!15787 fix codedex.

From: @liu_xiao_93
Reviewed-by: @zhoufeng54,@jjfeing
Signed-off-by: @jjfeing

mindspore/ccsrc/backend/kernel_compiler/tbe/tbe_kernel_build.cc

@@ -198,7 +198,7 @@ bool TbeKernelJsonCreator::GenTbeSingleKernelJson(const std::shared_ptr<mindspor
 }
 
 void GenNoneInputDescJson(const std::shared_ptr<OpIOInfo> &input_ptr, size_t input_i,
-                          std::vector<nlohmann::json> *input_list) {
+                          std::vector<nlohmann::json> *const input_list) {
   nlohmann::json input_desc_json;
   auto in_name = input_ptr->name();
   input_desc_json[kJName] = in_name + std::to_string(input_i);
@@ -209,7 +209,7 @@ void GenNoneInputDescJson(const std::shared_ptr<OpIOInfo> &input_ptr, size_t inp
 void TbeKernelJsonCreator::GenValidInputDescJson(const std::shared_ptr<AnfNode> &anf_node, size_t real_input_index,
                                                  bool value, const std::shared_ptr<OpIOInfo> &input_ptr,
                                                  const string &op_input_name, size_t input_i,
-                                                 std::vector<nlohmann::json> *input_list) {
+                                                 std::vector<nlohmann::json> *const input_list) {
   auto def_format = kOpFormat_NCHW;
   auto dtype = GetDeviceInputType(anf_node, real_input_index);
   auto format = GetDeviceInputFormat(anf_node, real_input_index);

mindspore/ccsrc/backend/optimizer/ascend/enhancer/split_n_optimizer.cc

@@ -30,7 +30,7 @@ namespace {
 using KernelWithIndex = std::pair<AnfNodePtr, size_t>;
 const std::set<std::string> InvalidOps = {kSplitOpName, kSplitVOpName, kConcatOpName};
 
-void GetSplitOutputs(const FuncGraphPtr &func_graph, const AnfNodePtr &node, std::vector<AnfNodePtr> *out_nodes) {
+void GetSplitOutputs(const FuncGraphPtr &func_graph, const AnfNodePtr &node, std::vector<AnfNodePtr> *const out_nodes) {
   MS_EXCEPTION_IF_NULL(func_graph);
   auto manager = func_graph->manager();
   MS_EXCEPTION_IF_NULL(manager);

mindspore/ccsrc/backend/optimizer/ascend/ir_fission/max_pool3d_grad_grad_fission.cc

@@ -36,12 +36,12 @@ tensor::TensorPtr CreateTensor(const AnfNodePtr &node) {
     MS_LOG(ERROR) << "MaxPool3DGradGrad only support NCDHW.";
   }
   MS_LOG(DEBUG) << "ksize of MaxPool3DGradGrad:" << ksize;
-  int64_t D = ksize[2];
-  int64_t H = ksize[3];
-  int64_t W = ksize[4];
+  int64_t d = ksize[2];
+  int64_t h = ksize[3];
+  int64_t w = ksize[4];
 
   // 1 create tensor
-  std::vector<int64_t> assist_shape = {1, 1, D, H, W};  // shape:NCDHW
+  std::vector<int64_t> assist_shape = {1, 1, d, h, w};  // shape:NCDHW
   TensorTypePtr tensor_type = std::make_shared<TensorType>(kFloat16);
   MS_EXCEPTION_IF_NULL(tensor_type);
   tensor::DeviceInfo device_info{kOpFormat_NDC1HWC0, tensor_type};
@@ -52,14 +52,14 @@ tensor::TensorPtr CreateTensor(const AnfNodePtr &node) {
   auto data_ptr = assist_tensor->data_c();
   MS_EXCEPTION_IF_NULL(data_ptr);
   std::vector<float16> half_data;
-  int64_t dims = 1 * 1 * D * H * W;
+  int64_t dims = 1 * 1 * d * h * w;
   int64_t counter = dims;
   for (int64_t i = 0; i < dims; i++) {
     half_data.emplace_back(float16(static_cast<float>(counter)));
     counter--;
   }
 
-  auto elem_num = dims * kFloat16Len;
+  int64_t elem_num = dims * kFloat16Len;
   auto ret_code = memcpy_s(data_ptr, static_cast<size_t>(assist_tensor->data().nbytes()), half_data.data(), elem_num);
   if (ret_code != 0) {
     MS_LOG(ERROR) << "Failed to copy data into Tensor.";