class_docstr: An extension of the Average Mean Class Accuracy (AMCA) metric
  (class:`AverageMeanClassAccuracy`) able to separate the computation of the
  AMCA based on the current stream.
class_docstr_tok: ["An","extension","of","the","Average","Mean","Class","Accuracy","(","AMCA",")","metric","(","class",":","`","AverageMeanClassAccuracy","`",")","able","to","separate","the","computation","of","the","AMCA","based","on","the","current","stream","."]
docstr: Resets the metric.
  
  :return: None.
docstr_tok: ["Resets","the","metric",".",":","return",":","None","."]
code: def reset(self) -> None:
      """
      Resets the metric.
  
      :return: None.
      """
      for metric in self._amcas.values():
          metric.reset()
      self._current_stream = None
      self._streams_in_this_phase.clear()
  
imports: from typing import Callable, Dict, Iterable, List, Union, TYPE_CHECKING, Optional, Sequence, Set
  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 generic_get_metric_name
  from avalanche.evaluation.metrics.class_accuracy import ClassAccuracy, TrackedClassesType
label_desc: Use image node_id 6 for calling the MultiStreamAMCA obj's underlying member method code with example usage: obj.reset() without return types