class_docstr: Combiner for computing DP Mean. Also returns sum and count in addition to
  the mean.
  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","Mean",".","Also","returns","sum","and","count","in","addition","to","the","mean",".","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 metrics_names(self) -> List[str]:
      return ["non_private_mean"]
  
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 4 for calling the RawMeanCombiner obj's underlying member method code with example usage: obj.metrics_names() and returns: list