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.flat<tstring>()(i) = example.SerializeAsString();
  }

  const tensorflow::string input_op_name(
      tensorflow::ParseTensorName(input_name).first);
  TF_Operation* input_op =
      TF_GraphOperationByName(graph, input_op_name.c_str());
  ASSERT_TRUE(input_op != nullptr);
  Status status;
  csession.SetInputs({{input_op, TF_TensorFromTensor(input, &status)}});

    // Create loop: while (input1 < input2) input1 += input2 + 1
    TF_Operation* less_than = LessThan(
        params->cond_inputs[0], params->cond_inputs[1], params->cond_graph, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    params->cond_output = {less_than, 0};

    TF_Operation* add1 = Add(params->body_inputs[0], params->body_inputs[1],

  while var is None:
    user_input_origin = get_input(question)
    user_input = user_input_origin.strip().lower()
    if user_input == 'y':
      print(yes_reply)
      var = True
    elif user_input == 'n':
      print(no_reply)
      var = False
    elif not user_input:
      if enabled_by_default:
        print(yes_reply)
        var = True
      else:

//   TF_Output concat_dim_input = {...};
//   TF_AddInput(desc, concat_dim_input);
//   TF_Output values_inputs[5] = {{...}, ..., {...}};
//   TF_AddInputList(desc, values_inputs, 5);

// For inputs that take a single tensor.
TF_CAPI_EXPORT extern void TF_AddInput(TF_OperationDescription* desc,
                                       TF_Output input);

// For inputs that take a list of tensors.

    outs = ["tensorflow_filtered_def_file.def"],
    cmd = select({
        "//tensorflow:windows": """
              $(location @local_config_def_file_filter//:def_file_filter) \\
              --input $(location :tensorflow_def_file) \\
              --output $@
          """,
        "//conditions:default": "touch $@",  # Just a placeholder for Unix platforms
    }),

/// `const`.
///
/// For consistency, the arguments on all these functions follow the same
/// pattern: first we have the opaque pointer argument ("this" above), then the
/// input arguments, then the in-out arguments (if any) and we finish the
/// argument list with the out arguments. We only use the return type for an out
/// parameter if that is a plain C type, as this ensures ABI compatibility