplegic'}, {'id': 16798, 'synset': 'quadruplet.n.02', 'name': 'quadruplet'}, {'id': 16799, 'synset': 'quaker.n.02', 'name': 'quaker'}, {'id': 16800, 'synset': 'quarter.n.11', 'name': 'quarter'}, {'id': 16801, 'synset': 'quarterback.n.01', 'name': 'quarterback'}, {'id': 16802, 'synset': 'quartermaster.n.01', 'name': 'quartermaster'}, {'id': 16803, 'synset': 'quartermaster_general.n.01', 'name': 'quartermaster_general'}, {'id': 16804, 'synset': 'quebecois.n.01', 'name': 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'name': 'reader'}, {'id': 16836, 'synset': 'reading_teacher.n.01', 'name': 'reading_teacher'}, {'id': 16837, 'synset': 'realist.n.01', 'name': 'realist'}, {'id': 16838, 'synset': 'real_estate_broker.n.01', 'name': 'real_estate_broker'}, {'id': 16839, 'synset': 'rear_admiral.n.01', 'name': 'rear_admiral'}, {'id': 16840, 'synset': 'receiver.n.05', 'name': 'receiver'}, {'id': 16841, 'synset': 'reciter.n.01', 'name': 'reciter'}, {'id': 16842, 'synset': 'recruit.n.02', 'name': 'recruit'}, {'id': 16843, 'synset': 'recruit.n.01', 'name': 'recruit'}, {'id': 16844, 'synset': 'recruiter.n.01', 'name': 'recruiter'}, {'id': 16845, 'synset': 'recruiting-sergeant.n.01', 'name': 'recruiting-sergeant'}, {'id': 16846, 'synset': 'redcap.n.01', 'name': 'redcap'}, {'id': 16847, 'synset': 'redhead.n.01', 'name': 'redhead'}, {'id': 16848, 'synset': 'redneck.n.01', 'name': 'redneck'}, {'id': 16849, 'synset': 'reeler.n.02', 'name': 'reeler'}, {'id': 16850, 'synset': 'reenactor.n.01', 'name': 'reenactor'}, 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{'id': 16881, 'synset': 'revolutionist.n.01', 'name': 'revolutionist'}, {'id': 16882, 'synset': 'rheumatologist.n.01', 'name': 'rheumatologist'}, {'id': 16883, 'synset': 'rhodesian_man.n.01', 'name': 'Rhodesian_man'}, {'id': 16884, 'synset': 'rhymer.n.01', 'name': 'rhymer'}, {'id': 16885, 'synset': 'rich_person.n.01', 'name': 'rich_person'}, {'id': 16886, 'synset': 'rider.n.03', 'name': 'rider'}, {'id': 16887, 'synset': 'riding_master.n.01', 'name': 'riding_master'}, {'id': 16888, 'synset': 'rifleman.n.02', 'name': 'rifleman'}, {'id': 16889, 'synset': 'right-hander.n.02', 'name': 'right-hander'}, {'id': 16890, 'synset': 'right-hand_man.n.01', 'name': 'right-hand_man'}, {'id': 16891, 'synset': 'ringer.n.03', 'name': 'ringer'}, {'id': 16892, 'synset': 'ringleader.n.01', 'name': 'ringleader'}, {'id': 16893, 'synset': 'roadman.n.02', 'name': 'roadman'}, {'id': 16894, 'synset': 'roarer.n.01', 'name': 'roarer'}, {'id': 16895, 'synset': 'rocket_engineer.n.01', 'name': 'rocket_engineer'}, {'id': 16896, 'synset': 'rocket_scientist.n.01', 'name': 'rocket_scientist'}, {'id': 16897, 'synset': 'rock_star.n.01', 'name': 'rock_star'}, {'id': 16898, 'synset': 'romanov.n.01', 'name': 'Romanov'}, {'id': 16899, 'synset': 'romanticist.n.02', 'name': 'romanticist'}, {'id': 16900, 'synset': 'ropemaker.n.01', 'name': 'ropemaker'}, {'id': 16901, 'synset': 'roper.n.02', 'name': 'roper'}, {'id': 16902, 'synset': 'roper.n.01', 'name': 'roper'}, {'id': 16903, 'synset': 'ropewalker.n.01', 'name': 'ropewalker'}, {'id': 16904, 'synset': 'rosebud.n.02', 'name': 'rosebud'}, {'id': 16905, 'synset': 'rosicrucian.n.02', 'name': 'Rosicrucian'}, {'id': 16906, 'synset': 'mountie.n.01', 'name': 'Mountie'}, {'id': 16907, 'synset': 'rough_rider.n.01', 'name': 'Rough_Rider'}, {'id': 16908, 'synset': 'roundhead.n.01', 'name': 'roundhead'}, {'id': 16909, 'synset': 'civil_authority.n.01', 'name': 'civil_authority'}, {'id': 16910, 'synset': 'runner.n.03', 'name': 'runner'}, {'id': 16911, 'synset': 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17484, 'synset': 'wonderer.n.01', 'name': 'wonderer'}, {'id': 17485, 'synset': 'working_girl.n.01', 'name': 'working_girl'}, {'id': 17486, 'synset': 'workman.n.01', 'name': 'workman'}, {'id': 17487, 'synset': 'workmate.n.01', 'name': 'workmate'}, {'id': 17488, 'synset': 'worldling.n.01', 'name': 'worldling'}, {'id': 17489, 'synset': 'worshiper.n.01', 'name': 'worshiper'}, {'id': 17490, 'synset': 'worthy.n.01', 'name': 'worthy'}, {'id': 17491, 'synset': 'wrecker.n.01', 'name': 'wrecker'}, {'id': 17492, 'synset': 'wright.n.07', 'name': 'wright'}, {'id': 17493, 'synset': 'write-in_candidate.n.01', 'name': 'write-in_candidate'}, {'id': 17494, 'synset': 'writer.n.01', 'name': 'writer'}, {'id': 17495, 'synset': 'wykehamist.n.01', 'name': 'Wykehamist'}, {'id': 17496, 'synset': 'yakuza.n.01', 'name': 'yakuza'}, {'id': 17497, 'synset': 'yard_bird.n.01', 'name': 'yard_bird'}, {'id': 17498, 'synset': 'yardie.n.01', 'name': 'yardie'}, {'id': 17499, 'synset': 'yardman.n.01', 'name': 'yardman'}, {'id': 17500, 'synset': 'yardmaster.n.01', 'name': 'yardmaster'}, {'id': 17501, 'synset': 'yenta.n.02', 'name': 'yenta'}, {'id': 17502, 'synset': 'yogi.n.02', 'name': 'yogi'}, {'id': 17503, 'synset': 'young_buck.n.01', 'name': 'young_buck'}, {'id': 17504, 'synset': 'young_turk.n.02', 'name': 'young_Turk'}, {'id': 17505, 'synset': 'young_turk.n.01', 'name': 'Young_Turk'}, {'id': 17506, 'synset': 'zionist.n.01', 'name': 'Zionist'}, {'id': 17507, 'synset': 'zoo_keeper.n.01', 'name': 'zoo_keeper'}, {'id': 17508, 'synset': 'genet.n.01', 'name': 'Genet'}, {'id': 17509, 'synset': 'kennan.n.01', 'name': 'Kennan'}, {'id': 17510, 'synset': 'munro.n.01', 'name': 'Munro'}, {'id': 17511, 'synset': 'popper.n.01', 'name': 'Popper'}, {'id': 17512, 'synset': 'stoker.n.01', 'name': 'Stoker'}, {'id': 17513, 'synset': 'townes.n.01', 'name': 'Townes'}, {'id': 17514, 'synset': 'dust_storm.n.01', 'name': 'dust_storm'}, {'id': 17515, 'synset': 'parhelion.n.01', 'name': 'parhelion'}, {'id': 17516, 'synset': 'snow.n.01', 'name': 'snow'}, {'id': 17517, 'synset': 'facula.n.01', 'name': 'facula'}, {'id': 17518, 'synset': 'wave.n.08', 'name': 'wave'}, {'id': 17519, 'synset': 'microflora.n.01', 'name': 'microflora'}, {'id': 17520, 'synset': 'wilding.n.01', 'name': 'wilding'}, {'id': 17521, 'synset': 'semi-climber.n.01', 'name': 'semi-climber'}, {'id': 17522, 'synset': 'volva.n.01', 'name': 'volva'}, {'id': 17523, 'synset': 'basidiocarp.n.01', 'name': 'basidiocarp'}, {'id': 17524, 'synset': 'domatium.n.01', 'name': 'domatium'}, {'id': 17525, 'synset': 'apomict.n.01', 'name': 'apomict'}, {'id': 17526, 'synset': 'aquatic.n.01', 'name': 'aquatic'}, {'id': 17527, 'synset': 'bryophyte.n.01', 'name': 'bryophyte'}, {'id': 17528, 'synset': 'acrocarp.n.01', 'name': 'acrocarp'}, {'id': 17529, 'synset': 'sphagnum.n.01', 'name': 'sphagnum'}, {'id': 17530, 'synset': 'liverwort.n.01', 'name': 'liverwort'}, {'id': 17531, 'synset': 'hepatica.n.02', 'name': 'hepatica'}, {'id': 17532, 'synset': 'pecopteris.n.01', 'name': 'pecopteris'}, {'id': 17533, 'synset': 'pteridophyte.n.01', 'name': 'pteridophyte'}, {'id': 17534, 'synset': 'fern.n.01', 'name': 'fern'}, {'id': 17535, 'synset': 'fern_ally.n.01', 'name': 'fern_ally'}, {'id': 17536, 'synset': 'spore.n.01', 'name': 'spore'}, {'id': 17537, 'synset': 'carpospore.n.01', 'name': 'carpospore'}, {'id': 17538, 'synset': 'chlamydospore.n.01', 'name': 'chlamydospore'}, {'id': 17539, 'synset': 'conidium.n.01', 'name': 'conidium'}, {'id': 17540, 'synset': 'oospore.n.01', 'name': 'oospore'}, {'id': 17541, 'synset': 'tetraspore.n.01', 'name': 'tetraspore'}, {'id': 17542, 'synset': 'zoospore.n.01', 'name': 'zoospore'}, {'id': 17543, 'synset': 'cryptogam.n.01', 'name': 'cryptogam'}, {'id': 17544, 'synset': 'spermatophyte.n.01', 'name': 'spermatophyte'}, {'id': 17545, 'synset': 'seedling.n.01', 'name': 'seedling'}, {'id': 17546, 'synset': 'annual.n.01', 'name': 'annual'}, {'id': 17547, 'synset': 'biennial.n.01', 'name': 'biennial'}, {'id': 17548, 'synset': 'perennial.n.01', 'name': 'perennial'}, {'id': 17549, 'synset': 'hygrophyte.n.01', 'name': 'hygrophyte'}, {'id': 17550, 'synset': 'gymnosperm.n.01', 'name': 'gymnosperm'}, {'id': 17551, 'synset': 'gnetum.n.01', 'name': 'gnetum'}, {'id': 17552, 'synset': 'catha_edulis.n.01', 'name': 'Catha_edulis'}, {'id': 17553, 'synset': 'ephedra.n.01', 'name': 'ephedra'}, {'id': 17554, 'synset': 'mahuang.n.01', 'name': 'mahuang'}, {'id': 17555, 'synset': 'welwitschia.n.01', 'name': 'welwitschia'}, {'id': 17556, 'synset': 'cycad.n.01', 'name': 'cycad'}, {'id': 17557, 'synset': 'sago_palm.n.02', 'name': 'sago_palm'}, {'id': 17558, 'synset': 'false_sago.n.01', 'name': 'false_sago'}, {'id': 17559, 'synset': 'zamia.n.01', 'name': 'zamia'}, {'id': 17560, 'synset': 'coontie.n.01', 'name': 'coontie'}, {'id': 17561, 'synset': 'ceratozamia.n.01', 'name': 'ceratozamia'}, {'id': 17562, 'synset': 'dioon.n.01', 'name': 'dioon'}, {'id': 17563, 'synset': 'encephalartos.n.01', 'name': 'encephalartos'}, {'id': 17564, 'synset': 'kaffir_bread.n.01', 'name': 'kaffir_bread'}, {'id': 17565, 'synset': 'macrozamia.n.01', 'name': 'macrozamia'}, {'id': 17566, 'synset': 'burrawong.n.01', 'name': 'burrawong'}, {'id': 17567, 'synset': 'pine.n.01', 'name': 'pine'}, {'id': 17568, 'synset': 'pinon.n.01', 'name': 'pinon'}, {'id': 17569, 'synset': 'nut_pine.n.01', 'name': 'nut_pine'}, {'id': 17570, 'synset': 'pinon_pine.n.01', 'name': 'pinon_pine'}, {'id': 17571, 'synset': 'rocky_mountain_pinon.n.01', 'name': 'Rocky_mountain_pinon'}, {'id': 17572, 'synset': 'single-leaf.n.01', 'name': 'single-leaf'}, {'id': 17573, 'synset': 'bishop_pine.n.01', 'name': 'bishop_pine'}, {'id': 17574, 'synset': 'california_single-leaf_pinyon.n.01', 'name': 'California_single-leaf_pinyon'}, {'id': 17575, 'synset': "parry's_pinyon.n.01", 'name': "Parry's_pinyon"}, {'id': 17576, 'synset': 'spruce_pine.n.04', 'name': 'spruce_pine'}, {'id': 17577, 'synset': 'black_pine.n.05', 'name': 'black_pine'}, {'id': 17578, 'synset': 'pitch_pine.n.02', 'name': 'pitch_pine'}, {'id': 17579, 'synset': 'pond_pine.n.01', 'name': 'pond_pine'}, {'id': 17580, 'synset': 'stone_pine.n.01', 'name': 'stone_pine'}, {'id': 17581, 'synset': 'swiss_pine.n.01', 'name': 'Swiss_pine'}, {'id': 17582, 'synset': 'cembra_nut.n.01', 'name': 'cembra_nut'}, {'id': 17583, 'synset': 'swiss_mountain_pine.n.01', 'name': 'Swiss_mountain_pine'}, {'id': 17584, 'synset': 'ancient_pine.n.01', 'name': 'ancient_pine'}, {'id': 17585, 'synset': 'white_pine.n.01', 'name': 'white_pine'}, {'id': 17586, 'synset': 'american_white_pine.n.01', 'name': 'American_white_pine'}, {'id': 17587, 'synset': 'western_white_pine.n.01', 'name': 'western_white_pine'}, {'id': 17588, 'synset': 'southwestern_white_pine.n.01', 'name': 'southwestern_white_pine'}, {'id': 17589, 'synset': 'limber_pine.n.01', 'name': 'limber_pine'}, {'id': 17590, 'synset': 'whitebark_pine.n.01', 'name': 'whitebark_pine'}, {'id': 17591, 'synset': 'yellow_pine.n.01', 'name': 'yellow_pine'}, {'id': 17592, 'synset': 'ponderosa.n.01', 'name': 'ponderosa'}, {'id': 17593, 'synset': 'jeffrey_pine.n.01', 'name': 'Jeffrey_pine'}, {'id': 17594, 'synset': 'shore_pine.n.01', 'name': 'shore_pine'}, {'id': 17595, 'synset': 'sierra_lodgepole_pine.n.01', 'name': 'Sierra_lodgepole_pine'}, {'id': 17596, 'synset': 'loblolly_pine.n.01', 'name': 'loblolly_pine'}, {'id': 17597, 'synset': 'jack_pine.n.01', 'name': 'jack_pine'}, {'id': 17598, 'synset': 'swamp_pine.n.01', 'name': 'swamp_pine'}, {'id': 17599, 'synset': 'longleaf_pine.n.01', 'name': 'longleaf_pine'}, {'id': 17600, 'synset': 'shortleaf_pine.n.01', 'name': 'shortleaf_pine'}, {'id': 17601, 'synset': 'red_pine.n.02', 'name': 'red_pine'}, {'id': 17602, 'synset': 'scotch_pine.n.01', 'name': 'Scotch_pine'}, {'id': 17603, 'synset': 'scrub_pine.n.01', 'name': 'scrub_pine'}, {'id': 17604, 'synset': 'monterey_pine.n.01', 'name': 'Monterey_pine'}, {'id': 17605, 'synset': 'bristlecone_pine.n.01', 'name': 'bristlecone_pine'}, {'id': 17606, 'synset': 'table-mountain_pine.n.01', 'name': 'table-mountain_pine'}, {'id': 17607, 'synset': 'knobcone_pine.n.01', 'name': 'knobcone_pine'}, {'id': 17608, 'synset': 'japanese_red_pine.n.01', 'name': 'Japanese_red_pine'}, {'id': 17609, 'synset': 'japanese_black_pine.n.01', 'name': 'Japanese_black_pine'}, {'id': 17610, 'synset': 'torrey_pine.n.01', 'name': 'Torrey_pine'}, {'id': 17611, 'synset': 'larch.n.02', 'name': 'larch'}, {'id': 17612, 'synset': 'american_larch.n.01', 'name': 'American_larch'}, {'id': 17613, 'synset': 'western_larch.n.01', 'name': 'western_larch'}, {'id': 17614, 'synset': 'subalpine_larch.n.01', 'name': 'subalpine_larch'}, {'id': 17615, 'synset': 'european_larch.n.01', 'name': 'European_larch'}, {'id': 17616, 'synset': 'siberian_larch.n.01', 'name': 'Siberian_larch'}, {'id': 17617, 'synset': 'golden_larch.n.01', 'name': 'golden_larch'}, {'id': 17618, 'synset': 'fir.n.02', 'name': 'fir'}, {'id': 17619, 'synset': 'silver_fir.n.01', 'name': 'silver_fir'}, {'id': 17620, 'synset': 'amabilis_fir.n.01', 'name': 'amabilis_fir'}, {'id': 17621, 'synset': 'european_silver_fir.n.01', 'name': 'European_silver_fir'}, {'id': 17622, 'synset': 'white_fir.n.01', 'name': 'white_fir'}, {'id': 17623, 'synset': 'balsam_fir.n.01', 'name': 'balsam_fir'}, {'id': 17624, 'synset': 'fraser_fir.n.01', 'name': 'Fraser_fir'}, {'id': 17625, 'synset': 'lowland_fir.n.01', 'name': 'lowland_fir'}, {'id': 17626, 'synset': 'alpine_fir.n.01', 'name': 'Alpine_fir'}, {'id': 17627, 'synset': 'santa_lucia_fir.n.01', 'name': 'Santa_Lucia_fir'}, {'id': 17628, 'synset': 'cedar.n.03', 'name': 'cedar'}, {'id': 17629, 'synset': 'cedar_of_lebanon.n.01', 'name': 'cedar_of_Lebanon'}, {'id': 17630, 'synset': 'deodar.n.01', 'name': 'deodar'}, {'id': 17631, 'synset': 'atlas_cedar.n.01', 'name': 'Atlas_cedar'}, {'id': 17632, 'synset': 'spruce.n.02', 'name': 'spruce'}, {'id': 17633, 'synset': 'norway_spruce.n.01', 'name': 'Norway_spruce'}, {'id': 17634, 'synset': 'weeping_spruce.n.01', 'name': 'weeping_spruce'}, {'id': 17635, 'synset': 'engelmann_spruce.n.01', 'name': 'Engelmann_spruce'}, {'id': 17636, 'synset': 'white_spruce.n.01', 'name': 'white_spruce'}, {'id': 17637, 'synset': 'black_spruce.n.01', 'name': 'black_spruce'}, {'id': 17638, 'synset': 'siberian_spruce.n.01', 'name': 'Siberian_spruce'}, {'id': 17639, 'synset': 'sitka_spruce.n.01', 'name': 'Sitka_spruce'}, {'id': 17640, 'synset': 'oriental_spruce.n.01', 'name': 'oriental_spruce'}, {'id': 17641, 'synset': 'colorado_spruce.n.01', 'name': 'Colorado_spruce'}, {'id': 17642, 'synset': 'red_spruce.n.01', 'name': 'red_spruce'}, {'id': 17643, 'synset': 'hemlock.n.04', 'name': 'hemlock'}, {'id': 17644, 'synset': 'eastern_hemlock.n.01', 'name': 'eastern_hemlock'}, {'id': 17645, 'synset': 'carolina_hemlock.n.01', 'name': 'Carolina_hemlock'}, {'id': 17646, 'synset': 'mountain_hemlock.n.01', 'name': 'mountain_hemlock'}, {'id': 17647, 'synset': 'western_hemlock.n.01', 'name': 'western_hemlock'}, {'id': 17648, 'synset': 'douglas_fir.n.02', 'name': 'douglas_fir'}, {'id': 17649, 'synset': 'green_douglas_fir.n.01', 'name': 'green_douglas_fir'}, {'id': 17650, 'synset': 'big-cone_spruce.n.01', 'name': 'big-cone_spruce'}, {'id': 17651, 'synset': 'cathaya.n.01', 'name': 'Cathaya'}, {'id': 17652, 'synset': 'cedar.n.01', 'name': 'cedar'}, {'id': 17653, 'synset': 'cypress.n.02', 'name': 'cypress'}, {'id': 17654, 'synset': 'gowen_cypress.n.01', 'name': 'gowen_cypress'}, {'id': 17655, 'synset': 'pygmy_cypress.n.01', 'name': 'pygmy_cypress'}, {'id': 17656, 'synset': 'santa_cruz_cypress.n.01', 'name': 'Santa_Cruz_cypress'}, {'id': 17657, 'synset': 'arizona_cypress.n.01', 'name': 'Arizona_cypress'}, {'id': 17658, 'synset': 'guadalupe_cypress.n.01', 'name': 'Guadalupe_cypress'}, {'id': 17659, 'synset': 'monterey_cypress.n.01', 'name': 'Monterey_cypress'}, {'id': 17660, 'synset': 'mexican_cypress.n.01', 'name': 'Mexican_cypress'}, {'id': 17661, 'synset': 'italian_cypress.n.01', 'name': 'Italian_cypress'}, {'id': 17662, 'synset': 'king_william_pine.n.01', 'name': 'King_William_pine'}, {'id': 17663, 'synset': 'chilean_cedar.n.01', 'name': 'Chilean_cedar'}, {'id': 17664, 'synset': 'incense_cedar.n.02', 'name': 'incense_cedar'}, {'id': 17665, 'synset': 'southern_white_cedar.n.01', 'name': 'southern_white_cedar'}, {'id': 17666, 'synset': 'oregon_cedar.n.01', 'name': 'Oregon_cedar'}, {'id': 17667, 'synset': 'yellow_cypress.n.01', 'name': 'yellow_cypress'}, {'id': 17668, 'synset': 'japanese_cedar.n.01', 'name': 'Japanese_cedar'}, {'id': 17669, 'synset': 'juniper_berry.n.01', 'name': 'juniper_berry'}, {'id': 17670, 'synset': 'incense_cedar.n.01', 'name': 'incense_cedar'}, {'id': 17671, 'synset': 'kawaka.n.01', 'name': 'kawaka'}, {'id': 17672, 'synset': 'pahautea.n.01', 'name': 'pahautea'}, {'id': 17673, 'synset': 'metasequoia.n.01', 'name': 'metasequoia'}, {'id': 17674, 'synset': 'arborvitae.n.01', 'name': 'arborvitae'}, {'id': 17675, 'synset': 'western_red_cedar.n.01', 'name': 'western_red_cedar'}, {'id': 17676, 'synset': 'american_arborvitae.n.01', 'name': 'American_arborvitae'}, {'id': 17677, 'synset': 'oriental_arborvitae.n.01', 'name': 'Oriental_arborvitae'}, {'id': 17678, 'synset': 'hiba_arborvitae.n.01', 'name': 'hiba_arborvitae'}, {'id': 17679, 'synset': 'keteleeria.n.01', 'name': 'keteleeria'}, {'id': 17680, 'synset': 'wollemi_pine.n.01', 'name': 'Wollemi_pine'}, {'id': 17681, 'synset': 'araucaria.n.01', 'name': 'araucaria'}, {'id': 17682, 'synset': 'monkey_puzzle.n.01', 'name': 'monkey_puzzle'}, {'id': 17683, 'synset': 'norfolk_island_pine.n.01', 'name': 'norfolk_island_pine'}, {'id': 17684, 'synset': 'new_caledonian_pine.n.01', 'name': 'new_caledonian_pine'}, {'id': 17685, 'synset': 'bunya_bunya.n.01', 'name': 'bunya_bunya'}, {'id': 17686, 'synset': 'hoop_pine.n.01', 'name': 'hoop_pine'}, {'id': 17687, 'synset': 'kauri_pine.n.01', 'name': 'kauri_pine'}, {'id': 17688, 'synset': 'kauri.n.02', 'name': 'kauri'}, {'id': 17689, 'synset': 'amboina_pine.n.01', 'name': 'amboina_pine'}, {'id': 17690, 'synset': 'dundathu_pine.n.01', 'name': 'dundathu_pine'}, {'id': 17691, 'synset': 'red_kauri.n.01', 'name': 'red_kauri'}, {'id': 17692, 'synset': 'plum-yew.n.01', 'name': 'plum-yew'}, {'id': 17693, 'synset': 'california_nutmeg.n.01', 'name': 'California_nutmeg'}, {'id': 17694, 'synset': 'stinking_cedar.n.01', 'name': 'stinking_cedar'}, {'id': 17695, 'synset': 'celery_pine.n.01', 'name': 'celery_pine'}, {'id': 17696, 'synset': 'celery_top_pine.n.01', 'name': 'celery_top_pine'}, {'id': 17697, 'synset': 'tanekaha.n.01', 'name': 'tanekaha'}, {'id': 17698, 'synset': 'alpine_celery_pine.n.01', 'name': 'Alpine_celery_pine'}, {'id': 17699, 'synset': 'yellowwood.n.02', 'name': 'yellowwood'}, {'id': 17700, 'synset': 'gymnospermous_yellowwood.n.01', 'name': 'gymnospermous_yellowwood'}, {'id': 17701, 'synset': 'podocarp.n.01', 'name': 'podocarp'}, {'id': 17702, 'synset': 'yacca.n.01', 'name': 'yacca'}, {'id': 17703, 'synset': 'brown_pine.n.01', 'name': 'brown_pine'}, {'id': 17704, 'synset': 'cape_yellowwood.n.01', 'name': 'cape_yellowwood'}, {'id': 17705, 'synset': 'south-african_yellowwood.n.01', 'name': 'South-African_yellowwood'}, {'id': 17706, 'synset': 'alpine_totara.n.01', 'name': 'alpine_totara'}, {'id': 17707, 'synset': 'totara.n.01', 'name': 'totara'}, {'id': 17708, 'synset': 'common_yellowwood.n.01', 'name': 'common_yellowwood'}, {'id': 17709, 'synset': 'kahikatea.n.01', 'name': 'kahikatea'}, {'id': 17710, 'synset': 'rimu.n.01', 'name': 'rimu'}, {'id': 17711, 'synset': 'tarwood.n.02', 'name': 'tarwood'}, {'id': 17712, 'synset': 'common_sickle_pine.n.01', 'name': 'common_sickle_pine'}, {'id': 17713, 'synset': 'yellow-leaf_sickle_pine.n.01', 'name': 'yellow-leaf_sickle_pine'}, {'id': 17714, 'synset': 'tarwood.n.01', 'name': 'tarwood'}, {'id': 17715, 'synset': 'westland_pine.n.01', 'name': 'westland_pine'}, {'id': 17716, 'synset': 'huon_pine.n.01', 'name': 'huon_pine'}, {'id': 17717, 'synset': 'chilean_rimu.n.01', 'name': 'Chilean_rimu'}, {'id': 17718, 'synset': 'mountain_rimu.n.01', 'name': 'mountain_rimu'}, {'id': 17719, 'synset': 'nagi.n.01', 'name': 'nagi'}, {'id': 17720, 'synset': 'miro.n.01', 'name': 'miro'}, {'id': 17721, 'synset': 'matai.n.01', 'name': 'matai'}, {'id': 17722, 'synset': 'plum-fruited_yew.n.01', 'name': 'plum-fruited_yew'}, {'id': 17723, 'synset': 'prince_albert_yew.n.01', 'name': 'Prince_Albert_yew'}, {'id': 17724, 'synset': 'sundacarpus_amara.n.01', 'name': 'Sundacarpus_amara'}, {'id': 17725, 'synset': 'japanese_umbrella_pine.n.01', 'name': 'Japanese_umbrella_pine'}, {'id': 17726, 'synset': 'yew.n.02', 'name': 'yew'}, {'id': 17727, 'synset': 'old_world_yew.n.01', 'name': 'Old_World_yew'}, {'id': 17728, 'synset': 'pacific_yew.n.01', 'name': 'Pacific_yew'}, {'id': 17729, 'synset': 'japanese_yew.n.01', 'name': 'Japanese_yew'}, {'id': 17730, 'synset': 'florida_yew.n.01', 'name': 'Florida_yew'}, {'id': 17731, 'synset': 'new_caledonian_yew.n.01', 'name': 'New_Caledonian_yew'}, {'id': 17732, 'synset': 'white-berry_yew.n.01', 'name': 'white-berry_yew'}, {'id': 17733, 'synset': 'ginkgo.n.01', 'name': 'ginkgo'}, {'id': 17734, 'synset': 'angiosperm.n.01', 'name': 'angiosperm'}, {'id': 17735, 'synset': 'dicot.n.01', 'name': 'dicot'}, {'id': 17736, 'synset': 'monocot.n.01', 'name': 'monocot'}, {'id': 17737, 'synset': 'floret.n.01', 'name': 'floret'}, {'id': 17738, 'synset': 'flower.n.01', 'name': 'flower'}, {'id': 17739, 'synset': 'bloomer.n.01', 'name': 'bloomer'}, {'id': 17740, 'synset': 'wildflower.n.01', 'name': 'wildflower'}, {'id': 17741, 'synset': 'apetalous_flower.n.01', 'name': 'apetalous_flower'}, {'id': 17742, 'synset': 'inflorescence.n.02', 'name': 'inflorescence'}, {'id': 17743, 'synset': 'rosebud.n.01', 'name': 'rosebud'}, {'id': 17744, 'synset': 'gynostegium.n.01', 'name': 'gynostegium'}, {'id': 17745, 'synset': 'pollinium.n.01', 'name': 'pollinium'}, {'id': 17746, 'synset': 'pistil.n.01', 'name': 'pistil'}, {'id': 17747, 'synset': 'gynobase.n.01', 'name': 'gynobase'}, {'id': 17748, 'synset': 'gynophore.n.01', 'name': 'gynophore'}, {'id': 17749, 'synset': 'stylopodium.n.01', 'name': 'stylopodium'}, {'id': 17750, 'synset': 'carpophore.n.01', 'name': 'carpophore'}, {'id': 17751, 'synset': 'cornstalk.n.01', 'name': 'cornstalk'}, {'id': 17752, 'synset': 'petiolule.n.01', 'name': 'petiolule'}, {'id': 17753, 'synset': 'mericarp.n.01', 'name': 'mericarp'}, {'id': 17754, 'synset': 'micropyle.n.01', 'name': 'micropyle'}, {'id': 17755, 'synset': 'germ_tube.n.01', 'name': 'germ_tube'}, {'id': 17756, 'synset': 'pollen_tube.n.01', 'name': 'pollen_tube'}, {'id': 17757, 'synset': 'gemma.n.01', 'name': 'gemma'}, {'id': 17758, 'synset': 'galbulus.n.01', 'name': 'galbulus'}, {'id': 17759, 'synset': 'nectary.n.01', 'name': 'nectary'}, {'id': 17760, 'synset': 'pericarp.n.01', 'name': 'pericarp'}, {'id': 17761, 'synset': 'epicarp.n.01', 'name': 'epicarp'}, {'id': 17762, 'synset': 'mesocarp.n.01', 'name': 'mesocarp'}, {'id': 17763, 'synset': 'pip.n.03', 'name': 'pip'}, {'id': 17764, 'synset': 'silique.n.01', 'name': 'silique'}, {'id': 17765, 'synset': 'cataphyll.n.01', 'name': 'cataphyll'}, {'id': 17766, 'synset': 'perisperm.n.01', 'name': 'perisperm'}, {'id': 17767, 'synset': 'monocarp.n.01', 'name': 'monocarp'}, {'id': 17768, 'synset': 'sporophyte.n.01', 'name': 'sporophyte'}, {'id': 17769, 'synset': 'gametophyte.n.01', 'name': 'gametophyte'}, {'id': 17770, 'synset': 'megasporangium.n.01', 'name': 'megasporangium'}, {'id': 17771, 'synset': 'microspore.n.01', 'name': 'microspore'}, {'id': 17772, 'synset': 'microsporangium.n.01', 'name': 'microsporangium'}, {'id': 17773, 'synset': 'microsporophyll.n.01', 'name': 'microsporophyll'}, {'id': 17774, 'synset': 'archespore.n.01', 'name': 'archespore'}, {'id': 17775, 'synset': 'bonduc_nut.n.01', 'name': 'bonduc_nut'}, {'id': 17776, 'synset': "job's_tears.n.01", 'name': "Job's_tears"}, {'id': 17777, 'synset': 'oilseed.n.01', 'name': 'oilseed'}, {'id': 17778, 'synset': 'castor_bean.n.01', 'name': 'castor_bean'}, {'id': 17779, 'synset': 'cottonseed.n.01', 'name': 'cottonseed'}, {'id': 17780, 'synset': 'candlenut.n.02', 'name': 'candlenut'}, {'id': 17781, 'synset': 'peach_pit.n.01', 'name': 'peach_pit'}, {'id': 17782, 'synset': 'hypanthium.n.01', 'name': 'hypanthium'}, {'id': 17783, 'synset': 'petal.n.01', 'name': 'petal'}, {'id': 17784, 'synset': 'corolla.n.01', 'name': 'corolla'}, {'id': 17785, 'synset': 'lip.n.02', 'name': 'lip'}, {'id': 17786, 'synset': 'perianth.n.01', 'name': 'perianth'}, {'id': 17787, 'synset': 'thistledown.n.01', 'name': 'thistledown'}, {'id': 17788, 'synset': 'custard_apple.n.01', 'name': 'custard_apple'}, {'id': 17789, 'synset': 'cherimoya.n.01', 'name': 'cherimoya'}, {'id': 17790, 'synset': 'ilama.n.01', 'name': 'ilama'}, {'id': 17791, 'synset': 'soursop.n.01', 'name': 'soursop'}, {'id': 17792, 'synset': "bullock's_heart.n.01", 'name': "bullock's_heart"}, {'id': 17793, 'synset': 'sweetsop.n.01', 'name': 'sweetsop'}, {'id': 17794, 'synset': 'pond_apple.n.01', 'name': 'pond_apple'}, {'id': 17795, 'synset': 'pawpaw.n.02', 'name': 'pawpaw'}, {'id': 17796, 'synset': 'ilang-ilang.n.02', 'name': 'ilang-ilang'}, {'id': 17797, 'synset': 'lancewood.n.02', 'name': 'lancewood'}, {'id': 17798, 'synset': 'guinea_pepper.n.02', 'name': 'Guinea_pepper'}, {'id': 17799, 'synset': 'barberry.n.01', 'name': 'barberry'}, {'id': 17800, 'synset': 'american_barberry.n.01', 'name': 'American_barberry'}, {'id': 17801, 'synset': 'common_barberry.n.01', 'name': 'common_barberry'}, {'id': 17802, 'synset': 'japanese_barberry.n.01', 'name': 'Japanese_barberry'}, {'id': 17803, 'synset': 'oregon_grape.n.02', 'name': 'Oregon_grape'}, {'id': 17804, 'synset': 'oregon_grape.n.01', 'name': 'Oregon_grape'}, {'id': 17805, 'synset': 'mayapple.n.01', 'name': 'mayapple'}, {'id': 17806, 'synset': 'may_apple.n.01', 'name': 'May_apple'}, {'id': 17807, 'synset': 'allspice.n.02', 'name': 'allspice'}, {'id': 17808, 'synset': 'carolina_allspice.n.01', 'name': 'Carolina_allspice'}, {'id': 17809, 'synset': 'spicebush.n.02', 'name': 'spicebush'}, {'id': 17810, 'synset': 'katsura_tree.n.01', 'name': 'katsura_tree'}, {'id': 17811, 'synset': 'laurel.n.01', 'name': 'laurel'}, {'id': 17812, 'synset': 'true_laurel.n.01', 'name': 'true_laurel'}, {'id': 17813, 'synset': 'camphor_tree.n.01', 'name': 'camphor_tree'}, {'id': 17814, 'synset': 'cinnamon.n.02', 'name': 'cinnamon'}, {'id': 17815, 'synset': 'cassia.n.03', 'name': 'cassia'}, {'id': 17816, 'synset': 'cassia_bark.n.01', 'name': 'cassia_bark'}, {'id': 17817, 'synset': 'saigon_cinnamon.n.01', 'name': 'Saigon_cinnamon'}, {'id': 17818, 'synset': 'cinnamon_bark.n.01', 'name': 'cinnamon_bark'}, {'id': 17819, 'synset': 'spicebush.n.01', 'name': 'spicebush'}, {'id': 17820, 'synset': 'avocado.n.02', 'name': 'avocado'}, {'id': 17821, 'synset': 'laurel-tree.n.01', 'name': 'laurel-tree'}, {'id': 17822, 'synset': 'sassafras.n.01', 'name': 'sassafras'}, {'id': 17823, 'synset': 'california_laurel.n.01', 'name': 'California_laurel'}, {'id': 17824, 'synset': 'anise_tree.n.01', 'name': 'anise_tree'}, {'id': 17825, 'synset': 'purple_anise.n.01', 'name': 'purple_anise'}, {'id': 17826, 'synset': 'star_anise.n.02', 'name': 'star_anise'}, {'id': 17827, 'synset': 'star_anise.n.01', 'name': 'star_anise'}, {'id': 17828, 'synset': 'magnolia.n.02', 'name': 'magnolia'}, {'id': 17829, 'synset': 'southern_magnolia.n.01', 'name': 'southern_magnolia'}, {'id': 17830, 'synset': 'umbrella_tree.n.02', 'name': 'umbrella_tree'}, {'id': 17831, 'synset': 'earleaved_umbrella_tree.n.01', 'name': 'earleaved_umbrella_tree'}, {'id': 17832, 'synset': 'cucumber_tree.n.01', 'name': 'cucumber_tree'}, {'id': 17833, 'synset': 'large-leaved_magnolia.n.01', 'name': 'large-leaved_magnolia'}, {'id': 17834, 'synset': 'saucer_magnolia.n.01', 'name': 'saucer_magnolia'}, {'id': 17835, 'synset': 'star_magnolia.n.01', 'name': 'star_magnolia'}, {'id': 17836, 'synset': 'sweet_bay.n.01', 'name': 'sweet_bay'}, {'id': 17837, 'synset': 'manglietia.n.01', 'name': 'manglietia'}, {'id': 17838, 'synset': 'tulip_tree.n.01', 'name': 'tulip_tree'}, {'id': 17839, 'synset': 'moonseed.n.01', 'name': 'moonseed'}, {'id': 17840, 'synset': 'common_moonseed.n.01', 'name': 'common_moonseed'}, {'id': 17841, 'synset': 'carolina_moonseed.n.01', 'name': 'Carolina_moonseed'}, {'id': 17842, 'synset': 'nutmeg.n.01', 'name': 'nutmeg'}, {'id': 17843, 'synset': 'water_nymph.n.02', 'name': 'water_nymph'}, {'id': 17844, 'synset': 'european_white_lily.n.01', 'name': 'European_white_lily'}, {'id': 17845, 'synset': 'southern_spatterdock.n.01', 'name': 'southern_spatterdock'}, {'id': 17846, 'synset': 'lotus.n.01', 'name': 'lotus'}, {'id': 17847, 'synset': 'water_chinquapin.n.01', 'name': 'water_chinquapin'}, {'id': 17848, 'synset': 'water-shield.n.02', 'name': 'water-shield'}, {'id': 17849, 'synset': 'water-shield.n.01', 'name': 'water-shield'}, {'id': 17850, 'synset': 'peony.n.01', 'name': 'peony'}, {'id': 17851, 'synset': 'buttercup.n.01', 'name': 'buttercup'}, {'id': 17852, 'synset': 'meadow_buttercup.n.01', 'name': 'meadow_buttercup'}, {'id': 17853, 'synset': 'water_crowfoot.n.01', 'name': 'water_crowfoot'}, {'id': 17854, 'synset': 'lesser_celandine.n.01', 'name': 'lesser_celandine'}, {'id': 17855, 'synset': 'lesser_spearwort.n.01', 'name': 'lesser_spearwort'}, {'id': 17856, 'synset': 'greater_spearwort.n.01', 'name': 'greater_spearwort'}, {'id': 17857, 'synset': 'western_buttercup.n.01', 'name': 'western_buttercup'}, {'id': 17858, 'synset': 'creeping_buttercup.n.01', 'name': 'creeping_buttercup'}, {'id': 17859, 'synset': 'cursed_crowfoot.n.01', 'name': 'cursed_crowfoot'}, {'id': 17860, 'synset': 'aconite.n.01', 'name': 'aconite'}, {'id': 17861, 'synset': 'monkshood.n.01', 'name': 'monkshood'}, {'id': 17862, 'synset': 'wolfsbane.n.01', 'name': 'wolfsbane'}, {'id': 17863, 'synset': 'baneberry.n.02', 'name': 'baneberry'}, {'id': 17864, 'synset': 'baneberry.n.01', 'name': 'baneberry'}, {'id': 17865, 'synset': 'red_baneberry.n.01', 'name': 'red_baneberry'}, {'id': 17866, 'synset': "pheasant's-eye.n.01", 'name': "pheasant's-eye"}, {'id': 17867, 'synset': 'anemone.n.01', 'name': 'anemone'}, {'id': 17868, 'synset': 'alpine_anemone.n.01', 'name': 'Alpine_anemone'}, {'id': 17869, 'synset': 'canada_anemone.n.01', 'name': 'Canada_anemone'}, {'id': 17870, 'synset': 'thimbleweed.n.01', 'name': 'thimbleweed'}, {'id': 17871, 'synset': 'wood_anemone.n.02', 'name': 'wood_anemone'}, {'id': 17872, 'synset': 'wood_anemone.n.01', 'name': 'wood_anemone'}, {'id': 17873, 'synset': 'longheaded_thimbleweed.n.01', 'name': 'longheaded_thimbleweed'}, {'id': 17874, 'synset': 'snowdrop_anemone.n.01', 'name': 'snowdrop_anemone'}, {'id': 17875, 'synset': 'virginia_thimbleweed.n.01', 'name': 'Virginia_thimbleweed'}, {'id': 17876, 'synset': 'rue_anemone.n.01', 'name': 'rue_anemone'}, {'id': 17877, 'synset': 'columbine.n.01', 'name': 'columbine'}, {'id': 17878, 'synset': 'meeting_house.n.01', 'name': 'meeting_house'}, {'id': 17879, 'synset': 'blue_columbine.n.01', 'name': 'blue_columbine'}, {'id': 17880, 'synset': "granny's_bonnets.n.01", 'name': "granny's_bonnets"}, {'id': 17881, 'synset': 'marsh_marigold.n.01', 'name': 'marsh_marigold'}, {'id': 17882, 'synset': 'american_bugbane.n.01', 'name': 'American_bugbane'}, {'id': 17883, 'synset': 'black_cohosh.n.01', 'name': 'black_cohosh'}, {'id': 17884, 'synset': 'fetid_bugbane.n.01', 'name': 'fetid_bugbane'}, {'id': 17885, 'synset': 'clematis.n.01', 'name': 'clematis'}, {'id': 17886, 'synset': 'pine_hyacinth.n.01', 'name': 'pine_hyacinth'}, {'id': 17887, 'synset': 'blue_jasmine.n.01', 'name': 'blue_jasmine'}, {'id': 17888, 'synset': 'golden_clematis.n.01', 'name': 'golden_clematis'}, {'id': 17889, 'synset': 'scarlet_clematis.n.01', 'name': 'scarlet_clematis'}, {'id': 17890, 'synset': 'leather_flower.n.02', 'name': 'leather_flower'}, {'id': 17891, 'synset': 'leather_flower.n.01', 'name': 'leather_flower'}, {'id': 17892, 'synset': "virgin's_bower.n.01", 'name': "virgin's_bower"}, {'id': 17893, 'synset': 'purple_clematis.n.01', 'name': 'purple_clematis'}, {'id': 17894, 'synset': 'goldthread.n.01', 'name': 'goldthread'}, {'id': 17895, 'synset': 'rocket_larkspur.n.01', 'name': 'rocket_larkspur'}, {'id': 17896, 'synset': 'delphinium.n.01', 'name': 'delphinium'}, {'id': 17897, 'synset': 'larkspur.n.01', 'name': 'larkspur'}, {'id': 17898, 'synset': 'winter_aconite.n.01', 'name': 'winter_aconite'}, {'id': 17899, 'synset': 'lenten_rose.n.01', 'name': 'lenten_rose'}, {'id': 17900, 'synset': 'green_hellebore.n.01', 'name': 'green_hellebore'}, {'id': 17901, 'synset': 'hepatica.n.01', 'name': 'hepatica'}, {'id': 17902, 'synset': 'goldenseal.n.01', 'name': 'goldenseal'}, {'id': 17903, 'synset': 'false_rue_anemone.n.01', 'name': 'false_rue_anemone'}, {'id': 17904, 'synset': 'giant_buttercup.n.01', 'name': 'giant_buttercup'}, {'id': 17905, 'synset': 'nigella.n.01', 'name': 'nigella'}, {'id': 17906, 'synset': 'love-in-a-mist.n.03', 'name': 'love-in-a-mist'}, {'id': 17907, 'synset': 'fennel_flower.n.01', 'name': 'fennel_flower'}, {'id': 17908, 'synset': 'black_caraway.n.01', 'name': 'black_caraway'}, {'id': 17909, 'synset': 'pasqueflower.n.01', 'name': 'pasqueflower'}, {'id': 17910, 'synset': 'meadow_rue.n.01', 'name': 'meadow_rue'}, {'id': 17911, 'synset': 'false_bugbane.n.01', 'name': 'false_bugbane'}, {'id': 17912, 'synset': 'globeflower.n.01', 'name': 'globeflower'}, {'id': 17913, 'synset': "winter's_bark.n.02", 'name': "winter's_bark"}, {'id': 17914, 'synset': 'pepper_shrub.n.01', 'name': 'pepper_shrub'}, {'id': 17915, 'synset': 'sweet_gale.n.01', 'name': 'sweet_gale'}, {'id': 17916, 'synset': 'wax_myrtle.n.01', 'name': 'wax_myrtle'}, {'id': 17917, 'synset': 'bay_myrtle.n.01', 'name': 'bay_myrtle'}, {'id': 17918, 'synset': 'bayberry.n.02', 'name': 'bayberry'}, {'id': 17919, 'synset': 'sweet_fern.n.02', 'name': 'sweet_fern'}, {'id': 17920, 'synset': 'corkwood.n.01', 'name': 'corkwood'}, {'id': 17921, 'synset': 'jointed_rush.n.01', 'name': 'jointed_rush'}, {'id': 17922, 'synset': 'toad_rush.n.01', 'name': 'toad_rush'}, {'id': 17923, 'synset': 'slender_rush.n.01', 'name': 'slender_rush'}, {'id': 17924, 'synset': 'zebrawood.n.02', 'name': 'zebrawood'}, {'id': 17925, 'synset': 'connarus_guianensis.n.01', 'name': 'Connarus_guianensis'}, {'id': 17926, 'synset': 'legume.n.01', 'name': 'legume'}, {'id': 17927, 'synset': 'peanut.n.01', 'name': 'peanut'}, {'id': 17928, 'synset': 'granadilla_tree.n.01', 'name': 'granadilla_tree'}, {'id': 17929, 'synset': 'arariba.n.01', 'name': 'arariba'}, {'id': 17930, 'synset': 'tonka_bean.n.01', 'name': 'tonka_bean'}, {'id': 17931, 'synset': 'courbaril.n.01', 'name': 'courbaril'}, {'id': 17932, 'synset': 'melilotus.n.01', 'name': 'melilotus'}, {'id': 17933, 'synset': 'darling_pea.n.01', 'name': 'darling_pea'}, {'id': 17934, 'synset': 'smooth_darling_pea.n.01', 'name': 'smooth_darling_pea'}, {'id': 17935, 'synset': 'clover.n.01', 'name': 'clover'}, {'id': 17936, 'synset': 'alpine_clover.n.01', 'name': 'alpine_clover'}, {'id': 17937, 'synset': 'hop_clover.n.02', 'name': 'hop_clover'}, {'id': 17938, 'synset': 'crimson_clover.n.01', 'name': 'crimson_clover'}, {'id': 17939, 'synset': 'red_clover.n.01', 'name': 'red_clover'}, {'id': 17940, 'synset': 'buffalo_clover.n.02', 'name': 'buffalo_clover'}, {'id': 17941, 'synset': 'white_clover.n.01', 'name': 'white_clover'}, {'id': 17942, 'synset': 'mimosa.n.02', 'name': 'mimosa'}, {'id': 17943, 'synset': 'acacia.n.01', 'name': 'acacia'}, {'id': 17944, 'synset': 'shittah.n.01', 'name': 'shittah'}, {'id': 17945, 'synset': 'wattle.n.03', 'name': 'wattle'}, {'id': 17946, 'synset': 'black_wattle.n.01', 'name': 'black_wattle'}, {'id': 17947, 'synset': 'gidgee.n.01', 'name': 'gidgee'}, {'id': 17948, 'synset': 'catechu.n.02', 'name': 'catechu'}, {'id': 17949, 'synset': 'silver_wattle.n.01', 'name': 'silver_wattle'}, {'id': 17950, 'synset': 'huisache.n.01', 'name': 'huisache'}, {'id': 17951, 'synset': 'lightwood.n.01', 'name': 'lightwood'}, {'id': 17952, 'synset': 'golden_wattle.n.01', 'name': 'golden_wattle'}, {'id': 17953, 'synset': 'fever_tree.n.04', 'name': 'fever_tree'}, {'id': 17954, 'synset': 'coralwood.n.01', 'name': 'coralwood'}, {'id': 17955, 'synset': 'albizzia.n.01', 'name': 'albizzia'}, {'id': 17956, 'synset': 'silk_tree.n.01', 'name': 'silk_tree'}, {'id': 17957, 'synset': 'siris.n.01', 'name': 'siris'}, {'id': 17958, 'synset': 'rain_tree.n.01', 'name': 'rain_tree'}, {'id': 17959, 'synset': 'calliandra.n.01', 'name': 'calliandra'}, {'id': 17960, 'synset': 'conacaste.n.01', 'name': 'conacaste'}, {'id': 17961, 'synset': 'inga.n.01', 'name': 'inga'}, {'id': 17962, 'synset': 'ice-cream_bean.n.01', 'name': 'ice-cream_bean'}, {'id': 17963, 'synset': 'guama.n.01', 'name': 'guama'}, {'id': 17964, 'synset': 'lead_tree.n.01', 'name': 'lead_tree'}, {'id': 17965, 'synset': 'wild_tamarind.n.02', 'name': 'wild_tamarind'}, {'id': 17966, 'synset': 'sabicu.n.02', 'name': 'sabicu'}, {'id': 17967, 'synset': 'nitta_tree.n.01', 'name': 'nitta_tree'}, {'id': 17968, 'synset': 'parkia_javanica.n.01', 'name': 'Parkia_javanica'}, {'id': 17969, 'synset': 'manila_tamarind.n.01', 'name': 'manila_tamarind'}, {'id': 17970, 'synset': "cat's-claw.n.01", 'name': "cat's-claw"}, {'id': 17971, 'synset': 'honey_mesquite.n.01', 'name': 'honey_mesquite'}, {'id': 17972, 'synset': 'algarroba.n.03', 'name': 'algarroba'}, {'id': 17973, 'synset': 'screw_bean.n.02', 'name': 'screw_bean'}, {'id': 17974, 'synset': 'screw_bean.n.01', 'name': 'screw_bean'}, {'id': 17975, 'synset': 'dogbane.n.01', 'name': 'dogbane'}, {'id': 17976, 'synset': 'indian_hemp.n.03', 'name': 'Indian_hemp'}, {'id': 17977, 'synset': "bushman's_poison.n.01", 'name': "bushman's_poison"}, {'id': 17978, 'synset': 'impala_lily.n.01', 'name': 'impala_lily'}, {'id': 17979, 'synset': 'allamanda.n.01', 'name': 'allamanda'}, {'id': 17980, 'synset': 'common_allamanda.n.01', 'name': 'common_allamanda'}, {'id': 17981, 'synset': 'dita.n.01', 'name': 'dita'}, {'id': 17982, 'synset': 'nepal_trumpet_flower.n.01', 'name': 'Nepal_trumpet_flower'}, {'id': 17983, 'synset': 'carissa.n.01', 'name': 'carissa'}, {'id': 17984, 'synset': 'hedge_thorn.n.01', 'name': 'hedge_thorn'}, {'id': 17985, 'synset': 'natal_plum.n.01', 'name': 'natal_plum'}, {'id': 17986, 'synset': 'periwinkle.n.02', 'name': 'periwinkle'}, {'id': 17987, 'synset': 'ivory_tree.n.01', 'name': 'ivory_tree'}, {'id': 17988, 'synset': 'white_dipladenia.n.01', 'name': 'white_dipladenia'}, {'id': 17989, 'synset': 'chilean_jasmine.n.01', 'name': 'Chilean_jasmine'}, {'id': 17990, 'synset': 'oleander.n.01', 'name': 'oleander'}, {'id': 17991, 'synset': 'frangipani.n.01', 'name': 'frangipani'}, {'id': 17992, 'synset': 'west_indian_jasmine.n.01', 'name': 'West_Indian_jasmine'}, {'id': 17993, 'synset': 'rauwolfia.n.02', 'name': 'rauwolfia'}, {'id': 17994, 'synset': 'snakewood.n.01', 'name': 'snakewood'}, {'id': 17995, 'synset': 'strophanthus_kombe.n.01', 'name': 'Strophanthus_kombe'}, {'id': 17996, 'synset': 'yellow_oleander.n.01', 'name': 'yellow_oleander'}, {'id': 17997, 'synset': 'myrtle.n.01', 'name': 'myrtle'}, {'id': 17998, 'synset': 'large_periwinkle.n.01', 'name': 'large_periwinkle'}, {'id': 17999, 'synset': 'arum.n.02', 'name': 'arum'}, {'id': 18000, 'synset': 'cuckoopint.n.01', 'name': 'cuckoopint'}, {'id': 18001, 'synset': 'black_calla.n.01', 'name': 'black_calla'}, {'id': 18002, 'synset': 'calamus.n.02', 'name': 'calamus'}, {'id': 18003, 'synset': 'alocasia.n.01', 'name': 'alocasia'}, {'id': 18004, 'synset': 'giant_taro.n.01', 'name': 'giant_taro'}, {'id': 18005, 'synset': 'amorphophallus.n.01', 'name': 'amorphophallus'}, {'id': 18006, 'synset': 'pungapung.n.01', 'name': 'pungapung'}, {'id': 18007, 'synset': "devil's_tongue.n.01", 'name': "devil's_tongue"}, {'id': 18008, 'synset': 'anthurium.n.01', 'name': 'anthurium'}, {'id': 18009, 'synset': 'flamingo_flower.n.01', 'name': 'flamingo_flower'}, {'id': 18010, 'synset': 'jack-in-the-pulpit.n.01', 'name': 'jack-in-the-pulpit'}, {'id': 18011, 'synset': "friar's-cowl.n.01", 'name': "friar's-cowl"}, {'id': 18012, 'synset': 'caladium.n.01', 'name': 'caladium'}, {'id': 18013, 'synset': 'caladium_bicolor.n.01', 'name': 'Caladium_bicolor'}, {'id': 18014, 'synset': 'wild_calla.n.01', 'name': 'wild_calla'}, {'id': 18015, 'synset': 'taro.n.02', 'name': 'taro'}, {'id': 18016, 'synset': 'taro.n.01', 'name': 'taro'}, {'id': 18017, 'synset': 'cryptocoryne.n.01', 'name': 'cryptocoryne'}, {'id': 18018, 'synset': 'dracontium.n.01', 'name': 'dracontium'}, {'id': 18019, 'synset': 'golden_pothos.n.01', 'name': 'golden_pothos'}, {'id': 18020, 'synset': 'skunk_cabbage.n.02', 'name': 'skunk_cabbage'}, {'id': 18021, 'synset': 'monstera.n.01', 'name': 'monstera'}, {'id': 18022, 'synset': 'ceriman.n.01', 'name': 'ceriman'}, {'id': 18023, 'synset': 'nephthytis.n.01', 'name': 'nephthytis'}, {'id': 18024, 'synset': 'nephthytis_afzelii.n.01', 'name': 'Nephthytis_afzelii'}, {'id': 18025, 'synset': 'arrow_arum.n.01', 'name': 'arrow_arum'}, {'id': 18026, 'synset': 'green_arrow_arum.n.01', 'name': 'green_arrow_arum'}, {'id': 18027, 'synset': 'philodendron.n.01', 'name': 'philodendron'}, {'id': 18028, 'synset': 'pistia.n.01', 'name': 'pistia'}, {'id': 18029, 'synset': 'pothos.n.01', 'name': 'pothos'}, {'id': 18030, 'synset': 'spathiphyllum.n.01', 'name': 'spathiphyllum'}, {'id': 18031, 'synset': 'skunk_cabbage.n.01', 'name': 'skunk_cabbage'}, {'id': 18032, 'synset': 'yautia.n.01', 'name': 'yautia'}, {'id': 18033, 'synset': 'calla_lily.n.01', 'name': 'calla_lily'}, {'id': 18034, 'synset': 'pink_calla.n.01', 'name': 'pink_calla'}, {'id': 18035, 'synset': 'golden_calla.n.01', 'name': 'golden_calla'}, {'id': 18036, 'synset': 'duckweed.n.01', 'name': 'duckweed'}, {'id': 18037, 'synset': 'common_duckweed.n.01', 'name': 'common_duckweed'}, {'id': 18038, 'synset': 'star-duckweed.n.01', 'name': 'star-duckweed'}, {'id': 18039, 'synset': 'great_duckweed.n.01', 'name': 'great_duckweed'}, {'id': 18040, 'synset': 'watermeal.n.01', 'name': 'watermeal'}, {'id': 18041, 'synset': 'common_wolffia.n.01', 'name': 'common_wolffia'}, {'id': 18042, 'synset': 'aralia.n.01', 'name': 'aralia'}, {'id': 18043, 'synset': 'american_angelica_tree.n.01', 'name': 'American_angelica_tree'}, {'id': 18044, 'synset': 'american_spikenard.n.01', 'name': 'American_spikenard'}, {'id': 18045, 'synset': 'bristly_sarsaparilla.n.01', 'name': 'bristly_sarsaparilla'}, {'id': 18046, 'synset': 'japanese_angelica_tree.n.01', 'name': 'Japanese_angelica_tree'}, {'id': 18047, 'synset': 'chinese_angelica.n.01', 'name': 'Chinese_angelica'}, {'id': 18048, 'synset': 'ivy.n.01', 'name': 'ivy'}, {'id': 18049, 'synset': 'puka.n.02', 'name': 'puka'}, {'id': 18050, 'synset': 'ginseng.n.02', 'name': 'ginseng'}, {'id': 18051, 'synset': 'ginseng.n.01', 'name': 'ginseng'}, {'id': 18052, 'synset': 'umbrella_tree.n.01', 'name': 'umbrella_tree'}, {'id': 18053, 'synset': 'birthwort.n.01', 'name': 'birthwort'}, {'id': 18054, 'synset': "dutchman's-pipe.n.01", 'name': "Dutchman's-pipe"}, {'id': 18055, 'synset': 'virginia_snakeroot.n.01', 'name': 'Virginia_snakeroot'}, {'id': 18056, 'synset': 'canada_ginger.n.01', 'name': 'Canada_ginger'}, {'id': 18057, 'synset': 'heartleaf.n.02', 'name': 'heartleaf'}, {'id': 18058, 'synset': 'heartleaf.n.01', 'name': 'heartleaf'}, {'id': 18059, 'synset': 'asarabacca.n.01', 'name': 'asarabacca'}, {'id': 18060, 'synset': 'caryophyllaceous_plant.n.01', 'name': 'caryophyllaceous_plant'}, {'id': 18061, 'synset': 'corn_cockle.n.01', 'name': 'corn_cockle'}, {'id': 18062, 'synset': 'sandwort.n.03', 'name': 'sandwort'}, {'id': 18063, 'synset': 'mountain_sandwort.n.01', 'name': 'mountain_sandwort'}, {'id': 18064, 'synset': 'pine-barren_sandwort.n.01', 'name': 'pine-barren_sandwort'}, {'id': 18065, 'synset': 'seabeach_sandwort.n.01', 'name': 'seabeach_sandwort'}, {'id': 18066, 'synset': 'rock_sandwort.n.01', 'name': 'rock_sandwort'}, {'id': 18067, 'synset': 'thyme-leaved_sandwort.n.01', 'name': 'thyme-leaved_sandwort'}, {'id': 18068, 'synset': 'mouse-ear_chickweed.n.01', 'name': 'mouse-ear_chickweed'}, {'id': 18069, 'synset': 'snow-in-summer.n.02', 'name': 'snow-in-summer'}, {'id': 18070, 'synset': 'alpine_mouse-ear.n.01', 'name': 'Alpine_mouse-ear'}, {'id': 18071, 'synset': 'pink.n.02', 'name': 'pink'}, {'id': 18072, 'synset': 'sweet_william.n.01', 'name': 'sweet_William'}, {'id': 18073, 'synset': 'china_pink.n.01', 'name': 'china_pink'}, {'id': 18074, 'synset': 'japanese_pink.n.01', 'name': 'Japanese_pink'}, {'id': 18075, 'synset': 'maiden_pink.n.01', 'name': 'maiden_pink'}, {'id': 18076, 'synset': 'cheddar_pink.n.01', 'name': 'cheddar_pink'}, {'id': 18077, 'synset': 'button_pink.n.01', 'name': 'button_pink'}, {'id': 18078, 'synset': 'cottage_pink.n.01', 'name': 'cottage_pink'}, {'id': 18079, 'synset': 'fringed_pink.n.02', 'name': 'fringed_pink'}, {'id': 18080, 'synset': 'drypis.n.01', 'name': 'drypis'}, {'id': 18081, 'synset': "baby's_breath.n.01", 'name': "baby's_breath"}, {'id': 18082, 'synset': 'coral_necklace.n.01', 'name': 'coral_necklace'}, {'id': 18083, 'synset': 'lychnis.n.01', 'name': 'lychnis'}, {'id': 18084, 'synset': 'ragged_robin.n.01', 'name': 'ragged_robin'}, {'id': 18085, 'synset': 'scarlet_lychnis.n.01', 'name': 'scarlet_lychnis'}, {'id': 18086, 'synset': 'mullein_pink.n.01', 'name': 'mullein_pink'}, {'id': 18087, 'synset': 'sandwort.n.02', 'name': 'sandwort'}, {'id': 18088, 'synset': 'sandwort.n.01', 'name': 'sandwort'}, {'id': 18089, 'synset': 'soapwort.n.01', 'name': 'soapwort'}, {'id': 18090, 'synset': 'knawel.n.01', 'name': 'knawel'}, {'id': 18091, 'synset': 'silene.n.01', 'name': 'silene'}, {'id': 18092, 'synset': 'moss_campion.n.01', 'name': 'moss_campion'}, {'id': 18093, 'synset': 'wild_pink.n.02', 'name': 'wild_pink'}, {'id': 18094, 'synset': 'red_campion.n.01', 'name': 'red_campion'}, {'id': 18095, 'synset': 'white_campion.n.01', 'name': 'white_campion'}, {'id': 18096, 'synset': 'fire_pink.n.01', 'name': 'fire_pink'}, {'id': 18097, 'synset': 'bladder_campion.n.01', 'name': 'bladder_campion'}, {'id': 18098, 'synset': 'corn_spurry.n.01', 'name': 'corn_spurry'}, {'id': 18099, 'synset': 'sand_spurry.n.01', 'name': 'sand_spurry'}, {'id': 18100, 'synset': 'chickweed.n.01', 'name': 'chickweed'}, {'id': 18101, 'synset': 'common_chickweed.n.01', 'name': 'common_chickweed'}, {'id': 18102, 'synset': 'cowherb.n.01', 'name': 'cowherb'}, {'id': 18103, 'synset': 'hottentot_fig.n.01', 'name': 'Hottentot_fig'}, {'id': 18104, 'synset': 'livingstone_daisy.n.01', 'name': 'livingstone_daisy'}, {'id': 18105, 'synset': 'fig_marigold.n.01', 'name': 'fig_marigold'}, {'id': 18106, 'synset': 'ice_plant.n.01', 'name': 'ice_plant'}, {'id': 18107, 'synset': 'new_zealand_spinach.n.01', 'name': 'New_Zealand_spinach'}, {'id': 18108, 'synset': 'amaranth.n.02', 'name': 'amaranth'}, {'id': 18109, 'synset': 'amaranth.n.01', 'name': 'amaranth'}, {'id': 18110, 'synset': 'tumbleweed.n.04', 'name': 'tumbleweed'}, {'id': 18111, 'synset': "prince's-feather.n.02", 'name': "prince's-feather"}, {'id': 18112, 'synset': 'pigweed.n.02', 'name': 'pigweed'}, {'id': 18113, 'synset': 'thorny_amaranth.n.01', 'name': 'thorny_amaranth'}, {'id': 18114, 'synset': 'alligator_weed.n.01', 'name': 'alligator_weed'}, {'id': 18115, 'synset': 'cockscomb.n.01', 'name': 'cockscomb'}, {'id': 18116, 'synset': 'cottonweed.n.02', 'name': 'cottonweed'}, {'id': 18117, 'synset': 'globe_amaranth.n.01', 'name': 'globe_amaranth'}, {'id': 18118, 'synset': 'bloodleaf.n.01', 'name': 'bloodleaf'}, {'id': 18119, 'synset': 'saltwort.n.02', 'name': 'saltwort'}, {'id': 18120, 'synset': "lamb's-quarters.n.01", 'name': "lamb's-quarters"}, {'id': 18121, 'synset': 'good-king-henry.n.01', 'name': 'good-king-henry'}, {'id': 18122, 'synset': 'jerusalem_oak.n.01', 'name': 'Jerusalem_oak'}, {'id': 18123, 'synset': 'oak-leaved_goosefoot.n.01', 'name': 'oak-leaved_goosefoot'}, {'id': 18124, 'synset': 'sowbane.n.01', 'name': 'sowbane'}, {'id': 18125, 'synset': 'nettle-leaved_goosefoot.n.01', 'name': 'nettle-leaved_goosefoot'}, {'id': 18126, 'synset': 'red_goosefoot.n.01', 'name': 'red_goosefoot'}, {'id': 18127, 'synset': 'stinking_goosefoot.n.01', 'name': 'stinking_goosefoot'}, {'id': 18128, 'synset': 'orach.n.01', 'name': 'orach'}, {'id': 18129, 'synset': 'saltbush.n.01', 'name': 'saltbush'}, {'id': 18130, 'synset': 'garden_orache.n.01', 'name': 'garden_orache'}, {'id': 18131, 'synset': 'desert_holly.n.01', 'name': 'desert_holly'}, {'id': 18132, 'synset': 'quail_bush.n.01', 'name': 'quail_bush'}, {'id': 18133, 'synset': 'beet.n.01', 'name': 'beet'}, {'id': 18134, 'synset': 'beetroot.n.01', 'name': 'beetroot'}, {'id': 18135, 'synset': 'chard.n.01', 'name': 'chard'}, {'id': 18136, 'synset': 'mangel-wurzel.n.01', 'name': 'mangel-wurzel'}, {'id': 18137, 'synset': 'winged_pigweed.n.01', 'name': 'winged_pigweed'}, {'id': 18138, 'synset': 'halogeton.n.01', 'name': 'halogeton'}, {'id': 18139, 'synset': 'glasswort.n.02', 'name': 'glasswort'}, {'id': 18140, 'synset': 'saltwort.n.01', 'name': 'saltwort'}, {'id': 18141, 'synset': 'russian_thistle.n.01', 'name': 'Russian_thistle'}, {'id': 18142, 'synset': 'greasewood.n.01', 'name': 'greasewood'}, {'id': 18143, 'synset': 'scarlet_musk_flower.n.01', 'name': 'scarlet_musk_flower'}, {'id': 18144, 'synset': 'sand_verbena.n.01', 'name': 'sand_verbena'}, {'id': 18145, 'synset': 'sweet_sand_verbena.n.01', 'name': 'sweet_sand_verbena'}, {'id': 18146, 'synset': 'yellow_sand_verbena.n.01', 'name': 'yellow_sand_verbena'}, {'id': 18147, 'synset': 'beach_pancake.n.01', 'name': 'beach_pancake'}, {'id': 18148, 'synset': 'beach_sand_verbena.n.01', 'name': 'beach_sand_verbena'}, {'id': 18149, 'synset': 'desert_sand_verbena.n.01', 'name': 'desert_sand_verbena'}, {'id': 18150, 'synset': "trailing_four_o'clock.n.01", 'name': "trailing_four_o'clock"}, {'id': 18151, 'synset': 'bougainvillea.n.01', 'name': 'bougainvillea'}, {'id': 18152, 'synset': 'umbrellawort.n.01', 'name': 'umbrellawort'}, {'id': 18153, 'synset': "four_o'clock.n.01", 'name': "four_o'clock"}, {'id': 18154, 'synset': "common_four-o'clock.n.01", 'name': "common_four-o'clock"}, {'id': 18155, 'synset': "california_four_o'clock.n.01", 'name': "California_four_o'clock"}, {'id': 18156, 'synset': "sweet_four_o'clock.n.01", 'name': "sweet_four_o'clock"}, {'id': 18157, 'synset': "desert_four_o'clock.n.01", 'name': "desert_four_o'clock"}, {'id': 18158, 'synset': "mountain_four_o'clock.n.01", 'name': "mountain_four_o'clock"}, {'id': 18159, 'synset': 'cockspur.n.02', 'name': 'cockspur'}, {'id': 18160, 'synset': 'rattail_cactus.n.01', 'name': 'rattail_cactus'}, {'id': 18161, 'synset': 'saguaro.n.01', 'name': 'saguaro'}, {'id': 18162, 'synset': 'night-blooming_cereus.n.03', 'name': 'night-blooming_cereus'}, {'id': 18163, 'synset': 'echinocactus.n.01', 'name': 'echinocactus'}, {'id': 18164, 'synset': 'hedgehog_cactus.n.01', 'name': 'hedgehog_cactus'}, {'id': 18165, 'synset': 'golden_barrel_cactus.n.01', 'name': 'golden_barrel_cactus'}, {'id': 18166, 'synset': 'hedgehog_cereus.n.01', 'name': 'hedgehog_cereus'}, {'id': 18167, 'synset': 'rainbow_cactus.n.01', 'name': 'rainbow_cactus'}, {'id': 18168, 'synset': 'epiphyllum.n.01', 'name': 'epiphyllum'}, {'id': 18169, 'synset': 'barrel_cactus.n.01', 'name': 'barrel_cactus'}, {'id': 18170, 'synset': 'night-blooming_cereus.n.02', 'name': 'night-blooming_cereus'}, {'id': 18171, 'synset': 'chichipe.n.01', 'name': 'chichipe'}, {'id': 18172, 'synset': 'mescal.n.01', 'name': 'mescal'}, {'id': 18173, 'synset': 'mescal_button.n.01', 'name': 'mescal_button'}, {'id': 18174, 'synset': 'mammillaria.n.01', 'name': 'mammillaria'}, {'id': 18175, 'synset': 'feather_ball.n.01', 'name': 'feather_ball'}, {'id': 18176, 'synset': 'garambulla.n.01', 'name': 'garambulla'}, {'id': 18177, 'synset': "knowlton's_cactus.n.01", 'name': "Knowlton's_cactus"}, {'id': 18178, 'synset': 'nopal.n.02', 'name': 'nopal'}, {'id': 18179, 'synset': 'prickly_pear.n.01', 'name': 'prickly_pear'}, {'id': 18180, 'synset': 'cholla.n.01', 'name': 'cholla'}, {'id': 18181, 'synset': 'nopal.n.01', 'name': 'nopal'}, {'id': 18182, 'synset': 'tuna.n.01', 'name': 'tuna'}, {'id': 18183, 'synset': 'barbados_gooseberry.n.01', 'name': 'Barbados_gooseberry'}, {'id': 18184, 'synset': 'mistletoe_cactus.n.01', 'name': 'mistletoe_cactus'}, {'id': 18185, 'synset': 'christmas_cactus.n.01', 'name': 'Christmas_cactus'}, {'id': 18186, 'synset': 'night-blooming_cereus.n.01', 'name': 'night-blooming_cereus'}, {'id': 18187, 'synset': 'crab_cactus.n.01', 'name': 'crab_cactus'}, {'id': 18188, 'synset': 'pokeweed.n.01', 'name': 'pokeweed'}, {'id': 18189, 'synset': 'indian_poke.n.02', 'name': 'Indian_poke'}, {'id': 18190, 'synset': 'poke.n.01', 'name': 'poke'}, {'id': 18191, 'synset': 'ombu.n.01', 'name': 'ombu'}, {'id': 18192, 'synset': 'bloodberry.n.01', 'name': 'bloodberry'}, {'id': 18193, 'synset': 'portulaca.n.01', 'name': 'portulaca'}, {'id': 18194, 'synset': 'rose_moss.n.01', 'name': 'rose_moss'}, {'id': 18195, 'synset': 'common_purslane.n.01', 'name': 'common_purslane'}, {'id': 18196, 'synset': 'rock_purslane.n.01', 'name': 'rock_purslane'}, {'id': 18197, 'synset': 'red_maids.n.01', 'name': 'red_maids'}, {'id': 18198, 'synset': 'carolina_spring_beauty.n.01', 'name': 'Carolina_spring_beauty'}, {'id': 18199, 'synset': 'spring_beauty.n.01', 'name': 'spring_beauty'}, {'id': 18200, 'synset': 'virginia_spring_beauty.n.01', 'name': 'Virginia_spring_beauty'}, {'id': 18201, 'synset': 'siskiyou_lewisia.n.01', 'name': 'siskiyou_lewisia'}, {'id': 18202, 'synset': 'bitterroot.n.01', 'name': 'bitterroot'}, {'id': 18203, 'synset': 'broad-leaved_montia.n.01', 'name': 'broad-leaved_montia'}, {'id': 18204, 'synset': 'blinks.n.01', 'name': 'blinks'}, {'id': 18205, 'synset': 'toad_lily.n.01', 'name': 'toad_lily'}, {'id': 18206, 'synset': 'winter_purslane.n.01', 'name': 'winter_purslane'}, {'id': 18207, 'synset': 'flame_flower.n.02', 'name': 'flame_flower'}, {'id': 18208, 'synset': 'pigmy_talinum.n.01', 'name': 'pigmy_talinum'}, {'id': 18209, 'synset': 'jewels-of-opar.n.01', 'name': 'jewels-of-opar'}, {'id': 18210, 'synset': 'caper.n.01', 'name': 'caper'}, {'id': 18211, 'synset': 'native_pomegranate.n.01', 'name': 'native_pomegranate'}, {'id': 18212, 'synset': 'caper_tree.n.02', 'name': 'caper_tree'}, {'id': 18213, 'synset': 'caper_tree.n.01', 'name': 'caper_tree'}, {'id': 18214, 'synset': 'common_caper.n.01', 'name': 'common_caper'}, {'id': 18215, 'synset': 'spiderflower.n.01', 'name': 'spiderflower'}, {'id': 18216, 'synset': 'rocky_mountain_bee_plant.n.01', 'name': 'Rocky_Mountain_bee_plant'}, {'id': 18217, 'synset': 'clammyweed.n.01', 'name': 'clammyweed'}, {'id': 18218, 'synset': 'crucifer.n.01', 'name': 'crucifer'}, {'id': 18219, 'synset': 'cress.n.01', 'name': 'cress'}, {'id': 18220, 'synset': 'watercress.n.01', 'name': 'watercress'}, {'id': 18221, 'synset': 'stonecress.n.01', 'name': 'stonecress'}, {'id': 18222, 'synset': 'garlic_mustard.n.01', 'name': 'garlic_mustard'}, {'id': 18223, 'synset': 'alyssum.n.01', 'name': 'alyssum'}, {'id': 18224, 'synset': 'rose_of_jericho.n.02', 'name': 'rose_of_Jericho'}, {'id': 18225, 'synset': 'arabidopsis_thaliana.n.01', 'name': 'Arabidopsis_thaliana'}, {'id': 18226, 'synset': 'arabidopsis_lyrata.n.01', 'name': 'Arabidopsis_lyrata'}, {'id': 18227, 'synset': 'rock_cress.n.01', 'name': 'rock_cress'}, {'id': 18228, 'synset': 'sicklepod.n.02', 'name': 'sicklepod'}, {'id': 18229, 'synset': 'tower_mustard.n.01', 'name': 'tower_mustard'}, {'id': 18230, 'synset': 'horseradish.n.01', 'name': 'horseradish'}, {'id': 18231, 'synset': 'winter_cress.n.01', 'name': 'winter_cress'}, {'id': 18232, 'synset': 'yellow_rocket.n.01', 'name': 'yellow_rocket'}, {'id': 18233, 'synset': 'hoary_alison.n.01', 'name': 'hoary_alison'}, {'id': 18234, 'synset': 'buckler_mustard.n.01', 'name': 'buckler_mustard'}, {'id': 18235, 'synset': 'wild_cabbage.n.01', 'name': 'wild_cabbage'}, {'id': 18236, 'synset': 'cabbage.n.03', 'name': 'cabbage'}, {'id': 18237, 'synset': 'head_cabbage.n.01', 'name': 'head_cabbage'}, {'id': 18238, 'synset': 'savoy_cabbage.n.01', 'name': 'savoy_cabbage'}, {'id': 18239, 'synset': 'brussels_sprout.n.01', 'name': 'brussels_sprout'}, {'id': 18240, 'synset': 'cauliflower.n.01', 'name': 'cauliflower'}, {'id': 18241, 'synset': 'collard.n.01', 'name': 'collard'}, {'id': 18242, 'synset': 'kohlrabi.n.01', 'name': 'kohlrabi'}, {'id': 18243, 'synset': 'turnip_plant.n.01', 'name': 'turnip_plant'}, {'id': 18244, 'synset': 'rutabaga.n.02', 'name': 'rutabaga'}, {'id': 18245, 'synset': 'broccoli_raab.n.01', 'name': 'broccoli_raab'}, {'id': 18246, 'synset': 'mustard.n.01', 'name': 'mustard'}, {'id': 18247, 'synset': 'chinese_mustard.n.01', 'name': 'chinese_mustard'}, {'id': 18248, 'synset': 'bok_choy.n.01', 'name': 'bok_choy'}, {'id': 18249, 'synset': 'rape.n.01', 'name': 'rape'}, {'id': 18250, 'synset': 'rapeseed.n.01', 'name': 'rapeseed'}, {'id': 18251, 'synset': "shepherd's_purse.n.01", 'name': "shepherd's_purse"}, {'id': 18252, 'synset': "lady's_smock.n.01", 'name': "lady's_smock"}, {'id': 18253, 'synset': 'coral-root_bittercress.n.01', 'name': 'coral-root_bittercress'}, {'id': 18254, 'synset': 'crinkleroot.n.01', 'name': 'crinkleroot'}, {'id': 18255, 'synset': 'american_watercress.n.01', 'name': 'American_watercress'}, {'id': 18256, 'synset': 'spring_cress.n.01', 'name': 'spring_cress'}, {'id': 18257, 'synset': 'purple_cress.n.01', 'name': 'purple_cress'}, {'id': 18258, 'synset': 'wallflower.n.02', 'name': 'wallflower'}, {'id': 18259, 'synset': 'prairie_rocket.n.02', 'name': 'prairie_rocket'}, {'id': 18260, 'synset': 'scurvy_grass.n.01', 'name': 'scurvy_grass'}, {'id': 18261, 'synset': 'sea_kale.n.01', 'name': 'sea_kale'}, {'id': 18262, 'synset': 'tansy_mustard.n.01', 'name': 'tansy_mustard'}, {'id': 18263, 'synset': 'draba.n.01', 'name': 'draba'}, {'id': 18264, 'synset': 'wallflower.n.01', 'name': 'wallflower'}, {'id': 18265, 'synset': 'prairie_rocket.n.01', 'name': 'prairie_rocket'}, {'id': 18266, 'synset': 'siberian_wall_flower.n.01', 'name': 'Siberian_wall_flower'}, {'id': 18267, 'synset': 'western_wall_flower.n.01', 'name': 'western_wall_flower'}, {'id': 18268, 'synset': 'wormseed_mustard.n.01', 'name': 'wormseed_mustard'}, {'id': 18269, 'synset': 'heliophila.n.01', 'name': 'heliophila'}, {'id': 18270, 'synset': 'damask_violet.n.01', 'name': 'damask_violet'}, {'id': 18271, 'synset': 'tansy-leaved_rocket.n.01', 'name': 'tansy-leaved_rocket'}, {'id': 18272, 'synset': 'candytuft.n.01', 'name': 'candytuft'}, {'id': 18273, 'synset': 'woad.n.02', 'name': 'woad'}, {'id': 18274, 'synset': "dyer's_woad.n.01", 'name': "dyer's_woad"}, {'id': 18275, 'synset': 'bladderpod.n.04', 'name': 'bladderpod'}, {'id': 18276, 'synset': 'sweet_alyssum.n.01', 'name': 'sweet_alyssum'}, {'id': 18277, 'synset': 'malcolm_stock.n.01', 'name': 'Malcolm_stock'}, {'id': 18278, 'synset': 'virginian_stock.n.01', 'name': 'Virginian_stock'}, {'id': 18279, 'synset': 'stock.n.12', 'name': 'stock'}, {'id': 18280, 'synset': 'brompton_stock.n.01', 'name': 'brompton_stock'}, {'id': 18281, 'synset': 'bladderpod.n.03', 'name': 'bladderpod'}, {'id': 18282, 'synset': 'chamois_cress.n.01', 'name': 'chamois_cress'}, {'id': 18283, 'synset': 'radish_plant.n.01', 'name': 'radish_plant'}, {'id': 18284, 'synset': 'jointed_charlock.n.01', 'name': 'jointed_charlock'}, {'id': 18285, 'synset': 'radish.n.04', 'name': 'radish'}, {'id': 18286, 'synset': 'radish.n.02', 'name': 'radish'}, {'id': 18287, 'synset': 'marsh_cress.n.01', 'name': 'marsh_cress'}, {'id': 18288, 'synset': 'great_yellowcress.n.01', 'name': 'great_yellowcress'}, {'id': 18289, 'synset': 'schizopetalon.n.01', 'name': 'schizopetalon'}, {'id': 18290, 'synset': 'field_mustard.n.01', 'name': 'field_mustard'}, {'id': 18291, 'synset': 'hedge_mustard.n.01', 'name': 'hedge_mustard'}, {'id': 18292, 'synset': 'desert_plume.n.01', 'name': 'desert_plume'}, {'id': 18293, 'synset': 'pennycress.n.01', 'name': 'pennycress'}, {'id': 18294, 'synset': 'field_pennycress.n.01', 'name': 'field_pennycress'}, {'id': 18295, 'synset': 'fringepod.n.01', 'name': 'fringepod'}, {'id': 18296, 'synset': 'bladderpod.n.02', 'name': 'bladderpod'}, {'id': 18297, 'synset': 'wasabi.n.01', 'name': 'wasabi'}, {'id': 18298, 'synset': 'poppy.n.01', 'name': 'poppy'}, {'id': 18299, 'synset': 'iceland_poppy.n.02', 'name': 'Iceland_poppy'}, {'id': 18300, 'synset': 'western_poppy.n.01', 'name': 'western_poppy'}, {'id': 18301, 'synset': 'prickly_poppy.n.02', 'name': 'prickly_poppy'}, {'id': 18302, 'synset': 'iceland_poppy.n.01', 'name': 'Iceland_poppy'}, {'id': 18303, 'synset': 'oriental_poppy.n.01', 'name': 'oriental_poppy'}, {'id': 18304, 'synset': 'corn_poppy.n.01', 'name': 'corn_poppy'}, {'id': 18305, 'synset': 'opium_poppy.n.01', 'name': 'opium_poppy'}, {'id': 18306, 'synset': 'prickly_poppy.n.01', 'name': 'prickly_poppy'}, {'id': 18307, 'synset': 'mexican_poppy.n.01', 'name': 'Mexican_poppy'}, {'id': 18308, 'synset': 'bocconia.n.02', 'name': 'bocconia'}, {'id': 18309, 'synset': 'celandine.n.02', 'name': 'celandine'}, {'id': 18310, 'synset': 'corydalis.n.01', 'name': 'corydalis'}, {'id': 18311, 'synset': 'climbing_corydalis.n.01', 'name': 'climbing_corydalis'}, {'id': 18312, 'synset': 'california_poppy.n.01', 'name': 'California_poppy'}, {'id': 18313, 'synset': 'horn_poppy.n.01', 'name': 'horn_poppy'}, {'id': 18314, 'synset': 'golden_cup.n.01', 'name': 'golden_cup'}, {'id': 18315, 'synset': 'plume_poppy.n.01', 'name': 'plume_poppy'}, {'id': 18316, 'synset': 'blue_poppy.n.01', 'name': 'blue_poppy'}, {'id': 18317, 'synset': 'welsh_poppy.n.01', 'name': 'Welsh_poppy'}, {'id': 18318, 'synset': 'creamcups.n.01', 'name': 'creamcups'}, {'id': 18319, 'synset': 'matilija_poppy.n.01', 'name': 'matilija_poppy'}, {'id': 18320, 'synset': 'wind_poppy.n.01', 'name': 'wind_poppy'}, {'id': 18321, 'synset': 'celandine_poppy.n.01', 'name': 'celandine_poppy'}, {'id': 18322, 'synset': 'climbing_fumitory.n.01', 'name': 'climbing_fumitory'}, {'id': 18323, 'synset': 'bleeding_heart.n.01', 'name': 'bleeding_heart'}, {'id': 18324, 'synset': "dutchman's_breeches.n.01", 'name': "Dutchman's_breeches"}, {'id': 18325, 'synset': 'squirrel_corn.n.01', 'name': 'squirrel_corn'}, {'id': 18326, 'synset': 'composite.n.02', 'name': 'composite'}, {'id': 18327, 'synset': 'compass_plant.n.02', 'name': 'compass_plant'}, {'id': 18328, 'synset': 'everlasting.n.01', 'name': 'everlasting'}, {'id': 18329, 'synset': 'achillea.n.01', 'name': 'achillea'}, {'id': 18330, 'synset': 'yarrow.n.01', 'name': 'yarrow'}, {'id': 18331, 'synset': 'pink-and-white_everlasting.n.01', 'name': 'pink-and-white_everlasting'}, {'id': 18332, 'synset': 'white_snakeroot.n.01', 'name': 'white_snakeroot'}, {'id': 18333, 'synset': 'ageratum.n.02', 'name': 'ageratum'}, {'id': 18334, 'synset': 'common_ageratum.n.01', 'name': 'common_ageratum'}, {'id': 18335, 'synset': 'sweet_sultan.n.03', 'name': 'sweet_sultan'}, {'id': 18336, 'synset': 'ragweed.n.02', 'name': 'ragweed'}, {'id': 18337, 'synset': 'common_ragweed.n.01', 'name': 'common_ragweed'}, {'id': 18338, 'synset': 'great_ragweed.n.01', 'name': 'great_ragweed'}, {'id': 18339, 'synset': 'western_ragweed.n.01', 'name': 'western_ragweed'}, {'id': 18340, 'synset': 'ammobium.n.01', 'name': 'ammobium'}, {'id': 18341, 'synset': 'winged_everlasting.n.01', 'name': 'winged_everlasting'}, {'id': 18342, 'synset': 'pellitory.n.02', 'name': 'pellitory'}, {'id': 18343, 'synset': 'pearly_everlasting.n.01', 'name': 'pearly_everlasting'}, {'id': 18344, 'synset': 'andryala.n.01', 'name': 'andryala'}, {'id': 18345, 'synset': 'plantain-leaved_pussytoes.n.01', 'name': 'plantain-leaved_pussytoes'}, {'id': 18346, 'synset': 'field_pussytoes.n.01', 'name': 'field_pussytoes'}, {'id': 18347, 'synset': 'solitary_pussytoes.n.01', 'name': 'solitary_pussytoes'}, {'id': 18348, 'synset': 'mountain_everlasting.n.01', 'name': 'mountain_everlasting'}, {'id': 18349, 'synset': 'mayweed.n.01', 'name': 'mayweed'}, {'id': 18350, 'synset': 'yellow_chamomile.n.01', 'name': 'yellow_chamomile'}, {'id': 18351, 'synset': 'corn_chamomile.n.01', 'name': 'corn_chamomile'}, {'id': 18352, 'synset': 'woolly_daisy.n.01', 'name': 'woolly_daisy'}, {'id': 18353, 'synset': 'burdock.n.01', 'name': 'burdock'}, {'id': 18354, 'synset': 'great_burdock.n.01', 'name': 'great_burdock'}, {'id': 18355, 'synset': 'african_daisy.n.03', 'name': 'African_daisy'}, {'id': 18356, 'synset': 'blue-eyed_african_daisy.n.01', 'name': 'blue-eyed_African_daisy'}, {'id': 18357, 'synset': 'marguerite.n.02', 'name': 'marguerite'}, {'id': 18358, 'synset': 'silversword.n.01', 'name': 'silversword'}, {'id': 18359, 'synset': 'arnica.n.02', 'name': 'arnica'}, {'id': 18360, 'synset': 'heartleaf_arnica.n.01', 'name': 'heartleaf_arnica'}, {'id': 18361, 'synset': 'arnica_montana.n.01', 'name': 'Arnica_montana'}, {'id': 18362, 'synset': 'lamb_succory.n.01', 'name': 'lamb_succory'}, {'id': 18363, 'synset': 'artemisia.n.01', 'name': 'artemisia'}, {'id': 18364, 'synset': 'mugwort.n.01', 'name': 'mugwort'}, {'id': 18365, 'synset': 'sweet_wormwood.n.01', 'name': 'sweet_wormwood'}, {'id': 18366, 'synset': 'field_wormwood.n.01', 'name': 'field_wormwood'}, {'id': 18367, 'synset': 'tarragon.n.01', 'name': 'tarragon'}, {'id': 18368, 'synset': 'sand_sage.n.01', 'name': 'sand_sage'}, {'id': 18369, 'synset': 'wormwood_sage.n.01', 'name': 'wormwood_sage'}, {'id': 18370, 'synset': 'western_mugwort.n.01', 'name': 'western_mugwort'}, {'id': 18371, 'synset': 'roman_wormwood.n.01', 'name': 'Roman_wormwood'}, {'id': 18372, 'synset': 'bud_brush.n.01', 'name': 'bud_brush'}, {'id': 18373, 'synset': 'common_mugwort.n.01', 'name': 'common_mugwort'}, {'id': 18374, 'synset': 'aster.n.01', 'name': 'aster'}, {'id': 18375, 'synset': 'wood_aster.n.01', 'name': 'wood_aster'}, {'id': 18376, 'synset': 'whorled_aster.n.01', 'name': 'whorled_aster'}, {'id': 18377, 'synset': 'heath_aster.n.02', 'name': 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18391, 'synset': 'prairie_aster.n.01', 'name': 'prairie_aster'}, {'id': 18392, 'synset': 'annual_salt-marsh_aster.n.01', 'name': 'annual_salt-marsh_aster'}, {'id': 18393, 'synset': 'aromatic_aster.n.01', 'name': 'aromatic_aster'}, {'id': 18394, 'synset': 'arrow_leaved_aster.n.01', 'name': 'arrow_leaved_aster'}, {'id': 18395, 'synset': 'azure_aster.n.01', 'name': 'azure_aster'}, {'id': 18396, 'synset': 'bog_aster.n.01', 'name': 'bog_aster'}, {'id': 18397, 'synset': 'crooked-stemmed_aster.n.01', 'name': 'crooked-stemmed_aster'}, {'id': 18398, 'synset': 'eastern_silvery_aster.n.01', 'name': 'Eastern_silvery_aster'}, {'id': 18399, 'synset': 'flat-topped_white_aster.n.01', 'name': 'flat-topped_white_aster'}, {'id': 18400, 'synset': 'late_purple_aster.n.01', 'name': 'late_purple_aster'}, {'id': 18401, 'synset': 'panicled_aster.n.01', 'name': 'panicled_aster'}, {'id': 18402, 'synset': 'perennial_salt_marsh_aster.n.01', 'name': 'perennial_salt_marsh_aster'}, {'id': 18403, 'synset': 'purple-stemmed_aster.n.01', 'name': 'purple-stemmed_aster'}, {'id': 18404, 'synset': 'rough-leaved_aster.n.01', 'name': 'rough-leaved_aster'}, {'id': 18405, 'synset': 'rush_aster.n.01', 'name': 'rush_aster'}, {'id': 18406, 'synset': "schreiber's_aster.n.01", 'name': "Schreiber's_aster"}, {'id': 18407, 'synset': 'small_white_aster.n.01', 'name': 'small_white_aster'}, {'id': 18408, 'synset': 'smooth_aster.n.01', 'name': 'smooth_aster'}, {'id': 18409, 'synset': 'southern_aster.n.01', 'name': 'southern_aster'}, {'id': 18410, 'synset': 'starved_aster.n.01', 'name': 'starved_aster'}, {'id': 18411, 'synset': "tradescant's_aster.n.01", 'name': "tradescant's_aster"}, {'id': 18412, 'synset': 'wavy-leaved_aster.n.01', 'name': 'wavy-leaved_aster'}, {'id': 18413, 'synset': 'western_silvery_aster.n.01', 'name': 'Western_silvery_aster'}, {'id': 18414, 'synset': 'willow_aster.n.01', 'name': 'willow_aster'}, {'id': 18415, 'synset': 'ayapana.n.01', 'name': 'ayapana'}, {'id': 18416, 'synset': 'mule_fat.n.01', 'name': 'mule_fat'}, {'id': 18417, 'synset': 'balsamroot.n.01', 'name': 'balsamroot'}, {'id': 18418, 'synset': 'daisy.n.01', 'name': 'daisy'}, {'id': 18419, 'synset': 'common_daisy.n.01', 'name': 'common_daisy'}, {'id': 18420, 'synset': 'bur_marigold.n.01', 'name': 'bur_marigold'}, {'id': 18421, 'synset': 'spanish_needles.n.02', 'name': 'Spanish_needles'}, {'id': 18422, 'synset': 'tickseed_sunflower.n.01', 'name': 'tickseed_sunflower'}, {'id': 18423, 'synset': 'european_beggar-ticks.n.01', 'name': 'European_beggar-ticks'}, {'id': 18424, 'synset': 'slender_knapweed.n.01', 'name': 'slender_knapweed'}, {'id': 18425, 'synset': 'false_chamomile.n.01', 'name': 'false_chamomile'}, {'id': 18426, 'synset': 'swan_river_daisy.n.01', 'name': 'Swan_River_daisy'}, {'id': 18427, 'synset': 'woodland_oxeye.n.01', 'name': 'woodland_oxeye'}, {'id': 18428, 'synset': 'indian_plantain.n.01', 'name': 'Indian_plantain'}, {'id': 18429, 'synset': 'calendula.n.01', 'name': 'calendula'}, {'id': 18430, 'synset': 'common_marigold.n.01', 'name': 'common_marigold'}, {'id': 18431, 'synset': 'china_aster.n.01', 'name': 'China_aster'}, {'id': 18432, 'synset': 'thistle.n.01', 'name': 'thistle'}, {'id': 18433, 'synset': 'welted_thistle.n.01', 'name': 'welted_thistle'}, {'id': 18434, 'synset': 'musk_thistle.n.01', 'name': 'musk_thistle'}, {'id': 18435, 'synset': 'carline_thistle.n.01', 'name': 'carline_thistle'}, {'id': 18436, 'synset': 'stemless_carline_thistle.n.01', 'name': 'stemless_carline_thistle'}, {'id': 18437, 'synset': 'common_carline_thistle.n.01', 'name': 'common_carline_thistle'}, {'id': 18438, 'synset': 'safflower.n.01', 'name': 'safflower'}, {'id': 18439, 'synset': 'safflower_seed.n.01', 'name': 'safflower_seed'}, {'id': 18440, 'synset': 'catananche.n.01', 'name': 'catananche'}, {'id': 18441, 'synset': 'blue_succory.n.01', 'name': 'blue_succory'}, {'id': 18442, 'synset': 'centaury.n.02', 'name': 'centaury'}, {'id': 18443, 'synset': 'dusty_miller.n.03', 'name': 'dusty_miller'}, {'id': 18444, 'synset': 'cornflower.n.02', 'name': 'cornflower'}, {'id': 18445, 'synset': 'star-thistle.n.01', 'name': 'star-thistle'}, {'id': 18446, 'synset': 'knapweed.n.01', 'name': 'knapweed'}, {'id': 18447, 'synset': 'sweet_sultan.n.02', 'name': 'sweet_sultan'}, {'id': 18448, 'synset': 'great_knapweed.n.01', 'name': 'great_knapweed'}, {'id': 18449, 'synset': "barnaby's_thistle.n.01", 'name': "Barnaby's_thistle"}, {'id': 18450, 'synset': 'chamomile.n.01', 'name': 'chamomile'}, {'id': 18451, 'synset': 'chaenactis.n.01', 'name': 'chaenactis'}, {'id': 18452, 'synset': 'chrysanthemum.n.02', 'name': 'chrysanthemum'}, {'id': 18453, 'synset': 'corn_marigold.n.01', 'name': 'corn_marigold'}, {'id': 18454, 'synset': 'crown_daisy.n.01', 'name': 'crown_daisy'}, {'id': 18455, 'synset': 'chop-suey_greens.n.01', 'name': 'chop-suey_greens'}, {'id': 18456, 'synset': 'golden_aster.n.01', 'name': 'golden_aster'}, {'id': 18457, 'synset': 'maryland_golden_aster.n.01', 'name': 'Maryland_golden_aster'}, {'id': 18458, 'synset': 'goldenbush.n.02', 'name': 'goldenbush'}, {'id': 18459, 'synset': 'rabbit_brush.n.01', 'name': 'rabbit_brush'}, {'id': 18460, 'synset': 'chicory.n.02', 'name': 'chicory'}, {'id': 18461, 'synset': 'endive.n.01', 'name': 'endive'}, {'id': 18462, 'synset': 'chicory.n.01', 'name': 'chicory'}, {'id': 18463, 'synset': 'plume_thistle.n.01', 'name': 'plume_thistle'}, {'id': 18464, 'synset': 'canada_thistle.n.01', 'name': 'Canada_thistle'}, {'id': 18465, 'synset': 'field_thistle.n.01', 'name': 'field_thistle'}, {'id': 18466, 'synset': 'woolly_thistle.n.02', 'name': 'woolly_thistle'}, {'id': 18467, 'synset': 'european_woolly_thistle.n.01', 'name': 'European_woolly_thistle'}, {'id': 18468, 'synset': 'melancholy_thistle.n.01', 'name': 'melancholy_thistle'}, {'id': 18469, 'synset': 'brook_thistle.n.01', 'name': 'brook_thistle'}, {'id': 18470, 'synset': 'bull_thistle.n.01', 'name': 'bull_thistle'}, {'id': 18471, 'synset': 'blessed_thistle.n.02', 'name': 'blessed_thistle'}, {'id': 18472, 'synset': 'mistflower.n.01', 'name': 'mistflower'}, {'id': 18473, 'synset': 'horseweed.n.02', 'name': 'horseweed'}, {'id': 18474, 'synset': 'coreopsis.n.01', 'name': 'coreopsis'}, {'id': 18475, 'synset': 'giant_coreopsis.n.01', 'name': 'giant_coreopsis'}, {'id': 18476, 'synset': 'sea_dahlia.n.01', 'name': 'sea_dahlia'}, {'id': 18477, 'synset': 'calliopsis.n.01', 'name': 'calliopsis'}, {'id': 18478, 'synset': 'cosmos.n.02', 'name': 'cosmos'}, {'id': 18479, 'synset': 'brass_buttons.n.01', 'name': 'brass_buttons'}, {'id': 18480, 'synset': 'billy_buttons.n.01', 'name': 'billy_buttons'}, {'id': 18481, 'synset': "hawk's-beard.n.01", 'name': "hawk's-beard"}, {'id': 18482, 'synset': 'artichoke.n.01', 'name': 'artichoke'}, {'id': 18483, 'synset': 'cardoon.n.01', 'name': 'cardoon'}, {'id': 18484, 'synset': 'dahlia.n.01', 'name': 'dahlia'}, {'id': 18485, 'synset': 'german_ivy.n.01', 'name': 'German_ivy'}, {'id': 18486, 'synset': "florist's_chrysanthemum.n.01", 'name': "florist's_chrysanthemum"}, {'id': 18487, 'synset': 'cape_marigold.n.01', 'name': 'cape_marigold'}, {'id': 18488, 'synset': "leopard's-bane.n.01", 'name': "leopard's-bane"}, {'id': 18489, 'synset': 'coneflower.n.03', 'name': 'coneflower'}, {'id': 18490, 'synset': 'globe_thistle.n.01', 'name': 'globe_thistle'}, {'id': 18491, 'synset': "elephant's-foot.n.02", 'name': "elephant's-foot"}, {'id': 18492, 'synset': 'tassel_flower.n.01', 'name': 'tassel_flower'}, {'id': 18493, 'synset': 'brittlebush.n.01', 'name': 'brittlebush'}, {'id': 18494, 'synset': 'sunray.n.02', 'name': 'sunray'}, {'id': 18495, 'synset': 'engelmannia.n.01', 'name': 'engelmannia'}, {'id': 18496, 'synset': 'fireweed.n.02', 'name': 'fireweed'}, {'id': 18497, 'synset': 'fleabane.n.02', 'name': 'fleabane'}, {'id': 18498, 'synset': 'blue_fleabane.n.01', 'name': 'blue_fleabane'}, {'id': 18499, 'synset': 'daisy_fleabane.n.01', 'name': 'daisy_fleabane'}, {'id': 18500, 'synset': 'orange_daisy.n.01', 'name': 'orange_daisy'}, {'id': 18501, 'synset': 'spreading_fleabane.n.01', 'name': 'spreading_fleabane'}, {'id': 18502, 'synset': 'seaside_daisy.n.01', 'name': 'seaside_daisy'}, {'id': 18503, 'synset': 'philadelphia_fleabane.n.01', 'name': 'Philadelphia_fleabane'}, {'id': 18504, 'synset': "robin's_plantain.n.01", 'name': "robin's_plantain"}, {'id': 18505, 'synset': 'showy_daisy.n.01', 'name': 'showy_daisy'}, {'id': 18506, 'synset': 'woolly_sunflower.n.01', 'name': 'woolly_sunflower'}, {'id': 18507, 'synset': 'golden_yarrow.n.01', 'name': 'golden_yarrow'}, {'id': 18508, 'synset': 'dog_fennel.n.01', 'name': 'dog_fennel'}, {'id': 18509, 'synset': 'joe-pye_weed.n.02', 'name': 'Joe-Pye_weed'}, {'id': 18510, 'synset': 'boneset.n.02', 'name': 'boneset'}, {'id': 18511, 'synset': 'joe-pye_weed.n.01', 'name': 'Joe-Pye_weed'}, {'id': 18512, 'synset': 'blue_daisy.n.01', 'name': 'blue_daisy'}, {'id': 18513, 'synset': 'kingfisher_daisy.n.01', 'name': 'kingfisher_daisy'}, {'id': 18514, 'synset': 'cotton_rose.n.02', 'name': 'cotton_rose'}, {'id': 18515, 'synset': 'herba_impia.n.01', 'name': 'herba_impia'}, {'id': 18516, 'synset': 'gaillardia.n.01', 'name': 'gaillardia'}, {'id': 18517, 'synset': 'gazania.n.01', 'name': 'gazania'}, {'id': 18518, 'synset': 'treasure_flower.n.01', 'name': 'treasure_flower'}, {'id': 18519, 'synset': 'african_daisy.n.02', 'name': 'African_daisy'}, {'id': 18520, 'synset': 'barberton_daisy.n.01', 'name': 'Barberton_daisy'}, {'id': 18521, 'synset': 'desert_sunflower.n.01', 'name': 'desert_sunflower'}, {'id': 18522, 'synset': 'cudweed.n.01', 'name': 'cudweed'}, {'id': 18523, 'synset': 'chafeweed.n.01', 'name': 'chafeweed'}, {'id': 18524, 'synset': 'gumweed.n.01', 'name': 'gumweed'}, {'id': 18525, 'synset': 'grindelia_robusta.n.01', 'name': 'Grindelia_robusta'}, {'id': 18526, 'synset': 'curlycup_gumweed.n.01', 'name': 'curlycup_gumweed'}, {'id': 18527, 'synset': 'little-head_snakeweed.n.01', 'name': 'little-head_snakeweed'}, {'id': 18528, 'synset': 'rabbitweed.n.01', 'name': 'rabbitweed'}, {'id': 18529, 'synset': 'broomweed.n.01', 'name': 'broomweed'}, {'id': 18530, 'synset': 'velvet_plant.n.02', 'name': 'velvet_plant'}, {'id': 18531, 'synset': 'goldenbush.n.01', 'name': 'goldenbush'}, {'id': 18532, 'synset': 'camphor_daisy.n.01', 'name': 'camphor_daisy'}, {'id': 18533, 'synset': 'yellow_spiny_daisy.n.01', 'name': 'yellow_spiny_daisy'}, {'id': 18534, 'synset': 'hoary_golden_bush.n.01', 'name': 'hoary_golden_bush'}, {'id': 18535, 'synset': 'sneezeweed.n.01', 'name': 'sneezeweed'}, {'id': 18536, 'synset': 'orange_sneezeweed.n.01', 'name': 'orange_sneezeweed'}, {'id': 18537, 'synset': 'rosilla.n.01', 'name': 'rosilla'}, {'id': 18538, 'synset': 'swamp_sunflower.n.01', 'name': 'swamp_sunflower'}, {'id': 18539, 'synset': 'common_sunflower.n.01', 'name': 'common_sunflower'}, {'id': 18540, 'synset': 'giant_sunflower.n.01', 'name': 'giant_sunflower'}, {'id': 18541, 'synset': 'showy_sunflower.n.01', 'name': 'showy_sunflower'}, {'id': 18542, 'synset': "maximilian's_sunflower.n.01", 'name': "Maximilian's_sunflower"}, {'id': 18543, 'synset': 'prairie_sunflower.n.01', 'name': 'prairie_sunflower'}, {'id': 18544, 'synset': 'jerusalem_artichoke.n.02', 'name': 'Jerusalem_artichoke'}, {'id': 18545, 'synset': 'jerusalem_artichoke.n.01', 'name': 'Jerusalem_artichoke'}, {'id': 18546, 'synset': 'strawflower.n.03', 'name': 'strawflower'}, {'id': 18547, 'synset': 'heliopsis.n.01', 'name': 'heliopsis'}, {'id': 18548, 'synset': 'strawflower.n.02', 'name': 'strawflower'}, {'id': 18549, 'synset': 'hairy_golden_aster.n.01', 'name': 'hairy_golden_aster'}, {'id': 18550, 'synset': 'hawkweed.n.02', 'name': 'hawkweed'}, {'id': 18551, 'synset': 'rattlesnake_weed.n.01', 'name': 'rattlesnake_weed'}, {'id': 18552, 'synset': 'alpine_coltsfoot.n.01', 'name': 'alpine_coltsfoot'}, {'id': 18553, 'synset': 'alpine_gold.n.01', 'name': 'alpine_gold'}, {'id': 18554, 'synset': 'dwarf_hulsea.n.01', 'name': 'dwarf_hulsea'}, {'id': 18555, 'synset': "cat's-ear.n.02", 'name': "cat's-ear"}, {'id': 18556, 'synset': 'inula.n.01', 'name': 'inula'}, {'id': 18557, 'synset': 'marsh_elder.n.01', 'name': 'marsh_elder'}, {'id': 18558, 'synset': 'burweed_marsh_elder.n.01', 'name': 'burweed_marsh_elder'}, {'id': 18559, 'synset': 'krigia.n.01', 'name': 'krigia'}, {'id': 18560, 'synset': 'dwarf_dandelion.n.01', 'name': 'dwarf_dandelion'}, {'id': 18561, 'synset': 'garden_lettuce.n.01', 'name': 'garden_lettuce'}, {'id': 18562, 'synset': 'cos_lettuce.n.01', 'name': 'cos_lettuce'}, {'id': 18563, 'synset': 'leaf_lettuce.n.01', 'name': 'leaf_lettuce'}, {'id': 18564, 'synset': 'celtuce.n.01', 'name': 'celtuce'}, {'id': 18565, 'synset': 'prickly_lettuce.n.01', 'name': 'prickly_lettuce'}, {'id': 18566, 'synset': 'goldfields.n.01', 'name': 'goldfields'}, {'id': 18567, 'synset': 'tidytips.n.01', 'name': 'tidytips'}, {'id': 18568, 'synset': 'hawkbit.n.01', 'name': 'hawkbit'}, {'id': 18569, 'synset': 'fall_dandelion.n.01', 'name': 'fall_dandelion'}, {'id': 18570, 'synset': 'edelweiss.n.01', 'name': 'edelweiss'}, {'id': 18571, 'synset': 'oxeye_daisy.n.02', 'name': 'oxeye_daisy'}, {'id': 18572, 'synset': 'oxeye_daisy.n.01', 'name': 'oxeye_daisy'}, {'id': 18573, 'synset': 'shasta_daisy.n.01', 'name': 'shasta_daisy'}, {'id': 18574, 'synset': 'pyrenees_daisy.n.01', 'name': 'Pyrenees_daisy'}, {'id': 18575, 'synset': 'north_island_edelweiss.n.01', 'name': 'north_island_edelweiss'}, {'id': 18576, 'synset': 'blazing_star.n.02', 'name': 'blazing_star'}, {'id': 18577, 'synset': 'dotted_gayfeather.n.01', 'name': 'dotted_gayfeather'}, {'id': 18578, 'synset': 'dense_blazing_star.n.01', 'name': 'dense_blazing_star'}, {'id': 18579, 'synset': 'texas_star.n.02', 'name': 'Texas_star'}, {'id': 18580, 'synset': 'african_daisy.n.01', 'name': 'African_daisy'}, {'id': 18581, 'synset': 'tahoka_daisy.n.01', 'name': 'tahoka_daisy'}, {'id': 18582, 'synset': 'sticky_aster.n.01', 'name': 'sticky_aster'}, {'id': 18583, 'synset': 'mojave_aster.n.01', 'name': 'Mojave_aster'}, {'id': 18584, 'synset': 'tarweed.n.01', 'name': 'tarweed'}, {'id': 18585, 'synset': 'sweet_false_chamomile.n.01', 'name': 'sweet_false_chamomile'}, {'id': 18586, 'synset': 'pineapple_weed.n.01', 'name': 'pineapple_weed'}, {'id': 18587, 'synset': 'climbing_hempweed.n.01', 'name': 'climbing_hempweed'}, {'id': 18588, 'synset': 'mutisia.n.01', 'name': 'mutisia'}, {'id': 18589, 'synset': 'rattlesnake_root.n.02', 'name': 'rattlesnake_root'}, {'id': 18590, 'synset': 'white_lettuce.n.01', 'name': 'white_lettuce'}, {'id': 18591, 'synset': 'daisybush.n.01', 'name': 'daisybush'}, {'id': 18592, 'synset': 'new_zealand_daisybush.n.01', 'name': 'New_Zealand_daisybush'}, {'id': 18593, 'synset': 'cotton_thistle.n.01', 'name': 'cotton_thistle'}, {'id': 18594, 'synset': 'othonna.n.01', 'name': 'othonna'}, {'id': 18595, 'synset': 'cascade_everlasting.n.01', 'name': 'cascade_everlasting'}, {'id': 18596, 'synset': 'butterweed.n.02', 'name': 'butterweed'}, {'id': 18597, 'synset': 'american_feverfew.n.01', 'name': 'American_feverfew'}, {'id': 18598, 'synset': 'cineraria.n.01', 'name': 'cineraria'}, {'id': 18599, 'synset': "florest's_cineraria.n.01", 'name': "florest's_cineraria"}, {'id': 18600, 'synset': 'butterbur.n.01', 'name': 'butterbur'}, {'id': 18601, 'synset': 'winter_heliotrope.n.01', 'name': 'winter_heliotrope'}, {'id': 18602, 'synset': 'sweet_coltsfoot.n.01', 'name': 'sweet_coltsfoot'}, {'id': 18603, 'synset': 'oxtongue.n.01', 'name': 'oxtongue'}, {'id': 18604, 'synset': 'hawkweed.n.01', 'name': 'hawkweed'}, {'id': 18605, 'synset': 'mouse-ear_hawkweed.n.01', 'name': 'mouse-ear_hawkweed'}, {'id': 18606, 'synset': 'stevia.n.02', 'name': 'stevia'}, {'id': 18607, 'synset': 'rattlesnake_root.n.01', 'name': 'rattlesnake_root'}, {'id': 18608, 'synset': 'fleabane.n.01', 'name': 'fleabane'}, {'id': 18609, 'synset': 'sheep_plant.n.01', 'name': 'sheep_plant'}, {'id': 18610, 'synset': 'coneflower.n.02', 'name': 'coneflower'}, {'id': 18611, 'synset': 'mexican_hat.n.01', 'name': 'Mexican_hat'}, {'id': 18612, 'synset': 'long-head_coneflower.n.01', 'name': 'long-head_coneflower'}, {'id': 18613, 'synset': 'prairie_coneflower.n.01', 'name': 'prairie_coneflower'}, {'id': 18614, 'synset': 'swan_river_everlasting.n.01', 'name': 'Swan_River_everlasting'}, {'id': 18615, 'synset': 'coneflower.n.01', 'name': 'coneflower'}, {'id': 18616, 'synset': 'black-eyed_susan.n.03', 'name': 'black-eyed_Susan'}, {'id': 18617, 'synset': 'cutleaved_coneflower.n.01', 'name': 'cutleaved_coneflower'}, {'id': 18618, 'synset': 'golden_glow.n.01', 'name': 'golden_glow'}, {'id': 18619, 'synset': 'lavender_cotton.n.01', 'name': 'lavender_cotton'}, {'id': 18620, 'synset': 'creeping_zinnia.n.01', 'name': 'creeping_zinnia'}, {'id': 18621, 'synset': 'golden_thistle.n.01', 'name': 'golden_thistle'}, {'id': 18622, 'synset': 'spanish_oyster_plant.n.01', 'name': 'Spanish_oyster_plant'}, {'id': 18623, 'synset': 'nodding_groundsel.n.01', 'name': 'nodding_groundsel'}, {'id': 18624, 'synset': 'dusty_miller.n.02', 'name': 'dusty_miller'}, {'id': 18625, 'synset': 'butterweed.n.01', 'name': 'butterweed'}, {'id': 18626, 'synset': 'ragwort.n.01', 'name': 'ragwort'}, {'id': 18627, 'synset': 'arrowleaf_groundsel.n.01', 'name': 'arrowleaf_groundsel'}, {'id': 18628, 'synset': 'black_salsify.n.01', 'name': 'black_salsify'}, {'id': 18629, 'synset': 'white-topped_aster.n.01', 'name': 'white-topped_aster'}, {'id': 18630, 'synset': 'narrow-leaved_white-topped_aster.n.01', 'name': 'narrow-leaved_white-topped_aster'}, {'id': 18631, 'synset': 'silver_sage.n.01', 'name': 'silver_sage'}, {'id': 18632, 'synset': 'sea_wormwood.n.01', 'name': 'sea_wormwood'}, {'id': 18633, 'synset': 'sawwort.n.01', 'name': 'sawwort'}, {'id': 18634, 'synset': 'rosinweed.n.01', 'name': 'rosinweed'}, {'id': 18635, 'synset': 'milk_thistle.n.02', 'name': 'milk_thistle'}, {'id': 18636, 'synset': 'goldenrod.n.01', 'name': 'goldenrod'}, {'id': 18637, 'synset': 'silverrod.n.01', 'name': 'silverrod'}, {'id': 18638, 'synset': 'meadow_goldenrod.n.01', 'name': 'meadow_goldenrod'}, {'id': 18639, 'synset': 'missouri_goldenrod.n.01', 'name': 'Missouri_goldenrod'}, {'id': 18640, 'synset': 'alpine_goldenrod.n.01', 'name': 'alpine_goldenrod'}, {'id': 18641, 'synset': 'grey_goldenrod.n.01', 'name': 'grey_goldenrod'}, {'id': 18642, 'synset': 'blue_mountain_tea.n.01', 'name': 'Blue_Mountain_tea'}, {'id': 18643, 'synset': "dyer's_weed.n.01", 'name': "dyer's_weed"}, {'id': 18644, 'synset': 'seaside_goldenrod.n.01', 'name': 'seaside_goldenrod'}, {'id': 18645, 'synset': 'narrow_goldenrod.n.01', 'name': 'narrow_goldenrod'}, {'id': 18646, 'synset': "boott's_goldenrod.n.01", 'name': "Boott's_goldenrod"}, {'id': 18647, 'synset': "elliott's_goldenrod.n.01", 'name': "Elliott's_goldenrod"}, {'id': 18648, 'synset': 'ohio_goldenrod.n.01', 'name': 'Ohio_goldenrod'}, {'id': 18649, 'synset': 'rough-stemmed_goldenrod.n.01', 'name': 'rough-stemmed_goldenrod'}, {'id': 18650, 'synset': 'showy_goldenrod.n.01', 'name': 'showy_goldenrod'}, {'id': 18651, 'synset': 'tall_goldenrod.n.01', 'name': 'tall_goldenrod'}, {'id': 18652, 'synset': 'zigzag_goldenrod.n.01', 'name': 'zigzag_goldenrod'}, {'id': 18653, 'synset': 'sow_thistle.n.01', 'name': 'sow_thistle'}, {'id': 18654, 'synset': 'milkweed.n.02', 'name': 'milkweed'}, {'id': 18655, 'synset': 'stevia.n.01', 'name': 'stevia'}, {'id': 18656, 'synset': "stokes'_aster.n.01", 'name': "stokes'_aster"}, {'id': 18657, 'synset': 'marigold.n.01', 'name': 'marigold'}, {'id': 18658, 'synset': 'african_marigold.n.01', 'name': 'African_marigold'}, {'id': 18659, 'synset': 'french_marigold.n.01', 'name': 'French_marigold'}, {'id': 18660, 'synset': 'painted_daisy.n.01', 'name': 'painted_daisy'}, {'id': 18661, 'synset': 'pyrethrum.n.02', 'name': 'pyrethrum'}, {'id': 18662, 'synset': 'northern_dune_tansy.n.01', 'name': 'northern_dune_tansy'}, {'id': 18663, 'synset': 'feverfew.n.01', 'name': 'feverfew'}, {'id': 18664, 'synset': 'dusty_miller.n.01', 'name': 'dusty_miller'}, {'id': 18665, 'synset': 'tansy.n.01', 'name': 'tansy'}, {'id': 18666, 'synset': 'dandelion.n.01', 'name': 'dandelion'}, {'id': 18667, 'synset': 'common_dandelion.n.01', 'name': 'common_dandelion'}, {'id': 18668, 'synset': 'dandelion_green.n.01', 'name': 'dandelion_green'}, {'id': 18669, 'synset': 'russian_dandelion.n.01', 'name': 'Russian_dandelion'}, {'id': 18670, 'synset': 'stemless_hymenoxys.n.01', 'name': 'stemless_hymenoxys'}, {'id': 18671, 'synset': 'mexican_sunflower.n.01', 'name': 'Mexican_sunflower'}, {'id': 18672, 'synset': 'easter_daisy.n.01', 'name': 'Easter_daisy'}, {'id': 18673, 'synset': 'yellow_salsify.n.01', 'name': 'yellow_salsify'}, {'id': 18674, 'synset': 'salsify.n.02', 'name': 'salsify'}, {'id': 18675, 'synset': 'meadow_salsify.n.01', 'name': 'meadow_salsify'}, {'id': 18676, 'synset': 'scentless_camomile.n.01', 'name': 'scentless_camomile'}, {'id': 18677, 'synset': 'turfing_daisy.n.01', 'name': 'turfing_daisy'}, {'id': 18678, 'synset': 'coltsfoot.n.02', 'name': 'coltsfoot'}, {'id': 18679, 'synset': 'ursinia.n.01', 'name': 'ursinia'}, {'id': 18680, 'synset': 'crownbeard.n.01', 'name': 'crownbeard'}, {'id': 18681, 'synset': 'wingstem.n.01', 'name': 'wingstem'}, {'id': 18682, 'synset': 'cowpen_daisy.n.01', 'name': 'cowpen_daisy'}, {'id': 18683, 'synset': 'gravelweed.n.01', 'name': 'gravelweed'}, {'id': 18684, 'synset': 'virginia_crownbeard.n.01', 'name': 'Virginia_crownbeard'}, {'id': 18685, 'synset': 'ironweed.n.01', 'name': 'ironweed'}, {'id': 18686, 'synset': "mule's_ears.n.01", 'name': "mule's_ears"}, {'id': 18687, 'synset': "white-rayed_mule's_ears.n.01", 'name': "white-rayed_mule's_ears"}, {'id': 18688, 'synset': 'cocklebur.n.01', 'name': 'cocklebur'}, {'id': 18689, 'synset': 'xeranthemum.n.01', 'name': 'xeranthemum'}, {'id': 18690, 'synset': 'immortelle.n.01', 'name': 'immortelle'}, {'id': 18691, 'synset': 'zinnia.n.01', 'name': 'zinnia'}, {'id': 18692, 'synset': 'white_zinnia.n.01', 'name': 'white_zinnia'}, {'id': 18693, 'synset': 'little_golden_zinnia.n.01', 'name': 'little_golden_zinnia'}, {'id': 18694, 'synset': 'blazing_star.n.01', 'name': 'blazing_star'}, {'id': 18695, 'synset': 'bartonia.n.01', 'name': 'bartonia'}, {'id': 18696, 'synset': 'achene.n.01', 'name': 'achene'}, {'id': 18697, 'synset': 'samara.n.01', 'name': 'samara'}, {'id': 18698, 'synset': 'campanula.n.01', 'name': 'campanula'}, {'id': 18699, 'synset': 'creeping_bellflower.n.01', 'name': 'creeping_bellflower'}, {'id': 18700, 'synset': 'canterbury_bell.n.02', 'name': 'Canterbury_bell'}, {'id': 18701, 'synset': 'tall_bellflower.n.01', 'name': 'tall_bellflower'}, {'id': 18702, 'synset': 'marsh_bellflower.n.01', 'name': 'marsh_bellflower'}, {'id': 18703, 'synset': 'clustered_bellflower.n.01', 'name': 'clustered_bellflower'}, {'id': 18704, 'synset': 'peach_bells.n.01', 'name': 'peach_bells'}, {'id': 18705, 'synset': 'chimney_plant.n.01', 'name': 'chimney_plant'}, {'id': 18706, 'synset': 'rampion.n.01', 'name': 'rampion'}, {'id': 18707, 'synset': 'tussock_bellflower.n.01', 'name': 'tussock_bellflower'}, {'id': 18708, 'synset': 'orchid.n.01', 'name': 'orchid'}, {'id': 18709, 'synset': 'orchis.n.01', 'name': 'orchis'}, {'id': 18710, 'synset': 'male_orchis.n.01', 'name': 'male_orchis'}, {'id': 18711, 'synset': 'butterfly_orchid.n.05', 'name': 'butterfly_orchid'}, {'id': 18712, 'synset': 'showy_orchis.n.01', 'name': 'showy_orchis'}, {'id': 18713, 'synset': 'aerides.n.01', 'name': 'aerides'}, {'id': 18714, 'synset': 'angrecum.n.01', 'name': 'angrecum'}, {'id': 18715, 'synset': 'jewel_orchid.n.01', 'name': 'jewel_orchid'}, {'id': 18716, 'synset': 'puttyroot.n.01', 'name': 'puttyroot'}, {'id': 18717, 'synset': 'arethusa.n.01', 'name': 'arethusa'}, {'id': 18718, 'synset': 'bog_rose.n.01', 'name': 'bog_rose'}, {'id': 18719, 'synset': 'bletia.n.01', 'name': 'bletia'}, {'id': 18720, 'synset': 'bletilla_striata.n.01', 'name': 'Bletilla_striata'}, {'id': 18721, 'synset': 'brassavola.n.01', 'name': 'brassavola'}, {'id': 18722, 'synset': 'spider_orchid.n.03', 'name': 'spider_orchid'}, {'id': 18723, 'synset': 'spider_orchid.n.02', 'name': 'spider_orchid'}, {'id': 18724, 'synset': 'caladenia.n.01', 'name': 'caladenia'}, {'id': 18725, 'synset': 'calanthe.n.01', 'name': 'calanthe'}, {'id': 18726, 'synset': 'grass_pink.n.01', 'name': 'grass_pink'}, {'id': 18727, 'synset': 'calypso.n.01', 'name': 'calypso'}, {'id': 18728, 'synset': 'cattleya.n.01', 'name': 'cattleya'}, {'id': 18729, 'synset': 'helleborine.n.03', 'name': 'helleborine'}, {'id': 18730, 'synset': 'red_helleborine.n.01', 'name': 'red_helleborine'}, {'id': 18731, 'synset': 'spreading_pogonia.n.01', 'name': 'spreading_pogonia'}, {'id': 18732, 'synset': 'rosebud_orchid.n.01', 'name': 'rosebud_orchid'}, {'id': 18733, 'synset': 'satyr_orchid.n.01', 'name': 'satyr_orchid'}, {'id': 18734, 'synset': 'frog_orchid.n.02', 'name': 'frog_orchid'}, {'id': 18735, 'synset': 'coelogyne.n.01', 'name': 'coelogyne'}, {'id': 18736, 'synset': 'coral_root.n.01', 'name': 'coral_root'}, {'id': 18737, 'synset': 'spotted_coral_root.n.01', 'name': 'spotted_coral_root'}, {'id': 18738, 'synset': 'striped_coral_root.n.01', 'name': 'striped_coral_root'}, {'id': 18739, 'synset': 'early_coral_root.n.01', 'name': 'early_coral_root'}, {'id': 18740, 'synset': 'swan_orchid.n.01', 'name': 'swan_orchid'}, {'id': 18741, 'synset': 'cymbid.n.01', 'name': 'cymbid'}, {'id': 18742, 'synset': 'cypripedia.n.01', 'name': 'cypripedia'}, {'id': 18743, 'synset': "lady's_slipper.n.01", 'name': "lady's_slipper"}, {'id': 18744, 'synset': 'moccasin_flower.n.01', 'name': 'moccasin_flower'}, {'id': 18745, 'synset': "common_lady's-slipper.n.01", 'name': "common_lady's-slipper"}, {'id': 18746, 'synset': "ram's-head.n.01", 'name': "ram's-head"}, {'id': 18747, 'synset': "yellow_lady's_slipper.n.01", 'name': "yellow_lady's_slipper"}, {'id': 18748, 'synset': "large_yellow_lady's_slipper.n.01", 'name': "large_yellow_lady's_slipper"}, {'id': 18749, 'synset': "california_lady's_slipper.n.01", 'name': "California_lady's_slipper"}, {'id': 18750, 'synset': "clustered_lady's_slipper.n.01", 'name': "clustered_lady's_slipper"}, {'id': 18751, 'synset': "mountain_lady's_slipper.n.01", 'name': "mountain_lady's_slipper"}, {'id': 18752, 'synset': 'marsh_orchid.n.01', 'name': 'marsh_orchid'}, {'id': 18753, 'synset': 'common_spotted_orchid.n.01', 'name': 'common_spotted_orchid'}, {'id': 18754, 'synset': 'dendrobium.n.01', 'name': 'dendrobium'}, {'id': 18755, 'synset': 'disa.n.01', 'name': 'disa'}, {'id': 18756, 'synset': 'phantom_orchid.n.01', 'name': 'phantom_orchid'}, {'id': 18757, 'synset': 'tulip_orchid.n.01', 'name': 'tulip_orchid'}, {'id': 18758, 'synset': 'butterfly_orchid.n.04', 'name': 'butterfly_orchid'}, {'id': 18759, 'synset': 'butterfly_orchid.n.03', 'name': 'butterfly_orchid'}, {'id': 18760, 'synset': 'epidendron.n.01', 'name': 'epidendron'}, {'id': 18761, 'synset': 'helleborine.n.02', 'name': 'helleborine'}, {'id': 18762, 'synset': 'epipactis_helleborine.n.01', 'name': 'Epipactis_helleborine'}, {'id': 18763, 'synset': 'stream_orchid.n.01', 'name': 'stream_orchid'}, {'id': 18764, 'synset': 'tongueflower.n.01', 'name': 'tongueflower'}, {'id': 18765, 'synset': 'rattlesnake_plantain.n.01', 'name': 'rattlesnake_plantain'}, {'id': 18766, 'synset': 'fragrant_orchid.n.01', 'name': 'fragrant_orchid'}, {'id': 18767, 'synset': 'short-spurred_fragrant_orchid.n.01', 'name': 'short-spurred_fragrant_orchid'}, {'id': 18768, 'synset': 'fringed_orchis.n.01', 'name': 'fringed_orchis'}, {'id': 18769, 'synset': 'frog_orchid.n.01', 'name': 'frog_orchid'}, {'id': 18770, 'synset': 'rein_orchid.n.01', 'name': 'rein_orchid'}, {'id': 18771, 'synset': 'bog_rein_orchid.n.01', 'name': 'bog_rein_orchid'}, {'id': 18772, 'synset': 'white_fringed_orchis.n.01', 'name': 'white_fringed_orchis'}, {'id': 18773, 'synset': 'elegant_habenaria.n.01', 'name': 'elegant_Habenaria'}, {'id': 18774, 'synset': 'purple-fringed_orchid.n.02', 'name': 'purple-fringed_orchid'}, {'id': 18775, 'synset': 'coastal_rein_orchid.n.01', 'name': 'coastal_rein_orchid'}, {'id': 18776, 'synset': "hooker's_orchid.n.01", 'name': "Hooker's_orchid"}, {'id': 18777, 'synset': 'ragged_orchid.n.01', 'name': 'ragged_orchid'}, {'id': 18778, 'synset': 'prairie_orchid.n.01', 'name': 'prairie_orchid'}, {'id': 18779, 'synset': 'snowy_orchid.n.01', 'name': 'snowy_orchid'}, {'id': 18780, 'synset': 'round-leaved_rein_orchid.n.01', 'name': 'round-leaved_rein_orchid'}, {'id': 18781, 'synset': 'purple_fringeless_orchid.n.01', 'name': 'purple_fringeless_orchid'}, {'id': 18782, 'synset': 'purple-fringed_orchid.n.01', 'name': 'purple-fringed_orchid'}, {'id': 18783, 'synset': 'alaska_rein_orchid.n.01', 'name': 'Alaska_rein_orchid'}, {'id': 18784, 'synset': 'crested_coral_root.n.01', 'name': 'crested_coral_root'}, {'id': 18785, 'synset': 'texas_purple_spike.n.01', 'name': 'Texas_purple_spike'}, {'id': 18786, 'synset': 'lizard_orchid.n.01', 'name': 'lizard_orchid'}, {'id': 18787, 'synset': 'laelia.n.01', 'name': 'laelia'}, {'id': 18788, 'synset': 'liparis.n.01', 'name': 'liparis'}, {'id': 18789, 'synset': 'twayblade.n.02', 'name': 'twayblade'}, {'id': 18790, 'synset': 'fen_orchid.n.01', 'name': 'fen_orchid'}, {'id': 18791, 'synset': 'broad-leaved_twayblade.n.01', 'name': 'broad-leaved_twayblade'}, {'id': 18792, 'synset': 'lesser_twayblade.n.01', 'name': 'lesser_twayblade'}, {'id': 18793, 'synset': 'twayblade.n.01', 'name': 'twayblade'}, {'id': 18794, 'synset': "green_adder's_mouth.n.01", 'name': "green_adder's_mouth"}, {'id': 18795, 'synset': 'masdevallia.n.01', 'name': 'masdevallia'}, {'id': 18796, 'synset': 'maxillaria.n.01', 'name': 'maxillaria'}, {'id': 18797, 'synset': 'pansy_orchid.n.01', 'name': 'pansy_orchid'}, {'id': 18798, 'synset': 'odontoglossum.n.01', 'name': 'odontoglossum'}, {'id': 18799, 'synset': 'oncidium.n.01', 'name': 'oncidium'}, {'id': 18800, 'synset': 'bee_orchid.n.01', 'name': 'bee_orchid'}, {'id': 18801, 'synset': 'fly_orchid.n.02', 'name': 'fly_orchid'}, {'id': 18802, 'synset': 'spider_orchid.n.01', 'name': 'spider_orchid'}, {'id': 18803, 'synset': 'early_spider_orchid.n.01', 'name': 'early_spider_orchid'}, {'id': 18804, 'synset': "venus'_slipper.n.01", 'name': "Venus'_slipper"}, {'id': 18805, 'synset': 'phaius.n.01', 'name': 'phaius'}, {'id': 18806, 'synset': 'moth_orchid.n.01', 'name': 'moth_orchid'}, {'id': 18807, 'synset': 'butterfly_plant.n.01', 'name': 'butterfly_plant'}, {'id': 18808, 'synset': 'rattlesnake_orchid.n.01', 'name': 'rattlesnake_orchid'}, {'id': 18809, 'synset': 'lesser_butterfly_orchid.n.01', 'name': 'lesser_butterfly_orchid'}, {'id': 18810, 'synset': 'greater_butterfly_orchid.n.01', 'name': 'greater_butterfly_orchid'}, {'id': 18811, 'synset': 'prairie_white-fringed_orchid.n.01', 'name': 'prairie_white-fringed_orchid'}, {'id': 18812, 'synset': 'tangle_orchid.n.01', 'name': 'tangle_orchid'}, {'id': 18813, 'synset': 'indian_crocus.n.01', 'name': 'Indian_crocus'}, {'id': 18814, 'synset': 'pleurothallis.n.01', 'name': 'pleurothallis'}, {'id': 18815, 'synset': 'pogonia.n.01', 'name': 'pogonia'}, {'id': 18816, 'synset': 'butterfly_orchid.n.01', 'name': 'butterfly_orchid'}, {'id': 18817, 'synset': 'psychopsis_krameriana.n.01', 'name': 'Psychopsis_krameriana'}, {'id': 18818, 'synset': 'psychopsis_papilio.n.01', 'name': 'Psychopsis_papilio'}, {'id': 18819, 'synset': 'helmet_orchid.n.01', 'name': 'helmet_orchid'}, {'id': 18820, 'synset': 'foxtail_orchid.n.01', 'name': 'foxtail_orchid'}, {'id': 18821, 'synset': 'orange-blossom_orchid.n.01', 'name': 'orange-blossom_orchid'}, {'id': 18822, 'synset': 'sobralia.n.01', 'name': 'sobralia'}, {'id': 18823, 'synset': "ladies'_tresses.n.01", 'name': "ladies'_tresses"}, {'id': 18824, 'synset': 'screw_augur.n.01', 'name': 'screw_augur'}, {'id': 18825, 'synset': "hooded_ladies'_tresses.n.01", 'name': "hooded_ladies'_tresses"}, {'id': 18826, 'synset': "western_ladies'_tresses.n.01", 'name': "western_ladies'_tresses"}, {'id': 18827, 'synset': "european_ladies'_tresses.n.01", 'name': "European_ladies'_tresses"}, {'id': 18828, 'synset': 'stanhopea.n.01', 'name': 'stanhopea'}, {'id': 18829, 'synset': 'stelis.n.01', 'name': 'stelis'}, {'id': 18830, 'synset': 'fly_orchid.n.01', 'name': 'fly_orchid'}, {'id': 18831, 'synset': 'vanda.n.01', 'name': 'vanda'}, {'id': 18832, 'synset': 'blue_orchid.n.01', 'name': 'blue_orchid'}, {'id': 18833, 'synset': 'vanilla.n.01', 'name': 'vanilla'}, {'id': 18834, 'synset': 'vanilla_orchid.n.01', 'name': 'vanilla_orchid'}, {'id': 18835, 'synset': 'yam.n.02', 'name': 'yam'}, {'id': 18836, 'synset': 'yam.n.01', 'name': 'yam'}, {'id': 18837, 'synset': 'white_yam.n.01', 'name': 'white_yam'}, {'id': 18838, 'synset': 'cinnamon_vine.n.01', 'name': 'cinnamon_vine'}, {'id': 18839, 'synset': "elephant's-foot.n.01", 'name': "elephant's-foot"}, {'id': 18840, 'synset': 'wild_yam.n.01', 'name': 'wild_yam'}, {'id': 18841, 'synset': 'cush-cush.n.01', 'name': 'cush-cush'}, {'id': 18842, 'synset': 'black_bryony.n.01', 'name': 'black_bryony'}, {'id': 18843, 'synset': 'primrose.n.01', 'name': 'primrose'}, {'id': 18844, 'synset': 'english_primrose.n.01', 'name': 'English_primrose'}, {'id': 18845, 'synset': 'cowslip.n.01', 'name': 'cowslip'}, {'id': 18846, 'synset': 'oxlip.n.01', 'name': 'oxlip'}, {'id': 18847, 'synset': 'chinese_primrose.n.01', 'name': 'Chinese_primrose'}, {'id': 18848, 'synset': 'polyanthus.n.01', 'name': 'polyanthus'}, {'id': 18849, 'synset': 'pimpernel.n.02', 'name': 'pimpernel'}, {'id': 18850, 'synset': 'scarlet_pimpernel.n.01', 'name': 'scarlet_pimpernel'}, {'id': 18851, 'synset': 'bog_pimpernel.n.01', 'name': 'bog_pimpernel'}, {'id': 18852, 'synset': 'chaffweed.n.01', 'name': 'chaffweed'}, {'id': 18853, 'synset': 'cyclamen.n.01', 'name': 'cyclamen'}, {'id': 18854, 'synset': 'sowbread.n.01', 'name': 'sowbread'}, {'id': 18855, 'synset': 'sea_milkwort.n.01', 'name': 'sea_milkwort'}, {'id': 18856, 'synset': 'featherfoil.n.01', 'name': 'featherfoil'}, {'id': 18857, 'synset': 'water_gillyflower.n.01', 'name': 'water_gillyflower'}, {'id': 18858, 'synset': 'water_violet.n.01', 'name': 'water_violet'}, {'id': 18859, 'synset': 'loosestrife.n.02', 'name': 'loosestrife'}, {'id': 18860, 'synset': 'gooseneck_loosestrife.n.01', 'name': 'gooseneck_loosestrife'}, {'id': 18861, 'synset': 'yellow_pimpernel.n.01', 'name': 'yellow_pimpernel'}, {'id': 18862, 'synset': 'fringed_loosestrife.n.01', 'name': 'fringed_loosestrife'}, {'id': 18863, 'synset': 'moneywort.n.01', 'name': 'moneywort'}, {'id': 18864, 'synset': 'swamp_candles.n.01', 'name': 'swamp_candles'}, {'id': 18865, 'synset': 'whorled_loosestrife.n.01', 'name': 'whorled_loosestrife'}, {'id': 18866, 'synset': 'water_pimpernel.n.01', 'name': 'water_pimpernel'}, {'id': 18867, 'synset': 'brookweed.n.02', 'name': 'brookweed'}, {'id': 18868, 'synset': 'brookweed.n.01', 'name': 'brookweed'}, {'id': 18869, 'synset': 'coralberry.n.02', 'name': 'coralberry'}, {'id': 18870, 'synset': 'marlberry.n.01', 'name': 'marlberry'}, {'id': 18871, 'synset': 'plumbago.n.02', 'name': 'plumbago'}, {'id': 18872, 'synset': 'leadwort.n.01', 'name': 'leadwort'}, {'id': 18873, 'synset': 'thrift.n.01', 'name': 'thrift'}, {'id': 18874, 'synset': 'sea_lavender.n.01', 'name': 'sea_lavender'}, {'id': 18875, 'synset': 'barbasco.n.01', 'name': 'barbasco'}, {'id': 18876, 'synset': 'gramineous_plant.n.01', 'name': 'gramineous_plant'}, {'id': 18877, 'synset': 'grass.n.01', 'name': 'grass'}, {'id': 18878, 'synset': 'midgrass.n.01', 'name': 'midgrass'}, {'id': 18879, 'synset': 'shortgrass.n.01', 'name': 'shortgrass'}, {'id': 18880, 'synset': 'sword_grass.n.01', 'name': 'sword_grass'}, {'id': 18881, 'synset': 'tallgrass.n.01', 'name': 'tallgrass'}, {'id': 18882, 'synset': 'herbage.n.01', 'name': 'herbage'}, {'id': 18883, 'synset': 'goat_grass.n.01', 'name': 'goat_grass'}, {'id': 18884, 'synset': 'wheatgrass.n.01', 'name': 'wheatgrass'}, {'id': 18885, 'synset': 'crested_wheatgrass.n.01', 'name': 'crested_wheatgrass'}, {'id': 18886, 'synset': 'bearded_wheatgrass.n.01', 'name': 'bearded_wheatgrass'}, {'id': 18887, 'synset': 'western_wheatgrass.n.01', 'name': 'western_wheatgrass'}, {'id': 18888, 'synset': 'intermediate_wheatgrass.n.01', 'name': 'intermediate_wheatgrass'}, {'id': 18889, 'synset': 'slender_wheatgrass.n.01', 'name': 'slender_wheatgrass'}, {'id': 18890, 'synset': 'velvet_bent.n.01', 'name': 'velvet_bent'}, {'id': 18891, 'synset': 'cloud_grass.n.01', 'name': 'cloud_grass'}, {'id': 18892, 'synset': 'meadow_foxtail.n.01', 'name': 'meadow_foxtail'}, {'id': 18893, 'synset': 'foxtail.n.01', 'name': 'foxtail'}, {'id': 18894, 'synset': 'broom_grass.n.01', 'name': 'broom_grass'}, {'id': 18895, 'synset': 'broom_sedge.n.01', 'name': 'broom_sedge'}, {'id': 18896, 'synset': 'tall_oat_grass.n.01', 'name': 'tall_oat_grass'}, {'id': 18897, 'synset': 'toetoe.n.02', 'name': 'toetoe'}, {'id': 18898, 'synset': 'oat.n.01', 'name': 'oat'}, {'id': 18899, 'synset': 'cereal_oat.n.01', 'name': 'cereal_oat'}, {'id': 18900, 'synset': 'wild_oat.n.01', 'name': 'wild_oat'}, {'id': 18901, 'synset': 'slender_wild_oat.n.01', 'name': 'slender_wild_oat'}, {'id': 18902, 'synset': 'wild_red_oat.n.01', 'name': 'wild_red_oat'}, {'id': 18903, 'synset': 'brome.n.01', 'name': 'brome'}, {'id': 18904, 'synset': 'chess.n.01', 'name': 'chess'}, {'id': 18905, 'synset': 'field_brome.n.01', 'name': 'field_brome'}, {'id': 18906, 'synset': 'grama.n.01', 'name': 'grama'}, {'id': 18907, 'synset': 'black_grama.n.01', 'name': 'black_grama'}, {'id': 18908, 'synset': 'buffalo_grass.n.02', 'name': 'buffalo_grass'}, {'id': 18909, 'synset': 'reed_grass.n.01', 'name': 'reed_grass'}, {'id': 18910, 'synset': 'feather_reed_grass.n.01', 'name': 'feather_reed_grass'}, {'id': 18911, 'synset': 'australian_reed_grass.n.01', 'name': 'Australian_reed_grass'}, {'id': 18912, 'synset': 'burgrass.n.01', 'name': 'burgrass'}, {'id': 18913, 'synset': 'buffel_grass.n.01', 'name': 'buffel_grass'}, {'id': 18914, 'synset': 'rhodes_grass.n.01', 'name': 'Rhodes_grass'}, {'id': 18915, 'synset': 'pampas_grass.n.01', 'name': 'pampas_grass'}, {'id': 18916, 'synset': 'giant_star_grass.n.01', 'name': 'giant_star_grass'}, {'id': 18917, 'synset': 'orchard_grass.n.01', 'name': 'orchard_grass'}, {'id': 18918, 'synset': 'egyptian_grass.n.01', 'name': 'Egyptian_grass'}, {'id': 18919, 'synset': 'crabgrass.n.01', 'name': 'crabgrass'}, {'id': 18920, 'synset': 'smooth_crabgrass.n.01', 'name': 'smooth_crabgrass'}, {'id': 18921, 'synset': 'large_crabgrass.n.01', 'name': 'large_crabgrass'}, {'id': 18922, 'synset': 'barnyard_grass.n.01', 'name': 'barnyard_grass'}, {'id': 18923, 'synset': 'japanese_millet.n.01', 'name': 'Japanese_millet'}, {'id': 18924, 'synset': 'yardgrass.n.01', 'name': 'yardgrass'}, {'id': 18925, 'synset': 'finger_millet.n.01', 'name': 'finger_millet'}, {'id': 18926, 'synset': 'lyme_grass.n.01', 'name': 'lyme_grass'}, {'id': 18927, 'synset': 'wild_rye.n.01', 'name': 'wild_rye'}, {'id': 18928, 'synset': 'giant_ryegrass.n.01', 'name': 'giant_ryegrass'}, {'id': 18929, 'synset': 'sea_lyme_grass.n.01', 'name': 'sea_lyme_grass'}, {'id': 18930, 'synset': 'canada_wild_rye.n.01', 'name': 'Canada_wild_rye'}, {'id': 18931, 'synset': 'teff.n.01', 'name': 'teff'}, {'id': 18932, 'synset': 'weeping_love_grass.n.01', 'name': 'weeping_love_grass'}, {'id': 18933, 'synset': 'plume_grass.n.01', 'name': 'plume_grass'}, {'id': 18934, 'synset': 'ravenna_grass.n.01', 'name': 'Ravenna_grass'}, {'id': 18935, 'synset': 'fescue.n.01', 'name': 'fescue'}, {'id': 18936, 'synset': 'reed_meadow_grass.n.01', 'name': 'reed_meadow_grass'}, {'id': 18937, 'synset': 'velvet_grass.n.01', 'name': 'velvet_grass'}, {'id': 18938, 'synset': 'creeping_soft_grass.n.01', 'name': 'creeping_soft_grass'}, {'id': 18939, 'synset': 'barleycorn.n.01', 'name': 'barleycorn'}, {'id': 18940, 'synset': 'barley_grass.n.01', 'name': 'barley_grass'}, {'id': 18941, 'synset': 'little_barley.n.01', 'name': 'little_barley'}, {'id': 18942, 'synset': 'rye_grass.n.01', 'name': 'rye_grass'}, {'id': 18943, 'synset': 'perennial_ryegrass.n.01', 'name': 'perennial_ryegrass'}, {'id': 18944, 'synset': 'italian_ryegrass.n.01', 'name': 'Italian_ryegrass'}, {'id': 18945, 'synset': 'darnel.n.01', 'name': 'darnel'}, {'id': 18946, 'synset': 'nimblewill.n.01', 'name': 'nimblewill'}, {'id': 18947, 'synset': 'cultivated_rice.n.01', 'name': 'cultivated_rice'}, {'id': 18948, 'synset': 'ricegrass.n.01', 'name': 'ricegrass'}, {'id': 18949, 'synset': 'smilo.n.01', 'name': 'smilo'}, {'id': 18950, 'synset': 'switch_grass.n.01', 'name': 'switch_grass'}, {'id': 18951, 'synset': 'broomcorn_millet.n.01', 'name': 'broomcorn_millet'}, {'id': 18952, 'synset': 'goose_grass.n.03', 'name': 'goose_grass'}, {'id': 18953, 'synset': 'dallisgrass.n.01', 'name': 'dallisgrass'}, {'id': 18954, 'synset': 'bahia_grass.n.01', 'name': 'Bahia_grass'}, {'id': 18955, 'synset': 'knotgrass.n.01', 'name': 'knotgrass'}, {'id': 18956, 'synset': 'fountain_grass.n.01', 'name': 'fountain_grass'}, {'id': 18957, 'synset': 'reed_canary_grass.n.01', 'name': 'reed_canary_grass'}, {'id': 18958, 'synset': 'canary_grass.n.01', 'name': 'canary_grass'}, {'id': 18959, 'synset': 'timothy.n.01', 'name': 'timothy'}, {'id': 18960, 'synset': 'bluegrass.n.01', 'name': 'bluegrass'}, {'id': 18961, 'synset': 'meadowgrass.n.01', 'name': 'meadowgrass'}, {'id': 18962, 'synset': 'wood_meadowgrass.n.01', 'name': 'wood_meadowgrass'}, {'id': 18963, 'synset': 'noble_cane.n.01', 'name': 'noble_cane'}, {'id': 18964, 'synset': 'munj.n.01', 'name': 'munj'}, {'id': 18965, 'synset': 'broom_beard_grass.n.01', 'name': 'broom_beard_grass'}, {'id': 18966, 'synset': 'bluestem.n.01', 'name': 'bluestem'}, {'id': 18967, 'synset': 'rye.n.02', 'name': 'rye'}, {'id': 18968, 'synset': 'bristlegrass.n.01', 'name': 'bristlegrass'}, {'id': 18969, 'synset': 'giant_foxtail.n.01', 'name': 'giant_foxtail'}, {'id': 18970, 'synset': 'yellow_bristlegrass.n.01', 'name': 'yellow_bristlegrass'}, {'id': 18971, 'synset': 'green_bristlegrass.n.01', 'name': 'green_bristlegrass'}, {'id': 18972, 'synset': 'siberian_millet.n.01', 'name': 'Siberian_millet'}, {'id': 18973, 'synset': 'german_millet.n.01', 'name': 'German_millet'}, {'id': 18974, 'synset': 'millet.n.01', 'name': 'millet'}, {'id': 18975, 'synset': 'rattan.n.02', 'name': 'rattan'}, {'id': 18976, 'synset': 'malacca.n.01', 'name': 'malacca'}, {'id': 18977, 'synset': 'reed.n.01', 'name': 'reed'}, {'id': 18978, 'synset': 'sorghum.n.01', 'name': 'sorghum'}, {'id': 18979, 'synset': 'grain_sorghum.n.01', 'name': 'grain_sorghum'}, {'id': 18980, 'synset': 'durra.n.01', 'name': 'durra'}, {'id': 18981, 'synset': 'feterita.n.01', 'name': 'feterita'}, {'id': 18982, 'synset': 'hegari.n.01', 'name': 'hegari'}, {'id': 18983, 'synset': 'kaoliang.n.01', 'name': 'kaoliang'}, {'id': 18984, 'synset': 'milo.n.01', 'name': 'milo'}, {'id': 18985, 'synset': 'shallu.n.01', 'name': 'shallu'}, {'id': 18986, 'synset': 'broomcorn.n.01', 'name': 'broomcorn'}, {'id': 18987, 'synset': 'cordgrass.n.01', 'name': 'cordgrass'}, {'id': 18988, 'synset': 'salt_reed_grass.n.01', 'name': 'salt_reed_grass'}, {'id': 18989, 'synset': 'prairie_cordgrass.n.01', 'name': 'prairie_cordgrass'}, {'id': 18990, 'synset': 'smut_grass.n.01', 'name': 'smut_grass'}, {'id': 18991, 'synset': 'sand_dropseed.n.01', 'name': 'sand_dropseed'}, {'id': 18992, 'synset': 'rush_grass.n.01', 'name': 'rush_grass'}, {'id': 18993, 'synset': 'st._augustine_grass.n.01', 'name': 'St._Augustine_grass'}, {'id': 18994, 'synset': 'grain.n.08', 'name': 'grain'}, {'id': 18995, 'synset': 'cereal.n.01', 'name': 'cereal'}, {'id': 18996, 'synset': 'wheat.n.01', 'name': 'wheat'}, {'id': 18997, 'synset': 'wheat_berry.n.01', 'name': 'wheat_berry'}, {'id': 18998, 'synset': 'durum.n.01', 'name': 'durum'}, {'id': 18999, 'synset': 'spelt.n.01', 'name': 'spelt'}, {'id': 19000, 'synset': 'emmer.n.01', 'name': 'emmer'}, {'id': 19001, 'synset': 'wild_wheat.n.01', 'name': 'wild_wheat'}, {'id': 19002, 'synset': 'corn.n.01', 'name': 'corn'}, {'id': 19003, 'synset': 'mealie.n.01', 'name': 'mealie'}, {'id': 19004, 'synset': 'corn.n.02', 'name': 'corn'}, {'id': 19005, 'synset': 'dent_corn.n.01', 'name': 'dent_corn'}, {'id': 19006, 'synset': 'flint_corn.n.01', 'name': 'flint_corn'}, {'id': 19007, 'synset': 'popcorn.n.01', 'name': 'popcorn'}, {'id': 19008, 'synset': 'zoysia.n.01', 'name': 'zoysia'}, {'id': 19009, 'synset': 'manila_grass.n.01', 'name': 'Manila_grass'}, {'id': 19010, 'synset': 'korean_lawn_grass.n.01', 'name': 'Korean_lawn_grass'}, {'id': 19011, 'synset': 'common_bamboo.n.01', 'name': 'common_bamboo'}, {'id': 19012, 'synset': 'giant_bamboo.n.01', 'name': 'giant_bamboo'}, {'id': 19013, 'synset': 'umbrella_plant.n.03', 'name': 'umbrella_plant'}, {'id': 19014, 'synset': 'chufa.n.01', 'name': 'chufa'}, {'id': 19015, 'synset': 'galingale.n.01', 'name': 'galingale'}, {'id': 19016, 'synset': 'nutgrass.n.01', 'name': 'nutgrass'}, {'id': 19017, 'synset': 'sand_sedge.n.01', 'name': 'sand_sedge'}, {'id': 19018, 'synset': 'cypress_sedge.n.01', 'name': 'cypress_sedge'}, {'id': 19019, 'synset': 'cotton_grass.n.01', 'name': 'cotton_grass'}, {'id': 19020, 'synset': 'common_cotton_grass.n.01', 'name': 'common_cotton_grass'}, {'id': 19021, 'synset': 'hardstem_bulrush.n.01', 'name': 'hardstem_bulrush'}, {'id': 19022, 'synset': 'wool_grass.n.01', 'name': 'wool_grass'}, {'id': 19023, 'synset': 'spike_rush.n.01', 'name': 'spike_rush'}, {'id': 19024, 'synset': 'water_chestnut.n.02', 'name': 'water_chestnut'}, {'id': 19025, 'synset': 'needle_spike_rush.n.01', 'name': 'needle_spike_rush'}, {'id': 19026, 'synset': 'creeping_spike_rush.n.01', 'name': 'creeping_spike_rush'}, {'id': 19027, 'synset': 'pandanus.n.02', 'name': 'pandanus'}, {'id': 19028, 'synset': 'textile_screw_pine.n.01', 'name': 'textile_screw_pine'}, {'id': 19029, 'synset': 'cattail.n.01', 'name': 'cattail'}, {'id': 19030, 'synset': "cat's-tail.n.01", 'name': "cat's-tail"}, {'id': 19031, 'synset': 'bur_reed.n.01', 'name': 'bur_reed'}, {'id': 19032, 'synset': 'grain.n.07', 'name': 'grain'}, {'id': 19033, 'synset': 'kernel.n.02', 'name': 'kernel'}, {'id': 19034, 'synset': 'rye.n.01', 'name': 'rye'}, {'id': 19035, 'synset': 'gourd.n.03', 'name': 'gourd'}, {'id': 19036, 'synset': 'pumpkin.n.01', 'name': 'pumpkin'}, {'id': 19037, 'synset': 