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opensecura/3p/openxla/iree/refs/heads/main
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3c2a79f36e8b3333ffebb55c4afef1798581ccb5
[log]
author
ziereis <44057120+ziereis@users.noreply.github.com>
Fri Aug 14 20:47:14 2026 +0200
committer
GitHub <noreply@github.com>
Fri Aug 14 20:47:14 2026 +0200
tree
f98098c531ec646a7a67f18ae873b0c6d7e91562
parent
95a00359cc0d7af31bac1dc05d675a5c35771103 [diff]
[DispatchCreation] Fix GatherFusionPattern on a scalar producer operand (#24803)

GatherFusionPattern builds a tensor.extract for every operand of the
producer generic, so a scalar operand reached cast<TensorType> and
asserted. A scalar is invariant over the iteration space, so there is no
index to permute and nothing to extract: the fused body reads the value
itself.

The producer has to be a bit extend or a transpose to qualify, and that
classification deliberately ignores non-tensor inputs, so a qualifying
producer can have them. A per-tensor dequantize widening i8 to f32 with
its scale passed as an f32 is one.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

Signed-off-by: default <ziereis@roofline.ai>
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2 files changed
tree: f98098c531ec646a7a67f18ae873b0c6d7e91562
  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
  22. .gitmodules
  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. GOVERNANCE.md
  32. LICENSE
  33. MAINTAINERS.md
  34. MODULE.bazel
  35. README.md
  36. RELEASING.md
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 news

Project status

Release status

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/.

Build status

CI PkgCI

Nightly build status

Operating systemBuild status
LinuxCI - Linux arm64 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.