modify code to add report errmsg

ge/hybrid/common/npu_memory_allocator.cc

@@ -39,7 +39,7 @@ 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 when %s.", __FUNCTION__);
+    GELOGE(RT_FAILED, "[Get][Device] Failed.");
     REPORT_INNER_ERROR("E19999", "rtGetDevice failed when %s.", __FUNCTION__);
     return nullptr;
   }
@@ -58,8 +58,8 @@ 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 when %s.", 
-        device_id_, allocate_size, __FUNCTION__);
+    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.", 
         device_id_, allocate_size, __FUNCTION__);
     return nullptr;
@@ -72,8 +72,10 @@ 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 when %s.", allocate_size, __FUNCTION__);
-      REPORT_CALL_ERROR("E19999", "Invalid HBM memory size: %zu when %s.", allocate_size, __FUNCTION__);
+      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.", 
+          allocate_size, kMaxHbmMemorySize, __FUNCTION__);
       return nullptr;
     }
     void *try_reuse_addr = nullptr;
@@ -92,8 +94,8 @@ 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 when %s.", 
-        device_id_, allocate_size, __FUNCTION__);
+    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.", 
         device_id_, allocate_size, __FUNCTION__);
     return nullptr;

ge/hybrid/common/tensor_value.cc

@@ -32,7 +32,7 @@ std::unique_ptr<TensorBuffer> TensorBuffer::Create(NpuMemoryAllocator *allocator
   }
 
   if (allocator == nullptr) {
-    GELOGE(INTERNAL_ERROR, "[Check][Param:NpuMemoryAllocator] allocator is NULL, when %s.", __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Check][Param:NpuMemoryAllocator] allocator is NULL.");
     REPORT_INNER_ERROR("E19999", "input allocator is NULL, when %s.", __FUNCTION__);
     return nullptr;
   }
@@ -43,7 +43,7 @@ std::unique_ptr<TensorBuffer> TensorBuffer::Create(NpuMemoryAllocator *allocator
   }
   buffer = allocator->Allocate(size, attr);
   if (buffer == nullptr) {
-    GELOGE(MEMALLOC_FAILED, "[Allocate][Memory] Failed. size = %zu, when %s.", size, __FUNCTION__);
+    GELOGE(MEMALLOC_FAILED, "[Allocate][Memory] Failed. size = %zu.", size);
     REPORT_CALL_ERROR("E19999", "allocate failed, size = %zu, when %s.", size, __FUNCTION__);
     return nullptr;
   }

ge/hybrid/executor/hybrid_execution_context.cc

@@ -60,7 +60,7 @@ Status GraphExecutionContext::Synchronize(rtStream_t rt_stream) {
   }
 
   GELOGE(RT_FAILED, 
-      "[Invoke][rtStreamSynchronize] failed when GraphExecutionContext %s, ret = %d", __FUNCTION__, rt_ret);
+      "[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

@@ -51,8 +51,13 @@ void HybridModelAsyncExecutor::SetModelName(const string &model_name) {
 }
 
 Status HybridModelAsyncExecutor::EnqueueData(const shared_ptr<InputDataWrapper> &data) {
-  GE_CHK_STATUS_EXEC(data_inputer_->Push(data), return domi::DATA_QUEUE_ISFULL,
-                     "[Push][Data] Data queue is full, please call again later, model_id %u ", model_id_);
+  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, 
+        "[Push][Data] Data queue is full, please call again later, model_id %u ", model_id_);
+    return domi::DATA_QUEUE_ISFULL;
+  }
   GELOGD("EnqueueData successfully. model_id = %u, data_index = %u", data->GetInput().model_id, data->GetInput().index);
   return SUCCESS;
 }
@@ -60,9 +65,12 @@ 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_);
-  GE_CHK_BOOL_RET_STATUS(!run_flag_, INTERNAL_ERROR, 
-      "[Check][RunState] Model already started when HybridModelAsyncExecutor %s.", __FUNCTION__);
-
+  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;
+  }
   run_flag_ = true;
   listener_ = listener;
   future_ = std::async(std::launch::async, [&]() -> Status {
@@ -73,7 +81,7 @@ Status HybridModelAsyncExecutor::Start(const std::shared_ptr<ModelListener> &lis
   });
 
