Welcome to Tianshou!

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on TensorFlow, have many nested classes, unfriendly API, or slow-speed, Tianshou provides a fast-speed framework and pythonic API for building the deep reinforcement learning agent. The supported interface algorithms include:

• PGPolicy Policy Gradient

• DQNPolicy Deep Q-Network

• DQNPolicy Double DQN with n-step returns

• DQNPolicy Prioritized DQN

• A2CPolicy Advantage Actor-Critic

• DDPGPolicy Deep Deterministic Policy Gradient

• PPOPolicy Proximal Policy Optimization

• TD3Policy Twin Delayed DDPG

• SACPolicy Soft Actor-Critic

• ImitationPolicy Imitation Learning

• compute_episodic_return() Generalized Advantage Estimation

Tianshou supports parallel workers for all algorithms as well. All of these algorithms are reformatted as replay-buffer based algorithms.

Installation

Tianshou is currently hosted on PyPI. You can simply install Tianshou with the following command:

pip3 install tianshou -U

You can also install with the newest version through GitHub:

pip3 install git+https://github.com/thu-ml/tianshou.git@master

After installation, open your python console and type

import tianshou as ts
print(ts.__version__)

If no error occurs, you have successfully installed Tianshou.

Tianshou is still under development, you can also check out the documents in stable version through tianshou.readthedocs.io/en/stable/.

Tutorials

• Deep Q Network
• Basic concepts in Tianshou
• Train a model-free RL agent within 30s
• Cheat Sheet

API Docs

• tianshou.data
• tianshou.env
• tianshou.policy
• tianshou.trainer
• tianshou.exploration
• tianshou.utils

Community

• Contributing
• Contributor

Indices and tables

• Index

• Module Index

• Search Page