1
0
Fork 0
TakwayDisplayPlatform/utils/bert_vits2/config.py

263 lines
8.8 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

"""
@Desc: 全局配置文件读取
"""
import argparse
import yaml
from typing import Dict, List
import os
import shutil
import sys
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 Emo_gen_config:
"""emo_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 Train_ms_config:
"""训练配置"""
def __init__(
self,
config_path: str,
env: Dict[str, any],
base: Dict[str, any],
model: 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 = (
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
)
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, models: List[Dict[str, any]], port: int = 5000, device: str = "cuda"
):
self.models: List[Dict[str, any]] = models # 需要加载的所有模型的配置
self.port: int = port # 端口号
self.device: str = device # 模型默认使用设备
@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):
if not os.path.isfile(config_path) and os.path.isfile("default_config.yml"):
shutil.copy(src="default_config.yml", dst=config_path)
print(
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。"
)
print("如无特殊需求请勿修改default_config.yml或备份该文件。")
sys.exit(0)
print(os.getcwd())
with open(file=config_path, mode="r", encoding="utf-8") as file:
yaml_config: Dict[str, any] = yaml.safe_load(file.read())
dataset_path: str = yaml_config["dataset_path"]
openi_token: str = yaml_config["openi_token"]
self.dataset_path: str = dataset_path
self.mirror: str = yaml_config["mirror"]
self.openi_token: str = openi_token
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.emo_gen_config: Emo_gen_config = Emo_gen_config.from_dict(
dataset_path, yaml_config["emo_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"]
)
parser = argparse.ArgumentParser()
# 为避免与以前的config.json起冲突将其更名如下
parser.add_argument("-y", "--yml_config", type=str, default="./utils/bert_vits2/config.yml")
args, _ = parser.parse_known_args()
config = Config(args.yml_config)