Ian Lance Taylor <******@****.***> 1765577893 -0800

    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();
  }

        assertEquals(expectedSize, request.size());
    }

    @Test
    @DisplayName("Test size calculation with empty path")
    void testSizeWithEmptyPath() {
        request = new Smb2CreateRequest(mockConfig, "");

        int expectedSize = Smb2Constants.SMB2_HEADER_LENGTH + 56;
        expectedSize += 8; // size8(1) - empty name gets 1 byte
        expectedSize = ((expectedSize + 7) / 8) * 8; // size8(size)

    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()),

        // When
        int size = req.size();

        // Then
        int expectedSize = Smb2Constants.SMB2_HEADER_LENGTH + 24;
        int alignedSize = (expectedSize + 7) & ~7; // size8 alignment
        assertEquals(alignedSize, size);
    }

    @Test
    @DisplayName("Should write correct bytes to wire format with session binding")
    void testWriteBytesWireFormatWithSessionBinding() throws Exception {

	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)
		}

  std::vector<int64_t> input_ids(inputs.size());
  std::vector<tensorflow::DataType> input_dtypes(inputs.size());
  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {
    tape_tensors.push_back(TapeTensor(t));
  }

                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(
            () ->

  void* data = tensorflow::port::Malloc(value.length());
  value.copy(static_cast<char*>(data), value.length(), 0);
  buf->data = data;
  buf->length = value.length();
  buf->data_deallocator = [](void* data, size_t length) {
    tensorflow::port::Free(data);
  };
}

TFE_MonitoringStringGauge0* TFE_MonitoringNewStringGauge0(
    const char* name, TF_Status* status, const char* description) {

Joe Tsai <******@****.***> 1503528984 -0700