为api_v2和inference_webui_fast适配V3版本 (#2188)

* modified:   GPT_SoVITS/TTS_infer_pack/TTS.py
	modified:   GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py
	modified:   GPT_SoVITS/inference_webui_fast.py

* 适配V3版本

* api_v2.py和inference_webui_fast.py的v3适配

* 修改了个远古bug,增加了更友好的提示信息

* 优化webui

* 修改为正确的path

* 修复v3 lora模型的载入问题

* 修复读取tts_infer.yaml文件时遇到的编码不匹配的问题

GPT_SoVITS/inference_webui_fast.py

@@ -7,7 +7,7 @@
 全部按日文识别
 '''
 import random
-import os, re, logging
+import os, re, logging, json
 import sys
 now_dir = os.getcwd()
 sys.path.append(now_dir)
@@ -44,7 +44,7 @@ bert_path = os.environ.get("bert_path", None)
 version=os.environ.get("version","v2")
 
 import gradio as gr
-from TTS_infer_pack.TTS import TTS, TTS_Config
+from TTS_infer_pack.TTS import TTS, TTS_Config, NO_PROMPT_ERROR
 from TTS_infer_pack.text_segmentation_method import get_method
 from tools.i18n.i18n import I18nAuto, scan_language_list
 
@@ -62,6 +62,9 @@ if torch.cuda.is_available():
 else:
     device = "cpu"
 
+# is_half = False
+# device = "cpu"
+
 dict_language_v1 = {
     i18n("中文"): "all_zh",#全部按中文识别
     i18n("英文"): "en",#全部按英文识别#######不变
@@ -123,11 +126,11 @@ def inference(text, text_lang,
               speed_factor, ref_text_free,
               split_bucket,fragment_interval,
               seed, keep_random, parallel_infer,
-              repetition_penalty
+              repetition_penalty, sample_steps, super_sampling,
               ):
 
     seed = -1 if keep_random else seed
-    actual_seed = seed if seed not in [-1, "", None] else random.randrange(1 << 32)
+    actual_seed = seed if seed not in [-1, "", None] else random.randint(0, 2**32 - 1)
     inputs={
         "text": text,
         "text_lang": dict_language[text_lang],
@@ -147,9 +150,14 @@ def inference(text, text_lang,
         "seed":actual_seed,
         "parallel_infer": parallel_infer,
         "repetition_penalty": repetition_penalty,
+        "sample_steps": int(sample_steps),
+        "super_sampling": super_sampling,
     }
-    for item in tts_pipeline.run(inputs):
-        yield item, actual_seed
+    try:
+        for item in tts_pipeline.run(inputs):
+            yield item, actual_seed
+    except NO_PROMPT_ERROR:
+        gr.Warning(i18n('V3不支持无参考文本模式，请填写参考文本！'))
 
 def custom_sort_key(s):
     # 使用正则表达式提取字符串中的数字部分和非数字部分
@@ -163,19 +171,38 @@ def change_choices():
     SoVITS_names, GPT_names = get_weights_names(GPT_weight_root, SoVITS_weight_root)
     return {"choices": sorted(SoVITS_names, key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}
 
+path_sovits_v3="GPT_SoVITS/pretrained_models/s2Gv3.pth"
+pretrained_sovits_name=["GPT_SoVITS/pretrained_models/s2G488k.pth", "GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth",path_sovits_v3]
+pretrained_gpt_name=["GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt","GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1v3.ckpt"]
 
-pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"]
-pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"]
 _ =[[],[]]
-for i in range(2):
-    if os.path.exists(pretrained_gpt_name[i]):
-        _[0].append(pretrained_gpt_name[i])
-    if os.path.exists(pretrained_sovits_name[i]):
-        _[-1].append(pretrained_sovits_name[i])
+for i in range(3):
+    if os.path.exists(pretrained_gpt_name[i]):_[0].append(pretrained_gpt_name[i])
+    if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i])
 pretrained_gpt_name,pretrained_sovits_name = _
 
-SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"]
-GPT_weight_root=["GPT_weights_v2","GPT_weights"]
+
+if os.path.exists(f"./weight.json"):
+    pass
+else:
+    with open(f"./weight.json", 'w', encoding="utf-8") as file:json.dump({'GPT':{},'SoVITS':{}},file)
+
+with open(f"./weight.json", 'r', encoding="utf-8") as file:
+    weight_data = file.read()
+    weight_data=json.loads(weight_data)
+    gpt_path = os.environ.get(
+        "gpt_path", weight_data.get('GPT',{}).get(version,pretrained_gpt_name))
+    sovits_path = os.environ.get(
+        "sovits_path", weight_data.get('SoVITS',{}).get(version,pretrained_sovits_name))
+    if isinstance(gpt_path,list):
+        gpt_path = gpt_path[0]
+    if isinstance(sovits_path,list):
+        sovits_path = sovits_path[0]
+
+
+
+SoVITS_weight_root=["SoVITS_weights","SoVITS_weights_v2","SoVITS_weights_v3"]
+GPT_weight_root=["GPT_weights","GPT_weights_v2","GPT_weights_v3"]
 for path in SoVITS_weight_root+GPT_weight_root:
     os.makedirs(path,exist_ok=True)
 
@@ -194,10 +221,18 @@ def get_weights_names(GPT_weight_root, SoVITS_weight_root):
 SoVITS_names, GPT_names = get_weights_names(GPT_weight_root, SoVITS_weight_root)
 
