code: def _compute_frequency_histogram_helper(
      col,
      backend: pipeline_backend.PipelineBackend,
      name: hist.HistogramType,
  ):
      """Computes histogram of element frequencies in collection.
  
      This is a helper function for _compute_frequency_histogram and
      _compute_weighted_frequency_histogram.
  
      Args:
          col: collection of (n:int, frequency_of_n: int)
          backend: PipelineBackend to run operations on the collection.
          name: name which is assigned to the computed histogram.
      Returns:
          1 element collection which contains hist.Histogram.
      """
  
      def _map_to_frequency_bin(
          value: int, frequency: int
      ) -> Tuple[int, hist.FrequencyBin]:
          bin_lower, bin_upper = _to_bin_lower_upper_logarithmic(value)
          return bin_lower, hist.FrequencyBin(
              lower=bin_lower,
              upper=bin_upper,
              count=frequency,
              sum=frequency * value,
              max=value,
          )
  
      col = backend.map_tuple(
          col, _map_to_frequency_bin, "To FrequencyBin"
      )
      # (lower_bin_value, hist.FrequencyBin)
      return _convert_frequency_bins_into_histogram(col, backend, name)
  
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 5 for calling a global function with example usage: _compute_frequency_histogram_helper(col, backend, name) and returns: _convert_frequency_bins_into_histogram, bin_lower,  hist