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v1v2 Version Switching (#1391)

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v1v2 Version Switching
This commit is contained in:
XXXXRT666
2024-08-06 12:00:51 +08:00
committed by GitHub
parent 4e34814c70
commit a3f5fb9614
26 changed files with 307 additions and 177 deletions
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4
GPT_SoVITS/AR/data/dataset.py
View File

@@ -15,6 +15,8 @@ from torch.utils.data import DataLoader
from torch.utils.data import Dataset
from transformers import AutoTokenizer
version = os.environ.get('version',None)
from text import cleaned_text_to_sequence
# from config import exp_dir
@@ -149,7 +151,7 @@ class Text2SemanticDataset(Dataset):
phoneme = phoneme.split(" ")
try:
phoneme_ids = cleaned_text_to_sequence(phoneme)
phoneme_ids = cleaned_text_to_sequence(phoneme, version)
except:
traceback.print_exc()
# print(f"{item_name} not in self.phoneme_data !")

149
GPT_SoVITS/inference_webui.py
View File

@@ -18,14 +18,19 @@ import LangSegment, os, re, sys, json
import pdb
import torch
if len(sys.argv)==1:sys.argv.append('v1')
version=os.environ.get("version","v1")
version="v2"if sys.argv[1]=="v2" else version
os.environ['version']=version
language=os.environ.get("language","auto")
language=sys.argv[-1] if len(sys.argv[-1])==5 else language
pretrained_sovits_name="GPT_SoVITS/pretrained_models/s2G488k.pth"if version=="v1"else"GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth"
pretrained_gpt_name="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"if version=="v1"else "GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt"
version=os.environ.get("version","v2")
pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"]
pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"]
_ =[[],[]]
for i in range(2):
if os.path.exists(pretrained_gpt_name[i]):
_[0].append(pretrained_gpt_name[i])
if os.path.exists(pretrained_sovits_name[i]):
_[-1].append(pretrained_sovits_name[i])
pretrained_gpt_name,pretrained_sovits_name = _
if os.path.exists(f"./weight.json"):
pass
@@ -39,7 +44,11 @@ with open(f"./weight.json", 'r', encoding="utf-8") as file:
"gpt_path", weight_data.get('GPT',{}).get(version,pretrained_gpt_name))
sovits_path = os.environ.get(
"sovits_path", weight_data.get('SoVITS',{}).get(version,pretrained_sovits_name))
if isinstance(gpt_path,list):
gpt_path = gpt_path[0]
if isinstance(sovits_path,list):
sovits_path = sovits_path[0]
# gpt_path = os.environ.get(
# "gpt_path", pretrained_gpt_name
# )
@@ -73,8 +82,10 @@ from text.cleaner import clean_text
from time import time as ttime
from module.mel_processing import spectrogram_torch
from tools.my_utils import load_audio
from tools.i18n.i18n import I18nAuto
from tools.i18n.i18n import I18nAuto, scan_language_list
language=os.environ.get("language","auto")
language=sys.argv[-1] if sys.argv[-1] in scan_language_list() else language
if language != 'auto':
i18n = I18nAuto(language=language)
else:
@@ -87,6 +98,29 @@ if torch.cuda.is_available():
else:
device = "cpu"
dict_language_v1 = {
i18n("中文"): "all_zh",#全部按中文识别
i18n("英文"): "en",#全部按英文识别#######不变
i18n("日文"): "all_ja",#全部按日文识别
i18n("中英混合"): "zh",#按中英混合识别####不变
i18n("日英混合"): "ja",#按日英混合识别####不变
i18n("多语种混合"): "auto",#多语种启动切分识别语种
}
dict_language_v2 = {
i18n("中文"): "all_zh",#全部按中文识别
i18n("英文"): "en",#全部按英文识别#######不变
i18n("日文"): "all_ja",#全部按日文识别
i18n("粤语"): "all_yue",#全部按中文识别
i18n("韩文"): "all_ko",#全部按韩文识别
i18n("中英混合"): "zh",#按中英混合识别####不变
i18n("日英混合"): "ja",#按日英混合识别####不变
i18n("粤英混合"): "yue",#按粤英混合识别####不变
i18n("韩英混合"): "ko",#按韩英混合识别####不变
i18n("多语种混合"): "auto",#多语种启动切分识别语种
i18n("多语种混合(粤语)"): "auto_yue",#多语种启动切分识别语种
}
dict_language = dict_language_v1 if version =='v1' else dict_language_v2
tokenizer = AutoTokenizer.from_pretrained(bert_path)
bert_model = AutoModelForMaskedLM.from_pretrained(bert_path)
if is_half == True:
@@ -146,8 +180,8 @@ else:
ssl_model = ssl_model.to(device)
def change_sovits_weights(sovits_path):
