llvm-project

75573041 - [mlir][linalg] Update vectorization of linalg.pack (#163539)

[mlir][linalg] Update vectorization of linalg.pack (#163539) This patch changes `vectorizeAsTensorPackOp` to require users to specify **all** write-side vector sizes for `linalg.pack` (not just the outer dimensions). This makes `linalg.pack` vectorization consistent with `linalg.unpack` (see https://github.com/llvm/llvm-project/pull/149293 for a similar change). Conceptually, `linalg.pack` consists of these high-level steps: * **Read** from the source tensor using `vector.transfer_read`. * **Re-associate** dimensions of the read value, as specified by the op (via `vector.shape_cast`) * **Transpose** the re-associated value according to the permutation in the `linalg.pack` op (via `vector.transpose`). * **Write** the result into the destination tensor via `vector.transfer_write`. Previously, the vector sizes provided by the user were interpreted as write-vector-sizes for PackOp **_outer_** dims (i.e. the final step above). These were used to: * Infer read-vector-sizes using the `inner_tiles` attribute of PackOp. * Deduce vector sizes for the transpose and shape cast operations. * Ultimately determine the vector shape for the read. However, this logic breaks when one or more tile sizes are dynamic (*). In such cases, `vectorizePackOpPrecondition` would currently fail (see `@pack_with_dynamic_dims_and_dynamic_inner_tile` added in this PR - without this change it will crash). This patch updates the contract: users now directly specify _all_ the "write-vector-sizes", which inherently encode all inner tile sizes - including dynamic ones. It becomes the user's responsibility to provide valid sizes. In practice, since `linalg.pack` is typically constructed, tiled, and vectorized by the same transformation pipeline, the necessary "write-vector-sizes" should be recoverable. Notes for reviewers: * See test updates for user-facing impact. * Review `vectorizeAsTensorPackOp` as a new implementation rather than a diff. * Comments and variable names were updated to align with `vectorizeAsTensorUnPackOp`. (*) As a concrete example, "scalable" tile sizes are represent as dynamic values. Note, support for "scalable" vectorisation will be added in a separate PR.