Installation Instructions

Installing OpenRL

OpenRL supports popular operating systems such as Ubuntu, MacOS, Windows, CentOS etc. Currently, OpenRL only supports Python version 3.8 and above. Currently, OpenRL is available on PyPI and Anaconda. Users can install it using pip or conda.

To install using pip:

pip install openrl

To install using conda:

conda install -c openrl openrl

To install from source:

git clone https://github.com/OpenRL-Lab/openrl.git
cd openrl
pip install .

Check the Version

You can check the current installed version of OpenRL by executing the following command in your terminal:

openrl --version

Use Docker

OpenRL currently provides Docker images with and without GPU support. If the user’s computer does not have an NVIDIA GPU, they can obtain an image without the GPU plugin using the following command:

sudo docker pull openrllab/openrl-cpu

If the user wants to accelerate training with a GPU, they can obtain it using the following command:

sudo docker pull openrllab/openrl

After successfully pulling the image, users can run OpenRL’s Docker image using the following commands:

# Without GPU acceleration
sudo docker run -it openrllab/openrl-cpu
# With GPU acceleration
sudo docker run -it --gpus all --net host openrllab/openrl

Once inside the Docker container, users can check OpenRL’s version and then run test cases using these commands:

# Check OpenRL version in Docker container
openrl --version
# Run test case
openrl --mode train --env CartPole-v1

Next, we will use a simple example to show how to train your first agent.