* Exploration API (+EpsilonGreedy sub-class).
* Exploration API (+EpsilonGreedy sub-class).
* Cleanup/LINT.
* Add `deterministic` to generic Trainer config (NOTE: this is still ignored by most Agents).
* Add `error` option to deprecation_warning().
* WIP.
* Bug fix: Get exploration-info for tf framework.
Bug fix: Properly deprecate some DQN config keys.
* WIP.
* LINT.
* WIP.
* Split PerWorkerEpsilonGreedy out of EpsilonGreedy.
Docstrings.
* Fix bug in sampler.py in case Policy has self.exploration = None
* Update rllib/agents/dqn/dqn.py
Co-Authored-By: Eric Liang <ekhliang@gmail.com>
* WIP.
* Update rllib/agents/trainer.py
Co-Authored-By: Eric Liang <ekhliang@gmail.com>
* WIP.
* Change requests.
* LINT
* In tune/utils/util.py::deep_update() Only keep deep_updat'ing if both original and value are dicts. If value is not a dict, set
* Completely obsolete syn_replay_optimizer.py's parameters schedule_max_timesteps AND beta_annealing_fraction (replaced with prioritized_replay_beta_annealing_timesteps).
* Update rllib/evaluation/worker_set.py
Co-Authored-By: Eric Liang <ekhliang@gmail.com>
* Review fixes.
* Fix default value for DQN's exploration spec.
* LINT
* Fix recursion bug (wrong parent c'tor).
* Do not pass timestep to get_exploration_info.
* Update tf_policy.py
* Fix some remaining issues with test cases and remove more deprecated DQN/APEX exploration configs.
* Bug fix tf-action-dist
* DDPG incompatibility bug fix with new DQN exploration handling (which is imported by DDPG).
* Switch off exploration when getting action probs from off-policy-estimator's policy.
* LINT
* Fix test_checkpoint_restore.py.
* Deprecate all SAC exploration (unused) configs.
* Properly use `model.last_output()` everywhere. Instead of `model._last_output`.
* WIP.
* Take out set_epsilon from multi-agent-env test (not needed, decays anyway).
* WIP.
* Trigger re-test (flaky checkpoint-restore test).
* WIP.
* WIP.
* Add test case for deterministic action sampling in PPO.
* bug fix.
* Added deterministic test cases for different Agents.
* Fix problem with TupleActions in dynamic-tf-policy.
* Separate supported_spaces tests so they can be run separately for easier debugging.
* LINT.
* Fix autoregressive_action_dist.py test case.
* Re-test.
* Fix.
* Remove duplicate py_test rule from bazel.
* LINT.
* WIP.
* WIP.
* SAC fix.
* SAC fix.
* WIP.
* WIP.
* WIP.
* FIX 2 examples tests.
* WIP.
* WIP.
* WIP.
* WIP.
* WIP.
* Fix.
* LINT.
* Renamed test file.
* WIP.
* Add unittest.main.
* Make action_dist_class mandatory.
* fix
* FIX.
* WIP.
* WIP.
* Fix.
* Fix.
* Fix explorations test case (contextlib cannot find its own nullcontext??).
* Force torch to be installed for QMIX.
* LINT.
* Fix determine_tests_to_run.py.
* Fix determine_tests_to_run.py.
* WIP
* Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function).
* Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function).
* Rename some stuff.
* Rename some stuff.
* WIP.
* WIP.
* Fix SAC.
* Fix SAC.
* Fix strange tf-error in ray core tests.
* Fix strange ray-core tf-error in test_memory_scheduling test case.
* Fix test_io.py.
* LINT.
* Update SAC yaml files' config.
Co-authored-by: Eric Liang <ekhliang@gmail.com>
* Avoid warning about swap being unlimited
Currently we get the following message on Jenkins:
"Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap."
Since we're not limiting swap anyway, we might as well avoid trying to.
https://docs.docker.com/config/containers/resource_constraints/#--memory-swap-details
* Fix escaping in re.search()
* Fix escaping in _noisy_layer()
* Raise a more descriptive error when dashboard data isn't found
* Don't error on dashboard files not being found when webui isn't required
* Change dashboard error to a warning instead
* WIP.
* Fix float32 conversion in OneHot preprocessor (would cause float64 in eager, then NN-matmul-failure).
Add proper seq-len + state-in construction in eager_tf_policy.py::_compute_gradients().
* LINT.
* eager_tf_policy.py: Only set samples["seq_lens"] if RNN. Otherwise, eager-tracing will throw flattened-dict key-mismatch error.
* Move issue code to examples folder.
Co-authored-by: Eric Liang <ekhliang@gmail.com>
* Added histogram functionality to custom metrics infrastructure (another tab in tensorboard)
* updated example to include histogram metric
* added histograms to TBXLogger
* add episode rewards
* lint
Co-authored-by: Eric Liang <ekhliang@gmail.com>
* Add `RandomEnv` example to examples folder.
Convert warning into Error message when using an LSTM in a non-shared-vf network (after the warning, the program would crash).
* LINT.
* Fix issue #6884. LSTM + non-shared vf NN + PPO crashes when using a Tuple action space.
* LINT
* Change warning message for Model: shared_vf=False, LSTM=True cases.
* Bug fix.
* Add examples/random_env.py test to Jenkins.
* Add PG torch regression test to tuned_examples/regression_tests dir.
* Rename cartpole-pg.yaml into cartpole-pg-tf.yaml
* cartpole-pg-tf.yaml: Change cartpole-pg name of tuned_example to cartpole-pg-tf.
* 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.
