diff --git a/paddle/framework/ddim.cc b/paddle/framework/ddim.cc
index fc3d508553c0e966978b28d58127bdbff10d45f1..a3357867530c110df16a5f3ec8c799735206cc71 100644
--- a/paddle/framework/ddim.cc
+++ b/paddle/framework/ddim.cc
@@ -292,5 +292,13 @@ DDim flatten_to_2d(const DDim& src, int num_col_dims) {
 
 DDim flatten_to_1d(const DDim& src) { return make_ddim({product(src)}); }
 
+DDim stride(const DDim& ddim) {
+  std::vector<int64_t> strides(ddim.size());
+  strides[ddim.size() - 1] = 1;
+  for (int i = ddim.size() - 2; i >= 0; --i) {
+    strides[i] = strides[i + 1] * ddim[i + 1];
+  }
+  return framework::make_ddim(strides);
+}
 }  // namespace framework
 }  // namespace paddle
diff --git a/paddle/framework/ddim.h b/paddle/framework/ddim.h
index ca29e7e8c7776de6adf3e3b0e8f11f0d4d8487c3..4a871bb0a91ed4050847509cc3f24218bcd57142 100644
--- a/paddle/framework/ddim.h
+++ b/paddle/framework/ddim.h
@@ -121,6 +121,7 @@ DDim flatten_to_2d(const DDim& src, int num_col_dims);
 
 DDim flatten_to_1d(const DDim& src);
 
+DDim stride(const DDim& ddim);
 }  // namespace framework
 }  // namespace paddle
 
diff --git a/paddle/operators/crop_op.cc b/paddle/operators/crop_op.cc
index d38c7ba35891ae73830726899468eaac8f7719dc..7ed21f336f69e494f3c4039c609c83407a80cd8c 100644
--- a/paddle/operators/crop_op.cc
+++ b/paddle/operators/crop_op.cc
@@ -32,8 +32,9 @@ class CropOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
                             "Output(Out) of CropOp should not be null.");
     auto x_dim = ctx.Input<LoDTensor>("X")->dims();
-    auto Y = ctx.Input<LoDTensor>("Y");
-    if (Y == nullptr) {
+    auto *y = ctx.Input<LoDTensor>("Y");
+    auto *out = ctx.Output<LoDTensor>("Out");
+    if (y == nullptr) {
       auto shape = Attr<std::vector<int>>("shape");
       PADDLE_ENFORCE_EQ(
           int64_t(shape.size()), x_dim.size(),
@@ -42,12 +43,12 @@ class CropOp : public framework::OperatorWithKernel {
       for (size_t i = 0; i < shape.size(); ++i) {
         tensor_shape[i] = static_cast<int64_t>(shape[i]);
       }
-      ctx.Output<LoDTensor>("Out")->Resize(framework::make_ddim(tensor_shape));
+      out->Resize(framework::make_ddim(tensor_shape));
     } else {
-      PADDLE_ENFORCE_EQ(framework::arity(x_dim), framework::arity(Y->dims()),
+      PADDLE_ENFORCE_EQ(framework::arity(x_dim), framework::arity(y->dims()),
                         "Tensor rank of both CropOp's "
                         "inputs must be same.");
-      ctx.Output<LoDTensor>("Out")->Resize(Y->dims());
+      out->Resize(y->dims());
     }
   }
 };
diff --git a/paddle/operators/crop_op.h b/paddle/operators/crop_op.h
index d4c523cf30e594575bfe5599597960829054f03f..2f40c059033ec649b29f6ecdee4fcedd128a63a6 100644
--- a/paddle/operators/crop_op.h
+++ b/paddle/operators/crop_op.h
@@ -24,19 +24,7 @@ namespace operators {  // Internal
 template <typename T, size_t D, int MajorType = Eigen::RowMajor,
           typename IndexType = Eigen::DenseIndex>
 using EigenTensor = framework::EigenTensor<T, D, MajorType, IndexType>;
-
 using framework::Tensor;
-using framework::DDim;
-
-// TODO(wanghaoshuang):  move this function to other place
-DDim stride(const DDim& ddim) {
-  std::vector<int64_t> strides(ddim.size());
-  strides[ddim.size() - 1] = 1;
-  for (int i = ddim.size() - 2; i >= 0; --i) {
-    strides[i] = strides[i + 1] * ddim[i + 1];
-  }
-  return make_ddim(strides);
-}
 
 template <typename T>
 class CropKernel : public framework::OpKernel {
@@ -44,13 +32,13 @@ class CropKernel : public framework::OpKernel {
   void Compute(const framework::ExecutionContext& context) const override {
     auto* x = context.Input<Tensor>("X");
     auto* out = context.Output<Tensor>("Out");
-    T* x_data = x->data<T>();
+    const T* x_data = x->data<T>();
     T* out_data = out->mutable_data<T>(context.GetPlace());
-    auto x_stride = stride(x->dims());
-    auto out_stride = stride(out->dims());
+    auto x_stride = framework::stride(x->dims());
+    auto out_stride = framework::stride(out->dims());
     auto offsets = context.Attr<std::vector<int>>("offsets");
     PADDLE_ENFORCE_EQ(
-        x_dims.size(), offsets.size(),
+        x->dims().size(), offsets.size(),
         "Offsets size should be equal to dimension size of input tensor.");
     int64_t offset = 0;
     for (int i = 0; i < offsets.size(); ++i) {
@@ -71,7 +59,7 @@ void CropGradFunction(const framework::ExecutionContext& context) {
     Eigen::array<std::pair<int, int>, D> paddings;
     for (int i = 0; i < D; ++i) {
       paddings[i].first = offsets[i];
-      paddings[i].second = d_x_dims[i] - d_out_dims[i] - offsets[i];
+      paddings[i].second = d_x->dims()[i] - d_out->dims()[i] - offsets[i];
     }
     auto d_x_tensor = EigenTensor<T, D>::From(*d_x);
     auto d_out_tensor = EigenTensor<T, D>::From(*d_out);