!377 c79 opensource告警清除

Merge pull request !377 from 赵鲁鹏/c79_open

parser/caffe/caffe_custom_parser_adapter.cc

@@ -85,10 +85,10 @@ Status CaffeCustomParserAdapter::ParseWeights(const Message *op_src, ge::NodePtr
     return SUCCESS;
   }
 
-  bool bias_en = false;
   bool update_in_turn = (static_cast<int64_t >(op->GetAllInputsSize()) == (layer->bottom_size() + layer->blobs_size()));
   int start_pos = layer->bottom_size();
   for (int i = 0; i < layer->blobs_size(); ++i) {
+    bool bias_en = false;
     ge::GeTensorPtr weight = ge::parser::MakeShared<ge::GeTensor>();
     GE_CHECK_NOTNULL(weight);
     GE_CHK_STATUS_RET(ConvertWeight(layer->blobs(i), layer->name(), weight),

parser/caffe/caffe_parser.cc

@@ -857,8 +857,7 @@ Status CaffeModelParser::AddNode(const domi::caffe::LayerParameter &layer, ge::C
   // AddConstInput is a function defined in caffe_op_parser, override in caffe_reshape_parser.
   std::shared_ptr<CaffeOpParser> caffe_op_parser = std::static_pointer_cast<CaffeOpParser>(op_parser);
   GE_CHECK_NOTNULL(caffe_op_parser);
-  Status status;
-  status = caffe_op_parser->AddConstInput(node);
+  Status status = caffe_op_parser->AddConstInput(node);
   if (status != SUCCESS) {
     REPORT_CALL_ERROR("E19999", "AddConstInput failed for node:%s", node->GetOpDesc()->GetName().c_str());
     GELOGE(FAILED, "[Add][ConstInput] to node %s fail.", node->GetOpDesc()->GetName().c_str());
@@ -938,7 +937,7 @@ Status CaffeModelParser::AddTensorDescToOpDescByIr(ge::OpDescPtr &op_desc, const
     for (int i = 0; i < valid_input_size; i++) {
       ge::GeTensorDesc input_tensor;
       std::string input_name;
-      ge::graphStatus ret = ge::GRAPH_SUCCESS;
+      ge::graphStatus ret;
       // Below cases are supported fow now when there are optional inputs
       // x means optional, o means requierd input
       // a. ooxxx, number of o and x>=layer.bottom_size+layer.blobs_size>=number of o

parser/common/acl_graph_parser_util.h

@@ -230,8 +230,6 @@ inline domi::Status CheckInt64Uint32MulOverflow(int64_t a, uint32_t b) {
 }  // namespace parser
 }  // namespace ge
 
-/*lint --emacro((773),GE_TIMESTAMP_START)*/
-/*lint -esym(773,GE_TIMESTAMP_START)*/
 #define PARSER_TIMESTAMP_START(stage) uint64_t startUsec_##stage = ge::parser::GetCurrentTimestamp()
 
 #define PARSER_TIMESTAMP_END(stage, stage_name)                                       \

parser/common/op_map.h

@@ -21,7 +21,6 @@
 #include <string>
 #include <vector>
 
-/*lint -e1073*/
 namespace ge {
 // the operator type mapping table of caffe and  mindspore
 extern std::map<std::string, std::string> caffe_op_map;
@@ -41,5 +40,4 @@ extern std::vector<std::string> is_dataset_op_vec;
 // output tensor num
 extern std::map<std::string, int32_t> op_output_tensor_num;
 }  // namespace ge
-/*lint +e1073*/
 #endif  // GE_COMMON_OP_MAP_H_

parser/common/op_parser_factory.h

@@ -101,7 +101,7 @@ class OpParserFactory {
    * @ingroup domi_omg
    * @brief Each Op corresponds to a Creator function
    */
-  std::map<std::string, CREATOR_FUN> op_parser_creator_map_;  // lint !e1073
+  std::map<std::string, CREATOR_FUN> op_parser_creator_map_;
   std::map<std::string, CREATOR_FUN> fusion_op_parser_creator_map_;
 
   friend class OpParserRegisterar;

