code: def call(self, x):
      for layer in self.layers_obj:
          x = layer(x)
      return tf.reduce_mean(x, [1, 2])
  
file_path: cleverhans/tutorials/tf2/cifar10_tutorial.py
imports: import math
  import numpy
  import tensorflow
  import tensorflow_datasets
  from absl import app, flags
  from easydict import EasyDict
  from tensorflow.keras import Model
  from tensorflow.keras.layers import AveragePooling2D, Conv2D
  from cleverhans.tf2.attacks.projected_gradient_descent import projected_gradient_descent
  from cleverhans.tf2.attacks.fast_gradient_method import fast_gradient_method
label_desc: Use image node_id 2 for calling the CNN obj's underlying member method code with example usage: obj.call(x) and returns: tf