Releases
0.9.0
[0.9.0] - 2023-01-13
Added
Support for Farama Gymnasium interface
Wrapper for robosuite environments
Weights & Biases integration (by @juhannc )
Set the running mode (training or evaluation) of the agents
Allow clipping the gradient norm for DDPG, TD3 and SAC agents
Initialize model biases
Add RNN (RNN, LSTM, GRU and any other variant) support for A2C, DDPG, PPO, SAC, TD3 and TRPO agents
Allow disabling training/evaluation progressbar
Farama Shimmy and robosuite examples
KUKA LBR iiwa real-world example
Changed
Forward model inputs as a Python dictionary [breaking change ]
Returns a Python dictionary with extra output values in model calls [breaking change ]
Adopt the implementation of terminated
and truncated
over done
for all environments
Fixed
Omniverse Isaac Gym simulation speed for the Franka Emika real-world example
Call agents' method record_transition
instead of parent method
to allow storing samples in memories during evaluation
Move TRPO policy optimization out of the value optimization loop
Access to the categorical model distribution
Call reset only once for Gym/Gymnasium vectorized environments
Removed
Deprecated method start
in trainers
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