code: def test_logs_bounds():
      def f(x, y):
          return x + y
  
      optimizer = BayesianOptimization(
          f=f, pbounds={"x": (-2, 2), "y": (-2, 2)}
      )
  
      with pytest.warns(UserWarning):
          load_logs(optimizer, [str(test_dir / "test_logs_bounds.log")])
  
      assert len(optimizer.space) == 5
  
file_path: BayesianOptimization/tests/test_util.py
imports: import pytest
  import numpy
  from bayes_opt import BayesianOptimization
  from bayes_opt.util import UtilityFunction, Colours
  from bayes_opt.util import acq_max, load_logs, ensure_rng
  from sklearn.gaussian_process.kernels import Matern
  from sklearn.gaussian_process import GaussianProcessRegressor
  from scipy.optimize import NonlinearConstraint
  from pathlib import Path
label_desc: Use image node_id 8 for calling a global function with example usage: test_logs_bounds() and returns: unknown