.that(percentiles().index(index).computeInPlace(dataset))
          .isWithin(ALLOWED_ERROR)
          .of(expectedLargeDatasetPercentile(index));
    }

    // Assert that the dataset contains the same elements after the in-place computation (although
    // they may be reordered). We only do this for one index rather than for all indexes, as it is
    // quite expensive (quadratic in the size of PSEUDORANDOM_DATASET).

}

// Recycle is a no-op.
func (NoPayload) Recycle() {}

// ArrayOf wraps an array of Messagepack compatible objects.
type ArrayOf[T RoundTripper] struct {
	aPool sync.Pool // Arrays
	ePool sync.Pool // Elements
}

// NewArrayOf returns a new ArrayOf.
// You must provide a function that returns a new instance of T.
func NewArrayOf[T RoundTripper](newFn func() T) *ArrayOf[T] {
	return &ArrayOf[T]{

NOTE: Due to the project size, the very first import can take a while and IntelliJ might become unresponsive for several seconds during this period.

      new ImmutableRangeMap<>(ImmutableList.<Range<Comparable<?>>>of(), ImmutableList.of());

  /**
   * Returns a {@code Collector} that accumulates the input elements into a new {@code
   * ImmutableRangeMap}. As in {@link Builder}, overlapping ranges are not permitted.
   *
   * @since 33.2.0 (available since 23.1 in guava-jre)
   */
  @SuppressWarnings("Java7ApiChecker")

  static final String ERROR_SELF_LOOP = "self-loops are not allowed";
  static final String ERROR_EDGE_NOT_IN_GRAPH =
      "Should not be allowed to pass an edge that is not an element of the graph.";
  static final String ERROR_ADDED_SELF_LOOP = "Should not be allowed to add a self-loop edge.";
  static final String ERROR_ADDED_PARALLEL_EDGE = "Should not be allowed to add a parallel edge.";

    this(multimap.keySet().size());
    putAll(multimap);
  }

  /**
   * Adds a new node for the specified key-value pair before the specified {@code nextSibling}
   * element, or at the end of the list if {@code nextSibling} is null. Note: if {@code nextSibling}
   * is specified, it MUST be for a node for the same {@code key}!
   */
  @CanIgnoreReturnValue
  private Node<K, V> addNode(

        * [`tf.data.Dataset.ragged_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ragged_batch), which batches elements of `tf.data.Dataset`s into `tf.RaggedTensor`s.
        * [`tf.data.Dataset.sparse_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#sparse_batch), which batches elements of `tf.data.Dataset`s into `tf.sparse.SparseTensor`s.

## Bug Fixes and Other Changes

*   `tf.image`

  // TODO(user): Write more tests for memory retention.
  @ForOverride
  @OverridingMethodsMustInvokeSuper
  void releaseResources(ReleaseResourcesReason reason) {
    checkNotNull(reason);
    /*
     * All elements of `futures` are completed, or this future has already completed and read
     * `futures` into a local variable (in preparation for propagating cancellation to them). In

    @Override
    ImmutableSortedSet<C> headSetImpl(C toElement, boolean inclusive) {
      return subSet(Range.upTo(toElement, BoundType.forBoolean(inclusive)));
    }

    @Override
    ImmutableSortedSet<C> subSetImpl(
        C fromElement, boolean fromInclusive, C toElement, boolean toInclusive) {
      if (!fromInclusive && !toInclusive && Range.compareOrThrow(fromElement, toElement) == 0) {
        return ImmutableSortedSet.of();

  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {
    // Note that we take the address of the elements in `all_input_tensors`
    // below. Allocate enough space so that no reallocation happens, which will
    // make the pointers invalid.
    all_input_tensors.reserve(num_inputs);
    for (int i = 0; i < num_inputs; ++i) {