# 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

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

# 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

MODULE.bazel.lock
.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

    requirements_lock = "//:requirements_lock_{}.txt".format(python_version.replace(".", "_")),
    whl_modifications = {
        "@pypi_mods//:numpy.json": "numpy",  # @pypi_mods is defined in XLA's MODULE.bazel
    },
) for python_version in [
    "3.10",
    "3.11",
    "3.12",
    "3.13",
]]

use_repo(pip, "pypi_mods", pypi = "tf_pypi")

TFCI_USE_CLANG_CL=0

# Map TFCI_BAZEL_* to BAZEL_* so cc_configure can find them in the environment.
# We use the shell's default value substitution to ensure that if these are
# already set (e.g. poisoned for RBE), we don't overwrite them with empty values
# before setup.sh has a chance to restore the TFCI_ variables.
export BAZEL_VC="${TFCI_BAZEL_VC:-$BAZEL_VC}"
export BAZEL_LLVM="${TFCI_BAZEL_LLVM:-$BAZEL_LLVM}"

TFCI_USE_CLANG_CL=0

# Map TFCI_BAZEL_* to BAZEL_* so cc_configure can find them in the environment.
# We use the shell's default value substitution to ensure that if these are
# already set (e.g. poisoned for RBE), we don't overwrite them with empty values
# before setup.sh has a chance to restore the TFCI_ variables.
export BAZEL_VC="${TFCI_BAZEL_VC:-$BAZEL_VC}"
export BAZEL_LLVM="${TFCI_BAZEL_LLVM:-$BAZEL_LLVM}"

Adrian Kuegel <******@****.***> 1774264389 -0700

*   AutoGraph no longer converts functions passed to `tf.py_function`,
    `tf.py_func` and `tf.numpy_function`.
*   Deprecating `XLA_CPU` and `XLA_GPU` devices with this release.
*   Increasing the minimum bazel version to build TF to 2.0.0 to use Bazel's
    `cc_experimental_shared_library`.
*   Keras compile/fit behavior for functional and subclassed models have been
    unified. Model properties such as `metrics`, `metrics_names` will now be

# 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');