Plan to support FSDP2?
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@muellerzr is already working on this.
Since Jul 29, 2024.
- #3231 by @kmehant — closed without merging
Assessment
This issue has not been assessed yet.
Description
FSDP2 provides smaller memory footprint, compatibility with torch compile, and more flexibility due to per param sharding. Does huggingface have plan to support FSDP2?
https://github.com/pytorch/torchtitan/blob/main/docs/fsdp.md
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- Python
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More from huggingface/accelerate
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FSDP2: prepare() keeps the whole unsharded model alive during sharding when cpu_ram_efficient_loading=FalsePossibly taken A pull request linked to this issue is open or already merged. Open
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huggingface/accelerate#4511 ·
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BatchSamplerShard padding mutates retained sampler batches and changes original loader samplesPossibly taken @davrens101 claimed this 4 days ago. Open
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huggingface/accelerate#4505 ·
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accelerator.reduce(tensor, "mean") fails on integer tensors when more than one process is usedPossibly taken @MaiAditya claimed this 12 days ago. Open
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
huggingface/accelerate#4469 ·
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merge_fsdp_weights with remove_checkpoint_dir=True deletes the merged model when output_path is inside checkpoint_dirPossibly taken @assass1nlike claimed this 1 day ago. Open
Difficulty 2/5 1-3 hours Newbie friendliness 25/100
huggingface/accelerate#4514 ·
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Difficulty 4/5 3-5 days Newbie friendliness 42/100
huggingface/accelerate#4510 ·
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