def METHOD_NAME():
    X, y = make_regression(
        n_samples=81,
        n_features=10,
        noise=0.1,
        random_state=42,
        dtype=np.float32,
    )
    model = reg().fit(X, y)
    z = model_func_call(X=X, model_func=model.predict, gpu_model=True)
    assert isinstance(z, cp.ndarray)
    z = model_func_call(
        X=cp.asnumpy(X), model_func=dummy_func, gpu_model=False
    )
    assert isinstance(z, cp.ndarray)
    with pytest.raises(TypeError):
        z = model_func_call(X=X, model_func=dummy_func, gpu_model=True)
    model = PCA(n_components=10).fit(X)
    z = model_func_call(X=X, model_func=model.transform, gpu_model=True)
    assert isinstance(z, cp.ndarray)