fix vocoder loading

src/f5_tts/api.py

@@ -47,7 +47,7 @@ class F5TTS:
         self.load_ema_model(model_type, ckpt_file, vocab_file, ode_method, use_ema)
 
     def load_vocoder_model(self, local_path):
-        self.vocos = load_vocoder(local_path is not None, local_path, self.device)
+        self.vocoder = load_vocoder(local_path is not None, local_path, self.device)
 
     def load_ema_model(self, model_type, ckpt_file, vocab_file, ode_method, use_ema):
         if model_type == "F5-TTS":
@@ -102,6 +102,7 @@ class F5TTS:
             ref_text,
             gen_text,
             self.ema_model,
+            self.vocoder,
             show_info=show_info,
             progress=progress,
             target_rms=target_rms,

src/f5_tts/infer/infer_cli.py

@@ -113,7 +113,7 @@ wave_path = Path(output_dir) / "infer_cli_out.wav"
 # spectrogram_path = Path(output_dir) / "infer_cli_out.png"
 vocos_local_path = "../checkpoints/charactr/vocos-mel-24khz"
 
-vocos = load_vocoder(is_local=args.load_vocoder_from_local, local_path=vocos_local_path)
+vocoder = load_vocoder(is_local=args.load_vocoder_from_local, local_path=vocos_local_path)
 
 
 # load models
@@ -175,7 +175,9 @@ def main_process(ref_audio, ref_text, text_gen, model_obj, remove_silence, speed
         ref_audio = voices[voice]["ref_audio"]
         ref_text = voices[voice]["ref_text"]
         print(f"Voice: {voice}")
-        audio, final_sample_rate, spectragram = infer_process(ref_audio, ref_text, gen_text, model_obj, speed=speed)
+        audio, final_sample_rate, spectragram = infer_process(
+            ref_audio, ref_text, gen_text, model_obj, vocoder, speed=speed
+        )
         generated_audio_segments.append(audio)
 
     if generated_audio_segments:

src/f5_tts/infer/infer_gradio.py

@@ -37,7 +37,7 @@ from f5_tts.infer.utils_infer import (
     save_spectrogram,
 )
 
-vocos = load_vocoder()
+vocoder = load_vocoder()
 
 
 # load models
@@ -94,6 +94,7 @@ def infer(
         ref_text,
         gen_text,
         ema_model,
+        vocoder,
         cross_fade_duration=cross_fade_duration,
         speed=speed,
         show_info=show_info,

src/f5_tts/infer/utils_infer.py

@@ -29,9 +29,6 @@ _ref_audio_cache = {}
 
 device = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
 
-vocos = Vocos.from_pretrained("charactr/vocos-mel-24khz")
-
-
 # -----------------------------------------
 
 target_sample_rate = 24000
@@ -263,6 +260,7 @@ def infer_process(
     ref_text,
     gen_text,
     model_obj,
+    vocoder,
     show_info=print,
     progress=tqdm,
     target_rms=target_rms,
@@ -287,6 +285,7 @@ def infer_process(
         ref_text,
         gen_text_batches,
         model_obj,
+        vocoder,
         progress=progress,
         target_rms=target_rms,
         cross_fade_duration=cross_fade_duration,
@@ -307,6 +306,7 @@ def infer_batch_process(
     ref_text,
     gen_text_batches,
     model_obj,
+    vocoder,
     progress=tqdm,
     target_rms=0.1,
     cross_fade_duration=0.15,
@@ -362,7 +362,7 @@ def infer_batch_process(
         generated = generated.to(torch.float32)
         generated = generated[:, ref_audio_len:, :]
         generated_mel_spec = generated.permute(0, 2, 1)
-        generated_wave = vocos.decode(generated_mel_spec.cpu())
+        generated_wave = vocoder.decode(generated_mel_spec.cpu())
         if rms < target_rms:
             generated_wave = generated_wave * rms / target_rms