commit | 2bb2240378831fbec23edb8e0b68a13c25513962 | [log] [tgz] |
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author | Thomas Raoux <thomasraoux@google.com> | Tue Jun 22 21:42:04 2021 +0000 |
committer | Copybara Fixup Action <iree-github-actions-bot@google.com> | Tue Jun 22 21:42:04 2021 +0000 |
tree | 05197475d93b8d03cb69a54cf3b1bea58ce34957 | |
parent | 116bd1da91a2e788c6cada1e4ef424e941d68ed6 [diff] | |
parent | 0d01d737b7a9cbe1217fe5ea1f42f1a625906f32 [diff] |
Merge main -> google * 79cf15440 Link CMAKE_DL_LIBS where needed instead of adding -ldl to linker flags (#5702).. * 44be4ec76 Fix broken links in TensorFlow framework doc. (#6279) * 3924a1034 Add a pass that drops export ops marked as excluded during the VMToEmitC conve.. * c8a160b89 Integrate MLIR-EmitC at iml130/mlir-emitc@1a4dea13 (#6261) * 52de5b2bb Merge google -> main (#6276) PiperOrigin-RevId: 380895576
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!
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.