code: def _posterize_level_to_arg(level, _hparams):
      # As per Tensorflow TPU EfficientNet impl
      # range [0, 4], 'keep 0 up to 4 MSB of original image'
      # intensity/severity of augmentation decreases with level
      return (int((level / _MAX_LEVEL) * 4),)
  
imports: import math
  import random
  import re
  import numpy
  import PIL
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
  from PIL import Image, ImageEnhance, ImageOps
label_desc: Use image node_id 27 for calling a global function with example usage: _posterize_level_to_arg(level, _hparams) and returns: int