diff --git a/mindspore/ccsrc/backend/session/kernel_graph.cc b/mindspore/ccsrc/backend/session/kernel_graph.cc
index 528db5b76d..6b49b4b878 100644
--- a/mindspore/ccsrc/backend/session/kernel_graph.cc
+++ b/mindspore/ccsrc/backend/session/kernel_graph.cc
@@ -961,18 +961,40 @@ void KernelGraph::PrintGraphExecuteOrder() const {
   }
 }
 
-void KernelGraph::AddInternalOutput(const AnfNodePtr &front_node, const AnfNodePtr &node) {
+void KernelGraph::AddInternalOutput(const AnfNodePtr &front_node, const AnfNodePtr &node, int output_idx,
+                                    bool unique_target) {
   if (front_node == nullptr || node == nullptr) {
     MS_LOG(INFO) << "Front node or node is nullptr";
     return;
   }
   MS_LOG(INFO) << "Add internal node " << node->DebugString() << " with front node " << front_node->DebugString();
   front_to_internal_outputs_map_[front_node] = node;
-  int output_idx = 0;
   if (AnfAlgo::CheckPrimitiveType(front_node, prim::kPrimTupleGetItem)) {
     output_idx = AnfAlgo::GetTupleGetItemOutIndex(front_node->cast<CNodePtr>());
   }
-  internal_outputs_to_front_map_[node][output_idx] = front_node;
+  internal_outputs_to_front_map_[node][output_idx] = std::pair<AnfNodePtr, bool>(front_node, unique_target);
+}
+
+void KernelGraph::AddInternalOutputTensor(const AnfNodePtr &node, int output_idx, const tensor::TensorPtr &tensor) {
+  if (node == nullptr) {
+    return;
+  }
+  internal_outputs_tensor_map_[node][output_idx] = tensor;
+}
+
+tensor::TensorPtr KernelGraph::GetInternalOutputTensor(const AnfNodePtr &node, int output_idx) {
+  if (node == nullptr) {
+    return nullptr;
+  }
+  auto iter = internal_outputs_tensor_map_.find(node);
+  if (iter == internal_outputs_tensor_map_.end()) {
+    return nullptr;
+  }
+  auto idx_iter = iter->second.find(output_idx);
+  if (idx_iter == iter->second.end()) {
+    return nullptr;
+  }
+  return idx_iter->second;
 }
 
 void KernelGraph::ReplaceInternalOutput(const AnfNodePtr &node, const AnfNodePtr &new_node, int src_output_idx,
@@ -996,7 +1018,7 @@ void KernelGraph::ReplaceInternalOutput(const AnfNodePtr &node, const AnfNodePtr
   if (src_output_idx == -1) {
     internal_outputs_to_front_map_[new_node] = front_nodes;
     for (const auto &front_node_iter : front_nodes) {
-      front_to_internal_outputs_map_[front_node_iter.second] = new_node;
+      front_to_internal_outputs_map_[front_node_iter.second.first] = new_node;
     }
     internal_outputs_to_front_map_.erase(iter);
     return;
@@ -1008,9 +1030,9 @@ void KernelGraph::ReplaceInternalOutput(const AnfNodePtr &node, const AnfNodePtr
     MS_LOG(INFO) << "The output " << src_output_idx << " of node " << node->DebugString() << " is not an internal node";
     return;
   }
-  auto front_node = front_node_iter->second;
-  internal_outputs_to_front_map_[new_node][dst_output_idx] = front_node;
-  front_to_internal_outputs_map_[front_node] = new_node;
+  auto front_node_pair = front_node_iter->second;
+  internal_outputs_to_front_map_[new_node][dst_output_idx] = front_node_pair;
+  front_to_internal_outputs_map_[front_node_pair.first] = new_node;
   front_nodes.erase(index);
   if (front_nodes.empty()) {
     internal_outputs_to_front_map_.erase(iter);
@@ -1027,16 +1049,30 @@ AnfNodePtr KernelGraph::GetInternalOutputByFrontNode(const AnfNodePtr &front_nod
 
 bool KernelGraph::IsInternalOutput(const AnfNodePtr &node, int output_idx) const {
   auto front_nodes_iter = internal_outputs_to_front_map_.find(node);
-  if (front_nodes_iter != internal_outputs_to_front_map_.end()) {
-    if (output_idx == -1) {
