class_docstr: A combiner for aggregating error metrics across partitions
class_docstr_tok: ["A","combiner","for","aggregating","error","metrics","across","partitions"]
code: def create_accumulator(
      self, metrics: metrics.PerPartitionMetrics
  ) -> AccumulatorType:
      actual_metrics = tuple(me.sum for me in metrics.metric_errors)
      weight = self._weight_fn(metrics)
      return (
          actual_metrics,
          _per_partition_to_utility_report(
              metrics, self._dp_metrics, self._public_partitions, weight
          ),
          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 2 for calling the CrossPartitionCombiner obj's underlying member method code with example usage: obj.create_accumulator(metrics) and returns: actual_metrics,  _per_partition_to_utility_report,  weight