
Worked on the huggingface/diffusers repository to address a critical bug affecting rotary positional embeddings in Wan and SkyReels V2 transformers. The solution involved storing t_dim, h_dim, and w_dim as instance variables within the rotary embedding classes and ensuring these dimensions were consistently used during both initialization and forward passes. This approach resolved a mismatch between initialization and computation logic, specifically addressing discrepancies in dimension splitting. By aligning split_sizes with actual embedding dimensions, the fix reduced runtime errors and improved model reproducibility. The work was implemented in Python using PyTorch and Transformers, with additional focus on maintainability and documentation improvements.
In November 2025, delivered a critical correctness fix for rotary positional embeddings in huggingface/diffusers, ensuring dimensional consistency across Wan and SkyReels V2 transformers. The fix stores t_dim, h_dim, and w_dim as instance variables in the relevant rotary embedding classes, and uses these stored dimensions in forward, aligning with initialization logic. This resolved a dimensional mismatch between init (using // 6) and forward (using // 3), and ensured split_sizes matched the actual embedding dimensions. The change reduces runtime errors in model initialization and inference, improves reproducibility, and supports stable usage across Wan and SkyReels V2 deployments. Collaboration with Charchit Sharma; quality improvements and documentation were included.
In November 2025, delivered a critical correctness fix for rotary positional embeddings in huggingface/diffusers, ensuring dimensional consistency across Wan and SkyReels V2 transformers. The fix stores t_dim, h_dim, and w_dim as instance variables in the relevant rotary embedding classes, and uses these stored dimensions in forward, aligning with initialization logic. This resolved a dimensional mismatch between init (using // 6) and forward (using // 3), and ensured split_sizes matched the actual embedding dimensions. The change reduces runtime errors in model initialization and inference, improves reproducibility, and supports stable usage across Wan and SkyReels V2 deployments. Collaboration with Charchit Sharma; quality improvements and documentation were included.

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