code: def test_find_label_issue_filters_match_origin_functions():
      label_issues = filter.find_label_issues(
          labels_, pred_probs_, filter_by="predicted_neq_given"
      )
      label_issues2 = filter.find_predicted_neq_given(
          labels_, pred_probs_
      )
      assert all(label_issues == label_issues2)
      label_issues3 = filter.find_label_issues(
          labels_,
          pred_probs_,
          filter_by="confident_learning",
          verbose=True,
      )
      label_issues4 = filter.find_predicted_neq_given(
          labels_, pred_probs_
      )
      assert all(label_issues3 == label_issues4)
      try:
          _ = filter.find_label_issues(
              labels_,
              pred_probs_,
              filter_by="predicted_neq_given",
              num_to_remove_per_class=[1] * pred_probs_.shape[1],
          )
      except ValueError as e:
          assert "not supported" in str(e)
  
imports: import cleanlab.multilabel_classification.dataset
  from cleanlab import count, filter
  from cleanlab.count import get_confident_thresholds, estimate_py_and_noise_matrices_from_probabilities
  from cleanlab.internal.latent_algebra import compute_inv_noise_matrix
  from cleanlab.benchmarking.noise_generation import generate_noise_matrix_from_trace
  from cleanlab.benchmarking.noise_generation import generate_noisy_labels
  from cleanlab.internal.util import value_counts
  from cleanlab.internal.multilabel_utils import int2onehot
  from cleanlab.experimental.label_issues_batched import find_label_issues_batched
  import numpy
  import scipy
  import pytest
  from sklearn.multioutput import MultiOutputClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import cross_val_predict
  from tempfile import mkdtemp
  import os.path
label_desc: Use image node_id 26 for calling a global function with example usage: test_find_label_issue_filters_match_origin_functions() without return types