DPKeras optimizer fails when num_microbatches is None (default)

Hi,

first of all, thanks for continuing to expand and improve this amazing repo. I've noticed a small issue with the usage of the new DPKeras* optimizers (the non vectorized version). Running with the default num_microbatches=None gives the following error:

TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, -1]. Consider casting elements to a supported type.

I think that this is due to the fact that self._num_microbatches is assigned the input value None. All other DP optimizers (vectorized keras ones included) contains a check for this situation (here, for example), which updates a None self._num_microbatches to the right value. This check is missing in dp_optimizer_keras, hence the error.

thanks a lot,
Matteo

Start by inspecting the non-vectorized DPKeras optimizer implementation in dp_optimizer_keras and compare its handling of num_microbatches with the referenced dp_optimizer.py check. Verify the default num_microbatches=None path no longer produces the reported TypeError and confirm existing optimizer behavior remains intact.