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v1.12.0: Deepspeed Ulysses/ALST

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@SunMarc SunMarc released this 21 Nov 12:47
· 13 commits to main since this release

Deepspeed Ulysses/ALST integration

Deepspeed Ulysses/ALST is an efficient way of training on long sequences by employing sequence parallelism and attention head parallelism. You can learn more about this technology in this paper https://arxiv.org/abs/2506.13996 or this deepspeed tutorial https://www.deepspeed.ai/tutorials/ulysses-alst-sequence-parallelism/.

0d8bd9e0

To enable Deepspeed Ulysses, you first need to create ParallelismConfig and setting sp related args:

parallelism_config = ParallelismConfig(
    sp_backend="deepspeed",
    sp_size=2,
    sp_handler=DeepSpeedSequenceParallelConfig(...),
)

Then, you need to make sure to compute the correct loss as described on our docs

        ...
        losses_per_rank = torch.distributed.nn.functional.all_gather(loss, group=sp_group)
        good_tokens = (shift_labels != -100).view(-1).sum()
        good_tokens_per_rank = torch.distributed.nn.functional.all_gather(good_tokens, group=sp_group)
        total_loss = sum(
            losses_per_rank[rank] * good_tokens_per_rank[rank]
            for rank in range(sp_world_size)
            if good_tokens_per_rank[rank] > 0
        )
        total_good_tokens = sum(good_tokens_per_rank)
        loss = total_loss / max(total_good_tokens, 1)

Thanks @S1ro1 for starting this work and for @stas00 for finishing this work. Also thanks @kashif for adding docs and reviewing/testing this PR !

This feature will also be available in HF Trainer thanks for this PR from @stas00: huggingface/transformers#41832

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New Contributors

Full Changelog: v1.11.0...v1.12.0