def test_init_(self) -> None:
target_param_names = ["learning_rate"] # Invalid parameter name.
with pytest.raises(NotImplementedError) as execinfo:
_OptunaObjective(target_param_names, {}, None, {}, 0, "tune_learning_rate", None)
assert execinfo.type is NotImplementedError
def test_call(self):
# type: () -> None
target_param_names = ["lambda_l1"]
lgbm_params = {} # type: Dict[str, Any]
train_set = lgb.Dataset(None)
val_set = lgb.Dataset(None)
lgbm_kwargs = {"valid_sets": val_set}
best_score = -np.inf
with turnoff_train():
objective = _OptunaObjective(
target_param_names,
lgbm_params,
train_set,
lgbm_kwargs,
best_score,
"tune_lambda_l1",
None,
)
study = optuna.create_study(direction="minimize")
study.optimize(objective, n_trials=10)
assert study.best_value == 0.5
def _create_objective(
self,
target_param_names: List[str],
train_set: "lgb.Dataset",
step_name: str,
pbar: Optional[tqdm.tqdm],
) -> _OptunaObjective:
return _OptunaObjective(
target_param_names,
self.lgbm_params,
train_set,
self.lgbm_kwargs,
self.best_score,
step_name=step_name,
model_dir=self._model_dir,
pbar=pbar,
)
