diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 190efe6c1bcc7916461b1069eb0e59b4d108a13d..07cc1e29341bd497e88097a9ee5653631b79d734 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -16,6 +16,7 @@ import core
 import multiprocessing
 import framework
 import executor
+import sys
 
 __all__ = ['ParallelExecutor']
 
@@ -125,6 +126,30 @@ class ParallelExecutor(object):
 
     def run(self, fetch_list, feed=None, feed_dict=None):
         """
+        Run a parallel executor with fetch_list.
+
+        The feed parameter can be a dict or a list. If feed is a dict, the
+        feed data will be split into multiple devices. If feed is a list, we
+        assume the data has been splitted into multiple devices, the each
+        element in the list will be copied to each device directly.
+
+        For example, if the feed is a dict:
+        >>> exe = ParallelExecutor()
+        >>> # the image will be splitted into devices. If there is two devices
+        >>> # each device will process an image with shape (24, 1, 28, 28)
+        >>> exe.run(feed={'image': numpy.random.random(size=(48, 1, 28, 28))})
+
+        For example, if the feed is a list:
+        >>> exe = ParallelExecutor()
+        >>> # each device will process each element in the list.
+        >>> # the 1st device will process an image with shape (48, 1, 28, 28)
+        >>> # the 2nd device will process an image with shape (32, 1, 28, 28)
+        >>> #
+        >>> # you can use exe.device_count to get the device number.
+        >>> exe.run(feed=[{"image": numpy.random.random(size=(48, 1, 28, 28))},
+        >>>               {"image": numpy.random.random(size=(32, 1, 28, 28))},
+        >>>              ])
+
 
         Args:
             fetch_list(list): The fetched variable names
@@ -133,12 +158,14 @@ class ParallelExecutor(object):
                 the feed is a list, each element of the list will be copied
                 to each device.
             feed_dict: Alias for feed parameter, for backward compatibility.
+                This parameter is deprecated.
 
         Returns: fetched result list.
 
         """
         if feed is None:
             feed = feed_dict
+            print >> sys.stderr, "`feed_dict` is deprecated. Please use `feed=`"
 
         if isinstance(feed, dict):
             feed_tensor_dict = dict()