diff --git a/cmake/options.cmake b/cmake/options.cmake
index 1b6cc34963f..391e64aa70c 100644
--- a/cmake/options.cmake
+++ b/cmake/options.cmake
@@ -76,8 +76,6 @@ if(ENABLE_ASAN)
     endif()
 endif()
 
-add_compile_definitions(ENABLE_TUPLE_UNFOLD)
-
 if(DEBUG_MODE)
     set(CMAKE_BUILD_TYPE "Debug")
     add_compile_definitions(MEM_REUSE_DEBUG)
diff --git a/mindspore/ccsrc/backend/common/optimizer/common_backend_optimization.cc b/mindspore/ccsrc/backend/common/optimizer/common_backend_optimization.cc
index f9e6a82fc80..dea720c42e4 100644
--- a/mindspore/ccsrc/backend/common/optimizer/common_backend_optimization.cc
+++ b/mindspore/ccsrc/backend/common/optimizer/common_backend_optimization.cc
@@ -55,14 +55,9 @@ PassManagerPtr GetBackendCommonOptimizationPassManagerPtr(const FuncGraphPtr &gr
   common_pm->AddPass(std::make_shared<ConvertTupleOutputToMaketuple>());
   common_pm->AddPass(std::make_shared<ConvertUnusedTupleParaToMakeTuple>());
   common_pm->AddPass(std::make_shared<ConvertConstScalarToTensor>());
-#ifdef ENABLE_TUPLE_UNFOLD
-  MS_LOG(INFO) << "Enable tuple unfold.";
   if (graph->has_flag(kAttrMutableKernel) || graph->has_flag(kFlagEnableRunGraphBySingleOp)) {
     common_pm->AddPass(std::make_shared<ConvertTupleInputToDynamicInput>());
   }
-#else
-  common_pm->AddPass(std::make_shared<ConvertTupleInputToDynamicInput>());
-#endif
   common_pm->AddPass(std::make_shared<FlattenConcatFission>());
   common_pm->AddPass(std::make_shared<AddDropoutAttrs>());
   return common_pm;
diff --git a/mindspore/ccsrc/backend/common/pass/convert_tuple_output_to_maketuple.cc b/mindspore/ccsrc/backend/common/pass/convert_tuple_output_to_maketuple.cc
index d8d7641794c..77c367ce942 100644
--- a/mindspore/ccsrc/backend/common/pass/convert_tuple_output_to_maketuple.cc
+++ b/mindspore/ccsrc/backend/common/pass/convert_tuple_output_to_maketuple.cc
@@ -49,25 +49,18 @@ AnfNodePtr ConvertTupleInputToMakeTuple(const FuncGraphPtr &graph, const AnfNode
   return make_tuple;
 }
 
-#ifdef ENABLE_TUPLE_UNFOLD
 bool IsKerenlGraphOutput(const FuncGraphPtr &func_graph, const AnfNodePtr &node) {
   const auto &outputs =
     common::AnfAlgo::GetAllOutputIndexByReturnTypes(func_graph->output(), {prim::kPrimTupleGetItem});
   return std::find_if(outputs.begin(), outputs.end(), [&node](const auto &output) { return output.first == node; }) !=
          outputs.end();
 }
-#endif
 
 bool IsNeedConvert(const FuncGraphPtr &func_graph, const AnfNodePtr &input) {
-#ifdef ENABLE_TUPLE_UNFOLD
   MS_EXCEPTION_IF_NULL(input);
   return (input->Type() != nullptr && AnfUtils::IsRealKernel(input) && common::AnfAlgo::IsTupleOutput(input) &&
           !common::AnfAlgo::CheckPrimitiveType(input, prim::kPrimCall) &&
           (input->isa<Parameter>() || input->isa<ValueNode>() || IsKerenlGraphOutput(func_graph, input)));
-#else
-  return (input->Type() != nullptr && AnfUtils::IsRealKernel(input) && common::AnfAlgo::IsTupleOutput(input) &&
-          !common::AnfAlgo::CheckPrimitiveType(input, prim::kPrimCall));
-#endif
 }
 }  // namespace
 
diff --git a/mindspore/ccsrc/backend/common/session/anf_runtime_algorithm.cc b/mindspore/ccsrc/backend/common/session/anf_runtime_algorithm.cc
index 2981075faff..3119d0bc537 100644
--- a/mindspore/ccsrc/backend/common/session/anf_runtime_algorithm.cc
+++ b/mindspore/ccsrc/backend/common/session/anf_runtime_algorithm.cc
@@ -139,7 +139,6 @@ tensor::TensorPtr GetForwardOutputTensor(const AnfNodePtr &node) {
   return nullptr;
 }
 
