Feature request: multiprocess env runner

[syuntoku14]

Hi Chris,

Do you plan to add an EnvRunner class supporting multiprocess?

[cpnota]

Maybe. For most of the standard Gym environments, the environment isn't really the bottleneck, so it's not clear that you get much of a speedup. However, it could be useful for more computationally expensive environments. Do you have any specific use case in mind?

[syuntoku14]

I think most of the RL algorithms with pybullet envs require much training time since pybullet is computationally expensive. For example, chainerrl requires 1.5 days to train kuka-diverse-object-env with DQN.

It seems that some of the continuous control scripts in your code require more than 5 hours to train, so I am implementing a simple multiprocess runner to reduce the training time. I tested it by training kuka-diverse-object-env with 30 CPUs. It saved a lot of time(Maybe I'll send pull request after refactor and test it.)
https://github.com/syuntoku14/image_based_controls/blob/master/experiments/runner.py