diff --git a/model_zoo/official/cv/yolov3_darknet53/train.py b/model_zoo/official/cv/yolov3_darknet53/train.py
index 5f7eca4fc4..76239047ba 100644
--- a/model_zoo/official/cv/yolov3_darknet53/train.py
+++ b/model_zoo/official/cv/yolov3_darknet53/train.py
@@ -124,15 +124,6 @@ def parse_args():
     args.data_root = os.path.join(args.data_dir, 'train2014')
     args.annFile = os.path.join(args.data_dir, 'annotations/instances_train2014.json')
 
-    # init distributed
-    if args.is_distributed:
-        if args.device_target == "Ascend":
-            init()
-        else:
-            init("nccl")
-        args.rank = get_rank()
-        args.group_size = get_group_size()
-
     # select for master rank save ckpt or all rank save, compatiable for model parallel
     args.rank_save_ckpt_flag = 0
     if args.is_save_on_master:
@@ -161,6 +152,14 @@ def train():
     devid = int(os.getenv('DEVICE_ID', '0'))
     context.set_context(mode=context.GRAPH_MODE, enable_auto_mixed_precision=True,
                         device_target=args.device_target, save_graphs=True, device_id=devid)
+    # init distributed
+    if args.is_distributed:
+        if args.device_target == "Ascend":
+            init()
+        else:
+            init("nccl")
+        args.rank = get_rank()
+        args.group_size = get_group_size()
     if args.need_profiler:
         from mindspore.profiler.profiling import Profiler
         profiler = Profiler(output_path=args.outputs_dir, is_detail=True, is_show_op_path=True)