commit | ae5e27bae0b5a92ec63e4213e54dff66ceacaab3 | [log] [tgz] |
---|---|---|
author | Ben Vanik <benvanik@google.com> | Tue Oct 19 19:36:24 2021 -0700 |
committer | GitHub <noreply@github.com> | Tue Oct 19 19:36:24 2021 -0700 |
tree | 877607029f0ac3dc3a2509e4dd5a8ac12894c463 | |
parent | 9cdbfe1f49195129eebf6e34a4c164213a188255 [diff] |
Adding `stream` dialect. (#7398) This adds the `stream` dialect, ops, types, interfaces, and canonicalizers. See `iree/compiler/Dialect/Stream/IR/StreamBase.td` for an overview of the dialect. Future changes will add conversions, analyses, and passes using the dialect. There are some aspects still work-in-progress, particularly around copy-on-write materialization, but the dialect is largely functionally complete (if yet still missing a lot of potential canonicalizations).
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.