-#ifdef ENABLE_TUPLE_UNFOLD
 size_t GetOutputTensorNumByKernelInfo(const AnfNodePtr &node) {
   MS_EXCEPTION_IF_NULL(node);
   MS_EXCEPTION_IF_NULL(node->kernel_info());
@@ -149,7 +148,6 @@ size_t GetOutputTensorNumByKernelInfo(const AnfNodePtr &node) {
   MS_EXCEPTION_IF_NULL(build_info);
   return build_info->GetAllOutputDeviceTypes().size();
 }
-#endif
 }  // namespace
 
 AnfNodePtr AnfRuntimeAlgorithm::MakeMonadValueNode(const KernelGraphPtr &kg) {
@@ -196,7 +194,6 @@ void AnfRuntimeAlgorithm::KeepOrder(const KernelGraphPtr &kg, const AnfNodePtr &
 }
 
 size_t AnfRuntimeAlgorithm::GetOutputTensorNum(const AnfNodePtr &node) {
-#ifdef ENABLE_TUPLE_UNFOLD
   MS_EXCEPTION_IF_NULL(node);
   size_t res;
   TypePtr type = node->Type();
@@ -225,13 +222,9 @@ size_t AnfRuntimeAlgorithm::GetOutputTensorNum(const AnfNodePtr &node) {
     res = 1;
   }
   return res;
-#else
-  return AnfUtils::GetOutputTensorNum(node);
-#endif
 }
 
 size_t AnfRuntimeAlgorithm::GetOutputNumWithoutKernelInfo(const AnfNodePtr &node) {
-#ifdef ENABLE_TUPLE_UNFOLD
   MS_EXCEPTION_IF_NULL(node);
   const auto &kernel_info = node->kernel_info();
   if (kernel_info != nullptr) {
@@ -261,9 +254,6 @@ size_t AnfRuntimeAlgorithm::GetOutputNumWithoutKernelInfo(const AnfNodePtr &node
     res = 1;
   }
   return res;
-#else
-  return AnfUtils::GetOutputTensorNum(node);
-#endif
 }
 
 namespace {
diff --git a/mindspore/ccsrc/plugin/device/cpu/hal/device/kernel_select_cpu.cc b/mindspore/ccsrc/plugin/device/cpu/hal/device/kernel_select_cpu.cc
index fdf388075dd..de8bc584d6f 100644
--- a/mindspore/ccsrc/plugin/device/cpu/hal/device/kernel_select_cpu.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/hal/device/kernel_select_cpu.cc
@@ -82,13 +82,11 @@ void GetOutputDtypes(const CNodePtr &kernel_node, std::vector<TypeId> *output_ty
   }
 }
 
-#ifdef ENABLE_TUPLE_UNFOLD
 // Real tuple isn't expanded.
 void GetOutputDtypesForRealTuple(const CNodePtr &kernel_node, std::vector<TypeId> *output_types) {
   TypeId dtype = common::AnfAlgo::GetOutputInferDataType(kernel_node, 0);
   (void)output_types->emplace_back(dtype);
 }
-#endif
 
