Description:

onnxcustom 0.4.293

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()
The documentation also introduces onnx, onnxruntime for
inference and training.
The tutorial related to scikit-learn
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,
functions to manipulate onnx graph.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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