Khronos Announces NNEF 1.0 Standard For Neural Networks
Written by Michael Larabel in Standards on 20 December 2017 at 09:03 AM EST. 2 Comments
Last year The Khronos Group announced NNEF as a open-source, royalty-free neural network format to combat the proprietary formats used today. In their last standards update of 2017, NNEF 1.0 is now available.

The Neural Network Exchange Format 1.0 (NNEF 1.0) is designed to facilitate the porting of trained neural networks across different inference engines and frameworks. The goal of NNEF is to reduce the fragmentation in the machine learning space by having this standard, interoperable format for more easily transferring networks across platforms.

NNEF 1.0 was designed with import/export in mind for Torch, TensorFlow, Caffe, Caffe2, Thano, Chainer, PyTorch, and MXNet.

From Khronos' announcement, "The NNEF 1.0 Provisional specification covers a wide range of use-cases and network types with a rich set of functions and a scalable design that borrows syntactical elements from Python but adds formal elements to aid in correctness. NNEF includes the definition of custom compound operations that offers opportunities for sophisticated network optimizations. Future work will build on this architecture in a predictable way so that NNEF tracks the rapidly moving field of machine learning while providing a stable platform for deployment."

For those into machine learning, you can learn more about NNEF 1.0 at
Related News
About The Author
Author picture

Michael Larabel is the principal author of and founded the site in 2004 with a focus on enriching the Linux hardware experience. Michael has written more than 20,000 articles covering the state of Linux hardware support, Linux performance, graphics drivers, and other topics. Michael is also the lead developer of the Phoronix Test Suite, Phoromatic, and automated benchmarking software. He can be followed via Twitter or contacted via

Popular News This Week