code: def split_input(mode, dp):
      """
      dp: the datapoint. first component is an RGB image of shape (s, 2s, 3).
      :return: [input, output]
      """
      img = dp[0]
      # split the image into left + right pairs
      s = img.shape[0]
      assert img.shape[1] == 2 * s
      input, output = img[:, :s, :], img[:, s:, :]
      if mode == "BtoA":
          input, output = output, input
      if IN_CH == 1:
          input = cv2.cvtColor(input, cv2.COLOR_RGB2GRAY)[
              :, :, np.newaxis
          ]
      if OUT_CH == 1:
          output = cv2.cvtColor(output, cv2.COLOR_RGB2GRAY)[
              :, :, np.newaxis
          ]
      return [input, output]
  
imports: import argparse
  import functools
  import glob
  import numpy
  import os
  import cv2
  import tensorflow
  from tensorpack import *
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
  from tensorpack.tfutils.summary import add_moving_summary
  from tensorpack.utils.gpu import get_num_gpu
  from tensorpack.utils.viz import stack_patches
  from GAN import GANModelDesc, GANTrainer
label_desc: Use image node_id 3 for calling a global function with example usage: split_input(mode, dp) and returns: list