mirror of https://github.com/open-mmlab/mmocr.git
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
#!/usr/bin/env python
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# 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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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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args = parser.parse_args()
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return args
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def process_checkpoint(in_file, out_file):
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checkpoint = torch.load(in_file, map_location='cpu')
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# remove optimizer for smaller file size
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if 'optimizer' in checkpoint:
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del checkpoint['optimizer']
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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 'meta' in checkpoint:
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checkpoint['meta'] = {'CLASSES': 0}
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torch.save(checkpoint, out_file, _use_new_zipfile_serialization=False)
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sha = subprocess.check_output(['sha256sum', out_file]).decode()
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final_file = out_file.rstrip('.pth') + '-{}.pth'.format(sha[:8])
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subprocess.Popen(['mv', out_file, final_file])
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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)
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if __name__ == '__main__':
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main()
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