'squash.n.01', 'name': 'squash'}, {'id': 19038, 'synset': 'summer_squash.n.01', 'name': 'summer_squash'}, {'id': 19039, 'synset': 'yellow_squash.n.01', 'name': 'yellow_squash'}, {'id': 19040, 'synset': 'marrow.n.02', 'name': 'marrow'}, {'id': 19041, 'synset': 'zucchini.n.01', 'name': 'zucchini'}, {'id': 19042, 'synset': 'cocozelle.n.01', 'name': 'cocozelle'}, {'id': 19043, 'synset': 'cymling.n.01', 'name': 'cymling'}, {'id': 19044, 'synset': 'spaghetti_squash.n.01', 'name': 'spaghetti_squash'}, {'id': 19045, 'synset': 'winter_squash.n.01', 'name': 'winter_squash'}, {'id': 19046, 'synset': 'acorn_squash.n.01', 'name': 'acorn_squash'}, {'id': 19047, 'synset': 'hubbard_squash.n.01', 'name': 'hubbard_squash'}, {'id': 19048, 'synset': 'turban_squash.n.01', 'name': 'turban_squash'}, {'id': 19049, 'synset': 'buttercup_squash.n.01', 'name': 'buttercup_squash'}, {'id': 19050, 'synset': 'butternut_squash.n.01', 'name': 'butternut_squash'}, {'id': 19051, 'synset': 'winter_crookneck.n.01', 'name': 'winter_crookneck'}, {'id': 19052, 'synset': 'cushaw.n.01', 'name': 'cushaw'}, {'id': 19053, 'synset': 'prairie_gourd.n.02', 'name': 'prairie_gourd'}, {'id': 19054, 'synset': 'prairie_gourd.n.01', 'name': 'prairie_gourd'}, {'id': 19055, 'synset': 'bryony.n.01', 'name': 'bryony'}, {'id': 19056, 'synset': 'white_bryony.n.01', 'name': 'white_bryony'}, {'id': 19057, 'synset': 'sweet_melon.n.01', 'name': 'sweet_melon'}, {'id': 19058, 'synset': 'cantaloupe.n.01', 'name': 'cantaloupe'}, {'id': 19059, 'synset': 'winter_melon.n.01', 'name': 'winter_melon'}, {'id': 19060, 'synset': 'net_melon.n.01', 'name': 'net_melon'}, {'id': 19061, 'synset': 'cucumber.n.01', 'name': 'cucumber'}, {'id': 19062, 'synset': 'squirting_cucumber.n.01', 'name': 'squirting_cucumber'}, {'id': 19063, 'synset': 'bottle_gourd.n.01', 'name': 'bottle_gourd'}, {'id': 19064, 'synset': 'luffa.n.02', 'name': 'luffa'}, {'id': 19065, 'synset': 'loofah.n.02', 'name': 'loofah'}, {'id': 19066, 'synset': 'angled_loofah.n.01', 'name': 'angled_loofah'}, {'id': 19067, 'synset': 'loofa.n.01', 'name': 'loofa'}, {'id': 19068, 'synset': 'balsam_apple.n.01', 'name': 'balsam_apple'}, {'id': 19069, 'synset': 'balsam_pear.n.01', 'name': 'balsam_pear'}, {'id': 19070, 'synset': 'lobelia.n.01', 'name': 'lobelia'}, {'id': 19071, 'synset': 'water_lobelia.n.01', 'name': 'water_lobelia'}, {'id': 19072, 'synset': 'mallow.n.01', 'name': 'mallow'}, {'id': 19073, 'synset': 'musk_mallow.n.02', 'name': 'musk_mallow'}, {'id': 19074, 'synset': 'common_mallow.n.01', 'name': 'common_mallow'}, {'id': 19075, 'synset': 'okra.n.02', 'name': 'okra'}, {'id': 19076, 'synset': 'okra.n.01', 'name': 'okra'}, {'id': 19077, 'synset': 'abelmosk.n.01', 'name': 'abelmosk'}, {'id': 19078, 'synset': 'flowering_maple.n.01', 'name': 'flowering_maple'}, {'id': 19079, 'synset': 'velvetleaf.n.02', 'name': 'velvetleaf'}, {'id': 19080, 'synset': 'hollyhock.n.02', 'name': 'hollyhock'}, {'id': 19081, 'synset': 'rose_mallow.n.02', 'name': 'rose_mallow'}, {'id': 19082, 'synset': 'althea.n.01', 'name': 'althea'}, {'id': 19083, 'synset': 'marsh_mallow.n.01', 'name': 'marsh_mallow'}, {'id': 19084, 'synset': 'poppy_mallow.n.01', 'name': 'poppy_mallow'}, {'id': 19085, 'synset': 'fringed_poppy_mallow.n.01', 'name': 'fringed_poppy_mallow'}, {'id': 19086, 'synset': 'purple_poppy_mallow.n.01', 'name': 'purple_poppy_mallow'}, {'id': 19087, 'synset': 'clustered_poppy_mallow.n.01', 'name': 'clustered_poppy_mallow'}, {'id': 19088, 'synset': 'sea_island_cotton.n.01', 'name': 'sea_island_cotton'}, {'id': 19089, 'synset': 'levant_cotton.n.01', 'name': 'Levant_cotton'}, {'id': 19090, 'synset': 'upland_cotton.n.01', 'name': 'upland_cotton'}, {'id': 19091, 'synset': 'peruvian_cotton.n.01', 'name': 'Peruvian_cotton'}, {'id': 19092, 'synset': 'wild_cotton.n.01', 'name': 'wild_cotton'}, {'id': 19093, 'synset': 'kenaf.n.02', 'name': 'kenaf'}, {'id': 19094, 'synset': 'sorrel_tree.n.02', 'name': 'sorrel_tree'}, {'id': 19095, 'synset': 'rose_mallow.n.01', 'name': 'rose_mallow'}, {'id': 19096, 'synset': 'cotton_rose.n.01', 'name': 'cotton_rose'}, {'id': 19097, 'synset': 'roselle.n.01', 'name': 'roselle'}, {'id': 19098, 'synset': 'mahoe.n.01', 'name': 'mahoe'}, {'id': 19099, 'synset': 'flower-of-an-hour.n.01', 'name': 'flower-of-an-hour'}, {'id': 19100, 'synset': 'lacebark.n.01', 'name': 'lacebark'}, {'id': 19101, 'synset': 'wild_hollyhock.n.02', 'name': 'wild_hollyhock'}, {'id': 19102, 'synset': 'mountain_hollyhock.n.01', 'name': 'mountain_hollyhock'}, {'id': 19103, 'synset': 'seashore_mallow.n.01', 'name': 'seashore_mallow'}, {'id': 19104, 'synset': 'salt_marsh_mallow.n.01', 'name': 'salt_marsh_mallow'}, {'id': 19105, 'synset': 'chaparral_mallow.n.01', 'name': 'chaparral_mallow'}, {'id': 19106, 'synset': 'malope.n.01', 'name': 'malope'}, {'id': 19107, 'synset': 'false_mallow.n.02', 'name': 'false_mallow'}, {'id': 19108, 'synset': 'waxmallow.n.01', 'name': 'waxmallow'}, {'id': 19109, 'synset': 'glade_mallow.n.01', 'name': 'glade_mallow'}, {'id': 19110, 'synset': 'pavonia.n.01', 'name': 'pavonia'}, {'id': 19111, 'synset': 'ribbon_tree.n.01', 'name': 'ribbon_tree'}, {'id': 19112, 'synset': 'bush_hibiscus.n.01', 'name': 'bush_hibiscus'}, {'id': 19113, 'synset': 'virginia_mallow.n.01', 'name': 'Virginia_mallow'}, {'id': 19114, 'synset': 'queensland_hemp.n.01', 'name': 'Queensland_hemp'}, {'id': 19115, 'synset': 'indian_mallow.n.01', 'name': 'Indian_mallow'}, {'id': 19116, 'synset': 'checkerbloom.n.01', 'name': 'checkerbloom'}, {'id': 19117, 'synset': 'globe_mallow.n.01', 'name': 'globe_mallow'}, {'id': 19118, 'synset': 'prairie_mallow.n.01', 'name': 'prairie_mallow'}, {'id': 19119, 'synset': 'tulipwood_tree.n.01', 'name': 'tulipwood_tree'}, {'id': 19120, 'synset': 'portia_tree.n.01', 'name': 'portia_tree'}, {'id': 19121, 'synset': 'red_silk-cotton_tree.n.01', 'name': 'red_silk-cotton_tree'}, {'id': 19122, 'synset': 'cream-of-tartar_tree.n.01', 'name': 'cream-of-tartar_tree'}, {'id': 19123, 'synset': 'baobab.n.01', 'name': 'baobab'}, {'id': 19124, 'synset': 'kapok.n.02', 'name': 'kapok'}, {'id': 19125, 'synset': 'durian.n.01', 'name': 'durian'}, {'id': 19126, 'synset': 'montezuma.n.01', 'name': 'Montezuma'}, {'id': 19127, 'synset': 'shaving-brush_tree.n.01', 'name': 'shaving-brush_tree'}, {'id': 19128, 'synset': 'quandong.n.03', 'name': 'quandong'}, {'id': 19129, 'synset': 'quandong.n.02', 'name': 'quandong'}, {'id': 19130, 'synset': 'makomako.n.01', 'name': 'makomako'}, {'id': 19131, 'synset': 'jamaican_cherry.n.01', 'name': 'Jamaican_cherry'}, {'id': 19132, 'synset': 'breakax.n.01', 'name': 'breakax'}, {'id': 19133, 'synset': 'sterculia.n.01', 'name': 'sterculia'}, {'id': 19134, 'synset': 'panama_tree.n.01', 'name': 'Panama_tree'}, {'id': 19135, 'synset': 'kalumpang.n.01', 'name': 'kalumpang'}, {'id': 19136, 'synset': 'bottle-tree.n.01', 'name': 'bottle-tree'}, {'id': 19137, 'synset': 'flame_tree.n.04', 'name': 'flame_tree'}, {'id': 19138, 'synset': 'flame_tree.n.03', 'name': 'flame_tree'}, {'id': 19139, 'synset': 'kurrajong.n.01', 'name': 'kurrajong'}, {'id': 19140, 'synset': 'queensland_bottletree.n.01', 'name': 'Queensland_bottletree'}, {'id': 19141, 'synset': 'kola.n.01', 'name': 'kola'}, {'id': 19142, 'synset': 'kola_nut.n.01', 'name': 'kola_nut'}, {'id': 19143, 'synset': 'chinese_parasol_tree.n.01', 'name': 'Chinese_parasol_tree'}, {'id': 19144, 'synset': 'flannelbush.n.01', 'name': 'flannelbush'}, {'id': 19145, 'synset': 'screw_tree.n.01', 'name': 'screw_tree'}, {'id': 19146, 'synset': 'nut-leaved_screw_tree.n.01', 'name': 'nut-leaved_screw_tree'}, {'id': 19147, 'synset': 'red_beech.n.02', 'name': 'red_beech'}, {'id': 19148, 'synset': 'looking_glass_tree.n.01', 'name': 'looking_glass_tree'}, {'id': 19149, 'synset': 'looking-glass_plant.n.01', 'name': 'looking-glass_plant'}, {'id': 19150, 'synset': 'honey_bell.n.01', 'name': 'honey_bell'}, {'id': 19151, 'synset': 'mayeng.n.01', 'name': 'mayeng'}, {'id': 19152, 'synset': 'silver_tree.n.02', 'name': 'silver_tree'}, {'id': 19153, 'synset': 'cacao.n.01', 'name': 'cacao'}, {'id': 19154, 'synset': 'obeche.n.02', 'name': 'obeche'}, {'id': 19155, 'synset': 'linden.n.02', 'name': 'linden'}, {'id': 19156, 'synset': 'american_basswood.n.01', 'name': 'American_basswood'}, {'id': 19157, 'synset': 'small-leaved_linden.n.01', 'name': 'small-leaved_linden'}, {'id': 19158, 'synset': 'white_basswood.n.01', 'name': 'white_basswood'}, {'id': 19159, 'synset': 'japanese_linden.n.01', 'name': 'Japanese_linden'}, {'id': 19160, 'synset': 'silver_lime.n.01', 'name': 'silver_lime'}, {'id': 19161, 'synset': 'corchorus.n.01', 'name': 'corchorus'}, {'id': 19162, 'synset': 'african_hemp.n.02', 'name': 'African_hemp'}, {'id': 19163, 'synset': 'herb.n.01', 'name': 'herb'}, {'id': 19164, 'synset': 'protea.n.01', 'name': 'protea'}, {'id': 19165, 'synset': 'honeypot.n.01', 'name': 'honeypot'}, {'id': 19166, 'synset': 'honeyflower.n.02', 'name': 'honeyflower'}, {'id': 19167, 'synset': 'banksia.n.01', 'name': 'banksia'}, {'id': 19168, 'synset': 'honeysuckle.n.02', 'name': 'honeysuckle'}, {'id': 19169, 'synset': 'smoke_bush.n.02', 'name': 'smoke_bush'}, {'id': 19170, 'synset': 'chilean_firebush.n.01', 'name': 'Chilean_firebush'}, {'id': 19171, 'synset': 'chilean_nut.n.01', 'name': 'Chilean_nut'}, {'id': 19172, 'synset': 'grevillea.n.01', 'name': 'grevillea'}, {'id': 19173, 'synset': 'red-flowered_silky_oak.n.01', 'name': 'red-flowered_silky_oak'}, {'id': 19174, 'synset': 'silky_oak.n.01', 'name': 'silky_oak'}, {'id': 19175, 'synset': 'beefwood.n.05', 'name': 'beefwood'}, {'id': 19176, 'synset': 'cushion_flower.n.01', 'name': 'cushion_flower'}, {'id': 19177, 'synset': 'rewa-rewa.n.01', 'name': 'rewa-rewa'}, {'id': 19178, 'synset': 'honeyflower.n.01', 'name': 'honeyflower'}, {'id': 19179, 'synset': 'silver_tree.n.01', 'name': 'silver_tree'}, {'id': 19180, 'synset': 'lomatia.n.01', 'name': 'lomatia'}, {'id': 19181, 'synset': 'macadamia.n.01', 'name': 'macadamia'}, {'id': 19182, 'synset': 'macadamia_integrifolia.n.01', 'name': 'Macadamia_integrifolia'}, {'id': 19183, 'synset': 'macadamia_nut.n.01', 'name': 'macadamia_nut'}, {'id': 19184, 'synset': 'queensland_nut.n.01', 'name': 'Queensland_nut'}, {'id': 19185, 'synset': 'prickly_ash.n.02', 'name': 'prickly_ash'}, {'id': 19186, 'synset': 'geebung.n.01', 'name': 'geebung'}, {'id': 19187, 'synset': 'wheel_tree.n.01', 'name': 'wheel_tree'}, {'id': 19188, 'synset': 'scrub_beefwood.n.01', 'name': 'scrub_beefwood'}, {'id': 19189, 'synset': 'waratah.n.02', 'name': 'waratah'}, {'id': 19190, 'synset': 'waratah.n.01', 'name': 'waratah'}, {'id': 19191, 'synset': 'casuarina.n.01', 'name': 'casuarina'}, {'id': 19192, 'synset': 'she-oak.n.01', 'name': 'she-oak'}, {'id': 19193, 'synset': 'beefwood.n.03', 'name': 'beefwood'}, {'id': 19194, 'synset': 'australian_pine.n.01', 'name': 'Australian_pine'}, {'id': 19195, 'synset': 'heath.n.01', 'name': 'heath'}, {'id': 19196, 'synset': 'tree_heath.n.02', 'name': 'tree_heath'}, {'id': 19197, 'synset': 'briarroot.n.01', 'name': 'briarroot'}, {'id': 19198, 'synset': 'winter_heath.n.01', 'name': 'winter_heath'}, {'id': 19199, 'synset': 'bell_heather.n.02', 'name': 'bell_heather'}, {'id': 19200, 'synset': 'cornish_heath.n.01', 'name': 'Cornish_heath'}, {'id': 19201, 'synset': 'spanish_heath.n.01', 'name': 'Spanish_heath'}, {'id': 19202, 'synset': "prince-of-wales'-heath.n.01", 'name': "Prince-of-Wales'-heath"}, {'id': 19203, 'synset': 'bog_rosemary.n.01', 'name': 'bog_rosemary'}, {'id': 19204, 'synset': 'marsh_andromeda.n.01', 'name': 'marsh_andromeda'}, {'id': 19205, 'synset': 'madrona.n.01', 'name': 'madrona'}, {'id': 19206, 'synset': 'strawberry_tree.n.01', 'name': 'strawberry_tree'}, {'id': 19207, 'synset': 'bearberry.n.03', 'name': 'bearberry'}, {'id': 19208, 'synset': 'alpine_bearberry.n.01', 'name': 'alpine_bearberry'}, {'id': 19209, 'synset': 'heartleaf_manzanita.n.01', 'name': 'heartleaf_manzanita'}, {'id': 19210, 'synset': 'parry_manzanita.n.01', 'name': 'Parry_manzanita'}, {'id': 19211, 'synset': 'spike_heath.n.01', 'name': 'spike_heath'}, {'id': 19212, 'synset': 'bryanthus.n.01', 'name': 'bryanthus'}, {'id': 19213, 'synset': 'leatherleaf.n.02', 'name': 'leatherleaf'}, {'id': 19214, 'synset': 'connemara_heath.n.01', 'name': 'Connemara_heath'}, {'id': 19215, 'synset': 'trailing_arbutus.n.01', 'name': 'trailing_arbutus'}, {'id': 19216, 'synset': 'creeping_snowberry.n.01', 'name': 'creeping_snowberry'}, {'id': 19217, 'synset': 'salal.n.01', 'name': 'salal'}, {'id': 19218, 'synset': 'huckleberry.n.02', 'name': 'huckleberry'}, {'id': 19219, 'synset': 'black_huckleberry.n.01', 'name': 'black_huckleberry'}, {'id': 19220, 'synset': 'dangleberry.n.01', 'name': 'dangleberry'}, {'id': 19221, 'synset': 'box_huckleberry.n.01', 'name': 'box_huckleberry'}, {'id': 19222, 'synset': 'kalmia.n.01', 'name': 'kalmia'}, {'id': 19223, 'synset': 'mountain_laurel.n.01', 'name': 'mountain_laurel'}, {'id': 19224, 'synset': 'swamp_laurel.n.01', 'name': 'swamp_laurel'}, {'id': 19225, 'synset': "trapper's_tea.n.01", 'name': "trapper's_tea"}, {'id': 19226, 'synset': 'wild_rosemary.n.01', 'name': 'wild_rosemary'}, {'id': 19227, 'synset': 'sand_myrtle.n.01', 'name': 'sand_myrtle'}, {'id': 19228, 'synset': 'leucothoe.n.01', 'name': 'leucothoe'}, {'id': 19229, 'synset': 'dog_laurel.n.01', 'name': 'dog_laurel'}, {'id': 19230, 'synset': 'sweet_bells.n.01', 'name': 'sweet_bells'}, {'id': 19231, 'synset': 'alpine_azalea.n.01', 'name': 'alpine_azalea'}, {'id': 19232, 'synset': 'staggerbush.n.01', 'name': 'staggerbush'}, {'id': 19233, 'synset': 'maleberry.n.01', 'name': 'maleberry'}, {'id': 19234, 'synset': 'fetterbush.n.02', 'name': 'fetterbush'}, {'id': 19235, 'synset': 'false_azalea.n.01', 'name': 'false_azalea'}, {'id': 19236, 'synset': 'minniebush.n.01', 'name': 'minniebush'}, {'id': 19237, 'synset': 'sorrel_tree.n.01', 'name': 'sorrel_tree'}, {'id': 19238, 'synset': 'mountain_heath.n.01', 'name': 'mountain_heath'}, {'id': 19239, 'synset': 'purple_heather.n.01', 'name': 'purple_heather'}, {'id': 19240, 'synset': 'fetterbush.n.01', 'name': 'fetterbush'}, {'id': 19241, 'synset': 'rhododendron.n.01', 'name': 'rhododendron'}, {'id': 19242, 'synset': 'coast_rhododendron.n.01', 'name': 'coast_rhododendron'}, {'id': 19243, 'synset': 'rosebay.n.01', 'name': 'rosebay'}, {'id': 19244, 'synset': 'swamp_azalea.n.01', 'name': 'swamp_azalea'}, {'id': 19245, 'synset': 'azalea.n.01', 'name': 'azalea'}, {'id': 19246, 'synset': 'cranberry.n.01', 'name': 'cranberry'}, {'id': 19247, 'synset': 'american_cranberry.n.01', 'name': 'American_cranberry'}, {'id': 19248, 'synset': 'european_cranberry.n.01', 'name': 'European_cranberry'}, {'id': 19249, 'synset': 'blueberry.n.01', 'name': 'blueberry'}, {'id': 19250, 'synset': 'farkleberry.n.01', 'name': 'farkleberry'}, {'id': 19251, 'synset': 'low-bush_blueberry.n.01', 'name': 'low-bush_blueberry'}, {'id': 19252, 'synset': 'rabbiteye_blueberry.n.01', 'name': 'rabbiteye_blueberry'}, {'id': 19253, 'synset': 'dwarf_bilberry.n.01', 'name': 'dwarf_bilberry'}, {'id': 19254, 'synset': 'evergreen_blueberry.n.01', 'name': 'evergreen_blueberry'}, {'id': 19255, 'synset': 'evergreen_huckleberry.n.01', 'name': 'evergreen_huckleberry'}, {'id': 19256, 'synset': 'bilberry.n.02', 'name': 'bilberry'}, {'id': 19257, 'synset': 'bilberry.n.01', 'name': 'bilberry'}, {'id': 19258, 'synset': 'bog_bilberry.n.01', 'name': 'bog_bilberry'}, {'id': 19259, 'synset': 'dryland_blueberry.n.01', 'name': 'dryland_blueberry'}, {'id': 19260, 'synset': 'grouseberry.n.01', 'name': 'grouseberry'}, {'id': 19261, 'synset': 'deerberry.n.01', 'name': 'deerberry'}, {'id': 19262, 'synset': 'cowberry.n.01', 'name': 'cowberry'}, {'id': 19263, 'synset': 'diapensia.n.01', 'name': 'diapensia'}, {'id': 19264, 'synset': 'galax.n.01', 'name': 'galax'}, {'id': 19265, 'synset': 'pyxie.n.01', 'name': 'pyxie'}, {'id': 19266, 'synset': 'shortia.n.01', 'name': 'shortia'}, {'id': 19267, 'synset': 'oconee_bells.n.01', 'name': 'oconee_bells'}, {'id': 19268, 'synset': 'australian_heath.n.01', 'name': 'Australian_heath'}, {'id': 19269, 'synset': 'epacris.n.01', 'name': 'epacris'}, {'id': 19270, 'synset': 'common_heath.n.02', 'name': 'common_heath'}, {'id': 19271, 'synset': 'common_heath.n.01', 'name': 'common_heath'}, {'id': 19272, 'synset': 'port_jackson_heath.n.01', 'name': 'Port_Jackson_heath'}, {'id': 19273, 'synset': 'native_cranberry.n.01', 'name': 'native_cranberry'}, {'id': 19274, 'synset': 'pink_fivecorner.n.01', 'name': 'pink_fivecorner'}, {'id': 19275, 'synset': 'wintergreen.n.01', 'name': 'wintergreen'}, {'id': 19276, 'synset': 'false_wintergreen.n.01', 'name': 'false_wintergreen'}, {'id': 19277, 'synset': 'lesser_wintergreen.n.01', 'name': 'lesser_wintergreen'}, {'id': 19278, 'synset': 'wild_lily_of_the_valley.n.02', 'name': 'wild_lily_of_the_valley'}, {'id': 19279, 'synset': 'wild_lily_of_the_valley.n.01', 'name': 'wild_lily_of_the_valley'}, {'id': 19280, 'synset': 'pipsissewa.n.01', 'name': 'pipsissewa'}, {'id': 19281, 'synset': 'love-in-winter.n.01', 'name': 'love-in-winter'}, {'id': 19282, 'synset': 'one-flowered_wintergreen.n.01', 'name': 'one-flowered_wintergreen'}, {'id': 19283, 'synset': 'indian_pipe.n.01', 'name': 'Indian_pipe'}, {'id': 19284, 'synset': 'pinesap.n.01', 'name': 'pinesap'}, {'id': 19285, 'synset': 'beech.n.01', 'name': 'beech'}, {'id': 19286, 'synset': 'common_beech.n.01', 'name': 'common_beech'}, {'id': 19287, 'synset': 'copper_beech.n.01', 'name': 'copper_beech'}, {'id': 19288, 'synset': 'american_beech.n.01', 'name': 'American_beech'}, {'id': 19289, 'synset': 'weeping_beech.n.01', 'name': 'weeping_beech'}, {'id': 19290, 'synset': 'japanese_beech.n.01', 'name': 'Japanese_beech'}, {'id': 19291, 'synset': 'chestnut.n.02', 'name': 'chestnut'}, {'id': 19292, 'synset': 'american_chestnut.n.01', 'name': 'American_chestnut'}, {'id': 19293, 'synset': 'european_chestnut.n.01', 'name': 'European_chestnut'}, {'id': 19294, 'synset': 'chinese_chestnut.n.01', 'name': 'Chinese_chestnut'}, {'id': 19295, 'synset': 'japanese_chestnut.n.01', 'name': 'Japanese_chestnut'}, {'id': 19296, 'synset': 'allegheny_chinkapin.n.01', 'name': 'Allegheny_chinkapin'}, {'id': 19297, 'synset': 'ozark_chinkapin.n.01', 'name': 'Ozark_chinkapin'}, {'id': 19298, 'synset': 'oak_chestnut.n.01', 'name': 'oak_chestnut'}, {'id': 19299, 'synset': 'giant_chinkapin.n.01', 'name': 'giant_chinkapin'}, {'id': 19300, 'synset': 'dwarf_golden_chinkapin.n.01', 'name': 'dwarf_golden_chinkapin'}, {'id': 19301, 'synset': 'tanbark_oak.n.01', 'name': 'tanbark_oak'}, {'id': 19302, 'synset': 'japanese_oak.n.02', 'name': 'Japanese_oak'}, {'id': 19303, 'synset': 'southern_beech.n.01', 'name': 'southern_beech'}, {'id': 19304, 'synset': 'myrtle_beech.n.01', 'name': 'myrtle_beech'}, {'id': 19305, 'synset': 'coigue.n.01', 'name': 'Coigue'}, {'id': 19306, 'synset': 'new_zealand_beech.n.01', 'name': 'New_Zealand_beech'}, {'id': 19307, 'synset': 'silver_beech.n.01', 'name': 'silver_beech'}, {'id': 19308, 'synset': 'roble_beech.n.01', 'name': 'roble_beech'}, {'id': 19309, 'synset': 'rauli_beech.n.01', 'name': 'rauli_beech'}, {'id': 19310, 'synset': 'black_beech.n.01', 'name': 'black_beech'}, {'id': 19311, 'synset': 'hard_beech.n.01', 'name': 'hard_beech'}, {'id': 19312, 'synset': 'acorn.n.01', 'name': 'acorn'}, {'id': 19313, 'synset': 'cupule.n.01', 'name': 'cupule'}, {'id': 19314, 'synset': 'oak.n.02', 'name': 'oak'}, {'id': 19315, 'synset': 'live_oak.n.01', 'name': 'live_oak'}, {'id': 19316, 'synset': 'coast_live_oak.n.01', 'name': 'coast_live_oak'}, {'id': 19317, 'synset': 'white_oak.n.01', 'name': 'white_oak'}, {'id': 19318, 'synset': 'american_white_oak.n.01', 'name': 'American_white_oak'}, {'id': 19319, 'synset': 'arizona_white_oak.n.01', 'name': 'Arizona_white_oak'}, {'id': 19320, 'synset': 'swamp_white_oak.n.01', 'name': 'swamp_white_oak'}, {'id': 19321, 'synset': 'european_turkey_oak.n.01', 'name': 'European_turkey_oak'}, {'id': 19322, 'synset': 'canyon_oak.n.01', 'name': 'canyon_oak'}, {'id': 19323, 'synset': 'scarlet_oak.n.01', 'name': 'scarlet_oak'}, {'id': 19324, 'synset': 'jack_oak.n.02', 'name': 'jack_oak'}, {'id': 19325, 'synset': 'red_oak.n.01', 'name': 'red_oak'}, {'id': 19326, 'synset': 'southern_red_oak.n.01', 'name': 'southern_red_oak'}, {'id': 19327, 'synset': 'oregon_white_oak.n.01', 'name': 'Oregon_white_oak'}, {'id': 19328, 'synset': 'holm_oak.n.02', 'name': 'holm_oak'}, {'id': 19329, 'synset': 'bear_oak.n.01', 'name': 'bear_oak'}, {'id': 19330, 'synset': 'shingle_oak.n.01', 'name': 'shingle_oak'}, {'id': 19331, 'synset': 'bluejack_oak.n.01', 'name': 'bluejack_oak'}, {'id': 19332, 'synset': 'california_black_oak.n.01', 'name': 'California_black_oak'}, {'id': 19333, 'synset': 'american_turkey_oak.n.01', 'name': 'American_turkey_oak'}, {'id': 19334, 'synset': 'laurel_oak.n.01', 'name': 'laurel_oak'}, {'id': 19335, 'synset': 'california_white_oak.n.01', 'name': 'California_white_oak'}, {'id': 19336, 'synset': 'overcup_oak.n.01', 'name': 'overcup_oak'}, {'id': 19337, 'synset': 'bur_oak.n.01', 'name': 'bur_oak'}, {'id': 19338, 'synset': 'scrub_oak.n.01', 'name': 'scrub_oak'}, {'id': 19339, 'synset': 'blackjack_oak.n.01', 'name': 'blackjack_oak'}, {'id': 19340, 'synset': 'swamp_chestnut_oak.n.01', 'name': 'swamp_chestnut_oak'}, {'id': 19341, 'synset': 'japanese_oak.n.01', 'name': 'Japanese_oak'}, {'id': 19342, 'synset': 'chestnut_oak.n.01', 'name': 'chestnut_oak'}, {'id': 19343, 'synset': 'chinquapin_oak.n.01', 'name': 'chinquapin_oak'}, {'id': 19344, 'synset': 'myrtle_oak.n.01', 'name': 'myrtle_oak'}, {'id': 19345, 'synset': 'water_oak.n.01', 'name': 'water_oak'}, {'id': 19346, 'synset': 'nuttall_oak.n.01', 'name': 'Nuttall_oak'}, {'id': 19347, 'synset': 'durmast.n.01', 'name': 'durmast'}, {'id': 19348, 'synset': 'basket_oak.n.01', 'name': 'basket_oak'}, {'id': 19349, 'synset': 'pin_oak.n.01', 'name': 'pin_oak'}, {'id': 19350, 'synset': 'willow_oak.n.01', 'name': 'willow_oak'}, {'id': 19351, 'synset': 'dwarf_chinkapin_oak.n.01', 'name': 'dwarf_chinkapin_oak'}, {'id': 19352, 'synset': 'common_oak.n.01', 'name': 'common_oak'}, {'id': 19353, 'synset': 'northern_red_oak.n.01', 'name': 'northern_red_oak'}, {'id': 19354, 'synset': 'shumard_oak.n.01', 'name': 'Shumard_oak'}, {'id': 19355, 'synset': 'post_oak.n.01', 'name': 'post_oak'}, {'id': 19356, 'synset': 'cork_oak.n.01', 'name': 'cork_oak'}, {'id': 19357, 'synset': 'spanish_oak.n.01', 'name': 'Spanish_oak'}, {'id': 19358, 'synset': 'huckleberry_oak.n.01', 'name': 'huckleberry_oak'}, {'id': 19359, 'synset': 'chinese_cork_oak.n.01', 'name': 'Chinese_cork_oak'}, {'id': 19360, 'synset': 'black_oak.n.01', 'name': 'black_oak'}, {'id': 19361, 'synset': 'southern_live_oak.n.01', 'name': 'southern_live_oak'}, {'id': 19362, 'synset': 'interior_live_oak.n.01', 'name': 'interior_live_oak'}, {'id': 19363, 'synset': 'mast.n.02', 'name': 'mast'}, {'id': 19364, 'synset': 'birch.n.02', 'name': 'birch'}, {'id': 19365, 'synset': 'yellow_birch.n.01', 'name': 'yellow_birch'}, {'id': 19366, 'synset': 'american_white_birch.n.01', 'name': 'American_white_birch'}, {'id': 19367, 'synset': 'grey_birch.n.01', 'name': 'grey_birch'}, {'id': 19368, 'synset': 'silver_birch.n.01', 'name': 'silver_birch'}, {'id': 19369, 'synset': 'downy_birch.n.01', 'name': 'downy_birch'}, {'id': 19370, 'synset': 'black_birch.n.02', 'name': 'black_birch'}, {'id': 19371, 'synset': 'sweet_birch.n.01', 'name': 'sweet_birch'}, {'id': 19372, 'synset': 'yukon_white_birch.n.01', 'name': 'Yukon_white_birch'}, {'id': 19373, 'synset': 'swamp_birch.n.01', 'name': 'swamp_birch'}, {'id': 19374, 'synset': 'newfoundland_dwarf_birch.n.01', 'name': 'Newfoundland_dwarf_birch'}, {'id': 19375, 'synset': 'alder.n.02', 'name': 'alder'}, {'id': 19376, 'synset': 'common_alder.n.01', 'name': 'common_alder'}, {'id': 19377, 'synset': 'grey_alder.n.01', 'name': 'grey_alder'}, {'id': 19378, 'synset': 'seaside_alder.n.01', 'name': 'seaside_alder'}, {'id': 19379, 'synset': 'white_alder.n.01', 'name': 'white_alder'}, {'id': 19380, 'synset': 'red_alder.n.01', 'name': 'red_alder'}, {'id': 19381, 'synset': 'speckled_alder.n.01', 'name': 'speckled_alder'}, {'id': 19382, 'synset': 'smooth_alder.n.01', 'name': 'smooth_alder'}, {'id': 19383, 'synset': 'green_alder.n.02', 'name': 'green_alder'}, {'id': 19384, 'synset': 'green_alder.n.01', 'name': 'green_alder'}, {'id': 19385, 'synset': 'hornbeam.n.01', 'name': 'hornbeam'}, {'id': 19386, 'synset': 'european_hornbeam.n.01', 'name': 'European_hornbeam'}, {'id': 19387, 'synset': 'american_hornbeam.n.01', 'name': 'American_hornbeam'}, {'id': 19388, 'synset': 'hop_hornbeam.n.01', 'name': 'hop_hornbeam'}, {'id': 19389, 'synset': 'old_world_hop_hornbeam.n.01', 'name': 'Old_World_hop_hornbeam'}, {'id': 19390, 'synset': 'eastern_hop_hornbeam.n.01', 'name': 'Eastern_hop_hornbeam'}, {'id': 19391, 'synset': 'hazelnut.n.01', 'name': 'hazelnut'}, {'id': 19392, 'synset': 'american_hazel.n.01', 'name': 'American_hazel'}, {'id': 19393, 'synset': 'cobnut.n.01', 'name': 'cobnut'}, {'id': 19394, 'synset': 'beaked_hazelnut.n.01', 'name': 'beaked_hazelnut'}, {'id': 19395, 'synset': 'centaury.n.01', 'name': 'centaury'}, {'id': 19396, 'synset': 'rosita.n.01', 'name': 'rosita'}, {'id': 19397, 'synset': 'lesser_centaury.n.01', 'name': 'lesser_centaury'}, {'id': 19398, 'synset': 'seaside_centaury.n.01', 'name': 'seaside_centaury'}, {'id': 19399, 'synset': 'slender_centaury.n.01', 'name': 'slender_centaury'}, {'id': 19400, 'synset': 'prairie_gentian.n.01', 'name': 'prairie_gentian'}, {'id': 19401, 'synset': 'persian_violet.n.01', 'name': 'Persian_violet'}, {'id': 19402, 'synset': 'columbo.n.01', 'name': 'columbo'}, {'id': 19403, 'synset': 'gentian.n.01', 'name': 'gentian'}, {'id': 19404, 'synset': 'gentianella.n.02', 'name': 'gentianella'}, {'id': 19405, 'synset': 'closed_gentian.n.02', 'name': 'closed_gentian'}, {'id': 19406, 'synset': "explorer's_gentian.n.01", 'name': "explorer's_gentian"}, {'id': 19407, 'synset': 'closed_gentian.n.01', 'name': 'closed_gentian'}, {'id': 19408, 'synset': 'great_yellow_gentian.n.01', 'name': 'great_yellow_gentian'}, {'id': 19409, 'synset': 'marsh_gentian.n.01', 'name': 'marsh_gentian'}, {'id': 19410, 'synset': 'soapwort_gentian.n.01', 'name': 'soapwort_gentian'}, {'id': 19411, 'synset': 'striped_gentian.n.01', 'name': 'striped_gentian'}, {'id': 19412, 'synset': 'agueweed.n.01', 'name': 'agueweed'}, {'id': 19413, 'synset': 'felwort.n.01', 'name': 'felwort'}, {'id': 19414, 'synset': 'fringed_gentian.n.01', 'name': 'fringed_gentian'}, {'id': 19415, 'synset': 'gentianopsis_crinita.n.01', 'name': 'Gentianopsis_crinita'}, {'id': 19416, 'synset': 'gentianopsis_detonsa.n.01', 'name': 'Gentianopsis_detonsa'}, {'id': 19417, 'synset': 'gentianopsid_procera.n.01', 'name': 'Gentianopsid_procera'}, {'id': 19418, 'synset': 'gentianopsis_thermalis.n.01', 'name': 'Gentianopsis_thermalis'}, {'id': 19419, 'synset': 'tufted_gentian.n.01', 'name': 'tufted_gentian'}, {'id': 19420, 'synset': 'spurred_gentian.n.01', 'name': 'spurred_gentian'}, {'id': 19421, 'synset': 'sabbatia.n.01', 'name': 'sabbatia'}, {'id': 19422, 'synset': 'toothbrush_tree.n.01', 'name': 'toothbrush_tree'}, {'id': 19423, 'synset': 'olive_tree.n.01', 'name': 'olive_tree'}, {'id': 19424, 'synset': 'olive.n.02', 'name': 'olive'}, {'id': 19425, 'synset': 'olive.n.01', 'name': 'olive'}, {'id': 19426, 'synset': 'black_maire.n.01', 'name': 'black_maire'}, {'id': 19427, 'synset': 'white_maire.n.01', 'name': 'white_maire'}, {'id': 19428, 'synset': 'fringe_tree.n.01', 'name': 'fringe_tree'}, {'id': 19429, 'synset': 'fringe_bush.n.01', 'name': 'fringe_bush'}, {'id': 19430, 'synset': 'forestiera.n.01', 'name': 'forestiera'}, {'id': 19431, 'synset': 'forsythia.n.01', 'name': 'forsythia'}, {'id': 19432, 'synset': 'ash.n.02', 'name': 'ash'}, {'id': 19433, 'synset': 'white_ash.n.02', 'name': 'white_ash'}, {'id': 19434, 'synset': 'swamp_ash.n.01', 'name': 'swamp_ash'}, {'id': 19435, 'synset': 'flowering_ash.n.03', 'name': 'flowering_ash'}, {'id': 19436, 'synset': 'european_ash.n.01', 'name': 'European_ash'}, {'id': 19437, 'synset': 'oregon_ash.n.01', 'name': 'Oregon_ash'}, {'id': 19438, 'synset': 'black_ash.n.01', 'name': 'black_ash'}, {'id': 19439, 'synset': 'manna_ash.n.01', 'name': 'manna_ash'}, {'id': 19440, 'synset': 'red_ash.n.01', 'name': 'red_ash'}, {'id': 19441, 'synset': 'green_ash.n.01', 'name': 'green_ash'}, {'id': 19442, 'synset': 'blue_ash.n.01', 'name': 'blue_ash'}, {'id': 19443, 'synset': 'mountain_ash.n.03', 'name': 'mountain_ash'}, {'id': 19444, 'synset': 'pumpkin_ash.n.01', 'name': 'pumpkin_ash'}, {'id': 19445, 'synset': 'arizona_ash.n.01', 'name': 'Arizona_ash'}, {'id': 19446, 'synset': 'jasmine.n.01', 'name': 'jasmine'}, {'id': 19447, 'synset': 'primrose_jasmine.n.01', 'name': 'primrose_jasmine'}, {'id': 19448, 'synset': 'winter_jasmine.n.01', 'name': 'winter_jasmine'}, {'id': 19449, 'synset': 'common_jasmine.n.01', 'name': 'common_jasmine'}, {'id': 19450, 'synset': 'privet.n.01', 'name': 'privet'}, {'id': 19451, 'synset': 'amur_privet.n.01', 'name': 'Amur_privet'}, {'id': 19452, 'synset': 'japanese_privet.n.01', 'name': 'Japanese_privet'}, {'id': 19453, 'synset': 'ligustrum_obtusifolium.n.01', 'name': 'Ligustrum_obtusifolium'}, {'id': 19454, 'synset': 'common_privet.n.01', 'name': 'common_privet'}, {'id': 19455, 'synset': 'devilwood.n.01', 'name': 'devilwood'}, {'id': 19456, 'synset': 'mock_privet.n.01', 'name': 'mock_privet'}, {'id': 19457, 'synset': 'lilac.n.01', 'name': 'lilac'}, {'id': 19458, 'synset': 'himalayan_lilac.n.01', 'name': 'Himalayan_lilac'}, {'id': 19459, 'synset': 'persian_lilac.n.02', 'name': 'Persian_lilac'}, {'id': 19460, 'synset': 'japanese_tree_lilac.n.01', 'name': 'Japanese_tree_lilac'}, {'id': 19461, 'synset': 'japanese_lilac.n.01', 'name': 'Japanese_lilac'}, {'id': 19462, 'synset': 'common_lilac.n.01', 'name': 'common_lilac'}, {'id': 19463, 'synset': 'bloodwort.n.01', 'name': 'bloodwort'}, {'id': 19464, 'synset': 'kangaroo_paw.n.01', 'name': 'kangaroo_paw'}, {'id': 19465, 'synset': 'virginian_witch_hazel.n.01', 'name': 'Virginian_witch_hazel'}, {'id': 19466, 'synset': 'vernal_witch_hazel.n.01', 'name': 'vernal_witch_hazel'}, {'id': 19467, 'synset': 'winter_hazel.n.01', 'name': 'winter_hazel'}, {'id': 19468, 'synset': 'fothergilla.n.01', 'name': 'fothergilla'}, {'id': 19469, 'synset': 'liquidambar.n.02', 'name': 'liquidambar'}, {'id': 19470, 'synset': 'sweet_gum.n.03', 'name': 'sweet_gum'}, {'id': 19471, 'synset': 'iron_tree.n.01', 'name': 'iron_tree'}, {'id': 19472, 'synset': 'walnut.n.03', 'name': 'walnut'}, {'id': 19473, 'synset': 'california_black_walnut.n.01', 'name': 'California_black_walnut'}, {'id': 19474, 'synset': 'butternut.n.01', 'name': 'butternut'}, {'id': 19475, 'synset': 'black_walnut.n.01', 'name': 'black_walnut'}, {'id': 19476, 'synset': 'english_walnut.n.01', 'name': 'English_walnut'}, {'id': 19477, 'synset': 'hickory.n.02', 'name': 'hickory'}, {'id': 19478, 'synset': 'water_hickory.n.01', 'name': 'water_hickory'}, {'id': 19479, 'synset': 'pignut.n.01', 'name': 'pignut'}, {'id': 19480, 'synset': 'bitternut.n.01', 'name': 'bitternut'}, {'id': 19481, 'synset': 'pecan.n.02', 'name': 'pecan'}, {'id': 19482, 'synset': 'big_shellbark.n.01', 'name': 'big_shellbark'}, {'id': 19483, 'synset': 'nutmeg_hickory.n.01', 'name': 'nutmeg_hickory'}, {'id': 19484, 'synset': 'shagbark.n.01', 'name': 'shagbark'}, {'id': 19485, 'synset': 'mockernut.n.01', 'name': 'mockernut'}, {'id': 19486, 'synset': 'wing_nut.n.01', 'name': 'wing_nut'}, {'id': 19487, 'synset': 'caucasian_walnut.n.01', 'name': 'Caucasian_walnut'}, {'id': 19488, 'synset': 'dhawa.n.01', 'name': 'dhawa'}, {'id': 19489, 'synset': 'combretum.n.01', 'name': 'combretum'}, {'id': 19490, 'synset': 'hiccup_nut.n.01', 'name': 'hiccup_nut'}, {'id': 19491, 'synset': 'bush_willow.n.02', 'name': 'bush_willow'}, {'id': 19492, 'synset': 'bush_willow.n.01', 'name': 'bush_willow'}, {'id': 19493, 'synset': 'button_tree.n.01', 'name': 'button_tree'}, {'id': 19494, 'synset': 'white_mangrove.n.02', 'name': 'white_mangrove'}, {'id': 19495, 'synset': 'oleaster.n.01', 'name': 'oleaster'}, {'id': 19496, 'synset': 'water_milfoil.n.01', 'name': 'water_milfoil'}, {'id': 19497, 'synset': 'anchovy_pear.n.01', 'name': 'anchovy_pear'}, {'id': 19498, 'synset': 'brazil_nut.n.01', 'name': 'brazil_nut'}, {'id': 19499, 'synset': 'loosestrife.n.01', 'name': 'loosestrife'}, {'id': 19500, 'synset': 'purple_loosestrife.n.01', 'name': 'purple_loosestrife'}, {'id': 19501, 'synset': 'grass_poly.n.01', 'name': 'grass_poly'}, {'id': 19502, 'synset': 'crape_myrtle.n.01', 'name': 'crape_myrtle'}, {'id': 19503, 'synset': "queen's_crape_myrtle.n.01", 'name': "Queen's_crape_myrtle"}, {'id': 19504, 'synset': 'myrtaceous_tree.n.01', 'name': 'myrtaceous_tree'}, {'id': 19505, 'synset': 'myrtle.n.02', 'name': 'myrtle'}, {'id': 19506, 'synset': 'common_myrtle.n.01', 'name': 'common_myrtle'}, {'id': 19507, 'synset': 'bayberry.n.01', 'name': 'bayberry'}, {'id': 19508, 'synset': 'allspice.n.01', 'name': 'allspice'}, {'id': 19509, 'synset': 'allspice_tree.n.01', 'name': 'allspice_tree'}, {'id': 19510, 'synset': 'sour_cherry.n.02', 'name': 'sour_cherry'}, {'id': 19511, 'synset': 'nakedwood.n.02', 'name': 'nakedwood'}, {'id': 19512, 'synset': 'surinam_cherry.n.02', 'name': 'Surinam_cherry'}, {'id': 19513, 'synset': 'rose_apple.n.01', 'name': 'rose_apple'}, {'id': 19514, 'synset': 'feijoa.n.01', 'name': 'feijoa'}, {'id': 19515, 'synset': 'jaboticaba.n.01', 'name': 'jaboticaba'}, {'id': 19516, 'synset': 'guava.n.02', 'name': 'guava'}, {'id': 19517, 'synset': 'guava.n.01', 'name': 'guava'}, {'id': 19518, 'synset': 'cattley_guava.n.01', 'name': 'cattley_guava'}, {'id': 19519, 'synset': 'brazilian_guava.n.01', 'name': 'Brazilian_guava'}, {'id': 19520, 'synset': 'gum_tree.n.01', 'name': 'gum_tree'}, {'id': 19521, 'synset': 'eucalyptus.n.02', 'name': 'eucalyptus'}, {'id': 19522, 'synset': 'flooded_gum.n.01', 'name': 'flooded_gum'}, {'id': 19523, 'synset': 'mallee.n.01', 'name': 'mallee'}, {'id': 19524, 'synset': 'stringybark.n.01', 'name': 'stringybark'}, {'id': 19525, 'synset': 'smoothbark.n.01', 'name': 'smoothbark'}, {'id': 19526, 'synset': 'red_gum.n.03', 'name': 'red_gum'}, {'id': 19527, 'synset': 'red_gum.n.02', 'name': 'red_gum'}, {'id': 19528, 'synset': 'river_red_gum.n.01', 'name': 'river_red_gum'}, {'id': 19529, 'synset': 'mountain_swamp_gum.n.01', 'name': 'mountain_swamp_gum'}, {'id': 19530, 'synset': 'snow_gum.n.01', 'name': 'snow_gum'}, {'id': 19531, 'synset': 'alpine_ash.n.01', 'name': 'alpine_ash'}, {'id': 19532, 'synset': 'white_mallee.n.01', 'name': 'white_mallee'}, {'id': 19533, 'synset': 'white_stringybark.n.01', 'name': 'white_stringybark'}, {'id': 19534, 'synset': 'white_mountain_ash.n.01', 'name': 'white_mountain_ash'}, {'id': 19535, 'synset': 'blue_gum.n.01', 'name': 'blue_gum'}, {'id': 19536, 'synset': 'rose_gum.n.01', 'name': 'rose_gum'}, {'id': 19537, 'synset': 'cider_gum.n.01', 'name': 'cider_gum'}, {'id': 19538, 'synset': 'swamp_gum.n.01', 'name': 'swamp_gum'}, {'id': 19539, 'synset': 'spotted_gum.n.01', 'name': 'spotted_gum'}, {'id': 19540, 'synset': 'lemon-scented_gum.n.01', 'name': 'lemon-scented_gum'}, {'id': 19541, 'synset': 'black_mallee.n.01', 'name': 'black_mallee'}, {'id': 19542, 'synset': 'forest_red_gum.n.01', 'name': 'forest_red_gum'}, {'id': 19543, 'synset': 'mountain_ash.n.02', 'name': 'mountain_ash'}, {'id': 19544, 'synset': 'manna_gum.n.01', 'name': 'manna_gum'}, {'id': 19545, 'synset': 'clove.n.02', 'name': 'clove'}, {'id': 19546, 'synset': 'clove.n.01', 'name': 'clove'}, {'id': 19547, 'synset': 'tupelo.n.02', 'name': 'tupelo'}, {'id': 19548, 'synset': 'water_gum.n.01', 'name': 'water_gum'}, {'id': 19549, 'synset': 'sour_gum.n.01', 'name': 'sour_gum'}, {'id': 19550, 'synset': "enchanter's_nightshade.n.01", 'name': "enchanter's_nightshade"}, {'id': 19551, 'synset': 'circaea_lutetiana.n.01', 'name': 'Circaea_lutetiana'}, {'id': 19552, 'synset': 'willowherb.n.01', 'name': 'willowherb'}, {'id': 19553, 'synset': 'fireweed.n.01', 'name': 'fireweed'}, {'id': 19554, 'synset': 'california_fuchsia.n.01', 'name': 'California_fuchsia'}, {'id': 19555, 'synset': 'fuchsia.n.01', 'name': 'fuchsia'}, {'id': 19556, 'synset': "lady's-eardrop.n.01", 'name': "lady's-eardrop"}, {'id': 19557, 'synset': 'evening_primrose.n.01', 'name': 'evening_primrose'}, {'id': 19558, 'synset': 'common_evening_primrose.n.01', 'name': 'common_evening_primrose'}, {'id': 19559, 'synset': 'sundrops.n.01', 'name': 'sundrops'}, {'id': 19560, 'synset': 'missouri_primrose.n.01', 'name': 'Missouri_primrose'}, {'id': 19561, 'synset': 'pomegranate.n.01', 'name': 'pomegranate'}, {'id': 19562, 'synset': 'mangrove.n.01', 'name': 'mangrove'}, {'id': 19563, 'synset': 'daphne.n.01', 'name': 'daphne'}, {'id': 19564, 'synset': 'garland_flower.n.01', 'name': 'garland_flower'}, {'id': 19565, 'synset': 'spurge_laurel.n.01', 'name': 'spurge_laurel'}, {'id': 19566, 'synset': 'mezereon.n.01', 'name': 'mezereon'}, {'id': 19567, 'synset': 'indian_rhododendron.n.01', 'name': 'Indian_rhododendron'}, {'id': 19568, 'synset': 'medinilla_magnifica.n.01', 'name': 'Medinilla_magnifica'}, {'id': 19569, 'synset': 'deer_grass.n.01', 'name': 'deer_grass'}, {'id': 19570, 'synset': 'canna.n.01', 'name': 'canna'}, {'id': 19571, 'synset': 'achira.n.01', 'name': 'achira'}, {'id': 19572, 'synset': 'arrowroot.n.02', 'name': 'arrowroot'}, {'id': 19573, 'synset': 'banana.n.01', 'name': 'banana'}, {'id': 19574, 'synset': 'dwarf_banana.n.01', 'name': 'dwarf_banana'}, {'id': 19575, 'synset': 'japanese_banana.n.01', 'name': 'Japanese_banana'}, {'id': 19576, 'synset': 'plantain.n.02', 'name': 'plantain'}, {'id': 19577, 'synset': 'edible_banana.n.01', 'name': 'edible_banana'}, {'id': 19578, 'synset': 'abaca.n.02', 'name': 'abaca'}, {'id': 19579, 'synset': 'abyssinian_banana.n.01', 'name': 'Abyssinian_banana'}, {'id': 19580, 'synset': 'ginger.n.01', 'name': 'ginger'}, {'id': 19581, 'synset': 'common_ginger.n.01', 'name': 'common_ginger'}, {'id': 19582, 'synset': 'turmeric.n.01', 'name': 'turmeric'}, {'id': 19583, 'synset': 'galangal.n.01', 'name': 'galangal'}, {'id': 19584, 'synset': 'shellflower.n.02', 'name': 'shellflower'}, {'id': 19585, 'synset': 'grains_of_paradise.n.01', 'name': 'grains_of_paradise'}, {'id': 19586, 'synset': 'cardamom.n.01', 'name': 'cardamom'}, {'id': 19587, 'synset': 'begonia.n.01', 'name': 'begonia'}, {'id': 19588, 'synset': 'fibrous-rooted_begonia.n.01', 'name': 'fibrous-rooted_begonia'}, {'id': 19589, 'synset': 'tuberous_begonia.n.01', 'name': 'tuberous_begonia'}, {'id': 19590, 'synset': 'rhizomatous_begonia.n.01', 'name': 'rhizomatous_begonia'}, {'id': 19591, 'synset': 'christmas_begonia.n.01', 'name': 'Christmas_begonia'}, {'id': 19592, 'synset': 'angel-wing_begonia.n.01', 'name': 'angel-wing_begonia'}, {'id': 19593, 'synset': 'beefsteak_begonia.n.01', 'name': 'beefsteak_begonia'}, {'id': 19594, 'synset': 'star_begonia.n.01', 'name': 'star_begonia'}, {'id': 19595, 'synset': 'rex_begonia.n.01', 'name': 'rex_begonia'}, {'id': 19596, 'synset': 'wax_begonia.n.01', 'name': 'wax_begonia'}, {'id': 19597, 'synset': 'socotra_begonia.n.01', 'name': 'Socotra_begonia'}, {'id': 19598, 'synset': 'hybrid_tuberous_begonia.n.01', 'name': 'hybrid_tuberous_begonia'}, {'id': 19599, 'synset': 'dillenia.n.01', 'name': 'dillenia'}, {'id': 19600, 'synset': 'guinea_gold_vine.n.01', 'name': 'guinea_gold_vine'}, {'id': 19601, 'synset': 'poon.n.02', 'name': 'poon'}, {'id': 19602, 'synset': 'calaba.n.01', 'name': 'calaba'}, {'id': 19603, 'synset': 'maria.n.02', 'name': 'Maria'}, {'id': 19604, 'synset': 'laurelwood.n.01', 'name': 'laurelwood'}, {'id': 19605, 'synset': 'alexandrian_laurel.n.01', 'name': 'Alexandrian_laurel'}, {'id': 19606, 'synset': 'clusia.n.01', 'name': 'clusia'}, {'id': 19607, 'synset': 'wild_fig.n.02', 'name': 'wild_fig'}, {'id': 19608, 'synset': 'waxflower.n.02', 'name': 'waxflower'}, {'id': 19609, 'synset': 'pitch_apple.n.01', 'name': 'pitch_apple'}, {'id': 19610, 'synset': 'mangosteen.n.01', 'name': 'mangosteen'}, {'id': 19611, 'synset': 'gamboge_tree.n.01', 'name': 'gamboge_tree'}, {'id': 19612, 'synset': "st_john's_wort.n.01", 'name': "St_John's_wort"}, {'id': 19613, 'synset': "common_st_john's_wort.n.01", 'name': "common_St_John's_wort"}, {'id': 19614, 'synset': "great_st_john's_wort.n.01", 'name': "great_St_John's_wort"}, {'id': 19615, 'synset': "creeping_st_john's_wort.n.01", 'name': "creeping_St_John's_wort"}, {'id': 19616, 'synset': "low_st_andrew's_cross.n.01", 'name': "low_St_Andrew's_cross"}, {'id': 19617, 'synset': 'klammath_weed.n.01', 'name': 'klammath_weed'}, {'id': 19618, 'synset': "shrubby_st_john's_wort.n.01", 'name': "shrubby_St_John's_wort"}, {'id': 19619, 'synset': "st_peter's_wort.n.01", 'name': "St_Peter's_wort"}, {'id': 19620, 'synset': "marsh_st-john's_wort.n.01", 'name': "marsh_St-John's_wort"}, {'id': 19621, 'synset': 'mammee_apple.n.01', 'name': 'mammee_apple'}, {'id': 19622, 'synset': 'rose_chestnut.n.01', 'name': 'rose_chestnut'}, {'id': 19623, 'synset': 'bower_actinidia.n.01', 'name': 'bower_actinidia'}, {'id': 19624, 'synset': 'chinese_gooseberry.n.01', 'name': 'Chinese_gooseberry'}, {'id': 19625, 'synset': 'silvervine.n.01', 'name': 'silvervine'}, {'id': 19626, 'synset': 'wild_cinnamon.n.01', 'name': 'wild_cinnamon'}, {'id': 19627, 'synset': 'papaya.n.01', 'name': 'papaya'}, {'id': 19628, 'synset': 'souari.n.01', 'name': 'souari'}, {'id': 19629, 'synset': 'rockrose.n.02', 'name': 'rockrose'}, {'id': 19630, 'synset': 'white-leaved_rockrose.n.01', 'name': 'white-leaved_rockrose'}, {'id': 19631, 'synset': 'common_gum_cistus.n.01', 'name': 'common_gum_cistus'}, {'id': 19632, 'synset': 'frostweed.n.01', 'name': 'frostweed'}, {'id': 19633, 'synset': 'dipterocarp.n.01', 'name': 'dipterocarp'}, {'id': 19634, 'synset': 'red_lauan.n.02', 'name': 'red_lauan'}, {'id': 19635, 'synset': "governor's_plum.n.01", 'name': "governor's_plum"}, {'id': 19636, 'synset': 'kei_apple.n.01', 'name': 'kei_apple'}, {'id': 19637, 'synset': 'ketembilla.n.01', 'name': 'ketembilla'}, {'id': 19638, 'synset': 'chaulmoogra.n.01', 'name': 'chaulmoogra'}, {'id': 19639, 'synset': 'wild_peach.n.01', 'name': 'wild_peach'}, {'id': 19640, 'synset': 'candlewood.n.01', 'name': 'candlewood'}, {'id': 19641, 'synset': 'boojum_tree.n.01', 'name': 'boojum_tree'}, {'id': 19642, 'synset': "bird's-eye_bush.n.01", 'name': "bird's-eye_bush"}, {'id': 19643, 'synset': 'granadilla.n.03', 'name': 'granadilla'}, {'id': 19644, 'synset': 'granadilla.n.02', 'name': 'granadilla'}, {'id': 19645, 'synset': 'granadilla.n.01', 'name': 'granadilla'}, {'id': 19646, 'synset': 'maypop.n.01', 'name': 'maypop'}, {'id': 19647, 'synset': 'jamaica_honeysuckle.n.01', 'name': 'Jamaica_honeysuckle'}, {'id': 19648, 'synset': 'banana_passion_fruit.n.01', 'name': 'banana_passion_fruit'}, {'id': 19649, 'synset': 'sweet_calabash.n.01', 'name': 'sweet_calabash'}, {'id': 19650, 'synset': 'love-in-a-mist.n.01', 'name': 'love-in-a-mist'}, {'id': 19651, 'synset': 'reseda.n.01', 'name': 'reseda'}, {'id': 19652, 'synset': 'mignonette.n.01', 'name': 'mignonette'}, {'id': 19653, 'synset': "dyer's_rocket.n.01", 'name': "dyer's_rocket"}, {'id': 19654, 'synset': 'false_tamarisk.n.01', 'name': 'false_tamarisk'}, {'id': 19655, 'synset': 'halophyte.n.01', 'name': 'halophyte'}, {'id': 19656, 'synset': 'viola.n.01', 'name': 'viola'}, {'id': 19657, 'synset': 'violet.n.01', 'name': 'violet'}, {'id': 19658, 'synset': 'field_pansy.n.01', 'name': 'field_pansy'}, {'id': 19659, 'synset': 'american_dog_violet.n.01', 'name': 'American_dog_violet'}, {'id': 19660, 'synset': 'dog_violet.n.01', 'name': 'dog_violet'}, {'id': 19661, 'synset': 'horned_violet.n.01', 'name': 'horned_violet'}, {'id': 19662, 'synset': 'two-eyed_violet.n.01', 'name': 'two-eyed_violet'}, {'id': 19663, 'synset': "bird's-foot_violet.n.01", 'name': "bird's-foot_violet"}, {'id': 19664, 'synset': 'downy_yellow_violet.n.01', 'name': 'downy_yellow_violet'}, {'id': 19665, 'synset': 'long-spurred_violet.n.01', 'name': 'long-spurred_violet'}, {'id': 19666, 'synset': 'pale_violet.n.01', 'name': 'pale_violet'}, {'id': 19667, 'synset': 'hedge_violet.n.01', 'name': 'hedge_violet'}, {'id': 19668, 'synset': 'nettle.n.01', 'name': 'nettle'}, {'id': 19669, 'synset': 'stinging_nettle.n.01', 'name': 'stinging_nettle'}, {'id': 19670, 'synset': 'roman_nettle.n.01', 'name': 'Roman_nettle'}, {'id': 19671, 'synset': 'ramie.n.01', 'name': 'ramie'}, {'id': 19672, 'synset': 'wood_nettle.n.01', 'name': 'wood_nettle'}, {'id': 19673, 'synset': 'australian_nettle.n.01', 'name': 'Australian_nettle'}, {'id': 19674, 'synset': 'pellitory-of-the-wall.n.01', 'name': 'pellitory-of-the-wall'}, {'id': 19675, 'synset': 'richweed.n.02', 'name': 'richweed'}, {'id': 19676, 'synset': 'artillery_plant.n.01', 'name': 'artillery_plant'}, {'id': 19677, 'synset': 'friendship_plant.n.01', 'name': 'friendship_plant'}, {'id': 19678, 'synset': 'queensland_grass-cloth_plant.n.01', 'name': 'Queensland_grass-cloth_plant'}, {'id': 19679, 'synset': 'pipturus_albidus.n.01', 'name': 'Pipturus_albidus'}, {'id': 19680, 'synset': 'cannabis.n.01', 'name': 'cannabis'}, {'id': 19681, 'synset': 'indian_hemp.n.01', 'name': 'Indian_hemp'}, {'id': 19682, 'synset': 'mulberry.n.01', 'name': 'mulberry'}, {'id': 19683, 'synset': 'white_mulberry.n.01', 'name': 'white_mulberry'}, {'id': 19684, 'synset': 'black_mulberry.n.01', 'name': 'black_mulberry'}, {'id': 19685, 'synset': 'red_mulberry.n.01', 'name': 'red_mulberry'}, {'id': 19686, 'synset': 'osage_orange.n.01', 'name': 'osage_orange'}, {'id': 19687, 'synset': 'breadfruit.n.01', 'name': 'breadfruit'}, {'id': 19688, 'synset': 'jackfruit.n.01', 'name': 'jackfruit'}, {'id': 19689, 'synset': 'marang.n.01', 'name': 'marang'}, {'id': 19690, 'synset': 'fig_tree.n.01', 'name': 'fig_tree'}, {'id': 19691, 'synset': 'fig.n.02', 'name': 'fig'}, {'id': 19692, 'synset': 'caprifig.n.01', 'name': 'caprifig'}, {'id': 19693, 'synset': 'golden_fig.n.01', 'name': 'golden_fig'}, {'id': 19694, 'synset': 'banyan.n.01', 'name': 'banyan'}, {'id': 19695, 'synset': 'pipal.n.01', 'name': 'pipal'}, {'id': 19696, 'synset': 'india-rubber_tree.n.01', 'name': 'India-rubber_tree'}, {'id': 19697, 'synset': 'mistletoe_fig.n.01', 'name': 'mistletoe_fig'}, {'id': 19698, 'synset': 'port_jackson_fig.n.01', 'name': 'Port_Jackson_fig'}, {'id': 19699, 'synset': 'sycamore.n.04', 'name': 'sycamore'}, {'id': 19700, 'synset': 'paper_mulberry.n.01', 'name': 'paper_mulberry'}, {'id': 19701, 'synset': 'trumpetwood.n.01', 'name': 'trumpetwood'}, {'id': 19702, 'synset': 'elm.n.01', 'name': 'elm'}, {'id': 19703, 'synset': 'winged_elm.n.01', 'name': 'winged_elm'}, {'id': 19704, 'synset': 'american_elm.n.01', 'name': 'American_elm'}, {'id': 19705, 'synset': 'smooth-leaved_elm.n.01', 'name': 'smooth-leaved_elm'}, {'id': 19706, 'synset': 'cedar_elm.n.01', 'name': 'cedar_elm'}, {'id': 19707, 'synset': 'witch_elm.n.01', 'name': 'witch_elm'}, {'id': 19708, 'synset': 'dutch_elm.n.01', 'name': 'Dutch_elm'}, {'id': 19709, 'synset': 'huntingdon_elm.n.01', 'name': 'Huntingdon_elm'}, {'id': 19710, 'synset': 'water_elm.n.01', 'name': 'water_elm'}, {'id': 19711, 'synset': 'chinese_elm.n.02', 'name': 'Chinese_elm'}, {'id': 19712, 'synset': 'english_elm.n.01', 'name': 'English_elm'}, {'id': 19713, 'synset': 'siberian_elm.n.01', 'name': 'Siberian_elm'}, {'id': 19714, 'synset': 'slippery_elm.n.01', 'name': 'slippery_elm'}, {'id': 19715, 'synset': 'jersey_elm.n.01', 'name': 'Jersey_elm'}, {'id': 19716, 'synset': 'september_elm.n.01', 'name': 'September_elm'}, {'id': 19717, 'synset': 'rock_elm.n.01', 'name': 'rock_elm'}, {'id': 19718, 'synset': 'hackberry.n.01', 'name': 'hackberry'}, {'id': 19719, 'synset': 'european_hackberry.n.01', 'name': 'European_hackberry'}, {'id': 19720, 'synset': 'american_hackberry.n.01', 'name': 'American_hackberry'}, {'id': 19721, 'synset': 'sugarberry.n.01', 'name': 'sugarberry'}, {'id': 19722, 'synset': 'iridaceous_plant.n.01', 'name': 'iridaceous_plant'}, {'id': 19723, 'synset': 'bearded_iris.n.01', 'name': 'bearded_iris'}, {'id': 19724, 'synset': 'beardless_iris.n.01', 'name': 'beardless_iris'}, {'id': 19725, 'synset': 'orrisroot.n.01', 'name': 'orrisroot'}, {'id': 19726, 'synset': 'dwarf_iris.n.02', 'name': 'dwarf_iris'}, {'id': 19727, 'synset': 'dutch_iris.n.02', 'name': 'Dutch_iris'}, {'id': 19728, 'synset': 'florentine_iris.n.01', 'name': 'Florentine_iris'}, {'id': 19729, 'synset': 'stinking_iris.n.01', 'name': 'stinking_iris'}, {'id': 19730, 'synset': 'german_iris.n.02', 'name': 'German_iris'}, {'id': 19731, 'synset': 'japanese_iris.n.01', 'name': 'Japanese_iris'}, {'id': 19732, 'synset': 'german_iris.n.01', 'name': 'German_iris'}, {'id': 19733, 'synset': 'dalmatian_iris.n.01', 'name': 'Dalmatian_iris'}, {'id': 19734, 'synset': 'persian_iris.n.01', 'name': 'Persian_iris'}, {'id': 19735, 'synset': 'dutch_iris.n.01', 'name': 'Dutch_iris'}, {'id': 19736, 'synset': 'dwarf_iris.n.01', 'name': 'dwarf_iris'}, {'id': 19737, 'synset': 'spanish_iris.n.01', 'name': 'Spanish_iris'}, {'id': 19738, 'synset': 'blackberry-lily.n.01', 'name': 'blackberry-lily'}, {'id': 19739, 'synset': 'crocus.n.01', 'name': 'crocus'}, {'id': 19740, 'synset': 'saffron.n.01', 'name': 'saffron'}, {'id': 19741, 'synset': 'corn_lily.n.01', 'name': 'corn_lily'}, {'id': 19742, 'synset': 'blue-eyed_grass.n.01', 'name': 'blue-eyed_grass'}, {'id': 19743, 'synset': 'wandflower.n.01', 'name': 'wandflower'}, {'id': 19744, 'synset': 'amaryllis.n.01', 'name': 'amaryllis'}, {'id': 19745, 'synset': 'salsilla.n.02', 'name': 'salsilla'}, {'id': 19746, 'synset': 'salsilla.n.01', 'name': 'salsilla'}, {'id': 19747, 'synset': 'blood_lily.n.01', 'name': 'blood_lily'}, {'id': 19748, 'synset': 'cape_tulip.n.01', 'name': 'Cape_tulip'}, {'id': 19749, 'synset': 'hippeastrum.n.01', 'name': 'hippeastrum'}, {'id': 19750, 'synset': 'narcissus.n.01', 'name': 'narcissus'}, {'id': 19751, 'synset': 'daffodil.n.01', 'name': 'daffodil'}, {'id': 19752, 'synset': 'jonquil.n.01', 'name': 'jonquil'}, {'id': 19753, 'synset': 'jonquil.n.02', 'name': 'jonquil'}, {'id': 19754, 'synset': 'jacobean_lily.n.01', 'name': 'Jacobean_lily'}, {'id': 19755, 'synset': 'liliaceous_plant.n.01', 'name': 'liliaceous_plant'}, {'id': 19756, 'synset': 'mountain_lily.n.01', 'name': 'mountain_lily'}, {'id': 19757, 'synset': 'canada_lily.n.01', 'name': 'Canada_lily'}, {'id': 19758, 'synset': 'tiger_lily.n.02', 'name': 'tiger_lily'}, {'id': 19759, 'synset': 'columbia_tiger_lily.n.01', 'name': 'Columbia_tiger_lily'}, {'id': 19760, 'synset': 'tiger_lily.n.01', 'name': 'tiger_lily'}, {'id': 19761, 'synset': 'easter_lily.n.01', 'name': 'Easter_lily'}, {'id': 19762, 'synset': 'coast_lily.n.01', 'name': 'coast_lily'}, {'id': 19763, 'synset': "turk's-cap.n.02", 'name': "Turk's-cap"}, {'id': 19764, 'synset': 'michigan_lily.n.01', 'name': 'Michigan_lily'}, {'id': 19765, 'synset': 'leopard_lily.n.01', 'name': 'leopard_lily'}, {'id': 19766, 'synset': "turk's-cap.n.01", 'name': "Turk's-cap"}, {'id': 19767, 'synset': 'african_lily.n.01', 'name': 'African_lily'}, {'id': 19768, 'synset': 'colicroot.n.01', 'name': 'colicroot'}, {'id': 19769, 'synset': 'ague_root.n.01', 'name': 'ague_root'}, {'id': 19770, 'synset': 'yellow_colicroot.n.01', 'name': 'yellow_colicroot'}, {'id': 19771, 'synset': 'alliaceous_plant.n.01', 'name': 'alliaceous_plant'}, {'id': 19772, 'synset': "hooker's_onion.n.01", 'name': "Hooker's_onion"}, {'id': 19773, 'synset': 'wild_leek.n.02', 'name': 'wild_leek'}, {'id': 19774, 'synset': 'canada_garlic.n.01', 'name': 'Canada_garlic'}, {'id': 19775, 'synset': 'keeled_garlic.n.01', 'name': 'keeled_garlic'}, {'id': 19776, 'synset': 'shallot.n.02', 'name': 'shallot'}, {'id': 19777, 'synset': 'nodding_onion.n.01', 'name': 'nodding_onion'}, {'id': 19778, 'synset': 'welsh_onion.n.01', 'name': 'Welsh_onion'}, {'id': 19779, 'synset': 'red-skinned_onion.n.01', 'name': 'red-skinned_onion'}, {'id': 19780, 'synset': 'daffodil_garlic.n.01', 'name': 'daffodil_garlic'}, {'id': 19781, 'synset': 'few-flowered_leek.n.01', 'name': 'few-flowered_leek'}, {'id': 19782, 'synset': 'garlic.n.01', 'name': 'garlic'}, {'id': 19783, 'synset': 'sand_leek.n.01', 'name': 'sand_leek'}, {'id': 19784, 'synset': 'chives.n.01', 'name': 'chives'}, {'id': 19785, 'synset': 'crow_garlic.n.01', 'name': 'crow_garlic'}, {'id': 19786, 'synset': 'wild_garlic.n.01', 'name': 'wild_garlic'}, {'id': 19787, 'synset': 'garlic_chive.n.01', 'name': 'garlic_chive'}, {'id': 19788, 'synset': 'round-headed_leek.n.01', 'name': 'round-headed_leek'}, {'id': 19789, 'synset': 'three-cornered_leek.n.01', 'name': 'three-cornered_leek'}, {'id': 19790, 'synset': 'cape_aloe.n.01', 'name': 'cape_aloe'}, {'id': 19791, 'synset': 'kniphofia.n.01', 'name': 'kniphofia'}, {'id': 19792, 'synset': 'poker_plant.n.01', 'name': 'poker_plant'}, {'id': 19793, 'synset': 'red-hot_poker.n.01', 'name': 'red-hot_poker'}, {'id': 19794, 'synset': 'fly_poison.n.01', 'name': 'fly_poison'}, {'id': 19795, 'synset': 'amber_lily.n.01', 'name': 'amber_lily'}, {'id': 19796, 'synset': 'asparagus.n.01', 'name': 'asparagus'}, {'id': 19797, 'synset': 'asparagus_fern.n.01', 'name': 'asparagus_fern'}, {'id': 19798, 'synset': 'smilax.n.02', 'name': 'smilax'}, {'id': 19799, 'synset': 'asphodel.n.01', 'name': 'asphodel'}, {'id': 19800, 'synset': "jacob's_rod.n.01", 'name': "Jacob's_rod"}, {'id': 19801, 'synset': 'aspidistra.n.01', 'name': 'aspidistra'}, {'id': 19802, 'synset': 'coral_drops.n.01', 'name': 'coral_drops'}, {'id': 19803, 'synset': 'christmas_bells.n.01', 'name': 'Christmas_bells'}, {'id': 19804, 'synset': 'climbing_onion.n.01', 'name': 'climbing_onion'}, {'id': 19805, 'synset': 'mariposa.n.01', 'name': 'mariposa'}, {'id': 19806, 'synset': 'globe_lily.n.01', 'name': 'globe_lily'}, {'id': 19807, 'synset': "cat's-ear.n.01", 'name': "cat's-ear"}, {'id': 19808, 'synset': 'white_globe_lily.n.01', 'name': 'white_globe_lily'}, {'id': 19809, 'synset': 'yellow_globe_lily.n.01', 'name': 'yellow_globe_lily'}, {'id': 19810, 'synset': 'rose_globe_lily.n.01', 'name': 'rose_globe_lily'}, {'id': 19811, 'synset': 'star_tulip.n.01', 'name': 'star_tulip'}, {'id': 19812, 'synset': 'desert_mariposa_tulip.n.01', 'name': 'desert_mariposa_tulip'}, {'id': 19813, 'synset': 'yellow_mariposa_tulip.n.01', 'name': 'yellow_mariposa_tulip'}, {'id': 19814, 'synset': 'sagebrush_mariposa_tulip.n.01', 'name': 'sagebrush_mariposa_tulip'}, {'id': 19815, 'synset': 'sego_lily.n.01', 'name': 'sego_lily'}, {'id': 19816, 'synset': 'camas.n.01', 'name': 'camas'}, {'id': 19817, 'synset': 'common_camas.n.01', 'name': 'common_camas'}, {'id': 19818, 'synset': "leichtlin's_camas.n.01", 'name': "Leichtlin's_camas"}, {'id': 19819, 'synset': 'wild_hyacinth.n.02', 'name': 'wild_hyacinth'}, {'id': 19820, 'synset': 'dogtooth_violet.n.01', 'name': 'dogtooth_violet'}, {'id': 19821, 'synset': 'white_dogtooth_violet.n.01', 'name': 'white_dogtooth_violet'}, {'id': 19822, 'synset': "yellow_adder's_tongue.n.01", 'name': "yellow_adder's_tongue"}, {'id': 19823, 'synset': 'european_dogtooth.n.01', 'name': 'European_dogtooth'}, {'id': 19824, 'synset': 'fawn_lily.n.01', 'name': 'fawn_lily'}, {'id': 19825, 'synset': 'glacier_lily.n.01', 'name': 'glacier_lily'}, {'id': 19826, 'synset': 'avalanche_lily.n.01', 'name': 'avalanche_lily'}, {'id': 19827, 'synset': 'fritillary.n.01', 'name': 'fritillary'}, {'id': 19828, 'synset': 'mission_bells.n.02', 'name': 'mission_bells'}, {'id': 19829, 'synset': 'mission_bells.n.01', 'name': 'mission_bells'}, {'id': 19830, 'synset': 'stink_bell.n.01', 'name': 'stink_bell'}, {'id': 19831, 'synset': 'crown_imperial.n.01', 'name': 'crown_imperial'}, {'id': 19832, 'synset': 'white_fritillary.n.01', 'name': 'white_fritillary'}, {'id': 19833, 'synset': "snake's_head_fritillary.n.01", 'name': "snake's_head_fritillary"}, {'id': 19834, 'synset': 'adobe_lily.n.01', 'name': 'adobe_lily'}, {'id': 19835, 'synset': 'scarlet_fritillary.n.01', 'name': 'scarlet_fritillary'}, {'id': 19836, 'synset': 'tulip.n.01', 'name': 'tulip'}, {'id': 19837, 'synset': 'dwarf_tulip.n.01', 'name': 'dwarf_tulip'}, {'id': 19838, 'synset': 'lady_tulip.n.01', 'name': 'lady_tulip'}, {'id': 19839, 'synset': 'tulipa_gesneriana.n.01', 'name': 'Tulipa_gesneriana'}, {'id': 19840, 'synset': 'cottage_tulip.n.01', 'name': 'cottage_tulip'}, {'id': 19841, 'synset': 'darwin_tulip.n.01', 'name': 'Darwin_tulip'}, {'id': 19842, 'synset': 'gloriosa.n.01', 'name': 'gloriosa'}, {'id': 19843, 'synset': 'lemon_lily.n.01', 'name': 'lemon_lily'}, {'id': 19844, 'synset': 'common_hyacinth.n.01', 'name': 'common_hyacinth'}, {'id': 19845, 'synset': 'roman_hyacinth.n.01', 'name': 'Roman_hyacinth'}, {'id': 19846, 'synset': 'summer_hyacinth.n.01', 'name': 'summer_hyacinth'}, {'id': 19847, 'synset': 'star-of-bethlehem.n.01', 'name': 'star-of-Bethlehem'}, {'id': 19848, 'synset': 'bath_asparagus.n.01', 'name': 'bath_asparagus'}, {'id': 19849, 'synset': 'grape_hyacinth.n.01', 'name': 'grape_hyacinth'}, {'id': 19850, 'synset': 'common_grape_hyacinth.n.01', 'name': 'common_grape_hyacinth'}, {'id': 19851, 'synset': 'tassel_hyacinth.n.01', 'name': 'tassel_hyacinth'}, {'id': 19852, 'synset': 'scilla.n.01', 'name': 'scilla'}, {'id': 19853, 'synset': 'spring_squill.n.01', 'name': 'spring_squill'}, {'id': 19854, 'synset': 'false_asphodel.n.01', 'name': 'false_asphodel'}, {'id': 19855, 'synset': 'scotch_asphodel.n.01', 'name': 'Scotch_asphodel'}, {'id': 19856, 'synset': 'sea_squill.n.01', 'name': 'sea_squill'}, {'id': 19857, 'synset': 'squill.n.01', 'name': 'squill'}, {'id': 19858, 'synset': "butcher's_broom.n.01", 'name': "butcher's_broom"}, {'id': 19859, 'synset': 'bog_asphodel.n.01', 'name': 'bog_asphodel'}, {'id': 19860, 'synset': 'european_bog_asphodel.n.01', 'name': 'European_bog_asphodel'}, {'id': 19861, 'synset': 'american_bog_asphodel.n.01', 'name': 'American_bog_asphodel'}, {'id': 19862, 'synset': 'hellebore.n.01', 'name': 'hellebore'}, {'id': 19863, 'synset': 'white_hellebore.n.01', 'name': 'white_hellebore'}, {'id': 19864, 'synset': 'squaw_grass.n.01', 'name': 'squaw_grass'}, {'id': 19865, 'synset': 'death_camas.n.01', 'name': 'death_camas'}, {'id': 19866, 'synset': 'alkali_grass.n.01', 'name': 'alkali_grass'}, {'id': 19867, 'synset': 'white_camas.n.01', 'name': 'white_camas'}, {'id': 19868, 'synset': 'poison_camas.n.01', 'name': 'poison_camas'}, {'id': 19869, 'synset': 'grassy_death_camas.n.01', 'name': 'grassy_death_camas'}, {'id': 19870, 'synset': 'prairie_wake-robin.n.01', 'name': 'prairie_wake-robin'}, {'id': 19871, 'synset': 'dwarf-white_trillium.n.01', 'name': 'dwarf-white_trillium'}, {'id': 19872, 'synset': 'herb_paris.n.01', 'name': 'herb_Paris'}, {'id': 19873, 'synset': 'sarsaparilla.n.01', 'name': 'sarsaparilla'}, {'id': 19874, 'synset': 'bullbrier.n.01', 'name': 'bullbrier'}, {'id': 19875, 'synset': 'rough_bindweed.n.01', 'name': 'rough_bindweed'}, {'id': 19876, 'synset': 'clintonia.n.01', 'name': 'clintonia'}, {'id': 19877, 'synset': 'false_lily_of_the_valley.n.02', 'name': 'false_lily_of_the_valley'}, {'id': 19878, 'synset': 'false_lily_of_the_valley.n.01', 'name': 'false_lily_of_the_valley'}, {'id': 19879, 'synset': "solomon's-seal.n.01", 'name': "Solomon's-seal"}, {'id': 19880, 'synset': "great_solomon's-seal.n.01", 'name': "great_Solomon's-seal"}, {'id': 19881, 'synset': 'bellwort.n.01', 'name': 'bellwort'}, {'id': 19882, 'synset': 'strawflower.n.01', 'name': 'strawflower'}, {'id': 19883, 'synset': 'pia.n.01', 'name': 'pia'}, {'id': 19884, 'synset': 'agave.n.01', 'name': 'agave'}, {'id': 19885, 'synset': 'american_agave.n.01', 'name': 'American_agave'}, {'id': 19886, 'synset': 'sisal.n.02', 'name': 'sisal'}, {'id': 19887, 'synset': 'maguey.n.02', 'name': 'maguey'}, {'id': 19888, 'synset': 'maguey.n.01', 'name': 'maguey'}, {'id': 19889, 'synset': 'agave_tequilana.n.01', 'name': 'Agave_tequilana'}, {'id': 19890, 'synset': 'cabbage_tree.n.03', 'name': 'cabbage_tree'}, {'id': 19891, 'synset': 'dracaena.n.01', 'name': 'dracaena'}, {'id': 19892, 'synset': 'tuberose.n.01', 'name': 'tuberose'}, {'id': 19893, 'synset': 'sansevieria.n.01', 'name': 'sansevieria'}, {'id': 19894, 'synset': 'african_bowstring_hemp.n.01', 'name': 'African_bowstring_hemp'}, {'id': 19895, 'synset': 'ceylon_bowstring_hemp.n.01', 'name': 'Ceylon_bowstring_hemp'}, {'id': 19896, 'synset': "mother-in-law's_tongue.n.01", 'name': "mother-in-law's_tongue"}, {'id': 19897, 'synset': 'spanish_bayonet.n.02', 'name': 'Spanish_bayonet'}, {'id': 19898, 'synset': 'spanish_bayonet.n.01', 'name': 'Spanish_bayonet'}, {'id': 19899, 'synset': 'joshua_tree.n.01', 'name': 'Joshua_tree'}, {'id': 19900, 'synset': 'soapweed.n.01', 'name': 'soapweed'}, {'id': 19901, 'synset': "adam's_needle.n.01", 'name': "Adam's_needle"}, {'id': 19902, 'synset': 'bear_grass.n.02', 'name': 'bear_grass'}, {'id': 19903, 'synset': 'spanish_dagger.n.01', 'name': 'Spanish_dagger'}, {'id': 19904, 'synset': "our_lord's_candle.n.01", 'name': "Our_Lord's_candle"}, {'id': 19905, 'synset': 'water_shamrock.n.01', 'name': 'water_shamrock'}, {'id': 19906, 'synset': 'butterfly_bush.n.01', 'name': 'butterfly_bush'}, {'id': 19907, 'synset': 'yellow_jasmine.n.01', 'name': 'yellow_jasmine'}, {'id': 19908, 'synset': 'flax.n.02', 'name': 'flax'}, {'id': 19909, 'synset': 'calabar_bean.n.01', 'name': 'calabar_bean'}, {'id': 19910, 'synset': 'bonduc.n.02', 'name': 'bonduc'}, {'id': 19911, 'synset': 'divi-divi.n.02', 'name': 'divi-divi'}, {'id': 19912, 'synset': 'mysore_thorn.n.01', 'name': 'Mysore_thorn'}, {'id': 19913, 'synset': 'brazilian_ironwood.n.01', 'name': 'brazilian_ironwood'}, {'id': 19914, 'synset': 'bird_of_paradise.n.01', 'name': 'bird_of_paradise'}, {'id': 19915, 'synset': 'shingle_tree.n.01', 'name': 'shingle_tree'}, {'id': 19916, 'synset': 'mountain_ebony.n.01', 'name': 'mountain_ebony'}, {'id': 19917, 'synset': 'msasa.n.01', 'name': 'msasa'}, {'id': 19918, 'synset': 'cassia.n.01', 'name': 'cassia'}, {'id': 19919, 'synset': 'golden_shower_tree.n.01', 'name': 'golden_shower_tree'}, {'id': 19920, 'synset': 'pink_shower.n.01', 'name': 'pink_shower'}, {'id': 19921, 'synset': 'rainbow_shower.n.01', 'name': 'rainbow_shower'}, {'id': 19922, 'synset': 'horse_cassia.n.01', 'name': 'horse_cassia'}, {'id': 19923, 'synset': 'carob.n.02', 'name': 'carob'}, {'id': 19924, 'synset': 'carob.n.01', 'name': 'carob'}, {'id': 19925, 'synset': 'paloverde.n.01', 'name': 'paloverde'}, {'id': 19926, 'synset': 'royal_poinciana.n.01', 'name': 'royal_poinciana'}, {'id': 19927, 'synset': 'locust_tree.n.01', 'name': 'locust_tree'}, {'id': 19928, 'synset': 'water_locust.n.01', 'name': 'water_locust'}, {'id': 19929, 'synset': 'honey_locust.n.01', 'name': 'honey_locust'}, {'id': 19930, 'synset': 'kentucky_coffee_tree.n.01', 'name': 'Kentucky_coffee_tree'}, {'id': 19931, 'synset': 'logwood.n.02', 'name': 'logwood'}, {'id': 19932, 'synset': 'jerusalem_thorn.n.03', 'name': 'Jerusalem_thorn'}, {'id': 19933, 'synset': 'palo_verde.n.01', 'name': 'palo_verde'}, {'id': 19934, 'synset': 'dalmatian_laburnum.n.01', 'name': 'Dalmatian_laburnum'}, {'id': 19935, 'synset': 'senna.n.01', 'name': 'senna'}, {'id': 19936, 'synset': 'avaram.n.01', 'name': 'avaram'}, {'id': 19937, 'synset': 'alexandria_senna.n.01', 'name': 'Alexandria_senna'}, {'id': 19938, 'synset': 'wild_senna.n.01', 'name': 'wild_senna'}, {'id': 19939, 'synset': 'sicklepod.n.01', 'name': 'sicklepod'}, {'id': 19940, 'synset': 'coffee_senna.n.01', 'name': 'coffee_senna'}, {'id': 19941, 'synset': 'tamarind.n.01', 'name': 'tamarind'}, {'id': 19942, 'synset': 'false_indigo.n.03', 'name': 'false_indigo'}, {'id': 19943, 'synset': 'false_indigo.n.02', 'name': 'false_indigo'}, {'id': 19944, 'synset': 'hog_peanut.n.01', 'name': 'hog_peanut'}, {'id': 19945, 'synset': 'angelim.n.01', 'name': 'angelim'}, {'id': 19946, 'synset': 'cabbage_bark.n.01', 'name': 'cabbage_bark'}, {'id': 19947, 'synset': 'kidney_vetch.n.01', 'name': 'kidney_vetch'}, {'id': 19948, 'synset': 'groundnut.n.01', 'name': 'groundnut'}, {'id': 19949, 'synset': 'rooibos.n.01', 'name': 'rooibos'}, {'id': 19950, 'synset': 'milk_vetch.n.01', 'name': 'milk_vetch'}, {'id': 19951, 'synset': 'alpine_milk_vetch.n.01', 'name': 'alpine_milk_vetch'}, {'id': 19952, 'synset': 'purple_milk_vetch.n.01', 'name': 'purple_milk_vetch'}, {'id': 19953, 'synset': 'camwood.n.01', 'name': 'camwood'}, {'id': 19954, 'synset': 'wild_indigo.n.01', 'name': 'wild_indigo'}, {'id': 19955, 'synset': 'blue_false_indigo.n.01', 'name': 'blue_false_indigo'}, {'id': 19956, 'synset': 'white_false_indigo.n.01', 'name': 'white_false_indigo'}, {'id': 19957, 'synset': 'indigo_broom.n.01', 'name': 'indigo_broom'}, {'id': 19958, 'synset': 'dhak.n.01', 'name': 'dhak'}, {'id': 19959, 'synset': 'pigeon_pea.n.01', 'name': 'pigeon_pea'}, {'id': 19960, 'synset': 'sword_bean.n.01', 'name': 'sword_bean'}, {'id': 19961, 'synset': 'pea_tree.n.01', 'name': 'pea_tree'}, {'id': 19962, 'synset': 'siberian_pea_tree.n.01', 'name': 'Siberian_pea_tree'}, {'id': 19963, 'synset': 'chinese_pea_tree.n.01', 'name': 'Chinese_pea_tree'}, {'id': 19964, 'synset': 'moreton_bay_chestnut.n.01', 'name': 'Moreton_Bay_chestnut'}, {'id': 19965, 'synset': 'butterfly_pea.n.03', 'name': 'butterfly_pea'}, {'id': 19966, 'synset': 'judas_tree.n.01', 'name': 'Judas_tree'}, {'id': 19967, 'synset': 'redbud.n.01', 'name': 'redbud'}, {'id': 19968, 'synset': 'western_redbud.n.01', 'name': 'western_redbud'}, {'id': 19969, 'synset': 'tagasaste.n.01', 'name': 'tagasaste'}, {'id': 19970, 'synset': 'weeping_tree_broom.n.01', 'name': 'weeping_tree_broom'}, {'id': 19971, 'synset': 'flame_pea.n.01', 'name': 'flame_pea'}, {'id': 19972, 'synset': 'chickpea.n.02', 'name': 'chickpea'}, {'id': 19973, 'synset': 'kentucky_yellowwood.n.01', 'name': 'Kentucky_yellowwood'}, {'id': 19974, 'synset': 'glory_pea.n.01', 'name': 'glory_pea'}, {'id': 19975, 'synset': 'desert_pea.n.01', 'name': 'desert_pea'}, {'id': 19976, 'synset': "parrot's_beak.n.01", 'name': "parrot's_beak"}, {'id': 19977, 'synset': 'butterfly_pea.n.02', 'name': 'butterfly_pea'}, {'id': 19978, 'synset': 'blue_pea.n.01', 'name': 'blue_pea'}, {'id': 19979, 'synset': 'telegraph_plant.n.01', 'name': 'telegraph_plant'}, {'id': 19980, 'synset': 'bladder_senna.n.01', 'name': 'bladder_senna'}, {'id': 19981, 'synset': 'axseed.n.01', 'name': 'axseed'}, {'id': 19982, 'synset': 'crotalaria.n.01', 'name': 'crotalaria'}, {'id': 19983, 'synset': 'guar.n.01', 'name': 'guar'}, {'id': 19984, 'synset': 'white_broom.n.01', 'name': 'white_broom'}, {'id': 19985, 'synset': 'common_broom.n.01', 'name': 'common_broom'}, {'id': 19986, 'synset': 'rosewood.n.02', 'name': 'rosewood'}, {'id': 19987, 'synset': 'indian_blackwood.n.01', 'name': 'Indian_blackwood'}, {'id': 19988, 'synset': 'sissoo.n.01', 'name': 'sissoo'}, {'id': 19989, 'synset': 'kingwood.n.02', 'name': 'kingwood'}, {'id': 19990, 'synset': 'brazilian_rosewood.n.01', 'name': 'Brazilian_rosewood'}, {'id': 19991, 'synset': 'cocobolo.n.01', 'name': 'cocobolo'}, {'id': 19992, 'synset': 'blackwood.n.02', 'name': 'blackwood'}, {'id': 19993, 'synset': 'bitter_pea.n.01', 'name': 'bitter_pea'}, {'id': 19994, 'synset': 'derris.n.01', 'name': 'derris'}, {'id': 19995, 'synset': 'derris_root.n.01', 'name': 'derris_root'}, {'id': 19996, 'synset': 'prairie_mimosa.n.01', 'name': 'prairie_mimosa'}, {'id': 19997, 'synset': 'tick_trefoil.n.01', 'name': 'tick_trefoil'}, {'id': 19998, 'synset': 'beggarweed.n.01', 'name': 'beggarweed'}, {'id': 19999, 'synset': 'australian_pea.n.01', 'name': 'Australian_pea'}, {'id': 20000, 'synset': 'coral_tree.n.01', 'name': 'coral_tree'}, {'id': 20001, 'synset': 'kaffir_boom.n.02', 'name': 'kaffir_boom'}, {'id': 20002, 'synset': 'coral_bean_tree.n.01', 'name': 'coral_bean_tree'}, {'id': 20003, 'synset': 'ceibo.n.01', 'name': 'ceibo'}, {'id': 20004, 'synset': 'kaffir_boom.n.01', 'name': 'kaffir_boom'}, {'id': 20005, 'synset': 'indian_coral_tree.n.01', 'name': 'Indian_coral_tree'}, {'id': 20006, 'synset': 'cork_tree.n.02', 'name': 'cork_tree'}, {'id': 20007, 'synset': "goat's_rue.n.02", 'name': "goat's_rue"}, {'id': 20008, 'synset': 'poison_bush.n.01', 'name': 'poison_bush'}, {'id': 20009, 'synset': 'spanish_broom.n.02', 'name': 'Spanish_broom'}, {'id': 20010, 'synset': 'woodwaxen.n.01', 'name': 'woodwaxen'}, {'id': 20011, 'synset': 'chanar.n.01', 'name': 'chanar'}, {'id': 20012, 'synset': 'gliricidia.n.01', 'name': 'gliricidia'}, {'id': 20013, 'synset': 'soy.n.01', 'name': 'soy'}, {'id': 20014, 'synset': 'licorice.n.01', 'name': 'licorice'}, {'id': 20015, 'synset': 'wild_licorice.n.02', 'name': 'wild_licorice'}, {'id': 20016, 'synset': 'licorice_root.n.01', 'name': 'licorice_root'}, {'id': 20017, 'synset': 'western_australia_coral_pea.n.01', 'name': 'Western_Australia_coral_pea'}, {'id': 20018, 'synset': 'sweet_vetch.n.01', 'name': 'sweet_vetch'}, {'id': 20019, 'synset': 'french_honeysuckle.n.02', 'name': 'French_honeysuckle'}, {'id': 20020, 'synset': 'anil.n.02', 'name': 'anil'}, {'id': 20021, 'synset': 'scarlet_runner.n.02', 'name': 'scarlet_runner'}, {'id': 20022, 'synset': 'hyacinth_bean.n.01', 'name': 'hyacinth_bean'}, {'id': 20023, 'synset': 'scotch_laburnum.n.01', 'name': 'Scotch_laburnum'}, {'id': 20024, 'synset': 'vetchling.n.01', 'name': 'vetchling'}, {'id': 20025, 'synset': 'wild_pea.n.01', 'name': 'wild_pea'}, {'id': 20026, 'synset': 'everlasting_pea.n.01', 'name': 'everlasting_pea'}, {'id': 20027, 'synset': 'beach_pea.n.01', 'name': 'beach_pea'}, {'id': 20028, 'synset': 'grass_vetch.n.01', 'name': 'grass_vetch'}, {'id': 20029, 'synset': 'marsh_pea.n.01', 'name': 'marsh_pea'}, {'id': 20030, 'synset': 'common_vetchling.n.01', 'name': 'common_vetchling'}, {'id': 20031, 'synset': 'grass_pea.n.01', 'name': 'grass_pea'}, {'id': 20032, 'synset': 'tangier_pea.n.01', 'name': 'Tangier_pea'}, {'id': 20033, 'synset': 'heath_pea.n.01', 'name': 'heath_pea'}, {'id': 20034, 'synset': 'bicolor_lespediza.n.01', 'name': 'bicolor_lespediza'}, {'id': 20035, 'synset': 'japanese_clover.n.01', 'name': 'japanese_clover'}, {'id': 20036, 'synset': 'korean_lespedeza.n.01', 'name': 'Korean_lespedeza'}, {'id': 20037, 'synset': 'sericea_lespedeza.n.01', 'name': 'sericea_lespedeza'}, {'id': 20038, 'synset': 'lentil.n.03', 'name': 'lentil'}, {'id': 20039, 'synset': 'lentil.n.02', 'name': 'lentil'}, {'id': 20040, 'synset': "prairie_bird's-foot_trefoil.n.01", 'name': "prairie_bird's-foot_trefoil"}, {'id': 20041, 'synset': "bird's_foot_trefoil.n.02", 'name': "bird's_foot_trefoil"}, {'id': 20042, 'synset': 'winged_pea.n.02', 'name': 'winged_pea'}, {'id': 20043, 'synset': 'lupine.n.01', 'name': 'lupine'}, {'id': 20044, 'synset': 'white_lupine.n.01', 'name': 'white_lupine'}, {'id': 20045, 'synset': 'tree_lupine.n.01', 'name': 'tree_lupine'}, {'id': 20046, 'synset': 'wild_lupine.n.01', 'name': 'wild_lupine'}, {'id': 20047, 'synset': 'bluebonnet.n.01', 'name': 'bluebonnet'}, {'id': 20048, 'synset': 'texas_bluebonnet.n.01', 'name': 'Texas_bluebonnet'}, {'id': 20049, 'synset': 'medic.n.01', 'name': 'medic'}, {'id': 20050, 'synset': 'moon_trefoil.n.01', 'name': 'moon_trefoil'}, {'id': 20051, 'synset': 'sickle_alfalfa.n.01', 'name': 'sickle_alfalfa'}, {'id': 20052, 'synset': 'calvary_clover.n.01', 'name': 'Calvary_clover'}, {'id': 20053, 'synset': 'black_medick.n.01', 'name': 'black_medick'}, {'id': 20054, 'synset': 'alfalfa.n.01', 'name': 'alfalfa'}, {'id': 20055, 'synset': 'millettia.n.01', 'name': 'millettia'}, {'id': 20056, 'synset': 'mucuna.n.01', 'name': 'mucuna'}, {'id': 20057, 'synset': 'cowage.n.02', 'name': 'cowage'}, {'id': 20058, 'synset': 'tolu_tree.n.01', 'name': 'tolu_tree'}, {'id': 20059, 'synset': 'peruvian_balsam.n.01', 'name': 'Peruvian_balsam'}, {'id': 20060, 'synset': 'sainfoin.n.01', 'name': 'sainfoin'}, {'id': 20061, 'synset': 'restharrow.n.02', 'name': 'restharrow'}, {'id': 20062, 'synset': 'bead_tree.n.01', 'name': 'bead_tree'}, {'id': 20063, 'synset': 'jumby_bead.n.01', 'name': 'jumby_bead'}, {'id': 20064, 'synset': 'locoweed.n.01', 'name': 'locoweed'}, {'id': 20065, 'synset': 'purple_locoweed.n.01', 'name': 'purple_locoweed'}, {'id': 20066, 'synset': 'tumbleweed.n.01', 'name': 'tumbleweed'}, {'id': 20067, 'synset': 'yam_bean.n.02', 'name': 'yam_bean'}, {'id': 20068, 'synset': 'shamrock_pea.n.01', 'name': 'shamrock_pea'}, {'id': 20069, 'synset': 'pole_bean.n.01', 'name': 'pole_bean'}, {'id': 20070, 'synset': 'kidney_bean.n.01', 'name': 'kidney_bean'}, {'id': 20071, 'synset': 'haricot.n.01', 'name': 'haricot'}, {'id': 20072, 'synset': 'wax_bean.n.01', 'name': 'wax_bean'}, {'id': 20073, 'synset': 'scarlet_runner.n.01', 'name': 'scarlet_runner'}, {'id': 20074, 'synset': 'lima_bean.n.02', 'name': 'lima_bean'}, {'id': 20075, 'synset': 'sieva_bean.n.01', 'name': 'sieva_bean'}, {'id': 20076, 'synset': 'tepary_bean.n.01', 'name': 'tepary_bean'}, {'id': 20077, 'synset': 'chaparral_pea.n.01', 'name': 'chaparral_pea'}, {'id': 20078, 'synset': 'jamaica_dogwood.n.01', 'name': 'Jamaica_dogwood'}, {'id': 20079, 'synset': 'pea.n.02', 'name': 'pea'}, {'id': 20080, 'synset': 'garden_pea.n.01', 'name': 'garden_pea'}, {'id': 20081, 'synset': 'edible-pod_pea.n.01', 'name': 'edible-pod_pea'}, {'id': 20082, 'synset': 'sugar_snap_pea.n.01', 'name': 'sugar_snap_pea'}, {'id': 20083, 'synset': 'field_pea.n.02', 'name': 'field_pea'}, {'id': 20084, 'synset': 'field_pea.n.01', 'name': 'field_pea'}, {'id': 20085, 'synset': 'common_flat_pea.n.01', 'name': 'common_flat_pea'}, {'id': 20086, 'synset': 'quira.n.02', 'name': 'quira'}, {'id': 20087, 'synset': 'roble.n.01', 'name': 'roble'}, {'id': 20088, 'synset': 'panama_redwood_tree.n.01', 'name': 'Panama_redwood_tree'}, {'id': 20089, 'synset': 'indian_beech.n.01', 'name': 'Indian_beech'}, {'id': 20090, 'synset': 'winged_bean.n.01', 'name': 'winged_bean'}, {'id': 20091, 'synset': 'breadroot.n.01', 'name': 'breadroot'}, {'id': 20092, 'synset': 'bloodwood_tree.n.01', 'name': 'bloodwood_tree'}, {'id': 20093, 'synset': 'kino.n.02', 'name': 'kino'}, {'id': 20094, 'synset': 'red_sandalwood.n.02', 'name': 'red_sandalwood'}, {'id': 20095, 'synset': 'kudzu.n.01', 'name': 'kudzu'}, {'id': 20096, 'synset': 'bristly_locust.n.01', 'name': 'bristly_locust'}, {'id': 20097, 'synset': 'black_locust.n.02', 'name': 'black_locust'}, {'id': 20098, 'synset': 'clammy_locust.n.01', 'name': 'clammy_locust'}, {'id': 20099, 'synset': 'carib_wood.n.01', 'name': 'carib_wood'}, {'id': 20100, 'synset': 'colorado_river_hemp.n.01', 'name': 'Colorado_River_hemp'}, {'id': 20101, 'synset': 'scarlet_wisteria_tree.n.01', 'name': 'scarlet_wisteria_tree'}, {'id': 20102, 'synset': 'japanese_pagoda_tree.n.01', 'name': 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{'id': 20235, 'synset': 'fragrant_agrimony.n.01', 'name': 'fragrant_agrimony'}, {'id': 20236, 'synset': 'alderleaf_juneberry.n.01', 'name': 'alderleaf_Juneberry'}, {'id': 20237, 'synset': 'flowering_quince.n.01', 'name': 'flowering_quince'}, {'id': 20238, 'synset': 'japonica.n.02', 'name': 'japonica'}, {'id': 20239, 'synset': 'coco_plum.n.01', 'name': 'coco_plum'}, {'id': 20240, 'synset': 'cotoneaster.n.01', 'name': 'cotoneaster'}, {'id': 20241, 'synset': 'cotoneaster_dammeri.n.01', 'name': 'Cotoneaster_dammeri'}, {'id': 20242, 'synset': 'cotoneaster_horizontalis.n.01', 'name': 'Cotoneaster_horizontalis'}, {'id': 20243, 'synset': 'parsley_haw.n.01', 'name': 'parsley_haw'}, {'id': 20244, 'synset': 'scarlet_haw.n.01', 'name': 'scarlet_haw'}, {'id': 20245, 'synset': 'blackthorn.n.02', 'name': 'blackthorn'}, {'id': 20246, 'synset': 'cockspur_thorn.n.01', 'name': 'cockspur_thorn'}, {'id': 20247, 'synset': 'mayhaw.n.01', 'name': 'mayhaw'}, {'id': 20248, 'synset': 'red_haw.n.02', 'name': 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20264, 'synset': 'crab_apple.n.01', 'name': 'crab_apple'}, {'id': 20265, 'synset': 'siberian_crab.n.01', 'name': 'Siberian_crab'}, {'id': 20266, 'synset': 'wild_crab.n.01', 'name': 'wild_crab'}, {'id': 20267, 'synset': 'american_crab_apple.n.01', 'name': 'American_crab_apple'}, {'id': 20268, 'synset': 'oregon_crab_apple.n.01', 'name': 'Oregon_crab_apple'}, {'id': 20269, 'synset': 'southern_crab_apple.n.01', 'name': 'Southern_crab_apple'}, {'id': 20270, 'synset': 'iowa_crab.n.01', 'name': 'Iowa_crab'}, {'id': 20271, 'synset': 'bechtel_crab.n.01', 'name': 'Bechtel_crab'}, {'id': 20272, 'synset': 'medlar.n.02', 'name': 'medlar'}, {'id': 20273, 'synset': 'cinquefoil.n.01', 'name': 'cinquefoil'}, {'id': 20274, 'synset': 'silverweed.n.02', 'name': 'silverweed'}, {'id': 20275, 'synset': 'salad_burnet.n.01', 'name': 'salad_burnet'}, {'id': 20276, 'synset': 'plum.n.01', 'name': 'plum'}, {'id': 20277, 'synset': 'wild_plum.n.01', 'name': 'wild_plum'}, {'id': 20278, 'synset': 'allegheny_plum.n.01', 'name': 'Allegheny_plum'}, {'id': 20279, 'synset': 'american_red_plum.n.01', 'name': 'American_red_plum'}, {'id': 20280, 'synset': 'chickasaw_plum.n.01', 'name': 'chickasaw_plum'}, {'id': 20281, 'synset': 'beach_plum.n.01', 'name': 'beach_plum'}, {'id': 20282, 'synset': 'common_plum.n.01', 'name': 'common_plum'}, {'id': 20283, 'synset': 'bullace.n.01', 'name': 'bullace'}, {'id': 20284, 'synset': 'damson_plum.n.02', 'name': 'damson_plum'}, {'id': 20285, 'synset': 'big-tree_plum.n.01', 'name': 'big-tree_plum'}, {'id': 20286, 'synset': 'canada_plum.n.01', 'name': 'Canada_plum'}, {'id': 20287, 'synset': 'plumcot.n.01', 'name': 'plumcot'}, {'id': 20288, 'synset': 'apricot.n.01', 'name': 'apricot'}, {'id': 20289, 'synset': 'japanese_apricot.n.01', 'name': 'Japanese_apricot'}, {'id': 20290, 'synset': 'common_apricot.n.01', 'name': 'common_apricot'}, {'id': 20291, 'synset': 'purple_apricot.n.01', 'name': 'purple_apricot'}, {'id': 20292, 'synset': 'cherry.n.02', 'name': 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20308, 'synset': 'jordan_almond.n.01', 'name': 'jordan_almond'}, {'id': 20309, 'synset': 'dwarf_flowering_almond.n.01', 'name': 'dwarf_flowering_almond'}, {'id': 20310, 'synset': 'holly-leaved_cherry.n.01', 'name': 'holly-leaved_cherry'}, {'id': 20311, 'synset': 'fuji.n.01', 'name': 'fuji'}, {'id': 20312, 'synset': 'flowering_almond.n.02', 'name': 'flowering_almond'}, {'id': 20313, 'synset': 'cherry_laurel.n.01', 'name': 'cherry_laurel'}, {'id': 20314, 'synset': 'catalina_cherry.n.01', 'name': 'Catalina_cherry'}, {'id': 20315, 'synset': 'bird_cherry.n.01', 'name': 'bird_cherry'}, {'id': 20316, 'synset': 'hagberry_tree.n.01', 'name': 'hagberry_tree'}, {'id': 20317, 'synset': 'hagberry.n.01', 'name': 'hagberry'}, {'id': 20318, 'synset': 'pin_cherry.n.01', 'name': 'pin_cherry'}, {'id': 20319, 'synset': 'peach.n.01', 'name': 'peach'}, {'id': 20320, 'synset': 'nectarine.n.01', 'name': 'nectarine'}, {'id': 20321, 'synset': 'sand_cherry.n.01', 'name': 'sand_cherry'}, {'id': 20322, 'synset': 'japanese_plum.n.01', 'name': 'Japanese_plum'}, {'id': 20323, 'synset': 'black_cherry.n.01', 'name': 'black_cherry'}, {'id': 20324, 'synset': 'flowering_cherry.n.01', 'name': 'flowering_cherry'}, {'id': 20325, 'synset': 'oriental_cherry.n.01', 'name': 'oriental_cherry'}, {'id': 20326, 'synset': 'japanese_flowering_cherry.n.01', 'name': 'Japanese_flowering_cherry'}, {'id': 20327, 'synset': 'sierra_plum.n.01', 'name': 'Sierra_plum'}, {'id': 20328, 'synset': 'rosebud_cherry.n.01', 'name': 'rosebud_cherry'}, {'id': 20329, 'synset': 'russian_almond.n.01', 'name': 'Russian_almond'}, {'id': 20330, 'synset': 'flowering_almond.n.01', 'name': 'flowering_almond'}, {'id': 20331, 'synset': 'chokecherry.n.02', 'name': 'chokecherry'}, {'id': 20332, 'synset': 'chokecherry.n.01', 'name': 'chokecherry'}, {'id': 20333, 'synset': 'western_chokecherry.n.01', 'name': 'western_chokecherry'}, {'id': 20334, 'synset': 'pyracantha.n.01', 'name': 'Pyracantha'}, {'id': 20335, 'synset': 'pear.n.02', 'name': 'pear'}, {'id': 20336, 'synset': 'fruit_tree.n.01', 'name': 'fruit_tree'}, {'id': 20337, 'synset': 'bramble_bush.n.01', 'name': 'bramble_bush'}, {'id': 20338, 'synset': 'lawyerbush.n.01', 'name': 'lawyerbush'}, {'id': 20339, 'synset': 'stone_bramble.n.01', 'name': 'stone_bramble'}, {'id': 20340, 'synset': 'sand_blackberry.n.01', 'name': 'sand_blackberry'}, {'id': 20341, 'synset': 'boysenberry.n.01', 'name': 'boysenberry'}, {'id': 20342, 'synset': 'loganberry.n.01', 'name': 'loganberry'}, {'id': 20343, 'synset': 'american_dewberry.n.02', 'name': 'American_dewberry'}, {'id': 20344, 'synset': 'northern_dewberry.n.01', 'name': 'Northern_dewberry'}, {'id': 20345, 'synset': 'southern_dewberry.n.01', 'name': 'Southern_dewberry'}, {'id': 20346, 'synset': 'swamp_dewberry.n.01', 'name': 'swamp_dewberry'}, {'id': 20347, 'synset': 'european_dewberry.n.01', 'name': 'European_dewberry'}, {'id': 20348, 'synset': 'raspberry.n.01', 'name': 'raspberry'}, {'id': 20349, 'synset': 'wild_raspberry.n.01', 'name': 'wild_raspberry'}, {'id': 20350, 'synset': 'american_raspberry.n.01', 'name': 'American_raspberry'}, {'id': 20351, 'synset': 'black_raspberry.n.01', 'name': 'black_raspberry'}, {'id': 20352, 'synset': 'salmonberry.n.03', 'name': 'salmonberry'}, {'id': 20353, 'synset': 'salmonberry.n.02', 'name': 'salmonberry'}, {'id': 20354, 'synset': 'wineberry.n.01', 'name': 'wineberry'}, {'id': 20355, 'synset': 'mountain_ash.n.01', 'name': 'mountain_ash'}, {'id': 20356, 'synset': 'rowan.n.01', 'name': 'rowan'}, {'id': 20357, 'synset': 'rowanberry.n.01', 'name': 'rowanberry'}, {'id': 20358, 'synset': 'american_mountain_ash.n.01', 'name': 'American_mountain_ash'}, {'id': 20359, 'synset': 'western_mountain_ash.n.01', 'name': 'Western_mountain_ash'}, {'id': 20360, 'synset': 'service_tree.n.01', 'name': 'service_tree'}, {'id': 20361, 'synset': 'wild_service_tree.n.01', 'name': 'wild_service_tree'}, {'id': 20362, 'synset': 'spirea.n.02', 'name': 'spirea'}, {'id': 20363, 'synset': 'bridal_wreath.n.02', 'name': 'bridal_wreath'}, {'id': 20364, 'synset': 'madderwort.n.01', 'name': 'madderwort'}, {'id': 20365, 'synset': 'indian_madder.n.01', 'name': 'Indian_madder'}, {'id': 20366, 'synset': 'madder.n.01', 'name': 'madder'}, {'id': 20367, 'synset': 'woodruff.n.02', 'name': 'woodruff'}, {'id': 20368, 'synset': 'dagame.n.01', 'name': 'dagame'}, {'id': 20369, 'synset': 'blolly.n.01', 'name': 'blolly'}, {'id': 20370, 'synset': 'coffee.n.02', 'name': 'coffee'}, {'id': 20371, 'synset': 'arabian_coffee.n.01', 'name': 'Arabian_coffee'}, {'id': 20372, 'synset': 'liberian_coffee.n.01', 'name': 'Liberian_coffee'}, {'id': 20373, 'synset': 'robusta_coffee.n.01', 'name': 'robusta_coffee'}, {'id': 20374, 'synset': 'cinchona.n.02', 'name': 'cinchona'}, {'id': 20375, 'synset': 'cartagena_bark.n.01', 'name': 'Cartagena_bark'}, {'id': 20376, 'synset': 'calisaya.n.01', 'name': 'calisaya'}, {'id': 20377, 'synset': 'cinchona_tree.n.01', 'name': 'cinchona_tree'}, {'id': 20378, 'synset': 'cinchona.n.01', 'name': 'cinchona'}, {'id': 20379, 'synset': 'bedstraw.n.01', 'name': 'bedstraw'}, {'id': 20380, 'synset': 'sweet_woodruff.n.01', 'name': 'sweet_woodruff'}, {'id': 20381, 'synset': 'northern_bedstraw.n.01', 'name': 'Northern_bedstraw'}, {'id': 20382, 'synset': 'yellow_bedstraw.n.01', 'name': 'yellow_bedstraw'}, {'id': 20383, 'synset': 'wild_licorice.n.01', 'name': 'wild_licorice'}, {'id': 20384, 'synset': 'cleavers.n.01', 'name': 'cleavers'}, {'id': 20385, 'synset': 'wild_madder.n.01', 'name': 'wild_madder'}, {'id': 20386, 'synset': 'cape_jasmine.n.01', 'name': 'cape_jasmine'}, {'id': 20387, 'synset': 'genipa.n.01', 'name': 'genipa'}, {'id': 20388, 'synset': 'genipap_fruit.n.01', 'name': 'genipap_fruit'}, {'id': 20389, 'synset': 'hamelia.n.01', 'name': 'hamelia'}, {'id': 20390, 'synset': 'scarlet_bush.n.01', 'name': 'scarlet_bush'}, {'id': 20391, 'synset': 'lemonwood.n.02', 'name': 'lemonwood'}, {'id': 20392, 'synset': 'negro_peach.n.01', 'name': 'negro_peach'}, {'id': 20393, 'synset': 'wild_medlar.n.01', 'name': 'wild_medlar'}, {'id': 20394, 'synset': 'spanish_tamarind.n.01', 'name': 'Spanish_tamarind'}, {'id': 20395, 'synset': 'abelia.n.01', 'name': 'abelia'}, {'id': 20396, 'synset': 'bush_honeysuckle.n.02', 'name': 'bush_honeysuckle'}, {'id': 20397, 'synset': 'american_twinflower.n.01', 'name': 'American_twinflower'}, {'id': 20398, 'synset': 'honeysuckle.n.01', 'name': 'honeysuckle'}, {'id': 20399, 'synset': 'american_fly_honeysuckle.n.01', 'name': 'American_fly_honeysuckle'}, {'id': 20400, 'synset': 'italian_honeysuckle.n.01', 'name': 'Italian_honeysuckle'}, {'id': 20401, 'synset': 'yellow_honeysuckle.n.01', 'name': 'yellow_honeysuckle'}, {'id': 20402, 'synset': 'hairy_honeysuckle.n.01', 'name': 'hairy_honeysuckle'}, {'id': 20403, 'synset': 'japanese_honeysuckle.n.01', 'name': 'Japanese_honeysuckle'}, {'id': 20404, 'synset': "hall's_honeysuckle.n.01", 'name': "Hall's_honeysuckle"}, {'id': 20405, 'synset': "morrow's_honeysuckle.n.01", 'name': "Morrow's_honeysuckle"}, {'id': 20406, 'synset': 'woodbine.n.02', 'name': 'woodbine'}, {'id': 20407, 'synset': 'trumpet_honeysuckle.n.01', 'name': 'trumpet_honeysuckle'}, {'id': 20408, 'synset': 'european_fly_honeysuckle.n.01', 'name': 'European_fly_honeysuckle'}, {'id': 20409, 'synset': 'swamp_fly_honeysuckle.n.01', 'name': 'swamp_fly_honeysuckle'}, {'id': 20410, 'synset': 'snowberry.n.01', 'name': 'snowberry'}, {'id': 20411, 'synset': 'coralberry.n.01', 'name': 'coralberry'}, {'id': 20412, 'synset': 'blue_elder.n.01', 'name': 'blue_elder'}, {'id': 20413, 'synset': 'dwarf_elder.n.01', 'name': 'dwarf_elder'}, {'id': 20414, 'synset': 'american_red_elder.n.01', 'name': 'American_red_elder'}, {'id': 20415, 'synset': 'european_red_elder.n.01', 'name': 'European_red_elder'}, {'id': 20416, 'synset': 'feverroot.n.01', 'name': 'feverroot'}, {'id': 20417, 'synset': 'cranberry_bush.n.01', 'name': 'cranberry_bush'}, {'id': 20418, 'synset': 'wayfaring_tree.n.01', 'name': 'wayfaring_tree'}, {'id': 20419, 'synset': 'guelder_rose.n.01', 'name': 'guelder_rose'}, {'id': 20420, 'synset': 'arrow_wood.n.01', 'name': 'arrow_wood'}, {'id': 20421, 'synset': 'black_haw.n.02', 'name': 'black_haw'}, {'id': 20422, 'synset': 'weigela.n.01', 'name': 'weigela'}, {'id': 20423, 'synset': 'teasel.n.01', 'name': 'teasel'}, {'id': 20424, 'synset': 'common_teasel.n.01', 'name': 'common_teasel'}, {'id': 20425, 'synset': "fuller's_teasel.n.01", 'name': "fuller's_teasel"}, {'id': 20426, 'synset': 'wild_teasel.n.01', 'name': 'wild_teasel'}, {'id': 20427, 'synset': 'scabious.n.01', 'name': 'scabious'}, {'id': 20428, 'synset': 'sweet_scabious.n.01', 'name': 'sweet_scabious'}, {'id': 20429, 'synset': 'field_scabious.n.01', 'name': 'field_scabious'}, {'id': 20430, 'synset': 'jewelweed.n.01', 'name': 'jewelweed'}, {'id': 20431, 'synset': 'geranium.n.01', 'name': 'geranium'}, {'id': 20432, 'synset': 'cranesbill.n.01', 'name': 'cranesbill'}, {'id': 20433, 'synset': 'wild_geranium.n.01', 'name': 'wild_geranium'}, {'id': 20434, 'synset': 'meadow_cranesbill.n.01', 'name': 'meadow_cranesbill'}, {'id': 20435, 'synset': "richardson's_geranium.n.01", 'name': "Richardson's_geranium"}, {'id': 20436, 'synset': 'herb_robert.n.01', 'name': 'herb_robert'}, {'id': 20437, 'synset': 'sticky_geranium.n.01', 'name': 'sticky_geranium'}, {'id': 20438, 'synset': "dove's_foot_geranium.n.01", 'name': "dove's_foot_geranium"}, {'id': 20439, 'synset': 'rose_geranium.n.01', 'name': 'rose_geranium'}, {'id': 20440, 'synset': 'fish_geranium.n.01', 'name': 'fish_geranium'}, {'id': 20441, 'synset': 'ivy_geranium.n.01', 'name': 'ivy_geranium'}, {'id': 20442, 'synset': 'apple_geranium.n.01', 'name': 'apple_geranium'}, {'id': 20443, 'synset': 'lemon_geranium.n.01', 'name': 'lemon_geranium'}, {'id': 20444, 'synset': 'storksbill.n.01', 'name': 'storksbill'}, {'id': 20445, 'synset': 'musk_clover.n.01', 'name': 'musk_clover'}, {'id': 20446, 'synset': 'incense_tree.n.01', 'name': 'incense_tree'}, {'id': 20447, 'synset': 'elephant_tree.n.01', 'name': 'elephant_tree'}, {'id': 20448, 'synset': 'gumbo-limbo.n.01', 'name': 'gumbo-limbo'}, {'id': 20449, 'synset': 'boswellia_carteri.n.01', 'name': 'Boswellia_carteri'}, {'id': 20450, 'synset': 'salai.n.01', 'name': 'salai'}, {'id': 20451, 'synset': 'balm_of_gilead.n.03', 'name': 'balm_of_gilead'}, {'id': 20452, 'synset': 'myrrh_tree.n.01', 'name': 'myrrh_tree'}, {'id': 20453, 'synset': 'protium_heptaphyllum.n.01', 'name': 'Protium_heptaphyllum'}, {'id': 20454, 'synset': 'protium_guianense.n.01', 'name': 'Protium_guianense'}, {'id': 20455, 'synset': 'water_starwort.n.01', 'name': 'water_starwort'}, {'id': 20456, 'synset': 'barbados_cherry.n.01', 'name': 'barbados_cherry'}, {'id': 20457, 'synset': 'mahogany.n.02', 'name': 'mahogany'}, {'id': 20458, 'synset': 'chinaberry.n.02', 'name': 'chinaberry'}, {'id': 20459, 'synset': 'neem.n.01', 'name': 'neem'}, {'id': 20460, 'synset': 'neem_seed.n.01', 'name': 'neem_seed'}, {'id': 20461, 'synset': 'spanish_cedar.n.01', 'name': 'Spanish_cedar'}, {'id': 20462, 'synset': 'satinwood.n.03', 'name': 'satinwood'}, {'id': 20463, 'synset': 'african_scented_mahogany.n.01', 'name': 'African_scented_mahogany'}, {'id': 20464, 'synset': 'silver_ash.n.01', 'name': 'silver_ash'}, {'id': 20465, 'synset': 'native_beech.n.01', 'name': 'native_beech'}, {'id': 20466, 'synset': 'bunji-bunji.n.01', 'name': 'bunji-bunji'}, {'id': 20467, 'synset': 'african_mahogany.n.01', 'name': 'African_mahogany'}, {'id': 20468, 'synset': 'lanseh_tree.n.01', 'name': 'lanseh_tree'}, {'id': 20469, 'synset': 'true_mahogany.n.01', 'name': 'true_mahogany'}, {'id': 20470, 'synset': 'honduras_mahogany.n.01', 'name': 'Honduras_mahogany'}, {'id': 20471, 'synset': 'philippine_mahogany.n.02', 'name': 'Philippine_mahogany'}, {'id': 20472, 'synset': 'caracolito.n.01', 'name': 'caracolito'}, {'id': 20473, 'synset': 'common_wood_sorrel.n.01', 'name': 'common_wood_sorrel'}, {'id': 20474, 'synset': 'bermuda_buttercup.n.01', 'name': 'Bermuda_buttercup'}, {'id': 20475, 'synset': 'creeping_oxalis.n.01', 'name': 'creeping_oxalis'}, {'id': 20476, 'synset': 'goatsfoot.n.01', 'name': 'goatsfoot'}, {'id': 20477, 'synset': 'violet_wood_sorrel.n.01', 'name': 'violet_wood_sorrel'}, {'id': 20478, 'synset': 'oca.n.01', 'name': 'oca'}, {'id': 20479, 'synset': 'carambola.n.01', 'name': 'carambola'}, {'id': 20480, 'synset': 'bilimbi.n.01', 'name': 'bilimbi'}, {'id': 20481, 'synset': 'milkwort.n.01', 'name': 'milkwort'}, {'id': 20482, 'synset': 'senega.n.02', 'name': 'senega'}, {'id': 20483, 'synset': 'orange_milkwort.n.01', 'name': 'orange_milkwort'}, {'id': 20484, 'synset': 'flowering_wintergreen.n.01', 'name': 'flowering_wintergreen'}, {'id': 20485, 'synset': 'seneca_snakeroot.n.01', 'name': 'Seneca_snakeroot'}, {'id': 20486, 'synset': 'common_milkwort.n.01', 'name': 'common_milkwort'}, {'id': 20487, 'synset': 'rue.n.01', 'name': 'rue'}, {'id': 20488, 'synset': 'citrus.n.02', 'name': 'citrus'}, {'id': 20489, 'synset': 'orange.n.03', 'name': 'orange'}, {'id': 20490, 'synset': 'sour_orange.n.01', 'name': 'sour_orange'}, {'id': 20491, 'synset': 'bergamot.n.01', 'name': 'bergamot'}, {'id': 20492, 'synset': 'pomelo.n.01', 'name': 'pomelo'}, {'id': 20493, 'synset': 'citron.n.02', 'name': 'citron'}, {'id': 20494, 'synset': 'grapefruit.n.01', 'name': 'grapefruit'}, {'id': 20495, 'synset': 'mandarin.n.01', 'name': 'mandarin'}, {'id': 20496, 'synset': 'tangerine.n.01', 'name': 'tangerine'}, {'id': 20497, 'synset': 'satsuma.n.01', 'name': 'satsuma'}, {'id': 20498, 'synset': 'sweet_orange.n.02', 'name': 'sweet_orange'}, {'id': 20499, 'synset': 'temple_orange.n.01', 'name': 'temple_orange'}, {'id': 20500, 'synset': 'tangelo.n.01', 'name': 'tangelo'}, {'id': 20501, 'synset': 'rangpur.n.01', 'name': 'rangpur'}, {'id': 20502, 'synset': 'lemon.n.03', 'name': 'lemon'}, {'id': 20503, 'synset': 'sweet_lemon.n.01', 'name': 'sweet_lemon'}, {'id': 20504, 'synset': 'lime.n.04', 'name': 'lime'}, {'id': 20505, 'synset': 'citrange.n.01', 'name': 'citrange'}, {'id': 20506, 'synset': 'fraxinella.n.01', 'name': 'fraxinella'}, {'id': 20507, 'synset': 'kumquat.n.01', 'name': 'kumquat'}, {'id': 20508, 'synset': 'marumi.n.01', 'name': 'marumi'}, {'id': 20509, 'synset': 'nagami.n.01', 'name': 'nagami'}, {'id': 20510, 'synset': 'cork_tree.n.01', 'name': 'cork_tree'}, {'id': 20511, 'synset': 'trifoliate_orange.n.01', 'name': 'trifoliate_orange'}, {'id': 20512, 'synset': 'prickly_ash.n.01', 'name': 'prickly_ash'}, {'id': 20513, 'synset': 'toothache_tree.n.01', 'name': 'toothache_tree'}, {'id': 20514, 'synset': "hercules'-club.n.01", 'name': "Hercules'-club"}, {'id': 20515, 'synset': 'bitterwood_tree.n.01', 'name': 'bitterwood_tree'}, {'id': 20516, 'synset': 'marupa.n.01', 'name': 'marupa'}, {'id': 20517, 'synset': 'paradise_tree.n.01', 'name': 'paradise_tree'}, {'id': 20518, 'synset': 'ailanthus.n.01', 'name': 'ailanthus'}, {'id': 20519, 'synset': 'tree_of_heaven.n.01', 'name': 'tree_of_heaven'}, {'id': 20520, 'synset': 'wild_mango.n.01', 'name': 'wild_mango'}, {'id': 20521, 'synset': 'pepper_tree.n.02', 'name': 'pepper_tree'}, {'id': 20522, 'synset': 'jamaica_quassia.n.02', 'name': 'Jamaica_quassia'}, {'id': 20523, 'synset': 'quassia.n.02', 'name': 'quassia'}, {'id': 20524, 'synset': 'nasturtium.n.01', 'name': 'nasturtium'}, {'id': 20525, 'synset': 'garden_nasturtium.n.01', 'name': 'garden_nasturtium'}, {'id': 20526, 'synset': 'bush_nasturtium.n.01', 'name': 'bush_nasturtium'}, {'id': 20527, 'synset': 'canarybird_flower.n.01', 'name': 'canarybird_flower'}, {'id': 20528, 'synset': 'bean_caper.n.01', 'name': 'bean_caper'}, {'id': 20529, 'synset': 'palo_santo.n.01', 'name': 'palo_santo'}, {'id': 20530, 'synset': 'lignum_vitae.n.02', 'name': 'lignum_vitae'}, {'id': 20531, 'synset': 'creosote_bush.n.01', 'name': 'creosote_bush'}, {'id': 20532, 'synset': 'caltrop.n.01', 'name': 'caltrop'}, {'id': 20533, 'synset': 'willow.n.01', 'name': 'willow'}, {'id': 20534, 'synset': 'osier.n.02', 'name': 'osier'}, {'id': 20535, 'synset': 'white_willow.n.01', 'name': 'white_willow'}, {'id': 20536, 'synset': 'silver_willow.n.01', 'name': 'silver_willow'}, {'id': 20537, 'synset': 'golden_willow.n.01', 'name': 'golden_willow'}, {'id': 20538, 'synset': 'cricket-bat_willow.n.01', 'name': 'cricket-bat_willow'}, {'id': 20539, 'synset': 'arctic_willow.n.01', 'name': 'arctic_willow'}, {'id': 20540, 'synset': 'weeping_willow.n.01', 'name': 'weeping_willow'}, {'id': 20541, 'synset': 'wisconsin_weeping_willow.n.01', 'name': 'Wisconsin_weeping_willow'}, {'id': 20542, 'synset': 'pussy_willow.n.01', 'name': 'pussy_willow'}, {'id': 20543, 'synset': 'sallow.n.01', 'name': 'sallow'}, {'id': 20544, 'synset': 'goat_willow.n.01', 'name': 'goat_willow'}, {'id': 20545, 'synset': 'peachleaf_willow.n.01', 'name': 'peachleaf_willow'}, {'id': 20546, 'synset': 'almond_willow.n.01', 'name': 'almond_willow'}, {'id': 20547, 'synset': 'hoary_willow.n.01', 'name': 'hoary_willow'}, {'id': 20548, 'synset': 'crack_willow.n.01', 'name': 'crack_willow'}, {'id': 20549, 'synset': 'prairie_willow.n.01', 'name': 'prairie_willow'}, {'id': 20550, 'synset': 'dwarf_willow.n.01', 'name': 'dwarf_willow'}, {'id': 20551, 'synset': 'grey_willow.n.01', 'name': 'grey_willow'}, {'id': 20552, 'synset': 'arroyo_willow.n.01', 'name': 'arroyo_willow'}, {'id': 20553, 'synset': 'shining_willow.n.01', 'name': 'shining_willow'}, {'id': 20554, 'synset': 'swamp_willow.n.01', 'name': 'swamp_willow'}, {'id': 20555, 'synset': 'bay_willow.n.01', 'name': 'bay_willow'}, {'id': 20556, 'synset': 'purple_willow.n.01', 'name': 'purple_willow'}, {'id': 20557, 'synset': 'balsam_willow.n.01', 'name': 'balsam_willow'}, {'id': 20558, 'synset': 'creeping_willow.n.01', 'name': 'creeping_willow'}, {'id': 20559, 'synset': 'sitka_willow.n.01', 'name': 'Sitka_willow'}, {'id': 20560, 'synset': 'dwarf_grey_willow.n.01', 'name': 'dwarf_grey_willow'}, {'id': 20561, 'synset': 'bearberry_willow.n.01', 'name': 'bearberry_willow'}, {'id': 20562, 'synset': 'common_osier.n.01', 'name': 'common_osier'}, {'id': 20563, 'synset': 'poplar.n.02', 'name': 'poplar'}, {'id': 20564, 'synset': 'balsam_poplar.n.01', 'name': 'balsam_poplar'}, {'id': 20565, 'synset': 'white_poplar.n.01', 'name': 'white_poplar'}, {'id': 20566, 'synset': 'grey_poplar.n.01', 'name': 'grey_poplar'}, {'id': 20567, 'synset': 'black_poplar.n.01', 'name': 'black_poplar'}, {'id': 20568, 'synset': 'lombardy_poplar.n.01', 'name': 'Lombardy_poplar'}, {'id': 20569, 'synset': 'cottonwood.n.01', 'name': 'cottonwood'}, {'id': 20570, 'synset': 'eastern_cottonwood.n.01', 'name': 'Eastern_cottonwood'}, {'id': 20571, 'synset': 'black_cottonwood.n.02', 'name': 'black_cottonwood'}, {'id': 20572, 'synset': 'swamp_cottonwood.n.01', 'name': 'swamp_cottonwood'}, {'id': 20573, 'synset': 'aspen.n.01', 'name': 'aspen'}, {'id': 20574, 'synset': 'quaking_aspen.n.01', 'name': 'quaking_aspen'}, {'id': 20575, 'synset': 'american_quaking_aspen.n.01', 'name': 'American_quaking_aspen'}, {'id': 20576, 'synset': 'canadian_aspen.n.01', 'name': 'Canadian_aspen'}, {'id': 20577, 'synset': 'sandalwood_tree.n.01', 'name': 'sandalwood_tree'}, {'id': 20578, 'synset': 'quandong.n.01', 'name': 'quandong'}, {'id': 20579, 'synset': 'rabbitwood.n.01', 'name': 'rabbitwood'}, {'id': 20580, 'synset': 'loranthaceae.n.01', 'name': 'Loranthaceae'}, {'id': 20581, 'synset': 'mistletoe.n.03', 'name': 'mistletoe'}, {'id': 20582, 'synset': 'american_mistletoe.n.02', 'name': 'American_mistletoe'}, {'id': 20583, 'synset': 'mistletoe.n.02', 'name': 'mistletoe'}, {'id': 20584, 'synset': 'american_mistletoe.n.01', 'name': 'American_mistletoe'}, {'id': 20585, 'synset': 'aalii.n.01', 'name': 'aalii'}, {'id': 20586, 'synset': 'soapberry.n.01', 'name': 'soapberry'}, {'id': 20587, 'synset': 'wild_china_tree.n.01', 'name': 'wild_China_tree'}, {'id': 20588, 'synset': 'china_tree.n.01', 'name': 'China_tree'}, {'id': 20589, 'synset': 'akee.n.01', 'name': 'akee'}, {'id': 20590, 'synset': 'soapberry_vine.n.01', 'name': 'soapberry_vine'}, {'id': 20591, 'synset': 'heartseed.n.01', 'name': 'heartseed'}, {'id': 20592, 'synset': 'balloon_vine.n.01', 'name': 'balloon_vine'}, {'id': 20593, 'synset': 'longan.n.01', 'name': 'longan'}, {'id': 20594, 'synset': 'harpullia.n.01', 'name': 'harpullia'}, {'id': 20595, 'synset': 'harpulla.n.01', 'name': 'harpulla'}, {'id': 20596, 'synset': 'moreton_bay_tulipwood.n.01', 'name': 'Moreton_Bay_tulipwood'}, {'id': 20597, 'synset': 'litchi.n.01', 'name': 'litchi'}, {'id': 20598, 'synset': 'spanish_lime.n.01', 'name': 'Spanish_lime'}, {'id': 20599, 'synset': 'rambutan.n.01', 'name': 'rambutan'}, {'id': 20600, 'synset': 'pulasan.n.01', 'name': 'pulasan'}, {'id': 20601, 'synset': 'pachysandra.n.01', 'name': 'pachysandra'}, {'id': 20602, 'synset': 'allegheny_spurge.n.01', 'name': 'Allegheny_spurge'}, {'id': 20603, 'synset': 'bittersweet.n.02', 'name': 'bittersweet'}, {'id': 20604, 'synset': 'spindle_tree.n.01', 'name': 'spindle_tree'}, {'id': 20605, 'synset': 'winged_spindle_tree.n.01', 'name': 'winged_spindle_tree'}, {'id': 20606, 'synset': 'wahoo.n.02', 'name': 'wahoo'}, {'id': 20607, 'synset': 'strawberry_bush.n.01', 'name': 'strawberry_bush'}, {'id': 20608, 'synset': 'evergreen_bittersweet.n.01', 'name': 'evergreen_bittersweet'}, {'id': 20609, 'synset': 'cyrilla.n.01', 'name': 'cyrilla'}, {'id': 20610, 'synset': 'titi.n.01', 'name': 'titi'}, {'id': 20611, 'synset': 'crowberry.n.01', 'name': 'crowberry'}, {'id': 20612, 'synset': 'maple.n.02', 'name': 'maple'}, {'id': 20613, 'synset': 'silver_maple.n.01', 'name': 'silver_maple'}, {'id': 20614, 'synset': 'sugar_maple.n.01', 'name': 'sugar_maple'}, {'id': 20615, 'synset': 'red_maple.n.01', 'name': 'red_maple'}, {'id': 20616, 'synset': 'moosewood.n.01', 'name': 'moosewood'}, {'id': 20617, 'synset': 'oregon_maple.n.01', 'name': 'Oregon_maple'}, {'id': 20618, 'synset': 'dwarf_maple.n.01', 'name': 'dwarf_maple'}, {'id': 20619, 'synset': 'mountain_maple.n.01', 'name': 'mountain_maple'}, {'id': 20620, 'synset': 'vine_maple.n.01', 'name': 'vine_maple'}, {'id': 20621, 'synset': 'hedge_maple.n.01', 'name': 'hedge_maple'}, {'id': 20622, 'synset': 'norway_maple.n.01', 'name': 'Norway_maple'}, {'id': 20623, 'synset': 'sycamore.n.03', 'name': 'sycamore'}, {'id': 20624, 'synset': 'box_elder.n.01', 'name': 'box_elder'}, {'id': 20625, 'synset': 'california_box_elder.n.01', 'name': 'California_box_elder'}, {'id': 20626, 'synset': 'pointed-leaf_maple.n.01', 'name': 'pointed-leaf_maple'}, {'id': 20627, 'synset': 'japanese_maple.n.02', 'name': 'Japanese_maple'}, {'id': 20628, 'synset': 'japanese_maple.n.01', 'name': 'Japanese_maple'}, {'id': 20629, 'synset': 'holly.n.01', 'name': 'holly'}, {'id': 20630, 'synset': 'chinese_holly.n.01', 'name': 'Chinese_holly'}, {'id': 20631, 'synset': 'bearberry.n.02', 'name': 'bearberry'}, {'id': 20632, 'synset': 'inkberry.n.01', 'name': 'inkberry'}, {'id': 20633, 'synset': 'mate.n.07', 'name': 'mate'}, {'id': 20634, 'synset': 'american_holly.n.01', 'name': 'American_holly'}, {'id': 20635, 'synset': 'low_gallberry_holly.n.01', 'name': 'low_gallberry_holly'}, {'id': 20636, 'synset': 'tall_gallberry_holly.n.01', 'name': 'tall_gallberry_holly'}, {'id': 20637, 'synset': 'yaupon_holly.n.01', 'name': 'yaupon_holly'}, {'id': 20638, 'synset': 'deciduous_holly.n.01', 'name': 'deciduous_holly'}, {'id': 20639, 'synset': 'juneberry_holly.n.01', 'name': 'juneberry_holly'}, {'id': 20640, 'synset': 'largeleaf_holly.n.01', 'name': 'largeleaf_holly'}, {'id': 20641, 'synset': 'geogia_holly.n.01', 'name': 'Geogia_holly'}, {'id': 20642, 'synset': 'common_winterberry_holly.n.01', 'name': 'common_winterberry_holly'}, {'id': 20643, 'synset': 'smooth_winterberry_holly.n.01', 'name': 'smooth_winterberry_holly'}, {'id': 20644, 'synset': 'cashew.n.01', 'name': 'cashew'}, {'id': 20645, 'synset': 'goncalo_alves.n.01', 'name': 'goncalo_alves'}, {'id': 20646, 'synset': 'venetian_sumac.n.01', 'name': 'Venetian_sumac'}, {'id': 20647, 'synset': 'laurel_sumac.n.01', 'name': 'laurel_sumac'}, {'id': 20648, 'synset': 'mango.n.01', 'name': 'mango'}, {'id': 20649, 'synset': 'pistachio.n.01', 'name': 'pistachio'}, {'id': 20650, 'synset': 'terebinth.n.01', 'name': 'terebinth'}, {'id': 20651, 'synset': 'mastic.n.03', 'name': 'mastic'}, {'id': 20652, 'synset': 'australian_sumac.n.01', 'name': 'Australian_sumac'}, {'id': 20653, 'synset': 'sumac.n.02', 'name': 'sumac'}, {'id': 20654, 'synset': 'smooth_sumac.n.01', 'name': 'smooth_sumac'}, {'id': 20655, 'synset': 'sugar-bush.n.01', 'name': 'sugar-bush'}, {'id': 20656, 'synset': 'staghorn_sumac.n.01', 'name': 'staghorn_sumac'}, {'id': 20657, 'synset': 'squawbush.n.01', 'name': 'squawbush'}, {'id': 20658, 'synset': 'aroeira_blanca.n.01', 'name': 'aroeira_blanca'}, {'id': 20659, 'synset': 'pepper_tree.n.01', 'name': 'pepper_tree'}, {'id': 20660, 'synset': 'brazilian_pepper_tree.n.01', 'name': 'Brazilian_pepper_tree'}, {'id': 20661, 'synset': 'hog_plum.n.01', 'name': 'hog_plum'}, {'id': 20662, 'synset': 'mombin.n.01', 'name': 'mombin'}, {'id': 20663, 'synset': 'poison_ash.n.01', 'name': 'poison_ash'}, {'id': 20664, 'synset': 'poison_ivy.n.02', 'name': 'poison_ivy'}, {'id': 20665, 'synset': 'western_poison_oak.n.01', 'name': 'western_poison_oak'}, {'id': 20666, 'synset': 'eastern_poison_oak.n.01', 'name': 'eastern_poison_oak'}, {'id': 20667, 'synset': 'varnish_tree.n.02', 'name': 'varnish_tree'}, {'id': 20668, 'synset': 'horse_chestnut.n.01', 'name': 'horse_chestnut'}, {'id': 20669, 'synset': 'buckeye.n.01', 'name': 'buckeye'}, {'id': 20670, 'synset': 'sweet_buckeye.n.01', 'name': 'sweet_buckeye'}, {'id': 20671, 'synset': 'ohio_buckeye.n.01', 'name': 'Ohio_buckeye'}, {'id': 20672, 'synset': 'dwarf_buckeye.n.01', 'name': 'dwarf_buckeye'}, {'id': 20673, 'synset': 'red_buckeye.n.01', 'name': 'red_buckeye'}, {'id': 20674, 'synset': 'particolored_buckeye.n.01', 'name': 'particolored_buckeye'}, {'id': 20675, 'synset': 'ebony.n.03', 'name': 'ebony'}, {'id': 20676, 'synset': 'marblewood.n.02', 'name': 'marblewood'}, {'id': 20677, 'synset': 'marblewood.n.01', 'name': 'marblewood'}, {'id': 20678, 'synset': 'persimmon.n.01', 'name': 'persimmon'}, {'id': 20679, 'synset': 'japanese_persimmon.n.01', 'name': 'Japanese_persimmon'}, {'id': 20680, 'synset': 'american_persimmon.n.01', 'name': 'American_persimmon'}, {'id': 20681, 'synset': 'date_plum.n.01', 'name': 'date_plum'}, {'id': 20682, 'synset': 'buckthorn.n.02', 'name': 'buckthorn'}, {'id': 20683, 'synset': 'southern_buckthorn.n.01', 'name': 'southern_buckthorn'}, {'id': 20684, 'synset': 'false_buckthorn.n.01', 'name': 'false_buckthorn'}, {'id': 20685, 'synset': 'star_apple.n.01', 'name': 'star_apple'}, {'id': 20686, 'synset': 'satinleaf.n.01', 'name': 'satinleaf'}, {'id': 20687, 'synset': 'balata.n.02', 'name': 'balata'}, {'id': 20688, 'synset': 'sapodilla.n.01', 'name': 'sapodilla'}, {'id': 20689, 'synset': 'gutta-percha_tree.n.02', 'name': 'gutta-percha_tree'}, {'id': 20690, 'synset': 'gutta-percha_tree.n.01', 'name': 'gutta-percha_tree'}, {'id': 20691, 'synset': 'canistel.n.01', 'name': 'canistel'}, {'id': 20692, 'synset': 'marmalade_tree.n.01', 'name': 'marmalade_tree'}, {'id': 20693, 'synset': 'sweetleaf.n.01', 'name': 'sweetleaf'}, {'id': 20694, 'synset': 'asiatic_sweetleaf.n.01', 'name': 'Asiatic_sweetleaf'}, {'id': 20695, 'synset': 'styrax.n.01', 'name': 'styrax'}, {'id': 20696, 'synset': 'snowbell.n.01', 'name': 'snowbell'}, {'id': 20697, 'synset': 'japanese_snowbell.n.01', 'name': 'Japanese_snowbell'}, {'id': 20698, 'synset': 'texas_snowbell.n.01', 'name': 'Texas_snowbell'}, {'id': 20699, 'synset': 'silver-bell_tree.n.01', 'name': 'silver-bell_tree'}, {'id': 20700, 'synset': 'carnivorous_plant.n.01', 'name': 'carnivorous_plant'}, {'id': 20701, 'synset': 'pitcher_plant.n.01', 'name': 'pitcher_plant'}, {'id': 20702, 'synset': 'common_pitcher_plant.n.01', 'name': 'common_pitcher_plant'}, {'id': 20703, 'synset': 'hooded_pitcher_plant.n.01', 'name': 'hooded_pitcher_plant'}, {'id': 20704, 'synset': "huntsman's_horn.n.01", 'name': "huntsman's_horn"}, {'id': 20705, 'synset': 'tropical_pitcher_plant.n.01', 'name': 'tropical_pitcher_plant'}, {'id': 20706, 'synset': 'sundew.n.01', 'name': 'sundew'}, {'id': 20707, 'synset': "venus's_flytrap.n.01", 'name': "Venus's_flytrap"}, {'id': 20708, 'synset': 'waterwheel_plant.n.01', 'name': 'waterwheel_plant'}, {'id': 20709, 'synset': 'drosophyllum_lusitanicum.n.01', 'name': 'Drosophyllum_lusitanicum'}, {'id': 20710, 'synset': 'roridula.n.01', 'name': 'roridula'}, {'id': 20711, 'synset': 'australian_pitcher_plant.n.01', 'name': 'Australian_pitcher_plant'}, {'id': 20712, 'synset': 'sedum.n.01', 'name': 'sedum'}, {'id': 20713, 'synset': 'stonecrop.n.01', 'name': 'stonecrop'}, {'id': 20714, 'synset': 'rose-root.n.01', 'name': 'rose-root'}, {'id': 20715, 'synset': 'orpine.n.01', 'name': 'orpine'}, {'id': 20716, 'synset': 'pinwheel.n.01', 'name': 'pinwheel'}, {'id': 20717, 'synset': 'christmas_bush.n.01', 'name': 'Christmas_bush'}, {'id': 20718, 'synset': 'hortensia.n.01', 'name': 'hortensia'}, {'id': 20719, 'synset': 'fall-blooming_hydrangea.n.01', 'name': 'fall-blooming_hydrangea'}, {'id': 20720, 'synset': 'carpenteria.n.01', 'name': 'carpenteria'}, {'id': 20721, 'synset': 'decumary.n.01', 'name': 'decumary'}, {'id': 20722, 'synset': 'deutzia.n.01', 'name': 'deutzia'}, {'id': 20723, 'synset': 'philadelphus.n.01', 'name': 'philadelphus'}, {'id': 20724, 'synset': 'mock_orange.n.01', 'name': 'mock_orange'}, {'id': 20725, 'synset': 'saxifrage.n.01', 'name': 'saxifrage'}, {'id': 20726, 'synset': 'yellow_mountain_saxifrage.n.01', 'name': 'yellow_mountain_saxifrage'}, {'id': 20727, 'synset': 'meadow_saxifrage.n.01', 'name': 'meadow_saxifrage'}, {'id': 20728, 'synset': 'mossy_saxifrage.n.01', 'name': 'mossy_saxifrage'}, {'id': 20729, 'synset': 'western_saxifrage.n.01', 'name': 'western_saxifrage'}, {'id': 20730, 'synset': 'purple_saxifrage.n.01', 'name': 'purple_saxifrage'}, {'id': 20731, 'synset': 'star_saxifrage.n.01', 'name': 'star_saxifrage'}, {'id': 20732, 'synset': 'strawberry_geranium.n.01', 'name': 'strawberry_geranium'}, {'id': 20733, 'synset': 'astilbe.n.01', 'name': 'astilbe'}, {'id': 20734, 'synset': 'false_goatsbeard.n.01', 'name': 'false_goatsbeard'}, {'id': 20735, 'synset': 'dwarf_astilbe.n.01', 'name': 'dwarf_astilbe'}, {'id': 20736, 'synset': 'spirea.n.01', 'name': 'spirea'}, {'id': 20737, 'synset': 'bergenia.n.01', 'name': 'bergenia'}, {'id': 20738, 'synset': 'coast_boykinia.n.01', 'name': 'coast_boykinia'}, {'id': 20739, 'synset': 'golden_saxifrage.n.01', 'name': 'golden_saxifrage'}, {'id': 20740, 'synset': 'umbrella_plant.n.01', 'name': 'umbrella_plant'}, {'id': 20741, 'synset': 'bridal_wreath.n.01', 'name': 'bridal_wreath'}, {'id': 20742, 'synset': 'alumroot.n.01', 'name': 'alumroot'}, {'id': 20743, 'synset': 'coralbells.n.01', 'name': 'coralbells'}, {'id': 20744, 'synset': 'leatherleaf_saxifrage.n.01', 'name': 'leatherleaf_saxifrage'}, {'id': 20745, 'synset': 'woodland_star.n.01', 'name': 'woodland_star'}, {'id': 20746, 'synset': 'prairie_star.n.01', 'name': 'prairie_star'}, {'id': 20747, 'synset': 'miterwort.n.01', 'name': 'miterwort'}, {'id': 20748, 'synset': "five-point_bishop's_cap.n.01", 'name': "five-point_bishop's_cap"}, {'id': 20749, 'synset': 'parnassia.n.01', 'name': 'parnassia'}, {'id': 20750, 'synset': 'bog_star.n.01', 'name': 'bog_star'}, {'id': 20751, 'synset': 'fringed_grass_of_parnassus.n.01', 'name': 'fringed_grass_of_Parnassus'}, {'id': 20752, 'synset': 'false_alumroot.n.01', 'name': 'false_alumroot'}, {'id': 20753, 'synset': 'foamflower.n.01', 'name': 'foamflower'}, {'id': 20754, 'synset': 'false_miterwort.n.01', 'name': 'false_miterwort'}, {'id': 20755, 'synset': 'pickaback_plant.n.01', 'name': 'pickaback_plant'}, {'id': 20756, 'synset': 'currant.n.02', 'name': 'currant'}, {'id': 20757, 'synset': 'black_currant.n.01', 'name': 'black_currant'}, {'id': 20758, 'synset': 'white_currant.n.01', 'name': 'white_currant'}, {'id': 20759, 'synset': 'gooseberry.n.01', 'name': 'gooseberry'}, {'id': 20760, 'synset': 'plane_tree.n.01', 'name': 'plane_tree'}, {'id': 20761, 'synset': 'london_plane.n.01', 'name': 'London_plane'}, {'id': 20762, 'synset': 'american_sycamore.n.01', 'name': 'American_sycamore'}, {'id': 20763, 'synset': 'oriental_plane.n.01', 'name': 'oriental_plane'}, {'id': 20764, 'synset': 'california_sycamore.n.01', 'name': 'California_sycamore'}, {'id': 20765, 'synset': 'arizona_sycamore.n.01', 'name': 'Arizona_sycamore'}, {'id': 20766, 'synset': 'greek_valerian.n.01', 'name': 'Greek_valerian'}, {'id': 20767, 'synset': "northern_jacob's_ladder.n.01", 'name': "northern_Jacob's_ladder"}, {'id': 20768, 'synset': 'skunkweed.n.01', 'name': 'skunkweed'}, {'id': 20769, 'synset': 'phlox.n.01', 'name': 'phlox'}, {'id': 20770, 'synset': 'moss_pink.n.02', 'name': 'moss_pink'}, {'id': 20771, 'synset': 'evening-snow.n.01', 'name': 'evening-snow'}, {'id': 20772, 'synset': 'acanthus.n.01', 'name': 'acanthus'}, {'id': 20773, 'synset': "bear's_breech.n.01", 'name': "bear's_breech"}, {'id': 20774, 'synset': 'caricature_plant.n.01', 'name': 'caricature_plant'}, {'id': 20775, 'synset': 'black-eyed_susan.n.01', 'name': 'black-eyed_Susan'}, {'id': 20776, 'synset': 'catalpa.n.01', 'name': 'catalpa'}, {'id': 20777, 'synset': 'catalpa_bignioides.n.01', 'name': 'Catalpa_bignioides'}, {'id': 20778, 'synset': 'catalpa_speciosa.n.01', 'name': 'Catalpa_speciosa'}, {'id': 20779, 'synset': 'desert_willow.n.01', 'name': 'desert_willow'}, {'id': 20780, 'synset': 'calabash.n.02', 'name': 'calabash'}, {'id': 20781, 'synset': 'calabash.n.01', 'name': 'calabash'}, {'id': 20782, 'synset': 'borage.n.01', 'name': 'borage'}, {'id': 20783, 'synset': 'common_amsinckia.n.01', 'name': 'common_amsinckia'}, {'id': 20784, 'synset': 'anchusa.n.01', 'name': 'anchusa'}, {'id': 20785, 'synset': 'bugloss.n.01', 'name': 'bugloss'}, {'id': 20786, 'synset': 'cape_forget-me-not.n.02', 'name': 'cape_forget-me-not'}, {'id': 20787, 'synset': 'cape_forget-me-not.n.01', 'name': 'cape_forget-me-not'}, {'id': 20788, 'synset': 'spanish_elm.n.02', 