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Merge branch 'fast_inference_' of https://github.com/KevinZhang19870314/GPT-SoVITS into fast_inference_dev

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kevin.zhang 2024-05-27 14:01:57 +08:00
commit c5dc7697a8
13 changed files with 43 additions and 37 deletions
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5
.gitignore vendored
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@ -10,8 +10,3 @@ reference
GPT_weights
SoVITS_weights
TEMP
PortableGit
ffmpeg.exe
ffprobe.exe
tmp_audio
trained

3
Dockerfile
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@ -34,9 +34,6 @@ RUN if [ "$IMAGE_TYPE" != "elite" ]; then \
fi
# Copy the rest of the application
COPY . /workspace
# Copy the rest of the application
COPY . /workspace

6
GPT_SoVITS/TTS_infer_pack/TTS.py
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@ -9,7 +9,7 @@ now_dir = os.getcwd()
sys.path.append(now_dir)
import ffmpeg
import os
from typing import Generator, List, Union
from typing import Generator, List, Tuple, Union
import numpy as np
import torch
import torch.nn.functional as F
@ -597,7 +597,7 @@ class TTS:
"repetition_penalty": 1.35 # float. repetition penalty for T2S model.
}
returns:
tuple[int, np.ndarray]: sampling rate and audio data.
Tuple[int, np.ndarray]: sampling rate and audio data.
"""
########## variables initialization ###########
self.stop_flag:bool = False
@ -880,7 +880,7 @@ class TTS:
speed_factor:float=1.0,
split_bucket:bool=True,
fragment_interval:float=0.3
)->tuple[int, np.ndarray]:
)->Tuple[int, np.ndarray]:
zero_wav = torch.zeros(
int(self.configs.sampling_rate * fragment_interval),
dtype=self.precision,

13
GPT_SoVITS/module/models.py
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@ -16,6 +16,7 @@ from module.mrte_model import MRTE
from module.quantize import ResidualVectorQuantizer
from text import symbols
from torch.cuda.amp import autocast
import contextlib
class StochasticDurationPredictor(nn.Module):
@ -891,9 +892,10 @@ class SynthesizerTrn(nn.Module):
self.ssl_proj = nn.Conv1d(ssl_dim, ssl_dim, 1, stride=1)
self.quantizer = ResidualVectorQuantizer(dimension=ssl_dim, n_q=1, bins=1024)
if freeze_quantizer:
self.ssl_proj.requires_grad_(False)
self.quantizer.requires_grad_(False)
self.freeze_quantizer = freeze_quantizer
# if freeze_quantizer:
# self.ssl_proj.requires_grad_(False)
# self.quantizer.requires_grad_(False)
#self.quantizer.eval()
# self.enc_p.text_embedding.requires_grad_(False)
# self.enc_p.encoder_text.requires_grad_(False)
@ -906,6 +908,11 @@ class SynthesizerTrn(nn.Module):
ge = self.ref_enc(y * y_mask, y_mask)
with autocast(enabled=False):
maybe_no_grad = torch.no_grad() if self.freeze_quantizer else contextlib.nullcontext()
with maybe_no_grad:
if self.freeze_quantizer:
self.ssl_proj.eval()
self.quantizer.eval()
ssl = self.ssl_proj(ssl)
quantized, codes, commit_loss, quantized_list = self.quantizer(
ssl, layers=[0]

3
GPT_SoVITS/prepare_datasets/1-get-text.py
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@ -117,9 +117,12 @@ if os.path.exists(txt_path) == False:
try:
wav_name, spk_name, language, text = line.split("|")
# todo.append([name,text,"zh"])
if language in language_v1_to_language_v2.keys():
todo.append(
[wav_name, text, language_v1_to_language_v2.get(language, language)]
)
else:
print(f"\033[33m[Waring] The {language = } of {wav_name} is not supported for training.\033[0m")
except:
print(line, traceback.format_exc())

6
GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py
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@ -82,7 +82,7 @@ def name2go(wav_name,wav_path):
tensor_wav16 = tensor_wav16.to(device)
ssl=model.model(tensor_wav16.unsqueeze(0))["last_hidden_state"].transpose(1,2).cpu()#torch.Size([1, 768, 215])
if np.isnan(ssl.detach().numpy()).sum()!= 0:
nan_fails.append(wav_name)
nan_fails.append((wav_name,wav_path))
print("nan filtered:%s"%wav_name)
return
wavfile.write(
@ -113,8 +113,8 @@ for line in lines[int(i_part)::int(all_parts)]:
if(len(nan_fails)>0 and is_half==True):
is_half=False
model=model.float()
for wav_name in nan_fails:
for wav in nan_fails:
try:
name2go(wav_name)
name2go(wav[0],wav[1])
except:
print(wav_name,traceback.format_exc())

