SciKit Learn: Multilayer perceptron early stopping, restore best weights

In the SciKit documentation of the MLP classifier, there is the early_stopping flag which allows to stop the learning if there is not any improvement in several iterations. However, it does not seem specified if the best weights found are restored or the final weights fo the model are those obtained at the last iteration. If not, is possible to restore the best weights found?