code: def test_classification_without_bias(mnist_visiondata_train):
      result = (
          PropertyLabelCorrelation()
          .add_condition_property_pps_less_than()
          .run(mnist_visiondata_train)
      )
      # assert check result
      assert_that(
          result.value,
          has_entries(
              {
                  "Brightness": close_to(0.079, 0.005),
                  "Area": close_to(0.0, 0.005),
              }
          ),
      )
      # assert condition
      assert_that(
          result.conditions_results[0],
          equal_condition_result(
              is_pass=True,
              details="Passed for all of the properties",
              name="Properties' Predictive Power Score is less than 0.3",
          ),
      )
  
file_path: deepchecks/tests/vision/checks/data_integrity/property_label_correlation_test.py
imports: import numpy
  from hamcrest import assert_that, close_to, contains_exactly, has_entries
  from deepchecks.vision.checks import PropertyLabelCorrelation
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 3 for calling a global function with example usage: test_classification_without_bias(mnist_visiondata_train) without return types