2
GPT_SoVITS/text/english.py
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@ -320,7 +320,7 @@ class en_G2p(G2p):
# 尝试分离所有格
if re.match(r"^([a-z]+)('s)$", word):
phones = self.qryword(word[:-2])
phones = self.qryword(word[:-2])[:]
# P T K F TH HH 无声辅音结尾 's 发 ['S']
if phones[-1] in ['P', 'T', 'K', 'F', 'TH', 'HH']:
phones.extend(['S'])

13
api.py
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@ -120,6 +120,11 @@ RESP: 无
import argparse
import os,re
import sys
now_dir = os.getcwd()
sys.path.append(now_dir)
sys.path.append("%s/GPT_SoVITS" % (now_dir))
import signal
import LangSegment
from time import time as ttime
@ -381,7 +386,7 @@ def read_clean_buffer(audio_bytes):
def cut_text(text, punc):
punc_list = [p for p in punc if p in {",", ".", ";", "?", "!", "、", "，", "。", "？", "！", ";", "：", "…"}]
punc_list = [p for p in punc if p in {",", ".", ";", "?", "!", "、", "，", "。", "？", "！", "；", "：", "…"}]
if len(punc_list) > 0:
punds = r"[" + "".join(punc_list) + r"]"
text = text.strip("\n")
@ -536,10 +541,6 @@ def handle(refer_wav_path, prompt_text, prompt_language, text, text_language, cu
# --------------------------------
# 初始化部分
# --------------------------------
now_dir = os.getcwd()
sys.path.append(now_dir)
sys.path.append("%s/GPT_SoVITS" % (now_dir))
dict_language = {
"中文": "all_zh",
"英文": "en",
@ -579,7 +580,7 @@ parser.add_argument("-hp", "--half_precision", action="store_true", default=Fals
# 此时 full_precision==True, half_precision==False
parser.add_argument("-sm", "--stream_mode", type=str, default="close", help="流式返回模式, close / normal / keepalive")
parser.add_argument("-mt", "--media_type", type=str, default="wav", help="音频编码格式, wav / ogg / aac")
parser.add_argument("-cp", "--cut_punc", type=str, default="", help="文本切分符号设定, 符号范围,.;?!、，。？！;：…")
parser.add_argument("-cp", "--cut_punc", type=str, default="", help="文本切分符号设定, 符号范围,.;?!、，。？！；：…")
# 切割常用分句符为 `python ./api.py -cp ".?!。？！"`
parser.add_argument("-hb", "--hubert_path", type=str, default=g_config.cnhubert_path, help="覆盖config.cnhubert_path")
parser.add_argument("-b", "--bert_path", type=str, default=g_config.bert_path, help="覆盖config.bert_path")

2
api_v2.py
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@ -446,7 +446,7 @@ async def set_sovits_weights(weights_path: str = None):
if __name__ == "__main__":
try:
uvicorn.run(APP, host=host, port=port, workers=1)
uvicorn.run(app="api_v2:APP", host=host, port=port, workers=1)
except Exception as e:
traceback.print_exc()
os.kill(os.getpid(), signal.SIGTERM)

4
gpt-sovits_kaggle.ipynb
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@ -54,11 +54,11 @@
"source": [
"# @title Download pretrained models 下载预训练模型\n",
"!mkdir -p /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
"!mkdir -p /kaggle/working/GPT-SoVITS/tools/damo_asr/models\n",
"!mkdir -p /kaggle/working/GPT-SoVITS/tools/asr/models\n",
"!mkdir -p /kaggle/working/GPT-SoVITS/tools/uvr5\n",
"%cd /kaggle/working/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
"!git clone https://huggingface.co/lj1995/GPT-SoVITS\n",
"%cd /kaggle/working/GPT-SoVITS/tools/damo_asr/models\n",
"%cd /kaggle/working/GPT-SoVITS/tools/asr/models\n",
"!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n",
"!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n",
"!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n",

2
tools/my_utils.py
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@ -28,4 +28,4 @@ def load_audio(file, sr):
def clean_path(path_str):
if platform.system() == 'Windows':
path_str = path_str.replace('/', '\\')
return path_str.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
return path_str.strip(" ").strip('"').strip("\n").strip('"').strip(" ").strip("\u202a")

7
webui.py
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@ -418,7 +418,10 @@ def open1a(inp_text,inp_wav_dir,exp_name,gpu_numbers,bert_pretrained_dir):
with open(path_text, "w", encoding="utf8") as f:
f.write("\n".join(opt) + "\n")
ps1a=[]
yield "文本进程结束",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
if len("".join(opt)) > 0:
yield "文本进程成功", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
else:
yield "文本进程失败", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False}
else:
yield "已有正在进行的文本任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
@ -583,7 +586,7 @@ def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numb
os.remove(txt_path)
with open(path_text, "w",encoding="utf8") as f:
f.write("\n".join(opt) + "\n")
assert len("".join(opt)) > 0, "1Aa-文本获取进程失败"
yield "进度：1a-done", {"__type__": "update", "visible": False}, {"__type__": "update", "visible": True}
ps1abc=[]
#############################1b