!30175 [MS][lite][providers]codex

Merge pull request !30175 from KXiong/master

mindspore/lite/providers/nnie/src/nnie_common.cc

@@ -22,10 +22,10 @@
 
 using mindspore::lite::RET_ERROR;
 using mindspore::lite::RET_OK;
-constexpr int kSleepUs = 100;
 
 namespace mindspore {
 namespace nnie {
+constexpr int kSleepUs = 100;
 static void NnieParamRelease(NnieParam *nnie_param) {
   if (nnie_param == nullptr) {
     return;
@@ -179,7 +179,8 @@ static void GetBlobMemSize(SVP_NNIE_NODE_S nnie_node[], HI_U32 node_num, HI_U32
 }
 
 static int GetTaskAndBlobBufSize(NnieCfg *nnie_cfg, NnieParam *nnie_param, HI_U32 *total_task_buf_size,
-                                 HI_U32 *tmp_buf_size, NnieBlobSize blob_size[], HI_U32 *total_size) {
+                                 HI_U32 *tmp_buf_size, NnieBlobSize blob_size[], HI_U32 blob_size_len,
+                                 HI_U32 *total_size) {
   HI_S32 ret = HI_SUCCESS;
   HI_U32 i, j;
   HI_U32 total_step = 0;
@@ -199,7 +200,7 @@ static int GetTaskAndBlobBufSize(NnieCfg *nnie_cfg, NnieParam *nnie_param, HI_U3
   *tmp_buf_size = nnie_param->model_->u32TmpBufSize;
   *total_size += *total_task_buf_size + *tmp_buf_size;
 
-  for (i = 0; i < nnie_param->model_->u32NetSegNum; i++) {
+  for (i = 0; i < nnie_param->model_->u32NetSegNum && i < blob_size_len; i++) {
     if (SVP_NNIE_NET_TYPE_RECURRENT == nnie_param->model_->astSeg[i].enNetType) {
       for (j = 0; j < nnie_param->seg_data_[i].src_[0].u32Num; j++) {
         total_step += *(reinterpret_cast<HI_S32 *>(
@@ -219,9 +220,7 @@ static int GetTaskAndBlobBufSize(NnieCfg *nnie_cfg, NnieParam *nnie_param, HI_U3
 
 static int NnieParamInit(NnieCfg *nnie_cfg, NnieParam *nnie_param) {
   HI_U32 i, j;
-  HI_U32 total_size = 0;
-  HI_U32 total_task_buf_size = 0;
-  HI_U32 tmp_buf_size_ = 0;
+  HI_U32 total_size = 0, total_task_buf_size = 0, tmp_buf_size_ = 0;
   HI_S32 ret = HI_SUCCESS;
   HI_U32 off_set = 0;
   HI_U64 phy_addr = 0;
@@ -230,7 +229,9 @@ static int NnieParamInit(NnieCfg *nnie_cfg, NnieParam *nnie_param) {
 
   FillForwardInfo(nnie_cfg, nnie_param);
 
-  ret = GetTaskAndBlobBufSize(nnie_cfg, nnie_param, &total_task_buf_size, &tmp_buf_size_, blob_size, &total_size);
+  HI_U32 blob_size_len = sizeof(blob_size) / sizeof(blob_size[0]);
+  ret = GetTaskAndBlobBufSize(nnie_cfg, nnie_param, &total_task_buf_size, &tmp_buf_size_, blob_size, blob_size_len,
+                              &total_size);
   if (HI_SUCCESS != ret) {
     LOGE("Error,Malloc memory failed! ");
     return RET_ERROR;

mindspore/lite/providers/nnie/src/nnie_manager.cc

@@ -21,10 +21,10 @@
 
 using mindspore::lite::RET_ERROR;
 using mindspore::lite::RET_OK;
-constexpr int kNumInput2 = 2;
 
 namespace mindspore {
 namespace nnie {
+constexpr int kNumInput2 = 2;
 int NNIEManager::CfgInit(int max_roi_num, int step, const std::vector<int> &core_id) {
   memset(&nnie_cfg_, 0, sizeof(NnieRunCfg));
 
@@ -80,10 +80,7 @@ int NNIEManager::Run(std::vector<mindspore::MSTensor> *outputs, unsigned int seg
   return RET_OK;
 }
 
