GitLab

* update

* updaet

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* Update docs/source/en/quantization/quanto.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

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

* update

* update

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* more sanity of mind with copied from ...

* better

* better

* Support STG for video pipelines

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update pipeline_stg_cogvideox.py

* Update pipeline_stg_hunyuan_video.py

* Update pipeline_stg_ltx.py

* Update pipeline_stg_ltx_image2video.py

* Update pipeline_stg_mochi.py

* Update pipeline_stg_hunyuan_video.py

* Update pipeline_stg_ltx.py

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* remove rescaling

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* update

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remove full key prefix from peft.

* Fix Graph Breaks When Compiling CogView4

Eliminate this:

```
t]V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles] Recompiling function forward in /home/zeyi/repos/diffusers/src/diffusers/models/transformers/transformer_cogview4.py:374
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     triggered by the following guard failure(s):
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/3: ___check_obj_id(L['self'].rope.freqs_h, 139976127328032)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/2: ___check_obj_id(L['self'].rope.freqs_h, 139976107780960)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/1: ___check_obj_id(L['self'].rope.freqs_h, 140022511848960)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/0: ___check_obj_id(L['self'].rope.freqs_h, 140024081342416)   
```

* Update transformer_cogview4.py

* fix cogview4 rotary pos embed

* Apply style fixes

---------
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* update

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* add tests

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* fix defaults

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* fix wan i2v pipeline bugs

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* add cogvideox ddim inversion script

* implement as a pipeline, and add documentation

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update

* Update pipeline_flux_controlnet.py

* Update pipeline_flux_controlnet_image_to_image.py

* Update pipeline_flux_controlnet_inpainting.py

* Update pipeline_flux_controlnet_inpainting.py

* Update pipeline_flux_controlnet_inpainting.py

Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.5 to 3.1.6.
- [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/3.1.5...3.1.6

)

---
updated-dependencies:
- dependency-name: jinja2
  dependency-type: direct:production
...
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removed synchornized.

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

fix tests

[train_dreambooth_lora.py] Fix the LR Schedulers when `num_train_epochs` is passed in a distributed training env (#10973)

* updated train_dreambooth_lora to fix the LR schedulers for `num_train_epochs` in distributed training env

* fixed formatting

* remove trailing newlines

* fixed style error

use style bot GH action from hfh
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* fix t5 training bug

* Apply style fixes

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fix

* Update pipeline_cogview4.py

* Use GLM instead of T5 in doc

* feat: add Mixture-of-Diffusers ControlNet Tile upscaler Pipeline for SDXL

* make style make quality

* Fix seed initialization to handle args.seed = 0 correctly

* Apply style fixes

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* update

* refactor image-to-video pipeline

* update

* fix copied from

* use FP32LayerNorm

Update quantization_config.py

* [Quantization] support pass MappingType for TorchAoConfig

* Apply style fixes

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* feat: support non-diffusers lumina2 LoRAs.

* revert ipynb changes (but I don't know why this is required ☹

️)

* empty

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

* Update evaluation.md

* Update docs/source/en/conceptual/evaluation.md
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* initial comit

* fix empty cache

* fix one more

* fix style

* update device functions

* update

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* Update src/diffusers/utils/testing_utils.py
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* Update src/diffusers/utils/testing_utils.py
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* Update src/diffusers/utils/testing_utils.py
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* Update tests/pipelines/controlnet/test_controlnet.py
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* Update src/diffusers/utils/testing_utils.py
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* Update src/diffusers/utils/testing_utils.py
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* Update tests/pipelines/controlnet/test_controlnet.py
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* with gc.collect

* update

* make style

* check_torch_dependencies

* add mps empty cache

* add changes

* bug fix

* enable on xpu

* update more cases

* revert

* revert back

* Update test_stable_diffusion_xl.py

* Update tests/pipelines/stable_diffusion/test_stable_diffusion.py
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* Update tests/pipelines/stable_diffusion/test_stable_diffusion.py
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* Update tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
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* Update tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
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* Update tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
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* Apply suggestions from code review
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* add test marker

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* Update ip_adapter.py

* Update ip_adapter.py

* Update ip_adapter.py

* Update ip_adapter.py

* Update ip_adapter.py

* Apply style fixes

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* Add example of Ip-Adapter-Callback.

* Add image links from HF Hub.

* Update pipeline_animatediff.py

* Update pipeline_animatediff_controlnet.py

* Update pipeline_animatediff_sparsectrl.py

* Update pipeline_animatediff_video2video.py

* Update pipeline_animatediff_video2video_controlnet.py

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

* Fix SD2.X clip single file load projection_dim

Infer projection_dim from the checkpoint before loading
from pretrained, override any incorrect hub config.

Hub configuration for SD2.X specifies projection_dim=512
which is incorrect for SD2.X checkpoints loaded from civitai
and similar.

Exception was previously thrown upon attempting to
load_model_dict_into_meta for SD2.X single file checkpoints.

Such LDM models usually require projection_dim=1024

* convert_open_clip_checkpoint use hidden_size for text_proj_dim

* convert_open_clip_checkpoint, revert checkpoint[text_proj_key].shape[1] -> [0]

values are identical

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* Update EasyAnimate V5.1

* Add docs && add tests && Fix comments problems in transformer3d and vae

* delete comments and remove useless import

* delete process

* Update EXAMPLE_DOC_STRING

* rename transformer file

* make fix-copies

* make style

* refactor pt. 1

* update toctree.yml

* add model tests

* Update layer_norm for norm_added_q and norm_added_k in Attention

* Fix processor problem

* refactor vae

* Fix problem in comments

* refactor tiling; remove einops dependency

* fix docs path

* make fix-copies

* Update src/diffusers/pipelines/easyanimate/pipeline_easyanimate_control.py

* update _toctree.yml

* fix test

* update

* update

* update

* make fix-copies

* fix tests

---------
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
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* fix-copies went uncaught it seems.

* remove more unneeded encode_prompt() tests

* Revert "fix-copies went uncaught it seems."

This reverts commit eefb302791172a4fb8ef008e400f94878de2c6c9.

* empty