class_docstr: Base class for all class accuracy plugin metrics
code: def __init__(self, reset_at, emit_at, mode, classes=None):
      super(ClassAccuracyPluginMetric, self).__init__(
          ClassAccuracy(classes=classes),
          reset_at=reset_at,
          emit_at=emit_at,
          mode=mode,
      )
      self.phase_name = "train"
      self.stream_name = "train"
      self.experience_id = 0
  
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 ClassAccuracyPluginMetric object from inherited base classes: _ExtendedGenericPluginMetric with example: obj = ClassAccuracyPluginMetric(reset_at, emit_at, mode, classes)