policy with `tf.data.experimental.service.ShardingPolicy` enum. It can
        be one of `OFF` (equivalent to today's `"parallel_epochs"` mode),
        `DYNAMIC` (equivalent to today's `"distributed_epoch"` mode), or one of
        the static sharding policies: `FILE`, `DATA`, `FILE_OR_DATA`, or `HINT`
        (corresponding to values of `tf.data.experimental.AutoShardPolicy`).

    check_success: (Function) function that takes one argument and returns a
      boolean. Should return True if the value provided is considered valid. May
      contain a complex error message if error_msg does not provide enough
      information. In that case, set suppress_default_error to True.
    error_msg: (String) String with one and only one '%s'. Formatted with each

# 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
  echo "More than one wheel file is present: moving the oldest to"

implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but
we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from

# We enable this in the nightly and release builds because before uploading the
# wheels, we install them in a virtual environment and run some smoke tests on
# it. TFCI Mac VMs only have one Python version installed so we need to install
# the other versions manually.
if [[ "${TFCI_MACOS_PYENV_INSTALL_ENABLE}" == 1 ]]; then
  # Install the necessary Python, unless it's already present

          include a readable copy of the attribution notices contained
          within such NOTICE file, excluding those notices that do not
          pertain to any part of the Derivative Works, in at least one
          of the following places: within a NOTICE text file distributed
          as part of the Derivative Works; within the Source form or
          documentation, if provided along with the Derivative Works; or,

    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);
    if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =

        "tensorflow.distribute.coordinator",
        "tensorflow.distribute.experimental.partitioners",
    ]

  def test_import_runtime(self):
    """Try to import all packages from api packages file one by one."""
    version = "v2"
    failed_packages = []

    logging.info("Try to import packages at runtime...")
    for package_name in self.api_packages_v2:
      # Convert package name to the short version:

          #Comma separated list of labels that can be assigned to PRs to exclude them from being marked as stale
          exempt-pr-labels: "override-stale"
          #Limit the No. of API calls in one run default value is 30.
          operations-per-run: 1000
          days-before-issue-stale: 7
          days-before-issue-close: 7
          stale-issue-label: "stale"

  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),
  # excluding dependencies and files that are known to be unneccessary.