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image:: https://circleci.com/gh/sdpython/onnxcustom/tree/master.svg?style=svg\n    :target: https://circleci.com/gh/sdpython/onnxcustom/tree/master\n\n.. image:: https://travis-ci.com/sdpython/onnxcustom.svg?branch=master\n    :target: https://app.travis-ci.com/github/sdpython/onnxcustom\n    :alt: Build status\n\n.. image:: https://ci.appveyor.com/api/projects/status/a3sn45a2fayoxb5q?svg=true\n    :target: https://ci.appveyor.com/project/sdpython/onnxcustom\n    :alt: Build Status Windows\n\n.. image:: https://codecov.io/gh/sdpython/onnxcustom/branch/master/graph/badge.svg\n    :target: https://codecov.io/gh/sdpython/onnxcustom\n\n.. image:: https://badge.fury.io/py/onnxcustom.svg\n    :target: http://badge.fury.io/py/onnxcustom\n\n.. image:: http://img.shields.io/github/issues/sdpython/onnxcustom.png\n    :alt: GitHub Issues\n    :target: https://github.com/sdpython/onnxcustom/issues\n\n.. image:: https://img.shields.io/badge/license-MIT-blue.svg\n    :alt: MIT License\n    :target: http://opensource.org/licenses/MIT\n\n.. image:: https://pepy.tech/badge/onnxcustom/month\n    :target: https://pepy.tech/project/onnxcustom/month\n    :alt: Downloads\n\n.. image:: https://img.shields.io/github/forks/sdpython/onnxcustom.svg\n    :target: https://github.com/sdpython/onnxcustom/\n    :alt: Forks\n\n.. image:: https://img.shields.io/github/stars/sdpython/onnxcustom.svg\n    :target: https://github.com/sdpython/onnxcustom/\n    :alt: Stars\n\n.. image:: https://img.shields.io/github/repo-size/sdpython/onnxcustom\n    :target: https://github.com/sdpython/onnxcustom/\n    :alt: size\n\nonnxcustom: custom ONNX\n=======================\n\n.. image:: https://raw.githubusercontent.com/sdpython/onnxcustom/master/_doc/sphinxdoc/source/_static/project_ico.png\n    :width: 50\n\n`documentation \u003chttp://www.xavierdupre.fr/app/onnxcustom/helpsphinx/index.html\u003e`_\n\nExamples, tutorial on how to convert machine learned models into ONNX,\nimplement your own converter or runtime, or even train with ONNX / onnxruntime.\n\nThe function *check* or the command line ``python -m onnxcustom check``\nchecks the module is properly installed and returns processing\ntime for a couple of functions or simply:\n\n::\n\n    import onnxcustom\n    onnxcustom.check()\n\nThe documentation also introduces *onnx*, *onnxruntime* for\ninference and training.\nThe tutorial related to *scikit-learn*\nhas been merged into `sklearn-onnx documentation\n\u003chttp://onnx.ai/sklearn-onnx/index_tutorial.html\u003e`_.\nAmong the tools this package implements, you may find:\n\n* a tool to convert NVidia Profilder logs into a dataframe,\n* a SGD optimizer similar to what *scikit-learn* implements but\n  based on *onnxruntime-training* and able to train an CPU and GPU,\n* functions to manipulate *onnx* graph.\n\n**Installation of onnxruntime-training**\n\nonnxruntime-training is only available on Linux. The CPU\ncan be installed with the following instruction.\n\n::\n\n    pip install onnxruntime-training --extra-index-url https://download.onnxruntime.ai/onnxruntime_nightly_cpu.html\n\nVersions using GPU with CUDA or ROCm are available. Check\n`download.onnxruntime.ai \u003chttps://download.onnxruntime.ai/\u003e`_\nto find a specific version.\nYou can use it on Windows\ninside WSL (Windows Linux Subsystem) or compile it for CPU:\n\n::\n\n    python tools\\ci_build\\build.py --skip_tests --build_dir .\\build\\Windows --config Release --build_shared_lib --build_wheel --numpy_version= --cmake_generator=\"Visual Studio 16 2019\" --enable_training --enable_training_ops\n\nGPU versions work better on WSL, see `Build onnxruntime on WSL (Windows Linux Subsystem)\n\u003chttp://www.xavierdupre.fr/app/onnxcustom/helpsphinx/blog/2021/2021-12-16_wsl.html\u003e`_.\n*onnxcustom* can be installed from pypi.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsdpython%2Fonnxcustom","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsdpython%2Fonnxcustom","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsdpython%2Fonnxcustom/lists"}