Update for tokenizer API

TTS/utils/synthesizer.py

@@ -114,8 +114,7 @@ class Synthesizer(object):
 
         self.tts_config = load_config(tts_config_path)
         self.use_phonemes = self.tts_config.use_phonemes
-        self.ap = AudioProcessor(verbose=False, **self.tts_config.audio)
-        self.tokenizer = TTSTokenizer.init_from_config(self.tts_config)
+        self.tts_model = setup_tts_model(config=self.tts_config)
 
         speaker_manager = self._init_speaker_manager()
         language_manager = self._init_language_manager()
@@ -245,7 +244,7 @@ class Synthesizer(object):
             path (str): output path to save the waveform.
         """
         wav = np.array(wav)
-        self.ap.save_wav(wav, path, self.output_sample_rate)
+        self.tts_model.ap.save_wav(wav, path, self.output_sample_rate)
 
     def tts(
         self,
@@ -333,13 +332,10 @@ class Synthesizer(object):
                 text=sen,
                 CONFIG=self.tts_config,
                 use_cuda=self.use_cuda,
-                ap=self.ap,
-                tokenizer=self.tokenizer,
                 speaker_id=speaker_id,
                 language_id=language_id,
                 language_name=language_name,
                 style_wav=style_wav,
-                enable_eos_bos_chars=self.tts_config.enable_eos_bos_chars,
                 use_griffin_lim=use_gl,
                 d_vector=speaker_embedding,
             )
@@ -347,14 +343,14 @@ class Synthesizer(object):
             mel_postnet_spec = outputs["outputs"]["model_outputs"][0].detach().cpu().numpy()
             if not use_gl:
                 # denormalize tts output based on tts audio config
-                mel_postnet_spec = self.ap.denormalize(mel_postnet_spec.T).T
+                mel_postnet_spec = self.tts_model.ap.denormalize(mel_postnet_spec.T).T
                 device_type = "cuda" if self.use_cuda else "cpu"
                 # renormalize spectrogram based on vocoder config
                 vocoder_input = self.vocoder_ap.normalize(mel_postnet_spec.T)
                 # compute scale factor for possible sample rate mismatch
                 scale_factor = [
                     1,
-                    self.vocoder_config["audio"]["sample_rate"] / self.ap.sample_rate,
+                    self.vocoder_config["audio"]["sample_rate"] / self.tts_model.ap.sample_rate,
                 ]
                 if scale_factor[1] != 1:
                     print(" > interpolating tts model output.")
@@ -372,7 +368,7 @@ class Synthesizer(object):
 
             # trim silence
             if self.tts_config.audio["do_trim_silence"] is True:
-                waveform = trim_silence(waveform, self.ap)
+                waveform = trim_silence(waveform, self.tts_model.ap)
 
             wavs += list(waveform)
             wavs += [0] * 10000

TTS/vocoder/models/__init__.py

@@ -28,8 +28,7 @@ def setup_model(config: Coqpit):
             except ModuleNotFoundError as e:
                 raise ValueError(f"Model {config.model} not exist!") from e
     print(" > Vocoder Model: {}".format(config.model))
-    model = MyModel(config)
-    return model
+    return MyModel.init_from_config(config)
 
 
 def setup_generator(c):