Top-level indices part 2: empty vector indices

Follow up to #3940

We are trying to make it possible to keep indices even though we don't have enough data to actually train them. In an earlier PR, we are adding a train: bool parameter to let the user choose whether they want to defer training an index. If train=False, then we just create an empty index and it will show num_indexed_rows: 0 in stats. They can later call optimize_indices() to do the actual training.

Vector indices are more complex because of IVF partitions, since we need a minimum amount of data to create them.

Here is the behavior I think we want:

1. Can pass train=False to create an empty index. No IVF or PQ will be trained. Will save metadata as empty array.
2. If you call create_index(..., train=True) or optimize_indices():
   • < 256 non-null vectors -> same as train=False
   • 256 <= number of non-null vectors < num_partitions * 256 => train on smaller number of partitions
   • number of non-null vectors >= num_partitions * 256 -> train full index