'name': 'Spanish_elm'}, {'id': 20789, 'synset': 'princewood.n.01', 'name': 'princewood'}, {'id': 20790, 'synset': 'chinese_forget-me-not.n.01', 'name': 'Chinese_forget-me-not'}, {'id': 20791, 'synset': "hound's-tongue.n.02", 'name': "hound's-tongue"}, {'id': 20792, 'synset': "hound's-tongue.n.01", 'name': "hound's-tongue"}, {'id': 20793, 'synset': 'blueweed.n.01', 'name': 'blueweed'}, {'id': 20794, 'synset': "beggar's_lice.n.01", 'name': "beggar's_lice"}, {'id': 20795, 'synset': 'gromwell.n.01', 'name': 'gromwell'}, {'id': 20796, 'synset': 'puccoon.n.01', 'name': 'puccoon'}, {'id': 20797, 'synset': 'virginia_bluebell.n.01', 'name': 'Virginia_bluebell'}, {'id': 20798, 'synset': 'garden_forget-me-not.n.01', 'name': 'garden_forget-me-not'}, {'id': 20799, 'synset': 'forget-me-not.n.01', 'name': 'forget-me-not'}, {'id': 20800, 'synset': 'false_gromwell.n.01', 'name': 'false_gromwell'}, {'id': 20801, 'synset': 'comfrey.n.01', 'name': 'comfrey'}, {'id': 20802, 'synset': 'common_comfrey.n.01', 'name': 'common_comfrey'}, {'id': 20803, 'synset': 'convolvulus.n.01', 'name': 'convolvulus'}, {'id': 20804, 'synset': 'bindweed.n.01', 'name': 'bindweed'}, {'id': 20805, 'synset': 'field_bindweed.n.01', 'name': 'field_bindweed'}, {'id': 20806, 'synset': 'scammony.n.03', 'name': 'scammony'}, {'id': 20807, 'synset': 'silverweed.n.01', 'name': 'silverweed'}, {'id': 20808, 'synset': 'dodder.n.01', 'name': 'dodder'}, {'id': 20809, 'synset': 'dichondra.n.01', 'name': 'dichondra'}, {'id': 20810, 'synset': 'cypress_vine.n.01', 'name': 'cypress_vine'}, {'id': 20811, 'synset': 'moonflower.n.01', 'name': 'moonflower'}, {'id': 20812, 'synset': 'wild_potato_vine.n.01', 'name': 'wild_potato_vine'}, {'id': 20813, 'synset': 'red_morning-glory.n.01', 'name': 'red_morning-glory'}, {'id': 20814, 'synset': 'man-of-the-earth.n.01', 'name': 'man-of-the-earth'}, {'id': 20815, 'synset': 'scammony.n.01', 'name': 'scammony'}, {'id': 20816, 'synset': 'japanese_morning_glory.n.01', 'name': 'Japanese_morning_glory'}, {'id': 20817, 'synset': 'imperial_japanese_morning_glory.n.01', 'name': 'imperial_Japanese_morning_glory'}, {'id': 20818, 'synset': 'gesneriad.n.01', 'name': 'gesneriad'}, {'id': 20819, 'synset': 'gesneria.n.01', 'name': 'gesneria'}, {'id': 20820, 'synset': 'achimenes.n.01', 'name': 'achimenes'}, {'id': 20821, 'synset': 'aeschynanthus.n.01', 'name': 'aeschynanthus'}, {'id': 20822, 'synset': 'lace-flower_vine.n.01', 'name': 'lace-flower_vine'}, {'id': 20823, 'synset': 'columnea.n.01', 'name': 'columnea'}, {'id': 20824, 'synset': 'episcia.n.01', 'name': 'episcia'}, {'id': 20825, 'synset': 'gloxinia.n.01', 'name': 'gloxinia'}, {'id': 20826, 'synset': 'canterbury_bell.n.01', 'name': 'Canterbury_bell'}, {'id': 20827, 'synset': 'kohleria.n.01', 'name': 'kohleria'}, {'id': 20828, 'synset': 'african_violet.n.01', 'name': 'African_violet'}, {'id': 20829, 'synset': 'streptocarpus.n.01', 'name': 'streptocarpus'}, {'id': 20830, 'synset': 'cape_primrose.n.01', 'name': 'Cape_primrose'}, {'id': 20831, 'synset': 'waterleaf.n.01', 'name': 'waterleaf'}, {'id': 20832, 'synset': 'virginia_waterleaf.n.01', 'name': 'Virginia_waterleaf'}, {'id': 20833, 'synset': 'yellow_bells.n.01', 'name': 'yellow_bells'}, {'id': 20834, 'synset': 'yerba_santa.n.01', 'name': 'yerba_santa'}, {'id': 20835, 'synset': 'nemophila.n.01', 'name': 'nemophila'}, {'id': 20836, 'synset': 'baby_blue-eyes.n.01', 'name': 'baby_blue-eyes'}, {'id': 20837, 'synset': 'five-spot.n.02', 'name': 'five-spot'}, {'id': 20838, 'synset': 'scorpionweed.n.01', 'name': 'scorpionweed'}, {'id': 20839, 'synset': 'california_bluebell.n.02', 'name': 'California_bluebell'}, {'id': 20840, 'synset': 'california_bluebell.n.01', 'name': 'California_bluebell'}, {'id': 20841, 'synset': 'fiddleneck.n.01', 'name': 'fiddleneck'}, {'id': 20842, 'synset': 'fiesta_flower.n.01', 'name': 'fiesta_flower'}, {'id': 20843, 'synset': 'basil_thyme.n.01', 'name': 'basil_thyme'}, {'id': 20844, 'synset': 'giant_hyssop.n.01', 'name': 'giant_hyssop'}, {'id': 20845, 'synset': 'yellow_giant_hyssop.n.01', 'name': 'yellow_giant_hyssop'}, {'id': 20846, 'synset': 'anise_hyssop.n.01', 'name': 'anise_hyssop'}, {'id': 20847, 'synset': 'mexican_hyssop.n.01', 'name': 'Mexican_hyssop'}, {'id': 20848, 'synset': 'bugle.n.02', 'name': 'bugle'}, {'id': 20849, 'synset': 'creeping_bugle.n.01', 'name': 'creeping_bugle'}, {'id': 20850, 'synset': 'erect_bugle.n.01', 'name': 'erect_bugle'}, {'id': 20851, 'synset': 'pyramid_bugle.n.01', 'name': 'pyramid_bugle'}, {'id': 20852, 'synset': 'wood_mint.n.01', 'name': 'wood_mint'}, {'id': 20853, 'synset': 'hairy_wood_mint.n.01', 'name': 'hairy_wood_mint'}, {'id': 20854, 'synset': 'downy_wood_mint.n.01', 'name': 'downy_wood_mint'}, {'id': 20855, 'synset': 'calamint.n.01', 'name': 'calamint'}, {'id': 20856, 'synset': 'common_calamint.n.01', 'name': 'common_calamint'}, {'id': 20857, 'synset': 'large-flowered_calamint.n.01', 'name': 'large-flowered_calamint'}, {'id': 20858, 'synset': 'lesser_calamint.n.01', 'name': 'lesser_calamint'}, {'id': 20859, 'synset': 'wild_basil.n.01', 'name': 'wild_basil'}, {'id': 20860, 'synset': 'horse_balm.n.01', 'name': 'horse_balm'}, {'id': 20861, 'synset': 'coleus.n.01', 'name': 'coleus'}, {'id': 20862, 'synset': 'country_borage.n.01', 'name': 'country_borage'}, {'id': 20863, 'synset': 'painted_nettle.n.01', 'name': 'painted_nettle'}, {'id': 20864, 'synset': 'apalachicola_rosemary.n.01', 'name': 'Apalachicola_rosemary'}, {'id': 20865, 'synset': 'dragonhead.n.01', 'name': 'dragonhead'}, {'id': 20866, 'synset': 'elsholtzia.n.01', 'name': 'elsholtzia'}, {'id': 20867, 'synset': 'hemp_nettle.n.01', 'name': 'hemp_nettle'}, {'id': 20868, 'synset': 'ground_ivy.n.01', 'name': 'ground_ivy'}, {'id': 20869, 'synset': 'pennyroyal.n.02', 'name': 'pennyroyal'}, {'id': 20870, 'synset': 'hyssop.n.01', 'name': 'hyssop'}, {'id': 20871, 'synset': 'dead_nettle.n.02', 'name': 'dead_nettle'}, {'id': 20872, 'synset': 'white_dead_nettle.n.01', 'name': 'white_dead_nettle'}, {'id': 20873, 'synset': 'henbit.n.01', 'name': 'henbit'}, {'id': 20874, 'synset': 'english_lavender.n.01', 'name': 'English_lavender'}, {'id': 20875, 'synset': 'french_lavender.n.02', 'name': 'French_lavender'}, {'id': 20876, 'synset': 'spike_lavender.n.01', 'name': 'spike_lavender'}, {'id': 20877, 'synset': 'dagga.n.01', 'name': 'dagga'}, {'id': 20878, 'synset': "lion's-ear.n.01", 'name': "lion's-ear"}, {'id': 20879, 'synset': 'motherwort.n.01', 'name': 'motherwort'}, {'id': 20880, 'synset': 'pitcher_sage.n.02', 'name': 'pitcher_sage'}, {'id': 20881, 'synset': 'bugleweed.n.01', 'name': 'bugleweed'}, {'id': 20882, 'synset': 'water_horehound.n.01', 'name': 'water_horehound'}, {'id': 20883, 'synset': 'gipsywort.n.01', 'name': 'gipsywort'}, {'id': 20884, 'synset': 'origanum.n.01', 'name': 'origanum'}, {'id': 20885, 'synset': 'oregano.n.01', 'name': 'oregano'}, {'id': 20886, 'synset': 'sweet_marjoram.n.01', 'name': 'sweet_marjoram'}, {'id': 20887, 'synset': 'horehound.n.01', 'name': 'horehound'}, {'id': 20888, 'synset': 'common_horehound.n.01', 'name': 'common_horehound'}, {'id': 20889, 'synset': 'lemon_balm.n.01', 'name': 'lemon_balm'}, {'id': 20890, 'synset': 'corn_mint.n.01', 'name': 'corn_mint'}, {'id': 20891, 'synset': 'water-mint.n.01', 'name': 'water-mint'}, {'id': 20892, 'synset': 'bergamot_mint.n.02', 'name': 'bergamot_mint'}, {'id': 20893, 'synset': 'horsemint.n.03', 'name': 'horsemint'}, {'id': 20894, 'synset': 'peppermint.n.01', 'name': 'peppermint'}, {'id': 20895, 'synset': 'spearmint.n.01', 'name': 'spearmint'}, {'id': 20896, 'synset': 'apple_mint.n.01', 'name': 'apple_mint'}, {'id': 20897, 'synset': 'pennyroyal.n.01', 'name': 'pennyroyal'}, {'id': 20898, 'synset': 'yerba_buena.n.01', 'name': 'yerba_buena'}, {'id': 20899, 'synset': 'molucca_balm.n.01', 'name': 'molucca_balm'}, {'id': 20900, 'synset': 'monarda.n.01', 'name': 'monarda'}, {'id': 20901, 'synset': 'bee_balm.n.02', 'name': 'bee_balm'}, {'id': 20902, 'synset': 'horsemint.n.02', 'name': 'horsemint'}, {'id': 20903, 'synset': 'bee_balm.n.01', 'name': 'bee_balm'}, {'id': 20904, 'synset': 'lemon_mint.n.01', 'name': 'lemon_mint'}, {'id': 20905, 'synset': 'plains_lemon_monarda.n.01', 'name': 'plains_lemon_monarda'}, {'id': 20906, 'synset': 'basil_balm.n.01', 'name': 'basil_balm'}, {'id': 20907, 'synset': 'mustang_mint.n.01', 'name': 'mustang_mint'}, {'id': 20908, 'synset': 'catmint.n.01', 'name': 'catmint'}, {'id': 20909, 'synset': 'basil.n.01', 'name': 'basil'}, {'id': 20910, 'synset': 'beefsteak_plant.n.01', 'name': 'beefsteak_plant'}, {'id': 20911, 'synset': 'phlomis.n.01', 'name': 'phlomis'}, {'id': 20912, 'synset': 'jerusalem_sage.n.01', 'name': 'Jerusalem_sage'}, {'id': 20913, 'synset': 'physostegia.n.01', 'name': 'physostegia'}, {'id': 20914, 'synset': 'plectranthus.n.01', 'name': 'plectranthus'}, {'id': 20915, 'synset': 'patchouli.n.01', 'name': 'patchouli'}, {'id': 20916, 'synset': 'self-heal.n.01', 'name': 'self-heal'}, {'id': 20917, 'synset': 'mountain_mint.n.01', 'name': 'mountain_mint'}, {'id': 20918, 'synset': 'rosemary.n.01', 'name': 'rosemary'}, {'id': 20919, 'synset': 'clary_sage.n.01', 'name': 'clary_sage'}, {'id': 20920, 'synset': 'purple_sage.n.01', 'name': 'purple_sage'}, {'id': 20921, 'synset': 'cancerweed.n.01', 'name': 'cancerweed'}, {'id': 20922, 'synset': 'common_sage.n.01', 'name': 'common_sage'}, {'id': 20923, 'synset': 'meadow_clary.n.01', 'name': 'meadow_clary'}, {'id': 20924, 'synset': 'clary.n.01', 'name': 'clary'}, {'id': 20925, 'synset': 'pitcher_sage.n.01', 'name': 'pitcher_sage'}, {'id': 20926, 'synset': 'mexican_mint.n.01', 'name': 'Mexican_mint'}, {'id': 20927, 'synset': 'wild_sage.n.01', 'name': 'wild_sage'}, {'id': 20928, 'synset': 'savory.n.01', 'name': 'savory'}, {'id': 20929, 'synset': 'summer_savory.n.01', 'name': 'summer_savory'}, {'id': 20930, 'synset': 'winter_savory.n.01', 'name': 'winter_savory'}, {'id': 20931, 'synset': 'skullcap.n.02', 'name': 'skullcap'}, {'id': 20932, 'synset': 'blue_pimpernel.n.01', 'name': 'blue_pimpernel'}, {'id': 20933, 'synset': 'hedge_nettle.n.02', 'name': 'hedge_nettle'}, {'id': 20934, 'synset': 'hedge_nettle.n.01', 'name': 'hedge_nettle'}, {'id': 20935, 'synset': 'germander.n.01', 'name': 'germander'}, {'id': 20936, 'synset': 'american_germander.n.01', 'name': 'American_germander'}, {'id': 20937, 'synset': 'cat_thyme.n.01', 'name': 'cat_thyme'}, {'id': 20938, 'synset': 'wood_sage.n.01', 'name': 'wood_sage'}, {'id': 20939, 'synset': 'thyme.n.01', 'name': 'thyme'}, {'id': 20940, 'synset': 'common_thyme.n.01', 'name': 'common_thyme'}, {'id': 20941, 'synset': 'wild_thyme.n.01', 'name': 'wild_thyme'}, {'id': 20942, 'synset': 'blue_curls.n.01', 'name': 'blue_curls'}, {'id': 20943, 'synset': 'turpentine_camphor_weed.n.01', 'name': 'turpentine_camphor_weed'}, {'id': 20944, 'synset': 'bastard_pennyroyal.n.01', 'name': 'bastard_pennyroyal'}, {'id': 20945, 'synset': 'bladderwort.n.01', 'name': 'bladderwort'}, {'id': 20946, 'synset': 'butterwort.n.01', 'name': 'butterwort'}, {'id': 20947, 'synset': 'genlisea.n.01', 'name': 'genlisea'}, {'id': 20948, 'synset': 'martynia.n.01', 'name': 'martynia'}, {'id': 20949, 'synset': 'common_unicorn_plant.n.01', 'name': 'common_unicorn_plant'}, {'id': 20950, 'synset': "sand_devil's_claw.n.01", 'name': "sand_devil's_claw"}, {'id': 20951, 'synset': 'sweet_unicorn_plant.n.01', 'name': 'sweet_unicorn_plant'}, {'id': 20952, 'synset': 'figwort.n.01', 'name': 'figwort'}, {'id': 20953, 'synset': 'snapdragon.n.01', 'name': 'snapdragon'}, {'id': 20954, 'synset': 'white_snapdragon.n.01', 'name': 'white_snapdragon'}, {'id': 20955, 'synset': 'yellow_twining_snapdragon.n.01', 'name': 'yellow_twining_snapdragon'}, {'id': 20956, 'synset': 'mediterranean_snapdragon.n.01', 'name': 'Mediterranean_snapdragon'}, {'id': 20957, 'synset': 'kitten-tails.n.01', 'name': 'kitten-tails'}, {'id': 20958, 'synset': 'alpine_besseya.n.01', 'name': 'Alpine_besseya'}, {'id': 20959, 'synset': 'false_foxglove.n.02', 'name': 'false_foxglove'}, {'id': 20960, 'synset': 'false_foxglove.n.01', 'name': 'false_foxglove'}, {'id': 20961, 'synset': 'calceolaria.n.01', 'name': 'calceolaria'}, {'id': 20962, 'synset': 'indian_paintbrush.n.02', 'name': 'Indian_paintbrush'}, {'id': 20963, 'synset': 'desert_paintbrush.n.01', 'name': 'desert_paintbrush'}, {'id': 20964, 'synset': 'giant_red_paintbrush.n.01', 'name': 'giant_red_paintbrush'}, {'id': 20965, 'synset': 'great_plains_paintbrush.n.01', 'name': 'great_plains_paintbrush'}, {'id': 20966, 'synset': 'sulfur_paintbrush.n.01', 'name': 'sulfur_paintbrush'}, {'id': 20967, 'synset': 'shellflower.n.01', 'name': 'shellflower'}, {'id': 20968, 'synset': 'maiden_blue-eyed_mary.n.01', 'name': 'maiden_blue-eyed_Mary'}, {'id': 20969, 'synset': 'blue-eyed_mary.n.01', 'name': 'blue-eyed_Mary'}, {'id': 20970, 'synset': 'foxglove.n.01', 'name': 'foxglove'}, {'id': 20971, 'synset': 'common_foxglove.n.01', 'name': 'common_foxglove'}, {'id': 20972, 'synset': 'yellow_foxglove.n.01', 'name': 'yellow_foxglove'}, {'id': 20973, 'synset': 'gerardia.n.01', 'name': 'gerardia'}, {'id': 20974, 'synset': 'blue_toadflax.n.01', 'name': 'blue_toadflax'}, {'id': 20975, 'synset': 'toadflax.n.01', 'name': 'toadflax'}, {'id': 20976, 'synset': 'golden-beard_penstemon.n.01', 'name': 'golden-beard_penstemon'}, {'id': 20977, 'synset': 'scarlet_bugler.n.01', 'name': 'scarlet_bugler'}, {'id': 20978, 'synset': 'red_shrubby_penstemon.n.01', 'name': 'red_shrubby_penstemon'}, {'id': 20979, 'synset': 'platte_river_penstemon.n.01', 'name': 'Platte_River_penstemon'}, {'id': 20980, 'synset': 'hot-rock_penstemon.n.01', 'name': 'hot-rock_penstemon'}, {'id': 20981, 'synset': "jones'_penstemon.n.01", 'name': "Jones'_penstemon"}, {'id': 20982, 'synset': 'shrubby_penstemon.n.01', 'name': 'shrubby_penstemon'}, {'id': 20983, 'synset': 'narrow-leaf_penstemon.n.01', 'name': 'narrow-leaf_penstemon'}, {'id': 20984, 'synset': 'balloon_flower.n.01', 'name': 'balloon_flower'}, {'id': 20985, 'synset': "parry's_penstemon.n.01", 'name': "Parry's_penstemon"}, {'id': 20986, 'synset': 'rock_penstemon.n.01', 'name': 'rock_penstemon'}, {'id': 20987, 'synset': "rydberg's_penstemon.n.01", 'name': "Rydberg's_penstemon"}, {'id': 20988, 'synset': 'cascade_penstemon.n.01', 'name': 'cascade_penstemon'}, {'id': 20989, 'synset': "whipple's_penstemon.n.01", 'name': "Whipple's_penstemon"}, {'id': 20990, 'synset': 'moth_mullein.n.01', 'name': 'moth_mullein'}, {'id': 20991, 'synset': 'white_mullein.n.01', 'name': 'white_mullein'}, {'id': 20992, 'synset': 'purple_mullein.n.01', 'name': 'purple_mullein'}, {'id': 20993, 'synset': 'common_mullein.n.01', 'name': 'common_mullein'}, {'id': 20994, 'synset': 'veronica.n.01', 'name': 'veronica'}, {'id': 20995, 'synset': 'field_speedwell.n.01', 'name': 'field_speedwell'}, {'id': 20996, 'synset': 'brooklime.n.02', 'name': 'brooklime'}, {'id': 20997, 'synset': 'corn_speedwell.n.01', 'name': 'corn_speedwell'}, {'id': 20998, 'synset': 'brooklime.n.01', 'name': 'brooklime'}, {'id': 20999, 'synset': 'germander_speedwell.n.01', 'name': 'germander_speedwell'}, {'id': 21000, 'synset': 'water_speedwell.n.01', 'name': 'water_speedwell'}, {'id': 21001, 'synset': 'common_speedwell.n.01', 'name': 'common_speedwell'}, {'id': 21002, 'synset': 'purslane_speedwell.n.01', 'name': 'purslane_speedwell'}, {'id': 21003, 'synset': 'thyme-leaved_speedwell.n.01', 'name': 'thyme-leaved_speedwell'}, {'id': 21004, 'synset': 'nightshade.n.01', 'name': 'nightshade'}, {'id': 21005, 'synset': 'horse_nettle.n.01', 'name': 'horse_nettle'}, {'id': 21006, 'synset': 'african_holly.n.01', 'name': 'African_holly'}, {'id': 21007, 'synset': 'potato_vine.n.02', 'name': 'potato_vine'}, {'id': 21008, 'synset': 'garden_huckleberry.n.01', 'name': 'garden_huckleberry'}, {'id': 21009, 'synset': 'naranjilla.n.01', 'name': 'naranjilla'}, {'id': 21010, 'synset': 'potato_vine.n.01', 'name': 'potato_vine'}, {'id': 21011, 'synset': 'potato_tree.n.01', 'name': 'potato_tree'}, {'id': 21012, 'synset': 'belladonna.n.01', 'name': 'belladonna'}, {'id': 21013, 'synset': 'bush_violet.n.01', 'name': 'bush_violet'}, {'id': 21014, 'synset': 'lady-of-the-night.n.01', 'name': 'lady-of-the-night'}, {'id': 21015, 'synset': "angel's_trumpet.n.02", 'name': "angel's_trumpet"}, {'id': 21016, 'synset': "angel's_trumpet.n.01", 'name': "angel's_trumpet"}, {'id': 21017, 'synset': "red_angel's_trumpet.n.01", 'name': "red_angel's_trumpet"}, {'id': 21018, 'synset': 'cone_pepper.n.01', 'name': 'cone_pepper'}, {'id': 21019, 'synset': 'bird_pepper.n.01', 'name': 'bird_pepper'}, {'id': 21020, 'synset': 'day_jessamine.n.01', 'name': 'day_jessamine'}, {'id': 21021, 'synset': 'night_jasmine.n.01', 'name': 'night_jasmine'}, {'id': 21022, 'synset': 'tree_tomato.n.01', 'name': 'tree_tomato'}, {'id': 21023, 'synset': 'thorn_apple.n.01', 'name': 'thorn_apple'}, {'id': 21024, 'synset': 'jimsonweed.n.01', 'name': 'jimsonweed'}, {'id': 21025, 'synset': 'pichi.n.01', 'name': 'pichi'}, {'id': 21026, 'synset': 'henbane.n.01', 'name': 'henbane'}, {'id': 21027, 'synset': 'egyptian_henbane.n.01', 'name': 'Egyptian_henbane'}, {'id': 21028, 'synset': 'matrimony_vine.n.01', 'name': 'matrimony_vine'}, {'id': 21029, 'synset': 'common_matrimony_vine.n.01', 'name': 'common_matrimony_vine'}, {'id': 21030, 'synset': 'christmasberry.n.01', 'name': 'Christmasberry'}, {'id': 21031, 'synset': 'plum_tomato.n.01', 'name': 'plum_tomato'}, {'id': 21032, 'synset': 'mandrake.n.02', 'name': 'mandrake'}, {'id': 21033, 'synset': 'mandrake_root.n.01', 'name': 'mandrake_root'}, {'id': 21034, 'synset': 'apple_of_peru.n.01', 'name': 'apple_of_Peru'}, {'id': 21035, 'synset': 'flowering_tobacco.n.01', 'name': 'flowering_tobacco'}, {'id': 21036, 'synset': 'common_tobacco.n.01', 'name': 'common_tobacco'}, {'id': 21037, 'synset': 'wild_tobacco.n.01', 'name': 'wild_tobacco'}, {'id': 21038, 'synset': 'cupflower.n.02', 'name': 'cupflower'}, {'id': 21039, 'synset': 'whitecup.n.01', 'name': 'whitecup'}, {'id': 21040, 'synset': 'petunia.n.01', 'name': 'petunia'}, {'id': 21041, 'synset': 'large_white_petunia.n.01', 'name': 'large_white_petunia'}, {'id': 21042, 'synset': 'violet-flowered_petunia.n.01', 'name': 'violet-flowered_petunia'}, {'id': 21043, 'synset': 'hybrid_petunia.n.01', 'name': 'hybrid_petunia'}, {'id': 21044, 'synset': 'cape_gooseberry.n.01', 'name': 'cape_gooseberry'}, {'id': 21045, 'synset': 'strawberry_tomato.n.01', 'name': 'strawberry_tomato'}, {'id': 21046, 'synset': 'tomatillo.n.02', 'name': 'tomatillo'}, {'id': 21047, 'synset': 'tomatillo.n.01', 'name': 'tomatillo'}, {'id': 21048, 'synset': 'yellow_henbane.n.01', 'name': 'yellow_henbane'}, {'id': 21049, 'synset': "cock's_eggs.n.01", 'name': "cock's_eggs"}, {'id': 21050, 'synset': 'salpiglossis.n.01', 'name': 'salpiglossis'}, {'id': 21051, 'synset': 'painted_tongue.n.01', 'name': 'painted_tongue'}, {'id': 21052, 'synset': 'butterfly_flower.n.01', 'name': 'butterfly_flower'}, {'id': 21053, 'synset': 'scopolia_carniolica.n.01', 'name': 'Scopolia_carniolica'}, {'id': 21054, 'synset': 'chalice_vine.n.01', 'name': 'chalice_vine'}, {'id': 21055, 'synset': 'verbena.n.01', 'name': 'verbena'}, {'id': 21056, 'synset': 'lantana.n.01', 'name': 'lantana'}, {'id': 21057, 'synset': 'black_mangrove.n.02', 'name': 'black_mangrove'}, {'id': 21058, 'synset': 'white_mangrove.n.01', 'name': 'white_mangrove'}, {'id': 21059, 'synset': 'black_mangrove.n.01', 'name': 'black_mangrove'}, {'id': 21060, 'synset': 'teak.n.02', 'name': 'teak'}, {'id': 21061, 'synset': 'spurge.n.01', 'name': 'spurge'}, {'id': 21062, 'synset': 'sun_spurge.n.01', 'name': 'sun_spurge'}, {'id': 21063, 'synset': 'petty_spurge.n.01', 'name': 'petty_spurge'}, {'id': 21064, 'synset': "medusa's_head.n.01", 'name': "medusa's_head"}, {'id': 21065, 'synset': 'wild_spurge.n.01', 'name': 'wild_spurge'}, {'id': 21066, 'synset': 'snow-on-the-mountain.n.01', 'name': 'snow-on-the-mountain'}, {'id': 21067, 'synset': 'cypress_spurge.n.01', 'name': 'cypress_spurge'}, {'id': 21068, 'synset': 'leafy_spurge.n.01', 'name': 'leafy_spurge'}, {'id': 21069, 'synset': 'hairy_spurge.n.01', 'name': 'hairy_spurge'}, {'id': 21070, 'synset': 'poinsettia.n.01', 'name': 'poinsettia'}, {'id': 21071, 'synset': 'japanese_poinsettia.n.01', 'name': 'Japanese_poinsettia'}, {'id': 21072, 'synset': 'fire-on-the-mountain.n.01', 'name': 'fire-on-the-mountain'}, {'id': 21073, 'synset': 'wood_spurge.n.01', 'name': 'wood_spurge'}, {'id': 21074, 'synset': 'dwarf_spurge.n.01', 'name': 'dwarf_spurge'}, {'id': 21075, 'synset': 'scarlet_plume.n.01', 'name': 'scarlet_plume'}, {'id': 21076, 'synset': 'naboom.n.01', 'name': 'naboom'}, {'id': 21077, 'synset': 'crown_of_thorns.n.02', 'name': 'crown_of_thorns'}, {'id': 21078, 'synset': 'toothed_spurge.n.01', 'name': 'toothed_spurge'}, {'id': 21079, 'synset': 'three-seeded_mercury.n.01', 'name': 'three-seeded_mercury'}, {'id': 21080, 'synset': 'croton.n.02', 'name': 'croton'}, {'id': 21081, 'synset': 'cascarilla.n.01', 'name': 'cascarilla'}, {'id': 21082, 'synset': 'cascarilla_bark.n.01', 'name': 'cascarilla_bark'}, {'id': 21083, 'synset': 'castor-oil_plant.n.01', 'name': 'castor-oil_plant'}, {'id': 21084, 'synset': 'spurge_nettle.n.01', 'name': 'spurge_nettle'}, {'id': 21085, 'synset': 'physic_nut.n.01', 'name': 'physic_nut'}, {'id': 21086, 'synset': 'para_rubber_tree.n.01', 'name': 'Para_rubber_tree'}, {'id': 21087, 'synset': 'cassava.n.03', 'name': 'cassava'}, {'id': 21088, 'synset': 'bitter_cassava.n.01', 'name': 'bitter_cassava'}, {'id': 21089, 'synset': 'cassava.n.02', 'name': 'cassava'}, {'id': 21090, 'synset': 'sweet_cassava.n.01', 'name': 'sweet_cassava'}, {'id': 21091, 'synset': 'candlenut.n.01', 'name': 'candlenut'}, {'id': 21092, 'synset': 'tung_tree.n.01', 'name': 'tung_tree'}, {'id': 21093, 'synset': 'slipper_spurge.n.01', 'name': 'slipper_spurge'}, {'id': 21094, 'synset': 'candelilla.n.01', 'name': 'candelilla'}, {'id': 21095, 'synset': 'jewbush.n.01', 'name': 'Jewbush'}, {'id': 21096, 'synset': 'jumping_bean.n.01', 'name': 'jumping_bean'}, {'id': 21097, 'synset': 'camellia.n.01', 'name': 'camellia'}, {'id': 21098, 'synset': 'japonica.n.01', 'name': 'japonica'}, {'id': 21099, 'synset': 'umbellifer.n.01', 'name': 'umbellifer'}, {'id': 21100, 'synset': 'wild_parsley.n.01', 'name': 'wild_parsley'}, {'id': 21101, 'synset': "fool's_parsley.n.01", 'name': "fool's_parsley"}, {'id': 21102, 'synset': 'dill.n.01', 'name': 'dill'}, {'id': 21103, 'synset': 'angelica.n.01', 'name': 'angelica'}, {'id': 21104, 'synset': 'garden_angelica.n.01', 'name': 'garden_angelica'}, {'id': 21105, 'synset': 'wild_angelica.n.01', 'name': 'wild_angelica'}, {'id': 21106, 'synset': 'chervil.n.01', 'name': 'chervil'}, {'id': 21107, 'synset': 'cow_parsley.n.01', 'name': 'cow_parsley'}, {'id': 21108, 'synset': 'wild_celery.n.01', 'name': 'wild_celery'}, {'id': 21109, 'synset': 'astrantia.n.01', 'name': 'astrantia'}, {'id': 21110, 'synset': 'greater_masterwort.n.01', 'name': 'greater_masterwort'}, {'id': 21111, 'synset': 'caraway.n.01', 'name': 'caraway'}, {'id': 21112, 'synset': 'whorled_caraway.n.01', 'name': 'whorled_caraway'}, {'id': 21113, 'synset': 'water_hemlock.n.01', 'name': 'water_hemlock'}, {'id': 21114, 'synset': 'spotted_cowbane.n.01', 'name': 'spotted_cowbane'}, {'id': 21115, 'synset': 'hemlock.n.02', 'name': 'hemlock'}, {'id': 21116, 'synset': 'earthnut.n.02', 'name': 'earthnut'}, {'id': 21117, 'synset': 'cumin.n.01', 'name': 'cumin'}, {'id': 21118, 'synset': 'wild_carrot.n.01', 'name': 'wild_carrot'}, {'id': 21119, 'synset': 'eryngo.n.01', 'name': 'eryngo'}, {'id': 21120, 'synset': 'sea_holly.n.01', 'name': 'sea_holly'}, {'id': 21121, 'synset': 'button_snakeroot.n.02', 'name': 'button_snakeroot'}, {'id': 21122, 'synset': 'rattlesnake_master.n.01', 'name': 'rattlesnake_master'}, {'id': 21123, 'synset': 'fennel.n.01', 'name': 'fennel'}, {'id': 21124, 'synset': 'common_fennel.n.01', 'name': 'common_fennel'}, {'id': 21125, 'synset': 'florence_fennel.n.01', 'name': 'Florence_fennel'}, {'id': 21126, 'synset': 'cow_parsnip.n.01', 'name': 'cow_parsnip'}, {'id': 21127, 'synset': 'lovage.n.01', 'name': 'lovage'}, {'id': 21128, 'synset': 'sweet_cicely.n.01', 'name': 'sweet_cicely'}, {'id': 21129, 'synset': 'water_fennel.n.01', 'name': 'water_fennel'}, {'id': 21130, 'synset': 'parsnip.n.02', 'name': 'parsnip'}, {'id': 21131, 'synset': 'cultivated_parsnip.n.01', 'name': 'cultivated_parsnip'}, {'id': 21132, 'synset': 'wild_parsnip.n.01', 'name': 'wild_parsnip'}, {'id': 21133, 'synset': 'parsley.n.01', 'name': 'parsley'}, {'id': 21134, 'synset': 'italian_parsley.n.01', 'name': 'Italian_parsley'}, {'id': 21135, 'synset': 'hamburg_parsley.n.01', 'name': 'Hamburg_parsley'}, {'id': 21136, 'synset': 'anise.n.01', 'name': 'anise'}, {'id': 21137, 'synset': 'sanicle.n.01', 'name': 'sanicle'}, {'id': 21138, 'synset': 'purple_sanicle.n.01', 'name': 'purple_sanicle'}, {'id': 21139, 'synset': 'european_sanicle.n.01', 'name': 'European_sanicle'}, {'id': 21140, 'synset': 'water_parsnip.n.01', 'name': 'water_parsnip'}, {'id': 21141, 'synset': 'greater_water_parsnip.n.01', 'name': 'greater_water_parsnip'}, {'id': 21142, 'synset': 'skirret.n.01', 'name': 'skirret'}, {'id': 21143, 'synset': 'dogwood.n.01', 'name': 'dogwood'}, {'id': 21144, 'synset': 'common_white_dogwood.n.01', 'name': 'common_white_dogwood'}, {'id': 21145, 'synset': 'red_osier.n.01', 'name': 'red_osier'}, {'id': 21146, 'synset': 'silky_dogwood.n.02', 'name': 'silky_dogwood'}, {'id': 21147, 'synset': 'silky_cornel.n.01', 'name': 'silky_cornel'}, {'id': 21148, 'synset': 'common_european_dogwood.n.01', 'name': 'common_European_dogwood'}, {'id': 21149, 'synset': 'bunchberry.n.01', 'name': 'bunchberry'}, {'id': 21150, 'synset': 'cornelian_cherry.n.01', 'name': 'cornelian_cherry'}, {'id': 21151, 'synset': 'puka.n.01', 'name': 'puka'}, {'id': 21152, 'synset': 'kapuka.n.01', 'name': 'kapuka'}, {'id': 21153, 'synset': 'valerian.n.01', 'name': 'valerian'}, {'id': 21154, 'synset': 'common_valerian.n.01', 'name': 'common_valerian'}, {'id': 21155, 'synset': 'common_corn_salad.n.01', 'name': 'common_corn_salad'}, {'id': 21156, 'synset': 'red_valerian.n.01', 'name': 'red_valerian'}, {'id': 21157, 'synset': 'filmy_fern.n.02', 'name': 'filmy_fern'}, {'id': 21158, 'synset': 'bristle_fern.n.01', 'name': 'bristle_fern'}, {'id': 21159, 'synset': "hare's-foot_bristle_fern.n.01", 'name': "hare's-foot_bristle_fern"}, {'id': 21160, 'synset': 'killarney_fern.n.01', 'name': 'Killarney_fern'}, {'id': 21161, 'synset': 'kidney_fern.n.01', 'name': 'kidney_fern'}, {'id': 21162, 'synset': 'flowering_fern.n.02', 'name': 'flowering_fern'}, {'id': 21163, 'synset': 'royal_fern.n.01', 'name': 'royal_fern'}, {'id': 21164, 'synset': 'interrupted_fern.n.01', 'name': 'interrupted_fern'}, {'id': 21165, 'synset': 'crape_fern.n.01', 'name': 'crape_fern'}, {'id': 21166, 'synset': 'crepe_fern.n.01', 'name': 'crepe_fern'}, {'id': 21167, 'synset': 'curly_grass.n.01', 'name': 'curly_grass'}, {'id': 21168, 'synset': 'pine_fern.n.01', 'name': 'pine_fern'}, {'id': 21169, 'synset': 'climbing_fern.n.01', 'name': 'climbing_fern'}, {'id': 21170, 'synset': 'creeping_fern.n.01', 'name': 'creeping_fern'}, {'id': 21171, 'synset': 'climbing_maidenhair.n.01', 'name': 'climbing_maidenhair'}, {'id': 21172, 'synset': 'scented_fern.n.02', 'name': 'scented_fern'}, {'id': 21173, 'synset': 'clover_fern.n.01', 'name': 'clover_fern'}, {'id': 21174, 'synset': 'nardoo.n.01', 'name': 'nardoo'}, {'id': 21175, 'synset': 'water_clover.n.01', 'name': 'water_clover'}, {'id': 21176, 'synset': 'pillwort.n.01', 'name': 'pillwort'}, {'id': 21177, 'synset': 'regnellidium.n.01', 'name': 'regnellidium'}, {'id': 21178, 'synset': 'floating-moss.n.01', 'name': 'floating-moss'}, {'id': 21179, 'synset': 'mosquito_fern.n.01', 'name': 'mosquito_fern'}, {'id': 21180, 'synset': "adder's_tongue.n.01", 'name': "adder's_tongue"}, {'id': 21181, 'synset': 'ribbon_fern.n.03', 'name': 'ribbon_fern'}, {'id': 21182, 'synset': 'grape_fern.n.01', 'name': 'grape_fern'}, {'id': 21183, 'synset': 'daisyleaf_grape_fern.n.01', 'name': 'daisyleaf_grape_fern'}, {'id': 21184, 'synset': 'leathery_grape_fern.n.01', 'name': 'leathery_grape_fern'}, {'id': 21185, 'synset': 'rattlesnake_fern.n.01', 'name': 'rattlesnake_fern'}, {'id': 21186, 'synset': 'flowering_fern.n.01', 'name': 'flowering_fern'}, {'id': 21187, 'synset': 'powdery_mildew.n.01', 'name': 'powdery_mildew'}, {'id': 21188, 'synset': 'dutch_elm_fungus.n.01', 'name': 'Dutch_elm_fungus'}, {'id': 21189, 'synset': 'ergot.n.02', 'name': 'ergot'}, {'id': 21190, 'synset': 'rye_ergot.n.01', 'name': 'rye_ergot'}, {'id': 21191, 'synset': 'black_root_rot_fungus.n.01', 'name': 'black_root_rot_fungus'}, {'id': 21192, 'synset': "dead-man's-fingers.n.01", 'name': "dead-man's-fingers"}, {'id': 21193, 'synset': 'sclerotinia.n.01', 'name': 'sclerotinia'}, {'id': 21194, 'synset': 'brown_cup.n.01', 'name': 'brown_cup'}, {'id': 21195, 'synset': 'earthball.n.01', 'name': 'earthball'}, {'id': 21196, 'synset': 'scleroderma_citrinum.n.01', 'name': 'Scleroderma_citrinum'}, {'id': 21197, 'synset': 'scleroderma_flavidium.n.01', 'name': 'Scleroderma_flavidium'}, {'id': 21198, 'synset': 'scleroderma_bovista.n.01', 'name': 'Scleroderma_bovista'}, {'id': 21199, 'synset': 'podaxaceae.n.01', 'name': 'Podaxaceae'}, {'id': 21200, 'synset': 'stalked_puffball.n.02', 'name': 'stalked_puffball'}, {'id': 21201, 'synset': 'stalked_puffball.n.01', 'name': 'stalked_puffball'}, {'id': 21202, 'synset': 'false_truffle.n.01', 'name': 'false_truffle'}, {'id': 21203, 'synset': 'rhizopogon_idahoensis.n.01', 'name': 'Rhizopogon_idahoensis'}, {'id': 21204, 'synset': 'truncocolumella_citrina.n.01', 'name': 'Truncocolumella_citrina'}, {'id': 21205, 'synset': 'mucor.n.01', 'name': 'mucor'}, {'id': 21206, 'synset': 'rhizopus.n.01', 'name': 'rhizopus'}, {'id': 21207, 'synset': 'bread_mold.n.01', 'name': 'bread_mold'}, {'id': 21208, 'synset': 'slime_mold.n.01', 'name': 'slime_mold'}, {'id': 21209, 'synset': 'true_slime_mold.n.01', 'name': 'true_slime_mold'}, {'id': 21210, 'synset': 'cellular_slime_mold.n.01', 'name': 'cellular_slime_mold'}, {'id': 21211, 'synset': 'dictostylium.n.01', 'name': 'dictostylium'}, {'id': 21212, 'synset': 'pond-scum_parasite.n.01', 'name': 'pond-scum_parasite'}, {'id': 21213, 'synset': 'potato_wart_fungus.n.01', 'name': 'potato_wart_fungus'}, {'id': 21214, 'synset': 'white_fungus.n.01', 'name': 'white_fungus'}, {'id': 21215, 'synset': 'water_mold.n.01', 'name': 'water_mold'}, {'id': 21216, 'synset': 'downy_mildew.n.01', 'name': 'downy_mildew'}, {'id': 21217, 'synset': 'blue_mold_fungus.n.01', 'name': 'blue_mold_fungus'}, {'id': 21218, 'synset': 'onion_mildew.n.01', 'name': 'onion_mildew'}, {'id': 21219, 'synset': 'tobacco_mildew.n.01', 'name': 'tobacco_mildew'}, {'id': 21220, 'synset': 'white_rust.n.01', 'name': 'white_rust'}, {'id': 21221, 'synset': 'pythium.n.01', 'name': 'pythium'}, {'id': 21222, 'synset': 'damping_off_fungus.n.01', 'name': 'damping_off_fungus'}, {'id': 21223, 'synset': 'phytophthora_citrophthora.n.01', 'name': 'Phytophthora_citrophthora'}, {'id': 21224, 'synset': 'phytophthora_infestans.n.01', 'name': 'Phytophthora_infestans'}, {'id': 21225, 'synset': 'clubroot_fungus.n.01', 'name': 'clubroot_fungus'}, {'id': 21226, 'synset': 'geglossaceae.n.01', 'name': 'Geglossaceae'}, {'id': 21227, 'synset': 'sarcosomataceae.n.01', 'name': 'Sarcosomataceae'}, {'id': 21228, 'synset': 'rufous_rubber_cup.n.01', 'name': 'Rufous_rubber_cup'}, {'id': 21229, 'synset': "devil's_cigar.n.01", 'name': "devil's_cigar"}, {'id': 21230, 'synset': "devil's_urn.n.01", 'name': "devil's_urn"}, {'id': 21231, 'synset': 'truffle.n.01', 'name': 'truffle'}, {'id': 21232, 'synset': 'club_fungus.n.01', 'name': 'club_fungus'}, {'id': 21233, 'synset': 'coral_fungus.n.01', 'name': 'coral_fungus'}, {'id': 21234, 'synset': 'tooth_fungus.n.01', 'name': 'tooth_fungus'}, {'id': 21235, 'synset': 'lichen.n.02', 'name': 'lichen'}, {'id': 21236, 'synset': 'ascolichen.n.01', 'name': 'ascolichen'}, {'id': 21237, 'synset': 'basidiolichen.n.01', 'name': 'basidiolichen'}, {'id': 21238, 'synset': 'lecanora.n.01', 'name': 'lecanora'}, {'id': 21239, 'synset': 'manna_lichen.n.01', 'name': 'manna_lichen'}, {'id': 21240, 'synset': 'archil.n.02', 'name': 'archil'}, {'id': 21241, 'synset': 'roccella.n.01', 'name': 'roccella'}, {'id': 21242, 'synset': 'beard_lichen.n.01', 'name': 'beard_lichen'}, {'id': 21243, 'synset': 'horsehair_lichen.n.01', 'name': 'horsehair_lichen'}, {'id': 21244, 'synset': 'reindeer_moss.n.01', 'name': 'reindeer_moss'}, {'id': 21245, 'synset': 'crottle.n.01', 'name': 'crottle'}, {'id': 21246, 'synset': 'iceland_moss.n.01', 'name': 'Iceland_moss'}, {'id': 21247, 'synset': 'fungus.n.01', 'name': 'fungus'}, {'id': 21248, 'synset': 'promycelium.n.01', 'name': 'promycelium'}, {'id': 21249, 'synset': 'true_fungus.n.01', 'name': 'true_fungus'}, {'id': 21250, 'synset': 'basidiomycete.n.01', 'name': 'basidiomycete'}, {'id': 21251, 'synset': 'mushroom.n.03', 'name': 'mushroom'}, {'id': 21252, 'synset': 'agaric.n.02', 'name': 'agaric'}, {'id': 21253, 'synset': 'mushroom.n.01', 'name': 'mushroom'}, {'id': 21254, 'synset': 'toadstool.n.01', 'name': 'toadstool'}, {'id': 21255, 'synset': 'horse_mushroom.n.01', 'name': 'horse_mushroom'}, {'id': 21256, 'synset': 'meadow_mushroom.n.01', 'name': 'meadow_mushroom'}, {'id': 21257, 'synset': 'shiitake.n.01', 'name': 'shiitake'}, {'id': 21258, 'synset': 'scaly_lentinus.n.01', 'name': 'scaly_lentinus'}, {'id': 21259, 'synset': 'royal_agaric.n.01', 'name': 'royal_agaric'}, {'id': 21260, 'synset': 'false_deathcap.n.01', 'name': 'false_deathcap'}, {'id': 21261, 'synset': 'fly_agaric.n.01', 'name': 'fly_agaric'}, {'id': 21262, 'synset': 'death_cap.n.01', 'name': 'death_cap'}, {'id': 21263, 'synset': 'blushing_mushroom.n.01', 'name': 'blushing_mushroom'}, {'id': 21264, 'synset': 'destroying_angel.n.01', 'name': 'destroying_angel'}, {'id': 21265, 'synset': 'chanterelle.n.01', 'name': 'chanterelle'}, {'id': 21266, 'synset': 'floccose_chanterelle.n.01', 'name': 'floccose_chanterelle'}, {'id': 21267, 'synset': "pig's_ears.n.01", 'name': "pig's_ears"}, {'id': 21268, 'synset': 'cinnabar_chanterelle.n.01', 'name': 'cinnabar_chanterelle'}, {'id': 21269, 'synset': 'jack-o-lantern_fungus.n.01', 'name': 'jack-o-lantern_fungus'}, {'id': 21270, 'synset': 'inky_cap.n.01', 'name': 'inky_cap'}, {'id': 21271, 'synset': 'shaggymane.n.01', 'name': 'shaggymane'}, {'id': 21272, 'synset': 'milkcap.n.01', 'name': 'milkcap'}, {'id': 21273, 'synset': 'fairy-ring_mushroom.n.01', 'name': 'fairy-ring_mushroom'}, {'id': 21274, 'synset': 'fairy_ring.n.01', 'name': 'fairy_ring'}, {'id': 21275, 'synset': 'oyster_mushroom.n.01', 'name': 'oyster_mushroom'}, {'id': 21276, 'synset': 'olive-tree_agaric.n.01', 'name': 'olive-tree_agaric'}, {'id': 21277, 'synset': 'pholiota_astragalina.n.01', 'name': 'Pholiota_astragalina'}, {'id': 21278, 'synset': 'pholiota_aurea.n.01', 'name': 'Pholiota_aurea'}, {'id': 21279, 'synset': 'pholiota_destruens.n.01', 'name': 'Pholiota_destruens'}, {'id': 21280, 'synset': 'pholiota_flammans.n.01', 'name': 'Pholiota_flammans'}, {'id': 21281, 'synset': 'pholiota_flavida.n.01', 'name': 'Pholiota_flavida'}, {'id': 21282, 'synset': 'nameko.n.01', 'name': 'nameko'}, {'id': 21283, 'synset': 'pholiota_squarrosa-adiposa.n.01', 'name': 'Pholiota_squarrosa-adiposa'}, {'id': 21284, 'synset': 'pholiota_squarrosa.n.01', 'name': 'Pholiota_squarrosa'}, {'id': 21285, 'synset': 'pholiota_squarrosoides.n.01', 'name': 'Pholiota_squarrosoides'}, {'id': 21286, 'synset': 'stropharia_ambigua.n.01', 'name': 'Stropharia_ambigua'}, {'id': 21287, 'synset': 'stropharia_hornemannii.n.01', 'name': 'Stropharia_hornemannii'}, {'id': 21288, 'synset': 'stropharia_rugoso-annulata.n.01', 'name': 'Stropharia_rugoso-annulata'}, {'id': 21289, 'synset': 'gill_fungus.n.01', 'name': 'gill_fungus'}, {'id': 21290, 'synset': 'entoloma_lividum.n.01', 'name': 'Entoloma_lividum'}, {'id': 21291, 'synset': 'entoloma_aprile.n.01', 'name': 'Entoloma_aprile'}, {'id': 21292, 'synset': 'chlorophyllum_molybdites.n.01', 'name': 'Chlorophyllum_molybdites'}, {'id': 21293, 'synset': 'lepiota.n.01', 'name': 'lepiota'}, {'id': 21294, 'synset': 'parasol_mushroom.n.01', 'name': 'parasol_mushroom'}, {'id': 21295, 'synset': 'poisonous_parasol.n.01', 'name': 'poisonous_parasol'}, {'id': 21296, 'synset': 'lepiota_naucina.n.01', 'name': 'Lepiota_naucina'}, {'id': 21297, 'synset': 'lepiota_rhacodes.n.01', 'name': 'Lepiota_rhacodes'}, {'id': 21298, 'synset': 'american_parasol.n.01', 'name': 'American_parasol'}, {'id': 21299, 'synset': 'lepiota_rubrotincta.n.01', 'name': 'Lepiota_rubrotincta'}, {'id': 21300, 'synset': 'lepiota_clypeolaria.n.01', 'name': 'Lepiota_clypeolaria'}, {'id': 21301, 'synset': 'onion_stem.n.01', 'name': 'onion_stem'}, {'id': 21302, 'synset': 'pink_disease_fungus.n.01', 'name': 'pink_disease_fungus'}, {'id': 21303, 'synset': 'bottom_rot_fungus.n.01', 'name': 'bottom_rot_fungus'}, {'id': 21304, 'synset': 'potato_fungus.n.01', 'name': 'potato_fungus'}, {'id': 21305, 'synset': 'coffee_fungus.n.01', 'name': 'coffee_fungus'}, {'id': 21306, 'synset': 'blewits.n.01', 'name': 'blewits'}, {'id': 21307, 'synset': 'sandy_mushroom.n.01', 'name': 'sandy_mushroom'}, {'id': 21308, 'synset': 'tricholoma_pessundatum.n.01', 'name': 'Tricholoma_pessundatum'}, {'id': 21309, 'synset': 'tricholoma_sejunctum.n.01', 'name': 'Tricholoma_sejunctum'}, {'id': 21310, 'synset': 'man-on-a-horse.n.01', 'name': 'man-on-a-horse'}, {'id': 21311, 'synset': 'tricholoma_venenata.n.01', 'name': 'Tricholoma_venenata'}, {'id': 21312, 'synset': 'tricholoma_pardinum.n.01', 'name': 'Tricholoma_pardinum'}, {'id': 21313, 'synset': 'tricholoma_vaccinum.n.01', 'name': 'Tricholoma_vaccinum'}, {'id': 21314, 'synset': 'tricholoma_aurantium.n.01', 'name': 'Tricholoma_aurantium'}, {'id': 21315, 'synset': 'volvaria_bombycina.n.01', 'name': 'Volvaria_bombycina'}, {'id': 21316, 'synset': 'pluteus_aurantiorugosus.n.01', 'name': 'Pluteus_aurantiorugosus'}, {'id': 21317, 'synset': 'pluteus_magnus.n.01', 'name': 'Pluteus_magnus'}, {'id': 21318, 'synset': 'deer_mushroom.n.01', 'name': 'deer_mushroom'}, {'id': 21319, 'synset': 'straw_mushroom.n.01', 'name': 'straw_mushroom'}, {'id': 21320, 'synset': 'volvariella_bombycina.n.01', 'name': 'Volvariella_bombycina'}, {'id': 21321, 'synset': 'clitocybe_clavipes.n.01', 'name': 'Clitocybe_clavipes'}, {'id': 21322, 'synset': 'clitocybe_dealbata.n.01', 'name': 'Clitocybe_dealbata'}, {'id': 21323, 'synset': 'clitocybe_inornata.n.01', 'name': 'Clitocybe_inornata'}, {'id': 21324, 'synset': 'clitocybe_robusta.n.01', 'name': 'Clitocybe_robusta'}, {'id': 21325, 'synset': 'clitocybe_irina.n.01', 'name': 'Clitocybe_irina'}, {'id': 21326, 'synset': 'clitocybe_subconnexa.n.01', 'name': 'Clitocybe_subconnexa'}, {'id': 21327, 'synset': 'winter_mushroom.n.01', 'name': 'winter_mushroom'}, {'id': 21328, 'synset': 'mycelium.n.01', 'name': 'mycelium'}, {'id': 21329, 'synset': 'sclerotium.n.02', 'name': 'sclerotium'}, {'id': 21330, 'synset': 'sac_fungus.n.01', 'name': 'sac_fungus'}, {'id': 21331, 'synset': 'ascomycete.n.01', 'name': 'ascomycete'}, {'id': 21332, 'synset': 'clavicipitaceae.n.01', 'name': 'Clavicipitaceae'}, {'id': 21333, 'synset': 'grainy_club.n.01', 'name': 'grainy_club'}, {'id': 21334, 'synset': 'yeast.n.02', 'name': 'yeast'}, {'id': 21335, 'synset': "baker's_yeast.n.01", 'name': "baker's_yeast"}, {'id': 21336, 'synset': "wine-maker's_yeast.n.01", 'name': "wine-maker's_yeast"}, {'id': 21337, 'synset': 'aspergillus_fumigatus.n.01', 'name': 'Aspergillus_fumigatus'}, {'id': 21338, 'synset': 'brown_root_rot_fungus.n.01', 'name': 'brown_root_rot_fungus'}, {'id': 21339, 'synset': 'discomycete.n.01', 'name': 'discomycete'}, {'id': 21340, 'synset': 'leotia_lubrica.n.01', 'name': 'Leotia_lubrica'}, {'id': 21341, 'synset': 'mitrula_elegans.n.01', 'name': 'Mitrula_elegans'}, {'id': 21342, 'synset': 'sarcoscypha_coccinea.n.01', 'name': 'Sarcoscypha_coccinea'}, {'id': 21343, 'synset': 'caloscypha_fulgens.n.01', 'name': 'Caloscypha_fulgens'}, {'id': 21344, 'synset': 'aleuria_aurantia.n.01', 'name': 'Aleuria_aurantia'}, {'id': 21345, 'synset': 'elf_cup.n.01', 'name': 'elf_cup'}, {'id': 21346, 'synset': 'peziza_domicilina.n.01', 'name': 'Peziza_domicilina'}, {'id': 21347, 'synset': 'blood_cup.n.01', 'name': 'blood_cup'}, {'id': 21348, 'synset': 'urnula_craterium.n.01', 'name': 'Urnula_craterium'}, {'id': 21349, 'synset': 'galiella_rufa.n.01', 'name': 'Galiella_rufa'}, {'id': 21350, 'synset': 'jafnea_semitosta.n.01', 'name': 'Jafnea_semitosta'}, {'id': 21351, 'synset': 'morel.n.01', 'name': 'morel'}, {'id': 21352, 'synset': 'common_morel.n.01', 'name': 'common_morel'}, {'id': 21353, 'synset': 'disciotis_venosa.n.01', 'name': 'Disciotis_venosa'}, {'id': 21354, 'synset': 'verpa.n.01', 'name': 'Verpa'}, {'id': 21355, 'synset': 'verpa_bohemica.n.01', 'name': 'Verpa_bohemica'}, {'id': 21356, 'synset': 'verpa_conica.n.01', 'name': 'Verpa_conica'}, {'id': 21357, 'synset': 'black_morel.n.01', 'name': 'black_morel'}, {'id': 21358, 'synset': 'morchella_crassipes.n.01', 'name': 'Morchella_crassipes'}, {'id': 21359, 'synset': 'morchella_semilibera.n.01', 'name': 'Morchella_semilibera'}, {'id': 21360, 'synset': 'wynnea_americana.n.01', 'name': 'Wynnea_americana'}, {'id': 21361, 'synset': 'wynnea_sparassoides.n.01', 'name': 'Wynnea_sparassoides'}, {'id': 21362, 'synset': 'false_morel.n.01', 'name': 'false_morel'}, {'id': 21363, 'synset': 'lorchel.n.01', 'name': 'lorchel'}, {'id': 21364, 'synset': 'helvella.n.01', 'name': 'helvella'}, {'id': 21365, 'synset': 'helvella_crispa.n.01', 'name': 'Helvella_crispa'}, {'id': 21366, 'synset': 'helvella_acetabulum.n.01', 'name': 'Helvella_acetabulum'}, {'id': 21367, 'synset': 'helvella_sulcata.n.01', 'name': 'Helvella_sulcata'}, {'id': 21368, 'synset': 'discina.n.01', 'name': 'discina'}, {'id': 21369, 'synset': 'gyromitra.n.01', 'name': 'gyromitra'}, {'id': 21370, 'synset': 'gyromitra_californica.n.01', 'name': 'Gyromitra_californica'}, {'id': 21371, 'synset': 'gyromitra_sphaerospora.n.01', 'name': 'Gyromitra_sphaerospora'}, {'id': 21372, 'synset': 'gyromitra_esculenta.n.01', 'name': 'Gyromitra_esculenta'}, {'id': 21373, 'synset': 'gyromitra_infula.n.01', 'name': 'Gyromitra_infula'}, {'id': 21374, 'synset': 'gyromitra_fastigiata.n.01', 'name': 'Gyromitra_fastigiata'}, {'id': 21375, 'synset': 'gyromitra_gigas.n.01', 'name': 'Gyromitra_gigas'}, {'id': 21376, 'synset': 'gasteromycete.n.01', 'name': 'gasteromycete'}, {'id': 21377, 'synset': 'stinkhorn.n.01', 'name': 'stinkhorn'}, {'id': 21378, 'synset': 'common_stinkhorn.n.01', 'name': 'common_stinkhorn'}, {'id': 21379, 'synset': 'phallus_ravenelii.n.01', 'name': 'Phallus_ravenelii'}, {'id': 21380, 'synset': 'dog_stinkhorn.n.01', 'name': 'dog_stinkhorn'}, {'id': 21381, 'synset': 'calostoma_lutescens.n.01', 'name': 'Calostoma_lutescens'}, {'id': 21382, 'synset': 'calostoma_cinnabarina.n.01', 'name': 'Calostoma_cinnabarina'}, {'id': 21383, 'synset': 'calostoma_ravenelii.n.01', 'name': 'Calostoma_ravenelii'}, {'id': 21384, 'synset': 'stinky_squid.n.01', 'name': 'stinky_squid'}, {'id': 21385, 'synset': 'puffball.n.01', 'name': 'puffball'}, {'id': 21386, 'synset': 'giant_puffball.n.01', 'name': 'giant_puffball'}, {'id': 21387, 'synset': 'earthstar.n.01', 'name': 'earthstar'}, {'id': 21388, 'synset': 'geastrum_coronatum.n.01', 'name': 'Geastrum_coronatum'}, {'id': 21389, 'synset': 'radiigera_fuscogleba.n.01', 'name': 'Radiigera_fuscogleba'}, {'id': 21390, 'synset': 'astreus_pteridis.n.01', 'name': 'Astreus_pteridis'}, {'id': 21391, 'synset': 'astreus_hygrometricus.n.01', 'name': 'Astreus_hygrometricus'}, {'id': 21392, 'synset': "bird's-nest_fungus.n.01", 'name': "bird's-nest_fungus"}, {'id': 21393, 'synset': 'gastrocybe_lateritia.n.01', 'name': 'Gastrocybe_lateritia'}, {'id': 21394, 'synset': 'macowanites_americanus.n.01', 'name': 'Macowanites_americanus'}, {'id': 21395, 'synset': 'polypore.n.01', 'name': 'polypore'}, {'id': 21396, 'synset': 'bracket_fungus.n.01', 'name': 'bracket_fungus'}, {'id': 21397, 'synset': 'albatrellus_dispansus.n.01', 'name': 'Albatrellus_dispansus'}, {'id': 21398, 'synset': 'albatrellus_ovinus.n.01', 'name': 'Albatrellus_ovinus'}, {'id': 21399, 'synset': 'neolentinus_ponderosus.n.01', 'name': 'Neolentinus_ponderosus'}, {'id': 21400, 'synset': 'oligoporus_leucospongia.n.01', 'name': 'Oligoporus_leucospongia'}, {'id': 21401, 'synset': 'polyporus_tenuiculus.n.01', 'name': 'Polyporus_tenuiculus'}, {'id': 21402, 'synset': 'hen-of-the-woods.n.01', 'name': 'hen-of-the-woods'}, {'id': 21403, 'synset': 'polyporus_squamosus.n.01', 'name': 'Polyporus_squamosus'}, {'id': 21404, 'synset': 'beefsteak_fungus.n.01', 'name': 'beefsteak_fungus'}, {'id': 21405, 'synset': 'agaric.n.01', 'name': 'agaric'}, {'id': 21406, 'synset': 'bolete.n.01', 'name': 'bolete'}, {'id': 21407, 'synset': 'boletus_chrysenteron.n.01', 'name': 'Boletus_chrysenteron'}, {'id': 21408, 'synset': 'boletus_edulis.n.01', 'name': 'Boletus_edulis'}, {'id': 21409, 'synset': "frost's_bolete.n.01", 'name': "Frost's_bolete"}, {'id': 21410, 'synset': 'boletus_luridus.n.01', 'name': 'Boletus_luridus'}, {'id': 21411, 'synset': 'boletus_mirabilis.n.01', 'name': 'Boletus_mirabilis'}, {'id': 21412, 'synset': 'boletus_pallidus.n.01', 'name': 'Boletus_pallidus'}, {'id': 21413, 'synset': 'boletus_pulcherrimus.n.01', 'name': 'Boletus_pulcherrimus'}, {'id': 21414, 'synset': 'boletus_pulverulentus.n.01', 'name': 'Boletus_pulverulentus'}, {'id': 21415, 'synset': 'boletus_roxanae.n.01', 'name': 'Boletus_roxanae'}, {'id': 21416, 'synset': 'boletus_subvelutipes.n.01', 'name': 'Boletus_subvelutipes'}, {'id': 21417, 'synset': 'boletus_variipes.n.01', 'name': 'Boletus_variipes'}, {'id': 21418, 'synset': 'boletus_zelleri.n.01', 'name': 'Boletus_zelleri'}, {'id': 21419, 'synset': 'fuscoboletinus_paluster.n.01', 'name': 'Fuscoboletinus_paluster'}, {'id': 21420, 'synset': 'fuscoboletinus_serotinus.n.01', 'name': 'Fuscoboletinus_serotinus'}, {'id': 21421, 'synset': 'leccinum_fibrillosum.n.01', 'name': 'Leccinum_fibrillosum'}, {'id': 21422, 'synset': 'suillus_albivelatus.n.01', 'name': 'Suillus_albivelatus'}, {'id': 21423, 'synset': 'old-man-of-the-woods.n.01', 'name': 'old-man-of-the-woods'}, {'id': 21424, 'synset': 'boletellus_russellii.n.01', 'name': 'Boletellus_russellii'}, {'id': 21425, 'synset': 'jelly_fungus.n.01', 'name': 'jelly_fungus'}, {'id': 21426, 'synset': 'snow_mushroom.n.01', 'name': 'snow_mushroom'}, {'id': 21427, 'synset': "witches'_butter.n.01", 'name': "witches'_butter"}, {'id': 21428, 'synset': 'tremella_foliacea.n.01', 'name': 'Tremella_foliacea'}, {'id': 21429, 'synset': 'tremella_reticulata.n.01', 'name': 'Tremella_reticulata'}, {'id': 21430, 'synset': "jew's-ear.n.01", 'name': "Jew's-ear"}, {'id': 21431, 'synset': 'rust.n.04', 'name': 'rust'}, {'id': 21432, 'synset': 'aecium.n.01', 'name': 'aecium'}, {'id': 21433, 'synset': 'flax_rust.n.01', 'name': 'flax_rust'}, {'id': 21434, 'synset': 'blister_rust.n.02', 'name': 'blister_rust'}, {'id': 21435, 'synset': 'wheat_rust.n.01', 'name': 'wheat_rust'}, {'id': 21436, 'synset': 'apple_rust.n.01', 'name': 'apple_rust'}, {'id': 21437, 'synset': 'smut.n.03', 'name': 'smut'}, {'id': 21438, 'synset': 'covered_smut.n.01', 'name': 'covered_smut'}, {'id': 21439, 'synset': 'loose_smut.n.02', 'name': 'loose_smut'}, {'id': 21440, 'synset': 'cornsmut.n.01', 'name': 'cornsmut'}, {'id': 21441, 'synset': 'boil_smut.n.01', 'name': 'boil_smut'}, {'id': 21442, 'synset': 'sphacelotheca.n.01', 'name': 'Sphacelotheca'}, {'id': 21443, 'synset': 'head_smut.n.01', 'name': 'head_smut'}, {'id': 21444, 'synset': 'bunt.n.04', 'name': 'bunt'}, {'id': 21445, 'synset': 'bunt.n.03', 'name': 'bunt'}, {'id': 21446, 'synset': 'onion_smut.n.01', 'name': 'onion_smut'}, {'id': 21447, 'synset': 'flag_smut_fungus.n.01', 'name': 'flag_smut_fungus'}, {'id': 21448, 'synset': 'wheat_flag_smut.n.01', 'name': 'wheat_flag_smut'}, {'id': 21449, 'synset': 'felt_fungus.n.01', 'name': 'felt_fungus'}, {'id': 21450, 'synset': 'waxycap.n.01', 'name': 'waxycap'}, {'id': 21451, 'synset': 'hygrocybe_acutoconica.n.01', 'name': 'Hygrocybe_acutoconica'}, {'id': 21452, 'synset': 'hygrophorus_borealis.n.01', 'name': 'Hygrophorus_borealis'}, {'id': 21453, 'synset': 'hygrophorus_caeruleus.n.01', 'name': 'Hygrophorus_caeruleus'}, {'id': 21454, 'synset': 'hygrophorus_inocybiformis.n.01', 'name': 'Hygrophorus_inocybiformis'}, {'id': 21455, 'synset': 'hygrophorus_kauffmanii.n.01', 'name': 'Hygrophorus_kauffmanii'}, {'id': 21456, 'synset': 'hygrophorus_marzuolus.n.01', 'name': 'Hygrophorus_marzuolus'}, {'id': 21457, 'synset': 'hygrophorus_purpurascens.n.01', 'name': 'Hygrophorus_purpurascens'}, {'id': 21458, 'synset': 'hygrophorus_russula.n.01', 'name': 'Hygrophorus_russula'}, {'id': 21459, 'synset': 'hygrophorus_sordidus.n.01', 'name': 'Hygrophorus_sordidus'}, {'id': 21460, 'synset': 'hygrophorus_tennesseensis.n.01', 'name': 'Hygrophorus_tennesseensis'}, {'id': 21461, 'synset': 'hygrophorus_turundus.n.01', 'name': 'Hygrophorus_turundus'}, {'id': 21462, 'synset': 'neohygrophorus_angelesianus.n.01', 'name': 'Neohygrophorus_angelesianus'}, {'id': 21463, 'synset': 'cortinarius_armillatus.n.01', 'name': 'Cortinarius_armillatus'}, {'id': 21464, 'synset': 'cortinarius_atkinsonianus.n.01', 'name': 'Cortinarius_atkinsonianus'}, {'id': 21465, 'synset': 'cortinarius_corrugatus.n.01', 'name': 'Cortinarius_corrugatus'}, {'id': 21466, 'synset': 'cortinarius_gentilis.n.01', 'name': 'Cortinarius_gentilis'}, {'id': 21467, 'synset': 'cortinarius_mutabilis.n.01', 'name': 'Cortinarius_mutabilis'}, {'id': 21468, 'synset': 'cortinarius_semisanguineus.n.01', 'name': 'Cortinarius_semisanguineus'}, {'id': 21469, 'synset': 'cortinarius_subfoetidus.n.01', 'name': 'Cortinarius_subfoetidus'}, {'id': 21470, 'synset': 'cortinarius_violaceus.n.01', 'name': 'Cortinarius_violaceus'}, {'id': 21471, 'synset': 'gymnopilus_spectabilis.n.01', 'name': 'Gymnopilus_spectabilis'}, {'id': 21472, 'synset': 'gymnopilus_validipes.n.01', 'name': 'Gymnopilus_validipes'}, {'id': 21473, 'synset': 'gymnopilus_ventricosus.n.01', 'name': 'Gymnopilus_ventricosus'}, {'id': 21474, 'synset': 'mold.n.05', 'name': 'mold'}, {'id': 21475, 'synset': 'mildew.n.02', 'name': 'mildew'}, {'id': 21476, 'synset': 'verticillium.n.01', 'name': 'verticillium'}, {'id': 21477, 'synset': 'monilia.n.01', 'name': 'monilia'}, {'id': 21478, 'synset': 'candida.n.01', 'name': 'candida'}, {'id': 21479, 'synset': 'candida_albicans.n.01', 'name': 'Candida_albicans'}, {'id': 21480, 'synset': 'blastomycete.n.01', 'name': 'blastomycete'}, {'id': 21481, 'synset': 'yellow_spot_fungus.n.01', 'name': 'yellow_spot_fungus'}, {'id': 21482, 'synset': 'green_smut_fungus.n.01', 'name': 'green_smut_fungus'}, {'id': 21483, 'synset': 'dry_rot.n.02', 'name': 'dry_rot'}, {'id': 21484, 'synset': 'rhizoctinia.n.01', 'name': 'rhizoctinia'}, {'id': 21485, 'synset': 'houseplant.n.01', 'name': 'houseplant'}, {'id': 21486, 'synset': 'bedder.n.01', 'name': 'bedder'}, {'id': 21487, 'synset': 'succulent.n.01', 'name': 'succulent'}, {'id': 21488, 'synset': 'cultivar.n.01', 'name': 'cultivar'}, {'id': 21489, 'synset': 'weed.n.01', 'name': 'weed'}, {'id': 21490, 'synset': 'wort.n.01', 'name': 'wort'}, {'id': 21491, 'synset': 'brier.n.02', 'name': 'brier'}, {'id': 21492, 'synset': 'aril.n.01', 'name': 'aril'}, {'id': 21493, 'synset': 'sporophyll.n.01', 'name': 'sporophyll'}, {'id': 21494, 'synset': 'sporangium.n.01', 'name': 'sporangium'}, {'id': 21495, 'synset': 'sporangiophore.n.01', 'name': 'sporangiophore'}, {'id': 21496, 'synset': 'ascus.n.01', 'name': 'ascus'}, {'id': 21497, 'synset': 'ascospore.n.01', 'name': 'ascospore'}, {'id': 21498, 'synset': 'arthrospore.n.02', 'name': 'arthrospore'}, {'id': 21499, 'synset': 'eusporangium.n.01', 'name': 'eusporangium'}, {'id': 21500, 'synset': 'tetrasporangium.n.01', 'name': 'tetrasporangium'}, {'id': 21501, 'synset': 'gametangium.n.01', 'name': 'gametangium'}, {'id': 21502, 'synset': 'sorus.n.02', 'name': 'sorus'}, {'id': 21503, 'synset': 'sorus.n.01', 'name': 'sorus'}, {'id': 21504, 'synset': 'partial_veil.n.01', 'name': 'partial_veil'}, {'id': 21505, 'synset': 'lignum.n.01', 'name': 'lignum'}, {'id': 21506, 'synset': 'vascular_ray.n.01', 'name': 'vascular_ray'}, {'id': 21507, 'synset': 'phloem.n.01', 'name': 'phloem'}, {'id': 21508, 'synset': 'evergreen.n.01', 'name': 'evergreen'}, {'id': 21509, 'synset': 'deciduous_plant.n.01', 'name': 'deciduous_plant'}, {'id': 21510, 'synset': 'poisonous_plant.n.01', 'name': 'poisonous_plant'}, {'id': 21511, 'synset': 'vine.n.01', 'name': 'vine'}, {'id': 21512, 'synset': 'creeper.n.01', 'name': 'creeper'}, {'id': 21513, 'synset': 'tendril.n.01', 'name': 'tendril'}, {'id': 21514, 'synset': 'root_climber.n.01', 'name': 'root_climber'}, {'id': 21515, 'synset': 'lignosae.n.01', 'name': 'lignosae'}, {'id': 21516, 'synset': 'arborescent_plant.n.01', 'name': 'arborescent_plant'}, {'id': 21517, 'synset': 'snag.n.02', 'name': 'snag'}, {'id': 21518, 'synset': 'tree.n.01', 'name': 'tree'}, {'id': 21519, 'synset': 'timber_tree.n.01', 'name': 'timber_tree'}, {'id': 21520, 'synset': 'treelet.n.01', 'name': 'treelet'}, {'id': 21521, 'synset': 'arbor.n.01', 'name': 'arbor'}, {'id': 21522, 'synset': 'bean_tree.n.01', 'name': 'bean_tree'}, {'id': 21523, 'synset': 'pollard.n.01', 'name': 'pollard'}, {'id': 21524, 'synset': 'sapling.n.01', 'name': 'sapling'}, {'id': 21525, 'synset': 'shade_tree.n.01', 'name': 'shade_tree'}, {'id': 21526, 'synset': 'gymnospermous_tree.n.01', 'name': 'gymnospermous_tree'}, {'id': 21527, 'synset': 'conifer.n.01', 'name': 'conifer'}, {'id': 21528, 'synset': 'angiospermous_tree.n.01', 'name': 'angiospermous_tree'}, {'id': 21529, 'synset': 'nut_tree.n.01', 'name': 'nut_tree'}, {'id': 21530, 'synset': 'spice_tree.n.01', 'name': 'spice_tree'}, {'id': 21531, 'synset': 'fever_tree.n.01', 'name': 'fever_tree'}, {'id': 21532, 'synset': 'stump.n.01', 'name': 'stump'}, {'id': 21533, 'synset': 'bonsai.n.01', 'name': 'bonsai'}, {'id': 21534, 'synset': 'ming_tree.n.02', 'name': 'ming_tree'}, {'id': 21535, 'synset': 'ming_tree.n.01', 'name': 'ming_tree'}, {'id': 21536, 'synset': 'undershrub.n.01', 'name': 'undershrub'}, {'id': 21537, 'synset': 'subshrub.n.01', 'name': 'subshrub'}, {'id': 21538, 'synset': 'bramble.n.01', 'name': 'bramble'}, {'id': 21539, 'synset': 'liana.n.01', 'name': 'liana'}, {'id': 21540, 'synset': 'geophyte.n.01', 'name': 'geophyte'}, {'id': 21541, 'synset': 'desert_plant.n.01', 'name': 'desert_plant'}, {'id': 21542, 'synset': 'mesophyte.n.01', 'name': 'mesophyte'}, {'id': 21543, 'synset': 'marsh_plant.n.01', 'name': 'marsh_plant'}, {'id': 21544, 'synset': 'hemiepiphyte.n.01', 'name': 'hemiepiphyte'}, {'id': 21545, 'synset': 'strangler.n.01', 'name': 'strangler'}, {'id': 21546, 'synset': 'lithophyte.n.01', 'name': 'lithophyte'}, {'id': 21547, 'synset': 'saprobe.n.01', 'name': 'saprobe'}, {'id': 21548, 'synset': 'autophyte.n.01', 'name': 'autophyte'}, {'id': 21549, 'synset': 'root.n.01', 'name': 'root'}, {'id': 21550, 'synset': 'taproot.n.01', 'name': 'taproot'}, {'id': 21551, 'synset': 'prop_root.n.01', 'name': 'prop_root'}, {'id': 21552, 'synset': 'prophyll.n.01', 'name': 'prophyll'}, {'id': 21553, 'synset': 'rootstock.n.02', 'name': 'rootstock'}, {'id': 21554, 'synset': 'quickset.n.01', 'name': 'quickset'}, {'id': 21555, 'synset': 'stolon.n.01', 'name': 'stolon'}, {'id': 21556, 'synset': 'tuberous_plant.n.01', 'name': 'tuberous_plant'}, {'id': 21557, 'synset': 'rhizome.n.01', 'name': 'rhizome'}, {'id': 21558, 'synset': 'rachis.n.01', 'name': 'rachis'}, {'id': 21559, 'synset': 'caudex.n.02', 'name': 'caudex'}, {'id': 21560, 'synset': 'cladode.n.01', 'name': 'cladode'}, {'id': 21561, 'synset': 'receptacle.n.02', 'name': 'receptacle'}, {'id': 21562, 'synset': 'scape.n.01', 'name': 'scape'}, {'id': 21563, 'synset': 'umbel.n.01', 'name': 'umbel'}, {'id': 21564, 'synset': 'petiole.n.01', 'name': 'petiole'}, {'id': 21565, 'synset': 'peduncle.n.02', 'name': 'peduncle'}, {'id': 21566, 'synset': 'pedicel.n.01', 'name': 'pedicel'}, {'id': 21567, 'synset': 'flower_cluster.n.01', 'name': 'flower_cluster'}, {'id': 21568, 'synset': 'raceme.n.01', 'name': 'raceme'}, {'id': 21569, 'synset': 'panicle.n.01', 'name': 'panicle'}, {'id': 21570, 'synset': 'thyrse.n.01', 'name': 'thyrse'}, {'id': 21571, 'synset': 'cyme.n.01', 'name': 'cyme'}, {'id': 21572, 'synset': 'cymule.n.01', 'name': 'cymule'}, {'id': 21573, 'synset': 'glomerule.n.01', 'name': 'glomerule'}, {'id': 21574, 'synset': 'scorpioid_cyme.n.01', 'name': 'scorpioid_cyme'}, {'id': 21575, 'synset': 'ear.n.05', 'name': 'ear'}, {'id': 21576, 'synset': 'spadix.n.01', 'name': 'spadix'}, {'id': 21577, 'synset': 'bulbous_plant.n.01', 'name': 'bulbous_plant'}, {'id': 21578, 'synset': 'bulbil.n.01', 'name': 'bulbil'}, {'id': 21579, 'synset': 'cormous_plant.n.01', 'name': 'cormous_plant'}, {'id': 21580, 'synset': 'fruit.n.01', 'name': 'fruit'}, {'id': 21581, 'synset': 'fruitlet.n.01', 'name': 'fruitlet'}, {'id': 21582, 'synset': 'seed.n.01', 'name': 'seed'}, {'id': 21583, 'synset': 'bean.n.02', 'name': 'bean'}, {'id': 21584, 'synset': 'nut.n.01', 'name': 'nut'}, {'id': 21585, 'synset': 'nutlet.n.01', 'name': 'nutlet'}, {'id': 21586, 'synset': 'kernel.n.01', 'name': 'kernel'}, {'id': 21587, 'synset': 'syconium.n.01', 'name': 'syconium'}, {'id': 21588, 'synset': 'berry.n.02', 'name': 'berry'}, {'id': 21589, 'synset': 'aggregate_fruit.n.01', 'name': 'aggregate_fruit'}, {'id': 21590, 'synset': 'simple_fruit.n.01', 'name': 'simple_fruit'}, {'id': 21591, 'synset': 'acinus.n.01', 'name': 'acinus'}, {'id': 21592, 'synset': 'drupe.n.01', 'name': 'drupe'}, {'id': 21593, 'synset': 'drupelet.n.01', 'name': 'drupelet'}, {'id': 21594, 'synset': 'pome.n.01', 'name': 'pome'}, {'id': 21595, 'synset': 'pod.n.02', 'name': 'pod'}, {'id': 21596, 'synset': 'loment.n.01', 'name': 'loment'}, {'id': 21597, 'synset': 'pyxidium.n.01', 'name': 'pyxidium'}, {'id': 21598, 'synset': 'husk.n.02', 'name': 'husk'}, {'id': 21599, 'synset': 'cornhusk.n.01', 'name': 'cornhusk'}, {'id': 21600, 'synset': 'pod.n.01', 'name': 'pod'}, {'id': 21601, 'synset': 'accessory_fruit.n.01', 'name': 'accessory_fruit'}, {'id': 21602, 'synset': 'buckthorn.n.01', 'name': 'buckthorn'}, {'id': 21603, 'synset': 'buckthorn_berry.n.01', 'name': 'buckthorn_berry'}, {'id': 21604, 'synset': 'cascara_buckthorn.n.01', 'name': 'cascara_buckthorn'}, {'id': 21605, 'synset': 'cascara.n.01', 'name': 'cascara'}, {'id': 21606, 'synset': 'carolina_buckthorn.n.01', 'name': 'Carolina_buckthorn'}, {'id': 21607, 'synset': 'coffeeberry.n.01', 'name': 'coffeeberry'}, {'id': 21608, 'synset': 'redberry.n.01', 'name': 'redberry'}, {'id': 21609, 'synset': 'nakedwood.n.01', 'name': 'nakedwood'}, {'id': 21610, 'synset': 'jujube.n.01', 'name': 'jujube'}, {'id': 21611, 'synset': "christ's-thorn.n.01", 'name': "Christ's-thorn"}, {'id': 21612, 'synset': 'hazel.n.01', 'name': 'hazel'}, {'id': 21613, 'synset': 'fox_grape.n.01', 'name': 'fox_grape'}, {'id': 21614, 'synset': 'muscadine.n.01', 'name': 'muscadine'}, {'id': 21615, 'synset': 'vinifera.n.01', 'name': 'vinifera'}, {'id': 21616, 'synset': 'pinot_blanc.n.01', 'name': 'Pinot_blanc'}, {'id': 21617, 'synset': 'sauvignon_grape.n.01', 'name': 'Sauvignon_grape'}, {'id': 21618, 'synset': 'sauvignon_blanc.n.01', 'name': 'Sauvignon_blanc'}, {'id': 21619, 'synset': 'muscadet.n.01', 'name': 'Muscadet'}, {'id': 21620, 'synset': 'riesling.n.01', 'name': 'Riesling'}, {'id': 21621, 'synset': 'zinfandel.n.01', 'name': 'Zinfandel'}, {'id': 21622, 'synset': 'chenin_blanc.n.01', 'name': 'Chenin_blanc'}, {'id': 21623, 'synset': 'malvasia.n.01', 'name': 'malvasia'}, {'id': 21624, 'synset': 'verdicchio.n.01', 'name': 'Verdicchio'}, {'id': 21625, 'synset': 'boston_ivy.n.01', 'name': 'Boston_ivy'}, {'id': 21626, 'synset': 'virginia_creeper.n.01', 'name': 'Virginia_creeper'}, {'id': 21627, 'synset': 'true_pepper.n.01', 'name': 'true_pepper'}, {'id': 21628, 'synset': 'betel.n.01', 'name': 'betel'}, {'id': 21629, 'synset': 'cubeb.n.01', 'name': 'cubeb'}, {'id': 21630, 'synset': 'schizocarp.n.01', 'name': 'schizocarp'}, {'id': 21631, 'synset': 'peperomia.n.01', 'name': 'peperomia'}, {'id': 21632, 'synset': 'watermelon_begonia.n.01', 'name': 'watermelon_begonia'}, {'id': 21633, 'synset': 'yerba_mansa.n.01', 'name': 'yerba_mansa'}, {'id': 21634, 'synset': 'pinna.n.01', 'name': 'pinna'}, {'id': 21635, 'synset': 'frond.n.01', 'name': 'frond'}, {'id': 21636, 'synset': 'bract.n.01', 'name': 'bract'}, {'id': 21637, 'synset': 'bracteole.n.01', 'name': 'bracteole'}, {'id': 21638, 'synset': 'involucre.n.01', 'name': 'involucre'}, {'id': 21639, 'synset': 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'giant_scrambling_fern.n.01', 'name': 'giant_scrambling_fern'}, {'id': 21668, 'synset': 'umbrella_fern.n.01', 'name': 'umbrella_fern'}, {'id': 21669, 'synset': 'floating_fern.n.02', 'name': 'floating_fern'}, {'id': 21670, 'synset': 'polypody.n.01', 'name': 'polypody'}, {'id': 21671, 'synset': 'licorice_fern.n.01', 'name': 'licorice_fern'}, {'id': 21672, 'synset': 'grey_polypody.n.01', 'name': 'grey_polypody'}, {'id': 21673, 'synset': 'leatherleaf.n.01', 'name': 'leatherleaf'}, {'id': 21674, 'synset': 'rock_polypody.n.01', 'name': 'rock_polypody'}, {'id': 21675, 'synset': 'common_polypody.n.01', 'name': 'common_polypody'}, {'id': 21676, 'synset': "bear's-paw_fern.n.01", 'name': "bear's-paw_fern"}, {'id': 21677, 'synset': 'strap_fern.n.01', 'name': 'strap_fern'}, {'id': 21678, 'synset': 'florida_strap_fern.n.01', 'name': 'Florida_strap_fern'}, {'id': 21679, 'synset': 'basket_fern.n.02', 'name': 'basket_fern'}, {'id': 21680, 'synset': 'snake_polypody.n.01', 'name': 'snake_polypody'}, {'id': 21681, 'synset': "climbing_bird's_nest_fern.n.01", 'name': "climbing_bird's_nest_fern"}, {'id': 21682, 'synset': 'golden_polypody.n.01', 'name': 'golden_polypody'}, {'id': 21683, 'synset': 'staghorn_fern.n.01', 'name': 'staghorn_fern'}, {'id': 21684, 'synset': 'south_american_staghorn.n.01', 'name': 'South_American_staghorn'}, {'id': 21685, 'synset': 'common_staghorn_fern.n.01', 'name': 'common_staghorn_fern'}, {'id': 21686, 'synset': 'felt_fern.n.01', 'name': 'felt_fern'}, {'id': 21687, 'synset': 'potato_fern.n.02', 'name': 'potato_fern'}, {'id': 21688, 'synset': 'myrmecophyte.n.01', 'name': 'myrmecophyte'}, {'id': 21689, 'synset': 'grass_fern.n.01', 'name': 'grass_fern'}, {'id': 21690, 'synset': 'spleenwort.n.01', 'name': 'spleenwort'}, {'id': 21691, 'synset': 'black_spleenwort.n.01', 'name': 'black_spleenwort'}, {'id': 21692, 'synset': "bird's_nest_fern.n.01", 'name': "bird's_nest_fern"}, {'id': 21693, 'synset': 'ebony_spleenwort.n.01', 'name': 'ebony_spleenwort'}, {'id': 21694, 'synset': 'black-stem_spleenwort.n.01', 'name': 'black-stem_spleenwort'}, {'id': 21695, 'synset': 'walking_fern.n.01', 'name': 'walking_fern'}, {'id': 21696, 'synset': 'green_spleenwort.n.01', 'name': 'green_spleenwort'}, {'id': 21697, 'synset': 'mountain_spleenwort.n.01', 'name': 'mountain_spleenwort'}, {'id': 21698, 'synset': 'lobed_spleenwort.n.01', 'name': 'lobed_spleenwort'}, {'id': 21699, 'synset': 'lanceolate_spleenwort.n.01', 'name': 'lanceolate_spleenwort'}, {'id': 21700, 'synset': "hart's-tongue.n.02", 'name': "hart's-tongue"}, {'id': 21701, 'synset': 'scale_fern.n.01', 'name': 'scale_fern'}, {'id': 21702, 'synset': 'scolopendrium.n.01', 'name': 'scolopendrium'}, {'id': 21703, 'synset': 'deer_fern.n.01', 'name': 'deer_fern'}, {'id': 21704, 'synset': 'doodia.n.01', 'name': 'doodia'}, {'id': 21705, 'synset': 'chain_fern.n.01', 'name': 'chain_fern'}, {'id': 21706, 'synset': 'virginia_chain_fern.n.01', 'name': 'Virginia_chain_fern'}, {'id': 21707, 'synset': 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"goldie's_fern.n.01", 'name': "Goldie's_fern"}, {'id': 21721, 'synset': 'wood_fern.n.01', 'name': 'wood_fern'}, {'id': 21722, 'synset': 'male_fern.n.01', 'name': 'male_fern'}, {'id': 21723, 'synset': 'marginal_wood_fern.n.01', 'name': 'marginal_wood_fern'}, {'id': 21724, 'synset': 'mountain_male_fern.n.01', 'name': 'mountain_male_fern'}, {'id': 21725, 'synset': 'lady_fern.n.01', 'name': 'lady_fern'}, {'id': 21726, 'synset': 'alpine_lady_fern.n.01', 'name': 'Alpine_lady_fern'}, {'id': 21727, 'synset': 'silvery_spleenwort.n.02', 'name': 'silvery_spleenwort'}, {'id': 21728, 'synset': 'holly_fern.n.02', 'name': 'holly_fern'}, {'id': 21729, 'synset': 'bladder_fern.n.01', 'name': 'bladder_fern'}, {'id': 21730, 'synset': 'brittle_bladder_fern.n.01', 'name': 'brittle_bladder_fern'}, {'id': 21731, 'synset': 'mountain_bladder_fern.n.01', 'name': 'mountain_bladder_fern'}, {'id': 21732, 'synset': 'bulblet_fern.n.01', 'name': 'bulblet_fern'}, {'id': 21733, 'synset': 'silvery_spleenwort.n.01', 'name': 'silvery_spleenwort'}, {'id': 21734, 'synset': 'oak_fern.n.01', 'name': 'oak_fern'}, {'id': 21735, 'synset': 'limestone_fern.n.01', 'name': 'limestone_fern'}, {'id': 21736, 'synset': 'ostrich_fern.n.01', 'name': 'ostrich_fern'}, {'id': 21737, 'synset': "hart's-tongue.n.01", 'name': "hart's-tongue"}, {'id': 21738, 'synset': 'sensitive_fern.n.01', 'name': 'sensitive_fern'}, {'id': 21739, 'synset': 'christmas_fern.n.01', 'name': 'Christmas_fern'}, {'id': 21740, 'synset': 'holly_fern.n.01', 'name': 'holly_fern'}, {'id': 21741, 'synset': "braun's_holly_fern.n.01", 'name': "Braun's_holly_fern"}, {'id': 21742, 'synset': 'western_holly_fern.n.01', 'name': 'western_holly_fern'}, {'id': 21743, 'synset': 'soft_shield_fern.n.01', 'name': 'soft_shield_fern'}, {'id': 21744, 'synset': 'leather_fern.n.02', 'name': 'leather_fern'}, {'id': 21745, 'synset': 'button_fern.n.02', 'name': 'button_fern'}, {'id': 21746, 'synset': 'indian_button_fern.n.01', 'name': 'Indian_button_fern'}, {'id': 21747, 'synset': 'woodsia.n.01', 'name': 'woodsia'}, {'id': 21748, 'synset': 'rusty_woodsia.n.01', 'name': 'rusty_woodsia'}, {'id': 21749, 'synset': 'alpine_woodsia.n.01', 'name': 'Alpine_woodsia'}, {'id': 21750, 'synset': 'smooth_woodsia.n.01', 'name': 'smooth_woodsia'}, {'id': 21751, 'synset': 'boston_fern.n.01', 'name': 'Boston_fern'}, {'id': 21752, 'synset': 'basket_fern.n.01', 'name': 'basket_fern'}, {'id': 21753, 'synset': 'golden_fern.n.02', 'name': 'golden_fern'}, {'id': 21754, 'synset': 'maidenhair.n.01', 'name': 'maidenhair'}, {'id': 21755, 'synset': 'common_maidenhair.n.01', 'name': 'common_maidenhair'}, {'id': 21756, 'synset': 'american_maidenhair_fern.n.01', 'name': 'American_maidenhair_fern'}, {'id': 21757, 'synset': 'bermuda_maidenhair.n.01', 'name': 'Bermuda_maidenhair'}, {'id': 21758, 'synset': 'brittle_maidenhair.n.01', 'name': 'brittle_maidenhair'}, {'id': 21759, 'synset': 'farley_maidenhair.n.01', 'name': 'Farley_maidenhair'}, {'id': 21760, 'synset': 'annual_fern.n.01', 'name': 'annual_fern'}, {'id': 21761, 'synset': 'lip_fern.n.01', 'name': 'lip_fern'}, {'id': 21762, 'synset': 'smooth_lip_fern.n.01', 'name': 'smooth_lip_fern'}, {'id': 21763, 'synset': 'lace_fern.n.01', 'name': 'lace_fern'}, {'id': 21764, 'synset': 'wooly_lip_fern.n.01', 'name': 'wooly_lip_fern'}, {'id': 21765, 'synset': 'southwestern_lip_fern.n.01', 'name': 'southwestern_lip_fern'}, {'id': 21766, 'synset': 'bamboo_fern.n.01', 'name': 'bamboo_fern'}, {'id': 21767, 'synset': 'american_rock_brake.n.01', 'name': 'American_rock_brake'}, {'id': 21768, 'synset': 'european_parsley_fern.n.01', 'name': 'European_parsley_fern'}, {'id': 21769, 'synset': 'hand_fern.n.01', 'name': 'hand_fern'}, {'id': 21770, 'synset': 'cliff_brake.n.01', 'name': 'cliff_brake'}, {'id': 21771, 'synset': 'coffee_fern.n.01', 'name': 'coffee_fern'}, {'id': 21772, 'synset': 'purple_rock_brake.n.01', 'name': 'purple_rock_brake'}, {'id': 21773, 'synset': "bird's-foot_fern.n.01", 'name': "bird's-foot_fern"}, {'id': 21774, 'synset': 'button_fern.n.01', 'name': 'button_fern'}, {'id': 21775, 'synset': 'silver_fern.n.02', 'name': 'silver_fern'}, {'id': 21776, 'synset': 'golden_fern.n.01', 'name': 'golden_fern'}, {'id': 21777, 'synset': 'gold_fern.n.01', 'name': 'gold_fern'}, {'id': 21778, 'synset': 'pteris_cretica.n.01', 'name': 'Pteris_cretica'}, {'id': 21779, 'synset': 'spider_brake.n.01', 'name': 'spider_brake'}, {'id': 21780, 'synset': 'ribbon_fern.n.01', 'name': 'ribbon_fern'}, {'id': 21781, 'synset': 'potato_fern.n.01', 'name': 'potato_fern'}, {'id': 21782, 'synset': 'angiopteris.n.01', 'name': 'angiopteris'}, {'id': 21783, 'synset': 'skeleton_fork_fern.n.01', 'name': 'skeleton_fork_fern'}, {'id': 21784, 'synset': 'horsetail.n.01', 'name': 'horsetail'}, {'id': 21785, 'synset': 'common_horsetail.n.01', 'name': 'common_horsetail'}, {'id': 21786, 'synset': 'swamp_horsetail.n.01', 'name': 'swamp_horsetail'}, {'id': 21787, 'synset': 'scouring_rush.n.01', 'name': 'scouring_rush'}, {'id': 21788, 'synset': 'marsh_horsetail.n.01', 'name': 'marsh_horsetail'}, {'id': 21789, 'synset': 'wood_horsetail.n.01', 'name': 'wood_horsetail'}, {'id': 21790, 'synset': 'variegated_horsetail.n.01', 'name': 'variegated_horsetail'}, {'id': 21791, 'synset': 'club_moss.n.01', 'name': 'club_moss'}, {'id': 21792, 'synset': 'shining_clubmoss.n.01', 'name': 'shining_clubmoss'}, {'id': 21793, 'synset': 'alpine_clubmoss.n.01', 'name': 'alpine_clubmoss'}, {'id': 21794, 'synset': 'fir_clubmoss.n.01', 'name': 'fir_clubmoss'}, {'id': 21795, 'synset': 'ground_cedar.n.01', 'name': 'ground_cedar'}, {'id': 21796, 'synset': 'ground_fir.n.01', 'name': 'ground_fir'}, {'id': 21797, 'synset': 'foxtail_grass.n.01', 'name': 'foxtail_grass'}, {'id': 21798, 'synset': 'spikemoss.n.01', 'name': 'spikemoss'}, {'id': 21799, 'synset': 'meadow_spikemoss.n.01', 'name': 'meadow_spikemoss'}, {'id': 21800, 'synset': 'desert_selaginella.n.01', 'name': 'desert_selaginella'}, {'id': 21801, 'synset': 'resurrection_plant.n.01', 'name': 'resurrection_plant'}, {'id': 21802, 'synset': 'florida_selaginella.n.01', 'name': 'florida_selaginella'}, {'id': 21803, 'synset': 'quillwort.n.01', 'name': 'quillwort'}, {'id': 21804, 'synset': 'earthtongue.n.01', 'name': 'earthtongue'}, {'id': 21805, 'synset': 'snuffbox_fern.n.01', 'name': 'snuffbox_fern'}, {'id': 21806, 'synset': 'christella.n.01', 'name': 'christella'}, {'id': 21807, 'synset': 'mountain_fern.n.01', 'name': 'mountain_fern'}, {'id': 21808, 'synset': 'new_york_fern.n.01', 'name': 'New_York_fern'}, {'id': 21809, 'synset': 'massachusetts_fern.n.01', 'name': 'Massachusetts_fern'}, {'id': 21810, 'synset': 'beech_fern.n.01', 'name': 'beech_fern'}, {'id': 21811, 'synset': 'broad_beech_fern.n.01', 'name': 'broad_beech_fern'}, {'id': 21812, 'synset': 'long_beech_fern.n.01', 'name': 'long_beech_fern'}, {'id': 21813, 'synset': 'shoestring_fungus.n.01', 'name': 'shoestring_fungus'}, {'id': 21814, 'synset': 'armillaria_caligata.n.01', 'name': 'Armillaria_caligata'}, {'id': 21815, 'synset': 'armillaria_ponderosa.n.01', 'name': 'Armillaria_ponderosa'}, {'id': 21816, 'synset': 'armillaria_zelleri.n.01', 'name': 'Armillaria_zelleri'}, {'id': 21817, 'synset': 'honey_mushroom.n.01', 'name': 'honey_mushroom'}, {'id': 21818, 'synset': 'milkweed.n.01', 'name': 'milkweed'}, {'id': 21819, 'synset': 'white_milkweed.n.01', 'name': 'white_milkweed'}, {'id': 21820, 'synset': 'poke_milkweed.n.01', 'name': 'poke_milkweed'}, {'id': 21821, 'synset': 'swamp_milkweed.n.01', 'name': 'swamp_milkweed'}, {'id': 21822, 'synset': "mead's_milkweed.n.01", 'name': "Mead's_milkweed"}, {'id': 21823, 'synset': 'purple_silkweed.n.01', 'name': 'purple_silkweed'}, {'id': 21824, 'synset': 'showy_milkweed.n.01', 'name': 'showy_milkweed'}, {'id': 21825, 'synset': 'poison_milkweed.n.01', 'name': 'poison_milkweed'}, {'id': 21826, 'synset': 'butterfly_weed.n.01', 'name': 'butterfly_weed'}, {'id': 21827, 'synset': 'whorled_milkweed.n.01', 'name': 'whorled_milkweed'}, {'id': 21828, 'synset': 'cruel_plant.n.01', 'name': 'cruel_plant'}, {'id': 21829, 'synset': 'wax_plant.n.01', 'name': 'wax_plant'}, {'id': 21830, 'synset': 'silk_vine.n.01', 'name': 'silk_vine'}, {'id': 21831, 'synset': 'stapelia.n.01', 'name': 'stapelia'}, {'id': 21832, 'synset': 'stapelias_asterias.n.01', 'name': 'Stapelias_asterias'}, {'id': 21833, 'synset': 'stephanotis.n.01', 'name': 'stephanotis'}, {'id': 21834, 'synset': 'madagascar_jasmine.n.01', 'name': 'Madagascar_jasmine'}, {'id': 21835, 'synset': 'negro_vine.n.01', 'name': 'negro_vine'}, {'id': 21836, 'synset': 'zygospore.n.01', 'name': 'zygospore'}, {'id': 21837, 'synset': 'tree_of_knowledge.n.01', 'name': 'tree_of_knowledge'}, {'id': 21838, 'synset': 'orangery.n.01', 'name': 'orangery'}, {'id': 21839, 'synset': 'pocketbook.n.01', 'name': 'pocketbook'}, {'id': 21840, 'synset': 'shit.n.04', 'name': 'shit'}, {'id': 21841, 'synset': 'cordage.n.01', 'name': 'cordage'}, {'id': 21842, 'synset': 'yard.n.01', 'name': 'yard'}, {'id': 21843, 'synset': 'extremum.n.02', 'name': 'extremum'}, {'id': 21844, 'synset': 'leaf_shape.n.01', 'name': 'leaf_shape'}, {'id': 21845, 'synset': 'equilateral.n.01', 'name': 'equilateral'}, {'id': 21846, 'synset': 'figure.n.06', 'name': 'figure'}, {'id': 21847, 'synset': 'pencil.n.03', 'name': 'pencil'}, {'id': 21848, 'synset': 'plane_figure.n.01', 'name': 'plane_figure'}, {'id': 21849, 'synset': 'solid_figure.n.01', 'name': 'solid_figure'}, {'id': 21850, 'synset': 'line.n.04', 'name': 'line'}, {'id': 21851, 'synset': 'bulb.n.04', 'name': 'bulb'}, {'id': 21852, 'synset': 'convex_shape.n.01', 'name': 'convex_shape'}, {'id': 21853, 'synset': 'concave_shape.n.01', 'name': 'concave_shape'}, {'id': 21854, 'synset': 'cylinder.n.01', 'name': 'cylinder'}, {'id': 21855, 'synset': 'round_shape.n.01', 'name': 'round_shape'}, {'id': 21856, 'synset': 'heart.n.07', 'name': 'heart'}, {'id': 21857, 'synset': 'polygon.n.01', 'name': 'polygon'}, {'id': 21858, 'synset': 'convex_polygon.n.01', 'name': 'convex_polygon'}, {'id': 21859, 'synset': 'concave_polygon.n.01', 'name': 'concave_polygon'}, {'id': 21860, 'synset': 'reentrant_polygon.n.01', 'name': 'reentrant_polygon'}, {'id': 21861, 'synset': 'amorphous_shape.n.01', 'name': 'amorphous_shape'}, {'id': 21862, 'synset': 'closed_curve.n.01', 'name': 'closed_curve'}, {'id': 21863, 'synset': 'simple_closed_curve.n.01', 'name': 'simple_closed_curve'}, {'id': 21864, 'synset': 's-shape.n.01', 'name': 'S-shape'}, {'id': 21865, 'synset': 'wave.n.07', 'name': 'wave'}, {'id': 21866, 'synset': 'extrados.n.01', 'name': 'extrados'}, {'id': 21867, 'synset': 'hook.n.02', 'name': 'hook'}, {'id': 21868, 'synset': 'envelope.n.03', 'name': 'envelope'}, {'id': 21869, 'synset': 'bight.n.02', 'name': 'bight'}, {'id': 21870, 'synset': 'diameter.n.02', 'name': 'diameter'}, {'id': 21871, 'synset': 'cone.n.02', 'name': 'cone'}, {'id': 21872, 'synset': 'funnel.n.01', 'name': 'funnel'}, {'id': 21873, 'synset': 'oblong.n.01', 'name': 'oblong'}, {'id': 21874, 'synset': 'circle.n.01', 'name': 'circle'}, {'id': 21875, 'synset': 'circle.n.03', 'name': 'circle'}, {'id': 21876, 'synset': 'equator.n.02', 'name': 'equator'}, {'id': 21877, 'synset': 'scallop.n.01', 'name': 'scallop'}, {'id': 21878, 'synset': 'ring.n.02', 'name': 'ring'}, {'id': 21879, 'synset': 'loop.n.02', 'name': 'loop'}, {'id': 21880, 'synset': 'bight.n.01', 'name': 'bight'}, {'id': 21881, 'synset': 'helix.n.01', 'name': 'helix'}, {'id': 21882, 'synset': 'element_of_a_cone.n.01', 'name': 'element_of_a_cone'}, {'id': 21883, 'synset': 'element_of_a_cylinder.n.01', 'name': 'element_of_a_cylinder'}, {'id': 21884, 'synset': 'ellipse.n.01', 'name': 'ellipse'}, {'id': 21885, 'synset': 'quadrate.n.02', 'name': 'quadrate'}, {'id': 21886, 'synset': 'triangle.n.01', 'name': 'triangle'}, {'id': 21887, 'synset': 'acute_triangle.n.01', 'name': 'acute_triangle'}, {'id': 21888, 'synset': 'isosceles_triangle.n.01', 'name': 'isosceles_triangle'}, {'id': 21889, 'synset': 'obtuse_triangle.n.01', 'name': 'obtuse_triangle'}, {'id': 21890, 'synset': 'right_triangle.n.01', 'name': 'right_triangle'}, {'id': 21891, 'synset': 'scalene_triangle.n.01', 'name': 'scalene_triangle'}, {'id': 21892, 'synset': 'parallel.n.03', 'name': 'parallel'}, {'id': 21893, 'synset': 'trapezoid.n.01', 'name': 'trapezoid'}, {'id': 21894, 'synset': 'star.n.05', 'name': 'star'}, {'id': 21895, 'synset': 'pentagon.n.03', 'name': 'pentagon'}, {'id': 21896, 'synset': 'hexagon.n.01', 'name': 'hexagon'}, {'id': 21897, 'synset': 'heptagon.n.01', 'name': 'heptagon'}, {'id': 21898, 'synset': 'octagon.n.01', 'name': 'octagon'}, {'id': 21899, 'synset': 'nonagon.n.01', 'name': 'nonagon'}, {'id': 21900, 'synset': 'decagon.n.01', 'name': 'decagon'}, {'id': 21901, 'synset': 'rhombus.n.01', 'name': 'rhombus'}, {'id': 21902, 'synset': 'spherical_polygon.n.01', 'name': 'spherical_polygon'}, {'id': 21903, 'synset': 'spherical_triangle.n.01', 'name': 'spherical_triangle'}, {'id': 21904, 'synset': 'convex_polyhedron.n.01', 'name': 'convex_polyhedron'}, {'id': 21905, 'synset': 'concave_polyhedron.n.01', 'name': 'concave_polyhedron'}, {'id': 21906, 'synset': 'cuboid.n.01', 'name': 'cuboid'}, {'id': 21907, 'synset': 'quadrangular_prism.n.01', 'name': 'quadrangular_prism'}, {'id': 21908, 'synset': 'bell.n.05', 'name': 'bell'}, {'id': 21909, 'synset': 'angular_distance.n.01', 'name': 'angular_distance'}, {'id': 21910, 'synset': 'true_anomaly.n.01', 'name': 'true_anomaly'}, {'id': 21911, 'synset': 'spherical_angle.n.01', 'name': 'spherical_angle'}, {'id': 21912, 'synset': 'angle_of_refraction.n.01', 'name': 'angle_of_refraction'}, {'id': 21913, 'synset': 'acute_angle.n.01', 'name': 'acute_angle'}, {'id': 21914, 'synset': 'groove.n.01', 'name': 'groove'}, {'id': 21915, 'synset': 'rut.n.01', 'name': 'rut'}, {'id': 21916, 'synset': 'bulge.n.01', 'name': 'bulge'}, {'id': 21917, 'synset': 'belly.n.03', 'name': 'belly'}, {'id': 21918, 'synset': 'bow.n.05', 'name': 'bow'}, {'id': 21919, 'synset': 'crescent.n.01', 'name': 'crescent'}, {'id': 21920, 'synset': 'ellipsoid.n.01', 'name': 'ellipsoid'}, {'id': 21921, 'synset': 'hypotenuse.n.01', 'name': 'hypotenuse'}, {'id': 21922, 'synset': 'balance.n.04', 'name': 'balance'}, {'id': 21923, 'synset': 'conformation.n.01', 'name': 'conformation'}, {'id': 21924, 'synset': 'symmetry.n.02', 'name': 'symmetry'}, {'id': 21925, 'synset': 'spheroid.n.01', 'name': 'spheroid'}, {'id': 21926, 'synset': 'spherule.n.01', 'name': 'spherule'}, {'id': 21927, 'synset': 'toroid.n.01', 'name': 'toroid'}, {'id': 21928, 'synset': 'column.n.04', 'name': 'column'}, {'id': 21929, 'synset': 'barrel.n.03', 'name': 'barrel'}, {'id': 21930, 'synset': 'pipe.n.03', 'name': 'pipe'}, {'id': 21931, 'synset': 'pellet.n.01', 'name': 'pellet'}, {'id': 21932, 'synset': 'bolus.n.01', 'name': 'bolus'}, {'id': 21933, 'synset': 'dewdrop.n.01', 'name': 'dewdrop'}, {'id': 21934, 'synset': 'ridge.n.02', 'name': 'ridge'}, {'id': 21935, 'synset': 'rim.n.01', 'name': 'rim'}, {'id': 21936, 'synset': 'taper.n.01', 'name': 'taper'}, {'id': 21937, 'synset': 'boundary.n.02', 'name': 'boundary'}, {'id': 21938, 'synset': 'incisure.n.01', 'name': 'incisure'}, {'id': 21939, 'synset': 'notch.n.01', 'name': 'notch'}, {'id': 21940, 'synset': 'wrinkle.n.01', 'name': 'wrinkle'}, {'id': 21941, 'synset': 'dermatoglyphic.n.01', 'name': 'dermatoglyphic'}, {'id': 21942, 'synset': 'frown_line.n.01', 'name': 'frown_line'}, {'id': 21943, 'synset': 'line_of_life.n.01', 'name': 'line_of_life'}, {'id': 21944, 'synset': 'line_of_heart.n.01', 'name': 'line_of_heart'}, {'id': 21945, 'synset': 'crevice.n.01', 'name': 'crevice'}, {'id': 21946, 'synset': 'cleft.n.01', 'name': 'cleft'}, {'id': 21947, 'synset': 'roulette.n.01', 'name': 'roulette'}, {'id': 21948, 'synset': 'node.n.01', 'name': 'node'}, {'id': 21949, 'synset': 'tree.n.02', 'name': 'tree'}, {'id': 21950, 'synset': 'stemma.n.01', 'name': 'stemma'}, {'id': 21951, 'synset': 'brachium.n.01', 'name': 'brachium'}, {'id': 21952, 'synset': 'fork.n.03', 'name': 'fork'}, {'id': 21953, 'synset': 'block.n.03', 'name': 'block'}, {'id': 21954, 'synset': 'ovoid.n.01', 'name': 'ovoid'}, {'id': 21955, 'synset': 'tetrahedron.n.01', 'name': 'tetrahedron'}, {'id': 21956, 'synset': 'pentahedron.n.01', 'name': 'pentahedron'}, {'id': 21957, 'synset': 'hexahedron.n.01', 'name': 'hexahedron'}, {'id': 21958, 'synset': 'regular_polyhedron.n.01', 'name': 'regular_polyhedron'}, {'id': 21959, 'synset': 'polyhedral_angle.n.01', 'name': 'polyhedral_angle'}, {'id': 21960, 'synset': 'cube.n.01', 'name': 'cube'}, {'id': 21961, 'synset': 'truncated_pyramid.n.01', 'name': 'truncated_pyramid'}, {'id': 21962, 'synset': 'truncated_cone.n.01', 'name': 'truncated_cone'}, {'id': 21963, 'synset': 'tail.n.03', 'name': 'tail'}, {'id': 21964, 'synset': 'tongue.n.03', 'name': 'tongue'}, {'id': 21965, 'synset': 'trapezohedron.n.01', 'name': 'trapezohedron'}, {'id': 21966, 'synset': 'wedge.n.01', 'name': 'wedge'}, {'id': 21967, 'synset': 'keel.n.01', 'name': 'keel'}, {'id': 21968, 'synset': 'place.n.06', 'name': 'place'}, {'id': 21969, 'synset': 'herpes.n.01', 'name': 'herpes'}, {'id': 21970, 'synset': 'chlamydia.n.01', 'name': 'chlamydia'}, {'id': 21971, 'synset': 'wall.n.04', 'name': 'wall'}, {'id': 21972, 'synset': 'micronutrient.n.01', 'name': 'micronutrient'}, {'id': 21973, 'synset': 'chyme.n.01', 'name': 'chyme'}, {'id': 21974, 'synset': 'ragweed_pollen.n.01', 'name': 'ragweed_pollen'}, {'id': 21975, 'synset': 'pina_cloth.n.01', 'name': 'pina_cloth'}, {'id': 21976, 'synset': 'chlorobenzylidenemalononitrile.n.01', 'name': 'chlorobenzylidenemalononitrile'}, {'id': 21977, 'synset': 'carbon.n.01', 'name': 'carbon'}, {'id': 21978, 'synset': 'charcoal.n.01', 'name': 'charcoal'}, {'id': 21979, 'synset': 'rock.n.02', 'name': 'rock'}, {'id': 21980, 'synset': 'gravel.n.01', 'name': 'gravel'}, {'id': 21981, 'synset': 'aflatoxin.n.01', 'name': 'aflatoxin'}, {'id': 21982, 'synset': 'alpha-tocopheral.n.01', 'name': 'alpha-tocopheral'}, {'id': 21983, 'synset': 'leopard.n.01', 'name': 'leopard'}, {'id': 21984, 'synset': 'bricks_and_mortar.n.01', 'name': 'bricks_and_mortar'}, {'id': 21985, 'synset': 'lagging.n.01', 'name': 'lagging'}, {'id': 21986, 'synset': 'hydraulic_cement.n.01', 'name': 'hydraulic_cement'}, {'id': 21987, 'synset': 'choline.n.01', 'name': 'choline'}, {'id': 21988, 'synset': 'concrete.n.01', 'name': 'concrete'}, {'id': 21989, 'synset': 'glass_wool.n.01', 'name': 'glass_wool'}, {'id': 21990, 'synset': 'soil.n.02', 'name': 'soil'}, {'id': 21991, 'synset': 'high_explosive.n.01', 'name': 'high_explosive'}, {'id': 21992, 'synset': 'litter.n.02', 'name': 'litter'}, {'id': 21993, 'synset': 'fish_meal.n.01', 'name': 'fish_meal'}, {'id': 21994, 'synset': 'greek_fire.n.01', 'name': 'Greek_fire'}, {'id': 21995, 'synset': 'culture_medium.n.01', 'name': 'culture_medium'}, {'id': 21996, 'synset': 'agar.n.01', 'name': 'agar'}, {'id': 21997, 'synset': 'blood_agar.n.01', 'name': 'blood_agar'}, {'id': 21998, 'synset': 'hip_tile.n.01', 'name': 'hip_tile'}, {'id': 21999, 'synset': 'hyacinth.n.01', 'name': 'hyacinth'}, {'id': 22000, 'synset': 'hydroxide_ion.n.01', 'name': 'hydroxide_ion'}, {'id': 22001, 'synset': 'ice.n.01', 'name': 'ice'}, {'id': 22002, 'synset': 'inositol.n.01', 'name': 'inositol'}, {'id': 22003, 'synset': 'linoleum.n.01', 'name': 'linoleum'}, {'id': 22004, 'synset': 'lithia_water.n.01', 'name': 'lithia_water'}, {'id': 22005, 'synset': 'lodestone.n.01', 'name': 'lodestone'}, {'id': 22006, 'synset': 'pantothenic_acid.n.01', 'name': 'pantothenic_acid'}, {'id': 22007, 'synset': 'paper.n.01', 'name': 'paper'}, {'id': 22008, 'synset': 'papyrus.n.01', 'name': 'papyrus'}, {'id': 22009, 'synset': 'pantile.n.01', 'name': 'pantile'}, {'id': 22010, 'synset': 'blacktop.n.01', 'name': 'blacktop'}, {'id': 22011, 'synset': 'tarmacadam.n.01', 'name': 'tarmacadam'}, {'id': 22012, 'synset': 'paving.n.01', 'name': 'paving'}, {'id': 22013, 'synset': 'plaster.n.01', 'name': 'plaster'}, {'id': 22014, 'synset': 'poison_gas.n.01', 'name': 'poison_gas'}, {'id': 22015, 'synset': 'ridge_tile.n.01', 'name': 'ridge_tile'}, {'id': 22016, 'synset': 'roughcast.n.01', 'name': 'roughcast'}, {'id': 22017, 'synset': 'sand.n.01', 'name': 'sand'}, {'id': 22018, 'synset': 'spackle.n.01', 'name': 'spackle'}, {'id': 22019, 'synset': 'render.n.01', 'name': 'render'}, {'id': 22020, 'synset': 'wattle_and_daub.n.01', 'name': 'wattle_and_daub'}, {'id': 22021, 'synset': 'stucco.n.01', 'name': 'stucco'}, {'id': 22022, 'synset': 'tear_gas.n.01', 'name': 'tear_gas'}, {'id': 22023, 'synset': 'linseed.n.01', 'name': 'linseed'}, {'id': 22024, 'synset': 'vitamin.n.01', 'name': 'vitamin'}, {'id': 22025, 'synset': 'fat-soluble_vitamin.n.01', 'name': 'fat-soluble_vitamin'}, {'id': 22026, 'synset': 'water-soluble_vitamin.n.01', 'name': 'water-soluble_vitamin'}, {'id': 22027, 'synset': 'vitamin_a.n.01', 'name': 'vitamin_A'}, {'id': 22028, 'synset': 'vitamin_a1.n.01', 'name': 'vitamin_A1'}, {'id': 22029, 'synset': 'vitamin_a2.n.01', 'name': 'vitamin_A2'}, {'id': 22030, 'synset': 'b-complex_vitamin.n.01', 'name': 'B-complex_vitamin'}, {'id': 22031, 'synset': 'vitamin_b1.n.01', 'name': 'vitamin_B1'}, {'id': 22032, 'synset': 'vitamin_b12.n.01', 'name': 'vitamin_B12'}, {'id': 22033, 'synset': 'vitamin_b2.n.01', 'name': 'vitamin_B2'}, {'id': 22034, 'synset': 'vitamin_b6.n.01', 'name': 'vitamin_B6'}, {'id': 22035, 'synset': 'vitamin_bc.n.01', 'name': 'vitamin_Bc'}, {'id': 22036, 'synset': 'niacin.n.01', 'name': 'niacin'}, {'id': 22037, 'synset': 'vitamin_d.n.01', 'name': 'vitamin_D'}, {'id': 22038, 'synset': 'vitamin_e.n.01', 'name': 'vitamin_E'}, {'id': 22039, 'synset': 'biotin.n.01', 'name': 'biotin'}, {'id': 22040, 'synset': 'vitamin_k.n.01', 'name': 'vitamin_K'}, {'id': 22041, 'synset': 'vitamin_k1.n.01', 'name': 'vitamin_K1'}, {'id': 22042, 'synset': 'vitamin_k3.n.01', 'name': 'vitamin_K3'}, {'id': 22043, 'synset': 'vitamin_p.n.01', 'name': 'vitamin_P'}, {'id': 22044, 'synset': 'vitamin_c.n.01', 'name': 'vitamin_C'}, {'id': 22045, 'synset': 'planking.n.01', 'name': 'planking'}, {'id': 22046, 'synset': 'chipboard.n.01', 'name': 'chipboard'}, {'id': 22047, 'synset': 'knothole.n.01', 'name': 'knothole'}] # noqa
\ No newline at end of file
diff --git a/spaces/ashercn97/AsherTesting/extensions/openai/images.py b/spaces/ashercn97/AsherTesting/extensions/openai/images.py
deleted file mode 100644
index d2be3192d68994c40ace6e55bffc82f6315f439c..0000000000000000000000000000000000000000
--- a/spaces/ashercn97/AsherTesting/extensions/openai/images.py
+++ /dev/null
@@ -1,49 +0,0 @@
-import os
-import time
-import requests
-from extensions.openai.errors import *
-
-
-def generations(prompt: str, size: str, response_format: str, n: int):
- # Stable Diffusion callout wrapper for txt2img
- # Low effort implementation for compatibility. With only "prompt" being passed and assuming DALL-E
- # the results will be limited and likely poor. SD has hundreds of models and dozens of settings.
- # If you want high quality tailored results you should just use the Stable Diffusion API directly.
- # it's too general an API to try and shape the result with specific tags like "masterpiece", etc,
- # Will probably work best with the stock SD models.
- # SD configuration is beyond the scope of this API.
- # At this point I will not add the edits and variations endpoints (ie. img2img) because they
- # require changing the form data handling to accept multipart form data, also to properly support
- # url return types will require file management and a web serving files... Perhaps later!
-
- width, height = [int(x) for x in size.split('x')] # ignore the restrictions on size
-
- # to hack on better generation, edit default payload.
- payload = {
- 'prompt': prompt, # ignore prompt limit of 1000 characters
- 'width': width,
- 'height': height,
- 'batch_size': n,
- 'restore_faces': True, # slightly less horrible
- }
-
- resp = {
- 'created': int(time.time()),
- 'data': []
- }
-
- # TODO: support SD_WEBUI_AUTH username:password pair.
- sd_url = f"{os.environ['SD_WEBUI_URL']}/sdapi/v1/txt2img"
-
- response = requests.post(url=sd_url, json=payload)
- r = response.json()
- if response.status_code != 200 or 'images' not in r:
- raise ServiceUnavailableError(r.get('detail', [{'msg': 'Unknown error calling Stable Diffusion'}])[0]['msg'], code=response.status_code)
- # r['parameters']...
- for b64_json in r['images']:
- if response_format == 'b64_json':
- resp['data'].extend([{'b64_json': b64_json}])
- else:
- resp['data'].extend([{'url': f'data:image/png;base64,{b64_json}'}]) # yeah it's lazy. requests.get() will not work with this
-
- return resp
diff --git a/spaces/ashercn97/AsherTesting/extensions/sd_api_pictures/style.css b/spaces/ashercn97/AsherTesting/extensions/sd_api_pictures/style.css
deleted file mode 100644
index 6f4994616a1d4ca52f3a8245f963ce0b7ebbb0d7..0000000000000000000000000000000000000000
--- a/spaces/ashercn97/AsherTesting/extensions/sd_api_pictures/style.css
+++ /dev/null
@@ -1,52 +0,0 @@
-/* Align the elements for SD_api_picture extension */
-.SDAP #sampler_box {
- padding-top: var(--spacing-sm);
- padding-bottom: var(--spacing-sm);
- border: 0;
-}
-
-.SDAP #steps_box {
- border-radius: 0 0 var(--block-radius) var(--block-radius);
-}
-
-.SDAP #sampler_col {
- gap: 0;
- padding: 0;
- background-color: transparent;
-}
-
-.SDAP #sampler_row {
- border-bottom: 0;
- box-shadow: var(--block-shadow);
- border-width: var(--block-border-width);
- border-color: var(--block-border-color);
- border-radius: var(--block-radius) var(--block-radius) 0 0;
- background: var(--block-background-fill);
- gap: 0;
-}
-
-.SDAP #sampler_row .refresh-button {
- margin-bottom: var(--spacing-sm);
- margin-right: var(--spacing-lg);
-}
-
-.SDAP #seed_box,
-.SDAP #cfg_box {
- padding-top: var(--spacing-md);
-}
-
-.SDAP #sampler_box span,
-.SDAP #seed_box span,
-.SDAP #cfg_box span,
-.SDAP #steps_box span {
- margin-bottom: var(--spacing-sm);
-}
-
-.SDAP svg.dropdown-arrow {
- flex-shrink: 0 !important;
- margin: 0px !important;
-}
-
-.SDAP .hires_opts input[type="number"] {
- width: 6em !important;
-}
diff --git a/spaces/aukaru/claude-wangy/README.md b/spaces/aukaru/claude-wangy/README.md
deleted file mode 100644
index 73250683211585e06fc7819116f27ca81a8fcac8..0000000000000000000000000000000000000000
--- a/spaces/aukaru/claude-wangy/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: Claude Wangy
-emoji: 🐨
-colorFrom: green
-colorTo: pink
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/awaawawawa/iurf7irfuyytruyyugb/README.md b/spaces/awaawawawa/iurf7irfuyytruyyugb/README.md
deleted file mode 100644
index bd4a44e6a2b592a05f2d9b6ca1da4bbb2bdf3c8f..0000000000000000000000000000000000000000
--- a/spaces/awaawawawa/iurf7irfuyytruyyugb/README.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-app_file: start.py
-colorFrom: green
-colorTo: green
-datasets:
- - emotion
-emoji: ⚡
-license: mit
-sdk: gradio
-sdk_version: "3.1.7"
-title: "Stable Diffusion 3"
-
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology/app.backup.py b/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology/app.backup.py
deleted file mode 100644
index fd97bf2a8592b219ba1c2d4c94187d984e63d114..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology/app.backup.py
+++ /dev/null
@@ -1,268 +0,0 @@
-import gradio as gr
-import pandas as pd
-import json
-from collections import defaultdict
-
-# Create tokenizer for biomed model
-from transformers import pipeline, AutoTokenizer, AutoModelForTokenClassification
-tokenizer = AutoTokenizer.from_pretrained("d4data/biomedical-ner-all") # https://huggingface.co/d4data/biomedical-ner-all?text=asthma
-model = AutoModelForTokenClassification.from_pretrained("d4data/biomedical-ner-all")
-pipe = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
-
-# Matplotlib for entity graph
-import matplotlib.pyplot as plt
-plt.switch_backend("Agg")
-
-# Load examples from JSON
-import os
-
-# Load terminology datasets:
-basedir = os.path.dirname(__file__)
-#dataLOINC = pd.read_csv(basedir + "\\" + f'LoincTableCore.csv')
-#dataPanels = pd.read_csv(basedir + "\\" + f'PanelsAndForms-ACW1208Labeled.csv')
-#dataSNOMED = pd.read_csv(basedir + "\\" + f'sct2_TextDefinition_Full-en_US1000124_20220901.txt',sep='\t')
-#dataOMS = pd.read_csv(basedir + "\\" + f'SnomedOMS.csv')
-#dataICD10 = pd.read_csv(basedir + "\\" + f'ICD10Diagnosis.csv')
-
-dataLOINC = pd.read_csv(f'LoincTableCore.csv')
-dataPanels = pd.read_csv(f'PanelsAndForms-ACW1208Labeled.csv')
-dataSNOMED = pd.read_csv(f'sct2_TextDefinition_Full-en_US1000124_20220901.txt',sep='\t')
-dataOMS = pd.read_csv(f'SnomedOMS.csv')
-dataICD10 = pd.read_csv(f'ICD10Diagnosis.csv')
-
-dir_path = os.path.dirname(os.path.realpath(__file__))
-EXAMPLES = {}
-#with open(dir_path + "\\" + "examples.json", "r") as f:
-with open("examples.json", "r") as f:
- example_json = json.load(f)
- EXAMPLES = {x["text"]: x["label"] for x in example_json}
-
-def MatchLOINC(name):
- #basedir = os.path.dirname(__file__)
- pd.set_option("display.max_rows", None)
- #data = pd.read_csv(basedir + "\\" + f'LoincTableCore.csv')
- data = dataLOINC
- swith=data.loc[data['COMPONENT'].str.contains(name, case=False, na=False)]
- return swith
-
-def MatchLOINCPanelsandForms(name):
- #basedir = os.path.dirname(__file__)
- #data = pd.read_csv(basedir + "\\" + f'PanelsAndForms-ACW1208Labeled.csv')
- data = dataPanels
- # Assessment Name:
- #swith=data.loc[data['ParentName'].str.contains(name, case=False, na=False)]
- # Assessment Question:
- swith=data.loc[data['LoincName'].str.contains(name, case=False, na=False)]
- return swith
-
-def MatchSNOMED(name):
- #basedir = os.path.dirname(__file__)
- #data = pd.read_csv(basedir + "\\" + f'sct2_TextDefinition_Full-en_US1000124_20220901.txt',sep='\t')
- data = dataSNOMED
- swith=data.loc[data['term'].str.contains(name, case=False, na=False)]
- return swith
-
-def MatchOMS(name):
- #basedir = os.path.dirname(__file__)
- #data = pd.read_csv(basedir + "\\" + f'SnomedOMS.csv')
- data = dataOMS
- swith=data.loc[data['SNOMED CT'].str.contains(name, case=False, na=False)]
- return swith
-
-def MatchICD10(name):
- #basedir = os.path.dirname(__file__)
- #data = pd.read_csv(basedir + "\\" + f'ICD10Diagnosis.csv')
- data = dataICD10
- swith=data.loc[data['Description'].str.contains(name, case=False, na=False)]
- return swith
-
-def SaveResult(text, outputfileName):
- #try:
- basedir = os.path.dirname(__file__)
- savePath = outputfileName
- print("Saving: " + text + " to " + savePath)
- from os.path import exists
- file_exists = exists(savePath)
- if file_exists:
- with open(outputfileName, "a") as f: #append
- #for line in text:
- f.write(str(text.replace("\n"," ")))
- f.write('\n')
- else:
- with open(outputfileName, "w") as f: #write
- #for line in text:
- f.write(str(text.replace("\n"," ")))
- f.write('\n')
- #except ValueError as err:
- # raise ValueError("File Save Error in SaveResult \n" + format_tb(err.__traceback__)[0] + err.args[0] + "\nEnd of error message.") from None
-
- return
-
-def loadFile(filename):
- try:
- basedir = os.path.dirname(__file__)
- loadPath = basedir + "\\" + filename
-
- print("Loading: " + loadPath)
-
- from os.path import exists
- file_exists = exists(loadPath)
-
- if file_exists:
- with open(loadPath, "r") as f: #read
- contents = f.read()
- print(contents)
- return contents
-
- except ValueError as err:
- raise ValueError("File Save Error in SaveResult \n" + format_tb(err.__traceback__)[0] + err.args[0] + "\nEnd of error message.") from None
-
- return ""
-
-def get_today_filename():
- from datetime import datetime
- date = datetime.now().strftime("%Y_%m_%d-%I.%M.%S.%p")
- #print(f"filename_{date}") 'filename_2023_01_12-03-29-22_AM'
- return f"MedNER_{date}.csv"
-
-def get_base(filename):
- basedir = os.path.dirname(__file__)
- loadPath = basedir + "\\" + filename
- #print("Loading: " + loadPath)
- return loadPath
-
-def group_by_entity(raw):
- outputFile = get_base(get_today_filename())
- out = defaultdict(int)
-
- for ent in raw:
- out[ent["entity_group"]] += 1
- myEntityGroup = ent["entity_group"]
- print("Found entity group type: " + myEntityGroup)
-
- if (myEntityGroup in ['Sign_symptom', 'Detailed_description', 'History', 'Activity', 'Medication' ]):
- eterm = ent["word"].replace('#','')
- minlength = 3
- if len(eterm) > minlength:
- print("Found eterm: " + eterm)
- eterm.replace("#","")
- g1=MatchLOINC(eterm)
- g2=MatchLOINCPanelsandForms(eterm)
- g3=MatchSNOMED(eterm)
- g4=MatchOMS(eterm)
- g5=MatchICD10(eterm)
- sAll = ""
-
- print("Saving to output file " + outputFile)
- # Create harmonisation output format of input to output code, name, Text
-
- try: # 18 fields, output to labeled CSV dataset for results teaching on scored regret changes to action plan with data inputs
- col = " 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19"
-
- #LOINC
- g11 = g1['LOINC_NUM'].to_string().replace(","," ").replace("\n"," ")
- g12 = g1['COMPONENT'].to_string().replace(","," ").replace("\n"," ")
- s1 = ("LOINC," + myEntityGroup + "," + eterm + ",questions of ," + g12 + "," + g11 + ", Label,Value, Label,Value, Label,Value ")
- if g11 != 'Series([] )': SaveResult(s1, outputFile)
-
- #LOINC Panels
- g21 = g2['Loinc'].to_string().replace(","," ").replace("\n"," ")
- g22 = g2['LoincName'].to_string().replace(","," ").replace("\n"," ")
- g23 = g2['ParentLoinc'].to_string().replace(","," ").replace("\n"," ")
- g24 = g2['ParentName'].to_string().replace(","," ").replace("\n"," ")
- # s2 = ("LOINC Panel," + myEntityGroup + "," + eterm + ",name of ," + g22 + "," + g21 + ", and Parent codes of ," + g23 + ", with Parent names of ," + g24 + ", Label,Value ")
- s2 = ("LOINC Panel," + myEntityGroup + "," + eterm + ",name of ," + g22 + "," + g21 + "," + g24 + ", and Parent codes of ," + g23 + "," + ", Label,Value ")
- if g21 != 'Series([] )': SaveResult(s2, outputFile)
-
- #SNOMED
- g31 = g3['conceptId'].to_string().replace(","," ").replace("\n"," ").replace("\l"," ").replace("\r"," ")
- g32 = g3['term'].to_string().replace(","," ").replace("\n"," ").replace("\l"," ").replace("\r"," ")
- s3 = ("SNOMED Concept," + myEntityGroup + "," + eterm + ",terms of ," + g32 + "," + g31 + ", Label,Value, Label,Value, Label,Value ")
- if g31 != 'Series([] )': SaveResult(s3, outputFile)
-
- #OMS
- g41 = g4['Omaha Code'].to_string().replace(","," ").replace("\n"," ")
- g42 = g4['SNOMED CT concept ID'].to_string().replace(","," ").replace("\n"," ")
- g43 = g4['SNOMED CT'].to_string().replace(","," ").replace("\n"," ")
- g44 = g4['PR'].to_string().replace(","," ").replace("\n"," ")
- g45 = g4['S&S'].to_string().replace(","," ").replace("\n"," ")
- s4 = ("OMS," + myEntityGroup + "," + eterm + ",concepts of ," + g44 + "," + g45 + ", and SNOMED codes of ," + g43 + ", and OMS problem of ," + g42 + ", and OMS Sign Symptom of ," + g41)
- if g41 != 'Series([] )': SaveResult(s4, outputFile)
-
- #ICD10
- g51 = g5['Code'].to_string().replace(","," ").replace("\n"," ")
- g52 = g5['Description'].to_string().replace(","," ").replace("\n"," ")
- s5 = ("ICD10," + myEntityGroup + "," + eterm + ",descriptions of ," + g52 + "," + g51 + ", Label,Value, Label,Value, Label,Value ")
- if g51 != 'Series([] )': SaveResult(s5, outputFile)
-
- except ValueError as err:
- raise ValueError("Error in group by entity \n" + format_tb(err.__traceback__)[0] + err.args[0] + "\nEnd of error message.") from None
-
- return outputFile
-
-
-def plot_to_figure(grouped):
- fig = plt.figure()
- plt.bar(x=list(grouped.keys()), height=list(grouped.values()))
- plt.margins(0.2)
- plt.subplots_adjust(bottom=0.4)
- plt.xticks(rotation=90)
- return fig
-
-
-def ner(text):
- raw = pipe(text)
- ner_content = {
- "text": text,
- "entities": [
- {
- "entity": x["entity_group"],
- "word": x["word"],
- "score": x["score"],
- "start": x["start"],
- "end": x["end"],
- }
- for x in raw
- ],
- }
-
- outputFile = group_by_entity(raw)
- label = EXAMPLES.get(text, "Unknown")
- outputDataframe = pd.read_csv(outputFile)
- return (ner_content, outputDataframe, outputFile)
-
-demo = gr.Blocks()
-with demo:
- gr.Markdown(
- """
- # 🩺⚕️NLP Clinical Ontology Biomedical NER
- """
- )
- input = gr.Textbox(label="Note text", value="")
-
- with gr.Tab("Biomedical Entity Recognition"):
- output=[
- gr.HighlightedText(label="NER", combine_adjacent=True),
- #gr.JSON(label="Entity Counts"),
- #gr.Label(label="Rating"),
- #gr.Plot(label="Bar"),
- gr.Dataframe(label="Dataframe"),
- gr.File(label="File"),
- ]
- examples=list(EXAMPLES.keys())
- gr.Examples(examples, inputs=input)
- input.change(fn=ner, inputs=input, outputs=output)
-
- with gr.Tab("Clinical Terminology Resolution"):
- with gr.Row(variant="compact"):
- btnLOINC = gr.Button("LOINC")
- btnPanels = gr.Button("Panels")
- btnSNOMED = gr.Button("SNOMED")
- btnOMS = gr.Button("OMS")
- btnICD10 = gr.Button("ICD10")
-
- examples=list(EXAMPLES.keys())
- gr.Examples(examples, inputs=input)
- input.change(fn=ner, inputs=input, outputs=output)
-#layout="vertical"
-demo.launch(debug=True)
diff --git a/spaces/awacke1/Easy-Button-Zero-Shot-Text-Classifier-facebook-bart-large-mnli/README.md b/spaces/awacke1/Easy-Button-Zero-Shot-Text-Classifier-facebook-bart-large-mnli/README.md
deleted file mode 100644
index b06e014bbef8415f4bd44a4dc0380211ececd4b9..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Easy-Button-Zero-Shot-Text-Classifier-facebook-bart-large-mnli/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Easy Button Zero Shot Text Classifier Facebook Bart Large Mnli
-emoji: 👀
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/awacke1/Git-GPG-Git-Actions-01-GraphViz/README.md b/spaces/awacke1/Git-GPG-Git-Actions-01-GraphViz/README.md
deleted file mode 100644
index d4955700781a662662cf8137cb09d523d285b11f..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Git-GPG-Git-Actions-01-GraphViz/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: 📈🩺Graph-Survey-Assess-Plan-Streamlit
-emoji: 📈🩺
-colorFrom: pink
-colorTo: red
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/awacke1/HTML5-Aframe-3dMap-Flight/README.md b/spaces/awacke1/HTML5-Aframe-3dMap-Flight/README.md
deleted file mode 100644
index 63d8323d8f0890522fa94a10eeeb0c317f9b93f0..0000000000000000000000000000000000000000
--- a/spaces/awacke1/HTML5-Aframe-3dMap-Flight/README.md
+++ /dev/null
@@ -1,52 +0,0 @@
----
-title: HTML5-3D-VR-Aframe-Map-Land
-emoji: 🗺️VR🏞️
-colorFrom: blue
-colorTo: green
-sdk: static
-pinned: false
-license: mit
----
-
-🏷️ **Title:** HTML5-3D-VR-Aframe-Map 📚3D-VR
-
-📋 **Description:** This is a fun 📚3D-VR simulator that shows a map 🗺️ with motion controls ⌨️ of the WASD keyboard. You can explore a 3D landscape 🏞️ using Aframe.
-
-🧐 **Details:**
-
-- **HTML5:** Refers to the version of the HTML (Hypertext Markup Language) used to create the web page on which the 3D-VR-Aframe-Map is hosted.
-
-- **3D:** Refers to the three-dimensional nature of the map in the 3D-VR-Aframe-Map simulator.
-
-- **VR:** Refers to the virtual reality aspect of the 3D-VR-Aframe-Map simulator. Users can immerse themselves in the virtual environment and interact with it using VR headsets.
-
-- **Aframe:** Refers to the web framework used to create the 3D-VR-Aframe-Map simulator. Aframe is a popular framework for creating virtual reality experiences on the web.
-
-- **Map:** Refers to the representation of geographic or spatial data in a visual form. In the 3D-VR-Aframe-Map simulator, users can explore a 3D landscape using motion controls and a map interface.
-
-💻 **Code Snippet:**
-
-```html
-
-
- HTML5-3D-VR-Aframe-Map 📚3D-VR
-
-
-
-
-
-
-
-```
-
-🔑 Acronyms:
-
-HTML: Hypertext Markup Language, a coding language used to create web pages.
-VR: Virtual Reality, an immersive experience that simulates a real environment.
-Aframe: A web framework used to create virtual reality experiences on the web.
-WASD: A set of four keyboard keys that are commonly used in video games for motion controls.
\ No newline at end of file
diff --git a/spaces/awacke1/PromptSuperHeroImageGenerator/README.md b/spaces/awacke1/PromptSuperHeroImageGenerator/README.md
deleted file mode 100644
index 6b9ab4319eab1c82ffc265646804fa9cd70202c7..0000000000000000000000000000000000000000
--- a/spaces/awacke1/PromptSuperHeroImageGenerator/README.md
+++ /dev/null
@@ -1,56 +0,0 @@
----
-title: SuperHero Image Gen w Diffusion Models
-emoji: 🎨🖥️
-colorFrom: grey
-colorTo: blue
-sdk: gradio
-sdk_version: 3.15.0
-app_file: app.py
-pinned: true
----
-# Break down of the code based on CHARMSEW framework:
-
-# Coder: Explanation of the Gradio Python App 🖥️ - The code aims to:
-
-1. Load a list of available models from a text file named models.txt.
-2. Render an interface to accept text input that serves as a prompt for image generation.
-3. Provide a dropdown for selecting a model.
-4. Generate an image based on the entered text and selected model.
-5. Save the generated image and text prompt to disk.
-6. Display the saved images and prompts in the interface.
-
-# Analysis: Keeping Track of Chat History 📊
-In this code, we've done the following steps:
-
-Imported datetime to generate a timestamp.
-Added a function called current_timestamp() that will generate a current timestamp.
-Modified send_it1() to append the chat prompt and model name to a file named using the current timestamp.
-Read this file in the Gradio interface, and display its contents in a textbox.
-
-# Reasoning: File Handling Approach 📜
-Append new data: Using 'a' mode in open to append data.
-Current timestamp: Using datetime to generate a unique timestamp for each operation.
-Exception Handling: A try-except block is used to display a message if the history file is not found.
-
-# Math: File Operations in Algorithm 🧮
-Open file in append mode: O(1)
-Write data to file: O(n) (n = length of string to be written)
-Close file: O(1)
-Reading the history file: O(m) (m = size of the history file)
-
-# STEM: Python File I/O and Gradio Interface 🎓
-Python File I/O: Reading and writing files are crucial tasks in many data manipulation and storage applications.
-Gradio: A Python library for creating customizable UI around your ML models.
-Keywords: File I/O, Gradio, Timestamp, Exception Handling, Data appending
-
-# Extraction: Content Extracted 🗃
-Functionality to generate and use a timestamp is added.
-Functionality to append prompts and model names to a text file is added.
-Steps to read this file and display its content in a Gradio textbox are outlined.
-
-# Writing: Culmination 📝
-The modified code not only unfurls your AI model's talents
-but also inscribes its own journey in a timeless tome,
-uniquely marked by the strokes of time through the mechanism of timestamps.
-A newfound capability that turns ephemeral experiences into a lasting chronicle. 🌟
-
diff --git a/spaces/awacke1/WikipediaProfilerTestforDatasets/style.css b/spaces/awacke1/WikipediaProfilerTestforDatasets/style.css
deleted file mode 100644
index 114adf441e9032febb46bc056b2a8bb651075f0d..0000000000000000000000000000000000000000
--- a/spaces/awacke1/WikipediaProfilerTestforDatasets/style.css
+++ /dev/null
@@ -1,28 +0,0 @@
-body {
- padding: 2rem;
- font-family: -apple-system, BlinkMacSystemFont, "Arial", sans-serif;
-}
-
-h1 {
- font-size: 16px;
- margin-top: 0;
-}
-
-p {
- color: rgb(107, 114, 128);
- font-size: 15px;
- margin-bottom: 10px;
- margin-top: 5px;
-}
-
-.card {
- max-width: 620px;
- margin: 0 auto;
- padding: 16px;
- border: 1px solid lightgray;
- border-radius: 16px;
-}
-
-.card p:last-child {
- margin-bottom: 0;
-}
diff --git a/spaces/awinml/2-qa-earnings-sentencewise/utils/entity_extraction.py b/spaces/awinml/2-qa-earnings-sentencewise/utils/entity_extraction.py
deleted file mode 100644
index cb1ffe6f0cfbea543e0ed90ebe577fed92dccf05..0000000000000000000000000000000000000000
--- a/spaces/awinml/2-qa-earnings-sentencewise/utils/entity_extraction.py
+++ /dev/null
@@ -1,243 +0,0 @@
-import re
-
-from nltk.stem import PorterStemmer, WordNetLemmatizer
-
-# Keyword Extraction
-
-
-def expand_list_of_lists(list_of_lists):
- """
- Expands a list of lists of strings to a list of strings.
- Args:
- list_of_lists: A list of lists of strings.
- Returns:
- A list of strings.
- """
-
- expanded_list = []
- for inner_list in list_of_lists:
- for string in inner_list:
- expanded_list.append(string)
- return expanded_list
-
-
-def keywords_no_companies(texts):
- # Company list (to remove companies from extracted entities)
-
- company_list = [
- "apple",
- "amd",
- "amazon",
- "cisco",
- "google",
- "microsoft",
- "nvidia",
- "asml",
- "intel",
- "micron",
- "aapl",
- "csco",
- "msft",
- "asml",
- "nvda",
- "googl",
- "mu",
- "intc",
- "amzn",
- "amd",
- ]
-
- texts = [text.split(" ") for text in texts]
- texts = expand_list_of_lists(texts)
-
- # Convert all strings to lowercase.
- lower_texts = [text.lower() for text in texts]
- keywords = [text for text in lower_texts if text not in company_list]
- return keywords
-
-
-def all_keywords_combs(texts):
-
- texts = [text.split(" ") for text in texts]
- texts = expand_list_of_lists(texts)
-
- # Convert all strings to lowercase.
- lower_texts = [text.lower() for text in texts]
-
- # Stem the words in each string.
- stemmer = PorterStemmer()
- stem_texts = [stemmer.stem(text) for text in texts]
-
- # Lemmatize the words in each string.
- lemmatizer = WordNetLemmatizer()
- lemm_texts = [lemmatizer.lemmatize(text) for text in texts]
-
- texts.extend(lower_texts)
- texts.extend(stem_texts)
- texts.extend(lemm_texts)
- return texts
-
-
-def extract_keywords(query_text, model):
- prompt = "###Instruction: Identify the key entities that accurately describe the context.\n\nInput:{query_text}\n\n###Response:"
- #prompt = f"###Instruction:Extract the important keywords which describe the context accurately.\n\nInput:{query_text}\n\n###Response:"
- response = model.predict(prompt)
- keywords = response.split(", ")
- keywords = keywords_no_companies(keywords)
- return keywords
-
-
-# Entity Extraction
-
-
-def generate_alpaca_ner_prompt(query):
- prompt = f"""Below is an instruction that describes a task, paired with an input that provides further context. Use the following guidelines to extract the entities representing the Company, Quarter, and Year in the sentence.
-
-### Instruction:
-- The output should be in the form "Company - Value, Quarter - Value, Year - Value".
-- The output should be in the form "Company - None, Quarter - None, Year - None", if no entities are found.
-- Only use entities that exist in the final sentence.
-- If Company cannot be found in the sentence, return "none" for that entity.
-- If Quarter cannot be found in the sentence, return "none" for that entity.
-- If Year cannot be found in the sentence, return "none" for that entity.
-- If there is ambiguity finding the entity, return "none" for that entity.
-
-### Input:
-
-What was discussed regarding Services revenue performance in Apple's Q3 2020 earnings call?
-Company - Apple, Quarter - Q3, Year - 2020
-
-How has the growth in Q1 been for the consumer market as seen by AMD?
-Company - AMD, Quarter - Q1, Year - none
-
-What was the long term view on GOOGL's cloud business growth as discussed in their earnings call?
-Company - Google, Quarter - none, Year - none
-
-What is Nvidia's outlook in the data center business in Q3 2020?
-Company - Nvidia, Quarter - Q3, Year - 2020
-
-What are the expansion plans of Amazon in the Asia Pacific region as discussed in their earnings call?
-Company - Amazon, Quarter - none, Year - none
-
-What did the Analysts ask about CSCO's cybersecurity business in the earnings call in 2016?
-Company - Cisco, Quarter - none, Year - 2016
-
-
-{query}
-### Response:"""
- return prompt
-
-
-def format_entities_flan_alpaca(values):
- """
- Extracts the text for each entity from the output generated by the
- Flan-Alpaca model.
