code: def test_wrong_inputs():
      X = np.array([[0.0, 2.0], [1.0, 0.5]])
      y = np.array([0, 1])
      model = cuml.ensemble.RandomForestRegressor().fit(X, y)
  
      # background/X different dtype
      with pytest.raises(
          ValueError,
          match="Expected background data" " to have the same dtype",
      ):
          explainer = TreeExplainer(
              model=model, data=X.astype(np.float32)
          )
          explainer.shap_values(X)
  
      # background/X different number columns
      with pytest.raises(RuntimeError):
          explainer = TreeExplainer(model=model, data=X[:, 0:1])
          explainer.shap_values(X)
  
      with pytest.raises(
          ValueError,
          match="Interventional algorithm not"
          " supported for interactions. Please"
          " specify data as None in constructor.",
      ):
          explainer = TreeExplainer(
              model=model, data=X.astype(np.float32)
          )
          explainer.shap_interaction_values(X)
  
      with pytest.raises(
          ValueError, match="Unknown interactions method."
      ):
          explainer = TreeExplainer(model=model)
          explainer.shap_interaction_values(X, method="asdasd")
  
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 22 for calling a global function with example usage: test_wrong_inputs() without return types