commit | 9459c4fc86cd236142ce1e81bf91ac9f895096e2 | [log] [tgz] |
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author | Ben Vanik <benvanik@google.com> | Wed Nov 03 10:21:20 2021 -0700 |
committer | GitHub <noreply@github.com> | Wed Nov 03 10:21:20 2021 -0700 |
tree | 50731acdb380200f59ac61a7832123846b218e0c | |
parent | d36d806bc918c4bd359deb8a52717dbaee5eb4f0 [diff] |
Adding docs on the various extension mechanisms available in IREE. (#7515) I tried to keep this relatively high-level for now (mostly because many of these mechanisms are not fully implemented) but it's such a common question that we really need someplace to direct people to for the 10,000ft view and capabilities we (will) provide. There's just the single design overview for now but as we build and document these mechanisms we can add user-facing docs for the ones that people will encounter with samples/etc.
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.