diff --git a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
index 3d390c8ad3b8897721b634b373b84e0993fc897b..841a95db38ce7cf0cb5961ff04cb569ee2633e6f 100644
--- a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
@@ -37,11 +37,11 @@ class Conv2dOpConverter : public OpConverter {
     auto* Y_t = Y_v->GetMutable<framework::LoDTensor>();
 
     platform::CPUPlace cpu_place;
-    framework::LoDTensor* weight_tensor = new framework::LoDTensor();
+    std::unique_ptr<framework::LoDTensor> weight_tensor(
+        new framework::LoDTensor());
     weight_tensor->Resize(Y_t->dims());
-    TensorCopySync((*Y_t), cpu_place, weight_tensor);
-    engine_->weight_map[op_desc.Input("Filter").front()] =
-        std::move(std::unique_ptr<framework::Tensor>(weight_tensor));
+    TensorCopySync((*Y_t), cpu_place, weight_tensor.get());
+
     auto* weight_data =
         weight_tensor->mutable_data<float>(platform::CPUPlace());
 
@@ -78,6 +78,8 @@ class Conv2dOpConverter : public OpConverter {
     layer->setNbGroups(groups);
 
     auto output_name = op_desc.Output("Output").front();
+    engine_->weight_map[op_desc.Input("Filter").front()] =
+        std::move(weight_tensor);
     engine_->SetITensor(output_name, layer->getOutput(0));
     if (test_mode) {
       engine_->DeclareOutput(output_name);
diff --git a/paddle/fluid/inference/tensorrt/convert/elementwise_op.cc b/paddle/fluid/inference/tensorrt/convert/elementwise_op.cc
index 066e5de373d15d50e5583e6ed7c5a07ae8abe791..60a72b4eb5c75b5cd12305f13763a9a1a567213f 100644
--- a/paddle/fluid/inference/tensorrt/convert/elementwise_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/elementwise_op.cc
@@ -41,12 +41,10 @@ class ElementwiseWeightOpConverter : public OpConverter {
     auto* Y_t = Y_v->GetMutable<framework::LoDTensor>();
 
     platform::CPUPlace cpu_place;
-    framework::LoDTensor* weight_tensor = new framework::LoDTensor();
+    std::unique_ptr<framework::LoDTensor> weight_tensor(
+        new framework::LoDTensor());
     weight_tensor->Resize(Y_t->dims());
-    TensorCopySync((*Y_t), cpu_place, weight_tensor);
-    engine_->weight_map[op_desc.Input("Y").front()] =
-        std::move(std::unique_ptr<framework::Tensor>(weight_tensor));
-
+    TensorCopySync((*Y_t), cpu_place, weight_tensor.get());
     auto* weight_data =
         weight_tensor->mutable_data<float>(platform::CPUPlace());
     auto scale_mode = nvinfer1::ScaleMode::kELEMENTWISE;
@@ -90,6 +88,8 @@ class ElementwiseWeightOpConverter : public OpConverter {
         engine_, Scale, *const_cast<nvinfer1::ITensor*>(X), scale_mode,
         shift_weights.get(), scale_weights.get(), power_weights.get());
     auto output_name = op_desc.Output("Out")[0];
+
+    engine_->weight_map[op_desc.Input("Y").front()] = std::move(weight_tensor);
     engine_->SetITensor(output_name, layer->getOutput(0));
     if (test_mode) {  // the test framework can not determine which is the
                       // output, so place the declaration inside.
diff --git a/paddle/fluid/inference/tensorrt/convert/fc_op.cc b/paddle/fluid/inference/tensorrt/convert/fc_op.cc
index 653ddb0ccae178008869e069617d7db2764f3866..ad98d85aae9cf594922aca00c43718ccfbce2278 100644
--- a/paddle/fluid/inference/tensorrt/convert/fc_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/fc_op.cc
@@ -78,10 +78,8 @@ class FcOpConverter : public OpConverter {
     PADDLE_ENFORCE_EQ(weight_tensor.dims().size(), 2UL);  // a matrix
     size_t n_output = weight_tensor.dims()[1];
 
-    framework::LoDTensor* tmp = new framework::LoDTensor();
+    std::unique_ptr<framework::Tensor> tmp(new framework::LoDTensor());
     tmp->Resize(weight_tensor.dims());
-    engine_->weight_map[op_desc.Input("Y").front()] =
-        std::move(std::unique_ptr<framework::Tensor>(tmp));
 
     memcpy(tmp->mutable_data<float>(platform::CPUPlace()), weight_data,
            Y_t->dims()[0] * Y_t->dims()[1] * sizeof(float));
@@ -110,6 +108,7 @@ class FcOpConverter : public OpConverter {
 
     auto output_name = op_desc.Output("Out").front();
     engine_->SetITensor(output_name, layer->getOutput(0));
+    engine_->weight_map[op_desc.Input("Y").front()] = std::move(tmp);
     if (test_mode) {
       engine_->DeclareOutput(output_name);
     }