Fix the code style problem. test=develop

paddleslim/prune/prune_walker.py

@@ -23,7 +23,7 @@ _logger = get_logger(__name__, level=logging.INFO)
 
 PRUNE_WORKER = Registry('prune_worker')
 
-SKIP_OPS = ["conditional_block","shape","reshape2"]
+SKIP_OPS = ["conditional_block", "shape", "reshape2"]
 
 
 class PruneWorker(object):
@@ -643,6 +643,7 @@ class roi_align(PruneWorker):
         for op in next_ops:
             self._prune_op(op, out_var, pruned_axis, pruned_idx)
 
+
 @PRUNE_WORKER.register
 class lod_reset(PruneWorker):
     def __init__(self, op, pruned_params, visited={}):
@@ -661,10 +662,12 @@ class lod_reset(PruneWorker):
         for op in next_ops:
             self._prune_op(op, out_var, pruned_axis, pruned_idx)
 
+
 @PRUNE_WORKER.register
 class gather(PruneWorker):
     def __init__(self, op, pruned_params, visited):
         super(gather, self).__init__(op, pruned_params, visited)
+
     def _prune(self, var, pruned_axis, pruned_idx):
         if var in self.op.outputs("Out"):
             in_var = self.op.inputs("X")[0]

tests/test_add_ops.py

@@ -42,21 +42,22 @@ class TestPrune(unittest.TestCase):
             conv3 = conv_bn_layer(sum1, 8, 3, "conv3")
             conv4 = conv_bn_layer(conv3, 8, 3, "conv4")
             sum2 = conv4 + sum1
-            #test roi_align
-            rois = fluid.data(
-                name='rois', shape=[None, 4], dtype='float32')
-            align_out = fluid.layers.roi_align(input=sum2,
+            # test roi_align
+            rois = fluid.data(name='rois', shape=[None, 4], dtype='float32')
+            align_out = fluid.layers.roi_align(
+                input=sum2,
                 rois=rois,
                 pooled_height=7,
                 pooled_width=7,
                 spatial_scale=0.5,
                 sampling_ratio=-1)
             conv5 = conv_bn_layer(align_out, 8, 3, "conv5")
-            #test gather
-            index = fluid.layers.data(name='index', shape=[-1, 1], dtype='int32')
+            # test gather
+            index = fluid.layers.data(
+                name='index', shape=[-1, 1], dtype='int32')
             gather_out = fluid.layers.gather(sum2, index)
             conv6 = conv_bn_layer(gather_out, 8, 3, "conv6")
-            #test lod_reset
+            # test lod_reset
             y = fluid.layers.data(name='y', shape=[6], lod_level=2)
             lodset_out = fluid.layers.lod_reset(x=sum2, y=y)
             conv7 = conv_bn_layer(lodset_out, 8, 3, "conv7")