mirror of https://github.com/open-mmlab/mmocr.git
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import subprocess
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import torch
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from mmengine.logging import print_log
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def parse_args():
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parser = argparse.ArgumentParser(
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description='Process a checkpoint to be published')
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parser.add_argument('in_file', help='input checkpoint filename')
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parser.add_argument('out_file', help='output checkpoint filename')
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parser.add_argument(
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'--save-keys',
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nargs='+',
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type=str,
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default=['meta', 'state_dict'],
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help='keys to save in the published checkpoint')
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args = parser.parse_args()
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return args
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def process_checkpoint(in_file, out_file, save_keys=['meta', 'state_dict']):
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checkpoint = torch.load(in_file, map_location='cpu')
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# only keep `meta` and `state_dict` for smaller file size
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ckpt_keys = list(checkpoint.keys())
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for k in ckpt_keys:
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if k not in save_keys:
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print_log(
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f'Key `{k}` will be removed because it is not in '
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f'save_keys. If you want to keep it, '
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f'please set --save-keys.',
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logger='current')
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checkpoint.pop(k, None)
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# if it is necessary to remove some sensitive data in checkpoint['meta'],
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# add the code here.
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if torch.__version__ >= '1.6':
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torch.save(checkpoint, out_file, _use_new_zipfile_serialization=False)
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else:
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torch.save(checkpoint, out_file)
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sha = subprocess.check_output(['sha256sum', out_file]).decode()
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final_file = out_file.rstrip('.pth') + f'-{sha[:8]}.pth'
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subprocess.Popen(['mv', out_file, final_file])
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print_log(
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f'The published model is saved at {final_file}.', logger='current')
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def main():
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args = parse_args()
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process_checkpoint(args.in_file, args.out_file, args.save_keys)
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if __name__ == '__main__':
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main()
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