diff --git a/mindspore/ccsrc/device/ascend/kernel_select_ascend.cc b/mindspore/ccsrc/device/ascend/kernel_select_ascend.cc
index a314668c950a458de7f0cb68df3642ac21af7ba3..704763404d8ca3ea78736207a41fbf7486c86a6e 100644
--- a/mindspore/ccsrc/device/ascend/kernel_select_ascend.cc
+++ b/mindspore/ccsrc/device/ascend/kernel_select_ascend.cc
@@ -503,6 +503,7 @@ KernelSelectStatus SetMatchedKernelInfo(const CNodePtr &kernel_node,
 
 KernelSelectStatus SelectKernelInfo(const CNodePtr &kernel_node) {
   std::vector<std::shared_ptr<kernel::KernelBuildInfo>> kernel_info_list;
+  std::vector<std::shared_ptr<kernel::KernelBuildInfo>> aicpu_kernel_info_list;
   MS_EXCEPTION_IF_NULL(kernel_node);
   kernel::KernelQuery(kernel_node, &kernel_info_list);
   auto select_status = SetMatchedKernelInfo(kernel_node, kernel_info_list);
@@ -510,7 +511,7 @@ KernelSelectStatus SelectKernelInfo(const CNodePtr &kernel_node) {
   if (select_status == kNoMatched) {
     MS_LOG(WARNING) << "The node [" << kernel_node->DebugString()
                     << "] cannot find valid TBE kernel info, try to get aicpu kernel info";
-    kernel::AICPUQuery(kernel_node, &kernel_info_list);
+    kernel::AICPUQuery(kernel_node, &aicpu_kernel_info_list);
     select_status = SetMatchedKernelInfo(kernel_node, kernel_info_list);
     AnfAlgo::SetNodeAttr(kAttrIsAICPUKernel, MakeValue(true), kernel_node);
   }
@@ -518,6 +519,15 @@ KernelSelectStatus SelectKernelInfo(const CNodePtr &kernel_node) {
   if (select_status == kNoMatched) {
     std::ostringstream buffer;
     PrintInputAndOutputInferType(buffer, kernel_node);
+    MS_LOG(WARNING) << "=========================kernel info list=====================================";
+    for (size_t index = 0; index < kernel_info_list.size(); ++index) {
+      MS_LOG(WARNING) << "kernel [" << index << "] :" << kernel_info_list[index]->ToString();
+    }
+    for (size_t index = 0; index < aicpu_kernel_info_list.size(); ++index) {
+      MS_LOG(WARNING) << "kernel [" << (kernel_info_list.size() + index)
+                      << "] :" << aicpu_kernel_info_list[index]->ToString();
+    }
+    MS_LOG(WARNING) << "=========================       end       ====================================";
     MS_EXCEPTION(TypeError) << "The node [" << kernel_node->DebugString()
                             << "] cannot find valid kernel info, not supported the type " << buffer.str();
   }
diff --git a/mindspore/ccsrc/kernel/kernel_build_info.cc b/mindspore/ccsrc/kernel/kernel_build_info.cc
index 9c0272dd7aef0e6218a8169187bd97e12d6e5a45..ce7164a0d167ced50fd56d047562b7b1ad92090c 100644
--- a/mindspore/ccsrc/kernel/kernel_build_info.cc
+++ b/mindspore/ccsrc/kernel/kernel_build_info.cc
@@ -110,9 +110,9 @@ bool KernelBuildInfo::operator==(const KernelBuildInfo &other) const {
   return !(inputs_device_type_ != other.inputs_device_type_ || outputs_device_type_ != other.outputs_device_type_);
 }
 
-bool KernelBuildInfo::IsInputDefaultPadding() const { return output_reshape_type_.empty(); }
+bool KernelBuildInfo::IsInputDefaultPadding() const { return input_reshape_type_.empty(); }
 
-bool KernelBuildInfo::IsOutputDefaultPadding() const { return input_reshape_type_.empty(); }
+bool KernelBuildInfo::IsOutputDefaultPadding() const { return output_reshape_type_.empty(); }
 