-      return true;
-    }
-    auto &front_nodes = front_nodes_iter->second;
-    if (front_nodes.find(output_idx) != front_nodes.end()) {
-      return true;
-    }
+  if (front_nodes_iter == internal_outputs_to_front_map_.end()) {
+    return false;
   }
-  return false;
+  if (output_idx == -1) {
+    return true;
+  }
+  auto &front_nodes = front_nodes_iter->second;
+  if (front_nodes.find(output_idx) == front_nodes.end()) {
+    return false;
+  }
+  return true;
+}
+
+bool KernelGraph::IsUniqueTargetInternalOutput(const AnfNodePtr &node, int output_idx) const {
+  auto front_nodes_iter = internal_outputs_to_front_map_.find(node);
+  if (front_nodes_iter == internal_outputs_to_front_map_.end()) {
+    return false;
+  }
+  auto &front_nodes = front_nodes_iter->second;
+  auto idx_iter = front_nodes.find(output_idx);
+  if (idx_iter == front_nodes.end()) {
+    return false;
+  }
+  return idx_iter->second.second;
 }
 
 void KernelGraph::UpdateChildGraphOrder() {
diff --git a/mindspore/ccsrc/backend/session/kernel_graph.h b/mindspore/ccsrc/backend/session/kernel_graph.h
index 25cea907fb..047c21ea20 100644
--- a/mindspore/ccsrc/backend/session/kernel_graph.h
+++ b/mindspore/ccsrc/backend/session/kernel_graph.h
@@ -143,11 +143,16 @@ class KernelGraph : public FuncGraph {
   void PrintGraphExecuteOrder() const;
   const std::map<std::string, std::pair<AnfNodePtr, int>> &summary_nodes() const { return summary_nodes_; }
   void set_summary_nodes(const std::map<std::string, std::pair<AnfNodePtr, int>> &nodes) { summary_nodes_ = nodes; }
-  void AddInternalOutput(const AnfNodePtr &front_node, const AnfNodePtr &node);
+  void AddInternalOutput(const AnfNodePtr &front_node, const AnfNodePtr &node, int output_idx = 0,
+                         bool unique_target = false);
   void ReplaceInternalOutput(const AnfNodePtr &node, const AnfNodePtr &new_node, int src_output_idx = -1,
                              int dst_output_idx = -1);
   AnfNodePtr GetInternalOutputByFrontNode(const AnfNodePtr &front_node) const;
   bool IsInternalOutput(const AnfNodePtr &node, int output_idx = -1) const;
+  bool IsUniqueTargetInternalOutput(const AnfNodePtr &node, int output_idx) const;
+  void AddInternalOutputTensor(const AnfNodePtr &node, int output_idx, const tensor::TensorPtr &tensor);
+  tensor::TensorPtr GetInternalOutputTensor(const AnfNodePtr &node, int output_idx);
+
   uint32_t current_epoch() const { return current_epoch_; }
   void set_current_epoch(uint32_t epoch) { current_epoch_ = epoch; }
   void UpdateChildGraphOrder();
@@ -217,7 +222,8 @@ class KernelGraph : public FuncGraph {
   CNodePtr end_goto_;
   bool null_output_;
   std::unordered_map<AnfNodePtr, AnfNodePtr> front_to_internal_outputs_map_;
-  std::unordered_map<AnfNodePtr, std::unordered_map<int, AnfNodePtr>> internal_outputs_to_front_map_;
+  std::unordered_map<AnfNodePtr, std::unordered_map<int, std::pair<AnfNodePtr, bool>>> internal_outputs_to_front_map_;
+  std::unordered_map<AnfNodePtr, std::unordered_map<int, tensor::TensorPtr>> internal_outputs_tensor_map_;
   uint32_t current_epoch_;
 };
 }  // namespace session
diff --git a/mindspore/ccsrc/backend/session/session_basic.cc b/mindspore/ccsrc/backend/session/session_basic.cc
index 5a4f443388..21ff3180e3 100644
--- a/mindspore/ccsrc/backend/session/session_basic.cc
+++ b/mindspore/ccsrc/backend/session/session_basic.cc
@@ -58,51 +58,38 @@ ValuePtr GetParamDefaultValue(const AnfNodePtr &node) {
   return parameter->default_param();
 }
 
-BaseRef CreateOneTensor(const AnfNodePtr &node, size_t output_index, const KernelGraph &graph,