- """
- try:
- company_string, quarter_string, year_string = values.split(", ")
- except:
- company = None
- quarter = None
- year = None
- try:
- company = company_string.split(" - ")[1].lower()
- company = None if company.lower() == "none" else company
- except:
- company = None
- try:
- quarter = quarter_string.split(" - ")[1]
- quarter = None if quarter.lower() == "none" else quarter
-
- except:
- quarter = None
- try:
- year = year_string.split(" - ")[1]
- year = None if year.lower() == "none" else year
-
- except:
- year = None
-
- print((company, quarter, year))
- return company, quarter, year
-
-
-def extract_quarter_year(string):
- # Extract year from string
- year_match = re.search(r"\d{4}", string)
- if year_match:
- year = year_match.group()
- else:
- year = None
-
- # Extract quarter from string
- quarter_match = re.search(r"Q\d", string)
- if quarter_match:
- quarter = "Q" + quarter_match.group()[1]
- else:
- quarter = None
-
- return quarter, year
-
-
-def extract_ticker_spacy(query, model):
- doc = model(query)
- entities = {ent.label_: ent.text for ent in doc.ents}
- print(entities.keys())
- if "ORG" in entities.keys():
- company = entities["ORG"].lower()
- else:
- company = None
- return company
-
-
-def clean_entities(company, quarter, year):
- company_ticker_map = {
- "apple": "AAPL",
- "amd": "AMD",
- "amazon": "AMZN",
- "cisco": "CSCO",
- "google": "GOOGL",
- "microsoft": "MSFT",
- "nvidia": "NVDA",
- "asml": "ASML",
- "intel": "INTC",
- "micron": "MU",
- }
-
- ticker_choice = [
- "AAPL",
- "CSCO",
- "MSFT",
- "ASML",
- "NVDA",
- "GOOGL",
- "MU",
- "INTC",
- "AMZN",
- "AMD",
- ]
- year_choice = ["2020", "2019", "2018", "2017", "2016", "All"]
- quarter_choice = ["Q1", "Q2", "Q3", "Q4", "All"]
- if company is not None:
- if company in company_ticker_map.keys():
- ticker = company_ticker_map[company]
- ticker_index = ticker_choice.index(ticker)
- else:
- ticker_index = 0
- else:
- ticker_index = 0
- if quarter is not None:
- if quarter in quarter_choice:
- quarter_index = quarter_choice.index(quarter)
- else:
- quarter_index = len(quarter_choice) - 1
- else:
- quarter_index = len(quarter_choice) - 1
- if year is not None:
- if year in year_choice:
- year_index = year_choice.index(year)
- else:
- year_index = len(year_choice) - 1
- else:
- year_index = len(year_choice) - 1
- return ticker_index, quarter_index, year_index
diff --git a/spaces/awsaf49/gcvit-tf/gcvit/utils/__init__.py b/spaces/awsaf49/gcvit-tf/gcvit/utils/__init__.py
deleted file mode 100644
index 3d06d536216fb17ca67b459e652d955261608d25..0000000000000000000000000000000000000000
--- a/spaces/awsaf49/gcvit-tf/gcvit/utils/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .gradcam import process_image, get_gradcam_model, get_gradcam_prediction
\ No newline at end of file
diff --git a/spaces/banana-projects/web3d/node_modules/three/examples/js/libs/ammo.js b/spaces/banana-projects/web3d/node_modules/three/examples/js/libs/ammo.js
deleted file mode 100644
index 24cd1aa99bcbccb68c3c53fc63e49316f62515cb..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/examples/js/libs/ammo.js
+++ /dev/null
@@ -1,31 +0,0 @@
-
-// This is ammo.js, a port of Bullet Physics to JavaScript. zlib licensed.
-var AmmoLib = function(Module) {
- Module = Module || {};
-
-var Module;if(!Module)Module=(typeof AmmoLib!=="undefined"?AmmoLib:null)||{};var moduleOverrides={};for(var key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;if(Module["ENVIRONMENT"]){if(Module["ENVIRONMENT"]==="WEB"){ENVIRONMENT_IS_WEB=true}else if(Module["ENVIRONMENT"]==="WORKER"){ENVIRONMENT_IS_WORKER=true}else if(Module["ENVIRONMENT"]==="NODE"){ENVIRONMENT_IS_NODE=true}else if(Module["ENVIRONMENT"]==="SHELL"){ENVIRONMENT_IS_SHELL=true}else{throw new Error("The provided Module['ENVIRONMENT'] value is not valid. It must be one of: WEB|WORKER|NODE|SHELL.")}}else{ENVIRONMENT_IS_WEB=typeof window==="object";ENVIRONMENT_IS_WORKER=typeof importScripts==="function";ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof require==="function"&&!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_WORKER;ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER}if(ENVIRONMENT_IS_NODE){if(!Module["print"])Module["print"]=console.log;if(!Module["printErr"])Module["printErr"]=console.warn;var nodeFS;var nodePath;Module["read"]=function read(filename,binary){if(!nodeFS)nodeFS=require("fs");if(!nodePath)nodePath=require("path");filename=nodePath["normalize"](filename);var ret=nodeFS["readFileSync"](filename);if(!ret&&filename!=nodePath["resolve"](filename)){filename=path.join(__dirname,"..","src",filename);ret=nodeFS["readFileSync"](filename)}if(ret&&!binary)ret=ret.toString();return ret};Module["readBinary"]=function readBinary(filename){var ret=Module["read"](filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};Module["load"]=function load(f){globalEval(read(f))};if(!Module["thisProgram"]){if(process["argv"].length>1){Module["thisProgram"]=process["argv"][1].replace(/\\/g,"/")}else{Module["thisProgram"]="unknown-program"}}Module["arguments"]=process["argv"].slice(2);if(typeof module!=="undefined"){module["exports"]=Module}process["on"]("uncaughtException",(function(ex){if(!(ex instanceof ExitStatus)){throw ex}}));Module["inspect"]=(function(){return"[Emscripten Module object]"})}else if(ENVIRONMENT_IS_SHELL){if(!Module["print"])Module["print"]=print;if(typeof printErr!="undefined")Module["printErr"]=printErr;if(typeof read!="undefined"){Module["read"]=read}else{Module["read"]=function read(){throw"no read() available (jsc?)"}}Module["readBinary"]=function readBinary(f){if(typeof readbuffer==="function"){return new Uint8Array(readbuffer(f))}var data=read(f,"binary");assert(typeof data==="object");return data};if(typeof scriptArgs!="undefined"){Module["arguments"]=scriptArgs}else if(typeof arguments!="undefined"){Module["arguments"]=arguments}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){Module["read"]=function read(url){var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.send(null);return xhr.responseText};Module["readAsync"]=function readAsync(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open("GET",url,true);xhr.responseType="arraybuffer";xhr.onload=function xhr_onload(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response)}else{onerror()}};xhr.onerror=onerror;xhr.send(null)};if(typeof arguments!="undefined"){Module["arguments"]=arguments}if(typeof console!=="undefined"){if(!Module["print"])Module["print"]=function print(x){console.log(x)};if(!Module["printErr"])Module["printErr"]=function printErr(x){console.warn(x)}}else{var TRY_USE_DUMP=false;if(!Module["print"])Module["print"]=TRY_USE_DUMP&&typeof dump!=="undefined"?(function(x){dump(x)}):(function(x){})}if(ENVIRONMENT_IS_WORKER){Module["load"]=importScripts}if(typeof Module["setWindowTitle"]==="undefined"){Module["setWindowTitle"]=(function(title){document.title=title})}}else{throw"Unknown runtime environment. Where are we?"}function globalEval(x){abort("NO_DYNAMIC_EXECUTION=1 was set, cannot eval")}if(!Module["load"]&&Module["read"]){Module["load"]=function load(f){globalEval(Module["read"](f))}}if(!Module["print"]){Module["print"]=(function(){})}if(!Module["printErr"]){Module["printErr"]=Module["print"]}if(!Module["arguments"]){Module["arguments"]=[]}if(!Module["thisProgram"]){Module["thisProgram"]="./this.program"}Module.print=Module["print"];Module.printErr=Module["printErr"];Module["preRun"]=[];Module["postRun"]=[];for(var key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=undefined;var Runtime={setTempRet0:(function(value){tempRet0=value}),getTempRet0:(function(){return tempRet0}),stackSave:(function(){return STACKTOP}),stackRestore:(function(stackTop){STACKTOP=stackTop}),getNativeTypeSize:(function(type){switch(type){case"i1":case"i8":return 1;case"i16":return 2;case"i32":return 4;case"i64":return 8;case"float":return 4;case"double":return 8;default:{if(type[type.length-1]==="*"){return Runtime.QUANTUM_SIZE}else if(type[0]==="i"){var bits=parseInt(type.substr(1));assert(bits%8===0);return bits/8}else{return 0}}}}),getNativeFieldSize:(function(type){return Math.max(Runtime.getNativeTypeSize(type),Runtime.QUANTUM_SIZE)}),STACK_ALIGN:16,prepVararg:(function(ptr,type){if(type==="double"||type==="i64"){if(ptr&7){assert((ptr&7)===4);ptr+=4}}else{assert((ptr&3)===0)}return ptr}),getAlignSize:(function(type,size,vararg){if(!vararg&&(type=="i64"||type=="double"))return 8;if(!type)return Math.min(size,8);return Math.min(size||(type?Runtime.getNativeFieldSize(type):0),Runtime.QUANTUM_SIZE)}),dynCall:(function(sig,ptr,args){if(args&&args.length){if(!args.splice)args=Array.prototype.slice.call(args);args.splice(0,0,ptr);return Module["dynCall_"+sig].apply(null,args)}else{return Module["dynCall_"+sig].call(null,ptr)}}),functionPointers:[],addFunction:(function(func){for(var i=0;i=TOTAL_MEMORY){var success=enlargeMemory();if(!success){DYNAMICTOP=ret;return 0}}return ret}),alignMemory:(function(size,quantum){var ret=size=Math.ceil(size/(quantum?quantum:16))*(quantum?quantum:16);return ret}),makeBigInt:(function(low,high,unsigned){var ret=unsigned?+(low>>>0)+ +(high>>>0)*+4294967296:+(low>>>0)+ +(high|0)*+4294967296;return ret}),GLOBAL_BASE:8,QUANTUM_SIZE:4,__dummy__:0};var ABORT=false;var EXITSTATUS=0;function assert(condition,text){if(!condition){abort("Assertion failed: "+text)}}function getCFunc(ident){var func=Module["_"+ident];if(!func){abort("NO_DYNAMIC_EXECUTION=1 was set, cannot eval")}assert(func,"Cannot call unknown function "+ident+" (perhaps LLVM optimizations or closure removed it?)");return func}var ccall;((function(){var JSfuncs={"stackSave":(function(){Runtime.stackSave()}),"stackRestore":(function(){Runtime.stackRestore()}),"arrayToC":(function(arr){var ret=Runtime.stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}),"stringToC":(function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){ret=Runtime.stackAlloc((str.length<<2)+1);writeStringToMemory(str,ret)}return ret})};var toC={"string":JSfuncs["stringToC"],"array":JSfuncs["arrayToC"]};ccall=function ccallFunc(ident,returnType,argTypes,args,opts){var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i>0]=value;break;case"i8":HEAP8[ptr>>0]=value;break;case"i16":HEAP16[ptr>>1]=value;break;case"i32":HEAP32[ptr>>2]=value;break;case"i64":tempI64=[value>>>0,(tempDouble=value,+Math_abs(tempDouble)>=+1?tempDouble>+0?(Math_min(+Math_floor(tempDouble/+4294967296),+4294967295)|0)>>>0:~~+Math_ceil((tempDouble- +(~~tempDouble>>>0))/+4294967296)>>>0:0)],HEAP32[ptr>>2]=tempI64[0],HEAP32[ptr+4>>2]=tempI64[1];break;case"float":HEAPF32[ptr>>2]=value;break;case"double":HEAPF64[ptr>>3]=value;break;default:abort("invalid type for setValue: "+type)}}function getValue(ptr,type,noSafe){type=type||"i8";if(type.charAt(type.length-1)==="*")type="i32";switch(type){case"i1":return HEAP8[ptr>>0];case"i8":return HEAP8[ptr>>0];case"i16":return HEAP16[ptr>>1];case"i32":return HEAP32[ptr>>2];case"i64":return HEAP32[ptr>>2];case"float":return HEAPF32[ptr>>2];case"double":return HEAPF64[ptr>>3];default:abort("invalid type for setValue: "+type)}return null}var ALLOC_NORMAL=0;var ALLOC_STATIC=2;var ALLOC_DYNAMIC=3;var ALLOC_NONE=4;function allocate(slab,types,allocator,ptr){var zeroinit,size;if(typeof slab==="number"){zeroinit=true;size=slab}else{zeroinit=false;size=slab.length}var singleType=typeof types==="string"?types:null;var ret;if(allocator==ALLOC_NONE){ret=ptr}else{ret=[typeof _malloc==="function"?_malloc:Runtime.staticAlloc,Runtime.stackAlloc,Runtime.staticAlloc,Runtime.dynamicAlloc][allocator===undefined?ALLOC_STATIC:allocator](Math.max(size,singleType?1:types.length))}if(zeroinit){var ptr=ret,stop;assert((ret&3)==0);stop=ret+(size&~3);for(;ptr>2]=0}stop=ret+size;while(ptr>0]=0}return ret}if(singleType==="i8"){if(slab.subarray||slab.slice){HEAPU8.set(slab,ret)}else{HEAPU8.set(new Uint8Array(slab),ret)}return ret}var i=0,type,typeSize,previousType;while(i>0];hasUtf|=t;if(t==0&&!length)break;i++;if(length&&i==length)break}if(!length)length=i;var ret="";if(hasUtf<128){var MAX_CHUNK=1024;var curr;while(length>0){curr=String.fromCharCode.apply(String,HEAPU8.subarray(ptr,ptr+Math.min(length,MAX_CHUNK)));ret=ret?ret+curr:curr;ptr+=MAX_CHUNK;length-=MAX_CHUNK}return ret}return Module["UTF8ToString"](ptr)}function UTF8ArrayToString(u8Array,idx){var u0,u1,u2,u3,u4,u5;var str="";while(1){u0=u8Array[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}u1=u8Array[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}u2=u8Array[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u3=u8Array[idx++]&63;if((u0&248)==240){u0=(u0&7)<<18|u1<<12|u2<<6|u3}else{u4=u8Array[idx++]&63;if((u0&252)==248){u0=(u0&3)<<24|u1<<18|u2<<12|u3<<6|u4}else{u5=u8Array[idx++]&63;u0=(u0&1)<<30|u1<<24|u2<<18|u3<<12|u4<<6|u5}}}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}function stringToUTF8Array(str,outU8Array,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127){if(outIdx>=endIdx)break;outU8Array[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;outU8Array[outIdx++]=192|u>>6;outU8Array[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;outU8Array[outIdx++]=224|u>>12;outU8Array[outIdx++]=128|u>>6&63;outU8Array[outIdx++]=128|u&63}else if(u<=2097151){if(outIdx+3>=endIdx)break;outU8Array[outIdx++]=240|u>>18;outU8Array[outIdx++]=128|u>>12&63;outU8Array[outIdx++]=128|u>>6&63;outU8Array[outIdx++]=128|u&63}else if(u<=67108863){if(outIdx+4>=endIdx)break;outU8Array[outIdx++]=248|u>>24;outU8Array[outIdx++]=128|u>>18&63;outU8Array[outIdx++]=128|u>>12&63;outU8Array[outIdx++]=128|u>>6&63;outU8Array[outIdx++]=128|u&63}else{if(outIdx+5>=endIdx)break;outU8Array[outIdx++]=252|u>>30;outU8Array[outIdx++]=128|u>>24&63;outU8Array[outIdx++]=128|u>>18&63;outU8Array[outIdx++]=128|u>>12&63;outU8Array[outIdx++]=128|u>>6&63;outU8Array[outIdx++]=128|u&63}}outU8Array[outIdx]=0;return outIdx-startIdx}function lengthBytesUTF8(str){var len=0;for(var i=0;i=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127){++len}else if(u<=2047){len+=2}else if(u<=65535){len+=3}else if(u<=2097151){len+=4}else if(u<=67108863){len+=5}else{len+=6}}return len}function demangle(func){var hasLibcxxabi=!!Module["___cxa_demangle"];if(hasLibcxxabi){try{var buf=_malloc(func.length);writeStringToMemory(func.substr(1),buf);var status=_malloc(4);var ret=Module["___cxa_demangle"](buf,0,0,status);if(getValue(status,"i32")===0&&ret){return Pointer_stringify(ret)}}catch(e){return func}finally{if(buf)_free(buf);if(status)_free(status);if(ret)_free(ret)}}Runtime.warnOnce("warning: build with -s DEMANGLE_SUPPORT=1 to link in libcxxabi demangling");return func}function demangleAll(text){return text.replace(/__Z[\w\d_]+/g,(function(x){var y=demangle(x);return x===y?x:x+" ["+y+"]"}))}function jsStackTrace(){var err=new Error;if(!err.stack){try{throw new Error(0)}catch(e){err=e}if(!err.stack){return"(no stack trace available)"}}return err.stack.toString()}function stackTrace(){return demangleAll(jsStackTrace())}var PAGE_SIZE=4096;function alignMemoryPage(x){if(x%4096>0){x+=4096-x%4096}return x}var HEAP;var buffer;var HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferViews(){Module["HEAP8"]=HEAP8=new Int8Array(buffer);Module["HEAP16"]=HEAP16=new Int16Array(buffer);Module["HEAP32"]=HEAP32=new Int32Array(buffer);Module["HEAPU8"]=HEAPU8=new Uint8Array(buffer);Module["HEAPU16"]=HEAPU16=new Uint16Array(buffer);Module["HEAPU32"]=HEAPU32=new Uint32Array(buffer);Module["HEAPF32"]=HEAPF32=new Float32Array(buffer);Module["HEAPF64"]=HEAPF64=new Float64Array(buffer)}var STATIC_BASE=0,STATICTOP=0,staticSealed=false;var STACK_BASE=0,STACKTOP=0,STACK_MAX=0;var DYNAMIC_BASE=0,DYNAMICTOP=0;function abortOnCannotGrowMemory(){abort("Cannot enlarge memory arrays. Either (1) compile with -s TOTAL_MEMORY=X with X higher than the current value "+TOTAL_MEMORY+", (2) compile with -s ALLOW_MEMORY_GROWTH=1 which adjusts the size at runtime but prevents some optimizations, (3) set Module.TOTAL_MEMORY to a higher value before the program runs, or if you want malloc to return NULL (0) instead of this abort, compile with -s ABORTING_MALLOC=0 ")}function enlargeMemory(){abortOnCannotGrowMemory()}var TOTAL_STACK=Module["TOTAL_STACK"]||5242880;var TOTAL_MEMORY=Module["TOTAL_MEMORY"]||67108864;var totalMemory=64*1024;while(totalMemory0){var callback=callbacks.shift();if(typeof callback=="function"){callback();continue}var func=callback.func;if(typeof func==="number"){if(callback.arg===undefined){Runtime.dynCall("v",func)}else{Runtime.dynCall("vi",func,[callback.arg])}}else{func(callback.arg===undefined?null:callback.arg)}}}var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;function preRun(){if(Module["preRun"]){if(typeof Module["preRun"]=="function")Module["preRun"]=[Module["preRun"]];while(Module["preRun"].length){addOnPreRun(Module["preRun"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function ensureInitRuntime(){if(runtimeInitialized)return;runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){callRuntimeCallbacks(__ATEXIT__);runtimeExited=true}function postRun(){if(Module["postRun"]){if(typeof Module["postRun"]=="function")Module["postRun"]=[Module["postRun"]];while(Module["postRun"].length){addOnPostRun(Module["postRun"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPreMain(cb){__ATMAIN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}function intArrayFromString(stringy,dontAddNull,length){var len=length>0?length:lengthBytesUTF8(stringy)+1;var u8array=new Array(len);var numBytesWritten=stringToUTF8Array(stringy,u8array,0,u8array.length);if(dontAddNull)u8array.length=numBytesWritten;return u8array}function writeStringToMemory(string,buffer,dontAddNull){var array=intArrayFromString(string,dontAddNull);var i=0;while(i>0]=chr;i=i+1}}function writeArrayToMemory(array,buffer){for(var i=0;i>0]=array[i]}}function writeAsciiToMemory(str,buffer,dontAddNull){for(var i=0;i>0]=str.charCodeAt(i)}if(!dontAddNull)HEAP8[buffer>>0]=0}if(!Math["imul"]||Math["imul"](4294967295,5)!==-5)Math["imul"]=function imul(a,b){var ah=a>>>16;var al=a&65535;var bh=b>>>16;var bl=b&65535;return al*bl+(ah*bl+al*bh<<16)|0};Math.imul=Math["imul"];if(!Math["clz32"])Math["clz32"]=(function(x){x=x>>>0;for(var i=0;i<32;i++){if(x&1<<31-i)return i}return 32});Math.clz32=Math["clz32"];var Math_abs=Math.abs;var Math_cos=Math.cos;var Math_sin=Math.sin;var Math_tan=Math.tan;var Math_acos=Math.acos;var Math_asin=Math.asin;var Math_atan=Math.atan;var Math_atan2=Math.atan2;var Math_exp=Math.exp;var Math_log=Math.log;var Math_sqrt=Math.sqrt;var Math_ceil=Math.ceil;var Math_floor=Math.floor;var Math_pow=Math.pow;var Math_imul=Math.imul;var Math_fround=Math.fround;var Math_min=Math.min;var Math_clz32=Math.clz32;var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;Module["preloadedImages"]={};Module["preloadedAudios"]={};var ASM_CONSTS=[(function($0,$1,$2,$3,$4,$5,$6,$7){{var self=Module["getCache"](Module["ConcreteContactResultCallback"])[$0];if(!self.hasOwnProperty("addSingleResult"))throw"a JSImplementation must implement all functions, you forgot ConcreteContactResultCallback::addSingleResult.";return self["addSingleResult"]($1,$2,$3,$4,$5,$6,$7)}})];function _emscripten_asm_const_diiiiiiii(code,a0,a1,a2,a3,a4,a5,a6,a7){return ASM_CONSTS[code](a0,a1,a2,a3,a4,a5,a6,a7)}STATIC_BASE=8;STATICTOP=STATIC_BASE+26272;__ATINIT__.push({func:(function(){__GLOBAL__sub_I_btQuickprof_cpp()})});allocate([88,37,0,0,220,37,0,0,128,37,0,0,7,38,0,0,8,0,0,0,0,0,0,0,88,37,0,0,57,38,0,0,88,37,0,0,78,38,0,0,128,37,0,0,94,38,0,0,40,0,0,0,0,0,0,0,88,37,0,0,117,38,0,0,128,37,0,0,145,38,0,0,64,0,0,0,0,0,0,0,88,37,0,0,167,38,0,0,128,37,0,0,207,38,0,0,88,0,0,0,0,0,0,0,88,37,0,0,254,38,0,0,128,37,0,0,42,39,0,0,112,0,0,0,0,0,0,0,128,37,0,0,114,40,0,0,152,0,0,0,0,0,0,0,88,37,0,0,140,40,0,0,128,37,0,0,159,40,0,0,0,4,0,0,0,0,0,0,128,37,0,0,203,40,0,0,192,0,0,0,0,0,0,0,88,37,0,0,248,40,0,0,128,37,0,0,25,41,0,0,192,0,0,0,0,0,0,0,128,37,0,0,71,41,0,0,192,0,0,0,0,0,0,0,128,37,0,0,123,41,0,0,192,0,0,0,0,0,0,0,128,37,0,0,182,41,0,0,176,3,0,0,0,0,0,0,128,37,0,0,136,42,0,0,24,1,0,0,0,0,0,0,88,37,0,0,168,42,0,0,88,37,0,0,187,42,0,0,128,37,0,0,208,42,0,0,32,1,0,0,0,0,0,0,128,37,0,0,230,42,0,0,48,8,0,0,0,0,0,0,128,37,0,0,60,43,0,0,24,1,0,0,0,0,0,0,128,37,0,0,95,43,0,0,104,1,0,0,0,0,0,0,128,37,0,0,129,43,0,0,24,1,0,0,0,0,0,0,128,37,0,0,162,43,0,0,176,7,0,0,0,0,0,0,128,37,0,0,230,43,0,0,104,1,0,0,0,0,0,0,128,37,0,0,8,44,0,0,24,1,0,0,0,0,0,0,128,37,0,0,42,44,0,0,184,1,0,0,0,0,0,0,88,37,0,0,74,44,0,0,128,37,0,0,97,44,0,0,184,1,0,0,0,0,0,0,128,37,0,0,135,44,0,0,208,7,0,0,0,0,0,0,128,37,0,0,164,44,0,0,208,7,0,0,0,0,0,0,88,37,0,0,68,45,0,0,128,37,0,0,97,45,0,0,120,7,0,0,0,0,0,0,128,37,0,0,124,45,0,0,96,2,0,0,0,0,0,0,128,37,0,0,159,45,0,0,40,2,0,0,0,0,0,0,128,37,0,0,185,45,0,0,56,2,0,0,0,0,0,0,88,37,0,0,211,45,0,0,128,37,0,0,37,46,0,0,184,1,0,0,0,0,0,0,128,37,0,0,68,46,0,0,176,3,0,0,0,0,0,0,128,37,0,0,103,46,0,0,112,2,0,0,0,0,0,0,128,37,0,0,129,46,0,0,40,5,0,0,0,0,0,0,128,37,0,0,36,47,0,0,16,0,0,0,0,0,0,0,128,37,0,0,53,48,0,0,160,2,0,0,0,0,0,0,88,37,0,0,83,48,0,0,128,37,0,0,129,48,0,0,184,2,0,0,0,0,0,0,188,37,0,0,155,48,0,0,0,0,0,0,1,0,0,0,208,2,0,0,2,4,0,0,88,37,0,0,175,48,0,0,128,37,0,0,219,48,0,0,168,2,0,0,0,0,0,0,128,37,0,0,29,49,0,0,184,2,0,0,0,0,0,0,128,37,0,0,115,49,0,0,184,2,0,0,0,0,0,0,128,37,0,0,159,49,0,0,184,2,0,0,0,0,0,0,128,37,0,0,209,49,0,0,184,2,0,0,0,0,0,0,128,37,0,0,0,50,0,0,56,3,0,0,0,0,0,0,88,37,0,0,38,50,0,0,128,37,0,0,133,50,0,0,80,3,0,0,0,0,0,0,88,37,0,0,152,50,0,0,128,37,0,0,172,50,0,0,32,0,0,0,0,0,0,0,128,37,0,0,200,50,0,0,120,3,0,0,0,0,0,0,128,37,0,0,233,50,0,0,80,3,0,0,0,0,0,0,128,37,0,0,10,51,0,0,16,0,0,0,0,0,0,0,128,37,0,0,56,51,0,0,168,3,0,0,0,0,0,0,88,37,0,0,81,51,0,0,88,37,0,0,96,51,0,0,128,37,0,0,143,51,0,0,176,3,0,0,0,0,0,0,128,37,0,0,159,51,0,0,184,3,0,0,0,0,0,0,128,37,0,0,186,51,0,0,136,9,0,0,0,0,0,0,128,37,0,0,210,51,0,0,248,3,0,0,0,0,0,0,88,37,0,0,236,51,0,0,128,37,0,0,0,52,0,0,16,4,0,0,0,0,0,0,88,37,0,0,34,52,0,0,128,37,0,0,61,52,0,0,192,0,0,0,0,0,0,0,128,37,0,0,111,52,0,0,192,0,0,0,0,0,0,0,128,37,0,0,168,52,0,0,192,0,0,0,0,0,0,0,128,37,0,0,213,52,0,0,192,0,0,0,0,0,0,0,128,37,0,0,10,53,0,0,192,0,0,0,0,0,0,0,128,37,0,0,62,53,0,0,192,0,0,0,0,0,0,0,128,37,0,0,95,53,0,0,192,0,0,0,0,0,0,0,128,37,0,0,144,53,0,0,192,0,0,0,0,0,0,0,128,37,0,0,195,53,0,0,192,0,0,0,0,0,0,0,128,37,0,0,238,53,0,0,192,0,0,0,0,0,0,0,88,37,0,0,30,54,0,0,128,37,0,0,101,54,0,0,184,1,0,0,0,0,0,0,128,37,0,0,135,54,0,0,56,10,0,0,0,0,0,0,128,37,0,0,171,54,0,0,208,7,0,0,0,0,0,0,128,37,0,0,198,54,0,0,208,7,0,0,0,0,0,0,128,37,0,0,100,55,0,0,56,10,0,0,0,0,0,0,128,37,0,0,129,55,0,0,32,5,0,0,0,0,0,0,88,37,0,0,148,55,0,0,88,37,0,0,196,55,0,0,188,37,0,0,189,56,0,0,0,0,0,0,2,0,0,0,208,7,0,0,2,0,0,0,216,7,0,0,2,4,0,0,128,37,0,0,209,56,0,0,40,2,0,0,0,0,0,0,128,37,0,0,231,56,0,0,152,9,0,0,0,0,0,0,128,37,0,0,122,57,0,0,152,9,0,0,0,0,0,0,128,37,0,0,15,58,0,0,24,1,0,0,0,0,0,0,128,37,0,0,141,58,0,0,88,0,0,0,0,0,0,0,128,37,0,0,78,59,0,0,168,9,0,0,0,0,0,0,128,37,0,0,253,59,0,0,168,9,0,0,0,0,0,0,128,37,0,0,194,60,0,0,8,0,0,0,0,0,0,0,128,37,0,0,111,61,0,0,40,2,0,0,0,0,0,0,128,37,0,0,135,61,0,0,56,2,0,0,0,0,0,0,128,37,0,0,161,61,0,0,16,5,0,0,0,0,0,0,128,37,0,0,187,61,0,0,56,10,0,0,0,0,0,0,128,37,0,0,224,61,0,0,192,0,0,0,0,0,0,0,128,37,0,0,8,62,0,0,56,10,0,0,0,0,0,0,128,37,0,0,34,62,0,0,32,5,0,0,0,0,0,0,128,37,0,0,167,62,0,0,32,5,0,0,0,0,0,0,128,37,0,0,52,63,0,0,16,5,0,0,0,0,0,0,128,37,0,0,79,63,0,0,56,10,0,0,0,0,0,0,128,37,0,0,110,63,0,0,24,1,0,0,0,0,0,0,128,37,0,0,135,63,0,0,56,10,0,0,0,0,0,0,128,37,0,0,174,63,0,0,24,1,0,0,0,0,0,0,128,37,0,0,207,63,0,0,152,7,0,0,0,0,0,0,128,37,0,0,23,64,0,0,176,7,0,0,0,0,0,0,128,37,0,0,58,64,0,0,176,6,0,0,0,0,0,0,128,37,0,0,79,64,0,0,176,6,0,0,0,0,0,0,128,37,0,0,100,64,0,0,176,7,0,0,0,0,0,0,128,37,0,0,123,64,0,0,56,7,0,0,0,0,0,0,128,37,0,0,188,64,0,0,16,7,0,0,0,0,0,0,88,37,0,0,42,65,0,0,128,37,0,0,66,65,0,0,16,7,0,0,0,0,0,0,128,37,0,0,170,65,0,0,16,7,0,0,0,0,0,0,128,37,0,0,27,66,0,0,48,8,0,0,0,0,0,0,128,37,0,0,62,66,0,0,216,7,0,0,0,0,0,0,128,37,0,0,164,66,0,0,208,7,0,0,0,0,0,0,128,37,0,0,188,66,0,0,48,8,0,0,0,0,0,0,128,37,0,0,244,66,0,0,176,7,0,0,0,0,0,0,128,37,0,0,14,67,0,0,120,7,0,0,0,0,0,0,88,37,0,0,51,67,0,0,128,37,0,0,91,67,0,0,152,7,0,0,0,0,0,0,128,37,0,0,107,67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tempDoublePtr=STATICTOP;STATICTOP+=16;Module["_i64Subtract"]=_i64Subtract;function ___setErrNo(value){if(Module["___errno_location"])HEAP32[Module["___errno_location"]()>>2]=value;return value}var ERRNO_CODES={EPERM:1,ENOENT:2,ESRCH:3,EINTR:4,EIO:5,ENXIO:6,E2BIG:7,ENOEXEC:8,EBADF:9,ECHILD:10,EAGAIN:11,EWOULDBLOCK:11,ENOMEM:12,EACCES:13,EFAULT:14,ENOTBLK:15,EBUSY:16,EEXIST:17,EXDEV:18,ENODEV:19,ENOTDIR:20,EISDIR:21,EINVAL:22,ENFILE:23,EMFILE:24,ENOTTY:25,ETXTBSY:26,EFBIG:27,ENOSPC:28,ESPIPE:29,EROFS:30,EMLINK:31,EPIPE:32,EDOM:33,ERANGE:34,ENOMSG:42,EIDRM:43,ECHRNG:44,EL2NSYNC:45,EL3HLT:46,EL3RST:47,ELNRNG:48,EUNATCH:49,ENOCSI:50,EL2HLT:51,EDEADLK:35,ENOLCK:37,EBADE:52,EBADR:53,EXFULL:54,ENOANO:55,EBADRQC:56,EBADSLT:57,EDEADLOCK:35,EBFONT:59,ENOSTR:60,ENODATA:61,ETIME:62,ENOSR:63,ENONET:64,ENOPKG:65,EREMOTE:66,ENOLINK:67,EADV:68,ESRMNT:69,ECOMM:70,EPROTO:71,EMULTIHOP:72,EDOTDOT:73,EBADMSG:74,ENOTUNIQ:76,EBADFD:77,EREMCHG:78,ELIBACC:79,ELIBBAD:80,ELIBSCN:81,ELIBMAX:82,ELIBEXEC:83,ENOSYS:38,ENOTEMPTY:39,ENAMETOOLONG:36,ELOOP:40,EOPNOTSUPP:95,EPFNOSUPPORT:96,ECONNRESET:104,ENOBUFS:105,EAFNOSUPPORT:97,EPROTOTYPE:91,ENOTSOCK:88,ENOPROTOOPT:92,ESHUTDOWN:108,ECONNREFUSED:111,EADDRINUSE:98,ECONNABORTED:103,ENETUNREACH:101,ENETDOWN:100,ETIMEDOUT:110,EHOSTDOWN:112,EHOSTUNREACH:113,EINPROGRESS:115,EALREADY:114,EDESTADDRREQ:89,EMSGSIZE:90,EPROTONOSUPPORT:93,ESOCKTNOSUPPORT:94,EADDRNOTAVAIL:99,ENETRESET:102,EISCONN:106,ENOTCONN:107,ETOOMANYREFS:109,EUSERS:87,EDQUOT:122,ESTALE:116,ENOTSUP:95,ENOMEDIUM:123,EILSEQ:84,EOVERFLOW:75,ECANCELED:125,ENOTRECOVERABLE:131,EOWNERDEAD:130,ESTRPIPE:86};function _sysconf(name){switch(name){case 30:return PAGE_SIZE;case 85:return totalMemory/PAGE_SIZE;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 80:case 81:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 79:return 0;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator==="object")return navigator["hardwareConcurrency"]||1;return 1}}___setErrNo(ERRNO_CODES.EINVAL);return-1}function __ZSt18uncaught_exceptionv(){return!!__ZSt18uncaught_exceptionv.uncaught_exception}var EXCEPTIONS={last:0,caught:[],infos:{},deAdjust:(function(adjusted){if(!adjusted||EXCEPTIONS.infos[adjusted])return adjusted;for(var ptr in EXCEPTIONS.infos){var info=EXCEPTIONS.infos[ptr];if(info.adjusted===adjusted){return ptr}}return adjusted}),addRef:(function(ptr){if(!ptr)return;var info=EXCEPTIONS.infos[ptr];info.refcount++}),decRef:(function(ptr){if(!ptr)return;var info=EXCEPTIONS.infos[ptr];assert(info.refcount>0);info.refcount--;if(info.refcount===0){if(info.destructor){Runtime.dynCall("vi",info.destructor,[ptr])}delete EXCEPTIONS.infos[ptr];___cxa_free_exception(ptr)}}),clearRef:(function(ptr){if(!ptr)return;var info=EXCEPTIONS.infos[ptr];info.refcount=0})};function ___resumeException(ptr){if(!EXCEPTIONS.last){EXCEPTIONS.last=ptr}EXCEPTIONS.clearRef(EXCEPTIONS.deAdjust(ptr));throw ptr+" - Exception catching is disabled, this exception cannot be caught. Compile with -s DISABLE_EXCEPTION_CATCHING=0 or DISABLE_EXCEPTION_CATCHING=2 to catch."}function ___cxa_find_matching_catch(){var thrown=EXCEPTIONS.last;if(!thrown){return(asm["setTempRet0"](0),0)|0}var info=EXCEPTIONS.infos[thrown];var throwntype=info.type;if(!throwntype){return(asm["setTempRet0"](0),thrown)|0}var typeArray=Array.prototype.slice.call(arguments);var pointer=Module["___cxa_is_pointer_type"](throwntype);if(!___cxa_find_matching_catch.buffer)___cxa_find_matching_catch.buffer=_malloc(4);HEAP32[___cxa_find_matching_catch.buffer>>2]=thrown;thrown=___cxa_find_matching_catch.buffer;for(var i=0;i>2];info.adjusted=thrown;return(asm["setTempRet0"](typeArray[i]),thrown)|0}}thrown=HEAP32[thrown>>2];return(asm["setTempRet0"](throwntype),thrown)|0}function ___cxa_throw(ptr,type,destructor){EXCEPTIONS.infos[ptr]={ptr:ptr,adjusted:ptr,type:type,destructor:destructor,refcount:0};EXCEPTIONS.last=ptr;if(!("uncaught_exception"in __ZSt18uncaught_exceptionv)){__ZSt18uncaught_exceptionv.uncaught_exception=1}else{__ZSt18uncaught_exceptionv.uncaught_exception++}throw ptr+" - Exception catching is disabled, this exception cannot be caught. Compile with -s DISABLE_EXCEPTION_CATCHING=0 or DISABLE_EXCEPTION_CATCHING=2 to catch."}Module["_memset"]=_memset;function ___gxx_personality_v0(){}Module["_bitshift64Shl"]=_bitshift64Shl;function _abort(){Module["abort"]()}function _pthread_once(ptr,func){if(!_pthread_once.seen)_pthread_once.seen={};if(ptr in _pthread_once.seen)return;Runtime.dynCall("v",func);_pthread_once.seen[ptr]=1}var PTHREAD_SPECIFIC={};function _pthread_getspecific(key){return PTHREAD_SPECIFIC[key]||0}Module["_i64Add"]=_i64Add;var PTHREAD_SPECIFIC_NEXT_KEY=1;function _pthread_key_create(key,destructor){if(key==0){return ERRNO_CODES.EINVAL}HEAP32[key>>2]=PTHREAD_SPECIFIC_NEXT_KEY;PTHREAD_SPECIFIC[PTHREAD_SPECIFIC_NEXT_KEY]=0;PTHREAD_SPECIFIC_NEXT_KEY++;return 0}var _llvm_pow_f32=Math_pow;function _pthread_setspecific(key,value){if(!(key in PTHREAD_SPECIFIC)){return ERRNO_CODES.EINVAL}PTHREAD_SPECIFIC[key]=value;return 0}function _malloc(bytes){var ptr=Runtime.dynamicAlloc(bytes+8);return ptr+8&4294967288}Module["_malloc"]=_malloc;function ___cxa_allocate_exception(size){return _malloc(size)}Module["_bitshift64Ashr"]=_bitshift64Ashr;Module["_bitshift64Lshr"]=_bitshift64Lshr;function ___cxa_pure_virtual(){ABORT=true;throw"Pure virtual function called!"}function _time(ptr){var ret=Date.now()/1e3|0;if(ptr){HEAP32[ptr>>2]=ret}return ret}function _pthread_cleanup_push(routine,arg){__ATEXIT__.push((function(){Runtime.dynCall("vi",routine,[arg])}));_pthread_cleanup_push.level=__ATEXIT__.length}function ___cxa_guard_acquire(variable){if(!HEAP8[variable>>0]){HEAP8[variable>>0]=1;return 1}return 0}function _pthread_cleanup_pop(){assert(_pthread_cleanup_push.level==__ATEXIT__.length,"cannot pop if something else added meanwhile!");__ATEXIT__.pop();_pthread_cleanup_push.level=__ATEXIT__.length}function ___cxa_begin_catch(ptr){__ZSt18uncaught_exceptionv.uncaught_exception--;EXCEPTIONS.caught.push(ptr);EXCEPTIONS.addRef(EXCEPTIONS.deAdjust(ptr));return ptr}function _emscripten_memcpy_big(dest,src,num){HEAPU8.set(HEAPU8.subarray(src,src+num),dest);return dest}Module["_memcpy"]=_memcpy;var SYSCALLS={varargs:0,get:(function(varargs){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret}),getStr:(function(){var ret=Pointer_stringify(SYSCALLS.get());return ret}),get64:(function(){var low=SYSCALLS.get(),high=SYSCALLS.get();if(low>=0)assert(high===0);else assert(high===-1);return low}),getZero:(function(){assert(SYSCALLS.get()===0)})};function ___syscall6(which,varargs){SYSCALLS.varargs=varargs;try{var stream=SYSCALLS.getStreamFromFD();FS.close(stream);return 0}catch(e){if(typeof FS==="undefined"||!(e instanceof FS.ErrnoError))abort(e);return-e.errno}}function _sbrk(bytes){var self=_sbrk;if(!self.called){DYNAMICTOP=alignMemoryPage(DYNAMICTOP);self.called=true;assert(Runtime.dynamicAlloc);self.alloc=Runtime.dynamicAlloc;Runtime.dynamicAlloc=(function(){abort("cannot dynamically allocate, sbrk now has control")})}var ret=DYNAMICTOP;if(bytes!=0){var success=self.alloc(bytes);if(!success)return-1>>>0}return ret}Module["_memmove"]=_memmove;function _gettimeofday(ptr){var now=Date.now();HEAP32[ptr>>2]=now/1e3|0;HEAP32[ptr+4>>2]=now%1e3*1e3|0;return 0}var _llvm_fabs_f32=Math_abs;Module["_llvm_bswap_i32"]=_llvm_bswap_i32;function _llvm_trap(){abort("trap!")}function ___cxa_guard_release(){}function _pthread_self(){return 0}function ___syscall140(which,varargs){SYSCALLS.varargs=varargs;try{var stream=SYSCALLS.getStreamFromFD(),offset_high=SYSCALLS.get(),offset_low=SYSCALLS.get(),result=SYSCALLS.get(),whence=SYSCALLS.get();var offset=offset_low;assert(offset_high===0);FS.llseek(stream,offset,whence);HEAP32[result>>2]=stream.position;if(stream.getdents&&offset===0&&whence===0)stream.getdents=null;return 0}catch(e){if(typeof FS==="undefined"||!(e instanceof FS.ErrnoError))abort(e);return-e.errno}}function ___syscall146(which,varargs){SYSCALLS.varargs=varargs;try{var stream=SYSCALLS.get(),iov=SYSCALLS.get(),iovcnt=SYSCALLS.get();var ret=0;if(!___syscall146.buffer){___syscall146.buffers=[null,[],[]];___syscall146.printChar=(function(stream,curr){var buffer=___syscall146.buffers[stream];assert(buffer);if(curr===0||curr===10){(stream===1?Module["print"]:Module["printErr"])(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}})}for(var i=0;i>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j>2]|0;c[d+128>>2]=q;o=c[a+84>>2]|0;c[d+128+4>>2]=o;m=c[a+100>>2]|0;c[d+128+8>>2]=m;g[d+128+12>>2]=0.0;l=d+128+16|0;t=c[a+72>>2]|0;c[l>>2]=t;s=c[a+88>>2]|0;c[d+128+20>>2]=s;r=c[a+104>>2]|0;c[d+128+24>>2]=r;g[d+128+28>>2]=0.0;j=d+128+32|0;w=c[a+76>>2]|0;c[j>>2]=w;v=c[a+92>>2]|0;c[d+128+36>>2]=v;u=c[a+108>>2]|0;c[d+128+40>>2]=u;g[d+128+44>>2]=0.0;p=-+g[a+116>>2];n=-+g[a+120>>2];h=-+g[a+124>>2];e=(c[k>>2]=w,+g[k>>2])*p;e=e+(c[k>>2]=v,+g[k>>2])*n;e=e+(c[k>>2]=u,+g[k>>2])*h;f=(c[k>>2]=t,+g[k>>2])*p;f=f+(c[k>>2]=s,+g[k>>2])*n;f=f+(c[k>>2]=r,+g[k>>2])*h;p=(c[k>>2]=q,+g[k>>2])*p;n=p+(c[k>>2]=o,+g[k>>2])*n;h=n+(c[k>>2]=m,+g[k>>2])*h;c[d>>2]=c[d+128>>2];c[d+4>>2]=c[d+128+4>>2];c[d+8>>2]=c[d+128+8>>2];c[d+12>>2]=c[d+128+12>>2];c[d+16>>2]=c[l>>2];c[d+16+4>>2]=c[l+4>>2];c[d+16+8>>2]=c[l+8>>2];c[d+16+12>>2]=c[l+12>>2];c[d+32>>2]=c[j>>2];c[d+32+4>>2]=c[j+4>>2];c[d+32+8>>2]=c[j+8>>2];c[d+32+12>>2]=c[j+12>>2];g[d+48>>2]=h;g[d+52>>2]=f;g[d+56>>2]=e;g[d+60>>2]=0.0;dh(d+64|0,d,a+4|0);c[b>>2]=c[d+64>>2];c[b+4>>2]=c[d+64+4>>2];c[b+8>>2]=c[d+64+8>>2];c[b+12>>2]=c[d+64+12>>2];c[b+16>>2]=c[d+64+16>>2];c[b+16+4>>2]=c[d+64+16+4>>2];c[b+16+8>>2]=c[d+64+16+8>>2];c[b+16+12>>2]=c[d+64+16+12>>2];c[b+32>>2]=c[d+64+32>>2];c[b+32+4>>2]=c[d+64+32+4>>2];c[b+32+8>>2]=c[d+64+32+8>>2];c[b+32+12>>2]=c[d+64+32+12>>2];c[b+48>>2]=c[d+64+48>>2];c[b+48+4>>2]=c[d+64+48+4>>2];c[b+48+8>>2]=c[d+64+48+8>>2];c[b+48+12>>2]=c[d+64+48+12>>2];i=d;return}function Ef(a,e,f){a=a|0;e=e|0;f=f|0;var h=0.0,i=0.0,j=0.0,k=0;si(a,e,f)|0;c[e+52>>2]=c[a+552>>2];c[e+56>>2]=c[a+556>>2];c[e+60>>2]=c[a+560>>2];c[e+64>>2]=c[a+564>>2];c[e+68>>2]=c[a+568>>2];c[e+72>>2]=c[a+572>>2];c[e+76>>2]=c[a+576>>2];c[e+80>>2]=c[a+580>>2];c[e+84>>2]=c[a+584>>2];c[e+88>>2]=c[a+588>>2];c[e+92>>2]=c[a+592>>2];c[e+96>>2]=c[a+596>>2];c[e+100>>2]=c[a+600>>2];c[e+104>>2]=c[a+604>>2];c[e+108>>2]=c[a+608>>2];c[e+112>>2]=c[a+612>>2];c[e+116>>2]=c[a+616>>2];c[e+120>>2]=c[a+620>>2];c[e+124>>2]=c[a+624>>2];c[e+128>>2]=c[a+628>>2];c[e+132>>2]=c[a+632>>2];c[e+136>>2]=c[a+636>>2];c[e+140>>2]=c[a+640>>2];c[e+144>>2]=c[a+644>>2];c[e+148>>2]=c[a+648>>2];c[e+152>>2]=c[a+652>>2];c[e+156>>2]=c[a+656>>2];c[e+160>>2]=c[a+660>>2];c[e+164>>2]=c[a+664>>2];c[e+168>>2]=c[a+668>>2];c[e+172>>2]=c[a+672>>2];c[e+176>>2]=c[a+676>>2];f=b[a+736>>1]|0;c[e+184>>2]=f&255;c[e+188>>2]=(f&65535)>>>8&65535;c[e+196>>2]=c[a+684>>2];c[e+192>>2]=c[a+680>>2];c[e+180>>2]=d[a+740>>0];i=+g[a+688>>2];j=+g[a+692>>2];h=+eh(i-j,6.2831854820251465);if(!(h<-3.1415927410125732)){if(h>3.1415927410125732)h=h+-6.2831854820251465}else h=h+6.2831854820251465;g[e+200>>2]=h;h=+eh(i+j,6.2831854820251465);if(h<-3.1415927410125732){j=h+6.2831854820251465;f=e+204|0;g[f>>2]=j;f=a+696|0;f=c[f>>2]|0;k=e+208|0;c[k>>2]=f;k=a+700|0;k=c[k>>2]|0;f=e+212|0;c[f>>2]=k;f=a+704|0;f=c[f>>2]|0;a=e+216|0;c[a>>2]=f;return 12773}if(!(h>3.1415927410125732)){j=h;k=e+204|0;g[k>>2]=j;k=a+696|0;k=c[k>>2]|0;f=e+208|0;c[f>>2]=k;f=a+700|0;f=c[f>>2]|0;k=e+212|0;c[k>>2]=f;a=a+704|0;a=c[a>>2]|0;k=e+216|0;c[k>>2]=a;return 12773}j=h+-6.2831854820251465;k=e+204|0;g[k>>2]=j;k=a+696|0;k=c[k>>2]|0;f=e+208|0;c[f>>2]=k;f=a+700|0;f=c[f>>2]|0;k=e+212|0;c[k>>2]=f;a=a+704|0;a=c[a>>2]|0;k=e+216|0;c[k>>2]=a;return 12773}function Ff(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0;i=c[b+4>>2]|0;if((i|0)==(c[b+8>>2]|0)?(h=i|0?i<<1:1,(i|0)<(h|0)):0){if(!h){e=0;f=i}else{c[6435]=(c[6435]|0)+1;e=yc((h*244|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[b+4>>2]|0}if((f|0)>0){g=0;do{k=e+(g*244|0)|0;j=c[b+12>>2]|0;l=j+(g*244|0)|0;c[k>>2]=c[l>>2];c[k+4>>2]=c[l+4>>2];c[k+8>>2]=c[l+8>>2];c[k+12>>2]=c[l+12>>2];k=e+(g*244|0)+16|0;l=j+(g*244|0)+16|0;c[k>>2]=c[l>>2];c[k+4>>2]=c[l+4>>2];c[k+8>>2]=c[l+8>>2];c[k+12>>2]=c[l+12>>2];k=e+(g*244|0)+32|0;l=j+(g*244|0)+32|0;c[k>>2]=c[l>>2];c[k+4>>2]=c[l+4>>2];c[k+8>>2]=c[l+8>>2];c[k+12>>2]=c[l+12>>2];k=e+(g*244|0)+48|0;l=j+(g*244|0)+48|0;c[k>>2]=c[l>>2];c[k+4>>2]=c[l+4>>2];c[k+8>>2]=c[l+8>>2];c[k+12>>2]=c[l+12>>2];_m(e+(g*244|0)+64|0,j+(g*244|0)+64|0,180)|0;g=g+1|0}while((g|0)!=(f|0))}f=c[b+12>>2]|0;if(f|0){if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=e;c[b+8>>2]=h;e=c[b+4>>2]|0}else e=i;c[b+4>>2]=e+1;l=c[b+12>>2]|0;c[l+(i*244|0)>>2]=c[d>>2];c[l+(i*244|0)+4>>2]=c[d+4>>2];c[l+(i*244|0)+8>>2]=c[d+8>>2];c[l+(i*244|0)+12>>2]=c[d+12>>2];c[l+(i*244|0)+16>>2]=c[d+16>>2];c[l+(i*244|0)+16+4>>2]=c[d+16+4>>2];c[l+(i*244|0)+16+8>>2]=c[d+16+8>>2];c[l+(i*244|0)+16+12>>2]=c[d+16+12>>2];c[l+(i*244|0)+32>>2]=c[d+32>>2];c[l+(i*244|0)+32+4>>2]=c[d+32+4>>2];c[l+(i*244|0)+32+8>>2]=c[d+32+8>>2];c[l+(i*244|0)+32+12>>2]=c[d+32+12>>2];c[l+(i*244|0)+48>>2]=c[d+48>>2];c[l+(i*244|0)+48+4>>2]=c[d+48+4>>2];c[l+(i*244|0)+48+8>>2]=c[d+48+8>>2];c[l+(i*244|0)+48+12>>2]=c[d+48+12>>2];_m(l+(i*244|0)+64|0,d+64|0,180)|0;return (c[b+12>>2]|0)+(i*244|0)|0}function Gf(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,j=0.0,k=0.0,l=0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0;l=i;i=i+64|0;n=+g[a+20>>2];u=+g[a+40>>2];p=+g[a+24>>2];s=+g[a+36>>2];t=+g[a+32>>2];m=+g[a+16>>2];k=+g[a>>2];j=+g[a+4>>2];q=+g[a+8>>2];h=1.0/((n*u-p*s)*k+j*(p*t-u*m)+(s*m-n*t)*q);z=+g[b>>2];y=+g[b+4>>2];A=+g[b+8>>2];x=+g[b+16>>2];w=+g[b+20>>2];v=+g[b+24>>2];r=+g[b+32>>2];o=+g[b+36>>2];f=+g[b+40>>2];g[l+16>>2]=A*(s*m-n*t)*h+(z*(n*u-p*s)*h+y*(p*t-u*m)*h);g[l+16+4>>2]=A*(t*j-s*k)*h+(z*(s*q-u*j)*h+y*(u*k-t*q)*h);g[l+16+8>>2]=A*(n*k-m*j)*h+(z*(p*j-n*q)*h+y*(m*q-p*k)*h);g[l+16+12>>2]=0.0;g[l+16+16>>2]=(n*u-p*s)*h*x+(p*t-u*m)*h*w+(s*m-n*t)*h*v;g[l+16+20>>2]=(s*q-u*j)*h*x+(u*k-t*q)*h*w+(t*j-s*k)*h*v;g[l+16+24>>2]=(p*j-n*q)*h*x+(m*q-p*k)*h*w+(n*k-m*j)*h*v;g[l+16+28>>2]=0.0;g[l+16+32>>2]=(n*u-p*s)*h*r+(p*t-u*m)*h*o+(s*m-n*t)*h*f;g[l+16+36>>2]=(s*q-u*j)*h*r+(u*k-t*q)*h*o+(t*j-s*k)*h*f;g[l+16+40>>2]=(p*j-n*q)*h*r+(m*q-p*k)*h*o+(n*k-m*j)*h*f;g[l+16+44>>2]=0.0;Wg(l+16|0,l);f=+g[l>>2];h=+g[l+4>>2];j=+g[l+8>>2];m=+g[l+12>>2];k=1.0/+O(+(f*f+h*h+j*j+m*m));g[l>>2]=f*k;g[l+4>>2]=h*k;g[l+8>>2]=j*k;g[l+12>>2]=m*k;m=m*k<-1.0?-1.0:m*k;g[e>>2]=+T(+(m>1.0?1.0:m))*2.0;g[d>>2]=f*k;g[d+4>>2]=h*k;g[d+8>>2]=j*k;g[d+12>>2]=0.0;if(f*k*f*k+h*k*h*k+j*k*j*k<1.4210854715202004e-14){c[d>>2]=1065353216;c[d+4>>2]=0;c[d+8>>2]=0;g[d+12>>2]=0.0;i=l;return}else{A=1.0/+O(+(f*k*f*k+h*k*h*k+j*k*j*k));g[d>>2]=f*k*A;g[d+4>>2]=A*h*k;g[d+8>>2]=A*j*k;i=l;return}}function Hf(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0,j=0;i=c[b+12>>2]|0;j=c[b+36>>2]|0;if((i|0)<=(j|0))return;if((i|0)>=(j|0)){do if((c[b+40>>2]|0)<(i|0)){if(!i){d=0;e=j}else{c[6435]=(c[6435]|0)+1;d=yc((i<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+36>>2]|0}f=c[b+44>>2]|0;if((e|0)<=0){if(!f){a[b+48>>0]=1;c[b+44>>2]=d;c[b+40>>2]=i;break}}else{g=0;do{c[d+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(e|0))}if(a[b+48>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[b+48>>0]=1;c[b+44>>2]=d;c[b+40>>2]=i}else d=c[b+44>>2]|0;while(0);Qn(d+(j<<2)|0,0,i-j<<2|0)|0}c[b+36>>2]=i;h=c[b+56>>2]|0;if((i|0)>(h|0)){do if((c[b+60>>2]|0)<(i|0)){if(!i){d=0;e=h}else{c[6435]=(c[6435]|0)+1;d=yc((i<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+56>>2]|0}f=c[b+64>>2]|0;if((e|0)<=0){if(!f){a[b+68>>0]=1;c[b+64>>2]=d;c[b+60>>2]=i;break}}else{g=0;do{c[d+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(e|0))}if(a[b+68>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[b+68>>0]=1;c[b+64>>2]=d;c[b+60>>2]=i}else d=c[b+64>>2]|0;while(0);Qn(d+(h<<2)|0,0,i-h<<2|0)|0}c[b+56>>2]=i;if((i|0)>0){Qn(c[b+44>>2]|0,-1,i<<2|0)|0;Qn(c[b+64>>2]|0,-1,i<<2|0)|0}if((j|0)<=0)return;d=c[b+16>>2]|0;e=c[b+44>>2]|0;f=c[b+64>>2]|0;g=0;do{i=c[(c[d+(g<<4)+4>>2]|0)+12>>2]<<16|c[(c[d+(g<<4)>>2]|0)+12>>2];i=(i+~(i<<15)>>10^i+~(i<<15))*9|0;i=e+((((i>>6^i)+~((i>>6^i)<<11)>>16^(i>>6^i)+~((i>>6^i)<<11))&(c[b+12>>2]|0)+-1)<<2)|0;c[f+(g<<2)>>2]=c[i>>2];c[i>>2]=g;g=g+1|0}while((g|0)!=(j|0));return}function If(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0,o=0;if((c[b+8>>2]|0)>=(d|0))return;if((d|0)!=0?(c[6435]=(c[6435]|0)+1,e=yc((d*36|3)+16|0)|0,(e|0)!=0):0){c[(e+4+15&-16)+-4>>2]=e;o=e+4+15&-16}else o=0;i=c[b+4>>2]|0;if((i|0)>0){m=0;do{j=o+(m*36|0)|0;k=c[b+12>>2]|0;a[j+16>>0]=1;c[j+12>>2]=0;c[j+4>>2]=0;c[j+8>>2]=0;l=c[k+(m*36|0)+4>>2]|0;if((l|0)>0){c[6435]=(c[6435]|0)+1;e=yc((l<<2|3)+16|0)|0;if(!e)h=0;else{c[(e+4+15&-16)+-4>>2]=e;h=e+4+15&-16}g=c[j+4>>2]|0;f=c[j+12>>2]|0;if((g|0)<=0)if(!f){a[j+16>>0]=1;c[j+12>>2]=h;c[j+8>>2]=l;Qn(h|0,0,l<<2|0)|0}else n=14;else{e=0;do{c[h+(e<<2)>>2]=c[f+(e<<2)>>2];e=e+1|0}while((e|0)!=(g|0));n=14}if((n|0)==14){n=0;if(a[j+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[j+16>>0]=1;c[j+12>>2]=h;c[j+8>>2]=l;Qn(h|0,0,l<<2|0)|0}e=c[j+12>>2]|0;c[j+4>>2]=l;f=c[k+(m*36|0)+12>>2]|0;g=0;do{c[e+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(l|0))}else c[j+4>>2]=l;l=k+(m*36|0)+20|0;c[j+20>>2]=c[l>>2];c[j+20+4>>2]=c[l+4>>2];c[j+20+8>>2]=c[l+8>>2];c[j+20+12>>2]=c[l+12>>2];m=m+1|0}while((m|0)!=(i|0));e=c[b+4>>2]|0;if((e|0)>0){k=0;do{g=c[b+12>>2]|0;h=g+(k*36|0)+4|0;i=g+(k*36|0)+12|0;j=c[i>>2]|0;f=g+(k*36|0)+16|0;if(j|0){if(a[f>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0)}c[i>>2]=0}a[f>>0]=1;c[i>>2]=0;c[h>>2]=0;c[g+(k*36|0)+8>>2]=0;k=k+1|0}while((k|0)!=(e|0))}}e=c[b+12>>2]|0;if(e|0){if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=o;c[b+8>>2]=d;return}function Jf(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0,i=0.0,j=0.0,k=0.0,l=0.0;c[b+4>>2]=4;c[b>>2]=4432;c[b+8>>2]=-1;c[b+12>>2]=-1;g[b+16>>2]=3402823466385288598117041.0e14;a[b+20>>0]=1;a[b+21>>0]=0;c[b+24>>2]=-1;c[b+28>>2]=d;Il();c[b+32>>2]=23268;g[b+36>>2]=0.0;g[b+40>>2]=.30000001192092896;c[b+44>>2]=0;c[b>>2]=4704;c[b+552>>2]=c[e>>2];c[b+552+4>>2]=c[e+4>>2];c[b+552+8>>2]=c[e+8>>2];c[b+552+12>>2]=c[e+12>>2];c[b+568>>2]=c[e+16>>2];c[b+568+4>>2]=c[e+16+4>>2];c[b+568+8>>2]=c[e+16+8>>2];c[b+568+12>>2]=c[e+16+12>>2];c[b+584>>2]=c[e+32>>2];c[b+584+4>>2]=c[e+32+4>>2];c[b+584+8>>2]=c[e+32+8>>2];c[b+584+12>>2]=c[e+32+12>>2];c[b+600>>2]=c[e+48>>2];c[b+600+4>>2]=c[e+48+4>>2];c[b+600+8>>2]=c[e+48+8>>2];c[b+600+12>>2]=c[e+48+12>>2];c[b+616>>2]=c[e>>2];c[b+616+4>>2]=c[e+4>>2];c[b+616+8>>2]=c[e+8>>2];c[b+616+12>>2]=c[e+12>>2];c[b+632>>2]=c[e+16>>2];c[b+632+4>>2]=c[e+16+4>>2];c[b+632+8>>2]=c[e+16+8>>2];c[b+632+12>>2]=c[e+16+12>>2];c[b+648>>2]=c[e+32>>2];c[b+648+4>>2]=c[e+32+4>>2];c[b+648+8>>2]=c[e+32+8>>2];c[b+648+12>>2]=c[e+32+12>>2];c[b+664>>2]=c[e+48>>2];c[b+664+4>>2]=c[e+48+4>>2];c[b+664+8>>2]=c[e+48+8>>2];c[b+664+12>>2]=c[e+48+12>>2];g[b+688>>2]=0.0;g[b+692>>2]=-1.0;g[b+696>>2]=.8999999761581421;g[b+700>>2]=.30000001192092896;g[b+704>>2]=1.0;g[b+708>>2]=0.0;g[b+712>>2]=0.0;a[b+716>>0]=0;a[b+736>>0]=0;a[b+737>>0]=0;a[b+738>>0]=0;a[b+739>>0]=1;a[b+740>>0]=f&1;c[b+748>>2]=0;e=c[b+28>>2]|0;l=+g[b+600>>2];k=+g[b+604>>2];j=+g[b+608>>2];i=l*+g[e+20>>2]+k*+g[e+24>>2]+j*+g[e+28>>2]+ +g[e+56>>2];h=l*+g[e+36>>2]+k*+g[e+40>>2]+j*+g[e+44>>2]+ +g[e+60>>2];g[b+664>>2]=l*+g[e+4>>2]+k*+g[e+8>>2]+j*+g[e+12>>2]+ +g[e+52>>2];g[b+668>>2]=i;g[b+672>>2]=h;g[b+676>>2]=0.0;g[b+732>>2]=f?-1.0:1.0;return}function Kf(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0,j=0;i=c[b+12>>2]|0;j=c[b+32>>2]|0;if((i|0)<=(j|0))return;if((i|0)>=(j|0)){do if((c[b+36>>2]|0)<(i|0)){if(!i){d=0;e=j}else{c[6435]=(c[6435]|0)+1;d=yc((i<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+32>>2]|0}f=c[b+40>>2]|0;if((e|0)<=0){if(!f){a[b+44>>0]=1;c[b+40>>2]=d;c[b+36>>2]=i;break}}else{g=0;do{c[d+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(e|0))}if(a[b+44>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[b+44>>0]=1;c[b+40>>2]=d;c[b+36>>2]=i}else d=c[b+40>>2]|0;while(0);Qn(d+(j<<2)|0,0,i-j<<2|0)|0}c[b+32>>2]=i;h=c[b+52>>2]|0;if((i|0)>(h|0)){do if((c[b+56>>2]|0)<(i|0)){if(!i){d=0;e=h}else{c[6435]=(c[6435]|0)+1;d=yc((i<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+52>>2]|0}f=c[b+60>>2]|0;if((e|0)<=0){if(!f){a[b+64>>0]=1;c[b+60>>2]=d;c[b+56>>2]=i;break}}else{g=0;do{c[d+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(e|0))}if(a[b+64>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[b+64>>0]=1;c[b+60>>2]=d;c[b+56>>2]=i}else d=c[b+60>>2]|0;while(0);Qn(d+(h<<2)|0,0,i-h<<2|0)|0}c[b+52>>2]=i;if((i|0)>0){Qn(c[b+40>>2]|0,-1,i<<2|0)|0;Qn(c[b+60>>2]|0,-1,i<<2|0)|0}if((j|0)<=0)return;d=c[b+16>>2]|0;e=c[b+40>>2]|0;f=c[b+60>>2]|0;g=0;do{i=c[d+(g*12|0)+4>>2]<<16|c[d+(g*12|0)>>2];i=(i+~(i<<15)>>10^i+~(i<<15))*9|0;i=e+((((i>>6^i)+~((i>>6^i)<<11)>>16^(i>>6^i)+~((i>>6^i)<<11))&(c[b+12>>2]|0)+-1)<<2)|0;c[f+(g<<2)>>2]=c[i>>2];c[i>>2]=g;g=g+1|0}while((g|0)!=(j|0));return}function Lf(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0;e=Zb[c[(c[d>>2]|0)+40>>2]&31](d,a)|0;g=Zb[c[(c[d>>2]|0)+28>>2]&31](d,e)|0;c[b>>2]=g;if(g|0)Cb[c[(c[d>>2]|0)+48>>2]&127](d,e);c[b+4>>2]=c[a+4>>2];c[b+20>>2]=c[a+72>>2];e=c[a+16>>2]|0;c[b+16>>2]=e;c[b+12>>2]=0;if(!e)return 16387;g=Ob[c[(c[d>>2]|0)+16>>2]&63](d,76,e)|0;e=c[g+8>>2]|0;c[b+12>>2]=Zb[c[(c[d>>2]|0)+28>>2]&31](d,e)|0;if((c[b+16>>2]|0)>0){f=0;while(1){h=c[a+24>>2]|0;c[e+72>>2]=c[h+(f*80|0)+72>>2];c[e+64>>2]=Zb[c[(c[d>>2]|0)+28>>2]&31](d,c[h+(f*80|0)+64>>2]|0)|0;if(!(Zb[c[(c[d>>2]|0)+24>>2]&31](d,c[(c[a+24>>2]|0)+(f*80|0)+64>>2]|0)|0)){h=c[(c[d>>2]|0)+16>>2]|0;i=c[(c[a+24>>2]|0)+(f*80|0)+64>>2]|0;i=Eb[c[(c[i>>2]|0)+52>>2]&127](i)|0;i=Ob[h&63](d,i,1)|0;h=c[(c[a+24>>2]|0)+(f*80|0)+64>>2]|0;h=Ob[c[(c[h>>2]|0)+56>>2]&63](h,c[i+8>>2]|0,d)|0;yb[c[(c[d>>2]|0)+20>>2]&31](d,i,h,1346455635,c[(c[a+24>>2]|0)+(f*80|0)+64>>2]|0)}i=c[a+24>>2]|0;c[e+68>>2]=c[i+(f*80|0)+68>>2];c[e>>2]=c[i+(f*80|0)>>2];c[e+4>>2]=c[i+(f*80|0)+4>>2];c[e+8>>2]=c[i+(f*80|0)+8>>2];c[e+12>>2]=c[i+(f*80|0)+12>>2];c[e+16>>2]=c[i+(f*80|0)+16>>2];c[e+20>>2]=c[i+(f*80|0)+20>>2];c[e+24>>2]=c[i+(f*80|0)+24>>2];c[e+28>>2]=c[i+(f*80|0)+28>>2];c[e+32>>2]=c[i+(f*80|0)+32>>2];c[e+36>>2]=c[i+(f*80|0)+36>>2];c[e+40>>2]=c[i+(f*80|0)+40>>2];c[e+44>>2]=c[i+(f*80|0)+44>>2];c[e+48>>2]=c[i+(f*80|0)+48>>2];c[e+52>>2]=c[i+(f*80|0)+52>>2];c[e+56>>2]=c[i+(f*80|0)+56>>2];c[e+60>>2]=c[i+(f*80|0)+60>>2];f=f+1|0;if((f|0)>=(c[b+16>>2]|0)){e=d;break}else e=e+76|0}}else e=d;yb[c[(c[e>>2]|0)+20>>2]&31](d,g,16362,1497453121,c[g+8>>2]|0);return 16387}function Mf(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0.0,j=0.0,k=0.0,l=0,m=0,n=0.0,o=0.0,p=0.0,q=0.0;f=i;i=i+256|0;c[f+32>>2]=5736;l=f+32+36|0;c[l>>2]=c[b>>2];c[l+4>>2]=c[b+4>>2];c[l+8>>2]=c[b+8>>2];c[l+12>>2]=c[b+12>>2];m=f+32+52|0;c[m>>2]=c[d>>2];c[m+4>>2]=c[d+4>>2];c[m+8>>2]=c[d+8>>2];c[m+12>>2]=c[d+12>>2];c[f+32+212>>2]=a;c[f+32+216>>2]=e;c[f+32+68>>2]=1065353216;c[f+32+72>>2]=0;c[f+32+72+4>>2]=0;c[f+32+72+8>>2]=0;c[f+32+72+12>>2]=0;c[f+32+88>>2]=1065353216;c[f+32+92>>2]=0;c[f+32+92+4>>2]=0;c[f+32+92+8>>2]=0;c[f+32+92+12>>2]=0;c[f+32+108>>2]=1065353216;c[f+32+112>>2]=0;c[f+32+116>>2]=c[l>>2];c[f+32+116+4>>2]=c[l+4>>2];c[f+32+116+8>>2]=c[l+8>>2];c[f+32+116+12>>2]=c[l+12>>2];c[f+32+132>>2]=1065353216;c[f+32+136>>2]=0;c[f+32+136+4>>2]=0;c[f+32+136+8>>2]=0;c[f+32+136+12>>2]=0;c[f+32+152>>2]=1065353216;c[f+32+156>>2]=0;c[f+32+156+4>>2]=0;c[f+32+156+8>>2]=0;c[f+32+156+12>>2]=0;c[f+32+172>>2]=1065353216;c[f+32+176>>2]=0;c[f+32+180>>2]=c[d>>2];c[f+32+180+4>>2]=c[d+4>>2];c[f+32+180+8>>2]=c[d+8>>2];c[f+32+180+12>>2]=c[d+12>>2];n=+g[d>>2]-+g[b>>2];k=+g[d+4>>2]-+g[b+4>>2];j=+g[d+8>>2]-+g[b+8>>2];h=1.0/+O(+(n*n+k*k+j*j));q=n*h==0.0?999999984306749440.0:1.0/(n*h);g[f+32+4>>2]=q;p=k*h==0.0?999999984306749440.0:1.0/(k*h);g[f+32+8>>2]=p;o=j*h==0.0?999999984306749440.0:1.0/(j*h);g[f+32+12>>2]=o;c[f+32+20>>2]=q<0.0&1;c[f+32+24>>2]=p<0.0&1;c[f+32+28>>2]=o<0.0&1;g[f+32+32>>2]=n*h*(+g[m>>2]-+g[l>>2])+k*h*(+g[f+32+56>>2]-+g[f+32+40>>2])+j*h*(+g[f+32+60>>2]-+g[f+32+44>>2]);a=c[a+68>>2]|0;e=c[(c[a>>2]|0)+24>>2]|0;c[f+16>>2]=0;c[f+16+4>>2]=0;c[f+16+8>>2]=0;c[f+16+12>>2]=0;c[f>>2]=0;c[f+4>>2]=0;c[f+8>>2]=0;c[f+12>>2]=0;Qb[e&7](a,b,d,f+32|0,f+16|0,f);i=f;return}function Nf(b,d,e,f,h,j,k,l,m){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;k=k|0;l=l|0;m=m|0;var n=0,o=0,p=0,q=0;q=i;i=i+80|0;g[q+16+60>>2]=0.0;g[q+16+8>>2]=0.0;g[q+16+12>>2]=.10000000149011612;g[q+16+16>>2]=300.0;g[q+16>>2]=1.0;g[q+16+4>>2]=-1.0;g[q+16+28>>2]=0.0;g[q+16+32>>2]=.20000000298023224;g[q+16+36>>2]=0.0;g[q+16+40>>2]=0.0;g[q+16+20>>2]=1.0;g[q+16+24>>2]=.5;c[q+16+56>>2]=0;g[q+16+48>>2]=0.0;a[q+16+44>>0]=0;p=0;do{n=c[b+856+(p<<2)>>2]|0;o=a[b+788+p>>0]|0;if(!((n|0)==0&o<<24>>24==0)){g[q+16+40>>2]=0.0;c[q+16+56>>2]=n;c[q+16+52>>2]=c[b+840+(p<<2)>>2];c[q+16+48>>2]=c[b+824+(p<<2)>>2];c[q+16+20>>2]=c[b+732>>2];a[q+16+44>>0]=o;c[q+16+4>>2]=c[b+696+(p<<2)>>2];c[q+16+24>>2]=c[b+728>>2];c[q+16>>2]=c[b+680+(p<<2)>>2];g[q+16+16>>2]=0.0;c[q+16+12>>2]=c[b+808+(p<<2)>>2];c[q+16+8>>2]=c[b+792+(p<<2)>>2];c[q>>2]=c[b+1064+(p<<2)>>2];c[q+4>>2]=c[b+1080+(p<<2)>>2];c[q+8>>2]=c[b+1096+(p<<2)>>2];g[q+12>>2]=0.0;o=c[b+1304>>2]>>p*3;if(!(o&1))n=c[d+32>>2]|0;else n=b+740+(p<<2)|0;c[q+16+28>>2]=c[n>>2];if(!(o&2))n=c[d+32>>2]|0;else n=b+772+(p<<2)|0;c[q+16+36>>2]=c[n>>2];c[q+16+32>>2]=c[((o&4|0)==0?d+4|0:b+756+(p<<2)|0)>>2];if(!(a[b+1301>>0]|0))n=Dd(b,q+16|0,f,h,j,k,l,m,d,e,q,0,0)|0;else{o=p+1|0;if(!(c[b+868+(((o|0)==3?0:o)<<6)+56>>2]|0))n=1;else n=(c[b+868+(((p+2|0)%3|0)<<6)+56>>2]|0)==0&1;n=Dd(b,q+16|0,f,h,j,k,l,m,d,e,q,0,n)|0}e=n+e|0}p=p+1|0}while((p|0)!=3);i=q;return e|0}function Of(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;var h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0;h=i;i=i+128|0;if(!b){i=h;return}if(c[b+40>>2]|0){Of(a,c[b+36>>2]|0,d+1|0,e,f);Of(a,c[b+40>>2]|0,d+1|0,e,f)}if((d|0)<0){i=h;return}m=+g[b>>2];r=+g[b+16>>2];k=+g[b+4>>2];q=+g[b+20>>2];j=+g[b+8>>2];p=+g[b+24>>2];l=(m+r)*.5-(r-m)*.5;n=(k+q)*.5-(q-k)*.5;o=(j+p)*.5-(p-j)*.5;m=(m+r)*.5+(r-m)*.5;k=(k+q)*.5+(q-k)*.5;j=(j+p)*.5+(p-j)*.5;b=(c[b+40>>2]|0)==0?f:e;g[h>>2]=l;g[h+4>>2]=n;g[h+8>>2]=o;g[h+12>>2]=0.0;g[h+16>>2]=m;g[h+20>>2]=n;g[h+24>>2]=o;g[h+28>>2]=0.0;g[h+32>>2]=m;g[h+36>>2]=k;g[h+40>>2]=o;g[h+44>>2]=0.0;g[h+48>>2]=l;g[h+52>>2]=k;g[h+56>>2]=o;g[h+60>>2]=0.0;g[h+64>>2]=l;g[h+68>>2]=n;g[h+72>>2]=j;g[h+76>>2]=0.0;g[h+80>>2]=m;g[h+84>>2]=n;g[h+88>>2]=j;g[h+92>>2]=0.0;g[h+96>>2]=m;g[h+100>>2]=k;g[h+104>>2]=j;g[h+108>>2]=0.0;g[h+112>>2]=l;g[h+116>>2]=k;g[h+120>>2]=j;g[h+124>>2]=0.0;mc[c[(c[a>>2]|0)+8>>2]&127](a,h,h+16|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+16|0,h+32|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+32|0,h+48|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+48|0,h,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+64|0,h+80|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+80|0,h+96|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+96|0,h+112|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+112|0,h+64|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h,h+64|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+16|0,h+80|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+32|0,h+96|0,b);mc[c[(c[a>>2]|0)+8>>2]&127](a,h+48|0,h+112|0,b);i=h;return}function Pf(a,b,c,d,e,f,h,i){a=a|0;b=+b;c=+c;d=+d;e=e|0;f=+f;h=+h;i=+i;var j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0;z=+g[e>>2];y=+g[e+16>>2];x=+g[e+32>>2];w=+g[e+4>>2];v=+g[e+20>>2];u=+g[e+36>>2];t=+g[e+8>>2];s=+g[e+24>>2];r=+g[e+40>>2];j=d-((z*0.0+y*-i+x*h)*0.0+(w*0.0+v*-i+u*h)*i+(t*0.0+s*-i+r*h)*-h)+c;o=0.0-((z*0.0+y*-i+x*h)*-i+(w*0.0+v*-i+u*h)*0.0+(t*0.0+s*-i+r*h)*f)+0.0;l=0.0-((z*0.0+y*-i+x*h)*h+(w*0.0+v*-i+u*h)*-f+(t*0.0+s*-i+r*h)*0.0)+0.0;m=0.0-((z*i+y*0.0+x*-f)*0.0+(w*i+v*0.0+u*-f)*i+(t*i+s*0.0+r*-f)*-h)+0.0;n=d-((z*i+y*0.0+x*-f)*-i+(w*i+v*0.0+u*-f)*0.0+(t*i+s*0.0+r*-f)*f)+c;k=0.0-((z*i+y*0.0+x*-f)*h+(w*i+v*0.0+u*-f)*-f+(t*i+s*0.0+r*-f)*0.0)+0.0;p=0.0-((z*-h+y*f+x*0.0)*0.0+(w*-h+v*f+u*0.0)*i+(t*-h+s*f+r*0.0)*-h)+0.0;q=0.0-((z*-h+y*f+x*0.0)*-i+(w*-h+v*f+u*0.0)*0.0+(t*-h+s*f+r*0.0)*f)+0.0;h=d-((z*-h+y*f+x*0.0)*h+(w*-h+v*f+u*0.0)*-f+(t*-h+s*f+r*0.0)*0.0)+c;i=1.0/(l*(q*m-n*p)+(j*(n*h-k*q)+o*(k*p-h*m)));g[a>>2]=(q*m-n*p)*i*0.0+(1.0/b*(n*h-k*q)*i+(k*p-h*m)*i*0.0);g[a+4>>2]=(p*o-q*j)*i*0.0+(1.0/b*(q*l-h*o)*i+(h*j-p*l)*i*0.0);g[a+8>>2]=(n*j-m*o)*i*0.0+(1.0/b*(k*o-n*l)*i+(m*l-k*j)*i*0.0);g[a+12>>2]=0.0;g[a+16>>2]=(q*m-n*p)*i*0.0+((n*h-k*q)*i*0.0+1.0/b*(k*p-h*m)*i);g[a+20>>2]=(p*o-q*j)*i*0.0+((q*l-h*o)*i*0.0+1.0/b*(h*j-p*l)*i);g[a+24>>2]=(n*j-m*o)*i*0.0+((k*o-n*l)*i*0.0+1.0/b*(m*l-k*j)*i);g[a+28>>2]=0.0;g[a+32>>2]=1.0/b*(q*m-n*p)*i+((n*h-k*q)*i*0.0+(k*p-h*m)*i*0.0);g[a+36>>2]=1.0/b*(p*o-q*j)*i+((q*l-h*o)*i*0.0+(h*j-p*l)*i*0.0);g[a+40>>2]=1.0/b*(n*j-m*o)*i+((k*o-n*l)*i*0.0+(m*l-k*j)*i*0.0);g[a+44>>2]=0.0;return}function Qf(b,d,e,f,h,j){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;var k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0;r=i;i=i+96|0;m=r;n=m+96|0;do{c[m>>2]=0;m=m+4|0}while((m|0)<(n|0));if(!j)q=c[c[b+880>>2]>>2]|0;else q=j;j=c[b+772>>2]|0;if((j|0)==(c[b+776>>2]|0)?(p=j|0?j<<1:1,(j|0)<(p|0)):0){if(!p)o=0;else{c[6435]=(c[6435]|0)+1;j=yc((p*104|3)+16|0)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}o=j;j=c[b+772>>2]|0}if((j|0)>0){k=0;do{m=o+(k*104|0)|0;l=(c[b+780>>2]|0)+(k*104|0)|0;n=m+104|0;do{c[m>>2]=c[l>>2];m=m+4|0;l=l+4|0}while((m|0)<(n|0));k=k+1|0}while((k|0)!=(j|0))}j=c[b+780>>2]|0;if(j|0){if(a[b+784>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0)}c[b+780>>2]=0}a[b+784>>0]=1;c[b+780>>2]=o;c[b+776>>2]=p;j=c[b+772>>2]|0}m=c[b+780>>2]|0;c[m+(j*104|0)>>2]=0;c[m+(j*104|0)+4>>2]=q;m=m+(j*104|0)+8|0;l=r;n=m+96|0;do{c[m>>2]=c[l>>2];m=m+4|0;l=l+4|0}while((m|0)<(n|0));q=c[b+772>>2]|0;c[b+772>>2]=q+1;p=c[b+780>>2]|0;l=c[b+720>>2]|0;c[p+(q*104|0)+8>>2]=l+(d*104|0);o=c[b+720>>2]|0;c[p+(q*104|0)+12>>2]=o+(e*104|0);m=c[b+720>>2]|0;c[p+(q*104|0)+16>>2]=m+(f*104|0);n=c[b+720>>2]|0;c[p+(q*104|0)+20>>2]=n+(h*104|0);z=+g[l+(d*104|0)+8>>2];w=+g[l+(d*104|0)+12>>2];A=+g[l+(d*104|0)+16>>2];t=+g[m+(f*104|0)+8>>2]-z;y=+g[m+(f*104|0)+12>>2]-w;v=+g[m+(f*104|0)+16>>2]-A;u=+g[n+(h*104|0)+8>>2]-z;x=+g[n+(h*104|0)+12>>2]-w;s=+g[n+(h*104|0)+16>>2]-A;g[p+(q*104|0)+24>>2]=(+g[o+(e*104|0)+16>>2]-A)*(t*x-y*u)+((+g[o+(e*104|0)+8>>2]-z)*(y*s-v*x)+(+g[o+(e*104|0)+12>>2]-w)*(v*u-t*s));a[b+924>>0]=1;i=r;return}function Rf(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0.0,s=0.0,t=0.0;q=i;i=i+48|0;p=c[b+720>>2]|0;a:do if(h?(l=c[b+732>>2]|0,(l|0)>0):0){j=c[b+740>>2]|0;k=0;while(1){h=c[j+(k*52|0)+8>>2]|0;if((h|0)==(p+(d*104|0)|0)?(c[j+(k*52|0)+12>>2]|0)==(p+(e*104|0)|0):0){h=25;break}if((h|0)==(p+(e*104|0)|0)?(c[j+(k*52|0)+12>>2]|0)==(p+(d*104|0)|0):0){h=25;break}k=k+1|0;if((k|0)>=(l|0))break a}if((h|0)==25){i=q;return}}while(0);l=q;m=l+44|0;do{c[l>>2]=0;l=l+4|0}while((l|0)<(m|0));if(!f)n=c[c[b+880>>2]>>2]|0;else n=f;h=c[b+732>>2]|0;if((h|0)==(c[b+736>>2]|0)?(o=h|0?h<<1:1,(h|0)<(o|0)):0){if(!o)f=0;else{c[6435]=(c[6435]|0)+1;h=yc((o*52|3)+16|0)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}f=h;h=c[b+732>>2]|0}if((h|0)>0){j=0;do{l=f+(j*52|0)|0;k=(c[b+740>>2]|0)+(j*52|0)|0;m=l+52|0;do{c[l>>2]=c[k>>2];l=l+4|0;k=k+4|0}while((l|0)<(m|0));j=j+1|0}while((j|0)!=(h|0))}h=c[b+740>>2]|0;if(h|0){if(a[b+744>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[b+740>>2]=0}a[b+744>>0]=1;c[b+740>>2]=f;c[b+736>>2]=o;h=c[b+732>>2]|0}l=c[b+740>>2]|0;c[l+(h*52|0)>>2]=0;c[l+(h*52|0)+4>>2]=n;l=l+(h*52|0)+8|0;k=q;m=l+44|0;do{c[l>>2]=c[k>>2];l=l+4|0;k=k+4|0}while((l|0)<(m|0));o=c[b+732>>2]|0;c[b+732>>2]=o+1;n=c[b+740>>2]|0;c[n+(o*52|0)+8>>2]=p+(d*104|0);c[n+(o*52|0)+12>>2]=p+(e*104|0);t=+g[p+(d*104|0)+8>>2]-+g[p+(e*104|0)+8>>2];s=+g[p+(d*104|0)+12>>2]-+g[p+(e*104|0)+12>>2];r=+g[p+(d*104|0)+16>>2]-+g[p+(e*104|0)+16>>2];g[n+(o*52|0)+16>>2]=+O(+(t*t+s*s+r*r));a[b+924>>0]=1;i=q;return}function Sf(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0;f=i;i=i+784|0;c[f+712>>2]=1065353216;c[f+712+4>>2]=0;c[f+712+4+4>>2]=0;c[f+712+4+8>>2]=0;c[f+712+4+12>>2]=0;c[f+712+20>>2]=1065353216;c[f+712+24>>2]=0;c[f+712+24+4>>2]=0;c[f+712+24+8>>2]=0;c[f+712+24+12>>2]=0;c[f+712+40>>2]=1065353216;e=f+712+44|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[e+16>>2]=0;c[f+536>>2]=3708;c[f+536+168>>2]=0;g[f+536+172>>2]=0.0;c[f+536+164>>2]=c[b+200>>2];e=c[b+196>>2]|0;c[f+480+8>>2]=0;c[f+480+12>>2]=1065353216;c[f+480+16>>2]=1065353216;c[f+480+20>>2]=1065353216;g[f+480+24>>2]=0.0;c[f+480>>2]=6672;c[f+480+4>>2]=8;c[f+480+28>>2]=e;c[f+480+44>>2]=e;c[f+376+8>>2]=0;c[f+376+12>>2]=1065353216;c[f+376+16>>2]=1065353216;c[f+376+20>>2]=1065353216;g[f+376+24>>2]=0.0;g[f+376+44>>2]=.03999999910593033;c[f+376+52>>2]=0;c[f+376>>2]=3736;c[f+376+4>>2]=1;c[f+376+56>>2]=c[d>>2];c[f+376+56+4>>2]=c[d+4>>2];c[f+376+56+8>>2]=c[d+8>>2];c[f+376+56+12>>2]=c[d+12>>2];c[f+376+72>>2]=c[d+16>>2];c[f+376+72+4>>2]=c[d+16+4>>2];c[f+376+72+8>>2]=c[d+16+8>>2];c[f+376+72+12>>2]=c[d+16+12>>2];c[f+376+88>>2]=c[d+32>>2];c[f+376+88+4>>2]=c[d+32+4>>2];c[f+376+88+8>>2]=c[d+32+8>>2];c[f+376+88+12>>2]=c[d+32+12>>2];g[f+16+308>>2]=9.999999747378752e-05;a[f+16+332>>0]=0;c[f>>2]=4960;c[f+4>>2]=f+16;c[f+8>>2]=f+480;c[f+12>>2]=f+376;if(od(f,b+4|0,b+68|0,f+712|0,f+712|0,f+536|0)|0?(h=+g[f+536+164>>2],+g[b+200>>2]>h):0)g[b+200>>2]=h;c[f+376>>2]=7124;e=c[f+376+52>>2]|0;if(!e){i=f;return}Ab[c[c[e>>2]>>2]&255](e);e=c[f+376+52>>2]|0;if(!e){i=f;return}c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);i=f;return}function Tf(d,e,f,g,h,j,k,l,m){d=d|0;e=e|0;f=f|0;g=g|0;h=h|0;j=j|0;k=k|0;l=l|0;m=m|0;var n=0,o=0;o=i;i=i+48|0;c[6435]=(c[6435]|0)+1;g=yc(83)|0;if(!g)n=0;else{c[(g+4+15&-16)+-4>>2]=g;n=g+4+15&-16}c[n>>2]=h;b[n+4>>1]=j;b[n+6>>1]=k;j=n+16|0;c[j>>2]=c[e>>2];c[j+4>>2]=c[e+4>>2];c[j+8>>2]=c[e+8>>2];c[j+12>>2]=c[e+12>>2];j=n+32|0;c[j>>2]=c[f>>2];c[j+4>>2]=c[f+4>>2];c[j+8>>2]=c[f+8>>2];c[j+12>>2]=c[f+12>>2];c[n+8>>2]=0;j=n+56|0;c[j>>2]=0;k=n+52|0;c[k>>2]=0;c[o+16>>2]=c[e>>2];c[o+16+4>>2]=c[e+4>>2];c[o+16+8>>2]=c[e+8>>2];c[o+16+12>>2]=c[e+12>>2];c[o+16+16>>2]=c[f>>2];c[o+16+16+4>>2]=c[f+4>>2];c[o+16+16+8>>2]=c[f+8>>2];c[o+16+16+12>>2]=c[f+12>>2];c[n+60>>2]=c[d+144>>2];g=(c[d+188>>2]|0)+1|0;c[d+188>>2]=g;c[n+12>>2]=g;g=c[d+8>>2]|0;if(!g){c[6435]=(c[6435]|0)+1;g=yc(63)|0;if(!g)g=0;else{c[(g+4+15&-16)+-4>>2]=g;g=g+4+15&-16}l=g;m=l+44|0;do{c[l>>2]=0;l=l+4|0}while((l|0)<(m|0))}else c[d+8>>2]=0;c[g+32>>2]=0;c[g+36>>2]=n;c[g+40>>2]=0;c[g>>2]=c[o+16>>2];c[g+4>>2]=c[o+16+4>>2];c[g+8>>2]=c[o+16+8>>2];c[g+12>>2]=c[o+16+12>>2];c[g+16>>2]=c[o+16+16>>2];c[g+20>>2]=c[o+16+20>>2];c[g+24>>2]=c[o+16+24>>2];c[g+28>>2]=c[o+16+28>>2];lf(d+4|0,c[d+4>>2]|0,g);c[d+16>>2]=(c[d+16>>2]|0)+1;c[n+48>>2]=g;l=d+124+(c[d+144>>2]<<2)|0;c[k>>2]=0;c[j>>2]=c[l>>2];g=c[l>>2]|0;if(g|0)c[g+52>>2]=n;c[l>>2]=n;if(a[d+193>>0]|0){i=o;return n|0}c[o>>2]=8904;c[o+4>>2]=d;c[o+8>>2]=n;bg(c[d+4>>2]|0,o+16|0,o);bg(c[d+64>>2]|0,o+16|0,o);i=o;return n|0}function Uf(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0;f=i;i=i+608|0;p=+g[d+116>>2]-+g[d+52>>2];o=+g[d+120>>2]-+g[d+56>>2];n=+g[d+124>>2]-+g[d+60>>2];j=+g[e+116>>2]-+g[e+52>>2];k=+g[e+120>>2]-+g[e+56>>2];l=+g[e+124>>2]-+g[e+60>>2];m=+g[d+252>>2];if(p*p+o*o+n*n>2],j*j+k*k+l*l>2]|0;h=c[e+248>>2]|0;c[f+552+8>>2]=0;c[f+552+12>>2]=1065353216;c[f+552+16>>2]=1065353216;c[f+552+20>>2]=1065353216;g[f+552+24>>2]=0.0;c[f+552>>2]=6672;c[f+552+4>>2]=8;c[f+552+28>>2]=h;c[f+552+44>>2]=h;c[f+376>>2]=3708;g[f+376+164>>2]=999999984306749440.0;c[f+376+168>>2]=0;g[f+376+172>>2]=0.0;g[f+16+308>>2]=9.999999747378752e-05;a[f+16+332>>0]=0;c[f>>2]=9140;c[f+4>>2]=f+16;c[f+8>>2]=b;c[f+12>>2]=f+552;if(Ed(f,d+4|0,d+68|0,e+4|0,e+68|0,f+376|0)|0){j=+g[f+376+164>>2];if(+g[d+244>>2]>j)g[d+244>>2]=j;if(+g[e+244>>2]>j)g[e+244>>2]=j;if(j<1.0)k=j;else k=1.0}else k=1.0;b=c[e+192>>2]|0;h=c[d+248>>2]|0;c[f+552+8>>2]=0;c[f+552+12>>2]=1065353216;c[f+552+16>>2]=1065353216;c[f+552+20>>2]=1065353216;g[f+552+24>>2]=0.0;c[f+552>>2]=6672;c[f+552+4>>2]=8;c[f+552+28>>2]=h;c[f+552+44>>2]=h;c[f+376>>2]=3708;g[f+376+164>>2]=999999984306749440.0;c[f+376+168>>2]=0;g[f+376+172>>2]=0.0;g[f+16+308>>2]=9.999999747378752e-05;a[f+16+332>>0]=0;c[f>>2]=9140;c[f+4>>2]=f+16;c[f+8>>2]=f+552;c[f+12>>2]=b;if(Ed(f,d+4|0,d+68|0,e+4|0,e+68|0,f+376|0)|0){j=+g[f+376+164>>2];if(+g[d+244>>2]>j)g[d+244>>2]=j;if(+g[e+244>>2]>j)g[e+244>>2]=j;if(!(k>j))j=k}else j=k;p=j;i=f;return +p}function Vf(a,d){a=a|0;d=d|0;var e=0,f=0,h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0;e=i;i=i+128|0;G=c[(c[a+8>>2]|0)+24>>2]|0;h=c[G+(d*80|0)+64>>2]|0;f=c[a+12>>2]|0;x=+g[G+(d*80|0)>>2];D=+g[f>>2];w=+g[G+(d*80|0)+16>>2];C=+g[f+4>>2];v=+g[G+(d*80|0)+32>>2];B=+g[f+8>>2];u=+g[G+(d*80|0)+4>>2];t=+g[G+(d*80|0)+20>>2];s=+g[G+(d*80|0)+36>>2];r=+g[G+(d*80|0)+8>>2];p=+g[G+(d*80|0)+24>>2];n=+g[G+(d*80|0)+40>>2];A=+g[f+16>>2];z=+g[f+20>>2];y=+g[f+24>>2];q=+g[f+32>>2];o=+g[f+36>>2];m=+g[f+40>>2];F=+g[G+(d*80|0)+48>>2];E=+g[G+(d*80|0)+52>>2];j=+g[G+(d*80|0)+56>>2];l=+g[f+48>>2]+(D*F+C*E+B*j);k=A*F+z*E+y*j+ +g[f+52>>2];j=q*F+o*E+m*j+ +g[f+56>>2];g[e+56>>2]=x*D+w*C+v*B;g[e+56+4>>2]=D*u+C*t+B*s;g[e+56+8>>2]=D*r+C*p+B*n;g[e+56+12>>2]=0.0;g[e+56+16>>2]=x*A+w*z+v*y;g[e+56+20>>2]=u*A+t*z+s*y;g[e+56+24>>2]=r*A+p*z+n*y;g[e+56+28>>2]=0.0;g[e+56+32>>2]=x*q+w*o+v*m;g[e+56+36>>2]=u*q+t*o+s*m;g[e+56+40>>2]=r*q+p*o+n*m;g[e+56+44>>2]=0.0;g[e+56+48>>2]=l;g[e+56+52>>2]=k;g[e+56+56>>2]=j;g[e+56+60>>2]=0.0;f=c[a+4>>2]|0;c[e+32>>2]=0;c[e+32+4>>2]=h;c[e+32+8>>2]=f;c[e+32+12>>2]=e+56;c[e+32+16>>2]=-1;c[e+32+20>>2]=d;f=c[a+24>>2]|0;g[e+4>>2]=1.0;c[e+8>>2]=0;b[e+12>>1]=1;b[e+14>>1]=-1;c[e+16>>2]=0;c[e>>2]=5840;c[e+20>>2]=f;c[e+24>>2]=d;c[e+4>>2]=c[f+4>>2];c[e+16>>2]=c[f+16>>2];bd(c[a+16>>2]|0,c[a+20>>2]|0,e+32|0,e);i=e;return}function Wf(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0;j=i;i=i+96|0;f=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);h=0;do{q=j+80+(h<<2)|0;c[j+80>>2]=0;c[j+80+4>>2]=0;c[j+80+8>>2]=0;c[j+80+12>>2]=0;g[q>>2]=1.0;k=c[(c[a>>2]|0)+64>>2]|0;l=+g[j+80>>2];m=+g[j+80+4>>2];n=+g[j+80+8>>2];o=l*+g[b+4>>2]+m*+g[b+20>>2]+n*+g[b+36>>2];p=l*+g[b+8>>2]+m*+g[b+24>>2]+n*+g[b+40>>2];g[j+32>>2]=+g[b>>2]*l+ +g[b+16>>2]*m+ +g[b+32>>2]*n;g[j+32+4>>2]=o;g[j+32+8>>2]=p;g[j+32+12>>2]=0.0;ic[k&127](j+64|0,a,j+32|0);p=+g[j+64>>2];o=+g[j+64+4>>2];n=+g[j+64+8>>2];m=p*+g[b+16>>2]+o*+g[b+20>>2]+n*+g[b+24>>2]+ +g[b+52>>2];l=p*+g[b+32>>2]+o*+g[b+36>>2]+n*+g[b+40>>2]+ +g[b+56>>2];g[j+48>>2]=p*+g[b>>2]+o*+g[b+4>>2]+n*+g[b+8>>2]+ +g[b+48>>2];g[j+48+4>>2]=m;g[j+48+8>>2]=l;g[j+48+12>>2]=0.0;k=j+48+(h<<2)|0;g[e+(h<<2)>>2]=f+ +g[k>>2];g[q>>2]=-1.0;q=c[(c[a>>2]|0)+64>>2]|0;l=+g[j+80>>2];m=+g[j+80+4>>2];n=+g[j+80+8>>2];o=l*+g[b+4>>2]+m*+g[b+20>>2]+n*+g[b+36>>2];p=l*+g[b+8>>2]+m*+g[b+24>>2]+n*+g[b+40>>2];g[j>>2]=+g[b>>2]*l+ +g[b+16>>2]*m+ +g[b+32>>2]*n;g[j+4>>2]=o;g[j+8>>2]=p;g[j+12>>2]=0.0;ic[q&127](j+16|0,a,j);p=+g[j+16>>2];o=+g[j+16+4>>2];n=+g[j+16+8>>2];m=p*+g[b+16>>2]+o*+g[b+20>>2]+n*+g[b+24>>2]+ +g[b+52>>2];l=p*+g[b+32>>2]+o*+g[b+36>>2]+n*+g[b+40>>2]+ +g[b+56>>2];g[j+48>>2]=p*+g[b>>2]+o*+g[b+4>>2]+n*+g[b+8>>2]+ +g[b+48>>2];g[j+48+4>>2]=m;g[j+48+8>>2]=l;g[j+48+12>>2]=0.0;g[d+(h<<2)>>2]=+g[k>>2]-f;h=h+1|0}while((h|0)!=3);i=j;return}function Xf(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0,l=0,m=0,n=0,o=0,p=0;l=i;i=i+160|0;j=c[b+12>>2]|0;if(!j){i=l;return}m=(a[b+16>>0]|0)!=0;n=m?e:d;e=m?d:e;p=c[n+4>>2]|0;o=c[e+4>>2]|0;c[h+4>>2]=j;d=c[j+752>>2]|0;c[l+136>>2]=9304;c[l+136+4>>2]=p;c[l+136+8>>2]=o;c[l+136+12>>2]=d;g[l+128>>2]=999999984306749440.0;d=c[n+12>>2]|0;c[l>>2]=c[d>>2];c[l+4>>2]=c[d+4>>2];c[l+8>>2]=c[d+8>>2];c[l+12>>2]=c[d+12>>2];c[l+16>>2]=c[d+16>>2];c[l+16+4>>2]=c[d+16+4>>2];c[l+16+8>>2]=c[d+16+8>>2];c[l+16+12>>2]=c[d+16+12>>2];c[l+32>>2]=c[d+32>>2];c[l+32+4>>2]=c[d+32+4>>2];c[l+32+8>>2]=c[d+32+8>>2];c[l+32+12>>2]=c[d+32+12>>2];c[l+48>>2]=c[d+48>>2];c[l+48+4>>2]=c[d+48+4>>2];c[l+48+8>>2]=c[d+48+8>>2];c[l+48+12>>2]=c[d+48+12>>2];e=c[e+12>>2]|0;c[l+64>>2]=c[e>>2];c[l+64+4>>2]=c[e+4>>2];c[l+64+8>>2]=c[e+8>>2];c[l+64+12>>2]=c[e+12>>2];c[l+80>>2]=c[e+16>>2];c[l+80+4>>2]=c[e+16+4>>2];c[l+80+8>>2]=c[e+16+8>>2];c[l+80+12>>2]=c[e+16+12>>2];c[l+96>>2]=c[e+32>>2];c[l+96+4>>2]=c[e+32+4>>2];c[l+96+8>>2]=c[e+32+8>>2];c[l+96+12>>2]=c[e+32+12>>2];c[l+112>>2]=c[e+48>>2];c[l+112+4>>2]=c[e+48+4>>2];c[l+112+8>>2]=c[e+48+8>>2];c[l+112+12>>2]=c[e+48+12>>2];$d(l+136|0,l,h,c[f+20>>2]|0,m);do if(a[b+8>>0]|0?(k=c[h+4>>2]|0,c[k+748>>2]|0):0){d=c[k+740>>2]|0;e=c[(c[h+8>>2]|0)+8>>2]|0;j=c[(c[h+12>>2]|0)+8>>2]|0;if((d|0)==(e|0)){ef(k,d+4|0,j+4|0);break}else{ef(k,j+4|0,e+4|0);break}}while(0);i=l;return}function Yf(d,e,f){d=d|0;e=e|0;f=f|0;var h=0,i=0,j=0;c[d+4>>2]=1065353216;c[d+8>>2]=1065353216;c[d+12>>2]=1065353216;g[d+16>>2]=0.0;a[d+36>>0]=1;c[d+32>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;c[d+48>>2]=0;c[d>>2]=8452;a[d+100>>0]=1;c[d+96>>2]=0;c[d+88>>2]=0;c[d+92>>2]=0;a[d+120>>0]=1;c[d+116>>2]=0;c[d+108>>2]=0;c[d+112>>2]=0;a[d+140>>0]=1;c[d+136>>2]=0;c[d+128>>2]=0;c[d+132>>2]=0;a[d+160>>0]=1;c[d+156>>2]=0;c[d+148>>2]=0;c[d+152>>2]=0;a[d+164>>0]=e&1;a[d+165>>0]=f&1;g[d+168>>2]=0.0;c[6435]=(c[6435]|0)+1;e=yc(51)|0;if(!e)h=0;else{c[(e+4+15&-16)+-4>>2]=e;h=e+4+15&-16}e=c[d+24>>2]|0;if((e|0)>0){f=0;do{i=h+(f<<5)|0;j=(c[d+32>>2]|0)+(f<<5)|0;c[i>>2]=c[j>>2];c[i+4>>2]=c[j+4>>2];c[i+8>>2]=c[j+8>>2];c[i+12>>2]=c[j+12>>2];c[i+16>>2]=c[j+16>>2];c[i+20>>2]=c[j+20>>2];c[i+24>>2]=c[j+24>>2];c[i+28>>2]=c[j+28>>2];f=f+1|0}while((f|0)!=(e|0))}e=c[d+32>>2]|0;if(e|0){if(a[d+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[d+32>>2]=0}a[d+36>>0]=1;c[d+32>>2]=h;c[d+28>>2]=1;e=c[d+24>>2]|0;c[h+(e<<5)>>2]=0;c[h+(e<<5)+4>>2]=0;c[h+(e<<5)+8>>2]=12;c[h+(e<<5)+12>>2]=0;c[h+(e<<5)+16>>2]=0;c[h+(e<<5)+20>>2]=16;c[h+(e<<5)+24>>2]=2;c[h+(e<<5)+28>>2]=0;c[d+24>>2]=(c[d+24>>2]|0)+1;e=b[d+164>>1]|0;if(!((e&255)<<24>>24)){f=c[d+32>>2]|0;c[f>>2]=(c[d+148>>2]|0)/3|0;c[f+4>>2]=0;c[f+24>>2]=3;c[f+8>>2]=6}else{f=c[d+32>>2]|0;c[f>>2]=(c[d+128>>2]|0)/3|0;c[f+4>>2]=0;c[f+24>>2]=2;c[f+8>>2]=12}if((e&65535)<256){i=12;d=(c[d+108>>2]|0)/3|0;j=f+12|0;c[j>>2]=d;j=f+16|0;c[j>>2]=0;j=f+20|0;c[j>>2]=i;return}else{i=16;d=c[d+88>>2]|0;j=f+12|0;c[j>>2]=d;j=f+16|0;c[j>>2]=0;j=f+20|0;c[j>>2]=i;return}}function Zf(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0;q=i;i=i+48|0;if((f|0)==(d|0)|((d|0)==(e|0)|(e|0)==(f|0))){i=q;return}l=q;m=l+36|0;do{c[l>>2]=0;l=l+4|0}while((l|0)<(m|0));if(!h)p=c[c[b+880>>2]>>2]|0;else p=h;h=c[b+752>>2]|0;if((h|0)==(c[b+756>>2]|0)?(o=h|0?h<<1:1,(h|0)<(o|0)):0){if(!o)n=0;else{c[6435]=(c[6435]|0)+1;h=yc((o*44|3)+16|0)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}n=h;h=c[b+752>>2]|0}if((h|0)>0){j=0;do{l=n+(j*44|0)|0;k=(c[b+760>>2]|0)+(j*44|0)|0;m=l+44|0;do{c[l>>2]=c[k>>2];l=l+4|0;k=k+4|0}while((l|0)<(m|0));j=j+1|0}while((j|0)!=(h|0))}h=c[b+760>>2]|0;if(h|0){if(a[b+764>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[b+760>>2]=0}a[b+764>>0]=1;c[b+760>>2]=n;c[b+756>>2]=o;h=c[b+752>>2]|0}l=c[b+760>>2]|0;c[l+(h*44|0)>>2]=0;c[l+(h*44|0)+4>>2]=p;l=l+(h*44|0)+8|0;k=q;m=l+36|0;do{c[l>>2]=c[k>>2];l=l+4|0;k=k+4|0}while((l|0)<(m|0));p=c[b+752>>2]|0;c[b+752>>2]=p+1;o=c[b+760>>2]|0;l=c[b+720>>2]|0;c[o+(p*44|0)+8>>2]=l+(d*104|0);m=c[b+720>>2]|0;c[o+(p*44|0)+12>>2]=m+(e*104|0);n=c[b+720>>2]|0;c[o+(p*44|0)+16>>2]=n+(f*104|0);t=+g[l+(d*104|0)+8>>2];v=+g[l+(d*104|0)+12>>2];r=+g[l+(d*104|0)+16>>2];s=+g[m+(e*104|0)+8>>2]-t;w=+g[m+(e*104|0)+12>>2]-v;u=+g[m+(e*104|0)+16>>2]-r;t=+g[n+(f*104|0)+8>>2]-t;v=+g[n+(f*104|0)+12>>2]-v;r=+g[n+(f*104|0)+16>>2]-r;g[o+(p*44|0)+36>>2]=+O(+((s*v-w*t)*(s*v-w*t)+((w*r-u*v)*(w*r-u*v)+(u*t-s*r)*(u*t-s*r))));a[b+924>>0]=1;i=q;return}function _f(b,d){b=b|0;d=+d;var e=0,f=0,h=0,j=0,k=0,l=0,m=0,n=0.0,o=0.0,p=0.0,q=0.0;m=i;i=i+16|0;li(12187);e=c[b+232>>2]|0;if((e|0)>0){l=(a[26260]|0)==0;k=0;do{j=c[(c[b+240>>2]|0)+(k<<2)>>2]|0;a:do if(j){f=c[j+216>>2]|0;b:do switch(f|0){case 4:case 2:{if((f|0)==4)break a;break}default:{q=+g[j+312>>2];p=+g[j+316>>2];o=+g[j+320>>2];n=+g[j+472>>2];if(q*q+p*p+o*o>2],o=+g[j+332>>2],p=+g[j+336>>2],q=+g[j+476>>2],n*n+o*o+p*p>2]=+g[j+220>>2]+d;break b}g[j+220>>2]=0.0;if((f&-2|0)!=4){c[j+216>>2]=0;f=0}}}while(0);h=f&-2;do if(l){if((h|0)!=2?!(+g[j+220>>2]>2.0):0)break;if(c[j+204>>2]&3|0){if((h|0)==4)break a;c[j+216>>2]=2;break a}if((f|0)==1){if((h|0)==4)break a;c[j+216>>2]=3;break a}else{if((f|0)!=2)break a;e=(c[j+260>>2]|0)+2|0;c[j+328>>2]=0;c[j+328+4>>2]=0;c[j+328+8>>2]=0;c[j+328+12>>2]=0;c[j+260>>2]=e;c[j+312>>2]=0;c[j+312+4>>2]=0;c[j+312+8>>2]=0;c[j+312+12>>2]=0;e=c[b+232>>2]|0;break a}}while(0);if((h|0)!=4)c[j+216>>2]=1}while(0);k=k+1|0}while((k|0)<(e|0))}e=c[2357]|0;b=(c[e+16>>2]|0)+-1|0;c[e+16>>2]=b;if(b|0){i=m;return}do if(c[e+4>>2]|0){tb(m|0,0)|0;b=c[6434]|0;g[e+8>>2]=+g[e+8>>2]+ +(((c[m+4>>2]|0)-(c[b+4>>2]|0)+(((c[m>>2]|0)-(c[b>>2]|0)|0)*1e6|0)-(c[e+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[e+16>>2]|0)){e=c[2357]|0;break}else{i=m;return}}while(0);c[2357]=c[e+20>>2];i=m;return}function $f(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0,G=0.0,H=0;H=i;i=i+32|0;k=+g[b+16>>2];f=+g[b>>2];l=+g[b+20>>2];h=+g[b+4>>2];n=+g[b+24>>2];j=+g[b+8>>2];r=+g[b+32>>2];v=+g[b+36>>2];w=+g[b+40>>2];B=(l-h)*(w-j)-(n-j)*(v-h);C=(n-j)*(r-f)-(k-f)*(w-j);D=(k-f)*(v-h)-(l-h)*(r-f);g[H+16>>2]=B;g[H+16+4>>2]=C;g[H+16+8>>2]=D;g[H+16+12>>2]=0.0;o=+g[a+4>>2];s=+g[a+8>>2];x=+g[a+12>>2];E=B*o+C*s+D*x-(f*B+h*C+j*D);p=+g[a+20>>2];t=+g[a+24>>2];y=+g[a+28>>2];if(E*(B*p+C*t+D*y-(f*B+h*C+j*D))>=0.0){i=H;return}F=c[a+36>>2]|0;if(E<=0.0&(F&1|0)!=0){i=H;return}G=E/(E-(B*p+C*t+D*y-(f*B+h*C+j*D)));if(!(G<+g[a+40>>2])){i=H;return}A=(B*B+C*C+D*D)*-9.999999747378752e-05;z=f-(p*G+o*(1.0-G));u=h-(t*G+s*(1.0-G));q=j-(y*G+x*(1.0-G));m=k-(p*G+o*(1.0-G));l=l-(t*G+s*(1.0-G));k=n-(y*G+x*(1.0-G));if(!(D*(z*l-u*m)+(B*(u*k-q*l)+C*(q*m-z*k))>=A)){i=H;return}j=r-(p*G+o*(1.0-G));h=v-(t*G+s*(1.0-G));f=w-(y*G+x*(1.0-G));if(!(D*(m*h-l*j)+(B*(l*f-k*h)+C*(k*j-m*f))>=A)){i=H;return}if(!(D*(u*j-z*h)+(B*(q*h-u*f)+C*(z*f-q*j))>=A)){i=H;return}f=1.0/+O(+(B*B+C*C+D*D));g[H+16>>2]=B*f;g[H+16+4>>2]=C*f;g[H+16+8>>2]=D*f;b=c[(c[a>>2]|0)+12>>2]|0;if(E<=0.0&(F&2|0)==0){g[H>>2]=-(B*f);g[H+4>>2]=-(C*f);g[H+8>>2]=-(D*f);g[H+12>>2]=0.0;g[a+40>>2]=+ec[b&3](a,H,G,d,e);i=H;return}else{g[a+40>>2]=+ec[b&3](a,H+16|0,G,d,e);i=H;return}}function ag(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0,l=0,m=0,n=0;l=i;i=i+144|0;j=c[b+12>>2]|0;if(!j){i=l;return}n=c[d+4>>2]|0;m=c[e+4>>2]|0;c[h+4>>2]=j;g[l+12+128>>2]=999999984306749440.0;d=c[d+12>>2]|0;c[l+12>>2]=c[d>>2];c[l+12+4>>2]=c[d+4>>2];c[l+12+8>>2]=c[d+8>>2];c[l+12+12>>2]=c[d+12>>2];c[l+12+16>>2]=c[d+16>>2];c[l+12+16+4>>2]=c[d+16+4>>2];c[l+12+16+8>>2]=c[d+16+8>>2];c[l+12+16+12>>2]=c[d+16+12>>2];c[l+12+32>>2]=c[d+32>>2];c[l+12+32+4>>2]=c[d+32+4>>2];c[l+12+32+8>>2]=c[d+32+8>>2];c[l+12+32+12>>2]=c[d+32+12>>2];c[l+12+48>>2]=c[d+48>>2];c[l+12+48+4>>2]=c[d+48+4>>2];c[l+12+48+8>>2]=c[d+48+8>>2];c[l+12+48+12>>2]=c[d+48+12>>2];e=c[e+12>>2]|0;c[l+12+64>>2]=c[e>>2];c[l+12+64+4>>2]=c[e+4>>2];c[l+12+64+8>>2]=c[e+8>>2];c[l+12+64+12>>2]=c[e+12>>2];c[l+12+80>>2]=c[e+16>>2];c[l+12+80+4>>2]=c[e+16+4>>2];c[l+12+80+8>>2]=c[e+16+8>>2];c[l+12+80+12>>2]=c[e+16+12>>2];c[l+12+96>>2]=c[e+32>>2];c[l+12+96+4>>2]=c[e+32+4>>2];c[l+12+96+8>>2]=c[e+32+8>>2];c[l+12+96+12>>2]=c[e+32+12>>2];c[l+12+112>>2]=c[e+48>>2];c[l+12+112+4>>2]=c[e+48+4>>2];c[l+12+112+8>>2]=c[e+48+8>>2];c[l+12+112+12>>2]=c[e+48+12>>2];c[l>>2]=9284;c[l+4>>2]=n;c[l+8>>2]=m;xc(l,l+12|0,h,c[f+20>>2]|0,0);do if(a[b+8>>0]|0?(k=c[h+4>>2]|0,c[k+748>>2]|0):0){d=c[k+740>>2]|0;e=c[(c[h+8>>2]|0)+8>>2]|0;j=c[(c[h+12>>2]|0)+8>>2]|0;if((d|0)==(e|0)){ef(k,d+4|0,j+4|0);break}else{ef(k,j+4|0,e+4|0);break}}while(0);i=l;return}function bg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,h=0,i=0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0,q=0.0,r=0,s=0.0,t=0;if(!a)return;n=+g[b>>2];o=+g[b+4>>2];q=+g[b+8>>2];s=+g[b+16>>2];m=+g[b+20>>2];l=+g[b+24>>2];c[6435]=(c[6435]|0)+1;b=yc(275)|0;c[(b+4+15&-16)+-4>>2]=b;c[(b+4+15&-16)>>2]=a;k=1;a=64;b=b+4+15&-16;while(1){e=k+-1|0;i=c[b+(e<<2)>>2]|0;do if(((((+g[i>>2]<=s?+g[i+16>>2]>=n:0)?+g[i+4>>2]<=m:0)?+g[i+20>>2]>=o:0)?+g[i+8>>2]<=l:0)?+g[i+24>>2]>=q:0){if(!(c[i+40>>2]|0)){Cb[c[(c[d>>2]|0)+12>>2]&127](d,i);break}j=c[i+36>>2]|0;do if((e|0)==(a|0)?(p=a|0?a<<1:1,(k|0)<=(p|0)):0){if((p|0)!=0?(c[6435]=(c[6435]|0)+1,r=yc((p<<2|3)+16|0)|0,(r|0)!=0):0){c[(r+4+15&-16)+-4>>2]=r;h=r+4+15&-16}else h=0;if((k|0)<=1){if(!b){a=p;b=h;break}}else{f=0;do{c[h+(f<<2)>>2]=c[b+(f<<2)>>2];f=f+1|0}while((f|0)!=(a|0))}c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0);a=p;b=h}while(0);c[b+(e<<2)>>2]=j;h=c[i+40>>2]|0;do if((k|0)==(a|0)){a=k|0?k<<1:1;if((k|0)<(a|0)){if((a|0)!=0?(c[6435]=(c[6435]|0)+1,t=yc((a<<2|3)+16|0)|0,(t|0)!=0):0){c[(t+4+15&-16)+-4>>2]=t;f=t+4+15&-16}else f=0;if((k|0)<=0){if(!b){b=f;break}}else{e=0;do{c[f+(e<<2)>>2]=c[b+(e<<2)>>2];e=e+1|0}while((e|0)!=(k|0))}c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0);b=f}else a=k}while(0);c[b+(k<<2)>>2]=h;e=k+1|0}while(0);if((e|0)>0)k=e;else break}if(!b)return;c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0);return}function cg(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0;if((c[b+104>>2]|0)>0){l=0;do{h=c[(c[b+4>>2]|0)+684>>2]|0;i=(c[b+112>>2]|0)+(l<<3)+4|0;d=c[i>>2]|0;if((c[h+60>>2]|0)>0){k=0;do{j=(c[h+68>>2]|0)+(k<<2)|0;e=c[j>>2]|0;a:do if(e|0){f=0;do{g=f+280|0;b:do if(!f)while(1){f=e;e=c[e+280>>2]|0;if((c[f+276>>2]|0)!=(d|0))break b;c[j>>2]=e;hd(f);if(!e)break a}else while(1){f=e;e=c[e+280>>2]|0;if((c[f+276>>2]|0)!=(d|0))break b;c[g>>2]=e;hd(f);if(!e)break a}while(0)}while((e|0)!=0)}while(0);k=k+1|0}while((k|0)<(c[h+60>>2]|0));d=c[i>>2]|0}if(d|0)Ab[c[(c[d>>2]|0)+4>>2]&255](d);l=l+1|0}while((l|0)<(c[b+104>>2]|0))}d=c[b+72>>2]|0;if(d|0){if(a[b+76>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+72>>2]=0}a[b+76>>0]=1;c[b+72>>2]=0;c[b+64>>2]=0;c[b+68>>2]=0;d=c[b+92>>2]|0;if(d|0){if(a[b+96>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+92>>2]=0}a[b+96>>0]=1;c[b+92>>2]=0;c[b+84>>2]=0;c[b+88>>2]=0;d=c[b+112>>2]|0;if(d|0){if(a[b+116>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+112>>2]=0}a[b+116>>0]=1;c[b+112>>2]=0;c[b+104>>2]=0;c[b+108>>2]=0;d=c[b+132>>2]|0;if(!d){a[b+136>>0]=1;c[b+132>>2]=0;c[b+124>>2]=0;b=b+128|0;c[b>>2]=0;return}if(a[b+136>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+132>>2]=0;a[b+136>>0]=1;c[b+132>>2]=0;c[b+124>>2]=0;b=b+128|0;c[b>>2]=0;return}function dg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0;e=c[a+56>>2]|0;if(!e){e=c[a+52>>2]|0;if(!e){c[6435]=(c[6435]|0)+1;e=yc(31)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[a+60>>2]|0;c[e+4>>2]=f;g=e+8|0;c[g>>2]=0;c[6435]=(c[6435]|0)+1;f=yc((f*24|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}c[e>>2]=f;c[g>>2]=c[a+48>>2];c[a+48>>2]=e}else c[a+52>>2]=c[e+8>>2];h=c[e+4>>2]|0;e=c[e>>2]|0;if((h|0)>0){f=0;g=e;do{f=f+1|0;i=g;g=g+24|0;c[i>>2]=(f|0)<(h|0)?g:0}while((f|0)!=(h|0));i=e}else i=e}else i=e;c[a+56>>2]=c[i>>2];c[i>>2]=0;c[i+4>>2]=0;c[i+8>>2]=0;c[i+12>>2]=0;c[i+16>>2]=0;c[i+20>>2]=0;e=c[a+56>>2]|0;if(!e){e=c[a+52>>2]|0;if(!e){c[6435]=(c[6435]|0)+1;e=yc(31)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[a+60>>2]|0;c[e+4>>2]=f;g=e+8|0;c[g>>2]=0;c[6435]=(c[6435]|0)+1;f=yc((f*24|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}c[e>>2]=f;c[g>>2]=c[a+48>>2];c[a+48>>2]=e}else c[a+52>>2]=c[e+8>>2];h=c[e+4>>2]|0;e=c[e>>2]|0;if((h|0)>0){f=0;g=e;do{f=f+1|0;j=g;g=g+24|0;c[j>>2]=(f|0)<(h|0)?g:0}while((f|0)!=(h|0))}}c[a+56>>2]=c[e>>2];c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[i+8>>2]=e;c[e+8>>2]=i;j=c[a+100>>2]|0;c[i+20>>2]=j;c[e+20>>2]=j;c[i+12>>2]=d;c[e+12>>2]=b;c[i+16>>2]=0;c[e+16>>2]=0;e=c[a+116>>2]|0;c[a+116>>2]=e+1;if((e|0)<(c[a+120>>2]|0))return i|0;c[a+120>>2]=e+1;return i|0}function eg(a){a=a|0;var b=0,d=0,e=0,f=0,h=0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0,p=0;b=c[a+752>>2]|0;if((b|0)>0){d=c[a+760>>2]|0;e=0;do{o=c[d+(e*44|0)+8>>2]|0;f=c[d+(e*44|0)+12>>2]|0;h=c[d+(e*44|0)+16>>2]|0;k=+g[o+8>>2];m=+g[o+12>>2];i=+g[o+16>>2];j=+g[f+8>>2]-k;n=+g[f+12>>2]-m;l=+g[f+16>>2]-i;k=+g[h+8>>2]-k;m=+g[h+12>>2]-m;i=+g[h+16>>2]-i;g[d+(e*44|0)+36>>2]=+O(+((j*m-n*k)*(j*m-n*k)+((n*i-l*m)*(n*i-l*m)+(l*k-j*i)*(l*k-j*i))));e=e+1|0}while((e|0)!=(b|0))}d=c[a+712>>2]|0;if((d|0)>0){c[6435]=(c[6435]|0)+1;b=yc((d<<2|3)+16|0)|0;if(!b)f=0;else{c[(b+4+15&-16)+-4>>2]=b;f=b+4+15&-16}Qn(f|0,0,d<<2|0)|0;d=c[a+712>>2]|0;if((d|0)>0){b=c[a+720>>2]|0;e=0;do{g[b+(e*104|0)+92>>2]=0.0;e=e+1|0}while((e|0)!=(d|0));h=f}else h=f}else h=0;f=c[a+752>>2]|0;if((f|0)>0){b=c[a+760>>2]|0;d=c[a+720>>2]|0;e=0;do{n=+N(+(+g[b+(e*44|0)+36>>2]));o=c[b+(e*44|0)+8>>2]|0;p=h+(((o-d|0)/104|0)<<2)|0;c[p>>2]=(c[p>>2]|0)+1;g[o+92>>2]=n+ +g[o+92>>2];o=c[b+(e*44|0)+12>>2]|0;p=h+(((o-d|0)/104|0)<<2)|0;c[p>>2]=(c[p>>2]|0)+1;g[o+92>>2]=n+ +g[o+92>>2];o=c[b+(e*44|0)+16>>2]|0;p=h+(((o-d|0)/104|0)<<2)|0;c[p>>2]=(c[p>>2]|0)+1;g[o+92>>2]=n+ +g[o+92>>2];e=e+1|0}while((e|0)!=(f|0));d=c[a+712>>2]|0}if((d|0)<=0){if(!h)return}else{e=0;do{b=c[h+(e<<2)>>2]|0;if((b|0)>0){p=(c[a+720>>2]|0)+(e*104|0)+92|0;g[p>>2]=+g[p>>2]/+(b|0)}else g[(c[a+720>>2]|0)+(e*104|0)+92>>2]=0.0;e=e+1|0}while((e|0)!=(d|0))}c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0);return}function fg(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,j=0,k=0,l=0;l=i;i=i+16|0;j=c[b+28>>2]|0;k=c[b+32>>2]|0;if(!(a[b+1301>>0]|0)){h=0;e=Nf(b,d,0,j+4|0,k+4|0,j+312|0,k+312|0,j+328|0,k+328|0)|0;do{f=b+868+(h<<6)|0;if(!((c[b+868+(h<<6)+56>>2]|0)==0?(a[b+868+(h<<6)+44>>0]|0)==0:0)){g=b+1208+(h<<4)|0;c[l>>2]=c[g>>2];c[l+4>>2]=c[g+4>>2];c[l+8>>2]=c[g+8>>2];c[l+12>>2]=c[g+12>>2];g=c[b+1304>>2]>>(h*3|0)+9;if(!(g&1))c[b+868+(h<<6)+28>>2]=c[c[d+32>>2]>>2];if(!(g&2))c[b+868+(h<<6)+36>>2]=c[c[d+32>>2]>>2];if(!(g&4))c[b+868+(h<<6)+32>>2]=c[d+4>>2];e=(Dd(b,f,j+4|0,k+4|0,j+312|0,k+312|0,j+328|0,k+328|0,d,e,l,1,0)|0)+e|0}h=h+1|0}while((h|0)!=3);i=l;return}h=0;e=0;do{f=b+868+(h<<6)|0;if(!((c[b+868+(h<<6)+56>>2]|0)==0?(a[b+868+(h<<6)+44>>0]|0)==0:0)){g=b+1208+(h<<4)|0;c[l>>2]=c[g>>2];c[l+4>>2]=c[g+4>>2];c[l+8>>2]=c[g+8>>2];c[l+12>>2]=c[g+12>>2];g=c[b+1304>>2]>>(h*3|0)+9;if(!(g&1))c[b+868+(h<<6)+28>>2]=c[c[d+32>>2]>>2];if(!(g&2))c[b+868+(h<<6)+36>>2]=c[c[d+32>>2]>>2];if(!(g&4))c[b+868+(h<<6)+32>>2]=c[d+4>>2];e=(Dd(b,f,j+4|0,k+4|0,j+312|0,k+312|0,j+328|0,k+328|0,d,e,l,1,0)|0)+e|0}h=h+1|0}while((h|0)!=3);Nf(b,d,e,j+4|0,k+4|0,j+312|0,k+312|0,j+328|0,k+328|0)|0;i=l;return}function gg(b){b=b|0;var d=0,e=0,f=0,h=0.0,i=0.0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0,s=0.0,t=0.0,u=0.0,v=0.0;d=c[b+988>>2]|0;if(d|0)xn(b+988|0,d);d=c[b+992>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+992>>2]=0;c[b+996>>2]=-1;d=c[b+1020>>2]|0;if(d|0){if(a[b+1024>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+1020>>2]=0}a[b+1024>>0]=1;c[b+1020>>2]=0;c[b+1012>>2]=0;c[b+1016>>2]=0;c[b+1004>>2]=0;if((c[b+752>>2]|0)<=0)return;r=0;do{j=c[b+760>>2]|0;k=j+(r*44|0)|0;e=c[j+(r*44|0)+8>>2]|0;f=c[j+(r*44|0)+12>>2]|0;d=c[j+(r*44|0)+16>>2]|0;o=+g[e+8>>2];p=+g[e+12>>2];q=+g[e+16>>2];i=+g[e+20>>2];v=+g[f+8>>2];l=v>2];m=s>2];n=t>2];h=u>2];l=u>2];m=t>2];n=s>2];h=v>2]|0;if(!d){c[6435]=(c[6435]|0)+1;d=yc(63)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=d;f=e+44|0;do{c[e>>2]=0;e=e+4|0}while((e|0)<(f|0))}else c[b+992>>2]=0;c[d+32>>2]=0;c[d+36>>2]=k;c[d+40>>2]=0;g[d>>2]=l;g[d+4>>2]=m;g[d+8>>2]=n;g[d+12>>2]=h;g[d+16>>2]=o;g[d+20>>2]=p;g[d+24>>2]=q;g[d+28>>2]=i;lf(b+988|0,c[b+988>>2]|0,d);c[b+1e3>>2]=(c[b+1e3>>2]|0)+1;c[j+(r*44|0)+40>>2]=d;r=r+1|0}while((r|0)<(c[b+752>>2]|0));return}function hg(b){b=b|0;var d=0,e=0.0,f=0,h=0,j=0.0,k=0.0,l=0;l=i;i=i+64|0;li(11978);a:do if(!(a[b+274>>0]|0)){d=c[b+232>>2]|0;if((d|0)>0){h=0;while(1){f=c[(c[b+240>>2]|0)+(h<<2)>>2]|0;switch(c[f+216>>2]|0){case 2:case 5:break;default:if((c[f+480>>2]|0)!=0?(c[f+204>>2]&3|0)==0:0){if((a[b+300>>0]|0)!=0?(k=+g[b+268>>2],k!=0.0):0)e=+g[b+264>>2]-k;else e=+g[b+264>>2]*+g[f+244>>2];Zg(f+68|0,+g[f+132>>2],+g[f+136>>2],+g[f+140>>2],f+148|0,e,l);d=c[f+480>>2]|0;Cb[c[(c[d>>2]|0)+12>>2]&127](d,l);d=c[b+232>>2]|0}}h=h+1|0;if((h|0)>=(d|0))break a}}}else{d=c[b+8>>2]|0;if((d|0)>0){h=0;do{f=c[(c[b+16>>2]|0)+(h<<2)>>2]|0;if((!((f|0)==0?1:(c[f+236>>2]&2|0)==0)?(c[f+480>>2]|0)!=0:0)?(c[f+204>>2]&3|0)==0:0){if((a[b+300>>0]|0)!=0?(j=+g[b+268>>2],j!=0.0):0)e=+g[b+264>>2]-j;else e=+g[b+264>>2]*+g[f+244>>2];Zg(f+68|0,+g[f+132>>2],+g[f+136>>2],+g[f+140>>2],f+148|0,e,l);d=c[f+480>>2]|0;Cb[c[(c[d>>2]|0)+12>>2]&127](d,l);d=c[b+8>>2]|0}h=h+1|0}while((h|0)<(d|0))}}while(0);d=c[2357]|0;b=(c[d+16>>2]|0)+-1|0;c[d+16>>2]=b;if(b|0){i=l;return}do if(c[d+4>>2]|0){tb(l|0,0)|0;b=c[6434]|0;g[d+8>>2]=+g[d+8>>2]+ +(((c[l+4>>2]|0)-(c[b+4>>2]|0)+(((c[l>>2]|0)-(c[b>>2]|0)|0)*1e6|0)-(c[d+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[d+16>>2]|0)){d=c[2357]|0;break}else{i=l;return}}while(0);c[2357]=c[d+20>>2];i=l;return}function ig(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0,h=0,j=0,k=0,l=0,m=0,n=0;n=i;i=i+32|0;if((b|0)<0)b=c[a+12>>2]|0;d=c[a>>2]|0;if(!((b|0)>0&(d|0)!=0)){i=n;return}while(1){e=d+40|0;if(c[e>>2]|0){m=0;while(1){l=(c[a+16>>2]|0)>>>m&1;f=d+32|0;g=c[f>>2]|0;if(g>>>0>d>>>0){h=(c[g+40>>2]|0)==(d|0)&1;j=c[g+36+((h^1)<<2)>>2]|0;k=c[g+32>>2]|0;if(!k)c[a>>2]=d;else c[k+36+(((c[k+40>>2]|0)==(g|0)&1)<<2)>>2]=d;c[j+32>>2]=d;c[g+32>>2]=d;c[f>>2]=k;k=d+36|0;c[g+36>>2]=c[k>>2];c[g+40>>2]=c[e>>2];c[(c[k>>2]|0)+32>>2]=g;c[(c[e>>2]|0)+32>>2]=g;c[d+36+(h<<2)>>2]=g;c[d+36+((h^1)<<2)>>2]=j;c[n>>2]=c[g>>2];c[n+4>>2]=c[g+4>>2];c[n+8>>2]=c[g+8>>2];c[n+12>>2]=c[g+12>>2];c[n+16>>2]=c[g+16>>2];c[n+20>>2]=c[g+20>>2];c[n+24>>2]=c[g+24>>2];c[n+28>>2]=c[g+28>>2];c[g>>2]=c[d>>2];c[g+4>>2]=c[d+4>>2];c[g+8>>2]=c[d+8>>2];c[g+12>>2]=c[d+12>>2];c[g+16>>2]=c[d+16>>2];c[g+20>>2]=c[d+20>>2];c[g+24>>2]=c[d+24>>2];c[g+28>>2]=c[d+28>>2];c[d>>2]=c[n>>2];c[d+4>>2]=c[n+4>>2];c[d+8>>2]=c[n+8>>2];c[d+12>>2]=c[n+12>>2];c[d+16>>2]=c[n+16>>2];c[d+20>>2]=c[n+20>>2];c[d+24>>2]=c[n+24>>2];c[d+28>>2]=c[n+28>>2];d=g}d=c[d+36+(l<<2)>>2]|0;e=d+40|0;if(!(c[e>>2]|0))break;else m=m+1&31}}if(!(hh(a,d)|0))e=0;else e=c[a>>2]|0;lf(a,e,d);c[a+16>>2]=(c[a+16>>2]|0)+1;b=b+-1|0;if(!b)break;d=c[a>>2]|0}i=n;return}function jg(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0;j=i;i=i+32|0;d=a[b+8>>0]|0?d:e;if(((c[(c[d+4>>2]|0)+4>>2]|0)+-21|0)>>>0>=9){i=j;return}e=c[(c[d+8>>2]|0)+192>>2]|0;y=+Sb[c[(c[e>>2]|0)+48>>2]&15](e);c[b+64>>2]=f;g[b+68>>2]=y+.05999999865889549;c[b+56>>2]=h;h=c[b+16>>2]|0;ic[c[(c[h>>2]|0)+28>>2]&127](h,j+16|0,j);y=+g[j>>2];x=+g[j+16>>2];w=+g[j+4>>2];v=+g[j+16+4>>2];u=+g[j+8>>2];t=+g[j+16+8>>2];h=c[d+12>>2]|0;B=+g[h>>2];o=+g[h+16>>2];C=+g[h+32>>2];z=+g[h+4>>2];m=+g[h+20>>2];A=+g[h+36>>2];q=+g[h+8>>2];k=+g[h+24>>2];r=+g[h+40>>2];D=-+g[h+48>>2];s=-+g[h+52>>2];l=-+g[h+56>>2];p=(y+x)*.5*B+(w+v)*.5*o+(u+t)*.5*C+(B*D+o*s+C*l);n=(y+x)*.5*z+(w+v)*.5*m+(u+t)*.5*A+(z*D+m*s+A*l);l=(y+x)*.5*q+(w+v)*.5*k+(u+t)*.5*r+(q*D+k*s+r*l);s=+g[b+68>>2];o=((y-x)*.5+s)*+N(+(B+o*0.0+C*0.0))+((w-v)*.5+s)*+N(+(B*0.0+o+C*0.0))+((u-t)*.5+s)*+N(+(C+(B*0.0+o*0.0)));m=((y-x)*.5+s)*+N(+(z+m*0.0+A*0.0))+((w-v)*.5+s)*+N(+(z*0.0+m+A*0.0))+((u-t)*.5+s)*+N(+(A+(z*0.0+m*0.0)));k=((y-x)*.5+s)*+N(+(q+k*0.0+r*0.0))+((w-v)*.5+s)*+N(+(q*0.0+k+r*0.0))+((u-t)*.5+s)*+N(+(r+(q*0.0+k*0.0)));g[b+24>>2]=p-o;g[b+28>>2]=n-m;g[b+32>>2]=l-k;g[b+36>>2]=0.0;g[b+40>>2]=p+o;g[b+44>>2]=n+m;g[b+48>>2]=l+k;g[b+52>>2]=0.0;mc[c[(c[e>>2]|0)+64>>2]&127](e,b+12|0,b+24|0,b+40|0);i=j;return}function kg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,j=0,k=0,l=0,m=0,n=0;l=i;i=i+16|0;c[b+8>>2]=0;c[b+12>>2]=1065353216;c[b+16>>2]=1065353216;c[b+20>>2]=1065353216;g[b+24>>2]=0.0;g[b+44>>2]=.03999999910593033;c[b+52>>2]=0;c[b+56>>2]=1065353216;c[b+60>>2]=1065353216;c[b+64>>2]=1065353216;g[b+68>>2]=0.0;c[b+72>>2]=-1082130432;c[b+76>>2]=-1082130432;c[b+80>>2]=-1082130432;g[b+84>>2]=0.0;a[b+88>>0]=0;c[b>>2]=7256;a[b+108>>0]=1;c[b+104>>2]=0;c[b+96>>2]=0;c[b+100>>2]=0;c[b+4>>2]=4;if((e|0)<=0){c[b+96>>2]=e;vj(b);i=l;return}c[6435]=(c[6435]|0)+1;h=yc((e<<4|3)+16|0)|0;if(!h)k=0;else{c[(h+4+15&-16)+-4>>2]=h;k=h+4+15&-16}h=c[b+96>>2]|0;if((h|0)>0){j=0;do{m=k+(j<<4)|0;n=(c[b+104>>2]|0)+(j<<4)|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];j=j+1|0}while((j|0)!=(h|0))}h=c[b+104>>2]|0;if(h|0){if(a[b+108>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[b+104>>2]=0}a[b+108>>0]=1;c[b+104>>2]=k;c[b+100>>2]=e;c[k>>2]=c[l>>2];c[k+4>>2]=c[l+4>>2];c[k+8>>2]=c[l+8>>2];c[k+12>>2]=c[l+12>>2];if((e|0)!=1){h=1;do{n=(c[b+104>>2]|0)+(h<<4)|0;c[n>>2]=c[l>>2];c[n+4>>2]=c[l+4>>2];c[n+8>>2]=c[l+8>>2];c[n+12>>2]=c[l+12>>2];h=h+1|0}while((h|0)!