chores (#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 @@ class TTS_Config:
 
             
     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 @@ class TTS:
                 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 @@ class TTS:
         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 @@ class TextPreprocessor:
         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 @@ class TextPreprocessor:
         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