diff --git a/src/auto_scheduler/cost_model.cc b/src/auto_scheduler/cost_model.cc
index 03e778e9129bc..e753c08a6a739 100644
--- a/src/auto_scheduler/cost_model.cc
+++ b/src/auto_scheduler/cost_model.cc
@@ -31,9 +31,11 @@ TVM_REGISTER_OBJECT_TYPE(CostModelNode);
 TVM_REGISTER_OBJECT_TYPE(RandomModelNode);
 TVM_REGISTER_OBJECT_TYPE(PythonBasedModelNode);
 
-void RandomNumber(size_t n, void* data) {
+void RandomNumber(TVMArgs args, TVMRetValue* rv) {
+  int n = args[0];
+  void* data = args[1];
   float* fdata = reinterpret_cast<float*>(data);
-  for (size_t i = 0; i < n; i++) {
+  for (int i = 0; i < n; i++) {
     fdata[i] = static_cast<float>(rand_r(nullptr)) / (static_cast<float>(RAND_MAX));
   }
 }
@@ -44,11 +46,10 @@ RandomModel::RandomModel() {
   if (node->random_number_func == nullptr) {
     LOG(WARNING) << "auto_scheduler.cost_model.random_fill_float is not registered, "
                  << "use C++ default random_number func instead.";
-    static TypedPackedFunc<void(size_t, void*)> cost_model_random_number(RandomNumber);
-    node->random_number_func = &cost_model_random_number;
-  } else {
-    node->random_number_func = reinterpret_cast<const TypedPackedFunc<void(size_t, void*)>*>(f);
+    const auto pf = PackedFunc(RandomNumber);
+    f = &pf;
   }
+  node->random_number_func = reinterpret_cast<const TypedPackedFunc<void(size_t, void*)>*>(f);
   data_ = std::move(node);
 }