FIX: All PEFT layers expose in_features, out_features #2784
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Resolves huggingface#2783. Most PEFT layers (BaseTunerLayers) expose the in_features and out_features attributes. Therefore, other packages like diffusers may expect this attribute to exist. However, there were a few PEFT methods where these attributes were missing: - LoHa - LoKr - LN Tuning - Trainable Tokens The layers of these methods now also expose the attributes. Implementation To avoid code duplication, I factored out the whole code block in LoRA layers that extracts these attributes, since LoRA has the most exhaustive list of checks. The new utility function has the exact same functionality and can now be used by other PEFT methods. I updated the four PEFT methods mentioned above to use this new function, but I did not update PEFT methods that already handled it, as there wasn't really a need (they check one or two layer types at most, so there is little duplication).
BenjaminBossan
commented
Sep 15, 2025
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Resolves #2783.
Description
Most PEFT layers (
BaseTunerLayers) expose thein_featuresandout_featuresattributes. Therefore, other packages like diffusers may expect this attribute to exist. However, there were a few PEFT methods where these attributes were missing:The layers of these methods now also expose the attributes.
Implementation
To avoid code duplication, I factored out the whole code block in LoRA layers that extracts these attributes, since LoRA has the most exhaustive list of checks. The new utility function has the exact same functionality and can now be used by other PEFT methods.
I updated the four PEFT methods mentioned above to use this new function, but I did not update PEFT methods that already handled it, as there wasn't really a need (they check one or two layer types at most, so there is little duplication).