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[mlir][Linalg] Support lowerUnPack for identity out_dims_perm cases. #79594

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Merged
merged 1 commit into from
Jan 26, 2024
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[mlir][Linalg] Support lowerUnPack for identity out_dims_perm cases. #79594

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7 changes: 5 additions & 2 deletions mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -377,8 +377,11 @@ FailureOr<LowerPackResult> linalg::lowerPack(RewriterBase &rewriter,
FailureOr<LowerUnPackOpResult> linalg::lowerUnPack(RewriterBase &rewriter,
tensor::UnPackOp unPackOp) {
// 1. Filter out NYI cases.
if (!unPackOp.getOuterDimsPerm().empty())
return rewriter.notifyMatchFailure(unPackOp, "outer dims perm NYI");
if (!unPackOp.getOuterDimsPerm().empty() &&
!isIdentityPermutation(unPackOp.getOuterDimsPerm())) {
return rewriter.notifyMatchFailure(unPackOp,
"non-identity outer dims perm NYI");
}

Location loc = unPackOp->getLoc();
OpBuilder::InsertionGuard g(rewriter);
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35 changes: 35 additions & 0 deletions mlir/test/Dialect/Linalg/transform-lower-pack.mlir
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Expand Up @@ -163,6 +163,41 @@ module attributes {transform.with_named_sequence} {

// -----

// CHECK-LABEL: func.func @unpack_with_identity_outer_dims_perm(
func.func @unpack_with_identity_outer_dims_perm(%arg0: tensor<17x2x16x16x32x8xf32>, %arg1: tensor<129x47x16x16xf32>) -> tensor<129x47x16x16xf32> {
%cst_0 = arith.constant 0.0 : f32
// CHECK-SAME: %[[ARG0:.*]]: tensor<17x2x16x16x32x8xf32>, %[[ARG1:.*]]: tensor<129x47x16x16xf32>
// CHECK: %[[EMPTY:.*]] = tensor.empty() : tensor<17x8x2x32x16x16xf32>
// CHECK: %[[TRAN:.*]] = linalg.transpose
// CHECK-SAME: ins(%[[ARG0]] : tensor<17x2x16x16x32x8xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<17x8x2x32x16x16xf32>)
// CHECK-SAME: permutation = [0, 5, 1, 4, 2, 3]
// CHECK: %[[CLP:.*]] = tensor.collapse_shape %[[TRAN]] {{\[}}[0, 1], [2, 3], [4], [5]]
// CHECK-SAME: : tensor<17x8x2x32x16x16xf32> into tensor<136x64x16x16xf32>
// CHECK: %[[SLICE:.*]] = tensor.extract_slice %[[CLP]][0, 0, 0, 0] [129, 47, 16, 16] [1, 1, 1, 1]
// CHECK-SAME: : tensor<136x64x16x16xf32> to tensor<129x47x16x16xf32>
// CHECK: linalg.copy ins(%[[SLICE]] : tensor<129x47x16x16xf32>)
// CHECK-SAME: outs(%[[ARG1]] : tensor<129x47x16x16xf32>)
%unpack = tensor.unpack %arg0 outer_dims_perm = [0, 1, 2, 3] inner_dims_pos = [1, 0] inner_tiles = [32, 8] into %arg1
: tensor<17x2x16x16x32x8xf32> -> tensor<129x47x16x16xf32>
return %unpack : tensor<129x47x16x16xf32>
}

module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%module_op: !transform.any_op {transform.readonly}) {
%unpack = transform.structured.match ops{["tensor.unpack"]} in %module_op
: (!transform.any_op) -> !transform.op<"tensor.unpack">
transform.structured.lower_unpack %unpack : (!transform.op<"tensor.unpack">)
-> (!transform.op<"tensor.empty">,
!transform.op<"linalg.transpose">,
!transform.op<"tensor.collapse_shape">,
!transform.op<"tensor.extract_slice">)
transform.yield
}
}

// -----

// When an unpack is a plain 'unpad', lower it to a simple extract_slice.
// CHECK-LABEL: func.func @unpack_as_pad(
func.func @unpack_as_pad(%arg0: tensor<1x1x1x1x136x64x16x16xf32>, %arg1: tensor<129x47x16x16xf32>) -> tensor<129x47x16x16xf32> {
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