code: def basic_augmentation(image, image_height, image_width, seed=None):
      """Augment image according to NasNet paper (random flip + random crop)."""
  
      # source: https://arxiv.org/pdf/1707.07012.pdf appendix A.1
      padding = 4
      image = tf.image.random_flip_left_right(image, seed=seed)
  
      image = tf.pad(
          image, [[padding, padding], [padding, padding], [0, 0]]
      )
      image = tf.random_crop(
          image, [image_height, image_width, 3], seed=seed
      )
      return image
  
file_path: adanet/research/improve_nas/trainer/image_processing.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: basic_augmentation(image, image_height, image_width, seed) and returns: image