Sven Mika
bb4e5cb70a
[RLlib] CQL: training iteration function. ( #24166 )
2022-04-26 14:28:39 +02:00
Avnish Narayan
477b9d22d2
[RLlib][Training iteration fn] APEX conversion ( #22937 )
2022-04-20 17:56:18 +02:00
Artur Niederfahrenhorst
e57ce7efd6
[RLlib] Replay Buffer API and Training Iteration Fn for DQN. ( #23420 )
2022-04-18 12:20:12 +02:00
Artur Niederfahrenhorst
9a64bd4e9b
[RLlib] Simple-Q uses training iteration fn (instead of execution_plan); ReplayBuffer API for Simple-Q ( #22842 )
2022-03-29 14:44:40 +02:00
Balaji Veeramani
31ed9e5d02
[CI] Replace YAPF disables with Black disables ( #21982 )
2022-02-08 16:29:25 -08:00
Balaji Veeramani
7f1bacc7dc
[CI] Format Python code with Black ( #21975 )
...
See #21316 and #21311 for the motivation behind these changes.
2022-01-29 18:41:57 -08:00
Sven Mika
371fbb17e4
[RLlib] Make policies_to_train more flexible via callable option. ( #20735 )
2022-01-27 12:17:34 +01:00
Sven Mika
d5bfb7b7da
[RLlib] Preparatory PR for multi-agent multi-GPU learner (alpha-star style) #03 ( #21652 )
2022-01-25 14:16:58 +01:00
Sven Mika
90c6b10498
[RLlib] Decentralized multi-agent learning; PR #01 ( #21421 )
2022-01-13 10:52:55 +01:00
Sven Mika
3d2e27485b
[RLlib] Trainer sub-class DQN/SimpleQ/APEX-DQN/R2D2 (instead of using build_trainer). ( #20633 )
2021-11-30 18:05:44 +01:00
Sven Mika
49cd7ea6f9
[RLlib] Trainer sub-class PPO/DDPPO (instead of build_trainer()). ( #20571 )
2021-11-23 23:01:05 +01:00
Artur Niederfahrenhorst
d07e50e957
[RLlib] Replay buffer API (cleanups; docstrings; renames; move into rllib/execution/buffers dir) ( #20552 )
2021-11-19 11:57:37 +01:00
gjoliver
99a0088233
[RLlib] Unify the way we create local replay buffer for all agents ( #19627 )
...
* [RLlib] Unify the way we create and use LocalReplayBuffer for all the agents.
This change
1. Get rid of the try...except clause when we call execution_plan(),
and get rid of the Deprecation warning as a result.
2. Fix the execution_plan() call in Trainer._try_recover() too.
3. Most importantly, makes it much easier to create and use different types
of local replay buffers for all our agents.
E.g., allow us to easily create a reservoir sampling replay buffer for
APPO agent for Riot in the near future.
* Introduce explicit configuration for replay buffer types.
* Fix is_training key error.
* actually deprecate buffer_size field.
2021-10-26 20:56:02 +02:00
gjoliver
9226f9bddc
[RLlib] Report timesteps_this_iter to Tune, so it can track/checkpoint/restore total timesteps trained. ( #19264 )
...
* Report timesteps_this_iter to Tune, so it can track/checkpoint/restore
total timesteps trained.
* Trigger Build
* lint
2021-10-12 16:03:41 +02:00
Sven Mika
ed85f59194
[RLlib] Unify all RLlib Trainer.train() -> results[info][learner][policy ID][learner_stats] and add structure tests. ( #18879 )
2021-09-30 16:39:05 +02:00
Sven Mika
599e589481
[RLlib] Move existing fake multi-GPU learning tests into separate buildkite job. ( #18065 )
2021-08-31 14:56:53 +02:00
Thomas Lecat
c02f91fa2d
[RLlib] Ape-X doesn't take the value of prioritized_replay into account ( #17541 )
2021-08-16 22:18:08 +02:00
Antoine Galataud
16f1011c07
[RLlib] Issue 15910: APEX current learning rate not updated on local worker ( #15911 )
2021-07-13 14:01:00 -04:00
Sven Mika
169ddabae7
[RLlib] Issue 15973: Trainer.with_updates(validate_config=...) behaves confusingly. ( #16429 )
2021-06-19 22:42:00 +02:00
Sven Mika
d0014cd351
[RLlib] Policies get/set_state fixes and enhancements. ( #16354 )
2021-06-15 13:08:43 +02:00
Amog Kamsetty
ebc44c3d76
[CI] Upgrade flake8 to 3.9.1 ( #15527 )
...
