change option names, add ddp kwargs if needed ref #1000

library/train_util.py

@@ -2900,10 +2900,14 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
         help="DDP timeout (min, None for default of accelerate) / DDPのタイムアウト（分、Noneでaccelerateのデフォルト）",
     )
     parser.add_argument(
-        "--gradient_as_bucket_view", action="store_true", help="enable gradient_as_bucket_view for DDP",
+        "--ddp_gradient_as_bucket_view",
+        action="store_true",
+        help="enable gradient_as_bucket_view for DDP / DDPでgradient_as_bucket_viewを有効にする",
     )
     parser.add_argument(
-        "--static_graph", action="store_true", help="enable static_graph for DDP",
+        "--ddp_static_graph",
+        action="store_true",
+        help="enable static_graph for DDP / DDPでstatic_graphを有効にする",
     )
     parser.add_argument(
         "--clip_skip",
@@ -3866,10 +3870,11 @@ def prepare_accelerator(args: argparse.Namespace):
             if args.wandb_api_key is not None:
                 wandb.login(key=args.wandb_api_key)
 
-    
     kwargs_handlers = (
         InitProcessGroupKwargs(timeout=datetime.timedelta(minutes=args.ddp_timeout)) if args.ddp_timeout else None,
-        DistributedDataParallelKwargs(gradient_as_bucket_view=args.gradient_as_bucket_view, static_graph=args.static_graph)
+        DistributedDataParallelKwargs(gradient_as_bucket_view=args.ddp_gradient_as_bucket_view, static_graph=args.ddp_static_graph)
+        if args.ddp_gradient_as_bucket_view or args.ddp_static_graph
+        else None,
     )
     kwargs_handlers = list(filter(lambda x: x is not None, kwargs_handlers))
     accelerator = Accelerator(