mirror of
https://github.com/saymrwulf/onnxruntime.git
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57 lines
2.5 KiB
Python
57 lines
2.5 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 onnx
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import os
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import pathlib
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import sys
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from .onnx_model_utils import make_dim_param_fixed, make_input_shape_fixed, fix_output_shapes
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def make_dynamic_shape_fixed_helper():
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parser = argparse.ArgumentParser(f'{os.path.basename(__file__)}:{make_dynamic_shape_fixed_helper.__name__}',
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description='''
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Assign a fixed value to a dim_param or input shape
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Provide either dim_param and dim_value or input_name and input_shape.''')
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parser.add_argument('--dim_param', type=str, required=False,
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help="Symbolic parameter name. Provider dim_value if specified.")
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parser.add_argument('--dim_value', type=int, required=False,
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help="Value to replace dim_param with in the model. Must be > 0.")
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parser.add_argument('--input_name', type=str, required=False,
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help="Model input name to replace shape of. Provider input_shape if specified.")
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parser.add_argument('--input_shape', type=lambda x: [int(i) for i in x.split(',')], required=False,
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help="Shape to use for input_shape. Provide comma separated list for the shape. "
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"All values must be > 0. e.g. --input_shape 1,3,256,256")
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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 updated ONNX model to.')
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args = parser.parse_args()
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if (args.dim_param and args.input_name) or \
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(not args.dim_param and not args.input_name) or \
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(args.dim_param and (not args.dim_value or args.dim_value < 1)) or \
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(args.input_name and (not args.input_shape or any([value < 1 for value in args.input_shape]))):
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print('Invalid usage.')
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parser.print_help()
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sys.exit(-1)
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model = onnx.load(str(args.input_model.resolve(strict=True)))
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if args.dim_param:
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make_dim_param_fixed(model.graph, args.dim_param, args.dim_value)
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else:
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make_input_shape_fixed(model.graph, args.input_name, args.input_shape)
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# update the output shapes to make them fixed if possible.
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fix_output_shapes(model)
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onnx.save(model, str(args.output_model.resolve()))
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if __name__ == '__main__':
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make_dynamic_shape_fixed_helper()
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