Files
baselines/baselines/trpo_mpi
pzhokhov 353bb15e90 deduplicate algorithms in rl-algs and baselines (#18)
* move vec_env

* cleaning up rl_common

* tests are passing (but mosts tests are deleted as moved to baselines)

* add benchmark runner for smoke tests

* removed duplicated algos

* route references to rl_algs.a2c to baselines.a2c

* route references to rl_algs.a2c to baselines.a2c

* unify conftest.py

* removing references to duplicated algs from codegen

* removing references to duplicated algs from codegen

* alex's changes to dummy_vec_env

* fixed test_carpole[deepq] testcase by decreasing number of training steps... alex's changes seemed to have fixed the bug and make it train better, but at seed=0 there is a dip in the training curve at 30k steps that fails the test

* codegen tests with atol=1e-6 seem to be unstable

* rl_common.vec_env -> baselines.common.vec_env mass replace

* fixed reference in trpo_mpi

* a2c.util references

* restored rl_algs.bench in sonic_prob

* fix reference in ci/runtests.sh

* simplifed expression in baselines/common/cmd_util

* further increased rtol to 1e-3 in codegen tests

* switched vecenvs to use SimpleImageViewer from gym instead of cv2

* make run.py --play option work with num_envs > 1

* make rosenbrock test reproducible

* git subrepo pull (merge) baselines

subrepo:
  subdir:   "baselines"
  merged:   "e23524a5"
upstream:
  origin:   "git@github.com:openai/baselines.git"
  branch:   "master"
  commit:   "bcde04e7"
git-subrepo:
  version:  "0.4.0"
  origin:   "git@github.com:ingydotnet/git-subrepo.git"
  commit:   "74339e8"

* updated baselines README (num-timesteps --> num_timesteps)

* typo in deepq/README.md
2018-08-17 13:54:11 -07:00
..
2017-08-27 22:36:24 -07:00
2018-08-16 14:53:49 -07:00

trpo_mpi

  • Original paper: https://arxiv.org/abs/1502.05477
  • Baselines blog post https://blog.openai.com/openai-baselines-ppo/
  • mpirun -np 16 python -m baselines.run --alg=trpo_mpi --env=PongNoFrameskip-v4 runs the algorithm for 40M frames = 10M timesteps on an Atari Pong. See help (-h) for more options.
  • python -m baselines.run --alg=trpo_mpi --env=Ant-v2 --num_timesteps=1e6 runs the algorithm for 1M timesteps on a Mujoco Ant environment.
  • also refer to the repo-wide README.md