*
     * @param id the unique identifier for this mapping item
     * @param inputs array of input character sequences that will be mapped to the output
     * @param output the output character sequence that inputs will be mapped to
     */
    public CharMappingItem(final long id, final String[] inputs, final String output) {
        this.id = id;
        this.inputs = inputs;

     * @param inputs  The input words.
     * @param outputs The output synonyms.
     */
    public SynonymItem(final long id, final String[] inputs, final String[] outputs) {
        this.id = id;
        this.inputs = inputs;
        this.outputs = outputs;

        if (id == 0) {
            // create
            newInputs = inputs;
            newOutputs = outputs;
        }
    }

        }
    }

    /**
     * Reloads the character mapping items from the provided input stream.
     * Parses mapping rules in the format: input1,input2,... => output
     *
     * @param updater the mapping updater to use for writing changes, or null for read-only reload
     * @param in the input stream to read the mapping data from
     */

void TF_AddInput(TF_OperationDescription* desc, TF_Output input) {
  desc->node_builder.Input(&input.oper->node, input.index);
}

void TF_AddInputList(TF_OperationDescription* desc, const TF_Output* inputs,
                     int num_inputs) {
  std::vector<NodeBuilder::NodeOut> input_list;
  input_list.reserve(num_inputs);
  for (int i = 0; i < num_inputs; ++i) {
    input_list.emplace_back(&inputs[i].oper->node, inputs[i].index);
  }

  TFE_DeleteContextOptions(opts);

  TFE_TensorHandle* input1 = TestMatrixTensorHandle(ctx);
  TFE_TensorHandle* input2 = TestMatrixTensorHandle(ctx);
  TFE_Op* identityOp = TFE_NewOp(ctx, "IdentityN", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_TensorHandle* inputs[] = {input1, input2};
  TFE_OpAddInputList(identityOp, inputs, 2, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

        // Test characters that need special encoding
        String input1 = "http://example.com/文档"; // Unicode characters
        String result1 = crawlingInfoHelper.generateId(input1);
        assertNotNull(result1);
        assertEquals(128, result1.length());

        String input2 = "http://example.com/path with spaces";
        String result2 = crawlingInfoHelper.generateId(input2);
        assertNotNull(result2);

//          automatic skipping of dummy input operations is performed.
//  ninputs - number of elements in `inputs` array
//  inputs - array of TF_Outputs that specify the inputs to the function.
//           If `ninputs` is zero (the function takes no inputs), `inputs`
//           can be null. The names used for function inputs are normalized

/**
 * A future whose value is derived from a collection of input futures.
 *
 * @param <InputT> the type of the individual inputs
 * @param <OutputT> the type of the output (i.e. this) future
 */
@GwtCompatible
@SuppressWarnings(
    // Whenever both tests are cheap and functional, it's faster to use &, | instead of &&, ||
    "ShortCircuitBoolean")
abstract class AggregateFuture<InputT extends @Nullable Object, OutputT extends @Nullable Object>

    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(
        fn_body->graph.IsValidOutputTensor(node, idx),
        "Encountered while processing input ", i, " into function '", fn_name,
        "'");

  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteStatus(s);
}

void CSession::SetInputs(
    std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs) {
  DeleteInputValues();
  inputs_.clear();
  for (const auto& p : inputs) {
    inputs_.emplace_back(TF_Output{p.first, 0});
    input_values_.emplace_back(p.second);
  }
}

void CSession::SetOutputs(std::initializer_list<TF_Operation*> outputs) {