| commit | 9aabcb3b296d89b2c1ba91b7d06af141663fc1b3 | [log] [tgz] |
|---|---|---|
| author | Benoit Jacob <jacob.benoit.1@gmail.com> | Mon Feb 12 15:20:58 2024 -0500 |
| committer | GitHub <noreply@github.com> | Mon Feb 12 20:20:58 2024 +0000 |
| tree | ff561a7b9387ba38018eeb40f2b8db3e1363712b | |
| parent | 4a49e37a062770df4a62b2d185ee4e4e5fb50d82 [diff] |
Add conversions for FP8 types (F8E5M2 and F8E4M3) (#16374) This PR almost doesn't make code any bigger because the existing conversion code was already essentially generic. So at least the F8E5M2 type falls for free. F8E4M3 is a bit trickier due to it not having infinities and reclaiming that encoding space to get extra large finite values.
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.