-                        const std::vector<tensor::TensorPtr> &input_tensors) {
+tensor::TensorPtr CreateOutputTensor(const AnfNodePtr &node, size_t output_index, const KernelGraphPtr &graph,
+                                     const DeviceAddressPtr &address) {
   MS_EXCEPTION_IF_NULL(node);
-  MS_LOG(INFO) << "Create tensor for output[" << node->DebugString() << "] index[" << output_index << "]";
-  // if node is a value node, no need sync addr from device to host
-  if (!AnfAlgo::OutputAddrExist(node, output_index)) {
-    if (node->isa<ValueNode>()) {
-      auto value_node = node->cast<ValueNodePtr>();
-      MS_EXCEPTION_IF_NULL(value_node);
-      return value_node->value();
-    }
-    if (node->isa<Parameter>()) {
-      for (size_t input_idx = 0; input_idx < graph.inputs().size(); input_idx++) {
-        if (input_idx >= input_tensors.size()) {
-          MS_LOG(EXCEPTION) << "Input idx:" << input_idx << "out of range:" << input_tensors.size();
-        }
-        if (graph.inputs()[input_idx] == node) {
-          return input_tensors[input_idx];
-        }
-      }
-      MS_LOG(EXCEPTION) << "Parameter : " << node->DebugString() << " has no output addr";
-    }
-  }
-  // if proccess reach here,it remarks item_with_index is a real node(Parameter,or executable CNode)
-  auto address = AnfAlgo::GetMutableOutputAddr(node, output_index);
-  MS_EXCEPTION_IF_NULL(address);
-  auto shape = AnfAlgo::GetOutputInferShape(node, output_index);
-  TypeId type_id = kNumberTypeFloat32;
-  type_id = AnfAlgo::GetOutputDeviceDataType(node, output_index);
+  MS_EXCEPTION_IF_NULL(graph);
+  TypeId type_id = AnfAlgo::GetOutputDeviceDataType(node, output_index);
   if (type_id == kTypeUnknown) {
     type_id = AnfAlgo::GetOutputInferDataType(node, output_index);
   }
+  tensor::TensorPtr tensor;
   std::vector<int> temp_shape;
-  if (graph.IsInternalOutput(node, output_index)) {
+  if (graph->IsUniqueTargetInternalOutput(node, output_index)) {
     temp_shape.emplace_back(1);
-    tensor::TensorPtr tensor = std::make_shared<tensor::Tensor>(type_id, temp_shape);
+    tensor = std::make_shared<tensor::Tensor>(type_id, temp_shape);
     tensor->set_device_address(address);
     tensor->set_dirty(false);
     return tensor;
   }
-  (void)std::copy(shape.begin(), shape.end(), std::back_inserter(temp_shape));
-  tensor::TensorPtr tensor = std::make_shared<tensor::Tensor>(type_id, temp_shape);
+
+  tensor = graph->GetInternalOutputTensor(node, output_index);
+  if (tensor == nullptr) {
+    auto shape = AnfAlgo::GetOutputInferShape(node, output_index);
+    (void)std::copy(shape.begin(), shape.end(), std::back_inserter(temp_shape));
+    tensor = std::make_shared<tensor::Tensor>(type_id, temp_shape);
+    bool is_internal_output = graph->IsInternalOutput(node, output_index);
+    if (is_internal_output) {
+      graph->AddInternalOutputTensor(node, output_index, tensor);
+    }
+  }
   // if in paynative mode,data only copyed to host when user want to print data
   auto ms_context = MsContext::GetInstance();
   MS_EXCEPTION_IF_NULL(ms_context);
+  MS_EXCEPTION_IF_NULL(address);
   if (ms_context->execution_mode() == kPynativeMode || ms_context->device_target() == kGPUDevice) {
     tensor->set_device_address(address);
     tensor->set_dirty(false);
@@ -114,7 +101,35 @@ BaseRef CreateOneTensor(const AnfNodePtr &node, size_t output_index, const Kerne
   return tensor;
 }
 
-BaseRef CreateTensorForOutput(const AnfNodePtr &anf, const KernelGraph &graph,
+BaseRef CreateOneTensor(const AnfNodePtr &node, size_t output_index, const KernelGraphPtr &graph,
