code: def test_get_label_quality_scores_output(labels, pred_probs, scorer):
      # Check that the function returns a dictionary with the correct keys.
      scores = ml_scorer.get_label_quality_scores(
          labels, pred_probs, method=scorer
      )
      assert isinstance(scores, np.ndarray)
      assert scores.shape == (labels.shape[0],)
      assert np.all(scores >= 0) and np.all(scores <= 1)
      assert np.all(np.isfinite(scores))
  
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 24 for calling a global function with example usage: test_get_label_quality_scores_output(labels, pred_probs, scorer) without return types