使用onnx进行infer逻辑，未完成

douzero/dmc/dmc.py

@@ -53,7 +53,7 @@ def learn(position, actor_models, model, batch, optimizer, flags, lock):
     if len(episode_returns) > 0:
         mean_episode_return_buf[position].append(torch.mean(episode_returns).to(device))
     with lock:
-        learner_outputs = model(obs_z, obs_x, return_value=True)
+        learner_outputs = model(obs_z, obs_x)
         if position == "bidding":
             loss = compute_loss(learner_outputs['values'], target)
             # pass

douzero/dmc/utils.py

@@ -118,7 +118,8 @@ def act(i, device, batch_queues, model, flags, onnx_frame):
                 for p in positions:
                     if p != 'bidding':
                         model_path = '%s/%s/model_%s.onnx' % (flags.savedir, flags.xpid, p)
-                        model.set_onnx_model(p, os.path.abspath(model_path))
+                        if os.path.exists(model_path):
+                            model.set_onnx_model(p, os.path.abspath(model_path))
 
             for bid_obs in bid_obs_buffer:
                 obs_z_buf["bidding"].append(bid_obs['z_batch'])