- Change in isaaclab_env wrapper to explicitly state GPU for each simulation
- Removing jax cache to support multi-gpu environment launch in MuJoCo Playground
- Removing .train() and .eval() in evaluation and rendering to avoid deadlock in multi-gpu training
- Supporting synchronous normalization for multi-gpu training
This PR includes these changes:
- Fixing a bug in MTBench evaluation
- Add a missing `critic_cls` in `train.py` (resolving an issue https://github.com/younggyoseo/FastTD3/issues/17)
- Updating hyperparameters for MTBench
This PR incorporates MTBench into the current codebase, as a good demonstration that shows how to use FastTD3 for multi-task setup.
- Add support for MTBench along with its wrapper
- Add support for per-task reward normalizer useful for multi-task RL, motivated by BRC paper (https://arxiv.org/abs/2505.23150v1)
