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