code: def make_wresnet(
      nb_classes=10, input_shape=(None, 32, 32, 3), scope=None
  ):
      layers = [
          Input(),
          Conv2D(),  # the whole ResNet is basically created in this layer
          Flatten(),
          Linear(nb_classes),
          Softmax(),
      ]
  
      model = ResNet(layers, input_shape, scope)
      return model
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from cleverhans.serial import NoRefModel
label_desc: Use image node_id 8 for calling a global function with example usage: make_wresnet(nb_classes, input_shape, scope) and returns: model