commit | 25de54960ea4c537833d85f471169c43ad19e87b | [log] [tgz] |
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author | Han-Chung Wang <hanhan0912@gmail.com> | Mon Dec 16 06:45:28 2024 -0800 |
committer | GitHub <noreply@github.com> | Mon Dec 16 09:45:28 2024 -0500 |
tree | b364502a3974f2ae1ca4ea4c799a471429faaec5 | |
parent | 05ce39f3fba4b5cc6eee18a431f8f8e16fa9b5d2 [diff] |
[NFC] Delete outdated e2e encoding tests. (#19487) It was introduced for GPU matmul data-tiling when the multi_mma code-generation was not ready yet. There is an e2e path in IREE (see tests/e2e/matmul/) now, so we no longer need the test suite. Signed-off-by: hanhanW <hanhan0912@gmail.com>
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-base-compiler | |
Python iree-base-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.