code warning clean

build.bat

@@ -16,12 +16,13 @@
 @title mindspore_build
 
 SET BASEPATH=%CD%
-IF NOT EXIST "%BASEPATH%/build" (
+SET BUILD_PATH=%BASEPATH%/build
+
+IF NOT EXIST "%BUILD_PATH%" (
     md "build"
 )
 
-cd %BASEPATH%/build
+cd %BUILD_PATH%
-set BUILD_PATH=%CD%
 
 IF NOT EXIST "%BUILD_PATH%/mindspore" (
     md "mindspore"

build.sh

@@ -235,7 +235,7 @@ checkopts()
         ;;
       z)
         eval ARG=\$\{$OPTIND\}
-        if [[ -n $ARG && $ARG != -* ]]; then
+        if [[ -n "$ARG" && "$ARG" != -* ]]; then
           OPTARG="$ARG"
           check_on_off $OPTARG z
           OPTIND=$((OPTIND + 1))

include/inference.h

@@ -81,7 +81,6 @@ class MS_API InferSession {
   }
   static std::shared_ptr<InferSession> CreateSession(const std::string &device, uint32_t device_id);
 };
-
 }  // namespace inference
 }  // namespace mindspore
 #endif  // MINDSPORE_INCLUDE_MS_SESSION_H

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/mirror_pad_gpu_kernel.h

@@ -66,7 +66,6 @@ class MirrorPadGpuFwdKernel : public GpuKernel {
     }
 
     string mode = GetValue<string>(AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("mode"));
-
     if (mode == "REFLECT") {
       mode_ = 0;  // reflected mirroring
     } else {

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/mirror_pad_grad_gpu_kernel.h

@@ -66,7 +66,6 @@ class MirrorPadGpuBackKernel : public GpuKernel {
     }
 
     string mode = GetValue<string>(AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("mode"));
-
     if (mode == "REFLECT") {
       mode_ = 0;  // reflected mirroring
     } else {

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/roi_align_gpu_kernel.cc

@@ -27,6 +27,5 @@ MS_REG_GPU_KERNEL_ONE(
   ROIAlign,
   KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
   ROIAlignGpuFwdKernel, half)
-
 }  // namespace kernel
 }  // namespace mindspore

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/roi_align_grad_gpu_kernel.cc

@@ -27,6 +27,5 @@ MS_REG_GPU_KERNEL_ONE(
   ROIAlignGrad,
   KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
   ROIAlignGradGpuFwdKernel, half)
-
 }  // namespace kernel
 }  // namespace mindspore

mindspore/ccsrc/runtime/device/CMakeLists.txt

@@ -14,12 +14,12 @@ endif ()
 
 if (ENABLE_CPU)
     file(GLOB_RECURSE CPU_SRC_LIST RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "cpu/*.cc")
-    list(REMOVE_ITEM CPU_SRC_LIST "cpu/mpi/mpi_adapter.cc", "cpu/mpi/mpi_export.cc")
+    list(REMOVE_ITEM CPU_SRC_LIST "cpu/mpi/mpi_adapter.cc" "cpu/mpi/mpi_export.cc")
 endif ()
 
 if (ENABLE_MPI)
     if (ENABLE_CPU)
-        file(GLOB_RECURSE MPI_SRC_LIST "cpu/mpi/mpi_adapter.cc", "cpu/mpi/mpi_export.cc")
+        file(GLOB_RECURSE MPI_SRC_LIST "cpu/mpi/mpi_adapter.cc" "cpu/mpi/mpi_export.cc")
         set_property(SOURCE ${MPI_SRC_LIST}
             PROPERTY COMPILE_DEFINITIONS SUBMODULE_ID=mindspore::SubModuleId::SM_DEVICE)
         add_library(mpi_adapter SHARED ${MPI_SRC_LIST})

mindspore/ccsrc/runtime/device/ascend/dump/data_dumper.cc

@@ -57,7 +57,6 @@ constexpr const char *kOpTypeOpDebug = "Opdebug";
 namespace mindspore {
 namespace device {
 namespace ascend {
-
 DataDumper::~DataDumper() {
   ReleaseDevMem(&dev_load_mem_);
   ReleaseDevMem(&dev_unload_mem_);

mindspore/ccsrc/runtime/device/gpu/gpu_common.h

@@ -141,7 +141,6 @@ inline bool CheckNullInput(std::vector<size_t> input_shape) {
       MS_LOG(EXCEPTION) << "CUAD curand Error: " << message << " | curandStatus: " << status; \
     }                                                                                         \
   }
-
 }  // namespace gpu
 }  // namespace device
 }  // namespace mindspore

