diff --git a/python/paddle/distributed/fleet/base/fleet_base.py b/python/paddle/distributed/fleet/base/fleet_base.py
index 845e331d55712afc54128a55c4d5323dc850188c..695fd01909c0e6eecb37b34a120f156fb5fed090 100644
--- a/python/paddle/distributed/fleet/base/fleet_base.py
+++ b/python/paddle/distributed/fleet/base/fleet_base.py
@@ -15,6 +15,7 @@
 from __future__ import print_function
 import paddle
 from .strategy_compiler import StrategyCompiler
+from .distributed_strategy import DistributedStrategy
 from .meta_optimizer_factory import MetaOptimizerFactory
 from .runtime_factory import RuntimeFactory
 from .util_factory import UtilFactory
@@ -209,7 +210,7 @@ class Fleet(object):
         assert self._runtime_handle is not None
         self._runtime_handle._stop_worker()
 
-    def distributed_optimizer(self, optimizer, strategy):
+    def distributed_optimizer(self, optimizer, strategy=None):
         """
         distirbuted_optimizer
         Returns:
@@ -225,6 +226,8 @@ class Fleet(object):
             optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy)
         """
         self.user_defined_optimizer = optimizer
+        if strategy == None:
+            strategy = DistributedStrategy()
         self.user_defined_strategy = strategy
         self.valid_strategy = None
         return self
diff --git a/python/paddle/fluid/tests/unittests/test_fleet_base.py b/python/paddle/fluid/tests/unittests/test_fleet_base.py
index 8019841f72eccd35cb76ece582f89179a880e892..3a79b694cad5b0cb3fe0a08b6a18506510eead5b 100644
--- a/python/paddle/fluid/tests/unittests/test_fleet_base.py
+++ b/python/paddle/fluid/tests/unittests/test_fleet_base.py
@@ -145,9 +145,9 @@ class TestFleetBase(unittest.TestCase):
         import paddle.fluid.incubate.fleet.base.role_maker as role_maker
         role = role_maker.PaddleCloudRoleMaker(is_collective=True)
         fleet.init(role)
-        strategy = fleet.DistributedStrategy()
+
         optimizer = paddle.optimizer.SGD(learning_rate=0.001)
-        optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy)
+        optimizer = fleet.distributed_optimizer(optimizer)
 
     def test_minimize(self):
         import paddle