 void KernelBuildInfo::KernelBuildInfoBuilder::SetKernelType(const KernelType &kernel_type) {
   MS_EXCEPTION_IF_NULL(kernel_build_info_);
diff --git a/mindspore/ccsrc/kernel/kernel_query.cc b/mindspore/ccsrc/kernel/kernel_query.cc
index 6afd2bef6844488f1603c5125b14f56c1697257d..f8523e94e8d0e70414581720425389814b566700 100755
--- a/mindspore/ccsrc/kernel/kernel_query.cc
+++ b/mindspore/ccsrc/kernel/kernel_query.cc
@@ -56,6 +56,11 @@ void KernelQuery(const CNodePtr &kernel_node, std::vector<std::shared_ptr<kernel
   TbeMetadataInfo(kernel_node, kernel_info_list);
   if (kernel_info_list->empty()) {
     AicpuMetadataInfo(kernel_node, kernel_info_list);
+    if (!kernel_info_list->empty()) {
+      MS_LOG(INFO) << "Warning The node [" << kernel_node->DebugString()
+                   << "] cannot find valid TBE kernel info, try to get aicpu kernel info";
+      AnfAlgo::SetNodeAttr(kAttrIsAICPUKernel, MakeValue(true), kernel_node);
+    }
   }
 
   if (kernel_info_list->empty()) {
diff --git a/mindspore/ccsrc/pre_activate/ascend/ascend_helper.cc b/mindspore/ccsrc/pre_activate/ascend/ascend_helper.cc
index 05d36fd4f22e32b9ccddfad7537dde2f3c7ce12b..f95882994e740e36e5a57ecf830bfa54e30aa577 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ascend_helper.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ascend_helper.cc
@@ -31,54 +31,6 @@ namespace mindspore {
 namespace opt {
 using KernelBuildInfoBuilder = kernel::KernelBuildInfo::KernelBuildInfoBuilder;
 namespace {
-kernel::KernelBuildInfoPtr RefreshKernelBuildInfo(const std::string &input_format, const std::string &output_format,
-                                                  const AnfNodePtr &node, const TypeId device_type,
-                                                  const kernel::KernelBuildInfo &ori_build_info) {
-  KernelBuildInfoBuilder builder;
-  builder.SetInputsFormat({input_format});
-  builder.SetOutputsFormat({output_format});
-  builder.SetInputsDeviceType({device_type});
-  builder.SetOutputsDeviceType({device_type});
-  builder.SetKernelType(ori_build_info.kernel_type());
-  builder.SetFusionType(ori_build_info.fusion_type());
-  builder.SetProcessor(ori_build_info.processor());
-  return builder.Build();
-}
-
-CNodePtr NewTransOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr &input, const KernelSelectPtr &kernel_select,
-                        const bool need_padding, const std::string &op_name) {
-  MS_EXCEPTION_IF_NULL(func_graph);
-  MS_EXCEPTION_IF_NULL(input);
-  std::vector<AnfNodePtr> trans_inputs;
-  auto prim = std::make_shared<Primitive>(op_name);
-  trans_inputs.push_back(NewValueNode(prim));
-  trans_inputs.push_back(input);
-  CNodePtr trans_node = func_graph->NewCNode(trans_inputs);
-  MS_EXCEPTION_IF_NULL(trans_node);
-  std::vector<kernel::Axis> padding_axis;
-  padding_axis = AnfAlgo::GetOutputReshapeType(input, 0);
-  if (need_padding) {
-    // if need padding we should set the transdata node's shape to the padding shape
-    AnfAlgo::SetOutputInferTypeAndShape({AnfAlgo::GetOutputInferDataType(input, 0)},
-                                        {trans::PaddingShapeTo4d(AnfAlgo::GetOutputInferShape(input, 0), padding_axis)},
-                                        trans_node.get());
-  } else {
-    AnfAlgo::SetOutputInferTypeAndShape({AnfAlgo::GetOutputInferDataType(input, 0)},
