diff --git "a/webui.py" "b/webui.py"
--- "a/webui.py"
+++ "b/webui.py"
@@ -1,1013 +1,1010 @@
-import os,sys
-if len(sys.argv)==1:sys.argv.append('v2')
-version="v1"if sys.argv[1]=="v1" else"v2"
-os.environ["version"]=version
-now_dir = os.getcwd()
-sys.path.insert(0, now_dir)
-import warnings
-warnings.filterwarnings("ignore")
-import json,yaml,torch,pdb,re,shutil
-import platform
-import psutil
-import signal
-torch.manual_seed(233333)
-tmp = os.path.join(now_dir, "TEMP")
-os.makedirs(tmp, exist_ok=True)
-os.environ["TEMP"] = tmp
-if(os.path.exists(tmp)):
-    for name in os.listdir(tmp):
-        if(name=="jieba.cache"):continue
-        path="%s/%s"%(tmp,name)
-        delete=os.remove if os.path.isfile(path) else shutil.rmtree
-        try:
-            delete(path)
-        except Exception as e:
-            print(str(e))
-            pass
-import site
-site_packages_roots = []
-for path in site.getsitepackages():
-    if "packages" in path:
-        site_packages_roots.append(path)
-if(site_packages_roots==[]):site_packages_roots=["%s/runtime/Lib/site-packages" % now_dir]
-#os.environ["OPENBLAS_NUM_THREADS"] = "4"
-os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
-os.environ["all_proxy"] = ""
-for site_packages_root in site_packages_roots:
-    if os.path.exists(site_packages_root):
-        try:
-            with open("%s/users.pth" % (site_packages_root), "w") as f:
-                f.write(
-                    "%s\n%s/tools\n%s/tools/damo_asr\n%s/GPT_SoVITS\n%s/tools/uvr5"
-                    % (now_dir, now_dir, now_dir, now_dir, now_dir)
-                )
-            break
-        except PermissionError:
-            pass
-from tools import my_utils
-import traceback
-import shutil
-import pdb
-from subprocess import Popen
-import signal
-from config import python_exec,infer_device,is_half,exp_root,webui_port_main,webui_port_infer_tts,webui_port_uvr5,webui_port_subfix,is_share
-from tools.i18n.i18n import I18nAuto, scan_language_list
-language=sys.argv[-1] if sys.argv[-1] in scan_language_list() else "Auto"
-os.environ["language"]=language
-i18n = I18nAuto(language=language)
-from scipy.io import wavfile
-from tools.my_utils import load_audio
-from multiprocessing import cpu_count
-# os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu
-import gradio.analytics as analytics
-analytics.version_check = lambda:None
-import gradio as gr
-n_cpu=cpu_count()
-           
-ngpu = torch.cuda.device_count()
-gpu_infos = []
-mem = []
-if_gpu_ok = False
-
-# 判断是否有能用来训练和加速推理的N卡
-ok_gpu_keywords={"10","16","20","30","40","A2","A3","A4","P4","A50","500","A60","70","80","90","M4","T4","TITAN","L4","4060","H"}
-set_gpu_numbers=set()
-if torch.cuda.is_available() or ngpu != 0:
-    for i in range(ngpu):
-        gpu_name = torch.cuda.get_device_name(i)
-        if any(value in gpu_name.upper()for value in ok_gpu_keywords):
-            # A10#A100#V100#A40#P40#M40#K80#A4500
-            if_gpu_ok = True  # 至少有一张能用的N卡
-            gpu_infos.append("%s\t%s" % (i, gpu_name))
-            set_gpu_numbers.add(i)
-            mem.append(int(torch.cuda.get_device_properties(i).total_memory/ 1024/ 1024/ 1024+ 0.4))
-# # 判断是否支持mps加速
-# if torch.backends.mps.is_available():
-#     if_gpu_ok = True
-#     gpu_infos.append("%s\t%s" % ("0", "Apple GPU"))
-#     mem.append(psutil.virtual_memory().total/ 1024 / 1024 / 1024) # 实测使用系统内存作为显存不会爆显存
-
-if if_gpu_ok and len(gpu_infos) > 0:
-    gpu_info = "\n".join(gpu_infos)
-    default_batch_size = min(mem) // 2
-else:
-    gpu_info = ("%s\t%s" % ("0", "CPU"))
-    gpu_infos.append("%s\t%s" % ("0", "CPU"))
-    set_gpu_numbers.add(0)
-    default_batch_size = int(psutil.virtual_memory().total/ 1024 / 1024 / 1024 / 2)
-gpus = "-".join([i[0] for i in gpu_infos])
-default_gpu_numbers=str(sorted(list(set_gpu_numbers))[0])
-def fix_gpu_number(input):#将越界的number强制改到界内
-    try:
-        if(int(input)not in set_gpu_numbers):return default_gpu_numbers
-    except:return input
-    return input
-def fix_gpu_numbers(inputs):
-    output=[]
-    try:
-        for input in inputs.split(","):output.append(str(fix_gpu_number(input)))
-        return ",".join(output)
-    except:
-        return inputs
-
-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"]
-
-pretrained_model_list = (pretrained_sovits_name[-int(version[-1])+2],pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"),pretrained_gpt_name[-int(version[-1])+2],"GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large","GPT_SoVITS/pretrained_models/chinese-hubert-base")
-
-_=''
-for i in pretrained_model_list:
-    if os.path.exists(i):...
-    else:_+=f'\n    {i}'
-if _:
-    print("warning:",i18n('以下模型不存在:')+_)
-
-_ =[[],[]]
-for i in range(2):
-    if os.path.exists(pretrained_gpt_name[i]):_[0].append(pretrained_gpt_name[i])
-    else:_[0].append("")##没有下pretrained模型的，说不定他们是想自己从零训底模呢
-    if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i])
-    else:_[-1].append("")
-pretrained_gpt_name,pretrained_sovits_name = _
-
-SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"]
-GPT_weight_root=["GPT_weights_v2","GPT_weights"]
-for root in SoVITS_weight_root+GPT_weight_root:
-    os.makedirs(root,exist_ok=True)
-def get_weights_names():
-    SoVITS_names = [name for name in pretrained_sovits_name if name!=""]
-    for path in SoVITS_weight_root:
-        for name in os.listdir(path):
-            if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (path, name))
-    GPT_names = [name for name in pretrained_gpt_name if name!=""]
-    for path in GPT_weight_root:
-        for name in os.listdir(path):
-            if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (path, name))
-    return SoVITS_names, GPT_names
-
-SoVITS_names,GPT_names = get_weights_names()
-for path in SoVITS_weight_root+GPT_weight_root:
-    os.makedirs(path,exist_ok=True)
-
-
-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
-    parts = re.split('(\d+)', s)
-    # 将数字部分转换为整数，非数字部分保持不变
-    parts = [int(part) if part.isdigit() else part for part in parts]
-    return parts
-
-def change_choices():
-    SoVITS_names, GPT_names = get_weights_names()
-    return {"choices": sorted(SoVITS_names,key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names,key=custom_sort_key), "__type__": "update"}
-
-p_label=None
-p_uvr5=None
-p_asr=None
-p_denoise=None
-p_tts_inference=None
-
-def kill_proc_tree(pid, including_parent=True):  
-    try:
-        parent = psutil.Process(pid)
-    except psutil.NoSuchProcess:
-        # Process already terminated
-        return
-
-    children = parent.children(recursive=True)
-    for child in children:
-        try:
-            os.kill(child.pid, signal.SIGTERM)  # or signal.SIGKILL
-        except OSError:
-            pass
-    if including_parent:
-        try:
-            os.kill(parent.pid, signal.SIGTERM)  # or signal.SIGKILL
-        except OSError:
-            pass
-
-system=platform.system()
-def kill_process(pid):
-    if(system=="Windows"):
-        cmd = "taskkill /t /f /pid %s" % pid
-        os.system(cmd)
-    else:
-        kill_proc_tree(pid)
-    
-
-def change_label(if_label,path_list):
-    global p_label
-    if(if_label==True and p_label==None):
-        path_list=my_utils.clean_path(path_list)
-        cmd = '"%s" tools/subfix_webui.py --load_list "%s" --webui_port %s --is_share %s'%(python_exec,path_list,webui_port_subfix,is_share)
-        yield i18n("打标工具WebUI已开启")
-        print(cmd)
-        p_label = Popen(cmd, shell=True)
-    elif(if_label==False and p_label!=None):
-        kill_process(p_label.pid)
-        p_label=None
-        yield i18n("打标工具WebUI已关闭")
-
-def change_uvr5(if_uvr5):
-    global p_uvr5
-    if(if_uvr5==True and p_uvr5==None):
-        cmd = '"%s" tools/uvr5/webui.py "%s" %s %s %s'%(python_exec,infer_device,is_half,webui_port_uvr5,is_share)
-        yield i18n("UVR5已开启")
-        print(cmd)
-        p_uvr5 = Popen(cmd, shell=True)
-    elif(if_uvr5==False and p_uvr5!=None):
-        kill_process(p_uvr5.pid)
-        p_uvr5=None
-        yield i18n("UVR5已关闭")
-
-def change_tts_inference(if_tts,bert_path,cnhubert_base_path,gpu_number,gpt_path,sovits_path):
-    global p_tts_inference
-    if(if_tts==True and p_tts_inference==None):
-        os.environ["gpt_path"]=gpt_path if "/" in gpt_path else "%s/%s"%(GPT_weight_root,gpt_path)
-        os.environ["sovits_path"]=sovits_path if "/"in sovits_path else "%s/%s"%(SoVITS_weight_root,sovits_path)
-        os.environ["cnhubert_base_path"]=cnhubert_base_path
-        os.environ["bert_path"]=bert_path
-        os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_number(gpu_number)
-        os.environ["is_half"]=str(is_half)
-        os.environ["infer_ttswebui"]=str(webui_port_infer_tts)
-        os.environ["is_share"]=str(is_share)
-        cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"'%(python_exec, language)
-        yield i18n("TTS推理进程已开启")
-        print(cmd)
-        p_tts_inference = Popen(cmd, shell=True)
-    elif(if_tts==False and p_tts_inference!=None):
-        kill_process(p_tts_inference.pid)
-        p_tts_inference=None
-        yield i18n("TTS推理进程已关闭")
-
-from tools.asr.config import asr_dict
-def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, asr_precision):
-    global p_asr
-    if(p_asr==None):
-        asr_inp_dir=my_utils.clean_path(asr_inp_dir)
-        asr_opt_dir=my_utils.clean_path(asr_opt_dir)
-        check_for_exists([asr_inp_dir])
-        cmd = f'"{python_exec}" tools/asr/{asr_dict[asr_model]["path"]}'
-        cmd += f' -i "{asr_inp_dir}"'
-        cmd += f' -o "{asr_opt_dir}"'
-        cmd += f' -s {asr_model_size}'
-        cmd += f' -l {asr_lang}'
-        cmd += f" -p {asr_precision}"
-        output_file_name = os.path.basename(asr_inp_dir)
-        output_folder = asr_opt_dir or "output/asr_opt"
-        output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')
-        yield "ASR任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"}
-        print(cmd)
-        p_asr = Popen(cmd, shell=True)
-        p_asr.wait()
-        p_asr=None
-        yield f"ASR任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":asr_inp_dir}
-    else:
-        yield "已有正在进行的ASR任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"}
-        # return None
-
-def close_asr():
-    global p_asr
-    if(p_asr!=None):
-        kill_process(p_asr.pid)
-        p_asr=None
-    return "已终止ASR进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-def open_denoise(denoise_inp_dir, denoise_opt_dir):
-    global p_denoise
-    if(p_denoise==None):
-        denoise_inp_dir=my_utils.clean_path(denoise_inp_dir)
-        denoise_opt_dir=my_utils.clean_path(denoise_opt_dir)
-        check_for_exists([denoise_inp_dir])
-        cmd = '"%s" tools/cmd-denoise.py -i "%s" -o "%s" -p %s'%(python_exec,denoise_inp_dir,denoise_opt_dir,"float16"if is_half==True else "float32")
-
-        yield "语音降噪任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}
-        print(cmd)
-        p_denoise = Popen(cmd, shell=True)
-        p_denoise.wait()
-        p_denoise=None
-        yield f"语音降噪任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":denoise_opt_dir}, {"__type__":"update","value":denoise_opt_dir}
-    else:
-        yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}
-        # return None
-
-def close_denoise():
-    global p_denoise
-    if(p_denoise!=None):
-        kill_process(p_denoise.pid)
-        p_denoise=None
-    return "已终止语音降噪进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-
-p_train_SoVITS=None
-def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D):
-    global p_train_SoVITS
-    if(p_train_SoVITS==None):
-        with open("GPT_SoVITS/configs/s2.json")as f:
-            data=f.read()
-            data=json.loads(data)
-        s2_dir="%s/%s"%(exp_root,exp_name)
-        os.makedirs("%s/logs_s2"%(s2_dir),exist_ok=True)
-        check_for_exists([s2_dir],is_train=True)
-        if(is_half==False):
-            data["train"]["fp16_run"]=False
-            batch_size=max(1,batch_size//2)
-        data["train"]["batch_size"]=batch_size
-        data["train"]["epochs"]=total_epoch
-        data["train"]["text_low_lr_rate"]=text_low_lr_rate
-        data["train"]["pretrained_s2G"]=pretrained_s2G
-        data["train"]["pretrained_s2D"]=pretrained_s2D
-        data["train"]["if_save_latest"]=if_save_latest
-        data["train"]["if_save_every_weights"]=if_save_every_weights
-        data["train"]["save_every_epoch"]=save_every_epoch
-        data["train"]["gpu_numbers"]=gpu_numbers1Ba
-        data["model"]["version"]=version
-        data["data"]["exp_dir"]=data["s2_ckpt_dir"]=s2_dir
-        data["save_weight_dir"]=SoVITS_weight_root[-int(version[-1])+2]
-        data["name"]=exp_name
-        data["version"]=version
-        tmp_config_path="%s/tmp_s2.json"%tmp
-        with open(tmp_config_path,"w")as f:f.write(json.dumps(data))
-
-        cmd = '"%s" GPT_SoVITS/s2_train.py --config "%s"'%(python_exec,tmp_config_path)
-        yield "SoVITS训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
-        print(cmd)
-        p_train_SoVITS = Popen(cmd, shell=True)
-        p_train_SoVITS.wait()
-        p_train_SoVITS=None
-        yield "SoVITS训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-    else:
-        yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
-
-def close1Ba():
-    global p_train_SoVITS
-    if(p_train_SoVITS!=None):
-        kill_process(p_train_SoVITS.pid)
-        p_train_SoVITS=None
-    return "已终止SoVITS训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-
-p_train_GPT=None
-def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers,pretrained_s1):
-    global p_train_GPT
-    if(p_train_GPT==None):
-        with open("GPT_SoVITS/configs/s1longer.yaml"if version=="v1"else "GPT_SoVITS/configs/s1longer-v2.yaml")as f:
-            data=f.read()
-            data=yaml.load(data, Loader=yaml.FullLoader)
-        s1_dir="%s/%s"%(exp_root,exp_name)
-        os.makedirs("%s/logs_s1"%(s1_dir),exist_ok=True)
-        check_for_exists([s1_dir],is_train=True)
-        if(is_half==False):
-            data["train"]["precision"]="32"
-            batch_size = max(1, batch_size // 2)
-        data["train"]["batch_size"]=batch_size
-        data["train"]["epochs"]=total_epoch
-        data["pretrained_s1"]=pretrained_s1
-        data["train"]["save_every_n_epoch"]=save_every_epoch
-        data["train"]["if_save_every_weights"]=if_save_every_weights
-        data["train"]["if_save_latest"]=if_save_latest
-        data["train"]["if_dpo"]=if_dpo
-        data["train"]["half_weights_save_dir"]=GPT_weight_root[-int(version[-1])+2]
-        data["train"]["exp_name"]=exp_name
-        data["train_semantic_path"]="%s/6-name2semantic.tsv"%s1_dir
-        data["train_phoneme_path"]="%s/2-name2text.txt"%s1_dir
-        data["output_dir"]="%s/logs_s1"%s1_dir
-        # data["version"]=version
-
-        os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_numbers(gpu_numbers.replace("-",","))
-        os.environ["hz"]="25hz"
-        tmp_config_path="%s/tmp_s1.yaml"%tmp
-        with open(tmp_config_path, "w") as f:f.write(yaml.dump(data, default_flow_style=False))
-        # cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" --train_semantic_path "%s/6-name2semantic.tsv" --train_phoneme_path "%s/2-name2text.txt" --output_dir "%s/logs_s1"'%(python_exec,tmp_config_path,s1_dir,s1_dir,s1_dir)
-        cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" '%(python_exec,tmp_config_path)
-        yield "GPT训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
-        print(cmd)
-        p_train_GPT = Popen(cmd, shell=True)
-        p_train_GPT.wait()
-        p_train_GPT=None
-        yield "GPT训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-    else:
-        yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
-
-def close1Bb():
-    global p_train_GPT
-    if(p_train_GPT!=None):
-        kill_process(p_train_GPT.pid)
-        p_train_GPT=None
-    return "已终止GPT训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-
-ps_slice=[]
-def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_parts):
-    global ps_slice
-    inp = my_utils.clean_path(inp)
-    opt_root = my_utils.clean_path(opt_root)
-    check_for_exists([inp])
-    if(os.path.exists(inp)==False):
-        yield "输入路径不存在", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
-        return
-    if os.path.isfile(inp):n_parts=1
-    elif os.path.isdir(inp):pass
-    else:
-        yield "输入路径存在但既不是文件也不是文件夹", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
-        return
-    if (ps_slice == []):
-        for i_part in range(n_parts):
-            cmd = '"%s" tools/slice_audio.py "%s" "%s" %s %s %s %s %s %s %s %s %s''' % (python_exec,inp, opt_root, threshold, min_length, min_interval, hop_size, max_sil_kept, _max, alpha, i_part, n_parts)
-            print(cmd)
-            p = Popen(cmd, shell=True)
-            ps_slice.append(p)
-        yield "切割执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
-        for p in ps_slice:
-            p.wait()
-        ps_slice=[]
-        yield "切割结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}
-    else:
-        yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
-
-def close_slice():
-    global ps_slice
-    if (ps_slice != []):
-        for p_slice in ps_slice:
-            try:
-                kill_process(p_slice.pid)
-            except:
-                traceback.print_exc()
-        ps_slice=[]
-    return "已终止所有切割进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-
-ps1a=[]
-def open1a(inp_text,inp_wav_dir,exp_name,gpu_numbers,bert_pretrained_dir):
-    global ps1a
-    inp_text = my_utils.clean_path(inp_text)
-    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
-    check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True)
-    if (ps1a == []):
-        opt_dir="%s/%s"%(exp_root,exp_name)
-        config={
-            "inp_text":inp_text,
-            "inp_wav_dir":inp_wav_dir,
-            "exp_name":exp_name,
-            "opt_dir":opt_dir,
-            "bert_pretrained_dir":bert_pretrained_dir,
-        }
-        gpu_names=gpu_numbers.split("-")
-        all_parts=len(gpu_names)
-        for i_part in range(all_parts):
-            config.update(
-                {
-                    "i_part": str(i_part),
-                    "all_parts": str(all_parts),
-                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                    "is_half": str(is_half)
-                }
-            )
-            os.environ.update(config)
-            cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
-            print(cmd)
-            p = Popen(cmd, shell=True)
-            ps1a.append(p)
-        yield "文本进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-        for p in ps1a:
-            p.wait()
-        opt = []
-        for i_part in range(all_parts):
-            txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
-            with open(txt_path, "r", encoding="utf8") as f:
-                opt += f.read().strip("\n").split("\n")
-            os.remove(txt_path)
-        path_text = "%s/2-name2text.txt" % opt_dir
-        with open(path_text, "w", encoding="utf8") as f:
-            f.write("\n".join(opt) + "\n")
-        ps1a=[]
-        if len("".join(opt)) > 0:
-            yield "文本进程成功", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-        else:
-            yield "文本进程失败", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-    else:
-        yield "已有正在进行的文本任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-
-def close1a():
-    global ps1a
-    if (ps1a != []):
-        for p1a in ps1a:
-            try:
-                kill_process(p1a.pid)
-            except:
-                traceback.print_exc()
-        ps1a=[]
-    return "已终止所有1a进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-
-ps1b=[]
-def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir):
-    global ps1b
-    inp_text = my_utils.clean_path(inp_text)
-    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
-    check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True)
-    if (ps1b == []):
-        config={
-            "inp_text":inp_text,
-            "inp_wav_dir":inp_wav_dir,
-            "exp_name":exp_name,
-            "opt_dir":"%s/%s"%(exp_root,exp_name),
-            "cnhubert_base_dir":ssl_pretrained_dir,
-            "is_half": str(is_half)
-        }
-        gpu_names=gpu_numbers.split("-")
-        all_parts=len(gpu_names)
-        for i_part in range(all_parts):
-            config.update(
-                {
-                    "i_part": str(i_part),
-                    "all_parts": str(all_parts),
-                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                }
-            )
-            os.environ.update(config)
-            cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
-            print(cmd)
-            p = Popen(cmd, shell=True)
-            ps1b.append(p)
-        yield "SSL提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-        for p in ps1b:
-            p.wait()
-        ps1b=[]
-        yield "SSL提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-    else:
-        yield "已有正在进行的SSL提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-
-def close1b():
-    global ps1b
-    if (ps1b != []):
-        for p1b in ps1b:
-            try:
-                kill_process(p1b.pid)
-            except:
-                traceback.print_exc()
-        ps1b=[]
-    return "已终止所有1b进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-
-ps1c=[]
-def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path):
-    global ps1c
-    inp_text = my_utils.clean_path(inp_text)
-    check_for_exists([inp_text,''], is_dataset_processing=True)
-    if (ps1c == []):
-        opt_dir="%s/%s"%(exp_root,exp_name)
-        config={
-            "inp_text":inp_text,
-            "exp_name":exp_name,
-            "opt_dir":opt_dir,
-            "pretrained_s2G":pretrained_s2G_path,
-            "s2config_path":"GPT_SoVITS/configs/s2.json",
-            "is_half": str(is_half)
-        }
-        gpu_names=gpu_numbers.split("-")
-        all_parts=len(gpu_names)
-        for i_part in range(all_parts):
-            config.update(
-                {
-                    "i_part": str(i_part),
-                    "all_parts": str(all_parts),
-                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                }
-            )
-            os.environ.update(config)
-            cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
-            print(cmd)
-            p = Popen(cmd, shell=True)
-            ps1c.append(p)
-        yield "语义token提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-        for p in ps1c:
-            p.wait()
-        opt = ["item_name\tsemantic_audio"]
-        path_semantic = "%s/6-name2semantic.tsv" % opt_dir
-        for i_part in range(all_parts):
-            semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part)
-            with open(semantic_path, "r", encoding="utf8") as f:
-                opt += f.read().strip("\n").split("\n")
-            os.remove(semantic_path)
-        with open(path_semantic, "w", encoding="utf8") as f:
-            f.write("\n".join(opt) + "\n")
-        ps1c=[]
-        yield "语义token提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
-    else:
-        yield "已有正在进行的语义token提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-
-def close1c():
-    global ps1c
-    if (ps1c != []):
-        for p1c in ps1c:
-            try:
-                kill_process(p1c.pid)
-            except:
-                traceback.print_exc()
-        ps1c=[]
-    return "已终止所有语义token进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-#####inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G
-ps1abc=[]
-def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,ssl_pretrained_dir,pretrained_s2G_path):
-    global ps1abc
