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  1. CREDITS

    Related Rights"). Copyright and Related Rights include, but are not
    limited to, the following:
    
      i. the right to reproduce, adapt, distribute, perform, display,
         communicate, and translate a Work;
     ii. moral rights retained by the original author(s) and/or performer(s);
    iii. publicity and privacy rights pertaining to a person's image or
         likeness depicted in a Work;
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  2. docs/tr/docs/index.md

    <div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>
    
    ---
    
    "_**FastAPI**'ı **tahminlerimiz**'i sorgulanabilir hale getirecek bir **REST** sunucu oluşturmak için benimsedik/kullanmaya başladık._"
    
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  3. docs/fr/docs/index.md

    <div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>
    
    ---
    
    "_Nous avons adopté la bibliothèque **FastAPI** pour créer un serveur **REST** qui peut être interrogé pour obtenir des **prédictions**. [pour Ludwig]_"
    
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  4. docs/uk/docs/index.md

    <div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>
    
    ---
    
    "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"
    
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  5. README.md

    <div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>
    
    ---
    
    "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"
    
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  6. docs/em/docs/index.md

    <div style="text-align: right; margin-right: 10%;">✡ 🍏, 👖 🇪🇸, 🌲 🍏 - <strong>📺</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(🇦🇪)</small></a></div>
    
    ---
    
    "_👤 🤭 🌕 😄 🔃 **FastAPI**. ⚫️ 🎊 ❗_"
    
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  7. docs/en/docs/async.md

    ---
    
    If you just don't know, use normal `def`.
    
    ---
    
    **Note**: You can mix `def` and `async def` in your *path operation functions* as much as you need and define each one using the best option for you. FastAPI will do the right thing with them.
    
    Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.
    
    But by following the steps above, it will be able to do some performance optimizations.
    
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  8. LICENSES/vendor/github.com/antlr4-go/antlr/v4/LICENSE

    = vendor/github.com/antlr4-go/antlr/v4 licensed under: =
    
    Copyright (c) 2012-2023 The ANTLR Project. 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.
    
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  9. analysis/analysis-api-fir/src/org/jetbrains/kotlin/analysis/api/fir/components/KtFirCallResolver.kt

            if (psi is KtBinaryExpression && psi.operationToken in KtTokens.AUGMENTED_ASSIGNMENTS) {
                val rightOperandPsi = deparenthesize(psi.right) ?: return null
                val leftOperandPsi = deparenthesize(psi.left) ?: return null
                val compoundAssignKind = psi.getCompoundAssignKind()
    
                // handle compound assignment with array access convention
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  10. RELEASE.md

        *   `steps_per_epoch` and `steps` arguments are supported with numpy arrays.
        *   New error message when unexpected keys are used in
            sample_weight/class_weight dictionaries
        *   Losses are scaled in Keras compile/fit and not in the optimizers
            anymore. If you are using custom training loop, we have new utilities to
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