commit | 7080942c4aca1d24ac4f041a3e1edfaa42238b53 | [log] [tgz] |
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author | Scott Todd <scotttodd@google.com> | Tue Aug 03 11:13:39 2021 -0700 |
committer | GitHub <noreply@github.com> | Tue Aug 03 11:13:39 2021 -0700 |
tree | 4cd8c1bf6193e47ecedf5ee5aedd225c4e4e9012 | |
parent | 772c47bf8d4b156d0b3924e1cc2d9994b1bdadd9 [diff] |
Add linalg detensorizing behind a flag. (#6626) Progress on https://github.com/google/iree/issues/1159 With this pass enabled, some programs do not yet compile fully through IREE's full mlir-to-vm pipeline. I think it would still be useful to wire up this way so others can more easily experiment.
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.