diff --git a/paddle/fluid/operators/renorm_op.cu b/paddle/fluid/operators/renorm_op.cu
index c8471fffa859809a64ad89395936e39bb9a7b4eb..1798faa759bed013c35f93bf0d2623f2a17da49a 100644
--- a/paddle/fluid/operators/renorm_op.cu
+++ b/paddle/fluid/operators/renorm_op.cu
@@ -12,16 +12,16 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/operators/renorm_op.h"
+
 #include <algorithm>
+#include <cstdio>
+
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h"
-#include "paddle/fluid/operators/reduce_ops/reduce_functor_op.h"
 #include "paddle/fluid/operators/reduce_ops/reduce_op.cu.h"
-#include "paddle/fluid/operators/reduce_ops/reduce_op.h"
-#include "paddle/fluid/operators/renorm_op.h"
 #include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
-#include "stdio.h"
 
 namespace paddle {
 namespace operators {
@@ -60,7 +60,7 @@ __global__ void RenormKernelFunc3(int64_t size, T* dim_value, float p,
 }
 
 template <typename T>
-__global__ void RenormKernelFunc4(T* x_data, T* out_data, int64_t size,
+__global__ void RenormKernelFunc4(const T* x_data, T* out_data, int64_t size,
                                   T* dim_value, int64_t dimension_each,
                                   int64_t dim_divisor) {
   int64_t i = ((int64_t)blockIdx.x) * blockDim.x + threadIdx.x;
@@ -74,8 +74,8 @@ __global__ void RenormKernelFunc4(T* x_data, T* out_data, int64_t size,
 }
 
 template <typename T>
-__global__ void RenormGradKernelFunc1(T* x_data, T* dout_data, T* pow_value,
-                                      T* mul_value, int64_t size,
+__global__ void RenormGradKernelFunc1(const T* x_data, const T* dout_data,
+                                      T* pow_value, T* mul_value, int64_t size,
                                       int64_t dimension_each, float p,
                                       int64_t dim_divisor) {
   int64_t i = ((int64_t)blockIdx.x) * blockDim.x + threadIdx.x;
@@ -87,8 +87,8 @@ __global__ void RenormGradKernelFunc1(T* x_data, T* dout_data, T* pow_value,
 }
 
 template <typename T>
-__global__ void RenormGradKernelFunc2(T* x_data, T* dout_data, T* dx_data,
-                                      int64_t size, T* dim_value,
+__global__ void RenormGradKernelFunc2(const T* x_data, const T* dout_data,
+                                      T* dx_data, int64_t size, T* dim_value,
                                       T* dim_power_sum, T* weight_derivative,
                                       int64_t dimension_each, float p,
                                       float max_norm, int64_t dim_divisor) {
@@ -100,8 +100,9 @@ __global__ void RenormGradKernelFunc2(T* x_data, T* dout_data, T* dx_data,
     if (temp > max_norm) {
       dim_power_sum[i] = pow(dim_value[i], (T)(-1.0 - 1.0 / p)) * -1 * max_norm;
       dim_value[i] = max_norm / temp;
-    } else
+    } else {
       dim_value[i] = 1.0;
+    }
   }
   __syncthreads();
   if (i < size) {
@@ -120,7 +121,7 @@ class CUDARenormKernel : public framework::OpKernel<T> {
     const Tensor* x = context.Input<Tensor>("X");
     Tensor* out = context.Output<Tensor>("Out");
     auto numel = x->numel();
-    T* x_data = (T*)x->data<T>();
+    const T* x_data = x->data<T>();
     auto input_dims = x->dims();
     float max_norm = context.Attr<float>("max_norm");
     float p = context.Attr<float>("p");
@@ -176,8 +177,8 @@ class CUDAGradRenormKernel : public framework::OpKernel<T> {
         ctx.Output<framework::Tensor>(framework::GradVarName("X"));
 
     auto numel = d_out->numel();
-    T* dout_data = (T*)d_out->data<T>();
-    T* x_data = (T*)x->data<T>();
+    const T* dout_data = d_out->data<T>();
+    const T* x_data = x->data<T>();
     auto input_dims = x->dims();
     float max_norm = ctx.Attr<float>("max_norm");
     float p = ctx.Attr<float>("p");
@@ -234,4 +235,4 @@ REGISTER_OP_CUDA_KERNEL(renorm, ops::CUDARenormKernel<float>,
                         ops::CUDARenormKernel<double>);
 
 REGISTER_OP_CUDA_KERNEL(renorm_grad, ops::CUDAGradRenormKernel<float>,
-                        ops::CUDAGradRenormKernel<double>);
\ No newline at end of file
+                        ops::CUDAGradRenormKernel<double>);