commit | 2c6281b7be3b2e698b7b943c940ff162d200f218 | [log] [tgz] |
---|---|---|
author | Geoffrey Martin-Noble <gcmn@google.com> | Wed Nov 17 21:47:02 2021 -0800 |
committer | GitHub <noreply@github.com> | Wed Nov 17 21:47:02 2021 -0800 |
tree | eb4bec5565a7ad9a064cee3e1097baa62bdd2697 | |
parent | 04ec31adc8e6b10b6566d74532721dacd21d1137 [diff] |
Make benchmarking script more fault-tolerant (#7674) This is not the prettiest Python I've ever written, but it does allow restarting benchmark runs rather than losing all progress after a single failure. This makes the workflow of starting a benchmarking run and then coming back when it is finished far more workable. I tried out incremental output of the final json results and reloading from that, but decided against it because I had to manually construct json (no native incremental support) and use context handlers to ensure structures were closed even on a failure exit. Overall it ended up being pretty gross. Since we were already using temporary files for captures, this seemed like a reasonable way to go.
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.