- name: Checkout repository
        if: ${{ github.event_name == 'push' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
      - name: Build binary and run C++ tests
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tf_ci_ext_c' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_ci_ext_c'

# limitations under the License.
# ==============================================================================

# script to run pip-compile for each requirement.
# if there is a change in requirements.in then all lock files will be updated
# accordingly

# All commands run relative to this directory
cd "$(dirname "${BASH_SOURCE[0]}")"

mv BUILD.bazel BUILD

SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")

    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
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"
# 

      id-token: write

    steps:
      - name: "Checkout code"
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
        with:
          persist-credentials: false

      - name: "Run analysis"
        uses: ossf/scorecard-action@15c10fcf1cf912bd22260bfec67569a359ab87da # v2.1.1
        with:
          results_file: results.sarif
          results_format: sarif

    f_ = src.release();
    return *this;
  }

  ~Cleanup() {
    if (!released_) f_();
  }

  // Releases the cleanup function instead of running it.
  // Hint: use c.release()() to run early.
  F release() {
    released_ = true;
    return std::move(f_);
  }

  bool is_released() const { return released_; }

 private:
  static_assert(!std::is_reference<F>::value, "F must not be a reference");

interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces
this file with a file generated from [`api_template.__init__.py`](https://www.github.com/tensorflow/tensorflow/blob/master/tensorflow/api_template.__init__.py)
"""

TensorFlow's official CI jobs run the scripts in this folder. Our internal CI
system, Kokoro, schedules our CI jobs by combining a build script with a file
from the `envs` directory that is filled with configuration options:

-   Nightly jobs (Run nightly on the `nightly` branch)
    -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`

# and click "Run Workflow." Leave "Use Workflow From" set to "master", then
# input the branch name and paste the cherry-pick commit and click Run. A PR
# will be created.

name: Release Branch Cherrypick
on:
  workflow_dispatch:
    inputs:
      # We use this instead of the "run on branch" argument because GitHub looks

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

# -e: abort script if one command fails
# -u: error if undefined variable used