fix memory leak

mindspore/lite/tools/converter/quantizer/weight_quantizer.cc

@@ -551,8 +551,8 @@ STATUS WeightQuantizer::DoQuantSearch(const FuncGraphPtr &func_graph) {
       // copy origin data in case to recover
       auto *raw_data = static_cast<float *>(param_value->tensor_addr());
       auto elem_count = param_value->tensor_shape_size();
-      auto origin_data = malloc(sizeof(float) * elem_count);
-      auto ret = memcpy_s(origin_data, sizeof(float) * elem_count, raw_data, param_value->tensor_size());
+      std::unique_ptr<float[]> origin_data(new (std::nothrow) float[elem_count]);
+      auto ret = memcpy_s(origin_data.get(), sizeof(float) * elem_count, raw_data, param_value->tensor_size());
       if (ret != EOK) {
         MS_LOG(ERROR) << "memcpy fail: "
                       << " dst size: " << sizeof(float) * elem_count << " src size: " << param_value->tensor_size();
@@ -617,7 +617,7 @@ STATUS WeightQuantizer::DoQuantSearch(const FuncGraphPtr &func_graph) {
           MS_LOG(DEBUG) << "op: " << op_name << " intermediate bit: " << bit_num_t << " mean_error: " << mean_error
                         << " [recover]";
           // recover
-          status = UpdateTensorDataAndSize(param_value, origin_data, sizeof(float) * elem_count);
+          status = UpdateTensorDataAndSize(param_value, origin_data.get(), sizeof(float) * elem_count);
           if (status != RET_OK) {
             MS_LOG(ERROR) << "UpdateTensorDataAndSize fail";
             return RET_ERROR;
@@ -627,9 +627,8 @@ STATUS WeightQuantizer::DoQuantSearch(const FuncGraphPtr &func_graph) {
           opname_bit_[op_name] = bit_num_t;
         }
       }  // end bit loop
-      free(origin_data);
-    }  //  if: conv and matmul
-  }    // end loop: all cnode
+    }    //  if: conv and matmul
+  }      // end loop: all cnode
   return status;
 }
 

mindspore/lite/tools/optimizer/fusion/tf_lstm_cell_fusion.cc

@@ -246,7 +246,8 @@ STATUS TfLstmCellFusion::PopulateBiasNode(const EquivPtr &body_equiv, const Para
   default_param->set_tensor_shape(shape);
   default_param->set_tensor_type(kNumberTypeFloat32);
   default_param->set_format(schema::Format_NHWC);
-  auto tensor_data = new (std::nothrow) float[hidden_size * 8];
+
+  std::unique_ptr<float[]> tensor_data(new (std::nothrow) float[hidden_size * 8]);
 
   auto forget_bias_node = utils::cast<AnfNodePtr>((*body_equiv)[forget_bias_]);
   if (forget_bias_node == nullptr) {
@@ -271,13 +272,12 @@ STATUS TfLstmCellFusion::PopulateBiasNode(const EquivPtr &body_equiv, const Para
       }
     }
   }
-  default_param->SetTensorData(tensor_data, hidden_size * 8 * 4);
+  default_param->SetTensorData(tensor_data.release(), hidden_size * 8 * 4);
   new_bias->set_default_param(default_param);
   std::vector<int64_t> shape_vector_i(shape.begin(), shape.end());
   auto abstract_tensor_i = std::make_shared<abstract::AbstractTensor>(kFloat32, shape_vector_i);
   if (abstract_tensor_i == nullptr) {
     MS_LOG(ERROR) << "abstract_tensor is nullptr";
-    delete[] tensor_data;
     return RET_ERROR;
   }
   new_bias->set_abstract(abstract_tensor_i);

mindspore/lite/tools/optimizer/graph/if_pass.cc

@@ -31,7 +31,7 @@
 namespace mindspore::opt {
 
 ValueNodePtr IfPass::GetSwitchAnfPrim() {
-  auto switch_primitiveT = new (std::nothrow) schema::PrimitiveT;
+  std::unique_ptr<schema::PrimitiveT> switch_primitiveT(new (std::nothrow) schema::PrimitiveT);
   if (switch_primitiveT == nullptr) {
     MS_LOG(ERROR) << "new switch_primitiveT failed";
     return nullptr;
@@ -43,7 +43,7 @@ ValueNodePtr IfPass::GetSwitchAnfPrim() {
     return nullptr;
   }
 
-  auto partial_prim = std::make_shared<lite::Partial>(switch_primitiveT);
+  auto partial_prim = std::make_shared<lite::Partial>(switch_primitiveT.release());
   ValueNodePtr partial_anf_prim = NewValueNode(partial_prim);
   return partial_anf_prim;
 }