Switch pkgci_regression_test_cpu.yml to use a self-hosted runner. (#17147)

This improves consistency across jobs in the workflow file. Ideally this
would be a self-hosted _CPU_ runner, but this _GPU_ runner already has a
nice local cache and is being used for CPU model tests.

We also have self-hosted runners on GCP but on
https://github.com/iree-org/iree/pull/16910 I found that they didn't
have `git-lfs` installed and the install commands I wanted to use didn't
work:
```yml
    runs-on:
      - self-hosted # must come first
      - runner-group=${{ github.event_name == 'pull_request' && 'presubmit' || 'postsubmit' }}
      - environment=prod
      - cpu
      - os-family=Linux
```
```
sudo apt-get install git-lfs
  git lfs install
E: Unable to locate package git-lfs
```

Standard sized GitHub-hosted runners should also work for small CPU
tests (that don't need cached model weights or lots of RAM). We have a
job upstream in the test suite repo using `ubuntu-latest`:
https://github.com/nod-ai/SHARK-TestSuite/blob/main/.github/workflows/test_iree.yml.

ci-exactly: build_packages,regression_test_cpu
1 file changed
tree: a9cbb2b67a1300dd2a1046330295e47934b24a51
  1. .devcontainer/
  2. .github/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. lib/
  9. llvm-external-projects/
  10. runtime/
  11. samples/
  12. tests/
  13. third_party/
  14. tools/
  15. .bazel_to_cmake.cfg.py
  16. .bazelignore
  17. .bazelrc
  18. .bazelversion
  19. .clang-format
  20. .dockerignore
  21. .git-blame-ignore-revs
  22. .gitignore
  23. .gitmodules
  24. .yamllint.yml
  25. AUTHORS
  26. BUILD.bazel
  27. CITATION.cff
  28. CMakeLists.txt
  29. configure_bazel.py
  30. CONTRIBUTING.md
  31. LICENSE
  32. MAINTAINERS.md
  33. README.md
  34. RELEASING.md
  35. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

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.

CI Status IREE Discord Status

Project Status

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!

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Architecture Overview

IREE Architecture IREE Architecture

See our website for more information.

Presentations and Talks

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.