add v2 run logic doc

Author: QiJune

doc/api/v2/run_logic.rst

@@ -6,22 +6,26 @@ Parameters
 ==========
 
 ..  automodule:: paddle.v2.parameters
+    :members: Parameters
     :noindex:
 
 Trainer
 =======
 
 ..  automodule:: paddle.v2.trainer
+    :members: Trainer
     :noindex:
 
 Event
 =====
 
 ..  automodule:: paddle.v2.event
+    :members: Event
     :noindex:
 
 Inference
 =========
 
 ..  autofunction:: paddle.v2.infer
+    :members: Inference
     :noindex:

python/paddle/v2/inference.py

@@ -9,6 +9,16 @@
 
 
 class Inference(object):
+    """
+    Inference combines neural network output and parameters together
+    to do inference.
+
+    :param outptut_layer: The neural network that should be inferenced.
+    :type output_layer: paddle.v2.config_base.Layer or the sequence
+                        of paddle.v2.config_base.Layer
+    :param parameters: The parameters dictionary.
+    :type parameters: paddle.v2.parameters.Parameters
+    """
     def __init__(self, output_layer, parameters):
         topo = topology.Topology(output_layer)
         gm = api.GradientMachine.createFromConfigProto(
@@ -39,7 +49,7 @@ def __reader_impl__():
     def iter_infer_field(self, field, **kwargs):
         for result in self.iter_infer(**kwargs):
             yield [each_result[field] for each_result in result]
-
+ 
     def infer(self, field='value', **kwargs):
         retv = None
         for result in self.iter_infer_field(field=field, **kwargs):

python/paddle/v2/trainer.py

@@ -29,7 +29,8 @@ def default_event_handler(event):
 class SGD(object):
     """
     Simple SGD Trainer.
-    TODO(yuyang18): Complete comments
+    SGD Trainer combines data reader, network topolopy and update_equation together
+    to train/test a neural network.
 
     :param update_equation: The optimizer object.
     :type update_equation: paddle.v2.optimizer.Optimizer
@@ -65,7 +66,9 @@ def train(self, reader, num_passes=1, event_handler=None, feeding=None):
         """
         Training method. Will train num_passes of input data.
 
-        :param reader:
+        :param reader: A reader that reads and yeilds data items. Usually we use a
+                       batched reader to do mini-batch training.
+        :type reader: collections.Iterable
         :param num_passes: The total train passes.
         :param event_handler: Event handler. A method will be invoked when event
                               occurred.
@@ -123,6 +126,16 @@ def train(self, reader, num_passes=1, event_handler=None, feeding=None):
         self.__gradient_machine__.finish()
 
     def test(self, reader, feeding=None):
+        """
+        Testing method. Will test input data.
+
+        :param reader: A reader that reads and yeilds data items.
+        :type reader: collections.Iterable      
+        :param feeding: Feeding is a map of neural network input name and array
+                        index that reader returns.
+        :type feeding: dict
+        :return:
+        """
         feeder = DataFeeder(self.__data_types__, feeding)
         evaluator = self.__gradient_machine__.makeEvaluator()
         out_args = api.Arguments.createArguments(0)