| commit | 671b0925fc5c54c7dfd2ac4c5ac7f90f30c7a23f | [log] [tgz] |
|---|---|---|
| author | Kunwar Grover <groverkss@gmail.com> | Fri Nov 10 20:52:58 2023 +0530 |
| committer | GitHub <noreply@github.com> | Fri Nov 10 20:52:58 2023 +0530 |
| tree | 13572d71737aaf872fa02a5754aef17ab78edd5f | |
| parent | f458a88724397414192c38e64f8af76e18eee49e [diff] |
Split transform.tile_and_decompose_attention (#15516) 78e9dbcc2b6b51f329238b4b25648527c64e60a7 split up the TileAndDecomposeAttention pass implementation into separate tiling and decomposition. This patch does the same splitting at transform dialect level. There are two reasons for this: 1. Easier to keep track of all the results from the transform operation. 2. After the previous splitting up patch, we were doing some hacks on moving operations filled around to get the same sequence of transform results as before.
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.