 
-
+from process_ckpt import get_sovits_version_from_path_fast
 def change_sovits_weights(sovits_path,prompt_language=None,text_language=None):
-    tts_pipeline.init_vits_weights(sovits_path)
     global version, dict_language
+    version, model_version, if_lora_v3=get_sovits_version_from_path_fast(sovits_path)
+
+    if if_lora_v3 and not os.path.exists(path_sovits_v3):
+        info= path_sovits_v3 + i18n("SoVITS V3 底模缺失，无法加载相应 LoRA 权重")
+        gr.Warning(info)
+        raise FileExistsError(info)
+
+    tts_pipeline.init_vits_weights(sovits_path)
+
     dict_language = dict_language_v1 if tts_pipeline.configs.version =='v1' else dict_language_v2
     if prompt_language is not None and text_language is not None:
         if prompt_language in list(dict_language.keys()):
@@ -210,9 +245,19 @@ def change_sovits_weights(sovits_path,prompt_language=None,text_language=None):
         else:
             text_update = {'__type__':'update', 'value':''}
             text_language_update = {'__type__':'update', 'value':i18n("中文")}
-        return  {'__type__':'update', 'choices':list(dict_language.keys())}, {'__type__':'update', 'choices':list(dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update
-
+        if model_version=="v3":
+            visible_sample_steps=True
+            visible_inp_refs=False
+        else:
+            visible_sample_steps=False
+            visible_inp_refs=True
+        yield  {'__type__':'update', 'choices':list(dict_language.keys())}, {'__type__':'update', 'choices':list(dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update,{"__type__": "update", "visible": visible_sample_steps},{"__type__": "update", "visible": visible_inp_refs},{"__type__": "update", "value": False,"interactive":True if model_version!="v3"else False},{"__type__": "update", "visible":True if model_version=="v3"else False}
 
+    with open("./weight.json")as f:
+        data=f.read()
+        data=json.loads(data)
+        data["SoVITS"][version]=sovits_path
+    with open("./weight.json","w")as f:f.write(json.dumps(data))
 
 with gr.Blocks(title="GPT-SoVITS WebUI") as app:
     gr.Markdown(
@@ -257,13 +302,19 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
         with gr.Row():
 
             with gr.Column():
-                batch_size = gr.Slider(minimum=1,maximum=200,step=1,label=i18n("batch_size"),value=20,interactive=True)
-                fragment_interval = gr.Slider(minimum=0.01,maximum=1,step=0.01,label=i18n("分段间隔(秒)"),value=0.3,interactive=True)
-                speed_factor = gr.Slider(minimum=0.6,maximum=1.65,step=0.05,label="speed_factor",value=1.0,interactive=True)
-                top_k = gr.Slider(minimum=1,maximum=100,step=1,label=i18n("top_k"),value=5,interactive=True)
-                top_p = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("top_p"),value=1,interactive=True)
-                temperature = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("temperature"),value=1,interactive=True)
-                repetition_penalty = gr.Slider(minimum=0,maximum=2,step=0.05,label=i18n("重复惩罚"),value=1.35,interactive=True)
+                with gr.Row():
+                    batch_size = gr.Slider(minimum=1,maximum=200,step=1,label=i18n("batch_size"),value=20,interactive=True)
+                    sample_steps = gr.Radio(label=i18n("采样步数(仅对V3生效)"),value=32,choices=[4,8,16,32],visible=True)
+                with gr.Row():
+                    fragment_interval = gr.Slider(minimum=0.01,maximum=1,step=0.01,label=i18n("分段间隔(秒)"),value=0.3,interactive=True)
+                    speed_factor = gr.Slider(minimum=0.6,maximum=1.65,step=0.05,label="语速",value=1.0,interactive=True)
+                with gr.Row():
+                    top_k = gr.Slider(minimum=1,maximum=100,step=1,label=i18n("top_k"),value=5,interactive=True)
+                    top_p = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("top_p"),value=1,interactive=True)
+                with gr.Row():
+                    temperature = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("temperature"),value=1,interactive=True)
+                    repetition_penalty = gr.Slider(minimum=0,maximum=2,step=0.05,label=i18n("重复惩罚"),value=1.35,interactive=True)
+                    
             with gr.Column():
                 with gr.Row():
                     how_to_cut = gr.Dropdown(
@@ -272,10 +323,14 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                             value=i18n("凑四句一切"),
                             interactive=True, scale=1
                         )
+                    super_sampling = gr.Checkbox(label=i18n("音频超采样(仅对V3生效))"), value=False, interactive=True, show_label=True)
+
+                with gr.Row():
                     parallel_infer = gr.Checkbox(label=i18n("并行推理"), value=True, interactive=True, show_label=True)
                     split_bucket = gr.Checkbox(label=i18n("数据分桶(并行推理时会降低一点计算量)"), value=True, interactive=True, show_label=True)
 
                 with gr.Row():
+                    
                     seed = gr.Number(label=i18n("随机种子"),value=-1)
                     keep_random = gr.Checkbox(label=i18n("保持随机"), value=True, interactive=True, show_label=True)
 
@@ -295,7 +350,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
                 speed_factor, ref_text_free,
                 split_bucket,fragment_interval,
                 seed, keep_random, parallel_infer,
-                repetition_penalty
+                repetition_penalty, sample_steps, super_sampling,
              ],
             [output, seed],
         )