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# SAC+AE implementaiton in PyTorch # SAC+AE implementaiton in PyTorch
## Requirements ## Requirements
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:
``` ```
conda env create -f conda_env.yml conda env create -f conda_env.yml
``` ```
After the instalation ends you can activate your environment with:
```
source activate pytorch_sac_ae
```
## Instructions ## Instructions
To train an SAC+AE agent on the `cheetah run` task from image-based observations run: To train an SAC+AE agent on the `cheetah run` task from image-based observations run: