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;
}

  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;

  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) {