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Heavy \nworkloads have been optimized with C++ backend with CUDA and OpenMP (depending on the hardware availability).\n\n# Installation\n\n#### To install RLPack, you can simply do\n\n```bash\npython -m pip install -U pip\npip install RLPack\n```\n\n#### To build and install RLPack from source, simply clone and install as follows: \u003cbr\u003e\n\n```bash\npython -m pip install -U pip\ngit clone https://github.com/kartik2309/RLPack.git\ncd RLPack \npip install . --use-feature=in-tree-build\n```\nThis will install the package in your python environment.\n\n# Documentation\nRLPack documentation was generated by Doxygen. It can be referred [here](https://kartik2309.github.io/RLPack/html/index.html)\n  \n# Issues and bugs\nPlease raise an issue if you encounter a bug. If you would like to fix the bug and contribute to RLPack, kindly refer\nto [CONTRIBUTING.md](https://github.com/kartik2309/RLPack/blob/master/CONTRIBUTING.md)\n\n# License\nRLPack is released under [MIT LICENSE](https://github.com/kartik2309/RLPack/blob/master/LICENSE.md).  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkartik2309%2Frlpack","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkartik2309%2Frlpack","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkartik2309%2Frlpack/lists"}