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  return nullptr;
}

void TFE_ContextAddFunctionDef(TFE_Context* ctx,
                               const char* serialized_function_def, size_t size,
                               TF_Status* status) {
  tensorflow::FunctionDef function_def;
  if (!function_def.ParseFromArray(serialized_function_def, size)) {
    status->status =
        tensorflow::errors::InvalidArgument("Invalid FunctionDef proto");
    return;
  }

  private static final int BYTE_MAX_SIZE = 1 << Byte.SIZE; // 2^8 = 256
  private static final int BYTE_MASK = (1 << Byte.SIZE) - 1; // 2^8 - 1 = 255

  private static final int SHORT_MAX_SIZE = 1 << Short.SIZE; // 2^16 = 65_536
  private static final int SHORT_MASK = (1 << Short.SIZE) - 1; // 2^16 - 1 = 65_535

  /**
   * Returns the power of 2 hashtable size required to hold the expected number of items or the

    assertEquals(expectedSize, multimap.size());

    int size = 0;
    for (Entry<K, V> entry : multimap.entries()) {
      assertTrue(multimap.containsEntry(entry.getKey(), entry.getValue()));
      size++;
    }
    assertEquals(expectedSize, size);

    int size2 = 0;
    for (Entry<K, Collection<V>> entry2 : multimap.asMap().entrySet()) {
      size2 += entry2.getValue().size();
    }
    assertEquals(expectedSize, size2);

Joe Tsai <******@****.***> 1446603151 -0800

  private static final int BYTE_MAX_SIZE = 1 << Byte.SIZE; // 2^8 = 256
  private static final int BYTE_MASK = (1 << Byte.SIZE) - 1; // 2^8 - 1 = 255

  private static final int SHORT_MAX_SIZE = 1 << Short.SIZE; // 2^16 = 65_536
  private static final int SHORT_MASK = (1 << Short.SIZE) - 1; // 2^16 - 1 = 65_535

  /**
   * Returns the power of 2 hashtable size required to hold the expected number of items or the

    std::vector<TF_Output> tf_outputs(inputs.size());
    for (int i = 0; i < inputs.size(); i++) {
      GraphTensor* t = dyn_cast<GraphTensor>(inputs[i]);
      if (!t) {
        return tensorflow::errors::InvalidArgument(
            "Unable to cast input to GraphTensor");
      }
      tf_outputs[i] = t->output_;
    }
    TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
    return absl::OkStatus();
  }

    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  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()),

	tgtCtnt, tgtOk := nextObject(tgtCh)

	var srcEOF, tgtEOF bool

	srcSha256 := sha256.New()
	tgtSha256 := sha256.New()

	for {
		srcSha256.Reset()
		tgtSha256.Reset()

		srcEOF = !srcOk
		tgtEOF = !tgtOk

		// No objects from source AND target: Finish
		if srcEOF && tgtEOF {
			break
		}

		if !srcEOF && srcCtnt.Err != nil {
			log.Fatal(srcCtnt.Err)
		}

                CollectSpliterators.flatMap(
                    Arrays.spliterator(new String[] {"abc", "", "de", "f", "g", ""}),
                    (String str) -> charactersOf(str).spliterator(),
                    Spliterator.SIZED | Spliterator.DISTINCT | Spliterator.NONNULL,
                    7))
        .expect('a', 'b', 'c', 'd', 'e', 'f', 'g');
  }

  public void testFlatMap_nullStream() {
    SpliteratorTester.of(
            () ->