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GPT-SoVITS-ProPlus
File size: 5,183 Bytes 
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from text import cleaned_text_to_sequence
import os
# if os.environ.get("version","v1")=="v1":
#     from text import chinese
#     from text.symbols import symbols
# else:
#     from text import chinese2 as chinese
#     from text.symbols2 import symbols

from text import symbols as symbols_v1
from text import symbols2 as symbols_v2

special = [
    # ("%", "zh", "SP"),
    ("￥", "zh", "SP2"),
    ("^", "zh", "SP3"),
    # ('@', 'zh', "SP4")#不搞鬼畜了，和第二版保持一致吧
]

def load_nvrtc():
    import torch,sys,os,ctypes
    from pathlib import Path

    if not torch.cuda.is_available():
        print("[INFO] CUDA is not available, skipping nvrtc setup.")
        return

    if sys.platform == "win32":
        torch_lib_dir = Path(torch.__file__).parent / "lib"
        if torch_lib_dir.exists():
            os.add_dll_directory(str(torch_lib_dir))
            print(f"[INFO] Added DLL directory: {torch_lib_dir}")
            matching_files = sorted(torch_lib_dir.glob("nvrtc*.dll"))
            if not matching_files:
                print(f"[ERROR] No nvrtc*.dll found in {torch_lib_dir}")
                return
            for dll_path in matching_files:
                dll_name = os.path.basename(dll_path)
                try:
                    ctypes.CDLL(dll_name)
                    print(f"[INFO] Loaded: {dll_name}")
                except OSError as e:
                    print(f"[WARNING] Failed to load {dll_name}: {e}")
        else:
            print(f"[WARNING] Torch lib directory not found: {torch_lib_dir}")

    elif sys.platform == "linux":
        site_packages = Path(torch.__file__).resolve().parents[1]
        nvrtc_dir = site_packages / "nvidia" / "cuda_nvrtc" / "lib"

        if not nvrtc_dir.exists():
            print(f"[ERROR] nvrtc dir not found: {nvrtc_dir}")
            return

        matching_files = sorted(nvrtc_dir.glob("libnvrtc*.so*"))
        if not matching_files:
            print(f"[ERROR] No libnvrtc*.so* found in {nvrtc_dir}")
            return

        for so_path in matching_files:
            try:
                ctypes.CDLL(so_path, mode=ctypes.RTLD_GLOBAL)  # type: ignore
                print(f"[INFO] Loaded: {so_path}")
            except OSError as e:
                print(f"[WARNING] Failed to load {so_path}: {e}")
load_nvrtc()
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", "ja": "japanese", "en": "english"}
    else:
        symbols = symbols_v2.symbols
        language_module_map = {"zh": "chinese2", "ja": "japanese", "en": "english", "ko": "korean", "yue": "cantonese"}

    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"):
        norm_text = language_module.text_normalize(text)
    else:
        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
        word2ph = None
    else:
        phones = language_module.g2p(norm_text)
        word2ph = None
    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 == "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"}

    """
    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]])
    norm_text = language_module.text_normalize(text)
    phones = language_module.g2p(norm_text)
    new_ph = []
    for ph in phones[0]:
        assert ph in symbols
        if ph == ",":
            new_ph.append(target_symbol)
        else:
            new_ph.append(ph)
    return new_ph, phones[1], norm_text


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, version)


if __name__ == "__main__":
    print(clean_text("你好%啊啊啊额、还是到付红四方。", "zh"))