-                                        {AnfAlgo::GetOutputInferShape(input, 0)}, trans_node.get());
-  }
-  // special handle for ut
-  if (trans_node->kernel_info() == nullptr) {
-    auto kernel_info = std::make_shared<device::KernelInfo>();
-    trans_node->set_kernel_info(kernel_info);
-  }
-  MS_EXCEPTION_IF_NULL(kernel_select);
-  kernel_select->SelectKernel(trans_node);
-  AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), trans_node);
-  MS_EXCEPTION_IF_NULL(trans_node);
-  trans_node->set_scope(input->scope());
-  return trans_node;
-}
-
 AnfNodePtr CreateReshapeNode(const FuncGraphPtr &func_graph, const AnfNodePtr &input_node,
                              const KernelSelectPtr &kernel_select, const std::vector<size_t> &dst_shape) {
   std::vector<AnfNodePtr> trans_inputs;
@@ -94,6 +46,58 @@ AnfNodePtr CreateReshapeNode(const FuncGraphPtr &func_graph, const AnfNodePtr &i
   return reshape;
 }
 
+AnfNodePtr AddTransOpNodeToGraph(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
+                                 const KernelSelectPtr &kernel_select, size_t insert_index, bool is_insert_input) {
+  AnfNodePtr trans_node = nullptr;
+  AnfNodePtr input_node = node;
+  CNodePtr trans_data = nullptr;
+  std::string input_format = is_insert_input ? kOpFormat_DEFAULT : AnfAlgo::GetOutputFormat(node, 0);
+  std::string dst_format = is_insert_input ? AnfAlgo::GetInputFormat(node, 0) : kOpFormat_DEFAULT;
+  TypeId dtype = AnfAlgo::GetOutputDeviceDataType(node, 0);
+  std::vector<kernel::Axis> padding_axis = AnfAlgo::GetOutputReshapeType(node, 0);
+  MS_EXCEPTION_IF_NULL(node);
+  // if insert transdata for input we need to change the input
+  if (is_insert_input) {
+    if (!node->isa<CNode>()) {
+      MS_LOG(EXCEPTION) << "cannot insert a transdata node to a node's input which the node is not a cnode";
+    }
+    auto cnode = node->cast<CNodePtr>();
+    dtype = AnfAlgo::GetInputDeviceDataType(cnode, insert_index);
+    dst_format = AnfAlgo::GetInputFormat(cnode, insert_index);
+    input_node = AnfAlgo::GetInputNode(cnode, insert_index);
+    padding_axis = AnfAlgo::GetInputReshapeType(node, 0);
+  }
+  bool need_padding = false;
+  if (is_insert_input) {
+    need_padding = (trans::IsNeedPadding(dst_format, AnfAlgo::GetOutputInferShape(input_node, 0).size()));
+  } else {
+    need_padding = (trans::IsNeedPadding(input_format, AnfAlgo::GetOutputInferShape(input_node, 0).size()));
+  }
+  if (!need_padding) {
+    // don't need padding insert transdata only
+    trans_data = NewTransOpNode(func_graph, input_node, kernel_select, need_padding, prim::KPrimTransData->name());
+    trans_node = trans_data;
+  } else if (is_insert_input) {
+    // if need padding & is input need insert a transdata
+    // reshape[padding shape] -> transdata[padding shape] -> node
+    auto padding_shape =
+      trans::PaddingShapeTo4d(AnfAlgo::GetOutputInferShape(input_node, 0), AnfAlgo::GetInputReshapeType(node, 0));
+    auto reshape_node = CreateReshapeNode(func_graph, input_node, kernel_select, padding_shape);
+    trans_data = NewTransOpNode(func_graph, reshape_node, kernel_select, need_padding, prim::KPrimTransData->name());
+    trans_node = trans_data;
+  } else {
+    // if need padding & is output need insert a transdata
