* repeat_action_probability
* Add test
* Undo atari wrapper doc change since CI fails
* remove action_repeat_probability from make_atari_env
* Add sticky action wrapper and improve documentation
* Update changelog
* handle the case noop_max=0
* Update tests
* Comply to ALE implementation
* Reorder doc
* Add doc warning and don't wrap with sticky action when not needed
* fix docstring and reorder
* Move `action_repeat_probability` args at the last position
* Add ref
* Update doc and wrap with frameskip only if needed
* Update changelog
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Modified actor-critic policies & MlpExtractor class
ActorCriticPolicy:
- changed type hint of net_arch param: now it's a dict
- removed check that if features extractor is not shared: no shared layers are allowed in the mlp_extractor regardless of the features extractor
ActorCriticCnnPolicy:
- changed type hint of net_arch param: now it's a dict
MultiInputActorcriticPolicy:
- changed type hint of net_arch param: now it's a dict
MlpExtractor:
- changed type hint of net_arch param: now it's a dict
- adapted networks creation
- adapted methods: forward, forward_actor & forward_critic
* Removed shared layers in mlp_extractor
* Updated docs and changelog + reformat
* Updated custom policy tests
* Removed test on deprecation warning for share layers in mlp_extractor
Now shared layers are removed
* Update version
* Update RL Zoo doc
* Fix linter warnings
* Add ruff to Makefile (experimental)
* Add backward compat code and minor updates
* Update tests
* Add backward compatibility
* Fix test
* Improve compat code
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Remove from mypy exclude
* type hint for metadata
* Union[float, int] -> float
* Remove useless __init__
* Type hint for model and logger in BaseCallback
* Type hint for metric_dict
* Update changelog
* fix test_tensorboard
* ignore gamma type checking
* Fix monitor type hint
* Update logger type hints
* Fix type annotation and bump version
* Fix circular import
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* generalize the use of `from gym import spaces`
* command line get system info
* Documentation line length for doc
* update changelog
* add space before os plateform to avoid ref to other issue
* format
* get_system_info update in changelog
* fix type check error
* fix get system info
* add comment about regex
* update version
* Modified ActorCriticPolicy to support non-shared features extractor
* Refactored features extraction with non-shared features extractor in ActorCriticPolicy and updated doc
Doc update: added 'warning' on custom policy docs that says that, if the features extractor is non-shared, it's not possible to have shared layers in the mlp_extractor
* Moved attrib share_features_extractor in class
* Updated custom policy doc for non-shared features extractor
* Updated changelog
* Made some if-statements more readable if policies.py
The if-statements are related to the shared/non-shared features extractor in ActorCritic policies
* Simplify implementation and add run test
* Keep order in module gain to keep previous results consistents
* Fix test
* Improved docstring in policies.py
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
* Added some tests
* feature extractor -> features extractor
* Fix test
* Fix env_id in test
* Make features extractor parameter explicit
* Remove duplicate
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
Co-authored-by: Antonin Raffin <antonin.raffin@dlr.de>
* Fix support of image like normalized inputs
* Improve docstring and warning message.
* Don't check if obs is image when normalize_images is False (lil opt)
* Comment fix
* Fix normalize_images not passed to parent
* Check for subclasses too
* Remove useless multiline
* Update version and add comment
* Fix some typos
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
* Replace .to(device) when possible
* fix numpy dep
* black
* Add warning for device != cpu and copy=False
* Update changelog
* Remove warning
* Update buffers.py
* Update version
* Fix type checking
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Add with_bias arg
* Update changelog
* move torch_layers to the last position
* Update version
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* Raise error when same env object instance is passed in vectorized environment
* At to changelog
* Add raises to docstring
* Add test
* Also test make_vec_env
* Fix test
* Try to enable color for MyPy
* Update version and ignore lint warnings
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Antonin Raffin <antonin.raffin@dlr.de>
* Add progress bar callback and argument
* Update doc
* Update changelog
* Upgrade pytype in docker image
* Use tqdm.write in the logger to have cleaner output
* Fix logger test
* Fix when doing multiple calls to learn()
* Address comments from code-review
* Added option to override or use existing CSVs
* Updated changelog for Monitor override
* Changed default value to override
* Simplify code and add test
* Update version
* Fix for pytype
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* fix nan in advnatages with batch size 1, for ppo
* changelog
* black
* Simplify test
* Bump version
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* include `running_mean` and `running_val` when updating target networks in DQN, SAC, TD3.
