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Set LANCZOS as the default interpolation for image resizing

* Fixing missing provider options argument

* Adding if else for provider options

* Apply suggestions from code review
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* Apply style fixes

* Update src/diffusers/pipelines/onnx_utils.py
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* Update src/diffusers/pipelines/onnx_utils.py
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remove unnecessary pipeline moving to cpu in validation
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* enable gguf test cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* make SD35LargeGGUFSingleFileTests::test_pipeline_inference pas
Signed-off-by: root <root@a4bf01945cfe.jf.intel.com>

* make FluxControlLoRAGGUFTests::test_lora_loading pass
Signed-off-by: Yao Matrix <matrix.yao@intel.com>

* polish code
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* Apply style fixes

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* Update train_text_to_image_lora.py

* update_train_text_to_image_lora

* Update train_text_to_image.py

* update

fix import.

* enable test_layerwise_casting_memory cases on XPU
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* fix style
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* enable group_offload cases and quanto cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* use backend APIs
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* fix style
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[tests] add tests to check for graph breaks, recompilation, cuda syncs in pipelines during torch.compile() (#11085)

* test for better torch.compile stuff.

* fixes

* recompilation and graph break.

* clear compilation cache.

* change to modeling level test.

* allow running compilation tests during nightlies.

* Set LANCZOS as default interpolation mode for resizing

* [train_dreambooth_lora.py] Set LANCZOS as default interpolation mode for resizing

update

Fix Flux IP adapter argument in the example

IP-Adapter example had a wrong argument. Fix `true_cfg` -> `true_cfg_scale`

* 1. add pre-computation of prompt embeddings when custom prompts are used as well
2. save model card even if model is not pushed to hub
3. remove scheduler initialization from code example - not necessary anymore (it's now if the base model's config)
4. add skip_final_inference - to allow to run with validation, but skip the final loading of the pipeline with the lora weights to reduce memory reqs

* pre encode validation prompt as well

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* pre encode validation prompt as well

* Apply style fixes

* empty commit

* change default trained modules

* empty commit

* address comments + change encoding of validation prompt (before it was only pre-encoded if custom prompts are provided, but should be pre-encoded either way)

* Apply style fixes

* empty commit

* fix validation_embeddings definition

* fix final inference condition

* fix pipeline deletion in last inference

* Apply style fixes

* empty commit

* layers

* remove readme remarks on only pre-computing when instance prompt is provided and change example to 3d icons

* smol fix

* empty commit

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* Kolors additional pipelines, community contrib

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update

* fix

* add tests

* add message check

Small change
requirements_sana.txt to 
requirements_hidream.txt

up

update

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>

* move prompt embeds, pooled embeds outside

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

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

* fix import

* fix import and tokenizer 4, text encoder 4 loading

* te

* prompt embeds

* fix naming

* shapes

* initial commit to add HiDreamImageLoraLoaderMixin

* fix init

* add tests

* loader

* fix model input

* add code example to readme

* fix default max length of text encoders

* prints

* nullify training cond in unpatchify for temp fix to incompatible shaping of transformer output during training

* smol fix

* unpatchify

* unpatchify

* fix validation

* flip pred and loss

* fix shift!!!

* revert unpatchify changes (for now)

* smol fix

* Apply style fixes

* workaround moe training

* workaround moe training

* remove prints

* to reduce some memory, keep vae in `weight_dtype` same as we have for flux (as it's the same vae)
https://github.com/huggingface/diffusers/blob/bbd0c161b55ba2234304f1e6325832dd69c60565/examples/dreambooth/train_dreambooth_lora_flux.py#L1207



* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* add support for cpu offloading of text encoders

* Apply style fixes

* adjust lr and rank for train example

* fix copies

* Apply style fixes

* update README

* update README

* update README

* fix license

* keep prompt2,3,4 as None in validation

* remove reverse ode comment

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* vae offload change

* fix text encoder offloading

* Apply style fixes

* cleaner to_kwargs

* fix module name in copied from

* add requirements

* fix offloading

* fix offloading

* fix offloading

* update transformers version in reqs

* try AutoTokenizer

* try AutoTokenizer

* Apply style fixes

* empty commit

* Delete tests/lora/test_lora_layers_hidream.py

* change tokenizer_4 to load with AutoTokenizer as well

* make text_encoder_four and tokenizer_four configurable

* save model card

* save model card

* revert T5

* fix test

* remove non diffusers lumina2 conversion

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* Add stochastic sampling to FlowMatchEulerDiscreteScheduler

This PR adds stochastic sampling to FlowMatchEulerDiscreteScheduler based on https://github.com/Lightricks/LTX-Video/commit/b1aeddd7ccac85e6d1b0d97762610ddb53c1b408

  ltx_video/schedulers/rf.py

* Apply style fixes

* Use config value directly

* Apply style fixes

* Swap order

* Update src/diffusers/schedulers/scheduling_flow_match_euler_discrete.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/schedulers/scheduling_flow_match_euler_discrete.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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* update

* update

* addressed PR comments

* update

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

[cogview4][feat] Support attention mechanism with variable-length support and batch packing (#11349)

* [cogview4] Enhance attention mechanism with variable-length support and batch packing

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* Update outputs.py

* bug fix kadinsky pipeline

update

* fix issue that training flux controlnet was unstable and validation results were unstable

* del unused code pieces, fix grammar

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[train_dreambooth_lora_sdxl.py] Fix the LR Schedulers when num_train_epochs is passed in a distributed training env (#11240)
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

* add fix

* add fix

* Apply style fixes

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update scheuler config in conversion sript

up

Fix: `StableDiffusionXLControlNetAdapterInpaintPipeline` incorrectly inherited `StableDiffusionLoraLoaderMixin` (#11357)

Fix: Inherit `StableDiffusionXLLoraLoaderMixin`

`StableDiffusionXLControlNetAdapterInpaintPipeline`
used to incorrectly inherit
`StableDiffusionLoraLoaderMixin`
instead of `StableDiffusionXLLoraLoaderMixin`

* update transformer

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

* enable 2 test cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* Apply style fixes

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