global vq_model, hps
def change_sovits_weights(sovits_path,prompt_language=None,text_language=None):
global vq_model, hps, version, dict_language
dict_s2 = torch.load(sovits_path, map_location="cpu")
hps = dict_s2["config"]
hps = DictToAttrRecursive(hps)
@@ -156,6 +190,7 @@ def change_sovits_weights(sovits_path):
hps.model.version = "v1"
else:
hps.model.version = "v2"
version = hps.model.version
# print("sovits版本:",hps.model.version)
vq_model = SynthesizerTrn(
hps.data.filter_length // 2 + 1,
@@ -171,11 +206,25 @@ def change_sovits_weights(sovits_path):
vq_model = vq_model.to(device)
vq_model.eval()
print(vq_model.load_state_dict(dict_s2["weight"], strict=False))
dict_language = dict_language_v1 if version =='v1' else dict_language_v2
with open("./weight.json")as f:
data=f.read()
data=json.loads(data)
data["SoVITS"][version]=sovits_path
data=f.read()
data=json.loads(data)
data["SoVITS"][version]=sovits_path
with open("./weight.json","w")as f:f.write(json.dumps(data))
if prompt_language is not None and text_language is not None:
if prompt_language in list(dict_language.keys()):
prompt_text_update, prompt_language_update = {'__type__':'update'}, {'__type__':'update', 'value':prompt_language}
else:
prompt_text_update = {'__type__':'update', 'value':''}
prompt_language_update = {'__type__':'update', 'value':i18n("中文")}
if text_language in list(dict_language.keys()):
text_update, text_language_update = {'__type__':'update'}, {'__type__':'update', 'value':text_language}
else:
text_update = {'__type__':'update', 'value':''}
text_language_update = {'__type__':'update', 'value':i18n("中文")}
return {'__type__':'update', 'choices':list(dict_language.keys())}, {'__type__':'update', 'choices':list(dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update
change_sovits_weights(sovits_path)
@@ -196,9 +245,9 @@ def change_gpt_weights(gpt_path):
total = sum([param.nelement() for param in t2s_model.parameters()])
print("Number of parameter: %.2fM" % (total / 1e6))
with open("./weight.json")as f:
data=f.read()
data=json.loads(data)
data["GPT"][version]=gpt_path
data=f.read()
data=json.loads(data)
data["GPT"][version]=gpt_path
with open("./weight.json","w")as f:f.write(json.dumps(data))
@@ -220,22 +269,6 @@ def get_spepc(hps, filename):
)
return spec
dict_language = {
i18n("中文"): "all_zh",#全部按中文识别
i18n("粤语"): "all_yue",#全部按中文识别
i18n("英文"): "en",#全部按英文识别#######不变
i18n("日文"): "all_ja",#全部按日文识别
i18n("韩文"): "all_ko",#全部按韩文识别
i18n("中英混合"): "zh",#按中英混合识别####不变
i18n("粤英混合"): "yue",#按粤英混合识别####不变
i18n("日英混合"): "ja",#按日英混合识别####不变
i18n("韩英混合"): "ko",#按韩英混合识别####不变
i18n("多语种混合"): "auto",#多语种启动切分识别语种
i18n("多语种混合(粤语)"): "auto_yue",#多语种启动切分识别语种
}
def clean_text_inf(text, language, version):
phones, word2ph, norm_text = clean_text(text, language, version)
phones = cleaned_text_to_sequence(phones, version)
@@ -363,7 +396,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
prompt_language = dict_language[prompt_language]
text_language = dict_language[text_language]
version = vq_model.version
if not ref_free:
prompt_text = prompt_text.strip("\n")
@@ -599,29 +631,29 @@ def process_text(texts):
def change_choices():
SoVITS_names, GPT_names = get_weights_names()
SoVITS_names, GPT_names = get_weights_names(GPT_weight_root, SoVITS_weight_root)
return {"choices": sorted(SoVITS_names, key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}
SoVITS_weight_root="SoVITS_weights_v2" if version=='v2' else "SoVITS_weights"
GPT_weight_root="GPT_weights_v2" if version=='v2' else "GPT_weights"
os.makedirs("SoVITS_weights",exist_ok=True)
os.makedirs("GPT_weights",exist_ok=True)
os.makedirs("SoVITS_weights_v2",exist_ok=True)
os.makedirs("GPT_weights_v2",exist_ok=True)
SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"]
GPT_weight_root=["GPT_weights_v2","GPT_weights"]
for path in SoVITS_weight_root+GPT_weight_root:
os.makedirs(path,exist_ok=True)
def get_weights_names():
SoVITS_names = [pretrained_sovits_name]
