modify static check

mindspore/lite/tools/converter/legacy_optimizer/graph/tensor_quant_pass.cc

@@ -54,7 +54,14 @@ STATUS TensorQuantPass::Run(schema::MetaGraphT *graph) {
           tensor->quantParams.emplace_back(weightQauntParam.release());
         }
         tensor->dataType = TypeId::kNumberTypeInt8;
-        ::memcpy(tensor->data.data(), qDatas.data(), wShapeSize);
+        tensor->data.clear();
+        tensor->data.resize(wShapeSize * sizeof(int8_t));
+        auto ret =
+          memcpy_s(tensor->data.data(), wShapeSize * sizeof(int8_t), qDatas.data(), wShapeSize * sizeof(int8_t));
+        if (ret != EOK) {
+          MS_LOG(ERROR) << "memcpy_s failed: " << ret;
+          return RET_ERROR;
+        }
       } else if (quantParam->dstDtype == TypeId::kNumberTypeInt32) {
         // quant bias data
         auto bShapeSize = GetShapeSize(*(tensor.get()));

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

@@ -98,8 +98,14 @@ STATUS AwareQuantizer::DoQuantize() {
           tensor->quantParams.clear();
           tensor->quantParams.emplace_back(weightQauntParam.release());
         }
-
-        ::memcpy(tensor->data.data(), qDatas.data(), wShapeSize);
+        tensor->data.clear();
+        tensor->data.resize(wShapeSize * sizeof(int8_t));
+        auto ret =
+          memcpy_s(tensor->data.data(), wShapeSize * sizeof(int8_t), qDatas.data(), wShapeSize * sizeof(int8_t));
+        if (ret != EOK) {
+          MS_LOG(ERROR) << "memcpy_s failed: " << ret;
+          return RET_ERROR;
+        }
       } else if (quantParam->dstDtype == TypeId::kNumberTypeInt32) {
         // quant bias data
         auto bShapeSize = GetShapeSize(*(tensor.get()));

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

@@ -216,6 +216,7 @@ int LinearCalcer::Calc(MetaGraphT *graph, const CNodeT &node) {
 class CalcConcat : public QuantParamCalcer {
  public:
   CalcConcat() = default;
+  ~CalcConcat() override = default;
 
   int Calc(MetaGraphT *graph, const CNodeT &node) override {
     MS_ASSERT(node.outputIndex.size() == 1);
@@ -280,6 +281,7 @@ class CalcConcat : public QuantParamCalcer {
 class CalcAdd : public QuantParamCalcer {
  public:
   CalcAdd() = default;
+  ~CalcAdd() override = default;
 
   int Calc(MetaGraphT *graph, const CNodeT &node) override {
     MS_ASSERT(node.inputIndex.size() == 2);
@@ -357,6 +359,7 @@ class CalcAdd : public QuantParamCalcer {
 class CalcRealDiv : public QuantParamCalcer {
  public:
   CalcRealDiv() = default;
+  ~CalcRealDiv() override = default;
 
   int Calc(MetaGraphT *graph, const CNodeT &node) override {
     MS_ASSERT(node.inputIndex.size() == 2);
@@ -424,6 +427,7 @@ class CalcRealDiv : public QuantParamCalcer {
 class CalcToSet : public QuantParamCalcer {
  public:
   CalcToSet(float min, float max) : min(min), max(max) {}
+  ~CalcToSet() override = default;
 
   int Calc(MetaGraphT *graph, const CNodeT &node) override {
     MS_ASSERT(node.inputIndex.size() == 1);
@@ -468,6 +472,7 @@ class CalcToSet : public QuantParamCalcer {
 class CalcActivation : public QuantParamCalcer {
  public:
   CalcActivation() = default;
+  ~CalcActivation() override = default;
 
   int Calc(MetaGraphT *subGraph, const CNodeT &node) override {
     MS_ASSERT(node.inputIndex.size() == 1);

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

@@ -1323,7 +1323,11 @@ STATUS PostTrainingQuantizer::BiasCorrection(FuncGraphPtr func_graph) {
           MS_LOG(ERROR) << "new char[] failed";
           return RET_MEMORY_FAILED;
         }
-        std::memcpy(tensor_data, bias_diff.data(), size);
+        ret = ::memcpy_s(tensor_data, size * sizeof(char), bias_diff.data(), size * sizeof(char));
+        if (ret != EOK) {
+          MS_LOG(ERROR) << "memcpy_s error: " << ret;
+          return false;
+        }
         param_value->set_tensor_addr(tensor_data);
         param_value->set_tensor_size(size);
         parameter->set_default_param(param_value);