Using grid search in `trainer.hyperparameter_search`
I am usingoptunaas the backend intrainer.hyperparameter_search().  I would like to use grid search in this method.Even thoughoptunadoes support grid search (seeoptunadoc), I could not see in how do I implement this withtrainer.hyperparameter_search()as it seems the method used here defaults to some complicated strategy andthere is no way to change this default behavior.I know I could set several categorical values like following but this willstilluse default search algorithm rather than enumerating all possible combinations (there should be3\times 3=9parameters to try). So even if I setn_trail=9, the search algorithm might not look at all 9 combinations.def hp_space_optuna(trial):
    return {
        "learning_rate": trial.suggest_categorical("learning_rate", [1e-5, 3e-5, 5e-5]),
        "num_train_epochs": trial.suggest_int("num_train_epochs", 1, 3),
    }

best_trail = trainer.hyperparameter_search(hp_space=hp_space_optuna,
                                           direction="maximize", 
                                           backend="optuna", 
                                           n_trials=9)I am wondering how do I directly use grid search intrainer.hyperparameter_search().