fix lr mult

ppcls/modeling/architectures/resnet_vd.py

-#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
 #
-#Licensed under the Apache License, Version 2.0 (the "License");
-#you may not use this file except in compliance with the License.
-#You may obtain a copy of the License at
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
 #
 #    http://www.apache.org/licenses/LICENSE-2.0
 #
-#Unless required by applicable law or agreed to in writing, software
-#distributed under the License is distributed on an "AS IS" BASIS,
-#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#See the License for the specific language governing permissions and
-#limitations under the License.
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 
 from __future__ import absolute_import
 from __future__ import division
@@ -49,7 +49,8 @@ class ResNet():
         layers = self.layers
         supported_layers = [18, 34, 50, 101, 152, 200]
         assert layers in supported_layers, \
-            "supported layers are {} but input layer is {}".format(supported_layers, layers)
+            "supported layers are {} but input layer is {}".format(
+                supported_layers, layers)
 
         if layers == 18:
             depth = [2, 2, 2, 2]
@@ -159,7 +160,9 @@ class ResNet():
             padding=(filter_size - 1) // 2,
             groups=groups,
             act=None,
-            param_attr=ParamAttr(name=name + "_weights" + self.postfix_name),
+            param_attr=ParamAttr(
+                name=name + "_weights" + self.postfix_name,
+                learning_rate=lr_mult),
             bias_attr=False)
         if name == "conv1":
             bn_name = "bn_" + name
@@ -168,8 +171,12 @@ class ResNet():
         return fluid.layers.batch_norm(
             input=conv,
             act=act,
-            param_attr=ParamAttr(name=bn_name + '_scale' + self.postfix_name),
-            bias_attr=ParamAttr(bn_name + '_offset' + self.postfix_name),
+            param_attr=ParamAttr(
+                name=bn_name + '_scale' + self.postfix_name,
+                learning_rate=lr_mult),
+            bias_attr=ParamAttr(
+                bn_name + '_offset' + self.postfix_name,
+                learning_rate=lr_mult),
             moving_mean_name=bn_name + '_mean' + self.postfix_name,
             moving_variance_name=bn_name + '_variance' + self.postfix_name)