class_docstr: Wrapper for transformations implemented with DALI that are meant to be used with
  automatic augmentations. You should not need to instantiate this class directly,
  use `@augmentation` decorator instead.
docstr: The method to update augmentation parameters specified with `@augmentation` decorator.
  Returns a new augmentation with the original operation decorated but updated parameters.
  Parameters that are not specified are kept as in the initial augmentation.
docstr_tok: ["The","method","to","update","augmentation","parameters","specified","with","`","@","augmentation","`","decorator",".","Returns","a","new","augmentation","with","the","original","operation","decorated","but","updated","parameters",".","Parameters","that","are","not","specified","are","kept","as","in","the","initial","augmentation","."]
code: def augmentation(
      self,
      mag_range=_UndefinedParam,
      randomly_negate=_UndefinedParam,
      mag_to_param=_UndefinedParam,
      param_device=_UndefinedParam,
      name=_UndefinedParam,
      augmentation_cls=None,
  ):
      """
      The method to update augmentation parameters specified with `@augmentation` decorator.
      Returns a new augmentation with the original operation decorated but updated parameters.
      Parameters that are not specified are kept as in the initial augmentation.
      """
      cls = augmentation_cls or self.__class__
      config = self._get_config()
      for key, value in dict(
          mag_range=mag_range,
          randomly_negate=randomly_negate,
          mag_to_param=mag_to_param,
          param_device=param_device,
          name=name,
      ).items():
          assert key in config
          if value is not _UndefinedParam:
              config[key] = value
      return cls(self.op, **config)
  
imports: import warnings
  from typing import Callable, Tuple, Optional, Union
  from nvidia.dali import fn, types
  from nvidia.dali.data_node import DataNode
  from nvidia.dali.auto_aug.core._args import filter_extra_accepted_kwargs, get_missing_kwargs, get_num_positional_args, MissingArgException
  from numpy import typing
label_desc: Use image node_id 10 for calling the Augmentation obj's underlying member method code with example usage: obj.augmentation(mag_range, randomly_negate, mag_to_param, param_device, name, augmentation_cls) and returns: cls