diff --git a/paddle/operators/beam_search_op.cc b/paddle/operators/beam_search_op.cc
index 2e0513b37a24b..ed2e7b738acd8 100644
--- a/paddle/operators/beam_search_op.cc
+++ b/paddle/operators/beam_search_op.cc
@@ -39,7 +39,7 @@ void BeamSearch::operator()(const framework::LoDTensor &pre_ids,
 
   std::map<size_t /*offset*/, std::vector<Item>> hash;
   framework::LoD new_lod;
-  auto *ids_data = selected_ids->mutable_data<int>(platform::CPUPlace());
+  auto *ids_data = selected_ids->mutable_data<int64_t>(platform::CPUPlace());
   auto *scores_data =
       selected_scores->mutable_data<float>(platform::CPUPlace());
 
@@ -66,7 +66,7 @@ void BeamSearch::operator()(const framework::LoDTensor &pre_ids,
 
 void BeamSearch::PruneEndidCandidates(const framework::LoDTensor &pre_ids,
                                       std::vector<std::vector<Item>> *items) {
-  auto *pre_ids_data = pre_ids.data<int>();
+  auto *pre_ids_data = pre_ids.data<int64_t>();
 
   for (size_t offset = 0; offset < items->size(); offset++) {
     auto prefix_id = pre_ids_data[offset];
@@ -127,7 +127,7 @@ bool BeamSearch::NextItemSet(std::vector<BeamSearch::Item> *items) {
   auto abs_lod = framework::ToAbsOffset(ids.lod());
   PADDLE_ENFORCE_GE(source_abs_two_level_lod.size(), 2UL);
 
-  auto *ids_data = ids.data<int>();
+  auto *ids_data = ids.data<int64_t>();
   auto *scores_data = scores.data<float>();
 
   size_t instance_dim = 1;
diff --git a/python/paddle/v2/fluid/tests/test_beam_search_op.py b/python/paddle/v2/fluid/tests/test_beam_search_op.py
index 595f132fa85f0..319a7e49e35b0 100644
--- a/python/paddle/v2/fluid/tests/test_beam_search_op.py
+++ b/python/paddle/v2/fluid/tests/test_beam_search_op.py
@@ -37,13 +37,13 @@ def test_run(self):
         print 'lod', selected_ids.lod()
 
     def _create_pre_ids(self):
-        np_data = np.array([[1, 2, 3, 4]], dtype='int32')
+        np_data = np.array([[1, 2, 3, 4]], dtype='int64')
         tensor = create_tensor(self.scope, "pre_ids", np_data)
 
     def _create_ids(self):
         self.lod = [[0, 1, 4], [0, 1, 2, 3, 4]]
         np_data = np.array(
-            [[4, 2, 5], [2, 1, 3], [3, 5, 2], [8, 2, 1]], dtype='int32')
+            [[4, 2, 5], [2, 1, 3], [3, 5, 2], [8, 2, 1]], dtype='int64')
         tensor = create_tensor(self.scope, "ids", np_data)
         tensor.set_lod(self.lod)