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android / platform / external / executorch / b5ae26fdb
commitb5ae26fdb63b99baf6a163e828d06200902c5275[log] [tgz]
authorJacob Szwejbka <jakeszwe@meta.com>Mon Sep 11 13:16:42 2023 -0700
committerFacebook GitHub Bot <facebook-github-bot@users.noreply.github.com>Mon Sep 11 13:16:42 2023 -0700
tree15ac57431c6f4f112125afc43d80a8a0a176dadb
parentd84d9021aa5131ebb520809d5e25d3ff10d42f24 [diff]
delete duplicated declaration (#256)

Summary:
Pull Request resolved: https://github.com/pytorch/executorch/pull/256

Method declarations appear twice in this file. Probably a rebase issue

Reviewed By: cccclai

Differential Revision: D49030241

fbshipit-source-id: 95b48f6deec00a8884ca0f38d3a90072a359e92c
1 file changed
tree: 15ac57431c6f4f112125afc43d80a8a0a176dadb
  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

A unified ML software stack within the PyTorch platform for edge devices. It defines new compiler entry points as well as a state-of-art runtime.

Why ExecuTorch?

Compared to the legacy Lite Interpreter, there are some major benefits:

  • Performance wins compared to Lite Interpreter
    • Faster (orders of magnitude lower framework tax in both DSP and CPU)
    • Much smaller binary size, 1.5 MB vs 30 KB without operators.
    • Smaller memory footprint because we do ahead of time memory planning in ExecuTorch and also have clear granular control over where the runtime allocations are done.
  • Long term alignment with the direction of PyTorch infrastructure
    • Lite Interpreter relies on TorchScript, which is being phased out; ExecuTorch is the planned replacement for Lite Interpreter.
  • Model Authoring & Productivity gains
    • More and better defined entry points to perform model, device, and/or use-case specific optimizations (e.g. better backend delegation, user-defined compiler transformations, default or user-defined memory planning, etc)
    • Ability to lower constructs like dynamic control flow to run on device.

Design goals

  • Minimal binary size (< 50KB not including kernels)
  • Minimal framework tax: loading program, initializing executor, kernel and backend-delegate dispatch, runtime memory utilization
  • Portable (cross-compile across many toolchains)
  • Executes ATen kernels (or ATen custom kernels)
  • Executes custom op kernels
  • Supports inter op asynchronous execution
  • Supports static memory allocation (heapless)
  • Supports custom allocation across memory hierarchies
  • Supports control flow needed by models
  • Allows selective build of kernels
  • Allows backend delegation with lightweight interface

Quick Links

Quick Links for Partners

Directory Structure [WIP]

executorch
├── backends                        #  1st party backend implementations.
|   ├── xnnpack
|   ├── vulkan
|   ├── backend_api.py              # TODO move to exir/backend
|   ├── backend_details.py          # TODO move to exir/backend
|   ├── partioner.py                # TODO move to exir/backend
├── 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.
|   ├── executor_runner
|   ├── export
|   ├── models
├── exir                            #  Ahead of time library, model capture and lowering 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 definition and registration.
|   ├── 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: NOT READY YET FOR OSS USE
├── 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.