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[mlir][sparse] emergency fix after constant -> arith.constant change 

Reviewed By: Mogball

Differential Revision: https://reviews.llvm.org/D111743
This commit is contained in:
Aart Bik 2021-10-13 10:13:44 -07:00
parent 92bec0e970
commit a652e5b53a
3 changed files with 8 additions and 8 deletions
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4
mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
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@ -225,9 +225,9 @@ static LogicalResult verify(InitOp op) {
for (unsigned i = 0; i < rank; i++) {
if (shape[i] == ShapedType::kDynamicSize)
continue;
auto constantOp = op.sizes()[i].getDefiningOp<ConstantOp>();
auto constantOp = op.sizes()[i].getDefiningOp<arith::ConstantOp>();
if (!constantOp ||
constantOp.getValue().cast<IntegerAttr>().getInt() != shape[i])
constantOp.value().cast<IntegerAttr>().getInt() != shape[i])
return op.emitError("unexpected mismatch with static dimension size ")
<< shape[i];
}

4
mlir/test/Dialect/SparseTensor/invalid.mlir
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@ -37,8 +37,8 @@ func @invalid_init_rank(%arg0: index) -> tensor<?xf32, #SparseVector> {
#SparseMatrix = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
func @invalid_init_size() -> tensor<?x10xf32, #SparseMatrix> {
%c10 = constant 10 : index
%c20 = constant 20 : index
%c10 = arith.constant 10 : index
%c20 = arith.constant 20 : index
// expected-error@+1 {{unexpected mismatch with static dimension size 10}}
%0 = sparse_tensor.init [%c10, %c20] : tensor<?x10xf32, #SparseMatrix>
return %0 : tensor<?x10xf32, #SparseMatrix>

8
mlir/test/Dialect/SparseTensor/roundtrip.mlir
View File

@ -16,13 +16,13 @@ func @sparse_new(%arg0: !llvm.ptr<i8>) -> tensor<128xf64, #SparseVector> {
#SparseMatrix = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
// CHECK-LABEL: func @sparse_init()
// CHECK-DAG: %[[C16:.*]] = constant 16 : index
// CHECK-DAG: %[[C32:.*]] = constant 32 : index
// CHECK-DAG: %[[C16:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[C32:.*]] = arith.constant 32 : index
// CHECK: %[[T:.*]] = sparse_tensor.init[%[[C16]], %[[C32]]] : tensor<?x32xf64, #{{.*}}>
// CHECK: return %[[T]] : tensor<?x32xf64, #{{.*}}>
func @sparse_init() -> tensor<?x32xf64, #SparseMatrix> {
%d1 = constant 16 : index
%d2 = constant 32 : index
%d1 = arith.constant 16 : index
%d2 = arith.constant 32 : index
%0 = sparse_tensor.init [%d1, %d2] : tensor<?x32xf64, #SparseMatrix>
return %0 : tensor<?x32xf64, #SparseMatrix>
}