diff --git a/paddleslim/prune/pruner.py b/paddleslim/prune/pruner.py
index cd79f5b286bbb34d1d688ce515691fdfc7e8f730..21b66a2ac9f1bc4c4acbcf668ef09cdba2b2148a 100644
--- a/paddleslim/prune/pruner.py
+++ b/paddleslim/prune/pruner.py
@@ -12,13 +12,17 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import logging
 import numpy as np
 import paddle.fluid as fluid
 import copy
 from ..core import VarWrapper, OpWrapper, GraphWrapper
+from ..common import get_logger
 
 __all__ = ["Pruner"]
 
+_logger = get_logger(__name__, level=logging.INFO)
+
 
 class Pruner():
     def __init__(self, criterion="l1_norm"):
@@ -69,6 +73,10 @@ class Pruner():
             only_graph=only_graph,
             param_backup=param_backup,
             param_shape_backup=param_shape_backup)
+        for op in graph.ops():
+            if op.type() == 'depthwise_conv2d' or op.type(
+            ) == 'depthwise_conv2d_grad':
+                op.set_attr('groups', op.inputs('Filter')[0].shape()[0])
         return graph.program
 
     def _prune_filters_by_ratio(self,
@@ -113,6 +121,8 @@ class Pruner():
             new_shape = list(param.shape())
             new_shape[0] = pruned_param.shape[0]
             param.set_shape(new_shape)
+            _logger.info("prune [{}] from {} to {}".format(param.name(
+            ), ori_shape, new_shape))
             self.pruned_list[0].append(param.name())
         return pruned_idx
 
@@ -158,6 +168,8 @@ class Pruner():
             new_shape = list(param.shape())
             new_shape[pruned_axis] = pruned_param.shape[pruned_axis]
             param.set_shape(new_shape)
+            _logger.info("prune [{}] from {} to {}".format(param.name(
+            ), ori_shape, new_shape))
             self.pruned_list[pruned_axis].append(param.name())
 
     def _forward_search_related_op(self, graph, param):