diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc
index d77c0607a08a701b6d6100d8d3469c47015f8718..95b495b87aa006c32ee777559d67f782ccdeefbd 100644
--- a/paddle/operators/mul_op.cc
+++ b/paddle/operators/mul_op.cc
@@ -62,10 +62,6 @@ class MulOpGrad : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
-    // PADDLE_ENFORCE_EQ(ctx.InputSize(), 3UL,
-    //                   "Input of MulOpGrad should be 3, X, Y, Out@GRAD");
-    // PADDLE_ENFORCE_EQ(ctx.OutputSize(), 2UL,
-    //                   "Output of MulOpGrad should be 2, X@GRAD, Y@GRAD");
     PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) should not be null");
     PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null");
     PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h
index 279454c7f3f098a60d313e90499c15b9e28ede98..2afed81842924796b6f54589fb61627917b4f2f4 100644
--- a/paddle/operators/mul_op.h
+++ b/paddle/operators/mul_op.h
@@ -31,8 +31,6 @@ template <typename Place, typename T>
 class MulKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    // Eigen::array<Eigen::IndexPair<Eigen::DenseIndex>, 1> dim_pair = {
-    //     {Eigen::IndexPair<Eigen::DenseIndex>(1, 0)}};
     auto* X = context.Input<Tensor>("X");
     auto* Y = context.Input<Tensor>("Y");
     auto* Z = context.Output<Tensor>("Out");
@@ -40,13 +38,6 @@ class MulKernel : public framework::OpKernel {
     auto* device_context =
         const_cast<platform::DeviceContext*>(context.device_context_);
     math::matmul<Place, T>(*X, false, *Y, false, 1, Z, 0, device_context);
-
-    // auto X = EigenMatrix<T>::From(*input0);
-    // auto Y = EigenMatrix<T>::From(*input1);
-    // auto Z = EigenMatrix<T>::From(*output);
-    // auto& place = context.GetEigenDevice<Place>();
-
-    // Z.device(place) = X.contract(Y, dim_pair);
   }
 };
 
@@ -60,25 +51,10 @@ class MulGradKernel : public framework::OpKernel {
 
     auto* dX = ctx.Output<Tensor>(framework::GradVarName("X"));
     auto* dY = ctx.Output<Tensor>(framework::GradVarName("Y"));
-    // auto* dXdata = dX->template mutable_data<T>(ctx.GetPlace());
-    // auto* dYdata = dY->template mutable_data<T>(ctx.GetPlace());
     auto* device_context =
         const_cast<platform::DeviceContext*>(ctx.device_context_);
     math::matmul<Place, T>(*dOut, false, *Y, true, 1, dX, 0, device_context);
     math::matmul<Place, T>(*X, true, *dOut, false, 1, dY, 0, device_context);
-
-    // auto X = EigenMatrix<T>::From(*input0);
-    // auto Y = EigenMatrix<T>::From(*input1);
-    // auto dOut = EigenMatrix<T>::From(*input2);
-    // auto dX = EigenMatrix<T>::From(*output0);
-    // auto dY = EigenMatrix<T>::From(*output1);
-
-    // dX = Out@G * Y'
-    // dY = X' * Out@G
-    // auto place = ctx.GetEigenDevice<Place>();
-    // TODO(dzh,qijun) : need transpose feature of blas library
-    // Eigen Tensor does not support it very well
-    // dX.device(place) = matmul(input2, )
   }
 };