parser/common/parser_fp16_t.cc

@@ -675,8 +675,7 @@ static uint16_t Fp16Div(uint16_t v_1, uint16_t v_2) {
     uint64_t m_tmp;
     if (e_a > e_b) {
       m_tmp = m_a;
-      uint16_t tmp;
-      tmp = e_a - e_b;
+      uint16_t tmp = e_a - e_b;
       for (int i = 0; i < tmp; i++) {
         m_tmp = m_tmp << 1;
       }
@@ -690,8 +689,7 @@ static uint16_t Fp16Div(uint16_t v_1, uint16_t v_2) {
       m_b = m_tmp;
     }
     m_div = static_cast<float>(m_a * 1.0f / m_b);
-    fp16_t fp_div;
-    fp_div = m_div;
+    fp16_t fp_div = m_div;
     ret = fp_div.val;
     if (s_a != s_b) {
       ret |= kFp16SignMask;

parser/onnx/subgraph_adapter/subgraph_adapter_factory.h

@@ -77,7 +77,7 @@ protected:
   void RegisterCreator(const std::string &type, CREATOR_FUN fun);
 
 private:
-  std::map<std::string, CREATOR_FUN> subgraph_adapter_creator_map_;  // lint !e1073
+  std::map<std::string, CREATOR_FUN> subgraph_adapter_creator_map_;
 
   friend class SubgraphAdapterRegisterar;
 };

parser/tensorflow/graph_optimizer.cc

@@ -858,7 +858,6 @@ Status CreateNodeDefBytes(ge::NodePtr n, string originalType, map<string, PIOLis
   // Set size
   for (auto ge_desc : opDesc->GetAllOutputsDescPtr()) {
     int64_t real_size = 1;
-    int64_t tmp_dim = 0;
     auto data_type = ge_desc->GetDataType();
 
     uint32_t size_type = 1;
@@ -873,7 +872,7 @@ Status CreateNodeDefBytes(ge::NodePtr n, string originalType, map<string, PIOLis
 
     // calculate size
     for (uint32_t j = 0; j < ge_desc->GetShape().GetDimNum(); ++j) {
-      tmp_dim = ge_desc->GetShape().GetDim(j);
+      int64_t tmp_dim = ge_desc->GetShape().GetDim(j);
       GE_CHECK_GE(tmp_dim, 0);
       PARSER_INT64_MULCHECK(real_size, tmp_dim);
       real_size *= tmp_dim;
@@ -1279,8 +1278,7 @@ Status CreateFuncDefBytes(ge::NodePtr n, string original_type, string func_bin_p
 
   GELOGI("len =%d\n", len);
 
-  ge::GeAttrValue::BYTES funcDefBytes;
-  funcDefBytes = ge::Buffer::CopyFrom((std::uint8_t *)buf, len);
+  ge::GeAttrValue::BYTES funcDefBytes = ge::Buffer::CopyFrom((std::uint8_t *)buf, len);
   (void)ge::AttrUtils::SetBytes(opDesc, ge::ATTR_NAME_FRAMEWORK_FUNC_DEF, funcDefBytes);
   GELOGI("funcDefBytes.GetSize() =%zu", funcDefBytes.GetSize());
 

parser/tensorflow/tensorflow_parser.cc

@@ -1049,11 +1049,9 @@ Status TensorFlowModelParser::AdaptOpType(const domi::tensorflow::NodeDef *node_
     op_type = tensorflow_train_op_map.at(node_op);
     GE_CHK_STATUS_RET(CheckOpType(node_def, op_type), "Failed to check op type");
   } else {
-    op_type = ge::parser::FRAMEWORKOP;
     domi::tensorflow::AttrValue attr_call_inference;
     if ((node_name == node_op) &&
         ge::TensorFlowUtil::FindAttrValue(node_def, "_disable_call_shape_inference", attr_call_inference)) {
-      op_type = node_op;
     }
   }
 
@@ -1688,7 +1686,6 @@ Status TensorFlowModelParser::CheckInputNodeName(const string &input_node_name,
     }
   }
 
