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_mags_to_params(self, magnitudes):
      params = [
          self._map_mag_to_param(magnitude) for magnitude in magnitudes
      ]
      if len(params) >= 2:
          ref_shape = params[0].shape
          ref_dtype = params[0].dtype
          for param, mag in zip(params, magnitudes):
              if param.shape != ref_shape or param.dtype != ref_dtype:
                  raise Exception(
                      f"The `mag_to_param` callback of `{self.name}` augmentation must return "
                      f"the arrays of the same type and shape for different magnitudes. "
                      f"Got param of shape {ref_shape} and {ref_dtype} type for magnitude "
                      f"{magnitudes[0]}, but for magnitude {mag} the returned array "
                      f"has shape {param.shape} and type {param.dtype}.\n\n"
                      f"Error in augmentation: {self}."
                  )
      return np.array(params)
  
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 15 for calling the Augmentation obj's underlying member method code with example usage: obj._map_mags_to_params(magnitudes) and returns: np