   GE_CHK_BOOL_RET_STATUS(future_.valid(), INTERNAL_ERROR, 
-      "[Check][RunState] Failed to start when HybridModelAsyncExecutor %s.", __FUNCTION__);
+      "[Check][RunState] Failed to start, model_id:%u.", model_id_);
   GELOGD("HybridModelExecutor::Start successfully");
   return SUCCESS;
 }
@@ -108,8 +116,8 @@ 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 when HybridModelAsyncExecutor %s.", __FUNCTION__);
-  GE_CHK_STATUS_RET(DumpOpDebug(), "[Dump][OpDebug] failed when HybridModelAsyncExecutor %s.", __FUNCTION__);
+      "[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());
   if (model_->GetRootGraphItem()->NumGroups() >= kMinimumPiplineStages) {
@@ -117,19 +125,19 @@ Status HybridModelAsyncExecutor::Init() {
         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 when HybridModelAsyncExecutor %s.", __FUNCTION__);
+        "[Init][HybridModelPipelineExecutor] failed, model_id:%u.", model_id_);
   }
 
-  GE_CHK_STATUS_RET(InitInputDesc(), "[Init][InputDesc] failed when HybridModelAsyncExecutor %s.", __FUNCTION__);
+  GE_CHK_STATUS_RET(InitInputDesc(), "[Init][InputDesc] failed, model_id:%u.", model_id_);
 
   return SUCCESS;
 }
 
 Status HybridModelAsyncExecutor::PreRun(InputData &current_data, HybridModelExecutor::ExecuteArgs &args) {
-  GE_CHK_STATUS_RET(SyncVarData(), "[Invoke][SyncVarData] failed when HybridModelAsyncExecutor %s.", __FUNCTION__);
+  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 when HybridModelAsyncExecutor %s.", __FUNCTION__);
+      "[Invoke][PrepareInputs] failed to copy input data to model, model_id:%u.", model_id_);
   RECORD_MODEL_EXECUTION_EVENT(executor_->GetContext(), "[CopyInputData] End");
   return SUCCESS;
 }
@@ -160,7 +168,7 @@ Status HybridModelAsyncExecutor::RunInternal() {
     GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(
         ret != SUCCESS, (void) HandleResult(ret, current_data.index, args, data_wrapper->GetOutput());
         CsaInteract::GetInstance().StoreInternalErrorCode(ret, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
-        continue, "[Invoke][PreRun] failed when HybridModelAsyncExecutor %s.", __FUNCTION__);  // [No need to check value]
+        continue, "[Invoke][PreRun] failed, model_id:%u.", model_id_);  // [No need to check value]
 
     if (pipe_executor_ != nullptr) {
       GELOGI("HybridModel will execute in pipeline mode");
@@ -204,9 +212,7 @@ Status HybridModelAsyncExecutor::HandleResult(Status exec_ret,
   }
 
   if (exec_ret != SUCCESS) {
-    GELOGE(exec_ret, 
-        "[Check][Param:Status] failed to execute graph when HybridModelAsyncExecutor %s. model_id = %u", 
-        __FUNCTION__, model_id_);
+    GELOGE(exec_ret, "[Check][Param:Status] failed to execute graph. model_id = %u", model_id_);
     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);
@@ -245,11 +251,11 @@ 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, 
-        "[Check][Size]Blob size mismatches, expect at least %zu, but got %zu when HybridModelAsyncExecutor %s.",
-        input_tensor_desc_.size(), current_data.blobs.size(), __FUNCTION__);
+        "[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", 
-        "Blob size mismatches, expect at least %zu, but got %zu when HybridModelAsyncExecutor %s.",
-        input_tensor_desc_.size(), current_data.blobs.size(), __FUNCTION__);
+        "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;
   }
 
@@ -262,11 +268,11 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
     if (is_input_dynamic_[input_index]) {
       if (input_index >= current_data.shapes.size()) {
         GELOGE(PARAM_INVALID, 
-            "[Check][Range]Shape index out of range, index = %zu, shape size = %zu when HybridModelAsyncExecutor %s.",
-            input_index, current_data.shapes.size(), __FUNCTION__);
+            "[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", 
-            "Shape index out of range, index = %zu, shape size = %zu when HybridModelAsyncExecutor %s.",
-            input_index, current_data.shapes.size(), __FUNCTION__);    
+            "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_);    
         return PARAM_INVALID;
       }
       auto &tensor_desc = input_tensor_desc_[input_index];
@@ -274,7 +280,7 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
       std::vector<std::pair<int64_t, int64_t>> range;
       auto range_ret = tensor_desc->GetShapeRange(range);
       GE_CHK_BOOL_RET_STATUS(range_ret == GRAPH_SUCCESS, INTERNAL_ERROR,
-                             "[Invoke][GetShapeRange] failed, ret=%u.", range_ret);
+                             "[Invoke][GetShapeRange] failed, ret=%u, model_id = %u.", range_ret, model_id_);
       for (size_t k = 0; k < range.size(); ++k) {
         if (k >= shape.GetDimNum()) {
           break;
@@ -282,11 +288,11 @@ 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, 
-              "[Check][Range]Dim out of range, shape idx = %zu, dim idx = %zu, dim = %ld, range = [%ld, %ld]",
-              input_index, k, shape.GetDim(k), range[k].first, range[k].second);
+              "[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", 
-              "Dim out of range, shape idx = %zu, dim idx = %zu, dim = %ld, range = [%ld, %ld]",
-              input_index, k, shape.GetDim(k), range[k].first, range[k].second);    
+              "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_);    
           return PARAM_INVALID;
         }
       }
@@ -294,8 +300,8 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
       args.input_desc[input_index] = tensor_desc;
       GELOGD("Update shape of input[%zu] to [%s]", input_index, tensor_desc->MutableShape().ToString().c_str());
       GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetTensorMemorySizeInBytes(*tensor_desc, tensor_size),
-          "[Invoke][GetTensorMemorySizeInBytes]Failed to calc tensor size, index = %zu, shape = [%s]",
-          input_index, tensor_desc->GetShape().ToString().c_str());
+          "[Invoke][GetTensorMemorySizeInBytes]Failed to calc tensor size, index = %zu, shape = [%s], model_id = %u.",
+          input_index, tensor_desc->GetShape().ToString().c_str(), model_id_);
       GELOGD("Input tensor[%zu] size = %zu", input_index, tensor_size);
     }
 
