diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc
index 5d27f5b60c7115a32aeeca5ec2a6654471c310c7..36049ee6a4a0d2a251b6d10cf1ff05a9d9845089 100644
--- a/paddle/fluid/operators/batch_norm_op.cc
+++ b/paddle/fluid/operators/batch_norm_op.cc
@@ -457,12 +457,39 @@ class BatchNormGradKernel<platform::CPUDeviceContext, T>
   }
 };
 
+class BatchNormGradMaker : public framework::SingleGradOpDescMaker {
+ public:
+  using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
+
+ protected:
+  std::unique_ptr<framework::OpDesc> Apply() const override {
+    auto *op = new framework::OpDesc();
+    op->SetType("batch_norm_grad");
+    op->SetInput("X", Input("X"));
+    op->SetInput(framework::GradVarName("Y"), OutputGrad("Y"));
+
+    op->SetInput("Scale", Input("Scale"));
+    op->SetInput("SavedMean", Output("SavedMean"));
+    op->SetInput("SavedVariance", Output("SavedVariance"));
+
+    op->SetAttrMap(Attrs());
+
+    op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
+    op->SetOutput(framework::GradVarName("Scale"), InputGrad("Scale"));
+    op->SetOutput(framework::GradVarName("Bias"), InputGrad("Bias"));
+
+    return std::unique_ptr<framework::OpDesc>(op);
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 namespace ops = paddle::operators;
-REGISTER_OP(batch_norm, ops::BatchNormOp, ops::BatchNormOpMaker,
-            batch_norm_grad, ops::BatchNormGradOp);
+REGISTER_OPERATOR(batch_norm, ops::BatchNormOp, ops::BatchNormOpMaker,
+                  ops::BatchNormGradMaker);
+REGISTER_OPERATOR(batch_norm_grad, ops::BatchNormGradOp);
+
 REGISTER_OP_CPU_KERNEL(
     batch_norm,
     ops::BatchNormKernel<paddle::platform::CPUDeviceContext, float>);