diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.cc b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.cc
index a524d694e67..9e2c6374ce9 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.cc
@@ -25,29 +25,8 @@
 
 namespace mindspore {
 namespace opt {
-namespace {
-void SetAttrsForFusionNode(const AnfNodePtr &sub_anf, const AnfNodePtr &fusion_node) {
-  MS_EXCEPTION_IF_NULL(sub_anf);
-  MS_EXCEPTION_IF_NULL(fusion_node);
-  auto sub = sub_anf->cast<CNodePtr>();
-  MS_EXCEPTION_IF_NULL(sub);
-  if (sub->size() != kSubInputNum) {
-    MS_LOG(EXCEPTION) << "Sub's size is not equal with 3";
-  }
-  auto reduce_sum_anf = sub->input(2);
-  MS_EXCEPTION_IF_NULL(reduce_sum_anf);
-  auto reduce_sum = reduce_sum_anf->cast<CNodePtr>();
-  if (reduce_sum == nullptr) {
-    MS_LOG(EXCEPTION) << "Sub's second input is not a cnode";
-  }
-  AnfAlgo::CopyNodeAttr(kAttrAxis, reduce_sum, fusion_node);
-  AnfAlgo::CopyNodeAttr(kAttrKeepDims, reduce_sum, fusion_node);
-}
-}  // namespace
-
 const BaseRef ConfusionSoftmaxGradRule::DefinePattern() const {
-  return VectorRef(
-    {prim::kPrimSub, input0_, VectorRef({prim::kPrimReduceSum, VectorRef({prim::kPrimMul, input1_, input0_})})});
+  return VectorRef({prim::kPrimSub, input0_, VectorRef({reduce_sum_, VectorRef({prim::kPrimMul, input1_, input0_})})});
 }
 
 const AnfNodePtr ConfusionSoftmaxGradRule::Process(const FuncGraphPtr &graph, const AnfNodePtr &node,
@@ -55,22 +34,28 @@ const AnfNodePtr ConfusionSoftmaxGradRule::Process(const FuncGraphPtr &graph, co
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(node);
   MS_EXCEPTION_IF_NULL(equiv);
-  auto input0 = utils::cast<AnfNodePtr>((*equiv)[input0_]);
-  auto input1 = utils::cast<AnfNodePtr>((*equiv)[input1_]);
-  MS_EXCEPTION_IF_NULL(input0);
-  MS_EXCEPTION_IF_NULL(input1);
+  AnfNodePtr input0 = GetAnfNodeByVar(equiv, input0_);
+  AnfNodePtr input1 = GetAnfNodeByVar(equiv, input1_);
+  AnfNodePtr sum_anf = GetAnfNodeByVar(equiv, reduce_sum_);
+  if (sum_anf == nullptr || !sum_anf->isa<CNode>()) {
+    MS_LOG(WARNING) << "Matched ReduceSum is not a CNode!";
+    return nullptr;
+  }
+  if (!GetBoolAttr(sum_anf, kAttrKeepDims)) {
+    MS_LOG(INFO) << "ReduceSum's attr keep_dims should be true if do fusion. Otherwise the calculation will be wrong";
+    return nullptr;
+  }
 
   auto prim = std::make_shared<Primitive>(kConfusionSoftmaxGradOpName);
   MS_EXCEPTION_IF_NULL(prim);
   std::vector<AnfNodePtr> inputs = {NewValueNode(prim), input0, input1};
-  auto confusion_softmax_grad = graph->NewCNode(inputs);
-  MS_EXCEPTION_IF_NULL(confusion_softmax_grad);
-  auto types = {AnfAlgo::GetOutputInferDataType(node, 0)};
-  auto shapes = {AnfAlgo::GetOutputInferShape(node, 0)};
-  AnfAlgo::SetOutputInferTypeAndShape(types, shapes, confusion_softmax_grad.get());
-  confusion_softmax_grad->set_scope(node->scope());
-  SetAttrsForFusionNode(node, confusion_softmax_grad);
-  return confusion_softmax_grad;
+  auto fusion_node = graph->NewCNode(inputs);
+  MS_EXCEPTION_IF_NULL(fusion_node);
+  fusion_node->set_abstract(node->abstract());
+  fusion_node->set_scope(node->scope());
+  AnfAlgo::CopyNodeAttr(kAttrAxis, sum_anf, fusion_node);
+  AnfAlgo::CopyNodeAttr(kAttrKeepDims, sum_anf, fusion_node);
+  return fusion_node;
 }
 }  // namespace opt
 }  // namespace mindspore
diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.h b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.h
index 58722e586f9..a4d0d1ce7aa 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.h
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/confusion_softmax_grad_rule.h
@@ -24,9 +24,11 @@ namespace opt {
 class ConfusionSoftmaxGradRule : public PatternProcessPass {
  public:
   explicit ConfusionSoftmaxGradRule(bool multigraph = true)
-      : PatternProcessPass("confusion_softmax_grad_rule", multigraph),
-        input0_(std::make_shared<Var>()),
-        input1_(std::make_shared<Var>()) {}
+      : PatternProcessPass("confusion_softmax_grad_rule", multigraph) {
+    input0_ = std::make_shared<Var>();
+    input1_ = std::make_shared<Var>();
+    reduce_sum_ = std::make_shared<Var>(std::make_shared<Primitive>(prim::kPrimReduceSum->name()));
+  }
   ~ConfusionSoftmaxGradRule() override = default;
   const BaseRef DefinePattern() const override;
   const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
@@ -34,6 +36,7 @@ class ConfusionSoftmaxGradRule : public PatternProcessPass {
  private:
   VarPtr input0_;
   VarPtr input1_;
+  VarPtr reduce_sum_;
 };
 }  // namespace opt
 }  // namespace mindspore
diff --git a/tests/ut/cpp/python_input/gtest_input/pre_activate/confusion_softmax_grad_rule.py b/tests/ut/cpp/python_input/gtest_input/pre_activate/confusion_softmax_grad_rule.py
index db435712f81..93902c24cac 100644
--- a/tests/ut/cpp/python_input/gtest_input/pre_activate/confusion_softmax_grad_rule.py
+++ b/tests/ut/cpp/python_input/gtest_input/pre_activate/confusion_softmax_grad_rule.py
@@ -16,7 +16,7 @@ from mindspore.ops import Primitive
 from mindspore.ops import operations as P
 
 mul = P.Mul()
-reduce_sum = P.ReduceSum()
+reduce_sum = P.ReduceSum(keep_dims=True)
 sub = P.Sub()
 confusion_softmax_grad = Primitive('ConfusionSoftmaxGrad')
 make_tuple = Primitive('make_tuple')