code: def optimizer(self):
      lr = tf.get_variable(
          "learning_rate",
          initializer=2e-4,
          dtype=tf.float32,
          trainable=False,
      )
      opt = tf.train.AdamOptimizer(lr, beta1=0.5, epsilon=1e-6)
      # generator learns 5 times faster
      return optimizer.apply_grad_processors(
          opt, [gradproc.ScaleGradient(("gen/.*", 5))]
      )
  
imports: import argparse
  import numpy
  import os
  import cv2
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow import dataset
  from tensorpack.tfutils import gradproc, optimizer, summary
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope, under_name_scope
  from tensorpack.utils import viz
  from GAN import GANModelDesc, GANTrainer
label_desc: Use image node_id 5 for calling the Model obj's underlying member method code with example usage: obj.optimizer() and returns: optimizer