code: def test_exact_regression_datasets(
      exact_shap_regression_dataset, model
  ):
      X_train, X_test, y_train, y_test = exact_shap_regression_dataset
  
      models = []
      models.append(model().fit(X_train, y_train))
      models.append(cuml_skl_class_dict[model]().fit(X_train, y_train))
  
      for mod in models:
          explainer, shap_values = get_shap_values(
              model=mod.predict,
              background_dataset=X_train,
              explained_dataset=X_test,
              explainer=KernelExplainer,
          )
          for i in range(3):
              print(i)
              assert_and_log(
                  shap_values[i],
                  golden_regression_results[model][i],
                  mod.predict(X_test[i].reshape(1, X_test.shape[1])),
                  explainer.expected_value,
              )
  
imports: from sklearn.model_selection import train_test_split
  from cuml.testing.utils import create_synthetic_dataset, ClassEnumerator, get_shap_values
  from cuml.datasets import make_regression
  from cuml.internals.import_utils import has_shap
  from cuml.internals.import_utils import has_scipy
  from cuml import KernelExplainer
  from cuml import Lasso
  import sklearn.neighbors
  import pytest
  import math
  from cuml.internals.safe_imports import cpu_only_import
  import cuml
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 2 for calling a global function with example usage: test_exact_regression_datasets(exact_shap_regression_dataset, model) without return types