diff --git a/paddle/operators/elementwise_op_function.h b/paddle/operators/elementwise_op_function.h
index 3eb97f60b59848d23bcd15ea1e3d2f21b721f6a4..488a35aafc8600bb8bb252fc3a5161c72a2f6df1 100644
--- a/paddle/operators/elementwise_op_function.h
+++ b/paddle/operators/elementwise_op_function.h
@@ -108,7 +108,7 @@ void ElementwiseCompute(const framework::ExecutionContext& ctx) {
   PADDLE_ENFORCE_GE(x_dims.size(), y_dims.size(),
                     "Rank of first input must >= rank of second input.")
 
-  if (x_dims == y_dims || product(y_dims) == 1) {
+  if (x_dims == y_dims) {
     functor f;
     f.template Run<Place, T>(x, y, z, ctx);
     return;
@@ -174,12 +174,6 @@ void ElementwiseGradCompute(const framework::ExecutionContext& ctx) {
     return;
   }
 
-  if (product(y_dims) == 1) {
-    functor1 f;
-    f(place, x, y, out, dx, dy, dout);
-    return;
-  }
-
   int axis = ctx.Attr<int>("axis");
   axis = (axis == -1 ? x_dims.size() - y_dims.size() : axis);
 
diff --git a/python/paddle/v2/framework/tests/test_elementwise_add_op.py b/python/paddle/v2/framework/tests/test_elementwise_add_op.py
index f3101a709b8bcf58e8682ab3d0ca5217a7f3572d..57daddd5698f77527bc5b78c436065a851867ae0 100644
--- a/python/paddle/v2/framework/tests/test_elementwise_add_op.py
+++ b/python/paddle/v2/framework/tests/test_elementwise_add_op.py
@@ -92,5 +92,33 @@ class TestElementwiseAddOp_broadcast_3(TestElementwiseOp):
         }
 
 
+class TestElementwiseAddOp_rowwise_add_0(TestElementwiseOp):
+    def setUp(self):
+        self.op_type = "elementwise_add"
+        self.inputs = {
+            'X': np.random.rand(2, 3, 4).astype(np.float32),
+            'Y': np.random.rand(3, 4).astype(np.float32)
+        }
+
+        self.attrs = {'axis': 1}
+        self.outputs = {
+            'Out': self.inputs['X'] + self.inputs['Y'].reshape(1, 3, 4)
+        }
+
+
+class TestElementwiseAddOp_rowwise_add_1(TestElementwiseOp):
+    def setUp(self):
+        self.op_type = "elementwise_add"
+        self.inputs = {
+            'X': np.random.rand(2, 1).astype(np.float32),
+            'Y': np.random.rand(1).astype(np.float32)
+        }
+
+        self.attrs = {'axis': 1}
+        self.outputs = {
+            'Out': self.inputs['X'] + self.inputs['Y'].reshape(1, 1)
+        }
+
+
 if __name__ == '__main__':
     unittest.main()