-    inp_text = my_utils.clean_path(inp_text)
-    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
-    check_for_exists([inp_text,inp_wav_dir])
-    if (ps1abc == []):
-        opt_dir="%s/%s"%(exp_root,exp_name)
-        try:
-            #############################1a
-            path_text="%s/2-name2text.txt" % opt_dir
-            if(os.path.exists(path_text)==False or (os.path.exists(path_text)==True and len(open(path_text,"r",encoding="utf8").read().strip("\n").split("\n"))<2)):
-                config={
-                    "inp_text":inp_text,
-                    "inp_wav_dir":inp_wav_dir,
-                    "exp_name":exp_name,
-                    "opt_dir":opt_dir,
-                    "bert_pretrained_dir":bert_pretrained_dir,
-                    "is_half": str(is_half)
-                }
-                gpu_names=gpu_numbers1a.split("-")
-                all_parts=len(gpu_names)
-                for i_part in range(all_parts):
-                    config.update(
-                        {
-                            "i_part": str(i_part),
-                            "all_parts": str(all_parts),
-                            "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                        }
-                    )
-                    os.environ.update(config)
-                    cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
-                    print(cmd)
-                    p = Popen(cmd, shell=True)
-                    ps1abc.append(p)
-                yield "进度：1a-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-                for p in ps1abc:p.wait()
-
-                opt = []
-                for i_part in range(all_parts):#txt_path="%s/2-name2text-%s.txt"%(opt_dir,i_part)
-                    txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
-                    with open(txt_path, "r",encoding="utf8") as f:
-                        opt += f.read().strip("\n").split("\n")
-                    os.remove(txt_path)
-                with open(path_text, "w",encoding="utf8") as f:
-                    f.write("\n".join(opt) + "\n")
-                assert len("".join(opt)) > 0, "1Aa-文本获取进程失败"
-            yield "进度：1a-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-            ps1abc=[]
-            #############################1b
-            config={
-                "inp_text":inp_text,
-                "inp_wav_dir":inp_wav_dir,
-                "exp_name":exp_name,
-                "opt_dir":opt_dir,
-                "cnhubert_base_dir":ssl_pretrained_dir,
-            }
-            gpu_names=gpu_numbers1Ba.split("-")
-            all_parts=len(gpu_names)
-            for i_part in range(all_parts):
-                config.update(
-                    {
-                        "i_part": str(i_part),
-                        "all_parts": str(all_parts),
-                        "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                    }
-                )
-                os.environ.update(config)
-                cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
-                print(cmd)
-                p = Popen(cmd, shell=True)
-                ps1abc.append(p)
-            yield "进度：1a-done, 1b-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-            for p in ps1abc:p.wait()
-            yield "进度：1a1b-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-            ps1abc=[]
-            #############################1c
-            path_semantic = "%s/6-name2semantic.tsv" % opt_dir
-            if(os.path.exists(path_semantic)==False or (os.path.exists(path_semantic)==True and os.path.getsize(path_semantic)<31)):
-                config={
-                    "inp_text":inp_text,
-                    "exp_name":exp_name,
-                    "opt_dir":opt_dir,
-                    "pretrained_s2G":pretrained_s2G_path,
-                    "s2config_path":"GPT_SoVITS/configs/s2.json",
-                }
-                gpu_names=gpu_numbers1c.split("-")
-                all_parts=len(gpu_names)
-                for i_part in range(all_parts):
-                    config.update(
-                        {
-                            "i_part": str(i_part),
-                            "all_parts": str(all_parts),
-                            "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
-                        }
-                    )
-                    os.environ.update(config)
-                    cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
-                    print(cmd)
-                    p = Popen(cmd, shell=True)
-                    ps1abc.append(p)
-                yield "进度：1a1b-done, 1cing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-                for p in ps1abc:p.wait()
-
-                opt = ["item_name\tsemantic_audio"]
-                for i_part in range(all_parts):
-                    semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part)
-                    with open(semantic_path, "r",encoding="utf8") as f:
-                        opt += f.read().strip("\n").split("\n")
-                    os.remove(semantic_path)
-                with open(path_semantic, "w",encoding="utf8") as f:
-                    f.write("\n".join(opt) + "\n")
-                yield "进度：all-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-            ps1abc = []
-            yield "一键三连进程结束", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-        except:
-            traceback.print_exc()
-            close1abc()
-            yield "一键三连中途报错", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-    else:
-        yield "已有正在进行的一键三连任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
-
-def close1abc():
-    global ps1abc
-    if (ps1abc != []):
-        for p1abc in ps1abc:
-            try:
-                kill_process(p1abc.pid)
-            except:
-                traceback.print_exc()
-        ps1abc=[]
-    return "已终止所有一键三连进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
-
-def switch_version(version_):
-    os.environ['version']=version_
-    global version
-    version = version_
-    if pretrained_sovits_name[-int(version[-1])+2] !='' and pretrained_gpt_name[-int(version[-1])+2] !='':...
-    else:   
-        gr.Warning(i18n(f'未下载{version.upper()}模型'))
-    return  {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D")}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}
-
-def check_for_exists(file_list=None,is_train=False,is_dataset_processing=False):
-    missing_files=[]
-    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):pass
-        else:missing_files.append(file)
-    if missing_files:
-        if is_train:
-            for missing_file in missing_files:
-                if missing_file != '':
-                    gr.Warning(missing_file)
-            gr.Warning(i18n('以下文件或文件夹不存在:'))
-        else:
-            for missing_file in missing_files:
-                if missing_file != '':
-                    gr.Warning(missing_file)
-            if file_list[-1]==[''] and is_dataset_processing:
-                pass
-            else:
-                gr.Warning(i18n('以下文件或文件夹不存在:'))
-
-if os.path.exists('GPT_SoVITS/text/G2PWModel'):...
-else:
-    cmd = '"%s" GPT_SoVITS/download.py'%python_exec
-    p = Popen(cmd, shell=True)
-    p.wait()
-
-with gr.Blocks(title="GPT-SoVITS WebUI") as app:
-    gr.Markdown(
-        value=
-            i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>.")
-    )
-    gr.Markdown(
-        value=
-            i18n("中文教程文档：https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e")
-    )
-
-    with gr.Tabs():
-        with gr.TabItem(i18n("0-前置数据集获取工具")):#提前随机切片防止uvr5爆内存->uvr5->slicer->asr->打标
-            gr.Markdown(value=i18n("0a-UVR5人声伴奏分离&去混响去延迟工具"))
-            with gr.Row():
-                if_uvr5 = gr.Checkbox(label=i18n("是否开启UVR5-WebUI"),show_label=True)
-                uvr5_info = gr.Textbox(label=i18n("UVR5进程输出信息"))
-            gr.Markdown(value=i18n("0b-语音切分工具"))
-            with gr.Row():
-                with gr.Column(scale=3):
-                    with gr.Row():
-                        slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="")
-                        slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt")
-                    with gr.Row():
-                        threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34")
-                        min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000")
-                        min_interval=gr.Textbox(label=i18n("min_interval:最短切割间隔"),value="300")
-                        hop_size=gr.Textbox(label=i18n("hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）"),value="10")
-                        max_sil_kept=gr.Textbox(label=i18n("max_sil_kept:切完后静音最多留多长"),value="500")
-                    with gr.Row():
-                        _max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("max:归一化后最大值多少"),value=0.9,interactive=True)
-                        alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True)
-                        n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True)
-                    with gr.Row():
-                        slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息"))
-                open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True)
-                close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False)
-            gr.Markdown(value=i18n("0bb-语音降噪工具"))
-            with gr.Row():
-                with gr.Column(scale=3):
-                    with gr.Row():
-                        denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="")
-                        denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt")
-                    with gr.Row():
-                        denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息"))
-                open_denoise_button = gr.Button(i18n("开启语音降噪"), variant="primary",visible=True)
-                close_denoise_button = gr.Button(i18n("终止语音降噪进程"), variant="primary",visible=False)
-            gr.Markdown(value=i18n("0c-中文批量离线ASR工具"))
-            with gr.Row():
-                with gr.Column(scale=3):
-                    with gr.Row():
-                        asr_inp_dir = gr.Textbox(
-                            label=i18n("输入文件夹路径"),
-                            value="D:\\GPT-SoVITS\\raw\\xxx",
-                            interactive=True,
-                        )
-                        asr_opt_dir = gr.Textbox(
-                            label       = i18n("输出文件夹路径"),
-                            value       = "output/asr_opt",
-                            interactive = True,
-                        )
-                    with gr.Row():
-                        asr_model = gr.Dropdown(
-                            label       = i18n("ASR 模型"),
-                            choices     = list(asr_dict.keys()),
-                            interactive = True,
-                            value="达摩 ASR (中文)"
-                        )
-                        asr_size = gr.Dropdown(
-                            label       = i18n("ASR 模型尺寸"),
-                            choices     = ["large"],
-                            interactive = True,
-                            value="large"
-                        )
-                        asr_lang = gr.Dropdown(
-                            label       = i18n("ASR 语言设置"),
-                            choices     = ["zh","yue"],
-                            interactive = True,
-                            value="zh"
-                        )
-                        asr_precision = gr.Dropdown(
-                            label       = i18n("数据类型精度"),
-                            choices     = ["float32"],
-                            interactive = True,
-                            value="float32"
-                        ) 
-                    with gr.Row():
