diff --git a/paddle/fluid/pybind/op_function_generator.cc b/paddle/fluid/pybind/op_function_generator.cc
index fc60b6302e7ab0ab155e5430ccb8f0a4ba0e94b1..89ebb925363f57d68bb47b9e3b5fd133f8496811 100644
--- a/paddle/fluid/pybind/op_function_generator.cc
+++ b/paddle/fluid/pybind/op_function_generator.cc
@@ -52,6 +52,9 @@ std::map<std::string, std::set<std::string>> op_ins_map = {
 std::map<std::string, std::set<std::string>> op_outs_map = {
     {"fake_quantize_dequantize_moving_average_abs_max",
      {"Out", "OutScale", "OutAccum", "OutState"}},
+    {"batch_norm",
+     {"Y", "MeanOut", "VarianceOut", "SavedMean", "SavedVariance",
+      "ReserveSpace"}},
 };
 
 // NOTE(zhiqiu): Commonly, the outputs in auto-generated OP function are
diff --git a/python/paddle/fluid/dygraph/nn.py b/python/paddle/fluid/dygraph/nn.py
index 7cb4702fedcbac9a3dd8fc7bb941735a1cfbe435..680e47bf4221c6168c337821e0ef1826f200636e 100644
--- a/python/paddle/fluid/dygraph/nn.py
+++ b/python/paddle/fluid/dygraph/nn.py
@@ -1310,9 +1310,10 @@ class BatchNorm(layers.Layer):
                      self._fuse_with_relu, "use_global_stats",
                      self._use_global_stats, 'trainable_statistics',
                      self._trainable_statistics)
-            batch_norm_out, _, _, _, _ = core.ops.batch_norm(
+            batch_norm_out, _, _, _, _, _ = core.ops.batch_norm(
                 input, self.weight, self.bias, self._mean, self._variance,
                 mean_out, variance_out, *attrs)
+
             return dygraph_utils._append_activation_in_dygraph(
                 batch_norm_out, act=self._act)