if (fflush(posix_file->handle) != 0)
    TF_SetStatusFromIOError(status, errno, posix_file->filename);
}

static void Sync(const TF_WritableFile* file, TF_Status* status) {
  // For historical reasons, this does the same as `Flush` at the moment.
  // TODO(b/144055243): This should use `fsync`/`sync`.
  Flush(file, status);
}

static void Close(const TF_WritableFile* file, TF_Status* status) {

// Causes the calling thread to block till all ops dispatched in this executor
// have been executed. Note that "execution" here refers to kernel execution /
// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee
// that lower level device queues (like GPU streams) have been flushed.
//
// This call may not block for execution of ops enqueued concurrently with this
// call.

        handle->TypeString(), " tensor handle.");
    return nullptr;
  }
  tensorflow::Device* device(handle->device());
  if (device != nullptr) {
    status->status = device->Sync();
    if (!status->status.ok()) {
      return nullptr;
    }
  }
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return nullptr;
  }

*   `tf.distribute`:
    *   Support added for global sync `BatchNormalization` by using the newly
        added `tf.keras.layers.experimental.SyncBatchNormalization` layer. This
        layer will sync `BatchNormalization` statistics every step across all
        replicas taking part in sync training.
    *   Performance improvements for GPU multi-worker distributed training using