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:
# "gsutil cp" always "copies into". It cannot act on the contents of a directory

# ==============================================================================
TFCI_INSTALLER_WHL_ENABLE=1
TFCI_INSTALLER_WHL_PROJECT_NAME="tensorflow"
TFCI_INSTALLER_WHL_NIGHTLY_PROJECT_NAME="tf_nightly"
# Supported wheel tags are stored as strings in TFCI_INSTALLER_WHL_TAGS
# separated by spaces.
TFCI_INSTALLER_WHL_TAGS="cp39-cp39-win_amd64 cp310-cp310-win_amd64 cp311-cp311-win_amd64 cp312-cp312-win_amd64"

TFCI_BAZEL_BAZELRC_ARGS=
TFCI_BAZEL_COMMON_ARGS=
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=
TFCI_BUILD_PIP_PACKAGE_BASE_ARGS=
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG=
# Mostly meant to be used for Windows.
# For Windows, the same wheel is uploaded to both tensorflow_cpu, and tensorflow
TFCI_BUILD_PIP_PACKAGE_ADDITIONAL_WHEEL_NAMES=
TFCI_DOCKER_ARGS=
TFCI_DOCKER_ENABLE=
TFCI_DOCKER_IMAGE=
TFCI_DOCKER_PULL_ENABLE=
TFCI_DOCKER_REBUILD_ARGS=

# at the scripts of ci/official/ to see how TF's CI uses them.

# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel
# will work properly. These are usually run Nightly or upon Release.
# CPU WHEEL
test:linux_cpu_wheel_test_filters --test_tag_filters=-no_oss,-tf_tosa,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310,-no_oss_py313

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ARGS="--gpus all"
TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
# TODO: Set back to 610M once the wheel size is fixed.

#       ./any.sh
#
# 2. RUN ANY OTHER SCRIPT AND ENV WITH NO SIDE EFFECTS (NO UPLOADS)
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_SCRIPT=ci/official/wheel.sh
#       ./any.sh
#
# 3. DO THE SAME WITH A LOCAL CACHE OR RBE:
#       export TF_ANY_EXTRA_ENV=ci/official/envs/public_cache,ci/official/envs/disk_cache
#       ...
#       ./any.sh
#     or

      with:
        python-version: "3.9"
    - name: Install Python dependencies
      run: |
        python -m pip install --upgrade pip
        pip install pylint==2.13.9 numpy wheel
    - name: Run PyLint on changed files
      run: |

#   TF_BISECT_BAD: First bad commit (e.g. commit from the first failing job)
#   TF_BISECT_SCRIPT: The build script path relative to the TF root dir, e.g.
#     ci/official/wheel.sh
#   TFCI: The env config path, relative to the TF root dir, e.g.
#     ci/official/envs/an_env_config
#
# Note that you can combine bisect.sh with any.sh to bisect a single test:
#
#   export TFCI=...

# Download and install patchelf v0.18.0 from GitHub. The default Ubuntu focal
# packages only provide the "0.10-2build1" version. We use patchelf to manipulate
# certain shared libraries during the wheel building process (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/build_pip_package.sh#L255-L262).
# When we use Patchelf versions <0.12, those shared libraries end up with a

- To be able to reliably use S3 multipart APIs feature of the SDKs without re-inventing the wheel of pre-signing the each URL in multipart API. This is very tedious to implement with all the scenarios of fault tolerance that's already implemented by the client SDK. The general client SDKs don't support multipart with presigned URLs.