shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash

# These flags share the user's gcloud credentials with the container, so that bazel
# inside the container can authenticate. Note: TF's CI does not have any credential
# stored here.

TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ARGS="--gpus all"
TFCI_LIB_SUFFIX="-gpu-linux-x86_64"

# ==============================================================================

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.:

build --distinct_host_configuration=false

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014

cat <<EOF
IMPORTANT: These tests ran under docker. This script does not clean up the
container for you! You can delete the container with:

$ docker rm -f tf

You can also execute more commands within the container with e.g.:

$ docker exec tf bazel clean
$ docker exec -it tf bash
EOF

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

  DOCKER_BUILDKIT=1 docker build --cache-from "$TFCI_DOCKER_IMAGE" -t "$TFCI_DOCKER_IMAGE" $TFCI_DOCKER_REBUILD_ARGS
  if [[ "$TFCI_DOCKER_REBUILD_UPLOAD_ENABLE" == 1 ]]; then
    docker push "$TFCI_DOCKER_IMAGE"
  fi
fi

# Keep the existing "tf" container if it's already present.
# The container is not cleaned up automatically! Remove it with:
# docker rm tf
if ! docker container inspect tf >/dev/null 2>&1 ; then

#   container and start fresh, run "docker rm -f tf". Removing the container
#   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.
#

      -
        name: Set up Docker Buildx
        uses: docker/setup-buildx-action@8c0edbc76e98fa90f69d9a2c020dcb50019dc325 # v2.2.1
      -
        name: Login to GCR
        if: contains(github.event.pull_request.labels.*.name, 'build and push to gcr.io for staging')
        uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a # v2.1.0
        with: