code: def test_token_classification_with_nones(
      small_wikiann_train_test_text_data,
  ):
      # Arrange
      train, test = small_wikiann_train_test_text_data
      train_label_with_nones = train.label
      train_label_with_nones[0][0] = None
      train = TextData(
          train.text,
          tokenized_text=train.tokenized_text,
          task_type="token_classification",
      )
      check = PredictionDrift()
  
      # Act
      result = check.run(
          train,
          test,
          train_predictions=np.asarray(train_label_with_nones),
          test_predictions=np.asarray(test.label),
      )
  
      # Assert
      assert_that(result.value["Drift score"], close_to(0, 0.04))
  
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 6 for calling a global function with example usage: test_token_classification_with_nones(small_wikiann_train_test_text_data) without return types