diff --git a/mindspore/ccsrc/pipeline/pipeline_ge.cc b/mindspore/ccsrc/pipeline/pipeline_ge.cc
index 2f68935591..0b37e8f930 100644
--- a/mindspore/ccsrc/pipeline/pipeline_ge.cc
+++ b/mindspore/ccsrc/pipeline/pipeline_ge.cc
@@ -391,7 +391,12 @@ std::shared_ptr<py::object> DoExecGraph(const FuncGraphPtr& graph, const std::ve
                                         const std::string& phase) {
   std::vector<GeTensorPtr> ge_tensors = TransformUtil::ConvertInputTensors(inputs, kOpFormat_NCHW);
   if (ge_tensors.size() != inputs.size()) {
+<<<<<<< HEAD
     MS_LOG(EXCEPTION) << "Convert me args to ge tensor error.";
+=======
+    MS_LOG(ERROR) << "args convert to ge tensor error";
+    return nullptr;
+>>>>>>> remove ge depend in cpu
   }
 
   std::vector<GeTensorPtr> ge_outputs;
@@ -402,7 +407,12 @@ std::shared_ptr<py::object> DoExecGraph(const FuncGraphPtr& graph, const std::ve
   auto graph_runner = DfGraphManager::GetInstance().GetGraphRunner();
 
   if (graph_runner == nullptr) {
+<<<<<<< HEAD
     MS_LOG(EXCEPTION) << "Can not found GraphRunner.";
+=======
+    MS_LOG(ERROR) << "Can not found GraphRunner";
+    return nullptr;
+>>>>>>> remove ge depend in cpu
   }
 
   {
@@ -419,7 +429,11 @@ std::shared_ptr<py::object> DoExecGraph(const FuncGraphPtr& graph, const std::ve
 
   std::vector<MeTensorPtr> me_outputs = TransformUtil::ConvertGeTensors(ge_outputs);
   if (me_outputs.size() != ge_outputs.size()) {
+<<<<<<< HEAD
     MS_LOG(WARNING) << "Convert output Ge tensor to Me tensor failed";
+=======
+    MS_LOG(ERROR) << "Convert output Ge tensor to Me tensor failed";
+>>>>>>> remove ge depend in cpu
   }
 
   py::tuple outputs(me_outputs.size());
@@ -429,11 +443,28 @@ std::shared_ptr<py::object> DoExecGraph(const FuncGraphPtr& graph, const std::ve
 
   std::shared_ptr<py::object> ret = nullptr;
 
+<<<<<<< HEAD
   AnfNodePtr output_node = graph->get_return()->input(1);
   MS_EXCEPTION_IF_NULL(output_node);
   size_t count = 0;
   py::object oj = StructureOutput(output_node, outputs, &count);
   ret = std::make_shared<py::object>(oj);
+=======
+#ifdef ENABLE_GE
+  AnfNodePtr root = graph->get_return();
+  MS_EXCEPTION_IF_NULL(root);
+  AbstractBasePtr output = root->abstract();
+  size_t count = 0;
+  py::object oj = StructureOutput(output, outputs, &count);
+  ret = std::make_shared<py::object>(oj);
+#else
+  if (outputs.size() == 1) {
+    ret = std::make_shared<py::object>(outputs[0]);
+  } else {
+    ret = std::make_shared<py::object>(outputs);
+  }
+#endif
+>>>>>>> remove ge depend in cpu
 
   return ret;
 }
@@ -444,7 +475,11 @@ void ProcessGeArg(const std::map<std::string, ExecutorInfoPtr>& info, const py::
   std::size_t size = args.size();
 
   if (info.count(phase) == 0) {
+<<<<<<< HEAD
     MS_LOG(EXCEPTION) << "No phase in executor:" << GetPhasePrefix(phase);
+=======
+    MS_LOG(EXCEPTION) << "no phase in executor:" << GetPhasePrefix(phase);
+>>>>>>> remove ge depend in cpu
   }
 
   auto arg_size = info.at(phase)->arg_list_size;
@@ -459,12 +494,20 @@ void ProcessGeArg(const std::map<std::string, ExecutorInfoPtr>& info, const py::
       ValuePtr converted = nullptr;
       bool succ = parse::ConvertData(args[i], &converted);
       if (!succ) {
+<<<<<<< HEAD
         MS_LOG(EXCEPTION) << "Args convert error";
+=======
+        MS_LOG(EXCEPTION) << "args convert error";
+>>>>>>> remove ge depend in cpu
       }
       if (converted->isa<tensor::Tensor>()) {
         (*inputs).push_back(converted->cast<tensor::TensorPtr>());
       } else {
+<<<<<<< HEAD
         MS_LOG(EXCEPTION) << "Args " << converted->ToString() << " is not tensor";
+=======
+        MS_LOG(EXCEPTION) << "args, " << converted->ToString() << " is not tensor";
+>>>>>>> remove ge depend in cpu
       }
     }
   }
@@ -481,12 +524,20 @@ py::object ExecDFGraph(const std::map<std::string, ExecutorInfoPtr>& info, const
   }
 
   if (info.count(phase) == 0) {
+<<<<<<< HEAD
     MS_LOG(EXCEPTION) << "There is no phase:" << phase;
+=======
+    MS_LOG(EXCEPTION) << "has no phase:" << phase;
+>>>>>>> remove ge depend in cpu
   }
 
   FuncGraphPtr anf_graph = info.at(phase)->func_graph;
 
+<<<<<<< HEAD
 #ifdef ENABLE_INFER
+=======
+#if (!defined ENABLE_GE) || (defined ENABLE_INFER)
+>>>>>>> remove ge depend in cpu
   // Now don't use the graph because the exec ge function don't take effect
   MS_EXCEPTION_IF_NULL(info.at(phase)->func_graph);
   if (ENABLE_TRAIN != info.at(phase)->func_graph->flags()["training"]) {
@@ -511,7 +562,11 @@ py::object ExecDFGraph(const std::map<std::string, ExecutorInfoPtr>& info, const
   if (ret != nullptr) {
     return *ret;
   } else {
+<<<<<<< HEAD
     MS_LOG(EXCEPTION) << "Exec graph failed";
+=======
+    MS_LOG(EXCEPTION) << "exec graph failed";
+>>>>>>> remove ge depend in cpu
   }
 }
 void ExportDFGraph(const std::string& file_name, const std::string& phase) {
diff --git a/mindspore/ccsrc/utils/callbacks.h b/mindspore/ccsrc/utils/callbacks.h
index a1e4e75d5b..6f099ef4ca 100644
--- a/mindspore/ccsrc/utils/callbacks.h
+++ b/mindspore/ccsrc/utils/callbacks.h
@@ -40,7 +40,7 @@ const int kCallbackOk = 0;
 const int kCallbackFalied = 1;
 
 bool GetParameterShape(const FuncGraphPtr& anf_graph, const std::string& param_name,
-                       const std::shared_ptr<std::vector<int>>& shape);
+                       const std::shared_ptr<std::vector<int>>& shape)
 uint32_t SummarySaveCallback(uint32_t, const std::map<std::string, TensorPtr>&);
 
 }  // namespace callbacks