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!6574 reviewbot warning clean

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Merge pull request !6574 from liubuyu/code_clean
pull/6574/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
parent 293a42723e fc7ea3db78
commit b94e85b303
20 changed files with 24 additions and 41 deletions
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7
build.bat
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@ -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
set BUILD_PATH=%CD%
cd %BUILD_PATH%
IF NOT EXIST "%BUILD_PATH%/mindspore" (
md "mindspore"

2
build.sh
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@ -237,7 +237,7 @@ 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))

1
include/inference.h
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@ -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

1
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/mirror_pad_gpu_kernel.h
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@ -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 {

1
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/mirror_pad_grad_gpu_kernel.h
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@ -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 {

1
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/roi_align_gpu_kernel.cc
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@ -27,6 +27,5 @@ MS_REG_GPU_KERNEL_ONE(
ROIAlign,
KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ROIAlignGpuFwdKernel, half)
} // namespace kernel
} // namespace mindspore

1
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/roi_align_grad_gpu_kernel.cc
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@ -27,6 +27,5 @@ MS_REG_GPU_KERNEL_ONE(
ROIAlignGrad,
KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ROIAlignGradGpuFwdKernel, half)
} // namespace kernel
} // namespace mindspore

4
mindspore/ccsrc/runtime/device/CMakeLists.txt
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@ -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})

1
mindspore/ccsrc/runtime/device/ascend/dump/data_dumper.cc
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@ -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_);

1
mindspore/ccsrc/runtime/device/gpu/gpu_common.h
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@ -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

1
mindspore/ccsrc/runtime/device/gpu/mpi/mpi_initializer.cc
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@ -25,7 +25,6 @@
namespace mindspore {
namespace device {
namespace gpu {
MPIInitializer &MPIInitializer::GetInstance() {
static MPIInitializer instance;
return instance;

2
model_zoo/official/cv/psenet/src/ETSNET/pse/adaptor.cpp
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@ -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;

4
model_zoo/official/lite/image_classification/app/src/main/cpp/MSNetWork.cpp
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@ -26,8 +26,7 @@ MSNetWork::MSNetWork(void) : session_(nullptr) {}
MSNetWork::~MSNetWork(void) {}
void
MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
void 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;
}

2
model_zoo/official/lite/image_classification/app/src/main/cpp/MSNetWork.h
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@ -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_;
};

13
model_zoo/official/lite/image_classification/app/src/main/cpp/MindSporeNetnative.cpp
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@ -145,9 +145,8 @@ char *CreateLocalModelBuffer(JNIEnv *env, jobject modelBuffer) {
* @param msOutputs
* @return
*/
std::string
ProcessRunnetResult(const int RET_CATEGORY_SUM, const char *const labels_name_map[],
std::unordered_map<std::string, mindspore::tensor::MSTensor *> msOutputs) {
std::string ProcessRunnetResult(const int RET_CATEGORY_SUM, const char *const labels_name_map[],
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);
ptr += info.width*4;
memcpy(ptr, data, info.width * 4);
ptr += info.width * 4;
data += info.stride;
}
ret = InitFromPixel(reinterpret_cast<const unsigned char *>(pixels_ptr),

2
model_zoo/official/lite/image_classification/app/src/main/cpp/MindSporeNetnative.h
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@ -18,6 +18,4 @@
#define MINDSPORE_JNI_HMS_DEBUG_MINDSPORENETNATIVE_H
#endif // MINDSPORE_JNI_HMS_DEBUG_MINDSPORENETNATIVE_H

3
model_zoo/official/lite/object_detection/app/src/main/cpp/MSNetWork.cpp
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@ -26,8 +26,7 @@ MSNetWork::MSNetWork(void) : session_(nullptr) {}
MSNetWork::~MSNetWork(void) {}
void
MSNetWork::CreateSessionMS(char *modelBuffer, size_t bufferLen, mindspore::lite::Context *ctx) {
void 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.");

2
model_zoo/official/lite/object_detection/app/src/main/cpp/MSNetWork.h
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@ -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_;
};

15
model_zoo/official/lite/object_detection/app/src/main/cpp/MindSporeNetnative.cpp
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@ -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);
ptr += info.width*4;
memcpy(ptr, data, 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,
mindspore::tensor::MSTensor *> msOutputs,
std::string ProcessRunnetResult(std::unordered_map<std::string, 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 *tmpdata = reinterpret_cast<float * >(branch2_tensor->MutableData());
float *tmpscores2 = reinterpret_cast<float *>(branch1_tensor->MutableData());
float *tmpdata = reinterpret_cast<float *>(branch2_tensor->MutableData());
// Using ssd model util to process model branch outputs.
SSDModelUtil ssdUtil(srcImageWidth, srcImageHeight);

1
model_zoo/official/lite/object_detection/app/src/main/cpp/ssd_util/ssd_util.cpp
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@ -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;

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