+    // node -> transdata[padding shape] -> reshape[ori_shape]
+    trans_data = NewTransOpNode(func_graph, input_node, kernel_select, need_padding, prim::KPrimTransData->name());
+    auto reshape_node =
+      CreateReshapeNode(func_graph, trans_data, kernel_select, AnfAlgo::GetOutputInferShape(input_node, 0));
+    trans_node = reshape_node;
+  }
+  // refresh the transdata's format to ori format & dst format
+  RefreshKernelBuildInfo(input_format, dst_format, dtype, trans_data, padding_axis);
+  return trans_node;
+}
+
 AnfNodePtr GetTransInputNodePtr(const FuncGraphPtr &func_graph, const CNodePtr &node, size_t index,
                                 const KernelSelectPtr &kernel_select) {
   MS_EXCEPTION_IF_NULL(node);
@@ -111,13 +115,11 @@ AnfNodePtr GetTransInputNodePtr(const FuncGraphPtr &func_graph, const CNodePtr &
                       << "when inserting the transdata node " << node->DebugString();
   }
   std::vector<size_t> origin_shape = AnfAlgo::GetPrevNodeOutputInferShape(node, index);
-  std::string origin_format = kOpFormat_DEFAULT;
   std::string dest_format = AnfAlgo::GetInputFormat(node, index);
   if (kNeedTransFormatSet.find(dest_format) != kNeedTransFormatSet.end() && origin_shape.size() > 1) {
     MS_LOG(DEBUG) << node->DebugString() << "Insert transdata " << AnfAlgo::GetInputFormat(node, index)
                   << " To DefaultFormat , index: " << index;
-    return AddTransOpNodeToGraph(func_graph, node, kernel_select, index, origin_format, dest_format, kTransDataOpName,
-                                 true);
+    return AddTransOpNodeToGraph(func_graph, node, kernel_select, index, true);
   }
   return input_node;
 }
@@ -131,12 +133,9 @@ AnfNodePtr InsertTransOpForSingleOutput(const FuncGraphPtr &func_graph, const An
     MS_LOG(EXCEPTION) << "got the hw format " << output_format << "when insert the transdata node "
                       << node->DebugString();
   }
-  std::string origin_format = output_format;
-  std::string dest_format = kOpFormat_DEFAULT;
   if (kNeedTransFormatSet.find(output_format) != kNeedTransFormatSet.end() && origin_shape.size() > 1) {
     MS_LOG(DEBUG) << "Inserted Transdata " << output_format << " To default , index :0";
-    return AddTransOpNodeToGraph(func_graph, node, kernel_select, 0, origin_format, dest_format, kTransDataOpName,
-                                 false);
+    return AddTransOpNodeToGraph(func_graph, node, kernel_select, 0, false);
   }
   return node;
 }
@@ -155,10 +154,8 @@ AnfNodePtr InsertTransOpForMultipleOutput(const FuncGraphPtr &func_graph, const
     }
     auto tuple_getitem = CreatTupleGetItemNode(func_graph, node, output_idx);
     std::vector<size_t> origin_shape = AnfAlgo::GetOutputInferShape(node, output_idx);
-    std::string dest_format = kOpFormat_DEFAULT;
     if (kNeedTransFormatSet.find(output_format) != kNeedTransFormatSet.end() && origin_shape.size() > 1) {
-      make_tuple_inputs.emplace_back(AddTransOpNodeToGraph(func_graph, tuple_getitem, kernel_select, 0, output_format,
-                                                           dest_format, kTransDataOpName, false));
+      make_tuple_inputs.emplace_back(AddTransOpNodeToGraph(func_graph, tuple_getitem, kernel_select, 0, false));
     } else {
       // No need insert trans op.
