64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import logging
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import os.path as osp
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from mmdeploy.apis import torch2onnx
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def parse_args():
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parser = argparse.ArgumentParser(description='Export model to ONNX.')
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parser.add_argument('deploy_cfg', help='deploy config path')
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parser.add_argument('model_cfg', help='model config path')
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parser.add_argument('checkpoint', help='model checkpoint path')
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parser.add_argument('img', help='image used to convert model model')
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parser.add_argument('output', help='output onnx path')
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parser.add_argument(
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'--device', help='device used for conversion', default='cpu')
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parser.add_argument(
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'--log-level',
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help='set log level',
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default='INFO',
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choices=list(logging._nameToLevel.keys()))
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args = parser.parse_args()
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return args
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def main():
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args = parse_args()
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logging.basicConfig(
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format='%(asctime)s,%(name)s %(levelname)-8s'
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' [%(filename)s:%(lineno)d] %(message)s',
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datefmt='%Y-%m-%d:%H:%M:%S')
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logger = logging.getLogger()
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logger.setLevel(args.log_level)
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deploy_cfg_path = args.deploy_cfg
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model_cfg_path = args.model_cfg
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checkpoint_path = args.checkpoint
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img = args.img
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output_path = args.output
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work_dir, save_file = osp.split(output_path)
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device = args.device
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logging.info(f'torch2onnx: \n\tmodel_cfg: {model_cfg_path} '
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f'\n\tdeploy_cfg: {deploy_cfg_path}')
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try:
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torch2onnx(
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img,
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work_dir,
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save_file,
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deploy_cfg=deploy_cfg_path,
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model_cfg=model_cfg_path,
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model_checkpoint=checkpoint_path,
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device=device)
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logging.info('torch2onnx success.')
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except Exception as e:
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logging.error(e)
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logging.error('torch2onnx failed.')
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if __name__ == '__main__':
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main()
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