code: def test_pruning_order_method():
      order_methods = ["self_confidence", "normalized_margin"]
      results = []
      for method in order_methods:
          results.append(
              filter.find_label_issues(
                  labels=data["labels"],
                  pred_probs=data["pred_probs"],
                  return_indices_ranked_by=method,
              )
          )
      assert len(results[0]) == len(results[1])
  
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 18 for calling a global function with example usage: test_pruning_order_method() without return types