code: def test_not_shuffled_explanation(exact_shap_regression_dataset):
      # in general permutation shap does not behave as predictable as
      # kernel shap, even when comparing permutation against kernel SHAP of the
      # mainline SHAP package. So these tests assure us that we're doing the
      # correct calculations, even if we can't compare directly.
      X_train, X_test, y_train, y_test = exact_shap_regression_dataset
  
      mod = cuml.LinearRegression().fit(X_train, y_train)
  
      explainer = PermutationExplainer(model=mod.predict, data=X_train)
  
      shap_values = explainer.shap_values(
          X_test[0], npermutations=1, testing=True
      )
  
      assert np.allclose(
          shap_values, not_shuffled_shap_values, rtol=1e-04, atol=1e-04
      )
  
file_path: cuml/python/cuml/tests/explainer/test_explainer_permutation_shap.py
imports: from cuml.testing.utils import ClassEnumerator, get_shap_values, create_synthetic_dataset
  from cuml import PermutationExplainer
  import sklearn.neighbors
  import pytest
  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 4 for calling a global function with example usage: test_not_shuffled_explanation(exact_shap_regression_dataset) without return types