git config --system protocol.file.allow always

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files
    if [[ "$(git rev-parse --abbrev-ref HEAD)" == "pull_branch" ]]; then
        # TF's CI runs 'git fetch origin "pull/PR#/merge:pull_branch"'

      uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
    - name: Get file changes
      id: get_file_changes
      uses: trilom/file-changes-action@a6ca26c14274c33b15e6499323aac178af06ad4b # v1.2.4
      with:
        output: ' '
    - name: Report list of changed files
      run: |
        echo Changed files: ${{ steps.get_file_changes.outputs.files }}
    - name: Set up Python 3.9

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.

# limitations under the License.
# ==============================================================================
# This script dumps some information about the environment. It's most useful
# for verifying changes to the TFCI scripts system, and most users won't need
# to interact with it at all.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

echo "==TFCI== env outside of tfrun:"
env
echo "==TFCI== env inside of tfrun:"

TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
# Note: this is not set to "--cpu", because that changes the package name
# to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow"
# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files
    if [[ "$(git rev-parse --abbrev-ref HEAD)" = "pull_branch" ]]; then
        # TF's CI runs 'git fetch origin "pull/PR#/merge:pull_branch"'

# limitations under the License.
# ==============================================================================
#
# Common setup for all TF scripts.
#
# Make as FEW changes to this file as possible. It should not contain utility
# functions (except for tfrun); use dedicated scripts instead and reference them
# specifically. Use your best judgment to keep the scripts in this directory

    changes to be made to PR to pass quality checks and send it back or on a
    rare occasion we may reject it.

**3. Review**

-   For a valid PR, reviewer (person familiar with the code/functionality)
    checks if the PR looks good or needs additional changes.
-   If all looks good, the reviewer will approve the PR.
-   If a change is needed, the contributor is requested to make the suggested

*   Clone the TensorFlow repo and switch to the corresponding branch for your
    desired TensorFlow version, for example, branch `r2.8` for version 2.8.
*   Apply (that is, cherry-pick) the desired changes and resolve any code
    conflicts.
*   Run TensorFlow tests and ensure they pass.
*   [Build](https://www.tensorflow.org/install/source) the TensorFlow pip
    package from source.

## Continuous build status

    -   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