modify codeDEX_C for R1.2

mindspore/ccsrc/backend/kernel_compiler/cpu/quantum/quantum_simulator/transformer.cc

@@ -109,7 +109,6 @@ Hamiltonians HamiltoniansTransfor(const PaulisCoeffsType &paulis_coeffs, const P
   }
   return hams;
 }
-
 }  // namespace transformer
 }  // namespace mindquantum
 }  // namespace mindspore

mindspore/core/abstract/prim_arrays.cc

@@ -1056,7 +1056,6 @@ AbstractBasePtr InferImplRange(const AnalysisEnginePtr &, const PrimitivePtr &pr
   TypePtr range_start_type = CheckTensorDType(range_start, supported_types, "range_start input of Range should be %s");
   TypePtr range_end_type = CheckTensorDType(range_end, supported_types, "range_start input of Range should be %s");
   TypePtr range_delta_type = CheckTensorDType(range_delta, supported_types, "range_start input of Range should be %s");
-
   // check all 3 inputs are same type
   if (!IsIdentidityOrSubclass(range_start_type, range_end_type) ||
       !IsIdentidityOrSubclass(range_end_type, range_delta_type)) {

mindspore/core/ir/value.cc

@@ -309,5 +309,4 @@ const ValuePtr kUMonad = std::make_shared<UMonad>();
 
 bool IOMonad::operator==(const Value &other) const { return other.isa<IOMonad>(); }
 const ValuePtr kIOMonad = std::make_shared<IOMonad>();
-
 }  // namespace mindspore

mindspore/core/ops/audio_spectrogram.cc

@@ -94,12 +94,12 @@ int64_t AudioSpectrogram::Log2Ceil(int64_t length) {
       floor += shift;
     }
   }
-  return length == (length & ~(length - 1)) ? floor : floor + 1;
+  return length == (length & ~(unsigned int)(length - 1)) ? floor : floor + 1;
 }
 
 int64_t AudioSpectrogram::GetFftLength(int64_t length) {
   int64_t shift = Log2Ceil(length);
-  return 1 << shift;
+  return 1 << (unsigned int)shift;
 }
 
 void AudioSpectrogram::set_mag_square(const bool mag_square) { this->AddAttr(kMagSquare, MakeValue(mag_square)); }

mindspore/core/ops/batch_norm_fold.cc

@@ -22,7 +22,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void BatchNormFold::Init(const float momentum, const float epsilon, const bool is_training, const int64_t freeze_bn) {
   set_momentum(momentum);
   set_epsilon(epsilon);

mindspore/core/ops/broadcast_to.h

@@ -41,7 +41,6 @@ class BroadcastTo : public PrimitiveC {
 AbstractBasePtr BroadcastToInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                  const std::vector<AbstractBasePtr> &input_args);
 using PrimBroadcastToPtr = std::shared_ptr<BroadcastTo>;
-
 }  // namespace ops
 }  // namespace mindspore
 

mindspore/core/ops/ceil.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 AbstractBasePtr CeilInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                           const std::vector<AbstractBasePtr> &input_args) {
   for (const auto &item : input_args) {

mindspore/core/ops/concat.cc

@@ -21,7 +21,6 @@
 #include "utils/check_convert_utils.h"
 namespace mindspore {
 namespace ops {
-
 void Concat::Init(const int64_t axis) { this->set_axis(axis); }
 int64_t Concat::get_axis() const {
   auto value_ptr = this->GetAttr(kAxis);

mindspore/core/ops/fusion/adder_fusion.h

@@ -31,6 +31,7 @@ constexpr auto kNameAdderFusion = "AdderFusion";
 class AdderFusion : public Adder {
  public:
   AdderFusion() : Adder(kNameAdderFusion) {}
+  ~AdderFusion() = default;
   MS_DECLARE_PARENT(AdderFusion, Adder);
   void Init(const int64_t in_channel, const int64_t out_channel, const std::vector<int64_t> &kernel_size,
             const PadMode &pad_mode, const std::vector<int64_t> &stride, const std::vector<int64_t> &pad_list,

