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diff --git a/AutoCoverTool/script/multi_trainer.py b/AutoCoverTool/script/multi_trainer.py
index fa4b194..7a67ea4 100644
--- a/AutoCoverTool/script/multi_trainer.py
+++ b/AutoCoverTool/script/multi_trainer.py
@@ -1,87 +1,92 @@
"""
分布式训练
"""
import os
import json
import glob
+from script.upload_mode2db import upload_one2db
def put_data():
dir_list = glob.glob("/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/*")
already_user_ids = [
"10133099162839896",
"10133099162997509",
"10133099163727028",
"10133099163890661",
"10133099163991355",
"10133099164311744",
"10133099164313669",
"10133099165386135",
"10133099166041782",
"10133099166050735",
"10133099166238022",
"10133099166605472",
"10133099166892845",
"10133099166898301",
"10133099167125366",
"10133099167394822",
"10133099167940583",
"10133099168376799",
"10133099168924385",
"8725724286358130",
"finish"
]
from online.beanstalk_helper import BeanstalkHelper
config = {"addr": "sg-test-common-box-1:11300", "consumer": "auto_user_svc_trainer"}
bean_helper = BeanstalkHelper(config)
for idx, line in enumerate(dir_list):
cur_dir = str(line.split("/")[-1])
if cur_dir not in already_user_ids:
message = json.dumps({"user_id": str(cur_dir)})
bean_helper.put_payload_to_beanstalk(config["consumer"], message, ttr=2 * 86400)
print(len("tot_num={}".format(len(dir_list))))
def process():
from online.beanstalk_helper import BeanstalkHelper
bb_dir = "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/"
config = {"addr": "sg-test-common-box-1:11300", "consumer": "auto_user_svc_trainer"}
bean_helper = BeanstalkHelper(config)
bean = bean_helper.get_beanstalkd()
bean.watch(config["consumer"])
while True:
payload = bean.reserve(5)
if not payload:
print("bean sleep...")
continue
in_data = json.loads(payload.body)
user_id = in_data["user_id"]
try:
user_id_int = int(float(user_id))
g_2000_path = os.path.join(bb_dir, os.path.join(str(user_id_int), "logs/32k/G_2000.pth"))
if os.path.exists(g_2000_path):
print("log, {} already exists!....".format(user_id_int))
payload.delete()
continue
src_dir = os.path.join(bb_dir, os.path.join(str(user_id_int), "src"))
if not os.path.exists(src_dir):
print("log, {} src not exists!....".format(user_id_int))
payload.delete()
continue
cmd = "bash script/train.sh {}".format(user_id_int)
print(cmd)
os.system(cmd)
+
+ # 上传到cos并更新数据库
+ if os.path.exists(g_2000_path):
+ upload_one2db(g_2000_path, user_id_int)
print("log, train {} ok....".format(user_id_int))
except Exception as ex:
pass
payload.delete()
if __name__ == '__main__':
process()
diff --git a/AutoCoverTool/script/upload_mode2db.py b/AutoCoverTool/script/upload_mode2db.py
index be3773d..2c8af9b 100644
--- a/AutoCoverTool/script/upload_mode2db.py
+++ b/AutoCoverTool/script/upload_mode2db.py
@@ -1,280 +1,280 @@
"""
将训练好的模型写入到数据库
"""
from online.common import update_db, get_data_by_mysql
import os
GS_COSCMD = "/data/gpu_env_common/env/anaconda3/envs/auto_song_cover/bin/coscmd"
GS_CONFIG_PATH = "/home/normal/.cos.conf"
def exec_cmd(cmd):
ret = os.system(cmd)
if ret != 0:
return False
return True
def exec_cmd_and_result(cmd):
r = os.popen(cmd)
text = r.read()
r.close()
return text
def upload_file2cos(key, file_path, region, bucket_name):
"""
将文件上传到cos
:param key: 桶上的具体地址
:param file_path: 本地文件地址
:param region: 区域
:param bucket_name: 桶地址
:return:
"""
cmd = "{} -c {} -r {} -b {} upload {} {}".format(GS_COSCMD, GS_CONFIG_PATH, region, bucket_name, file_path, key)
print(cmd)
if exec_cmd(cmd):
cmd = "{} -c {} -r {} -b {} info {}".format(GS_COSCMD, GS_CONFIG_PATH, region, bucket_name, key) \
+ "| grep Content-Length |awk \'{print $2}\'"
res_str = exec_cmd_and_result(cmd)
size = float(res_str)
if size > 0:
return True
return False
return False
def upload_one2db(db_path, db_name):
# 判断已经在数据库中，则不上传
sql = "select * from av_db.av_svc_model where user_id=\"{}\"".format(db_name)
data = get_data_by_mysql(sql)
if len(data) == 0:
print('start upload ....')
