class_docstr: Test the MultilabelScorer class.
class_docstr_tok: ["Test","the","MultilabelScorer","class","."]
docstr: Make sure the instatiated aggregator kwargs can be overridden.
  I.e. switching from a forgetting-factor 1.0 to 0.5.
docstr_tok: ["Make","sure","the","instatiated","aggregator","kwargs","can","be","overridden",".","I.e",".","switching","from","a","forgetting-factor","1.0","to","0.5","."]
code: def test_aggregate_kwargs(self, base_scorer):
      """Make sure the instatiated aggregator kwargs can be overridden.
      I.e. switching from a forgetting-factor 1.0 to 0.5.
      """
      class_label_quality_scores = np.array(
          [[0.9, 0.9, 0.3], [0.4, 0.9, 0.6]]
      )
      aggregator = ml_scorer.Aggregator(
          ml_scorer.exponential_moving_average, alpha=1.0
      )
      scorer = ml_scorer.MultilabelScorer(
          base_scorer=base_scorer,
          aggregator=aggregator,
      )
      scores = scorer.aggregate(class_label_quality_scores)
      assert np.allclose(scores, np.array([0.3, 0.4]))
      # Use different alpha, should change scores
      new_scores = scorer.aggregate(
          class_label_quality_scores, alpha=0.0
      )
      assert np.allclose(new_scores, np.array([0.9, 0.9]))
  
imports: import itertools
  import typing
  import numpy
  import pytest
  import sklearn
  from hypothesis import given, settings
  from hypothesis import strategies
  from hypothesis.strategies import composite
  from hypothesis.extra.numpy import arrays
  from sklearn.linear_model import LogisticRegression
  from sklearn.multiclass import OneVsRestClassifier
  from cleanlab import multilabel_classification
  from cleanlab.internal import multilabel_scorer
  from cleanlab.internal.multilabel_utils import get_onehot_num_classes, onehot2int, stack_complement
  from cleanlab.multilabel_classification import filter
  from cleanlab.multilabel_classification.dataset import common_multilabel_issues, multilabel_health_summary, overall_multilabel_health_score, rank_classes_by_multilabel_quality
  from cleanlab.multilabel_classification.rank import get_label_quality_scores_per_class
label_desc: Use image node_id 5 for calling the TestMultilabelScorer obj's underlying member method code with example usage: obj.test_aggregate_kwargs(base_scorer) without return types