code: def test_drift_mode_proba_warnings(
      small_wikiann_train_test_text_data,
  ):
      # Arrange
      train, test = small_wikiann_train_test_text_data
      check = PredictionDrift(drift_mode="proba")
  
      # Act
      with pytest.warns(
          UserWarning,
          match='Cannot use drift_mode="proba" for multi-label text classification tasks or token '
          'classification tasks. Using drift_mode="prediction" instead.',
      ):
          check.run(
              train,
              test,
              train_predictions=np.asarray(train.label),
              test_predictions=np.asarray(test.label),
          )
  
      # Make sure doesn't raise alert regularly:
      check = PredictionDrift()
  
      with pytest.warns(None) as record:
          check.run(
              train,
              test,
              train_predictions=np.asarray(train.label),
              test_predictions=np.asarray(test.label),
          )
  
      assert_that(record, has_length(0))
  
file_path: deepchecks/tests/nlp/checks/model_evaluation/prediction_drift_test.py
imports: import numpy
  import pytest
  from hamcrest import assert_that, close_to, equal_to, has_items, has_length
  from deepchecks.nlp import TextData
  from deepchecks.nlp.checks import PredictionDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 7 for calling a global function with example usage: test_drift_mode_proba_warnings(small_wikiann_train_test_text_data) without return types