docstr: Creates an accumulator for data.
  
  Args:
      data is a Tuple containing:
        1) the count of the user's contributions for a single partition
        2) the sum of the user's contributions for the same partition
        3) the total number of partitions a user contributed to.
  
      Only COUNT, PRIVACY_ID_COUNT, SUM metrics can be supported with the
      current format of data.
  
  Returns:
      A tuple which is an accumulator.
code: def create_accumulator(self, data: Tuple[int, float, int]):
      """Creates an accumulator for data.
  
      Args:
          data is a Tuple containing:
            1) the count of the user's contributions for a single partition
            2) the sum of the user's contributions for the same partition
            3) the total number of partitions a user contributed to.
  
          Only COUNT, PRIVACY_ID_COUNT, SUM metrics can be supported with the
          current format of data.
  
      Returns:
          A tuple which is an accumulator.
      """
  
imports: import abc
  import copy
  from dataclasses import dataclass
  from typing import Any, List, Optional, Tuple
  import numpy
  import math
  import pipeline_dp
  from pipeline_dp import budget_accounting
  from pipeline_dp import dp_computations
  from analysis import metrics
  from analysis import poisson_binomial
  from pipeline_dp import partition_selection
label_desc: Use image node_id 1 for calling the UtilityAnalysisCombiner obj's underlying member method code with example usage: obj.create_accumulator(data) without return types