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opensecura / 3p / openxla / iree / be510b67a2312bd23c13525826f2e46b7055f29f
commitbe510b67a2312bd23c13525826f2e46b7055f29f[log] [tgz]
authorIan Wood <ianwood2024@u.northwestern.edu>Tue Sep 09 16:28:19 2025 -0700
committerGitHub <noreply@github.com>Tue Sep 09 16:28:19 2025 -0700
treec605b2cf60565fbb377d86b946387cfd3ac4ae7d
parentb18e45c26edd5545fe0a2ef22f533072f4900fef [diff]
[LinalgExt] Fix `FoldWithProducerReshapeByExpansion` for >1 dyn dim (#21894)

The builder for `tensor.expand_shape` cannot infer the output shape in
cases where there are more then 1 dynamic dimensions. So,
`ExpansionInfo` needs to track the SSA values for the expanded shape to
be able to create reshapes.

This introduces two problems:
1. Creating `tensor.dim` ops early (i.e. before knowing if the pattern
can be successfully applied) will cause the greedy pattern rewrite
driver to loop forever. This is fixed by using the `DimSize` class to
delay IR modifications until the pattern is known to not fail.
2. In the case of `iree_linalg_ext -> tensor.expand_shape`, the output
shape SSA values must be moved to dominate the op. This is also done
upstream:

https://github.com/llvm/llvm-project/blob/879f40ab041b31fa73b9b25e4ec9e06e810bc767/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp#L875-L894


Closes https://github.com/iree-org/iree/issues/21889

---------

Signed-off-by: Ian Wood <ianwood@u.northwestern.edu>
2 files changed
tree: c605b2cf60565fbb377d86b946387cfd3ac4ae7d
  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. .git-blame-ignore-revs
  20. .gitattributes
  21. .gitignore
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  23. .pre-commit-config.yaml
  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.

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Releases notes are published on GitHub releases.

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

For more details on the release process, see https://iree.dev/developers/general/release-management/.

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Operating systemBuild status
LinuxCI - Linux arm64 clang
macOSCI - macOS x64 clang
macOSCI - macOS arm64 clang

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

DateTitleRecordingSlides
2025-06-10Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM)recordingslides
2025-05-17Introduction to GPU architecture and IREE's GPU CodeGen Pipelinerecordingslides
2025-02-12The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised)recordingslides
2024-10-01Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardwarerecording
2021-06-09IREE Runtime Design Tech Talkrecordingslides
2020-08-20IREE CodeGen (MLIR Open Design Meeting)recordingslides
2020-03-18Interactive HAL IR Walkthroughrecording
2020-01-31End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting)recordingslides

License

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