class_docstr: The standalone mean metric.
  
  This utility metric is a general purpose metric that can be used to keep
  track of the mean of a sequence of values.
class_docstr_tok: ["The","standalone","mean","metric",".","This","utility","metric","is","a","general","purpose","metric","that","can","be","used","to","keep","track","of","the","mean","of","a","sequence","of","values","."]
docstr: Return a metric representing the weighted mean of the 2 means.
  
  :param other: the other mean
  :return: The weighted mean
docstr_tok: ["Return","a","metric","representing","the","weighted","mean","of","the","2","means",".",":","param","other",":","the","other","mean",":","return",":","The","weighted","mean"]
code: def __add__(self, other: "Mean") -> "Mean":
      """
      Return a metric representing the weighted mean of the 2 means.
  
      :param other: the other mean
      :return: The weighted mean"""
      res = Mean()
      res.summed = self.summed + other.summed
      res.weight = self.weight + other.weight
      return res
  
file_path: avalanche/avalanche/evaluation/metrics/mean.py
imports: from typing import SupportsFloat
  from avalanche.evaluation import Metric
label_desc: Use image node_id 5 for calling the Mean obj's underlying member method code with example usage: obj.__add__(other) and returns: res