!349 fix coding style check warning for auto parallel

Merge pull request !349 from chentingting/fix_coding_style_check_warning

mindspore/ccsrc/parallel/device_manager.cc

@@ -370,6 +370,5 @@ void DeviceManager::Clear() {
   stage_devices_.clear();
   gm_.Clear();
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/device_matrix.cc

@@ -29,7 +29,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 DeviceMatrix::DeviceMatrix(int32_t rank, RankList dev_list, Shape dev_shape)
     : rank_(rank), dev_list_(std::move(dev_list)), dev_shape_(std::move(dev_shape)) {
   if (!std::any_of(dev_list_.begin(), dev_list_.end(), [rank](int32_t a) { return a == rank; })) {

mindspore/ccsrc/parallel/dynamic_creator.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 #define REGISTER(className)                                                                                  \
   OperatorInfoPtr objectCreator##className(std::string name, Shapes in, Shapes out, PrimitiveAttrs& attrs) { \
     return std::make_shared<className>(name, in, out, attrs);                                                \

mindspore/ccsrc/parallel/ops_info/activation_info.cc

@@ -229,7 +229,8 @@ Status Softmax::GenerateStrategies(int32_t stage_id) {
   }
 
   is_auto_parallel_ = true;
-  Shape input0_split(inputs_shape_[0].size(), 1);
+  Shape input0_split;
+  (void)input0_split.insert(input0_split.begin(), inputs_shape_[0].size(), 1);
   for (auto& element : axis_) {
     int32_t axis_index = element;
     if (element < 0) {

mindspore/ccsrc/parallel/ops_info/batch_parallel_info.cc

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status BatchParallelInfo::CheckStrategy(const StrategyPtr& strategy) {
   if (CheckStrategyValue(strategy, inputs_shape_, is_auto_parallel_) != SUCCESS) {
     if (is_auto_parallel_) {

mindspore/ccsrc/parallel/ops_info/loss_info.cc

@@ -194,7 +194,8 @@ Status SoftmaxCrossEntropyWithLogitsInfo::GenerateStrategies(int32_t stage_id) {
   }
   is_auto_parallel_ = true;
 
-  Shape input0_split(inputs_shape_[0].size(), 1);
+  Shape input0_split;
+  (void)input0_split.insert(input0_split.begin(), inputs_shape_[0].size(), 1);
   input0_split[IntToSize(axis_index)] = 0;
   Shapes splittable_inputs = {input0_split, input0_split};
   std::vector<StrategyPtr> sp_vector;

mindspore/ccsrc/parallel/ops_info/operator_info.cc

@@ -1255,6 +1255,5 @@ void OperatorInfo::BreakingTiesForPerferringDataParallel(const StrategyPtr& stra
 double OperatorInfo::GetForwardMemoryCostFromCNode() {
   return operator_cost()->GetForwardComputationCost(inputs_tensor_info_, outputs_tensor_info_, 0);
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/ops_info/prelu_info.cc

@@ -212,8 +212,10 @@ Status PReLUInfo::GenerateStrategies(int32_t stage_id) {
     return FAILED;
   }
   is_auto_parallel_ = true;
-  Shape input0_split(inputs_shape_[0].size(), 1);
-  input0_split[1] = 0;
+  Shape input0_split;
+  input0_split.emplace_back(1);
+  input0_split.emplace_back(0);
+  (void)input0_split.insert(input0_split.end(), inputs_shape_[0].size() - 2, 1);
   Shape input1_split(inputs_shape_[1].size(), 0);
   Shapes splittable_inputs = {input0_split, input1_split};
   std::vector<StrategyPtr> sp_vector;

