code: def pytorch_parse(architecture_name, test_input_path):
      from mmdnn.conversion.examples.pytorch.extractor import (
          pytorch_extractor,
      )
      from mmdnn.conversion.pytorch.pytorch_parser import (
          PytorchParser040,
      )
      from mmdnn.conversion.pytorch.pytorch_parser import (
          PytorchParser151,
      )
      import torch
  
      # download model
      architecture_file = pytorch_extractor.download(
          architecture_name, TestModels.cachedir
      )
  
      # get original model prediction result
      original_predict = pytorch_extractor.inference(
          architecture_name, architecture_file, test_input_path
      )
      del pytorch_extractor
  
      # get shape
      func = TestKit.preprocess_func["pytorch"][architecture_name]
  
      import inspect
  
      funcstr = inspect.getsource(func)
  
      pytorch_pre = funcstr.split("(")[0].split(".")[-1]
  
      if len(funcstr.split(",")) == 3:
          size = int(funcstr.split("path,")[1].split(")")[0])
  
      elif len(funcstr.split(",")) == 4:
          size = int(funcstr.split("path,")[1].split(",")[0])
  
      elif len(funcstr.split(",")) == 11:
          size = int(funcstr.split("path,")[1].split(",")[0])
  
      # original to IR
      IR_file = (
          TestModels.tmpdir
          + "pytorch_"
          + architecture_name
          + "_converted"
      )
      if torch.__version__ == "0.4.0":
          parser = PytorchParser040(architecture_file, [3, size, size])
      else:
          parser = PytorchParser151(architecture_file, [3, size, size])
      parser.run(IR_file)
      del parser
      del PytorchParser040
      del PytorchParser151
      return original_predict
  
imports: from __future__ import absolute_import
  from __future__ import print_function
  import os
  import sys
  import imp
  import numpy
  from mmdnn.conversion.examples.imagenet_test import TestKit
  import utils
  from utils import *
  from datetime import datetime
label_desc: Use image node_id 10 for calling the TestModels obj's underlying member method code with example usage: obj.pytorch_parse(architecture_name, test_input_path) and returns: original_predict