diff --git a/fluid/PaddleCV/video/configs/attention_cluster.txt b/fluid/PaddleCV/video/configs/attention_cluster.txt
index c9c3037beddf457f47d2b5466a1547191d2ae02b..6a0d79f23c4b00638b830c7cb3a1b1df1996f735 100755
--- a/fluid/PaddleCV/video/configs/attention_cluster.txt
+++ b/fluid/PaddleCV/video/configs/attention_cluster.txt
@@ -1,7 +1,7 @@
 [MODEL]
 name = "AttentionCluster"
 dataset = "YouTube-8M"
-bone_nework = None
+bone_network = None
 drop_rate = 0.5
 feature_num = 2
 feature_names = ['rgb', 'audio']
diff --git a/fluid/PaddleCV/video/models/attention_cluster/logistic_model.py b/fluid/PaddleCV/video/models/attention_cluster/logistic_model.py
index 79c1a5f8b4029d84d6df8bccc18b0e73d5b4aa48..bbc3a803fe00235103606f0d3440f9b7269556dd 100755
--- a/fluid/PaddleCV/video/models/attention_cluster/logistic_model.py
+++ b/fluid/PaddleCV/video/models/attention_cluster/logistic_model.py
@@ -3,12 +3,10 @@ import paddle.fluid as fluid
 
 
 class LogisticModel(object):
-    """Logistic model with L2 regularization."""
-
+    """Logistic model."""
     def build_model(self,
                     model_input,
                     vocab_size,
-                    l2_penalty=None,
                     **unused_params):
         """Creates a logistic model.
 
diff --git a/fluid/PaddleCV/video/models/attention_cluster/shifting_attention.py b/fluid/PaddleCV/video/models/attention_cluster/shifting_attention.py
index 245a4465c03ecc45204fb68e177dce0918313e83..c67baca4122770e6183c52201479a2f9d05d5b33 100755
--- a/fluid/PaddleCV/video/models/attention_cluster/shifting_attention.py
+++ b/fluid/PaddleCV/video/models/attention_cluster/shifting_attention.py
@@ -18,7 +18,6 @@ class ShiftingAttentionModel(object):
         x_shape.stop_gradient = True
         flat_x = fluid.layers.reshape(x, shape=(-1, self.seg_num))
         flat_softmax = fluid.layers.softmax(flat_x)
-        # return fluid.layers.reshape(flat_softmax, shape=(x.shape[0], self.n_att, -1), actual_shape=x_shape)
         return fluid.layers.reshape(
             flat_softmax, shape=x.shape, actual_shape=x_shape)