diff --git a/PaddleCV/image_classification/models/resnet.py b/PaddleCV/image_classification/models/resnet.py
index d99181e82d909008fc5fc2aafea55439463e4820..b44a6192e798e7513fed0af2ee17023b4ef2aec6 100644
--- a/PaddleCV/image_classification/models/resnet.py
+++ b/PaddleCV/image_classification/models/resnet.py
@@ -105,7 +105,7 @@ class ResNet():
             num_filters=num_filters,
             filter_size=filter_size,
             stride=stride,
-            padding=(filter_size - 1) / 2,
+            padding=(filter_size - 1) // 2,
             groups=groups,
             act=None,
             param_attr=ParamAttr(name=name + "_weights"),
diff --git a/PaddleCV/image_classification/train.py b/PaddleCV/image_classification/train.py
index b18fdd4693cd3af4bf2ad6bb6f595a789d8aaeb9..0dc3f60616f723d438f5d073f4ee9ab692d2fcc0 100644
--- a/PaddleCV/image_classification/train.py
+++ b/PaddleCV/image_classification/train.py
@@ -40,7 +40,6 @@ add_arg('lr_strategy',      str,   "piecewise_decay",    "Set the learning rate
 add_arg('model',            str,   "SE_ResNeXt50_32x4d", "Set the network to use.")
 add_arg('enable_ce',        bool,  False,                "If set True, enable continuous evaluation job.")
 add_arg('data_dir',         str,   "./data/ILSVRC2012",  "The ImageNet dataset root dir.")
-add_arg('model_category',   str,   "models_name",        "Whether to use models_name or not, valid value:'models','models_name'." )
 add_arg('fp16',             bool,  False,                "Enable half precision training with fp16." )
 add_arg('scale_loss',       float, 1.0,                  "Scale loss for fp16." )
 add_arg('l2_decay',         float, 1e-4,                 "L2_decay parameter.")