@@ -311,12 +317,16 @@ Status HybridModelAsyncExecutor::PrepareInputs(const InputData &current_data, Hy
     GELOGD("To copy input data for input[%zu]", input_index);
     const DataBuffer &data_buf = blobs[input_index];
     auto mem_size = static_cast<uint64_t>(tensor_size);
-    GE_CHK_BOOL_RET_STATUS(mem_size >= data_buf.length,
-                           PARAM_INVALID,
-                           "[Check][Size]input data size(%lu) does not match model required size(%lu), ret failed.",
-                           data_buf.length,
-                           mem_size);
 
+    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; 
+    }
     if (data_buf.length > 0) {
       GELOGI("[IMAS]CopyPlainData memcpy graph_%u type[F] output[%zu] memaddr[%p] mem_size[%zu] datasize[%lu]",
              model_->root_runtime_param_.graph_id,
@@ -371,7 +381,7 @@ Status HybridModelAsyncExecutor::OnComputeDone(uint32_t data_index, uint32_t res
   GELOGD("OnComputeDone. model id = %u, data index = %u, execution ret = %u", model_id_, data_index, result_code);
   if (listener_ != nullptr) {
     GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_index, result_code, outputs),
-                  "[Invoke][OnComputeDone] failed.");
+                  "[Invoke][OnComputeDone] failed, model_id = %u.", model_id_);
   }
 
   return result_code;
@@ -385,12 +395,11 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
   std::vector<TensorValue> &output_tensors = args.outputs;
   if (output_tensor_desc_list.size() != output_tensors.size()) {
     GELOGE(INTERNAL_ERROR,
-        "[Check][Size]Output sizes mismatch. From op_desc = %zu, and from output tensors = %zu "
-        "when HybridModelAsyncExecutor %s.",
-        output_tensor_desc_list.size(), output_tensors.size(), __FUNCTION__);
-    REPORT_INNER_ERROR("E19999", "Output sizes mismatch. From op_desc = %zu, and from output tensors = %zu "
-        "when HybridModelAsyncExecutor %s.",
-        output_tensor_desc_list.size(), output_tensors.size(), __FUNCTION__);
+        "[Check][Size]Output sizes mismatch. From op_desc = %zu, and from output tensors = %zu, model_id = %u.",
+        output_tensor_desc_list.size(), output_tensors.size(), model_id_);
+    REPORT_INNER_ERROR("E19999", "Output sizes mismatch. From op_desc = %zu, and from output tensors = %zu, "
+        "when HybridModelAsyncExecutor %s, model_id = %u.",
+        output_tensor_desc_list.size(), output_tensors.size(), __FUNCTION__, model_id_);
     return INTERNAL_ERROR;
   }
 
@@ -422,10 +431,12 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
     GE_CHECK_LE(output_size, UINT32_MAX);
     if (output_tensor.GetSize() < static_cast<size_t>(output_size)) {
       GELOGE(INTERNAL_ERROR,
-          "[Check][Size]output[%zu] tensor size(%zu) is not enough for output shape [%s]",
-          i, output_tensor.GetSize(), tensor_desc->GetShape().ToString().c_str());
-      REPORT_INNER_ERROR("E19999", "output[%zu] tensor size(%zu) is not enough for output shape [%s]",
-          i, output_tensor.GetSize(), tensor_desc->GetShape().ToString().c_str());
+          "[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", 
+          "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__);
       return INTERNAL_ERROR;
     }
 
