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Refactor: Format Code with Ruff and Update Deprecated G2PW Link (#2255)

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* ruff check --fix

* ruff format --line-length 120 --target-version py39

* Change the link for G2PW Model

* update pytorch version and colab
This commit is contained in:
XXXXRT666
2025-04-07 09:42:47 +01:00
committed by GitHub
parent 9da7e17efe
commit 53cac93589
132 changed files with 8185 additions and 6648 deletions
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89
GPT_SoVITS/process_ckpt.py
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@@ -1,37 +1,44 @@
import traceback
from collections import OrderedDict
from time import time as ttime
import shutil,os
import shutil
import 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))
'''
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):
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)
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):
def savee(ckpt, name, epoch, steps, hps, lora_rank=None):
try:
opt = OrderedDict()
opt["weight"] = {}
@@ -42,7 +49,7 @@ def savee(ckpt, name, epoch, steps, hps,lora_rank=None):
opt["config"] = hps
opt["info"] = "%sepoch_%siteration" % (epoch, steps)
if lora_rank:
opt["lora_rank"]=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))
@@ -50,41 +57,48 @@ def savee(ckpt, name, epoch, steps, hps,lora_rank=None):
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],
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
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)
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)
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":
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)
'''
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:
@@ -92,15 +106,16 @@ def get_sovits_version_from_path_fast(sovits_path):
else:
version = "v2"
model_version = "v3"
return version,model_version,if_lora_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()
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)
return torch.load(sovits_path, map_location="cpu", weights_only=False)