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  1. ci/official/wheel_test/README.md

    ## Wheel Test
    
    This directory is dedicated to tests that require a built TensorFlow wheel
    file for testing, such as:
    
    * Ensuring the entire API is importable
    * Testing downstream projects against the wheel
    
    Ensure you have Bazel installed and accessible from your command line.
    
    These tests use hermetic Python. They also require a built TensorFlow wheel file
    and a requirements_lock file. The requirements_lock file is generated by the
    Plain Text
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  2. ci/official/envs/rbe

    # it enables a derived --config setting.  If RBE is not available (i.e. there
    # is no --config setting), bazel would fail and quit. This script does a quick
    # check This script checks for such errors early
    if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then
      cat <<EOF
    ERROR: RBE was enabled via the 'rbe' env in the 'TFCI' variable.
           TFCI: $TFCI
    Plain Text
    - Registered: Tue Apr 30 12:39:09 GMT 2024
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  3. ci/official/utilities/get_versions.sh

    export TF_VER_PATCH=$(awk '/#define TF_PATCH_VERSION/ {print $3}' tensorflow/core/public/version.h)
    
    # Note: in awk, "print $N" prints the Nth "field", where fields are strings separated
    # by whitespace. The flag "-F<x>" changes the behavior such that fields are now strings
    # separated by the character <x>. Therefore, -F\' (escaped single quote) means that field
    # $2 in <Tensor'flow'> is <flow>. This is useful for reading string literals like below.
    Shell Script
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  4. tensorflow/c/experimental/filesystem/modular_filesystem_test.cc

    // parsed.
    //
    // Furthermore, as `INSTANTIATE_TEST_SUITE_P` needs to be at global level and we
    // don't want to have a `std::vector<std::string>` at global level, we use a
    // static pointer to such a vector: we construct it via `SchemeVector()` below
    // and when tests are instantiated we process it using `GetSchemes()`.
    static std::vector<std::string>* SchemeVector() {
    C++
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Fri May 27 20:25:58 GMT 2022
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  5. tensorflow/c/eager/c_api_unified_experimental.h

    // here.
    void TF_SetTracingImplementation(const char* name, TF_Status*);
    
    // Creates a new TensorFlow function. A Function is an execution context, and as
    // such it can trace operations through TF_ExecuteOperation. After completing
    // tracing, a function can be obtained by TF_FinalizeFunction.
    TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* status);
    
    C
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    - Last Modified: Sun Oct 24 11:27:00 GMT 2021
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  6. CONTRIBUTING.md

    ### Typical Pull Request Workflow -
    
    **1. New PR**
    
    - As a contributor, you submit a New PR on GitHub.
    - We inspect every incoming PR and add certain labels to the PR such as `size:`,
      `comp:` etc.  At this stage we check if the PR is valid and meets certain
      quality requirements. For example, we check if the CLA is signed, PR has
    Plain Text
    - Registered: Tue May 07 12:40:20 GMT 2024
    - Last Modified: Thu Mar 21 11:45:51 GMT 2024
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  7. CODE_OF_CONDUCT.md

        advances.
    *   Trolling, insulting/derogatory comments, and personal or political attacks.
    *   Public or private harassment.
    *   Publishing others' private information, such as a physical or electronic
        address, without explicit permission.
    *   Conduct which could reasonably be considered inappropriate for the forum in
        which it occurs.
    
    Plain Text
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    - Last Modified: Fri Feb 05 18:43:16 GMT 2021
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  8. ci/official/README.md

    #   your builds. This usually saves a lot of time, especially when
    #   re-running tests. However, note that:
    #
    #    - New environments like new CUDA versions, changes to manylinux,
    #      compilers, etc. can cause undefined behavior such as build failures
    #      or tests passing incorrectly.
    #    - Automatic LLVM updates are known to extend build time even with
    #      the cache; this is unavoidable.
    export TFCI=py311,linux_x86,public_cache,disk_cache
    
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  9. requirements_lock_3_10.txt

        --hash=sha256:da46cec9fd2de5be3a8a784f434e4c4ab670b4ff54d605c4c2717e9d49c4c367
        # via rich
    requests==2.31.0 \
        --hash=sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f \
        --hash=sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1
        # via -r requirements.in
    rich==13.7.0 \
        --hash=sha256:5cb5123b5cf9ee70584244246816e9114227e0b98ad9176eede6ad54bf5403fa \
    Plain Text
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    - Last Modified: Fri Apr 12 04:38:53 GMT 2024
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  10. tensorflow/c/eager/abstract_operation.h

      // chosen for the operation by the device placement logic in the
      // executor. After that, the value returned by DeviceName will be a full
      // device name such as "/job:localhost/replica:0/task:0/device:GPU:1".
      virtual const string& DeviceName() const = 0;
    
      // Sets the operation device name.
      //
      // The given `name` must be parseable by DeviceNameUtils::ParseFullName, and
    C
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    - Last Modified: Wed Jul 14 16:20:41 GMT 2021
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