ray/python at e4f68ff8cf6665897e06e2145e72b3ccc26fc9d3 - ray

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Eric Liang 9a479b3a63 [rllib] Document creating an ensemble of envs; also add vector_index attribute to env config (#2513 )

This also removes the async resetting code in VectorEnv. While that improves benchmark performance slightly, it substantially complicates env configuration and probably isn't worth it for most envs.

This makes it easy to efficiently support setups like Joint PPO: https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/retro-contest/gotta_learn_fast_report.pdf

For example, for 188 envs, you could do something like num_envs: 10, num_envs_per_worker: 19.

2018-08-01 16:29:27 -07:00

benchmarks

Add benchmark for ray.get (#2499 )

2018-07-28 09:09:21 -07:00

ray

[rllib] Document creating an ensemble of envs; also add vector_index attribute to env config (#2513 )

2018-08-01 16:29:27 -07:00

asv.conf.json

[asv] Pushing to s3 (#2246 )

2018-06-20 10:43:44 -07:00

build-wheel-macos.sh

Fix MAC_WHEELS=1 (#2477 )