diff --git a/ppcls/modeling/architectures/resnet.py b/ppcls/modeling/architectures/resnet.py
index 2d46772b5d78ef72d4d859b622d1c961769a5859..f6227053c74eb1672634fc5cfcbb2e12f6a3cfc1 100644
--- a/ppcls/modeling/architectures/resnet.py
+++ b/ppcls/modeling/architectures/resnet.py
@@ -19,6 +19,7 @@ from __future__ import print_function
 import numpy as np
 import paddle
 from paddle import ParamAttr
+# from paddle.fluid.param_attr import ParamAttr
 import paddle.nn as nn
 from paddle.nn import Conv2d, Pool2D, BatchNorm, Linear, Dropout
 
@@ -39,14 +40,13 @@ class ConvBNLayer(nn.Layer):
         super(ConvBNLayer, self).__init__()
 
         self._conv = Conv2d(
-            num_channels=num_channels,
-            num_filters=num_filters,
-            filter_size=filter_size,
+            in_channels=num_channels,
+            out_channels=num_filters,
+            kernel_size=filter_size,
             stride=stride,
             padding=(filter_size - 1) // 2,
             groups=groups,
-            act=None,
-            param_attr=ParamAttr(name=name + "_weights"),
+            weight_attr=ParamAttr(name=name + "_weights"),
             bias_attr=False)
         if name == "conv1":
             bn_name = "bn_" + name
@@ -248,8 +248,8 @@ class ResNet(nn.Layer):
         self.out = Linear(
             self.pool2d_avg_channels,
             class_dim,
-            param_attr=ParamAttr(
-                initializer=paddle.distribution.Uniform(-stdv, stdv),
+            weight_attr=ParamAttr(
+                initializer=paddle.nn.initializer.Uniform(-stdv, stdv),
                 name="fc_0.w_0"),
             bias_attr=ParamAttr(name="fc_0.b_0"))