std::vector<const TensorSpecProto*> input_specs;
  TF_RETURN_IF_ERROR(FlattenSignature(input_signature, &input_specs));
  if (input_specs.size() + saved_concrete_function.bound_inputs_size() !=
      function_def->signature().input_arg_size()) {
    return errors::FailedPrecondition(
        "FunctionDef ", name, " has ",
        function_def->signature().input_arg_size(),

                                                 builder.getContext());

      int bound_input_base =
          func.getNumArguments() - concrete_function.bound_inputs_size();
      TF_ASSIGN_OR_RETURN(auto input_index_paths,
                          input_linearizer.GetLeafIndexPaths(
                              error_context + "in input signature: "));