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CleanRL is an open-source library that provides high-quality single-fileimplementations of Deep Reinforcement Learning algorithms. It provides asimpler yet scalable developing experience by having a straightforward codebaseand integrating production tools to help interact and scale experiments. InCleanRL, we put all details of an algorithm into a single file, making theseperformance-relevant details easier to recognize. Additionally, an experimenttracking feature is available to help log metrics, hyperparameters, videos ofan agent's gameplay, dependencies, and more to the cloud. Despite succinctimplementations, we have also designed tools to help scale, at one pointorchestrating experiments on more than 2000 machines simultaneously via Dockerand cloud providers. Finally, we have ensured the quality of theimplementations by benchmarking against a variety of environments. The sourcecode of CleanRL can be found at https://github.com/vwxyzjn/cleanrl

CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms