commit | 4a8b169993b6c9d1188cff6948c12d453edde177 | [log] [tgz] |
---|---|---|
author | Stella Laurenzo <stellaraccident@gmail.com> | Wed May 26 10:42:49 2021 -0700 |
committer | GitHub <noreply@github.com> | Wed May 26 10:42:49 2021 -0700 |
tree | 52b1c7b0a223f518f6074973903d3ce576916547 | |
parent | ba661e87802a23de3cc02e2aefc5fda1a1c6e71c [diff] |
Create new pass PromoteTensorLoads. (#6023) * Create new pass PromoteTensorLoads. * In the new input pipeline, the only part of PrePartitioningConversionPass which survives is the tensor.extract_element -> flow.tensor.load conversion. * This conversion actually needs to be done at a couple of points during lowering, first promoting any extracts that are introduced as part of control flow (in the input pipeline), then allowing most of the program to be loaded onto the device, and finally converting any remaining, otherwise unrecognized extract elements. * As such, I opted to make it a very specific pass that does exactly what it says on the label. We may want to do something more sophisticated later, and at least having one thing to see and replace will help. * Once the new input pipeline lands, PrePostPartitioningConversion.cpp will be deleted.
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!
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.