mindspore/ccsrc/parallel/ops_info/reshape_info.cc

@@ -413,8 +413,9 @@ Status ReshapeInfo::GenerateStrategies(int32_t stage_id) {
     return FAILED;
   }
   is_auto_parallel_ = true;
-  Shape input0_split(inputs_shape_[0].size(), 0);
-  input0_split[0] = 1;
+  Shape input0_split;
+  input0_split.emplace_back(1);
+  (void)input0_split.insert(input0_split.end(), inputs_shape_[0].size() - 1, 0);
   Shapes splittable_inputs = {input0_split};
   std::vector<StrategyPtr> sp_vector;
   if (GenerateStrategiesForIndependentInputs(stage_id, inputs_shape_, splittable_inputs, &sp_vector) != SUCCESS) {

mindspore/ccsrc/parallel/ops_info/virtual_dataset_info.cc

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status VirtualDatasetInfo::CheckStrategy(const StrategyPtr& strategy) {
   if (CheckStrategyValue(strategy, inputs_shape_, is_auto_parallel_) != SUCCESS) {
     if (is_auto_parallel_) {
@@ -225,8 +224,9 @@ Status VirtualDatasetInfo::GenerateStrategies(int32_t stage_id) {
   StrategyPtr sp;
   std::vector<Dimensions> strategy;
   for (auto& shape : inputs_shape_) {
-    Shape temp(shape.size(), 1);
-    temp[0] = SizeToInt(total_dev_num);
+    Shape temp;
+    temp.emplace_back(SizeToInt(total_dev_num));
+    (void)temp.insert(temp.end(), shape.size() - 1, 1);
     strategy.push_back(temp);
   }
   sp = std::make_shared<Strategy>(stage_id, strategy);

mindspore/ccsrc/parallel/ops_info/virtual_dataset_info.h

@@ -51,7 +51,6 @@ class VirtualDatasetInfo : public OperatorInfo {
   Status GetAttrs() override;
   Status InferAsLossDivisor() override;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/status.h

@@ -21,7 +21,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 enum Status {
   SUCCESS = 0,
   FAILED,

mindspore/ccsrc/parallel/step_auto_parallel.cc

@@ -477,7 +477,6 @@ Status ConstructCostGraphNodes(const std::vector<AnfNodePtr> &all_nodes, const F
         bool is_find_wrong = (current_op_ptr->name().find(VIRTUAL_DATA_SET_INFO) == std::string::npos) &&
                              (current_op_ptr->name().find(BATCH_PARALLEL) == std::string::npos) &&
                              (current_op_ptr->name().find(prim->name()) == std::string::npos);
-
         if (is_find_wrong) {
           MS_LOG(EXCEPTION) << "The OperatorInfo: " << current_op_ptr->name()
                             << " does not match the Prim: " << prim->name();
@@ -937,7 +936,6 @@ Status ParallelStrategyRecSearch(const std::vector<AnfNodePtr> &all_nodes, const
 
   graph = EliminateGraph(graph, eli_list, index_list);
   size_t num_device = g_device_manager->DeviceNum();
-
   if (PartitionForAllDevices(num_device, graph) == SUCCESS) {
     MS_LOG(INFO) << "Partition Success With " << num_device << " devices.";
   } else {

mindspore/ccsrc/parallel/step_auto_parallel.h

@@ -55,7 +55,6 @@ Status ParallelStrategyRecSearch(const std::vector<AnfNodePtr> &all_nodes, const
 
 std::vector<std::vector<std::string>> RecInputTensorNames(const std::map<std::string, std::string>::iterator &it,
                                                           std::vector<std::vector<std::string>> input_tensor_names);
-
 }  // namespace parallel
 }  // namespace mindspore
 #endif  // PARALLEL_STEP_AUTO_PARALLEL_H_

mindspore/ccsrc/parallel/step_parallel.cc

@@ -2094,7 +2094,6 @@ CNodePtr FindLossCNodeFromRoot(const FuncGraphPtr& root) {
   MS_EXCEPTION_IF_NULL(root_return_node);
   const auto& all_nodes = root->nodes();
   FuncGraphPtr func_graph = FindForwardGraphByRootNodes(all_nodes);
-
   if (func_graph == nullptr) {
     return FindLossCNode(root);
   } else {
@@ -2109,7 +2108,6 @@ FuncGraphPtr ForwardGraph(const FuncGraphPtr& root) {
   MS_EXCEPTION_IF_NULL(root_return_node);
   const auto& all_nodes = root->nodes();
   FuncGraphPtr func_graph = FindForwardGraphByRootNodes(all_nodes);
-
   if (func_graph != nullptr) {
     forward_graph = func_graph;
   }

