class_docstr: A combiner for aggregating error metrics across partitions
class_docstr_tok: ["A","combiner","for","aggregating","error","metrics","across","partitions"]
code: def merge_accumulators(
      self, acc1: AccumulatorType, acc2: AccumulatorType
  ) -> AccumulatorType:
      sum_actual1, report1, weight1 = acc1
      sum_actual2, report2, weight2 = acc2
      sum_actual = tuple(
          x + y for x, y in zip(sum_actual1, sum_actual2)
      )
      _merge_utility_reports(report1, report2)
      weight = weight1 + weight2
      return sum_actual, report1, weight
  
imports: import copy
  import pipeline_dp
  from analysis import metrics
  import dataclasses
  from typing import List, Tuple, Callable
  import math
label_desc: Use image node_id 3 for calling the CrossPartitionCombiner obj's underlying member method code with example usage: obj.merge_accumulators(acc1, acc2) and returns: sum_actual,  report1,  weight