commit | f43f8a3454452f92d13e0e34c336018bfd03b6b5 | [log] [tgz] |
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author | MaheshRavishankar <1663364+MaheshRavishankar@users.noreply.github.com> | Thu Mar 02 13:59:35 2023 -0800 |
committer | GitHub <noreply@github.com> | Thu Mar 02 21:59:35 2023 +0000 |
tree | 177f9ed8d1cc9880b13490a32ffbf1a0c6e3290d | |
parent | 787b518a33782184bc96039b4b547bac4dca7d9f [diff] |
Pad fusion bufferization workaround. (#12425) It seems like handling the code generated by the tiling of pad operations needs more work in bufferization. To unblock the work of handling pad operations natively in IREE, #11273 (comment) is implemented here as a workaround. To ensure bufferization without allocation, yields of the then and else branch and the result of the scf.if are all tied together. If the then and else come from different bindings, then this would be illegal (because a copy is needed). This example led to adding more constraints on what sets can be merged during the BufferizationAnalysis to avoid merging sets that have constants or have two different interface_bindings. benchmarks: x86_64, cuda
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.