mindspore/ccsrc/parallel/strategy.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 #define MIN_SLICE_NUM 1
 
 using Dimensions = std::vector<int32_t>;

mindspore/ccsrc/parallel/tensor_layout/arrangement.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status Arrangement::Init(const std::vector<int32_t>& array) {
   Status status = Array::Init(array);
   if (status != Status::SUCCESS) {

mindspore/ccsrc/parallel/tensor_layout/arrangement.h

@@ -28,7 +28,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class Arrangement : public Array {
  public:
   Arrangement() : size_(1) {}
@@ -53,7 +52,6 @@ class Arrangement : public Array {
   void ComputeSize();
   int32_t size_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/array.cc

@@ -21,7 +21,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 std::string Array::ToString() const {
   std::ostringstream buffer;
   buffer << "[ ";

mindspore/ccsrc/parallel/tensor_layout/array.h

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class Array {
  public:
   Array() = default;
@@ -43,7 +42,6 @@ class Array {
  protected:
   std::vector<int32_t> array_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/construct_operator.h

@@ -52,7 +52,6 @@ class ConstructOperator {
   Shape dev_matrix_shape_;
   Status CreateGroupByDim(size_t axis, std::vector<Group>* group);
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/layout_transfer.cc

@@ -20,7 +20,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 std::string LayoutTransfer::ToString() const {
   std::ostringstream buffer;
   buffer << std::endl << std::string("from_in_ tensor layout:" + from_in_.ToString());
@@ -37,6 +36,5 @@ Status LayoutTransfer::Init(const TensorLayout& from_in, const TensorLayout& to_
   Status status = CheckValidTransfer();
   return status;
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/tensor_layout/layout_transfer.h

@@ -23,7 +23,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class LayoutTransfer {
  public:
   LayoutTransfer() = default;
@@ -43,7 +42,6 @@ class LayoutTransfer {
  private:
   virtual Status CheckValidTransfer() = 0;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/map.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status Map::Init(const std::vector<int32_t>& array) {
   Status status = Array::Init(array);
   if (status != Status::SUCCESS) {

mindspore/ccsrc/parallel/tensor_layout/map.h

@@ -46,7 +46,6 @@ class Map : public Array {
  private:
   bool IsValidMap();
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/redistribution_layout_transfer.cc

@@ -21,7 +21,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status RedistributionLayoutTransfer::CheckValidTransfer() { return Status::SUCCESS; }
 
 /*
@@ -66,6 +65,5 @@ std::shared_ptr<ReshapeLayoutTransfer> RedistributionLayoutTransfer::UnifyDevice
   }
   return unified_device_arrangement_ptr->UnifyDeviceArrangementAndTensorShape();
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/tensor_layout/redistribution_layout_transfer.h

@@ -24,7 +24,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class RedistributionLayoutTransfer : public LayoutTransfer {
  public:
   RedistributionLayoutTransfer() = default;
@@ -35,7 +34,6 @@ class RedistributionLayoutTransfer : public LayoutTransfer {
   Status CheckValidTransfer() override;
   std::shared_ptr<ReshapeLayoutTransfer> UnifyDeviceArrangement() const;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/redistribution_operator_infer.cc

@@ -22,7 +22,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status RedistributionOperatorInfer::Init(const TensorLayout& tensor_layout, const Map& out_tensor_map,
                                          RankList dev_list) {
   in_tensor_map_ = tensor_layout.tensor_map();
@@ -273,6 +272,5 @@ Status RedistributionOperatorInfer::TransferConcatByAxis(Args args) {
   }
   return Status::SUCCESS;
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/tensor_layout/redistribution_operator_infer.h

