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  1. ci/official/wheel_test/README.md

    init files creation process and is subsequently stored in the wheel file after
    the build. It also contains a few paths that cannot be directly imported. These
    paths point to attributes or sub-modules within a module's namespace, but they
    don't correspond to an actual file or directory on the filesystem. The list of
    such paths is stored in the packages_for_skip variable and will be skipped
    during the test.
    
    ##### How to Build
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  2. ci/devinfra/README.md

    # DevInfra CI Directory
    
    > **Warning** This folder is still under construction. It is part of an ongoing
    > effort to improve the structure of CI and build related files within the
    > TensorFlow repo. This warning will be removed when the contents of this
    > directory are stable and appropriate documentation around its usage is in
    > place.
    
    Maintainer: TensorFlow DevInfra
    
    Issue Reporting: File an issue against this repo and tag
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  3. ci/README.md

    # TensorFlow continuous integration
    
    > **Warning** This folder is still under construction. It is part of an ongoing
    > effort to improve the structure of CI and build related files within the
    > TensorFlow repo. This warning will be removed when the contents of this
    > directory are stable and appropriate documentation around its usage is in
    > place.
    
    Maintainer: TensorFlow DevInfra
    
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  4. README.md

    researchers push the state-of-the-art in ML and developers easily build and
    deploy ML-powered applications.
    
    TensorFlow was originally developed by researchers and engineers working within
    the Machine Intelligence team at Google Brain to conduct research in machine
    learning and neural networks. However, the framework is versatile enough to be
    used in other areas as well.
    
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  5. ci/official/README.md

        -   Uses `pycpp.sh`, `code_check_changed_files.sh`
    
    These "env" files match up with an environment matrix that roughly covers:
    
    -   Different Python versions
    -   Linux, MacOS, and Windows machines (these pool definitions are internal)
    -   x86 and arm64
    -   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs
    
    ## How to Test Your Changes to TensorFlow
    
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  6. ci/official/requirements_updater/README.md

    ## Requirements updater
    
    Requirements updater is a standalone tool, intended to simplify process of
    updating requirements for multiple minor versions of Python.
    
    It takes in a file with a set of dependencies, and produces a more detailed
    requirements file for each version, with hashes specified for each
    dependency required, as well as their sub-dependencies.
    
    ### How to update/add requirements
    
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