class_docstr: The average accuracy over a single training epoch.
  This plugin metric only works at training time.
  
  The accuracy will be logged after each training epoch by computing
  the number of correctly predicted patterns during the epoch divided by
  the overall number of patterns encountered in that epoch.
class_docstr_tok: ["The","average","accuracy","over","a","single","training","epoch",".","This","plugin","metric","only","works","at","training","time",".","The","accuracy","will","be","logged","after","each","training","epoch","by","computing","the","number","of","correctly","predicted","patterns","during","the","epoch","divided","by","the","overall","number","of","patterns","encountered","in","that","epoch","."]
code: def __str__(self):
      return "Top1_Acc_Epoch"
  
imports: from typing import List, Optional, Union, Dict
  import torch
  from torch import Tensor
  from avalanche.evaluation import Metric, GenericPluginMetric
  from avalanche.evaluation.metrics.mean import Mean
  from collections import defaultdict
label_desc: Use image node_id 2 for calling the EpochAccuracy obj's underlying member method code with example usage: obj.__str__() and returns: str