class_docstr: Function to score different max_partitions_contributed bounds.
  
  Suitable only for COUNT and PRIVACY_ID_COUNT aggregations.
code: def __init__(
      self,
      params: pipeline_dp.CalculatePrivateContributionBoundsParams,
      number_of_partitions: int,
      l0_histogram: Histogram,
  ):
      super().__init__()
      self._params = params
      self._number_of_partitions = number_of_partitions
      self._l0_histogram = l0_histogram
  
imports: from dataclasses import dataclass
  from functools import lru_cache
  from typing import List
  import pipeline_dp
  from pipeline_dp import dp_computations
  from pipeline_dp.dataset_histograms.histograms import Histogram
  from pipeline_dp import pipeline_functions
label_desc: Use image node_id 1 to create a new L0ScoringFunction object from inherited base classes: dp_computations.ExponentialMechanism with example: obj = L0ScoringFunction(params, number_of_partitions, l0_histogram)