code: def test_acq_optimizer(base_estimator):
      with pytest.raises(ValueError) as e:
          Optimizer(
              [(-2.0, 2.0)],
              base_estimator=base_estimator,
              n_initial_points=1,
              acq_optimizer="lbfgs",
          )
      assert "should run with acq_optimizer='sampling'" in str(e.value)
  
imports: import numpy
  import pytest
  from sklearn.multioutput import MultiOutputRegressor
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from skopt import gp_minimize
  from skopt import forest_minimize
  from skopt.benchmarks import bench1, bench1_with_time
  from skopt.benchmarks import branin
  from skopt.learning import ExtraTreesRegressor, RandomForestRegressor
  from skopt.learning import GradientBoostingQuantileRegressor
  from skopt.optimizer import Optimizer
  from scipy.optimize import OptimizeResult
label_desc: Use image node_id 12 for calling a global function with example usage: test_acq_optimizer(base_estimator) without return types