[rllib] Parallel-data loading and multi-gpu support for IMPALA

[ericl]

What do these changes do?

• Add support for multi-gpu optimizer to IMPALA.
• Add option for parallel data loading and replay.
• These are all disabled by default.

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[ericl]

Personally, I think the multi-GPU stuff is too messy and we should move away from it. However it's not clear what the best way to do that is, perhaps with TF eager, or moving a lot of the logic into numpy, it would be simpler.

[ericl]

I don't know what will happen if gpu_fraction > 1, but for < 1 I believe it should work.

[ericl]

Also, having public documentation for the shared configs and algorithm specific things would be really good.

It would be good to figure this out. Sphinx doesn't seem to have a good way to do this, unless you duplicate the comments in the dict, or change it to a class or something. For now I think it's reasonable to expect users to read the code since it's at the top of the file.

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[ericl]

I just did a quick multi-GPU run on PPO / IMPALA atari and perf looks good still.

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