for name in os.listdir(SoVITS_weight_root):
if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (SoVITS_weight_root, name))
GPT_names = [pretrained_gpt_name]
for name in os.listdir(GPT_weight_root):
if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (GPT_weight_root, name))
def get_weights_names(GPT_weight_root, SoVITS_weight_root):
SoVITS_names = [i for i in pretrained_sovits_name]
for path in SoVITS_weight_root:
for name in os.listdir(path):
if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (path, name))
GPT_names = [i for i in pretrained_gpt_name]
for path in GPT_weight_root:
for name in os.listdir(path):
if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (path, name))
return SoVITS_names, GPT_names
SoVITS_names, GPT_names = get_weights_names()
SoVITS_names, GPT_names = get_weights_names(GPT_weight_root, SoVITS_weight_root)
def html_center(text, label='p'):
return f"""<div style="text-align: center; margin: 100; padding: 50;">
@@ -633,6 +665,7 @@ def html_left(text, label='p'):
<{label} style="margin: 0; padding: 0;">{text}</{label}>
</div>"""
with gr.Blocks(title="GPT-SoVITS WebUI") as app:
gr.Markdown(
value=i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>.")
@@ -640,21 +673,19 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
with gr.Group():
gr.Markdown(html_center(i18n("模型切换"),'h3'))
with gr.Row():
GPT_dropdown = gr.Dropdown(label=i18n("GPT模型列表"), choices=sorted(GPT_names, key=custom_sort_key), value=gpt_path, interactive=True,scale=13)
SoVITS_dropdown = gr.Dropdown(label=i18n("SoVITS模型列表"), choices=sorted(SoVITS_names, key=custom_sort_key), value=sovits_path, interactive=True,scale=13)
refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary",scale=13)
GPT_dropdown = gr.Dropdown(label=i18n("GPT模型列表"), choices=sorted(GPT_names, key=custom_sort_key), value=gpt_path, interactive=True, scale=14)
SoVITS_dropdown = gr.Dropdown(label=i18n("SoVITS模型列表"), choices=sorted(SoVITS_names, key=custom_sort_key), value=sovits_path, interactive=True, scale=14)
refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary", scale=14)
refresh_button.click(fn=change_choices, inputs=[], outputs=[SoVITS_dropdown, GPT_dropdown])
SoVITS_dropdown.change(change_sovits_weights, [SoVITS_dropdown], [])
GPT_dropdown.change(change_gpt_weights, [GPT_dropdown], [])
gr.Markdown(html_center(i18n("*请上传并填写参考信息"),'h3'))
with gr.Row():
inp_ref = gr.Audio(label=i18n("请上传3~10秒内参考音频，超过会报错！"), type="filepath",scale=13)
inp_ref = gr.Audio(label=i18n("请上传3~10秒内参考音频，超过会报错！"), type="filepath", scale=13)
with gr.Column(scale=13):
ref_text_free = gr.Checkbox(label=i18n("开启无参考文本模式。不填参考文本亦相当于开启。"), value=False, interactive=True, show_label=True)
gr.Markdown(html_left(i18n("使用无参考文本模式时建议使用微调的GPT，听不清参考音频说的啥(不晓得写啥)可以开。<br>开启后无视填写的参考文本。")))
prompt_text = gr.Textbox(label=i18n("参考音频的文本"), value="", lines=3, max_lines=3)
prompt_language = gr.Dropdown(
label=i18n("参考音频的语种"), choices=list(dict_language.keys()), value=i18n("中文"),scale=14
label=i18n("参考音频的语种"), choices=list(dict_language.keys()), value=i18n("中文"), scale=14
)
gr.Markdown(html_center(i18n("*请填写需要合成的目标文本和语种模式"),'h3'))
with gr.Row():
@@ -683,13 +714,15 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
# get_phoneme_button = gr.Button(i18n("目标文本转音素"), variant="primary")
with gr.Row():
inference_button = gr.Button(i18n("合成语音"), variant="primary", size='lg', scale=25)
output = gr.Audio(label=i18n("输出的语音"),scale=14)
output = gr.Audio(label=i18n("输出的语音"), scale=14)
inference_button.click(
get_tts_wav,
[inp_ref, prompt_text, prompt_language, text, text_language, how_to_cut, top_k, top_p, temperature, ref_text_free,speed,if_freeze],
[output],
)
SoVITS_dropdown.change(change_sovits_weights, [SoVITS_dropdown,prompt_language,text_language], [prompt_language,text_language,prompt_text,prompt_language,text,text_language])
GPT_dropdown.change(change_gpt_weights, [GPT_dropdown], [])
# gr.Markdown(value=i18n("文本切分工具。太长的文本合成出来效果不一定好，所以太长建议先切。合成会根据文本的换行分开合成再拼起来。"))
# with gr.Row():

