| commit | 450db0c26701f0948140291874608fd85350b33b | [log] [tgz] |
|---|---|---|
| author | lialan <me@alanli.org> | Tue Jun 25 14:48:03 2024 -0700 |
| committer | GitHub <noreply@github.com> | Tue Jun 25 14:48:03 2024 -0700 |
| tree | fc6fd292a28ec4da4fa20ec5cf2f873d462ee6c8 | |
| parent | 0d9e58740c78364ec7b4084d5dbeebd88185c4c2 [diff] |
Change `EncodingRole` to `IntegerAttr` (#17708) In the future it is possible to encode types other than a matmul, so changing the `EncodingRole` to be the index of the operand. Instead of using integers, use enum to retain the role's symbolic meaning in the code. Note that: It is one's responsibility to make sure the operand index is correct. The index follows the convention that in MLIR output operands are after input operands and are at the end of the operand list. Signed-off-by: Alan Li <me@alanli.org>
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.
Community meeting recordings: IREE YouTube channel
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.