diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp
@@ -358,6 +358,14 @@
   }
 };
 
+static Value allocaIndices(ConversionPatternRewriter &rewriter, Location loc,
+                           int64_t rank) {
+  auto indexTp = rewriter.getIndexType();
+  auto memTp = MemRefType::get({ShapedType::kDynamicSize}, indexTp);
+  Value arg = rewriter.create<ConstantOp>(loc, rewriter.getIndexAttr(rank));
+  return rewriter.create<memref::AllocaOp>(loc, memTp, ValueRange{arg});
+}
+
 /// Sparse conversion rule for the convert operator.
 class SparseTensorConvertConverter : public OpConversionPattern<ConvertOp> {
   using OpConversionPattern::OpConversionPattern;
@@ -412,13 +420,9 @@
     // loop is generated by genAddElt().
     Location loc = op->getLoc();
     ShapedType shape = resType.cast<ShapedType>();
-    auto memTp =
-        MemRefType::get({ShapedType::kDynamicSize}, rewriter.getIndexType());
     Value perm;
     Value ptr = genNewCall(rewriter, op, encDst, 2, perm);
-    Value arg = rewriter.create<ConstantOp>(
-        loc, rewriter.getIndexAttr(shape.getRank()));
-    Value ind = rewriter.create<memref::AllocaOp>(loc, memTp, ValueRange{arg});
+    Value ind = allocaIndices(rewriter, loc, shape.getRank());
     SmallVector<Value> lo;
     SmallVector<Value> hi;
     SmallVector<Value> st;