code: def augment_list():  # 16 operations and their ranges
      # https://github.com/google-research/uda/blob/master/image/randaugment/policies.py#L57
      # l = [
      #     (Identity, 0., 1.0),
      #     (ShearX, 0., 0.3),  # 0
      #     (ShearY, 0., 0.3),  # 1
      #     (TranslateX, 0., 0.33),  # 2
      #     (TranslateY, 0., 0.33),  # 3
      #     (Rotate, 0, 30),  # 4
      #     (AutoContrast, 0, 1),  # 5
      #     (Invert, 0, 1),  # 6
      #     (Equalize, 0, 1),  # 7
      #     (Solarize, 0, 110),  # 8
      #     (Posterize, 4, 8),  # 9
      #     # (Contrast, 0.1, 1.9),  # 10
      #     (Color, 0.1, 1.9),  # 11
      #     (Brightness, 0.1, 1.9),  # 12
      #     (Sharpness, 0.1, 1.9),  # 13
      #     # (Cutout, 0, 0.2),  # 14
      #     # (SamplePairing(imgs), 0, 0.4),  # 15
      # ]
  
      # https://github.com/tensorflow/tpu/blob/8462d083dd89489a79e3200bcc8d4063bf362186/models/official/efficientnet/autoaugment.py#L505
      l = [
          (AutoContrast, 0, 1),
          (Equalize, 0, 1),
          # (Invert, 0, 1),
          (Rotate, 0, 30),
          (Posterize, 0, 4),
          (Solarize, 0, 256),
          (SolarizeAdd, 0, 110),
          (Color, 0.1, 1.9),
          (Contrast, 0.1, 1.9),
          (Brightness, 0.1, 1.9),
          (Sharpness, 0.1, 1.9),
          (ShearX, 0.0, 0.3),
          (ShearY, 0.0, 0.3),
          # (CutoutAbs, 0, 40),
          (TranslateXabs, 0.0, 100),
          (TranslateYabs, 0.0, 100),
      ]
  
      return l
  
imports: import random
  import numpy
  import PIL
  import PIL.ImageDraw
  import PIL.ImageEnhance
  import PIL.ImageOps
  import torch
  from PIL import Image
label_desc: Use image node_id 23 for calling a global function with example usage: augment_list() and returns: l