# Copyright (c) OpenMMLab. All rights reserved. import argparse import subprocess from datetime import date import torch from mmengine.logging import print_log from mmengine.utils import digit_version from mmengine.utils.dl_utils import TORCH_VERSION def parse_args(): parser = argparse.ArgumentParser( description='Process a checkpoint to be published') parser.add_argument('in_file', help='input checkpoint filename') parser.add_argument('out_file', help='output checkpoint filename') parser.add_argument( '--save-keys', nargs='+', type=str, default=['meta', 'state_dict'], help='keys to save in published checkpoint (default: meta state_dict)') args = parser.parse_args() return args def process_checkpoint(in_file, out_file, save_keys=['meta', 'state_dict']): checkpoint = torch.load(in_file, map_location='cpu') # only keep `meta` and `state_dict` for smaller file size ckpt_keys = list(checkpoint.keys()) for k in ckpt_keys: if k not in save_keys: print_log( f'Key `{k}` will be removed because it is not in ' f'save_keys. If you want to keep it, ' f'please set --save-keys.', logger='current') checkpoint.pop(k, None) # if it is necessary to remove some sensitive data in checkpoint['meta'], # add the code here. if digit_version(TORCH_VERSION) >= digit_version('1.8.0'): torch.save(checkpoint, out_file, _use_new_zipfile_serialization=False) else: torch.save(checkpoint, out_file) sha = subprocess.check_output(['sha256sum', out_file]).decode() if out_file.endswith('.pth'): out_file_name = out_file[:-4] else: out_file_name = out_file date_now = date.today().strftime('%Y%m%d') final_file = out_file_name + f'-{sha[:8]}_{date_now}.pth' subprocess.Popen(['mv', out_file, final_file]) def main(): args = parse_args() process_checkpoint(args.in_file, args.out_file, args.save_keys) if __name__ == '__main__': main()