UT passed

paddle/fluid/inference/tensorrt/plugin/spmm_plugin.cu

@@ -412,6 +412,7 @@ SpmmPluginDynamic::SpmmPluginDynamic(const std::string name, const void* data,
                                      size_t length)
     : layer_name_(name),
       weight_compressed_(nullptr),
+      weight_compressed_dev_(nullptr),
       weight_compressed_dev_global_(nullptr),
       bias_(nullptr),
       bias_dev_(nullptr) {
@@ -435,18 +436,26 @@ SpmmPluginDynamic::SpmmPluginDynamic(const std::string name, const void* data,
   weight_compressed_ = new char[compressed_size_];
   deserialize_value_size(&data, &length, weight_compressed_, compressed_size_);
   //MEM: how to deal with deserialization?
-  auto* p_tmp = weight_compressed_dev_global_.get();
-  cudaMalloc(reinterpret_cast<void**>(&p_tmp),
-             compressed_size_);
-  cudaMemcpy(weight_compressed_dev_global_.get(), weight_compressed_, compressed_size_,
-             cudaMemcpyHostToDevice);
+  cudaMalloc(reinterpret_cast<void**>(&weight_compressed_dev_), compressed_size_);
+  cudaMemcpy(weight_compressed_dev_, weight_compressed_, compressed_size_, cudaMemcpyHostToDevice);
+  weight_compressed_dev_global_.reset(weight_compressed_dev_, cudaFreeFunc);
 
-  std::cout << "compressed weight:";
+  char* test_weight = new char[compressed_size_];
+  cudaMemcpy(test_weight, weight_compressed_dev_global_.get(), compressed_size_,
+         cudaMemcpyDeviceToHost);
+  std::cout << "compressed weight in deserial:";
   for(int i=0; i<10; i++) {
     std::cout << " " << static_cast<float>(reinterpret_cast<float*>(weight_compressed_)[i]);
   }
   std::cout << std::endl;
 
+  std::cout << "weight from shared ptr in deserial:";
+  for(int i=0; i<10; i++) {
+    std::cout << " " << static_cast<float>(reinterpret_cast<float*>(test_weight)[i]);
+  }
+  std::cout << std::endl;
+
+
   if (has_bias_) {
     bias_ = new float[out_dim_];
     deserialize_value_size(&data, &length, bias_, sizeof(float) * out_dim_);