update combined loss for accelerate classification training speed

ppcls/loss/__init__.py

@@ -44,12 +44,18 @@ class CombinedLoss(nn.Layer):
 
     def __call__(self, input, batch):
         loss_dict = {}
-        for idx, loss_func in enumerate(self.loss_func):
-            loss = loss_func(input, batch)
-            weight = self.loss_weight[idx]
-            loss = {key: loss[key] * weight for key in loss}
+        # just for accelerate classification traing speed
+        if len(self.loss_func) == 1:
+            loss = self.loss_func[0](input, batch)
             loss_dict.update(loss)
-        loss_dict["loss"] = paddle.add_n(list(loss_dict.values()))
+            loss_dict["loss"] = list(loss.values())[0]
+        else:
+            for idx, loss_func in enumerate(self.loss_func):
+                loss = loss_func(input, batch)
+                weight = self.loss_weight[idx]
+                loss = {key: loss[key] * weight for key in loss}
+                loss_dict.update(loss)
+            loss_dict["loss"] = paddle.add_n(list(loss_dict.values()))
         return loss_dict