* Use F.softmax instead of a pointless network layer
Stateless functions should not be network layers.
* Use correct pytorch functions
* Rename argument name to out_size
Matches in_size and makes more sense.
* Fix shapes of tensors
Advantages and rewards both should be scalars, and therefore a list of them
should be 1D.
* Fmt
* replace deprecated function
* rm unnecessary Variable wrapper
* rm all use of torch Variables
Torch does this for us now.
* Ensure that values are flat list
* Fix shape error in conv nets
* fmt
* Fix shape errors
Reshaping the action before stepping in the env fixes a few errors.
* Add TODO
* Use correct filter size
Works when `self.config['model']['channel_major'] = True`.
* Add missing channel major
* Revert reshape of action
This should be handled by the agent or at least in a cleaner way that doesn't
break existing envs.
* Squeeze action
* Squeeze actions along first dimension
This should deal with some cases such as cartpole where actions are scalars
while leaving alone cases where actions are arrays (some robotics tasks).
* try adding pytorch tests
* typo
* fixup docker messages
* Fix A3C for some envs
Pendulum doesn't work since it's an edge case (expects singleton arrays, which
`.squeeze()` collapses to scalars).
* fmt
* nit flake
* small lint
* Treat actor creation like a regular task.
* Small cleanups.
* Change semantics of actor resource handling.
* Bug fix.
* Minor linting
* Bug fix
* Fix jenkins test.
* Fix actor tests
* Some cleanups
* Bug fix
* Fix bug.
* Remove cached actor tasks when a driver is removed.
* Add more info to taskspec in global state API.
* Fix cyclic import bug in tune.
* Fix
* Fix linting.
* Fix linting.
* Don't schedule any tasks (especially actor creaiton tasks) on local schedulers with 0 CPUs.
* Bug fix.
* Add test for 0 CPU case
* Fix linting
* Address comments.
* Fix typos and add comment.
* Add assertion and fix test.
* Fri Feb 16 13:53:50 PST 2018
* Sat Feb 17 15:32:08 PST 2018
* Sat Feb 17 15:44:59 PST 2018
* fix
* Sun Feb 18 14:46:24 PST 2018
* Sun Feb 18 14:46:37 PST 2018
* Sun Feb 18 14:55:52 PST 2018
* Sun Feb 18 15:14:32 PST 2018
* Wed Feb 21 17:34:17 PST 2018
* Sun Feb 25 17:51:17 PST 2018
* Sun Feb 25 22:18:40 PST 2018
* Wed Feb 28 13:19:05 PST 2018
* Wed Feb 28 13:22:13 PST 2018
* Wed Feb 28 13:33:29 PST 2018
* Wed Feb 28 13:35:33 PST 2018
* add ex
* Fri Mar 2 12:50:17 PST 2018
* Fri Mar 2 12:54:31 PST 2018
* patch up pbt
* Sat Jan 27 01:00:03 PST 2018
* Sat Jan 27 01:04:14 PST 2018
* Sat Jan 27 01:04:21 PST 2018
* Sat Jan 27 01:15:15 PST 2018
* Sat Jan 27 01:15:42 PST 2018
* Sat Jan 27 01:16:14 PST 2018
* Sat Jan 27 01:38:42 PST 2018
* Sat Jan 27 01:39:21 PST 2018
* add pbt
* Sat Jan 27 01:41:19 PST 2018
* Sat Jan 27 01:44:21 PST 2018
* Sat Jan 27 01:45:46 PST 2018
* Sat Jan 27 16:54:42 PST 2018
* Sat Jan 27 16:57:53 PST 2018
* clean up test
* Sat Jan 27 18:01:15 PST 2018
* Sat Jan 27 18:02:54 PST 2018
* Sat Jan 27 18:11:18 PST 2018
* Sat Jan 27 18:11:55 PST 2018
* Sat Jan 27 18:14:09 PST 2018
* review
* try out a ppo example
* some tweaks to ppo example
* add postprocess hook
* Sun Jan 28 15:00:40 PST 2018
* clean up custom explore fn
* Sun Jan 28 15:10:21 PST 2018
* Sun Jan 28 15:14:53 PST 2018
* Sun Jan 28 15:17:04 PST 2018
* Sun Jan 28 15:33:13 PST 2018
* Sun Jan 28 15:56:40 PST 2018
* Sun Jan 28 15:57:36 PST 2018
* Sun Jan 28 16:00:35 PST 2018
* Sun Jan 28 16:02:58 PST 2018
* Sun Jan 28 16:29:50 PST 2018
* Sun Jan 28 16:30:36 PST 2018
* Sun Jan 28 16:31:44 PST 2018
* improve tune doc
* concepts
* update humanoid
* Fri Feb 2 18:03:33 PST 2018
* fix example
* show error file
* working multi action distribution and multiagent model
* currently working but the splits arent done in the right place
* added shared models
* added categorical support and mountain car example
* now compatible with generalized advantage estimation
* working multiagent code with discrete and continuous example
* moved reshaper to utils
* code review changes made, ppo action placeholder moved to model catalog, all multiagent code moved out of fcnet
* added examples in
* added PEP8 compliance
* examples are mostly pep8 compliant
* removed all flake errors
* added examples to jenkins tests
* fixed custom options bug
* added lines to let docker file find multiagent tests
* shortened example run length
* corrected nits
* fixed flake errors
* trying to fix jenkins tests
* comment out more tests
* remove pytorch stuff
* use non-monotonic clock (monotonic not supported on python 2.7)
* whitespace
This introduces rllib.Evaluator and rllib.Optimizer classes. Optimizers encapsulate a particular distributed optimization strategy for RL. Evaluators encapsulate the model graph, and once implemented, any Optimizer may be "plugged in" to any algorithm that implements the Evaluator interface.