 void GetOutputFormat(const CNodePtr &kernel_node, std::vector<std::string> *output_formats) {
   size_t output_num = AnfAlgo::GetOutputElementNum(kernel_node);
@@ -544,7 +542,6 @@ bool SelectKernel(const CNodePtr &kernel_node, kernel::KernelAttr *selected_kern
   bool input_matched = false;
   for (auto kernel_attr : kernel_attrs) {
     output_types.clear();
-#ifdef ENABLE_TUPLE_UNFOLD
     // The real tuple and allsame don't fold the tuple.
     if (kernel_attr.GetAllSame() ||
         (kernel_attr.GetOutputSize() != 0 && kernel_attr.GetOutputAttr(0).object_type == kObjectTypeTuple)) {
@@ -552,9 +549,6 @@ bool SelectKernel(const CNodePtr &kernel_node, kernel::KernelAttr *selected_kern
     } else {
       GetOutputDtypes(kernel_node, &output_types);
     }
-#else
-    GetOutputDtypes(kernel_node, &output_types);
-#endif
     MS_LOG(DEBUG) << "Select kernel for op: " << kernel_node->fullname_with_scope() << ", input types:" << input_types
                   << ", output types:" << output_types;
 
@@ -647,7 +641,6 @@ std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kerne
   // First select the kernel object types.
   std::vector<kernel::KernelAttr> object_selected_kernel_attrs;
   const auto &kernel_attrs = kernel::NativeCpuKernelMod::GetCpuSupportedList(op_name);
-#ifdef ENABLE_TUPLE_UNFOLD
   if (kernel_attrs.empty()) {
     return KernelNotSupportWarning(kernel_node, false);
   } else if (kernel_attrs[0].GetSkipCheck()) {
@@ -656,9 +649,6 @@ std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kerne
              !kernel::SelectKernelByObjectType(kernel_node, kernel_attrs, &object_selected_kernel_attrs, false)) {
     return kernel::KernelObjectTypeNotSupportWarning(kernel_node);
   }
-#else
-  object_selected_kernel_attrs = kernel_attrs;
-#endif
 
   // Second select the matched kernel attr.
   kernel::KernelAttr selected_kernel_attr;
diff --git a/mindspore/ccsrc/plugin/device/cpu/hal/hardware/cpu_device_context.cc b/mindspore/ccsrc/plugin/device/cpu/hal/hardware/cpu_device_context.cc
index 88500446bdb..216d1366e8c 100644
--- a/mindspore/ccsrc/plugin/device/cpu/hal/hardware/cpu_device_context.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/hal/hardware/cpu_device_context.cc
@@ -236,9 +236,7 @@ void CPUKernelExecutor::OptimizeGraphImpl(const KernelGraphPtr &graph) const {
   MS_EXCEPTION_IF_NULL(graph);
   auto optimizer = std::make_shared<opt::GraphOptimizer>();
   auto pm = std::make_shared<opt::PassManager>();
-#ifdef ENABLE_TUPLE_UNFOLD
   pm->AddPass(std::make_shared<opt::InsertTypeTransformOp>("insert_type_transform_op"));
-#endif
   pm->AddPass(std::make_shared<opt::InsertFormatTransformOpCPU>("insert_format_transform_op_cpu"));
   pm->AddPass(std::make_shared<opt::AllReduceFusion>());
   pm->AddPass(std::make_shared<opt::InsertCastCPU>("insert_cast"));
diff --git a/mindspore/ccsrc/plugin/device/gpu/hal/device/kernel_info_setter.cc b/mindspore/ccsrc/plugin/device/gpu/hal/device/kernel_info_setter.cc
index 366ad09cee2..b9670870994 100644
--- a/mindspore/ccsrc/plugin/device/gpu/hal/device/kernel_info_setter.cc
+++ b/mindspore/ccsrc/plugin/device/gpu/hal/device/kernel_info_setter.cc
@@ -593,7 +593,6 @@ bool GetSelectKernelResult(const CNodePtr &kernel_node,
   return result;
 }
 
-#ifdef ENABLE_TUPLE_UNFOLD
 bool GetSelectKernelObjectTypeResult(const CNodePtr &kernel_node, KernelType kernel_type) {
   auto kernel_name = common::AnfAlgo::GetCNodeName(kernel_node);
   // Only the kernel nodes that register kernel attr can support the backoff.
@@ -631,7 +630,6 @@ bool GetSelectKernelObjectTypeResult(const CNodePtr &kernel_node, KernelType ker
   kernel::SetKernelObjectTypeWithSelectedAttr(kernel_node, object_selected_kernel_attrs[0]);
   return true;
 }
-#endif
 
