code: def _get_augmentation(
      aug_type: str, aug_paras: Optional[Dict[str, Any]] = None
  ) -> List[Callable]:
      """
      Initializes a list of callable transforms for video augmentation.
  
      Args:
          aug_type (str): Currently supports 'default', 'randaug', or 'augmix'.
              Returns an empty list when aug_type is 'default'. Returns a list
              of transforms containing RandAugment when aug_type is 'randaug'
              and a list containing AugMix when aug_type is 'augmix'.
          aug_paras (Dict[str, Any], optional): A dictionary that contains the necessary
              parameters for the augmentation set in aug_type. If any parameters are
              missing or if None, default parameters will be used. Default is None.
  
      Returns:
          aug (List[Callable]): List of callable transforms with the specified augmentation.
      """
  
      if aug_paras is None:
          aug_paras = {}
  
      if aug_type == "default":
          aug = []
      elif aug_type == "randaug":
          aug = [
              Permute((1, 0, 2, 3)),
              RandAugment(
                  magnitude=aug_paras.get(
                      "magnitude", _RANDAUG_DEFAULT_PARAS["magnitude"]
                  ),
                  num_layers=aug_paras.get(
                      "num_layers", _RANDAUG_DEFAULT_PARAS["num_layers"]
                  ),
                  prob=aug_paras.get(
                      "prob", _RANDAUG_DEFAULT_PARAS["prob"]
                  ),
                  sampling_type=aug_paras.get(
                      "sampling_type",
                      _RANDAUG_DEFAULT_PARAS["sampling_type"],
                  ),
                  sampling_hparas=aug_paras.get(
                      "sampling_hparas",
                      _RANDAUG_DEFAULT_PARAS["sampling_hparas"],
                  ),
              ),
              Permute((1, 0, 2, 3)),
          ]
      elif aug_type == "augmix":
          aug = [
              Permute((1, 0, 2, 3)),
              AugMix(
                  magnitude=aug_paras.get(
                      "magnitude", _AUGMIX_DEFAULT_PARAS["magnitude"]
                  ),
                  alpha=aug_paras.get(
                      "alpha", _AUGMIX_DEFAULT_PARAS["alpha"]
                  ),
                  width=aug_paras.get(
                      "width", _AUGMIX_DEFAULT_PARAS["width"]
                  ),
                  depth=aug_paras.get(
                      "depth", _AUGMIX_DEFAULT_PARAS["depth"]
                  ),
              ),
              Permute((1, 0, 2, 3)),
          ]
      else:
          raise NotImplementedError
  
      return aug
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torch
  from pytorchvideo.transforms import ApplyTransformToKey, AugMix, ConvertUint8ToFloat, Normalize, Permute, RandAugment, RandomResizedCrop, RandomShortSideScale, RemoveKey, ShortSideScale, UniformTemporalSubsample
  from torchvision.transforms import CenterCrop, Compose, RandomCrop, RandomHorizontalFlip
label_desc: Use image node_id 1 for calling a global function with example usage: _get_augmentation(aug_type, aug_paras) and returns: aug