This adds a new transform `eliminateVectorMasks()` which aims at
removing scalable `vector.create_masks` that will be all-true at
runtime. It attempts to do this by simply pattern-matching the mask
operands (similar to some canonicalizations), if that does not lead to
an answer (is all-true? yes/no), then value bounds analysis will be used
to find the lower bound of the unknown operands. If the lower bound is
>= to the corresponding mask vector type dim, then that dimension of the
mask is all true.
Note that the pattern matching prevents expensive value-bounds analysis
in cases where the mask won't be all true.
For example:
```mlir
%mask = vector.create_mask %dynamicValue, %c2 : vector<8x4xi1>
```
From looking at `%c2` we can tell this is not going to be an all-true
mask, so we don't need to run the value-bounds analysis for
`%dynamicValue` (and can exit the transform early).
Note: Eliminating create_masks here means replacing them with all-true
constants (which will then lead to the masks folding away).
