fix: add serialize, deserialize

deepmd/tf/fit/dipole.py

@@ -89,6 +89,7 @@ def __init__(
         self.seed = seed
         self.uniform_seed = uniform_seed
         self.seed_shift = one_layer_rand_seed_shift()
+        self.activation_function_name = activation_function
         self.fitting_activation_fn = get_activation_func(activation_function)
         self.fitting_precision = get_precision(precision)
         self.dim_rot_mat_1 = embedding_width
@@ -333,3 +334,58 @@ def get_loss(self, loss: dict, lr) -> Loss:
             tensor_size=3,
             label_name="dipole",
         )
+
+    def serialize(self, suffix: str) -> dict:
+        """Serialize the model.
+        Returns
+        -------
+        dict
+            The serialized data
+        """
+        data = {
+            "var_name": "energy",
+            "ntypes": self.ntypes,
+            "dim_descrpt": self.dim_descrpt,
+            # very bad design: type embedding is not passed to the class
+            # TODO: refactor the class
+            "distinguish_types": True,
+            "dim_out": 3,
+            "neuron": self.n_neuron,
+            "resnet_dt": self.resnet_dt,
+            "activation_function": self.activation_function_name,
+            "precision": self.fitting_precision.name,
+            "exclude_types": [],
+            "nets": self.serialize_network(
+                ntypes=self.ntypes,
+                # TODO: consider type embeddings
+                ndim=self.dim_rot_mat_1,
+                in_dim=self.dim_descrpt,
+                neuron=self.n_neuron,
+                activation_function=self.activation_function_name,
+                resnet_dt=self.resnet_dt,
+                variables=self.fitting_net_variables,
+                suffix=suffix,
+            )
+        }
+        return data
+
+    @classmethod
+    def deserialize(cls, data: dict, suffix: str):
+        """Deserialize the model.
+
+        Parameters
+        ----------
+        data : dict
+            The serialized data
+
+        Returns
+        -------
+        Model
+            The deserialized model
+        """
+        fitting = cls(**data)
+        fitting.fitting_net_variables = cls.deserialize_network(
+            data["nets"],
+            suffix=suffix,
+        )
+        return fitting

source/tests/consistent/fitting/test_dipole.py

@@ -119,6 +119,7 @@ def build_tf(self, obj: Any, suffix: str) -> Tuple[list, dict]:
             self.inputs.ravel(),
             self.natoms,
             self.atype,
+            None,
             suffix,
         )