code: def test_compute_metrics_mix_sparse_dense(self):
      sparse = ([1, 11], [10, 2], [100, 300])
      dense = (4, ((2, 1.5, 2, -1, 3),))
      acc = (sparse, dense)
  
      output = self._create_combiner().compute_metrics(acc)
  
      self.assertLen(output, 1)  # only 1 combiner.
      common.assert_dataclasses_are_equal(
          self,
          metrics.SumMetrics(
              aggregation=pipeline_dp.Metrics.COUNT,
              sum=14,
              clipping_to_min_error=1.5,
              clipping_to_max_error=-7.0,
              expected_l0_bounding_error=-3.9833333333333334,
              std_l0_bounding_error=1.738731977300955,
              std_noise=7.46484375,
              noise_kind=pipeline_dp.NoiseKind.GAUSSIAN,
          ),
          output[0],
      )
  
imports: import dataclasses
  import numpy
  from absl.testing import absltest
  from absl.testing import parameterized
  from unittest.mock import patch
  from typing import Tuple
  import pipeline_dp
  from analysis import per_partition_combiners
  from analysis import metrics
  from analysis.tests import common
label_desc: Use image node_id 10 for calling the UtilityAnalysisCompoundCombinerTest obj's underlying member method code with example usage: obj.test_compute_metrics_mix_sparse_dense() without return types