code: def test_acq_optimizer(base_estimator):
      err = f"Regressor {type(base_estimator)} requires `acq_optimizer`='sampling'"
      with pytest.raises(ValueError, match=err):
          Optimizer(
              [(-2.0, 2.0)],
              base_estimator=base_estimator,
              n_initial_points=1,
              acq_optimizer="lbfgs",
          )
  
imports: from hyperparameter_hunter.optimization.backends.skopt.engine import Optimizer
  import numpy
  import pytest
  from scipy.optimize import OptimizeResult
  from sklearn.multioutput import MultiOutputRegressor
  from sklearn.utils.testing import assert_array_equal
  from skopt.benchmarks import bench1, bench1_with_time
  from skopt.learning import ExtraTreesRegressor, RandomForestRegressor
  from skopt.learning import GradientBoostingQuantileRegressor
label_desc: Use image node_id 6 for calling a global function with example usage: test_acq_optimizer(base_estimator) without return types