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9ce9803abe
Summary: RFC: https://github.com/pytorch/rfcs/pull/40 This PR (re)introduces python codegen for unboxing wrappers. Given an entry of `native_functions.yaml` the codegen should be able to generate the corresponding C++ code to convert ivalues from the stack to their proper types. To trigger the codegen, run ``` tools/jit/gen_unboxing.py -d cg/torch/share/ATen ``` Merged changes on CI test. In https://github.com/pytorch/pytorch/issues/71782 I added an e2e test for static dispatch + codegen unboxing. The test exports a mobile model of mobilenetv2, load and run it on a new binary for lite interpreter: `test/mobile/custom_build/lite_predictor.cpp`. ## Lite predictor build specifics 1. Codegen: `gen.py` generates `RegisterCPU.cpp` and `RegisterSchema.cpp`. Now with this PR, once `static_dispatch` mode is enabled, `gen.py` will not generate `TORCH_LIBRARY` API calls in those cpp files, hence avoids interaction with the dispatcher. Once `USE_LIGHTWEIGHT_DISPATCH` is turned on, `cmake/Codegen.cmake` calls `gen_unboxing.py` which generates `UnboxingFunctions.h`, `UnboxingFunctions_[0-4].cpp` and `RegisterCodegenUnboxedKernels_[0-4].cpp`. 2. Build: `USE_LIGHTWEIGHT_DISPATCH` adds generated sources into `all_cpu_cpp` in `aten/src/ATen/CMakeLists.txt`. All other files remain unchanged. In reality all the `Operators_[0-4].cpp` are not necessary but we can rely on linker to strip them off. ## Current CI job test coverage update Created a new CI job `linux-xenial-py3-clang5-mobile-lightweight-dispatch-build` that enables the following build options: * `USE_LIGHTWEIGHT_DISPATCH=1` * `BUILD_LITE_INTERPRETER=1` * `STATIC_DISPATCH_BACKEND=CPU` This job triggers `test/mobile/lightweight_dispatch/build.sh` and builds `libtorch`. Then the script runs C++ tests written in `test_lightweight_dispatch.cpp` and `test_codegen_unboxing.cpp`. Recent commits added tests to cover as many C++ argument type as possible: in `build.sh` we installed PyTorch Python API so that we can export test models in `tests_setup.py`. Then we run C++ test binary to run these models on lightweight dispatch enabled runtime. Pull Request resolved: https://github.com/pytorch/pytorch/pull/69881 Reviewed By: iseeyuan Differential Revision: D33692299 Pulled By: larryliu0820 fbshipit-source-id: 211e59f2364100703359b4a3d2ab48ca5155a023 (cherry picked from commit 58e1c9a25e3d1b5b656282cf3ac2f548d98d530b) |
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| .. | ||
| appveyor | ||
| fbcode-dev-setup | ||
| model_zoo | ||
| onnx | ||
| release | ||
| release_notes | ||
| add_apache_header.sh | ||
| apache_header.txt | ||
| apache_python.txt | ||
| build_android.sh | ||
| build_host_protoc.sh | ||
| build_ios.sh | ||
| build_local.sh | ||
| build_mobile.sh | ||
| build_pytorch_android.sh | ||
| build_raspbian.sh | ||
| build_tegra_x1.sh | ||
| build_tizen.sh | ||
| build_windows.bat | ||
| diagnose_protobuf.py | ||
| get_python_cmake_flags.py | ||
| proto.ps1 | ||
| read_conda_versions.sh | ||
| README.md | ||
| remove_apache_header.sh | ||
| temp.sh | ||
| xcode_build.rb | ||
This directory contains the useful tools.
build_android.sh
This script is to build PyTorch/Caffe2 library for Android. Take the following steps to start the build:
- set ANDROID_NDK to the location of ndk
export ANDROID_NDK=YOUR_NDK_PATH
- run build_android.sh
#in your PyTorch root directory
bash scripts/build_android.sh
If succeeded, the libraries and headers would be generated to build_android/install directory. You can then copy these files from build_android/install to your Android project for further usage.
You can also override the cmake flags via command line, e.g., following command will also compile the executable binary files:
bash scripts/build_android.sh -DBUILD_BINARY=ON
build_ios.sh
This script is to build PyTorch/Caffe2 library for iOS, and can only be performed on macOS. Take the following steps to start the build:
- Install Xcode from App Store, and configure "Command Line Tools" properly on Xcode.
- Install the dependencies:
brew install cmake automake libtool
- run build_ios.sh
#in your PyTorch root directory
bash scripts/build_ios.sh
If succeeded, the libraries and headers would be generated to build_ios/install directory. You can then copy these files to your Xcode project for further usage.