View source for Open Neural Network Exchange

{{Short description|Open-source artificial intelligence ecosystem}}
{{Infobox software
| name                   = Open Neural Network Exchange (ONNX)
| logo                   = Open Neural Network Exchange logo.svg
| author                 = [[Facebook]], [[Microsoft]]
| developer              = [[Linux Foundation]]
| released               = {{Start date and age|2017|09}}
| latest release version = {{Wikidata|property|reference|P348}}
| latest release date    = {{Start date and age|{{wikidata|qualifier|P348|P577}}}}
| programming language   = [[C++]], [[Python (programming language)|Python]]
| operating system       = [[Microsoft Windows|Windows]], [[Linux]]
| platform               =
| genre                  = [[Artificial intelligence]] ecosystem
| license                = initially [[MIT License]];<br />later changed to [[Apache License 2.0]]
| website                =
}}
The '''Open Neural Network Exchange''' ('''ONNX''') [{{IPA|ˈɒnɪks}}]<ref name="Official Twitter account">{{Cite tweet |user=onnxai |number=973566899584950272 |title=Hi Hu, it's not spelled the same, but pronounced the same as Onyx.}}</ref>  is an [[Open-source software|open-source]] [[artificial intelligence]] ecosystem<ref name=":02">{{Cite news|url=https://www.engadget.com/2017/10/11/microsoft-facebooks-ai-onxx-partners/|title=Microsoft and Facebook's open AI ecosystem gains more support|work=Engadget|access-date=2017-10-11|language=en-US}}</ref> of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector. ONNX is available on [[GitHub]].

== History ==
ONNX was originally named Toffee<ref>{{Cite web|title=Codemod Toffee -> ONNX, toffee -> onnx. Change file names to match · pytorch/pytorch@6d8d5ba|url=https://github.com/pytorch/pytorch/commit/6d8d5bab4c3651a47a06d56c7ed6d64bbb1b753d|access-date=2021-10-12|website=GitHub|language=en}}</ref> and was developed by the [[PyTorch]] team at [[Facebook]].<ref>{{Cite web|title=A model exporter for PyTorch by ezyang · Pull Request #2565 · pytorch/pytorch|url=https://github.com/pytorch/pytorch/pull/2565|access-date=2021-10-12|website=GitHub|language=en}}</ref> In September 2017 it was renamed to ONNX and announced by Facebook and [[Microsoft]].<ref name=":0" /> Later, [[IBM]], [[Huawei]], [[Intel]], [[Advanced Micro Devices|AMD]], [[Arm Holdings|Arm]] and [[Qualcomm]] announced support for the initiative.<ref name=":02" />

In October 2017, Microsoft announced that it would add its [[Microsoft Cognitive Toolkit|Cognitive Toolkit]] and [[Project Brainwave]] platform to the initiative.<ref name=":02" />

In November 2019 ONNX was accepted as graduate project in Linux Foundation AI.<ref>{{cite web |title=LF AI & Data Day – ONNX Community Meetup – Silicon Valley |url=https://community.linuxfoundation.org/events/details/lfhq-lf-ai-data-foundation-presents-lf-ai-data-day-onnx-community-meetup-silicon-valley/ |website=LF Online Community |language=en}}</ref>

In October 2020 Zetane Systems became a member of the ONNX ecosystem.<ref>{{Cite web|url=https://medium.com/zetane-blog/zetane-systems-joins-the-onnx-community-to-accelerate-open-source-innovation-and-universal-2bd9ff84d96f|title = Zetane Systems Joins the ONNX Community to Accelerate Open-Source Innovation and Universal…|date = 14 October 2020}}</ref>

== Intent ==
The initiative targets:

=== Framework interoperability ===
Allow developers to more easily move between frameworks, some of which may be more desirable for specific phases of the development process, such as fast training, network architecture flexibility or inferencing on mobile devices.<ref name=":0">{{Cite news|url=https://www.microsoft.com/en-us/cognitive-toolkit/blog/2017/09/microsoft-facebook-create-open-ecosystem-ai-model-interoperability/|title=Microsoft and Facebook create open ecosystem for AI model interoperability – Microsoft Cognitive Toolkit|date=2017-09-07|work=Microsoft Cognitive Toolkit|access-date=2017-10-11|language=en-US}}</ref>

=== Shared optimization ===
Allow hardware vendors and others to improve the performance of [[artificial neural network]]s of multiple frameworks at once by targeting the ONNX representation.<ref name=":0" />

== Contents ==
ONNX provides definitions of an extensible computation graph model, built-in operators and standard [[data type]]s, focused on inferencing (evaluation).<ref name=":0" />

Each computation [[dataflow]] graph is a list of nodes that form an [[Forest (graph theory)|acyclic graph]]. Nodes have inputs and outputs. Each node is a call to an operator. Metadata documents the graph. Built-in operators are to be available on each ONNX-supporting framework.<ref name=":0" />

== See also ==
{{Portal|Free and open-source software}}
* [[Neural Network Exchange Format]]
* [[Comparison of deep learning software]]
* [[Predictive Model Markup Language]]—an XML-based predictive model interchange format
* PicklingTools—an open-source collection of tools for allowing C++ and Python systems to share information quickly and easily.

== References ==
{{Reflist}}

== External links ==
* {{Cite news|url=https://www.microsoft.com/en-us/cognitive-toolkit/blog/2017/09/microsoft-facebook-create-open-ecosystem-ai-model-interoperability/|title=Microsoft and Facebook create open ecosystem for AI model interoperability – Microsoft Cognitive Toolkit|last=Boyd|first=Eric|date=2017-09-07|work=Microsoft Cognitive Toolkit|access-date=2017-10-11|language=en-US}}
* {{Citation|title=onnx: Open Neural Network Exchange|date=2017-10-11|url=https://github.com/onnx/onnx|publisher=Open Neural Network Exchange|access-date=2017-10-11}}

{{Microsoft FOSS}}

[[Category:Microsoft free software]]
[[Category:Software using the Apache license]]
[[Category:Neural network data exchange formats]]
[[Category:2017 software]]
[[Category:Applied machine learning]]