Fix code style and CI errors.

.pre-commit-config.yaml

@@ -3,7 +3,7 @@
     hooks:
     -   id: remove-crlf
         files: (?!.*third_party)^.*$ | (?!.*book)^.*$
--   repo: https://github.com/reyoung/mirrors-yapf.git
+-   repo: https://github.com/pre-commit/mirrors-yapf.git
     sha: v0.13.2
     hooks:
     -   id: yapf

paddle/function/BufferArgTest.cpp

@@ -12,8 +12,8 @@ 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. */
 
-#include "BufferArg.h"
 #include <gtest/gtest.h>
+#include "BufferArg.h"
 #include "paddle/math/MemoryHandle.h"
 
 namespace paddle {

paddle/function/FunctionTest.cpp

@@ -12,8 +12,8 @@ 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. */
 
-#include "Function.h"
 #include <gtest/gtest.h>
+#include "Function.h"
 #include "paddle/math/SparseMatrix.h"
 
 namespace paddle {

paddle/function/TensorShapeTest.cpp

@@ -12,8 +12,8 @@ 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. */
 
-#include "TensorShape.h"
 #include <gtest/gtest.h>
+#include "TensorShape.h"
 
 namespace paddle {
 

paddle/function/TensorTypeTest.cpp

@@ -12,8 +12,8 @@ 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. */
 
-#include "TensorType.h"
 #include <gtest/gtest.h>
+#include "TensorType.h"
 
 namespace paddle {
 

python/paddle/trainer_config_helpers/config_parser_utils.py

@@ -15,7 +15,6 @@
 import copy
 import paddle.trainer.config_parser as config_parser
 from paddle.proto.TrainerConfig_pb2 import OptimizationConfig
-
 '''
 This file is a wrapper of formal config_parser. The main idea of this file is to
 separete different config logic into different function, such as network configuration

python/paddle/trainer_config_helpers/networks.py

@@ -1404,7 +1404,7 @@ def inputs(layers, *args):
     if len(args) != 0:
         layers.extend(args)
 
-    Inputs(*[l.name for l in layers])
+    Inputs(* [l.name for l in layers])
 
 
 def outputs(layers, *args):
@@ -1447,7 +1447,7 @@ def __dfs_travel__(layer,
     assert len(layers) > 0
 
     if HasInputsSet():  # input already set
-        Outputs(*[l.name for l in layers])
+        Outputs(* [l.name for l in layers])
         return  # just return outputs.
 
     if len(layers) != 1:

python/paddle/v2/layer.py

@@ -40,6 +40,7 @@
 __all__ = ['data', 'parse_network']
 __layer_map__ = {}
 
+
 def __wrap__(f):
     def wrapped(*args, **xargs):
         out = f(*args, **xargs)
@@ -53,6 +54,7 @@ def wrapped(*args, **xargs):
 
     return wrapped
 
+
 def __need_to_keep__(name):
     if name in ['StaticInput', 'LayerType', 'layer_support']:
         return False
@@ -99,6 +101,7 @@ def __data_layer__(name, type, **kwargs):
     l.data_type = type
     return l
 
+
 data = __wrap__(__data_layer__)
 
 LayerV2 = v1_layers.LayerOutput
@@ -107,6 +110,7 @@ def __data_layer__(name, type, **kwargs):
 def __get_used_layers__(output_layers, extra_layers=None):
     layer_names = set()
     parents = {}
+
     def add_parent(child, parent):
         if child in parents:
             parents[child].append(parent)
@@ -181,28 +185,25 @@ def __get_used_evaluators__(layer_names):
     return evaluator_names
 
 
-def __trim_submodel__(old_submodel,
-                      layer_names,
-                      input_layer_names,
-                      output_layer_names,
-                      evaluator_names):
+def __trim_submodel__(old_submodel, layer_names, input_layer_names,
+                      output_layer_names, evaluator_names):
 
     submodel = SubModelConfig()
     submodel.name = old_submodel.name
-    submodel.layer_names.extend(filter(lambda x: x in layer_names,
-                                       old_submodel.layer_names))
-    submodel.input_layer_names.extend(filter(lambda x: x in input_layer_names,
-                                             submodel.layer_names))
-    submodel.output_layer_names.extend(filter(lambda x: x in output_layer_names,
-                                              submodel.layer_names))
-    submodel.evaluator_names.extend(filter(lambda x: x in evaluator_names,
-                                           old_submodel.evaluator_names))
+    submodel.layer_names.extend(
+        filter(lambda x: x in layer_names, old_submodel.layer_names))
+    submodel.input_layer_names.extend(
+        filter(lambda x: x in input_layer_names, submodel.layer_names))
+    submodel.output_layer_names.extend(
+        filter(lambda x: x in output_layer_names, submodel.layer_names))
+    submodel.evaluator_names.extend(
+        filter(lambda x: x in evaluator_names, old_submodel.evaluator_names))
 
     submodel.is_recurrent_layer_group = old_submodel.is_recurrent_layer_group
     submodel.reversed = old_submodel.reversed
 
-    submodel.memories.extend(filter(lambda x: x.link_name in layer_names,
-                                    old_submodel.memories))
+    submodel.memories.extend(
+        filter(lambda x: x.link_name in layer_names, old_submodel.memories))
     target_inlinkid = (old_submodel.target_inlinkid
                        if old_submodel.HasField('target_inlinkid') else -1)
     in_links = []
@@ -213,8 +214,8 @@ def __trim_submodel__(old_submodel,
                 target_inlinkid = len(in_links) - 1
     submodel.in_links.extend(in_links)
 
-    submodel.out_links.extend(filter(lambda x: x.link_name in layer_names,
-                                     old_submodel.out_links))
+    submodel.out_links.extend(
+        filter(lambda x: x.link_name in layer_names, old_submodel.out_links))
     if old_submodel.HasField('generator'):
         submodel.generator.CopyFrom(old_submodel.generator)
 
@@ -264,9 +265,8 @@ def parse_network(output_layers, extra_layers=None):
 
     for s in cp.g_config.model_config.sub_models:
         if s.name in submodel_names:
-            s = __trim_submodel__(
-                s, layer_names, input_layer_names, output_layer_names,
-                evaluator_names)
+            s = __trim_submodel__(s, layer_names, input_layer_names,
+                                  output_layer_names, evaluator_names)
             model_config.sub_models.extend([s])
 
     return model_config

python/paddle/v2/tests/test_rnn_layer.py

@@ -32,6 +32,7 @@ def test_simple_rnn(self):
 
         def parse_old_rnn():
             reset_parser()
+
             def step(y):
                 mem = conf_helps.memory(name="rnn_state", size=hidden_dim)
                 out = conf_helps.fc_layer(
@@ -52,6 +53,7 @@ def test():
 
         def parse_new_rnn():
             reset_parser()
+
             def new_step(y):
                 mem = layer.memory(name="rnn_state", size=hidden_dim)
                 out = layer.fc(input=[y, mem],
@@ -72,7 +74,6 @@ def new_step(y):
                                     parse_new_rnn().splitlines(1))
         print ''.join(diff)
 
-
     def test_sequence_rnn_multi_input(self):
         dict_dim = 10
         word_dim = 8
@@ -81,6 +82,7 @@ def test_sequence_rnn_multi_input(self):
 
         def parse_old_rnn():
             reset_parser()
+
             def test():
                 data = conf_helps.data_layer(name="word", size=dict_dim)
                 label = conf_helps.data_layer(name="label", size=label_dim)