code: def test_sklearn_rf_classifier(n_classes):
      n_samples = 100
      X, y = make_classification(
          n_samples=n_samples,
          n_features=8,
          n_informative=8,
          n_redundant=0,
          n_repeated=0,
          n_classes=n_classes,
          random_state=2021,
      )
      X, y = X.astype(np.float32), y.astype(np.float32)
      skl_model = sklrfc(
          max_features=1.0,
          max_samples=0.1,
          min_samples_leaf=2,
          random_state=123,
          n_estimators=10,
          max_depth=16,
      )
      skl_model.fit(X, y)
  
      explainer = TreeExplainer(model=skl_model)
      out = explainer.shap_values(X)
  
      ref_explainer = shap.explainers.Tree(model=skl_model)
      correct_out = np.array(ref_explainer.shap_values(X))
      expected_value = ref_explainer.expected_value
      if n_classes == 2:
          correct_out = correct_out[1, :, :]
          expected_value = expected_value[1:]
      np.testing.assert_almost_equal(out, correct_out, decimal=5)
      np.testing.assert_almost_equal(
          explainer.expected_value, expected_value, decimal=5
      )
  
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 11 for calling a global function with example usage: test_sklearn_rf_classifier(n_classes) without return types