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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.
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  2. tensorflow/c/eager/c_api_unified_experimental_test.cc

      ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
      TFE_DeleteContextOptions(opts);
    
      ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
    
      /* Want to test simple MatMul example:
        [[0,0],    *   [[0,0],    =   [[0,0],
         [0,0]]         [0,0]]         [0,0]]
      */
    
      // Build an abstract input tensor.
      int64_t dims[] = {2, 2};  // Matrices will be 2 x 2
    C++
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  3. tensorflow/c/c_api_test.cc

      // Write {0, 1, 2, 3} as tensorflow::Example inputs.
      Tensor input(tensorflow::DT_STRING, TensorShape({4}));
      for (int64_t i = 0; i < input.NumElements(); ++i) {
        tensorflow::Example example;
        auto* feature_map = example.mutable_features()->mutable_feature();
        (*feature_map)["x"].mutable_float_list()->add_value(i);
        input.flat<tstring>()(i) = example.SerializeAsString();
      }
    
    C++
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  4. CONTRIBUTING.md

    *   [C/C++ license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op.cc#L1)
    *   [Python license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/nn.py#L1)
    *   [Java license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1)
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  5. 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.
    
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  6. 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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  7. 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.
    
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  8. tensorflow/c/eager/c_api_test.cc

    // 6. Create a context D using the full cluster server def E.
    // 7. Read the variable in D.
    TEST(CAPI, SingleHostServerDefV1Works) {
      // Create a server def that represents a 2-process cluster and a client.
      // Example:
      //
      // cluster { job { name: "worker"
      //                 tasks { key: 0 value: "localhost:14522" }
      //                 tasks { key: 1 value: "localhost:14523" }
      //               }
    C++
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  9. 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
    
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  10. .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
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