code: def _get_metric_utility(coef: int) -> metrics.MetricUtility:
      """Returns MetricUtility with numerical fields proportional to 'coef'"""
      get_mean_var = lambda: metrics.MeanVariance(coef, 2 * coef)
      get_bounding_errors = lambda: metrics.ContributionBoundingErrors(
          l0=get_mean_var(), linf_min=3 * coef, linf_max=4 * coef
      )
      get_value_errors = lambda: metrics.ValueErrors(
          bounding_errors=get_bounding_errors(),
          mean=5 * coef,
          variance=6 * coef,
          rmse=7 * coef,
          l1=8 * coef,
          rmse_with_dropped_partitions=9 * coef,
          l1_with_dropped_partitions=10 * coef,
      )
      noise_std = (
          1000  # it's not merged, that's why not multiplied by coef.
      )
      return metrics.MetricUtility(
          metric=pipeline_dp.Metrics.COUNT,
          noise_std=noise_std,
          noise_kind=pipeline_dp.NoiseKind.LAPLACE,
          ratio_data_dropped=None,
          absolute_error=get_value_errors(),
          relative_error=get_value_errors().to_relative(10.0),
      )
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  import dataclasses
  import math
  from unittest import mock
  from unittest.mock import patch
  from analysis import metrics
  from analysis import cross_partition_combiners
  import pipeline_dp
label_desc: Use image node_id 3 for calling a global function with example usage: _get_metric_utility(coef) and returns: metrics