添加了自定义修改随机数种子，方便复现结果。

GPT_SoVITS/TTS_infer_pack/TTS.py

@@ -51,17 +51,23 @@ custom:
 
 """
 
-# def set_seed(seed):
-#     random.seed(seed)
-#     os.environ['PYTHONHASHSEED'] = str(seed)
-#     np.random.seed(seed)
-#     torch.manual_seed(seed)
-#     torch.cuda.manual_seed(seed)
-#     torch.cuda.manual_seed_all(seed)
-#     torch.backends.cudnn.deterministic = True
-#     torch.backends.cudnn.benchmark = False
-#     torch.backends.cudnn.enabled = True
-# set_seed(1234) 
+def set_seed(seed:int):
+    seed = int(seed)
+    seed = seed if seed != -1 else random.randrange(1 << 32)
+    print(f"Set seed to {seed}")
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    try:
+        if torch.cuda.is_available():
+            torch.cuda.manual_seed(seed)
+            torch.cuda.manual_seed_all(seed)
+            # torch.backends.cudnn.deterministic = True
+            # torch.backends.cudnn.benchmark = False
+            # torch.backends.cudnn.enabled = True
+    except:
+        pass
+    return seed
     
 class TTS_Config:
     default_configs={
@@ -563,6 +569,7 @@ class TTS:
                     "return_fragment": False, # bool. step by step return the audio fragment.
                     "speed_factor":1.0,       # float. control the speed of the synthesized audio.
                     "fragment_interval":0.3,  # float. to control the interval of the audio fragment.
+                    "seed": -1,               # int. random seed for reproducibility.
                 }
         returns:
             tulpe[int, np.ndarray]: sampling rate and audio data.
@@ -584,6 +591,9 @@ class TTS:
         split_bucket = inputs.get("split_bucket", True)
         return_fragment = inputs.get("return_fragment", False)
         fragment_interval = inputs.get("fragment_interval", 0.3)
+        seed = inputs.get("seed", -1)
+        
+        set_seed(seed)
         
         if return_fragment:
             # split_bucket = False

GPT_SoVITS/inference_webui.py

@@ -92,6 +92,7 @@ def inference(text, text_lang,
               text_split_method, batch_size, 
               speed_factor, ref_text_free,
               split_bucket,fragment_interval,
+              seed,
               ):
     inputs={
         "text": text,
@@ -108,6 +109,7 @@ def inference(text, text_lang,
         "split_bucket":split_bucket,
         "return_fragment":False,
         "fragment_interval":fragment_interval,
+        "seed":seed,
     }
     
     for item in tts_pipline.run(inputs):
@@ -203,6 +205,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                 )
                 with gr.Row():
                     split_bucket = gr.Checkbox(label=i18n("数据分桶(可能会降低一点计算量，选就对了)"), value=True, interactive=True, show_label=True)
+                    seed = gr.Number(label=i18n("随机种子"),value=-1)
             # with gr.Column():
                 output = gr.Audio(label=i18n("输出的语音"))
                 with gr.Row():
@@ -219,6 +222,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                 how_to_cut, batch_size, 
                 speed_factor, ref_text_free,
                 split_bucket,fragment_interval,
+                seed
              ],
             [output],
         )