Develop C++/CUDA extensions with PyTorch like Python scripts

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  • License: MIT License
  • Author: Patrick Stotko
  • Requires: Python >=3.10
  • Provides-Extra: dev
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Project description

CharonLoad

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CharonLoad is a bridge between Python code and rapidly developed custom C++/CUDA extensions to make writing high-performance research code with PyTorch easy:

  • 🔥 PyTorch C++ API detection and linking
  • 🔨 Automatic just-in-time (JIT) compilation of the C++/CUDA part
  • 📦 Cached incremental builds and automatic clean builds
  • 🔗 Full power of CMake for handling C++ dependencies
  • ⌨️ Python stub file generation for syntax highlighting and auto-completion in VS Code
  • 🐛 Interactive mixed Python/C++ debugging support in VS Code via Python C++ Debugger extension

CharonLoad reduces the burden to start writing and experimenting with custom GPU kernels in PyTorch by getting complex boilerplate code and common pitfalls out of your way. Developing C++/CUDA code with CharonLoad feels similar to writing Python scripts and lets you follow the same familiar workflow.

Installation

CharonLoad requires Python >=3.10 and can be installed from PyPI:

pip install charonload

Quick Start

CharonLoad only requires minimal changes to existing projects. In particular, a small configuration of the C++/CUDA project is added in the Python part while the CMake and C++ part should adopt some predefined functions:

  • <your_project>/main.py

    import charonload

VSCODE_STUBS_DIRECTORY = pathlib.Path(__file__).parent / "typings"

charonload.module_config["my_cpp_cuda_ext"] = charonload.Config(
    project_directory=pathlib.Path(__file__).parent / "<my_cpp_cuda_ext>",
    build_directory="custom/build/directory",  # optional
    stubs_directory=VSCODE_STUBS_DIRECTORY,  # optional
)

import other_module

  • <your_project>/other_module.py

    import my_cpp_cuda_ext  # JIT compiles and loads the extension

tensor_from_ext = my_cpp_cuda_ext.generate_tensor()

  • <your_project>/<my_cpp_cuda_ext>/CMakeLists.txt

    find_package(charonload)

if(charonload_FOUND)
    charonload_add_torch_library(${TORCH_EXTENSION_NAME} MODULE)

    target_sources(${TORCH_EXTENSION_NAME} PRIVATE src/<my_bindings>.cpp)
    # Further properties, e.g. link against other 3rd-party libraries, etc.
    # ...
endif()

  • <your_project>/<my_cpp_cuda_ext>/src/<my_bindings>.cpp

    #include <torch/python.h>

torch::Tensor generate_tensor();  // Implemented somewhere in <my_cpp_cuda_ext>

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
{
    m.def("generate_tensor", &generate_tensor, "Optional Python docstring");
}

Contributing

If you would like to contribute to CharonLoad, you can find more information in the Contributing guide.

License

MIT

Contact

Patrick Stotko - stotko@cs.uni-bonn.de

Project details

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  • License: MIT License
  • Author: Patrick Stotko
  • Requires: Python >=3.10
  • Provides-Extra: dev
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