code: def test_drift_max_drift_score_condition_fail_psi(
      drifted_data_and_model,
  ):
      # Arrange
      train, test, model = drifted_data_and_model
      train = remove_label(train)
      test = remove_label(test)
      check = PredictionDrift(
          categorical_drift_method="PSI", drift_mode="prediction"
      ).add_condition_drift_score_less_than()
  
      # Act
      result = check.run(train, test, model)
      condition_result, *_ = check.conditions_decision(result)
  
      # Assert
      assert_that(
          condition_result,
          equal_condition_result(
              is_pass=False,
              name="Prediction drift score < 0.15",
              details="Found model prediction PSI drift score of 0.79",
          ),
      )
  
imports: import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DeepchecksValueError, NotEnoughSamplesError
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.checks import PredictionDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 10 for calling a global function with example usage: test_drift_max_drift_score_condition_fail_psi(drifted_data_and_model) without return types