-                        asr_info = gr.Textbox(label=i18n("ASR进程输出信息"))     
-                open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True)
-                close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False)                  
-
-                def change_lang_choices(key): #根据选择的模型修改可选的语言
-                    # return gr.Dropdown(choices=asr_dict[key]['lang'])
-                    return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]}
-                def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸
-                    # return gr.Dropdown(choices=asr_dict[key]['size'])
-                    return {"__type__": "update", "choices": asr_dict[key]['size'],"value":asr_dict[key]['size'][-1]}
-                def change_precision_choices(key): #根据选择的模型修改可选的语言
-                    if key =="Faster Whisper (多语种)":
-                        if default_batch_size <= 4:
-                            precision = 'int8'
-                        elif is_half:
-                            precision = 'float16'
-                        else:
-                            precision = 'float32'
-                    else:
-                        precision = 'float32'
-                    # return gr.Dropdown(choices=asr_dict[key]['precision'])
-                    return {"__type__": "update", "choices": asr_dict[key]['precision'],"value":precision}
-                asr_model.change(change_lang_choices, [asr_model], [asr_lang])
-                asr_model.change(change_size_choices, [asr_model], [asr_size])
-                asr_model.change(change_precision_choices, [asr_model], [asr_precision])
-
-                
-            gr.Markdown(value=i18n("0d-语音文本校对标注工具"))
-            with gr.Row():
-                if_label = gr.Checkbox(label=i18n("是否开启打标WebUI"),show_label=True)
-                path_list = gr.Textbox(
-                    label=i18n(".list标注文件的路径"),
-                    value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx.list",
-                    interactive=True,
-                )
-                label_info = gr.Textbox(label=i18n("打标工具进程输出信息"))
-            if_label.change(change_label, [if_label,path_list], [label_info])
-            if_uvr5.change(change_uvr5, [if_uvr5], [uvr5_info])
-
-        with gr.TabItem(i18n("1-GPT-SoVITS-TTS")):
-            with gr.Row():
-                exp_name = gr.Textbox(label=i18n("*实验/模型名"), value="xxx", interactive=True)
-                gpu_info = gr.Textbox(label=i18n("显卡信息"), value=gpu_info, visible=True, interactive=False)
-                version_checkbox = gr.Radio(label=i18n("版本"),value=version,choices=['v1','v2'])
-                pretrained_s2G = gr.Textbox(label=i18n("预训练的SoVITS-G模型路径"), value=pretrained_sovits_name[-int(version[-1])+2], interactive=True)
-                pretrained_s2D = gr.Textbox(label=i18n("预训练的SoVITS-D模型路径"), value=pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"), interactive=True)
-                pretrained_s1 = gr.Textbox(label=i18n("预训练的GPT模型路径"), value=pretrained_gpt_name[-int(version[-1])+2], interactive=True)
-            with gr.TabItem(i18n("1A-训练集格式化工具")):
-                gr.Markdown(value=i18n("输出logs/实验名目录下应有23456开头的文件和文件夹"))
-                with gr.Row():
-                    inp_text = gr.Textbox(label=i18n("*文本标注文件"),value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",interactive=True)
-                    inp_wav_dir = gr.Textbox(
-                        label=i18n("*训练集音频文件目录"),
-                        # value=r"D:\RVC1006\GPT-SoVITS\raw\xxx",
-                        interactive=True,
-                        placeholder=i18n("填切割后音频所在目录！读取的音频文件完整路径=该目录-拼接-list文件里波形对应的文件名（不是全路径）。如果留空则使用.list文件里的绝对全路径。")
-                    )
-                gr.Markdown(value=i18n("1Aa-文本内容"))
-                with gr.Row():
-                    gpu_numbers1a = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
-                    bert_pretrained_dir = gr.Textbox(label=i18n("预训练的中文BERT模型路径"),value="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",interactive=False)
-                    button1a_open = gr.Button(i18n("开启文本获取"), variant="primary",visible=True)
-                    button1a_close = gr.Button(i18n("终止文本获取进程"), variant="primary",visible=False)
-                    info1a=gr.Textbox(label=i18n("文本进程输出信息"))
-                gr.Markdown(value=i18n("1Ab-SSL自监督特征提取"))
-                with gr.Row():
-                    gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
-                    cnhubert_base_dir = gr.Textbox(label=i18n("预训练的SSL模型路径"),value="GPT_SoVITS/pretrained_models/chinese-hubert-base",interactive=False)
-                    button1b_open = gr.Button(i18n("开启SSL提取"), variant="primary",visible=True)
-                    button1b_close = gr.Button(i18n("终止SSL提取进程"), variant="primary",visible=False)
-                    info1b=gr.Textbox(label=i18n("SSL进程输出信息"))
-                gr.Markdown(value=i18n("1Ac-语义token提取"))
-                with gr.Row():
-                    gpu_numbers1c = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
-                    button1c_open = gr.Button(i18n("开启语义token提取"), variant="primary",visible=True)
-                    button1c_close = gr.Button(i18n("终止语义token提取进程"), variant="primary",visible=False)
-                    info1c=gr.Textbox(label=i18n("语义token提取进程输出信息"))
-                gr.Markdown(value=i18n("1Aabc-训练集格式化一键三连"))
-                with gr.Row():
-                    button1abc_open = gr.Button(i18n("开启一键三连"), variant="primary",visible=True)
-                    button1abc_close = gr.Button(i18n("终止一键三连"), variant="primary",visible=False)
-                    info1abc=gr.Textbox(label=i18n("一键三连进程输出信息"))
-
-            open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang, asr_precision], [asr_info,open_asr_button,close_asr_button,path_list,inp_text,inp_wav_dir])
-            close_asr_button.click(close_asr, [], [asr_info,open_asr_button,close_asr_button])
-            open_slicer_button.click(open_slice, [slice_inp_path,slice_opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_process], [slicer_info,open_slicer_button,close_slicer_button,asr_inp_dir,denoise_input_dir,inp_wav_dir])
-            close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button])
-            open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button,asr_inp_dir,inp_wav_dir])
-            close_denoise_button.click(close_denoise, [], [denoise_info,open_denoise_button,close_denoise_button])
-            
-            button1a_open.click(open1a, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,bert_pretrained_dir], [info1a,button1a_open,button1a_close])
-            button1a_close.click(close1a, [], [info1a,button1a_open,button1a_close])
-            button1b_open.click(open1b, [inp_text,inp_wav_dir,exp_name,gpu_numbers1Ba,cnhubert_base_dir], [info1b,button1b_open,button1b_close])
-            button1b_close.click(close1b, [], [info1b,button1b_open,button1b_close])
-            button1c_open.click(open1c, [inp_text,exp_name,gpu_numbers1c,pretrained_s2G], [info1c,button1c_open,button1c_close])
-            button1c_close.click(close1c, [], [info1c,button1c_open,button1c_close])
-            button1abc_open.click(open1abc, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G], [info1abc,button1abc_open,button1abc_close])
-            button1abc_close.click(close1abc, [], [info1abc,button1abc_open,button1abc_close])
-            with gr.TabItem(i18n("1B-微调训练")):
-                gr.Markdown(value=i18n("1Ba-SoVITS训练。用于分享的模型文件输出在SoVITS_weights下。"))
-                with gr.Row():
-                    batch_size = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
-                    total_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("总训练轮数total_epoch，不建议太高"),value=8,interactive=True)
-                    text_low_lr_rate = gr.Slider(minimum=0.2,maximum=0.6,step=0.05,label=i18n("文本模块学习率权重"),value=0.4,interactive=True)
-                    save_every_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("保存频率save_every_epoch"),value=4,interactive=True)
-                    if_save_latest = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
-                    if_save_every_weights = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
-                    gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True)
-                with gr.Row():
-                    button1Ba_open = gr.Button(i18n("开启SoVITS训练"), variant="primary",visible=True)
-                    button1Ba_close = gr.Button(i18n("终止SoVITS训练"), variant="primary",visible=False)
-                    info1Ba=gr.Textbox(label=i18n("SoVITS训练进程输出信息"))
-                gr.Markdown(value=i18n("1Bb-GPT训练。用于分享的模型文件输出在GPT_weights下。"))
-                with gr.Row():
-                    batch_size1Bb = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
-                    total_epoch1Bb = gr.Slider(minimum=2,maximum=50,step=1,label=i18n("总训练轮数total_epoch"),value=15,interactive=True)
-                    if_dpo = gr.Checkbox(label=i18n("是否开启dpo训练选项(实验性)"), value=False, interactive=True, show_label=True)
-                    if_save_latest1Bb = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
-                    if_save_every_weights1Bb = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
-                    save_every_epoch1Bb = gr.Slider(minimum=1,maximum=50,step=1,label=i18n("保存频率save_every_epoch"),value=5,interactive=True)
-                    gpu_numbers1Bb = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True)
-                with gr.Row():
-                    button1Bb_open = gr.Button(i18n("开启GPT训练"), variant="primary",visible=True)
-                    button1Bb_close = gr.Button(i18n("终止GPT训练"), variant="primary",visible=False)
-                    info1Bb=gr.Textbox(label=i18n("GPT训练进程输出信息"))
-            button1Ba_open.click(open1Ba, [batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D], [info1Ba,button1Ba_open,button1Ba_close])
-            button1Ba_close.click(close1Ba, [], [info1Ba,button1Ba_open,button1Ba_close])
-            button1Bb_open.click(open1Bb, [batch_size1Bb,total_epoch1Bb,exp_name,if_dpo,if_save_latest1Bb,if_save_every_weights1Bb,save_every_epoch1Bb,gpu_numbers1Bb,pretrained_s1],   [info1Bb,button1Bb_open,button1Bb_close])
-            button1Bb_close.click(close1Bb, [], [info1Bb,button1Bb_open,button1Bb_close])
-            with gr.TabItem(i18n("1C-推理")):
-                gr.Markdown(value=i18n("选择训练完存放在SoVITS_weights和GPT_weights下的模型。默认的一个是底模，体验5秒Zero Shot TTS用。"))
-                with gr.Row():
-                    GPT_dropdown = gr.Dropdown(label=i18n("*GPT模型列表"), choices=sorted(GPT_names,key=custom_sort_key),value=pretrained_gpt_name[0],interactive=True)
-                    SoVITS_dropdown = gr.Dropdown(label=i18n("*SoVITS模型列表"), choices=sorted(SoVITS_names,key=custom_sort_key),value=pretrained_sovits_name[0],interactive=True)
-                    gpu_number_1C=gr.Textbox(label=i18n("GPU卡号,只能填1个整数"), value=gpus, interactive=True)
-                    refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary")
-                    refresh_button.click(fn=change_choices,inputs=[],outputs=[SoVITS_dropdown,GPT_dropdown])
-                with gr.Row():
-                    if_tts = gr.Checkbox(label=i18n("是否开启TTS推理WebUI"), show_label=True)
-                    tts_info = gr.Textbox(label=i18n("TTS推理WebUI进程输出信息"))
-                    if_tts.change(change_tts_inference, [if_tts,bert_pretrained_dir,cnhubert_base_dir,gpu_number_1C,GPT_dropdown,SoVITS_dropdown], [tts_info])
-            version_checkbox.change(switch_version,[version_checkbox],[pretrained_s2G,pretrained_s2D,pretrained_s1,GPT_dropdown,SoVITS_dropdown])
-        with gr.TabItem(i18n("2-GPT-SoVITS-变声")):gr.Markdown(value=i18n("施工中，请静候佳音"))
-    app.queue(concurrency_count=511, max_size=1022).launch(
-        server_name="0.0.0.0",
-        inbrowser=True,
-        share=True,
-        server_port=webui_port_main,
