| commit | 3ca0a49b424c7d9918a2e73d0c19c308e7d8e6db | [log] [tgz] |
|---|---|---|
| author | Ben Vanik <ben.vanik@gmail.com> | Tue May 07 14:38:36 2024 -0700 |
| committer | GitHub <noreply@github.com> | Tue May 07 14:38:36 2024 -0700 |
| tree | 5ad27851e76d7db498533b6b50505af12dd7ed04 | |
| parent | d8f49dcabd2ed7f929b436a01817a7d777d4ba59 [diff] |
Moving OutlineConstantsPass to flow and adding parameter support. (#17303) This allows us to hide the stream dialect attributes from frontends and use inline flow.tensor.constant ops with parameter attrs. Outlining now also properly preserves hoistable attrs such as stream affinity. By running IPO at the head of the flow pipeline we gain fusion opportunities for hoisted (by user or by global opt) constants and then we clean up the inlined constants at the end of flow so that the stream dialect can handle all values consistently.
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.