Hi authors, thank you for your impressive work on IC-Effect!
I noticed a potential dimension mismatch in models/transformer_wan.py.
The base model (Wan) typically operates on a 36-channel latent space (due to its specific VAE architecture). However, the newly added branch for conditioning, specifically the patch_embedding_extra layer, seems to be initialized or hardcoded with 16 channels.
Then I got: RuntimeError: The size of tensor a (36) must match the size of tensor b (16) at non-singleton dimension 1
Hi authors, thank you for your impressive work on IC-Effect!
I noticed a potential dimension mismatch in models/transformer_wan.py.
The base model (Wan) typically operates on a 36-channel latent space (due to its specific VAE architecture). However, the newly added branch for conditioning, specifically the patch_embedding_extra layer, seems to be initialized or hardcoded with 16 channels.
Then I got: RuntimeError: The size of tensor a (36) must match the size of tensor b (16) at non-singleton dimension 1