       make_tuple_inputs.push_back(tuple_getitem);
@@ -168,62 +165,54 @@ AnfNodePtr InsertTransOpForMultipleOutput(const FuncGraphPtr &func_graph, const
   return make_tuple;
 }
 }  // namespace
-AnfNodePtr AddTransOpNodeToGraph(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
-                                 const KernelSelectPtr &kernel_select, size_t insert_index,
-                                 const std::string &origin_format, const std::string &dest_format,
-                                 const std::string &op_name, bool is_insert_input) {
-  AnfNodePtr trans_node = nullptr;
-  AnfNodePtr input_node = node;
-  AnfNodePtr trans_data = nullptr;
-  TypeId dtype = AnfAlgo::GetOutputDeviceDataType(node, 0);
-  MS_EXCEPTION_IF_NULL(node);
-  if (origin_format.empty() || dest_format.empty()) {
-    MS_LOG(EXCEPTION) << "trans op format is error, origin = " << origin_format << ", dest " << origin_format;
-  }
-  // if insert transdata for input we need to change the input
-  if (is_insert_input) {
-    if (!node->isa<CNode>()) {
-      MS_LOG(EXCEPTION) << "cannot insert a transdata node to a node's input which the node is not a cnode";
-    }
-    auto cnode = node->cast<CNodePtr>();
-    dtype = AnfAlgo::GetInputDeviceDataType(cnode, insert_index);
-    MS_EXCEPTION_IF_NULL(cnode);
-    input_node = AnfAlgo::GetInputNode(cnode, insert_index);
-  }
-  bool need_padding = false;
-  if (is_insert_input) {
-    need_padding = (trans::IsNeedPadding(dest_format, AnfAlgo::GetOutputInferShape(input_node, 0).size()) &&
-                    op_name == kTransDataOpName);
+void RefreshKernelBuildInfo(const std::string &input_format, const std::string &output_format, const TypeId device_type,
+                            const AnfNodePtr &trans_data, const std::vector<kernel::Axis> &reshape_type) {
+  MS_EXCEPTION_IF_NULL(trans_data);
+  MS_EXCEPTION_IF_NULL(trans_data->kernel_info());
+  auto ori_build_info = trans_data->kernel_info()->select_kernel_build_info();
+  KernelBuildInfoBuilder builder;
+  builder.SetInputsFormat({input_format});
+  builder.SetInputReshapeType({reshape_type});
+  builder.SetInputReshapeType({reshape_type});
+  builder.SetOutputsFormat({output_format});
+  builder.SetInputsDeviceType({device_type});
+  builder.SetOutputsDeviceType({device_type});
+  builder.SetKernelType(ori_build_info->kernel_type());
+  builder.SetFusionType(ori_build_info->fusion_type());
+  builder.SetProcessor(ori_build_info->processor());
+  AnfAlgo::SetSelectKernelBuildInfo(builder.Build(), trans_data.get());
+}
+
+CNodePtr NewTransOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr &input, const KernelSelectPtr &kernel_select,
+                        const bool need_padding, const std::string &op_name) {
+  MS_EXCEPTION_IF_NULL(func_graph);
+  MS_EXCEPTION_IF_NULL(input);
+  std::vector<AnfNodePtr> trans_inputs;
+  auto prim = std::make_shared<Primitive>(op_name);
+  trans_inputs.push_back(NewValueNode(prim));
+  trans_inputs.push_back(input);
+  CNodePtr trans_node = func_graph->NewCNode(trans_inputs);
+  MS_EXCEPTION_IF_NULL(trans_node);
+  auto padding_axis = AnfAlgo::GetOutputReshapeType(input, 0);
+  if (need_padding) {
+    // if need padding we should set the transdata node's shape to the padding shape
+    AnfAlgo::SetOutputInferTypeAndShape({AnfAlgo::GetOutputInferDataType(input, 0)},
