protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    Status s = StatusFromTF_Status(status.get());
    CHECK_EQ(errors::OK, s.code()) << s.message();
  }

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }
  bool UseFunction() const { return std::get<2>(GetParam()); }
};

if [[ "${TFCI_MACOS_PYENV_INSTALL_ENABLE}" == 1 ]]; then
  # Install the necessary Python, unless it's already present
  pyenv install -s "$TFCI_PYTHON_VERSION"
  pyenv local "$TFCI_PYTHON_VERSION"
  # Do a sanity check to make sure that we using the correct Python version
  python --version
fi

# TFCI Mac VM images do not have twine installed by default so we need to

  // context and TF server for multi-client execution.
  virtual Status EnableCollectiveOps(const ServerDef& server_def) = 0;

  // Set a distributed manager that helps set up, update, and check liveness
  // of member tasks in the cluster.
  virtual void SetDistributedManager(
      std::unique_ptr<ImmediateExecutionDistributedManager> distributed) = 0;

  TF_VLog(1, "Successful read of %s @ %u of size: %u", path.c_str(), offset,
          read);
  stream.read(buffer, read);
  read = stream.gcount();
  if (read < buffer_size) {
    // Check stat cache to see if we encountered an interrupted read.
    tf_gcs_filesystem::GcsFileStat stat;
    if (gcs_file->stat_cache->Lookup(path, &stat)) {
      if (offset + read < stat.base.length) {

# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.
check_deps(
    name = "cuda_plugins_check_deps",
    disallowed_deps = if_static(
        [],
        otherwise = [
            "@local_xla//xla/stream_executor/cuda:all_runtime",
            "@local_xla//xla/stream_executor/cuda:cuda_driver",

}

@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" \
    "//tensorflow/tools/lib_package:clicenses_generate"
}

                                 const int64_t* dims, int num_dims) {
  DCHECK(index >= 0 && index < shape_list->num_items);
  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];

    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    name: "validate"
    runs-on: ubuntu-latest
    steps:
      - name: Check out a copy of the repository
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0

      - name: Check whether the citation metadata from CITATION.cff is valid
        uses: citation-file-format/cffconvert-github-action@4cf11baa70a673bfdf9dad0acc7ee33b3f4b6084 # v2.0.0

    CHECK_EQ(errors::OK, s.code()) << s.message();
  }
};

class PassThroughGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    CHECK_EQ(grad_outputs.size(), 1);
    CHECK_EQ(grad_inputs.size(), 1);

  if stderr is None:
    stderr = sys.stdout
  if allow_non_zero:
    try:
      output = subprocess.check_output(cmd, stderr=stderr)
    except subprocess.CalledProcessError as e:
      output = e.output
  else:
    output = subprocess.check_output(cmd, stderr=stderr)
  return output.decode('UTF-8').strip()


def cygpath(path):
  """Convert path from posix to windows."""