diff --git a/paddle/fluid/operators/concat_op.h b/paddle/fluid/operators/concat_op.h
index a496301526f58875ff51aeaa5b2094c3c656531c..78be2e1e1f06c7a518e35a770c1dc9581b2d10fe 100644
--- a/paddle/fluid/operators/concat_op.h
+++ b/paddle/fluid/operators/concat_op.h
@@ -62,9 +62,21 @@ class ConcatGradKernel : public framework::OpKernel<T> {
   void Compute(const framework::ExecutionContext& ctx) const {
     auto* out_grad =
         ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
-    auto ins = ctx.MultiInput<framework::Tensor>("X");
+    auto ins = ctx.MultiInput<framework::LoDTensor>("X");
     auto out_var_names = ctx.Outputs(framework::GradVarName("X"));
-    auto outs = ctx.MultiOutput<framework::Tensor>(framework::GradVarName("X"));
+    auto outs =
+        ctx.MultiOutput<framework::LoDTensor>(framework::GradVarName("X"));
+
+    {
+      auto dx = outs;
+      auto x = ins;
+      for (size_t i = 0; i < dx.size(); ++i) {
+        if (dx[i] != nullptr) {
+          dx[i]->set_lod(x[i]->lod());
+        }
+      }
+    }
+
     int64_t axis = static_cast<int64_t>(ctx.Attr<int>("axis"));
 
     // get output tensor that the name is not kEmptyVarName
diff --git a/paddle/fluid/operators/math/concat.cc b/paddle/fluid/operators/math/concat.cc
index 55c8a472aca7fe700ef6a3f96bed1496d7b12b80..fbe7c2978385401b35765101c87387ff727be4e0 100644
--- a/paddle/fluid/operators/math/concat.cc
+++ b/paddle/fluid/operators/math/concat.cc
@@ -71,7 +71,7 @@ class ConcatGradFunctor<platform::CPUDeviceContext, T> {
  public:
   void operator()(const platform::CPUDeviceContext& context,
                   const framework::Tensor& input,
-                  const std::vector<const framework::Tensor*>& ref_inputs,
+                  const std::vector<const framework::LoDTensor*>& ref_inputs,
                   const int axis, std::vector<framework::Tensor*>* outputs) {
     // TODO(zcd): Add input data validity checking
     size_t num = outputs->size();
diff --git a/paddle/fluid/operators/math/concat.cu b/paddle/fluid/operators/math/concat.cu
index 5863d74fca21de8b77bc208fb95d8fd52562f7a7..820e73e779720e4f76168e0a84a254ef645784ee 100644
--- a/paddle/fluid/operators/math/concat.cu
+++ b/paddle/fluid/operators/math/concat.cu
@@ -189,7 +189,7 @@ class ConcatGradFunctor<platform::CUDADeviceContext, T> {
  public:
   void operator()(const platform::CUDADeviceContext& context,
                   const framework::Tensor& input,
-                  const std::vector<const framework::Tensor*>& ref_inputs,
+                  const std::vector<const framework::LoDTensor*>& ref_inputs,
                   const int axis, std::vector<framework::Tensor*>* outputs) {
     // TODO(zcd): Add input data validity checking
     int o_num = outputs->size();
diff --git a/paddle/fluid/operators/math/concat.h b/paddle/fluid/operators/math/concat.h
index 9e080f2e8be23768dcea47b577043beef37b2eaf..e5d7d860b371677b3cfc67a57390bdee0d0ecc37 100644
--- a/paddle/fluid/operators/math/concat.h
+++ b/paddle/fluid/operators/math/concat.h
@@ -15,7 +15,7 @@ limitations under the License. */
 #pragma once
 #include <vector>
 #include "paddle/fluid/framework/data_type.h"
-#include "paddle/fluid/framework/tensor.h"
+#include "paddle/fluid/framework/lod_tensor.h"
 
 namespace paddle {
 namespace operators {
@@ -57,7 +57,7 @@ template <typename DeviceContext, typename T>
 class ConcatGradFunctor {
  public:
   void operator()(const DeviceContext& context, const framework::Tensor& input,
-                  const std::vector<const framework::Tensor*>& ref_inputs,
+                  const std::vector<const framework::LoDTensor*>& ref_inputs,
                   const int axis, std::vector<framework::Tensor*>* outputs);
 };
 
diff --git a/paddle/fluid/operators/sequence_softmax_op.h b/paddle/fluid/operators/sequence_softmax_op.h
index cb93a02b8386ed50ff176fc25b88449b7eb16902..bca564e16f9951519eefe25126aadebb4c1326b6 100644
--- a/paddle/fluid/operators/sequence_softmax_op.h
+++ b/paddle/fluid/operators/sequence_softmax_op.h
@@ -66,6 +66,9 @@ class SequenceSoftmaxGradKernel : public framework::OpKernel<T> {
     auto* out_grad = ctx.Input<LoDTensor>(framework::GradVarName("Out"));
     auto* x = ctx.Input<LoDTensor>("X");
     auto* x_grad = ctx.Output<LoDTensor>(framework::GradVarName("X"));
+    if (x_grad) {
+      x_grad->set_lod(x->lod());
+    }
 
     auto lod = x->lod();
     const size_t level = lod.size() - 1;