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38 lines
1.3 KiB
38 lines
1.3 KiB
#!/usr/bin/env python3
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import argparse
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import onnx
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from onnx import version_converter
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(prog=__doc__)
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parser.add_argument(
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"--model-file", type=str, required=True, help='path/to/the/model.onnx.')
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parser.add_argument(
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"--save-model",
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type=str,
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required=True,
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help='path/to/saved/model.onnx.')
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# Models must be opset10 or higher to be quantized.
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parser.add_argument(
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"--target-opset", type=int, default=11, help='path/to/the/model.onnx.')
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args = parser.parse_args()
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print(f"to opset: {args.target_opset}")
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# Preprocessing: load the model to be converted.
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model_path = args.model_file
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original_model = onnx.load(model_path)
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# print('The model before conversion:\n{}'.format(original_model))
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# A full list of supported adapters can be found here:
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# https://github.com/onnx/onnx/blob/main/onnx/version_converter.py#L21
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# Apply the version conversion on the original model
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converted_model = version_converter.convert_version(original_model,
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args.target_opset)
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# print('The model after conversion:\n{}'.format(converted_model))
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onnx.save(converted_model, args.save_model)
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