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opensecura / 3p / openxla / iree / 907b2cdbafb3f69666695b4e66b737932b6eb71b
commit907b2cdbafb3f69666695b4e66b737932b6eb71b[log] [tgz]
authorStanley Winata <68087699+raikonenfnu@users.noreply.github.com>Sun Jul 21 13:25:02 2024 -0700
committerGitHub <noreply@github.com>Sun Jul 21 13:25:02 2024 -0700
tree56f3fa95424dc279baec3f357578094bb35df4c0
parent0d0b9891ea62d78475967a1cf2df833bae942cc6 [diff]
[Codegen] Ensure hoisted extraction replaced by induction var. (#17975)

This commit teaches the compiler to replace hoisted extraction of IV by
the newly generated IV with the correct shapes. Previously we would
hoist the extraction and replace the IV uses by the hoisted extraction,
however this may not always be correct since the IV's value may be
updated in the loop.

The main motivation of this PR is to fix numerical issue caused by such
case that exists in the attention-cpp pipeline. Although this happens at
the vector level as opposed to the test cases we have for at tensor
level, we can re-use said test. Specific example for this case will be
left in the comment section of this PR.

---------

Signed-off-by: Stanley Winata <stanley.winata@amd.com>
2 files changed
tree: 56f3fa95424dc279baec3f357578094bb35df4c0
  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.

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

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.