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  1. ci/official/wheel_test/README.md

    specific Python version.
    
    ##### Parameters
    `path_to_tensorflow_wheel`: The local path to the TensorFlow wheel file.
    Example: `/tmp/tensorflow-2.14.0-cp311-cp311-linux_x86_64.whl`
    
    `python_version`: The target Python version, replacing `.` with `_`.
    Example: For Python 3.11, use `3_11`
    
    The script performs the following steps:
    
    1. Navigates to the `../requirements_updater` directory.
    Plain Text
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  2. ci/official/requirements_updater/README.md

    and
    [here](https://github.com/tensorflow/tensorflow/commit/052445e04ce20fd747657e0198a1bcec2b6dff5b),
    for an example.
    
    See
    [this commit](https://github.com/tensorflow/tensorflow/commit/5f7f05a80aac9b01325a78ec3fcff0dbedb1cc23)
    as a rough example of the steps below.
    
    All the files referenced below are located in the same directory as this README,
    unless indicated otherwise.
    
    Plain Text
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  3. ci/official/containers/linux_arm64/devel.usertools/setup_venv_test.sh

    set -euxo pipefail
    
    # Run this from inside the tensorflow github directory.
    # Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file"
    # Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl"
    # 
    # This will create a venv with that wheel file installed in it, and a symlink
    # in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
    # "pip" tests.
    
    Shell Script
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  4. SECURITY.md

    to the network can execute arbitrary code with the privileges of the user
    running the `tf.train.Server`.
    
    ## Untrusted inputs during training and prediction
    
    TensorFlow supports a wide range of input data formats. For example it can
    process images, audio, videos, and text. There are several modules specialized
    in taking those formats, modifying them, and/or converting them to intermediate
    formats that can be processed by TensorFlow.
    
    Plain Text
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  5. ci/official/README.md

    against a pending change. Search for "MLCI" internally to find it.
    
    You may invoke a CI script of your choice by following these instructions:
    
    ```bash
    cd tensorflow-git-dir
    
    # Here is a single-line example of running a script on Linux to build the
    # GPU version of TensorFlow for Python 3.12, using the public TF bazel cache and
    # a local build cache:
    TFCI=py312,linux_x86_cuda,public_cache,disk_cache ci/official/wheel.sh
    
    Plain Text
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  6. .gitignore

    # iOS
    *.pbxproj
    *.xcworkspace
    /*.podspec
    /tensorflow/lite/**/coreml/**/BUILD
    /tensorflow/lite/**/ios/BUILD
    /tensorflow/lite/**/objc/BUILD
    /tensorflow/lite/**/swift/BUILD
    /tensorflow/lite/examples/ios/simple/data/*.tflite
    /tensorflow/lite/examples/ios/simple/data/*.txt
    Podfile.lock
    Pods
    Plain Text
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  7. ci/official/containers/linux_arm64/devel.usertools/squash_testlogs.py

    # ==============================================================================
    """Merge all JUnit test.xml files in one directory into one.
    
    Usage: squash_testlogs.py START_DIRECTORY OUTPUT_FILE
    
    Example: squash_testlogs.py /tf/pkg/testlogs /tf/pkg/merged.xml
    
    Recursively find all the JUnit test.xml files in one directory, and merge any
    of them that contain failures into one file. The TensorFlow DevInfra team
    Python
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