* Update stable_baselines3/common/utils.py
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Precompute batch norm parameters in `_setup_model` and directly copy them in the target update.
* include `running_mean` and `running_val` when updating target networks in DQN, SAC, TD3.
* Update stable_baselines3/common/utils.py
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Precompute batch norm parameters in `_setup_model` and directly copy them in the target update.
* Fix `DictReplayBuffer.next_observations` type (#1013)
* Fix DictReplayBuffer.next_observations type
* Update changelog
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Fixed missing verbose parameter passing (#1011)
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
* Support for `device=auto` buffers and set it as default value (#1009)
* Default device is "auto" for buffer + auto device support in BufferBaseClass
* Update docstring
* Update tests
* Unify tests
* Update changelog
* Fix tests on CUDA device
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Antonin Raffin <antonin.raffin@dlr.de>
* Precompute batch norm parameters in `_setup_model` and directly copy them in the target update.
* Update test
* Add comments and update tests
* Bump version
* Remove one extra space to conform code style.
* Update docstrings
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
Co-authored-by: Burak Demirbilek <BurakDmb@users.noreply.github.com>
Co-authored-by: Antonin Raffin <antonin.raffin@dlr.de>
* create Hparam class & support in all OutputFormats
* add hparams documentation & example
* add hparam tests
* remove unnecessary test & fix name
* format changes
* support hyperparameters logging to tensorboard
* fix HParams class docstring
* use more explicit variable names
* raise error instead of warning
* Unpin protobuf
* Add test for logging hparams
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* escape tensorboard log name
Otherwise utils does not recognize the log.
* Added fix to changelog
* Modifications made by: make commit-checks .
* Revert "Modifications made by: make commit-checks ."
This reverts commit 529a275d9475f85ef031038a8f3565f7301e5371.
* Update changelog and add test
Co-authored-by: James Hirschorn <James.Hirschorn@quantitative-technologies.com>
* Goal sampled from next_achieved_goal instead of achived_goal
* No need to have special case for future anymore
* Update changelog
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* Replacing the policy registry with policy "aliases"
* Fixing import order and SAC
* Changing arg. order to be sure policy_aliases is a kwarg
* Import orders
* Removing pytype error check
* Reformat
* Fix alias import
* Not using mutable {} as default for policy_aliases
* Empty aliases initialization
* Using static attributes for policy_aliases
* Fixing isort
* Fixing back bad merge
* Running isort
* Fixing aliases for A2C and PPO
* Using f-string
* Moving policy_aliases definition position
* Adding change in the changelog
* Update version
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* Add Hugging Face to SB3 doc
* Update doc + fixes
* Use SB3 model from the hub
* Bump version
* Fixes
Co-authored-by: simoninithomas <simonini_thomas@outlook.fr>
* Add multi-env training support for SAC
* Fix for dict obs
* Pytype fixes
* Fix assert on number of envs
* Remove for loop
* Add support for Dict obs
* Start cleanup
* Update doc and bug fix
* Add support for vectorized action noise
and add multi env example for off-policy
* Update version
* Bug fix with VecNormalize
* Update README table
* Update variable names
* Update changelog and version
* Update doc and fix for `gradient_steps=-1`
* Add test for `gradient_steps=-1`
* Disable pytype pyi errors
* Fix for DQN
* Update comment on deepcopy
* Remove episode_reward field
* Fix RolloutReturn
* Avoid modification by reference
* Fix error message
Co-authored-by: Anssi <kaneran21@hotmail.com>
* Fix evaluation script for RNN
* Add error message
* Revert "Add error message"
This reverts commit 8d69b6cf4de2cd13aecfb425bd3145fad6a6c49a.
* Fix for pytype
* Rename mask to `episode_start`
* Fix type hint
* Fix type hints
* Remove confusing part of sentence
Co-authored-by: Anssi <kaneran21@hotmail.com>
* Add `system_env_info`
* Add `print_system_info` to load
and store system info at save time
* Remove TODO
* Rename to `get_system_info`
* Import as sb3 for consistency
* Update changelog
* Add warning for old SB3 versions
* Use underscore litteral for more clarity
* Use a consistent key to log the total timesteps
This changes the timestep logging key of on-policy algorithms from
`time/total_timesteps` to `time/total timesteps` (note the
underscore/space). The off-policy algorithms and the eval callback
already use the latter, so this behavior is more consistent.
