modify geloge and add err report

ge/hybrid/common/npu_memory_allocator.cc

@@ -38,9 +38,11 @@ AllocationAttr::AllocationAttr(void *try_reuse_addr) : AllocationAttr(0, try_reu
 
 NpuMemoryAllocator *NpuMemoryAllocator::GetAllocator() {
   int32_t device_id = 0;
-  if (rtGetDevice(&device_id) != RT_ERROR_NONE) {
-    GELOGE(RT_FAILED, "[Get][Device] Failed.");
-    REPORT_INNER_ERROR("E19999", "rtGetDevice failed when %s.", __FUNCTION__);
+  auto rt_result = rtGetDevice(&device_id);
+  if (rt_result != RT_ERROR_NONE) {
+    GELOGE(RT_FAILED, "[Get][Device] Failed, result:%d.", rt_result);
+    REPORT_INNER_ERROR("E19999", "rtGetDevice failed when NpuMemoryAllocator %s, result:%d.",
+        __FUNCTION__, rt_result);
     return nullptr;
   }
 
@@ -58,9 +60,9 @@ void *NpuMemoryAllocator::Allocate(std::size_t size, AllocationAttr *attr) {
   }
 
   if (allocate_size == 0) {
-    GELOGE(MEMALLOC_FAILED, "[Check][Param:size_t]Memory size is 0, device_id = %u, size = %zu.", 
+    GELOGE(MEMALLOC_FAILED, "[Check][Param:size_t]Memory size is 0, device_id = %u, size = %zu.",
         device_id_, allocate_size);
-    REPORT_INNER_ERROR("E19999", "Memory size is 0, device_id = %u, size = %zu when %s.", 
+    REPORT_INNER_ERROR("E19999", "Memory size is 0, device_id = %u, size = %zu when %s.",
         device_id_, allocate_size, __FUNCTION__);
     return nullptr;
   }
@@ -72,9 +74,9 @@ void *NpuMemoryAllocator::Allocate(std::size_t size, AllocationAttr *attr) {
     buffer = MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(allocate_size);
   } else {
     if (allocate_size > kMaxHbmMemorySize) {
-      GELOGE(PARAM_INVALID, "[Check][Param:size_t]Invalid HBM memory size: %zu bigger than limit:%lu, check invalid.", 
+      GELOGE(PARAM_INVALID, "[Check][Param:size_t]Invalid HBM memory size: %zu bigger than limit:%lu, check invalid.",
           allocate_size, kMaxHbmMemorySize);
-      REPORT_CALL_ERROR("E19999", "Invalid HBM memory size: %zu bigger than limit:%lu, check invalid when %s.", 
+      REPORT_CALL_ERROR("E19999", "Invalid HBM memory size: %zu bigger than limit:%lu, check invalid when %s.",
           allocate_size, kMaxHbmMemorySize, __FUNCTION__);
       return nullptr;
     }
@@ -94,9 +96,9 @@ void *NpuMemoryAllocator::Allocate(std::size_t size, AllocationAttr *attr) {
                  .Malloc(allocate_size, reinterpret_cast<uint8_t *>(try_reuse_addr), device_id_);
   }
   if (buffer == nullptr) {
-    GELOGE(MEMALLOC_FAILED, "[Malloc][Memory] Failed, device_id = %u, size = %zu.", 
+    GELOGE(MEMALLOC_FAILED, "[Malloc][Memory] Failed, device_id = %u, size = %zu.",
         device_id_, allocate_size);
-    REPORT_CALL_ERROR("E19999", "malloc memory failed, device_id = %u, size = %zu when %s.", 
+    REPORT_CALL_ERROR("E19999", "malloc memory failed, device_id = %u, size = %zu when %s.",
         device_id_, allocate_size, __FUNCTION__);
     return nullptr;
   }

ge/hybrid/executor/hybrid_execution_context.cc

@@ -59,9 +59,8 @@ Status GraphExecutionContext::Synchronize(rtStream_t rt_stream) {
     return SUCCESS;
   }
 
-  GELOGE(RT_FAILED, 
-      "[Invoke][rtStreamSynchronize] failed, ret = %d", rt_ret);
-  REPORT_CALL_ERROR("E19999", 
+  GELOGE(RT_FAILED, "[Invoke][rtStreamSynchronize] failed, ret = %d", rt_ret);
+  REPORT_CALL_ERROR("E19999",
       "invoke rtStreamSynchronize failed when GraphExecutionContext %s, ret = %d", __FUNCTION__, rt_ret);
   return RT_FAILED;
 }

ge/hybrid/executor/hybrid_model_async_executor.cc

@@ -51,10 +51,10 @@ void HybridModelAsyncExecutor::SetModelName(const string &model_name) {
 }
 
 Status HybridModelAsyncExecutor::EnqueueData(const shared_ptr<InputDataWrapper> &data) {
-  if(data_inputer_->Push(data) != SUCCESS){
+  if (data_inputer_->Push(data) != SUCCESS) {
     REPORT_CALL_ERROR("E19999", "Data queue is full, please call again later when %s, model_id %u.",
         __FUNCTION__, model_id_);
-    GELOGE(domi::DATA_QUEUE_ISFULL, 
+    GELOGE(domi::DATA_QUEUE_ISFULL,
         "[Push][Data] Data queue is full, please call again later, model_id %u ", model_id_);
     return domi::DATA_QUEUE_ISFULL;
   }
@@ -65,9 +65,9 @@ Status HybridModelAsyncExecutor::EnqueueData(const shared_ptr<InputDataWrapper>
 Status HybridModelAsyncExecutor::Start(const std::shared_ptr<ModelListener> &listener) {
   GELOGD("HybridModelExecutor::Start IN, has listener = %d", listener != nullptr);
   std::lock_guard<std::mutex> lk(mu_);
-  if(run_flag_){
-    REPORT_INNER_ERROR("E19999", "Model already started when HybridModelAsyncExecutor %s, model_id:%u.", 
-        __FUNCTION__, model_id_);
+  if (run_flag_) {
+    REPORT_INNER_ERROR("E19999",
+        "Model already started when HybridModelAsyncExecutor %s, model_id:%u.", __FUNCTION__, model_id_);
     GELOGE(INTERNAL_ERROR, "[Check][RunState] Model already started, model_id:%u.", model_id_);
     return INTERNAL_ERROR;
   }
@@ -80,8 +80,8 @@ Status HybridModelAsyncExecutor::Start(const std::shared_ptr<ModelListener> &lis
     return RunInternal();
   });
 
-  GE_CHK_BOOL_RET_STATUS(future_.valid(), INTERNAL_ERROR, 
-      "[Check][RunState] Failed to start, model_id:%u.", model_id_);
+  GE_CHK_BOOL_RET_STATUS(future_.valid(), INTERNAL_ERROR,
+                         "[Check][RunState] Failed to start, model_id:%u.", model_id_);
   GELOGD("HybridModelExecutor::Start successfully");
   return SUCCESS;
 }
@@ -115,8 +115,8 @@ Status HybridModelAsyncExecutor::Init() {
 
   executor_ = std::unique_ptr<HybridModelExecutor>(new(std::nothrow) HybridModelExecutor(model_, device_id_, stream_));
   GE_CHECK_NOTNULL(executor_);
-  GE_CHK_STATUS_RET(executor_->Init(), 
-      "[Init][HybridModelExecutor] failed, model_id:%u.", model_id_);
+  GE_CHK_STATUS_RET(executor_->Init(),
+                    "[Init][HybridModelExecutor] failed, model_id:%u.", model_id_);
   GE_CHK_STATUS_RET(DumpOpDebug(), "[Dump][OpDebug] failed, model_id:%u.", model_id_);
 
