| commit | aa55bb6e9f48e134e4de514564111f9d956d23a6 | [log] [tgz] |
|---|---|---|
| author | Scott Todd <scotttodd@google.com> | Thu Nov 09 12:02:30 2023 -0800 |
| committer | GitHub <noreply@github.com> | Thu Nov 09 12:02:30 2023 -0800 |
| tree | 85effebfc54769949c42c9869e69245082d9b34e | |
| parent | 2f47c081bc9506dd583a8249e06745b83dde79b1 [diff] |
Plumb 'torch' input to auto detect via plugin interface. (#15438) This teaches the 'auto' input conversion pipeline how to run plugin-provided conversions automatically when plugins detect that ops in their related dialects are present in a module. Now, programs coming from PyTorch (torch-mlir) can omit `--iree-input-type=torch` and rely on the default of `--iree-input-type=auto` (this fixes https://github.com/openxla/iree/issues/15353). The code is awkward for a few reasons, but I think it can be improved incrementally: * StableHLO and TOSA are "built in" to the compiler (gated on `IREE_HAVE_STABLEHLO_INPUT` / `IREE_HAVE_TOSA_INPUT`), while Torch is implemented via a compiler plugin * I think we could migrate both to be plugins, which would put the input dialects on even footing * The new dynamic pass pipeline needs to know which dialects to register * If all input conversions were plugins, that would feel like less of a special case * There is a dep cycle that I'm trying to avoid narrowly... that may be fixed by migrating all input conversions to plugins
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.