- key = "av_res/so_vits_models/3.0/male/{}.pth".format(db_name)
+ key = "av_res/so_vits_models/3.0/unknown/{}.pth".format(db_name)
if upload_file2cos(key, db_path, region="ap-beijing", bucket_name="av-audit-sync-bj-1256122840"):
# 写入到数据库
- sql = "insert into av_db.av_svc_model (model_version, user_id, model_url, gender) values (\"sovits3.0\", \"{}\", \"{}\", 1)".format(
+ sql = "insert into av_db.av_svc_model (model_version, user_id, model_url, gender) values (\"sovits3.0\", \"{}\", \"{}\", 3)".format(
db_name, key)
update_db(sql)
if __name__ == '__main__':
# arr = [
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099162839896/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099162997509/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099163727028/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099163890661/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099163991355/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099164311744/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099164313669/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099165386135/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166041782/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166050735/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166238022/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166605472/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166892845/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099166898301/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099167125366/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099167394822/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099167940583/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099168376799/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099168924385/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099169324630/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099169381678/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099169957610/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099169975944/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099170492806/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099170892510/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171013390/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171081854/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171087756/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171192036/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171607206/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099171754668/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099172086640/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099172138002/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099172207062/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099172269180/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099172339368/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574138359736/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574138369704/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574138530136/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574139102564/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574139888146/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574139967984/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574140258122/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574140405046/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574140676612/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574140780266/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574142812606/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574143134746/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574143604234/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574143906306/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574144526110/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574144707118/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574145823464/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574145904464/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574146080322/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574146420792/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574146884926/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147339012/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147372254/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147425002/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147597736/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147647706/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147658166/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574147828554/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148014424/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148247626/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148624370/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148669184/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148692388/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574148859406/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574149000590/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574149067094/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574149143568/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574149221618/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10414574149303702/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049115833380/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049115944594/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049115987498/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049116130908/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049116285936/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049117044138/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049117276112/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049117685892/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049119207544/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049119659788/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049120426324/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049120919532/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049121183928/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049121338248/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049121406512/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049121502826/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123071172/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123219186/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123447868/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123506368/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123660154/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049123805538/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124073344/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124110520/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124182084/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124450100/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