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| """ | |
| @Desc: 全局配置文件读取 | |
| """ | |
| import os | |
| import shutil | |
| from typing import Dict, List | |
| import torch | |
| import yaml | |
| from common.log import logger | |
| # If not cuda available, set possible devices to cpu | |
| cuda_available = torch.cuda.is_available() | |
| class Resample_config: | |
| """重采样配置""" | |
| def __init__(self, in_dir: str, out_dir: str, sampling_rate: int = 44100): | |
| self.sampling_rate: int = sampling_rate # 目标采样率 | |
| self.in_dir: str = in_dir # 待处理音频目录路径 | |
| self.out_dir: str = out_dir # 重采样输出路径 | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| """从字典中生成实例""" | |
| # 不检查路径是否有效，此逻辑在resample.py中处理 | |
| data["in_dir"] = os.path.join(dataset_path, data["in_dir"]) | |
| data["out_dir"] = os.path.join(dataset_path, data["out_dir"]) | |
| return cls(**data) | |
| class Preprocess_text_config: | |
| """数据预处理配置""" | |
| def __init__( | |
| self, | |
| transcription_path: str, | |
| cleaned_path: str, | |
| train_path: str, | |
| val_path: str, | |
| config_path: str, | |
| val_per_lang: int = 5, | |
| max_val_total: int = 10000, | |
| clean: bool = True, | |
| ): | |
| self.transcription_path: str = ( | |
| transcription_path # 原始文本文件路径，文本格式应为{wav_path}|{speaker_name}|{language}|{text}。 | |
| ) | |
| self.cleaned_path: str = ( | |
| cleaned_path # 数据清洗后文本路径，可以不填。不填则将在原始文本目录生成 | |
| ) | |
| self.train_path: str = ( | |
| train_path # 训练集路径，可以不填。不填则将在原始文本目录生成 | |
| ) | |
| self.val_path: str = ( | |
| val_path # 验证集路径，可以不填。不填则将在原始文本目录生成 | |
| ) | |
| self.config_path: str = config_path # 配置文件路径 | |
| self.val_per_lang: int = val_per_lang # 每个speaker的验证集条数 | |
| self.max_val_total: int = ( | |
| max_val_total # 验证集最大条数，多于的会被截断并放到训练集中 | |
| ) | |
| self.clean: bool = clean # 是否进行数据清洗 | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| """从字典中生成实例""" | |
| data["transcription_path"] = os.path.join( | |
| dataset_path, data["transcription_path"] | |
| ) | |
| if data["cleaned_path"] == "" or data["cleaned_path"] is None: | |
| data["cleaned_path"] = None | |
| else: | |
| data["cleaned_path"] = os.path.join(dataset_path, data["cleaned_path"]) | |
| data["train_path"] = os.path.join(dataset_path, data["train_path"]) | |
| data["val_path"] = os.path.join(dataset_path, data["val_path"]) | |
| data["config_path"] = os.path.join(dataset_path, data["config_path"]) | |
| return cls(**data) | |
| class Bert_gen_config: | |
| """bert_gen 配置""" | |
| def __init__( | |
| self, | |
| config_path: str, | |
| num_processes: int = 2, | |
| device: str = "cuda", | |
| use_multi_device: bool = False, | |
| ): | |
| self.config_path = config_path | |
| self.num_processes = num_processes | |
| if not cuda_available: | |
| device = "cpu" | |
| self.device = device | |
| self.use_multi_device = use_multi_device | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| data["config_path"] = os.path.join(dataset_path, data["config_path"]) | |
| return cls(**data) | |
| class Style_gen_config: | |
| """style_gen 配置""" | |
| def __init__( | |
| self, | |
| config_path: str, | |
| num_processes: int = 4, | |
| device: str = "cuda", | |
| ): | |
| self.config_path = config_path | |
| self.num_processes = num_processes | |
| if not cuda_available: | |
| device = "cpu" | |
| self.device = device | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| data["config_path"] = os.path.join(dataset_path, data["config_path"]) | |
| return cls(**data) | |
| class Train_ms_config: | |
| """训练配置""" | |
| def __init__( | |
| self, | |
| config_path: str, | |
| env: Dict[str, any], | |
| # base: Dict[str, any], | |
| model_dir: str, | |
| num_workers: int, | |
| spec_cache: bool, | |
| keep_ckpts: int, | |
| ): | |
| self.env = env # 需要加载的环境变量 | |
| # self.base = base # 底模配置 | |
| self.model_dir = model_dir # 训练模型存储目录，该路径为相对于dataset_path的路径，而非项目根目录 | |
| self.config_path = config_path # 配置文件路径 | |
| self.num_workers = num_workers # worker数量 | |
| self.spec_cache = spec_cache # 是否启用spec缓存 | |
| self.keep_ckpts = keep_ckpts # ckpt数量 | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| # data["model"] = os.path.join(dataset_path, data["model"]) | |
| data["config_path"] = os.path.join(dataset_path, data["config_path"]) | |
| return cls(**data) | |
| class Webui_config: | |
| """webui 配置 (for webui.py, not supported now)""" | |
