class_docstr: Implementation of STRIP: A Defence Against Trojan Attacks on Deep Neural Networks (Gao et. al. 2020)
  
  | Paper link: https://arxiv.org/abs/1902.06531
docstr: Create an instance of the neural cleanse defence.
  
  :param classifier: A trained classifier.
code: def __init__(self, classifier: "CLASSIFIER_TYPE"):
      """
      Create an instance of the neural cleanse defence.
  
      :param classifier: A trained classifier.
      """
      super().__init__(classifier=classifier)
      self._check_params()
  
file_path: adversarial-robustness-toolbox/art/defences/transformer/poisoning/strip.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Optional, TYPE_CHECKING
  import numpy
  from art.defences.transformer.transformer import Transformer
  from art.estimators.poison_mitigation.strip import STRIPMixin
label_desc: Use image node_id 1 to create a new STRIP object from inherited base classes: Transformer with example: obj = STRIP(classifier)