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Neural Network Exchange Format (NNEF)
Developer(s)Khronos Group
Stable release
1.0.5 / February 16, 2022; 2 years ago (2022-02-16)[1]
Operating systemCross-platform
PlatformCross-platform
TypeAPI
Websitewww.khronos.org/nnef/

Neural Network Exchange Format (NNEF) is an artificial neural network data exchange format developed by the Khronos Group. It is intended to reduce machine learning deployment fragmentation by enabling a rich mix of neural network training tools and inference engines to be used by applications across a diverse range of devices and platforms.[2][3]

History

NNEF was proposed in 2015 by member companies of the Khronos Group as a device and implementation independent transfer format capable of describing any artificial neural net in terms of its structure, operations and data.

The first version of the standard was launched in provisional form in December 2017, and was ratified as an official Khronos standard in August 2018.

Objectives

The goal of NNEF is to enable data scientists and engineers to easily transfer trained networks from their chosen training framework into a wide variety of inference engines. NNEF encapsulates a complete description of the structure, operations and parameters of a trained neural network, independent of the training tools used to produce it and the inference engine used to execute it.

Governance and Availability

NNEF is maintained by the Khronos Group under its Open Governance Principles[4] as follows:

The NNEF specification is available on the Khronos NNEF registry and tools are available on Github

Versions

Industry Participation

The following Khronos members have participated in the NNEF working group:

Tools

The NNEF tools project on GitHub contains the following open source tools:

See also

References

  1. ^ "Releases".
  2. ^ "NNEF - Neural Network Exchange Format (NNEF)". The Khronos Group. 2016-10-04. Retrieved 2019-02-07.
  3. ^ Seo, B.; Shin, M.; Mo, Y. J.; Kim, J. (January 2018). "Top-down parsing for Neural Network Exchange Format (NNEF) in TensorFlow-based deep learning computation". 2018 International Conference on Information Networking (ICOIN). pp. 522–524. doi:10.1109/ICOIN.2018.8343173. ISBN 978-1-5386-2290-2. S2CID 5053900.
  4. ^ Khronos IP Framework
  5. ^ v1.0p Khronos PR
  6. ^ "The Khronos Group launches new standard for deploying trained neural networks". SD Times. 2018-08-13. Retrieved 2019-02-11.
  7. ^ "Khronos NNEF Registry - The Khronos Group Inc". www.khronos.org. Retrieved 2019-08-15.
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