assertThat(MediaType.parse("text/plain; charset =utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset= utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset = utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain;charset =utf-8").charset()).hasValue(UTF_8);
  }

  public void testGetCharset() {

    assertThat(iterable.firstMatch(equalTo("cool"))).hasValue("cool");
    assertThat(iterable.firstMatch(equalTo("pants"))).hasValue("pants");
    assertThat(iterable.firstMatch(Predicates.alwaysFalse())).isAbsent();
    assertThat(iterable.firstMatch(Predicates.alwaysTrue())).hasValue("cool");
  }

  private static final class IntegerValueOfFunction implements Function<String, Integer> {

    graph.putEdgeValue(1, 2, "A");
    assertThat(graph.edgeValue(EndpointPair.unordered(1, 2))).hasValue("A");
  }

  @Test
  public void edgeValue_undirected_backwards() {
    graph = ValueGraphBuilder.undirected().build();
    graph.putEdgeValue(1, 2, "A");
    assertThat(graph.edgeValue(EndpointPair.unordered(2, 1))).hasValue("A");
  }

  @Test
  public void edgeValue_undirected_mismatch() {

  }

  public void testTryFind() {
    Iterable<String> list = newArrayList("cool", "pants");
    assertThat(tryFind(list, equalTo("cool"))).hasValue("cool");
    assertThat(tryFind(list, equalTo("pants"))).hasValue("pants");
    assertThat(tryFind(list, Predicates.alwaysTrue())).hasValue("cool");
    assertThat(tryFind(list, Predicates.alwaysFalse())).isAbsent();
    assertCanIterateAgain(list);
  }

        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];
      if (input_shape.has_value()) {
        TF_ShapeAndTypeListSetShape(input_shapes, i, input_shape->data(),
                                    input_shape->size());
      } else {
        TF_ShapeAndTypeListSetUnknownShape(input_shapes, i);

  if (TF_GetCode(status) != TF_OK) return;

  // unwrap op_ and set step_id only if valid step id value was set.
  // Currently only required for non-TFRT use cases, e.g., EagerOp.
  if (step_id_.has_value()) {
    tensorflow::unwrap(op_.get())->SetStepId(step_id_.value());
  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);
  if (TF_GetCode(status) != TF_OK) {

      maybe_parallel_results(
          parallel_device.Execute(context, parallel_inputs, operation_name,
                                  attributes, expected_max_outputs, status));
  if (!maybe_parallel_results.has_value()) return result;
  std::vector<std::unique_ptr<ParallelTensor>> parallel_results(
      std::move(maybe_parallel_results.value()));
  std::vector<MaybeParallelTensorOwned> result_content;

  DLManagedTensor* dlmt = static_cast<DLManagedTensor*>(dlm);
  DLTensor* dl_tensor = &dlmt->dl_tensor;
  absl::optional<std::string> device_name =
      DeviceNameFromDlContext(dl_tensor->device, status);
  if (!device_name.has_value()) {
    status->status =
        tensorflow::errors::InvalidArgument("Unsupported Device Type");
    return nullptr;
  }
  TF_DataType dtype;
  absl::Status s = TfDataTypeFormDlDataType(dl_tensor->dtype, &dtype);