diff --git a/app/yolov5/train_server.py b/app/yolov5/train_server.py
index 0146c60..0d50d5f 100644
--- a/app/yolov5/train_server.py
+++ b/app/yolov5/train_server.py
@@ -217,16 +217,16 @@ def train(hyp, opt, device, data_list,id,callbacks):  # hyp is path/to/hyp.yaml
             best_fitness, start_epoch, epochs = smart_resume(ckpt, optimizer, ema, weights, epochs, resume)
         del ckpt, csd
 
-    # DP mode
-    if cuda and RANK == -1 and torch.cuda.device_count() > 1:
-        LOGGER.warning('WARNING: DP not recommended, use torch.distributed.run for best DDP Multi-GPU results.\n'
-                       'See Multi-GPU Tutorial at https://github.com/ultralytics/yolov5/issues/475 to get started.')
-        model = torch.nn.DataParallel(model)
+    # # DP mode
+    # if cuda and RANK == -1 and torch.cuda.device_count() > 1:
+    #     LOGGER.warning('WARNING: DP not recommended, use torch.distributed.run for best DDP Multi-GPU results.\n'
+    #                    'See Multi-GPU Tutorial at https://github.com/ultralytics/yolov5/issues/475 to get started.')
+    #     model = torch.nn.DataParallel(model)
 
-    # SyncBatchNorm
-    if opt.sync_bn and cuda and RANK != -1:
-        model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model).to(device)
-        LOGGER.info('Using SyncBatchNorm()')
+    # # SyncBatchNorm
+    # if opt.sync_bn and cuda and RANK != -1:
+    #     model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model).to(device)
+    #     LOGGER.info('Using SyncBatchNorm()')
 
     print("Trainloader")
     # Trainloader