+                                        {trans::PaddingShapeTo4d(AnfAlgo::GetOutputInferShape(input, 0), padding_axis)},
+                                        trans_node.get());
   } else {
-    need_padding = (trans::IsNeedPadding(origin_format, AnfAlgo::GetOutputInferShape(input_node, 0).size()) &&
-                    op_name == kTransDataOpName);
+    AnfAlgo::SetOutputInferTypeAndShape({AnfAlgo::GetOutputInferDataType(input, 0)},
+                                        {AnfAlgo::GetOutputInferShape(input, 0)}, trans_node.get());
   }
-  if (!need_padding) {
-    // don't need padding insert transdata only
-    trans_data = NewTransOpNode(func_graph, input_node, kernel_select, need_padding, op_name);
-    trans_node = trans_data;
-  } else if (is_insert_input) {
-    // if need padding & is input need insert a transdata
-    // reshape[padding shape] -> transdata[padding shape] -> node
-    auto padding_shape =
-      trans::PaddingShapeTo4d(AnfAlgo::GetOutputInferShape(input_node, 0), AnfAlgo::GetInputReshapeType(node, 0));
-    auto reshape_node = CreateReshapeNode(func_graph, input_node, kernel_select, padding_shape);
-    trans_data = NewTransOpNode(func_graph, reshape_node, kernel_select, need_padding, op_name);
-    trans_node = trans_data;
-  } else {
-    // if need padding & is output need insert a transdata
-    // node -> transdata[padding shape] -> reshape[ori_shape]
-    trans_data = NewTransOpNode(func_graph, input_node, kernel_select, need_padding, op_name);
-    auto reshape_node =
-      CreateReshapeNode(func_graph, trans_data, kernel_select, AnfAlgo::GetOutputInferShape(input_node, 0));
-    trans_node = reshape_node;
+  // special handle for ut
+  if (trans_node->kernel_info() == nullptr) {
+    auto kernel_info = std::make_shared<device::KernelInfo>();
+    trans_node->set_kernel_info(kernel_info);
   }
-  // refresh the transdata's format to ori format & dst format
-  MS_EXCEPTION_IF_NULL(trans_data);
-  MS_EXCEPTION_IF_NULL(trans_data->kernel_info());
-  auto trans_ori_build_info = trans_data->kernel_info()->select_kernel_build_info();
-  auto kernel_build_info = RefreshKernelBuildInfo(origin_format, dest_format, input_node, dtype, *trans_ori_build_info);
-  AnfAlgo::SetSelectKernelBuildInfo(kernel_build_info, trans_data.get());
+  MS_EXCEPTION_IF_NULL(kernel_select);
+  kernel_select->SelectKernel(trans_node);
+  AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), trans_node);
+  MS_EXCEPTION_IF_NULL(trans_node);
+  trans_node->set_scope(input->scope());
   return trans_node;
 }
 
diff --git a/mindspore/ccsrc/pre_activate/ascend/ascend_helper.h b/mindspore/ccsrc/pre_activate/ascend/ascend_helper.h
index a5463131b4709871bfe5c680957e58f07cf461bb..66e3f2ad330fb69d8be86426581afa50440ad96f 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ascend_helper.h
+++ b/mindspore/ccsrc/pre_activate/ascend/ascend_helper.h
@@ -58,11 +58,11 @@ class KernelQuery {
   }
 };
 using KernelQueryPtr = std::shared_ptr<KernelQuery>;
+void RefreshKernelBuildInfo(const std::string &input_format, const std::string &output_format, const TypeId device_type,
+                            const AnfNodePtr &trans_data, const std::vector<kernel::Axis> &reshape_type = {});
 
-AnfNodePtr AddTransOpNodeToGraph(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
