Gym wrapper for DeepMind Lab environments
This is a gym-like wrapper for Deepmind lab environment. This repo is inspired by jkulhanek/gym-deepmindlab-env and I add some observation options which might helpful!
Usage
According to Deepmind lab's documents, we defined some task-specific wrappers:
| environment id | Class names |
|---|---|
| DeepmindLabEnv-v0 | DeepmindLabEnvironment |
| DeepmindLabNavEnv-v0 | DeepmindLabMazeNavigationEnvironment |
Please note that DeepmindLabMazeNavigationEnvironment is a class extends DeepmindLabEnvironment and implements abstract methods in base class.
Gym-like abstract methods:
resetsteprenderget_action_meanings
Common use:
import gym
import deepmind_lab_as_gym
env = gym.make(id='DeepmindLabNavEnv-v0', level=level)
# Use the environment
observation = env.reset()Installation
python setup.py develop # for development
python setup.py install # for users