| def __init__( | |
| self, | |
| device: str, | |
| model: str, | |
| config_path: str, | |
| language_identification_library: str, | |
| port: int = 7860, | |
| share: bool = False, | |
| debug: bool = False, | |
| ): | |
| if not cuda_available: | |
| device = "cpu" | |
| self.device: str = device | |
| self.model: str = model # 端口号 | |
| self.config_path: str = config_path # 是否公开部署，对外网开放 | |
| self.port: int = port # 是否开启debug模式 | |
| self.share: bool = share # 模型路径 | |
| self.debug: bool = debug # 配置文件路径 | |
| self.language_identification_library: str = ( | |
| language_identification_library # 语种识别库 | |
| ) | |
| def from_dict(cls, dataset_path: str, data: Dict[str, any]): | |
| data["config_path"] = os.path.join(dataset_path, data["config_path"]) | |
| data["model"] = os.path.join(dataset_path, data["model"]) | |
| return cls(**data) | |
| class Server_config: | |
| def __init__( | |
| self, | |
| port: int = 5000, | |
| device: str = "cuda", | |
| limit: int = 100, | |
| language: str = "JP", | |
| origins: List[str] = None, | |
| ): | |
| self.port: int = port | |
| if not cuda_available: | |
| device = "cpu" | |
| self.device: str = device | |
| self.language: str = language | |
| self.limit: int = limit | |
| self.origins: List[str] = origins | |
| def from_dict(cls, data: Dict[str, any]): | |
| return cls(**data) | |
| class Translate_config: | |
| """翻译api配置""" | |
| def __init__(self, app_key: str, secret_key: str): | |
| self.app_key = app_key | |
| self.secret_key = secret_key | |
| def from_dict(cls, data: Dict[str, any]): | |
| return cls(**data) | |
| class Config: | |
| def __init__(self, config_path: str, path_config: dict[str, str]): | |
| if not os.path.isfile(config_path) and os.path.isfile("default_config.yml"): | |
| shutil.copy(src="default_config.yml", dst=config_path) | |
| logger.info( | |
| f"A configuration file {config_path} has been generated based on the default configuration file default_config.yml." | |
| ) | |
| logger.info( | |
| "If you have no special needs, please do not modify default_config.yml." | |
| ) | |
| # sys.exit(0) | |
| with open(file=config_path, mode="r", encoding="utf-8") as file: | |
| yaml_config: Dict[str, any] = yaml.safe_load(file.read()) | |
| model_name: str = yaml_config["model_name"] | |
| self.model_name: str = model_name | |
| if "dataset_path" in yaml_config: | |
| dataset_path = yaml_config["dataset_path"] | |
| else: | |
| dataset_path = os.path.join(path_config["dataset_root"], model_name) | |
| self.dataset_path: str = dataset_path | |
| self.assets_root: str = path_config["assets_root"] | |
| self.out_dir = os.path.join(self.assets_root, model_name) | |
| self.resample_config: Resample_config = Resample_config.from_dict( | |
| dataset_path, yaml_config["resample"] | |
| ) | |
| self.preprocess_text_config: Preprocess_text_config = ( | |
| Preprocess_text_config.from_dict( | |
| dataset_path, yaml_config["preprocess_text"] | |
| ) | |
| ) | |
| self.bert_gen_config: Bert_gen_config = Bert_gen_config.from_dict( | |
| dataset_path, yaml_config["bert_gen"] | |
| ) | |
| self.style_gen_config: Style_gen_config = Style_gen_config.from_dict( | |
| dataset_path, yaml_config["style_gen"] | |
| ) | |
| self.train_ms_config: Train_ms_config = Train_ms_config.from_dict( | |
| dataset_path, yaml_config["train_ms"] | |
| ) | |
| self.webui_config: Webui_config = Webui_config.from_dict( | |
| dataset_path, yaml_config["webui"] | |
| ) | |
| self.server_config: Server_config = Server_config.from_dict( | |
| yaml_config["server"] | |
| ) | |
| # self.translate_config: Translate_config = Translate_config.from_dict( | |
| # yaml_config["translate"] | |
| # ) | |
| with open(os.path.join("configs", "paths.yml"), "r", encoding="utf-8") as f: | |
| path_config: dict[str, str] = yaml.safe_load(f.read()) | |
| # Should contain the following keys: | |
| # - dataset_root: the root directory of the dataset, default to "Data" | |
| # - assets_root: the root directory of the assets, default to "model_assets" | |
| try: | |
| config = Config("config.yml", path_config) | |
| except (TypeError, KeyError): | |
| logger.warning("Old config.yml found. Replace it with default_config.yml.") | |
| shutil.copy(src="default_config.yml", dst="config.yml") | |
| config = Config("config.yml", path_config) | |