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.
code: def __init__(
      self,
      op: Callable[..., _DataNode],
      mag_range: Optional[
          Union[Tuple[float, float], np.ndarray]
      ] = None,
      randomly_negate: Optional[bool] = None,
      mag_to_param: Optional[Callable[[float], npt.ArrayLike]] = None,
      param_device: Optional[str] = None,
      name: Optional[str] = None,
  ):
      self._op = op
      self._mag_range = mag_range
      self._randomly_negate = randomly_negate
      self._mag_to_param = mag_to_param
      self._param_device = param_device
      self._name = name
      self._validate_op_sig()
  
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 1 to create a new Augmentation object  with example: obj = Augmentation(op, mag_range, randomly_negate, mag_to_param, param_device, name)