@@ -481,7 +492,7 @@ Status HybridModelAsyncExecutor::Execute(const std::vector<DataBuffer> &inputs,
     args.input_desc.emplace_back(tensor_desc_ptr);
   }
 
-  GE_CHK_STATUS_RET(executor_->Execute(args), "[Invoke][Execute] Failed when HybridModelAsyncExecutor %s.", __FUNCTION__);
+  GE_CHK_STATUS_RET(executor_->Execute(args), "[Invoke][Execute] Failed, model_id = %u.", model_id_);
   for (const auto &output_tensor_desc : args.output_desc) {
     output_desc.emplace_back(*output_tensor_desc);
   }
@@ -502,14 +513,15 @@ Status HybridModelAsyncExecutor::Execute(const vector<GeTensor> &inputs, vector<
   }
 
   HybridModelExecutor::ExecuteArgs args;
-  GE_CHK_STATUS_RET(PrepareInputs(input_data, args), "[Invoke][PrepareInputs]Failed to copy input data to model");
+  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.");
+  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), 
-      "[Invoke][CopyOutputs]Failed to copy outputs.");
+      "[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());
 
   int out_index = 0;
@@ -560,7 +572,8 @@ 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(), "[Invoke][LoadDumpInfo] failed in hybrid engine");
+    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");
   }
   return SUCCESS;

ge/hybrid/executor/hybrid_model_executor.cc

@@ -72,7 +72,7 @@ Status HybridModelExecutor::Execute(HybridModelExecutor::ExecuteArgs &args) {
   if (ret == END_OF_SEQUENCE) {
     args.is_eos = true;
   } else {
-    GE_CHK_STATUS_RET(ret, "[Invoke][ExecuteGraphInternal]Failed when HybridModelExecutor %s.", __FUNCTION__);
+    GE_CHK_STATUS_RET(ret, "[Invoke][ExecuteGraphInternal] Failed, ret:%d.", ret);
   }
   return SUCCESS;
 }

ge/hybrid/executor/hybrid_model_pipeline_executor.cc

@@ -59,8 +59,8 @@ 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 when StageExecutor %s.", 
-          id_, task_info.iteration, __FUNCTION__);
+      GELOGE(INTERNAL_ERROR, "[Check][Range][Executor: %d] Unexpected iteration: %d.", 
+          id_, task_info.iteration);
       REPORT_INNER_ERROR("E19999", "[Executor: %d] Unexpected iteration: %d when StageExecutor %s.", 
           id_, task_info.iteration, __FUNCTION__);
       return INTERNAL_ERROR;
@@ -97,10 +97,10 @@ 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 when StageExecutor %s. iteration = %d", 
-          id_, __FUNCTION__, task_info.iteration);
-      REPORT_CALL_ERROR("E19999", "[Executor: %d] Failed to sync result when StageExecutor %s. iteration = %d", 
-          id_, __FUNCTION__, task_info.iteration);
+          "[Invoke][Synchronize][Executor: %d] Failed to sync result:%d. iteration = %d", 
+          id_, sync_result, task_info.iteration);
+      REPORT_CALL_ERROR("E19999", "[Executor: %d] Failed to sync result:%d when StageExecutor %s. iteration = %d", 
+          id_, sync_result, __FUNCTION__, task_info.iteration);
       context_.profiler->Dump(std::cout);
       context_.callback_manager->Destroy();
       RuntimeInferenceContext::DestroyContext(std::to_string(context_.context_id));
@@ -249,8 +249,7 @@ Status HybridModelPipelineExecutor::Execute(HybridModelExecutor::ExecuteArgs &ar
     GELOGD("Start to sync result of executor[%zu]", i);
     auto ret = futures[i].get();
     if (ret != SUCCESS) {
-      GELOGE(ret, "[Check][Result][Executor: %zu] Failed to schedule tasks when HybridModelPipelineExecutor %s.",
-          i, __FUNCTION__);
+      GELOGE(ret, "[Check][Result][Executor: %zu] Failed to schedule tasks.", i);
       REPORT_INNER_ERROR("E19999", "[Executor: %zu] Failed to schedule tasks when HybridModelPipelineExecutor %s.",
           i, __FUNCTION__);
       has_error = true;
@@ -260,8 +259,7 @@ Status HybridModelPipelineExecutor::Execute(HybridModelExecutor::ExecuteArgs &ar
     ret = stage_executors_[i]->Synchronize();
 
