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chore: update train_utils.py (meta-llama#690)
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src/llama_recipes/utils/train_utils.py

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@@ -432,7 +432,7 @@ def setup_environ_flags(rank):
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os.environ["NCCL_ASYNC_ERROR_HANDLING"] = str(1)
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# os.environ["TORCH_DISTRIBUTED_DEBUG"] = "DETAIL"
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# This flag will help with CUDA memory fragmentations that can lead into OOM in some cases.
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# Note this is only availble in PyTorch Nighlies (as of July 30 2023)
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# Note this is only available in PyTorch Nighlies (as of July 30 2023)
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# os.environ['PYTORCH_CUDA_ALLOC_CONF']='expandable_segments:True'
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if rank == 0:
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print(f"--> Running with torch dist debug set to detail")

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