chores (RVC-Boss#1528)

* chores

* ...

* Add files via upload

* ...

* remove gradio warnings

* Update inference_webui.py

Fix inference_cli issue

GPT_SoVITS/TTS_infer_pack/TTS.py

@@ -182,6 +182,11 @@ def __init__(self, configs: Union[dict, str]=None):
 
 
     def _load_configs(self, configs_path: str)->dict:
+        if os.path.exists(configs_path):
+            ...
+        else:
+            print(i18n("路径不存在,使用默认配置"))
+            self.save_configs(configs_path)
         with open(configs_path, 'r') as f:
             configs = yaml.load(f, Loader=yaml.FullLoader)
 
@@ -748,7 +753,8 @@ def run(self, inputs:dict):
                 phones, bert_features, norm_text = \
                     self.text_preprocessor.segment_and_extract_feature_for_text(
                                                                         prompt_text, 
-                                                                        prompt_lang)
+                                                                        prompt_lang,
+                                                                        self.configs.version)
                 self.prompt_cache["phones"] = phones
                 self.prompt_cache["bert_features"] = bert_features
                 self.prompt_cache["norm_text"] = norm_text
@@ -760,7 +766,7 @@ def run(self, inputs:dict):
         t1 = ttime()
         data:list = None
         if not return_fragment:
-            data = self.text_preprocessor.preprocess(text, text_lang, text_split_method)
+            data = self.text_preprocessor.preprocess(text, text_lang, text_split_method, self.configs.version)
             if len(data) == 0:
                 yield self.configs.sampling_rate, np.zeros(int(self.configs.sampling_rate),
                                                             dtype=np.int16)

GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py

@@ -55,9 +55,9 @@ def __init__(self, bert_model:AutoModelForMaskedLM,
         self.tokenizer = tokenizer
         self.device = device
 
-    def preprocess(self, text:str, lang:str, text_split_method:str, version:str="v1")->List[Dict]:
+    def preprocess(self, text:str, lang:str, text_split_method:str, version:str="v2")->List[Dict]:
         print(i18n("############ 切分文本 ############"))
-        text = self.replace_consecutive_punctuation(text) # 变量命名应该是写错了
+        text = self.replace_consecutive_punctuation(text)
         texts = self.pre_seg_text(text, lang, text_split_method)
         result = []
         print(i18n("############ 提取文本Bert特征 ############"))
@@ -204,7 +204,7 @@ def get_bert_feature(self, text:str, word2ph:list)->torch.Tensor:
         phone_level_feature = torch.cat(phone_level_feature, dim=0)
         return phone_level_feature.T
 
-    def clean_text_inf(self, text:str, language:str, version:str="v1"):
+    def clean_text_inf(self, text:str, language:str, version:str="v2"):
         phones, word2ph, norm_text = clean_text(text, language, version)
         phones = cleaned_text_to_sequence(phones, version)
         return phones, word2ph, norm_text

GPT_SoVITS/configs/.gitignore

@@ -0,0 +1 @@
+*.yaml

GPT_SoVITS/inference_webui.py

@@ -21,6 +21,11 @@
 import pdb
 import torch
 
+try:
+    import gradio.analytics as analytics
+    analytics.version_check = lambda:None
+except:...
+
 version=os.environ.get("version","v2")
 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"]
@@ -392,7 +397,8 @@ def merge_short_text_in_array(texts, threshold):
 ##ref_wav_path+prompt_text+prompt_language+text(单个)+text_language+top_k+top_p+temperature
 # cache_tokens={}#暂未实现清理机制
 cache= {}
-def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切"), top_k=20, top_p=0.6, temperature=0.6, ref_free = False,speed=1,if_freeze=False,inp_refs=123):
+def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切"), top_k=20, top_p=0.6, temperature=0.6, ref_free 
+    =False,speed=1,if_freeze=False,inp_refs=None):
     global cache
     if ref_wav_path:pass
     else:gr.Warning(i18n('请上传参考音频'))

GPT_SoVITS/inference_webui_fast.py

@@ -23,6 +23,11 @@
 import pdb
 import torch
 
+try:
+    import gradio.analytics as analytics
+    analytics.version_check = lambda:None
+except:...
+
 
 infer_ttswebui = os.environ.get("infer_ttswebui", 9872)
 infer_ttswebui = int(infer_ttswebui)

tools/subfix_webui.py

@@ -4,6 +4,11 @@
 import os
 import uuid
 
+try:
+    import gradio.analytics as analytics
+    analytics.version_check = lambda:None
+except:...
+
 import librosa
 import gradio as gr
 import numpy as np

tools/uvr5/webui.py

@@ -14,6 +14,11 @@
 from vr import AudioPre, AudioPreDeEcho
 from bsroformer import BsRoformer_Loader
 
+try:
+    import gradio.analytics as analytics
+    analytics.version_check = lambda:None
+except:...
+
 weight_uvr5_root = "tools/uvr5/uvr5_weights"
 uvr5_names = []
 for name in os.listdir(weight_uvr5_root):