fix(dpmodel): align Loss.call return type with implementation

deepmd/dpmodel/loss/ener.py

@@ -93,7 +93,7 @@ def call(
         natoms: int,
         model_dict: dict[str, Array],
         label_dict: dict[str, Array],
-    ) -> dict[str, Array]:
+    ) -> tuple[Array, dict[str, Array]]:
         """Calculate loss from model results and labeled results."""
         energy = model_dict["energy"]
         force = model_dict["force"]
@@ -244,10 +244,10 @@ def call(
         if self.has_gf:
             find_drdq = label_dict["find_drdq"]
             drdq = label_dict["drdq"]
-            force_reshape_nframes = xp.reshape(force, (-1, natoms[0] * 3))
-            force_hat_reshape_nframes = xp.reshape(force_hat, (-1, natoms[0] * 3))
+            force_reshape_nframes = xp.reshape(force, (-1, natoms * 3))
+            force_hat_reshape_nframes = xp.reshape(force_hat, (-1, natoms * 3))
             drdq_reshape = xp.reshape(
-                drdq, (-1, natoms[0] * 3, self.numb_generalized_coord)
+                drdq, (-1, natoms * 3, self.numb_generalized_coord)
             )
             gen_force_hat = xp.einsum(
                 "bij,bi->bj", drdq_reshape, force_hat_reshape_nframes

deepmd/dpmodel/loss/loss.py

@@ -28,8 +28,16 @@ def call(
         natoms: int,
         model_dict: dict[str, Array],
         label_dict: dict[str, Array],
-    ) -> dict[str, Array]:
-        """Calculate loss from model results and labeled results."""
+    ) -> tuple[Array, dict[str, Array]]:
+        """Calculate loss from model results and labeled results.
+
+        Returns
+        -------
+        loss
+            The scalar loss to minimize.
+        more_loss
+            A dictionary of additional loss terms/metrics for logging.
+        """
 
     @property
     @abstractmethod