handle_data.set_is_set(true);
  {
    mutex_lock l(graph->mu);
    tensorflow::shape_inference::InferenceContext* ic =
        graph->refiner.GetContext(node);
    CHECK(ic != nullptr);                       // Crash OK
    CHECK_LT(output.index, ic->num_outputs());  // Crash OK
    const auto* shapes_and_types =
        ic->output_handle_shapes_and_types(output.index);
    if (shapes_and_types == nullptr) return nullptr;

  // a different TFE context for each thread of execution (for running graph
  // functions, and their send/recvs corountines).
  config.set_inter_op_parallelism_threads(1);

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(config, ret));
  return ret;
}

TF_Buffer* TF_CreateRunOptions(unsigned char enable_full_trace) {
  tensorflow::RunOptions options;
  if (enable_full_trace) {

  TF_DeviceList* device_list = list.get();

  CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  const int num_devices = TF_DeviceListCount(device_list);
  LOG(INFO) << "There are " << num_devices << " devices.";
  for (int i = 0; i < num_devices; ++i) {
    const char* device_name = TF_DeviceListName(device_list, i, s);
    CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);