   GELOGI("HybridModel stage nums:%zu", model_->GetRootGraphItem()->NumGroups());
@@ -124,8 +124,8 @@ Status HybridModelAsyncExecutor::Init() {
     pipe_executor_ =
         std::unique_ptr<HybridModelPipelineExecutor>(new(std::nothrow) HybridModelPipelineExecutor(model_, device_id_));
     GE_CHECK_NOTNULL(pipe_executor_);
-    GE_CHK_STATUS_RET(pipe_executor_->Init(), 
-        "[Init][HybridModelPipelineExecutor] failed, model_id:%u.", model_id_);
+    GE_CHK_STATUS_RET(pipe_executor_->Init(),
+                      "[Init][HybridModelPipelineExecutor] failed, model_id:%u.", model_id_);
   }
 
   GE_CHK_STATUS_RET(InitInputDesc(), "[Init][InputDesc] failed, model_id:%u.", model_id_);
@@ -136,8 +136,8 @@ Status HybridModelAsyncExecutor::Init() {
 Status HybridModelAsyncExecutor::PreRun(InputData &current_data, HybridModelExecutor::ExecuteArgs &args) {
   GE_CHK_STATUS_RET(SyncVarData(), "[Invoke][SyncVarData] failed, model_id:%u.", model_id_);
   RECORD_MODEL_EXECUTION_EVENT(executor_->GetContext(), "[SyncVarData] End");
-  GE_CHK_STATUS_RET(PrepareInputs(current_data, args), 
-      "[Invoke][PrepareInputs] failed to copy input data to model, model_id:%u.", model_id_);
+  GE_CHK_STATUS_RET(PrepareInputs(current_data, args),
+                    "[Invoke][PrepareInputs] failed to copy input data to model, model_id:%u.", model_id_);
   RECORD_MODEL_EXECUTION_EVENT(executor_->GetContext(), "[CopyInputData] End");
   return SUCCESS;
 }
@@ -213,7 +213,7 @@ Status HybridModelAsyncExecutor::HandleResult(Status exec_ret,
 
   if (exec_ret != SUCCESS) {
     GELOGE(exec_ret, "[Check][Param:Status] failed to execute graph. model_id = %u", model_id_);
-    REPORT_INNER_ERROR("E19999", 
+    REPORT_INNER_ERROR("E19999",
         "failed to execute graph when HybridModelAsyncExecutor %s. model_id = %u", __FUNCTION__, model_id_);
     return OnComputeDone(data_id, INTERNAL_ERROR, output_tensor_info_list);
   }
@@ -250,10 +250,10 @@ Status HybridModelAsyncExecutor::SyncVarData() {
 
 Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, HybridModelExecutor::ExecuteArgs &args) {
   if (current_data.blobs.size() < input_tensor_desc_.size()) {
-    GELOGE(PARAM_INVALID, 
+    GELOGE(PARAM_INVALID,
         "[Check][Size]Blob size mismatches, expect at least %zu, but got %zu, model_id = %u",
         input_tensor_desc_.size(), current_data.blobs.size(), model_id_);
-    REPORT_INNER_ERROR("E19999", 
+    REPORT_INNER_ERROR("E19999",
         "Blob size mismatches, expect at least %zu, but got %zu when HybridModelAsyncExecutor %s, model_id = %u.",
         input_tensor_desc_.size(), current_data.blobs.size(), __FUNCTION__, model_id_);
     return PARAM_INVALID;
@@ -267,12 +267,12 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
     auto tensor_size = input_sizes_[input_index];
     if (is_input_dynamic_[input_index]) {
       if (input_index >= current_data.shapes.size()) {
-        GELOGE(PARAM_INVALID, 
+        GELOGE(PARAM_INVALID,
             "[Check][Range]Shape index out of range, index = %zu, shape size = %zu model_id = %u.",
             input_index, current_data.shapes.size(), model_id_);
-        REPORT_INNER_ERROR("E19999", 
+        REPORT_INNER_ERROR("E19999",
             "Shape index out of range, index = %zu, shape size = %zu when HybridModelAsyncExecutor %s, model_id = %u.",
-            input_index, current_data.shapes.size(), __FUNCTION__, model_id_);    
+            input_index, current_data.shapes.size(), __FUNCTION__, model_id_);
         return PARAM_INVALID;
       }
       auto &tensor_desc = input_tensor_desc_[input_index];
@@ -287,12 +287,12 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
         }
         // range[k].second can be -1
         if (shape.GetDim(k) < range[k].first || (range[k].second >= 0 && shape.GetDim(k) > range[k].second)) {
-          GELOGE(PARAM_INVALID, 
+          GELOGE(PARAM_INVALID,
               "[Check][Range]Dim out of range, shape idx = %zu, dim idx = %zu, dim = %ld, range = [%ld, %ld], model_id = %u.",
               input_index, k, shape.GetDim(k), range[k].first, range[k].second, model_id_);
-          REPORT_INNER_ERROR("E19999", 
+          REPORT_INNER_ERROR("E19999",
               "Dim out of range, shape idx = %zu, dim idx = %zu, dim = %ld, range = [%ld, %ld], model_id = %u.",
-              input_index, k, shape.GetDim(k), range[k].first, range[k].second, model_id_);    
+              input_index, k, shape.GetDim(k), range[k].first, range[k].second, model_id_);
           return PARAM_INVALID;
         }
       }
@@ -318,14 +318,14 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
     const DataBuffer &data_buf = blobs[input_index];
     auto mem_size = static_cast<uint64_t>(tensor_size);
 
-    if(mem_size < data_buf.length){
-      REPORT_INNER_ERROR("E19999", 
+    if (mem_size < data_buf.length) {
+      REPORT_INNER_ERROR("E19999",
           "input data size(%lu) does not match model required size(%lu) when %s, ret failed, model_id = %u.",
           data_buf.length, mem_size, __FUNCTION__, model_id_);
       GELOGE(PARAM_INVALID,
           "[Check][Size]input data size(%lu) does not match model required size(%lu), ret failed, model_id = %u.",
           data_buf.length, mem_size, model_id_);
-      return PARAM_INVALID; 
+      return PARAM_INVALID;
     }
     if (data_buf.length > 0) {
       GELOGI("[IMAS]CopyPlainData memcpy graph_%u type[F] output[%zu] memaddr[%p] mem_size[%zu] datasize[%lu]",
@@ -433,7 +433,7 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
       GELOGE(INTERNAL_ERROR,
           "[Check][Size]output[%zu] tensor size(%zu) is not enough for output shape [%s], model_id = %u.",
           i, output_tensor.GetSize(), tensor_desc->GetShape().ToString().c_str(), model_id_);
-      REPORT_INNER_ERROR("E19999", 
+      REPORT_INNER_ERROR("E19999",
           "output[%zu] tensor size(%zu) is not enough for output shape [%s] model_id = %u,"
           " when HybridModelAsyncExecutor %s.",
           i, output_tensor.GetSize(), tensor_desc->GetShape().ToString().c_str(), model_id_, __FUNCTION__);
@@ -513,14 +513,14 @@ Status HybridModelAsyncExecutor::Execute(const vector<GeTensor> &inputs, vector<
   }
 
