Plumb through tensor.pack e2e execution for llvm-cpu backend.

[hanhanW]

All the tensor.pack ops with static inner_tile_sizes are vectorized, which are all covered by e2e tests.

[MaheshRavishankar]

Can we make this test separate so that it is tested on vmvx path where it is used and vectorization isnt important.

[MaheshRavishankar]

Mostly looks good. Nice! Just a comment on the tests.

[hanhanW]

Can we make this test separate so that it is tested on vmvx path where it is used and vectorization isnt important.

Supporting the op on VMVX is my next step. Although vectorization is not used on VMVX side, it requires a memref version of pack/unpack. In this PR, I'd like to make sure that tensor version covers all the cases for llvm-cpu side.

I'm preparing a separate PR that will bufferize tensor.pack/unpack into iree_linalg_ext.pack/unpack; will enable the test for vmvx. After that, I'll switch data tiling approach to use tensor.pack/unpack version, and deprecate iree_linalg_ext ops and transforms as much as possible. WDYT?

[MaheshRavishankar]

Can we make this test separate so that it is tested on vmvx path where it is used and vectorization isnt important.

Supporting the op on VMVX is my next step. Although vectorization is not used on VMVX side, it requires a memref version of pack/unpack. In this PR, I'd like to make sure that tensor version covers all the cases for llvm-cpu side.

I'm preparing a separate PR that will bufferize tensor.pack/unpack into iree_linalg_ext.pack/unpack; will enable the test for vmvx. After that, I'll switch data tiling approach to use tensor.pack/unpack version, and deprecate iree_linalg_ext ops and transforms as much as possible. WDYT?

Sounds good!