* Fix bug in AdvancedSubtensor infer_shape

The underlying utility `indexed_result_shape` was off by 1 in terms of when do the advanced index operations have to be brought to the front of the array.

* The rewrite no longer bails out when dimshuffle affects both unique param dimensions and repeated param dimensions from the size argument. This requires:
  1) Adding broadcastable dimensions to the parameters, which should be "cost-free" and would need to be done in the `perform` method anyway.
  2) Extend size to incorporate implicit batch dimensions coming from the parameters. This requires computing the shape resulting from broadcasting the parameters. It's unclear whether this is less performant, because the `perform` method can now simply broadcast each parameter to the size, instead of having to broadcast the parameters together.
* The rewrite now works with Multivariate RVs
* The rewrite bails out when dimensions are dropped by the Dimshuffle. This case was not correctly handled by the previous rewrite

This allows PyTensor to infer more broadcastable patterns, by placing the casting inside the MakeVector Op