Incremental Hyperparameter optimization in GPy classifier

Is there any way to do an epoch-wise incremental gradient descent hyperparameter optimization for the Gaussian Process class GPy.core.gp under the GPy package? I am familiar with the complete optimization function model.optimize(), but unable to find any clue for incremental learning, as is supported by partial_fit() methods in sklearn estimators.

Any clue or help in this is highly appreciated.

Thanks in advance!