class_docstr: Combiner for computing DP Variance. Also returns sum, count and mean in addition to
  the variance.
  The type of the accumulator is a tuple(count: int, sum: float) that holds
  the count and sum of elements in the dataset for which this accumulator is
  computed.
class_docstr_tok: ["Combiner","for","computing","DP","Variance",".","Also","returns","sum",",","count","and","mean","in","addition","to","the","variance",".","The","type","of","the","accumulator","is","a","tuple","(","count",":","int",",","sum",":","float",")","that","holds","the","count","and","sum","of","elements","in","the","dataset","for","which","this","accumulator","is","computed","."]
code: def merge_accumulators(
      self, accum1: AccumulatorType, accum2: AccumulatorType
  ):
      count1, sum1, sum_of_squares1 = accum1
      count2, sum2, sum_of_squares2 = accum2
      return (
          count1 + count2,
          sum1 + sum2,
          sum_of_squares1 + sum_of_squares2,
      )
  
imports: import abc
  import copy
  from typing import Iterable, Sized, Tuple, List
  import pipeline_dp
  import numpy
  from collections import namedtuple
label_desc: Use image node_id 2 for calling the RawVarianceCombiner obj's underlying member method code with example usage: obj.merge_accumulators(accum1, accum2) and returns: unknown,  unknown,  unknown