mindspore/ccsrc/runtime/device/gpu/mpi/mpi_initializer.cc

@@ -25,7 +25,6 @@
 namespace mindspore {
 namespace device {
 namespace gpu {
-
 MPIInitializer &MPIInitializer::GetInstance() {
   static MPIInitializer instance;
   return instance;

mindspore/ccsrc/utils/scoped_long_running.h

@@ -21,7 +21,6 @@
 #include <utility>
 
 namespace mindspore {
-
 // Base Class for scoped long running code.
 // Enter() should release some global resoure, like Python GIL;
 // Leave() should acquire the same global resource released.

model_zoo/official/cv/psenet/src/ETSNET/pse/adaptor.cpp

@@ -63,10 +63,8 @@ namespace pse_adaptor {
             vector<int> row(label_mat.cols);
             for (int y = 0; y < label_mat.cols; ++y) {
                 int label = label_mat.at<int>(x, y);
-
                 if (label == 0) continue;
                 if (area[label] < min_area) continue;
-
                 Point point(x, y);
                 queue.push(point);
                 row[y] = label;

model_zoo/official/lite/image_classification/app/src/main/cpp/MSNetWork.cpp

@@ -26,8 +26,7 @@ MSNetWork::MSNetWork(void) : session_(nullptr) {}
 
 MSNetWork::~MSNetWork(void) {}
 
-void
+void MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
-MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
   session_ = mindspore::session::LiteSession::CreateSession(ctx);
   if (session_ == nullptr) {
     MS_PRINT("Create Session failed.");
@@ -52,4 +51,3 @@ int MSNetWork::ReleaseNets(void) {
   delete session_;
   return 0;
 }
-

model_zoo/official/lite/image_classification/app/src/main/cpp/MSNetWork.h

@@ -52,7 +52,7 @@ class MSNetWork {
 
   int ReleaseNets(void);
 
-  mindspore::session::LiteSession * session() const { return session_; }
+  mindspore::session::LiteSession *session() const { return session_; }
  private:
   mindspore::session::LiteSession *session_;
 };

model_zoo/official/lite/image_classification/app/src/main/cpp/MindSporeNetnative.cpp

@@ -145,9 +145,8 @@ char *CreateLocalModelBuffer(JNIEnv *env, jobject modelBuffer) {
  * @param msOutputs
  * @return
  */
-std::string
+std::string ProcessRunnetResult(const int RET_CATEGORY_SUM, const char *const labels_name_map[],
-ProcessRunnetResult(const int RET_CATEGORY_SUM, const char *const labels_name_map[],
+                                std::unordered_map<std::string, mindspore::tensor::MSTensor *> msOutputs) {
-                    std::unordered_map<std::string, mindspore::tensor::MSTensor *> msOutputs) {
   // Get the branch of the model output.
   // Use iterators to get map elements.
   std::unordered_map<std::string, mindspore::tensor::MSTensor *>::iterator iter;
@@ -160,7 +159,7 @@ ProcessRunnetResult(const int RET_CATEGORY_SUM, const char *const labels_name_ma
   MS_PRINT("Number of tensor elements:%d", tensorNum);
 
   // Get a pointer to the first score.
-  float *temp_scores = static_cast<float * >(outputTensor->MutableData());
+  float *temp_scores = static_cast<float *>(outputTensor->MutableData());
 
   float scores[RET_CATEGORY_SUM];
   for (int i = 0; i < RET_CATEGORY_SUM; ++i) {
@@ -202,12 +201,12 @@ bool BitmapToLiteMat(JNIEnv *env, const jobject &srcBitmap, LiteMat *lite_mat) {
       MS_PRINT("Init From RGBA error");
     }
   } else {
-    unsigned char *pixels_ptr = new unsigned char[info.width*info.height*4];
+    unsigned char *pixels_ptr = new unsigned char[info.width * info.height * 4];
     unsigned char *ptr = pixels_ptr;
     unsigned char *data = reinterpret_cast<unsigned char *>(pixels);
     for (int i = 0; i < info.height; i++) {
-      memcpy(ptr, data, info.width*4);
+      memcpy(ptr, data, info.width * 4);
-      ptr += info.width*4;
+      ptr += info.width * 4;
       data += info.stride;
     }
     ret = InitFromPixel(reinterpret_cast<const unsigned char *>(pixels_ptr),

model_zoo/official/lite/image_classification/app/src/main/cpp/MindSporeNetnative.h

