RVC/Retrieval-based-Voice-Conversion-WebUI
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RVC-Boss
2023-08-13 01:05:58 +08:00
committed by GitHub
parent 7f78dce483
commit 03e7c68c11
11 changed files with 478 additions and 270 deletions
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186
infer-web.py
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@@ -23,7 +23,7 @@ import ffmpeg
import gradio as gr
import soundfile as sf
from config import Config
from fairseq import checkpoint_utils
import fairseq
from i18n import I18nAuto
from lib.infer_pack.models import (
SynthesizerTrnMs256NSFsid,
@@ -43,7 +43,9 @@ logging.getLogger("numba").setLevel(logging.WARNING)
now_dir = os.getcwd()
tmp = os.path.join(now_dir, "TEMP")
shutil.rmtree(tmp, ignore_errors=True)
shutil.rmtree("%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True)
shutil.rmtree(
"%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True
)
shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True)
os.makedirs(tmp, exist_ok=True)
os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True)
@@ -54,6 +56,12 @@ torch.manual_seed(114514)
config = Config()
if(config.dml==True):
def forward_dml(ctx, x, scale):
ctx.scale = scale
res = x.clone().detach()
return res
fairseq.modules.grad_multiply.GradMultiply.forward=forward_dml
i18n = I18nAuto()
i18n.print()
# 判断是否有能用来训练和加速推理的N卡
@@ -124,7 +132,7 @@ hubert_model = None
def load_hubert():
global hubert_model
models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
models, _, _ = fairseq.checkpoint_utils.load_model_ensemble_and_task(
["hubert_base.pt"],
suffix="",
)
@@ -443,7 +451,15 @@ def get_vc(sid, to_return_protect0, to_return_protect1):
del net_g, cpt
if torch.cuda.is_available():
torch.cuda.empty_cache()
return {"visible": False, "__type__": "update"}
return {"visible": False, "__type__": "update"},{
"visible": True,
"value": to_return_protect0,
"__type__": "update",
},{
"visible": True,
"value": to_return_protect1,
"__type__": "update",
},"",""
person = "%s/%s" % (weight_root, sid)
print("loading %s" % person)
@@ -454,7 +470,7 @@ def get_vc(sid, to_return_protect0, to_return_protect1):
if if_f0 == 0:
to_return_protect0 = to_return_protect1 = {
"visible": False,
"value": 0.5,
"value": 0.33,
"__type__": "update",
}
else:
@@ -488,11 +504,15 @@ def get_vc(sid, to_return_protect0, to_return_protect1):
net_g = net_g.float()
vc = VC(tgt_sr, config)
n_spk = cpt["config"][-3]
index={
"value":get_index_path_from_model(sid),
"__type__": "update"
}
return (
{"visible": True, "maximum": n_spk, "__type__": "update"},
to_return_protect0,
to_return_protect1,
get_index_path_from_model(sid),
index,index
)
@@ -608,58 +628,55 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, gpus_rmvp
p,
),
).start()
while 1:
with open(
"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
) as f:
yield (f.read())
sleep(1)
if done[0]:
break
with open(
"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
) as f:
log = f.read()
print(log)
yield log
else:
gpus_rmvpe = gpus_rmvpe.split("-")
leng = len(gpus_rmvpe)
ps = []
for idx, n_g in enumerate(gpus_rmvpe):
cmd = (
config.python_cmd
+ ' extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
% (leng, idx, n_g, now_dir, exp_dir, config.is_half)
if(gpus_rmvpe!="-"):
gpus_rmvpe = gpus_rmvpe.split("-")
leng = len(gpus_rmvpe)
ps = []
for idx, n_g in enumerate(gpus_rmvpe):
cmd = (
config.python_cmd
+ ' extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
