code: def add_input_output_tensor(multi_net_def, model_conf):
      if len(model_conf[ModelKeys.subgraphs]) == 1:
          model_conf = model_conf[ModelKeys.subgraphs][
              ModelKeys.default_graph
          ]
      for input_tensor in model_conf[ModelKeys.input_tensors]:
          multi_net_def.input_tensor.append(input_tensor)
      for output_tensor in model_conf[ModelKeys.output_tensors]:
          multi_net_def.output_tensor.append(output_tensor)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import copy
  import sys
  from micro_converter import MicroConverter
  from py_proto import mace_pb2
  from utils import config_parser
  from utils.config_parser import DataFormat
  from utils.config_parser import DeviceType
  from utils.config_parser import Platform
  from utils import util
  from utils.util import mace_check
  from utils.config_parser import normalize_model_config
  from utils.config_parser import ModelKeys
  from utils.convert_util import merge_params
  from transform import base_converter
  from transform import transformer
  from visualize import visualize_model
label_desc: Use image node_id 3 for calling a global function with example usage: add_input_output_tensor(multi_net_def, model_conf) without return types