124595430/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049124833978/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125084058/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125481092/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125584584/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125798928/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125820940/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125864268/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125885128/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125972416/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125997808/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10696049125999636/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524091895906/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524092611108/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524092703694/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524092737576/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524092926748/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524093350560/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524093613618/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524094859474/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524096635844/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524096695280/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524096819198/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524096995342/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524098416100/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524098804908/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524099612646/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524100174518/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524100978492/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101050108/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101220516/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101243434/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101575638/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101593280/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524101680844/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102313334/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102348346/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102432628/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102444474/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102525738/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102533320/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102598012/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102674590/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102678972/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10977524102679572/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899906849269/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899908853925/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899908854526/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899908904395/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899909347935/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899909790502/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910057693/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910105120/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910461551/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910516883/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910808376/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910826302/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899910943438/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899911011477/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899911821662/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899911962207/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912327206/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912442110/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912511535/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912520616/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912538184/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912584668/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912859360/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912895306/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912929958/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/1125899912987231/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/3635049378/logs/32k/G_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/8725724286358130/logs/32k/G_2000.pth"
# ]
arr = [
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10133099162058848.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10133099162258844.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10133099162560644.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10133099162797809.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10414574138721494.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/10414574140317353.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/1688849864840588.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/3634463651.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/5629499489839033.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/5910973794723621.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/6755399374234747.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/8162774327817435.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/8162774329368194.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/denglijun_g2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/female/taylor_g2000.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/10133099161752147.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/10133099161920114.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/10133099162292113.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/10133099162767013.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/1125899914308640.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/12384898975368914.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/12947848931397021.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/3096224748076687.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/3096224751151928.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/5066549357604730.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/5348024335101054.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/6755399442719465.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/7036874421386111.pth",
"/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/male/jianli_g_2000.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/unknown/10133099171607206.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/unknown/10133099172269180.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/unknown/10414574138369704.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/unknown/10414574143604234.pth",
# "/data/rsync/jianli.yang/AutoCoverTool/data/online_models/models/unknown/10414574144707118.pth"
]
