From 1c54a945cbc5e5541e9e249675ec3425cffda37a Mon Sep 17 00:00:00 2001
From: __kaning123__ <131787647+kaning123@users.noreply.github.com>
Date: Wed, 25 Feb 2026 07:53:03 +0800
Subject: [PATCH] feat: Added entrys to save sv_emb and refers

---
 GPT_SoVITS/VoiceSave/__init__.py | 12 +++----
 GPT_SoVITS/inference_webui.py    | 60 ++++++++++++++++++++++++++++++++
 2 files changed, 66 insertions(+), 6 deletions(-)

diff --git a/GPT_SoVITS/VoiceSave/__init__.py b/GPT_SoVITS/VoiceSave/__init__.py
index 703cce51..b64bae9b 100644
--- a/GPT_SoVITS/VoiceSave/__init__.py
+++ b/GPT_SoVITS/VoiceSave/__init__.py
@@ -1,11 +1,11 @@
-import numpy as np
-import torch
 import zipfile
 from . import file_lib as fl
 from . import time_lib as tl
 from . import info_lib as il
 import os
 from typing import Union
+import numpy as np
+import torch
 
 POOL:set = set() 
 def get_unique_name(name,MySet:set=set()):
@@ -59,9 +59,9 @@ class ZIP_File:
             file_path = fl.merge_dir_txt2(self.temp_write,file_name)
         else:
             file_path = fl.merge_dir_txt2(self.temp_write, location, file_name)
-        if not os.path.exists(location):
-            os.makedirs(location,exist_ok=True)
-        with open(file_path, 'x') as f:
+        if not os.path.exists(file_path):
+            os.makedirs(os.path.dirname(file_path),exist_ok=True)
+        with open(file_path, 'w') as f:
             pass
 
     def get_file_path(self, file_name:str,location:str=''):
@@ -116,7 +116,7 @@ def save_tensor(path: str, tensors: Union[torch.Tensor, list],name:str,MySet:set
     zf.create_file("voice.json")
     info = {'name': name}
     info.update(info_save)
-    il.save_info(str(zf.get_file_path("voice.json")), info)
+    il.save_info(info, str(zf.get_file_path("voice.json")))
     for i in range(len(files)):
         file_name = files[i]
         np_array = np_arrays[i]
diff --git a/GPT_SoVITS/inference_webui.py b/GPT_SoVITS/inference_webui.py
index a361ed58..25f424bb 100644
--- a/GPT_SoVITS/inference_webui.py
+++ b/GPT_SoVITS/inference_webui.py
@@ -8,6 +8,36 @@
 """
 import psutil
 import os
+import sys
+from pathlib import Path
+
+def get_my_dir():
+    return os.path.dirname(os.path.abspath(__file__))
+
+def get_parent_dir(dir_path,depth=1):
+    parent_path = Path(dir_path)
+    for _ in range(depth):
+        parent_path = parent_path.parent
+    return parent_path
+
+def merge_dir_txt2(*TXT):
+    return Path(os.path.join(*TXT))
+
+ROOT_DIR = str(get_parent_dir(get_my_dir()))
+sys.path.append(get_my_dir())
+import VoiceSave
+
+POOL:set = set() 
+def _get_unique_name(name,MySet:set=set()):
+    _id = 1
+    if name not in POOL and name not in MySet:
+        POOL.add(name)
+        return name
+    while name in POOL or name in MySet:
+        _id += 1
+        name = f'{name}_{_id}'
+    POOL.add(name)
+    return name
 
 def set_high_priority():
     """把当前 Python 进程设为 HIGH_PRIORITY_CLASS"""
@@ -765,6 +795,11 @@ def get_tts_wav(
     sample_steps=8,
     if_sr=False,
     pause_second=0.3,
+
+    SaveSvEmb=False,
+    SaveRefers=False,
+    SaveSvEmbName=None,
+    SaveRefersName=None
 ):
     global cache
     if ref_wav_path:
@@ -912,6 +947,31 @@ def get_tts_wav(
                 refers = [refers]
                 if is_v2pro:
                     sv_emb = [sv_cn_model.compute_embedding3(audio_tensor)]
+
+            try:
+                if SaveSvEmb and is_v2pro:
+                    names = []
+                    for i in sv_emb:
+                        names.append(_get_unique_name(str(i.shape)))
+                    sv_path = merge_dir_txt2(ROOT_DIR,"output","sv_emb_opt")
+                    if not os.path.exists(sv_path):
+                        os.makedirs(sv_path,exist_ok=True)
+                    VoiceSave.save_tensor(str(merge_dir_txt2(ROOT_DIR,"output","sv_emb_opt",SaveSvEmbName)),sv_emb,SaveSvEmbName,file_names=names,access_list=names)
+            except:
+                traceback.print_exc()
+
+            try:                
+                if SaveRefers:
+                    names = []
+                    for i in refers:
+                        names.append(_get_unique_name(str(i.shape)))
+                    refers_path = merge_dir_txt2(ROOT_DIR,"output","refers_opt")
+                    if not os.path.exists(refers_path):
+                        os.makedirs(refers_path,exist_ok=True)
+                    VoiceSave.save_tensor(str(merge_dir_txt2(ROOT_DIR,"output","refers_opt",SaveRefersName)),refers,SaveRefersName,file_names=names,access_list=names)
+            except:
+                traceback.print_exc()
+
             if is_v2pro:
                 audio = vq_model.decode(
                     pred_semantic, torch.LongTensor(phones2).to(device).unsqueeze(0), refers, speed=speed, sv_emb=sv_emb