* Use underscores instead of spaces in logging keys
Most keys already followed this policy and consistent behavior is
friendlier to new users.
* Minor edit and bump version
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* feat: add method predict_values for ActorCriticPolicy
* Fixes for new gym version
* Reformat
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* feat: get_distribution method for ActorCriticPolicy
New method get_distribution for class ActorCriticPolicy returning current action distribution given observations
* doc: updating changelog.rst
- adding block for Release 1.2.1a0
- adding cyprienc to contributors
* style: make format
* fix: updating version.txt
Changing version from 1.2.0 to 1.2.1a0
* Update changelog
* Add test for get distribution
Co-authored-by: Cyprien <courtot.c@gmail.com>
* make sure DQN policy is always in correct mode - train or eval
* make set_training_mode an abstract method of the base policy - safer
* update docstring of _build method to note that the target network is put into eval mode
* use set_training_mode to put the dqn target network into eval mode
* use set_training_mode to set the training model of the q-network
* move set_training_mode abstract method from BasePolicy to BaseModel
* set train and eval mode for TD3
* make sure critic is always in correct mode during train
* set train and eval mode for SAC
* add comment re batch norm and dropout
* set train and eval mode for A2C and PPO
* add tests for collect rollouts with batch norm
* fix formatting
* update change log
* update version
* remove Optional typing for batch size - causing type check to fail
* Fix scipy dependency for toy text envs
* implement set_training_mode method in BaseModel
* move all tests of train/eval mode to test_train_eval_mode
* call learn with learning_starts = total_timesteps to test that collect_rollouts does not update batch norm
* remove extra calls to set_training_mode in train method of TD3 and SAC
* Allow gradient_steps=0
* Refactor tests
* Add comment + use aliases
* Typos
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* training and evaluation: call model.train() and model.eval() to enable and disable dropout and batchnorm
* Add comment documentation
* Fix train and eval for the Actor class
* Run black
* Add github handle to changelog
* Add unit tests for PPO and DQN
* Refactor unit test
* Run black
* unit test: add a dropout layer and check that calling predict with deterministic=True is deterministic
* documentation: add bugfix description to changelog
* unit test: use learning_starts=0, decrease the size of the network and use more training steps
* on policy algorithms: call policy.train() and policy.eval() instead of disable_training and enable_training as it is a th.nn.module
* Rename unit test
* unit test: use drop out probability of 0.5
* Call policy.train and policy.eval
* Fixes + update tests
* Remove unneeded eval
Co-authored-by: David Blom <davidsblom@gmail.com>
Co-authored-by: Antonin Raffin <antonin.raffin@ensta.org>
* Bump version and update doc
* Fix name
* Apply suggestions from code review
Co-authored-by: Adam Gleave <adam@gleave.me>
* Update docs/index.rst
Co-authored-by: Adam Gleave <adam@gleave.me>
* Update wording for RL zoo
Co-authored-by: Adam Gleave <adam@gleave.me>
* Add support for custom objects
* Add python 3.8 to the CI
* Bump version
* PyType fixes
* [ci skip] Fix typo
* Add note about slow-down + fix typos
* Minor edits to the doc
* Bug fix for DQN
* Update test
* Add test for custom objects
* Removed unneeded overrides of feature_extractor and normalize_images in the TD3 Actor.
* Add learning rate schedule example (#248)
* Add learning rate schedule example
* Update docs/guide/examples.rst
Co-authored-by: Adam Gleave <adam@gleave.me>
* Address comments
Co-authored-by: Adam Gleave <adam@gleave.me>
* Add supported action spaces checks (#254)
* Add supported action spaces checks
* Address comment
* Use `pass` in an abstractmethod instead of deleting the arguments.
* Remove the "deterministic" keyword from the forward method of the TD3 Actor since it always is deterministic anyways.
* Rename _get_data to _get_data_to_reconstruct_model.
_get_data was too generic and could have meant anything.
* Remove the n_episodes_rollout parameter and allow passing tuples as train_freq instead.
* Fix docstring of `train_freq` parameter.
* Black fixes.
* Fix TD3 delayed update + rename `_get_data()`
* Fix TD3 test
* Normalize `train_freq` to a tuple in the constructor and turn the warning into an assert.
* Make one step the default train frequency.
* Black fixes.
* Change np.bool to bool.
