class_docstr: A combiner for aggregating error metrics across partitions
class_docstr_tok: ["A","combiner","for","aggregating","error","metrics","across","partitions"]
docstr: Returns UtilityReport with final metrics.
docstr_tok: ["Returns","UtilityReport","with","final","metrics","."]
code: def compute_metrics(
      self, acc: AccumulatorType
  ) -> metrics.UtilityReport:
      """Returns UtilityReport with final metrics."""
      sum_actual, report, total_weight = acc
      report_copy = copy.deepcopy(report)
      _average_utility_report(report_copy, sum_actual, total_weight)
      return report_copy
  
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 4 for calling the CrossPartitionCombiner obj's underlying member method code with example usage: obj.compute_metrics(acc) and returns: report_copy