# "-devYYYYMMDD" to the end of the version string for nightly builds.
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  export TF_VER_FULL="$(tfrun bazel run //tensorflow/tools/ci_build:calculate_full_version -- --wheel-type nightly)"
else
  export TF_VER_FULL="$(tfrun bazel run //tensorflow/tools/ci_build:calculate_full_version -- --wheel-type release)"
fi

# Note on gsutil commands:

  cp ./ci/official/requirements_updater/numpy1_requirements/*.txt .
fi

tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=cuda_wheel //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_BASE_ARGS $TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG --verbose_failures

tfrun "$TFCI_FIND_BIN" ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun mkdir -p ./dist

# Install various tools.
# - bats: bash unit testing framework
# - bazelisk: always use the correct bazel version
# - buildifier: clean bazel build deps
# - buildozer: clean bazel build deps
# - gcloud SDK: communicate with Google Cloud Platform (GCP) for RBE, CI
# - patchelf: Utility tool to modify existing ELF executables and libraries

setup_file() {
    bazel version  # Start the bazel server

    # Fixes "fatal: detected dubious ownership in repository" for Docker.
    git config --system --add safe.directory '*'
    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

      placeholder: e.g., Linux Ubuntu 16.04
  - type: input
    id: Python
    attributes:
      label: Python version
      placeholder: e.g., 3.9
  - type: input
    id: Bazel
    attributes:
      label: Bazel version
      description: If compiling from source
  - type: input
    id: Compiler
    attributes:
      label: GCC/compiler version
      description: If compiling from source
  - type: input

#   destroys some temporary bazel data and causes longer builds.
#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".

fi

if [[ $(uname -s) != MSYS_NT* ]]; then
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS test $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_test
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_build
else
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=windows_libtensorflow_build
fi

#                                           ^^^^
# This env is only valid when RBE is available on the selected platform, since
# 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

# 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');

# 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');