code: def test_binary_model_info_object(
      iris_dataset_single_class_labeled, iris_random_forest_single_class
  ):
      # Arrange
      check = CalibrationScore()
      # Act X
      result = check.run(
          iris_dataset_single_class_labeled,
          iris_random_forest_single_class,
      ).value
      # Assert
      assert_that(result, has_length(1))
  
      assert_that(result, has_entries({0: close_to(0.0002, 0.0005)}))
  
file_path: deepchecks/tests/tabular/checks/model_evaluation/calibration_score_test.py
imports: from hamcrest import assert_that, calling, close_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError, ModelValidationError
  from deepchecks.tabular.checks.model_evaluation import CalibrationScore
  from deepchecks.tabular.dataset import Dataset
label_desc: Use image node_id 6 for calling a global function with example usage: test_binary_model_info_object(iris_dataset_single_class_labeled, iris_random_forest_single_class) without return types