convert_eo.py

import os
import sys
from dataclasses import is_dataclass
from datasets import load_dataset
from datasets.utils.logging import set_verbosity_info, enable_progress_bar
from omegaconf import OmegaConf

# 开启 datasets 进度条和日志
set_verbosity_info()
enable_progress_bar()

# 添加脚本所在路径到 sys.path
sys.path.append(os.path.join(os.path.dirname(__file__), 'scripts', 'speech_recognition'))

from convert_hf_dataset_to_nemo import HFDatasetConversionConfig, prepare_output_dirs, process_dataset

def convert_eo():
    # 本地数据集路径
    dataset_path = os.path.join(os.path.dirname(__file__), "data", "common_voice_11_0")
    # 输出路径
    output_dir = os.path.join(os.path.dirname(__file__), "data", "nemo_eo")
    
    # 构建配置
    cfg = HFDatasetConversionConfig(
        output_dir=output_dir,
        path=dataset_path,
        name="eo",
        ensure_ascii=False,
        use_auth_token=False,
        num_proc=8,  # 使用多进程加快速度
    )
    
    # 转换为 OmegaConf
    if is_dataclass(cfg):
        cfg = OmegaConf.structured(cfg)
        
    # 准备输出目录
    prepare_output_dirs(cfg)
    
    print(f"开始加载数据集 {cfg.path}，语言: {cfg.name}...")
    print("此过程会进行数据的准备和解压，请耐心等待（可以通过命令行查看进度条）...")
    
    # 加载数据集
    try:
        dataset = load_dataset(
            path=cfg.path,
            name=cfg.name,
            split=cfg.split,
            cache_dir=None,
            streaming=cfg.streaming,
            token=cfg.use_auth_token,
            trust_remote_code=True,
            download_mode="force_redownload",
        )
        print("数据集加载完成！")
    except Exception as e:
        import traceback
        print("Failed to load dataset. Traceback:")
        print(traceback.format_exc())
        sys.exit(1)
        
    print("开始进行格式转换 (HF -> NeMo)...")
    # 处理数据集
    if isinstance(dataset, dict):
        print(f"\nMultiple splits found for dataset {cfg.path}: {list(dataset.keys())}")
        keys = list(dataset.keys())
        for key in keys:
            ds_split = dataset[key]
            print(f"Processing split {key} for dataset {cfg.path}")
            cfg.split_output_dir = os.path.join(cfg.resolved_output_dir, key)
            process_dataset(ds_split, cfg)
            del dataset[key], ds_split
            
        cfg.split_output_dir = None
    else:
        print(f"Single split found for dataset {cfg.path} | Split chosen = {cfg.split}")
        if cfg.split is not None:
            cfg.split_output_dir = os.path.join(cfg.resolved_output_dir, cfg.split)
            
        process_dataset(dataset, cfg)

if __name__ == '__main__':
    convert_eo()