Keras, best way to save state when optimizing
You could create a tar archive containing the weights and the architecture, as well as a pickle file containing the optimizer state returned by model.optimizer.get_state().
I was just wondering what is the best way to save the state of a model while it it optimizing.  I want to do this so I can run it for a while, save it, and come back to it some time later.  I know there is a function to save the weights and another function to save the model as JSON.  During learning I would need to save both the weights and the parameters of the model.  This includes parameters like the momentum and learning rate.  Is there a way to save both the model and weights in the same file.  I read that it is not considered good practice to use pickle.  Also would the momentums for the graident decent be included with the models JSON or in the weights?