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

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<h1 align="center">CharonLoad</h1>

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:

```sh
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`
  
    ```python
    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`
  
    ```python
    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`
  
    ```cmake
    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``

```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](https://vc-bonn.github.io/charonload/src/contributing.html) guide.

## License

MIT

## Contact

Patrick Stotko - <a href="mailto:stotko@cs.uni-bonn.de">stotko@cs.uni-bonn.de</a><br/>

charonload

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