diff --git a/lib/Dialect/Torch/Transforms/RefineTypes.cpp b/lib/Dialect/Torch/Transforms/RefineTypes.cpp
index 1520c2baf..b0d961ced 100644
--- a/lib/Dialect/Torch/Transforms/RefineTypes.cpp
+++ b/lib/Dialect/Torch/Transforms/RefineTypes.cpp
@@ -646,7 +646,8 @@ static Type getPromotedResultTypeAssumingNonZeroRank(
 
 void TypeAnalysis::fillInDTypeGivenDTypeIntAndInputDType(
     ValueKnowledge &knowledge, Value dtype, Type inputDType) {
-  assert(isBuiltInType(inputDType) && "`inputDType` must be a builtin type");
+  assert(!inputDType ||
+         isBuiltInType(inputDType) && "`inputDType` must be a builtin type");
   int64_t dtypeInt;
   if (dtype.getType().isa<Torch::NoneType>())
     knowledge.dtype = inputDType;
@@ -946,6 +947,12 @@ void TypeAnalysis::visitOperation(Operation *op,
   }
   if (auto sumDimIntList = dyn_cast<AtenSumDimIntListOp>(op)) {
     Type defaultDtype = operands[0]->getValue().dtype;
+    if (!defaultDtype) {
+      incorporateKnowledge(
+          sumDimIntList.getResult(),
+          ValueKnowledge::getTensorPessimisticValueState(op->getContext()));
+      return;
+    }
     // If the input dtype is bool, the result type should be i64.
     if (defaultDtype.isInteger(1))
       defaultDtype =
diff --git a/test/Dialect/Torch/refine-types.mlir b/test/Dialect/Torch/refine-types.mlir
index b8ee124fb..52f30b1bc 100644
--- a/test/Dialect/Torch/refine-types.mlir
+++ b/test/Dialect/Torch/refine-types.mlir
@@ -272,3 +272,24 @@ func.func @forward(%arg0: !torch.bool, %arg1: !torch.tensor) {
   %2 = torch.aten.mul.Tensor %1, %1 : !torch.vtensor, !torch.vtensor -> !torch.vtensor
   return
 }
+
+// -----
+
+// CHECK-LABEL:   func.func @torch.aten.zeros_like(
+// CHECK-SAME:        %[[arg:.*]]: !torch.vtensor) {
+// CHECK:           %[[INT6:.*]] = torch.constant.int 6
+// CHECK:           %[[FALSE:.*]] = torch.constant.bool false
+// CHECK:           %[[INT1:.*]] = torch.constant.int 1
+// CHECK:           %[[INT0:.*]] = torch.constant.int 0
+// CHECK:           %[[CPU:.*]] = torch.constant.device "cpu"
+// CHECK:           %[[ZEROS:.*]] = torch.aten.zeros_like %[[arg]], %[[INT6]], %[[INT0]], %[[CPU]], %[[FALSE]], %[[INT1]] : !torch.vtensor, !torch.int, !torch.int, !torch.Device, !torch.bool, !torch.int -> !torch.vtensor<*,f32>
+// CHECK:           return
+func.func @torch.aten.zeros_like(%arg: !torch.vtensor) {
+  %int6 = torch.constant.int 6
+  %false = torch.constant.bool false
+  %int1 = torch.constant.int 1
+  %int0 = torch.constant.int 0
+  %cpu = torch.constant.device "cpu"
+  %2 = torch.aten.zeros_like %arg, %int6, %int0, %cpu, %false, %int1 : !torch.vtensor, !torch.int, !torch.int, !torch.Device, !torch.bool, !torch.int -> !torch.vtensor
+  return
+}