def test_log_completed_trial_skip_storage_access() -> None:
study = create_study()
# Create a trial to retrieve it as the `study.best_trial`.
study.optimize(lambda _: 0.0, n_trials=1)
trial = Trial(study, study._storage.create_new_trial(study._study_id))
storage = study._storage
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(trial, [1.0])
# Trial.best_trial and Trial.best_params access storage.
assert mock_object.call_count == 2
logging.set_verbosity(logging.WARNING)
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(trial, [1.0])
assert mock_object.call_count == 0
logging.set_verbosity(logging.DEBUG)
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(trial, [1.0])
assert mock_object.call_count == 2
def test_log_completed_trial_skip_storage_access() -> None:
study = create_study()
# Create a trial to retrieve it as the `study.best_trial`.
study.optimize(lambda _: 0.0, n_trials=1)
frozen_trial = study.best_trial
storage = study._storage
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(frozen_trial)
assert mock_object.call_count == 1
logging.set_verbosity(logging.WARNING)
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(frozen_trial)
assert mock_object.call_count == 0
logging.set_verbosity(logging.DEBUG)
with patch.object(storage, "get_best_trial",
wraps=storage.get_best_trial) as mock_object:
study._log_completed_trial(frozen_trial)
assert mock_object.call_count == 1
def logging_setup() -> Generator[None, None, None]:
# We need to reconstruct our default handler to properly capture stderr.
logging._reset_library_root_logger()
logging.enable_default_handler()
logging.set_verbosity(logging.INFO)
logging.enable_propagation()
yield
# After testing, restore default propagation setting.
logging.disable_propagation()
def solve(self, optimization_function):
from optuna import create_study
from optuna.logging import set_verbosity
from optuna.samplers import TPESampler
study = create_study(direction='minimize',
sampler=TPESampler(self.seed))
n_dim = optimization_function.X.shape[1]
n_dim_surface = n_dim - 1
def objective(trial):
uniform = np.zeros(n_dim_surface)
for i in range(n_dim_surface):
uniform[i] = trial.suggest_uniform(f'uniform[{i}]', 0, 1)
return optimization_function.compute(uniform)
set_verbosity(0)
study.optimize(objective, n_trials=self.n_trials)
def _set_verbosity(self):
# type: () -> None
if self.verbose > 1:
logging.set_verbosity(DEBUG)
elif self.verbose > 0:
logging.set_verbosity(INFO)
else:
logging.set_verbosity(WARNING)
def test_log_completed_trial(capsys: _pytest.capture.CaptureFixture) -> None:
# We need to reconstruct our default handler to properly capture stderr.
logging._reset_library_root_logger()
logging.set_verbosity(logging.INFO)
study = create_study()
study.optimize(lambda _: 1.0, n_trials=1)
_, err = capsys.readouterr()
assert "Trial 0" in err
logging.set_verbosity(logging.WARNING)
study.optimize(lambda _: 1.0, n_trials=1)
_, err = capsys.readouterr()
assert "Trial 1" not in err
logging.set_verbosity(logging.DEBUG)
study.optimize(lambda _: 1.0, n_trials=1)
_, err = capsys.readouterr()
assert "Trial 2" in err