     if (ret != SUCCESS) {
-      GELOGE(ret, "[Invoke][Synchronize] failed for [Executor: %zu] when HybridModelPipelineExecutor %s.",
-          i, __FUNCTION__);
+      GELOGE(ret, "[Invoke][Synchronize] failed for [Executor: %zu].", i);
       REPORT_CALL_ERROR("E19999", "[Executor: %zu] failed to Synchronize result when HybridModelPipelineExecutor %s.",
           i, __FUNCTION__);    
       has_error = true;
@@ -279,7 +277,7 @@ Status HybridModelPipelineExecutor::Execute(HybridModelExecutor::ExecuteArgs &ar
   iteration_ = config_.iteration_end;
 
   if (has_error) {
-    GELOGE(FAILED, "[Check][Error]Error occurred while execution when HybridModelPipelineExecutor %s.", __FUNCTION__);
+    GELOGE(FAILED, "[Check][Error]Error occurred while execution.");
     REPORT_INNER_ERROR("E19999", "Error occurred while execution when HybridModelPipelineExecutor %s.", __FUNCTION__);
     return FAILED;
   }

ge/hybrid/executor/hybrid_profiler.cc

@@ -40,8 +40,8 @@ void HybridProfiler::RecordEvent(EventType event_type, const char *fmt, ...) {
 
   char buf[kEventDescMax];
   if (vsnprintf_s(buf, kEventDescMax, kEventDescMax - 1, fmt, args) == -1) {
-    GELOGE(FAILED, "[Parse][Param:fmt]Format %s failed when HybridProfiler %s.", fmt, __FUNCTION__);
-    REPORT_INNER_ERROR("E19999", "Parse Format %s failed when HybridProfiler %s.", fmt, __FUNCTION__);
+    GELOGE(FAILED, "[Parse][Param:fmt]Format %s failed.", fmt);
+    REPORT_CALL_ERROR("E19999", "Parse Format %s failed when HybridProfiler %s.", fmt, __FUNCTION__);
     va_end(args);
     return;
   }

ge/hybrid/executor/node_done_manager.cc

@@ -28,8 +28,8 @@ bool NodeDoneManager::Cond::Await() {
   if (!cv_.wait_for(lk,
                     std::chrono::seconds(kDefaultWaitTimeoutInSec),
                     [&]() { return is_released_ || is_cancelled_; })) {
-    GELOGE(INTERNAL_ERROR, "[Invoke][wait_for]Wait timed out when %s.", __FUNCTION__);
-    REPORT_INNER_ERROR("E19999", "wait timed out when %s.", __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Invoke][wait_for]Wait timed out.");
+    REPORT_INNER_ERROR("E19999", "wait timed out[%d] when %s.", kDefaultWaitTimeoutInSec, __FUNCTION__);
     return false;
   }
 

ge/hybrid/executor/node_state.cc

@@ -67,8 +67,8 @@ 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] when ShapeInferenceState %s.", 
-          node_item.NodeName().c_str(), __FUNCTION__);
+      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__);    
       return FAILED;
@@ -124,8 +124,8 @@ Status ShapeInferenceState::AwaitShapesReady(const GraphExecutionContext &contex
       }
 
       if (context.GetStatus() != SUCCESS) {
-        GELOGE(FAILED, "[Check][Status][%s] Await pending shape cancelled when %s.", 
-            node_item.NodeName().c_str(), __FUNCTION__);
+        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.", 
             node_item.NodeName().c_str(), __FUNCTION__);
         break;
@@ -133,10 +133,10 @@ Status ShapeInferenceState::AwaitShapesReady(const GraphExecutionContext &contex
     }
 
     if (!wait_success) {
-      GELOGE(FAILED, "[Check][Status][%s] Wait for shape timeout when %s.", 
-          node_item.NodeName().c_str(), __FUNCTION__);
-      REPORT_CALL_ERROR("E19999", "[%s] Wait for shape timeout when %s.", 
-          node_item.NodeName().c_str(), __FUNCTION__);
+      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.", 
+          node_item.NodeName().c_str(), kWaitInternal, __FUNCTION__);
       return FAILED;
     }
   }
@@ -241,7 +241,7 @@ Status NodeState::WaitForPrepareDone() {
   if (prepare_future_.valid()) {
     GELOGD("[%s] Start to wait for prepare future.", GetName().c_str());
     GE_CHK_STATUS_RET(prepare_future_.get(),
-        "[Check][Status][%s] PreRun failed when NodeState %s.", GetName().c_str(), __FUNCTION__);
+        "[Check][Status][%s] PreRun failed.", GetName().c_str());
   }
 
   return SUCCESS;

ge/hybrid/executor/worker/execution_engine.cc

@@ -102,9 +102,9 @@ Status NodeDoneCallback::PrepareConstInputs(const NodeItem &node_item) {
 
