Make broadcast_buffers disable its own flag for now (needs more testing on interaction with dist_bn)

train.py

@@ -270,6 +270,8 @@ parser.add_argument('--apex-amp', action='store_true', default=False,
                     help='Use NVIDIA Apex AMP mixed precision')
 parser.add_argument('--native-amp', action='store_true', default=False,
                     help='Use Native Torch AMP mixed precision')
+parser.add_argument('--no-ddp-bb', action='store_true', default=False,
+                    help='Force broadcast buffers for native DDP to off.')
 parser.add_argument('--channels-last', action='store_true', default=False,
                     help='Use channels_last memory layout')
 parser.add_argument('--pin-mem', action='store_true', default=False,
@@ -463,7 +465,7 @@ def main():
         else:
             if args.local_rank == 0:
                 _logger.info("Using native Torch DistributedDataParallel.")
-            model = NativeDDP(model, device_ids=[args.local_rank], broadcast_buffers=not args.dist_bn)
+            model = NativeDDP(model, device_ids=[args.local_rank], broadcast_buffers=not args.no_ddp_bb)
         # NOTE: EMA model does not need to be wrapped by DDP
 
     # setup learning rate schedule and starting epoch