[Mlir-commits] [mlir] [mlir][linalg] Allow pack consumer fusion if the tile size is greater than dimension size. (PR #149438)

[Han-Chung Wang]

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@@ -451,6 +451,57 @@ module attributes {transform.with_named_sequence} {
 
 // -----
 
+#map = affine_map<(d0) -> (-d0 + 4, 16)>
+func.func @fuse_pack_consumer_if_single_iteration(%arg0: tensor<4x4xf32>) -> tensor<1x4x16x1xf32> {
+  %0 = tensor.empty() : tensor<1x4x16x1xf32>
+  %1 = tensor.empty() : tensor<4x4xf32>
+  %2 = scf.forall (%arg1) = (0) to (4) step (16) shared_outs(%arg2 = %1) -> (tensor<4x4xf32>) {
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hanhanW wrote:

If this is `scf.for`, we can fold them away. What I'm not sure is the case that distribution mapping attributes are present. I think the semantic is that you'll need to distribute the computation using the core_id/thread_id. It may be correct to still fold it away though.

https://github.com/llvm/llvm-project/pull/149438