mindspore/core/ops/fusion/avg_pool_fusion.cc

@@ -18,7 +18,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void AvgPoolFusion::Init(const std::vector<int64_t> &kernel_size, const std::vector<int64_t> &stride,
                          const PadMode &pad_mode, const Format &format, const std::vector<int64_t> &pad,
                          const RoundMode &round_mode, const bool global, const ActivationType activation_type) {

mindspore/core/ops/fusion/conv2d_backprop_input_fusion.h

@@ -27,6 +27,7 @@ constexpr auto kNameConv2DBackpropInputFusion = "Conv2DBackpropInputFusion";
 class Conv2DBackpropInputFusion : public Conv2DBackpropInput {
  public:
   Conv2DBackpropInputFusion() : Conv2DBackpropInput(kNameConv2DBackpropInputFusion) {}
+  ~Conv2DBackpropInputFusion() = default;
   MS_DECLARE_PARENT(Conv2DBackpropInputFusion, Conv2DBackpropInput);
   void Init(int64_t in_channel, int64_t out_channel, const std::vector<int64_t> &kernel_size, int64_t mode = 1,
             const PadMode &pad_mode = VALID, const std::vector<int64_t> &pad = {0, 0, 0, 0},

mindspore/core/ops/fusion/conv2d_fusion.h

@@ -28,6 +28,7 @@ constexpr auto kNameConv2DFusion = "Conv2DFusion";
 class Conv2DFusion : public Conv2D {
  public:
   Conv2DFusion() : Conv2D(kNameConv2DFusion) {}
+  ~Conv2DFusion() = default;
   MS_DECLARE_PARENT(Conv2DFusion, Conv2D);
   void Init(int64_t in_channel, int64_t out_channel, const std::vector<int64_t> &kernel_size, int64_t mode = 1,
             const PadMode &pad_mode = VALID, const std::vector<int64_t> &pad = {0, 0, 0, 0},

mindspore/core/ops/fusion/div_fusion.h

@@ -26,6 +26,7 @@ constexpr auto kNameDivFusion = "DivFusion";
 class DivFusion : public Div {
  public:
   DivFusion() : Div(kNameDivFusion) {}
+  ~DivFusion() = default;
   MS_DECLARE_PARENT(DivFusion, Div);
   void Init(const ActivationType &activation_type = NO_ACTIVATION);
   void set_activation_type(const ActivationType &activation_type);

mindspore/core/ops/fusion/l2_normalize_fusion.h

@@ -28,6 +28,7 @@ constexpr auto kNameL2NormalizeFusion = "L2NormalizeFusion";
 class L2NormalizeFusion : public L2Normalize {
  public:
   L2NormalizeFusion() : L2Normalize(kNameL2NormalizeFusion) {}
+  ~L2NormalizeFusion() = default;
   MS_DECLARE_PARENT(L2NormalizeFusion, L2Normalize);
   void Init(const std::vector<int64_t> &axis, const float epsilon = 1e-4,
             const ActivationType &activation_type = NO_ACTIVATION);

mindspore/core/ops/fusion/reduce_fusion.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void ReduceFusion::set_keep_dims(const bool keep_dims) { this->AddAttr(kKeepDims, MakeValue(keep_dims)); }
 
 void ReduceFusion::set_mode(const ReduceMode mode) {

mindspore/core/ops/fusion/scale_fusion.h

@@ -26,6 +26,7 @@ constexpr auto kNameScaleFusion = "ScaleFusion";
 class ScaleFusion : public Scale {
  public:
   ScaleFusion() : Scale(kNameScaleFusion) {}
+  ~ScaleFusion() = default;
   MS_DECLARE_PARENT(ScaleFusion, Scale);
   void Init(const int64_t axis = -1, const ActivationType &activation_type = NO_ACTIVATION);
   void set_activation_type(const ActivationType &activation_type);

