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"""
@Desc: 全局配置文件读取
"""
import argparse
import os
import shutil
from typing import Dict, List
import yaml
from common.log import logger
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
@classmethod
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
@classmethod
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
self.device = device
self.use_multi_device = use_multi_device
@classmethod
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
self.device = device
@classmethod
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
@classmethod
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"""
def __init__(
self,
device: str,
model: str,
config_path: str,
language_identification_library: str,
port: int = 7860,
share: bool = False,
debug: bool = False,
):
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
)
@classmethod
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
self.device: str = device
self.language: str = language
self.limit: int = limit
self.origins: List[str] = origins
@classmethod
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
@classmethod
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)
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