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Sliding Tile Attention (STA)

STA inference integration is archived from main.

The full STA pipeline code (including mask search and STA inference wiring in fastvideo/) is preserved in:

In this branch, STA kernels in fastvideo-kernel are still kept.

Why STA is not in main

We do not keep STA pipeline integration in main because we believe Video Sparse Attention (VSA) is strictly better than STA for the actively maintained FastVideo inference path.

What to checkout for STA workflows

To run the full STA workflow, switch to the archived branch:

git fetch origin
git checkout sta_do_not_delete

Mask Search (archive branch)

The reference script is:

  • examples/inference/sta_mask_search/inference_wan_sta.sh

It runs two stages:

  1. STA_searching (full search), output at inference_results/sta/mask_search_full
  2. STA_tuning (sparse tuning), output at inference_results/sta/mask_search_sparse

Run:

export FASTVIDEO_ATTENTION_BACKEND=SLIDING_TILE_ATTN
export FASTVIDEO_ATTENTION_CONFIG=assets/mask_strategy_wan.json

bash examples/inference/sta_mask_search/inference_wan_sta.sh

STA Inference (archive branch)

With a selected mask strategy, run inference with:

export FASTVIDEO_ATTENTION_BACKEND=SLIDING_TILE_ATTN
export FASTVIDEO_ATTENTION_CONFIG=assets/mask_strategy_wan.json

fastvideo generate \
  --model-path Wan-AI/Wan2.1-T2V-14B-Diffusers \
  --num-gpus 2 \
  --tp-size 2 \
  --sp-size 2 \
  --height 768 \
  --width 1280 \
  --num-frames 69 \
  --num-inference-steps 50 \
  --prompt "A cinematic wildlife shot of a lion walking in golden grasslands." \
  --output-path outputs_video/STA/

Python usage on the archive branch can also set STA_mode in VideoGenerator.from_pretrained(...):

  • STA_searching
  • STA_tuning
  • STA_inference

Kernel-level API (current branch)

STA kernels remain available from fastvideo-kernel. See Attention overview for build instructions.

Citation

If you use Sliding Tile Attention in your research, please cite:

@article{zhang2025fast,
  title={Fast video generation with sliding tile attention},
  author={Zhang, Peiyuan and Chen, Yongqi and Su, Runlong and Ding, Hangliang and Stoica, Ion and Liu, Zhengzhong and Zhang, Hao},
  journal={arXiv preprint arXiv:2502.04507},
  year={2025}
}