class_docstr: The average class 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 (separately
  for each class).
docstr: Creates an instance of the EpochClassAccuracy metric.
docstr_tok: ["Creates","an","instance","of","the","EpochClassAccuracy","metric","."]
code: def __init__(self, classes=None):
      """
      Creates an instance of the EpochClassAccuracy metric.
      """
      super().__init__(
          reset_at="epoch",
          emit_at="epoch",
          mode="train",
          classes=classes,
      )
  
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 1 to create a new EpochClassAccuracy object from inherited base classes: ClassAccuracyPluginMetric with example: obj = EpochClassAccuracy(classes)