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[mlir][transform] Use LoopInvariant passes in the tileConsumerAndFuseProducersUsingSCF #163222

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[mlir][transform] Use LoopInvariant passes in the tileConsumerAndFuseProducersUsingSCF #163222

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8c3ad61
use -loop-invariant-subset-hoisting in transform fuse.
linuxlonelyeagle Oct 13, 2025
e2d9db3
add pooling_ncw_max_fill_fuse example.
linuxlonelyeagle Oct 13, 2025
414a123
fix test
linuxlonelyeagle Oct 13, 2025
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19 changes: 18 additions & 1 deletion mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@
#include "mlir/Interfaces/TilingInterface.h"
#include "mlir/Rewrite/FrozenRewritePatternSet.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "mlir/Transforms/LoopInvariantCodeMotionUtils.h"
#include "llvm/ADT/ScopeExit.h"
#include "llvm/ADT/TypeSwitch.h"
#include "llvm/Support/Debug.h"
Expand Down Expand Up @@ -1316,7 +1317,15 @@ getUntiledProducerFromSliceSource(OpOperand *source,
ArrayRef<LoopLikeOpInterface> loops) {
std::optional<OpOperand *> destinationIterArg;
assert(!loops.empty() && "expected non empty loops container");

// The `extractOp` may not reside within the innermost loop, calculate the
// distance between it and the last LoopLikeInterfaceOp. Adding this
// `distance` to `loopIt` yields the start of the loop.
auto loopIt = loops.rbegin();
auto parentLoop = source->getOwner()->getParentOfType<LoopLikeOpInterface>();
const LoopLikeOpInterface *it = llvm::find(loops, parentLoop);
int64_t distance = std::distance(loops.begin(), it);
loopIt += (loops.size() - distance - 1);
while (loopIt != loops.rend() && isa<BlockArgument>(source->get())) {
auto iterArg = cast<BlockArgument>(source->get());
auto loop = *loopIt;
Expand Down Expand Up @@ -1347,7 +1356,6 @@ mlir::scf::tileAndFuseProducerOfSlice(

OpBuilder::InsertionGuard g(rewriter);
rewriter.setInsertionPoint(candidateSliceOp);

// 2. Clone the fused producer
// 2a. Compute the destination operands to use for the cloned operation.
SmallVector<Value> origDestinationTensors, clonedOpDestinationTensors;
Expand Down Expand Up @@ -1750,6 +1758,15 @@ mlir::scf::tileConsumerAndFuseProducersUsingSCF(
replacements};
}

// The extract_slice op is created in the innermost loop by default. Using
// `moveLoopInvariantCode` and `hoistLoopInvariantSubsets` improves the
// position of the extract_slice op within the loops, allowing the fuse Op to
// be created in the correct loop.
for (LoopLikeOpInterface loop : loops)
(void)moveLoopInvariantCode(loop);
for (LoopLikeOpInterface loop : loops)
(void)hoistLoopInvariantSubsets(rewriter, loop);

