clean code

mindspore/ccsrc/backend/kernel_compiler/gpu/math/matrix_inverse_gpu_kernel.h

@@ -89,7 +89,6 @@ class MatrixInverseGpuKernel : public GpuKernel {
     kernel_node_ = kernel_node;
     handle_ = device::gpu::GPUDeviceManager::GetInstance().GetCublasHandle();
     auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
-
     if (input_shape.empty() || input_shape.size() < 2) {
       MS_LOG(EXCEPTION) << "The dim entered needs to be greater than 2, but " << input_shape.size() << " was taken";
     }

mindspore/ccsrc/backend/kernel_compiler/hccl/hcom_all_broadcast.cc

@@ -33,7 +33,6 @@ bool HcomAllBroadCastKernel::Launch(const std::vector<AddressPtr> &inputs,
   MS_EXCEPTION_IF_NULL(stream_ptr);
   auto hccl_result = HcclBroadcast(inputs[0]->addr, hccl_count_, hccl_data_type_list_[0], root_id_,
                                    HcclContext::GetInstance().hccl_comm(), stream_ptr);
-
   if (hccl_result != HCCL_SUCCESS) {
     MS_LOG(ERROR) << "HcomBroadcastOp : hcom_broadcast fail, return: " << hccl_result;
     return false;

mindspore/ccsrc/backend/optimizer/somas/somas_solver_core.cc

@@ -33,7 +33,6 @@ using std::vector;
 
 namespace mindspore {
 namespace somas {
-
 Status SomasSolverCore::MemoryAllocationSolver() {
   auto start = std::chrono::system_clock::now();
   Status retval = SUCCESS;

mindspore/ccsrc/backend/optimizer/somas/somas_solver_pre.cc

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace somas {
-
 constexpr auto kSolNumThresholdMultiThread = 8;
 Status SomasSolverPre::checkTensors(TensorsDescMap *pTensors, uint32_t index1, uint32_t index2) {
   auto &tensors = *pTensors;

mindspore/ccsrc/backend/session/ascend_inference_session.cc

@@ -212,6 +212,5 @@ std::string AscendInferenceSession::InputsInfo(const std::vector<ParameterPtr> &
   }
   return graph + "   " + actual;
 }
-
 }  // namespace session
 }  // namespace mindspore

mindspore/ccsrc/runtime/device/ascend/ascend_stream_assign.cc

@@ -63,7 +63,6 @@ bool IsSameServer(const std::vector<uint32_t> &rank_ids) {
 
 string DoGetHcomGroup(const string &original_group) {
   string communi_parallel_mode = parallel::ParallelContext::GetInstance()->communi_parallel_mode();
-
   if (communi_parallel_mode == parallel::ALL_GROUP_PARALLEL) {
     return original_group;
   }

mindspore/ccsrc/runtime/device/ascend/profiling/profiling_manager.cc

@@ -112,7 +112,6 @@ void ProfilingManager::PluginUnInit() const {
 
 Status ProfilingManager::GetProfConf(const NotNull<MsprofGeOptions *> prof) {
   string job_id = std::to_string(GetJobId());
-
   if (memcpy_s(prof->jobId, sizeof(prof->jobId), job_id.c_str(), strlen(job_id.c_str())) != EOK) {
     MS_LOG(ERROR) << "Copy job_id failed.";
     return PROF_FAILED;

mindspore/ccsrc/runtime/device/cpu/cpu_memory_manager.cc

@@ -21,7 +21,6 @@
 namespace mindspore {
 namespace device {
 namespace cpu {
-
 uint8_t *CPUMemoryManager::MallocStaticMem(size_t size, bool, uint32_t) {
   void *ptr = malloc(size);
   if (ptr != nullptr) {

mindspore/ccsrc/runtime/device/executor/dynamic_kernel.h

@@ -27,7 +27,6 @@
 
 namespace mindspore {
 namespace device {
-
 class DynamicKernel {
  public:
   DynamicKernel(void *stream, const CNodePtr &cnode_ptr)

mindspore/ccsrc/runtime/device/gpu/gpu_kernel_runtime.cc

@@ -1268,7 +1268,6 @@ session::KernelWithIndex GPUKernelRuntime::GetPrevNodeOutput(const AnfNodePtr &n
 
   return addr_iter->second[i];
 }
-
 }  // namespace gpu
 }  // namespace device
 }  // namespace mindspore