Chores (#1422)

Make Gradio Great Again
附带vs2017下载链接
增加了各种数据集检查,若缺失会弹出warning
修复了warning乱弹的bug
修复了参考音频混合只能上传一条的bug
修复了下载G2PW Model出现import错误的bug
修复了Windows训练无N卡在预处理阶段的报错

tools/my_utils.py

@@ -1,7 +1,10 @@
 import platform,os,traceback
 import ffmpeg
 import numpy as np
-
+import gradio as gr
+from tools.i18n.i18n import I18nAuto
+import pandas as pd
+i18n = I18nAuto(language=os.environ.get('language','Auto'))
 
 def load_audio(file, sr):
     try:
@@ -20,7 +23,7 @@ def load_audio(file, sr):
         )
     except Exception as e:
         traceback.print_exc()
-        raise RuntimeError(f"Failed to load audio: {e}")
+        raise RuntimeError(i18n("音频加载失败"))
 
     return np.frombuffer(out, np.float32).flatten()
 
@@ -30,3 +33,83 @@ def clean_path(path_str:str):
         return clean_path(path_str[0:-1])
     path_str = path_str.replace('/', os.sep).replace('\\', os.sep)
     return path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a")
+
+
+def check_for_existance(file_list:list=None,is_train=False,is_dataset_processing=False):
+    files_status=[]
+    if is_train == True and file_list:
+        file_list.append(os.path.join(file_list[0],'2-name2text.txt'))
+        file_list.append(os.path.join(file_list[0],'3-bert'))
+        file_list.append(os.path.join(file_list[0],'4-cnhubert'))
+        file_list.append(os.path.join(file_list[0],'5-wav32k'))
+        file_list.append(os.path.join(file_list[0],'6-name2semantic.tsv'))
+    for file in file_list:
+        if os.path.exists(file):files_status.append(True)
+        else:files_status.append(False)
+    if sum(files_status)!=len(files_status):
+        if is_train:
+            for file,status in zip(file_list,files_status):
+                if status:pass
+                else:gr.Warning(file)
+            gr.Warning(i18n('以下文件或文件夹不存在'))
+            return False
+        elif is_dataset_processing:
+            if files_status[0]:
+                return True
+            elif not files_status[0]:
+                gr.Warning(file_list[0])
+            elif not files_status[1] and file_list[1]:
+                gr.Warning(file_list[1])
+            gr.Warning(i18n('以下文件或文件夹不存在'))
+            return False
+        else:
+            if file_list[0]:
+                gr.Warning(file_list[0])
+                gr.Warning(i18n('以下文件或文件夹不存在'))
+            else:
+                gr.Warning(i18n('路径不能为空'))
+            return False
+    return True
+
+def check_details(path_list=None,is_train=False,is_dataset_processing=False):
+    if is_dataset_processing:
+        list_path, audio_path = path_list
+        if (not list_path.endswith('.list')):
+            gr.Warning(i18n('请填入正确的List路径'))
+            return
+        if audio_path:
+            if not os.path.isdir(audio_path):
+                gr.Warning(i18n('请填入正确的音频文件夹路径'))
+                return
+        with open(list_path,"r",encoding="utf8")as f:
+            line=f.readline().strip("\n").split("\n")
+        wav_name, _, __, ___ = line[0].split("|")
+        wav_name=clean_path(wav_name)
+        if (audio_path != "" and audio_path != None):
+            wav_name = os.path.basename(wav_name)
+            wav_path = "%s/%s"%(audio_path, wav_name)
+        else:
+            wav_path=wav_name
+        if os.path.exists(wav_path):
+            ...
+        else:
+            gr.Warning(i18n('路径错误'))
+        return
+    if is_train:
+        path_list.append(os.path.join(path_list[0],'2-name2text.txt'))
+        path_list.append(os.path.join(path_list[0],'4-cnhubert'))
+        path_list.append(os.path.join(path_list[0],'5-wav32k'))
+        path_list.append(os.path.join(path_list[0],'6-name2semantic.tsv'))
+        phone_path, hubert_path, wav_path, semantic_path = path_list[1:]
+        with open(phone_path,'r',encoding='utf-8') as f:
+            if f.read(1):...
+            else:gr.Warning(i18n('缺少音素数据集'))
+        if os.listdir(hubert_path):...
+        else:gr.Warning(i18n('缺少Hubert数据集'))
+        if os.listdir(wav_path):...
+        else:gr.Warning(i18n('缺少音频数据集'))
+        df = pd.read_csv(
+            semantic_path, delimiter="\t", encoding="utf-8"
+        )
+        if len(df) >= 1:...
+        else:gr.Warning(i18n('缺少语义数据集'))