const std::string filename_tensor_name = FindFilePrefixTensorName(graph_def);
  const std::string restore_op_name =
      GetNodeName(control_ret_node_names, kTfSavedModelInitializerRestoreType);
  const std::string save_node_name =
      GetNodeName(control_ret_node_names, kTfQuantSaveOpName);

  const std::vector<absl::string_view> fields = {
      filename_tensor_name, restore_op_name, save_node_name};

  // SaverDef including the information required for saving and restoring
  // variables. This field is not set if there are no variables in the exported
  // graph. If set, the fields `version`, `filename_tensor_name`,
  // `restore_op_name` and `save_tensor_name` are populated.
  SaverDef saver_def = 10;

  ASSERT_TRUE(TextFormat::ParseFromString(
      R"pb(filename_tensor_name: "my_file")pb", &saver_def));

  const ExportedModel exported_model = CreateExportedModelFromGraphDef(
      GraphDef(), /*init_node_name=*/"", /*checkpoint_dir=*/"", saver_def,
      /*function_aliases=*/{}, /*asset_file_defs=*/{});
  EXPECT_THAT(exported_model.saver_def().filename_tensor_name(), "my_file");
}

// Creates a new `SaverDef` instance, which contains information regarding
// checkpoint saving and restoring. This function returns a `SaverDef` instance
// with four fields populated: `version`, `filename_tensor_name`,
// `restore_op_name` and `save_tensor_name`. For valid quantized `graph_def` and
// `control_ret_node_names`, it should be able to retrieve the last three fields
// if there is at lest one variable in the graph.
//

    TF_RETURN_IF_ERROR(RunRestore(run_options, export_dir,
                                  meta_graph.saver_def().restore_op_name(),
                                  meta_graph.saver_def().filename_tensor_name(),
                                  asset_file_defs, session->get()));
  }
  // Record walltime spent in restoring graph from disk, but postpone metric
  // increments until graph init finishes.

    }
    node {
      name: "save/restore_all"
      op: "NoOp"
      input: "^save/restore_shard"
    }
    versions {
      producer: 23
    }
  }
  saver_def {
    filename_tensor_name: "save/Const:0"
    save_tensor_name: "save/Identity:0"
    restore_op_name: "save/restore_all"
    max_to_keep: 5
    sharded: true
    keep_checkpoint_every_n_hours: 10000.0
    version: V2
  }

                                           kSavedModelVariablesFilename)));
    variable_and_assets.push_back(
        {input_.meta_graph_def().saver_def().filename_tensor_name(),
         variable_filename_op});
    variable_and_assets.insert(variable_and_assets.end(), assets.begin(),
                               assets.end());

    const auto& restore_op_name =

              }
            }
          }
        }
      }
    }
    versions {
      producer: 1520
      min_consumer: 12
    }
  }
  saver_def {
    filename_tensor_name: "saver_filename:0"
    save_tensor_name: "StatefulPartitionedCall:0"
    restore_op_name: "StatefulPartitionedCall_1"
    version: V2
  }
  collection_def {
    key: "saved_model_main_op"