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# SAC+AE implementaiton in PyTorch # SAC+AE implementaiton in PyTorch
This is PyTorch implementation of SAC+AE from
**Improving Sample Efficiency in Model-Free Reinforcement Learning from Images** by
[Denis Yarats](https://cs.nyu.edu/~dy1042/), [Amy Zhang](https://mila.quebec/en/person/amy-zhang/), [Ilya Kostrikov](https://github.com/ikostrikov), [Brandon Amos](http://bamos.github.io/), [Joelle Pineau](https://www.cs.mcgill.ca/~jpineau/), and [Rob Fergus](https://cs.nyu.edu/~fergus/pmwiki/pmwiki.php).
[[Paper]](https://arxiv.org/abs/1910.01741) [[Webpage]](https://sites.google.com/view/sac-ae/home)
## Requirements ## Requirements
We assume you have access to a gpu that can run CUDA 9.2. Then, the simplest way to install all required dependencies is to create an anaconda environment by running: We assume you have access to a gpu that can run CUDA 9.2. Then, the simplest way to install all required dependencies is to create an anaconda environment by running:
``` ```