code: def generator(self, z, y):
      l = FullyConnected(
          "fc0", tf.concat([z, y], 1), 1024, activation=BNReLU
      )
      l = FullyConnected(
          "fc1", tf.concat([l, y], 1), 64 * 2 * 7 * 7, activation=BNReLU
      )
      l = tf.reshape(l, [-1, 7, 7, 64 * 2])
  
      y = tf.reshape(y, [-1, 1, 1, 10])
      l = tf.concat([l, tf.tile(y, [1, 7, 7, 1])], 3)
      l = Conv2DTranspose("deconv1", l, 64 * 2, 5, 2, activation=BNReLU)
  
      l = tf.concat([l, tf.tile(y, [1, 14, 14, 1])], 3)
      l = Conv2DTranspose("deconv2", l, 1, 5, 2, activation=tf.identity)
      l = tf.nn.tanh(l, name="gen")
      return l
  
file_path: tensorpack/examples/GAN/ConditionalGAN-mnist.py
imports: import argparse
  import numpy
  import os
  import cv2
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow import dataset
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
  from tensorpack.utils.viz import interactive_imshow, stack_patches
  from GAN import GANModelDesc, GANTrainer, RandomZData
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.generator(z, y) and returns: l