code: def test_just_dance_small_drift(
      just_dance_train_test_textdata_sampled,
  ):
      # Arrange
      train, test = just_dance_train_test_textdata_sampled
      check = LabelDrift().add_condition_drift_score_less_than(0.1)
      # Act
      result = check.run(train, test)
      condition_result = check.conditions_decision(result)
  
      # Assert
      assert_that(
          condition_result,
          has_items(
              equal_condition_result(
                  is_pass=True,
                  details="Label's drift score Cramer's V is 0.07",
                  name="Label drift score < 0.1",
              )
          ),
      )
  
      assert_that(result.value["Drift score"], close_to(0.07, 0.01))
  
file_path: deepchecks/tests/nlp/checks/train_test_validation/label_drift_test.py
imports: from hamcrest import assert_that, close_to, has_items
  from deepchecks.nlp.checks import LabelDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 1 for calling a global function with example usage: test_just_dance_small_drift(just_dance_train_test_textdata_sampled) without return types