     if (output_tensor->GetSize() < static_cast<size_t>(tensor_size)) {
       GELOGE(INTERNAL_ERROR,
-          "[Check][Size][%s] Tensor size is not enough. output index = %d, required size = %ld, tensor = %s when %s.",
+          "[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(), __FUNCTION__);
+          output_tensor->DebugString().c_str());
       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,
@@ -175,7 +175,7 @@ Status NodeDoneCallback::GetTaskDescInfo(const NodePtr node, const HybridModel *
 Status NodeDoneCallback::ProfilingReport() {
   auto node = context_->GetNodeItem().node;
   if (node == nullptr) {
-    GELOGE(PARAM_INVALID, "[Get][Node] value is nullptr when %s.", __FUNCTION__);
+    GELOGE(PARAM_INVALID, "[Get][Node] value is nullptr.");
     REPORT_INNER_ERROR("E19999", "Get node failed, when %s.", __FUNCTION__);
     return PARAM_INVALID;
   }
@@ -193,7 +193,7 @@ Status NodeDoneCallback::ProfilingReport() {
   std::vector<TaskDescInfo> task_desc_info;
   auto profiling_ret = GetTaskDescInfo(node, model, task_desc_info);
   if (profiling_ret != RT_ERROR_NONE) {
-    GELOGE(profiling_ret, "[Get][TaskDescInfo] of node:%s failed, when %s.", node->GetName().c_str(), __FUNCTION__);
+    GELOGE(profiling_ret, "[Get][TaskDescInfo] of node:%s failed.", node->GetName().c_str());
     REPORT_CALL_ERROR("E19999", "GetTaskDescInfo of node:%s failed, when %s.", node->GetName().c_str(), __FUNCTION__);
     return profiling_ret;
   }
@@ -206,7 +206,7 @@ Status NodeDoneCallback::ProfilingReport() {
 Status NodeDoneCallback::DumpDynamicNode() {
   auto node = context_->GetNodeItem().node;
   if (node == nullptr) {
-    GELOGE(PARAM_INVALID, "[Get][Node] value is nullptr when %s.", __FUNCTION__);
+    GELOGE(PARAM_INVALID, "[Get][Node] value is nullptr.");
     REPORT_INNER_ERROR("E19999", "get node is nullptr when %s.", __FUNCTION__);
     return PARAM_INVALID;
   }
@@ -250,12 +250,12 @@ Status NodeDoneCallback::DumpDynamicNode() {
   void *global_step = context_->GetExecutionContext()->global_step;
   dump_op_.SetLoopAddr(global_step, loop_per_iter, loop_cond);
 
-  GE_CHK_STATUS_RET(dump_op_.LaunchDumpOp(), "[Launch][DumpOp] failed in hybird model when %s.", __FUNCTION__);
+  GE_CHK_STATUS_RET(dump_op_.LaunchDumpOp(), "[Launch][DumpOp] failed in hybird model.");
 
   auto rt_ret = rtStreamSynchronize(stream);
   if (rt_ret != RT_ERROR_NONE) {
-    GELOGE(rt_ret, "[Call][rtStreamSynchronize] failed when %s.", __FUNCTION__);
-    REPORT_CALL_ERROR("E19999", "call rtStreamSynchronize failed when %s.", __FUNCTION__);
+    GELOGE(rt_ret, "[Call][rtStreamSynchronize] failed, ret = %d.", rt_ret);
+    REPORT_CALL_ERROR("E19999", "call rtStreamSynchronize failed when %s, ret = %d.", __FUNCTION__, rt_ret);
     return rt_ret;
   }
   return SUCCESS;
@@ -270,12 +270,12 @@ Status NodeDoneCallback::OnNodeDone() {
   const DumpProperties &dump_properties = context_->GetDumpProperties();
   if (dump_properties.IsDumpOpen() || context_->IsOverFlow()) {
     GELOGI("Start to dump dynamic shape op");
-    GE_CHK_STATUS_RET(DumpDynamicNode(), "[Call][DumpDynamicNode] Failed when %s.", __FUNCTION__);
+    GE_CHK_STATUS_RET(DumpDynamicNode(), "[Call][DumpDynamicNode] Failed.");
   }
 
   if (ProfilingManager::Instance().ProfilingModelExecuteOn()) {
-    GE_CHK_STATUS_RET(ProfilingReport(), "[Report][Profiling] of node[%s] failed when %s.",
-        node_item.NodeName().c_str(), __FUNCTION__);
+    GE_CHK_STATUS_RET(ProfilingReport(), "[Report][Profiling] of node[%s] failed.",
+        node_item.NodeName().c_str());
   }
 
   // release workspace
@@ -298,7 +298,7 @@ Status NodeDoneCallback::OnNodeDone() {
     }
 