// Since the loop gets potentially replaced during fusion, we need to track
// the mutation of replacement values. To do this, we attach a listener to
// update the replacements as they happen.
Expand Down
47 changes: 44 additions & 3 deletions mlir/test/Interfaces/TilingInterface/tile-and-fuse-using-interface.mlir
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Expand Up @@ -28,9 +28,9 @@ module attributes {transform.with_named_sequence} {
// CHECK: %[[INIT:.+]] = tensor.empty
// CHECK: scf.for %[[IV0:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG0:.+]] = %[[INIT]])
// CHECK-DAG: %[[LHS_TILE:.+]] = tensor.extract_slice %[[ARG0]][%[[IV0]], 0]
// CHECK: scf.for %[[IV1:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG1:.+]] = %[[ITERARG0]])
// CHECK-DAG: %[[LHS_TILE:.+]] = tensor.extract_slice %[[ARG0]][%[[IV0]], 0]
// CHECK-DAG: %[[RHS_TILE:.+]] = tensor.extract_slice %[[ARG1]][0, %[[IV1]]]
// CHECK-DAG: %[[INIT_TILE:.+]] = tensor.extract_slice %[[ITERARG1]][%[[IV0]], %[[IV1]]]
// CHECK: %[[FILL_TILE:.+]] = linalg.fill
Expand Down Expand Up @@ -141,6 +141,7 @@ module attributes {transform.with_named_sequence} {
// CHECK-DAG: %[[INIT0:.+]] = tensor.empty(%[[D0]], %[[D1]])
// CHECK-DAG: %[[D2:.+]] = tensor.dim %[[RHS1]], %[[C1]]
// CHECK: %[[INIT1:.+]] = tensor.empty(%[[D0]], %[[D2]])
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK: scf.for %[[IV:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG:.+]] = %[[INIT1]])
// CHECK-DAG: %[[LHS0_TILE:.+]] = tensor.extract_slice %[[LHS0]][%[[IV]], 0]
Expand All @@ -151,7 +152,6 @@ module attributes {transform.with_named_sequence} {
// CHECK: %[[GEMM0_TILE:.+]] = linalg.matmul
// CHECK-SAME: ins(%[[LHS0_TILE]], %[[RHS0_TILE]] :
// CHECK-SAME: outs(%[[FILL0_TILE]] :
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK-DAG: %[[INIT1_TILE:.+]] = tensor.extract_slice %[[ITERARG]][%[[IV]], 0]
// CHECK: %[[FILL1_TILE:.+]] = linalg.fill
// CHECK-SAME: outs(%[[INIT1_TILE]] :
Expand Down Expand Up @@ -444,6 +444,7 @@ module attributes {transform.with_named_sequence} {
// CHECK-DAG: %[[M:.+]] = tensor.dim %[[ORIG_GEMM2]], %[[C0]]
// CHECK-DAG: %[[N2:.+]] = tensor.dim %[[ORIG_GEMM2]], %[[C1]]
// CHECK-DAG: %[[N3:.+]] = tensor.dim %[[ARG5]], %[[C1]]
// CHECK-DAG: %[[SLICE_ARG5:.+]] = tensor.extract_slice %[[ARG5]][0, 0] [%[[N2]], %[[N3]]]
// CHECK: %[[R0:.+]] = scf.for %[[IV:[a-zA-Z0-9_]+]] =
// CHECK-SAME: iter_args(%[[ARG8:.+]] = %[[ARG6]]) -> (tensor<?x?xf32>) {
// CHECK-DAG: %[[N1:.+]] = tensor.dim %[[ORIG_GEMM1]], %[[C1]]
Expand All @@ -458,7 +459,6 @@ module attributes {transform.with_named_sequence} {
// CHECK-DAG: %[[SLICE_ARG4:.+]] = tensor.extract_slice %[[ARG4]][%[[IV]], 0] [%[[TILE_M]], %[[N2]]]
// CHECK-DAG: %[[TILE_GEMM2:.+]] = linalg.matmul ins(%[[TILE_GEMM1]], %[[SLICE_ARG3]] :
// CHECK-SAME: outs(%[[SLICE_ARG4]] :
// CHECK-DAG: %[[SLICE_ARG5:.+]] = tensor.extract_slice %[[ARG5]][0, 0] [%[[N2]], %[[N3]]]
// CHECK-DAG: %[[SLICE_ARG6:.+]] = tensor.extract_slice %[[ARG8]][%[[IV]], 0] [%[[TILE_M]], %[[N3]]]
// CHECK-DAG: %[[TILE_GEMM3:.+]] = linalg.matmul
// CHECK-SAME: ins(%[[TILE_GEMM2]], %[[SLICE_ARG5]] :
Expand Down Expand Up @@ -688,3 +688,44 @@ module attributes {transform.with_named_sequence} {
// CHECK: }
// CHECK: }

// -----

func.func @pooling_ncw_max_fill_fuse(%input: tensor<?x?x?xf32>, %fake: tensor<?xf32>, %init: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
%cst = arith.constant 0.000000e+00 : f32
%fill = linalg.fill ins(%cst : f32) outs(%init : tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
%res = linalg.pooling_ncw_max {dilations = dense<1> : tensor<1xi64>, strides = dense<1> : tensor<1xi64>}
ins(%input, %fake: tensor<?x?x?xf32>, tensor<?xf32>)
outs(%fill: tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
return %res : tensor<?x?x?xf32>
}

module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(
%arg0: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.pooling_ncw_max"]} in %arg0 : (!transform.any_op) -> !transform.any_op
%a, %b, %c, %d, %e = transform.structured.fuse %0 tile_sizes [1, 16, 1, 1]
: (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
transform.yield
}
}