@@ -28,7 +28,6 @@
 #include "utils/convert_utils.h"
 namespace mindspore {
 namespace parallel {
-
 using DeviceArrangement = std::vector<int32_t>;
 using TensorMap = std::vector<int32_t>;
 using TensorShape = std::vector<int32_t>;
@@ -69,7 +68,6 @@ class RedistributionOperatorInfer {
   RankList dev_list_;
   bool construct_op_flag_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/reshape_layout_transfer.cc

@@ -20,7 +20,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status ReshapeLayoutTransfer::CheckValidTransfer() {
   if (!IsSameDeviceArrangement()) {
     return Status::FAILED;

mindspore/ccsrc/parallel/tensor_layout/reshape_layout_transfer.h

@@ -23,7 +23,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class ReshapeLayoutTransfer : public LayoutTransfer {
  public:
   ReshapeLayoutTransfer() = default;
@@ -43,7 +42,6 @@ class ReshapeLayoutTransfer : public LayoutTransfer {
   bool FromTensorShapeCanBeExpandByTo() const;
   bool ToTensorShapeCanBeExpandByFrom() const;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/shape_util.cc

@@ -21,7 +21,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 /*
  * example:
  * shape = [2, 8, 32]
@@ -260,6 +259,5 @@ Status ExpandShape(const std::vector<int32_t>& in, const std::vector<int32_t>& e
   }
   return status;
 }
-
 }  // namespace parallel
 }  // namespace mindspore

mindspore/ccsrc/parallel/tensor_layout/shape_util.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 /*
  * compute the accumulating product of all the values in shape from left to right,
  * the accumulating results are saved in shape_accum from left to right
@@ -167,7 +166,6 @@ Status ExpandAccumulateProduct(const std::vector<int64_t>& in_accum_reverse,
  * out = [2, 4, 2, 4, 8]
  */
 Status ExpandShape(const std::vector<int32_t>& in, const std::vector<int32_t>& expand, std::vector<int32_t>* out);
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/tensor_info.h

@@ -28,7 +28,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 using Shapes = std::vector<Shape>;
 
 class TensorInfo {
@@ -55,7 +54,6 @@ class TensorInfo {
   // reduce method's reduce dim
   std::vector<int32_t> reduce_dim_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/tensor_layout.cc

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 std::string TensorLayout::ToString() const { return StandardToString() + OriginToString(); }
 
 std::string TensorLayout::StandardToString() const {
@@ -337,7 +336,7 @@ Status TensorLayout::UpdateTensorMap(uint32_t index, int32_t value) {
     MS_LOG(ERROR) << "Index is out of the size of the tensor map!";
     return Status::FAILED;
   }
-  Shape shape = tensor_map_.array();
+  auto shape = tensor_map_.array();
   shape[index] = value;
   if (tensor_map_.Init(shape) == Status::FAILED) {
     MS_LOG(ERROR) << "Update tensor map failed!";

mindspore/ccsrc/parallel/tensor_layout/tensor_layout.h

@@ -30,7 +30,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class TensorLayout {
  public:
   TensorLayout() = default;
@@ -94,7 +93,6 @@ class TensorLayout {
   Map tensor_map_;
   Arrangement tensor_shape_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore
 

mindspore/ccsrc/parallel/tensor_layout/tensor_redistribution.cc

@@ -24,7 +24,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 Status TensorRedistribution::Init(const TensorLayout& from, const TensorLayout& to, const RankList& dev_list) {
   from_origin_ = from;
   to_origin_ = to;

mindspore/ccsrc/parallel/tensor_layout/tensor_redistribution.h

@@ -33,7 +33,6 @@
 
 namespace mindspore {
 namespace parallel {
-
 class TensorRedistribution {
  public:
   explicit TensorRedistribution(bool construct_op_flag = true, bool keep_reshape = false)
@@ -83,7 +82,6 @@ class TensorRedistribution {
   bool construct_op_flag_;
   bool keep_reshape_;
 };
-
 }  // namespace parallel
 }  // namespace mindspore