-        quiet=True,
+import os,sys
+if len(sys.argv)==1:sys.argv.append('v2')
+version="v1"if sys.argv[1]=="v1" else"v2"
+os.environ["version"]=version
+now_dir = os.getcwd()
+sys.path.insert(0, now_dir)
+import warnings
+warnings.filterwarnings("ignore")
+import json,yaml,torch,pdb,re,shutil
+import platform
+import psutil
+import signal
+torch.manual_seed(233333)
+tmp = os.path.join(now_dir, "TEMP")
+os.makedirs(tmp, exist_ok=True)
+os.environ["TEMP"] = tmp
+if(os.path.exists(tmp)):
+    for name in os.listdir(tmp):
+        if(name=="jieba.cache"):continue
+        path="%s/%s"%(tmp,name)
+        delete=os.remove if os.path.isfile(path) else shutil.rmtree
+        try:
+            delete(path)
+        except Exception as e:
+            print(str(e))
+            pass
+import site
+site_packages_roots = []
+for path in site.getsitepackages():
+    if "packages" in path:
+        site_packages_roots.append(path)
+if(site_packages_roots==[]):site_packages_roots=["%s/runtime/Lib/site-packages" % now_dir]
+#os.environ["OPENBLAS_NUM_THREADS"] = "4"
+os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
+os.environ["all_proxy"] = ""
+for site_packages_root in site_packages_roots:
+    if os.path.exists(site_packages_root):
+        try:
+            with open("%s/users.pth" % (site_packages_root), "w") as f:
+                f.write(
+                    "%s\n%s/tools\n%s/tools/damo_asr\n%s/GPT_SoVITS\n%s/tools/uvr5"
+                    % (now_dir, now_dir, now_dir, now_dir, now_dir)
+                )
+            break
+        except PermissionError:
+            pass
+from tools import my_utils
+import traceback
+import shutil
+import pdb
+from subprocess import Popen
+import signal
+from config import python_exec,infer_device,is_half,exp_root,webui_port_main,webui_port_infer_tts,webui_port_uvr5,webui_port_subfix,is_share
+from tools.i18n.i18n import I18nAuto, scan_language_list
+language=sys.argv[-1] if sys.argv[-1] in scan_language_list() else "Auto"
+os.environ["language"]=language
+i18n = I18nAuto(language=language)
+from scipy.io import wavfile
+from tools.my_utils import load_audio
+from multiprocessing import cpu_count
+# os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu
+import gradio.analytics as analytics
+analytics.version_check = lambda:None
+import gradio as gr
+n_cpu=cpu_count()
+           
+ngpu = torch.cuda.device_count()
+gpu_infos = []
+mem = []
+if_gpu_ok = False
+
+# 判断是否有能用来训练和加速推理的N卡
+ok_gpu_keywords={"10","16","20","30","40","A2","A3","A4","P4","A50","500","A60","70","80","90","M4","T4","TITAN","L4","4060","H"}
+set_gpu_numbers=set()
+if torch.cuda.is_available() or ngpu != 0:
+    for i in range(ngpu):
+        gpu_name = torch.cuda.get_device_name(i)
+        if any(value in gpu_name.upper()for value in ok_gpu_keywords):
+            # A10#A100#V100#A40#P40#M40#K80#A4500
+            if_gpu_ok = True  # 至少有一张能用的N卡
+            gpu_infos.append("%s\t%s" % (i, gpu_name))
+            set_gpu_numbers.add(i)
+            mem.append(int(torch.cuda.get_device_properties(i).total_memory/ 1024/ 1024/ 1024+ 0.4))
+# # 判断是否支持mps加速
+# if torch.backends.mps.is_available():
+#     if_gpu_ok = True
+#     gpu_infos.append("%s\t%s" % ("0", "Apple GPU"))
+#     mem.append(psutil.virtual_memory().total/ 1024 / 1024 / 1024) # 实测使用系统内存作为显存不会爆显存
+
+if if_gpu_ok and len(gpu_infos) > 0:
+    gpu_info = "\n".join(gpu_infos)
+    default_batch_size = min(mem) // 2
+else:
+    gpu_info = ("%s\t%s" % ("0", "CPU"))
+    gpu_infos.append("%s\t%s" % ("0", "CPU"))
+    set_gpu_numbers.add(0)
+    default_batch_size = int(psutil.virtual_memory().total/ 1024 / 1024 / 1024 / 2)
+gpus = "-".join([i[0] for i in gpu_infos])
+default_gpu_numbers=str(sorted(list(set_gpu_numbers))[0])
+def fix_gpu_number(input):#将越界的number强制改到界内
+    try:
+        if(int(input)not in set_gpu_numbers):return default_gpu_numbers
+    except:return input
+    return input
+def fix_gpu_numbers(inputs):
+    output=[]
+    try:
+        for input in inputs.split(","):output.append(str(fix_gpu_number(input)))
+        return ",".join(output)
+    except:
+        return inputs
+
+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"]
+
+pretrained_model_list = (pretrained_sovits_name[-int(version[-1])+2],pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"),pretrained_gpt_name[-int(version[-1])+2],"GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large","GPT_SoVITS/pretrained_models/chinese-hubert-base")
+
+_=''
+for i in pretrained_model_list:
+    if os.path.exists(i):...
+    else:_+=f'\n    {i}'
+if _:
+    print("warning:",i18n('以下模型不存在:')+_)
+
+_ =[[],[]]
+for i in range(2):
+    if os.path.exists(pretrained_gpt_name[i]):_[0].append(pretrained_gpt_name[i])
+    else:_[0].append("")##没有下pretrained模型的，说不定他们是想自己从零训底模呢
+    if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i])
+    else:_[-1].append("")
+pretrained_gpt_name,pretrained_sovits_name = _
+
+SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"]
+GPT_weight_root=["GPT_weights_v2","GPT_weights"]
+for root in SoVITS_weight_root+GPT_weight_root:
+    os.makedirs(root,exist_ok=True)
+def get_weights_names():
+    SoVITS_names = [name for name in pretrained_sovits_name if name!=""]
+    for path in SoVITS_weight_root:
+        for name in os.listdir(path):
+            if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (path, name))
+    GPT_names = [name for name in pretrained_gpt_name if name!=""]
+    for path in GPT_weight_root:
+        for name in os.listdir(path):
+            if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (path, name))
+    return SoVITS_names, GPT_names
+
+SoVITS_names,GPT_names = get_weights_names()
+for path in SoVITS_weight_root+GPT_weight_root:
+    os.makedirs(path,exist_ok=True)
+
+
+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
+    parts = re.split('(\d+)', s)
+    # 将数字部分转换为整数，非数字部分保持不变
+    parts = [int(part) if part.isdigit() else part for part in parts]
+    return parts
+
+def change_choices():
+    SoVITS_names, GPT_names = get_weights_names()
+    return {"choices": sorted(SoVITS_names,key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names,key=custom_sort_key), "__type__": "update"}
+
+p_label=None
+p_uvr5=None
+p_asr=None
+p_denoise=None
+p_tts_inference=None
+
+def kill_proc_tree(pid, including_parent=True):  
+    try:
+        parent = psutil.Process(pid)
+    except psutil.NoSuchProcess:
+        # Process already terminated
+        return
+
+    children = parent.children(recursive=True)
+    for child in children:
+        try:
+            os.kill(child.pid, signal.SIGTERM)  # or signal.SIGKILL
+        except OSError:
+            pass
+    if including_parent:
+        try:
+            os.kill(parent.pid, signal.SIGTERM)  # or signal.SIGKILL
+        except OSError:
+            pass
+
+system=platform.system()
+def kill_process(pid):
+    if(system=="Windows"):
+        cmd = "taskkill /t /f /pid %s" % pid
+        os.system(cmd)
+    else:
+        kill_proc_tree(pid)
+    
+
+def change_label(if_label,path_list):
+    global p_label
+    if(if_label==True and p_label==None):
+        path_list=my_utils.clean_path(path_list)
+        cmd = '"%s" tools/subfix_webui.py --load_list "%s" --webui_port %s --is_share %s'%(python_exec,path_list,webui_port_subfix,is_share)
+        yield i18n("打标工具WebUI已开启")
+        print(cmd)
+        p_label = Popen(cmd, shell=True)
+    elif(if_label==False and p_label!=None):
+        kill_process(p_label.pid)
+        p_label=None
+        yield i18n("打标工具WebUI已关闭")
+
+def change_uvr5(if_uvr5):
+    global p_uvr5
+    if(if_uvr5==True and p_uvr5==None):
+        cmd = '"%s" tools/uvr5/webui.py "%s" %s %s %s'%(python_exec,infer_device,is_half,webui_port_uvr5,is_share)
+        yield i18n("UVR5已开启")
+        print(cmd)
+        p_uvr5 = Popen(cmd, shell=True)
+    elif(if_uvr5==False and p_uvr5!=None):
+        kill_process(p_uvr5.pid)
+        p_uvr5=None
+        yield i18n("UVR5已关闭")
+
+def change_tts_inference(if_tts,bert_path,cnhubert_base_path,gpu_number,gpt_path,sovits_path):
+    global p_tts_inference
+    if(if_tts==True and p_tts_inference==None):
+        os.environ["gpt_path"]=gpt_path if "/" in gpt_path else "%s/%s"%(GPT_weight_root,gpt_path)
+        os.environ["sovits_path"]=sovits_path if "/"in sovits_path else "%s/%s"%(SoVITS_weight_root,sovits_path)
+        os.environ["cnhubert_base_path"]=cnhubert_base_path
+        os.environ["bert_path"]=bert_path
+        os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_number(gpu_number)
+        os.environ["is_half"]=str(is_half)
+        os.environ["infer_ttswebui"]=str(webui_port_infer_tts)
+        os.environ["is_share"]=str(is_share)
+        cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"'%(python_exec, language)
+        yield i18n("TTS推理进程已开启")
+        print(cmd)
+        p_tts_inference = Popen(cmd, shell=True)
+    elif(if_tts==False and p_tts_inference!=None):
+        kill_process(p_tts_inference.pid)
+        p_tts_inference=None
+        yield i18n("TTS推理进程已关闭")
+
+from tools.asr.config import asr_dict
+def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, asr_precision):
+    global p_asr
+    if(p_asr==None):
+        asr_inp_dir=my_utils.clean_path(asr_inp_dir)
+        asr_opt_dir=my_utils.clean_path(asr_opt_dir)
+        check_for_exists([asr_inp_dir])
+        cmd = f'"{python_exec}" tools/asr/{asr_dict[asr_model]["path"]}'
+        cmd += f' -i "{asr_inp_dir}"'
+        cmd += f' -o "{asr_opt_dir}"'
+        cmd += f' -s {asr_model_size}'
+        cmd += f' -l {asr_lang}'
+        cmd += f" -p {asr_precision}"
+        output_file_name = os.path.basename(asr_inp_dir)
+        output_folder = asr_opt_dir or "output/asr_opt"
+        output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')
+        yield "ASR任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"}
+        print(cmd)
+        p_asr = Popen(cmd, shell=True)
+        p_asr.wait()
+        p_asr=None
+        yield f"ASR任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":asr_inp_dir}
+    else:
+        yield "已有正在进行的ASR任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"}
+        # return None
+
+def close_asr():
+    global p_asr
+    if(p_asr!=None):
+        kill_process(p_asr.pid)
+        p_asr=None
+    return "已终止ASR进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+def open_denoise(denoise_inp_dir, denoise_opt_dir):
+    global p_denoise
+    if(p_denoise==None):
+        denoise_inp_dir=my_utils.clean_path(denoise_inp_dir)
+        denoise_opt_dir=my_utils.clean_path(denoise_opt_dir)
+        check_for_exists([denoise_inp_dir])
+        cmd = '"%s" tools/cmd-denoise.py -i "%s" -o "%s" -p %s'%(python_exec,denoise_inp_dir,denoise_opt_dir,"float16"if is_half==True else "float32")
+
+        yield "语音降噪任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}
+        print(cmd)
+        p_denoise = Popen(cmd, shell=True)
+        p_denoise.wait()
+        p_denoise=None
+        yield f"语音降噪任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":denoise_opt_dir}, {"__type__":"update","value":denoise_opt_dir}
+    else:
+        yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}
+        # return None
+
+def close_denoise():
+    global p_denoise
+    if(p_denoise!=None):
+        kill_process(p_denoise.pid)
+        p_denoise=None
+    return "已终止语音降噪进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+
+p_train_SoVITS=None
+def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D):
+    global p_train_SoVITS
+    if(p_train_SoVITS==None):
+        with open("GPT_SoVITS/configs/s2.json")as f:
+            data=f.read()
+            data=json.loads(data)
+        s2_dir="%s/%s"%(exp_root,exp_name)
+        os.makedirs("%s/logs_s2"%(s2_dir),exist_ok=True)
+        check_for_exists([s2_dir],is_train=True)
+        if(is_half==False):
+            data["train"]["fp16_run"]=False
+            batch_size=max(1,batch_size//2)
+        data["train"]["batch_size"]=batch_size