=(e|0))}c[b+96>>2]=e;j=0;h=d;while(1){n=c[b+104>>2]|0;d=c[h+4>>2]|0;m=c[h+8>>2]|0;c[n+(j<<4)>>2]=c[h>>2];c[n+(j<<4)+4>>2]=d;c[n+(j<<4)+8>>2]=m;g[n+(j<<4)+12>>2]=0.0;j=j+1|0;if((j|0)==(e|0))break;else h=h+f|0}vj(b);i=l;return}function lg(b){b=b|0;var d=0;c[b>>2]=4756;d=c[b+176>>2]|0;if(d|0){if(a[b+180>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+176>>2]=0}a[b+180>>0]=1;c[b+176>>2]=0;c[b+168>>2]=0;c[b+172>>2]=0;d=c[b+156>>2]|0;if(d|0){if(a[b+160>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+156>>2]=0}a[b+160>>0]=1;c[b+156>>2]=0;c[b+148>>2]=0;c[b+152>>2]=0;d=c[b+136>>2]|0;if(d|0){if(a[b+140>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+136>>2]=0}a[b+140>>0]=1;c[b+136>>2]=0;c[b+128>>2]=0;c[b+132>>2]=0;d=c[b+116>>2]|0;if(d|0){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+116>>2]=0}a[b+120>>0]=1;c[b+116>>2]=0;c[b+108>>2]=0;c[b+112>>2]=0;d=c[b+96>>2]|0;if(d|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;d=c[b+76>>2]|0;if(d|0){if(a[b+80>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+76>>2]=0}a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;c[b+72>>2]=0;d=c[b+56>>2]|0;if(d|0){if(a[b+60>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+56>>2]=0}a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;d=c[b+36>>2]|0;if(d|0){if(a[b+40>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+36>>2]=0}a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;d=c[b+16>>2]|0;if(!d){a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}function mg(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0,y=0.0;x=i;i=i+48|0;t=+g[e>>2];u=+g[d>>2];v=+g[e+4>>2];w=+g[d+4>>2];s=+g[e+8>>2];h=+g[d+8>>2];j=+O(+((t-u)*.5*(t-u)*.5+(v-w)*.5*(v-w)*.5+(s-h)*.5*(s-h)*.5));k=+g[a+56>>2];d=+N(+k)>.7071067690849304;l=+g[a+52>>2];if(d){r=1.0/+O(+(k*k+l*l));y=+g[a+48>>2];f=y*-(k*r);m=y;n=0.0;o=-(k*r);p=l*r;q=(k*k+l*l)*r;r=-(y*l*r)}else{q=+g[a+48>>2];r=1.0/+O(+(q*q+l*l));f=(q*q+l*l)*r;m=q;n=-(l*r);o=q*r;p=0.0;q=-(k*q*r);r=k*-(l*r)}y=(t+u)*.5*m+(v+w)*.5*l+(s+h)*.5*k-+g[a+64>>2];m=(t+u)*.5-m*y;n=j*n;o=j*o;u=j*p;q=j*q;r=j*r;t=j*f;g[x>>2]=q+(n+m);g[x+4>>2]=r+(o+((v+w)*.5-l*y));g[x+8>>2]=t+(u+((s+h)*.5-k*y));g[x+12>>2]=0.0;g[x+16>>2]=n+m-q;g[x+20>>2]=o+((v+w)*.5-l*y)-r;g[x+24>>2]=u+((s+h)*.5-k*y)-t;g[x+28>>2]=0.0;g[x+32>>2]=m-n-q;g[x+36>>2]=(v+w)*.5-l*y-o-r;g[x+40>>2]=(s+h)*.5-k*y-u-t;g[x+44>>2]=0.0;mc[c[(c[b>>2]|0)+8>>2]&127](b,x,0,0);g[x>>2]=m-n-q;g[x+4>>2]=(v+w)*.5-l*y-o-r;g[x+8>>2]=(s+h)*.5-k*y-u-t;g[x+12>>2]=0.0;g[x+16>>2]=q+(m-n);g[x+20>>2]=r+((v+w)*.5-l*y-o);g[x+24>>2]=t+((s+h)*.5-k*y-u);g[x+28>>2]=0.0;g[x+32>>2]=q+(n+m);g[x+36>>2]=r+(o+((v+w)*.5-l*y));g[x+40>>2]=t+(u+((s+h)*.5-k*y));g[x+44>>2]=0.0;mc[c[(c[b>>2]|0)+8>>2]&127](b,x,0,1);i=x;return}function ng(a,b,e){a=a|0;b=b|0;e=e|0;mf(a,b,e)|0;c[b+256>>2]=c[a+264>>2];c[b+260>>2]=c[a+268>>2];c[b+264>>2]=c[a+272>>2];c[b+268>>2]=c[a+276>>2];c[b+272>>2]=c[a+280>>2];c[b+276>>2]=c[a+284>>2];c[b+280>>2]=c[a+288>>2];c[b+284>>2]=c[a+292>>2];c[b+288>>2]=c[a+296>>2];c[b+292>>2]=c[a+300>>2];c[b+296>>2]=c[a+304>>2];c[b+300>>2]=c[a+308>>2];c[b+304>>2]=c[a+312>>2];c[b+308>>2]=c[a+316>>2];c[b+312>>2]=c[a+320>>2];c[b+316>>2]=c[a+324>>2];c[b+320>>2]=c[a+328>>2];c[b+324>>2]=c[a+332>>2];c[b+328>>2]=c[a+336>>2];c[b+332>>2]=c[a+340>>2];c[b+448>>2]=c[a+344>>2];c[b+336>>2]=c[a+544>>2];c[b+340>>2]=c[a+548>>2];c[b+344>>2]=c[a+552>>2];c[b+348>>2]=c[a+556>>2];c[b+352>>2]=c[a+348>>2];c[b+356>>2]=c[a+352>>2];c[b+360>>2]=c[a+356>>2];c[b+364>>2]=c[a+360>>2];c[b+368>>2]=c[a+364>>2];c[b+372>>2]=c[a+368>>2];c[b+376>>2]=c[a+372>>2];c[b+380>>2]=c[a+376>>2];c[b+384>>2]=c[a+380>>2];c[b+388>>2]=c[a+384>>2];c[b+392>>2]=c[a+388>>2];c[b+396>>2]=c[a+392>>2];c[b+400>>2]=c[a+396>>2];c[b+404>>2]=c[a+400>>2];c[b+408>>2]=c[a+404>>2];c[b+412>>2]=c[a+408>>2];c[b+416>>2]=c[a+412>>2];c[b+420>>2]=c[a+416>>2];c[b+424>>2]=c[a+420>>2];c[b+428>>2]=c[a+424>>2];c[b+432>>2]=c[a+428>>2];c[b+436>>2]=c[a+432>>2];c[b+440>>2]=c[a+436>>2];c[b+444>>2]=c[a+440>>2];c[b+452>>2]=c[a+444>>2];c[b+456>>2]=c[a+448>>2];c[b+484>>2]=d[a+452>>0];c[b+460>>2]=c[a+456>>2];c[b+464>>2]=c[a+460>>2];c[b+468>>2]=c[a+464>>2];c[b+472>>2]=c[a+468>>2];c[b+476>>2]=c[a+472>>2];c[b+480>>2]=c[a+476>>2];return 11858}function og(b,d,e,f,h){b=b|0;d=+d;e=e|0;f=f|0;h=h|0;var j=0;j=i;i=i+144|0;c[b+164>>2]=1065353216;c[b+168>>2]=1065353216;c[b+172>>2]=1065353216;g[b+176>>2]=0.0;c[b+180>>2]=0;g[b+184>>2]=999999984306749440.0;c[b+188>>2]=0;c[b+188+4>>2]=0;c[b+188+8>>2]=0;c[b+188+12>>2]=0;c[b+204>>2]=1;c[b+208>>2]=-1;c[b+212>>2]=-1;c[b+216>>2]=1;g[b+220>>2]=0.0;g[b+224>>2]=.5;g[b+228>>2]=0.0;g[b+232>>2]=0.0;c[b+236>>2]=1;c[b+240>>2]=0;g[b+244>>2]=1.0;c[b+248>>2]=0;c[b+248+4>>2]=0;c[b+248+8>>2]=0;c[b+248+12>>2]=0;c[b+4>>2]=1065353216;c[b+8>>2]=0;c[b+8+4>>2]=0;c[b+8+8>>2]=0;c[b+8+12>>2]=0;c[b+24>>2]=1065353216;c[b+28>>2]=0;c[b+28+4>>2]=0;c[b+28+8>>2]=0;c[b+28+12>>2]=0;c[b+44>>2]=1065353216;c[b+48>>2]=0;c[b+48+4>>2]=0;c[b+48+8>>2]=0;c[b+48+12>>2]=0;c[b+48+16>>2]=0;c[b>>2]=4108;a[b+500>>0]=1;c[b+496>>2]=0;c[b+488>>2]=0;c[b+492>>2]=0;g[j>>2]=d;c[j+4>>2]=e;c[j+72>>2]=f;c[j+76>>2]=c[h>>2];c[j+76+4>>2]=c[h+4>>2];c[j+76+8>>2]=c[h+8>>2];c[j+76+12>>2]=c[h+12>>2];g[j+92>>2]=0.0;g[j+96>>2]=0.0;g[j+100>>2]=.5;g[j+104>>2]=0.0;g[j+108>>2]=0.0;g[j+112>>2]=.800000011920929;g[j+116>>2]=1.0;a[j+120>>0]=0;g[j+124>>2]=.004999999888241291;g[j+128>>2]=.009999999776482582;g[j+132>>2]=.009999999776482582;g[j+136>>2]=.009999999776482582;c[j+8>>2]=1065353216;c[j+12>>2]=0;c[j+12+4>>2]=0;c[j+12+8>>2]=0;c[j+12+12>>2]=0;c[j+28>>2]=1065353216;c[j+32>>2]=0;c[j+32+4>>2]=0;c[j+32+8>>2]=0;c[j+32+12>>2]=0;c[j+48>>2]=1065353216;c[j+52>>2]=0;c[j+52+4>>2]=0;c[j+52+8>>2]=0;c[j+52+12>>2]=0;c[j+52+16>>2]=0;Od(b,j);i=j;return}function pg(b,d){b=b|0;d=d|0;var e=0,f=0,h=0,i=0;c[6435]=(c[6435]|0)+1;e=yc(627)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e+4>>2]=5;c[e>>2]=4432;c[e+8>>2]=-1;c[e+12>>2]=-1;g[e+16>>2]=3402823466385288598117041.0e14;a[e+20>>0]=1;a[e+21>>0]=0;c[e+24>>2]=-1;c[e+28>>2]=b;Il();c[e+32>>2]=23268;g[e+36>>2]=0.0;g[e+40>>2]=.30000001192092896;c[e+44>>2]=0;c[e>>2]=4648;h=e+300|0;c[h>>2]=c[d>>2];c[h+4>>2]=c[d+4>>2];c[h+8>>2]=c[d+8>>2];c[h+12>>2]=c[d+12>>2];f=e+316|0;c[f>>2]=c[d+16>>2];c[f+4>>2]=c[d+16+4>>2];c[f+8>>2]=c[d+16+8>>2];c[f+12>>2]=c[d+16+12>>2];b=e+332|0;c[b>>2]=c[d+32>>2];c[b+4>>2]=c[d+32+4>>2];c[b+8>>2]=c[d+32+8>>2];c[b+12>>2]=c[d+32+12>>2];i=e+348|0;c[i>>2]=c[d+48>>2];c[i+4>>2]=c[d+48+4>>2];c[i+8>>2]=c[d+48+8>>2];c[i+12>>2]=c[d+48+12>>2];d=e+364|0;a[e+527>>0]=0;c[d>>2]=c[h>>2];c[d+4>>2]=c[h+4>>2];c[d+8>>2]=c[h+8>>2];c[d+12>>2]=c[h+12>>2];d=e+380|0;c[d>>2]=c[f>>2];c[d+4>>2]=c[f+4>>2];c[d+8>>2]=c[f+8>>2];c[d+12>>2]=c[f+12>>2];d=e+396|0;c[d>>2]=c[b>>2];c[d+4>>2]=c[b+4>>2];c[d+8>>2]=c[b+8>>2];c[d+12>>2]=c[b+12>>2];d=e+412|0;a[e+524>>0]=0;a[e+525>>0]=0;a[e+526>>0]=0;a[e+552>>0]=0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;g[e+572>>2]=-1.0;g[e+444>>2]=999999984306749440.0;g[e+448>>2]=999999984306749440.0;g[e+452>>2]=999999984306749440.0;g[e+428>>2]=1.0;g[e+432>>2]=.30000001192092896;g[e+436>>2]=1.0;g[e+440>>2]=.009999999776482582;g[e+456>>2]=.05000000074505806;c[e+592>>2]=0;g[e+596>>2]=0.0;g[e+600>>2]=.699999988079071;g[e+604>>2]=0.0;return e|0}function qg(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0;Zd(b,d);c[b>>2]=3068;c[6435]=(c[6435]|0)+1;e=yc(27)|0;i=e+4+15&-16;c[i+-4>>2]=e;a[i+4>>0]=0;c[(e+4+15&-16)>>2]=3100;c[b+92>>2]=i;c[6435]=(c[6435]|0)+1;i=yc(27)|0;e=i+4+15&-16;c[e+-4>>2]=i;a[e+4>>0]=0;c[(i+4+15&-16)>>2]=3120;c[b+96>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e>>2]=3120;c[b+100>>2]=e;a[e+4>>0]=1;c[6435]=(c[6435]|0)+1;i=yc(27)|0;e=i+4+15&-16;c[e+-4>>2]=i;a[e+4>>0]=0;c[(i+4+15&-16)>>2]=3140;c[b+104>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e>>2]=3160;c[b+108>>2]=e;a[e+4>>0]=1;if(!(a[b+20>>0]|0))return;e=c[b+16>>2]|0;if(!e)return;if((c[e>>2]|0)>=156)return;f=c[e+16>>2]|0;if(f){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0);e=c[b+16>>2]|0;if(!e)i=b+16|0;else{f=b+16|0;g=11}}else{f=b+16|0;g=11}if((g|0)==11){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);i=f}c[6435]=(c[6435]|0)+1;e=yc(39)|0;if(!e)h=0;else{c[(e+4+15&-16)+-4>>2]=e;h=e+4+15&-16}e=c[d+12>>2]|0;c[h>>2]=156;f=h+4|0;c[f>>2]=e;c[6435]=(c[6435]|0)+1;e=yc((e*156|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[h+16>>2]=e;c[h+12>>2]=e;f=c[f>>2]|0;c[h+8>>2]=f;if(f+-1|0){b=c[h>>2]|0;g=f+-1|0;d=e;do{j=d;d=d+b|0;c[j>>2]=d;g=g+-1|0}while((g|0)!=0);e=e+(_(b,f+-1|0)|0)|0}c[e>>2]=0;c[i>>2]=h;return}function rg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0;c[6435]=(c[6435]|0)+1;h=yc(627)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}c[h+4>>2]=5;c[h+8>>2]=-1;c[h+12>>2]=-1;g[h+16>>2]=3402823466385288598117041.0e14;a[h+20>>0]=1;a[h+21>>0]=0;c[h+24>>2]=-1;c[h+28>>2]=b;c[h+32>>2]=d;g[h+36>>2]=0.0;g[h+40>>2]=.30000001192092896;c[h+44>>2]=0;c[h>>2]=4648;d=h+300|0;c[d>>2]=c[e>>2];c[d+4>>2]=c[e+4>>2];c[d+8>>2]=c[e+8>>2];c[d+12>>2]=c[e+12>>2];d=h+316|0;c[d>>2]=c[e+16>>2];c[d+4>>2]=c[e+16+4>>2];c[d+8>>2]=c[e+16+8>>2];c[d+12>>2]=c[e+16+12>>2];d=h+332|0;c[d>>2]=c[e+32>>2];c[d+4>>2]=c[e+32+4>>2];c[d+8>>2]=c[e+32+8>>2];c[d+12>>2]=c[e+32+12>>2];d=h+348|0;c[d>>2]=c[e+48>>2];c[d+4>>2]=c[e+48+4>>2];c[d+8>>2]=c[e+48+8>>2];c[d+12>>2]=c[e+48+12>>2];e=h+364|0;c[e>>2]=c[f>>2];c[e+4>>2]=c[f+4>>2];c[e+8>>2]=c[f+8>>2];c[e+12>>2]=c[f+12>>2];e=h+380|0;c[e>>2]=c[f+16>>2];c[e+4>>2]=c[f+16+4>>2];c[e+8>>2]=c[f+16+8>>2];c[e+12>>2]=c[f+16+12>>2];e=h+396|0;c[e>>2]=c[f+32>>2];c[e+4>>2]=c[f+32+4>>2];c[e+8>>2]=c[f+32+8>>2];c[e+12>>2]=c[f+32+12>>2];e=h+412|0;c[e>>2]=c[f+48>>2];c[e+4>>2]=c[f+48+4>>2];c[e+8>>2]=c[f+48+8>>2];c[e+12>>2]=c[f+48+12>>2];a[h+552>>0]=0;c[h+524>>2]=0;g[h+572>>2]=-1.0;g[h+444>>2]=999999984306749440.0;g[h+448>>2]=999999984306749440.0;g[h+452>>2]=999999984306749440.0;g[h+428>>2]=1.0;g[h+432>>2]=.30000001192092896;g[h+436>>2]=1.0;g[h+440>>2]=.009999999776482582;g[h+456>>2]=.05000000074505806;c[h+592>>2]=0;g[h+596>>2]=0.0;g[h+600>>2]=.699999988079071;g[h+604>>2]=0.0;return h|0}function sg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0;l=c[d>>2]|0;l=Zb[c[(c[l>>2]|0)+56>>2]&31](l,48)|0;c[l+4>>2]=c[d>>2];c[l>>2]=6228;a[l+28>>0]=1;c[l+24>>2]=0;c[l+16>>2]=0;c[l+20>>2]=0;c[l+32>>2]=c[d+4>>2];a[l+36>>0]=0;c[6435]=(c[6435]|0)+1;b=yc(87)|0;if(!b)k=0;else{c[(b+4+15&-16)+-4>>2]=b;k=b+4+15&-16}c[k>>2]=9324;h=k+20|0;a[h>>0]=1;i=k+16|0;c[i>>2]=0;d=k+8|0;c[d>>2]=0;j=k+12|0;c[j>>2]=0;a[k+24>>0]=0;a[k+44>>0]=1;c[k+40>>2]=0;c[k+32>>2]=0;c[k+36>>2]=0;a[k+64>>0]=1;c[k+60>>2]=0;c[k+52>>2]=0;c[k+56>>2]=0;c[6435]=(c[6435]|0)+1;b=yc(43)|0;if(!b)g=0;else{c[(b+4+15&-16)+-4>>2]=b;g=b+4+15&-16}b=c[d>>2]|0;if((b|0)>0){d=0;do{m=g+(d*12|0)|0;n=(c[i>>2]|0)+(d*12|0)|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];d=d+1|0}while((d|0)!=(b|0))}b=c[i>>2]|0;if(!b){a[h>>0]=1;c[i>>2]=g;c[j>>2]=2;Kf(k);n=l+8|0;c[n>>2]=k;n=e+4|0;n=c[n>>2]|0;n=n+68|0;n=c[n>>2]|0;m=l+40|0;c[m>>2]=n;m=f+4|0;m=c[m>>2]|0;m=m+68|0;m=c[m>>2]|0;n=l+44|0;c[n>>2]=m;return l|0}if(a[h>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}c[i>>2]=0;a[h>>0]=1;c[i>>2]=g;c[j>>2]=2;Kf(k);n=l+8|0;c[n>>2]=k;n=e+4|0;n=c[n>>2]|0;n=n+68|0;n=c[n>>2]|0;m=l+40|0;c[m>>2]=n;m=f+4|0;m=c[m>>2]|0;m=m+68|0;m=c[m>>2]|0;n=l+44|0;c[n>>2]=m;return l|0}function tg(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0;Ab[c[(c[b>>2]|0)+32>>2]&255](b);d=Ob[c[(c[b>>2]|0)+16>>2]&63](b,104,1)|0;e=c[d+8>>2]|0;f=e;g=f+104|0;do{c[f>>2]=0;f=f+4|0}while((f|0)<(g|0));c[e+88>>2]=c[a+248>>2];c[e+92>>2]=c[a+252>>2];c[e+96>>2]=c[a+256>>2];c[e+100>>2]=c[a+260>>2];c[e>>2]=c[a+92>>2];c[e+4>>2]=c[a+96>>2];c[e+8>>2]=c[a+100>>2];c[e+12>>2]=c[a+104>>2];c[e+16>>2]=c[a+108>>2];c[e+20>>2]=c[a+116>>2];c[e+24>>2]=c[a+120>>2];c[e+28>>2]=c[a+124>>2];c[e+32>>2]=c[a+128>>2];c[e+36>>2]=c[a+132>>2];c[e+40>>2]=c[a+140>>2];c[e+44>>2]=c[a+144>>2];c[e+48>>2]=c[a+148>>2];c[e+52>>2]=c[a+152>>2];c[e+56>>2]=c[a+168>>2];c[e+60>>2]=c[a+172>>2];c[e+64>>2]=c[a+112>>2];c[e+68>>2]=c[a+156>>2];c[e+72>>2]=c[a+160>>2];c[e+76>>2]=c[a+164>>2];c[e+80>>2]=c[a+136>>2];yb[c[(c[b>>2]|0)+20>>2]&31](b,d,11938,1145853764,e);d=c[a+8>>2]|0;if((d|0)<=0){mj(a,b);td(a,b);a=c[b>>2]|0;a=a+36|0;a=c[a>>2]|0;Ab[a&255](b);return}f=0;do{e=c[(c[a+16>>2]|0)+(f<<2)>>2]|0;if(c[e+236>>2]&8){g=Eb[c[(c[e>>2]|0)+16>>2]&127](e)|0;g=Ob[c[(c[b>>2]|0)+16>>2]&63](b,g,1)|0;d=Ob[c[(c[e>>2]|0)+20>>2]&63](e,c[g+8>>2]|0,b)|0;yb[c[(c[b>>2]|0)+20>>2]&31](b,g,d,1497645651,e);d=c[a+8>>2]|0}f=f+1|0}while((f|0)<(d|0));mj(a,b);td(a,b);a=c[b>>2]|0;a=a+36|0;a=c[a>>2]|0;Ab[a&255](b);return}function ug(a,b){a=a|0;b=+b;var d=0,e=0,f=0,h=0,j=0.0,k=0.0,l=0.0;h=i;i=i+32|0;d=c[a+8>>2]|0;if((d|0)<=0){i=h;return}f=0;do{e=c[(c[a+16>>2]|0)+(f<<2)>>2]|0;if((!((e|0)==0?1:(c[e+236>>2]&2|0)==0)?(c[e+216>>2]|0)!=2:0)?!(b==0.0?1:(c[e+204>>2]&2|0)==0):0){d=c[e+480>>2]|0;if(!d)d=e+4|0;else{Cb[c[(c[d>>2]|0)+8>>2]&127](d,e+4|0);d=e+4|0}k=1.0/b*(+g[e+56>>2]-+g[e+120>>2]);l=1.0/b*(+g[e+60>>2]-+g[e+124>>2]);g[e+312>>2]=1.0/b*(+g[e+52>>2]-+g[e+116>>2]);g[e+316>>2]=k;g[e+320>>2]=l;g[e+324>>2]=0.0;Gf(e+68|0,d,h+8|0,h);l=+g[h>>2];k=1.0/b*l*+g[h+8+4>>2];j=1.0/b*l*+g[h+8+8>>2];g[e+328>>2]=1.0/b*+g[h+8>>2]*l;g[e+332>>2]=k;g[e+336>>2]=j;g[e+340>>2]=0.0;c[e+132>>2]=c[e+312>>2];c[e+132+4>>2]=c[e+312+4>>2];c[e+132+8>>2]=c[e+312+8>>2];c[e+132+12>>2]=c[e+312+12>>2];c[e+148>>2]=c[e+328>>2];c[e+148+4>>2]=c[e+328+4>>2];c[e+148+8>>2]=c[e+328+8>>2];c[e+148+12>>2]=c[e+328+12>>2];c[e+68>>2]=c[d>>2];c[e+68+4>>2]=c[d+4>>2];c[e+68+8>>2]=c[d+8>>2];c[e+68+12>>2]=c[d+12>>2];c[e+84>>2]=c[e+20>>2];c[e+84+4>>2]=c[e+20+4>>2];c[e+84+8>>2]=c[e+20+8>>2];c[e+84+12>>2]=c[e+20+12>>2];c[e+100>>2]=c[e+36>>2];c[e+100+4>>2]=c[e+36+4>>2];c[e+100+8>>2]=c[e+36+8>>2];c[e+100+12>>2]=c[e+36+12>>2];c[e+116>>2]=c[e+52>>2];c[e+116+4>>2]=c[e+52+4>>2];c[e+116+8>>2]=c[e+52+8>>2];c[e+116+12>>2]=c[e+52+12>>2];d=c[a+8>>2]|0}f=f+1|0}while((f|0)<(d|0));i=h;return}function vg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0;c[6421]=(c[6421]|0)+1;g=((d<<16|b)+~((d<<16|b)<<15)>>10^(d<<16|b)+~((d<<16|b)<<15))*9|0;l=c[a+40>>2]|0;g=l+(((c[a+12>>2]|0)+-1&((g>>6^g)+~((g>>6^g)<<11)>>16^(g>>6^g)+~((g>>6^g)<<11)))<<2)|0;f=c[g>>2]|0;if((f|0)==-1){n=0;return n|0}m=c[a+16>>2]|0;e=f;while(1){k=m+(e*12|0)|0;if((c[k>>2]|0)==(b|0)?(c[m+(e*12|0)+4>>2]|0)==(d|0):0)break;e=c[(c[a+60>>2]|0)+(e<<2)>>2]|0;if((e|0)==-1){e=0;n=21;break}}if((n|0)==21)return e|0;if(!k){n=0;return n|0}j=c[m+(e*12|0)+8>>2]|0;i=(e*12|0)/12|0;b=c[a+60>>2]|0;if((f|0)!=(i|0)){while(1){d=b+(f<<2)|0;e=c[d>>2]|0;if((e|0)==(i|0))break;else f=e}e=c[b+(i<<2)>>2]|0;if((f|0)==-1)n=11;else c[d>>2]=e}else{e=c[b+(f<<2)>>2]|0;n=11}if((n|0)==11)c[g>>2]=e;g=(c[a+8>>2]|0)+-1|0;if((g|0)==(i|0)){c[a+8>>2]=i;n=j;return n|0}h=c[m+(g*12|0)+4>>2]<<16|c[m+(g*12|0)>>2];h=(h+~(h<<15)>>10^h+~(h<<15))*9|0;h=((h>>6^h)+~((h>>6^h)<<11)>>16^(h>>6^h)+~((h>>6^h)<<11))&(c[a+12>>2]|0)+-1;e=c[l+(h<<2)>>2]|0;b=c[a+60>>2]|0;if((e|0)!=(g|0)){f=e;while(1){d=b+(f<<2)|0;e=c[d>>2]|0;if((e|0)==(g|0))break;else f=e}e=c[b+(g<<2)>>2]|0;if((f|0)==-1)n=19;else c[d>>2]=e}else{e=c[b+(g<<2)>>2]|0;n=19}if((n|0)==19)c[l+(h<<2)>>2]=e;c[k>>2]=c[m+(g*12|0)>>2];c[k+4>>2]=c[m+(g*12|0)+4>>2];c[k+8>>2]=c[m+(g*12|0)+8>>2];n=(c[a+40>>2]|0)+(h<<2)|0;c[(c[a+60>>2]|0)+(i<<2)>>2]=c[n>>2];c[n>>2]=i;c[a+8>>2]=(c[a+8>>2]|0)+-1;n=j;return n|0}function wg(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0;d=c[b+236>>2]|0;if((b|0)==0|(d|0)!=8){if(!((b|0)==0|(d&2|0)==0)){Cb[c[(c[a>>2]|0)+92>>2]&127](a,b);return}d=c[b+188>>2]|0;if(d|0){h=c[a+68>>2]|0;h=Eb[c[(c[h>>2]|0)+36>>2]&127](h)|0;ic[c[(c[h>>2]|0)+40>>2]&127](h,d,c[a+24>>2]|0);h=c[a+68>>2]|0;ic[c[(c[h>>2]|0)+12>>2]&127](h,d,c[a+24>>2]|0);c[b+188>>2]=0}d=c[a+8>>2]|0;if((d|0)<=0)return;e=c[a+16>>2]|0;h=0;while(1){f=e+(h<<2)|0;if((c[f>>2]|0)==(b|0))break;g=h+1|0;if((g|0)<(d|0))h=g;else{i=26;break}}if((i|0)==26)return;if((h|0)>=(d|0))return;c[f>>2]=c[e+(d+-1<<2)>>2];c[(c[a+16>>2]|0)+(d+-1<<2)>>2]=b;c[a+8>>2]=d+-1;return}f=c[a+328>>2]|0;a:do if((f|0)>0){g=c[a+336>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0))break a}if((d|0)<(f|0)){c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+336>>2]|0)+(f+-1<<2)>>2]=b;c[a+328>>2]=f+-1}}while(0);d=c[b+188>>2]|0;if(d|0){h=c[a+68>>2]|0;h=Eb[c[(c[h>>2]|0)+36>>2]&127](h)|0;ic[c[(c[h>>2]|0)+40>>2]&127](h,d,c[a+24>>2]|0);h=c[a+68>>2]|0;ic[c[(c[h>>2]|0)+12>>2]&127](h,d,c[a+24>>2]|0);c[b+188>>2]=0}d=c[a+8>>2]|0;if((d|0)<=0)return;e=c[a+16>>2]|0;h=0;while(1){f=e+(h<<2)|0;if((c[f>>2]|0)==(b|0))break;g=h+1|0;if((g|0)<(d|0))h=g;else{i=26;break}}if((i|0)==26)return;if((h|0)>=(d|0))return;c[f>>2]=c[e+(d+-1<<2)>>2];c[(c[a+16>>2]|0)+(d+-1<<2)>>2]=b;c[a+8>>2]=d+-1;return}function xg(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var i=0;c[6435]=(c[6435]|0)+1;i=yc(783)|0;if(!i)i=0;else{c[(i+4+15&-16)+-4>>2]=i;i=i+4+15&-16}c[i+4>>2]=4;c[i+8>>2]=-1;c[i+12>>2]=-1;g[i+16>>2]=3402823466385288598117041.0e14;a[i+20>>0]=1;a[i+21>>0]=0;c[i+24>>2]=-1;c[i+28>>2]=b;c[i+32>>2]=d;g[i+36>>2]=0.0;g[i+40>>2]=.30000001192092896;c[i+44>>2]=0;c[i>>2]=4704;d=i+552|0;c[d>>2]=c[e>>2];c[d+4>>2]=c[e+4>>2];c[d+8>>2]=c[e+8>>2];c[d+12>>2]=c[e+12>>2];d=i+568|0;c[d>>2]=c[e+16>>2];c[d+4>>2]=c[e+16+4>>2];c[d+8>>2]=c[e+16+8>>2];c[d+12>>2]=c[e+16+12>>2];d=i+584|0;c[d>>2]=c[e+32>>2];c[d+4>>2]=c[e+32+4>>2];c[d+8>>2]=c[e+32+8>>2];c[d+12>>2]=c[e+32+12>>2];d=i+600|0;c[d>>2]=c[e+48>>2];c[d+4>>2]=c[e+48+4>>2];c[d+8>>2]=c[e+48+8>>2];c[d+12>>2]=c[e+48+12>>2];e=i+616|0;c[e>>2]=c[f>>2];c[e+4>>2]=c[f+4>>2];c[e+8>>2]=c[f+8>>2];c[e+12>>2]=c[f+12>>2];e=i+632|0;c[e>>2]=c[f+16>>2];c[e+4>>2]=c[f+16+4>>2];c[e+8>>2]=c[f+16+8>>2];c[e+12>>2]=c[f+16+12>>2];e=i+648|0;c[e>>2]=c[f+32>>2];c[e+4>>2]=c[f+32+4>>2];c[e+8>>2]=c[f+32+8>>2];c[e+12>>2]=c[f+32+12>>2];e=i+664|0;c[e>>2]=c[f+48>>2];c[e+4>>2]=c[f+48+4>>2];c[e+8>>2]=c[f+48+8>>2];c[e+12>>2]=c[f+48+12>>2];g[i+688>>2]=0.0;g[i+692>>2]=-1.0;g[i+696>>2]=.8999999761581421;g[i+700>>2]=.30000001192092896;g[i+704>>2]=1.0;g[i+708>>2]=0.0;g[i+712>>2]=0.0;a[i+716>>0]=0;a[i+736>>0]=0;a[i+737>>0]=0;a[i+738>>0]=0;a[i+739>>0]=1;a[i+740>>0]=h&1;c[i+748>>2]=0;g[i+732>>2]=h?-1.0:1.0;return i|0}function yg(a,b,d){a=a|0;b=+b;d=+d;var e=0,f=0,h=0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0,u=0.0,v=0.0,w=0,x=0.0,y=0.0,z=0.0,A=0.0;h=i;i=i+16|0;d=+g[a+336>>2]*b;b=+g[a+452>>2];e=c[a+792>>2]|0;if((e|0)<=0){i=h;return}f=0;do{t=c[a+800>>2]|0;k=t+(f*96|0)+20|0;w=c[k>>2]|0;o=c[t+(f*96|0)>>2]|0;z=+g[t+(f*96|0)+4>>2];y=+g[t+(f*96|0)+8>>2];x=+g[t+(f*96|0)+12>>2];j=t+(f*96|0)+76|0;v=+g[w+332>>2];q=+g[t+(f*96|0)+84>>2];A=+g[w+336>>2];m=+g[t+(f*96|0)+80>>2];l=+g[j>>2];n=+g[w+328>>2];s=+g[o+8>>2];r=+g[o+12>>2];p=+g[o+16>>2];u=d*(z*+g[w+4>>2]+y*+g[w+8>>2]+x*+g[w+12>>2]+ +g[w+52>>2]-s)+(b*(v*q-A*m+ +g[w+312>>2])-(s-+g[o+24>>2]));q=d*(z*+g[w+20>>2]+y*+g[w+24>>2]+x*+g[w+28>>2]+ +g[w+56>>2]-r)+(b*(+g[w+316>>2]+(A*l-q*n))-(r-+g[o+28>>2]));l=d*(z*+g[w+36>>2]+y*+g[w+40>>2]+x*+g[w+44>>2]+ +g[w+60>>2]-p)+(b*(m*n-v*l+ +g[w+320>>2])-(p-+g[o+32>>2]));v=+g[t+(f*96|0)+24>>2];n=(u*+g[t+(f*96|0)+28>>2]+q*+g[t+(f*96|0)+32>>2]+ +g[t+(f*96|0)+36>>2]*l)*v;m=(u*+g[t+(f*96|0)+44>>2]+q*+g[t+(f*96|0)+48>>2]+l*+g[t+(f*96|0)+52>>2])*v;l=v*(u*+g[t+(f*96|0)+60>>2]+q*+g[t+(f*96|0)+64>>2]+l*+g[t+(f*96|0)+68>>2]);q=+g[t+(f*96|0)+92>>2];g[o+8>>2]=s+n*q;g[o+12>>2]=q*m+r;g[o+16>>2]=q*l+p;k=c[k>>2]|0;g[h>>2]=-n;g[h+4>>2]=-m;g[h+8>>2]=-l;g[h+12>>2]=0.0;gj(k,h,j);f=f+1|0}while((f|0)!=(e|0));i=h;return}function zg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;h=+g[d+100>>2];k=+g[d+16>>2];i=+g[d+20>>2];j=+g[d+24>>2];e=+g[d+108>>2];e=+g[d+112>>2]-h*+g[d+116>>2]-(k*+g[a+64>>2]+i*+g[a+68>>2]+j*+g[a+72>>2]+(+g[d>>2]*+g[a+80>>2]+ +g[d+4>>2]*+g[a+84>>2]+ +g[d+8>>2]*+g[a+88>>2]))*e-e*(+g[d+48>>2]*+g[b+64>>2]+ +g[d+52>>2]*+g[b+68>>2]+ +g[d+56>>2]*+g[b+72>>2]+(+g[d+32>>2]*+g[b+80>>2]+ +g[d+36>>2]*+g[b+84>>2]+ +g[d+40>>2]*+g[b+88>>2]));f=+g[d+120>>2];do if(!(h+e>2];if(h+e>f){g[d+100>>2]=f;e=f-h;break}else{g[d+100>>2]=h+e;break}}else{g[d+100>>2]=f;e=f-h}while(0);if(c[a+240>>2]|0){i=e*i*+g[a+132>>2]*+g[a+116>>2];j=e*j*+g[a+136>>2]*+g[a+120>>2];g[a+64>>2]=+g[a+112>>2]*e*k*+g[a+128>>2]+ +g[a+64>>2];g[a+68>>2]=i+ +g[a+68>>2];g[a+72>>2]=j+ +g[a+72>>2];j=e*+g[a+100>>2]*+g[d+68>>2];k=e*+g[a+104>>2]*+g[d+72>>2];g[a+80>>2]=e*+g[a+96>>2]*+g[d+64>>2]+ +g[a+80>>2];g[a+84>>2]=j+ +g[a+84>>2];g[a+88>>2]=k+ +g[a+88>>2]}if(!(c[b+240>>2]|0))return;k=e*+g[d+52>>2]*+g[b+132>>2]*+g[b+116>>2];j=e*+g[d+56>>2]*+g[b+136>>2]*+g[b+120>>2];g[b+64>>2]=+g[b+112>>2]*e*+g[d+48>>2]*+g[b+128>>2]+ +g[b+64>>2];g[b+68>>2]=k+ +g[b+68>>2];g[b+72>>2]=j+ +g[b+72>>2];j=e*+g[b+100>>2]*+g[d+84>>2];k=e*+g[b+104>>2]*+g[d+88>>2];g[b+80>>2]=e*+g[b+96>>2]*+g[d+80>>2]+ +g[b+80>>2];g[b+84>>2]=j+ +g[b+84>>2];g[b+88>>2]=k+ +g[b+88>>2];return}function Ag(a,b){a=a|0;b=b|0;var d=0,f=0,g=0,h=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0,q=0;p=i;i=i+32|0;o=c[a+92>>2]|0;if(!(Eb[c[(c[o>>2]|0)+56>>2]&127](o)|0)){i=p;return}o=c[a+92>>2]|0;o=Eb[c[(c[o>>2]|0)+28>>2]&127](o)|0;d=c[o+4>>2]|0;if((d|0)>1){Vd(o,0,d+-1|0);d=c[o+4>>2]|0}d=d-(c[a+104>>2]|0)|0;c[p+16>>2]=0;c[p+16+4>>2]=0;c[p+16+8>>2]=0;c[p+16+12>>2]=0;yi(o,d,p+16|0);c[a+104>>2]=0;d=c[o+4>>2]|0;if((d|0)>0){f=0;l=0;m=0;h=0;while(1){k=c[o+12>>2]|0;j=k+(l<<4)|0;q=m;m=c[j>>2]|0;k=k+(l<<4)+4|0;g=c[k>>2]|0;if(!((m|0)==(q|0)&(g|0)==(h|0))){q=m+54|0;h=m+48|0;if(!((((((e[q>>1]|0)>=(e[g+48>>1]|0)?(e[g+54>>1]|0)>=(e[h>>1]|0):0)?(e[q+2>>1]|0)>=(e[g+48+2>>1]|0):0)?(e[g+54+2>>1]|0)>=(e[h+2>>1]|0):0)?(e[q+4>>1]|0)>=(e[g+52>>1]|0):0)?(e[g+54+4>>1]|0)>=(e[m+52>>1]|0):0))n=13}else{g=h;n=13}if((n|0)==13){n=0;f=c[a+92>>2]|0;ic[c[(c[f>>2]|0)+32>>2]&127](f,j,b);c[j>>2]=0;c[k>>2]=0;f=(c[a+104>>2]|0)+1|0;c[a+104>>2]=f;c[6163]=(c[6163]|0)+-1;d=c[o+4>>2]|0}l=l+1|0;if((l|0)>=(d|0))break;else h=g}if((d|0)>1){Vd(o,0,d+-1|0);f=c[a+104>>2]|0;d=c[o+4>>2]|0}}else f=0;c[p>>2]=0;c[p+4>>2]=0;c[p+8>>2]=0;c[p+12>>2]=0;yi(o,d-f|0,p);c[a+104>>2]=0;i=p;return}function Bg(a){a=a|0;var b=0,d=0,e=0.0,f=0.0,h=0.0,i=0,j=0.0,k=0,l=0,m=0.0,n=0.0,o=0,p=0.0;b=c[a+712>>2]|0;if((b|0)>0){d=0;do{l=(c[a+720>>2]|0)+(d*104|0)+72|0;d=d+1|0;c[l>>2]=0;c[l+4>>2]=0;c[l+8>>2]=0;c[l+12>>2]=0}while((d|0)!=(b|0))}b=c[a+752>>2]|0;if((b|0)>0){d=0;do{o=c[a+760>>2]|0;k=c[o+(d*44|0)+12>>2]|0;i=c[o+(d*44|0)+8>>2]|0;j=+g[i+8>>2];e=+g[k+8>>2]-j;f=+g[i+12>>2];h=+g[k+12>>2]-f;m=+g[i+16>>2];n=+g[k+16>>2]-m;l=c[o+(d*44|0)+16>>2]|0;j=+g[l+8>>2]-j;f=+g[l+12>>2]-f;m=+g[l+16>>2]-m;p=1.0/+O(+((e*f-h*j)*(e*f-h*j)+((h*m-n*f)*(h*m-n*f)+(n*j-e*m)*(n*j-e*m))));g[o+(d*44|0)+20>>2]=p*(h*m-n*f);g[o+(d*44|0)+24>>2]=p*(n*j-e*m);g[o+(d*44|0)+28>>2]=(e*f-h*j)*p;c[o+(d*44|0)+32>>2]=0;g[i+72>>2]=h*m-n*f+ +g[i+72>>2];g[i+76>>2]=n*j-e*m+ +g[i+76>>2];g[i+80>>2]=e*f-h*j+ +g[i+80>>2];g[k+72>>2]=h*m-n*f+ +g[k+72>>2];g[k+76>>2]=n*j-e*m+ +g[k+76>>2];g[k+80>>2]=e*f-h*j+ +g[k+80>>2];g[l+72>>2]=h*m-n*f+ +g[l+72>>2];g[l+76>>2]=n*j-e*m+ +g[l+76>>2];g[l+80>>2]=e*f-h*j+ +g[l+80>>2];d=d+1|0}while((d|0)!=(b|0))}l=c[a+712>>2]|0;if((l|0)<=0)return;a=c[a+720>>2]|0;k=0;do{i=a+(k*104|0)+72|0;j=+g[i>>2];b=a+(k*104|0)+76|0;e=+g[b>>2];d=a+(k*104|0)+80|0;f=+g[d>>2];h=+O(+(j*j+e*e+f*f));if(h>1.1920928955078125e-07){g[i>>2]=j*(1.0/h);g[b>>2]=1.0/h*e;g[d>>2]=1.0/h*f}k=k+1|0}while((k|0)!=(l|0));return}function Cg(b,d,e,f){b=b|0;d=+d;e=e|0;f=+f;var h=0,j=0.0,k=0,l=0;l=i;i=i+16|0;tb(c[6434]|0,0)|0;Vq(25696);c[6425]=(c[6425]|0)+1;k=c[6428]|0;c[6428]=k+1;if(!k){tb(l|0,0)|0;k=c[6434]|0;c[6427]=(c[l+4>>2]|0)-(c[k+4>>2]|0)+(((c[l>>2]|0)-(c[k>>2]|0)|0)*1e6|0)}c[6433]=0;tb(l|0,0)|0;li(11963);if(e){g[b+268>>2]=f;j=+g[b+264>>2]+d;g[b+264>>2]=j;if(!(j>=f)){d=f;k=0}else{g[b+264>>2]=j-+(~~(j/f)|0)*f;d=f;k=~~(j/f)}}else{g[b+264>>2]=a[b+300>>0]|0?0.0:d;g[b+268>>2]=0.0;k=!(+N(+d)<1.1920928955078125e-07)&1;e=k}if(Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0){h=Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0;a[26260]=(Eb[c[(c[h>>2]|0)+48>>2]&127](h)|0)>>>4&1}if(k){e=(k|0)>(e|0)?e:k;zb[c[(c[b>>2]|0)+164>>2]&31](b,d*+(e|0));Ab[c[(c[b>>2]|0)+168>>2]&255](b);if((e|0)>0){h=0;do{zb[c[(c[b>>2]|0)+160>>2]&31](b,d);Ab[c[(c[b>>2]|0)+80>>2]&255](b);h=h+1|0}while((h|0)<(e|0));e=b}else e=b}else{Ab[c[(c[b>>2]|0)+80>>2]&255](b);e=b}Ab[c[(c[e>>2]|0)+120>>2]&255](b);c[6433]=(c[6433]|0)+1;e=c[2357]|0;b=(c[e+16>>2]|0)+-1|0;c[e+16>>2]=b;if(b|0){i=l;return k|0}do if(c[e+4>>2]|0){tb(l|0,0)|0;b=c[6434]|0;g[e+8>>2]=+g[e+8>>2]+ +(((c[l+4>>2]|0)-(c[b+4>>2]|0)+(((c[l>>2]|0)-(c[b>>2]|0)|0)*1e6|0)-(c[e+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[e+16>>2]|0)){e=c[2357]|0;break}else{i=l;return k|0}}while(0);c[2357]=c[e+20>>2];i=l;return k|0}function Dg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0;c[6435]=(c[6435]|0)+1;h=yc(783)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}c[h+4>>2]=4;c[h+8>>2]=-1;c[h+12>>2]=-1;g[h+16>>2]=3402823466385288598117041.0e14;a[h+20>>0]=1;a[h+21>>0]=0;c[h+24>>2]=-1;c[h+28>>2]=b;c[h+32>>2]=d;g[h+36>>2]=0.0;g[h+40>>2]=.30000001192092896;c[h+44>>2]=0;c[h>>2]=4704;d=h+552|0;c[d>>2]=c[e>>2];c[d+4>>2]=c[e+4>>2];c[d+8>>2]=c[e+8>>2];c[d+12>>2]=c[e+12>>2];d=h+568|0;c[d>>2]=c[e+16>>2];c[d+4>>2]=c[e+16+4>>2];c[d+8>>2]=c[e+16+8>>2];c[d+12>>2]=c[e+16+12>>2];d=h+584|0;c[d>>2]=c[e+32>>2];c[d+4>>2]=c[e+32+4>>2];c[d+8>>2]=c[e+32+8>>2];c[d+12>>2]=c[e+32+12>>2];d=h+600|0;c[d>>2]=c[e+48>>2];c[d+4>>2]=c[e+48+4>>2];c[d+8>>2]=c[e+48+8>>2];c[d+12>>2]=c[e+48+12>>2];e=h+616|0;c[e>>2]=c[f>>2];c[e+4>>2]=c[f+4>>2];c[e+8>>2]=c[f+8>>2];c[e+12>>2]=c[f+12>>2];e=h+632|0;c[e>>2]=c[f+16>>2];c[e+4>>2]=c[f+16+4>>2];c[e+8>>2]=c[f+16+8>>2];c[e+12>>2]=c[f+16+12>>2];e=h+648|0;c[e>>2]=c[f+32>>2];c[e+4>>2]=c[f+32+4>>2];c[e+8>>2]=c[f+32+8>>2];c[e+12>>2]=c[f+32+12>>2];e=h+664|0;c[e>>2]=c[f+48>>2];c[e+4>>2]=c[f+48+4>>2];c[e+8>>2]=c[f+48+8>>2];c[e+12>>2]=c[f+48+12>>2];g[h+688>>2]=0.0;g[h+692>>2]=-1.0;g[h+696>>2]=.8999999761581421;g[h+700>>2]=.30000001192092896;g[h+704>>2]=1.0;g[h+708>>2]=0.0;g[h+712>>2]=0.0;a[h+716>>0]=0;a[h+736>>0]=0;a[h+737>>0]=0;a[h+738>>0]=0;a[h+739>>0]=1;a[h+740>>0]=0;c[h+748>>2]=0;g[h+732>>2]=1.0;return h|0}function Eg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0,j=0.0,k=0.0,l=0.0,m=0,n=0.0;m=i;i=i+672|0;c[m+568+8>>2]=0;c[m+568+12>>2]=1065353216;c[m+568+16>>2]=1065353216;c[m+568+20>>2]=1065353216;g[m+568+24>>2]=0.0;c[m+568+52>>2]=0;c[m+568>>2]=3736;c[m+568+4>>2]=1;c[m+568+56>>2]=c[d>>2];c[m+568+56+4>>2]=c[d+4>>2];c[m+568+56+8>>2]=c[d+8>>2];c[m+568+56+12>>2]=c[d+12>>2];c[m+568+72>>2]=c[d+16>>2];c[m+568+72+4>>2]=c[d+16+4>>2];c[m+568+72+8>>2]=c[d+16+8>>2];c[m+568+72+12>>2]=c[d+16+12>>2];c[m+568+88>>2]=c[d+32>>2];c[m+568+88+4>>2]=c[d+32+4>>2];c[m+568+88+8>>2]=c[d+32+8>>2];c[m+568+88+12>>2]=c[d+32+12>>2];c[m+568+44>>2]=c[b+204>>2];g[m+208+308>>2]=9.999999747378752e-05;a[m+208+332>>0]=0;c[m+200>>2]=9120;d=c[b+4>>2]|0;c[m+176>>2]=9188;c[m+176+4>>2]=m+208;c[m+176+8>>2]=m+200;c[m+176+12>>2]=d;c[m+176+16>>2]=m+568;c[m+176+20>>2]=0;c[m>>2]=3708;c[m+168>>2]=0;g[m+164>>2]=1.0;c[m+172>>2]=c[b+208>>2];if((Xd(m+176|0,b+8|0,b+72|0,b+136|0,b+136|0,m)|0?(h=+g[m+132>>2],j=+g[m+136>>2],k=+g[m+140>>2],h*h+j*j+k*k>9.999999747378752e-05):0)?(l=+g[m+164>>2],l<+g[b+200>>2]):0){n=1.0/+O(+(h*h+j*j+k*k));g[m+132>>2]=h*n;g[m+136>>2]=j*n;g[m+140>>2]=k*n;+Ub[c[(c[b>>2]|0)+12>>2]&3](b,m+132|0,m+148|0,l,e,f)}c[m+568>>2]=7124;e=c[m+568+52>>2]|0;if(!e){i=m;return}Ab[c[c[e>>2]>>2]&255](e);e=c[m+568+52>>2]|0;if(!e){i=m;return}c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);i=m;return}function Fg(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0,q=0,r=0;q=i;i=i+32|0;p=c[a+12>>2]|0;if(!p){i=q;return}c[f+4>>2]=p;a=c[b+4>>2]|0;r=c[d+4>>2]|0;b=c[b+12>>2]|0;e=c[d+12>>2]|0;h=+g[b+48>>2]-+g[e+48>>2];j=+g[b+52>>2]-+g[e+52>>2];l=+g[b+56>>2]-+g[e+56>>2];m=+O(+(h*h+j*j+l*l));n=+g[r+28>>2]*+g[r+12>>2];o=+g[a+28>>2]*+g[a+12>>2]+n;if(m>o){if(!(c[p+748>>2]|0)){i=q;return}a=c[p+740>>2]|0;b=c[(c[f+8>>2]|0)+8>>2]|0;e=c[(c[f+12>>2]|0)+8>>2]|0;if((a|0)==(b|0)){ef(p,a+4|0,e+4|0);i=q;return}else{ef(p,e+4|0,b+4|0);i=q;return}}c[q+16>>2]=1065353216;c[q+16+4>>2]=0;c[q+16+8>>2]=0;g[q+16+12>>2]=0.0;if(m>1.1920928955078125e-07){g[q+16>>2]=h*(1.0/m);g[q+16+4>>2]=j*(1.0/m);g[q+16+8>>2]=l*(1.0/m);g[q+16+12>>2]=0.0;k=h*(1.0/m);j=j*(1.0/m);h=l*(1.0/m)}else{k=1.0;j=0.0;h=0.0}j=n*j+ +g[e+52>>2];l=n*h+ +g[e+56>>2];g[q>>2]=n*k+ +g[e+48>>2];g[q+4>>2]=j;g[q+8>>2]=l;g[q+12>>2]=0.0;hc[c[(c[f>>2]|0)+16>>2]&15](f,q+16|0,q,m-o);a=c[f+4>>2]|0;do if(c[a+748>>2]|0){b=c[a+740>>2]|0;d=c[(c[f+8>>2]|0)+8>>2]|0;e=c[(c[f+12>>2]|0)+8>>2]|0;if((b|0)==(d|0)){ef(a,b+4|0,e+4|0);break}else{ef(a,e+4|0,d+4|0);break}}while(0);i=q;return}function Gg(a,b){a=a|0;b=b|0;var d=0,e=0;c[6435]=(c[6435]|0)+1;d=yc(219)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}c[d>>2]=2896;e=d+4|0;c[e>>2]=c[a>>2];c[e+4>>2]=c[a+4>>2];c[e+8>>2]=c[a+8>>2];c[e+12>>2]=c[a+12>>2];e=d+20|0;c[e>>2]=c[a+16>>2];c[e+4>>2]=c[a+16+4>>2];c[e+8>>2]=c[a+16+8>>2];c[e+12>>2]=c[a+16+12>>2];e=d+36|0;c[e>>2]=c[a+32>>2];c[e+4>>2]=c[a+32+4>>2];c[e+8>>2]=c[a+32+8>>2];c[e+12>>2]=c[a+32+12>>2];e=d+52|0;c[e>>2]=c[a+48>>2];c[e+4>>2]=c[a+48+4>>2];c[e+8>>2]=c[a+48+8>>2];c[e+12>>2]=c[a+48+12>>2];e=d+68|0;c[e>>2]=c[b>>2];c[e+4>>2]=c[b+4>>2];c[e+8>>2]=c[b+8>>2];c[e+12>>2]=c[b+12>>2];e=d+84|0;c[e>>2]=c[b+16>>2];c[e+4>>2]=c[b+16+4>>2];c[e+8>>2]=c[b+16+8>>2];c[e+12>>2]=c[b+16+12>>2];e=d+100|0;c[e>>2]=c[b+32>>2];c[e+4>>2]=c[b+32+4>>2];c[e+8>>2]=c[b+32+8>>2];c[e+12>>2]=c[b+32+12>>2];e=d+116|0;c[e>>2]=c[b+48>>2];c[e+4>>2]=c[b+48+4>>2];c[e+8>>2]=c[b+48+8>>2];c[e+12>>2]=c[b+48+12>>2];b=d+132|0;c[b>>2]=c[a>>2];c[b+4>>2]=c[a+4>>2];c[b+8>>2]=c[a+8>>2];c[b+12>>2]=c[a+12>>2];b=d+148|0;c[b>>2]=c[a+16>>2];c[b+4>>2]=c[a+16+4>>2];c[b+8>>2]=c[a+16+8>>2];c[b+12>>2]=c[a+16+12>>2];b=d+164|0;c[b>>2]=c[a+32>>2];c[b+4>>2]=c[a+32+4>>2];c[b+8>>2]=c[a+32+8>>2];c[b+12>>2]=c[a+32+12>>2];b=d+180|0;c[b>>2]=c[a+48>>2];c[b+4>>2]=c[a+48+4>>2];c[b+8>>2]=c[a+48+8>>2];c[b+12>>2]=c[a+48+12>>2];c[d+196>>2]=0;return d|0}function Hg(d,e){d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0,k=0;if(!(a[d+164>>0]|0)){f=c[d+148>>2]|0;if((f|0)==(c[d+152>>2]|0)?(k=f|0?f<<1:1,(f|0)<(k|0)):0){if(!k)i=0;else{c[6435]=(c[6435]|0)+1;f=yc((k<<1)+19|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}i=f;f=c[d+148>>2]|0}h=c[d+156>>2]|0;if((f|0)<=0)if(!h)f=d+160|0;else g=27;else{g=0;do{b[i+(g<<1)>>1]=b[h+(g<<1)>>1]|0;g=g+1|0}while((g|0)!=(f|0));g=27}if((g|0)==27){if(a[d+160>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[d+156>>2]=0;f=d+160|0}a[f>>0]=1;c[d+156>>2]=i;c[d+152>>2]=k;f=c[d+148>>2]|0}k=c[d+156>>2]|0;b[k+(f<<1)>>1]=e;c[d+148>>2]=f+1;c[(c[d+32>>2]|0)+4>>2]=k;return}else{f=c[d+128>>2]|0;if((f|0)==(c[d+132>>2]|0)?(j=f|0?f<<1:1,(f|0)<(j|0)):0){if(!j)i=0;else{c[6435]=(c[6435]|0)+1;f=yc((j<<2|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}i=f;f=c[d+128>>2]|0}h=c[d+136>>2]|0;if((f|0)<=0)if(!h)f=d+140|0;else g=12;else{g=0;do{c[i+(g<<2)>>2]=c[h+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0));g=12}if((g|0)==12){if(a[d+140>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[d+136>>2]=0;f=d+140|0}a[f>>0]=1;c[d+136>>2]=i;c[d+132>>2]=j;f=c[d+128>>2]|0}k=c[d+136>>2]|0;c[k+(f<<2)>>2]=e;c[d+128>>2]=(c[d+128>>2]|0)+1;c[(c[d+32>>2]|0)+4>>2]=k;return}}function Ig(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0;e=+g[d+128>>2];if(!(e!=0.0))return;c[5971]=(c[5971]|0)+1;k=+g[d+96>>2];f=+g[d+16>>2];h=+g[d+20>>2];i=+g[d+24>>2];j=+g[d+108>>2];j=e-k*+g[d+116>>2]-(f*+g[a+144>>2]+h*+g[a+148>>2]+i*+g[a+152>>2]+(+g[d>>2]*+g[a+160>>2]+ +g[d+4>>2]*+g[a+164>>2]+ +g[d+8>>2]*+g[a+168>>2]))*j-j*(+g[d+48>>2]*+g[b+144>>2]+ +g[d+52>>2]*+g[b+148>>2]+ +g[d+56>>2]*+g[b+152>>2]+(+g[d+32>>2]*+g[b+160>>2]+ +g[d+36>>2]*+g[b+164>>2]+ +g[d+40>>2]*+g[b+168>>2]));l=+g[d+120>>2];e=k+j>2]=k+j>2]|0){l=e*h*+g[a+132>>2]*+g[a+116>>2];k=e*i*+g[a+136>>2]*+g[a+120>>2];g[a+144>>2]=+g[a+112>>2]*e*f*+g[a+128>>2]+ +g[a+144>>2];g[a+148>>2]=l+ +g[a+148>>2];g[a+152>>2]=k+ +g[a+152>>2];k=e*+g[a+100>>2]*+g[d+68>>2];l=e*+g[a+104>>2]*+g[d+72>>2];g[a+160>>2]=e*+g[a+96>>2]*+g[d+64>>2]+ +g[a+160>>2];g[a+164>>2]=k+ +g[a+164>>2];g[a+168>>2]=l+ +g[a+168>>2]}if(!(c[b+240>>2]|0))return;l=e*+g[d+52>>2]*+g[b+132>>2]*+g[b+116>>2];k=e*+g[d+56>>2]*+g[b+136>>2]*+g[b+120>>2];g[b+144>>2]=+g[b+112>>2]*e*+g[d+48>>2]*+g[b+128>>2]+ +g[b+144>>2];g[b+148>>2]=l+ +g[b+148>>2];g[b+152>>2]=k+ +g[b+152>>2];k=e*+g[b+100>>2]*+g[d+84>>2];l=e*+g[b+104>>2]*+g[d+88>>2];g[b+160>>2]=e*+g[b+96>>2]*+g[d+80>>2]+ +g[b+160>>2];g[b+164>>2]=k+ +g[b+164>>2];g[b+168>>2]=l+ +g[b+168>>2];return}function Jg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0;e=Zb[c[(c[d>>2]|0)+40>>2]&31](d,a)|0;g=Zb[c[(c[d>>2]|0)+28>>2]&31](d,e)|0;c[b>>2]=g;if(g|0)Cb[c[(c[d>>2]|0)+48>>2]&127](d,e);c[b+4>>2]=c[a+4>>2];g=c[a+48>>2]|0;Ob[c[(c[g>>2]|0)+56>>2]&63](g,b+12|0,d)|0;c[b+52>>2]=c[a+12>>2];do if((c[a+52>>2]|0)!=0?((Eb[c[(c[d>>2]|0)+52>>2]&127](d)|0)&1|0)==0:0){e=Zb[c[(c[d>>2]|0)+24>>2]&31](d,c[a+52>>2]|0)|0;if(!e){c[b+40>>2]=Zb[c[(c[d>>2]|0)+28>>2]&31](d,c[a+52>>2]|0)|0;c[b+44>>2]=0;e=c[a+52>>2]|0;e=Eb[c[(c[e>>2]|0)+12>>2]&127](e)|0;e=Ob[c[(c[d>>2]|0)+16>>2]&63](d,e,1)|0;g=c[a+52>>2]|0;g=Ob[c[(c[g>>2]|0)+16>>2]&63](g,c[e+8>>2]|0,d)|0;yb[c[(c[d>>2]|0)+20>>2]&31](d,e,g,1213612625,c[a+52>>2]|0);break}else{c[b+40>>2]=e;c[b+44>>2]=0;break}}else f=8;while(0);if((f|0)==8){c[b+40>>2]=0;c[b+44>>2]=0}if(c[a+56>>2]|0?((Eb[c[(c[d>>2]|0)+52>>2]&127](d)|0)&2|0)==0:0){e=Zb[c[(c[d>>2]|0)+24>>2]&31](d,c[a+56>>2]|0)|0;if(!e){c[b+48>>2]=Zb[c[(c[d>>2]|0)+28>>2]&31](d,c[a+56>>2]|0)|0;b=c[a+56>>2]|0;b=Eb[c[(c[b>>2]|0)+8>>2]&127](b)|0;b=Ob[c[(c[d>>2]|0)+16>>2]&63](d,b,1)|0;g=c[a+56>>2]|0;g=Ob[c[(c[g>>2]|0)+12>>2]&63](g,c[b+8>>2]|0,d)|0;yb[c[(c[d>>2]|0)+20>>2]&31](d,b,g,1346456916,c[a+56>>2]|0);return 16548}else{c[b+48>>2]=e;return 16548}}c[b+48>>2]=0;return 16548}function Kg(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0;c[6422]=(c[6422]|0)+1;k=((e<<16|d)+~((e<<16|d)<<15)>>10^(e<<16|d)+~((e<<16|d)<<15))*9|0;k=(k>>6^k)+~((k>>6^k)<<11)>>16^(k>>6^k)+~((k>>6^k)<<11);l=c[b+12>>2]|0;f=c[(c[b+40>>2]|0)+((l+-1&k)<<2)>>2]|0;a:do if((f|0)!=-1){h=c[b+16>>2]|0;while(1){g=h+(f*12|0)|0;if((c[g>>2]|0)==(d|0)?(c[h+(f*12|0)+4>>2]|0)==(e|0):0)break;f=c[(c[b+60>>2]|0)+(f<<2)>>2]|0;if((f|0)==-1)break a}if(g|0){b=g;return b|0}}while(0);j=c[b+8>>2]|0;if((j|0)==(l|0)){h=l|0?l<<1:1;if((l|0)<(h|0)){if(!h){f=0;g=l}else{c[6435]=(c[6435]|0)+1;f=yc((h*12|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}g=c[b+8>>2]|0}if((g|0)>0){i=0;do{m=f+(i*12|0)|0;n=(c[b+16>>2]|0)+(i*12|0)|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];i=i+1|0}while((i|0)!=(g|0))}g=c[b+16>>2]|0;if(g|0){if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+16>>2]=0}a[b+20>>0]=1;c[b+16>>2]=f;c[b+12>>2]=h;f=c[b+8>>2]|0}else{f=l;h=l}}else{f=j;h=l}c[b+8>>2]=f+1;g=c[b+16>>2]|0;if((l|0)<(h|0)){Kf(b);f=(c[b+12>>2]|0)+-1&k}else f=l+-1&k;c[g+(j*12|0)>>2]=d;c[g+(j*12|0)+4>>2]=e;c[g+(j*12|0)+8>>2]=0;n=(c[b+40>>2]|0)+(f<<2)|0;c[(c[b+60>>2]|0)+(j<<2)>>2]=c[n>>2];c[n>>2]=j;n=g+(j*12|0)|0;return n|0}function Lg(a){a=a|0;var b=0,d=0,e=0;c[6435]=(c[6435]|0)+1;b=yc(219)|0;if(!b)b=0;else{c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16}ml();c[b>>2]=2896;d=b+52|0;e=b+4|0;c[e>>2]=c[a>>2];c[e+4>>2]=c[a+4>>2];c[e+8>>2]=c[a+8>>2];c[e+12>>2]=c[a+12>>2];e=b+20|0;c[e>>2]=c[a+16>>2];c[e+4>>2]=c[a+16+4>>2];c[e+8>>2]=c[a+16+8>>2];c[e+12>>2]=c[a+16+12>>2];e=b+36|0;c[e>>2]=c[a+32>>2];c[e+4>>2]=c[a+32+4>>2];c[e+8>>2]=c[a+32+8>>2];c[e+12>>2]=c[a+32+12>>2];c[d>>2]=c[a+48>>2];c[d+4>>2]=c[a+48+4>>2];c[d+8>>2]=c[a+48+8>>2];c[d+12>>2]=c[a+48+12>>2];d=b+116|0;e=b+68|0;c[e>>2]=c[5710];c[e+4>>2]=c[5711];c[e+8>>2]=c[5712];c[e+12>>2]=c[5713];e=b+84|0;c[e>>2]=c[5714];c[e+4>>2]=c[5715];c[e+8>>2]=c[5716];c[e+12>>2]=c[5717];e=b+100|0;c[e>>2]=c[5718];c[e+4>>2]=c[5719];c[e+8>>2]=c[5720];c[e+12>>2]=c[5721];c[d>>2]=c[5722];c[d+4>>2]=c[5723];c[d+8>>2]=c[5724];c[d+12>>2]=c[5725];d=b+180|0;e=b+132|0;c[e>>2]=c[a>>2];c[e+4>>2]=c[a+4>>2];c[e+8>>2]=c[a+8>>2];c[e+12>>2]=c[a+12>>2];e=b+148|0;c[e>>2]=c[a+16>>2];c[e+4>>2]=c[a+16+4>>2];c[e+8>>2]=c[a+16+8>>2];c[e+12>>2]=c[a+16+12>>2];e=b+164|0;c[e>>2]=c[a+32>>2];c[e+4>>2]=c[a+32+4>>2];c[e+8>>2]=c[a+32+8>>2];c[e+12>>2]=c[a+32+12>>2];c[d>>2]=c[a+48>>2];c[d+4>>2]=c[a+48+4>>2];c[d+8>>2]=c[a+48+8>>2];c[d+12>>2]=c[a+48+12>>2];c[b+196>>2]=0;return b|0}function Mg(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0;k=+g[d+100>>2];h=+g[d+16>>2];e=+g[d+20>>2];f=+g[d+24>>2];j=+g[d+108>>2];j=+g[d+112>>2]-k*+g[d+116>>2]-(h*+g[a+64>>2]+e*+g[a+68>>2]+f*+g[a+72>>2]+(+g[d>>2]*+g[a+80>>2]+ +g[d+4>>2]*+g[a+84>>2]+ +g[d+8>>2]*+g[a+88>>2]))*j-j*(+g[d+48>>2]*+g[b+64>>2]+ +g[d+52>>2]*+g[b+68>>2]+ +g[d+56>>2]*+g[b+72>>2]+(+g[d+32>>2]*+g[b+80>>2]+ +g[d+36>>2]*+g[b+84>>2]+ +g[d+40>>2]*+g[b+88>>2]));l=+g[d+120>>2];i=k+j>2]=k+j>2]|0){l=i*e*+g[a+132>>2]*+g[a+116>>2];k=i*f*+g[a+136>>2]*+g[a+120>>2];g[a+64>>2]=+g[a+112>>2]*i*h*+g[a+128>>2]+ +g[a+64>>2];g[a+68>>2]=l+ +g[a+68>>2];g[a+72>>2]=k+ +g[a+72>>2];k=i*+g[a+100>>2]*+g[d+68>>2];l=i*+g[a+104>>2]*+g[d+72>>2];g[a+80>>2]=i*+g[a+96>>2]*+g[d+64>>2]+ +g[a+80>>2];g[a+84>>2]=k+ +g[a+84>>2];g[a+88>>2]=l+ +g[a+88>>2]}if(!(c[b+240>>2]|0))return;l=i*+g[d+52>>2]*+g[b+132>>2]*+g[b+116>>2];k=i*+g[d+56>>2]*+g[b+136>>2]*+g[b+120>>2];g[b+64>>2]=+g[b+112>>2]*i*+g[d+48>>2]*+g[b+128>>2]+ +g[b+64>>2];g[b+68>>2]=l+ +g[b+68>>2];g[b+72>>2]=k+ +g[b+72>>2];k=i*+g[b+100>>2]*+g[d+84>>2];l=i*+g[b+104>>2]*+g[d+88>>2];g[b+80>>2]=i*+g[b+96>>2]*+g[d+80>>2]+ +g[b+80>>2];g[b+84>>2]=k+ +g[b+84>>2];g[b+88>>2]=l+ +g[b+88>>2];return}function Ng(b,d,e,f,h,i,j,k,l){b=b|0;d=d|0;e=e|0;f=+f;h=+h;i=+i;j=j|0;k=k|0;l=l|0;var m=0,n=0.0,o=0.0,p=0.0;c[6435]=(c[6435]|0)+1;m=yc(143)|0;if(!m)m=0;else{c[(m+4+15&-16)+-4>>2]=m;m=m+4+15&-16}c[m+8>>2]=0;g[m+12>>2]=0.0;c[m>>2]=8060;c[m+4>>2]=24;c[m+64>>2]=b;c[m+68>>2]=d;g[m+72>>2]=h;g[m+76>>2]=i;g[m+80>>2]=+(b+-1|0);g[m+84>>2]=+(d+-1|0);g[m+88>>2]=f;c[m+92>>2]=e;c[m+96>>2]=k;a[m+100>>0]=l&1;a[m+101>>0]=0;a[m+102>>0]=0;c[m+104>>2]=j;c[m+108>>2]=1065353216;c[m+112>>2]=1065353216;c[m+116>>2]=1065353216;g[m+120>>2]=0.0;switch(j|0){case 0:{g[m+16>>2]=h;c[m+20>>2]=0;c[m+24>>2]=0;g[m+28>>2]=0.0;g[m+32>>2]=i;g[m+36>>2]=+(b+-1|0);g[m+40>>2]=+(d+-1|0);g[m+44>>2]=0.0;o=i;p=h;f=+(b+-1|0);n=0.0;i=+(d+-1|0);h=0.0;break}case 1:{c[m+16>>2]=0;g[m+20>>2]=h;c[m+24>>2]=0;g[m+28>>2]=0.0;g[m+32>>2]=+(b+-1|0);g[m+36>>2]=i;g[m+40>>2]=+(d+-1|0);g[m+44>>2]=0.0;o=+(b+-1|0);p=0.0;f=i;n=h;i=+(d+-1|0);h=0.0;break}case 2:{c[m+16>>2]=0;c[m+20>>2]=0;g[m+24>>2]=h;g[m+28>>2]=0.0;g[m+32>>2]=+(b+-1|0);g[m+36>>2]=+(d+-1|0);g[m+40>>2]=i;g[m+44>>2]=0.0;o=+(b+-1|0);p=0.0;f=+(d+-1|0);n=0.0;break}default:{o=+g[m+32>>2];p=+g[m+16>>2];f=+g[m+36>>2];n=+g[m+20>>2];i=+g[m+40>>2];h=+g[m+24>>2]}}g[m+48>>2]=(p+o)*.5;g[m+52>>2]=(n+f)*.5;g[m+56>>2]=(h+i)*.5;g[m+60>>2]=0.0;return m|0}function Og(b,d){b=b|0;d=d|0;var e=0,f=0,h=0,i=0.0,j=0.0,k=0.0,l=0;if(a[b+1308>>0]|0){c[d>>2]=0;c[d+4>>2]=0;return}sd(b,(c[b+28>>2]|0)+4|0,(c[b+32>>2]|0)+4|0);c[d>>2]=0;c[d+4>>2]=6;if((c[b+856>>2]|0)==0?(a[b+788>>0]|0)==0:0){e=0;f=6}else{c[d>>2]=1;c[d+4>>2]=5;e=1;f=5}if(!((c[b+860>>2]|0)==0?(a[b+789>>0]|0)==0:0)){e=e+1|0;c[d>>2]=e;f=f+-1|0;c[d+4>>2]=f}if((c[b+864>>2]|0)==0?(a[b+790>>0]|0)==0:0)l=0;else{e=e+1|0;c[d>>2]=e;f=f+-1|0;c[d+4>>2]=f;l=0}do{i=+g[b+868+(l<<6)>>2];j=+g[b+868+(l<<6)+4>>2];k=+ik(+g[b+1192+(l<<2)>>2],i,j);g[b+868+(l<<6)+52>>2]=k;do if(!(i>j)){if(i>k){c[b+868+(l<<6)+56>>2]=1;h=b+868+(l<<6)+48|0;g[h>>2]=k-i;if(k-i>3.1415927410125732){g[h>>2]=k-i+-6.2831854820251465;h=21;break}if(!(k-i<-3.1415927410125732)){h=21;break}g[h>>2]=k-i+6.2831854820251465;h=21;break}h=b+868+(l<<6)+56|0;if(!(j>2]=0;h=20;break}c[h>>2]=2;h=b+868+(l<<6)+48|0;g[h>>2]=k-j;if(k-j>3.1415927410125732){g[h>>2]=k-j+-6.2831854820251465;h=21;break}if(k-j<-3.1415927410125732){g[h>>2]=k-j+6.2831854820251465;h=21}else h=21}else{c[b+868+(l<<6)+56>>2]=0;h=20}while(0);if((h|0)==20){h=0;if(a[b+868+(l<<6)+44>>0]|0)h=21}if((h|0)==21){e=e+1|0;c[d>>2]=e;f=f+-1|0;c[d+4>>2]=f}l=l+1|0}while((l|0)!=3);return}function Pg(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var g=0,h=0,j=0,k=0,l=0;l=i;i=i+96|0;g=c[b+8>>2]|0;if((g|0)==(c[b+12>>2]|0)?(k=g|0?g<<1:1,(g|0)<(k|0)):0){if(!k)j=0;else{c[6435]=(c[6435]|0)+1;g=yc((k<<2|3)+16|0)|0;if(!g)g=0;else{c[(g+4+15&-16)+-4>>2]=g;g=g+4+15&-16}j=g;g=c[b+8>>2]|0}if((g|0)>0){h=0;do{c[j+(h<<2)>>2]=c[(c[b+16>>2]|0)+(h<<2)>>2];h=h+1|0}while((h|0)!=(g|0))}h=c[b+16>>2]|0;if(h){if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0);g=c[b+8>>2]|0}c[b+16>>2]=0}a[b+20>>0]=1;c[b+16>>2]=j;c[b+12>>2]=k}c[(c[b+16>>2]|0)+(g<<2)>>2]=d;c[b+8>>2]=g+1;c[l+32>>2]=c[d+4>>2];c[l+32+4>>2]=c[d+4+4>>2];c[l+32+8>>2]=c[d+4+8>>2];c[l+32+12>>2]=c[d+4+12>>2];c[l+32+16>>2]=c[d+20>>2];c[l+32+16+4>>2]=c[d+20+4>>2];c[l+32+16+8>>2]=c[d+20+8>>2];c[l+32+16+12>>2]=c[d+20+12>>2];c[l+32+32>>2]=c[d+36>>2];c[l+32+32+4>>2]=c[d+36+4>>2];c[l+32+32+8>>2]=c[d+36+8>>2];c[l+32+32+12>>2]=c[d+36+12>>2];c[l+32+48>>2]=c[d+52>>2];c[l+32+48+4>>2]=c[d+52+4>>2];c[l+32+48+8>>2]=c[d+52+8>>2];c[l+32+48+12>>2]=c[d+52+12>>2];k=c[d+192>>2]|0;mc[c[(c[k>>2]|0)+8>>2]&127](k,l+32|0,l+16|0,l);k=c[b+68>>2]|0;c[d+188>>2]=gc[c[(c[k>>2]|0)+8>>2]&3](k,l+16|0,l,c[(c[d+192>>2]|0)+4>>2]|0,d,e,f,c[b+24>>2]|0,0)|0;i=l;return}function Qg(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0,v=0,w=0.0,x=0,y=0;x=i;i=i+16|0;f=c[a+52>>2]|0;w=+g[a+28+(((f+2|0)%3|0)<<2)>>2];if((e|0)<=0){i=x;return}h=0;while(1){c[x>>2]=0;c[x+4>>2]=0;c[x+8>>2]=0;c[x+12>>2]=0;c[x+(f<<2)>>2]=c[a+28+(f<<2)>>2];f=b+(h<<4)|0;u=b+(h<<4)+4|0;v=b+(h<<4)+8|0;j=w*+g[f>>2]+ +g[x>>2];k=w*+g[u>>2]+ +g[x+4>>2];l=w*+g[v>>2]+ +g[x+8>>2];m=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);n=+g[f>>2];o=+g[u>>2];p=+g[v>>2];if(n*(j-m*n)+o*(k-m*o)+p*(l-m*p)>-999999984306749440.0){g[d+(h<<4)>>2]=j-m*n;g[d+(h<<4)+4>>2]=k-m*o;g[d+(h<<4)+8>>2]=l-m*p;g[d+(h<<4)+12>>2]=0.0;q=+g[f>>2];s=+g[u>>2];t=+g[v>>2];r=n*(j-m*n)+o*(k-m*o)+p*(l-m*p)}else{q=n;s=o;t=p;r=-999999984306749440.0}c[x>>2]=0;c[x+4>>2]=0;c[x+8>>2]=0;c[x+12>>2]=0;y=c[a+52>>2]|0;g[x+(y<<2)>>2]=-+g[a+28+(y<<2)>>2];p=w*q+ +g[x>>2];o=w*s+ +g[x+4>>2];m=w*t+ +g[x+8>>2];n=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);l=+g[f>>2];k=+g[u>>2];j=+g[v>>2];if(l*(p-n*l)+k*(o-n*k)+j*(m-n*j)>r){g[d+(h<<4)>>2]=p-n*l;g[d+(h<<4)+4>>2]=o-n*k;g[d+(h<<4)+8>>2]=m-n*j;g[d+(h<<4)+12>>2]=0.0}h=h+1|0;if((h|0)==(e|0))break;f=c[a+52>>2]|0}i=x;return}function Rg(a,b,d,e,f,h,i,j,k,l){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;i=i|0;j=+j;k=k|0;l=+l;var m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0;c[a>>2]=c[h>>2];c[a+4>>2]=c[h+4>>2];c[a+8>>2]=c[h+8>>2];c[a+12>>2]=c[h+12>>2];s=+g[e+4>>2];v=+g[a+8>>2];w=+g[e+8>>2];p=+g[a+4>>2];m=+g[a>>2];r=+g[e>>2];u=(s*v-w*p)*+g[b>>2]+ +g[b+4>>2]*(w*m-v*r)+(p*r-s*m)*+g[b+8>>2];t=(s*v-w*p)*+g[b+16>>2]+(w*m-v*r)*+g[b+20>>2]+(p*r-s*m)*+g[b+24>>2];s=(s*v-w*p)*+g[b+32>>2]+(w*m-v*r)*+g[b+36>>2]+(p*r-s*m)*+g[b+40>>2];g[a+16>>2]=u;g[a+20>>2]=t;g[a+24>>2]=s;g[a+28>>2]=0.0;r=+g[f+4>>2];w=+g[f+8>>2];n=+g[f>>2];q=+g[d>>2]*(r*-v-w*-p)+ +g[d+4>>2]*(w*-m-n*-v)+(n*-p-r*-m)*+g[d+8>>2];o=(r*-v-w*-p)*+g[d+16>>2]+(w*-m-n*-v)*+g[d+20>>2]+(n*-p-r*-m)*+g[d+24>>2];m=(r*-v-w*-p)*+g[d+32>>2]+(w*-m-n*-v)*+g[d+36>>2]+(n*-p-r*-m)*+g[d+40>>2];g[a+32>>2]=q;g[a+36>>2]=o;g[a+40>>2]=m;g[a+44>>2]=0.0;u=+g[i>>2]*u;t=+g[i+4>>2]*t;s=+g[i+8>>2]*s;g[a+48>>2]=u;g[a+52>>2]=t;g[a+56>>2]=s;g[a+60>>2]=0.0;r=+g[k>>2]*q;p=+g[k+4>>2]*o;n=+g[k+8>>2]*m;g[a+64>>2]=r;g[a+68>>2]=p;g[a+72>>2]=n;g[a+76>>2]=0.0;g[a+80>>2]=u*+g[a+16>>2]+t*+g[a+20>>2]+s*+g[a+24>>2]+j+l+(r*q+p*o+n*m);return}function Sg(b){b=b|0;var d=0,e=0,f=0;c[b>>2]=4144;if(a[b+272>>0]|0?(d=c[b+204>>2]|0,Ab[c[c[d>>2]>>2]&255](d),d=c[b+204>>2]|0,d|0):0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+196>>2]|0;if(d|0?(Ab[c[c[d>>2]>>2]&255](d),e=c[b+196>>2]|0,e|0):0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}if(a[b+273>>0]|0?(f=c[b+200>>2]|0,Ab[c[c[f>>2]>>2]&255](f),f=c[b+200>>2]|0,f|0):0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}d=c[b+316>>2]|0;if(d|0){if(a[b+320>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+316>>2]=0}a[b+320>>0]=1;c[b+316>>2]=0;c[b+308>>2]=0;c[b+312>>2]=0;d=c[b+288>>2]|0;if(d|0){if(a[b+292>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+288>>2]=0}a[b+292>>0]=1;c[b+288>>2]=0;c[b+280>>2]=0;c[b+284>>2]=0;d=c[b+240>>2]|0;if(d|0){if(a[b+244>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+240>>2]=0}a[b+244>>0]=1;c[b+240>>2]=0;c[b+232>>2]=0;c[b+236>>2]=0;d=c[b+220>>2]|0;if(d|0){if(a[b+224>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+220>>2]=0}a[b+224>>0]=1;c[b+220>>2]=0;c[b+212>>2]=0;c[b+216>>2]=0;d=c[b+188>>2]|0;if(!d){a[b+192>>0]=1;c[b+188>>2]=0;c[b+180>>2]=0;f=b+184|0;c[f>>2]=0;_j(b);return}if(a[b+192>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+188>>2]=0;a[b+192>>0]=1;c[b+188>>2]=0;c[b+180>>2]=0;f=b+184|0;c[f>>2]=0;_j(b);return}function Tg(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0;h=i;i=i+64|0;a[d+84>>0]=0;c[h>>2]=c[b+4>>2];c[h+4>>2]=c[b+4+4>>2];c[h+8>>2]=c[b+4+8>>2];c[h+12>>2]=c[b+4+12>>2];c[h+16>>2]=c[b+20>>2];c[h+16+4>>2]=c[b+20+4>>2];c[h+16+8>>2]=c[b+20+8>>2];c[h+16+12>>2]=c[b+20+12>>2];c[h+32>>2]=c[b+36>>2];c[h+32+4>>2]=c[b+36+4>>2];c[h+32+8>>2]=c[b+36+8>>2];c[h+32+12>>2]=c[b+36+12>>2];c[h+48>>2]=c[b+52>>2];c[h+48+4>>2]=c[b+52+4>>2];c[h+48+8>>2]=c[b+52+8>>2];c[h+48+12>>2]=c[b+52+12>>2];if(e?(f=c[b+480>>2]|0,f|0):0)Cb[c[(c[f>>2]|0)+8>>2]&127](f,h);w=+g[d+156>>2];u=+g[h>>2];v=+g[d+160>>2];t=+g[h+4>>2];o=+g[d+164>>2];s=+g[h+8>>2];r=+g[h+16>>2];q=+g[h+20>>2];p=+g[h+24>>2];n=+g[h+32>>2];l=+g[h+36>>2];j=+g[h+40>>2];m=w*r+v*q+o*p+ +g[h+52>>2];k=w*n+v*l+o*j+ +g[h+56>>2];g[d+36>>2]=w*u+v*t+o*s+ +g[h+48>>2];g[d+40>>2]=m;g[d+44>>2]=k;g[d+48>>2]=0.0;k=+g[d+172>>2];m=+g[d+176>>2];o=+g[d+180>>2];g[d+52>>2]=u*k+t*m+s*o;g[d+56>>2]=k*r+m*q+o*p;g[d+60>>2]=k*n+m*l+o*j;g[d+64>>2]=0.0;o=+g[d+188>>2];m=+g[d+192>>2];k=+g[d+196>>2];g[d+68>>2]=u*o+t*m+s*k;g[d+72>>2]=o*r+m*q+k*p;g[d+76>>2]=o*n+m*l+k*j;g[d+80>>2]=0.0;i=h;return}function Ug(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0.0;a:do if(b>>>0<=20)do switch(b|0){case 9:{e=(c[d>>2]|0)+(4-1)&~(4-1);b=c[e>>2]|0;c[d>>2]=e+4;c[a>>2]=b;break a}case 10:{b=(c[d>>2]|0)+(4-1)&~(4-1);e=c[b>>2]|0;c[d>>2]=b+4;c[a>>2]=e;c[a+4>>2]=((e|0)<0)<<31>>31;break a}case 11:{b=(c[d>>2]|0)+(4-1)&~(4-1);e=c[b>>2]|0;c[d>>2]=b+4;c[a>>2]=e;c[a+4>>2]=0;break a}case 12:{f=(c[d>>2]|0)+(8-1)&~(8-1);b=c[f>>2]|0;e=c[f+4>>2]|0;c[d>>2]=f+8;c[a>>2]=b;c[a+4>>2]=e;break a}case 13:{e=(c[d>>2]|0)+(4-1)&~(4-1);f=c[e>>2]|0;c[d>>2]=e+4;c[a>>2]=(f&65535)<<16>>16;c[a+4>>2]=(((f&65535)<<16>>16|0)<0)<<31>>31;break a}case 14:{e=(c[d>>2]|0)+(4-1)&~(4-1);f=c[e>>2]|0;c[d>>2]=e+4;c[a>>2]=f&65535;c[a+4>>2]=0;break a}case 15:{e=(c[d>>2]|0)+(4-1)&~(4-1);f=c[e>>2]|0;c[d>>2]=e+4;c[a>>2]=(f&255)<<24>>24;c[a+4>>2]=(((f&255)<<24>>24|0)<0)<<31>>31;break a}case 16:{e=(c[d>>2]|0)+(4-1)&~(4-1);f=c[e>>2]|0;c[d>>2]=e+4;c[a>>2]=f&255;c[a+4>>2]=0;break a}case 17:{f=(c[d>>2]|0)+(8-1)&~(8-1);g=+h[f>>3];c[d>>2]=f+8;h[a>>3]=g;break a}case 18:{f=(c[d>>2]|0)+(8-1)&~(8-1);g=+h[f>>3];c[d>>2]=f+8;h[a>>3]=g;break a}default:break a}while(0);while(0);return}function Vg(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0,o=0,p=0,q=0,r=0,s=0,t=0,u=0,v=0,w=0,x=0.0,y=0;w=i;i=i+2048|0;if((e|0)>0)f=0;else{i=w;return}do{g[d+(f<<4)+12>>2]=-999999984306749440.0;f=f+1|0}while((f|0)!=(e|0));t=0;do{if((Eb[c[(c[a>>2]|0)+96>>2]&127](a)|0)>0){r=b+(t<<4)|0;s=b+(t<<4)+4|0;o=b+(t<<4)+8|0;p=d+(t<<4)+12|0;q=d+(t<<4)|0;u=0;do{if(((Eb[c[(c[a>>2]|0)+96>>2]&127](a)|0)-u|0)<128){f=(Eb[c[(c[a>>2]|0)+96>>2]&127](a)|0)-u|0;if((f|0)>0)v=10;else{j=-3402823466385288598117041.0e14;f=-1}}else{f=128;v=10}if((v|0)==10){v=0;h=0;do{ic[c[(c[a>>2]|0)+108>>2]&127](a,h,w+(h<<4)|0);h=h+1|0}while((h|0)!=(f|0));k=+g[r>>2];l=+g[s>>2];m=+g[o>>2];n=0;j=-3402823466385288598117041.0e14;h=-1;do{x=k*+g[w+(n<<4)>>2]+l*+g[w+(n<<4)+4>>2]+m*+g[w+(n<<4)+8>>2];y=x>j;h=y?n:h;j=y?x:j;n=n+1|0}while((n|0)!=(f|0));f=h}if(j>+g[p>>2]){y=w+(f<<4)|0;c[q>>2]=c[y>>2];c[q+4>>2]=c[y+4>>2];c[q+8>>2]=c[y+8>>2];c[q+12>>2]=c[y+12>>2];g[p>>2]=j}u=u+128|0}while((u|0)<(Eb[c[(c[a>>2]|0)+96>>2]&127](a)|0))}t=t+1|0}while((t|0)!=(e|0));i=w;return}function Wg(a,b){a=a|0;b=b|0;var d=0.0,e=0.0,f=0.0,h=0,j=0,l=0,m=0,n=0.0;h=i;i=i+16|0;d=+g[a>>2];e=+g[a+20>>2];f=+g[a+40>>2];if(d+e+f>0.0){f=+O(+(d+e+f+1.0));g[h+12>>2]=f*.5;n=(+g[a+36>>2]-+g[a+24>>2])*(.5/f);g[h>>2]=n;d=(+g[a+8>>2]-+g[a+32>>2])*(.5/f);g[h+4>>2]=d;e=(+g[a+16>>2]-+g[a+4>>2])*(.5/f);g[h+8>>2]=e;a=(g[k>>2]=n,c[k>>2]|0);m=(g[k>>2]=d,c[k>>2]|0);l=(g[k>>2]=e,c[k>>2]|0);j=(g[k>>2]=f*.5,c[k>>2]|0);c[b>>2]=a;a=b+4|0;c[a>>2]=m;a=b+8|0;c[a>>2]=l;a=b+12|0;c[a>>2]=j;i=h;return}else{m=d>2]-+g[a+((((m+1|0)>>>0)%3|0)<<4)+((((m+1|0)>>>0)%3|0)<<2)>>2]-+g[a+((((m+2|0)>>>0)%3|0)<<4)+((((m+2|0)>>>0)%3|0)<<2)>>2]+1.0));g[h+(m<<2)>>2]=n*.5;g[h+12>>2]=(+g[a+((((m+2|0)>>>0)%3|0)<<4)+((((m+1|0)>>>0)%3|0)<<2)>>2]-+g[a+((((m+1|0)>>>0)%3|0)<<4)+((((m+2|0)>>>0)%3|0)<<2)>>2])*(.5/n);g[h+((((m+1|0)>>>0)%3|0)<<2)>>2]=(+g[a+((((m+1|0)>>>0)%3|0)<<4)+(m<<2)>>2]+ +g[a+(m<<4)+((((m+1|0)>>>0)%3|0)<<2)>>2])*(.5/n);g[h+((((m+2|0)>>>0)%3|0)<<2)>>2]=(+g[a+((((m+2|0)>>>0)%3|0)<<4)+(m<<2)>>2]+ +g[a+(m<<4)+((((m+2|0)>>>0)%3|0)<<2)>>2])*(.5/n);m=c[h>>2]|0;a=c[h+4>>2]|0;j=c[h+8>>2]|0;l=c[h+12>>2]|0;c[b>>2]=m;m=b+4|0;c[m>>2]=a;m=b+8|0;c[m>>2]=j;m=b+12|0;c[m>>2]=l;i=h;return}}function Xg(a,b){a=a|0;b=b|0;var d=0,e=0;d=i;i=i+48|0;e=(c[a+48>>2]|0)+4|0;c[e>>2]=c[b>>2];c[e+4>>2]=c[b+4>>2];c[e+8>>2]=c[b+8>>2];c[e+12>>2]=c[b+12>>2];c[d+32>>2]=0;c[d+32+4>>2]=0;c[d+32+8>>2]=0;c[d+32+12>>2]=0;g[d+32>>2]=1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d+16|0,a,d+32|0);g[a+32>>2]=+g[d+16>>2]+ +g[a+12>>2];g[d+32>>2]=-1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d,a,d+32|0);c[d+16>>2]=c[d>>2];c[d+16+4>>2]=c[d+4>>2];c[d+16+8>>2]=c[d+8>>2];c[d+16+12>>2]=c[d+12>>2];g[a+16>>2]=+g[d+16>>2]-+g[a+12>>2];c[d+32>>2]=0;c[d+32+4>>2]=0;c[d+32+8>>2]=0;c[d+32+12>>2]=0;g[d+32+4>>2]=1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d+16|0,a,d+32|0);g[a+36>>2]=+g[d+16+4>>2]+ +g[a+12>>2];g[d+32+4>>2]=-1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d,a,d+32|0);c[d+16>>2]=c[d>>2];c[d+16+4>>2]=c[d+4>>2];c[d+16+8>>2]=c[d+8>>2];c[d+16+12>>2]=c[d+12>>2];g[a+20>>2]=+g[d+16+4>>2]-+g[a+12>>2];c[d+32>>2]=0;c[d+32+4>>2]=0;c[d+32+8>>2]=0;c[d+32+12>>2]=0;g[d+32+8>>2]=1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d+16|0,a,d+32|0);g[a+40>>2]=+g[d+16+8>>2]+ +g[a+12>>2];g[d+32+8>>2]=-1.0;ic[c[(c[a>>2]|0)+68>>2]&127](d,a,d+32|0);c[d+16>>2]=c[d>>2];c[d+16+4>>2]=c[d+4>>2];c[d+16+8>>2]=c[d+8>>2];c[d+16+12>>2]=c[d+12>>2];g[a+24>>2]=+g[d+16+8>>2]-+g[a+12>>2];i=d;return}function Yg(a,b,d,e,f,h,j){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;var l=0.0,m=0.0,n=0,o=0.0,p=0.0,q=0,r=0,s=0.0,t=0;r=i;i=i+16|0;g[e>>2]=3402823466385288598117041.0e14;g[f>>2]=-3402823466385288598117041.0e14;n=c[a+96>>2]|0;if((n|0)>0){q=0;do{t=c[a+104>>2]|0;s=+g[t+(q<<4)>>2]*+g[a+12>>2];p=+g[t+(q<<4)+4>>2]*+g[a+16>>2];o=+g[t+(q<<4)+8>>2]*+g[a+20>>2];l=s*+g[b>>2]+p*+g[b+4>>2]+o*+g[b+8>>2]+ +g[b+48>>2];m=s*+g[b+16>>2]+p*+g[b+20>>2]+o*+g[b+24>>2]+ +g[b+52>>2];o=s*+g[b+32>>2]+p*+g[b+36>>2]+o*+g[b+40>>2]+ +g[b+56>>2];p=l*+g[d>>2]+m*+g[d+4>>2]+o*+g[d+8>>2];if(p<+g[e>>2]){g[e>>2]=p;g[h>>2]=l;g[h+4>>2]=m;g[h+8>>2]=o;g[h+12>>2]=0.0}if(p>+g[f>>2]){g[f>>2]=p;g[j>>2]=l;g[j+4>>2]=m;g[j+8>>2]=o;g[j+12>>2]=0.0}q=q+1|0}while((q|0)!=(n|0));s=+g[f>>2];m=s;n=(g[k>>2]=s,c[k>>2]|0)}else{m=-3402823466385288598117041.0e14;n=-8388609}l=+g[e>>2];if(!(l>m)){i=r;return}c[e>>2]=n;g[f>>2]=l;c[r>>2]=c[h>>2];c[r+4>>2]=c[h+4>>2];c[r+8>>2]=c[h+8>>2];c[r+12>>2]=c[h+12>>2];c[h>>2]=c[j>>2];c[h+4>>2]=c[j+4>>2];c[h+8>>2]=c[j+8>>2];c[h+12>>2]=c[j+12>>2];c[j>>2]=c[r>>2];c[j+4>>2]=c[r+4>>2];c[j+8>>2]=c[r+8>>2];c[j+12>>2]=c[r+12>>2];i=r;return}function Zg(a,b,c,d,e,f,h){a=a|0;b=+b;c=+c;d=+d;e=e|0;f=+f;h=h|0;var j=0.0,k=0.0,l=0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0;l=i;i=i+16|0;k=c*f+ +g[a+52>>2];j=d*f+ +g[a+56>>2];g[h+48>>2]=b*f+ +g[a+48>>2];g[h+52>>2]=k;g[h+56>>2]=j;g[h+60>>2]=0.0;j=+g[e>>2];k=+g[e+4>>2];c=+g[e+8>>2];d=+O(+(j*j+k*k+c*c));d=d*f>.7853981852531433?.7853981852531433/f:d;if(d<1.0000000474974513e-03)b=f*.5-d*f*f*f*.02083333395421505*d;else b=+R(+(d*.5*f))/d;o=j*b;n=k*b;j=c*b;q=+Q(+(d*f*.5));Wg(a,l);b=+g[l>>2];p=+g[l+12>>2];c=+g[l+8>>2];f=+g[l+4>>2];r=1.0/+O(+((q*p-o*b-n*f-j*c)*(q*p-o*b-n*f-j*c)+((j*p+q*c+o*f-n*b)*(j*p+q*c+o*f-n*b)+((q*b+o*p+n*c-j*f)*(q*b+o*p+n*c-j*f)+(j*b+(n*p+q*f)-o*c)*(j*b+(n*p+q*f)-o*c)))));d=(q*b+o*p+n*c-j*f)*r;k=r*(j*b+(n*p+q*f)-o*c);m=r*(j*p+q*c+o*f-n*b);c=r*(q*p-o*b-n*f-j*c);j=d*(2.0/(c*c+(m*m+(d*d+k*k))));f=k*(2.0/(c*c+(m*m+(d*d+k*k))));b=m*(2.0/(c*c+(m*m+(d*d+k*k))));g[h>>2]=1.0-(k*f+m*b);g[h+4>>2]=d*f-c*b;g[h+8>>2]=d*b+c*f;g[h+12>>2]=0.0;g[h+16>>2]=d*f+c*b;g[h+20>>2]=1.0-(d*j+m*b);g[h+24>>2]=k*b-c*j;g[h+28>>2]=0.0;g[h+32>>2]=d*b-c*f;g[h+36>>2]=k*b+c*j;g[h+40>>2]=1.0-(d*j+k*f);g[h+44>>2]=0.0;i=l;return}function _g(b,d,e){b=b|0;d=+d;e=e|0;var f=0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0;f=c[b+8>>2]|0;if(f|0?(c[f+204>>2]&3|0)==0:0){if((c[f+216>>2]&-2|0)!=4)c[f+216>>2]=1;g[f+220>>2]=0.0}f=c[b+12>>2]|0;if(f|0?(c[f+204>>2]&3|0)==0:0){if((c[f+216>>2]&-2|0)!=4)c[f+216>>2]=1;g[f+220>>2]=0.0}f=c[b+20>>2]|0;if(f|0?(c[f+204>>2]&3|0)==0:0){if((c[f+216>>2]&-2|0)!=4)c[f+216>>2]=1;g[f+220>>2]=0.0}f=c[b+24>>2]|0;if(f|0?(c[f+204>>2]&3|0)==0:0){if((c[f+216>>2]&-2|0)!=4)c[f+216>>2]=1;g[f+220>>2]=0.0}f=c[b+156>>2]|0;c[b+156>>2]=f+1;a[b+152>>0]=(f|0)>=(c[b+160>>2]|0)&1;if(f|0){c[b+72>>2]=0;c[b+72+4>>2]=0;c[b+72+8>>2]=0;c[b+72+12>>2]=0;c[b+72+16>>2]=0;c[b+72+20>>2]=0;c[b+72+24>>2]=0;c[b+72+28>>2]=0;return}j=+g[b+64>>2];i=1.0/d*+g[b+72>>2]*j;h=1.0/d*j*+g[b+76>>2];d=1.0/d*j*+g[b+80>>2];g[b+72>>2]=i;g[b+76>>2]=h;g[b+80>>2]=d;g[b+84>>2]=0.0;j=+g[b+68>>2];if(j>0.0){l=j*i*+g[b+120>>2]+j*h*+g[b+124>>2]+j*d*+g[b+128>>2];k=j*i*+g[b+136>>2]+j*h*+g[b+140>>2]+j*d*+g[b+144>>2];g[b+88>>2]=j*i*+g[b+104>>2]+j*h*+g[b+108>>2]+j*d*+g[b+112>>2];g[b+92>>2]=l;g[b+96>>2]=k;g[b+100>>2]=0.0;g[b+72>>2]=(1.0-j)*i;g[b+76>>2]=(1.0-j)*h;g[b+80>>2]=(1.0-j)*d;i=(1.0-j)*i;h=(1.0-j)*h;d=(1.0-j)*d}g[b+72>>2]=1.0/+(e|0)*i;g[b+76>>2]=1.0/+(e|0)*h;g[b+80>>2]=1.0/+(e|0)*d;return}function $g(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0;while(1){k=c[a+12>>2]|0;l=c[k+(((b+d|0)/2|0)<<2)>>2]|0;e=b;f=d;while(1){j=c[(c[l+740>>2]|0)+208>>2]|0;if((j|0)>-1)while(1){h=c[k+(e<<2)>>2]|0;g=c[(c[h+740>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+744>>2]|0)+208>>2]|0;if((g|0)<(j|0))e=e+1|0;else break}else{i=c[(c[l+744>>2]|0)+208>>2]|0;while(1){h=c[k+(e<<2)>>2]|0;g=c[(c[h+740>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+744>>2]|0)+208>>2]|0;if((g|0)<(i|0))e=e+1|0;else break}}if((j|0)>-1)while(1){h=c[k+(f<<2)>>2]|0;g=c[(c[h+740>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+744>>2]|0)+208>>2]|0;if((j|0)<(g|0))f=f+-1|0;else break}else{i=c[(c[l+744>>2]|0)+208>>2]|0;while(1){h=c[k+(f<<2)>>2]|0;g=c[(c[h+740>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+744>>2]|0)+208>>2]|0;if((i|0)<(g|0))f=f+-1|0;else break}}if((e|0)<=(f|0)){i=k+(e<<2)|0;j=c[i>>2]|0;c[i>>2]=c[k+(f<<2)>>2];c[(c[a+12>>2]|0)+(f<<2)>>2]=j;e=e+1|0;f=f+-1|0}if((e|0)>(f|0))break;k=c[a+12>>2]|0}if((f|0)>(b|0))$g(a,b,f);if((e|0)<(d|0))b=e;else break}return}function ah(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0,j=0.0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0;k=i;i=i+64|0;n=+g[d>>2];o=+g[d+4>>2];m=+g[d+8>>2];p=n*+g[b+4>>2]+o*+g[b+20>>2]+m*+g[b+36>>2];q=n*+g[b+8>>2]+o*+g[b+24>>2]+m*+g[b+40>>2];g[k+48>>2]=+g[b>>2]*n+ +g[b+16>>2]*o+ +g[b+32>>2]*m;g[k+48+4>>2]=p;g[k+48+8>>2]=q;g[k+48+12>>2]=0.0;ic[c[(c[a>>2]|0)+64>>2]&127](k+32|0,a,k+48|0);q=+g[k+32>>2];p=+g[k+32+4>>2];m=+g[k+32+8>>2];o=q*+g[b>>2]+p*+g[b+4>>2]+m*+g[b+8>>2]+ +g[b+48>>2];n=q*+g[b+16>>2]+p*+g[b+20>>2]+m*+g[b+24>>2]+ +g[b+52>>2];m=q*+g[b+32>>2]+p*+g[b+36>>2]+m*+g[b+40>>2]+ +g[b+56>>2];r=c[(c[a>>2]|0)+64>>2]|0;p=-+g[k+48+4>>2];q=-+g[k+48+8>>2];g[k>>2]=-+g[k+48>>2];g[k+4>>2]=p;g[k+8>>2]=q;g[k+12>>2]=0.0;ic[r&127](k+16|0,a,k);q=+g[k+16>>2];p=+g[k+16+4>>2];h=+g[k+16+8>>2];l=q*+g[b>>2]+p*+g[b+4>>2]+h*+g[b+8>>2]+ +g[b+48>>2];j=q*+g[b+16>>2]+p*+g[b+20>>2]+h*+g[b+24>>2]+ +g[b+52>>2];h=q*+g[b+32>>2]+p*+g[b+36>>2]+h*+g[b+40>>2]+ +g[b+56>>2];g[e>>2]=o*+g[d>>2]+n*+g[d+4>>2]+m*+g[d+8>>2];h=l*+g[d>>2]+j*+g[d+4>>2]+h*+g[d+8>>2];g[f>>2]=h;j=+g[e>>2];if(!(j>h)){i=k;return}g[e>>2]=h;g[f>>2]=j;i=k;return}function bh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0;while(1){k=c[a+12>>2]|0;l=c[k+(((b+d|0)/2|0)<<2)>>2]|0;e=b;f=d;while(1){j=c[(c[l+28>>2]|0)+208>>2]|0;if((j|0)>-1)while(1){h=c[k+(e<<2)>>2]|0;g=c[(c[h+28>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+32>>2]|0)+208>>2]|0;if((g|0)<(j|0))e=e+1|0;else break}else{i=c[(c[l+32>>2]|0)+208>>2]|0;while(1){h=c[k+(e<<2)>>2]|0;g=c[(c[h+28>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+32>>2]|0)+208>>2]|0;if((g|0)<(i|0))e=e+1|0;else break}}if((j|0)>-1)while(1){h=c[k+(f<<2)>>2]|0;g=c[(c[h+28>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+32>>2]|0)+208>>2]|0;if((j|0)<(g|0))f=f+-1|0;else break}else{i=c[(c[l+32>>2]|0)+208>>2]|0;while(1){h=c[k+(f<<2)>>2]|0;g=c[(c[h+28>>2]|0)+208>>2]|0;if((g|0)<=-1)g=c[(c[h+32>>2]|0)+208>>2]|0;if((i|0)<(g|0))f=f+-1|0;else break}}if((e|0)<=(f|0)){i=k+(e<<2)|0;j=c[i>>2]|0;c[i>>2]=c[k+(f<<2)>>2];c[(c[a+12>>2]|0)+(f<<2)>>2]=j;e=e+1|0;f=f+-1|0}if((e|0)>(f|0))break;k=c[a+12>>2]|0}if((f|0)>(b|0))bh(a,b,f);if((e|0)<(d|0))b=e;else break}return}function ch(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,j=0,k=0,l=0,m=0;m=i;i=i+16|0;h=c[a+12>>2]|0;j=c[h+(((d+b|0)/2|0)<<4)>>2]|0;k=c[h+(((d+b|0)/2|0)<<4)+4>>2]|0;l=c[h+(((d+b|0)/2|0)<<4)+8>>2]|0;e=b;f=d;while(1){g=e;while(1){e=c[h+(g<<4)+4>>2]|0;if((e|0)>=(k|0)){if((e|0)!=(k|0))break;e=c[h+(g<<4)>>2]|0;if((e|0)>=(j|0)){if((e|0)!=(j|0))break;if((c[h+(g<<4)+8>>2]|0)>=(l|0))break}}g=g+1|0}while(1){e=c[h+(f<<4)+4>>2]|0;if((k|0)>=(e|0)){if((k|0)!=(e|0))break;e=c[h+(f<<4)>>2]|0;if((j|0)>=(e|0)){if((j|0)!=(e|0))break;if((l|0)>=(c[h+(f<<4)+8>>2]|0))break}}f=f+-1|0}if((g|0)>(f|0))e=g;else{e=h+(g<<4)|0;c[m>>2]=c[e>>2];c[m+4>>2]=c[e+4>>2];c[m+8>>2]=c[e+8>>2];c[m+12>>2]=c[e+12>>2];h=h+(f<<4)|0;c[e>>2]=c[h>>2];c[e+4>>2]=c[h+4>>2];c[e+8>>2]=c[h+8>>2];c[e+12>>2]=c[h+12>>2];e=(c[a+12>>2]|0)+(f<<4)|0;c[e>>2]=c[m>>2];c[e+4>>2]=c[m+4>>2];c[e+8>>2]=c[m+8>>2];c[e+12>>2]=c[m+12>>2];e=g+1|0;f=f+-1|0}if((e|0)>(f|0))break;h=c[a+12>>2]|0}if((f|0)>(b|0))ch(a,b,f);if((e|0)>=(d|0)){i=m;return}ch(a,e,d);i=m;return}function dh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0;e=i;i=i+48|0;y=+g[d>>2];n=+g[b>>2];x=+g[d+16>>2];l=+g[b+4>>2];w=+g[d+32>>2];j=+g[b+8>>2];v=+g[d+4>>2];u=+g[d+20>>2];t=+g[d+36>>2];k=+g[d+8>>2];m=+g[d+24>>2];o=+g[d+40>>2];q=+g[b+16>>2];p=+g[b+20>>2];h=+g[b+24>>2];s=+g[b+32>>2];r=+g[b+36>>2];f=+g[b+40>>2];g[e>>2]=y*n+x*l+w*j;g[e+4>>2]=v*n+u*l+t*j;g[e+8>>2]=k*n+m*l+o*j;g[e+12>>2]=0.0;g[e+16>>2]=y*q+x*p+w*h;g[e+20>>2]=v*q+u*p+t*h;g[e+24>>2]=k*q+m*p+o*h;g[e+28>>2]=0.0;g[e+32>>2]=y*s+x*r+w*f;g[e+36>>2]=v*s+u*r+t*f;g[e+40>>2]=k*s+m*r+o*f;g[e+44>>2]=0.0;o=+g[d+48>>2];m=+g[d+52>>2];k=+g[d+56>>2];f=o*s+m*r+k*f+ +g[b+56>>2];h=o*q+m*p+k*h+ +g[b+52>>2];j=o*n+m*l+k*j+ +g[b+48>>2];c[a>>2]=c[e>>2];c[a+4>>2]=c[e+4>>2];c[a+8>>2]=c[e+8>>2];c[a+12>>2]=c[e+12>>2];c[a+16>>2]=c[e+16>>2];c[a+16+4>>2]=c[e+16+4>>2];c[a+16+8>>2]=c[e+16+8>>2];c[a+16+12>>2]=c[e+16+12>>2];c[a+32>>2]=c[e+32>>2];c[a+32+4>>2]=c[e+32+4>>2];c[a+32+8>>2]=c[e+32+8>>2];c[a+32+12>>2]=c[e+32+12>>2];g[a+48>>2]=j;g[a+52>>2]=h;g[a+56>>2]=f;g[a+60>>2]=0.0;i=e;return}function eh(a,b){a=+a;b=+b;var d=0,e=0,f=0,h=0,i=0,j=0,l=0,m=0,n=0,o=0.0;m=(g[k>>2]=a,c[k>>2]|0);i=(g[k>>2]=b,c[k>>2]|0);a:do if((i<<1|0)!=0?(o=+N(+b),!((g[k>>2]=o,c[k>>2]|0)>>>0>2139095040|(m>>>23&255|0)==255)):0){if(m<<1>>>0<=i<<1>>>0)return +((m<<1|0)==(i<<1|0)?a*0.0:a);if(!(m>>>23&255)){if((m<<9|0)>-1){d=0;e=m<<9;do{d=d+-1|0;e=e<<1}while((e|0)>-1);e=d}else e=0;d=e;f=m<<1-e}else{d=m>>>23&255;f=m&8388607|8388608}if(!(i>>>23&255)){if((i<<9|0)>-1){e=0;h=i<<9;do{e=e+-1|0;h=h<<1}while((h|0)>-1)}else e=0;j=e;l=i<<1-e}else{j=i>>>23&255;l=i&8388607|8388608}h=f-l|0;b:do if((d|0)>(j|0)){i=(h|0)>-1;e=h;while(1){if(i){if((f|0)==(l|0))break}else e=f;f=e<<1;d=d+-1|0;h=f-l|0;if((d|0)>(j|0)){i=(h|0)>-1;e=h}else{e=h;h=(h|0)>-1;break b}}b=a*0.0;break a}else{e=h;h=(h|0)>-1}while(0);if(h){if((f|0)==(l|0)){b=a*0.0;break}}else e=f;if(e>>>0<8388608)do{e=e<<1;d=d+-1|0}while(e>>>0<8388608);if((d|0)>0)d=e+-8388608|d<<23;else d=e>>>(1-d|0);b=(c[k>>2]=d|m&-2147483648,+g[k>>2])}else n=3;while(0);if((n|0)==3)b=a*b/(a*b);return +b}function fh(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;var h=0,j=0.0,k=0.0,l=0,m=0,n=0,o=0.0,p=0.0,q=0;n=i;i=i+16|0;if((f|0)>-3&(f+3|0)>-1){if((f+3|0)!=0?(c[6435]=(c[6435]|0)+1,h=yc((f+3<<4|3)+16|0)|0,(h|0)!=0):0){c[(h+4+15&-16)+-4>>2]=h;a=h+4+15&-16}else a=0;h=0;do{m=a+(h<<4)|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];h=h+1|0}while((h|0)!=(f+3|0));m=a}else m=0;if((f|0)>-3){h=m;l=0;while(1){if(!l)j=0.0;else{a=l;k=.5;j=0.0;while(1){j=(a&1|0)==0?j:j+k;a=a>>1;if(!a)break;else k=k*.5}}k=j*2.0+-1.0;o=(+(l<<1|0)*3.1415927410125732+3.1415927410125732)/+(f+3|0);p=+O(+(1.0-k*k));j=p*+R(+o);g[h>>2]=p*+Q(+o);g[h+4>>2]=j;g[h+8>>2]=k;g[h+12>>2]=0.0;l=l+1|0;if((l|0)==(f+3|0))break;else h=h+16|0}a=0;do{q=m+(a<<4)|0;h=m+(a<<4)+4|0;l=m+(a<<4)+8|0;o=+g[h>>2]*+g[e+4>>2]+ +g[d+4>>2];p=+g[l>>2]*+g[e+8>>2]+ +g[d+8>>2];g[q>>2]=+g[q>>2]*+g[e>>2]+ +g[d>>2];g[h>>2]=o;g[l>>2]=p;g[m+(a<<4)+12>>2]=0.0;a=a+1|0}while((a|0)<(f+3|0))}a=rc(b,m,f+3|0,1)|0;if(!m){i=n;return a|0}c[6436]=(c[6436]|0)+1;hd(c[m+-4>>2]|0);i=n;return a|0}function gh(a,b,d,e,f,h,j){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;var l=0.0,m=0.0,n=0,o=0.0,p=0.0,q=0,r=0,s=0.0,t=0;r=i;i=i+16|0;g[e>>2]=3402823466385288598117041.0e14;g[f>>2]=-3402823466385288598117041.0e14;n=c[a+8>>2]|0;if((n|0)>0){q=0;do{t=c[a+16>>2]|0;s=+g[t+(q<<4)>>2];p=+g[t+(q<<4)+4>>2];o=+g[t+(q<<4)+8>>2];l=s*+g[b>>2]+p*+g[b+4>>2]+o*+g[b+8>>2]+ +g[b+48>>2];m=s*+g[b+16>>2]+p*+g[b+20>>2]+o*+g[b+24>>2]+ +g[b+52>>2];o=s*+g[b+32>>2]+p*+g[b+36>>2]+o*+g[b+40>>2]+ +g[b+56>>2];p=l*+g[d>>2]+m*+g[d+4>>2]+o*+g[d+8>>2];if(p<+g[e>>2]){g[e>>2]=p;g[h>>2]=l;g[h+4>>2]=m;g[h+8>>2]=o;g[h+12>>2]=0.0}if(p>+g[f>>2]){g[f>>2]=p;g[j>>2]=l;g[j+4>>2]=m;g[j+8>>2]=o;g[j+12>>2]=0.0}q=q+1|0}while((q|0)!=(n|0));s=+g[f>>2];m=s;n=(g[k>>2]=s,c[k>>2]|0)}else{m=-3402823466385288598117041.0e14;n=-8388609}l=+g[e>>2];if(!(l>m)){i=r;return}c[e>>2]=n;g[f>>2]=l;c[r>>2]=c[h>>2];c[r+4>>2]=c[h+4>>2];c[r+8>>2]=c[h+8>>2];c[r+12>>2]=c[h+12>>2];c[h>>2]=c[j>>2];c[h+4>>2]=c[j+4>>2];c[h+8>>2]=c[j+8>>2];c[h+12>>2]=c[j+12>>2];c[j>>2]=c[r>>2];c[j+4>>2]=c[r+4>>2];c[j+8>>2]=c[r+8>>2];c[j+12>>2]=c[r+12>>2];i=r;return}function hh(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0,v=0,w=0,x=0,y=0;if((c[a>>2]|0)==(b|0)){c[a>>2]=0;a=0;return a|0}e=c[b+32>>2]|0;d=c[e+32>>2]|0;b=c[e+36+(((c[e+40>>2]|0)!=(b|0)&1)<<2)>>2]|0;if(!d){c[a>>2]=b;c[b+32>>2]=0;d=c[a+4>>2]|0;if(!d)d=b;else{c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);d=c[a>>2]|0}c[a+4>>2]=e;a=d;return a|0}c[d+36+(((c[d+40>>2]|0)==(e|0)&1)<<2)>>2]=b;c[b+32>>2]=d;b=c[a+4>>2]|0;if(b|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}c[a+4>>2]=e;do{s=+g[d>>2];x=d+4|0;q=+g[x>>2];v=d+8|0;o=+g[v>>2];y=d+16|0;m=+g[y>>2];w=d+20|0;i=+g[w>>2];e=d+24|0;k=+g[e>>2];u=c[d+36>>2]|0;b=c[d+40>>2]|0;t=+g[u>>2];r=+g[b>>2];r=t>2]=r;t=+g[u+16>>2];l=+g[b+16>>2];l=t>l?t:l;g[y>>2]=l;t=+g[u+4>>2];p=+g[b+4>>2];p=t>2]=p;t=+g[u+20>>2];h=+g[b+20>>2];h=t>h?t:h;g[w>>2]=h;t=+g[u+8>>2];n=+g[b+8>>2];n=t>2]=n;t=+g[u+24>>2];j=+g[b+24>>2];j=t>j?t:j;g[e>>2]=j;if(!(s!=r|q!=p|o!=n|m!=l)?!(k!=j|i!=h):0){f=14;break}d=c[d+32>>2]|0}while((d|0)!=0);if((f|0)==14)return d|0;y=c[a>>2]|0;return y|0}function ih(a){a=a|0;var b=0,d=0,e=0.0,f=0.0,h=0.0,i=0,j=0;i=c[a+28>>2]|0;e=0.0;f=0.0;h=0.0;j=0;a:while(1){switch(j|0){case 0:{e=+g[a+80>>2]+ +g[a+64>>2];f=+g[a+84>>2]+ +g[a+68>>2];h=+g[a+88>>2]+ +g[a+72>>2];break}case 1:{e=+g[a+80>>2]+ +g[a+64>>2];f=+g[a+84>>2]+ +g[a+68>>2];h=+g[a+72>>2]-+g[a+88>>2];break}case 2:{e=+g[a+80>>2]+ +g[a+64>>2];f=+g[a+68>>2]-+g[a+84>>2];h=+g[a+88>>2]+ +g[a+72>>2];break}case 3:{e=+g[a+80>>2]+ +g[a+64>>2];f=+g[a+68>>2]-+g[a+84>>2];h=+g[a+72>>2]-+g[a+88>>2];break}case 4:{e=+g[a+64>>2]-+g[a+80>>2];f=+g[a+84>>2]+ +g[a+68>>2];h=+g[a+88>>2]+ +g[a+72>>2];break}case 5:{e=+g[a+64>>2]-+g[a+80>>2];f=+g[a+84>>2]+ +g[a+68>>2];h=+g[a+72>>2]-+g[a+88>>2];break}case 6:{e=+g[a+64>>2]-+g[a+80>>2];f=+g[a+68>>2]-+g[a+84>>2];h=+g[a+88>>2]+ +g[a+72>>2];break}case 7:{e=+g[a+64>>2]-+g[a+80>>2];f=+g[a+68>>2]-+g[a+84>>2];h=+g[a+72>>2]-+g[a+88>>2];break}default:{}}if((i|0)>0){b=c[a+36>>2]|0;d=0;do{if(+g[b+(d*36|0)+32>>2]+(e*+g[b+(d*36|0)+20>>2]+f*+g[b+(d*36|0)+24>>2]+h*+g[b+(d*36|0)+28>>2])>0.0){b=0;d=16;break a}d=d+1|0}while((d|0)<(i|0))}j=j+1|0;if((j|0)>=8){b=1;d=16;break}}if((d|0)==16)return b|0;return 0}function jh(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=+f;var h=0,i=0.0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0;o=+g[d>>2];if(+g[b>>2]<=o){i=+g[d+4>>2];if((((+g[b+4>>2]<=i?+g[b+8>>2]<=+g[d+8>>2]:0)?+g[b+16>>2]>=+g[d+16>>2]:0)?+g[b+20>>2]>=+g[d+20>>2]:0)?+g[b+24>>2]>=+g[d+24>>2]:0){d=0;return d|0}else h=d+4|0}else{h=d+4|0;i=+g[d+4>>2]}g[d>>2]=o-f;m=i-f;g[h>>2]=m;p=+g[d+8>>2]-f;g[d+8>>2]=p;i=+g[d+16>>2]+f;g[d+16>>2]=i;n=+g[d+20>>2]+f;g[d+20>>2]=n;q=+g[d+24>>2]+f;g[d+24>>2]=q;l=+g[e>>2];if(l>0.0)g[d+16>>2]=l+i;else g[d>>2]=l+(o-f);i=+g[e+4>>2];if(i>0.0)g[d+20>>2]=i+n;else g[h>>2]=i+m;i=+g[e+8>>2];if(i>0.0)g[d+24>>2]=i+q;else g[d+8>>2]=i+p;h=hh(a,b)|0;a:do if(h){j=c[a+8>>2]|0;if((j|0)<=-1){h=c[a>>2]|0;break}if((j|0)>0){k=0;while(1){e=c[h+32>>2]|0;k=k+1|0;if(!e)break a;if((k|0)>=(j|0)){h=e;break}else h=e}}}else h=0;while(0);c[b>>2]=c[d>>2];c[b+4>>2]=c[d+4>>2];c[b+8>>2]=c[d+8>>2];c[b+12>>2]=c[d+12>>2];c[b+16>>2]=c[d+16>>2];c[b+20>>2]=c[d+20>>2];c[b+24>>2]=c[d+24>>2];c[b+28>>2]=c[d+28>>2];lf(a,h,b);d=1;return d|0}function kh(a,d,e){a=a|0;d=d|0;e=e|0;si(a,d,e)|0;c[d+52>>2]=c[a+48>>2];c[d+56>>2]=c[a+52>>2];c[d+60>>2]=c[a+56>>2];c[d+64>>2]=c[a+60>>2];c[d+68>>2]=c[a+64>>2];c[d+72>>2]=c[a+68>>2];c[d+76>>2]=c[a+72>>2];c[d+80>>2]=c[a+76>>2];c[d+84>>2]=c[a+80>>2];c[d+88>>2]=c[a+84>>2];c[d+92>>2]=c[a+88>>2];c[d+96>>2]=c[a+92>>2];c[d+100>>2]=c[a+96>>2];c[d+104>>2]=c[a+100>>2];c[d+108>>2]=c[a+104>>2];c[d+112>>2]=c[a+108>>2];c[d+116>>2]=c[a+112>>2];c[d+120>>2]=c[a+116>>2];c[d+124>>2]=c[a+120>>2];c[d+128>>2]=c[a+124>>2];c[d+132>>2]=c[a+128>>2];c[d+136>>2]=c[a+132>>2];c[d+140>>2]=c[a+136>>2];c[d+144>>2]=c[a+140>>2];c[d+148>>2]=c[a+144>>2];c[d+152>>2]=c[a+148>>2];c[d+156>>2]=c[a+152>>2];c[d+160>>2]=c[a+156>>2];c[d+164>>2]=c[a+160>>2];c[d+168>>2]=c[a+164>>2];c[d+172>>2]=c[a+168>>2];c[d+176>>2]=c[a+172>>2];c[d+228>>2]=c[a+868>>2];c[d+212>>2]=c[a+872>>2];c[d+196>>2]=c[a+680>>2];c[d+180>>2]=c[a+696>>2];c[d+232>>2]=c[a+932>>2];c[d+216>>2]=c[a+936>>2];c[d+200>>2]=c[a+684>>2];c[d+184>>2]=c[a+700>>2];c[d+236>>2]=c[a+996>>2];c[d+220>>2]=c[a+1e3>>2];c[d+204>>2]=c[a+688>>2];c[d+188>>2]=c[a+704>>2];a=b[a+1300>>1]|0;c[d+244>>2]=a&255;c[d+248>>2]=(a&65535)>>>8&65535;return 12479}function lh(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,j=0,k=0,l=0,m=0;m=i;i=i+32|0;h=(a[b+28>>0]|0)!=0;l=h?e:d;h=h?d:e;j=c[l+4>>2]|0;k=c[j+16>>2]|0;g=c[b+12>>2]|0;if((g|0)<(k|0)){if((c[b+16>>2]|0)<(k|0)){if(!k){d=0;e=g}else{c[6435]=(c[6435]|0)+1;d=yc((k<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+12>>2]|0}if((e|0)>0){f=0;do{c[d+(f<<2)>>2]=c[(c[b+20>>2]|0)+(f<<2)>>2];f=f+1|0}while((f|0)!=(e|0))}e=c[b+20>>2]|0;if(e|0){if(a[b+24>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+20>>2]=0}a[b+24>>0]=1;c[b+20>>2]=d;c[b+16>>2]=k;e=b+20|0}else e=b+20|0;d=g;do{c[(c[e>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=(k|0))}c[b+12>>2]=k;if((k|0)<=0){i=m;return}d=0;do{if(!(c[j+64>>2]|0)){e=c[(c[j+24>>2]|0)+(d*80|0)+64>>2]|0;f=c[l+8>>2]|0;g=c[l+12>>2]|0;c[m>>2]=l;c[m+4>>2]=e;c[m+8>>2]=f;c[m+12>>2]=g;c[m+16>>2]=-1;c[m+20>>2]=d;g=c[b+4>>2]|0;g=Ib[c[(c[g>>2]|0)+8>>2]&31](g,m,h,c[b+32>>2]|0)|0;c[(c[b+20>>2]|0)+(d<<2)>>2]=g}else c[(c[b+20>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=(k|0));i=m;return}function mh(){var a=0,b=0,d=0;c[6435]=(c[6435]|0)+1;a=yc(219)|0;if(!a)a=0;else{c[(a+4+15&-16)+-4>>2]=a;a=a+4+15&-16}ml();ml();c[a>>2]=2896;b=a+52|0;d=a+4|0;c[d>>2]=c[5710];c[d+4>>2]=c[5711];c[d+8>>2]=c[5712];c[d+12>>2]=c[5713];d=a+20|0;c[d>>2]=c[5714];c[d+4>>2]=c[5715];c[d+8>>2]=c[5716];c[d+12>>2]=c[5717];d=a+36|0;c[d>>2]=c[5718];c[d+4>>2]=c[5719];c[d+8>>2]=c[5720];c[d+12>>2]=c[5721];c[b>>2]=c[5722];c[b+4>>2]=c[5723];c[b+8>>2]=c[5724];c[b+12>>2]=c[5725];b=a+116|0;d=a+68|0;c[d>>2]=c[5710];c[d+4>>2]=c[5711];c[d+8>>2]=c[5712];c[d+12>>2]=c[5713];d=a+84|0;c[d>>2]=c[5714];c[d+4>>2]=c[5715];c[d+8>>2]=c[5716];c[d+12>>2]=c[5717];d=a+100|0;c[d>>2]=c[5718];c[d+4>>2]=c[5719];c[d+8>>2]=c[5720];c[d+12>>2]=c[5721];c[b>>2]=c[5722];c[b+4>>2]=c[5723];c[b+8>>2]=c[5724];c[b+12>>2]=c[5725];b=a+180|0;d=a+132|0;c[d>>2]=c[5710];c[d+4>>2]=c[5711];c[d+8>>2]=c[5712];c[d+12>>2]=c[5713];d=a+148|0;c[d>>2]=c[5714];c[d+4>>2]=c[5715];c[d+8>>2]=c[5716];c[d+12>>2]=c[5717];d=a+164|0;c[d>>2]=c[5718];c[d+4>>2]=c[5719];c[d+8>>2]=c[5720];c[d+12>>2]=c[5721];c[b>>2]=c[5722];c[b+4>>2]=c[5723];c[b+8>>2]=c[5724];c[b+12>>2]=c[5725];c[a+196>>2]=0;return a|0}function nh(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0,j=0;d=c[b+32>>2]|0;if(!d)f=0;else f=c[b+40>>2]|0;i=c[b+52>>2]|0;if(!i)g=0;else g=c[b+60>>2]|0;e=c[b+72>>2]|0;if(!e)h=0;else h=c[b+80>>2]|0;j=c[b+8>>2]|0;+$b[c[(c[j>>2]|0)+12>>2]&3](j,f,d,g,i,h,e,c[b+4>>2]|0,c[b+20>>2]|0,c[b+24>>2]|0);d=c[b+32>>2]|0;if((d|0)<0){if((c[b+36>>2]|0)<0){e=c[b+40>>2]|0;if(e|0){if(a[b+44>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+40>>2]=0}a[b+44>>0]=1;c[b+40>>2]=0;c[b+36>>2]=0}do{c[(c[b+40>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=0)}c[b+32>>2]=0;d=c[b+52>>2]|0;if((d|0)<0){if((c[b+56>>2]|0)<0){e=c[b+60>>2]|0;if(e|0){if(a[b+64>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+60>>2]=0}a[b+64>>0]=1;c[b+60>>2]=0;c[b+56>>2]=0}do{c[(c[b+60>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=0)}c[b+52>>2]=0;d=c[b+72>>2]|0;if((d|0)>=0){c[b+72>>2]=0;return}if((c[b+76>>2]|0)<0){e=c[b+80>>2]|0;if(e|0){if(a[b+84>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+80>>2]=0}a[b+84>>0]=1;c[b+80>>2]=0;c[b+76>>2]=0}do{c[(c[b+80>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=0);c[b+72>>2]=0;return}function oh(b,d,e){b=b|0;d=+d;e=e|0;var f=0.0,h=0,i=0,j=0,k=0,l=0,m=0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0;j=c[b+712>>2]|0;if(e){if((j|0)>0){e=c[b+720>>2]|0;h=0;do{g[e+(h*104|0)+88>>2]=0.0;h=h+1|0}while((h|0)!=(j|0))}e=c[b+752>>2]|0;if((e|0)>0){h=c[b+760>>2]|0;i=0;do{m=c[h+(i*44|0)+8>>2]|0;l=c[h+(i*44|0)+12>>2]|0;k=c[h+(i*44|0)+16>>2]|0;o=+g[m+8>>2];q=+g[m+12>>2];f=+g[m+16>>2];n=+g[l+8>>2]-o;r=+g[l+12>>2]-q;p=+g[l+16>>2]-f;o=+g[k+8>>2]-o;q=+g[k+12>>2]-q;f=+g[k+16>>2]-f;f=+O(+((n*q-r*o)*(n*q-r*o)+((r*f-p*q)*(r*f-p*q)+(p*o-n*f)*(p*o-n*f))));g[m+88>>2]=f+ +g[m+88>>2];g[l+88>>2]=f+ +g[l+88>>2];g[k+88>>2]=f+ +g[k+88>>2];i=i+1|0}while((i|0)!=(e|0))}if((j|0)<=0){m=b+924|0;a[m>>0]=1;return}e=c[b+720>>2]|0;h=0;do{m=e+(h*104|0)+88|0;g[m>>2]=1.0/+g[m>>2];h=h+1|0}while((h|0)!=(j|0))}if((j|0)<=0){m=b+924|0;a[m>>0]=1;return}i=c[b+720>>2]|0;e=0;f=0.0;do{r=+g[i+(e*104|0)+88>>2];f=f+(r>0.0?1.0/r:0.0);e=e+1|0}while((e|0)!=(j|0));f=1.0/f*d;e=c[b+712>>2]|0;h=0;do{m=i+(h*104|0)+88|0;g[m>>2]=+g[m>>2]/f;h=h+1|0}while((h|0)<(e|0));m=b+924|0;a[m>>0]=1;return}function ph(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0;c[6435]=(c[6435]|0)+1;d=yc(39)|0;if(!d)i=0;else{c[(d+4+15&-16)+-4>>2]=d;i=d+4+15&-16}g=i;c[i>>2]=0;c[i+4>>2]=0;c[i+8>>2]=0;c[i+12>>2]=0;c[i+16>>2]=0;if((c[b+872>>2]|0)>0){h=c[c[b+880>>2]>>2]|0;c[i>>2]=c[h>>2];c[i+4>>2]=c[h+4>>2];c[i+8>>2]=c[h+8>>2];c[i+12>>2]=c[h+12>>2];c[i+16>>2]=c[h+16>>2]}else{c[i>>2]=0;c[i+4>>2]=0;c[i+8>>2]=0;c[i+12>>2]=0;c[i+16>>2]=0}e=c[b+872>>2]|0;if((e|0)!=(c[b+876>>2]|0)){h=e;f=b+880|0;f=c[f>>2]|0;f=f+(h<<2)|0;c[f>>2]=g;h=h+1|0;c[b+872>>2]=h;return i|0}h=e|0?e<<1:1;if((e|0)>=(h|0)){h=e;f=b+880|0;f=c[f>>2]|0;f=f+(h<<2)|0;c[f>>2]=g;h=h+1|0;c[b+872>>2]=h;return i|0}if(!h)d=0;else{c[6435]=(c[6435]|0)+1;d=yc((h<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+872>>2]|0}if((e|0)>0){f=0;do{c[d+(f<<2)>>2]=c[(c[b+880>>2]|0)+(f<<2)>>2];f=f+1|0}while((f|0)!=(e|0))}f=c[b+880>>2]|0;if(f){if(a[b+884>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0);e=c[b+872>>2]|0}c[b+880>>2]=0}a[b+884>>0]=1;c[b+880>>2]=d;c[b+876>>2]=h;h=e;f=b+880|0;f=c[f>>2]|0;f=f+(h<<2)|0;c[f>>2]=g;h=h+1|0;c[b+872>>2]=h;return i|0}function qh(b,d,e,f,h,i){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;i=i|0;var j=0,k=0,l=0,m=0,n=0.0,o=0.0,p=0.0,q=0.0;c[6435]=(c[6435]|0)+1;b=yc((h+2|0)>>>0>268435455?18:(h+2<<4|3)+16|0)|0;if(!b)m=0;else{c[(b+4+15&-16)+-4>>2]=b;m=b+4+15&-16}j=(h+2|0)>>>0>1073741823?-1:h+2<<2;j=(j|0)==0?1:j;while(1){k=yc(j)|0;if(k|0)break;b=c[6564]|0;c[6564]=b+0;if(!b){l=7;break}jc[b&3]()}if((l|0)==7){h=Ya(4)|0;c[h>>2]=9640;pb(h|0,2800,251)}if((h|0)>-2){b=0;do{q=+(b|0)/+(h+1|0);p=+g[e>>2];o=+g[e+4>>2];o=o+q*(+g[f+4>>2]-o);n=+g[e+8>>2];n=n+q*(+g[f+8>>2]-n);g[m+(b<<4)>>2]=p+q*(+g[f>>2]-p);g[m+(b<<4)+4>>2]=o;g[m+(b<<4)+8>>2]=n;g[m+(b<<4)+12>>2]=0.0;g[k+(b<<2)>>2]=1.0;b=b+1|0}while((b|0)<(h+2|0))}c[6435]=(c[6435]|0)+1;b=yc(1271)|0;if(!b)j=0;else{c[(b+4+15&-16)+-4>>2]=b;j=b+4+15&-16}Kc(j,d,h+2|0,m,k);if(i&1|0){g[(c[j+720>>2]|0)+88>>2]=0.0;a[j+924>>0]=1}if(i&2|0){g[(c[j+720>>2]|0)+((h+1|0)*104|0)+88>>2]=0.0;a[j+924>>0]=1}if(m|0){c[6436]=(c[6436]|0)+1;hd(c[m+-4>>2]|0)}hd(k);if((h+2|0)>1)b=1;else return j|0;do{Rf(j,b+-1|0,b,0,0);b=b+1|0}while((b|0)!=(h+2|0));return j|0}function rh(a,b,d,e,f,h){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var i=0,j=0,l=0,m=0.0,n=0,o=0,p=0.0,q=0.0;mc[c[(c[a>>2]|0)+8>>2]&127](a,b,f,h);l=c[h>>2]|0;o=c[h+4>>2]|0;i=c[h+8>>2]|0;n=c[f>>2]|0;j=c[f+4>>2]|0;b=c[f+8>>2]|0;m=+g[d>>2];p=+g[d+4>>2];q=+g[d+8>>2];if(m>0.0)l=(g[k>>2]=(c[k>>2]=l,+g[k>>2])+m,c[k>>2]|0);else n=(g[k>>2]=(c[k>>2]=n,+g[k>>2])+m,c[k>>2]|0);if(p>0.0)d=(g[k>>2]=(c[k>>2]=o,+g[k>>2])+p,c[k>>2]|0);else{d=o;j=(g[k>>2]=(c[k>>2]=j,+g[k>>2])+p,c[k>>2]|0)}if(q>0.0)i=(g[k>>2]=(c[k>>2]=i,+g[k>>2])+q,c[k>>2]|0);else b=(g[k>>2]=(c[k>>2]=b,+g[k>>2])+q,c[k>>2]|0);m=+g[e>>2];p=+g[e+4>>2];q=+g[e+8>>2];q=+O(+(m*m+p*p+q*q));q=q*+Sb[c[(c[a>>2]|0)+16>>2]&15](a);c[f>>2]=n;c[f+4>>2]=j;c[f+8>>2]=b;g[f+12>>2]=0.0;c[h>>2]=l;c[h+4>>2]=d;c[h+8>>2]=i;g[h+12>>2]=0.0;g[f>>2]=+g[f>>2]-q;g[f+4>>2]=+g[f+4>>2]-q;g[f+8>>2]=+g[f+8>>2]-q;g[h>>2]=q+ +g[h>>2];g[h+4>>2]=q+ +g[h+4>>2];g[h+8>>2]=q+ +g[h+8>>2];return}function sh(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,j=0,k=0,l=0,m=0,n=0;n=i;i=i+112|0;m=c[d+4>>2]|0;k=n;l=k+100|0;do{c[k>>2]=0;k=k+4|0}while((k|0)<(l|0));h=c[b+712>>2]|0;a:do if((h|0)>(m|0))e=b+720|0;else{if((h|0)<(m|0)?(c[b+716>>2]|0)<(m|0):0){if((m|0)!=0?(c[6435]=(c[6435]|0)+1,e=yc((m*104|3)+16|0)|0,(e|0)!=0):0){c[(e+4+15&-16)+-4>>2]=e;g=e+4+15&-16}else g=0;e=c[b+712>>2]|0;f=0;while(1){if((f|0)>=(e|0))break;k=g+(f*104|0)|0;j=(c[b+720>>2]|0)+(f*104|0)|0;l=k+104|0;do{c[k>>2]=c[j>>2];k=k+4|0;j=j+4|0}while((k|0)<(l|0));f=f+1|0}e=c[b+720>>2]|0;if(e|0){if(!((a[b+724>>0]&1)==0|(e|0)==0)){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+720>>2]=0}a[b+724>>0]=1;c[b+720>>2]=g;c[b+716>>2]=m}e=h;while(1){if((e|0)>=(m|0)){e=b+720|0;break a}k=c[b+720>>2]|0;c[k+(e*104|0)>>2]=0;k=k+(e*104|0)+4|0;j=n;l=k+100|0;do{c[k>>2]=c[j>>2];k=k+4|0;j=j+4|0}while((k|0)<(l|0));e=e+1|0}}while(0);c[b+712>>2]=m;e=c[e>>2]|0;f=0;while(1){if((f|0)>=(m|0))break;k=e+(f*104|0)|0;j=(c[d+12>>2]|0)+(f*104|0)|0;l=k+104|0;do{c[k>>2]=c[j>>2];k=k+4|0;j=j+4|0}while((k|0)<(l|0));f=f+1|0}i=n;return}function th(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0;e=c[b+4>>2]|0;if((e|0)==(c[b+8>>2]|0)){If(b,e|0?e<<1:1);e=c[b+4>>2]|0}j=(c[b+12>>2]|0)+(e*36|0)|0;a[j+16>>0]=1;c[j+12>>2]=0;c[j+4>>2]=0;c[j+8>>2]=0;k=c[d+4>>2]|0;if((k|0)<=0){c[j+4>>2]=k;k=j+20|0;d=d+20|0;c[k>>2]=c[d>>2];c[k+4>>2]=c[d+4>>2];c[k+8>>2]=c[d+8>>2];c[k+12>>2]=c[d+12>>2];d=c[b+4>>2]|0;d=d+1|0;c[b+4>>2]=d;return}c[6435]=(c[6435]|0)+1;e=yc((k<<2|3)+16|0)|0;if(!e)h=0;else{c[(e+4+15&-16)+-4>>2]=e;h=e+4+15&-16}g=c[j+4>>2]|0;f=c[j+12>>2]|0;if((g|0)<=0)if(!f){a[j+16>>0]=1;c[j+12>>2]=h;c[j+8>>2]=k;Qn(h|0,0,k<<2|0)|0}else i=11;else{e=0;do{c[h+(e<<2)>>2]=c[f+(e<<2)>>2];e=e+1|0}while((e|0)!=(g|0));i=11}if((i|0)==11){if(a[j+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}a[j+16>>0]=1;c[j+12>>2]=h;c[j+8>>2]=k;Qn(h|0,0,k<<2|0)|0}e=c[j+12>>2]|0;c[j+4>>2]=k;f=c[d+12>>2]|0;g=0;do{c[e+(g<<2)>>2]=c[f+(g<<2)>>2];g=g+1|0}while((g|0)!=(k|0));k=j+20|0;d=d+20|0;c[k>>2]=c[d>>2];c[k+4>>2]=c[d+4>>2];c[k+8>>2]=c[d+8>>2];c[k+12>>2]=c[d+12>>2];d=c[b+4>>2]|0;d=d+1|0;c[b+4>>2]=d;return}function uh(a,d,f,g){a=a|0;d=d|0;f=f|0;g=g|0;var h=0,i=0,j=0,k=0,l=0,m=0,n=0,o=0;i=c[a+68+(d<<2)>>2]|0;h=b[i+((f&65535)<<2)+-4>>1]|0;if((e[i+((f&65535)<<2)>>1]|0)>=(h&65535))return;k=c[a+60>>2]|0;l=k+((e[i+((f&65535)<<2)+2>>1]|0)<<6)+54+(d<<1)|0;j=i+((f&65535)<<2)|0;f=i+((f&65535)<<2)+-4|0;while(1){i=e[j+-2>>1]|0;if(!(h&1)){h=e[j+2>>1]|0;if(((((e[k+(h<<6)+54+((1<>1]|0)>=(e[k+(i<<6)+48+((1<>1]|0)?(e[k+(i<<6)+54+((1<>1]|0)>=(e[k+(h<<6)+48+((1<>1]|0):0)?(e[k+(h<<6)+54+((1<<(1<>1]|0)>=(e[k+(i<<6)+48+((1<<(1<>1]|0):0)?(e[k+(i<<6)+54+((1<<(1<>1]|0)>=(e[k+(h<<6)+48+((1<<(1<>1]|0):0)?(o=c[a+92>>2]|0,m=k+(h<<6)|0,n=k+(i<<6)|0,Ib[c[(c[o>>2]|0)+12>>2]&31](o,m,n,g)|0,o=c[a+96>>2]|0,o|0):0)Ib[c[(c[o>>2]|0)+12>>2]&31](o,m,n,g)|0;k=k+(i<<6)+48+(d<<1)|0;b[k>>1]=(b[k>>1]|0)+1<<16>>16}else{k=k+(i<<6)+54+(d<<1)|0;b[k>>1]=(b[k>>1]|0)+1<<16>>16}b[l>>1]=(b[l>>1]|0)+-1<<16>>16;i=e[j>>1]|e[j+2>>1]<<16;h=e[f>>1]|e[f+2>>1]<<16;b[j>>1]=h;b[j+2>>1]=h>>>16;b[f>>1]=i;b[f+2>>1]=i>>>16;i=j+-4|0;f=f+-4|0;h=b[f>>1]|0;if((e[i>>1]|0)>=(h&65535))break;k=c[a+60>>2]|0;j=i}return}function vh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,j=0,k=0;k=i;i=i+48|0;g=c[a+28>>2]|0;c[k+32>>2]=g;g=(c[a+20>>2]|0)-g|0;c[k+32+4>>2]=g;c[k+32+8>>2]=b;c[k+32+12>>2]=d;j=k+32|0;f=2;g=g+d|0;while(1){if(!0){c[k+16>>2]=c[a+60>>2];c[k+16+4>>2]=j;c[k+16+8>>2]=f;b=wb(146,k+16|0)|0;if(b>>>0>4294963200){if(!0)e=25748;else e=c[(ib()|0)+64>>2]|0;c[e>>2]=0-b;b=-1}}else{rb(254,a|0);c[k>>2]=c[a+60>>2];c[k+4>>2]=j;c[k+8>>2]=f;b=wb(146,k|0)|0;if(b>>>0>4294963200){if(!0)e=25748;else e=c[(ib()|0)+64>>2]|0;c[e>>2]=0-b;b=-1}Ua(0)}if((g|0)==(b|0)){b=13;break}if((b|0)<0){b=15;break}g=g-b|0;e=c[j+4>>2]|0;if(b>>>0<=e>>>0)if((f|0)==2){c[a+28>>2]=(c[a+28>>2]|0)+b;h=e;e=j;f=2}else{h=e;e=j}else{h=c[a+44>>2]|0;c[a+28>>2]=h;c[a+20>>2]=h;h=c[j+12>>2]|0;b=b-e|0;e=j+8|0;f=f+-1|0}c[e>>2]=(c[e>>2]|0)+b;c[e+4>>2]=h-b;j=e}if((b|0)==13){j=c[a+44>>2]|0;c[a+16>>2]=j+(c[a+48>>2]|0);c[a+28>>2]=j;c[a+20>>2]=j}else if((b|0)==15){c[a+16>>2]=0;c[a+28>>2]=0;c[a+20>>2]=0;c[a>>2]=c[a>>2]|32;if((f|0)==2)d=0;else d=d-(c[j+4>>2]|0)|0}i=k;return d|0}function wh(a,d,f){a=a|0;d=d|0;f=f|0;var g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0;h=c[a+68+(d<<2)>>2]|0;m=c[a+60>>2]|0;n=e[h+((f&65535)<<2)+2>>1]|0;g=b[h+((f&65535)<<2)+-4>>1]|0;if((e[h+((f&65535)<<2)>>1]|0)>=(g&65535))return;j=m;i=h+((f&65535)<<2)|0;f=h+((f&65535)<<2)+-4|0;while(1){h=e[i+-2>>1]|0;if(!(g&1)){j=j+(h<<6)+48+(d<<1)|0;b[j>>1]=(b[j>>1]|0)+1<<16>>16}else{if(((((e[m+(n<<6)+54+((1<>1]|0)>=(e[j+(h<<6)+48+((1<>1]|0)?(e[j+(h<<6)+54+((1<>1]|0)>=(e[m+(n<<6)+48+((1<>1]|0):0)?(e[m+(n<<6)+54+((1<<(1<>1]|0)>=(e[j+(h<<6)+48+((1<<(1<>1]|0):0)?(e[j+(h<<6)+54+((1<<(1<>1]|0)>=(e[m+(n<<6)+48+((1<<(1<>1]|0):0)?(l=c[a+92>>2]|0,k=j+(h<<6)|0,Ob[c[(c[l>>2]|0)+8>>2]&63](l,m+(n<<6)|0,k)|0,l=c[a+96>>2]|0,l|0):0)Ob[c[(c[l>>2]|0)+8>>2]&63](l,m+(n<<6)|0,k)|0;j=j+(h<<6)+54+(d<<1)|0;b[j>>1]=(b[j>>1]|0)+1<<16>>16}b[m+(n<<6)+48+(d<<1)>>1]=(b[m+(n<<6)+48+(d<<1)>>1]|0)+-1<<16>>16;h=e[i>>1]|e[i+2>>1]<<16;g=e[f>>1]|e[f+2>>1]<<16;b[i>>1]=g;b[i+2>>1]=g>>>16;b[f>>1]=h;b[f+2>>1]=h>>>16;h=i+-4|0;f=f+-4|0;g=b[f>>1]|0;if((e[h>>1]|0)>=(g&65535))break;j=c[a+60>>2]|0;i=h}return}function xh(a,b,d,e,f,h,j,k,l,m){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;k=k|0;l=l|0;m=m|0;var n=0.0,o=0.0;m=i;i=i+80|0;o=+g[h+52>>2]-+g[f+52>>2];n=+g[h+56>>2]-+g[f+56>>2];g[m+56>>2]=+g[h+48>>2]-+g[f+48>>2];g[m+56+4>>2]=o;g[m+56+8>>2]=n;g[m+56+12>>2]=0.0;if(Pc(d,f,e,h,m+56|0,m,1)|0){c[k>>2]=c[m+4>>2];c[k+4>>2]=c[m+4+4>>2];c[k+8>>2]=c[m+4+8>>2];c[k+12>>2]=c[m+4+12>>2];c[l>>2]=c[m+20>>2];c[l+4>>2]=c[m+20+4>>2];c[l+8>>2]=c[m+20+8>>2];c[l+12>>2]=c[m+20+12>>2];c[j>>2]=c[m+36>>2];c[j+4>>2]=c[m+36+4>>2];c[j+8>>2]=c[m+36+8>>2];c[j+12>>2]=c[m+36+12>>2];l=1;i=m;return l|0}if(!(Jd(d,f,e,h,m+56|0,m)|0)){l=0;i=m;return l|0}c[k>>2]=c[m+4>>2];c[k+4>>2]=c[m+4+4>>2];c[k+8>>2]=c[m+4+8>>2];c[k+12>>2]=c[m+4+12>>2];c[l>>2]=c[m+20>>2];c[l+4>>2]=c[m+20+4>>2];c[l+8>>2]=c[m+20+8>>2];c[l+12>>2]=c[m+20+12>>2];c[j>>2]=c[m+36>>2];c[j+4>>2]=c[m+36+4>>2];c[j+8>>2]=c[m+36+8>>2];c[j+12>>2]=c[m+36+12>>2];l=0;i=m;return l|0}function yh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,j=0,k=0,l=0,m=0.0,n=0.0,o=0,p=0,q=0.0,r=0;p=i;i=i+2048|0;c[a>>2]=0;c[a+4>>2]=0;c[a+8>>2]=0;c[a+12>>2]=0;e=+g[d>>2];h=+g[d+4>>2];f=+g[d+8>>2];if(e*e+h*h+f*f<9.999999747378752e-05){n=1.0;m=0.0;h=0.0}else{q=1.0/+O(+(e*e+h*h+f*f));n=e*q;m=f*q;h=h*q}if((Eb[c[(c[b>>2]|0)+96>>2]&127](b)|0)<=0){i=p;return}l=0;f=-999999984306749440.0;while(1){if(((Eb[c[(c[b>>2]|0)+96>>2]&127](b)|0)-l|0)<128){d=(Eb[c[(c[b>>2]|0)+96>>2]&127](b)|0)-l|0;if((d|0)>0)o=8;else{e=-3402823466385288598117041.0e14;d=-1}}else{d=128;o=8}if((o|0)==8){o=0;j=0;do{ic[c[(c[b>>2]|0)+108>>2]&127](b,j,p+(j<<4)|0);j=j+1|0}while((j|0)!=(d|0));k=0;e=-3402823466385288598117041.0e14;j=-1;do{q=n*+g[p+(k<<4)>>2]+h*+g[p+(k<<4)+4>>2]+m*+g[p+(k<<4)+8>>2];r=q>e;j=r?k:j;e=r?q:e;k=k+1|0}while((k|0)!=(d|0));d=j}if(e>f){r=p+(d<<4)|0;c[a>>2]=c[r>>2];c[a+4>>2]=c[r+4>>2];c[a+8>>2]=c[r+8>>2];c[a+12>>2]=c[r+12>>2]}else e=f;l=l+128|0;if((l|0)>=(Eb[c[(c[b>>2]|0)+96>>2]&127](b)|0))break;else f=e}i=p;return}function zh(b,e,f,h,i,j){b=b|0;e=e|0;f=f|0;h=h|0;i=i|0;j=j|0;var k=0;if((d[h+55>>0]|0|0)==(e|0)){h=0;return h|0}k=c[4976+(i<<2)>>2]|0;if(+g[h>>2]*+g[f+16>>2]+ +g[h+4>>2]*+g[f+20>>2]+ +g[h+8>>2]*+g[f+24>>2]-+g[h+16>>2]<-9.999999747378752e-06){k=nf(b,c[h+20+(k<<2)>>2]|0,c[h+20+(i<<2)>>2]|0,f,0)|0;if(!k){h=0;return h|0}a[k+52>>0]=i;c[k+32>>2]=h;a[h+52+i>>0]=0;c[h+32+(i<<2)>>2]=k;i=c[j>>2]|0;if(!i)c[j+4>>2]=k;else{a[i+53>>0]=2;c[i+36>>2]=k;a[k+54>>0]=1;c[k+40>>2]=i}c[j>>2]=k;c[j+8>>2]=(c[j+8>>2]|0)+1;h=1;return h|0}i=c[4988+(i<<2)>>2]|0;a[h+55>>0]=e;if(!(zh(b,e,f,c[h+32+(k<<2)>>2]|0,d[h+52+k>>0]|0,j)|0)){h=0;return h|0}if(!(zh(b,e,f,c[h+32+(i<<2)>>2]|0,d[h+52+i>>0]|0,j)|0)){h=0;return h|0}i=c[h+48>>2]|0;if(i|0)c[i+44>>2]=c[h+44>>2];i=c[h+44>>2]|0;if(i|0)c[i+48>>2]=c[h+48>>2];if((c[b+9280>>2]|0)==(h|0))c[b+9280>>2]=c[h+48>>2];c[b+9284>>2]=(c[b+9284>>2]|0)+-1;c[h+44>>2]=0;c[h+48>>2]=c[b+9288>>2];i=c[b+9288>>2]|0;if(i|0)c[i+44>>2]=h;c[b+9288>>2]=h;c[b+9292>>2]=(c[b+9292>>2]|0)+1;h=1;return h|0}function Ah(b,d){b=b|0;d=d|0;var e=0,f=0,h=0.0,i=0,j=0,k=0.0,l=0.0;e=c[d+204>>2]|0;if((e&3|0)==0?(c[d+504>>2]&1|0)==0:0){h=+g[d+344>>2];if(h!=0.0){l=1.0/h*+g[b+252>>2];k=1.0/h*+g[b+256>>2];g[d+364>>2]=1.0/h*+g[b+248>>2];g[d+368>>2]=l;g[d+372>>2]=k;g[d+376>>2]=0.0}c[d+380>>2]=c[b+248>>2];c[d+380+4>>2]=c[b+248+4>>2];c[d+380+8>>2]=c[b+248+8>>2];c[d+380+12>>2]=c[b+248+12>>2]}if(!(c[d+192>>2]|0))return;if(e&1){if((c[d+216>>2]&-2|0)!=4)c[d+216>>2]=2}else{f=c[b+232>>2]|0;if((f|0)==(c[b+236>>2]|0)?(j=f|0?f<<1:1,(f|0)<(j|0)):0){if(!j)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((j<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[b+232>>2]|0}if((f|0)>0){i=0;do{c[e+(i<<2)>>2]=c[(c[b+240>>2]|0)+(i<<2)>>2];i=i+1|0}while((i|0)!=(f|0))}i=c[b+240>>2]|0;if(i){if(a[b+244>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[i+-4>>2]|0);f=c[b+232>>2]|0}c[b+240>>2]=0}a[b+244>>0]=1;c[b+240>>2]=e;c[b+236>>2]=j;e=c[d+204>>2]|0}c[(c[b+240>>2]|0)+(f<<2)>>2]=d;c[b+232>>2]=f+1}j=(e&3|0)==0;mc[c[(c[b>>2]|0)+36>>2]&127](b,d,j?1:2,j?-1:-3);return}function Bh(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,i=0.0,j=0,k=0,l=0,m=0.0,n=0.0;h=c[d+204>>2]|0;if((h&3|0)==0?(c[d+504>>2]&1|0)==0:0){i=+g[d+344>>2];if(i!=0.0){n=1.0/i*+g[b+252>>2];m=1.0/i*+g[b+256>>2];g[d+364>>2]=1.0/i*+g[b+248>>2];g[d+368>>2]=n;g[d+372>>2]=m;g[d+376>>2]=0.0}c[d+380>>2]=c[b+248>>2];c[d+380+4>>2]=c[b+248+4>>2];c[d+380+8>>2]=c[b+248+8>>2];c[d+380+12>>2]=c[b+248+12>>2]}if(!(c[d+192>>2]|0))return;if(h&1){if((c[d+216>>2]&-2|0)!=4)c[d+216>>2]=2}else{h=c[b+232>>2]|0;if((h|0)==(c[b+236>>2]|0)?(l=h|0?h<<1:1,(h|0)<(l|0)):0){if(!l)k=0;else{c[6435]=(c[6435]|0)+1;h=yc((l<<2|3)+16|0)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}k=h;h=c[b+232>>2]|0}if((h|0)>0){j=0;do{c[k+(j<<2)>>2]=c[(c[b+240>>2]|0)+(j<<2)>>2];j=j+1|0}while((j|0)!=(h|0))}j=c[b+240>>2]|0;if(j){if(a[b+244>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0);h=c[b+232>>2]|0}c[b+240>>2]=0}a[b+244>>0]=1;c[b+240>>2]=k;c[b+236>>2]=l}c[(c[b+240>>2]|0)+(h<<2)>>2]=d;c[b+232>>2]=h+1}mc[c[(c[b>>2]|0)+36>>2]&127](b,d,e,f);return}function Ch(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0;o=(+g[a+32>>2]-+g[a+16>>2])*.5;l=(+g[a+36>>2]-+g[a+20>>2])*.5;i=(+g[a+40>>2]-+g[a+24>>2])*.5;n=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);k=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);i=i+ +Sb[c[(c[a>>2]|0)+48>>2]&15](a);B=(+g[a+32>>2]+ +g[a+16>>2])*.5;z=(+g[a+36>>2]+ +g[a+20>>2])*.5;x=(+g[a+40>>2]+ +g[a+24>>2])*.5;F=+g[b>>2];w=+N(+F);E=+g[b+4>>2];v=+N(+E);t=+g[b+8>>2];u=+N(+t);D=+g[b+16>>2];s=+N(+D);C=+g[b+20>>2];r=+N(+C);p=+g[b+24>>2];q=+N(+p);A=+g[b+32>>2];m=+N(+A);y=+g[b+36>>2];j=+N(+y);f=+g[b+40>>2];h=+N(+f);t=B*F+z*E+x*t+ +g[b+48>>2];p=B*D+z*C+x*p+ +g[b+52>>2];f=B*A+z*y+x*f+ +g[b+56>>2];g[d>>2]=t-((o+n)*w+(l+k)*v+i*u);g[d+4>>2]=p-((o+n)*s+(l+k)*r+i*q);g[d+8>>2]=f-((o+n)*m+(l+k)*j+i*h);g[d+12>>2]=0.0;g[e>>2]=(o+n)*w+(l+k)*v+i*u+t;g[e+4>>2]=(o+n)*s+(l+k)*r+i*q+p;g[e+8>>2]=(o+n)*m+(l+k)*j+i*h+f;g[e+12>>2]=0.0;return}function Dh(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0,G=0.0,H=0.0;H=+g[a+48>>2];z=+g[a+32>>2];G=+g[a+52>>2];x=+g[a+36>>2];E=+g[a+56>>2];v=+g[a+40>>2];F=(c[a+16>>2]|0)==0;m=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);k=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);i=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);m=(F?0.0:(H-z)*.5)+m;k=(F?0.0:(G-x)*.5)+k;i=(F?0.0:(E-v)*.5)+i;D=+g[b>>2];u=+N(+D);C=+g[b+4>>2];t=+N(+C);r=+g[b+8>>2];s=+N(+r);B=+g[b+16>>2];q=+N(+B);A=+g[b+20>>2];p=+N(+A);n=+g[b+24>>2];o=+N(+n);y=+g[b+32>>2];l=+N(+y);w=+g[b+36>>2];j=+N(+w);f=+g[b+40>>2];h=+N(+f);z=F?0.0:(H+z)*.5;x=F?0.0:(G+x)*.5;v=F?0.0:(E+v)*.5;r=z*D+x*C+v*r+ +g[b+48>>2];n=z*B+x*A+v*n+ +g[b+52>>2];f=z*y+x*w+v*f+ +g[b+56>>2];g[d>>2]=r-(m*u+k*t+i*s);g[d+4>>2]=n-(m*q+k*p+i*o);g[d+8>>2]=f-(m*l+k*j+i*h);g[d+12>>2]=0.0;g[e>>2]=m*u+k*t+i*s+r;g[e+4>>2]=m*q+k*p+i*o+n;g[e+8>>2]=m*l+k*j+i*h+f;g[e+12>>2]=0.0;return}function Eh(b,d){b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0,l=0.0,m=0.0;if(a[b+48>>0]|0){c[d>>2]=0;c[d+4>>2]=0;return}c[d>>2]=4;c[d+4>>2]=2;kd(b,(c[b+28>>2]|0)+4|0,(c[b+32>>2]|0)+4|0);g[b+1088>>2]=0.0;a[b+297>>0]=0;f=+g[b+192>>2];h=+g[b+196>>2];do if(f<=h){m=+g[b+892>>2];l=+g[b+908>>2];i=+g[b+924>>2];i=+ik(+W(+(+g[b+832>>2]*m+ +g[b+848>>2]*l+ +g[b+864>>2]*i),+(+g[b+828>>2]*m+ +g[b+844>>2]*l+ +g[b+860>>2]*i)),f,h);g[b+1084>>2]=i;if(i>2]=i-f;a[b+297>>0]=1;j=1;break}if(i>h){g[b+1088>>2]=i-h;a[b+297>>0]=1;j=1}else j=0}else j=0;while(0);a[b+296>>0]=0;e=c[b+1032>>2]|0;c[b+1080>>2]=e;f=+g[b+184>>2];h=+g[b+188>>2];i=(c[k>>2]=e,+g[k>>2]);do if(f<=h){if(i>h){g[b+1032>>2]=i-h;a[b+296>>0]=1;e=14;break}if(i>2]=i-f;a[b+296>>0]=1;e=14}else e=13}else e=13;while(0);if((e|0)==13?(g[b+1032>>2]=0.0,a[b+1096>>0]|0):0)e=14;if((e|0)==14){c[d>>2]=(c[d>>2]|0)+1;c[d+4>>2]=(c[d+4>>2]|0)+-1}if(j<<24>>24==0?(a[b+1112>>0]|0)==0:0)return;c[d>>2]=(c[d>>2]|0)+1;c[d+4>>2]=(c[d+4>>2]|0)+-1;return}function Fh(a){a=a|0;var b=0,d=0.0,e=0,f=0,h=0,i=0,j=0.0,k=0.0,l=0,m=0,n=0.0,o=0,p=0.0;c[6435]=(c[6435]|0)+1;b=yc(75)|0;if(!b)i=0;else{c[(b+4+15&-16)+-4>>2]=b;i=b+4+15&-16}c[i+8>>2]=0;e=i+12|0;c[e>>2]=1065353216;f=i+16|0;c[f>>2]=1065353216;h=i+20|0;c[h>>2]=1065353216;g[i+24>>2]=0.0;b=i+44|0;g[b>>2]=.03999999910593033;c[i+52>>2]=0;c[i>>2]=7844;c[i+4>>2]=0;k=+g[a>>2];j=+g[a+4>>2];d=+g[a+8>>2];d=+g[a+((k>2]*.10000000149011612;if(d<.03999999910593033){p=+xz(i);n=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);k=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);o=i+28|0;p=p+ +g[o>>2];m=i+32|0;n=n+ +g[m>>2];l=i+36|0;k=k+ +g[l>>2];g[b>>2]=d;d=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);j=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);k=k-+Sb[c[(c[i>>2]|0)+48>>2]&15](i);g[o>>2]=p-d;g[m>>2]=n-j;g[l>>2]=k;g[i+40>>2]=0.0;b=c[i>>2]|0}else b=7844;k=+Sb[c[b+48>>2]&15](i);n=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);p=+Sb[c[(c[i>>2]|0)+48>>2]&15](i);n=+g[a+4>>2]*+g[f>>2]-n;p=+g[a+8>>2]*+g[h>>2]-p;g[i+28>>2]=+g[a>>2]*+g[e>>2]-k;g[i+32>>2]=n;g[i+36>>2]=p;g[i+40>>2]=0.0;return i|0}function Gh(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0,h=0;f=c[a+212>>2]|0;a:do if((f|0)>0){g=c[a+220>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0))break a}if((d|0)<(f|0)){c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+220>>2]|0)+(f+-1<<2)>>2]=b;c[a+212>>2]=f+-1}}while(0);a=c[b+28>>2]|0;d=c[a+488>>2]|0;b:do if((d|0)>0){g=c[a+496>>2]|0;e=0;while(1){f=g+(e<<2)|0;if((c[f>>2]|0)==(b|0))break;e=e+1|0;if((e|0)>=(d|0))break b}if((e|0)<(d|0)){c[f>>2]=c[g+(d+-1<<2)>>2];c[(c[a+496>>2]|0)+(d+-1<<2)>>2]=b;c[a+488>>2]=d+-1;d=d+-1|0}}while(0);c[a+256>>2]=(d|0)>0&1;a=c[b+32>>2]|0;d=c[a+488>>2]|0;if((d|0)<=0){b=d;b=(b|0)>0;b=b&1;h=a+256|0;c[h>>2]=b;return}g=c[a+496>>2]|0;e=0;while(1){f=g+(e<<2)|0;if((c[f>>2]|0)==(b|0))break;e=e+1|0;if((e|0)>=(d|0)){h=19;break}}if((h|0)==19){b=(d|0)>0;b=b&1;h=a+256|0;c[h>>2]=b;return}if((e|0)>=(d|0)){b=d;b=(b|0)>0;b=b&1;h=a+256|0;c[h>>2]=b;return}c[f>>2]=c[g+(d+-1<<2)>>2];c[(c[a+496>>2]|0)+(d+-1<<2)>>2]=b;c[a+488>>2]=d+-1;b=d+-1|0;b=(b|0)>0;b=b&1;h=a+256|0;c[h>>2]=b;return}function Hh(b,d){b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0;j=Eb[c[(c[b>>2]|0)+28>>2]&127](b)|0;i=+g[j>>2]-+g[d>>2];h=+g[j+4>>2]-+g[d+4>>2];f=+g[j+8>>2]-+g[d+8>>2];if(!(i*i+h*h+f*f>1.1920928955078125e-07))return;Xg(b,d);if((a[b+61>>0]|0)!=0?(e=c[b+52>>2]|0,Ab[c[c[e>>2]>>2]&255](e),e=c[b+52>>2]|0,(e|0)!=0):0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);d=b+52|0}else d=b+52|0;c[6435]=(c[6435]|0)+1;e=yc(191)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e+52>>2]=282;a[e+60>>0]=0;a[e+80>>0]=1;c[e+76>>2]=0;c[e+68>>2]=0;c[e+72>>2]=0;a[e+100>>0]=1;c[e+96>>2]=0;c[e+88>>2]=0;c[e+92>>2]=0;a[e+120>>0]=1;c[e+116>>2]=0;c[e+108>>2]=0;c[e+112>>2]=0;a[e+140>>0]=1;c[e+136>>2]=0;c[e+128>>2]=0;c[e+132>>2]=0;c[e+144>>2]=0;a[e+164>>0]=1;c[e+160>>2]=0;c[e+152>>2]=0;c[e+156>>2]=0;c[e+168>>2]=0;c[e+4>>2]=-8388609;c[e+8>>2]=-8388609;c[e+12>>2]=-8388609;g[e+16>>2]=0.0;c[e+20>>2]=2139095039;c[e+24>>2]=2139095039;c[e+28>>2]=2139095039;g[e+32>>2]=0.0;c[e>>2]=7980;c[d>>2]=e;pd(e,c[b+48>>2]|0,(a[b+60>>0]|0)!=0,b+16|0,b+32|0);a[b+61>>0]=1;return}function Ih(b,d){b=b|0;d=d|0;var e=0.0,f=0.0;if(a[b+1309>>0]|0){e=(+g[b+1256>>2]-+g[b+1316>>2])*+g[b+1340>>2];g[b+792>>2]=e*(+g[d>>2]*+g[b+1364>>2]/+(c[d+48>>2]|0));e=+N(+e);g[b+808>>2]=e/+g[d>>2]}if(a[b+1310>>0]|0){e=(+g[b+1260>>2]-+g[b+1320>>2])*+g[b+1344>>2];g[b+796>>2]=e*(+g[d>>2]*+g[b+1368>>2]/+(c[d+48>>2]|0));e=+N(+e);g[b+812>>2]=e/+g[d>>2]}if(a[b+1311>>0]|0){e=(+g[b+1264>>2]-+g[b+1324>>2])*+g[b+1348>>2];g[b+800>>2]=e*(+g[d>>2]*+g[b+1372>>2]/+(c[d+48>>2]|0));e=+N(+e);g[b+816>>2]=e/+g[d>>2]}if(a[b+1312>>0]|0){f=-((+g[b+1192>>2]-+g[b+1328>>2])*+g[b+1352>>2]);e=+g[d>>2];g[b+876>>2]=e*+g[b+1376>>2]/+(c[d+48>>2]|0)*f;g[b+880>>2]=+N(+f)/e}if(a[b+1313>>0]|0){e=-((+g[b+1196>>2]-+g[b+1332>>2])*+g[b+1356>>2]);f=+g[d>>2];g[b+940>>2]=f*+g[b+1380>>2]/+(c[d+48>>2]|0)*e;g[b+944>>2]=+N(+e)/f}if(!