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opensecura / 3p / openxla / iree / 3323519bad0f2b91532a8272234034920101709b
commit3323519bad0f2b91532a8272234034920101709b[log] [tgz]
authorScott Todd <scotttodd@google.com>Fri Oct 20 15:12:44 2023 -0700
committerGitHub <noreply@github.com>Fri Oct 20 15:12:44 2023 -0700
tree17f13e84d1c93255bdeb3607cef9af36f4dfbff4
parent20e2112cf149bb342e1d9bfe8f01229a674de1ab [diff]
Port samples/dynamic_shapes/ to PyTorch using SHARK-Turbine. (#15255)

Progress on https://github.com/openxla/iree/issues/15117 and towards
documenting the "advanced AOT toolkit" on
https://www.iree.dev/guides/ml-frameworks/pytorch/ (trying out the
various features so I can write about them).

This notebook produces a program with the same interface as the existing
TensorFlow notebook used by this sample.
* `export_name="module"` could be removed, but then I'd want to somehow
change the TF program and update the C code from
`iree_make_cstring_view("module.reduce_sum_2d")` to
`iree_make_cstring_view("dynamic_shapes.reduce_sum_2d")`. Keeping that
messiness at least as long as the TF notebook remains.
* Yes, I want to delete the TF notebook and rebase on PyTorch + JAX...

New notebook preview for review:
https://colab.research.google.com/github/scotttodd/iree/blob/samples-pytorch/samples/dynamic_shapes/pytorch_dynamic_shapes.ipynb
4 files changed
tree: 17f13e84d1c93255bdeb3607cef9af36f4dfbff4
  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. README.md
  33. 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

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.