mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2026-01-19 18:41:52 +00:00
fix: train step2a & add arg --port --pycmd --noparallel
This commit is contained in:
源文雨
35
infer-web.py
35
infer-web.py
@@ -1,9 +1,10 @@
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from multiprocessing import cpu_count
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import threading
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from time import sleep
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from subprocess import Popen,PIPE,run as runn
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from subprocess import Popen
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from time import sleep
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import torch, pdb, os,traceback,sys,warnings,shutil,numpy as np,faiss
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import torch, os,traceback,sys,warnings,shutil,numpy as np
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import faiss
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#判断是否有能用来训练和加速推理的N卡
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ncpu=cpu_count()
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ngpu=torch.cuda.device_count()
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@@ -33,11 +34,9 @@ from infer_pack.models import SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFs
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from scipy.io import wavfile
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from fairseq import checkpoint_utils
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import gradio as gr
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import librosa
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import logging
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from vc_infer_pipeline import VC
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import soundfile as sf
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from config import is_half,device,is_half
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from config import is_half,device,is_half,python_cmd,listen_port,iscolab,noparallel
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from infer_uvr5 import _audio_pre_
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from my_utils import load_audio
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from train.process_ckpt import show_info,change_info,merge,extract_small_model
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@@ -222,7 +221,7 @@ def preprocess_dataset(trainset_dir,exp_dir,sr,n_p=ncpu):
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os.makedirs("%s/logs/%s"%(now_dir,exp_dir),exist_ok=True)
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f = open("%s/logs/%s/preprocess.log"%(now_dir,exp_dir), "w")
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f.close()
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cmd="python trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s"%(trainset_dir,sr,n_p,now_dir,exp_dir)
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cmd=python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "%(trainset_dir,sr,n_p,now_dir,exp_dir)+str(noparallel)
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print(cmd)
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p = Popen(cmd, shell=True)#, stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir
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###煞笔gr，popen read都非得全跑完了再一次性读取，不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
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@@ -242,7 +241,7 @@ def extract_f0_feature(gpus,n_p,f0method,if_f0,exp_dir):
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f = open("%s/logs/%s/extract_f0_feature.log"%(now_dir,exp_dir), "w")
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f.close()
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if(if_f0=="是"):
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cmd="python extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir,n_p,f0method)
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cmd=python_cmd + " extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir,n_p,f0method)
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print(cmd)
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p = Popen(cmd, shell=True,cwd=now_dir)#, stdin=PIPE, stdout=PIPE,stderr=PIPE
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###煞笔gr，popen read都非得全跑完了再一次性读取，不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
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@@ -266,7 +265,7 @@ def extract_f0_feature(gpus,n_p,f0method,if_f0,exp_dir):
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leng=len(gpus)
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ps=[]
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for idx,n_g in enumerate(gpus):
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cmd="python extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir)
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cmd=python_cmd + " extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir)
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print(cmd)
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p = Popen(cmd, shell=True, cwd=now_dir)#, shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
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ps.append(p)
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@@ -305,8 +304,8 @@ def click_train(exp_dir1,sr2,if_f0_3,spk_id5,save_epoch10,total_epoch11,batch_si
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with open("%s/filelist.txt"%exp_dir,"w")as f:f.write("\n".join(opt))
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print("write filelist done")
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#生成config#无需生成config
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# cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0"
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cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0)
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# cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0"
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cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0)
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print(cmd)
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p = Popen(cmd, shell=True, cwd=now_dir)
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p.wait()
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@@ -351,7 +350,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth
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os.makedirs("%s/logs/%s"%(now_dir,exp_dir1),exist_ok=True)
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#########step1:处理数据
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open("%s/logs/%s/preprocess.log"%(now_dir,exp_dir1), "w").close()
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cmd="python trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s"%(trainset_dir4,sr_dict[sr2],ncpu,now_dir,exp_dir1)
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cmd=python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "%(trainset_dir4,sr_dict[sr2],ncpu,now_dir,exp_dir1)+str(noparallel)
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yield get_info_str("step1:正在处理数据")
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yield get_info_str(cmd)
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p = Popen(cmd, shell=True)
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@@ -361,7 +360,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth
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open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir1), "w")
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if(if_f0_3=="是"):
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yield get_info_str("step2a:正在提取音高")
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cmd="python extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir1,np7,f0method8)
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cmd=python_cmd + " extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir1,np7,f0method8)
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yield get_info_str(cmd)
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p = Popen(cmd, shell=True,cwd=now_dir)
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p.wait()
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@@ -373,7 +372,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth
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leng=len(gpus)
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ps=[]
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for idx,n_g in enumerate(gpus):
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cmd="python extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir1)
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cmd=python_cmd + " extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir1)
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yield get_info_str(cmd)
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p = Popen(cmd, shell=True, cwd=now_dir)#, shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
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ps.append(p)
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@@ -399,7 +398,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth
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opt.append("%s/%s.wav|%s/%s.npy|%s"%(gt_wavs_dir.replace("\\","\\\\"),name,co256_dir.replace("\\","\\\\"),name,spk_id5))
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with open("%s/filelist.txt"%exp_dir,"w")as f:f.write("\n".join(opt))
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yield get_info_str("write filelist done")
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cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0)
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cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0)
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yield get_info_str(cmd)
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p = Popen(cmd, shell=True, cwd=now_dir)
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p.wait()
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@@ -630,11 +629,7 @@ with gr.Blocks() as app:
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with gr.TabItem("点击查看交流、问题反馈群号"):
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gr.Markdown(value="""xxxxx""")
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument("--colab", action='store_true', help="Launch in colab")
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cmd_opts = parser.parse_args()
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if cmd_opts.colab:
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if iscolab:
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app.queue(concurrency_count=511, max_size=1022).launch(share=True)
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else:
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app.queue(concurrency_count=511, max_size=1022).launch(server_name="0.0.0.0",inbrowser=True,server_port=7865,quiet=True)
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app.queue(concurrency_count=511, max_size=1022).launch(server_name="0.0.0.0",inbrowser=True,server_port=listen_port,quiet=True)
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