Update

[ghstack-poisoned]

sota-implementations/td3/td3.py

@@ -49,7 +49,8 @@ def main(cfg: "DictConfig"):  # noqa: F821
             device = torch.device("cuda:0")
         else:
             device = torch.device("cpu")
-    device = torch.device(device)
+    else:
+        device = torch.device(device)
 
     # Create logger
     exp_name = generate_exp_name("TD3", cfg.logger.exp_name)
@@ -72,7 +73,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
     np.random.seed(cfg.env.seed)
 
     # Create environments
-    train_env, eval_env = make_environment(cfg, logger=logger)
+    train_env, eval_env = make_environment(cfg, logger=logger, device=device)
 
     # Create agent
     model, exploration_policy = make_td3_agent(cfg, train_env, eval_env, device)
@@ -91,7 +92,11 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
     # Create off-policy collector
     collector = make_collector(
-        cfg, train_env, exploration_policy, compile_mode=compile_mode
+        cfg,
+        train_env,
+        exploration_policy,
+        compile_mode=compile_mode,
+        device=device,
     )
 
     # Create replay buffer

sota-implementations/td3/utils.py

@@ -75,13 +75,14 @@ def apply_env_transforms(env, max_episode_steps):
     return transformed_env
 
 
-def make_environment(cfg, logger=None):
+def make_environment(cfg, logger, device):
     """Make environments for training and evaluation."""
     partial = functools.partial(env_maker, cfg=cfg)
     parallel_env = ParallelEnv(
         cfg.collector.env_per_collector,
         EnvCreator(partial),
         serial_for_single=True,
+        device=device,
     )
     parallel_env.set_seed(cfg.env.seed)
 
@@ -98,6 +99,7 @@ def make_environment(cfg, logger=None):
             cfg.collector.env_per_collector,
             EnvCreator(partial),
             serial_for_single=True,
+            device=device,
         ),
         trsf_clone,
     )
@@ -109,22 +111,19 @@ def make_environment(cfg, logger=None):
 # ---------------------------
 
 
-def make_collector(cfg, train_env, actor_model_explore, compile_mode):
+def make_collector(cfg, train_env, actor_model_explore, compile_mode, device):
     """Make collector."""
-    device = cfg.collector.device
-    if device in ("", None):
-        if torch.cuda.is_available():
-            device = torch.device("cuda:0")
-        else:
-            device = torch.device("cpu")
+    collector_device = cfg.collector.device
+    if collector_device in ("", None):
+        collector_device = device
     collector = SyncDataCollector(
         train_env,
         actor_model_explore,
         init_random_frames=cfg.collector.init_random_frames,
         frames_per_batch=cfg.collector.frames_per_batch,
         total_frames=cfg.collector.total_frames,
         reset_at_each_iter=cfg.collector.reset_at_each_iter,
-        device=device,
+        device=collector_device,
         compile_policy={"mode": compile_mode} if compile_mode else False,
         cudagraph_policy=cfg.compile.cudagraphs,
     )