class_docstr: Compound combiner for Utility analysis per partition metrics.
class_docstr_tok: ["Compound","combiner","for","Utility","analysis","per","partition","metrics","."]
code: def _to_dense(
      self, sparse_acc: SparseAccumulatorType
  ) -> DenseAccumulatorType:
      # sparse_acc contains lists, convert them to numpy arrays in order to
      # speed up creation of accumulators.
      sparse_acc = [np.array(a) for a in sparse_acc]
      return (
          len(sparse_acc[0]),
          tuple(
              [
                  combiner.create_accumulator(sparse_acc)
                  for combiner in self._combiners
              ]
          ),
      )
  
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 2 for calling the CompoundCombiner obj's underlying member method code with example usage: obj._to_dense(sparse_acc) and returns: len,  tuple