https://github.com/ttitcombe/docker_openai_gym

A Docker image for using openai gym with pytorch
https://github.com/ttitcombe/docker_openai_gym

docker docker-image dockerfile gym openai openai-gym pytorch pytorch-cpu reinforcement-learning

Last synced: about 2 months ago
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A Docker image for using openai gym with pytorch

• Host: GitHub
• URL: https://github.com/ttitcombe/docker_openai_gym
• Owner: TTitcombe
• Created: 2019-07-29T11:05:35.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-07-31T08:45:40.000Z (over 5 years ago)
• Last Synced: 2023-03-06T01:33:42.839Z (almost 2 years ago)
• Topics: docker, docker-image, dockerfile, gym, openai, openai-gym, pytorch, pytorch-cpu, reinforcement-learning
• Language: Dockerfile
• Size: 119 KB
• Stars: 9
• Watchers: 2
• Forks: 8
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
[![Build Status](https://travis-ci.com/TTitcombe/docker_openai_gym.svg?branch=master)](https://travis-ci.com/TTitcombe/docker_openai_gym)

# OpenAI gym Docker Image

This Docker image comes with openai and pytorch-cpu. This allows users to start working on reinforcement learning in a couple of easy steps.

This image is particularly ideal for Windows users, for whom openai gym is not easily installed.

Current features:

* cpu enabled pytorch

* classic control gym environments

* box2d environments

* Recording of environments

To be developed:

* Automated environment recording (no manual command entry)

* environment rendering

* Atari environments

* cpu enabled tensorflow

## How to use

1. Either

    - Clone the repo and build the image: `docker build --tag=image_name .`

    - pull the image: `docker pull ttitcombe/rl_pytorch:latest`

2. Launch the container: `docker run -it --name=container_name image_name python`. This should enter the python interpreter.

3. Before entering the python interpreter, a script to attach the graphical display should have been run. 

4. If you want to re-enter the container and record, you can run `/usr/local/bin/startup_script.py` as the `CMD`, 

e.g. `docker exec -it container_name /usr/local/bin/startup_script.py`. This should enter a bash script.  

Alternatively, you can open a bash script and run it from there. 

5. If you want to re-enter the container, record, AND run something, try

`/usr/local/bin/startup_script.py "python /path/to/my/file.py"` as your `CMD`.

6. If you don't care about recording, use `/bin/bash` to enter bash or `python` to enter the python interpreter.

To test that the container works, try recording an environment:

```python

import gym

import torch

env_to_wrap = gym.make("LunarLander-v1")

env = gym.wrappers.Monitor(env_to_wrap, "someDir")

frame = env.reset()

is_done = False

while not is_done:

  action = env.action_space.sample()

  _, _, is_done, _ = env.step(action)

env.close()

env_to_wrap.close()

``` 

If this doesn't throw an error, then congratulations, you can record OpenAI gym!

You can extract the recording once you are outside of the container with the command `docker cp container_name:/path/to/my/file local/path/to/file`.

![LunarLander example](results/lunar_lander.gif)