-                                 const KernelSelectPtr &kernel_select, size_t insert_index,
-                                 const std::string &origin_format, const std::string &dest_format,
-                                 const std::string &op_name, bool is_insert_input);
+CNodePtr NewTransOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr &input, const KernelSelectPtr &kernel_select,
+                        const bool need_padding, const std::string &op_name);
 
 AnfNodePtr AddCastOpNodeToGraph(const FuncGraphPtr &func_graph, const AnfNodePtr &input, const std::string &format,
                                 const TypeId &input_type, const TypeId &output_type,
diff --git a/mindspore/ccsrc/pre_activate/ascend/format_type/deal_ref_trans_and_cast.cc b/mindspore/ccsrc/pre_activate/ascend/format_type/deal_ref_trans_and_cast.cc
index a9196c5c428659d2e4ccf7599e976da2dd4054b2..43857dddfd8a6bdfc9acb3ea93ba0b06ffbdde5d 100644
--- a/mindspore/ccsrc/pre_activate/ascend/format_type/deal_ref_trans_and_cast.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/format_type/deal_ref_trans_and_cast.cc
@@ -105,8 +105,8 @@ AnfNodePtr AddAdditionalToRefOutput(const FuncGraphPtr &func_graph, const CNodeP
   // insert trans
   if (origin_format != cur_format && cur_shape.size() > 1) {
     auto kernel_select = std::make_shared<KernelSelect>();
-    final_node = AddTransOpNodeToGraph(func_graph, final_node, kernel_select, 0, cur_format, origin_format,
-                                       kTransDataOpName, false);
+    final_node = NewTransOpNode(func_graph, final_node, kernel_select, false, prim::KPrimTransData->name());
+    RefreshKernelBuildInfo(cur_format, origin_format, origin_type, final_node);
     final_index = 0;
     MS_EXCEPTION_IF_NULL(final_node);
     MS_LOG(INFO) << "DealRefTransAndCast add trans op, op debug info is " << final_node->DebugString();
diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fission/transdata_split.cc b/mindspore/ccsrc/pre_activate/ascend/ir_fission/transdata_split.cc
index 2c77794b145a9f75f4a133e4876ae00b5a6b4227..035455db5e5803f3a3768d48c5e2da5132d700bb 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fission/transdata_split.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fission/transdata_split.cc
@@ -67,22 +67,30 @@ bool TransDataSplit::DoSplit(const FuncGraphPtr &func_graph, const AnfNodePtr &n
   // if output_format=default transdata need split transdata->transpose else transpose->transdata
   if (output_format == kOpFormat_DEFAULT || output_format == kOpFormat_NCHW) {
     // trans input_format to hwcn
-    new_transdata_node =
-      AddTransOpNodeToGraph(func_graph, node, kernel_select_, 0, input_format, kOpFormat_HWCN, kTransDataOpName, true);
+    new_transdata_node = NewTransOpNode(func_graph, AnfAlgo::GetInputNode(node->cast<CNodePtr>(), 0), kernel_select_,
+                                        false, prim::KPrimTransData->name());
+    RefreshKernelBuildInfo(input_format, kOpFormat_HWCN, AnfAlgo::GetOutputDeviceDataType(new_transdata_node, 0),
+                           new_transdata_node);
     // trans hwcn to default_format
-    new_transpose_node = AddTransOpNodeToGraph(func_graph, new_transdata_node, kernel_select_, 0, kOpFormat_HWCN,
-                                               output_format, prim::kPrimTranspose->name(), false);
+    new_transpose_node =
