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opensecura / 3p / openxla / iree / c9c80a6bf449ba722cb543af075fb85c356f9f59
commitc9c80a6bf449ba722cb543af075fb85c356f9f59[log] [tgz]
authorMehdi Amini <aminim@google.com>Tue Jun 15 10:32:32 2021 -0700
committerCopybara-Service <iree-copybara-bot@google.com>Tue Jun 15 10:33:39 2021 -0700
tree50a2268302f0fbc111e9028e6e2c57a2554a2eca
parenta727999566450cfa7d2dccfe988800840599686b [diff]
PR #49919: [MLIR][DISC] pattern conversion from tf2mhlo: ConvertUnpackOpDynamic, ConvertSignOpDynamic, ConvertSigmoidGradOpDynamic

Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/49919

We are porting our MLIR-based dynamic shape compiler to tf community (From OP def, Patttern, to Optimization pass, etc).
This is the 5th PR about tf2mhlo pattern conversion, which including ConvertUnpackOpDynamic, ConvertSignOpDynamic, ConvertSigmoidGradOpDynamic.
The rest pattern conversions we will add:
- ConvertSqueezeOpxxx
- ConvertStridedSliceOpxxx
- ConvertPrintOp
Copybara import of the project:

--
21b3c3eb05b12956bcdb8b98cc54d9371dbf034d by azazhu <azazhu@gmail.com>:

[MLIR][DISC] pattern conversion from tf2mhlo: ConvertUnpackOpDynamic, ConvertSignOpDynamic, ConvertSigmoidGradOpDynamic

--
634630a4e2e426357290650bd579b35efecab5b3 by azazhu <azazhu@gmail.com>:

[MLIR][DISC] refine ConvertUnpackOpDynamic, ConvertSignOpDynamic, ConvertSigmoidGradOpDynamic

--
39a2bedd6dafb369ae960c5197b7a352bfdfbc80 by azazhu <azazhu@gmail.com>:

add RealDynamicSliceOp's canonicalize and fix CI

--
a1c38dd0963d602ed4812da0d77a096a95920ddb by azazhu <azazhu@gmail.com>:

fix CI for ConvertUnpackOpDynamic

--
5a8b4eb389ed6dc554104356c37f2f1550802b8c by azazhu <azazhu@gmail.com>:

fix typo in ConvertSigmoidGradOpDynamic

PiperOrigin-RevId: 379521079
1 file changed
tree: 50a2268302f0fbc111e9028e6e2c57a2554a2eca
  1. .github/
  2. bindings/
  3. build_tools/
  4. colab/
  5. docs/
  6. experimental/
  7. integrations/
  8. iree/
  9. scripts/
  10. third_party/
  11. .bazelignore
  12. .bazelrc
  13. .bazelversion
  14. .clang-format
  15. .gitignore
  16. .gitmodules
  17. .style.yapf
  18. .yamllint.yml
  19. AUTHORS
  20. BUILD.bazel
  21. CMakeLists.txt
  22. configure_bazel.py
  23. CONTRIBUTING.md
  24. LICENSE
  25. README.md
  26. SUBMODULE_VERSIONS.txt
  27. 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.

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.

Build Status

CI SystemBuild SystemPlatformArchitectureComponentStatus
KokoroBazelLinuxx86Corekokoro_status_bazel_linux_x86_core
KokoroCMake & BazelLinuxx86-swiftshaderIntegrationskokoro_status_cmake-bazel_linux_x86-swiftshader_integrations
KokoroCMake & BazelLinuxx86-turingIntegrationskokoro_status_cmake-bazel_linux_x86-turing_integrations
KokoroCMakeLinuxx86-swiftshaderCore + Bindingskokoro_status_cmake_linux_x86-swiftshader
KokoroCMakeLinuxx86-swiftshader-asanCore + Bindingskokoro_status_cmake_linux_x86-swiftshader-asan
KokoroCMakeLinuxx86-turingCore + Bindingskokoro_status_cmake_linux_x86-turing
KokoroCMakeAndroidarm64-v8aRuntime (build only)kokoro_status_cmake_android_arm64-v8a
BuildKiteCMakeAndroidarm64-v8aRuntimebuildkite-status-cmake-android-arm

Presentations and Talks

  • 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.