   HybridModelExecutor::ExecuteArgs args;
-  GE_CHK_STATUS_RET(PrepareInputs(input_data, args), 
+  GE_CHK_STATUS_RET(PrepareInputs(input_data, args),
       "[Invoke][PrepareInputs]Failed to copy input data to model, model_id = %u", model_id_);
   GELOGD("Done copying input data successfully.");
   GE_CHK_STATUS_RET(executor_->Execute(args), "[Invoke][Execute] Failed, model_id = %u.", model_id_);
 
   std::vector<ge::OutputTensorInfo> output_tensor_info_list;
   OutputData output_data;
-  GE_CHK_STATUS_RET(CopyOutputs(args, &output_data, output_tensor_info_list), 
+  GE_CHK_STATUS_RET(CopyOutputs(args, &output_data, output_tensor_info_list),
       "[Invoke][CopyOutputs]Failed to copy outputs, model_id = %u.", model_id_);
   GELOGD("Done copying output data successfully. output count = %zu", output_tensor_info_list.size());
 
@@ -572,7 +572,7 @@ Status HybridModelAsyncExecutor::DumpOpDebug() {
       loop_cond = const_cast<void *>(varible_loop_cond->GetData());
     }
     data_dumper_.SetLoopAddr(global_step, loop_per_iter, loop_cond);
-    GE_CHK_STATUS_RET(data_dumper_.LoadDumpInfo(), 
+    GE_CHK_STATUS_RET(data_dumper_.LoadDumpInfo(),
         "[Invoke][LoadDumpInfo] failed in hybrid engine, model_id = %u.", model_id_);
     GELOGD("Dump op debug SUCCESS in hybrid engine");
   }

ge/hybrid/executor/hybrid_model_pipeline_executor.cc

@@ -59,9 +59,9 @@ Status StageExecutor::Start(const std::vector<TensorValue> &inputs, const std::v
     task_queue_.Pop(task_info);
     GELOGD("[Executor: %d] Got task, stage = %d, iteration = %ld", id_, task_info.stage, task_info.iteration);
     if (task_info.iteration >= pipe_config_->iteration_end) {
-      GELOGE(INTERNAL_ERROR, "[Check][Range][Executor: %d] Unexpected iteration: %d.", 
+      GELOGE(INTERNAL_ERROR, "[Check][Range][Executor: %d] Unexpected iteration: %ld.",
           id_, task_info.iteration);
-      REPORT_INNER_ERROR("E19999", "[Executor: %d] Unexpected iteration: %d when StageExecutor %s.", 
+      REPORT_INNER_ERROR("E19999", "[Executor: %d] Unexpected iteration: %ld when StageExecutor %s.",
           id_, task_info.iteration, __FUNCTION__);
       return INTERNAL_ERROR;
     }
@@ -69,16 +69,16 @@ Status StageExecutor::Start(const std::vector<TensorValue> &inputs, const std::v
     if (task_info.event != nullptr) {
       GELOGD("[%d] Add StreamWaitEvent", id_);
       GE_CHK_RT_RET(rtStreamWaitEvent(stream_, task_info.event));
-      RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %d] [Stage = %d] End", task_info.iteration - 1,
+      RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %ld] [Stage = %d] End", task_info.iteration - 1,
                                    task_info.stage);
     }
 
-    RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %d] [Stage = %d] Start", task_info.iteration,
+    RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %lld] [Stage = %d] Start", task_info.iteration,
                                  task_info.stage);
 
     if (task_info.stage == 0) {
       GELOGD("[Executor: %d] To ResetExecutionContext", id_);
-      GE_CHK_STATUS_RET(ResetExecutionContext(context_), 
+      GE_CHK_STATUS_RET(ResetExecutionContext(context_),
           "[Invoke][ResetExecutionContext][Executor: %d] Failed to reset context", id_);
       context_.iteration = task_info.iteration;
       GE_CHK_STATUS_RET_NOLOG(SetInputs(inputs, input_desc));
@@ -96,10 +96,10 @@ Status StageExecutor::Start(const std::vector<TensorValue> &inputs, const std::v
 
     auto sync_result = Synchronize();
     if (sync_result != SUCCESS) {
-      GELOGE(sync_result, 
-          "[Invoke][Synchronize][Executor: %d] Failed to sync result:%d. iteration = %d", 
+      GELOGE(sync_result,
+          "[Invoke][Synchronize][Executor: %d] Failed to sync result:%d. iteration = %ld",
           id_, sync_result, task_info.iteration);
-      REPORT_CALL_ERROR("E19999", "[Executor: %d] Failed to sync result:%d when StageExecutor %s. iteration = %d", 
+      REPORT_CALL_ERROR("E19999", "[Executor: %d] Failed to sync result:%d when StageExecutor %s. iteration = %ld",
           id_, sync_result, __FUNCTION__, task_info.iteration);
       context_.profiler->Dump(std::cout);
       context_.callback_manager->Destroy();
@@ -107,11 +107,11 @@ Status StageExecutor::Start(const std::vector<TensorValue> &inputs, const std::v
       return sync_result;
     }
 
-    RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %d] [Stage = %d] End", task_info.iteration, task_info.stage);
+    RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %ld] [Stage = %d] End", task_info.iteration, task_info.stage);
 
     // if not end stage
     if (task_info.stage >= pipe_config_->num_stages - 1) {
-      RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %d] Schedule End", task_info.iteration);
+      RECORD_MODEL_EXECUTION_EVENT(&context_, "[iteration = %ld] Schedule End", task_info.iteration);
       GELOGD("[Executor: %d] End of iteration [%ld]", id_, task_info.iteration);
       context_.callback_manager->Destroy();
       RuntimeInferenceContext::DestroyContext(std::to_string(context_.context_id));
@@ -261,7 +261,7 @@ Status HybridModelPipelineExecutor::Execute(HybridModelExecutor::ExecuteArgs &ar
     if (ret != SUCCESS) {
       GELOGE(ret, "[Invoke][Synchronize] failed for [Executor: %zu].", i);
       REPORT_CALL_ERROR("E19999", "[Executor: %zu] failed to Synchronize result when HybridModelPipelineExecutor %s.",
-          i, __FUNCTION__);    
+          i, __FUNCTION__);
       has_error = true;
       continue;
     }

ge/hybrid/executor/hybrid_profiler.cc

@@ -49,9 +49,9 @@ void HybridProfiler::RecordEvent(EventType event_type, const char *fmt, ...) {
   va_end(args);
   auto index = counter_++;
   if (index >= static_cast<int>(events_.size())) {
-    GELOGE(INTERNAL_ERROR, 
+    GELOGE(INTERNAL_ERROR,
         "[Check][Range]index out of range. index = %d, max event size = %zu", index, events_.size());
-    REPORT_INNER_ERROR("E19999", "index out of range when HybridProfiler %s. index = %d, max event size = %zu", 
+    REPORT_INNER_ERROR("E19999", "index out of range when HybridProfiler %s. index = %d, max event size = %zu",
         __FUNCTION__, index, events_.size());
     return;
   }

