code: def test_googlenet_v2_slim(self):
      url = "https://storage.googleapis.com/download.tensorflow.org/models/inception_v2_2016_08_28_frozen.pb.tar.gz"
      tf_model_dir = _download_file(url=url)
      tf_model_path = os.path.join(
          TMP_MODEL_DIR, "inception_v2_2016_08_28_frozen.pb"
      )
  
      mlmodel_path = os.path.join(
          TMP_MODEL_DIR, "inception_v2_2016_08_28_frozen.mlmodel"
      )
      mlmodel = tf_converter.convert(
          tf_model_path=tf_model_path,
          mlmodel_path=mlmodel_path,
          output_feature_names=["InceptionV2/Predictions/Softmax:0"],
          input_name_shape_dict={"input:0": [1, 244, 224, 3]},
          image_input_names=["input:0"],
          red_bias=-1,
          green_bias=-1,
          blue_bias=-1,
          image_scale=2.0 / 255.0,
      )
  
      # Test predictions on an image
      self._test_coreml_model_image_input(
          tf_model_path=tf_model_path,
          coreml_model=mlmodel,
          input_tensor_name="input:0",
          output_tensor_name="InceptionV2/Predictions/Softmax:0",
          img_size=224,
      )
  
imports: import unittest
  import urllib
  import os
  import tarfile
  import zipfile
  import numpy
  import PIL.Image
  import tensorflow
  from tensorflow.core.framework import graph_pb2
  import tfcoreml
label_desc: Use image node_id 5 for calling the TestModels obj's underlying member method code with example usage: obj.test_googlenet_v2_slim() without return types