* Use the tuple format to specify an amount of steps in terms of steps or episodes in the collect_collouts of the off policy algorithm.
* Use the tuple format to specify an amount of steps in terms of steps or episodes in the collect_collouts of HER.
* Use named tuple for train freq
* Rename train_freq to train_every and TrainFreq to ExperienceDuration. Also add some type annotations and documentation.
* Black fixes.
* Revert to train_freq
* Fix terminal observation issues
* Typo
* Fix action noise bug in HER
* Add assert when loading HER models
* Update version
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Adam Gleave <adam@gleave.me>
* Fixed discrete obs support
* Suggest new edit, fix failed test
* Revert "Suggest new edit, fix failed test"
This reverts commit 6892bf05506bb5ad0e87016d8d382705ab72e6a4.
* Fix test
* Special case for discrete obs
Co-authored-by: Anssi "Miffyli" Kanervisto <kaneran21@hotmail.com>
* Added Image and Figure classes to logger. For now, these objects can only be logged by TensorBoardOutputFormat
* Added documentation for figure and image logging into tensorboard
* Updated changelog
* Minor changes to documentation. Reviewed supported types for logging images and figures
* Fix type for np arrays
* Added more explicit example for logging figures in the documentation. Added docstrings for parameters in logging auxiliary classes
* Added tests for image and figure logging
* Applied autoformatting
* Update doc
* Fix documentation example
* Bump version
Co-authored-by: Carlos Casas <ccasascuadrado@guidewire.com>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Fix big when saving/loading q-net alone
* Rename variables to match SB3-contrib
* Update docker image
* Set min version for tensorboard
* Add SB3-Contrib to doc
* Update DQN
* Apply suggestions from code review
Co-authored-by: Adam Gleave <adam@gleave.me>
* Update wording
Co-authored-by: Adam Gleave <adam@gleave.me>
* Added working her version, Online sampling is missing.
* Updated test_her.
* Added first version of online her sampling. Still problems with tensor dimensions.
* Reformat
* Fixed tests
* Added some comments.
* Updated changelog.
* Add missing init file
* Fixed some small bugs.
* Reduced arguments for HER, small changes.
* Added getattr. Fixed bug for online sampling.
* Updated save/load funtions. Small changes.
* Added her to init.
* Updated save method.
* Updated her ratio.
* Move obs_wrapper
* Added DQN test.
* Fix potential bug
* Offline and online her share same sample_goal function.
* Changed lists into arrays.
* Updated her test.
* Fix online sampling
* Fixed action bug. Updated time limit for episodes.
* Updated convert_dict method to take keys as arguments.
* Renamed obs dict wrapper.
* Seed bit flipping env
* Remove get_episode_dict
* Add fast online sampling version
* Added documentation.
* Vectorized reward computation
* Vectorized goal sampling
* Update time limit for episodes in online her sampling.
* Fix max episode length inference
* Bug fix for Fetch envs
* Fix for HER + gSDE
* Reformat (new black version)
* Added info dict to compute new reward. Check her_replay_buffer again.
* Fix info buffer
* Updated done flag.
* Fixes for gSDE
* Offline her version uses now HerReplayBuffer as episode storage.
* Fix num_timesteps computation
* Fix get torch params
* Vectorized version for offline sampling.
* Modified offline her sampling to use sample method of her_replay_buffer
* Updated HER tests.
* Updated documentation
* Cleanup docstrings
* Updated to review comments
* Fix pytype
* Update according to review comments.
* Removed random goal strategy. Updated sample transitions.
* Updated migration. Removed time signal removal.
* Update doc
* Fix potential load issue
* Add VecNormalize support for dict obs
* Updated saving/loading replay buffer for HER.
* Fix test memory usage
* Fixed save/load replay buffer.
* Fixed save/load replay buffer
* Fixed transition index after loading replay buffer in online sampling
* Better error handling
* Add tests for get_time_limit
* More tests for VecNormalize with dict obs
* Update doc
* Improve HER description
* Add test for sde support
* Add comments
* Add comments
* Remove check that was always valid
* Fix for terminal observation
* Updated buffer size in offline version and reset of HER buffer
* Reformat
* Update doc
* Remove np.empty + add doc
* Fix loading
* Updated loading replay buffer
* Separate online and offline sampling + bug fixes
* Update tensorboard log name
* Version bump
* Bug fix for special case
Co-authored-by: Antonin Raffin <antonin.raffin@dlr.de>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