* fix yaml bug
* add ext agent
* gpus
* update
* tuning
* docs
* Sun Oct 15 21:09:25 PDT 2017
* lint
* update
* Sun Oct 15 22:39:55 PDT 2017
* Sun Oct 15 22:40:17 PDT 2017
* Sun Oct 15 22:43:06 PDT 2017
* Sun Oct 15 22:46:06 PDT 2017
* Sun Oct 15 22:46:21 PDT 2017
* Sun Oct 15 22:48:11 PDT 2017
* Sun Oct 15 22:48:44 PDT 2017
* Sun Oct 15 22:49:23 PDT 2017
* Sun Oct 15 22:50:21 PDT 2017
* Sun Oct 15 22:53:00 PDT 2017
* Sun Oct 15 22:53:34 PDT 2017
* Sun Oct 15 22:54:33 PDT 2017
* Sun Oct 15 22:54:50 PDT 2017
* Sun Oct 15 22:55:20 PDT 2017
* Sun Oct 15 22:56:56 PDT 2017
* Sun Oct 15 22:59:03 PDT 2017
* fix
* Update tune_mnist_ray.py
* remove script trial
* fix
* reorder
* fix ex
* py2 support
* upd
* comments
* comments
* cleanup readme
* fix trial
* annotate
* Update rllib.rst
* Fix bug in wait_for_pid_to_exit, add test for actor deletion.
* Fix actor garbage collection by breaking cyclic references
* Add test for calling actor method immediately after actor creation.
* Fix bug, must dispatch tasks when workers are killed.
* Fix python test
* Fix cyclic reference problem by creating ActorMethod objects on the fly.
* Try simply increasing the time allowed for many_drivers_test.py.
* make information available for GAE
* buggy version of GAE estimator
* fix
* add more logging and reweight losses
* fix logging
* fix loss
* adapt advantage calculation
* update gae
* standardize returns
* don't normalize td lambda ret
* fix
* don't standardize advantages
* do standardization earlier
* different standardization
* initializer
* drop into the debugger
* fix tensorflow broadcasting bug
* vf clipping
* don't standardize tdlambdaret
* different standardization
* use huber loss for value function
* refactor -- first half
* it runs
* fix
* update
* documentation
* linting and tests
* fix linting
* naming
* fix
* linting
* fix
* remove prefix madness
* fixes
* fix
* add value function example
* fix linting
* remove newline
* Test example applications in Jenkins.
* Fix default upload_dir argument for Algorithm class.
* Fix evolution strategies.
* Comment out policy gradient example which doesn't seem to work.
* Set --env-name for evolution strategies.
* 4 space indentation for actor.py.
* 4 space indentation for worker.py.
* 4 space indentation for more files.
* 4 space indentation for some test files.
* Check indentation in Travis.
* 4 space indentation for some rl files.
* Fix failure test.
* Fix multi_node_test.
* 4 space indentation for more files.
* 4 space indentation for remaining files.
* Fixes.
* implement restarting workers after certain number of task executions
* Clean up python code.
* Don't start new worker when an actor disconnects.
* Move wait_for_pid_to_exit to test_utils.py.
* Add test.
* Fix linting errors.
* Fix linting.
* Fix typo.
