bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status) {
  TFE_CustomDevice custom_device;
  custom_device.copy_tensor_to_device = &CopyToLoggingDevice;
  custom_device.copy_tensor_from_device = &CopyTensorFromLoggingDevice;
  custom_device.delete_device = &DeleteLoggingDevice;
  custom_device.execute = &LoggingDeviceExecute;

  return TensorHandlePtr(TFE_NewCustomDeviceTensorHandle(
      context, parallel_device_name.c_str(), t_released->dtype(), t_released,
      handle_methods, status));
}

// For TFE_CustomDevice::copy_tensor_to_device in the parallel device
// registration.
//
// Since this function is used to satisfy the TFE_CustomDevice C API,
// device_info is passed in using a C-style generic. It must always be a
// ParallelDevice.

typedef struct TFE_CustomDevice {
  int version = TFE_CUSTOM_DEVICE_VERSION;
  // Method to copy a tensor to the custom device.
  TFE_TensorHandle* (*copy_tensor_to_device)(TFE_Context* context,
                                             TFE_TensorHandle* tensor,
                                             TF_Status* status,
                                             void* device_info);

      ImmediateExecutionTensorHandle* handle,
      ImmediateExecutionTensorHandle** result) override {
    handle->Ref();
    TF_Status status;
    TFE_TensorHandle* result_handle = device_.copy_tensor_to_device(
        context_, tensorflow::wrap(handle), &status, info_);
    handle->Unref();
    if (!status.status.ok()) return status.status;
    *result = tensorflow::unwrap(result_handle);
    (*result)->Ref();