+        data["train"]["epochs"]=total_epoch
+        data["train"]["text_low_lr_rate"]=text_low_lr_rate
+        data["train"]["pretrained_s2G"]=pretrained_s2G
+        data["train"]["pretrained_s2D"]=pretrained_s2D
+        data["train"]["if_save_latest"]=if_save_latest
+        data["train"]["if_save_every_weights"]=if_save_every_weights
+        data["train"]["save_every_epoch"]=save_every_epoch
+        data["train"]["gpu_numbers"]=gpu_numbers1Ba
+        data["model"]["version"]=version
+        data["data"]["exp_dir"]=data["s2_ckpt_dir"]=s2_dir
+        data["save_weight_dir"]=SoVITS_weight_root[-int(version[-1])+2]
+        data["name"]=exp_name
+        data["version"]=version
+        tmp_config_path="%s/tmp_s2.json"%tmp
+        with open(tmp_config_path,"w")as f:f.write(json.dumps(data))
+
+        cmd = '"%s" GPT_SoVITS/s2_train.py --config "%s"'%(python_exec,tmp_config_path)
+        yield "SoVITS训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
+        print(cmd)
+        p_train_SoVITS = Popen(cmd, shell=True)
+        p_train_SoVITS.wait()
+        p_train_SoVITS=None
+        yield "SoVITS训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+    else:
+        yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
+
+def close1Ba():
+    global p_train_SoVITS
+    if(p_train_SoVITS!=None):
+        kill_process(p_train_SoVITS.pid)
+        p_train_SoVITS=None
+    return "已终止SoVITS训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+
+p_train_GPT=None
+def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers,pretrained_s1):
+    global p_train_GPT
+    if(p_train_GPT==None):
+        with open("GPT_SoVITS/configs/s1longer.yaml"if version=="v1"else "GPT_SoVITS/configs/s1longer-v2.yaml")as f:
+            data=f.read()
+            data=yaml.load(data, Loader=yaml.FullLoader)
+        s1_dir="%s/%s"%(exp_root,exp_name)
+        os.makedirs("%s/logs_s1"%(s1_dir),exist_ok=True)
+        check_for_exists([s1_dir],is_train=True)
+        if(is_half==False):
+            data["train"]["precision"]="32"
+            batch_size = max(1, batch_size // 2)
+        data["train"]["batch_size"]=batch_size
+        data["train"]["epochs"]=total_epoch
+        data["pretrained_s1"]=pretrained_s1
+        data["train"]["save_every_n_epoch"]=save_every_epoch
+        data["train"]["if_save_every_weights"]=if_save_every_weights
+        data["train"]["if_save_latest"]=if_save_latest
+        data["train"]["if_dpo"]=if_dpo
+        data["train"]["half_weights_save_dir"]=GPT_weight_root[-int(version[-1])+2]
+        data["train"]["exp_name"]=exp_name
+        data["train_semantic_path"]="%s/6-name2semantic.tsv"%s1_dir
+        data["train_phoneme_path"]="%s/2-name2text.txt"%s1_dir
+        data["output_dir"]="%s/logs_s1"%s1_dir
+        # data["version"]=version
+
+        os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_numbers(gpu_numbers.replace("-",","))
+        os.environ["hz"]="25hz"
+        tmp_config_path="%s/tmp_s1.yaml"%tmp
+        with open(tmp_config_path, "w") as f:f.write(yaml.dump(data, default_flow_style=False))
+        # cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" --train_semantic_path "%s/6-name2semantic.tsv" --train_phoneme_path "%s/2-name2text.txt" --output_dir "%s/logs_s1"'%(python_exec,tmp_config_path,s1_dir,s1_dir,s1_dir)
+        cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" '%(python_exec,tmp_config_path)
+        yield "GPT训练开始：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
+        print(cmd)
+        p_train_GPT = Popen(cmd, shell=True)
+        p_train_GPT.wait()
+        p_train_GPT=None
+        yield "GPT训练完成", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+    else:
+        yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}
+
+def close1Bb():
+    global p_train_GPT
+    if(p_train_GPT!=None):
+        kill_process(p_train_GPT.pid)
+        p_train_GPT=None
+    return "已终止GPT训练", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+
+ps_slice=[]
+def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_parts):
+    global ps_slice
+    inp = my_utils.clean_path(inp)
+    opt_root = my_utils.clean_path(opt_root)
+    check_for_exists([inp])
+    if(os.path.exists(inp)==False):
+        yield "输入路径不存在", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+        return
+    if os.path.isfile(inp):n_parts=1
+    elif os.path.isdir(inp):pass
+    else:
+        yield "输入路径存在但既不是文件也不是文件夹", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+        return
+    if (ps_slice == []):
+        for i_part in range(n_parts):
+            cmd = '"%s" tools/slice_audio.py "%s" "%s" %s %s %s %s %s %s %s %s %s''' % (python_exec,inp, opt_root, threshold, min_length, min_interval, hop_size, max_sil_kept, _max, alpha, i_part, n_parts)
+            print(cmd)
+            p = Popen(cmd, shell=True)
+            ps_slice.append(p)
+        yield "切割执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+        for p in ps_slice:
+            p.wait()
+        ps_slice=[]
+        yield "切割结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}
+    else:
+        yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+
+def close_slice():
+    global ps_slice
+    if (ps_slice != []):
+        for p_slice in ps_slice:
+            try:
+                kill_process(p_slice.pid)
+            except:
+                traceback.print_exc()
+        ps_slice=[]
+    return "已终止所有切割进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+
+ps1a=[]
+def open1a(inp_text,inp_wav_dir,exp_name,gpu_numbers,bert_pretrained_dir):
+    global ps1a
+    inp_text = my_utils.clean_path(inp_text)
+    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
+    check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True)
+    if (ps1a == []):
+        opt_dir="%s/%s"%(exp_root,exp_name)
+        config={
+            "inp_text":inp_text,
+            "inp_wav_dir":inp_wav_dir,
+            "exp_name":exp_name,
+            "opt_dir":opt_dir,
+            "bert_pretrained_dir":bert_pretrained_dir,
+        }
+        gpu_names=gpu_numbers.split("-")
+        all_parts=len(gpu_names)
+        for i_part in range(all_parts):
+            config.update(
+                {
+                    "i_part": str(i_part),
+                    "all_parts": str(all_parts),
+                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                    "is_half": str(is_half)
+                }
+            )
+            os.environ.update(config)
+            cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
+            print(cmd)
+            p = Popen(cmd, shell=True)
+            ps1a.append(p)
+        yield "文本进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+        for p in ps1a:
+            p.wait()
+        opt = []
+        for i_part in range(all_parts):
+            txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
+            with open(txt_path, "r", encoding="utf8") as f:
+                opt += f.read().strip("\n").split("\n")
+            os.remove(txt_path)
+        path_text = "%s/2-name2text.txt" % opt_dir
+        with open(path_text, "w", encoding="utf8") as f:
+            f.write("\n".join(opt) + "\n")
+        ps1a=[]
+        if len("".join(opt)) > 0:
+            yield "文本进程成功", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+        else:
+            yield "文本进程失败", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+    else:
+        yield "已有正在进行的文本任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+
+def close1a():
+    global ps1a
+    if (ps1a != []):
+        for p1a in ps1a:
+            try:
+                kill_process(p1a.pid)
+            except:
+                traceback.print_exc()
+        ps1a=[]
+    return "已终止所有1a进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+
+ps1b=[]
+def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir):
+    global ps1b
+    inp_text = my_utils.clean_path(inp_text)
+    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
+    check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True)
+    if (ps1b == []):
+        config={
+            "inp_text":inp_text,
+            "inp_wav_dir":inp_wav_dir,
+            "exp_name":exp_name,
+            "opt_dir":"%s/%s"%(exp_root,exp_name),
+            "cnhubert_base_dir":ssl_pretrained_dir,
+            "is_half": str(is_half)
+        }
+        gpu_names=gpu_numbers.split("-")
+        all_parts=len(gpu_names)
+        for i_part in range(all_parts):
+            config.update(
+                {
+                    "i_part": str(i_part),
+                    "all_parts": str(all_parts),
+                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                }
+            )
+            os.environ.update(config)
+            cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
+            print(cmd)
+            p = Popen(cmd, shell=True)
+            ps1b.append(p)
+        yield "SSL提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+        for p in ps1b:
+            p.wait()
+        ps1b=[]
+        yield "SSL提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+    else:
+        yield "已有正在进行的SSL提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+
+def close1b():
+    global ps1b
+    if (ps1b != []):
+        for p1b in ps1b:
+            try:
+                kill_process(p1b.pid)
+            except:
+                traceback.print_exc()
+        ps1b=[]
+    return "已终止所有1b进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+
+ps1c=[]
+def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path):
+    global ps1c
+    inp_text = my_utils.clean_path(inp_text)
+    check_for_exists([inp_text,''], is_dataset_processing=True)
+    if (ps1c == []):
+        opt_dir="%s/%s"%(exp_root,exp_name)
+        config={
+            "inp_text":inp_text,
+            "exp_name":exp_name,
+            "opt_dir":opt_dir,
+            "pretrained_s2G":pretrained_s2G_path,
+            "s2config_path":"GPT_SoVITS/configs/s2.json",
+            "is_half": str(is_half)
+        }
+        gpu_names=gpu_numbers.split("-")
+        all_parts=len(gpu_names)
+        for i_part in range(all_parts):
+            config.update(
+                {
+                    "i_part": str(i_part),
+                    "all_parts": str(all_parts),
+                    "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                }
+            )
+            os.environ.update(config)
+            cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
+            print(cmd)
+            p = Popen(cmd, shell=True)
+            ps1c.append(p)
+        yield "语义token提取进程执行中", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+        for p in ps1c:
+            p.wait()
+        opt = ["item_name\tsemantic_audio"]
+        path_semantic = "%s/6-name2semantic.tsv" % opt_dir
+        for i_part in range(all_parts):
+            semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part)
+            with open(semantic_path, "r", encoding="utf8") as f:
+                opt += f.read().strip("\n").split("\n")
+            os.remove(semantic_path)
+        with open(path_semantic, "w", encoding="utf8") as f:
+            f.write("\n".join(opt) + "\n")
+        ps1c=[]
+        yield "语义token提取进程结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}
+    else:
+        yield "已有正在进行的语义token提取任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+
+def close1c():
+    global ps1c
+    if (ps1c != []):
+        for p1c in ps1c:
+            try:
+                kill_process(p1c.pid)
+            except:
+                traceback.print_exc()
+        ps1c=[]
+    return "已终止所有语义token进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+#####inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G
+ps1abc=[]
+def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,ssl_pretrained_dir,pretrained_s2G_path):
+    global ps1abc
+    inp_text = my_utils.clean_path(inp_text)
