class_docstr: The average class accuracy across all minibatches up to the current
  epoch iteration.
  This plugin metric only works at training time.
  
  At each iteration, this metric logs the accuracy averaged over all patterns
  seen so far in the current epoch (separately for each class).
  The metric resets its state after each training epoch.
code: def __str__(self):
      return "Top1_RunningClassAcc_Epoch"
  
imports: from typing import Dict, List, Set, Union, TYPE_CHECKING, Iterable, Optional
  from collections import defaultdict, OrderedDict
  import torch
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, _ExtendedGenericPluginMetric, _ExtendedPluginMetricValue
  from avalanche.evaluation.metric_utils import default_metric_name_template, generic_get_metric_name
  from avalanche.evaluation.metrics import Mean
label_desc: Use image node_id 2 for calling the RunningEpochClassAccuracy obj's underlying member method code with example usage: obj.__str__() and returns: str