+                        const std::vector<tensor::TensorPtr> &input_tensors) {
+  MS_EXCEPTION_IF_NULL(node);
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_LOG(INFO) << "Create tensor for output[" << node->DebugString() << "] index[" << output_index << "]";
+  // if node is a value node, no need sync addr from device to host
+  if (!AnfAlgo::OutputAddrExist(node, output_index)) {
+    if (node->isa<ValueNode>()) {
+      auto value_node = node->cast<ValueNodePtr>();
+      MS_EXCEPTION_IF_NULL(value_node);
+      return value_node->value();
+    }
+    if (node->isa<Parameter>()) {
+      for (size_t input_idx = 0; input_idx < graph->inputs().size(); input_idx++) {
+        if (input_idx >= input_tensors.size()) {
+          MS_LOG(EXCEPTION) << "Input idx:" << input_idx << "out of range:" << input_tensors.size();
+        }
+        if (graph->inputs()[input_idx] == node) {
+          return input_tensors[input_idx];
+        }
+      }
+      MS_LOG(EXCEPTION) << "Parameter : " << node->DebugString() << " has no output addr";
+    }
+  }
+  auto address = AnfAlgo::GetMutableOutputAddr(node, output_index);
+  return CreateOutputTensor(node, output_index, graph, address);
+}
+
+BaseRef CreateTensorForOutput(const AnfNodePtr &anf, const KernelGraphPtr &graph,
                               const std::vector<tensor::TensorPtr> &input_tensors) {
   MS_EXCEPTION_IF_NULL(anf);
   MS_LOG(INFO) << "Create tensor for output[" << anf->DebugString() << "]";
@@ -308,7 +323,7 @@ void SessionBasic::InitInternalOutputParameter(const AnfNodePtr &out_node, const
   auto real_kernel = AnfAlgo::VisitKernel(ref_node, output_idx);
   auto ref_real_node = real_kernel.first;
   auto ref_real_node_index = real_kernel.second;
-  if (ref_real_node->isa<CNode>() && node_graph->IsInternalOutput(ref_real_node, ref_real_node_index)) {
+  if (ref_real_node->isa<CNode>() && node_graph->IsUniqueTargetInternalOutput(ref_real_node, ref_real_node_index)) {
     auto kernel_info = ref_real_node->kernel_info();
     if (kernel_info == nullptr || !kernel_info->has_build_info()) {
       MS_LOG(INFO) << "No kernel info";
@@ -888,7 +903,7 @@ void SessionBasic::UpdateOutputs(const std::shared_ptr<KernelGraph> &kernel_grap
   for (auto &item : anf_outputs) {
     MS_EXCEPTION_IF_NULL(item);
     MS_LOG(INFO) << "Update output[" << item->DebugString() << "]";
-    outputs->emplace_back(CreateTensorForOutput(item, *kernel_graph, input_tensors));
+    outputs->emplace_back(CreateTensorForOutput(item, kernel_graph, input_tensors));
   }
 }
 
@@ -967,6 +982,71 @@ void SessionBasic::Summary(KernelGraph *graph) {
   summary_callback_(0, params_list);
 }
 
+namespace {
+bool CNodePrimIsValueNode(const AnfNodePtr &node) {
+  if (node == nullptr) {
+    return false;
+  }
+  auto cnode = node->cast<CNodePtr>();
+  if (cnode == nullptr) {
+    return false;
+  }
+  auto prim = cnode->input(kAnfPrimitiveIndex);
+  if (prim == nullptr || !prim->isa<ValueNode>()) {
+    return false;
+  }
+  return true;
+}
+
+void HandleInternalOutput(const AnfNodePtr &front_node, const AnfNodePtr &backend_node,
+                          const FuncGraphManagerPtr &front_func_graph_manager,
+                          const std::shared_ptr<KernelGraph> &backend_graph) {
+  auto node_users = front_func_graph_manager->node_users();
+  auto users = node_users[front_node];
+  auto front_real_kernel_pair = AnfAlgo::VisitKernel(front_node, 0);
+  auto backend_real_kernel_pair = AnfAlgo::VisitKernel(backend_node, 0);
+
+  auto front_real_kernel = front_real_kernel_pair.first;