ge/hybrid/executor/node_state.cc

@@ -67,10 +67,10 @@ Status ShapeInferenceState::UpdateInputShape(int idx, const GeTensorDesc &target
     Format format = input_desc.GetFormat();
     DataType data_type = input_desc.GetDataType();
     if (TensorUtils::CalcTensorMemSize(shape, format, data_type, tensor_size) != GRAPH_SUCCESS) {
-      GELOGE(FAILED, "[Invoke][CalcTensorMemSize] failed for [%s].", 
+      GELOGE(FAILED, "[Invoke][CalcTensorMemSize] failed for [%s].",
           node_item.NodeName().c_str());
-      REPORT_CALL_ERROR("E19999", "CalcTensorMemSize failed for [%s] when ShapeInferenceState %s.", 
-          node_item.NodeName().c_str(), __FUNCTION__);    
+      REPORT_CALL_ERROR("E19999", "CalcTensorMemSize failed for [%s] when ShapeInferenceState %s.",
+          node_item.NodeName().c_str(), __FUNCTION__);
       return FAILED;
     }
   }
@@ -124,18 +124,18 @@ Status ShapeInferenceState::AwaitShapesReady(const GraphExecutionContext &contex
       }
 
       if (context.GetStatus() != SUCCESS) {
-        GELOGE(FAILED, "[Check][Status][%s] Await pending shape cancelled.", 
+        GELOGE(FAILED, "[Check][Status][%s] Await pending shape cancelled.",
             node_item.NodeName().c_str());
-        REPORT_CALL_ERROR("E19999", "[%s] Await pending shape cancelled when %s.", 
+        REPORT_CALL_ERROR("E19999", "[%s] Await pending shape cancelled when %s.",
             node_item.NodeName().c_str(), __FUNCTION__);
         break;
       }
     }
 
     if (!wait_success) {
-      GELOGE(FAILED, "[Check][Status][%s] Wait for shape timeout:%d.", 
+      GELOGE(FAILED, "[Check][Status][%s] Wait for shape timeout:%d.",
           node_item.NodeName().c_str(), kWaitInternal);
-      REPORT_CALL_ERROR("E19999", "[%s] Wait for shape timeout:%d when %s.", 
+      REPORT_CALL_ERROR("E19999", "[%s] Wait for shape timeout:%d when %s.",
           node_item.NodeName().c_str(), kWaitInternal, __FUNCTION__);
       return FAILED;
     }

ge/hybrid/executor/rt_callback_manager.cc

@@ -76,7 +76,7 @@ Status CallbackManager::CallbackProcess(rtContext_t context) {
     auto rt_err = rtEventSynchronize(event);
     if (rt_err != RT_ERROR_NONE) {
       GELOGE(RT_FAILED, "[Invoke][rtEventSynchronize] failed. ret = %d", rt_err);
-      REPORT_CALL_ERROR("E19999", 
+      REPORT_CALL_ERROR("E19999",
           "Invoke rtEventSynchronize failed when CallbackManager %s, ret = %d.", __FUNCTION__, rt_err);
       GE_CHK_RT(rtEventDestroy(event));
       return RT_FAILED;

ge/hybrid/executor/subgraph_context.cc

@@ -50,10 +50,10 @@ NodeStatePtr SubgraphContext::GetOrCreateNodeState(const NodeItem *node_item) {
 Status SubgraphContext::SetInput(int index, const TensorValue &tensor) {
   if (static_cast<size_t>(index) >= all_inputs_.size()) {
     GELOGE(INTERNAL_ERROR,
-        "[Check][Param:index]output index output range. all input num = %zu, input index = %d",
+        "[Check][Param:index]input index out of range. all input num = %zu, input index = %d",
         all_inputs_.size(), index);
-    REPORT_INNER_ERROR("E19999", 
-        "input param index out range when SubgraphContext %s, all input num = %zu, input index = %d.",
+    REPORT_INNER_ERROR("E19999",
+        "input param index out of range when SubgraphContext %s, all input num = %zu, input index = %d.",
         __FUNCTION__, all_inputs_.size(), index);
     return INTERNAL_ERROR;
   }
@@ -70,9 +70,9 @@ Status SubgraphContext::SetOutput(const NodeItem &node_item, int output_index, c
   auto index = node_item.output_start + output_index;
   if ((output_index >= node_item.num_outputs) || (static_cast<size_t>(index) >= all_outputs_.size())) {
     GELOGE(INTERNAL_ERROR,
-        "[Check][Param:output_index]output index output range. all output num = %zu, node_item = %s,"
+        "[Check][Param:output_index]output index out of range. all output num = %zu, node_item = %s,"
         "output index = %d.", all_outputs_.size(), node_item.DebugString().c_str(), output_index);
-    REPORT_INNER_ERROR("E19999", "output index output range when SubgraphContext %s. "
+    REPORT_INNER_ERROR("E19999", "output index out of range when SubgraphContext %s. "
         "all output num = %zu, node_item = %s, output index = %d.",
         __FUNCTION__, all_outputs_.size(), node_item.DebugString().c_str(), output_index);
     return INTERNAL_ERROR;
@@ -129,9 +129,10 @@ Status SubgraphContext::Await(const NodePtr &node) {
 
 void SubgraphContext::OnError(Status error) {
   if (error != END_OF_SEQUENCE) {
-    GELOGE(error, "[Check][Param:error][%s] Error occurred while executing graph.", graph_item_->GetName().c_str());
-    REPORT_INNER_ERROR("E19999", "[%s] Error occurred while executing graph when SubgraphContext %s.",
-        graph_item_->GetName().c_str(), __FUNCTION__);
+    GELOGE(error, "[Check][Param:error][%s] Error:%d occurred while executing graph.",
+        graph_item_->GetName().c_str(), error);
+    REPORT_INNER_ERROR("E19999", "[%s] Error:%d occurred while executing graph when SubgraphContext %s.",
+        graph_item_->GetName().c_str(), error, __FUNCTION__);
   }
   node_done_manager_.Destroy();
 }

ge/hybrid/executor/subgraph_executor.cc

@@ -44,7 +44,7 @@ Status SubgraphExecutor::Init(const std::vector<TensorValue> &inputs,
                               const std::vector<ConstGeTensorDescPtr> &input_desc) {
   subgraph_context_.reset(new(std::nothrow)SubgraphContext(graph_item_, context_));
   GE_CHECK_NOTNULL(subgraph_context_);
-  GE_CHK_STATUS_RET(subgraph_context_->Init(), 
+  GE_CHK_STATUS_RET(subgraph_context_->Init(),
       "[Init][SubgraphContext][%s] Failed to init subgraph context.", graph_item_->GetName().c_str());
 
