lllyasviel / lllyasviel/sd-forge-layerdiffuse
subtraction in attention sharing mechanism
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Description
In the implementation of attention sharing, I noticed there's a stacked temporal attention adapter.
My question is, why did you subtract the `modified_hidden_states` with input `h`? Could you share some insights behind the rationale of this design? Thanks!
https://github.com/layerdiffusion/sd-forge-layerdiffuse/blob/e4d5060e05c7b4337a3258bb03c4e3ad2f8b15bb/lib_layerdiffusion/attention_sharing.py#L131-L137
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Research direction
Start with lib_layerdiffusion/attention_sharing.py at lines 131-137 and trace the stacked temporal attention adapter's inputs and outputs. Read the surrounding implementation to determine the rationale for subtracting modified_hidden_states from h. Done means documenting a clear explanation of that design choice.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100