diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index dd6d1f7f8c683b71d86514df41fc47f1c1ea57f6..be854c38f76af4cd6d5f628785b3e4dbfc6ebacb 100755
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -2589,7 +2589,7 @@ def img_pool_layer(input,
 
     assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling,
                                CudnnMaxPooling], \
-        "only AvgPooling and MaxPooling are supported"
+        "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported"
 
     if pool_type is None:
         pool_type = MaxPooling()
@@ -6236,11 +6236,11 @@ def kmax_sequence_score_layer(input, name=None, beam_size=1):
 @wrap_bias_attr_default()
 def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None):
     """
-    A layer applies a linear transformation to each element in each row of 
-    the input matrix. For each element, the layer first re-scale it and then 
+    A layer applies a linear transformation to each element in each row of
+    the input matrix. For each element, the layer first re-scale it and then
     adds a bias to it.
 
-    This layer is very like the SlopeInterceptLayer, except the scale and 
+    This layer is very like the SlopeInterceptLayer, except the scale and
     bias are trainable.
 
     .. math::