LoggingDevice* dev = reinterpret_cast<LoggingDevice*>(device_info);
  TFE_TensorHandle* t = TFE_TensorHandleCopyToDevice(
      tensor, context, dev->underlying_device.c_str(), status);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  auto dst = std::make_unique<LoggedTensor>(t);
  *(dev->arrived_flag) = true;
  return MakeLoggedTensorHandle(context, dev->device_name, std::move(dst),

  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return nullptr;
  }

  std::vector<int64_t> dev_dims = TensorShapeAsVector(*handle, &status->status);
  if (!status->status.ok()) {
    return nullptr;
  }
  return new TFE_TensorDebugInfo(dev_dims);
}

TF_CAPI_EXPORT extern void TFE_DeleteTensorDebugInfo(
    TFE_TensorDebugInfo* debug_info) {
  delete debug_info;
}

  bool has_gpu0 = false;
  bool has_gpu1 = false;
  for (int i = 0; i < num_devices; ++i) {
    const char* dev = TF_DeviceListName(devices, i, status.get());
    ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
    string device_name(dev);
    if (device_name.find("GPU:0") != string::npos) {
      has_gpu0 = true;
    }
    if (device_name.find("GPU:1") != string::npos) {

  for (int i = 0; i < num_devices; ++i) {
    const string dev_type(TF_DeviceListType(devices, i, status.get()));
    CHECK_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
    const string dev_name(TF_DeviceListName(devices, i, status.get()));
    CHECK_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
    if (dev_type == device_type) {
      *device_name = dev_name;