Metadata-Version: 2.1
Name: onnxcustom
Version: 0.4.274
Summary: Extends scikit-learn with a couple of new models, transformers, metrics, plotting.
Home-page: http://www.xavierdupre.fr/app/onnxcustom/helpsphinx/index.html
Author: Xavier Dupré
Author-email: xavier.dupre@gmail.com
License: MIT
Download-URL: https://github.com/sdpython/onnxcustom/
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        onnxcustom: custom ONNX
        =======================
        
        .. image:: https://raw.githubusercontent.com/sdpython/onnxcustom/master/_doc/sphinxdoc/source/phdoc_static/project_ico.png
            :width: 50
        
        `documentation <http://www.xavierdupre.fr/app/onnxcustom/helpsphinx/index.html>`_
        
        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
        <http://onnx.ai/sklearn-onnx/index_tutorial.html>`_.
        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.
        
Keywords: onnxcustom,Xavier Dupré
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Education
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 5 - Production/Stable
Provides-Extra: all
