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recipes_source/distributed_async_checkpoint_recipe.rst

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@@ -26,7 +26,7 @@ to show how this can be integrated quite easily with ``torch.distributed.checkpo
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Asynchronous Checkpointing Overview
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Before getting started with Asynchronous Checkpointing, it's important to understand it's differences and limitations as compared to synchronous checkpointing.
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Speciically:
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Specifically:
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* Memory requirements - Asynchronous checkpointing works by first copying models into internal CPU-buffers.
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This is helpful since it ensures model and optimizer weights are not changing while the model is still checkpointing,

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