diff --git a/paddle/gserver/layers/CrossEntropyOverBeam.cpp b/paddle/gserver/layers/CrossEntropyOverBeam.cpp
index 500cd6ff8ccc6..bffcc30154370 100644
--- a/paddle/gserver/layers/CrossEntropyOverBeam.cpp
+++ b/paddle/gserver/layers/CrossEntropyOverBeam.cpp
@@ -39,7 +39,6 @@ void CostForOneSequence::calValidExpandStep() {
     if (start + beamSize_ == findEnd) return;
     goldColIds_[i] = findEnd - start;
   }
-
   if (goldColIds_[beams_->expansionCount - 1] != -1) goldAsExtraPath_ = false;
 }
 
diff --git a/python/paddle/v2/inference.py b/python/paddle/v2/inference.py
index 4dcc3ab57e7e6..8acea6155c588 100644
--- a/python/paddle/v2/inference.py
+++ b/python/paddle/v2/inference.py
@@ -70,7 +70,7 @@ def iter_infer_field(self, field, **kwargs):
                 item = [each_result[each_field] for each_field in field]
                 yield item
 
-    def infer(self, input, field='value', **kwargs):
+    def infer(self, input, field='value', flatten_result=True, **kwargs):
         """
         Infer a data by model.
         :param input: input data batch. Should be python iterable object.
@@ -83,7 +83,10 @@ def infer(self, input, field='value', **kwargs):
                 retv = [[] for i in xrange(len(result))]
             for i, item in enumerate(result):
                 retv[i].append(item)
-        retv = [numpy.concatenate(out) for out in retv]
+
+        if flatten_result:
+            retv = [numpy.concatenate(out) for out in retv]
+
         if len(retv) == 1:
             return retv[0]
         else: