fix: Allow for multi node training for accelerated moe #129
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kmehant
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@kmehant i understand the fix, but can you update the description for record keeping purposes |
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@fabianlim |
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LGTM but one suggestion
| if torch.distributed.is_initialized(): | ||
| world_size = torch.distributed.get_world_size() | ||
| rank = torch.distributed.get_rank() | ||
| rank = int(os.environ["LOCAL_RANK"]) |
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can we make it consistent and follow the new style.
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| rank = int(os.environ["LOCAL_RANK"]) | |
| # we do not need to use the fallback as this is wrapped in an `is_initialized` block | |
| rank = torch.distributed.get_node_local_rank() |
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@fabianlim Have included this suggestion thanks.
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Signed-off-by: Mehant Kammakomati <[email protected]> Signed-off-by: Yu Chin Fabian Lim <[email protected]> Signed-off-by: Mehant Kammakomati <[email protected]>
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@fabianlim requesting your merge. |
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Current implementation uses global rank of the process to prepare the device index which would not work in a multi node setting. Therefore, we would need to use local rank since devices are not continuously indexed across the nodes.