Run all framework sanity check tests and organize jobs. (#18420)

Fixes https://github.com/iree-org/iree/issues/16624 by running the
existing ONNX and PyTorch importer tests _with the packages they need
installed_.

Sample logs when a test fails:
https://github.com/iree-org/iree/actions/runs/10691656074/job/29638920091?pr=18420#step:9:19
```
Traceback (most recent call last):
  File "/home/runner/work/iree/iree/compiler/bindings/python/test/extras/fx_importer_test.py", line 8, in <module>
    from iree.compiler.extras import fx_importer
  File "/home/runner/work/iree/iree/.venv/lib/python3.11/site-packages/iree/compiler/extras/fx_importer.py", line 138, in <module>
    from .._mlir_libs._torchMlir import get_int64_max, get_int64_min
ModuleNotFoundError: No module named 'iree.compiler._mlir_libs._torchMlir'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/runner/work/iree/iree/compiler/bindings/python/test/extras/fx_importer_test.py", line [19](https://github.com/iree-org/iree/actions/runs/10691656074/job/29638920091?pr=18420#step:9:20), in <module>
    raise ModuleNotFoundError(
ModuleNotFoundError: Failed to import the fx_importer (for a reason other than torch not being found)
Error: Process completed with exit code 1.
```

---

I'm not really satisfied with how these tests are distributed across
jobs either before or after these changes, but I think this is a step in
a good direction at least.
* These tests depend on optional packages (torch, onnx, tensorflow) and
disable themselves if those optional packages are not present.
* The core project build (CMake/CTest, Python, packaging builds) strives
to be modular and not require the entire kitchen sink to function.
* Test workflows should make sense for both local development _and_ CI
usage. The local development flows here are relatively convoluted and
could use some work.
14 files changed
tree: 4ff38de7aee14b1a3d1f540b200936ad3e0c7342
  1. .github/
  2. build_tools/
  3. compiler/
  4. docs/
  5. experimental/
  6. integrations/
  7. lib/
  8. llvm-external-projects/
  9. runtime/
  10. samples/
  11. tests/
  12. third_party/
  13. tools/
  14. .bazel_to_cmake.cfg.py
  15. .bazelignore
  16. .bazelrc
  17. .bazelversion
  18. .clang-format
  19. .dockerignore
  20. .git-blame-ignore-revs
  21. .gitattributes
  22. .gitignore
  23. .gitmodules
  24. .pre-commit-config.yaml
  25. .yamllint.yml
  26. AUTHORS
  27. BUILD.bazel
  28. CITATION.cff
  29. CMakeLists.txt
  30. configure_bazel.py
  31. CONTRIBUTING.md
  32. LICENSE
  33. MAINTAINERS.md
  34. README.md
  35. RELEASING.md
  36. 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.

IREE Discord Status pre-commit OpenSSF Best Practices

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

Release status

PackageRelease status
GitHub release (stable)GitHub Release
GitHub release (nightly)GitHub Release
Python iree-compilerPyPI version
Python iree-runtimePyPI version

Build status

CI PkgCI

Host platformBuild status
LinuxCI - Linux x64 clang
CI - Linux arm64 clang
macOSCI - macOS x64 clang
WindowsCI - Windows x64 MSVC

For the full list of workflows see https://iree.dev/developers/general/github-actions/.

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

Community meeting recordings: IREE YouTube channel

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

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