code: def obfuscate_name(net_def):
      input_nodes = set()
      for input_node in net_def.input_info:
          input_nodes.add(input_node.name)
      output_nodes = set()
      for output_node in net_def.output_info:
          output_nodes.add(output_node.name)
      net_def_names_set = set()
      tensor_map = generate_tensor_map(
          net_def.tensors, net_def_names_set
      )
      in_out_map = generate_in_out_map(
          net_def.op, tensor_map, net_def_names_set
      )
      for t in net_def.tensors:
          if t.name not in input_nodes and t.name not in output_nodes:
              t.name = tensor_map[t.name]
      for op in net_def.op:
          for i in range(len(op.input)):
              if (op.input[i] not in input_nodes) and (
                  op.input[i] not in output_nodes
              ):
                  op.input[i] = in_out_map[op.input[i]]
          for i in range(len(op.output)):
              if op.output[i] not in output_nodes:
                  op.output[i] = in_out_map[op.output[i]]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import datetime
  import os
  import hashlib
  from jinja2 import Environment, FileSystemLoader
  from py_proto import mace_pb2
  from utils import device
  from utils import util
  from utils.util import mace_check
  from utils.util import MaceLogger
  from utils import config_parser
  from utils.config_parser import CPP_KEYWORDS
  from transform.base_converter import MaceKeyword
label_desc: Use image node_id 5 for calling a global function with example usage: obfuscate_name(net_def) without return types