+  std::string kernel_target = GetCNodeTarget(front_real_kernel);
+  bool internal_output = CNodePrimIsValueNode(front_real_kernel);
+  bool unique_target = true;
+  if (internal_output && opt::IsNopNode(front_real_kernel)) {
+    auto pre_node_pair = AnfAlgo::GetPrevNodeOutput(front_real_kernel, 0);
+    auto pre_node_target = GetCNodeTarget(pre_node_pair.first);
+    if (pre_node_target != kernel_target) {
+      unique_target = false;
+    }
+  }
+  if (internal_output) {
+    for (auto user : users) {
+      auto cnode = user.first->cast<CNodePtr>();
+      if (cnode == nullptr) {
+        internal_output = false;
+        break;
+      }
+      auto prim = cnode->input(kAnfPrimitiveIndex);
+      if (prim == nullptr || !prim->isa<ValueNode>()) {
+        internal_output = false;
+        break;
+      }
+      if (!AnfAlgo::IsRealKernel(user.first)) {
+        internal_output = false;
+        break;
+      }
+      if (kernel_target != GetCNodeTarget(user.first)) {
+        unique_target = false;
+      }
+    }
+  }
+  if (internal_output) {
+    MS_LOG(INFO) << "Internal output: " << front_node->DebugString() << "To "
+                 << backend_real_kernel_pair.first->DebugString();
+    backend_graph->AddInternalOutput(front_node, backend_real_kernel_pair.first, backend_real_kernel_pair.second,
+                                     unique_target);
+  }
+}
+}  // namespace
+
 CNodePtr SessionBasic::ConstructOutput(const AnfNodePtrList &outputs, const std::shared_ptr<KernelGraph> &graph) {
   MS_EXCEPTION_IF_NULL(graph);
   std::vector<AnfNodePtr> output_args;
@@ -982,9 +1062,7 @@ CNodePtr SessionBasic::ConstructOutput(const AnfNodePtrList &outputs, const std:
       if (context_ptr->execution_mode() == kPynativeMode) {
         return backend_anf;
       }
-      auto front_real_kernel_pair = AnfAlgo::VisitKernel(out, 0);
-      auto front_real_kernel = front_real_kernel_pair.first;
-      auto backend_real_kernel_pair = AnfAlgo::VisitKernel(backend_anf, 0);
+
       MS_EXCEPTION_IF_NULL(out);
       auto out_func_graph = out->func_graph();
       MS_EXCEPTION_IF_NULL(out_func_graph);
@@ -992,51 +1070,7 @@ CNodePtr SessionBasic::ConstructOutput(const AnfNodePtrList &outputs, const std:
       if (out_func_graph_manager == nullptr) {
         return backend_anf;
       }
-      auto node_users = out_func_graph_manager->node_users();
-      auto users = node_users[out];
-      bool internal_output = true;
-      std::string kernel_target = GetCNodeTarget(front_real_kernel);
-      if (front_real_kernel != nullptr && front_real_kernel->isa<CNode>()) {
-        auto front_cnode = front_real_kernel->cast<CNodePtr>();
-        if (front_cnode != nullptr) {
-          auto prim = front_cnode->input(kAnfPrimitiveIndex);
-          if (prim == nullptr || !prim->isa<ValueNode>()) {
-            internal_output = false;
-          }
-        } else {
-          internal_output = false;
-        }
-      }
-      if (internal_output && opt::IsNopNode(front_real_kernel)) {
-        auto pre_node_pair = AnfAlgo::GetPrevNodeOutput(front_real_kernel, 0);
-        auto pre_node_target = GetCNodeTarget(pre_node_pair.first);
-        if (pre_node_target != kernel_target) {
-          internal_output = false;
-        }
-      }
-      if (internal_output) {
-        for (auto user : users) {
-          auto cnode = user.first->cast<CNodePtr>();
-          if (cnode == nullptr) {
-            internal_output = false;
-            break;
-          }
-          auto prim = cnode->input(kAnfPrimitiveIndex);
-          if (prim == nullptr || !prim->isa<ValueNode>()) {
