mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-04-05 04:22:46 +08:00
106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
import traceback
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from collections import OrderedDict
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from time import time as ttime
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import shutil,os
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import torch
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from tools.i18n.i18n import I18nAuto
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i18n = I18nAuto()
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def my_save(fea,path):#####fix issue: torch.save doesn't support chinese path
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dir=os.path.dirname(path)
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name=os.path.basename(path)
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tmp_path="%s.pth"%(ttime())
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torch.save(fea,tmp_path)
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shutil.move(tmp_path,"%s/%s"%(dir,name))
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'''
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00:v1
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01:v2
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02:v3
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03:v3lora
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'''
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from io import BytesIO
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def my_save2(fea,path):
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bio = BytesIO()
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torch.save(fea, bio)
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bio.seek(0)
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data = bio.getvalue()
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data = b'03' + data[2:]###temp for v3lora only, todo
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with open(path, "wb") as f: f.write(data)
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def savee(ckpt, name, epoch, steps, hps,lora_rank=None):
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try:
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opt = OrderedDict()
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opt["weight"] = {}
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for key in ckpt.keys():
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if "enc_q" in key:
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continue
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opt["weight"][key] = ckpt[key].half()
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opt["config"] = hps
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opt["info"] = "%sepoch_%siteration" % (epoch, steps)
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if lora_rank:
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opt["lora_rank"]=lora_rank
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my_save2(opt, "%s/%s.pth" % (hps.save_weight_dir, name))
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else:
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my_save(opt, "%s/%s.pth" % (hps.save_weight_dir, name))
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return "Success."
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except:
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return traceback.format_exc()
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head2version={
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b'00':["v1","v1",False],
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b'01':["v2","v2",False],
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b'02':["v2","v3",False],
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b'03':["v2","v3",True],
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}
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hash_pretrained_dict={
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"dc3c97e17592963677a4a1681f30c653":["v2","v2",False],#s2G488k.pth#sovits_v1_pretrained
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"43797be674a37c1c83ee81081941ed0f":["v2","v3",False],#s2Gv3.pth#sovits_v3_pretrained
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"6642b37f3dbb1f76882b69937c95a5f3":["v2","v2",False],#s2G2333K.pth#sovits_v2_pretrained
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}
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import hashlib
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def get_hash_from_file(sovits_path):
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with open(sovits_path,"rb")as f:data=f.read(8192)
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hash_md5 = hashlib.md5()
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hash_md5.update(data)
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return hash_md5.hexdigest()
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def get_sovits_version_from_path_fast(sovits_path):
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###1-if it is pretrained sovits models, by hash
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hash=get_hash_from_file(sovits_path)
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if hash in hash_pretrained_dict:
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return hash_pretrained_dict[hash]
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###2-new weights or old weights, by head
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with open(sovits_path,"rb")as f:version=f.read(2)
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if version!=b"PK":
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return head2version[version]
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###3-old weights, by file size
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if_lora_v3=False
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size=os.path.getsize(sovits_path)
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'''
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v1weights:about 82942KB
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half thr:82978KB
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v2weights:about 83014KB
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v3weights:about 750MB
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'''
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if size < 82978 * 1024:
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model_version = version = "v1"
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elif size < 700 * 1024 * 1024:
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model_version = version = "v2"
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else:
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version = "v2"
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model_version = "v3"
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return version,model_version,if_lora_v3
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def load_sovits_new(sovits_path):
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f=open(sovits_path,"rb")
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meta=f.read(2)
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if meta!="PK":
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data = b'PK' + f.read()
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bio = BytesIO()
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bio.write(data)
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bio.seek(0)
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return torch.load(bio, map_location="cpu", weights_only=False)
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return torch.load(sovits_path,map_location="cpu", weights_only=False) |