Loading src/suggestions.py +2 −2 Original line number Diff line number Diff line from optuna import Trial from typing import Tuple, List from typing import Tuple def suggest_params_general(trial: Trial) -> None: Loading Loading @@ -91,7 +91,7 @@ def suggest_dropout(trial: Trial, n: int, is_in_fc: bool) -> None: name_prefix = "l_layers_{}_layer_{}".format(trial.params["l_layers"], n) if is_in_fc \ else "c_layers_{}_layer_{}".format(trial.params["c_layers"], n) contains_dropout = trial.suggest_categorical("{}_contains_dropout".format(name_prefix), [False, False, False]) contains_dropout = trial.suggest_categorical("{}_contains_dropout".format(name_prefix), [False, True, True]) if contains_dropout: rate_low = 0.3 if is_in_fc else 0.1 Loading Loading
src/suggestions.py +2 −2 Original line number Diff line number Diff line from optuna import Trial from typing import Tuple, List from typing import Tuple def suggest_params_general(trial: Trial) -> None: Loading Loading @@ -91,7 +91,7 @@ def suggest_dropout(trial: Trial, n: int, is_in_fc: bool) -> None: name_prefix = "l_layers_{}_layer_{}".format(trial.params["l_layers"], n) if is_in_fc \ else "c_layers_{}_layer_{}".format(trial.params["c_layers"], n) contains_dropout = trial.suggest_categorical("{}_contains_dropout".format(name_prefix), [False, False, False]) contains_dropout = trial.suggest_categorical("{}_contains_dropout".format(name_prefix), [False, True, True]) if contains_dropout: rate_low = 0.3 if is_in_fc else 0.1 Loading