code: def test_drift_max_drift_score_condition_fail(mnist_drifted_datasets):
      # Arrange
      check = PredictionDrift(
          categorical_drift_method="PSI"
      ).add_condition_drift_score_less_than()
      mod_train_ds, mod_test_ds = mnist_drifted_datasets
  
      # Act
      result = check.run(mod_train_ds, mod_test_ds, random_state=42)
  
      condition_result, *_ = result.conditions_results
  
      # Assert
      assert_that(
          condition_result,
          equal_condition_result(
              is_pass=False,
              name="categorical drift score < 0.15 and numerical drift score < 0.15 for prediction drift",
              details="Failed for 1 out of 1 prediction properties.\n"
              "Found 1 categorical prediction properties with PSI above threshold: {'Samples Per Class': '0.39'}",
          ),
      )
  
file_path: deepchecks/tests/vision/checks/model_evaluation/prediction_drift_test.py
imports: from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import NotEnoughSamplesError
  from deepchecks.vision.checks import PredictionDrift
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 12 for calling a global function with example usage: test_drift_max_drift_score_condition_fail(mnist_drifted_datasets) without return types