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refactor(sac): simplify optimizer return structure

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Khalil Meftah
2026-04-18 15:45:22 +02:00
parent 2c97cb23c8
commit 72fb0faf62
1 changed files with 3 additions and 7 deletions
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src/lerobot/rl/algorithms/sac/sac_algorithm.py
+3 -7
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@@ -457,14 +457,10 @@ class SACAlgorithm(RLAlgorithm):
policy (nn.Module): The policy model containing the actor, critic, and temperature components. policy (nn.Module): The policy model containing the actor, critic, and temperature components.
Returns: Returns:
Tuple[Dict[str, torch.optim.Optimizer], Optional[torch.optim.lr_scheduler._LRScheduler]]: A dictionary mapping component names ("actor", "critic", "temperature")
A tuple containing: to their respective Adam optimizers.
- `optimizers`: A dictionary mapping component names ("actor", "critic", "temperature") to their respective Adam optimizers.
- `lr_scheduler`: Currently set to `None` but can be extended to support learning rate scheduling.
""" """
actor_params = self.policy.get_optim_params()["actor"] actor_params = self.policy.get_optim_params()["actor"]
lr_scheduler = None
self.optimizers = { self.optimizers = {
"actor": torch.optim.Adam(actor_params, lr=self.config.actor_lr), "actor": torch.optim.Adam(actor_params, lr=self.config.actor_lr),
"critic": torch.optim.Adam(self.critic_ensemble.parameters(), lr=self.config.critic_lr), "critic": torch.optim.Adam(self.critic_ensemble.parameters(), lr=self.config.critic_lr),
@@ -474,7 +470,7 @@ class SACAlgorithm(RLAlgorithm):
self.optimizers["discrete_critic"] = torch.optim.Adam( self.optimizers["discrete_critic"] = torch.optim.Adam(
self.discrete_critic.parameters(), lr=self.config.critic_lr self.discrete_critic.parameters(), lr=self.config.critic_lr
) )
return self.optimizers, lr_scheduler return self.optimizers
def get_optimizers(self) -> dict[str, Optimizer]: def get_optimizers(self) -> dict[str, Optimizer]:
return self.optimizers return self.optimizers