diff --git a/torch/csrc/jit/codegen/cuda/manager.cpp b/torch/csrc/jit/codegen/cuda/manager.cpp
index cf41cb03e6d07..454b832863547 100644
--- a/torch/csrc/jit/codegen/cuda/manager.cpp
+++ b/torch/csrc/jit/codegen/cuda/manager.cpp
@@ -147,6 +147,7 @@ class CudaFusionManager {
   }
 
   void debugPrint(const TensorTypePtr& type) {
+    printf("\nsizes:");
     if (auto sizes = type->symbolic_sizes().sizes()) {
       // for (const auto& shape_symbol : sizes.value()) {
       int rank = static_cast<int>(sizes->size());
@@ -165,24 +166,27 @@ class CudaFusionManager {
       int rank = static_cast<int>(stride_properties->size());
       printf("\nstride: ");
       for (int i = 0; i < rank; i++) {
-        if (auto val = (*stride_properties)[i]->stride_) {
-          printf("%ld, ", val.value());
+        if ((*stride_properties)[i].has_value() &&
+            (*stride_properties)[i]->stride_.has_value()) {
+          printf("%ld, ", (*stride_properties)[i]->stride_.value());
         } else {
           printf("?, ");
         }
       }
       printf("\nstride index: ");
       for (int i = 0; i < rank; i++) {
-        if (auto val = (*stride_properties)[i]->stride_index_) {
-          printf("%ld, ", val.value());
+        if ((*stride_properties)[i].has_value() &&
+            (*stride_properties)[i]->stride_index_.has_value()) {
+          printf("%ld, ", (*stride_properties)[i]->stride_index_.value());
         } else {
           printf("?, ");
         }
       }
       printf("\ncontiguous: ");
       for (int i = 0; i < rank; i++) {
-        if (auto val = (*stride_properties)[i]->contiguous_) {
-          printf("%d, ", val.value());
+        if ((*stride_properties)[i].has_value() &&
+            (*stride_properties)[i]->contiguous_.has_value()) {
+          printf("%d, ", (*stride_properties)[i]->contiguous_.value());
         } else {
           printf("?, ");
         }
@@ -196,7 +200,7 @@ class CudaFusionManager {
   at::DimVector restorePermutation(at::DimVector permuted) {
     int rank = static_cast<int>(permuted.size());
     at::DimVector permutation(rank, -1);
-    for (int i; i < rank; i++) {
+    for (int i = 0; i < rank; i++) {
       permutation[permuted[i]] = i;
     }
     return permutation;
@@ -220,17 +224,19 @@ class CudaFusionManager {
 
     // TODO: this does not support broadcast yet;
     for (int i = 0; i < rank; i++) {
-      if (auto index = (*stride_properties)[i]->stride_index_) {
-        ordered_axes.insert(*index);
+      if ((*stride_properties)[i].has_value() &&
+          (*stride_properties)[i]->stride_index_.has_value()) {
+        ordered_axes.insert((*stride_properties)[i]->stride_index_.value());
       }
     }
 
     int unallocated_axis = 0;
     // we push from slowest to fastest
     for (int i = rank - 1; i >= 0; i--) {
-      if (auto index = (*stride_properties)[i]->stride_index_) {
-        // pushing axis index to current entry in permute_seq;
-        permute_seq.emplace_back(*index);
+      if ((*stride_properties)[i].has_value() &&
+          (*stride_properties)[i]->stride_index_.has_value()) {
+        permute_seq.emplace_back(
+            (*stride_properties)[i]->stride_index_.value());
       } else {
         // no designated axis for this slot, so we push an axis w/o designated
         // order;
@@ -282,6 +288,7 @@ class CudaFusionManager {
 
     auto strategy = getSortStrideScheme(acc_type);
     // TODO: early return if permutation is no-op;
+
     auto restore_strategy = restorePermutation(strategy);
 
     std::vector<at::Tensor> permuted_outputs;