diff --git a/fastNLP/core/drivers/paddle_driver/fleet.py b/fastNLP/core/drivers/paddle_driver/fleet.py
index c407ab9f..bde6f37f 100644
--- a/fastNLP/core/drivers/paddle_driver/fleet.py
+++ b/fastNLP/core/drivers/paddle_driver/fleet.py
@@ -11,6 +11,7 @@ from .utils import (
     replace_sampler,
     replace_batch_sampler,
 )
+from .dist_utils import fastnlp_paddle_all_gather, fastnlp_paddle_broadcast_object
 
 from fastNLP.envs.imports import _NEED_IMPORT_PADDLE
 from fastNLP.core.utils import (
@@ -451,12 +452,12 @@ class PaddleFleetDriver(PaddleDriver):
         :return: 如果当前不是分布式 driver 直接返回输入的 obj 。如果当前 rank 是接收端（其 global rank 包含在了 dst 中），则返回
             接收到的参数；如果是 source 端则返回发射的内容；既不是发送端、又不是接收端，则返回 None 。
         """
-        return
-        if int(os.environ.get(FASTNLP_NO_SYNC, 0)) == 2:  # 如果 FASTNLP_NO_SYNC == 2 直接返回。
-            return
-        return fastnlp_paddle_broadcast_object(obj, src, device=self.data_device, group=group)
+        device = self.data_device
+        # 因为设置了CUDA_VISIBLE_DEVICES，可能会引起错误
+        device = get_device_from_visible(device)
+        return fastnlp_paddle_broadcast_object(obj, src, device=device, group=group)
 
-    def all_gather(self, obj, group) -> List:
+    def all_gather(self, obj, group=None) -> List:
         """
         将 obj 互相传送到其它所有的 rank 上，其中 obj 可能是 Tensor，也可能是嵌套结构的 object 。如果不是基础类型的数据，尝试通过
             pickle 进行序列化，接收到之后再反序列化。
@@ -479,7 +480,4 @@ class PaddleFleetDriver(PaddleDriver):
         :param group:
         :return:
         """
-        return
-        if int(os.environ.get(FASTNLP_NO_SYNC, 0)) == 2:  # 如果 FASTNLP_NO_SYNC 表示不执行
-            return [obj]
         return fastnlp_paddle_all_gather(obj, group=group)
diff --git a/tests/core/drivers/paddle_driver/test_fleet.py b/tests/core/drivers/paddle_driver/test_fleet.py
index 76d1f793..52739f53 100644
--- a/tests/core/drivers/paddle_driver/test_fleet.py
+++ b/tests/core/drivers/paddle_driver/test_fleet.py
@@ -14,7 +14,7 @@ from fastNLP.core.samplers import (
 from tests.helpers.models.paddle_model import PaddleNormalModel_Classification_1
 from tests.helpers.datasets.paddle_data import PaddleNormalDataset, PaddleRandomMaxDataset
 from tests.helpers.utils import magic_argv_env_context
-from fastNLP.core import synchronize_safe_rm
+from fastNLP.core import rank_zero_rm
 
 import paddle
 import paddle.distributed as dist
@@ -112,6 +112,35 @@ class TestFleetDriverFunction:
         self.driver.get_local_rank()
         dist.barrier()
 
+    @magic_argv_env_context
+    def test_all_gather(self):
+        """
+        测试 all_gather 函数
+        详细的测试在 test_dist_utils.py 中完成
+        """
+        obj = {
+            "rank": self.driver.global_rank
+        }
+        obj_list = self.driver.all_gather(obj, group=None)
+        for i, res in enumerate(obj_list):
+            assert res["rank"] == i
+
+    @magic_argv_env_context
+    @pytest.mark.parametrize("src_rank", ([0, 1]))
+    def test_broadcast_object(self, src_rank):
+        """
+        测试 broadcast_object 函数
+        详细的函数在 test_dist_utils.py 中完成
+        """
+        if self.driver.global_rank == src_rank:
+            obj = {
+                "rank": self.driver.global_rank
+            }
+        else:
+            obj = None
+        res = self.driver.broadcast_object(obj, src=src_rank)
+        assert res["rank"] == src_rank
+
 ############################################################################
 #
 # 测试 set_dist_repro_dataloader 函数
@@ -543,11 +572,11 @@ class TestSaveLoad:
                 assert paddle.equal_all(res1["pred"], res2["pred"])
         finally:
             if only_state_dict:
-                synchronize_safe_rm(path)
+                rank_zero_rm(path)
             else:
-                synchronize_safe_rm(path + ".pdiparams")
-                synchronize_safe_rm(path + ".pdiparams.info")
-                synchronize_safe_rm(path + ".pdmodel")
+                rank_zero_rm(path + ".pdiparams")
+                rank_zero_rm(path + ".pdiparams.info")
+                rank_zero_rm(path + ".pdmodel")
 
     @magic_argv_env_context
     @pytest.mark.parametrize("only_state_dict", ([True, False]))
@@ -658,7 +687,7 @@ class TestSaveLoad:
             assert len(left_y_batches) + len(already_seen_y_set) == len(self.dataset) / num_replicas
             assert len(left_y_batches | already_seen_y_set) == len(self.dataset) / num_replicas
         finally:
-            synchronize_safe_rm(path)
+            rank_zero_rm(path)
 
     @magic_argv_env_context
     @pytest.mark.parametrize("only_state_dict", ([True, False]))
@@ -769,4 +798,4 @@ class TestSaveLoad:
             assert len(left_y_batches | already_seen_y_set) == len(self.dataset) / num_replicas
 
         finally:
-            synchronize_safe_rm(path)
\ No newline at end of file
+            rank_zero_rm(path)
\ No newline at end of file