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[mlir][Vector] Fix an assertion on failing cast in vector-transfer-flatten-patterns #86030

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Merged
merged 6 commits into from
Mar 25, 2024
Merged

[mlir][Vector] Fix an assertion on failing cast in vector-transfer-flatten-patterns #86030

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afc2639
Added a dynamic check for VectorType.
bviyer Mar 20, 2024
a99587b
Added a test
bviyer Mar 21, 2024
aa83879
Added test into the correct file
bviyer Mar 22, 2024
add5ceb
Added the changes requested by Andrej
bviyer Mar 25, 2024
0908cf6
Added comment
bviyer Mar 25, 2024
8a7633e
Fixed the test as requested by Andrej
bviyer Mar 25, 2024
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4 changes: 2 additions & 2 deletions mlir/lib/Dialect/Vector/Transforms/VectorLinearize.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -22,9 +22,9 @@ using namespace mlir;
static bool isLessThanTargetBitWidth(Operation *op, unsigned targetBitWidth) {
auto resultTypes = op->getResultTypes();
for (auto resType : resultTypes) {
VectorType vecType = cast<VectorType>(resType);
VectorType vecType = dyn_cast<VectorType>(resType);
// Reject index since getElementTypeBitWidth will abort for Index types.
if (vecType.getElementType().isIndex())
if (!vecType || vecType.getElementType().isIndex())
return false;
unsigned trailingVecDimBitWidth =
vecType.getShape().back() * vecType.getElementTypeBitWidth();
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13 changes: 13 additions & 0 deletions mlir/test/Dialect/Vector/linearize.mlir
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Expand Up @@ -90,3 +90,16 @@ func.func @test_index_no_linearize(%arg0: vector<2x2xindex>, %arg1: vector<2x2xi
%0 = arith.addi %arg0, %arg1 : vector<2x2xindex>
return %0 : vector<2x2xindex>
}

// -----

// vectorizable operation (arith.mulf) with tensor result types.

func.func @nonvec_result(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> (tensor<2x2xf32>, tensor<2x2xf32>) {
// CHECK: %[[MULF:.*]] = arith.mulf %arg0, %arg1 : tensor<2x2xf32>
// CHECK128: %[[MULF:.*]] = arith.mulf %arg0, %arg1 : tensor<2x2xf32>
// CHECK0: %[[MULF:.*]] = arith.mulf %arg0, %arg1 : tensor<2x2xf32>
%0 = arith.mulf %arg0, %arg1 : tensor<2x2xf32>

return %0, %arg0 : tensor<2x2xf32>, tensor<2x2xf32>
}