From e80a02bdd5ded8599a024e112a9e079737241cca Mon Sep 17 00:00:00 2001 From: XXXXRT666 Date: Tue, 6 Aug 2024 17:09:01 +0800 Subject: [PATCH] chores:warning --- webui.py | 26 ++++++++++++++++++++++++-- 1 file changed, 24 insertions(+), 2 deletions(-) diff --git a/webui.py b/webui.py index 78d1c95b..3a990690 100644 --- a/webui.py +++ b/webui.py @@ -48,7 +48,6 @@ from tools import my_utils import traceback import shutil import pdb -import gradio as gr 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 @@ -63,7 +62,9 @@ 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() @@ -248,6 +249,7 @@ def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, 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}"' @@ -278,6 +280,7 @@ def open_denoise(denoise_inp_dir, denoise_opt_dir): 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"} @@ -306,6 +309,7 @@ def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_s 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) @@ -352,6 +356,7 @@ def open1Bb(batch_size,total_epoch,exp_name,if_dpo,if_save_latest,if_save_every_ 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) @@ -396,6 +401,7 @@ def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_k 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"} return @@ -434,6 +440,7 @@ 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]) if (ps1a == []): opt_dir="%s/%s"%(exp_root,exp_name) config={ @@ -495,6 +502,7 @@ 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]) if (ps1b == []): config={ "inp_text":inp_text, @@ -542,6 +550,7 @@ 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]) if (ps1c == []): opt_dir="%s/%s"%(exp_root,exp_name) config={ @@ -600,6 +609,7 @@ def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numb 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: @@ -736,6 +746,18 @@ def switch_version(version_): 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=[],is_train=False): + _='' + 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:_+=f'\n {file}' + if _:gr.Warning(i18n('以下文件不存在:')) from text.g2pw import G2PWPinyin g2pw = G2PWPinyin(model_dir="GPT_SoVITS/text/G2PWModel",model_source="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",v_to_u=False, neutral_tone_with_five=True)