commit | 871e591625a2e6829d50c5e18b9f6c42e6ed215b | [log] [tgz] |
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author | Rob Suderman <rob.suderman@gmail.com> | Thu Feb 24 16:34:49 2022 -0800 |
committer | GitHub <noreply@github.com> | Thu Feb 24 16:34:49 2022 -0800 |
tree | 0028c49b8cb2a2c94e86079474762c74082d40f4 | |
parent | cb0b84f450a0071a3b808f1fb58894f4e8ec5ce1 [diff] |
Integrate llvm-project at e2f627e5e3855309f3a7421f6786b401efb6b7c7 (#8406) Integrate llvm-project at e2f627e5e3855309f3a7421f6786b401efb6b7c7 Advance sub-projects: tensorflow: 576057d1c6fcb61dec6c6d6319bbb129b5954113 mlir-hlo: 7878104a845708490cafdec74b5b28b9aabfc923 Piper CL: 430679467 Integration fixes for D120182 Includes cherry-pick 92cf9f14814a5e8308c431095fb2205202445676 for llvm-project
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.