Cleanup unused Dockerfiles and build_all.yml workflow. (#18222) Follow-up to https://github.com/iree-org/iree/pull/18144. Related to https://github.com/iree-org/iree/issues/15332. * `build_all.yml` was used as the first step in multiple other workflows. New workflows are using `pkgci_build_packages.yml` directly or nightly releases. Workflows could also use historical artifacts from `pkgci_build_packages.yml` if they want to use versions different from the nightly releases. * `android.Dockerfile` was used for Android builds and benchmarks. New workflows install the NDK on demand without needing a large Dockerfile. * `nvidia.Dockerfile` and `nvidia-bleeding-edge.Dockerfile` were used for CUDA/Vulkan benchmarks. New workflows rely on the drivers and software packages that are already installed on runners. We could have workflows install on demand or add new Dockerfiles as needed.
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 |
|---|---|
| GitHub release (stable) | |
| GitHub release (nightly) | |
| Python iree-compiler | |
| Python iree-runtime |
| Host platform | Build status |
|---|---|
| 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.