   shape_inference_engine_.reset(new(std::nothrow) ShapeInferenceEngine(context_, subgraph_context_.get()));
@@ -68,11 +68,12 @@ Status SubgraphExecutor::InitInputsForUnknownShape(const std::vector<TensorValue
   // Number of inputs of parent node should be greater or equal than that of subgraph
   auto input_nodes = graph_item_->GetInputNodes();
   if (inputs.size() < input_nodes.size()) {
-    GELOGE(INTERNAL_ERROR, 
+    GELOGE(INTERNAL_ERROR,
         "[Check][Size][%s] Number of inputs [%zu] is not sufficient for subgraph which needs [%zu] inputs.",
         graph_item_->GetName().c_str(), inputs.size(), input_nodes.size());
-    REPORT_INNER_ERROR("E19999", 
-        "Number of inputs [%zu] is not sufficient for subgraph which needs [%zu] inputs when SubgraphExecutor %s.",
+    REPORT_INNER_ERROR("E19999",
+        "[%s] Number of inputs [%zu] is not sufficient for subgraph which needs [%zu] inputs,"
+        "check invalid when SubgraphExecutor %s.",
         graph_item_->GetName().c_str(), inputs.size(), input_nodes.size(), __FUNCTION__);
     return INTERNAL_ERROR;
   }
@@ -117,8 +118,9 @@ Status SubgraphExecutor::InitInputsForKnownShape(const std::vector<TensorValue>
       GELOGE(INTERNAL_ERROR,
           "[Check][Size][%s] Number of inputs [%zu] is not sufficient for subgraph which needs at lease [%d] inputs",
           graph_item_->GetName().c_str(), inputs.size(), parent_input_index + 1);
-      REPORT_INNER_ERROR("E19999", 
-          "[%s] Number of inputs [%zu] is not sufficient for subgraph which needs at lease [%d] inputs when %s.",
+      REPORT_INNER_ERROR("E19999",
+          "[%s] Number of inputs [%zu] is not sufficient for subgraph which needs at lease [%d] inputs,"
+          "check invalid when %s.",
           graph_item_->GetName().c_str(), inputs.size(), parent_input_index + 1, __FUNCTION__);
       return INTERNAL_ERROR;
     }
@@ -387,9 +389,10 @@ Status SubgraphExecutor::GetOutputs(vector<TensorValue> &outputs, std::vector<Co
       "[Invoke][GetOutputDescList][%s] Failed to get output tensor desc.", graph_item_->GetName().c_str());
   if (outputs.size() != output_desc.size()) {
     GELOGE(INTERNAL_ERROR,
-        "[Check][Size]Number of output tensors(%zu) mismatch number of output tensor desc(%zu).",
+        "[Check][Size]Number of outputs(%zu) mismatch number of output_desc(%zu).",
         outputs.size(), output_desc.size());
-    REPORT_INNER_ERROR("E19999", "Number of output tensors(%zu) mismatch number of output tensor desc(%zu) when %s.",
+    REPORT_INNER_ERROR("E19999", "Number of outputs(%zu) mismatch number of output_desc(%zu),"
+        "check invlid when SubgraphExecutor %s.",
         outputs.size(), output_desc.size(), __FUNCTION__);
     return INTERNAL_ERROR;
   }
@@ -413,9 +416,11 @@ Status SubgraphExecutor::SetOutputsToParentNode(TaskContext &task_context) {
       "[Invoke][GetOutputDescList][%s] Failed to get output tensor desc.", graph_item_->GetName().c_str());
 
   if (outputs.size() != output_desc_list.size()) {
-    GELOGE(INTERNAL_ERROR, "[Check][Size][%s] num output tensors = %zu, num output tensor desc = %zu",
+    GELOGE(INTERNAL_ERROR, "[Check][Size][%s] num of output tensors = %zu, num of output tensor desc = %zu not equal",
         graph_item_->GetName().c_str(), outputs.size(), output_desc_list.size());
-    REPORT_INNER_ERROR("E19999", "[%s] num output tensors = %zu, num output tensor desc = %zu when %s",
+    REPORT_INNER_ERROR("E19999",
+        "%s num of output tensors = %zu, num of output tensor desc = %zu not equal,"
+        "check invalid when SubgraphExecutor %s",
         graph_item_->GetName().c_str(), outputs.size(), output_desc_list.size(), __FUNCTION__);
     return INTERNAL_ERROR;
   }

ge/hybrid/executor/worker/execution_engine.cc

@@ -105,7 +105,7 @@ Status NodeDoneCallback::PrepareConstInputs(const NodeItem &node_item) {
           "[Check][Size][%s] Tensor size is not enough. output index = %d, required size = %ld, tensor = %s.",
           node_item.NodeName().c_str(), output_idx, tensor_size,
           output_tensor->DebugString().c_str());
-      REPORT_INNER_ERROR("E19999", 
+      REPORT_INNER_ERROR("E19999",
           "[%s] Tensor size is not enough. output index = %d, required size = %ld, tensor = %s when %s.",
           node_item.NodeName().c_str(), output_idx, tensor_size,
           output_tensor->DebugString().c_str(), __FUNCTION__);
@@ -423,7 +423,7 @@ Status ExecutionEngine::ValidateInputTensors(const NodeState &node_state, const
             "[Check][Size] for [%s] Input[%d]: tensor size mismatches. expected: %ld, but given %zu.",
             task_context.GetNodeName(), i, expected_size, input_tensor->GetSize());
         REPORT_INNER_ERROR("E19999", "[%s] Input[%d]: tensor size mismatches. expected: %ld, but given %zu when %s.",
-            task_context.GetNodeName(), i, expected_size, input_tensor->GetSize(), __FUNCTION__);    
+            task_context.GetNodeName(), i, expected_size, input_tensor->GetSize(), __FUNCTION__);
         return INTERNAL_ERROR;
       }
     }

ge/hybrid/executor/worker/shape_inference_engine.cc

@@ -205,8 +205,8 @@ Status ShapeInferenceEngine::UpdatePeerNodeShape(const Node &node) {
       auto peer_input_desc = peer_op_desc->MutableInputDesc(peer_anchor->GetIdx());
       if (peer_input_desc == nullptr) {
         GELOGE(GRAPH_FAILED, "[Call][MutableInputDesc] for %s return nullptr.", peer_op_desc->GetName().c_str());
-        REPORT_CALL_ERROR("E19999", "%s call MutableInputDesc return nullptr when ShapeInferenceEngine %s.", 
-            peer_op_desc->GetName().c_str(), __FUNCTION__);    
+        REPORT_CALL_ERROR("E19999", "%s call MutableInputDesc return nullptr when ShapeInferenceEngine %s.",
+            peer_op_desc->GetName().c_str(), __FUNCTION__);
         continue;
       }
 
@@ -231,11 +231,11 @@ Status ShapeInferenceEngine::CanonicalizeShape(GeTensorDesc &tensor_desc,
   const auto &tensor_shape = tensor_desc.MutableShape();
   if (tensor_shape.IsUnknownShape()) {
     if (!fallback_with_range) {
-      GELOGE(INTERNAL_ERROR, 
-          "[Is][UnknownShape] Output shape is still unknown after shape inference. shape = [%s].", 
+      GELOGE(INTERNAL_ERROR,
+          "[Is][UnknownShape] Output shape is still unknown after shape inference. shape = [%s].",
           tensor_shape.ToString().c_str());
       REPORT_INNER_ERROR("E19999", "Output shape is still unknown after shape inference. "
-          "shape = [%s] when ShapeInferenceEngine %s.", tensor_shape.ToString().c_str(), __FUNCTION__);    
+          "shape = [%s] when ShapeInferenceEngine %s.", tensor_shape.ToString().c_str(), __FUNCTION__);
       return INTERNAL_ERROR;
     }
 
