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base repository: Lightning-AI/pytorch-lightning
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head repository: Lightning-AI/pytorch-lightning
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compare: 1ebcfae34be677d73e4be2ad56311b1130bf1385
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Showing with 1 addition and 1 deletion.
  1. +1 −1 docs/source-pytorch/extensions/strategy.rst
2 changes: 1 addition & 1 deletion docs/source-pytorch/extensions/strategy.rst
Original file line number Diff line number Diff line change
@@ -77,7 +77,7 @@ The below table lists all relevant strategies available in Lightning with their
- Strategy for multi-process single-device training on one or multiple nodes. :ref:`Learn more. <accelerators/gpu_intermediate:Distributed Data Parallel>`
* - ddp_spawn
- :class:`~lightning.pytorch.strategies.DDPStrategy`
- Same as "ddp" but launches processes using :func:`torch.multiprocessing.spawn` method and joins processes after training finishes. :ref:`Learn more. <accelerators/gpu_intermediate:Distributed Data Parallel Spawn>`
- Same as "ddp" but launches processes using ``torch.multiprocessing.spawn`` method and joins processes after training finishes. :ref:`Learn more. <accelerators/gpu_intermediate:Distributed Data Parallel Spawn>`
* - deepspeed
- :class:`~lightning.pytorch.strategies.DeepSpeedStrategy`
- Provides capabilities to run training using the DeepSpeed library, with training optimizations for large billion parameter models. :doc:`Learn more. <../advanced/model_parallel/deepspeed>`