commit | abe3f893bc6027fe38dc89093666ac6776f070e1 | [log] [tgz] |
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author | Ian Wood <75152913+IanWood1@users.noreply.github.com> | Thu Oct 24 09:39:13 2024 -0700 |
committer | GitHub <noreply@github.com> | Thu Oct 24 09:39:13 2024 -0700 |
tree | ac29d3f0b13c43e849fcb5913735076c0338a282 | |
parent | c3fae2f7443908e91a00eb65a4f330ad1f71e63f [diff] |
Add conversions for 1x1 conv_2d to matmul (#18736) Convert1X1FilterConv2DToMatmul: handle dynamic cases and conversion to `linalg.generic` representing a broadcasted batch matmul. This pass is kept because it is used in plugins. GeneralizeLinalgNamedOps: generalize conv ops to `linalg.generic` ops when possible. Converting more ops to linalg.generic ops allows for better reshape propagation and fusion opportunities. Also, removed Convert1X1FilterConv2DToMatmulPass from global optimization because generalize named ops would have already generalized any convolutions that were possible to convert. Signed-off-by: Ian Wood <ianwood2024@u.northwestern.edu>
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
Package | Release status |
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GitHub release (stable) | |
GitHub release (nightly) | |
Python iree-compiler | |
Python iree-runtime |
Host platform | Build status |
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Linux | |
macOS | |
Windows |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
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.