mindspore/core/ops/fusion/sub_fusion.h

@@ -26,6 +26,7 @@ constexpr auto kNameSubFusion = "SubFusion";
 class SubFusion : public Sub {
  public:
   SubFusion() : Sub(kNameSubFusion) {}
+  ~SubFusion() = default;
   MS_DECLARE_PARENT(SubFusion, Sub);
   void Init(const ActivationType &activation_type = NO_ACTIVATION);
   void set_activation_type(const ActivationType &activation_type);

mindspore/core/ops/fusion/tile_fusion.h

@@ -28,6 +28,7 @@ constexpr auto kNameTileFusion = "TileFusion";
 class TileFusion : public Tile {
  public:
   TileFusion() : Tile(kNameTileFusion) {}
+  ~TileFusion() = default;
   MS_DECLARE_PARENT(TileFusion, Tile);
   void Init(const std::vector<int64_t> &dims);
   void set_dims(const std::vector<int64_t> &dims);

mindspore/core/ops/fusion/topk_fusion.h

@@ -28,6 +28,7 @@ constexpr auto kNameTopKFusion = "TopKFusion";
 class TopKFusion : public TopK {
  public:
   TopKFusion() : TopK(kNameTopKFusion) {}
+  ~TopKFusion() = default;
   MS_DECLARE_PARENT(TopKFusion, TopK);
   void Init(const bool sorted, const int64_t axis, const int64_t largest);
   void set_axis(const int64_t axis);

mindspore/core/ops/grad/activation_grad.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void ActivationGrad::Init(const ActivationType &type, const float alpha) {
   this->set_activation_type(type);
   this->set_alpha(alpha);

mindspore/core/ops/grad/avg_pool_grad.h

@@ -38,7 +38,6 @@ class AvgPoolGrad : public PoolGrad {
 AbstractBasePtr AvgPoolGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                  const std::vector<AbstractBasePtr> &input_args);
 using PrimAvgPoolGradPtr = std::shared_ptr<AvgPoolGrad>;
-
 }  // namespace ops
 }  // namespace mindspore
 

mindspore/core/ops/grad/power_grad.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void PowerGrad::set_power(const float power) { this->AddAttr(kPower, MakeValue(power)); }
 float PowerGrad::get_power() const {
   auto value_ptr = GetAttr(kPower);

mindspore/core/ops/hashtable_lookup.cc

@@ -21,7 +21,6 @@
 
 namespace mindspore {
 namespace ops {
-
 AbstractBasePtr HashtableLookupInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                      const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);

mindspore/core/ops/lstm.cc

@@ -57,8 +57,8 @@ AbstractBasePtr LstmInfer(const PrimitivePtr &primitive, const std::vector<Abstr
     (num_layers + 1) * num_directions * (x_input_shape[0] + 1) * x_input_shape[1] * states_ws_ld * type_size;
   int64_t ws_diff_states_size =
     (num_layers + 1) * num_directions * 3 * (x_input_shape[0] + 1) * x_input_shape[1] * states_ws_ld * type_size;
-  int64_t ws_grad_comp_size = 0;
-  int64_t page_size = 4096;
+  const int64_t ws_grad_comp_size = 0;
+  const int64_t page_size = 4096;
   int64_t current_offset = 0;
   current_offset += ws_gates_size;
   current_offset = ((current_offset / page_size - 1) / page_size) * page_size;

mindspore/core/ops/merge.cc

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace ops {
-
 AbstractBasePtr MergeInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                            const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);

mindspore/core/ops/non_max_suppression.cc

@@ -20,7 +20,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void NonMaxSuppression::set_center_point_box(const int64_t center_point_box) {
   AddAttr(kCenterPointBox, MakeValue(center_point_box));
 }

mindspore/core/ops/permute.cc

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void Permute::set_order(const std::vector<int64_t> &order) { this->AddAttr(kOrder, MakeValue(order)); }
 
