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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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35
GPT_SoVITS/text/cleaner.py
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@@ -19,55 +19,57 @@ special = [
def clean_text(text, language, version=None):
if version is None:version=os.environ.get('version', 'v2')
if version is None:
version = os.environ.get("version", "v2")
if version == "v1":
symbols = symbols_v1.symbols
language_module_map = {"zh": "chinese", "ja": "japanese", "en": "english"}
else:
symbols = symbols_v2.symbols
language_module_map = {"zh": "chinese2", "ja": "japanese", "en": "english", "ko": "korean","yue":"cantonese"}
language_module_map = {"zh": "chinese2", "ja": "japanese", "en": "english", "ko": "korean", "yue": "cantonese"}
if(language not in language_module_map):
language="en"
text=" "
if language not in language_module_map:
language = "en"
text = " "
for special_s, special_l, target_symbol in special:
if special_s in text and language == special_l:
return clean_special(text, language, special_s, target_symbol, version)
language_module = __import__("text."+language_module_map[language],fromlist=[language_module_map[language]])
if hasattr(language_module,"text_normalize"):
language_module = __import__("text." + language_module_map[language], fromlist=[language_module_map[language]])
if hasattr(language_module, "text_normalize"):
norm_text = language_module.text_normalize(text)
else:
norm_text=text
if language == "zh" or language=="yue":##########
norm_text = text
if language == "zh" or language == "yue": ##########
phones, word2ph = language_module.g2p(norm_text)
assert len(phones) == sum(word2ph)
assert len(norm_text) == len(word2ph)
elif language == "en":
phones = language_module.g2p(norm_text)
if len(phones) < 4:
phones = [','] + phones
phones = [","] + phones
word2ph = None
else:
phones = language_module.g2p(norm_text)
word2ph = None
phones = ['UNK' if ph not in symbols else ph for ph in phones]
phones = ["UNK" if ph not in symbols else ph for ph in phones]
return phones, word2ph, norm_text
def clean_special(text, language, special_s, target_symbol, version=None):
if version is None:version=os.environ.get('version', 'v2')
if version is None:
version = os.environ.get("version", "v2")
if version == "v1":
symbols = symbols_v1.symbols
language_module_map = {"zh": "chinese", "ja": "japanese", "en": "english"}
else:
symbols = symbols_v2.symbols
language_module_map = {"zh": "chinese2", "ja": "japanese", "en": "english", "ko": "korean","yue":"cantonese"}
language_module_map = {"zh": "chinese2", "ja": "japanese", "en": "english", "ko": "korean", "yue": "cantonese"}
"""
特殊静音段sp符号处理
"""
text = text.replace(special_s, ",")
language_module = __import__("text."+language_module_map[language],fromlist=[language_module_map[language]])
language_module = __import__("text." + language_module_map[language], fromlist=[language_module_map[language]])
norm_text = language_module.text_normalize(text)
phones = language_module.g2p(norm_text)
new_ph = []
@@ -81,8 +83,9 @@ def clean_special(text, language, special_s, target_symbol, version=None):
def text_to_sequence(text, language, version=None):
version = os.environ.get('version',version)
if version is None:version='v2'
version = os.environ.get("version", version)
if version is None:
version = "v2"
phones = clean_text(text)
return cleaned_text_to_sequence(phones, version)