[Python 2's EOL on January 1, 2020](https://www.python.org/dev/peps/pep-0373/#update).

Coinciding with this change, new releases of
[TensorFlow's Docker images](https://hub.docker.com/r/tensorflow/tensorflow/)
provide Python 3 exclusively. Because all images now use Python 3, Docker tags
containing `-py3` will no longer be provided and existing `-py3` tags like
`latest-py3` will not be updated.

## Major Features and Improvements

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

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.:

if [[ "$TFCI_DOCKER_PULL_ENABLE" == 1 ]]; then
  # Simple retry logic for docker-pull errors. Sleeps if a pull fails.
  # Pulling an already-pulled container image will finish instantly, so
  # repeating the command costs nothing.
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 30
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 60
  docker pull "$TFCI_DOCKER_IMAGE"
fi 

        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
          docker image prune -af
      - name: Clean repository
        shell: bash

    groups:
      github-actions:
        patterns:
          - "*"

  - package-ecosystem: docker
    directory: /ci/devinfra/docker_windows
    schedule:
      interval: monthly
    ignore:
      - dependency-name: "*"
        update-types: ["version-update:semver-major", "version-update:semver-minor"]

  - package-ecosystem: docker
    directory: /tensorflow/tools/gcs_test
    schedule:
      interval: monthly

          <item index="10" class="java.lang.String" itemvalue="org.checkerframework.checker.nullness.compatqual.NullableDecl" />
          <item index="11" class="java.lang.String" itemvalue="org.checkerframework.checker.nullness.compatqual.NullableType" />
          <item index="12" class="java.lang.String" itemvalue="org.checkerframework.checker.nullness.qual.Nullable" />

        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

#   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.
#

# when using variables like `TFCI_OUTPUT_DIR` in `docker exec commands,
# requiring conditional path adjustments throughout the CI scripts.
# Note: This does not work for `docker cp` commands.
# For a little more detail, see:
# https://github.com/tensorflow/tensorflow/blob/cc3006af6fea8d2a1360b3b5e65f9d14bbdb7094/ci/devinfra/docker/windows2022/Dockerfile#L196
TFCI_OUTPUT_WIN_DOCKER_DIR='C:/drive_t'

# Do not print anything if this is not being used interactively
[ -z "$PS1" ] && return

# Set up attractive prompt
export PS1="\[\e[31m\]tf-docker\[\e[m\] \[\e[33m\]\w\[\e[m\] > "
export TERM=xterm-256color
alias grep="grep --color=auto"
alias ls="ls --color=auto"
# Fix nvidia-docker