fix ut

Author: iProzd

deepmd/pd/loss/ener.py

@@ -125,6 +125,10 @@ def __init__(
             raise NotImplementedError(
                 "Paddle backend does not support f_use_norm=True."
             )
+        if kwargs.get("use_default_pf", False):
+            raise NotImplementedError(
+                "Paddle backend does not support use_default_pf=True."
+            )
 
         self.starter_learning_rate = starter_learning_rate
         self.has_e = (start_pref_e != 0.0 and limit_pref_e != 0.0) or inference
@@ -554,7 +558,7 @@ def serialize(self) -> dict:
         """
         return {
             "@class": "EnergyLoss",
-            "@version": 2,
+            "@version": 3,
             "starter_learning_rate": self.starter_learning_rate,
             "start_pref_e": self.start_pref_e,
             "limit_pref_e": self.limit_pref_e,
@@ -575,6 +579,7 @@ def serialize(self) -> dict:
             "huber_delta": self.huber_delta,
             "loss_func": self.loss_func,
             "f_use_norm": self.f_use_norm,
+            "use_default_pf": getattr(self, "use_default_pf", False),
         }
 
     @classmethod

deepmd/tf/loss/ener.py

@@ -133,6 +133,10 @@ def __init__(
             raise NotImplementedError(
                 "TensorFlow backend does not support f_use_norm=True."
             )
+        if kwargs.get("use_default_pf", False):
+            raise NotImplementedError(
+                "TensorFlow backend does not support use_default_pf=True."
+            )
 
         self.starter_learning_rate = starter_learning_rate
         self.start_pref_e = start_pref_e
@@ -531,7 +535,7 @@ def serialize(self, suffix: str = "") -> dict:
         """
         return {
             "@class": "EnergyLoss",
-            "@version": 2,
+            "@version": 3,
             "starter_learning_rate": self.starter_learning_rate,
             "start_pref_e": self.start_pref_e,
             "limit_pref_e": self.limit_pref_e,
@@ -552,6 +556,7 @@ def serialize(self, suffix: str = "") -> dict:
             "huber_delta": self.huber_delta,
             "loss_func": self.loss_func,
             "f_use_norm": self.f_use_norm,
+            "use_default_pf": getattr(self, "use_default_pf", False),
         }
 
     @classmethod