Learning Calibratable Policies using Programmatic Style-Consistency (arXiv)
Code is written in Python 3.7.4 and PyTorch v.1.0.1. Will be updated for PyTorch 1.3 in the future.
Train models with:
$ python run_single.py -d <device id> --config_dir <config folder name>
Not specifying a device will use CPU by default. See JSONs in configs\
to see examples of config files.
$ python run_single.py --config_dir test --test_code
should run without errors.
$ python scripts/check_dynamics_loss.py -f <config folder name>
will compute and visualize the dynamics model error, where applicable.
$ python scripts/compute_stylecon_ctvae.py -f <config folder name>
will compute the style-consistency.
$ python scripts/visualize_samples_ctvae.py -f <config folder name>
will sample and save trajectories for each label class.