code: def load_image_train(datapoint):
      input_image = tf.image.resize(datapoint["image"], (128, 128))
      input_mask = tf.image.resize(
          datapoint["segmentation_mask"], (128, 128)
      )
  
      if tf.random.uniform(()) > 0.5:
          input_image = tf.image.flip_left_right(input_image)
          input_mask = tf.image.flip_left_right(input_mask)
  
      input_image, input_mask = normalize(input_image, input_mask)
  
      return input_image, input_mask
  
file_path: TensorFlowOnSpark/examples/segmentation/segmentation_dist.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from tensorflow_examples.models.pix2pix import pix2pix
  import json
  import os
  import tensorflow_datasets
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: load_image_train(datapoint) and returns: input_image,  input_mask