diff --git a/lib/Conversion/TorchToLinalg/DataMovement.cpp b/lib/Conversion/TorchToLinalg/DataMovement.cpp
index add32ff05..a609b1791 100644
--- a/lib/Conversion/TorchToLinalg/DataMovement.cpp
+++ b/lib/Conversion/TorchToLinalg/DataMovement.cpp
@@ -741,15 +741,23 @@ public:
   // `aten.view`.
   static std::pair<SmallVector<int64_t>, SmallVector<int64_t>>
   getInputAndOutputShape(Value inputTorchTensor,
-                         SmallVector<Value> outputSizeTorchInt) {
+                         SmallVector<Value> outputSizeTorchInt, ArrayRef<int64_t> resultTypeShape) {
     SmallVector<int64_t> inputShape(
         inputTorchTensor.getType().cast<BaseTensorType>().getSizes());
     SmallVector<int64_t> outputShape(outputSizeTorchInt.size(), kUnknownSize);
-    for (auto [outputDim, outputDimSize] :
-         llvm::enumerate(outputSizeTorchInt)) {
+//    for (auto [outputDim, outputDimSize] :
+//         llvm::enumerate(outputSizeTorchInt)) {
+    for (const auto &it : llvm::enumerate(llvm::zip_equal(outputSizeTorchInt, resultTypeShape))) {
+      int64_t outputDim = it.index();
+      Value outputDimSize = std::get<0>(it.value());
+      int64_t resultShapeSize = std::get<1>(it.value());
       int64_t inputDim;
       int64_t outputDimSizeInt;
       // Match torch.aten.size.int(inputTensor, inputDim) with constant inputDim
+      if (resultShapeSize >= 0) {
+	outputShape[outputDim] = resultShapeSize;
+	continue;
+      }
       if (matchPattern(outputDimSize,
                        m_TorchTensorSizeInt(inputTorchTensor, &inputDim))) {
         outputShape[outputDim] = inputShape[inputDim];
@@ -813,7 +821,7 @@ public:
     }
 
     auto [inputShape, outputShape] =
-        getInputAndOutputShape(op.getSelf(), outputSizeTorchInt);
+        getInputAndOutputShape(op.getSelf(), outputSizeTorchInt, resultType.getShape());
 
     // Currently, we only handle the cases where each dimension is either
     // being expanded or collapsed. We do not handle cases where it's neither