mirror of
https://github.com/saymrwulf/onnxruntime.git
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46 lines
1.9 KiB
Python
46 lines
1.9 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import argparse
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import os
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import pathlib
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from .onnx_model_utils import get_optimization_level, optimize_model
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def optimize_model_helper():
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parser = argparse.ArgumentParser(f'{os.path.basename(__file__)}:{optimize_model_helper.__name__}',
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description='''
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Optimize an ONNX model using ONNX Runtime to the specified level.
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See https://onnxruntime.ai/docs/performance/graph-optimizations.html for more
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details of the optimization levels.'''
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)
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parser.add_argument('--opt_level', default='basic',
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choices=['disable', 'basic', 'extended', 'all'],
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help="Optimization level to use.")
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parser.add_argument('--log_level', choices=['debug', 'info', 'warning', 'error'], type=str, required=False,
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default='error',
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help="Log level. Defaults to Error so we don't get output about unused initializers "
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"being removed. Warning or Info may be desirable in some scenarios.")
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parser.add_argument('input_model', type=pathlib.Path, help='Provide path to ONNX model to update.')
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parser.add_argument('output_model', type=pathlib.Path, help='Provide path to write optimized ONNX model to.')
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args = parser.parse_args()
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if args.log_level == 'error':
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log_level = 3
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elif args.log_level == 'debug':
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log_level = 0 # ORT verbose level
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elif args.log_level == 'info':
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log_level = 1
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elif args.log_level == 'warning':
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log_level = 2
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optimize_model(args.input_model, args.output_model, get_optimization_level(args.opt_level), log_level)
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if __name__ == '__main__':
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optimize_model_helper()
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