perf(reforcexy): reduce optuna search space

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/ReforceXY/user_data/freqaimodels/ReforceXY.py b/ReforceXY/user_data/freqaimodels/ReforceXY.py
index 76d723f1319c81d11c447ff85d461eb75bc54ada..56017e879a3fe08fc929b13124b4981c9f5f939a 100644 (file)
--- a/ReforceXY/user_data/freqaimodels/ReforceXY.py
+++ b/ReforceXY/user_data/freqaimodels/ReforceXY.py
@@ -1558,7 +1558,6 @@ def get_optimizer_class(optimizer_class_name: str) -> type[th.optim.Optimizer]:
     """
     return {
         "adam": th.optim.Adam,
-        "rmsprop": th.optim.RMSprop,
     }.get(optimizer_class_name, th.optim.Adam)
 
 
@@ -1593,9 +1592,7 @@ def sample_params_ppo(trial: Trial) -> Dict[str, Any]:
         "activation_fn", ["tanh", "relu", "elu", "leaky_relu"]
     )
     activation_fn = get_activation_fn(activation_fn_name)
-    optimizer_class_name = trial.suggest_categorical(
-        "optimizer_class", ["adam", "rmsprop"]
-    )
+    optimizer_class_name = trial.suggest_categorical("optimizer_class", ["adam"])
     optimizer_class = get_optimizer_class(optimizer_class_name)
     return {
         "n_steps": n_steps,
@@ -1653,9 +1650,7 @@ def sample_params_dqn(trial: Trial) -> Dict[str, Any]:
         "activation_fn", ["tanh", "relu", "elu", "leaky_relu"]
     )
     activation_fn = get_activation_fn(activation_fn_name)
-    optimizer_class_name = trial.suggest_categorical(
-        "optimizer_class", ["adam", "rmsprop"]
-    )
+    optimizer_class_name = trial.suggest_categorical("optimizer_class", ["adam"])
     optimizer_class = get_optimizer_class(optimizer_class_name)
     return {
         "gamma": gamma,