[mlir][vector] Update `CombineContractBroadcastMask` (#140050)

This patch updates `CombineContractBroadcastMask` to inherit from
`MaskableOpRewritePattern`, enabling it to handle masked
`vector.contract` operations. The pattern rewrites:
```mlir
  %a = vector.broadcast %a_bc
  %res vector.contract %a_bc, %b, ...
```

into:
```mlir
  // Move the broadcast into vector.contract (by updating the indexing
  // maps)
  %res vector.contract %a, %b, ...
```

The main challenge is supporting cases where the pattern drops a leading
unit dimension. For example:
```mlir
func.func @contract_broadcast_unit_dim_reduction_masked(
    %arg0 : vector<8x4xi32>,
    %arg1 : vector<8x4xi32>,
    %arg2 : vector<8x8xi32>,
    %mask: vector<1x8x8x4xi1>) -> vector<8x8xi32> {

  %0 = vector.broadcast %arg0 : vector<8x4xi32> to vector<1x8x4xi32>
  %1 = vector.broadcast %arg1 : vector<8x4xi32> to vector<1x8x4xi32>
  %result = vector.mask %mask {
    vector.contract {
      indexing_maps = [#map0, #map1, #map2],
      iterator_types = ["reduction", "parallel", "parallel", "reduction"],
      kind = #vector.kind<add>
    } %0, %1, %arg2 : vector<1x8x4xi32>, vector<1x8x4xi32> into vector<8x8xi32>
  } : vector<1x8x8x4xi1> -> vector<8x8xi32>

  return %result : vector<8x8xi32>
}
```

Here, the leading unit dimension is dropped. To handle this, the mask is
cast to the correct shape using a `vector.shape_cast`:

```mlir
func.func @contract_broadcast_unit_dim_reduction_masked(
    %arg0: vector<8x4xi32>,
    %arg1: vector<8x4xi32>,
    %arg2: vector<8x8xi32>,
    %arg3: vector<1x8x8x4xi1>) -> vector<8x8xi32> {

  %mask_sc = vector.shape_cast %arg3 : vector<1x8x8x4xi1> to vector<8x8x4xi1>
  %res = vector.mask %mask_sc {
    vector.contract {
      indexing_maps = [#map, #map1, #map2],
      iterator_types = ["parallel", "parallel", "reduction"],
      kind = #vector.kind<add>
    } %arg0, %arg1, %mask_sc : vector<8x4xi32>, vector<8x4xi32> into vector<8x8xi32>
  } : vector<8x8x4xi1> -> vector<8x8xi32>

  return %res : vector<8x8xi32>
}
```

While this isn't ideal - since it introduces a `vector.shape_cast` that
must be cleaned up later - it reflects the best we can do once the input
reaches `CombineContractBroadcastMask`. A more robust solution may
involve simplifying the input earlier. I am leaving that as  a TODO for
myself to explore this further. Posting this now to unblock downstream
work.

LIMITATIONS

Currently, this pattern assumes:
* Only leading dimensions are dropped in the mask.
* All dropped dimensions must be unit-sized.