!17165 pclint clean

From: @zhangzhaoju
Reviewed-by: @ginfung,@zh_qh
Signed-off-by: @zh_qh

mindspore/ccsrc/frontend/optimizer/irpass/special_op_eliminate.h

@@ -293,7 +293,7 @@ class ZeroLikeFillZero : public AnfVisitor {
     }
 
     tensor::TensorPtr new_tensor_ptr = std::make_shared<tensor::Tensor>(tensor_type_ptr->type_id(), tensor_shape);
-    size_t mem_size = GetTypeByte(tensor_type_ptr) * LongToSize(new_tensor_ptr->ElementsNum());
+    size_t mem_size = GetTypeByte(tensor_type_ptr) * IntToSize(new_tensor_ptr->ElementsNum());
     char *data = reinterpret_cast<char *>(new_tensor_ptr->data_c());
     (void)memset_s(data, mem_size, 0, mem_size);
 

mindspore/ccsrc/pipeline/jit/pass.cc

@@ -92,7 +92,7 @@ bool TransformTopGraphPass(const ResourcePtr &res) {
     AbstractBasePtrList abs_spec_list;
     auto &params = func_graph->parameters();
     std::transform(params.begin(), params.end(), std::back_inserter(abs_spec_list),
-                   [](AnfNodePtr node) { return node->abstract(); });
+                   [](const AnfNodePtr &node) { return node->abstract(); });
     res->set_args_spec(abs_spec_list);
   }
   return true;
@@ -428,7 +428,7 @@ OptPassGroupMap GetOptPassesPynativeElim(const opt::irpass::OptimizeIRPassLib &i
   return map;
 }
 
-OptPassGroupMap GetOptPassesC(const opt::irpass::OptimizeIRPassLib &irpass) {
+OptPassGroupMap GetOptPassesC(const opt::irpass::OptimizeIRPassLib &) {
   return OptPassGroupMap({{"renormalize", opt::OptPassConfig::Renormalize()}});
 }
 
@@ -465,7 +465,7 @@ OptPassGroupMap GetPreparePhases(const opt::irpass::OptimizeIRPassLib &irpass) {
   return map;
 }
 
-OptPassGroupMap GetAfterRecomputePass(const opt::irpass::OptimizeIRPassLib &irpass) {
+OptPassGroupMap GetAfterRecomputePass(const opt::irpass::OptimizeIRPassLib &) {
   OptPassGroupMap map({{"cse", opt::OptPassConfig(opt::CSEPass(false))}});
   return map;
 }

mindspore/core/abstract/prim_maths.cc

@@ -198,7 +198,7 @@ AbstractBasePtr InferImplReduceFunc(const AnalysisEnginePtr &, const PrimitivePt
   return std::make_shared<AbstractTensor>(input_x->element(), std::make_shared<Shape>(shape));
 }
 
-AbstractBasePtr InferImplBinaryBase(const AnalysisEnginePtr &engine_ptr, const PrimitivePtr &primitive,
+AbstractBasePtr InferImplBinaryBase(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                     const AbstractBasePtrList &args_spec_list) {
   const std::string op_name = primitive->name();
   constexpr size_t args_size = 2;
@@ -340,8 +340,8 @@ AbstractBasePtr InferImplMatMul(const AnalysisEnginePtr &, const PrimitivePtr &p
   ShapeVector x_max_shape = x->shape()->max_shape();
   ShapeVector y_min_shape = y->shape()->min_shape();
   ShapeVector y_max_shape = y->shape()->max_shape();
-  (void)CheckMinMaxShape(x_shp, &x_min_shape, &x_max_shape);
-  (void)CheckMinMaxShape(y_shp, &y_min_shape, &y_max_shape);
+  CheckMinMaxShape(x_shp, &x_min_shape, &x_max_shape);
+  CheckMinMaxShape(y_shp, &y_min_shape, &y_max_shape);
   // Additional check for dynamic shape
   // Last infer will be real shape values
   bool x_not_dyn = std::all_of(x_shp.begin(), x_shp.end(), [](int64_t value) { return value != Shape::SHP_ANY; });
@@ -398,8 +398,8 @@ AbstractBasePtr InferImplBatchMatMul(const AnalysisEnginePtr &, const PrimitiveP
   ShapeVector x_max_shape = x->shape()->max_shape();
   ShapeVector y_min_shape = y->shape()->min_shape();
   ShapeVector y_max_shape = y->shape()->max_shape();
-  (void)CheckMinMaxShape(x_shp, &x_min_shape, &x_max_shape);
-  (void)CheckMinMaxShape(y_shp, &y_min_shape, &y_max_shape);
+  CheckMinMaxShape(x_shp, &x_min_shape, &x_max_shape);
+  CheckMinMaxShape(y_shp, &y_min_shape, &y_max_shape);
   // Additional check for dynamic shape
   // Last infer will be real shape values
   bool x_not_dyn = std::all_of(x_shp.begin(), x_shp.end(), [](int64_t value) { return value != Shape::SHP_ANY; });

mindspore/core/ir/meta_tensor.cc

@@ -61,8 +61,8 @@ bool MetaTensor::operator==(const MetaTensor &meta_tensor) const {
 // The given index number should be in [0, shape_.size()).
 // param index Dimension index number.
 // return The size of the dimension if succeed, or -1 if failed.
-int MetaTensor::DimensionSize(const size_t index) const {
-  int dim_size = -1;
+int64_t MetaTensor::DimensionSize(const size_t index) const {
+  int64_t dim_size = -1;
   if (index < shape_.size()) {
     dim_size = shape_[index];
   } else {
@@ -71,9 +71,7 @@ int MetaTensor::DimensionSize(const size_t index) const {
   return dim_size;
 }
 
-int MetaTensor::ElementsNum() const {
-  return std::accumulate(shape_.begin(), shape_.end(), 1LL, std::multiplies<int>());
-}
+int MetaTensor::ElementsNum() const { return std::accumulate(shape_.begin(), shape_.end(), 1, std::multiplies<int>()); }
 
 TypePtr MetaTensor::SetDtype(const TypePtr type_ptr) {
   if (type_ptr == nullptr) {

mindspore/core/ir/meta_tensor.h

@@ -144,7 +144,7 @@ class MetaTensor : public Value {
                      const std::string &host_format = "DefaultFormat");
 
   // Get the size of a given dimension by its index number.
-  int DimensionSize(size_t index) const;
+  int64_t DimensionSize(size_t index) const;
 
   // Get total number of elements in a tensor.
   int ElementsNum() const;

mindspore/core/utils/check_convert_utils.cc

@@ -413,9 +413,8 @@ abstract::ShapePtr CheckAndConvertUtils::GetTensorInputShape(const std::string &
   return shape;
 }
 
-void CheckAndConvertUtils::Check(const string &arg_name, int64_t arg_value, CompareEnum compare_type,
-                                 const string &value_name, int64_t value, const string &prim_name,
-                                 ExceptionType exception_type) {
+void CheckAndConvertUtils::Check(const string &arg_name, int64_t arg_value, CompareEnum compare_type, const string &,
+                                 int64_t value, const string &prim_name, ExceptionType exception_type) {
   auto iter = kCompareMap<float>.find(compare_type);
   if (iter == kCompareMap<float>.end()) {
     MS_EXCEPTION(NotExistsError) << "the compare type :" << compare_type << " is not in the compare map";