only set training mode on first entrance and exiting valid

deepmd/pt/train/training.py

@@ -656,8 +656,6 @@ def step(_step_id, task_key="Default") -> None:
             # PyTorch Profiler
             if self.enable_profiler or self.profiling:
                 prof.step()
-            if not self.wrapper.training:
-                self.wrapper.train()
             if isinstance(self.lr_exp, dict):
                 _lr = self.lr_exp[task_key]
             else:
@@ -766,7 +764,7 @@ def fake_model():
             if self.display_in_training and (
                 display_step_id % self.disp_freq == 0 or display_step_id == 1
             ):
-                self.wrapper.eval()
+                self.wrapper.eval() # Will set to train mode before fininshing validation
 
                 def log_loss_train(_loss, _more_loss, _task_key="Default"):
                     results = {}
@@ -872,6 +870,7 @@ def log_loss_valid(_task_key="Default"):
                                         learning_rate=None,
                                     )
                                 )
+                self.wrapper.train()
 
                 current_time = time.time()
                 train_time = current_time - self.t0
@@ -926,7 +925,7 @@ def log_loss_valid(_task_key="Default"):
                     writer.add_scalar(
                         f"{task_key}/{item}", more_loss[item], display_step_id
                     )
-
+        self.wrapper.train()
         self.t0 = time.time()
         self.total_train_time = 0.0
         for step_id in range(self.num_steps):