-            internal_output = false;
-            break;
-          }
-          if (!AnfAlgo::IsRealKernel(user.first) || kernel_target != GetCNodeTarget(user.first)) {
-            internal_output = false;
-            break;
-          }
-        }
-      }
-      if (internal_output) {
-        MS_LOG(INFO) << "Internal output: " << out->DebugString() << "To "
-                     << backend_real_kernel_pair.first->DebugString();
-        graph->AddInternalOutput(out, backend_real_kernel_pair.first);
-      }
+      HandleInternalOutput(out, backend_anf, out_func_graph_manager, graph);
       return backend_anf;
     }
     MS_LOG(EXCEPTION) << "Can't find the node in the equiv map!";
diff --git a/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.cc b/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.cc
index 5af81eadbf..6904c6a0be 100644
--- a/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.cc
+++ b/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.cc
@@ -20,7 +20,7 @@
 #include <numeric>
 #include <utility>
 #include <functional>
-#include <unordered_map>
+#include <map>
 #include <set>
 #include "backend/kernel_compiler/kernel.h"
 #include "runtime/device/cpu/cpu_device_address.h"
@@ -124,11 +124,10 @@ DeviceAddressPtr CPUKernelRuntime::CreateDeviceAddress(void *device_ptr, size_t
   return std::make_shared<CPUDeviceAddress>(device_ptr, device_size, format, type_id);
 }
 
-tensor::TensorPtr CPUKernelRuntime::CreatTensorForOutput(const CNodePtr &node, size_t index,
-                                                         std::set<DeviceAddressPtr> *bound_addresses,
+tensor::TensorPtr CPUKernelRuntime::CreatTensorForOutput(session::KernelGraph *kernel_graph, const CNodePtr &node,
+                                                         size_t index,
                                                          std::vector<tensor::TensorPtr> *need_sync_outputs) {
   MS_EXCEPTION_IF_NULL(node);
-  MS_EXCEPTION_IF_NULL(bound_addresses);
   MS_EXCEPTION_IF_NULL(need_sync_outputs);
   size_t output_size = AnfAlgo::GetOutputTensorNum(node);
   if (index >= output_size) {
@@ -136,14 +135,21 @@ tensor::TensorPtr CPUKernelRuntime::CreatTensorForOutput(const CNodePtr &node, s
   }
   auto address = AnfAlgo::GetMutableOutputAddr(node, index);
   MS_EXCEPTION_IF_NULL(address);
-  auto shape = AnfAlgo::GetOutputInferShape(node, index);
-  std::vector<int> temp_shape;
-  (void)temp_shape.insert(temp_shape.end(), shape.begin(), shape.end());
+
   TypeId infer_type_id = AnfAlgo::GetOutputInferDataType(node, index);
   TypeId device_type_id = AnfAlgo::GetOutputDeviceDataType(node, index);
-  tensor::TensorPtr tensor = std::make_shared<tensor::Tensor>(infer_type_id, temp_shape);
-  MS_EXCEPTION_IF_NULL(tensor);
-  if (bound_addresses->find(address) != bound_addresses->end()) {
+  tensor::TensorPtr tensor = kernel_graph->GetInternalOutputTensor(node, index);
+  if (tensor == nullptr) {
+    auto shape = AnfAlgo::GetOutputInferShape(node, index);
+    std::vector<int> temp_shape;
+    (void)temp_shape.insert(temp_shape.end(), shape.begin(), shape.end());
+    tensor = std::make_shared<tensor::Tensor>(infer_type_id, temp_shape);
+    bool is_internal_output = kernel_graph->IsInternalOutput(node, index);
+    if (is_internal_output) {
+      kernel_graph->AddInternalOutputTensor(node, index, tensor);
+    }
+  }
+  if (bound_addresses_.find(address) != bound_addresses_.end()) {
     tensor->set_device_address(address);
     need_sync_outputs->emplace_back(tensor);
   } else {
@@ -159,15 +165,14 @@ tensor::TensorPtr CPUKernelRuntime::CreatTensorForOutput(const CNodePtr &node, s