@@ -18,6 +18,4 @@
 #define MINDSPORE_JNI_HMS_DEBUG_MINDSPORENETNATIVE_H
 
 
-
-
 #endif  // MINDSPORE_JNI_HMS_DEBUG_MINDSPORENETNATIVE_H

model_zoo/official/lite/object_detection/app/src/main/cpp/MSNetWork.cpp

@@ -26,8 +26,7 @@ MSNetWork::MSNetWork(void) : session_(nullptr) {}
 
 MSNetWork::~MSNetWork(void) {}
 
-void
+void MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
-MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
   session_ = mindspore::session::LiteSession::CreateSession(ctx);
   if (session_ == nullptr) {
     MS_PRINT("Create Session failed.");

model_zoo/official/lite/object_detection/app/src/main/cpp/MSNetWork.h

@@ -52,7 +52,7 @@ class MSNetWork {
 
   int ReleaseNets(void);
 
-  mindspore::session::LiteSession * session() const { return session_; }
+  mindspore::session::LiteSession *session() const { return session_; }
  private:
   mindspore::session::LiteSession *session_;
 };

model_zoo/official/lite/object_detection/app/src/main/cpp/MindSporeNetnative.cpp

@@ -45,7 +45,7 @@ bool BitmapToLiteMat(JNIEnv *env, const jobject &srcBitmap, LiteMat *lite_mat) {
     return false;
   }
   AndroidBitmap_lockPixels(env, srcBitmap, &pixels);
-  if (info.stride == info.width*4) {
+  if (info.stride == info.width * 4) {
     ret = InitFromPixel(reinterpret_cast<const unsigned char *>(pixels),
                         LPixelType::RGBA2RGB, LDataType::UINT8,
                         info.width, info.height, lite_mat_bgr);
@@ -53,12 +53,12 @@ bool BitmapToLiteMat(JNIEnv *env, const jobject &srcBitmap, LiteMat *lite_mat) {
       MS_PRINT("Init From RGBA error");
     }
   } else {
-    unsigned char *pixels_ptr = new unsigned char[info.width*info.height*4];
+    unsigned char *pixels_ptr = new unsigned char[info.width * info.height * 4];
     unsigned char *ptr = pixels_ptr;
     unsigned char *data = reinterpret_cast<unsigned char *>(pixels);
     for (int i = 0; i < info.height; i++) {
-      memcpy(ptr, data, info.width*4);
+      memcpy(ptr, data, info.width * 4);
-      ptr += info.width*4;
+      ptr += info.width * 4;
       data += info.stride;
     }
     ret = InitFromPixel(reinterpret_cast<const unsigned char *>(pixels_ptr),
@@ -110,8 +110,7 @@ char *CreateLocalModelBuffer(JNIEnv *env, jobject modelBuffer) {
  * @param srcImageHeight The height of the original input image.
  * @return
  */
-std::string ProcessRunnetResult(std::unordered_map<std::string,
+std::string ProcessRunnetResult(std::unordered_map<std::string, mindspore::tensor::MSTensor *> msOutputs,
-        mindspore::tensor::MSTensor *> msOutputs,
                                 int srcImageWidth, int srcImageHeight) {
   std::unordered_map<std::string, mindspore::tensor::MSTensor *>::iterator iter;
   iter = msOutputs.begin();
@@ -124,8 +123,8 @@ std::string ProcessRunnetResult(std::unordered_map<std::string,
   MS_PRINT("%s %s", branch1_string.c_str(), branch2_string.c_str());
 
   // ----------- 接口测试 --------------------------
-  float *tmpscores2 = reinterpret_cast<float * >(branch1_tensor->MutableData());
+  float *tmpscores2 = reinterpret_cast<float *>(branch1_tensor->MutableData());
-  float *tmpdata = reinterpret_cast<float * >(branch2_tensor->MutableData());
+  float *tmpdata = reinterpret_cast<float *>(branch2_tensor->MutableData());
 
   // Using ssd model util to process model branch outputs.
   SSDModelUtil ssdUtil(srcImageWidth, srcImageHeight);

model_zoo/official/lite/object_detection/app/src/main/cpp/ssd_util/ssd_util.cpp

@@ -177,7 +177,6 @@ void SSDModelUtil::getDefaultBoxes() {
             tempWHBox.boxw = h;
             tempWHBox.boxh = w;
             all_sizes.push_back(tempWHBox);
-
         } else {
             // len(all_sizes) = 6.
             tempWHBox.boxw = sk1;