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diffusers/docs/source/en/api/cache.md
Tran Thanh Luan 6290fdfda4 [Feat] TaylorSeer Cache (#12648)
* init taylor_seer cache

* make compatible with any tuple size returned

* use logger for printing, add warmup feature

* still update in warmup steps

* refractor, add docs

* add configurable cache, skip compute module

* allow special cache ids only

* add stop_predicts (cooldown)

* update docs

* apply ruff

* update to handle multple calls per timestep

* refractor to use state manager

* fix format & doc

* chores: naming, remove redundancy

* add docs

* quality & style

* fix taylor precision

* Apply style fixes

* add tests

* Apply style fixes

* Remove TaylorSeerCacheTesterMixin from flux2 tests

* rename identifiers, use more expressive taylor predict loop

* torch compile compatible

* Apply style fixes

* Update src/diffusers/hooks/taylorseer_cache.py

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* update docs

* make fix-copies

* fix example usage.

* remove tests on flux kontext

---------

Co-authored-by: toilaluan <toilaluan@github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2025-12-06 05:39:54 +05:30

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# Caching methods
Cache methods speedup diffusion transformers by storing and reusing intermediate outputs of specific layers, such as attention and feedforward layers, instead of recalculating them at each inference step.
## CacheMixin
[[autodoc]] CacheMixin
## PyramidAttentionBroadcastConfig
[[autodoc]] PyramidAttentionBroadcastConfig
[[autodoc]] apply_pyramid_attention_broadcast
## FasterCacheConfig
[[autodoc]] FasterCacheConfig
[[autodoc]] apply_faster_cache
### FirstBlockCacheConfig
[[autodoc]] FirstBlockCacheConfig
[[autodoc]] apply_first_block_cache
### TaylorSeerCacheConfig
[[autodoc]] TaylorSeerCacheConfig
[[autodoc]] apply_taylorseer_cache