size_t size = results.missing_unused_input_map_keys.size();
  tf_results->missing_unused_key_names.resize(size);
  tf_results->missing_unused_key_indexes.resize(size);

  for (int i = 0; i < size; ++i) {
    TensorId id = results.missing_unused_input_map_keys[i];
    tf_results->missing_unused_key_names_data.emplace_back(id.first);
    tf_results->missing_unused_key_names[i] =

  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());
  }
  return SetAttrStringList(attr_name,
                           reinterpret_cast<const void**>(raw_strs.data()),
                           lengths.data(), values.size());
}

namespace internal {

      sort(entries, Range.<K>rangeLexOrdering().onKeys());
      ImmutableList.Builder<Range<K>> rangesBuilder = new ImmutableList.Builder<>(entries.size());
      ImmutableList.Builder<V> valuesBuilder = new ImmutableList.Builder<>(entries.size());
      for (int i = 0; i < entries.size(); i++) {
        Range<K> range = entries.get(i).getKey();
        if (i > 0) {
          Range<K> prevRange = entries.get(i - 1).getKey();

    @CanIgnoreReturnValue
    public Builder addAll(LongStream stream) {
      Spliterator.OfLong spliterator = stream.spliterator();
      long size = spliterator.getExactSizeIfKnown();
      if (size > 0) { // known *and* nonempty
        ensureRoomFor(Ints.saturatedCast(size));
      }
      spliterator.forEachRemaining((LongConsumer) this::add);
      return this;
    }

    /**

     */
    @CanIgnoreReturnValue
    public Builder addAll(IntStream stream) {
      Spliterator.OfInt spliterator = stream.spliterator();
      long size = spliterator.getExactSizeIfKnown();
      if (size > 0) { // known *and* nonempty
        ensureRoomFor(Ints.saturatedCast(size));
      }
      spliterator.forEachRemaining((IntConsumer) this::add);
      return this;
    }

    /**

      static_cast<bool>(should_enable);
}

void TF_SetXlaMinClusterSize(int size) {
  tensorflow::MarkForCompilationPassFlags* flags =
      tensorflow::GetMarkForCompilationPassFlags();
  flags->tf_xla_min_cluster_size = size;
}

TF_Buffer* TF_CreateConfig(unsigned char enable_xla_compilation,
                           unsigned char gpu_memory_allow_growth,

- Choice of erasure set size is automatic based on the number of drives available, let's say for example if there are 32 servers and 32 drives which is a total of 1024 drives. In this scenario 16 becomes the erasure set size. This is decided based on the greatest common divisor (GCD) of acceptable erasure set sizes ranging from *4 to 16*.

        .sortedBy { -it.totalTime }
    return splitIntoBuckets(
        LinkedList(testProjectDurations),
        TestProjectDuration::totalTime,
        { largeElement: TestProjectDuration, size: Int -> largeElement.split(size) },
        { list: List<TestProjectDuration> -> MultipleTestProjectBucket(list) },
        numberOfBuckets,
        MAX_TEST_PROJECTS_PER_BUCKET,

   * @since 2.0
   */
  public static MappedByteBuffer map(File file, MapMode mode, long size) throws IOException {
    checkArgument(size >= 0, "size (%s) may not be negative", size);
    return mapInternal(file, mode, size);
  }

  private static MappedByteBuffer mapInternal(File file, MapMode mode, long size)
      throws IOException {
    checkNotNull(file);
    checkNotNull(mode);

 * ```
 * WWW-Authenticate: Digest ,foo=bar
 * WWW-Authenticate: Digest ,foo
 * ```
 */
fun Headers.parseChallenges(headerName: String): List<Challenge> {
  val result = mutableListOf<Challenge>()
  for (h in 0 until size) {
    if (headerName.equals(name(h), ignoreCase = true)) {
      val header = Buffer().writeUtf8(value(h))
      try {
        header.readChallengeHeader(result)
      } catch (e: EOFException) {