code: def test_condition_pass(mnist_visiondata_train):
      # Arrange
      check = PredictionDrift(
          categorical_drift_method="PSI"
      ).add_condition_drift_score_less_than()
  
      # Act
      result = check.run(mnist_visiondata_train, mnist_visiondata_train)
  
      # Assert
      assert_that(
          result.conditions_results[0],
          equal_condition_result(
              is_pass=True,
              name="categorical drift score < 0.15 and numerical drift score < 0.15 for prediction drift",
              details="Passed for 1 prediction properties out of 1 prediction properties.\n"
              'Found prediction property "Samples Per Class" has the highest categorical drift score: 0',
          ),
      )
  
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 13 for calling a global function with example usage: test_condition_pass(mnist_visiondata_train) without return types