code: def get_gan_inverse_gan_ft():
      import tensorflow as tf
  
      from utils.resources.create_inverse_gan_models import (
          build_gan_graph,
          build_inverse_gan_graph,
      )
  
      if tf.__version__[0] == "2":
          return None, None, None
      else:
          lr = 0.0002
          latent_enc_len = 100
  
          (
              gen_tf,
              z_ph,
              gen_loss,
              gen_opt_tf,
              disc_loss_tf,
              disc_opt_tf,
              x_ph,
          ) = build_gan_graph(lr, latent_enc_len)
  
          (
              enc_tf,
              image_to_enc_ph,
              latent_enc_loss,
              enc_opt,
          ) = build_inverse_gan_graph(lr, gen_tf, z_ph, latent_enc_len)
  
          sess = tf.Session()
          sess.run(tf.global_variables_initializer())
  
          gan = TensorFlowGenerator(
              input_ph=z_ph,
              model=gen_tf,
              sess=sess,
          )
  
          inverse_gan = TensorFlowEncoder(
              input_ph=image_to_enc_ph,
              model=enc_tf,
              sess=sess,
          )
          return gan, inverse_gan, sess
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import json
  import logging
  import os
  import pickle
  import time
  import unittest
  import warnings
  import sklearn
  import numpy
  from art.estimators.classification.tensorflow import TensorFlowV2Classifier
  from art.estimators.encoding.tensorflow import TensorFlowEncoder
  from art.estimators.generation.tensorflow import TensorFlowGenerator, TensorFlowV2Generator
  from art.estimators.gan.tensorflow import TensorFlowV2GAN
  from art.utils import load_dataset
label_desc: Use image node_id 25 for calling a global function with example usage: get_gan_inverse_gan_ft() and returns: None,  None,  None, gan,  inverse_gan,  sess