class_docstr: A container for alternative representations of the same metric value.
code: def __init__(self, *alternatives: MetricType):
      self.alternatives: Tuple[MetricType, ...] = alternatives
  
file_path: avalanche/avalanche/evaluation/metric_results.py
imports: from dataclasses import dataclass
  from typing import List, Optional, TYPE_CHECKING, Tuple, Union
  from PIL.Image import Image
  from matplotlib.figure import Figure
  from torch import Tensor
  from enum import Enum
label_desc: Use image node_id 1 to create a new AlternativeValues object  with example: obj = AlternativeValues()