change the parameter topology of trainer to cost

Author: jacquesqiao

demo/mnist/api_train_v2.py

@@ -41,7 +41,7 @@ def event_handler(event):
 
     trainer.train(
         train_data_reader=train_reader,
-        topology=cost,
+        cost=cost,
         parameters=parameters,
         event_handler=event_handler,
         batch_size=32,  # batch size should be refactor in Data reader

python/paddle/v2/trainer.py

@@ -62,7 +62,7 @@ def __init__(self, update_equation):
 
     def train(self,
               train_data_reader,
-              topology,
+              cost,
               parameters,
               num_passes=1,
               test_data_reader=None,
@@ -73,7 +73,7 @@ def train(self,
         Training method. Will train num_passes of input data.
 
         :param train_data_reader:
-        :param topology: cost layers, use one or more Layers to represent it.
+        :param cost: cost layers, to be optimized.
         :param parameters: The parameter pools.
         :param num_passes: The total train passes.
         :param test_data_reader:
@@ -86,7 +86,7 @@ def train(self,
         if event_handler is None:
             event_handler = default_event_handler
 
-        topology = Topology(topology)
+        topology = Topology(cost)
 
         __check_train_args__(**locals())