4
GPT_SoVITS/module/data_utils.py
View File

@@ -18,7 +18,7 @@ import requests
from scipy.io import wavfile
from io import BytesIO
from tools.my_utils import load_audio
version = os.environ.get('version',None)
# ZeroDivisionError fixed by Tybost (https://github.com/RVC-Boss/GPT-SoVITS/issues/79)
class TextAudioSpeakerLoader(torch.utils.data.Dataset):
"""
@@ -77,7 +77,7 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
try:
phoneme = self.phoneme_data[audiopath][0]
phoneme = phoneme.split(' ')
phoneme_ids = cleaned_text_to_sequence(phoneme)
phoneme_ids = cleaned_text_to_sequence(phoneme, version)
except Exception:
print(f"{audiopath} not in self.phoneme_data !")
skipped_phone += 1

3
GPT_SoVITS/prepare_datasets/1-get-text.py
View File

@@ -12,6 +12,7 @@ opt_dir = os.environ.get("opt_dir")
bert_pretrained_dir = os.environ.get("bert_pretrained_dir")
import torch
is_half = eval(os.environ.get("is_half", "True")) and torch.cuda.is_available()
version = os.environ.get('version', None)
import sys, numpy as np, traceback, pdb
import os.path
from glob import glob
@@ -84,7 +85,7 @@ if os.path.exists(txt_path) == False:
name = os.path.basename(name)
print(name)
phones, word2ph, norm_text = clean_text(
text.replace("%", "-").replace("￥", ","), lan
text.replace("%", "-").replace("￥", ","), lan, version
)
path_bert = "%s/%s.pt" % (bert_dir, name)
if os.path.exists(path_bert) == False and lan == "zh":

2
GPT_SoVITS/prepare_datasets/3-get-semantic.py
View File

@@ -8,6 +8,7 @@ os.environ["CUDA_VISIBLE_DEVICES"] = os.environ.get("_CUDA_VISIBLE_DEVICES")
opt_dir = os.environ.get("opt_dir")
pretrained_s2G = os.environ.get("pretrained_s2G")
s2config_path = os.environ.get("s2config_path")
version=os.environ.get("version","v2")
import torch
is_half = eval(os.environ.get("is_half", "True")) and torch.cuda.is_available()
import math, traceback
@@ -50,6 +51,7 @@ if os.path.exists(semantic_path) == False:
hps.data.filter_length // 2 + 1,
hps.train.segment_size // hps.data.hop_length,
n_speakers=hps.data.n_speakers,
version=version,
**hps.model
)
if is_half == True:

3
GPT_SoVITS/text/.gitignore vendored
View File

@@ -1,2 +1,3 @@
G2PWModel
__pycache__
__pycache__
*.zip

3
GPT_SoVITS/text/__init__.py
View File

@@ -10,13 +10,14 @@ from text import symbols2 as symbols_v2
_symbol_to_id_v1 = {s: i for i, s in enumerate(symbols_v1.symbols)}
_symbol_to_id_v2 = {s: i for i, s in enumerate(symbols_v2.symbols)}
def cleaned_text_to_sequence(cleaned_text, version):
def cleaned_text_to_sequence(cleaned_text, version=None):
'''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
Args:
text: string to convert to a sequence
Returns:
List of integers corresponding to the symbols in the text
'''
if version is None:version=os.environ.get('version', 'v2')
if version == "v1":
phones = [_symbol_to_id_v1[symbol] for symbol in cleaned_text]
else:

12
GPT_SoVITS/text/cleaner.py
View File

@@ -20,7 +20,8 @@ special = [
]
def clean_text(text, language, version):
def clean_text(text, language, version=None):
if version is None:version=os.environ.get('version', 'v2')
if version == "v1":
symbols = symbols_v1.symbols
language_module_map = {"zh": chinese_v1, "ja": japanese, "en": english}
@@ -57,7 +58,8 @@ def clean_text(text, language, version):
return phones, word2ph, norm_text
def clean_special(text, language, special_s, target_symbol, version):
def clean_special(text, language, special_s, target_symbol, version=None):
if version is None:version=os.environ.get('version', 'v2')
if version == "v1":
symbols = symbols_v1.symbols
language_module_map = {"zh": chinese_v1, "ja": japanese, "en": english}
@@ -82,9 +84,11 @@ def clean_special(text, language, special_s, target_symbol, version):
return new_ph, phones[1], norm_text
def text_to_sequence(text, language):
def text_to_sequence(text, language, version=None):
version = os.environ.get('version',version)
if version is None:version='v2'
phones = clean_text(text)
return cleaned_text_to_sequence(phones)
return cleaned_text_to_sequence(phones, version)
if __name__ == "__main__":