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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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38
GPT_SoVITS/prepare_datasets/1-get-text.py
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@@ -8,19 +8,17 @@ exp_name = os.environ.get("exp_name")
i_part = os.environ.get("i_part")
all_parts = os.environ.get("all_parts")
if "_CUDA_VISIBLE_DEVICES" in os.environ:
os.environ["CUDA_VISIBLE_DEVICES"] = os.environ["_CUDA_VISIBLE_DEVICES"]
os.environ["CUDA_VISIBLE_DEVICES"] = os.environ["_CUDA_VISIBLE_DEVICES"]
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
version = os.environ.get("version", None)
import traceback
import os.path
from glob import glob
from tqdm import tqdm
from text.cleaner import clean_text
from transformers import AutoModelForMaskedLM, AutoTokenizer
import numpy as np
from tools.my_utils import clean_path
# inp_text=sys.argv[1]
@@ -36,13 +34,13 @@ from time import time as ttime
import shutil
def my_save(fea,path):#####fix issue: torch.save doesn't support chinese path
dir=os.path.dirname(path)
name=os.path.basename(path)
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/%s%s.pth"%(dir,ttime(),i_part)
tmp_path="%s%s.pth"%(ttime(),i_part)
torch.save(fea,tmp_path)
shutil.move(tmp_path,"%s/%s"%(dir,name))
tmp_path = "%s%s.pth" % (ttime(), i_part)
torch.save(fea, tmp_path)
shutil.move(tmp_path, "%s/%s" % (dir, name))
txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
@@ -56,8 +54,10 @@ if os.path.exists(txt_path) == False:
# device = "mps"
else:
device = "cpu"
if os.path.exists(bert_pretrained_dir):...
else:raise FileNotFoundError(bert_pretrained_dir)
if os.path.exists(bert_pretrained_dir):
...
else:
raise FileNotFoundError(bert_pretrained_dir)
tokenizer = AutoTokenizer.from_pretrained(bert_pretrained_dir)
bert_model = AutoModelForMaskedLM.from_pretrained(bert_pretrained_dir)
if is_half == True:
@@ -86,12 +86,10 @@ if os.path.exists(txt_path) == False:
def process(data, res):
for name, text, lan in data:
try:
name=clean_path(name)
name = clean_path(name)
name = os.path.basename(name)
print(name)
phones, word2ph, norm_text = clean_text(
text.replace("%", "-").replace("￥", ","), lan, version
)
phones, word2ph, norm_text = clean_text(text.replace("%", "-").replace("￥", ","), lan, version)
path_bert = "%s/%s.pt" % (bert_dir, name)
if os.path.exists(path_bert) == False and lan == "zh":
bert_feature = get_bert_feature(norm_text, word2ph)
@@ -131,9 +129,7 @@ if os.path.exists(txt_path) == False:
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)]
)
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: