I have gathered that train.py saves the actor_critic at a specified interval. Is there an easy way to load, run, and visualize the saved actor_critic?
If you mean to just load it and visualize it in the standard GUI, then you should be able to do it using the
--test flag like this (the method is different if you are using the rl_games package):
python train.py --task=FrankaCabinet --num_envs=1 --test --resume=1000 --seed=1
--resume flag should load the weights that were saved after 1000 iterations and is stored in your
python/rlgpu/logs/ directory (in this case there should be a
FrankaCabinet directory full of trained models.
If you have used the
--logdir flag to save the weights elsewhere you would want to use it again here to specify where the code should find your stored weights.
If you want an overview of the available flags, check the
python/rlgpu/utils/config.py script or run
python train.py --help.
Perfect, thanks so much.
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