diff --git a/douzero/evaluation/deep_agent.py b/douzero/evaluation/deep_agent.py
index 398bb54..e1a8561 100644
--- a/douzero/evaluation/deep_agent.py
+++ b/douzero/evaluation/deep_agent.py
@@ -8,6 +8,9 @@ from douzero.env.env import get_obs
 
 def _load_model(position, model_path, model_type, use_legacy, use_lite, use_onnx=False):
     from douzero.dmc.models import model_dict_new, model_dict_new_lite, model_dict, model_dict_legacy, model_dict_lite
+    model_path = model_path + '.onnx'
+    if use_onnx and os.path.exists(model_path):
+        return None
     model = None
     if model_type == "general":
         if use_lite:
@@ -29,21 +32,19 @@ def _load_model(position, model_path, model_type, use_legacy, use_lite, use_onnx
     model.load_state_dict(model_state_dict)
     # torch.save(model.state_dict(), model_path.replace(".ckpt", "_nobn.ckpt"))
     model.eval()
-    model_path = model_path + '.onnx'
-    if use_onnx:
-        if not os.path.exists(model_path):
-            onnx_params = model.get_onnx_params(torch.device('cpu'))
-            torch.onnx.export(
-                model,
-                onnx_params['args'],
-                model_path,
-                export_params=True,
-                opset_version=10,
-                do_constant_folding=True,
-                input_names=onnx_params['input_names'],
-                output_names=onnx_params['output_names'],
-                dynamic_axes=onnx_params['dynamic_axes']
-            )
+    if use_onnx and not os.path.exists(model_path):
+        onnx_params = model.get_onnx_params(torch.device('cpu'))
+        torch.onnx.export(
+            model,
+            onnx_params['args'],
+            model_path,
+            export_params=True,
+            opset_version=10,
+            do_constant_folding=True,
+            input_names=onnx_params['input_names'],
+            output_names=onnx_params['output_names'],
+            dynamic_axes=onnx_params['dynamic_axes']
+        )
         return None
 
     return model