commit | eb9449636970c0bc17a75c3e399f7ee3417b8ba5 | [log] [tgz] |
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author | MaheshRavishankar <1663364+MaheshRavishankar@users.noreply.github.com> | Mon Jun 27 10:02:55 2022 -0700 |
committer | GitHub <noreply@github.com> | Mon Jun 27 10:02:55 2022 -0700 |
tree | d16dee57c649d45b9bddbdbd23384771b34b499d | |
parent | 883763f67e9e817e920b7946317f3afae2d68a4b [diff] |
Integrate llvm-project at 6f258c0fd34cf4001ffa08c61f6e4e0f1254c50f (#9610) Co-authored-by: Alex Zinenko <zinenko@google.com> - Bump MHLO and TF MHLO: a31dd0ba162c417cd3b8786cbb19407fb1fd7250 TF: 5b1b6ca21ea659027dd0ada2d3d8328d0f984fa4 - Some fixes for MLIR header moves - Fix SCF headr file path in third_party/torch-mlir/ - Disable failing round.mlir tests on SPIR-V backend. - Add roundf as a builtin for CPU backend. - Handle deprecation of llvm::commonAlignment methods.
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.