Merge pull request #2136 from luotao1/infer

add multiple outputs in annotation of paddle.infer

python/paddle/v2/inference.py

@@ -88,7 +88,7 @@ def infer(output_layer, parameters, input, feeding=None, field='value'):
     Infer a neural network by given neural network output and parameters.  The
     user should pass either a batch of input data or reader method.
 
-    Example usages:
+    Example usage for sinlge output_layer:
 
     ..  code-block:: python
 
@@ -97,8 +97,19 @@ def infer(output_layer, parameters, input, feeding=None, field='value'):
                               input=SomeData)
         print result
 
+    Example usage for multiple outout_layers and fields:
+
+    ..  code-block:: python
+
+        result = paddle.infer(output_layer=[prediction1, prediction2], 
+                              parameters=parameters, 
+                              input=SomeData,
+                              field=[id, value]])
+        print result
+
     :param output_layer: output of the neural network that would be inferred
-    :type output_layer: paddle.v2.config_base.Layer
+    :type output_layer: paddle.v2.config_base.Layer or a list of 
+                        paddle.v2.config_base.Layer
     :param parameters: parameters of the neural network.
     :type parameters: paddle.v2.parameters.Parameters
     :param input: input data batch. Should be a python iterable object, and each
@@ -112,7 +123,9 @@ def infer(output_layer, parameters, input, feeding=None, field='value'):
                   Note that `prob` only used when output_layer is beam_search 
                   or max_id.
     :type field: str
-    :return: a numpy array
+    :return: The prediction result. If there are multiple outout_layers and fields, 
+             the return order is outout_layer1.field1, outout_layer2.field1, ..., 
+             outout_layer1.field2, outout_layer2.field2 ...
     :rtype: numpy.ndarray
     """