Currently, the Linalg vectorizer disallows non-trailing parallel
dimensions to be scalable, e.g., `vector_sizes [[8], 1]` (*), for cases
like:
```mlir
%0 = linalg.fill ins(%arg0 : f32) outs(%A : tensor<?x?xf32>) -> tensor<?x?xf32>
```
This restriction exists to avoid generating "scalable" arrays of
aggregates, which LLVM does not support (multi-dim vectors are lowered
into arrays of aggregates at the LLVM level).
This patch relaxes that restriction when the trailing parallel vector
dimension is `1`, e.g., for `vector_sizes [[8], 1]`. Such cases are safe
since trailing unit dimensions can be collapsed. This relaxation is
necessary to support scalable vectorization for tensor.pack, where inner
tile sizes are `[8]` (scalable) and `1` (scalar).
(*) Transform Dialect notation
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