class_docstr: Implementation of the adversarial patch attack for square and rectangular images and videos.
  
  | Paper link: https://arxiv.org/abs/1712.09665
class_docstr_tok: ["Implementation","of","the","adversarial","patch","attack","for","square","and","rectangular","images","and","videos",".","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/1712.09665"]
code: def set_params(self, **kwargs) -> None:
      super().set_params(**kwargs)
      self._attack.set_params(**kwargs)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.attacks.evasion.adversarial_patch.adversarial_patch_numpy import AdversarialPatchNumpy
  from art.attacks.evasion.adversarial_patch.adversarial_patch_tensorflow import AdversarialPatchTensorFlowV2
  from art.attacks.evasion.adversarial_patch.adversarial_patch_pytorch import AdversarialPatchPyTorch
  from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from art.estimators.classification import TensorFlowV2Classifier, PyTorchClassifier
  from art.attacks.attack import EvasionAttack
label_desc: Use image node_id 6 for calling the AdversarialPatch obj's underlying member method code with example usage: obj.set_params() without return types