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 _map_mag_to_param(self, magnitude):
      param = self.mag_to_param(magnitude)
      if _contains_data_node(param):
          raise Exception(
              f"The `mag_to_param` callback of `{self.name}` augmentation returned `DataNode`, "
              f"i.e. an output of DALI pipelined operator, which is not supported there. "
              f"Instead, the `mag_to_param` callback must return parameter that is `np.ndarray` "
              f"or is directly convertible to `np.ndarray`, so that the all parameters can "
              f"be precomputed and reused across iterations.\n\n"
              f"You can move DALI operators from `mag_to_param` callback to the "
              f"decorated augmentation code or replace the DALI operators in `mag_to_param` "
              f"callback with their `dali.experimental.eger` counterparts.\n\n"
              f"Error in augmentation: {self}."
          )
      return np.array(param)
  
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 14 for calling the Augmentation obj's underlying member method code with example usage: obj._map_mag_to_param(magnitude) and returns: np