[ T5] fix fp16 loading issue#20878
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younesbelkada merged 4 commits intohuggingface:mainfrom Dec 26, 2022
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Thanks for fixing! LGTM with just one nit.
| force_upcast_dtype = torch.float32 | ||
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| # For backward compatibility with older versions of `accelerate` | ||
| if set_module_tensor_to_device.__code__.co_argcount == 5: |
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Slight nit: can we use the signature and parameter names using inspect? It would be clearer to read. Also add a TODO that this should become a version check at the next version of Accelerate (I will take care of it after next release).
- remove `force_upcast_dtype` as it is used once - use `inspect` - add `TODO`
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* fix fp16 loading issue * add backward compatibility * better refactor * better readability - remove `force_upcast_dtype` as it is used once - use `inspect` - add `TODO`
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* fix fp16 loading issue * add backward compatibility * better refactor * better readability - remove `force_upcast_dtype` as it is used once - use `inspect` - add `TODO`
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What does this PR do?
This PR mainly fixes https://github.com/huggingface/transformers/actions/runs/3754402958/jobs/6378652143
Since the PR huggingface/accelerate#920 has been merged, the fix proposed in #20760 seems to not work anymore using the main branch of
acceleratefor some specific cases.To reproduce (use the main branch of
accelerate):Why?
I believe this is because the aforementioned PR introduced a new argument
dtypeon the functionset_module_tensor_to_device, if this argument is set toNone(by default), the target value is automatically set to thedtypeof the old tensor - which slightly breaks some assumptions made in #20760I believe upstreaming this change on
modeling_utilsby adding the support of this new argument should be the fix. As some users might not use the latest version of accelerate, I added a small hack to make this change backward compatible, but I am not sure if this is the best solutionTested this fix on the main branch of
accelerate,accelerate==0.15.0and all relevant tests passcc @sgugger