GitLab

* add

* fix-copies

* support more SDXL loras.

* update

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adjust diff

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loose expected_max_diff from 5e-1 to 8e-1 to make
KandinskyV22PipelineInpaintCombinedFastTests::test_float16_inference
pass on XPU
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* Forcing update

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* Revert "added proper styling"

This reverts commit 344ee8a7014ada095b295034ef84341f03b0e359.

* manually ordered

* Apply suggestions from code review

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* HiDream Image

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* joint_attention_kwargs -> attention_kwargs, fixes

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‍♂️

* Update src/diffusers/models/transformers/transformer_hidream_image.py
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Co-authored-by: hlky <hlky@hlky.ac>
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Correction typo

* add flow matching lcm scheduler
* stochastic sampling
* upscaling for scale-wise generation

* Apply style fixes

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

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* HiDream Image


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fix to a constant

relax tolerance for unclip further.

* start cleaning up lora test utils for reusability

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Signed-off-by: Matrix Yao <matrix.yao@intel.com>

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* fix test_vanilla_funetuning failure on XPU and A100
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* change back to 5e-2
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* support musubi wan loras.

* Update src/diffusers/loaders/lora_conversion_utils.py
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* support i2v loras from musubi too.

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* fix consisid imports

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* fix

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* style

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Before this if txt_ids was 3d tensor, line with txt_ids[:1] concat txt_ids by batch dim. Now we first check that txt_ids is 2d tensor (or take first batch element) and then concat by token dim

* update

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* loose test_float16_inference's tolerance from 5e-2 to 6e-2, so XPU can
pass UT
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* AutoModel

* ...

* lol

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* fix: SD3 ControlNet validation so that it runs on a A100.

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* no position_embedding

* 🚨

 introduce a breaking change to let peft handle module ambiguity

* styling

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* improvements.

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* Update src/diffusers/loaders/peft.py
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minor updates to dtype map docs.

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* Update src/diffusers/hooks/group_offloading.py
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