-  int32_t tmp_index = 0;
   auto find = tmp_input_node_name.find(":");
   if (find == string::npos) {
     *node_name = tmp_input_node_name;
@@ -1696,6 +1693,7 @@ Status TensorFlowModelParser::CheckInputNodeName(const string &input_node_name,
     if (index == nullptr) {
       return SUCCESS;
     }
+    int32_t tmp_index = 0;
     *index = tmp_index;
 
     return SUCCESS;
@@ -2060,15 +2058,14 @@ Status TensorFlowModelParser::EraseNormalOpOutputIfChild(shared_ptr<ge::ScopeGra
   for (auto iter = normal_op_node_context.output_map.begin(); iter != normal_op_node_context.output_map.end();) {
     string output_node_name = iter->first;
     ge::ScopeFusionOpInfo to_info;
-    int32_t from_index = 0;
-    int32_t to_index = 0;
 
     if (IsFusionOpChild(output_node_name, &to_info) &&
         nodedef_map_[output_node_name]->op() != TENSORFLOWF_NODE_OP_CONST) {
       // Fuse operator, update index
       std::vector<std::pair<int32_t, int32_t>> &pairs = iter->second;
       for (auto &pair : pairs) {
-        from_index = pair.first;
+        int32_t from_index = pair.first;
+        int32_t to_index = 0;
         GE_RETURN_WITH_LOG_IF_ERROR(GetInPutIndex(scope_graph, to_info, pair.second, to_index),
                                     "GetInPutIndex failed ,output_node_name %s.", output_node_name.c_str());
         tmp_output_map[to_info.fusion_node_name].push_back({from_index, to_index});
@@ -2097,15 +2094,14 @@ Status TensorFlowModelParser::UpdateNormalOpContext(shared_ptr<ge::ScopeGraph> &
   for (auto iter = normal_op_node_context.input_map.begin(); iter != normal_op_node_context.input_map.end();) {
     string input_node_name = iter->first;
     ge::ScopeFusionOpInfo from_info;
-    int32_t from_index = 0;
-    int32_t to_index = 0;
 
     if (IsFusionOpChild(input_node_name, &from_info) &&
         nodedef_map_[input_node_name]->op() != TENSORFLOWF_NODE_OP_CONST) {
       // Fuse operator, update index
       std::vector<std::pair<int32_t, int32_t>> &pairs = iter->second;
       for (auto &pair : pairs) {
-        to_index = pair.second;
+        int32_t from_index = 0;
+        int32_t to_index = pair.second;
         GE_RETURN_WITH_LOG_IF_ERROR(GetOutPutIndex(scope_graph, from_info, pair.first, from_index),
                                     "GetOutPutIndex failed ,input_node_name %s.", input_node_name.c_str());
         tmp_input_map[from_info.fusion_node_name].push_back({from_index, to_index});
@@ -3180,8 +3176,7 @@ Status TensorFlowModelParser::TrimGraphByInput(const domi::tensorflow::GraphDef
   output_graph_def->Clear();
   for (const NodeDef &node : filtered_graph_def.node()) {
     if (input_nodes.count(node.name())) {
-      NodeDef placeholder_node;
-      placeholder_node = node;
+      NodeDef placeholder_node = node;
       placeholder_node.clear_input();
       GE_IF_BOOL_EXEC(node.op() != "Placeholder", placeholder_node.set_op("Placeholder"));
       domi::tensorflow::AttrValue attr_value;
@@ -3778,8 +3773,8 @@ void TensorFlowModelParser::UpdateInnerInputMap(const string &fusion_op_name, Op
       std::map<std::string, std::vector<std::pair<int32_t, int32_t>>> tmp_input_map;
       for (auto iter = op_node_context.input_map.begin(); iter != op_node_context.input_map.end();) {
         string src_name = iter->first;
-        std::vector<std::pair<int32_t, int32_t>> &input_idx = iter->second;
         if (src_name == ge::kInputFromFusionScope) {
+          std::vector<std::pair<int32_t, int32_t>> &input_idx = iter->second;
           for (const auto &in_pair : input_idx) {
             if (in_pair.second != kControlSlot) {
               auto data = remap_data_input[fusion_op_name + std::to_string(in_pair.first)];
@@ -3825,8 +3820,8 @@ void TensorFlowModelParser::UpdateInnerOutputMap(const string &fusion_op_name, O
       std::map<std::string, std::vector<std::pair<int32_t, int32_t>>> tmp_output_map;
       for (auto iter = op_node_context.output_map.begin(); iter != op_node_context.output_map.end();) {
         string dst_name = iter->first;
-        std::vector<std::pair<int32_t, int32_t>> &output_idx = iter->second;
         if (dst_name == ge::kOutputToFusionScope) {
+          std::vector<std::pair<int32_t, int32_t>> &output_idx = iter->second;
           for (const auto &out_pair : output_idx) {
             if (out_pair.second != kControlSlot) {
               auto data_outputs = remap_data_output[fusion_op_name + std::to_string(out_pair.second)];

