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[mlir][Linalg] Fix insertion point in comprehensive bufferization

This commit is contained in:
Nicolas Vasilache 2021-10-14 15:20:31 +00:00
parent 849b36bf6f
commit 0eeaad3012
2 changed files with 22 additions and 1 deletions
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2
mlir/lib/Dialect/Linalg/Transforms/ComprehensiveBufferize.cpp
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@ -1369,7 +1369,7 @@ createNewAllocDeallocPairForShapedValue(OpBuilder &b, Location loc,
b.setInsertionPointToStart(bbArg.getOwner());
loc = bbArg.getOwner()->getParentOp()->getLoc();
} else {
b.setInsertionPointAfter(shapedValue.getDefiningOp());
b.setInsertionPoint(shapedValue.getDefiningOp());
loc = shapedValue.getDefiningOp()->getLoc();
}

21
mlir/test/Dialect/Linalg/comprehensive-module-bufferize.mlir
View File

@ -755,3 +755,24 @@ func @tensor_cast_not_in_place(
return %r1 : tensor<?xf32>
}
// -----
//===----------------------------------------------------------------------===//
// Insertion point cases.
//===----------------------------------------------------------------------===//
/// These tests just check the produced IR is valid and does not have dominance
/// errors in the def-use chains.
// CHECK-LABEL: func @dominance_violation_bug_1
func @dominance_violation_bug_1(%A : tensor<?x?xf32>, %idx : index) -> tensor<?x?xf32> {
%f0 = arith.constant 0.0 : f32
%sA = tensor.extract_slice %A[0, 0][%idx, %idx][1, 1] : tensor<?x?xf32> to tensor<?x?xf32>
%ssA = tensor.extract_slice %sA[0, 0][4, 4][1, 1] : tensor<?x?xf32> to tensor<4x4xf32>
%FA = linalg.fill(%f0, %ssA) : f32, tensor<4x4xf32> -> tensor<4x4xf32>
%rsA = tensor.insert_slice %FA into %sA[0, 0][4, 4][1, 1] : tensor<4x4xf32> into tensor<?x?xf32>
%rA = tensor.insert_slice %rsA into %A[0, 0][%idx, %idx][1, 1] : tensor<?x?xf32> into tensor<?x?xf32>
return %rA : tensor<?x?xf32>
}