Image/run_all_models.py

import os
import subprocess
from pathlib import Path

# 模型列表
models = [
    'AlexNet', 'DenseNet', 'EfficientNet', 'GoogLeNet', 'LeNet5',
    'MobileNetv1', 'MobileNetv2', 'MobileNetv3', 'ResNet', 'SENet',
    'ShuffleNet', 'ShuffleNetv2', 'SwinTransformer', 'VGG', 'ViT', 'ZFNet'
]


def run_training(model_name, train_type, script_dir):
    """运行指定模型的训练"""
    model_code_dir = os.path.join(script_dir, model_name, 'code')
    train_script = os.path.join(model_code_dir, 'train.py')
    dataset_path = os.path.join(script_dir, 'AlexNet', 'dataset')
    
    if not os.path.exists(train_script):
        print(f"警告: {train_script} 不存在，跳过")
        return
    
    # 切换到模型的code目录
    os.chdir(model_code_dir)
    
    cmd = [
        'python', 'train.py',  # 使用相对路径
        '--train-type', train_type,
        '--dataset-path', dataset_path,  # 保持dataset_path为绝对路径
        '--gpu', '1'
    ]
    
    print(f"\n开始训练 {model_name} (train_type={train_type})")
    print(f"工作目录: {os.getcwd()}")
    print(f"执行命令: {' '.join(cmd)}")
    
    try:
        subprocess.run(cmd, check=True)
        print(f"{model_name} (train_type={train_type}) 训练完成")
    except subprocess.CalledProcessError as e:
        print(f"错误: {model_name} (train_type={train_type}) 训练失败")
        print(f"错误信息: {str(e)}")

def main():
    # 获取脚本的绝对路径
    script_dir = os.path.dirname(os.path.abspath(__file__))
    original_dir = os.getcwd()  # 保存原始工作目录
    
    try:     
        # 遍历所有模型和训练类型
        for model in models:
            for train_type in ['0', '1', '2']:
                run_training(model, train_type, script_dir)
    finally:
        # 恢复原始工作目录
        os.chdir(original_dir)

if __name__ == '__main__':
    main()