parser/tensorflow/tensorflow_reshape_parser.cc

@@ -34,7 +34,6 @@ Status TensorFlowReshapeParser::ParseDesc(const domi::tensorflow::AttrValue &att
                          "parse ge_desc failed.");
   uint32_t size_type = 1;
   int64_t real_size = 1;
-  int64_t tmp_dim = 0;
 
   auto data_type = ge_desc.GetDataType();
   bool type_ret = ge::TypeUtils::GetDataTypeLength(data_type, size_type);
@@ -46,7 +45,7 @@ Status TensorFlowReshapeParser::ParseDesc(const domi::tensorflow::AttrValue &att
                   return PARAM_INVALID);
   // calculate size
   for (uint32_t j = 0; j < ge_desc.GetShape().GetDimNum(); ++j) {
-    tmp_dim = ge_desc.GetShape().GetDim(j);
+    int64_t tmp_dim = ge_desc.GetShape().GetDim(j);
     GE_IF_BOOL_EXEC(tmp_dim < 0, real_size = tmp_dim * (-1) * real_size; continue;);
     real_size *= tmp_dim;
   }

parser/tensorflow/tensorflow_squeeze_parser.cc

@@ -38,7 +38,6 @@ Status TensorFlowSqueezeParser::ParseDesc(const domi::tensorflow::AttrValue &att
                          "parse ge_desc failed.");
   uint32_t size_type;
   int64_t real_size = 1;
-  int64_t tmp_dim = 0;
 
   auto data_type = ge_desc.GetDataType();
   bool type_ret = ge::TypeUtils::GetDataTypeLength(data_type, size_type);
@@ -50,7 +49,7 @@ Status TensorFlowSqueezeParser::ParseDesc(const domi::tensorflow::AttrValue &att
                   return domi::PARAM_INVALID);
   // calculate size
   for (uint32_t j = 0; j < ge_desc.GetShape().GetDimNum(); ++j) {
-    tmp_dim = ge_desc.GetShape().GetDim(j);
+    int64_t tmp_dim = ge_desc.GetShape().GetDim(j);
     GE_IF_BOOL_EXEC(tmp_dim < 0, real_size = tmp_dim * (-1) * real_size; continue;);
     PARSER_INT64_MULCHECK(real_size, tmp_dim);
     real_size *= tmp_dim;

parser/tensorflow/tensorflow_util.cc

@@ -179,14 +179,13 @@ FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY domi::Status TensorFlowUtil::Tr
                            "parse ge_desc failed.");
 
     uint32_t size_type = 1;
-    int64_t tmp_dim = 0;
 
     auto data_type = ge_desc.GetDataType();
     GE_CHK_BOOL_RET_STATUS(ge::TypeUtils::GetDataTypeLength(data_type, size_type), PARAM_INVALID,
                            "dataType no define size , parse ge_desc failed.");
     // get size
     for (uint32_t j = 0; j < ge_desc.GetShape().GetDimNum(); ++j) {
-      tmp_dim = ge_desc.GetShape().GetDim(j);
+      int64_t tmp_dim = ge_desc.GetShape().GetDim(j);
 
       // The shape infered by fusedbatchnormgrad and mean calling tensorflow is not accurate.
       // Here, special treatment is given to the two operators.