code: def test_run_attack_by_percentiles_slice(self):
      result = mia.run_attacks(
          get_multilabel_test_input(100, 100),
          SlicingSpec(
              entire_dataset=True, by_class=False, by_percentiles=True
          ),
          (AttackType.THRESHOLD_ATTACK,),
      )
  
      # 1 attack on entire dataset, 1 attack each of 10 percentile ranges, total
      # of 11.
      self.assertLen(result.single_attack_results, 11)
      expected_slice = SingleSliceSpec(
          SlicingFeature.PERCENTILE, (20, 30)
      )
      # First slice (Slice #0) is entire dataset. Hence Slice #3 is the 3rd
      # percentile range 20-30.
      self.assertEqual(
          result.single_attack_results[3].slice_spec, expected_slice
      )
  
imports: from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  import numpy
  from tensorflow_privacy.privacy.privacy_tests import epsilon_lower_bound
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import membership_inference_attack
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import models
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackInputData
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import AttackType
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import DataSize
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import SingleSliceSpec
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import SlicingFeature
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack.data_structures import SlicingSpec
label_desc: Use image node_id 7 for calling the RunAttacksTestOnMultilabelData obj's underlying member method code with example usage: obj.test_run_attack_by_percentiles_slice() without return types