+      NewTransOpNode(func_graph, new_transdata_node, kernel_select_, false, prim::kPrimTranspose->name());
+    RefreshKernelBuildInfo(kOpFormat_HWCN, output_format, AnfAlgo::GetOutputDeviceDataType(new_transpose_node, 0),
+                           new_transpose_node);
     AnfAlgo::SetNodeAttr(kAttrPerm, MakeValue(std::vector<int>{3, 2, 0, 1}), new_transpose_node);
     new_replace_node = new_transpose_node;
   } else {
     // trans default to hwcn
-    new_transpose_node = AddTransOpNodeToGraph(func_graph, node, kernel_select_, 0, input_format, kOpFormat_HWCN,
-                                               prim::kPrimTranspose->name(), true);
+    new_transpose_node = NewTransOpNode(func_graph, AnfAlgo::GetInputNode(node->cast<CNodePtr>(), 0), kernel_select_,
+                                        false, prim::kPrimTranspose->name());
     AnfAlgo::SetNodeAttr(kAttrPerm, MakeValue(std::vector<int>{2, 3, 1, 0}), new_transpose_node);
+    RefreshKernelBuildInfo(input_format, kOpFormat_HWCN, AnfAlgo::GetOutputDeviceDataType(new_transpose_node, 0),
+                           new_transpose_node);
 
     // trans hwcn to output_format
-    new_transdata_node = AddTransOpNodeToGraph(func_graph, new_transpose_node, kernel_select_, 0, kOpFormat_HWCN,
-                                               output_format, kTransDataOpName, false);
+    new_transdata_node =
+      NewTransOpNode(func_graph, new_transpose_node, kernel_select_, false, prim::KPrimTransData->name());
+    RefreshKernelBuildInfo(kOpFormat_HWCN, output_format, AnfAlgo::GetOutputDeviceDataType(new_transdata_node, 0),
+                           new_transpose_node);
     new_replace_node = new_transdata_node;
   }
   FuncGraphManagerPtr manager = func_graph->manager();
diff --git a/mindspore/ccsrc/session/kernel_graph.cc b/mindspore/ccsrc/session/kernel_graph.cc
index c6b84d57ad6fd96d277d2a942f65abf865b73265..6e2f4a8a2ed34ae99bea34e95b927be87cdb57c0 100644
--- a/mindspore/ccsrc/session/kernel_graph.cc
+++ b/mindspore/ccsrc/session/kernel_graph.cc
@@ -196,10 +196,10 @@ CNodePtr KernelGraph::NewCNode(const std::vector<AnfNodePtr> &inputs) {
   }
   if (inputs.size() == 1 || !feature_map_input_indexs.empty()) {
     kernel_info->SetFeatureMapFlag(true);
-    AnfAlgo::SetNodeAttr(kIsFeatureMapOutput, MakeValue(true), cnode);
+  }
+  if (AnfAlgo::IsRealCNodeKernel(cnode)) {
+    AnfAlgo::SetNodeAttr(kIsFeatureMapOutput, MakeValue(kernel_info->is_feature_map()), cnode);
     AnfAlgo::SetNodeAttr(kIsFeatureMapInputList, MakeValue(feature_map_input_indexs), cnode);
-  } else {
-    AnfAlgo::SetNodeAttr(kIsFeatureMapOutput, MakeValue(false), cnode);
   }
   cnode->set_kernel_info(kernel_info);
   AnfAlgo::SetGraphId(graph_id_, cnode.get());
diff --git a/mindspore/ccsrc/utils/utils.h b/mindspore/ccsrc/utils/utils.h
index 8eacd10be0e591b3c9c2c13c1de21641009dc2bf..e829a49d793ceff19827279031fe78a779a9538d 100644
--- a/mindspore/ccsrc/utils/utils.h
+++ b/mindspore/ccsrc/utils/utils.h
@@ -151,7 +151,7 @@ constexpr auto kSquareSumAllOpName = "SquareSumAll";
 
 // attr key name
 constexpr auto kAttrInputNames = "input_names";
-constexpr auto kAttrIsAICPUKernel = "is_ai_cpu_kernel";
+constexpr auto kAttrIsAICPUKernel = "is_AICPU_kernel";
 constexpr auto kIsBackendCast = "is_backed_cast";
 constexpr auto kAttrOutputNames = "output_names";
 constexpr auto kAttrVisited = "visited";