Store model after training

MIT-REALM / neural_clbf

Toolkit for learning controllers based on robust control Lyapunov barrier functions

BSD 3-Clause "New" or "Revised" License

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Store model after training #6

Closed KehanLong closed 1 year ago

KehanLong commented 1 year ago

Hi,

I am trying to define new examples as you suggested by writing new control-affine systems and training. However, I did not find a way of storing the model parameters after training. (I tried to check the train_inverted_pendulum.py script but it seems that it does not store the model parameters).

Any help would be appreciated!