diff --git a/ctr/README.md b/ctr/README.md
index 80053d565eea65d460603c030bcc9fed689d3d70..3ed09385fa1d57d7a429b21b6f8abba1c8bde37f 100644
--- a/ctr/README.md
+++ b/ctr/README.md
@@ -117,12 +117,12 @@ Deep 部分使用了标准的多层前向传导的 NN 模型
 def build_dnn_submodel(dnn_layer_dims):
     dnn_embedding = layer.fc(input=dnn_merged_input, size=dnn_layer_dims[0])
     _input_layer = dnn_embedding
-    for no, dim in enumerate(dnn_layer_dims[1:]):
+    for i, dim in enumerate(dnn_layer_dims[1:]):
         fc = layer.fc(
             input=_input_layer,
             size=dim,
             act=paddle.activation.Relu(),
-            name='dnn-fc-%d' % no)
+            name='dnn-fc-%d' % i)
         _input_layer = fc
     return _input_layer
 ```
diff --git a/ctr/train.py b/ctr/train.py
index 7525c80295345e8e08b6ac6112edcdeb86b03eeb..53536d999b2c8851458598b4a5b4414ac45fda25 100644
--- a/ctr/train.py
+++ b/ctr/train.py
@@ -40,12 +40,12 @@ click = paddle.layer.data(name='click', type=dtype.dense_vector(1))
 def build_dnn_submodel(dnn_layer_dims):
     dnn_embedding = layer.fc(input=dnn_merged_input, size=dnn_layer_dims[0])
     _input_layer = dnn_embedding
-    for no, dim in enumerate(dnn_layer_dims[1:]):
+    for i, dim in enumerate(dnn_layer_dims[1:]):
         fc = layer.fc(
             input=_input_layer,
             size=dim,
             act=paddle.activation.Relu(),
-            name='dnn-fc-%d' % no)
+            name='dnn-fc-%d' % i)
         _input_layer = fc
     return _input_layer