class_docstr: Abstract base class for postprocessing defences. Postprocessing defences are not included in the loss function
  evaluation for loss gradients or the calculation of class gradients.
docstr: Create a postprocessing object.
  
  Optionally, set attributes.
docstr_tok: ["Create","a","postprocessing","object",".","Optionally",",","set","attributes","."]
code: def __init__(
      self,
      is_fitted: bool = False,
      apply_fit: bool = True,
      apply_predict: bool = True,
  ) -> None:
      """
      Create a postprocessing object.
  
      Optionally, set attributes.
      """
      self._is_fitted = bool(is_fitted)
      self._apply_fit = bool(apply_fit)
      self._apply_predict = bool(apply_predict)
      Postprocessor._check_params(self)
  
file_path: adversarial-robustness-toolbox/art/defences/postprocessor/postprocessor.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from typing import List
  import abc
  import numpy
label_desc: Use image node_id 1 to create a new Postprocessor object from inherited base classes: abc with example: obj = Postprocessor(is_fitted, apply_fit, apply_predict)