commit | 9d7a4babf893d1719b020fb810a08d973453f1ba | [log] [tgz] |
---|---|---|
author | bjacob <benoitjacob@google.com> | Mon Oct 16 16:14:53 2023 -0400 |
committer | GitHub <noreply@github.com> | Mon Oct 16 16:14:53 2023 -0400 |
tree | 35d017aca4c602e8c9a0e8e455195fbd75fdbd91 | |
parent | 2b5e61f7d1c387343ca99672bf274f4cf8d2f162 [diff] |
Data-tiling encodings: take the element types out of the enums. (#15182) This has been discussed for a while: ever since #14336 made encodings a data structure, it was an odd remnant that we were still encoding the element types tuple in the user enum. This was cumbersome, and resurfaced in every design discussion as it looked like something that wasn't scaling with new data types. Concretely, this is good to fix ahead of adding `i16xi16` and `i16xi4` data-tiling support (#15158).
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.