| commit | ded4145b281ca87590382980f5ce4da1bbe85f77 | [log] [tgz] |
|---|---|---|
| author | Han-Chung Wang <hanhan0912@gmail.com> | Wed Jan 03 09:45:03 2024 -0800 |
| committer | GitHub <noreply@github.com> | Wed Jan 03 09:45:03 2024 -0800 |
| tree | 8a94d9e6968f8e134f68f89599f4fa0cb4943a75 | |
| parent | 957af5485a48de32acaa5b7f5aaba8887266dac4 [diff] |
[LinalgExt] Switch tiling LinalgExt tests to use transform dialect. (#15904) This allows us to test tiling LinalgExt through interfaces. In this context, we don't need to implement its own tiling passes. The lit tests change because 1. The upstream interface methods extract the destination slices from iter_args, not original tensor. 2. We have better helpers that use OpFoldResult (i.e., `makeComposedFoldedAffineApply`) in upstream methods. 3. Delete the lit test about tiling on reduction dims.
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.