code: def _compute_partition_privacy_id_count_histogram(
      col, backend: pipeline_backend.PipelineBackend
  ):
      """Computes histogram of privacy id counts per partition.
  
      This histogram contains: the number of partitions with privacy_id_count=1,
      with privacy_id_count=2 etc.
  
      Args:
          col: collection with elements (privacy_id, partition_key).
           Assumption: 'col' contains distinct elements!
          backend: PipelineBackend to run operations on the collection.
      Returns:
          1 element collection, which contains the computed hist.Histogram.
      """
  
      col = backend.values(col, "Drop privacy key")
      # col: (pk)
  
      col = backend.count_per_element(
          col, "Compute partitions per privacy id"
      )
      # col: (pk, count_pid_per_pk)
  
      col = backend.values(col, "Drop partition key")
      # col: (int)
  
      return _compute_frequency_histogram(
          col,
          backend,
          hist.HistogramType.COUNT_PRIVACY_ID_PER_PARTITION,
      )
  
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 16 for calling a global function with example usage: _compute_partition_privacy_id_count_histogram(col, backend) and returns: _compute_frequency_histogram