       address->ptr_ = tensor->data_c();
     }
     address->ref_count_ = INIT_NODE_REF;
-    (void)bound_addresses->insert(address);
+    (void)bound_addresses_.insert(address);
   }
   tensor->set_dirty(false);
   return tensor;
 }
 
-BaseRef CPUKernelRuntime::CreatTensorForOutput(const session::KernelWithIndex &kernel_with_index,
-                                               const std::unordered_map<AnfNode *, tensor::TensorPtr> &input_map,
-                                               std::set<DeviceAddressPtr> *bound_addresses,
+BaseRef CPUKernelRuntime::CreatTensorForOutput(session::KernelGraph *kernel_graph,
+                                               const session::KernelWithIndex &kernel_with_index,
                                                std::vector<tensor::TensorPtr> *need_sync_outputs) {
   auto &input_node = kernel_with_index.first;
   auto index = kernel_with_index.second;
@@ -179,15 +184,15 @@ BaseRef CPUKernelRuntime::CreatTensorForOutput(const session::KernelWithIndex &k
       VectorRef ret;
       for (size_t i = 1; i < node->inputs().size(); i++) {
         auto item_with_index = AnfAlgo::VisitKernelWithReturnType(node->input(i), 0);
-        auto out = CreatTensorForOutput(item_with_index, input_map, bound_addresses, need_sync_outputs);
+        auto out = CreatTensorForOutput(kernel_graph, item_with_index, need_sync_outputs);
         ret.push_back(out);
       }
       return ret;
     }
-    return CreatTensorForOutput(node, index, bound_addresses, need_sync_outputs);
+    return CreatTensorForOutput(kernel_graph, node, index, need_sync_outputs);
   } else if (input_node->isa<Parameter>()) {
-    auto iter = input_map.find(input_node.get());
-    if (iter != input_map.end()) {
+    auto iter = input_param_tensor_map_.find(input_node);
+    if (iter != input_param_tensor_map_.end()) {
       return iter->second;
     }
   } else if (input_node->isa<ValueNode>()) {
@@ -197,10 +202,8 @@ BaseRef CPUKernelRuntime::CreatTensorForOutput(const session::KernelWithIndex &k
   }
   return BaseRef();
 }
-
-void CPUKernelRuntime::BindInputOutput(const session::KernelGraph *kernel_graph,
-                                       const std::vector<tensor::TensorPtr> &inputs, VectorRef *outputs,
-                                       std::vector<tensor::TensorPtr> *need_sync_outputs) {
+void CPUKernelRuntime::BindInputOutput(session::KernelGraph *kernel_graph, const std::vector<tensor::TensorPtr> &inputs,
+                                       VectorRef *outputs, std::vector<tensor::TensorPtr> *need_sync_outputs) {
   MS_EXCEPTION_IF_NULL(kernel_graph);
   MS_EXCEPTION_IF_NULL(outputs);
   // bind input ptr
@@ -208,11 +211,11 @@ void CPUKernelRuntime::BindInputOutput(const session::KernelGraph *kernel_graph,
   if (input_nodes.size() != inputs.size()) {
     MS_LOG(EXCEPTION) << "Input size not equal to input node size!";
   }
-  std::unordered_map<AnfNode *, tensor::TensorPtr> input_map;
+  input_param_tensor_map_.clear();
   size_t input_idx = 0;
   for (auto &item : input_nodes) {
     MS_EXCEPTION_IF_NULL(item);
-    input_map[item.get()] = inputs[input_idx];
+    input_param_tensor_map_[item] = inputs[input_idx];
     if (item->isa<Parameter>()) {
       auto address = AnfAlgo::GetMutableOutputAddr(item, 0);
       auto tensor = inputs[input_idx];
@@ -222,7 +225,6 @@ void CPUKernelRuntime::BindInputOutput(const session::KernelGraph *kernel_graph,
       if (tensor_address != nullptr && tensor_address != address) {
         (void)tensor->data_sync();
