// TensorHandles we've computed into a single parallel TensorHandle.
  std::vector<std::unique_ptr<ParallelTensor>> per_device_outputs;
  per_device_outputs.reserve(first_op_output_count);
  for (int i = 0; i < first_op_output_count; ++i) {
    std::vector<TensorHandlePtr> components;
    components.reserve(underlying_devices_.size());
    for (int j = 0; j < underlying_devices_.size(); ++j) {

   * Array.newInstance(type, len))}.
   *
   * @param type the type of the elements
   * @return a newly-allocated array into which all the elements of this fluent iterable have been
   *     copied
   */
  @GwtIncompatible // Array.newArray(Class, int)
  public final E[] toArray(Class<@NonNull E> type) {
    return Iterables.<E>toArray(getDelegate(), type);
  }

  /**

              @Override
              protected void finalize() {
                finalizerRan.countDown();
              }
            });

    // Don't copy this into your own test!
    // Use e.g. awaitClear or await(CountDownLatch) instead.
    GcFinalization.awaitFullGc();

    // If this test turns out to be flaky, add a second call to awaitFullGc()

)

// Config represents the heal settings.
type Config struct {
	// Delay is the sleep multiplier.
	Delay float64 `json:"delay"`

	// Sleep always or based on incoming S3 requests.
	IdleMode int32 // 0 => on, 1 => off

	// Alert upon this many excess object versions
	ExcessVersions int64 // 100

	// Alert upon this many excess sub-folders per folder in an erasure set.
	ExcessFolders int64 // 50000

}

// TransitionDays is a type alias to unmarshal Days in Transition
type TransitionDays int

// UnmarshalXML parses number of days from Transition and validates if
// >= 0
func (tDays *TransitionDays) UnmarshalXML(d *xml.Decoder, startElement xml.StartElement) error {
	var days int
	err := d.DecodeElement(&days, &startElement)
	if err != nil {
		return err
	}

	if days < 0 {

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests

			objs:   3,
			oSizes: sizeHistogram{0: 1, 1: 2},
		},
		{
			path:   "bucket/newfolder",
			size:   5,
			objs:   3,
			oSizes: sizeHistogram{0: 3},
		},
		{
			// Compacted into bucket/dir1
			path:  "bucket/dir1/dira",
			isNil: true,
		},
		{
			path:  "bucket/nonexistying",
			isNil: true,
		},
	}

	for _, w := range want {
		t.Run(w.path, func(t *testing.T) {

                (layout != null) ? layout.getClass().getSimpleName() : "legacy");

        /*
         * NOTE: "invoker:install" vs "appassembler:assemble": Both mojos use the artifact installer to put an artifact
         * into a repository. In the first case, the result needs to be a proper local repository that one can use for
         * local artifact resolution. In the second case, the result needs to precisely obey the path information of the

        options.addOption(Option.builder(Character.toString(NON_RECURSIVE))
                .longOpt("non-recursive")
                .desc(
                        "Do not recurse into sub-projects. When used together with -pl, do not recurse into sub-projects of selected aggregators")
                .build());
        options.addOption(Option.builder(Character.toString(UPDATE_SNAPSHOTS))
                .longOpt("update-snapshots")

                                                 const TF_DataType* values,
                                                 int num_values);
TF_CAPI_EXPORT extern void TFE_OpSetAttrShapeList(
    TFE_Op* op, const char* attr_name, const int64_t** dims,
    const int* num_dims, int num_values, TF_Status* out_status);
TF_CAPI_EXPORT extern void TFE_OpSetAttrFunctionList(TFE_Op* op,