const std::vector<string>& output_names,
               bool expect_failure = false) {
    ASSERT_EQ(func_, nullptr);
    const char** output_names_ptr = ToArray(output_names);
    func_ = TF_GraphToFunction(func_graph_, func_name_, false, num_opers,
                               num_opers == -1 ? nullptr : opers.data(),
                               inputs.size(), inputs.data(), outputs.size(),

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,

  TF_Function* tf_function = new TF_Function();
  tf_function->record = new tensorflow::FunctionRecord(
      std::move(fdef), std::move(stack_traces), false);

  return tf_function;
}

TF_Function* TF_GraphToFunction(const TF_Graph* fn_body, const char* fn_name,
                                unsigned char append_hash_to_fn_name,
                                int num_opers, const TF_Operation* const* opers,

    const TF_FunctionOptions* opts, const char* description, TF_Status* status);

// Similar to TF_GraphToFunction but allows specifying control outputs of the
// function.
//
//  The arguments of TF_GraphToFunction have the same meaning, but the new
//  arguments are as follows:
//
//    ncontrol_outputs: Number of control outputs of the function.