+    inp_wav_dir = my_utils.clean_path(inp_wav_dir)
+    check_for_exists([inp_text,inp_wav_dir])
+    if (ps1abc == []):
+        opt_dir="%s/%s"%(exp_root,exp_name)
+        try:
+            #############################1a
+            path_text="%s/2-name2text.txt" % opt_dir
+            if(os.path.exists(path_text)==False or (os.path.exists(path_text)==True and len(open(path_text,"r",encoding="utf8").read().strip("\n").split("\n"))<2)):
+                config={
+                    "inp_text":inp_text,
+                    "inp_wav_dir":inp_wav_dir,
+                    "exp_name":exp_name,
+                    "opt_dir":opt_dir,
+                    "bert_pretrained_dir":bert_pretrained_dir,
+                    "is_half": str(is_half)
+                }
+                gpu_names=gpu_numbers1a.split("-")
+                all_parts=len(gpu_names)
+                for i_part in range(all_parts):
+                    config.update(
+                        {
+                            "i_part": str(i_part),
+                            "all_parts": str(all_parts),
+                            "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                        }
+                    )
+                    os.environ.update(config)
+                    cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
+                    print(cmd)
+                    p = Popen(cmd, shell=True)
+                    ps1abc.append(p)
+                yield "进度：1a-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+                for p in ps1abc:p.wait()
+
+                opt = []
+                for i_part in range(all_parts):#txt_path="%s/2-name2text-%s.txt"%(opt_dir,i_part)
+                    txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
+                    with open(txt_path, "r",encoding="utf8") as f:
+                        opt += f.read().strip("\n").split("\n")
+                    os.remove(txt_path)
+                with open(path_text, "w",encoding="utf8") as f:
+                    f.write("\n".join(opt) + "\n")
+                assert len("".join(opt)) > 0, "1Aa-文本获取进程失败"
+            yield "进度：1a-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+            ps1abc=[]
+            #############################1b
+            config={
+                "inp_text":inp_text,
+                "inp_wav_dir":inp_wav_dir,
+                "exp_name":exp_name,
+                "opt_dir":opt_dir,
+                "cnhubert_base_dir":ssl_pretrained_dir,
+            }
+            gpu_names=gpu_numbers1Ba.split("-")
+            all_parts=len(gpu_names)
+            for i_part in range(all_parts):
+                config.update(
+                    {
+                        "i_part": str(i_part),
+                        "all_parts": str(all_parts),
+                        "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                    }
+                )
+                os.environ.update(config)
+                cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
+                print(cmd)
+                p = Popen(cmd, shell=True)
+                ps1abc.append(p)
+            yield "进度：1a-done, 1b-ing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+            for p in ps1abc:p.wait()
+            yield "进度：1a1b-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+            ps1abc=[]
+            #############################1c
+            path_semantic = "%s/6-name2semantic.tsv" % opt_dir
+            if(os.path.exists(path_semantic)==False or (os.path.exists(path_semantic)==True and os.path.getsize(path_semantic)<31)):
+                config={
+                    "inp_text":inp_text,
+                    "exp_name":exp_name,
+                    "opt_dir":opt_dir,
+                    "pretrained_s2G":pretrained_s2G_path,
+                    "s2config_path":"GPT_SoVITS/configs/s2.json",
+                }
+                gpu_names=gpu_numbers1c.split("-")
+                all_parts=len(gpu_names)
+                for i_part in range(all_parts):
+                    config.update(
+                        {
+                            "i_part": str(i_part),
+                            "all_parts": str(all_parts),
+                            "_CUDA_VISIBLE_DEVICES": fix_gpu_number(gpu_names[i_part]),
+                        }
+                    )
+                    os.environ.update(config)
+                    cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
+                    print(cmd)
+                    p = Popen(cmd, shell=True)
+                    ps1abc.append(p)
+                yield "进度：1a1b-done, 1cing", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+                for p in ps1abc:p.wait()
+
+                opt = ["item_name\tsemantic_audio"]
+                for i_part in range(all_parts):
+                    semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part)
+                    with open(semantic_path, "r",encoding="utf8") as f:
+                        opt += f.read().strip("\n").split("\n")
+                    os.remove(semantic_path)
+                with open(path_semantic, "w",encoding="utf8") as f:
+                    f.write("\n".join(opt) + "\n")
+                yield "进度：all-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+            ps1abc = []
+            yield "一键三连进程结束", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+        except:
+            traceback.print_exc()
+            close1abc()
+            yield "一键三连中途报错", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+    else:
+        yield "已有正在进行的一键三连任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
+
+def close1abc():
+    global ps1abc
+    if (ps1abc != []):
+        for p1abc in ps1abc:
+            try:
+                kill_process(p1abc.pid)
+            except:
+                traceback.print_exc()
+        ps1abc=[]
+    return "已终止所有一键三连进程", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
+
+def switch_version(version_):
+    os.environ['version']=version_
+    global version
+    version = version_
+    if pretrained_sovits_name[-int(version[-1])+2] !='' and pretrained_gpt_name[-int(version[-1])+2] !='':...
+    else:   
+        gr.Warning(i18n(f'未下载{version.upper()}模型'))
+    return  {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D")}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}
+
+def check_for_exists(file_list=None,is_train=False,is_dataset_processing=False):
+    missing_files=[]
+    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):pass
+        else:missing_files.append(file)
+    if missing_files:
+        if is_train:
+            for missing_file in missing_files:
+                if missing_file != '':
+                    gr.Warning(missing_file)
+            gr.Warning(i18n('以下文件或文件夹不存在:'))
+        else:
+            for missing_file in missing_files:
+                if missing_file != '':
+                    gr.Warning(missing_file)
+            if file_list[-1]==[''] and is_dataset_processing:
+                pass
+            else:
+                gr.Warning(i18n('以下文件或文件夹不存在:'))
+
+if os.path.exists('GPT_SoVITS/text/G2PWModel'):...
+else:
+    cmd = '"%s" GPT_SoVITS/download.py'%python_exec
+    p = Popen(cmd, shell=True)
+    p.wait()
+
+with gr.Blocks(title="GPT-SoVITS WebUI") as app:
+    gr.Markdown(
+        value=
+            i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>.")
+    )
+    gr.Markdown(
+        value=
+            i18n("中文教程文档：https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e")
+    )
+
+    with gr.Tabs():
+        with gr.TabItem(i18n("0-前置数据集获取工具")):#提前随机切片防止uvr5爆内存->uvr5->slicer->asr->打标
+            gr.Markdown(value=i18n("0a-UVR5人声伴奏分离&去混响去延迟工具"))
+            with gr.Row():
+                if_uvr5 = gr.Checkbox(label=i18n("是否开启UVR5-WebUI"),show_label=True)
+                uvr5_info = gr.Textbox(label=i18n("UVR5进程输出信息"))
+            gr.Markdown(value=i18n("0b-语音切分工具"))
+            with gr.Row():
+                with gr.Column(scale=3):
+                    with gr.Row():
+                        slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="")
+                        slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt")
+                    with gr.Row():
+                        threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34")
+                        min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000")
+                        min_interval=gr.Textbox(label=i18n("min_interval:最短切割间隔"),value="300")
+                        hop_size=gr.Textbox(label=i18n("hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）"),value="10")
+                        max_sil_kept=gr.Textbox(label=i18n("max_sil_kept:切完后静音最多留多长"),value="500")
+                    with gr.Row():
+                        _max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("max:归一化后最大值多少"),value=0.9,interactive=True)
+                        alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True)
+                        n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True)
+                    with gr.Row():
+                        slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息"))
+                open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True)
+                close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False)
+            gr.Markdown(value=i18n("0bb-语音降噪工具"))
+            with gr.Row():
+                with gr.Column(scale=3):
+                    with gr.Row():
+                        denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="")
+                        denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt")
+                    with gr.Row():
+                        denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息"))
+                open_denoise_button = gr.Button(i18n("开启语音降噪"), variant="primary",visible=True)
+                close_denoise_button = gr.Button(i18n("终止语音降噪进程"), variant="primary",visible=False)
+            gr.Markdown(value=i18n("0c-中文批量离线ASR工具"))
+            with gr.Row():
+                with gr.Column(scale=3):
+                    with gr.Row():
+                        asr_inp_dir = gr.Textbox(
+                            label=i18n("输入文件夹路径"),
+                            value="D:\\GPT-SoVITS\\raw\\xxx",
+                            interactive=True,
+                        )
+                        asr_opt_dir = gr.Textbox(
+                            label       = i18n("输出文件夹路径"),
+                            value       = "output/asr_opt",
+                            interactive = True,
+                        )
+                    with gr.Row():
+                        asr_model = gr.Dropdown(
+                            label       = i18n("ASR 模型"),
+                            choices     = list(asr_dict.keys()),
+                            interactive = True,
+                            value="达摩 ASR (中文)"
+                        )
+                        asr_size = gr.Dropdown(
+                            label       = i18n("ASR 模型尺寸"),
+                            choices     = ["large"],
+                            interactive = True,
+                            value="large"
+                        )
+                        asr_lang = gr.Dropdown(
+                            label       = i18n("ASR 语言设置"),
+                            choices     = ["zh","yue"],
+                            interactive = True,
+                            value="zh"
+                        )
+                        asr_precision = gr.Dropdown(
+                            label       = i18n("数据类型精度"),
+                            choices     = ["float32"],
+                            interactive = True,
+                            value="float32"
+                        ) 
+                    with gr.Row():
+                        asr_info = gr.Textbox(label=i18n("ASR进程输出信息"))     
