return {};
  }
  const auto& fdef_lib = gdef.library();
  if (fdef_lib.gradient_size() > 0) {
    status->status = tensorflow::errors::Internal(
        "GradientDef is not supported in reading Dataset related functions: ",
        text_proto);
    return {};
  }
  std::vector<UniqueFuncPtr> ret;
  for (const FunctionDef& fdef : fdef_lib.function()) {
    // Make a copy so that we can mutate it.

    * Introduced API `tf.saved_model.experimental.read_fingerprint(export_dir)` for reading the fingerprint of a SavedModel.
* `tf.random`
  * Added non-experimental aliases for `tf.random.split` and `tf.random.fold_in`, the experimental endpoints are still available so no code changes are necessary.