code: def load_model(sess, model_name, model_path):
      saver = tf.train.import_meta_graph(
          os.path.join(model_path, model_name + ".meta")
      )
      saver.restore(sess, os.path.join(model_path, model_name))
  
      graph = tf.get_default_graph()
      generator_tf = graph.get_tensor_by_name("generator/output:0")
      image_to_encode_ph = graph.get_tensor_by_name(
          "image_to_encode_input:0"
      )
      encoder_tf = graph.get_tensor_by_name(
          "encoder_1/fully_connected/Relu:0"
      )
      z_ph = graph.get_tensor_by_name("z_input:0")
  
      return generator_tf, encoder_tf, z_ph, image_to_encode_ph
  
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 4 for calling a global function with example usage: load_model(sess, model_name, model_path) and returns: generator_tf,  encoder_tf,  z_ph,  image_to_encode_ph