The code is built off of SUPE with inspiration from SkiMo.

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Before setting up the environment, make sure that MuJoCo and the dependencies for mujoco-py are installed (https://github.com/openai/mujoco-py). Then, run the create_env.sh script, which will create the conda environment and download the pretrained checkpoints.

Pretrained checkpoints for all environments are downloaded in create_env.sh. Below are the commands used to generate the checkpoints.

python run_opal.py --env_name=kitchen-mixed-v0 --seed=1 --vision=False

Replace the env_name with kitchen-partial-v0 and kitchen-complete-v0 to test the other tasks.

python train_finetuning_mosaud.py --config.backup_entropy=False --config.num_min_qs=2 --offline_relabel_type=pred --use_rnd_offline=True --use_rnd_online=True --env_name=kitchen-mixed-v0 --seed=1 --config.init_temperature=1.0