Make api_train_v2 runnable

demo/mnist/api_train_v2.py

@@ -20,7 +20,7 @@ def main():
 
     adam_optimizer = paddle.optimizer.Adam(learning_rate=0.01)
 
-    trainer = paddle.trainer.SGD(topology=cost,
+    trainer = paddle.trainer.SGD(cost=cost,
                                  parameters=parameters,
                                  update_equation=adam_optimizer)
 
@@ -28,7 +28,7 @@ def main():
         if isinstance(event, paddle.event.EndIteration):
             if event.batch_id % 1000 == 0:
                 result = trainer.test(reader=paddle.reader.batched(
-                    paddle.dataset.mnist.test_creator(), batch_size=256))
+                    paddle.dataset.mnist.test(), batch_size=256))
 
                 print "Pass %d, Batch %d, Cost %f, %s, Testing metrics %s" % (
                     event.pass_id, event.batch_id, event.cost, event.metrics,

python/paddle/v2/dataset/mnist.py

@@ -9,9 +9,9 @@ __all__ = ['train', 'test']
 
 URL_PREFIX = 'http://yann.lecun.com/exdb/mnist/'
 TEST_IMAGE_URL = URL_PREFIX + 't10k-images-idx3-ubyte.gz'
-TEST_IMAGE_MD5 = '25e3cc63507ef6e98d5dc541e8672bb6'
+TEST_IMAGE_MD5 = '9fb629c4189551a2d022fa330f9573f3'
 TEST_LABEL_URL = URL_PREFIX + 't10k-labels-idx1-ubyte.gz'
-TEST_LABEL_MD5 = '4e9511fe019b2189026bd0421ba7b688'
+TEST_LABEL_MD5 = 'ec29112dd5afa0611ce80d1b7f02629c'
 TRAIN_IMAGE_URL = URL_PREFIX + 'train-images-idx3-ubyte.gz'
 TRAIN_IMAGE_MD5 = 'f68b3c2dcbeaaa9fbdd348bbdeb94873'
 TRAIN_LABEL_URL = URL_PREFIX + 'train-labels-idx1-ubyte.gz'

python/paddle/v2/trainer.py

@@ -61,7 +61,7 @@ class SGD(ITrainer):
         self.__topology__ = topology
         self.__parameters__ = parameters
         self.__topology_in_proto__ = topology.proto()
-        self.__data_types__ = topology.data_layers()
+        self.__data_types__ = topology.data_type()
         gm = api.GradientMachine.createFromConfigProto(
             self.__topology_in_proto__, api.CREATE_MODE_NORMAL,
             self.__optimizer__.enable_types())