Redundancy between consecutive diffusion steps varies widely across DiT models but is stable within each model across prompts, step counts, and schedulers, so caching strategies must be model-specific.
xdit: an inference engine for diffusion transformers (dits) with massive parallelism, 2024
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Unveiling Redundancy in Diffusion Transformers (DiTs): A Systematic Study
Redundancy between consecutive diffusion steps varies widely across DiT models but is stable within each model across prompts, step counts, and schedulers, so caching strategies must be model-specific.