fix(show): align backend serialize output contracts

Route JAX DeepEval serialization through the existing file-based serializer so .hlo and .savedmodel models follow the supported path instead of calling unimplemented model-level serialize() methods.

Also add the missing pt_version field to the PyTorch backend serializer and wrap pt_expt serialization in the backend-unified payload expected by dp show serialization-tree.

Add a targeted pt_expt serialization contract test.

Authored by OpenClaw (model: gpt-5.4)

Author: njzjz-bot

deepmd/jax/infer/deep_eval.py

@@ -191,17 +191,11 @@ def get_ntypes_spin(self) -> int:
         return 0
 
     def serialize(self) -> dict[str, Any]:
-        model = self.dp
-        data: dict[str, Any] = {
-            "backend": "JAX",
-            "jax_version": jax.__version__,
-            "model": model.serialize(),
-            "model_def_script": json.loads(model.get_model_def_script()),
-            "@variables": {},
-        }
-        if model.get_min_nbor_dist() is not None:
-            data["@variables"]["min_nbor_dist"] = model.get_min_nbor_dist()
-        return data
+        from deepmd.jax.utils.serialization import (
+            serialize_from_file,
+        )
+
+        return serialize_from_file(self.model_path)
 
     def eval(
         self,

deepmd/pt/infer/deep_eval.py

@@ -706,6 +706,7 @@ def serialize(self) -> dict[str, Any]:
         model = self.dp.model["Default"]
         data: dict[str, Any] = {
             "backend": "PyTorch",
+            "pt_version": str(torch.__version__),
             "model": model.serialize(),
             "model_def_script": self.get_model_def_script(),
             "@variables": {},

deepmd/pt_expt/infer/deep_eval.py

@@ -670,7 +670,13 @@ def serialize(self) -> dict[str, Any]:
             serialize_from_file,
         )
 
-        return serialize_from_file(self.model_path)
+        model_dict = serialize_from_file(self.model_path)
+        return {
+            "backend": "PyTorch Exportable",
+            "model": model_dict,
+            "model_def_script": self.get_model_def_script(),
+            "@variables": {},
+        }
 
     def get_model(self) -> torch.nn.Module:
         """Get the exported model module.

source/tests/pt_expt/infer/test_deep_eval.py

@@ -109,6 +109,16 @@ def test_get_model_def_script(self) -> None:
         self.assertAlmostEqual(mds["rcut"], self.rcut)
         self.assertEqual(mds["sel"], list(self.sel))
 
+    def test_serialize_contract(self) -> None:
+        data = self.dp.deep_eval.serialize()
+        self.assertEqual(data["backend"], "PyTorch Exportable")
+        self.assertIn("model", data)
+        self.assertIn("model_def_script", data)
+        self.assertIn("@variables", data)
+        self.assertIsInstance(data["@variables"], dict)
+        self.assertEqual(data["model_def_script"]["type_map"], self.type_map)
+        self.assertEqual(data["model"], serialize_from_file(self.tmpfile.name))
+
     def test_eval_consistency(self) -> None:
         """Test that DeepPot.eval gives same results as direct model forward."""
         rng = np.random.default_rng(GLOBAL_SEED)