code: def preprocess_image(
      image, label, height=32, width=32, num_channels=3
  ):
      """Performs data augmentation of the image."""
      image = tf.image.resize_with_crop_or_pad(
          image, height + 8, width + 8
      )
      image = tf.image.random_crop(image, [height, width, num_channels])
      image = tf.image.random_flip_left_right(image)
      return image, label
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/data.py
imports: import gin
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess_image(image, label, height, width, num_channels) and returns: image,  label