     GE_CHK_STATUS_RET(context_->PropagateOutputs(),
-        "[Propagate][Outputs] of [%s] failed when %s.", node_item.NodeName().c_str(), __FUNCTION__);
+        "[Propagate][Outputs] of [%s] failed.", node_item.NodeName().c_str());
 
     RECORD_CALLBACK_EVENT(graph_context_, context_->GetNodeName(), "[PropagateOutputs] End");
   }
@@ -338,8 +338,8 @@ Status ExecutionEngine::DoExecuteAsync(NodeState &node_state,
                                        const std::function<void()> &callback) {
   const auto &task = node_state.GetKernelTask();
   if (task == nullptr) {
-    GELOGE(INTERNAL_ERROR, "[Get][KernelTask] of [%s] is null when %s.", node_state.GetName().c_str(), __FUNCTION__);
-    REPORT_CALL_ERROR("E19999", "GetKernelTask of %s is null when %s.", node_state.GetName().c_str(), __FUNCTION__);
+    GELOGE(INTERNAL_ERROR, "[Get][KernelTask] of [%s] is null.", node_state.GetName().c_str());
+    REPORT_INNER_ERROR("E19999", "GetKernelTask of %s is null when %s.", node_state.GetName().c_str(), __FUNCTION__);
     return INTERNAL_ERROR;
   }
 
@@ -354,7 +354,7 @@ Status ExecutionEngine::DoExecuteAsync(NodeState &node_state,
   GE_CHECK_NOTNULL(executor);
   RECORD_EXECUTION_EVENT(&context, task_context.GetNodeName(), "[PrepareTask] Start");
   GE_CHK_STATUS_RET(executor->PrepareTask(*task, task_context),
-      "[Prepare][Task] for [%s] failed when %s", node_state.GetName().c_str(), __FUNCTION__);
+      "[Prepare][Task] for [%s] failed.", node_state.GetName().c_str());
   RECORD_EXECUTION_EVENT(&context, task_context.GetNodeName(), "[PrepareTask] End");
   GELOGD("[%s] Done task preparation successfully.", node_state.GetName().c_str());
 
@@ -365,8 +365,8 @@ Status ExecutionEngine::DoExecuteAsync(NodeState &node_state,
     }
   }
 
-  GE_CHK_STATUS_RET(ValidateInputTensors(node_state, task_context), "[Validate][InputTensors] for %s failed when %s.",
-      node_state.GetName().c_str(), __FUNCTION__);
+  GE_CHK_STATUS_RET(ValidateInputTensors(node_state, task_context), "[Validate][InputTensors] for %s failed.",
+      node_state.GetName().c_str());
   RECORD_EXECUTION_EVENT(&context, task_context.GetNodeName(), "[ValidateInputTensors] End");
 
   if (context.profiling_level > 0) {
@@ -420,8 +420,8 @@ Status ExecutionEngine::ValidateInputTensors(const NodeState &node_state, const
                input_tensor->GetSize());
       } else {
         GELOGE(INTERNAL_ERROR,
-            "[Check][Size] for [%s] Input[%d]: tensor size mismatches. expected: %ld, but given %zu when %s.",
-            task_context.GetNodeName(), i, expected_size, input_tensor->GetSize(), __FUNCTION__);
+            "[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__);    
         return INTERNAL_ERROR;
@@ -437,7 +437,7 @@ Status ExecutionEngine::PropagateOutputs(const NodeItem &node_item,
                                          GraphExecutionContext &context) {
   if (node_item.shape_inference_type != DEPEND_COMPUTE) {
     GE_CHK_STATUS_RET(task_context.PropagateOutputs(),
-        "[Propagate][Outputs] for [%s] failed when ExecutionEngine %s.", node_item.NodeName().c_str(), __FUNCTION__);
+        "[Propagate][Outputs] for [%s] failed.", node_item.NodeName().c_str());
     RECORD_EXECUTION_EVENT(&context, task_context.GetNodeName(), "[PropagateOutputs] End");
     GELOGD("[%s] Done propagating outputs successfully.", node_item.NodeName().c_str());
   }

ge/hybrid/executor/worker/shape_inference_engine.cc

@@ -70,7 +70,7 @@ Status ShapeInferenceEngine::InferShape(NodeState &node_state) {
   {
     RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] Start");
     GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndTypeForRunning(node_item.node, true),
-        "[Invoke][InferShapeAndType] for %s failed when %s.", node_item.NodeName().c_str(), __FUNCTION__);
+        "[Invoke][InferShapeAndType] for %s failed.", node_item.NodeName().c_str());
     RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] End");
   }
 
