code: def test_aggregate_computation_graph_per_partition_bounding(
      self, mock_bound_contributions
  ):
      # Arrange
      aggregate_params = pipeline_dp.AggregateParams(
          noise_kind=pipeline_dp.NoiseKind.GAUSSIAN,
          metrics=[pipeline_dp.Metrics.SUM],
          min_sum_per_partition=0,
          max_sum_per_partition=1,
          max_partitions_contributed=1,
          max_contributions_per_partition=1,
      )
  
      engine = self._create_dp_engine_default()
      mock_bound_contributions.return_value = []
  
      engine.aggregate(
          col=[0],
          params=aggregate_params,
          data_extractors=self._get_default_extractors(),
      )
  
      # Assert
      mock_bound_contributions.assert_called_with(
          unittest.mock.ANY,
          aggregate_params,
          unittest.mock.ANY,
          unittest.mock.ANY,
          unittest.mock.ANY,
      )
  
imports: import sys
  import unittest
  from typing import List, Optional, Tuple
  from unittest.mock import patch
  import numpy
  import apache_beam
  import apache_beam.testing.test_pipeline
  import apache_beam.testing.util
  import pydp.algorithms.partition_selection
  from absl.testing import absltest
  from absl.testing import parameterized
  import pipeline_dp
  from pipeline_dp import aggregate_params
  from pipeline_dp import budget_accounting
  from pipeline_dp import dp_computations
  from pipeline_dp.budget_accounting import NaiveBudgetAccountant
  from pipeline_dp.pipeline_backend import PipelineBackend
  from pipeline_dp.pipeline_functions import collect_to_container
  from pipeline_dp.report_generator import ReportGenerator
label_desc: Use image node_id 18 for calling the DpEngineTest obj's underlying member method code with example usage: obj.test_aggregate_computation_graph_per_partition_bounding(mock_bound_contributions) without return types