Moss: A Python library for Reinforcement Learning

Moss is a Python library for Reinforcement Learning based on jax.

Installation

To get up and running quickly just follow the steps below:

Installing from PyPI: Moss is currently hosted on PyPI, you can simply install Moss from PyPI with the following command:

pip install moss-rl

Installing from github: If you are interested in running Moss as a developer, you can do so by cloning the Moss GitHub repository and then executing following command from the main directory (where setup.py is located):

pip install -e ".[dev]"

After installation, open your python console and type

import moss
print(moss.__version__)

If no error occurs, you have successfully installed Moss.

Work on GPU or TPU

If you want to run Moss with NVIDIA GPU, please run the steps below:

pip install --upgrade pip

# CUDA 12 installation
# Note: wheels only available on linux.
pip install --upgrade "jax[cuda12_pip]==0.4.9" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

# CUDA 11 installation
# Note: wheels only available on linux.
pip install --upgrade "jax[cuda11_pip]==0.4.9" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Or if you want to run with Google Cloud TPU:

pip install "jax[tpu]==0.4.9" -f https://storage.googleapis.com/jax-releases/libtpu_releases.html

For more details, please see the JAX installation instructions here.

Quick Start

This is an example of Impala to train Atari game(use envpool).

python examples/atari/impala.py --task_id Pong-v5 --learning_rate 1e-3