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Release v1.8.0 #1434

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Apr 8, 2023
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Release v1.8.0 #1434

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22 changes: 19 additions & 3 deletions docs/misc/changelog.rst
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Expand Up @@ -4,9 +4,11 @@ Changelog
==========


Release 1.8.0a14 (WIP)
Release 1.8.0 (2023-04-07)
--------------------------

**Multi-env HerReplayBuffer, Open RL Benchmark, Improved env checker**

.. warning::

Stable-Baselines3 (SB3) v1.8.0 will be the last one to use Gym as a backend.
Expand All @@ -31,23 +33,37 @@ New Features:
- Added support for dict/tuple observations spaces for ``VecCheckNan``, the check is now active in the ``env_checker()`` (@DavyMorgan)
- Added multiprocessing support for ``HerReplayBuffer``
- ``HerReplayBuffer`` now supports all datatypes supported by ``ReplayBuffer``
- Provide more helpful failure messages when validating the ``observation_space`` of custom gym environments using ``check_env``` (@FieteO)
- Provide more helpful failure messages when validating the ``observation_space`` of custom gym environments using ``check_env`` (@FieteO)
- Added ``stats_window_size`` argument to control smoothing in rollout logging (@jonasreiher)


`SB3-Contrib`_
^^^^^^^^^^^^^^
- Added warning about potential crashes caused by ``check_env`` in the ``MaskablePPO`` docs (@AlexPasqua)
- Fixed ``sb3_contrib/qrdqn/*.py`` type hints
- Removed shared layers in ``mlp_extractor`` (@AlexPasqua)

`RL Zoo`_
^^^^^^^^^
- `Open RL Benchmark <https://github.com/openrlbenchmark/openrlbenchmark/issues/7>`_
- Upgraded to new `HerReplayBuffer` implementation that supports multiple envs
- Removed `TimeFeatureWrapper` for Panda and Fetch envs, as the new replay buffer should handle timeout.
- Tuned hyperparameters for RecurrentPPO on Swimmer
- Documentation is now built using Sphinx and hosted on read the doc
- Removed `use_auth_token` for push to hub util
- Reverted from v3 to v2 for HumanoidStandup, Reacher, InvertedPendulum and InvertedDoublePendulum since they were not part of the mujoco refactoring (see https://github.com/openai/gym/pull/1304)
- Fixed `gym-minigrid` policy (from `MlpPolicy` to `MultiInputPolicy`)
- Replaced deprecated `optuna.suggest_loguniform(...)` by `optuna.suggest_float(..., log=True)`
- Switched to `ruff` and `pyproject.toml`
- Removed `online_sampling` and `max_episode_length` argument when using `HerReplayBuffer`

Bug Fixes:
^^^^^^^^^^
- Fixed Atari wrapper that missed the reset condition (@luizapozzobon)
- Added the argument ``dtype`` (default to ``float32``) to the noise for consistency with gym action (@sidney-tio)
- Fixed PPO train/n_updates metric not accounting for early stopping (@adamfrly)
- Fixed loading of normalized image-based environments
- Fixed `DictRolloutBuffer.add` with multidimensional action space (@younik)
- Fixed ``DictRolloutBuffer.add`` with multidimensional action space (@younik)

Deprecations:
^^^^^^^^^^^^^
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4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -90,7 +90,7 @@

extra_packages = extra_no_roms + [ # noqa: RUF005
# For atari roms,
"autorom[accept-rom-license]~=0.5.5",
"autorom[accept-rom-license]~=0.6.0",
]


Expand Down Expand Up @@ -138,7 +138,7 @@
# For spelling
"sphinxcontrib.spelling",
# Type hints support
"sphinx-autodoc-typehints==1.21.1", # TODO: remove version constraint, see #1290
"sphinx-autodoc-typehints",
# Copy button for code snippets
"sphinx_copybutton",
],
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1 change: 0 additions & 1 deletion stable_baselines3/common/distributions.py
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Expand Up @@ -617,7 +617,6 @@ class TanhBijector:
"""
Bijective transformation of a probability distribution
using a squashing function (tanh)
TODO: use Pyro instead (https://pyro.ai/)
:param epsilon: small value to avoid NaN due to numerical imprecision.
"""
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5 changes: 0 additions & 5 deletions stable_baselines3/common/policies.py
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Expand Up @@ -337,11 +337,6 @@ def predict(
:return: the model's action and the next hidden state
(used in recurrent policies)
"""
# TODO (GH/1): add support for RNN policies
# if state is None:
# state = self.initial_state
# if episode_start is None:
# episode_start = [False for _ in range(self.n_envs)]
# Switch to eval mode (this affects batch norm / dropout)
self.set_training_mode(False)

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2 changes: 1 addition & 1 deletion stable_baselines3/version.txt
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@@ -1 +1 @@
1.8.0a14
1.8.0
2 changes: 1 addition & 1 deletion tests/test_her.py
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Expand Up @@ -260,7 +260,7 @@ def env_fn():
del model.replay_buffer

with pytest.raises(AttributeError):
model.replay_buffer
model.replay_buffer # noqa: B018

# Check that there is no warning
assert len(recwarn) == 0
Expand Down