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 create_accumulator(
      self, values: Iterable[float]
  ) -> AccumulatorType:
      return (
          len(values),
          sum(values),
          sum(value**2 for value in values),
      )
  
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 1 for calling the RawVarianceCombiner obj's underlying member method code with example usage: obj.create_accumulator(values) and returns: len,  sum,  sum