(a[b+1314>>0]|0)){fg(b,d);return}e=-((+g[b+1200>>2]-+g[b+1336>>2])*+g[b+1360>>2]);f=+g[d>>2];g[b+1004>>2]=f*+g[b+1384>>2]/+(c[d+48>>2]|0)*e;g[b+1008>>2]=+N(+e)/f;fg(b,d);return}function Jh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,h=0.0,j=0.0,k=0.0;e=i;i=i+160|0;c[e+136>>2]=0;c[e+136+4>>2]=0;c[e+136+8>>2]=0;c[e+136+12>>2]=0;c[e+136+16>>2]=0;c[e+32>>2]=7028;f=e+32+4|0;c[f>>2]=0;c[f+4>>2]=0;c[f+8>>2]=0;c[f+12>>2]=0;c[e+32+20>>2]=1065353216;c[e+32+24>>2]=0;c[e+32+24+4>>2]=0;c[e+32+24+8>>2]=0;c[e+32+24+12>>2]=0;c[e+32+40>>2]=1065353216;c[e+32+44>>2]=0;c[e+32+44+4>>2]=0;c[e+32+44+8>>2]=0;c[e+32+44+12>>2]=0;c[e+32+60>>2]=1065353216;c[e+32+64>>2]=0;c[e+32+68>>2]=c[e+136+4>>2];c[e+32+68+4>>2]=c[e+136+4+4>>2];c[e+32+68+8>>2]=c[e+136+4+8>>2];c[e+32+68+12>>2]=c[e+136+4+12>>2];g[e+32+84>>2]=-999999984306749440.0;k=+g[d>>2];j=+g[d+4>>2];h=+g[d+8>>2];g[e+32+88>>2]=k+j*0.0+h*0.0;g[e+32+92>>2]=k*0.0+j+h*0.0;g[e+32+96>>2]=k*0.0+j*0.0+h;g[e+32+100>>2]=0.0;c[e+16>>2]=1566444395;c[e+16+4>>2]=1566444395;c[e+16+8>>2]=1566444395;g[e+16+12>>2]=0.0;d=c[(c[b>>2]|0)+64>>2]|0;g[e>>2]=-999999984306749440.0;g[e+4>>2]=-999999984306749440.0;g[e+8>>2]=-999999984306749440.0;g[e+12>>2]=0.0;mc[d&127](b,e+32|0,e,e+16|0);c[a>>2]=c[f>>2];c[a+4>>2]=c[f+4>>2];c[a+8>>2]=c[f+8>>2];c[a+12>>2]=c[f+12>>2];i=e;return}function Kh(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0;q=i;i=i+16|0;c[a>>2]=0;c[a+4>>2]=0;c[a+8>>2]=0;c[a+12>>2]=0;e=+g[d>>2];f=+g[d+4>>2];h=+g[d+8>>2];if(e*e+f*f+h*h<9.999999747378752e-05){p=1.0;o=0.0;n=0.0}else{n=1.0/+O(+(e*e+f*f+h*h));p=e*n;o=f*n;n=h*n}d=c[b+52>>2]|0;m=+g[b+28+(((d+2|0)%3|0)<<2)>>2];c[q>>2]=0;c[q+4>>2]=0;c[q+8>>2]=0;c[q+12>>2]=0;c[q+(d<<2)>>2]=c[b+28+(d<<2)>>2];k=p*m;l=o*m;m=n*m;e=k+ +g[q>>2];f=l+ +g[q+4>>2];j=m+ +g[q+8>>2];h=+Sb[c[(c[b>>2]|0)+48>>2]&15](b);e=e-p*h;f=f-o*h;h=j-n*h;j=n*h+(p*e+o*f);if(j>-999999984306749440.0){g[a>>2]=e;g[a+4>>2]=f;g[a+8>>2]=h;g[a+12>>2]=0.0}else j=-999999984306749440.0;c[q>>2]=0;c[q+4>>2]=0;c[q+8>>2]=0;c[q+12>>2]=0;d=c[b+52>>2]|0;g[q+(d<<2)>>2]=-+g[b+28+(d<<2)>>2];e=k+ +g[q>>2];f=l+ +g[q+4>>2];m=m+ +g[q+8>>2];h=+Sb[c[(c[b>>2]|0)+48>>2]&15](b);e=e-p*h;f=f-o*h;h=m-n*h;if(!(n*h+(p*e+o*f)>j)){i=q;return}g[a>>2]=e;g[a+4>>2]=f;g[a+8>>2]=h;g[a+12>>2]=0.0;i=q;return}function Lh(a,b,d,e,f,h,j,k,l,m){a=a|0;b=b|0;d=d|0;e=e|0;f=+f;h=+h;j=+j;k=+k;l=+l;m=+m;var n=0;n=i;i=i+128|0;c[n+80>>2]=c[a+4>>2];c[n+80+4>>2]=c[a+20>>2];c[n+80+8>>2]=c[a+36>>2];g[n+80+12>>2]=0.0;c[n+80+16>>2]=c[a+8>>2];c[n+80+20>>2]=c[a+24>>2];c[n+80+24>>2]=c[a+40>>2];g[n+80+28>>2]=0.0;c[n+80+32>>2]=c[a+12>>2];c[n+80+36>>2]=c[a+28>>2];c[n+80+40>>2]=c[a+44>>2];g[n+80+44>>2]=0.0;c[n+32>>2]=c[b+4>>2];c[n+32+4>>2]=c[b+20>>2];c[n+32+8>>2]=c[b+36>>2];g[n+32+12>>2]=0.0;c[n+32+16>>2]=c[b+8>>2];c[n+32+20>>2]=c[b+24>>2];c[n+32+24>>2]=c[b+40>>2];g[n+32+28>>2]=0.0;c[n+32+32>>2]=c[b+12>>2];c[n+32+36>>2]=c[b+28>>2];c[n+32+40>>2]=c[b+44>>2];g[n+32+44>>2]=0.0;h=h-+g[a+56>>2];j=j-+g[a+60>>2];g[n+16>>2]=f-+g[a+52>>2];g[n+16+4>>2]=h;g[n+16+8>>2]=j;g[n+16+12>>2]=0.0;l=l-+g[b+56>>2];m=m-+g[b+60>>2];g[n>>2]=k-+g[b+52>>2];g[n+4>>2]=l;g[n+8>>2]=m;g[n+12>>2]=0.0;Rg(d,n+80|0,n+32|0,n+16|0,n,e,a+396|0,+g[a+344>>2],b+396|0,+g[b+344>>2]);i=n;return}function Mh(a,b,c,d,e,f,h,i,j,k,l,m,n,o){a=a|0;b=+b;c=+c;d=+d;e=+e;f=+f;h=+h;i=+i;j=+j;k=+k;l=+l;m=+m;n=+n;o=+o;var p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0;s=(j-f)*(n-h)-(k-h)*(m-f);q=(k-h)*(l-e)-(i-e)*(n-h);r=(i-e)*(m-f)-(j-f)*(l-e);if(+N(+(r*d+(s*b+q*c)))<1.1920928955078125e-07){d=-1.0;return +d}t=+g[a>>2];v=+g[a+4>>2];u=+g[a+8>>2];p=-(s*t+q*v+r*u-(r*h+(s*e+q*f)))/(r*d+(s*b+q*c));if(((p>1.1920928955078125e-06&p-1.1920928955078125e-06:0)?r*((m-(v+p*c))*(i-(t+p*b))-(j-(v+p*c))*(l-(t+p*b)))+(s*((j-(v+p*c))*(n-(u+p*d))-(k-(u+p*d))*(m-(v+p*c)))+q*((k-(u+p*d))*(l-(t+p*b))-(n-(u+p*d))*(i-(t+p*b))))>-1.1920928955078125e-06:0)?r*((f-(v+p*c))*(l-(t+p*b))-(m-(v+p*c))*(e-(t+p*b)))+(s*((m-(v+p*c))*(h-(u+p*d))-(n-(u+p*d))*(f-(v+p*c)))+q*((n-(u+p*d))*(e-(t+p*b))-(h-(u+p*d))*(l-(t+p*b))))>-1.1920928955078125e-06:0){v=p;return +v}v=-1.0;return +v}function Nh(a,b,d,e,f){a=a|0;b=+b;d=+d;e=+e;f=f|0;var h=0,j=0,k=0,l=0,m=0.0,n=0.0;k=i;i=i+48|0;m=1.0/+O(+(b*b+d*d+e*e));g[f>>2]=m*b;g[f+4>>2]=m*d;g[f+8>>2]=m*e;g[f+12>>2]=0.0;h=c[a+120>>2]|0;l=c[a+124>>2]|0;j=(c[a>>2]|0)+(l>>1)|0;if(l&1)h=c[(c[j>>2]|0)+h>>2]|0;ic[h&127](k,j,f);b=-+g[f>>2];d=-+g[f+4>>2];e=-+g[f+8>>2];h=c[a+120>>2]|0;l=c[a+124>>2]|0;j=(c[a+4>>2]|0)+(l>>1)|0;if(l&1)h=c[(c[j>>2]|0)+h>>2]|0;m=+g[a+24>>2]*b+ +g[a+28>>2]*d+ +g[a+32>>2]*e;n=+g[a+40>>2]*b+ +g[a+44>>2]*d+ +g[a+48>>2]*e;g[k+16>>2]=+g[a+8>>2]*b+ +g[a+12>>2]*d+ +g[a+16>>2]*e;g[k+16+4>>2]=m;g[k+16+8>>2]=n;g[k+16+12>>2]=0.0;ic[h&127](k+32|0,j,k+16|0);n=+g[k+32>>2];b=+g[k+32+4>>2];d=+g[k+32+8>>2];e=+g[k+4>>2]-(n*+g[a+72>>2]+b*+g[a+76>>2]+d*+g[a+80>>2]+ +g[a+108>>2]);m=+g[k+8>>2]-(n*+g[a+88>>2]+b*+g[a+92>>2]+d*+g[a+96>>2]+ +g[a+112>>2]);g[f+16>>2]=+g[k>>2]-(n*+g[a+56>>2]+b*+g[a+60>>2]+d*+g[a+64>>2]+ +g[a+104>>2]);g[f+20>>2]=e;g[f+24>>2]=m;g[f+28>>2]=0.0;i=k;return}function Oh(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0;if(a[b+165>>0]|0){if((c[b+92>>2]|0)>=(d|0))return;if((d|0)!=0?(c[6435]=(c[6435]|0)+1,e=yc((d<<4|3)+16|0)|0,(e|0)!=0):0){c[(e+4+15&-16)+-4>>2]=e;g=e+4+15&-16}else g=0;e=c[b+88>>2]|0;if((e|0)>0){f=0;do{i=g+(f<<4)|0;h=(c[b+96>>2]|0)+(f<<4)|0;c[i>>2]=c[h>>2];c[i+4>>2]=c[h+4>>2];c[i+8>>2]=c[h+8>>2];c[i+12>>2]=c[h+12>>2];f=f+1|0}while((f|0)!=(e|0))}e=c[b+96>>2]|0;if(e|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=g;c[b+92>>2]=d;return}if((c[b+112>>2]|0)>=(d|0))return;if((d|0)!=0?(c[6435]=(c[6435]|0)+1,f=yc((d<<2|3)+16|0)|0,(f|0)!=0):0){c[(f+4+15&-16)+-4>>2]=f;h=f+4+15&-16}else h=0;f=c[b+108>>2]|0;g=c[b+116>>2]|0;if((f|0)<=0)if(!g)e=b+120|0;else i=21;else{e=0;do{c[h+(e<<2)>>2]=c[g+(e<<2)>>2];e=e+1|0}while((e|0)!=(f|0));i=21}if((i|0)==21){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+116>>2]=0;e=b+120|0}a[e>>0]=1;c[b+116>>2]=h;c[b+112>>2]=d;return}function Ph(){var b=0,d=0,e=0;c[6435]=(c[6435]|0)+1;b=yc(307)|0;if(!b)d=0;else{c[(b+4+15&-16)+-4>>2]=b;d=b+4+15&-16}c[d+164>>2]=1065353216;c[d+168>>2]=1065353216;c[d+172>>2]=1065353216;g[d+176>>2]=0.0;c[d+180>>2]=0;g[d+184>>2]=999999984306749440.0;b=d+188|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[d+204>>2]=1;c[d+208>>2]=-1;c[d+212>>2]=-1;c[d+216>>2]=1;g[d+220>>2]=0.0;g[d+224>>2]=.5;g[d+228>>2]=0.0;g[d+232>>2]=0.0;c[d+240>>2]=0;g[d+244>>2]=1.0;b=d+248|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[d+4>>2]=1065353216;b=d+8|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[d+24>>2]=1065353216;b=d+28|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[d+44>>2]=1065353216;b=d+48|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[b+16>>2]=0;a[d+280>>0]=1;c[d+276>>2]=0;c[d+268>>2]=0;c[d+272>>2]=0;c[d+236>>2]=4;c[d>>2]=5088;c[6435]=(c[6435]|0)+1;b=yc(95)|0;if(!b){e=0;Ri(e);b=d+284|0;c[b>>2]=e;return d|0}c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16;Ri(b);e=d+284|0;c[e>>2]=b;return d|0}function Qh(a,b,d,e,f,g,h,i,j){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;g=g|0;h=h|0;i=i|0;j=j|0;if(!(c[i+44>>2]|0))return;b=c[i+20>>2]|0;if(!(c[i+64>>2]&256)){if((b|0)<=0)return;j=0;do{g=c[a+28>>2]|0;if((g|0)>0){b=0;do{f=c[(c[a+116>>2]|0)+(b<<2)>>2]|0;h=c[a+36>>2]|0;d=c[a+16>>2]|0;Ig(d+((c[h+(f*152|0)+144>>2]|0)*244|0)|0,d+((c[h+(f*152|0)+148>>2]|0)*244|0)|0,h+(f*152|0)|0);b=b+1|0}while((b|0)!=(g|0));b=c[i+20>>2]|0}j=j+1|0}while((j|0)<(b|0));return}else{if((b|0)<=0)return;j=0;do{g=c[a+28>>2]|0;if((g|0)>0){b=0;do{f=c[(c[a+116>>2]|0)+(b<<2)>>2]|0;h=c[a+36>>2]|0;d=c[a+16>>2]|0;Ig(d+((c[h+(f*152|0)+144>>2]|0)*244|0)|0,d+((c[h+(f*152|0)+148>>2]|0)*244|0)|0,h+(f*152|0)|0);b=b+1|0}while((b|0)!=(g|0));b=c[i+20>>2]|0}j=j+1|0}while((j|0)<(b|0));return}}function Rh(d,e){d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0;if(!(a[d+164>>0]|0)){if((c[d+152>>2]|0)>=(e|0))return;if((e|0)!=0?(c[6435]=(c[6435]|0)+1,g=yc((e<<1)+19|0)|0,(g|0)!=0):0){c[(g+4+15&-16)+-4>>2]=g;i=g+4+15&-16}else i=0;g=c[d+148>>2]|0;h=c[d+156>>2]|0;if((g|0)<=0)if(!h)f=d+160|0;else j=22;else{f=0;do{b[i+(f<<1)>>1]=b[h+(f<<1)>>1]|0;f=f+1|0}while((f|0)!=(g|0));j=22}if((j|0)==22){if(a[d+160>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[d+156>>2]=0;f=d+160|0}a[f>>0]=1;c[d+156>>2]=i;c[d+152>>2]=e;return}else{if((c[d+132>>2]|0)>=(e|0))return;if((e|0)!=0?(c[6435]=(c[6435]|0)+1,f=yc((e<<2|3)+16|0)|0,(f|0)!=0):0){c[(f+4+15&-16)+-4>>2]=f;i=f+4+15&-16}else i=0;g=c[d+128>>2]|0;h=c[d+136>>2]|0;if((g|0)<=0)if(!h)f=d+140|0;else j=10;else{f=0;do{c[i+(f<<2)>>2]=c[h+(f<<2)>>2];f=f+1|0}while((f|0)!=(g|0));j=10}if((j|0)==10){if(a[d+140>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[d+136>>2]=0;f=d+140|0}a[f>>0]=1;c[d+136>>2]=i;c[d+132>>2]=e;return}}function Sh(a,b,d){a=a|0;b=b|0;d=d|0;si(a,b,d)|0;c[b+52>>2]=c[a+300>>2];c[b+56>>2]=c[a+304>>2];c[b+60>>2]=c[a+308>>2];c[b+64>>2]=c[a+312>>2];c[b+68>>2]=c[a+316>>2];c[b+72>>2]=c[a+320>>2];c[b+76>>2]=c[a+324>>2];c[b+80>>2]=c[a+328>>2];c[b+84>>2]=c[a+332>>2];c[b+88>>2]=c[a+336>>2];c[b+92>>2]=c[a+340>>2];c[b+96>>2]=c[a+344>>2];c[b+100>>2]=c[a+348>>2];c[b+104>>2]=c[a+352>>2];c[b+108>>2]=c[a+356>>2];c[b+112>>2]=c[a+360>>2];c[b+116>>2]=c[a+364>>2];c[b+120>>2]=c[a+368>>2];c[b+124>>2]=c[a+372>>2];c[b+128>>2]=c[a+376>>2];c[b+132>>2]=c[a+380>>2];c[b+136>>2]=c[a+384>>2];c[b+140>>2]=c[a+388>>2];c[b+144>>2]=c[a+392>>2];c[b+148>>2]=c[a+396>>2];c[b+152>>2]=c[a+400>>2];c[b+156>>2]=c[a+404>>2];c[b+160>>2]=c[a+408>>2];c[b+164>>2]=c[a+412>>2];c[b+168>>2]=c[a+416>>2];c[b+172>>2]=c[a+420>>2];c[b+176>>2]=c[a+424>>2];c[b+180>>2]=c[a+444>>2];c[b+184>>2]=c[a+448>>2];c[b+188>>2]=c[a+452>>2];c[b+192>>2]=c[a+428>>2];c[b+196>>2]=c[a+432>>2];c[b+200>>2]=c[a+436>>2];c[b+204>>2]=c[a+440>>2];return 12727}function Th(a,b,d){a=a|0;b=b|0;d=+d;var e=0,f=0.0,h=0.0,j=0.0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0;k=i;i=i+32|0;n=+g[a+56>>2];r=+g[a+72>>2]-n;m=+g[a+60>>2];p=+g[a+76>>2]-m;l=+g[a+64>>2];s=+g[a+80>>2]-l;o=+g[a+88>>2]-n;q=+g[a+92>>2]-m;h=+g[a+96>>2]-l;j=1.0/+O(+((r*q-p*o)*(r*q-p*o)+((p*h-s*q)*(p*h-s*q)+(s*o-r*h)*(s*o-r*h))));f=j*(p*h-s*q);h=j*(s*o-r*h);j=(r*q-p*o)*j;l=j*+g[b+8>>2]+(+g[b>>2]*f+ +g[b+4>>2]*h)-(f*n+h*m+j*l);if(!(l>=-d)|!(l<=d)){a=0;i=k;return a|0}e=0;while(1){mc[c[(c[a>>2]|0)+104>>2]&127](a,e,k+16|0,k);n=+g[k+16>>2];s=+g[k>>2]-n;p=+g[k+16+4>>2];o=+g[k+4>>2]-p;m=+g[k+16+8>>2];r=+g[k+8>>2]-m;q=1.0/+O(+((h*s-f*o)*(h*s-f*o)+((j*o-h*r)*(j*o-h*r)+(f*r-j*s)*(f*r-j*s))));e=e+1|0;if((h*s-f*o)*q*+g[b+8>>2]+(+g[b>>2]*q*(j*o-h*r)+ +g[b+4>>2]*q*(f*r-j*s))-(m*(h*s-f*o)*q+(n*q*(j*o-h*r)+p*q*(f*r-j*s)))<-d){e=0;b=5;break}if((e|0)>=3){e=1;b=5;break}}if((b|0)==5){i=k;return e|0}return 0}function Uh(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,i=0,j=0;c[6435]=(c[6435]|0)+1;h=yc(55)|0;if(!h)j=0;else{c[(h+4+15&-16)+-4>>2]=h;j=h+4+15&-16}c[j>>2]=d;c[j+4>>2]=e;c[j+8>>2]=f;c[j+12>>2]=-1;c[j+16>>2]=-1;c[j+20>>2]=-1;c[j+28>>2]=-1;g[j+32>>2]=0.0;f=j;d=c[b+4>>2]|0;c[j+24>>2]=d;if((d|0)!=(c[b+8>>2]|0)){i=d;e=b+12|0;e=c[e>>2]|0;e=e+(i<<2)|0;c[e>>2]=f;i=i+1|0;c[b+4>>2]=i;return j|0}i=d|0?d<<1:1;if((d|0)>=(i|0)){i=d;e=b+12|0;e=c[e>>2]|0;e=e+(i<<2)|0;c[e>>2]=f;i=i+1|0;c[b+4>>2]=i;return j|0}if(!i)h=0;else{c[6435]=(c[6435]|0)+1;h=yc((i<<2|3)+16|0)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}d=c[b+4>>2]|0}if((d|0)>0){e=0;do{c[h+(e<<2)>>2]=c[(c[b+12>>2]|0)+(e<<2)>>2];e=e+1|0}while((e|0)!=(d|0))}e=c[b+12>>2]|0;if(e){if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);d=c[b+4>>2]|0}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=h;c[b+8>>2]=i;i=d;e=b+12|0;e=c[e>>2]|0;e=e+(i<<2)|0;c[e>>2]=f;i=i+1|0;c[b+4>>2]=i;return j|0}function Vh(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0;o=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);u=+g[a+72>>2];t=+g[a+56>>2];r=+g[a+76>>2];q=+g[a+60>>2];n=+g[a+80>>2];m=+g[a+64>>2];E=+g[b>>2];y=+N(+E);D=+g[b+4>>2];x=+N(+D);k=+g[b+8>>2];l=+N(+k);C=+g[b+16>>2];w=+N(+C);B=+g[b+20>>2];v=+N(+B);i=+g[b+24>>2];j=+N(+i);A=+g[b+32>>2];s=+N(+A);z=+g[b+36>>2];p=+N(+z);f=+g[b+40>>2];h=+N(+f);k=(u+t)*.5*E+(r+q)*.5*D+(n+m)*.5*k+ +g[b+48>>2];i=(u+t)*.5*C+(r+q)*.5*B+(n+m)*.5*i+ +g[b+52>>2];f=(u+t)*.5*A+(r+q)*.5*z+(n+m)*.5*f+ +g[b+56>>2];l=(o+(u-t)*.5)*y+(o+(r-q)*.5)*x+(o+(n-m)*.5)*l;j=(o+(u-t)*.5)*w+(o+(r-q)*.5)*v+(o+(n-m)*.5)*j;h=(o+(u-t)*.5)*s+(o+(r-q)*.5)*p+(o+(n-m)*.5)*h;g[d>>2]=k-l;g[d+4>>2]=i-j;g[d+8>>2]=f-h;g[d+12>>2]=0.0;g[e>>2]=l+k;g[e+4>>2]=j+i;g[e+8>>2]=h+f;g[e+12>>2]=0.0;return}function Wh(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0.0,j=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0,z=0;f=i;i=i+16|0;y=c[a+52>>2]|0;z=c[a+28+(((y+2|0)%3|0)<<2)>>2]|0;c[f>>2]=z;c[f+4>>2]=z;c[f+8>>2]=z;g[f+12>>2]=0.0;g[f+(y<<2)>>2]=(c[k>>2]=z,+g[k>>2])+ +g[a+28+(y<<2)>>2];l=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);h=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);o=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);l=l+ +g[f>>2];g[f>>2]=l;h=h+ +g[f+4>>2];g[f+4>>2]=h;o=o+ +g[f+8>>2];v=+N(+(+g[b>>2]));u=+N(+(+g[b+4>>2]));w=+N(+(+g[b+8>>2]));r=+N(+(+g[b+16>>2]));q=+N(+(+g[b+20>>2]));s=+N(+(+g[b+24>>2]));m=+N(+(+g[b+32>>2]));j=+N(+(+g[b+36>>2]));n=+N(+(+g[b+40>>2]));x=+g[b+48>>2];t=+g[b+52>>2];p=+g[b+56>>2];g[d>>2]=x-(o*w+(v*l+u*h));g[d+4>>2]=t-(o*s+(r*l+q*h));g[d+8>>2]=p-(o*n+(m*l+j*h));g[d+12>>2]=0.0;g[e>>2]=x+(o*w+(v*l+u*h));g[e+4>>2]=t+(o*s+(r*l+q*h));g[e+8>>2]=p+(o*n+(m*l+j*h));g[e+12>>2]=0.0;i=f;return}function Xh(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0;if(a[d+32>>0]&1){f=c[b+4>>2]|0;if(f|0)gj(f,d,e);f=c[b>>2]|0;if(f|0){n=+g[d>>2];l=+g[f+128>>2];m=+g[d+4>>2];k=+g[d+8>>2];h=+g[e+4>>2];p=+g[e+8>>2];o=+g[e>>2];j=+g[f+180>>2]*(k*h-m*p)+ +g[f+184>>2]*(n*p-k*o)+(m*o-n*h)*+g[f+188>>2];i=(k*h-m*p)*+g[f+196>>2]+(n*p-k*o)*+g[f+200>>2]+(m*o-n*h)*+g[f+204>>2];h=(k*h-m*p)*+g[f+212>>2]+(n*p-k*o)*+g[f+216>>2]+(m*o-n*h)*+g[f+220>>2];g[f+244>>2]=n*l+ +g[f+244>>2];g[f+248>>2]=l*m+ +g[f+248>>2];g[f+252>>2]=l*k+ +g[f+252>>2];g[f+316>>2]=n*l+ +g[f+316>>2];g[f+320>>2]=l*m+ +g[f+320>>2];g[f+324>>2]=l*k+ +g[f+324>>2];g[f+260>>2]=j+ +g[f+260>>2];g[f+264>>2]=i+ +g[f+264>>2];g[f+268>>2]=h+ +g[f+268>>2];g[f+332>>2]=j+ +g[f+332>>2];g[f+336>>2]=i+ +g[f+336>>2];g[f+340>>2]=h+ +g[f+340>>2];c[f+308>>2]=(c[f+308>>2]|0)+1}}if(!(a[d+32>>0]&2))return;jj(b,d+16|0,e);return}function Yh(a){a=a|0;var b=0,d=0,e=0,f=0;d=i;i=i+16|0;li(15122);Ab[c[(c[a>>2]|0)+8>>2]&255](a);Ab[c[(c[a>>2]|0)+12>>2]&255](a);b=c[a+24>>2]|0;li(15156);if(b|0){f=c[(c[b>>2]|0)+32>>2]|0;e=c[a+68>>2]|0;e=Eb[c[(c[e>>2]|0)+36>>2]&127](e)|0;mc[f&127](b,e,a+28|0,c[a+24>>2]|0)}a=c[2357]|0;f=(c[a+16>>2]|0)+-1|0;c[a+16>>2]=f;do if(!f){if(c[a+4>>2]|0){tb(d|0,0)|0;b=c[6434]|0;g[a+8>>2]=+g[a+8>>2]+ +(((c[d+4>>2]|0)-(c[b+4>>2]|0)+(((c[d>>2]|0)-(c[b>>2]|0)|0)*1e6|0)-(c[a+12>>2]|0)|0)>>>0)/1.0e3;b=c[2357]|0;if(c[a+16>>2]|0)break}else b=a;b=c[b+20>>2]|0;c[2357]=b}else b=a;while(0);a=b+16|0;f=(c[a>>2]|0)+-1|0;c[a>>2]=f;if(f|0){i=d;return}do if(c[b+4>>2]|0){tb(d|0,0)|0;e=c[6434]|0;f=b+8|0;g[f>>2]=+g[f>>2]+ +(((c[d+4>>2]|0)-(c[e+4>>2]|0)+(((c[d>>2]|0)-(c[e>>2]|0)|0)*1e6|0)-(c[b+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[a>>2]|0)){b=c[2357]|0;break}else{i=d;return}}while(0);c[2357]=c[b+20>>2];i=d;return}function Zh(b,d){b=b|0;d=d|0;var e=0;c[b>>2]=8840;a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;c[b+12>>2]=-1;c[b+16>>2]=0;c[b+20>>2]=0;a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;a[b+120>>0]=1;c[b+116>>2]=0;c[b+108>>2]=0;c[b+112>>2]=0;c[b+64>>2]=0;c[b+68>>2]=0;c[b+72>>2]=-1;c[b+76>>2]=0;c[b+80>>2]=0;a[b+193>>0]=0;a[b+194>>0]=1;a[b+192>>0]=(d|0)!=0^1;g[b+140>>2]=0.0;c[b+144>>2]=0;c[b+164>>2]=0;c[b+148>>2]=1;c[b+152>>2]=0;c[b+156>>2]=10;c[b+160>>2]=1;c[b+168>>2]=0;c[b+172>>2]=0;g[b+176>>2]=0.0;if(d|0){e=d;d=b+136|0;c[d>>2]=e;d=b+188|0;c[d>>2]=0;d=b+180|0;c[d>>2]=0;d=b+184|0;c[d>>2]=0;b=b+124|0;c[b>>2]=0;c[b+4>>2]=0;c[b+8>>2]=0;return}c[6435]=(c[6435]|0)+1;d=yc(95)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}Ri(d);e=b+136|0;c[e>>2]=d;e=b+188|0;c[e>>2]=0;e=b+180|0;c[e>>2]=0;e=b+184|0;c[e>>2]=0;e=b+124|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;return}function _h(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0,j=0.0,k=0.0;i=c[b>>2]|0;if((i|0)==(c[a+80>>2]|0)){k=1.0;return +k}if(c[i+204>>2]&4|0){k=1.0;return +k}h=+g[b+8>>2];f=+g[b+12>>2];e=+g[b+16>>2];if(d){j=h;k=f}else{j=+g[i+4>>2]*h+ +g[i+8>>2]*f+ +g[i+12>>2]*e;k=h*+g[i+20>>2]+f*+g[i+24>>2]+e*+g[i+28>>2];e=h*+g[i+36>>2]+f*+g[i+40>>2]+e*+g[i+44>>2]}if(j*+g[a+84>>2]+k*+g[a+88>>2]+e*+g[a+92>>2]<+g[a+100>>2]){k=1.0;return +k}c[a+4>>2]=c[b+40>>2];c[a+76>>2]=i;if(d){c[a+44>>2]=c[b+8>>2];c[a+44+4>>2]=c[b+8+4>>2];c[a+44+8>>2]=c[b+8+8>>2];c[a+44+12>>2]=c[b+8+12>>2]}else{e=+g[b+8>>2];f=+g[b+12>>2];h=+g[b+16>>2];j=e*+g[i+20>>2]+f*+g[i+24>>2]+h*+g[i+28>>2];k=e*+g[i+36>>2]+f*+g[i+40>>2]+h*+g[i+44>>2];g[a+44>>2]=+g[i+4>>2]*e+ +g[i+8>>2]*f+ +g[i+12>>2]*h;g[a+48>>2]=j;g[a+52>>2]=k;g[a+56>>2]=0.0}c[a+60>>2]=c[b+24>>2];c[a+60+4>>2]=c[b+24+4>>2];c[a+60+8>>2]=c[b+24+8>>2];c[a+60+12>>2]=c[b+24+12>>2];k=+g[b+40>>2];return +k}function $h(b){b=b|0;var d=0,e=0,f=0,g=0,h=0;d=c[b+16>>2]|0;if(d|0){if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0}a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;d=c[b+40>>2]|0;if(d|0){if(a[b+44>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+40>>2]=0}a[b+44>>0]=1;c[b+40>>2]=0;c[b+32>>2]=0;c[b+36>>2]=0;d=c[b+60>>2]|0;if(d|0){if(a[b+64>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+60>>2]=0}a[b+64>>0]=1;c[b+60>>2]=0;c[b+52>>2]=0;c[b+56>>2]=0;if((c[b+12>>2]|0)>=2){Kf(b);return}c[6435]=(c[6435]|0)+1;d=yc(43)|0;if(!d)f=0;else{c[(d+4+15&-16)+-4>>2]=d;f=d+4+15&-16}d=c[b+8>>2]|0;if((d|0)>0){e=0;do{g=f+(e*12|0)|0;h=(c[b+16>>2]|0)+(e*12|0)|0;c[g>>2]=c[h>>2];c[g+4>>2]=c[h+4>>2];c[g+8>>2]=c[h+8>>2];e=e+1|0}while((e|0)!=(d|0))}d=c[b+16>>2]|0;if(d|0){if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0}a[b+20>>0]=1;c[b+16>>2]=f;c[b+12>>2]=2;Kf(b);return}function ai(a,b,e){a=a|0;b=b|0;e=e|0;si(a,b,e)|0;c[b+52>>2]=c[a+52>>2];c[b+56>>2]=c[a+56>>2];c[b+60>>2]=c[a+60>>2];c[b+64>>2]=c[a+64>>2];c[b+68>>2]=c[a+68>>2];c[b+72>>2]=c[a+72>>2];c[b+76>>2]=c[a+76>>2];c[b+80>>2]=c[a+80>>2];c[b+84>>2]=c[a+84>>2];c[b+88>>2]=c[a+88>>2];c[b+92>>2]=c[a+92>>2];c[b+96>>2]=c[a+96>>2];c[b+100>>2]=c[a+100>>2];c[b+104>>2]=c[a+104>>2];c[b+108>>2]=c[a+108>>2];c[b+112>>2]=c[a+112>>2];c[b+116>>2]=c[a+116>>2];c[b+120>>2]=c[a+120>>2];c[b+124>>2]=c[a+124>>2];c[b+128>>2]=c[a+128>>2];c[b+132>>2]=c[a+132>>2];c[b+136>>2]=c[a+136>>2];c[b+140>>2]=c[a+140>>2];c[b+144>>2]=c[a+144>>2];c[b+148>>2]=c[a+148>>2];c[b+152>>2]=c[a+152>>2];c[b+156>>2]=c[a+156>>2];c[b+160>>2]=c[a+160>>2];c[b+164>>2]=c[a+164>>2];c[b+168>>2]=c[a+168>>2];c[b+172>>2]=c[a+172>>2];c[b+176>>2]=c[a+176>>2];c[b+180>>2]=c[a+188>>2];c[b+184>>2]=c[a+184>>2];c[b+188>>2]=c[a+196>>2];c[b+192>>2]=c[a+192>>2];c[b+196>>2]=d[a+180>>0];c[b+200>>2]=d[a+49>>0];return 12680}function bi(a,b){a=a|0;b=b|0;var d=0,e=0,f=0.0;e=i;i=i+32|0;d=c[b+388>>2]|0;switch(c[a+388>>2]&48&d|0){case 32:{if((a|0)==(b|0)&(d&64|0)==0){i=e;return}g[e+4>>2]=1.0;c[e+8>>2]=0;c[e+8+4>>2]=0;c[e+8+8>>2]=0;c[e+8+12>>2]=0;c[e>>2]=3540;c[e+8>>2]=c[a+456>>2];d=c[a+192>>2]|0;f=+Sb[c[(c[d>>2]|0)+48>>2]&15](d);d=c[b+192>>2]|0;g[e+12>>2]=f+ +Sb[c[(c[d>>2]|0)+48>>2]&15](d);c[e+16>>2]=c[(+g[a+316>>2]<+g[b+316>>2]?a+316|0:b+316|0)>>2];c[e+24>>2]=a;c[e+28>>2]=b;We(c[a+1048>>2]|0,c[b+1048>>2]|0,e);i=e;return}case 16:{if((a|0)==(b|0)){i=e;return}c[e>>2]=3576;d=c[a+192>>2]|0;f=+Sb[c[(c[d>>2]|0)+48>>2]&15](d);d=c[b+192>>2]|0;g[e+12>>2]=f+ +Sb[c[(c[d>>2]|0)+48>>2]&15](d);c[e+4>>2]=a;c[e+8>>2]=b;We(c[a+928>>2]|0,c[b+988>>2]|0,e);c[e+4>>2]=b;c[e+8>>2]=a;We(c[b+928>>2]|0,c[a+988>>2]|0,e);i=e;return}default:{i=e;return}}}function ci(a,d,e,f){a=a|0;d=d|0;e=e|0;f=f|0;var h=0,j=0.0,k=0.0,l=0.0,m=0.0;h=i;i=i+96|0;g[h+4>>2]=1.0;c[h+8>>2]=0;b[h+12>>1]=1;b[h+14>>1]=-1;c[h+16>>2]=0;c[h>>2]=2948;c[h+20>>2]=c[d>>2];c[h+20+4>>2]=c[d+4>>2];c[h+20+8>>2]=c[d+8>>2];c[h+20+12>>2]=c[d+12>>2];c[h+36>>2]=c[e>>2];c[h+36+4>>2]=c[e+4>>2];c[h+36+8>>2]=c[e+8>>2];c[h+36+12>>2]=c[e+12>>2];a=c[a+4>>2]|0;mc[c[(c[a>>2]|0)+32>>2]&127](a,d,e,h);d=c[h+8>>2]|0;if(!d){f=0;i=h;return f|0}if(!(c[d+236>>2]&2)){f=0;i=h;return f|0}if(c[d+204>>2]&4|0){f=0;i=h;return f|0}c[f>>2]=c[h+68>>2];c[f+4>>2]=c[h+68+4>>2];c[f+8>>2]=c[h+68+8>>2];c[f+12>>2]=c[h+68+12>>2];c[f+16>>2]=c[h+52>>2];c[f+16+4>>2]=c[h+52+4>>2];c[f+16+8>>2]=c[h+52+8>>2];c[f+16+12>>2]=c[h+52+12>>2];m=+g[f+16>>2];l=+g[f+20>>2];k=+g[f+24>>2];j=1.0/+O(+(m*m+l*l+k*k));g[f+16>>2]=m*j;g[f+20>>2]=l*j;g[f+24>>2]=k*j;c[f+32>>2]=c[h+4>>2];f=d;i=h;return f|0}function di(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0;e=b+288|0;f=d;g=e+104|0;do{c[e>>2]=c[f>>2];e=e+4|0;f=f+4|0}while((e|0)<(g|0));i=c[d+108>>2]|0;e=c[b+396>>2]|0;a:do if((e|0)>(i|0))e=b+404|0;else{if((e|0)<(i|0)?(c[b+400>>2]|0)<(i|0):0){if((i|0)!=0?(c[6435]=(c[6435]|0)+1,h=yc((i<<2|3)+16|0)|0,(h|0)!=0):0){c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}else h=0;f=c[b+396>>2]|0;g=0;while(1){if((g|0)>=(f|0))break;c[h+(g<<2)>>2]=c[(c[b+404>>2]|0)+(g<<2)>>2];g=g+1|0}f=c[b+404>>2]|0;if(f|0){if(!((a[b+408>>0]&1)==0|(f|0)==0)){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+404>>2]=0}a[b+408>>0]=1;c[b+404>>2]=h;c[b+400>>2]=i}while(1){if((e|0)>=(i|0)){e=b+404|0;break a}c[(c[b+404>>2]|0)+(e<<2)>>2]=0;e=e+1|0}}while(0);c[b+396>>2]=i;e=c[e>>2]|0;f=0;while(1){if((f|0)>=(i|0))break;c[e+(f<<2)>>2]=c[(c[d+116>>2]|0)+(f<<2)>>2];f=f+1|0}Yi(b+412|0,d+124|0);Yi(b+432|0,d+144|0);return}function ei(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0;Ab[c[(c[b>>2]|0)+32>>2]&255](b);d=Ob[c[(c[b>>2]|0)+16>>2]&63](b,104,1)|0;e=c[d+8>>2]|0;f=e;g=f+104|0;do{c[f>>2]=0;f=f+4|0}while((f|0)<(g|0));c[e+88>>2]=c[a+248>>2];c[e+92>>2]=c[a+252>>2];c[e+96>>2]=c[a+256>>2];c[e+100>>2]=c[a+260>>2];c[e>>2]=c[a+92>>2];c[e+4>>2]=c[a+96>>2];c[e+8>>2]=c[a+100>>2];c[e+12>>2]=c[a+104>>2];c[e+16>>2]=c[a+108>>2];c[e+20>>2]=c[a+116>>2];c[e+24>>2]=c[a+120>>2];c[e+28>>2]=c[a+124>>2];c[e+32>>2]=c[a+128>>2];c[e+36>>2]=c[a+132>>2];c[e+40>>2]=c[a+140>>2];c[e+44>>2]=c[a+144>>2];c[e+48>>2]=c[a+148>>2];c[e+52>>2]=c[a+152>>2];c[e+56>>2]=c[a+168>>2];c[e+60>>2]=c[a+172>>2];c[e+64>>2]=c[a+112>>2];c[e+68>>2]=c[a+156>>2];c[e+72>>2]=c[a+160>>2];c[e+76>>2]=c[a+164>>2];c[e+80>>2]=c[a+136>>2];yb[c[(c[b>>2]|0)+20>>2]&31](b,d,11938,1145853764,e);mj(a,b);td(a,b);Ab[c[(c[b>>2]|0)+36>>2]&255](b);return}function fi(b,d){b=b|0;d=d|0;if((c[b+16>>2]|0)!=(0-(c[b+76>>2]|0)|0))return;d=c[b+4>>2]|0;if(d|0)xn(b+4|0,d);d=c[b+8>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+8>>2]=0;c[b+12>>2]=-1;d=c[b+36>>2]|0;if(d|0){if(a[b+40>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+36>>2]=0}a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;c[b+20>>2]=0;d=c[b+64>>2]|0;if(d|0)xn(b+64|0,d);d=c[b+68>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+68>>2]=0;c[b+72>>2]=-1;d=c[b+96>>2]|0;if(d|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;c[b+80>>2]=0;a[b+193>>0]=0;a[b+194>>0]=1;c[b+144>>2]=0;c[b+164>>2]=0;c[b+148>>2]=1;c[b+152>>2]=0;c[b+156>>2]=10;c[b+160>>2]=1;c[b+124>>2]=0;c[b+124+4>>2]=0;c[b+124+8>>2]=0;c[b+168>>2]=0;c[b+168+4>>2]=0;c[b+168+8>>2]=0;c[b+168+12>>2]=0;c[b+168+16>>2]=0;c[b+168+20>>2]=0;return}function gi(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,j=0,k=0.0;j=i;i=i+32|0;c[j+16>>2]=c[d>>2];c[j+16+4>>2]=c[d+4>>2];c[j+16+8>>2]=c[d+8>>2];c[j+16+12>>2]=c[d+12>>2];e=+g[j+16>>2];h=+g[j+16+4>>2];f=+g[j+16+8>>2];if(e*e+h*h+f*f<1.4210854715202004e-14){c[j+16>>2]=-1082130432;c[j+16+4>>2]=-1082130432;c[j+16+8>>2]=-1082130432;g[j+16+12>>2]=0.0;e=-1.0;h=-1.0;f=-1.0}k=1.0/+O(+(e*e+h*h+f*f));g[j+16>>2]=e*k;g[j+16+4>>2]=h*k;g[j+16+8>>2]=f*k;Gd(j,b,j+16|0);switch(c[b+4>>2]|0){case 8:{e=+g[b+28>>2]*+g[b+12>>2];break}case 0:{e=+g[b+44>>2];break}case 1:{e=+g[b+44>>2];break}case 13:{e=+g[b+44>>2];break}case 11:{e=+g[b+44>>2];break}case 10:{e=+g[b+44>>2];break}case 4:case 5:{e=+g[b+44>>2];break}default:e=+Sb[c[(c[b>>2]|0)+48>>2]&15](b)}h=e*+g[j+16+4>>2]+ +g[j+4>>2];k=e*+g[j+16+8>>2]+ +g[j+8>>2];g[a>>2]=e*+g[j+16>>2]+ +g[j>>2];g[a+4>>2]=h;g[a+8>>2]=k;g[a+12>>2]=0.0;i=j;return}function hi(a,b){a=a|0;b=b|0;var d=0.0,e=0,f=0.0,h=0.0,i=0.0,j=0.0;c[a+4>>2]=35;c[a+8>>2]=0;c[a+12>>2]=1065353216;c[a+16>>2]=1065353216;c[a+20>>2]=1065353216;g[a+24>>2]=0.0;g[a+44>>2]=.03999999910593033;c[a>>2]=8140;c[a+52>>2]=1;h=+g[b>>2];f=+g[b+4>>2];d=+g[b+8>>2];d=+g[b+((h>2]*.10000000149011612;if(d<.03999999910593033){j=+xz(a);i=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);h=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);j=j+ +g[a+28>>2];i=i+ +g[a+32>>2];h=h+ +g[a+36>>2];g[a+44>>2]=d;d=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);f=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);h=h-+Sb[c[(c[a>>2]|0)+48>>2]&15](a);g[a+28>>2]=j-d;g[a+32>>2]=i-f;g[a+36>>2]=h;g[a+40>>2]=0.0;e=c[a>>2]|0}else e=8140;h=+Sb[c[e+48>>2]&15](a);i=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);j=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);i=+g[b+4>>2]*+g[a+16>>2]-i;j=+g[b+8>>2]*+g[a+20>>2]-j;g[a+28>>2]=+g[b>>2]*+g[a+12>>2]-h;g[a+32>>2]=i;g[a+36>>2]=j;g[a+40>>2]=0.0;c[a+4>>2]=13;return}function ii(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,j=0,l=0,m=0,n=0,o=0.0;m=i;i=i+80|0;c[a>>2]=0;c[a+4>>2]=0;c[a+8>>2]=0;c[a+12>>2]=0;e=+g[d>>2];f=+g[d+4>>2];h=+g[d+8>>2];if(e*e+f*f+h*h<9.999999747378752e-05){l=1065353216;j=0;e=0.0;d=0}else{o=1.0/+O(+(e*e+f*f+h*h));l=(g[k>>2]=e*o,c[k>>2]|0);n=(g[k>>2]=f*o,c[k>>2]|0);j=(g[k>>2]=h*o,c[k>>2]|0);e=+g[d+12>>2];d=n}c[m+32>>2]=7824;n=m+32+4|0;c[n>>2]=0;c[n+4>>2]=0;c[n+8>>2]=0;c[n+12>>2]=0;g[m+32+20>>2]=-999999984306749440.0;c[m+32+24>>2]=l;c[m+32+28>>2]=d;c[m+32+32>>2]=j;g[m+32+36>>2]=e;c[m+16>>2]=1566444395;c[m+16+4>>2]=1566444395;c[m+16+8>>2]=1566444395;g[m+16+12>>2]=0.0;b=c[b+92>>2]|0;l=c[(c[b>>2]|0)+8>>2]|0;g[m>>2]=-999999984306749440.0;g[m+4>>2]=-999999984306749440.0;g[m+8>>2]=-999999984306749440.0;g[m+12>>2]=0.0;mc[l&127](b,m+32|0,m,m+16|0);c[a>>2]=c[n>>2];c[a+4>>2]=c[n+4>>2];c[a+8>>2]=c[n+8>>2];c[a+12>>2]=c[n+12>>2];i=m;return}function ji(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0,h=0.0,i=0,j=0.0,k=0.0,l=0,m=0.0;e=+g[b+60>>2]*.5;l=c[b+68>>2]|0;h=+g[d>>2];j=+g[d+4>>2];k=+g[d+8>>2];k=+O(+(h*h+j*j+k*k));f=c[b+64>>2]|0;do if(!(+g[d+(l<<2)>>2]>k*+g[b+52>>2])){h=+g[d+(f<<2)>>2];i=c[b+72>>2]|0;j=+g[d+(i<<2)>>2];k=+O(+(h*h+j*j));if(k>1.1920928955078125e-07){k=+g[b+56>>2]/k;g[a+(f<<2)>>2]=h*k;g[a+(l<<2)>>2]=-e;g[a+(i<<2)>>2]=j*k;break}else{g[a+(f<<2)>>2]=0.0;g[a+(l<<2)>>2]=-e;g[a+(i<<2)>>2]=0.0;break}}else{g[a+(f<<2)>>2]=0.0;g[a+(l<<2)>>2]=e;g[a+(c[b+72>>2]<<2)>>2]=0.0}while(0);if(!(+Sb[c[(c[b>>2]|0)+48>>2]&15](b)!=0.0))return;h=+g[d>>2];j=+g[d+4>>2];k=+g[d+8>>2];m=h*h+j*j+k*k<1.4210854715202004e-14?-1.0:h;e=h*h+j*j+k*k<1.4210854715202004e-14?-1.0:j;k=h*h+j*j+k*k<1.4210854715202004e-14?-1.0:k;j=1.0/+O(+(k*k+(m*m+e*e)));h=+Sb[c[(c[b>>2]|0)+48>>2]&15](b);g[a>>2]=+g[a>>2]+h*j*m;g[a+4>>2]=h*j*e+ +g[a+4>>2];g[a+8>>2]=h*j*k+ +g[a+8>>2];return}function ki(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0;e=Zb[c[(c[d>>2]|0)+40>>2]&31](d,a)|0;g=Zb[c[(c[d>>2]|0)+28>>2]&31](d,e)|0;c[b>>2]=g;if(g|0)Cb[c[(c[d>>2]|0)+48>>2]&127](d,e);c[b+4>>2]=c[a+4>>2];c[b+28>>2]=c[a+28>>2];c[b+32>>2]=c[a+32>>2];c[b+36>>2]=c[a+36>>2];c[b+40>>2]=c[a+40>>2];c[b+12>>2]=c[a+12>>2];c[b+16>>2]=c[a+16>>2];c[b+20>>2]=c[a+20>>2];c[b+24>>2]=c[a+24>>2];c[b+44>>2]=c[a+44>>2];f=c[a+96>>2]|0;c[b+60>>2]=f;if(!f){c[b+52>>2]=0;c[b+56>>2]=0;return 17310}c[b+52>>2]=Zb[c[(c[d>>2]|0)+28>>2]&31](d,c[a+104>>2]|0)|0;c[b+56>>2]=0;g=Ob[c[(c[d>>2]|0)+16>>2]&63](d,16,f)|0;if((f|0)>0){e=c[a+104>>2]|0;b=0;a=c[g+8>>2]|0;while(1){c[a>>2]=c[e+(b<<4)>>2];c[a+4>>2]=c[e+(b<<4)+4>>2];c[a+8>>2]=c[e+(b<<4)+8>>2];c[a+12>>2]=c[e+(b<<4)+12>>2];b=b+1|0;if((b|0)==(f|0))break;else a=a+16|0}}else e=c[a+104>>2]|0;yb[c[(c[d>>2]|0)+20>>2]&31](d,g,19308,1497453121,e);return 17310}function li(a){a=a|0;var b=0,d=0,e=0,f=0;f=i;i=i+16|0;d=c[2357]|0;if((c[d>>2]|0)==(a|0))b=d;else{b=c[d+24>>2]|0;a:do if(!b)e=5;else while(1){if((c[b>>2]|0)==(a|0))break a;b=c[b+28>>2]|0;if(!b){e=5;break}}while(0);do if((e|0)==5){while(1){b=yc(36)|0;if(b|0){e=9;break}b=c[6564]|0;c[6564]=b+0;if(!b){e=8;break}jc[b&3]();e=5}if((e|0)==8){f=Ya(4)|0;c[f>>2]=9640;pb(f|0,2800,251)}else if((e|0)==9){c[b>>2]=a;c[b+4>>2]=0;c[b+4+4>>2]=0;c[b+4+8>>2]=0;c[b+4+12>>2]=0;c[b+20>>2]=d;c[b+24>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;Vq(b);c[b+28>>2]=c[d+24>>2];c[d+24>>2]=b;break}}while(0);c[2357]=b}a=b+4|0;c[a>>2]=(c[a>>2]|0)+1;a=b+16|0;e=c[a>>2]|0;c[a>>2]=e+1;if(e|0){i=f;return}tb(f|0,0)|0;e=c[6434]|0;c[b+12>>2]=(c[f+4>>2]|0)-(c[e+4>>2]|0)+(((c[f>>2]|0)-(c[e>>2]|0)|0)*1e6|0);i=f;return}function mi(a,b,d){a=a|0;b=b|0;d=d|0;c[a+300>>2]=c[b>>2];c[a+300+4>>2]=c[b+4>>2];c[a+300+8>>2]=c[b+8>>2];c[a+300+12>>2]=c[b+12>>2];c[a+316>>2]=c[b+16>>2];c[a+316+4>>2]=c[b+16+4>>2];c[a+316+8>>2]=c[b+16+8>>2];c[a+316+12>>2]=c[b+16+12>>2];c[a+332>>2]=c[b+32>>2];c[a+332+4>>2]=c[b+32+4>>2];c[a+332+8>>2]=c[b+32+8>>2];c[a+332+12>>2]=c[b+32+12>>2];c[a+348>>2]=c[b+48>>2];c[a+348+4>>2]=c[b+48+4>>2];c[a+348+8>>2]=c[b+48+8>>2];c[a+348+12>>2]=c[b+48+12>>2];c[a+364>>2]=c[d>>2];c[a+364+4>>2]=c[d+4>>2];c[a+364+8>>2]=c[d+8>>2];c[a+364+12>>2]=c[d+12>>2];c[a+380>>2]=c[d+16>>2];c[a+380+4>>2]=c[d+16+4>>2];c[a+380+8>>2]=c[d+16+8>>2];c[a+380+12>>2]=c[d+16+12>>2];c[a+396>>2]=c[d+32>>2];c[a+396+4>>2]=c[d+32+4>>2];c[a+396+8>>2]=c[d+32+8>>2];c[a+396+12>>2]=c[d+32+12>>2];c[a+412>>2]=c[d+48>>2];c[a+412+4>>2]=c[d+48+4>>2];c[a+412+8>>2]=c[d+48+8>>2];c[a+412+12>>2]=c[d+48+12>>2];Ab[c[(c[a>>2]|0)+8>>2]&255](a);return}function ni(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0,n=0.0;m=c[a+4>>2]|0;a=c[a+64>>2]|0;do if(!m)if(!a){e=0.0;n=0.0;j=0.0;l=0.0;h=0.0;k=0.0;i=0.0;f=0.0}else{e=+g[a>>2];n=+g[a+12>>2];j=+g[a+16>>2];l=+g[a+20>>2];h=+g[a+24>>2];k=+g[a+28>>2];i=+g[a+4>>2];f=+g[a+8>>2]}else{e=+g[m>>2];if(!a){n=+g[m+12>>2];j=+g[m+16>>2];l=+g[m+20>>2];h=+g[m+24>>2];k=+g[m+28>>2];i=+g[m+4>>2];f=+g[m+8>>2];break}k=+g[a>>2];e=e>2];j=+g[a+16>>2];j=k>j?k:j;k=+g[m+4>>2];i=+g[a+4>>2];i=k>2];l=+g[a+20>>2];l=k>l?k:l;k=+g[m+8>>2];f=+g[a+8>>2];f=k>2];h=+g[a+24>>2];if(k>h){n=0.0;h=k;k=0.0}else{n=0.0;k=0.0}}while(0);g[b>>2]=e;g[b+4>>2]=i;g[b+8>>2]=f;g[b+12>>2]=n;g[d>>2]=j;g[d+4>>2]=l;g[d+8>>2]=h;g[d+12>>2]=k;return}function oi(a,b){a=a|0;b=b|0;var c=0,d=0.0,e=0.0,f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0;c=i;i=i+48|0;Wg(a+364|0,c+16|0);h=-+g[c+16>>2];e=-+g[c+16+4>>2];m=-+g[c+16+8>>2];l=+g[c+16+12>>2];f=+g[b>>2];n=+g[b+12>>2];k=+g[b+8>>2];j=+g[b+4>>2];Wg(a+300|0,c);p=+g[c>>2];q=+g[c+12>>2];d=+g[c+8>>2];o=+g[c+4>>2];g[c+32>>2]=p*(l*n-f*h-j*e-k*m)+(l*f+n*h+k*e-j*m)*q+(f*m+(n*e+l*j)-k*h)*d-(n*m+l*k+j*h-f*e)*o;g[c+32+4>>2]=p*(n*m+l*k+j*h-f*e)+(q*(f*m+(n*e+l*j)-k*h)+(l*n-f*h-j*e-k*m)*o)-(l*f+n*h+k*e-j*m)*d;g[c+32+8>>2]=q*(n*m+l*k+j*h-f*e)+(l*n-f*h-j*e-k*m)*d+(l*f+n*h+k*e-j*m)*o-p*(f*m+(n*e+l*j)-k*h);g[c+32+12>>2]=(l*n-f*h-j*e-k*m)*q-p*(l*f+n*h+k*e-j*m)-(f*m+(n*e+l*j)-k*h)*o-(n*m+l*k+j*h-f*e)*d;Yd(a,c+32|0);i=c;return}function pi(b){b=b|0;var d=0;d=c[b>>2]|0;if(d|0)xn(b,d);d=c[b+4>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+4>>2]=0;c[b+8>>2]=-1;d=c[b+32>>2]|0;if(d|0){if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+32>>2]=0}a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;c[b+16>>2]=0;d=c[b+52>>2]|0;if(!d){a[b+56>>0]=1;c[b+52>>2]=0;c[b+44>>2]=0;c[b+48>>2]=0;a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;return}if(!(a[b+56>>0]|0)){a[b+56>>0]=1;c[b+52>>2]=0;c[b+44>>2]=0;c[b+48>>2]=0;a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;return}c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);d=c[b+32>>2]|0;a[b+56>>0]=1;c[b+52>>2]=0;c[b+44>>2]=0;c[b+48>>2]=0;if(!d){a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;return}if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+32>>2]=0;a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;return}function qi(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0;if(!e)e=c[b+188>>2]|0;j=c[d>>2]|0;f=c[b+268>>2]|0;a:do if((f|0)>0){h=c[b+276>>2]|0;g=0;while(1){if((c[h+(g<<2)>>2]|0)==(j|0))break;g=g+1|0;if((g|0)>=(f|0))break a}if((g|0)!=(f|0))return}while(0);if((f|0)==(c[b+272>>2]|0)?(i=f|0?f<<1:1,(f|0)<(i|0)):0){if(!i)h=0;else{c[6435]=(c[6435]|0)+1;f=yc((i<<2|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}h=f;f=c[b+268>>2]|0}if((f|0)>0){g=0;do{c[h+(g<<2)>>2]=c[(c[b+276>>2]|0)+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0))}g=c[b+276>>2]|0;if(g){if(a[b+280>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0);f=c[b+268>>2]|0}c[b+276>>2]=0}a[b+280>>0]=1;c[b+276>>2]=h;c[b+272>>2]=i}c[(c[b+276>>2]|0)+(f<<2)>>2]=j;c[b+268>>2]=f+1;b=c[b+284>>2]|0;Ob[c[(c[b>>2]|0)+8>>2]&63](b,e,d)|0;return}function ri(b){b=b|0;var d=0;if((a[22496]|0)==0?Wa(22496)|0:0){if((a[22456]|0)==0?Wa(22456)|0:0){if((a[22464]|0)==0?Wa(22464)|0:0){c[5698]=1065353216;c[5699]=0;c[5700]=0;c[5701]=0;c[5702]=0;c[5703]=1065353216;c[5704]=0;c[5705]=0;c[5706]=0;c[5707]=0;c[5708]=1065353216;g[5709]=0.0;_a(22464)}c[5710]=c[5698];c[5711]=c[5699];c[5712]=c[5700];c[5713]=c[5701];c[5714]=c[5702];c[5715]=c[5703];c[5716]=c[5704];c[5717]=c[5705];c[5718]=c[5706];c[5719]=c[5707];c[5720]=c[5708];c[5721]=c[5709];c[5722]=0;c[5723]=0;c[5724]=0;c[5725]=0;_a(22456)}c[5755]=c[5710];c[5756]=c[5711];c[5757]=c[5712];c[5758]=c[5713];c[5759]=c[5714];c[5760]=c[5715];c[5761]=c[5716];c[5762]=c[5717];c[5763]=c[5718];c[5764]=c[5719];c[5765]=c[5720];c[5766]=c[5721];c[5767]=c[5722];c[5768]=c[5723];c[5769]=c[5724];c[5770]=c[5725];_a(22496)}d=c[b+8>>2]|0;if(!d){b=c[b>>2]|0;return ((b|0)==0?23020:b+60|0)|0}else return d+4|0;return 0}function si(a,b,e){a=a|0;b=b|0;e=e|0;var f=0,g=0;c[b>>2]=Zb[c[(c[e>>2]|0)+28>>2]&31](e,c[a+28>>2]|0)|0;c[b+4>>2]=Zb[c[(c[e>>2]|0)+28>>2]&31](e,c[a+32>>2]|0)|0;f=Zb[c[(c[e>>2]|0)+40>>2]&31](e,a)|0;g=Zb[c[(c[e>>2]|0)+28>>2]&31](e,f)|0;c[b+8>>2]=g;if(g|0)Cb[c[(c[e>>2]|0)+48>>2]&127](e,f);c[b+12>>2]=c[a+4>>2];c[b+24>>2]=d[a+21>>0];c[b+40>>2]=c[a+24>>2];c[b+44>>2]=c[a+16>>2];c[b+48>>2]=d[a+20>>0];c[b+20>>2]=c[a+12>>2];c[b+16>>2]=c[a+8>>2];c[b+28>>2]=c[a+36>>2];c[b+32>>2]=c[a+40>>2];c[b+36>>2]=0;f=c[a+28>>2]|0;if((c[f+488>>2]|0)>0){e=0;do{if((c[(c[f+496>>2]|0)+(e<<2)>>2]|0)==(a|0)){c[b+36>>2]=1;f=c[a+28>>2]|0}e=e+1|0}while((e|0)<(c[f+488>>2]|0))}f=c[a+32>>2]|0;if((c[f+488>>2]|0)>0)e=0;else return 12632;do{if((c[(c[f+496>>2]|0)+(e<<2)>>2]|0)==(a|0)){c[b+36>>2]=1;f=c[a+32>>2]|0}e=e+1|0}while((e|0)<(c[f+488>>2]|0));return 12632}function ti(b,d,e,f){b=+b;d=d|0;e=e|0;f=f|0;var h=0,i=0;while(1){h=yc(140)|0;if(h|0){i=6;break}h=c[6564]|0;c[6564]=h+0;if(!h){i=5;break}jc[h&3]()}if((i|0)==5){f=Ya(4)|0;c[f>>2]=9640;pb(f|0,2800,251)}else if((i|0)==6){g[h>>2]=b;c[h+4>>2]=d;c[h+72>>2]=e;c[h+76>>2]=c[f>>2];c[h+76+4>>2]=c[f+4>>2];c[h+76+8>>2]=c[f+8>>2];c[h+76+12>>2]=c[f+12>>2];g[h+92>>2]=0.0;g[h+96>>2]=0.0;g[h+100>>2]=.5;g[h+104>>2]=0.0;g[h+108>>2]=0.0;g[h+112>>2]=.800000011920929;g[h+116>>2]=1.0;a[h+120>>0]=0;g[h+124>>2]=.004999999888241291;g[h+128>>2]=.009999999776482582;g[h+132>>2]=.009999999776482582;g[h+136>>2]=.009999999776482582;c[h+8>>2]=1065353216;c[h+12>>2]=0;c[h+12+4>>2]=0;c[h+12+8>>2]=0;c[h+12+12>>2]=0;c[h+28>>2]=1065353216;c[h+32>>2]=0;c[h+32+4>>2]=0;c[h+32+8>>2]=0;c[h+32+12>>2]=0;c[h+48>>2]=1065353216;c[h+52>>2]=0;c[h+52+4>>2]=0;c[h+52+8>>2]=0;c[h+52+12>>2]=0;c[h+52+16>>2]=0;return h|0}return 0}function ui(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0;if(Eb[c[(c[d>>2]|0)+16>>2]&127](d)|0)return;j=c[b+712>>2]|0;i=Eb[c[(c[d>>2]|0)+36>>2]&127](d)|0;if(Eb[c[(c[d>>2]|0)+8>>2]&127](d)|0?(f=Eb[c[(c[d>>2]|0)+20>>2]&127](d)|0,h=Eb[c[(c[d>>2]|0)+24>>2]&127](d)|0,(j|0)>0):0){e=c[b+720>>2]|0;g=0;a=i+(f<<2)|0;while(1){k=c[e+(g*104|0)+12>>2]|0;f=c[e+(g*104|0)+16>>2]|0;c[a>>2]=c[e+(g*104|0)+8>>2];c[a+4>>2]=k;c[a+8>>2]=f;g=g+1|0;if((g|0)==(j|0))break;else a=a+(h<<2)|0}}if(!(Eb[c[(c[d>>2]|0)+12>>2]&127](d)|0))return;a=Eb[c[(c[d>>2]|0)+28>>2]&127](d)|0;g=Eb[c[(c[d>>2]|0)+32>>2]&127](d)|0;if((j|0)<=0)return;f=c[b+720>>2]|0;a=i+(a<<2)|0;e=0;while(1){b=c[f+(e*104|0)+76>>2]|0;k=c[f+(e*104|0)+80>>2]|0;c[a>>2]=c[f+(e*104|0)+72>>2];c[a+4>>2]=b;c[a+8>>2]=k;e=e+1|0;if((e|0)==(j|0))break;else a=a+(g<<2)|0}return}function vi(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0,j=0,k=0.0,l=0,m=0.0,n=0.0,o=0,p=0,q=0;q=i;i=i+16|0;if((e|0)<=0){i=q;return}p=0;do{o=d+(p<<4)|0;f=+g[a+60>>2]*.5;h=c[a+68>>2]|0;k=+g[b+(p<<4)>>2];m=+g[b+(p<<4)+4>>2];n=+g[b+(p<<4)+8>>2];n=+O(+(k*k+m*m+n*n));j=c[a+64>>2]|0;do if(!(+g[b+(p<<4)+(h<<2)>>2]>n*+g[a+52>>2])){k=+g[b+(p<<4)+(j<<2)>>2];l=c[a+72>>2]|0;m=+g[b+(p<<4)+(l<<2)>>2];n=+O(+(k*k+m*m));if(n>1.1920928955078125e-07){n=+g[a+56>>2]/n;g[q+(j<<2)>>2]=k*n;g[q+(h<<2)>>2]=-f;g[q+(l<<2)>>2]=m*n;break}else{g[q+(j<<2)>>2]=0.0;g[q+(h<<2)>>2]=-f;g[q+(l<<2)>>2]=0.0;break}}else{g[q+(j<<2)>>2]=0.0;g[q+(h<<2)>>2]=f;g[q+(c[a+72>>2]<<2)>>2]=0.0}while(0);c[o>>2]=c[q>>2];c[o+4>>2]=c[q+4>>2];c[o+8>>2]=c[q+8>>2];c[o+12>>2]=c[q+12>>2];p=p+1|0}while((p|0)!=(e|0));i=q;return}function wi(b){b=b|0;var d=0,e=0,f=0,g=0,h=0,i=0,j=0;c[b>>2]=9352;d=c[b+56>>2]|0;if(d|0){if(a[b+60>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+56>>2]=0}a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;e=c[b+28>>2]|0;if((e|0)>0){j=0;do{f=c[b+36>>2]|0;g=f+(j*36|0)+4|0;h=f+(j*36|0)+12|0;i=c[h>>2]|0;d=f+(j*36|0)+16|0;if(i|0){if(a[d>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[i+-4>>2]|0)}c[h>>2]=0}a[d>>0]=1;c[h>>2]=0;c[g>>2]=0;c[f+(j*36|0)+8>>2]=0;j=j+1|0}while((j|0)!=(e|0))}d=c[b+36>>2]|0;if(d|0){if(a[b+40>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+36>>2]=0}a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;d=c[b+16>>2]|0;if(!d){a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}function xi(b){b=b|0;var d=0;c[b>>2]=8452;d=c[b+156>>2]|0;if(d|0){if(a[b+160>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+156>>2]=0}a[b+160>>0]=1;c[b+156>>2]=0;c[b+148>>2]=0;c[b+152>>2]=0;d=c[b+136>>2]|0;if(d|0){if(a[b+140>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+136>>2]=0}a[b+140>>0]=1;c[b+136>>2]=0;c[b+128>>2]=0;c[b+132>>2]=0;d=c[b+116>>2]|0;if(d|0){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+116>>2]=0}a[b+120>>0]=1;c[b+116>>2]=0;c[b+108>>2]=0;c[b+112>>2]=0;d=c[b+96>>2]|0;if(d|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;c[b>>2]=9368;d=c[b+32>>2]|0;if(!d){a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;b=b+28|0;c[b>>2]=0;return}if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+32>>2]=0;a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;b=b+28|0;c[b>>2]=0;return}function yi(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0;i=c[b+4>>2]|0;if((i|0)>=(d|0)){c[b+4>>2]=d;return}if((c[b+8>>2]|0)<(d|0)){if(!d){f=0;g=i}else{c[6435]=(c[6435]|0)+1;f=yc((d<<4|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}g=c[b+4>>2]|0}if((g|0)>0){h=0;do{j=c[b+12>>2]|0;c[f+(h<<4)>>2]=c[j+(h<<4)>>2];c[f+(h<<4)+4>>2]=c[j+(h<<4)+4>>2];c[f+(h<<4)+8>>2]=c[j+(h<<4)+8>>2];c[f+(h<<4)+12>>2]=c[j+(h<<4)+12>>2];h=h+1|0}while((h|0)!=(g|0))}g=c[b+12>>2]|0;if(g|0){if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=f;c[b+8>>2]=d;g=b+12|0}else g=b+12|0;f=i;do{j=c[g>>2]|0;c[j+(f<<4)>>2]=c[e>>2];c[j+(f<<4)+4>>2]=c[e+4>>2];c[j+(f<<4)+8>>2]=c[e+8>>2];c[j+(f<<4)+12>>2]=c[e+12>>2];f=f+1|0}while((f|0)!=(d|0));c[b+4>>2]=d;return}function zi(b){b=b|0;var d=0,e=0;c[6435]=(c[6435]|0)+1;d=yc(635)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}c[d+164>>2]=1065353216;c[d+168>>2]=1065353216;c[d+172>>2]=1065353216;g[d+176>>2]=0.0;c[d+180>>2]=0;g[d+184>>2]=999999984306749440.0;e=d+188|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[d+204>>2]=1;c[d+208>>2]=-1;c[d+212>>2]=-1;c[d+216>>2]=1;g[d+220>>2]=0.0;g[d+224>>2]=.5;g[d+228>>2]=0.0;g[d+232>>2]=0.0;c[d+236>>2]=1;c[d+240>>2]=0;g[d+244>>2]=1.0;e=d+248|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[d+4>>2]=1065353216;e=d+8|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[d+24>>2]=1065353216;e=d+28|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[d+44>>2]=1065353216;e=d+48|0;c[e>>2]=0;c[e+4>>2]=0;c[e+8>>2]=0;c[e+12>>2]=0;c[e+16>>2]=0;c[d>>2]=4108;a[d+500>>0]=1;c[d+496>>2]=0;c[d+488>>2]=0;c[d+492>>2]=0;Od(d,b);return d|0}function Ai(b){b=b|0;var d=0;c[b>>2]=9012;d=c[b+160>>2]|0;if(d|0){if(a[b+164>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+160>>2]=0}a[b+164>>0]=1;c[b+160>>2]=0;c[b+152>>2]=0;c[b+156>>2]=0;d=c[b+136>>2]|0;if(d|0){if(a[b+140>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+136>>2]=0}a[b+140>>0]=1;c[b+136>>2]=0;c[b+128>>2]=0;c[b+132>>2]=0;d=c[b+116>>2]|0;if(d|0){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+116>>2]=0}a[b+120>>0]=1;c[b+116>>2]=0;c[b+108>>2]=0;c[b+112>>2]=0;d=c[b+96>>2]|0;if(d|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;d=c[b+76>>2]|0;if(!d){a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;b=b+72|0;c[b>>2]=0;return}if(a[b+80>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+76>>2]=0;a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;b=b+72|0;c[b>>2]=0;return}function Bi(b,d,e,f,g){b=b|0;d=d|0;e=e|0;f=f|0;g=g|0;do if((b|0)==(c[d+8>>2]|0)){if((c[d+4>>2]|0)==(e|0)?(c[d+28>>2]|0)!=1:0)c[d+28>>2]=f}else{if((b|0)!=(c[d>>2]|0)){b=c[b+8>>2]|0;yb[c[(c[b>>2]|0)+24>>2]&31](b,d,e,f,g);break}if((c[d+16>>2]|0)!=(e|0)?(c[d+20>>2]|0)!=(e|0):0){c[d+32>>2]=f;if((c[d+44>>2]|0)==4)break;a[d+52>>0]=0;a[d+53>>0]=0;b=c[b+8>>2]|0;Qb[c[(c[b>>2]|0)+20>>2]&7](b,d,e,e,1,g);if(a[d+53>>0]|0)if(!(a[d+52>>0]|0)){f=1;b=13}else b=17;else{f=0;b=13}do if((b|0)==13){c[d+20>>2]=e;c[d+40>>2]=(c[d+40>>2]|0)+1;if((c[d+36>>2]|0)==1?(c[d+24>>2]|0)==2:0){a[d+54>>0]=1;if(f){b=17;break}else{f=4;break}}if(f)b=17;else f=4}while(0);if((b|0)==17)f=3;c[d+44>>2]=f;break}if((f|0)==1)c[d+32>>2]=1}while(0);return}function Ci(b){b=b|0;var d=0;c[b>>2]=4816;d=c[b+144>>2]|0;if(d|0){if(a[b+148>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+144>>2]=0}a[b+148>>0]=1;c[b+144>>2]=0;c[b+136>>2]=0;c[b+140>>2]=0;d=c[b+76>>2]|0;if(d|0){if(a[b+80>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+76>>2]=0}a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;c[b+72>>2]=0;d=c[b+56>>2]|0;if(d|0){if(a[b+60>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+56>>2]=0}a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;d=c[b+36>>2]|0;if(d|0){if(a[b+40>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+36>>2]=0}a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;d=c[b+16>>2]|0;if(!d){a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;b=b+12|0;c[b>>2]=0;return}function Di(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0;o=(+g[a+32>>2]-+g[a+16>>2])*+g[a+108>>2]*.5;m=(+g[a+36>>2]-+g[a+20>>2])*+g[a+112>>2]*.5;k=(+g[a+40>>2]-+g[a+24>>2])*+g[a+116>>2]*.5;t=+N(+(+g[b>>2]));s=+N(+(+g[b+4>>2]));r=+N(+(+g[b+8>>2]));n=+N(+(+g[b+16>>2]));l=+N(+(+g[b+20>>2]));j=+N(+(+g[b+24>>2]));w=+N(+(+g[b+32>>2]));v=+N(+(+g[b+36>>2]));f=+N(+(+g[b+40>>2]));u=+g[b+48>>2];p=+g[b+52>>2];h=+g[b+56>>2];q=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);i=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);f=o*w+m*v+k*f+ +Sb[c[(c[a>>2]|0)+48>>2]&15](a);g[d>>2]=u-(o*t+m*s+k*r+q);g[d+4>>2]=p-(o*n+m*l+k*j+i);g[d+8>>2]=h-f;g[d+12>>2]=0.0;g[e>>2]=u+(o*t+m*s+k*r+q);g[e+4>>2]=p+(o*n+m*l+k*j+i);g[e+8>>2]=h+f;g[e+12>>2]=0.0;return}function Ei(b,d){b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0;c[6435]=(c[6435]|0)+1;e=yc(379)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e+4>>2]=3;c[e>>2]=4432;c[e+8>>2]=-1;c[e+12>>2]=-1;g[e+16>>2]=3402823466385288598117041.0e14;a[e+20>>0]=1;a[e+21>>0]=0;c[e+24>>2]=-1;c[e+28>>2]=b;Il();c[e+32>>2]=23268;g[e+36>>2]=0.0;g[e+40>>2]=.30000001192092896;c[e+44>>2]=0;c[e>>2]=4544;l=e+300|0;c[l>>2]=c[d>>2];c[l+4>>2]=c[d+4>>2];c[l+8>>2]=c[d+8>>2];c[l+12>>2]=c[d+12>>2];k=+g[d>>2];j=+g[d+4>>2];i=+g[d+8>>2];h=k*+g[b+20>>2]+j*+g[b+24>>2]+i*+g[b+28>>2]+ +g[b+56>>2];f=k*+g[b+36>>2]+j*+g[b+40>>2]+i*+g[b+44>>2]+ +g[b+60>>2];g[e+316>>2]=k*+g[b+4>>2]+j*+g[b+8>>2]+i*+g[b+12>>2]+ +g[b+52>>2];g[e+320>>2]=h;g[e+324>>2]=f;g[e+328>>2]=0.0;c[e+332>>2]=0;a[e+344>>0]=0;g[e+348>>2]=.30000001192092896;g[e+352>>2]=1.0;g[e+356>>2]=0.0;return e|0}function Fi(b,d,e){b=+b;d=d|0;e=e|0;var f=0,h=0;while(1){f=yc(140)|0;if(f|0){h=6;break}f=c[6564]|0;c[6564]=f+0;if(!f){h=5;break}jc[f&3]()}if((h|0)==5){e=Ya(4)|0;c[e>>2]=9640;pb(e|0,2800,251)}else if((h|0)==6){g[f>>2]=b;c[f+4>>2]=d;c[f+72>>2]=e;c[f+76>>2]=0;c[f+76+4>>2]=0;c[f+76+8>>2]=0;c[f+76+12>>2]=0;c[f+76+16>>2]=0;c[f+76+20>>2]=0;g[f+100>>2]=.5;g[f+104>>2]=0.0;g[f+108>>2]=0.0;g[f+112>>2]=.800000011920929;g[f+116>>2]=1.0;a[f+120>>0]=0;g[f+124>>2]=.004999999888241291;g[f+128>>2]=.009999999776482582;g[f+132>>2]=.009999999776482582;g[f+136>>2]=.009999999776482582;c[f+8>>2]=1065353216;c[f+12>>2]=0;c[f+12+4>>2]=0;c[f+12+8>>2]=0;c[f+12+12>>2]=0;c[f+28>>2]=1065353216;c[f+32>>2]=0;c[f+32+4>>2]=0;c[f+32+8>>2]=0;c[f+32+12>>2]=0;c[f+48>>2]=1065353216;c[f+52>>2]=0;c[f+52+4>>2]=0;c[f+52+8>>2]=0;c[f+52+12>>2]=0;c[f+52+16>>2]=0;return f|0}return 0}function Gi(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;e=c[b>>2]|0;if((e|0)==(c[a+80>>2]|0)){f=1.0;return +f}if(c[e+204>>2]&4|0){f=1.0;return +f}if((+g[a+28>>2]-+g[a+12>>2])*+g[b+8>>2]+(+g[a+32>>2]-+g[a+16>>2])*+g[b+12>>2]+(+g[a+36>>2]-+g[a+20>>2])*+g[b+16>>2]>=-+g[a+84>>2]){f=1.0;return +f}c[a+4>>2]=c[b+40>>2];c[a+76>>2]=e;if(d){c[a+44>>2]=c[b+8>>2];c[a+44+4>>2]=c[b+8+4>>2];c[a+44+8>>2]=c[b+8+8>>2];c[a+44+12>>2]=c[b+8+12>>2]}else{k=+g[b+8>>2];j=+g[b+12>>2];i=+g[b+16>>2];h=k*+g[e+20>>2]+j*+g[e+24>>2]+i*+g[e+28>>2];f=k*+g[e+36>>2]+j*+g[e+40>>2]+i*+g[e+44>>2];g[a+44>>2]=+g[e+4>>2]*k+ +g[e+8>>2]*j+ +g[e+12>>2]*i;g[a+48>>2]=h;g[a+52>>2]=f;g[a+56>>2]=0.0}c[a+60>>2]=c[b+24>>2];c[a+60+4>>2]=c[b+24+4>>2];c[a+60+8>>2]=c[b+24+8>>2];c[a+60+12>>2]=c[b+24+12>>2];k=+g[b+40>>2];return +k}function Hi(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0,j=0,k=0,l=0;j=i;i=i+80|0;if((e|0)>0)f=0;else{i=j;return}do{g[d+(f<<4)+12>>2]=-999999984306749440.0;f=f+1|0}while((f|0)!=(e|0));f=j+32+4|0;h=0;do{k=b+(h<<4)|0;c[j+32>>2]=7824;c[f>>2]=0;c[f+4>>2]=0;c[f+8>>2]=0;c[f+12>>2]=0;g[j+32+20>>2]=-999999984306749440.0;c[j+32+24>>2]=c[k>>2];c[j+32+24+4>>2]=c[k+4>>2];c[j+32+24+8>>2]=c[k+8>>2];c[j+32+24+12>>2]=c[k+12>>2];c[j+16>>2]=1566444395;c[j+16+4>>2]=1566444395;c[j+16+8>>2]=1566444395;g[j+16+12>>2]=0.0;k=c[a+92>>2]|0;l=c[(c[k>>2]|0)+8>>2]|0;g[j>>2]=-999999984306749440.0;g[j+4>>2]=-999999984306749440.0;g[j+8>>2]=-999999984306749440.0;g[j+12>>2]=0.0;mc[l&127](k,j+32|0,j,j+16|0);k=d+(h<<4)|0;c[k>>2]=c[f>>2];c[k+4>>2]=c[f+4>>2];c[k+8>>2]=c[f+8>>2];c[k+12>>2]=c[f+12>>2];h=h+1|0}while((h|0)<(e|0));i=j;return}function Ii(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0,j=0,k=0;f=c[b+96>>2]|0;if((f|0)==(c[b+100>>2]|0)?(i=f|0?f<<1:1,(f|0)<(i|0)):0){if(!i)h=0;else{c[6435]=(c[6435]|0)+1;f=yc((i<<4|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}h=f;f=c[b+96>>2]|0}if((f|0)>0){g=0;do{j=h+(g<<4)|0;k=(c[b+104>>2]|0)+(g<<4)|0;c[j>>2]=c[k>>2];c[j+4>>2]=c[k+4>>2];c[j+8>>2]=c[k+8>>2];c[j+12>>2]=c[k+12>>2];g=g+1|0}while((g|0)!=(f|0))}f=c[b+104>>2]|0;if(f|0){if(a[b+108>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+104>>2]=0}a[b+108>>0]=1;c[b+104>>2]=h;c[b+100>>2]=i;f=c[b+96>>2]|0}k=(c[b+104>>2]|0)+(f<<4)|0;c[k>>2]=c[d>>2];c[k+4>>2]=c[d+4>>2];c[k+8>>2]=c[d+8>>2];c[k+12>>2]=c[d+12>>2];c[b+96>>2]=(c[b+96>>2]|0)+1;if(!e)return;vj(b);return}function Ji(b){b=b|0;var d=0,e=0,f=0,h=0;c[b+32>>2]=262144;h=c[b+4>>2]|0;if((h|0)<2383){if((c[b+8>>2]|0)<2383){c[6435]=(c[6435]|0)+1;d=yc(9551)|0;if(!d)f=0;else{c[(d+4+15&-16)+-4>>2]=d;f=d+4+15&-16}d=c[b+4>>2]|0;if((d|0)>0){e=0;do{c[f+(e<<2)>>2]=c[(c[b+12>>2]|0)+(e<<2)>>2];e=e+1|0}while((e|0)!=(d|0))}d=c[b+12>>2]|0;if(d|0){if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=f;c[b+8>>2]=2383;e=b+12|0}else e=b+12|0;d=h;do{c[(c[e>>2]|0)+(d<<2)>>2]=0;d=d+1|0}while((d|0)!=2383)}c[b+4>>2]=2383;e=0;do{h=(c[b+12>>2]|0)+(e<<2)|0;d=c[h>>2]|0;c[h>>2]=0;if(d|0)do{h=d;d=c[d+280>>2]|0;hd(h)}while((d|0)!=0);e=e+1|0}while((e|0)!=2383);g[b+20>>2]=.25;c[b+24>>2]=0;c[b+28>>2]=0;c[b+36>>2]=1;c[b+40>>2]=1;return}function Ki(){var b=0,d=0;c[6435]=(c[6435]|0)+1;b=yc(303)|0;if(!b)b=0;else{c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16}c[b+164>>2]=1065353216;c[b+168>>2]=1065353216;c[b+172>>2]=1065353216;g[b+176>>2]=0.0;c[b+180>>2]=0;g[b+184>>2]=999999984306749440.0;d=b+188|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[b+204>>2]=1;c[b+208>>2]=-1;c[b+212>>2]=-1;c[b+216>>2]=1;g[b+220>>2]=0.0;g[b+224>>2]=.5;g[b+228>>2]=0.0;g[b+232>>2]=0.0;c[b+240>>2]=0;g[b+244>>2]=1.0;d=b+248|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[b+4>>2]=1065353216;d=b+8|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[b+24>>2]=1065353216;d=b+28|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[b+44>>2]=1065353216;d=b+48|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[d+16>>2]=0;c[b>>2]=5044;a[b+280>>0]=1;c[b+276>>2]=0;c[b+268>>2]=0;c[b+272>>2]=0;c[b+236>>2]=4;return b|0}function Li(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0,o=0,p=0,q=0.0,r=0,s=0.0,t=0;if((e|0)>0)f=0;else return;do{g[d+(f<<4)+12>>2]=-999999984306749440.0;f=f+1|0}while((f|0)!=(e|0));p=0;do{h=+g[a+12>>2];i=+g[b+(p<<4)>>2]*h;j=+g[a+16>>2];k=+g[b+(p<<4)+4>>2]*j;l=+g[a+20>>2];m=+g[b+(p<<4)+8>>2]*l;f=c[a+96>>2]|0;if((f|0)>0){n=c[a+104>>2]|0;o=0;q=-3402823466385288598117041.0e14;r=-1;do{s=i*+g[n+(o<<4)>>2]+k*+g[n+(o<<4)+4>>2]+m*+g[n+(o<<4)+8>>2];t=s>q;r=t?o:r;q=t?s:q;o=o+1|0}while((o|0)!=(f|0));m=+g[n+(r<<4)+4>>2]*j;s=+g[n+(r<<4)+8>>2]*l;g[d+(p<<4)>>2]=+g[n+(r<<4)>>2]*h;g[d+(p<<4)+4>>2]=m;g[d+(p<<4)+8>>2]=s;g[d+(p<<4)+12>>2]=q}else g[d+(p<<4)+12>>2]=-999999984306749440.0;p=p+1|0}while((p|0)!=(e|0));return}function Mi(a,b){a=a|0;b=b|0;var d=0,e=0,f=0;d=i;i=i+96|0;b=c[b>>2]|0;if((b|0)==(c[a+4>>2]|0)){i=d;return 1}e=c[a+12>>2]|0;if(!(Zb[c[(c[e>>2]|0)+8>>2]&31](e,c[b+188>>2]|0)|0)){i=d;return 1}e=c[a+4>>2]|0;f=c[e+192>>2]|0;c[d+64>>2]=0;c[d+64+4>>2]=f;c[d+64+8>>2]=e;c[d+64+12>>2]=e+4;c[d+64+16>>2]=-1;c[d+64+20>>2]=-1;e=c[b+192>>2]|0;c[d+40>>2]=0;c[d+40+4>>2]=e;c[d+40+8>>2]=b;c[d+40+12>>2]=b+4;c[d+40+16>>2]=-1;c[d+40+20>>2]=-1;b=c[(c[a+8>>2]|0)+24>>2]|0;b=Ib[c[(c[b>>2]|0)+8>>2]&31](b,d+64|0,d+40|0,0)|0;if(b|0){f=c[a+12>>2]|0;c[d+4>>2]=0;c[d+8>>2]=d+64;c[d+12>>2]=d+40;c[d>>2]=5976;c[d+32>>2]=f;yb[c[(c[b>>2]|0)+8>>2]&31](b,d+64|0,d+40|0,(c[a+8>>2]|0)+28|0,d);Ab[c[c[b>>2]>>2]&255](b);f=c[(c[a+8>>2]|0)+24>>2]|0;Cb[c[(c[f>>2]|0)+60>>2]&127](f,b)}i=d;return 1}function Ni(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0,h=0,j=0,k=0,l=0;l=i;i=i+80|0;h=c[c[a>>2]>>2]|0;j=c[c[a+4>>2]>>2]|0;if(!(Ob[c[(c[b>>2]|0)+24>>2]&63](b,h,j)|0)){i=l;return}f=c[h+192>>2]|0;c[l+56>>2]=0;c[l+56+4>>2]=f;c[l+56+8>>2]=h;c[l+56+12>>2]=h+4;c[l+56+16>>2]=-1;c[l+56+20>>2]=-1;f=c[j+192>>2]|0;c[l+32>>2]=0;c[l+32+4>>2]=f;c[l+32+8>>2]=j;c[l+32+12>>2]=j+4;c[l+32+16>>2]=-1;c[l+32+20>>2]=-1;f=c[a+8>>2]|0;if(!f){f=Ib[c[(c[b>>2]|0)+8>>2]&31](b,l+56|0,l+32|0,0)|0;c[a+8>>2]=f;if(f|0)k=4}else k=4;if((k|0)==4){c[l>>2]=5604;c[l+4>>2]=0;c[l+8>>2]=l+56;c[l+12>>2]=l+32;if((c[d+8>>2]|0)!=1){e=+Mb[c[(c[f>>2]|0)+12>>2]&15](f,h,j,d,l);if(+g[d+12>>2]>e)g[d+12>>2]=e}else yb[c[(c[f>>2]|0)+8>>2]&31](f,l+56|0,l+32|0,d,l)}i=l;return}function Oi(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0;i=c[d+4>>2]|0;f=c[b+24>>2]|0;if((f|0)<(i|0)){if((c[b+28>>2]|0)<(i|0)){if(!i){e=0;g=f}else{c[6435]=(c[6435]|0)+1;e=yc((i<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}g=c[b+24>>2]|0}if((g|0)>0){h=0;do{c[e+(h<<2)>>2]=c[(c[b+32>>2]|0)+(h<<2)>>2];h=h+1|0}while((h|0)!=(g|0))}g=c[b+32>>2]|0;if(g|0){if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+32>>2]=0}a[b+36>>0]=1;c[b+32>>2]=e;c[b+28>>2]=i;e=b+32|0}else e=b+32|0;do{c[(c[e>>2]|0)+(f<<2)>>2]=0;f=f+1|0}while((f|0)!=(i|0))}else e=b+32|0;c[b+24>>2]=i;e=c[e>>2]|0;if((i|0)<=0)return;f=0;do{c[e+(f<<2)>>2]=c[(c[d+12>>2]|0)+(f<<2)>>2];f=f+1|0}while((f|0)!=(i|0));return}function Pi(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0;e=c[b+488>>2]|0;a:do if((e|0)>0){g=c[b+496>>2]|0;f=0;while(1){if((c[g+(f<<2)>>2]|0)==(d|0))break;f=f+1|0;if((f|0)>=(e|0))break a}if((f|0)!=(e|0)){b=b+256|0;c[b>>2]=1;return}}while(0);if((e|0)==(c[b+492>>2]|0)?(h=e|0?e<<1:1,(e|0)<(h|0)):0){if(!h)g=0;else{c[6435]=(c[6435]|0)+1;e=yc((h<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}g=e;e=c[b+488>>2]|0}if((e|0)>0){f=0;do{c[g+(f<<2)>>2]=c[(c[b+496>>2]|0)+(f<<2)>>2];f=f+1|0}while((f|0)!=(e|0))}f=c[b+496>>2]|0;if(f){if(a[b+500>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0);e=c[b+488>>2]|0}c[b+496>>2]=0}a[b+500>>0]=1;c[b+496>>2]=g;c[b+492>>2]=h}c[(c[b+496>>2]|0)+(e<<2)>>2]=d;c[b+488>>2]=e+1;b=b+256|0;c[b>>2]=1;return}function Qi(a,b,c,d,e,f,h,i,j,k,l){a=a|0;b=b|0;c=+c;d=+d;e=+e;f=+f;h=+h;i=+i;j=j|0;k=k|0;l=+l;var m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0;x=+g[a>>2]*f+ +g[a+16>>2]*h+ +g[a+32>>2]*i;v=+g[a+4>>2]*f+ +g[a+20>>2]*h+ +g[a+36>>2]*i;t=+g[a+8>>2]*f+ +g[a+24>>2]*h+ +g[a+40>>2]*i;s=+g[b>>2]*f+ +g[b+16>>2]*h+ +g[b+32>>2]*i;q=+g[b+4>>2]*f+ +g[b+20>>2]*h+ +g[b+36>>2]*i;o=+g[b+8>>2]*f+ +g[b+24>>2]*h+ +g[b+40>>2]*i;w=+g[j+80>>2];u=+g[j+84>>2];p=+g[j+88>>2];r=+g[k+80>>2];m=+g[k+84>>2];n=+g[k+88>>2];p=x*(x<0.0?-w:w)+v*(v<0.0?-u:u)+t*(t<0.0?-p:p);n=s*(s<0.0?-r:r)+q*(q<0.0?-m:m)+o*(o<0.0?-n:n);o=+g[j+96>>2];m=+g[k+96>>2];m=(p>o?p:o)+(n>m?n:m);return !((c*f+d*h+e*i+ml)|0}function Ri(b){b=b|0;var d=0,e=0,f=0,g=0;c[b>>2]=8724;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[b+24>>2]=0;a[b+28>>0]=0;a[b+48>>0]=1;c[b+44>>2]=0;c[b+36>>2]=0;c[b+40>>2]=0;a[b+68>>0]=1;c[b+64>>2]=0;c[b+56>>2]=0;c[b+60>>2]=0;c[b+72>>2]=0;c[6435]=(c[6435]|0)+1;d=yc(51)|0;if(!d)f=0;else{c[(d+4+15&-16)+-4>>2]=d;f=d+4+15&-16}d=c[b+8>>2]|0;if((d|0)>0){e=0;do{g=c[b+16>>2]|0;c[f+(e<<4)>>2]=c[g+(e<<4)>>2];c[f+(e<<4)+4>>2]=c[g+(e<<4)+4>>2];c[f+(e<<4)+8>>2]=c[g+(e<<4)+8>>2];c[f+(e<<4)+12>>2]=c[g+(e<<4)+12>>2];e=e+1|0}while((e|0)!=(d|0))}d=c[b+16>>2]|0;if(!d){a[b+20>>0]=1;c[b+16>>2]=f;c[b+12>>2]=2;Hf(b);return}if(a[b+20>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+16>>2]=0;a[b+20>>0]=1;c[b+16>>2]=f;c[b+12>>2]=2;Hf(b);return}function Si(a,b,d){a=a|0;b=b|0;d=d|0;do if(!((b|0)==32&(d|0)==32)){if((b|0)==32){if((d|0)<20){b=a+96|0;break}if((d+-21|0)>>>0<9){b=a+104|0;break}}else{if((b|0)<20&(d|0)==32){b=a+100|0;break}if((b+-21|0)>>>0<9&(d|0)==32){b=a+108|0;break}if((b|0)==8&(d|0)==8){b=a+60|0;break}if((b|0)==8&(d|0)==1){b=a+76|0;break}if((b|0)==1&(d|0)==8){b=a+80|0;break}}if(!(d|b)){b=a+72|0;break}if((b|0)<20&(d|0)==28){b=a+88|0;break}if((b|0)==28&(d|0)<20){b=a+84|0;break}if((b|0)<20){if((d|0)<20){b=a+32|0;break}if((d+-21|0)>>>0<9){b=a+36|0;break}}else{if((d|0)<20&(b+-21|0)>>>0<9){b=a+40|0;break}if((b|0)==31)if((d|0)==31){b=a+48|0;break}else{b=a+44|0;break}}if((d|0)==31){b=a+52|0;break}else{b=a+56|0;break}}else b=a+92|0;while(0);return c[b>>2]|0}function Ti(a,b,d,e,f,h,j,k,l){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;k=k|0;l=l|0;var m=0,n=0,o=0;o=i;i=i+16|0;li(12899);Xb[c[(c[a>>2]|0)+32>>2]&1](a,b,d,e,f,h,j,k,l);n=c[a+184>>2]|0;m=c[k+20>>2]|0;m=(n|0)>(m|0)?n:m;if((m|0)>0){n=0;do{+$b[c[(c[a>>2]|0)+40>>2]&3](a,n,b,d,e,f,h,j,k,l);n=n+1|0}while((n|0)<(m|0))}m=c[2357]|0;a=(c[m+16>>2]|0)+-1|0;c[m+16>>2]=a;if(a|0){i=o;return 0.0}do if(c[m+4>>2]|0){tb(o|0,0)|0;a=c[6434]|0;g[m+8>>2]=+g[m+8>>2]+ +(((c[o+4>>2]|0)-(c[a+4>>2]|0)+(((c[o>>2]|0)-(c[a>>2]|0)|0)*1e6|0)-(c[m+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[m+16>>2]|0)){m=c[2357]|0;break}else{i=o;return 0.0}}while(0);c[2357]=c[m+20>>2];i=o;return 0.0}function Ui(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0;g=c[d>>2]|0;d=c[b+268>>2]|0;a:do if((d|0)>0){f=c[b+276>>2]|0;e=0;while(1){if((c[f+(e<<2)>>2]|0)==(g|0))break;e=e+1|0;if((e|0)>=(d|0))break a}if((e|0)!=(d|0))return}while(0);if((d|0)==(c[b+272>>2]|0)?(h=d|0?d<<1:1,(d|0)<(h|0)):0){if(!h)f=0;else{c[6435]=(c[6435]|0)+1;d=yc((h<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}f=d;d=c[b+268>>2]|0}if((d|0)>0){e=0;do{c[f+(e<<2)>>2]=c[(c[b+276>>2]|0)+(e<<2)>>2];e=e+1|0}while((e|0)!=(d|0))}e=c[b+276>>2]|0;if(e){if(a[b+280>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);d=c[b+268>>2]|0}c[b+276>>2]=0}a[b+280>>0]=1;c[b+276>>2]=f;c[b+272>>2]=h}c[(c[b+276>>2]|0)+(d<<2)>>2]=g;c[b+268>>2]=d+1;return}function Vi(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0,h=0;f=c[a+232>>2]|0;a:do if((f|0)>0){g=c[a+240>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0))break a}if((d|0)<(f|0)){c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+240>>2]|0)+(f+-1<<2)>>2]=b;c[a+232>>2]=f+-1}}while(0);d=c[b+188>>2]|0;if(d|0){g=c[a+68>>2]|0;g=Eb[c[(c[g>>2]|0)+36>>2]&127](g)|0;ic[c[(c[g>>2]|0)+40>>2]&127](g,d,c[a+24>>2]|0);g=c[a+68>>2]|0;ic[c[(c[g>>2]|0)+12>>2]&127](g,d,c[a+24>>2]|0);c[b+188>>2]=0}f=c[a+8>>2]|0;if((f|0)<=0)return;g=c[a+16>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0)){h=15;break}}if((h|0)==15)return;if((d|0)>=(f|0))return;c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+16>>2]|0)+(f+-1<<2)>>2]=b;c[a+8>>2]=f+-1;return}function Wi(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0,h=0;f=c[a+328>>2]|0;a:do if((f|0)>0){g=c[a+336>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0))break a}if((d|0)<(f|0)){c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+336>>2]|0)+(f+-1<<2)>>2]=b;c[a+328>>2]=f+-1}}while(0);d=c[b+188>>2]|0;if(d|0){g=c[a+68>>2]|0;g=Eb[c[(c[g>>2]|0)+36>>2]&127](g)|0;ic[c[(c[g>>2]|0)+40>>2]&127](g,d,c[a+24>>2]|0);g=c[a+68>>2]|0;ic[c[(c[g>>2]|0)+12>>2]&127](g,d,c[a+24>>2]|0);c[b+188>>2]=0}f=c[a+8>>2]|0;if((f|0)<=0)return;g=c[a+16>>2]|0;d=0;while(1){e=g+(d<<2)|0;if((c[e>>2]|0)==(b|0))break;d=d+1|0;if((d|0)>=(f|0)){h=15;break}}if((h|0)==15)return;if((d|0)>=(f|0))return;c[e>>2]=c[g+(f+-1<<2)>>2];c[(c[a+16>>2]|0)+(f+-1<<2)>>2]=b;c[a+8>>2]=f+-1;return}function Xi(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0;i=c[d+4>>2]|0;e=c[b+872>>2]|0;a:do if((e|0)>(i|0))e=b+880|0;else{if((e|0)<(i|0)?(c[b+876>>2]|0)<(i|0):0){if((i|0)!=0?(c[6435]=(c[6435]|0)+1,f=yc((i<<2|3)+16|0)|0,(f|0)!=0):0){c[(f+4+15&-16)+-4>>2]=f;h=f+4+15&-16}else h=0;f=c[b+872>>2]|0;g=0;while(1){if((g|0)>=(f|0))break;c[h+(g<<2)>>2]=c[(c[b+880>>2]|0)+(g<<2)>>2];g=g+1|0}f=c[b+880>>2]|0;if(f|0){if(!((a[b+884>>0]&1)==0|(f|0)==0)){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+880>>2]=0}a[b+884>>0]=1;c[b+880>>2]=h;c[b+876>>2]=i}while(1){if((e|0)>=(i|0)){e=b+880|0;break a}c[(c[b+880>>2]|0)+(e<<2)>>2]=0;e=e+1|0}}while(0);c[b+872>>2]=i;e=c[e>>2]|0;f=0;while(1){if((f|0)>=(i|0))break;c[e+(f<<2)>>2]=c[(c[d+12>>2]|0)+(f<<2)>>2];f=f+1|0}return}function Yi(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0;i=c[d+4>>2]|0;e=c[b+4>>2]|0;a:do if((e|0)>(i|0))e=b+12|0;else{if((e|0)<(i|0)?(c[b+8>>2]|0)<(i|0):0){if((i|0)!=0?(c[6435]=(c[6435]|0)+1,f=yc((i<<2|3)+16|0)|0,(f|0)!=0):0){c[(f+4+15&-16)+-4>>2]=f;h=f+4+15&-16}else h=0;f=c[b+4>>2]|0;g=0;while(1){if((g|0)>=(f|0))break;c[h+(g<<2)>>2]=c[(c[b+12>>2]|0)+(g<<2)>>2];g=g+1|0}f=c[b+12>>2]|0;if(f|0){if(!((a[b+16>>0]&1)==0|(f|0)==0)){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+12>>2]=0}a[b+16>>0]=1;c[b+12>>2]=h;c[b+8>>2]=i}while(1){if((e|0)>=(i|0)){e=b+12|0;break a}c[(c[b+12>>2]|0)+(e<<2)>>2]=0;e=e+1|0}}while(0);c[b+4>>2]=i;e=c[e>>2]|0;f=0;while(1){if((f|0)>=(i|0))break;c[e+(f<<2)>>2]=c[(c[d+12>>2]|0)+(f<<2)>>2];f=f+1|0}return}function Zi(b){b=b|0;var d=0,e=0;d=c[b+92>>2]|0;if(d|0){if(a[b+96>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+92>>2]=0}a[b+96>>0]=1;c[b+92>>2]=0;c[b+84>>2]=0;c[b+88>>2]=0;d=c[b+64>>2]|0;if(d|0)do{c[b+64>>2]=c[d+8>>2];e=c[d>>2]|0;if(e|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);d=c[b+64>>2]|0}while((d|0)!=0);d=c[b+48>>2]|0;if(d|0)do{c[b+48>>2]=c[d+8>>2];e=c[d>>2]|0;if(e|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);d=c[b+48>>2]|0}while((d|0)!=0);d=c[b+32>>2]|0;if(!d)return;do{c[b+32>>2]=c[d+8>>2];e=c[d>>2]|0;if(e|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);d=c[b+32>>2]|0}while((d|0)!=0);return}function _i(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var g=0,h=0,i=0,j=0;h=c[d>>2]|0;h=Zb[c[(c[h>>2]|0)+56>>2]&31](h,28)|0;j=(a[b+4>>0]|0)==0;i=c[b+8>>2]|0;g=c[b+12>>2]|0;b=c[d>>2]|0;c[h+4>>2]=b;c[h>>2]=5480;a[h+8>>0]=0;c[h+12>>2]=0;if(j){a[h+16>>0]=0;c[h+20>>2]=i;c[h+24>>2]=g;if(!(Ob[c[(c[b>>2]|0)+24>>2]&63](b,c[e+8>>2]|0,c[f+8>>2]|0)|0))return h|0;j=c[h+4>>2]|0;c[h+12>>2]=Ob[c[(c[j>>2]|0)+12>>2]&63](j,c[e+8>>2]|0,c[f+8>>2]|0)|0;a[h+8>>0]=1;return h|0}else{a[h+16>>0]=1;c[h+20>>2]=i;c[h+24>>2]=g;if(!(Ob[c[(c[b>>2]|0)+24>>2]&63](b,c[f+8>>2]|0,c[e+8>>2]|0)|0))return h|0;j=c[h+4>>2]|0;c[h+12>>2]=Ob[c[(c[j>>2]|0)+12>>2]&63](j,c[f+8>>2]|0,c[e+8>>2]|0)|0;a[h+8>>0]=1;return h|0}return 0}function $i(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;c[a+4>>2]=c[b+40>>2];e=c[b>>2]|0;c[a+76>>2]=e;if(d){c[a+44>>2]=c[b+8>>2];c[a+44+4>>2]=c[b+8+4>>2];c[a+44+8>>2]=c[b+8+8>>2];c[a+44+12>>2]=c[b+8+12>>2];a=a+60|0;d=b+24|0;c[a>>2]=c[d>>2];c[a+4>>2]=c[d+4>>2];c[a+8>>2]=c[d+8>>2];c[a+12>>2]=c[d+12>>2];f=+g[b+40>>2];return +f}else{k=+g[b+8>>2];j=+g[b+12>>2];i=+g[b+16>>2];h=+g[e+20>>2]*k+ +g[e+24>>2]*j+ +g[e+28>>2]*i;f=+g[e+36>>2]*k+ +g[e+40>>2]*j+ +g[e+44>>2]*i;g[a+44>>2]=+g[e+4>>2]*k+ +g[e+8>>2]*j+ +g[e+12>>2]*i;g[a+48>>2]=h;g[a+52>>2]=f;g[a+56>>2]=0.0;a=a+60|0;d=b+24|0;c[a>>2]=c[d>>2];c[a+4>>2]=c[d+4>>2];c[a+8>>2]=c[d+8>>2];c[a+12>>2]=c[d+12>>2];f=+g[b+40>>2];return +f}return 0.0}function aj(){var b=0,d=0;c[6435]=(c[6435]|0)+1;b=yc(791)|0;if(!b)b=0;else{c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16}c[b>>2]=1025;c[b+116>>2]=0;a[b+120>>0]=0;d=b+124|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[d+16>>2]=0;c[d+20>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;c[b+300>>2]=0;a[b+304>>0]=0;d=b+308|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[d+16>>2]=0;c[d+20>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;c[b+484>>2]=0;a[b+488>>0]=0;d=b+492|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[d+16>>2]=0;c[d+20>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;c[b+668>>2]=0;a[b+672>>0]=0;d=b+676|0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=0;c[d+12>>2]=0;c[d+16>>2]=0;c[d+20>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;c[b+740>>2]=0;c[b+744>>2]=0;c[b+748>>2]=0;c[b+768>>2]=0;return b|0}function bj(b,d){b=b|0;d=d|0;var e=0,f=0,h=0,j=0.0,k=0.0,l=0,m=0;f=i;i=i+48|0;if((c[b+136>>2]|0)<=0){i=f;return}e=0;do{m=c[b+144>>2]|0;c[f+32>>2]=(a[m+(e*284|0)+84>>0]|0)==0?1065353216:0;c[f+32+4>>2]=0;c[f+32+8>>2]=1065353216;g[f+32+12>>2]=0.0;l=m+(e*284|0)+140|0;c[f+16>>2]=c[l>>2];c[f+16+4>>2]=c[l+4>>2];c[f+16+8>>2]=c[l+8>>2];c[f+16+12>>2]=c[l+12>>2];l=c[b+120>>2]|0;h=c[(c[d>>2]|0)+8>>2]|0;k=+g[m+(e*284|0)+108+(l<<2)>>2]+ +g[f+16+4>>2];j=+g[m+(e*284|0)+124+(l<<2)>>2]+ +g[f+16+8>>2];g[f>>2]=+g[m+(e*284|0)+92+(l<<2)>>2]+ +g[f+16>>2];g[f+4>>2]=k;g[f+8>>2]=j;g[f+12>>2]=0.0;mc[h&127](d,f+16|0,f,f+32|0);mc[c[(c[d>>2]|0)+8>>2]&127](d,f+16|0,(c[b+144>>2]|0)+(e*284|0)+16|0,f+32|0);e=e+1|0}while((e|0)<(c[b+136>>2]|0));i=f;return}function cj(d,e,f,g,h,i){d=d|0;e=e|0;f=f|0;g=g|0;h=h|0;i=i|0;var j=0,k=0,l=0,m=0;if((d|0)==(c[e+8>>2]|0))zl(e,f,g,h);else{l=b[e+52>>1]|0;j=c[d+12>>2]|0;a[e+52>>0]=0;a[e+53>>0]=0;On(d+16|0,e,f,g,h,i);a:do if((j|0)>1){m=d+24|0;do{if(a[e+54>>0]|0)break a;k=b[e+52>>1]|0;if(!((k&255)<<24>>24)){if((k&65535)>=256?(c[d+8>>2]&1|0)==0:0)break a}else{if((c[e+24>>2]|0)==1)break a;if(!(c[d+8>>2]&2))break a}a[e+52>>0]=0;a[e+53>>0]=0;On(m,e,f,g,h,i);m=m+8|0}while(m>>>0<(d+16+(j<<3)|0)>>>0)}while(0);a[e+52>>0]=l;a[e+53>>0]=(l&65535)>>>8}return}function dj(a,b,d,e){a=a|0;b=b|0;d=+d;e=e|0;switch(b|0){case 2:{if((e|0)<1){g[a+232>>2]=d;c[a+300>>2]=c[a+300>>2]|512;return}if((e|0)<3){g[a+264>>2]=d;c[a+300>>2]=c[a+300>>2]|32;return}if((e|0)==3){g[a+248>>2]=d;c[a+300>>2]=c[a+300>>2]|2048;return}if((e|0)>=6)return;g[a+280>>2]=d;c[a+300>>2]=c[a+300>>2]|128;return}case 3:{if((e|0)<1){g[a+212>>2]=d;c[a+300>>2]=c[a+300>>2]|1;return}if((e|0)!=3)return;g[a+228>>2]=d;c[a+300>>2]=c[a+300>>2]|4;return}case 4:{if((e|0)<1){g[a+244>>2]=d;c[a+300>>2]=c[a+300>>2]|256;return}if((e|0)<3){g[a+276>>2]=d;c[a+300>>2]=c[a+300>>2]|16;return}if((e|0)==3){g[a+260>>2]=d;c[a+300>>2]=c[a+300>>2]|1024;return}if((e|0)>=6)return;g[a+292>>2]=d;c[a+300>>2]=c[a+300>>2]|64;return}default:return}}function ej(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0;f=i;i=i+240|0;c[f+80>>2]=d;d=f+96|0;e=d+40|0;do{c[d>>2]=0;d=d+4|0}while((d|0)<(e|0));c[f+136>>2]=c[f+80>>2];if((Bc(0,b,f+136|0,f,f+96|0)|0)>=0){d=c[2359]|0;if((a[9510]|0)<1)c[2359]=d&-33;if(!(c[2371]|0)){e=c[2370]|0;c[2370]=f+152;c[2366]=f+152;c[2364]=f+152;c[2371]=80;c[2363]=f+152+80;Bc(9436,b,f+136|0,f,f+96|0)|0;if(e|0){Ob[c[9472>>2]&63](9436,0,0)|0;c[2370]=e;c[2371]=0;c[2363]=0;c[2366]=0;c[2364]=0}}else Bc(9436,b,f+136|0,f,f+96|0)|0;c[2359]=c[2359]|d&32}d=(a[9511]|0)==10;do if((c[2378]|0)<0){if(!d?(g=c[2364]|0,g>>>0<(c[2363]|0)>>>0):0){c[2364]=g+1;a[g>>0]=10;break}om(9436,10)|0}else{if(!d?(h=c[2364]|0,h>>>0<(c[2363]|0)>>>0):0){c[2364]=h+1;a[h>>0]=10;break}om(9436,10)|0}while(0);Va()}function fj(a,b,d){a=a|0;b=+b;d=d|0;var e=0,f=0.0,h=0.0,j=0.0,k=0.0,l=0;e=i;i=i+96|0;c[e+32>>2]=1065353216;c[e+32+4>>2]=0;c[e+32+4+4>>2]=0;c[e+32+4+8>>2]=0;c[e+32+4+12>>2]=0;c[e+32+20>>2]=1065353216;c[e+32+24>>2]=0;c[e+32+24+4>>2]=0;c[e+32+24+8>>2]=0;c[e+32+24+12>>2]=0;c[e+32+40>>2]=1065353216;l=e+32+44|0;c[l>>2]=0;c[l+4>>2]=0;c[l+8>>2]=0;c[l+12>>2]=0;c[l+16>>2]=0;mc[c[(c[a>>2]|0)+8>>2]&127](a,e+32|0,e+16|0,e);j=(+g[e>>2]-+g[e+16>>2])*.5;h=(+g[e+4>>2]-+g[e+16+4>>2])*.5;k=(+g[e+8>>2]-+g[e+16+8>>2])*.5;f=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);g[d>>2]=b*.0833333283662796*((h+f)*2.0*(h+f)*2.0+(k+f)*2.0*(k+f)*2.0);g[d+4>>2]=b*.0833333283662796*((j+f)*2.0*(j+f)*2.0+(k+f)*2.0*(k+f)*2.0);g[d+8>>2]=b*.0833333283662796*((j+f)*2.0*(j+f)*2.0+(h+f)*2.0*(h+f)*2.0);g[d+12>>2]=0.0;i=e;return}function gj(a,b,c){a=a|0;b=b|0;c=c|0;var d=0.0,e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0;d=+g[a+344>>2];if(!(d!=0.0))return;f=+g[a+348>>2];i=+g[a+352>>2];k=+g[a+356>>2];l=+g[b+4>>2]*i*d;h=+g[b+8>>2]*k*d;g[a+312>>2]=+g[a+312>>2]+ +g[b>>2]*f*d;g[a+316>>2]=+g[a+316>>2]+l;g[a+320>>2]=+g[a+320>>2]+h;f=+g[b>>2]*f;i=+g[b+4>>2]*i;k=+g[b+8>>2]*k;h=+g[c+4>>2];l=+g[c+8>>2];j=+g[c>>2];e=(+g[a+280>>2]*(h*k-l*i)+ +g[a+284>>2]*(l*f-j*k)+ +g[a+288>>2]*(j*i-h*f))*+g[a+548>>2];d=(+g[a+296>>2]*(h*k-l*i)+ +g[a+300>>2]*(l*f-j*k)+ +g[a+304>>2]*(j*i-h*f))*+g[a+552>>2];g[a+328>>2]=+g[a+328>>2]+(+g[a+264>>2]*(h*k-l*i)+ +g[a+268>>2]*(l*f-j*k)+ +g[a+272>>2]*(j*i-h*f))*+g[a+544>>2];g[a+332>>2]=+g[a+332>>2]+e;g[a+336>>2]=+g[a+336>>2]+d;return}function hj(a,b,d,e,f,h,j,k,l,m){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;k=k|0;l=l|0;m=m|0;var n=0;n=i;i=i+16|0;li(12859);+bc[c[(c[a>>2]|0)+44>>2]&3](a,b,d,e,f,h,j,k,l);+bc[c[(c[a>>2]|0)+48>>2]&3](a,b,d,e,f,h,j,k,l);+fc[c[(c[a>>2]|0)+36>>2]&1](a,b,d,k);m=c[2357]|0;a=(c[m+16>>2]|0)+-1|0;c[m+16>>2]=a;if(a|0){i=n;return 0.0}do if(c[m+4>>2]|0){tb(n|0,0)|0;a=c[6434]|0;g[m+8>>2]=+g[m+8>>2]+ +(((c[n+4>>2]|0)-(c[a+4>>2]|0)+(((c[n>>2]|0)-(c[a>>2]|0)|0)*1e6|0)-(c[m+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[m+16>>2]|0)){m=c[2357]|0;break}else{i=n;return 0.0}}while(0);c[2357]=c[m+20>>2];i=n;return 0.0}function ij(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0,i=0;f=c[b+212>>2]|0;if((f|0)==(c[b+216>>2]|0)?(i=f|0?f<<1:1,(f|0)<(i|0)):0){if(!i)h=0;else{c[6435]=(c[6435]|0)+1;f=yc((i<<2|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}h=f;f=c[b+212>>2]|0}if((f|0)>0){g=0;do{c[h+(g<<2)>>2]=c[(c[b+220>>2]|0)+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0))}g=c[b+220>>2]|0;if(g){if(a[b+224>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0);f=c[b+212>>2]|0}c[b+220>>2]=0}a[b+224>>0]=1;c[b+220>>2]=h;c[b+216>>2]=i}c[(c[b+220>>2]|0)+(f<<2)>>2]=d;c[b+212>>2]=f+1;if(!e)return;Pi(c[d+28>>2]|0,d);Pi(c[d+32>>2]|0,d);return}function jj(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0;e=c[a+4>>2]|0;if(e|0)gj(e,b,d);e=c[a>>2]|0;if(!e)return;m=+g[b>>2];k=+g[e+128>>2];l=+g[b+4>>2];j=+g[b+8>>2];f=+g[d+4>>2];o=+g[d+8>>2];n=+g[d>>2];i=+g[e+180>>2]*(j*f-l*o)+ +g[e+184>>2]*(m*o-j*n)+(l*n-m*f)*+g[e+188>>2];h=(j*f-l*o)*+g[e+196>>2]+(m*o-j*n)*+g[e+200>>2]+(l*n-m*f)*+g[e+204>>2];f=(j*f-l*o)*+g[e+212>>2]+(m*o-j*n)*+g[e+216>>2]+(l*n-m*f)*+g[e+220>>2];g[e+276>>2]=m*k+ +g[e+276>>2];g[e+280>>2]=k*l+ +g[e+280>>2];g[e+284>>2]=k*j+ +g[e+284>>2];g[e+292>>2]=i+ +g[e+292>>2];g[e+296>>2]=h+ +g[e+296>>2];g[e+300>>2]=f+ +g[e+300>>2];c[e+312>>2]=(c[e+312>>2]|0)+1;return}function kj(a,b,c){a=a|0;b=b|0;c=c|0;var d=0.0,e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0;v=+g[a+552>>2];u=+g[a+568>>2];t=+g[a+584>>2];s=+g[b>>2];r=+g[b+4>>2];q=+g[b+8>>2];o=+g[b+16>>2];n=+g[b+20>>2];m=+g[b+24>>2];k=+g[b+32>>2];i=+g[b+36>>2];f=+g[b+40>>2];j=+g[a+556>>2];h=+g[a+572>>2];e=+g[a+588>>2];x=+g[a+620>>2];w=+g[a+636>>2];d=+g[a+652>>2];p=x*+g[c>>2]+w*+g[c+4>>2]+d*+g[c+8>>2];l=x*+g[c+16>>2]+w*+g[c+20>>2]+d*+g[c+24>>2];d=x*+g[c+32>>2]+w*+g[c+36>>2]+d*+g[c+40>>2];d=+W(+((v*s+u*r+t*q)*p+(v*o+u*n+t*m)*l+(v*k+u*i+t*f)*d),+((s*j+r*h+q*e)*p+(o*j+n*h+m*e)*l+(k*j+i*h+f*e)*d));return +(d*+g[a+732>>2])}function lj(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0,h=0;a:do if((e|0)!=0&(b&3|0)!=0){f=e;while(1){if((a[b>>0]|0)==(d&255)<<24>>24)break a;b=b+1|0;e=f+-1|0;if((e|0)!=0&(b&3|0)!=0)f=e;else{f=e;e=(e|0)!=0;g=5;break}}}else{f=e;e=(e|0)!=0;g=5}while(0);b:do if((g|0)==5)if(e){if((a[b>>0]|0)!=(d&255)<<24>>24){e=_(d&255,16843009)|0;c:do if(f>>>0>3)while(1){h=c[b>>2]^e;if((h&-2139062144^-2139062144)&h+-16843009|0)break;b=b+4|0;f=f+-4|0;if(f>>>0<=3){g=11;break c}}else g=11;while(0);if((g|0)==11)if(!f){f=0;break}while(1){if((a[b>>0]|0)==(d&255)<<24>>24)break b;b=b+1|0;f=f+-1|0;if(!f){f=0;break}}}}else f=0;while(0);return (f|0?b:0)|0}function mj(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0;d=c[a+8>>2]|0;if((d|0)>0){f=0;do{e=c[(c[a+16>>2]|0)+(f<<2)>>2]|0;if(c[e+236>>2]&2){g=Eb[c[(c[e>>2]|0)+16>>2]&127](e)|0;g=Ob[c[(c[b>>2]|0)+16>>2]&63](b,g,1)|0;d=Ob[c[(c[e>>2]|0)+20>>2]&63](e,c[g+8>>2]|0,b)|0;yb[c[(c[b>>2]|0)+20>>2]&31](b,g,d,1497645650,e);d=c[a+8>>2]|0}f=f+1|0}while((f|0)<(d|0))}if((c[a+212>>2]|0)<=0)return;d=0;do{g=c[(c[a+220>>2]|0)+(d<<2)>>2]|0;e=Eb[c[(c[g>>2]|0)+36>>2]&127](g)|0;e=Ob[c[(c[b>>2]|0)+16>>2]&63](b,e,1)|0;f=Ob[c[(c[g>>2]|0)+40>>2]&63](g,c[e+8>>2]|0,b)|0;yb[c[(c[b>>2]|0)+20>>2]&31](b,e,f,1397641027,g);d=d+1|0}while((d|0)<(c[a+212>>2]|0));return}function nj(a){a=a|0;var b=0.0,d=0,e=0,f=0,h=0;e=i;i=i+32|0;c[a+32>>2]=1566444395;c[a+36>>2]=1566444395;c[a+40>>2]=1566444395;g[a+44>>2]=0.0;c[a+48>>2]=-581039253;c[a+52>>2]=-581039253;c[a+56>>2]=-581039253;g[a+60>>2]=0.0;if((c[a+16>>2]|0)<=0){i=e;return}d=0;do{f=c[a+24>>2]|0;h=c[f+(d*80|0)+64>>2]|0;mc[c[(c[h>>2]|0)+8>>2]&127](h,f+(d*80|0)|0,e+16|0,e);b=+g[e+16>>2];if(+g[a+32>>2]>b)g[a+32>>2]=b;b=+g[e>>2];if(+g[a+48>>2]>2]=b;b=+g[e+16+4>>2];if(+g[a+36>>2]>b)g[a+36>>2]=b;b=+g[e+4>>2];if(+g[a+52>>2]>2]=b;b=+g[e+16+8>>2];if(+g[a+40>>2]>b)g[a+40>>2]=b;b=+g[e+8>>2];if(+g[a+56>>2]>2]=b;d=d+1|0}while((d|0)<(c[a+16>>2]|0));i=e;return}function oj(a,b,d){a=a|0;b=+b;d=d|0;var e=0,f=0.0,h=0.0,j=0.0,k=0;e=i;i=i+96|0;j=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);c[e+32>>2]=1065353216;c[e+32+4>>2]=0;c[e+32+4+4>>2]=0;c[e+32+4+8>>2]=0;c[e+32+4+12>>2]=0;c[e+32+20>>2]=1065353216;c[e+32+24>>2]=0;c[e+32+24+4>>2]=0;c[e+32+24+8>>2]=0;c[e+32+24+12>>2]=0;c[e+32+40>>2]=1065353216;k=e+32+44|0;c[k>>2]=0;c[k+4>>2]=0;c[k+8>>2]=0;c[k+12>>2]=0;c[k+16>>2]=0;mc[c[(c[a>>2]|0)+8>>2]&127](a,e+32|0,e+16|0,e);h=(j+(+g[e>>2]-+g[e+16>>2])*.5)*2.0;f=(j+(+g[e+4>>2]-+g[e+16+4>>2])*.5)*2.0;j=(j+(+g[e+8>>2]-+g[e+16+8>>2])*.5)*2.0;g[d>>2]=b*.0833333283662796*(f*f+j*j);g[d+4>>2]=b*.0833333283662796*(h*h+j*j);g[d+8>>2]=b*.0833333283662796*(h*h+f*f);g[d+12>>2]=0.0;i=e;return}function pj(b){b=b|0;var d=0;d=c[b+72>>2]|0;if(d|0){if(a[b+76>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+72>>2]=0}a[b+76>>0]=1;c[b+72>>2]=0;c[b+64>>2]=0;c[b+68>>2]=0;d=c[b+52>>2]|0;if(d|0){if(a[b+56>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+52>>2]=0}a[b+56>>0]=1;c[b+52>>2]=0;c[b+44>>2]=0;c[b+48>>2]=0;d=c[b+32>>2]|0;if(d|0){if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+32>>2]=0}a[b+36>>0]=1;c[b+32>>2]=0;c[b+24>>2]=0;c[b+28>>2]=0;d=c[b+12>>2]|0;if(!d){a[b+16>>0]=1;c[b+12>>2]=0;c[b+4>>2]=0;b=b+8|0;c[b>>2]=0;return}if(a[b+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+12>>2]=0;a[b+16>>0]=1;c[b+12>>2]=0;c[b+4>>2]=0;b=b+8|0;c[b>>2]=0;return}function qj(a,b){a=a|0;b=+b;var d=0,e=0,f=0,h=0.0,i=0.0,j=0.0,k=0,l=0,m=0,n=0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0;e=c[a+732>>2]|0;if((e|0)<=0)return;a=c[a+740>>2]|0;d=0;do{n=c[a+(d*52|0)+8>>2]|0;f=c[a+(d*52|0)+12>>2]|0;s=+g[n+40>>2];q=+g[n+44>>2];i=+g[n+48>>2];k=a+(d*52|0)+36|0;r=+g[k>>2];m=a+(d*52|0)+40|0;p=+g[m>>2];l=a+(d*52|0)+44|0;o=+g[l>>2];j=-(+g[a+(d*52|0)+32>>2]*((s-+g[f+40>>2])*r+(q-+g[f+44>>2])*p+(i-+g[f+48>>2])*o)*b);h=+g[n+88>>2]*j;g[n+40>>2]=s+r*h;g[n+44>>2]=q+p*h;g[n+48>>2]=o*h+i;j=+g[f+88>>2]*j;i=j*+g[m>>2];h=j*+g[l>>2];g[f+40>>2]=+g[f+40>>2]-+g[k>>2]*j;g[f+44>>2]=+g[f+44>>2]-i;g[f+48>>2]=+g[f+48>>2]-h;d=d+1|0}while((d|0)!=(e|0));return}function rj(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0;e=c[b+12>>2]|0;if(!e)return;if(!(a[b+8>>0]|0))return;f=c[d+4>>2]|0;if((f|0)==(c[d+8>>2]|0)?(h=f|0?f<<1:1,(f|0)<(h|0)):0){if(!h)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((h<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[d+4>>2]|0}if((f|0)>0){g=0;do{c[e+(g<<2)>>2]=c[(c[d+12>>2]|0)+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0))}g=c[d+12>>2]|0;if(g){if(a[d+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0);f=c[d+4>>2]|0}c[d+12>>2]=0}a[d+16>>0]=1;c[d+12>>2]=e;c[d+8>>2]=h;e=c[b+12>>2]|0}c[(c[d+12>>2]|0)+(f<<2)>>2]=e;c[d+4>>2]=f+1;return}function sj(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var g=0,h=0,i=0,j=0;g=c[b+328>>2]|0;if((g|0)==(c[b+332>>2]|0)?(j=g|0?g<<1:1,(g|0)<(j|0)):0){if(!j)i=0;else{c[6435]=(c[6435]|0)+1;g=yc((j<<2|3)+16|0)|0;if(!g)g=0;else{c[(g+4+15&-16)+-4>>2]=g;g=g+4+15&-16}i=g;g=c[b+328>>2]|0}if((g|0)>0){h=0;do{c[i+(h<<2)>>2]=c[(c[b+336>>2]|0)+(h<<2)>>2];h=h+1|0}while((h|0)!=(g|0))}h=c[b+336>>2]|0;if(h){if(a[b+340>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0);g=c[b+328>>2]|0}c[b+336>>2]=0}a[b+340>>0]=1;c[b+336>>2]=i;c[b+332>>2]=j}c[(c[b+336>>2]|0)+(g<<2)>>2]=d;c[b+328>>2]=g+1;c[d+284>>2]=c[b+452>>2];Pg(b,d,e,f);return}function tj(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0;e=c[b+20>>2]|0;if(!e)return;if(!(a[b+16>>0]|0))return;f=c[d+4>>2]|0;if((f|0)==(c[d+8>>2]|0)?(h=f|0?f<<1:1,(f|0)<(h|0)):0){if(!h)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((h<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[d+4>>2]|0}if((f|0)>0){g=0;do{c[e+(g<<2)>>2]=c[(c[d+12>>2]|0)+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0))}g=c[d+12>>2]|0;if(g){if(a[d+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0);f=c[d+4>>2]|0}c[d+12>>2]=0}a[d+16>>0]=1;c[d+12>>2]=e;c[d+8>>2]=h;e=c[b+20>>2]|0}c[(c[d+12>>2]|0)+(f<<2)>>2]=e;c[d+4>>2]=f+1;return}function uj(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;j=+g[a+24>>2];k=+g[a+28>>2];i=+g[a+32>>2];f=j*+g[b>>2]+k*+g[b+4>>2]+i*+g[b+8>>2];h=+g[a+20>>2];if(f>h){g[a+20>>2]=f;c[a+4>>2]=c[b>>2];c[a+4+4>>2]=c[b+4>>2];c[a+4+8>>2]=c[b+8>>2];c[a+4+12>>2]=c[b+12>>2]}else f=h;h=j*+g[b+16>>2]+k*+g[b+20>>2]+i*+g[b+24>>2];if(h>f){g[a+20>>2]=h;c[a+4>>2]=c[b+16>>2];c[a+4+4>>2]=c[b+16+4>>2];c[a+4+8>>2]=c[b+16+8>>2];c[a+4+12>>2]=c[b+16+12>>2]}else h=f;f=j*+g[b+32>>2]+k*+g[b+36>>2]+i*+g[b+40>>2];if(!(f>h))return;g[a+20>>2]=f;c[a+4>>2]=c[b+32>>2];c[a+4+4>>2]=c[b+32+4>>2];c[a+4+8>>2]=c[b+32+8>>2];c[a+4+12>>2]=c[b+32+12>>2];return}function vj(b){b=b|0;var d=0,e=0,f=0,h=0.0;e=i;i=i+96|0;a[b+88>>0]=1;if((a[22568]|0)==0?Wa(22568)|0:0){c[6139]=1065353216;c[6140]=0;c[6141]=0;c[6142]=0;c[6143]=0;c[6144]=1065353216;c[6145]=0;c[6146]=0;c[6147]=0;c[6148]=0;c[6149]=1065353216;g[6150]=0.0;c[6151]=-1082130432;c[6152]=0;c[6153]=0;c[6154]=0;c[6155]=0;c[6156]=-1082130432;c[6157]=0;c[6158]=0;c[6159]=0;c[6160]=0;c[6161]=-1082130432;g[6162]=0.0;_a(22568)}d=e;f=d+96|0;do{c[d>>2]=0;d=d+4|0}while((d|0)<(f|0));mc[c[(c[b>>2]|0)+76>>2]&127](b,24556,e,6);h=+g[b+44>>2];g[b+72>>2]=+g[e>>2]+h;g[b+56>>2]=+g[e+48>>2]-h;g[b+76>>2]=+g[e+20>>2]+h;g[b+60>>2]=+g[e+68>>2]-h;g[b+80>>2]=+g[e+40>>2]+h;g[b+64>>2]=+g[e+88>>2]-h;i=e;return}function wj(d,e){d=d|0;e=e|0;var f=0,g=0,h=0,j=0;j=i;i=i+64|0;h=c[d>>2]|0;g=d+(c[h+-8>>2]|0)|0;h=c[h+-4>>2]|0;c[j>>2]=e;c[j+4>>2]=d;c[j+8>>2]=2776;d=j+12|0;f=d+40|0;do{c[d>>2]=0;d=d+4|0}while((d|0)<(f|0));b[j+12+40>>1]=0;a[j+12+42>>0]=0;a:do if((h|0)==(e|0)){c[j+48>>2]=1;Qb[c[(c[e>>2]|0)+20>>2]&7](e,j,g,g,1,0);d=(c[j+24>>2]|0)==1?g:0}else{yb[c[(c[h>>2]|0)+24>>2]&31](h,j,g,1,0);switch(c[j+36>>2]|0){case 0:{d=((c[j+40>>2]|0)==1?(c[j+28>>2]|0)==1:0)&(c[j+32>>2]|0)==1?c[j+20>>2]|0:0;break a}case 1:break;default:{d=0;break a}}if((c[j+24>>2]|0)!=1?!(((c[j+40>>2]|0)==0?(c[j+28>>2]|0)==1:0)&(c[j+32>>2]|0)==1):0){d=0;break}d=c[j+16>>2]|0}while(0);i=j;return d|0}function xj(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;j=+g[a+88>>2];k=+g[a+92>>2];i=+g[a+96>>2];f=j*+g[b>>2]+k*+g[b+4>>2]+i*+g[b+8>>2];h=+g[a+84>>2];if(f>h){g[a+84>>2]=f;c[a+4>>2]=c[b>>2];c[a+4+4>>2]=c[b+4>>2];c[a+4+8>>2]=c[b+8>>2];c[a+4+12>>2]=c[b+12>>2]}else f=h;h=j*+g[b+16>>2]+k*+g[b+20>>2]+i*+g[b+24>>2];if(h>f){g[a+84>>2]=h;c[a+4>>2]=c[b+16>>2];c[a+4+4>>2]=c[b+16+4>>2];c[a+4+8>>2]=c[b+16+8>>2];c[a+4+12>>2]=c[b+16+12>>2]}else h=f;f=j*+g[b+32>>2]+k*+g[b+36>>2]+i*+g[b+40>>2];if(!(f>h))return;g[a+84>>2]=f;c[a+4>>2]=c[b+32>>2];c[a+4+4>>2]=c[b+32+4>>2];c[a+4+8>>2]=c[b+32+8>>2];c[a+4+12>>2]=c[b+32+12>>2];return}function yj(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0;while(1){j=c[a+12>>2]|0;k=c[j+(((b+d|0)/2|0)<<3)>>2]|0;e=b;f=d;while(1){while(1){h=e+1|0;if((c[j+(e<<3)>>2]|0)<(k|0))e=h;else{i=f;break}}while(1){g=j+(i<<3)|0;f=i+-1|0;if((k|0)<(c[g>>2]|0))i=f;else break}if((e|0)>(i|0))f=i;else{e=j+(e<<3)|0;l=c[e>>2]|0;j=c[e+4>>2]|0;m=c[g+4>>2]|0;c[e>>2]=c[g>>2];c[e+4>>2]=m;e=(c[a+12>>2]|0)+(i<<3)|0;c[e>>2]=l;c[e+4>>2]=j;e=h}if((e|0)>(f|0))break;j=c[a+12>>2]|0}if((f|0)>(b|0))yj(a,b,f);if((e|0)<(d|0))b=e;else break}return}function zj(a,b,e){a=a|0;b=b|0;e=e|0;kh(a,b,e)|0;c[b+276>>2]=c[a+1316>>2];c[b+324>>2]=c[a+1364>>2];c[b+252>>2]=d[a+1309>>0];c[b+300>>2]=c[a+1340>>2];c[b+280>>2]=c[a+1320>>2];c[b+328>>2]=c[a+1368>>2];c[b+256>>2]=d[a+1310>>0];c[b+304>>2]=c[a+1344>>2];c[b+284>>2]=c[a+1324>>2];c[b+332>>2]=c[a+1372>>2];c[b+260>>2]=d[a+1311>>0];c[b+308>>2]=c[a+1348>>2];c[b+288>>2]=c[a+1328>>2];c[b+336>>2]=c[a+1376>>2];c[b+264>>2]=d[a+1312>>0];c[b+312>>2]=c[a+1352>>2];c[b+292>>2]=c[a+1332>>2];c[b+340>>2]=c[a+1380>>2];c[b+268>>2]=d[a+1313>>0];c[b+316>>2]=c[a+1356>>2];c[b+296>>2]=c[a+1336>>2];c[b+344>>2]=c[a+1384>>2];c[b+272>>2]=d[a+1314>>0];c[b+320>>2]=c[a+1360>>2];return 12539}function Aj(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0;i=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);m=i+ +g[a+28>>2];k=i+ +g[a+32>>2];i=i+ +g[a+36>>2];u=+N(+(+g[b>>2]));t=+N(+(+g[b+4>>2]));s=+N(+(+g[b+8>>2]));q=+N(+(+g[b+16>>2]));p=+N(+(+g[b+20>>2]));o=+N(+(+g[b+24>>2]));l=+N(+(+g[b+32>>2]));j=+N(+(+g[b+36>>2]));h=+N(+(+g[b+40>>2]));r=+g[b+48>>2];n=+g[b+52>>2];f=+g[b+56>>2];g[d>>2]=r-(m*u+k*t+i*s);g[d+4>>2]=n-(m*q+k*p+i*o);g[d+8>>2]=f-(m*l+k*j+i*h);g[d+12>>2]=0.0;g[e>>2]=m*u+k*t+i*s+r;g[e+4>>2]=m*q+k*p+i*o+n;g[e+8>>2]=m*l+k*j+i*h+f;g[e+12>>2]=0.0;return}function Bj(a,c,d,e,f,h){a=a|0;c=c|0;d=+d;e=+e;f=+f;h=h|0;var i=0,j=0;d=(d-+g[a+8>>2])*+g[a+40>>2];e=(e-+g[a+12>>2])*+g[a+44>>2];f=(f-+g[a+16>>2])*+g[a+48>>2];do if(!(d<=0.0)){i=b[a+6>>1]|0;j=b[a+4>>1]|0;if(!(d>=+(i&65535))){i=j&(~~d&65535)&65535|h;break}else{i=j&i&65535|h;break}}else i=h;while(0);b[c>>1]=i;do if(!(e<=0.0)){i=b[a+6>>1]|0;j=b[a+4>>1]|0;if(!(e>=+(i&65535))){i=j&(~~e&65535)&65535|h;break}else{i=j&i&65535|h;break}}else i=h;while(0);b[c+2>>1]=i;if(f<=0.0){h=h&65535;c=c+4|0;b[c>>1]=h;return}j=b[a+6>>1]|0;i=b[a+4>>1]|0;if(!(f>=+(j&65535))){h=i&(~~f&65535)&65535|h;h=h&65535;c=c+4|0;b[c>>1]=h;return}else{h=i&j&65535|h;h=h&65535;c=c+4|0;b[c>>1]=h;return}}function Cj(b){b=b|0;var d=0;c[b>>2]=8520;if(c[b+108>>2]|0){d=c[b+112>>2]|0;Ab[c[c[d>>2]>>2]&255](d);d=c[b+112>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+108>>2]|0;Ab[c[c[d>>2]>>2]&255](d);d=c[b+108>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}}d=c[b+88>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+84>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+80>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+60>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}if(!(a[b+100>>0]|0))return;d=c[b+92>>2]|0;Ab[c[c[d>>2]>>2]&255](d);d=c[b+92>>2]|0;if(!d)return;c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);return}function Dj(b,d){b=b|0;d=d|0;var e=0,f=0,g=0,h=0;e=c[b+76>>2]|0;if(!e)return;f=c[d+4>>2]|0;if((f|0)==(c[d+8>>2]|0)?(h=f|0?f<<1:1,(f|0)<(h|0)):0){if(!h)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((h<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[d+4>>2]|0}if((f|0)>0){g=0;do{c[e+(g<<2)>>2]=c[(c[d+12>>2]|0)+(g<<2)>>2];g=g+1|0}while((g|0)!=(f|0))}g=c[d+12>>2]|0;if(g){if(a[d+16>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0);f=c[d+4>>2]|0}c[d+12>>2]=0}a[d+16>>0]=1;c[d+12>>2]=e;c[d+8>>2]=h;e=c[b+76>>2]|0}c[(c[d+12>>2]|0)+(f<<2)>>2]=e;c[d+4>>2]=f+1;return}function Ej(a,b,d,e){a=a|0;b=b|0;d=+d;e=+e;var f=0,h=0.0,i=0.0,j=0.0,l=0,m=0.0,n=0.0,o=0.0;j=+Q(+d);i=+R(+d);f=c[b+444>>2]|0;l=+N(+j)>1.1920928955078125e-07;d=(c[k>>2]=f,+g[k>>2]);if(l){m=+g[b+448>>2];m=+O(+((i*i/(j*j)+1.0)/(1.0/(m*m)+i*i/(j*j)/(d*d))));d=i*i;h=j*j;f=(g[k>>2]=m,c[k>>2]|0)}else{d=i*i;h=j*j}m=+O(+(h+0.0+d));n=(c[k>>2]=f,+g[k>>2])*.5;m=+R(+n)/m;n=+Q(+n);o=n*e+j*m*0.0-i*m*-0.0;h=n*0.0-i*m*e-m*0.0*0.0;d=n*0.0+m*0.0*0.0-j*m*e;e=-(m*0.0*e)-j*m*0.0-i*m*-0.0;g[a>>2]=i*m*h+(n*o+e*-(m*0.0))-d*-(j*m);g[a+4>>2]=d*-(m*0.0)+(n*h+e*-(j*m))-i*m*o;g[a+8>>2]=o*-(j*m)+(i*m*e+n*d)-h*-(m*0.0);g[a+12>>2]=0.0;return}function Fj(a,d,f,h){a=a|0;d=d|0;f=f|0;h=h|0;var i=0,j=0,k=0,l=0,m=0;i=c[a+108>>2]|0;if(i|0){mc[c[(c[i>>2]|0)+28>>2]&127](i,d,f,h);return}i=b[a+56>>1]|0;if((i&65535)<<1>>>0<=1)return;k=1;m=1;do{j=c[a+68>>2]|0;if(b[j+(k<<2)>>1]&1){l=c[a+60>>2]|0;k=e[j+(k<<2)+2>>1]|0;if(!(+g[d>>2]>+g[l+(k<<6)+32>>2])?!(+g[f>>2]<+g[l+(k<<6)+16>>2]):0)j=1;else j=0;if(!(!(+g[d+8>>2]>+g[l+(k<<6)+40>>2])?!(+g[f+8>>2]<+g[l+(k<<6)+24>>2]):0))j=0;if(!(+g[d+4>>2]>+g[l+(k<<6)+36>>2])?!(+g[f+4>>2]<+g[l+(k<<6)+20>>2]|j^1):0){Zb[c[(c[h>>2]|0)+8>>2]&31](h,l+(k<<6)|0)|0;i=b[a+56>>1]|0}}m=m+1<<16>>16;k=m&65535}while(k>>>0<((i&65535)<<1|1)>>>0);return}function Gj(a,b,d){a=a|0;b=+b;d=+d;var e=0,f=0,h=0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0,q=0.0;f=c[a+732>>2]|0;if((f|0)<=0)return;a=c[a+740>>2]|0;e=0;do{d=+g[a+(e*52|0)+24>>2];if(d>0.0?(p=c[a+(e*52|0)+8>>2]|0,h=c[a+(e*52|0)+12>>2]|0,i=+g[p+8>>2],j=+g[h+8>>2]-i,k=+g[p+12>>2],l=+g[h+12>>2]-k,m=+g[p+16>>2],n=+g[h+16>>2]-m,o=+g[a+(e*52|0)+28>>2],o+(j*j+l*l+n*n)>1.1920928955078125e-07):0){d=(o-(j*j+l*l+n*n))/(d*(o+(j*j+l*l+n*n)))*b;q=d*+g[p+88>>2];g[p+8>>2]=i-j*q;g[p+12>>2]=k-l*q;g[p+16>>2]=m-n*q;d=d*+g[h+88>>2];g[h+8>>2]=+g[h+8>>2]+j*d;g[h+12>>2]=l*d+ +g[h+12>>2];g[h+16>>2]=n*d+ +g[h+16>>2]}e=e+1|0}while((e|0)!=(f|0));return}function Hj(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0;e=i;i=i+96|0;c[e+32>>2]=1065353216;c[e+32+4>>2]=0;c[e+32+4+4>>2]=0;c[e+32+4+8>>2]=0;c[e+32+4+12>>2]=0;c[e+32+20>>2]=1065353216;c[e+32+24>>2]=0;c[e+32+24+4>>2]=0;c[e+32+24+8>>2]=0;c[e+32+24+12>>2]=0;c[e+32+40>>2]=1065353216;n=e+32+44|0;c[n>>2]=0;c[n+4>>2]=0;c[n+8>>2]=0;c[n+12>>2]=0;c[n+16>>2]=0;mc[c[(c[a>>2]|0)+8>>2]&127](a,e+32|0,e+16|0,e);l=+g[e>>2];m=+g[e+16>>2];j=+g[e+4>>2];k=+g[e+16+4>>2];f=+g[e+8>>2];h=+g[e+16+8>>2];g[d>>2]=+O(+((l-m)*(l-m)+(j-k)*(j-k)+(f-h)*(f-h)))*.5;g[b>>2]=(m+l)*.5;g[b+4>>2]=(k+j)*.5;g[b+8>>2]=(h+f)*.5;g[b+12>>2]=0.0;i=e;return}function Ij(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0;c[a+4>>2]=c[b+24>>2];e=c[b>>2]|0;c[a+8>>2]=e;if(d){c[a+52>>2]=c[b+8>>2];c[a+52+4>>2]=c[b+8+4>>2];c[a+52+8>>2]=c[b+8+8>>2];c[a+52+12>>2]=c[b+8+12>>2]}else{k=+g[b+8>>2];j=+g[b+12>>2];i=+g[b+16>>2];h=+g[e+20>>2]*k+ +g[e+24>>2]*j+ +g[e+28>>2]*i;f=+g[e+36>>2]*k+ +g[e+40>>2]*j+ +g[e+44>>2]*i;g[a+52>>2]=+g[e+4>>2]*k+ +g[e+8>>2]*j+ +g[e+12>>2]*i;g[a+56>>2]=h;g[a+60>>2]=f;g[a+64>>2]=0.0}k=+g[b+24>>2];g[a+68>>2]=(1.0-k)*+g[a+20>>2]+ +g[a+36>>2]*k;g[a+72>>2]=(1.0-k)*+g[a+24>>2]+ +g[a+40>>2]*k;g[a+76>>2]=(1.0-k)*+g[a+28>>2]+ +g[a+44>>2]*k;return +(+g[b+24>>2])}function Jj(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0.0,h=0.0,i=0.0,j=0.0,k=0;f=+g[b>>2];h=+g[b+16>>2];j=f>2];if((j+g[a+24>>2])return;k=f>h?b:b+16|0;if(+g[(+g[k>>2]>i?k:b+32|0)>>2]<+g[a+8>>2])return;f=+g[b+8>>2];h=+g[b+24>>2];j=f>2];if((j+g[a+32>>2])return;k=f>h?b+8|0:b+24|0;if(+g[(+g[k>>2]>i?k:b+40|0)>>2]<+g[a+16>>2])return;f=+g[b+4>>2];h=+g[b+20>>2];j=f>2];if((j+g[a+28>>2])return;k=f>h?b+4|0:b+20|0;if(+g[(+g[k>>2]>i?k:b+36|0)>>2]<+g[a+12>>2])return;k=c[a+4>>2]|0;mc[c[(c[k>>2]|0)+8>>2]&127](k,b,d,e);return}function Kj(b,d,e,f){b=b|0;d=d|0;e=e|0;f=+f;var h=0,j=0.0,k=0.0,l=0.0;h=i;i=i+16|0;g[b+32>>2]=f;c[b+8>>2]=c[d>>2];c[b+8+4>>2]=c[d+4>>2];c[b+8+8>>2]=c[d+8>>2];c[b+8+12>>2]=c[d+12>>2];j=+g[b+28>>2];l=+g[e+4>>2]-j*+g[d+4>>2];k=+g[e+8>>2]-j*+g[d+8>>2];g[h>>2]=+g[e>>2]-+g[d>>2]*j;g[h+4>>2]=l;g[h+8>>2]=k;g[h+12>>2]=0.0;f=+g[b+24>>2]+j+f;g[b+32>>2]=f;if(!(f<0.0)){b=b+4|0;b=c[b>>2]|0;e=c[b>>2]|0;e=e+16|0;e=c[e>>2]|0;hc[e&15](b,d,h,f);i=h;return}a[b+36>>0]=1;b=b+4|0;b=c[b>>2]|0;e=c[b>>2]|0;e=e+16|0;e=c[e>>2]|0;hc[e&15](b,d,h,f);i=h;return}function Lj(b){b=b|0;var d=0,e=0,f=0,g=0,h=0;c[b>>2]=6228;d=c[b+8>>2]|0;e=c[d+8>>2]|0;if((e|0)>0){g=0;do{f=c[(c[d+16>>2]|0)+(g*12|0)+8>>2]|0;if(f|0){Ab[c[c[f>>2]>>2]&255](f);h=c[b+4>>2]|0;Cb[c[(c[h>>2]|0)+60>>2]&127](h,f)}g=g+1|0}while((g|0)!=(e|0));d=c[b+8>>2]|0}$h(d);d=c[b+8>>2]|0;Ab[c[c[d>>2]>>2]&255](d);d=c[b+8>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}d=c[b+24>>2]|0;if(!d){a[b+28>>0]=1;c[b+24>>2]=0;c[b+16>>2]=0;h=b+20|0;c[h>>2]=0;return}if(a[b+28>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+24>>2]=0;a[b+28>>0]=1;c[b+24>>2]=0;c[b+16>>2]=0;h=b+20|0;c[h>>2]=0;return}function Mj(a,b){a=a|0;b=b|0;var d=0,e=0.0,f=0.0,h=0.0,j=0.0,k=0.0,l=0.0,m=0.0;d=i;i=i+64|0;c[d+4>>2]=0;c[d+4+4>>2]=0;c[d+24>>2]=0;c[d+24+4>>2]=0;c[d+44>>2]=0;c[d+44+4>>2]=0;c[d+44+8>>2]=0;c[d+44+12>>2]=0;c[d+44+16>>2]=0;j=+g[b>>2];f=+g[b+4>>2];m=+g[b+8>>2];k=+g[b+12>>2];h=j*(2.0/(j*j+f*f+m*m+k*k));e=f*(2.0/(j*j+f*f+m*m+k*k));l=m*(2.0/(j*j+f*f+m*m+k*k));g[d>>2]=1.0-(f*e+m*l);g[d+4>>2]=j*e-k*l;g[d+8>>2]=j*l+k*e;g[d+12>>2]=0.0;g[d+16>>2]=j*e+k*l;g[d+20>>2]=1.0-(j*h+m*l);g[d+24>>2]=f*l-k*h;g[d+28>>2]=0.0;g[d+32>>2]=j*l-k*e;g[d+36>>2]=f*l+k*h;g[d+40>>2]=1.0-(j*h+f*e);g[d+44>>2]=0.0;Pd(a,d);i=d;return}function Nj(b,d,e){b=b|0;d=d|0;e=e|0;var f=0;while(1){b=yc(152)|0;if(b|0){f=6;break}b=c[6564]|0;c[6564]=b+0;if(!b){f=5;break}jc[b&3]()}if((f|0)==5){e=Ya(4)|0;c[e>>2]=9640;pb(e|0,2800,251)}else if((f|0)==6){c[b>>2]=4816;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;c[b+72>>2]=0;c[b+100>>2]=e;g[b+104>>2]=0.0;a[b+148>>0]=1;c[b+144>>2]=0;c[b+136>>2]=0;c[b+140>>2]=0;c[b+116>>2]=d;c[b+120>>2]=0;c[b+124>>2]=2;c[b+128>>2]=1;g[b+112>>2]=0.0;g[b+108>>2]=0.0;return b|0}return 0}function Oj(){var b=0;c[6435]=(c[6435]|0)+1;b=yc(215)|0;if(!b)b=0;else{c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16}c[b>>2]=4756;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;a[b+40>>0]=1;c[b+36>>2]=0;c[b+28>>2]=0;c[b+32>>2]=0;a[b+60>>0]=1;c[b+56>>2]=0;c[b+48>>2]=0;c[b+52>>2]=0;a[b+80>>0]=1;c[b+76>>2]=0;c[b+68>>2]=0;c[b+72>>2]=0;a[b+100>>0]=1;c[b+96>>2]=0;c[b+88>>2]=0;c[b+92>>2]=0;a[b+120>>0]=1;c[b+116>>2]=0;c[b+108>>2]=0;c[b+112>>2]=0;a[b+140>>0]=1;c[b+136>>2]=0;c[b+128>>2]=0;c[b+132>>2]=0;a[b+160>>0]=1;c[b+156>>2]=0;c[b+148>>2]=0;c[b+152>>2]=0;a[b+180>>0]=1;c[b+176>>2]=0;c[b+168>>2]=0;c[b+172>>2]=0;c[b+192>>2]=0;return b|0}function Pj(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,g=0;if((c[d+60>>2]|0)==2){f=c[d+48>>2]|0;hh(b+64|0,f)|0;g=c[b+68>>2]|0;if(g|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+68>>2]=f;c[b+76>>2]=(c[b+76>>2]|0)+-1}else{f=c[d+48>>2]|0;hh(b+4|0,f)|0;g=c[b+8>>2]|0;if(g|0){c[6436]=(c[6436]|0)+1;hd(c[g+-4>>2]|0)}c[b+8>>2]=f;c[b+16>>2]=(c[b+16>>2]|0)+-1}f=c[d+52>>2]|0;g=c[d+56>>2]|0;if(!f)c[b+124+(c[d+60>>2]<<2)>>2]=g;else c[f+56>>2]=g;f=c[d+56>>2]|0;if(f|0)c[f+52>>2]=c[d+52>>2];g=c[b+136>>2]|0;ic[c[(c[g>>2]|0)+16>>2]&127](g,d,e);c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0);a[b+194>>0]=1;return}function Qj(a,b,d,e){a=a|0;b=b|0;d=d|0;e=e|0;var f=0,g=0;f=i;i=i+96|0;g=c[b+192>>2]|0;c[f+64>>2]=0;c[f+64+4>>2]=g;c[f+64+8>>2]=b;c[f+64+12>>2]=b+4;c[f+64+16>>2]=-1;c[f+64+20>>2]=-1;b=c[d+192>>2]|0;c[f+40>>2]=0;c[f+40+4>>2]=b;c[f+40+8>>2]=d;c[f+40+12>>2]=d+4;c[f+40+16>>2]=-1;c[f+40+20>>2]=-1;b=c[a+24>>2]|0;b=Ib[c[(c[b>>2]|0)+8>>2]&31](b,f+64|0,f+40|0,0)|0;if(!b){i=f;return}c[f+4>>2]=0;c[f+8>>2]=f+64;c[f+12>>2]=f+40;c[f>>2]=5976;c[f+32>>2]=e;yb[c[(c[b>>2]|0)+8>>2]&31](b,f+64|0,f+40|0,a+28|0,f);Ab[c[c[b>>2]>>2]&255](b);g=c[a+24>>2]|0;Cb[c[(c[g>>2]|0)+60>>2]&127](g,b);i=f;return}function Rj(a,b,d){a=a|0;b=+b;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0;e=+g[a+28>>2];i=+g[a+32>>2];h=+g[a+36>>2];j=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);f=+Sb[c[(c[a>>2]|0)+48>>2]&15](a);h=+Sb[c[(c[a>>2]|0)+48>>2]&15](a)+h;switch(c[a+52>>2]|0){case 0:{j=b*.25*(f+i)*(f+i)+b/12.0*(j+e)*(j+e)*4.0;g[d>>2]=b*.5*(f+i)*(f+i);g[d+4>>2]=j;g[d+8>>2]=j;g[d+12>>2]=0.0;return}case 2:{g[d>>2]=b*.25*(j+e)*(j+e)+b/12.0*h*h*4.0;g[d+4>>2]=b*.25*(j+e)*(j+e)+b/12.0*h*h*4.0;g[d+8>>2]=b*.5*(j+e)*(j+e);g[d+12>>2]=0.0;return}default:{i=b*.25*(j+e)*(j+e)+b/12.0*(f+i)*(f+i)*4.0;g[d>>2]=i;g[d+4>>2]=b*.5*(j+e)*(j+e);g[d+8>>2]=i;g[d+12>>2]=0.0;return}}}function Sj(b,d){b=b|0;d=d|0;c[b+8>>2]=0;c[b>>2]=6292;a[b+28>>0]=1;c[b+24>>2]=0;c[b+16>>2]=0;c[b+20>>2]=0;c[b+32>>2]=1566444395;c[b+36>>2]=1566444395;c[b+40>>2]=1566444395;g[b+44>>2]=0.0;c[b+48>>2]=-581039253;c[b+52>>2]=-581039253;c[b+56>>2]=-581039253;g[b+60>>2]=0.0;c[b+64>>2]=0;c[b+68>>2]=1;g[b+72>>2]=0.0;c[b+76>>2]=1065353216;c[b+80>>2]=1065353216;c[b+84>>2]=1065353216;g[b+88>>2]=0.0;c[b+4>>2]=31;if(!d)return;c[6435]=(c[6435]|0)+1;d=yc(79)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}a[d+36>>0]=1;c[d+32>>2]=0;c[d+24>>2]=0;c[d+28>>2]=0;a[d+56>>0]=1;c[d+52>>2]=0;c[d+44>>2]=0;c[d+48>>2]=0;c[d>>2]=0;c[d+4>>2]=0;c[d+8>>2]=-1;c[d+12>>2]=0;c[d+16>>2]=0;c[b+64>>2]=d;return}function Tj(a){a=a|0;var b=0;c[a>>2]=3068;b=c[a+92>>2]|0;Ab[c[c[b>>2]>>2]&255](b);b=c[a+92>>2]|0;if(b|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}b=c[a+96>>2]|0;Ab[c[c[b>>2]>>2]&255](b);b=c[a+96>>2]|0;if(b|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}b=c[a+100>>2]|0;Ab[c[c[b>>2]>>2]&255](b);b=c[a+100>>2]|0;if(b|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}b=c[a+104>>2]|0;Ab[c[c[b>>2]>>2]&255](b);b=c[a+104>>2]|0;if(b|0){c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0)}b=c[a+108>>2]|0;Ab[c[c[b>>2]>>2]&255](b);b=c[a+108>>2]|0;if(!b){kf(a);return}c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0);kf(a);return}function Uj(b,d,e,f){b=b|0;d=d|0;e=+e;f=f|0;var h=0,i=0;c[6435]=(c[6435]|0)+1;h=yc(203)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}c[h>>2]=4872;i=h+60|0;a[h+144>>0]=1;c[h+140>>2]=0;c[h+132>>2]=0;c[h+136>>2]=0;c[h+176>>2]=f;g[h+56>>2]=.019999999552965164;c[i>>2]=0;c[i+4>>2]=0;c[i+8>>2]=0;c[i+12>>2]=0;a[h+170>>0]=1;c[h+8>>2]=b;g[h+52>>2]=e;g[h+48>>2]=0.0;c[h+12>>2]=d;a[h+171>>0]=1;g[h+172>>2]=0.0;g[h+16>>2]=0.0;g[h+20>>2]=0.0;g[h+44>>2]=29.399999618530273;g[h+24>>2]=55.0;g[h+28>>2]=10.0;a[h+168>>0]=0;a[h+169>>0]=0;a[h+180>>0]=1;g[h+36>>2]=.7853981852531433;g[h+40>>2]=.7071067690849304;g[h+108>>2]=0.0;a[h+181>>0]=0;a[h+182>>0]=0;return h|0}function Vj(a,b,d){a=a|0;b=b|0;d=d|0;var e=0.0,f=0.0,h=0,i=0.0,j=0.0,k=0.0,l=0,m=0;m=c[b+52>>2]|0;l=c[m+32>>2]|0;b=c[l>>2]|0;m=c[m+24>>2]|0;if((m|0)<=1){m=b;m=m+8|0;c[a>>2]=c[m>>2];c[a+4>>2]=c[m+4>>2];c[a+8>>2]=c[m+8>>2];c[a+12>>2]=c[m+12>>2];return}j=+g[d>>2];k=+g[d+4>>2];i=+g[d+8>>2];f=j*+g[b+8>>2]+k*+g[b+12>>2]+i*+g[b+16>>2];d=1;h=0;while(1){b=c[l+(d<<2)>>2]|0;e=j*+g[b+8>>2]+k*+g[b+12>>2]+i*+g[b+16>>2];b=e>f;h=b?d:h;d=d+1|0;if((d|0)==(m|0))break;else f=b?e:f}m=c[l+(h<<2)>>2]|0;m=m+8|0;c[a>>2]=c[m>>2];c[a+4>>2]=c[m+4>>2];c[a+8>>2]=c[m+8>>2];c[a+12>>2]=c[m+12>>2];return}