 std::vector<int64_t> Permute::get_order() const {

mindspore/core/ops/primitive_c.cc

@@ -43,6 +43,5 @@ OpPrimCRegister &OpPrimCRegister::GetInstance() {
 
 std::map<std::string, OpPrimCDefineFunc> OpPrimCRegister::GetPrimCMap() { return op_primc_fns_; }
 void OpPrimCRegister::SetPrimCMap(const std::string &kname, const OpPrimCDefineFunc &fn) { op_primc_fns_[kname] = fn; }
-
 }  // namespace ops
 }  // namespace mindspore

mindspore/core/ops/proposal.h

@@ -51,7 +51,6 @@ class Proposal : public PrimitiveC {
   int64_t get_post_nms_topn() const;
   float get_nms_thresh() const;
 };
-
 }  // namespace ops
 }  // namespace mindspore
 

mindspore/core/ops/range.cc

@@ -65,7 +65,7 @@ AbstractBasePtr RangeInfer(const abstract::AnalysisEnginePtr &, const PrimitiveP
   MS_EXCEPTION_IF_NULL(primitive);
   auto prim = primitive->cast<PrimRangePtr>();
   MS_EXCEPTION_IF_NULL(prim);
-  int64_t shape_size;
+  int64_t shape_size = 0;
   TypeId dtype;
   if (input_args.size() == 3) {
     MS_EXCEPTION_IF_NULL(input_args[0]->BuildValue());

mindspore/core/ops/reduce.cc

@@ -26,7 +26,6 @@
 namespace mindspore {
 namespace ops {
 namespace {
-
 void reduce_one_axis(const int64_t one_axis, const int64_t dim, std::set<int64_t> axis_reduce) {
   CheckAndConvertUtils::CheckInRange("axis", one_axis, kIncludeLeft, {-dim, dim}, "Reduce");
   if (one_axis < 0) {

mindspore/core/ops/reduce_all.cc

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace ops {
-
 REGISTER_PRIMITIVE_C(kNameReduceAll, ReduceAll);
 }  // namespace ops
 }  // namespace mindspore

mindspore/core/ops/resize_bilinear.cc

@@ -25,7 +25,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void ResizeBilinear::set_size(const std::vector<int64_t> &size) { this->AddAttr(kSize, MakeValue(size)); }
 
 std::vector<int64_t> ResizeBilinear::get_size() const {

mindspore/core/ops/softmax_cross_entropy_with_logits.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 AbstractBasePtr SoftmaxCrossEntropyWithLogitsInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                                    const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);

mindspore/core/ops/space_to_batch_nd.cc

@@ -35,7 +35,7 @@ abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<A
   CheckAndConvertUtils::CheckInteger("input_x rank", x_shape.size(), kEqual, 4, prim_name);
   auto out_shape = x_shape;
   int64_t block_shape_prod = 1;
-  int64_t offset = 2;
+  const int64_t offset = 2;
   auto block_shape = space_prim->get_block_shape();
   auto padding = space_prim->get_paddings();
   int64_t size = block_shape.size();

mindspore/core/ops/to_format.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void ToFormat::set_src_t(const int64_t src_t) { this->AddAttr(kSrcT, MakeValue(src_t)); }
 int64_t ToFormat::get_src_t() const {
   auto value_ptr = GetAttr(kSrcT);

mindspore/core/ops/unpack.cc

@@ -18,7 +18,6 @@
 
 namespace mindspore {
 namespace ops {
-
 void Unpack::Init(const int64_t axis) { this->set_axis(axis); }
 void Unpack::set_axis(const int64_t axis) { AddAttr(kAxis, MakeValue(axis)); }
 int64_t Unpack::get_axis() const {

mindspore/core/ops/where.cc

@@ -22,7 +22,6 @@
 
 namespace mindspore {
 namespace ops {
-
 AbstractBasePtr WhereInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                            const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);