class_docstr: Class implementation of backdoor-based RED poisoning attack on DGM.
  
  | Paper link: https://arxiv.org/abs/2108.01644
class_docstr_tok: ["Class","implementation","of","backdoor-based","RED","poisoning","attack","on","DGM",".","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/2108.01644"]
docstr: Initialize a backdoor RED poisoning attack.
  :param generator: the generator to be poisoned
docstr_tok: ["Initialize","a","backdoor","RED","poisoning","attack",".",":","param","generator",":","the","generator","to","be","poisoned"]
code: def __init__(self, generator: "TensorFlowV2Generator") -> None:
      """
      Initialize a backdoor RED poisoning attack.
      :param generator: the generator to be poisoned
      """
      import tensorflow as tf
  
      # pylint: disable=W0212
      super().__init__(generator=generator)
  
      self._model_clone = tf.keras.models.clone_model(
          self.estimator.model
      )
      self._model_clone.set_weights(self.estimator.model.get_weights())
  
file_path: adversarial-robustness-toolbox/art/attacks/poisoning/backdoor_attack_dgm/backdoor_attack_dgm_red.py
imports: import logging
  from typing import TYPE_CHECKING
  import numpy
  from art.attacks.attack import PoisoningAttackGenerator
  from art.estimators.generation.tensorflow import TensorFlowV2Generator
label_desc: Use image node_id 1 to create a new BackdoorAttackDGMReDTensorFlowV2 object from inherited base classes: PoisoningAttackGenerator with example: obj = BackdoorAttackDGMReDTensorFlowV2(generator)