tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
  # replace tensorflow to tf_nightly in the wheel name
  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"
fi

tfrun bazel build $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_ARGS
tfrun find ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;

# This script is aware of TFCI_ variables, so it doesn't need any arguments.
# Puts new wheel through auditwheel to rename and verify it, deletes the old
# one, checks the filesize, and then ensures the new wheel is installable.
set -euxo pipefail

cd "$TFCI_OUTPUT_DIR"

# Move extra wheel files somewhere out of the way. This script
# expects just one wheel file to exist.
if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then

          pip install -r requirements-tests.txt
      - name: Run source distribution tests
        run: |
          cd dist/fastapi-*/
          bash scripts/test.sh
      - name: Build wheel distribution
        run: |
          cd dist
          pip wheel --no-deps fastapi-*.tar.gz
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}

test:linux_cpu_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:linux_cpu_wheel_test --config=linux_cpu_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# CUDA WHEEL

      - name: Checkout repository for releases (skipped for nightly)
        if: ${{ github.event_name == 'push' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
      - name: Build and test pip wheel
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tensorflow_cpu_aws' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_cpu_aws'

}

@test "Pip package generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow/tools/pip_package:wheel" \
    "//tensorflow/tools/pip_package:licenses"
}

@test "Libtensorflow generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow:libtensorflow.so" \

# TODO(b/304751256): Adjust the numpy pin to a single version, when ready
numpy ~= 1.23.5 ; python_version <= "3.11"
numpy ~= 1.26.0 ; python_version >= "3.12"
wheel ~= 0.41.2
h5py >= 3.10.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0

# Install tensorboard, and keras

TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=tensorflow/build:2.16-python${TFCI_PYTHON_VERSION}
TFCI_DOCKER_PULL_ENABLE=1

# Note: this is not set to "--cpu", because that changes the package name
# to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow"
# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64"

source ci/official/envs/linux_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M