code: def compute_dataset_histograms_on_preaggregated_data(
      col,
      data_extractors: pipeline_dp.PreAggregateExtractors,
      backend: pipeline_backend.PipelineBackend,
  ):
      """Computes dataset histograms on pre-aggregated dataset.
  
      Args:
          col: collection with a pre-aggregated dataset, each element is
            (partition_key, (count, sum, n_partitions, n_contributions)).
          backend: PipelineBackend to run operations on the collection.
  
      Returns:
          1 element collection, which contains a histograms.DatasetHistograms object.
      """
  
      col = backend.map(
          col,
          lambda row: (
              data_extractors.partition_extractor(row),
              data_extractors.preaggregate_extractor(row),
          ),
          "Extract (partition_key, preaggregate_data))",
      )
      # col: (partition_key, (count, sum, n_partitions, n_contributions))
  
      col = backend.to_multi_transformable_collection(col)
      # col: (partition_key, (count, sum, n_partitions, n_contributions))
  
      # Compute histograms.
      l0_contributions_histogram = (
          _compute_l0_contributions_histogram_on_preaggregated_data(
              col, backend
          )
      )
      l1_contributions_histogram = (
          _compute_l1_contributions_histogram_on_preaggregated_data(
              col, backend
          )
      )
      linf_contributions_histogram = (
          _compute_linf_contributions_histogram_on_preaggregated_data(
              col, backend
          )
      )
      linf_sum_contributions_histogram = _compute_linf_sum_contributions_histogram_on_preaggregated_data(
          col, backend
      )
      partition_count_histogram = (
          _compute_partition_count_histogram_on_preaggregated_data(
              col, backend
          )
      )
      partition_privacy_id_count_histogram = _compute_partition_privacy_id_count_histogram_on_preaggregated_data(
          col, backend
      )
      partition_sum_histogram = (
          _compute_partition_sum_histogram_on_preaggregated_data(
              col, backend
          )
      )
  
      # Combine histograms to histograms.DatasetHistograms.
      return _to_dataset_histograms(
          [
              l0_contributions_histogram,
              l1_contributions_histogram,
              linf_contributions_histogram,
              linf_sum_contributions_histogram,
              partition_count_histogram,
              partition_privacy_id_count_histogram,
              partition_sum_histogram,
          ],
          backend,
      )
  
imports: import bisect
  import operator
  from typing import List, Tuple
  import numpy
  import pipeline_dp
  from pipeline_dp import pipeline_backend, pipeline_functions
  from pipeline_dp.dataset_histograms import histograms
label_desc: Use image node_id 26 for calling a global function with example usage: compute_dataset_histograms_on_preaggregated_data(col, data_extractors, backend) and returns: _to_dataset_histograms