code: def test_drift_grayscale_without_display(mnist_drifted_datasets):
      # Arrange
      train, test = mnist_drifted_datasets
      check = ImageDatasetDrift(
          categorical_drift_method="PSI", min_meaningful_drift_score=-1
      )
  
      # Act
      result = check.run(train, test, with_display=False)
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "domain_classifier_auc": close_to(0.525, 0.001),
                  "domain_classifier_drift_score": close_to(
                      0.051, 0.001
                  ),
                  "domain_classifier_feature_importance": has_entries(
                      {"Brightness": close_to(0.852, 0.001)}
                  ),
              }
          ),
      )
      assert_that(result.display, has_length(0))
  
file_path: deepchecks/tests/vision/checks/train_test_validation/image_dataset_drift_test.py
imports: import numpy
  from hamcrest import assert_that, close_to, equal_to, greater_than, has_entries, has_length
  from deepchecks.vision.checks import ImageDatasetDrift
  from deepchecks.vision.datasets.detection.coco_torch import collate_without_model
  from deepchecks.vision.utils.test_utils import replace_collate_fn_visiondata
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 6 for calling a global function with example usage: test_drift_grayscale_without_display(mnist_drifted_datasets) without return types