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fix: distributed training in windows

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Akegarasu
2024-10-10 14:03:59 +08:00
parent 83e3048cb0
commit 3de42b6edb
1 changed files with 12 additions and 11 deletions
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23
library/train_util.py
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@@ -5045,17 +5045,18 @@ def prepare_accelerator(args: argparse.Namespace):
if args.torch_compile: if args.torch_compile:
dynamo_backend = args.dynamo_backend dynamo_backend = args.dynamo_backend
kwargs_handlers = ( kwargs_handlers = [
InitProcessGroupKwargs(timeout=datetime.timedelta(minutes=args.ddp_timeout)) if args.ddp_timeout else None, InitProcessGroupKwargs(
( backend = "gloo" if os.name == "nt" or not torch.cuda.is_available() else "nccl",
DistributedDataParallelKwargs( init_method="env://?use_libuv=False" if os.name == "nt" else None,
gradient_as_bucket_view=args.ddp_gradient_as_bucket_view, static_graph=args.ddp_static_graph timeout=datetime.timedelta(minutes=args.ddp_timeout) if args.ddp_timeout else None
) ) if torch.cuda.device_count() > 1 else None,
if args.ddp_gradient_as_bucket_view or args.ddp_static_graph DistributedDataParallelKwargs(
else None 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)) ]
kwargs_handlers = [i for i in kwargs_handlers if i is not None]
deepspeed_plugin = deepspeed_utils.prepare_deepspeed_plugin(args) deepspeed_plugin = deepspeed_utils.prepare_deepspeed_plugin(args)
accelerator = Accelerator( accelerator = Accelerator(