code: def _get_per_partition_metrics(self, n_configurations=3):
      result = []
      for i in range(n_configurations):
          result.append(
              metrics.PerPartitionMetrics(
                  partition_selection_probability_to_keep=0.1,
                  raw_statistics=metrics.RawStatistics(
                      privacy_id_count=5, count=10
                  ),
                  metric_errors=[self._get_sum_metrics(150)],
              )
          )
      return result
  
imports: import copy
  from absl.testing import absltest
  from absl.testing import parameterized
  import pipeline_dp
  import analysis
  from analysis import metrics
  from analysis import utility_analysis
  from analysis.tests import common
  from typing import Optional
label_desc: Use image node_id 3 for calling the UtilityAnalysis obj's underlying member method code with example usage: obj._get_per_partition_metrics(n_configurations) and returns: result