code: def predict(sess, batch_size, generator_tf, z):
      z_ = np.random.normal(0, 1, (batch_size, 100))
      return sess.run([generator_tf], {z: z_})[0]
  
file_path: adversarial-robustness-toolbox/utils/resources/create_inverse_gan_models.py
imports: import logging
  import time
  import os
  import numpy
  import tensorflow
  from art.utils import load_mnist
label_desc: Use image node_id 5 for calling a global function with example usage: predict(sess, batch_size, generator_tf, z) and returns: sess