code: def svhn_tf_preprocess(inp, random_crop=True):
      image_size = 32
      image = inp
      if random_crop:
          print("Apply random cropping")
          image = tf.image.resize_image_with_crop_or_pad(
              inp, image_size + 4, image_size + 4
          )
          image = tf.random_crop(image, [image_size, image_size, 3])
      return inp, image
  
file_path: cleverhans/cleverhans_v3.1.0/examples/multigpu_advtrain/utils_svhn.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import os
  import numpy
  from six.moves import range
  import tensorflow
  import scipy.io
label_desc: Use image node_id 2 for calling a global function with example usage: svhn_tf_preprocess(inp, random_crop) and returns: inp,  image