code: def test_calculate_importance(iris_split_dataset_and_model):
      # Arrange
      train_ds, _, adaboost = iris_split_dataset_and_model
  
      # Act
      fi = calculate_feature_importance(adaboost, train_ds)
  
      # Assert
      assert_that(fi.sum(), close_to(1, 0.000001))
  
imports: from hamcrest import assert_that, calling, close_to, raises
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.feature_importance import calculate_feature_importance
  from deepchecks.tabular.metric_utils import DeepcheckScorer
label_desc: Use image node_id 1 for calling a global function with example usage: test_calculate_importance(iris_split_dataset_and_model) without return types