Installation

First, we suggest you to create a virtual environment using Miniconda.

$ conda create -n rlberry
$ conda activate rlberry

Latest version (0.7.3)

Install the latest version for a stable release.

minimal version :

$ pip install rlberry

Recommanded version (more adapted for RL usage):

$ pip install rlberry[extras]

extras allow to install :

optuna : Optuna is an automatic hyperparameter optimization software framework. More information here.

ffmpeg-python : Python bindings for FFmpeg - with complex filtering support. A complete, cross-platform solution to record, convert and stream audio and video. More information here.

scikit-fda : This package offers classes, methods and functions to give support to Functional Data Analysis in Python. More information here.

DeepRL version :

$ pip install rlberry[torch,extras]

torch allow to install :

ale-py : The Arcade Learning Environment (ALE) is a simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games. More information here.

opencv-python : Wrapper package for OpenCV python bindings. OpenCV provides a real-time optimized Computer Vision library. More information here.

stable-baselines3 : Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. More information here.

tensorboard : TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. More information here.

torch : The torch package contains data structures for multi-dimensional tensors and defines mathematical operations over these tensors. More information here.

Options

To install rlberry with more options, you can use pip install rlberry[xxxxxxxx], with xxxxxxxx as :

  • torch to install opencv-python, ale-py, stable-baselines3, tensorboard, torch

  • extras to install optuna, ffmpeg-python, scikit-fda

(for dev)

  • doc to install sphinx, sphinx-gallery, sphinx-math-dollar, numpydoc, myst-parser, sphinxcontrib-video, matplotlib

Development version

Install the development version to test new features.

$ pip install rlberry@git+https://github.com/rlberry-py/rlberry.git

⚠ warning : ⚠

For zsh users, zsh uses brackets for globbing, therefore it is necessary to add quotes around the argument, e.g. pip install 'rlberry@git+https://github.com/rlberry-py/rlberry.git'.

Previous versions

If you used a previous version in your work, you can install it by running

$ pip install rlberry@git+https://github.com/rlberry-py/rlberry.git@{TAG_NAME}

replacing {TAG_NAME} by the tag of the corresponding version, e.g., pip install rlberry@git+https://github.com/rlberry-py/rlberry.git@v0.1 to install version 0.1.

⚠ warning : ⚠

For zsh users, zsh uses brackets for globbing, therefore it is necessary to add quotes around the argument, e.g. pip install 'rlberry@git+https://github.com/rlberry-py/rlberry.git@v0.1'.

Deep RL agents

Deep RL agents require extra libraries, like PyTorch.

  • PyTorch agents:

$ pip install rlberry[torch]@git+https://github.com/rlberry-py/rlberry.git

⚠ warning : ⚠

For zsh users, zsh uses brackets for globbing, therefore it is necessary to add quotes around the argument, e.g. pip install 'rlberry[torch_agents]@git+https://github.com/rlberry-py/rlberry.git'.