Update tacotron2_updater.py

paddlespeech/t2s/models/tacotron2/tacotron2_updater.py

@@ -114,7 +114,7 @@ class Tacotron2Updater(StandardUpdater):
         optimizer.step()
 
         if self.use_guided_attn_loss:
-            report("eval/attn_loss", float(attn_loss))
+            report("train/attn_loss", float(attn_loss))
             losses_dict["attn_loss"] = float(attn_loss)
         
         report("train/l1_loss", float(l1_loss))
@@ -204,17 +204,19 @@ class Tacotron2Evaluator(StandardEvaluator):
             attn_loss = self.attn_loss(
                 att_ws=att_ws, ilens=batch["text_lengths"] + 1, olens=olens_in)
             loss = loss + attn_loss
+        
+        if self.use_guided_attn_loss:
+            report("eval/attn_loss", float(attn_loss))
+            losses_dict["attn_loss"] = float(attn_loss)
 
         report("eval/l1_loss", float(l1_loss))
         report("eval/mse_loss", float(mse_loss))
         report("eval/bce_loss", float(bce_loss))
-        report("eval/attn_loss", float(attn_loss))
         report("eval/loss", float(loss))
 
         losses_dict["l1_loss"] = float(l1_loss)
         losses_dict["mse_loss"] = float(mse_loss)
         losses_dict["bce_loss"] = float(bce_loss)
-        losses_dict["attn_loss"] = float(attn_loss)
         losses_dict["loss"] = float(loss)
         self.msg += ', '.join('{}: {:>.6f}'.format(k, v)
                               for k, v in losses_dict.items())