rename 'feed_dict' in ParallelExecutor.run() to 'feed'

python/paddle/fluid/parallel_executor.py

@@ -61,8 +61,8 @@ class ParallelExecutor(object):
                   main_program=test_program,
                   share_vars_from=train_exe)
 
-              train_loss, = train_exe.run([loss.name], feed_dict=feed_dict)
-              test_loss, = test_exe.run([loss.name], feed_dict=feed_dict)
+              train_loss, = train_exe.run([loss.name], feed=feed_dict)
+              test_loss, = test_exe.run([loss.name], feed=feed_dict)
         """
 
         self._places = []
@@ -123,22 +123,23 @@ class ParallelExecutor(object):
             allow_op_delay)
         self.scope = scope
 
-    def run(self, fetch_list, feed_dict={}):
+    def run(self, fetch_list, feed={}, feed_dict={}):
         """
         :param fetch_list: A list of variable names that will be fetched.
-        :param feed_dict: A dict mapping for feed variable name to LoDTensor
+        :param feed: A dict mapping for feed variable name to LoDTensor
           or numpy array.
         :return: fetched value list.
         """
-        if not isinstance(feed_dict, dict):
-            raise TypeError("feed_dict should be a dict")
+        feed = feed_dict
+        if not isinstance(feed, dict):
+            raise TypeError("feed should be a dict")
 
         feed_tensor_dict = {}
-        for i, feed_name in enumerate(feed_dict):
-            feed_tensor = feed_dict[feed_name]
+        for i, feed_name in enumerate(feed):
+            feed_tensor = feed[feed_name]
             if not isinstance(feed_tensor, core.LoDTensor):
                 feed_tensor = core.LoDTensor()
-                feed_tensor.set(feed_dict[feed_name], self._act_places[0])
+                feed_tensor.set(feed[feed_name], self._act_places[0])
             feed_tensor_dict[feed_name] = feed_tensor
 
         fetch_var_name = '@FETCHED_VAR_NAME@'