class_docstr: Metric used to monitor the labels repartition.
class_docstr_tok: ["Metric","used","to","monitor","the","labels","repartition","."]
code: def __init__(self):
      self.task2label2count: Dict[int, Dict[int, int]] = {}
      self.class_order = None
      self.reset()
  
imports: from collections import defaultdict
  from typing import Callable, Dict, Sequence, TYPE_CHECKING, Optional, List, Counter, overload
  from matplotlib.figure import Figure
  from avalanche.evaluation import GenericPluginMetric, Metric, PluginMetric
  from avalanche.evaluation.metric_results import MetricValue, AlternativeValues
  from avalanche.evaluation.metric_utils import stream_type, default_history_repartition_image_creator
  from typing_extensions import Literal
label_desc: Use image node_id 1 to create a new LabelsRepartition object from inherited base classes: Metric with example: obj = LabelsRepartition()