CharMappingItem item3 = new CharMappingItem(3L, inputs3, "output");
        CharMappingItem item4 = new CharMappingItem(4L, inputs1, "different");

        // Same inputs and output should have same hash code
        assertEquals(item1.hashCode(), item2.hashCode());

        // Different inputs should have different hash code
        assertNotSame(item1.hashCode(), item3.hashCode());

     *
     * @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;

        }
    }

    /**
     * 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
     */

    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();
  }

  TF_Output* cond_inputs = new TF_Output[ninputs];
  TF_Output cond_output = {nullptr, -1};
  TF_Output* body_inputs = new TF_Output[ninputs];
  TF_Output* body_outputs = new TF_Output[ninputs];
  for (int i = 0; i < ninputs; ++i) body_outputs[i] = {nullptr, -1};
  const char* name = nullptr;

  for (int i = 0; i < ninputs; ++i) {
    // TODO(skyewm): prefix names with underscore (requires some plumbing)

     * @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;
        }
    }

  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);

	"strings"
	"text/scanner"

	"cmd/asm/internal/flags"
	"cmd/internal/objabi"
	"cmd/internal/src"
)

// Input is the main input: a stack of readers and some macro definitions.
// It also handles #include processing (by pushing onto the input stack)
// and parses and instantiates macro definitions.
type Input struct {
	Stack
	includes        []string
	beginningOfLine bool
	ifdefStack      []bool

        // 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);

  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};
    std::unique_ptr<TF_WhileParams> params(new TF_WhileParams(
        TF_NewWhile(func_graph_, &inputs[0], inputs.size(), s_)));