code: def _after_training_exp(self, **kwargs):
      self.buffer.update(self)
      super()._after_training_exp(**kwargs)
  
imports: from copy import deepcopy
  from typing import Callable, Optional, Sequence, Union
  import torch
  import torch.nn.functional
  from torch.nn import CrossEntropyLoss, Module
  from torch.optim import Optimizer
  from avalanche.models.utils import avalanche_forward
  from avalanche.training.plugins import EvaluationPlugin, SupervisedPlugin
  from avalanche.training.plugins.evaluation import default_evaluator
  from avalanche.training.storage_policy import ReservoirSamplingBuffer
  from avalanche.training.templates import SupervisedMetaLearningTemplate
label_desc: Use image node_id 5 for calling the MER obj's underlying member method code with example usage: obj._after_training_exp() without return types