code: def build_graph(self, image_pos):
      image_pos = image_pos / 128.0 - 1
  
      z = tf.random_uniform(
          [self.batch, self.zdim], -1, 1, name="z_train"
      )
      z = tf.placeholder_with_default(z, [None, self.zdim], name="z")
  
      with argscope(
          [Conv2D, Conv2DTranspose, FullyConnected],
          kernel_initializer=tf.truncated_normal_initializer(
              stddev=0.02
          ),
      ):
          with tf.variable_scope("gen"):
              image_gen = self.generator(z)
          tf.summary.image(
              "generated-samples", image_gen, max_outputs=30
          )
          with tf.variable_scope("discrim"):
              vecpos = self.discriminator(image_pos)
              vecneg = self.discriminator(image_gen)
  
      self.build_losses(vecpos, vecneg)
      self.collect_variables()
  
imports: import argparse
  import glob
  import numpy
  import os
  import tensorflow
  from tensorpack import *
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
  from tensorpack.utils.viz import stack_patches
  from GAN import GANModelDesc, GANTrainer, RandomZData
label_desc: Use image node_id 5 for calling the Model obj's underlying member method code with example usage: obj.build_graph(image_pos) without return types