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#!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
from __future__ import annotations
import argparse
import os
import pathlib
import sys
import onnx
from .onnx_model_utils import fix_output_shapes, make_dim_param_fixed, make_input_shape_fixed
def make_dynamic_shape_fixed_helper():
parser = argparse.ArgumentParser(
f"{os.path.basename(__file__)}:{make_dynamic_shape_fixed_helper.__name__}",
description="""
Assign a fixed value to a dim_param or input shape
Provide either dim_param and dim_value or input_name and input_shape.""",
)
parser.add_argument(
"--dim_param", type=str, required=False, help="Symbolic parameter name. Provide dim_value if specified."
)
parser.add_argument(
"--dim_value", type=int, required=False, help="Value to replace dim_param with in the model. Must be > 0."
)
parser.add_argument(
"--input_name",
type=str,
required=False,
help="Model input name to replace shape of. Provide input_shape if specified.",
)
parser.add_argument(
"--input_shape",
type=lambda x: [int(i) for i in x.split(",")],
required=False,
help="Shape to use for input_shape. Provide comma separated list for the shape. "
"All values must be > 0. e.g. --input_shape 1,3,256,256",
)
parser.add_argument("input_model", type=pathlib.Path, help="Provide path to ONNX model to update.")
parser.add_argument("output_model", type=pathlib.Path, help="Provide path to write updated ONNX model to.")
args = parser.parse_args()
if (
(args.dim_param and args.input_name)
or (not args.dim_param and not args.input_name)
or (args.dim_param and (not args.dim_value or args.dim_value < 1))
or (args.input_name and (not args.input_shape or any(value < 1 for value in args.input_shape)))
):
print("Invalid usage.")
parser.print_help()
sys.exit(-1)
model = onnx.load(str(args.input_model.resolve(strict=True)))
if args.dim_param:
make_dim_param_fixed(model.graph, args.dim_param, args.dim_value)
else:
make_input_shape_fixed(model.graph, args.input_name, args.input_shape)
# update the output shapes to make them fixed if possible.
fix_output_shapes(model)
onnx.save(model, str(args.output_model.resolve()))
if __name__ == "__main__":
make_dynamic_shape_fixed_helper()
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