From dbb6b42fdb06467c31258189daac64a04e29bb0d Mon Sep 17 00:00:00 2001
From: KamioRinn <snowsdream@live.com>
Date: Mon, 19 Aug 2024 21:26:20 +0800
Subject: [PATCH] Optimize detail

---
 api.py | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/api.py b/api.py
index 3eb0ee8..92924dc 100644
--- a/api.py
+++ b/api.py
@@ -221,7 +221,7 @@ def get_sovits_weights(sovits_path):
         hps.model.version = "v1"
     else:
         hps.model.version = "v2"
-    print("sovits版本:",hps.model.version)
+    logger.info(f"模型版本: {hps.model.version}")
     model_params_dict = vars(hps.model)
     vq_model = SynthesizerTrn(
         hps.data.filter_length // 2 + 1,
@@ -489,8 +489,7 @@ def pack_raw(audio_bytes, data, rate):
 def pack_wav(audio_bytes, rate):
     data = np.frombuffer(audio_bytes.getvalue(),dtype=np.int16)
     wav_bytes = BytesIO()
-    sf.write(wav_bytes, data, rate, format='wav')
-
+    sf.write(wav_bytes, data, rate, format='WAV')
     return wav_bytes
 
 
@@ -543,6 +542,7 @@ def only_punc(text):
     return not any(t.isalnum() or t.isalpha() for t in text)
 
 
+splits = {"，", "。", "？", "！", ",", ".", "?", "!", "~", ":", "：", "—", "…", }
 def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, top_k= 15, top_p = 0.6, temperature = 0.6, speed = 1, inp_refs = None, spk = "default"):
     infer_sovits = speaker_list[spk].sovits
     vq_model = infer_sovits.vq_model
@@ -554,6 +554,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
 
     t0 = ttime()
     prompt_text = prompt_text.strip("\n")
+    if (prompt_text[-1] not in splits): prompt_text += "。" if prompt_language != "en" else "."
     prompt_language, text = prompt_language, text.strip("\n")
     dtype = torch.float16 if is_half == True else torch.float32
     zero_wav = np.zeros(int(hps.data.sampling_rate * 0.3), dtype=np.float16 if is_half == True else np.float32)
@@ -599,6 +600,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
             continue
 
         audio_opt = []
+        if (text[-1] not in splits): text += "。" if text_language != "en" else "."
         phones2, bert2, norm_text2 = get_phones_and_bert(text, text_language, version)
         bert = torch.cat([bert1, bert2], 1)
 
@@ -607,7 +609,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
         all_phoneme_len = torch.tensor([all_phoneme_ids.shape[-1]]).to(device)
         t2 = ttime()
         with torch.no_grad():
-            # pred_semantic = t2s_model.model.infer(
             pred_semantic, idx = t2s_model.model.infer_panel(
                 all_phoneme_ids,
                 all_phoneme_len,
@@ -618,20 +619,20 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
                 top_p = top_p,
                 temperature = temperature,
                 early_stop_num=hz * max_sec)
+            pred_semantic = pred_semantic[:, -idx:].unsqueeze(0)
         t3 = ttime()
-        # print(pred_semantic.shape,idx)
-        pred_semantic = pred_semantic[:, -idx:].unsqueeze(0)  # .unsqueeze(0)#mq要多unsqueeze一次
-        # audio = vq_model.decode(pred_semantic, all_phoneme_ids, refer).detach().cpu().numpy()[0, 0]
         audio = \
             vq_model.decode(pred_semantic, torch.LongTensor(phones2).to(device).unsqueeze(0),
                             refers,speed=speed).detach().cpu().numpy()[
                 0, 0]  ###试试重建不带上prompt部分
-        max_audio=np.abs(audio).max()#简单防止16bit爆音
-        if max_audio>1:audio/=max_audio
+        max_audio=np.abs(audio).max()
+        if max_audio>1:
+            audio/=max_audio
         audio_opt.append(audio)
         audio_opt.append(zero_wav)
         t4 = ttime()
         audio_bytes = pack_audio(audio_bytes,(np.concatenate(audio_opt, 0) * 32768).astype(np.int16),hps.data.sampling_rate)
+        # audio_bytes = pack_audio(audio_bytes,(np.concatenate(audio_opt, 0) * 2147483647).astype(np.int32),hps.data.sampling_rate)
     # logger.info("%.3f\t%.3f\t%.3f\t%.3f" % (t1 - t0, t2 - t1, t3 - t2, t4 - t3))
         if stream_mode == "normal":
             audio_bytes, audio_chunk = read_clean_buffer(audio_bytes)