class_docstr: ER AML, as proposed in
  "New Insights on Reducing Abrupt Representation
  Change in Online Continual Learning"
  by Lucas Caccia et. al.
  https://openreview.net/forum?id=N8MaByOzUfb
class_docstr_tok: ["ER","AML",",","as","proposed","in","''","New","Insights","on","Reducing","Abrupt","Representation","Change","in","Online","Continual","Learning","''","by","Lucas","Caccia","et",".","al",".","https",":","\/\/openreview.net\/forum","?","id=N8MaByOzUfb"]
code: def _train_cleanup(self):
      super()._train_cleanup()
      # reset the value to avoid serialization failures
      self.replay_loader = None
  
file_path: avalanche/avalanche/training/supervised/er_aml.py
imports: from typing import Callable, List, Optional, Union
  import torch
  from torch.nn import CrossEntropyLoss, Module
  from torch.optim import Optimizer
  from avalanche.core import SupervisedPlugin
  from avalanche.models.utils import avalanche_forward
  from avalanche.training import AMLCriterion
  from avalanche.training.plugins.evaluation import EvaluationPlugin, default_evaluator
  from avalanche.training.storage_policy import ClassBalancedBuffer
  from avalanche.training.templates import SupervisedTemplate
  from avalanche.training.utils import cycle
label_desc: Use image node_id 4 for calling the ER_AML obj's underlying member method code with example usage: obj._train_cleanup() without return types