code: def mxnet_parse(architecture_name, test_input_path):
      from mmdnn.conversion.examples.mxnet.extractor import (
          mxnet_extractor,
      )
      from mmdnn.conversion.mxnet.mxnet_parser import MXNetParser
  
      # download model
      architecture_file, weight_file = mxnet_extractor.download(
          architecture_name, TestModels.cachedir
      )
  
      # get original model prediction result
      original_predict = mxnet_extractor.inference(
          architecture_name, None, TestModels.cachedir, test_input_path
      )
      del mxnet_extractor
  
      # original to IR
      import re
  
      if re.search(".", weight_file):
          weight_file = weight_file[:-7]
      prefix, epoch = weight_file.rsplit("-", 1)
      model = (architecture_file, prefix, epoch, [3, 224, 224])
  
      IR_file = (
          TestModels.tmpdir
          + "mxnet_"
          + architecture_name
          + "_converted"
      )
      parser = MXNetParser(model)
      parser.run(IR_file)
      del parser
      del MXNetParser
  
      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 5 for calling the TestModels obj's underlying member method code with example usage: obj.mxnet_parse(architecture_name, test_input_path) and returns: original_predict