diff --git a/python/paddle/v2/fluid/average.py b/python/paddle/v2/fluid/average.py
new file mode 100644
index 0000000000000000000000000000000000000000..ded6eb085968343fcdc9f6e4b8353c08408df426
--- /dev/null
+++ b/python/paddle/v2/fluid/average.py
@@ -0,0 +1,61 @@
+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import numpy as np
+"""
+    Class of all kinds of Average.
+
+    All Averages are accomplished via Python totally. 
+    They do not change Paddle's Program, nor do anything to
+    modify NN model's configuration. They are completely 
+    wrappers of Python functions.
+"""
+
+
+def _is_number_(var):
+    return isinstance(var, int) or isinstance(var, float) or (isinstance(
+        var, np.ndarray) and var.shape == (1, ))
+
+
+def _is_number_or_matrix_(var):
+    return _is_number_(var) or isinstance(var, np.ndarray)
+
+
+class WeightedAverage(object):
+    def __init__(self):
+        self.reset()
+
+    def reset(self):
+        self.numerator = None
+        self.denominator = None
+
+    def add(self, value, weight):
+        if not _is_number_or_matrix_(value):
+            raise ValueError(
+                "The 'value' must be a number(int, float) or a numpy ndarray.")
+        if not _is_number_(weight):
+            raise ValueError("The 'weight' must be a number(int, float).")
+
+        if self.numerator is None or self.denominator is None:
+            self.numerator = value * weight
+            self.denominator = weight
+        else:
+            self.numerator += value * weight
+            self.denominator += weight
+
+    def eval(self):
+        if self.numerator is None or self.denominator is None:
+            raise ValueError(
+                "There is no data to be averaged in WeightedAverage.")
+        return self.numerator / self.denominator
diff --git a/python/paddle/v2/fluid/layers/nn.py b/python/paddle/v2/fluid/layers/nn.py
index f090288aa8db2f3fc4f8f757b013281b8c83aba7..4a47d3f425f716ea6ad215ff0e4b66330b75ce2f 100644
--- a/python/paddle/v2/fluid/layers/nn.py
+++ b/python/paddle/v2/fluid/layers/nn.py
@@ -3161,7 +3161,7 @@ def smooth_l1(x, y, inside_weight=None, outside_weight=None, sigma=None):
             data = fluid.layers.data(name='data', shape=[128], dtype='float32')
             label = fluid.layers.data(name='label', shape=[100], dtype='int64')
             fc = fluid.layers.fc(input=data, size=100)
-            out = fluid.layers.smooth_l1(logits=fc, label=label)
+            out = fluid.layers.smooth_l1(x=fc, y=label)
     """
     helper = LayerHelper('smooth_l1_loss', **locals())
     diff = helper.create_tmp_variable(dtype=x.dtype)