for d_file in arr:
# d_file = "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/multi_users/10133099162839896/logs/32k/G_2000.pth"
# d_name = "10133099162839896"
d_name = d_file.split("/")[-1].split(".")[0]
print(d_file, d_name)
upload_one2db(d_file, d_name)
# exit(-1)
diff --git a/AutoCoverTool/svc_inference/svc_inference_one.py b/AutoCoverTool/svc_inference/svc_inference_one.py
index 5218e1e..ecb8e8c 100644
--- a/AutoCoverTool/svc_inference/svc_inference_one.py
+++ b/AutoCoverTool/svc_inference/svc_inference_one.py
@@ -1,210 +1,215 @@
"""
SVC推理逻辑
conda activate auto_song_cover_t4
export PYTHONPATH=$PWD:$PWD/ref/music_remover/demucs:$PWD/ref/so_vits_svc:$PWD/ref/split_dirty_frame:$PWD/ref/online
"""
import os
+import json
import shutil
from ref.so_vits_svc.inference_main import *
from ref.speaker_feature_extractor.sf_extractor_interface import SFExtractorInterface
gs_draw_volume_exe = "/data/gpu_env_common/bin/draw_volume"
gs_simple_mixer_path = "/data/gpu_env_common/bin/simple_mixer"
gs_svci_success = 0
gs_svci_data_params_check_model_path = 1
gs_svci_data_params_check_vocal_path = 2
gs_svci_data_params_check_acc_path = 3
gs_svci_data_params_check_video_path = 4
gs_svci_data_prepare_transcode_media = 5
gs_svci_data_inference = 6
gs_svci_svc_trans_442 = 7
gs_svci_svc_volume = 8
gs_svci_svc_mix = 9
gs_svci_svc_mix_gen = 10
gs_svci_svc_mix_audio_video = 11
class SVCInferenceOne:
def __init__(self):
self.vocal_32_wav_path = None
self.vocal_wav_path = None
self.acc_wav_path = None
self.config = os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json")
self.spk_emb_inst = SFExtractorInterface()
def mix(self, work_dir, svc_file, vocal_file, acc_file, mix_path):
"""
:param work_dir:
:param svc_file:
:param vocal_file:
:param acc_file:
:param mix_path:
:return:
"""
cache_dir = os.path.join(work_dir, "cache")
if os.path.exists(cache_dir):
shutil.rmtree(cache_dir)
os.makedirs(cache_dir)
# svc转码到442
svc_442_file = os.path.join(cache_dir, "442.wav")
st = time.time()
cmd = "ffmpeg -i {} -ar 44100 -ac 2 -y {} -loglevel fatal".format(svc_file, svc_442_file)
os.system(cmd)
if not os.path.exists(svc_442_file):
return gs_svci_svc_trans_442
logging.info("transcode,{},sp={}".format(svc_file, time.time() - st))
# 合并转码后再做一次拉伸，保证响度
st = time.time()
volume_path = os.path.join(cache_dir, "volume.wav")
cmd = "{} {} {} {}".format(gs_draw_volume_exe, svc_442_file, vocal_file, volume_path)
os.system(cmd)
if not os.path.exists(volume_path):
print("{} ERROR draw volume".format(volume_path))
return gs_svci_svc_volume
logging.info("draw_volume2,{},sp={}".format(svc_file, time.time() - st))
# 混合
st = time.time()
mix_wav_path = os.path.join(cache_dir, "mix.wav")
cmd = "{} {} {} {}".format(gs_simple_mixer_path, volume_path, acc_file, mix_wav_path)
os.system(cmd)
if not os.path.exists(mix_wav_path):
return gs_svci_svc_mix
logging.info("mixer,{},sp={}".format(svc_file, time.time() - st))
# 编码为m4a
st = time.time()
cmd = "ffmpeg -i {} -ab 128k -y {} -loglevel fatal".format(mix_wav_path, mix_path)
print(cmd)
os.system(cmd)
if not os.path.exists(mix_path):
return gs_svci_svc_mix
logging.info("encode,{},sp={}".format(svc_file, time.time() - st))
return gs_svci_success
def params_check(self, model_path, vocal_path, acc_path, video_path):
if not os.path.exists(model_path):
print("model_path={} is null".format(model_path))
return gs_svci_data_params_check_model_path
if not os.path.exists(vocal_path):
print("vocal_path={} is null".format(vocal_path))
return gs_svci_data_params_check_vocal_path
if not os.path.exists(acc_path):
print("acc_path={} is null".format(acc_path))
return gs_svci_data_params_check_acc_path
if not os.path.exists(video_path):
print("video_path={} is null".format(video_path))
return gs_svci_data_params_check_video_path
return gs_svci_success
def data_prepare(self, work_dir, vocal_path, acc_path):
self.vocal_32_wav_path = os.path.join(work_dir, "vocal_32.wav")
self.vocal_wav_path = os.path.join(work_dir, "vocal.wav")
self.acc_wav_path = os.path.join(work_dir, "acc.wav")
cmd = "ffmpeg -i {} -ar 44100 -ac 2 -y {}".format(vocal_path, self.vocal_wav_path)
os.system(cmd)
cmd = "ffmpeg -i {} -ar 32000 -ac 1 -y {}".format(vocal_path, self.vocal_32_wav_path)
os.system(cmd)
cmd = "ffmpeg -i {} -ar 44100 -ac 2 -y {}".format(acc_path, self.acc_wav_path)
os.system(cmd)
return os.path.exists(self.vocal_32_wav_path) and os.path.exists(self.acc_wav_path)
def process_logic(self, work_dir, model_path, vocal_path, acc_path, video_path, out_path):
# 1. 先转码人声和伴奏
st = time.time()
if not self.data_prepare(work_dir, vocal_path, acc_path):
print("transcode vocal={} or acc={} err!\n".format(vocal_path, acc_path))
return gs_svci_data_prepare_transcode_media
print("transcode vocal and acc sp={}".format(time.time() - st))
# 2. 进行推理
# raw_audio_path, dst_path
st = time.time()
svc_file = os.path.join(work_dir, "trans_vocal.wav")
# try:
inf(model_path, self.config, self.vocal_32_wav_path, svc_file, 'prod')
# except Exception as ex:
# print(ex)
if not os.path.exists(svc_file):
print("inference err vocal_path={}, model_path={}".format(vocal_path, model_path))
return gs_svci_data_inference, []
print("inf sp={}".format(time.time() - st))
# 3. 生成作品
st = time.time()
mix_tmp_path = os.path.join(work_dir, "mix.wav")
err = self.mix(work_dir, svc_file, self.vocal_wav_path, self.acc_wav_path, mix_tmp_path)
if err != gs_svci_success:
return err, []
if not os.path.exists(mix_tmp_path):
return gs_svci_svc_mix_gen, []
print("mix sp={}".format(time.time() - st))
st = time.time()
# 4. 音频编码，并且和视频合并
cmd = "ffmpeg -i {} -i {} -acodec aac -strict -2 -b:a 128k -vcodec copy -shortest -af apad -y {}".format(
video_path,
mix_tmp_path,
out_path)
os.system(cmd)
if not os.path.exists(out_path):
print("mix audio_video err={}".format(video_path, mix_tmp_path))
return gs_svci_svc_mix_audio_video, []
print("mix audio and video sp={}".format(time.time() - st))
# 5. 提取emb
st = time.time()
emb = self.spk_emb_inst.process(svc_file)
print("get emb sp={}".format(time.time() - st))
return gs_svci_success, emb
def process(self, work_dir, model_path, vocal_path, acc_path, video_path, out_path):
err = self.params_check(model_path, vocal_path, acc_path, video_path)
if err != gs_svci_success:
return err, []
if os.path.exists(work_dir):
shutil.rmtree(work_dir)
os.makedirs(work_dir)
st = time.time()
err, emb = self.process_logic(work_dir, model_path, vocal_path, acc_path, video_path, out_path)
print("process_logic sp={}".format(time.time() - st))
shutil.rmtree(work_dir)
return err, emb
def test():
svc_inst = SVCInferenceOne()
b_dir = "/data/rsync/jianli.yang/AutoCoverTool/data/test_svc_inference_one/"
w_dir = os.path.join(b_dir, "rg_input")
in_m4a = os.path.join(b_dir, "rg_input.m4a")
in_acc_m4a = os.path.join(b_dir, "acc.m4a")
in_video = os.path.join(b_dir, "rg.mp4")
out_video = os.path.join(b_dir, "rg_input_out.mp4")
m_path = "/data/rsync/jianli.yang/AutoCoverTool/data/train_users/jianli/logs/32k/G_2000.pth"
err, emb = svc_inst.process(w_dir, m_path, in_m4a, in_acc_m4a, in_video, out_video)
print(err)
print(emb)
if __name__ == '__main__':
- if len(sys.argv) != 7:
+ if len(sys.argv) != 8:
print("input err!")
