bert-vits2-utils
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"""
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@Desc: 全局配置文件读取
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"""
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import argparse
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import yaml
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from typing import Dict, List
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import os
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import shutil
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import sys
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class Resample_config:
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"""重采样配置"""
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def __init__(self, in_dir: str, out_dir: str, sampling_rate: int = 44100):
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self.sampling_rate: int = sampling_rate # 目标采样率
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self.in_dir: str = in_dir # 待处理音频目录路径
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self.out_dir: str = out_dir # 重采样输出路径
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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"""从字典中生成实例"""
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# 不检查路径是否有效，此逻辑在resample.py中处理
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data["in_dir"] = os.path.join(dataset_path, data["in_dir"])
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data["out_dir"] = os.path.join(dataset_path, data["out_dir"])
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return cls(**data)
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class Preprocess_text_config:
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"""数据预处理配置"""
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def __init__(
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self,
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transcription_path: str,
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cleaned_path: str,
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train_path: str,
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val_path: str,
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config_path: str,
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val_per_lang: int = 5,
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max_val_total: int = 10000,
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clean: bool = True,
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):
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self.transcription_path: str = (
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transcription_path # 原始文本文件路径，文本格式应为{wav_path}|{speaker_name}|{language}|{text}。
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)
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self.cleaned_path: str = (
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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
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)
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self.train_path: str = (
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train_path # 训练集路径，可以不填。不填则将在原始文本目录生成
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)
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self.val_path: str = (
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val_path # 验证集路径，可以不填。不填则将在原始文本目录生成
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)
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self.config_path: str = config_path # 配置文件路径
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self.val_per_lang: int = val_per_lang # 每个speaker的验证集条数
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self.max_val_total: int = (
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max_val_total # 验证集最大条数，多于的会被截断并放到训练集中
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)
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self.clean: bool = clean # 是否进行数据清洗
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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"""从字典中生成实例"""
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data["transcription_path"] = os.path.join(
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dataset_path, data["transcription_path"]
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)
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if data["cleaned_path"] == "" or data["cleaned_path"] is None:
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data["cleaned_path"] = None
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else:
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data["cleaned_path"] = os.path.join(dataset_path, data["cleaned_path"])
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data["train_path"] = os.path.join(dataset_path, data["train_path"])
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data["val_path"] = os.path.join(dataset_path, data["val_path"])
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data["config_path"] = os.path.join(dataset_path, data["config_path"])
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return cls(**data)
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class Bert_gen_config:
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"""bert_gen 配置"""
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def __init__(
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self,
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config_path: str,
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num_processes: int = 2,
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device: str = "cuda",
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use_multi_device: bool = False,
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):
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self.config_path = config_path
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self.num_processes = num_processes
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self.device = device
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self.use_multi_device = use_multi_device
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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data["config_path"] = os.path.join(dataset_path, data["config_path"])
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return cls(**data)
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class Emo_gen_config:
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"""emo_gen 配置"""
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def __init__(
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self,
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config_path: str,
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num_processes: int = 2,
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device: str = "cuda",
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use_multi_device: bool = False,
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):
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self.config_path = config_path
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self.num_processes = num_processes
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self.device = device
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self.use_multi_device = use_multi_device
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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data["config_path"] = os.path.join(dataset_path, data["config_path"])
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return cls(**data)
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class Train_ms_config:
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"""训练配置"""
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def __init__(
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self,
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config_path: str,
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env: Dict[str, any],
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base: Dict[str, any],
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model: str,
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num_workers: int,
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spec_cache: bool,
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keep_ckpts: int,
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):
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self.env = env # 需要加载的环境变量
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self.base = base # 底模配置
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self.model = (
