diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc
index 82e5df591d0e596831d409aadbc816bb8e59d18e..f07dd8f602cda2ba1ef02e6c6b736018288bbd9f 100644
--- a/paddle/operators/rowwise_add_op.cc
+++ b/paddle/operators/rowwise_add_op.cc
@@ -63,6 +63,7 @@ class RowwiseAddGradOp : public framework::OperatorWithKernel {
                             "Input(Out@GRAD) should not be null");
     auto dims0 = ctx.Input<Tensor>("X")->dims();
     auto dims1 = ctx.Input<Tensor>("b")->dims();
+    PADDLE_ENFORCE_EQ(1, framework::product(dims1), "b dims should be 1")
     ctx.Output<Tensor>(framework::GradVarName("X"))->Resize(dims0);
     ctx.Output<Tensor>(framework::GradVarName("b"))->Resize(dims1);
   }
diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py
index 8118d2d7418ed74dea6cf03bf820f97d17b8995d..29d72e850099734a9828ccceed47cc0a57fc3d6b 100644
--- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py
+++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py
@@ -21,12 +21,10 @@ class RowwiseAddGradOpTest(GradientChecker):
         op = create_op("rowwise_add")
         inputs = {
             "X": np.random.uniform(0.1, 1, [10, 10]).astype("float32"),
-            "b": np.random.uniform(0.1, 1, [10, 1]).astype("float32")
+            "b": np.random.uniform(0.1, 1, [10]).astype("float32")
         }
         self.check_grad(op, inputs, set(["X", "b"]), "Out")
 
 
-#TODO(dzh): rowwise_grad check
-
 if __name__ == '__main__':
     unittest.main()