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AMD is excited to see the emergence of the Open Neural Network Exchange (ONNX) format which is creating  a common format model to bridge three industry-leading deep learning frameworks (PyTorch, Caffe2, and Cognitive Toolkit)  to give our customers simpler paths to explore their networks via rich framework interoperability.

The ONNX format, via its extensible computation graph model, built-in operators, and standard data types will allow our team to focus on more in-depth optimization with our Radeon Instinct Hardware and more productive solution set via our open source MIOpen deep learning solver library and ROCm Compiler technology.  It also gives us the path to explore new foundation production beyond traditional frameworks for production to bring lighter weight more optimized solutions for our hardware.

It is great to see the collaboration of Facebook and Microsoft continuing to also follow in the path of open software development practice with ONNX, building on their open source projects PyTorch, Caffe2, and Cognitive Toolkit.  Open Software development aligns with our philosophy of bringing out open source software platform, tools, and driver to allow the research community to have more powerful ability to explore broader deep learning design space.

We feel this is an excellent step for the community to open up these platform to a broader set of diverse architectures.  We look forward to working with the project and help it grow in the coming months.

Gregory Stoner, is Sr. Director of Radeon Open Compute. Links to third-party sites and references to third-party trademarks are provided for convenience and illustrative purposes only. Unless explicitly stated, AMD is not responsible for the contents of such links, and no third-party endorsement of AMD or any of its products is implied. Use of third-party names or marks is for informational purposes only and no endorsement of or by AMD is intended or implied.

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