class_docstr: Implement the thermometer encoding defence approach.
  
  | Paper link: https://openreview.net/forum?id=S18Su--CW
  
  | Please keep in mind the limitations of defences. For more information on the limitations of this defence,
      see https://arxiv.org/abs/1802.00420 . For details on how to evaluate classifier security in general, see
      https://arxiv.org/abs/1902.06705
code: def _check_params(self) -> None:
      if not isinstance(self.num_space, int) or self.num_space <= 0:
          logger.error(
              "Number of evenly spaced levels must be a positive integer."
          )
          raise ValueError(
              "Number of evenly spaced levels must be a positive integer."
          )
  
      if len(self.clip_values) != 2:
          raise ValueError(
              "`clip_values` should be a tuple of 2 floats containing the allowed data range."
          )
  
      if self.clip_values[0] >= self.clip_values[1]:
          raise ValueError(
              "first entry of `clip_values` should be strictly smaller than the second one."
          )
  
file_path: adversarial-robustness-toolbox/art/defences/preprocessor/thermometer_encoding.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
  from art.utils import to_categorical
label_desc: Use image node_id 5 for calling the ThermometerEncoding obj's underlying member method code with example usage: obj._check_params() without return types