YuchenJin commented on code in PR #89: URL: https://github.com/apache/tvm-rfcs/pull/89#discussion_r952996763
########## rfcs/0089-relax-upstreaming.md: ########## @@ -0,0 +1,701 @@ +- Feature Name: Relax Upstreaming +- Start Date: 2022-08-17 +- RFC PR: [apache/tvm-rfcs#0089](https://github.com/apache/tvm-rfcs/pull/0089) +- GitHub Issue: [apache/tvm#0000](https://github.com/apache/tvm/issues/0000) +- Co-Authors: [@denise-k](https://github.com/denise-k), [@jwfromm](https://github.com/jwfromm) + +# 1. **Summary** + +This RFC proposes to upstream the core foundation of Relax (Relay Next). Relax is a new graph-level IR that enables new capabilities to address the [critical needs](https://discuss.tvm.apache.org/t/establish-tvm-unity-connection-a-technical-strategy/13344) identified by the TVM community over the years of using and developing deep learning compilers. + +# 2. **Motivation and goals** + +Relax is an effort within [TVM Unity](https://tvm.apache.org/2021/12/15/tvm-unity) that aims to evolve the graph-level IR to maximize **expressibility, performance, and portability** across today and tomorrow’s workloads. Relax has three key goals motivated by the TVM community’s needs, and lessons the community has learned in ML acceleration through years of using and developing TVM: Review Comment: Hi @Mousius, the expressibility here does not mean the support for TVMScript. It means the ability of the IR to express workloads. For example, we need to be able to express symbolic shapes in the IR to support and optimize dynamic shape workloads; we need to be able to express side effects to support training workloads that make inplace updates to the model’s weights during backpropagation. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
