Releases: rlworkgroup/garage
2020.10.0rc5
This is a pre-release of v2020.10. It contains changes to garage since v2020.06.0.
This pre-release makes cutting-edge features available via PyPI, but comes with no promises of support or bug fixes. If you encounter problems with this release, you are encouraged to either install from master or revert to the v2020.06 release.
For information on what to expected in garage v2020.09, see the release notes for v2020.06.0
2020.06.3
This is a maintenance release for 2020.06.
- Fixed
- PyTorch 1.7 support (#1934)
LocalRunner
ignoresworker_cls
attribute of algorithms (#1984)mujoco_py
versions greater than v2.0.2.8 are incompatible with some GCC versions in conda (#2000)- MTSAC not learning because it corrupts the termination signal by wrapping with
GarageEnv
twice (#2029) - MTSAC does not respect
max_episode_length_eval
hyperparameter (#2029) - MTSAC MetaWorld examples do not use the correct number of tasks (#2029)
- MTSAC now supports a separate
max_episode_length
for evalaution via themax_episode_length_eval
hyperparameter (#2029) - MTSAC MetaWorld MT50 example used an incorrect
max_episode_length
(#2029)
2020.09.0rc4
This is a pre-release of v2020.09. It contains changes to garage since v2020.06.0.
This pre-release makes cutting-edge features available via PyPI, but comes with no promises of support or bug fixes. If you encounter problems with this release, you are encouraged to either install from master or revert to the v2020.06 release.
For information on what to expected in garage v2020.09, see the release notes for v2020.06.0
2020.09.0rc3
This is a pre-release of v2020.09. It contains changes to garage since v2020.06.0.
This pre-release makes cutting-edge features available via PyPI, but comes with no promises of support or bug fixes. If you encounter problems with this release, you are encouraged to either install from master or revert to the v2020.06 release.
For information on what to expected in garage v2020.09, see the release notes for v2020.06.0
2020.06.2
This is a maintenance release for 2020.06.
- Fixed
- Better parameters for example
her_ddpg_fetchreach
(#1763) - Ensure determinism in TensorFlow by using
tfp.SeedStream
(#1821) - Broken rendering of MuJoCo environments to pixels in the NVIDIA Docker container (#1838)
- Enable cudnn in the NVIDIA Docker container (#1840)
- Bug in
DiscreteQfDerivedPolicy
in which parameters were not returned (#1847) - Populate
TimeLimit.truncated
at every step when usinggym.Env
(#1852) - Bug in which parameters where not copied when TensorFlow primitives are
clone()
ed (#1855) - Typo in the
Makefile
targetrun-nvidia
(#1914)
- Better parameters for example
2020.09.0rc2
This is a pre-release of v2020.09. It contains changes to garage since v2020.06.0.
This pre-release makes cutting-edge features available via PyPI, but comes with no promises of support or bug fixes. If you encounter problems with this release, you are encouraged to either install from master or revert to the v2020.06 release.
For information on what to expected in garage v2020.09, see the release notes for v2020.06.0
2019.10.3
2020.06.1
2020.09.0rc1
This is a pre-release of v2020.09.0rc1. It contains changes to garage since v2020.06.0.
This pre-release makes cutting-edge features available via PyPI, but comes with no promises of support or bug fixes. If you encounter problems with this release, you are encouraged to either install from master or revert to the v2020.06 release.
For information on what to expected in garage v2020.09, see the release notes for v2020.06.0
2019.10.2
This is a maintenance release for 2019.10.
Fixed
- Use a GitHub Token in the CI to retrieve packages to avoid hitting GitHub API rate limit (#1250)
- Avoid installing dev extra dependencies during the conda check (#1296)
- Install
dm_control
from PyPI (#1406) - Pin tfp to 0.8.x to avoid breaking pipenv (#1480)
- Force python 3.5 in CI (#1522)
- Separate terminal and completion signal in vectorized sampler (#1581)
- Disable certicate check for roboti.us (#1595)
- Fix
advantages
shape incompute_advantage()
in torch tree (#1209) - Fix plotting using tf.plotter (#1292)
- Fix duplicate window rendering when using garage.Plotter (#1299)
- Fix setting garage.model parameters (#1363)
- Fix two example jupyter notebook (#1584)
- Fix collecting samples in
RaySampler
(#1583)