// CHECK-LABEL: func.func @pooling_ncw_max_fill_fuse(
// CHECK-SAME: %[[INPUT:.*]]: tensor<?x?x?xf32>,
// CHECK-SAME: %[[FAKE:.*]]: tensor<?xf32>,
// CHECK-SAME: %[[INIT:.*]]: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
// CHECK: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK: scf.for %[[IV0:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG0:.+]] = %[[INIT]])
// CHECK: scf.for %[[IV1:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG1:.+]] = %[[ITERARG0]])
// CHECK: scf.for %[[IV2:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG2:.+]] = %[[ITERARG1]])
// CHECK: %[[FILL_EXTRACT:.*]] = tensor.extract_slice %[[ITERARG2]]{{\[}}%[[IV0]], %[[IV1]], %[[IV2]]]
// CHECK: %[[TILED_FILL:.*]] = linalg.fill ins(%[[ZERO]] : f32) outs(%[[FILL_EXTRACT]] : tensor<1x?x1xf32>) -> tensor<1x?x1xf32>
// CHECK: scf.for %[[IV3:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG3:.*]] = %[[ITERARG2]], %[[ITERARG4:.*]] = %[[TILED_FILL]])
// CHECK: %[[TILED_INPUT:.*]] = tensor.extract_slice %[[INPUT]]{{\[}}%[[IV0]], %[[IV1]]
// CHECK: %[[TILED_FAKE:.*]] = tensor.extract_slice %[[FAKE]]{{\[}}%[[IV3]]]
// CHECK: linalg.pooling_ncw_max
// CHECK-SAME: ins(%[[TILED_INPUT]], %[[TILED_FAKE]] :
// CHECK-SAME: outs(%[[ITERARG4]] :
2 changes: 1 addition & 1 deletion mlir/test/Interfaces/TilingInterface/tile-fuse-and-yield-using-interface.mlir
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Expand Up @@ -37,6 +37,7 @@ module attributes {transform.with_named_sequence} {
// CHECK-SAME: %[[INIT1:[a-zA-Z0-9]+]]: tensor<?x?xf32>)
// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK: %[[RESULT:.+]]:2 = scf.for %[[IV:[a-zA-Z0-9]+]] =
// CHECK-SAME: iter_args(%[[ITERARG0:[a-zA-Z0-9]+]] = %[[INIT1]], %[[ITERARG1:[a-zA-Z0-9]+]] = %[[INIT0]])
// CHECK-DAG: %[[LHS0_TILE:.+]] = tensor.extract_slice %[[LHS0]][%[[IV]], 0]
Expand All @@ -47,7 +48,6 @@ module attributes {transform.with_named_sequence} {
// CHECK: %[[GEMM0_TILE:.+]] = linalg.matmul
// CHECK-SAME: ins(%[[LHS0_TILE]], %[[RHS0_TILE]] :
// CHECK-SAME: outs(%[[FILL0_TILE]] :
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK-DAG: %[[INIT1_TILE:.+]] = tensor.extract_slice %[[ITERARG0]][%[[IV]], 0]
// CHECK: %[[FILL1_TILE:.+]] = linalg.fill
// CHECK-SAME: outs(%[[INIT1_TILE]] :
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Interfaces/TilingInterface/tile-fuse-and-yield-using-scfforall.mlir
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Expand Up @@ -37,6 +37,7 @@ module attributes {transform.with_named_sequence} {
// CHECK-SAME: %[[INIT1:[a-zA-Z0-9]+]]: tensor<?x?xf32>)
// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK: %[[RESULT:.+]]:2 = scf.forall (%[[IV:[a-zA-Z0-9]+]]) =
// CHECK-SAME: shared_outs(%[[ITERARG0:[a-zA-Z0-9]+]] = %[[INIT1]], %[[ITERARG1:[a-zA-Z0-9]+]] = %[[INIT0]])
// CHECK-DAG: %[[LHS0_TILE:.+]] = tensor.extract_slice %[[LHS0]][%[[IV]], 0]
Expand All @@ -47,7 +48,6 @@ module attributes {transform.with_named_sequence} {
// CHECK: %[[GEMM0_TILE:.+]] = linalg.matmul
// CHECK-SAME: ins(%[[LHS0_TILE]], %[[RHS0_TILE]] :
// CHECK-SAME: outs(%[[FILL0_TILE]] :
// CHECK-DAG: %[[RHS1_TILE:.+]] = tensor.extract_slice %[[RHS1]][0, 0]
// CHECK-DAG: %[[INIT1_TILE:.+]] = tensor.extract_slice %[[ITERARG0]][%[[IV]], 0]
// CHECK: %[[FILL1_TILE:.+]] = linalg.fill
// CHECK-SAME: outs(%[[INIT1_TILE]] :
Expand Down