61 lines
1.8 KiB
Python
61 lines
1.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import warnings
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from pathlib import Path
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import torch
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from mmcls.apis import init_model
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bright_style, reset_style = '\x1b[1m', '\x1b[0m'
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red_text, blue_text = '\x1b[31m', '\x1b[34m'
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white_background = '\x1b[107m'
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msg = bright_style + red_text
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msg += 'DeprecationWarning: This tool will be deprecated in future. '
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msg += red_text + 'Welcome to use the '
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msg += white_background
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msg += '"tools/convert_models/reparameterize_model.py"'
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msg += reset_style
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warnings.warn(msg)
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def convert_repvggblock_param(config_path, checkpoint_path, save_path):
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model = init_model(config_path, checkpoint=checkpoint_path)
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print('Converting...')
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model.backbone.switch_to_deploy()
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torch.save(model.state_dict(), save_path)
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print('Done! Save at path "{}"'.format(save_path))
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def main():
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parser = argparse.ArgumentParser(
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description='Convert the parameters of the repvgg block '
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'from training mode to deployment mode.')
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parser.add_argument(
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'config_path',
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help='The path to the configuration file of the network '
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'containing the repvgg block.')
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parser.add_argument(
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'checkpoint_path',
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help='The path to the checkpoint file corresponding to the model.')
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parser.add_argument(
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'save_path',
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help='The path where the converted checkpoint file is stored.')
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args = parser.parse_args()
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save_path = Path(args.save_path)
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if save_path.suffix != '.pth':
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print('The path should contain the name of the pth format file.')
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exit(1)
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save_path.parent.mkdir(parents=True, exist_ok=True)
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convert_repvggblock_param(args.config_path, args.checkpoint_path,
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args.save_path)
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if __name__ == '__main__':
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main()
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