-function Ld(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0,H=0.0,I=0.0,J=0.0,K=0,L=0,M=0,N=0,O=0;h=i;i=i+256|0;if(!(c[b+16>>2]|0)){K=c[b+12>>2]|0;b=c[b+20>>2]|0;n=+g[d>>2];q=+g[d+4>>2];u=+g[d+8>>2];k=+g[d+16>>2];r=+g[d+20>>2];j=+g[d+24>>2];m=+g[d+32>>2];s=+g[d+36>>2];l=+g[d+40>>2];F=+g[d+48>>2];E=+g[d+52>>2];D=+g[d+56>>2];J=+g[e>>2];I=+g[e+16>>2];y=+g[e+32>>2];H=+g[e+4>>2];G=+g[e+20>>2];w=+g[e+36>>2];v=+g[e+8>>2];z=+g[e+24>>2];x=+g[e+40>>2];C=-+g[e+48>>2];B=-+g[e+52>>2];p=-+g[e+56>>2];d=c[(c[K>>2]|0)+64>>2]|0;A=-+g[b+48>>2];t=-+g[b+52>>2];o=-+g[b+56>>2];g[h+16>>2]=(n*J+k*I+m*y)*A+(n*H+k*G+m*w)*t+(n*v+k*z+m*x)*o;g[h+16+4>>2]=(q*J+r*I+s*y)*A+(q*H+r*G+s*w)*t+(q*v+r*z+s*x)*o;g[h+16+8>>2]=(u*J+j*I+l*y)*A+(u*H+j*G+l*w)*t+(u*v+j*z+l*x)*o;g[h+16+12>>2]=0.0;ic[d&127](h+168|0,K,h+16|0);o=+g[h+168>>2];t=+g[h+168+4>>2];A=+g[h+168+8>>2];y=F*J+E*I+D*y+(J*C+I*B+y*p)+((n*J+k*I+m*y)*o+(q*J+r*I+s*y)*t+(u*J+j*I+l*y)*A);w=F*H+E*G+D*w+(H*C+G*B+w*p)+((n*H+k*G+m*w)*o+(q*H+r*G+s*w)*t+(u*H+j*G+l*w)*A);A=F*v+E*z+D*x+(v*C+z*B+x*p)+((n*v+k*z+m*x)*o+(q*v+r*z+s*x)*t+(u*v+j*z+l*x)*A);x=+g[b+48>>2];l=+g[b+52>>2];z=+g[b+56>>2];j=z*A+(x*y+l*w)-+g[b+64>>2];v=+g[e>>2];u=+g[e+4>>2];t=+g[e+8>>2];s=+g[e+16>>2];r=+g[e+20>>2];q=+g[e+24>>2];o=+g[e+32>>2];m=+g[e+36>>2];k=+g[e+40>>2];n=(y-x*j)*s+(w-l*j)*r+(A-z*j)*q+ +g[e+52>>2];p=(y-x*j)*o+(w-l*j)*m+(A-z*j)*k+ +g[e+56>>2];g[h+32>>2]=t*(A-z*j)+(v*(y-x*j)+u*(w-l*j))+ +g[e+48>>2];g[h+32+4>>2]=n;g[h+32+8>>2]=p;g[h+32+12>>2]=0.0;p=+g[b+48>>2];n=+g[b+52>>2];l=+g[b+56>>2];g[h>>2]=v*p+u*n+t*l;g[h+4>>2]=p*s+n*r+l*q;g[h+8>>2]=p*o+n*m+l*k;g[h+12>>2]=0.0;hc[c[(c[f>>2]|0)+16>>2]&15](f,h,h+32|0,j);i=h;return}else{N=c[b+4>>2]|0;a[N+312>>0]=0;c[N>>2]=0;a[N+356>>0]=1;c[N+292>>2]=1566444395;c[N+296>>2]=1566444395;c[N+300>>2]=1566444395;g[N+304>>2]=0.0;c[N+336>>2]=0;c[N+336+4>>2]=0;c[N+336+8>>2]=0;c[N+336+12>>2]=0;a[N+336+16>>0]=0;a[N+332>>0]=a[N+332>>0]&-16;N=c[b+12>>2]|0;M=c[b+16>>2]|0;L=c[N+4>>2]|0;K=c[M+4>>2]|0;I=+Sb[c[(c[N>>2]|0)+48>>2]&15](N);O=c[b+16>>2]|0;J=+Sb[c[(c[O>>2]|0)+48>>2]&15](O);O=c[b+4>>2]|0;b=c[b+8>>2]|0;c[h+168>>2]=9208;c[h+168+4>>2]=0;c[h+168+8>>2]=1065353216;c[h+168+12>>2]=0;g[h+168+16>>2]=0.0;c[h+168+20>>2]=b;c[h+168+24>>2]=O;c[h+168+28>>2]=N;c[h+168+32>>2]=M;c[h+168+36>>2]=L;c[h+168+40>>2]=K;g[h+168+44>>2]=I;g[h+168+48>>2]=J;a[h+168+52>>0]=0;c[h+168+60>>2]=-1;c[h+168+72>>2]=1;c[h+168+76>>2]=1;g[h+32+128>>2]=999999984306749440.0;c[h+32>>2]=c[d>>2];c[h+32+4>>2]=c[d+4>>2];c[h+32+8>>2]=c[d+8>>2];c[h+32+12>>2]=c[d+12>>2];c[h+32+16>>2]=c[d+16>>2];c[h+32+16+4>>2]=c[d+16+4>>2];c[h+32+16+8>>2]=c[d+16+8>>2];c[h+32+16+12>>2]=c[d+16+12>>2];c[h+32+32>>2]=c[d+32>>2];c[h+32+32+4>>2]=c[d+32+4>>2];c[h+32+32+8>>2]=c[d+32+8>>2];c[h+32+32+12>>2]=c[d+32+12>>2];c[h+32+48>>2]=c[d+48>>2];c[h+32+48+4>>2]=c[d+48+4>>2];c[h+32+48+8>>2]=c[d+48+8>>2];c[h+32+48+12>>2]=c[d+48+12>>2];c[h+32+64>>2]=c[e>>2];c[h+32+64+4>>2]=c[e+4>>2];c[h+32+64+8>>2]=c[e+8>>2];c[h+32+64+12>>2]=c[e+12>>2];c[h+32+80>>2]=c[e+16>>2];c[h+32+80+4>>2]=c[e+16+4>>2];c[h+32+80+8>>2]=c[e+16+8>>2];c[h+32+80+12>>2]=c[e+16+12>>2];c[h+32+96>>2]=c[e+32>>2];c[h+32+96+4>>2]=c[e+32+4>>2];c[h+32+96+8>>2]=c[e+32+8>>2];c[h+32+96+12>>2]=c[e+32+12>>2];c[h+32+112>>2]=c[e+48>>2];c[h+32+112+4>>2]=c[e+48+4>>2];c[h+32+112+8>>2]=c[e+48+8>>2];c[h+32+112+12>>2]=c[e+48+12>>2];Vc(h+168|0,h+32|0,f,0,0);i=h;return}}function Md(d,e,f){d=d|0;e=e|0;f=f|0;var g=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0,s=0,t=0,u=0;t=i;i=i+32|0;g=Eb[c[(c[d>>2]|0)+28>>2]&127](d)|0;c[e+20>>2]=g;c[e>>2]=0;if(!g){s=d+4|0;f=e+4|0;s=c[s>>2]|0;c[f>>2]=s;f=d+8|0;f=c[f>>2]|0;s=e+8|0;c[s>>2]=f;s=d+12|0;s=c[s>>2]|0;f=e+12|0;c[f>>2]=s;f=d+16|0;f=c[f>>2]|0;d=e+16|0;c[d>>2]=f;i=t;return 19362}s=Ob[c[(c[f>>2]|0)+16>>2]&63](f,32,g)|0;g=c[s+8>>2]|0;c[e>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,g)|0;r=Eb[c[(c[d>>2]|0)+28>>2]&127](d)|0;a:do if((r|0)>0){q=0;while(1){Yb[c[(c[d>>2]|0)+16>>2]&3](d,t+28|0,t+4|0,t+16|0,t+8|0,t+24|0,t+20|0,t,t+12|0,q);c[g+24>>2]=c[t>>2];c[g+28>>2]=c[t+4>>2];k=g+12|0;m=g+16|0;p=g+4|0;c[g>>2]=0;c[g+4>>2]=0;c[g+8>>2]=0;c[g+12>>2]=0;c[g+16>>2]=0;c[g+20>>2]=0;switch(c[t+12>>2]|0){case 2:{j=c[t>>2]|0;if(j|0){j=Ob[c[(c[f>>2]|0)+16>>2]&63](f,4,j*3|0)|0;k=c[j+8>>2]|0;c[g+8>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,k)|0;if((c[t>>2]|0)>0){l=c[t+24>>2]|0;m=0;do{n=l+(_(c[t+20>>2]|0,m)|0)|0;o=m*3|0;c[k+(o<<2)>>2]=c[n>>2];c[k+(o+1<<2)>>2]=c[n+4>>2];c[k+(o+2<<2)>>2]=c[n+8>>2];m=m+1|0}while((m|0)<(c[t>>2]|0))}yb[c[(c[f>>2]|0)+20>>2]&31](f,j,19243,1497453121,c[j+8>>2]|0)}break}case 3:{j=c[t>>2]|0;if(j|0){n=Ob[c[(c[f>>2]|0)+16>>2]&63](f,8,j)|0;o=c[n+8>>2]|0;c[k>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,o)|0;j=c[t>>2]|0;if((j|0)>0){k=c[t+24>>2]|0;l=c[t+20>>2]|0;m=0;do{u=k+(_(l,m)|0)|0;b[o+(m<<3)>>1]=b[u>>1]|0;b[o+(m<<3)+2>>1]=b[u+2>>1]|0;b[o+(m<<3)+4>>1]=b[u+4>>1]|0;m=m+1|0}while((m|0)!=(j|0))}yb[c[(c[f>>2]|0)+20>>2]&31](f,n,19258,1497453121,c[n+8>>2]|0)}break}case 5:{j=c[t>>2]|0;if(j|0){k=Ob[c[(c[f>>2]|0)+16>>2]&63](f,4,j)|0;l=c[k+8>>2]|0;c[m>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,l)|0;if((c[t>>2]|0)>0){j=0;do{u=(c[t+24>>2]|0)+(_(c[t+20>>2]|0,j)|0)|0;a[l+(j<<2)>>0]=a[u>>0]|0;a[l+(j<<2)+1>>0]=a[u+1>>0]|0;a[l+(j<<2)+2>>0]=a[u+2>>0]|0;j=j+1|0}while((j|0)<(c[t>>2]|0))}yb[c[(c[f>>2]|0)+20>>2]&31](f,k,19285,1497453121,c[k+8>>2]|0)}break}default:{}}switch(c[t+16>>2]|0){case 0:{j=c[t+4>>2]|0;if(j|0){j=Ob[c[(c[f>>2]|0)+16>>2]&63](f,16,j)|0;k=c[j+8>>2]|0;c[g>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,k)|0;l=c[t+4>>2]|0;if((l|0)>0){m=c[t+28>>2]|0;n=c[t+8>>2]|0;o=0;do{u=m+(_(n,o)|0)|0;c[k+(o<<4)>>2]=c[u>>2];c[k+(o<<4)+4>>2]=c[u+4>>2];c[k+(o<<4)+8>>2]=c[u+8>>2];o=o+1|0}while((o|0)!=(l|0))}yb[c[(c[f>>2]|0)+20>>2]&31](f,j,19308,1497453121,c[j+8>>2]|0)}break}case 1:{j=c[t+4>>2]|0;if(j|0){n=Ob[c[(c[f>>2]|0)+16>>2]&63](f,32,j)|0;o=c[n+8>>2]|0;c[p>>2]=Zb[c[(c[f>>2]|0)+28>>2]&31](f,o)|0;j=c[t+4>>2]|0;if((j|0)>0){k=c[t+28>>2]|0;l=c[t+8>>2]|0;m=0;do{u=k+(_(l,m)|0)|0;h[o+(m<<5)>>3]=+h[u>>3];h[o+(m<<5)+8>>3]=+h[u+8>>3];h[o+(m<<5)+16>>3]=+h[u+16>>3];m=m+1|0}while((m|0)!=(j|0))}yb[c[(c[f>>2]|0)+20>>2]&31](f,n,19327,1497453121,c[n+8>>2]|0)}break}default:{}}Cb[c[(c[d>>2]|0)+24>>2]&127](d,q);q=q+1|0;if((q|0)==(r|0)){g=f;break a}else g=g+32|0}}else g=f;while(0);yb[c[(c[g>>2]|0)+20>>2]&31](f,s,19347,1497453121,c[s+8>>2]|0);f=d+4|0;u=e+4|0;f=c[f>>2]|0;c[u>>2]=f;u=d+8|0;u=c[u>>2]|0;f=e+8|0;c[f>>2]=u;f=d+12|0;f=c[f>>2]|0;u=e+12|0;c[u>>2]=f;d=d+16|0;d=c[d>>2]|0;u=e+16|0;c[u>>2]=d;i=t;return 19362}function Nd(b,d,e,f,h,i){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;i=i|0;var j=0,l=0,m=0,n=0.0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0,C=0,D=0;D=c[b+88>>2]|0;if((D|0)==(c[b+92>>2]|0)?(o=D|0?D<<1:1,(D|0)<(o|0)):0){if(!o){j=0;l=D}else{c[6435]=(c[6435]|0)+1;j=yc((o*152|3)+16|0)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}l=c[b+88>>2]|0}if((l|0)>0){m=0;do{_m(j+(m*152|0)|0,(c[b+96>>2]|0)+(m*152|0)|0,152)|0;m=m+1|0}while((m|0)!=(l|0))}l=c[b+96>>2]|0;if(l|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[l+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=j;c[b+92>>2]=o;j=c[b+88>>2]|0}else j=D;c[b+88>>2]=j+1;C=c[b+96>>2]|0;c[C+(D*152|0)+140>>2]=h;c[C+(D*152|0)+16>>2]=0;c[C+(D*152|0)+16+4>>2]=0;c[C+(D*152|0)+16+8>>2]=0;c[C+(D*152|0)+16+12>>2]=0;g[C+(D*152|0)+48>>2]=-0.0;g[C+(D*152|0)+52>>2]=-0.0;g[C+(D*152|0)+56>>2]=-0.0;g[C+(D*152|0)+60>>2]=0.0;b=c[b+16>>2]|0;o=c[b+(e*244|0)+240>>2]|0;B=c[b+(f*244|0)+240>>2]|0;c[C+(D*152|0)+144>>2]=e;c[C+(D*152|0)+148>>2]=f;h=c[i+88>>2]|0;c[C+(D*152|0)+104>>2]=h;c[C+(D*152|0)+132>>2]=0;g[C+(D*152|0)+100>>2]=0.0;g[C+(D*152|0)+96>>2]=0.0;x=-+g[d>>2];y=-+g[d+4>>2];z=-+g[d+8>>2];g[C+(D*152|0)>>2]=x;g[C+(D*152|0)+4>>2]=y;g[C+(D*152|0)+8>>2]=z;g[C+(D*152|0)+12>>2]=0.0;A=(c[k>>2]=h,+g[k>>2]);if(o|0){j=(g[k>>2]=(+g[o+264>>2]*x+ +g[o+268>>2]*y+ +g[o+272>>2]*z)*+g[o+544>>2],c[k>>2]|0);l=(g[k>>2]=(+g[o+280>>2]*x+ +g[o+284>>2]*y+ +g[o+288>>2]*z)*+g[o+548>>2],c[k>>2]|0);m=(g[k>>2]=(+g[o+296>>2]*x+ +g[o+300>>2]*y+ +g[o+304>>2]*z)*+g[o+552>>2],c[k>>2]|0)}else{j=0;l=0;m=0}c[C+(D*152|0)+64>>2]=j;c[C+(D*152|0)+68>>2]=l;c[C+(D*152|0)+72>>2]=m;g[C+(D*152|0)+76>>2]=0.0;u=+g[d>>2];v=+g[d+4>>2];w=+g[d+8>>2];d=c[d+12>>2]|0;g[C+(D*152|0)+32>>2]=u;g[C+(D*152|0)+36>>2]=v;g[C+(D*152|0)+40>>2]=w;c[C+(D*152|0)+44>>2]=d;if(B|0){j=(g[k>>2]=(u*+g[B+264>>2]+v*+g[B+268>>2]+w*+g[B+272>>2])*+g[B+544>>2],c[k>>2]|0);l=(g[k>>2]=(u*+g[B+280>>2]+v*+g[B+284>>2]+w*+g[B+288>>2])*+g[B+548>>2],c[k>>2]|0);m=(g[k>>2]=(u*+g[B+296>>2]+v*+g[B+300>>2]+w*+g[B+304>>2])*+g[B+552>>2],c[k>>2]|0)}else{j=0;l=0;m=0}c[C+(D*152|0)+80>>2]=j;c[C+(D*152|0)+84>>2]=l;c[C+(D*152|0)+88>>2]=m;g[C+(D*152|0)+92>>2]=0.0;if(o|0){n=+g[o+264>>2]*x+ +g[o+268>>2]*y+ +g[o+272>>2]*z;p=+g[o+280>>2]*x+ +g[o+284>>2]*y+ +g[o+288>>2]*z;q=+g[o+296>>2]*x+ +g[o+300>>2]*y+ +g[o+304>>2]*z}else{n=0.0;p=0.0;q=0.0}if(B|0){r=+g[B+264>>2]*u+ +g[B+268>>2]*v+ +g[B+272>>2]*w;s=u*+g[B+280>>2]+v*+g[B+284>>2]+w*+g[B+288>>2];t=u*+g[B+296>>2]+v*+g[B+300>>2]+w*+g[B+304>>2]}else{r=0.0;s=0.0;t=0.0}s=1.0/(n*x+p*y+q*z+0.0+(r*u+s*v+t*w));g[C+(D*152|0)+108>>2]=s;if(o|0){p=+g[b+(e*244|0)+192>>2];q=+g[b+(e*244|0)+196>>2];r=+g[b+(e*244|0)+200>>2];n=(+g[b+(e*244|0)+176>>2]+ +g[b+(e*244|0)+208>>2])*0.0+(+g[b+(e*244|0)+180>>2]+ +g[b+(e*244|0)+212>>2])*0.0+(+g[b+(e*244|0)+184>>2]+ +g[b+(e*244|0)+216>>2])*0.0}else{p=0.0;q=0.0;r=0.0;n=0.0}n=n+(p*x+q*y+r*z);if(!B){t=0.0;x=0.0;z=0.0;y=-0.0;u=t*u;x=x*v;x=u+x;z=z*w;z=x+z;z=y+z;z=n+z;z=0.0-z;z=s*z;f=C+(D*152|0)+112|0;g[f>>2]=z;f=C+(D*152|0)+116|0;g[f>>2]=0.0;A=-A;f=C+(D*152|0)+120|0;g[f>>2]=A;f=C+(D*152|0)+124|0;c[f>>2]=h;return}t=+g[b+(f*244|0)+192>>2];x=+g[b+(f*244|0)+196>>2];z=+g[b+(f*244|0)+200>>2];y=(+g[b+(f*244|0)+176>>2]+ +g[b+(f*244|0)+208>>2])*-0.0+(+g[b+(f*244|0)+180>>2]+ +g[b+(f*244|0)+212>>2])*-0.0+(+g[b+(f*244|0)+184>>2]+ +g[b+(f*244|0)+216>>2])*-0.0;u=t*u;x=x*v;x=u+x;z=z*w;z=x+z;z=y+z;z=n+z;z=0.0-z;z=s*z;f=C+(D*152|0)+112|0;g[f>>2]=z;f=C+(D*152|0)+116|0;g[f>>2]=0.0;A=-A;f=C+(D*152|0)+120|0;g[f>>2]=A;f=C+(D*152|0)+124|0;c[f>>2]=h;return}function Od(b,d){b=b|0;d=d|0;var e=0,f=0.0,h=0,j=0,l=0,m=0.0,n=0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0;n=i;i=i+32|0;c[b+236>>2]=2;c[b+312>>2]=0;c[b+312+4>>2]=0;c[b+312+8>>2]=0;c[b+312+12>>2]=0;c[b+312+16>>2]=0;c[b+312+20>>2]=0;c[b+312+24>>2]=0;c[b+312+28>>2]=0;c[b+544>>2]=1065353216;c[b+548>>2]=1065353216;c[b+552>>2]=1065353216;g[b+556>>2]=0.0;c[b+348>>2]=1065353216;c[b+352>>2]=1065353216;c[b+356>>2]=1065353216;e=b+360|0;h=e+36|0;do{c[e>>2]=0;e=e+4|0}while((e|0)<(h|0));c[b+412>>2]=0;c[b+412+4>>2]=0;c[b+412+8>>2]=0;c[b+412+12>>2]=0;c[b+412+16>>2]=0;c[b+412+20>>2]=0;c[b+412+24>>2]=0;c[b+412+28>>2]=0;f=+g[d+92>>2];m=+g[d+96>>2];g[n+20>>2]=f;g[n+16>>2]=m;g[n+12>>2]=0.0;g[n+8>>2]=1.0;c[b+444>>2]=c[(f<0.0?n+12|0:f>1.0?n+8|0:n+20|0)>>2];g[n+4>>2]=0.0;g[n>>2]=1.0;c[b+448>>2]=c[(m<0.0?n+4|0:m>1.0?n:n+16|0)>>2];c[b+472>>2]=c[d+112>>2];c[b+476>>2]=c[d+116>>2];e=c[d+4>>2]|0;c[b+480>>2]=e;c[b+608>>2]=0;c[b+612>>2]=0;a[b+452>>0]=a[d+120>>0]|0;c[b+456>>2]=c[d+124>>2];c[b+460>>2]=c[d+128>>2];c[b+464>>2]=c[d+132>>2];c[b+468>>2]=c[d+136>>2];if(!e){c[b+4>>2]=c[d+8>>2];c[b+4+4>>2]=c[d+8+4>>2];c[b+4+8>>2]=c[d+8+8>>2];c[b+4+12>>2]=c[d+8+12>>2];c[b+20>>2]=c[d+24>>2];c[b+20+4>>2]=c[d+24+4>>2];c[b+20+8>>2]=c[d+24+8>>2];c[b+20+12>>2]=c[d+24+12>>2];c[b+36>>2]=c[d+40>>2];c[b+36+4>>2]=c[d+40+4>>2];c[b+36+8>>2]=c[d+40+8>>2];c[b+36+12>>2]=c[d+40+12>>2];c[b+52>>2]=c[d+56>>2];c[b+52+4>>2]=c[d+56+4>>2];c[b+52+8>>2]=c[d+56+8>>2];c[b+52+12>>2]=c[d+56+12>>2];e=b+4|0;h=b+20|0;j=b+36|0;l=b+52|0}else{Cb[c[(c[e>>2]|0)+8>>2]&127](e,b+4|0);e=b+4|0;h=b+20|0;j=b+36|0;l=b+52|0}c[b+68>>2]=c[e>>2];c[b+68+4>>2]=c[e+4>>2];c[b+68+8>>2]=c[e+8>>2];c[b+68+12>>2]=c[e+12>>2];c[b+84>>2]=c[h>>2];c[b+84+4>>2]=c[h+4>>2];c[b+84+8>>2]=c[h+8>>2];c[b+84+12>>2]=c[h+12>>2];c[b+100>>2]=c[j>>2];c[b+100+4>>2]=c[j+4>>2];c[b+100+8>>2]=c[j+8>>2];c[b+100+12>>2]=c[j+12>>2];c[b+116>>2]=c[l>>2];c[b+116+4>>2]=c[l+4>>2];c[b+116+8>>2]=c[l+8>>2];c[b+116+12>>2]=c[l+12>>2];c[b+132>>2]=0;c[b+132+4>>2]=0;c[b+132+8>>2]=0;c[b+132+12>>2]=0;c[b+132+16>>2]=0;c[b+132+20>>2]=0;c[b+132+24>>2]=0;c[b+132+28>>2]=0;c[b+224>>2]=c[d+100>>2];c[b+232>>2]=c[d+104>>2];c[b+228>>2]=c[d+108>>2];Cb[c[(c[b>>2]|0)+12>>2]&127](b,c[d+72>>2]|0);e=c[5815]|0;c[5815]=e+1;c[b+508>>2]=e;f=+g[d>>2];e=c[b+204>>2]|0;if(f==0.0){c[b+204>>2]=e|1;m=0.0}else{c[b+204>>2]=e&-2;m=1.0/f}g[b+344>>2]=m;p=f*+g[b+384>>2];o=f*+g[b+388>>2];g[b+364>>2]=f*+g[b+380>>2];g[b+368>>2]=p;g[b+372>>2]=o;g[b+376>>2]=0.0;f=+g[d+76>>2];h=f!=0.0?(g[k>>2]=1.0/f,c[k>>2]|0):0;f=+g[d+80>>2];e=f!=0.0?(g[k>>2]=1.0/f,c[k>>2]|0):0;f=+g[d+84>>2];d=f!=0.0?(g[k>>2]=1.0/f,c[k>>2]|0):0;c[b+396>>2]=h;c[b+400>>2]=e;c[b+404>>2]=d;g[b+408>>2]=0.0;r=m*+g[b+352>>2];x=m*+g[b+356>>2];g[b+560>>2]=m*+g[b+348>>2];g[b+564>>2]=r;g[b+568>>2]=x;g[b+572>>2]=0.0;x=+g[b+4>>2];r=(c[k>>2]=h,+g[k>>2]);w=+g[b+8>>2];f=(c[k>>2]=e,+g[k>>2]);v=+g[b+12>>2];o=(c[k>>2]=d,+g[k>>2]);u=+g[b+20>>2];t=+g[b+24>>2];s=+g[b+28>>2];q=+g[b+36>>2];p=+g[b+40>>2];m=+g[b+44>>2];g[b+264>>2]=x*x*r+w*w*f+v*v*o;g[b+268>>2]=x*r*u+w*f*t+v*o*s;g[b+272>>2]=x*r*q+w*f*p+v*o*m;g[b+276>>2]=0.0;g[b+280>>2]=x*r*u+w*f*t+v*o*s;g[b+284>>2]=u*r*u+t*f*t+s*o*s;g[b+288>>2]=r*u*q+f*t*p+o*s*m;g[b+292>>2]=0.0;g[b+296>>2]=x*r*q+w*f*p+v*o*m;g[b+300>>2]=u*r*q+t*f*p+s*o*m;g[b+304>>2]=q*r*q+p*f*p+m*o*m;g[b+308>>2]=0.0;c[b+504>>2]=0;c[b+512>>2]=0;c[b+512+4>>2]=0;c[b+512+8>>2]=0;c[b+512+12>>2]=0;c[b+512+16>>2]=0;c[b+512+20>>2]=0;c[b+512+24>>2]=0;c[b+512+28>>2]=0;m=+g[b+344>>2];o=m*+g[b+352>>2];p=m*+g[b+356>>2];g[b+560>>2]=+g[b+348>>2]*m;g[b+564>>2]=o;g[b+568>>2]=p;e=b+572|0;h=e+36|0;do{c[e>>2]=0;e=e+4|0}while((e|0)<(h|0));i=n;return}function Pd(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,h=0,i=0.0,j=0.0,k=0.0,l=0,m=0.0,n=0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0;n=c[a+192>>2]|0;m=+Sb[c[(c[n>>2]|0)+48>>2]&15](n);n=c[a+712>>2]|0;if((n|0)>0){o=0;do{l=c[a+720>>2]|0;f=l+(o*104|0)+8|0;q=+g[f>>2];h=l+(o*104|0)+12|0;p=+g[h>>2];d=l+(o*104|0)+16|0;k=+g[d>>2];i=q*+g[b>>2]+p*+g[b+4>>2]+k*+g[b+8>>2]+ +g[b+48>>2];j=q*+g[b+16>>2]+p*+g[b+20>>2]+k*+g[b+24>>2]+ +g[b+52>>2];k=q*+g[b+32>>2]+p*+g[b+36>>2]+k*+g[b+40>>2]+ +g[b+56>>2];g[f>>2]=i;g[h>>2]=j;g[d>>2]=k;g[l+(o*104|0)+20>>2]=0.0;d=l+(o*104|0)+24|0;p=+g[d>>2];h=l+(o*104|0)+28|0;q=+g[h>>2];f=l+(o*104|0)+32|0;r=+g[f>>2];s=p*+g[b+16>>2]+q*+g[b+20>>2]+r*+g[b+24>>2]+ +g[b+52>>2];t=p*+g[b+32>>2]+q*+g[b+36>>2]+r*+g[b+40>>2]+ +g[b+56>>2];g[d>>2]=p*+g[b>>2]+q*+g[b+4>>2]+r*+g[b+8>>2]+ +g[b+48>>2];g[h>>2]=s;g[f>>2]=t;g[l+(o*104|0)+36>>2]=0.0;f=l+(o*104|0)+72|0;t=+g[f>>2];h=l+(o*104|0)+76|0;s=+g[h>>2];d=l+(o*104|0)+80|0;r=+g[d>>2];q=t*+g[b+16>>2]+s*+g[b+20>>2]+r*+g[b+24>>2];p=t*+g[b+32>>2]+s*+g[b+36>>2]+r*+g[b+40>>2];g[f>>2]=+g[b>>2]*t+ +g[b+4>>2]*s+ +g[b+8>>2]*r;g[h>>2]=q;g[d>>2]=p;g[l+(o*104|0)+84>>2]=0.0;l=c[l+(o*104|0)+96>>2]|0;d=hh(a+928|0,l)|0;a:do if(d){f=c[a+936>>2]|0;if((f|0)<=-1){d=c[a+928>>2]|0;break}if((f|0)>0){h=0;while(1){e=c[d+32>>2]|0;h=h+1|0;if(!e)break a;if((h|0)>=(f|0)){d=e;break}else d=e}}}else d=0;while(0);g[l>>2]=i-m;g[l+4>>2]=j-m;g[l+8>>2]=k-m;g[l+12>>2]=0.0;g[l+16>>2]=m+i;g[l+20>>2]=m+j;g[l+24>>2]=m+k;g[l+28>>2]=0.0;lf(a+928|0,d,l);o=o+1|0}while((o|0)!=(n|0))}Bg(a);d=c[a+928>>2]|0;if(d){o=c[a+192>>2]|0;r=+Sb[c[(c[o>>2]|0)+48>>2]&15](o);t=+g[d+4>>2]-r;s=+g[d+8>>2]-r;g[a+892>>2]=+g[d>>2]-r;g[a+896>>2]=t;g[a+900>>2]=s;g[a+904>>2]=0.0;s=r+ +g[d+20>>2];t=r+ +g[d+24>>2];g[a+908>>2]=r+ +g[d+16>>2];g[a+912>>2]=s;g[a+916>>2]=t;g[a+920>>2]=0.0;d=c[a+188>>2]|0;if(d|0){o=c[a+684>>2]|0;n=c[o+32>>2]|0;yb[c[(c[n>>2]|0)+16>>2]&31](n,d,a+892|0,a+908|0,c[o+36>>2]|0)}}else{c[a+892>>2]=0;c[a+892+4>>2]=0;c[a+892+8>>2]=0;c[a+892+12>>2]=0;c[a+892+16>>2]=0;c[a+892+20>>2]=0;c[a+892+24>>2]=0;c[a+892+28>>2]=0}f=c[a+732>>2]|0;if((f|0)<=0){eg(a);o=a+1148|0;c[o>>2]=c[b>>2];c[o+4>>2]=c[b+4>>2];c[o+8>>2]=c[b+8>>2];c[o+12>>2]=c[b+12>>2];o=a+1164|0;n=b+16|0;c[o>>2]=c[n>>2];c[o+4>>2]=c[n+4>>2];c[o+8>>2]=c[n+8>>2];c[o+12>>2]=c[n+12>>2];o=a+1180|0;n=b+32|0;c[o>>2]=c[n>>2];c[o+4>>2]=c[n+4>>2];c[o+8>>2]=c[n+8>>2];c[o+12>>2]=c[n+12>>2];a=a+1196|0;b=b+48|0;c[a>>2]=c[b>>2];c[a+4>>2]=c[b+4>>2];c[a+8>>2]=c[b+8>>2];c[a+12>>2]=c[b+12>>2];return}d=c[a+740>>2]|0;e=0;do{n=c[d+(e*52|0)+8>>2]|0;o=c[d+(e*52|0)+12>>2]|0;r=+g[n+8>>2]-+g[o+8>>2];s=+g[n+12>>2]-+g[o+12>>2];t=+g[n+16>>2]-+g[o+16>>2];t=+O(+(r*r+s*s+t*t));g[d+(e*52|0)+16>>2]=t;g[d+(e*52|0)+28>>2]=t*t;e=e+1|0}while((e|0)!=(f|0));d=c[a+740>>2]|0;e=0;do{g[d+(e*52|0)+24>>2]=(+g[(c[d+(e*52|0)+8>>2]|0)+88>>2]+ +g[(c[d+(e*52|0)+12>>2]|0)+88>>2])/+g[(c[d+(e*52|0)+4>>2]|0)+4>>2];e=e+1|0}while((e|0)!=(f|0));eg(a);o=a+1148|0;c[o>>2]=c[b>>2];c[o+4>>2]=c[b+4>>2];c[o+8>>2]=c[b+8>>2];c[o+12>>2]=c[b+12>>2];o=a+1164|0;n=b+16|0;c[o>>2]=c[n>>2];c[o+4>>2]=c[n+4>>2];c[o+8>>2]=c[n+8>>2];c[o+12>>2]=c[n+12>>2];o=a+1180|0;n=b+32|0;c[o>>2]=c[n>>2];c[o+4>>2]=c[n+4>>2];c[o+8>>2]=c[n+8>>2];c[o+12>>2]=c[n+12>>2];a=a+1196|0;b=b+48|0;c[a>>2]=c[b>>2];c[a+4>>2]=c[b+4>>2];c[a+8>>2]=c[b+8>>2];c[a+12>>2]=c[b+12>>2];return}function Qd(a,b){a=a|0;b=b|0;var d=0,e=0.0,f=0.0,h=0,j=0.0,l=0,m=0.0,n=0.0,o=0.0,p=0,q=0,r=0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0,E=0,F=0,G=0,H=0,I=0;F=i;i=i+96|0;d=c[a+216>>2]|0;if(+g[d+4>>2]==0.0){E=0;i=F;return E|0}E=c[b>>2]|0;if(!(Zb[c[(c[d>>2]|0)+8>>2]&31](d,c[E+188>>2]|0)|0)){E=1;i=F;return E|0}b=c[E+192>>2]|0;D=c[a+216>>2]|0;if((c[b+4>>2]|0)!=32){c[F+32>>2]=0;c[F+32+4>>2]=b;c[F+32+8>>2]=E;c[F+32+12>>2]=E+4;c[F+32+16>>2]=-1;c[F+32+20>>2]=-1;bd(a+68|0,a+132|0,F+32|0,D);E=1;i=F;return E|0}if((E|0)==0?1:(c[E+236>>2]|0)!=8){E=1;i=F;return E|0}if(c[E+752>>2]|0?(c[E+988>>2]|0)==0:0)gg(E);A=+g[a+180>>2]-+g[a+116>>2];B=+g[a+184>>2]-+g[a+120>>2];C=+g[a+188>>2]-+g[a+124>>2];b=c[E+988>>2]|0;if(!b){q=c[E+752>>2]|0;if((q|0)>0){p=c[E+760>>2]|0;f=1.0;d=0;r=0;b=-1;l=1065353216;h=0;do{I=c[p+(r*44|0)+8>>2]|0;H=c[p+(r*44|0)+12>>2]|0;G=c[p+(r*44|0)+16>>2]|0;e=+Mh(a+116|0,A,B,C,+g[I+8>>2],+g[I+12>>2],+g[I+16>>2],+g[H+8>>2],+g[H+12>>2],+g[H+16>>2],+g[G+8>>2],+g[G+12>>2],+g[G+16>>2],f);if(e>0.0){f=e;d=d+1|0;b=r;l=(g[k>>2]=e,c[k>>2]|0);h=3}r=r+1|0}while((r|0)!=(q|0))}else{d=0;b=-1;l=1065353216;h=0}}else{c[F+32>>2]=3220;c[F+32+4>>2]=c[a+116>>2];c[F+32+4+4>>2]=c[a+116+4>>2];c[F+32+4+8>>2]=c[a+116+8>>2];c[F+32+4+12>>2]=c[a+116+12>>2];g[F+32+36>>2]=A;g[F+32+40>>2]=B;g[F+32+44>>2]=C;g[F+32+48>>2]=0.0;c[F+32+20>>2]=c[a+180>>2];c[F+32+20+4>>2]=c[a+180+4>>2];c[F+32+20+8>>2]=c[a+180+8>>2];c[F+32+20+12>>2]=c[a+180+12>>2];c[F+32+52>>2]=1065353216;c[F+32+56>>2]=0;c[F+32+60>>2]=0;ff(b,a+116|0,a+180|0,F+32|0);b=c[F+32+56>>2]|0;if(!b){d=0;b=-1;l=1065353216;h=0}else{d=1;b=(b-(c[E+760>>2]|0)|0)/44|0;l=c[F+32+52>>2]|0;h=3}}r=c[E+772>>2]|0;if((r|0)>0){q=c[E+780>>2]|0;f=(c[k>>2]=l,+g[k>>2]);p=0;do{I=c[q+(p*104|0)+8>>2]|0;x=+g[I+8>>2];y=+g[I+12>>2];z=+g[I+16>>2];I=c[q+(p*104|0)+12>>2]|0;o=+g[I+8>>2];s=+g[I+12>>2];t=+g[I+16>>2];I=c[q+(p*104|0)+16>>2]|0;u=+g[I+8>>2];v=+g[I+12>>2];w=+g[I+16>>2];e=+Mh(a+116|0,A,B,C,x,y,z,o,s,t,u,v,w,f);if(e>0.0){f=e;d=d+1|0;b=p;l=(g[k>>2]=e,c[k>>2]|0);h=4}I=c[q+(p*104|0)+20>>2]|0;j=+g[I+8>>2];m=+g[I+12>>2];n=+g[I+16>>2];e=+Mh(a+116|0,A,B,C,x,y,z,o,s,t,j,m,n,f);if(e>0.0){f=e;d=d+1|0;b=p;l=(g[k>>2]=e,c[k>>2]|0);h=4}e=+Mh(a+116|0,A,B,C,o,s,t,u,v,w,j,m,n,f);if(e>0.0){f=e;d=d+1|0;b=p;l=(g[k>>2]=e,c[k>>2]|0);h=4}e=+Mh(a+116|0,A,B,C,x,y,z,u,v,w,j,m,n,f);if(e>0.0){f=e;d=d+1|0;b=p;l=(g[k>>2]=e,c[k>>2]|0);h=4}p=p+1|0}while((p|0)!=(r|0))}if(!d){I=1;i=F;return I|0}if(!((c[k>>2]=l,+g[k>>2])<=+g[D+4>>2])){I=1;i=F;return I|0}c[F+32>>2]=0;c[F+32+4>>2]=b;m=+g[a+180>>2]-+g[a+116>>2];n=+g[a+184>>2]-+g[a+120>>2];o=+g[a+188>>2]-+g[a+124>>2];e=1.0/+O(+(m*m+n*n+o*o));if((h|0)==3){d=c[E+748+12>>2]|0;e=+g[d+(b*44|0)+20>>2];j=+g[d+(b*44|0)+24>>2];f=+g[d+(b*44|0)+28>>2];if(m*e+n*j+o*f>0.0){m=-e;j=-j;f=-f;e=0.0}else{m=e;e=+g[d+(b*44|0)+32>>2]}}else{m=-(m*e);j=-(n*e);f=-(o*e);e=0.0}c[F>>2]=E;c[F+4>>2]=F+32;g[F+8>>2]=m;g[F+12>>2]=j;g[F+16>>2]=f;g[F+20>>2]=e;c[F+24>>2]=l;+_b[c[(c[D>>2]|0)+12>>2]&15](D,F,1);I=1;i=F;return I|0}function Rd(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,h=0,j=0,k=0,l=0,m=0,n=0.0,o=0.0;m=i;i=i+400|0;f=c[d+36>>2]|0;d=c[e+36>>2]|0;e=c[b+24>>2]|0;if(((e|0)==(c[b+28>>2]|0)?c[e+1132>>2]|0:0)?(k=(_(c[d+380>>2]|0,c[e+1112>>2]|0)|0)+(c[f+380>>2]|0)|0,a[(c[e+1140>>2]|0)+k>>0]|0):0){c[5802]=(c[5802]|0)+1;i=m;return}c[m+344+4>>2]=35;c[m+344+8>>2]=0;c[m+344+12>>2]=1065353216;c[m+344+16>>2]=1065353216;c[m+344+20>>2]=1065353216;g[m+344+24>>2]=0.0;c[m+344>>2]=3436;c[m+344+52>>2]=f;g[m+344+44>>2]=0.0;c[m+288+4>>2]=35;c[m+288+8>>2]=0;c[m+288+12>>2]=1065353216;c[m+288+16>>2]=1065353216;c[m+288+20>>2]=1065353216;g[m+288+24>>2]=0.0;c[m+288>>2]=3436;c[m+288+52>>2]=d;g[m+288+44>>2]=0.0;if((a[22456]|0)==0?Wa(22456)|0:0){if((a[22464]|0)==0?Wa(22464)|0:0){c[5698]=1065353216;c[5699]=0;c[5700]=0;c[5701]=0;c[5702]=0;c[5703]=1065353216;c[5704]=0;c[5705]=0;c[5706]=0;c[5707]=0;c[5708]=1065353216;g[5709]=0.0;_a(22464)}c[5710]=c[5698];c[5711]=c[5699];c[5712]=c[5700];c[5713]=c[5701];c[5714]=c[5702];c[5715]=c[5703];c[5716]=c[5704];c[5717]=c[5705];c[5718]=c[5706];c[5719]=c[5707];c[5720]=c[5708];c[5721]=c[5709];c[5722]=0;c[5723]=0;c[5724]=0;c[5725]=0;_a(22456)}if((a[22456]|0)==0?Wa(22456)|0:0){if((a[22464]|0)==0?Wa(22464)|0:0){c[5698]=1065353216;c[5699]=0;c[5700]=0;c[5701]=0;c[5702]=0;c[5703]=1065353216;c[5704]=0;c[5705]=0;c[5706]=0;c[5707]=0;c[5708]=1065353216;g[5709]=0.0;_a(22464)}c[5710]=c[5698];c[5711]=c[5699];c[5712]=c[5700];c[5713]=c[5701];c[5714]=c[5702];c[5715]=c[5703];c[5716]=c[5704];c[5717]=c[5705];c[5718]=c[5706];c[5719]=c[5707];c[5720]=c[5708];c[5721]=c[5709];c[5722]=0;c[5723]=0;c[5724]=0;c[5725]=0;_a(22456)}o=+g[f+232>>2]-+g[d+232>>2];n=+g[f+236>>2]-+g[d+236>>2];g[m>>2]=+g[f+228>>2]-+g[d+228>>2];g[m+4>>2]=o;g[m+8>>2]=n;g[m+12>>2]=0.0;if(!(!(Jd(m+344|0,22840,m+288|0,22840,m,m+232|0)|0)?!(Pc(m+344|0,22840,m+288|0,22840,m,m+232|0,0)|0):0))h=18;if((h|0)==18?(k=m+16+4|0,a[m+16+152>>0]=0,c[k>>2]=0,c[k+4>>2]=0,c[k+8>>2]=0,c[k+12>>2]=0,c[k+16>>2]=0,c[k+20>>2]=0,c[m+16>>2]=3256,jd(b,m+232|0,f,0,0,d,0,0,m+16|0)|0):0){c[6435]=(c[6435]|0)+1;d=yc(235)|0;if(!d)k=0;else{c[(d+4+15&-16)+-4>>2]=d;k=d+4+15&-16}d=k+152|0;Qn(k|0,0,156)|0;c[k>>2]=3256;e=k+4|0;f=m+16+4|0;h=e+100|0;do{c[e>>2]=c[f>>2];e=e+4|0;f=f+4|0}while((e|0)<(h|0));e=k+104|0;c[e>>2]=c[m+16+104>>2];c[e+4>>2]=c[m+16+104+4>>2];c[e+8>>2]=c[m+16+104+8>>2];c[e+12>>2]=c[m+16+104+12>>2];e=k+120|0;c[e>>2]=c[m+16+120>>2];c[e+4>>2]=c[m+16+120+4>>2];c[e+8>>2]=c[m+16+120+8>>2];c[e+12>>2]=c[m+16+120+12>>2];e=k+136|0;c[e>>2]=c[m+16+136>>2];c[e+4>>2]=c[m+16+136+4>>2];c[e+8>>2]=c[m+16+136+8>>2];c[e+12>>2]=c[m+16+136+12>>2];a[d>>0]=a[m+16+152>>0]|0;e=k+156|0;f=m+16+156|0;h=e+60|0;do{c[e>>2]=c[f>>2];e=e+4|0;f=f+4|0}while((e|0)<(h|0));h=c[b+24>>2]|0;j=k;d=c[h+852>>2]|0;if((d|0)==(c[h+856>>2]|0)?(l=d|0?d<<1:1,(d|0)<(l|0)):0){if(!l)f=0;else{c[6435]=(c[6435]|0)+1;d=yc((l<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}f=d;d=c[h+852>>2]|0}if((d|0)>0){e=0;do{c[f+(e<<2)>>2]=c[(c[h+860>>2]|0)+(e<<2)>>2];e=e+1|0}while((e|0)!=(d|0))}e=c[h+860>>2]|0;if(e){if(a[h+864>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);d=c[h+852>>2]|0}c[h+860>>2]=0}a[h+864>>0]=1;c[h+860>>2]=f;c[h+856>>2]=l}c[(c[h+860>>2]|0)+(d<<2)>>2]=j;c[h+852>>2]=d+1;j=c[b+24>>2]|0;l=c[b+28>>2]|0;n=+g[j+348>>2];o=+g[l+348>>2];b=k+64|0;g[b>>2]=+g[b>>2]*(n>o?n:o);b=k+68|0;g[b>>2]=+g[b>>2]*(+g[j+360>>2]+ +g[l+360>>2])*.5}i=m;return}function Sd(b,d,e){b=b|0;d=d|0;e=e|0;var f=0,h=0,i=0,j=0.0,k=0.0,l=0.0,m=0.0,n=0,o=0,p=0.0,q=0.0,r=0.0;if(a[b+165>>0]|0){f=c[b+88>>2]|0;a:do if((f|0)>0&e){h=c[b+96>>2]|0;m=+g[d>>2];j=+g[d+4>>2];k=+g[d+8>>2];l=+g[b+168>>2];e=0;while(1){r=+g[h+(e<<4)>>2]-m;q=+g[h+(e<<4)+4>>2]-j;p=+g[h+(e<<4)+8>>2]-k;if(r*r+q*q+p*p<=l)break;e=e+1|0;if((e|0)>=(f|0))break a}return e|0}while(0);o=(c[b+32>>2]|0)+12|0;c[o>>2]=(c[o>>2]|0)+1;if((f|0)==(c[b+92>>2]|0)?(i=f|0?f<<1:1,(f|0)<(i|0)):0){if(!i)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((i<<4|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}f=c[b+88>>2]|0}if((f|0)>0){h=0;do{o=e+(h<<4)|0;n=(c[b+96>>2]|0)+(h<<4)|0;c[o>>2]=c[n>>2];c[o+4>>2]=c[n+4>>2];c[o+8>>2]=c[n+8>>2];c[o+12>>2]=c[n+12>>2];h=h+1|0}while((h|0)!=(f|0))}f=c[b+96>>2]|0;if(f|0){if(a[b+100>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+96>>2]=0}a[b+100>>0]=1;c[b+96>>2]=e;c[b+92>>2]=i;e=c[b+88>>2]|0}else e=f;o=(c[b+96>>2]|0)+(e<<4)|0;c[o>>2]=c[d>>2];c[o+4>>2]=c[d+4>>2];c[o+8>>2]=c[d+8>>2];c[o+12>>2]=c[d+12>>2];d=c[b+88>>2]|0;c[b+88>>2]=d+1;c[(c[b+32>>2]|0)+16>>2]=c[b+96>>2];return d|0}h=c[b+108>>2]|0;b:do if((h|0)>0&e){e=c[b+116>>2]|0;j=+g[d>>2];k=+g[d+4>>2];l=+g[d+8>>2];m=+g[b+168>>2];i=0;while(1){p=+g[e+(i<<2)>>2]-j;q=+g[e+(i+1<<2)>>2]-k;r=+g[e+(i+2<<2)>>2]-l;f=i+3|0;if(p*p+q*q+r*r<=m)break;if((f|0)<(h|0))i=f;else break b}d=(i|0)/3|0;return d|0}while(0);e=c[b+112>>2]|0;if((h|0)==(e|0)){n=h|0?h<<1:1;if((h|0)<(n|0)){if(!n)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((n<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}h=c[b+108>>2]|0}i=c[b+116>>2]|0;if((h|0)<=0)if(!i)f=b+120|0;else o=34;else{f=0;do{c[e+(f<<2)>>2]=c[i+(f<<2)>>2];f=f+1|0}while((f|0)!=(h|0));o=34}if((o|0)==34){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[i+-4>>2]|0)}c[b+116>>2]=0;f=b+120|0}a[f>>0]=1;c[b+116>>2]=e;c[b+112>>2]=n;f=c[b+108>>2]|0;h=n}else f=h}else{f=h;h=e}c[(c[b+116>>2]|0)+(f<<2)>>2]=c[d>>2];e=f+1|0;c[b+108>>2]=e;if((e|0)==(h|0)){n=h|0?h<<1:1;if((h|0)<(n|0)){if(!n)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((n<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}h=c[b+108>>2]|0}i=c[b+116>>2]|0;if((h|0)<=0)if(!i)f=b+120|0;else o=48;else{f=0;do{c[e+(f<<2)>>2]=c[i+(f<<2)>>2];f=f+1|0}while((f|0)!=(h|0));o=48}if((o|0)==48){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[i+-4>>2]|0)}c[b+116>>2]=0;f=b+120|0}a[f>>0]=1;c[b+116>>2]=e;c[b+112>>2]=n;e=c[b+108>>2]|0;h=n}else e=h}c[(c[b+116>>2]|0)+(e<<2)>>2]=c[d+4>>2];e=e+1|0;c[b+108>>2]=e;if((e|0)==(h|0)){n=h|0?h<<1:1;if((h|0)<(n|0)){if(!n)e=0;else{c[6435]=(c[6435]|0)+1;e=yc((n<<2|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}h=c[b+108>>2]|0}i=c[b+116>>2]|0;if((h|0)<=0)if(!i)f=b+120|0;else o=62;else{f=0;do{c[e+(f<<2)>>2]=c[i+(f<<2)>>2];f=f+1|0}while((f|0)!=(h|0));o=62}if((o|0)==62){if(a[b+120>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[i+-4>>2]|0)}c[b+116>>2]=0;f=b+120|0}a[f>>0]=1;c[b+116>>2]=e;c[b+112>>2]=n;e=c[b+108>>2]|0}else e=h}o=c[b+116>>2]|0;c[o+(e<<2)>>2]=c[d+8>>2];d=e+1|0;c[b+108>>2]=d;b=c[b+32>>2]|0;c[b+12>>2]=(c[b+12>>2]|0)+1;c[b+16>>2]=o;d=((d|0)/3|0)+-1|0;return d|0}function Td(b){b=b|0;var d=0,e=0.0,f=0.0,h=0.0,j=0,k=0,l=0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0,H=0.0,I=0.0,J=0.0,K=0;k=i;i=i+16|0;if(!(a[b+1308>>0]|0)){i=k;return}g[b+928>>2]=0.0;g[b+992>>2]=0.0;g[b+1056>>2]=0.0;c[b+712>>2]=0;c[b+712+4>>2]=0;c[b+712+8>>2]=0;c[b+712+12>>2]=0;sd(b,(c[b+28>>2]|0)+4|0,(c[b+32>>2]|0)+4|0);Ab[c[(c[b>>2]|0)+44>>2]&255](b);e=+g[b+1284>>2];f=+g[b+1288>>2];h=+g[b+1292>>2];if(+g[b+696>>2]>=+g[b+680>>2]){l=(a[b+1300>>0]|0)==0;j=c[(l?b+1160|0:b+1096|0)>>2]|0;d=c[(l?b+1144|0:b+1080|0)>>2]|0;c[k>>2]=c[(l?b+1128|0:b+1064|0)>>2];c[k+4>>2]=d;c[k+8>>2]=j;g[k+12>>2]=0.0;Lh(c[b+28>>2]|0,c[b+32>>2]|0,b+176|0,k,e,f,h,e,f,h)}if(+g[b+700>>2]>=+g[b+684>>2]){d=(a[b+1300>>0]|0)==0;l=c[(d?b+1164|0:b+1100|0)>>2]|0;j=c[(d?b+1148|0:b+1084|0)>>2]|0;c[k>>2]=c[(d?b+1132|0:b+1068|0)>>2];c[k+4>>2]=j;c[k+8>>2]=l;g[k+12>>2]=0.0;Lh(c[b+28>>2]|0,c[b+32>>2]|0,b+260|0,k,e,f,h,e,f,h)}if(+g[b+704>>2]>=+g[b+688>>2]){d=(a[b+1300>>0]|0)==0;l=c[(d?b+1168|0:b+1104|0)>>2]|0;j=c[(d?b+1152|0:b+1088|0)>>2]|0;c[k>>2]=c[(d?b+1136|0:b+1072|0)>>2];c[k+4>>2]=j;c[k+8>>2]=l;g[k+12>>2]=0.0;Lh(c[b+28>>2]|0,c[b+32>>2]|0,b+344|0,k,e,f,h,e,f,h)}j=0;do{e=+g[b+868+(j<<6)>>2];f=+g[b+868+(j<<6)+4>>2];h=+ik(+g[b+1192+(j<<2)>>2],e,f);g[b+868+(j<<6)+52>>2]=h;do if(!(e>f)){if(e>h){c[b+868+(j<<6)+56>>2]=1;d=b+868+(j<<6)+48|0;g[d>>2]=h-e;if(h-e>3.1415927410125732){g[d>>2]=h-e+-6.2831854820251465;d=19;break}if(!(h-e<-3.1415927410125732)){d=19;break}g[d>>2]=h-e+6.2831854820251465;d=19;break}d=b+868+(j<<6)+56|0;if(!(f>2]=0;d=18;break}c[d>>2]=2;d=b+868+(j<<6)+48|0;g[d>>2]=h-f;if(h-f>3.1415927410125732){g[d>>2]=h-f+-6.2831854820251465;d=19;break}if(h-f<-3.1415927410125732){g[d>>2]=h-f+6.2831854820251465;d=19}else d=19}else{c[b+868+(j<<6)+56>>2]=0;d=18}while(0);if((d|0)==18?(d=0,a[b+868+(j<<6)+44>>0]|0):0)d=19;if((d|0)==19){K=b+1208+(j<<4)|0;c[k>>2]=c[K>>2];c[k+4>>2]=c[K+4>>2];c[k+8>>2]=c[K+8>>2];c[k+12>>2]=c[K+12>>2];K=b+428+(j*84|0)|0;d=c[b+28>>2]|0;J=+g[d+4>>2];I=+g[d+20>>2];H=+g[d+36>>2];F=+g[d+8>>2];E=+g[d+24>>2];D=+g[d+40>>2];B=+g[d+12>>2];A=+g[d+28>>2];z=+g[d+44>>2];l=c[b+32>>2]|0;x=+g[l+4>>2];w=+g[l+20>>2];v=+g[l+36>>2];t=+g[l+8>>2];s=+g[l+24>>2];r=+g[l+40>>2];p=+g[l+12>>2];n=+g[l+28>>2];e=+g[l+44>>2];c[K>>2]=0;c[K+4>>2]=0;c[K+8>>2]=0;c[K+12>>2]=0;o=+g[k>>2];m=+g[k+4>>2];f=+g[k+8>>2];g[b+428+(j*84|0)+16>>2]=J*o+I*m+H*f;g[b+428+(j*84|0)+20>>2]=F*o+E*m+D*f;g[b+428+(j*84|0)+24>>2]=B*o+A*m+z*f;g[b+428+(j*84|0)+28>>2]=0.0;g[b+428+(j*84|0)+32>>2]=x*-o+w*-m+v*-f;g[b+428+(j*84|0)+36>>2]=t*-o+s*-m+r*-f;g[b+428+(j*84|0)+40>>2]=p*-o+n*-m+e*-f;g[b+428+(j*84|0)+44>>2]=0.0;G=(J*o+I*m+H*f)*+g[d+396>>2];C=(F*o+E*m+D*f)*+g[d+400>>2];y=(B*o+A*m+z*f)*+g[d+404>>2];g[b+428+(j*84|0)+48>>2]=G;g[b+428+(j*84|0)+52>>2]=C;g[b+428+(j*84|0)+56>>2]=y;g[b+428+(j*84|0)+60>>2]=0.0;u=(x*-o+w*-m+v*-f)*+g[l+396>>2];q=(t*-o+s*-m+r*-f)*+g[l+400>>2];h=(p*-o+n*-m+e*-f)*+g[l+404>>2];g[b+428+(j*84|0)+64>>2]=u;g[b+428+(j*84|0)+68>>2]=q;g[b+428+(j*84|0)+72>>2]=h;g[b+428+(j*84|0)+76>>2]=0.0;g[b+428+(j*84|0)+80>>2]=(J*o+I*m+H*f)*G+(F*o+E*m+D*f)*C+(B*o+A*m+z*f)*y+((x*-o+w*-m+v*-f)*u+(t*-o+s*-m+r*-f)*q+(p*-o+n*-m+e*-f)*h)}j=j+1|0}while((j|0)!=3);i=k;return}function Ud(b,d,e){b=b|0;d=d|0;e=e|0;var f=0.0,h=0,j=0,k=0,l=0,m=0,n=0,o=0.0,p=0,q=0,r=0,s=0;p=i;i=i+128|0;c[b+68>>2]=(c[b+68>>2]|0)+1;c[p>>2]=c[d>>2];c[p+4>>2]=c[d+4>>2];c[p+8>>2]=c[d+8>>2];c[p+12>>2]=c[d+12>>2];c[p+16>>2]=c[d+16>>2];c[p+16+4>>2]=c[d+16+4>>2];c[p+16+8>>2]=c[d+16+8>>2];c[p+16+12>>2]=c[d+16+12>>2];c[p+32>>2]=c[d+32>>2];c[p+32+4>>2]=c[d+32+4>>2];c[p+32+8>>2]=c[d+32+8>>2];c[p+32+12>>2]=c[d+32+12>>2];c[p+48>>2]=c[d+48>>2];c[p+48+4>>2]=c[d+48+4>>2];c[p+48+8>>2]=c[d+48+8>>2];c[p+48+12>>2]=c[d+48+12>>2];n=c[e+4>>2]|0;o=+Sb[c[(c[e>>2]|0)+48>>2]&15](e);mc[c[(c[e>>2]|0)+8>>2]&127](e,d,p+112|0,p+96|0);f=+g[p+112>>2];if(+g[b+32>>2]>f)g[b+32>>2]=f;f=+g[p+96>>2];if(+g[b+48>>2]>2]=f;f=+g[p+112+4>>2];if(+g[b+36>>2]>f)g[b+36>>2]=f;f=+g[p+96+4>>2];if(+g[b+52>>2]>2]=f;f=+g[p+112+8>>2];if(+g[b+40>>2]>f)g[b+40>>2]=f;f=+g[p+96+8>>2];if(+g[b+56>>2]>2]=f;l=c[b+64>>2]|0;if(!l){l=b+16|0;k=0}else{c[p+64>>2]=c[p+112>>2];c[p+64+4>>2]=c[p+112+4>>2];c[p+64+8>>2]=c[p+112+8>>2];c[p+64+12>>2]=c[p+112+12>>2];c[p+64+16>>2]=c[p+96>>2];c[p+64+16+4>>2]=c[p+96+4>>2];c[p+64+16+8>>2]=c[p+96+8>>2];c[p+64+16+12>>2]=c[p+96+12>>2];k=c[b+16>>2]|0;d=c[l+4>>2]|0;if(!d){c[6435]=(c[6435]|0)+1;d=yc(63)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}h=d;j=h+44|0;do{c[h>>2]=0;h=h+4|0}while((h|0)<(j|0))}else c[l+4>>2]=0;c[d+32>>2]=0;c[d+36>>2]=k;c[d+40>>2]=0;c[d>>2]=c[p+64>>2];c[d+4>>2]=c[p+64+4>>2];c[d+8>>2]=c[p+64+8>>2];c[d+12>>2]=c[p+64+12>>2];c[d+16>>2]=c[p+64+16>>2];c[d+20>>2]=c[p+64+20>>2];c[d+24>>2]=c[p+64+24>>2];c[d+28>>2]=c[p+64+28>>2];lf(l,c[l>>2]|0,d);c[l+12>>2]=(c[l+12>>2]|0)+1;l=b+16|0;k=d}d=c[l>>2]|0;if((d|0)==(c[b+20>>2]|0)?(m=d|0?d<<1:1,(d|0)<(m|0)):0){if(!m)j=0;else{c[6435]=(c[6435]|0)+1;d=yc((m*80|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}j=d;d=c[l>>2]|0}if((d|0)>0){h=0;do{q=j+(h*80|0)|0;r=c[b+24>>2]|0;s=r+(h*80|0)|0;c[q>>2]=c[s>>2];c[q+4>>2]=c[s+4>>2];c[q+8>>2]=c[s+8>>2];c[q+12>>2]=c[s+12>>2];q=j+(h*80|0)+16|0;s=r+(h*80|0)+16|0;c[q>>2]=c[s>>2];c[q+4>>2]=c[s+4>>2];c[q+8>>2]=c[s+8>>2];c[q+12>>2]=c[s+12>>2];q=j+(h*80|0)+32|0;s=r+(h*80|0)+32|0;c[q>>2]=c[s>>2];c[q+4>>2]=c[s+4>>2];c[q+8>>2]=c[s+8>>2];c[q+12>>2]=c[s+12>>2];q=j+(h*80|0)+48|0;s=r+(h*80|0)+48|0;c[q>>2]=c[s>>2];c[q+4>>2]=c[s+4>>2];c[q+8>>2]=c[s+8>>2];c[q+12>>2]=c[s+12>>2];q=j+(h*80|0)+64|0;r=r+(h*80|0)+64|0;c[q>>2]=c[r>>2];c[q+4>>2]=c[r+4>>2];c[q+8>>2]=c[r+8>>2];c[q+12>>2]=c[r+12>>2];h=h+1|0}while((h|0)!=(d|0))}d=c[b+24>>2]|0;if(d|0){if(a[b+28>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[b+24>>2]=0}a[b+28>>0]=1;c[b+24>>2]=j;c[b+20>>2]=m;d=c[l>>2]|0}s=c[b+24>>2]|0;r=s+(d*80|0)|0;c[r>>2]=c[p>>2];c[r+4>>2]=c[p+4>>2];c[r+8>>2]=c[p+8>>2];c[r+12>>2]=c[p+12>>2];r=s+(d*80|0)+16|0;c[r>>2]=c[p+16>>2];c[r+4>>2]=c[p+16+4>>2];c[r+8>>2]=c[p+16+8>>2];c[r+12>>2]=c[p+16+12>>2];r=s+(d*80|0)+32|0;c[r>>2]=c[p+32>>2];c[r+4>>2]=c[p+32+4>>2];c[r+8>>2]=c[p+32+8>>2];c[r+12>>2]=c[p+32+12>>2];r=s+(d*80|0)+48|0;c[r>>2]=c[p+48>>2];c[r+4>>2]=c[p+48+4>>2];c[r+8>>2]=c[p+48+8>>2];c[r+12>>2]=c[p+48+12>>2];s=s+(d*80|0)+64|0;c[s>>2]=e;c[s+4>>2]=n;g[s+8>>2]=o;c[s+12>>2]=k;c[l>>2]=(c[l>>2]|0)+1;i=p;return}function Vd(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0;while(1){p=(b+d|0)/2|0;m=c[a+12>>2]|0;n=c[m+(p<<4)>>2]|0;o=c[m+(p<<4)+4>>2]|0;p=c[m+(p<<4)+8>>2]|0;e=b;f=d;while(1){a:do if(!n)while(1){j=c[m+(e<<4)>>2]|0;if(!j)g=-1;else g=c[j+12>>2]|0;k=c[m+(e<<4)+4>>2]|0;if(!k)h=-1;else h=c[k+12>>2]|0;if(!o)i=-1;else i=c[o+12>>2]|0;do if((g|0)<=-1){g=(h|0)>(i|0);if(g|(j|0)==0^1)if((j|0)==0&g)break;else break a;if((k|0)!=(o|0))break a;if((c[m+(e<<4)+8>>2]|0)>>>0<=p>>>0)break a}while(0);e=e+1|0}else{l=c[n+12>>2]|0;if(!o)while(1){i=c[m+(e<<4)>>2]|0;if(!i)g=-1;else g=c[i+12>>2]|0;j=c[m+(e<<4)+4>>2]|0;if(!j)h=-1;else h=c[j+12>>2]|0;do if((g|0)<=(l|0)){g=(h|0)>-1;if(g|(i|0)==(n|0)^1)if((i|0)==(n|0)&g)break;else break a;if(j|0)break a;if((c[m+(e<<4)+8>>2]|0)>>>0<=p>>>0)break a}while(0);e=e+1|0}k=c[o+12>>2]|0;while(1){i=c[m+(e<<4)>>2]|0;if(!i)g=-1;else g=c[i+12>>2]|0;j=c[m+(e<<4)+4>>2]|0;if(!j)h=-1;else h=c[j+12>>2]|0;do if((g|0)<=(l|0)){g=(h|0)>(k|0);if(g|(i|0)==(n|0)^1)if((i|0)==(n|0)&g)break;else break a;if((j|0)!=(o|0))break a;if((c[m+(e<<4)+8>>2]|0)>>>0<=p>>>0)break a}while(0);e=e+1|0}}while(0);b:do if(!n)while(1){j=c[m+(f<<4)>>2]|0;if(!j)g=-1;else g=c[j+12>>2]|0;if(!o)h=-1;else h=c[o+12>>2]|0;k=c[m+(f<<4)+4>>2]|0;if(!k)i=-1;else i=c[k+12>>2]|0;do if((g|0)>=-1){g=(h|0)>(i|0);if(g|(j|0)==0^1)if((j|0)==0&g)break;else break b;if((o|0)!=(k|0))break b;if(p>>>0<=(c[m+(f<<4)+8>>2]|0)>>>0)break b}while(0);f=f+-1|0}else{l=c[n+12>>2]|0;if(!o)while(1){i=c[m+(f<<4)>>2]|0;if(!i)g=-1;else g=c[i+12>>2]|0;j=c[m+(f<<4)+4>>2]|0;if(!j)h=-1;else h=c[j+12>>2]|0;do if((l|0)<=(g|0)){g=(h|0)<-1;if(g|(n|0)==(i|0)^1)if((n|0)==(i|0)&g)break;else break b;if(j|0)break b;if(p>>>0<=(c[m+(f<<4)+8>>2]|0)>>>0)break b}while(0);f=f+-1|0}k=c[o+12>>2]|0;while(1){i=c[m+(f<<4)>>2]|0;if(!i)g=-1;else g=c[i+12>>2]|0;j=c[m+(f<<4)+4>>2]|0;if(!j)h=-1;else h=c[j+12>>2]|0;do if((l|0)<=(g|0)){g=(k|0)>(h|0);if(g|(n|0)==(i|0)^1)if((n|0)==(i|0)&g)break;else break b;if((o|0)!=(j|0))break b;if(p>>>0<=(c[m+(f<<4)+8>>2]|0)>>>0)break b}while(0);f=f+-1|0}}while(0);if((e|0)<=(f|0)){h=m+(e<<4)|0;i=c[h>>2]|0;j=c[m+(e<<4)+4>>2]|0;k=c[m+(e<<4)+8>>2]|0;l=c[m+(e<<4)+12>>2]|0;m=m+(f<<4)|0;c[h>>2]=c[m>>2];c[h+4>>2]=c[m+4>>2];c[h+8>>2]=c[m+8>>2];c[h+12>>2]=c[m+12>>2];m=c[a+12>>2]|0;c[m+(f<<4)>>2]=i;c[m+(f<<4)+4>>2]=j;c[m+(f<<4)+8>>2]=k;c[m+(f<<4)+12>>2]=l;e=e+1|0;f=f+-1|0}if((e|0)>(f|0))break;m=c[a+12>>2]|0}if((f|0)>(b|0))Vd(a,b,f);if((e|0)<(d|0))b=e;else break}return}function Wd(a,b){a=a|0;b=b|0;var d=0,e=0.0,f=0,h=0,j=0,k=0,l=0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0,s=0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0,A=0,B=0,C=0,D=0,E=0;D=i;i=i+16|0;li(11054);C=c[a+712>>2]|0;if((C|0)>0){c[6435]=(c[6435]|0)+1;d=yc((C<<4|3)+16|0)|0;if(!d)h=0;else{c[(d+4+15&-16)+-4>>2]=d;h=d+4+15&-16}d=0;do{B=h+(d<<4)|0;d=d+1|0;c[B>>2]=0;c[B+4>>2]=0;c[B+8>>2]=0;c[B+12>>2]=0}while((d|0)!=(C|0));f=c[a+712>>2]|0;if((f|0)>0){c[6435]=(c[6435]|0)+1;d=yc((f<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}Qn(d|0,0,f<<2|0)|0;B=h;A=d}else{B=h;A=0}}else{B=0;A=0}s=c[a+1112>>2]|0;if(b){if((s|0)>0){h=c[a+1120>>2]|0;j=0;do{d=c[h+(j<<2)>>2]|0;f=c[d+312>>2]|0;if(f|0){g[d+276>>2]=1.0/+(f|0)*+g[d+276>>2];g[d+280>>2]=1.0/+(f|0)*+g[d+280>>2];g[d+284>>2]=1.0/+(f|0)*+g[d+284>>2];g[d+292>>2]=+g[d+292>>2]*(1.0/+(f|0));g[d+296>>2]=1.0/+(f|0)*+g[d+296>>2];g[d+300>>2]=1.0/+(f|0)*+g[d+300>>2]}j=j+1|0}while((j|0)!=(s|0));j=13}}else j=13;if((j|0)==13?(s|0)>0:0){l=c[a+1120>>2]|0;if(b){b=0;do{d=c[l+(b<<2)>>2]|0;if((c[d+312>>2]|0)>0?(y=+g[a+452>>2],t=+g[d+276>>2]*y,u=y*+g[d+280>>2],v=y*+g[d+284>>2],w=y*+g[d+292>>2],x=y*+g[d+296>>2],y=y*+g[d+300>>2],z=c[d+24>>2]|0,(z|0)>0):0){f=c[d+32>>2]|0;h=c[a+720>>2]|0;j=c[d+12>>2]|0;k=0;do{r=c[f+(k<<2)>>2]|0;q=+g[j+(k<<2)>>2];p=+g[r+8>>2]-+g[d+228>>2];o=+g[r+12>>2]-+g[d+232>>2];n=+g[r+16>>2]-+g[d+236>>2];E=B+(((r-h|0)/104|0)<<4)|0;g[E>>2]=+g[E>>2]+q*(t+(x*n-y*o));E=B+(((r-h|0)/104|0)<<4)+4|0;g[E>>2]=+g[E>>2]+q*(u+(y*p-w*n));E=B+(((r-h|0)/104|0)<<4)+8|0;g[E>>2]=q*(v+(w*o-x*p))+ +g[E>>2];r=A+(((r-h|0)/104|0)<<2)|0;g[r>>2]=q+ +g[r>>2];k=k+1|0}while((k|0)!=(z|0))}b=b+1|0}while((b|0)!=(s|0))}else{b=0;do{d=c[l+(b<<2)>>2]|0;if((c[d+308>>2]|0)>0?(q=+g[a+452>>2],e=+g[d+244>>2]*q,m=q*+g[d+248>>2],n=q*+g[d+252>>2],o=q*+g[d+260>>2],p=q*+g[d+264>>2],q=q*+g[d+268>>2],r=c[d+24>>2]|0,(r|0)>0):0){f=c[d+32>>2]|0;h=c[a+720>>2]|0;j=c[d+12>>2]|0;k=0;do{E=c[f+(k<<2)>>2]|0;y=+g[j+(k<<2)>>2];x=+g[E+8>>2]-+g[d+228>>2];w=+g[E+12>>2]-+g[d+232>>2];v=+g[E+16>>2]-+g[d+236>>2];z=B+(((E-h|0)/104|0)<<4)|0;g[z>>2]=+g[z>>2]+y*(e+(p*v-q*w));z=B+(((E-h|0)/104|0)<<4)+4|0;g[z>>2]=+g[z>>2]+y*(m+(q*x-o*v));z=B+(((E-h|0)/104|0)<<4)+8|0;g[z>>2]=y*(n+(o*w-p*x))+ +g[z>>2];E=A+(((E-h|0)/104|0)<<2)|0;g[E>>2]=y+ +g[E>>2];k=k+1|0}while((k|0)!=(r|0))}b=b+1|0}while((b|0)!=(s|0))}}if((C|0)>0){d=0;do{e=+g[A+(d<<2)>>2];if(e>0.0){E=c[a+720>>2]|0;x=1.0/e*+g[B+(d<<4)+4>>2];y=1.0/e*+g[B+(d<<4)+8>>2];z=E+(d*104|0)+8|0;g[z>>2]=1.0/e*+g[B+(d<<4)>>2]+ +g[z>>2];z=E+(d*104|0)+12|0;g[z>>2]=x+ +g[z>>2];E=E+(d*104|0)+16|0;g[E>>2]=y+ +g[E>>2]}d=d+1|0}while((d|0)!=(C|0))}if(A|0){c[6436]=(c[6436]|0)+1;hd(c[A+-4>>2]|0)}if(B|0){c[6436]=(c[6436]|0)+1;hd(c[B+-4>>2]|0)}d=c[2357]|0;E=(c[d+16>>2]|0)+-1|0;c[d+16>>2]=E;if(E|0){i=D;return}do if(c[d+4>>2]|0){tb(D|0,0)|0;E=c[6434]|0;g[d+8>>2]=+g[d+8>>2]+ +(((c[D+4>>2]|0)-(c[E+4>>2]|0)+(((c[D>>2]|0)-(c[E>>2]|0)|0)*1e6|0)-(c[d+12>>2]|0)|0)>>>0)/1.0e3;if(!(c[d+16>>2]|0)){d=c[2357]|0;break}else{i=D;return}}while(0);c[2357]=c[d+20>>2];i=D;return}function Xd(b,d,e,f,h,j){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;var l=0,m=0.0,n=0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0,D=0;C=i;i=i+304|0;B=+g[e+48>>2]-+g[d+48>>2];z=+g[e+52>>2]-+g[d+52>>2];A=+g[e+56>>2]-+g[d+56>>2];Gf(d,e,C+288|0,C+240|0);v=+g[C+240>>2];t=+g[C+288>>2]*v;u=v*+g[C+288+4>>2];v=v*+g[C+288+8>>2];g[C+208>>2]=t;g[C+208+4>>2]=u;g[C+208+8>>2]=v;g[C+208+12>>2]=0.0;w=+g[h+48>>2]-+g[f+48>>2];x=+g[h+52>>2]-+g[f+52>>2];y=+g[h+56>>2]-+g[f+56>>2];Gf(f,h,C+288|0,C+240|0);r=+g[C+240>>2];p=+g[C+288>>2]*r;q=r*+g[C+288+4>>2];r=r*+g[C+288+8>>2];g[C+192>>2]=p;g[C+192+4>>2]=q;g[C+192+8>>2]=r;g[C+192+12>>2]=0.0;e=c[b+12>>2]|0;s=+Sb[c[(c[e>>2]|0)+16>>2]&15](e);e=c[b+16>>2]|0;if(!e)m=0.0;else m=+Sb[c[(c[e>>2]|0)+16>>2]&15](e);s=s*+O(+(t*t+u*u+v*v))+m*+O(+(p*p+q*q+r*r));if(s+ +O(+((w-B)*(w-B)+(x-z)*(x-z)+(y-A)*(y-A)))==0.0){j=0;i=C;return j|0}c[C+240>>2]=9160;g[C+240+36>>2]=999999984306749440.0;a[C+240+40>>0]=0;Ld(b,d,f,C+240|0);h=(a[C+240+40>>0]|0)==0;c[C+288>>2]=c[C+240+20>>2];c[C+288+4>>2]=c[C+240+20+4>>2];c[C+288+8>>2]=c[C+240+20+8>>2];c[C+288+12>>2]=c[C+240+20+12>>2];a:do if(!h?(o=c[C+240+4>>2]|0,l=c[C+240+8>>2]|0,n=c[C+240+12>>2]|0,v=(w-B)*(c[k>>2]=o,+g[k>>2]),v=v+(x-z)*(c[k>>2]=l,+g[k>>2]),!(s+(v+(y-A)*(c[k>>2]=n,+g[k>>2]))<=1.1920928955078125e-07)):0){m=+g[C+240+16>>2];p=+g[C+240+36>>2]+ +g[j+172>>2];b:do if(p>1.0000000474974513e-03){q=p;r=0.0;h=0;while(1){e=c[j+168>>2]|0;if(e|0){D=c[(c[e>>2]|0)+20>>2]|0;c[C+224>>2]=1065353216;c[C+224+4>>2]=1065353216;c[C+224+8>>2]=1065353216;g[C+224+12>>2]=0.0;Fb[D&7](e,C+288|0,.20000000298023224,C+224|0)}m=(w-B)*(c[k>>2]=o,+g[k>>2]);m=m+(x-z)*(c[k>>2]=l,+g[k>>2]);m=s+(m+(y-A)*(c[k>>2]=n,+g[k>>2]));if(m<=1.1920928955078125e-07){l=0;break a}p=r+q/m;if(!(!(p<=r)&(!(p<0.0)&!(p>1.0)))){l=0;break a}Zg(d,B,z,A,C+208|0,p,C+112|0);Zg(f,w,x,y,C+192|0,p,C+48|0);l=c[j+168>>2]|0;if(l|0){D=c[(c[l>>2]|0)+20>>2]|0;c[C+176>>2]=1065353216;c[C+176+4>>2]=0;c[C+176+8>>2]=0;g[C+176+12>>2]=0.0;Fb[D&7](l,C+112+48|0,.20000000298023224,C+176|0)}zb[c[c[j>>2]>>2]&31](j,p);c[C>>2]=9160;g[C+36>>2]=999999984306749440.0;a[C+40>>0]=0;Ld(b,C+112|0,C+48|0,C);if(!(a[C+40>>0]|0)){l=15;break}m=+g[C+36>>2];q=+g[j+172>>2];c[C+288>>2]=c[C+20>>2];c[C+288+4>>2]=c[C+20+4>>2];c[C+288+8>>2]=c[C+20+8>>2];c[C+288+12>>2]=c[C+20+12>>2];e=h+1|0;if((h|0)>63){l=16;break}n=c[C+12>>2]|0;l=c[C+8>>2]|0;o=c[C+4>>2]|0;q=m+q;if(!(q>1.0000000474974513e-03)){m=+g[C+16>>2];break b}else{r=p;h=e}}if((l|0)==15)ic[c[(c[j>>2]|0)+8>>2]&127](j,-1,h);else if((l|0)==16)ic[c[(c[j>>2]|0)+8>>2]&127](j,-2,e);l=0;break a}else p=0.0;while(0);g[j+164>>2]=p;c[j+132>>2]=o;c[j+136>>2]=l;c[j+140>>2]=n;g[j+144>>2]=m;c[j+148>>2]=c[C+288>>2];c[j+148+4>>2]=c[C+288+4>>2];c[j+148+8>>2]=c[C+288+8>>2];c[j+148+12>>2]=c[C+288+12>>2];l=1}else l=0;while(0);D=l;i=C;return D|0}function Yd(a,b){a=a|0;b=b|0;var d=0.0,e=0.0,f=0.0,h=0,i=0,j=0.0,l=0.0,m=0,n=0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0,v=0,w=0.0,x=0.0,y=0,z=0.0,A=0.0,B=0.0;c[a+556>>2]=c[b>>2];c[a+556+4>>2]=c[b+4>>2];c[a+556+8>>2]=c[b+8>>2];c[a+556+12>>2]=c[b+12>>2];q=+g[a+568>>2];r=+g[a+560>>2];s=+g[a+564>>2];p=+g[a+556>>2];d=-p-r*0.0-s*0.0;e=(s+q*0.0-p*0.0)*-s+(q*(q+r*0.0-s*0.0)+d*-p)-(q*0.0+p*0.0-r)*-r;f=(q*0.0+p*0.0-r)*-p+(q*(s+q*0.0-p*0.0)+d*-r)-(q+r*0.0-s*0.0)*-s;d=(q+r*0.0-s*0.0)*-r+(d*-s+q*(q*0.0+p*0.0-r))-(s+q*0.0-p*0.0)*-p;if(d*0.0+(f*0.0+e)<-.9999998807907104){j=-0.0;l=1.0;d=0.0;e=0.0}else{B=+O(+((d*0.0+(f*0.0+e)+1.0)*2.0));j=(d*0.0-f*0.0)*(1.0/B);l=(e*0.0-d)*(1.0/B);d=(f-e*0.0)*(1.0/B);e=B*.5}z=1.0/+O(+(e*e+(j*j+l*l+d*d)));j=j*z;n=(g[k>>2]=j,c[k>>2]|0);w=l*z;t=d*z;v=(g[k>>2]=t,c[k>>2]|0);d=e*z;u=(g[k>>2]=d,c[k>>2]|0);e=1.0/+O(+((d*q-p*-j-r*-w-s*-t)*(d*q-p*-j-r*-w-s*-t)+((q*-t+d*s+r*-j-p*-w)*(q*-t+d*s+r*-j-p*-w)+((p*d+q*-j+s*-w-r*-t)*(p*d+q*-j+s*-w-r*-t)+(p*-t+(q*-w+d*r)-s*-j)*(p*-t+(q*-w+d*r)-s*-j)))));z=(p*d+q*-j+s*-w-r*-t)*e;i=(g[k>>2]=z,c[k>>2]|0);A=e*(p*-t+(q*-w+d*r)-s*-j);b=(g[k>>2]=A,c[k>>2]|0);B=e*(q*-t+d*s+r*-j-p*-w);h=(g[k>>2]=B,c[k>>2]|0);p=e*(d*q-p*-j-r*-w-s*-t);e=+g[a+444>>2];m=(g[k>>2]=e,c[k>>2]|0);if(e>=.05000000074505806?(x=+g[a+448>>2],x>=.05000000074505806):0){d=d<-1.0?-1.0:d;d=+T(+(d>1.0?1.0:d))*2.0;if(d>1.1920928955078125e-07){f=1.0/+O(+(t*t+(j*j+w*w)));if(+N(+(w*f))>1.1920928955078125e-07){x=+O(+((t*f*t*f/(w*f*w*f)+1.0)/(1.0/(x*x)+t*f*t*f/(w*f*w*f)/(e*e))));j=j*f;l=w*f;f=t*f;m=(g[k>>2]=x,c[k>>2]|0)}else{j=j*f;l=w*f;f=t*f}}else{j=0.0;l=0.0;f=0.0;m=0}if(+N(+d)>1.1920928955078125e-07){e=(c[k>>2]=m,+g[k>>2]);if(!(d>e)){if(d<-e)d=-e}else d=e;x=d*.5;w=+R(+x)/+O(+(j*j+l*l+f*f));x=+Q(+x);y=(g[k>>2]=j*w,c[k>>2]|0);v=(g[k>>2]=f*w,c[k>>2]|0);w=l*w;u=(g[k>>2]=x,c[k>>2]|0)}else y=n}else y=n;d=+g[a+452>>2];if(d>=.05000000074505806){e=p<-1.0?-1.0:p;e=+T(+(e>1.0?1.0:e))*2.0;if(e>3.1415927410125732){o=(g[k>>2]=-z,c[k>>2]|0);n=(g[k>>2]=-A,c[k>>2]|0);e=-p<-1.0?-1.0:-p;m=(g[k>>2]=-B,c[k>>2]|0);e=+T(+(e>1.0?1.0:e))*2.0}else{o=i;n=b;m=h}f=(c[k>>2]=o,+g[k>>2]);j=(c[k>>2]=n,+g[k>>2]);l=(c[k>>2]=m,+g[k>>2]);if(e>1.1920928955078125e-07){B=1.0/+O(+(f*f+j*j+l*l));o=(g[k>>2]=f*B,c[k>>2]|0);n=(g[k>>2]=j*B,c[k>>2]|0);m=(g[k>>2]=l*B,c[k>>2]|0)}if(+N(+e)>1.1920928955078125e-07){if(!(e>d))if(e<-d)d=-d;else d=e;x=(c[k>>2]=o,+g[k>>2]);z=(c[k>>2]=n,+g[k>>2]);A=(c[k>>2]=m,+g[k>>2]);d=d*.5;B=+R(+d)/+O(+(A*A+(z*z+x*x)));d=+Q(+d);i=(g[k>>2]=x*B,c[k>>2]|0);b=(g[k>>2]=z*B,c[k>>2]|0);h=(g[k>>2]=A*B,c[k>>2]|0)}else d=p}else d=p;s=(c[k>>2]=u,+g[k>>2]);x=(c[k>>2]=i,+g[k>>2]);t=(c[k>>2]=y,+g[k>>2]);B=(c[k>>2]=h,+g[k>>2]);A=(c[k>>2]=v,+g[k>>2]);z=(c[k>>2]=b,+g[k>>2]);g[a+556>>2]=w*B+(s*x+t*d)-A*z;g[a+560>>2]=A*x+(s*z+w*d)-t*B;g[a+564>>2]=t*z+(s*B+A*d)-w*x;g[a+568>>2]=s*d-t*x-w*z-A*B;return}function Zd(b,d){b=b|0;d=d|0;var e=0,f=0,h=0,i=0,j=0,k=0,l=0,m=0;c[b>>2]=5224;c[6435]=(c[6435]|0)+1;e=yc(379)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}g[e+308>>2]=9.999999747378752e-05;f=e+332|0;a[f>>0]=a[f>>0]&-16;c[b+24>>2]=e;f=(c[d+20>>2]|0)==0;c[6435]=(c[6435]|0)+1;e=yc(23)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}if(f){c[e>>2]=9072;c[b+28>>2]=e;f=b+28|0}else{c[e>>2]=9120;c[b+28>>2]=e;f=b+28|0}c[6435]=(c[6435]|0)+1;e=yc(43)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}k=c[b+24>>2]|0;l=c[f>>2]|0;a[e+4>>0]=0;c[e>>2]=6032;c[e+16>>2]=0;c[e+20>>2]=3;c[e+12>>2]=k;c[e+8>>2]=l;c[b+32>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5256;c[b+36>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5276;c[b+40>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5296;c[b+44>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5316;c[b+48>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5336;c[b+52>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5356;c[b+56>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5376;c[b+60>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5396;c[b+76>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e>>2]=5396;c[b+80>>2]=e;a[e+4>>0]=1;c[6435]=(c[6435]|0)+1;e=yc(27)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5416;c[b+72>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(35)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}a[e+4>>0]=0;c[e>>2]=5436;c[e+8>>2]=1;c[e+12>>2]=0;c[b+88>>2]=e;c[6435]=(c[6435]|0)+1;e=yc(35)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[e>>2]=5436;c[e+8>>2]=1;c[e+12>>2]=0;c[b+84>>2]=e;a[e+4>>0]=1;l=c[d+16>>2]|0;l=(l|0)>80?l:80;e=c[d>>2]|0;if(!e){a[b+12>>0]=1;c[6435]=(c[6435]|0)+1;e=yc(39)|0;if(!e)k=0;else{c[(e+4+15&-16)+-4>>2]=e;k=e+4+15&-16}e=c[d+8>>2]|0;c[k>>2]=772;f=k+4|0;c[f>>2]=e;c[6435]=(c[6435]|0)+1;e=yc((e*772|3)+16|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[k+16>>2]=e;c[k+12>>2]=e;f=c[f>>2]|0;c[k+8>>2]=f;if(f+-1|0){h=c[k>>2]|0;i=f+-1|0;j=e;do{m=j;j=j+h|0;c[m>>2]=j;i=i+-1|0}while((i|0)!=0);e=e+(_(h,f+-1|0)|0)|0}c[e>>2]=0;c[b+8>>2]=k}else{a[b+12>>0]=0;c[b+8>>2]=e}e=c[d+4>>2]|0;if(e|0){a[b+20>>0]=0;c[b+16>>2]=e;return}a[b+20>>0]=1;c[6435]=(c[6435]|0)+1;e=yc(39)|0;if(!e)k=0;else{c[(e+4+15&-16)+-4>>2]=e;k=e+4+15&-16}e=c[d+12>>2]|0;c[k>>2]=l;f=k+4|0;c[f>>2]=e;e=_(e,l)|0;c[6435]=(c[6435]|0)+1;e=yc(e+19|0)|0;if(!e)e=0;else{c[(e+4+15&-16)+-4>>2]=e;e=e+4+15&-16}c[k+16>>2]=e;c[k+12>>2]=e;f=c[f>>2]|0;c[k+8>>2]=f;if(f+-1|0){h=c[k>>2]|0;i=f+-1|0;j=e;do{m=j;j=j+h|0;c[m>>2]=j;i=i+-1|0}while((i|0)!=0);e=e+(_(h,f+-1|0)|0)|0}c[e>>2]=0;c[b+16>>2]=k;return}function _d(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=+h;var j=0,k=0,l=0,m=0,n=0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0,E=0;D=i;i=i+80|0;B=+g[e+4>>2];C=+g[e+20>>2];o=+g[e+36>>2];p=+g[e+8>>2];q=+g[e+24>>2];r=+g[e+40>>2];s=+g[e+12>>2];t=+g[e+28>>2];u=+g[e+44>>2];v=-+g[e+52>>2];w=-+g[e+56>>2];x=-+g[e+60>>2];l=c[b+720>>2]|0;y=+g[l+(d*104|0)+8>>2];z=+g[l+(d*104|0)+12>>2];A=+g[l+(d*104|0)+16>>2];a:do if(f){f=c[b+268>>2]|0;b:do if((f|0)>0){k=c[b+276>>2]|0;j=0;while(1){if((c[k+(j<<2)>>2]|0)==(e|0))break;j=j+1|0;if((j|0)>=(f|0))break b}if((j|0)!=(f|0)){f=l;break a}}while(0);if((f|0)==(c[b+272>>2]|0)?(m=f|0?f<<1:1,(f|0)<(m|0)):0){if(!m)k=0;else{c[6435]=(c[6435]|0)+1;f=yc((m<<2|3)+16|0)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}k=f;f=c[b+268>>2]|0}if((f|0)>0){j=0;do{c[k+(j<<2)>>2]=c[(c[b+276>>2]|0)+(j<<2)>>2];j=j+1|0}while((j|0)!=(f|0))}j=c[b+276>>2]|0;if(j){if(a[b+280>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0);f=c[b+268>>2]|0}c[b+276>>2]=0}a[b+280>>0]=1;c[b+276>>2]=k;c[b+272>>2]=m}c[(c[b+276>>2]|0)+(f<<2)>>2]=e;c[b+268>>2]=f+1;f=c[b+720>>2]|0}else f=l;while(0);l=f+(d*104|0)|0;f=f+(d*104|0)+100|0;a[f>>0]=a[f>>0]|1;f=c[b+792>>2]|0;if((f|0)==(c[b+796>>2]|0)?(n=f|0?f<<1:1,(f|0)<(n|0)):0){if(!n)k=0;else{c[6435]=(c[6435]|0)+1;f=yc(n*96|19)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}k=f;f=c[b+792>>2]|0}if((f|0)>0){j=0;do{d=k+(j*96|0)|0;m=c[b+800>>2]|0;E=m+(j*96|0)|0;c[d>>2]=c[E>>2];c[d+4>>2]=c[E+4>>2];c[d+8>>2]=c[E+8>>2];c[d+12>>2]=c[E+12>>2];c[d+16>>2]=c[E+16>>2];c[d+20>>2]=c[E+20>>2];c[d+24>>2]=c[E+24>>2];d=k+(j*96|0)+28|0;E=m+(j*96|0)+28|0;c[d>>2]=c[E>>2];c[d+4>>2]=c[E+4>>2];c[d+8>>2]=c[E+8>>2];c[d+12>>2]=c[E+12>>2];d=k+(j*96|0)+44|0;E=m+(j*96|0)+44|0;c[d>>2]=c[E>>2];c[d+4>>2]=c[E+4>>2];c[d+8>>2]=c[E+8>>2];c[d+12>>2]=c[E+12>>2];d=k+(j*96|0)+60|0;E=m+(j*96|0)+60|0;c[d>>2]=c[E>>2];c[d+4>>2]=c[E+4>>2];c[d+8>>2]=c[E+8>>2];c[d+12>>2]=c[E+12>>2];d=k+(j*96|0)+76|0;m=m+(j*96|0)+76|0;c[d>>2]=c[m>>2];c[d+4>>2]=c[m+4>>2];c[d+8>>2]=c[m+8>>2];c[d+12>>2]=c[m+12>>2];c[d+16>>2]=c[m+16>>2];j=j+1|0}while((j|0)!=(f|0))}f=c[b+800>>2]|0;if(f|0){if(a[b+804>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+800>>2]=0}a[b+804>>0]=1;c[b+800>>2]=k;c[b+796>>2]=n;f=c[b+792>>2]|0}E=c[b+800>>2]|0;c[E+(f*96|0)>>2]=l;g[E+(f*96|0)+4>>2]=B*v+C*w+o*x+(B*y+C*z+o*A);g[E+(f*96|0)+8>>2]=p*v+q*w+r*x+(p*y+q*z+r*A);g[E+(f*96|0)+12>>2]=s*v+t*w+u*x+(s*y+t*z+u*A);g[E+(f*96|0)+16>>2]=0.0;c[E+(f*96|0)+20>>2]=e;g[E+(f*96|0)+24>>2]=h;e=E+(f*96|0)+28|0;c[e>>2]=c[D+56>>2];c[e+4>>2]=c[D+56+4>>2];c[e+8>>2]=c[D+56+8>>2];c[e+12>>2]=c[D+56+12>>2];e=E+(f*96|0)+44|0;c[e>>2]=c[D+40>>2];c[e+4>>2]=c[D+40+4>>2];c[e+8>>2]=c[D+40+8>>2];c[e+12>>2]=c[D+40+12>>2];e=E+(f*96|0)+60|0;c[e>>2]=c[D+24>>2];c[e+4>>2]=c[D+24+4>>2];c[e+8>>2]=c[D+24+8>>2];c[e+12>>2]=c[D+24+12>>2];E=E+(f*96|0)+76|0;c[E>>2]=c[D>>2];c[E+4>>2]=c[D+4>>2];c[E+8>>2]=c[D+8>>2];c[E+12>>2]=c[D+12>>2];c[E+16>>2]=c[D+16>>2];c[b+792>>2]=(c[b+792>>2]|0)+1;i=D;return}function $d(a,b,d,e,f){a=a|0;b=b|0;d=d|0;e=e|0;f=f|0;var h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0,A=0.0,B=0.0,C=0.0,D=0.0,E=0,F=0;E=i;i=i+64|0;A=+g[b+48>>2]-+g[b+112>>2];h=+g[b+52>>2]-+g[b+116>>2];D=+g[b+56>>2]-+g[b+120>>2];B=A*+g[b+64>>2]+h*+g[b+80>>2]+D*+g[b+96>>2];C=A*+g[b+68>>2]+h*+g[b+84>>2]+D*+g[b+100>>2];D=A*+g[b+72>>2]+h*+g[b+88>>2]+D*+g[b+104>>2];e=c[a+8>>2]|0;z=c[a+4>>2]|0;h=+g[z+28>>2]*+g[z+12>>2];A=h+ +g[a+12>>2];p=+g[e+72>>2];q=+g[e+56>>2];r=+g[e+76>>2];s=+g[e+60>>2];t=+g[e+80>>2];u=+g[e+64>>2];v=+g[e+88>>2];w=+g[e+92>>2];x=+g[e+96>>2];k=(r-s)*(x-u)-(t-u)*(w-s);m=(t-u)*(v-q)-(p-q)*(x-u);o=(p-q)*(w-s)-(r-s)*(v-q);n=1.0/+O(+(o*o+(k*k+m*m)));j=(B-q)*n*k+(C-s)*n*m+n*o*(D-u);if(j<0.0){y=-j;l=-(n*k);j=-(n*m);k=-(n*o)}else{y=j;l=n*k;j=n*m;k=n*o}if(!(y0.0&(o>0.0&t>0.0))?!(x<=0.0&(o<=0.0&t<=0.0)):0){if((Eb[c[(c[e>>2]|0)+100>>2]&127](e)|0)<=0){i=E;return}s=0.0;r=0.0;q=0.0;e=0;z=0;do{F=c[a+8>>2]|0;mc[c[(c[F>>2]|0)+104>>2]&127](F,z,E+48|0,E+32|0);m=+g[E+48>>2];w=+g[E+48+4>>2];u=+g[E+48+8>>2];n=+g[E+32>>2]-m;x=+g[E+32+4>>2]-w;v=+g[E+32+8>>2]-u;do if((B-m)*n+(C-w)*x+(D-u)*v>0.0)if((B-m)*n+(C-w)*x+(D-u)*v>2]|0}while((z|0)<(Eb[c[(c[F>>2]|0)+100>>2]&127](F)|0));if(!(e&1)){i=E;return}else p=A*A}else{p=A*A;s=B-y*l;r=D-y*k;q=C-y*j}n=B-s;o=C-q;m=D-r;if(!(n*n+o*o+m*m1.1920928955078125e-07){j=+O(+(n*n+o*o+m*m));h=h-j;l=n*(1.0/j);k=m*(1.0/j);j=o*(1.0/j)}h=-h;if(f){x=+g[b+64>>2];y=+g[b+68>>2];A=+g[b+72>>2];B=x*l+y*j+A*k;o=+g[b+80>>2];p=+g[b+84>>2];t=+g[b+88>>2];C=l*o+j*p+k*t;u=+g[b+96>>2];v=+g[b+100>>2];w=+g[b+104>>2];D=l*u+j*v+k*w;g[E+48>>2]=-B;g[E+48+4>>2]=-C;g[E+48+8>>2]=-D;g[E+48+12>>2]=0.0;C=s*o+q*p+r*t+ +g[b+116>>2]+C*h;D=s*u+q*v+r*w+ +g[b+120>>2]+D*h;g[E+32>>2]=s*x+q*y+r*A+ +g[b+112>>2]+B*h;g[E+32+4>>2]=C;g[E+32+8>>2]=D;g[E+32+12>>2]=0.0;hc[c[(c[d>>2]|0)+16>>2]&15](d,E+48|0,E+32|0,h);i=E;return}else{F=c[(c[d>>2]|0)+16>>2]|0;y=+g[b+64>>2];A=+g[b+68>>2];B=+g[b+72>>2];u=+g[b+80>>2];v=+g[b+84>>2];C=+g[b+88>>2];w=+g[b+96>>2];x=+g[b+100>>2];D=+g[b+104>>2];g[E+16>>2]=y*l+A*j+B*k;g[E+16+4>>2]=l*u+j*v+k*C;g[E+16+8>>2]=l*w+j*x+k*D;g[E+16+12>>2]=0.0;C=s*u+q*v+r*C+ +g[b+116>>2];D=s*w+q*x+r*D+ +g[b+120>>2];g[E>>2]=s*y+q*A+r*B+ +g[b+112>>2];g[E+4>>2]=C;g[E+8>>2]=D;g[E+12>>2]=0.0;hc[F&15](d,E+16|0,E,h);i=E;return}}function ae(b){b=b|0;var d=0.0,e=0,f=0,h=0,j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0,r=0;r=i;i=i+80|0;if((Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0?(q=Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0,(Eb[c[(c[q>>2]|0)+48>>2]&127](q)|0)&8|0):0)?(e=c[b+24>>2]|0,e=Eb[c[(c[e>>2]|0)+36>>2]&127](e)|0,c[r+64>>2]=1065353216,c[r+64+4>>2]=1065353216,c[r+64+8>>2]=0,g[r+64+12>>2]=0.0,(e|0)>0):0){j=0;do{f=c[b+24>>2]|0;f=Zb[c[(c[f>>2]|0)+40>>2]&31](f,j)|0;h=c[f+748>>2]|0;if((h|0)>0){k=0;do{q=Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0;Bb[c[(c[q>>2]|0)+32>>2]&0](q,f+4+(k*184|0)+32|0,f+4+(k*184|0)+64|0,+g[f+4+(k*184|0)+80>>2],c[f+4+(k*184|0)+148>>2]|0,r+64|0);k=k+1|0}while((k|0)!=(h|0))}j=j+1|0}while((j|0)!=(e|0))}if(!(Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0)){i=r;return}q=Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0;if(!((Eb[c[(c[q>>2]|0)+48>>2]&127](q)|0)&3)){i=r;return}if((c[b+8>>2]|0)<=0){i=r;return}h=r+64+4|0;j=r+64+8|0;k=r+64+12|0;q=0;do{f=c[(c[b+16>>2]|0)+(q<<2)>>2]|0;if(!(c[f+204>>2]&32)){if(Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0?(e=Eb[c[(c[b>>2]|0)+20>>2]&127](b)|0,(Eb[c[(c[e>>2]|0)+48>>2]&127](e)|0)&1|0):0){c[r+64>>2]=1065353216;c[h>>2]=1065353216;c[j>>2]=1065353216;g[k>>2]=0.0;switch(c[f+216>>2]|0){case 1:{c[r+64>>2]=1065353216;c[h>>2]=1065353216;c[j>>2]=1065353216;g[k>>2]=0.0;break}case 2:{c[r+64>>2]=0;c[h>>2]=1065353216;c[j>>2]=0;g[k>>2]=0.0;break}case 3:{c[r+64>>2]=0;c[h>>2]=1065353216;c[j>>2]=1065353216;g[k>>2]=0.0;break}case 4:{c[r+64>>2]=1065353216;c[h>>2]=0;c[j>>2]=0;g[k>>2]=0.0;break}case 5:{c[r+64>>2]=1065353216;c[h>>2]=1065353216;c[j>>2]=0;g[k>>2]=0.0;break}default:{c[r+64>>2]=1065353216;c[h>>2]=0;c[j>>2]=0;g[k>>2]=0.0}}mc[c[(c[b>>2]|0)+28>>2]&127](b,f+4|0,c[f+192>>2]|0,r+64|0)}e=c[b+72>>2]|0;if(e|0?(Eb[c[(c[e>>2]|0)+48>>2]&127](e)|0)&2|0:0){c[r+32>>2]=1065353216;c[r+32+4>>2]=0;c[r+32+8>>2]=0;g[r+32+12>>2]=0.0;e=c[f+192>>2]|0;mc[c[(c[e>>2]|0)+8>>2]&127](e,f+4|0,r+64|0,r+48|0);g[r+64>>2]=+g[r+64>>2]+-.019999999552965164;g[r+64+4>>2]=+g[r+64+4>>2]+-.019999999552965164;g[r+64+8>>2]=+g[r+64+8>>2]+-.019999999552965164;g[r+48>>2]=+g[r+48>>2]+.019999999552965164;g[r+48+4>>2]=+g[r+48+4>>2]+.019999999552965164;g[r+48+8>>2]=+g[r+48+8>>2]+.019999999552965164;do if((a[b+44>>0]|0?(c[f+236>>2]|0)==2:0)?(c[f+204>>2]&3|0)==0:0){e=c[f+192>>2]|0;mc[c[(c[e>>2]|0)+8>>2]&127](e,f+68|0,r+16|0,r);d=+g[r+16>>2]+-.019999999552965164;g[r+16>>2]=d;l=+g[r+16+4>>2]+-.019999999552965164;g[r+16+4>>2]=l;m=+g[r+16+8>>2]+-.019999999552965164;g[r+16+8>>2]=m;n=+g[r>>2]+.019999999552965164;g[r>>2]=n;o=+g[r+4>>2]+.019999999552965164;g[r+4>>2]=o;p=+g[r+8>>2]+.019999999552965164;g[r+8>>2]=p;if(d<+g[r+64>>2])g[r+64>>2]=d;if(l<+g[r+64+4>>2])g[r+64+4>>2]=l;if(m<+g[r+64+8>>2])g[r+64+8>>2]=m;d=+g[r+16+12>>2];if(d<+g[r+64+12>>2])g[r+64+12>>2]=d;if(+g[r+48>>2]>2]=n;if(+g[r+48+4>>2]>2]=o;if(+g[r+48+8>>2]>2]=p;d=+g[r+12>>2];if(!(+g[r+48+12>>2]>2]=d}while(0);f=c[b+72>>2]|0;mc[c[(c[f>>2]|0)+52>>2]&127](f,r+64|0,r+48|0,r+32|0)}}q=q+1|0}while((q|0)<(c[b+8>>2]|0));i=r;return}function be(b,d,e,f,h,i,j,k,l,m,n){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;i=i|0;j=j|0;k=k|0;l=l|0;m=m|0;n=n|0;var o=0,p=0,q=0,r=0.0,s=0.0,t=0,u=0.0,v=0.0,w=0.0,x=0.0,y=0,z=0.0,A=0;if((j|0)<2|(k|0)<2){n=0;return n|0}y=_(k,j)|0;c[6435]=(c[6435]|0)+1;b=yc(y>>>0>268435455?18:(y<<4|3)+16|0)|0;if(!b)t=0;else{c[(b+4+15&-16)+-4>>2]=b;t=b+4+15&-16}o=y>>>0>1073741823?-1:y<<2;o=(o|0)==0?1:o;while(1){q=yc(o)|0;if(q|0)break;b=c[6564]|0;c[6564]=b+0;if(!b){p=8;break}jc[b&3]()}if((p|0)==8){n=Ya(4)|0;c[n>>2]=9640;pb(n|0,2800,251)}if((k|0)>0?(j|0)>0:0){p=0;do{z=+(p|0)/+(k+-1|0);r=+g[e>>2];r=r+z*(+g[h>>2]-r);s=+g[e+4>>2];s=s+z*(+g[h+4>>2]-s);u=+g[e+8>>2];u=u+z*(+g[h+8>>2]-u);v=+g[f>>2];w=+g[f+4>>2];x=+g[f+8>>2];b=_(p,j)|0;v=v+z*(+g[i>>2]-v)-r;w=w+z*(+g[i+4>>2]-w)-s;x=x+z*(+g[i+8>>2]-x)-u;o=0;do{z=+(o|0)/+(j+-1|0);A=o+b|0;g[t+(A<<4)>>2]=r+v*z;g[t+(A<<4)+4>>2]=s+w*z;g[t+(A<<4)+8>>2]=u+x*z;g[t+(A<<4)+12>>2]=0.0;g[q+(A<<2)>>2]=1.0;o=o+1|0}while((o|0)!=(j|0));p=p+1|0}while((p|0)!=(k|0))}c[6435]=(c[6435]|0)+1;b=yc(1271)|0;if(!b)b=0;else{c[(b+4+15&-16)+-4>>2]=b;b=b+4+15&-16}Kc(b,d,y,t,q);if(l&1|0){g[(c[b+720>>2]|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&2|0){g[(c[b+720>>2]|0)+((j+-1|0)*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&4|0){A=_(k+-1|0,j)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&8|0){A=j+-1+(_(k+-1|0,j)|0)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&16|0){g[(c[b+720>>2]|0)+(((j+-1|0)/2|0)*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&32|0){A=_((k+-1|0)/2|0,j)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&64|0){A=j+-1+(_((k+-1|0)/2|0,j)|0)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&128|0){A=(_(k+-1|0,j)|0)+((j+-1|0)/2|0)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(l&256|0){A=(_((k+-1|0)/2|0,j)|0)+((j+-1|0)/2|0)|0;g[(c[b+720>>2]|0)+(A*104|0)+88>>2]=0.0;a[b+924>>0]=1}if(t|0){c[6436]=(c[6436]|0)+1;hd(c[t+-4>>2]|0)}hd(q);if((k|0)<=0){A=b;return A|0}y=j+-1|0;d=0;o=0;while(1){p=d;d=d+1|0;a:do if((j|0)>0){t=_(p,j)|0;i=_(d,j)|0;s=1.0/+(k+-1|0)*+(k+-1-p|0);r=1.0/+(k+-1|0)*+(k+-2-p|0);if((d|0)<(k|0)){f=0;h=o}else{if((j|0)>1){q=1;p=0}else break;while(1){Rf(b,p+t|0,q+t|0,0,0);p=q+1|0;if((p|0)==(j|0))break a;else{A=q;q=p;p=A}}}while(1){p=f+1|0;q=f+t|0;e=f+i|0;if((f|0)==(j+-1|0))break;Rf(b,q,p+t|0,0,0);Rf(b,q,e,0,0);Zf(b,q,e,p+i|0,0);if(!n)Zf(b,p+i|0,p+t|0,q,0);else{z=1.0/+(j+-1|0)*+(f|0);g[n+(h<<2)>>2]=z;g[n+(h+1<<2)>>2]=s;g[n+(h+2<<2)>>2]=z;g[n+(h+3<<2)>>2]=r;x=1.0/+(j+-1|0)*+(p|0);g[n+(h+4<<2)>>2]=x;g[n+(h+5<<2)>>2]=r;Zf(b,p+i|0,p+t|0,q,0);g[n+(h+6<<2)>>2]=x;g[n+(h+7<<2)>>2]=r;g[n+(h+8<<2)>>2]=x;g[n+(h+9<<2)>>2]=s;g[n+(h+10<<2)>>2]=z;g[n+(h+11<<2)>>2]=s}if(m)Rf(b,q,p+i|0,0,0);f=p;h=h+12|0}Rf(b,y,e,0,0);o=(j*12|0)+-12+o|0}while(0);if((d|0)==(k|0))break;else y=y+j|0}return b|0}function ce(b,d,e,f,h,j,k,l){b=b|0;d=d|0;e=e|0;f=f|0;h=+h;j=+j;k=k|0;l=l|0;var m=0,n=0,o=0,p=0,q=0,r=0,s=0,t=0,u=0,v=0,w=0;w=i;i=i+288|0;c[w+208>>2]=c[d>>2];c[w+208+4>>2]=c[d+4>>2];c[w+208+8>>2]=c[d+8>>2];c[w+208+12>>2]=c[d+12>>2];o=w+208+16|0;c[o>>2]=c[e>>2];c[o+4>>2]=c[e+4>>2];c[o+8>>2]=c[e+8>>2];c[o+12>>2]=c[e+12>>2];e=w+208+32|0;c[e>>2]=c[f>>2];c[e+4>>2]=c[f+4>>2];c[e+8>>2]=c[f+8>>2];c[e+12>>2]=c[f+12>>2];r=c[k>>2]|0;t=c[k+4>>2]|0;u=c[k+8>>2]|0;v=c[k+16>>2]|0;q=c[k+12>>2]|0;p=c[k+20>>2]|0;c[w>>2]=c[w+208>>2];c[w+4>>2]=c[w+208+4>>2];c[w+8>>2]=c[w+208+8>>2];c[w+12>>2]=c[w+208+12>>2];c[w+16>>2]=c[o>>2];c[w+16+4>>2]=c[o+4>>2];c[w+16+8>>2]=c[o+8>>2];c[w+16+12>>2]=c[o+12>>2];c[w+32>>2]=c[e>>2];c[w+32+4>>2]=c[e+4>>2];c[w+32+8>>2]=c[e+8>>2];c[w+32+12>>2]=c[e+12>>2];e=c[b+136>>2]|0;if((e|0)==(c[b+140>>2]|0)?(s=e|0?e<<1:1,(e|0)<(s|0)):0){if(!s)d=0;else{c[6435]=(c[6435]|0)+1;d=yc((s*284|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}e=c[b+136>>2]|0}if((e|0)>0){k=0;do{f=c[b+144>>2]|0;m=d+(k*284|0)|0;n=f+(k*284|0)|0;o=m+92|0;do{c[m>>2]=c[n>>2];m=m+4|0;n=n+4|0}while((m|0)<(o|0));m=d+(k*284|0)+92|0;n=f+(k*284|0)+92|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];m=d+(k*284|0)+108|0;n=f+(k*284|0)+108|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];m=d+(k*284|0)+124|0;n=f+(k*284|0)+124|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];m=d+(k*284|0)+140|0;n=f+(k*284|0)+140|0;c[m>>2]=c[n>>2];c[m+4>>2]=c[n+4>>2];c[m+8>>2]=c[n+8>>2];c[m+12>>2]=c[n+12>>2];m=d+(k*284|0)+156|0;n=f+(k*284|0)+156|0;o=m+128|0;do{c[m>>2]=c[n>>2];m=m+4|0;n=n+4|0}while((m|0)<(o|0));k=k+1|0}while((k|0)!=(e|0))}e=c[b+144>>2]|0;if(e|0){if(a[b+148>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0)}c[b+144>>2]=0}a[b+148>>0]=1;c[b+144>>2]=d;c[b+140>>2]=s;e=c[b+136>>2]|0}d=c[b+144>>2]|0;m=d+(e*284|0)|0;n=w+48|0;o=m+92|0;do{c[m>>2]=c[n>>2];m=m+4|0;n=n+4|0}while((m|0)<(o|0));m=d+(e*284|0)+92|0;c[m>>2]=c[w+192>>2];c[m+4>>2]=c[w+192+4>>2];c[m+8>>2]=c[w+192+8>>2];c[m+12>>2]=c[w+192+12>>2];m=d+(e*284|0)+108|0;c[m>>2]=c[w+176>>2];c[m+4>>2]=c[w+176+4>>2];c[m+8>>2]=c[w+176+8>>2];c[m+12>>2]=c[w+176+12>>2];m=d+(e*284|0)+124|0;c[m>>2]=c[w+160>>2];c[m+4>>2]=c[w+160+4>>2];c[m+8>>2]=c[w+160+8>>2];c[m+12>>2]=c[w+160+12>>2];m=d+(e*284|0)+140|0;c[m>>2]=c[w+144>>2];c[m+4>>2]=c[w+144+4>>2];c[m+8>>2]=c[w+144+8>>2];c[m+12>>2]=c[w+144+12>>2];d=d+(e*284|0)+156|0;m=d;n=w;o=m+48|0;do{c[m>>2]=c[n>>2];m=m+4|0;n=n+4|0}while((m|0)<(o|0));g[d+48>>2]=h;c[d+52>>2]=q;g[d+56>>2]=j;c[d+60>>2]=r;c[d+64>>2]=t;c[d+68>>2]=u;c[d+72>>2]=v;g[d+76>>2]=0.0;g[d+80>>2]=0.0;g[d+84>>2]=0.0;g[d+88>>2]=.10000000149011612;c[d+92>>2]=p;g[d+96>>2]=0.0;g[d+100>>2]=0.0;a[d+104>>0]=l&1;m=d+105|0;n=w+256|0;o=m+23|0;do{a[m>>0]=a[n>>0]|0;m=m+1|0;n=n+1|0}while((m|0)<(o|0));l=c[b+136>>2]|0;c[b+136>>2]=l+1;l=(c[b+144>>2]|0)+(l*284|0)|0;Tg(c[b+116>>2]|0,l,0);Ae(c[b+116>>2]|0,c[b+144>>2]|0,(c[b+136>>2]|0)+-1|0,0);i=w;return l|0}function de(a,d,f,h,j){a=a|0;d=d|0;f=f|0;h=h|0;j=j|0;var k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0,s=0,t=0,u=0,v=0,w=0,x=0,y=0,z=0,A=0,B=0,C=0,D=0,E=0,F=0,G=0,H=0,I=0;I=i;i=i+16|0;c[d+16>>2]=c[f>>2];c[d+16+4>>2]=c[f+4>>2];c[d+16+8>>2]=c[f+8>>2];c[d+16+12>>2]=c[f+12>>2];c[d+32>>2]=c[h>>2];c[d+32+4>>2]=c[h+4>>2];c[d+32+8>>2]=c[h+8>>2];c[d+32+12>>2]=c[h+12>>2];D=c[a+60>>2]|0;E=c[d+12>>2]&65535;Bj(a,I+6|0,+g[f>>2],+g[f+4>>2],+g[f+8>>2],0);Bj(a,I,+g[h>>2],+g[h+4>>2],+g[h+8>>2],1);H=0;do{t=b[D+(E<<6)+48+(H<<1)>>1]|0;w=b[D+(E<<6)+54+(H<<1)>>1]|0;q=b[I+6+(H<<1)>>1]|0;l=a+68+(H<<2)|0;s=c[l>>2]|0;m=(q&65535)-(e[s+((t&65535)<<2)>>1]|0)|0;r=b[I+(H<<1)>>1]|0;y=(r&65535)-(e[s+((w&65535)<<2)>>1]|0)|0;b[s+((t&65535)<<2)>>1]=q;b[s+((w&65535)<<2)>>1]=r;if((m|0)<0)wh(a,H,t);a:do if((y|0)>0?(z=c[l>>2]|0,A=c[a+60>>2]|0,B=e[z+((w&65535)<<2)+2>>1]|0,C=b[z+((w&65535)<<2)+6>>1]|0,C<<16>>16):0){n=1<>1]|0;if((e[s>>1]|0)<(p&65535))break a;q=c[a+60>>2]|0;k=k&65535;if(!(p&1)){if(((((e[A+(B<<6)+54+(n<<1)>>1]|0)>=(e[q+(k<<6)+48+(n<<1)>>1]|0)?(e[q+(k<<6)+54+(n<<1)>>1]|0)>=(e[A+(B<<6)+48+(n<<1)>>1]|0):0)?(e[A+(B<<6)+54+((1<>1]|0)>=(e[q+(k<<6)+48+((1<>1]|0):0)?(e[q+(k<<6)+54+((1<>1]|0)>=(e[A+(B<<6)+48+((1<>1]|0):0)?(G=c[a+92>>2]|0,F=q+((e[s+2>>1]|0)<<6)|0,Ob[c[(c[G>>2]|0)+8>>2]&63](G,F,q+(k<<6)|0)|0,G=c[a+96>>2]|0,G|0):0)Ob[c[(c[G>>2]|0)+8>>2]&63](G,F,q+(k<<6)|0)|0;q=q+(k<<6)+48+(H<<1)|0;b[q>>1]=(b[q>>1]|0)+-1<<16>>16}else{q=q+(k<<6)+54+(H<<1)|0;b[q>>1]=(b[q>>1]|0)+-1<<16>>16}b[o>>1]=(b[o>>1]|0)+1<<16>>16;k=e[s>>1]|e[s+2>>1]<<16;q=e[r>>1]|e[r+2>>1]<<16;b[s>>1]=q;b[s+2>>1]=q>>>16;b[r>>1]=k;b[r+2>>1]=k>>>16;k=b[s+10>>1]|0}while(k<<16>>16!=0)}while(0);b:do if((m|0)>0?(u=c[l>>2]|0,v=b[u+((t&65535)<<2)+6>>1]|0,v<<16>>16):0){p=(c[a+60>>2]|0)+((e[u+((t&65535)<<2)+2>>1]|0)<<6)+48+(H<<1)|0;q=1<>1]|0;if((e[o>>1]|0)<(k&65535))break b;m=c[a+60>>2]|0;l=l&65535;if(!(k&1)){t=m+(l<<6)+48+(H<<1)|0;b[t>>1]=(b[t>>1]|0)+-1<<16>>16}else{k=e[o+2>>1]|0;if(((((e[m+(k<<6)+54+(q<<1)>>1]|0)>=(e[m+(l<<6)+48+(q<<1)>>1]|0)?(e[m+(l<<6)+54+(q<<1)>>1]|0)>=(e[m+(k<<6)+48+(q<<1)>>1]|0):0)?(e[m+(k<<6)+54+((1<>1]|0)>=(e[m+(l<<6)+48+((1<>1]|0):0)?(e[m+(l<<6)+54+((1<>1]|0)>=(e[m+(k<<6)+48+((1<>1]|0):0)?(x=c[a+92>>2]|0,Ib[c[(c[x>>2]|0)+12>>2]&31](x,m+(k<<6)|0,m+(l<<6)|0,j)|0,x=c[a+96>>2]|0,x|0):0)Ib[c[(c[x>>2]|0)+12>>2]&31](x,m+(k<<6)|0,m+(l<<6)|0,j)|0;t=m+(l<<6)+54+(H<<1)|0;b[t>>1]=(b[t>>1]|0)+-1<<16>>16}b[p>>1]=(b[p>>1]|0)+1<<16>>16;l=e[o>>1]|e[o+2>>1]<<16;t=e[n>>1]|e[n+2>>1]<<16;b[o>>1]=t;b[o+2>>1]=t>>>16;b[n>>1]=l;b[n+2>>1]=l>>>16;l=b[o+10>>1]|0}while(l<<16>>16!=0)}while(0);if((y|0)<0)uh(a,H,w,j);H=H+1|0}while((H|0)!=3);k=c[a+108>>2]|0;if(!k){i=I;return}yb[c[(c[k>>2]|0)+16>>2]&31](k,c[d+60>>2]|0,f,h,j);i=I;return}function ee(b,d,e){b=b|0;d=+d;e=+e;var f=0,h=0,j=0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0,t=0.0,u=0.0,v=0.0;s=i;i=i+144|0;f=c[b+8>>2]|0;if(!f){f=c[b+4>>2]|0;if(!f){d=0.0;k=0.0;n=0.0;o=0.0;l=0.0;m=0.0}else{r=+g[f+336>>2];n=+g[b+172>>2];o=+g[f+340>>2];p=+g[b+168>>2];m=+g[b+164>>2];q=+g[f+332>>2];d=r*n-o*p;k=+g[f+316>>2];n=o*m-n*q;o=+g[f+320>>2];l=+g[f+324>>2];m=p*q-r*m}}else{r=+g[f+332>>2];n=+g[b+172>>2];o=+g[f+336>>2];p=+g[b+168>>2];m=+g[b+164>>2];q=+g[f+328>>2];d=r*n-o*p;k=+g[f+312>>2];n=o*m-n*q;o=+g[f+316>>2];l=+g[f+320>>2];m=p*q-r*m}p=k+d;r=o+n;q=l+m;f=c[b+20>>2]|0;if(!f){f=c[b+16>>2]|0;if(!f){d=0.0;k=0.0;n=0.0;o=0.0;l=0.0;m=0.0}else{t=+g[f+336>>2];n=+g[b+188>>2];o=+g[f+340>>2];v=+g[b+184>>2];m=+g[b+180>>2];u=+g[f+332>>2];d=t*n-o*v;k=+g[f+316>>2];n=o*m-n*u;o=+g[f+320>>2];l=+g[f+324>>2];m=v*u-t*m}}else{v=+g[f+332>>2];n=+g[b+188>>2];o=+g[f+336>>2];t=+g[b+184>>2];m=+g[b+180>>2];u=+g[f+328>>2];d=v*n-o*t;k=+g[f+312>>2];n=o*m-n*u;o=+g[f+316>>2];l=+g[f+320>>2];m=t*u-v*m}p=p-(k+d);n=r-(o+n);d=q-(l+m);k=+g[b+196>>2];l=+g[b+200>>2];m=+g[b+204>>2];a[s+108+32>>0]=1;c[s+108+16>>2]=0;c[s+108+16+4>>2]=0;c[s+108+16+8>>2]=0;c[s+108+16+12>>2]=0;c[s+108>>2]=c[b+72>>2];c[s+108+4>>2]=c[b+72+4>>2];c[s+108+8>>2]=c[b+72+8>>2];c[s+108+12>>2]=c[b+72+12>>2];if(k*p+n*l+d*m<0.0){t=+g[b+212>>2];u=+g[s+108>>2]+((k*p+n*l+d*m)*k+(p-(k*p+n*l+d*m)*k)*t);g[s+108>>2]=u;v=(k*p+n*l+d*m)*l+t*(n-(k*p+n*l+d*m)*l)+ +g[s+108+4>>2];g[s+108+4>>2]=v;l=(k*p+n*l+d*m)*m+t*(d-(k*p+n*l+d*m)*m)+ +g[s+108+8>>2];g[s+108+8>>2]=l;f=s+108+4|0;h=s+108+8|0;j=s+108|0;d=u;k=v}else{f=s+108+4|0;h=s+108+8|0;j=s+108|0;d=+g[s+108>>2];k=+g[s+108+4>>2];l=+g[s+108+8>>2]}m=(+g[b+104>>2]*d+ +g[b+108>>2]*k+ +g[b+112>>2]*l)*e;n=(d*+g[b+120>>2]+k*+g[b+124>>2]+l*+g[b+128>>2])*e;d=(d*+g[b+136>>2]+k*+g[b+140>>2]+l*+g[b+144>>2])*e;g[j>>2]=m;g[f>>2]=n;g[h>>2]=d;g[s+108+12>>2]=0.0;f=c[b+4>>2]|0;if((f|0)!=(c[b+16>>2]|0)){f=s;h=s+108|0;j=f+36|0;do{c[f>>2]=c[h>>2];f=f+4|0;h=h+4|0}while((f|0)<(j|0));v=-+g[s+4>>2];u=-+g[s+8>>2];g[s>>2]=-+g[s>>2];g[s+4>>2]=v;g[s+8>>2]=u;g[s+12>>2]=0.0;u=-+g[s+20>>2];v=-+g[s+24>>2];g[s+16>>2]=-+g[s+16>>2];g[s+20>>2]=u;g[s+24>>2]=v;g[s+28>>2]=0.0;Xh(b+4|0,s,b+164|0);Xh(b+16|0,s+108|0,b+180|0);i=s;return}if(!(m==m&n==n&(d==d&0.0==0.0))){i=s;return}v=+O(+(m*m+n*n+d*d));if(v<+g[f+368>>2]){i=s;return}h=c[s+108+32>>2]|0;v=+g[f+372>>2];g[s+72+12>>2]=0.0;g[s+72+28>>2]=0.0;c[s+72+32>>2]=h;g[s+72>>2]=-(m*v);g[s+72+4>>2]=-(n*v);g[s+72+8>>2]=-(d*v);g[s+72+16>>2]=v*-0.0;g[s+72+20>>2]=v*-0.0;g[s+72+24>>2]=v*-0.0;Xh(b+4|0,s+72|0,b+164|0);d=+g[(c[b+4>>2]|0)+372>>2];f=s+36|0;h=s+108|0;j=f+36|0;do{c[f>>2]=c[h>>2];f=f+4|0;h=h+4|0}while((f|0)<(j|0));g[s+36>>2]=d*+g[s+36>>2];g[s+36+4>>2]=d*+g[s+36+4>>2];g[s+36+8>>2]=d*+g[s+36+8>>2];g[s+36+16>>2]=d*+g[s+36+16>>2];g[s+36+20>>2]=d*+g[s+36+20>>2];g[s+36+24>>2]=d*+g[s+36+24>>2];Xh(b+16|0,s+36|0,b+180|0);i=s;return}function fe(b,d,e,f){b=b|0;d=d|0;e=e|0;f=+f;var h=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0,q=0,r=0.0,s=0.0,t=0.0,u=0.0,v=0,w=0,x=0,y=0,z=0,A=0,B=0.0,C=0.0,D=0,E=0;A=i;i=i+192|0;x=c[b+4>>2]|0;if(+g[x+752>>2]>2]|0;w=(c[b+8>>2]|0)+8|0;y=c[w>>2]|0;l=+g[e>>2];n=+g[d>>2]*f+l;h=+g[e+4>>2];o=+g[d+4>>2]*f+h;j=+g[e+8>>2];r=+g[d+8>>2]*f+j;v=(c[b+12>>2]|0)+8|0;p=c[v>>2]|0;m=+g[p+52>>2];if((z|0)!=(y|0)){k=o-+g[p+56>>2];u=r-+g[p+60>>2];B=l-+g[y+52>>2];l=h-+g[y+56>>2];h=j-+g[y+60>>2];s=(n-m)*+g[p+4>>2]+k*+g[p+20>>2]+u*+g[p+36>>2];t=(n-m)*+g[p+8>>2]+k*+g[p+24>>2]+u*+g[p+40>>2];u=(n-m)*+g[p+12>>2]+k*+g[p+28>>2]+u*+g[p+44>>2];j=B*+g[y+4>>2]+l*+g[y+20>>2]+h*+g[y+36>>2];k=B*+g[y+8>>2]+l*+g[y+24>>2]+h*+g[y+40>>2];h=B*+g[y+12>>2]+l*+g[y+28>>2]+h*+g[y+44>>2]}else{C=n-+g[z+52>>2];k=o-+g[z+56>>2];u=r-+g[z+60>>2];B=h-+g[p+56>>2];h=j-+g[p+60>>2];s=C*+g[z+4>>2]+k*+g[z+20>>2]+u*+g[z+36>>2];t=C*+g[z+8>>2]+k*+g[z+24>>2]+u*+g[z+40>>2];u=C*+g[z+12>>2]+k*+g[z+28>>2]+u*+g[z+44>>2];j=(l-m)*+g[p+4>>2]+B*+g[p+20>>2]+h*+g[p+36>>2];k=(l-m)*+g[p+8>>2]+B*+g[p+24>>2]+h*+g[p+40>>2];h=(l-m)*+g[p+12>>2]+B*+g[p+28>>2]+h*+g[p+44>>2]}g[A>>2]=s;g[A+4>>2]=t;g[A+8>>2]=u;g[A+12>>2]=0.0;g[A+16>>2]=j;g[A+20>>2]=k;g[A+24>>2]=h;g[A+28>>2]=0.0;c[A+64>>2]=c[d>>2];c[A+64+4>>2]=c[d+4>>2];c[A+64+8>>2]=c[d+8>>2];c[A+64+12>>2]=c[d+12>>2];g[A+80>>2]=f;g[A+84>>2]=0.0;g[A+88>>2]=0.0;g[A+92>>2]=0.0;c[A+112>>2]=0;a[A+116>>0]=0;c[A+120>>2]=0;c[A+120+4>>2]=0;c[A+120+8>>2]=0;c[A+120+12>>2]=0;c[A+120+16>>2]=0;c[A+120+20>>2]=0;c[A+120+24>>2]=0;c[A+120+28>>2]=0;g[A+48>>2]=n;g[A+52>>2]=o;g[A+56>>2]=r;g[A+60>>2]=0.0;c[A+32>>2]=c[e>>2];c[A+32+4>>2]=c[e+4>>2];c[A+32+8>>2]=c[e+8>>2];c[A+32+12>>2]=c[e+12>>2];h=+g[x+752>>2];e=c[x+748>>2]|0;if((e|0)>0){q=0;p=-1;l=h*h;while(1){h=+g[x+4+(q*184|0)>>2]-s;j=+g[x+4+(q*184|0)+4>>2]-t;k=+g[x+4+(q*184|0)+8>>2]-u;d=h*h+j*j+k*k>2]|0;w=c[v>>2]|0;h=+g[q+224>>2]*+g[w+224>>2];h=h<-10.0?-10.0:h;g[A+84>>2]=h>10.0?10.0:h;g[A+92>>2]=+g[q+228>>2]*+g[w+228>>2];h=+g[q+232>>2]*+g[w+232>>2];h=h<-10.0?-10.0:h;g[A+88>>2]=h>10.0?10.0:h;h=+g[A+72>>2];w=+N(+h)>.7071067690849304;l=+g[A+68>>2];if(w){C=1.0/+O(+(h*h+l*l));n=+g[A+64>>2];m=-(C*l*n);n=n*-(C*h);o=-(C*h);j=(h*h+l*l)*C;k=0.0;h=C*l}else{j=+g[A+64>>2];k=1.0/+O(+(j*j+l*l));m=h*-(l*k);n=(j*j+l*l)*k;o=k*j;j=-(k*j*h);k=-(l*k);h=0.0}g[A+152>>2]=k;g[A+156>>2]=o;g[A+160>>2]=h;g[A+168>>2]=j;g[A+172>>2]=m;g[A+176>>2]=n;v=c[b+20>>2]|0;q=c[b+16>>2]|0;w=c[b+28>>2]|0;b=c[b+24>>2]|0;c[A+96>>2]=(z|0)!=(y|0)?v:q;c[A+100>>2]=(z|0)!=(y|0)?q:v;c[A+104>>2]=(z|0)!=(y|0)?w:b;c[A+108>>2]=(z|0)!=(y|0)?b:w;if((p|0)>-1){b=x+4+(p*184|0)+148|0;z=c[b>>2]|0;e=x+4+(p*184|0)+120|0;d=c[e>>2]|0;v=x+4+(p*184|0)+124|0;q=c[v>>2]|0;y=x+4+(p*184|0)+128|0;w=c[y>>2]|0;D=x+4+(p*184|0)+112|0;E=c[D>>2]|0;_m(x+4+(p*184|0)|0,A|0,184)|0;c[D>>2]=E;c[e>>2]=d;c[v>>2]=q;c[y>>2]=w;c[b>>2]=z}else _e(x,A)|0;i=A;return}function ge(b,d,e,f,g,h){b=b|0;d=d|0;e=e|0;f=f|0;g=g|0;h=h|0;var i=0,j=0,k=0,l=0,m=0,n=0,o=0;if((h|0)<0){o=c[b+8>>2]|0;+$b[c[(c[o>>2]|0)+12>>2]&3](o,d,e,f,g,c[b+12>>2]|0,c[b+16>>2]|0,c[b+4>>2]|0,c[b+20>>2]|0,c[b+24>>2]|0);return}n=c[b+16>>2]|0;a:do if((n|0)>0){m=c[b+12>>2]|0;i=0;while(1){l=m+(i<<2)|0;k=c[l>>2]|0;j=c[(c[k+28>>2]|0)+208>>2]|0;if((j|0)<=-1)j=c[(c[k+32>>2]|0)+208>>2]|0;if((j|0)==(h|0)){o=l;break a}i=i+1|0;if((i|0)>=(n|0)){o=0;break}}}else{i=0;o=0}while(0);if((i|0)<(n|0)){m=c[b+12>>2]|0;j=0;do{l=c[m+(i<<2)>>2]|0;k=c[(c[l+28>>2]|0)+208>>2]|0;if((k|0)<=-1)k=c[(c[l+32>>2]|0)+208>>2]|0;j=((k|0)==(h|0)&1)+j|0;i=i+1|0}while((i|0)!=(n|0));h=j}else h=0;i=c[b+4>>2]|0;if((c[i+72>>2]|0)<2){n=c[b+8>>2]|0;+$b[c[(c[n>>2]|0)+12>>2]&3](n,d,e,f,g,o,h,i,c[b+20>>2]|0,c[b+24>>2]|0);return}if((e|0)>0){i=c[b+32>>2]|0;j=c[b+36>>2]|0;n=0;do{m=d+(n<<2)|0;if((i|0)==(j|0)){l=j|0?j<<1:1;if((j|0)<(l|0)){if(!l)i=0;else{c[6435]=(c[6435]|0)+1;i=yc((l<<2|3)+16|0)|0;if(!i)i=0;else{c[(i+4+15&-16)+-4>>2]=i;i=i+4+15&-16}j=c[b+32>>2]|0}if((j|0)>0){k=0;do{c[i+(k<<2)>>2]=c[(c[b+40>>2]|0)+(k<<2)>>2];k=k+1|0}while((k|0)!=(j|0))}k=c[b+40>>2]|0;if(k){if(a[b+44>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[k+-4>>2]|0);j=c[b+32>>2]|0}c[b+40>>2]=0}a[b+44>>0]=1;c[b+40>>2]=i;c[b+36>>2]=l;i=j;j=l}else i=j}c[(c[b+40>>2]|0)+(i<<2)>>2]=c[m>>2];i=i+1|0;c[b+32>>2]=i;n=n+1|0}while((n|0)!=(e|0))}if((g|0)>0){i=c[b+52>>2]|0;j=c[b+56>>2]|0;n=0;do{m=f+(n<<2)|0;if((i|0)==(j|0)){l=j|0?j<<1:1;if((j|0)<(l|0)){if(!l)i=0;else{c[6435]=(c[6435]|0)+1;i=yc((l<<2|3)+16|0)|0;if(!i)i=0;else{c[(i+4+15&-16)+-4>>2]=i;i=i+4+15&-16}j=c[b+52>>2]|0}if((j|0)>0){k=0;do{c[i+(k<<2)>>2]=c[(c[b+60>>2]|0)+(k<<2)>>2];k=k+1|0}while((k|0)!=(j|0))}k=c[b+60>>2]|0;if(k){if(a[b+64>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[k+-4>>2]|0);j=c[b+52>>2]|0}c[b+60>>2]=0}a[b+64>>0]=1;c[b+60>>2]=i;c[b+56>>2]=l;i=j;j=l}else i=j}c[(c[b+60>>2]|0)+(i<<2)>>2]=c[m>>2];i=i+1|0;c[b+52>>2]=i;n=n+1|0}while((n|0)!=(g|0))}if((h|0)>0){i=c[b+72>>2]|0;j=c[b+76>>2]|0;n=0;do{m=o+(n<<2)|0;if((i|0)==(j|0)){l=j|0?j<<1:1;if((j|0)<(l|0)){if(!l){k=0;i=j}else{c[6435]=(c[6435]|0)+1;i=yc((l<<2|3)+16|0)|0;if(!i)i=0;else{c[(i+4+15&-16)+-4>>2]=i;i=i+4+15&-16}k=i;i=c[b+72>>2]|0}if((i|0)>0){j=0;do{c[k+(j<<2)>>2]=c[(c[b+80>>2]|0)+(j<<2)>>2];j=j+1|0}while((j|0)!=(i|0))}j=c[b+80>>2]|0;if(j){if(a[b+84>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0);i=c[b+72>>2]|0}c[b+80>>2]=0}a[b+84>>0]=1;c[b+80>>2]=k;c[b+76>>2]=l;j=l}else i=j}c[(c[b+80>>2]|0)+(i<<2)>>2]=c[m>>2];i=i+1|0;c[b+72>>2]=i;n=n+1|0}while((n|0)!=(h|0))}else i=c[b+72>>2]|0;if(((c[b+52>>2]|0)+i|0)<=(c[(c[b+4>>2]|0)+72>>2]|0))return;nh(b);return}function he(d,e,f,h,j){d=d|0;e=e|0;f=+f;h=+h;j=+j;var k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0,r=0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0;q=i;i=i+240|0;o=+g[d+96>>2]+h;p=+g[d+100>>2]+j;g[d+112>>2]=+g[d+92>>2]+f;g[d+116>>2]=o;g[d+120>>2]=p;g[d+124>>2]=0.0;c[q+168>>2]=1065353216;c[q+168+4>>2]=0;c[q+168+4+4>>2]=0;c[q+168+4+8>>2]=0;c[q+168+4+12>>2]=0;c[q+168+20>>2]=1065353216;c[q+168+24>>2]=0;c[q+168+24+4>>2]=0;c[q+168+24+8>>2]=0;c[q+168+24+12>>2]=0;c[q+168+40>>2]=1065353216;k=q+168+44|0;c[k>>2]=0;c[k+4>>2]=0;c[k+8>>2]=0;c[k+12>>2]=0;c[k+16>>2]=0;c[q+104>>2]=1065353216;c[q+104+4>>2]=0;c[q+104+4+4>>2]=0;c[q+104+4+8>>2]=0;c[q+104+4+12>>2]=0;c[q+104+20>>2]=1065353216;c[q+104+24>>2]=0;c[q+104+24+4>>2]=0;c[q+104+24+8>>2]=0;c[q+104+24+12>>2]=0;c[q+104+40>>2]=1065353216;k=q+104+44|0;c[k>>2]=0;c[k+4>>2]=0;c[k+8>>2]=0;c[k+12>>2]=0;c[k+16>>2]=0;p=1.0;k=10;while(1){if((k|0)<=0){k=14;break}k=k+-1|0;c[q+168+48>>2]=c[d+92>>2];c[q+168+48+4>>2]=c[d+92+4>>2];c[q+168+48+8>>2]=c[d+92+8>>2];c[q+168+48+12>>2]=c[d+92+12>>2];c[q+104+48>>2]=c[d+112>>2];c[q+104+48+4>>2]=c[d+112+4>>2];c[q+104+48+8>>2]=c[d+112+8>>2];c[q+104+48+12>>2]=c[d+112+12>>2];n=+g[d+92>>2]-+g[d+112>>2];o=+g[d+96>>2]-+g[d+116>>2];f=+g[d+100>>2]-+g[d+120>>2];r=c[d+8>>2]|0;g[q+4>>2]=1.0;b[q+8>>1]=1;b[q+10>>1]=-1;c[q+76>>2]=0;c[q+12>>2]=0;c[q+12+4>>2]=0;c[q+12+8>>2]=0;c[q+12+12>>2]=0;c[q+12+16>>2]=0;c[q+12+20>>2]=0;c[q+12+24>>2]=0;c[q+12+28>>2]=0;c[q>>2]=4936;c[q+80>>2]=r;g[q+84>>2]=n;g[q+88>>2]=o;g[q+92>>2]=f;g[q+96>>2]=0.0;g[q+100>>2]=0.0;r=c[(c[r+188>>2]|0)+4>>2]|0;b[q+8>>1]=r;b[q+10>>1]=r>>>16;r=c[d+12>>2]|0;f=+Sb[c[(c[r>>2]|0)+48>>2]&15](r);r=c[d+12>>2]|0;zb[c[(c[r>>2]|0)+44>>2]&31](r,f+ +g[d+56>>2]);if(!(a[d+170>>0]|0))Kd(e,c[d+12>>2]|0,q+168|0,q+104|0,q,+g[e+56>>2]);else wd(c[d+8>>2]|0,c[d+12>>2]|0,q+168|0,q+104|0,q,+g[e+56>>2]);r=c[d+12>>2]|0;zb[c[(c[r>>2]|0)+44>>2]&31](r,f);o=+g[q+4>>2];p=p-o;if(o<1.0){h=+g[d+112>>2];m=+g[d+92>>2];j=+g[d+116>>2];n=+g[d+96>>2];l=+g[d+120>>2];o=+g[d+100>>2];f=+O(+((h-m)*(h-m)+(j-n)*(j-n)+(l-o)*(l-o)));if(f>1.1920928955078125e-07){v=+g[q+44>>2];t=+g[q+48>>2];x=+g[q+52>>2];w=((h-m)*(1.0/f)*v+(j-n)*(1.0/f)*t+(l-o)*(1.0/f)*x)*2.0;u=(h-m)*(1.0/f)-v*w;s=(j-n)*(1.0/f)-t*w;w=(l-o)*(1.0/f)-x*w;l=1.0/+O(+(w*w+(u*u+s*s)));c[d+112>>2]=c[d+92>>2];c[d+112+4>>2]=c[d+92+4>>2];c[d+112+8>>2]=c[d+92+8>>2];c[d+112+12>>2]=c[d+92+12>>2];h=f*(l*u-v*(x*l*w+(v*l*u+t*l*s)))+ +g[d+112>>2];g[d+112>>2]=h;j=f*(l*s-t*(x*l*w+(v*l*u+t*l*s)))+ +g[d+116>>2];g[d+116>>2]=j;l=f*(l*w-x*(x*l*w+(v*l*u+t*l*s)))+ +g[d+120>>2];g[d+120>>2]=l;f=j}else f=j;j=h-m;h=f-n;f=l-o;if(!(j*j+h*h+f*f>1.1920928955078125e-07)){k=11;break}x=1.0/+O(+(j*j+h*h+f*f));if(+g[d+76>>2]*j*x+h*x*+g[d+80>>2]+f*x*+g[d+84>>2]<=0.0){k=11;break}}else{c[d+92>>2]=c[d+112>>2];c[d+92+4>>2]=c[d+112+4>>2];c[d+92+8>>2]=c[d+112+8>>2];c[d+92+12>>2]=c[d+112+12>>2]}if(!(p>.009999999776482582)){k=14;break}}if((k|0)==11){i=q;return}else if((k|0)==14){i=q;return}}function ie(d,f,h,j){d=d|0;f=f|0;h=h|0;j=j|0;var k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0,s=0,t=0,u=0,v=0,w=0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0,H=0.0,I=0.0;w=i;i=i+80|0;v=c[d+48>>2]|0;c[w>>2]=6864;c[w+4>>2]=v;c[w+8>>2]=f;v=c[d+52>>2]|0;if(!(a[v+60>>0]|0)){f=c[v+56>>2]|0;if((f|0)>0){d=f;m=0;p=c[v+96>>2]|0;f=0;while(1){f=f+1|0;if(!(+g[h>>2]>+g[p+16>>2])?!(+g[j>>2]<+g[p>>2]):0)k=1;else k=0;if(!(!(+g[h+8>>2]>+g[p+24>>2])?!(+g[j+8>>2]<+g[p+8>>2]):0))k=0;if(!(+g[h+4>>2]>+g[p+20>>2])?!(+g[j+4>>2]<+g[p+4>>2]):0){l=c[p+32>>2]|0;if(k&(l|0)==-1){ic[c[(c[w>>2]|0)+8>>2]&127](w,c[p+36>>2]|0,c[p+40>>2]|0);d=c[v+56>>2]|0;o=43}else{n=(l|0)==-1;o=42}}else{l=c[p+32>>2]|0;k=0;n=(l|0)==-1;o=42}if((o|0)==42){o=0;if(n|k)o=43;else{m=l+m|0;k=p+(l<<6)|0}}if((o|0)==43){m=m+1|0;k=p+64|0}if((m|0)<(d|0))p=k;else break}}else f=0;if((c[6167]|0)>=(f|0)){i=w;return}c[6167]=f;i=w;return}D=+g[h>>2];H=+g[h+4>>2];z=+g[h+8>>2];G=+g[v+4>>2];D=D>2];H=H>2];z=z>2];A=+g[v+24>>2];E=+g[v+28>>2];F=+g[v+36>>2];x=+g[v+40>>2];B=+g[v+44>>2];u=~~(((I>1]=u;s=~~(((E>1]=t;b[w+66+4>>1]=s;H=+g[j>>2];z=+g[j+4>>2];D=+g[j+8>>2];H=H>1]=r;j=(~~(((E>1]=q;b[w+60+4>>1]=j;switch(c[v+144>>2]|0){case 0:{o=c[v+56>>2]|0;if((o|0)>0){d=0;k=c[v+136>>2]|0;f=0;do{f=f+1|0;l=((r&65535)>=(e[k>>1]|0)?(u&65535)<=(e[k+6>>1]|0):0)&(s&65535)<=(e[k+10>>1]|0)&(j&65535)>=(e[k+4>>1]|0)&(t&65535)<=(e[k+8>>1]|0)&(q&65535)>=(e[k+2>>1]|0);m=k+12|0;n=c[m>>2]|0;if((n|0)>-1&l)ic[c[(c[w>>2]|0)+8>>2]&127](w,n>>21,n&2097151);if(l|(n|0)>-1){d=d+1|0;k=k+16|0}else{v=c[m>>2]|0;d=d-v|0;k=k+(0-v<<4)|0}}while((d|0)<(o|0))}else f=0;if((c[6167]|0)<(f|0))c[6167]=f;break}case 1:{if((c[v+152>>2]|0)>0){h=0;do{f=c[v+160>>2]|0;if(((r&65535)>=(e[f+(h<<5)>>1]|0)?(u&65535)<=(e[f+(h<<5)+6>>1]|0):0)&(s&65535)<=(e[f+(h<<5)+10>>1]|0)&(j&65535)>=(e[f+(h<<5)+4>>1]|0)&(t&65535)<=(e[f+(h<<5)+8>>1]|0)&(q&65535)>=(e[f+(h<<5)+2>>1]|0)){p=c[f+(h<<5)+12>>2]|0;o=c[f+(h<<5)+16>>2]|0;if((o|0)>0){d=p;k=(c[v+136>>2]|0)+(p<<4)|0;f=0;do{f=f+1|0;l=((r&65535)>=(e[k>>1]|0)?(u&65535)<=(e[k+6>>1]|0):0)&(s&65535)<=(e[k+10>>1]|0)&(j&65535)>=(e[k+4>>1]|0)&(t&65535)<=(e[k+8>>1]|0)&(q&65535)>=(e[k+2>>1]|0);m=k+12|0;n=c[m>>2]|0;if((n|0)>-1&l)ic[c[(c[w>>2]|0)+8>>2]&127](w,n>>21,n&2097151);if(l|(n|0)>-1){d=d+1|0;k=k+16|0}else{n=c[m>>2]|0;d=d-n|0;k=k+(0-n<<4)|0}}while((d|0)<(o+p|0))}else f=0;if((c[6167]|0)<(f|0))c[6167]=f}h=h+1|0}while((h|0)<(c[v+152>>2]|0))}break}case 2:{Lk(c[v+136>>2]|0,w,w+66|0,w+60|0);break}default:{}}i=w;return}function je(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0;a[b+20>>0]=1;c[b+16>>2]=0;c[b+8>>2]=0;c[b+12>>2]=0;c[b+24>>2]=d;g[b+28>>2]=0.0;c[b+32>>2]=0;c[b+36>>2]=1;g[b+40>>2]=1.0;a[b+44>>0]=1;c[b+48>>2]=0;a[b+52>>0]=0;a[b+53>>0]=1;a[b+54>>0]=1;g[b+56>>2]=.03999999910593033;a[b+60>>0]=0;g[b+64>>2]=0.0;c[b+68>>2]=e;c[b+72>>2]=0;a[b+76>>0]=1;c[b+80>>2]=0;c[b+84>>2]=0;c[b+88>>2]=0;g[b+92>>2]=.6000000238418579;g[b+96>>2]=1.0;g[b+100>>2]=.30000001192092896;g[b+104>>2]=.01666666753590107;g[b+108>>2]=0.0;g[b+116>>2]=20.0;c[b+112>>2]=10;g[b+124>>2]=.20000000298023224;g[b+128>>2]=.800000011920929;g[b+132>>2]=0.0;g[b+120>>2]=1.0;c[b+136>>2]=1;g[b+140>>2]=-.03999999910593033;g[b+144>>2]=.10000000149011612;g[b+148>>2]=0.0;g[b+152>>2]=.8500000238418579;c[b+156>>2]=260;c[b+160>>2]=2;c[b+164>>2]=128;g[b+168>>2]=100.0;g[b+172>>2]=1000000015047466219876688.0e6;c[b>>2]=4144;a[b+192>>0]=1;c[b+188>>2]=0;c[b+180>>2]=0;c[b+184>>2]=0;c[b+196>>2]=0;c[b+200>>2]=f;a[b+224>>0]=1;c[b+220>>2]=0;c[b+212>>2]=0;c[b+216>>2]=0;a[b+244>>0]=1;c[b+240>>2]=0;c[b+232>>2]=0;c[b+236>>2]=0;c[b+248>>2]=0;c[b+252>>2]=-1054867456;a[b+274>>0]=0;a[b+275>>0]=0;c[b+256>>2]=0;c[b+256+4>>2]=0;c[b+256+8>>2]=0;c[b+256+12>>2]=0;a[b+292>>0]=1;c[b+288>>2]=0;c[b+280>>2]=0;c[b+284>>2]=0;c[b+296>>2]=0;a[b+300>>0]=1;a[b+320>>0]=1;c[b+316>>2]=0;c[b+308>>2]=0;c[b+312>>2]=0;if(!f){c[6435]=(c[6435]|0)+1;f=yc(215)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}c[f>>2]=4756;a[f+20>>0]=1;c[f+16>>2]=0;c[f+8>>2]=0;c[f+12>>2]=0;a[f+40>>0]=1;c[f+36>>2]=0;c[f+28>>2]=0;c[f+32>>2]=0;a[f+60>>0]=1;c[f+56>>2]=0;c[f+48>>2]=0;c[f+52>>2]=0;a[f+80>>0]=1;c[f+76>>2]=0;c[f+68>>2]=0;c[f+72>>2]=0;a[f+100>>0]=1;c[f+96>>2]=0;c[f+88>>2]=0;c[f+92>>2]=0;a[f+120>>0]=1;c[f+116>>2]=0;c[f+108>>2]=0;c[f+112>>2]=0;a[f+140>>0]=1;c[f+136>>2]=0;c[f+128>>2]=0;c[f+132>>2]=0;a[f+160>>0]=1;c[f+156>>2]=0;c[f+148>>2]=0;c[f+152>>2]=0;a[f+180>>0]=1;c[f+176>>2]=0;c[f+168>>2]=0;c[f+172>>2]=0;c[f+192>>2]=0;c[b+200>>2]=f;a[b+273>>0]=1}else a[b+273>>0]=0;c[6435]=(c[6435]|0)+1;f=yc(87)|0;if(!f)f=0;else{c[(f+4+15&-16)+-4>>2]=f;f=f+4+15&-16}c[f>>2]=5456;a[f+20>>0]=1;c[f+16>>2]=0;c[f+8>>2]=0;c[f+12>>2]=0;a[f+40>>0]=1;c[f+36>>2]=0;c[f+28>>2]=0;c[f+32>>2]=0;a[f+60>>0]=1;c[f+56>>2]=0;c[f+48>>2]=0;c[f+52>>2]=0;a[f+64>>0]=1;c[b+204>>2]=f;a[b+272>>0]=1;c[6435]=(c[6435]|0)+1;f=yc(107)|0;if(!f){e=0;h=c[b+200>>2]|0;c[e>>2]=4356;f=e+4|0;c[f>>2]=0;f=e+8|0;c[f>>2]=h;f=e+12|0;c[f>>2]=0;f=e+16|0;c[f>>2]=0;f=e+20|0;c[f>>2]=0;f=e+24|0;c[f>>2]=d;d=e+44|0;a[d>>0]=1;d=e+40|0;c[d>>2]=0;d=e+32|0;c[d>>2]=0;d=e+36|0;c[d>>2]=0;d=e+64|0;a[d>>0]=1;d=e+60|0;c[d>>2]=0;d=e+52|0;c[d>>2]=0;d=e+56|0;c[d>>2]=0;d=e+84|0;a[d>>0]=1;d=e+80|0;c[d>>2]=0;d=e+72|0;c[d>>2]=0;d=e+76|0;c[d>>2]=0;c[b+196>>2]=e;return}c[(f+4+15&-16)+-4>>2]=f;h=f+4+15&-16;f=c[b+200>>2]|0;c[h>>2]=4356;e=h+4|0;c[e>>2]=0;e=h+8|0;c[e>>2]=f;e=h+12|0;c[e>>2]=0;e=h+16|0;c[e>>2]=0;e=h+20|0;c[e>>2]=0;e=h+24|0;c[e>>2]=d;d=h+44|0;a[d>>0]=1;d=h+40|0;c[d>>2]=0;d=h+32|0;c[d>>2]=0;d=h+36|0;c[d>>2]=0;d=h+64|0;a[d>>0]=1;d=h+60|0;c[d>>2]=0;d=h+52|0;c[d>>2]=0;d=h+56|0;c[d>>2]=0;d=h+84|0;a[d>>0]=1;d=h+80|0;c[d>>2]=0;d=h+72|0;c[d>>2]=0;d=h+76|0;c[d>>2]=0;c[b+196>>2]=h;return}function ke(b,d){b=b|0;d=d|0;var e=0,f=0,h=0.0,j=0,k=0.0,l=0,m=0,n=0.0,o=0,p=0,q=0,r=0,s=0,t=0,u=0,v=0.0,w=0.0;u=i;i=i+96|0;s=c[b+12>>2]|0;mc[c[(c[s>>2]|0)+8>>2]&127](s,(c[b+8>>2]|0)+4|0,u+80|0,u+64|0);s=c[d+68>>2]|0;yb[c[(c[s>>2]|0)+16>>2]&31](s,c[(c[b+8>>2]|0)+188>>2]|0,u+80|0,u+64|0,c[d+24>>2]|0);s=c[d+24>>2]|0;mc[c[(c[s>>2]|0)+32>>2]&127](s,c[(c[b+8>>2]|0)+284>>2]|0,d+28|0,s);s=c[b+8>>2]|0;c[b+92>>2]=c[s+52>>2];c[b+92+4>>2]=c[s+52+4>>2];c[b+92+8>>2]=c[s+52+8>>2];c[b+92+12>>2]=c[s+52+12>>2];s=c[s+284>>2]|0;if((Eb[c[(c[s>>2]|0)+36>>2]&127](s)|0)>0){s=0;h=0.0;d=0;do{e=c[b+132>>2]|0;if((e|0)<0){if((c[b+136>>2]|0)<0){f=c[b+140>>2]|0;if(f|0){if(a[b+144>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}c[b+140>>2]=0}a[b+144>>0]=1;c[b+140>>2]=0;c[b+136>>2]=0}do{c[(c[b+140>>2]|0)+(e<<2)>>2]=0;e=e+1|0}while((e|0)!=0)}c[b+132>>2]=0;e=c[(c[b+8>>2]|0)+284>>2]|0;e=c[(Eb[c[(c[e>>2]|0)+28>>2]&127](e)|0)+12>>2]|0;r=c[c[e+(s<<4)>>2]>>2]|0;f=c[c[e+(s<<4)+4>>2]>>2]|0;if(!((r|0)!=0?(c[r+204>>2]&4|0)!=0:0))t=14;do if((t|0)==14){t=0;if(f|0?c[f+204>>2]&4|0:0)break;e=c[e+(s<<4)+8>>2]|0;if(e|0)Cb[c[(c[e>>2]|0)+16>>2]&127](e,b+128|0);q=c[b+132>>2]|0;if((q|0)>0){o=c[b+140>>2]|0;p=c[b+8>>2]|0;r=0;do{m=c[o+(r<<2)>>2]|0;n=(c[m+740>>2]|0)==(p|0)?-1.0:1.0;e=c[m+748>>2]|0;if((e|0)>0){l=0;do{k=+g[m+4+(l*184|0)+80>>2];if(k<0.0){j=m+4+(l*184|0)+64|0;if(k>2];f=m+4+(l*184|0)+72|0;h=n*+g[f>>2];g[b+152>>2]=n*+g[j>>2];g[b+156>>2]=v;g[b+160>>2]=h;g[b+164>>2]=0.0;e=c[m+748>>2]|0;h=k}else{d=m+4+(l*184|0)+68|0;f=m+4+(l*184|0)+72|0}w=k*n*+g[d>>2]*.20000000298023224;v=k*n*+g[f>>2]*.20000000298023224;g[b+92>>2]=k*n*+g[j>>2]*.20000000298023224+ +g[b+92>>2];g[b+96>>2]=w+ +g[b+96>>2];g[b+100>>2]=v+ +g[b+100>>2];d=1}l=l+1|0}while((l|0)<(e|0))}r=r+1|0}while((r|0)!=(q|0))}}while(0);s=s+1|0;r=c[(c[b+8>>2]|0)+284>>2]|0}while((s|0)<(Eb[c[(c[r>>2]|0)+36>>2]&127](r)|0))}else d=0;t=c[b+8>>2]|0;c[u>>2]=c[t+4>>2];c[u+4>>2]=c[t+4+4>>2];c[u+8>>2]=c[t+4+8>>2];c[u+12>>2]=c[t+4+12>>2];c[u+16>>2]=c[t+20>>2];c[u+16+4>>2]=c[t+20+4>>2];c[u+16+8>>2]=c[t+20+8>>2];c[u+16+12>>2]=c[t+20+12>>2];c[u+32>>2]=c[t+36>>2];c[u+32+4>>2]=c[t+36+4>>2];c[u+32+8>>2]=c[t+36+8>>2];c[u+32+12>>2]=c[t+36+12>>2];c[u+48>>2]=c[b+92>>2];c[u+48+4>>2]=c[b+92+4>>2];c[u+48+8>>2]=c[b+92+8>>2];c[u+48+12>>2]=c[b+92+12>>2];c[t+260>>2]=(c[t+260>>2]|0)+1;c[t+4>>2]=c[u>>2];c[t+4+4>>2]=c[u+4>>2];c[t+4+8>>2]=c[u+8>>2];c[t+4+12>>2]=c[u+12>>2];c[t+20>>2]=c[u+16>>2];c[t+20+4>>2]=c[u+16+4>>2];c[t+20+8>>2]=c[u+16+8>>2];c[t+20+12>>2]=c[u+16+12>>2];c[t+36>>2]=c[u+32>>2];c[t+36+4>>2]=c[u+32+4>>2];c[t+36+8>>2]=c[u+32+8>>2];c[t+36+12>>2]=c[u+32+12>>2];c[t+52>>2]=c[u+48>>2];c[t+52+4>>2]=c[u+48+4>>2];c[t+52+8>>2]=c[u+48+8>>2];c[t+52+12>>2]=c[u+48+12>>2];i=u;return d|0}function le(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0,k=0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0,r=0,s=0,t=0.0,u=0.0;s=i;i=i+48|0;c[s+16>>2]=c[e>>2];c[s+16+4>>2]=c[e+4>>2];c[s+16+8>>2]=c[e+8>>2];c[s+16+12>>2]=c[e+12>>2];c[s+16+16>>2]=c[f>>2];c[s+16+16+4>>2]=c[f+4>>2];c[s+16+16+8>>2]=c[f+8>>2];c[s+16+16+12>>2]=c[f+12>>2];do if((c[d+60>>2]|0)==2){h=c[d+48>>2]|0;hh(b+64|0,h)|0;j=c[b+68>>2]|0;if(j|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0)}c[b+68>>2]=h;c[b+76>>2]=(c[b+76>>2]|0)+-1;h=c[b+8>>2]|0;if(!h){c[6435]=(c[6435]|0)+1;h=yc(63)|0;if(!h)h=0;else{c[(h+4+15&-16)+-4>>2]=h;h=h+4+15&-16}j=h;k=j+44|0;do{c[j>>2]=0;j=j+4|0}while((j|0)<(k|0))}else c[b+8>>2]=0;c[h+32>>2]=0;c[h+36>>2]=d;c[h+40>>2]=0;c[h>>2]=c[s+16>>2];c[h+4>>2]=c[s+16+4>>2];c[h+8>>2]=c[s+16+8>>2];c[h+12>>2]=c[s+16+12>>2];c[h+16>>2]=c[s+16+16>>2];c[h+20>>2]=c[s+16+20>>2];c[h+24>>2]=c[s+16+24>>2];c[h+28>>2]=c[s+16+28>>2];lf(b+4|0,c[b+4>>2]|0,h);c[b+16>>2]=(c[b+16>>2]|0)+1;c[d+48>>2]=h;k=1}else{c[b+168>>2]=(c[b+168>>2]|0)+1;r=c[d+48>>2]|0;if(((((+g[r>>2]<=+g[s+16+16>>2]?+g[r+16>>2]>=+g[s+16>>2]:0)?+g[r+4>>2]<=+g[s+16+20>>2]:0)?+g[r+20>>2]>=+g[s+16+4>>2]:0)?+g[r+8>>2]<=+g[s+16+24>>2]:0)?