public class ProtwordsItem extends DictionaryItem {
    private final String input;

    private String newInput;

    public ProtwordsItem(final long id, final String input) {
        this.id = id;
        this.input = input;

        if (id == 0) {
            // create
            newInput = input;
        }
    }

    public String getNewInput() {
        return newInput;
    }

    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,
    std::unordered_map<const Node*, std::vector<int>>* input_nodes)
    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  input_tensors->reserve(ninputs);
  for (int i = 0; i < ninputs; ++i) {
    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

    TF_RETURN_WITH_CONTEXT_IF_ERROR(

    return newHasher(8).putLong(input).hash();
  }

  @Override
  public HashCode hashBytes(byte[] input) {
    return hashBytes(input, 0, input.length);
  }

  @Override
  public HashCode hashBytes(byte[] input, int off, int len) {
    checkPositionIndexes(off, off + len, input.length);
    return newHasher(len).putBytes(input, off, len).hash();
  }

  @Override
  public HashCode hashBytes(ByteBuffer input) {

        }
        assertImageSize(outputFile, 100, 66);

        imagePath = "thumbnail/600x400.jpg";
        try (ImageInputStream input = ImageIO.createImageInputStream(classLoader.getResourceAsStream(imagePath))) {
            generator.saveImage(input, outputFile);
        }
        assertImageSize(outputFile, 100, 66);

        imagePath = "thumbnail/400x400.png";

    }
    ImmutableList<SettableFuture<Long>> inputs = builder.build();
    ImmutableList<ListenableFuture<Long>> delegates = inCompletionOrder(inputs);

    for (ListenableFuture<?> delegate : delegates) {
      delegate.cancel(true);
    }

    for (ListenableFuture<?> input : inputs) {
      assertTrue(input.isDone());
    }
  }

    // 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) {
      if (input_tensors[i] == nullptr) continue;
      all_input_tensors.emplace_back();
      Tensor& input_tensor = all_input_tensors.back();
      status->status = TF_TensorToTensor(input_tensors[i], &input_tensor);

    }
    ImmutableList<SettableFuture<Long>> inputs = builder.build();
    ImmutableList<ListenableFuture<Long>> delegates = inCompletionOrder(inputs);

    for (ListenableFuture<?> delegate : delegates) {
      delegate.cancel(true);
    }

    for (ListenableFuture<?> input : inputs) {
      assertTrue(input.isDone());
    }
  }

  int num_inputs = TFE_OpGetFlatInputCount(other, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  for (int input_index = 0; input_index < num_inputs; ++input_index) {
    TFE_TensorHandle* input = TFE_OpGetFlatInput(other, input_index, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_OpAddInput(ret, input, status);

    "input": "aa--",
    "output": "aa--"
  },
  {
    "input": "a†--",
    "output": "xn--a---kp0a"
  },
  {
    "input": "ab--c",
    "output": "ab--c"
  },
  {
    "comment": "Label with leading hyphen",
    "input": "-x",
    "output": "-x"
  },
  {
    "input": "-†",
    "output": "xn----xhn"
  },
  {
    "input": "-x.xn--zca",
    "output": "-x.xn--zca"

      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        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];