inference stage layerdiffusion: layer_xl_transparent_attn.safetensors

Nobody has claimed this yet.

Thank you for your commendable work. Your remarkable contributions have served as a significant source of inspiration for recent advancements in layer-based image editing. Figure 2 of your paper on Transparent Image Layer Diffusion using Latent Transparency (https://arxiv.org/pdf/2402.17113.pdf) demonstrates that during the training phase, only the encoder and decoder weights are required, while the remaining weights of sd-xl are held fixed. However, I am currently perplexed regarding the inference stage. Is it necessary to employ the alpha-based encoder weight despite the absence of an alpha channel? As far as my understanding goes, for the sole purpose of foreground image generation during inference, a well-trained decoder and other layer_xl_transparent_attn.safetensors are indispensable. Where does layer_xl_transparent_attn.safetensors come from? how it train in paper. I greatly appreciate your reply.

Start with Figure 2 of the linked paper and the inference-stage questions about layer_xl_transparent_attn.safetensors. Trace how that file is produced and whether the alpha-based encoder is required when no alpha channel is present. Done means documenting the inference weights and training provenance clearly enough to resolve both questions.

Written by the indexing model from the issue text.