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: Take in a dictionary of parameters and apply checks before saving them as attributes.
docstr_tok: ["Take","in","a","dictionary","of","parameters","and","apply","checks","before","saving","them","as","attributes","."]
code: def set_params(self, **kwargs) -> None:
      """
      Take in a dictionary of parameters and apply checks before saving them as attributes.
      """
      for key, value in kwargs.items():
          if key in self.params:
              setattr(self, key, value)
      self._check_params()
  
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 7 for calling the Postprocessor obj's underlying member method code with example usage: obj.set_params() without return types