diff --git a/cleanrl/ppo_continuous_action_wandb.py b/cleanrl/ppo_continuous_action_wandb.py
index 28b4faf0..79b2abbb 100644
--- a/cleanrl/ppo_continuous_action_wandb.py
+++ b/cleanrl/ppo_continuous_action_wandb.py
@@ -838,7 +838,7 @@ def train(cfg):
                     real_next_obs[idx] = infos["final_observation"][idx]
             
             if cfg.use_csc:
-                csc_rb.add(obs_, real_next_obs, action, np.array(terminated).astype(float), done, infos)
+                csc_rb.add(obs_, real_next_obs, action.cpu().numpy(), np.array(terminated).astype(float), done, infos)
 
             info_dict = {'reward': reward, 'done': done, 'cost': cost, 'obs': obs} 
             # if cfg.collect_data:
@@ -868,7 +868,7 @@ def train(cfg):
                     f_dones[i] = next_done[i].unsqueeze(0).to(device) if f_dones[i] is None else torch.concat([f_dones[i], next_done[i].unsqueeze(0).to(device)], axis=0)
 
             obs_ = next_obs_
-            obs = next_obs
+            obs_old = next_obs
             # if global_step % cfg.update_risk_model == 0 and cfg.fine_tune_risk:
             # if cfg.use_risk and (global_step > cfg.start_risk_update and cfg.fine_tune_risk) and global_step % cfg.risk_update_period == 0:
             #     for epoch in range(cfg.num_risk_epochs):