code: def test_multilabel_num_to_remove_per_class(
      data_multilabel, num_to_remove_per_class
  ):
      labels, pred_probs = data_multilabel
  
      issues = filter.find_label_issues(
          labels=labels,
          pred_probs=pred_probs,
          num_to_remove_per_class=num_to_remove_per_class,
      )
      num_issues = sum(issues)
      if num_to_remove_per_class is None:
          assert num_issues == 9
      else:
          assert num_issues == sum(num_to_remove_per_class)
  
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 16 for calling a global function with example usage: test_multilabel_num_to_remove_per_class(data_multilabel, num_to_remove_per_class) without return types