class_docstr: Performs DP aggregations.
class_docstr_tok: ["Performs","DP","aggregations","."]
code: def _check_calculate_private_contribution_bounds_params(
      self,
      col,
      params: pipeline_dp.CalculatePrivateContributionBoundsParams,
      data_extractors: pipeline_dp.DataExtractors,
      check_data_extractors: bool = True,
  ):
      _check_col(col)
      if params is None:
          raise ValueError(
              "params must be set to a valid "
              "CalculatePrivateContributionBoundsParams"
          )
      if not isinstance(
          params, pipeline_dp.CalculatePrivateContributionBoundsParams
      ):
          raise TypeError(
              "params must be set to a valid "
              "CalculatePrivateContributionBoundsParams"
          )
      if check_data_extractors:
          _check_data_extractors(data_extractors)
  
imports: import functools
  from typing import Any, Callable, Optional, Sequence, Tuple, Union
  import pipeline_dp
  from pipeline_dp import budget_accounting
  from pipeline_dp import combiners
  from pipeline_dp import contribution_bounders
  from pipeline_dp import dp_computations
  from pipeline_dp import partition_selection
  from pipeline_dp import pipeline_functions
  from pipeline_dp import report_generator
  from pipeline_dp import sampling_utils
  from pipeline_dp.dataset_histograms import computing_histograms
  from pipeline_dp.private_contribution_bounds import PrivateL0Calculator
label_desc: Use image node_id 20 for calling the DPEngine obj's underlying member method code with example usage: obj._check_calculate_private_contribution_bounds_params(col, params, data_extractors, check_data_extractors) without return types