Tensorflow: Saving optimizer state (adagrad/momentum/etc.)

Hey everybody,

Last week I asked this question on stackoverflow: https://stackoverflow.com/questions/40547198/saving-the-state-of-the-adagrad-algorithm-in-tensorflow .
My problem is that I want to save the state of the optimizer (in my case the adagrad accumulators) so I can stop my learning and continue whenever I want.

Unless I'm mistaken the state of the optimizer can't be saved (you cant pass an optimizer to a tf.train.Saver, right?). A quick (hacky?) solution for me might be is calling Optimizer.get_slot_names() and save the op of each slot.
The next problem would be putting this op back in the slots, as I don't think there is a set_slot(name,op) at the moment.

So my questions are:

• Am I right that this is currently impossible?
• Do we want to have a set_slot(name,op) function in the Optimizer class? (I am willing to help out with this)
• Do we want to be able to pass an optimizer to a Saver object?