code: def test_run_base_checks(coco_visiondata_train):
      # Arrange
      executions = defaultdict(int)
  
      class DummyCheck(SingleDatasetCheck):
          def initialize_run(self, context, dataset_kind: DatasetKind):
              executions["initialize_run"] += 1
  
          def update(self, context, batch, dataset_kind: DatasetKind):
              executions["update"] += 1
  
          def compute(
              self, context, dataset_kind: DatasetKind
          ) -> CheckResult:
              executions["compute"] += 1
              return CheckResult(None)
  
      class DummyTrainTestCheck(TrainTestCheck):
          def initialize_run(self, context):
              executions["initialize_run"] += 1
  
          def update(self, context, batch, dataset_kind: DatasetKind):
              executions["update"] += 1
  
          def compute(self, context) -> CheckResult:
              executions["compute"] += 1
              return CheckResult(None)
  
      # Act
      DummyCheck().run(coco_visiondata_train)
      DummyTrainTestCheck().run(
          coco_visiondata_train, coco_visiondata_train
      )
  
      # Assert
      assert_that(
          executions,
          is_({"initialize_run": 2, "compute": 2, "update": 6}),
      )
  
imports: from collections import defaultdict
  from hamcrest import assert_that, calling, is_, raises
  from deepchecks.core import CheckResult, DatasetKind
  from deepchecks.vision.base_checks import ModelOnlyCheck, SingleDatasetCheck, TrainTestCheck
label_desc: Use image node_id 1 for calling a global function with example usage: test_run_base_checks(coco_visiondata_train) and returns: CheckResult, CheckResult