       }
-
       if (tensor->data_type() == address->type_id_ || tensor->data_type() == kNumberTypeFloat32 ||
           tensor->data_type() == kNumberTypeInt32) {
         address->ptr_ = tensor->data_c();
@@ -243,11 +245,11 @@ void CPUKernelRuntime::BindInputOutput(const session::KernelGraph *kernel_graph,
     input_idx++;
   }
   // new output and bind ptr
-  std::set<DeviceAddressPtr> bound_addresses;
+  bound_addresses_.clear();
   auto output_nodes = kernel_graph->outputs();
   for (const auto &item : output_nodes) {
     auto item_with_index = AnfAlgo::VisitKernelWithReturnType(item, 0, true);
-    auto out = CreatTensorForOutput(item_with_index, input_map, &bound_addresses, need_sync_outputs);
+    auto out = CreatTensorForOutput(kernel_graph, item_with_index, need_sync_outputs);
     outputs->push_back(std::move(out));
   }
 }
diff --git a/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.h b/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.h
index a486ab1a8b..e391332f85 100644
--- a/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.h
+++ b/mindspore/ccsrc/runtime/device/cpu/cpu_kernel_runtime.h
@@ -19,7 +19,7 @@
 #include <memory>
 #include <vector>
 #include <string>
-#include <unordered_map>
+#include <map>
 #include <set>
 #include "runtime/device/kernel_runtime.h"
 #include "backend/session/kernel_graph.h"
@@ -38,7 +38,7 @@ class CPUKernelRuntime : public KernelRuntime {
   bool Init() override { return true; }
   bool Run(session::KernelGraph *graph, Debugger *debugger = nullptr) override;
   void AssignKernelAddress(session::KernelGraph *kernel_graph);
-  void BindInputOutput(const session::KernelGraph *kernel_graph, const std::vector<tensor::TensorPtr> &inputs,
+  void BindInputOutput(session::KernelGraph *kernel_graph, const std::vector<tensor::TensorPtr> &inputs,
                        VectorRef *outputs, std::vector<tensor::TensorPtr> *need_sync_outputs);
   void IncreaseSummaryRefCount(const session::NamedSummaryOutputs &summary_outputs);
   void DecreaseSummaryRefCount(const session::NamedSummaryOutputs &summary_outputs);
@@ -49,19 +49,18 @@ class CPUKernelRuntime : public KernelRuntime {
                                        TypeId type_id) override;
 
  private:
-  tensor::TensorPtr CreatTensorForOutput(const CNodePtr &node, size_t index,
-                                         std::set<DeviceAddressPtr> *bound_addresses,
+  tensor::TensorPtr CreatTensorForOutput(session::KernelGraph *kernel_graph, const CNodePtr &node, size_t index,
                                          std::vector<tensor::TensorPtr> *need_sync_outputs);
 
-  BaseRef CreatTensorForOutput(const session::KernelWithIndex &kernel_with_index,
-                               const std::unordered_map<AnfNode *, tensor::TensorPtr> &input_map,
-                               std::set<DeviceAddressPtr> *bound_addresses,
+  BaseRef CreatTensorForOutput(session::KernelGraph *kernel_graph, const session::KernelWithIndex &kernel_with_index,
                                std::vector<tensor::TensorPtr> *need_sync_outputs);
   void AssignValueNodeAddress(session::KernelGraph *kernel_graph);
   void AssignInputNodeAddress(const session::KernelGraph *kernel_graph);
   void AssignKernelOutputAddress(const session::KernelGraph *kernel_graph);
   void AddRuntimeAddress(DeviceAddress *address, std::vector<kernel::AddressPtr> *input_list);
   CPUResourceManager resource_manager_;
+  std::set<DeviceAddressPtr> bound_addresses_;
+  std::map<AnfNodePtr, tensor::TensorPtr> input_param_tensor_map_;
 };
 }  // namespace cpu
 }  // namespace device