+                open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True)
+                close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False)                  
+
+                def change_lang_choices(key): #根据选择的模型修改可选的语言
+                    # return gr.Dropdown(choices=asr_dict[key]['lang'])
+                    return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]}
+                def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸
+                    # return gr.Dropdown(choices=asr_dict[key]['size'])
+                    return {"__type__": "update", "choices": asr_dict[key]['size'],"value":asr_dict[key]['size'][-1]}
+                def change_precision_choices(key): #根据选择的模型修改可选的语言
+                    if key =="Faster Whisper (多语种)":
+                        if default_batch_size <= 4:
+                            precision = 'int8'
+                        elif is_half:
+                            precision = 'float16'
+                        else:
+                            precision = 'float32'
+                    else:
+                        precision = 'float32'
+                    # return gr.Dropdown(choices=asr_dict[key]['precision'])
+                    return {"__type__": "update", "choices": asr_dict[key]['precision'],"value":precision}
+                asr_model.change(change_lang_choices, [asr_model], [asr_lang])
+                asr_model.change(change_size_choices, [asr_model], [asr_size])
+                asr_model.change(change_precision_choices, [asr_model], [asr_precision])
+
+                
+            gr.Markdown(value=i18n("0d-语音文本校对标注工具"))
+            with gr.Row():
+                if_label = gr.Checkbox(label=i18n("是否开启打标WebUI"),show_label=True)
+                path_list = gr.Textbox(
+                    label=i18n(".list标注文件的路径"),
+                    value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx.list",
+                    interactive=True,
+                )
+                label_info = gr.Textbox(label=i18n("打标工具进程输出信息"))
+            if_label.change(change_label, [if_label,path_list], [label_info])
+            if_uvr5.change(change_uvr5, [if_uvr5], [uvr5_info])
+
+        with gr.TabItem(i18n("1-GPT-SoVITS-TTS")):
+            with gr.Row():
+                exp_name = gr.Textbox(label=i18n("*实验/模型名"), value="xxx", interactive=True)
+                gpu_info = gr.Textbox(label=i18n("显卡信息"), value=gpu_info, visible=True, interactive=False)
+                version_checkbox = gr.Radio(label=i18n("版本"),value=version,choices=['v1','v2'])
+                pretrained_s2G = gr.Textbox(label=i18n("预训练的SoVITS-G模型路径"), value=pretrained_sovits_name[-int(version[-1])+2], interactive=True)
+                pretrained_s2D = gr.Textbox(label=i18n("预训练的SoVITS-D模型路径"), value=pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"), interactive=True)
+                pretrained_s1 = gr.Textbox(label=i18n("预训练的GPT模型路径"), value=pretrained_gpt_name[-int(version[-1])+2], interactive=True)
+            with gr.TabItem(i18n("1A-训练集格式化工具")):
+                gr.Markdown(value=i18n("输出logs/实验名目录下应有23456开头的文件和文件夹"))
+                with gr.Row():
+                    inp_text = gr.Textbox(label=i18n("*文本标注文件"),value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",interactive=True)
+                    inp_wav_dir = gr.Textbox(
+                        label=i18n("*训练集音频文件目录"),
+                        # value=r"D:\RVC1006\GPT-SoVITS\raw\xxx",
+                        interactive=True,
+                        placeholder=i18n("填切割后音频所在目录！读取的音频文件完整路径=该目录-拼接-list文件里波形对应的文件名（不是全路径）。如果留空则使用.list文件里的绝对全路径。")
+                    )
+                gr.Markdown(value=i18n("1Aa-文本内容"))
+                with gr.Row():
+                    gpu_numbers1a = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
+                    bert_pretrained_dir = gr.Textbox(label=i18n("预训练的中文BERT模型路径"),value="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",interactive=False)
+                    button1a_open = gr.Button(i18n("开启文本获取"), variant="primary",visible=True)
+                    button1a_close = gr.Button(i18n("终止文本获取进程"), variant="primary",visible=False)
+                    info1a=gr.Textbox(label=i18n("文本进程输出信息"))
+                gr.Markdown(value=i18n("1Ab-SSL自监督特征提取"))
+                with gr.Row():
+                    gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
+                    cnhubert_base_dir = gr.Textbox(label=i18n("预训练的SSL模型路径"),value="GPT_SoVITS/pretrained_models/chinese-hubert-base",interactive=False)
+                    button1b_open = gr.Button(i18n("开启SSL提取"), variant="primary",visible=True)
+                    button1b_close = gr.Button(i18n("终止SSL提取进程"), variant="primary",visible=False)
+                    info1b=gr.Textbox(label=i18n("SSL进程输出信息"))
+                gr.Markdown(value=i18n("1Ac-语义token提取"))
+                with gr.Row():
+                    gpu_numbers1c = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"),value="%s-%s"%(gpus,gpus),interactive=True)
+                    button1c_open = gr.Button(i18n("开启语义token提取"), variant="primary",visible=True)
+                    button1c_close = gr.Button(i18n("终止语义token提取进程"), variant="primary",visible=False)
+                    info1c=gr.Textbox(label=i18n("语义token提取进程输出信息"))
+                gr.Markdown(value=i18n("1Aabc-训练集格式化一键三连"))
+                with gr.Row():
+                    button1abc_open = gr.Button(i18n("开启一键三连"), variant="primary",visible=True)
+                    button1abc_close = gr.Button(i18n("终止一键三连"), variant="primary",visible=False)
+                    info1abc=gr.Textbox(label=i18n("一键三连进程输出信息"))
+
+            open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang, asr_precision], [asr_info,open_asr_button,close_asr_button,path_list,inp_text,inp_wav_dir])
+            close_asr_button.click(close_asr, [], [asr_info,open_asr_button,close_asr_button])
+            open_slicer_button.click(open_slice, [slice_inp_path,slice_opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_process], [slicer_info,open_slicer_button,close_slicer_button,asr_inp_dir,denoise_input_dir,inp_wav_dir])
+            close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button])
+            open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button,asr_inp_dir,inp_wav_dir])
+            close_denoise_button.click(close_denoise, [], [denoise_info,open_denoise_button,close_denoise_button])
+            
+            button1a_open.click(open1a, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,bert_pretrained_dir], [info1a,button1a_open,button1a_close])
+            button1a_close.click(close1a, [], [info1a,button1a_open,button1a_close])
+            button1b_open.click(open1b, [inp_text,inp_wav_dir,exp_name,gpu_numbers1Ba,cnhubert_base_dir], [info1b,button1b_open,button1b_close])
+            button1b_close.click(close1b, [], [info1b,button1b_open,button1b_close])
+            button1c_open.click(open1c, [inp_text,exp_name,gpu_numbers1c,pretrained_s2G], [info1c,button1c_open,button1c_close])
+            button1c_close.click(close1c, [], [info1c,button1c_open,button1c_close])
+            button1abc_open.click(open1abc, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G], [info1abc,button1abc_open,button1abc_close])
+            button1abc_close.click(close1abc, [], [info1abc,button1abc_open,button1abc_close])
+            with gr.TabItem(i18n("1B-微调训练")):
+                gr.Markdown(value=i18n("1Ba-SoVITS训练。用于分享的模型文件输出在SoVITS_weights下。"))
+                with gr.Row():
+                    batch_size = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
+                    total_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("总训练轮数total_epoch，不建议太高"),value=8,interactive=True)
+                    text_low_lr_rate = gr.Slider(minimum=0.2,maximum=0.6,step=0.05,label=i18n("文本模块学习率权重"),value=0.4,interactive=True)
+                    save_every_epoch = gr.Slider(minimum=1,maximum=25,step=1,label=i18n("保存频率save_every_epoch"),value=4,interactive=True)
+                    if_save_latest = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
+                    if_save_every_weights = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
+                    gpu_numbers1Ba = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True)
+                with gr.Row():
+                    button1Ba_open = gr.Button(i18n("开启SoVITS训练"), variant="primary",visible=True)
+                    button1Ba_close = gr.Button(i18n("终止SoVITS训练"), variant="primary",visible=False)
+                    info1Ba=gr.Textbox(label=i18n("SoVITS训练进程输出信息"))
+                gr.Markdown(value=i18n("1Bb-GPT训练。用于分享的模型文件输出在GPT_weights下。"))
+                with gr.Row():
+                    batch_size1Bb = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
+                    total_epoch1Bb = gr.Slider(minimum=2,maximum=50,step=1,label=i18n("总训练轮数total_epoch"),value=15,interactive=True)
+                    if_dpo = gr.Checkbox(label=i18n("是否开启dpo训练选项(实验性)"), value=False, interactive=True, show_label=True)
+                    if_save_latest1Bb = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
+                    if_save_every_weights1Bb = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
+                    save_every_epoch1Bb = gr.Slider(minimum=1,maximum=50,step=1,label=i18n("保存频率save_every_epoch"),value=5,interactive=True)
+                    gpu_numbers1Bb = gr.Textbox(label=i18n("GPU卡号以-分割，每个卡号一个进程"), value="%s" % (gpus), interactive=True)
+                with gr.Row():
+                    button1Bb_open = gr.Button(i18n("开启GPT训练"), variant="primary",visible=True)
+                    button1Bb_close = gr.Button(i18n("终止GPT训练"), variant="primary",visible=False)
+                    info1Bb=gr.Textbox(label=i18n("GPT训练进程输出信息"))
+            button1Ba_open.click(open1Ba, [batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D], [info1Ba,button1Ba_open,button1Ba_close])
+            button1Ba_close.click(close1Ba, [], [info1Ba,button1Ba_open,button1Ba_close])
+            button1Bb_open.click(open1Bb, [batch_size1Bb,total_epoch1Bb,exp_name,if_dpo,if_save_latest1Bb,if_save_every_weights1Bb,save_every_epoch1Bb,gpu_numbers1Bb,pretrained_s1],   [info1Bb,button1Bb_open,button1Bb_close])
+            button1Bb_close.click(close1Bb, [], [info1Bb,button1Bb_open,button1Bb_close])
+            with gr.TabItem(i18n("1C-推理")):
+                gr.Markdown(value=i18n("选择训练完存放在SoVITS_weights和GPT_weights下的模型。默认的一个是底模，体验5秒Zero Shot TTS用。"))
+                with gr.Row():
+                    GPT_dropdown = gr.Dropdown(label=i18n("*GPT模型列表"), choices=sorted(GPT_names,key=custom_sort_key),value=pretrained_gpt_name[0],interactive=True)
+                    SoVITS_dropdown = gr.Dropdown(label=i18n("*SoVITS模型列表"), choices=sorted(SoVITS_names,key=custom_sort_key),value=pretrained_sovits_name[0],interactive=True)
+                    gpu_number_1C=gr.Textbox(label=i18n("GPU卡号,只能填1个整数"), value=gpus, interactive=True)
+                    refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary")
+                    refresh_button.click(fn=change_choices,inputs=[],outputs=[SoVITS_dropdown,GPT_dropdown])
+                with gr.Row():
+                    if_tts = gr.Checkbox(label=i18n("是否开启TTS推理WebUI"), show_label=True)
+                    tts_info = gr.Textbox(label=i18n("TTS推理WebUI进程输出信息"))
+                    if_tts.change(change_tts_inference, [if_tts,bert_pretrained_dir,cnhubert_base_dir,gpu_number_1C,GPT_dropdown,SoVITS_dropdown], [tts_info])
+            version_checkbox.change(switch_version,[version_checkbox],[pretrained_s2G,pretrained_s2D,pretrained_s1,GPT_dropdown,SoVITS_dropdown])
+        with gr.TabItem(i18n("2-GPT-SoVITS-变声")):gr.Markdown(value=i18n("施工中，请静候佳音"))
+    app.queue(concurrency_count=511, max_size=1022).launch(
+        share=False,
+        show_error=True,
     )
\ No newline at end of file