updata, test=tts

paddlespeech/t2s/exps/fastspeech2/train.py

@@ -145,17 +145,27 @@ def train_sp(args, config):
         # copy conf to output_dir
         shutil.copyfile(args.config, output_dir / config_name)
 
+    if "enable_speaker_classifier" in config.model:
+        enable_spk_cls = config.model.enable_speaker_classifier
+    else:
+        enable_spk_cls = False
+
     updater = FastSpeech2Updater(
         model=model,
         optimizer=optimizer,
         dataloader=train_dataloader,
         output_dir=output_dir,
-        **config["updater"])
+        **config["updater"],
+        enable_spk_cls=enable_spk_cls)
 
     trainer = Trainer(updater, (config.max_epoch, 'epoch'), output_dir)
 
     evaluator = FastSpeech2Evaluator(
-        model, dev_dataloader, output_dir=output_dir, **config["updater"])
+        model,
+        dev_dataloader,
+        output_dir=output_dir,
+        **config["updater"],
+        enable_spk_cls=enable_spk_cls)
 
     if dist.get_rank() == 0:
         trainer.extend(evaluator, trigger=(1, "epoch"))

paddlespeech/t2s/models/fastspeech2/fastspeech2_updater.py

@@ -33,7 +33,8 @@ logger.setLevel(logging.INFO)
 
 
 class FastSpeech2Updater(StandardUpdater):
-    def __init__(self,
+    def __init__(
+            self,
             model: Layer,
             optimizer: Optimizer,
             dataloader: DataLoader,
@@ -41,7 +42,8 @@ class FastSpeech2Updater(StandardUpdater):
             use_masking: bool=False,
             spk_loss_scale: float=0.02,
             use_weighted_masking: bool=False,
-                 output_dir: Path=None):
+            output_dir: Path=None,
+            enable_spk_cls: bool=False, ):
         super().__init__(model, optimizer, dataloader, init_state=None)
 
         self.criterion = FastSpeech2Loss(
@@ -54,6 +56,7 @@ class FastSpeech2Updater(StandardUpdater):
         self.logger = logger
         self.msg = ""
         self.spk_loss_scale = spk_loss_scale
+        self.enable_spk_cls = enable_spk_cls
 
     def update_core(self, batch):
         self.msg = "Rank: {}, ".format(dist.get_rank())
@@ -118,7 +121,7 @@ class FastSpeech2Updater(StandardUpdater):
         report("train/duration_loss", float(duration_loss))
         report("train/pitch_loss", float(pitch_loss))
         report("train/energy_loss", float(energy_loss))
-        if speaker_loss != 0.0:
+        if self.enable_spk_cls:
             report("train/speaker_loss", float(speaker_loss))
             report("train/scale_speaker_loss",
                    float(self.spk_loss_scale * speaker_loss))
@@ -128,7 +131,7 @@ class FastSpeech2Updater(StandardUpdater):
         losses_dict["pitch_loss"] = float(pitch_loss)
         losses_dict["energy_loss"] = float(energy_loss)
         losses_dict["energy_loss"] = float(energy_loss)
-        if speaker_loss != 0.0:
+        if self.enable_spk_cls:
             losses_dict["speaker_loss"] = float(speaker_loss)
             losses_dict["scale_speaker_loss"] = float(self.spk_loss_scale *
                                                       speaker_loss)
@@ -144,7 +147,8 @@ class FastSpeech2Evaluator(StandardEvaluator):
                  use_masking: bool=False,
                  use_weighted_masking: bool=False,
                  spk_loss_scale: float=0.02,
-                 output_dir: Path=None):
+                 output_dir: Path=None,
+                 enable_spk_cls: bool=False):
         super().__init__(model, dataloader)
 
         log_file = output_dir / 'worker_{}.log'.format(dist.get_rank())
@@ -153,6 +157,7 @@ class FastSpeech2Evaluator(StandardEvaluator):
         self.logger = logger
         self.msg = ""
         self.spk_loss_scale = spk_loss_scale
+        self.enable_spk_cls = enable_spk_cls
 
         self.criterion = FastSpeech2Loss(
             use_masking=use_masking, use_weighted_masking=use_weighted_masking)
@@ -213,7 +218,7 @@ class FastSpeech2Evaluator(StandardEvaluator):
         report("eval/duration_loss", float(duration_loss))
         report("eval/pitch_loss", float(pitch_loss))
         report("eval/energy_loss", float(energy_loss))
-        if speaker_loss != 0.0:
+        if self.enable_spk_cls:
             report("train/speaker_loss", float(speaker_loss))
             report("train/scale_speaker_loss",
                    float(self.spk_loss_scale * speaker_loss))
@@ -222,7 +227,7 @@ class FastSpeech2Evaluator(StandardEvaluator):
         losses_dict["duration_loss"] = float(duration_loss)
         losses_dict["pitch_loss"] = float(pitch_loss)
         losses_dict["energy_loss"] = float(energy_loss)
-        if speaker_loss != 0.0:
+        if self.enable_spk_cls:
             losses_dict["speaker_loss"] = float(speaker_loss)
             losses_dict["scale_speaker_loss"] = float(self.spk_loss_scale *
                                                       speaker_loss)