class_docstr: The CumulativeForgetting metric, describing the accuracy loss
  detected for a certain experience.
  
  This plugin metric, computed separately for each experience,
  is the difference between the cumulative accuracy result obtained after
  first training on a experience and the accuracy result obtained
  on the same experience at the end of successive experiences.
  
  This metric is computed during the eval phase only.
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code: def update(self, strategy):
      self._metric.update(
          self.classes_splits, strategy.mb_output, strategy.mb_y
      )
  
imports: from collections import defaultdict
  from typing import Dict, List, Union, TYPE_CHECKING
  import numpy
  import torch
  from torch import Tensor
  from avalanche.benchmarks import OnlineCLExperience
  from avalanche.evaluation import GenericPluginMetric, Metric, PluginMetric
  from avalanche.evaluation.metrics.mean import Mean
  from avalanche.evaluation.metric_utils import phase_and_task, stream_type, generic_get_metric_name, default_metric_name_template
  from avalanche.evaluation.metric_results import MetricValue
label_desc: Use image node_id 6 for calling the CumulativeForgettingPluginMetric obj's underlying member method code with example usage: obj.update(strategy) without return types