code: def test_bounds_checking_2D(et_optimizer, tell_x, tell_y):
      """Test that `tell`-ing points outside of an `Optimizer`'s bounds raises ValueError. The
      parenthesized "high", "low", "ok" values in the `pytest.param` `id` fields refer to which
      dimensions fall outside of the expected bounds and in which direction. "(low, low)" means both
      the first and second dimensions fall below their lower bounds. "(high, ok)" means the first
      dimension exceeds its upper bound, while the second dimension is within its expected bounds
      """
      with pytest.raises(ValueError):
          et_optimizer.tell(tell_x, tell_y)
  
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 12 for calling a global function with example usage: test_bounds_checking_2D(et_optimizer, tell_x, tell_y) without return types