% (leng, idx, n_g, now_dir, exp_dir, config.is_half)
)
print(cmd)
p = Popen(
cmd, shell=True, cwd=now_dir
) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
ps.append(p)
###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
done = [False]
threading.Thread(
target=if_done_multi,#
args=(
done,
ps,
),
).start()
else:
cmd = config.python_cmd + ' extract_f0_rmvpe_dml.py "%s/logs/%s" ' % (
now_dir, exp_dir
)
print(cmd)
p = Popen(
cmd, shell=True, cwd=now_dir
) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
ps.append(p)
###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
done = [False]
threading.Thread(
target=if_done_multi,
args=(
done,
ps,
),
).start()
while 1:
with open(
"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
) as f:
yield (f.read())
sleep(1)
if done[0]:
break
p.wait()
done = [True]
while 1:
with open(
"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
) as f:
log = f.read()
print(log)
yield log
yield (f.read())
sleep(1)
if done[0]:
break
with open(
"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
) as f:
log = f.read()
print(log)
yield log
####对不同part分别开多进程
"""
n_part=int(sys.argv[1])
@@ -937,8 +954,8 @@ def click_train(
batch_size12,
total_epoch11,
save_epoch10,
"-pg %s" % pretrained_G14 if pretrained_G14 != "" else "\b",
"-pd %s" % pretrained_D15 if pretrained_D15 != "" else "\b",
"-pg %s" % pretrained_G14 if pretrained_G14 != "" else "",
"-pd %s" % pretrained_D15 if pretrained_D15 != "" else "",
1 if if_save_latest13 == i18n("是") else 0,
1 if if_cache_gpu17 == i18n("是") else 0,
1 if if_save_every_weights18 == i18n("是") else 0,
@@ -953,7 +970,8 @@ def click_train(
# but4.click(train_index, [exp_dir1], info3)
def train_index(exp_dir1, version19):
exp_dir = "%s/logs/%s" % (now_dir, exp_dir1)
# exp_dir = "%s/logs/%s" % (now_dir, exp_dir1)
exp_dir = "logs/%s" % ( exp_dir1)
os.makedirs(exp_dir, exist_ok=True)
feature_dir = (
"%s/3_feature256" % (exp_dir)
@@ -975,7 +993,6 @@ def train_index(exp_dir1, version19):
np.random.shuffle(big_npy_idx)
big_npy = big_npy[big_npy_idx]
if big_npy.shape[0] > 2e5:
# if(1):
infos.append("Trying doing kmeans %s shape to 10k centers." % big_npy.shape[0])
yield "\n".join(infos)
try:
@@ -1012,7 +1029,7 @@ def train_index(exp_dir1, version19):
"%s/trained_IVF%s_Flat_nprobe_%s_%s_%s.index"
% (exp_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19),
)
# faiss.write_index(index, '%s/trained_IVF%s_Flat_FastScan_%s.index'%(exp_dir,n_ivf,version19))
infos.append("adding")
yield "\n".join(infos)
batch_size_add = 8192
@@ -1098,23 +1115,33 @@ def train1key(
p = Popen(cmd, shell=True, cwd=now_dir)
p.wait()
else:
gpus_rmvpe = gpus_rmvpe.split("-")
leng = len(gpus_rmvpe)
ps = []
for idx, n_g in enumerate(gpus_rmvpe):
cmd = config.python_cmd + ' extract_f0_rmvpe.py %s %s %s "%s" %s ' % (
leng,
idx,
n_g,
model_log_dir,
config.is_half,
if(gpus_rmvpe!="-"):
gpus_rmvpe = gpus_rmvpe.split("-")
leng = len(gpus_rmvpe)
ps = []
for idx, n_g in enumerate(gpus_rmvpe):
cmd = config.python_cmd + ' extract_f0_rmvpe.py %s %s %s "%s" %s ' % (
leng,
idx,
n_g,
model_log_dir,
config.is_half,
)
yield get_info_str(cmd)
p = Popen(
cmd, shell=True, cwd=now_dir
) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
ps.append(p)
for p in ps:
p.wait()
else:#dml
cmd = config.python_cmd + ' extract_f0_rmvpe_dml.py "%s" ' % (
model_log_dir
)
yield get_info_str(cmd)
p = Popen(
cmd, shell=True, cwd=now_dir
) # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
ps.append(p)
