code: def test_wrong_length_custom_weights_error():
      labels = data["labels"]
      pred_probs = data["pred_probs"]
  
      # baseline scenario where all the pred_probs are the same in the ensemble list
      num_repeat = 3
      pred_probs_list = list(
          np.repeat([pred_probs], num_repeat, axis=0)
      )
  
      # baseline scenario where custom_weights are uniform
      custom_weights = np.ones(num_repeat) / 3
  
      with pytest.raises(AssertionError) as e:
          _ = rank.get_label_quality_ensemble_scores(
              labels,
              pred_probs_list,
              weight_ensemble_members_by="custom",
              custom_weights=custom_weights[1:],
              # this should raise AssertionError because length of custom_weights don't match len(pred_probs_list)
          )
  
imports: import numpy
  import pytest
  from cleanlab import rank
  from cleanlab.internal.label_quality_utils import _subtract_confident_thresholds
  from cleanlab.benchmarking.noise_generation import generate_noise_matrix_from_trace
  from cleanlab.benchmarking.noise_generation import generate_noisy_labels
  from cleanlab import count
  from cleanlab import outlier
  from sklearn.neighbors import NearestNeighbors
label_desc: Use image node_id 11 for calling a global function with example usage: test_wrong_length_custom_weights_error() without return types