Fix slow parsing a recursive depends topology

* Fix  #2797
* It because trainer_config_helpers' __dfs_travel__ did not record the
  node which travelled, and if the topology has a recursive dependency,
  there are some nodes will be travelled multiple times.
* Add a `travelled` set to record which node is travelled.
* Also add a unittest for this situation.

python/paddle/trainer_config_helpers/networks.py

@@ -1408,6 +1408,8 @@ def outputs(layers, *args):
     :return:
     """
 
+    traveled = set()
+
     def __dfs_travel__(layer,
                        predicate=lambda x: x.layer_type == LayerType.DATA):
         """
@@ -1419,6 +1421,11 @@ def outputs(layers, *args):
         :type layer: LayerOutput
         :return:
         """
+        if layer in traveled:
+            return []
+        else:
+            traveled.add(layer)
+
         assert isinstance(layer, LayerOutput), "layer is %s" % (layer)
         retv = []
         if layer.parents is not None:

python/paddle/trainer_config_helpers/tests/configs/file_list.sh

@@ -6,6 +6,7 @@ img_layers img_trans_layers util_layers simple_rnn_layers unused_layers test_cos
 test_rnn_group shared_fc shared_lstm shared_gru test_cost_layers_with_weight
 test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops
 test_seq_concat_reshape test_pad test_smooth_l1 test_multiplex_layer
-test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer)
+test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer
+test_recursive_topology)
 
 export whole_configs=(test_split_datasource)

python/paddle/trainer_config_helpers/tests/configs/protostr/test_cost_layers_with_weight.protostr

@@ -131,6 +131,7 @@ input_layer_names: "weight"
 input_layer_names: "multi_class_label"
 output_layer_names: "__cost_0__"
 output_layer_names: "__mse_cost_0__"
+output_layer_names: "__nce_layer_0__"
 evaluators {
   name: "classification_error_evaluator"
   type: "classification_error"
@@ -154,6 +155,7 @@ sub_models {
   input_layer_names: "multi_class_label"
   output_layer_names: "__cost_0__"
   output_layer_names: "__mse_cost_0__"
+  output_layer_names: "__nce_layer_0__"
   evaluator_names: "classification_error_evaluator"
   is_recurrent_layer_group: false
 }

python/paddle/trainer_config_helpers/tests/configs/test_recursive_topology.py

@@ -0,0 +1,16 @@
+from paddle.trainer_config_helpers import *
+
+settings(batch_size=1000, learning_rate=1e-5)
+
+din = data_layer(name='data', size=100)
+
+enc = din
+for i in range(32):
+    enc = addto_layer([enc, enc])
+
+pred = fc_layer(
+    input=fc_layer(
+        input=enc, size=32, act=ReluActivation()),
+    size=10,
+    act=SoftmaxActivation())
+outputs(pred)