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GPT_SoVITS/inference_webui.py

@@ -331,6 +331,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
         int(hps.data.sampling_rate * 0.3),
         dtype=np.float16 if is_half == True else np.float32,
     )
+    if not ref_free:
         with torch.no_grad():
             wav16k, sr = librosa.load(ref_wav_path, sr=16000)
             if (wav16k.shape[0] > 160000 or wav16k.shape[0] < 48000):
@@ -350,8 +351,9 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
                 1, 2
             )  # .float()
             codes = vq_model.extract_latent(ssl_content)
-   
             prompt_semantic = codes[0, 0]
+            prompt = prompt_semantic.unsqueeze(0).to(device)
+
     t1 = ttime()
 
     if (how_to_cut == i18n("凑四句一切")):
@@ -391,7 +393,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
 
         bert = bert.to(device).unsqueeze(0)
         all_phoneme_len = torch.tensor([all_phoneme_ids.shape[-1]]).to(device)
-        prompt = prompt_semantic.unsqueeze(0).to(device)
+
         t2 = ttime()
         with torch.no_grad():
             # pred_semantic = t2s_model.model.infer(