Fix bug for aten_nll_loss op in the refine types pass

The check for `self.hasSizes` was missing before performing `.size()`
operation.

lib/Dialect/Torch/Transforms/RefineTypes.cpp

@@ -1177,26 +1177,24 @@ ChangeResult TypeAnalyzer::visitAtenNllLossForwardOp(
   auto self = operands[0]->getValue();
   auto outputKnowledge =
       ValueKnowledge::getNotNonePessimisticValueState(op.getContext());
-
-  // Contains Knowledge of shape and dtype for the 1st result.
-  outputKnowledge.dtype = self.dtype;
-  int64_t reduction;
-  unsigned resultRank = self.sizes.size();
-
-  // Contains Knowledge of shape and dtype for the 2nd result.
   auto totalWeightKnowledge =
       ValueKnowledge::getNotNonePessimisticValueState(op.getContext());
+
+  // `AtenNllLossForward` op returns two outputs, output and total_weight.
+  // The rank of the output depends on the reduction parameter and total_weight
+  // is a scalar value.
+  outputKnowledge.dtype = self.dtype;
   totalWeightKnowledge.dtype = self.dtype;
-  totalWeightKnowledge.sizes.resize(0, kUnknownSize);
   totalWeightKnowledge.hasSizes = true;
-
-  if (self.hasSizes &&
-      matchPattern(op.reduction(), m_TorchConstantInt(&reduction))) {
-    if (reduction != Reduction::None)
-      resultRank -= 1;
+  if (self.hasSizes) {
+    int64_t reduction;
+    if (matchPattern(op.reduction(), m_TorchConstantInt(&reduction))) {
+      outputKnowledge.hasSizes = true;
+      unsigned resultRank = self.sizes.size();
+      if (reduction == Reduction::None)
+        outputKnowledge.sizes.resize(resultRank - 1, kUnknownSize);
+    }
   }
-  outputKnowledge.sizes.resize(resultRank - 1, kUnknownSize);
-  outputKnowledge.hasSizes = true;
   auto resultLattice = getLatticeElement(op.getResult(0)).join(outputKnowledge);
   resultLattice |=
       getLatticeElement(op.getResult(1)).join(totalWeightKnowledge);