* formatting
* format util
* format release
* format rllib/agents
* format rllib/env
* format rllib/execution
* format rllib/evaluation
* format rllib/examples
* format rllib/policy
* format rllib utils and tests
* format streaming
* more formatting
* update requirements files
* fix rllib type checking
* updates
* update
* fix circular import
* Update python/ray/tests/test_runtime_env.py
* noqa
2021-05-03 14:23:28 -07:00
Sven Mika
c90de315e5
[RLlib] APEX returns incorrect default resources (PleacementGroupFactory) colocated missing replay actors. ( #15295 )
2021-04-15 16:50:42 +01:00
Sven Mika
732197e23a
[RLlib] Multi-GPU for tf-DQN/PG/A2C. ( #13393 )
2021-03-08 15:41:27 +01:00
Sven Mika
8000258333
[RLlib] R2D2 Implementation. ( #13933 )
2021-02-25 12:18:11 +01:00
Sumanth Ratna
9da7bdcc8e
Use master for links to docs in source ( #10866 )
2020-09-19 00:30:45 -07:00
desktable
4ccfd07a61
[RLlib] Add docstrings for agents/dqn ( #10710 )
2020-09-15 12:37:07 +02:00
Sven Mika
2256047876
[RLlib] Rename rllib.utils.types into typing to match built-in python module's name. ( #10114 )
2020-08-15 13:24:22 +02:00
Piotr Januszewski
155cc81e40
Clarify training intensity configuration docstring ( #9244 ) ( #9306 )
2020-07-05 20:07:27 -07:00
Eric Liang
1e0e1a45e6
[rllib] Add type annotations for evaluation/, env/ packages ( #9003 )
2020-06-19 13:09:05 -07:00
Eric Liang
34bae27ac7
[rllib] Flexible multi-agent replay modes and replay_sequence_length ( #8893 )
2020-06-12 20:17:27 -07:00
Eric Liang
9a83908c46
[rllib] Deprecate policy optimizers ( #8345 )
2020-05-21 10:16:18 -07:00
Eric Liang
aa7a58e92f
[rllib] Support training intensity for dqn / apex ( #8396 )
2020-05-20 11:22:30 -07:00
Eric Liang
9d012626e5
[rllib] Distributed exec workflow for impala ( #8321 )
2020-05-11 20:24:43 -07:00
Eric Liang
2c599dbf05
[rllib] Port QMIX, MADDPG to new execution API ( #8344 )
2020-05-07 23:41:10 -07:00
Eric Liang
9f04a65922
[rllib] Add PPO+DQN two trainer multiagent workflow example ( #8334 )
2020-05-07 23:40:29 -07:00
Eric Liang
ee0eb44a32
Rename async_queue_depth -> num_async ( #8207 )
...
* rename
* lint
2020-05-05 01:38:10 -07:00
Sven Mika
b95e28faea
[RLlib] APEX_DDPG (PyTorch) test case and docs. ( #8288 )
...
APEX_DDPG (PyTorch) test case and docs.
2020-05-04 09:36:27 +02:00
Eric Liang
2298f6fb40
[rllib] Port DQN/Ape-X to training workflow api ( #8077 )
2020-04-23 12:39:19 -07:00
Eric Liang
31b40b00f6
[rllib] Pull out experimental dsl into rllib.execution module, add initial unit tests ( #7958 )
2020-04-10 00:56:08 -07:00
Eric Liang
dd70720578
[rllib] Rename sample_batch_size => rollout_fragment_length ( #7503 )
...
* bulk rename
* deprecation warn
* update doc
* update fig
* line length
* rename
* make pytest comptaible
* fix test
* fi sys
* rename
* wip
* fix more
* lint
* update svg
* comments
* lint
* fix use of batch steps
2020-03-14 12:05:04 -07:00
Eric Liang
f5d12a958b
[rllib] Port Ape-X to distributed execution API ( #7497 )
2020-03-12 00:54:08 -07:00
Sven Mika
6043ce710d
Fix old exploration configs. ( #7240 )
2020-02-20 08:39:16 -08:00
Sven Mika
6e1c3ea824
[RLlib] Exploration API (+EpsilonGreedy sub-class). ( #6974 )
2020-02-10 15:22:07 -08:00
Sven Mika
303547f119
[RLlib] Policy-classes cleanup and torch/tf unification. ( #6770 )
2020-01-17 22:26:28 -08:00
Sven
60d4d5e1aa
Remove future imports ( #6724 )
...
* Remove all __future__ imports from RLlib.
* Remove (object) again from tf_run_builder.py::TFRunBuilder.
* Fix 2xLINT warnings.
* Fix broken appo_policy import (must be appo_tf_policy)
* Remove future imports from all other ray files (not just RLlib).
* Remove future imports from all other ray files (not just RLlib).
* Remove future import blocks that contain `unicode_literals` as well.
Revert appo_tf_policy.py to appo_policy.py (belongs to another PR).
* Add two empty lines before Schedule class.
* Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
2020-01-09 00:15:48 -08:00
Eric Liang
5d7afe8092
[rllib] Try moving RLlib to top level dir ( #5324 )
2019-08-05 23:25:49 -07:00
