splitting of training examples into the mini batch: what to do with the rest tiny mini-batch?
A few basic approaches come to mind. It depends on your context and intention which might work best for you. Here are some ideas assuming that working with a partial batch is not an option:


Drop the remainder. This might make more sense when you have many complete batches, and you consider the set of examples to be enough.
Complement the final batch with duplicated samples from the other batches. E.g. randomly get one example from each batch.
If something like that is feasible at all, generate additional (possibly synthetic) examples to complete the final batch.