Add memory optimization option to ReplayBuffer

- Introduce `optimize_memory` parameter to reduce memory usage in replay buffer
- Implement simplified memory optimization by not storing duplicate next_states
- Update learner server and buffer initialization to use memory optimization by default

lerobot/scripts/server/learner_server.py

@@ -154,6 +154,7 @@ def initialize_replay_buffer(
             device=device,
             state_keys=cfg.policy.input_shapes.keys(),
             storage_device=device,
+            optimize_memory=True,
         )
 
     dataset = LeRobotDataset(
@@ -166,6 +167,7 @@ def initialize_replay_buffer(
         capacity=cfg.training.online_buffer_capacity,
         device=device,
         state_keys=cfg.policy.input_shapes.keys(),
+        optimize_memory=True,
     )
 
 
@@ -648,6 +650,7 @@ def train(cfg: DictConfig, out_dir: str | None = None, job_name: str | None = No
             action_mask=active_action_dims,
             action_delta=cfg.env.wrapper.delta_action,
             storage_device=device,
+            optimize_memory=True,
         )
         batch_size: int = batch_size // 2  # We will sample from both replay buffer