 std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kernel_node, KernelType kernel_type) {
   MS_EXCEPTION_IF_NULL(kernel_node);
@@ -643,12 +641,10 @@ std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kerne
   }
   auto builder = std::make_shared<KernelBuildInfo::KernelBuildInfoBuilder>();
   AnfAlgo::SetSelectKernelBuildInfo(builder->Build(), kernel_node.get());
-#ifdef ENABLE_TUPLE_UNFOLD
   bool selected = GetSelectKernelObjectTypeResult(kernel_node, kernel_type);
   if (!selected) {
     return kernel::KernelObjectTypeNotSupportWarning(kernel_node);
   }
-#endif
   std::vector<std::string> inputs_format;
   std::vector<TypeId> inputs_type;
   size_t input_num = common::AnfAlgo::GetInputTensorNum(kernel_node);
@@ -659,21 +655,17 @@ std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kerne
 
   std::vector<std::string> outputs_format;
   std::vector<TypeId> outputs_type;
-#ifdef ENABLE_TUPLE_UNFOLD
   auto output_kernel_object_types = builder->Build()->GetAllOutputKernelObjectTypes();
   if (output_kernel_object_types.size() == 1 && output_kernel_object_types[0] == kernel::KernelObjectType::TUPLE) {
     outputs_type = {common::AnfAlgo::GetOutputInferDataType(kernel_node, 0)};
     outputs_format = {kOpFormat_DEFAULT};
   } else {
-#endif
     size_t output_num = AnfAlgo::GetOutputElementNum(kernel_node);
     for (size_t output_index = 0; output_index < output_num; ++output_index) {
       outputs_format.emplace_back(kOpFormat_DEFAULT);
       outputs_type.push_back(common::AnfAlgo::GetOutputInferDataType(kernel_node, output_index));
     }
-#ifdef ENABLE_TUPLE_UNFOLD
   }
-#endif
   std::string origin_data_format = kOpFormat_DEFAULT;
   if (IsNeedProcessFormatInfo(kernel_node, inputs_type)) {
     UpdateKernelFormatInfo(kernel_node, inputs_type, &inputs_format, &outputs_format, &origin_data_format);
@@ -683,12 +675,10 @@ std::pair<std::string, ExceptionType> SetKernelInfoWithMsg(const CNodePtr &kerne
   builder->SetInputsDeviceType(inputs_type);
   builder->SetOutputsFormat(outputs_format);
   builder->SetOutputsDeviceType(outputs_type);
-#ifdef ENABLE_TUPLE_UNFOLD
   kernel::UnfoldKernelBuildInfo(kernel_node);
   if (!common::AnfAlgo::HasNodeAttr(kAttrDynInputSizes, kernel_node)) {
     kernel::SetDynamicInputSizeAttr(kernel_node);
   }
-#endif
   MS_LOG(INFO) << kernel_node->fullname_with_scope() << " kernel attr info: "
                << kernel::FetchPrintInfoByKernelAttr(kernel::GetKernelAttrFromBuildInfo(builder->Build()));
 
diff --git a/mindspore/ccsrc/plugin/device/gpu/hal/hardware/gpu_device_context.cc b/mindspore/ccsrc/plugin/device/gpu/hal/hardware/gpu_device_context.cc
index 1c434edde8d..7a818f98891 100644
--- a/mindspore/ccsrc/plugin/device/gpu/hal/hardware/gpu_device_context.cc
+++ b/mindspore/ccsrc/plugin/device/gpu/hal/hardware/gpu_device_context.cc
@@ -356,9 +356,7 @@ void GPUKernelExecutor::OptimizeGraphWithDeviceInfo(const KernelGraphPtr &graph)
   // Graph optimization relevant to device data format
   auto optimizer = std::make_shared<opt::GraphOptimizer>();
   auto pm = std::make_shared<opt::PassManager>();
-#ifdef ENABLE_TUPLE_UNFOLD
   pm->AddPass(std::make_shared<opt::InsertTypeTransformOp>("insert_type_transform_op"));
-#endif
   // ReplaceAddNFusion depends on the input expansion of AddN, so must be after the operator select.
   pm->AddPass(std::make_shared<opt::ReplaceAddNFusion>());
   // PrintReduceFusion depends on the input expansion of Print, so must be after the operator select.