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[mlir][linalg] Fix invalid IR in Linalg op fusion #74425

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24 changes: 7 additions & 17 deletions mlir/lib/Dialect/Linalg/Transforms/Fusion.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -144,27 +144,17 @@ static LinalgOp fuse(OpBuilder &b, LinalgOp producer,
b, loc, producer, getTiledOperands(producer), ivs, tileSizes, sizeBounds,
/**omitPartialTileCheck=*/false));

// Iterate over the results in order.
// Extract the subtensor type from the linearized range.
// Since we do not enforce any canonicalizations on the fly, this is always
// fully dynamic at construction time.
// Take result types from the tiled init operands.
MutableOperandRange producerDpsInits = producer.getDpsInitsMutable();
SmallVector<Type, 4> resultTypes;
resultTypes.reserve(producer->getNumResults());
for (Value operand : producer.getDpsInits()) {
auto tensorType = dyn_cast<RankedTensorType>(operand.getType());
if (!tensorType)
continue;
unsigned rank = tensorType.getRank();
SmallVector<int64_t, 4> staticOffsetsVector(
rank, ShapedType::kDynamic);
SmallVector<int64_t, 4> staticSizesVector(rank, ShapedType::kDynamic);
SmallVector<int64_t, 4> staticStridesVector(
rank, ShapedType::kDynamic);
resultTypes.push_back(tensor::ExtractSliceOp::inferResultType(
tensorType, staticOffsetsVector, staticSizesVector,
staticStridesVector));
int64_t firstInitOperandIdx =
static_cast<OperandRange>(producerDpsInits).getBeginOperandIndex();
for (int64_t i = 0, e = producer->getNumResults(); i < e; ++i) {
resultTypes.push_back(clonedShapes[firstInitOperandIdx + i].getType());
}

// Clone the producer with new operands and result types.
LinalgOp clonedOp = clone(b, producer, resultTypes, clonedShapes);

// Shift all IndexOp results by the tile offset.
Expand Down