@@ -243,10 +243,10 @@ Status ShapeInferenceEngine::CanonicalizeShape(GeTensorDesc &tensor_desc,
     std::vector<std::pair<int64_t, int64_t>> shape_range;
     GE_CHK_GRAPH_STATUS_RET(tensor_desc.GetShapeRange(shape_range), "Failed to get shape range");
     if (shape_range.size() != shape.size()) {
-      GELOGE(INTERNAL_ERROR, "[Check][Size] Number of shape ranges (%zu) mismatches that of dims (%zu).", 
+      GELOGE(INTERNAL_ERROR, "[Check][Size] Number of shape ranges (%zu) mismatches that of dims (%zu).",
           shape_range.size(), shape.size());
-      REPORT_INNER_ERROR("E19999", "Number of shape ranges (%zu) mismatches that of dims (%zu)" 
-          " when ShapeInferenceEngine %s.", shape_range.size(), shape.size(), __FUNCTION__);    
+      REPORT_INNER_ERROR("E19999", "Number of shape ranges (%zu) mismatches that of dims (%zu)"
+          " when ShapeInferenceEngine %s.", shape_range.size(), shape.size(), __FUNCTION__);
       return INTERNAL_ERROR;
     }
 
@@ -270,10 +270,10 @@ Status ShapeInferenceEngine::CalcTensorSize(DataType data_type,
   GELOGD("To calc tensor size by shape = [%s]", GeShape(shape).ToString().c_str());
   uint32_t type_size;
   if (!TypeUtils::GetDataTypeLength(data_type, type_size)) {
-    GELOGE(INTERNAL_ERROR, "[Get][DataTypeLength] failed for type:%s.", 
+    GELOGE(INTERNAL_ERROR, "[Get][DataTypeLength] failed for type:%s.",
         TypeUtils::DataTypeToSerialString(data_type).c_str());
-    REPORT_CALL_ERROR("E19999", "GetDataTypeLength failed for type:%s when ShapeInferenceEngine %s.", 
-        TypeUtils::DataTypeToSerialString(data_type).c_str(), __FUNCTION__);    
+    REPORT_CALL_ERROR("E19999", "GetDataTypeLength failed for type:%s when ShapeInferenceEngine %s.",
+        TypeUtils::DataTypeToSerialString(data_type).c_str(), __FUNCTION__);
     return INTERNAL_ERROR;
   }
 
@@ -300,23 +300,24 @@ Status ShapeInferenceEngine::CalcOutputTensorSizes(const NodeItem &node_item, bo
     const auto &shape = tensor_desc->MutableShape();
     // modify on copy
     auto dims = shape.GetDims();
-    auto _status = CanonicalizeShape(*tensor_desc, dims, fallback_with_range);    
-    if(_status != SUCCESS){
-      REPORT_CALL_ERROR("E19999", "Invoke CanonicalizeShape failed when ShapeInferenceEngine %s, node:%s, output:%zu.",
-          node_item.NodeName().c_str(), __FUNCTION__, output_index);
+    auto status_result = CanonicalizeShape(*tensor_desc, dims, fallback_with_range);
+    if (status_result != SUCCESS) {
+      REPORT_CALL_ERROR("E19999",
+                        "Invoke CanonicalizeShape failed when ShapeInferenceEngine %s, node:%s, output:%zu.",
+                        node_item.NodeName().c_str(), __FUNCTION__, output_index);
       GELOGE(ge::FAILED, "[Canonicalize][Shape] failed for [%s], output %zu.",
-          node_item.NodeName().c_str(), output_index); 
-      return _status; 
+             node_item.NodeName().c_str(), output_index);
+      return status_result;
     }
     int64_t tensor_size;
-    _status = CalcTensorSize(tensor_desc->GetDataType(), dims, tensor_size);
-    if(_status != SUCCESS){
+    status_result = CalcTensorSize(tensor_desc->GetDataType(), dims, tensor_size);
+    if (status_result != SUCCESS) {
       REPORT_CALL_ERROR("E19999", "Invoke CalcTensorSize failed when ShapeInferenceEngine %s, node:%s, output:%zu.",
           node_item.NodeName().c_str(), __FUNCTION__, output_index);
       GELOGE(ge::FAILED, "[Calc][TensorSize] failed for [%s], output %zu.",
-          node_item.NodeName().c_str(), output_index); 
-      return _status; 
-    }    
+          node_item.NodeName().c_str(), output_index);
+      return status_result;
+    }
     GELOGD("[%s] Tensor size of output %zu = %ld", node_item.NodeName().c_str(), output_index, tensor_size);
     (void) TensorUtils::SetSize(*tensor_desc, tensor_size);
   }

ge/hybrid/model/graph_item.cc

@@ -95,8 +95,8 @@ Status GraphItem::GroupNodes() {
     int group = node->group;
     if (group != last_group) {
       if (seen_groups.find(group) != seen_groups.end()) {
-        GELOGE(INTERNAL_ERROR, 
-            "[Order][NodeGroup]Unordered node group found. node = %s, group = %d", node->NodeName().c_str(), group);
+        GELOGE(INTERNAL_ERROR,
+            "[Find][Group]Unordered node group found. node = %s, group = %d", node->NodeName().c_str(), group);
         return INTERNAL_ERROR;
       } else {
         last_group = group;

ge/hybrid/model/hybrid_model_builder.cc

@@ -71,8 +71,10 @@ Status SetOutputNameAttr(ComputeGraph &graph) {
     }
   }
   GE_CHK_BOOL_EXEC(ge::AttrUtils::SetListStr(&graph, ATTR_MODEL_OUT_NODES_NAME, output_names),
-                   GELOGE(FAILED, "[Invoke][SetListStr] of ATTR_MODEL_OUT_NODES_NAME failed.");
-                   return FAILED);
+      GELOGE(FAILED, "[Invoke][SetListStr] failed, name:%s.", ATTR_MODEL_OUT_NODES_NAME.c_str());
+      REPORT_CALL_ERROR("E19999", "SetListStr failed when %s, name:%s.",
+          __FUNCTION__, ATTR_MODEL_OUT_NODES_NAME.c_str());
+      return FAILED);
   return SUCCESS;
 }
 
@@ -109,10 +111,11 @@ Status CollectDependenciesForFusedGraph(NodeItem &node_item, std::set<OpDesc *>
       GE_CHECK_NOTNULL(src_op_desc);
       if (src_node->GetType() != DATA_TYPE) {
         GELOGE(UNSUPPORTED,
-            "[Check][NodeType][%s::%s] Node in fused subgraph can only depend on Data nodes, but depend on %s",
+            "[Check][NodeType][%s::%s] Node in fused subgraph can only depend on Data nodes,"
+            "but depend on %s actually",
             node_item.NodeName().c_str(), node->GetName().c_str(), src_node->GetType().c_str());
-        REPORT_INNER_ERROR("E19999", 
-            "[%s::%s] Node in fused subgraph can only depend on Data nodes, but depend on %s when %s.",
+        REPORT_INNER_ERROR("E19999", "[%s::%s] Node in fused subgraph can only depend on Data nodes,"
+            " but depend on %s actually, check invalid when %s.",
             node_item.NodeName().c_str(), node->GetName().c_str(), src_node->GetType().c_str(), __FUNCTION__);
         return UNSUPPORTED;
       }
@@ -134,12 +137,13 @@ Status HybridModelBuilder::Build() {
   hybrid_model_.model_name_ = ge_root_model_->GetRootGraph()->GetName();
   GELOGI("[%s] Start to build hybrid model.", GetGraphName());
   GE_CHK_STATUS_RET(InitRuntimeParams(), "[Invoke][InitRuntimeParams] failed, model_name_:[%s]", GetGraphName());
-  GE_CHK_STATUS_RET(RecoverGraphUnknownFlag(), "[Invoke][RecoverGraphUnknownFlag] failed, model_name_:[%s]", GetGraphName());
+  GE_CHK_STATUS_RET(RecoverGraphUnknownFlag(),
+      "[Invoke][RecoverGraphUnknownFlag] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(IndexSpecialNodes(), "[Invoke][IndexSpecialNodes] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(IndexTaskDefs(), "[Invoke][IndexTaskDefs] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(InitWeights(), "[Invoke][InitWeights] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(LoadGraph(), "[Invoke][LoadGraph] failed, model_name_:[%s]", GetGraphName());
-  GE_CHK_STATUS_RET(AssignUninitializedConstantOps(), 
+  GE_CHK_STATUS_RET(AssignUninitializedConstantOps(),
       "[Invoke][AssignUninitializedConstantOps] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(TransAllVarData(), "[Invoke][TransAllVarData] failed, model_name_:[%s]", GetGraphName());
   GE_CHK_STATUS_RET(CopyVarData(), "[Invoke][CopyVarData] failed, model_name_:[%s]", GetGraphName());
@@ -335,6 +339,8 @@ Status HybridModelBuilder::ParseDependentInputNodes(NodeItem &node_item, const s
     if (input_index < 0) {
       GELOGE(INTERNAL_ERROR, "[Get][InputIndex]failed, node:[%s] inputname: %s.",
           node_item.NodeName().c_str(), input_name.c_str());
+      REPORT_CALL_ERROR("E19999", "GetInputIndexByName failed when HybridModelBuilder %s, node:[%s] inputname: %s.",
+          __FUNCTION__, node_item.NodeName().c_str(), input_name.c_str());
       return INTERNAL_ERROR;
     }
 