-void NNIEManager::Release() {
-  // NniePrintReportResult(&nnie_cfg_.param_);
-  NnieCommDelete(&nnie_cfg_.param_, &nnie_cfg_.model_);
-}
+void NNIEManager::Release() { NnieCommDelete(&nnie_cfg_.param_, &nnie_cfg_.model_); }
 
 int NNIEManager::GetOutputData(std::vector<mindspore::MSTensor> *outputs,
                                const std::vector<std::vector<int64_t>> &outputs_shape, bool run_box) {

mindspore/lite/providers/nnie_proposal/src/proposal.cc

@@ -22,11 +22,11 @@
 
 using mindspore::lite::RET_ERROR;
 using mindspore::lite::RET_OK;
-constexpr int kNumInput2 = 2;
-constexpr int kNCHWDims = 4;
 
 namespace mindspore {
 namespace proposal {
+constexpr int kNumInput2 = 2;
+constexpr int kNCHWDims = 4;
 uint32_t RpnTmpBufSize(uint32_t num_ratio_anchors, uint32_t num_scale_anchors, uint32_t input_height,
                        uint32_t input_width) {
   uint32_t anchors_num = num_ratio_anchors * num_scale_anchors * input_height * input_width;
@@ -156,6 +156,10 @@ static int32_t NonRecursiveArgQuickSort(int32_t *array, int32_t low, int32_t hig
 
 static int32_t FilterLowScoreBbox(int32_t *proposals, uint32_t anchors_num, uint32_t filter_thresh,
                                   uint32_t *num_after_filter) {
+  if (proposals == nullptr) {
+    LOGE("inputs proposals is nullptr");
+    return RET_ERROR;
+  }
   uint32_t proposal_cnt = anchors_num;
 
   if (filter_thresh > 0) {
@@ -222,6 +226,10 @@ static int32_t SVP_NNIE_Overlap(int32_t x_min1, int32_t y_min1, int32_t x_max1,
 
 static int32_t SVP_NNIE_NonMaxSuppression(int32_t *proposals, uint32_t anchors_num, uint32_t nms_thresh,
                                           uint32_t max_roi_num) {
+  if (proposals == nullptr) {
+    LOGE("inputs proposals is nullptr");
+    return RET_ERROR;
+  }
   /****** define variables *******/
   int32_t x_min1;
   int32_t y_min1;
@@ -276,7 +284,6 @@ static void Rpn(float **inputs, uint32_t num_ratio_anchors, uint32_t num_scale_a
                 uint32_t min_size, uint32_t spatial_scale, uint32_t nms_thresh, uint32_t filter_thresh,
                 uint32_t num_before_nms, char *pu32MemPool, float *proposal_result, uint32_t dst_stride,
                 uint32_t *num_rois) {
-#if 1
   /******************** define parameters ****************/
   uint32_t size;
   int32_t *anchors = nullptr;
@@ -400,6 +407,10 @@ static void Rpn(float **inputs, uint32_t num_ratio_anchors, uint32_t num_scale_a
 
   /******************* Copy the anchors to every pixel in the feature map ******************/
   ptr1 = anchors;
+  if (spatial_scale == 0) {
+    LOGE("inputs spatial_scale is zero.");
+    return;
+  }
   pixel_interval = QUANT_BASE / spatial_scale;
 
   for (p = 0; p < inputs_height[0]; p++) {
@@ -527,7 +538,6 @@ static void Rpn(float **inputs, uint32_t num_ratio_anchors, uint32_t num_scale_a
   }
 
   *num_rois = roi_count;
-#endif
 }
 
 int32_t ProposalInit(ProposalParam *param, const std::vector<mindspore::MSTensor> &inputs, uint32_t max_roi_num,

mindspore/lite/providers/nnie_proposal/src/proposal_fp32.cc

@@ -25,13 +25,13 @@
 using mindspore::lite::RET_ERROR;
 using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_Custom;
+
+namespace mindspore {
+namespace proposal {
 constexpr int kMaxSize = 1024;
 constexpr int kNumInput2 = 2;
 constexpr int kDecimal = 10;
 constexpr auto kMazRoiNum = "MaxROINum";
-
-namespace mindspore {
-namespace proposal {
 bool IsValidUnsignedNum(const std::string &num_str) {
   return !num_str.empty() && std::all_of(num_str.begin(), num_str.end(), ::isdigit);
 }
@@ -186,8 +186,6 @@ std::shared_ptr<mindspore::kernel::Kernel> ProposalCreateKernel(const std::vecto
   }
 
   auto kernel = std::make_shared<ProposalCPUKernel>(inputs, outputs, primitive, ctx, ndims, image_height, image_width);
-  // auto kernel = new (std::nothrow) ProposalCPUKernel(inputs, outputs, primitive, ctx, ndims, image_height,
-  // image_width);
   if (kernel == nullptr) {
     LOGE("new custom kernel is nullptr");
     return nullptr;

mindspore/lite/providers/nnie_proposal/src/proposal_infer.cc

@@ -67,7 +67,6 @@ Status ProposalInterface::Infer(std::vector<mindspore::MSTensor> *inputs, std::v
 }  // namespace mindspore
 namespace mindspore {
 namespace kernel {
-// static KernelInterfaceReg a(aa, schema::PrimitiveType_Custom, CustomInferCreater);
 REGISTER_CUSTOM_KERNEL_INTERFACE(NNIE, Proposal, proposal::ProposalInferCreater);
 }  // namespace kernel
 }  // namespace mindspore