code: def test_sentinels_optimization(env_0):
      optimizer = GBRT(iterations=2)
      optimizer.forge_experiment(
          model_initializer=XGBClassifier,
          model_init_params=dict(
              objective="reg:linear",
              max_depth=Integer(2, 20),
              subsample=0.5,
          ),
          model_extra_params=dict(
              fit=dict(
                  eval_set=get_all_sentinels(env_0),
                  early_stopping_rounds=5,
                  eval_metric=Categorical(["auc", "mae"]),
              )
          ),
      )
      optimizer.go()
  
file_path: hyperparameter_hunter/tests/test_sentinels.py
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical, GBRT
  from hyperparameter_hunter import lambda_callback
  from hyperparameter_hunter.sentinels import DatasetSentinel
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  import pytest
  import sys
label_desc: Use image node_id 6 for calling a global function with example usage: test_sentinels_optimization(env_0) without return types