+g[r+24>>2]>=+g[s+16+8>>2]:0){l=+g[d+16>>2];t=+g[e>>2]-l;m=+g[d+20>>2];o=+g[e+4>>2]-m;n=+g[d+24>>2];p=+g[e+8>>2]-n;u=+g[b+140>>2];l=(+g[d+32>>2]-l)*.5*u;m=(+g[d+36>>2]-m)*.5*u;n=u*(+g[d+40>>2]-n)*.5;g[s>>2]=l;g[s+4>>2]=m;g[s+8>>2]=n;g[s+12>>2]=0.0;if(t<0.0)g[s>>2]=-l;if(o<0.0)g[s+4>>2]=-m;if(p<0.0)g[s+8>>2]=-n;if(jh(b+4|0,r,s+16|0,s,.05000000074505806)|0){c[b+172>>2]=(c[b+172>>2]|0)+1;h=1}else h=0;k=h;break}h=hh(b+4|0,r)|0;a:do if(h){k=c[b+12>>2]|0;if((k|0)<=-1){h=c[b+4>>2]|0;break}if((k|0)>0){q=0;while(1){j=c[h+32>>2]|0;q=q+1|0;if(!j)break a;if((q|0)>=(k|0)){h=j;break}else h=j}}}else h=0;while(0);c[r>>2]=c[s+16>>2];c[r+4>>2]=c[s+16+4>>2];c[r+8>>2]=c[s+16+8>>2];c[r+12>>2]=c[s+16+12>>2];c[r+16>>2]=c[s+16+16>>2];c[r+20>>2]=c[s+16+20>>2];c[r+24>>2]=c[s+16+24>>2];c[r+28>>2]=c[s+16+28>>2];lf(b+4|0,h,r);c[b+172>>2]=(c[b+172>>2]|0)+1;k=1}while(0);h=c[d+52>>2]|0;j=c[d+56>>2]|0;if(!h)c[b+124+(c[d+60>>2]<<2)>>2]=j;else c[h+56>>2]=j;h=c[d+56>>2]|0;if(h|0)c[h+52>>2]=c[d+52>>2];c[d+16>>2]=c[e>>2];c[d+16+4>>2]=c[e+4>>2];c[d+16+8>>2]=c[e+8>>2];c[d+16+12>>2]=c[e+12>>2];c[d+32>>2]=c[f>>2];c[d+32+4>>2]=c[f+4>>2];c[d+32+8>>2]=c[f+8>>2];c[d+32+12>>2]=c[f+12>>2];h=c[b+144>>2]|0;c[d+60>>2]=h;c[d+52>>2]=0;c[d+56>>2]=c[b+124+(h<<2)>>2];j=c[b+124+(h<<2)>>2]|0;if(j|0)c[j+52>>2]=d;c[b+124+(h<<2)>>2]=d;if(!k){i=s;return}a[b+194>>0]=1;if(a[b+193>>0]|0){i=s;return}c[s>>2]=8904;c[s+4>>2]=b;we(b+64|0,c[b+64>>2]|0,c[d+48>>2]|0,s);we(b+4|0,c[b+4>>2]|0,c[d+48>>2]|0,s);i=s;return}function me(b,d){b=b|0;d=d|0;var e=0,f=0,h=0,j=0,k=0,l=0,m=0;m=i;i=i+352|0;e=c[d+36>>2]|0;c[m+288+4>>2]=35;c[m+288+8>>2]=0;c[m+288+12>>2]=1065353216;c[m+288+16>>2]=1065353216;c[m+288+20>>2]=1065353216;g[m+288+24>>2]=0.0;c[m+288>>2]=3436;c[m+288+52>>2]=e;g[m+288+44>>2]=0.0;k=c[b+28>>2]|0;d=c[k+4>>2]|0;if(c[(c[k+8>>2]|0)+204>>2]&3|0?a[e+376>>0]|0:0){i=m;return}if((a[22456]|0)==0?Wa(22456)|0:0){if((a[22464]|0)==0?Wa(22464)|0:0){c[5698]=1065353216;c[5699]=0;c[5700]=0;c[5701]=0;c[5702]=0;c[5703]=1065353216;c[5704]=0;c[5705]=0;c[5706]=0;c[5707]=0;c[5708]=1065353216;g[5709]=0.0;_a(22464)}c[5710]=c[5698];c[5711]=c[5699];c[5712]=c[5700];c[5713]=c[5701];c[5714]=c[5702];c[5715]=c[5703];c[5716]=c[5704];c[5717]=c[5705];c[5718]=c[5706];c[5719]=c[5707];c[5720]=c[5708];c[5721]=c[5709];c[5722]=0;c[5723]=0;c[5724]=0;c[5725]=0;_a(22456)}f=c[(c[b+28>>2]|0)+12>>2]|0;c[m>>2]=1065353216;c[m+4>>2]=0;c[m+8>>2]=0;g[m+12>>2]=0.0;if(!(!(Jd(m+288|0,22840,d,f,m,m+232|0)|0)?!(Pc(m+288|0,22840,d,f,m,m+232|0,0)|0):0)){k=m+16+4|0;a[m+16+152>>0]=0;c[k>>2]=0;c[k+4>>2]=0;c[k+8>>2]=0;c[k+12>>2]=0;c[k+16>>2]=0;c[k+20>>2]=0;c[m+16>>2]=3256;k=c[(c[b+28>>2]|0)+8>>2]|0;do if(jd(b,m+232|0,e,0,0,0,(c[k+236>>2]&2|0)==0?0:k,k,m+16|0)|0){c[6435]=(c[6435]|0)+1;d=yc(235)|0;if(!d)k=0;else{c[(d+4+15&-16)+-4>>2]=d;k=d+4+15&-16}d=k+152|0;Qn(k|0,0,156)|0;c[k>>2]=3256;e=k+4|0;f=m+16+4|0;h=e+100|0;do{c[e>>2]=c[f>>2];e=e+4|0;f=f+4|0}while((e|0)<(h|0));e=k+104|0;c[e>>2]=c[m+16+104>>2];c[e+4>>2]=c[m+16+104+4>>2];c[e+8>>2]=c[m+16+104+8>>2];c[e+12>>2]=c[m+16+104+12>>2];e=k+120|0;c[e>>2]=c[m+16+120>>2];c[e+4>>2]=c[m+16+120+4>>2];c[e+8>>2]=c[m+16+120+8>>2];c[e+12>>2]=c[m+16+120+12>>2];e=k+136|0;c[e>>2]=c[m+16+136>>2];c[e+4>>2]=c[m+16+136+4>>2];c[e+8>>2]=c[m+16+136+8>>2];c[e+12>>2]=c[m+16+136+12>>2];a[d>>0]=a[m+16+152>>0]|0;e=k+156|0;f=m+16+156|0;h=e+60|0;do{c[e>>2]=c[f>>2];e=e+4|0;f=f+4|0}while((e|0)<(h|0));h=c[b+24>>2]|0;j=k;d=c[h+852>>2]|0;if((d|0)==(c[h+856>>2]|0)?(l=d|0?d<<1:1,(d|0)<(l|0)):0){if(!l)f=0;else{c[6435]=(c[6435]|0)+1;d=yc((l<<2|3)+16|0)|0;if(!d)d=0;else{c[(d+4+15&-16)+-4>>2]=d;d=d+4+15&-16}f=d;d=c[h+852>>2]|0}if((d|0)>0){e=0;do{c[f+(e<<2)>>2]=c[(c[h+860>>2]|0)+(e<<2)>>2];e=e+1|0}while((e|0)!=(d|0))}e=c[h+860>>2]|0;if(e){if(a[h+864>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[e+-4>>2]|0);d=c[h+852>>2]|0}c[h+860>>2]=0}a[h+864>>0]=1;c[h+860>>2]=f;c[h+856>>2]=l}c[(c[h+860>>2]|0)+(d<<2)>>2]=j;c[h+852>>2]=d+1;d=c[b+24>>2]|0;if(!(c[(c[(c[b+28>>2]|0)+8>>2]|0)+204>>2]&3)){b=k+64|0;g[b>>2]=+g[d+340>>2]*+g[b>>2];b=k+68|0;g[b>>2]=+g[d+352>>2]*+g[b>>2];break}else{b=k+64|0;g[b>>2]=+g[d+344>>2]*+g[b>>2];b=k+68|0;g[b>>2]=+g[d+356>>2]*+g[b>>2];break}}while(0)}i=m;return}function ne(b,d,e,f,h,i,j,l){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;i=i|0;j=j|0;l=l|0;var m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0,u=0,v=0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0;c[b+4>>2]=4;c[b+8>>2]=-1;c[b+12>>2]=-1;g[b+16>>2]=3402823466385288598117041.0e14;a[b+20>>0]=1;a[b+21>>0]=0;c[b+24>>2]=-1;c[b+28>>2]=d;c[b+32>>2]=e;g[b+36>>2]=0.0;g[b+40>>2]=.30000001192092896;c[b+44>>2]=0;c[b>>2]=4704;g[b+688>>2]=0.0;g[b+692>>2]=-1.0;g[b+696>>2]=.8999999761581421;g[b+700>>2]=.30000001192092896;g[b+704>>2]=1.0;g[b+708>>2]=0.0;g[b+712>>2]=0.0;a[b+716>>0]=0;a[b+736>>0]=0;a[b+737>>0]=0;a[b+738>>0]=0;a[b+739>>0]=1;a[b+740>>0]=l&1;c[b+748>>2]=0;c[b+600>>2]=c[f>>2];c[b+600+4>>2]=c[f+4>>2];c[b+600+8>>2]=c[f+8>>2];c[b+600+12>>2]=c[f+12>>2];m=+g[d+4>>2];n=+g[d+20>>2];o=+g[d+36>>2];p=+g[i>>2];q=+g[i+4>>2];r=+g[i+8>>2];do if(!(m*p+n*q+o*r>=.9999998807907104))if(!(m*p+n*q+o*r<=-.9999998807907104)){e=(g[k>>2]=o*q-n*r,c[k>>2]|0);f=(g[k>>2]=m*r-o*p,c[k>>2]|0);l=(g[k>>2]=n*p-m*q,c[k>>2]|0);u=(g[k>>2]=r*(m*r-o*p)-q*(n*p-m*q),c[k>>2]|0);v=(g[k>>2]=p*(n*p-m*q)-r*(o*q-n*r),c[k>>2]|0);t=(g[k>>2]=q*(o*q-n*r)-p*(m*r-o*p),c[k>>2]|0);break}else{u=c[d+12>>2]|0;v=c[d+28>>2]|0;t=c[d+44>>2]|0;e=c[d+8>>2]|0;l=c[d+40>>2]|0;f=c[d+24>>2]|0;break}else{u=(g[k>>2]=-+g[d+12>>2],c[k>>2]|0);v=(g[k>>2]=-+g[d+28>>2],c[k>>2]|0);t=(g[k>>2]=-+g[d+44>>2],c[k>>2]|0);e=c[d+8>>2]|0;l=c[d+40>>2]|0;f=c[d+24>>2]|0}while(0);c[b+552>>2]=u;c[b+556>>2]=e;c[b+560>>2]=c[i>>2];g[b+564>>2]=0.0;c[b+568>>2]=v;c[b+572>>2]=f;c[b+576>>2]=c[i+4>>2];g[b+580>>2]=0.0;c[b+584>>2]=t;c[b+588>>2]=l;c[b+592>>2]=c[i+8>>2];g[b+596>>2]=0.0;o=+g[i+4>>2];q=+g[j+8>>2];m=+g[i+8>>2];r=+g[j+4>>2];s=+g[j>>2];n=+g[i>>2];do if(q*m+(o*r+s*n)<-.9999998807907104)if(+N(+m)>.7071067690849304){n=1.0/+O(+(o*o+m*m));e=0;p=0.0;m=-(m*n);f=(g[k>>2]=o*n,c[k>>2]|0);break}else{m=1.0/+O(+(o*o+n*n));e=(g[k>>2]=-(o*m),c[k>>2]|0);p=0.0;m=n*m;f=0;break}else{w=+O(+((q*m+(o*r+s*n)+1.0)*2.0));e=(g[k>>2]=(o*q-m*r)*(1.0/w),c[k>>2]|0);p=w*.5;m=(m*s-q*n)*(1.0/w);f=(g[k>>2]=(r*n-o*s)*(1.0/w),c[k>>2]|0)}while(0);o=(c[k>>2]=u,+g[k>>2]);A=(c[k>>2]=t,+g[k>>2]);z=(c[k>>2]=f,+g[k>>2]);w=(c[k>>2]=v,+g[k>>2]);B=o*p+A*m-w*z;n=(c[k>>2]=e,+g[k>>2]);x=w*p+o*z-A*n;y=A*p+w*n-o*m;A=-(o*n)-w*m-A*z;m=-m;w=x*-z+(p*B+A*-n)-y*m;o=y*-n+(p*x+A*m)-B*-z;p=B*m+(A*-z+p*y)-x*-n;c[b+664>>2]=c[h>>2];c[b+664+4>>2]=c[h+4>>2];c[b+664+8>>2]=c[h+8>>2];c[b+664+12>>2]=c[h+12>>2];g[b+616>>2]=w;g[b+620>>2]=r*p-q*o;c[b+624>>2]=c[j>>2];g[b+628>>2]=0.0;g[b+632>>2]=o;g[b+636>>2]=q*w-s*p;c[b+640>>2]=c[j+4>>2];g[b+644>>2]=0.0;g[b+648>>2]=p;g[b+652>>2]=s*o-r*w;c[b+656>>2]=c[j+8>>2];g[b+660>>2]=0.0;g[b+732>>2]=a[b+740>>0]|0?-1.0:1.0;return}function oe(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,h=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0,q=0.0,r=0.0;p=i;i=i+144|0;if((c[a+16>>2]|0)<=0){o=a+76|0;c[o>>2]=c[b>>2];c[o+4>>2]=c[b+4>>2];c[o+8>>2]=c[b+8>>2];c[o+12>>2]=c[b+12>>2];b=c[a>>2]|0;b=b+68|0;b=c[b>>2]|0;Ab[b&255](a);i=p;return}j=p+16+16|0;k=p+16+32|0;l=p+16+48|0;o=0;do{n=c[a+24>>2]|0;m=n+(o*80|0)|0;c[p+16>>2]=c[m>>2];c[p+16+4>>2]=c[m+4>>2];c[p+16+8>>2]=c[m+8>>2];c[p+16+12>>2]=c[m+12>>2];m=n+(o*80|0)+16|0;c[j>>2]=c[m>>2];c[j+4>>2]=c[m+4>>2];c[j+8>>2]=c[m+8>>2];c[j+12>>2]=c[m+12>>2];m=n+(o*80|0)+32|0;c[k>>2]=c[m>>2];c[k+4>>2]=c[m+4>>2];c[k+8>>2]=c[m+8>>2];c[k+12>>2]=c[m+12>>2];m=n+(o*80|0)+48|0;c[l>>2]=c[m>>2];c[l+4>>2]=c[m+4>>2];c[l+8>>2]=c[m+8>>2];c[l+12>>2]=c[m+12>>2];n=c[n+(o*80|0)+64>>2]|0;n=Eb[c[(c[n>>2]|0)+28>>2]&127](n)|0;c[p>>2]=c[n>>2];c[p+4>>2]=c[n+4>>2];c[p+8>>2]=c[n+8>>2];q=+g[p+4>>2]*+g[b+4>>2]/+g[a+80>>2];r=+g[p+8>>2]*+g[b+8>>2]/+g[a+84>>2];g[p>>2]=+g[p>>2]*+g[b>>2]/+g[a+76>>2];g[p+4>>2]=q;g[p+8>>2]=r;g[p+12>>2]=0.0;n=c[(c[a+24>>2]|0)+(o*80|0)+64>>2]|0;Cb[c[(c[n>>2]|0)+24>>2]&127](n,p);r=+g[p+16+52>>2]*+g[b+4>>2]/+g[a+80>>2];q=+g[p+16+56>>2]*+g[b+8>>2]/+g[a+84>>2];g[p+16+48>>2]=+g[l>>2]*+g[b>>2]/+g[a+76>>2];g[p+16+52>>2]=r;g[p+16+56>>2]=q;g[p+16+60>>2]=0.0;n=c[a+24>>2]|0;m=n+(o*80|0)|0;c[m>>2]=c[p+16>>2];c[m+4>>2]=c[p+16+4>>2];c[m+8>>2]=c[p+16+8>>2];c[m+12>>2]=c[p+16+12>>2];m=n+(o*80|0)+16|0;c[m>>2]=c[j>>2];c[m+4>>2]=c[j+4>>2];c[m+8>>2]=c[j+8>>2];c[m+12>>2]=c[j+12>>2];m=n+(o*80|0)+32|0;c[m>>2]=c[k>>2];c[m+4>>2]=c[k+4>>2];c[m+8>>2]=c[k+8>>2];c[m+12>>2]=c[k+12>>2];n=n+(o*80|0)+48|0;c[n>>2]=c[l>>2];c[n+4>>2]=c[l+4>>2];c[n+8>>2]=c[l+8>>2];c[n+12>>2]=c[l+12>>2];if(c[a+64>>2]|0){m=c[(c[a+24>>2]|0)+(o*80|0)+64>>2]|0;mc[c[(c[m>>2]|0)+8>>2]&127](m,p+16|0,p+128|0,p+112|0);c[p+80>>2]=c[p+128>>2];c[p+80+4>>2]=c[p+128+4>>2];c[p+80+8>>2]=c[p+128+8>>2];c[p+80+12>>2]=c[p+128+12>>2];c[p+80+16>>2]=c[p+112>>2];c[p+80+16+4>>2]=c[p+112+4>>2];c[p+80+16+8>>2]=c[p+112+8>>2];c[p+80+16+12>>2]=c[p+112+12>>2];m=c[a+64>>2]|0;n=c[(c[a+24>>2]|0)+(o*80|0)+76>>2]|0;d=hh(m,n)|0;a:do if(d){f=c[m+8>>2]|0;if((f|0)<=-1){d=c[m>>2]|0;break}if((f|0)>0){h=0;while(1){e=c[d+32>>2]|0;h=h+1|0;if(!e)break a;if((h|0)>=(f|0)){d=e;break}else d=e}}}else d=0;while(0);c[n>>2]=c[p+80>>2];c[n+4>>2]=c[p+80+4>>2];c[n+8>>2]=c[p+80+8>>2];c[n+12>>2]=c[p+80+12>>2];c[n+16>>2]=c[p+80+16>>2];c[n+20>>2]=c[p+80+20>>2];c[n+24>>2]=c[p+80+24>>2];c[n+28>>2]=c[p+80+28>>2];lf(m,d,n)}o=o+1|0}while((o|0)<(c[a+16>>2]|0));o=a+76|0;c[o>>2]=c[b>>2];c[o+4>>2]=c[b+4>>2];c[o+8>>2]=c[b+8>>2];c[o+12>>2]=c[b+12>>2];b=c[a>>2]|0;b=b+68|0;b=c[b>>2]|0;Ab[b&255](a);i=p;return}function pe(d,f,h,i,j,k){d=d|0;f=f|0;h=h|0;i=i|0;j=j|0;k=k|0;var l=0.0,m=0.0,n=0.0;c[d>>2]=8520;b[d+4>>1]=-2;b[d+6>>1]=-1;c[d+92>>2]=j;c[d+96>>2]=0;a[d+100>>0]=0;c[d+104>>2]=0;c[d+108>>2]=0;if(!j){c[6435]=(c[6435]|0)+1;j=yc(95)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}Ri(j);c[d+92>>2]=j;a[d+100>>0]=1}if(!k){c[6435]=(c[6435]|0)+1;j=yc(43)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}c[j>>2]=0;c[j+4>>2]=0;c[j+8>>2]=0;c[j+12>>2]=0;c[j+16>>2]=0;c[j+20>>2]=0;c[j>>2]=8584;a[j+20>>0]=1;c[j+16>>2]=0;c[j+8>>2]=0;c[j+12>>2]=0;c[d+112>>2]=j;c[6435]=(c[6435]|0)+1;j=yc(215)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}Zh(j,c[d+112>>2]|0);c[d+108>>2]=j;a[j+193>>0]=1}c[d+8>>2]=c[f>>2];c[d+8+4>>2]=c[f+4>>2];c[d+8+8>>2]=c[f+8>>2];c[d+8+12>>2]=c[f+12>>2];c[d+24>>2]=c[h>>2];c[d+24+4>>2]=c[h+4>>2];c[d+24+8>>2]=c[h+8>>2];c[d+24+12>>2]=c[h+12>>2];n=+(e[d+6>>1]|0);m=n/(+g[d+28>>2]-+g[d+12>>2]);l=n/(+g[d+32>>2]-+g[d+16>>2]);g[d+40>>2]=n/(+g[d+24>>2]-+g[d+8>>2]);g[d+44>>2]=m;g[d+48>>2]=l;g[d+52>>2]=0.0;f=(i&65535)+1&65535;c[6435]=(c[6435]|0)+1;j=yc(f<<6|19)|0;if(!j)h=0;else{c[(j+4+15&-16)+-4>>2]=j;h=j+4+15&-16}if(f|0){j=h+(f<<6)|0;k=h;do{c[k>>2]=0;c[k+8>>2]=0;k=k+64|0}while((k|0)!=(j|0))}c[d+60>>2]=h;b[d+58>>1]=(i&65535)+1;b[d+56>>1]=0;b[d+64>>1]=1;if(f>>>0>1){j=1;k=1;do{b[h+(j<<6)+48>>1]=j+1;k=k+1<<16>>16;j=k&65535}while(j>>>0>>0)}b[h+(f+-1<<6)+48>>1]=0;c[6435]=(c[6435]|0)+1;j=yc((f<<3|3)+16|0)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}c[d+80>>2]=j;c[d+68>>2]=j;c[6435]=(c[6435]|0)+1;j=yc((f<<3|3)+16|0)|0;if(!j)j=0;else{c[(j+4+15&-16)+-4>>2]=j;j=j+4+15&-16}c[d+84>>2]=j;c[d+72>>2]=j;c[6435]=(c[6435]|0)+1;j=yc((f<<3|3)+16|0)|0;if(!j){h=0;i=d+88|0;c[i>>2]=h;i=d+76|0;c[i>>2]=h;h=c[d+60>>2]|0;c[h>>2]=0;f=h+48|0;b[f>>1]=0;f=h+54|0;b[f>>1]=1;f=c[d+68>>2]|0;b[f>>1]=0;k=f+2|0;b[k>>1]=0;k=b[d+6>>1]|0;j=f+4|0;b[j>>1]=k;f=f+6|0;b[f>>1]=0;f=h+50|0;b[f>>1]=0;f=h+56|0;b[f>>1]=1;f=c[d+72>>2]|0;b[f>>1]=0;j=f+2|0;b[j>>1]=0;j=b[d+6>>1]|0;k=f+4|0;b[k>>1]=j;f=f+6|0;b[f>>1]=0;f=h+52|0;b[f>>1]=0;h=h+58|0;b[h>>1]=1;i=c[i>>2]|0;b[i>>1]=0;h=i+2|0;b[h>>1]=0;h=b[d+6>>1]|0;f=i+4|0;b[f>>1]=h;i=i+6|0;b[i>>1]=0;c[d>>2]=8660;return}c[(j+4+15&-16)+-4>>2]=j;h=j+4+15&-16;i=d+88|0;c[i>>2]=h;i=d+76|0;c[i>>2]=h;h=c[d+60>>2]|0;c[h>>2]=0;f=h+48|0;b[f>>1]=0;f=h+54|0;b[f>>1]=1;f=c[d+68>>2]|0;b[f>>1]=0;k=f+2|0;b[k>>1]=0;k=b[d+6>>1]|0;j=f+4|0;b[j>>1]=k;f=f+6|0;b[f>>1]=0;f=h+50|0;b[f>>1]=0;f=h+56|0;b[f>>1]=1;f=c[d+72>>2]|0;b[f>>1]=0;j=f+2|0;b[j>>1]=0;j=b[d+6>>1]|0;k=f+4|0;b[k>>1]=j;f=f+6|0;b[f>>1]=0;f=h+52|0;b[f>>1]=0;h=h+58|0;b[h>>1]=1;i=c[i>>2]|0;b[i>>1]=0;h=i+2|0;b[h>>1]=0;h=b[d+6>>1]|0;f=i+4|0;b[f>>1]=h;i=i+6|0;b[i>>1]=0;c[d>>2]=8660;return}function qe(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0;Il();c[b+4>>2]=6;c[b+8>>2]=-1;c[b+12>>2]=-1;g[b+16>>2]=3402823466385288598117041.0e14;a[b+20>>0]=1;a[b+21>>0]=0;c[b+24>>2]=-1;c[b+28>>2]=23268;c[b+32>>2]=d;g[b+36>>2]=0.0;g[b+40>>2]=.30000001192092896;c[b+44>>2]=0;c[b>>2]=4376;c[b+112>>2]=c[e>>2];c[b+112+4>>2]=c[e+4>>2];c[b+112+8>>2]=c[e+8>>2];c[b+112+12>>2]=c[e+12>>2];c[b+128>>2]=c[e+16>>2];c[b+128+4>>2]=c[e+16+4>>2];c[b+128+8>>2]=c[e+16+8>>2];c[b+128+12>>2]=c[e+16+12>>2];c[b+144>>2]=c[e+32>>2];c[b+144+4>>2]=c[e+32+4>>2];c[b+144+8>>2]=c[e+32+8>>2];c[b+144+12>>2]=c[e+32+12>>2];c[b+160>>2]=c[e+48>>2];c[b+160+4>>2]=c[e+48+4>>2];c[b+160+8>>2]=c[e+48+8>>2];c[b+160+12>>2]=c[e+48+12>>2];e=b+680|0;h=e+48|0;do{c[e>>2]=0;e=e+4|0}while((e|0)<(h|0));c[b+740>>2]=0;c[b+740+4>>2]=0;c[b+740+8>>2]=0;c[b+740+12>>2]=0;c[b+756>>2]=1045220557;c[b+760>>2]=1045220557;c[b+764>>2]=1045220557;c[b+768>>2]=0;c[b+768+4>>2]=0;c[b+768+8>>2]=0;c[b+768+12>>2]=0;c[b+768+16>>2]=0;g[b+728>>2]=.699999988079071;g[b+732>>2]=1.0;g[b+736>>2]=.5;a[b+788>>0]=0;g[b+792>>2]=0.0;g[b+808>>2]=0.0;a[b+789>>0]=0;g[b+796>>2]=0.0;g[b+812>>2]=0.0;a[b+790>>0]=0;g[b+800>>2]=0.0;g[b+816>>2]=0.0;g[b+928>>2]=0.0;g[b+876>>2]=0.0;g[b+880>>2]=.10000000149011612;g[b+884>>2]=300.0;g[b+868>>2]=1.0;g[b+872>>2]=-1.0;g[b+896>>2]=0.0;g[b+900>>2]=.20000000298023224;g[b+904>>2]=0.0;g[b+908>>2]=0.0;g[b+888>>2]=1.0;g[b+892>>2]=.5;c[b+924>>2]=0;g[b+916>>2]=0.0;a[b+912>>0]=0;g[b+992>>2]=0.0;g[b+940>>2]=0.0;g[b+944>>2]=.10000000149011612;g[b+948>>2]=300.0;g[b+932>>2]=1.0;g[b+936>>2]=-1.0;g[b+960>>2]=0.0;g[b+964>>2]=.20000000298023224;g[b+968>>2]=0.0;g[b+972>>2]=0.0;g[b+952>>2]=1.0;g[b+956>>2]=.5;c[b+988>>2]=0;g[b+980>>2]=0.0;a[b+976>>0]=0;g[b+1056>>2]=0.0;g[b+1004>>2]=0.0;g[b+1008>>2]=.10000000149011612;g[b+1012>>2]=300.0;g[b+996>>2]=1.0;g[b+1e3>>2]=-1.0;g[b+1024>>2]=0.0;g[b+1028>>2]=.20000000298023224;g[b+1032>>2]=0.0;g[b+1036>>2]=0.0;g[b+1016>>2]=1.0;g[b+1020>>2]=.5;c[b+1052>>2]=0;g[b+1044>>2]=0.0;a[b+1040>>0]=0;a[b+1300>>0]=f&1;a[b+1301>>0]=1;c[b+1304>>2]=0;a[b+1308>>0]=0;w=+g[b+112>>2];C=+g[d+4>>2];v=+g[b+128>>2];B=+g[d+8>>2];u=+g[b+144>>2];A=+g[d+12>>2];t=+g[b+116>>2];s=+g[b+132>>2];r=+g[b+148>>2];q=+g[b+120>>2];o=+g[b+136>>2];m=+g[b+152>>2];z=+g[d+20>>2];y=+g[d+24>>2];x=+g[d+28>>2];p=+g[d+36>>2];n=+g[d+40>>2];l=+g[d+44>>2];E=+g[b+160>>2];D=+g[b+164>>2];i=+g[b+168>>2];k=+g[d+52>>2]+(C*E+B*D+A*i);j=z*E+y*D+x*i+ +g[d+56>>2];i=p*E+n*D+l*i+ +g[d+60>>2];g[b+48>>2]=w*C+v*B+u*A;g[b+52>>2]=C*t+B*s+A*r;g[b+56>>2]=C*q+B*o+A*m;g[b+60>>2]=0.0;g[b+64>>2]=w*z+v*y+u*x;g[b+68>>2]=t*z+s*y+r*x;g[b+72>>2]=q*z+o*y+m*x;g[b+76>>2]=0.0;g[b+80>>2]=w*p+v*n+u*l;g[b+84>>2]=t*p+s*n+r*l;g[b+88>>2]=q*p+o*n+m*l;g[b+92>>2]=0.0;g[b+96>>2]=k;g[b+100>>2]=j;g[b+104>>2]=i;g[b+108>>2]=0.0;sd(b,(c[b+28>>2]|0)+4|0,(c[b+32>>2]|0)+4|0);return}function re(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0,H=0.0,I=0.0,J=0.0,K=0.0,L=0.0,M=0.0,N=0.0,O=0.0,P=0.0,Q=0.0,R=0.0,S=0.0,T=0.0,U=0.0,V=0.0,W=0,X=0.0,Y=0.0;W=i;i=i+240|0;f=(a[b+8>>0]|0)!=0;h=f?e:d;f=f?d:e;S=+g[h+116>>2]-+g[h+52>>2];T=+g[h+120>>2]-+g[h+56>>2];U=+g[h+124>>2]-+g[h+60>>2];V=+g[h+252>>2];if(S*S+T*T+U*U>2];G=+g[f+20>>2];H=+g[f+36>>2];I=+g[f+8>>2];J=+g[f+24>>2];K=+g[f+40>>2];L=+g[f+12>>2];M=+g[f+28>>2];N=+g[f+44>>2];k=-+g[f+52>>2];l=-+g[f+56>>2];m=-+g[f+60>>2];O=+g[h+4>>2];P=+g[h+20>>2];Q=+g[h+36>>2];R=+g[h+8>>2];S=+g[h+24>>2];T=+g[h+40>>2];U=+g[h+12>>2];V=+g[h+28>>2];p=+g[h+44>>2];u=+g[h+52>>2];t=+g[h+56>>2];s=+g[h+60>>2];q=F*k+G*l+H*m+(F*u+G*t+H*s);r=I*k+J*l+K*m+(I*u+J*t+K*s);s=L*k+M*l+N*m+(L*u+M*t+N*s);t=+g[h+68>>2];u=+g[h+84>>2];v=+g[h+100>>2];w=+g[h+72>>2];x=+g[h+88>>2];y=+g[h+104>>2];z=+g[h+76>>2];A=+g[h+92>>2];B=+g[h+108>>2];n=+g[h+116>>2];o=+g[h+120>>2];E=+g[h+124>>2];C=F*k+G*l+H*m+(F*n+G*o+H*E);D=I*k+J*l+K*m+(I*n+J*o+K*E);E=L*k+M*l+N*m+(L*n+M*o+N*E);f=c[f+192>>2]|0;if(((c[f+4>>2]|0)+-21|0)>>>0>=9){X=1.0;i=W;return +X}g[W+224>>2]=q;g[W+224+4>>2]=r;g[W+224+8>>2]=s;g[W+224+12>>2]=0.0;if(C>2]=C;j=C}else j=q;if(D>2]=D;k=D}else k=r;if(E>2]=E;l=E}else l=s;g[W+208>>2]=q;g[W+208+4>>2]=r;g[W+208+8>>2]=s;g[W+208+12>>2]=0.0;if(q>2]=C;m=C}else m=q;if(r>2]=D;n=D}else n=r;if(s>2]=E;o=E}else o=s;Y=+g[h+248>>2];g[W+224>>2]=j-Y;g[W+224+4>>2]=k-Y;g[W+224+8>>2]=l-Y;g[W+208>>2]=Y+m;g[W+208+4>>2]=Y+n;g[W+208+8>>2]=Y+o;c[W>>2]=3688;g[W+4>>2]=F*O+G*P+H*Q;g[W+8>>2]=F*R+G*S+H*T;g[W+12>>2]=F*U+G*V+H*p;g[W+16>>2]=0.0;g[W+20>>2]=I*O+J*P+K*Q;g[W+24>>2]=I*R+J*S+K*T;g[W+28>>2]=I*U+J*V+K*p;g[W+32>>2]=0.0;g[W+36>>2]=L*O+M*P+N*Q;g[W+40>>2]=L*R+M*S+N*T;g[W+44>>2]=L*U+M*V+N*p;g[W+48>>2]=0.0;g[W+52>>2]=q;g[W+56>>2]=r;g[W+60>>2]=s;g[W+64>>2]=0.0;g[W+68>>2]=F*t+G*u+H*v;g[W+72>>2]=F*w+G*x+H*y;g[W+76>>2]=F*z+G*A+H*B;g[W+80>>2]=0.0;g[W+84>>2]=I*t+J*u+K*v;g[W+88>>2]=I*w+J*x+K*y;g[W+92>>2]=I*z+J*A+K*B;g[W+96>>2]=0.0;g[W+100>>2]=L*t+M*u+N*v;g[W+104>>2]=L*w+M*x+N*y;g[W+108>>2]=L*z+M*A+N*B;g[W+112>>2]=0.0;g[W+116>>2]=C;g[W+120>>2]=D;g[W+124>>2]=E;g[W+128>>2]=0.0;g[W+196>>2]=Y;c[W+200>>2]=c[h+244>>2];if(f|0?(mc[c[(c[f>>2]|0)+64>>2]&127](f,W,W+224|0,W+208|0),X=+g[W+200>>2],X<+g[h+244>>2]):0){g[h+244>>2]=X;Y=X;i=W;return +Y}Y=1.0;i=W;return +Y}function se(b,d,e,f,h){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;var j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0,H=0.0,I=0.0,J=0.0,K=0.0,L=0.0,M=0.0,N=0.0,O=0.0,P=0.0,Q=0.0,R=0.0,S=0.0,T=0.0,U=0.0,V=0.0,W=0,X=0.0,Y=0.0;W=i;i=i+240|0;f=(a[b+8>>0]|0)!=0;h=f?e:d;f=f?d:e;S=+g[h+116>>2]-+g[h+52>>2];T=+g[h+120>>2]-+g[h+56>>2];U=+g[h+124>>2]-+g[h+60>>2];V=+g[h+252>>2];if(S*S+T*T+U*U>2];G=+g[f+20>>2];H=+g[f+36>>2];I=+g[f+8>>2];J=+g[f+24>>2];K=+g[f+40>>2];L=+g[f+12>>2];M=+g[f+28>>2];N=+g[f+44>>2];k=-+g[f+52>>2];l=-+g[f+56>>2];m=-+g[f+60>>2];O=+g[h+4>>2];P=+g[h+20>>2];Q=+g[h+36>>2];R=+g[h+8>>2];S=+g[h+24>>2];T=+g[h+40>>2];U=+g[h+12>>2];V=+g[h+28>>2];p=+g[h+44>>2];u=+g[h+52>>2];t=+g[h+56>>2];s=+g[h+60>>2];q=F*k+G*l+H*m+(F*u+G*t+H*s);r=I*k+J*l+K*m+(I*u+J*t+K*s);s=L*k+M*l+N*m+(L*u+M*t+N*s);t=+g[h+68>>2];u=+g[h+84>>2];v=+g[h+100>>2];w=+g[h+72>>2];x=+g[h+88>>2];y=+g[h+104>>2];z=+g[h+76>>2];A=+g[h+92>>2];B=+g[h+108>>2];n=+g[h+116>>2];o=+g[h+120>>2];E=+g[h+124>>2];C=F*k+G*l+H*m+(F*n+G*o+H*E);D=I*k+J*l+K*m+(I*n+J*o+K*E);E=L*k+M*l+N*m+(L*n+M*o+N*E);f=c[f+192>>2]|0;if(((c[f+4>>2]|0)+-21|0)>>>0>=9){X=1.0;i=W;return +X}g[W+224>>2]=q;g[W+224+4>>2]=r;g[W+224+8>>2]=s;g[W+224+12>>2]=0.0;if(C>2]=C;j=C}else j=q;if(D>2]=D;k=D}else k=r;if(E>2]=E;l=E}else l=s;g[W+208>>2]=q;g[W+208+4>>2]=r;g[W+208+8>>2]=s;g[W+208+12>>2]=0.0;if(q>2]=C;m=C}else m=q;if(r>2]=D;n=D}else n=r;if(s>2]=E;o=E}else o=s;Y=+g[h+248>>2];g[W+224>>2]=j-Y;g[W+224+4>>2]=k-Y;g[W+224+8>>2]=l-Y;g[W+208>>2]=Y+m;g[W+208+4>>2]=Y+n;g[W+208+8>>2]=Y+o;c[W>>2]=5556;g[W+4>>2]=F*O+G*P+H*Q;g[W+8>>2]=F*R+G*S+H*T;g[W+12>>2]=F*U+G*V+H*p;g[W+16>>2]=0.0;g[W+20>>2]=I*O+J*P+K*Q;g[W+24>>2]=I*R+J*S+K*T;g[W+28>>2]=I*U+J*V+K*p;g[W+32>>2]=0.0;g[W+36>>2]=L*O+M*P+N*Q;g[W+40>>2]=L*R+M*S+N*T;g[W+44>>2]=L*U+M*V+N*p;g[W+48>>2]=0.0;g[W+52>>2]=q;g[W+56>>2]=r;g[W+60>>2]=s;g[W+64>>2]=0.0;g[W+68>>2]=F*t+G*u+H*v;g[W+72>>2]=F*w+G*x+H*y;g[W+76>>2]=F*z+G*A+H*B;g[W+80>>2]=0.0;g[W+84>>2]=I*t+J*u+K*v;g[W+88>>2]=I*w+J*x+K*y;g[W+92>>2]=I*z+J*A+K*B;g[W+96>>2]=0.0;g[W+100>>2]=L*t+M*u+N*v;g[W+104>>2]=L*w+M*x+N*y;g[W+108>>2]=L*z+M*A+N*B;g[W+112>>2]=0.0;g[W+116>>2]=C;g[W+120>>2]=D;g[W+124>>2]=E;g[W+128>>2]=0.0;g[W+196>>2]=Y;c[W+200>>2]=c[h+244>>2];if(f|0?(mc[c[(c[f>>2]|0)+64>>2]&127](f,W,W+224|0,W+208|0),X=+g[W+200>>2],X<+g[h+244>>2]):0){g[h+244>>2]=X;Y=X;i=W;return +Y}Y=1.0;i=W;return +Y}function te(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0;m=0;do{k=m;m=m+1|0;l=(m|0)==3;j=c[b+((l?0:m)<<2)>>2]|0;k=c[b+(((k+2|0)%3|0)<<2)>>2]|0;e=c[d>>2]|0;f=c[d+4>>2]|0;do if((e|0)==(k|0)&(f|0)==(j|0)){e=2;n=3}else{if(!((e|0)==(j|0)&(f|0)==(k|0))){g=c[d+8>>2]|0;if((f|0)==(k|0)&(g|0)==(j|0)){e=0;n=3;break}if(!((f|0)==(j|0)&(g|0)==(k|0))){if(!((g|0)!=(k|0)|(e|0)==(j|0)^1)){e=1;n=3;break}if((g|0)!=(j|0)|(e|0)==(k|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=d+12+(e<<2)|0}while(0);if((n|0)==3){n=0;e=d+12+(e<<2)|0}i=c[e>>2]|0;e=c[b>>2]|0;f=c[b+4>>2]|0;do if((e|0)==(j|0)&(f|0)==(k|0)){e=2;n=11}else{if(!((e|0)==(k|0)&(f|0)==(j|0))){g=c[b+8>>2]|0;if((f|0)==(j|0)&(g|0)==(k|0)){e=0;n=11;break}if(!((f|0)==(k|0)&(g|0)==(j|0))){if(!((g|0)!=(j|0)|(e|0)==(k|0)^1)){e=1;n=11;break}if((g|0)!=(k|0)|(e|0)==(j|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=b+12+(e<<2)|0}while(0);if((n|0)==11){n=0;e=b+12+(e<<2)|0}h=c[a+(c[e>>2]<<2)>>2]|0;e=c[h>>2]|0;f=c[h+4>>2]|0;do if((e|0)==(k|0)&(f|0)==(j|0)){e=2;n=19}else{if(!((e|0)==(j|0)&(f|0)==(k|0))){g=c[h+8>>2]|0;if((f|0)==(k|0)&(g|0)==(j|0)){e=0;n=19;break}if(!((f|0)==(j|0)&(g|0)==(k|0))){if(!((g|0)!=(k|0)|(e|0)==(j|0)^1)){e=1;n=19;break}if((g|0)!=(j|0)|(e|0)==(k|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=h+12+(e<<2)|0}while(0);if((n|0)==19){n=0;e=h+12+(e<<2)|0}c[e>>2]=i;e=c[b>>2]|0;f=c[b+4>>2]|0;do if((e|0)==(j|0)&(f|0)==(k|0)){e=2;n=27}else{if(!((e|0)==(k|0)&(f|0)==(j|0))){g=c[b+8>>2]|0;if((f|0)==(j|0)&(g|0)==(k|0)){e=0;n=27;break}if(!((f|0)==(k|0)&(g|0)==(j|0))){if(!((g|0)!=(j|0)|(e|0)==(k|0)^1)){e=1;n=27;break}if((g|0)!=(k|0)|(e|0)==(j|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=b+12+(e<<2)|0}while(0);if((n|0)==27){n=0;e=b+12+(e<<2)|0}i=c[e>>2]|0;e=c[d>>2]|0;f=c[d+4>>2]|0;do if((e|0)==(k|0)&(f|0)==(j|0)){e=2;n=35}else{if(!((e|0)==(j|0)&(f|0)==(k|0))){g=c[d+8>>2]|0;if((f|0)==(k|0)&(g|0)==(j|0)){e=0;n=35;break}if(!((f|0)==(j|0)&(g|0)==(k|0))){if(!((g|0)!=(k|0)|(e|0)==(j|0)^1)){e=1;n=35;break}if((g|0)!=(j|0)|(e|0)==(k|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=d+12+(e<<2)|0}while(0);if((n|0)==35){n=0;e=d+12+(e<<2)|0}h=c[a+(c[e>>2]<<2)>>2]|0;e=c[h>>2]|0;f=c[h+4>>2]|0;do if((e|0)==(j|0)&(f|0)==(k|0)){e=2;n=43}else{if(!((e|0)==(k|0)&(f|0)==(j|0))){g=c[h+8>>2]|0;if((f|0)==(j|0)&(g|0)==(k|0)){e=0;n=43;break}if(!((f|0)==(k|0)&(g|0)==(j|0))){if(!((g|0)!=(j|0)|(e|0)==(k|0)^1)){e=1;n=43;break}if((g|0)!=(k|0)|(e|0)==(j|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=h+12+(e<<2)|0}while(0);if((n|0)==43){n=0;e=h+12+(e<<2)|0}c[e>>2]=i}while(!l);return}function ue(a,b,d){a=a|0;b=b|0;d=d|0;var e=0,f=0,g=0,h=0,i=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0;l=c[b>>2]|0;m=c[b+4>>2]|0;i=c[b+8>>2]|0;n=c[a+4>>2]|0;p=Uh(a,d,m,i)|0;c[p+12>>2]=c[b+12>>2];c[p+16>>2]=n+1;c[p+20>>2]=n+2;h=c[(c[a+12>>2]|0)+(c[b+12>>2]<<2)>>2]|0;e=c[h>>2]|0;f=c[h+4>>2]|0;do if((e|0)==(m|0)&(f|0)==(i|0)){e=2;o=2}else{if(!((e|0)==(i|0)&(f|0)==(m|0))){g=c[h+8>>2]|0;if((f|0)==(m|0)&(g|0)==(i|0)){e=0;o=2;break}if(!((f|0)==(i|0)&(g|0)==(m|0))){if(!((g|0)!=(m|0)|(e|0)==(i|0)^1)){e=1;o=2;break}if((g|0)!=(i|0)|(e|0)==(m|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=h+12+(e<<2)|0}while(0);if((o|0)==2)e=h+12+(e<<2)|0;c[e>>2]=n;k=Uh(a,d,i,l)|0;c[k+12>>2]=c[b+12+4>>2];c[k+16>>2]=n+2;c[k+20>>2]=n;h=c[(c[a+12>>2]|0)+(c[b+12+4>>2]<<2)>>2]|0;e=c[h>>2]|0;f=c[h+4>>2]|0;do if((e|0)==(i|0)&(f|0)==(l|0)){e=2;o=10}else{if(!((e|0)==(l|0)&(f|0)==(i|0))){g=c[h+8>>2]|0;if((f|0)==(i|0)&(g|0)==(l|0)){e=0;o=10;break}if(!((f|0)==(l|0)&(g|0)==(i|0))){if(!((g|0)!=(i|0)|(e|0)==(l|0)^1)){e=1;o=10;break}if((g|0)!=(l|0)|(e|0)==(i|0)^1){e=9432;break}else e=1}else e=0}else e=2;e=h+12+(e<<2)|0}while(0);if((o|0)==10)e=h+12+(e<<2)|0;c[e>>2]=n+1;j=Uh(a,d,l,m)|0;c[j+12>>2]=c[b+12+8>>2];c[j+16>>2]=n;c[j+20>>2]=n+1;e=c[a+12>>2]|0;i=c[e+(c[b+12+8>>2]<<2)>>2]|0;f=c[i>>2]|0;g=c[i+4>>2]|0;do if((f|0)==(l|0)&(g|0)==(m|0)){f=2;o=18}else{if(!((f|0)==(m|0)&(g|0)==(l|0))){h=c[i+8>>2]|0;if((g|0)==(l|0)&(h|0)==(m|0)){f=0;o=18;break}if(!((g|0)==(m|0)&(h|0)==(l|0))){if(!((h|0)!=(l|0)|(f|0)==(m|0)^1)){f=1;o=18;break}if((h|0)!=(m|0)|(f|0)==(l|0)^1){f=9432;break}else f=1}else f=0}else f=2;f=i+12+(f<<2)|0}while(0);if((o|0)==18)f=i+12+(f<<2)|0;c[f>>2]=n+2;f=c[e+(c[p+12>>2]<<2)>>2]|0;if(!(((c[f>>2]|0)!=(d|0)?(c[f+4>>2]|0)!=(d|0):0)?(c[f+8>>2]|0)!=(d|0):0)){te(c[a+12>>2]|0,p,f);c[(c[a+12>>2]|0)+(c[p+24>>2]<<2)>>2]=0;c[6436]=(c[6436]|0)+1;hd(c[p+-4>>2]|0);c[(c[a+12>>2]|0)+(c[f+24>>2]<<2)>>2]=0;if(f|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}e=c[a+12>>2]|0}f=c[e+(c[k+12>>2]<<2)>>2]|0;if(!(((c[f>>2]|0)!=(d|0)?(c[f+4>>2]|0)!=(d|0):0)?(c[f+8>>2]|0)!=(d|0):0)){te(c[a+12>>2]|0,k,f);c[(c[a+12>>2]|0)+(c[k+24>>2]<<2)>>2]=0;c[6436]=(c[6436]|0)+1;hd(c[k+-4>>2]|0);c[(c[a+12>>2]|0)+(c[f+24>>2]<<2)>>2]=0;if(f|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}e=c[a+12>>2]|0}f=c[e+(c[j+12>>2]<<2)>>2]|0;if(!(((c[f>>2]|0)!=(d|0)?(c[f+4>>2]|0)!=(d|0):0)?(c[f+8>>2]|0)!=(d|0):0)){te(c[a+12>>2]|0,j,f);c[(c[a+12>>2]|0)+(c[j+24>>2]<<2)>>2]=0;c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0);c[(c[a+12>>2]|0)+(c[f+24>>2]<<2)>>2]=0;if(f|0){c[6436]=(c[6436]|0)+1;hd(c[f+-4>>2]|0)}e=c[a+12>>2]|0}c[e+(c[b+24>>2]<<2)>>2]=0;if(!b)return;c[6436]=(c[6436]|0)+1;hd(c[b+-4>>2]|0);return}function ve(b){b=b|0;var d=0,e=0.0,f=0.0,h=0.0,j=0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0,w=0.0,x=0.0,y=0;v=i;i=i+176|0;if(!(a[b+527>>0]|0)){i=v;return}g[b+36>>2]=0.0;g[b+520>>2]=0.0;g[b+516>>2]=0.0;c[b+576>>2]=0;c[b+576+4>>2]=0;c[b+576+8>>2]=0;c[b+576+12>>2]=0;if(!(a[b+524>>0]|0)){d=c[b+28>>2]|0;k=+g[b+348>>2];l=+g[b+352>>2];r=+g[b+356>>2];t=k*+g[d+20>>2]+l*+g[d+24>>2]+r*+g[d+28>>2]+ +g[d+56>>2];j=c[b+32>>2]|0;m=+g[b+412>>2];n=+g[b+416>>2];s=+g[b+420>>2];o=+g[j+52>>2];e=+g[j+56>>2];u=m*+g[j+20>>2]+n*+g[j+24>>2]+s*+g[j+28>>2]+e;p=m*+g[j+36>>2]+n*+g[j+40>>2]+s*+g[j+44>>2]+ +g[j+60>>2];q=k*+g[d+4>>2]+l*+g[d+8>>2]+r*+g[d+12>>2]+ +g[d+52>>2];r=k*+g[d+36>>2]+l*+g[d+40>>2]+r*+g[d+44>>2]+ +g[d+60>>2];s=m*+g[j+4>>2]+n*+g[j+8>>2]+s*+g[j+12>>2]+o;if((s-q)*(s-q)+(u-t)*(u-t)+(p-r)*(p-r)>1.1920928955078125e-07){h=1.0/+O(+((s-q)*(s-q)+(u-t)*(u-t)+(p-r)*(p-r)));g[v+128>>2]=(s-q)*h;g[v+128+4>>2]=(u-t)*h;g[v+128+8>>2]=(p-r)*h;c[v+128+12>>2]=0;k=(p-r)*h;f=(u-t)*h;h=(s-q)*h}else{c[v+128>>2]=1065353216;c[v+128+4>>2]=0;c[v+128+8>>2]=0;g[v+128+12>>2]=0.0;k=0.0;f=0.0;h=1.0}if(+N(+k)>.7071067690849304){x=k*k+f*f;w=1.0/+O(+x);m=-(w*k);k=w*f;n=-(k*h);l=h*m;f=x*w;h=k;k=0.0}else{m=h*h+f*f;l=1.0/+O(+m);x=-(f*l);f=l*h;n=k*x;l=m*l;m=f;f=-(f*k);h=0.0;k=x}g[v+128+16>>2]=k;g[v+128+20>>2]=m;g[v+128+24>>2]=h;g[v+128+32>>2]=f;g[v+128+36>>2]=n;g[v+128+40>>2]=l;f=o;d=0;while(1){y=c[b+28>>2]|0;c[v+80>>2]=c[y+4>>2];c[v+80+4>>2]=c[y+20>>2];c[v+80+8>>2]=c[y+36>>2];g[v+80+12>>2]=0.0;c[v+80+16>>2]=c[y+8>>2];c[v+80+20>>2]=c[y+24>>2];c[v+80+24>>2]=c[y+40>>2];g[v+80+28>>2]=0.0;c[v+80+32>>2]=c[y+12>>2];c[v+80+36>>2]=c[y+28>>2];c[v+80+40>>2]=c[y+44>>2];g[v+80+44>>2]=0.0;c[v+32>>2]=c[j+4>>2];c[v+32+4>>2]=c[j+20>>2];c[v+32+8>>2]=c[j+36>>2];g[v+32+12>>2]=0.0;c[v+32+16>>2]=c[j+8>>2];c[v+32+20>>2]=c[j+24>>2];c[v+32+24>>2]=c[j+40>>2];g[v+32+28>>2]=0.0;c[v+32+32>>2]=c[j+12>>2];c[v+32+36>>2]=c[j+28>>2];c[v+32+40>>2]=c[j+44>>2];g[v+32+44>>2]=0.0;w=t-+g[y+56>>2];x=r-+g[y+60>>2];g[v+16>>2]=q-+g[y+52>>2];g[v+16+4>>2]=w;g[v+16+8>>2]=x;g[v+16+12>>2]=0.0;x=p-+g[j+60>>2];g[v>>2]=s-f;g[v+4>>2]=u-e;g[v+8>>2]=x;g[v+12>>2]=0.0;y=c[b+28>>2]|0;j=c[b+32>>2]|0;Rg(b+48+(d*84|0)|0,v+80|0,v+32|0,v+16|0,v,v+128+(d<<4)|0,y+396|0,+g[y+344>>2],j+396|0,+g[j+344>>2]);d=d+1|0;if((d|0)==3)break;y=c[b+32>>2]|0;j=y;f=+g[y+52>>2];e=+g[y+56>>2]}d=b+32|0}else d=b+32|0;j=c[b+28>>2]|0;y=c[d>>2]|0;Fc(b,j+4|0,y+4|0,j+264|0,y+264|0);i=v;return}function we(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,i=0,j=0,k=0,l=0,m=0,n=0,o=0,p=0;if(!((d|0)!=0&(e|0)!=0))return;if((c[b+24>>2]|0)<128?(c[b+28>>2]|0)<128:0){c[6435]=(c[6435]|0)+1;h=yc(1043)|0;if(!h)j=0;else{c[(h+4+15&-16)+-4>>2]=h;j=h+4+15&-16}h=c[b+24>>2]|0;if((h|0)>0){i=0;do{l=(c[b+32>>2]|0)+(i<<3)|0;m=c[l+4>>2]|0;n=j+(i<<3)|0;c[n>>2]=c[l>>2];c[n+4>>2]=m;i=i+1|0}while((i|0)!=(h|0))}h=c[b+32>>2]|0;if(h|0){if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[h+-4>>2]|0)}c[b+32>>2]=0}a[b+36>>0]=1;c[b+32>>2]=j;c[b+28>>2]=128}c[b+24>>2]=128;n=c[b+32>>2]|0;c[n>>2]=d;c[n+4>>2]=e;n=1;j=124;while(1){h=n+-1|0;i=c[b+32>>2]|0;l=c[i+(h<<3)>>2]|0;m=c[i+(h<<3)+4>>2]|0;if((h|0)>(j|0)){e=c[b+24>>2]|0;if((e|0)<(e<<1|0)?(c[b+28>>2]|0)<(e<<1|0):0){if(e){c[6435]=(c[6435]|0)+1;i=yc((e<<4|3)+16|0)|0;if(!i)i=0;else{c[(i+4+15&-16)+-4>>2]=i;i=i+4+15&-16}j=c[b+24>>2]|0;if((j|0)>0){d=0;do{p=(c[b+32>>2]|0)+(d<<3)|0;o=c[p+4>>2]|0;k=i+(d<<3)|0;c[k>>2]=c[p>>2];c[k+4>>2]=o;d=d+1|0}while((d|0)!=(j|0))}}else i=0;j=c[b+32>>2]|0;if(j|0){if(a[b+36>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[j+-4>>2]|0)}c[b+32>>2]=0}a[b+36>>0]=1;c[b+32>>2]=i;c[b+28>>2]=e<<1}c[b+24>>2]=e<<1;j=(e<<1)+-4|0}do if((l|0)==(m|0)){if(c[l+40>>2]|0){p=c[l+36>>2]|0;c[i+(h<<3)>>2]=p;c[i+(h<<3)+4>>2]=p;h=n+1|0;p=c[b+32>>2]|0;o=c[l+40>>2]|0;c[p+(n<<3)>>2]=o;c[p+(n<<3)+4>>2]=o;p=c[b+32>>2]|0;o=c[l+40>>2]|0;c[p+(h<<3)>>2]=c[l+36>>2];c[p+(h<<3)+4>>2]=o;h=n+2|0}}else if(((((+g[l>>2]<=+g[m+16>>2]?+g[l+16>>2]>=+g[m>>2]:0)?+g[l+4>>2]<=+g[m+20>>2]:0)?+g[l+20>>2]>=+g[m+4>>2]:0)?+g[l+8>>2]<=+g[m+24>>2]:0)?+g[l+24>>2]>=+g[m+8>>2]:0){d=(c[m+40>>2]|0)!=0;if(!(c[l+40>>2]|0))if(d){p=c[m+36>>2]|0;c[i+(h<<3)>>2]=l;c[i+(h<<3)+4>>2]=p;h=c[b+32>>2]|0;p=c[m+40>>2]|0;c[h+(n<<3)>>2]=l;c[h+(n<<3)+4>>2]=p;h=n+1|0;break}else{ic[c[(c[f>>2]|0)+8>>2]&127](f,l,m);break}else{e=i+(h<<3)|0;k=c[l+36>>2]|0;if(d){p=c[m+36>>2]|0;c[e>>2]=k;c[i+(h<<3)+4>>2]=p;p=n+1|0;h=c[b+32>>2]|0;o=c[m+36>>2]|0;c[h+(n<<3)>>2]=c[l+40>>2];c[h+(n<<3)+4>>2]=o;h=n+2|0;o=c[b+32>>2]|0;k=c[m+40>>2]|0;c[o+(p<<3)>>2]=c[l+36>>2];c[o+(p<<3)+4>>2]=k;p=c[b+32>>2]|0;o=c[m+40>>2]|0;c[p+(h<<3)>>2]=c[l+40>>2];c[p+(h<<3)+4>>2]=o;h=n+3|0;break}else{c[e>>2]=k;c[i+(h<<3)+4>>2]=m;h=c[b+32>>2]|0;c[h+(n<<3)>>2]=c[l+40>>2];c[h+(n<<3)+4>>2]=m;h=n+1|0;break}}}while(0);if(!h)break;else n=h}return}function xe(a,b){a=a|0;b=b|0;var d=0,e=0,f=0,g=0;g=i;i=i+80|0;c[a+68>>2]=(c[a+68>>2]|0)+1;e=c[a+64>>2]|0;if(e|0){f=c[(c[a+24>>2]|0)+(b*80|0)+76>>2]|0;hh(e,f)|0;d=c[e+4>>2]|0;if(d|0){c[6436]=(c[6436]|0)+1;hd(c[d+-4>>2]|0)}c[e+4>>2]=f;c[e+12>>2]=(c[e+12>>2]|0)+-1}f=(c[a+16>>2]|0)+-1|0;e=c[a+24>>2]|0;c[g>>2]=c[e+(b*80|0)>>2];c[g+4>>2]=c[e+(b*80|0)+4>>2];c[g+8>>2]=c[e+(b*80|0)+8>>2];c[g+12>>2]=c[e+(b*80|0)+12>>2];c[g+16>>2]=c[e+(b*80|0)+16>>2];c[g+16+4>>2]=c[e+(b*80|0)+16+4>>2];c[g+16+8>>2]=c[e+(b*80|0)+16+8>>2];c[g+16+12>>2]=c[e+(b*80|0)+16+12>>2];c[g+32>>2]=c[e+(b*80|0)+32>>2];c[g+32+4>>2]=c[e+(b*80|0)+32+4>>2];c[g+32+8>>2]=c[e+(b*80|0)+32+8>>2];c[g+32+12>>2]=c[e+(b*80|0)+32+12>>2];c[g+48>>2]=c[e+(b*80|0)+48>>2];c[g+48+4>>2]=c[e+(b*80|0)+48+4>>2];c[g+48+8>>2]=c[e+(b*80|0)+48+8>>2];c[g+48+12>>2]=c[e+(b*80|0)+48+12>>2];c[g+64>>2]=c[e+(b*80|0)+64>>2];c[g+64+4>>2]=c[e+(b*80|0)+64+4>>2];c[g+64+8>>2]=c[e+(b*80|0)+64+8>>2];c[g+64+12>>2]=c[e+(b*80|0)+64+12>>2];c[e+(b*80|0)>>2]=c[e+(f*80|0)>>2];c[e+(b*80|0)+4>>2]=c[e+(f*80|0)+4>>2];c[e+(b*80|0)+8>>2]=c[e+(f*80|0)+8>>2];c[e+(b*80|0)+12>>2]=c[e+(f*80|0)+12>>2];c[e+(b*80|0)+16>>2]=c[e+(f*80|0)+16>>2];c[e+(b*80|0)+16+4>>2]=c[e+(f*80|0)+16+4>>2];c[e+(b*80|0)+16+8>>2]=c[e+(f*80|0)+16+8>>2];c[e+(b*80|0)+16+12>>2]=c[e+(f*80|0)+16+12>>2];c[e+(b*80|0)+32>>2]=c[e+(f*80|0)+32>>2];c[e+(b*80|0)+32+4>>2]=c[e+(f*80|0)+32+4>>2];c[e+(b*80|0)+32+8>>2]=c[e+(f*80|0)+32+8>>2];c[e+(b*80|0)+32+12>>2]=c[e+(f*80|0)+32+12>>2];c[e+(b*80|0)+48>>2]=c[e+(f*80|0)+48>>2];c[e+(b*80|0)+48+4>>2]=c[e+(f*80|0)+48+4>>2];c[e+(b*80|0)+48+8>>2]=c[e+(f*80|0)+48+8>>2];c[e+(b*80|0)+48+12>>2]=c[e+(f*80|0)+48+12>>2];c[e+(b*80|0)+64>>2]=c[e+(f*80|0)+64>>2];c[e+(b*80|0)+64+4>>2]=c[e+(f*80|0)+64+4>>2];c[e+(b*80|0)+64+8>>2]=c[e+(f*80|0)+64+8>>2];c[e+(b*80|0)+64+12>>2]=c[e+(f*80|0)+64+12>>2];e=c[a+24>>2]|0;c[e+(f*80|0)>>2]=c[g>>2];c[e+(f*80|0)+4>>2]=c[g+4>>2];c[e+(f*80|0)+8>>2]=c[g+8>>2];c[e+(f*80|0)+12>>2]=c[g+12>>2];c[e+(f*80|0)+16>>2]=c[g+16>>2];c[e+(f*80|0)+16+4>>2]=c[g+16+4>>2];c[e+(f*80|0)+16+8>>2]=c[g+16+8>>2];c[e+(f*80|0)+16+12>>2]=c[g+16+12>>2];c[e+(f*80|0)+32>>2]=c[g+32>>2];c[e+(f*80|0)+32+4>>2]=c[g+32+4>>2];c[e+(f*80|0)+32+8>>2]=c[g+32+8>>2];c[e+(f*80|0)+32+12>>2]=c[g+32+12>>2];c[e+(f*80|0)+48>>2]=c[g+48>>2];c[e+(f*80|0)+48+4>>2]=c[g+48+4>>2];c[e+(f*80|0)+48+8>>2]=c[g+48+8>>2];c[e+(f*80|0)+48+12>>2]=c[g+48+12>>2];c[e+(f*80|0)+64>>2]=c[g+64>>2];c[e+(f*80|0)+64+4>>2]=c[g+64+4>>2];c[e+(f*80|0)+64+8>>2]=c[g+64+8>>2];c[e+(f*80|0)+64+12>>2]=c[g+64+12>>2];if(!(c[a+64>>2]|0)){b=c[a+16>>2]|0;b=b+-1|0;c[a+16>>2]=b;i=g;return}c[(c[(c[a+24>>2]|0)+(b*80|0)+76>>2]|0)+36>>2]=b;b=c[a+16>>2]|0;b=b+-1|0;c[a+16>>2]=b;i=g;return}function ye(b,d,e,f,h,j){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=j|0;var k=0,l=0,m=0,n=0,o=0,p=0,q=0,r=0,s=0;s=i;i=i+80|0;if((h|0)>0){k=0;b=0;do{r=c[f+(k<<2)>>2]|0;b=(r|0)>(b|0)?r:b;k=k+1|0}while((k|0)<(h*3|0))}else b=0;p=b+1|0;l=_(p,p)|0;if(!l)r=0;else{c[6435]=(c[6435]|0)+1;k=yc(l+19|0)|0;if(!k)k=0;else{c[(k+4+15&-16)+-4>>2]=k;k=k+4+15&-16}Qn(k|0,0,l|0)|0;r=k}if((b|0)>-1){if((p|0)!=0?(c[6435]=(c[6435]|0)+1,m=yc((p<<4|3)+16|0)|0,(m|0)!=0):0){c[(m+4+15&-16)+-4>>2]=m;l=m+4+15&-16}else l=0;b=0;do{q=l+(b<<4)|0;c[q>>2]=c[s>>2];c[q+4>>2]=c[s+4>>2];c[q+8>>2]=c[s+8>>2];c[q+12>>2]=c[s+12>>2];b=b+1|0}while((b|0)!=(p|0));b=0;k=0;while(1){o=c[e+(b+1<<2)>>2]|0;q=c[e+(b+2<<2)>>2]|0;c[l+(k<<4)>>2]=c[e+(b<<2)>>2];c[l+(k<<4)+4>>2]=o;c[l+(k<<4)+8>>2]=q;g[l+(k<<4)+12>>2]=0.0;b=b+3|0;if((b|0)>=(p*3|0))break;else k=k+1|0}}else l=0;c[6435]=(c[6435]|0)+1;b=yc(1271)|0;if(!b)q=0;else{c[(b+4+15&-16)+-4>>2]=b;q=b+4+15&-16}Kc(q,d,p,l,0);if((h|0)>0){o=0;do{e=c[f+(o<<2)>>2]|0;d=c[f+(o+1<<2)>>2]|0;n=c[f+(o+2<<2)>>2]|0;k=_(e,p)|0;b=r+(k+n)|0;if(!(a[b>>0]|0)){a[b>>0]=1;a[r+(e+(_(n,p)|0))>>0]=1;Rf(q,n,e,0,0)}m=_(d,p)|0;b=r+(m+e)|0;if(!(a[b>>0]|0)){a[b>>0]=1;a[r+(d+k)>>0]=1;Rf(q,e,d,0,0)}b=r+((_(n,p)|0)+d)|0;if(!(a[b>>0]|0)){a[b>>0]=1;a[r+(n+m)>>0]=1;Rf(q,d,n,0,0)}Zf(q,e,d,n,0);o=o+3|0}while((o|0)<(h*3|0))}if(j){k=c[q+732>>2]|0;if((k|0)>0){m=q+740|0;n=0;b=243703;do{e=c[m>>2]|0;d=e+(n*52|0)|0;b=(_(b,1664525)|0)+1013904223|0;o=s+16|0;p=d;f=o+52|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));o=d;p=e+(((b>>>0)%(k>>>0)|0)*52|0)|0;f=o+52|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));o=e+(((b>>>0)%(k>>>0)|0)*52|0)|0;p=s+16|0;f=o+52|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));n=n+1|0}while((n|0)!=(k|0))}else b=243703;d=c[q+752>>2]|0;if((d|0)>0){e=q+760|0;n=0;do{m=c[e>>2]|0;k=m+(n*44|0)|0;b=(_(b,1664525)|0)+1013904223|0;m=m+(((b>>>0)%(d>>>0)|0)*44|0)|0;o=s+16|0;p=k;f=o+44|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));o=k;p=m;f=o+44|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));o=m;p=s+16|0;f=o+44|0;do{c[o>>2]=c[p>>2];o=o+4|0;p=p+4|0}while((o|0)<(f|0));n=n+1|0}while((n|0)!=(d|0))}}if(l|0){c[6436]=(c[6436]|0)+1;hd(c[l+-4>>2]|0)}if(!r){i=s;return q|0}c[6436]=(c[6436]|0)+1;hd(c[r+-4>>2]|0);i=s;return q|0}function ze(a,d,f,h,j,k,l,m,n){a=a|0;d=d|0;f=f|0;h=+h;j=+j;k=+k;l=l|0;m=m|0;n=n|0;var o=0,p=0,q=0,r=0,s=0.0,t=0.0,u=0.0,v=0.0,w=0,x=0,y=0,z=0,A=0,B=0,C=0,D=0,E=0,F=0,G=0,H=0.0,I=0,J=0.0,K=0.0,L=0.0,M=0.0,N=0.0,P=0.0,Q=0.0,R=0.0,S=0.0,T=0,U=0.0,V=0,W=0.0,X=0.0,Y=0.0,Z=0.0,_=0.0,$=0.0,aa=0.0,ba=0.0,ca=0.0,da=0.0,ea=0.0;V=i;i=i+32|0;H=+g[f>>2];Q=+g[f+4>>2];S=+g[f+8>>2];J=1.0/+O(+((h-H)*(h-H)+(j-Q)*(j-Q)+(k-S)*(k-S)));N=(h-H)*J==0.0?999999984306749440.0:1.0/((h-H)*J);P=(j-Q)*J==0.0?999999984306749440.0:1.0/((j-Q)*J);R=(k-S)*J==0.0?999999984306749440.0:1.0/((k-S)*J);ea=(H>h?h:H)+ +g[l>>2];ca=(Q>j?j:Q)+ +g[l+4>>2];da=(S>k?k:S)+ +g[l+8>>2];aa=(H>2];t=(Q>2];Y=(S>2];$=+g[a+4>>2];ea=ea<$?$:ea;u=+g[a+8>>2];ca=ca>2];da=da>2];s=+g[a+24>>2];Z=+g[a+28>>2];_=+g[a+36>>2];v=+g[a+40>>2];W=+g[a+44>>2];T=~~(((ba0){p=0;q=c[a+136>>2]|0;o=0;do{o=o+1|0;r=q+6|0;w=b[q>>1]|0;x=q+10|0;y=b[q+4>>1]|0;z=q+8|0;A=b[q+2>>1]|0;B=q+12|0;C=(c[B>>2]|0)>-1;do if(((I&65535)>=(w&65535)?(T&65535)<=(e[r>>1]|0):0)&(E&65535)<=(e[x>>1]|0)&(D&65535)>=(y&65535)&(G&65535)<=(e[z>>1]|0)&(F&65535)>=(A&65535)){aa=+g[a+36>>2];ca=+g[a+40>>2];ea=+g[a+44>>2];ba=+g[a+4>>2];da=+g[a+8>>2];u=+g[a+12>>2];g[V+12>>2]=0.0;v=+(e[r>>1]|0)/aa+ba;s=+(e[z>>1]|0)/ca+da;t=+(e[x>>1]|0)/ea+u;g[V+28>>2]=0.0;g[V>>2]=+(w&65535)/aa+ba-+g[m>>2];g[V+4>>2]=+(A&65535)/ca+da-+g[m+4>>2];g[V+8>>2]=+(y&65535)/ea+u-+g[m+8>>2];g[V+16>>2]=v-+g[l>>2];g[V+20>>2]=s-+g[l+4>>2];g[V+24>>2]=t-+g[l+8>>2];t=+g[f>>2];s=N*(+g[V+((N<0.0&1)<<4)>>2]-t);t=N*(+g[V+((N<0.0^1)<<4)>>2]-t);v=+g[f+4>>2];u=P*(+g[V+((P<0.0&1)<<4)+4>>2]-v);v=P*(+g[V+((P<0.0^1)<<4)+4>>2]-v);if(!(u>t|s>v)?(K=u>s?u:s,U=v>2],L=R*(+g[V+((R<0.0&1)<<4)+8>>2]-M),M=R*(+g[V+((R<0.0^1)<<4)+8>>2]-M),!(L>U|K>M)):0){r=(M0.0?(L>K?L:K)<(k-S)*(k-S)*J+((h-H)*(h-H)*J+(j-Q)*(j-Q)*J):0;if(!(C&r)){w=9;break}w=c[B>>2]|0;ic[c[(c[d>>2]|0)+8>>2]&127](d,w>>21,w&2097151);w=10;break}r=0;w=9}else{r=0;w=9}while(0);if((w|0)==9){w=0;if(C|r)w=10;else{C=c[B>>2]|0;p=p-C|0;q=q+(0-C<<4)|0}}if((w|0)==10){p=p+1|0;q=q+16|0}}while((p|0)<(n|0))}else o=0;if((c[6167]|0)>=(o|0)){i=V;return}c[6167]=o;i=V;return}function Ae(a,b,c,d){a=a|0;b=b|0;c=c|0;d=d|0;var e=0.0,f=0.0,h=0.0,i=0.0,j=0.0,k=0.0,l=0.0,m=0.0,n=0.0,o=0.0,p=0.0,q=0.0,r=0.0,s=0.0,t=0.0,u=0.0,v=0.0,w=0.0,x=0.0,y=0.0,z=0.0,A=0.0,B=0.0,C=0.0,D=0.0,E=0.0,F=0.0,G=0.0;Tg(a,b+(c*284|0)|0,d);m=+g[b+(c*284|0)+52>>2];h=+g[b+(c*284|0)+56>>2];q=+g[b+(c*284|0)+60>>2];G=+g[b+(c*284|0)+76>>2];x=+g[b+(c*284|0)+72>>2];z=+g[b+(c*284|0)+68>>2];w=1.0/+O(+((x*-m-z*-h)*(x*-m-z*-h)+((G*-h-x*-q)*(G*-h-x*-q)+(z*-q-G*-m)*(z*-q-G*-m))));v=(G*-h-x*-q)*w;u=w*(z*-q-G*-m);w=w*(x*-m-z*-h);e=+g[b+(c*284|0)+232>>2]*.5;k=+R(+e)/+O(+(m*m+h*h+q*q));e=+Q(+e);l=2.0/(e*e+(k*-q*k*-q+(k*-m*k*-m+k*-h*k*-h)));E=1.0-(k*-h*k*-h*l+k*-q*k*-q*l);D=k*-m*k*-h*l-e*k*-q*l;F=k*-m*k*-q*l+e*k*-h*l;B=k*-m*k*-h*l+e*k*-q*l;A=1.0-(k*-m*k*-m*l+k*-q*k*-q*l);C=k*-h*k*-q*l-e*k*-m*l;j=k*-m*k*-q*l-e*k*-h*l;e=k*-h*k*-q*l+e*k*-m*l;l=1.0-(k*-m*k*-m*l+k*-h*k*-h*l);k=+g[b+(c*284|0)+236>>2]*-.5;y=+R(+k)/+O(+(G*G+(x*x+z*z)));k=+Q(+k);r=2.0/(k*k+(G*y*G*y+(z*y*z*y+x*y*x*y)));n=1.0-(x*y*x*y*r+G*y*G*y*r);i=z*y*x*y*r-k*G*y*r;t=z*y*G*y*r+k*x*y*r;o=z*y*x*y*r+k*G*y*r;f=1.0-(z*y*z*y*r+G*y*G*y*r);s=x*y*G*y*r-k*z*y*r;p=z*y*G*y*r-k*x*y*r;k=x*y*G*y*r+k*z*y*r;r=1.0-(z*y*z*y*r+x*y*x*y*r);y=+g[b+(c*284|0)+68>>2];x=+g[b+(c*284|0)+72>>2];z=+g[b+(c*284|0)+76>>2];g[b+(c*284|0)+92>>2]=z*(E*t+D*s+F*r)+(y*(F*p+(D*o+E*n))+x*(F*k+(E*i+D*f)));g[b+(c*284|0)+96>>2]=w*(E*t+D*s+F*r)+(v*(F*p+(D*o+E*n))+u*(F*k+(E*i+D*f)));g[b+(c*284|0)+100>>2]=(E*t+D*s+F*r)*-q+((F*p+(D*o+E*n))*-m+(F*k+(E*i+D*f))*-h);g[b+(c*284|0)+104>>2]=0.0;g[b+(c*284|0)+108>>2]=z*(B*t+A*s+C*r)+(y*(C*p+(A*o+B*n))+x*(C*k+(B*i+A*f)));g[b+(c*284|0)+112>>2]=w*(B*t+A*s+C*r)+(v*(C*p+(A*o+B*n))+u*(C*k+(B*i+A*f)));g[b+(c*284|0)+116>>2]=(B*t+A*s+C*r)*-q+((C*p+(A*o+B*n))*-m+(C*k+(B*i+A*f))*-h);g[b+(c*284|0)+120>>2]=0.0;g[b+(c*284|0)+124>>2]=z*(j*t+e*s+l*r)+(y*(l*p+(e*o+j*n))+x*(l*k+(j*i+e*f)));g[b+(c*284|0)+128>>2]=w*(j*t+e*s+l*r)+(v*(l*p+(e*o+j*n))+u*(l*k+(j*i+e*f)));g[b+(c*284|0)+132>>2]=(j*t+e*s+l*r)*-q+((l*p+(e*o+j*n))*-m+(l*k+(j*i+e*f))*-h);g[b+(c*284|0)+136>>2]=0.0;h=+g[b+(c*284|0)+32>>2];f=h*+g[b+(c*284|0)+56>>2]+ +g[b+(c*284|0)+40>>2];e=h*+g[b+(c*284|0)+60>>2]+ +g[b+(c*284|0)+44>>2];g[b+(c*284|0)+140>>2]=+g[b+(c*284|0)+52>>2]*h+ +g[b+(c*284|0)+36>>2];g[b+(c*284|0)+144>>2]=f;g[b+(c*284|0)+148>>2]=e;g[b+(c*284|0)+152>>2]=0.0;return}function Be(b,d,e,f,h,j,k,l,m){b=b|0;d=d|0;e=e|0;f=f|0;h=h|0;j=+j;k=k|0;l=l|0;m=m|0;var n=0,o=0,p=0,q=0,r=0.0,s=0.0,t=0.0,u=0.0,v=0,w=0,x=0,y=0,z=0.0,A=0.0,B=0.0,C=0.0,D=0,E=0.0;D=i;i=i+32|0;if(!d){i=D;return}q=c[b+44>>2]|0;if((q|0)<128){if((c[b+48>>2]|0)<128){c[6435]=(c[6435]|0)+1;n=yc(531)|0;if(!n)p=0;else{c[(n+4+15&-16)+-4>>2]=n;p=n+4+15&-16}n=c[b+44>>2]|0;if((n|0)>0){o=0;do{c[p+(o<<2)>>2]=c[(c[b+52>>2]|0)+(o<<2)>>2];o=o+1|0}while((o|0)!=(n|0))}n=c[b+52>>2]|0;if(n|0){if(a[b+56>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[n+-4>>2]|0)}c[b+52>>2]=0}a[b+56>>0]=1;c[b+52>>2]=p;c[b+48>>2]=128;o=b+52|0}else o=b+52|0;n=q;do{c[(c[o>>2]|0)+(n<<2)>>2]=0;n=n+1|0}while((n|0)!=128);y=b+48|0}else{o=b+52|0;y=b+48|0}c[b+44>>2]=128;c[c[o>>2]>>2]=d;x=1;n=126;while(1){p=x+-1|0;q=c[o>>2]|0;w=c[q+(p<<2)>>2]|0;t=+g[w+4>>2]-+g[l+4>>2];r=+g[w+8>>2]-+g[l+8>>2];g[D>>2]=+g[w>>2]-+g[l>>2];g[D+4>>2]=t;g[D+8>>2]=r;g[D+12>>2]=0.0;r=+g[w+20>>2]-+g[k+4>>2];t=+g[w+24>>2]-+g[k+8>>2];g[D+16>>2]=+g[w+16>>2]-+g[k>>2];g[D+20>>2]=r;g[D+24>>2]=t;g[D+28>>2]=0.0;v=c[h>>2]|0;t=+g[e>>2];r=+g[f>>2];s=(+g[D+(v<<4)>>2]-t)*r;t=r*(+g[D+(1-v<<4)>>2]-t);v=c[h+4>>2]|0;r=+g[e+4>>2];E=+g[f+4>>2];u=(+g[D+(v<<4)+4>>2]-r)*E;r=E*(+g[D+(1-v<<4)+4>>2]-r);do if((!(u>t|s>r)?(z=u>s?u:s,C=r>2]|0,B=+g[e+8>>2],E=+g[f+8>>2],A=(+g[D+(v<<4)+8>>2]-B)*E,B=E*(+g[D+(1-v<<4)+8>>2]-B),!(A>C|z>B)):0)?((B0.0?(A>z?A:z)>2]|0)){Cb[c[(c[m>>2]|0)+12>>2]&127](m,w);break}if((p|0)>(n|0)){v=c[b+44>>2]|0;if((v|0)<(v<<1|0)){if((c[y>>2]|0)<(v<<1|0)){if(v){c[6435]=(c[6435]|0)+1;n=yc((v<<3|3)+16|0)|0;if(!n)n=0;else{c[(n+4+15&-16)+-4>>2]=n;n=n+4+15&-16}q=c[b+44>>2]|0;if((q|0)>0){d=0;do{c[n+(d<<2)>>2]=c[(c[o>>2]|0)+(d<<2)>>2];d=d+1|0}while((d|0)!=(q|0))}}else n=0;q=c[o>>2]|0;if(q|0){if(a[b+56>>0]|0){c[6436]=(c[6436]|0)+1;hd(c[q+-4>>2]|0)}c[o>>2]=0}a[b+56>>0]=1;c[o>>2]=n;c[y>>2]=v<<1;q=v}else{n=q;q=v}do{c[n+(q<<2)>>2]=0;q=q+1|0;n=c[o>>2]|0}while((q|0)!=(v<<1|0))}else n=q;c[b+44>>2]=v<<1;q=n;n=(v<<1)+-2|0}c[q+(p<<2)>>2]=c[w+36>>2];c[(c[o>>2]|0)+(x<<2)>>2]=c[w+40>>2];p=x+1|0}while(0);if(!p)break;else x=p}i=D;return}function Ce(b,d,e,f){b=b|0;d=d|0;e=e|0;f=f|0;var h=0,j=0,l=0,m=0,n=0,o=0,p=0.0,q=0.0,r=0.0,s=0.0,t=0,u=0,v=0,w=0,x=0,y=0.0,z=0,A=0,B=0,C=0,D=0,E=0.0;D=i;i=i+32|0;q=+g[d>>2];j=(g[k>>2]=q,c[k>>2]|0);t=q<999999984306749440.0?j:1566444395;p=+g[d+4>>2];m=(g[k>>2]=p,c[k>>2]|0);u=p<999999984306749440.0?m:1566444395;E=+g[d+8>>2];o=(g[k>>2]=E,c[k>>2]|0);w=E<999999984306749440.0?o:1566444395;s=+g[d+12>>2];y=s<0.0?s:0.0;j=q>-999999984306749440.0?j:-581039253;m=p>-999999984306749440.0?m:-581039253;o=E>-999999984306749440.0?o:-581039253;s=s>0.0?s:0.0;E=+g[d+16>>2];B=E<(c[k>>2]=t,+g[k>>2]);h=(g[k>>2]=E,c[k>>2]|0);t=B?h:t;p=+g[d+20>>2];B=p<(c[k>>2]=u,+g[k>>2]);l=(g[k>>2]=p,c[k>>2]|0);u=B?l:u;q=+g[d+24>>2];B=q<(c[k>>2]=w,+g[k>>2]);n=(g[k>>2]=q,c[k>>2]|0);w=B?n:w;r=+g[d+28>>2];y=r>2]=j,+g[k>>2])>2]=m,+g[k>>2])>2]=o,+g[k>>2])
- """ - return st.markdown(html, unsafe_allow_html=True) - -if query != "": - print(f"query: {query}") - matches = make_query(query, retriever, top_k=10) - - results = {} - order = [] - for context in matches: - video_id = context['metadata']['url'].split('/')[-1] - if video_id not in results: - results[video_id] = { - 'title': context['metadata']['title'], - 'urls': [f"{context['metadata']['url']}?t={int(context['metadata']['start'])}"], - 'contexts': [context['metadata']['text']], - 'starts': [int(context['metadata']['start'])], - 'ends': [int(context['metadata']['end'])] - } - order.append(video_id) - else: - results[video_id]['urls'].append( - f"{context['metadata']['url']}?t={int(context['metadata']['start'])}" - ) - results[video_id]['contexts'].append( - context['metadata']['text'] - ) - results[video_id]['starts'].append(int(context['metadata']['start'])) - results[video_id]['ends'].append(int(context['metadata']['end'])) - # now display cards - for video_id in order: - thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" - title = results[video_id]['title'] - urls = results[video_id]['urls'] - contexts = results[video_id]['contexts'] - starts = results[video_id]['starts'] - ends = results[video_id]['ends'] - card( - thumbnail=thumbnail, - title=title, - urls=urls, - contexts=contexts, - starts=starts, - ends=ends - ) \ No newline at end of file diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py deleted file mode 100644 index 3b10f4b2ac720e096db27b7e54dcc75611f92dfa..0000000000000000000000000000000000000000 --- a/spaces/Mountchicken/MAERec-Gradio/mmocr/evaluation/metrics/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -# Copyright (c) OpenMMLab. All rights reserved. -from .f_metric import F1Metric -from .hmean_iou_metric import HmeanIOUMetric -from .recog_metric import CharMetric, OneMinusNEDMetric, WordMetric - -__all__ = [ - 'WordMetric', 'CharMetric', 'OneMinusNEDMetric', 'HmeanIOUMetric', - 'F1Metric' -] diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py deleted file mode 100644 index 26edafb79869c840ec9362faef7a871759d15d3b..0000000000000000000000000000000000000000 --- a/spaces/Mountchicken/MAERec-Gradio/mmocr/models/textrecog/encoders/base.py +++ /dev/null @@ -1,12 +0,0 @@ -# Copyright (c) OpenMMLab. All rights reserved. -from mmengine.model import BaseModule - -from mmocr.registry import MODELS - - -@MODELS.register_module() -class BaseEncoder(BaseModule): - """Base Encoder class for text recognition.""" - - def forward(self, feat, **kwargs): - return feat diff --git a/spaces/MrBodean/VoiceClone/synthesizer/hparams.py b/spaces/MrBodean/VoiceClone/synthesizer/hparams.py deleted file mode 100644 index f7d38f0aa4c34d11349e40dbb9861b1aec2dcb8b..0000000000000000000000000000000000000000 --- a/spaces/MrBodean/VoiceClone/synthesizer/hparams.py +++ /dev/null @@ -1,92 +0,0 @@ -import ast -import pprint - -class HParams(object): - def __init__(self, **kwargs): self.__dict__.update(kwargs) - def __setitem__(self, key, value): setattr(self, key, value) - def __getitem__(self, key): return getattr(self, key) - def __repr__(self): return pprint.pformat(self.__dict__) - - def parse(self, string): - # Overrides hparams from a comma-separated string of name=value pairs - if len(string) > 0: - overrides = [s.split("=") for s in string.split(",")] - keys, values = zip(*overrides) - keys = list(map(str.strip, keys)) - values = list(map(str.strip, values)) - for k in keys: - self.__dict__[k] = ast.literal_eval(values[keys.index(k)]) - return self - -hparams = HParams( - ### Signal Processing (used in both synthesizer and vocoder) - sample_rate = 16000, - n_fft = 800, - num_mels = 80, - hop_size = 200, # Tacotron uses 12.5 ms frame shift (set to sample_rate * 0.0125) - win_size = 800, # Tacotron uses 50 ms frame length (set to sample_rate * 0.050) - fmin = 55, - min_level_db = -100, - ref_level_db = 20, - max_abs_value = 4., # Gradient explodes if too big, premature convergence if too small. - preemphasis = 0.97, # Filter coefficient to use if preemphasize is True - preemphasize = True, - - ### Tacotron Text-to-Speech (TTS) - tts_embed_dims = 512, # Embedding dimension for the graphemes/phoneme inputs - tts_encoder_dims = 256, - tts_decoder_dims = 128, - tts_postnet_dims = 512, - tts_encoder_K = 5, - tts_lstm_dims = 1024, - tts_postnet_K = 5, - tts_num_highways = 4, - tts_dropout = 0.5, - tts_cleaner_names = ["english_cleaners"], - tts_stop_threshold = -3.4, # Value below which audio generation ends. - # For example, for a range of [-4, 4], this - # will terminate the sequence at the first - # frame that has all values < -3.4 - - ### Tacotron Training - tts_schedule = [(2, 1e-3, 20_000, 12), # Progressive training schedule - (2, 5e-4, 40_000, 12), # (r, lr, step, batch_size) - (2, 2e-4, 80_000, 12), # - (2, 1e-4, 160_000, 12), # r = reduction factor (# of mel frames - (2, 3e-5, 320_000, 12), # synthesized for each decoder iteration) - (2, 1e-5, 640_000, 12)], # lr = learning rate - - tts_clip_grad_norm = 1.0, # clips the gradient norm to prevent explosion - set to None if not needed - tts_eval_interval = 500, # Number of steps between model evaluation (sample generation) - # Set to -1 to generate after completing epoch, or 0 to disable - - tts_eval_num_samples = 1, # Makes this number of samples - - ### Data Preprocessing - max_mel_frames = 900, - rescale = True, - rescaling_max = 0.9, - synthesis_batch_size = 16, # For vocoder preprocessing and inference. - - ### Mel Visualization and Griffin-Lim - signal_normalization = True, - power = 1.5, - griffin_lim_iters = 60, - - ### Audio processing options - fmax = 7600, # Should not exceed (sample_rate // 2) - allow_clipping_in_normalization = True, # Used when signal_normalization = True - clip_mels_length = True, # If true, discards samples exceeding max_mel_frames - use_lws = False, # "Fast spectrogram phase recovery using local weighted sums" - symmetric_mels = True, # Sets mel range to [-max_abs_value, max_abs_value] if True, - # and [0, max_abs_value] if False - trim_silence = True, # Use with sample_rate of 16000 for best results - - ### SV2TTS - speaker_embedding_size = 256, # Dimension for the speaker embedding - silence_min_duration_split = 0.4, # Duration in seconds of a silence for an utterance to be split - utterance_min_duration = 1.6, # Duration in seconds below which utterances are discarded - ) - -def hparams_debug_string(): - return str(hparams) diff --git a/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py b/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py deleted file mode 100644 index 2c98d880d6b0b76ddb21f1bd516c4ce90515b8f3..0000000000000000000000000000000000000000 --- a/spaces/NAACL2022/CLIP-Caption-Reward/scripts/prepro_feats.py +++ /dev/null @@ -1,103 +0,0 @@ -""" -Preprocess a raw json dataset into features files for use in data_loader.py - -Input: json file that has the form -[{ file_path: 'path/img.jpg', captions: ['a caption', ...] }, ...] -example element in this list would look like -{'captions': [u'A man with a red helmet on a small moped on a dirt road. ', u'Man riding a motor bike on a dirt road on the countryside.', u'A man riding on the back of a motorcycle.', u'A dirt path with a young person on a motor bike rests to the foreground of a verdant area with a bridge and a background of cloud-wreathed mountains. ', u'A man in a red shirt and a red hat is on a motorcycle on a hill side.'], 'file_path': u'val2014/COCO_val2014_000000391895.jpg', 'id': 391895} - -This script reads this json, does some basic preprocessing on the captions -(e.g. lowercase, etc.), creates a special UNK token, and encodes everything to arrays - -Output: two folders of features -""" - -from __future__ import absolute_import -from __future__ import division -from __future__ import print_function - -import os -import json -import argparse -from random import shuffle, seed -import string -# non-standard dependencies: -import h5py -from six.moves import cPickle -import numpy as np -import torch -import torchvision.models as models -import skimage.io - -from torchvision import transforms as trn -preprocess = trn.Compose([ - #trn.ToTensor(), - trn.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) -]) - -from captioning.utils.resnet_utils import myResnet -import captioning.utils.resnet as resnet - - -def main(params): - net = getattr(resnet, params['model'])() - net.load_state_dict(torch.load(os.path.join(params['model_root'],params['model']+'.pth'))) - my_resnet = myResnet(net) - my_resnet.cuda() - my_resnet.eval() - - imgs = json.load(open(params['input_json'], 'r')) - imgs = imgs['images'] - N = len(imgs) - - seed(123) # make reproducible - - dir_fc = params['output_dir']+'_fc' - dir_att = params['output_dir']+'_att' - if not os.path.isdir(dir_fc): - os.mkdir(dir_fc) - if not os.path.isdir(dir_att): - os.mkdir(dir_att) - - for i,img in enumerate(imgs): - # load the image - I = skimage.io.imread(os.path.join(params['images_root'], img['filepath'], img['filename'])) - # handle grayscale input images - if len(I.shape) == 2: - I = I[:,:,np.newaxis] - I = np.concatenate((I,I,I), axis=2) - - I = I.astype('float32')/255.0 - I = torch.from_numpy(I.transpose([2,0,1])).cuda() - I = preprocess(I) - with torch.no_grad(): - tmp_fc, tmp_att = my_resnet(I, params['att_size']) - # write to pkl - # print(dir_fc, str(img['cocoid']), tmp_fc.shape, tmp_att.shape, dir_att) - # exit() - np.save(os.path.join(dir_fc, str(img['cocoid'])), tmp_fc.data.cpu().float().numpy()) - np.savez_compressed(os.path.join(dir_att, str(img['cocoid'])), feat=tmp_att.data.cpu().float().numpy()) - - if i % 1000 == 0: - print('processing %d/%d (%.2f%% done)' % (i, N, i*100.0/N)) - print('wrote ', params['output_dir']) - -if __name__ == "__main__": - - parser = argparse.ArgumentParser() - - # input json - parser.add_argument('--input_json', required=True, help='input json file to process into hdf5') - parser.add_argument('--output_dir', default='data', help='output h5 file') - - # options - parser.add_argument('--images_root', default='', help='root location in which images are stored, to be prepended to file_path in input json') - parser.add_argument('--att_size', default=14, type=int, help='14x14 or 7x7') - parser.add_argument('--model', default='resnet101', type=str, help='resnet101, resnet152') - parser.add_argument('--model_root', default='./data/imagenet_weights', type=str, help='model root') - - args = parser.parse_args() - params = vars(args) # convert to ordinary dict - print('parsed input parameters:') - print(json.dumps(params, indent = 2)) - main(params) diff --git a/spaces/NCTCMumbai/NCTC/models/research/cognitive_mapping_and_planning/render/__init__.py b/spaces/NCTCMumbai/NCTC/models/research/cognitive_mapping_and_planning/render/__init__.py deleted file mode 100644 index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000 diff --git a/spaces/NeuralInternet/Text-Generation_Playground/download-model.py b/spaces/NeuralInternet/Text-Generation_Playground/download-model.py deleted file mode 100644 index 8be398c4e0d3ca0c0a915efb442f432fc2056834..0000000000000000000000000000000000000000 --- a/spaces/NeuralInternet/Text-Generation_Playground/download-model.py +++ /dev/null @@ -1,176 +0,0 @@ -''' -Downloads models from Hugging Face to models/model-name. - -Example: -python download-model.py facebook/opt-1.3b - -''' - -import argparse -import base64 -import json -import multiprocessing -import re -import sys -from pathlib import Path - -import requests -import tqdm - -parser = argparse.ArgumentParser() -parser.add_argument('MODEL', type=str, default=None, nargs='?') -parser.add_argument('--branch', type=str, default='main', help='Name of the Git branch to download from.') -parser.add_argument('--threads', type=int, default=1, help='Number of files to download simultaneously.') -parser.add_argument('--text-only', action='store_true', help='Only download text files (txt/json).') -args = parser.parse_args() - -def get_file(args): - url = args[0] - output_folder = args[1] - idx = args[2] - tot = args[3] - - print(f"Downloading file {idx} of {tot}...") - r = requests.get(url, stream=True) - with open(output_folder / Path(url.split('/')[-1]), 'wb') as f: - total_size = int(r.headers.get('content-length', 0)) - block_size = 1024 - t = tqdm.tqdm(total=total_size, unit='iB', unit_scale=True) - for data in r.iter_content(block_size): - t.update(len(data)) - f.write(data) - t.close() - -def sanitize_branch_name(branch_name): - pattern = re.compile(r"^[a-zA-Z0-9._-]+$") - if pattern.match(branch_name): - return branch_name - else: - raise ValueError("Invalid branch name. Only alphanumeric characters, period, underscore and dash are allowed.") - -def select_model_from_default_options(): - models = { - "Pygmalion 6B original": ("PygmalionAI", "pygmalion-6b", "b8344bb4eb76a437797ad3b19420a13922aaabe1"), - "Pygmalion 6B main": ("PygmalionAI", "pygmalion-6b", "main"), - "Pygmalion 6B dev": ("PygmalionAI", "pygmalion-6b", "dev"), - "Pygmalion 2.7B": ("PygmalionAI", "pygmalion-2.7b", "main"), - "Pygmalion 1.3B": ("PygmalionAI", "pygmalion-1.3b", "main"), - "Pygmalion 350m": ("PygmalionAI", "pygmalion-350m", "main"), - "OPT 6.7b": ("facebook", "opt-6.7b", "main"), - "OPT 2.7b": ("facebook", "opt-2.7b", "main"), - "OPT 1.3b": ("facebook", "opt-1.3b", "main"), - "OPT 350m": ("facebook", "opt-350m", "main"), - } - choices = {} - - print("Select the model that you want to download:\n") - for i,name in enumerate(models): - char = chr(ord('A')+i) - choices[char] = name - print(f"{char}) {name}") - char = chr(ord('A')+len(models)) - print(f"{char}) None of the above") - - print() - print("Input> ", end='') - choice = input()[0].strip().upper() - if choice == char: - print("""\nThen type the name of your desired Hugging Face model in the format organization/name. - -Examples: -PygmalionAI/pygmalion-6b -facebook/opt-1.3b -""") - - print("Input> ", end='') - model = input() - branch = "main" - else: - arr = models[choices[choice]] - model = f"{arr[0]}/{arr[1]}" - branch = arr[2] - - return model, branch - -def get_download_links_from_huggingface(model, branch): - base = "https://huggingface.co" - page = f"/api/models/{model}/tree/{branch}?cursor=" - cursor = b"" - - links = [] - classifications = [] - has_pytorch = False - has_safetensors = False - while True: - content = requests.get(f"{base}{page}{cursor.decode()}").content - - dict = json.loads(content) - if len(dict) == 0: - break - - for i in range(len(dict)): - fname = dict[i]['path'] - - is_pytorch = re.match("pytorch_model.*\.bin", fname) - is_safetensors = re.match("model.*\.safetensors", fname) - is_tokenizer = re.match("tokenizer.*\.model", fname) - is_text = re.match(".*\.(txt|json)", fname) or is_tokenizer - - if any((is_pytorch, is_safetensors, is_text, is_tokenizer)): - if is_text: - links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}") - classifications.append('text') - continue - if not args.text_only: - links.append(f"https://huggingface.co/{model}/resolve/{branch}/{fname}") - if is_safetensors: - has_safetensors = True - classifications.append('safetensors') - elif is_pytorch: - has_pytorch = True - classifications.append('pytorch') - - cursor = base64.b64encode(f'{{"file_name":"{dict[-1]["path"]}"}}'.encode()) + b':50' - cursor = base64.b64encode(cursor) - cursor = cursor.replace(b'=', b'%3D') - - # If both pytorch and safetensors are available, download safetensors only - if has_pytorch and has_safetensors: - for i in range(len(classifications)-1, -1, -1): - if classifications[i] == 'pytorch': - links.pop(i) - - return links - -if __name__ == '__main__': - model = args.MODEL - branch = args.branch - if model is None: - model, branch = select_model_from_default_options() - else: - if model[-1] == '/': - model = model[:-1] - branch = args.branch - if branch is None: - branch = "main" - else: - try: - branch = sanitize_branch_name(branch) - except ValueError as err_branch: - print(f"Error: {err_branch}") - sys.exit() - if branch != 'main': - output_folder = Path("models") / (model.split('/')[-1] + f'_{branch}') - else: - output_folder = Path("models") / model.split('/')[-1] - if not output_folder.exists(): - output_folder.mkdir() - - links = get_download_links_from_huggingface(model, branch) - - # Downloading the files - print(f"Downloading the model to {output_folder}") - pool = multiprocessing.Pool(processes=args.threads) - results = pool.map(get_file, [[links[i], output_folder, i+1, len(links)] for i in range(len(links))]) - pool.close() - pool.join() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py deleted file mode 100644 index 7e2caa03400129ac0bb34ae35274cdf46f27a055..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import torch -from fairseq import utils -from fairseq.modules import TransformerEncoderLayer - -from .multihead_linear_attention import MultiheadLinearAttention - - -class LinformerTransformerEncoderLayer(TransformerEncoderLayer): - """ - Implements a Linformer Encoder Layer used in BERT/XLM style pre-trained - models. - """ - - def __init__(self, args, shared_compress_layer): - # wrap in a list so it's not automatically registered by PyTorch - self.shared_compress_layer = [shared_compress_layer] - - super().__init__(args) - - self.register_buffer("version", torch.tensor(2)) - - def build_self_attention(self, embed_dim, args): - return MultiheadLinearAttention( - embed_dim, - args.encoder_attention_heads, - dropout=args.dropout, - self_attention=True, - q_noise=args.quant_noise_pq, - qn_block_size=args.quant_noise_pq_block_size, - compressed=args.compressed, - max_seq_len=args.max_positions, - shared_kv_compressed=args.shared_kv_compressed, - shared_compress_layer=self.shared_compress_layer[0], - freeze_compress=args.freeze_compress, - ) - - def upgrade_state_dict_named(self, state_dict, name): - super().upgrade_state_dict_named(state_dict, name) - prefix = name + "." if name != "" else "" - - # some old checkpoints had weight sharing implemented incorrectly - # (note: this was correct in the original paper code) - if utils.item(state_dict.get(f"{prefix}version", torch.tensor(1))) < 2: - state_dict[f"{prefix}version"] = torch.tensor(1) - # check compression layer sharing - if f"{prefix}shared_compress_layer.weight" in state_dict: - # reinitialize block without sharing compression layer to match - # old behavior - self.shared_compress_layer = [ - torch.nn.Linear( - self.shared_compress_layer[0].weight.size(1), - self.shared_compress_layer[0].weight.size(0), - ) - ] - self.self_attn = self.build_self_attention(self.embed_dim, self.args) - # delete shared_compress_layer, since it's already copied to - # self_attn.compress_k.weight - del state_dict[f"{prefix}shared_compress_layer.weight"] - if f"{prefix}shared_compress_layer.bias" in state_dict: - del state_dict[f"{prefix}shared_compress_layer.bias"] diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py deleted file mode 100644 index 43fe0451bf4d5762d734314075b1402c2a8db2bb..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/roberta/multiprocessing_bpe_encoder.py +++ /dev/null @@ -1,130 +0,0 @@ -#!/usr/bin/env python -# Copyright (c) Facebook, Inc. and its affiliates. -# All rights reserved. -# -# This source code is licensed under the license found in the -# LICENSE file in the root directory of this source tree. - -import argparse -import contextlib -import sys -from collections import Counter -from multiprocessing import Pool - -from fairseq.data.encoders.gpt2_bpe import get_encoder - - -def main(): - """ - Helper script to encode raw text with the GPT-2 BPE using multiple processes. - - The encoder.json and vocab.bpe files can be obtained here: - - https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/encoder.json - - https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/vocab.bpe - """ - parser = argparse.ArgumentParser() - parser.add_argument( - "--encoder-json", - help="path to encoder.json", - ) - parser.add_argument( - "--vocab-bpe", - type=str, - help="path to vocab.bpe", - ) - parser.add_argument( - "--inputs", - nargs="+", - default=["-"], - help="input files to filter/encode", - ) - parser.add_argument( - "--outputs", - nargs="+", - default=["-"], - help="path to save encoded outputs", - ) - parser.add_argument( - "--keep-empty", - action="store_true", - help="keep empty lines", - ) - parser.add_argument("--workers", type=int, default=20) - args = parser.parse_args() - - assert len(args.inputs) == len( - args.outputs - ), "number of input and output paths should match" - - with contextlib.ExitStack() as stack: - inputs = [ - stack.enter_context(open(input, "r", encoding="utf-8")) - if input != "-" - else sys.stdin - for input in args.inputs - ] - outputs = [ - stack.enter_context(open(output, "w", encoding="utf-8")) - if output != "-" - else sys.stdout - for output in args.outputs - ] - - encoder = MultiprocessingEncoder(args) - pool = Pool(args.workers, initializer=encoder.initializer) - encoded_lines = pool.imap(encoder.encode_lines, zip(*inputs), 100) - - stats = Counter() - for i, (filt, enc_lines) in enumerate(encoded_lines, start=1): - if filt == "PASS": - for enc_line, output_h in zip(enc_lines, outputs): - print(enc_line, file=output_h) - else: - stats["num_filtered_" + filt] += 1 - if i % 10000 == 0: - print("processed {} lines".format(i), file=sys.stderr) - - for k, v in stats.most_common(): - print("[{}] filtered {} lines".format(k, v), file=sys.stderr) - - -class MultiprocessingEncoder(object): - def __init__(self, args): - self.args = args - - def initializer(self): - global bpe - bpe = get_encoder(self.args.encoder_json, self.args.vocab_bpe) - - def encode(self, line): - global bpe - ids = bpe.encode(line) - return list(map(str, ids)) - - def decode(self, tokens): - global bpe - return bpe.decode(tokens) - - def encode_lines(self, lines): - """ - Encode a set of lines. All lines will be encoded together. - """ - enc_lines = [] - for line in lines: - line = line.strip() - if len(line) == 0 and not self.args.keep_empty: - return ["EMPTY", None] - tokens = self.encode(line) - enc_lines.append(" ".join(tokens)) - return ["PASS", enc_lines] - - def decode_lines(self, lines): - dec_lines = [] - for line in lines: - tokens = map(int, line.strip().split()) - dec_lines.append(self.decode(tokens)) - return ["PASS", dec_lines] - - -if __name__ == "__main__": - main() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py deleted file mode 100644 index 257a96593ff7af93c206c066d8db4ad795b2ae36..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/simultaneous_translation/models/__init__.py +++ /dev/null @@ -1,15 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import importlib -import os - - -for file in sorted(os.listdir(os.path.dirname(__file__))): - if file.endswith(".py") and not file.startswith("_"): - model_name = file[: file.find(".py")] - importlib.import_module( - "examples.simultaneous_translation.models." + model_name - ) diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py deleted file mode 100644 index 7ec1fb7521b8a9b821d28bcaaaedb034f6e95e0b..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_synthesis/preprocessing/get_ljspeech_audio_manifest.py +++ /dev/null @@ -1,70 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. - -import argparse -import logging -from pathlib import Path -from collections import defaultdict - -import pandas as pd -from torchaudio.datasets import LJSPEECH -from tqdm import tqdm - -from examples.speech_to_text.data_utils import save_df_to_tsv - - -log = logging.getLogger(__name__) - -SPLITS = ["train", "dev", "test"] - - -def process(args): - out_root = Path(args.output_data_root).absolute() - out_root.mkdir(parents=True, exist_ok=True) - - # Generate TSV manifest - print("Generating manifest...") - # following FastSpeech's splits - dataset = LJSPEECH(out_root.as_posix(), download=True) - id_to_split = {} - for x in dataset._flist: - id_ = x[0] - speaker = id_.split("-")[0] - id_to_split[id_] = { - "LJ001": "test", "LJ002": "test", "LJ003": "dev" - }.get(speaker, "train") - manifest_by_split = {split: defaultdict(list) for split in SPLITS} - progress = tqdm(enumerate(dataset), total=len(dataset)) - for i, (waveform, _, utt, normalized_utt) in progress: - sample_id = dataset._flist[i][0] - split = id_to_split[sample_id] - manifest_by_split[split]["id"].append(sample_id) - audio_path = f"{dataset._path}/{sample_id}.wav" - manifest_by_split[split]["audio"].append(audio_path) - manifest_by_split[split]["n_frames"].append(len(waveform[0])) - manifest_by_split[split]["tgt_text"].append(normalized_utt) - manifest_by_split[split]["speaker"].append("ljspeech") - manifest_by_split[split]["src_text"].append(utt) - - manifest_root = Path(args.output_manifest_root).absolute() - manifest_root.mkdir(parents=True, exist_ok=True) - for split in SPLITS: - save_df_to_tsv( - pd.DataFrame.from_dict(manifest_by_split[split]), - manifest_root / f"{split}.audio.tsv" - ) - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument("--output-data-root", "-d", required=True, type=str) - parser.add_argument("--output-manifest-root", "-m", required=True, type=str) - args = parser.parse_args() - - process(args) - - -if __name__ == "__main__": - main() diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md deleted file mode 100644 index 920ff271c2e178c7a4ca3c7c8ce57a2f28653969..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md +++ /dev/null @@ -1,76 +0,0 @@ -[[Back]](..) - -# Joint Speech Text Training for the 2021 IWSLT multilingual speech translation - -This directory contains the code from paper ["FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task"](https://arxiv.org/pdf/2107.06959.pdf). - -## Prepare Data -#### Download files -- Sentence piece model [spm.model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/spm.model) -- Dictionary [tgt_dict.txt](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/dict.txt) -- Config [config.yaml](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/config.yaml) - -#### Prepare -- [Please follow the data preparation in speech-to-text](https://github.com/pytorch/fairseq/blob/main/examples/speech_to_text/docs/mtedx_example.md) - - - -## Training - -#### Download pretrained models -- [Pretrained mbart model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/mbart.pt) -- [Pretrained w2v model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/xlsr_53_56k.pt) - - -#### Training scripts - -```bash -python train.py ${MANIFEST_ROOT} \ - --save-dir ${save_dir} \ - --user-dir examples/speech_text_joint_to_text \ - --train-subset train_es_en_tedx,train_es_es_tedx,train_fr_en_tedx,train_fr_es_tedx,train_fr_fr_tedx,train_it_it_tedx,train_pt_en_tedx,train_pt_pt_tedx \ - --valid-subset valid_es_en_tedx,valid_es_es_tedx,valid_es_fr_tedx,valid_es_it_tedx,valid_es_pt_tedx,valid_fr_en_tedx,valid_fr_es_tedx,valid_fr_fr_tedx,valid_fr_pt_tedx,valid_it_en_tedx,valid_it_es_tedx,valid_it_it_tedx,valid_pt_en_tedx,valid_pt_es_tedx,valid_pt_pt_tedx \ - --config-yaml config.yaml --ddp-backend no_c10d \ - --num-workers 2 --task speech_text_joint_to_text \ - --criterion guided_label_smoothed_cross_entropy_with_accuracy \ - --label-smoothing 0.3 --guide-alpha 0.8 \ - --disable-text-guide-update-num 5000 --arch dualinputxmtransformer_base \ - --max-tokens 500000 --max-sentences 3 --max-tokens-valid 800000 \ - --max-source-positions 800000 --enc-grad-mult 2.0 \ - --attentive-cost-regularization 0.02 --optimizer adam \ - --clip-norm 1.0 --log-format simple --log-interval 200 \ - --keep-last-epochs 5 --seed 1 \ - --w2v-path ${w2v_path} \ - --load-pretrained-mbart-from ${mbart_path} \ - --max-update 1000000 --update-freq 4 \ - --skip-invalid-size-inputs-valid-test \ - --skip-encoder-projection --save-interval 1 \ - --attention-dropout 0.3 --mbart-dropout 0.3 \ - --finetune-w2v-params all --finetune-mbart-decoder-params all \ - --finetune-mbart-encoder-params all --stack-w2v-mbart-encoder \ - --drop-w2v-layers 12 --normalize \ - --lr 5e-05 --lr-scheduler inverse_sqrt --warmup-updates 5000 -``` - -## Evaluation -```bash -python ./fairseq_cli/generate.py - ${MANIFEST_ROOT} \ - --task speech_text_joint_to_text \ - --user-dir ./examples/speech_text_joint_to_text \ - --load-speech-only --gen-subset test_es_en_tedx \ - --path ${model} \ - --max-source-positions 800000 \ - --skip-invalid-size-inputs-valid-test \ - --config-yaml config.yaml \ - --infer-target-lang en \ - --max-tokens 800000 \ - --beam 5 \ - --results-path ${RESULTS_DIR} \ - --scoring sacrebleu -``` -The trained model can be downloaded [here](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/checkpoint17.pt) - -|direction|es_en|fr_en|pt_en|it_en|fr_es|pt_es|it_es|es_es|fr_fr|pt_pt|it_it| -|---|---|---|---|---|---|---|---|---|---|---|---| -|BLEU|31.62|36.93|35.07|27.12|38.87|35.57|34.13|74.59|74.64|70.84|69.76| diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py deleted file mode 100644 index 6bbd0ae821b42ab693f4141e7c161d6d7cb0b15a..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/audio/feature_transforms/utterance_cmvn.py +++ /dev/null @@ -1,40 +0,0 @@ -import numpy as np -from fairseq.data.audio.feature_transforms import ( - AudioFeatureTransform, - register_audio_feature_transform, -) - - -@register_audio_feature_transform("utterance_cmvn") -class UtteranceCMVN(AudioFeatureTransform): - """Utterance-level CMVN (cepstral mean and variance normalization)""" - - @classmethod - def from_config_dict(cls, config=None): - _config = {} if config is None else config - return UtteranceCMVN( - _config.get("norm_means", True), - _config.get("norm_vars", True), - ) - - def __init__(self, norm_means=True, norm_vars=True): - self.norm_means, self.norm_vars = norm_means, norm_vars - - def __repr__(self): - return ( - self.__class__.__name__ - + f"(norm_means={self.norm_means}, norm_vars={self.norm_vars})" - ) - - def __call__(self, x): - mean = x.mean(axis=0) - square_sums = (x ** 2).sum(axis=0) - - if self.norm_means: - x = np.subtract(x, mean) - if self.norm_vars: - var = square_sums / x.shape[0] - mean ** 2 - std = np.sqrt(np.maximum(var, 1e-10)) - x = np.divide(x, std) - - return x diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py deleted file mode 100644 index 71d0b27cd2c0655fe3b00479b672d6d042a4d5ed..0000000000000000000000000000000000000000 --- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/models/bart/model.py +++ /dev/null @@ -1,384 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -# -# This source code is licensed under the MIT license found in the -# LICENSE file in the root directory of this source tree. -""" -BART: Denoising Sequence-to-Sequence Pre-training for -Natural Language Generation, Translation, and Comprehension -""" -from typing import Optional - -import logging - -import torch -import torch.nn as nn -from fairseq import utils -from fairseq.models import register_model, register_model_architecture -from fairseq.models.transformer import TransformerModel -from fairseq.modules.transformer_sentence_encoder import init_bert_params - -from .hub_interface import BARTHubInterface - - -logger = logging.getLogger(__name__) - - -@register_model("bart") -class BARTModel(TransformerModel): - __jit_unused_properties__ = ["supported_targets"] - - @classmethod - def hub_models(cls): - return { - "bart.base": "http://dl.fbaipublicfiles.com/fairseq/models/bart.base.tar.gz", - "bart.large": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.tar.gz", - "bart.large.mnli": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.mnli.tar.gz", - "bart.large.cnn": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.cnn.tar.gz", - "bart.large.xsum": "http://dl.fbaipublicfiles.com/fairseq/models/bart.large.xsum.tar.gz", - } - - def __init__(self, args, encoder, decoder): - super().__init__(args, encoder, decoder) - - # We follow BERT's random weight initialization - self.apply(init_bert_params) - - self.classification_heads = nn.ModuleDict() - if hasattr(self.encoder, "dictionary"): - self.eos: int = self.encoder.dictionary.eos() - - @staticmethod - def add_args(parser): - super(BARTModel, BARTModel).add_args(parser) - parser.add_argument( - "--pooler-dropout", - type=float, - metavar="D", - help="dropout probability in the masked_lm pooler layers", - ) - parser.add_argument( - "--pooler-activation-fn", - choices=utils.get_available_activation_fns(), - help="activation function to use for pooler layer", - ) - parser.add_argument( - "--spectral-norm-classification-head", - action="store_true", - help="Apply spectral normalization on the classification head", - ) - - @property - def supported_targets(self): - return {"self"} - - def forward( - self, - src_tokens, - src_lengths, - prev_output_tokens, - features_only: bool = False, - classification_head_name: Optional[str] = None, - token_embeddings: Optional[torch.Tensor] = None, - return_all_hiddens: bool = True, - alignment_layer: Optional[int] = None, - alignment_heads: Optional[int] = None, - ): - if classification_head_name is not None: - features_only = True - - encoder_out = self.encoder( - src_tokens, - src_lengths=src_lengths, - token_embeddings=token_embeddings, - return_all_hiddens=return_all_hiddens - ) - x, extra = self.decoder( - prev_output_tokens, - encoder_out=encoder_out, - features_only=features_only, - alignment_layer=alignment_layer, - alignment_heads=alignment_heads, - src_lengths=src_lengths, - return_all_hiddens=return_all_hiddens, - ) - eos: int = self.eos - if classification_head_name is not None: - sentence_representation = x[ - src_tokens.eq(eos), : - ].view(x.size(0), -1, x.size(-1))[:, -1, :] - for k, head in self.classification_heads.items(): - # for torch script only supports iteration - if k == classification_head_name: - x = head(sentence_representation) - break - return x, extra - - @classmethod - def from_pretrained( - cls, - model_name_or_path, - checkpoint_file="model.pt", - data_name_or_path=".", - bpe="gpt2", - sample_break_mode="eos", - **kwargs, - ): - from fairseq import hub_utils - - x = hub_utils.from_pretrained( - model_name_or_path, - checkpoint_file, - data_name_or_path, - archive_map=cls.hub_models(), - bpe=bpe, - load_checkpoint_heads=True, - sample_break_mode=sample_break_mode, - **kwargs, - ) - return BARTHubInterface(x["args"], x["task"], x["models"][0]) - - def register_classification_head( - self, name, num_classes=None, inner_dim=None, **kwargs - ): - """Register a classification head.""" - logger.info("Registering classification head: {0}".format(name)) - if name in self.classification_heads: - prev_num_classes = self.classification_heads[name].out_proj.out_features - prev_inner_dim = self.classification_heads[name].dense.out_features - if num_classes != prev_num_classes or inner_dim != prev_inner_dim: - logger.warning( - 're-registering head "{}" with num_classes {} (prev: {}) ' - "and inner_dim {} (prev: {})".format( - name, num_classes, prev_num_classes, inner_dim, prev_inner_dim - ) - ) - self.classification_heads[name] = BARTClassificationHead( - input_dim=self.args.encoder_embed_dim, - inner_dim=inner_dim or self.args.encoder_embed_dim, - num_classes=num_classes, - activation_fn=self.args.pooler_activation_fn, - pooler_dropout=self.args.pooler_dropout, - do_spectral_norm=getattr( - self.args, "spectral_norm_classification_head", False - ), - ) - - def upgrade_state_dict_named(self, state_dict, name): - super().upgrade_state_dict_named(state_dict, name) - - prefix = name + "." if name != "" else "" - current_head_names = ( - [] - if not hasattr(self, "classification_heads") - else self.classification_heads.keys() - ) - - # Handle new classification heads present in the state dict. - keys_to_delete = [] - for k in state_dict.keys(): - if not k.startswith(prefix + "classification_heads."): - continue - - head_name = k[len(prefix + "classification_heads.") :].split(".")[0] - num_classes = state_dict[ - prefix + "classification_heads." + head_name + ".out_proj.weight" - ].size(0) - inner_dim = state_dict[ - prefix + "classification_heads." + head_name + ".dense.weight" - ].size(0) - - if getattr(self.args, "load_checkpoint_heads", False): - if head_name not in current_head_names: - self.register_classification_head(head_name, num_classes, inner_dim) - else: - if head_name not in current_head_names: - logger.warning( - "deleting classification head ({}) from checkpoint " - "not present in current model: {}".format(head_name, k) - ) - keys_to_delete.append(k) - elif ( - num_classes - != self.classification_heads[head_name].out_proj.out_features - or inner_dim - != self.classification_heads[head_name].dense.out_features - ): - logger.warning( - "deleting classification head ({}) from checkpoint " - "with different dimensions than current model: {}".format( - head_name, k - ) - ) - keys_to_delete.append(k) - for k in keys_to_delete: - del state_dict[k] - - def truncate_emb(key): - if key in state_dict: - state_dict[key] = state_dict[key][:-1, :] - - # When finetuning on translation task, remove last row of - # embedding matrix that corresponds to mask_idx token. - loaded_dict_size = state_dict["encoder.embed_tokens.weight"].size(0) - if ( - loaded_dict_size == len(self.encoder.dictionary) + 1 - and "
- 你已达到每日最大发送消息次数，请更换账号或隔一天后重试
-
- )
- }
- if (error.code === ErrorCode.BING_IP_FORBIDDEN) {
- return (
-
- 当前话题已中止，请点
- 重新开始
- 开启新的对话
-
- )
- }
- if (error.code === ErrorCode.BING_CAPTCHA) {
- return (
-
-
- )
-}
diff --git a/spaces/Pluviophile/vits-uma-genshin-honkai/text/cleaners.py b/spaces/Pluviophile/vits-uma-genshin-honkai/text/cleaners.py
deleted file mode 100644
index d26581deb399609163518054718ad80ecca5d934..0000000000000000000000000000000000000000
--- a/spaces/Pluviophile/vits-uma-genshin-honkai/text/cleaners.py
+++ /dev/null
@@ -1,475 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-
-'''
-Cleaners are transformations that run over the input text at both training and eval time.
-
-Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
-hyperparameter. Some cleaners are English-specific. You'll typically want to use:
- 1. "english_cleaners" for English text
- 2. "transliteration_cleaners" for non-English text that can be transliterated to ASCII using
- the Unidecode library (https://pypi.python.org/pypi/Unidecode)
- 3. "basic_cleaners" if you do not want to transliterate (in this case, you should also update
- the symbols in symbols.py to match your data).
-'''
-
-import re
-from unidecode import unidecode
-import pyopenjtalk
-from jamo import h2j, j2hcj
-from pypinyin import lazy_pinyin, BOPOMOFO
-import jieba, cn2an
-
-
-# This is a list of Korean classifiers preceded by pure Korean numerals.
-_korean_classifiers = '군데 권 개 그루 닢 대 두 마리 모 모금 뭇 발 발짝 방 번 벌 보루 살 수 술 시 쌈 움큼 정 짝 채 척 첩 축 켤레 톨 통'
-
-# Regular expression matching whitespace:
-_whitespace_re = re.compile(r'\s+')
-
-# Regular expression matching Japanese without punctuation marks:
-_japanese_characters = re.compile(r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
-
-# Regular expression matching non-Japanese characters or punctuation marks:
-_japanese_marks = re.compile(r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
-
-# List of (regular expression, replacement) pairs for abbreviations:
-_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [
- ('mrs', 'misess'),
- ('mr', 'mister'),
- ('dr', 'doctor'),
- ('st', 'saint'),
- ('co', 'company'),
- ('jr', 'junior'),
- ('maj', 'major'),
- ('gen', 'general'),
- ('drs', 'doctors'),
- ('rev', 'reverend'),
- ('lt', 'lieutenant'),
- ('hon', 'honorable'),
- ('sgt', 'sergeant'),
- ('capt', 'captain'),
- ('esq', 'esquire'),
- ('ltd', 'limited'),
- ('col', 'colonel'),
- ('ft', 'fort'),
-]]
-
-# List of (hangul, hangul divided) pairs:
-_hangul_divided = [(re.compile('%s' % x[0]), x[1]) for x in [
- ('ㄳ', 'ㄱㅅ'),
- ('ㄵ', 'ㄴㅈ'),
- ('ㄶ', 'ㄴㅎ'),
- ('ㄺ', 'ㄹㄱ'),
- ('ㄻ', 'ㄹㅁ'),
- ('ㄼ', 'ㄹㅂ'),
- ('ㄽ', 'ㄹㅅ'),
- ('ㄾ', 'ㄹㅌ'),
- ('ㄿ', 'ㄹㅍ'),
- ('ㅀ', 'ㄹㅎ'),
- ('ㅄ', 'ㅂㅅ'),
- ('ㅘ', 'ㅗㅏ'),
- ('ㅙ', 'ㅗㅐ'),
- ('ㅚ', 'ㅗㅣ'),
- ('ㅝ', 'ㅜㅓ'),
- ('ㅞ', 'ㅜㅔ'),
- ('ㅟ', 'ㅜㅣ'),
- ('ㅢ', 'ㅡㅣ'),
- ('ㅑ', 'ㅣㅏ'),
- ('ㅒ', 'ㅣㅐ'),
- ('ㅕ', 'ㅣㅓ'),
- ('ㅖ', 'ㅣㅔ'),
- ('ㅛ', 'ㅣㅗ'),
- ('ㅠ', 'ㅣㅜ')
-]]
-
-# List of (Latin alphabet, hangul) pairs:
-_latin_to_hangul = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
- ('a', '에이'),
- ('b', '비'),
- ('c', '시'),
- ('d', '디'),
- ('e', '이'),
- ('f', '에프'),
- ('g', '지'),
- ('h', '에이치'),
- ('i', '아이'),
- ('j', '제이'),
- ('k', '케이'),
- ('l', '엘'),
- ('m', '엠'),
- ('n', '엔'),
- ('o', '오'),
- ('p', '피'),
- ('q', '큐'),
- ('r', '아르'),
- ('s', '에스'),
- ('t', '티'),
- ('u', '유'),
- ('v', '브이'),
- ('w', '더블유'),
- ('x', '엑스'),
- ('y', '와이'),
- ('z', '제트')
-]]
-
-# List of (Latin alphabet, bopomofo) pairs:
-_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
- ('a', 'ㄟˉ'),
- ('b', 'ㄅㄧˋ'),
- ('c', 'ㄙㄧˉ'),
- ('d', 'ㄉㄧˋ'),
- ('e', 'ㄧˋ'),
- ('f', 'ㄝˊㄈㄨˋ'),
- ('g', 'ㄐㄧˋ'),
- ('h', 'ㄝˇㄑㄩˋ'),
- ('i', 'ㄞˋ'),
- ('j', 'ㄐㄟˋ'),
- ('k', 'ㄎㄟˋ'),
- ('l', 'ㄝˊㄛˋ'),
- ('m', 'ㄝˊㄇㄨˋ'),
- ('n', 'ㄣˉ'),
- ('o', 'ㄡˉ'),
- ('p', 'ㄆㄧˉ'),
- ('q', 'ㄎㄧㄡˉ'),
- ('r', 'ㄚˋ'),
- ('s', 'ㄝˊㄙˋ'),
- ('t', 'ㄊㄧˋ'),
- ('u', 'ㄧㄡˉ'),
- ('v', 'ㄨㄧˉ'),
- ('w', 'ㄉㄚˋㄅㄨˋㄌㄧㄡˋ'),
- ('x', 'ㄝˉㄎㄨˋㄙˋ'),
- ('y', 'ㄨㄞˋ'),
- ('z', 'ㄗㄟˋ')
-]]
-
-
-# List of (bopomofo, romaji) pairs:
-_bopomofo_to_romaji = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
- ('ㄅㄛ', 'p⁼wo'),
- ('ㄆㄛ', 'pʰwo'),
- ('ㄇㄛ', 'mwo'),
- ('ㄈㄛ', 'fwo'),
- ('ㄅ', 'p⁼'),
- ('ㄆ', 'pʰ'),
- ('ㄇ', 'm'),
- ('ㄈ', 'f'),
- ('ㄉ', 't⁼'),
- ('ㄊ', 'tʰ'),
- ('ㄋ', 'n'),
- ('ㄌ', 'l'),
- ('ㄍ', 'k⁼'),
- ('ㄎ', 'kʰ'),
- ('ㄏ', 'h'),
- ('ㄐ', 'ʧ⁼'),
- ('ㄑ', 'ʧʰ'),
- ('ㄒ', 'ʃ'),
- ('ㄓ', 'ʦ`⁼'),
- ('ㄔ', 'ʦ`ʰ'),
- ('ㄕ', 's`'),
- ('ㄖ', 'ɹ`'),
- ('ㄗ', 'ʦ⁼'),
- ('ㄘ', 'ʦʰ'),
- ('ㄙ', 's'),
- ('ㄚ', 'a'),
- ('ㄛ', 'o'),
- ('ㄜ', 'ə'),
- ('ㄝ', 'e'),
- ('ㄞ', 'ai'),
- ('ㄟ', 'ei'),
- ('ㄠ', 'au'),
- ('ㄡ', 'ou'),
- ('ㄧㄢ', 'yeNN'),
- ('ㄢ', 'aNN'),
- ('ㄧㄣ', 'iNN'),
- ('ㄣ', 'əNN'),
- ('ㄤ', 'aNg'),
- ('ㄧㄥ', 'iNg'),
- ('ㄨㄥ', 'uNg'),
- ('ㄩㄥ', 'yuNg'),
- ('ㄥ', 'əNg'),
- ('ㄦ', 'əɻ'),
- ('ㄧ', 'i'),
- ('ㄨ', 'u'),
- ('ㄩ', 'ɥ'),
- ('ˉ', '→'),
- ('ˊ', '↑'),
- ('ˇ', '↓↑'),
- ('ˋ', '↓'),
- ('˙', ''),
- ('，', ','),
- ('。', '.'),
- ('！', '!'),
- ('？', '?'),
- ('—', '-')
-]]
-
-
-def expand_abbreviations(text):
- for regex, replacement in _abbreviations:
- text = re.sub(regex, replacement, text)
- return text
-
-
-def lowercase(text):
- return text.lower()
-
-
-def collapse_whitespace(text):
- return re.sub(_whitespace_re, ' ', text)
-
-
-def convert_to_ascii(text):
- return unidecode(text)
-
-
-def japanese_to_romaji_with_accent(text):
- '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
- sentences = re.split(_japanese_marks, text)
- marks = re.findall(_japanese_marks, text)
- text = ''
- for i, sentence in enumerate(sentences):
- if re.match(_japanese_characters, sentence):
- if text!='':
- text+=' '
- labels = pyopenjtalk.extract_fullcontext(sentence)
- for n, label in enumerate(labels):
- phoneme = re.search(r'\-([^\+]*)\+', label).group(1)
- if phoneme not in ['sil','pau']:
- text += phoneme.replace('ch','ʧ').replace('sh','ʃ').replace('cl','Q')
- else:
- continue
- n_moras = int(re.search(r'/F:(\d+)_', label).group(1))
- a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
- a2 = int(re.search(r"\+(\d+)\+", label).group(1))
- a3 = int(re.search(r"\+(\d+)/", label).group(1))
- if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil','pau']:
- a2_next=-1
- else:
- a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
- # Accent phrase boundary
- if a3 == 1 and a2_next == 1:
- text += ' '
- # Falling
- elif a1 == 0 and a2_next == a2 + 1 and a2 != n_moras:
- text += '↓'
- # Rising
- elif a2 == 1 and a2_next == 2:
- text += '↑'
- if i
-
-
-
-
-
-
-
- YAKE! : Github Repo | Paper
"
-
-iface = gr.Interface(yake_func, inputs=[gr.inputs.Textbox(label="Text",lines=10),
- gr.inputs.Slider(minimum=1,maximum=20,step=1,default=3,
- label="Number of keywords"),
- gr.inputs.Slider(minimum=1,maximum=5,step=1,default=3,
- label="Max ngram size"),],
- outputs=[ gr.outputs.Dataframe(),gr.outputs.HTML()],
- examples=[[ex1,1,3],[ex2,1,3]], examples_per_page=2, live=False,
- layout="horizontal", interpretation=None, title=title,
- description=description, article=article)
-
-iface.launch()
diff --git a/spaces/abdvl/datahub_qa_bot/docs/api/tutorials/adding-terms.md b/spaces/abdvl/datahub_qa_bot/docs/api/tutorials/adding-terms.md
deleted file mode 100644
index 5948ac168c7bd61ae73574bb1f3ef8f5abedb365..0000000000000000000000000000000000000000
--- a/spaces/abdvl/datahub_qa_bot/docs/api/tutorials/adding-terms.md
+++ /dev/null
@@ -1,209 +0,0 @@
-# Adding Terms On Datasets/Columns
-
-## Why Would You Add Terms?
-The Business Glossary(Term) feature in DataHub helps you use a shared vocabulary within the orgarnization, by providing a framework for defining a standardized set of data concepts and then associating them with the physical assets that exist within your data ecosystem.
-
-Fore more information about terms, refer to [About DataHub Business Glossary](/docs/glossary/business-glossary.md).
-
-### Goal Of This Guide
-This guide will show you how to add a `CustomerAccount` term to `user_name` column of a dataset named `fct_users_created`.
-Also, we will cover how to add a term to a dataset itself.
-
-
-## Pre-requisites
-For this tutorial, you need to deploy DataHub Quickstart and ingest sample data.
-For detailed information, please refer to [Prepare Local DataHub Environment](/docs/api/tutorials/references/prepare-datahub.md).
-
-:::note
-Before adding terms, you need to ensure the targeted dataset and the term are already present in your datahub.
-If you attempt to manipulate entities that do not exist, your operation will fail.
-In this guide, we will be using data from a sample ingestion.
-If you want to know how to create entities using APIs & SDKs, please refer to [Creating Terms](/docs/api/tutorials/creating-terms.md) and [Creating Datasets](/docs/api/tutorials/creating-datasets.md).
-:::
-
-
-## Add Terms With GraphQL
-
-:::note
-Please note that there are two available endpoints (`:8000`, `:9002`) to access GraphQL.
-For more information about the differences between these endpoints, please refer to [DataHub Metadata Service](../../../metadata-service/README.md#graphql-api)
-:::
-
-### GraphQL Explorer
-GraphQL Explorer is the fastest way to experiment with GraphQL without any dependancies.
-Navigate to GraphQL Explorer (`http://localhost:9002/api/graphiql`) and run the following query.
-
-```python
-mutation addTerms {
- addTerms(
- input: {
- termUrns: ["urn:li:glossaryTerm:CustomerAccount"],
- resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)",
- subResourceType:DATASET_FIELD,
- subResource:"user_name"})
-}
-```
-
-Note that you can also add a term on a dataset if you don't specify `subResourceType` and `subResource`.
-```json
-mutation addTerms {
- addTerms(
- input: {
- termUrns: ["urn:li:glossaryTerm:CustomerAccount"],
- resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)",
- }
- )
-}
-```
-
-If you see the following response, the operation was successful:
-```python
-{
- "data": {
- "addTerms": true
- },
- "extensions": {}
-}
-```
-
-### CURL
-
-With CURL, you need to provide tokens. To generate a token, please refer to [Generate Access Token](/docs/api/tutorials/references/generate-access-token.md).
-With `accessToken`, you can run the following command.
-
-```shell
-curl --location --request POST 'http://localhost:8080/api/graphql' \
---header 'Authorization: Bearer