| commit | d93c2634cb03a61e831cf78988174f123cdfe2b6 | [log] [tgz] |
|---|---|---|
| author | Kojo Acquah <KoolJBlack@users.noreply.github.com> | Tue Nov 22 04:07:22 2022 -0500 |
| committer | GitHub <noreply@github.com> | Tue Nov 22 09:07:22 2022 +0000 |
| tree | 40a8c6169870905d51f65cc901ed53ea310bfeb9 | |
| parent | 16e2d9ca2f404bb64b50a64dd7d43bfa5ed20890 [diff] |
Integrate llvm-project at 119cef40d18c and bump dependencies. (#11245) LLVM-COMMIT: 119cef40d18c48240854edc553dca61c4e9fdf27 MHLO-COMMIT: a8219039ba70b6d75217a215e50c3f34176f9716 TF-COMMIT: c74d0b7525d3d7fb68bb5fd48cf4dade1fbc1918 Revert https://github.com/tensorflow/mlir-hlo/commit/f56007837b21cb716f148e8f9cb079386ca4d6a9 Co-authored-by: Hanhan Wang <hanchung@google.com>
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.