@@ -423,20 +429,24 @@ Status HybridModelBuilder::UpdateAnchorStatus(const NodePtr &node) {
     auto peer_anchor = anchor->GetPeerOutAnchor();
     if (peer_anchor == nullptr) {
       if (AnchorUtils::SetStatus(anchor, ANCHOR_SUSPEND) != GRAPH_SUCCESS) {
-        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed, node:[%s].", node->GetName().c_str());
-        REPORT_CALL_ERROR("E19999", "SetStatus failed, node:[%s] when %s.", node->GetName().c_str(), __FUNCTION__);
+        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed to set ANCHOR_SUSPEND, node:[%s].",
+            node->GetName().c_str());
+        REPORT_CALL_ERROR("E19999", "SetStatus failed to set ANCHOR_SUSPEND, node:[%s] when HybridModelBuilder %s.",
+            node->GetName().c_str(), __FUNCTION__);
         return INTERNAL_ERROR;
       }
     } else if (peer_anchor->GetOwnerNode()->GetType() == CONSTANT) {
       if (AnchorUtils::SetStatus(anchor, ANCHOR_CONST) != GRAPH_SUCCESS) {
-        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed, node:[%s].", node->GetName().c_str());
-        REPORT_CALL_ERROR("E19999", "SetStatus failed, node:[%s] when %s.", node->GetName().c_str(), __FUNCTION__);
+        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed to set ANCHOR_CONST, node:[%s].", node->GetName().c_str());
+        REPORT_CALL_ERROR("E19999", "SetStatus failed to set ANCHOR_CONST, node:[%s] when HybridModelBuilder %s.",
+            node->GetName().c_str(), __FUNCTION__);
         return INTERNAL_ERROR;
       }
     } else {
       if (AnchorUtils::SetStatus(anchor, ANCHOR_DATA) != GRAPH_SUCCESS) {
-        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed, node:[%s].", node->GetName().c_str());
-        REPORT_CALL_ERROR("E19999", "SetStatus failed, node:[%s] when %s.", node->GetName().c_str(), __FUNCTION__);
+        GELOGE(INTERNAL_ERROR, "[Invoke][SetStatus] failed to set ANCHOR_DATA, node:[%s].", node->GetName().c_str());
+        REPORT_CALL_ERROR("E19999", "SetStatus failed to set ANCHOR_DATA, node:[%s] when HybridModelBuilder %s.",
+            node->GetName().c_str(), __FUNCTION__);
         return INTERNAL_ERROR;
       }
     }
@@ -563,6 +573,8 @@ Status HybridModelBuilder::MergeNetOutputNode(ComputeGraph &graph) {
     if (input_desc == nullptr) {
       GELOGE(INTERNAL_ERROR, "[Invoke][MutableInputDesc][%s] Failed to get input desc[%d]",
           net_output_desc->GetName().c_str(), index);
+      REPORT_CALL_ERROR("E19999", "[%s] Failed to get input desc[%d] when HybridModelBuilder %s.",
+          net_output_desc->GetName().c_str(), index, __FUNCTION__);
       return INTERNAL_ERROR;
     }
 
@@ -763,7 +775,7 @@ Status HybridModelBuilder::LoadGraph() {
     GELOGI("Before merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
            root_graph->GetDirectNodesSize(),
            root_graph->GetAllNodesSize());
-    GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraphs(root_graph, merged_graph), 
+    GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraphs(root_graph, merged_graph),
         "[Invoke][UnfoldSubgraphs]Failed to unfold subgraphs, model_name_:%s.", GetGraphName());
     root_graph = std::move(merged_graph);
     GELOGI("After merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
@@ -786,7 +798,7 @@ Status HybridModelBuilder::LoadGraph() {
     op_desc->SetId(index++);
   }
   GE_DUMP(root_graph, "hybrid_merged_graph");
-  GE_CHK_STATUS_RET(LoadDynamicSubgraph(*root_graph, true), 
+  GE_CHK_STATUS_RET(LoadDynamicSubgraph(*root_graph, true),
       "[Invoke][LoadDynamicSubgraph]Failed to load root graph, model_name_:%s.", GetGraphName());
   GELOGD("Done loading root graph successfully.");
   GE_CHK_STATUS_RET(hybrid_model_.root_graph_item_->GroupNodes(),
@@ -825,7 +837,7 @@ Status HybridModelBuilder::LoadGraph() {
     }
   }
 
