code: def __init__(self, sess, model_saved_path, labels_path):
      image_shape_v1 = [224, 224, 3]
      self.image_value_range = (-117, 255 - 117)
      endpoints_v1 = dict(
          input="input:0",
          logit="softmax2_pre_activation:0",
          prediction="output2:0",
          pre_avgpool="mixed5b:0",
          logit_weight="softmax2_w:0",
          logit_bias="softmax2_b:0",
      )
      self.sess = sess
      super(GoogleNetWrapper_public, self).__init__(
          sess,
          model_saved_path,
          labels_path,
          image_shape_v1,
          endpoints_v1,
          scope="v1",
      )
      self.model_name = "GoogleNet_public"
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from abc import ABCMeta
  from abc import abstractmethod
  from six.moves import zip
  import numpy
  import six
  import tensorflow
  from google.protobuf import text_format
label_desc: Use image node_id 1 to create a new GoogleNetWrapper_public object from inherited base classes: PublicImageModelWrapper with example: obj = GoogleNetWrapper_public(sess, model_saved_path, labels_path)