diff --git a/lib/Dialect/mhlo/transforms/hlo_legalize_to_lhlo.cc b/lib/Dialect/mhlo/transforms/hlo_legalize_to_lhlo.cc
index 6710d37..24f12d4 100644
--- a/lib/Dialect/mhlo/transforms/hlo_legalize_to_lhlo.cc
+++ b/lib/Dialect/mhlo/transforms/hlo_legalize_to_lhlo.cc
@@ -87,6 +87,32 @@ Value InsertAlloc(Location loc, OpResult result,
   return alloc;
 }
 
+/// Converts the results of the operation `op` to memref types and append them
+/// to the `results` vector.
+LogicalResult ConvertResults(Operation* op, SmallVectorImpl<Value>& results,
+                             ConversionPatternRewriter& rewriter) {
+  for (auto result : llvm::enumerate(op->getResults())) {
+    RankedTensorType resultType =
+        result.value().getType().dyn_cast<RankedTensorType>();
+    if (!resultType) return failure();
+
+    if (resultType.hasStaticShape()) {
+      results.push_back(InsertAlloc(op->getLoc(), result.value(), &rewriter));
+      continue;
+    }
+    auto shape_type_op = dyn_cast<InferShapedTypeOpInterface>(op);
+    if (!shape_type_op) return failure();
+
+    SmallVector<Value, 1> results_shape;
+    auto status = shape_type_op.reifyReturnTypeShapes(rewriter, results_shape);
+    if (failed(status)) return failure();
+    results.push_back(
+        InsertDynamicAllocAndDealloc(op->getLoc(), result.value(),
+                                     results_shape[result.index()], &rewriter));
+  }
+  return success();
+}
+
 template <typename HloOpTy>
 class HloToLhloOpConverter : public BaseOpConversion<HloOpTy> {
  public:
@@ -95,29 +121,8 @@ class HloToLhloOpConverter : public BaseOpConversion<HloOpTy> {
       HloOpTy hloOp, ArrayRef<Value> operands,
       ConversionPatternRewriter& rewriter) const final {
     Operation* op = hloOp.getOperation();
-    const auto& original_results = op->getResults();
     SmallVector<Value, 4> buffer_args(operands.begin(), operands.end());
-    for (auto result : llvm::enumerate(original_results)) {
-      RankedTensorType resultType =
-          result.value().getType().dyn_cast<RankedTensorType>();
-      if (!resultType) {
-        return failure();
-      }
-      if (resultType.hasStaticShape()) {
-        buffer_args.push_back(
-            InsertAlloc(op->getLoc(), result.value(), &rewriter));
-      } else {
-        auto shape_type_op = dyn_cast<InferShapedTypeOpInterface>(op);
-        if (!shape_type_op) return failure();
-
-        SmallVector<Value, 1> results_shape;
-        auto status =
-            shape_type_op.reifyReturnTypeShapes(rewriter, results_shape);
-        if (failed(status)) return failure();
-        buffer_args.push_back(InsertDynamicAllocAndDealloc(
-            op->getLoc(), result.value(), results_shape.front(), &rewriter));
-      }
-    }
+    if (failed(ConvertResults(op, buffer_args, rewriter))) return failure();
     rewriter.create<mhlo::HloToLhloOp<HloOpTy>>(op->getLoc(), llvm::None,
                                                 buffer_args, op->getAttrs());
     rewriter.replaceOp(
@@ -139,28 +144,8 @@ class HloToLhloOpConverter<mhlo::DotOp> : public BaseOpConversion<mhlo::DotOp> {
       mhlo::DotOp hloOp, ArrayRef<Value> operands,
       ConversionPatternRewriter& rewriter) const final {
     Operation* op = hloOp.getOperation();
-    const auto& original_results = op->getResults();
     SmallVector<Value, 2> buffer_args(operands.begin(), operands.end());
-    for (auto result : llvm::enumerate(original_results)) {
-      RankedTensorType resultType =
-          result.value().getType().dyn_cast<RankedTensorType>();
-      if (!resultType) {
-        return failure();
-      }
-      if (resultType.hasStaticShape()) {
-        buffer_args.push_back(
-            InsertAlloc(op->getLoc(), result.value(), &rewriter));
-      } else {
-        SmallVector<Value, 1> results_shape;
-        auto shape_type_op = dyn_cast<InferShapedTypeOpInterface>(op);
-        if (!shape_type_op) return failure();
-        if (failed(
-                shape_type_op.reifyReturnTypeShapes(rewriter, results_shape)))
-          return failure();
-        buffer_args.push_back(InsertDynamicAllocAndDealloc(
-            op->getLoc(), result.value(), results_shape.front(), &rewriter));
-      }
-    }
+    if (failed(ConvertResults(op, buffer_args, rewriter))) return failure();
 
     // TODO(silvasean): Move this helper to MLIR core.
     auto make_elements_attr = [&rewriter](ArrayRef<int64_t> integers) {