ORT tools

Userful tools for ONNX models

Installation

Install using pip
From source:

pip3 install git+https://github.com/ninja-96/ort-tools

Getting Started

1. Quantize ONNX mode

python3 -m ort_tools.quant -m <path to onnx model>

2. Speedtest ONNX model

python3 -m ort_tools.speedtest -m <path to onnx model>

Note

• Quantization module quantize model using random input data.
• You must set --shapes argument to run tools:

python3 -m ort_tools.speedtest -m ./model.onnx --shape images:1x3x224x224:fp32

If ONNX model has 2 or more inputs, just enumerate input names separated by commas:

python3 -m ort_tools.speedtest -m ./model.onnx --shape images:1x3x224x224:fp32,gray_images:1x3x224x224:fp32

Built with

• onnx - Open standard for machine learning interoperability
• onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Versioning

All versions available, see the tags on this repository.

Authors

• Oleg Kachalov - Initial work - ninja-96

See also the list of contributors who participated in this project.

License

This project is licensed under the GPL-3.0 license - see the LICENSE.md file for details.