class_docstr: Add Gaussian noise to a dataset in one of two ways: either add noise to each sample (keeping the size of the
  original dataset) or perform augmentation by keeping all original samples and adding noisy counterparts. When used
  as part of a :class:`.Classifier` instance, the defense will be applied automatically only when training if
  `augmentation` is true, and only when performing prediction otherwise.
class_docstr_tok: ["Add","Gaussian","noise","to","a","dataset","in","one","of","two","ways",":","either","add","noise","to","each","sample","(","keeping","the","size","of","the","original","dataset",")","or","perform","augmentation","by","keeping","all","original","samples","and","adding","noisy","counterparts",".","When","used","as","part","of","a",":","class",":","`",".Classifier","`","instance",",","the","defense","will","be","applied","automatically","only","when","training","if","`","augmentation","`","is","true",",","and","only","when","performing","prediction","otherwise","."]
code: def _check_params(self) -> None:
      if self.augmentation and self.ratio <= 0:
          raise ValueError("The augmentation ratio must be positive.")
  
      if self.clip_values is not None:
          if len(self.clip_values) != 2:
              raise ValueError(
                  "`clip_values` should be a tuple of 2 floats or arrays containing the allowed data range."
              )
          if np.array(self.clip_values[0] >= self.clip_values[1]).any():
              raise ValueError("Invalid `clip_values`: min >= max.")
  
file_path: adversarial-robustness-toolbox/art/defences/preprocessor/gaussian_augmentation.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Optional, Tuple, TYPE_CHECKING
  import numpy
  from art.config import ART_NUMPY_DTYPE
  from art.defences.preprocessor.preprocessor import Preprocessor
label_desc: Use image node_id 3 for calling the GaussianAugmentation obj's underlying member method code with example usage: obj._check_params() without return types