# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc

# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user

# Here are bazelrc configs for release builds
# Build TensorFlow v2.
test:release_base --test_size_filters=small,medium

# Enable support for all targets

.DS_Store
.ipynb_checkpoints
node_modules
/.bazelrc.user
/.tf_configure.bazelrc
/xla_configure.bazelrc
/bazel-*
/bazel_pip
/tools/python_bin_path.sh
/tensorflow/tools/git/gen
/pip_test
/_python_build
*.pyc
__pycache__
*.swp
.vscode/
cmake_build/
tensorflow/contrib/cmake/_build/
.idea/**
/build/
[Bb]uild/
/build_output/
/tensorflow/core/util/version_info.cc
/tensorflow/python/framework/fast_tensor_util.cpp

# Don't use the bazel cache when a new docker image is created.
RUN echo build --action_env=DOCKER_CACHEBUSTER=$(date +%s%N)$RANDOM >> /etc/bazel.bazelrc

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: $TFCI
       TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX is "$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX".
       But in .bazelrc, there is no "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX".
       That setting must exist for this script to function correctly.
EOF
  exit 1
fi

def retrieve_bazel_version():
  """Retrieve installed bazel version (or bazelisk).

  Returns:
    The bazel version detected.
  """
  bazel_executable = shutil.which('bazel')
  if bazel_executable is None:
    bazel_executable = shutil.which('bazelisk')
    if bazel_executable is None:
      print('Cannot find bazel. Please install bazel/bazelisk.')
      sys.exit(1)

  stderr = open(os.devnull, 'wb')

you wish the updater to consider pre-release versions simply pass `--pre`
argument to the bazel command:

```
bazel run //ci/official/requirements_updater:requirements.update --repo_env=HERMETIC_PYTHON_VERSION=3.12 -- --pre
```

If you need to upgrade all of the packages in requirements lock file, just pass
the `--upgrade` parameter:

```

# ENV BAZEL_VC_FULL_VERSION 14.39.33519

# Install Bazelisk.
RUN md C:\tools\bazel
RUN (New-Object Net.WebClient).DownloadFile( \
         'https://github.com/bazelbuild/bazelisk/releases/download/v1.19.0/bazelisk-windows-amd64.exe', \
         'C:\tools\bazel\bazel.exe'); \
    $env:PATH = [Environment]::GetEnvironmentVariable('PATH', 'Machine') + ';C:\tools\bazel'; \
    [Environment]::SetEnvironmentVariable('PATH', $env:PATH, 'Machine');

A. Unique TensorFlower <******@****.***> 1758223501 -0700

# ENV BAZEL_VC_FULL_VERSION 14.39.33519

# Install Bazelisk.
RUN md C:\tools\bazel
RUN (New-Object Net.WebClient).DownloadFile( \
         'https://github.com/bazelbuild/bazelisk/releases/download/v1.22.1/bazelisk-windows-amd64.exe', \
         'C:\tools\bazel\bazel.exe'); \
    $env:PATH = [Environment]::GetEnvironmentVariable('PATH', 'Machine') + ';C:\tools\bazel'; \
    [Environment]::SetEnvironmentVariable('PATH', $env:PATH, 'Machine');

    once you get into the running container so `bazel` can find the `tensorflow`
    workspace).

    you can do this by using the following command. As an example-

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```

    Once you have the packages installed, you can run a specific unit test in
    bazel by doing as follows:

    ```bash