diff --git a/paddle/operators/block_expand_op.cc b/paddle/operators/block_expand_op.cc
index bef82183b8caa6692d1434a3a7da13f8d9656208..f9b75ffee707d9f41926f13c1f9b7a78e4ccc98f 100644
--- a/paddle/operators/block_expand_op.cc
+++ b/paddle/operators/block_expand_op.cc
@@ -57,16 +57,14 @@ class BlockExpandOp : public framework::OperatorWithKernel {
 
 class BlockExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BlockExpandOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  BlockExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("X", R"DOC(
-(Tensor)The input tensor has NCHW format.
-    N: batch size
-    C: channels
-    H: height
-    W: width
-)DOC");
+    AddInput("X",
+             "(Tensor)The input tensor has NCHW format."
+             "N: batch size"
+             "C: channels"
+             "H: height"
+             "W: width");
     AddOutput("Out", "(LodTensor)The output data of block_expand op,");
     AddAttr<int>("block_height", "(int)height of block.");
     AddAttr<int>("block_width", "(int)width of block.");
@@ -155,7 +153,8 @@ namespace ops = paddle::operators;
 REGISTER_OP(block_expand, ops::BlockExpandOp, ops::BlockExpandOpMaker,
             block_expand_grad, ops::BlockExpandGradOp);
 REGISTER_OP_CPU_KERNEL(
-    block_expand, ops::BlockExpandKernel<paddle::platform::CPUPlace, float>);
+    block_expand,
+    ops::BlockExpandKernel<paddle::platform::CPUDeviceContext, float>);
 REGISTER_OP_CPU_KERNEL(
     block_expand_grad,
-    ops::BlockExpandGradKernel<paddle::platform::CPUPlace, float>);
+    ops::BlockExpandGradKernel<paddle::platform::CPUDeviceContext, float>);
diff --git a/paddle/operators/block_expand_op.cu b/paddle/operators/block_expand_op.cu
index 492ac0c9b2ed2e1092e3eda4504576d9083f5dcb..c17b113807694737ad19aa73697df04bc7bfee21 100644
--- a/paddle/operators/block_expand_op.cu
+++ b/paddle/operators/block_expand_op.cu
@@ -17,8 +17,9 @@
 
 namespace ops = paddle::operators;
 
-REGISTER_OP_GPU_KERNEL(
-    block_expand, ops::BlockExpandKernel<paddle::platform::GPUPlace, float>);
-REGISTER_OP_GPU_KERNEL(
+REGISTER_OP_CUDA_KERNEL(
+    block_expand,
+    ops::BlockExpandKernel<paddle::platform::CUDADeviceContext, float>);
+REGISTER_OP_CUDA_KERNEL(
     block_expand_grad,
-    ops::BlockExpandGradKernel<paddle::platform::GPUPlace, float>);
+    ops::BlockExpandGradKernel<paddle::platform::CUDADeviceContext, float>);
diff --git a/paddle/operators/block_expand_op.h b/paddle/operators/block_expand_op.h
index 2e4f0cb6f1d1df92e6392196afb368c234385bb2..72760fb23c12c2243ad63ea8a655250009d3360d 100644
--- a/paddle/operators/block_expand_op.h
+++ b/paddle/operators/block_expand_op.h
@@ -31,7 +31,7 @@ inline int get_output_size(int img_size, int block_size, int stride,
   return (1 + (img_size + 2 * padding - block_size + stride - 1) / stride);
 }
 
-template <typename Place, typename T>
+template <typename DeviceContext, typename T>
 class BlockExpandKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
@@ -71,8 +71,9 @@ class BlockExpandKernel : public framework::OpKernel<T> {
                                                 img_channels, block_height,
                                                 block_width});
 
-      math::Im2ColFunctor<math::ColFormat::kOCF, Place, T> f;
-      f(ctx.device_context(), src, dilations, strides, paddings, &dst);
+      math::Im2ColFunctor<math::ColFormat::kOCF, DeviceContext, T> f;
+      auto& dev_ctx = ctx.template device_context<DeviceContext>();
+      f(dev_ctx, src, dilations, strides, paddings, &dst);
     }
     out->Resize(out_dims);
 
@@ -87,7 +88,7 @@ class BlockExpandKernel : public framework::OpKernel<T> {
   }
 };
 
-template <typename Place, typename T>
+template <typename DeviceContext, typename T>
 class BlockExpandGradKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
@@ -98,7 +99,8 @@ class BlockExpandGradKernel : public framework::OpKernel<T> {
     d_x->mutable_data<T>(ctx.GetPlace());
 
     auto x_v = framework::EigenVector<T>::Flatten(*d_x);
-    x_v.device(ctx.GetEigenDevice<Place>()) = x_v.constant(0.0);
+    auto& place = *ctx.template device_context<DeviceContext>().eigen_device();
+    x_v.device(place) = x_v.constant(0.0);
 
     auto in_dim = in->dims();
     int batch_size = in_dim[0];
@@ -131,8 +133,9 @@ class BlockExpandGradKernel : public framework::OpKernel<T> {
       const Tensor src = d_out->Slice(i, i + 1).Resize(
           {output_height, output_width, img_channels, block_height,
            block_width});
-      math::Col2ImFunctor<math::ColFormat::kOCF, Place, T> f;
-      f(ctx.device_context(), src, dilations, strides, paddings, &dst);
+      math::Col2ImFunctor<math::ColFormat::kOCF, DeviceContext, T> f;
+      auto& dev_ctx = ctx.template device_context<DeviceContext>();
+      f(dev_ctx, src, dilations, strides, paddings, &dst);
     }
     d_out->Resize(d_out_dims);
   }