print(
- "example: work_dir[临时工作目录，内部会自动清除数据] model_path in_media_path in_acc_media_path in_video_path out_video_path")
+ "example: work_dir[临时工作目录，内部会自动清除数据] model_path in_media_path in_acc_media_path in_video_path out_video_path emb_path")
exit(-1)
w_dir = sys.argv[1]
m_path = sys.argv[2]
in_m4a = sys.argv[3]
in_acc_m4a = sys.argv[4]
in_video = sys.argv[5]
out_video = sys.argv[6]
+ emb_path = sys.argv[7]
svc_inst = SVCInferenceOne()
err, emb = svc_inst.process(w_dir, m_path, in_m4a, in_acc_m4a, in_video, out_video)
- print(err)
- print(emb)
+ with open(emb_path, "w") as f:
+ f.write(json.dumps({"emb": list(emb.tolist())}))
+
+ # print(err)
+ # print(emb)
diff --git a/AutoCoverTool/svc_inference/webui.py b/AutoCoverTool/svc_inference/webui.py
index 42d40fc..9b5de2a 100644
--- a/AutoCoverTool/svc_inference/webui.py
+++ b/AutoCoverTool/svc_inference/webui.py
@@ -1,101 +1,92 @@
"""
构建唱歌音色转换网页(基于3.0)
要求:
1. 音频上传
2. 推理
3. 下载
"""
import os
import time
import glob
import shutil
import librosa
import soundfile
import gradio as gr
from online.common import update_db
from ref.so_vits_svc.inference_main import *
gs_tmp_dir = "/tmp/svc_inference"
gs_model_dir = "/data/prod/so_vits_models/3.0"
gs_test_wav_dir = "/data/prod/so_vits_models/test_svc_file/3.0"
gs_config_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json")
def generate_svc_file():
"""
:return:
"""
if not os.path.exists(gs_test_wav_dir):
os.makedirs(gs_test_wav_dir)
test_wav_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "../res/syz_test.wav")
model_path_list = glob.glob(os.path.join(gs_model_dir, "*/*pth"))
st = time.time()
for idx, model_path in enumerate(model_path_list):
- model_name = model_path.strip().split("/")[-1].split(".pth", "")
+ model_name = model_path.strip().split("/")[-1].replace(".pth", "")
dst_path = os.path.join(gs_test_wav_dir, "{}.wav".format(model_name))
if not os.path.exists(dst_path):
inf(model_path, gs_config_path, test_wav_path, dst_path, "prod")
print("now_per={}/{}".format(idx, len(model_path_list), time.time() - st))
def update_state(gender, user_id):
sql = "update av_db.av_svc_model set gender={} where user_id=\"{}\"".format(gender, user_id)
update_db(sql)
# 按钮控制
def click_male(user_id):
+ print("click_male={}".format(user_id))
pass
def click_female(user_id):
- pass
+ print("click_female={}".format(user_id))
def click_delete(user_id):
- pass
+ print("click_delete={}".format(user_id))
def main():
# header
st = time.time()
generate_svc_file()
print("generate svc sp={}".format(time.time() - st))
app = gr.Blocks()
with app:
# 头部介绍
gr.Markdown(value="""
### 人声质量评价
作者：starmaker音视频
""")
# 列表展示
# 1. 每一行有音频,性别,删除等按钮
svc_files = glob.glob(os.path.join(gs_test_wav_dir, "*wav"))
for svc_file in svc_files:
user_id = svc_file.split("/")[-1].replace(".wav", "")
gr.Audio(source=svc_file)
male_gender_btn = gr.Button("male")
female_gender_btn = gr.Button("female")
del_btn = gr.Button("female")
male_gender_btn.click(click_male, inputs=[user_id])
female_gender_btn.click(click_female, inputs=[user_id])
del_btn.click(click_delete, inputs=[user_id])
-
- refresh_btn = gr.Button("refresh_model_list")
- refresh_btn.click(fn=model_select, inputs=[], outputs=gs_model_list_dropdown)
-
- # 音频输入框
- input_audio = gr.inputs.Audio(label="input")
- vc_transform = gr.Number(label="变调（整数，可以正负，半音数量，升高八度就是12）", value=0)
- gen_btn = gr.Button("generate", variant="primary")
- output_audio = gr.outputs.Audio(label="output", type='filepath')
- gen_btn.click(fn=svc, inputs=[input_audio, gs_model_list_dropdown, vc_transform], outputs=output_audio)
# 本方法实现同一时刻只有一个程序在服务器端运行
app.queue(concurrency_count=1, max_size=2044).launch(server_name="0.0.0.0", inbrowser=True, quiet=True,
server_port=7860)
if __name__ == '__main__':
main()

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