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android / platform / external / executorch / bb7d5e6bb
commitbb7d5e6bbc46a8faaa251a9c8a6b6f1553d11499[log] [tgz]
authorChen Lai <chenlai@meta.com>Mon Oct 16 13:54:48 2023 -0700
committerFacebook GitHub Bot <facebook-github-bot@users.noreply.github.com>Mon Oct 16 13:54:48 2023 -0700
tree8958d76bf653f451ca2a3222d604324243ec43e8
parent5fc6e72b2eed7dc96fc02245adc1090d7745cbc4 [diff]
update delegate doc (#956)

Summary: Pull Request resolved: https://github.com/pytorch/executorch/pull/956

Reviewed By: mcr229

Differential Revision: D50333307

fbshipit-source-id: 00a8c862e18f6da1fdacac03e2334566381fbb3c
5 files changed
tree: 8958d76bf653f451ca2a3222d604324243ec43e8
  1. .ci/
  2. .github/
  3. backends/
  4. build/
  5. bundled_program/
  6. codegen/
  7. configurations/
  8. docs/
  9. examples/
  10. exir/
  11. extension/
  12. kernels/
  13. profiler/
  14. runtime/
  15. schema/
  16. scripts/
  17. sdk/
  18. shim/
  19. test/
  20. third-party/
  21. util/
  22. .buckconfig
  23. .clang-format
  24. .clang-tidy
  25. .cmakelintrc
  26. .flake8
  27. .gitignore
  28. .gitmodules
  29. .lintrunner.toml
  30. CMakeLists.txt
  31. CODE_OF_CONDUCT.md
  32. CONTRIBUTING.md
  33. install_requirements.sh
  34. LICENSE
  35. pyproject.toml
  36. pytest.ini
  37. README.md
  38. requirements-lintrunner.txt
  39. setup.py
README.md

ExecuTorch

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices.

Key value propositions of ExecuTorch are:

  • Portability: Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers.
  • Productivity: Enabling developers to use the same toolchains and SDK from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms.
  • Performance: Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs, and DSPs.

For a comprehensive technical overview of ExecuTorch and step-by-step tutorials, please visit our documentation website.

Important: This is a preview release

This is a preview version of ExecuTorch and should be used for testing and evaluation purposes only. It is not recommended for use in production settings. We welcome any feedback, suggestions, and bug reports from the community to help us improve the technology. Please use the PyTorch Forums for discussion and feedback about ExecuTorch using the tag #executorch and our GitHub repository for bug reporting.

The ExecuTorch code and APIs are still changing quickly, and there are not yet any guarantees about forward/backward source compatibility. We recommend using the latest v#.#.# release tag from the Releases page when experimenting with this preview release.

Directory Structure

executorch
├── backends                        #  Backend delegate implementations.
├── build                           #  Utilities for managing the build system.
├── bundled_program                 #  Utilities for attaching reference inputs and outputs to models. TODO move to extension
├── codegen                         #  Tooling to autogenerate bindings between kernels and the runtime. TODO move to tool
├── configurations                  #  TODO delete this
├── docs                            #  Static docs tooling
├── examples                        #  Examples of various user flows, such as model export, delegates, and runtime execution.
├── exir                            #  Ahead of time library, model capture and lowering apis.
|   ├── backend                     #  Backend delegate ahead of time APIs
|   ├── capture                     #  Program capture.
|   ├── dialects                    #  Op sets for various dialects in the export process.
|   ├── emit                        #  Conversion from ExportedProgram to ExecuTorch execution instructions.
|   ├── program                     #  Export artifacts.
|   ├── serialize                   #  Serialize final export artifact.
├── extension                       #  Extensions built on top of the runtime.
|   ├── aten_util
|   ├── data_loader                 # 1st party data loader implementations.
|   ├── memory_allocator            # 1st party memory allocator implementations.
|   ├── pybindings                  # Python api for executorch runtime.
|   ├── pytree                      # C++ and Python flattening and unflattening lib for pytrees.
|   ├── testing_util
├── kernels                         #  1st party kernel implementations.
|   ├── aten
|   ├── optimized
|   ├── portable                    #  Reference implementations of ATen operators.
|   ├── prim_ops                    #  Special ops used in executorch runtime for control flow and symbolic primitives.
|   ├── quantized
├── profiler                        #  Utilities for profiling. TODO delete in favor of ETDump in sdk/
├── runtime                         #  core cpp runtime of executorch
|   ├── backend                     #  Backend delegate runtime APIs
|   ├── core                        #  Core structures used across all levels of the runtime
|   ├── executor                    #  Model loading, initalization, and execution.
|   ├── kernel                      #  Kernel registration and management.
|   ├── platform                    #  Layer between architecture specific code and user calls.
├── schema                          #  ExecuTorch program definition, TODO move under serialization/
├── scripts                         #  Utility scripts for size management, dependency management, etc.
├── sdk                             #  Model profiling, debugging, and introspection.
├── shim                            #  Compatibility layer between OSS and Internal builds
├── test                            #  Broad scoped end2end tests
├── third-party                     #  third-party dependencies
├── util                            #  TODO delete this

License

ExecuTorch is BSD licensed, as found in the LICENSE file.