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: Perform model postprocessing and return postprocessed output.
  
  :param preds: model output to be postprocessed.
  :return: Postprocessed model output.
docstr_tok: ["Perform","model","postprocessing","and","return","postprocessed","output",".",":","param","preds",":","model","output","to","be","postprocessed",".",":","return",":","Postprocessed","model","output","."]
code: def __call__(self, preds: np.ndarray) -> np.ndarray:
      """
      Perform model postprocessing and return postprocessed output.
  
      :param preds: model output to be postprocessed.
      :return: Postprocessed model output.
      """
      raise NotImplementedError
  
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 5 for calling the Postprocessor obj's underlying member method code with example usage: obj.__call__(preds) without return types