onnxcustom 0.3.245

onnxcustom: custom ONNX

documentation

Examples, tutorial on how to convert machine learned models into ONNX, implement your own converter or runtime, or even train with ONNX / onnxruntime.

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()

Most of the tutorial has been merged into sklearn-onnx documentation. Among the tools this package implements, you may find:

• a tool to convert NVidia Profilder logs into a dataframe

• a SGD optimizer similar to what scikit-learn implements but based on onnxruntime-training and able to train an CPU and GPU.