tweak the executor implementation to better match origin behavior

test=develop

python/paddle/fluid/executor.py

@@ -305,7 +305,9 @@ class Executor(object):
     def __init__(self, place):
         self.place = place
         self.program_caches = dict()
-        self.executor = None
+        p = core.Place()
+        p.set_place(self.place)
+        self._default_executor = core.Executor(p)
         self._closed = False
 
     def _get_program_cache(self, program_cache_key):
@@ -397,12 +399,13 @@ class Executor(object):
             >>> ...
             >>> exe.close()
         """
-        if not self._closed and self.executor:
-            self.executor.close()
+        if not self._closed:
+            self._default_executor.close()
             self._closed = True
 
     def _run_parallel(self, program, scope, feed, fetch_list, fetch_var_name,
                       return_numpy):
+        exe = program._executor
         if isinstance(feed, dict):
             feed_tensor_dict = dict()
             for feed_name in feed:
@@ -414,8 +417,7 @@ class Executor(object):
                     feed_tensor.set(feed[feed_name], core.CPUPlace())
                 feed_tensor_dict[feed_name] = feed_tensor
 
-            self.executor.feed_and_split_tensor_into_local_scopes(
-                feed_tensor_dict)
+            exe.feed_and_split_tensor_into_local_scopes(feed_tensor_dict)
         elif isinstance(feed, list) or isinstance(feed, tuple):
             if len(feed) != len(program._places):
                 raise ValueError(
@@ -436,10 +438,10 @@ class Executor(object):
                         tensor = tmp
                     res_dict[feed_name] = tensor
                 res.append(res_dict)
-            self.executor.feed_tensors_into_local_scopes(res)
+            exe.feed_tensors_into_local_scopes(res)
 
         fetch_var_names = list(map(_to_name_str, fetch_list))
-        self.executor.run(fetch_var_names, fetch_var_name)
+        exe.run(fetch_var_names, fetch_var_name)
         arr = scope.find_var(fetch_var_name).get_lod_tensor_array()
 
         if return_numpy:
@@ -511,12 +513,9 @@ class Executor(object):
         compiled = isinstance(program, compiler.CompiledProgram)
         # For backward compatibility, run directly.
         if not compiled:
-            if not self.executor:
-                p = core.Place()
-                p.set_place(self.place)
-                self.executor = core.Executor(p)
             return self._run(
                 program,
+                self._default_executor,
                 feed=feed,
                 fetch_list=fetch_list,
                 feed_var_name=feed_var_name,
@@ -526,7 +525,6 @@ class Executor(object):
                 use_program_cache=use_program_cache)
 
         program._compile(scope, self.place)
-        self.executor = program._executor
         if program._is_data_parallel:
             return self._run_parallel(
                 program,
@@ -542,6 +540,7 @@ class Executor(object):
             # performance.
             return self._run(
                 program._program,
+                self._default_executor,
                 feed=feed,
                 fetch_list=fetch_list,
                 feed_var_name=feed_var_name,
@@ -550,8 +549,8 @@ class Executor(object):
                 return_numpy=return_numpy,
                 use_program_cache=use_program_cache)
 
-    def _run(self, program, feed, fetch_list, feed_var_name, fetch_var_name,
-             scope, return_numpy, use_program_cache):
+    def _run(self, program, exe, feed, fetch_list, feed_var_name,
+             fetch_var_name, scope, return_numpy, use_program_cache):
 
         if feed is None:
             feed = {}
@@ -589,7 +588,7 @@ class Executor(object):
                 fetch_var_name=fetch_var_name)
 
         self._feed_data(program, feed, feed_var_name, scope)
-        self.executor.run(program.desc, scope, 0, True, True)
+        exe.run(program.desc, scope, 0, True, True)
         outs = self._fetch_data(fetch_list, fetch_var_name, scope)
         if return_numpy:
             outs = as_numpy(outs)