for p in ps:
p.wait()
with open(extract_f0_feature_log_path, "r") as f:
print(f.read())
@@ -1282,8 +1309,6 @@ def train1key(
yield get_info_str(info)
np.save("%s/total_fea.npy" % model_log_dir, big_npy)
# n_ivf = big_npy.shape[0] // 39
n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])), big_npy.shape[0] // 39)
yield get_info_str("%s,%s" % (big_npy.shape, n_ivf))
index = faiss.index_factory(256 if version19 == "v1" else 768, "IVF%s,Flat" % n_ivf)
@@ -1291,11 +1316,7 @@ def train1key(
index_ivf = faiss.extract_index_ivf(index) #
index_ivf.nprobe = 1
index.train(big_npy)
faiss.write_index(
index,
"%s/trained_IVF%s_Flat_nprobe_%s_%s_%s.index"
% (model_log_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19),
)
faiss.write_index(index,"%s/trained_IVF%s_Flat_nprobe_%s_%s_%s.index"% (model_log_dir.replace(now_dir+"/",""), n_ivf, index_ivf.nprobe, exp_dir1, version19))
yield get_info_str("adding index")
batch_size_add = 8192
for i in range(0, big_npy.shape[0], batch_size_add):
@@ -1303,7 +1324,7 @@ def train1key(
faiss.write_index(
index,
"%s/added_IVF%s_Flat_nprobe_%s_%s_%s.index"
% (model_log_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19),
% (model_log_dir.replace(now_dir+"/",""), n_ivf, index_ivf.nprobe, exp_dir1, version19),
)
yield get_info_str(
"成功构建索引, added_IVF%s_Flat_nprobe_%s_%s_%s.index"
@@ -1329,9 +1350,10 @@ def change_info_(ckpt_path):
return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
F0GPUVisible = config.dml == False
def change_f0_method(f0method8):
if f0method8 == "rmvpe_gpu":
visible = True
visible = F0GPUVisible
else:
visible = False
return {"visible": visible, "__type__": "update"}
@@ -1428,7 +1450,7 @@ with gr.Blocks(title="RVC WebUI") as app:
label=i18n(
"选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
),
choices=["pm", "harvest", "crepe", "rmvpe"],
choices=["pm", "harvest", "crepe", "rmvpe"]if config.dml==False else ["pm", "harvest", "rmvpe"],
value="pm",
interactive=True,
)
@@ -1534,7 +1556,7 @@ with gr.Blocks(title="RVC WebUI") as app:
label=i18n(
"选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU,rmvpe效果最好且微吃GPU"
),
choices=["pm", "harvest", "crepe", "rmvpe"],
choices=["pm", "harvest", "crepe", "rmvpe"]if config.dml==False else ["pm", "harvest", "rmvpe"],
value="pm",
interactive=True,
)
@@ -1643,7 +1665,7 @@ with gr.Blocks(title="RVC WebUI") as app:
sid0.change(
fn=get_vc,
inputs=[sid0, protect0, protect1],
outputs=[spk_item, protect0, protect1, file_index2],
outputs=[spk_item, protect0, protect1, file_index2, file_index4],
)
with gr.TabItem(i18n("伴奏人声分离&去混响&去回声")):
with gr.Group():
@@ -1768,13 +1790,13 @@ with gr.Blocks(title="RVC WebUI") as app:
gpus6 = gr.Textbox(
label=i18n("以-分隔输入使用的卡号, 例如 0-1-2 使用卡0和卡1和卡2"),
value=gpus,
interactive=True,
interactive=True,visible=F0GPUVisible
)
gpu_info9 = gr.Textbox(label=i18n("显卡信息"), value=gpu_info)
gpu_info9 = gr.Textbox(label=i18n("显卡信息"), value=gpu_info,visible=F0GPUVisible)
with gr.Column():
f0method8 = gr.Radio(
label=i18n(
"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢"
"选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢,rmvpe效果最好且微吃CPU/GPU"
),
choices=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"],
value="rmvpe_gpu",
@@ -1786,7 +1808,7 @@ with gr.Blocks(title="RVC WebUI") as app:
),
value="%s-%s" % (gpus, gpus),
interactive=True,
visible=True,
visible=F0GPUVisible,
)
but2 = gr.Button(i18n("特征提取"), variant="primary")
info2 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)