TF_ColocateWith(desc_, feed1_);
  SetViaProto(desc_, {});
  FinishAndVerify(desc_, {});
}

TEST(CAPI, SavedModel) {
  // Load the saved model.
  const string saved_model_dir = tensorflow::GetDataDependencyFilepath(
      tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata",
                               "half_plus_two", "00000123"));

  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")
    if _os.path.exists(_plugin_dir):
      _ll.load_library(_plugin_dir)
      # Load Pluggable Device Library
      _ll.load_pluggable_device_library(_plugin_dir)

    DCHECK_EQ(nullptr, session);
    return nullptr;
  }
}

TF_Session* TF_LoadSessionFromSavedModel(
    const TF_SessionOptions* session_options, const TF_Buffer* run_options,
    const char* export_dir, const char* const* tags, int tags_len,
    TF_Graph* graph, TF_Buffer* meta_graph_def, TF_Status* status) {
// TODO(sjr): Remove the IS_MOBILE_PLATFORM guard. This will require ensuring

  mkdir -p $TFCI_OUTPUT_DIR/extra_wheels
  ls -t *.whl | tail -n +2 | xargs mv -t $TFCI_OUTPUT_DIR/extra_wheels
fi

# Repair wheels with auditwheel and delete the old one.
if [[ "$TFCI_WHL_AUDIT_ENABLE" == "1" ]]; then
  python3 -m auditwheel repair --plat "$TFCI_WHL_AUDIT_PLAT" --wheel-dir . *.whl
  # if the wheel is already named correctly, auditwheel won't rename it. so we

tfrun find ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun ./ci/official/utilities/rename_and_verify_wheels.sh

if [[ "$TFCI_ARTIFACT_STAGING_GCS_ENABLE" == 1 ]]; then
  # Note: -n disables overwriting previously created files.
  gsutil cp -n "$TFCI_OUTPUT_DIR"/*.whl "$TFCI_ARTIFACT_STAGING_GCS_URI"
fi

if [[ "$TFCI_WHL_BAZEL_TEST_ENABLE" == 1 ]]; then

    compat_api_versions = [
        1,
        2,
    ],
    compat_init_templates = [
        "compat_template_v1.__init__.py",
        "compat_template.__init__.py",
    ],
    output_dir = "_api/v1/",
    output_files = TENSORFLOW_API_INIT_FILES_V1,
    output_package = "tensorflow._api.v1",
    packages_to_ignore = ["tensorflow.python.framework.test_ops"],
    root_file_name = "v1.py",

    data from the dataset.
*   Adds support for dispatcher fault tolerance. To enable fault tolerance,
    configure a `work_dir` when running your dispatcher server and set
    `dispatcher_fault_tolerance=True`. The dispatcher will store its state to
    `work_dir`, so that on restart it can continue from its previous state after
    restart.
*   Adds support for sharing dataset graphs via shared filesystem instead of

        plugin_memory_allocate(num_entries * sizeof((*entries)[0])));
    for (int i = 0; i < num_entries; i++) {
      (*entries)[i] = strdup(dir_entries[i]->d_name);
      plugin_memory_free(dir_entries[i]);
    }
    plugin_memory_free(dir_entries);
  }

  return num_entries;
}

}  // namespace tf_posix_filesystem

static void ProvideFilesystemSupportFor(TF_FilesystemPluginOps* ops,

  print('Found CUDA %s in:' % config['cuda_version'])
  print('    %s' % config['cuda_library_dir'])
  print('    %s' % config['cuda_include_dir'])

  print('Found cuDNN %s in:' % config['cudnn_version'])
  print('    %s' % config['cudnn_library_dir'])
  print('    %s' % config['cudnn_include_dir'])

  if 'tensorrt_version' in config:
    print('Found TensorRT %s in:' % config['tensorrt_version'])

build:release_cpu_macos --config=avx_linux

# Base build configs for macOS
build:release_macos_base --action_env  DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
build:release_macos_base --define=no_nccl_support=true --output_filter=^$

# Ensure release_base is set on mac
build:release_macos_base --config=release_base