Installation

Express Install

The fastest way to set up dependencies for garage is via running the setup script.

Clone our repo (https://github.com/rlworkgroup/garage) and navigate to its directory.

A MuJoCo key is required for installation. You can get one here: https://www.roboti.us/license.html

Make sure you run these scripts from the root directory of the repo, not from the scripts directory.

  • On Linux, run the following:
./scripts/setup_linux.sh --mjkey path-to-your-mjkey.txt --modify-bashrc
  • On macOS, run the following:
./scripts/setup_macos.sh --mjkey path-to-your-mjkey.txt --modify-bashrc

The script sets up a conda environment, which is similar to virtualenv. To start using it, run the following:

source activate garage

Optionally, if you would like to run experiments that depends on the MuJoCo environment, you can set it up by running the following command:

./scripts/setup_mujoco.sh

and follow the instructions. You need to have the zip file for Mujoco v1.50 and the license file ready.

Manual Install

Anaconda

garage assumes that you are using Anaconda Python distribution. You can download it from https://www.continuum.io/downloads<https://www.continuum.io/downloads. Make sure to download the installer for Python 2.7.

System dependencies for pygame

A few environments in garage are implemented using Box2D, which uses pygame for visualization. It requires a few system dependencies to be installed first.

On Linux, run the following:

sudo apt-get install swig
sudo apt-get build-dep python-pygame

On macOS, run the following:

brew install swig sdl sdl_image sdl_mixer sdl_ttf portmidi

System dependencies for scipy

This step is only needed under Linux:

sudo apt-get install build-dep python-scipy

Install Python modules

conda env create -f environment.yml

GPU Support

To enable GPU support, you need to run the express installation script with the argument --gpu. This options installs GPU-supported Tensorflow and modules needed by Theano.

Before you run garage, you need to specify the directory for the CUDA library in environment variable LD_LIBRARY_PATH. You may need to replace the directory conforming to your CUDA version accordingly.

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-9.0/lib64

You should now be able to use GPU in Tensorflow. For Theano, two additional steps are needed.

  • Specify CUDA root in ~/.theanorc (Create the file if it doesn’t exist)
[cuda]
root = /usr/local/cuda-9.0

export THEANO_FLAGS=device=cuda,floatX=float32,force_device=True