commit | e818e8aeaeee1e21478b6fcd3d8b7473bac1a76e | [log] [tgz] |
---|---|---|
author | Okwan Kwon <okwan@google.com> | Wed Aug 31 15:44:24 2022 -0700 |
committer | GitHub <noreply@github.com> | Wed Aug 31 15:44:24 2022 -0700 |
tree | 9fe087b085e17d529db484695eadba5dd9fd1520 | |
parent | 796ddaf1d7f06619c35e82d5793937dc760b19d2 [diff] |
Bump llvm 20220829 (#10243) Integrate llvm-project and bump dependencies * llvm-project: fffd966f0b0f * mlir-hlo: 739e59efacfb77fd63a9f462bc5caa93a838a4ae * tensorflow: dce6d82dd250df450a082e281ab7efc2c7488cce This includes the following changes: * update ResourceAnalysis to use setToEntryState() * changes for the stablehlo transition * disable compile_sample_module.py test temporarily * add an explicit type casting to get Value * rename SubViewOp by MemRefAliasOp
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.