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model # 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
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)
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self.config_path = config_path # 配置文件路径
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self.num_workers = num_workers # worker数量
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self.spec_cache = spec_cache # 是否启用spec缓存
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self.keep_ckpts = keep_ckpts # ckpt数量
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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# data["model"] = os.path.join(dataset_path, data["model"])
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data["config_path"] = os.path.join(dataset_path, data["config_path"])
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return cls(**data)
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class Webui_config:
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"""webui 配置"""
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def __init__(
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self,
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device: str,
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model: str,
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config_path: str,
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language_identification_library: str,
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port: int = 7860,
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share: bool = False,
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debug: bool = False,
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):
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self.device: str = device
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self.model: str = model # 端口号
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self.config_path: str = config_path # 是否公开部署，对外网开放
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self.port: int = port # 是否开启debug模式
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self.share: bool = share # 模型路径
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self.debug: bool = debug # 配置文件路径
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self.language_identification_library: str = (
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language_identification_library # 语种识别库
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)
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@classmethod
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def from_dict(cls, dataset_path: str, data: Dict[str, any]):
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data["config_path"] = os.path.join(dataset_path, data["config_path"])
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data["model"] = os.path.join(dataset_path, data["model"])
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return cls(**data)
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class Server_config:
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def __init__(
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self, models: List[Dict[str, any]], port: int = 5000, device: str = "cuda"
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):
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self.models: List[Dict[str, any]] = models # 需要加载的所有模型的配置
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self.port: int = port # 端口号
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self.device: str = device # 模型默认使用设备
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@classmethod
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def from_dict(cls, data: Dict[str, any]):
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return cls(**data)
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class Translate_config:
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"""翻译api配置"""
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def __init__(self, app_key: str, secret_key: str):
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self.app_key = app_key
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self.secret_key = secret_key
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@classmethod
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def from_dict(cls, data: Dict[str, any]):
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return cls(**data)
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class Config:
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def __init__(self, config_path: str):
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if not os.path.isfile(config_path) and os.path.isfile("default_config.yml"):
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shutil.copy(src="default_config.yml", dst=config_path)
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print(
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f"已根据默认配置文件default_config.yml生成配置文件{config_path}。请按该配置文件的说明进行配置后重新运行。"
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)
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print("如无特殊需求，请勿修改default_config.yml或备份该文件。")
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sys.exit(0)
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print(os.getcwd())
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with open(file=config_path, mode="r", encoding="utf-8") as file:
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yaml_config: Dict[str, any] = yaml.safe_load(file.read())
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dataset_path: str = yaml_config["dataset_path"]
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openi_token: str = yaml_config["openi_token"]
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self.dataset_path: str = dataset_path
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self.mirror: str = yaml_config["mirror"]
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self.openi_token: str = openi_token
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self.resample_config: Resample_config = Resample_config.from_dict(
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dataset_path, yaml_config["resample"]
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)
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self.preprocess_text_config: Preprocess_text_config = (
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Preprocess_text_config.from_dict(
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dataset_path, yaml_config["preprocess_text"]
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)
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)
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self.bert_gen_config: Bert_gen_config = Bert_gen_config.from_dict(
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dataset_path, yaml_config["bert_gen"]
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)
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self.emo_gen_config: Emo_gen_config = Emo_gen_config.from_dict(
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dataset_path, yaml_config["emo_gen"]
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)
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self.train_ms_config: Train_ms_config = Train_ms_config.from_dict(
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dataset_path, yaml_config["train_ms"]
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)
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self.webui_config: Webui_config = Webui_config.from_dict(
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dataset_path, yaml_config["webui"]
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)
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self.server_config: Server_config = Server_config.from_dict(
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yaml_config["server"]
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)
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self.translate_config: Translate_config = Translate_config.from_dict(
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yaml_config["translate"]
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)
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parser = argparse.ArgumentParser()
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# 为避免与以前的config.json起冲突，将其更名如下
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parser.add_argument("-y", "--yml_config", type=str, default="./utils/bert_vits2/config.yml")
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args, _ = parser.parse_known_args()
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config = Config(args.yml_config)
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