@@ -172,7 +172,7 @@ Status ShapeInferenceEngine::InferShapeForSubgraph(const NodeItem &node_item, co
     GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndType(node));
     GELOGD("[%s] Done invoking InferShapeAndType", node->GetName().c_str());
     GE_CHK_STATUS_RET(UpdatePeerNodeShape(*node),
-        "[Update][PeerNodeShape] failed for [%s] when %s.", node->GetName().c_str(), __FUNCTION__);
+        "[Update][PeerNodeShape] failed for [%s].", node->GetName().c_str());
   }
 
   for (auto &it : fused_subgraph.output_mapping) {
@@ -204,8 +204,7 @@ Status ShapeInferenceEngine::UpdatePeerNodeShape(const Node &node) {
       GE_CHECK_NOTNULL(peer_op_desc);
       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 when ShapeInferenceEngine %s.", 
-            peer_op_desc->GetName().c_str(), __FUNCTION__);
+        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__);    
         continue;
@@ -233,8 +232,8 @@ Status ShapeInferenceEngine::CanonicalizeShape(GeTensorDesc &tensor_desc,
   if (tensor_shape.IsUnknownShape()) {
     if (!fallback_with_range) {
       GELOGE(INTERNAL_ERROR, 
-          "[Is][UnknownShape] Output shape is still unknown after shape inference. "
-          "shape = [%s] when ShapeInferenceEngine %s.", tensor_shape.ToString().c_str(), __FUNCTION__);
+          "[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__);    
       return INTERNAL_ERROR;
@@ -244,8 +243,8 @@ 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)" 
-          " when ShapeInferenceEngine %s.", shape_range.size(), shape.size(), __FUNCTION__);
+      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__);    
       return INTERNAL_ERROR;
@@ -271,8 +270,8 @@ 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 when ShapeInferenceEngine %s.", 
-        TypeUtils::DataTypeToSerialString(data_type).c_str(), __FUNCTION__);
+    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__);    
     return INTERNAL_ERROR;
@@ -287,7 +286,7 @@ Status ShapeInferenceEngine::CalcTensorSize(DataType data_type,
   }
 
   GE_CHK_STATUS_RET(CheckInt64AddOverflow(tensor_size, kAlignment - 1),
-      "[Check][Overflow]Tensor size is too large: %ld, shape = [%s]",
+      "[Check][Overflow]Tensor size is too large: %ld, shape = [%s] Shape size will overflow when add align.",
       tensor_size, GeShape(shape).ToString().c_str());
   tensor_size = (tensor_size + kAlignment - 1) / kAlignment * kAlignment;
   return SUCCESS;
@@ -301,14 +300,23 @@ Status ShapeInferenceEngine::CalcOutputTensorSizes(const NodeItem &node_item, bo
     const auto &shape = tensor_desc->MutableShape();
     // modify on copy
     auto dims = shape.GetDims();
-    GE_CHK_STATUS_RET(CanonicalizeShape(*tensor_desc, dims, fallback_with_range),
-        "[Canonicalize][Shape] failed for [%s], output %zu, when ShapeInferenceEngine %s.",
-        node_item.NodeName().c_str(), output_index, __FUNCTION__);
-
+    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);
+      GELOGE(ge::FAILED, "[Canonicalize][Shape] failed for [%s], output %zu.",
+          node_item.NodeName().c_str(), output_index); 
+      return _status; 
+    }
     int64_t tensor_size;
-    GE_CHK_STATUS_RET(CalcTensorSize(tensor_desc->GetDataType(), dims, tensor_size),
-        "[Calc][TensorSize] failed for [%s], output %zu when ShapeInferenceEngine %s.",
-        node_item.NodeName().c_str(), output_index, __FUNCTION__);
+    _status = CalcTensorSize(tensor_desc->GetDataType(), dims, tensor_size);
+    if(_status != 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; 
+    }    
     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/executor/worker/task_compile_engine.cc

@@ -32,8 +32,7 @@ Status TaskCompileEngine::Compile(NodeState &node_state, GraphExecutionContext *
   shared_ptr<NodeTask> kernel_task;
   auto ret = node_item.node_executor->CompileTask(*context->model, node_item.node, kernel_task);
   RECORD_COMPILE_EVENT(context, node_state.GetName().c_str(), "[Compile] End");
-  GE_CHK_STATUS_RET(ret, "[Compile][Task] failed for node: %s, when TaskCompileEngine %s.", 
-      node_item.NodeName().c_str(), __FUNCTION__);
+  GE_CHK_STATUS_RET(ret, "[Compile][Task] failed for node: %s.", node_item.NodeName().c_str());
   node_state.SetKernelTask(kernel_task);
   GELOGI("Compiling node %s successfully", node_state.GetName().c_str());
   return SUCCESS;