| commit | 53faf3a11f31d0127526d841811f7c0f89c195b5 | [log] [tgz] |
|---|---|---|
| author | Jacques Pienaar <jpienaar@google.com> | Thu May 25 08:12:06 2023 -0700 |
| committer | GitHub <noreply@github.com> | Thu May 25 08:12:06 2023 -0700 |
| tree | 8f70609964b5d289dc488ae54662248d999449fc | |
| parent | c1d499e0d3696e27b98c6cfb6b23d6a92d5435f8 [diff] |
Update cast form to preferred form (#13778) Following https://reviews.llvm.org/D150348 and https://mlir.llvm.org/deprecation/'s "Use the free function variants for dyn_cast/cast/isa/…". Kept it mechanical rather and used namespaced version of tool. The only place where the tool struggled was OpFoldResult instances which didn't work as advertised and so I manually reverted those (so all changes here are due to tool, but it subset of what tool produced).
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.