Hi, > as a community we recently moves towards the relax IR for latest genAI > workloads
Thanks for directing us towards Relax. I guess that means that new frontends should convert their representations into Relax IR instead of Relay? The documentation on tvm.apache.org refers to Relay, but not Relax. Is that documentation obsolete in this area? Is Relay going to be superseded by Relax? We only see frontend examples in tvm.relax that we can use as reference. Is there further documentation on tvm.relax? It is interesting to hear that there's more focus on dynamic graphs / shape inference, as one of the key goals of the next version of NNEF, under development, is support for dynamic graphs and shape inference. > it is unclear how much adoption NNEF have as of now versus ONNX and other > formats One of the goals of integration into compiler stacks like TVM would be exactly to drive more adoption, as adoption requires public tooling to be able to demonstrate the capabilities / usage of NNEF in end-to-end workflows. As the next version of NNEF will focus on dynamic graphs, custom operations and lowering to tensor IR level, TVM seems like a good option to demonstrate its potential in compilation based inference engines. But first we would like to start with integrating the currently publicly available version of NNEF. Also, TVM has backends to multiple Khronos formats, such as SPIR-V (Vulkan) and OpenCL, that is why TVM could provide us with an end-to-end workflow starting from a Khronos defined input format, and resulting in Khronos defined outputs. Furthermore, some Khronos members may be interested in implementing their own (proprietary) hardware backends to TVM, with which an NNEF frontend could also provide an end-to-end workflow. -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm-rfcs/pull/108#issuecomment-2058579469 You are receiving this because you are subscribed to this thread. Message ID: <apache/tvm-rfcs/pull/108/c2058579...@github.com>
