diff --git a/fastNLP/core/drivers/paddle_driver/fleet.py b/fastNLP/core/drivers/paddle_driver/fleet.py
index a083e42c..762b3114 100644
--- a/fastNLP/core/drivers/paddle_driver/fleet.py
+++ b/fastNLP/core/drivers/paddle_driver/fleet.py
@@ -37,7 +37,7 @@ if _NEED_IMPORT_PADDLE:
     import paddle
     from paddle import DataParallel
     import paddle.distributed.fleet as fleet
-    import paddle.distributed as dist
+    import paddle.distributed as paddledist
     from paddle.io import BatchSampler
     from paddle.optimizer import Optimizer
     from paddle.fluid.reader import _DatasetKind
@@ -185,8 +185,8 @@ class PaddleFleetDriver(PaddleDriver):
                 if sorted(pre_gpus) != sorted(self.parallel_device):
                     raise RuntimeError("Notice you are using `PaddleFleetDriver` after one instantiated `PaddleFleetDriver`, it is not"
                                     "allowed that your second `PaddleFleetDriver` has a new setting of parameters `parallel_device`.")
-                self.world_size = dist.get_world_size()
-                self.global_rank = dist.get_rank()
+                self.world_size = paddledist.get_world_size()
+                self.global_rank = paddledist.get_rank()
 
         if not self.outside_fleet:
             # self.model.to(self.model_device)
@@ -197,12 +197,12 @@ class PaddleFleetDriver(PaddleDriver):
         # 初始化 self._pids，从而使得每一个进程都能接受到 rank0 的 send 操作；
         # TODO 不用.to会怎么样？
         self._pids = []
-        dist.all_gather(self._pids, paddle.to_tensor(os.getpid(), dtype="int32"))
+        paddledist.all_gather(self._pids, paddle.to_tensor(os.getpid(), dtype="int32"))
         # TODO LOCAL_WORLD_SIZE
         local_world_size = int(os.environ.get("LOCAL_WORLD_SIZE")) if "LOCAL_WORLD_SIZE" in os.environ else None
         if local_world_size is None:
             local_world_size = paddle.to_tensor(self.local_rank, dtype="int32")
-            dist.all_reduce(local_world_size, op=dist.ReduceOp.MAX)
+            paddledist.all_reduce(local_world_size, op=paddledist.ReduceOp.MAX)
             local_world_size = local_world_size.item() + 1
 
         node_rank = self.global_rank // local_world_size
@@ -232,11 +232,11 @@ class PaddleFleetDriver(PaddleDriver):
         当用户使用了 `python -m paddle.distributed.launch xxx.py` 启动时，我们需要
         根据 paddle 设置的环境变量来获得各种属性
         """
-        self.world_size = dist.get_world_size()
-        self.global_rank = dist.get_rank()
+        self.world_size = paddledist.get_world_size()
+        self.global_rank = paddledist.get_rank()
 
     def barrier(self):
-        dist.barrier()
+        paddledist.barrier()
 
     def configure_fleet(self):
         if not self._has_fleetwrapped and not isinstance(self.model, DataParallel):