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import traceback
from collections import OrderedDict
from time import time as ttime
import shutil,os
import torch
from tools.i18n.i18n import I18nAuto
i18n = I18nAuto()
def my_save(fea,path):#####fix issue: torch.save doesn't support chinese path
dir=os.path.dirname(path)
name=os.path.basename(path)
tmp_path="%s.pth"%(ttime())
torch.save(fea,tmp_path)
shutil.move(tmp_path,"%s/%s"%(dir,name))
'''
00:v1
01:v2
02:v3
03:v3lora
'''
from io import BytesIO
def my_save2(fea,path):
bio = BytesIO()
torch.save(fea, bio)
bio.seek(0)
data = bio.getvalue()
data = b'03' + data[2:]###temp for v3lora only, todo
with open(path, "wb") as f: f.write(data)
def savee(ckpt, name, epoch, steps, hps,lora_rank=None):
try:
opt = OrderedDict()
opt["weight"] = {}
for key in ckpt.keys():
if "enc_q" in key:
continue
opt["weight"][key] = ckpt[key].half()
opt["config"] = hps
opt["info"] = "%sepoch_%siteration" % (epoch, steps)
if lora_rank:
opt["lora_rank"]=lora_rank
my_save2(opt, "%s/%s.pth" % (hps.save_weight_dir, name))
else:
my_save(opt, "%s/%s.pth" % (hps.save_weight_dir, name))
return "Success."
except:
return traceback.format_exc()
head2version={
b'00':["v1","v1",False],
b'01':["v2","v2",False],
b'02':["v2","v3",False],
b'03':["v2","v3",True],
}
hash_pretrained_dict={
"dc3c97e17592963677a4a1681f30c653":["v2","v2",False],#s2G488k.pth#sovits_v1_pretrained
"43797be674a37c1c83ee81081941ed0f":["v2","v3",False],#s2Gv3.pth#sovits_v3_pretrained
"6642b37f3dbb1f76882b69937c95a5f3":["v2","v2",False],#s2G2333K.pth#sovits_v2_pretrained
}
import hashlib
def get_hash_from_file(sovits_path):
with open(sovits_path,"rb")as f:data=f.read(8192)
hash_md5 = hashlib.md5()
hash_md5.update(data)
return hash_md5.hexdigest()
def get_sovits_version_from_path_fast(sovits_path):
###1-if it is pretrained sovits models, by hash
hash=get_hash_from_file(sovits_path)
if hash in hash_pretrained_dict:
return hash_pretrained_dict[hash]
###2-new weights or old weights, by head
with open(sovits_path,"rb")as f:version=f.read(2)
if version!=b"PK":
return head2version[version]
###3-old weights, by file size
if_lora_v3=False
size=os.path.getsize(sovits_path)
'''
v1weights:about 82942KB
half thr:82978KB
v2weights:about 83014KB
v3weights:about 750MB
'''
if size < 82978 * 1024:
model_version = version = "v1"
elif size < 700 * 1024 * 1024:
model_version = version = "v2"
else:
version = "v2"
model_version = "v3"
return version,model_version,if_lora_v3
def load_sovits_new(sovits_path):
f=open(sovits_path,"rb")
meta=f.read(2)
if meta!="PK":
data = b'PK' + f.read()
bio = BytesIO()
bio.write(data)
bio.seek(0)
return torch.load(bio, map_location="cpu", weights_only=False)
return torch.load(sovits_path,map_location="cpu", weights_only=False) |