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","."]
code: def _is_stream_tracked(self, stream_name):
      return (
          self._limit_streams is None
          or stream_name in self._limit_streams
      )
  
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 7 for calling the MultiStreamAMCA obj's underlying member method code with example usage: obj._is_stream_tracked(stream_name) and returns: unknown