code: def distort_image_with_autoaugment(image, augmentation_name):
      """Applies the AutoAugment policy to `image`.
  
      AutoAugment is from the paper: https://arxiv.org/abs/1805.09501.
      Args:
        image: `Tensor` of shape [height, width, 3] representing an image.
        augmentation_name: The name of the AutoAugment policy to use. The available
          options are `v0` and `test`. `v0` is the policy used for all of the
          results in the paper and was found to achieve the best results on the COCO
          dataset. `v1`, `v2` and `v3` are additional good policies found on the
          COCO dataset that have slight variation in what operations were used
          during the search procedure along with how many operations are applied in
          parallel to a single image (2 vs 3).
  
      Returns:
        A tuple containing the augmented versions of `image`.
      """
      available_policies = {"v0": policy_v0, "test": policy_vtest}
      if augmentation_name not in available_policies:
          raise ValueError(
              "Invalid augmentation_name: {}".format(augmentation_name)
          )
  
      policy = available_policies[augmentation_name]()
      # Hparams that will be used for AutoAugment.
      augmentation_hparams = HParams(
          cutout_const=100, translate_const=250
      )
  
      return build_and_apply_nas_policy(
          policy, image, augmentation_hparams
      )
  
imports: import dataclasses
  import inspect
  import math
  import tensorflow.compat.v1
  from tensorflow_addons import image
label_desc: Use image node_id 33 for calling a global function with example usage: distort_image_with_autoaugment(image, augmentation_name) and returns: build_and_apply_nas_policy