* Adds deprecation warning if `eval_env` or `eval_freq` parameters are used. See #925
* added changelog entry
* added missing backtick
* deprecating `create_eval_env` parameter as well and adding comments to explain the `stacklevel` parameter used
* Updated tests to ignore DeprecationWarnings
* Updated changelog entry
* - Removed the `create_eval_env` parameter from the examples in the docs
- Removed information about the `create_eval_env` parameter from the migration docs
- Added information about deprecation of the `create_eval_env` parameter in the docs
* Add alternative in docstring
* Update docstrings
* `eval_freq` warning in docstring
* Add deprecation comments in tests
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: Quentin GALLOUÉDEC <gallouedec.quentin@gmail.com>
* 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>
* Use higher resolution time and round up to eps
* Update changelog
* Add test case
* Fix formatting, time()->time_ns
* Bugfix: ns is integer not float
* Move test to better place
* Divide by 1e9 earlier
* Allow PPO to turn of advantage normalization
* update changelog
* Add a test case
* Update test and sanity check
* Fix tests
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* fix Atari in CI
* fix dtype and atari extra
* Update setup.py
* remove 3.6
* note about how to install Atari
* pendulum-v1
* atari v5
* black
* fix pendulum capitalization
* add minimum version
* moved things in changelog to breaking changes
* partial v5 fix
* env update to pass tests
* mismatch env version fixed
* Fix tests after merge
* Include autorom in setup.py
* Blacken code
* Fix dtype issue in more robust way
* Fix GitLab CI: switch to Docker container with new black version
* Remove workaround from GitLab. (May need to rebuild Docker for this though.)
* Revert to v4
* Update setup.py
* Apply suggestions from code review
* Remove unnecessary autorom
* Consistent gym versions
Co-authored-by: J K Terry <justinkterry@gmail.com>
Co-authored-by: Anssi <kaneran21@hotmail.com>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
Co-authored-by: modanesh <mohamad4danesh@gmail.com>
Co-authored-by: Adam Gleave <adam@gleave.me>
* 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>
* Add custom arch for off-policy actor/critic networks
* Fix type hints
* Address comments
* Make sure number of updated parameters match in polyak
* Add zip_strict for strict-length zipping
* Fix building docs
* Add test for zip strict
* Faster tests
Co-authored-by: Anssi "Miffyli" Kanervisto <kaneran21@hotmail.com>
* Add auto formatting with black and isort
* Reformat code
* Ignore typing errors
* Add note about line length
* Add minimum version for isort
* Add commit-checks
* Update docker image
* Fixed lost import (during last merge)
* Fix opencv dependency
* Add DDPG + TD3 with any number of critics
* Allow any number of critics for SAC
* Update doc
* [ci skip] Update DDPG example
* Remove unused parameter
* Add DDPG to identity test
* Fix computation with n_critics=1,3
* Update doc
* Apply suggestions from code review
Co-authored-by: Adam Gleave <adam@gleave.me>
* Update docstrings for off-policy algos
* Add check for sde
Co-authored-by: Adam Gleave <adam@gleave.me>
* Created DQN template according to the paper.
Next steps:
- Create Policy
- Complete Training
- Debug
* Changed Base Class
* refactor save, to be consistence with overriding the excluded_save_params function. Do not try to exclude the parameters twice.
* Added simple DQN policy
* Finished learn and train function
- missing correct loss computation
* changed collect_rollouts to work with discrete space
* moved discrete space collect_rollouts to dqn
* basic dqn working
* deleted SDE related code
* added gradient clipping and moved greedy policy to policy
* changed policy to implement target network
and added soft update(in fact standart tau is 1 so hard update)
* fixed policy setup
* rebase target_update_intervall on _n_updates
* adapted all tests
all tests passing
* Move to stable-baseline3
* Fixes for DQN
* Fix tests + add CNNPolicy
* Allow any optimizer for DQN
* added some util functions to create a arbitrary linear schedule, fixed pickle problem with old exploration schedule
* more documentation
* changed buffer dtype
* refactor and document
* Added Sphinx Documentation
Updated changelog.rst
* removed custom collect_rollouts as it is no longer necessary
* Implemented suggestions to clean code and documentation.
* extracted some functions on tests to reduce duplicated code
* added support for exploration_fraction
* Fixed exploration_fraction
* Added documentation
* Fixed get_linear_fn -> proper progress scaling
* Merged master
* Added nature reference
* Changed default parameters to https://www.nature.com/articles/nature14236/tables/1
* Fixed n_updates to be incremented correctly
* Correct train_freq
* Doc update
* added special parameter for DQN in tests
* different fix for test_discrete
* Update docs/modules/dqn.rst
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Update docs/modules/dqn.rst
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Update docs/modules/dqn.rst
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Added RMSProp in optimizer_kwargs, as described in nature paper
* Exploration fraction is inverse of 50.000.000 (total frames) / 1.000.000 (frames with linear schedule) according to nature paper
* Changelog update for buffer dtype
* standard exlude parameters should be always excluded to assure proper saving only if intentionally included by ``include`` parameter
* slightly more iterations on test_discrete to pass the test
* added param use_rms_prop instead of mutable default argument
* forgot alpha
* using huber loss, adam and learning rate 1e-4
* account for train_freq in update_target_network
* Added memory check for both buffers
* Doc updated for buffer allocation
* Added psutil Requirement
* Adapted test_identity.py
* Fixes with new SB3 version
* Fix for tensorboard name
* Convert assert to warning and fix tests
* Refactor off-policy algorithms
* Fixes
* test: remove next_obs in replay buffer
* Update changelog
* Fix tests and use tmp_path where possible
* Fix sampling bug in buffer
* Do not store next obs on episode termination
* Fix replay buffer sampling
* Update comment
* moved epsilon from policy to model
* Update predict method
* Update atari wrappers to match SB2
* Minor edit in the buffers
* Update changelog
* Merge branch 'master' into dqn
* Update DQN to new structure
* Fix tests and remove hardcoded path
* Fix for DQN
* Disable memory efficient replay buffer by default
* Fix docstring
* Add tests for memory efficient buffer
* Update changelog
* Split collect rollout
* Move target update outside `train()` for DQN
* Update changelog
* Update linear schedule doc
* Cleanup DQN code
* Minor edit
* Update version and docker images
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
* Change saving/loading normalization parameters to use single pickle file
* Remove 'use_gae' from RolloutBuffer compute_returns function
* Add some missing tests for normalizer, nan-checker and PPO clip_value_fn argument
* Update changelog
* Fix typo
* Use proper pytest.raises for catching errors in tests
* Add comment on GAE and how to obtain non-GAE behaviour
* Remove save/load_running_average from VecNormalize in favor of load/save
* Update changelog
* Update docstring
* Add accidentally removed tests for VecNormalize
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
