diff --git a/mindspore/core/ops/fusion/add_fusion.cc b/mindspore/core/ops/fusion/add_fusion.cc
index c32ff9e1ac..cdd05e84be 100644
--- a/mindspore/core/ops/fusion/add_fusion.cc
+++ b/mindspore/core/ops/fusion/add_fusion.cc
@@ -62,7 +62,7 @@ AbstractBasePtr AddFusionInfer(const abstract::AnalysisEnginePtr &, const Primit
   return std::make_shared<abstract::AbstractTensor>(InferType(primitive, input_args),
                                                     InferShape(primitive, input_args)->shape());
 }
-REGISTER_PRIMITIVE_EVAL_IMPL(AddFusion, prim::kPrimAdd, AddFusionInfer);
+REGISTER_PRIMITIVE_EVAL_IMPL(AddFusion, prim::kPrimAddFusion, AddFusionInfer);
 REGISTER_PRIMITIVE_C(kNameAddFusion, AddFusion);
 }  // namespace ops
 }  // namespace mindspore
diff --git a/mindspore/core/ops/grad/dropout_grad.cc b/mindspore/core/ops/grad/dropout_grad.cc
index 464f1d98d3..3c9e6af94f 100644
--- a/mindspore/core/ops/grad/dropout_grad.cc
+++ b/mindspore/core/ops/grad/dropout_grad.cc
@@ -19,18 +19,31 @@
 
 namespace mindspore {
 namespace ops {
-void DropoutGrad::Init(const float ratio) { set_ratio(ratio); }
+void DropoutGrad::Init(const float ratio, const float keep_prob) {
+  this->set_ratio(ratio);
+  this->set_keep_prob(keep_prob);
+}
 
 void DropoutGrad::set_ratio(const float ratio) {
   CheckAndConvertUtils::CheckInRange<float>(kRatio, ratio, kIncludeRight, {0.0, 1.0}, this->name());
   this->AddAttr(kRatio, MakeValue(ratio));
 }
 
+void DropoutGrad::set_keep_prob(const float keep_prob) {
+  CheckAndConvertUtils::CheckInRange<float>(kKeepProb, keep_prob, kIncludeRight, {0.0, 1.0}, this->name());
+  this->AddAttr(kKeepProb, MakeValue(keep_prob));
+}
+
 float DropoutGrad::get_ratio() const {
   auto value_ptr = GetAttr(kRatio);
   return GetValue<float>(value_ptr);
 }
 
+float DropoutGrad::get_keep_prob() const {
+  auto value_ptr = GetAttr(kKeepProb);
+  return GetValue<float>(value_ptr);
+}
+
 namespace {
 abstract::ShapePtr DropoutGradInferShape(const PrimitivePtr &primitive,
                                          const std::vector<AbstractBasePtr> &input_args) {
diff --git a/mindspore/core/ops/grad/dropout_grad.h b/mindspore/core/ops/grad/dropout_grad.h
index bc92d5a517..9881dd36a9 100644
--- a/mindspore/core/ops/grad/dropout_grad.h
+++ b/mindspore/core/ops/grad/dropout_grad.h
@@ -31,9 +31,11 @@ class DropoutGrad : public PrimitiveC {
   DropoutGrad() : PrimitiveC(kNameDropoutGrad) {}
   ~DropoutGrad() = default;
   MS_DECLARE_PARENT(DropoutGrad, PrimitiveC);
-  void Init(const float ratio = 0.5);
+  void Init(const float ratio = 0.5, const float keep_prob = 0.5);
   void set_ratio(const float ratio);
+  void set_keep_prob(const float keep_prob);
   float get_ratio() const;
+  float get_keep_prob() const;
 };
 
 AbstractBasePtr DropoutGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
diff --git a/tests/ut/cpp/ops/test_ops_add.cc b/tests/ut/cpp/ops/test_ops_add.cc
index 41a5592c6b..ce22771179 100644
--- a/tests/ut/cpp/ops/test_ops_add.cc
+++ b/tests/ut/cpp/ops/test_ops_add.cc
@@ -28,5 +28,34 @@ class TestAdd : public UT::Common {
   void SetUp() {}
   void TearDown() {}
 };
+
+TEST_F(TestAdd, test_ops_add) {
+  auto add = std::make_shared<Add>();
+  add->Init();
+  auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1, 3});
+  auto tensor_y = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{1, 3});
+  MS_EXCEPTION_IF_NULL(tensor_x);
+  MS_EXCEPTION_IF_NULL(tensor_y);
+  auto add_abstract = add->Infer({tensor_x->ToAbstract(), tensor_y->ToAbstract()});
+  MS_EXCEPTION_IF_NULL(add_abstract);
+  EXPECT_EQ(add_abstract->isa<abstract::AbstractTensor>(), true);
+  auto shape_ptr = add_abstract->BuildShape();
+  MS_EXCEPTION_IF_NULL(shape_ptr);
+  EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true);
+  auto add_shape = shape_ptr->cast<abstract::ShapePtr>();
+  MS_EXCEPTION_IF_NULL(add_shape);
+  auto shape_vec = add_shape->shape();
+  auto type = add_abstract->BuildType();
+  MS_EXCEPTION_IF_NULL(type);
+  EXPECT_EQ(type->isa<TensorType>(), true);
+  auto tensor_type = type->cast<TensorTypePtr>();
+  MS_EXCEPTION_IF_NULL(tensor_type);
+  auto elem_type = tensor_type->element();
+  EXPECT_EQ(elem_type->type_id(), kNumberTypeFloat32);
+  EXPECT_EQ(shape_vec.size(), 2);
+  EXPECT_EQ(shape_vec[0], 1);
+  EXPECT_EQ(shape_vec[1], 3);
+}
+
 }  // namespace ops
 }  // namespace mindspore