code: def test_different_algorithms_different_output():
      # ensure different algorithms are actually being called
      rng = np.random.RandomState(3)
      X = rng.normal(size=(100, 10))
      y = rng.normal(size=100)
      model = cuml.ensemble.RandomForestRegressor().fit(X, y)
      interventional_explainer = TreeExplainer(model=model, data=X)
      explainer = TreeExplainer(model=model)
      assert not np.all(
          explainer.shap_values(X)
          == interventional_explainer.shap_values(X)
      )
      assert not np.all(
          explainer.shap_interaction_values(
              X, method="shapley-interactions"
          )
          == explainer.shap_interaction_values(
              X, method="shapley-taylor"
          )
      )
  
imports: from cuml.testing.utils import as_type
  import cuml
  from cuml.ensemble import RandomForestClassifier
  from cuml.ensemble import RandomForestRegressor
  from cuml.common.exceptions import NotFittedError
  from cuml.internals.import_utils import has_sklearn
  from cuml.internals.import_utils import has_lightgbm, has_shap
  from cuml.explainer.tree_shap import TreeExplainer
  from hypothesis import given, settings, assume, HealthCheck, strategies
  from cuml.internals.safe_imports import gpu_only_import
  import json
  import pytest
  import treelite
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 23 for calling a global function with example usage: test_different_algorithms_different_output() without return types