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Implementation of RL Algorithms with PyTorch.

License: MIT License

Python 66.94% CMake 1.94% Shell 0.07% C++ 12.86% Cuda 18.14% C 0.04%
gym-environments pytorch-implementation reinforcement-learning dqn dqn-pytorch prioritized-experience-replay a2c-agent a2c-algorithm a2c-pytorch a3c a3c-agent a3c-pytorch deep-reinforcement-learning

rlpack's Introduction

RLPack

Introduction

RLPack; Reinforcement Learning Package is the implementation of RL Algorithms built on top of PyTorch. Heavy workloads have been optimized with C++ backend with CUDA and OpenMP (depending on the hardware availability).

Installation

To install RLPack, you can simply do

python -m pip install -U pip
pip install RLPack

To build and install RLPack from source, simply clone and install as follows:

python -m pip install -U pip
git clone https://github.com/kartik2309/RLPack.git
cd RLPack 
pip install . --use-feature=in-tree-build

This will install the package in your python environment.

Documentation

RLPack documentation was generated by Doxygen. It can be referred here

Issues and bugs

Please raise an issue if you encounter a bug. If you would like to fix the bug and contribute to RLPack, kindly refer to CONTRIBUTING.md

License

RLPack is released under MIT LICENSE.

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