code: def test_property_with_nones(mnist_visiondata_train):
      # Arrange
      def property_with_none(images):
          return np.random.choice([1, None], len(images))
  
      image_properties = [
          {
              "name": "test",
              "method": property_with_none,
              "output_type": "categorical",
          }
      ]
      check = ImagePropertyOutliers(image_properties=image_properties)
      # Act
      result = check.run(mnist_visiondata_train)
      assert_that(
          result.value,
          has_entries(
              {
                  "test": has_entries(
                      {
                          "outliers_identifiers": has_length(0),
                          "lower_limit": is_(1),
                          "upper_limit": is_(1),
                      }
                  )
              }
          ),
      )
  
file_path: deepchecks/tests/vision/checks/data_integrity/image_property_outliers_test.py
imports: import numpy
  from hamcrest import all_of, any_of, assert_that, calling, close_to, has_entries, has_key, has_length, has_properties, instance_of, is_, raises
  from hamcrest.core.matcher import Matcher
  from deepchecks.core import CheckResult
  from deepchecks.core.errors import DeepchecksProcessError, NotEnoughSamplesError
  from deepchecks.vision.checks import ImagePropertyOutliers
  from deepchecks.vision.utils.image_properties import default_image_properties
label_desc: Use image node_id 10 for calling a global function with example usage: test_property_with_nones(mnist_visiondata_train) and returns: np