diff --git a/src/core/graph.cc b/src/core/graph.cc
index 800f4ca5..3d33fa82 100644
--- a/src/core/graph.cc
+++ b/src/core/graph.cc
@@ -11,10 +11,10 @@ GraphObj::GraphObj(Runtime runtime, OpVec ops_in)
     for (const auto &op : ops_in) {
         for (const auto &t : op->getInputs())
             if (tensorPool.find(t->getFuid()) == tensorPool.end())
-                tensorPool[t->getFuid()] = t->clone();
+                tensorPool[t->getFuid()] = cloneTensor(t);
         for (const auto &t : op->getOutputs())
             if (tensorPool.find(t->getFuid()) == tensorPool.end())
-                tensorPool[t->getFuid()] = t->clone();
+                tensorPool[t->getFuid()] = cloneTensor(t);
     }
     for (const auto &[_, t] : tensorPool)
         addTensor(t);
@@ -127,8 +127,12 @@ Tensor GraphObj::addTensor(Shape dim, DataType dtype) {
 }
 
 Tensor GraphObj::addTensor(const Tensor &tensor) {
-    IT_ASSERT(tensor->getRuntime() == runtime, "Tensor runtime mismatch");
-    return tensors.emplace_back(tensor);
+    IT_ASSERT(tensor->getRuntime() == runtime,
+              std::string("Tensor runtime mismatch: cannot add a tenosr in ") +
+                  tensor->getRuntime()->toString() + " to " +
+                  runtime->toString());
+    tensors.emplace_back(tensor);
+    return tensor;
 }
 
 TensorVec GraphObj::addTensor(const TensorVec &tensors) {
diff --git a/test/nnet/test_mutator.cc b/test/nnet/test_mutator.cc
index 2fc4c4ed..963cbe34 100644
--- a/test/nnet/test_mutator.cc
+++ b/test/nnet/test_mutator.cc
@@ -56,15 +56,12 @@ TEST(Mutator, NaiveConvWithInterpreter) {
 
 // FIXME: failed since implicit transpose for DLT
 TEST(Mutator, InfoGAN_TConv_3_correctness) {
-    // verifyNaiveMembound True: subgraph after transformation
-    // verifyNaiveMembound False: subgraph of one single membound (eOP)
-    // const bool verifyNaiveMembound = false;
+    const bool verifyMutator = true;
     Runtime runtime = make_ref<CudaRuntimeObj>();
     Graph g = make_ref<GraphObj>(runtime);
     Runtime cpu = NativeCpuRuntimeObj::getInstance(); // CPUruntime is singleton
     Graph gCpu = make_ref<GraphObj>(cpu);
 
-    // TODO: recover me for InfoGAN
     const int n = 1, c = 256, h = 2, w = 2, f = 448, r = 4, s = 4;
     // // Minimum config for test
     // const int n = 1, c = 1, h = 2, w = 2, f = 1, r = 4, s = 4;
@@ -76,39 +73,50 @@ TEST(Mutator, InfoGAN_TConv_3_correctness) {
     auto mutator =
         make_ref<NMutator>(NMutator::Mode::RuleBased,
                            vector<int>{3, 2, 2, 2, 2, 5, 8, 8, 6, 91, 90});
+
     // mutator->setToNaiveMembound();
-    SearchEngine searchEngine(runtime, mutator);
-    auto bestGraph = searchEngine.run(g);
-    bestGraph->print();
-    printf("--- SearchEngine Finished ---\n");
+    vector<Graph> bestGraphs;
+    if (verifyMutator) {
+        SearchEngine searchEngine(runtime, mutator);
+        bestGraphs.emplace_back(searchEngine.run(g));
+        printf("--- SearchEngine Finished ---\n");
+    } else {
+        bestGraphs = mutator->run(g);
+    }
 
-    g->dataMalloc();
-    bestGraph->dataMalloc();
-    for (auto t : g->getInputs()) {
-        t->setData(IncrementalGenerator());
-    }
-    for (auto t : bestGraph->getInputs()) {
-        t->setData(IncrementalGenerator());
-    }
-    for (auto t : g->getOutputs()) {
-        t->setData(IncrementalGenerator());
-    }
-    for (auto t : bestGraph->getOutputs()) {
-        t->setData(IncrementalGenerator());
-    }
-    runtime->run(g);
-    // puts("cuDNN");
-    // g->getOutputs()[0]->printData();
-    runtime->run(bestGraph);
-    // puts("Output");
-    // bestGraph->getOutputs()[0]->printData();
+    for (auto bestGraph : bestGraphs) {
+        puts("====== New best graph");
+        bestGraph->print();
 
-    auto go0 = gCpu->cloneTensor(g->getOutputs()[0]);
-    auto bgo0 = gCpu->cloneTensor(bestGraph->getOutputs()[0]);
+        g->dataMalloc();
+        bestGraph->dataMalloc();
+        for (auto t : g->getInputs()) {
+            t->setData(IncrementalGenerator());
+        }
+        for (auto t : bestGraph->getInputs()) {
+            t->setData(IncrementalGenerator());
+        }
+        for (auto t : g->getOutputs()) {
+            t->setData(IncrementalGenerator());
+        }
+        for (auto t : bestGraph->getOutputs()) {
+            t->setData(IncrementalGenerator());
+        }
+        const bool tuningOp = true; // FIXME: some eOps are not tuned
+        runtime->run(g);
+        // puts("cuDNN");
+        // g->getOutputs()[0]->printData();
+        runtime->run(bestGraph, tuningOp);
+        // puts("Output");
+        // bestGraph->getOutputs()[0]->printData();
 
-    EXPECT_TRUE(go0->equalData(bgo0));
-    EXPECT_TRUE(g->getOutputs()[0]->getRawDataPtr<void *>() !=
-                bestGraph->getOutputs()[0]->getRawDataPtr<void *>());
+        auto go0 = gCpu->cloneTensor(g->getOutputs()[0]);
+        auto bgo0 = gCpu->cloneTensor(bestGraph->getOutputs()[0]);
+
+        EXPECT_TRUE(go0->equalData(bgo0));
+        EXPECT_TRUE(g->getOutputs()[0]->getRawDataPtr<void *>() !=
+                    bestGraph->getOutputs()[0]->getRawDataPtr<void *>());
+    }
 }
 
 // TEST(Mutator, Conv9x9) {