}
  std::vector<string> output_names(noutputs);
  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }
  TF_Run_Helper(s->session, nullptr, run_options, input_pairs, output_names,

              const std::vector<TF_Operation*>& inputs,
              const std::vector<TF_Operation*>& outputs,
              const std::vector<std::string>& output_names,
              bool expect_failure = false) {
    DefineT(num_opers, opers, ToOutput(inputs), ToOutput(outputs), output_names,
            expect_failure);
  }

  // Caller must delete[] the returned value
  static const char** ToArray(const std::vector<std::string>& strs) {

  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());
  ASSERT_EQ(TF_OK, TF_GetCode(s.get())) << TF_Message(s.get());
  ASSERT_NE(*func, nullptr);
}

  return ret;
}

TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,
                                                const char* output_name,
                                                TF_Status* status) {
  int ret = -1;
  status->status = tensorflow::unwrap(op)->OutputLength(output_name, &ret);
  return ret;
}

void TFE_Execute(TFE_Op* op, TFE_TensorHandle** retvals, int* num_retvals,

  const auto signature_def = signature_def_map.at("regress_x_to_y");

  const std::string input_name =
      signature_def.inputs().at(tensorflow::kRegressInputs).name();
  const std::string output_name =
      signature_def.outputs().at(tensorflow::kRegressOutputs).name();

  // Write {0, 1, 2, 3} as tensorflow::Example inputs.
  Tensor input(tensorflow::DT_STRING, TensorShape({4}));