diff --git a/ppcls/modeling/architectures/regnet.py b/ppcls/modeling/architectures/regnet.py
index 8c2ec57e8eedf279260cae6c0eff6ec9bec6fa91..19ddaaad1b1ed3ebcc6557bcb19c753f8f33c50f 100644
--- a/ppcls/modeling/architectures/regnet.py
+++ b/ppcls/modeling/architectures/regnet.py
@@ -144,7 +144,7 @@ class BottleneckBlock(nn.Layer):
             self.se_block = SELayer(
                 num_channels=w_b,
                 num_filters=w_b,
-                reduction_channels=w_se,
+                reduction_ratio=w_se,
                 name=name + "_branch2se")
         self.conv2 = ConvBNLayer(
             num_channels=w_b,
diff --git a/ppcls/modeling/architectures/vgg.py b/ppcls/modeling/architectures/vgg.py
index 06ba8d08c323da0a1c1d6bcfcca104817085885d..25398603390873b15b1c0e6e6ec1cb98c43a93fa 100644
--- a/ppcls/modeling/architectures/vgg.py
+++ b/ppcls/modeling/architectures/vgg.py
@@ -80,7 +80,7 @@ class VGGNet(nn.Layer):
         }
         assert self.layers in self.vgg_configure.keys(), \
             "supported layers are {} but input layer is {}".format(
-                vgg_configure.keys(), layers)
+                self.vgg_configure.keys(), layers)
         self.groups = self.vgg_configure[self.layers]
 
         self._conv_block_1 = ConvBlock(3, 64, self.groups[0], name="conv1_")
diff --git a/ppcls/modeling/architectures/xception.py b/ppcls/modeling/architectures/xception.py
index 61c87ab4a11e07da806e75682d9f0447740ad5b7..3964fedbe1833857b66145594fa0dfaf3b86a2d5 100644
--- a/ppcls/modeling/architectures/xception.py
+++ b/ppcls/modeling/architectures/xception.py
@@ -6,6 +6,7 @@ from paddle.nn import Conv2D, BatchNorm, Linear, Dropout
 from paddle.nn import AdaptiveAvgPool2D, MaxPool2D, AvgPool2D
 from paddle.nn.initializer import Uniform
 import math
+import sys
 
 __all__ = ['Xception41', 'Xception65', 'Xception71']