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Custom ONNX operators and converters

Project description

https://raw.githubusercontent.com/sdpython/onnxcustom/master/doc/_static/logo.png

documentation

Tutorial on how to convert machine learned models into ONNX, implement your own converter or runtime. The module must be compiled to be used inplace:

python setup.py build_ext --inplace

Generate the setup in subfolder dist:

python setup.py sdist

Generate the documentation in folder dist/html:

python -m sphinx -T -b html doc dist/html

Run the unit tests:

python -m unittest discover tests

Or:

python -m pytest

To check style:

python -m flake8 onnxcustom tests examples

The function check or the command line python -m onnxcustom check checks the module is properly installed and returns processing time for a couple of functions or simply:

import onnxcustom
onnxcustom.check()

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