code: def evaluate(self, *args, **kwargs):
      if hasattr(tf.keras.backend, "get_session"):
          # Sets the Keras Session as default TF Session, so that the variable
          # in Keras subclassed model can be initialized correctly. The variable
          # is not created until the first call to the model, so the initialization
          # is not captured in the global_variables_initializer above.
          with tf.keras.backend.get_session().as_default():
              return super(AdversarialLossTest, self).evaluate(
                  *args, **kwargs
              )
      else:
          return super(AdversarialLossTest, self).evaluate(
              *args, **kwargs
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  from absl.testing import parameterized
  import neural_structured_learning.configs
  from neural_structured_learning.keras import adversarial_regularization
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 3 for calling the AdversarialLossTest obj's underlying member method code with example usage: obj.evaluate() and returns: super, super