-  GE_CHK_STATUS_RET(ParseDependentByParallelGroup(), 
+  GE_CHK_STATUS_RET(ParseDependentByParallelGroup(),
       "[Invoke][ParseDependentByParallelGroup]Failed to establish dependencies for hccl ops, model_name_:%s.",
       GetGraphName());
   GELOGI("Done loading all subgraphs successfully.");
@@ -941,7 +953,7 @@ Status HybridModelBuilder::InitConstantOps() {
     auto op_desc = var_node->GetOpDesc();
     auto v_weights = ModelUtils::GetWeights(op_desc);
     if (v_weights.empty()) {
-      GELOGE(INTERNAL_ERROR, "[Check][Size][%s] Constant no not have value", var_node->GetName().c_str());
+      GELOGE(INTERNAL_ERROR, "[Check][Size][%s] Constant op has no weight", var_node->GetName().c_str());
       return INTERNAL_ERROR;
     }
     auto *ge_tensor = const_cast<GeTensor *>(v_weights[0].get());
@@ -955,7 +967,7 @@ Status HybridModelBuilder::InitConstantOps() {
       GELOGD("Init tensor with host constant %s size = %zu", var_name.c_str(), aligned_tensor.MutableData().GetSize());
       if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(aligned_tensor.GetAlignedPtr(),
                                                                        aligned_tensor.GetData().size()) == nullptr) {
-        GELOGE(MEMALLOC_FAILED, "Malloc host memory for an existed GeTensor failed, model_name_:%s.", GetGraphName());
+        GELOGE(MEMALLOC_FAILED, "[Malloc][HostMemory] for an existed GeTensor failed, model_name_:%s.", GetGraphName());
         return MEMALLOC_FAILED;
       }
       var_tensor.reset(new(std::nothrow)TensorValue(aligned_tensor.MutableData().data(),
@@ -1006,6 +1018,8 @@ Status HybridModelBuilder::InitVariableTensors() {
     int64_t tensor_size = 0;
     if (TensorUtils::CalcTensorMemSize(output_tensor.GetShape(), output_tensor.GetFormat(), output_tensor.GetDataType(),
                                        tensor_size) != SUCCESS) {
+      REPORT_CALL_ERROR("E19999", "CalcTensorMemSize failed when HybridModelBuilder %s, node name:%s",
+          __FUNCTION__, it.first.c_str());
       GELOGE(INTERNAL_ERROR, "[Calculate][TensorMemSize] failed, node name:%s", it.first.c_str());
       return INTERNAL_ERROR;
     }
@@ -1016,7 +1030,7 @@ Status HybridModelBuilder::InitVariableTensors() {
     }
     if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(mem_info.host_aligned_ptr,
                                                                      tensor_size) == nullptr) {
-      GELOGE(MEMALLOC_FAILED, 
+      GELOGE(MEMALLOC_FAILED,
           "[Malloc][HostMem] for an existed GeTensor failed, Host variable [%s].", it.first.c_str());
       return MEMALLOC_FAILED;
     }
@@ -1078,7 +1092,7 @@ Status HybridModelBuilder::InitWeights() {
       const GeTensorDesc &tensor_desc = ge_tensor->GetTensorDesc();
       int64_t tensor_size = 0;
       GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetSize(*op_desc->MutableOutputDesc(0), tensor_size),
-                              "[Invoke][GetSize][%s] Failed to get tensor size",
+                              "[Invoke][GetSize][%s] Failed to get output tensor size",
                               node->GetName().c_str());
       int64_t data_offset = 0;
       GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetDataOffset(tensor_desc, data_offset),
@@ -1333,16 +1347,18 @@ Status HybridModelBuilder::GetPeerNodeAcrossSubGraphs(const NodePtr &data_node,
   GELOGD("To get peer node of %s::%s", sub_graph->GetName().c_str(), data_node->GetName().c_str());
   auto wrapped_node = data_node->GetOwnerComputeGraph()->GetParentNode();
   if (wrapped_node == nullptr) {
+    REPORT_INNER_ERROR("E19999", "[%s] Node is in root graph when HybridModelBuilder %s.",
+        data_node->GetName().c_str(), __FUNCTION__);
     GELOGE(INTERNAL_ERROR, "[Invoke][GetParentNode][%s] Node is in root graph.", data_node->GetName().c_str());
     return INTERNAL_ERROR;
   }
   auto data_op_desc = data_node->GetOpDesc();
   uint32_t parent_index = 0;
   if (!AttrUtils::GetInt(data_op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
-    GELOGE(INTERNAL_ERROR,
-           "[Invoke][GetInt][%s] Failed to get attr [%s]",
-           data_op_desc->GetName().c_str(),
-           ATTR_NAME_PARENT_NODE_INDEX.c_str());
+    REPORT_CALL_ERROR("E19999", "[%s] Failed to get attr [%s] when HybridModelBuilder %s.",
+        data_op_desc->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str(), __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Invoke][GetInt][%s] Failed to get attr [%s]",
+        data_op_desc->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str());
     return INTERNAL_ERROR;
   }
 
@@ -1350,7 +1366,9 @@ Status HybridModelBuilder::GetPeerNodeAcrossSubGraphs(const NodePtr &data_node,
   GE_CHECK_NOTNULL(wrapped_node_in_anchor);
   auto src_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
   if (src_out_anchor == nullptr || src_out_anchor->GetOwnerNode() == nullptr) {
-    GELOGE(INTERNAL_ERROR, 
+    REPORT_INNER_ERROR("E19999", "[%s] Parent node do not have peer anchor when HybridModelBuilder %s.",
+        data_node->GetName().c_str(), __FUNCTION__);
+    GELOGE(INTERNAL_ERROR,
         "[Check][ParentNode][%s] Parent node do not have peer anchor.", data_node->GetName().c_str());
     return INTERNAL_ERROR;
   }
@@ -1374,10 +1392,13 @@ Status HybridModelBuilder::GetPeerNodeAcrossSubGraphs(const NodePtr &data_node,
   auto src_graph = NodeUtils::GetSubgraph(*src_wrapped_node, kSubgraphIndex);
   GE_CHECK_NOTNULL(src_graph);
   auto src_net_output_node = src_graph->FindFirstNodeMatchType(NETOUTPUT);
-  GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(src_net_output_node == nullptr,
-                                 return INTERNAL_ERROR,
-                                 "[Invoke][FindFirstNodeMatchType]Failed to find NetOutput in subgraph: %s",
-                                 src_graph->GetName().c_str());
+  if (src_net_output_node == nullptr) {
+    REPORT_INNER_ERROR("E19999", "Failed to find NetOutput in subgraph: %s when HybridModelBuilder %s",
+        src_graph->GetName().c_str(), __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Invoke][FindFirstNodeMatchType]Failed to find NetOutput in subgraph: %s",
+        src_graph->GetName().c_str());
+    return INTERNAL_ERROR;
+  }
   auto net_output_desc = src_net_output_node->GetOpDesc();
   GE_CHECK_NOTNULL(net_output_desc);
 
@@ -1567,10 +1588,10 @@ Status HybridModelBuilder::GetParentNodeOutputIndex(const OpDesc &op_desc, int i
   auto input_desc = op_desc.MutableInputDesc(index);
   GE_CHECK_NOTNULL(input_desc);
   if (!AttrUtils::GetInt(input_desc, ATTR_NAME_PARENT_NODE_INDEX, out_index)) {
-    GELOGE(INTERNAL_ERROR, "[Invoke][GetInt]NetOutput input tensor %d, attr %s not found.",
-        index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
-    REPORT_CALL_ERROR("E19999", "NetOutput input tensor %d, attr %s not found when %s.",
-        index, ATTR_NAME_PARENT_NODE_INDEX.c_str(), __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Invoke][GetInt]NetOutput %s input tensor %d, attr %s not found.",
+        op_desc.GetName().c_str(), index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
+    REPORT_CALL_ERROR("E19999", "NetOutput %s input tensor %d, attr %s not found when %s.",
+        op_desc.GetName().c_str(), index, ATTR_NAME_PARENT_NODE_INDEX.c_str(), __FUNCTION__);
     return INTERNAL_ERROR;
   }
   return SUCCESS;
@@ -2026,10 +2047,10 @@ Status HybridModelBuilder::BuildInputMapping(GraphItem &graph_item,
       data_op_index++;
     } else {
       if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
-        GELOGE(FAILED,
-               "[Invoke][GetInt][%s] Failed to get attr [%s]",
-               node->GetName().c_str(),
-               ATTR_NAME_PARENT_NODE_INDEX.c_str());
+        GELOGE(FAILED, "[Invoke][GetInt][%s] Failed to get attr [%s]",
+            node->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str());
+        REPORT_CALL_ERROR("E19999", "call GetInt failed when HybridModelBuilder %s, [%s] Failed to get attr [%s]",
+            __FUNCTION__, node->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str());
         return FAILED;
       }
     }