class_docstr: Learning without Forgetting plugin.
  
  LwF uses distillation to regularize the current loss with soft targets
  taken from a previous version of the model.
  When used with multi-headed models, all heads are distilled.
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docstr: :param alpha: distillation hyperparameter. It can be either a float
          number or a list containing alpha for each experience.
  :param temperature: softmax temperature for distillation
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code: def __init__(self, alpha=1, temperature=2):
      """
      :param alpha: distillation hyperparameter. It can be either a float
              number or a list containing alpha for each experience.
      :param temperature: softmax temperature for distillation
      """
      super().__init__()
      self.lwf = LearningWithoutForgetting(alpha, temperature)
  
imports: from avalanche.training import LearningWithoutForgetting
  from avalanche.training.plugins.strategy_plugin import SupervisedPlugin
label_desc: Use image node_id 1 to create a new LwFPlugin object from inherited base classes: SupervisedPlugin with example: obj = LwFPlugin(alpha, temperature)