diff --git a/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.cc b/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.cc
index 39ab8e4721..bf271d6bcc 100644
--- a/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.cc
+++ b/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.cc
@@ -100,13 +100,13 @@ void FeedTeOpTensorOutputArg(const NotNull<CNodePtr> &cnode,
 void FeedTeOpConstTensor(const NotNull<CNodePtr> &cnode, const std::map<uint32_t, tensor::TensorPtr> &depend_tensor_map,
                          NotNull<std::map<std::string, optiling::TeConstTensorData> *> const_inputs) {
   MS_LOG(INFO) << "FeedTeOpConstTensor start, node:" << cnode->fullname_with_scope();
-  if (!AnfAlgo::HasNodeAttr(kDynamicShapeDepends, cnode.get())) {
+  auto depends_list_me = abstract::GetDependsFormMap(cnode);
+  if (depends_list_me.empty()) {
     MS_LOG(INFO) << "No input depend found, " << cnode->fullname_with_scope();
     return;
   }
 
   std::vector<int> depends_list;
-  std::vector<int64_t> depends_list_me = AnfAlgo::GetNodeAttr<std::vector<int64_t>>(cnode.get(), kDynamicShapeDepends);
   (void)std::transform(depends_list_me.begin(), depends_list_me.end(), std::back_inserter(depends_list),
                        [](const int64_t &value) { return static_cast<int>(value); });
   for (auto index : depends_list) {
diff --git a/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.h b/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.h
index 066d21dd05..17c4262f19 100644
--- a/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.h
+++ b/mindspore/ccsrc/runtime/device/ascend/executor/tiling/op_tiling_calculater.h
@@ -25,6 +25,7 @@
 #include "ir/anf.h"
 #include "ir/tensor.h"
 #include "register/op_tiling.h"
+#include "abstract/primitive_infer_map.h"
 
 namespace mindspore {
 namespace device {
diff --git a/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.cc b/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.cc
index 1ed054895f..79c1de652a 100644
--- a/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.cc
+++ b/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.cc
@@ -39,16 +39,14 @@ void DynamicKernel::Initialize() {
   is_input_dynamic_shape_ = AnfAlgo::GetBooleanAttr(cnode_ptr_, kAttrInputIsDynamicShape);
   is_output_dynamic_shape_ = AnfAlgo::GetBooleanAttr(cnode_ptr_, kAttrOutputIsDynamicShape);
 
-  auto have_depends = AnfAlgo::HasNodeAttr(kDynamicShapeDepends, cnode_ptr_);
-  if (!have_depends) {
+  auto ret = abstract::GetDependsFormMap(cnode_ptr_);
+  if (ret.empty()) {
     MS_LOG(DEBUG) << "No dynamic_shape_depends found";
     return;
   }
   MS_LOG(INFO) << "Have depends";
-  std::vector<int64_t> depends_list_me = AnfAlgo::GetNodeAttr<std::vector<int64_t>>(cnode_ptr_, kDynamicShapeDepends);
-  (void)std::transform(depends_list_me.begin(), depends_list_me.end(), std::back_inserter(depend_list_),
+  (void)std::transform(ret.begin(), ret.end(), std::back_inserter(depend_list_),
                        [](const int64_t &value) { return static_cast<int>(value); });
-
   MS_LOG(INFO) << "Init End";
 }
 
diff --git a/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.h b/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.h
index 637bdc410e..fcf3b0ba8e 100644
--- a/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.h
+++ b/mindspore/ccsrc/runtime/device/executor/dynamic_kernel.h
@@ -23,6 +23,7 @@
 #include <map>
 #include "ir/anf.h"
 #include "ir/tensor.h"
+#include "abstract/primitive_infer_map.h"
 
 namespace mindspore {
 namespace device {
diff --git a/mindspore/core/abstract/primitive_infer_map.cc b/mindspore/core/abstract/primitive_infer_map.cc
index dd94ebfc57..b356662590 100644
--- a/mindspore/core/abstract/primitive_infer_map.cc
+++ b/mindspore/core/abstract/primitive_infer_map.cc
@@ -22,6 +22,25 @@
 
 namespace mindspore {
 namespace abstract {
+std::vector<int64_t> GetDependsFormMap(const CNodePtr &cnode) {
+  constexpr auto kUnsortedSegmentSum = "UnsortedSegmentSum";
+  constexpr auto kUnsortedSegmentMin = "UnsortedSegmentMin";
+  constexpr auto kUnsortedSegmentMax = "UnsortedSegmentMax";
+  static std::map<std::string, std::vector<int64_t>> dynamic_shape_depends = {
+    {kUnsortedSegmentSum, {2}}, {kUnsortedSegmentMin, {2}}, {kUnsortedSegmentMax, {2}}};
+  MS_EXCEPTION_IF_NULL(cnode);
+  if (cnode->inputs().empty()) {
+    MS_LOG(EXCEPTION) << "Invalid inputs";
+  }
+  auto primitive = GetValueNode<PrimitivePtr>(cnode->inputs()[0]);
+  MS_EXCEPTION_IF_NULL(primitive);
+  auto iter = dynamic_shape_depends.find(primitive->ToString());
+  if (iter != dynamic_shape_depends.end()) {
+    return iter->second;
+  }
+  return {};
+}
+
 PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap() {
   static PrimitiveEvalImplMap prim_eval_implement_map = {
     // Statements
diff --git a/mindspore/core/abstract/primitive_infer_map.h b/mindspore/core/abstract/primitive_infer_map.h
index 1274e1ac50..77329ce901 100644
--- a/mindspore/core/abstract/primitive_infer_map.h
+++ b/mindspore/core/abstract/primitive_infer_map.h
@@ -21,6 +21,8 @@
 #include "ir/primitive.h"
 #include "base/core_ops.h"
 #include "abstract/abstract_value.h"
+#include "ir/anf.h"
+
 namespace mindspore {
 namespace abstract {
 using StandardPrimitiveEvalImpl = AbstractBasePtr (*)(const abstract::AnalysisEnginePtr &, const PrimitivePtr &,
@@ -35,6 +37,8 @@ using PrimitiveEvalImplMap =
 
 PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap();
 
+std::vector<int64_t> GetDependsFormMap(const CNodePtr &cnode);
+
 void RegisterStandardPrimitiveImpl(const PrimitivePtr &primitive, const StandardPrimitiveImplReg &impl_reg);
 
 class RegisterStandardPrimitiveEvalHelper {
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index a792910808..d313ba0e19 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -1892,7 +1892,6 @@ class UnsortedSegmentSum(PrimitiveWithInfer):
     def __init__(self):
         """Initialize UnsortedSegmentSum"""
         self.init_prim_io_names(inputs=['x', 'segment_ids', 'num_segments'], outputs=['y'])
-        self.add_prim_attr("dynamic_shape_depends", [2])
 
     def __infer__(self, x, segment_ids, num_segments):
         x_type = x['dtype']