class_docstr: Statistic tracking the count, mean, and (diagonal) variance of a single
  :class:`torch.Tensor`.
code: def merge(
      self, other: "CountMeanVarianceStats"
  ) -> "CountMeanVarianceStats":
      assert isinstance(other, type(self))
      if self.shape is None:
          return copy.deepcopy(other)
      if other.shape is None:
          return copy.deepcopy(self)
      result = copy.deepcopy(self)
      res = result.welford
      lhs = self.welford
      rhs = other.welford
      res.n_samples = lhs.n_samples + rhs.n_samples
      lhs_weight = lhs.n_samples / res.n_samples
      rhs_weight = rhs.n_samples / res.n_samples
      res._mean = lhs_weight * lhs._mean + rhs_weight * rhs._mean
      res._m2 = (
          lhs._m2
          + rhs._m2
          + (lhs.n_samples * rhs.n_samples / res.n_samples)
          * (lhs._mean - rhs._mean) ** 2
      )
      return result
  
imports: import copy
  from abc import ABC, abstractmethod
  from collections import defaultdict
  from typing import Any, Callable, Dict, Hashable, Union
  import torch
  from pyro.ops.welford import WelfordCovariance
label_desc: Use image node_id 3 for calling the CountMeanVarianceStats obj's underlying member method code with example usage: obj.merge(other) and returns: result, copy, copy