code: def get_frozen_para(cls, architecture):
      frozenname = architecture + "_frozen"
      tensor_in = list(
          map(
              lambda x: x.split(":")[0],
              cls.architecture_map[frozenname]["tensor_in"],
          )
      )
      tensor_out = list(
          map(
              lambda x: x.split(":")[0],
              cls.architecture_map[frozenname]["tensor_out"],
          )
      )
      return (
          cls.architecture_map[frozenname]["filename"],
          cls.architecture_map[frozenname]["input_shape"],
          tensor_in,
          tensor_out,
      )
  
imports: from __future__ import absolute_import
  import os
  import tensorflow
  from tensorflow.contrib.slim.nets import vgg
  from tensorflow.contrib.slim.nets import inception
  from tensorflow.contrib.slim.nets import resnet_v1
  from tensorflow.contrib.slim.nets import resnet_v2
  from mmdnn.conversion.examples.tensorflow.models import inception_resnet_v2
  from mmdnn.conversion.examples.tensorflow.models import mobilenet_v1
  from mmdnn.conversion.examples.tensorflow.models import nasnet
  from mmdnn.conversion.examples.tensorflow.models.mobilenet import mobilenet_v2
  from mmdnn.conversion.examples.tensorflow.models import inception_resnet_v1
  from mmdnn.conversion.examples.tensorflow.models import test_rnn
  from mmdnn.conversion.examples.imagenet_test import TestKit
  from mmdnn.conversion.examples.extractor import base_extractor
  from mmdnn.conversion.common.utils import download_file
label_desc: Use image node_id 3 for calling the tensorflow_extractor obj's underlying member method code with example usage: obj.get_frozen_para(cls, architecture) and returns: cls,  cls,  tensor_in,  tensor_out