Merge pull request #3 from HighCWu/diffsinger_tmp

fix diffsinger loss target to noisy_mel

paddlespeech/t2s/models/diffsinger/diffsinger.py

@@ -236,8 +236,9 @@ class DiffSinger(nn.Layer):
         cond_fs2 = cond_fs2.transpose((0, 2, 1))
 
         # get the output(final mel) from diffusion module
-        mel = self.diffusion(speech.transpose((0, 2, 1)), cond_fs2.detach())
-        return mel[0], mel_masks
+        mel, mel_ref = self.diffusion(
+            speech.transpose((0, 2, 1)), cond_fs2.detach())
+        return mel, mel_ref, mel_masks
 
     def inference(
             self,
@@ -271,7 +272,8 @@ class DiffSinger(nn.Layer):
         cond_fs2 = cond_fs2.transpose((0, 2, 1))
         # mel, _ = self.diffusion(mel_fs2, cond_fs2)
         noise = paddle.randn(mel_fs2.shape)
-        mel = self.diffusion.inference(noise=noise, cond=cond_fs2, ref_x=mel_fs2, num_inference_steps=100)
+        mel = self.diffusion.inference(
+            noise=noise, cond=cond_fs2, ref_x=mel_fs2, num_inference_steps=100)
         mel = mel.transpose((0, 2, 1))
         return mel[0]
 

paddlespeech/t2s/models/diffsinger/diffsinger_updater.py

@@ -16,7 +16,6 @@ from pathlib import Path
 from typing import Dict
 
 import paddle
-from paddle import DataParallel
 from paddle import distributed as dist
 from paddle.io import DataLoader
 from paddle.nn import Layer
@@ -110,8 +109,8 @@ class DiffSingerUpdater(StandardUpdater):
                 olens=olens,
                 spk_logits=spk_logits,
                 spk_ids=spk_id, )
-            
-            loss_fs2 = l1_loss_fs2 + ssim_loss_fs2 + duration_loss + pitch_loss + energy_loss 
+
+            loss_fs2 = l1_loss_fs2 + ssim_loss_fs2 + duration_loss + pitch_loss + energy_loss
 
             self.optimizer_fs2.clear_grad()
             loss_fs2.backward()
@@ -140,7 +139,7 @@ class DiffSingerUpdater(StandardUpdater):
             for param in self.model.fs2.parameters():
                 param.trainable = False
 
-            mel, mel_masks = self.model(
+            mel, mel_ref, mel_masks = self.model(
                 text=batch["text"],
                 note=batch["note"],
                 note_dur=batch["note_dur"],
@@ -156,9 +155,10 @@ class DiffSingerUpdater(StandardUpdater):
                 train_fs2=False, )
 
             mel = mel.transpose((0, 2, 1))
+            mel_ref = mel_ref.transpose((0, 2, 1))
             mel_masks = mel_masks.transpose((0, 2, 1))
             l1_loss_ds = self.criterion_ds(
-                ref_mels=batch["speech"],
+                ref_mels=mel_ref,
                 out_mels=mel,
                 mel_masks=mel_masks, )
 
@@ -238,6 +238,6 @@ class DiffSingerEvaluator(StandardEvaluator):
         losses_dict["l1_loss_ds"] = float(l1_loss_ds)
         losses_dict["loss_ds"] = float(loss_ds)
         self.msg += ', '.join('{}: {:>.6f}'.format(k, v)
-                                for k, v in losses_dict.items())
+                              for k, v in losses_dict.items())
 
         self.logger.info(self.msg)