GitLab

* autoencoder_dc tiling

* add tiling and slicing support in SANA pipelines

* create variables for padding length because the line becomes too long

* add tiling and slicing support in pag SANA pipelines

* revert changes to tile size

* make style

* add vae tiling test

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Co-authored-by: Aryan <aryan@huggingface.co>

Correcting a typo in the table number of a referenced paper (in scheduling_ddim_inverse.py)

Changed the number of the referenced table from 1 to 2 in a comment of the set_timesteps() method of the DDIMInverseScheduler class (also according to the description of the 'timestep_spacing' attribute of its __init__ method).

* Update rerender_a_video.py

* Update rerender_a_video.py

* Update examples/community/rerender_a_video.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update rerender_a_video.py

* make style

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Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* print

* remove print.

* print

* update slice.

* empty

Add a `disable_mmap` option to the `from_single_file` loader to improve load performance on network mounts (#10305)

* Add no_mmap arg.

* Fix arg parsing.

* Update another method to force no mmap.

* logging

* logging2

* propagate no_mmap

* logging3

* propagate no_mmap

* logging4

* fix open call

* clean up logging

* cleanup

* fix missing arg

* update logging and comments

* Rename to disable_mmap and update other references.

* [Docs] Update ltx_video.md to remove generator from `from_pretrained()` (#10316)

Update ltx_video.md to remove generator from `from_pretrained()`

* docs: fix a mistake in docstring (#10319)

Update pipeline_hunyuan_video.py

docs: fix a mistake

* [BUG FIX] [Stable Audio Pipeline] Resolve torch.Tensor.new_zeros() TypeError in function prepare_latents caused by audio_vae_length (#10306)

[BUG FIX] [Stable Audio Pipeline] TypeError: new_zeros(): argument 'size' failed to unpack the object at pos 3 with error "type must be tuple of ints,but got float"

torch.Tensor.new_zeros() takes a single argument size (int...) – a list, tuple, or torch.Size of integers defining the shape of the output tensor.

in function prepare_latents:
audio_vae_length = self.transformer.config.sample_size * self.vae.hop_length
audio_shape = (batch_size // num_waveforms_per_prompt, audio_channels, audio_vae_length)
...
audio = initial_audio_waveforms.new_zeros(audio_shape)

audio_vae_length evaluates to float because self.transformer.config.sample_size returns a float
Co-authored-by: hlky <hlky@hlky.ac>

* [docs] Fix quantization links (#10323)

Update overview.md

* [Sana]add 2K related model for Sana (#10322)

add 2K related model for Sana

* Update src/diffusers/loaders/single_file_model.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/loaders/single_file.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* make style

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Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Leojc <liao_junchao@outlook.com>
Co-authored-by: Aditya Raj <syntaxticsugr@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Junsong Chen <cjs1020440147@icloud.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* allow big lora tests to run on the CI.

* print

* print.

* print

* print

* print

* print

* more

* print

* remove print.

* remove print

* directly place on cuda.

* remove pipeline.

* remove

* fix

* fix

* spaces

* quality

* updates

* directly place flux controlnet pipeline on cuda.

* torch_device instead of cuda.

* style

* device placement.

* fixes

* add big gpu marker for mochi; rename test correctly

* address feedback

* fix

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Co-authored-by: Aryan <aryan@huggingface.co>

* Use Pipelines without unet

* unet.config.in_channels

* default_sample_size

* is_unet_version_less_0_9_0

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add to readme about hf login and wandb installation to address https://github.com/huggingface/diffusers/issues/10142#issuecomment-2571655570

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Support pass kwargs to cogvideox custom attention processor

* remove args in cogvideox attn processor

* remove unused kwargs

* factor out text encoder loading.

* make fix-copies

* remove copied from fuse_lora and unfuse_lora as needed.

* remove unused imports

* Update rerender_a_video.py

* Update rerender_a_video.py

* Update examples/community/rerender_a_video.py
Co-authored-by: hlky <hlky@hlky.ac>

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Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* dont assume scheduler has optional config params

* make style, make fix-copies

* calculate_shift

* fix-copies, usage in pipelines

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Co-authored-by: hlky <hlky@hlky.ac>

* fix docstrings

* add

remove prints from tests.

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add 4K support for Sana

* fix for #7365, prevent pipelines from overriding provided prompt embeds

* fix-copies

* fix implementation

* update

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Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>

Add 5 Notebooks for Diffusers Community
Pipelines.

* Fix tokenizers install from main in LoRA tests

* @

* rust

* -e

* uv

* just update tokenizers

update

* fix device issue in single gpu case

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Update tokenizers

* Add support for loading AuraFlow models from GGUF

https://huggingface.co/city96/AuraFlow-v0.3-gguf



* Update AuraFlow documentation for GGUF, add GGUF tests and model detection.

* Address code review comments.

* Remove unused config.

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Co-authored-by: hlky <hlky@hlky.ac>

change clean_caption from True to False.

* set supports gradient checkpointing to true where necessary; add missing no split modules

* fix cogvideox tests

* update

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

* Use pipelines without vae

* getattr

* vqvae

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

RFInversionFluxPipeline, small fix for enable_model_cpu_offload & enable_sequential_cpu_offload compatibility (#10480)

RFInversionFluxPipeline.encode_image, device fix

Use self._execution_device instead of self.device when selecting
a device for the input image tensor.

This allows for compatibility with enable_model_cpu_offload &
enable_sequential_cpu_offload
Co-authored-by: Teriks <Teriks@users.noreply.github.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.4 to 3.1.5.
- [Release notes](https://github.com/pallets/jinja/releases)
- [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst)
- [Commits](https://github.com/pallets/jinja/compare/3.1.4...3.1.5

)

---
updated-dependencies:
- dependency-name: jinja2
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* update

* update

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

* fix make copies

* update

* add relevant markers to the integration test suite.

* add copied.

* fox-copies

* temporarily add print.

* directly place on CUDA as CPU isn't that big on the CIO.

* fixes to fuse_lora, aryan was right.

* fixes

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make base code changes referred from train_instructpix2pix script in examples

* change code to use PEFT as discussed in issue 10062

* update README training command

* update README training command

* refactor variable name and freezing unet

* Update examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update README installation instructions.

* cleanup code using make style and quality

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* qol improvements to the Flux script.

* propagate the dataloader changes.

fix

Regarding the RunwayML path for V1.5 did change to stable-diffusion-v1-5/[stable-diffusion-v1-5/ stable-diffusion-inpainting] (#10476)

* Update pipeline_controlnet.py

* Update pipeline_controlnet_img2img.py

runwayml Take-down so change all from to this
stable-diffusion-v1-5/stable-diffusion-v1-5

* Update pipeline_controlnet_inpaint.py

* runwayml take-down make change to sd-legacy

* runwayml take-down make change to sd-legacy

* runwayml take-down make change to sd-legacy

* runwayml take-down make change to sd-legacy

* Update convert_blipdiffusion_to_diffusers.py

style change

* Add torch_xla and from_single_file to instruct-pix2pix

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

* StableDiffusionInstructPix2PixPipelineSingleFileSlowTests

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* fix

* add coauthor
Co-Authored-By: Nerogar <nerogar@arcor.de>

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Co-authored-by: Nerogar <nerogar@arcor.de>