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Fix: update type hints for Tuple parameters across multiple files to support variable-length tuples (#12544)

* Fix: update type hints for Tuple parameters across multiple files to support variable-length tuples

* Apply style fixes

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* fix crash in tiling mode is enabled
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* fmt
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add

* up

* correct wording.

* up

* up

* up

* Update autoencoder_kl_wan.py

When using the Wan2.2 VAE, the spatial compression ratio calculated here is incorrect. It should be 16 instead of 8. Pass it in directly via the config to ensure it’s correct here.

* Update autoencoder_kl_wan.py

up

* support wan 2.2 i2v

* add t2v + vae2.2

* add conversion script for vae 2.2

* add

* add 5b t2v

* conversion script

* refactor out reearrange

* remove a copied from in skyreels

* Apply suggestions from code review
Co-authored-by: bagheera <59658056+bghira@users.noreply.github.com>

* Update src/diffusers/models/transformers/transformer_wan.py

* fix fast tests

* style

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Co-authored-by: bagheera <59658056+bghira@users.noreply.github.com>

* ⚡

️ Speed up method `AutoencoderKLWan.clear_cache` by 886%

**Key optimizations:**
- Compute the number of `WanCausalConv3d` modules in each model (`encoder`/`decoder`) **only once during initialization**, store in `self._cached_conv_counts`. This removes unnecessary repeated tree traversals at every `clear_cache` call, which was the main bottleneck (from profiling).
- The internal helper `_count_conv3d_fast` is optimized via a generator expression with `sum` for efficiency.

All comments from the original code are preserved, except for updated or removed local docstrings/comments relevant to changed lines.  
**Function signatures and outputs remain unchanged.**

* Apply style fixes

* Apply suggestions from code review
Co-authored-by: Aryan <contact.aryanvs@gmail.com>

* Apply style fixes

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Co-authored-by: codeflash-ai[bot] <148906541+codeflash-ai[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: Aseem Saxena <aseem.bits@gmail.com>

* implement tiled encode/decode

* address review comments

* update

* update

* update

* update

* update

* update

* update

* Add wanx pipeline, model and example

* wanx_merged_v1

* change WanX into Wan

* fix i2v fp32 oom error

Link: https://code.alibaba-inc.com/open_wanx2/diffusers/codereview/20607813



* support t2v load fp32 ckpt

* add example

* final merge v1

* Update autoencoder_kl_wan.py

* up

* update middle, test up_block

* up up

* one less nn.sequential

* up more

* up

* more

* [refactor] [wip] Wan transformer/pipeline (#10926)

* update

* update

* refactor rope

* refactor pipeline

* make fix-copies

* add transformer test

* update

* update

* make style

* update tests

* tests

* conversion script

* conversion script

* update

* docs

* remove unused code

* fix _toctree.yml

* update dtype

* fix test

* fix tests: scale

* up

* more

* Apply suggestions from code review

* Apply suggestions from code review

* style

* Update scripts/convert_wan_to_diffusers.py

* update docs

* fix

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Co-authored-by: Yitong Huang <huangyitong.hyt@alibaba-inc.com>
Co-authored-by: 亚森 <wangjiayu.wjy@alibaba-inc.com>
Co-authored-by: Aryan <aryan@huggingface.co>